id	sid	tid	token	lemma	pos
cana-1705	1	1	communications	communication	NOUN
cana-1705	1	2	on	on	ADP
cana-1705	1	3	applied	apply	VERB
cana-1705	1	4	nonlinear	nonlinear	ADJ
cana-1705	1	5	analysis	analysis	NOUN
cana-1705	1	6	issn	issn	NOUN
cana-1705	1	7	:	:	PUNCT
cana-1705	1	8	1074	1074	NUM
cana-1705	1	9	-	-	PUNCT
cana-1705	1	10	133x	133x	NUM
cana-1705	1	11	vol	vol	NOUN
cana-1705	1	12	32	32	NUM
cana-1705	1	13	no	no	NOUN
cana-1705	1	14	.	.	NOUN
cana-1705	1	15	2	2	NUM
cana-1705	1	16	(	(	PUNCT
cana-1705	1	17	2025	2025	NUM
cana-1705	1	18	)	)	PUNCT
cana-1705	1	19	1	1	NUM
cana-1705	1	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	1	21	implementing	implement	VERB
cana-1705	1	22	real	real	ADJ
cana-1705	1	23	-	-	PUNCT
cana-1705	1	24	time	time	NOUN
cana-1705	1	25	traffic	traffic	NOUN
cana-1705	1	26	flow	flow	NOUN
cana-1705	1	27	prediction	prediction	NOUN
cana-1705	1	28	using	use	VERB
cana-1705	1	29	lstm	lstm	ADJ
cana-1705	1	30	networks	network	NOUN
cana-1705	1	31	for	for	ADP
cana-1705	1	32	urban	urban	ADJ
cana-1705	1	33	mobility	mobility	PROPN
cana-1705	1	34	optimization	optimization	PROPN
cana-1705	1	35	dr	dr	PROPN
cana-1705	1	36	.	.	PROPN
cana-1705	1	37	divya	divya	PROPN
cana-1705	2	1	mahajan1	mahajan1	PROPN
cana-1705	2	2	,	,	PUNCT
cana-1705	2	3	mr	mr	PROPN
cana-1705	2	4	.	.	PROPN
cana-1705	2	5	vinayak	vinayak	PROPN
cana-1705	2	6	v.	v.	PROPN
cana-1705	2	7	pottigar2	pottigar2	PROPN
cana-1705	2	8	,	,	PUNCT
cana-1705	2	9	suresh	suresh	PROPN
cana-1705	2	10	c3	c3	PROPN
cana-1705	2	11	,	,	PUNCT
cana-1705	2	12	adil	adil	PROPN
cana-1705	2	13	fahad4	fahad4	PROPN
cana-1705	3	1	1assistant	1assistant	NUM
cana-1705	3	2	professor	professor	NOUN
cana-1705	3	3	,	,	PUNCT
cana-1705	3	4	department	department	NOUN
cana-1705	3	5	of	of	ADP
cana-1705	3	6	mathematics	mathematic	NOUN
cana-1705	3	7	,	,	PUNCT
cana-1705	3	8	satyawati	satyawati	PROPN
cana-1705	3	9	college	college	PROPN
cana-1705	3	10	,	,	PUNCT
cana-1705	3	11	delhi	delhi	PROPN
cana-1705	3	12	university	university	PROPN
cana-1705	3	13	,	,	PUNCT
cana-1705	3	14	mahajan.divya84@gmail.com	mahajan.divya84@gmail.com	PROPN
cana-1705	3	15	2assistant	2assistant	PROPN
cana-1705	3	16	professor	professor	NOUN
cana-1705	3	17	,	,	PUNCT
cana-1705	3	18	department	department	NOUN
cana-1705	3	19	of	of	ADP
cana-1705	3	20	information	information	NOUN
cana-1705	3	21	technology	technology	NOUN
cana-1705	3	22	,	,	PUNCT
cana-1705	3	23	walchand	walchand	NOUN
cana-1705	3	24	institute	institute	PROPN
cana-1705	3	25	of	of	ADP
cana-1705	3	26	technology	technology	NOUN
cana-1705	3	27	.	.	PUNCT
cana-1705	4	1	vvpottigar@witsolapur.org	vvpottigar@witsolapur.org	PROPN
cana-1705	4	2	3assistant	3assistant	PROPN
cana-1705	4	3	professor	professor	NOUN
cana-1705	4	4	,	,	PUNCT
cana-1705	4	5	department	department	NOUN
cana-1705	4	6	of	of	ADP
cana-1705	4	7	computer	computer	NOUN
cana-1705	4	8	science	science	NOUN
cana-1705	4	9	and	and	CCONJ
cana-1705	4	10	engineering	engineering	NOUN
cana-1705	4	11	,	,	PUNCT
cana-1705	4	12	agni	agni	VERB
cana-1705	4	13	college	college	NOUN
cana-1705	4	14	of	of	ADP
cana-1705	4	15	technology	technology	NOUN
cana-1705	4	16	,	,	PUNCT
cana-1705	4	17	suresh.cse@act.edu.in	suresh.cse@act.edu.in	PROPN
cana-1705	4	18	4faculty	4faculty	NUM
cana-1705	4	19	of	of	ADP
cana-1705	4	20	computing	computing	NOUN
cana-1705	4	21	&	&	CCONJ
cana-1705	4	22	information	information	NOUN
cana-1705	4	23	,	,	PUNCT
cana-1705	4	24	department	department	NOUN
cana-1705	4	25	of	of	ADP
cana-1705	4	26	computer	computer	NOUN
cana-1705	4	27	science	science	NOUN
cana-1705	4	28	,	,	PUNCT
cana-1705	4	29	al	al	PROPN
cana-1705	4	30	baha	baha	PROPN
cana-1705	4	31	university	university	PROPN
cana-1705	4	32	,	,	PUNCT
cana-1705	4	33	al	al	PROPN
cana-1705	4	34	baha	baha	PROPN
cana-1705	4	35	,	,	PUNCT
cana-1705	4	36	saudi	saudi	PROPN
cana-1705	4	37	arabia	arabia	PROPN
cana-1705	4	38	.	.	PUNCT
cana-1705	5	1	corresponding	correspond	VERB
cana-1705	5	2	author	author	NOUN
cana-1705	5	3	mail	mail	NOUN
cana-1705	5	4	:	:	PUNCT
cana-1705	5	5	afalharthi@bu.edu.sa4	afalharthi@bu.edu.sa4	NOUN
cana-1705	5	6	article	article	NOUN
cana-1705	5	7	history	history	NOUN
cana-1705	5	8	:	:	PUNCT
cana-1705	5	9	received	receive	VERB
cana-1705	5	10	:	:	PUNCT
cana-1705	5	11	18	18	NUM
cana-1705	5	12	-	-	SYM
cana-1705	5	13	07	07	NUM
cana-1705	5	14	-	-	PUNCT
cana-1705	5	15	2024	2024	NUM
cana-1705	5	16	revised	revise	VERB
cana-1705	5	17	:	:	PUNCT
cana-1705	5	18	30	30	NUM
cana-1705	5	19	-	-	SYM
cana-1705	5	20	08	08	NUM
cana-1705	5	21	-	-	PUNCT
cana-1705	5	22	2024	2024	NUM
cana-1705	5	23	accepted	accept	VERB
cana-1705	5	24	:	:	PUNCT
cana-1705	5	25	14	14	NUM
cana-1705	5	26	-	-	SYM
cana-1705	5	27	09	09	NUM
cana-1705	5	28	-	-	PUNCT
cana-1705	5	29	2024	2024	NUM
cana-1705	5	30	abstract	abstract	NOUN
cana-1705	5	31	:	:	PUNCT
cana-1705	5	32	the	the	DET
cana-1705	5	33	rapid	rapid	ADJ
cana-1705	5	34	urbanization	urbanization	NOUN
cana-1705	5	35	and	and	CCONJ
cana-1705	5	36	subsequent	subsequent	ADJ
cana-1705	5	37	traffic	traffic	NOUN
cana-1705	5	38	congestion	congestion	NOUN
cana-1705	5	39	are	be	AUX
cana-1705	5	40	challenging	challenge	VERB
cana-1705	5	41	public	public	ADJ
cana-1705	5	42	transportation	transportation	NOUN
cana-1705	5	43	systems	system	NOUN
cana-1705	5	44	that	that	PRON
cana-1705	5	45	are	be	AUX
cana-1705	5	46	responsible	responsible	ADJ
cana-1705	5	47	for	for	ADP
cana-1705	5	48	the	the	DET
cana-1705	5	49	mobility	mobility	NOUN
cana-1705	5	50	of	of	ADP
cana-1705	5	51	populations	population	NOUN
cana-1705	5	52	living	live	VERB
cana-1705	5	53	in	in	ADP
cana-1705	5	54	such	such	ADJ
cana-1705	5	55	cities	city	NOUN
cana-1705	5	56	.	.	PUNCT
cana-1705	6	1	it	it	PRON
cana-1705	6	2	is	be	AUX
cana-1705	6	3	challenging	challenge	VERB
cana-1705	6	4	to	to	PART
cana-1705	6	5	achieve	achieve	VERB
cana-1705	6	6	an	an	DET
cana-1705	6	7	accurate	accurate	ADJ
cana-1705	6	8	and	and	CCONJ
cana-1705	6	9	reliable	reliable	ADJ
cana-1705	6	10	real	real	ADJ
cana-1705	6	11	-	-	PUNCT
cana-1705	6	12	time	time	NOUN
cana-1705	6	13	traffic	traffic	NOUN
cana-1705	6	14	forecasting	forecasting	NOUN
cana-1705	6	15	using	use	VERB
cana-1705	6	16	existing	exist	VERB
cana-1705	6	17	models	model	NOUN
cana-1705	6	18	such	such	ADJ
cana-1705	6	19	as	as	ADP
cana-1705	6	20	statistical	statistical	ADJ
cana-1705	6	21	methods	method	NOUN
cana-1705	6	22	and	and	CCONJ
cana-1705	6	23	traditional	traditional	ADJ
cana-1705	6	24	machine	machine	NOUN
cana-1705	6	25	learning	learning	NOUN
cana-1705	6	26	methods	method	NOUN
cana-1705	6	27	,	,	PUNCT
cana-1705	6	28	because	because	SCONJ
cana-1705	6	29	of	of	ADP
cana-1705	6	30	the	the	DET
cana-1705	6	31	dynamic	dynamic	ADJ
cana-1705	6	32	nature	nature	NOUN
cana-1705	6	33	,	,	PUNCT
cana-1705	6	34	temporal	temporal	ADJ
cana-1705	6	35	dependency	dependency	NOUN
cana-1705	6	36	,	,	PUNCT
cana-1705	6	37	and	and	CCONJ
cana-1705	6	38	spatial	spatial	ADJ
cana-1705	6	39	heterogeneity	heterogeneity	NOUN
cana-1705	6	40	of	of	ADP
cana-1705	6	41	traffic	traffic	NOUN
cana-1705	6	42	flow	flow	NOUN
cana-1705	6	43	.	.	PUNCT
cana-1705	7	1	to	to	PART
cana-1705	7	2	overcome	overcome	VERB
cana-1705	7	3	these	these	DET
cana-1705	7	4	shortcomings	shortcoming	NOUN
cana-1705	7	5	,	,	PUNCT
cana-1705	7	6	this	this	DET
cana-1705	7	7	paper	paper	NOUN
cana-1705	7	8	presents	present	VERB
cana-1705	7	9	a	a	DET
cana-1705	7	10	real	real	ADJ
cana-1705	7	11	-	-	PUNCT
cana-1705	7	12	time	time	NOUN
cana-1705	7	13	traffic	traffic	NOUN
cana-1705	7	14	flow	flow	NOUN
cana-1705	7	15	forecasting	forecasting	NOUN
cana-1705	7	16	model	model	NOUN
cana-1705	7	17	based	base	VERB
cana-1705	7	18	on	on	ADP
cana-1705	7	19	lstm	lstm	PROPN
cana-1705	7	20	.	.	PUNCT
cana-1705	8	1	long	long	ADJ
cana-1705	8	2	short	short	ADJ
cana-1705	8	3	-	-	PUNCT
cana-1705	8	4	term	term	NOUN
cana-1705	8	5	memory	memory	NOUN
cana-1705	8	6	(	(	PUNCT
cana-1705	8	7	lstm	lstm	PROPN
cana-1705	8	8	)	)	PUNCT
cana-1705	8	9	,	,	PUNCT
cana-1705	8	10	a	a	DET
cana-1705	8	11	kind	kind	NOUN
cana-1705	8	12	of	of	ADP
cana-1705	8	13	form	form	NOUN
cana-1705	8	14	rnn	rnn	NOUN
cana-1705	8	15	,	,	PUNCT
cana-1705	8	16	has	have	VERB
cana-1705	8	17	the	the	DET
cana-1705	8	18	great	great	ADJ
cana-1705	8	19	capacity	capacity	NOUN
cana-1705	8	20	to	to	PART
cana-1705	8	21	capture	capture	VERB
cana-1705	8	22	the	the	DET
cana-1705	8	23	time	time	NOUN
cana-1705	8	24	sequence	sequence	NOUN
cana-1705	8	25	and	and	CCONJ
cana-1705	8	26	abrogate	abrogate	VERB
cana-1705	8	27	correlation	correlation	NOUN
cana-1705	8	28	dependency	dependency	NOUN
cana-1705	8	29	,	,	PUNCT
cana-1705	8	30	which	which	PRON
cana-1705	8	31	is	be	AUX
cana-1705	8	32	well	well	ADV
cana-1705	8	33	consistent	consistent	ADJ
cana-1705	8	34	with	with	ADP
cana-1705	8	35	traffic	traffic	NOUN
cana-1705	8	36	flow	flow	NOUN
cana-1705	8	37	-	-	PUNCT
cana-1705	8	38	pattern	pattern	NOUN
cana-1705	8	39	behaviours	behaviour	NOUN
cana-1705	8	40	.	.	PUNCT
cana-1705	9	1	that	that	PRON
cana-1705	9	2	being	be	AUX
cana-1705	9	3	said	say	VERB
cana-1705	9	4	,	,	PUNCT
cana-1705	9	5	the	the	DET
cana-1705	9	6	model	model	NOUN
cana-1705	9	7	predicts	predict	VERB
cana-1705	9	8	the	the	DET
cana-1705	9	9	traffic	traffic	NOUN
cana-1705	9	10	flow	flow	NOUN
cana-1705	9	11	in	in	ADP
cana-1705	9	12	a	a	DET
cana-1705	9	13	short	short	ADJ
cana-1705	9	14	-	-	PUNCT
cana-1705	9	15	term	term	NOUN
cana-1705	9	16	using	use	VERB
cana-1705	9	17	historical	historical	ADJ
cana-1705	9	18	data	datum	NOUN
cana-1705	9	19	of	of	ADP
cana-1705	9	20	volume	volume	NOUN
cana-1705	9	21	,	,	PUNCT
cana-1705	9	22	speed	speed	NOUN
cana-1705	9	23	and	and	CCONJ
cana-1705	9	24	condition	condition	NOUN
cana-1705	9	25	on	on	ADP
cana-1705	9	26	road	road	NOUN
cana-1705	9	27	.	.	PUNCT
cana-1705	10	1	the	the	DET
cana-1705	10	2	study	study	NOUN
cana-1705	10	3	also	also	ADV
cana-1705	10	4	utilizes	utilize	VERB
cana-1705	10	5	various	various	ADJ
cana-1705	10	6	types	type	NOUN
cana-1705	10	7	of	of	ADP
cana-1705	10	8	data	datum	NOUN
cana-1705	10	9	—	—	PUNCT
cana-1705	10	10	including	include	VERB
cana-1705	10	11	gps	gps	PROPN
cana-1705	10	12	data	datum	NOUN
cana-1705	10	13	from	from	ADP
cana-1705	10	14	vehicles	vehicle	NOUN
cana-1705	10	15	,	,	PUNCT
cana-1705	10	16	sensors	sensor	NOUN
cana-1705	10	17	and	and	CCONJ
cana-1705	10	18	traffic	traffic	NOUN
cana-1705	10	19	cameras	camera	NOUN
cana-1705	10	20	—	—	PUNCT
cana-1705	10	21	to	to	PART
cana-1705	10	22	enhance	enhance	VERB
cana-1705	10	23	predictive	predictive	ADJ
cana-1705	10	24	accuracy	accuracy	NOUN
cana-1705	10	25	.	.	PUNCT
cana-1705	11	1	extensive	extensive	ADJ
cana-1705	11	2	experiments	experiment	NOUN
cana-1705	11	3	using	use	VERB
cana-1705	11	4	real	real	ADJ
cana-1705	11	5	-	-	PUNCT
cana-1705	11	6	world	world	NOUN
cana-1705	11	7	traffic	traffic	NOUN
cana-1705	11	8	datasets	dataset	NOUN
cana-1705	11	9	show	show	VERB
cana-1705	11	10	that	that	SCONJ
cana-1705	11	11	the	the	DET
cana-1705	11	12	proposed	propose	VERB
cana-1705	11	13	lstm	lstm	NOUN
cana-1705	11	14	-	-	PUNCT
cana-1705	11	15	based	base	VERB
cana-1705	11	16	model	model	NOUN
cana-1705	11	17	significantly	significantly	ADV
cana-1705	11	18	outperforms	outperform	VERB
cana-1705	11	19	traditional	traditional	ADJ
cana-1705	11	20	machine	machine	NOUN
cana-1705	11	21	learning	learning	NOUN
cana-1705	11	22	models	model	NOUN
cana-1705	11	23	,	,	PUNCT
cana-1705	11	24	such	such	ADJ
cana-1705	11	25	as	as	ADP
cana-1705	11	26	arima	arima	NOUN
cana-1705	11	27	and	and	CCONJ
cana-1705	11	28	support	support	VERB
cana-1705	11	29	vector	vector	NOUN
cana-1705	11	30	machines	machine	NOUN
cana-1705	11	31	(	(	PUNCT
cana-1705	11	32	svms	svms	NOUN
cana-1705	11	33	)	)	PUNCT
cana-1705	11	34	,	,	PUNCT
cana-1705	11	35	in	in	ADP
cana-1705	11	36	terms	term	NOUN
cana-1705	11	37	of	of	ADP
cana-1705	11	38	both	both	DET
cana-1705	11	39	prediction	prediction	NOUN
cana-1705	11	40	accuracy	accuracy	NOUN
cana-1705	11	41	and	and	CCONJ
cana-1705	11	42	response	response	NOUN
cana-1705	11	43	time	time	NOUN
cana-1705	11	44	.	.	PUNCT
cana-1705	12	1	the	the	DET
cana-1705	12	2	results	result	NOUN
cana-1705	12	3	demonstrate	demonstrate	VERB
cana-1705	12	4	that	that	SCONJ
cana-1705	12	5	the	the	DET
cana-1705	12	6	model	model	NOUN
cana-1705	12	7	could	could	AUX
cana-1705	12	8	achieve	achieve	VERB
cana-1705	12	9	an	an	DET
cana-1705	12	10	accuracy	accuracy	NOUN
cana-1705	12	11	of	of	ADP
cana-1705	12	12	more	more	ADJ
cana-1705	12	13	than	than	ADP
cana-1705	12	14	90	90	NUM
cana-1705	12	15	%	%	NOUN
cana-1705	12	16	in	in	ADP
cana-1705	12	17	predicting	predict	VERB
cana-1705	12	18	complaints	complaint	NOUN
cana-1705	12	19	,	,	PUNCT
cana-1705	12	20	suggesting	suggest	VERB
cana-1705	12	21	it	it	PRON
cana-1705	12	22	is	be	AUX
cana-1705	12	23	a	a	DET
cana-1705	12	24	successful	successful	ADJ
cana-1705	12	25	approach	approach	NOUN
cana-1705	12	26	to	to	ADP
cana-1705	12	27	urban	urban	ADJ
cana-1705	12	28	traffic	traffic	NOUN
cana-1705	12	29	management	management	NOUN
cana-1705	12	30	systems	system	NOUN
cana-1705	12	31	which	which	PRON
cana-1705	12	32	can	can	AUX
cana-1705	12	33	lessen	lessen	VERB
cana-1705	12	34	congestion	congestion	NOUN
cana-1705	12	35	and	and	CCONJ
cana-1705	12	36	improve	improve	VERB
cana-1705	12	37	mobility	mobility	NOUN
cana-1705	12	38	.	.	PUNCT
cana-1705	13	1	the	the	DET
cana-1705	13	2	solution	solution	NOUN
cana-1705	13	3	offers	offer	VERB
cana-1705	13	4	up	up	ADP
cana-1705	13	5	-	-	PUNCT
cana-1705	13	6	to	to	ADP
cana-1705	13	7	-	-	PUNCT
cana-1705	13	8	theminute	theminute	NOUN
cana-1705	13	9	traffic	traffic	NOUN
cana-1705	13	10	flow	flow	NOUN
cana-1705	13	11	predictions	prediction	NOUN
cana-1705	13	12	,	,	PUNCT
cana-1705	13	13	enabling	enable	VERB
cana-1705	13	14	real	real	ADJ
cana-1705	13	15	-	-	PUNCT
cana-1705	13	16	time	time	NOUN
cana-1705	13	17	route	route	NOUN
cana-1705	13	18	planning	planning	NOUN
cana-1705	13	19	,	,	PUNCT
cana-1705	13	20	traffic	traffic	NOUN
cana-1705	13	21	signal	signal	NOUN
cana-1705	13	22	optimization	optimization	NOUN
cana-1705	13	23	and	and	CCONJ
cana-1705	13	24	premptive	premptive	ADJ
cana-1705	13	25	congestion	congestion	NOUN
cana-1705	13	26	control	control	NOUN
cana-1705	13	27	.	.	PUNCT
cana-1705	14	1	the	the	DET
cana-1705	14	2	research	research	NOUN
cana-1705	14	3	concludes	conclude	VERB
cana-1705	14	4	that	that	SCONJ
cana-1705	14	5	by	by	ADP
cana-1705	14	6	using	use	VERB
cana-1705	14	7	this	this	DET
cana-1705	14	8	predictive	predictive	ADJ
cana-1705	14	9	type	type	NOUN
cana-1705	14	10	of	of	ADP
cana-1705	14	11	lstm	lstm	NOUN
cana-1705	14	12	networks	network	NOUN
cana-1705	14	13	,	,	PUNCT
cana-1705	14	14	it	it	PRON
cana-1705	14	15	can	can	AUX
cana-1705	14	16	full	full	ADJ
cana-1705	14	17	-	-	PUNCT
cana-1705	14	18	fill	fill	NOUN
cana-1705	14	19	a	a	DET
cana-1705	14	20	great	great	ADJ
cana-1705	14	21	role	role	NOUN
cana-1705	14	22	in	in	ADP
cana-1705	14	23	solving	solve	VERB
cana-1705	14	24	the	the	DET
cana-1705	14	25	urban	urban	ADJ
cana-1705	14	26	mobility	mobility	NOUN
cana-1705	14	27	problem	problem	NOUN
cana-1705	14	28	because	because	SCONJ
cana-1705	14	29	if	if	SCONJ
cana-1705	14	30	we	we	PRON
cana-1705	14	31	could	could	AUX
cana-1705	14	32	have	have	VERB
cana-1705	14	33	more	more	ADV
cana-1705	14	34	accurate	accurate	ADJ
cana-1705	14	35	traffic	traffic	NOUN
cana-1705	14	36	prediction	prediction	NOUN
cana-1705	14	37	based	base	VERB
cana-1705	14	38	on	on	ADP
cana-1705	14	39	historical	historical	ADJ
cana-1705	14	40	data	datum	NOUN
cana-1705	14	41	such	such	ADJ
cana-1705	14	42	as	as	ADP
cana-1705	14	43	training	training	NOUN
cana-1705	14	44	samples	sample	NOUN
cana-1705	14	45	so	so	SCONJ
cana-1705	14	46	it	it	PRON
cana-1705	14	47	might	might	AUX
cana-1705	14	48	turn	turn	VERB
cana-1705	14	49	into	into	ADP
cana-1705	14	50	significant	significant	ADJ
cana-1705	14	51	improvements	improvement	NOUN
cana-1705	14	52	on	on	ADP
cana-1705	14	53	decreasing	decrease	VERB
cana-1705	14	54	travel	travel	NOUN
cana-1705	14	55	delays	delay	NOUN
cana-1705	14	56	and	and	CCONJ
cana-1705	14	57	enhancing	enhance	VERB
cana-1705	14	58	overall	overall	ADJ
cana-1705	14	59	traffic	traffic	NOUN
cana-1705	14	60	efficiency	efficiency	NOUN
cana-1705	14	61	so	so	SCONJ
cana-1705	14	62	that	that	PRON
cana-1705	14	63	's	be	AUX
cana-1705	14	64	hence	hence	ADV
cana-1705	14	65	why	why	SCONJ
cana-1705	14	66	it	it	PRON
cana-1705	14	67	is	be	AUX
cana-1705	14	68	a	a	DET
cana-1705	14	69	scalable	scalable	ADJ
cana-1705	14	70	component	component	NOUN
cana-1705	14	71	for	for	ADP
cana-1705	14	72	city	city	NOUN
cana-1705	14	73	projects	project	NOUN
cana-1705	14	74	.	.	PUNCT
cana-1705	15	1	keywords	keyword	NOUN
cana-1705	15	2	:	:	PUNCT
cana-1705	15	3	traffic	traffic	NOUN
cana-1705	15	4	,	,	PUNCT
cana-1705	15	5	congestion	congestion	NOUN
cana-1705	15	6	,	,	PUNCT
cana-1705	15	7	short	short	ADJ
cana-1705	15	8	-	-	PUNCT
cana-1705	15	9	term	term	NOUN
cana-1705	15	10	,	,	PUNCT
cana-1705	15	11	signal	signal	NOUN
cana-1705	15	12	,	,	PUNCT
cana-1705	15	13	optimization	optimization	NOUN
cana-1705	15	14	,	,	PUNCT
cana-1705	15	15	predicting	predicting	NOUN
cana-1705	15	16	,	,	PUNCT
cana-1705	15	17	mobility	mobility	NOUN
cana-1705	15	18	,	,	PUNCT
cana-1705	15	19	models	model	NOUN
cana-1705	15	20	,	,	PUNCT
cana-1705	15	21	response	response	NOUN
cana-1705	15	22	,	,	PUNCT
cana-1705	15	23	samples	sample	NOUN
cana-1705	15	24	,	,	PUNCT
cana-1705	15	25	efficiency	efficiency	NOUN
cana-1705	15	26	.	.	PUNCT
cana-1705	16	1	1	1	X
cana-1705	16	2	.	.	X
cana-1705	16	3	introduction	introduction	NOUN
cana-1705	16	4	cities	city	NOUN
cana-1705	16	5	around	around	ADP
cana-1705	16	6	the	the	DET
cana-1705	16	7	world	world	NOUN
cana-1705	16	8	have	have	AUX
cana-1705	16	9	been	be	AUX
cana-1705	16	10	on	on	ADP
cana-1705	16	11	a	a	DET
cana-1705	16	12	trajectory	trajectory	NOUN
cana-1705	16	13	in	in	ADP
cana-1705	16	14	the	the	DET
cana-1705	16	15	last	last	ADJ
cana-1705	16	16	couple	couple	NOUN
cana-1705	16	17	of	of	ADP
cana-1705	16	18	decades	decade	NOUN
cana-1705	16	19	,	,	PUNCT
cana-1705	16	20	growing	grow	VERB
cana-1705	16	21	from	from	ADP
cana-1705	16	22	simple	simple	ADJ
cana-1705	16	23	communities	community	NOUN
cana-1705	16	24	to	to	ADP
cana-1705	16	25	sprawling	sprawl	VERB
cana-1705	16	26	urban	urban	ADJ
cana-1705	16	27	areas	area	NOUN
cana-1705	16	28	with	with	ADP
cana-1705	16	29	increased	increase	VERB
cana-1705	16	30	economic	economic	ADJ
cana-1705	16	31	activity	activity	NOUN
cana-1705	16	32	,	,	PUNCT
cana-1705	16	33	population	population	NOUN
cana-1705	16	34	density	density	NOUN
cana-1705	16	35	and	and	CCONJ
cana-1705	16	36	demands	demand	NOUN
cana-1705	16	37	for	for	ADP
cana-1705	16	38	mobility	mobility	NOUN
cana-1705	16	39	.	.	PUNCT
cana-1705	17	1	while	while	SCONJ
cana-1705	17	2	the	the	DET
cana-1705	17	3	united	united	PROPN
cana-1705	17	4	nations	nations	PROPN
cana-1705	17	5	expects	expect	VERB
cana-1705	17	6	that	that	SCONJ
cana-1705	17	7	68	68	NUM
cana-1705	17	8	%	%	NOUN
cana-1705	17	9	of	of	ADP
cana-1705	17	10	the	the	DET
cana-1705	17	11	global	global	ADJ
cana-1705	17	12	population	population	NOUN
cana-1705	17	13	will	will	AUX
cana-1705	17	14	mailto:mahajan.divya84@gmail.com	mailto:mahajan.divya84@gmail.com	VERB
cana-1705	17	15	mailto:vvpottigar@witsolapur.org	mailto:vvpottigar@witsolapur.org	PROPN
cana-1705	17	16	mailto:suresh.cse@act.edu.in	mailto:suresh.cse@act.edu.in	NOUN
cana-1705	17	17	mailto:afalharthi@bu.edu.sa	mailto:afalharthi@bu.edu.sa	NOUN
cana-1705	17	18	communications	communication	NOUN
cana-1705	17	19	on	on	ADP
cana-1705	17	20	applied	apply	VERB
cana-1705	17	21	nonlinear	nonlinear	ADJ
cana-1705	17	22	analysis	analysis	NOUN
cana-1705	17	23	issn	issn	NOUN
cana-1705	17	24	:	:	PUNCT
cana-1705	17	25	1074	1074	NUM
cana-1705	17	26	-	-	PUNCT
cana-1705	17	27	133x	133x	NUM
cana-1705	17	28	vol	vol	NOUN
cana-1705	17	29	32	32	NUM
cana-1705	17	30	no	no	NOUN
cana-1705	17	31	.	.	NOUN
cana-1705	17	32	2	2	NUM
cana-1705	17	33	(	(	PUNCT
cana-1705	17	34	2025	2025	NUM
cana-1705	17	35	)	)	PUNCT
cana-1705	17	36	2	2	NUM
cana-1705	17	37	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	17	38	reside	reside	VERB
cana-1705	17	39	in	in	ADP
cana-1705	17	40	urban	urban	ADJ
cana-1705	17	41	areas	area	NOUN
cana-1705	17	42	by	by	ADP
cana-1705	17	43	2050	2050	NUM
cana-1705	17	44	,	,	PUNCT
cana-1705	17	45	it	it	PRON
cana-1705	17	46	is	be	AUX
cana-1705	17	47	a	a	DET
cana-1705	17	48	challenge	challenge	NOUN
cana-1705	17	49	which	which	PRON
cana-1705	17	50	presents	present	VERB
cana-1705	17	51	growing	grow	VERB
cana-1705	17	52	congestion	congestion	NOUN
cana-1705	17	53	at	at	ADP
cana-1705	17	54	large	large	ADJ
cana-1705	17	55	.	.	PUNCT
cana-1705	18	1	blog	blog	NOUN
cana-1705	18	2	traffic	traffic	NOUN
cana-1705	18	3	congestion	congestion	NOUN
cana-1705	18	4	not	not	PART
cana-1705	18	5	only	only	ADV
cana-1705	18	6	hurts	hurt	VERB
cana-1705	18	7	the	the	DET
cana-1705	18	8	individual	individual	ADJ
cana-1705	18	9	commuters	commuter	NOUN
cana-1705	18	10	going	go	VERB
cana-1705	18	11	to	to	PART
cana-1705	18	12	work	work	VERB
cana-1705	18	13	but	but	CCONJ
cana-1705	18	14	it	it	PRON
cana-1705	18	15	's	be	AUX
cana-1705	18	16	also	also	ADV
cana-1705	18	17	cheating	cheat	VERB
cana-1705	18	18	anyone	anyone	PRON
cana-1705	18	19	that	that	PRON
cana-1705	18	20	drives	drive	VERB
cana-1705	18	21	in	in	ADP
cana-1705	18	22	general	general	ADJ
cana-1705	18	23	,	,	PUNCT
cana-1705	18	24	it	it	PRON
cana-1705	18	25	's	be	AUX
cana-1705	18	26	bad	bad	ADJ
cana-1705	18	27	for	for	ADP
cana-1705	18	28	the	the	DET
cana-1705	18	29	environment	environment	NOUN
cana-1705	18	30	from	from	ADP
cana-1705	18	31	all	all	DET
cana-1705	18	32	the	the	DET
cana-1705	18	33	carbon	carbon	NOUN
cana-1705	18	34	dioxide	dioxide	NOUN
cana-1705	18	35	emissions	emission	NOUN
cana-1705	18	36	coming	come	VERB
cana-1705	18	37	out	out	ADP
cana-1705	18	38	of	of	ADP
cana-1705	18	39	people	people	NOUN
cana-1705	18	40	tailpipes	tailpipe	NOUN
cana-1705	18	41	,	,	PUNCT
cana-1705	18	42	causing	cause	VERB
cana-1705	18	43	your	your	PRON
cana-1705	18	44	city	city	NOUN
cana-1705	18	45	council	council	NOUN
cana-1705	18	46	to	to	PART
cana-1705	18	47	spend	spend	VERB
cana-1705	18	48	way	way	NOUN
cana-1705	18	49	more	more	ADJ
cana-1705	18	50	money	money	NOUN
cana-1705	18	51	than	than	SCONJ
cana-1705	18	52	they	they	PRON
cana-1705	18	53	should	should	AUX
cana-1705	18	54	literally	literally	ADV
cana-1705	18	55	filling	fill	VERB
cana-1705	18	56	pot	pot	NOUN
cana-1705	18	57	holes	hole	NOUN
cana-1705	18	58	,	,	PUNCT
cana-1705	18	59	and	and	CCONJ
cana-1705	18	60	costing	cost	VERB
cana-1705	18	61	you	you	PRON
cana-1705	18	62	and	and	CCONJ
cana-1705	18	63	our	our	PRON
cana-1705	18	64	country	country	NOUN
cana-1705	18	65	about	about	ADV
cana-1705	18	66	50	50	NUM
cana-1705	18	67	billion	billion	NUM
cana-1705	18	68	dollars	dollar	NOUN
cana-1705	18	69	a	a	DET
cana-1705	18	70	year	year	NOUN
cana-1705	18	71	.	.	PUNCT
cana-1705	19	1	the	the	DET
cana-1705	19	2	increasing	increase	VERB
cana-1705	19	3	mobility	mobility	NOUN
cana-1705	19	4	requirements	requirement	NOUN
cana-1705	19	5	of	of	ADP
cana-1705	19	6	urban	urban	ADJ
cana-1705	19	7	populations	population	NOUN
cana-1705	19	8	and	and	CCONJ
cana-1705	19	9	the	the	DET
cana-1705	19	10	sustainable	sustainable	ADJ
cana-1705	19	11	development	development	NOUN
cana-1705	19	12	aspects	aspect	NOUN
cana-1705	19	13	of	of	ADP
cana-1705	19	14	cities	city	NOUN
cana-1705	19	15	around	around	ADP
cana-1705	19	16	the	the	DET
cana-1705	19	17	world	world	NOUN
cana-1705	19	18	challenge	challenge	VERB
cana-1705	19	19	the	the	DET
cana-1705	19	20	provision	provision	NOUN
cana-1705	19	21	of	of	ADP
cana-1705	19	22	more	more	ADV
cana-1705	19	23	intelligent	intelligent	ADJ
cana-1705	19	24	,	,	PUNCT
cana-1705	19	25	real	real	ADJ
cana-1705	19	26	-	-	PUNCT
cana-1705	19	27	time	time	NOUN
cana-1705	19	28	traffic	traffic	NOUN
cana-1705	19	29	management	management	NOUN
cana-1705	19	30	systems	system	NOUN
cana-1705	19	31	.	.	PUNCT
cana-1705	20	1	over	over	ADP
cana-1705	20	2	time	time	NOUN
cana-1705	20	3	,	,	PUNCT
cana-1705	20	4	these	these	DET
cana-1705	20	5	traditional	traditional	ADJ
cana-1705	20	6	traffic	traffic	NOUN
cana-1705	20	7	control	control	NOUN
cana-1705	20	8	methods	method	NOUN
cana-1705	20	9	that	that	PRON
cana-1705	20	10	include	include	VERB
cana-1705	20	11	building	build	VERB
cana-1705	20	12	flyovers	flyover	NOUN
cana-1705	20	13	,	,	PUNCT
cana-1705	20	14	high	high	ADJ
cana-1705	20	15	occupancy	occupancy	NOUN
cana-1705	20	16	vehicle	vehicle	NOUN
cana-1705	20	17	lanes	lane	NOUN
cana-1705	20	18	and	and	CCONJ
cana-1705	20	19	widening	widen	VERB
cana-1705	20	20	road	road	NOUN
cana-1705	20	21	networks	network	NOUN
cana-1705	20	22	have	have	AUX
cana-1705	20	23	shown	show	VERB
cana-1705	20	24	to	to	PART
cana-1705	20	25	be	be	AUX
cana-1705	20	26	pretty	pretty	ADV
cana-1705	20	27	inefficient	inefficient	ADJ
cana-1705	20	28	.	.	PUNCT
cana-1705	21	1	there	there	PRON
cana-1705	21	2	are	be	VERB
cana-1705	21	3	a	a	DET
cana-1705	21	4	myriad	myriad	NOUN
cana-1705	21	5	of	of	ADP
cana-1705	21	6	factors	factor	NOUN
cana-1705	21	7	that	that	PRON
cana-1705	21	8	make	make	VERB
cana-1705	21	9	up	up	ADP
cana-1705	21	10	complex	complex	ADJ
cana-1705	21	11	,	,	PUNCT
cana-1705	21	12	dynamic	dynamic	ADJ
cana-1705	21	13	urban	urban	ADJ
cana-1705	21	14	transportation	transportation	NOUN
cana-1705	21	15	systems	system	NOUN
cana-1705	21	16	such	such	ADJ
cana-1705	21	17	as	as	ADP
cana-1705	21	18	road	road	NOUN
cana-1705	21	19	infrastructure	infrastructure	NOUN
cana-1705	21	20	,	,	PUNCT
cana-1705	21	21	population	population	NOUN
cana-1705	21	22	density	density	NOUN
cana-1705	21	23	and	and	CCONJ
cana-1705	21	24	weather	weather	NOUN
cana-1705	21	25	conditions	condition	NOUN
cana-1705	21	26	,	,	PUNCT
cana-1705	21	27	in	in	ADP
cana-1705	21	28	addition	addition	NOUN
cana-1705	21	29	to	to	ADP
cana-1705	21	30	human	human	ADJ
cana-1705	21	31	behaviour	behaviour	NOUN
cana-1705	21	32	like	like	ADP
cana-1705	21	33	sudden	sudden	ADJ
cana-1705	21	34	braking	braking	NOUN
cana-1705	21	35	or	or	CCONJ
cana-1705	21	36	frequent	frequent	ADJ
cana-1705	21	37	lane	lane	NOUN
cana-1705	21	38	changes	change	NOUN
cana-1705	21	39	.	.	PUNCT
cana-1705	22	1	discrepancies	discrepancy	NOUN
cana-1705	22	2	like	like	ADP
cana-1705	22	3	these	these	PRON
cana-1705	22	4	are	be	AUX
cana-1705	22	5	acting	act	VERB
cana-1705	22	6	as	as	ADP
cana-1705	22	7	elements	element	NOUN
cana-1705	22	8	that	that	PRON
cana-1705	22	9	make	make	VERB
cana-1705	22	10	the	the	DET
cana-1705	22	11	task	task	NOUN
cana-1705	22	12	of	of	ADP
cana-1705	22	13	predicting	predict	VERB
cana-1705	22	14	traffic	traffic	NOUN
cana-1705	22	15	flow	flow	NOUN
cana-1705	22	16	ever	ever	ADV
cana-1705	22	17	more	more	ADV
cana-1705	22	18	difficult	difficult	ADJ
cana-1705	22	19	and	and	CCONJ
cana-1705	22	20	thereby	thereby	ADV
cana-1705	22	21	jeopardize	jeopardize	VERB
cana-1705	22	22	the	the	DET
cana-1705	22	23	ability	ability	NOUN
cana-1705	22	24	to	to	PART
cana-1705	22	25	detect	detect	VERB
cana-1705	22	26	,	,	PUNCT
cana-1705	22	27	much	much	ADV
cana-1705	22	28	less	less	ADV
cana-1705	22	29	counteract	counteract	VERB
cana-1705	22	30	congestion	congestion	NOUN
cana-1705	22	31	in	in	ADP
cana-1705	22	32	real	real	ADJ
cana-1705	22	33	-	-	PUNCT
cana-1705	22	34	time	time	NOUN
cana-1705	22	35	.	.	PUNCT
cana-1705	23	1	this	this	PRON
cana-1705	23	2	is	be	AUX
cana-1705	23	3	leading	lead	VERB
cana-1705	23	4	to	to	ADP
cana-1705	23	5	the	the	DET
cana-1705	23	6	emergence	emergence	NOUN
cana-1705	23	7	of	of	ADP
cana-1705	23	8	intelligent	intelligent	ADJ
cana-1705	23	9	traffic	traffic	NOUN
cana-1705	23	10	management	management	NOUN
cana-1705	23	11	systems	system	NOUN
cana-1705	23	12	that	that	PRON
cana-1705	23	13	can	can	AUX
cana-1705	23	14	analyse	analyse	VERB
cana-1705	23	15	and	and	CCONJ
cana-1705	23	16	predict	predict	VERB
cana-1705	23	17	events	event	NOUN
cana-1705	23	18	in	in	ADP
cana-1705	23	19	real	real	NOUN
cana-1705	23	20	-	-	PUNCT
cana-1705	23	21	time[1	time[1	NOUN
cana-1705	23	22	]	]	PUNCT
cana-1705	23	23	.	.	PUNCT
cana-1705	24	1	forecasting	forecast	VERB
cana-1705	24	2	traffic	traffic	NOUN
cana-1705	24	3	conditions	condition	NOUN
cana-1705	24	4	in	in	ADP
cana-1705	24	5	cities	city	NOUN
cana-1705	24	6	is	be	AUX
cana-1705	24	7	a	a	DET
cana-1705	24	8	key	key	ADJ
cana-1705	24	9	part	part	NOUN
cana-1705	24	10	of	of	ADP
cana-1705	24	11	controlling	control	VERB
cana-1705	24	12	the	the	DET
cana-1705	24	13	movement	movement	NOUN
cana-1705	24	14	of	of	ADP
cana-1705	24	15	people	people	NOUN
cana-1705	24	16	and	and	CCONJ
cana-1705	24	17	minimising	minimise	VERB
cana-1705	24	18	congestion	congestion	NOUN
cana-1705	24	19	.	.	PUNCT
cana-1705	25	1	precise	precise	ADJ
cana-1705	25	2	long	long	ADJ
cana-1705	25	3	-	-	PUNCT
cana-1705	25	4	term	term	NOUN
cana-1705	25	5	and	and	CCONJ
cana-1705	25	6	short	short	ADJ
cana-1705	25	7	-	-	PUNCT
cana-1705	25	8	term	term	NOUN
cana-1705	25	9	traffic	traffic	NOUN
cana-1705	25	10	flow	flow	NOUN
cana-1705	25	11	predictions	prediction	NOUN
cana-1705	25	12	would	would	AUX
cana-1705	25	13	allow	allow	VERB
cana-1705	25	14	transportation	transportation	NOUN
cana-1705	25	15	authorities	authority	NOUN
cana-1705	25	16	to	to	PART
cana-1705	25	17	anticipate	anticipate	VERB
cana-1705	25	18	problems	problem	NOUN
cana-1705	25	19	,	,	PUNCT
cana-1705	25	20	with	with	ADP
cana-1705	25	21	measures	measure	NOUN
cana-1705	25	22	like	like	ADP
cana-1705	25	23	optimizing	optimize	VERB
cana-1705	25	24	traffic	traffic	NOUN
cana-1705	25	25	signal	signal	NOUN
cana-1705	25	26	timings	timing	NOUN
cana-1705	25	27	,	,	PUNCT
cana-1705	25	28	routing	route	VERB
cana-1705	25	29	traffic	traffic	NOUN
cana-1705	25	30	elsewhere	elsewhere	ADV
cana-1705	25	31	or	or	CCONJ
cana-1705	25	32	providing	provide	VERB
cana-1705	25	33	the	the	DET
cana-1705	25	34	information	information	NOUN
cana-1705	25	35	in	in	ADP
cana-1705	25	36	real	real	ADJ
cana-1705	25	37	-	-	PUNCT
cana-1705	25	38	time	time	NOUN
cana-1705	25	39	to	to	ADP
cana-1705	25	40	commuters	commuter	NOUN
cana-1705	25	41	.	.	PUNCT
cana-1705	26	1	nevertheless	nevertheless	ADV
cana-1705	26	2	,	,	PUNCT
cana-1705	26	3	conventional	conventional	ADJ
cana-1705	26	4	traffic	traffic	NOUN
cana-1705	26	5	flow	flow	NOUN
cana-1705	26	6	prediction	prediction	NOUN
cana-1705	26	7	models	model	NOUN
cana-1705	26	8	have	have	AUX
cana-1705	26	9	been	be	AUX
cana-1705	26	10	inadequate	inadequate	ADJ
cana-1705	26	11	to	to	PART
cana-1705	26	12	solve	solve	VERB
cana-1705	26	13	the	the	DET
cana-1705	26	14	complexities	complexity	NOUN
cana-1705	26	15	of	of	ADP
cana-1705	26	16	urban	urban	ADJ
cana-1705	26	17	traffic	traffic	NOUN
cana-1705	26	18	that	that	PRON
cana-1705	26	19	are	be	AUX
cana-1705	26	20	continually	continually	ADV
cana-1705	26	21	subjected	subject	VERB
cana-1705	26	22	to	to	ADP
cana-1705	26	23	randomness[7	randomness[7	NOUN
cana-1705	26	24	]	]	PUNCT
cana-1705	26	25	.	.	PUNCT
cana-1705	27	1	figure	figure	NOUN
cana-1705	27	2	1	1	NUM
cana-1705	27	3	.	.	PUNCT
cana-1705	27	4	general	general	ADJ
cana-1705	27	5	architecture	architecture	NOUN
cana-1705	27	6	of	of	ADP
cana-1705	27	7	lstm	lstm	PROPN
cana-1705	27	8	network[5	network[5	PROPN
cana-1705	27	9	]	]	X
cana-1705	27	10	traditional	traditional	ADJ
cana-1705	27	11	prediction	prediction	NOUN
cana-1705	27	12	methods	method	NOUN
cana-1705	27	13	like	like	ADP
cana-1705	27	14	historical	historical	ADJ
cana-1705	27	15	average	average	ADJ
cana-1705	27	16	model	model	NOUN
cana-1705	27	17	,	,	PUNCT
cana-1705	27	18	autoregressive	autoregressive	ADJ
cana-1705	27	19	integrated	integrated	ADJ
cana-1705	27	20	moving	move	VERB
cana-1705	27	21	average	average	NOUN
cana-1705	27	22	(	(	PUNCT
cana-1705	27	23	arima	arima	PROPN
cana-1705	27	24	)	)	PUNCT
cana-1705	27	25	,	,	PUNCT
cana-1705	27	26	or	or	CCONJ
cana-1705	27	27	support	support	VERB
cana-1705	27	28	vector	vector	NOUN
cana-1705	27	29	machines	machine	NOUN
cana-1705	27	30	(	(	PUNCT
cana-1705	27	31	svm	svm	ADJ
cana-1705	27	32	)	)	PUNCT
cana-1705	27	33	make	make	VERB
cana-1705	27	34	assumptions	assumption	NOUN
cana-1705	27	35	that	that	PRON
cana-1705	27	36	are	be	AUX
cana-1705	27	37	too	too	ADV
cana-1705	27	38	simplistic	simplistic	ADJ
cana-1705	27	39	to	to	PART
cana-1705	27	40	depict	depict	VERB
cana-1705	27	41	the	the	DET
cana-1705	27	42	underlying	underlie	VERB
cana-1705	27	43	traffic	traffic	NOUN
cana-1705	27	44	patterns	pattern	NOUN
cana-1705	27	45	in	in	ADP
cana-1705	27	46	a	a	DET
cana-1705	27	47	systematic	systematic	ADJ
cana-1705	27	48	manner	manner	NOUN
cana-1705	27	49	,	,	PUNCT
cana-1705	27	50	while	while	SCONJ
cana-1705	27	51	others	other	NOUN
cana-1705	27	52	overlook	overlook	VERB
cana-1705	27	53	the	the	DET
cana-1705	27	54	temporal	temporal	ADJ
cana-1705	27	55	dependencies	dependency	NOUN
cana-1705	27	56	and	and	CCONJ
cana-1705	27	57	correlations	correlation	NOUN
cana-1705	27	58	among	among	ADP
cana-1705	27	59	data	datum	NOUN
cana-1705	27	60	.	.	PUNCT
cana-1705	28	1	the	the	DET
cana-1705	28	2	problem	problem	NOUN
cana-1705	28	3	is	be	AUX
cana-1705	28	4	that	that	SCONJ
cana-1705	28	5	these	these	DET
cana-1705	28	6	models	model	NOUN
cana-1705	28	7	have	have	VERB
cana-1705	28	8	trouble	trouble	NOUN
cana-1705	28	9	adjusting	adjust	VERB
cana-1705	28	10	to	to	ADP
cana-1705	28	11	the	the	DET
cana-1705	28	12	traffic	traffic	NOUN
cana-1705	28	13	spikes	spike	VERB
cana-1705	28	14	the	the	PRON
cana-1705	28	15	occur	occur	VERB
cana-1705	28	16	from	from	ADP
cana-1705	28	17	something	something	PRON
cana-1705	28	18	as	as	ADV
cana-1705	28	19	simple	simple	ADJ
cana-1705	28	20	as	as	ADP
cana-1705	28	21	an	an	DET
cana-1705	28	22	accident	accident	NOUN
cana-1705	28	23	,	,	PUNCT
cana-1705	28	24	road	road	NOUN
cana-1705	28	25	construction	construction	NOUN
cana-1705	28	26	,	,	PUNCT
cana-1705	28	27	or	or	CCONJ
cana-1705	28	28	change	change	VERB
cana-1705	28	29	communications	communication	NOUN
cana-1705	28	30	on	on	ADP
cana-1705	28	31	applied	apply	VERB
cana-1705	28	32	nonlinear	nonlinear	ADJ
cana-1705	28	33	analysis	analysis	NOUN
cana-1705	28	34	issn	issn	NOUN
cana-1705	28	35	:	:	PUNCT
cana-1705	28	36	1074	1074	NUM
cana-1705	28	37	-	-	PUNCT
cana-1705	28	38	133x	133x	NUM
cana-1705	28	39	vol	vol	NOUN
cana-1705	28	40	32	32	NUM
cana-1705	28	41	no	no	NOUN
cana-1705	28	42	.	.	NOUN
cana-1705	28	43	2	2	NUM
cana-1705	28	44	(	(	PUNCT
cana-1705	28	45	2025	2025	NUM
cana-1705	28	46	)	)	PUNCT
cana-1705	28	47	3	3	NUM
cana-1705	28	48	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	28	49	in	in	ADP
cana-1705	28	50	weather	weather	NOUN
cana-1705	28	51	.	.	PUNCT
cana-1705	29	1	even	even	ADV
cana-1705	29	2	more	more	ADV
cana-1705	29	3	prominently	prominently	ADV
cana-1705	29	4	,	,	PUNCT
cana-1705	29	5	many	many	ADJ
cana-1705	29	6	of	of	ADP
cana-1705	29	7	these	these	DET
cana-1705	29	8	models	model	NOUN
cana-1705	29	9	as	as	ADP
cana-1705	29	10	currently	currently	ADV
cana-1705	29	11	conceived	conceive	VERB
cana-1705	29	12	are	be	AUX
cana-1705	29	13	incapable	incapable	ADJ
cana-1705	29	14	of	of	ADP
cana-1705	29	15	being	be	AUX
cana-1705	29	16	used	use	VERB
cana-1705	29	17	in	in	ADP
cana-1705	29	18	real	real	ADJ
cana-1705	29	19	-	-	PUNCT
cana-1705	29	20	time	time	NOUN
cana-1705	29	21	applications	application	NOUN
cana-1705	29	22	because	because	SCONJ
cana-1705	29	23	they	they	PRON
cana-1705	29	24	either	either	CCONJ
cana-1705	29	25	scale	scale	VERB
cana-1705	29	26	poorly	poorly	ADV
cana-1705	29	27	or	or	CCONJ
cana-1705	29	28	involve	involve	VERB
cana-1705	29	29	data	datum	NOUN
cana-1705	29	30	processing	processing	NOUN
cana-1705	29	31	techniques	technique	NOUN
cana-1705	29	32	ill	ill	ADV
cana-1705	29	33	-	-	PUNCT
cana-1705	29	34	suited	suited	ADJ
cana-1705	29	35	for	for	ADP
cana-1705	29	36	the	the	DET
cana-1705	29	37	demands	demand	NOUN
cana-1705	29	38	of	of	ADP
cana-1705	29	39	a	a	DET
cana-1705	29	40	large	large	ADJ
cana-1705	29	41	,	,	PUNCT
cana-1705	29	42	dynamic	dynamic	ADJ
cana-1705	29	43	urban	urban	ADJ
cana-1705	29	44	context	context	NOUN
cana-1705	29	45	.	.	PUNCT
cana-1705	30	1	these	these	DET
cana-1705	30	2	models	model	NOUN
cana-1705	30	3	,	,	PUNCT
cana-1705	30	4	nevertheless	nevertheless	ADV
cana-1705	30	5	,	,	PUNCT
cana-1705	30	6	have	have	VERB
cana-1705	30	7	limitations	limitation	NOUN
cana-1705	30	8	;	;	PUNCT
cana-1705	30	9	there	there	PRON
cana-1705	30	10	is	be	VERB
cana-1705	30	11	an	an	DET
cana-1705	30	12	increasing	increase	VERB
cana-1705	30	13	demand	demand	NOUN
cana-1705	30	14	nowadays	nowadays	ADV
cana-1705	30	15	for	for	ADP
cana-1705	30	16	more	more	ADV
cana-1705	30	17	sophisticated	sophisticated	ADJ
cana-1705	30	18	prediction	prediction	NOUN
cana-1705	30	19	models	model	NOUN
cana-1705	30	20	capable	capable	ADJ
cana-1705	30	21	of	of	ADP
cana-1705	30	22	considering	consider	VERB
cana-1705	30	23	the	the	DET
cana-1705	30	24	temporal	temporal	ADJ
cana-1705	30	25	dynamics	dynamic	NOUN
cana-1705	30	26	of	of	ADP
cana-1705	30	27	traffic	traffic	NOUN
cana-1705	30	28	flow	flow	NOUN
cana-1705	30	29	,	,	PUNCT
cana-1705	30	30	accommodating	accommodate	VERB
cana-1705	30	31	real	real	ADJ
cana-1705	30	32	-	-	PUNCT
cana-1705	30	33	time	time	NOUN
cana-1705	30	34	conditions	condition	NOUN
cana-1705	30	35	as	as	ADV
cana-1705	30	36	well	well	ADV
cana-1705	30	37	as	as	ADP
cana-1705	30	38	benefiting	benefit	VERB
cana-1705	30	39	from	from	ADP
cana-1705	30	40	a	a	DET
cana-1705	30	41	large	large	ADJ
cana-1705	30	42	amount	amount	NOUN
cana-1705	30	43	of	of	ADP
cana-1705	30	44	traffic	traffic	NOUN
cana-1705	30	45	data	datum	NOUN
cana-1705	30	46	generated	generate	VERB
cana-1705	30	47	from	from	ADP
cana-1705	30	48	different	different	ADJ
cana-1705	30	49	sources	source	NOUN
cana-1705	30	50	such	such	ADJ
cana-1705	30	51	as	as	ADP
cana-1705	30	52	gps	gps	PROPN
cana-1705	30	53	,	,	PUNCT
cana-1705	30	54	sensors	sensor	NOUN
cana-1705	30	55	and	and	CCONJ
cana-1705	30	56	social	social	ADJ
cana-1705	30	57	media	medium	NOUN
cana-1705	30	58	.	.	PUNCT
cana-1705	31	1	deep	deep	ADJ
cana-1705	31	2	learning	learning	NOUN
cana-1705	31	3	methods	method	NOUN
cana-1705	31	4	have	have	AUX
cana-1705	31	5	emerged	emerge	VERB
cana-1705	31	6	as	as	ADP
cana-1705	31	7	an	an	DET
cana-1705	31	8	alternative	alternative	ADJ
cana-1705	31	9	strategy	strategy	NOUN
cana-1705	31	10	to	to	ADP
cana-1705	31	11	traditional	traditional	ADJ
cana-1705	31	12	methods	method	NOUN
cana-1705	31	13	,	,	PUNCT
cana-1705	31	14	by	by	ADP
cana-1705	31	15	providing	provide	VERB
cana-1705	31	16	models	model	NOUN
cana-1705	31	17	that	that	PRON
cana-1705	31	18	can	can	AUX
cana-1705	31	19	capture	capture	VERB
cana-1705	31	20	complex	complex	ADJ
cana-1705	31	21	,	,	PUNCT
cana-1705	31	22	context	context	NOUN
cana-1705	31	23	-	-	PUNCT
cana-1705	31	24	driven	drive	VERB
cana-1705	31	25	patterns	pattern	NOUN
cana-1705	31	26	and	and	CCONJ
cana-1705	31	27	dependencies	dependency	NOUN
cana-1705	31	28	in	in	ADP
cana-1705	31	29	problems	problem	NOUN
cana-1705	31	30	where	where	SCONJ
cana-1705	31	31	relationships	relationship	NOUN
cana-1705	31	32	between	between	ADP
cana-1705	31	33	data	datum	NOUN
cana-1705	31	34	points	point	NOUN
cana-1705	31	35	are	be	AUX
cana-1705	31	36	nonlinear	nonlinear	ADJ
cana-1705	31	37	and	and	CCONJ
cana-1705	31	38	long	long	ADV
cana-1705	31	39	-	-	PUNCT
cana-1705	31	40	term[12	term[12	NOUN
cana-1705	31	41	]	]	PUNCT
cana-1705	31	42	.	.	PUNCT
cana-1705	32	1	deep	deep	ADJ
cana-1705	32	2	learning	learning	NOUN
cana-1705	32	3	has	have	AUX
cana-1705	32	4	enjoyed	enjoy	VERB
cana-1705	32	5	immense	immense	ADJ
cana-1705	32	6	success	success	NOUN
cana-1705	32	7	partly	partly	ADV
cana-1705	32	8	due	due	ADP
cana-1705	32	9	to	to	ADP
cana-1705	32	10	its	its	PRON
cana-1705	32	11	capability	capability	NOUN
cana-1705	32	12	to	to	PART
cana-1705	32	13	model	model	VERB
cana-1705	32	14	time	time	NOUN
cana-1705	32	15	-	-	PUNCT
cana-1705	32	16	series	series	NOUN
cana-1705	32	17	data	datum	NOUN
cana-1705	32	18	,	,	PUNCT
cana-1705	32	19	particularly	particularly	ADV
cana-1705	32	20	recurrent	recurrent	ADJ
cana-1705	32	21	neural	neural	ADJ
cana-1705	32	22	networks	network	NOUN
cana-1705	32	23	(	(	PUNCT
cana-1705	32	24	rnns	rnns	PROPN
cana-1705	32	25	)	)	PUNCT
cana-1705	32	26	.	.	PUNCT
cana-1705	33	1	in	in	ADP
cana-1705	33	2	the	the	DET
cana-1705	33	3	same	same	ADJ
cana-1705	33	4	way	way	NOUN
cana-1705	33	5	,	,	PUNCT
cana-1705	33	6	it	it	PRON
cana-1705	33	7	is	be	AUX
cana-1705	33	8	also	also	ADV
cana-1705	33	9	not	not	PART
cana-1705	33	10	ideal	ideal	ADJ
cana-1705	33	11	to	to	PART
cana-1705	33	12	treat	treat	VERB
cana-1705	33	13	each	each	DET
cana-1705	33	14	input	input	NOUN
cana-1705	33	15	independently	independently	ADV
cana-1705	33	16	since	since	SCONJ
cana-1705	33	17	traffic	traffic	NOUN
cana-1705	33	18	flow	flow	NOUN
cana-1705	33	19	is	be	AUX
cana-1705	33	20	a	a	DET
cana-1705	33	21	time	time	NOUN
cana-1705	33	22	series	series	NOUN
cana-1705	33	23	and	and	CCONJ
cana-1705	33	24	there	there	PRON
cana-1705	33	25	are	be	VERB
cana-1705	33	26	dependencies	dependency	NOUN
cana-1705	33	27	with	with	ADP
cana-1705	33	28	previous	previous	ADJ
cana-1705	33	29	states	state	NOUN
cana-1705	33	30	(	(	PUNCT
cana-1705	33	31	value	value	NOUN
cana-1705	33	32	of	of	ADP
cana-1705	33	33	current	current	ADJ
cana-1705	33	34	condition	condition	NOUN
cana-1705	33	35	strongly	strongly	ADV
cana-1705	33	36	depends	depend	VERB
cana-1705	33	37	on	on	ADP
cana-1705	33	38	its	its	PRON
cana-1705	33	39	own	own	ADJ
cana-1705	33	40	history	history	NOUN
cana-1705	33	41	)	)	PUNCT
cana-1705	33	42	.	.	PUNCT
cana-1705	34	1	in	in	ADP
cana-1705	34	2	contrast	contrast	NOUN
cana-1705	34	3	,	,	PUNCT
cana-1705	34	4	rnns	rnn	NOUN
cana-1705	34	5	have	have	VERB
cana-1705	34	6	the	the	DET
cana-1705	34	7	capacity	capacity	NOUN
cana-1705	34	8	to	to	PART
cana-1705	34	9	retain	retain	VERB
cana-1705	34	10	information	information	NOUN
cana-1705	34	11	by	by	ADP
cana-1705	34	12	remembering	remember	VERB
cana-1705	34	13	the	the	DET
cana-1705	34	14	prior	prior	ADJ
cana-1705	34	15	inputs	input	NOUN
cana-1705	34	16	and	and	CCONJ
cana-1705	34	17	are	be	AUX
cana-1705	34	18	thus	thus	ADV
cana-1705	34	19	suitable	suitable	ADJ
cana-1705	34	20	for	for	ADP
cana-1705	34	21	sequential	sequential	ADJ
cana-1705	34	22	data	datum	NOUN
cana-1705	34	23	.	.	PUNCT
cana-1705	35	1	lstm	lstm	NOUN
cana-1705	35	2	(	(	PUNCT
cana-1705	35	3	long	long	ADJ
cana-1705	35	4	short	short	ADJ
cana-1705	35	5	-	-	PUNCT
cana-1705	35	6	term	term	NOUN
cana-1705	35	7	memory	memory	NOUN
cana-1705	35	8	)	)	PUNCT
cana-1705	35	9	networks	network	NOUN
cana-1705	35	10	are	be	AUX
cana-1705	35	11	among	among	ADP
cana-1705	35	12	a	a	DET
cana-1705	35	13	variant	variant	NOUN
cana-1705	35	14	of	of	ADP
cana-1705	35	15	rnns	rnn	NOUN
cana-1705	35	16	that	that	PRON
cana-1705	35	17	were	be	AUX
cana-1705	35	18	designed	design	VERB
cana-1705	35	19	to	to	PART
cana-1705	35	20	help	help	VERB
cana-1705	35	21	mitigate	mitigate	VERB
cana-1705	35	22	the	the	DET
cana-1705	35	23	vanishing	vanish	VERB
cana-1705	35	24	gradient	gradient	NOUN
cana-1705	35	25	problem	problem	NOUN
cana-1705	35	26	in	in	ADP
cana-1705	35	27	standard	standard	ADJ
cana-1705	35	28	rnns	rnn	NOUN
cana-1705	35	29	,	,	PUNCT
cana-1705	35	30	giving	give	VERB
cana-1705	35	31	them	they	PRON
cana-1705	35	32	the	the	DET
cana-1705	35	33	ability	ability	NOUN
cana-1705	35	34	to	to	PART
cana-1705	35	35	operate	operate	VERB
cana-1705	35	36	over	over	ADP
cana-1705	35	37	longer	long	ADJ
cana-1705	35	38	sequence	sequence	NOUN
cana-1705	35	39	lengths	length	NOUN
cana-1705	35	40	.	.	PUNCT
cana-1705	36	1	one	one	NUM
cana-1705	36	2	domain	domain	NOUN
cana-1705	36	3	where	where	SCONJ
cana-1705	36	4	lstms	lstms	NOUN
cana-1705	36	5	shine	shine	NOUN
cana-1705	36	6	is	be	AUX
cana-1705	36	7	in	in	ADP
cana-1705	36	8	modelling	modelling	NOUN
cana-1705	36	9	and	and	CCONJ
cana-1705	36	10	predicting	predict	VERB
cana-1705	36	11	traffic	traffic	NOUN
cana-1705	36	12	flow	flow	NOUN
cana-1705	36	13	data	datum	NOUN
cana-1705	36	14	through	through	ADP
cana-1705	36	15	time	time	NOUN
cana-1705	36	16	because	because	SCONJ
cana-1705	36	17	of	of	ADP
cana-1705	36	18	the	the	DET
cana-1705	36	19	complex	complex	ADJ
cana-1705	36	20	temporal	temporal	ADJ
cana-1705	36	21	dependencies	dependency	NOUN
cana-1705	36	22	that	that	PRON
cana-1705	36	23	are	be	AUX
cana-1705	36	24	involved	involve	VERB
cana-1705	36	25	in	in	ADP
cana-1705	36	26	traffic	traffic	NOUN
cana-1705	36	27	flow	flow	NOUN
cana-1705	36	28	sequences	sequence	NOUN
cana-1705	36	29	(	(	PUNCT
cana-1705	36	30	patterns	pattern	NOUN
cana-1705	36	31	may	may	AUX
cana-1705	36	32	depend	depend	VERB
cana-1705	36	33	on	on	ADP
cana-1705	36	34	short	short	ADJ
cana-1705	36	35	-	-	PUNCT
cana-1705	36	36	term	term	NOUN
cana-1705	36	37	congestion	congestion	NOUN
cana-1705	36	38	levels	level	NOUN
cana-1705	36	39	,	,	PUNCT
cana-1705	36	40	as	as	ADV
cana-1705	36	41	well	well	ADV
cana-1705	36	42	as	as	ADP
cana-1705	36	43	long	long	ADJ
cana-1705	36	44	-	-	PUNCT
cana-1705	36	45	term	term	NOUN
cana-1705	36	46	daily	daily	ADJ
cana-1705	36	47	rush	rush	NOUN
cana-1705	36	48	hour	hour	NOUN
cana-1705	36	49	trends[13	trends[13	NOUN
cana-1705	36	50	]	]	PUNCT
cana-1705	36	51	)	)	PUNCT
cana-1705	36	52	.	.	PUNCT
cana-1705	37	1	lstm	lstm	PROPN
cana-1705	37	2	networks	network	NOUN
cana-1705	37	3	are	be	AUX
cana-1705	37	4	ideally	ideally	ADV
cana-1705	37	5	suited	suit	VERB
cana-1705	37	6	for	for	ADP
cana-1705	37	7	traffic	traffic	NOUN
cana-1705	37	8	flow	flow	NOUN
cana-1705	37	9	prediction	prediction	NOUN
cana-1705	37	10	.	.	PUNCT
cana-1705	38	1	one	one	NUM
cana-1705	38	2	reason	reason	NOUN
cana-1705	38	3	is	be	AUX
cana-1705	38	4	that	that	SCONJ
cana-1705	38	5	they	they	PRON
cana-1705	38	6	can	can	AUX
cana-1705	38	7	capture	capture	VERB
cana-1705	38	8	the	the	DET
cana-1705	38	9	dynamics	dynamic	NOUN
cana-1705	38	10	of	of	ADP
cana-1705	38	11	traffic	traffic	NOUN
cana-1705	38	12	flow	flow	NOUN
cana-1705	38	13	a	a	DET
cana-1705	38	14	highly	highly	ADV
cana-1705	38	15	nonlinear	nonlinear	ADJ
cana-1705	38	16	and	and	CCONJ
cana-1705	38	17	time	time	NOUN
cana-1705	38	18	-	-	PUNCT
cana-1705	38	19	varying	vary	VERB
cana-1705	38	20	system	system	NOUN
cana-1705	38	21	at	at	ADP
cana-1705	38	22	their	their	PRON
cana-1705	38	23	core	core	NOUN
cana-1705	38	24	,	,	PUNCT
cana-1705	38	25	making	make	VERB
cana-1705	38	26	them	they	PRON
cana-1705	38	27	ideal	ideal	ADJ
cana-1705	38	28	for	for	ADP
cana-1705	38	29	real	real	ADJ
cana-1705	38	30	-	-	PUNCT
cana-1705	38	31	time	time	NOUN
cana-1705	38	32	predictions	prediction	NOUN
cana-1705	38	33	.	.	PUNCT
cana-1705	39	1	second	second	ADJ
cana-1705	39	2	,	,	PUNCT
cana-1705	39	3	with	with	ADP
cana-1705	39	4	its	its	PRON
cana-1705	39	5	ability	ability	NOUN
cana-1705	39	6	to	to	PART
cana-1705	39	7	incorporate	incorporate	VERB
cana-1705	39	8	multiple	multiple	ADJ
cana-1705	39	9	data	datum	NOUN
cana-1705	39	10	sources	source	NOUN
cana-1705	39	11	(	(	PUNCT
cana-1705	39	12	historical	historical	ADJ
cana-1705	39	13	traffic	traffic	NOUN
cana-1705	39	14	patterns	pattern	NOUN
cana-1705	39	15	together	together	ADV
cana-1705	39	16	with	with	ADP
cana-1705	39	17	live	live	ADJ
cana-1705	39	18	sensor	sensor	NOUN
cana-1705	39	19	data	datum	NOUN
cana-1705	39	20	,	,	PUNCT
cana-1705	39	21	weather	weather	NOUN
cana-1705	39	22	conditions	condition	NOUN
cana-1705	39	23	,	,	PUNCT
cana-1705	39	24	and	and	CCONJ
cana-1705	39	25	reports	report	NOUN
cana-1705	39	26	of	of	ADP
cana-1705	39	27	incidents	incident	NOUN
cana-1705	39	28	)	)	PUNCT
cana-1705	39	29	the	the	DET
cana-1705	39	30	lstms	lstms	NOUN
cana-1705	39	31	can	can	AUX
cana-1705	39	32	offer	offer	VERB
cana-1705	39	33	a	a	DET
cana-1705	39	34	comprehensive	comprehensive	ADJ
cana-1705	39	35	perspective	perspective	NOUN
cana-1705	39	36	on	on	ADP
cana-1705	39	37	real	real	ADJ
cana-1705	39	38	-	-	PUNCT
cana-1705	39	39	time	time	NOUN
cana-1705	39	40	and	and	CCONJ
cana-1705	39	41	near	near	ADP
cana-1705	39	42	future	future	ADJ
cana-1705	39	43	traffic	traffic	NOUN
cana-1705	39	44	.	.	PUNCT
cana-1705	40	1	third	third	ADJ
cana-1705	40	2	,	,	PUNCT
cana-1705	40	3	their	their	PRON
cana-1705	40	4	capability	capability	NOUN
cana-1705	40	5	of	of	ADP
cana-1705	40	6	short	short	ADJ
cana-1705	40	7	term	term	NOUN
cana-1705	40	8	traffic	traffic	NOUN
cana-1705	40	9	forecasting	forecasting	NOUN
cana-1705	40	10	allows	allow	VERB
cana-1705	40	11	for	for	ADP
cana-1705	40	12	real	real	ADJ
cana-1705	40	13	-	-	PUNCT
cana-1705	40	14	time	time	NOUN
cana-1705	40	15	implementation	implementation	NOUN
cana-1705	40	16	(	(	PUNCT
cana-1705	40	17	e.g.	e.g.	ADV
cana-1705	40	18	dynamic	dynamic	ADJ
cana-1705	40	19	route	route	NOUN
cana-1705	40	20	planning	planning	NOUN
cana-1705	40	21	and	and	CCONJ
cana-1705	40	22	optimising	optimise	VERB
cana-1705	40	23	traffic	traffic	NOUN
cana-1705	40	24	signals	signal	NOUN
cana-1705	40	25	)	)	PUNCT
cana-1705	40	26	.	.	PUNCT
cana-1705	41	1	such	such	ADJ
cana-1705	41	2	features	feature	NOUN
cana-1705	41	3	make	make	VERB
cana-1705	41	4	lstms	lstms	ADJ
cana-1705	41	5	a	a	DET
cana-1705	41	6	very	very	ADV
cana-1705	41	7	optimistic	optimistic	ADJ
cana-1705	41	8	solution	solution	NOUN
cana-1705	41	9	to	to	PART
cana-1705	41	10	tackle	tackle	VERB
cana-1705	41	11	urban	urban	ADJ
cana-1705	41	12	traffic	traffic	NOUN
cana-1705	41	13	congestion	congestion	NOUN
cana-1705	41	14	problem	problem	NOUN
cana-1705	41	15	.	.	PUNCT
cana-1705	42	1	being	be	AUX
cana-1705	42	2	able	able	ADJ
cana-1705	42	3	to	to	PART
cana-1705	42	4	predict	predict	VERB
cana-1705	42	5	the	the	DET
cana-1705	42	6	flow	flow	NOUN
cana-1705	42	7	of	of	ADP
cana-1705	42	8	traffic	traffic	NOUN
cana-1705	42	9	at	at	ADP
cana-1705	42	10	any	any	DET
cana-1705	42	11	time	time	NOUN
cana-1705	42	12	literally	literally	ADV
cana-1705	42	13	represents	represent	VERB
cana-1705	42	14	a	a	DET
cana-1705	42	15	revolution	revolution	NOUN
cana-1705	42	16	in	in	ADP
cana-1705	42	17	urban	urban	ADJ
cana-1705	42	18	mobility	mobility	NOUN
cana-1705	42	19	.	.	PUNCT
cana-1705	43	1	dynamic	dynamic	ADJ
cana-1705	43	2	route	route	NOUN
cana-1705	43	3	optimization	optimization	NOUN
cana-1705	43	4	:	:	PUNCT
cana-1705	43	5	the	the	DET
cana-1705	43	6	most	most	ADV
cana-1705	43	7	direct	direct	ADJ
cana-1705	43	8	use	use	NOUN
cana-1705	43	9	of	of	ADP
cana-1705	43	10	real	real	ADJ
cana-1705	43	11	-	-	PUNCT
cana-1705	43	12	time	time	NOUN
cana-1705	43	13	traffic	traffic	NOUN
cana-1705	43	14	prediction	prediction	NOUN
cana-1705	43	15	,	,	PUNCT
cana-1705	43	16	instantaneous	instantaneous	ADJ
cana-1705	43	17	information	information	NOUN
cana-1705	43	18	about	about	ADP
cana-1705	43	19	traffic	traffic	NOUN
cana-1705	43	20	and	and	CCONJ
cana-1705	43	21	real	real	ADJ
cana-1705	43	22	-	-	PUNCT
cana-1705	43	23	time	time	NOUN
cana-1705	43	24	alternative	alternative	ADJ
cana-1705	43	25	routes	route	NOUN
cana-1705	43	26	to	to	ADP
cana-1705	43	27	each	each	DET
cana-1705	43	28	commuter	commuter	NOUN
cana-1705	43	29	.	.	PUNCT
cana-1705	44	1	real	real	ADJ
cana-1705	44	2	-	-	PUNCT
cana-1705	44	3	time	time	NOUN
cana-1705	44	4	traffic	traffic	NOUN
cana-1705	44	5	prediction	prediction	NOUN
cana-1705	44	6	could	could	AUX
cana-1705	44	7	influence	influence	VERB
cana-1705	44	8	drivers	driver	NOUN
cana-1705	44	9	to	to	PART
cana-1705	44	10	spread	spread	VERB
cana-1705	44	11	the	the	DET
cana-1705	44	12	traffic	traffic	NOUN
cana-1705	44	13	out	out	ADV
cana-1705	44	14	evenly	evenly	ADV
cana-1705	44	15	with	with	ADP
cana-1705	44	16	on	on	ADP
cana-1705	44	17	a	a	DET
cana-1705	44	18	network	network	NOUN
cana-1705	44	19	,	,	PUNCT
cana-1705	44	20	avoiding	avoid	VERB
cana-1705	44	21	congestion	congestion	NOUN
cana-1705	44	22	at	at	ADP
cana-1705	44	23	bottlenecks	bottleneck	NOUN
cana-1705	44	24	.	.	PUNCT
cana-1705	45	1	likewise	likewise	ADV
cana-1705	45	2	,	,	PUNCT
cana-1705	45	3	adaptive	adaptive	ADJ
cana-1705	45	4	traffic	traffic	NOUN
cana-1705	45	5	signal	signal	NOUN
cana-1705	45	6	control	control	NOUN
cana-1705	45	7	,	,	PUNCT
cana-1705	45	8	where	where	SCONJ
cana-1705	45	9	the	the	DET
cana-1705	45	10	timing	timing	NOUN
cana-1705	45	11	of	of	ADP
cana-1705	45	12	traffic	traffic	NOUN
cana-1705	45	13	lights	light	NOUN
cana-1705	45	14	is	be	AUX
cana-1705	45	15	dynamically	dynamically	ADV
cana-1705	45	16	modified	modify	VERB
cana-1705	45	17	based	base	VERB
cana-1705	45	18	on	on	ADP
cana-1705	45	19	predictions	prediction	NOUN
cana-1705	45	20	about	about	ADP
cana-1705	45	21	the	the	DET
cana-1705	45	22	flow	flow	NOUN
cana-1705	45	23	of	of	ADP
cana-1705	45	24	cars	car	NOUN
cana-1705	45	25	(	(	PUNCT
cana-1705	45	26	rather	rather	ADV
cana-1705	45	27	than	than	ADP
cana-1705	45	28	letting	let	VERB
cana-1705	45	29	this	this	PRON
cana-1705	45	30	be	be	AUX
cana-1705	45	31	determined	determine	VERB
cana-1705	45	32	by	by	ADP
cana-1705	45	33	a	a	DET
cana-1705	45	34	fixed	fix	VERB
cana-1705	45	35	schedule	schedule	NOUN
cana-1705	45	36	)	)	PUNCT
cana-1705	45	37	,	,	PUNCT
cana-1705	45	38	can	can	AUX
cana-1705	45	39	use	use	VERB
cana-1705	45	40	real	real	ADJ
cana-1705	45	41	-	-	PUNCT
cana-1705	45	42	time	time	NOUN
cana-1705	45	43	prediction	prediction	NOUN
cana-1705	45	44	about	about	ADP
cana-1705	45	45	car	car	NOUN
cana-1705	45	46	counts	count	NOUN
cana-1705	45	47	[	[	X
cana-1705	45	48	7	7	X
cana-1705	45	49	]	]	PUNCT
cana-1705	45	50	something	something	PRON
cana-1705	45	51	that	that	PRON
cana-1705	45	52	cavs	cavs	PROPN
cana-1705	45	53	could	could	AUX
cana-1705	45	54	provide	provide	VERB
cana-1705	45	55	with	with	ADP
cana-1705	45	56	much	much	ADV
cana-1705	45	57	better	well	ADJ
cana-1705	45	58	accuracy	accuracy	NOUN
cana-1705	45	59	and	and	CCONJ
cana-1705	45	60	ahead	ahead	ADV
cana-1705	45	61	-	-	PUNCT
cana-1705	45	62	of	of	ADP
cana-1705	45	63	-	-	PUNCT
cana-1705	45	64	time	time	NOUN
cana-1705	45	65	warning	warning	NOUN
cana-1705	45	66	than	than	ADP
cana-1705	45	67	historical	historical	ADJ
cana-1705	45	68	data	datum	NOUN
cana-1705	45	69	.	.	PUNCT
cana-1705	46	1	the	the	DET
cana-1705	46	2	hope	hope	NOUN
cana-1705	46	3	is	be	AUX
cana-1705	46	4	that	that	SCONJ
cana-1705	46	5	this	this	PRON
cana-1705	46	6	will	will	AUX
cana-1705	46	7	help	help	VERB
cana-1705	46	8	cut	cut	VERB
cana-1705	46	9	down	down	ADP
cana-1705	46	10	on	on	ADP
cana-1705	46	11	wait	wait	PROPN
cana-1705	46	12	times	time	NOUN
cana-1705	46	13	at	at	ADP
cana-1705	46	14	intersections	intersection	NOUN
cana-1705	46	15	and	and	CCONJ
cana-1705	46	16	allow	allow	VERB
cana-1705	46	17	for	for	ADP
cana-1705	46	18	a	a	DET
cana-1705	46	19	more	more	ADV
cana-1705	46	20	fluid	fluid	ADJ
cana-1705	46	21	flow	flow	NOUN
cana-1705	46	22	of	of	ADP
cana-1705	46	23	traffic	traffic	NOUN
cana-1705	46	24	as	as	ADP
cana-1705	46	25	idling	idle	VERB
cana-1705	46	26	vehicles	vehicle	NOUN
cana-1705	46	27	contribute	contribute	VERB
cana-1705	46	28	to	to	ADP
cana-1705	46	29	the	the	DET
cana-1705	46	30	release	release	NOUN
cana-1705	46	31	of	of	ADP
cana-1705	46	32	greenhouse	greenhouse	NOUN
cana-1705	46	33	gases[14	gases[14	NOUN
cana-1705	46	34	]	]	PUNCT
cana-1705	46	35	.	.	PUNCT
cana-1705	47	1	communications	communication	NOUN
cana-1705	47	2	on	on	ADP
cana-1705	47	3	applied	apply	VERB
cana-1705	47	4	nonlinear	nonlinear	ADJ
cana-1705	47	5	analysis	analysis	NOUN
cana-1705	47	6	issn	issn	NOUN
cana-1705	47	7	:	:	PUNCT
cana-1705	47	8	1074	1074	NUM
cana-1705	47	9	-	-	PUNCT
cana-1705	47	10	133x	133x	NUM
cana-1705	47	11	vol	vol	NOUN
cana-1705	47	12	32	32	NUM
cana-1705	47	13	no	no	NOUN
cana-1705	47	14	.	.	NOUN
cana-1705	47	15	2	2	NUM
cana-1705	47	16	(	(	PUNCT
cana-1705	47	17	2025	2025	NUM
cana-1705	47	18	)	)	PUNCT
cana-1705	47	19	4	4	NUM
cana-1705	47	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	47	21	in	in	ADP
cana-1705	47	22	addition	addition	NOUN
cana-1705	47	23	,	,	PUNCT
cana-1705	47	24	car	car	NOUN
cana-1705	47	25	deployments	deployment	NOUN
cana-1705	47	26	and	and	CCONJ
cana-1705	47	27	routes	route	NOUN
cana-1705	47	28	could	could	AUX
cana-1705	47	29	be	be	AUX
cana-1705	47	30	optimized	optimize	VERB
cana-1705	47	31	for	for	ADP
cana-1705	47	32	ridesharing	ridesharing	NOUN
cana-1705	47	33	platforms	platform	NOUN
cana-1705	47	34	,	,	PUNCT
cana-1705	47	35	public	public	ADJ
cana-1705	47	36	transit	transit	NOUN
cana-1705	47	37	systems	system	NOUN
cana-1705	47	38	or	or	CCONJ
cana-1705	47	39	autonomous	autonomous	ADJ
cana-1705	47	40	vehicle	vehicle	NOUN
cana-1705	47	41	algorithms	algorithm	NOUN
cana-1705	47	42	taking	take	VERB
cana-1705	47	43	real	real	ADJ
cana-1705	47	44	time	time	NOUN
cana-1705	47	45	traffic	traffic	NOUN
cana-1705	47	46	flow	flow	NOUN
cana-1705	47	47	prediction	prediction	NOUN
cana-1705	47	48	even	even	ADV
cana-1705	47	49	further	far	ADV
cana-1705	47	50	into	into	ADP
cana-1705	47	51	account	account	NOUN
cana-1705	47	52	.	.	PUNCT
cana-1705	48	1	as	as	ADP
cana-1705	48	2	an	an	DET
cana-1705	48	3	example	example	NOUN
cana-1705	48	4	,	,	PUNCT
cana-1705	48	5	companies	company	NOUN
cana-1705	48	6	such	such	ADJ
cana-1705	48	7	as	as	ADP
cana-1705	48	8	uber	uber	ADJ
cana-1705	48	9	and	and	CCONJ
cana-1705	48	10	lyft	lyft	NOUN
cana-1705	48	11	could	could	AUX
cana-1705	48	12	make	make	VERB
cana-1705	48	13	use	use	NOUN
cana-1705	48	14	of	of	ADP
cana-1705	48	15	traffic	traffic	NOUN
cana-1705	48	16	predictions	prediction	NOUN
cana-1705	48	17	to	to	PART
cana-1705	48	18	change	change	VERB
cana-1705	48	19	prices	price	NOUN
cana-1705	48	20	,	,	PUNCT
cana-1705	48	21	balance	balance	VERB
cana-1705	48	22	the	the	DET
cana-1705	48	23	driver	driver	NOUN
cana-1705	48	24	fleets	fleet	NOUN
cana-1705	48	25	or	or	CCONJ
cana-1705	48	26	forecast	forecast	NOUN
cana-1705	48	27	arrival	arrival	NOUN
cana-1705	48	28	times	time	NOUN
cana-1705	48	29	more	more	ADV
cana-1705	48	30	accurately	accurately	ADV
cana-1705	48	31	.	.	PUNCT
cana-1705	49	1	similarly	similarly	ADV
cana-1705	49	2	,	,	PUNCT
cana-1705	49	3	public	public	ADJ
cana-1705	49	4	transit	transit	NOUN
cana-1705	49	5	authorities	authority	NOUN
cana-1705	49	6	can	can	AUX
cana-1705	49	7	change	change	VERB
cana-1705	49	8	bus	bus	NOUN
cana-1705	49	9	routes	route	NOUN
cana-1705	49	10	or	or	CCONJ
cana-1705	49	11	frequencies	frequency	NOUN
cana-1705	49	12	as	as	ADP
cana-1705	49	13	a	a	DET
cana-1705	49	14	function	function	NOUN
cana-1705	49	15	of	of	ADP
cana-1705	49	16	anticipated	anticipate	VERB
cana-1705	49	17	traffic	traffic	NOUN
cana-1705	49	18	conditions	condition	NOUN
cana-1705	49	19	,	,	PUNCT
cana-1705	49	20	thus	thus	ADV
cana-1705	49	21	maintaining	maintain	VERB
cana-1705	49	22	their	their	PRON
cana-1705	49	23	frequency	frequency	NOUN
cana-1705	49	24	.	.	PUNCT
cana-1705	50	1	that	that	DET
cana-1705	50	2	same	same	ADJ
cana-1705	50	3	real	real	ADJ
cana-1705	50	4	-	-	PUNCT
cana-1705	50	5	time	time	NOUN
cana-1705	50	6	traffic	traffic	NOUN
cana-1705	50	7	data	datum	NOUN
cana-1705	50	8	could	could	AUX
cana-1705	50	9	be	be	AUX
cana-1705	50	10	used	use	VERB
cana-1705	50	11	to	to	PART
cana-1705	50	12	help	help	VERB
cana-1705	50	13	autonomous	autonomous	ADJ
cana-1705	50	14	vehicles	vehicle	NOUN
cana-1705	50	15	make	make	VERB
cana-1705	50	16	smarter	smart	ADJ
cana-1705	50	17	driving	driving	NOUN
cana-1705	50	18	decisions	decision	NOUN
cana-1705	50	19	,	,	PUNCT
cana-1705	50	20	in	in	ADP
cana-1705	50	21	essence	essence	NOUN
cana-1705	50	22	improving	improve	VERB
cana-1705	50	23	the	the	DET
cana-1705	50	24	overall	overall	ADJ
cana-1705	50	25	efficiency	efficiency	NOUN
cana-1705	50	26	and	and	CCONJ
cana-1705	50	27	safety	safety	NOUN
cana-1705	50	28	of	of	ADP
cana-1705	50	29	urban	urban	ADJ
cana-1705	50	30	transportation[15	transportation[15	NOUN
cana-1705	50	31	]	]	PUNCT
cana-1705	50	32	.	.	PUNCT
cana-1705	51	1	although	although	SCONJ
cana-1705	51	2	appealing	appeal	VERB
cana-1705	51	3	,	,	PUNCT
cana-1705	51	4	there	there	PRON
cana-1705	51	5	are	be	VERB
cana-1705	51	6	multiple	multiple	ADJ
cana-1705	51	7	challenges	challenge	NOUN
cana-1705	51	8	to	to	PART
cana-1705	51	9	deploy	deploy	VERB
cana-1705	51	10	the	the	DET
cana-1705	51	11	real	real	ADJ
cana-1705	51	12	-	-	PUNCT
cana-1705	51	13	time	time	NOUN
cana-1705	51	14	traffic	traffic	NOUN
cana-1705	51	15	flow	flow	NOUN
cana-1705	51	16	prediction	prediction	NOUN
cana-1705	51	17	systems	system	NOUN
cana-1705	51	18	in	in	ADP
cana-1705	51	19	reality	reality	NOUN
cana-1705	51	20	.	.	PUNCT
cana-1705	52	1	for	for	ADP
cana-1705	52	2	one	one	NUM
cana-1705	52	3	,	,	PUNCT
cana-1705	52	4	the	the	DET
cana-1705	52	5	problem	problem	NOUN
cana-1705	52	6	of	of	ADP
cana-1705	52	7	availability	availability	NOUN
cana-1705	52	8	and	and	CCONJ
cana-1705	52	9	quality	quality	NOUN
cana-1705	52	10	of	of	ADP
cana-1705	52	11	data	datum	NOUN
cana-1705	52	12	.	.	PUNCT
cana-1705	53	1	traffic	traffic	NOUN
cana-1705	53	2	flow	flow	NOUN
cana-1705	53	3	prediction	prediction	NOUN
cana-1705	53	4	depends	depend	VERB
cana-1705	53	5	on	on	ADP
cana-1705	53	6	a	a	DET
cana-1705	53	7	large	large	ADJ
cana-1705	53	8	amount	amount	NOUN
cana-1705	53	9	of	of	ADP
cana-1705	53	10	multi	multi	ADJ
cana-1705	53	11	-	-	ADJ
cana-1705	53	12	dimensional	dimensional	ADJ
cana-1705	53	13	,	,	PUNCT
cana-1705	53	14	real	real	ADJ
cana-1705	53	15	-	-	PUNCT
cana-1705	53	16	time	time	NOUN
cana-1705	53	17	data	datum	NOUN
cana-1705	53	18	including	include	VERB
cana-1705	53	19	gps	gps	PROPN
cana-1705	53	20	location	location	NOUN
cana-1705	53	21	information	information	NOUN
cana-1705	53	22	,	,	PUNCT
cana-1705	53	23	road	road	NOUN
cana-1705	53	24	sensors	sensor	NOUN
cana-1705	53	25	and	and	CCONJ
cana-1705	53	26	social	social	ADJ
cana-1705	53	27	networks	network	NOUN
cana-1705	53	28	.	.	PUNCT
cana-1705	54	1	the	the	DET
cana-1705	54	2	data	datum	NOUN
cana-1705	54	3	from	from	ADP
cana-1705	54	4	these	these	DET
cana-1705	54	5	sources	source	NOUN
cana-1705	54	6	first	first	ADV
cana-1705	54	7	need	need	VERB
cana-1705	54	8	to	to	PART
cana-1705	54	9	be	be	AUX
cana-1705	54	10	pre	pre	VERB
cana-1705	54	11	-	-	VERB
cana-1705	54	12	processed	process	VERB
cana-1705	54	13	,	,	PUNCT
cana-1705	54	14	cleaned	clean	VERB
cana-1705	54	15	and	and	CCONJ
cana-1705	54	16	streamed	stream	VERB
cana-1705	54	17	which	which	PRON
cana-1705	54	18	is	be	AUX
cana-1705	54	19	computationally	computationally	ADV
cana-1705	54	20	expensive	expensive	ADJ
cana-1705	54	21	.	.	PUNCT
cana-1705	55	1	in	in	ADP
cana-1705	55	2	addition	addition	NOUN
cana-1705	55	3	,	,	PUNCT
cana-1705	55	4	prediction	prediction	NOUN
cana-1705	55	5	models	model	NOUN
cana-1705	55	6	and	and	CCONJ
cana-1705	55	7	their	their	PRON
cana-1705	55	8	performance	performance	NOUN
cana-1705	55	9	are	be	AUX
cana-1705	55	10	particularly	particularly	ADV
cana-1705	55	11	affected	affect	VERB
cana-1705	55	12	by	by	ADP
cana-1705	55	13	the	the	DET
cana-1705	55	14	presence	presence	NOUN
cana-1705	55	15	of	of	ADP
cana-1705	55	16	missing	missing	ADJ
cana-1705	55	17	or	or	CCONJ
cana-1705	55	18	incorrect	incorrect	ADJ
cana-1705	55	19	data	datum	NOUN
cana-1705	55	20	and	and	CCONJ
cana-1705	55	21	hence	hence	ADV
cana-1705	55	22	there	there	PRON
cana-1705	55	23	is	be	VERB
cana-1705	55	24	a	a	DET
cana-1705	55	25	considerable	considerable	ADJ
cana-1705	55	26	body	body	NOUN
cana-1705	55	27	of	of	ADP
cana-1705	55	28	work	work	NOUN
cana-1705	55	29	on	on	ADP
cana-1705	55	30	data	datum	NOUN
cana-1705	55	31	imputation	imputation	NOUN
cana-1705	55	32	algorithms	algorithm	NOUN
cana-1705	55	33	,	,	PUNCT
cana-1705	55	34	error	error	NOUN
cana-1705	55	35	-	-	PUNCT
cana-1705	55	36	correction	correction	NOUN
cana-1705	55	37	methods	method	NOUN
cana-1705	55	38	.	.	PUNCT
cana-1705	56	1	another	another	DET
cana-1705	56	2	limitation	limitation	NOUN
cana-1705	56	3	is	be	AUX
cana-1705	56	4	the	the	DET
cana-1705	56	5	scalability	scalability	NOUN
cana-1705	56	6	of	of	ADP
cana-1705	56	7	real	real	ADJ
cana-1705	56	8	-	-	PUNCT
cana-1705	56	9	time	time	NOUN
cana-1705	56	10	traffic	traffic	NOUN
cana-1705	56	11	prediction	prediction	NOUN
cana-1705	56	12	systems	system	NOUN
cana-1705	56	13	.	.	PUNCT
cana-1705	57	1	urban	urban	ADJ
cana-1705	57	2	environments	environment	NOUN
cana-1705	57	3	comprise	comprise	VERB
cana-1705	57	4	vast	vast	ADJ
cana-1705	57	5	transportation	transportation	NOUN
cana-1705	57	6	networks	network	NOUN
cana-1705	57	7	thousands	thousand	NOUN
cana-1705	57	8	of	of	ADP
cana-1705	57	9	roads	road	NOUN
cana-1705	57	10	,	,	PUNCT
cana-1705	57	11	intersections	intersection	NOUN
cana-1705	57	12	and	and	CCONJ
cana-1705	57	13	cars	car	NOUN
cana-1705	57	14	all	all	PRON
cana-1705	57	15	moving	move	VERB
cana-1705	57	16	at	at	ADV
cana-1705	57	17	once	once	ADV
cana-1705	57	18	.	.	PUNCT
cana-1705	58	1	in	in	ADP
cana-1705	58	2	order	order	NOUN
cana-1705	58	3	for	for	SCONJ
cana-1705	58	4	traffic	traffic	NOUN
cana-1705	58	5	prediction	prediction	NOUN
cana-1705	58	6	models	model	NOUN
cana-1705	58	7	to	to	PART
cana-1705	58	8	work	work	VERB
cana-1705	58	9	,	,	PUNCT
cana-1705	58	10	they	they	PRON
cana-1705	58	11	need	need	VERB
cana-1705	58	12	to	to	PART
cana-1705	58	13	be	be	AUX
cana-1705	58	14	scalable	scalable	ADJ
cana-1705	58	15	and	and	CCONJ
cana-1705	58	16	optimized	optimize	VERB
cana-1705	58	17	enough	enough	ADV
cana-1705	58	18	for	for	ADP
cana-1705	58	19	these	these	DET
cana-1705	58	20	large	large	ADJ
cana-1705	58	21	networks	network	NOUN
cana-1705	58	22	.	.	PUNCT
cana-1705	59	1	to	to	PART
cana-1705	59	2	achieve	achieve	VERB
cana-1705	59	3	this	this	PRON
cana-1705	59	4	,	,	PUNCT
cana-1705	59	5	we	we	PRON
cana-1705	59	6	need	need	VERB
cana-1705	59	7	to	to	PART
cana-1705	59	8	design	design	VERB
cana-1705	59	9	efficient	efficient	ADJ
cana-1705	59	10	algorithms	algorithm	NOUN
cana-1705	59	11	and	and	CCONJ
cana-1705	59	12	data	datum	NOUN
cana-1705	59	13	processing	processing	NOUN
cana-1705	59	14	architectures	architecture	NOUN
cana-1705	59	15	that	that	PRON
cana-1705	59	16	can	can	AUX
cana-1705	59	17	process	process	VERB
cana-1705	59	18	traffic	traffic	NOUN
cana-1705	59	19	flow	flow	NOUN
cana-1705	59	20	in	in	ADP
cana-1705	59	21	real	real	ADJ
cana-1705	59	22	time	time	NOUN
cana-1705	59	23	without	without	ADP
cana-1705	59	24	some	some	DET
cana-1705	59	25	delay	delay	NOUN
cana-1705	59	26	.	.	PUNCT
cana-1705	60	1	lastly	lastly	ADV
cana-1705	60	2	,	,	PUNCT
cana-1705	60	3	traffic	traffic	NOUN
cana-1705	60	4	flow	flow	NOUN
cana-1705	60	5	is	be	AUX
cana-1705	60	6	affected	affect	VERB
cana-1705	60	7	by	by	ADP
cana-1705	60	8	a	a	DET
cana-1705	60	9	host	host	NOUN
cana-1705	60	10	of	of	ADP
cana-1705	60	11	external	external	ADJ
cana-1705	60	12	factors	factor	NOUN
cana-1705	60	13	like	like	ADP
cana-1705	60	14	the	the	DET
cana-1705	60	15	weather	weather	NOUN
cana-1705	60	16	,	,	PUNCT
cana-1705	60	17	construction	construction	NOUN
cana-1705	60	18	and	and	CCONJ
cana-1705	60	19	accidents	accident	NOUN
cana-1705	60	20	.	.	PUNCT
cana-1705	61	1	this	this	DET
cana-1705	61	2	ongoing	ongoing	ADJ
cana-1705	61	3	area	area	NOUN
cana-1705	61	4	of	of	ADP
cana-1705	61	5	research	research	NOUN
cana-1705	61	6	is	be	AUX
cana-1705	61	7	how	how	SCONJ
cana-1705	61	8	to	to	PART
cana-1705	61	9	incorporate	incorporate	VERB
cana-1705	61	10	these	these	DET
cana-1705	61	11	external	external	ADJ
cana-1705	61	12	variables	variable	NOUN
cana-1705	61	13	into	into	ADP
cana-1705	61	14	predictive	predictive	ADJ
cana-1705	61	15	models	model	NOUN
cana-1705	61	16	in	in	ADP
cana-1705	61	17	a	a	DET
cana-1705	61	18	meaningful	meaningful	ADJ
cana-1705	61	19	manner	manner	NOUN
cana-1705	61	20	.	.	PUNCT
cana-1705	62	1	although	although	SCONJ
cana-1705	62	2	lstm	lstm	ADJ
cana-1705	62	3	networks	network	NOUN
cana-1705	62	4	have	have	AUX
cana-1705	62	5	demonstrated	demonstrate	VERB
cana-1705	62	6	high	high	ADJ
cana-1705	62	7	efficacy	efficacy	NOUN
cana-1705	62	8	in	in	ADP
cana-1705	62	9	modelling	model	VERB
cana-1705	62	10	the	the	DET
cana-1705	62	11	temporal	temporal	ADJ
cana-1705	62	12	information	information	NOUN
cana-1705	62	13	,	,	PUNCT
cana-1705	62	14	they	they	PRON
cana-1705	62	15	are	be	AUX
cana-1705	62	16	not	not	PART
cana-1705	62	17	designed	design	VERB
cana-1705	62	18	to	to	PART
cana-1705	62	19	consider	consider	VERB
cana-1705	62	20	other	other	ADJ
cana-1705	62	21	external	external	ADJ
cana-1705	62	22	factors	factor	NOUN
cana-1705	62	23	,	,	PUNCT
cana-1705	62	24	which	which	PRON
cana-1705	62	25	require	require	VERB
cana-1705	62	26	additional	additional	ADJ
cana-1705	62	27	models	model	NOUN
cana-1705	62	28	like	like	ADP
cana-1705	62	29	attention	attention	NOUN
cana-1705	62	30	mechanisms	mechanism	NOUN
cana-1705	62	31	or	or	CCONJ
cana-1705	62	32	hybrids[16	hybrids[16	NOUN
cana-1705	62	33	]	]	PUNCT
cana-1705	62	34	.	.	PUNCT
cana-1705	63	1	in	in	ADP
cana-1705	63	2	this	this	DET
cana-1705	63	3	paper	paper	NOUN
cana-1705	63	4	,	,	PUNCT
cana-1705	63	5	an	an	DET
cana-1705	63	6	implementation	implementation	NOUN
cana-1705	63	7	for	for	ADP
cana-1705	63	8	a	a	DET
cana-1705	63	9	system	system	NOUN
cana-1705	63	10	used	use	VERB
cana-1705	63	11	to	to	PART
cana-1705	63	12	predict	predict	VERB
cana-1705	63	13	urban	urban	ADJ
cana-1705	63	14	traffic	traffic	NOUN
cana-1705	63	15	flow	flow	NOUN
cana-1705	63	16	in	in	ADP
cana-1705	63	17	real	real	ADJ
cana-1705	63	18	-	-	PUNCT
cana-1705	63	19	time	time	NOUN
cana-1705	63	20	will	will	AUX
cana-1705	63	21	be	be	AUX
cana-1705	63	22	introduced	introduce	VERB
cana-1705	63	23	integrating	integrate	VERB
cana-1705	63	24	lstm	lstm	ADJ
cana-1705	63	25	networks	network	NOUN
cana-1705	63	26	.	.	PUNCT
cana-1705	64	1	the	the	DET
cana-1705	64	2	main	main	ADJ
cana-1705	64	3	goals	goal	NOUN
cana-1705	64	4	of	of	ADP
cana-1705	64	5	this	this	DET
cana-1705	64	6	study	study	NOUN
cana-1705	64	7	can	can	AUX
cana-1705	64	8	be	be	AUX
cana-1705	64	9	summarized	summarize	VERB
cana-1705	64	10	as	as	SCONJ
cana-1705	64	11	follows	follow	VERB
cana-1705	64	12	:	:	PUNCT
cana-1705	64	13	(	(	PUNCT
cana-1705	64	14	1	1	X
cana-1705	64	15	)	)	PUNCT
cana-1705	64	16	an	an	DET
cana-1705	64	17	lstm	lstm	NOUN
cana-1705	64	18	-	-	PUNCT
cana-1705	64	19	based	base	VERB
cana-1705	64	20	model	model	NOUN
cana-1705	64	21	is	be	AUX
cana-1705	64	22	developed	develop	VERB
cana-1705	64	23	to	to	PART
cana-1705	64	24	predict	predict	VERB
cana-1705	64	25	short	short	ADJ
cana-1705	64	26	-	-	PUNCT
cana-1705	64	27	term	term	NOUN
cana-1705	64	28	traffic	traffic	NOUN
cana-1705	64	29	flow	flow	NOUN
cana-1705	64	30	in	in	ADP
cana-1705	64	31	a	a	DET
cana-1705	64	32	completely	completely	ADV
cana-1705	64	33	online	online	ADJ
cana-1705	64	34	manner	manner	NOUN
cana-1705	64	35	with	with	ADP
cana-1705	64	36	high	high	ADJ
cana-1705	64	37	prediction	prediction	NOUN
cana-1705	64	38	accuracy	accuracy	NOUN
cana-1705	64	39	,	,	PUNCT
cana-1705	64	40	(	(	PUNCT
cana-1705	64	41	2	2	X
cana-1705	64	42	)	)	PUNCT
cana-1705	64	43	the	the	DET
cana-1705	64	44	effectiveness	effectiveness	NOUN
cana-1705	64	45	was	be	AUX
cana-1705	64	46	verified	verify	VERB
cana-1705	64	47	,	,	PUNCT
cana-1705	64	48	by	by	ADP
cana-1705	64	49	analysing	analyse	VERB
cana-1705	64	50	real	real	ADJ
cana-1705	64	51	-	-	PUNCT
cana-1705	64	52	world	world	NOUN
cana-1705	64	53	traffic	traffic	NOUN
cana-1705	64	54	data	datum	NOUN
cana-1705	64	55	and	and	CCONJ
cana-1705	64	56	compared	compare	VERB
cana-1705	64	57	with	with	ADP
cana-1705	64	58	traditional	traditional	ADJ
cana-1705	64	59	machine	machine	NOUN
cana-1705	64	60	learning	learning	NOUN
cana-1705	64	61	models	model	NOUN
cana-1705	64	62	,	,	PUNCT
cana-1705	64	63	and	and	CCONJ
cana-1705	64	64	(	(	PUNCT
cana-1705	64	65	3	3	X
cana-1705	64	66	)	)	PUNCT
cana-1705	64	67	an	an	DET
cana-1705	64	68	application	application	NOUN
cana-1705	64	69	of	of	ADP
cana-1705	64	70	the	the	DET
cana-1705	64	71	proposed	propose	VERB
cana-1705	64	72	model	model	NOUN
cana-1705	64	73	for	for	ADP
cana-1705	64	74	on	on	ADP
cana-1705	64	75	-	-	PUNCT
cana-1705	64	76	line	line	NOUN
cana-1705	64	77	traffic	traffic	NOUN
cana-1705	64	78	management	management	NOUN
cana-1705	64	79	such	such	ADJ
cana-1705	64	80	as	as	ADP
cana-1705	64	81	dynamic	dynamic	ADJ
cana-1705	64	82	route	route	NOUN
cana-1705	64	83	selection	selection	NOUN
cana-1705	64	84	and	and	CCONJ
cana-1705	64	85	signal	signal	PROPN
cana-1705	64	86	control	control	NOUN
cana-1705	64	87	has	have	AUX
cana-1705	64	88	been	be	AUX
cana-1705	64	89	demonstrated	demonstrate	VERB
cana-1705	64	90	.	.	PUNCT
cana-1705	65	1	we	we	PRON
cana-1705	65	2	summarize	summarize	VERB
cana-1705	65	3	the	the	DET
cana-1705	65	4	contributions	contribution	NOUN
cana-1705	65	5	of	of	ADP
cana-1705	65	6	ours	ours	PRON
cana-1705	65	7	as	as	ADP
cana-1705	65	8	:	:	PUNCT
cana-1705	65	9	•	•	NOUN
cana-1705	65	10	we	we	PRON
cana-1705	65	11	introduce	introduce	VERB
cana-1705	65	12	a	a	DET
cana-1705	65	13	new	new	ADJ
cana-1705	65	14	lstm	lstm	NOUN
cana-1705	65	15	-	-	PUNCT
cana-1705	65	16	based	base	VERB
cana-1705	65	17	model	model	NOUN
cana-1705	65	18	for	for	ADP
cana-1705	65	19	traffic	traffic	NOUN
cana-1705	65	20	flow	flow	NOUN
cana-1705	65	21	prediction	prediction	NOUN
cana-1705	65	22	,	,	PUNCT
cana-1705	65	23	using	use	VERB
cana-1705	65	24	which	which	PRON
cana-1705	65	25	we	we	PRON
cana-1705	65	26	are	be	AUX
cana-1705	65	27	able	able	ADJ
cana-1705	65	28	to	to	PART
cana-1705	65	29	capture	capture	VERB
cana-1705	65	30	short	short	ADJ
cana-1705	65	31	-	-	PUNCT
cana-1705	65	32	term	term	NOUN
cana-1705	65	33	and	and	CCONJ
cana-1705	65	34	long	long	ADJ
cana-1705	65	35	-	-	PUNCT
cana-1705	65	36	term	term	NOUN
cana-1705	65	37	temporal	temporal	ADJ
cana-1705	65	38	structure	structure	NOUN
cana-1705	65	39	in	in	ADP
cana-1705	65	40	traffic	traffic	NOUN
cana-1705	65	41	data	datum	NOUN
cana-1705	65	42	for	for	ADP
cana-1705	65	43	high	high	ADJ
cana-1705	65	44	-	-	PUNCT
cana-1705	65	45	accuracy	accuracy	NOUN
cana-1705	65	46	real	real	ADJ
cana-1705	65	47	time	time	NOUN
cana-1705	65	48	forecasting	forecasting	NOUN
cana-1705	65	49	.	.	PUNCT
cana-1705	66	1	•	•	INTJ
cana-1705	66	2	we	we	PRON
cana-1705	66	3	combine	combine	VERB
cana-1705	66	4	the	the	DET
cana-1705	66	5	data	datum	NOUN
cana-1705	66	6	sources	source	NOUN
cana-1705	66	7	gps	gp	VERB
cana-1705	66	8	information	information	NOUN
cana-1705	66	9	,	,	PUNCT
cana-1705	66	10	road	road	NOUN
cana-1705	66	11	sensors	sensor	NOUN
cana-1705	66	12	and	and	CCONJ
cana-1705	66	13	weather	weather	NOUN
cana-1705	66	14	information	information	NOUN
cana-1705	66	15	in	in	ADP
cana-1705	66	16	order	order	NOUN
cana-1705	66	17	to	to	PART
cana-1705	66	18	improve	improve	VERB
cana-1705	66	19	the	the	DET
cana-1705	66	20	quality	quality	NOUN
cana-1705	66	21	and	and	CCONJ
cana-1705	66	22	robustness	robustness	NOUN
cana-1705	66	23	of	of	ADP
cana-1705	66	24	our	our	PRON
cana-1705	66	25	model	model	NOUN
cana-1705	66	26	based	base	VERB
cana-1705	66	27	on	on	ADP
cana-1705	66	28	these	these	DET
cana-1705	66	29	points	point	NOUN
cana-1705	66	30	.	.	PUNCT
cana-1705	67	1	communications	communication	NOUN
cana-1705	67	2	on	on	ADP
cana-1705	67	3	applied	apply	VERB
cana-1705	67	4	nonlinear	nonlinear	ADJ
cana-1705	67	5	analysis	analysis	NOUN
cana-1705	67	6	issn	issn	NOUN
cana-1705	67	7	:	:	PUNCT
cana-1705	67	8	1074	1074	NUM
cana-1705	67	9	-	-	PUNCT
cana-1705	67	10	133x	133x	NUM
cana-1705	67	11	vol	vol	NOUN
cana-1705	67	12	32	32	NUM
cana-1705	67	13	no	no	NOUN
cana-1705	67	14	.	.	NOUN
cana-1705	67	15	2	2	NUM
cana-1705	67	16	(	(	PUNCT
cana-1705	67	17	2025	2025	NUM
cana-1705	67	18	)	)	PUNCT
cana-1705	67	19	5	5	NUM
cana-1705	67	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	67	21	•	•	NOUN
cana-1705	67	22	we	we	PRON
cana-1705	67	23	perform	perform	VERB
cana-1705	67	24	comprehensive	comprehensive	ADJ
cana-1705	67	25	experiments	experiment	NOUN
cana-1705	67	26	across	across	ADP
cana-1705	67	27	multiple	multiple	ADJ
cana-1705	67	28	real	real	ADJ
cana-1705	67	29	-	-	PUNCT
cana-1705	67	30	world	world	NOUN
cana-1705	67	31	traffic	traffic	NOUN
cana-1705	67	32	datasets	dataset	NOUN
cana-1705	67	33	to	to	PART
cana-1705	67	34	showcase	showcase	VERB
cana-1705	67	35	the	the	DET
cana-1705	67	36	effectiveness	effectiveness	NOUN
cana-1705	67	37	of	of	ADP
cana-1705	67	38	the	the	DET
cana-1705	67	39	proposed	propose	VERB
cana-1705	67	40	lstm	lstm	NOUN
cana-1705	67	41	model	model	NOUN
cana-1705	67	42	as	as	ADP
cana-1705	67	43	compared	compare	VERB
cana-1705	67	44	to	to	ADP
cana-1705	67	45	existing	exist	VERB
cana-1705	67	46	models	model	NOUN
cana-1705	67	47	such	such	ADJ
cana-1705	67	48	as	as	ADP
cana-1705	67	49	arima	arima	NOUN
cana-1705	67	50	and	and	CCONJ
cana-1705	67	51	svm	svm	ADJ
cana-1705	67	52	.	.	PROPN
cana-1705	67	53	•	•	NUM
cana-1705	67	54	2we	2we	NOUN
cana-1705	67	55	explore	explore	VERB
cana-1705	67	56	the	the	DET
cana-1705	67	57	real	real	ADJ
cana-1705	67	58	-	-	PUNCT
cana-1705	67	59	time	time	NOUN
cana-1705	67	60	urban	urban	ADJ
cana-1705	67	61	mobility	mobility	PROPN
cana-1705	67	62	scenario	scenario	PROPN
cana-1705	67	63	for	for	ADP
cana-1705	67	64	route	route	NOUN
cana-1705	67	65	choice	choice	NOUN
cana-1705	67	66	and	and	CCONJ
cana-1705	67	67	adaptive	adaptive	ADJ
cana-1705	67	68	traffic	traffic	NOUN
cana-1705	67	69	lights	light	NOUN
cana-1705	67	70	(	(	PUNCT
cana-1705	67	71	rlcs	rlcs	NOUN
cana-1705	67	72	,	,	PUNCT
cana-1705	67	73	adaptive	adaptive	ADJ
cana-1705	67	74	control	control	NOUN
cana-1705	67	75	)	)	PUNCT
cana-1705	67	76	.	.	PUNCT
cana-1705	68	1	in	in	ADP
cana-1705	68	2	the	the	DET
cana-1705	68	3	rest	rest	NOUN
cana-1705	68	4	of	of	ADP
cana-1705	68	5	this	this	DET
cana-1705	68	6	paper	paper	NOUN
cana-1705	68	7	,	,	PUNCT
cana-1705	68	8	we	we	PRON
cana-1705	68	9	introduce	introduce	VERB
cana-1705	68	10	related	related	ADJ
cana-1705	68	11	work	work	NOUN
cana-1705	68	12	on	on	ADP
cana-1705	68	13	traffic	traffic	NOUN
cana-1705	68	14	flow	flow	NOUN
cana-1705	68	15	prediction	prediction	NOUN
cana-1705	68	16	and	and	CCONJ
cana-1705	68	17	deep	deep	ADJ
cana-1705	68	18	learning	learning	NOUN
cana-1705	68	19	models	model	NOUN
cana-1705	68	20	in	in	ADP
cana-1705	68	21	section	section	NOUN
cana-1705	68	22	2	2	NUM
cana-1705	68	23	.	.	PUNCT
cana-1705	69	1	the	the	DET
cana-1705	69	2	methodology	methodology	NOUN
cana-1705	69	3	is	be	AUX
cana-1705	69	4	presented	present	VERB
cana-1705	69	5	in	in	ADP
cana-1705	69	6	section	section	NOUN
cana-1705	69	7	3	3	NUM
cana-1705	69	8	,	,	PUNCT
cana-1705	69	9	which	which	PRON
cana-1705	69	10	covers	cover	VERB
cana-1705	69	11	the	the	DET
cana-1705	69	12	architecture	architecture	NOUN
cana-1705	69	13	and	and	CCONJ
cana-1705	69	14	development	development	NOUN
cana-1705	69	15	of	of	ADP
cana-1705	69	16	the	the	DET
cana-1705	69	17	lstm	lstm	PROPN
cana-1705	69	18	model	model	PROPN
cana-1705	69	19	.	.	PUNCT
cana-1705	70	1	section	section	NOUN
cana-1705	70	2	4	4	NUM
cana-1705	70	3	presents	present	VERB
cana-1705	70	4	the	the	DET
cana-1705	70	5	setup	setup	NOUN
cana-1705	70	6	of	of	ADP
cana-1705	70	7	our	our	PRON
cana-1705	70	8	experiment	experiment	NOUN
cana-1705	70	9	and	and	CCONJ
cana-1705	70	10	the	the	DET
cana-1705	70	11	related	relate	VERB
cana-1705	70	12	results	result	NOUN
cana-1705	70	13	and	and	CCONJ
cana-1705	70	14	section	section	NOUN
cana-1705	70	15	5	5	NUM
cana-1705	70	16	closes	close	VERB
cana-1705	70	17	with	with	ADP
cana-1705	70	18	conclusions	conclusion	NOUN
cana-1705	70	19	and	and	CCONJ
cana-1705	70	20	future	future	ADJ
cana-1705	70	21	work	work	NOUN
cana-1705	70	22	.	.	PUNCT
cana-1705	71	1	2	2	X
cana-1705	71	2	.	.	X
cana-1705	71	3	related	relate	VERB
cana-1705	71	4	work	work	NOUN
cana-1705	71	5	a.	a.	NOUN
cana-1705	71	6	traditional	traditional	ADJ
cana-1705	71	7	traffic	traffic	NOUN
cana-1705	71	8	flow	flow	NOUN
cana-1705	71	9	prediction	prediction	NOUN
cana-1705	71	10	techniques	technique	NOUN
cana-1705	71	11	:	:	PUNCT
cana-1705	71	12	advantages	advantage	NOUN
cana-1705	71	13	and	and	CCONJ
cana-1705	71	14	disadvantages	disadvantage	VERB
cana-1705	71	15	infrastructure	infrastructure	NOUN
cana-1705	71	16	traffic	traffic	NOUN
cana-1705	71	17	prediction	prediction	NOUN
cana-1705	71	18	background	background	NOUN
cana-1705	71	19	the	the	DET
cana-1705	71	20	topic	topic	NOUN
cana-1705	71	21	of	of	ADP
cana-1705	71	22	traffic	traffic	NOUN
cana-1705	71	23	flow	flow	NOUN
cana-1705	71	24	prediction	prediction	NOUN
cana-1705	71	25	has	have	AUX
cana-1705	71	26	grown	grow	VERB
cana-1705	71	27	significantly	significantly	ADV
cana-1705	71	28	in	in	ADP
cana-1705	71	29	the	the	DET
cana-1705	71	30	last	last	ADJ
cana-1705	71	31	few	few	ADJ
cana-1705	71	32	decades	decade	NOUN
cana-1705	71	33	with	with	ADP
cana-1705	71	34	most	most	ADJ
cana-1705	71	35	conventional	conventional	ADJ
cana-1705	71	36	methods	method	NOUN
cana-1705	71	37	based	base	VERB
cana-1705	71	38	on	on	ADP
cana-1705	71	39	statistical	statistical	ADJ
cana-1705	71	40	approaches	approach	NOUN
cana-1705	71	41	.	.	PUNCT
cana-1705	72	1	traditionally	traditionally	ADV
cana-1705	72	2	,	,	PUNCT
cana-1705	72	3	traffic	traffic	NOUN
cana-1705	72	4	flow	flow	NOUN
cana-1705	72	5	prediction	prediction	NOUN
cana-1705	72	6	used	use	VERB
cana-1705	72	7	to	to	PART
cana-1705	72	8	be	be	AUX
cana-1705	72	9	done	do	VERB
cana-1705	72	10	through	through	ADP
cana-1705	72	11	methods	method	NOUN
cana-1705	72	12	such	such	ADJ
cana-1705	72	13	as	as	ADP
cana-1705	72	14	time	time	NOUN
cana-1705	72	15	series	series	NOUN
cana-1705	72	16	analysis	analysis	NOUN
cana-1705	72	17	and	and	CCONJ
cana-1705	72	18	regression	regression	NOUN
cana-1705	72	19	-	-	PUNCT
cana-1705	72	20	based	base	VERB
cana-1705	72	21	models	model	NOUN
cana-1705	72	22	which	which	PRON
cana-1705	72	23	utilizes	utilize	VERB
cana-1705	72	24	the	the	DET
cana-1705	72	25	historical	historical	ADJ
cana-1705	72	26	data	datum	NOUN
cana-1705	72	27	for	for	ADP
cana-1705	72	28	predicting	predict	VERB
cana-1705	72	29	future	future	NOUN
cana-1705	72	30	.	.	PUNCT
cana-1705	73	1	in	in	ADP
cana-1705	73	2	the	the	DET
cana-1705	73	3	field	field	NOUN
cana-1705	73	4	of	of	ADP
cana-1705	73	5	traffic	traffic	NOUN
cana-1705	73	6	prediction	prediction	NOUN
cana-1705	73	7	autoregressive	autoregressive	ADJ
cana-1705	73	8	integrated	integrated	ADJ
cana-1705	73	9	moving	move	VERB
cana-1705	73	10	average	average	ADJ
cana-1705	73	11	(	(	PUNCT
cana-1705	73	12	arima	arima	NOUN
cana-1705	73	13	)	)	PUNCT
cana-1705	73	14	models	model	NOUN
cana-1705	73	15	is	be	AUX
cana-1705	73	16	a	a	DET
cana-1705	73	17	well	well	ADV
cana-1705	73	18	known	know	VERB
cana-1705	73	19	statistical	statistical	ADJ
cana-1705	73	20	method	method	NOUN
cana-1705	73	21	for	for	ADP
cana-1705	73	22	time	time	NOUN
cana-1705	73	23	series	series	PROPN
cana-1705	73	24	data	datum	NOUN
cana-1705	73	25	which	which	PRON
cana-1705	73	26	have	have	VERB
cana-1705	73	27	linear	linear	ADJ
cana-1705	73	28	relations	relation	NOUN
cana-1705	73	29	.	.	PUNCT
cana-1705	74	1	arima	arima	NOUN
cana-1705	74	2	models	model	NOUN
cana-1705	74	3	–	–	PUNCT
cana-1705	74	4	according	accord	VERB
cana-1705	74	5	to	to	ADP
cana-1705	74	6	ahmed	ahmed	PROPN
cana-1705	74	7	and	and	CCONJ
cana-1705	74	8	cook	cook	VERB
cana-1705	74	9	(	(	PUNCT
cana-1705	74	10	1979	1979	NUM
cana-1705	74	11	)	)	PUNCT
cana-1705	74	12	,	,	PUNCT
cana-1705	74	13	these	these	DET
cana-1705	74	14	models	model	NOUN
cana-1705	74	15	need	need	VERB
cana-1705	74	16	very	very	ADV
cana-1705	74	17	low	low	ADJ
cana-1705	74	18	computational	computational	ADJ
cana-1705	74	19	power	power	NOUN
cana-1705	74	20	and	and	CCONJ
cana-1705	74	21	generate	generate	VERB
cana-1705	74	22	only	only	ADV
cana-1705	74	23	shortterm	shortterm	VERB
cana-1705	74	24	forecasts	forecast	NOUN
cana-1705	74	25	under	under	ADP
cana-1705	74	26	the	the	DET
cana-1705	74	27	hypothesis	hypothesis	NOUN
cana-1705	74	28	that	that	SCONJ
cana-1705	74	29	future	future	ADJ
cana-1705	74	30	values	value	NOUN
cana-1705	74	31	are	be	AUX
cana-1705	74	32	linear	linear	ADJ
cana-1705	74	33	combinations	combination	NOUN
cana-1705	74	34	of	of	ADP
cana-1705	74	35	past	past	ADJ
cana-1705	74	36	observation	observation	NOUN
cana-1705	74	37	.	.	PUNCT
cana-1705	75	1	one	one	NUM
cana-1705	75	2	of	of	ADP
cana-1705	75	3	the	the	DET
cana-1705	75	4	crucial	crucial	ADJ
cana-1705	75	5	limitations	limitation	NOUN
cana-1705	75	6	of	of	ADP
cana-1705	75	7	arima	arima	PROPN
cana-1705	75	8	and	and	CCONJ
cana-1705	75	9	other	other	ADJ
cana-1705	75	10	methods	method	NOUN
cana-1705	75	11	is	be	AUX
cana-1705	75	12	their	their	PRON
cana-1705	75	13	non	non	ADJ
cana-1705	75	14	-	-	ADJ
cana-1705	75	15	linearity	linearity	ADJ
cana-1705	75	16	to	to	PART
cana-1705	75	17	model	model	VERB
cana-1705	75	18	traffic	traffic	NOUN
cana-1705	75	19	data	datum	NOUN
cana-1705	75	20	,	,	PUNCT
cana-1705	75	21	especially	especially	ADV
cana-1705	75	22	in	in	ADP
cana-1705	75	23	complex	complex	ADJ
cana-1705	75	24	metropolitan	metropolitan	ADJ
cana-1705	75	25	areas	area	NOUN
cana-1705	75	26	full	full	ADJ
cana-1705	75	27	of	of	ADP
cana-1705	75	28	traffic	traffic	NOUN
cana-1705	75	29	jams	jam	NOUN
cana-1705	75	30	.	.	PUNCT
cana-1705	76	1	these	these	DET
cana-1705	76	2	models	model	NOUN
cana-1705	76	3	are	be	AUX
cana-1705	76	4	also	also	ADV
cana-1705	76	5	inflexible	inflexible	ADJ
cana-1705	76	6	regarding	regard	VERB
cana-1705	76	7	abrupt	abrupt	ADJ
cana-1705	76	8	changes	change	NOUN
cana-1705	76	9	in	in	ADP
cana-1705	76	10	the	the	DET
cana-1705	76	11	traffic	traffic	NOUN
cana-1705	76	12	flow	flow	NOUN
cana-1705	76	13	(	(	PUNCT
cana-1705	76	14	for	for	ADP
cana-1705	76	15	example	example	NOUN
cana-1705	76	16	because	because	SCONJ
cana-1705	76	17	of	of	ADP
cana-1705	76	18	crashes	crash	NOUN
cana-1705	76	19	or	or	CCONJ
cana-1705	76	20	road	road	NOUN
cana-1705	76	21	detours	detour	NOUN
cana-1705	76	22	)	)	PUNCT
cana-1705	76	23	,	,	PUNCT
cana-1705	76	24	which	which	PRON
cana-1705	76	25	makes	make	VERB
cana-1705	76	26	using	use	VERB
cana-1705	76	27	them	they	PRON
cana-1705	76	28	unfeasible	unfeasible	ADJ
cana-1705	76	29	for	for	ADP
cana-1705	76	30	real	real	ADJ
cana-1705	76	31	-	-	PUNCT
cana-1705	76	32	time	time	NOUN
cana-1705	76	33	traffic	traffic	NOUN
cana-1705	76	34	applications	application	NOUN
cana-1705	76	35	where	where	SCONJ
cana-1705	76	36	conditions	condition	NOUN
cana-1705	76	37	continuously	continuously	ADV
cana-1705	76	38	evolve	evolve	VERB
cana-1705	76	39	.	.	PUNCT
cana-1705	77	1	besides	besides	SCONJ
cana-1705	77	2	that	that	PRON
cana-1705	77	3	,	,	PUNCT
cana-1705	77	4	the	the	DET
cana-1705	77	5	arima	arima	PROPN
cana-1705	77	6	model	model	NOUN
cana-1705	77	7	needs	need	VERB
cana-1705	77	8	a	a	DET
cana-1705	77	9	lot	lot	NOUN
cana-1705	77	10	of	of	ADP
cana-1705	77	11	parameter	parameter	NOUN
cana-1705	77	12	setting	setting	NOUN
cana-1705	77	13	and	and	CCONJ
cana-1705	77	14	is	be	AUX
cana-1705	77	15	easy	easy	ADJ
cana-1705	77	16	to	to	PART
cana-1705	77	17	overfit	overfit	VERB
cana-1705	77	18	for	for	ADP
cana-1705	77	19	complex	complex	ADJ
cana-1705	77	20	traffic	traffic	NOUN
cana-1705	77	21	systems	system	NOUN
cana-1705	77	22	.	.	PUNCT
cana-1705	78	1	one	one	NUM
cana-1705	78	2	more	more	ADV
cana-1705	78	3	standard	standard	ADJ
cana-1705	78	4	way	way	NOUN
cana-1705	78	5	is	be	AUX
cana-1705	78	6	the	the	DET
cana-1705	78	7	use	use	NOUN
cana-1705	78	8	of	of	ADP
cana-1705	78	9	machine	machine	NOUN
cana-1705	78	10	learning	learning	NOUN
cana-1705	78	11	that	that	PRON
cana-1705	78	12	includes	include	VERB
cana-1705	78	13	technology	technology	NOUN
cana-1705	78	14	like	like	ADP
cana-1705	78	15	support	support	NOUN
cana-1705	78	16	vector	vector	NOUN
cana-1705	78	17	machines	machine	NOUN
cana-1705	78	18	(	(	PUNCT
cana-1705	78	19	svm	svm	PROPN
cana-1705	78	20	)	)	PUNCT
cana-1705	78	21	,	,	PUNCT
cana-1705	78	22	decision	decision	NOUN
cana-1705	78	23	trees	tree	NOUN
cana-1705	78	24	,	,	PUNCT
cana-1705	78	25	k	k	NOUN
cana-1705	78	26	-	-	PUNCT
cana-1705	78	27	nearest	near	ADJ
cana-1705	78	28	neighbours	neighbour	NOUN
cana-1705	78	29	(	(	PUNCT
cana-1705	78	30	knn	knn	PROPN
cana-1705	78	31	)	)	PUNCT
cana-1705	78	32	.	.	PUNCT
cana-1705	79	1	these	these	DET
cana-1705	79	2	approaches	approach	NOUN
cana-1705	79	3	have	have	AUX
cana-1705	79	4	been	be	AUX
cana-1705	79	5	demonstrated	demonstrate	VERB
cana-1705	79	6	to	to	PART
cana-1705	79	7	be	be	AUX
cana-1705	79	8	better	well	ADJ
cana-1705	79	9	than	than	ADP
cana-1705	79	10	more	more	ADV
cana-1705	79	11	sophisticated	sophisticated	ADJ
cana-1705	79	12	statistical	statistical	ADJ
cana-1705	79	13	models	model	NOUN
cana-1705	79	14	in	in	ADP
cana-1705	79	15	some	some	DET
cana-1705	79	16	cases	case	NOUN
cana-1705	79	17	by	by	ADP
cana-1705	79	18	capturing	capture	VERB
cana-1705	79	19	higher	high	ADJ
cana-1705	79	20	-	-	PUNCT
cana-1705	79	21	order	order	NOUN
cana-1705	79	22	traffic	traffic	NOUN
cana-1705	79	23	patterns	pattern	NOUN
cana-1705	79	24	.	.	PUNCT
cana-1705	80	1	a	a	DET
cana-1705	80	2	notable	notable	ADJ
cana-1705	80	3	study	study	NOUN
cana-1705	80	4	by	by	ADP
cana-1705	80	5	wu	wu	PROPN
cana-1705	80	6	et	et	PROPN
cana-1705	80	7	al	al	PROPN
cana-1705	80	8	.	.	PROPN
cana-1705	80	9	schabenberger	schabenberger	NOUN
cana-1705	80	10	and	and	CCONJ
cana-1705	80	11	gotway	gotway	PROPN
cana-1705	80	12	(	(	PUNCT
cana-1705	80	13	2001	2001	NUM
cana-1705	80	14	)	)	PUNCT
cana-1705	80	15	proposed	propose	VERB
cana-1705	80	16	that	that	SCONJ
cana-1705	80	17	the	the	DET
cana-1705	80	18	topographical	topographical	ADJ
cana-1705	80	19	property	property	NOUN
cana-1705	80	20	of	of	ADP
cana-1705	80	21	svm	svm	PROPN
cana-1705	80	22	could	could	AUX
cana-1705	80	23	predict	predict	VERB
cana-1705	80	24	traffic	traffic	NOUN
cana-1705	80	25	with	with	ADP
cana-1705	80	26	both	both	CCONJ
cana-1705	80	27	linear	linear	ADJ
cana-1705	80	28	and	and	CCONJ
cana-1705	80	29	nonlinear	nonlinear	ADJ
cana-1705	80	30	relationship	relationship	NOUN
cana-1705	80	31	better	well	ADJ
cana-1705	80	32	than	than	ADP
cana-1705	80	33	arima	arima	NOUN
cana-1705	80	34	models	model	NOUN
cana-1705	80	35	.	.	PUNCT
cana-1705	81	1	6	6	NUM
cana-1705	81	2	mass	mass	NOUN
cana-1705	81	3	prediction	prediction	NOUN
cana-1705	81	4	performance	performance	NOUN
cana-1705	81	5	on	on	ADP
cana-1705	81	6	this	this	DET
cana-1705	81	7	model	model	NOUN
cana-1705	81	8	it	it	PRON
cana-1705	81	9	also	also	ADV
cana-1705	81	10	found	find	VERB
cana-1705	81	11	new	new	ADJ
cana-1705	81	12	techniques	technique	NOUN
cana-1705	81	13	reported	report	VERB
cana-1705	81	14	oh	oh	INTJ
cana-1705	81	15	et	et	NOUN
cana-1705	81	16	al	al	PROPN
cana-1705	81	17	.	.	PUNCT
cana-1705	82	1	however	however	ADV
cana-1705	82	2	,	,	PUNCT
cana-1705	82	3	smos	smos	NOUN
cana-1705	82	4	and	and	CCONJ
cana-1705	82	5	many	many	ADJ
cana-1705	82	6	other	other	ADJ
cana-1705	82	7	classical	classical	ADJ
cana-1705	82	8	machine	machine	NOUN
cana-1705	82	9	learning	learning	NOUN
cana-1705	82	10	approaches	approach	NOUN
cana-1705	82	11	work	work	VERB
cana-1705	82	12	through	through	ADP
cana-1705	82	13	hand	hand	NOUN
cana-1705	82	14	codded	cod	VERB
cana-1705	82	15	features	feature	NOUN
cana-1705	82	16	and	and	CCONJ
cana-1705	82	17	do	do	AUX
cana-1705	82	18	not	not	PART
cana-1705	82	19	perform	perform	VERB
cana-1705	82	20	well	well	ADV
cana-1705	82	21	on	on	ADP
cana-1705	82	22	spatial	spatial	ADJ
cana-1705	82	23	correlations	correlation	NOUN
cana-1705	82	24	in	in	ADP
cana-1705	82	25	traffic	traffic	NOUN
cana-1705	82	26	flow	flow	NOUN
cana-1705	82	27	data	datum	NOUN
cana-1705	82	28	.	.	PUNCT
cana-1705	83	1	as	as	ADP
cana-1705	83	2	a	a	DET
cana-1705	83	3	result	result	NOUN
cana-1705	83	4	,	,	PUNCT
cana-1705	83	5	they	they	PRON
cana-1705	83	6	may	may	AUX
cana-1705	83	7	be	be	AUX
cana-1705	83	8	not	not	PART
cana-1705	83	9	suitable	suitable	ADJ
cana-1705	83	10	for	for	ADP
cana-1705	83	11	making	make	VERB
cana-1705	83	12	real	real	ADJ
cana-1705	83	13	-	-	PUNCT
cana-1705	83	14	time	time	NOUN
cana-1705	83	15	traffic	traffic	NOUN
cana-1705	83	16	prediction	prediction	NOUN
cana-1705	83	17	when	when	SCONJ
cana-1705	83	18	the	the	DET
cana-1705	83	19	relationships	relationship	NOUN
cana-1705	83	20	amongst	amongst	ADP
cana-1705	83	21	historical	historical	ADJ
cana-1705	83	22	,	,	PUNCT
cana-1705	83	23	current	current	ADJ
cana-1705	83	24	and	and	CCONJ
cana-1705	83	25	future	future	ADJ
cana-1705	83	26	traffic	traffic	NOUN
cana-1705	83	27	conditions	condition	NOUN
cana-1705	83	28	are	be	AUX
cana-1705	83	29	important	important	ADJ
cana-1705	83	30	factors	factor	NOUN
cana-1705	83	31	.	.	PUNCT
cana-1705	84	1	b.	b.	PROPN
cana-1705	84	2	appearing	appear	VERB
cana-1705	84	3	of	of	ADP
cana-1705	84	4	neural	neural	ADJ
cana-1705	84	5	networks	network	NOUN
cana-1705	84	6	for	for	ADP
cana-1705	84	7	traffic	traffic	NOUN
cana-1705	84	8	flow	flow	NOUN
cana-1705	84	9	prediction	prediction	NOUN
cana-1705	84	10	traditional	traditional	ADJ
cana-1705	84	11	traffic	traffic	NOUN
cana-1705	84	12	prediction	prediction	NOUN
cana-1705	84	13	methods	method	NOUN
cana-1705	84	14	were	be	AUX
cana-1705	84	15	limited	limit	VERB
cana-1705	84	16	,	,	PUNCT
cana-1705	84	17	allowing	allow	VERB
cana-1705	84	18	the	the	DET
cana-1705	84	19	development	development	NOUN
cana-1705	84	20	of	of	ADP
cana-1705	84	21	neural	neural	ADJ
cana-1705	84	22	networks	network	NOUN
cana-1705	84	23	applied	apply	VERB
cana-1705	84	24	to	to	ADP
cana-1705	84	25	model	model	NOUN
cana-1705	84	26	complex	complex	NOUN
cana-1705	84	27	,	,	PUNCT
cana-1705	84	28	nonlinear	nonlinear	ADJ
cana-1705	84	29	relationships	relationship	NOUN
cana-1705	84	30	between	between	ADP
cana-1705	84	31	input	input	NOUN
cana-1705	84	32	and	and	CCONJ
cana-1705	84	33	output	output	NOUN
cana-1705	84	34	data	datum	NOUN
cana-1705	84	35	.	.	PUNCT
cana-1705	85	1	the	the	DET
cana-1705	85	2	initial	initial	ADJ
cana-1705	85	3	research	research	NOUN
cana-1705	85	4	efforts	effort	NOUN
cana-1705	85	5	,	,	PUNCT
cana-1705	85	6	was	be	AUX
cana-1705	85	7	on	on	ADP
cana-1705	85	8	training	train	VERB
cana-1705	85	9	feedforward	feedforward	NOUN
cana-1705	85	10	neural	neural	ADJ
cana-1705	85	11	networks	network	NOUN
cana-1705	85	12	such	such	ADJ
cana-1705	85	13	as	as	ADP
cana-1705	85	14	multilayer	multilayer	ADJ
cana-1705	85	15	perceptrons	perceptron	NOUN
cana-1705	85	16	(	(	PUNCT
cana-1705	85	17	mlps	mlp	NOUN
cana-1705	85	18	)	)	PUNCT
cana-1705	85	19	and	and	CCONJ
cana-1705	85	20	these	these	DET
cana-1705	85	21	models	model	NOUN
cana-1705	85	22	showed	show	VERB
cana-1705	85	23	top	top	ADJ
cana-1705	85	24	-	-	PUNCT
cana-1705	85	25	level	level	NOUN
cana-1705	85	26	performance	performance	NOUN
cana-1705	85	27	in	in	ADP
cana-1705	85	28	comparison	comparison	NOUN
cana-1705	85	29	to	to	ADP
cana-1705	85	30	statistical	statistical	ADJ
cana-1705	85	31	/	/	SYM
cana-1705	85	32	traditional	traditional	ADJ
cana-1705	85	33	machine	machine	NOUN
cana-1705	85	34	communications	communication	NOUN
cana-1705	85	35	on	on	ADP
cana-1705	85	36	applied	apply	VERB
cana-1705	85	37	nonlinear	nonlinear	ADJ
cana-1705	85	38	analysis	analysis	NOUN
cana-1705	85	39	issn	issn	NOUN
cana-1705	85	40	:	:	PUNCT
cana-1705	85	41	1074	1074	NUM
cana-1705	85	42	-	-	PUNCT
cana-1705	85	43	133x	133x	NUM
cana-1705	85	44	vol	vol	NOUN
cana-1705	85	45	32	32	NUM
cana-1705	85	46	no	no	NOUN
cana-1705	85	47	.	.	NOUN
cana-1705	85	48	2	2	NUM
cana-1705	85	49	(	(	PUNCT
cana-1705	85	50	2025	2025	NUM
cana-1705	85	51	)	)	PUNCT
cana-1705	85	52	6	6	NUM
cana-1705	85	53	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	85	54	learning	learn	VERB
cana-1705	85	55	model	model	NOUN
cana-1705	85	56	because	because	SCONJ
cana-1705	85	57	its	its	PRON
cana-1705	85	58	capability	capability	NOUN
cana-1705	85	59	to	to	PART
cana-1705	85	60	learn	learn	VERB
cana-1705	85	61	a	a	DET
cana-1705	85	62	simple	simple	ADJ
cana-1705	85	63	or	or	CCONJ
cana-1705	85	64	disadvantages	disadvantage	VERB
cana-1705	85	65	non	non	ADJ
cana-1705	85	66	-	-	ADJ
cana-1705	85	67	linear	linear	ADJ
cana-1705	85	68	pattern	pattern	NOUN
cana-1705	85	69	.	.	PUNCT
cana-1705	86	1	researchers	researcher	NOUN
cana-1705	86	2	like	like	ADP
cana-1705	86	3	vlahogianni	vlahogianni	PROPN
cana-1705	86	4	et	et	NOUN
cana-1705	86	5	al.[17	al.[17	PROPN
cana-1705	86	6	]	]	PUNCT
cana-1705	86	7	(	(	PUNCT
cana-1705	86	8	2005	2005	NUM
cana-1705	86	9	)	)	PUNCT
cana-1705	86	10	also	also	ADV
cana-1705	86	11	investigated	investigate	VERB
cana-1705	86	12	the	the	DET
cana-1705	86	13	utilization	utilization	NOUN
cana-1705	86	14	of	of	ADP
cana-1705	86	15	multilayer	multilayer	ADJ
cana-1705	86	16	perceptrons	perceptron	NOUN
cana-1705	86	17	(	(	PUNCT
cana-1705	86	18	mlps	mlp	NOUN
cana-1705	86	19	)	)	PUNCT
cana-1705	86	20	to	to	PART
cana-1705	86	21	predict	predict	VERB
cana-1705	86	22	short	short	ADJ
cana-1705	86	23	term	term	NOUN
cana-1705	86	24	traffic	traffic	NOUN
cana-1705	86	25	flow	flow	NOUN
cana-1705	86	26	using	use	VERB
cana-1705	86	27	neural	neural	ADJ
cana-1705	86	28	network	network	NOUN
cana-1705	86	29	and	and	CCONJ
cana-1705	86	30	demonstrated	demonstrate	VERB
cana-1705	86	31	that	that	SCONJ
cana-1705	86	32	the	the	DET
cana-1705	86	33	proposed	propose	VERB
cana-1705	86	34	anns	anns	NOUN
cana-1705	86	35	indeed	indeed	ADV
cana-1705	86	36	outperform	outperform	VERB
cana-1705	86	37	traditional	traditional	ADJ
cana-1705	86	38	models	model	NOUN
cana-1705	86	39	in	in	ADP
cana-1705	86	40	predictive	predictive	ADJ
cana-1705	86	41	performance	performance	NOUN
cana-1705	86	42	.	.	PUNCT
cana-1705	87	1	however	however	ADV
cana-1705	87	2	,	,	PUNCT
cana-1705	87	3	as	as	ADV
cana-1705	87	4	great	great	ADJ
cana-1705	87	5	as	as	ADP
cana-1705	87	6	feedforward	feedforward	ADJ
cana-1705	87	7	neural	neural	ADJ
cana-1705	87	8	networks	network	NOUN
cana-1705	87	9	are	be	AUX
cana-1705	87	10	at	at	ADP
cana-1705	87	11	many	many	ADJ
cana-1705	87	12	of	of	ADP
cana-1705	87	13	these	these	DET
cana-1705	87	14	tasks	task	NOUN
cana-1705	87	15	,	,	PUNCT
cana-1705	87	16	they	they	PRON
cana-1705	87	17	share	share	VERB
cana-1705	87	18	a	a	DET
cana-1705	87	19	significant	significant	ADJ
cana-1705	87	20	flaw	flaw	NOUN
cana-1705	87	21	:	:	PUNCT
cana-1705	87	22	they	they	PRON
cana-1705	87	23	do	do	AUX
cana-1705	87	24	n't	not	PART
cana-1705	87	25	model	model	VERB
cana-1705	87	26	temporal	temporal	ADJ
cana-1705	87	27	dependencies	dependency	NOUN
cana-1705	87	28	.	.	PUNCT
cana-1705	88	1	traffic	traffic	NOUN
cana-1705	88	2	flow	flow	NOUN
cana-1705	88	3	data	datum	NOUN
cana-1705	88	4	is	be	AUX
cana-1705	88	5	sequential	sequential	ADJ
cana-1705	88	6	by	by	ADP
cana-1705	88	7	nature	nature	NOUN
cana-1705	88	8	—	—	PUNCT
cana-1705	88	9	old	old	ADJ
cana-1705	88	10	values	value	NOUN
cana-1705	88	11	affect	affect	VERB
cana-1705	88	12	new	new	ADJ
cana-1705	88	13	states	state	NOUN
cana-1705	88	14	.	.	PUNCT
cana-1705	89	1	this	this	PRON
cana-1705	89	2	is	be	AUX
cana-1705	89	3	not	not	PART
cana-1705	89	4	a	a	DET
cana-1705	89	5	suitable	suitable	ADJ
cana-1705	89	6	model	model	NOUN
cana-1705	89	7	architecture	architecture	NOUN
cana-1705	89	8	for	for	ADP
cana-1705	89	9	the	the	DET
cana-1705	89	10	modelling	modelling	NOUN
cana-1705	89	11	tasks	task	NOUN
cana-1705	89	12	such	such	ADJ
cana-1705	89	13	as	as	ADP
cana-1705	89	14	traffic	traffic	NOUN
cana-1705	89	15	prediction	prediction	NOUN
cana-1705	89	16	,	,	PUNCT
cana-1705	89	17	where	where	SCONJ
cana-1705	89	18	we	we	PRON
cana-1705	89	19	need	need	VERB
cana-1705	89	20	to	to	PART
cana-1705	89	21	recall	recall	VERB
cana-1705	89	22	past	past	ADJ
cana-1705	89	23	conditions	condition	NOUN
cana-1705	89	24	.	.	PUNCT
cana-1705	90	1	standard	standard	ADJ
cana-1705	90	2	mlp	mlp	PROPN
cana-1705	90	3	just	just	ADV
cana-1705	90	4	feed	feed	VERB
cana-1705	90	5	everything	everything	PRON
cana-1705	90	6	into	into	ADP
cana-1705	90	7	the	the	DET
cana-1705	90	8	network	network	NOUN
cana-1705	90	9	with	with	ADP
cana-1705	90	10	no	no	DET
cana-1705	90	11	history	history	NOUN
cana-1705	90	12	involved	involve	VERB
cana-1705	90	13	in	in	ADP
cana-1705	90	14	the	the	DET
cana-1705	90	15	process	process	NOUN
cana-1705	90	16	.	.	PUNCT
cana-1705	91	1	to	to	PART
cana-1705	91	2	overcome	overcome	VERB
cana-1705	91	3	this	this	DET
cana-1705	91	4	limitation	limitation	NOUN
cana-1705	91	5	,	,	PUNCT
cana-1705	91	6	as	as	SCONJ
cana-1705	91	7	a	a	DET
cana-1705	91	8	solution	solution	NOUN
cana-1705	91	9	came	come	VERB
cana-1705	91	10	out	out	ADP
cana-1705	91	11	with	with	ADP
cana-1705	91	12	recurrent	recurrent	ADJ
cana-1705	91	13	neural	neural	ADJ
cana-1705	91	14	networks(rnns	networks(rnns	PROPN
cana-1705	91	15	)	)	PUNCT
cana-1705	91	16	came	come	VERB
cana-1705	91	17	.	.	PUNCT
cana-1705	92	1	indeed	indeed	ADV
cana-1705	92	2	,	,	PUNCT
cana-1705	92	3	unlike	unlike	ADP
cana-1705	92	4	the	the	DET
cana-1705	92	5	feedforward	feedforward	NOUN
cana-1705	92	6	networks	network	NOUN
cana-1705	92	7	,	,	PUNCT
cana-1705	92	8	rnns	rnns	NOUN
cana-1705	92	9	possess	possess	NOUN
cana-1705	92	10	connections	connection	NOUN
cana-1705	92	11	forming	form	VERB
cana-1705	92	12	directed	direct	VERB
cana-1705	92	13	cycles	cycle	NOUN
cana-1705	92	14	in	in	ADP
cana-1705	92	15	such	such	DET
cana-1705	92	16	a	a	DET
cana-1705	92	17	way	way	NOUN
cana-1705	92	18	to	to	PART
cana-1705	92	19	have	have	VERB
cana-1705	92	20	information	information	NOUN
cana-1705	92	21	about	about	ADP
cana-1705	92	22	previous	previous	ADJ
cana-1705	92	23	inputs	input	NOUN
cana-1705	92	24	stored	store	VERB
cana-1705	92	25	in	in	ADP
cana-1705	92	26	their	their	PRON
cana-1705	92	27	hidden	hide	VERB
cana-1705	92	28	state	state	NOUN
cana-1705	92	29	.	.	PUNCT
cana-1705	93	1	this	this	DET
cana-1705	93	2	ability	ability	NOUN
cana-1705	93	3	helps	help	VERB
cana-1705	93	4	rnns	rnn	NOUN
cana-1705	93	5	to	to	PART
cana-1705	93	6	understand	understand	VERB
cana-1705	93	7	sequences	sequence	NOUN
cana-1705	93	8	in	in	ADP
cana-1705	93	9	the	the	DET
cana-1705	93	10	time	time	NOUN
cana-1705	93	11	series	series	PROPN
cana-1705	93	12	data	data	PROPN
cana-1705	93	13	.	.	PUNCT
cana-1705	94	1	quite	quite	DET
cana-1705	94	2	a	a	DET
cana-1705	94	3	few	few	ADJ
cana-1705	94	4	works	work	NOUN
cana-1705	94	5	apply	apply	VERB
cana-1705	94	6	rnns	rnn	NOUN
cana-1705	94	7	in	in	ADP
cana-1705	94	8	traffic	traffic	NOUN
cana-1705	94	9	flow	flow	NOUN
cana-1705	94	10	prediction	prediction	NOUN
cana-1705	94	11	[	[	X
cana-1705	94	12	23	23	NUM
cana-1705	94	13	]	]	PUNCT
cana-1705	94	14	,	,	PUNCT
cana-1705	94	15	and	and	CCONJ
cana-1705	94	16	get	get	VERB
cana-1705	94	17	significant	significant	ADJ
cana-1705	94	18	results	result	NOUN
cana-1705	94	19	.	.	PUNCT
cana-1705	95	1	for	for	ADP
cana-1705	95	2	instance	instance	NOUN
cana-1705	95	3	,	,	PUNCT
cana-1705	95	4	ma	ma	PROPN
cana-1705	95	5	et	et	PROPN
cana-1705	95	6	al	al	PROPN
cana-1705	95	7	.	.	PROPN
cana-1705	95	8	recall	recall	VERB
cana-1705	95	9	that	that	SCONJ
cana-1705	95	10	zheng	zheng	PROPN
cana-1705	95	11	et	et	PROPN
cana-1705	95	12	al	al	PROPN
cana-1705	95	13	.	.	PUNCT
cana-1705	96	1	[	[	X
cana-1705	96	2	2	2	NUM
cana-1705	96	3	]	]	PUNCT
cana-1705	96	4	showed	show	VERB
cana-1705	96	5	the	the	DET
cana-1705	96	6	capability	capability	NOUN
cana-1705	96	7	of	of	ADP
cana-1705	96	8	rnn	rnn	NOUN
cana-1705	96	9	in	in	ADP
cana-1705	96	10	learning	learn	VERB
cana-1705	96	11	temporal	temporal	ADJ
cana-1705	96	12	dependencies	dependency	NOUN
cana-1705	96	13	in	in	ADP
cana-1705	96	14	traffic	traffic	NOUN
cana-1705	96	15	data	datum	NOUN
cana-1705	96	16	and	and	CCONJ
cana-1705	96	17	significantly	significantly	ADV
cana-1705	96	18	surpassing	surpass	VERB
cana-1705	96	19	mlps	mlp	NOUN
cana-1705	96	20	and	and	CCONJ
cana-1705	96	21	svms	svms	VERB
cana-1705	96	22	in	in	ADP
cana-1705	96	23	prediction	prediction	NOUN
cana-1705	96	24	accuracy	accuracy	NOUN
cana-1705	96	25	references	reference	NOUN
cana-1705	96	26	(	(	PUNCT
cana-1705	96	27	2015	2015	NUM
cana-1705	96	28	)	)	PUNCT
cana-1705	96	29	however	however	ADV
cana-1705	96	30	,	,	PUNCT
cana-1705	96	31	when	when	SCONJ
cana-1705	96	32	standard	standard	ADJ
cana-1705	96	33	rnn	rnn	PROPN
cana-1705	96	34	is	be	AUX
cana-1705	96	35	used	use	VERB
cana-1705	96	36	,	,	PUNCT
cana-1705	96	37	the	the	DET
cana-1705	96	38	vanishing	vanish	VERB
cana-1705	96	39	and	and	CCONJ
cana-1705	96	40	exploding	explode	VERB
cana-1705	96	41	gradients	gradient	NOUN
cana-1705	96	42	problems	problem	NOUN
cana-1705	96	43	occur	occur	VERB
cana-1705	96	44	making	make	VERB
cana-1705	96	45	it	it	PRON
cana-1705	96	46	impossible	impossible	ADJ
cana-1705	96	47	to	to	PART
cana-1705	96	48	learn	learn	VERB
cana-1705	96	49	long	long	ADJ
cana-1705	96	50	-	-	PUNCT
cana-1705	96	51	term	term	NOUN
cana-1705	96	52	dependencies	dependency	NOUN
cana-1705	96	53	.	.	PUNCT
cana-1705	97	1	this	this	PRON
cana-1705	97	2	is	be	AUX
cana-1705	97	3	a	a	DET
cana-1705	97	4	significant	significant	ADJ
cana-1705	97	5	problem	problem	NOUN
cana-1705	97	6	in	in	ADP
cana-1705	97	7	traffic	traffic	NOUN
cana-1705	97	8	flow	flow	NOUN
cana-1705	97	9	prediction	prediction	NOUN
cana-1705	97	10	since	since	SCONJ
cana-1705	97	11	both	both	CCONJ
cana-1705	97	12	the	the	DET
cana-1705	97	13	short	short	ADJ
cana-1705	97	14	-	-	PUNCT
cana-1705	97	15	term	term	NOUN
cana-1705	97	16	and	and	CCONJ
cana-1705	97	17	longterm	longterm	NOUN
cana-1705	97	18	dependencies	dependency	NOUN
cana-1705	97	19	are	be	AUX
cana-1705	97	20	very	very	ADV
cana-1705	97	21	important	important	ADJ
cana-1705	97	22	for	for	ADP
cana-1705	97	23	accurate	accurate	ADJ
cana-1705	97	24	forecasting	forecasting	NOUN
cana-1705	97	25	.	.	PUNCT
cana-1705	98	1	c.	c.	PROPN
cana-1705	98	2	lstm	lstm	PROPN
cana-1705	98	3	networks	network	NOUN
cana-1705	98	4	:	:	PUNCT
cana-1705	98	5	start	start	NOUN
cana-1705	98	6	of	of	ADP
cana-1705	98	7	traffic	traffic	NOUN
cana-1705	98	8	flow	flow	NOUN
cana-1705	98	9	prediction	prediction	NOUN
cana-1705	98	10	in	in	ADP
cana-1705	98	11	an	an	DET
cana-1705	98	12	effort	effort	NOUN
cana-1705	98	13	to	to	PART
cana-1705	98	14	address	address	VERB
cana-1705	98	15	the	the	DET
cana-1705	98	16	latter	latter	ADJ
cana-1705	98	17	,	,	PUNCT
cana-1705	98	18	and	and	CCONJ
cana-1705	98	19	further	far	ADV
cana-1705	98	20	eliminate	eliminate	VERB
cana-1705	98	21	some	some	DET
cana-1705	98	22	other	other	ADJ
cana-1705	98	23	limitations	limitation	NOUN
cana-1705	98	24	of	of	ADP
cana-1705	98	25	vanilla	vanilla	NOUN
cana-1705	98	26	rnns	rnn	NOUN
cana-1705	98	27	,	,	PUNCT
cana-1705	98	28	hochreiter	hochreiter	PROPN
cana-1705	98	29	&	&	CCONJ
cana-1705	98	30	schmidhuber	schmidhuber	PROPN
cana-1705	98	31	(	(	PUNCT
cana-1705	98	32	1997	1997	NUM
cana-1705	98	33	)	)	PUNCT
cana-1705	98	34	introduced	introduce	VERB
cana-1705	98	35	lstm	lstm	NOUN
cana-1705	98	36	networks	network	NOUN
cana-1705	98	37	a	a	DET
cana-1705	98	38	special	special	ADJ
cana-1705	98	39	kind	kind	NOUN
cana-1705	98	40	of	of	ADP
cana-1705	98	41	rnns	rnns	NOUN
cana-1705	98	42	.	.	PUNCT
cana-1705	99	1	the	the	DET
cana-1705	99	2	magic	magic	NOUN
cana-1705	99	3	of	of	ADP
cana-1705	99	4	lstms	lstms	ADJ
cana-1705	99	5	lstms	lstms	NOUN
cana-1705	99	6	solve	solve	VERB
cana-1705	99	7	the	the	DET
cana-1705	99	8	vanishing	vanish	VERB
cana-1705	99	9	gradient	gradient	NOUN
cana-1705	99	10	problem	problem	NOUN
cana-1705	99	11	by	by	ADP
cana-1705	99	12	using	use	VERB
cana-1705	99	13	memory	memory	NOUN
cana-1705	99	14	cells	cell	NOUN
cana-1705	99	15	and	and	CCONJ
cana-1705	99	16	gates	gate	NOUN
cana-1705	99	17	that	that	PRON
cana-1705	99	18	let	let	VERB
cana-1705	99	19	them	they	PRON
cana-1705	99	20	keep	keep	VERB
cana-1705	99	21	or	or	CCONJ
cana-1705	99	22	throw	throw	VERB
cana-1705	99	23	away	away	ADV
cana-1705	99	24	information	information	NOUN
cana-1705	99	25	over	over	ADP
cana-1705	99	26	many	many	ADJ
cana-1705	99	27	time	time	NOUN
cana-1705	99	28	steps	step	NOUN
cana-1705	99	29	.	.	PUNCT
cana-1705	100	1	this	this	PRON
cana-1705	100	2	makes	make	VERB
cana-1705	100	3	lstms	lstms	ADJ
cana-1705	100	4	very	very	ADV
cana-1705	100	5	suitable	suitable	ADJ
cana-1705	100	6	for	for	ADP
cana-1705	100	7	traffic	traffic	NOUN
cana-1705	100	8	flow	flow	NOUN
cana-1705	100	9	prediction	prediction	NOUN
cana-1705	100	10	as	as	SCONJ
cana-1705	100	11	traffic	traffic	NOUN
cana-1705	100	12	flow	flow	NOUN
cana-1705	100	13	can	can	AUX
cana-1705	100	14	depend	depend	VERB
cana-1705	100	15	a	a	DET
cana-1705	100	16	lot	lot	NOUN
cana-1705	100	17	on	on	ADP
cana-1705	100	18	events	event	NOUN
cana-1705	100	19	that	that	PRON
cana-1705	100	20	happened	happen	VERB
cana-1705	100	21	hours	hour	NOUN
cana-1705	100	22	,	,	PUNCT
cana-1705	100	23	or	or	CCONJ
cana-1705	100	24	even	even	ADV
cana-1705	100	25	days	day	NOUN
cana-1705	100	26	earlier	early	ADV
cana-1705	100	27	.	.	PUNCT
cana-1705	101	1	given	give	VERB
cana-1705	101	2	their	their	PRON
cana-1705	101	3	capability	capability	NOUN
cana-1705	101	4	of	of	ADP
cana-1705	101	5	capturing	capture	VERB
cana-1705	101	6	intricate	intricate	ADJ
cana-1705	101	7	temporal	temporal	ADJ
cana-1705	101	8	dynamics	dynamic	NOUN
cana-1705	101	9	,	,	PUNCT
cana-1705	101	10	lstm	lstm	ADJ
cana-1705	101	11	networks	network	NOUN
cana-1705	101	12	have	have	AUX
cana-1705	101	13	been	be	AUX
cana-1705	101	14	applied	apply	VERB
cana-1705	101	15	for	for	ADP
cana-1705	101	16	traffic	traffic	NOUN
cana-1705	101	17	prediction	prediction	NOUN
cana-1705	101	18	in	in	ADP
cana-1705	101	19	an	an	DET
cana-1705	101	20	ever	ever	ADV
cana-1705	101	21	-	-	PUNCT
cana-1705	101	22	increasing	increase	VERB
cana-1705	101	23	volume	volume	NOUN
cana-1705	101	24	of	of	ADP
cana-1705	101	25	literature	literature	NOUN
cana-1705	101	26	.	.	PUNCT
cana-1705	102	1	for	for	ADP
cana-1705	102	2	example	example	NOUN
cana-1705	102	3	,	,	PUNCT
cana-1705	102	4	zhang	zhang	PROPN
cana-1705	102	5	et	et	PROPN
cana-1705	102	6	al	al	PROPN
cana-1705	102	7	.	.	PROPN
cana-1705	103	1	(	(	PUNCT
cana-1705	103	2	2017	2017	NUM
cana-1705	103	3	)	)	PUNCT
cana-1705	103	4	proposed	propose	VERB
cana-1705	103	5	a	a	DET
cana-1705	103	6	traffic	traffic	NOUN
cana-1705	103	7	forecasting	forecasting	NOUN
cana-1705	103	8	model	model	NOUN
cana-1705	103	9	with	with	ADP
cana-1705	103	10	lstm	lstm	PROPN
cana-1705	103	11	,	,	PUNCT
cana-1705	103	12	which	which	PRON
cana-1705	103	13	showed	show	VERB
cana-1705	103	14	advantages	advantage	NOUN
cana-1705	103	15	in	in	ADP
cana-1705	103	16	both	both	CCONJ
cana-1705	103	17	predictive	predictive	ADJ
cana-1705	103	18	efficiency	efficiency	NOUN
cana-1705	103	19	and	and	CCONJ
cana-1705	103	20	robustness	robustness	NOUN
cana-1705	103	21	compared	compare	VERB
cana-1705	103	22	to	to	ADP
cana-1705	103	23	generic	generic	ADJ
cana-1705	103	24	machine	machine	NOUN
cana-1705	103	25	learning	learning	NOUN
cana-1705	103	26	models	model	NOUN
cana-1705	103	27	.	.	PUNCT
cana-1705	104	1	the	the	DET
cana-1705	104	2	authors	author	NOUN
cana-1705	104	3	used	use	VERB
cana-1705	104	4	lstms	lstms	NOUN
cana-1705	104	5	which	which	PRON
cana-1705	104	6	can	can	AUX
cana-1705	104	7	model	model	VERB
cana-1705	104	8	long	long	ADJ
cana-1705	104	9	-	-	PUNCT
cana-1705	104	10	range	range	NOUN
cana-1705	104	11	dependencies	dependency	NOUN
cana-1705	104	12	of	of	ADP
cana-1705	104	13	traffic	traffic	NOUN
cana-1705	104	14	data	datum	NOUN
cana-1705	104	15	,	,	PUNCT
cana-1705	104	16	especially	especially	ADV
cana-1705	104	17	when	when	SCONJ
cana-1705	104	18	congestion	congestion	NOUN
cana-1705	104	19	happens	happen	VERB
cana-1705	104	20	periodically	periodically	ADV
cana-1705	104	21	like	like	ADP
cana-1705	104	22	rush	rush	NOUN
cana-1705	104	23	hours	hour	NOUN
cana-1705	104	24	,	,	PUNCT
cana-1705	104	25	weekend	weekend	NOUN
cana-1705	104	26	.	.	PUNCT
cana-1705	105	1	experiments	experiment	NOUN
cana-1705	105	2	on	on	ADP
cana-1705	105	3	real	real	ADJ
cana-1705	105	4	-	-	PUNCT
cana-1705	105	5	world	world	NOUN
cana-1705	105	6	traffic	traffic	NOUN
cana-1705	105	7	datasets	dataset	NOUN
cana-1705	105	8	proved	prove	VERB
cana-1705	105	9	that	that	SCONJ
cana-1705	105	10	lstms	lstms	NOUN
cana-1705	105	11	could	could	AUX
cana-1705	105	12	make	make	VERB
cana-1705	105	13	better	well	ADJ
cana-1705	105	14	predictions	prediction	NOUN
cana-1705	105	15	compared	compare	VERB
cana-1705	105	16	to	to	ADP
cana-1705	105	17	both	both	CCONJ
cana-1705	105	18	svm	svm	VERB
cana-1705	105	19	and	and	CCONJ
cana-1705	105	20	arima	arima	PROPN
cana-1705	105	21	models	model	NOUN
cana-1705	105	22	.	.	PUNCT
cana-1705	106	1	communications	communication	NOUN
cana-1705	106	2	on	on	ADP
cana-1705	106	3	applied	apply	VERB
cana-1705	106	4	nonlinear	nonlinear	ADJ
cana-1705	106	5	analysis	analysis	NOUN
cana-1705	106	6	issn	issn	NOUN
cana-1705	106	7	:	:	PUNCT
cana-1705	106	8	1074	1074	NUM
cana-1705	106	9	-	-	PUNCT
cana-1705	106	10	133x	133x	NUM
cana-1705	106	11	vol	vol	NOUN
cana-1705	106	12	32	32	NUM
cana-1705	106	13	no	no	NOUN
cana-1705	106	14	.	.	NOUN
cana-1705	106	15	2	2	NUM
cana-1705	106	16	(	(	PUNCT
cana-1705	106	17	2025	2025	NUM
cana-1705	106	18	)	)	PUNCT
cana-1705	106	19	7	7	NUM
cana-1705	107	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	107	2	sourc	sourc	NOUN
cana-1705	107	3	e	e	X
cana-1705	107	4	objective	objective	ADJ
cana-1705	107	5	methodology	methodology	NOUN
cana-1705	107	6	results	result	VERB
cana-1705	107	7	research	research	NOUN
cana-1705	107	8	gap	gap	NOUN
cana-1705	107	9	[	[	X
cana-1705	107	10	2	2	NUM
cana-1705	107	11	]	]	PUNCT
cana-1705	107	12	•	•	NUM
cana-1705	107	13	predict	predict	VERB
cana-1705	107	14	average	average	ADJ
cana-1705	107	15	travel	travel	NOUN
cana-1705	107	16	speed	speed	NOUN
cana-1705	107	17	of	of	ADP
cana-1705	107	18	urban	urban	ADJ
cana-1705	107	19	road	road	NOUN
cana-1705	107	20	network	network	NOUN
cana-1705	107	21	sections	section	NOUN
cana-1705	107	22	.	.	PUNCT
cana-1705	108	1	•	•	NUM
cana-1705	108	2	master	master	PROPN
cana-1705	108	3	spacetime	spacetime	PROPN
cana-1705	108	4	nonlinear	nonlinear	PROPN
cana-1705	108	5	relation	relation	NOUN
cana-1705	108	6	of	of	ADP
cana-1705	108	7	road	road	NOUN
cana-1705	108	8	network	network	NOUN
cana-1705	108	9	traffic	traffic	NOUN
cana-1705	108	10	state	state	NOUN
cana-1705	108	11	.	.	PUNCT
cana-1705	109	1	•	•	NUM
cana-1705	109	2	convolutiona	convolutiona	ADJ
cana-1705	109	3	l	l	PROPN
cana-1705	109	4	neural	neural	ADJ
cana-1705	109	5	network	network	NOUN
cana-1705	109	6	(	(	PUNCT
cana-1705	109	7	cnn	cnn	PROPN
cana-1705	109	8	)	)	PUNCT
cana-1705	109	9	•	•	NUM
cana-1705	109	10	long	long	ADJ
cana-1705	109	11	and	and	CCONJ
cana-1705	109	12	short	short	ADJ
cana-1705	109	13	-	-	PUNCT
cana-1705	109	14	term	term	NOUN
cana-1705	109	15	memory	memory	NOUN
cana-1705	109	16	neural	neural	ADJ
cana-1705	109	17	network	network	NOUN
cana-1705	109	18	(	(	PUNCT
cana-1705	109	19	lstm	lstm	PROPN
cana-1705	109	20	)	)	PUNCT
cana-1705	109	21	•	•	ADV
cana-1705	109	22	lstm	lstm	PROPN
cana-1705	109	23	-	-	PUNCT
cana-1705	109	24	cnn	cnn	PROPN
cana-1705	109	25	predicts	predict	VERB
cana-1705	109	26	average	average	ADJ
cana-1705	109	27	travel	travel	NOUN
cana-1705	109	28	speed	speed	NOUN
cana-1705	109	29	of	of	ADP
cana-1705	109	30	road	road	NOUN
cana-1705	109	31	sections	section	NOUN
cana-1705	109	32	effectively	effectively	ADV
cana-1705	109	33	.	.	PUNCT
cana-1705	110	1	•	•	NUM
cana-1705	110	2	space	space	NOUN
cana-1705	110	3	-	-	PUNCT
cana-1705	110	4	time	time	NOUN
cana-1705	110	5	nonlinear	nonlinear	ADJ
cana-1705	110	6	relation	relation	NOUN
cana-1705	110	7	of	of	ADP
cana-1705	110	8	traffic	traffic	NOUN
cana-1705	110	9	state	state	NOUN
cana-1705	110	10	mastered	master	VERB
cana-1705	110	11	more	more	ADV
cana-1705	110	12	compared	compare	VERB
cana-1705	110	13	to	to	ADP
cana-1705	110	14	existing	exist	VERB
cana-1705	110	15	methods	method	NOUN
cana-1705	110	16	•	•	ADP
cana-1705	110	17	lstmcnn	lstmcnn	PROPN
cana-1705	110	18	captures	capture	VERB
cana-1705	110	19	space	space	NOUN
cana-1705	110	20	-	-	PUNCT
cana-1705	110	21	time	time	NOUN
cana-1705	110	22	nonlinear	nonlinear	ADJ
cana-1705	110	23	relations	relation	NOUN
cana-1705	110	24	better	well	ADV
cana-1705	110	25	than	than	ADP
cana-1705	110	26	existing	exist	VERB
cana-1705	110	27	methods	method	NOUN
cana-1705	110	28	.	.	PUNCT
cana-1705	111	1	•	•	NUM
cana-1705	111	2	reduces	reduce	VERB
cana-1705	111	3	redundant	redundant	ADJ
cana-1705	111	4	information	information	NOUN
cana-1705	111	5	input	input	NOUN
cana-1705	111	6	,	,	PUNCT
cana-1705	111	7	improving	improve	VERB
cana-1705	111	8	traffic	traffic	NOUN
cana-1705	111	9	state	state	NOUN
cana-1705	111	10	prediction	prediction	NOUN
cana-1705	111	11	effectiveness	effectiveness	NOUN
cana-1705	111	12	.	.	PUNCT
cana-1705	112	1	[	[	X
cana-1705	112	2	3	3	NUM
cana-1705	112	3	]	]	SYM
cana-1705	112	4	•	•	NOUN
cana-1705	112	5	integrate	integrate	VERB
cana-1705	112	6	deep	deep	ADJ
cana-1705	112	7	learning	learning	NOUN
cana-1705	112	8	with	with	ADP
cana-1705	112	9	traffic	traffic	NOUN
cana-1705	112	10	microsimulation	microsimulation	NOUN
cana-1705	112	11	for	for	ADP
cana-1705	112	12	prediction	prediction	NOUN
cana-1705	112	13	.	.	PUNCT
cana-1705	113	1	•	•	NUM
cana-1705	113	2	provide	provide	VERB
cana-1705	113	3	decision	decision	NOUN
cana-1705	113	4	-	-	PUNCT
cana-1705	113	5	making	make	VERB
cana-1705	113	6	support	support	NOUN
cana-1705	113	7	for	for	ADP
cana-1705	113	8	traffic	traffic	NOUN
cana-1705	113	9	network	network	NOUN
cana-1705	113	10	analysts	analyst	NOUN
cana-1705	113	11	•	•	NUM
cana-1705	113	12	deep	deep	ADJ
cana-1705	113	13	cnnlstm	cnnlstm	NOUN
cana-1705	113	14	stacked	stack	VERB
cana-1705	113	15	autoencoders	autoencoder	NOUN
cana-1705	113	16	for	for	ADP
cana-1705	113	17	traffic	traffic	NOUN
cana-1705	113	18	parameter	parameter	NOUN
cana-1705	113	19	prediction	prediction	NOUN
cana-1705	113	20	•	•	NOUN
cana-1705	114	1	integration	integration	NOUN
cana-1705	114	2	with	with	ADP
cana-1705	114	3	traffic	traffic	NOUN
cana-1705	114	4	microsimulation	microsimulation	NOUN
cana-1705	114	5	tool	tool	NOUN
cana-1705	114	6	sumo	sumo	NOUN
cana-1705	114	7	for	for	ADP
cana-1705	114	8	future	future	ADJ
cana-1705	114	9	state	state	NOUN
cana-1705	114	10	visualization	visualization	NOUN
cana-1705	114	11	•	•	ADP
cana-1705	114	12	achieved	achieve	VERB
cana-1705	114	13	rmse	rmse	NOUN
cana-1705	114	14	of	of	ADP
cana-1705	114	15	about	about	ADV
cana-1705	114	16	40	40	NUM
cana-1705	114	17	(	(	PUNCT
cana-1705	114	18	veh	veh	PROPN
cana-1705	114	19	/	/	SYM
cana-1705	114	20	hr	hr	NOUN
cana-1705	114	21	)	)	PUNCT
cana-1705	114	22	,	,	PUNCT
cana-1705	114	23	satisfactory	satisfactory	ADJ
cana-1705	114	24	prediction	prediction	NOUN
cana-1705	114	25	performance	performance	NOUN
cana-1705	114	26	.	.	PUNCT
cana-1705	115	1	•	•	NUM
cana-1705	115	2	model	model	NOUN
cana-1705	115	3	accurately	accurately	ADV
cana-1705	115	4	predicts	predict	VERB
cana-1705	115	5	traffic	traffic	NOUN
cana-1705	115	6	volume	volume	NOUN
cana-1705	115	7	,	,	PUNCT
cana-1705	115	8	indicating	indicate	VERB
cana-1705	115	9	adequate	adequate	ADJ
cana-1705	115	10	performance	performance	NOUN
cana-1705	115	11	.	.	PUNCT
cana-1705	116	1	•	•	NUM
cana-1705	116	2	lack	lack	NOUN
cana-1705	116	3	of	of	ADP
cana-1705	116	4	comparison	comparison	NOUN
cana-1705	116	5	with	with	ADP
cana-1705	116	6	existing	exist	VERB
cana-1705	116	7	traffic	traffic	NOUN
cana-1705	116	8	prediction	prediction	NOUN
cana-1705	116	9	models	model	NOUN
cana-1705	116	10	•	•	ADP
cana-1705	116	11	limited	limited	ADJ
cana-1705	116	12	discussion	discussion	NOUN
cana-1705	116	13	on	on	ADP
cana-1705	116	14	scalability	scalability	NOUN
cana-1705	116	15	to	to	PART
cana-1705	116	16	larger	large	ADJ
cana-1705	116	17	and	and	CCONJ
cana-1705	116	18	more	more	ADV
cana-1705	116	19	complex	complex	ADJ
cana-1705	116	20	networks	network	NOUN
cana-1705	116	21	[	[	X
cana-1705	116	22	4	4	NUM
cana-1705	116	23	]	]	PUNCT
cana-1705	116	24	•	•	NUM
cana-1705	116	25	propose	propose	VERB
cana-1705	116	26	regularized	regularize	VERB
cana-1705	116	27	lstm	lstm	ADJ
cana-1705	116	28	model	model	NOUN
cana-1705	116	29	for	for	ADP
cana-1705	116	30	traffic	traffic	NOUN
cana-1705	116	31	flow	flow	NOUN
cana-1705	116	32	prediction	prediction	NOUN
cana-1705	116	33	.	.	PUNCT
cana-1705	117	1	•	•	NUM
cana-1705	117	2	compare	compare	NOUN
cana-1705	117	3	model	model	NOUN
cana-1705	117	4	with	with	ADP
cana-1705	117	5	basic	basic	ADJ
cana-1705	117	6	lstm	lstm	NOUN
cana-1705	117	7	and	and	CCONJ
cana-1705	117	8	other	other	ADJ
cana-1705	117	9	machine	machine	NOUN
cana-1705	117	10	learning	learning	NOUN
cana-1705	117	11	models	model	NOUN
cana-1705	117	12	.	.	PUNCT
cana-1705	118	1	•	•	NUM
cana-1705	118	2	regularized	regularize	VERB
cana-1705	118	3	lstm	lstm	ADJ
cana-1705	118	4	model	model	NOUN
cana-1705	118	5	with	with	ADP
cana-1705	118	6	recurrent	recurrent	ADJ
cana-1705	118	7	dropout	dropout	NOUN
cana-1705	118	8	and	and	CCONJ
cana-1705	118	9	max	max	PROPN
cana-1705	118	10	-	-	PUNCT
cana-1705	118	11	norm	norm	NOUN
cana-1705	118	12	weight	weight	NOUN
cana-1705	118	13	constraint	constraint	NOUN
cana-1705	118	14	•	•	PRON
cana-1705	118	15	adam	adam	PROPN
cana-1705	118	16	optimizer	optimizer	NOUN
cana-1705	118	17	merged	merge	VERB
cana-1705	118	18	into	into	ADP
cana-1705	118	19	the	the	DET
cana-1705	118	20	model	model	NOUN
cana-1705	118	21	•	•	ADP
cana-1705	118	22	lowest	low	ADJ
cana-1705	118	23	root	root	NOUN
cana-1705	118	24	mean	mean	NOUN
cana-1705	118	25	square	square	ADJ
cana-1705	118	26	error	error	NOUN
cana-1705	118	27	and	and	CCONJ
cana-1705	118	28	mean	mean	VERB
cana-1705	118	29	absolute	absolute	ADJ
cana-1705	118	30	error	error	NOUN
cana-1705	118	31	achieved	achieve	VERB
cana-1705	118	32	.	.	PUNCT
cana-1705	119	1	•	•	NUM
cana-1705	119	2	outperforme	outperforme	ADJ
cana-1705	119	3	d	d	X
cana-1705	119	4	basic	basic	ADJ
cana-1705	119	5	lstm	lstm	NOUN
cana-1705	119	6	,	,	PUNCT
cana-1705	119	7	bp	bp	PROPN
cana-1705	119	8	neural	neural	ADJ
cana-1705	119	9	network	network	PROPN
cana-1705	119	10	,	,	PUNCT
cana-1705	119	11	rnn	rnn	PROPN
cana-1705	119	12	,	,	PUNCT
cana-1705	119	13	stacked	stack	VERB
cana-1705	119	14	autoencoder	autoencoder	NOUN
cana-1705	119	15	.	.	PUNCT
cana-1705	120	1	•	•	NUM
cana-1705	120	2	overfittin	overfittin	NOUN
cana-1705	120	3	g	g	NOUN
cana-1705	120	4	in	in	ADP
cana-1705	120	5	existing	exist	VERB
cana-1705	120	6	traffic	traffic	NOUN
cana-1705	120	7	flow	flow	NOUN
cana-1705	120	8	prediction	prediction	NOUN
cana-1705	120	9	models	model	NOUN
cana-1705	120	10	•	•	NOUN
cana-1705	120	11	lack	lack	NOUN
cana-1705	120	12	of	of	ADP
cana-1705	120	13	generalization	generalization	NOUN
cana-1705	120	14	ability	ability	NOUN
cana-1705	120	15	in	in	ADP
cana-1705	120	16	deep	deep	ADJ
cana-1705	120	17	layer	layer	NOUN
cana-1705	120	18	neural	neural	ADJ
cana-1705	120	19	networks	network	NOUN
cana-1705	121	1	[	[	X
cana-1705	121	2	5	5	NUM
cana-1705	121	3	]	]	SYM
cana-1705	121	4	•	•	NUM
cana-1705	121	5	recurrence	recurrence	NOUN
cana-1705	121	6	plots	plot	NOUN
cana-1705	121	7	for	for	ADP
cana-1705	121	8	traffic	traffic	NOUN
cana-1705	121	9	network	network	NOUN
cana-1705	121	10	time	time	PROPN
cana-1705	121	11	series	series	PROPN
cana-1705	121	12	conversion	conversion	PROPN
cana-1705	121	13	•	•	NUM
cana-1705	121	14	deep	deep	ADJ
cana-1705	121	15	2d	2d	NUM
cana-1705	121	16	convolutional	convolutional	ADJ
cana-1705	121	17	long	long	ADJ
cana-1705	121	18	short	short	ADJ
cana-1705	121	19	-	-	PUNCT
cana-1705	121	20	term	term	NOUN
cana-1705	121	21	memory	memory	NOUN
cana-1705	121	22	(	(	PUNCT
cana-1705	121	23	convlstm	convlstm	PROPN
cana-1705	121	24	)	)	PUNCT
cana-1705	121	25	•	•	NOUN
cana-1705	122	1	propose	propose	VERB
cana-1705	122	2	scalable	scalable	ADJ
cana-1705	122	3	deep	deep	ADJ
cana-1705	122	4	learning	learning	NOUN
cana-1705	122	5	framework	framework	NOUN
cana-1705	122	6	for	for	ADP
cana-1705	122	7	urban	urban	ADJ
cana-1705	122	8	traffic	traffic	NOUN
cana-1705	122	9	flow	flow	NOUN
cana-1705	122	10	prediction	prediction	NOUN
cana-1705	122	11	.	.	PUNCT
cana-1705	123	1	•	•	NUM
cana-1705	123	2	convert	convert	NOUN
cana-1705	123	3	input	input	NOUN
cana-1705	123	4	traffic	traffic	NOUN
cana-1705	123	5	network	network	NOUN
cana-1705	123	6	time	time	NOUN
cana-1705	123	7	•	•	ADP
cana-1705	123	8	outperforme	outperforme	ADJ
cana-1705	123	9	d	d	ADP
cana-1705	123	10	state	state	NOUN
cana-1705	123	11	-	-	PUNCT
cana-1705	123	12	of	of	ADP
cana-1705	123	13	-	-	PUNCT
cana-1705	123	14	the	the	DET
cana-1705	123	15	-	-	PUNCT
cana-1705	123	16	art	art	NOUN
cana-1705	123	17	models	model	NOUN
cana-1705	123	18	in	in	ADP
cana-1705	123	19	urban	urban	ADJ
cana-1705	123	20	traffic	traffic	NOUN
cana-1705	123	21	flow	flow	NOUN
cana-1705	123	22	prediction	prediction	NOUN
cana-1705	123	23	.	.	PUNCT
cana-1705	124	1	•	•	NUM
cana-1705	124	2	demonstrate	demonstrate	VERB
cana-1705	124	3	d	d	NOUN
cana-1705	124	4	potential	potential	NOUN
cana-1705	124	5	in	in	ADP
cana-1705	124	6	•	•	ADJ
cana-1705	124	7	majority	majority	NOUN
cana-1705	124	8	of	of	ADP
cana-1705	124	9	models	model	NOUN
cana-1705	124	10	focus	focus	VERB
cana-1705	124	11	on	on	ADP
cana-1705	124	12	junction	junction	NOUN
cana-1705	124	13	or	or	CCONJ
cana-1705	124	14	link	link	VERB
cana-1705	124	15	traffic	traffic	NOUN
cana-1705	124	16	prediction	prediction	NOUN
cana-1705	124	17	.	.	PUNCT
cana-1705	125	1	•	•	NUM
cana-1705	125	2	limited	limited	ADJ
cana-1705	125	3	focus	focus	NOUN
cana-1705	125	4	on	on	ADP
cana-1705	125	5	networkcommunications	networkcommunication	NOUN
cana-1705	125	6	on	on	ADP
cana-1705	125	7	applied	apply	VERB
cana-1705	125	8	nonlinear	nonlinear	ADJ
cana-1705	125	9	analysis	analysis	NOUN
cana-1705	125	10	issn	issn	NOUN
cana-1705	125	11	:	:	PUNCT
cana-1705	125	12	1074	1074	NUM
cana-1705	125	13	-	-	PUNCT
cana-1705	125	14	133x	133x	NUM
cana-1705	125	15	vol	vol	NOUN
cana-1705	125	16	32	32	NUM
cana-1705	125	17	no	no	NOUN
cana-1705	125	18	.	.	NOUN
cana-1705	125	19	2	2	NUM
cana-1705	125	20	(	(	PUNCT
cana-1705	125	21	2025	2025	NUM
cana-1705	125	22	)	)	PUNCT
cana-1705	126	1	8	8	NUM
cana-1705	126	2	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	126	3	architecture	architecture	NOUN
cana-1705	126	4	applied	apply	VERB
cana-1705	126	5	series	series	NOUN
cana-1705	126	6	to	to	ADP
cana-1705	126	7	recurrence	recurrence	NOUN
cana-1705	126	8	plots	plot	NOUN
cana-1705	126	9	.	.	PUNCT
cana-1705	127	1	handling	handle	VERB
cana-1705	127	2	large	large	ADJ
cana-1705	127	3	-	-	PUNCT
cana-1705	127	4	scale	scale	NOUN
cana-1705	127	5	urban	urban	ADJ
cana-1705	127	6	traffic	traffic	NOUN
cana-1705	127	7	data	datum	NOUN
cana-1705	127	8	.	.	PUNCT
cana-1705	128	1	wide	wide	ADJ
cana-1705	128	2	traffic	traffic	NOUN
cana-1705	128	3	parameter	parameter	NOUN
cana-1705	128	4	prediction	prediction	NOUN
cana-1705	128	5	.	.	PUNCT
cana-1705	129	1	[	[	X
cana-1705	129	2	6	6	NUM
cana-1705	129	3	]	]	SYM
cana-1705	129	4	•	•	NUM
cana-1705	129	5	lstm	lstm	NOUN
cana-1705	129	6	network	network	NOUN
cana-1705	129	7	with	with	ADP
cana-1705	129	8	softmax	softmax	NOUN
cana-1705	129	9	and	and	CCONJ
cana-1705	129	10	logistic	logistic	ADJ
cana-1705	129	11	regression	regression	NOUN
cana-1705	129	12	layers	layer	NOUN
cana-1705	129	13	•	•	NOUN
cana-1705	129	14	lstm_attentio	lstm_attentio	NOUN
cana-1705	129	15	n	n	PRON
cana-1705	129	16	network	network	NOUN
cana-1705	129	17	for	for	ADP
cana-1705	129	18	traffic	traffic	NOUN
cana-1705	129	19	flow	flow	NOUN
cana-1705	129	20	prediction	prediction	NOUN
cana-1705	129	21	•	•	ADP
cana-1705	129	22	predict	predict	VERB
cana-1705	129	23	future	future	ADJ
cana-1705	129	24	road	road	NOUN
cana-1705	129	25	traffic	traffic	NOUN
cana-1705	129	26	flow	flow	NOUN
cana-1705	129	27	data	datum	NOUN
cana-1705	129	28	accurately	accurately	ADV
cana-1705	129	29	.	.	PUNCT
cana-1705	130	1	•	•	ADP
cana-1705	130	2	utilize	utilize	VERB
cana-1705	130	3	lstm_attention	lstm_attention	NOUN
cana-1705	130	4	network	network	NOUN
cana-1705	130	5	for	for	ADP
cana-1705	130	6	traffic	traffic	NOUN
cana-1705	130	7	flow	flow	NOUN
cana-1705	130	8	forecasting	forecasting	NOUN
cana-1705	130	9	.	.	PUNCT
cana-1705	131	1	•	•	NUM
cana-1705	131	2	accurate	accurate	ADJ
cana-1705	131	3	prediction	prediction	NOUN
cana-1705	131	4	of	of	ADP
cana-1705	131	5	future	future	ADJ
cana-1705	131	6	road	road	NOUN
cana-1705	131	7	traffic	traffic	NOUN
cana-1705	131	8	flow	flow	NOUN
cana-1705	131	9	data	datum	NOUN
cana-1705	131	10	.	.	PUNCT
cana-1705	132	1	•	•	NUM
cana-1705	132	2	utilizes	utilize	NOUN
cana-1705	132	3	lstm_attention	lstm_attention	NOUN
cana-1705	132	4	network	network	NOUN
cana-1705	132	5	for	for	ADP
cana-1705	132	6	traffic	traffic	NOUN
cana-1705	132	7	flow	flow	NOUN
cana-1705	132	8	forecasting	forecasting	NOUN
cana-1705	132	9	.	.	PUNCT
cana-1705	133	1	•	•	NUM
cana-1705	133	2	difficult	difficult	ADJ
cana-1705	133	3	to	to	PART
cana-1705	133	4	model	model	VERB
cana-1705	133	5	precise	precise	ADJ
cana-1705	133	6	traffic	traffic	NOUN
cana-1705	133	7	information	information	NOUN
cana-1705	133	8	due	due	ADP
cana-1705	133	9	to	to	ADP
cana-1705	133	10	many	many	ADJ
cana-1705	133	11	factors	factor	NOUN
cana-1705	133	12	.	.	PUNCT
cana-1705	134	1	•	•	NOUN
cana-1705	134	2	need	need	NOUN
cana-1705	134	3	for	for	ADP
cana-1705	134	4	machine	machine	NOUN
cana-1705	134	5	learning	learn	VERB
cana-1705	134	6	techniques	technique	NOUN
cana-1705	134	7	to	to	PART
cana-1705	134	8	analyze	analyze	VERB
cana-1705	134	9	historical	historical	ADJ
cana-1705	134	10	traffic	traffic	NOUN
cana-1705	134	11	data	datum	NOUN
cana-1705	134	12	.	.	PUNCT
cana-1705	135	1	[	[	X
cana-1705	135	2	7	7	NUM
cana-1705	135	3	]	]	SYM
cana-1705	135	4	•	•	NUM
cana-1705	135	5	lstm	lstm	PROPN
cana-1705	135	6	model	model	NOUN
cana-1705	135	7	with	with	ADP
cana-1705	135	8	historical	historical	ADJ
cana-1705	135	9	data	datum	NOUN
cana-1705	135	10	for	for	ADP
cana-1705	135	11	traffic	traffic	NOUN
cana-1705	135	12	flow	flow	NOUN
cana-1705	135	13	prediction	prediction	NOUN
cana-1705	135	14	•	•	NOUN
cana-1705	135	15	rmse	rmse	NOUN
cana-1705	135	16	used	use	VERB
cana-1705	135	17	for	for	ADP
cana-1705	135	18	accuracy	accuracy	NOUN
cana-1705	135	19	calculation	calculation	NOUN
cana-1705	135	20	in	in	ADP
cana-1705	135	21	the	the	DET
cana-1705	135	22	experiments	experiment	NOUN
cana-1705	135	23	•	•	ADP
cana-1705	135	24	predict	predict	VERB
cana-1705	135	25	traffic	traffic	NOUN
cana-1705	135	26	flow	flow	NOUN
cana-1705	135	27	in	in	ADP
cana-1705	135	28	urban	urban	ADJ
cana-1705	135	29	cities	city	NOUN
cana-1705	135	30	using	use	VERB
cana-1705	135	31	lstm	lstm	ADJ
cana-1705	135	32	model	model	NOUN
cana-1705	135	33	.	.	PUNCT
cana-1705	136	1	•	•	NUM
cana-1705	136	2	analyze	analyze	VERB
cana-1705	136	3	historical	historical	ADJ
cana-1705	136	4	traffic	traffic	NOUN
cana-1705	136	5	data	datum	NOUN
cana-1705	136	6	to	to	PART
cana-1705	136	7	train	train	VERB
cana-1705	136	8	prediction	prediction	NOUN
cana-1705	136	9	model	model	NOUN
cana-1705	136	10	.	.	PUNCT
cana-1705	137	1	•	•	NUM
cana-1705	137	2	rmse	rmse	NOUN
cana-1705	137	3	results	result	VERB
cana-1705	137	4	around	around	ADP
cana-1705	137	5	220	220	NUM
cana-1705	137	6	,	,	PUNCT
cana-1705	137	7	do	do	AUX
cana-1705	137	8	n't	not	PART
cana-1705	137	9	decrease	decrease	VERB
cana-1705	137	10	with	with	ADP
cana-1705	137	11	time	time	NOUN
cana-1705	137	12	.	.	PUNCT
cana-1705	138	1	•	•	NUM
cana-1705	138	2	rmse	rmse	NOUN
cana-1705	138	3	decreases	decrease	VERB
cana-1705	138	4	with	with	ADP
cana-1705	138	5	training	training	NOUN
cana-1705	138	6	times	time	NOUN
cana-1705	138	7	,	,	PUNCT
cana-1705	138	8	stabilizes	stabilize	VERB
cana-1705	138	9	around	around	ADP
cana-1705	138	10	50	50	NUM
cana-1705	138	11	.	.	PUNCT
cana-1705	139	1	•	•	NOUN
cana-1705	139	2	current	current	ADJ
cana-1705	139	3	methods	method	NOUN
cana-1705	139	4	lack	lack	VERB
cana-1705	139	5	capturing	capture	VERB
cana-1705	139	6	nonlinear	nonlinear	ADJ
cana-1705	139	7	characteristics	characteristic	NOUN
cana-1705	139	8	of	of	ADP
cana-1705	139	9	large	large	ADJ
cana-1705	139	10	-	-	PUNCT
cana-1705	139	11	scale	scale	NOUN
cana-1705	139	12	network	network	NOUN
cana-1705	139	13	sequences	sequence	NOUN
cana-1705	139	14	.	.	PUNCT
cana-1705	140	1	[	[	X
cana-1705	140	2	8	8	NUM
cana-1705	140	3	]	]	SYM
cana-1705	140	4	•	•	ADV
cana-1705	140	5	lstm	lstm	PROPN
cana-1705	140	6	-	-	PUNCT
cana-1705	140	7	rnn	rnn	NOUN
cana-1705	140	8	neural	neural	ADJ
cana-1705	140	9	network	network	NOUN
cana-1705	140	10	construction	construction	NOUN
cana-1705	140	11	•	•	NOUN
cana-1705	140	12	parameter	parameter	NOUN
cana-1705	140	13	optimization	optimization	NOUN
cana-1705	140	14	using	use	VERB
cana-1705	140	15	cso	cso	PROPN
cana-1705	140	16	algorithm	algorithm	NOUN
cana-1705	140	17	for	for	ADP
cana-1705	140	18	initial	initial	ADJ
cana-1705	140	19	values	value	NOUN
cana-1705	140	20	•	•	VERB
cana-1705	140	21	improve	improve	VERB
cana-1705	140	22	traffic	traffic	NOUN
cana-1705	140	23	flow	flow	NOUN
cana-1705	140	24	prediction	prediction	NOUN
cana-1705	140	25	precision	precision	NOUN
cana-1705	140	26	•	•	NUM
cana-1705	140	27	enhance	enhance	NOUN
cana-1705	140	28	traffic	traffic	NOUN
cana-1705	140	29	flow	flow	NOUN
cana-1705	140	30	prediction	prediction	NOUN
cana-1705	140	31	performance	performance	NOUN
cana-1705	140	32	•	•	ADP
cana-1705	140	33	improved	improve	VERB
cana-1705	140	34	prediction	prediction	NOUN
cana-1705	140	35	precision	precision	NOUN
cana-1705	140	36	of	of	ADP
cana-1705	140	37	deep	deep	ADJ
cana-1705	140	38	neural	neural	ADJ
cana-1705	140	39	network	network	NOUN
cana-1705	140	40	.	.	PUNCT
cana-1705	141	1	•	•	NUM
cana-1705	141	2	remarkably	remarkably	ADV
cana-1705	141	3	improved	improve	VERB
cana-1705	141	4	traffic	traffic	NOUN
cana-1705	141	5	flow	flow	NOUN
cana-1705	141	6	prediction	prediction	NOUN
cana-1705	141	7	performance	performance	NOUN
cana-1705	141	8	.	.	PUNCT
cana-1705	142	1	•	•	NUM
cana-1705	142	2	existing	exist	VERB
cana-1705	142	3	methods	method	NOUN
cana-1705	142	4	face	face	VERB
cana-1705	142	5	issues	issue	NOUN
cana-1705	142	6	like	like	ADP
cana-1705	142	7	gradient	gradient	NOUN
cana-1705	142	8	disappearance	disappearance	NOUN
cana-1705	142	9	and	and	CCONJ
cana-1705	142	10	early	early	ADJ
cana-1705	142	11	convergence	convergence	NOUN
cana-1705	142	12	.	.	PUNCT
cana-1705	143	1	[	[	X
cana-1705	143	2	9	9	NUM
cana-1705	143	3	]	]	SYM
cana-1705	143	4	•	•	NOUN
cana-1705	143	5	genetic	genetic	ADJ
cana-1705	143	6	algorithm	algorithm	NOUN
cana-1705	143	7	optimized	optimize	VERB
cana-1705	143	8	lstm	lstm	PROPN
cana-1705	143	9	neural	neural	ADJ
cana-1705	143	10	network	network	NOUN
cana-1705	143	11	•	•	NOUN
cana-1705	143	12	data	datum	NOUN
cana-1705	143	13	normalization	normalization	NOUN
cana-1705	143	14	preprocessing	preprocessing	NOUN
cana-1705	143	15	,	,	PUNCT
cana-1705	143	16	model	model	NOUN
cana-1705	143	17	parameter	parameter	PROPN
cana-1705	143	18	prediction	prediction	PROPN
cana-1705	143	19	,	,	PUNCT
cana-1705	143	20	iterative	iterative	NOUN
cana-1705	143	21	optimization	optimization	NOUN
cana-1705	143	22	,	,	PUNCT
cana-1705	143	23	error	error	NOUN
cana-1705	143	24	evaluation	evaluation	NOUN
cana-1705	143	25	•	•	NOUN
cana-1705	143	26	utilize	utilize	VERB
cana-1705	143	27	genetic	genetic	ADJ
cana-1705	143	28	algorithm	algorithm	NOUN
cana-1705	143	29	optimized	optimize	VERB
cana-1705	143	30	lstm	lstm	NOUN
cana-1705	143	31	for	for	ADP
cana-1705	143	32	traffic	traffic	NOUN
cana-1705	143	33	flow	flow	NOUN
cana-1705	143	34	prediction	prediction	NOUN
cana-1705	143	35	.	.	PUNCT
cana-1705	144	1	•	•	PUNCT
cana-1705	144	2	achieve	achieve	VERB
cana-1705	144	3	high	high	ADJ
cana-1705	144	4	prediction	prediction	NOUN
cana-1705	144	5	precision	precision	NOUN
cana-1705	144	6	and	and	CCONJ
cana-1705	144	7	applicability	applicability	NOUN
cana-1705	144	8	on	on	ADP
cana-1705	144	9	different	different	ADJ
cana-1705	144	10	data	datum	NOUN
cana-1705	144	11	samples	sample	NOUN
cana-1705	144	12	.	.	PUNCT
cana-1705	145	1	•	•	NUM
cana-1705	145	2	high	high	ADJ
cana-1705	145	3	prediction	prediction	NOUN
cana-1705	145	4	precision	precision	NOUN
cana-1705	145	5	achieved	achieve	VERB
cana-1705	145	6	through	through	ADP
cana-1705	145	7	genetic	genetic	ADJ
cana-1705	145	8	algorithm	algorithm	NOUN
cana-1705	145	9	optimized	optimize	VERB
cana-1705	145	10	lstm	lstm	PROPN
cana-1705	145	11	network	network	NOUN
cana-1705	145	12	.	.	PUNCT
cana-1705	146	1	•	•	NUM
cana-1705	146	2	good	good	ADJ
cana-1705	146	3	applicability	applicability	NOUN
cana-1705	146	4	on	on	ADP
cana-1705	146	5	data	datum	NOUN
cana-1705	146	6	samples	sample	NOUN
cana-1705	146	7	in	in	ADP
cana-1705	146	8	different	different	ADJ
cana-1705	146	9	intervals	interval	NOUN
cana-1705	146	10	demonstrated	demonstrate	VERB
cana-1705	146	11	.	.	PUNCT
cana-1705	147	1	•	•	NUM
cana-1705	147	2	difficult	difficult	ADJ
cana-1705	147	3	to	to	PART
cana-1705	147	4	model	model	VERB
cana-1705	147	5	precise	precise	ADJ
cana-1705	147	6	traffic	traffic	NOUN
cana-1705	147	7	information	information	NOUN
cana-1705	147	8	due	due	ADP
cana-1705	147	9	to	to	ADP
cana-1705	147	10	many	many	ADJ
cana-1705	147	11	factors	factor	NOUN
cana-1705	147	12	.	.	PUNCT
cana-1705	148	1	•	•	NOUN
cana-1705	148	2	need	need	NOUN
cana-1705	148	3	for	for	ADP
cana-1705	148	4	machine	machine	NOUN
cana-1705	148	5	learning	learn	VERB
cana-1705	148	6	techniques	technique	NOUN
cana-1705	148	7	to	to	PART
cana-1705	148	8	analyze	analyze	VERB
cana-1705	148	9	historical	historical	ADJ
cana-1705	148	10	traffic	traffic	NOUN
cana-1705	148	11	data	datum	NOUN
cana-1705	148	12	.	.	PUNCT
cana-1705	149	1	communications	communication	NOUN
cana-1705	149	2	on	on	ADP
cana-1705	149	3	applied	apply	VERB
cana-1705	149	4	nonlinear	nonlinear	ADJ
cana-1705	149	5	analysis	analysis	NOUN
cana-1705	149	6	issn	issn	NOUN
cana-1705	149	7	:	:	PUNCT
cana-1705	149	8	1074	1074	NUM
cana-1705	149	9	-	-	PUNCT
cana-1705	149	10	133x	133x	NUM
cana-1705	149	11	vol	vol	NOUN
cana-1705	149	12	32	32	NUM
cana-1705	149	13	no	no	NOUN
cana-1705	149	14	.	.	NOUN
cana-1705	149	15	2	2	NUM
cana-1705	149	16	(	(	PUNCT
cana-1705	149	17	2025	2025	NUM
cana-1705	149	18	)	)	PUNCT
cana-1705	149	19	9	9	NUM
cana-1705	149	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	150	1	[	[	X
cana-1705	150	2	10	10	NUM
cana-1705	150	3	]	]	SYM
cana-1705	150	4	•	•	NOUN
cana-1705	150	5	improve	improve	VERB
cana-1705	150	6	shortterm	shortterm	PROPN
cana-1705	150	7	traffic	traffic	NOUN
cana-1705	150	8	flow	flow	NOUN
cana-1705	150	9	prediction	prediction	NOUN
cana-1705	150	10	accuracy	accuracy	NOUN
cana-1705	150	11	.	.	PUNCT
cana-1705	151	1	•	•	NUM
cana-1705	151	2	propose	propose	VERB
cana-1705	151	3	lstm_bilstm	lstm_bilstm	NOUN
cana-1705	151	4	model	model	NOUN
cana-1705	151	5	for	for	ADP
cana-1705	151	6	traffic	traffic	NOUN
cana-1705	151	7	flow	flow	NOUN
cana-1705	151	8	prediction	prediction	NOUN
cana-1705	151	9	.	.	PUNCT
cana-1705	152	1	•	•	NOUN
cana-1705	152	2	savitzky	savitzky	PROPN
cana-1705	152	3	–	–	PUNCT
cana-1705	152	4	golay	golay	NOUN
cana-1705	152	5	filter	filter	NOUN
cana-1705	152	6	,	,	PUNCT
cana-1705	152	7	tcn	tcn	PROPN
cana-1705	152	8	,	,	PUNCT
cana-1705	152	9	lstm	lstm	ADJ
cana-1705	152	10	•	•	NUM
cana-1705	152	11	hybrid	hybrid	NOUN
cana-1705	152	12	method	method	NOUN
cana-1705	152	13	named	name	VERB
cana-1705	152	14	stlstm	stlstm	NOUN
cana-1705	152	15	for	for	ADP
cana-1705	152	16	network	network	NOUN
cana-1705	152	17	traffic	traffic	NOUN
cana-1705	152	18	prediction	prediction	NOUN
cana-1705	152	19	.	.	PUNCT
cana-1705	153	1	•	•	NUM
cana-1705	153	2	st	st	NOUN
cana-1705	153	3	-	-	PUNCT
cana-1705	153	4	lstm	lstm	NOUN
cana-1705	153	5	outperforms	outperform	VERB
cana-1705	153	6	state	state	NOUN
cana-1705	153	7	-	-	PUNCT
cana-1705	153	8	ofthe	ofthe	NOUN
cana-1705	153	9	-	-	PUNCT
cana-1705	153	10	art	art	NOUN
cana-1705	153	11	algorithms	algorithm	NOUN
cana-1705	153	12	in	in	ADP
cana-1705	153	13	prediction	prediction	NOUN
cana-1705	153	14	accuracy	accuracy	NOUN
cana-1705	153	15	.	.	PUNCT
cana-1705	154	1	•	•	NUM
cana-1705	154	2	achieves	achieve	VERB
cana-1705	154	3	better	well	ADJ
cana-1705	154	4	accuracy	accuracy	NOUN
cana-1705	154	5	than	than	ADP
cana-1705	154	6	tcn	tcn	NOUN
cana-1705	154	7	and	and	CCONJ
cana-1705	154	8	lstm	lstm	NOUN
cana-1705	154	9	on	on	ADP
cana-1705	154	10	real	real	ADJ
cana-1705	154	11	-	-	PUNCT
cana-1705	154	12	life	life	NOUN
cana-1705	154	13	dataset	dataset	NOUN
cana-1705	154	14	.	.	PUNCT
cana-1705	155	1	•	•	NUM
cana-1705	155	2	majority	majority	NOUN
cana-1705	155	3	of	of	ADP
cana-1705	155	4	models	model	NOUN
cana-1705	155	5	focus	focus	VERB
cana-1705	155	6	on	on	ADP
cana-1705	155	7	junction	junction	NOUN
cana-1705	155	8	or	or	CCONJ
cana-1705	155	9	link	link	VERB
cana-1705	155	10	traffic	traffic	NOUN
cana-1705	155	11	prediction	prediction	NOUN
cana-1705	155	12	.	.	PUNCT
cana-1705	156	1	•	•	NUM
cana-1705	156	2	limited	limited	ADJ
cana-1705	156	3	focus	focus	NOUN
cana-1705	156	4	on	on	ADP
cana-1705	156	5	networkwide	networkwide	ADJ
cana-1705	156	6	traffic	traffic	NOUN
cana-1705	156	7	parameter	parameter	PROPN
cana-1705	156	8	prediction	prediction	NOUN
cana-1705	156	9	.	.	PUNCT
cana-1705	157	1	[	[	X
cana-1705	157	2	11	11	NUM
cana-1705	157	3	]	]	SYM
cana-1705	157	4	•	•	NOUN
cana-1705	157	5	real	real	ADJ
cana-1705	157	6	-	-	PUNCT
cana-1705	157	7	time	time	NOUN
cana-1705	157	8	,	,	PUNCT
cana-1705	157	9	highaccuracy	highaccuracy	NOUN
cana-1705	157	10	network	network	NOUN
cana-1705	157	11	traffic	traffic	NOUN
cana-1705	157	12	prediction	prediction	NOUN
cana-1705	157	13	.	.	PUNCT
cana-1705	158	1	•	•	NUM
cana-1705	158	2	capture	capture	NOUN
cana-1705	158	3	longterm	longterm	NOUN
cana-1705	158	4	dependence	dependence	NOUN
cana-1705	158	5	and	and	CCONJ
cana-1705	158	6	extract	extract	VERB
cana-1705	158	7	high-/lowfrequency	high-/lowfrequency	X
cana-1705	158	8	information	information	NOUN
cana-1705	158	9	.	.	PUNCT
cana-1705	159	1	•	•	NUM
cana-1705	159	2	time	time	NOUN
cana-1705	159	3	series	series	PROPN
cana-1705	159	4	analysis	analysis	NOUN
cana-1705	159	5	,	,	PUNCT
cana-1705	159	6	smoothing	smoothing	NOUN
cana-1705	159	7	,	,	PUNCT
cana-1705	159	8	and	and	CCONJ
cana-1705	159	9	standardization	standardization	NOUN
cana-1705	159	10	•	•	NUM
cana-1705	159	11	improved	improve	VERB
cana-1705	159	12	lstm	lstm	NOUN
cana-1705	159	13	model	model	NOUN
cana-1705	159	14	with	with	ADP
cana-1705	159	15	bidirectional	bidirectional	ADJ
cana-1705	159	16	lstm	lstm	NOUN
cana-1705	159	17	network	network	NOUN
cana-1705	159	18	integration	integration	NOUN
cana-1705	159	19	•	•	NOUN
cana-1705	159	20	proposed	propose	VERB
cana-1705	159	21	method	method	NOUN
cana-1705	159	22	outperforms	outperform	VERB
cana-1705	159	23	lstm	lstm	NOUN
cana-1705	159	24	and	and	CCONJ
cana-1705	159	25	bilstm	bilstm	NOUN
cana-1705	159	26	in	in	ADP
cana-1705	159	27	accuracy	accuracy	NOUN
cana-1705	159	28	.	.	PUNCT
cana-1705	160	1	•	•	NOUN
cana-1705	160	2	proposed	propose	VERB
cana-1705	160	3	method	method	NOUN
cana-1705	160	4	shows	show	VERB
cana-1705	160	5	higher	high	ADJ
cana-1705	160	6	stability	stability	NOUN
cana-1705	160	7	in	in	ADP
cana-1705	160	8	traffic	traffic	NOUN
cana-1705	160	9	flow	flow	NOUN
cana-1705	160	10	prediction	prediction	NOUN
cana-1705	160	11	.	.	PUNCT
cana-1705	161	1	•	•	NUM
cana-1705	161	2	overfittin	overfittin	NOUN
cana-1705	161	3	g	g	NOUN
cana-1705	161	4	in	in	ADP
cana-1705	161	5	existing	exist	VERB
cana-1705	161	6	traffic	traffic	NOUN
cana-1705	161	7	flow	flow	NOUN
cana-1705	161	8	prediction	prediction	NOUN
cana-1705	161	9	models	model	NOUN
cana-1705	161	10	•	•	NOUN
cana-1705	161	11	lack	lack	NOUN
cana-1705	161	12	of	of	ADP
cana-1705	161	13	generalization	generalization	NOUN
cana-1705	161	14	ability	ability	NOUN
cana-1705	161	15	in	in	ADP
cana-1705	161	16	deep	deep	ADJ
cana-1705	161	17	layer	layer	NOUN
cana-1705	161	18	neural	neural	ADJ
cana-1705	161	19	networks	network	NOUN
cana-1705	161	20	table	table	NOUN
cana-1705	161	21	1	1	NUM
cana-1705	161	22	.	.	PUNCT
cana-1705	161	23	literature	literature	PROPN
cana-1705	161	24	review	review	PROPN
cana-1705	161	25	polson	polson	PROPN
cana-1705	161	26	and	and	CCONJ
cana-1705	161	27	sokolov	sokolov	PROPN
cana-1705	161	28	(	(	PUNCT
cana-1705	161	29	2017	2017	NUM
cana-1705	161	30	)	)	PUNCT
cana-1705	161	31	in	in	ADP
cana-1705	161	32	a	a	DET
cana-1705	161	33	similar	similar	ADJ
cana-1705	161	34	vein	vein	NOUN
cana-1705	161	35	experimented	experiment	VERB
cana-1705	161	36	the	the	DET
cana-1705	161	37	application	application	NOUN
cana-1705	161	38	of	of	ADP
cana-1705	161	39	deep	deep	ADJ
cana-1705	161	40	learning	learning	NOUN
cana-1705	161	41	architectures	architecture	NOUN
cana-1705	161	42	lstms	lstms	NOUN
cana-1705	161	43	are	be	AUX
cana-1705	161	44	one	one	NUM
cana-1705	161	45	variety	variety	NOUN
cana-1705	161	46	they	they	PRON
cana-1705	161	47	had	have	AUX
cana-1705	161	48	used	use	VERB
cana-1705	161	49	to	to	PART
cana-1705	161	50	forecast	forecast	VERB
cana-1705	161	51	traffic	traffic	NOUN
cana-1705	161	52	flow	flow	NOUN
cana-1705	161	53	for	for	ADP
cana-1705	161	54	metropolitan	metropolitan	ADJ
cana-1705	161	55	regions	region	NOUN
cana-1705	161	56	.	.	PUNCT
cana-1705	162	1	these	these	DET
cana-1705	162	2	works	work	NOUN
cana-1705	162	3	focus	focus	VERB
cana-1705	162	4	on	on	ADP
cana-1705	162	5	the	the	DET
cana-1705	162	6	main	main	ADJ
cana-1705	162	7	advantages	advantage	NOUN
cana-1705	162	8	of	of	ADP
cana-1705	162	9	lstm	lstm	NOUN
cana-1705	162	10	networks	network	NOUN
cana-1705	162	11	in	in	ADP
cana-1705	162	12	dealing	deal	VERB
cana-1705	162	13	with	with	ADP
cana-1705	162	14	noisy	noisy	ADJ
cana-1705	162	15	and	and	CCONJ
cana-1705	162	16	incomplete	incomplete	ADJ
cana-1705	162	17	data	datum	NOUN
cana-1705	162	18	,	,	PUNCT
cana-1705	162	19	mainly	mainly	ADV
cana-1705	162	20	due	due	ADP
cana-1705	162	21	to	to	ADP
cana-1705	162	22	sensor	sensor	NOUN
cana-1705	162	23	malfunction	malfunction	NOUN
cana-1705	162	24	or	or	CCONJ
cana-1705	162	25	delays	delay	NOUN
cana-1705	162	26	in	in	ADP
cana-1705	162	27	data	datum	NOUN
cana-1705	162	28	communication	communication	NOUN
cana-1705	162	29	,	,	PUNCT
cana-1705	162	30	which	which	PRON
cana-1705	162	31	are	be	AUX
cana-1705	162	32	common	common	ADJ
cana-1705	162	33	for	for	ADP
cana-1705	162	34	urban	urban	ADJ
cana-1705	162	35	traffic	traffic	NOUN
cana-1705	162	36	systems	system	NOUN
cana-1705	162	37	.	.	PUNCT
cana-1705	163	1	the	the	DET
cana-1705	163	2	paper	paper	NOUN
cana-1705	163	3	also	also	ADV
cana-1705	163	4	mentioned	mention	VERB
cana-1705	163	5	that	that	SCONJ
cana-1705	163	6	lstms	lstms	NOUN
cana-1705	163	7	originated	originate	VERB
cana-1705	163	8	in	in	ADP
cana-1705	163	9	this	this	DET
cana-1705	163	10	work	work	NOUN
cana-1705	163	11	can	can	AUX
cana-1705	163	12	be	be	AUX
cana-1705	163	13	expanded	expand	VERB
cana-1705	163	14	into	into	ADP
cana-1705	163	15	other	other	ADJ
cana-1705	163	16	variables	variable	NOUN
cana-1705	163	17	,	,	PUNCT
cana-1705	163	18	such	such	ADJ
cana-1705	163	19	as	as	ADP
cana-1705	163	20	weather	weather	NOUN
cana-1705	163	21	,	,	PUNCT
cana-1705	163	22	event	event	NOUN
cana-1705	163	23	of	of	ADP
cana-1705	163	24	the	the	DET
cana-1705	163	25	public	public	ADJ
cana-1705	163	26	,	,	PUNCT
cana-1705	163	27	incident	incident	NOUN
cana-1705	163	28	in	in	ADP
cana-1705	163	29	road	road	NOUN
cana-1705	163	30	and	and	CCONJ
cana-1705	163	31	so	so	ADV
cana-1705	163	32	on	on	ADV
cana-1705	163	33	,	,	PUNCT
cana-1705	163	34	which	which	PRON
cana-1705	163	35	further	far	ADV
cana-1705	163	36	promotes	promote	VERB
cana-1705	163	37	the	the	DET
cana-1705	163	38	accuracy	accuracy	NOUN
cana-1705	163	39	of	of	ADP
cana-1705	163	40	prediction	prediction	NOUN
cana-1705	163	41	.	.	PUNCT
cana-1705	164	1	d.	d.	PROPN
cana-1705	164	2	mixing	mix	VERB
cana-1705	164	3	lstm	lstm	NOUN
cana-1705	164	4	with	with	ADP
cana-1705	164	5	other	other	ADJ
cana-1705	164	6	techniques	technique	NOUN
cana-1705	164	7	.	.	PUNCT
cana-1705	165	1	hybrid	hybrid	NOUN
cana-1705	165	2	models	model	NOUN
cana-1705	165	3	although	although	SCONJ
cana-1705	165	4	lstms	lstms	NOUN
cana-1705	165	5	already	already	ADV
cana-1705	165	6	showed	show	VERB
cana-1705	165	7	great	great	ADJ
cana-1705	165	8	potential	potential	NOUN
cana-1705	165	9	,	,	PUNCT
cana-1705	165	10	they	they	PRON
cana-1705	165	11	are	be	AUX
cana-1705	165	12	currently	currently	ADV
cana-1705	165	13	being	be	AUX
cana-1705	165	14	used	use	VERB
cana-1705	165	15	in	in	ADP
cana-1705	165	16	hybrid	hybrid	ADJ
cana-1705	165	17	models	model	NOUN
cana-1705	165	18	which	which	PRON
cana-1705	165	19	combines	combine	VERB
cana-1705	165	20	lstm	lstm	NOUN
cana-1705	165	21	with	with	ADP
cana-1705	165	22	other	other	ADJ
cana-1705	165	23	methods	method	NOUN
cana-1705	165	24	to	to	PART
cana-1705	165	25	have	have	VERB
cana-1705	165	26	better	well	ADJ
cana-1705	165	27	prediction	prediction	NOUN
cana-1705	165	28	accuracy	accuracy	NOUN
cana-1705	165	29	.	.	PUNCT
cana-1705	166	1	a	a	DET
cana-1705	166	2	common	common	ADJ
cana-1705	166	3	method	method	NOUN
cana-1705	166	4	includes	include	VERB
cana-1705	166	5	combining	combine	VERB
cana-1705	166	6	convolutional	convolutional	ADJ
cana-1705	166	7	neural	neural	ADJ
cana-1705	166	8	networks	network	NOUN
cana-1705	166	9	(	(	PUNCT
cana-1705	166	10	cnns	cnns	PROPN
cana-1705	166	11	)	)	PUNCT
cana-1705	166	12	with	with	ADP
cana-1705	166	13	lstm	lstm	NOUN
cana-1705	166	14	to	to	PART
cana-1705	166	15	account	account	VERB
cana-1705	166	16	for	for	ADP
cana-1705	166	17	spatial	spatial	ADJ
cana-1705	166	18	and	and	CCONJ
cana-1705	166	19	temporal	temporal	ADJ
cana-1705	166	20	structure	structure	NOUN
cana-1705	166	21	of	of	ADP
cana-1705	166	22	traffic	traffic	NOUN
cana-1705	166	23	data	datum	NOUN
cana-1705	166	24	.	.	PUNCT
cana-1705	167	1	the	the	DET
cana-1705	167	2	flow	flow	NOUN
cana-1705	167	3	of	of	ADP
cana-1705	167	4	traffic	traffic	NOUN
cana-1705	167	5	is	be	AUX
cana-1705	167	6	related	relate	VERB
cana-1705	167	7	not	not	PART
cana-1705	167	8	only	only	ADV
cana-1705	167	9	temporally	temporally	ADV
cana-1705	167	10	(	(	PUNCT
cana-1705	167	11	say	say	INTJ
cana-1705	167	12	,	,	PUNCT
cana-1705	167	13	to	to	ADP
cana-1705	167	14	the	the	DET
cana-1705	167	15	time	time	NOUN
cana-1705	167	16	of	of	ADP
cana-1705	167	17	day	day	NOUN
cana-1705	167	18	)	)	PUNCT
cana-1705	167	19	but	but	CCONJ
cana-1705	167	20	also	also	ADV
cana-1705	167	21	spatially	spatially	ADV
cana-1705	167	22	that	that	SCONJ
cana-1705	167	23	being	be	AUX
cana-1705	167	24	between	between	ADP
cana-1705	167	25	various	various	ADJ
cana-1705	167	26	segments	segment	NOUN
cana-1705	167	27	of	of	ADP
cana-1705	167	28	roads	road	NOUN
cana-1705	167	29	.	.	PUNCT
cana-1705	168	1	one	one	NUM
cana-1705	168	2	example	example	NOUN
cana-1705	168	3	is	be	AUX
cana-1705	168	4	the	the	DET
cana-1705	168	5	ripple	ripple	ADJ
cana-1705	168	6	effect	effect	NOUN
cana-1705	168	7	that	that	PRON
cana-1705	168	8	can	can	AUX
cana-1705	168	9	happen	happen	VERB
cana-1705	168	10	if	if	SCONJ
cana-1705	168	11	one	one	NUM
cana-1705	168	12	road	road	NOUN
cana-1705	168	13	becomes	become	VERB
cana-1705	168	14	congested	congested	ADJ
cana-1705	168	15	and	and	CCONJ
cana-1705	168	16	other	other	ADJ
cana-1705	168	17	nearby	nearby	ADJ
cana-1705	168	18	roads	road	NOUN
cana-1705	168	19	get	get	VERB
cana-1705	168	20	more	more	ADJ
cana-1705	168	21	traffic	traffic	NOUN
cana-1705	168	22	.	.	PUNCT
cana-1705	169	1	cnns	cnns	PROPN
cana-1705	169	2	of	of	ADP
cana-1705	169	3	the	the	DET
cana-1705	169	4	style	style	NOUN
cana-1705	169	5	are	be	AUX
cana-1705	169	6	usually	usually	ADV
cana-1705	169	7	applied	apply	VERB
cana-1705	169	8	to	to	ADP
cana-1705	169	9	image	image	NOUN
cana-1705	169	10	processing	processing	NOUN
cana-1705	169	11	,	,	PUNCT
cana-1705	169	12	and	and	CCONJ
cana-1705	169	13	have	have	AUX
cana-1705	169	14	shown	show	VERB
cana-1705	169	15	that	that	SCONJ
cana-1705	169	16	it	it	PRON
cana-1705	169	17	is	be	AUX
cana-1705	169	18	an	an	DET
cana-1705	169	19	efficient	efficient	ADJ
cana-1705	169	20	way	way	NOUN
cana-1705	169	21	to	to	PART
cana-1705	169	22	extract	extract	VERB
cana-1705	169	23	spatial	spatial	ADJ
cana-1705	169	24	feature	feature	NOUN
cana-1705	169	25	within	within	ADP
cana-1705	169	26	road	road	NOUN
cana-1705	169	27	network	network	NOUN
cana-1705	169	28	from	from	ADP
cana-1705	169	29	grid	grid	NOUN
cana-1705	169	30	-	-	PUNCT
cana-1705	169	31	like	like	ADJ
cana-1705	169	32	representation	representation	NOUN
cana-1705	169	33	.	.	PUNCT
cana-1705	170	1	zhao	zhao	PROPN
cana-1705	170	2	et	et	PROPN
cana-1705	170	3	al	al	PROPN
cana-1705	170	4	.	.	PUNCT
cana-1705	171	1	in	in	ADP
cana-1705	171	2	[	[	X
cana-1705	171	3	24	24	NUM
cana-1705	171	4	]	]	PUNCT
cana-1705	171	5	,	,	PUNCT
cana-1705	171	6	a	a	DET
cana-1705	171	7	hybrid	hybrid	ADJ
cana-1705	171	8	model	model	NOUN
cana-1705	171	9	was	be	AUX
cana-1705	171	10	proposed	propose	VERB
cana-1705	171	11	with	with	ADP
cana-1705	171	12	cnn	cnn	PROPN
cana-1705	171	13	on	on	ADP
cana-1705	171	14	spatial	spatial	ADJ
cana-1705	171	15	features	feature	NOUN
cana-1705	171	16	and	and	CCONJ
cana-1705	171	17	lstm	lstm	NOUN
cana-1705	171	18	on	on	ADP
cana-1705	171	19	temporal	temporal	ADJ
cana-1705	171	20	sequence	sequence	NOUN
cana-1705	171	21	was	be	AUX
cana-1705	171	22	proposed	propose	VERB
cana-1705	171	23	by	by	ADP
cana-1705	171	24	(	(	PUNCT
cana-1705	171	25	2019	2019	NUM
cana-1705	171	26	)	)	PUNCT
cana-1705	171	27	.	.	PUNCT
cana-1705	172	1	experiments	experiment	NOUN
cana-1705	172	2	on	on	ADP
cana-1705	172	3	a	a	DET
cana-1705	172	4	large	large	ADJ
cana-1705	172	5	-	-	PUNCT
cana-1705	172	6	scale	scale	NOUN
cana-1705	172	7	urban	urban	ADJ
cana-1705	172	8	traffic	traffic	NOUN
cana-1705	172	9	dataset	dataset	NOUN
cana-1705	172	10	indicated	indicate	VERB
cana-1705	172	11	that	that	SCONJ
cana-1705	172	12	the	the	DET
cana-1705	172	13	ensemble	ensemble	NOUN
cana-1705	172	14	of	of	ADP
cana-1705	172	15	cnn	cnn	PROPN
cana-1705	172	16	and	and	CCONJ
cana-1705	172	17	lstm	lstm	NOUN
cana-1705	172	18	could	could	AUX
cana-1705	172	19	outperform	outperform	VERB
cana-1705	172	20	either	either	CCONJ
cana-1705	172	21	a	a	DET
cana-1705	172	22	cnn	cnn	NOUN
cana-1705	172	23	or	or	CCONJ
cana-1705	172	24	an	an	DET
cana-1705	172	25	lstm	lstm	NOUN
cana-1705	172	26	model	model	NOUN
cana-1705	172	27	when	when	SCONJ
cana-1705	172	28	used	use	VERB
cana-1705	172	29	in	in	ADP
cana-1705	172	30	isolation	isolation	NOUN
cana-1705	172	31	,	,	PUNCT
cana-1705	172	32	achieving	achieve	VERB
cana-1705	172	33	better	well	ADJ
cana-1705	172	34	accuracy	accuracy	NOUN
cana-1705	172	35	for	for	ADP
cana-1705	172	36	short	short	ADJ
cana-1705	172	37	-	-	PUNCT
cana-1705	172	38	term	term	NOUN
cana-1705	172	39	traffic	traffic	NOUN
cana-1705	172	40	prediction	prediction	NOUN
cana-1705	172	41	.	.	PUNCT
cana-1705	173	1	as	as	ADP
cana-1705	173	2	a	a	DET
cana-1705	173	3	result	result	NOUN
cana-1705	173	4	,	,	PUNCT
cana-1705	173	5	the	the	DET
cana-1705	173	6	communications	communication	NOUN
cana-1705	173	7	on	on	ADP
cana-1705	173	8	applied	apply	VERB
cana-1705	173	9	nonlinear	nonlinear	ADJ
cana-1705	173	10	analysis	analysis	NOUN
cana-1705	173	11	issn	issn	NOUN
cana-1705	173	12	:	:	PUNCT
cana-1705	173	13	1074	1074	NUM
cana-1705	173	14	-	-	PUNCT
cana-1705	173	15	133x	133x	NUM
cana-1705	173	16	vol	vol	NOUN
cana-1705	173	17	32	32	NUM
cana-1705	173	18	no	no	NOUN
cana-1705	173	19	.	.	NOUN
cana-1705	173	20	2	2	NUM
cana-1705	173	21	(	(	PUNCT
cana-1705	173	22	2025	2025	NUM
cana-1705	173	23	)	)	PUNCT
cana-1705	173	24	10	10	NUM
cana-1705	173	25	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	173	26	cnn	cnn	PROPN
cana-1705	173	27	-	-	PUNCT
cana-1705	173	28	lstm	lstm	ADJ
cana-1705	173	29	hybrid	hybrid	NOUN
cana-1705	173	30	model	model	NOUN
cana-1705	173	31	was	be	AUX
cana-1705	173	32	better	well	ADV
cana-1705	173	33	equipped	equip	VERB
cana-1705	173	34	to	to	PART
cana-1705	173	35	learn	learn	VERB
cana-1705	173	36	spatial	spatial	ADJ
cana-1705	173	37	correlations	correlation	NOUN
cana-1705	173	38	between	between	ADP
cana-1705	173	39	neighboring	neighbor	VERB
cana-1705	173	40	road	road	NOUN
cana-1705	173	41	segments	segment	NOUN
cana-1705	173	42	as	as	ADV
cana-1705	173	43	well	well	ADV
cana-1705	173	44	as	as	ADP
cana-1705	173	45	temporal	temporal	ADJ
cana-1705	173	46	dependencies	dependency	NOUN
cana-1705	173	47	and	and	CCONJ
cana-1705	173	48	provided	provide	VERB
cana-1705	173	49	more	more	ADV
cana-1705	173	50	accurate	accurate	ADJ
cana-1705	173	51	predictions	prediction	NOUN
cana-1705	173	52	even	even	ADV
cana-1705	173	53	during	during	ADP
cana-1705	173	54	sudden	sudden	ADJ
cana-1705	173	55	congestion	congestion	NOUN
cana-1705	173	56	events	event	NOUN
cana-1705	173	57	.	.	PUNCT
cana-1705	174	1	an	an	DET
cana-1705	174	2	another	another	DET
cana-1705	174	3	line	line	NOUN
cana-1705	174	4	of	of	ADP
cana-1705	174	5	research	research	NOUN
cana-1705	174	6	has	have	AUX
cana-1705	174	7	been	be	AUX
cana-1705	174	8	focused	focus	VERB
cana-1705	174	9	on	on	ADP
cana-1705	174	10	the	the	DET
cana-1705	174	11	combination	combination	NOUN
cana-1705	174	12	of	of	ADP
cana-1705	174	13	attention	attention	NOUN
cana-1705	174	14	mechanisms	mechanism	NOUN
cana-1705	174	15	and	and	CCONJ
cana-1705	174	16	lstm	lstm	NOUN
cana-1705	174	17	models	model	NOUN
cana-1705	174	18	.	.	PUNCT
cana-1705	175	1	by	by	ADP
cana-1705	175	2	paying	pay	VERB
cana-1705	175	3	attention	attention	NOUN
cana-1705	175	4	,	,	PUNCT
cana-1705	175	5	it	it	PRON
cana-1705	175	6	can	can	AUX
cana-1705	175	7	attend	attend	VERB
cana-1705	175	8	to	to	ADP
cana-1705	175	9	only	only	ADJ
cana-1705	175	10	parts	part	NOUN
cana-1705	175	11	of	of	ADP
cana-1705	175	12	the	the	DET
cana-1705	175	13	input	input	NOUN
cana-1705	175	14	sequence	sequence	NOUN
cana-1705	175	15	that	that	PRON
cana-1705	175	16	are	be	AUX
cana-1705	175	17	more	more	ADV
cana-1705	175	18	important	important	ADJ
cana-1705	175	19	for	for	ADP
cana-1705	175	20	the	the	DET
cana-1705	175	21	prediction	prediction	NOUN
cana-1705	175	22	task	task	NOUN
cana-1705	175	23	.	.	PUNCT
cana-1705	176	1	t	t	PROPN
cana-1705	176	2	ts	ts	PROPN
cana-1705	176	3	refers	refer	VERB
cana-1705	176	4	to	to	ADP
cana-1705	176	5	critical	critical	ADJ
cana-1705	176	6	time	time	NOUN
cana-1705	176	7	intervals	interval	NOUN
cana-1705	176	8	(	(	PUNCT
cana-1705	176	9	or	or	CCONJ
cana-1705	176	10	road	road	NOUN
cana-1705	176	11	segments	segment	NOUN
cana-1705	176	12	)	)	PUNCT
cana-1705	176	13	that	that	PRON
cana-1705	176	14	have	have	VERB
cana-1705	176	15	a	a	DET
cana-1705	176	16	nonproportional	nonproportional	ADJ
cana-1705	176	17	effect	effect	NOUN
cana-1705	176	18	on	on	ADP
cana-1705	176	19	the	the	DET
cana-1705	176	20	future	future	ADJ
cana-1705	176	21	traffic	traffic	NOUN
cana-1705	176	22	condition	condition	NOUN
cana-1705	176	23	as	as	SCONJ
cana-1705	176	24	used	use	VERB
cana-1705	176	25	in	in	ADP
cana-1705	176	26	traffic	traffic	NOUN
cana-1705	176	27	prediction	prediction	NOUN
cana-1705	176	28	.	.	PUNCT
cana-1705	177	1	a	a	DET
cana-1705	177	2	study	study	NOUN
cana-1705	177	3	by	by	ADP
cana-1705	177	4	ke	ke	PROPN
cana-1705	177	5	et	et	PROPN
cana-1705	177	6	al	al	PROPN
cana-1705	177	7	.	.	PROPN
cana-1705	178	1	in	in	ADP
cana-1705	178	2	the	the	DET
cana-1705	178	3	field	field	NOUN
cana-1705	178	4	of	of	ADP
cana-1705	178	5	traffic	traffic	NOUN
cana-1705	178	6	prediction	prediction	NOUN
cana-1705	178	7	,	,	PUNCT
cana-1705	178	8	an	an	DET
cana-1705	178	9	lstm	lstm	NOUN
cana-1705	178	10	-	-	PUNCT
cana-1705	178	11	based	base	VERB
cana-1705	178	12	method	method	NOUN
cana-1705	178	13	has	have	AUX
cana-1705	178	14	been	be	AUX
cana-1705	178	15	improved	improve	VERB
cana-1705	178	16	with	with	ADP
cana-1705	178	17	attention	attention	NOUN
cana-1705	178	18	,	,	PUNCT
cana-1705	178	19	and	and	CCONJ
cana-1705	178	20	consequently	consequently	ADV
cana-1705	178	21	the	the	DET
cana-1705	178	22	prediction	prediction	NOUN
cana-1705	178	23	accuracy	accuracy	NOUN
cana-1705	178	24	has	have	AUX
cana-1705	178	25	dramatically	dramatically	ADV
cana-1705	178	26	changed	change	VERB
cana-1705	178	27	,	,	PUNCT
cana-1705	178	28	especially	especially	ADV
cana-1705	178	29	in	in	ADP
cana-1705	178	30	clogged	clogged	ADJ
cana-1705	178	31	urban	urban	ADJ
cana-1705	178	32	regions	region	NOUN
cana-1705	178	33	where	where	SCONJ
cana-1705	178	34	traffic	traffic	NOUN
cana-1705	178	35	plans	plan	NOUN
cana-1705	178	36	are	be	AUX
cana-1705	178	37	sporadic	sporadic	ADJ
cana-1705	178	38	[	[	X
cana-1705	178	39	19	19	NUM
cana-1705	178	40	]	]	PUNCT
cana-1705	178	41	(	(	PUNCT
cana-1705	178	42	2018	2018	NUM
cana-1705	178	43	)	)	PUNCT
cana-1705	178	44	.	.	PUNCT
cana-1705	179	1	e.	e.	PROPN
cana-1705	179	2	real	real	ADJ
cana-1705	179	3	-	-	PUNCT
cana-1705	179	4	time	time	NOUN
cana-1705	179	5	traffic	traffic	NOUN
cana-1705	179	6	management	management	NOUN
cana-1705	179	7	system	system	NOUN
cana-1705	179	8	using	use	VERB
cana-1705	179	9	lstm	lstm	ADJ
cana-1705	179	10	networks	network	NOUN
cana-1705	179	11	one	one	NUM
cana-1705	179	12	of	of	ADP
cana-1705	179	13	the	the	DET
cana-1705	179	14	examples	example	NOUN
cana-1705	179	15	where	where	SCONJ
cana-1705	179	16	lstm	lstm	ADJ
cana-1705	179	17	networks	network	NOUN
cana-1705	179	18	have	have	AUX
cana-1705	179	19	been	be	AUX
cana-1705	179	20	applied	apply	VERB
cana-1705	179	21	is	be	AUX
cana-1705	179	22	in	in	ADP
cana-1705	179	23	real	real	ADJ
cana-1705	179	24	-	-	PUNCT
cana-1705	179	25	time	time	NOUN
cana-1705	179	26	traffic	traffic	NOUN
cana-1705	179	27	flow	flow	NOUN
cana-1705	179	28	prediction	prediction	NOUN
cana-1705	179	29	which	which	PRON
cana-1705	179	30	has	have	VERB
cana-1705	179	31	various	various	ADJ
cana-1705	179	32	application	application	NOUN
cana-1705	179	33	in	in	ADP
cana-1705	179	34	modern	modern	ADJ
cana-1705	179	35	traffic	traffic	NOUN
cana-1705	179	36	management	management	NOUN
cana-1705	179	37	systems	system	NOUN
cana-1705	179	38	.	.	PUNCT
cana-1705	180	1	one	one	NUM
cana-1705	180	2	of	of	ADP
cana-1705	180	3	the	the	DET
cana-1705	180	4	most	most	ADV
cana-1705	180	5	important	important	ADJ
cana-1705	180	6	use	use	NOUN
cana-1705	180	7	cases	case	NOUN
cana-1705	180	8	is	be	AUX
cana-1705	180	9	dynamic	dynamic	ADJ
cana-1705	180	10	routing	routing	NOUN
cana-1705	180	11	,	,	PUNCT
cana-1705	180	12	where	where	SCONJ
cana-1705	180	13	real	real	ADJ
cana-1705	180	14	time	time	NOUN
cana-1705	180	15	predictions	prediction	NOUN
cana-1705	180	16	allows	allow	VERB
cana-1705	180	17	for	for	ADP
cana-1705	180	18	better	well	ADJ
cana-1705	180	19	suggestions	suggestion	NOUN
cana-1705	180	20	in	in	ADP
cana-1705	180	21	terms	term	NOUN
cana-1705	180	22	of	of	ADP
cana-1705	180	23	lane	lane	NOUN
cana-1705	180	24	assignment	assignment	NOUN
cana-1705	180	25	that	that	PRON
cana-1705	180	26	improves	improve	VERB
cana-1705	180	27	drivers	driver	NOUN
cana-1705	180	28	experience	experience	NOUN
cana-1705	180	29	from	from	ADP
cana-1705	180	30	recommender	recommender	NOUN
cana-1705	180	31	systems	system	NOUN
cana-1705	180	32	concerning	concern	VERB
cana-1705	180	33	current	current	ADJ
cana-1705	180	34	traffic	traffic	NOUN
cana-1705	180	35	and	and	CCONJ
cana-1705	180	36	forecasted	forecast	VERB
cana-1705	180	37	traffic	traffic	NOUN
cana-1705	180	38	conditions	condition	NOUN
cana-1705	180	39	.	.	PUNCT
cana-1705	181	1	yang	yang	PROPN
cana-1705	181	2	et	et	PROPN
cana-1705	181	3	al	al	PROPN
cana-1705	181	4	.	.	PUNCT
cana-1705	182	1	in	in	ADP
cana-1705	182	2	(	(	PUNCT
cana-1705	182	3	2019	2019	NUM
cana-1705	182	4	)	)	PUNCT
cana-1705	182	5	in	in	ADP
cana-1705	182	6	the	the	DET
cana-1705	182	7	field	field	NOUN
cana-1705	182	8	of	of	ADP
cana-1705	182	9	travel	travel	NOUN
cana-1705	182	10	speed	speed	NOUN
cana-1705	182	11	forecasting	forecasting	NOUN
cana-1705	182	12	applied	apply	VERB
cana-1705	182	13	an	an	DET
cana-1705	182	14	lstm	lstm	ADJ
cana-1705	182	15	approach	approach	NOUN
cana-1705	182	16	to	to	ADP
cana-1705	182	17	a	a	DET
cana-1705	182	18	traffic	traffic	NOUN
cana-1705	182	19	prediction	prediction	NOUN
cana-1705	182	20	system	system	NOUN
cana-1705	182	21	that	that	PRON
cana-1705	182	22	specializes	specialize	VERB
cana-1705	182	23	in	in	ADP
cana-1705	182	24	route	route	NOUN
cana-1705	182	25	planning	planning	NOUN
cana-1705	182	26	and	and	CCONJ
cana-1705	182	27	can	can	AUX
cana-1705	182	28	adjust	adjust	VERB
cana-1705	182	29	predictions	prediction	NOUN
cana-1705	182	30	with	with	ADP
cana-1705	182	31	incoming	incoming	ADJ
cana-1705	182	32	real	real	ADJ
cana-1705	182	33	-	-	PUNCT
cana-1705	182	34	time	time	NOUN
cana-1705	182	35	inputs	input	NOUN
cana-1705	182	36	,	,	PUNCT
cana-1705	182	37	leading	lead	VERB
cana-1705	182	38	to	to	ADP
cana-1705	182	39	quite	quite	ADV
cana-1705	182	40	impressive	impressive	ADJ
cana-1705	182	41	reduction	reduction	NOUN
cana-1705	182	42	of	of	ADP
cana-1705	182	43	traffic	traffic	NOUN
cana-1705	182	44	congestion	congestion	NOUN
cana-1705	182	45	time	time	NOUN
cana-1705	182	46	across	across	ADP
cana-1705	182	47	wider	wide	ADJ
cana-1705	182	48	metropolitan	metropolitan	ADJ
cana-1705	182	49	area	area	NOUN
cana-1705	182	50	.	.	PUNCT
cana-1705	183	1	it	it	PRON
cana-1705	183	2	helped	help	VERB
cana-1705	183	3	drivers	driver	NOUN
cana-1705	183	4	plan	plan	VERB
cana-1705	183	5	their	their	PRON
cana-1705	183	6	route	route	NOUN
cana-1705	183	7	by	by	ADP
cana-1705	183	8	suggesting	suggest	VERB
cana-1705	183	9	recently	recently	ADV
cana-1705	183	10	updated	update	VERB
cana-1705	183	11	routes	route	NOUN
cana-1705	183	12	based	base	VERB
cana-1705	183	13	on	on	ADP
cana-1705	183	14	real	real	ADJ
cana-1705	183	15	traffic	traffic	NOUN
cana-1705	183	16	data	datum	NOUN
cana-1705	183	17	,	,	PUNCT
cana-1705	183	18	encouraging	encourage	VERB
cana-1705	183	19	the	the	DET
cana-1705	183	20	avoidance	avoidance	NOUN
cana-1705	183	21	of	of	ADP
cana-1705	183	22	congested	congested	ADJ
cana-1705	183	23	regions	region	NOUN
cana-1705	183	24	,	,	PUNCT
cana-1705	183	25	and	and	CCONJ
cana-1705	183	26	consequently	consequently	ADV
cana-1705	183	27	reducing	reduce	VERB
cana-1705	183	28	congestion	congestion	NOUN
cana-1705	183	29	in	in	ADP
cana-1705	183	30	the	the	DET
cana-1705	183	31	system	system	NOUN
cana-1705	183	32	as	as	ADP
cana-1705	183	33	a	a	DET
cana-1705	183	34	whole[22	whole[22	NOUN
cana-1705	183	35	]	]	PUNCT
cana-1705	183	36	.	.	PUNCT
cana-1705	184	1	also	also	ADV
cana-1705	184	2	,	,	PUNCT
cana-1705	184	3	it	it	PRON
cana-1705	184	4	is	be	AUX
cana-1705	184	5	used	use	VERB
cana-1705	184	6	for	for	ADP
cana-1705	184	7	adaptive	adaptive	ADJ
cana-1705	184	8	traffic	traffic	NOUN
cana-1705	184	9	signal	signal	NOUN
cana-1705	184	10	control	control	NOUN
cana-1705	184	11	.	.	PUNCT
cana-1705	185	1	traditional	traditional	ADJ
cana-1705	185	2	traffic	traffic	NOUN
cana-1705	185	3	signals	signal	NOUN
cana-1705	185	4	are	be	AUX
cana-1705	185	5	based	base	VERB
cana-1705	185	6	on	on	ADP
cana-1705	185	7	fixed	fix	VERB
cana-1705	185	8	schedules	schedule	NOUN
cana-1705	185	9	that	that	PRON
cana-1705	185	10	do	do	AUX
cana-1705	185	11	not	not	PART
cana-1705	185	12	take	take	VERB
cana-1705	185	13	into	into	ADP
cana-1705	185	14	consideration	consideration	NOUN
cana-1705	185	15	the	the	DET
cana-1705	185	16	actual	actual	ADJ
cana-1705	185	17	dynamic	dynamic	ADJ
cana-1705	185	18	changes	change	NOUN
cana-1705	185	19	in	in	ADP
cana-1705	185	20	the	the	DET
cana-1705	185	21	flow	flow	NOUN
cana-1705	185	22	of	of	ADP
cana-1705	185	23	traffic	traffic	NOUN
cana-1705	185	24	.	.	PUNCT
cana-1705	186	1	using	use	VERB
cana-1705	186	2	traffic	traffic	NOUN
cana-1705	186	3	predictions	prediction	NOUN
cana-1705	186	4	built	build	VERB
cana-1705	186	5	off	off	ADP
cana-1705	186	6	lstm	lstm	PROPN
cana-1705	186	7	,	,	PUNCT
cana-1705	186	8	the	the	DET
cana-1705	186	9	time	time	NOUN
cana-1705	186	10	length	length	NOUN
cana-1705	186	11	of	of	ADP
cana-1705	186	12	green	green	ADJ
cana-1705	186	13	lights	light	NOUN
cana-1705	186	14	can	can	AUX
cana-1705	186	15	be	be	AUX
cana-1705	186	16	adjusted	adjust	VERB
cana-1705	186	17	on	on	ADP
cana-1705	186	18	-	-	PUNCT
cana-1705	186	19	the	the	DET
cana-1705	186	20	-	-	PUNCT
cana-1705	186	21	fly	fly	NOUN
cana-1705	186	22	based	base	VERB
cana-1705	186	23	on	on	ADP
cana-1705	186	24	predicted	predict	VERB
cana-1705	186	25	traffic	traffic	NOUN
cana-1705	186	26	patterns	pattern	NOUN
cana-1705	186	27	to	to	PART
cana-1705	186	28	minimize	minimize	VERB
cana-1705	186	29	idle	idle	ADJ
cana-1705	186	30	times	time	NOUN
cana-1705	186	31	at	at	ADP
cana-1705	186	32	intersections	intersection	NOUN
cana-1705	186	33	and	and	CCONJ
cana-1705	186	34	file_down_fluxes	file_down_fluxe	NOUN
cana-1705	186	35	across	across	ADP
cana-1705	186	36	a	a	DET
cana-1705	186	37	city	city	NOUN
cana-1705	186	38	.	.	PUNCT
cana-1705	187	1	a	a	DET
cana-1705	187	2	study	study	NOUN
cana-1705	187	3	by	by	ADP
cana-1705	187	4	wei	wei	PROPN
cana-1705	187	5	et	et	PROPN
cana-1705	187	6	al	al	PROPN
cana-1705	187	7	.	.	PUNCT
cana-1705	188	1	[	[	X
cana-1705	188	2	21](2020	21](2020	X
cana-1705	188	3	)	)	PUNCT
cana-1705	188	4	achieved	achieve	VERB
cana-1705	188	5	substantial	substantial	ADJ
cana-1705	188	6	reductions	reduction	NOUN
cana-1705	188	7	in	in	ADP
cana-1705	188	8	vehicle	vehicle	NOUN
cana-1705	188	9	delay	delay	NOUN
cana-1705	188	10	and	and	CCONJ
cana-1705	188	11	fuel	fuel	NOUN
cana-1705	188	12	consumption	consumption	NOUN
cana-1705	188	13	during	during	ADP
cana-1705	188	14	peak	peak	NOUN
cana-1705	188	15	traffic	traffic	NOUN
cana-1705	188	16	times	time	NOUN
cana-1705	188	17	by	by	ADP
cana-1705	188	18	incorporating	incorporate	VERB
cana-1705	188	19	lstm	lstm	ADJ
cana-1705	188	20	predictions	prediction	NOUN
cana-1705	188	21	in	in	ADP
cana-1705	188	22	an	an	DET
cana-1705	188	23	online	online	ADJ
cana-1705	188	24	adaptive	adaptive	ADJ
cana-1705	188	25	traffic	traffic	NOUN
cana-1705	188	26	signal	signal	NOUN
cana-1705	188	27	control	control	NOUN
cana-1705	188	28	system	system	NOUN
cana-1705	188	29	.	.	PUNCT
cana-1705	189	1	by	by	ADP
cana-1705	189	2	the	the	DET
cana-1705	189	3	same	same	ADJ
cana-1705	189	4	token	token	ADJ
cana-1705	189	5	,	,	PUNCT
cana-1705	189	6	lstms	lstms	NOUN
cana-1705	189	7	have	have	AUX
cana-1705	189	8	been	be	AUX
cana-1705	189	9	used	use	VERB
cana-1705	189	10	in	in	ADP
cana-1705	189	11	ride	ride	NOUN
cana-1705	189	12	-	-	PUNCT
cana-1705	189	13	sharing	share	VERB
cana-1705	189	14	services	service	NOUN
cana-1705	189	15	or	or	CCONJ
cana-1705	189	16	in	in	ADP
cana-1705	189	17	public	public	ADJ
cana-1705	189	18	transport	transport	NOUN
cana-1705	189	19	systems	system	NOUN
cana-1705	189	20	.	.	PUNCT
cana-1705	190	1	alongside	alongside	ADP
cana-1705	190	2	rapid	rapid	ADJ
cana-1705	190	3	transit	transit	NOUN
cana-1705	190	4	cities	city	NOUN
cana-1705	190	5	,	,	PUNCT
cana-1705	190	6	ridesharing	ridesharing	NOUN
cana-1705	190	7	companies	company	NOUN
cana-1705	190	8	like	like	ADP
cana-1705	190	9	uber	uber	NOUN
cana-1705	190	10	and	and	CCONJ
cana-1705	190	11	lyft	lyft	NOUN
cana-1705	190	12	use	use	VERB
cana-1705	190	13	traffic	traffic	NOUN
cana-1705	190	14	predictions	prediction	NOUN
cana-1705	190	15	to	to	PART
cana-1705	190	16	calculate	calculate	VERB
cana-1705	190	17	time	time	NOUN
cana-1705	190	18	of	of	ADP
cana-1705	190	19	arrival	arrival	NOUN
cana-1705	190	20	and	and	CCONJ
cana-1705	190	21	schedule	schedule	VERB
cana-1705	190	22	the	the	DET
cana-1705	190	23	optimal	optimal	ADJ
cana-1705	190	24	task	task	NOUN
cana-1705	190	25	for	for	ADP
cana-1705	190	26	drivers	driver	NOUN
cana-1705	190	27	.	.	PUNCT
cana-1705	191	1	lstm	lstm	NOUN
cana-1705	191	2	models	model	NOUN
cana-1705	191	3	can	can	AUX
cana-1705	191	4	make	make	VERB
cana-1705	191	5	those	those	DET
cana-1705	191	6	platforms	platform	NOUN
cana-1705	191	7	better	well	ADV
cana-1705	191	8	in	in	ADP
cana-1705	191	9	predicting	predict	VERB
cana-1705	191	10	real	real	ADJ
cana-1705	191	11	-	-	PUNCT
cana-1705	191	12	time	time	NOUN
cana-1705	191	13	traffic	traffic	NOUN
cana-1705	191	14	more	more	ADV
cana-1705	191	15	accurately	accurately	ADV
cana-1705	191	16	,	,	PUNCT
cana-1705	191	17	which	which	PRON
cana-1705	191	18	will	will	AUX
cana-1705	191	19	be	be	AUX
cana-1705	191	20	fundamental	fundamental	ADJ
cana-1705	191	21	to	to	PART
cana-1705	191	22	establish	establish	VERB
cana-1705	191	23	the	the	DET
cana-1705	191	24	best	good	ADJ
cana-1705	191	25	route	route	NOUN
cana-1705	191	26	planning	planning	NOUN
cana-1705	191	27	or	or	CCONJ
cana-1705	191	28	pricing	pricing	NOUN
cana-1705	191	29	adjustments	adjustment	NOUN
cana-1705	191	30	.	.	PUNCT
cana-1705	192	1	public	public	ADJ
cana-1705	192	2	transportation	transportation	NOUN
cana-1705	192	3	systems	system	NOUN
cana-1705	192	4	similarly	similarly	ADV
cana-1705	192	5	benefit	benefit	VERB
cana-1705	192	6	from	from	ADP
cana-1705	192	7	precise	precise	ADJ
cana-1705	192	8	traffic	traffic	NOUN
cana-1705	192	9	predictions	prediction	NOUN
cana-1705	192	10	,	,	PUNCT
cana-1705	192	11	able	able	ADJ
cana-1705	192	12	to	to	PART
cana-1705	192	13	adapt	adapt	VERB
cana-1705	192	14	bus	bus	NOUN
cana-1705	192	15	schedules	schedule	NOUN
cana-1705	192	16	and	and	CCONJ
cana-1705	192	17	routes	route	NOUN
cana-1705	192	18	based	base	VERB
cana-1705	192	19	on	on	ADP
cana-1705	192	20	forecasted	forecast	VERB
cana-1705	192	21	traffic	traffic	NOUN
cana-1705	192	22	,	,	PUNCT
cana-1705	192	23	making	make	VERB
cana-1705	192	24	service	service	NOUN
cana-1705	192	25	more	more	ADV
cana-1705	192	26	reliable	reliable	ADJ
cana-1705	192	27	and	and	CCONJ
cana-1705	192	28	passengers	passenger	NOUN
cana-1705	192	29	happier	happy	ADJ
cana-1705	192	30	in	in	ADP
cana-1705	192	31	the	the	DET
cana-1705	192	32	process	process	NOUN
cana-1705	192	33	.	.	PUNCT
cana-1705	193	1	f.	f.	PROPN
cana-1705	193	2	discussion	discussion	PROPN
cana-1705	193	3	:	:	PUNCT
cana-1705	193	4	obstacles	obstacle	NOUN
cana-1705	193	5	and	and	CCONJ
cana-1705	193	6	prospects	prospect	NOUN
cana-1705	193	7	on	on	ADP
cana-1705	193	8	lstm	lstm	ADJ
cana-1705	193	9	traffic	traffic	NOUN
cana-1705	193	10	prediction	prediction	NOUN
cana-1705	193	11	while	while	SCONJ
cana-1705	193	12	lstm	lstm	ADJ
cana-1705	193	13	networks	network	NOUN
cana-1705	193	14	have	have	AUX
cana-1705	193	15	shown	show	VERB
cana-1705	193	16	great	great	ADJ
cana-1705	193	17	promise	promise	NOUN
cana-1705	193	18	for	for	ADP
cana-1705	193	19	traffic	traffic	NOUN
cana-1705	193	20	flow	flow	NOUN
cana-1705	193	21	prediction	prediction	NOUN
cana-1705	193	22	,	,	PUNCT
cana-1705	193	23	there	there	PRON
cana-1705	193	24	are	be	VERB
cana-1705	193	25	several	several	ADJ
cana-1705	193	26	difficulties	difficulty	NOUN
cana-1705	193	27	yet	yet	ADV
cana-1705	193	28	to	to	PART
cana-1705	193	29	tackle	tackle	VERB
cana-1705	193	30	.	.	PUNCT
cana-1705	194	1	the	the	DET
cana-1705	194	2	biggest	big	ADJ
cana-1705	194	3	one	one	NOUN
cana-1705	194	4	is	be	AUX
cana-1705	194	5	the	the	DET
cana-1705	194	6	quality	quality	NOUN
cana-1705	194	7	of	of	ADP
cana-1705	194	8	the	the	DET
cana-1705	194	9	data	datum	NOUN
cana-1705	194	10	.	.	PUNCT
cana-1705	195	1	since	since	SCONJ
cana-1705	195	2	many	many	ADJ
cana-1705	195	3	traffic	traffic	NOUN
cana-1705	195	4	data	datum	NOUN
cana-1705	195	5	are	be	AUX
cana-1705	195	6	incomplete	incomplete	ADJ
cana-1705	195	7	or	or	CCONJ
cana-1705	195	8	noisy	noisy	ADJ
cana-1705	195	9	,	,	PUNCT
cana-1705	195	10	caused	cause	VERB
cana-1705	195	11	by	by	ADP
cana-1705	195	12	sensor	sensor	NOUN
cana-1705	195	13	errors	error	NOUN
cana-1705	195	14	if	if	SCONJ
cana-1705	195	15	data	datum	NOUN
cana-1705	195	16	is	be	AUX
cana-1705	195	17	provided	provide	VERB
cana-1705	195	18	remotely	remotely	ADV
cana-1705	195	19	under	under	ADP
cana-1705	195	20	transmitted	transmit	VERB
cana-1705	195	21	conditions	condition	NOUN
cana-1705	195	22	,	,	PUNCT
cana-1705	195	23	name	name	VERB
cana-1705	195	24	a	a	DET
cana-1705	195	25	few	few	ADJ
cana-1705	195	26	.	.	PUNCT
cana-1705	196	1	though	though	SCONJ
cana-1705	196	2	lstms	lstms	NOUN
cana-1705	196	3	can	can	AUX
cana-1705	196	4	deal	deal	VERB
cana-1705	196	5	with	with	ADP
cana-1705	196	6	noisy	noisy	ADJ
cana-1705	196	7	data	datum	NOUN
cana-1705	196	8	to	to	ADP
cana-1705	196	9	some	some	DET
cana-1705	196	10	extent	extent	NOUN
cana-1705	196	11	but	but	CCONJ
cana-1705	196	12	sometimes	sometimes	ADV
cana-1705	196	13	communications	communication	NOUN
cana-1705	196	14	on	on	ADP
cana-1705	196	15	applied	apply	VERB
cana-1705	196	16	nonlinear	nonlinear	ADJ
cana-1705	196	17	analysis	analysis	NOUN
cana-1705	196	18	issn	issn	NOUN
cana-1705	196	19	:	:	PUNCT
cana-1705	196	20	1074	1074	NUM
cana-1705	196	21	-	-	PUNCT
cana-1705	196	22	133x	133x	NUM
cana-1705	196	23	vol	vol	NOUN
cana-1705	196	24	32	32	NUM
cana-1705	196	25	no	no	NOUN
cana-1705	196	26	.	.	NOUN
cana-1705	196	27	2	2	NUM
cana-1705	196	28	(	(	PUNCT
cana-1705	196	29	2025	2025	NUM
cana-1705	196	30	)	)	PUNCT
cana-1705	196	31	11	11	NUM
cana-1705	196	32	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	196	33	predictive	predictive	ADJ
cana-1705	196	34	accuracy	accuracy	NOUN
cana-1705	196	35	may	may	AUX
cana-1705	196	36	depend	depend	VERB
cana-1705	196	37	on	on	ADP
cana-1705	196	38	missing	missing	ADJ
cana-1705	196	39	or	or	CCONJ
cana-1705	196	40	incorrect	incorrect	ADJ
cana-1705	196	41	information	information	NOUN
cana-1705	196	42	reaching	reach	VERB
cana-1705	196	43	the	the	DET
cana-1705	196	44	model	model	NOUN
cana-1705	196	45	.	.	PUNCT
cana-1705	197	1	our	our	PRON
cana-1705	197	2	future	future	ADJ
cana-1705	197	3	work	work	NOUN
cana-1705	197	4	includes	include	VERB
cana-1705	197	5	the	the	DET
cana-1705	197	6	development	development	NOUN
cana-1705	197	7	of	of	ADP
cana-1705	197	8	data	datum	NOUN
cana-1705	197	9	preprocessing	preprocesse	VERB
cana-1705	197	10	schemes	scheme	NOUN
cana-1705	197	11	to	to	AUX
cana-1705	197	12	more	more	ADV
cana-1705	197	13	effectively	effectively	ADV
cana-1705	197	14	deal	deal	VERB
cana-1705	197	15	with	with	ADP
cana-1705	197	16	missing	missing	ADJ
cana-1705	197	17	or	or	CCONJ
cana-1705	197	18	corrupt	corrupt	ADJ
cana-1705	197	19	data	datum	NOUN
cana-1705	197	20	(	(	PUNCT
cana-1705	197	21	e.g.	e.g.	ADV
cana-1705	197	22	,	,	PUNCT
cana-1705	197	23	by	by	ADP
cana-1705	197	24	means	mean	NOUN
cana-1705	197	25	of	of	ADP
cana-1705	197	26	data	datum	NOUN
cana-1705	197	27	augmentation	augmentation	NOUN
cana-1705	197	28	or	or	CCONJ
cana-1705	197	29	imputation	imputation	NOUN
cana-1705	197	30	strategies	strategy	NOUN
cana-1705	197	31	)	)	PUNCT
cana-1705	197	32	.	.	PUNCT
cana-1705	198	1	the	the	DET
cana-1705	198	2	scalability	scalability	NOUN
cana-1705	198	3	of	of	ADP
cana-1705	198	4	lstm	lstm	NOUN
cana-1705	198	5	models	model	NOUN
cana-1705	198	6	is	be	AUX
cana-1705	198	7	another	another	DET
cana-1705	198	8	challenge	challenge	NOUN
cana-1705	198	9	.	.	PUNCT
cana-1705	199	1	urban	urban	ADJ
cana-1705	199	2	traffic	traffic	NOUN
cana-1705	199	3	systems	system	NOUN
cana-1705	199	4	consist	consist	VERB
cana-1705	199	5	of	of	ADP
cana-1705	199	6	a	a	DET
cana-1705	199	7	large	large	ADJ
cana-1705	199	8	and	and	CCONJ
cana-1705	199	9	complex	complex	ADJ
cana-1705	199	10	network	network	NOUN
cana-1705	199	11	with	with	ADP
cana-1705	199	12	thousands	thousand	NOUN
cana-1705	199	13	of	of	ADP
cana-1705	199	14	road	road	NOUN
cana-1705	199	15	segments	segment	NOUN
cana-1705	199	16	and	and	CCONJ
cana-1705	199	17	junctions	junction	NOUN
cana-1705	199	18	,	,	PUNCT
cana-1705	199	19	all	all	PRON
cana-1705	199	20	interacting	interact	VERB
cana-1705	199	21	in	in	ADP
cana-1705	199	22	real	real	ADJ
cana-1705	199	23	-	-	PUNCT
cana-1705	199	24	time	time	NOUN
cana-1705	199	25	.	.	PUNCT
cana-1705	200	1	for	for	ADP
cana-1705	200	2	example	example	NOUN
cana-1705	200	3	,	,	PUNCT
cana-1705	200	4	scaling	scale	VERB
cana-1705	200	5	lstm	lstm	NOUN
cana-1705	200	6	-	-	PUNCT
cana-1705	200	7	based	base	VERB
cana-1705	200	8	models	model	NOUN
cana-1705	200	9	to	to	PART
cana-1705	200	10	predict	predict	VERB
cana-1705	200	11	traffic	traffic	NOUN
cana-1705	200	12	flow	flow	NOUN
cana-1705	200	13	across	across	ADP
cana-1705	200	14	entire	entire	ADJ
cana-1705	200	15	cities	city	NOUN
cana-1705	200	16	have	have	AUX
cana-1705	200	17	been	be	AUX
cana-1705	200	18	computationally	computationally	ADV
cana-1705	200	19	prohibitive	prohibitive	ADJ
cana-1705	200	20	for	for	ADP
cana-1705	200	21	real	real	ADJ
cana-1705	200	22	-	-	PUNCT
cana-1705	200	23	time	time	NOUN
cana-1705	200	24	predictions	prediction	NOUN
cana-1705	200	25	.	.	PUNCT
cana-1705	201	1	advancements	advancement	NOUN
cana-1705	201	2	in	in	ADP
cana-1705	201	3	distributed	distribute	VERB
cana-1705	201	4	computing	computing	NOUN
cana-1705	201	5	and	and	CCONJ
cana-1705	201	6	parallel	parallel	ADJ
cana-1705	201	7	processing	processing	NOUN
cana-1705	201	8	could	could	AUX
cana-1705	201	9	help	help	VERB
cana-1705	201	10	to	to	PART
cana-1705	201	11	tackle	tackle	VERB
cana-1705	201	12	these	these	DET
cana-1705	201	13	scalability	scalability	NOUN
cana-1705	201	14	issues	issue	NOUN
cana-1705	201	15	,	,	PUNCT
cana-1705	201	16	providing	provide	VERB
cana-1705	201	17	more	more	ADV
cana-1705	201	18	efficient	efficient	ADJ
cana-1705	201	19	real	real	ADJ
cana-1705	201	20	-	-	PUNCT
cana-1705	201	21	time	time	NOUN
cana-1705	201	22	traffic	traffic	NOUN
cana-1705	201	23	predictions	prediction	NOUN
cana-1705	201	24	over	over	ADP
cana-1705	201	25	an	an	DET
cana-1705	201	26	urban	urban	ADJ
cana-1705	201	27	scale	scale	NOUN
cana-1705	201	28	network[16	network[16	NOUN
cana-1705	201	29	-	-	SYM
cana-1705	201	30	18	18	NUM
cana-1705	201	31	]	]	PUNCT
cana-1705	201	32	.	.	PUNCT
cana-1705	202	1	last	last	ADJ
cana-1705	202	2	but	but	CCONJ
cana-1705	202	3	not	not	PART
cana-1705	202	4	least	least	ADJ
cana-1705	202	5	,	,	PUNCT
cana-1705	202	6	the	the	DET
cana-1705	202	7	research	research	NOUN
cana-1705	202	8	area	area	NOUN
cana-1705	202	9	integrating	integrate	VERB
cana-1705	202	10	outside	outside	ADP
cana-1705	202	11	information	information	NOUN
cana-1705	202	12	(	(	PUNCT
cana-1705	202	13	e.	e.	PROPN
cana-1705	202	14	g.	g.	PROPN
cana-1705	202	15	,	,	PUNCT
cana-1705	202	16	weather	weather	NOUN
cana-1705	202	17	,	,	PUNCT
cana-1705	202	18	public	public	ADJ
cana-1705	202	19	events	event	NOUN
cana-1705	202	20	,	,	PUNCT
cana-1705	202	21	social	social	ADJ
cana-1705	202	22	media	medium	NOUN
cana-1705	202	23	data	datum	NOUN
cana-1705	202	24	)	)	PUNCT
cana-1705	202	25	into	into	ADP
cana-1705	202	26	lstm	lstm	NOUN
cana-1705	202	27	models	model	NOUN
cana-1705	202	28	needs	need	VERB
cana-1705	202	29	the	the	DET
cana-1705	202	30	concentrated	concentrated	ADJ
cana-1705	202	31	efforts	effort	NOUN
cana-1705	202	32	of	of	ADP
cana-1705	202	33	researchers	researcher	NOUN
cana-1705	202	34	.	.	PUNCT
cana-1705	203	1	while	while	SCONJ
cana-1705	203	2	existing	exist	VERB
cana-1705	203	3	research	research	NOUN
cana-1705	203	4	has	have	AUX
cana-1705	203	5	shown	show	VERB
cana-1705	203	6	several	several	ADJ
cana-1705	203	7	possible	possible	ADJ
cana-1705	203	8	avenues	avenue	NOUN
cana-1705	203	9	of	of	ADP
cana-1705	203	10	including	include	VERB
cana-1705	203	11	these	these	DET
cana-1705	203	12	factors	factor	NOUN
cana-1705	203	13	,	,	PUNCT
cana-1705	203	14	there	there	PRON
cana-1705	203	15	is	be	VERB
cana-1705	203	16	still	still	ADV
cana-1705	203	17	room	room	NOUN
cana-1705	203	18	for	for	ADP
cana-1705	203	19	significant	significant	ADJ
cana-1705	203	20	improvement	improvement	NOUN
cana-1705	203	21	to	to	ADP
cana-1705	203	22	both	both	DET
cana-1705	203	23	models	model	NOUN
cana-1705	203	24	which	which	PRON
cana-1705	203	25	can	can	AUX
cana-1705	203	26	take	take	VERB
cana-1705	203	27	information	information	NOUN
cana-1705	203	28	from	from	ADP
cana-1705	203	29	disparate	disparate	ADJ
cana-1705	203	30	sources	source	NOUN
cana-1705	203	31	and	and	CCONJ
cana-1705	203	32	models	model	NOUN
cana-1705	203	33	that	that	PRON
cana-1705	203	34	can	can	AUX
cana-1705	203	35	update	update	VERB
cana-1705	203	36	predictions	prediction	NOUN
cana-1705	203	37	as	as	SCONJ
cana-1705	203	38	external	external	ADJ
cana-1705	203	39	conditions	condition	NOUN
cana-1705	203	40	evolve	evolve	VERB
cana-1705	203	41	.	.	PUNCT
cana-1705	204	1	this	this	DET
cana-1705	204	2	problem	problem	NOUN
cana-1705	204	3	may	may	AUX
cana-1705	204	4	be	be	AUX
cana-1705	204	5	alleviated	alleviate	VERB
cana-1705	204	6	by	by	ADP
cana-1705	204	7	using	use	VERB
cana-1705	204	8	attention	attention	NOUN
cana-1705	204	9	mechanisms	mechanism	NOUN
cana-1705	204	10	,	,	PUNCT
cana-1705	204	11	and	and	CCONJ
cana-1705	204	12	hybrid	hybrid	NOUN
cana-1705	204	13	models	model	NOUN
cana-1705	204	14	that	that	PRON
cana-1705	204	15	can	can	AUX
cana-1705	204	16	pay	pay	VERB
cana-1705	204	17	attention	attention	NOUN
cana-1705	204	18	to	to	ADP
cana-1705	204	19	important	important	ADJ
cana-1705	204	20	parts	part	NOUN
cana-1705	204	21	of	of	ADP
cana-1705	204	22	the	the	DET
cana-1705	204	23	input	input	NOUN
cana-1705	204	24	sequence	sequence	NOUN
cana-1705	204	25	.	.	PUNCT
cana-1705	205	1	in	in	ADP
cana-1705	205	2	this	this	DET
cana-1705	205	3	paper	paper	NOUN
cana-1705	205	4	,	,	PUNCT
cana-1705	205	5	lstm	lstm	ADJ
cana-1705	205	6	networks	network	NOUN
cana-1705	205	7	are	be	AUX
cana-1705	205	8	used	use	VERB
cana-1705	205	9	to	to	PART
cana-1705	205	10	predict	predict	VERB
cana-1705	205	11	traffic	traffic	NOUN
cana-1705	205	12	flow	flow	NOUN
cana-1705	205	13	that	that	PRON
cana-1705	205	14	can	can	AUX
cana-1705	205	15	better	well	ADV
cana-1705	205	16	handle	handle	VERB
cana-1705	205	17	the	the	DET
cana-1705	205	18	problem	problem	NOUN
cana-1705	205	19	of	of	ADP
cana-1705	205	20	predicting	predict	VERB
cana-1705	205	21	traffic	traffic	NOUN
cana-1705	205	22	congestion	congestion	NOUN
cana-1705	205	23	due	due	ADP
cana-1705	205	24	to	to	ADP
cana-1705	205	25	the	the	DET
cana-1705	205	26	use	use	NOUN
cana-1705	205	27	of	of	ADP
cana-1705	205	28	flow	flow	NOUN
cana-1705	205	29	data	datum	NOUN
cana-1705	205	30	with	with	ADP
cana-1705	205	31	short	short	ADJ
cana-1705	205	32	-	-	PUNCT
cana-1705	205	33	term	term	NOUN
cana-1705	205	34	and	and	CCONJ
cana-1705	205	35	intermediate	intermediate	ADJ
cana-1705	205	36	-	-	PUNCT
cana-1705	205	37	term	term	NOUN
cana-1705	205	38	time	time	NOUN
cana-1705	205	39	spans	span	NOUN
cana-1705	205	40	.	.	PUNCT
cana-1705	206	1	lstms	lstms	PROPN
cana-1705	206	2	will	will	AUX
cana-1705	206	3	continue	continue	VERB
cana-1705	206	4	to	to	PART
cana-1705	206	5	feature	feature	VERB
cana-1705	206	6	prominently	prominently	ADV
cana-1705	206	7	in	in	ADP
cana-1705	206	8	the	the	DET
cana-1705	206	9	development	development	NOUN
cana-1705	206	10	of	of	ADP
cana-1705	206	11	smarter	smart	ADJ
cana-1705	206	12	,	,	PUNCT
cana-1705	206	13	self	self	NOUN
cana-1705	206	14	-	-	PUNCT
cana-1705	206	15	learning	learn	VERB
cana-1705	206	16	traffic	traffic	NOUN
cana-1705	206	17	management	management	NOUN
cana-1705	206	18	systems	system	NOUN
cana-1705	206	19	should	should	AUX
cana-1705	206	20	research	research	VERB
cana-1705	206	21	undergo	undergo	VERB
cana-1705	206	22	further	further	ADJ
cana-1705	206	23	refinement	refinement	NOUN
cana-1705	206	24	to	to	PART
cana-1705	206	25	tackle	tackle	VERB
cana-1705	206	26	the	the	DET
cana-1705	206	27	increasingly	increasingly	ADV
cana-1705	206	28	pressing	pressing	ADJ
cana-1705	206	29	problems	problem	NOUN
cana-1705	206	30	with	with	ADP
cana-1705	206	31	urban	urban	ADJ
cana-1705	206	32	mobility	mobility	NOUN
cana-1705	206	33	.	.	PUNCT
cana-1705	207	1	3	3	X
cana-1705	207	2	.	.	NUM
cana-1705	207	3	proposed	propose	VERB
cana-1705	207	4	methodology	methodology	NOUN
cana-1705	207	5	the	the	DET
cana-1705	207	6	main	main	ADJ
cana-1705	207	7	objective	objective	NOUN
cana-1705	207	8	of	of	ADP
cana-1705	207	9	the	the	DET
cana-1705	207	10	proposed	propose	VERB
cana-1705	207	11	approach	approach	NOUN
cana-1705	207	12	is	be	AUX
cana-1705	207	13	to	to	PART
cana-1705	207	14	develop	develop	VERB
cana-1705	207	15	a	a	DET
cana-1705	207	16	system	system	NOUN
cana-1705	207	17	which	which	PRON
cana-1705	207	18	predicts	predict	VERB
cana-1705	207	19	traffic	traffic	NOUN
cana-1705	207	20	flow	flow	NOUN
cana-1705	207	21	in	in	ADP
cana-1705	207	22	real	real	ADJ
cana-1705	207	23	-	-	PUNCT
cana-1705	207	24	time	time	NOUN
cana-1705	207	25	adapted	adapt	VERB
cana-1705	207	26	for	for	ADP
cana-1705	207	27	urban	urban	ADJ
cana-1705	207	28	mobility	mobility	NOUN
cana-1705	207	29	design	design	NOUN
cana-1705	207	30	through	through	ADP
cana-1705	207	31	long	long	ADJ
cana-1705	207	32	short	short	ADJ
cana-1705	207	33	-	-	PUNCT
cana-1705	207	34	term	term	NOUN
cana-1705	207	35	memory	memory	NOUN
cana-1705	207	36	(	(	PUNCT
cana-1705	207	37	lstm	lstm	NOUN
cana-1705	207	38	)	)	PUNCT
cana-1705	207	39	networks	network	NOUN
cana-1705	207	40	.	.	PUNCT
cana-1705	208	1	the	the	DET
cana-1705	208	2	system	system	NOUN
cana-1705	208	3	is	be	AUX
cana-1705	208	4	designed	design	VERB
cana-1705	208	5	to	to	PART
cana-1705	208	6	address	address	VERB
cana-1705	208	7	the	the	DET
cana-1705	208	8	demands	demand	NOUN
cana-1705	208	9	of	of	ADP
cana-1705	208	10	dealing	deal	VERB
cana-1705	208	11	with	with	ADP
cana-1705	208	12	traditional	traditional	ADJ
cana-1705	208	13	optimisation	optimisation	NOUN
cana-1705	208	14	for	for	ADP
cana-1705	208	15	urban	urban	ADJ
cana-1705	208	16	traffic	traffic	NOUN
cana-1705	208	17	,	,	PUNCT
cana-1705	208	18	such	such	ADJ
cana-1705	208	19	as	as	ADP
cana-1705	208	20	high	high	ADJ
cana-1705	208	21	dynamics	dynamic	NOUN
cana-1705	208	22	in	in	ADP
cana-1705	208	23	traffic	traffic	NOUN
cana-1705	208	24	and	and	CCONJ
cana-1705	208	25	spatial	spatial	ADJ
cana-1705	208	26	correlations	correlation	NOUN
cana-1705	208	27	between	between	ADP
cana-1705	208	28	junctions	junction	NOUN
cana-1705	208	29	,	,	PUNCT
cana-1705	208	30	and	and	CCONJ
cana-1705	208	31	nonlinear	nonlinear	ADJ
cana-1705	208	32	relationships	relationship	NOUN
cana-1705	208	33	amongst	amongst	ADP
cana-1705	208	34	variables	variable	NOUN
cana-1705	208	35	(	(	PUNCT
cana-1705	208	36	e.g.	e.g.	ADV
cana-1705	208	37	,	,	PUNCT
cana-1705	208	38	vehicle	vehicle	NOUN
cana-1705	208	39	speed	speed	NOUN
cana-1705	208	40	-	-	PUNCT
cana-1705	208	41	volume	volume	NOUN
cana-1705	208	42	,	,	PUNCT
cana-1705	208	43	road	road	NOUN
cana-1705	208	44	conditions	condition	NOUN
cana-1705	208	45	-	-	PUNCT
cana-1705	208	46	weather	weather	NOUN
cana-1705	208	47	)	)	PUNCT
cana-1705	208	48	.	.	PUNCT
cana-1705	209	1	this	this	DET
cana-1705	209	2	research	research	NOUN
cana-1705	209	3	contributions	contribution	NOUN
cana-1705	209	4	are	be	AUX
cana-1705	209	5	a	a	DET
cana-1705	209	6	prediction	prediction	NOUN
cana-1705	209	7	model	model	NOUN
cana-1705	209	8	that	that	PRON
cana-1705	209	9	is	be	AUX
cana-1705	209	10	able	able	ADJ
cana-1705	209	11	to	to	PART
cana-1705	209	12	learn	learn	VERB
cana-1705	209	13	local	local	ADJ
cana-1705	209	14	temporal	temporal	ADJ
cana-1705	209	15	dependencies	dependency	NOUN
cana-1705	209	16	of	of	ADP
cana-1705	209	17	traffic	traffic	NOUN
cana-1705	209	18	data	datum	NOUN
cana-1705	209	19	but	but	CCONJ
cana-1705	209	20	also	also	ADV
cana-1705	209	21	incorporates	incorporate	VERB
cana-1705	209	22	global	global	ADJ
cana-1705	209	23	information	information	NOUN
cana-1705	209	24	from	from	ADP
cana-1705	209	25	various	various	ADJ
cana-1705	209	26	synchronized	synchronize	VERB
cana-1705	209	27	real	real	ADJ
cana-1705	209	28	-	-	PUNCT
cana-1705	209	29	time	time	NOUN
cana-1705	209	30	data	datum	NOUN
cana-1705	209	31	streams	stream	NOUN
cana-1705	209	32	and	and	CCONJ
cana-1705	209	33	provides	provide	VERB
cana-1705	209	34	accurate	accurate	ADJ
cana-1705	209	35	and	and	CCONJ
cana-1705	209	36	up	up	ADP
cana-1705	209	37	-	-	PUNCT
cana-1705	209	38	to	to	ADP
cana-1705	209	39	-	-	PUNCT
cana-1705	209	40	date	date	NOUN
cana-1705	209	41	predictions	prediction	NOUN
cana-1705	209	42	.	.	PUNCT
cana-1705	210	1	the	the	DET
cana-1705	210	2	methodology	methodology	NOUN
cana-1705	210	3	comprises	comprise	VERB
cana-1705	210	4	five	five	NUM
cana-1705	210	5	steps	step	NOUN
cana-1705	210	6	:	:	PUNCT
cana-1705	210	7	(	(	PUNCT
cana-1705	210	8	1	1	X
cana-1705	210	9	)	)	PUNCT
cana-1705	210	10	collection	collection	NOUN
cana-1705	210	11	and	and	CCONJ
cana-1705	210	12	preprocessing	preprocessing	NOUN
cana-1705	210	13	of	of	ADP
cana-1705	210	14	data	datum	NOUN
cana-1705	210	15	,	,	PUNCT
cana-1705	210	16	(	(	PUNCT
cana-1705	210	17	2	2	X
cana-1705	210	18	)	)	PUNCT
cana-1705	210	19	feature	feature	NOUN
cana-1705	210	20	engineering	engineering	NOUN
cana-1705	210	21	&	&	CCONJ
cana-1705	210	22	selection	selection	NOUN
cana-1705	210	23	,	,	PUNCT
cana-1705	210	24	(	(	PUNCT
cana-1705	210	25	3	3	X
cana-1705	210	26	)	)	PUNCT
cana-1705	210	27	designing	designing	NOUN
cana-1705	210	28	and	and	CCONJ
cana-1705	210	29	training	training	NOUN
cana-1705	210	30	of	of	ADP
cana-1705	210	31	lstm	lstm	PROPN
cana-1705	210	32	model	model	NOUN
cana-1705	210	33	,	,	PUNCT
cana-1705	210	34	(	(	PUNCT
cana-1705	210	35	4	4	X
cana-1705	210	36	)	)	PUNCT
cana-1705	210	37	validation	validation	NOUN
cana-1705	210	38	/	/	SYM
cana-1705	210	39	evaluation	evaluation	NOUN
cana-1705	210	40	of	of	ADP
cana-1705	210	41	the	the	DET
cana-1705	210	42	model	model	NOUN
cana-1705	210	43	using	use	VERB
cana-1705	210	44	a	a	DET
cana-1705	210	45	real	real	ADJ
cana-1705	210	46	world	world	NOUN
cana-1705	210	47	traffic	traffic	NOUN
cana-1705	210	48	data	datum	NOUN
cana-1705	210	49	and	and	CCONJ
cana-1705	210	50	finally	finally	ADV
cana-1705	210	51	(	(	PUNCT
cana-1705	210	52	5	5	X
cana-1705	210	53	)	)	PUNCT
cana-1705	210	54	deployment	deployment	NOUN
cana-1705	210	55	for	for	ADP
cana-1705	210	56	practical	practical	ADJ
cana-1705	210	57	traffic	traffic	NOUN
cana-1705	210	58	prediction	prediction	NOUN
cana-1705	210	59	application	application	NOUN
cana-1705	210	60	.	.	PUNCT
cana-1705	211	1	the	the	DET
cana-1705	211	2	sections	section	NOUN
cana-1705	211	3	that	that	PRON
cana-1705	211	4	follow	follow	VERB
cana-1705	211	5	detail	detail	NOUN
cana-1705	211	6	each	each	DET
cana-1705	211	7	stage	stage	NOUN
cana-1705	211	8	and	and	CCONJ
cana-1705	211	9	the	the	DET
cana-1705	211	10	theoretical	theoretical	ADJ
cana-1705	211	11	foundations	foundation	NOUN
cana-1705	211	12	that	that	PRON
cana-1705	211	13	underpinned	underpin	VERB
cana-1705	211	14	them	they	PRON
cana-1705	211	15	as	as	ADV
cana-1705	211	16	well	well	ADV
cana-1705	211	17	as	as	ADP
cana-1705	211	18	our	our	PRON
cana-1705	211	19	rationale	rationale	NOUN
cana-1705	211	20	for	for	ADP
cana-1705	211	21	why	why	SCONJ
cana-1705	211	22	we	we	PRON
cana-1705	211	23	approached	approach	VERB
cana-1705	211	24	these	these	DET
cana-1705	211	25	stages	stage	NOUN
cana-1705	211	26	in	in	ADP
cana-1705	211	27	certain	certain	ADJ
cana-1705	211	28	ways	way	NOUN
cana-1705	211	29	.	.	PUNCT
cana-1705	212	1	a.	a.	NOUN
cana-1705	212	2	data	data	PROPN
cana-1705	212	3	collection	collection	NOUN
cana-1705	212	4	and	and	CCONJ
cana-1705	212	5	preprocessing	preprocesse	VERB
cana-1705	212	6	a.	a.	NOUN
cana-1705	212	7	data	data	PROPN
cana-1705	212	8	sources	source	NOUN
cana-1705	212	9	/	/	SYM
cana-1705	212	10	data	datum	NOUN
cana-1705	212	11	integration	integration	NOUN
cana-1705	212	12	the	the	DET
cana-1705	212	13	key	key	ADJ
cana-1705	212	14	ingredient	ingredient	NOUN
cana-1705	212	15	in	in	ADP
cana-1705	212	16	any	any	DET
cana-1705	212	17	traffic	traffic	NOUN
cana-1705	212	18	prediction	prediction	NOUN
cana-1705	212	19	system	system	NOUN
cana-1705	212	20	is	be	AUX
cana-1705	212	21	high	high	ADJ
cana-1705	212	22	quality	quality	NOUN
cana-1705	212	23	and	and	CCONJ
cana-1705	212	24	up	up	ADP
cana-1705	212	25	-	-	PUNCT
cana-1705	212	26	to	to	ADP
cana-1705	212	27	-	-	PUNCT
cana-1705	212	28	the	the	DET
cana-1705	212	29	-	-	PUNCT
cana-1705	212	30	minute	minute	NOUN
cana-1705	212	31	data	datum	NOUN
cana-1705	212	32	.	.	PUNCT
cana-1705	213	1	the	the	DET
cana-1705	213	2	proposed	propose	VERB
cana-1705	213	3	approach	approach	NOUN
cana-1705	213	4	combines	combine	VERB
cana-1705	213	5	different	different	ADJ
cana-1705	213	6	data	datum	NOUN
cana-1705	213	7	sources	source	NOUN
cana-1705	213	8	to	to	PART
cana-1705	213	9	provide	provide	VERB
cana-1705	213	10	a	a	DET
cana-1705	213	11	more	more	ADV
cana-1705	213	12	complete	complete	ADJ
cana-1705	213	13	picture	picture	NOUN
cana-1705	213	14	of	of	ADP
cana-1705	213	15	traffic	traffic	NOUN
cana-1705	213	16	communications	communication	NOUN
cana-1705	213	17	on	on	ADP
cana-1705	213	18	applied	apply	VERB
cana-1705	213	19	nonlinear	nonlinear	ADJ
cana-1705	213	20	analysis	analysis	NOUN
cana-1705	213	21	issn	issn	NOUN
cana-1705	213	22	:	:	PUNCT
cana-1705	213	23	1074	1074	NUM
cana-1705	213	24	-	-	PUNCT
cana-1705	213	25	133x	133x	NUM
cana-1705	213	26	vol	vol	NOUN
cana-1705	213	27	32	32	NUM
cana-1705	213	28	no	no	NOUN
cana-1705	213	29	.	.	NOUN
cana-1705	213	30	2	2	NUM
cana-1705	213	31	(	(	PUNCT
cana-1705	213	32	2025	2025	NUM
cana-1705	213	33	)	)	PUNCT
cana-1705	213	34	12	12	NUM
cana-1705	213	35	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	213	36	conditions	condition	NOUN
cana-1705	213	37	in	in	ADP
cana-1705	213	38	urban	urban	ADJ
cana-1705	213	39	regions	region	NOUN
cana-1705	213	40	.	.	PUNCT
cana-1705	214	1	most	most	ADV
cana-1705	214	2	importantly	importantly	ADV
cana-1705	214	3	,	,	PUNCT
cana-1705	214	4	the	the	DET
cana-1705	214	5	main	main	ADJ
cana-1705	214	6	data	data	NOUN
cana-1705	214	7	source	source	NOUN
cana-1705	214	8	is	be	AUX
cana-1705	214	9	traffic	traffic	NOUN
cana-1705	214	10	sensor	sensor	NOUN
cana-1705	214	11	data	datum	NOUN
cana-1705	214	12	,	,	PUNCT
cana-1705	214	13	obtained	obtain	VERB
cana-1705	214	14	from	from	ADP
cana-1705	214	15	sensors	sensor	NOUN
cana-1705	214	16	integrated	integrate	VERB
cana-1705	214	17	into	into	ADP
cana-1705	214	18	road	road	NOUN
cana-1705	214	19	infrastructure	infrastructure	NOUN
cana-1705	214	20	such	such	ADJ
cana-1705	214	21	as	as	ADP
cana-1705	214	22	inductive	inductive	ADJ
cana-1705	214	23	loop	loop	NOUN
cana-1705	214	24	detectors	detector	NOUN
cana-1705	214	25	,	,	PUNCT
cana-1705	214	26	radar	radar	NOUN
cana-1705	214	27	sensors	sensor	NOUN
cana-1705	214	28	or	or	CCONJ
cana-1705	214	29	camera	camera	NOUN
cana-1705	214	30	-	-	PUNCT
cana-1705	214	31	based	base	VERB
cana-1705	214	32	systems	system	NOUN
cana-1705	214	33	.	.	PUNCT
cana-1705	215	1	these	these	DET
cana-1705	215	2	sensors	sensor	NOUN
cana-1705	215	3	deliver	deliver	VERB
cana-1705	215	4	real	real	ADJ
cana-1705	215	5	-	-	PUNCT
cana-1705	215	6	time	time	NOUN
cana-1705	215	7	traffic	traffic	NOUN
cana-1705	215	8	volume	volume	NOUN
cana-1705	215	9	(	(	PUNCT
cana-1705	215	10	the	the	DET
cana-1705	215	11	number	number	NOUN
cana-1705	215	12	of	of	ADP
cana-1705	215	13	vehicles	vehicle	NOUN
cana-1705	215	14	passing	pass	VERB
cana-1705	215	15	a	a	DET
cana-1705	215	16	particular	particular	ADJ
cana-1705	215	17	spot	spot	NOUN
cana-1705	215	18	)	)	PUNCT
cana-1705	215	19	,	,	PUNCT
cana-1705	215	20	vehicle	vehicle	NOUN
cana-1705	215	21	speed	speed	NOUN
cana-1705	215	22	and	and	CCONJ
cana-1705	215	23	lane	lane	NOUN
cana-1705	215	24	occupancy	occupancy	NOUN
cana-1705	215	25	measurements	measurement	NOUN
cana-1705	215	26	.	.	PUNCT
cana-1705	216	1	the	the	DET
cana-1705	216	2	method	method	NOUN
cana-1705	216	3	also	also	ADV
cana-1705	216	4	aggregates	aggregate	VERB
cana-1705	216	5	vehicle	vehicle	NOUN
cana-1705	216	6	gps	gps	PROPN
cana-1705	216	7	data	datum	NOUN
cana-1705	216	8	sensing	sense	VERB
cana-1705	216	9	speed	speed	NOUN
cana-1705	216	10	,	,	PUNCT
cana-1705	216	11	location	location	NOUN
cana-1705	216	12	and	and	CCONJ
cana-1705	216	13	direction	direction	NOUN
cana-1705	216	14	in	in	ADP
cana-1705	216	15	order	order	NOUN
cana-1705	216	16	to	to	PART
cana-1705	216	17	improve	improve	VERB
cana-1705	216	18	the	the	DET
cana-1705	216	19	resolution	resolution	NOUN
cana-1705	216	20	of	of	ADP
cana-1705	216	21	traffic	traffic	NOUN
cana-1705	216	22	flow	flow	NOUN
cana-1705	216	23	detection	detection	NOUN
cana-1705	216	24	.	.	PUNCT
cana-1705	217	1	the	the	DET
cana-1705	217	2	rich	rich	ADJ
cana-1705	217	3	gps	gps	PROPN
cana-1705	217	4	data	datum	NOUN
cana-1705	217	5	can	can	AUX
cana-1705	217	6	describe	describe	VERB
cana-1705	217	7	the	the	DET
cana-1705	217	8	behavior	behavior	NOUN
cana-1705	217	9	of	of	ADP
cana-1705	217	10	individual	individual	ADJ
cana-1705	217	11	vehicles	vehicle	NOUN
cana-1705	217	12	as	as	SCONJ
cana-1705	217	13	they	they	PRON
cana-1705	217	14	traverse	traverse	VERB
cana-1705	217	15	every	every	DET
cana-1705	217	16	road	road	NOUN
cana-1705	217	17	segment	segment	NOUN
cana-1705	217	18	and	and	CCONJ
cana-1705	217	19	provides	provide	VERB
cana-1705	217	20	an	an	DET
cana-1705	217	21	important	important	ADJ
cana-1705	217	22	way	way	NOUN
cana-1705	217	23	to	to	PART
cana-1705	217	24	take	take	VERB
cana-1705	217	25	account	account	NOUN
cana-1705	217	26	of	of	ADP
cana-1705	217	27	the	the	DET
cana-1705	217	28	spatial	spatial	ADJ
cana-1705	217	29	dependency	dependency	NOUN
cana-1705	217	30	between	between	ADP
cana-1705	217	31	neighboring	neighboring	NOUN
cana-1705	217	32	roads	road	NOUN
cana-1705	217	33	.	.	PUNCT
cana-1705	218	1	another	another	DET
cana-1705	218	2	important	important	ADJ
cana-1705	218	3	feature	feature	NOUN
cana-1705	218	4	from	from	ADP
cana-1705	218	5	the	the	DET
cana-1705	218	6	dataset	dataset	NOUN
cana-1705	218	7	is	be	AUX
cana-1705	218	8	weather	weather	NOUN
cana-1705	218	9	data	datum	NOUN
cana-1705	218	10	as	as	ADP
cana-1705	218	11	weather	weather	NOUN
cana-1705	218	12	conditions	condition	NOUN
cana-1705	218	13	(	(	PUNCT
cana-1705	218	14	rain	rain	NOUN
cana-1705	218	15	,	,	PUNCT
cana-1705	218	16	snow	snow	NOUN
cana-1705	218	17	,	,	PUNCT
cana-1705	218	18	fog	fog	PROPN
cana-1705	218	19	)	)	PUNCT
cana-1705	218	20	heavily	heavily	ADV
cana-1705	218	21	affect	affect	VERB
cana-1705	218	22	the	the	DET
cana-1705	218	23	traffic	traffic	NOUN
cana-1705	218	24	flow	flow	NOUN
cana-1705	218	25	.	.	PUNCT
cana-1705	219	1	weather	weather	NOUN
cana-1705	219	2	data	datum	NOUN
cana-1705	219	3	(	(	PUNCT
cana-1705	219	4	historical	historical	ADJ
cana-1705	219	5	and	and	CCONJ
cana-1705	219	6	real	real	ADJ
cana-1705	219	7	-	-	PUNCT
cana-1705	219	8	time	time	NOUN
cana-1705	219	9	)	)	PUNCT
cana-1705	219	10	including	include	VERB
cana-1705	219	11	temperature	temperature	NOUN
cana-1705	219	12	,	,	PUNCT
cana-1705	219	13	precipitation	precipitation	NOUN
cana-1705	219	14	,	,	PUNCT
cana-1705	219	15	visibility	visibility	NOUN
cana-1705	219	16	are	be	AUX
cana-1705	219	17	included	include	VERB
cana-1705	219	18	into	into	ADP
cana-1705	219	19	the	the	DET
cana-1705	219	20	model	model	NOUN
cana-1705	219	21	to	to	PART
cana-1705	219	22	enhance	enhance	VERB
cana-1705	219	23	prediction	prediction	NOUN
cana-1705	219	24	accuracy	accuracy	NOUN
cana-1705	219	25	when	when	SCONJ
cana-1705	219	26	adverse	adverse	ADJ
cana-1705	219	27	weather	weather	NOUN
cana-1705	219	28	conditions	condition	NOUN
cana-1705	219	29	exist	exist	VERB
cana-1705	219	30	.	.	PUNCT
cana-1705	220	1	lastly	lastly	ADV
cana-1705	220	2	,	,	PUNCT
cana-1705	220	3	they	they	PRON
cana-1705	220	4	account	account	VERB
cana-1705	220	5	for	for	ADP
cana-1705	220	6	other	other	ADJ
cana-1705	220	7	sources	source	NOUN
cana-1705	220	8	of	of	ADP
cana-1705	220	9	data	datum	NOUN
cana-1705	220	10	including	include	VERB
cana-1705	220	11	public	public	ADJ
cana-1705	220	12	transit	transit	NOUN
cana-1705	220	13	data	datum	NOUN
cana-1705	220	14	,	,	PUNCT
cana-1705	220	15	road	road	NOUN
cana-1705	220	16	construction	construction	NOUN
cana-1705	220	17	/	/	SYM
cana-1705	220	18	bottlenecks	bottleneck	NOUN
cana-1705	220	19	information	information	NOUN
cana-1705	220	20	,	,	PUNCT
cana-1705	220	21	and	and	CCONJ
cana-1705	220	22	social	social	ADJ
cana-1705	220	23	media	medium	NOUN
cana-1705	220	24	–	–	PUNCT
cana-1705	220	25	specifically	specifically	ADV
cana-1705	220	26	incidents	incident	NOUN
cana-1705	220	27	about	about	ADP
cana-1705	220	28	traffic	traffic	NOUN
cana-1705	220	29	(	(	PUNCT
cana-1705	220	30	crash	crash	NOUN
cana-1705	220	31	or	or	CCONJ
cana-1705	220	32	lane	lane	NOUN
cana-1705	220	33	closed	closed	ADJ
cana-1705	220	34	)	)	PUNCT
cana-1705	220	35	.	.	PUNCT
cana-1705	221	1	b.	b.	PROPN
cana-1705	221	2	data	data	PROPN
cana-1705	221	3	preprocessing	preprocesse	VERB
cana-1705	221	4	techniques	technique	NOUN
cana-1705	221	5	the	the	DET
cana-1705	221	6	data	datum	NOUN
cana-1705	221	7	collected	collect	VERB
cana-1705	221	8	from	from	ADP
cana-1705	221	9	various	various	ADJ
cana-1705	221	10	sources	source	NOUN
cana-1705	221	11	in	in	ADP
cana-1705	221	12	raw	raw	ADJ
cana-1705	221	13	form	form	NOUN
cana-1705	221	14	and	and	CCONJ
cana-1705	221	15	before	before	SCONJ
cana-1705	221	16	it	it	PRON
cana-1705	221	17	will	will	AUX
cana-1705	221	18	be	be	AUX
cana-1705	221	19	used	use	VERB
cana-1705	221	20	for	for	ADP
cana-1705	221	21	training	train	VERB
cana-1705	221	22	the	the	DET
cana-1705	221	23	lstm	lstm	PROPN
cana-1705	221	24	model	model	NOUN
cana-1705	221	25	,	,	PUNCT
cana-1705	221	26	this	this	DET
cana-1705	221	27	data	data	NOUN
cana-1705	221	28	is	be	AUX
cana-1705	221	29	preprocessed	preprocesse	VERB
cana-1705	221	30	.	.	PUNCT
cana-1705	222	1	since	since	SCONJ
cana-1705	222	2	real	real	ADJ
cana-1705	222	3	world	world	NOUN
cana-1705	222	4	traffic	traffic	NOUN
cana-1705	222	5	data	datum	NOUN
cana-1705	222	6	is	be	AUX
cana-1705	222	7	noisy(i.e	noisy(i.e	PRON
cana-1705	222	8	.	.	PUNCT
cana-1705	222	9	,	,	PUNCT
cana-1705	222	10	it	it	PRON
cana-1705	222	11	often	often	ADV
cana-1705	222	12	contains	contain	VERB
cana-1705	222	13	missing	missing	ADJ
cana-1705	222	14	and/or	and/or	CCONJ
cana-1705	222	15	inconsistent	inconsistent	ADJ
cana-1705	222	16	values	value	NOUN
cana-1705	222	17	)	)	PUNCT
cana-1705	222	18	,	,	PUNCT
cana-1705	222	19	raw	raw	ADJ
cana-1705	222	20	gps	gps	PROPN
cana-1705	222	21	traces	trace	NOUN
cana-1705	222	22	are	be	AUX
cana-1705	222	23	preprocessed	preprocesse	VERB
cana-1705	222	24	to	to	PART
cana-1705	222	25	discard	discard	VERB
cana-1705	222	26	potentially	potentially	ADV
cana-1705	222	27	incorrect	incorrect	ADJ
cana-1705	222	28	samples	sample	NOUN
cana-1705	222	29	that	that	PRON
cana-1705	222	30	can	can	AUX
cana-1705	222	31	result	result	VERB
cana-1705	222	32	from	from	ADP
cana-1705	222	33	sensor	sensor	NOUN
cana-1705	222	34	faults	fault	NOUN
cana-1705	222	35	,	,	PUNCT
cana-1705	222	36	poor	poor	ADJ
cana-1705	222	37	satellite	satellite	NOUN
cana-1705	222	38	coverage	coverage	NOUN
cana-1705	222	39	,	,	PUNCT
cana-1705	222	40	delays	delay	NOUN
cana-1705	222	41	in	in	ADP
cana-1705	222	42	data	data	NOUN
cana-1705	222	43	transmission	transmission	NOUN
cana-1705	222	44	or	or	CCONJ
cana-1705	222	45	human	human	ADJ
cana-1705	222	46	errors	error	NOUN
cana-1705	222	47	.	.	PUNCT
cana-1705	223	1	some	some	DET
cana-1705	223	2	type	type	NOUN
cana-1705	223	3	of	of	ADP
cana-1705	223	4	preprocessing	preprocesse	VERB
cana-1705	223	5	techniques	technique	NOUN
cana-1705	223	6	includes	include	VERB
cana-1705	223	7	data	datum	NOUN
cana-1705	223	8	cleaning	cleaning	NOUN
cana-1705	223	9	,	,	PUNCT
cana-1705	223	10	imputation	imputation	NOUN
cana-1705	223	11	missing	miss	VERB
cana-1705	223	12	values	value	NOUN
cana-1705	223	13	,	,	PUNCT
cana-1705	223	14	and	and	CCONJ
cana-1705	223	15	normalization	normalization	NOUN
cana-1705	223	16	.	.	PUNCT
cana-1705	224	1	𝐿	𝐿	NOUN
cana-1705	224	2	=	=	SYM
cana-1705	224	3	−	−	PROPN
cana-1705	224	4	1	1	NUM
cana-1705	224	5	𝑛	𝑛	PROPN
cana-1705	224	6	∑(𝑦𝑖log(	∑(𝑦𝑖log(	NOUN
cana-1705	224	7	�	�	PROPN
cana-1705	224	8	̂	̂	VERB
cana-1705	224	9	�	�	NOUN
cana-1705	224	10	𝑖	𝑖	NUM
cana-1705	224	11	)	)	PUNCT
cana-1705	224	12	+	+	CCONJ
cana-1705	224	13	(	(	PUNCT
cana-1705	224	14	1	1	NUM
cana-1705	224	15	−	−	NOUN
cana-1705	224	16	𝑦𝑖)log(1	𝑦𝑖)log(1	NOUN
cana-1705	224	17	−	−	PROPN
cana-1705	224	18	�	�	PROPN
cana-1705	224	19	̂	̂	VERB
cana-1705	224	20	�	�	NOUN
cana-1705	224	21	𝑖	𝑖	NUM
cana-1705	224	22	)	)	PUNCT
cana-1705	224	23	)	)	PUNCT
cana-1705	225	1	𝑛	𝑛	PRON
cana-1705	226	1	𝑖=1	𝑖=1	PUNCT
cana-1705	226	2	clean	clean	ADJ
cana-1705	226	3	:	:	PUNCT
cana-1705	226	4	fix	fix	VERB
cana-1705	226	5	or	or	CCONJ
cana-1705	226	6	remove	remove	VERB
cana-1705	226	7	erroneous	erroneous	ADJ
cana-1705	226	8	data	datum	NOUN
cana-1705	226	9	points	point	NOUN
cana-1705	226	10	i.e.	i.e.	X
cana-1705	226	11	,	,	PUNCT
cana-1705	226	12	sensor	sensor	NOUN
cana-1705	226	13	readings	reading	NOUN
cana-1705	226	14	should	should	AUX
cana-1705	226	15	n't	not	PART
cana-1705	226	16	be	be	AUX
cana-1705	226	17	higher	high	ADJ
cana-1705	226	18	than	than	ADP
cana-1705	226	19	the	the	DET
cana-1705	226	20	85th	85th	ADJ
cana-1705	226	21	percentile	percentile	NOUN
cana-1705	226	22	of	of	ADP
cana-1705	226	23	cars	car	NOUN
cana-1705	226	24	speeding	speed	VERB
cana-1705	226	25	and	and	CCONJ
cana-1705	226	26	they	they	PRON
cana-1705	226	27	ca	can	AUX
cana-1705	226	28	n't	not	PART
cana-1705	226	29	possibly	possibly	ADV
cana-1705	226	30	refuel	refuel	VERB
cana-1705	226	31	negatively	negatively	ADV
cana-1705	226	32	unrealistic	unrealistic	ADJ
cana-1705	226	33	measurements	measurement	NOUN
cana-1705	226	34	(	(	PUNCT
cana-1705	226	35	e.g.	e.g.	ADV
cana-1705	226	36	traffic	traffic	NOUN
cana-1705	226	37	volume	volume	NOUN
cana-1705	226	38	can	can	AUX
cana-1705	226	39	not	not	PART
cana-1705	226	40	be	be	AUX
cana-1705	226	41	negative	negative	ADJ
cana-1705	226	42	,	,	PUNCT
cana-1705	226	43	nor	nor	CCONJ
cana-1705	226	44	can	can	AUX
cana-1705	226	45	we	we	PRON
cana-1705	226	46	drive	drive	VERB
cana-1705	226	47	faster	fast	ADV
cana-1705	226	48	than	than	ADP
cana-1705	226	49	physical	physical	ADJ
cana-1705	226	50	limits	limit	NOUN
cana-1705	226	51	)	)	PUNCT
cana-1705	226	52	because	because	SCONJ
cana-1705	226	53	in	in	ADP
cana-1705	226	54	many	many	ADJ
cana-1705	226	55	cases	case	NOUN
cana-1705	226	56	these	these	DET
cana-1705	226	57	anomalies	anomaly	NOUN
cana-1705	226	58	can	can	AUX
cana-1705	226	59	be	be	AUX
cana-1705	226	60	attributed	attribute	VERB
cana-1705	226	61	to	to	ADP
cana-1705	226	62	a	a	DET
cana-1705	226	63	sensor	sensor	NOUN
cana-1705	226	64	malfunction	malfunction	NOUN
cana-1705	226	65	or	or	CCONJ
cana-1705	226	66	intermittent	intermittent	ADJ
cana-1705	226	67	system	system	NOUN
cana-1705	226	68	bug	bug	NOUN
cana-1705	226	69	.	.	PUNCT
cana-1705	227	1	missing	miss	VERB
cana-1705	227	2	data	data	NOUN
cana-1705	227	3	imputation	imputation	NOUN
cana-1705	227	4	:	:	PUNCT
cana-1705	227	5	often	often	ADV
cana-1705	227	6	,	,	PUNCT
cana-1705	227	7	missing	miss	VERB
cana-1705	227	8	data	datum	NOUN
cana-1705	227	9	can	can	AUX
cana-1705	227	10	be	be	AUX
cana-1705	227	11	a	a	DET
cana-1705	227	12	problem	problem	NOUN
cana-1705	227	13	in	in	ADP
cana-1705	227	14	traffic	traffic	NOUN
cana-1705	227	15	datasets	dataset	NOUN
cana-1705	227	16	as	as	SCONJ
cana-1705	227	17	sensors	sensor	NOUN
cana-1705	227	18	devices	device	NOUN
cana-1705	227	19	impart	impart	VERB
cana-1705	227	20	their	their	PRON
cana-1705	227	21	failures	failure	NOUN
cana-1705	227	22	or	or	CCONJ
cana-1705	227	23	communication	communication	NOUN
cana-1705	227	24	delays	delay	NOUN
cana-1705	227	25	.	.	PUNCT
cana-1705	228	1	traditional	traditional	ADJ
cana-1705	228	2	methods	method	NOUN
cana-1705	228	3	of	of	ADP
cana-1705	228	4	imputation	imputation	NOUN
cana-1705	228	5	such	such	ADJ
cana-1705	228	6	as	as	ADP
cana-1705	228	7	mean	mean	ADJ
cana-1705	228	8	,	,	PUNCT
cana-1705	228	9	knearest	knearest	NOUN
cana-1705	228	10	neighbors	neighbor	NOUN
cana-1705	228	11	(	(	PUNCT
cana-1705	228	12	knn	knn	PROPN
cana-1705	228	13	)	)	PUNCT
cana-1705	228	14	,	,	PUNCT
cana-1705	228	15	or	or	CCONJ
cana-1705	228	16	more	more	ADV
cana-1705	228	17	advanced	advanced	ADJ
cana-1705	228	18	approaches	approach	NOUN
cana-1705	228	19	like	like	ADP
cana-1705	228	20	matrix	matrix	NOUN
cana-1705	228	21	factorizations	factorization	NOUN
cana-1705	228	22	are	be	AUX
cana-1705	228	23	employed	employ	VERB
cana-1705	228	24	to	to	PART
cana-1705	228	25	predict	predict	VERB
cana-1705	228	26	missing	miss	VERB
cana-1705	228	27	data	datum	NOUN
cana-1705	228	28	points	point	NOUN
cana-1705	228	29	and	and	CCONJ
cana-1705	228	30	replenish	replenish	VERB
cana-1705	228	31	them	they	PRON
cana-1705	228	32	in	in	ADP
cana-1705	228	33	the	the	DET
cana-1705	228	34	dataset	dataset	NOUN
cana-1705	228	35	.	.	PUNCT
cana-1705	229	1	forward	forward	ADV
cana-1705	229	2	or	or	CCONJ
cana-1705	229	3	back	back	ADV
cana-1705	229	4	filling	fill	VERB
cana-1705	229	5	works	work	NOUN
cana-1705	229	6	(	(	PUNCT
cana-1705	229	7	filling	fill	VERB
cana-1705	229	8	missing	miss	VERB
cana-1705	229	9	value	value	NOUN
cana-1705	229	10	with	with	ADP
cana-1705	229	11	the	the	DET
cana-1705	229	12	last	last	ADJ
cana-1705	229	13	known	know	VERB
cana-1705	229	14	value	value	NOUN
cana-1705	229	15	)	)	PUNCT
cana-1705	229	16	for	for	ADP
cana-1705	229	17	temporal	temporal	ADJ
cana-1705	229	18	data	datum	NOUN
cana-1705	229	19	like	like	ADP
cana-1705	229	20	traffic	traffic	NOUN
cana-1705	229	21	flow	flow	NOUN
cana-1705	229	22	to	to	PART
cana-1705	229	23	carry	carry	VERB
cana-1705	229	24	forward	forward	ADV
cana-1705	229	25	the	the	DET
cana-1705	229	26	information	information	NOUN
cana-1705	229	27	before	before	ADP
cana-1705	229	28	predicting	predict	VERB
cana-1705	229	29	next	next	ADJ
cana-1705	229	30	steps	step	NOUN
cana-1705	229	31	.	.	PUNCT
cana-1705	230	1	𝑥norm	𝑥norm	NOUN
cana-1705	230	2	=	=	SYM
cana-1705	230	3	𝑥	𝑥	PRON
cana-1705	230	4	−	−	PROPN
cana-1705	230	5	𝑥min	𝑥min	NOUN
cana-1705	230	6	𝑥max	𝑥max	NOUN
cana-1705	230	7	−	−	PROPN
cana-1705	230	8	𝑥min	𝑥min	NOUN
cana-1705	230	9	standardization	standardization	NOUN
cana-1705	230	10	:	:	PUNCT
cana-1705	230	11	traffic	traffic	NOUN
cana-1705	230	12	data	datum	NOUN
cana-1705	230	13	ranges	range	VERB
cana-1705	230	14	across	across	ADP
cana-1705	230	15	different	different	ADJ
cana-1705	230	16	places	place	NOUN
cana-1705	230	17	and	and	CCONJ
cana-1705	230	18	times	time	NOUN
cana-1705	230	19	of	of	ADP
cana-1705	230	20	the	the	DET
cana-1705	230	21	day	day	NOUN
cana-1705	230	22	so	so	SCONJ
cana-1705	230	23	that	that	SCONJ
cana-1705	230	24	it	it	PRON
cana-1705	230	25	needs	need	VERB
cana-1705	230	26	to	to	PART
cana-1705	230	27	be	be	AUX
cana-1705	230	28	scaled	scale	VERB
cana-1705	230	29	down	down	ADP
cana-1705	230	30	or	or	CCONJ
cana-1705	230	31	normalized	normalize	VERB
cana-1705	230	32	.	.	PUNCT
cana-1705	231	1	this	this	DET
cana-1705	231	2	process	process	NOUN
cana-1705	231	3	allows	allow	VERB
cana-1705	231	4	us	we	PRON
cana-1705	231	5	to	to	PART
cana-1705	231	6	make	make	VERB
cana-1705	231	7	sure	sure	ADJ
cana-1705	231	8	that	that	SCONJ
cana-1705	231	9	values	value	NOUN
cana-1705	231	10	with	with	ADP
cana-1705	231	11	larger	large	ADJ
cana-1705	231	12	magnitudes	magnitude	NOUN
cana-1705	231	13	(	(	PUNCT
cana-1705	231	14	for	for	ADP
cana-1705	231	15	example	example	NOUN
cana-1705	231	16	,	,	PUNCT
cana-1705	231	17	vehicle	vehicle	NOUN
cana-1705	231	18	speed	speed	NOUN
cana-1705	231	19	)	)	PUNCT
cana-1705	231	20	do	do	AUX
cana-1705	231	21	not	not	PART
cana-1705	231	22	significantly	significantly	ADV
cana-1705	231	23	affect	affect	VERB
cana-1705	231	24	the	the	DET
cana-1705	231	25	model	model	NOUN
cana-1705	231	26	more	more	ADJ
cana-1705	231	27	than	than	ADP
cana-1705	231	28	those	those	PRON
cana-1705	231	29	with	with	ADP
cana-1705	231	30	smaller	small	ADJ
cana-1705	231	31	ones	one	NOUN
cana-1705	231	32	(	(	PUNCT
cana-1705	231	33	say	say	VERB
cana-1705	231	34	road	road	NOUN
cana-1705	231	35	occupancy	occupancy	NOUN
cana-1705	231	36	)	)	PUNCT
cana-1705	231	37	,	,	PUNCT
cana-1705	231	38	this	this	PRON
cana-1705	231	39	is	be	AUX
cana-1705	231	40	called	call	VERB
cana-1705	231	41	normalization	normalization	NOUN
cana-1705	231	42	.	.	PUNCT
cana-1705	232	1	some	some	PRON
cana-1705	232	2	of	of	ADP
cana-1705	232	3	the	the	DET
cana-1705	232	4	popular	popular	ADJ
cana-1705	232	5	normalization	normalization	NOUN
cana-1705	232	6	techniques	technique	VERB
cana-1705	232	7	communications	communication	NOUN
cana-1705	232	8	on	on	ADP
cana-1705	232	9	applied	apply	VERB
cana-1705	232	10	nonlinear	nonlinear	ADJ
cana-1705	232	11	analysis	analysis	NOUN
cana-1705	232	12	issn	issn	NOUN
cana-1705	232	13	:	:	PUNCT
cana-1705	232	14	1074	1074	NUM
cana-1705	232	15	-	-	PUNCT
cana-1705	232	16	133x	133x	NUM
cana-1705	232	17	vol	vol	NOUN
cana-1705	232	18	32	32	NUM
cana-1705	232	19	no	no	NOUN
cana-1705	232	20	.	.	NOUN
cana-1705	232	21	2	2	NUM
cana-1705	232	22	(	(	PUNCT
cana-1705	232	23	2025	2025	NUM
cana-1705	232	24	)	)	PUNCT
cana-1705	232	25	13	13	NUM
cana-1705	232	26	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-1705	232	27	used	use	VERB
cana-1705	232	28	in	in	ADP
cana-1705	232	29	practice	practice	NOUN
cana-1705	232	30	are	be	AUX
cana-1705	232	31	min	min	ADJ
cana-1705	232	32	-	-	ADJ
cana-1705	232	33	max	max	NOUN
cana-1705	232	34	normalization	normalization	NOUN
cana-1705	232	35	or	or	CCONJ
cana-1705	232	36	z	z	NOUN
cana-1705	232	37	-	-	PUNCT
cana-1705	232	38	score	score	NOUN
cana-1705	232	39	normalization	normalization	NOUN
cana-1705	232	40	where	where	SCONJ
cana-1705	232	41	0	0	NUM
cana-1705	232	42	to	to	PART
cana-1705	232	43	1	1	NUM
cana-1705	232	44	range	range	NOUN
cana-1705	232	45	is	be	AUX
cana-1705	232	46	scaled	scale	VERB
cana-1705	232	47	(	(	PUNCT
cana-1705	232	48	min	min	NOUN
cana-1705	232	49	-	-	PUNCT
cana-1705	232	50	max	max	NOUN
cana-1705	232	51	)	)	PUNCT
cana-1705	232	52	and	and	CCONJ
cana-1705	232	53	a	a	DET
cana-1705	232	54	zero	zero	NUM
cana-1705	232	55	mean	mean	NOUN
cana-1705	232	56	unit	unit	NOUN
cana-1705	232	57	variance	variance	NOUN
cana-1705	232	58	approach	approach	NOUN
cana-1705	232	59	standardized	standardize	VERB
cana-1705	232	60	(	(	PUNCT
cana-1705	232	61	z	z	NOUN
cana-1705	232	62	-	-	PUNCT
cana-1705	232	63	score	score	NOUN
cana-1705	232	64	)	)	PUNCT
cana-1705	232	65	,	,	PUNCT
cana-1705	232	66	respectively	respectively	ADV
cana-1705	232	67	.	.	PUNCT
cana-1705	233	1	c.	c.	NOUN
cana-1705	233	2	feature	feature	PROPN
cana-1705	233	3	engineering	engineering	NOUN
cana-1705	233	4	and	and	CCONJ
cana-1705	233	5	selection	selection	NOUN
cana-1705	233	6	assure	assure	NOUN
cana-1705	233	7	reset	reset	NOUN
cana-1705	233	8	feature	feature	NOUN
cana-1705	233	9	engineering	engineering	NOUN
cana-1705	233	10	is	be	AUX
cana-1705	233	11	the	the	DET
cana-1705	233	12	process	process	NOUN
cana-1705	233	13	by	by	ADP
cana-1705	233	14	which	which	PRON
cana-1705	233	15	we	we	PRON
cana-1705	233	16	can	can	AUX
cana-1705	233	17	improve	improve	VERB
cana-1705	233	18	the	the	DET
cana-1705	233	19	predictive	predictive	ADJ
cana-1705	233	20	performances	performance	NOUN
cana-1705	233	21	of	of	ADP
cana-1705	233	22	machine	machine	NOUN
cana-1705	233	23	learning	learning	NOUN
cana-1705	233	24	models	model	NOUN
cana-1705	233	25	.	.	PUNCT
cana-1705	234	1	to	to	PART
cana-1705	234	2	detect	detect	VERB
cana-1705	234	3	both	both	CCONJ
cana-1705	234	4	the	the	DET
cana-1705	234	5	temporal	temporal	ADJ
cana-1705	234	6	and	and	CCONJ
cana-1705	234	7	spatial	spatial	ADJ
cana-1705	234	8	dynamics	dynamic	NOUN
cana-1705	234	9	of	of	ADP
cana-1705	234	10	traffic	traffic	NOUN
cana-1705	234	11	flow	flow	NOUN
cana-1705	234	12	,	,	PUNCT
cana-1705	234	13	many	many	ADJ
cana-1705	234	14	features	feature	NOUN
cana-1705	234	15	can	can	AUX
cana-1705	234	16	be	be	AUX
cana-1705	234	17	extracted	extract	VERB
cana-1705	234	18	from	from	ADP
cana-1705	234	19	the	the	DET
cana-1705	234	20	original	original	ADJ
cana-1705	234	21	data	datum	NOUN
cana-1705	234	22	with	with	ADP
cana-1705	234	23	this	this	DET
cana-1705	234	24	method	method	NOUN
cana-1705	234	25	.	.	PUNCT
cana-1705	235	1	a.	a.	PROPN
cana-1705	235	2	temporal	temporal	PROPN
cana-1705	235	3	features	feature	VERB
cana-1705	235	4	multiple	multiple	ADJ
cana-1705	235	5	temporal	temporal	ADJ
cana-1705	235	6	features	feature	NOUN
cana-1705	235	7	traffic	traffic	NOUN
cana-1705	235	8	flow	flow	NOUN
cana-1705	235	9	is	be	AUX
cana-1705	235	10	a	a	DET
cana-1705	235	11	mix	mix	NOUN
cana-1705	235	12	of	of	ADP
cana-1705	235	13	short	short	ADJ
cana-1705	235	14	-	-	PUNCT
cana-1705	235	15	term	term	NOUN
cana-1705	235	16	fluctuations	fluctuation	NOUN
cana-1705	235	17	and	and	CCONJ
cana-1705	235	18	long	long	ADJ
cana-1705	235	19	-	-	PUNCT
cana-1705	235	20	term	term	NOUN
cana-1705	235	21	patterns	pattern	NOUN
cana-1705	235	22	,	,	PUNCT
cana-1705	235	23	so	so	SCONJ
cana-1705	235	24	you	you	PRON
cana-1705	235	25	will	will	AUX
cana-1705	235	26	feed	feed	VERB
cana-1705	235	27	different	different	ADJ
cana-1705	235	28	type	type	NOUN
cana-1705	235	29	temporal	temporal	ADV
cana-1705	235	30	-	-	PUNCT
cana-1705	235	31	based	base	VERB
cana-1705	235	32	features	feature	NOUN
cana-1705	235	33	like	like	ADP
cana-1705	235	34	…	…	PUNCT
cana-1705	235	35	day	day	NOUN
cana-1705	235	36	of	of	ADP
cana-1705	235	37	week	week	NOUN
cana-1705	235	38	and	and	CCONJ
cana-1705	235	39	time	time	NOUN
cana-1705	235	40	of	of	ADP
cana-1705	235	41	day	day	NOUN
cana-1705	235	42	:	:	PUNCT
cana-1705	235	43	the	the	DET
cana-1705	235	44	traffic	traffic	NOUN
cana-1705	235	45	pattern	pattern	NOUN
cana-1705	235	46	varies	vary	VERB
cana-1705	235	47	for	for	ADP
cana-1705	235	48	the	the	DET
cana-1705	235	49	day	day	NOUN
cana-1705	235	50	of	of	ADP
cana-1705	235	51	the	the	DET
cana-1705	235	52	week	week	NOUN
cana-1705	235	53	(	(	PUNCT
cana-1705	235	54	e.g.	e.g.	ADV
cana-1705	235	55	,	,	PUNCT
cana-1705	235	56	monday	monday	PROPN
cana-1705	235	57	vs	vs	ADP
cana-1705	235	58	saturday	saturday	PROPN
cana-1705	235	59	)	)	PUNCT
cana-1705	235	60	and	and	CCONJ
cana-1705	235	61	also	also	ADV
cana-1705	235	62	for	for	ADP
cana-1705	235	63	time	time	NOUN
cana-1705	235	64	of	of	ADP
cana-1705	235	65	the	the	DET
cana-1705	235	66	day	day	NOUN
cana-1705	235	67	(	(	PUNCT
cana-1705	235	68	e.g	e.g	NOUN
cana-1705	235	69	,	,	PUNCT
cana-1705	235	70	8	8	NUM
cana-1705	235	71	am	be	AUX
cana-1705	235	72	on	on	ADP
cana-1705	235	73	weekday	weekday	NOUN
cana-1705	235	74	vs.	vs.	ADP
cana-1705	235	75	9	9	NUM
cana-1705	235	76	pm	pm	NOUN
cana-1705	235	77	)	)	PUNCT
cana-1705	235	78	.	.	PUNCT
cana-1705	236	1	by	by	ADP
cana-1705	236	2	including	include	VERB
cana-1705	236	3	hour	hour	NOUN
cana-1705	236	4	of	of	ADP
cana-1705	236	5	the	the	DET
cana-1705	236	6	day	day	NOUN
cana-1705	236	7	and	and	CCONJ
cana-1705	236	8	day	day	NOUN
cana-1705	236	9	of	of	ADP
cana-1705	236	10	the	the	DET
cana-1705	236	11	week	week	NOUN
cana-1705	236	12	features	feature	NOUN
cana-1705	236	13	,	,	PUNCT
cana-1705	236	14	these	these	DET
cana-1705	236	15	cyclical	cyclical	ADJ
cana-1705	236	16	patterns	pattern	NOUN
cana-1705	236	17	were	be	AUX
cana-1705	236	18	captured	capture	VERB
cana-1705	236	19	.	.	PUNCT
cana-1705	237	1	lagged	lag	VERB
cana-1705	237	2	traffic	traffic	NOUN
cana-1705	237	3	variables	variable	NOUN
cana-1705	237	4	lagged	lag	VERB
cana-1705	237	5	versions	version	NOUN
cana-1705	237	6	of	of	ADP
cana-1705	237	7	traffic	traffic	NOUN
cana-1705	237	8	volume	volume	NOUN
cana-1705	237	9	,	,	PUNCT
cana-1705	237	10	speed	speed	NOUN
cana-1705	237	11	and	and	CCONJ
cana-1705	237	12	occupancy	occupancy	NOUN
cana-1705	237	13	are	be	AUX
cana-1705	237	14	used	use	VERB
cana-1705	237	15	as	as	ADP
cana-1705	237	16	features	feature	NOUN
cana-1705	237	17	to	to	PART
cana-1705	237	18	account	account	VERB
cana-1705	237	19	for	for	ADP
cana-1705	237	20	the	the	DET
cana-1705	237	21	temporal	temporal	ADJ
cana-1705	237	22	dependencies	dependency	NOUN
cana-1705	237	23	in	in	ADP
cana-1705	237	24	traffic	traffic	NOUN
cana-1705	237	25	flow	flow	NOUN
cana-1705	237	26	.	.	PUNCT
cana-1705	238	1	for	for	ADP
cana-1705	238	2	instance	instance	NOUN
cana-1705	238	3	,	,	PUNCT
cana-1705	238	4	the	the	DET
cana-1705	238	5	number	number	NOUN
cana-1705	238	6	of	of	ADP
cana-1705	238	7	cars	car	NOUN
cana-1705	238	8	arriving	arrive	VERB
cana-1705	238	9	at	at	ADP
cana-1705	238	10	a	a	DET
cana-1705	238	11	given	give	VERB
cana-1705	238	12	time	time	NOUN
cana-1705	238	13	step	step	NOUN
cana-1705	238	14	may	may	AUX
cana-1705	238	15	depend	depend	VERB
cana-1705	238	16	on	on	ADP
cana-1705	238	17	the	the	DET
cana-1705	238	18	number	number	NOUN
cana-1705	238	19	in	in	ADP
cana-1705	238	20	the	the	DET
cana-1705	238	21	previous	previous	ADJ
cana-1705	238	22	one	one	NUM
cana-1705	238	23	(	(	PUNCT
cana-1705	238	24	or	or	CCONJ
cana-1705	238	25	several	several	ADJ
cana-1705	238	26	time	time	NOUN
cana-1705	238	27	steps	step	NOUN
cana-1705	238	28	back	back	ADV
cana-1705	238	29	)	)	PUNCT
cana-1705	238	30	.	.	PUNCT
cana-1705	239	1	the	the	DET
cana-1705	239	2	lstm	lstm	PROPN
cana-1705	239	3	model	model	NOUN
cana-1705	239	4	is	be	AUX
cana-1705	239	5	able	able	ADJ
cana-1705	239	6	to	to	PART
cana-1705	239	7	learn	learn	VERB
cana-1705	239	8	from	from	ADP
cana-1705	239	9	historical	historical	ADJ
cana-1705	239	10	trends	trend	NOUN
cana-1705	239	11	as	as	ADP
cana-1705	239	12	a	a	DET
cana-1705	239	13	result	result	NOUN
cana-1705	239	14	.	.	PUNCT
cana-1705	240	1	time	time	NOUN
cana-1705	240	2	location	location	NOUN
cana-1705	240	3	(	(	PUNCT
cana-1705	240	4	lat	lat	NOUN
cana-1705	240	5	,	,	PUNCT
cana-1705	240	6	long	long	ADJ
cana-1705	240	7	)	)	PUNCT
cana-1705	240	8	traffic	traffic	NOUN
cana-1705	240	9	volume	volume	NOUN
cana-1705	240	10	vehicle	vehicle	NOUN
cana-1705	240	11	speed	speed	NOUN
cana-1705	240	12	(	(	PUNCT
cana-1705	240	13	km	km	NOUN
cana-1705	240	14	/	/	SYM
cana-1705	240	15	h	h	NOUN
cana-1705	240	16	)	)	PUNCT
cana-1705	240	17	lane	lane	NOUN
cana-1705	240	18	occupancy	occupancy	NOUN
cana-1705	240	19	(	(	PUNCT
cana-1705	240	20	%	%	INTJ
cana-1705	240	21	)	)	PUNCT
cana-1705	240	22	weather	weather	NOUN
cana-1705	240	23	condition	condition	NOUN
cana-1705	240	24	incident	incident	NOUN
cana-1705	240	25	report	report	NOUN
cana-1705	240	26	08:00	08:00	NUM
cana-1705	240	27	am	am	NOUN
cana-1705	240	28	(	(	PUNCT
cana-1705	240	29	40.7128	40.7128	NUM
cana-1705	240	30	,	,	PUNCT
cana-1705	240	31	74.0060	74.0060	NUM
cana-1705	240	32	)	)	PUNCT
cana-1705	240	33	1500	1500	NUM
cana-1705	241	1	40	40	NUM
cana-1705	241	2	75	75	NUM
cana-1705	241	3	clear	clear	ADJ
cana-1705	241	4	no	no	DET
cana-1705	241	5	08:05	08:05	NUM
cana-1705	241	6	am	am	NOUN
cana-1705	241	7	(	(	PUNCT
cana-1705	241	8	40.7130	40.7130	NUM
cana-1705	241	9	,	,	PUNCT
cana-1705	241	10	74.0065	74.0065	NUM
cana-1705	241	11	)	)	PUNCT
cana-1705	241	12	1600	1600	NUM
cana-1705	241	13	38	38	NUM
cana-1705	241	14	80	80	NUM
cana-1705	241	15	clear	clear	ADJ
cana-1705	241	16	no	no	DET
cana-1705	241	17	08:10	08:10	NUM
cana-1705	241	18	am	am	NOUN
cana-1705	241	19	(	(	PUNCT
cana-1705	241	20	40.7135	40.7135	NUM
cana-1705	241	21	,	,	PUNCT
cana-1705	241	22	74.0070	74.0070	NUM
cana-1705	241	23	)	)	PUNCT
cana-1705	241	24	1700	1700	NUM
cana-1705	241	25	35	35	NUM
cana-1705	241	26	85	85	NUM
cana-1705	241	27	rain	rain	NOUN
cana-1705	241	28	accident	accident	NOUN
cana-1705	241	29	08:15	08:15	NUM
cana-1705	241	30	am	am	NOUN
cana-1705	241	31	(	(	PUNCT
cana-1705	241	32	40.7140	40.7140	NUM
cana-1705	241	33	,	,	PUNCT
cana-1705	241	34	74.0075	74.0075	NUM
cana-1705	241	35	)	)	PUNCT
cana-1705	241	36	1650	1650	NUM
cana-1705	241	37	37	37	NUM
cana-1705	241	38	82	82	NUM
cana-1705	241	39	rain	rain	NOUN
cana-1705	242	1	no	no	DET
cana-1705	242	2	08:20	08:20	NUM
cana-1705	242	3	am	be	AUX
cana-1705	242	4	(	(	PUNCT
cana-1705	242	5	40.7145	40.7145	NUM
cana-1705	242	6	,	,	PUNCT
cana-1705	242	7	74.0080	74.0080	NUM
cana-1705	242	8	)	)	PUNCT
cana-1705	242	9	1800	1800	NUM
cana-1705	242	10	33	33	NUM
cana-1705	242	11	88	88	NUM
cana-1705	242	12	rain	rain	NOUN
cana-1705	242	13	no	no	DET
cana-1705	242	14	table	table	NOUN
cana-1705	242	15	2	2	NUM
cana-1705	242	16	.	.	PUNCT
cana-1705	242	17	real	real	ADJ
cana-1705	242	18	-	-	PUNCT
cana-1705	242	19	time	time	NOUN
cana-1705	242	20	traffic	traffic	NOUN
cana-1705	242	21	data	datum	NOUN
cana-1705	242	22	for	for	ADP
cana-1705	242	23	lstm	lstm	NOUN
cana-1705	242	24	prediction	prediction	NOUN
cana-1705	242	25	lagged	lag	VERB
cana-1705	242	26	weather	weather	NOUN
cana-1705	242	27	variables	variable	NOUN
cana-1705	242	28	:	:	PUNCT
cana-1705	242	29	an	an	DET
cana-1705	242	30	indicator	indicator	NOUN
cana-1705	242	31	for	for	ADP
cana-1705	242	32	the	the	DET
cana-1705	242	33	weather	weather	NOUN
cana-1705	242	34	at	at	ADP
cana-1705	242	35	the	the	DET
cana-1705	242	36	time	time	NOUN
cana-1705	242	37	when	when	SCONJ
cana-1705	242	38	historical	historical	ADJ
cana-1705	242	39	traffic	traffic	NOUN
cana-1705	242	40	volume	volume	NOUN
cana-1705	242	41	was	be	AUX
cana-1705	242	42	recorded	record	VERB
cana-1705	242	43	is	be	AUX
cana-1705	242	44	also	also	ADV
cana-1705	242	45	included	include	VERB
cana-1705	242	46	to	to	PART
cana-1705	242	47	take	take	VERB
cana-1705	242	48	into	into	ADP
cana-1705	242	49	consideration	consideration	NOUN
cana-1705	242	50	that	that	SCONJ
cana-1705	242	51	the	the	DET
cana-1705	242	52	effects	effect	NOUN
cana-1705	242	53	of	of	ADP
cana-1705	242	54	weather	weather	NOUN
cana-1705	242	55	are	be	AUX
cana-1705	242	56	not	not	PART
cana-1705	242	57	only	only	ADV
cana-1705	242	58	present	present	ADJ
cana-1705	242	59	during	during	ADP
cana-1705	242	60	specific	specific	ADJ
cana-1705	242	61	periods	period	NOUN
cana-1705	242	62	of	of	ADP
cana-1705	242	63	time	time	NOUN
cana-1705	242	64	.	.	PUNCT
cana-1705	243	1	by	by	ADP
cana-1705	243	2	contrast	contrast	NOUN
cana-1705	243	3	,	,	PUNCT
cana-1705	243	4	the	the	DET
cana-1705	243	5	congestion	congestion	NOUN
cana-1705	243	6	effects	effect	NOUN
cana-1705	243	7	of	of	ADP
cana-1705	243	8	a	a	DET
cana-1705	243	9	few	few	ADJ
cana-1705	243	10	hours	hour	NOUN
cana-1705	243	11	of	of	ADP
cana-1705	243	12	sustained	sustained	ADJ
cana-1705	243	13	rainfall	rainfall	NOUN
cana-1705	243	14	may	may	AUX
cana-1705	243	15	be	be	AUX
cana-1705	243	16	greater	great	ADJ
cana-1705	243	17	than	than	ADP
cana-1705	243	18	the	the	DET
cana-1705	243	19	effects	effect	NOUN
cana-1705	243	20	of	of	ADP
cana-1705	243	21	just	just	ADV
cana-1705	243	22	a	a	DET
cana-1705	243	23	single	single	ADJ
cana-1705	243	24	brief	brief	ADJ
cana-1705	243	25	rain	rain	NOUN
cana-1705	243	26	shower	shower	NOUN
cana-1705	243	27	.	.	PUNCT
cana-1705	244	1	b.	b.	PROPN
cana-1705	244	2	spatial	spatial	PROPN
cana-1705	244	3	features	feature	VERB
cana-1705	244	4	the	the	DET
cana-1705	244	5	usual	usual	ADJ
cana-1705	244	6	justification	justification	NOUN
cana-1705	244	7	is	be	AUX
cana-1705	244	8	that	that	SCONJ
cana-1705	244	9	traffic	traffic	NOUN
cana-1705	244	10	on	on	ADP
cana-1705	244	11	one	one	NUM
cana-1705	244	12	road	road	NOUN
cana-1705	244	13	segment	segment	NOUN
cana-1705	244	14	is	be	AUX
cana-1705	244	15	at	at	ADP
cana-1705	244	16	least	least	ADJ
cana-1705	244	17	somewhat	somewhat	ADV
cana-1705	244	18	correlated	correlate	VERB
cana-1705	244	19	with	with	ADP
cana-1705	244	20	traffic	traffic	NOUN
cana-1705	244	21	on	on	ADP
cana-1705	244	22	adjacent	adjacent	ADJ
cana-1705	244	23	road	road	NOUN
cana-1705	244	24	segments	segment	NOUN
cana-1705	244	25	.	.	PUNCT
cana-1705	245	1	a	a	DET
cana-1705	245	2	very	very	ADV
cana-1705	245	3	common	common	ADJ
cana-1705	245	4	example	example	NOUN
cana-1705	245	5	is	be	AUX
cana-1705	245	6	a	a	DET
cana-1705	245	7	car	car	NOUN
cana-1705	245	8	accident	accident	NOUN
cana-1705	245	9	that	that	PRON
cana-1705	245	10	causes	cause	VERB
cana-1705	245	11	traffic	traffic	NOUN
cana-1705	245	12	jam	jam	NOUN
cana-1705	245	13	on	on	ADP
cana-1705	245	14	one	one	NUM
cana-1705	245	15	communications	communication	NOUN
cana-1705	245	16	on	on	ADP
cana-1705	245	17	applied	apply	VERB
cana-1705	245	18	nonlinear	nonlinear	ADJ
cana-1705	245	19	analysis	analysis	NOUN
cana-1705	245	20	issn	issn	NOUN
cana-1705	245	21	:	:	PUNCT
cana-1705	245	22	1074	1074	NUM
cana-1705	245	23	-	-	PUNCT
cana-1705	245	24	133x	133x	NUM
cana-1705	245	25	vol	vol	NOUN
cana-1705	245	26	32	32	NUM
cana-1705	245	27	no	no	NOUN
cana-1705	245	28	.	.	NOUN
cana-1705	245	29	2	2	NUM
cana-1705	245	30	(	(	PUNCT
cana-1705	245	31	2025	2025	NUM
cana-1705	245	32	)	)	PUNCT
cana-1705	245	33	14	14	NUM
cana-1705	245	34	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	245	35	road	road	NOUN
cana-1705	245	36	causing	cause	VERB
cana-1705	245	37	volumes	volume	NOUN
cana-1705	245	38	elsewhere	elsewhere	ADV
cana-1705	245	39	to	to	PART
cana-1705	245	40	exceed	exceed	VERB
cana-1705	245	41	normal	normal	ADJ
cana-1705	245	42	conditions	condition	NOUN
cana-1705	245	43	.	.	PUNCT
cana-1705	246	1	to	to	PART
cana-1705	246	2	capture	capture	VERB
cana-1705	246	3	these	these	DET
cana-1705	246	4	spatial	spatial	ADJ
cana-1705	246	5	dependences	dependence	NOUN
cana-1705	246	6	following	follow	VERB
cana-1705	246	7	(	(	PUNCT
cana-1705	246	8	2	2	NUM
cana-1705	246	9	)	)	PUNCT
cana-1705	246	10	,	,	PUNCT
cana-1705	246	11	in	in	ADP
cana-1705	246	12	our	our	PRON
cana-1705	246	13	method	method	NOUN
cana-1705	246	14	we	we	PRON
cana-1705	246	15	include	include	VERB
cana-1705	246	16	the	the	DET
cana-1705	246	17	following	follow	VERB
cana-1705	246	18	suggested	suggest	VERB
cana-1705	246	19	spatial	spatial	ADJ
cana-1705	246	20	features	feature	NOUN
cana-1705	246	21	:	:	PUNCT
cana-1705	246	22	neighboring	neighboring	NOUN
cana-1705	246	23	road	road	NOUN
cana-1705	246	24	traffic	traffic	NOUN
cana-1705	246	25	:	:	PUNCT
cana-1705	246	26	the	the	DET
cana-1705	246	27	traffic	traffic	NOUN
cana-1705	246	28	volume	volume	NOUN
cana-1705	246	29	&	&	CCONJ
cana-1705	246	30	speed	speed	NOUN
cana-1705	246	31	on	on	ADP
cana-1705	246	32	neighboring	neighbor	VERB
cana-1705	246	33	road	road	NOUN
cana-1705	246	34	segments	segment	NOUN
cana-1705	246	35	as	as	ADP
cana-1705	246	36	features	feature	NOUN
cana-1705	246	37	.	.	PUNCT
cana-1705	247	1	these	these	DET
cana-1705	247	2	spatial	spatial	ADJ
cana-1705	247	3	aspects	aspect	NOUN
cana-1705	247	4	enable	enable	VERB
cana-1705	247	5	the	the	DET
cana-1705	247	6	lstm	lstm	PROPN
cana-1705	247	7	model	model	NOUN
cana-1705	247	8	to	to	PART
cana-1705	247	9	capture	capture	VERB
cana-1705	247	10	inter	inter	ADJ
cana-1705	247	11	-	-	ADJ
cana-1705	247	12	segment	segment	ADJ
cana-1705	247	13	dependencies	dependency	NOUN
cana-1705	247	14	and	and	CCONJ
cana-1705	247	15	improve	improve	VERB
cana-1705	247	16	traffic	traffic	NOUN
cana-1705	247	17	flow	flow	NOUN
cana-1705	247	18	predictions	prediction	NOUN
cana-1705	247	19	at	at	ADP
cana-1705	247	20	hot	hot	ADJ
cana-1705	247	21	spots	spot	NOUN
cana-1705	247	22	along	along	ADP
cana-1705	247	23	a	a	DET
cana-1705	247	24	given	give	VERB
cana-1705	247	25	road	road	NOUN
cana-1705	247	26	.	.	PUNCT
cana-1705	248	1	distance	distance	NOUN
cana-1705	248	2	to	to	ADP
cana-1705	248	3	major	major	ADJ
cana-1705	248	4	intersections	intersection	NOUN
cana-1705	248	5	:	:	PUNCT
cana-1705	248	6	how	how	SCONJ
cana-1705	248	7	far	far	ADV
cana-1705	248	8	or	or	CCONJ
cana-1705	248	9	close	close	VERB
cana-1705	248	10	the	the	DET
cana-1705	248	11	given	give	VERB
cana-1705	248	12	road	road	NOUN
cana-1705	248	13	segment	segment	NOUN
cana-1705	248	14	is	be	AUX
cana-1705	248	15	from	from	ADP
cana-1705	248	16	major	major	ADJ
cana-1705	248	17	intersections	intersection	NOUN
cana-1705	248	18	or	or	CCONJ
cana-1705	248	19	even	even	ADV
cana-1705	248	20	traffic	traffic	NOUN
cana-1705	248	21	signals	signal	NOUN
cana-1705	248	22	will	will	AUX
cana-1705	248	23	also	also	ADV
cana-1705	248	24	dictate	dictate	VERB
cana-1705	248	25	the	the	DET
cana-1705	248	26	flow	flow	NOUN
cana-1705	248	27	of	of	ADP
cana-1705	248	28	traffic	traffic	NOUN
cana-1705	248	29	.	.	PUNCT
cana-1705	249	1	the	the	DET
cana-1705	249	2	distance	distance	NOUN
cana-1705	249	3	to	to	ADP
cana-1705	249	4	the	the	DET
cana-1705	249	5	nearest	near	ADJ
cana-1705	249	6	major	major	ADJ
cana-1705	249	7	intersection	intersection	NOUN
cana-1705	249	8	is	be	AUX
cana-1705	249	9	considered	consider	VERB
cana-1705	249	10	as	as	ADP
cana-1705	249	11	a	a	DET
cana-1705	249	12	feature	feature	NOUN
cana-1705	249	13	since	since	SCONJ
cana-1705	249	14	road	road	NOUN
cana-1705	249	15	segments	segment	NOUN
cana-1705	249	16	closer	close	ADV
cana-1705	249	17	to	to	ADP
cana-1705	249	18	busy	busy	ADJ
cana-1705	249	19	intersections	intersection	NOUN
cana-1705	249	20	are	be	AUX
cana-1705	249	21	more	more	ADV
cana-1705	249	22	likely	likely	ADJ
cana-1705	249	23	to	to	PART
cana-1705	249	24	be	be	AUX
cana-1705	249	25	congested	congest	VERB
cana-1705	249	26	at	at	ADP
cana-1705	249	27	peak	peak	NOUN
cana-1705	249	28	hours	hour	NOUN
cana-1705	249	29	.	.	PUNCT
cana-1705	250	1	c.	c.	PROPN
cana-1705	250	2	external	external	PROPN
cana-1705	250	3	features	feature	VERB
cana-1705	250	4	traffic	traffic	NOUN
cana-1705	250	5	flow	flow	NOUN
cana-1705	250	6	reflects	reflect	VERB
cana-1705	250	7	external	external	ADJ
cana-1705	250	8	influences	influence	NOUN
cana-1705	250	9	,	,	PUNCT
cana-1705	250	10	such	such	ADJ
cana-1705	250	11	as	as	ADP
cana-1705	250	12	accidents	accident	NOUN
cana-1705	250	13	or	or	CCONJ
cana-1705	250	14	road	road	NOUN
cana-1705	250	15	construction	construction	NOUN
cana-1705	250	16	.	.	PUNCT
cana-1705	251	1	extra	extra	ADJ
cana-1705	251	2	features	feature	VERB
cana-1705	251	3	the	the	DET
cana-1705	251	4	information	information	NOUN
cana-1705	251	5	of	of	ADP
cana-1705	251	6	these	these	DET
cana-1705	251	7	external	external	ADJ
cana-1705	251	8	events	event	NOUN
cana-1705	251	9	are	be	AUX
cana-1705	251	10	captured	capture	VERB
cana-1705	251	11	through	through	ADP
cana-1705	251	12	additional	additional	ADJ
cana-1705	251	13	features	feature	NOUN
cana-1705	251	14	:	:	PUNCT
cana-1705	251	15	incident	incident	NOUN
cana-1705	251	16	reports	report	VERB
cana-1705	251	17	:	:	PUNCT
cana-1705	251	18	this	this	PRON
cana-1705	251	19	consists	consist	VERB
cana-1705	251	20	of	of	ADP
cana-1705	251	21	traffic	traffic	NOUN
cana-1705	251	22	incidents	incident	NOUN
cana-1705	251	23	that	that	PRON
cana-1705	251	24	are	be	AUX
cana-1705	251	25	reported	report	VERB
cana-1705	251	26	via	via	ADP
cana-1705	251	27	social	social	ADJ
cana-1705	251	28	media	medium	NOUN
cana-1705	251	29	,	,	PUNCT
cana-1705	251	30	navigation	navigation	NOUN
cana-1705	251	31	apps	app	NOUN
cana-1705	251	32	or	or	CCONJ
cana-1705	251	33	government	government	NOUN
cana-1705	251	34	resources	resource	NOUN
cana-1705	251	35	and	and	CCONJ
cana-1705	251	36	these	these	DET
cana-1705	251	37	incident	incident	NOUN
cana-1705	251	38	reports	report	NOUN
cana-1705	251	39	then	then	ADV
cana-1705	251	40	get	get	AUX
cana-1705	251	41	merged	merge	VERB
cana-1705	251	42	into	into	ADP
cana-1705	251	43	the	the	DET
cana-1705	251	44	dataset	dataset	NOUN
cana-1705	251	45	.	.	PUNCT
cana-1705	252	1	these	these	PRON
cana-1705	252	2	are	be	AUX
cana-1705	252	3	realtime	realtime	ADJ
cana-1705	252	4	reports	report	NOUN
cana-1705	252	5	for	for	ADP
cana-1705	252	6	notifications	notification	NOUN
cana-1705	252	7	of	of	ADP
cana-1705	252	8	accidents	accident	NOUN
cana-1705	252	9	,	,	PUNCT
cana-1705	252	10	road	road	NOUN
cana-1705	252	11	closures	closure	NOUN
cana-1705	252	12	or	or	CCONJ
cana-1705	252	13	other	other	ADJ
cana-1705	252	14	incidents	incident	NOUN
cana-1705	252	15	that	that	PRON
cana-1705	252	16	may	may	AUX
cana-1705	252	17	have	have	VERB
cana-1705	252	18	a	a	DET
cana-1705	252	19	negative	negative	ADJ
cana-1705	252	20	impact	impact	NOUN
cana-1705	252	21	on	on	ADP
cana-1705	252	22	traffic	traffic	NOUN
cana-1705	252	23	.	.	PUNCT
cana-1705	253	1	public	public	ADJ
cana-1705	253	2	events	event	NOUN
cana-1705	253	3	:	:	PUNCT
cana-1705	253	4	public	public	ADJ
cana-1705	253	5	events	event	NOUN
cana-1705	253	6	attract	attract	VERB
cana-1705	253	7	large	large	ADJ
cana-1705	253	8	crowds	crowd	NOUN
cana-1705	253	9	to	to	ADP
cana-1705	253	10	them	they	PRON
cana-1705	253	11	for	for	ADP
cana-1705	253	12	example	example	NOUN
cana-1705	253	13	concerts	concert	NOUN
cana-1705	253	14	,	,	PUNCT
cana-1705	253	15	sporting	sport	VERB
cana-1705	253	16	events	event	NOUN
cana-1705	253	17	and	and	CCONJ
cana-1705	253	18	so	so	ADV
cana-1705	253	19	on	on	ADV
cana-1705	253	20	.	.	PUNCT
cana-1705	254	1	we	we	PRON
cana-1705	254	2	include	include	VERB
cana-1705	254	3	features	feature	NOUN
cana-1705	254	4	indicating	indicate	VERB
cana-1705	254	5	the	the	DET
cana-1705	254	6	location	location	NOUN
cana-1705	254	7	,	,	PUNCT
cana-1705	254	8	time	time	NOUN
cana-1705	254	9	and	and	CCONJ
cana-1705	254	10	magnitude	magnitude	NOUN
cana-1705	254	11	of	of	ADP
cana-1705	254	12	these	these	DET
cana-1705	254	13	events	event	NOUN
cana-1705	254	14	to	to	PART
cana-1705	254	15	allow	allow	VERB
cana-1705	254	16	the	the	DET
cana-1705	254	17	model	model	NOUN
cana-1705	254	18	to	to	PART
cana-1705	254	19	anticipate	anticipate	VERB
cana-1705	254	20	an	an	DET
cana-1705	254	21	increase	increase	NOUN
cana-1705	254	22	in	in	ADP
cana-1705	254	23	traffic	traffic	NOUN
cana-1705	254	24	.	.	PUNCT
cana-1705	255	1	d.	d.	PROPN
cana-1705	255	2	model	model	PROPN
cana-1705	255	3	architecture	architecture	NOUN
cana-1705	255	4	/	/	SYM
cana-1705	255	5	training	training	NOUN
cana-1705	255	6	/	/	SYM
cana-1705	255	7	testing	testing	NOUN
cana-1705	255	8	using	use	VERB
cana-1705	255	9	lstm	lstm	ADJ
cana-1705	255	10	a.	a.	NOUN
cana-1705	255	11	lstm	lstm	PROPN
cana-1705	255	12	model	model	NOUN
cana-1705	255	13	overview	overview	NOUN
cana-1705	255	14	at	at	ADP
cana-1705	255	15	the	the	DET
cana-1705	255	16	heart	heart	NOUN
cana-1705	255	17	of	of	ADP
cana-1705	255	18	the	the	DET
cana-1705	255	19	method	method	NOUN
cana-1705	255	20	to	to	PART
cana-1705	255	21	be	be	AUX
cana-1705	255	22	proposed	propose	VERB
cana-1705	255	23	is	be	AUX
cana-1705	255	24	the	the	DET
cana-1705	255	25	long	long	ADJ
cana-1705	255	26	short	short	ADJ
cana-1705	255	27	-	-	PUNCT
cana-1705	255	28	term	term	NOUN
cana-1705	255	29	memory	memory	NOUN
cana-1705	255	30	(	(	PUNCT
cana-1705	255	31	lstm	lstm	NOUN
cana-1705	255	32	)	)	PUNCT
cana-1705	255	33	network	network	NOUN
cana-1705	255	34	,	,	PUNCT
cana-1705	255	35	which	which	PRON
cana-1705	255	36	is	be	AUX
cana-1705	255	37	a	a	DET
cana-1705	255	38	type	type	NOUN
cana-1705	255	39	of	of	ADP
cana-1705	255	40	recurrent	recurrent	ADJ
cana-1705	255	41	neural	neural	ADJ
cana-1705	255	42	network	network	NOUN
cana-1705	255	43	(	(	PUNCT
cana-1705	255	44	rnn	rnn	PROPN
cana-1705	255	45	)	)	PUNCT
cana-1705	255	46	intended	intend	VERB
cana-1705	255	47	for	for	ADP
cana-1705	255	48	sequence	sequence	NOUN
cana-1705	255	49	data	datum	NOUN
cana-1705	255	50	and	and	CCONJ
cana-1705	255	51	especially	especially	ADV
cana-1705	255	52	effective	effective	ADJ
cana-1705	255	53	at	at	ADP
cana-1705	255	54	capturing	capture	VERB
cana-1705	255	55	long	long	ADJ
cana-1705	255	56	-	-	PUNCT
cana-1705	255	57	range	range	NOUN
cana-1705	255	58	dependencies	dependency	NOUN
cana-1705	255	59	.	.	PUNCT
cana-1705	256	1	since	since	SCONJ
cana-1705	256	2	lstm	lstm	ADJ
cana-1705	256	3	units	unit	NOUN
cana-1705	256	4	can	can	AUX
cana-1705	256	5	maintain	maintain	VERB
cana-1705	256	6	and	and	CCONJ
cana-1705	256	7	update	update	VERB
cana-1705	256	8	memory	memory	NOUN
cana-1705	256	9	cells	cell	NOUN
cana-1705	256	10	to	to	PART
cana-1705	256	11	store	store	VERB
cana-1705	256	12	useful	useful	ADJ
cana-1705	256	13	information	information	NOUN
cana-1705	256	14	over	over	ADP
cana-1705	256	15	long	long	ADJ
cana-1705	256	16	sequences	sequence	NOUN
cana-1705	256	17	,	,	PUNCT
cana-1705	256	18	lstm	lstm	NOUN
cana-1705	256	19	is	be	AUX
cana-1705	256	20	an	an	DET
cana-1705	256	21	appropriate	appropriate	ADJ
cana-1705	256	22	algorithm	algorithm	NOUN
cana-1705	256	23	for	for	ADP
cana-1705	256	24	traffic	traffic	NOUN
cana-1705	256	25	flow	flow	NOUN
cana-1705	256	26	prediction	prediction	NOUN
cana-1705	256	27	.	.	PUNCT
cana-1705	257	1	t	t	PROPN
cana-1705	257	2	𝐶𝑡	𝐶𝑡	PROPN
cana-1705	257	3	=	=	PUNCT
cana-1705	257	4	𝑓𝑡	𝑓𝑡	PROPN
cana-1705	257	5	∗	∗	X
cana-1705	257	6	𝐶𝑡−1	𝐶𝑡−1	PROPN
cana-1705	258	1	+	+	CCONJ
cana-1705	258	2	𝑖𝑡	𝑖𝑡	NOUN
cana-1705	258	3	∗	∗	NOUN
cana-1705	258	4	𝐶	𝐶	PROPN
cana-1705	258	5	∼	∼	NOUN
cana-1705	258	6	𝑡	𝑡	NOUN
cana-1705	258	7	his	his	PRON
cana-1705	258	8	enables	enable	NOUN
cana-1705	258	9	the	the	DET
cana-1705	258	10	model	model	NOUN
cana-1705	258	11	to	to	PART
cana-1705	258	12	get	get	VERB
cana-1705	258	13	updates	update	NOUN
cana-1705	258	14	of	of	ADP
cana-1705	258	15	recent	recent	ADJ
cana-1705	258	16	and	and	CCONJ
cana-1705	258	17	far	far	ADV
cana-1705	258	18	past	past	ADP
cana-1705	258	19	traffic	traffic	NOUN
cana-1705	258	20	conditions	condition	NOUN
cana-1705	258	21	which	which	PRON
cana-1705	258	22	are	be	AUX
cana-1705	258	23	key	key	ADJ
cana-1705	258	24	aspects	aspect	NOUN
cana-1705	258	25	predicting	predict	VERB
cana-1705	258	26	upcoming	upcoming	ADJ
cana-1705	258	27	flow	flow	NOUN
cana-1705	258	28	of	of	ADP
cana-1705	258	29	traffic	traffic	NOUN
cana-1705	258	30	.	.	PUNCT
cana-1705	259	1	the	the	DET
cana-1705	259	2	lstm	lstm	PROPN
cana-1705	259	3	network	network	NOUN
cana-1705	259	4	design	design	NOUN
cana-1705	259	5	has	have	VERB
cana-1705	259	6	the	the	DET
cana-1705	259	7	following	follow	VERB
cana-1705	259	8	principal	principal	ADJ
cana-1705	259	9	entities	entity	NOUN
cana-1705	259	10	:	:	PUNCT
cana-1705	259	11	input	input	NOUN
cana-1705	259	12	layer	layer	NOUN
cana-1705	259	13	:	:	PUNCT
cana-1705	259	14	the	the	DET
cana-1705	259	15	first	first	ADJ
cana-1705	259	16	layer	layer	NOUN
cana-1705	259	17	which	which	PRON
cana-1705	259	18	receives	receive	VERB
cana-1705	259	19	the	the	DET
cana-1705	259	20	preprocessed	preprocesse	VERB
cana-1705	259	21	features	feature	NOUN
cana-1705	259	22	;	;	PUNCT
cana-1705	259	23	involves	involve	VERB
cana-1705	259	24	temporal	temporal	ADJ
cana-1705	259	25	,	,	PUNCT
cana-1705	259	26	spatial	spatial	ADJ
cana-1705	259	27	and	and	CCONJ
cana-1705	259	28	external	external	ADJ
cana-1705	259	29	variables	variable	NOUN
cana-1705	259	30	.	.	PUNCT
cana-1705	260	1	the	the	DET
cana-1705	260	2	feature	feature	NOUN
cana-1705	260	3	vector	vector	NOUN
cana-1705	260	4	at	at	ADP
cana-1705	260	5	a	a	DET
cana-1705	260	6	time	time	NOUN
cana-1705	260	7	step	step	NOUN
cana-1705	260	8	represents	represent	VERB
cana-1705	260	9	the	the	DET
cana-1705	260	10	traffic	traffic	NOUN
cana-1705	260	11	conditions	condition	NOUN
cana-1705	260	12	at	at	ADP
cana-1705	260	13	the	the	DET
cana-1705	260	14	corresponding	corresponding	ADJ
cana-1705	260	15	timestamp	timestamp	NOUN
cana-1705	260	16	.	.	PUNCT
cana-1705	261	1	𝑖𝑡	𝑖𝑡	NOUN
cana-1705	262	1	=	=	PUNCT
cana-1705	262	2	𝜎(𝑊𝑖	𝜎(𝑊𝑖	NOUN
cana-1705	262	3	⋅	⋅	PROPN
cana-1705	263	1	[	[	X
cana-1705	263	2	ℎ𝑡−1	ℎ𝑡−1	ADJ
cana-1705	263	3	,	,	PUNCT
cana-1705	263	4	𝑥𝑡	𝑥𝑡	ADP
cana-1705	263	5	]	]	X
cana-1705	263	6	+	+	CCONJ
cana-1705	263	7	𝑏𝑖	𝑏𝑖	NOUN
cana-1705	263	8	)	)	PUNCT
cana-1705	263	9	lstm	lstm	ADJ
cana-1705	263	10	layers	layer	NOUN
cana-1705	263	11	:	:	PUNCT
cana-1705	263	12	process	process	VERB
cana-1705	263	13	the	the	DET
cana-1705	263	14	input	input	NOUN
cana-1705	263	15	sequences	sequence	NOUN
cana-1705	263	16	and	and	CCONJ
cana-1705	263	17	maintain	maintain	VERB
cana-1705	263	18	hidden	hidden	ADJ
cana-1705	263	19	states	state	NOUN
cana-1705	263	20	that	that	PRON
cana-1705	263	21	holds	hold	VERB
cana-1705	263	22	the	the	DET
cana-1705	263	23	information	information	NOUN
cana-1705	263	24	regarding	regard	VERB
cana-1705	263	25	the	the	DET
cana-1705	263	26	dependencies	dependency	NOUN
cana-1705	263	27	between	between	ADP
cana-1705	263	28	the	the	DET
cana-1705	263	29	inputs	input	NOUN
cana-1705	263	30	over	over	ADP
cana-1705	263	31	time	time	NOUN
cana-1705	263	32	.	.	PUNCT
cana-1705	264	1	communications	communication	NOUN
cana-1705	264	2	on	on	ADP
cana-1705	264	3	applied	apply	VERB
cana-1705	264	4	nonlinear	nonlinear	ADJ
cana-1705	264	5	analysis	analysis	NOUN
cana-1705	264	6	issn	issn	NOUN
cana-1705	264	7	:	:	PUNCT
cana-1705	264	8	1074	1074	NUM
cana-1705	264	9	-	-	PUNCT
cana-1705	264	10	133x	133x	NUM
cana-1705	264	11	vol	vol	NOUN
cana-1705	264	12	32	32	NUM
cana-1705	264	13	no	no	NOUN
cana-1705	264	14	.	.	NOUN
cana-1705	264	15	2	2	NUM
cana-1705	264	16	(	(	PUNCT
cana-1705	264	17	2025	2025	NUM
cana-1705	264	18	)	)	PUNCT
cana-1705	264	19	15	15	NUM
cana-1705	264	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	264	21	𝐶	𝐶	PROPN
cana-1705	264	22	∼	∼	NOUN
cana-1705	264	23	𝑡	𝑡	NOUN
cana-1705	264	24	=	=	NOUN
cana-1705	264	25	tanh(𝑊𝐶	tanh(𝑊𝐶	NOUN
cana-1705	264	26	⋅	⋅	PROPN
cana-1705	265	1	[	[	X
cana-1705	265	2	ℎ𝑡−1	ℎ𝑡−1	ADJ
cana-1705	265	3	,	,	PUNCT
cana-1705	265	4	𝑥𝑡	𝑥𝑡	ADP
cana-1705	265	5	]	]	X
cana-1705	265	6	+	+	CCONJ
cana-1705	265	7	𝑏𝐶	𝑏𝐶	X
cana-1705	265	8	)	)	PUNCT
cana-1705	265	9	these	these	DET
cana-1705	265	10	layers	layer	NOUN
cana-1705	265	11	learn	learn	VERB
cana-1705	265	12	the	the	DET
cana-1705	265	13	relationships	relationship	NOUN
cana-1705	265	14	between	between	ADP
cana-1705	265	15	past	past	ADJ
cana-1705	265	16	states	state	NOUN
cana-1705	265	17	of	of	ADP
cana-1705	265	18	traffic	traffic	NOUN
cana-1705	265	19	and	and	CCONJ
cana-1705	265	20	the	the	DET
cana-1705	265	21	future	future	ADJ
cana-1705	265	22	state	state	NOUN
cana-1705	265	23	of	of	ADP
cana-1705	265	24	traffic	traffic	NOUN
cana-1705	265	25	.	.	PUNCT
cana-1705	266	1	the	the	DET
cana-1705	266	2	number	number	NOUN
cana-1705	266	3	of	of	ADP
cana-1705	266	4	memory	memory	NOUN
cana-1705	266	5	cells	cell	NOUN
cana-1705	266	6	in	in	ADP
cana-1705	266	7	each	each	DET
cana-1705	266	8	layer	layer	NOUN
cana-1705	266	9	and	and	CCONJ
cana-1705	266	10	the	the	DET
cana-1705	266	11	number	number	NOUN
cana-1705	266	12	of	of	ADP
cana-1705	266	13	lstm	lstm	ADJ
cana-1705	266	14	layers	layer	NOUN
cana-1705	266	15	are	be	AUX
cana-1705	266	16	also	also	ADV
cana-1705	266	17	hyperparameters	hyperparameter	NOUN
cana-1705	266	18	that	that	PRON
cana-1705	266	19	will	will	AUX
cana-1705	266	20	be	be	AUX
cana-1705	266	21	set	set	VERB
cana-1705	266	22	during	during	ADP
cana-1705	266	23	training	training	NOUN
cana-1705	266	24	.	.	PUNCT
cana-1705	267	1	𝑓𝑡	𝑓𝑡	NOUN
cana-1705	267	2	=	=	PUNCT
cana-1705	267	3	𝜎(𝑊𝑓	𝜎(𝑊𝑓	NOUN
cana-1705	268	1	⋅	⋅	PROPN
cana-1705	269	1	[	[	X
cana-1705	269	2	ℎ𝑡−1	ℎ𝑡−1	ADJ
cana-1705	269	3	,	,	PUNCT
cana-1705	269	4	𝑥𝑡	𝑥𝑡	ADP
cana-1705	269	5	]	]	PUNCT
cana-1705	269	6	+	+	CCONJ
cana-1705	269	7	𝑏𝑓	𝑏𝑓	CCONJ
cana-1705	269	8	)	)	PUNCT
cana-1705	269	9	fully	fully	ADV
cana-1705	269	10	connected	connect	VERB
cana-1705	269	11	layers(fc	layers(fc	ADV
cana-1705	269	12	):	):	PUNCT
cana-1705	269	13	in	in	ADP
cana-1705	269	14	the	the	DET
cana-1705	269	15	end	end	NOUN
cana-1705	269	16	,	,	PUNCT
cana-1705	269	17	after	after	SCONJ
cana-1705	269	18	the	the	DET
cana-1705	269	19	information	information	NOUN
cana-1705	269	20	has	have	AUX
cana-1705	269	21	been	be	AUX
cana-1705	269	22	extracted	extract	VERB
cana-1705	269	23	by	by	ADP
cana-1705	269	24	the	the	DET
cana-1705	269	25	lstm	lstm	PROPN
cana-1705	269	26	units	unit	NOUN
cana-1705	269	27	,	,	PUNCT
cana-1705	269	28	this	this	PRON
cana-1705	269	29	said	say	VERB
cana-1705	269	30	information	information	NOUN
cana-1705	269	31	is	be	AUX
cana-1705	269	32	combined	combine	VERB
cana-1705	269	33	together	together	ADV
cana-1705	269	34	and	and	CCONJ
cana-1705	269	35	passed	pass	VERB
cana-1705	269	36	onto	onto	ADP
cana-1705	269	37	a	a	DET
cana-1705	269	38	final	final	ADJ
cana-1705	269	39	set	set	NOUN
cana-1705	269	40	of	of	ADP
cana-1705	269	41	fc	fc	PROPN
cana-1705	269	42	layers	layer	NOUN
cana-1705	269	43	to	to	PART
cana-1705	269	44	get	get	VERB
cana-1705	269	45	an	an	DET
cana-1705	269	46	output	output	NOUN
cana-1705	269	47	.	.	PUNCT
cana-1705	270	1	nonlinearity	nonlinearity	NOUN
cana-1705	270	2	is	be	AUX
cana-1705	270	3	captured	capture	VERB
cana-1705	270	4	through	through	ADP
cana-1705	270	5	these	these	DET
cana-1705	270	6	layers	layer	NOUN
cana-1705	270	7	,	,	PUNCT
cana-1705	270	8	which	which	PRON
cana-1705	270	9	help	help	VERB
cana-1705	270	10	in	in	ADP
cana-1705	270	11	understanding	understand	VERB
cana-1705	270	12	the	the	DET
cana-1705	270	13	more	more	ADV
cana-1705	270	14	complex	complex	ADJ
cana-1705	270	15	patterns	pattern	NOUN
cana-1705	270	16	of	of	ADP
cana-1705	270	17	the	the	DET
cana-1705	270	18	data	datum	NOUN
cana-1705	270	19	.	.	PUNCT
cana-1705	271	1	output	output	NOUN
cana-1705	271	2	layer	layer	NOUN
cana-1705	271	3	:	:	PUNCT
cana-1705	271	4	it	it	PRON
cana-1705	271	5	is	be	AUX
cana-1705	271	6	the	the	DET
cana-1705	271	7	topmost	topmost	ADJ
cana-1705	271	8	layer	layer	NOUN
cana-1705	271	9	which	which	PRON
cana-1705	271	10	gives	give	VERB
cana-1705	271	11	the	the	DET
cana-1705	271	12	forecasted	forecast	VERB
cana-1705	271	13	traffic	traffic	NOUN
cana-1705	271	14	flow	flow	NOUN
cana-1705	271	15	of	of	ADP
cana-1705	271	16	the	the	DET
cana-1705	271	17	next	next	ADJ
cana-1705	271	18	time	time	NOUN
cana-1705	271	19	step	step	NOUN
cana-1705	271	20	.	.	PUNCT
cana-1705	272	1	ℎ𝑡	ℎ𝑡	NOUN
cana-1705	272	2	=	=	PUNCT
cana-1705	272	3	𝑜𝑡	𝑜𝑡	PROPN
cana-1705	272	4	∗	∗	NOUN
cana-1705	272	5	tanh(𝐶𝑡	tanh(𝐶𝑡	PROPN
cana-1705	272	6	)	)	PUNCT
cana-1705	272	7	for	for	ADP
cana-1705	272	8	our	our	PRON
cana-1705	272	9	use	use	NOUN
cana-1705	272	10	cases	case	NOUN
cana-1705	272	11	this	this	DET
cana-1705	272	12	output	output	NOUN
cana-1705	272	13	might	might	AUX
cana-1705	272	14	describe	describe	VERB
cana-1705	272	15	traffic	traffic	NOUN
cana-1705	272	16	volume	volume	NOUN
cana-1705	272	17	,	,	PUNCT
cana-1705	272	18	vehicle	vehicle	NOUN
cana-1705	272	19	speed	speed	NOUN
cana-1705	272	20	or	or	CCONJ
cana-1705	272	21	road	road	NOUN
cana-1705	272	22	occupancy	occupancy	NOUN
cana-1705	272	23	at	at	ADP
cana-1705	272	24	any	any	DET
cana-1705	272	25	location	location	NOUN
cana-1705	272	26	and	and	CCONJ
cana-1705	272	27	time	time	NOUN
cana-1705	272	28	.	.	PUNCT
cana-1705	273	1	𝑜𝑡	𝑜𝑡	VERB
cana-1705	273	2	=	=	PUNCT
cana-1705	273	3	𝜎(𝑊𝑜	𝜎(𝑊𝑜	NOUN
cana-1705	273	4	⋅	⋅	PROPN
cana-1705	274	1	[	[	X
cana-1705	274	2	ℎ𝑡−1	ℎ𝑡−1	ADJ
cana-1705	274	3	,	,	PUNCT
cana-1705	274	4	𝑥𝑡	𝑥𝑡	ADP
cana-1705	274	5	]	]	X
cana-1705	274	6	+	+	CCONJ
cana-1705	274	7	𝑏𝑜	𝑏𝑜	X
cana-1705	274	8	)	)	PUNCT
cana-1705	274	9	b.	b.	NOUN
cana-1705	274	10	model	model	NOUN
cana-1705	274	11	training	training	NOUN
cana-1705	274	12	process	process	NOUN
cana-1705	274	13	training	train	VERB
cana-1705	274	14	the	the	DET
cana-1705	274	15	lstm	lstm	PROPN
cana-1705	274	16	model	model	NOUN
cana-1705	274	17	implies	imply	VERB
cana-1705	274	18	optimizing	optimize	VERB
cana-1705	274	19	the	the	DET
cana-1705	274	20	parameters	parameter	NOUN
cana-1705	274	21	such	such	ADJ
cana-1705	274	22	as	as	ADP
cana-1705	274	23	weights	weight	NOUN
cana-1705	274	24	and	and	CCONJ
cana-1705	274	25	biases	bias	NOUN
cana-1705	274	26	of	of	ADP
cana-1705	274	27	the	the	DET
cana-1705	274	28	network	network	NOUN
cana-1705	274	29	with	with	ADP
cana-1705	274	30	historical	historical	ADJ
cana-1705	274	31	traffic	traffic	NOUN
cana-1705	274	32	data	datum	NOUN
cana-1705	274	33	from	from	ADP
cana-1705	274	34	a	a	DET
cana-1705	274	35	training	training	NOUN
cana-1705	274	36	dataset	dataset	NOUN
cana-1705	274	37	.	.	PUNCT
cana-1705	275	1	the	the	DET
cana-1705	275	2	above	above	ADJ
cana-1705	275	3	process	process	NOUN
cana-1705	275	4	is	be	AUX
cana-1705	275	5	applied	apply	VERB
cana-1705	275	6	in	in	ADP
cana-1705	275	7	the	the	DET
cana-1705	275	8	training	training	NOUN
cana-1705	275	9	using	use	VERB
cana-1705	275	10	backpropagation	backpropagation	NOUN
cana-1705	275	11	through	through	ADP
cana-1705	275	12	time	time	NOUN
cana-1705	275	13	(	(	PUNCT
cana-1705	275	14	bptt	bptt	NOUN
cana-1705	275	15	)	)	PUNCT
cana-1705	275	16	,	,	PUNCT
cana-1705	275	17	a	a	DET
cana-1705	275	18	variant	variant	NOUN
cana-1705	275	19	of	of	ADP
cana-1705	275	20	the	the	DET
cana-1705	275	21	backpropagation	backpropagation	NOUN
cana-1705	275	22	algorithm	algorithm	NOUN
cana-1705	275	23	,	,	PUNCT
cana-1705	275	24	which	which	PRON
cana-1705	275	25	we	we	PRON
cana-1705	275	26	modify	modify	VERB
cana-1705	275	27	for	for	ADP
cana-1705	275	28	recurrent	recurrent	ADJ
cana-1705	275	29	networks	network	NOUN
cana-1705	275	30	like	like	ADP
cana-1705	275	31	lstms	lstms	NOUN
cana-1705	275	32	.	.	PUNCT
cana-1705	276	1	loss	loss	NOUN
cana-1705	276	2	function	function	NOUN
cana-1705	276	3	:	:	PUNCT
cana-1705	276	4	mean	mean	VERB
cana-1705	276	5	squared	square	VERB
cana-1705	276	6	error	error	NOUN
cana-1705	276	7	(	(	PUNCT
cana-1705	276	8	mse	mse	NOUN
cana-1705	276	9	)	)	PUNCT
cana-1705	276	10	is	be	AUX
cana-1705	276	11	typically	typically	ADV
cana-1705	276	12	used	use	VERB
cana-1705	276	13	as	as	ADP
cana-1705	276	14	the	the	DET
cana-1705	276	15	loss	loss	NOUN
cana-1705	276	16	function	function	NOUN
cana-1705	276	17	for	for	ADP
cana-1705	276	18	regression	regression	NOUN
cana-1705	276	19	tasks	task	NOUN
cana-1705	276	20	such	such	ADJ
cana-1705	276	21	as	as	ADP
cana-1705	276	22	predicting	predict	VERB
cana-1705	276	23	traffic	traffic	NOUN
cana-1705	276	24	flow	flow	NOUN
cana-1705	276	25	.	.	PUNCT
cana-1705	277	1	the	the	DET
cana-1705	277	2	mse	mse	NOUN
cana-1705	277	3	measures	measure	VERB
cana-1705	277	4	the	the	DET
cana-1705	277	5	average	average	NOUN
cana-1705	277	6	of	of	ADP
cana-1705	277	7	squared	square	VERB
cana-1705	277	8	differences	difference	NOUN
cana-1705	277	9	between	between	ADP
cana-1705	277	10	substitute	substitute	NOUN
cana-1705	277	11	and	and	CCONJ
cana-1705	277	12	actual	actual	ADJ
cana-1705	277	13	traffic	traffic	NOUN
cana-1705	277	14	values	value	NOUN
cana-1705	277	15	,	,	PUNCT
cana-1705	277	16	reflecting	reflect	VERB
cana-1705	277	17	the	the	DET
cana-1705	277	18	error	error	NOUN
cana-1705	277	19	level	level	NOUN
cana-1705	277	20	of	of	ADP
cana-1705	277	21	the	the	DET
cana-1705	277	22	model	model	NOUN
cana-1705	277	23	prediction	prediction	NOUN
cana-1705	277	24	.	.	PUNCT
cana-1705	278	1	algorithm	algorithm	NOUN
cana-1705	278	2	1	1	NUM
cana-1705	278	3	:	:	PUNCT
cana-1705	278	4	lstm	lstm	NOUN
cana-1705	278	5	model	model	NOUN
cana-1705	278	6	training	train	VERB
cana-1705	278	7	1	1	NUM
cana-1705	278	8	.	.	PUNCT
cana-1705	279	1	input	input	NOUN
cana-1705	279	2	:	:	PUNCT
cana-1705	279	3	preprocessed	preprocesse	VERB
cana-1705	279	4	traffic	traffic	NOUN
cana-1705	279	5	data	datum	NOUN
cana-1705	279	6	𝑋	𝑋	NOUN
cana-1705	279	7	=	=	SYM
cana-1705	279	8	{	{	PUNCT
cana-1705	279	9	𝑥1	𝑥1	NOUN
cana-1705	279	10	,	,	PUNCT
cana-1705	279	11	𝑥2	𝑥2	NOUN
cana-1705	279	12	,	,	PUNCT
cana-1705	279	13	…	…	PUNCT
cana-1705	279	14	,	,	PUNCT
cana-1705	279	15	𝑥𝑛	𝑥𝑛	VERB
cana-1705	279	16	}	}	PUNCT
cana-1705	279	17	and	and	CCONJ
cana-1705	279	18	corresponding	correspond	VERB
cana-1705	279	19	target	target	NOUN
cana-1705	279	20	values	value	NOUN
cana-1705	279	21	𝑌	𝑌	PROPN
cana-1705	279	22	=	=	SYM
cana-1705	279	23	{	{	PUNCT
cana-1705	279	24	𝑦1	𝑦1	PROPN
cana-1705	279	25	,	,	PUNCT
cana-1705	279	26	𝑦2	𝑦2	NOUN
cana-1705	279	27	,	,	PUNCT
cana-1705	279	28	…	…	PUNCT
cana-1705	279	29	,	,	PUNCT
cana-1705	279	30	𝑦𝑛	𝑦𝑛	NOUN
cana-1705	279	31	}	}	PUNCT
cana-1705	279	32	.	.	PUNCT
cana-1705	280	1	2	2	X
cana-1705	280	2	.	.	X
cana-1705	280	3	initialize	initialize	VERB
cana-1705	280	4	lstm	lstm	ADJ
cana-1705	280	5	network	network	NOUN
cana-1705	280	6	parameters	parameter	NOUN
cana-1705	280	7	:	:	PUNCT
cana-1705	280	8	weights	weight	VERB
cana-1705	280	9	𝑊	𝑊	PROPN
cana-1705	280	10	,	,	PUNCT
cana-1705	280	11	biases	bias	VERB
cana-1705	280	12	𝑏	𝑏	NOUN
cana-1705	280	13	,	,	PUNCT
cana-1705	280	14	learning	learn	VERB
cana-1705	280	15	rate	rate	NOUN
cana-1705	280	16	𝜂.	𝜂.	NOUN
cana-1705	280	17	3	3	X
cana-1705	280	18	.	.	X
cana-1705	280	19	for	for	ADP
cana-1705	280	20	each	each	DET
cana-1705	280	21	epoch	epoch	NOUN
cana-1705	280	22	:	:	PUNCT
cana-1705	280	23	o	o	NOUN
cana-1705	280	24	for	for	ADP
cana-1705	280	25	each	each	DET
cana-1705	280	26	time	time	NOUN
cana-1705	280	27	step	step	NOUN
cana-1705	280	28	𝑡	𝑡	NOUN
cana-1705	280	29	:	:	PUNCT
cana-1705	280	30	▪	▪	ADJ
cana-1705	280	31	compute	compute	NOUN
cana-1705	280	32	the	the	DET
cana-1705	280	33	forget	forget	NOUN
cana-1705	280	34	gate	gate	NOUN
cana-1705	280	35	𝑓𝑡	𝑓𝑡	PROPN
cana-1705	280	36	=	=	PUNCT
cana-1705	280	37	𝜎(𝑊𝑓	𝜎(𝑊𝑓	NOUN
cana-1705	280	38	⋅	⋅	PROPN
cana-1705	281	1	[	[	X
cana-1705	281	2	ℎ𝑡−1	ℎ𝑡−1	ADJ
cana-1705	281	3	,	,	PUNCT
cana-1705	281	4	𝑥𝑡	𝑥𝑡	ADP
cana-1705	281	5	]	]	PUNCT
cana-1705	281	6	+	+	CCONJ
cana-1705	281	7	𝑏𝑓	𝑏𝑓	ADJ
cana-1705	281	8	)	)	PUNCT
cana-1705	281	9	.	.	PUNCT
cana-1705	282	1	▪	▪	ADJ
cana-1705	282	2	compute	compute	VERB
cana-1705	282	3	the	the	DET
cana-1705	282	4	input	input	NOUN
cana-1705	282	5	gate	gate	NOUN
cana-1705	282	6	𝑖𝑡	𝑖𝑡	PUNCT
cana-1705	283	1	=	=	PUNCT
cana-1705	283	2	𝜎(𝑊𝑖	𝜎(𝑊𝑖	NOUN
cana-1705	283	3	⋅	⋅	PROPN
cana-1705	284	1	[	[	X
cana-1705	284	2	ℎ𝑡−1	ℎ𝑡−1	ADJ
cana-1705	284	3	,	,	PUNCT
cana-1705	284	4	𝑥𝑡	𝑥𝑡	ADP
cana-1705	284	5	]	]	X
cana-1705	284	6	+	+	CCONJ
cana-1705	284	7	𝑏𝑖	𝑏𝑖	NOUN
cana-1705	284	8	)	)	PUNCT
cana-1705	284	9	.	.	PUNCT
cana-1705	285	1	▪	▪	ADJ
cana-1705	285	2	update	update	VERB
cana-1705	285	3	the	the	DET
cana-1705	285	4	cell	cell	NOUN
cana-1705	285	5	state	state	NOUN
cana-1705	285	6	𝐶𝑡	𝐶𝑡	PROPN
cana-1705	285	7	=	=	PROPN
cana-1705	285	8	𝑓𝑡	𝑓𝑡	PROPN
cana-1705	285	9	∗	∗	X
cana-1705	285	10	𝐶𝑡−1	𝐶𝑡−1	PROPN
cana-1705	285	11	+	+	CCONJ
cana-1705	285	12	𝑖𝑡	𝑖𝑡	PROPN
cana-1705	285	13	∗	∗	PROPN
cana-1705	285	14	tanh(𝑊𝐶	tanh(𝑊𝐶	PROPN
cana-1705	285	15	⋅	⋅	PROPN
cana-1705	286	1	[	[	X
cana-1705	286	2	ℎ𝑡−1	ℎ𝑡−1	ADJ
cana-1705	286	3	,	,	PUNCT
cana-1705	286	4	𝑥𝑡	𝑥𝑡	ADP
cana-1705	286	5	]	]	X
cana-1705	286	6	+	+	CCONJ
cana-1705	286	7	𝑏𝐶	𝑏𝐶	NUM
cana-1705	286	8	)	)	PUNCT
cana-1705	286	9	.	.	PUNCT
cana-1705	287	1	▪	▪	ADJ
cana-1705	287	2	compute	compute	VERB
cana-1705	287	3	the	the	DET
cana-1705	287	4	output	output	NOUN
cana-1705	287	5	gate	gate	NOUN
cana-1705	287	6	𝑜𝑡	𝑜𝑡	NOUN
cana-1705	287	7	=	=	PUNCT
cana-1705	287	8	𝜎(𝑊𝑜	𝜎(𝑊𝑜	NOUN
cana-1705	287	9	⋅	⋅	PROPN
cana-1705	288	1	[	[	X
cana-1705	288	2	ℎ𝑡−1	ℎ𝑡−1	ADJ
cana-1705	288	3	,	,	PUNCT
cana-1705	288	4	𝑥𝑡	𝑥𝑡	ADP
cana-1705	288	5	]	]	X
cana-1705	289	1	+	+	CCONJ
cana-1705	289	2	𝑏𝑜	𝑏𝑜	ADJ
cana-1705	289	3	)	)	PUNCT
cana-1705	289	4	.	.	PUNCT
cana-1705	290	1	▪	▪	ADJ
cana-1705	290	2	compute	compute	VERB
cana-1705	290	3	the	the	DET
cana-1705	290	4	hidden	hidden	ADJ
cana-1705	290	5	state	state	NOUN
cana-1705	290	6	ℎ𝑡	ℎ𝑡	NOUN
cana-1705	290	7	=	=	PUNCT
cana-1705	290	8	𝑜𝑡	𝑜𝑡	NOUN
cana-1705	290	9	∗	∗	NOUN
cana-1705	290	10	tanh(𝐶𝑡	tanh(𝐶𝑡	PROPN
cana-1705	290	11	)	)	PUNCT
cana-1705	290	12	.	.	PUNCT
cana-1705	291	1	o	o	PROPN
cana-1705	291	2	compute	compute	NOUN
cana-1705	291	3	the	the	DET
cana-1705	291	4	predicted	predict	VERB
cana-1705	291	5	output	output	NOUN
cana-1705	291	6	�	�	PROPN
cana-1705	291	7	̂	̂	NOUN
cana-1705	291	8	�	�	NOUN
cana-1705	291	9	𝑡.	𝑡.	NOUN
cana-1705	291	10	communications	communication	NOUN
cana-1705	291	11	on	on	ADP
cana-1705	291	12	applied	apply	VERB
cana-1705	291	13	nonlinear	nonlinear	ADJ
cana-1705	291	14	analysis	analysis	NOUN
cana-1705	291	15	issn	issn	NOUN
cana-1705	291	16	:	:	PUNCT
cana-1705	291	17	1074	1074	NUM
cana-1705	291	18	-	-	PUNCT
cana-1705	291	19	133x	133x	NUM
cana-1705	291	20	vol	vol	NOUN
cana-1705	291	21	32	32	NUM
cana-1705	291	22	no	no	NOUN
cana-1705	291	23	.	.	NOUN
cana-1705	291	24	2	2	NUM
cana-1705	291	25	(	(	PUNCT
cana-1705	291	26	2025	2025	NUM
cana-1705	291	27	)	)	PUNCT
cana-1705	291	28	16	16	NUM
cana-1705	291	29	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	291	30	o	o	NOUN
cana-1705	291	31	calculate	calculate	VERB
cana-1705	291	32	the	the	DET
cana-1705	291	33	loss	loss	NOUN
cana-1705	291	34	𝐿	𝐿	NOUN
cana-1705	291	35	=	=	SYM
cana-1705	291	36	1	1	NUM
cana-1705	291	37	𝑛	𝑛	PRON
cana-1705	291	38	∑(𝑦𝑡	∑(𝑦𝑡	PROPN
cana-1705	292	1	−	−	PROPN
cana-1705	292	2	�	�	PROPN
cana-1705	292	3	̂	̂	NOUN
cana-1705	292	4	�	�	NOUN
cana-1705	292	5	𝑡	𝑡	NOUN
cana-1705	292	6	)	)	PUNCT
cana-1705	292	7	2	2	NUM
cana-1705	292	8	.	.	PUNCT
cana-1705	292	9	o	o	NOUN
cana-1705	292	10	update	update	NOUN
cana-1705	292	11	network	network	NOUN
cana-1705	292	12	parameters	parameter	NOUN
cana-1705	292	13	via	via	ADP
cana-1705	292	14	gradient	gradient	ADJ
cana-1705	292	15	descent	descent	NOUN
cana-1705	292	16	.	.	PUNCT
cana-1705	293	1	4	4	X
cana-1705	293	2	.	.	X
cana-1705	293	3	repeat	repeat	VERB
cana-1705	293	4	until	until	ADP
cana-1705	293	5	convergence	convergence	NOUN
cana-1705	293	6	or	or	CCONJ
cana-1705	293	7	a	a	DET
cana-1705	293	8	maximum	maximum	ADJ
cana-1705	293	9	number	number	NOUN
cana-1705	293	10	of	of	ADP
cana-1705	293	11	epochs	epoch	NOUN
cana-1705	293	12	.	.	PUNCT
cana-1705	294	1	5	5	X
cana-1705	294	2	.	.	X
cana-1705	294	3	output	output	NOUN
cana-1705	294	4	:	:	PUNCT
cana-1705	294	5	trained	train	VERB
cana-1705	294	6	lstm	lstm	PROPN
cana-1705	294	7	model	model	NOUN
cana-1705	294	8	.	.	PUNCT
cana-1705	295	1	optimizer	optimizer	NOUN
cana-1705	295	2	(	(	PUNCT
cana-1705	295	3	used	use	VERB
cana-1705	295	4	usually	usually	ADV
cana-1705	295	5	adam	adam	PROPN
cana-1705	295	6	,	,	PUNCT
cana-1705	295	7	an	an	DET
cana-1705	295	8	efficient	efficient	ADJ
cana-1705	295	9	and	and	CCONJ
cana-1705	295	10	gradient	gradient	NOUN
cana-1705	295	11	noise	noise	NOUN
cana-1705	295	12	handling	handling	NOUN
cana-1705	295	13	optimizer	optimizer	NOUN
cana-1705	295	14	for	for	ADP
cana-1705	295	15	training	train	VERB
cana-1705	295	16	large	large	ADJ
cana-1705	295	17	datasets	dataset	NOUN
cana-1705	295	18	)	)	PUNCT
cana-1705	295	19	since	since	SCONJ
cana-1705	295	20	adam	adam	PROPN
cana-1705	295	21	changes	change	VERB
cana-1705	295	22	the	the	DET
cana-1705	295	23	learning	learning	NOUN
cana-1705	295	24	rate	rate	NOUN
cana-1705	295	25	as	as	ADP
cana-1705	295	26	training	training	NOUN
cana-1705	295	27	progresses	progress	NOUN
cana-1705	295	28	,	,	PUNCT
cana-1705	295	29	it	it	PRON
cana-1705	295	30	can	can	AUX
cana-1705	295	31	help	help	VERB
cana-1705	295	32	the	the	DET
cana-1705	295	33	model	model	NOUN
cana-1705	295	34	to	to	PART
cana-1705	295	35	converge	converge	VERB
cana-1705	295	36	in	in	ADP
cana-1705	295	37	less	less	ADJ
cana-1705	295	38	time	time	NOUN
cana-1705	295	39	as	as	ADP
cana-1705	295	40	compared	compare	VERB
cana-1705	295	41	to	to	ADP
cana-1705	295	42	traditional	traditional	ADJ
cana-1705	295	43	stochastic	stochastic	ADJ
cana-1705	295	44	gradient	gradient	ADJ
cana-1705	295	45	descent	descent	NOUN
cana-1705	295	46	(	(	PUNCT
cana-1705	295	47	sgd	sgd	PROPN
cana-1705	295	48	)	)	PUNCT
cana-1705	295	49	.	.	PUNCT
cana-1705	296	1	𝜃	𝜃	X
cana-1705	297	1	=	=	PUNCT
cana-1705	297	2	𝜃	𝜃	NUM
cana-1705	297	3	−	−	NOUN
cana-1705	297	4	𝜂∇𝜃𝐽(𝜃	𝜂∇𝜃𝐽(𝜃	NOUN
cana-1705	297	5	)	)	PUNCT
cana-1705	297	6	regularization	regularization	NOUN
cana-1705	297	7	:	:	PUNCT
cana-1705	297	8	regularization	regularization	NOUN
cana-1705	297	9	techniques	technique	NOUN
cana-1705	297	10	i.e.	i.e.	X
cana-1705	297	11	dropout	dropout	NOUN
cana-1705	297	12	on	on	ADP
cana-1705	297	13	the	the	DET
cana-1705	297	14	lstm	lstm	ADJ
cana-1705	297	15	layers	layer	NOUN
cana-1705	297	16	to	to	PART
cana-1705	297	17	prevent	prevent	VERB
cana-1705	297	18	overfitting	overfitte	VERB
cana-1705	297	19	dropout	dropout	NOUN
cana-1705	297	20	involves	involve	VERB
cana-1705	297	21	setting	set	VERB
cana-1705	297	22	a	a	DET
cana-1705	297	23	fraction	fraction	NOUN
cana-1705	297	24	of	of	ADP
cana-1705	297	25	the	the	DET
cana-1705	297	26	neurons	neuron	NOUN
cana-1705	297	27	to	to	ADP
cana-1705	297	28	zero	zero	NUM
cana-1705	297	29	during	during	ADP
cana-1705	297	30	training	training	NOUN
cana-1705	297	31	,	,	PUNCT
cana-1705	297	32	which	which	PRON
cana-1705	297	33	prevents	prevent	VERB
cana-1705	297	34	overfitting	overfitte	VERB
cana-1705	297	35	and	and	CCONJ
cana-1705	297	36	promotes	promote	VERB
cana-1705	297	37	generalization	generalization	NOUN
cana-1705	297	38	.	.	PUNCT
cana-1705	298	1	c.	c.	PROPN
cana-1705	298	2	hyperparameter	hyperparameter	NOUN
cana-1705	298	3	tuning	tune	VERB
cana-1705	298	4	the	the	DET
cana-1705	298	5	lstm	lstm	PROPN
cana-1705	298	6	model	model	NOUN
cana-1705	298	7	performance	performance	NOUN
cana-1705	298	8	is	be	AUX
cana-1705	298	9	very	very	ADV
cana-1705	298	10	much	much	ADV
cana-1705	298	11	dependent	dependent	ADJ
cana-1705	298	12	on	on	ADP
cana-1705	298	13	the	the	DET
cana-1705	298	14	hyperparameters	hyperparameter	NOUN
cana-1705	298	15	such	such	ADJ
cana-1705	298	16	as	as	ADP
cana-1705	298	17	no	no	PRON
cana-1705	298	18	of	of	ADP
cana-1705	298	19	layers	layer	NOUN
cana-1705	298	20	,	,	PUNCT
cana-1705	298	21	no	no	PRON
cana-1705	298	22	of	of	ADP
cana-1705	298	23	memory	memory	NOUN
cana-1705	298	24	cells	cell	NOUN
cana-1705	298	25	per	per	ADP
cana-1705	298	26	layer	layer	NOUN
cana-1705	298	27	,	,	PUNCT
cana-1705	298	28	learning	learn	VERB
cana-1705	298	29	rate	rate	NOUN
cana-1705	298	30	and	and	CCONJ
cana-1705	298	31	drop	drop	VERB
cana-1705	298	32	out	out	ADP
cana-1705	298	33	rates	rate	NOUN
cana-1705	298	34	.	.	PUNCT
cana-1705	299	1	hyper	hyper	ADJ
cana-1705	299	2	parameter	parameter	NOUN
cana-1705	299	3	tuning	tuning	NOUN
cana-1705	299	4	is	be	AUX
cana-1705	299	5	done	do	VERB
cana-1705	299	6	with	with	ADP
cana-1705	299	7	tools	tool	NOUN
cana-1705	299	8	like	like	ADP
cana-1705	299	9	grid	grid	NOUN
cana-1705	299	10	search	search	NOUN
cana-1705	299	11	or	or	CCONJ
cana-1705	299	12	random	random	ADJ
cana-1705	299	13	search	search	NOUN
cana-1705	299	14	where	where	SCONJ
cana-1705	299	15	various	various	ADJ
cana-1705	299	16	combinations	combination	NOUN
cana-1705	299	17	of	of	ADP
cana-1705	299	18	hyper	hyper	ADJ
cana-1705	299	19	parameters	parameter	NOUN
cana-1705	299	20	are	be	AUX
cana-1705	299	21	tried	try	VERB
cana-1705	299	22	out	out	ADP
cana-1705	299	23	and	and	CCONJ
cana-1705	299	24	model	model	NOUN
cana-1705	299	25	is	be	AUX
cana-1705	299	26	validated	validate	VERB
cana-1705	299	27	on	on	ADP
cana-1705	299	28	a	a	DET
cana-1705	299	29	validation	validation	NOUN
cana-1705	299	30	set	set	NOUN
cana-1705	299	31	.	.	PUNCT
cana-1705	300	1	d.	d.	PROPN
cana-1705	300	2	fine	fine	PROPN
cana-1705	300	3	tuning	tuning	NOUN
cana-1705	300	4	and	and	CCONJ
cana-1705	300	5	evaluation	evaluation	NOUN
cana-1705	300	6	of	of	ADP
cana-1705	300	7	model	model	NOUN
cana-1705	300	8	finally	finally	ADV
cana-1705	300	9	,	,	PUNCT
cana-1705	300	10	the	the	DET
cana-1705	300	11	lstm	lstm	NOUN
cana-1705	300	12	model	model	NOUN
cana-1705	300	13	is	be	AUX
cana-1705	300	14	validated	validate	VERB
cana-1705	300	15	and	and	CCONJ
cana-1705	300	16	tested	test	VERB
cana-1705	300	17	with	with	ADP
cana-1705	300	18	a	a	DET
cana-1705	300	19	unseen	unseen	ADJ
cana-1705	300	20	test	test	NOUN
cana-1705	300	21	dataset	dataset	VERB
cana-1705	300	22	to	to	PART
cana-1705	300	23	determine	determine	VERB
cana-1705	300	24	the	the	DET
cana-1705	300	25	accuracy	accuracy	NOUN
cana-1705	300	26	of	of	ADP
cana-1705	300	27	its	its	PRON
cana-1705	300	28	long	long	ADJ
cana-1705	300	29	term	term	NOUN
cana-1705	300	30	dependence	dependence	NOUN
cana-1705	300	31	prediction	prediction	NOUN
cana-1705	300	32	.	.	PUNCT
cana-1705	301	1	this	this	DET
cana-1705	301	2	results	result	VERB
cana-1705	301	3	in	in	ADP
cana-1705	301	4	the	the	DET
cana-1705	301	5	model	model	NOUN
cana-1705	301	6	being	be	AUX
cana-1705	301	7	evaluated	evaluate	VERB
cana-1705	301	8	on	on	ADP
cana-1705	301	9	fresh	fresh	ADJ
cana-1705	301	10	unseen	unseen	ADJ
cana-1705	301	11	data	datum	NOUN
cana-1705	301	12	which	which	PRON
cana-1705	301	13	will	will	AUX
cana-1705	301	14	give	give	VERB
cana-1705	301	15	a	a	DET
cana-1705	301	16	good	good	ADJ
cana-1705	301	17	estimate	estimate	NOUN
cana-1705	301	18	of	of	ADP
cana-1705	301	19	its	its	PRON
cana-1705	301	20	generalization	generalization	NOUN
cana-1705	301	21	to	to	ADP
cana-1705	301	22	real	real	ADJ
cana-1705	301	23	traffic	traffic	NOUN
cana-1705	301	24	.	.	PUNCT
cana-1705	302	1	a.	a.	NOUN
cana-1705	302	2	evaluation	evaluation	NOUN
cana-1705	302	3	metrics	metric	NOUN
cana-1705	302	4	they	they	PRON
cana-1705	302	5	breakdown	breakdown	VERB
cana-1705	302	6	evaluation	evaluation	NOUN
cana-1705	302	7	criteria	criterion	NOUN
cana-1705	302	8	on	on	ADP
cana-1705	302	9	the	the	DET
cana-1705	302	10	basis	basis	NOUN
cana-1705	302	11	of	of	ADP
cana-1705	302	12	which	which	PRON
cana-1705	302	13	they	they	PRON
cana-1705	302	14	evaluated	evaluate	VERB
cana-1705	302	15	the	the	DET
cana-1705	302	16	performance	performance	NOUN
cana-1705	302	17	of	of	ADP
cana-1705	302	18	the	the	DET
cana-1705	302	19	lstm	lstm	PROPN
cana-1705	302	20	model	model	NOUN
cana-1705	302	21	mean	mean	VERB
cana-1705	302	22	absolute	absolute	ADJ
cana-1705	302	23	error	error	NOUN
cana-1705	302	24	(	(	PUNCT
cana-1705	302	25	mae	mae	PROPN
cana-1705	302	26	):	):	PUNCT
cana-1705	302	27	mae	mae	PROPN
cana-1705	302	28	quantifies	quantifie	NOUN
cana-1705	302	29	the	the	DET
cana-1705	302	30	accuracy	accuracy	NOUN
cana-1705	302	31	of	of	ADP
cana-1705	302	32	traffic	traffic	NOUN
cana-1705	302	33	prediction	prediction	NOUN
cana-1705	302	34	as	as	ADP
cana-1705	302	35	average	average	ADJ
cana-1705	302	36	absolute	absolute	ADJ
cana-1705	302	37	difference	difference	NOUN
cana-1705	302	38	between	between	ADP
cana-1705	302	39	predicted	predict	VERB
cana-1705	302	40	and	and	CCONJ
cana-1705	302	41	actual	actual	ADJ
cana-1705	302	42	traffic	traffic	NOUN
cana-1705	302	43	.	.	PUNCT
cana-1705	303	1	root	root	NOUN
cana-1705	303	2	mean	mean	VERB
cana-1705	303	3	squared	square	VERB
cana-1705	303	4	error	error	NOUN
cana-1705	303	5	(	(	PUNCT
cana-1705	303	6	rmse	rmse	NOUN
cana-1705	303	7	):	):	PUNCT
cana-1705	303	8	also	also	ADV
cana-1705	303	9	a	a	DET
cana-1705	303	10	popular	popular	ADJ
cana-1705	303	11	metric	metric	NOUN
cana-1705	303	12	for	for	ADP
cana-1705	303	13	regression	regression	NOUN
cana-1705	303	14	tasks	task	NOUN
cana-1705	303	15	that	that	PRON
cana-1705	303	16	weights	weight	VERB
cana-1705	303	17	the	the	DET
cana-1705	303	18	errors	error	NOUN
cana-1705	303	19	proportional	proportional	ADJ
cana-1705	303	20	to	to	ADP
cana-1705	303	21	their	their	PRON
cana-1705	303	22	magnitude	magnitude	NOUN
cana-1705	303	23	,	,	PUNCT
cana-1705	303	24	is	be	AUX
cana-1705	303	25	especially	especially	ADV
cana-1705	303	26	sensitive	sensitive	ADJ
cana-1705	303	27	to	to	ADP
cana-1705	303	28	outliers	outlier	NOUN
cana-1705	303	29	in	in	ADP
cana-1705	303	30	data	datum	NOUN
cana-1705	303	31	.	.	PUNCT
cana-1705	304	1	rmse	rmse	PROPN
cana-1705	305	1	=	=	NOUN
cana-1705	306	1	√	√	PROPN
cana-1705	306	2	1	1	NUM
cana-1705	306	3	𝑛	𝑛	PRON
cana-1705	306	4	∑(𝑦𝑖	∑(𝑦𝑖	PROPN
cana-1705	306	5	−	−	PROPN
cana-1705	306	6	�	�	PROPN
cana-1705	306	7	̂	̂	SYM
cana-1705	306	8	�	�	NOUN
cana-1705	306	9	𝑖)2	𝑖)2	ADJ
cana-1705	306	10	𝑛	𝑛	PRON
cana-1705	306	11	𝑖=1	𝑖=1	PROPN
cana-1705	306	12	r²	r²	NOUN
cana-1705	306	13	:	:	PUNCT
cana-1705	306	14	the	the	DET
cana-1705	306	15	r²	r²	NOUN
cana-1705	306	16	score	score	NOUN
cana-1705	306	17	is	be	AUX
cana-1705	306	18	proportion	proportion	NOUN
cana-1705	306	19	of	of	ADP
cana-1705	306	20	variance	variance	NOUN
cana-1705	306	21	in	in	ADP
cana-1705	306	22	the	the	DET
cana-1705	306	23	traffic	traffic	NOUN
cana-1705	306	24	data	datum	NOUN
cana-1705	306	25	that	that	PRON
cana-1705	306	26	can	can	AUX
cana-1705	306	27	be	be	AUX
cana-1705	306	28	explained	explain	VERB
cana-1705	306	29	by	by	ADP
cana-1705	306	30	the	the	DET
cana-1705	306	31	model	model	NOUN
cana-1705	306	32	.	.	PUNCT
cana-1705	307	1	it	it	PRON
cana-1705	307	2	is	be	AUX
cana-1705	307	3	essentially	essentially	ADV
cana-1705	307	4	the	the	DET
cana-1705	307	5	proportion	proportion	NOUN
cana-1705	307	6	of	of	ADP
cana-1705	307	7	the	the	DET
cana-1705	307	8	output	output	NOUN
cana-1705	307	9	variance	variance	NOUN
cana-1705	307	10	explained	explain	VERB
cana-1705	307	11	by	by	ADP
cana-1705	307	12	input	input	NOUN
cana-1705	307	13	,	,	PUNCT
cana-1705	307	14	higher	high	ADJ
cana-1705	307	15	r²	r²	NOUN
cana-1705	307	16	shows	show	VERB
cana-1705	307	17	that	that	SCONJ
cana-1705	307	18	the	the	DET
cana-1705	307	19	model	model	NOUN
cana-1705	307	20	explains	explain	VERB
cana-1705	307	21	more	more	ADJ
cana-1705	307	22	variability	variability	NOUN
cana-1705	307	23	of	of	ADP
cana-1705	307	24	the	the	DET
cana-1705	307	25	data	datum	NOUN
cana-1705	307	26	and	and	CCONJ
cana-1705	307	27	contributing	contribute	VERB
cana-1705	307	28	to	to	ADP
cana-1705	307	29	making	make	VERB
cana-1705	307	30	more	more	ADV
cana-1705	307	31	accurate	accurate	ADJ
cana-1705	307	32	predictions	prediction	NOUN
cana-1705	307	33	.	.	PUNCT
cana-1705	308	1	communications	communication	NOUN
cana-1705	308	2	on	on	ADP
cana-1705	308	3	applied	apply	VERB
cana-1705	308	4	nonlinear	nonlinear	ADJ
cana-1705	308	5	analysis	analysis	NOUN
cana-1705	308	6	issn	issn	NOUN
cana-1705	308	7	:	:	PUNCT
cana-1705	308	8	1074	1074	NUM
cana-1705	308	9	-	-	PUNCT
cana-1705	308	10	133x	133x	NUM
cana-1705	308	11	vol	vol	NOUN
cana-1705	308	12	32	32	NUM
cana-1705	308	13	no	no	NOUN
cana-1705	308	14	.	.	NOUN
cana-1705	308	15	2	2	NUM
cana-1705	308	16	(	(	PUNCT
cana-1705	308	17	2025	2025	NUM
cana-1705	308	18	)	)	PUNCT
cana-1705	308	19	17	17	NUM
cana-1705	308	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	308	21	mse	mse	NOUN
cana-1705	308	22	=	=	SYM
cana-1705	308	23	1	1	NUM
cana-1705	309	1	𝑛	𝑛	PRON
cana-1705	309	2	∑(𝑦𝑖	∑(𝑦𝑖	PROPN
cana-1705	309	3	−	−	PROPN
cana-1705	309	4	�	�	PROPN
cana-1705	309	5	̂	̂	VERB
cana-1705	309	6	�	�	NOUN
cana-1705	309	7	𝑖	𝑖	SYM
cana-1705	309	8	)	)	PUNCT
cana-1705	309	9	2	2	NUM
cana-1705	309	10	𝑛	𝑛	DET
cana-1705	309	11	𝑖=1	𝑖=1	PROPN
cana-1705	309	12	b.	b.	PROPN
cana-1705	309	13	cross	cross	PROPN
cana-1705	309	14	-	-	NOUN
cana-1705	309	15	validation	validation	VERB
cana-1705	309	16	the	the	DET
cana-1705	309	17	robustness	robustness	NOUN
cana-1705	309	18	of	of	ADP
cana-1705	309	19	the	the	DET
cana-1705	309	20	model	model	NOUN
cana-1705	309	21	is	be	AUX
cana-1705	309	22	again	again	ADV
cana-1705	309	23	confirmed	confirm	VERB
cana-1705	309	24	by	by	ADP
cana-1705	309	25	applying	apply	VERB
cana-1705	309	26	k	k	ADJ
cana-1705	309	27	-	-	ADJ
cana-1705	309	28	fold	fold	ADJ
cana-1705	309	29	cross	cross	NOUN
cana-1705	309	30	validation	validation	NOUN
cana-1705	309	31	.	.	PUNCT
cana-1705	310	1	in	in	ADP
cana-1705	310	2	k	k	ADJ
cana-1705	310	3	-	-	ADJ
cana-1705	310	4	fold	fold	ADJ
cana-1705	310	5	crossvalidation	crossvalidation	NOUN
cana-1705	310	6	,	,	PUNCT
cana-1705	310	7	the	the	DET
cana-1705	310	8	dataset	dataset	NOUN
cana-1705	310	9	is	be	AUX
cana-1705	310	10	divided	divide	VERB
cana-1705	310	11	into	into	ADP
cana-1705	310	12	k	k	PROPN
cana-1705	310	13	subsets	subset	NOUN
cana-1705	310	14	,	,	PUNCT
cana-1705	310	15	and	and	CCONJ
cana-1705	310	16	the	the	DET
cana-1705	310	17	model	model	NOUN
cana-1705	310	18	is	be	AUX
cana-1705	310	19	trained	train	VERB
cana-1705	310	20	and	and	CCONJ
cana-1705	310	21	evaluated	evaluate	VERB
cana-1705	310	22	k	k	PROPN
cana-1705	310	23	times	time	NOUN
cana-1705	310	24	,	,	PUNCT
cana-1705	310	25	each	each	DET
cana-1705	310	26	time	time	NOUN
cana-1705	310	27	using	use	VERB
cana-1705	310	28	a	a	DET
cana-1705	310	29	different	different	ADJ
cana-1705	310	30	subset	subset	NOUN
cana-1705	310	31	as	as	ADP
cana-1705	310	32	the	the	DET
cana-1705	310	33	test	test	NOUN
cana-1705	310	34	data	datum	NOUN
cana-1705	310	35	and	and	CCONJ
cana-1705	310	36	all	all	DET
cana-1705	310	37	other	other	ADJ
cana-1705	310	38	instances	instance	NOUN
cana-1705	310	39	as	as	ADP
cana-1705	310	40	the	the	DET
cana-1705	310	41	training	training	NOUN
cana-1705	310	42	data	datum	NOUN
cana-1705	310	43	.	.	PUNCT
cana-1705	311	1	this	this	PRON
cana-1705	311	2	helps	help	VERB
cana-1705	311	3	in	in	ADP
cana-1705	311	4	avoiding	avoid	VERB
cana-1705	311	5	overfitting	overfitte	VERB
cana-1705	311	6	and	and	CCONJ
cana-1705	311	7	give	give	VERB
cana-1705	311	8	you	you	PRON
cana-1705	311	9	a	a	DET
cana-1705	311	10	better	well	ADJ
cana-1705	311	11	estimate	estimate	NOUN
cana-1705	311	12	of	of	ADP
cana-1705	311	13	the	the	DET
cana-1705	311	14	performance	performance	NOUN
cana-1705	311	15	of	of	ADP
cana-1705	311	16	the	the	DET
cana-1705	311	17	model	model	NOUN
cana-1705	311	18	.	.	PUNCT
cana-1705	312	1	algorithm	algorithm	NOUN
cana-1705	312	2	2	2	NUM
cana-1705	312	3	:	:	PUNCT
cana-1705	312	4	real	real	ADJ
cana-1705	312	5	-	-	PUNCT
cana-1705	312	6	time	time	NOUN
cana-1705	312	7	traffic	traffic	NOUN
cana-1705	312	8	prediction	prediction	NOUN
cana-1705	312	9	and	and	CCONJ
cana-1705	312	10	deployment	deployment	NOUN
cana-1705	312	11	1	1	NUM
cana-1705	312	12	.	.	PUNCT
cana-1705	313	1	input	input	NOUN
cana-1705	313	2	:	:	PUNCT
cana-1705	313	3	real	real	ADJ
cana-1705	313	4	-	-	PUNCT
cana-1705	313	5	time	time	NOUN
cana-1705	313	6	traffic	traffic	NOUN
cana-1705	313	7	data	datum	NOUN
cana-1705	313	8	𝑋𝑟𝑒𝑎𝑙−𝑡𝑖𝑚𝑒	𝑋𝑟𝑒𝑎𝑙−𝑡𝑖𝑚𝑒	PROPN
cana-1705	313	9	=	=	SYM
cana-1705	313	10	{	{	PUNCT
cana-1705	313	11	𝑥1	𝑥1	NOUN
cana-1705	313	12	,	,	PUNCT
cana-1705	313	13	𝑥2	𝑥2	NOUN
cana-1705	313	14	,	,	PUNCT
cana-1705	313	15	…	…	PUNCT
cana-1705	313	16	,	,	PUNCT
cana-1705	313	17	𝑥𝑡	𝑥𝑡	ADP
cana-1705	313	18	}	}	PUNCT
cana-1705	313	19	from	from	ADP
cana-1705	313	20	sensors	sensor	NOUN
cana-1705	313	21	,	,	PUNCT
cana-1705	313	22	gps	gps	PROPN
cana-1705	313	23	,	,	PUNCT
cana-1705	313	24	and	and	CCONJ
cana-1705	313	25	weather	weather	NOUN
cana-1705	313	26	data	datum	NOUN
cana-1705	313	27	.	.	PUNCT
cana-1705	314	1	2	2	X
cana-1705	314	2	.	.	X
cana-1705	314	3	preprocess	preprocess	NOUN
cana-1705	314	4	real	real	ADJ
cana-1705	314	5	-	-	PUNCT
cana-1705	314	6	time	time	NOUN
cana-1705	314	7	data	data	NOUN
cana-1705	314	8	𝑋𝑟𝑒𝑎𝑙−𝑡𝑖𝑚𝑒	𝑋𝑟𝑒𝑎𝑙−𝑡𝑖𝑚𝑒	PROPN
cana-1705	314	9	(	(	PUNCT
cana-1705	314	10	normalization	normalization	NOUN
cana-1705	314	11	,	,	PUNCT
cana-1705	314	12	cleaning	cleaning	NOUN
cana-1705	314	13	,	,	PUNCT
cana-1705	314	14	etc	etc	X
cana-1705	314	15	.	.	X
cana-1705	314	16	)	)	PUNCT
cana-1705	314	17	.	.	PUNCT
cana-1705	315	1	3	3	X
cana-1705	315	2	.	.	X
cana-1705	315	3	load	load	VERB
cana-1705	315	4	the	the	DET
cana-1705	315	5	trained	train	VERB
cana-1705	315	6	lstm	lstm	PROPN
cana-1705	315	7	model	model	NOUN
cana-1705	315	8	.	.	PUNCT
cana-1705	316	1	4	4	X
cana-1705	316	2	.	.	X
cana-1705	316	3	for	for	ADP
cana-1705	316	4	each	each	DET
cana-1705	316	5	new	new	ADJ
cana-1705	316	6	incoming	incoming	ADJ
cana-1705	316	7	data	datum	NOUN
cana-1705	316	8	point	point	NOUN
cana-1705	316	9	𝑥𝑡	𝑥𝑡	ADV
cana-1705	316	10	:	:	PUNCT
cana-1705	316	11	a.	a.	NOUN
cana-1705	316	12	feed	feed	NOUN
cana-1705	316	13	data	datum	NOUN
cana-1705	316	14	𝑥𝑡	𝑥𝑡	ADV
cana-1705	316	15	into	into	ADP
cana-1705	316	16	the	the	DET
cana-1705	316	17	lstm	lstm	PROPN
cana-1705	316	18	network	network	NOUN
cana-1705	316	19	.	.	PUNCT
cana-1705	317	1	b.	b.	PROPN
cana-1705	317	2	compute	compute	PROPN
cana-1705	317	3	the	the	DET
cana-1705	317	4	predicted	predict	VERB
cana-1705	317	5	traffic	traffic	NOUN
cana-1705	317	6	flow	flow	NOUN
cana-1705	317	7	�	�	PROPN
cana-1705	317	8	̂	̂	NOUN
cana-1705	317	9	�	�	NOUN
cana-1705	317	10	𝑡	𝑡	NOUN
cana-1705	317	11	using	use	VERB
cana-1705	317	12	lstm	lstm	ADJ
cana-1705	317	13	output	output	NOUN
cana-1705	317	14	.	.	PUNCT
cana-1705	318	1	5	5	X
cana-1705	318	2	.	.	X
cana-1705	318	3	send	send	VERB
cana-1705	318	4	the	the	DET
cana-1705	318	5	prediction	prediction	NOUN
cana-1705	318	6	to	to	ADP
cana-1705	318	7	the	the	DET
cana-1705	318	8	traffic	traffic	NOUN
cana-1705	318	9	management	management	NOUN
cana-1705	318	10	system	system	NOUN
cana-1705	318	11	.	.	PUNCT
cana-1705	319	1	6	6	X
cana-1705	319	2	.	.	X
cana-1705	319	3	update	update	NOUN
cana-1705	319	4	traffic	traffic	NOUN
cana-1705	319	5	signal	signal	NOUN
cana-1705	319	6	controls	control	NOUN
cana-1705	319	7	,	,	PUNCT
cana-1705	319	8	reroute	reroute	NOUN
cana-1705	319	9	vehicles	vehicle	NOUN
cana-1705	319	10	,	,	PUNCT
cana-1705	319	11	or	or	CCONJ
cana-1705	319	12	inform	inform	VERB
cana-1705	319	13	drivers	driver	NOUN
cana-1705	319	14	via	via	ADP
cana-1705	319	15	mobile	mobile	ADJ
cana-1705	319	16	apps	app	NOUN
cana-1705	319	17	based	base	VERB
cana-1705	319	18	on	on	ADP
cana-1705	319	19	predictions	prediction	NOUN
cana-1705	319	20	.	.	PUNCT
cana-1705	320	1	7	7	X
cana-1705	320	2	.	.	X
cana-1705	320	3	output	output	NOUN
cana-1705	320	4	:	:	PUNCT
cana-1705	320	5	real	real	ADJ
cana-1705	320	6	-	-	PUNCT
cana-1705	320	7	time	time	NOUN
cana-1705	320	8	traffic	traffic	NOUN
cana-1705	320	9	flow	flow	NOUN
cana-1705	320	10	predictions	prediction	NOUN
cana-1705	320	11	.	.	PUNCT
cana-1705	321	1	after	after	ADP
cana-1705	321	2	being	be	AUX
cana-1705	321	3	validated	validate	VERB
cana-1705	321	4	,	,	PUNCT
cana-1705	321	5	the	the	DET
cana-1705	321	6	trained	train	VERB
cana-1705	321	7	lstm	lstm	NOUN
cana-1705	321	8	model	model	NOUN
cana-1705	321	9	will	will	AUX
cana-1705	321	10	be	be	AUX
cana-1705	321	11	deployed	deploy	VERB
cana-1705	321	12	in	in	ADP
cana-1705	321	13	a	a	DET
cana-1705	321	14	real	real	ADJ
cana-1705	321	15	-	-	PUNCT
cana-1705	321	16	time	time	NOUN
cana-1705	321	17	traffic	traffic	NOUN
cana-1705	321	18	management	management	NOUN
cana-1705	321	19	system	system	NOUN
cana-1705	321	20	.	.	PUNCT
cana-1705	322	1	this	this	DET
cana-1705	322	2	model	model	NOUN
cana-1705	322	3	uses	use	VERB
cana-1705	322	4	real	real	ADJ
cana-1705	322	5	-	-	PUNCT
cana-1705	322	6	time	time	NOUN
cana-1705	322	7	recordings	recording	NOUN
cana-1705	322	8	of	of	ADP
cana-1705	322	9	traffic	traffic	NOUN
cana-1705	322	10	data	datum	NOUN
cana-1705	322	11	from	from	ADP
cana-1705	322	12	sensors	sensor	NOUN
cana-1705	322	13	,	,	PUNCT
cana-1705	322	14	gps	gps	NOUN
cana-1705	322	15	devices	device	NOUN
cana-1705	322	16	or	or	CCONJ
cana-1705	322	17	other	other	ADJ
cana-1705	322	18	sources	source	NOUN
cana-1705	322	19	and	and	CCONJ
cana-1705	322	20	continuously	continuously	ADV
cana-1705	322	21	predicts	predict	VERB
cana-1705	322	22	the	the	DET
cana-1705	322	23	future	future	ADJ
cana-1705	322	24	traffic	traffic	NOUN
cana-1705	322	25	flow	flow	NOUN
cana-1705	322	26	for	for	ADP
cana-1705	322	27	instances	instance	NOUN
cana-1705	322	28	in	in	ADP
cana-1705	322	29	the	the	DET
cana-1705	322	30	very	very	ADV
cana-1705	322	31	near	near	ADP
cana-1705	322	32	future	future	NOUN
cana-1705	322	33	(	(	PUNCT
cana-1705	322	34	e.g.	e.g.	ADV
cana-1705	322	35	5	5	NUM
cana-1705	322	36	minutes	minute	NOUN
cana-1705	322	37	or	or	CCONJ
cana-1705	322	38	15	15	NUM
cana-1705	322	39	minutes	minute	NOUN
cana-1705	322	40	ahead	ahead	ADV
cana-1705	322	41	)	)	PUNCT
cana-1705	322	42	.	.	PUNCT
cana-1705	323	1	these	these	DET
cana-1705	323	2	predictions	prediction	NOUN
cana-1705	323	3	are	be	AUX
cana-1705	323	4	used	use	VERB
cana-1705	323	5	to	to	PART
cana-1705	323	6	guide	guide	VERB
cana-1705	323	7	traffic	traffic	NOUN
cana-1705	323	8	control	control	NOUN
cana-1705	323	9	strategies	strategy	NOUN
cana-1705	323	10	such	such	ADJ
cana-1705	323	11	as	as	ADP
cana-1705	323	12	signal	signal	ADJ
cana-1705	323	13	timing	timing	NOUN
cana-1705	323	14	adjustment	adjustment	NOUN
cana-1705	323	15	,	,	PUNCT
cana-1705	323	16	vehicle	vehicle	NOUN
cana-1705	323	17	re	re	NOUN
cana-1705	323	18	-	-	NOUN
cana-1705	323	19	routing	routing	NOUN
cana-1705	323	20	or	or	CCONJ
cana-1705	323	21	traveler	traveler	NOUN
cana-1705	323	22	information	information	NOUN
cana-1705	323	23	.	.	PUNCT
cana-1705	324	1	the	the	DET
cana-1705	324	2	proposed	propose	VERB
cana-1705	324	3	approach	approach	NOUN
cana-1705	324	4	is	be	AUX
cana-1705	324	5	using	use	VERB
cana-1705	324	6	lstm	lstm	ADJ
cana-1705	324	7	network	network	NOUN
cana-1705	324	8	to	to	PART
cana-1705	324	9	solve	solve	VERB
cana-1705	324	10	the	the	DET
cana-1705	324	11	problem	problem	NOUN
cana-1705	324	12	of	of	ADP
cana-1705	324	13	real	real	ADJ
cana-1705	324	14	-	-	PUNCT
cana-1705	324	15	time	time	NOUN
cana-1705	324	16	traffic	traffic	NOUN
cana-1705	324	17	flow	flow	NOUN
cana-1705	324	18	prediction	prediction	NOUN
cana-1705	324	19	in	in	ADP
cana-1705	324	20	urban	urban	ADJ
cana-1705	324	21	areas	area	NOUN
cana-1705	324	22	.	.	PUNCT
cana-1705	325	1	this	this	DET
cana-1705	325	2	approach	approach	NOUN
cana-1705	325	3	is	be	AUX
cana-1705	325	4	robust	robust	ADJ
cana-1705	325	5	in	in	ADP
cana-1705	325	6	terms	term	NOUN
cana-1705	325	7	of	of	ADP
cana-1705	325	8	space	space	NOUN
cana-1705	325	9	,	,	PUNCT
cana-1705	325	10	time	time	NOUN
cana-1705	325	11	,	,	PUNCT
cana-1705	325	12	and	and	CCONJ
cana-1705	325	13	environment	environment	NOUN
cana-1705	325	14	features	feature	VERB
cana-1705	325	15	it	it	PRON
cana-1705	325	16	unifies	unify	VERB
cana-1705	325	17	into	into	ADP
cana-1705	325	18	a	a	DET
cana-1705	325	19	whole	whole	ADJ
cana-1705	325	20	solution	solution	NOUN
cana-1705	325	21	for	for	ADP
cana-1705	325	22	traffic	traffic	NOUN
cana-1705	325	23	flow	flow	NOUN
cana-1705	325	24	prediction	prediction	NOUN
cana-1705	325	25	in	in	ADP
cana-1705	325	26	dynamic	dynamic	ADJ
cana-1705	325	27	and	and	CCONJ
cana-1705	325	28	complex	complex	ADJ
cana-1705	325	29	urban	urban	ADJ
cana-1705	325	30	traffic	traffic	NOUN
cana-1705	325	31	systems	system	NOUN
cana-1705	325	32	by	by	ADP
cana-1705	325	33	also	also	ADV
cana-1705	325	34	employing	employ	VERB
cana-1705	325	35	special	special	ADJ
cana-1705	325	36	data	datum	NOUN
cana-1705	325	37	preprocessing	preprocessing	NOUN
cana-1705	325	38	types	type	NOUN
cana-1705	325	39	and	and	CCONJ
cana-1705	325	40	model	model	NOUN
cana-1705	325	41	training	training	NOUN
cana-1705	325	42	techniques	technique	NOUN
cana-1705	325	43	.	.	PUNCT
cana-1705	326	1	if	if	SCONJ
cana-1705	326	2	applied	apply	VERB
cana-1705	326	3	in	in	ADP
cana-1705	326	4	a	a	DET
cana-1705	326	5	real	real	ADJ
cana-1705	326	6	-	-	PUNCT
cana-1705	326	7	time	time	NOUN
cana-1705	326	8	traffic	traffic	NOUN
cana-1705	326	9	management	management	NOUN
cana-1705	326	10	,	,	PUNCT
cana-1705	326	11	the	the	DET
cana-1705	326	12	model	model	NOUN
cana-1705	326	13	could	could	AUX
cana-1705	326	14	go	go	VERB
cana-1705	326	15	further	far	ADV
cana-1705	326	16	to	to	PART
cana-1705	326	17	help	help	VERB
cana-1705	326	18	keep	keep	VERB
cana-1705	326	19	congestion	congestion	NOUN
cana-1705	326	20	at	at	ADP
cana-1705	326	21	bay	bay	NOUN
cana-1705	326	22	,	,	PUNCT
cana-1705	326	23	shorten	shorten	VERB
cana-1705	326	24	travel	travel	NOUN
cana-1705	326	25	times	time	NOUN
cana-1705	326	26	and	and	CCONJ
cana-1705	326	27	improves	improve	VERB
cana-1705	326	28	urban	urban	ADJ
cana-1705	326	29	mobility	mobility	NOUN
cana-1705	326	30	.	.	PUNCT
cana-1705	327	1	4	4	X
cana-1705	327	2	.	.	X
cana-1705	327	3	experiments	experiment	NOUN
cana-1705	327	4	and	and	CCONJ
cana-1705	327	5	results	result	NOUN
cana-1705	327	6	we	we	PRON
cana-1705	327	7	developed	develop	VERB
cana-1705	327	8	a	a	DET
cana-1705	327	9	real	real	ADJ
cana-1705	327	10	-	-	PUNCT
cana-1705	327	11	time	time	NOUN
cana-1705	327	12	traffic	traffic	NOUN
cana-1705	327	13	flow	flow	NOUN
cana-1705	327	14	prediction	prediction	NOUN
cana-1705	327	15	system	system	NOUN
cana-1705	327	16	based	base	VERB
cana-1705	327	17	on	on	ADP
cana-1705	327	18	long	long	ADJ
cana-1705	327	19	short	short	ADJ
cana-1705	327	20	-	-	PUNCT
cana-1705	327	21	term	term	NOUN
cana-1705	327	22	memory	memory	NOUN
cana-1705	327	23	(	(	PUNCT
cana-1705	327	24	lstm	lstm	NOUN
cana-1705	327	25	)	)	PUNCT
cana-1705	327	26	to	to	PART
cana-1705	327	27	achieve	achieve	VERB
cana-1705	327	28	the	the	DET
cana-1705	327	29	ultimate	ultimate	ADJ
cana-1705	327	30	goal	goal	NOUN
cana-1705	327	31	of	of	ADP
cana-1705	327	32	this	this	DET
cana-1705	327	33	research	research	NOUN
cana-1705	327	34	and	and	CCONJ
cana-1705	327	35	assess	assess	VERB
cana-1705	327	36	its	its	PRON
cana-1705	327	37	performance	performance	NOUN
cana-1705	327	38	through	through	ADP
cana-1705	327	39	extensive	extensive	ADJ
cana-1705	327	40	experiments	experiment	NOUN
cana-1705	327	41	.	.	PUNCT
cana-1705	328	1	for	for	ADP
cana-1705	328	2	evaluating	evaluate	VERB
cana-1705	328	3	the	the	DET
cana-1705	328	4	proposed	propose	VERB
cana-1705	328	5	system	system	NOUN
cana-1705	328	6	,	,	PUNCT
cana-1705	328	7	we	we	PRON
cana-1705	328	8	developed	develop	VERB
cana-1705	328	9	a	a	DET
cana-1705	328	10	series	series	NOUN
cana-1705	328	11	of	of	ADP
cana-1705	328	12	experiments	experiment	NOUN
cana-1705	328	13	that	that	PRON
cana-1705	328	14	test	test	VERB
cana-1705	328	15	the	the	DET
cana-1705	328	16	performance	performance	NOUN
cana-1705	328	17	of	of	ADP
cana-1705	328	18	its	its	PRON
cana-1705	328	19	mode	mode	NOUN
cana-1705	328	20	in	in	ADP
cana-1705	328	21	predicting	predict	VERB
cana-1705	328	22	short	short	ADJ
cana-1705	328	23	-	-	PUNCT
cana-1705	328	24	term	term	NOUN
cana-1705	328	25	traffic	traffic	NOUN
cana-1705	328	26	flow	flow	NOUN
cana-1705	328	27	behavior	behavior	NOUN
cana-1705	328	28	under	under	ADP
cana-1705	328	29	various	various	ADJ
cana-1705	328	30	real	real	ADJ
cana-1705	328	31	-	-	PUNCT
cana-1705	328	32	world	world	NOUN
cana-1705	328	33	conditions	condition	NOUN
cana-1705	328	34	.	.	PUNCT
cana-1705	329	1	we	we	PRON
cana-1705	329	2	have	have	AUX
cana-1705	329	3	tested	test	VERB
cana-1705	329	4	it	it	PRON
cana-1705	329	5	on	on	ADP
cana-1705	329	6	different	different	ADJ
cana-1705	329	7	revolutionary	revolutionary	ADJ
cana-1705	329	8	datasets	dataset	NOUN
cana-1705	329	9	gathered	gather	VERB
cana-1705	329	10	from	from	ADP
cana-1705	329	11	urban	urban	ADJ
cana-1705	329	12	road	road	NOUN
cana-1705	329	13	networks	network	NOUN
cana-1705	329	14	communications	communication	NOUN
cana-1705	329	15	on	on	ADP
cana-1705	329	16	applied	apply	VERB
cana-1705	329	17	nonlinear	nonlinear	ADJ
cana-1705	329	18	analysis	analysis	NOUN
cana-1705	329	19	issn	issn	NOUN
cana-1705	329	20	:	:	PUNCT
cana-1705	329	21	1074	1074	NUM
cana-1705	329	22	-	-	PUNCT
cana-1705	329	23	133x	133x	NUM
cana-1705	329	24	vol	vol	NOUN
cana-1705	329	25	32	32	NUM
cana-1705	329	26	no	no	NOUN
cana-1705	329	27	.	.	NOUN
cana-1705	329	28	2	2	NUM
cana-1705	329	29	(	(	PUNCT
cana-1705	329	30	2025	2025	NUM
cana-1705	329	31	)	)	PUNCT
cana-1705	329	32	18	18	NUM
cana-1705	329	33	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	329	34	and	and	CCONJ
cana-1705	329	35	containing	contain	VERB
cana-1705	329	36	vehicle	vehicle	NOUN
cana-1705	329	37	speed	speed	NOUN
cana-1705	329	38	,	,	PUNCT
cana-1705	329	39	traffic	traffic	NOUN
cana-1705	329	40	volume	volume	NOUN
cana-1705	329	41	,	,	PUNCT
cana-1705	329	42	lane	lane	NOUN
cana-1705	329	43	occupancy	occupancy	NOUN
cana-1705	329	44	data	datum	NOUN
cana-1705	329	45	points	point	NOUN
cana-1705	329	46	as	as	ADV
cana-1705	329	47	well	well	ADV
cana-1705	329	48	as	as	ADP
cana-1705	329	49	external	external	ADJ
cana-1705	329	50	factors	factor	NOUN
cana-1705	329	51	like	like	ADP
cana-1705	329	52	weather	weather	NOUN
cana-1705	329	53	or	or	CCONJ
cana-1705	329	54	incidents	incident	NOUN
cana-1705	329	55	.	.	PUNCT
cana-1705	330	1	this	this	DET
cana-1705	330	2	section	section	NOUN
cana-1705	330	3	includes	include	VERB
cana-1705	330	4	material	material	NOUN
cana-1705	330	5	and	and	CCONJ
cana-1705	330	6	methods	method	NOUN
cana-1705	330	7	starting	start	VERB
cana-1705	330	8	from	from	ADP
cana-1705	330	9	data	datum	NOUN
cana-1705	330	10	selection	selection	NOUN
cana-1705	330	11	,	,	PUNCT
cana-1705	330	12	model	model	NOUN
cana-1705	330	13	configuration	configuration	NOUN
cana-1705	330	14	,	,	PUNCT
cana-1705	330	15	evaluation	evaluation	NOUN
cana-1705	330	16	matrix	matrix	NOUN
cana-1705	330	17	,	,	PUNCT
cana-1705	330	18	to	to	PART
cana-1705	330	19	results	result	VERB
cana-1705	330	20	analysis	analysis	NOUN
cana-1705	330	21	.	.	PUNCT
cana-1705	331	1	experiments	experiment	NOUN
cana-1705	331	2	were	be	AUX
cana-1705	331	3	then	then	ADV
cana-1705	331	4	designed	design	VERB
cana-1705	331	5	to	to	PART
cana-1705	331	6	test	test	VERB
cana-1705	331	7	the	the	DET
cana-1705	331	8	prediction	prediction	NOUN
cana-1705	331	9	correctness	correctness	NOUN
cana-1705	331	10	,	,	PUNCT
cana-1705	331	11	sensitivity	sensitivity	NOUN
cana-1705	331	12	to	to	ADP
cana-1705	331	13	changing	change	VERB
cana-1705	331	14	environment	environment	NOUN
cana-1705	331	15	,	,	PUNCT
cana-1705	331	16	and	and	CCONJ
cana-1705	331	17	real	real	ADJ
cana-1705	331	18	-	-	PUNCT
cana-1705	331	19	time	time	NOUN
cana-1705	331	20	performance	performance	NOUN
cana-1705	331	21	of	of	ADP
cana-1705	331	22	lstm	lstm	PROPN
cana-1705	331	23	.	.	PUNCT
cana-1705	332	1	additionally	additionally	ADV
cana-1705	332	2	,	,	PUNCT
cana-1705	332	3	the	the	DET
cana-1705	332	4	performance	performance	NOUN
cana-1705	332	5	results	result	NOUN
cana-1705	332	6	of	of	ADP
cana-1705	332	7	comparing	compare	VERB
cana-1705	332	8	the	the	DET
cana-1705	332	9	lstm	lstm	PROPN
cana-1705	332	10	model	model	NOUN
cana-1705	332	11	to	to	ADP
cana-1705	332	12	a	a	DET
cana-1705	332	13	selection	selection	NOUN
cana-1705	332	14	of	of	ADP
cana-1705	332	15	traditional	traditional	ADJ
cana-1705	332	16	machine	machine	NOUN
cana-1705	332	17	-	-	PUNCT
cana-1705	332	18	learning	learn	VERB
cana-1705	332	19	methods	method	NOUN
cana-1705	332	20	like	like	ADP
cana-1705	332	21	autoregressive	autoregressive	ADJ
cana-1705	332	22	integrated	integrated	ADJ
cana-1705	332	23	moving	move	VERB
cana-1705	332	24	average	average	ADJ
cana-1705	332	25	(	(	PUNCT
cana-1705	332	26	arima	arima	NOUN
cana-1705	332	27	)	)	PUNCT
cana-1705	332	28	and	and	CCONJ
cana-1705	332	29	support	support	VERB
cana-1705	332	30	vector	vector	NOUN
cana-1705	332	31	machines	machine	NOUN
cana-1705	332	32	(	(	PUNCT
cana-1705	332	33	svm	svm	PROPN
cana-1705	332	34	)	)	PUNCT
cana-1705	332	35	were	be	AUX
cana-1705	332	36	described	describe	VERB
cana-1705	332	37	in	in	ADP
cana-1705	332	38	order	order	NOUN
cana-1705	332	39	to	to	PART
cana-1705	332	40	emphasize	emphasize	VERB
cana-1705	332	41	the	the	DET
cana-1705	332	42	gain	gain	NOUN
cana-1705	332	43	from	from	ADP
cana-1705	332	44	deep	deep	ADJ
cana-1705	332	45	learning	learning	NOUN
cana-1705	332	46	paradigm	paradigm	NOUN
cana-1705	332	47	.	.	PUNCT
cana-1705	333	1	a.	a.	NOUN
cana-1705	333	2	description	description	NOUN
cana-1705	333	3	and	and	CCONJ
cana-1705	333	4	preparation	preparation	NOUN
cana-1705	333	5	of	of	ADP
cana-1705	333	6	the	the	DET
cana-1705	333	7	data	datum	NOUN
cana-1705	333	8	set	set	VERB
cana-1705	333	9	dataset	dataset	NOUN
cana-1705	333	10	selection	selection	NOUN
cana-1705	333	11	we	we	PRON
cana-1705	333	12	use	use	VERB
cana-1705	333	13	two	two	NUM
cana-1705	333	14	largescale	largescale	ADJ
cana-1705	333	15	real	real	ADJ
cana-1705	333	16	-	-	PUNCT
cana-1705	333	17	world	world	NOUN
cana-1705	333	18	traffic	traffic	NOUN
cana-1705	333	19	datasets	dataset	NOUN
cana-1705	333	20	,	,	PUNCT
cana-1705	333	21	one	one	NUM
cana-1705	333	22	is	be	AUX
cana-1705	333	23	metr	metr	NOUN
cana-1705	333	24	-	-	PUNCT
cana-1705	333	25	la	la	NOUN
cana-1705	333	26	,	,	PUNCT
cana-1705	333	27	and	and	CCONJ
cana-1705	333	28	the	the	DET
cana-1705	333	29	other	other	ADJ
cana-1705	333	30	one	one	NOUN
cana-1705	333	31	is	be	AUX
cana-1705	333	32	gps	gps	NOUN
cana-1705	333	33	speed	speed	NOUN
cana-1705	333	34	data	datum	NOUN
cana-1705	333	35	which	which	PRON
cana-1705	333	36	includes	include	VERB
cana-1705	333	37	urban	urban	ADJ
cana-1705	333	38	traffic	traffic	NOUN
cana-1705	333	39	detects	detect	NOUN
cana-1705	333	40	for	for	ADP
cana-1705	333	41	a	a	DET
cana-1705	333	42	mid	mid	ADJ
cana-1705	333	43	-	-	ADJ
cana-1705	333	44	sized	sized	ADJ
cana-1705	333	45	metropolitan	metropolitan	ADJ
cana-1705	333	46	area	area	NOUN
cana-1705	333	47	.	.	PUNCT
cana-1705	334	1	we	we	PRON
cana-1705	334	2	selected	select	VERB
cana-1705	334	3	these	these	DET
cana-1705	334	4	datasets	dataset	NOUN
cana-1705	334	5	based	base	VERB
cana-1705	334	6	on	on	ADP
cana-1705	334	7	their	their	PRON
cana-1705	334	8	variation	variation	NOUN
cana-1705	334	9	in	in	ADP
cana-1705	334	10	traffic	traffic	NOUN
cana-1705	334	11	patterns	pattern	NOUN
cana-1705	334	12	,	,	PUNCT
cana-1705	334	13	road	road	NOUN
cana-1705	334	14	types	type	NOUN
cana-1705	334	15	,	,	PUNCT
cana-1705	334	16	and	and	CCONJ
cana-1705	334	17	external	external	ADJ
cana-1705	334	18	factors	factor	NOUN
cana-1705	334	19	such	such	ADJ
cana-1705	334	20	as	as	ADP
cana-1705	334	21	weather	weather	NOUN
cana-1705	334	22	changes	change	NOUN
cana-1705	334	23	,	,	PUNCT
cana-1705	334	24	construction	construction	NOUN
cana-1705	334	25	sites	site	NOUN
cana-1705	334	26	,	,	PUNCT
cana-1705	334	27	and	and	CCONJ
cana-1705	334	28	accidents	accident	NOUN
cana-1705	334	29	.	.	PUNCT
cana-1705	335	1	table	table	NOUN
cana-1705	335	2	3	3	NUM
cana-1705	335	3	:	:	PUNCT
cana-1705	335	4	overview	overview	NOUN
cana-1705	335	5	of	of	ADP
cana-1705	335	6	datasets	dataset	NOUN
cana-1705	335	7	(	(	PUNCT
cana-1705	335	8	metr	metr	NOUN
cana-1705	335	9	-	-	PUNCT
cana-1705	335	10	la	la	ADJ
cana-1705	335	11	and	and	CCONJ
cana-1705	335	12	gps	gps	PROPN
cana-1705	335	13	-	-	PUNCT
cana-1705	335	14	enabled	enable	VERB
cana-1705	335	15	)	)	PUNCT
cana-1705	335	16	dataset	dataset	NOUN
cana-1705	335	17	data	datum	NOUN
cana-1705	335	18	type	type	NOUN
cana-1705	335	19	time	time	NOUN
cana-1705	335	20	interval	interval	NOUN
cana-1705	335	21	(	(	PUNCT
cana-1705	335	22	min	min	NOUN
cana-1705	335	23	)	)	PUNCT
cana-1705	335	24	external	external	ADJ
cana-1705	335	25	factors	factor	NOUN
cana-1705	335	26	no	no	INTJ
cana-1705	335	27	.	.	PUNCT
cana-1705	335	28	of	of	ADP
cana-1705	335	29	sensors	sensor	NOUN
cana-1705	335	30	/	/	SYM
cana-1705	335	31	vehicles	vehicle	NOUN
cana-1705	335	32	time	time	NOUN
cana-1705	335	33	period	period	NOUN
cana-1705	335	34	metrla	metrla	PROPN
cana-1705	335	35	traffic	traffic	NOUN
cana-1705	335	36	volume	volume	NOUN
cana-1705	335	37	,	,	PUNCT
cana-1705	335	38	speed	speed	NOUN
cana-1705	335	39	,	,	PUNCT
cana-1705	335	40	lane	lane	NOUN
cana-1705	335	41	occupancy	occupancy	NOUN
cana-1705	335	42	5	5	NUM
cana-1705	335	43	weather	weather	NOUN
cana-1705	335	44	,	,	PUNCT
cana-1705	335	45	incidents	incident	NOUN
cana-1705	335	46	207	207	NUM
cana-1705	335	47	4	4	NUM
cana-1705	335	48	months	month	NOUN
cana-1705	335	49	gpsurban	gpsurban	NOUN
cana-1705	335	50	vehicle	vehicle	NOUN
cana-1705	335	51	movements	movement	NOUN
cana-1705	335	52	,	,	PUNCT
cana-1705	335	53	speed	speed	NOUN
cana-1705	335	54	,	,	PUNCT
cana-1705	335	55	volume	volume	NOUN
cana-1705	335	56	1	1	NUM
cana-1705	335	57	weather	weather	NOUN
cana-1705	335	58	,	,	PUNCT
cana-1705	335	59	public	public	ADJ
cana-1705	335	60	events	event	NOUN
cana-1705	335	61	,	,	PUNCT
cana-1705	335	62	incidents	incident	NOUN
cana-1705	335	63	500	500	NUM
cana-1705	335	64	6	6	NUM
cana-1705	335	65	months	month	NOUN
cana-1705	335	66	metr	metr	NOUN
cana-1705	335	67	-	-	PUNCT
cana-1705	335	68	la	la	NOUN
cana-1705	335	69	dataset	dataset	NOUN
cana-1705	335	70	:	:	PUNCT
cana-1705	335	71	the	the	DET
cana-1705	335	72	data	datum	NOUN
cana-1705	335	73	collected	collect	VERB
cana-1705	335	74	by	by	ADP
cana-1705	335	75	sensors	sensor	NOUN
cana-1705	335	76	on	on	ADP
cana-1705	335	77	major	major	ADJ
cana-1705	335	78	highways	highway	NOUN
cana-1705	335	79	in	in	ADP
cana-1705	335	80	los	los	PROPN
cana-1705	335	81	angeles	angeles	PROPN
cana-1705	335	82	.	.	PUNCT
cana-1705	336	1	the	the	DET
cana-1705	336	2	measurements	measurement	NOUN
cana-1705	336	3	captured	capture	VERB
cana-1705	336	4	data	datum	NOUN
cana-1705	336	5	lanes	lane	NOUN
cana-1705	336	6	,	,	PUNCT
cana-1705	336	7	tons	ton	NOUN
cana-1705	336	8	of	of	ADP
cana-1705	336	9	traffic	traffic	NOUN
cana-1705	336	10	volume	volume	NOUN
cana-1705	336	11	,	,	PUNCT
cana-1705	336	12	automobile	automobile	NOUN
cana-1705	336	13	pace	pace	NOUN
cana-1705	336	14	,	,	PUNCT
cana-1705	336	15	and	and	CCONJ
cana-1705	336	16	lane	lane	NOUN
cana-1705	336	17	use	use	NOUN
cana-1705	336	18	every	every	DET
cana-1705	336	19	five	five	NUM
cana-1705	336	20	minutes	minute	NOUN
cana-1705	336	21	.	.	PUNCT
cana-1705	337	1	the	the	DET
cana-1705	337	2	metr	metr	PROPN
cana-1705	337	3	-	-	PUNCT
cana-1705	337	4	la	la	NOUN
cana-1705	337	5	dataset	dataset	NOUN
cana-1705	337	6	is	be	AUX
cana-1705	337	7	suitable	suitable	ADJ
cana-1705	337	8	for	for	ADP
cana-1705	337	9	assessing	assess	VERB
cana-1705	337	10	models	model	NOUN
cana-1705	337	11	of	of	ADP
cana-1705	337	12	traffic	traffic	NOUN
cana-1705	337	13	flow	flow	NOUN
cana-1705	337	14	prediction	prediction	NOUN
cana-1705	337	15	,	,	PUNCT
cana-1705	337	16	since	since	SCONJ
cana-1705	337	17	it	it	PRON
cana-1705	337	18	has	have	VERB
cana-1705	337	19	high	high	ADJ
cana-1705	337	20	temporal	temporal	ADJ
cana-1705	337	21	resolution	resolution	NOUN
cana-1705	337	22	and	and	CCONJ
cana-1705	337	23	covers	cover	VERB
cana-1705	337	24	a	a	DET
cana-1705	337	25	large	large	ADJ
cana-1705	337	26	number	number	NOUN
cana-1705	337	27	of	of	ADP
cana-1705	337	28	sensors	sensor	NOUN
cana-1705	337	29	on	on	ADP
cana-1705	337	30	the	the	DET
cana-1705	337	31	road	road	NOUN
cana-1705	337	32	.	.	PUNCT
cana-1705	338	1	gps	gps	NOUN
cana-1705	338	2	-	-	PUNCT
cana-1705	338	3	enabled	enable	VERB
cana-1705	338	4	urban	urban	ADJ
cana-1705	338	5	dataset	dataset	NOUN
cana-1705	338	6	:	:	PUNCT
cana-1705	338	7	it	it	PRON
cana-1705	338	8	is	be	AUX
cana-1705	338	9	a	a	DET
cana-1705	338	10	dataset	dataset	NOUN
cana-1705	338	11	collected	collect	VERB
cana-1705	338	12	from	from	ADP
cana-1705	338	13	vehicles	vehicle	NOUN
cana-1705	338	14	in	in	ADP
cana-1705	338	15	a	a	DET
cana-1705	338	16	midsized	midsized	ADJ
cana-1705	338	17	city	city	NOUN
cana-1705	338	18	using	use	VERB
cana-1705	338	19	gps	gps	NOUN
cana-1705	338	20	devices	device	NOUN
cana-1705	338	21	.	.	PUNCT
cana-1705	339	1	more	more	ADV
cana-1705	339	2	specifically	specifically	ADV
cana-1705	339	3	,	,	PUNCT
cana-1705	339	4	it	it	PRON
cana-1705	339	5	covers	cover	VERB
cana-1705	339	6	data	datum	NOUN
cana-1705	339	7	regarding	regard	VERB
cana-1705	339	8	traffic	traffic	NOUN
cana-1705	339	9	such	such	ADJ
cana-1705	339	10	as	as	ADP
cana-1705	339	11	vehicle	vehicle	NOUN
cana-1705	339	12	movements	movement	NOUN
cana-1705	339	13	,	,	PUNCT
cana-1705	339	14	speed	speed	NOUN
cana-1705	339	15	and	and	CCONJ
cana-1705	339	16	volume	volume	NOUN
cana-1705	339	17	of	of	ADP
cana-1705	339	18	the	the	DET
cana-1705	339	19	traffic	traffic	NOUN
cana-1705	339	20	.	.	PUNCT
cana-1705	340	1	further	far	ADV
cana-1705	340	2	,	,	PUNCT
cana-1705	340	3	it	it	PRON
cana-1705	340	4	includes	include	VERB
cana-1705	340	5	external	external	ADJ
cana-1705	340	6	information	information	NOUN
cana-1705	340	7	like	like	ADP
cana-1705	340	8	weather	weather	NOUN
cana-1705	340	9	conditions	condition	NOUN
cana-1705	340	10	,	,	PUNCT
cana-1705	340	11	public	public	ADJ
cana-1705	340	12	events	event	NOUN
cana-1705	340	13	,	,	PUNCT
cana-1705	340	14	and	and	CCONJ
cana-1705	340	15	incident	incident	NOUN
cana-1705	340	16	reports	report	NOUN
cana-1705	340	17	carries	carry	VERB
cana-1705	340	18	extra	extra	ADJ
cana-1705	340	19	utility	utility	NOUN
cana-1705	340	20	in	in	ADP
cana-1705	340	21	assessing	assess	VERB
cana-1705	340	22	how	how	SCONJ
cana-1705	340	23	those	those	DET
cana-1705	340	24	factors	factor	NOUN
cana-1705	340	25	impact	impact	VERB
cana-1705	340	26	traffic	traffic	NOUN
cana-1705	340	27	flow	flow	NOUN
cana-1705	340	28	predictions	prediction	NOUN
cana-1705	340	29	.	.	PUNCT
cana-1705	341	1	data	datum	NOUN
cana-1705	341	2	preprocessing	preprocesse	VERB
cana-1705	341	3	data	datum	NOUN
cana-1705	341	4	preprocessing	preprocesse	VERB
cana-1705	341	5	in	in	ADP
cana-1705	341	6	order	order	NOUN
cana-1705	341	7	to	to	PART
cana-1705	341	8	prepare	prepare	VERB
cana-1705	341	9	data	datum	NOUN
cana-1705	341	10	for	for	ADP
cana-1705	341	11	lstm	lstm	PROPN
cana-1705	341	12	model	model	NOUN
cana-1705	341	13	-	-	PUNCT
cana-1705	341	14	training	training	NOUN
cana-1705	341	15	we	we	PRON
cana-1705	341	16	also	also	ADV
cana-1705	341	17	pre	pre	VERB
cana-1705	341	18	-	-	VERB
cana-1705	341	19	processed	process	VERB
cana-1705	341	20	the	the	DET
cana-1705	341	21	raw	raw	ADJ
cana-1705	341	22	traffic	traffic	NOUN
cana-1705	341	23	data	datum	NOUN
cana-1705	341	24	(	(	PUNCT
cana-1705	341	25	cleaning	cleaning	NOUN
cana-1705	341	26	,	,	PUNCT
cana-1705	341	27	normalizing	normalizing	NOUN
cana-1705	341	28	)	)	PUNCT
cana-1705	341	29	and	and	CCONJ
cana-1705	341	30	feature	feature	NOUN
cana-1705	341	31	engineering	engineering	NOUN
cana-1705	341	32	was	be	AUX
cana-1705	341	33	done	do	VERB
cana-1705	341	34	to	to	PART
cana-1705	341	35	enhance	enhance	VERB
cana-1705	341	36	the	the	DET
cana-1705	341	37	prediction	prediction	NOUN
cana-1705	341	38	.	.	PUNCT
cana-1705	342	1	communications	communication	NOUN
cana-1705	342	2	on	on	ADP
cana-1705	342	3	applied	apply	VERB
cana-1705	342	4	nonlinear	nonlinear	ADJ
cana-1705	342	5	analysis	analysis	NOUN
cana-1705	342	6	issn	issn	NOUN
cana-1705	342	7	:	:	PUNCT
cana-1705	342	8	1074	1074	NUM
cana-1705	342	9	-	-	PUNCT
cana-1705	342	10	133x	133x	NUM
cana-1705	342	11	vol	vol	NOUN
cana-1705	342	12	32	32	NUM
cana-1705	342	13	no	no	NOUN
cana-1705	342	14	.	.	NOUN
cana-1705	342	15	2	2	NUM
cana-1705	342	16	(	(	PUNCT
cana-1705	342	17	2025	2025	NUM
cana-1705	342	18	)	)	PUNCT
cana-1705	342	19	19	19	NUM
cana-1705	342	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	342	21	table	table	NOUN
cana-1705	342	22	4	4	NUM
cana-1705	342	23	:	:	PUNCT
cana-1705	342	24	summary	summary	NOUN
cana-1705	342	25	of	of	ADP
cana-1705	342	26	data	datum	NOUN
cana-1705	342	27	preprocessing	preprocessing	NOUN
cana-1705	342	28	steps	step	NOUN
cana-1705	342	29	step	step	NOUN
cana-1705	342	30	description	description	NOUN
cana-1705	342	31	data	datum	NOUN
cana-1705	342	32	cleaning	clean	VERB
cana-1705	342	33	remove	remove	NOUN
cana-1705	342	34	sensor	sensor	NOUN
cana-1705	342	35	malfunctions	malfunction	NOUN
cana-1705	342	36	,	,	PUNCT
cana-1705	342	37	handle	handle	VERB
cana-1705	342	38	missing	miss	VERB
cana-1705	342	39	data	datum	NOUN
cana-1705	342	40	normalization	normalization	PROPN
cana-1705	342	41	min	min	PROPN
cana-1705	342	42	-	-	PROPN
cana-1705	342	43	max	max	PROPN
cana-1705	342	44	normalization	normalization	NOUN
cana-1705	342	45	(	(	PUNCT
cana-1705	342	46	0	0	NUM
cana-1705	342	47	-	-	SYM
cana-1705	342	48	1	1	NUM
cana-1705	342	49	)	)	PUNCT
cana-1705	342	50	feature	feature	NOUN
cana-1705	342	51	engineering	engineering	NOUN
cana-1705	342	52	time	time	NOUN
cana-1705	342	53	of	of	ADP
cana-1705	342	54	day	day	NOUN
cana-1705	342	55	,	,	PUNCT
cana-1705	342	56	day	day	NOUN
cana-1705	342	57	of	of	ADP
cana-1705	342	58	week	week	NOUN
cana-1705	342	59	,	,	PUNCT
cana-1705	342	60	lags	lag	VERB
cana-1705	342	61	train	train	NOUN
cana-1705	342	62	-	-	PUNCT
cana-1705	342	63	test	test	NOUN
cana-1705	342	64	split	split	VERB
cana-1705	342	65	70	70	NUM
cana-1705	342	66	%	%	NOUN
cana-1705	342	67	train	train	NOUN
cana-1705	342	68	,	,	PUNCT
cana-1705	342	69	15	15	NUM
cana-1705	342	70	%	%	NOUN
cana-1705	342	71	validation	validation	NOUN
cana-1705	342	72	,	,	PUNCT
cana-1705	342	73	15	15	NUM
cana-1705	342	74	%	%	NOUN
cana-1705	342	75	test	test	NOUN
cana-1705	342	76	the	the	DET
cana-1705	342	77	steps	step	NOUN
cana-1705	342	78	followed	follow	VERB
cana-1705	342	79	were	be	AUX
cana-1705	342	80	:	:	PUNCT
cana-1705	342	81	data	datum	NOUN
cana-1705	342	82	cleaning	cleaning	NOUN
cana-1705	342	83	:	:	PUNCT
cana-1705	342	84	through	through	ADP
cana-1705	342	85	removing	remove	VERB
cana-1705	342	86	sensor	sensor	NOUN
cana-1705	342	87	mal	mal	ADJ
cana-1705	342	88	-	-	PUNCT
cana-1705	342	89	function	function	NOUN
cana-1705	342	90	or	or	CCONJ
cana-1705	342	91	missing	miss	VERB
cana-1705	342	92	readings	reading	NOUN
cana-1705	342	93	due	due	ADP
cana-1705	342	94	to	to	ADP
cana-1705	342	95	errors	error	NOUN
cana-1705	342	96	.	.	PUNCT
cana-1705	343	1	interpolation	interpolation	NOUN
cana-1705	343	2	techniques	technique	NOUN
cana-1705	343	3	were	be	AUX
cana-1705	343	4	further	far	ADV
cana-1705	343	5	used	use	VERB
cana-1705	343	6	to	to	PART
cana-1705	343	7	identify	identify	VERB
cana-1705	343	8	and	and	CCONJ
cana-1705	343	9	replace	replace	VERB
cana-1705	343	10	outliers	outlier	NOUN
cana-1705	343	11	in	in	ADP
cana-1705	343	12	the	the	DET
cana-1705	343	13	data	datum	NOUN
cana-1705	343	14	.	.	PUNCT
cana-1705	344	1	min	min	ADJ
cana-1705	344	2	-	-	PUNCT
cana-1705	344	3	max	max	PROPN
cana-1705	344	4	normalization	normalization	NOUN
cana-1705	344	5	was	be	AUX
cana-1705	344	6	used	use	VERB
cana-1705	344	7	to	to	PART
cana-1705	344	8	scale	scale	VERB
cana-1705	344	9	all	all	DET
cana-1705	344	10	the	the	DET
cana-1705	344	11	features	feature	NOUN
cana-1705	344	12	(	(	PUNCT
cana-1705	344	13	including	include	VERB
cana-1705	344	14	traffic	traffic	NOUN
cana-1705	344	15	volume	volume	NOUN
cana-1705	344	16	,	,	PUNCT
cana-1705	344	17	speed	speed	NOUN
cana-1705	344	18	and	and	CCONJ
cana-1705	344	19	lane	lane	NOUN
cana-1705	344	20	occupancy	occupancy	NOUN
cana-1705	344	21	)	)	PUNCT
cana-1705	344	22	into	into	ADP
cana-1705	344	23	a	a	DET
cana-1705	344	24	range	range	NOUN
cana-1705	344	25	of	of	ADP
cana-1705	344	26	0–1	0–1	NOUN
cana-1705	344	27	(	(	PUNCT
cana-1705	344	28	both	both	DET
cana-1705	344	29	input	input	NOUN
cana-1705	344	30	data	datum	NOUN
cana-1705	344	31	and	and	CCONJ
cana-1705	344	32	labels	label	NOUN
cana-1705	344	33	were	be	AUX
cana-1705	344	34	normalized	normalize	VERB
cana-1705	344	35	since	since	SCONJ
cana-1705	344	36	lstm	lstm	ADJ
cana-1705	344	37	networks	network	NOUN
cana-1705	344	38	are	be	AUX
cana-1705	344	39	sensitive	sensitive	ADJ
cana-1705	344	40	to	to	ADP
cana-1705	344	41	input	input	NOUN
cana-1705	344	42	data	data	NOUN
cana-1705	344	43	scales	scale	NOUN
cana-1705	344	44	[	[	X
cana-1705	344	45	3	3	NUM
cana-1705	344	46	]	]	NUM
cana-1705	344	47	)	)	PUNCT
cana-1705	344	48	.	.	PUNCT
cana-1705	345	1	feature	feature	NOUN
cana-1705	345	2	engineering	engineering	NOUN
cana-1705	345	3	:	:	PUNCT
cana-1705	345	4	we	we	PRON
cana-1705	345	5	created	create	VERB
cana-1705	345	6	new	new	ADJ
cana-1705	345	7	features	feature	NOUN
cana-1705	345	8	like	like	ADP
cana-1705	345	9	time	time	NOUN
cana-1705	345	10	of	of	ADP
cana-1705	345	11	the	the	DET
cana-1705	345	12	day	day	NOUN
cana-1705	345	13	,	,	PUNCT
cana-1705	345	14	day	day	NOUN
cana-1705	345	15	of	of	ADP
cana-1705	345	16	week	week	NOUN
cana-1705	345	17	,	,	PUNCT
cana-1705	345	18	lags	lag	VERB
cana-1705	345	19	which	which	PRON
cana-1705	345	20	are	be	AUX
cana-1705	345	21	helpful	helpful	ADJ
cana-1705	345	22	for	for	SCONJ
cana-1705	345	23	the	the	DET
cana-1705	345	24	model	model	NOUN
cana-1705	345	25	to	to	PART
cana-1705	345	26	understand	understand	VERB
cana-1705	345	27	traffic	traffic	NOUN
cana-1705	345	28	behavior	behavior	NOUN
cana-1705	345	29	over	over	ADP
cana-1705	345	30	time	time	NOUN
cana-1705	345	31	.	.	PUNCT
cana-1705	346	1	moreover	moreover	ADV
cana-1705	346	2	,	,	PUNCT
cana-1705	346	3	the	the	DET
cana-1705	346	4	dataset	dataset	NOUN
cana-1705	346	5	was	be	AUX
cana-1705	346	6	complemented	complement	VERB
cana-1705	346	7	with	with	ADP
cana-1705	346	8	weather	weather	NOUN
cana-1705	346	9	data	datum	NOUN
cana-1705	346	10	(	(	PUNCT
cana-1705	346	11	temperature	temperature	NOUN
cana-1705	346	12	,	,	PUNCT
cana-1705	346	13	precipitation	precipitation	NOUN
cana-1705	346	14	)	)	PUNCT
cana-1705	346	15	and	and	CCONJ
cana-1705	346	16	incident	incident	NOUN
cana-1705	346	17	data	datum	NOUN
cana-1705	346	18	to	to	PART
cana-1705	346	19	consider	consider	VERB
cana-1705	346	20	external	external	ADJ
cana-1705	346	21	factors	factor	NOUN
cana-1705	346	22	relevant	relevant	ADJ
cana-1705	346	23	for	for	ADP
cana-1705	346	24	traffic	traffic	NOUN
cana-1705	346	25	.	.	PUNCT
cana-1705	347	1	train	train	NOUN
cana-1705	347	2	-	-	PUNCT
cana-1705	347	3	test	test	NOUN
cana-1705	347	4	-	-	PUNCT
cana-1705	347	5	split	split	NOUN
cana-1705	347	6	:	:	PUNCT
cana-1705	347	7	the	the	DET
cana-1705	347	8	dataset	dataset	NOUN
cana-1705	347	9	has	have	AUX
cana-1705	347	10	been	be	AUX
cana-1705	347	11	split	split	VERB
cana-1705	347	12	into	into	ADP
cana-1705	347	13	train	train	NOUN
cana-1705	347	14	,	,	PUNCT
cana-1705	347	15	validation	validation	NOUN
cana-1705	347	16	and	and	CCONJ
cana-1705	347	17	test	test	NOUN
cana-1705	347	18	set	set	VERB
cana-1705	347	19	by	by	ADP
cana-1705	347	20	time	time	NOUN
cana-1705	347	21	-	-	PUNCT
cana-1705	347	22	split	split	NOUN
cana-1705	347	23	approximation	approximation	NOUN
cana-1705	347	24	of	of	ADP
cana-1705	347	25	a	a	DET
cana-1705	347	26	real	real	ADJ
cana-1705	347	27	-	-	PUNCT
cana-1705	347	28	world	world	NOUN
cana-1705	347	29	scenario	scenario	NOUN
cana-1705	347	30	.	.	PUNCT
cana-1705	348	1	we	we	PRON
cana-1705	348	2	predicted	predict	VERB
cana-1705	348	3	the	the	DET
cana-1705	348	4	tst	tst	NOUN
cana-1705	348	5	labels	label	NOUN
cana-1705	348	6	of	of	ADP
cana-1705	348	7	unseen	unseen	ADJ
cana-1705	348	8	samples	sample	NOUN
cana-1705	348	9	using	use	VERB
cana-1705	348	10	a	a	DET
cana-1705	348	11	training	training	NOUN
cana-1705	348	12	/	/	SYM
cana-1705	348	13	validation	validation	NOUN
cana-1705	348	14	/	/	SYM
cana-1705	348	15	testing	testing	NOUN
cana-1705	348	16	split	split	NOUN
cana-1705	348	17	(	(	PUNCT
cana-1705	348	18	70/15/15	70/15/15	NOUN
cana-1705	348	19	%	%	NOUN
cana-1705	348	20	)	)	PUNCT
cana-1705	348	21	.	.	PUNCT
cana-1705	349	1	we	we	PRON
cana-1705	349	2	chose	choose	VERB
cana-1705	349	3	a	a	DET
cana-1705	349	4	time	time	NOUN
cana-1705	349	5	-	-	PUNCT
cana-1705	349	6	based	base	VERB
cana-1705	349	7	split	split	NOUN
cana-1705	349	8	to	to	PART
cana-1705	349	9	adhere	adhere	VERB
cana-1705	349	10	to	to	ADP
cana-1705	349	11	the	the	DET
cana-1705	349	12	principle	principle	NOUN
cana-1705	349	13	of	of	ADP
cana-1705	349	14	not	not	PART
cana-1705	349	15	using	use	VERB
cana-1705	349	16	future	future	ADJ
cana-1705	349	17	data	datum	NOUN
cana-1705	349	18	points	point	NOUN
cana-1705	349	19	in	in	ADP
cana-1705	349	20	the	the	DET
cana-1705	349	21	training	training	NOUN
cana-1705	349	22	.	.	PUNCT
cana-1705	350	1	b.	b.	PROPN
cana-1705	350	2	experimental	experimental	ADJ
cana-1705	350	3	setup	setup	PROPN
cana-1705	350	4	lstm	lstm	PROPN
cana-1705	350	5	model	model	NOUN
cana-1705	350	6	configuration	configuration	NOUN
cana-1705	350	7	the	the	DET
cana-1705	350	8	architecture	architecture	NOUN
cana-1705	350	9	of	of	ADP
cana-1705	350	10	the	the	DET
cana-1705	350	11	lstm	lstm	PROPN
cana-1705	350	12	network	network	NOUN
cana-1705	350	13	is	be	AUX
cana-1705	350	14	chosen	choose	VERB
cana-1705	350	15	to	to	PART
cana-1705	350	16	accommodate	accommodate	VERB
cana-1705	350	17	the	the	DET
cana-1705	350	18	sequentiality	sequentiality	NOUN
cana-1705	350	19	of	of	ADP
cana-1705	350	20	traffic	traffic	NOUN
cana-1705	350	21	data	datum	NOUN
cana-1705	350	22	and	and	CCONJ
cana-1705	350	23	captures	capture	VERB
cana-1705	350	24	long	long	ADJ
cana-1705	350	25	-	-	PUNCT
cana-1705	350	26	term	term	NOUN
cana-1705	350	27	dependencies	dependency	NOUN
cana-1705	350	28	.	.	PUNCT
cana-1705	351	1	the	the	DET
cana-1705	351	2	model	model	NOUN
cana-1705	351	3	included	include	VERB
cana-1705	351	4	following	follow	VERB
cana-1705	351	5	components	component	NOUN
cana-1705	351	6	:	:	PUNCT
cana-1705	351	7	input	input	NOUN
cana-1705	351	8	layer	layer	NOUN
cana-1705	351	9	:	:	PUNCT
cana-1705	351	10	traffic	traffic	NOUN
cana-1705	351	11	features	feature	VERB
cana-1705	351	12	such	such	ADJ
cana-1705	351	13	as	as	ADP
cana-1705	351	14	traffic	traffic	NOUN
cana-1705	351	15	volume	volume	NOUN
cana-1705	351	16	,	,	PUNCT
cana-1705	351	17	speed	speed	NOUN
cana-1705	351	18	,	,	PUNCT
cana-1705	351	19	lane	lane	NOUN
cana-1705	351	20	occupancy	occupancy	NOUN
cana-1705	351	21	,	,	PUNCT
cana-1705	351	22	weather	weather	NOUN
cana-1705	351	23	conditions	condition	NOUN
cana-1705	351	24	and	and	CCONJ
cana-1705	351	25	incident	incident	NOUN
cana-1705	351	26	reports	report	NOUN
cana-1705	351	27	received	receive	VERB
cana-1705	351	28	in	in	ADP
cana-1705	351	29	this	this	DET
cana-1705	351	30	layer	layer	NOUN
cana-1705	351	31	which	which	PRON
cana-1705	351	32	processed	process	VERB
cana-1705	351	33	in	in	ADP
cana-1705	351	34	a	a	DET
cana-1705	351	35	time	time	NOUN
cana-1705	351	36	-	-	PUNCT
cana-1705	351	37	series	series	NOUN
cana-1705	351	38	input	input	NOUN
cana-1705	351	39	.	.	PUNCT
cana-1705	352	1	lstm	lstm	ADJ
cana-1705	352	2	layers	layer	NOUN
cana-1705	352	3	:	:	PUNCT
cana-1705	352	4	there	there	PRON
cana-1705	352	5	are	be	VERB
cana-1705	352	6	two	two	NUM
cana-1705	352	7	lstm	lstm	ADJ
cana-1705	352	8	layers	layer	NOUN
cana-1705	352	9	used	use	VERB
cana-1705	352	10	with	with	ADP
cana-1705	352	11	128	128	NUM
cana-1705	352	12	memory	memory	NOUN
cana-1705	352	13	units	unit	NOUN
cana-1705	352	14	in	in	ADP
cana-1705	352	15	each	each	PRON
cana-1705	352	16	.	.	PUNCT
cana-1705	353	1	after	after	ADP
cana-1705	353	2	the	the	DET
cana-1705	353	3	lstm	lstm	ADJ
cana-1705	353	4	layers	layer	NOUN
cana-1705	353	5	i	i	PRON
cana-1705	353	6	included	include	VERB
cana-1705	353	7	a	a	DET
cana-1705	353	8	recurrent	recurrent	ADJ
cana-1705	353	9	dropout	dropout	NOUN
cana-1705	353	10	to	to	PART
cana-1705	353	11	avoid	avoid	VERB
cana-1705	353	12	overfitting	overfitte	VERB
cana-1705	353	13	.	.	PUNCT
cana-1705	354	1	hyperparameters	hyperparameter	NOUN
cana-1705	354	2	of	of	ADP
cana-1705	354	3	the	the	DET
cana-1705	354	4	model	model	NOUN
cana-1705	354	5	;	;	PUNCT
cana-1705	354	6	the	the	DET
cana-1705	354	7	best	good	ADJ
cana-1705	354	8	performance	performance	NOUN
cana-1705	354	9	was	be	AUX
cana-1705	354	10	achieved	achieve	VERB
cana-1705	354	11	using	use	VERB
cana-1705	354	12	experimentally	experimentally	ADV
cana-1705	354	13	adjusted	adjust	VERB
cana-1705	354	14	features	feature	NOUN
cana-1705	354	15	of	of	ADP
cana-1705	354	16	an	an	DET
cana-1705	354	17	lstm	lstm	ADJ
cana-1705	354	18	network	network	NOUN
cana-1705	354	19	where	where	SCONJ
cana-1705	354	20	the	the	DET
cana-1705	354	21	number	number	NOUN
cana-1705	354	22	of	of	ADP
cana-1705	354	23	hidden	hidden	ADJ
cana-1705	354	24	layers	layer	NOUN
cana-1705	354	25	,	,	PUNCT
cana-1705	354	26	memory	memory	NOUN
cana-1705	354	27	units	unit	NOUN
cana-1705	354	28	and	and	CCONJ
cana-1705	354	29	some	some	DET
cana-1705	354	30	regularization	regularization	NOUN
cana-1705	354	31	techniques	technique	NOUN
cana-1705	354	32	like	like	ADP
cana-1705	354	33	a	a	DET
cana-1705	354	34	dropout	dropout	NOUN
cana-1705	354	35	(	(	PUNCT
cana-1705	354	36	with	with	ADP
cana-1705	354	37	0.2	0.2	NUM
cana-1705	354	38	rate	rate	NOUN
cana-1705	354	39	)	)	PUNCT
cana-1705	354	40	.	.	PUNCT
cana-1705	355	1	fully	fully	ADV
cana-1705	355	2	connected	connected	ADJ
cana-1705	355	3	layers	layer	NOUN
cana-1705	355	4	:	:	PUNCT
cana-1705	355	5	a	a	DET
cana-1705	355	6	fully	fully	ADV
cana-1705	355	7	connected	connect	VERB
cana-1705	355	8	layer	layer	NOUN
cana-1705	355	9	with	with	ADP
cana-1705	355	10	relu	relu	NOUN
cana-1705	355	11	activation	activation	NOUN
cana-1705	355	12	was	be	AUX
cana-1705	355	13	introduced	introduce	VERB
cana-1705	355	14	at	at	ADP
cana-1705	355	15	a	a	DET
cana-1705	355	16	higher	high	ADJ
cana-1705	355	17	level	level	NOUN
cana-1705	355	18	right	right	ADV
cana-1705	355	19	after	after	SCONJ
cana-1705	355	20	the	the	DET
cana-1705	355	21	lstm	lstm	ADJ
cana-1705	355	22	layers	layer	NOUN
cana-1705	355	23	to	to	PART
cana-1705	355	24	link	link	VERB
cana-1705	355	25	capabilities	capability	NOUN
cana-1705	355	26	learned	learn	VERB
cana-1705	355	27	through	through	ADP
cana-1705	355	28	them	they	PRON
cana-1705	355	29	as	as	SCONJ
cana-1705	355	30	seen	see	VERB
cana-1705	355	31	in	in	ADP
cana-1705	355	32	figure	figure	NOUN
cana-1705	355	33	1	1	NUM
cana-1705	355	34	,	,	PUNCT
cana-1705	355	35	followed	follow	VERB
cana-1705	355	36	by	by	ADP
cana-1705	355	37	a	a	DET
cana-1705	355	38	final	final	ADJ
cana-1705	355	39	output	output	NOUN
cana-1705	355	40	layer	layer	NOUN
cana-1705	355	41	for	for	ADP
cana-1705	355	42	regression	regression	NOUN
cana-1705	355	43	.	.	PUNCT
cana-1705	356	1	output	output	NOUN
cana-1705	356	2	layer	layer	NOUN
cana-1705	356	3	:	:	PUNCT
cana-1705	356	4	produced	produce	VERB
cana-1705	356	5	the	the	DET
cana-1705	356	6	predicted	predict	VERB
cana-1705	356	7	traffic	traffic	NOUN
cana-1705	356	8	flow	flow	NOUN
cana-1705	356	9	(	(	PUNCT
cana-1705	356	10	in	in	ADP
cana-1705	356	11	terms	term	NOUN
cana-1705	356	12	of	of	ADP
cana-1705	356	13	volume	volume	NOUN
cana-1705	356	14	or	or	CCONJ
cana-1705	356	15	speed	speed	NOUN
cana-1705	356	16	)	)	PUNCT
cana-1705	356	17	in	in	ADP
cana-1705	356	18	the	the	DET
cana-1705	356	19	next	next	ADJ
cana-1705	356	20	time	time	NOUN
cana-1705	356	21	step	step	NOUN
cana-1705	356	22	.	.	PUNCT
cana-1705	357	1	communications	communication	NOUN
cana-1705	357	2	on	on	ADP
cana-1705	357	3	applied	apply	VERB
cana-1705	357	4	nonlinear	nonlinear	ADJ
cana-1705	357	5	analysis	analysis	NOUN
cana-1705	357	6	issn	issn	NOUN
cana-1705	357	7	:	:	PUNCT
cana-1705	357	8	1074	1074	NUM
cana-1705	357	9	-	-	PUNCT
cana-1705	357	10	133x	133x	NUM
cana-1705	357	11	vol	vol	NOUN
cana-1705	357	12	32	32	NUM
cana-1705	357	13	no	no	NOUN
cana-1705	357	14	.	.	NOUN
cana-1705	357	15	2	2	NUM
cana-1705	357	16	(	(	PUNCT
cana-1705	357	17	2025	2025	NUM
cana-1705	357	18	)	)	PUNCT
cana-1705	357	19	20	20	NUM
cana-1705	357	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	357	21	table	table	NOUN
cana-1705	357	22	5	5	NUM
cana-1705	357	23	:	:	PUNCT
cana-1705	357	24	lstm	lstm	ADJ
cana-1705	357	25	architecture	architecture	NOUN
cana-1705	357	26	and	and	CCONJ
cana-1705	357	27	hyperparameters	hyperparameter	VERB
cana-1705	357	28	layer	layer	NOUN
cana-1705	357	29	type	type	NOUN
cana-1705	357	30	units	unit	NOUN
cana-1705	357	31	/	/	SYM
cana-1705	357	32	activation	activation	NOUN
cana-1705	357	33	dropout	dropout	NOUN
cana-1705	357	34	rate	rate	NOUN
cana-1705	357	35	regularization	regularization	NOUN
cana-1705	357	36	input	input	NOUN
cana-1705	357	37	layer	layer	NOUN
cana-1705	357	38	5	5	NUM
cana-1705	357	39	features	feature	VERB
cana-1705	357	40	lstm	lstm	ADJ
cana-1705	357	41	layer	layer	NOUN
cana-1705	357	42	1	1	NUM
cana-1705	357	43	128	128	NUM
cana-1705	357	44	units	unit	NOUN
cana-1705	357	45	0.2	0.2	NUM
cana-1705	357	46	lstm	lstm	NOUN
cana-1705	357	47	layer	layer	NOUN
cana-1705	357	48	2	2	NUM
cana-1705	357	49	128	128	NUM
cana-1705	357	50	units	unit	NOUN
cana-1705	357	51	0.2	0.2	NUM
cana-1705	357	52	fully	fully	ADV
cana-1705	357	53	connected	connect	VERB
cana-1705	357	54	layer	layer	NOUN
cana-1705	357	55	relu	relu	NOUN
cana-1705	357	56	l2	l2	NOUN
cana-1705	357	57	output	output	NOUN
cana-1705	357	58	layer	layer	NOUN
cana-1705	357	59	1	1	NUM
cana-1705	357	60	(	(	PUNCT
cana-1705	357	61	regression	regression	NOUN
cana-1705	357	62	)	)	PUNCT
cana-1705	357	63	the	the	DET
cana-1705	357	64	model	model	NOUN
cana-1705	357	65	was	be	AUX
cana-1705	357	66	trained	train	VERB
cana-1705	357	67	using	use	VERB
cana-1705	357	68	the	the	DET
cana-1705	357	69	adam	adam	PROPN
cana-1705	357	70	optimizer	optimizer	NOUN
cana-1705	357	71	with	with	ADP
cana-1705	357	72	an	an	DET
cana-1705	357	73	initial	initial	ADJ
cana-1705	357	74	learning	learning	NOUN
cana-1705	357	75	rate	rate	NOUN
cana-1705	357	76	of	of	ADP
cana-1705	357	77	0.001	0.001	NUM
cana-1705	357	78	the	the	DET
cana-1705	357	79	loss	loss	NOUN
cana-1705	357	80	function	function	NOUN
cana-1705	357	81	for	for	ADP
cana-1705	357	82	regression	regression	NOUN
cana-1705	357	83	tasks	task	NOUN
cana-1705	357	84	is	be	AUX
cana-1705	357	85	mse	mse	NOUN
cana-1705	357	86	(	(	PUNCT
cana-1705	357	87	mean	mean	VERB
cana-1705	357	88	squared	square	VERB
cana-1705	357	89	error	error	NOUN
cana-1705	357	90	)	)	PUNCT
cana-1705	357	91	which	which	PRON
cana-1705	357	92	punishes	punish	VERB
cana-1705	357	93	large	large	ADJ
cana-1705	357	94	differences	difference	NOUN
cana-1705	357	95	between	between	ADP
cana-1705	357	96	predicted	predict	VERB
cana-1705	357	97	and	and	CCONJ
cana-1705	357	98	true	true	ADJ
cana-1705	357	99	labels	label	NOUN
cana-1705	357	100	.	.	PUNCT
cana-1705	358	1	comparison	comparison	NOUN
cana-1705	358	2	of	of	ADP
cana-1705	358	3	baseline	baseline	NOUN
cana-1705	358	4	models	model	NOUN
cana-1705	358	5	we	we	PRON
cana-1705	358	6	benchmarked	benchmarke	VERB
cana-1705	358	7	the	the	DET
cana-1705	358	8	lstm	lstm	PROPN
cana-1705	358	9	network	network	NOUN
cana-1705	358	10	against	against	ADP
cana-1705	358	11	several	several	ADJ
cana-1705	358	12	state	state	NOUN
cana-1705	358	13	-	-	PUNCT
cana-1705	358	14	of	of	ADP
cana-1705	358	15	-	-	PUNCT
cana-1705	358	16	the	the	DET
cana-1705	358	17	-	-	PUNCT
cana-1705	358	18	art	art	NOUN
cana-1705	358	19	traffic	traffic	NOUN
cana-1705	358	20	flow	flow	NOUN
cana-1705	358	21	prediction	prediction	NOUN
cana-1705	358	22	baseline	baseline	NOUN
cana-1705	358	23	models	model	NOUN
cana-1705	358	24	.	.	PUNCT
cana-1705	359	1	arima	arima	PROPN
cana-1705	359	2	model	model	NOUN
cana-1705	359	3	:	:	PUNCT
cana-1705	359	4	arima	arima	PROPN
cana-1705	359	5	is	be	AUX
cana-1705	359	6	a	a	DET
cana-1705	359	7	time	time	NOUN
cana-1705	359	8	series	series	NOUN
cana-1705	359	9	forecasting	forecasting	NOUN
cana-1705	359	10	method	method	NOUN
cana-1705	359	11	,	,	PUNCT
cana-1705	359	12	where	where	SCONJ
cana-1705	359	13	depending	depend	VERB
cana-1705	359	14	on	on	ADP
cana-1705	359	15	the	the	DET
cana-1705	359	16	previous	previous	ADJ
cana-1705	359	17	values	value	NOUN
cana-1705	359	18	how	how	SCONJ
cana-1705	359	19	the	the	DET
cana-1705	359	20	upcoming	upcoming	ADJ
cana-1705	359	21	traffic	traffic	NOUN
cana-1705	359	22	flow	flow	NOUN
cana-1705	359	23	can	can	AUX
cana-1705	359	24	be	be	AUX
cana-1705	359	25	predicted	predict	VERB
cana-1705	359	26	.	.	PUNCT
cana-1705	360	1	although	although	SCONJ
cana-1705	360	2	this	this	PRON
cana-1705	360	3	is	be	AUX
cana-1705	360	4	a	a	DET
cana-1705	360	5	widely	widely	ADV
cana-1705	360	6	used	use	VERB
cana-1705	360	7	baseline	baseline	NOUN
cana-1705	360	8	for	for	ADP
cana-1705	360	9	traffic	traffic	NOUN
cana-1705	360	10	prediction	prediction	NOUN
cana-1705	360	11	,	,	PUNCT
cana-1705	360	12	it	it	PRON
cana-1705	360	13	can	can	AUX
cana-1705	360	14	not	not	PART
cana-1705	360	15	capture	capture	VERB
cana-1705	360	16	the	the	DET
cana-1705	360	17	non	non	ADJ
cana-1705	360	18	-	-	ADJ
cana-1705	360	19	linear	linear	ADJ
cana-1705	360	20	patterns	pattern	NOUN
cana-1705	360	21	and	and	CCONJ
cana-1705	360	22	complex	complex	ADJ
cana-1705	360	23	temporal	temporal	ADJ
cana-1705	360	24	dependencies	dependency	NOUN
cana-1705	360	25	.	.	PUNCT
cana-1705	361	1	support	support	NOUN
cana-1705	361	2	vector	vector	NOUN
cana-1705	361	3	machine	machine	NOUN
cana-1705	361	4	(	(	PUNCT
cana-1705	361	5	svm)the	svm)the	DET
cana-1705	361	6	svm	svm	PROPN
cana-1705	361	7	model	model	NOUN
cana-1705	361	8	was	be	AUX
cana-1705	361	9	implemented	implement	VERB
cana-1705	361	10	with	with	ADP
cana-1705	361	11	an	an	DET
cana-1705	361	12	rbf	rbf	PROPN
cana-1705	361	13	kernel	kernel	PROPN
cana-1705	361	14	.	.	PUNCT
cana-1705	362	1	even	even	ADV
cana-1705	362	2	though	though	SCONJ
cana-1705	362	3	svms	svms	NOUN
cana-1705	362	4	can	can	AUX
cana-1705	362	5	encode	encode	VERB
cana-1705	362	6	some	some	DET
cana-1705	362	7	(	(	PUNCT
cana-1705	362	8	linear	linear	ADJ
cana-1705	362	9	and	and	CCONJ
cana-1705	362	10	gaussian	gaussian	ADJ
cana-1705	362	11	)	)	PUNCT
cana-1705	362	12	nonlinearity	nonlinearity	NOUN
cana-1705	362	13	,	,	PUNCT
cana-1705	362	14	dealing	deal	VERB
cana-1705	362	15	with	with	ADP
cana-1705	362	16	temporal	temporal	ADJ
cana-1705	362	17	sequences	sequence	NOUN
cana-1705	362	18	is	be	AUX
cana-1705	362	19	a	a	DET
cana-1705	362	20	challenging	challenging	ADJ
cana-1705	362	21	task	task	NOUN
cana-1705	362	22	which	which	PRON
cana-1705	362	23	makes	make	VERB
cana-1705	362	24	them	they	PRON
cana-1705	362	25	less	less	ADV
cana-1705	362	26	useful	useful	ADJ
cana-1705	362	27	in	in	ADP
cana-1705	362	28	practical	practical	ADJ
cana-1705	362	29	applications	application	NOUN
cana-1705	362	30	such	such	ADJ
cana-1705	362	31	as	as	ADP
cana-1705	362	32	for	for	ADP
cana-1705	362	33	time	time	NOUN
cana-1705	362	34	-	-	PUNCT
cana-1705	362	35	series	series	NOUN
cana-1705	362	36	prediction	prediction	NOUN
cana-1705	362	37	tasks	task	NOUN
cana-1705	362	38	(	(	PUNCT
cana-1705	362	39	like	like	ADP
cana-1705	362	40	traffic	traffic	NOUN
cana-1705	362	41	flow	flow	NOUN
cana-1705	362	42	)	)	PUNCT
cana-1705	362	43	.	.	PUNCT
cana-1705	363	1	baseline	baseline	PROPN
cana-1705	363	2	multilayer	multilayer	PROPN
cana-1705	363	3	perceptron	perceptron	PROPN
cana-1705	363	4	(	(	PUNCT
cana-1705	363	5	mlp	mlp	PROPN
cana-1705	363	6	)	)	PUNCT
cana-1705	363	7	:	:	PUNCT
cana-1705	363	8	another	another	DET
cana-1705	363	9	baseline	baseline	NOUN
cana-1705	363	10	which	which	PRON
cana-1705	363	11	was	be	AUX
cana-1705	363	12	an	an	DET
cana-1705	363	13	si	si	PROPN
cana-1705	363	14	mple	mple	PROPN
cana-1705	363	15	feedforward	feedforward	PROPN
cana-1705	363	16	neural	neural	ADJ
cana-1705	363	17	network	network	NOUN
cana-1705	363	18	.	.	PUNCT
cana-1705	364	1	the	the	DET
cana-1705	364	2	model	model	NOUN
cana-1705	364	3	is	be	AUX
cana-1705	364	4	not	not	PART
cana-1705	364	5	a	a	DET
cana-1705	364	6	lstm	lstm	ADJ
cana-1705	364	7	network	network	NOUN
cana-1705	364	8	which	which	PRON
cana-1705	364	9	maintains	maintain	VERB
cana-1705	364	10	people	people	NOUN
cana-1705	364	11	warm	warm	ADJ
cana-1705	364	12	if	if	SCONJ
cana-1705	364	13	they	they	PRON
cana-1705	364	14	be	be	AUX
cana-1705	364	15	used	use	VERB
cana-1705	364	16	in	in	ADP
cana-1705	364	17	continuous	continuous	ADJ
cana-1705	364	18	control	control	NOUN
cana-1705	364	19	problems	problem	NOUN
cana-1705	364	20	because	because	SCONJ
cana-1705	364	21	the	the	DET
cana-1705	364	22	model	model	NOUN
cana-1705	364	23	has	have	VERB
cana-1705	364	24	no	no	DET
cana-1705	364	25	recurrent	recurrent	ADJ
cana-1705	364	26	connections	connection	NOUN
cana-1705	364	27	.	.	PUNCT
cana-1705	365	1	table	table	NOUN
cana-1705	365	2	6	6	NUM
cana-1705	365	3	:	:	PUNCT
cana-1705	365	4	comparison	comparison	NOUN
cana-1705	365	5	of	of	ADP
cana-1705	365	6	lstm	lstm	NOUN
cana-1705	365	7	vs	vs	ADP
cana-1705	365	8	arima	arima	PROPN
cana-1705	365	9	,	,	PUNCT
cana-1705	365	10	svm	svm	PROPN
cana-1705	365	11	,	,	PUNCT
cana-1705	365	12	and	and	CCONJ
cana-1705	365	13	mlp	mlp	PROPN
cana-1705	365	14	on	on	ADP
cana-1705	365	15	metr	metr	PROPN
cana-1705	365	16	-	-	PUNCT
cana-1705	365	17	la	la	ADJ
cana-1705	365	18	dataset	dataset	NOUN
cana-1705	365	19	(	(	PUNCT
cana-1705	365	20	performance	performance	NOUN
cana-1705	365	21	metrics	metric	NOUN
cana-1705	365	22	)	)	PUNCT
cana-1705	365	23	model	model	NOUN
cana-1705	365	24	rmse	rmse	PROPN
cana-1705	365	25	mae	mae	PROPN
cana-1705	365	26	mse	mse	PROPN
cana-1705	365	27	lstm	lstm	PROPN
cana-1705	365	28	6.78	6.78	NUM
cana-1705	365	29	5.12	5.12	NUM
cana-1705	365	30	45.96	45.96	NUM
cana-1705	365	31	arima	arima	PROPN
cana-1705	365	32	10.34	10.34	NUM
cana-1705	365	33	8.34	8.34	NUM
cana-1705	365	34	106.88	106.88	NUM
cana-1705	365	35	svm	svm	NOUN
cana-1705	365	36	8.72	8.72	NUM
cana-1705	365	37	6.78	6.78	NUM
cana-1705	365	38	76.06	76.06	NUM
cana-1705	365	39	mlp	mlp	NOUN
cana-1705	365	40	9.45	9.45	NUM
cana-1705	365	41	7.23	7.23	NUM
cana-1705	365	42	89.28	89.28	NUM
cana-1705	365	43	table	table	NOUN
cana-1705	365	44	7	7	NUM
cana-1705	365	45	:	:	PUNCT
cana-1705	365	46	performance	performance	NOUN
cana-1705	365	47	metrics	metric	NOUN
cana-1705	365	48	for	for	ADP
cana-1705	365	49	lstm	lstm	PROPN
cana-1705	365	50	,	,	PUNCT
cana-1705	365	51	arima	arima	PROPN
cana-1705	365	52	,	,	PUNCT
cana-1705	365	53	svm	svm	VERB
cana-1705	365	54	on	on	ADP
cana-1705	365	55	gps	gps	NOUN
cana-1705	365	56	-	-	PUNCT
cana-1705	365	57	enabled	enable	VERB
cana-1705	365	58	dataset	dataset	NOUN
cana-1705	365	59	model	model	NOUN
cana-1705	365	60	rmse	rmse	PROPN
cana-1705	365	61	mae	mae	PROPN
cana-1705	365	62	mse	mse	PROPN
cana-1705	365	63	lstm	lstm	PROPN
cana-1705	365	64	5.90	5.90	NUM
cana-1705	365	65	4.65	4.65	NUM
cana-1705	365	66	34.81	34.81	NUM
cana-1705	365	67	arima	arima	NOUN
cana-1705	365	68	9.21	9.21	NUM
cana-1705	365	69	7.12	7.12	NUM
cana-1705	365	70	84.88	84.88	NUM
cana-1705	365	71	svm	svm	NOUN
cana-1705	365	72	7.45	7.45	NUM
cana-1705	365	73	6.01	6.01	NUM
cana-1705	365	74	55.50	55.50	NUM
cana-1705	365	75	hyperparameter	hyperparameter	NOUN
cana-1705	365	76	tuning	tuning	NOUN
cana-1705	365	77	&	&	CCONJ
cana-1705	365	78	optimization	optimization	NOUN
cana-1705	365	79	hyperparameter	hyperparameter	NOUN
cana-1705	365	80	tuning	tuning	NOUN
cana-1705	365	81	:	:	PUNCT
cana-1705	365	82	grid	grid	NOUN
cana-1705	365	83	search	search	NOUN
cana-1705	365	84	and	and	CCONJ
cana-1705	365	85	random	random	ADJ
cana-1705	365	86	search	search	NOUN
cana-1705	365	87	to	to	PART
cana-1705	365	88	tune	tune	VERB
cana-1705	365	89	individual	individual	ADJ
cana-1705	365	90	models	model	NOUN
cana-1705	365	91	.	.	PUNCT
cana-1705	366	1	hyperparameters	hyperparameter	NOUN
cana-1705	366	2	such	such	ADJ
cana-1705	366	3	as	as	ADP
cana-1705	366	4	the	the	DET
cana-1705	366	5	number	number	NOUN
cana-1705	366	6	of	of	ADP
cana-1705	366	7	layers	layer	NOUN
cana-1705	366	8	,	,	PUNCT
cana-1705	366	9	memory	memory	NOUN
cana-1705	366	10	units	unit	NOUN
cana-1705	366	11	per	per	ADP
cana-1705	366	12	layer	layer	NOUN
cana-1705	366	13	,	,	PUNCT
cana-1705	366	14	learning	learn	VERB
cana-1705	366	15	rate	rate	NOUN
cana-1705	366	16	,	,	PUNCT
cana-1705	366	17	batch	batch	NOUN
cana-1705	366	18	size	size	NOUN
cana-1705	366	19	and	and	CCONJ
cana-1705	366	20	dropout	dropout	NOUN
cana-1705	366	21	were	be	AUX
cana-1705	366	22	communications	communication	NOUN
cana-1705	366	23	on	on	ADP
cana-1705	366	24	applied	apply	VERB
cana-1705	366	25	nonlinear	nonlinear	ADJ
cana-1705	366	26	analysis	analysis	NOUN
cana-1705	366	27	issn	issn	NOUN
cana-1705	366	28	:	:	PUNCT
cana-1705	366	29	1074	1074	NUM
cana-1705	366	30	-	-	PUNCT
cana-1705	366	31	133x	133x	NUM
cana-1705	366	32	vol	vol	NOUN
cana-1705	366	33	32	32	NUM
cana-1705	366	34	no	no	NOUN
cana-1705	366	35	.	.	NOUN
cana-1705	366	36	2	2	NUM
cana-1705	366	37	(	(	PUNCT
cana-1705	366	38	2025	2025	NUM
cana-1705	366	39	)	)	PUNCT
cana-1705	366	40	21	21	NUM
cana-1705	366	41	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	366	42	tuned	tune	VERB
cana-1705	366	43	according	accord	VERB
cana-1705	366	44	to	to	ADP
cana-1705	366	45	the	the	DET
cana-1705	366	46	validation	validation	NOUN
cana-1705	366	47	set	set	VERB
cana-1705	366	48	performance	performance	NOUN
cana-1705	366	49	.	.	PUNCT
cana-1705	367	1	the	the	DET
cana-1705	367	2	best	well	ADV
cana-1705	367	3	-	-	PUNCT
cana-1705	367	4	performing	perform	VERB
cana-1705	367	5	lstm	lstm	ADJ
cana-1705	367	6	architecture	architecture	NOUN
cana-1705	367	7	was	be	AUX
cana-1705	367	8	the	the	DET
cana-1705	367	9	one	one	NOUN
cana-1705	367	10	that	that	PRON
cana-1705	367	11	returned	return	VERB
cana-1705	367	12	the	the	DET
cana-1705	367	13	lowest	low	ADJ
cana-1705	367	14	validation	validation	NOUN
cana-1705	367	15	loss	loss	NOUN
cana-1705	367	16	.	.	PUNCT
cana-1705	368	1	c.	c.	NOUN
cana-1705	368	2	results	result	NOUN
cana-1705	368	3	and	and	CCONJ
cana-1705	368	4	analysis	analysis	NOUN
cana-1705	368	5	lstm	lstm	ADJ
cana-1705	368	6	model	model	NOUN
cana-1705	368	7	in	in	ADP
cana-1705	368	8	-	-	PUNCT
cana-1705	368	9	sample	sample	NOUN
cana-1705	368	10	predictive	predictive	ADJ
cana-1705	368	11	accuracy	accuracy	NOUN
cana-1705	368	12	experiment	experiment	NOUN
cana-1705	368	13	results	result	NOUN
cana-1705	368	14	demonstrated	demonstrate	VERB
cana-1705	368	15	that	that	SCONJ
cana-1705	368	16	in	in	ADP
cana-1705	368	17	predicting	predict	VERB
cana-1705	368	18	real	real	ADJ
cana-1705	368	19	-	-	PUNCT
cana-1705	368	20	time	time	NOUN
cana-1705	368	21	traffic	traffic	NOUN
cana-1705	368	22	flow	flow	NOUN
cana-1705	368	23	,	,	PUNCT
cana-1705	368	24	the	the	DET
cana-1705	368	25	lstm	lstm	PROPN
cana-1705	368	26	model	model	NOUN
cana-1705	368	27	performs	perform	VERB
cana-1705	368	28	incredibly	incredibly	ADV
cana-1705	368	29	better	well	ADJ
cana-1705	368	30	than	than	ADP
cana-1705	368	31	the	the	DET
cana-1705	368	32	baseline	baseline	NOUN
cana-1705	368	33	models	model	NOUN
cana-1705	368	34	.	.	PUNCT
cana-1705	369	1	for	for	ADP
cana-1705	369	2	the	the	DET
cana-1705	369	3	metr	metr	PROPN
cana-1705	369	4	-	-	PUNCT
cana-1705	369	5	la	la	NOUN
cana-1705	369	6	and	and	CCONJ
cana-1705	369	7	the	the	DET
cana-1705	369	8	gps	gps	PROPN
cana-1705	369	9	-	-	PUNCT
cana-1705	369	10	enabled	enable	VERB
cana-1705	369	11	urban	urban	ADJ
cana-1705	369	12	datasets	dataset	NOUN
cana-1705	369	13	,	,	PUNCT
cana-1705	369	14	the	the	DET
cana-1705	369	15	lstm	lstm	PROPN
cana-1705	369	16	model	model	NOUN
cana-1705	369	17	performed	perform	VERB
cana-1705	369	18	better	well	ADV
cana-1705	369	19	in	in	ADP
cana-1705	369	20	terms	term	NOUN
cana-1705	369	21	of	of	ADP
cana-1705	369	22	mse	mse	NOUN
cana-1705	369	23	,	,	PUNCT
cana-1705	369	24	rmse	rmse	NOUN
cana-1705	369	25	,	,	PUNCT
cana-1705	369	26	and	and	CCONJ
cana-1705	369	27	mae	mae	PROPN
cana-1705	369	28	than	than	ADP
cana-1705	369	29	arima	arima	PROPN
cana-1705	369	30	,	,	PUNCT
cana-1705	369	31	svm	svm	PROPN
cana-1705	369	32	,	,	PUNCT
cana-1705	369	33	and	and	CCONJ
cana-1705	369	34	mlp	mlp	PROPN
cana-1705	369	35	.	.	PUNCT
cana-1705	370	1	for	for	ADP
cana-1705	370	2	illustration	illustration	NOUN
cana-1705	370	3	,	,	PUNCT
cana-1705	370	4	on	on	ADP
cana-1705	370	5	the	the	DET
cana-1705	370	6	metr	metr	PROPN
cana-1705	370	7	-	-	PUNCT
cana-1705	370	8	la	la	NOUN
cana-1705	370	9	dataset	dataset	NOUN
cana-1705	370	10	,	,	PUNCT
cana-1705	370	11	the	the	DET
cana-1705	370	12	rmse	rmse	NOUN
cana-1705	370	13	of	of	ADP
cana-1705	370	14	arima	arima	PROPN
cana-1705	370	15	was	be	AUX
cana-1705	370	16	10.34	10.34	NUM
cana-1705	370	17	and	and	CCONJ
cana-1705	370	18	that	that	PRON
cana-1705	370	19	of	of	ADP
cana-1705	370	20	svms	svms	NOUN
cana-1705	370	21	was	be	AUX
cana-1705	370	22	8.72	8.72	NUM
cana-1705	370	23	while	while	SCONJ
cana-1705	370	24	it	it	PRON
cana-1705	370	25	was	be	AUX
cana-1705	370	26	only	only	ADV
cana-1705	370	27	6.78	6.78	NUM
cana-1705	370	28	for	for	ADP
cana-1705	370	29	lstm	lstm	NOUN
cana-1705	370	30	.	.	PUNCT
cana-1705	371	1	especially	especially	ADV
cana-1705	371	2	when	when	SCONJ
cana-1705	371	3	traffic	traffic	NOUN
cana-1705	371	4	was	be	AUX
cana-1705	371	5	very	very	ADV
cana-1705	371	6	slow	slow	ADJ
cana-1705	371	7	,	,	PUNCT
cana-1705	371	8	there	there	PRON
cana-1705	371	9	was	be	VERB
cana-1705	371	10	an	an	DET
cana-1705	371	11	even	even	ADV
cana-1705	371	12	greater	great	ADJ
cana-1705	371	13	gap	gap	NOUN
cana-1705	371	14	in	in	ADP
cana-1705	371	15	performance	performance	NOUN
cana-1705	371	16	because	because	SCONJ
cana-1705	371	17	the	the	DET
cana-1705	371	18	conventional	conventional	ADJ
cana-1705	371	19	models	model	NOUN
cana-1705	371	20	could	could	AUX
cana-1705	371	21	not	not	PART
cana-1705	371	22	keep	keep	VERB
cana-1705	371	23	up	up	ADP
cana-1705	371	24	with	with	ADP
cana-1705	371	25	new	new	ADJ
cana-1705	371	26	real	real	ADJ
cana-1705	371	27	-	-	PUNCT
cana-1705	371	28	time	time	NOUN
cana-1705	371	29	readings	reading	NOUN
cana-1705	371	30	of	of	ADP
cana-1705	371	31	flows	flow	NOUN
cana-1705	371	32	that	that	PRON
cana-1705	371	33	change	change	VERB
cana-1705	371	34	over	over	ADP
cana-1705	371	35	seconds	second	NOUN
cana-1705	371	36	.	.	PUNCT
cana-1705	372	1	the	the	DET
cana-1705	372	2	robustness	robustness	NOUN
cana-1705	372	3	of	of	ADP
cana-1705	372	4	the	the	DET
cana-1705	372	5	lstm	lstm	PROPN
cana-1705	372	6	model	model	NOUN
cana-1705	372	7	to	to	PART
cana-1705	372	8	remember	remember	VERB
cana-1705	372	9	longterm	longterm	NOUN
cana-1705	372	10	dependencies	dependency	NOUN
cana-1705	372	11	has	have	AUX
cana-1705	372	12	made	make	VERB
cana-1705	372	13	it	it	PRON
cana-1705	372	14	a	a	DET
cana-1705	372	15	stronger	strong	ADJ
cana-1705	372	16	model	model	NOUN
cana-1705	372	17	for	for	ADP
cana-1705	372	18	traffic	traffic	NOUN
cana-1705	372	19	flow	flow	NOUN
cana-1705	372	20	prediction	prediction	NOUN
cana-1705	372	21	,	,	PUNCT
cana-1705	372	22	especially	especially	ADV
cana-1705	372	23	under	under	ADP
cana-1705	372	24	peak	peak	NOUN
cana-1705	372	25	hours	hour	NOUN
cana-1705	372	26	and	and	CCONJ
cana-1705	372	27	inclement	inclement	NOUN
cana-1705	372	28	weather	weather	NOUN
cana-1705	372	29	conditions	condition	NOUN
cana-1705	372	30	.	.	PUNCT
cana-1705	373	1	table	table	NOUN
cana-1705	373	2	8	8	NUM
cana-1705	373	3	:	:	PUNCT
cana-1705	373	4	performance	performance	NOUN
cana-1705	373	5	comparison	comparison	NOUN
cana-1705	373	6	in	in	ADP
cana-1705	373	7	different	different	ADJ
cana-1705	373	8	traffic	traffic	NOUN
cana-1705	373	9	scenarios	scenario	NOUN
cana-1705	373	10	scenario	scenario	VERB
cana-1705	373	11	lstm	lstm	PROPN
cana-1705	373	12	rmse	rmse	PROPN
cana-1705	373	13	arima	arima	PROPN
cana-1705	373	14	rmse	rmse	PROPN
cana-1705	373	15	svm	svm	PROPN
cana-1705	373	16	rmse	rmse	PROPN
cana-1705	373	17	normal	normal	ADJ
cana-1705	373	18	5.8	5.8	NUM
cana-1705	373	19	8.9	8.9	NUM
cana-1705	373	20	7.2	7.2	NUM
cana-1705	373	21	rush	rush	NOUN
cana-1705	373	22	hour	hour	NOUN
cana-1705	373	23	7.0	7.0	NUM
cana-1705	373	24	11.4	11.4	NUM
cana-1705	373	25	9.0	9.0	NUM
cana-1705	373	26	adverse	adverse	ADJ
cana-1705	373	27	weather	weather	NOUN
cana-1705	373	28	6.4	6.4	NUM
cana-1705	373	29	10.2	10.2	NUM
cana-1705	373	30	8.1	8.1	NUM
cana-1705	373	31	similarly	similarly	ADV
cana-1705	373	32	,	,	PUNCT
cana-1705	373	33	on	on	ADP
cana-1705	373	34	gps	gps	NOUN
cana-1705	373	35	-	-	PUNCT
cana-1705	373	36	enabled	enable	VERB
cana-1705	373	37	urban	urban	ADJ
cana-1705	373	38	dataset	dataset	NOUN
cana-1705	373	39	,	,	PUNCT
cana-1705	373	40	which	which	PRON
cana-1705	373	41	contained	contain	VERB
cana-1705	373	42	weather	weather	NOUN
cana-1705	373	43	and	and	CCONJ
cana-1705	373	44	traffic	traffic	NOUN
cana-1705	373	45	incidents	incident	NOUN
cana-1705	373	46	into	into	ADP
cana-1705	373	47	account	account	NOUN
cana-1705	373	48	,	,	PUNCT
cana-1705	373	49	the	the	DET
cana-1705	373	50	lstm	lstm	PROPN
cana-1705	373	51	model	model	NOUN
cana-1705	373	52	showed	show	VERB
cana-1705	373	53	high	high	ADJ
cana-1705	373	54	-	-	PUNCT
cana-1705	373	55	performance	performance	NOUN
cana-1705	373	56	compared	compare	VERB
cana-1705	373	57	to	to	ADP
cana-1705	373	58	the	the	DET
cana-1705	373	59	baselines	baseline	NOUN
cana-1705	373	60	.	.	PUNCT
cana-1705	374	1	the	the	DET
cana-1705	374	2	lstm	lstm	PROPN
cana-1705	374	3	model	model	NOUN
cana-1705	374	4	was	be	AUX
cana-1705	374	5	more	more	ADV
cana-1705	374	6	robust	robust	ADJ
cana-1705	374	7	than	than	ADP
cana-1705	374	8	the	the	DET
cana-1705	374	9	cnpm	cnpm	NOUN
cana-1705	374	10	,	,	PUNCT
cana-1705	374	11	specifically	specifically	ADV
cana-1705	374	12	under	under	ADP
cana-1705	374	13	adverse	adverse	ADJ
cana-1705	374	14	weather	weather	NOUN
cana-1705	374	15	conditions	condition	NOUN
cana-1705	374	16	(	(	PUNCT
cana-1705	374	17	e.g.	e.g.	ADV
cana-1705	374	18	,	,	PUNCT
cana-1705	374	19	high	high	ADJ
cana-1705	374	20	rainfall	rainfall	NOUN
cana-1705	374	21	)	)	PUNCT
cana-1705	374	22	due	due	ADP
cana-1705	374	23	to	to	ADP
cana-1705	374	24	it	it	PRON
cana-1705	374	25	included	include	VERB
cana-1705	374	26	a	a	DET
cana-1705	374	27	wider	wide	ADJ
cana-1705	374	28	range	range	NOUN
cana-1705	374	29	of	of	ADP
cana-1705	374	30	features	feature	NOUN
cana-1705	374	31	from	from	ADP
cana-1705	374	32	the	the	DET
cana-1705	374	33	weather	weather	NOUN
cana-1705	374	34	and	and	CCONJ
cana-1705	374	35	incidents	incident	NOUN
cana-1705	374	36	data	datum	NOUN
cana-1705	374	37	.	.	PUNCT
cana-1705	375	1	on	on	ADP
cana-1705	375	2	this	this	DET
cana-1705	375	3	dataset	dataset	NOUN
cana-1705	375	4	,	,	PUNCT
cana-1705	375	5	the	the	DET
cana-1705	375	6	rmse	rmse	NOUN
cana-1705	375	7	for	for	ADP
cana-1705	375	8	lstm	lstm	NOUN
cana-1705	375	9	was	be	AUX
cana-1705	375	10	5.90	5.90	NUM
cana-1705	375	11	,	,	PUNCT
cana-1705	375	12	whereas	whereas	SCONJ
cana-1705	375	13	it	it	PRON
cana-1705	375	14	was	be	AUX
cana-1705	375	15	9.21	9.21	NUM
cana-1705	375	16	for	for	ADP
cana-1705	375	17	arima	arima	NOUN
cana-1705	375	18	and	and	CCONJ
cana-1705	375	19	7.45	7.45	NUM
cana-1705	375	20	for	for	ADP
cana-1705	375	21	svm	svm	PROPN
cana-1705	375	22	.	.	PROPN
cana-1705	375	23	compared	compare	VERB
cana-1705	375	24	with	with	ADP
cana-1705	375	25	the	the	DET
cana-1705	375	26	baseline	baseline	NOUN
cana-1705	375	27	models	model	NOUN
cana-1705	375	28	the	the	DET
cana-1705	375	29	arima	arima	PROPN
cana-1705	375	30	model	model	NOUN
cana-1705	375	31	is	be	AUX
cana-1705	375	32	used	use	VERB
cana-1705	375	33	for	for	ADP
cana-1705	375	34	linear	linear	ADJ
cana-1705	375	35	time	time	NOUN
cana-1705	375	36	-	-	PUNCT
cana-1705	375	37	series	series	NOUN
cana-1705	375	38	data	datum	NOUN
cana-1705	375	39	,	,	PUNCT
cana-1705	375	40	which	which	PRON
cana-1705	375	41	was	be	AUX
cana-1705	375	42	not	not	PART
cana-1705	375	43	able	able	ADJ
cana-1705	375	44	to	to	PART
cana-1705	375	45	provide	provide	VERB
cana-1705	375	46	good	good	ADJ
cana-1705	375	47	performance	performance	NOUN
cana-1705	375	48	since	since	SCONJ
cana-1705	375	49	the	the	DET
cana-1705	375	50	relationships	relationship	NOUN
cana-1705	375	51	between	between	ADP
cana-1705	375	52	urban	urban	ADJ
cana-1705	375	53	traffic	traffic	NOUN
cana-1705	375	54	and	and	CCONJ
cana-1705	375	55	input	input	NOUN
cana-1705	375	56	sequence	sequence	NOUN
cana-1705	375	57	are	be	AUX
cana-1705	375	58	highly	highly	ADV
cana-1705	375	59	nonlinear	nonlinear	ADJ
cana-1705	375	60	.	.	PUNCT
cana-1705	376	1	its	its	PRON
cana-1705	376	2	performance	performance	NOUN
cana-1705	376	3	was	be	AUX
cana-1705	376	4	very	very	ADV
cana-1705	376	5	low	low	ADJ
cana-1705	376	6	,	,	PUNCT
cana-1705	376	7	especially	especially	ADV
cana-1705	376	8	when	when	SCONJ
cana-1705	376	9	it	it	PRON
cana-1705	376	10	experienced	experience	VERB
cana-1705	376	11	irregular	irregular	ADJ
cana-1705	376	12	traffics	traffic	NOUN
cana-1705	376	13	flow	flow	NOUN
cana-1705	376	14	(	(	PUNCT
cana-1705	376	15	like	like	ADP
cana-1705	376	16	an	an	DET
cana-1705	376	17	accident	accident	NOUN
cana-1705	376	18	)	)	PUNCT
cana-1705	376	19	or	or	CCONJ
cana-1705	376	20	a	a	DET
cana-1705	376	21	road	road	NOUN
cana-1705	376	22	we	we	PRON
cana-1705	376	23	never	never	ADV
cana-1705	376	24	have	have	AUX
cana-1705	376	25	seen	see	VERB
cana-1705	376	26	closed	closed	ADJ
cana-1705	376	27	.	.	PUNCT
cana-1705	377	1	this	this	PRON
cana-1705	377	2	can	can	AUX
cana-1705	377	3	be	be	AUX
cana-1705	377	4	seen	see	VERB
cana-1705	377	5	in	in	ADP
cana-1705	377	6	higher	high	ADJ
cana-1705	377	7	rmse	rmse	NOUN
cana-1705	377	8	scores	score	NOUN
cana-1705	377	9	especially	especially	ADV
cana-1705	377	10	during	during	ADP
cana-1705	377	11	the	the	DET
cana-1705	377	12	rush	rush	NOUN
cana-1705	377	13	hour	hour	NOUN
cana-1705	377	14	.	.	PUNCT
cana-1705	378	1	table	table	NOUN
cana-1705	378	2	9	9	NUM
cana-1705	378	3	:	:	PUNCT
cana-1705	378	4	runtime	runtime	NOUN
cana-1705	378	5	performance	performance	NOUN
cana-1705	378	6	comparison	comparison	NOUN
cana-1705	378	7	model	model	NOUN
cana-1705	378	8	prediction	prediction	NOUN
cana-1705	378	9	time	time	NOUN
cana-1705	378	10	(	(	PUNCT
cana-1705	378	11	ms	ms	NOUN
cana-1705	378	12	)	)	PUNCT
cana-1705	378	13	scalability	scalability	NOUN
cana-1705	378	14	lstm	lstm	NOUN
cana-1705	378	15	20	20	NUM
cana-1705	378	16	high	high	ADJ
cana-1705	378	17	arima	arima	PROPN
cana-1705	378	18	150	150	NUM
cana-1705	378	19	low	low	ADJ
cana-1705	378	20	svm	svm	PROPN
cana-1705	378	21	200	200	NUM
cana-1705	378	22	medium	medium	NOUN
cana-1705	378	23	the	the	DET
cana-1705	378	24	elastic	elastic	ADJ
cana-1705	378	25	svm	svm	NOUN
cana-1705	378	26	model	model	NOUN
cana-1705	378	27	can	can	AUX
cana-1705	378	28	not	not	PART
cana-1705	378	29	capture	capture	VERB
cana-1705	378	30	the	the	DET
cana-1705	378	31	temporal	temporal	ADJ
cana-1705	378	32	dependencies	dependency	NOUN
cana-1705	378	33	inherent	inherent	ADJ
cana-1705	378	34	in	in	ADP
cana-1705	378	35	traffic	traffic	NOUN
cana-1705	378	36	data	datum	NOUN
cana-1705	378	37	.	.	PUNCT
cana-1705	379	1	because	because	SCONJ
cana-1705	379	2	svm	svm	PROPN
cana-1705	379	3	does	do	AUX
cana-1705	379	4	not	not	PART
cana-1705	379	5	have	have	VERB
cana-1705	379	6	memory	memory	NOUN
cana-1705	379	7	functionality	functionality	NOUN
cana-1705	379	8	,	,	PUNCT
cana-1705	379	9	it	it	PRON
cana-1705	379	10	could	could	AUX
cana-1705	379	11	not	not	PART
cana-1705	379	12	utilize	utilize	VERB
cana-1705	379	13	information	information	NOUN
cana-1705	379	14	from	from	ADP
cana-1705	379	15	past	past	ADJ
cana-1705	379	16	traffic	traffic	NOUN
cana-1705	379	17	data	datum	NOUN
cana-1705	379	18	as	as	ADV
cana-1705	379	19	well	well	ADV
cana-1705	379	20	as	as	ADP
cana-1705	379	21	the	the	DET
cana-1705	379	22	lstm	lstm	PROPN
cana-1705	379	23	net	net	NOUN
cana-1705	379	24	.	.	PUNCT
cana-1705	380	1	communications	communication	NOUN
cana-1705	380	2	on	on	ADP
cana-1705	380	3	applied	apply	VERB
cana-1705	380	4	nonlinear	nonlinear	ADJ
cana-1705	380	5	analysis	analysis	NOUN
cana-1705	380	6	issn	issn	NOUN
cana-1705	380	7	:	:	PUNCT
cana-1705	380	8	1074	1074	NUM
cana-1705	380	9	-	-	PUNCT
cana-1705	380	10	133x	133x	NUM
cana-1705	380	11	vol	vol	NOUN
cana-1705	380	12	32	32	NUM
cana-1705	380	13	no	no	NOUN
cana-1705	380	14	.	.	NOUN
cana-1705	380	15	2	2	NUM
cana-1705	380	16	(	(	PUNCT
cana-1705	380	17	2025	2025	NUM
cana-1705	380	18	)	)	PUNCT
cana-1705	380	19	22	22	NUM
cana-1705	380	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	381	1	the	the	DET
cana-1705	381	2	model	model	NOUN
cana-1705	381	3	was	be	AUX
cana-1705	381	4	simply	simply	ADV
cana-1705	381	5	not	not	PART
cana-1705	381	6	able	able	ADJ
cana-1705	381	7	to	to	PART
cana-1705	381	8	look	look	VERB
cana-1705	381	9	in	in	ADP
cana-1705	381	10	the	the	DET
cana-1705	381	11	past	past	NOUN
cana-1705	381	12	(	(	PUNCT
cana-1705	381	13	we	we	PRON
cana-1705	381	14	can	can	AUX
cana-1705	381	15	call	call	VERB
cana-1705	381	16	this	this	PRON
cana-1705	381	17	also	also	ADV
cana-1705	381	18	handling	handle	VERB
cana-1705	381	19	temporal	temporal	ADJ
cana-1705	381	20	dependencies	dependency	NOUN
cana-1705	381	21	)	)	PUNCT
cana-1705	381	22	,	,	PUNCT
cana-1705	381	23	even	even	ADV
cana-1705	381	24	though	though	SCONJ
cana-1705	381	25	the	the	DET
cana-1705	381	26	mlp	mlp	NOUN
cana-1705	381	27	is	be	AUX
cana-1705	381	28	able	able	ADJ
cana-1705	381	29	to	to	PART
cana-1705	381	30	handle	handle	VERB
cana-1705	381	31	non	non	ADJ
cana-1705	381	32	-	-	ADJ
cana-1705	381	33	linearity	linearity	ADJ
cana-1705	381	34	.	.	PUNCT
cana-1705	382	1	although	although	SCONJ
cana-1705	382	2	it	it	PRON
cana-1705	382	3	outperformed	outperform	VERB
cana-1705	382	4	arima	arima	PROPN
cana-1705	382	5	,	,	PUNCT
cana-1705	382	6	yet	yet	CCONJ
cana-1705	382	7	this	this	DET
cana-1705	382	8	model	model	NOUN
cana-1705	382	9	was	be	AUX
cana-1705	382	10	not	not	PART
cana-1705	382	11	as	as	ADV
cana-1705	382	12	accurate	accurate	ADJ
cana-1705	382	13	as	as	ADP
cana-1705	382	14	the	the	DET
cana-1705	382	15	lstm	lstm	NOUN
cana-1705	382	16	model	model	NOUN
cana-1705	382	17	because	because	SCONJ
cana-1705	382	18	it	it	PRON
cana-1705	382	19	did	do	AUX
cana-1705	382	20	not	not	PART
cana-1705	382	21	feed	feed	VERB
cana-1705	382	22	its	its	PRON
cana-1705	382	23	own	own	ADJ
cana-1705	382	24	sequences	sequence	NOUN
cana-1705	382	25	back	back	ADP
cana-1705	382	26	.	.	PUNCT
cana-1705	383	1	real	real	ADJ
cana-1705	383	2	-	-	PUNCT
cana-1705	383	3	time	time	NOUN
cana-1705	383	4	applicability	applicability	NOUN
cana-1705	383	5	the	the	DET
cana-1705	383	6	deployment	deployment	NOUN
cana-1705	383	7	of	of	ADP
cana-1705	383	8	lstm	lstm	PROPN
cana-1705	383	9	model	model	NOUN
cana-1705	383	10	in	in	ADP
cana-1705	383	11	the	the	DET
cana-1705	383	12	real	real	ADJ
cana-1705	383	13	time	time	NOUN
cana-1705	383	14	traffic	traffic	NOUN
cana-1705	383	15	management	management	NOUN
cana-1705	383	16	system	system	NOUN
cana-1705	383	17	was	be	AUX
cana-1705	383	18	one	one	NUM
cana-1705	383	19	of	of	ADP
cana-1705	383	20	the	the	DET
cana-1705	383	21	prime	prime	ADJ
cana-1705	383	22	objectives	objective	NOUN
cana-1705	383	23	for	for	ADP
cana-1705	383	24	this	this	DET
cana-1705	383	25	research	research	NOUN
cana-1705	383	26	.	.	PUNCT
cana-1705	384	1	for	for	ADP
cana-1705	384	2	this	this	PRON
cana-1705	384	3	,	,	PUNCT
cana-1705	384	4	we	we	PRON
cana-1705	384	5	analyzed	analyze	VERB
cana-1705	384	6	the	the	DET
cana-1705	384	7	prediction	prediction	NOUN
cana-1705	384	8	speed	speed	NOUN
cana-1705	384	9	(	(	PUNCT
cana-1705	384	10	i.e.	i.e.	X
cana-1705	384	11	runtime	runtime	NOUN
cana-1705	384	12	performance	performance	NOUN
cana-1705	384	13	)	)	PUNCT
cana-1705	384	14	of	of	ADP
cana-1705	384	15	the	the	DET
cana-1705	384	16	models	model	NOUN
cana-1705	384	17	.	.	PUNCT
cana-1705	385	1	the	the	DET
cana-1705	385	2	lstm	lstm	PROPN
cana-1705	385	3	model	model	NOUN
cana-1705	385	4	produced	produce	VERB
cana-1705	385	5	predictions	prediction	NOUN
cana-1705	385	6	in	in	ADP
cana-1705	385	7	milliseconds	millisecond	NOUN
cana-1705	385	8	,	,	PUNCT
cana-1705	385	9	applicable	applicable	ADJ
cana-1705	385	10	for	for	ADP
cana-1705	385	11	real	real	ADJ
cana-1705	385	12	-	-	PUNCT
cana-1705	385	13	time	time	NOUN
cana-1705	385	14	scenarios	scenario	NOUN
cana-1705	385	15	including	include	VERB
cana-1705	385	16	dynamic	dynamic	ADJ
cana-1705	385	17	traffic	traffic	NOUN
cana-1705	385	18	signal	signal	NOUN
cana-1705	385	19	control	control	NOUN
cana-1705	385	20	and	and	CCONJ
cana-1705	385	21	route	route	NOUN
cana-1705	385	22	optimization	optimization	NOUN
cana-1705	385	23	.	.	PUNCT
cana-1705	386	1	table	table	NOUN
cana-1705	386	2	10	10	NUM
cana-1705	386	3	:	:	PUNCT
cana-1705	386	4	impact	impact	NOUN
cana-1705	386	5	of	of	ADP
cana-1705	386	6	weather	weather	NOUN
cana-1705	386	7	and	and	CCONJ
cana-1705	386	8	incidents	incident	NOUN
cana-1705	386	9	on	on	ADP
cana-1705	386	10	traffic	traffic	NOUN
cana-1705	386	11	flow	flow	NOUN
cana-1705	386	12	prediction	prediction	NOUN
cana-1705	386	13	model	model	NOUN
cana-1705	386	14	normal	normal	ADJ
cana-1705	386	15	weather	weather	NOUN
cana-1705	386	16	rmse	rmse	PROPN
cana-1705	386	17	rainy	rainy	ADJ
cana-1705	386	18	weather	weather	PROPN
cana-1705	386	19	rmse	rmse	PROPN
cana-1705	386	20	incident	incident	PROPN
cana-1705	386	21	rmse	rmse	PROPN
cana-1705	386	22	lstm	lstm	VERB
cana-1705	386	23	5.9	5.9	NUM
cana-1705	386	24	6.3	6.3	NUM
cana-1705	386	25	6.5	6.5	NUM
cana-1705	386	26	arima	arima	NOUN
cana-1705	386	27	9.1	9.1	NUM
cana-1705	386	28	11.5	11.5	NUM
cana-1705	386	29	12.1	12.1	NUM
cana-1705	386	30	svm	svm	NOUN
cana-1705	386	31	7.0	7.0	NUM
cana-1705	386	32	8.2	8.2	NUM
cana-1705	386	33	9.0	9.0	NUM
cana-1705	386	34	in	in	ADP
cana-1705	386	35	contrast	contrast	NOUN
cana-1705	386	36	,	,	PUNCT
cana-1705	386	37	the	the	DET
cana-1705	386	38	arima	arima	PROPN
cana-1705	386	39	model	model	NOUN
cana-1705	386	40	took	take	VERB
cana-1705	386	41	longer	long	ADV
cana-1705	386	42	because	because	SCONJ
cana-1705	386	43	estimates	estimate	NOUN
cana-1705	386	44	about	about	ADP
cana-1705	386	45	parameters	parameter	NOUN
cana-1705	386	46	and	and	CCONJ
cana-1705	386	47	their	their	PRON
cana-1705	386	48	confidence	confidence	NOUN
cana-1705	386	49	intervals	interval	NOUN
cana-1705	386	50	were	be	AUX
cana-1705	386	51	required	require	VERB
cana-1705	386	52	up	up	ADP
cana-1705	386	53	front	front	NOUN
cana-1705	386	54	(	(	PUNCT
cana-1705	386	55	and	and	CCONJ
cana-1705	386	56	also	also	ADV
cana-1705	386	57	every	every	DET
cana-1705	386	58	time	time	NOUN
cana-1705	386	59	new	new	ADJ
cana-1705	386	60	data	datum	NOUN
cana-1705	386	61	was	be	AUX
cana-1705	386	62	collected	collect	VERB
cana-1705	386	63	—	—	PUNCT
cana-1705	386	64	when	when	SCONJ
cana-1705	386	65	updating	update	VERB
cana-1705	386	66	the	the	DET
cana-1705	386	67	model	model	NOUN
cana-1705	386	68	…	…	PUNCT
cana-1705	386	69	as	as	SCONJ
cana-1705	386	70	in	in	ADP
cana-1705	386	71	those	those	PRON
cana-1705	386	72	are	be	AUX
cana-1705	386	73	online	online	ADJ
cana-1705	386	74	learning	learn	VERB
cana-1705	386	75	algorithms	algorithm	NOUN
cana-1705	386	76	!	!	PUNCT
cana-1705	387	1	the	the	DET
cana-1705	387	2	svm	svm	PROPN
cana-1705	387	3	model	model	NOUN
cana-1705	387	4	was	be	AUX
cana-1705	387	5	also	also	ADV
cana-1705	387	6	computational	computational	ADJ
cana-1705	387	7	expensive	expensive	ADJ
cana-1705	387	8	to	to	PART
cana-1705	387	9	evaluate	evaluate	VERB
cana-1705	387	10	due	due	ADP
cana-1705	387	11	to	to	ADP
cana-1705	387	12	the	the	DET
cana-1705	387	13	5000	5000	NUM
cana-1705	387	14	kernel	kernel	NOUN
cana-1705	387	15	evaluations	evaluation	NOUN
cana-1705	387	16	required	require	VERB
cana-1705	387	17	at	at	ADP
cana-1705	387	18	every	every	DET
cana-1705	387	19	time	time	NOUN
cana-1705	387	20	step	step	NOUN
cana-1705	387	21	.	.	PUNCT
cana-1705	388	1	on	on	ADP
cana-1705	388	2	the	the	DET
cana-1705	388	3	contrary	contrary	NOUN
cana-1705	388	4	,	,	PUNCT
cana-1705	388	5	lstm	lstm	ADJ
cana-1705	388	6	model	model	NOUN
cana-1705	388	7	took	take	VERB
cana-1705	388	8	only	only	ADV
cana-1705	388	9	less	less	ADJ
cana-1705	388	10	time	time	NOUN
cana-1705	388	11	as	as	ADP
cana-1705	388	12	becouse	becouse	ADJ
cana-1705	388	13	it	it	PRON
cana-1705	388	14	had	have	VERB
cana-1705	388	15	a	a	DET
cana-1705	388	16	well	well	ADV
cana-1705	388	17	-	-	PUNCT
cana-1705	388	18	built	build	VERB
cana-1705	388	19	network	network	NOUN
cana-1705	388	20	so	so	SCONJ
cana-1705	388	21	which	which	PRON
cana-1705	388	22	took	take	VERB
cana-1705	388	23	time	time	NOUN
cana-1705	388	24	to	to	PART
cana-1705	388	25	build	build	VERB
cana-1705	388	26	and	and	CCONJ
cana-1705	388	27	once	once	SCONJ
cana-1705	388	28	it	it	PRON
cana-1705	388	29	has	have	AUX
cana-1705	388	30	been	be	AUX
cana-1705	388	31	trained	train	VERB
cana-1705	388	32	is	be	AUX
cana-1705	388	33	very	very	ADV
cana-1705	388	34	faster	fast	ADV
cana-1705	388	35	in	in	ADP
cana-1705	388	36	giving	give	VERB
cana-1705	388	37	outputs	output	NOUN
cana-1705	388	38	and	and	CCONJ
cana-1705	388	39	towards	towards	ADP
cana-1705	388	40	by	by	ADP
cana-1705	388	41	proving	prove	VERB
cana-1705	388	42	that	that	SCONJ
cana-1705	388	43	it	it	PRON
cana-1705	388	44	has	have	VERB
cana-1705	388	45	efficient	efficient	ADJ
cana-1705	388	46	network	network	NOUN
cana-1705	388	47	.	.	PUNCT
cana-1705	389	1	table	table	NOUN
cana-1705	389	2	11	11	NUM
cana-1705	389	3	:	:	PUNCT
cana-1705	389	4	hyperparameter	hyperparameter	NOUN
cana-1705	389	5	tuning	tune	VERB
cana-1705	389	6	results	result	NOUN
cana-1705	389	7	for	for	ADP
cana-1705	389	8	lstm	lstm	NOUN
cana-1705	389	9	model	model	NOUN
cana-1705	389	10	no	no	INTJ
cana-1705	389	11	.	.	PROPN
cana-1705	389	12	of	of	ADP
cana-1705	389	13	layers	layer	NOUN
cana-1705	389	14	memory	memory	NOUN
cana-1705	389	15	units	unit	NOUN
cana-1705	389	16	per	per	ADP
cana-1705	389	17	layer	layer	NOUN
cana-1705	389	18	dropout	dropout	NOUN
cana-1705	389	19	rate	rate	NOUN
cana-1705	389	20	batch	batch	NOUN
cana-1705	389	21	size	size	NOUN
cana-1705	389	22	learning	learn	VERB
cana-1705	389	23	rate	rate	NOUN
cana-1705	389	24	validation	validation	NOUN
cana-1705	389	25	loss	loss	NOUN
cana-1705	389	26	2	2	NUM
cana-1705	389	27	64	64	NUM
cana-1705	389	28	0.1	0.1	NUM
cana-1705	389	29	32	32	NUM
cana-1705	389	30	0.0010	0.0010	NUM
cana-1705	389	31	0.45	0.45	NUM
cana-1705	389	32	3	3	NUM
cana-1705	389	33	128	128	NUM
cana-1705	389	34	0.2	0.2	NUM
cana-1705	389	35	64	64	NUM
cana-1705	389	36	0.0005	0.0005	NUM
cana-1705	389	37	0.42	0.42	NUM
cana-1705	389	38	4	4	NUM
cana-1705	389	39	256	256	NUM
cana-1705	389	40	0.3	0.3	NUM
cana-1705	389	41	128	128	NUM
cana-1705	389	42	0.0001	0.0001	NUM
cana-1705	389	43	0.48	0.48	NUM
cana-1705	389	44	experiments	experiment	NOUN
cana-1705	389	45	results	result	NOUN
cana-1705	389	46	confirm	confirm	VERB
cana-1705	389	47	that	that	SCONJ
cana-1705	389	48	lstm	lstm	NOUN
cana-1705	389	49	could	could	AUX
cana-1705	389	50	predict	predict	VERB
cana-1705	389	51	traffic	traffic	NOUN
cana-1705	389	52	flow	flow	NOUN
cana-1705	389	53	in	in	ADP
cana-1705	389	54	real	real	ADJ
cana-1705	389	55	-	-	PUNCT
cana-1705	389	56	time	time	NOUN
cana-1705	389	57	well	well	ADV
cana-1705	389	58	.	.	PUNCT
cana-1705	390	1	because	because	SCONJ
cana-1705	390	2	of	of	ADP
cana-1705	390	3	the	the	DET
cana-1705	390	4	flexibility	flexibility	NOUN
cana-1705	390	5	for	for	ADP
cana-1705	390	6	this	this	DET
cana-1705	390	7	model	model	NOUN
cana-1705	390	8	to	to	PART
cana-1705	390	9	capture	capture	VERB
cana-1705	390	10	both	both	DET
cana-1705	390	11	short	short	ADJ
cana-1705	390	12	-	-	PUNCT
cana-1705	390	13	term	term	NOUN
cana-1705	390	14	and	and	CCONJ
cana-1705	390	15	long	long	ADJ
cana-1705	390	16	-	-	PUNCT
cana-1705	390	17	term	term	NOUN
cana-1705	390	18	dependencies	dependency	NOUN
cana-1705	390	19	in	in	ADP
cana-1705	390	20	traffic	traffic	NOUN
cana-1705	390	21	data	datum	NOUN
cana-1705	390	22	,	,	PUNCT
cana-1705	390	23	it	it	PRON
cana-1705	390	24	has	have	AUX
cana-1705	390	25	outperformed	outperform	VERB
cana-1705	390	26	some	some	DET
cana-1705	390	27	traditional	traditional	ADJ
cana-1705	390	28	statistical	statistical	ADJ
cana-1705	390	29	time	time	NOUN
cana-1705	390	30	series	series	NOUN
cana-1705	390	31	models	model	NOUN
cana-1705	390	32	like	like	ADP
cana-1705	390	33	arima	arima	NOUN
cana-1705	390	34	and	and	CCONJ
cana-1705	390	35	svm	svm	PROPN
cana-1705	390	36	especially	especially	ADV
cana-1705	390	37	during	during	ADP
cana-1705	390	38	rush	rush	NOUN
cana-1705	390	39	hours	hour	NOUN
cana-1705	390	40	or	or	CCONJ
cana-1705	390	41	under	under	ADP
cana-1705	390	42	poor	poor	ADJ
cana-1705	390	43	weather	weather	NOUN
cana-1705	390	44	conditions	condition	NOUN
cana-1705	390	45	in	in	ADP
cana-1705	390	46	our	our	PRON
cana-1705	390	47	experiment	experiment	NOUN
cana-1705	390	48	.	.	PUNCT
cana-1705	391	1	in	in	ADP
cana-1705	391	2	addition	addition	NOUN
cana-1705	391	3	,	,	PUNCT
cana-1705	391	4	the	the	DET
cana-1705	391	5	integration	integration	NOUN
cana-1705	391	6	of	of	ADP
cana-1705	391	7	extraneous	extraneous	ADJ
cana-1705	391	8	conditions	condition	NOUN
cana-1705	391	9	like	like	ADP
cana-1705	391	10	weather	weather	NOUN
cana-1705	391	11	and	and	CCONJ
cana-1705	391	12	incidents	incident	NOUN
cana-1705	391	13	in	in	ADP
cana-1705	391	14	turn	turn	NOUN
cana-1705	391	15	improved	improve	VERB
cana-1705	391	16	the	the	DET
cana-1705	391	17	model	model	NOUN
cana-1705	391	18	’s	’s	PART
cana-1705	391	19	predictive	predictive	ADJ
cana-1705	391	20	precision	precision	NOUN
cana-1705	391	21	rendering	render	VERB
cana-1705	391	22	it	it	PRON
cana-1705	391	23	applicable	applicable	ADJ
cana-1705	391	24	to	to	ADP
cana-1705	391	25	real	real	ADJ
cana-1705	391	26	-	-	PUNCT
cana-1705	391	27	world	world	NOUN
cana-1705	391	28	scenarios	scenario	NOUN
cana-1705	391	29	.	.	PUNCT
cana-1705	392	1	the	the	DET
cana-1705	392	2	runtime	runtime	NOUN
cana-1705	392	3	performance	performance	NOUN
cana-1705	392	4	of	of	ADP
cana-1705	392	5	our	our	PRON
cana-1705	392	6	lstm	lstm	NOUN
cana-1705	392	7	model	model	NOUN
cana-1705	392	8	further	far	ADV
cana-1705	392	9	suggests	suggest	VERB
cana-1705	392	10	that	that	SCONJ
cana-1705	392	11	it	it	PRON
cana-1705	392	12	could	could	AUX
cana-1705	392	13	be	be	AUX
cana-1705	392	14	deployed	deploy	VERB
cana-1705	392	15	in	in	ADP
cana-1705	392	16	real	real	ADJ
cana-1705	392	17	-	-	PUNCT
cana-1705	392	18	time	time	NOUN
cana-1705	392	19	traffic	traffic	NOUN
cana-1705	392	20	management	management	NOUN
cana-1705	392	21	systems	system	NOUN
cana-1705	392	22	.	.	PUNCT
cana-1705	393	1	this	this	DET
cana-1705	393	2	way	way	NOUN
cana-1705	393	3	,	,	PUNCT
cana-1705	393	4	the	the	DET
cana-1705	393	5	model	model	NOUN
cana-1705	393	6	can	can	AUX
cana-1705	393	7	be	be	AUX
cana-1705	393	8	connected	connect	VERB
cana-1705	393	9	to	to	ADP
cana-1705	393	10	other	other	ADJ
cana-1705	393	11	traffic	traffic	NOUN
cana-1705	393	12	control	control	NOUN
cana-1705	393	13	systems	system	NOUN
cana-1705	393	14	and	and	CCONJ
cana-1705	393	15	can	can	AUX
cana-1705	393	16	help	help	VERB
cana-1705	393	17	optimize	optimize	VERB
cana-1705	393	18	traffic	traffic	NOUN
cana-1705	393	19	signals	signal	NOUN
cana-1705	393	20	according	accord	VERB
cana-1705	393	21	to	to	ADP
cana-1705	393	22	the	the	DET
cana-1705	393	23	drive	drive	ADJ
cana-1705	393	24	predictions	prediction	NOUN
cana-1705	393	25	it	it	PRON
cana-1705	393	26	generates	generate	VERB
cana-1705	393	27	;	;	PUNCT
cana-1705	393	28	divert	divert	NOUN
cana-1705	393	29	vehicles	vehicle	NOUN
cana-1705	393	30	and	and	CCONJ
cana-1705	393	31	notify	notify	VERB
cana-1705	393	32	motorists	motorist	NOUN
cana-1705	393	33	in	in	ADP
cana-1705	393	34	real	real	ADJ
cana-1705	393	35	-	-	PUNCT
cana-1705	393	36	time	time	NOUN
cana-1705	393	37	.	.	PUNCT
cana-1705	394	1	communications	communication	NOUN
cana-1705	394	2	on	on	ADP
cana-1705	394	3	applied	apply	VERB
cana-1705	394	4	nonlinear	nonlinear	ADJ
cana-1705	394	5	analysis	analysis	NOUN
cana-1705	394	6	issn	issn	NOUN
cana-1705	394	7	:	:	PUNCT
cana-1705	394	8	1074	1074	NUM
cana-1705	394	9	-	-	PUNCT
cana-1705	394	10	133x	133x	NUM
cana-1705	394	11	vol	vol	NOUN
cana-1705	394	12	32	32	NUM
cana-1705	394	13	no	no	NOUN
cana-1705	394	14	.	.	NOUN
cana-1705	394	15	2	2	NUM
cana-1705	394	16	(	(	PUNCT
cana-1705	394	17	2025	2025	NUM
cana-1705	394	18	)	)	PUNCT
cana-1705	395	1	23	23	NUM
cana-1705	395	2	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	395	3	table	table	NOUN
cana-1705	395	4	12	12	NUM
cana-1705	395	5	:	:	PUNCT
cana-1705	395	6	real	real	ADJ
cana-1705	395	7	-	-	PUNCT
cana-1705	395	8	time	time	NOUN
cana-1705	395	9	applicability	applicability	NOUN
cana-1705	395	10	for	for	ADP
cana-1705	395	11	traffic	traffic	NOUN
cana-1705	395	12	management	management	NOUN
cana-1705	395	13	model	model	NOUN
cana-1705	395	14	prediction	prediction	NOUN
cana-1705	395	15	time	time	NOUN
cana-1705	395	16	(	(	PUNCT
cana-1705	395	17	ms	ms	NOUN
cana-1705	395	18	)	)	PUNCT
cana-1705	395	19	real	real	ADJ
cana-1705	395	20	-	-	PUNCT
cana-1705	395	21	time	time	NOUN
cana-1705	395	22	feasibility	feasibility	NOUN
cana-1705	395	23	lstm	lstm	NOUN
cana-1705	395	24	15	15	NUM
cana-1705	395	25	yes	yes	INTJ
cana-1705	395	26	arima	arima	PROPN
cana-1705	395	27	100	100	NUM
cana-1705	395	28	no	no	DET
cana-1705	395	29	svm	svm	NOUN
cana-1705	395	30	150	150	NUM
cana-1705	395	31	no	no	DET
cana-1705	395	32	overall	overall	ADJ
cana-1705	395	33	,	,	PUNCT
cana-1705	395	34	the	the	DET
cana-1705	395	35	experimental	experimental	ADJ
cana-1705	395	36	results	result	NOUN
cana-1705	395	37	further	far	ADV
cana-1705	395	38	substantiate	substantiate	VERB
cana-1705	395	39	that	that	SCONJ
cana-1705	395	40	quantitatively	quantitatively	ADV
cana-1705	395	41	simulating	simulate	VERB
cana-1705	395	42	the	the	DET
cana-1705	395	43	urban	urban	ADJ
cana-1705	395	44	traffic	traffic	NOUN
cana-1705	395	45	characteristics	characteristic	NOUN
cana-1705	395	46	is	be	AUX
cana-1705	395	47	feasible	feasible	ADJ
cana-1705	395	48	by	by	ADP
cana-1705	395	49	learning	learn	VERB
cana-1705	395	50	the	the	DET
cana-1705	395	51	prior	prior	ADJ
cana-1705	395	52	knowledge	knowledge	NOUN
cana-1705	395	53	of	of	ADP
cana-1705	395	54	lstm	lstm	NOUN
cana-1705	395	55	-	-	PUNCT
cana-1705	395	56	based	base	VERB
cana-1705	395	57	traffic	traffic	NOUN
cana-1705	395	58	flow	flow	NOUN
cana-1705	395	59	prediction	prediction	NOUN
cana-1705	395	60	.	.	PUNCT
cana-1705	396	1	the	the	DET
cana-1705	396	2	superior	superior	ADJ
cana-1705	396	3	performance	performance	NOUN
cana-1705	396	4	of	of	ADP
cana-1705	396	5	the	the	DET
cana-1705	396	6	model	model	NOUN
cana-1705	396	7	to	to	ADP
cana-1705	396	8	traditional	traditional	ADJ
cana-1705	396	9	methods	method	NOUN
cana-1705	396	10	such	such	ADJ
cana-1705	396	11	as	as	ADP
cana-1705	396	12	arima	arima	NOUN
cana-1705	396	13	and	and	CCONJ
cana-1705	396	14	svm	svm	PROPN
cana-1705	396	15	show	show	VERB
cana-1705	396	16	the	the	DET
cana-1705	396	17	necessity	necessity	NOUN
cana-1705	396	18	of	of	ADP
cana-1705	396	19	combining	combine	VERB
cana-1705	396	20	deep	deep	ADJ
cana-1705	396	21	learning	learning	NOUN
cana-1705	396	22	algorithms	algorithm	NOUN
cana-1705	396	23	into	into	ADP
cana-1705	396	24	real	real	ADJ
cana-1705	396	25	-	-	PUNCT
cana-1705	396	26	time	time	NOUN
cana-1705	396	27	traffic	traffic	NOUN
cana-1705	396	28	management	management	NOUN
cana-1705	396	29	.	.	PUNCT
cana-1705	397	1	by	by	ADP
cana-1705	397	2	incorporating	incorporate	VERB
cana-1705	397	3	external	external	ADJ
cana-1705	397	4	data	datum	NOUN
cana-1705	397	5	sources	source	NOUN
cana-1705	397	6	(	(	PUNCT
cana-1705	397	7	e.g.	e.g.	ADV
cana-1705	397	8	weather	weather	NOUN
cana-1705	397	9	and	and	CCONJ
cana-1705	397	10	incident	incident	NOUN
cana-1705	397	11	reports	report	NOUN
cana-1705	397	12	)	)	PUNCT
cana-1705	397	13	and	and	CCONJ
cana-1705	397	14	achieving	achieve	VERB
cana-1705	397	15	high	high	ADJ
cana-1705	397	16	model	model	NOUN
cana-1705	397	17	performance	performance	NOUN
cana-1705	397	18	,	,	PUNCT
cana-1705	397	19	this	this	PRON
cana-1705	397	20	shows	show	VERB
cana-1705	397	21	the	the	DET
cana-1705	397	22	bridge	bridge	NOUN
cana-1705	397	23	of	of	ADP
cana-1705	397	24	our	our	PRON
cana-1705	397	25	models	model	NOUN
cana-1705	397	26	with	with	ADP
cana-1705	397	27	non	non	ADJ
cana-1705	397	28	-	-	ADJ
cana-1705	397	29	standard	standard	ADJ
cana-1705	397	30	target	target	NOUN
cana-1705	397	31	variable	variable	NOUN
cana-1705	397	32	demonstrates	demonstrate	VERB
cana-1705	397	33	a	a	DET
cana-1705	397	34	potential	potential	ADJ
cana-1705	397	35	pathway	pathway	NOUN
cana-1705	397	36	to	to	ADP
cana-1705	397	37	using	use	VERB
cana-1705	397	38	these	these	DET
cana-1705	397	39	models	model	NOUN
cana-1705	397	40	as	as	ADP
cana-1705	397	41	an	an	DET
cana-1705	397	42	optimization	optimization	NOUN
cana-1705	397	43	for	for	ADP
cana-1705	397	44	urban	urban	ADJ
cana-1705	397	45	mobility	mobility	NOUN
cana-1705	397	46	landscape	landscape	NOUN
cana-1705	397	47	.	.	PUNCT
cana-1705	398	1	5	5	X
cana-1705	398	2	.	.	X
cana-1705	398	3	conclusion	conclusion	NOUN
cana-1705	398	4	a	a	DET
cana-1705	398	5	fundamental	fundamental	ADJ
cana-1705	398	6	part	part	NOUN
cana-1705	398	7	of	of	ADP
cana-1705	398	8	urban	urban	ADJ
cana-1705	398	9	mobility	mobility	NOUN
cana-1705	398	10	is	be	AUX
cana-1705	398	11	the	the	DET
cana-1705	398	12	network	network	NOUN
cana-1705	398	13	to	to	PART
cana-1705	398	14	move	move	VERB
cana-1705	398	15	all	all	DET
cana-1705	398	16	city	city	NOUN
cana-1705	398	17	users	user	NOUN
cana-1705	398	18	(	(	PUNCT
cana-1705	398	19	citizens	citizen	NOUN
cana-1705	398	20	and	and	CCONJ
cana-1705	398	21	freight	freight	NOUN
cana-1705	398	22	)	)	PUNCT
cana-1705	398	23	through	through	ADP
cana-1705	398	24	the	the	DET
cana-1705	398	25	cities	city	NOUN
cana-1705	398	26	,	,	PUNCT
cana-1705	398	27	called	call	VERB
cana-1705	398	28	"	"	PUNCT
cana-1705	398	29	urban	urban	ADJ
cana-1705	398	30	transportation	transportation	NOUN
cana-1705	398	31	network	network	NOUN
cana-1705	398	32	"	"	PUNCT
cana-1705	398	33	.	.	PUNCT
cana-1705	399	1	traffic	traffic	NOUN
cana-1705	399	2	congestion	congestion	NOUN
cana-1705	399	3	was	be	AUX
cana-1705	399	4	one	one	NUM
cana-1705	399	5	of	of	ADP
cana-1705	399	6	the	the	DET
cana-1705	399	7	biggest	big	ADJ
cana-1705	399	8	problems	problem	NOUN
cana-1705	399	9	for	for	ADP
cana-1705	399	10	urban	urban	ADJ
cana-1705	399	11	areas	area	NOUN
cana-1705	399	12	and	and	CCONJ
cana-1705	399	13	has	have	VERB
cana-1705	399	14	destructive	destructive	ADJ
cana-1705	399	15	effect	effect	NOUN
cana-1705	399	16	on	on	ADP
cana-1705	399	17	economic	economic	ADJ
cana-1705	399	18	efficiency	efficiency	NOUN
cana-1705	399	19	,	,	PUNCT
cana-1705	399	20	environmental	environmental	ADJ
cana-1705	399	21	sustainability	sustainability	NOUN
cana-1705	399	22	and	and	CCONJ
cana-1705	399	23	life	life	NOUN
cana-1705	399	24	quality	quality	NOUN
cana-1705	399	25	.	.	PUNCT
cana-1705	400	1	here	here	ADV
cana-1705	400	2	,	,	PUNCT
cana-1705	400	3	real	real	ADJ
cana-1705	400	4	-	-	PUNCT
cana-1705	400	5	time	time	NOUN
cana-1705	400	6	and	and	CCONJ
cana-1705	400	7	accurate	accurate	ADJ
cana-1705	400	8	traffic	traffic	NOUN
cana-1705	400	9	flow	flow	NOUN
cana-1705	400	10	prediction	prediction	NOUN
cana-1705	400	11	is	be	AUX
cana-1705	400	12	critical	critical	ADJ
cana-1705	400	13	for	for	ADP
cana-1705	400	14	transportation	transportation	NOUN
cana-1705	400	15	system	system	NOUN
cana-1705	400	16	optimization	optimization	NOUN
cana-1705	400	17	,	,	PUNCT
cana-1705	400	18	congestion	congestion	NOUN
cana-1705	400	19	mitigation	mitigation	NOUN
cana-1705	400	20	and	and	CCONJ
cana-1705	400	21	urban	urban	ADJ
cana-1705	400	22	mobility	mobility	NOUN
cana-1705	400	23	enhancement	enhancement	NOUN
cana-1705	400	24	.	.	PUNCT
cana-1705	401	1	in	in	ADP
cana-1705	401	2	this	this	DET
cana-1705	401	3	paper	paper	NOUN
cana-1705	401	4	,	,	PUNCT
cana-1705	401	5	we	we	PRON
cana-1705	401	6	proposed	propose	VERB
cana-1705	401	7	to	to	PART
cana-1705	401	8	develop	develop	VERB
cana-1705	401	9	a	a	DET
cana-1705	401	10	real	real	ADJ
cana-1705	401	11	-	-	PUNCT
cana-1705	401	12	time	time	NOUN
cana-1705	401	13	traffic	traffic	NOUN
cana-1705	401	14	flow	flow	NOUN
cana-1705	401	15	prediction	prediction	NOUN
cana-1705	401	16	system	system	NOUN
cana-1705	401	17	using	use	VERB
cana-1705	401	18	long	long	ADJ
cana-1705	401	19	short	short	ADJ
cana-1705	401	20	-	-	PUNCT
cana-1705	401	21	term	term	NOUN
cana-1705	401	22	memory	memory	NOUN
cana-1705	401	23	(	(	PUNCT
cana-1705	401	24	lstm	lstm	NOUN
cana-1705	401	25	)	)	PUNCT
cana-1705	401	26	,	,	PUNCT
cana-1705	401	27	which	which	PRON
cana-1705	401	28	will	will	AUX
cana-1705	401	29	address	address	VERB
cana-1705	401	30	the	the	DET
cana-1705	401	31	challenges	challenge	NOUN
cana-1705	401	32	faced	face	VERB
cana-1705	401	33	by	by	ADP
cana-1705	401	34	various	various	ADJ
cana-1705	401	35	urban	urban	ADJ
cana-1705	401	36	mobility	mobility	NOUN
cana-1705	401	37	solutions	solution	NOUN
cana-1705	401	38	.	.	PUNCT
cana-1705	402	1	using	use	VERB
cana-1705	402	2	deep	deep	ADJ
cana-1705	402	3	learning	learning	NOUN
cana-1705	402	4	voice	voice	NOUN
cana-1705	402	5	,	,	PUNCT
cana-1705	402	6	lstm	lstm	NOUN
cana-1705	402	7	network	network	NOUN
cana-1705	402	8	,	,	PUNCT
cana-1705	402	9	this	this	DET
cana-1705	402	10	study	study	NOUN
cana-1705	402	11	brings	bring	VERB
cana-1705	402	12	a	a	DET
cana-1705	402	13	method	method	NOUN
cana-1705	402	14	than	than	SCONJ
cana-1705	402	15	can	can	AUX
cana-1705	402	16	perform	perform	VERB
cana-1705	402	17	traditional	traditional	ADJ
cana-1705	402	18	shortterm	shortterm	NOUN
cana-1705	402	19	traffic	traffic	NOUN
cana-1705	402	20	prediction	prediction	NOUN
cana-1705	402	21	model	model	NOUN
cana-1705	402	22	and	and	CCONJ
cana-1705	402	23	establish	establish	VERB
cana-1705	402	24	in	in	ADP
cana-1705	402	25	real	real	ADJ
cana-1705	402	26	world	world	NOUN
cana-1705	402	27	urban	urban	ADJ
cana-1705	402	28	area	area	NOUN
cana-1705	402	29	wide	wide	ADJ
cana-1705	402	30	range	range	NOUN
cana-1705	402	31	traffic	traffic	NOUN
cana-1705	402	32	management	management	NOUN
cana-1705	402	33	offering	offer	VERB
cana-1705	402	34	more	more	ADV
cana-1705	402	35	reliable	reliable	ADJ
cana-1705	402	36	accuracy	accuracy	NOUN
cana-1705	402	37	and	and	CCONJ
cana-1705	402	38	energy	energy	NOUN
cana-1705	402	39	efficiency	efficiency	NOUN
cana-1705	402	40	solution	solution	NOUN
cana-1705	402	41	.	.	PUNCT
cana-1705	403	1	first	first	ADV
cana-1705	403	2	of	of	ADP
cana-1705	403	3	all	all	PRON
cana-1705	403	4	,	,	PUNCT
cana-1705	403	5	as	as	SCONJ
cana-1705	403	6	shown	show	VERB
cana-1705	403	7	in	in	ADP
cana-1705	403	8	our	our	PRON
cana-1705	403	9	experiments	experiment	NOUN
cana-1705	403	10	,	,	PUNCT
cana-1705	403	11	the	the	DET
cana-1705	403	12	strength	strength	NOUN
cana-1705	403	13	of	of	ADP
cana-1705	403	14	lstm	lstm	PROPN
cana-1705	403	15	model	model	NOUN
cana-1705	403	16	is	be	AUX
cana-1705	403	17	to	to	PART
cana-1705	403	18	capture	capture	VERB
cana-1705	403	19	short	short	ADJ
cana-1705	403	20	-	-	PUNCT
cana-1705	403	21	term	term	NOUN
cana-1705	403	22	and	and	CCONJ
cana-1705	403	23	long	long	ADJ
cana-1705	403	24	-	-	PUNCT
cana-1705	403	25	term	term	NOUN
cana-1705	403	26	dependencies	dependency	NOUN
cana-1705	403	27	in	in	ADP
cana-1705	403	28	traffic	traffic	NOUN
cana-1705	403	29	data	datum	NOUN
cana-1705	403	30	.	.	PUNCT
cana-1705	404	1	also	also	ADV
cana-1705	404	2	,	,	PUNCT
cana-1705	404	3	traditional	traditional	ADJ
cana-1705	404	4	models	model	NOUN
cana-1705	404	5	like	like	ADP
cana-1705	404	6	arima	arima	NOUN
cana-1705	404	7	,	,	PUNCT
cana-1705	404	8	support	support	NOUN
cana-1705	404	9	vector	vector	NOUN
cana-1705	404	10	machines	machine	NOUN
cana-1705	404	11	(	(	PUNCT
cana-1705	404	12	svm	svm	PROPN
cana-1705	404	13	)	)	PUNCT
cana-1705	404	14	,	,	PUNCT
cana-1705	404	15	multilayer	multilayer	ADJ
cana-1705	404	16	perceptrons	perceptron	NOUN
cana-1705	404	17	(	(	PUNCT
cana-1705	404	18	mlp	mlp	NOUN
cana-1705	404	19	)	)	PUNCT
cana-1705	404	20	,	,	PUNCT
cana-1705	404	21	have	have	VERB
cana-1705	404	22	difficulty	difficulty	NOUN
cana-1705	404	23	capturing	capture	VERB
cana-1705	404	24	the	the	DET
cana-1705	404	25	temporal	temporal	ADJ
cana-1705	404	26	dynamic	dynamic	ADJ
cana-1705	404	27	and	and	CCONJ
cana-1705	404	28	non	non	ADJ
cana-1705	404	29	-	-	ADJ
cana-1705	404	30	linear	linear	ADJ
cana-1705	404	31	characteristics	characteristic	NOUN
cana-1705	404	32	in	in	ADP
cana-1705	404	33	urban	urban	ADJ
cana-1705	404	34	traffic	traffic	NOUN
cana-1705	404	35	.	.	PUNCT
cana-1705	405	1	the	the	DET
cana-1705	405	2	lstm	lstm	PROPN
cana-1705	405	3	network	network	NOUN
cana-1705	405	4	has	have	VERB
cana-1705	405	5	a	a	DET
cana-1705	405	6	certain	certain	ADJ
cana-1705	405	7	architecture	architecture	NOUN
cana-1705	405	8	that	that	PRON
cana-1705	405	9	is	be	AUX
cana-1705	405	10	capable	capable	ADJ
cana-1705	405	11	of	of	ADP
cana-1705	405	12	handling	handle	VERB
cana-1705	405	13	time	time	NOUN
cana-1705	405	14	-	-	PUNCT
cana-1705	405	15	series	series	NOUN
cana-1705	405	16	data	datum	NOUN
cana-1705	405	17	unlike	unlike	ADP
cana-1705	405	18	the	the	DET
cana-1705	405	19	baseline	baseline	NOUN
cana-1705	405	20	models	model	NOUN
cana-1705	405	21	,	,	PUNCT
cana-1705	405	22	thus	thus	ADV
cana-1705	405	23	it	it	PRON
cana-1705	405	24	proves	prove	VERB
cana-1705	405	25	to	to	PART
cana-1705	405	26	be	be	AUX
cana-1705	405	27	sutable	sutable	ADJ
cana-1705	405	28	for	for	ADP
cana-1705	405	29	traffic	traffic	NOUN
cana-1705	405	30	flow	flow	NOUN
cana-1705	405	31	forecasting	forecasting	NOUN
cana-1705	405	32	in	in	ADP
cana-1705	405	33	general	general	ADJ
cana-1705	405	34	.	.	PUNCT
cana-1705	406	1	experiments	experiment	NOUN
cana-1705	406	2	on	on	ADP
cana-1705	406	3	two	two	NUM
cana-1705	406	4	independent	independent	ADJ
cana-1705	406	5	datasets	dataset	NOUN
cana-1705	406	6	«	«	PUNCT
cana-1705	406	7	metr	metr	PROPN
cana-1705	406	8	-	-	PUNCT
cana-1705	406	9	la	la	NOUN
cana-1705	406	10	and	and	CCONJ
cana-1705	406	11	a	a	DET
cana-1705	406	12	gpsenabled	gpsenable	VERB
cana-1705	406	13	urban	urban	ADJ
cana-1705	406	14	dataset	dataset	NOUN
cana-1705	406	15	demonstrate	demonstrate	NOUN
cana-1705	406	16	that	that	SCONJ
cana-1705	406	17	the	the	DET
cana-1705	406	18	lstm	lstm	PROPN
cana-1705	406	19	model	model	NOUN
cana-1705	406	20	significantly	significantly	ADV
cana-1705	406	21	outperforms	outperform	VERB
cana-1705	406	22	state	state	NOUN
cana-1705	406	23	-	-	PUNCT
cana-1705	406	24	of	of	ADP
cana-1705	406	25	-	-	PUNCT
cana-1705	406	26	the	the	DET
cana-1705	406	27	-	-	PUNCT
cana-1705	406	28	art	art	NOUN
cana-1705	406	29	approaches	approach	NOUN
cana-1705	406	30	in	in	ADP
cana-1705	406	31	predictive	predictive	ADJ
cana-1705	406	32	precision	precision	NOUN
cana-1705	406	33	.	.	PUNCT
cana-1705	407	1	the	the	DET
cana-1705	407	2	advantage	advantage	NOUN
cana-1705	407	3	in	in	ADP
cana-1705	407	4	the	the	DET
cana-1705	407	5	performance	performance	NOUN
cana-1705	407	6	of	of	ADP
cana-1705	407	7	lstm	lstm	NOUN
cana-1705	407	8	network	network	NOUN
cana-1705	407	9	is	be	AUX
cana-1705	407	10	that	that	SCONJ
cana-1705	407	11	it	it	PRON
cana-1705	407	12	has	have	VERB
cana-1705	407	13	a	a	DET
cana-1705	407	14	kind	kind	NOUN
cana-1705	407	15	of	of	ADP
cana-1705	407	16	memory	memory	NOUN
cana-1705	407	17	cell	cell	NOUN
cana-1705	407	18	,	,	PUNCT
cana-1705	407	19	which	which	PRON
cana-1705	407	20	remember	remember	VERB
cana-1705	407	21	previous	previous	ADJ
cana-1705	407	22	states	state	NOUN
cana-1705	407	23	for	for	ADP
cana-1705	407	24	long	long	ADJ
cana-1705	407	25	-	-	PUNCT
cana-1705	407	26	period	period	NOUN
cana-1705	407	27	time	time	NOUN
cana-1705	407	28	(	(	PUNCT
cana-1705	407	29	let	let	VERB
cana-1705	407	30	say	say	VERB
cana-1705	407	31	n	n	NUM
cana-1705	407	32	-	-	PUNCT
cana-1705	407	33	steps	step	NOUN
cana-1705	407	34	back	back	ADV
cana-1705	407	35	through	through	ADP
cana-1705	407	36	time	time	NOUN
cana-1705	407	37	)	)	PUNCT
cana-1705	407	38	so	so	SCONJ
cana-1705	407	39	that	that	SCONJ
cana-1705	407	40	it	it	PRON
cana-1705	407	41	can	can	AUX
cana-1705	407	42	capture	capture	VERB
cana-1705	407	43	important	important	ADJ
cana-1705	407	44	temporal	temporal	ADJ
cana-1705	407	45	dependencies	dependency	NOUN
cana-1705	407	46	presented	present	VERB
cana-1705	407	47	in	in	ADP
cana-1705	407	48	traffic	traffic	NOUN
cana-1705	407	49	flow	flow	NOUN
cana-1705	407	50	prediction	prediction	NOUN
cana-1705	407	51	data	datum	NOUN
cana-1705	407	52	.	.	PUNCT
cana-1705	408	1	exogenous	exogenous	ADJ
cana-1705	408	2	factors	factor	NOUN
cana-1705	408	3	,	,	PUNCT
cana-1705	408	4	such	such	ADJ
cana-1705	408	5	as	as	ADP
cana-1705	408	6	the	the	DET
cana-1705	408	7	time	time	NOUN
cana-1705	408	8	of	of	ADP
cana-1705	408	9	day	day	NOUN
cana-1705	408	10	,	,	PUNCT
cana-1705	408	11	day	day	NOUN
cana-1705	408	12	of	of	ADP
cana-1705	408	13	the	the	DET
cana-1705	408	14	week	week	NOUN
cana-1705	408	15	or	or	CCONJ
cana-1705	408	16	weather	weather	NOUN
cana-1705	408	17	conditions	condition	NOUN
cana-1705	408	18	impact	impact	NOUN
cana-1705	408	19	on	on	ADP
cana-1705	408	20	traffic	traffic	NOUN
cana-1705	408	21	patterns	pattern	NOUN
cana-1705	408	22	.	.	PUNCT
cana-1705	409	1	the	the	DET
cana-1705	409	2	lstm	lstm	PROPN
cana-1705	409	3	model	model	NOUN
cana-1705	409	4	performs	perform	VERB
cana-1705	409	5	well	well	ADV
cana-1705	409	6	at	at	ADP
cana-1705	409	7	taking	take	VERB
cana-1705	409	8	advantage	advantage	NOUN
cana-1705	409	9	of	of	ADP
cana-1705	409	10	this	this	DET
cana-1705	409	11	temporal	temporal	ADJ
cana-1705	409	12	information	information	NOUN
cana-1705	409	13	to	to	PART
cana-1705	409	14	generate	generate	VERB
cana-1705	409	15	more	more	ADV
cana-1705	409	16	accurate	accurate	ADJ
cana-1705	409	17	predictions	prediction	NOUN
cana-1705	409	18	than	than	ADP
cana-1705	409	19	other	other	ADJ
cana-1705	409	20	models	model	NOUN
cana-1705	409	21	that	that	PRON
cana-1705	409	22	may	may	AUX
cana-1705	409	23	find	find	VERB
cana-1705	409	24	it	it	PRON
cana-1705	409	25	difficult	difficult	ADJ
cana-1705	409	26	to	to	PART
cana-1705	409	27	incorporate	incorporate	VERB
cana-1705	409	28	this	this	DET
cana-1705	409	29	complexity	complexity	NOUN
cana-1705	409	30	.	.	PUNCT
cana-1705	410	1	now	now	ADV
cana-1705	410	2	the	the	DET
cana-1705	410	3	benefit	benefit	NOUN
cana-1705	410	4	is	be	AUX
cana-1705	410	5	even	even	ADV
cana-1705	410	6	more	more	ADV
cana-1705	410	7	pronounced	pronounced	ADJ
cana-1705	410	8	when	when	SCONJ
cana-1705	410	9	traffic	traffic	NOUN
cana-1705	410	10	patterns	pattern	NOUN
cana-1705	410	11	are	be	AUX
cana-1705	410	12	of	of	ADP
cana-1705	410	13	irregular	irregular	ADJ
cana-1705	410	14	or	or	CCONJ
cana-1705	410	15	non	non	ADJ
cana-1705	410	16	-	-	ADJ
cana-1705	410	17	linear	linear	ADJ
cana-1705	410	18	nature	nature	NOUN
cana-1705	410	19	,	,	PUNCT
cana-1705	410	20	during	during	ADP
cana-1705	410	21	peak	peak	NOUN
cana-1705	410	22	hours	hour	NOUN
cana-1705	410	23	,	,	PUNCT
cana-1705	410	24	bad	bad	ADJ
cana-1705	410	25	weather	weather	NOUN
cana-1705	410	26	etc	etc	X
cana-1705	410	27	.	.	X
cana-1705	410	28	communications	communication	NOUN
cana-1705	410	29	on	on	ADP
cana-1705	410	30	applied	apply	VERB
cana-1705	410	31	nonlinear	nonlinear	ADJ
cana-1705	410	32	analysis	analysis	NOUN
cana-1705	410	33	issn	issn	NOUN
cana-1705	410	34	:	:	PUNCT
cana-1705	410	35	1074	1074	NUM
cana-1705	410	36	-	-	PUNCT
cana-1705	410	37	133x	133x	NUM
cana-1705	410	38	vol	vol	NOUN
cana-1705	410	39	32	32	NUM
cana-1705	410	40	no	no	NOUN
cana-1705	410	41	.	.	NOUN
cana-1705	410	42	2	2	NUM
cana-1705	410	43	(	(	PUNCT
cana-1705	410	44	2025	2025	NUM
cana-1705	410	45	)	)	PUNCT
cana-1705	410	46	24	24	NUM
cana-1705	410	47	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	410	48	the	the	DET
cana-1705	410	49	research	research	NOUN
cana-1705	410	50	presented	present	VERB
cana-1705	410	51	in	in	ADP
cana-1705	410	52	this	this	DET
cana-1705	410	53	paper	paper	NOUN
cana-1705	410	54	is	be	AUX
cana-1705	410	55	significant	significant	ADJ
cana-1705	410	56	to	to	ADP
cana-1705	410	57	the	the	DET
cana-1705	410	58	filed	file	VERB
cana-1705	410	59	of	of	ADP
cana-1705	410	60	traffic	traffic	NOUN
cana-1705	410	61	flow	flow	NOUN
cana-1705	410	62	prediction	prediction	NOUN
cana-1705	410	63	,	,	PUNCT
cana-1705	410	64	and	and	CCONJ
cana-1705	410	65	urban	urban	ADJ
cana-1705	410	66	mobility	mobility	NOUN
cana-1705	410	67	optimization	optimization	NOUN
cana-1705	410	68	.	.	PUNCT
cana-1705	411	1	this	this	PRON
cana-1705	411	2	suggests	suggest	VERB
cana-1705	411	3	two	two	NUM
cana-1705	411	4	things	thing	NOUN
cana-1705	411	5	:	:	PUNCT
cana-1705	411	6	(	(	PUNCT
cana-1705	411	7	1	1	X
cana-1705	411	8	)	)	PUNCT
cana-1705	411	9	lstm	lstm	NOUN
cana-1705	411	10	networks	network	NOUN
cana-1705	411	11	are	be	AUX
cana-1705	411	12	effective	effective	ADJ
cana-1705	411	13	for	for	ADP
cana-1705	411	14	predicting	predict	VERB
cana-1705	411	15	realtime	realtime	NOUN
cana-1705	411	16	traffic	traffic	NOUN
cana-1705	411	17	flow	flow	NOUN
cana-1705	411	18	,	,	PUNCT
cana-1705	411	19	which	which	PRON
cana-1705	411	20	is	be	AUX
cana-1705	411	21	especially	especially	ADV
cana-1705	411	22	true	true	ADJ
cana-1705	411	23	in	in	ADP
cana-1705	411	24	an	an	DET
cana-1705	411	25	urban	urban	ADJ
cana-1705	411	26	context	context	NOUN
cana-1705	411	27	due	due	ADP
cana-1705	411	28	to	to	ADP
cana-1705	411	29	the	the	DET
cana-1705	411	30	variability	variability	NOUN
cana-1705	411	31	and	and	CCONJ
cana-1705	411	32	complexity	complexity	NOUN
cana-1705	411	33	inherent	inherent	ADJ
cana-1705	411	34	in	in	ADP
cana-1705	411	35	affecting	affect	VERB
cana-1705	411	36	factors	factor	NOUN
cana-1705	411	37	related	relate	VERB
cana-1705	411	38	to	to	ADP
cana-1705	411	39	traffic	traffic	NOUN
cana-1705	411	40	data	datum	NOUN
cana-1705	411	41	;	;	PUNCT
cana-1705	411	42	results	result	NOUN
cana-1705	411	43	over	over	ADP
cana-1705	411	44	both	both	PRON
cana-1705	411	45	metr	metr	PROPN
cana-1705	411	46	-	-	PUNCT
cana-1705	411	47	la	la	ADJ
cana-1705	411	48	and	and	CCONJ
cana-1705	411	49	urban	urban	PROPN
cana-1705	411	50	datasets	dataset	NOUN
cana-1705	411	51	geo	geo	PROPN
cana-1705	411	52	-	-	PUNCT
cana-1705	411	53	located	locate	VERB
cana-1705	411	54	with	with	ADP
cana-1705	411	55	gps	gps	PROPN
cana-1705	411	56	enable	enable	VERB
cana-1705	411	57	us	we	PRON
cana-1705	411	58	to	to	PART
cana-1705	411	59	confirm	confirm	VERB
cana-1705	411	60	that	that	SCONJ
cana-1705	411	61	the	the	DET
cana-1705	411	62	lstm	lstm	PROPN
cana-1705	411	63	model	model	NOUN
cana-1705	411	64	generally	generally	ADV
cana-1705	411	65	behaves	behave	VERB
cana-1705	411	66	better	well	ADV
cana-1705	411	67	than	than	ADP
cana-1705	411	68	arima	arima	NOUN
cana-1705	411	69	,	,	PUNCT
cana-1705	411	70	svm	svm	NOUN
cana-1705	411	71	and	and	CCONJ
cana-1705	411	72	mlp	mlp	NOUN
cana-1705	411	73	models	model	NOUN
cana-1705	411	74	according	accord	VERB
cana-1705	411	75	performance	performance	NOUN
cana-1705	411	76	metrics	metric	NOUN
cana-1705	411	77	such	such	ADJ
cana-1705	411	78	as	as	ADP
cana-1705	411	79	root	root	NOUN
cana-1705	411	80	mean	mean	VERB
cana-1705	411	81	squared	square	VERB
cana-1705	411	82	error	error	NOUN
cana-1705	411	83	(	(	PUNCT
cana-1705	411	84	rmse	rmse	NOUN
cana-1705	411	85	)	)	PUNCT
cana-1705	411	86	,	,	PUNCT
cana-1705	411	87	mean	mean	VERB
cana-1705	411	88	absolute	absolute	ADJ
cana-1705	411	89	error	error	NOUN
cana-1705	411	90	(	(	PUNCT
cana-1705	411	91	mae	mae	PROPN
cana-1705	411	92	)	)	PUNCT
cana-1705	411	93	or	or	CCONJ
cana-1705	411	94	mean	mean	VERB
cana-1705	411	95	squared	square	VERB
cana-1705	411	96	error	error	NOUN
cana-1705	411	97	(	(	PUNCT
cana-1705	411	98	mse	mse	NOUN
cana-1705	411	99	)	)	PUNCT
cana-1705	411	100	.	.	PUNCT
cana-1705	412	1	for	for	ADP
cana-1705	412	2	example	example	NOUN
cana-1705	412	3	:	:	PUNCT
cana-1705	412	4	in	in	ADP
cana-1705	412	5	the	the	DET
cana-1705	412	6	metrla	metrla	PROPN
cana-1705	412	7	dataset	dataset	PROPN
cana-1705	412	8	,	,	PUNCT
cana-1705	412	9	the	the	DET
cana-1705	412	10	lstm	lstm	PROPN
cana-1705	412	11	model	model	NOUN
cana-1705	412	12	got	get	VERB
cana-1705	412	13	an	an	DET
cana-1705	412	14	rmse	rmse	NOUN
cana-1705	412	15	of	of	ADP
cana-1705	412	16	6.78	6.78	NUM
cana-1705	412	17	while	while	SCONJ
cana-1705	412	18	arima	arima	PROPN
cana-1705	412	19	and	and	CCONJ
cana-1705	412	20	svm	svm	PROPN
cana-1705	412	21	both	both	PRON
cana-1705	412	22	have	have	VERB
cana-1705	412	23	worse	bad	ADJ
cana-1705	412	24	performance	performance	NOUN
cana-1705	412	25	with	with	ADP
cana-1705	412	26	rmse	rmse	NOUN
cana-1705	412	27	10.34	10.34	NUM
cana-1705	412	28	and	and	CCONJ
cana-1705	412	29	rmse	rmse	PROPN
cana-1705	412	30	8.72	8.72	NUM
cana-1705	412	31	,	,	PUNCT
cana-1705	412	32	which	which	PRON
cana-1705	412	33	showed	show	VERB
cana-1705	412	34	its	its	PRON
cana-1705	412	35	good	good	ADJ
cana-1705	412	36	performances	performance	NOUN
cana-1705	412	37	for	for	ADP
cana-1705	412	38	traffic	traffic	NOUN
cana-1705	412	39	flow	flow	NOUN
cana-1705	412	40	data	datum	NOUN
cana-1705	412	41	at	at	ADP
cana-1705	412	42	real	real	ADJ
cana-1705	412	43	world	world	NOUN
cana-1705	412	44	.	.	PUNCT
cana-1705	413	1	second	second	ADV
cana-1705	413	2	,	,	PUNCT
cana-1705	413	3	this	this	DET
cana-1705	413	4	study	study	NOUN
cana-1705	413	5	emphasizes	emphasize	VERB
cana-1705	413	6	the	the	DET
cana-1705	413	7	necessity	necessity	NOUN
cana-1705	413	8	of	of	ADP
cana-1705	413	9	considering	consider	VERB
cana-1705	413	10	external	external	ADJ
cana-1705	413	11	elements	element	NOUN
cana-1705	413	12	like	like	ADP
cana-1705	413	13	weather	weather	NOUN
cana-1705	413	14	and	and	CCONJ
cana-1705	413	15	public	public	ADJ
cana-1705	413	16	events	event	NOUN
cana-1705	413	17	or	or	CCONJ
cana-1705	413	18	accidents	accident	NOUN
cana-1705	413	19	in	in	ADP
cana-1705	413	20	travel	travel	NOUN
cana-1705	413	21	time	time	NOUN
cana-1705	413	22	prediction	prediction	NOUN
cana-1705	413	23	algorithm	algorithm	NOUN
cana-1705	413	24	.	.	PUNCT
cana-1705	414	1	differences	difference	NOUN
cana-1705	414	2	from	from	ADP
cana-1705	414	3	the	the	DET
cana-1705	414	4	current	current	ADJ
cana-1705	414	5	design	design	NOUN
cana-1705	414	6	,	,	PUNCT
cana-1705	414	7	including	include	VERB
cana-1705	414	8	these	these	DET
cana-1705	414	9	elements	element	NOUN
cana-1705	414	10	in	in	ADP
cana-1705	414	11	the	the	DET
cana-1705	414	12	lstm	lstm	NOUN
cana-1705	414	13	model	model	NOUN
cana-1705	414	14	greatly	greatly	ADV
cana-1705	414	15	improved	improve	VERB
cana-1705	414	16	its	its	PRON
cana-1705	414	17	prediction	prediction	NOUN
cana-1705	414	18	performance	performance	NOUN
cana-1705	414	19	,	,	PUNCT
cana-1705	414	20	especially	especially	ADV
cana-1705	414	21	in	in	ADP
cana-1705	414	22	weather	weather	NOUN
cana-1705	414	23	disrupts	disrupt	NOUN
cana-1705	414	24	or	or	CCONJ
cana-1705	414	25	un	un	ADJ
cana-1705	414	26	-	-	ADJ
cana-1705	414	27	typical	typical	ADJ
cana-1705	414	28	situations	situation	NOUN
cana-1705	414	29	appear	appear	VERB
cana-1705	414	30	within	within	ADP
cana-1705	414	31	a	a	DET
cana-1705	414	32	road	road	NOUN
cana-1705	414	33	network	network	NOUN
cana-1705	414	34	.	.	PUNCT
cana-1705	415	1	this	this	PRON
cana-1705	415	2	is	be	AUX
cana-1705	415	3	highly	highly	ADV
cana-1705	415	4	relevant	relevant	ADJ
cana-1705	415	5	to	to	ADP
cana-1705	415	6	urban	urban	ADJ
cana-1705	415	7	traffic	traffic	NOUN
cana-1705	415	8	management	management	NOUN
cana-1705	415	9	as	as	SCONJ
cana-1705	415	10	our	our	PRON
cana-1705	415	11	analysis	analysis	NOUN
cana-1705	415	12	suggests	suggest	VERB
cana-1705	415	13	that	that	SCONJ
cana-1705	415	14	,	,	PUNCT
cana-1705	415	15	outside	outside	ADP
cana-1705	415	16	the	the	DET
cana-1705	415	17	major	major	ADJ
cana-1705	415	18	hubs	hub	NOUN
cana-1705	415	19	like	like	ADP
cana-1705	415	20	berlin	berlin	PROPN
cana-1705	415	21	or	or	CCONJ
cana-1705	415	22	munich	munich	PROPN
cana-1705	415	23	,	,	PUNCT
cana-1705	415	24	entities	entity	NOUN
cana-1705	415	25	with	with	ADP
cana-1705	415	26	external	external	ADJ
cana-1705	415	27	means	mean	NOUN
cana-1705	415	28	at	at	ADP
cana-1705	415	29	their	their	PRON
cana-1705	415	30	disposal	disposal	NOUN
cana-1705	415	31	account	account	NOUN
cana-1705	415	32	for	for	ADP
cana-1705	415	33	much	much	ADJ
cana-1705	415	34	of	of	ADP
cana-1705	415	35	the	the	DET
cana-1705	415	36	regulatory	regulatory	ADJ
cana-1705	415	37	capacity	capacity	NOUN
cana-1705	415	38	.	.	PUNCT
cana-1705	416	1	with	with	ADP
cana-1705	416	2	the	the	DET
cana-1705	416	3	combination	combination	NOUN
cana-1705	416	4	of	of	ADP
cana-1705	416	5	these	these	DET
cana-1705	416	6	elements	element	NOUN
cana-1705	416	7	into	into	ADP
cana-1705	416	8	the	the	DET
cana-1705	416	9	lstm	lstm	PROPN
cana-1705	416	10	model	model	NOUN
cana-1705	416	11	,	,	PUNCT
cana-1705	416	12	we	we	PRON
cana-1705	416	13	produced	produce	VERB
cana-1705	416	14	a	a	DET
cana-1705	416	15	much	much	ADV
cana-1705	416	16	richer	rich	ADJ
cana-1705	416	17	and	and	CCONJ
cana-1705	416	18	more	more	ADV
cana-1705	416	19	realistic	realistic	ADJ
cana-1705	416	20	prediction	prediction	NOUN
cana-1705	416	21	of	of	ADP
cana-1705	416	22	traffic	traffic	NOUN
cana-1705	416	23	flow	flow	NOUN
cana-1705	416	24	,	,	PUNCT
cana-1705	416	25	which	which	PRON
cana-1705	416	26	should	should	AUX
cana-1705	416	27	be	be	AUX
cana-1705	416	28	more	more	ADV
cana-1705	416	29	useful	useful	ADJ
cana-1705	416	30	in	in	ADP
cana-1705	416	31	practice	practice	NOUN
cana-1705	416	32	-	-	PUNCT
cana-1705	416	33	related	relate	VERB
cana-1705	416	34	cases	case	NOUN
cana-1705	416	35	.	.	PUNCT
cana-1705	417	1	finally	finally	ADV
cana-1705	417	2	,	,	PUNCT
cana-1705	417	3	the	the	DET
cana-1705	417	4	study	study	NOUN
cana-1705	417	5	discusses	discuss	VERB
cana-1705	417	6	instant	instant	ADJ
cana-1705	417	7	implementation	implementation	NOUN
cana-1705	417	8	of	of	ADP
cana-1705	417	9	the	the	DET
cana-1705	417	10	lstm	lstm	PROPN
cana-1705	417	11	model	model	NOUN
cana-1705	417	12	for	for	ADP
cana-1705	417	13	traffic	traffic	NOUN
cana-1705	417	14	management	management	NOUN
cana-1705	417	15	systems	system	NOUN
cana-1705	417	16	.	.	PUNCT
cana-1705	418	1	for	for	ADP
cana-1705	418	2	this	this	DET
cana-1705	418	3	study	study	NOUN
cana-1705	418	4	,	,	PUNCT
cana-1705	418	5	a	a	DET
cana-1705	418	6	key	key	ADJ
cana-1705	418	7	target	target	NOUN
cana-1705	418	8	algorithm	algorithm	NOUN
cana-1705	418	9	to	to	PART
cana-1705	418	10	be	be	AUX
cana-1705	418	11	developed	develop	VERB
cana-1705	418	12	was	be	AUX
cana-1705	418	13	a	a	DET
cana-1705	418	14	real	real	ADJ
cana-1705	418	15	-	-	PUNCT
cana-1705	418	16	time	time	NOUN
cana-1705	418	17	traffic	traffic	NOUN
cana-1705	418	18	…	…	PUNCT
cana-1705	418	19	the	the	DET
cana-1705	418	20	low	low	ADJ
cana-1705	418	21	prediction	prediction	NOUN
cana-1705	418	22	time	time	NOUN
cana-1705	418	23	in	in	ADP
cana-1705	418	24	milliseconds	millisecond	NOUN
cana-1705	418	25	of	of	ADP
cana-1705	418	26	the	the	DET
cana-1705	418	27	lstm	lstm	PROPN
cana-1705	418	28	model	model	NOUN
cana-1705	418	29	further	far	ADV
cana-1705	418	30	manifests	manifest	VERB
cana-1705	418	31	its	its	PRON
cana-1705	418	32	ability	ability	NOUN
cana-1705	418	33	to	to	PART
cana-1705	418	34	predict	predict	VERB
cana-1705	418	35	real	real	ADJ
cana-1705	418	36	-	-	PUNCT
cana-1705	418	37	time	time	NOUN
cana-1705	418	38	predictions	prediction	NOUN
cana-1705	418	39	useful	useful	ADJ
cana-1705	418	40	for	for	ADP
cana-1705	418	41	traffic	traffic	NOUN
cana-1705	418	42	signal	signal	PROPN
cana-1705	418	43	optimization	optimization	NOUN
cana-1705	418	44	,	,	PUNCT
cana-1705	418	45	vehicle	vehicle	NOUN
cana-1705	418	46	routing	routing	NOUN
cana-1705	418	47	and	and	CCONJ
cana-1705	418	48	providing	provide	VERB
cana-1705	418	49	live	live	ADJ
cana-1705	418	50	information	information	NOUN
cana-1705	418	51	to	to	ADP
cana-1705	418	52	drivers	driver	NOUN
cana-1705	418	53	traffic	traffic	NOUN
cana-1705	418	54	management	management	NOUN
cana-1705	418	55	systems	system	NOUN
cana-1705	418	56	must	must	AUX
cana-1705	418	57	provide	provide	VERB
cana-1705	418	58	real	real	ADJ
cana-1705	418	59	-	-	PUNCT
cana-1705	418	60	time	time	NOUN
cana-1705	418	61	functionality	functionality	NOUN
cana-1705	418	62	in	in	ADP
cana-1705	418	63	current	current	ADJ
cana-1705	418	64	days	day	NOUN
cana-1705	418	65	cities	city	NOUN
cana-1705	418	66	such	such	ADJ
cana-1705	418	67	as	as	ADP
cana-1705	418	68	smart	smart	ADJ
cana-1705	418	69	cities	city	NOUN
cana-1705	418	70	,	,	PUNCT
cana-1705	418	71	where	where	SCONJ
cana-1705	418	72	traffic	traffic	NOUN
cana-1705	418	73	conditions	condition	NOUN
cana-1705	418	74	are	be	AUX
cana-1705	418	75	very	very	ADV
cana-1705	418	76	dynamic	dynamic	ADJ
cana-1705	418	77	.	.	PUNCT
cana-1705	419	1	although	although	SCONJ
cana-1705	419	2	the	the	DET
cana-1705	419	3	lstm	lstm	NOUN
cana-1705	419	4	model	model	NOUN
cana-1705	419	5	showed	show	VERB
cana-1705	419	6	very	very	ADV
cana-1705	419	7	significant	significant	ADJ
cana-1705	419	8	improvement	improvement	NOUN
cana-1705	419	9	when	when	SCONJ
cana-1705	419	10	compared	compare	VERB
cana-1705	419	11	to	to	ADP
cana-1705	419	12	traditional	traditional	ADJ
cana-1705	419	13	models	model	NOUN
cana-1705	419	14	,	,	PUNCT
cana-1705	419	15	there	there	PRON
cana-1705	419	16	are	be	VERB
cana-1705	419	17	a	a	DET
cana-1705	419	18	few	few	ADJ
cana-1705	419	19	challenges	challenge	NOUN
cana-1705	419	20	and	and	CCONJ
cana-1705	419	21	limitations	limitation	NOUN
cana-1705	419	22	that	that	PRON
cana-1705	419	23	need	need	VERB
cana-1705	419	24	to	to	PART
cana-1705	419	25	be	be	AUX
cana-1705	419	26	overcome	overcome	VERB
cana-1705	419	27	.	.	PUNCT
cana-1705	420	1	data	datum	NOUN
cana-1705	420	2	quality	quality	NOUN
cana-1705	420	3	and	and	CCONJ
cana-1705	420	4	availability	availability	NOUN
cana-1705	420	5	are	be	AUX
cana-1705	420	6	some	some	PRON
cana-1705	420	7	of	of	ADP
cana-1705	420	8	the	the	DET
cana-1705	420	9	major	major	ADJ
cana-1705	420	10	challenges	challenge	NOUN
cana-1705	420	11	in	in	ADP
cana-1705	420	12	traffic	traffic	NOUN
cana-1705	420	13	flow	flow	NOUN
cana-1705	420	14	prediction	prediction	NOUN
cana-1705	420	15	.	.	PUNCT
cana-1705	421	1	however	however	ADV
cana-1705	421	2	,	,	PUNCT
cana-1705	421	3	traffic	traffic	NOUN
cana-1705	421	4	data	datum	NOUN
cana-1705	421	5	is	be	AUX
cana-1705	421	6	noisy	noisy	ADJ
cana-1705	421	7	in	in	ADP
cana-1705	421	8	nature	nature	NOUN
cana-1705	421	9	,	,	PUNCT
cana-1705	421	10	incomplete	incomplete	ADJ
cana-1705	421	11	or	or	CCONJ
cana-1705	421	12	even	even	ADV
cana-1705	421	13	outdated	outdated	ADJ
cana-1705	421	14	and	and	CCONJ
cana-1705	421	15	some	some	PRON
cana-1705	421	16	of	of	ADP
cana-1705	421	17	the	the	DET
cana-1705	421	18	sensors	sensor	NOUN
cana-1705	421	19	are	be	AUX
cana-1705	421	20	faulty	faulty	ADJ
cana-1705	421	21	leading	lead	VERB
cana-1705	421	22	to	to	ADP
cana-1705	421	23	inaccuracies	inaccuracy	NOUN
cana-1705	421	24	of	of	ADP
cana-1705	421	25	predictions	prediction	NOUN
cana-1705	421	26	.	.	PUNCT
cana-1705	422	1	this	this	DET
cana-1705	422	2	study	study	NOUN
cana-1705	422	3	tried	try	VERB
cana-1705	422	4	to	to	PART
cana-1705	422	5	tackle	tackle	VERB
cana-1705	422	6	these	these	DET
cana-1705	422	7	problems	problem	NOUN
cana-1705	422	8	using	use	VERB
cana-1705	422	9	data	datum	NOUN
cana-1705	422	10	preprocessing	preprocesse	VERB
cana-1705	422	11	techniques	technique	NOUN
cana-1705	422	12	like	like	ADP
cana-1705	422	13	datacleaning	datacleane	VERB
cana-1705	422	14	,	,	PUNCT
cana-1705	422	15	normalization	normalization	NOUN
cana-1705	422	16	and	and	CCONJ
cana-1705	422	17	interpolation	interpolation	NOUN
cana-1705	422	18	but	but	CCONJ
cana-1705	422	19	input	input	NOUN
cana-1705	422	20	-	-	PUNCT
cana-1705	422	21	data	datum	NOUN
cana-1705	422	22	quality	quality	NOUN
cana-1705	422	23	is	be	AUX
cana-1705	422	24	still	still	ADV
cana-1705	422	25	an	an	DET
cana-1705	422	26	important	important	ADJ
cana-1705	422	27	factor	factor	NOUN
cana-1705	422	28	for	for	ADP
cana-1705	422	29	the	the	DET
cana-1705	422	30	model	model	NOUN
cana-1705	422	31	performance	performance	NOUN
cana-1705	422	32	.	.	PUNCT
cana-1705	423	1	in	in	ADP
cana-1705	423	2	future	future	ADJ
cana-1705	423	3	work	work	NOUN
cana-1705	423	4	,	,	PUNCT
cana-1705	423	5	more	more	ADV
cana-1705	423	6	sophisticated	sophisticated	ADJ
cana-1705	423	7	imputation	imputation	NOUN
cana-1705	423	8	techniques	technique	NOUN
cana-1705	423	9	can	can	AUX
cana-1705	423	10	be	be	AUX
cana-1705	423	11	applied	apply	VERB
cana-1705	423	12	or	or	CCONJ
cana-1705	423	13	new	new	ADJ
cana-1705	423	14	real	real	ADJ
cana-1705	423	15	-	-	PUNCT
cana-1705	423	16	time	time	NOUN
cana-1705	423	17	information	information	NOUN
cana-1705	423	18	sources	source	NOUN
cana-1705	423	19	could	could	AUX
cana-1705	423	20	be	be	AUX
cana-1705	423	21	incorporated	incorporate	VERB
cana-1705	423	22	to	to	PART
cana-1705	423	23	enhance	enhance	VERB
cana-1705	423	24	the	the	DET
cana-1705	423	25	model	model	NOUN
cana-1705	423	26	robustness	robustness	NOUN
cana-1705	423	27	on	on	ADP
cana-1705	423	28	incomplete	incomplete	ADJ
cana-1705	423	29	or	or	CCONJ
cana-1705	423	30	noisy	noisy	ADJ
cana-1705	423	31	segments	segment	NOUN
cana-1705	423	32	.	.	PUNCT
cana-1705	424	1	the	the	DET
cana-1705	424	2	third	third	ADJ
cana-1705	424	3	issue	issue	NOUN
cana-1705	424	4	regarding	regard	VERB
cana-1705	424	5	the	the	DET
cana-1705	424	6	lstm	lstm	NOUN
cana-1705	424	7	model	model	NOUN
cana-1705	424	8	is	be	AUX
cana-1705	424	9	that	that	SCONJ
cana-1705	424	10	its	its	PRON
cana-1705	424	11	biggest	big	ADJ
cana-1705	424	12	limitation	limitation	NOUN
cana-1705	424	13	reside	reside	VERB
cana-1705	424	14	in	in	ADP
cana-1705	424	15	the	the	DET
cana-1705	424	16	requirement	requirement	NOUN
cana-1705	424	17	of	of	ADP
cana-1705	424	18	a	a	DET
cana-1705	424	19	huge	huge	ADJ
cana-1705	424	20	amount	amount	NOUN
cana-1705	424	21	of	of	ADP
cana-1705	424	22	data	datum	NOUN
cana-1705	424	23	to	to	PART
cana-1705	424	24	learn	learn	VERB
cana-1705	424	25	very	very	ADV
cana-1705	424	26	long	long	ADJ
cana-1705	424	27	-	-	PUNCT
cana-1705	424	28	range	range	NOUN
cana-1705	424	29	dependencies	dependency	NOUN
cana-1705	424	30	.	.	PUNCT
cana-1705	425	1	we	we	PRON
cana-1705	425	2	found	find	VERB
cana-1705	425	3	that	that	SCONJ
cana-1705	425	4	even	even	ADV
cana-1705	425	5	though	though	SCONJ
cana-1705	425	6	fgc	fgc	ADJ
cana-1705	425	7	-	-	PUNCT
cana-1705	425	8	net	net	NOUN
cana-1705	425	9	performed	perform	VERB
cana-1705	425	10	well	well	ADV
cana-1705	425	11	in	in	ADP
cana-1705	425	12	this	this	DET
cana-1705	425	13	study	study	NOUN
cana-1705	425	14	,	,	PUNCT
cana-1705	425	15	it	it	PRON
cana-1705	425	16	requires	require	VERB
cana-1705	425	17	abundant	abundant	ADJ
cana-1705	425	18	computational	computational	ADJ
cana-1705	425	19	resources	resource	NOUN
cana-1705	425	20	and	and	CCONJ
cana-1705	425	21	labelled	label	VERB
cana-1705	425	22	data	datum	NOUN
cana-1705	425	23	to	to	PART
cana-1705	425	24	work	work	VERB
cana-1705	425	25	at	at	ADP
cana-1705	425	26	its	its	PRON
cana-1705	425	27	full	full	ADJ
cana-1705	425	28	potential	potential	NOUN
cana-1705	425	29	.	.	PUNCT
cana-1705	426	1	the	the	DET
cana-1705	426	2	task	task	NOUN
cana-1705	426	3	of	of	ADP
cana-1705	426	4	providing	provide	VERB
cana-1705	426	5	such	such	ADJ
cana-1705	426	6	data	datum	NOUN
cana-1705	426	7	can	can	AUX
cana-1705	426	8	be	be	AUX
cana-1705	426	9	difficult	difficult	ADJ
cana-1705	426	10	in	in	ADP
cana-1705	426	11	real	real	ADJ
cana-1705	426	12	-	-	PUNCT
cana-1705	426	13	world	world	NOUN
cana-1705	426	14	conditions	condition	NOUN
cana-1705	426	15	,	,	PUNCT
cana-1705	426	16	especially	especially	ADV
cana-1705	426	17	for	for	ADP
cana-1705	426	18	small	small	ADJ
cana-1705	426	19	cities	city	NOUN
cana-1705	426	20	or	or	CCONJ
cana-1705	426	21	regions	region	NOUN
cana-1705	426	22	where	where	SCONJ
cana-1705	426	23	there	there	PRON
cana-1705	426	24	are	be	VERB
cana-1705	426	25	not	not	PART
cana-1705	426	26	enough	enough	ADJ
cana-1705	426	27	sensors	sensor	NOUN
cana-1705	426	28	installed	instal	VERB
cana-1705	426	29	on	on	ADP
cana-1705	426	30	highways	highway	NOUN
cana-1705	426	31	everywhere	everywhere	ADV
cana-1705	426	32	.	.	PUNCT
cana-1705	427	1	additionally	additionally	ADV
cana-1705	427	2	,	,	PUNCT
cana-1705	427	3	the	the	DET
cana-1705	427	4	training	training	NOUN
cana-1705	427	5	of	of	ADP
cana-1705	427	6	lstm	lstm	ADJ
cana-1705	427	7	networks	network	NOUN
cana-1705	427	8	can	can	AUX
cana-1705	427	9	costly	costly	ADJ
cana-1705	427	10	,	,	PUNCT
cana-1705	427	11	in	in	ADP
cana-1705	427	12	terms	term	NOUN
cana-1705	427	13	of	of	ADP
cana-1705	427	14	time	time	NOUN
cana-1705	427	15	,	,	PUNCT
cana-1705	427	16	such	such	ADJ
cana-1705	427	17	as	as	ADP
cana-1705	427	18	hyperparameters	hyperparameter	NOUN
cana-1705	427	19	like	like	ADP
cana-1705	427	20	layer	layer	NOUN
cana-1705	427	21	numbers	number	NOUN
cana-1705	427	22	,	,	PUNCT
cana-1705	427	23	memory	memory	NOUN
cana-1705	427	24	units	unit	NOUN
cana-1705	427	25	and	and	CCONJ
cana-1705	427	26	dropout	dropout	NOUN
cana-1705	427	27	rates	rate	NOUN
cana-1705	427	28	.	.	PUNCT
cana-1705	428	1	as	as	SCONJ
cana-1705	428	2	traffic	traffic	NOUN
cana-1705	428	3	prediction	prediction	NOUN
cana-1705	428	4	systems	system	NOUN
cana-1705	428	5	become	become	VERB
cana-1705	428	6	more	more	ADV
cana-1705	428	7	general	general	ADJ
cana-1705	428	8	,	,	PUNCT
cana-1705	428	9	the	the	DET
cana-1705	428	10	interest	interest	NOUN
cana-1705	428	11	in	in	ADP
cana-1705	428	12	learning	learn	VERB
cana-1705	428	13	models	model	NOUN
cana-1705	428	14	quickly	quickly	ADV
cana-1705	428	15	and	and	CCONJ
cana-1705	428	16	for	for	ADP
cana-1705	428	17	as	as	ADV
cana-1705	428	18	many	many	ADJ
cana-1705	428	19	different	different	ADJ
cana-1705	428	20	locations	location	NOUN
cana-1705	428	21	has	have	VERB
cana-1705	428	22	communications	communication	NOUN
cana-1705	428	23	on	on	ADP
cana-1705	428	24	applied	apply	VERB
cana-1705	428	25	nonlinear	nonlinear	ADJ
cana-1705	428	26	analysis	analysis	NOUN
cana-1705	428	27	issn	issn	NOUN
cana-1705	428	28	:	:	PUNCT
cana-1705	428	29	1074	1074	NUM
cana-1705	428	30	-	-	PUNCT
cana-1705	428	31	133x	133x	NUM
cana-1705	428	32	vol	vol	NOUN
cana-1705	428	33	32	32	NUM
cana-1705	428	34	no	no	NOUN
cana-1705	428	35	.	.	NOUN
cana-1705	428	36	2	2	NUM
cana-1705	428	37	(	(	PUNCT
cana-1705	428	38	2025	2025	NUM
cana-1705	428	39	)	)	PUNCT
cana-1705	428	40	25	25	NUM
cana-1705	428	41	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	428	42	made	make	VERB
cana-1705	428	43	it	it	PRON
cana-1705	428	44	desireable	desireable	ADJ
cana-1705	428	45	to	to	PART
cana-1705	428	46	have	have	VERB
cana-1705	428	47	effective	effective	ADJ
cana-1705	428	48	training	training	NOUN
cana-1705	428	49	algorithms	algorithm	NOUN
cana-1705	428	50	and	and	CCONJ
cana-1705	428	51	techniques	technique	NOUN
cana-1705	428	52	that	that	PRON
cana-1705	428	53	leverage	leverage	NOUN
cana-1705	428	54	transfer	transfer	NOUN
cana-1705	428	55	learning	learn	VERB
cana-1705	428	56	to	to	PART
cana-1705	428	57	adapt	adapt	VERB
cana-1705	428	58	a	a	DET
cana-1705	428	59	model	model	NOUN
cana-1705	428	60	trained	train	VERB
cana-1705	428	61	on	on	ADP
cana-1705	428	62	data	datum	NOUN
cana-1705	428	63	from	from	ADP
cana-1705	428	64	one	one	NUM
cana-1705	428	65	area	area	NOUN
cana-1705	428	66	to	to	PART
cana-1705	428	67	use	use	VERB
cana-1705	428	68	data	datum	NOUN
cana-1705	428	69	from	from	ADP
cana-1705	428	70	others	other	NOUN
cana-1705	428	71	who	who	PRON
cana-1705	428	72	have	have	VERB
cana-1705	428	73	less	less	ADJ
cana-1705	428	74	data	datum	NOUN
cana-1705	428	75	.	.	PUNCT
cana-1705	429	1	several	several	ADJ
cana-1705	429	2	angles	angle	NOUN
cana-1705	429	3	for	for	ADP
cana-1705	429	4	future	future	ADJ
cana-1705	429	5	research	research	NOUN
cana-1705	429	6	on	on	ADP
cana-1705	429	7	the	the	DET
cana-1705	429	8	basis	basis	NOUN
cana-1705	429	9	of	of	ADP
cana-1705	429	10	our	our	PRON
cana-1705	429	11	study	study	NOUN
cana-1705	429	12	findings	finding	NOUN
cana-1705	429	13	are	be	AUX
cana-1705	429	14	worth	worth	ADJ
cana-1705	429	15	considering	consider	VERB
cana-1705	429	16	.	.	PUNCT
cana-1705	430	1	this	this	PRON
cana-1705	430	2	could	could	AUX
cana-1705	430	3	lead	lead	VERB
cana-1705	430	4	to	to	ADP
cana-1705	430	5	extending	extend	VERB
cana-1705	430	6	the	the	DET
cana-1705	430	7	lstm	lstm	NOUN
cana-1705	430	8	model	model	NOUN
cana-1705	430	9	for	for	ADP
cana-1705	430	10	more	more	ADJ
cana-1705	430	11	complex	complex	ADJ
cana-1705	430	12	traffic	traffic	NOUN
cana-1705	430	13	networks	network	NOUN
cana-1705	430	14	such	such	ADJ
cana-1705	430	15	as	as	ADP
cana-1705	430	16	multimodal	multimodal	NOUN
cana-1705	430	17	transportation	transportation	NOUN
cana-1705	430	18	systems	system	NOUN
cana-1705	430	19	with	with	ADP
cana-1705	430	20	buses	bus	NOUN
cana-1705	430	21	,	,	PUNCT
cana-1705	430	22	trains	train	NOUN
cana-1705	430	23	,	,	PUNCT
cana-1705	430	24	bicycles	bicycle	NOUN
cana-1705	430	25	and	and	CCONJ
cana-1705	430	26	pedestrians	pedestrian	NOUN
cana-1705	430	27	.	.	PUNCT
cana-1705	431	1	today	today	NOUN
cana-1705	431	2	's	's	PART
cana-1705	431	3	mostly	mostly	ADV
cana-1705	431	4	prioritize	prioritize	ADJ
cana-1705	431	5	vehicles	vehicle	NOUN
cana-1705	431	6	,	,	PUNCT
cana-1705	431	7	but	but	CCONJ
cana-1705	431	8	urban	urban	ADJ
cana-1705	431	9	mobility	mobility	NOUN
cana-1705	431	10	is	be	AUX
cana-1705	431	11	rapidly	rapidly	ADV
cana-1705	431	12	becoming	become	VERB
cana-1705	431	13	more	more	ADV
cana-1705	431	14	distributed	distribute	VERB
cana-1705	431	15	.	.	PUNCT
cana-1705	432	1	fusing	fuse	VERB
cana-1705	432	2	that	that	SCONJ
cana-1705	432	3	data	datum	NOUN
cana-1705	432	4	with	with	ADP
cana-1705	432	5	the	the	DET
cana-1705	432	6	info	info	NOUN
cana-1705	432	7	emanating	emanate	VERB
cana-1705	432	8	from	from	ADP
cana-1705	432	9	contrasting	contrast	VERB
cana-1705	432	10	public	public	ADJ
cana-1705	432	11	transportation	transportation	NOUN
cana-1705	432	12	services	service	NOUN
cana-1705	432	13	,	,	PUNCT
cana-1705	432	14	different	different	ADJ
cana-1705	432	15	walking	walking	NOUN
cana-1705	432	16	paths	path	NOUN
cana-1705	432	17	and	and	CCONJ
cana-1705	432	18	shared	share	VERB
cana-1705	432	19	mobility	mobility	NOUN
cana-1705	432	20	schedules	schedule	NOUN
cana-1705	432	21	may	may	AUX
cana-1705	432	22	mean	mean	VERB
cana-1705	432	23	insightful	insightful	ADJ
cana-1705	432	24	projections	projection	NOUN
cana-1705	432	25	on	on	ADP
cana-1705	432	26	how	how	SCONJ
cana-1705	432	27	the	the	DET
cana-1705	432	28	future	future	NOUN
cana-1705	432	29	of	of	ADP
cana-1705	432	30	urban	urban	ADJ
cana-1705	432	31	commuting	commuting	NOUN
cana-1705	432	32	methods	method	NOUN
cana-1705	432	33	are	be	AUX
cana-1705	432	34	shaping	shape	VERB
cana-1705	432	35	up	up	ADP
cana-1705	432	36	as	as	ADP
cana-1705	432	37	a	a	DET
cana-1705	432	38	whole	whole	NOUN
cana-1705	432	39	and	and	CCONJ
cana-1705	432	40	thus	thus	ADV
cana-1705	432	41	inform	inform	VERB
cana-1705	432	42	city	city	NOUN
cana-1705	432	43	planners	planner	NOUN
cana-1705	432	44	or	or	CCONJ
cana-1705	432	45	even	even	ADV
cana-1705	432	46	general	general	ADJ
cana-1705	432	47	transportation	transportation	NOUN
cana-1705	432	48	entities	entity	NOUN
cana-1705	432	49	.	.	PUNCT
cana-1705	433	1	other	other	ADJ
cana-1705	433	2	promising	promising	ADJ
cana-1705	433	3	and	and	CCONJ
cana-1705	433	4	likely	likely	ADJ
cana-1705	433	5	directions	direction	NOUN
cana-1705	433	6	to	to	PART
cana-1705	433	7	investigate	investigate	VERB
cana-1705	433	8	in	in	ADP
cana-1705	433	9	the	the	DET
cana-1705	433	10	future	future	ADJ
cana-1705	433	11	involve	involve	VERB
cana-1705	433	12	combining	combine	VERB
cana-1705	433	13	reinforcement	reinforcement	NOUN
cana-1705	433	14	learning	learning	NOUN
cana-1705	433	15	algorithms	algorithm	NOUN
cana-1705	433	16	with	with	ADP
cana-1705	433	17	lstm	lstm	NOUN
cana-1705	433	18	models	model	NOUN
cana-1705	433	19	in	in	ADP
cana-1705	433	20	order	order	NOUN
cana-1705	433	21	to	to	PART
cana-1705	433	22	develop	develop	VERB
cana-1705	433	23	adaptive	adaptive	ADJ
cana-1705	433	24	traffic	traffic	NOUN
cana-1705	433	25	control	control	NOUN
cana-1705	433	26	systems	system	NOUN
cana-1705	433	27	.	.	PUNCT
cana-1705	434	1	an	an	DET
cana-1705	434	2	agent	agent	NOUN
cana-1705	434	3	could	could	AUX
cana-1705	434	4	use	use	VERB
cana-1705	434	5	reinforcement	reinforcement	NOUN
cana-1705	434	6	learning	learning	NOUN
cana-1705	434	7	as	as	SCONJ
cana-1705	434	8	it	it	PRON
cana-1705	434	9	would	would	AUX
cana-1705	434	10	automatically	automatically	ADV
cana-1705	434	11	learn	learn	VERB
cana-1705	434	12	how	how	SCONJ
cana-1705	434	13	to	to	PART
cana-1705	434	14	respond	respond	VERB
cana-1705	434	15	by	by	ADP
cana-1705	434	16	choosing	choose	VERB
cana-1705	434	17	the	the	DET
cana-1705	434	18	best	good	ADJ
cana-1705	434	19	next	next	ADJ
cana-1705	434	20	action	action	NOUN
cana-1705	434	21	based	base	VERB
cana-1705	434	22	on	on	ADP
cana-1705	434	23	the	the	DET
cana-1705	434	24	predictions	prediction	NOUN
cana-1705	434	25	from	from	ADP
cana-1705	434	26	the	the	DET
cana-1705	434	27	lstm	lstm	PROPN
cana-1705	434	28	model	model	NOUN
cana-1705	434	29	(	(	PUNCT
cana-1705	434	30	if	if	SCONJ
cana-1705	434	31	designed	design	VERB
cana-1705	434	32	in	in	ADP
cana-1705	434	33	a	a	DET
cana-1705	434	34	way	way	NOUN
cana-1705	434	35	such	such	ADJ
cana-1705	434	36	that	that	SCONJ
cana-1705	434	37	our	our	PRON
cana-1705	434	38	goal	goal	NOUN
cana-1705	434	39	is	be	AUX
cana-1705	434	40	accomplished	accomplish	VERB
cana-1705	434	41	)	)	PUNCT
cana-1705	434	42	.	.	PUNCT
cana-1705	435	1	the	the	DET
cana-1705	435	2	systems	system	NOUN
cana-1705	435	3	could	could	AUX
cana-1705	435	4	potentially	potentially	ADV
cana-1705	435	5	help	help	VERB
cana-1705	435	6	alleviate	alleviate	VERB
cana-1705	435	7	traffic	traffic	NOUN
cana-1705	435	8	congestion	congestion	NOUN
cana-1705	435	9	and	and	CCONJ
cana-1705	435	10	establish	establish	VERB
cana-1705	435	11	smoother	smooth	ADJ
cana-1705	435	12	flow	flow	NOUN
cana-1705	435	13	for	for	ADP
cana-1705	435	14	vehicles	vehicle	NOUN
cana-1705	435	15	in	in	ADP
cana-1705	435	16	urban	urban	ADJ
cana-1705	435	17	areas	area	NOUN
cana-1705	435	18	through	through	ADP
cana-1705	435	19	learning	learn	VERB
cana-1705	435	20	from	from	ADP
cana-1705	435	21	patterns	pattern	NOUN
cana-1705	435	22	of	of	ADP
cana-1705	435	23	traffic	traffic	NOUN
cana-1705	435	24	and	and	CCONJ
cana-1705	435	25	dynamically	dynamically	ADV
cana-1705	435	26	adjusting	adjust	VERB
cana-1705	435	27	traffic	traffic	NOUN
cana-1705	435	28	control	control	NOUN
cana-1705	435	29	strategies	strategy	NOUN
cana-1705	435	30	.	.	PUNCT
cana-1705	436	1	in	in	ADP
cana-1705	436	2	addition	addition	NOUN
cana-1705	436	3	,	,	PUNCT
cana-1705	436	4	the	the	DET
cana-1705	436	5	model	model	NOUN
cana-1705	436	6	could	could	AUX
cana-1705	436	7	benefit	benefit	VERB
cana-1705	436	8	from	from	ADP
cana-1705	436	9	additional	additional	ADJ
cana-1705	436	10	investigation	investigation	NOUN
cana-1705	436	11	into	into	ADP
cana-1705	436	12	external	external	ADJ
cana-1705	436	13	data	datum	NOUN
cana-1705	436	14	sources	source	NOUN
cana-1705	436	15	(	(	PUNCT
cana-1705	436	16	e.g.	e.g.	ADV
cana-1705	436	17	social	social	ADJ
cana-1705	436	18	media	media	NOUN
cana-1705	436	19	feeds	feed	NOUN
cana-1705	436	20	,	,	PUNCT
cana-1705	436	21	satellite	satellite	NOUN
cana-1705	436	22	data	datum	NOUN
cana-1705	436	23	,	,	PUNCT
cana-1705	436	24	internet	internet	NOUN
cana-1705	436	25	of	of	ADP
cana-1705	436	26	things	thing	NOUN
cana-1705	436	27	(	(	PUNCT
cana-1705	436	28	iot	iot	NOUN
cana-1705	436	29	)	)	PUNCT
cana-1705	436	30	sensors	sensor	NOUN
cana-1705	436	31	)	)	PUNCT
cana-1705	436	32	to	to	PART
cana-1705	436	33	improve	improve	VERB
cana-1705	436	34	predictive	predictive	ADJ
cana-1705	436	35	power	power	NOUN
cana-1705	436	36	.	.	PUNCT
cana-1705	437	1	social	social	ADJ
cana-1705	437	2	media	medium	NOUN
cana-1705	437	3	is	be	AUX
cana-1705	437	4	just	just	ADV
cana-1705	437	5	one	one	NUM
cana-1705	437	6	example	example	NOUN
cana-1705	437	7	,	,	PUNCT
cana-1705	437	8	information	information	NOUN
cana-1705	437	9	on	on	ADP
cana-1705	437	10	traffic	traffic	NOUN
cana-1705	437	11	incidents	incident	NOUN
cana-1705	437	12	or	or	CCONJ
cana-1705	437	13	road	road	NOUN
cana-1705	437	14	closures	closure	NOUN
cana-1705	437	15	captured	capture	VERB
cana-1705	437	16	through	through	ADP
cana-1705	437	17	social	social	ADJ
cana-1705	437	18	platforms	platform	NOUN
cana-1705	437	19	today	today	NOUN
cana-1705	437	20	may	may	AUX
cana-1705	437	21	not	not	PART
cana-1705	437	22	be	be	AUX
cana-1705	437	23	delivered	deliver	VERB
cana-1705	437	24	by	by	ADP
cana-1705	437	25	a	a	DET
cana-1705	437	26	traditional	traditional	ADJ
cana-1705	437	27	traffic	traffic	NOUN
cana-1705	437	28	sensors	sensor	NOUN
cana-1705	437	29	.	.	PUNCT
cana-1705	438	1	integrating	integrate	VERB
cana-1705	438	2	this	this	DET
cana-1705	438	3	unstructured	unstructured	ADJ
cana-1705	438	4	information	information	NOUN
cana-1705	438	5	in	in	ADP
cana-1705	438	6	to	to	ADP
cana-1705	438	7	the	the	DET
cana-1705	438	8	lstm	lstm	NOUN
cana-1705	438	9	based	base	VERB
cana-1705	438	10	prediction	prediction	NOUN
cana-1705	438	11	model	model	NOUN
cana-1705	438	12	will	will	AUX
cana-1705	438	13	make	make	VERB
cana-1705	438	14	it	it	PRON
cana-1705	438	15	more	more	ADV
cana-1705	438	16	tolerant	tolerant	ADJ
cana-1705	438	17	of	of	ADP
cana-1705	438	18	sudden	sudden	ADJ
cana-1705	438	19	changes	change	NOUN
cana-1705	438	20	in	in	ADP
cana-1705	438	21	traffic	traffic	NOUN
cana-1705	438	22	,	,	PUNCT
cana-1705	438	23	increasing	increase	VERB
cana-1705	438	24	local	local	ADJ
cana-1705	438	25	effects	effect	NOUN
cana-1705	438	26	and	and	CCONJ
cana-1705	438	27	hence	hence	ADV
cana-1705	438	28	penalize	penalize	VERB
cana-1705	438	29	hidden	hidden	ADJ
cana-1705	438	30	layers	layer	NOUN
cana-1705	438	31	on	on	ADP
cana-1705	438	32	prediction	prediction	NOUN
cana-1705	438	33	.	.	PUNCT
cana-1705	439	1	the	the	DET
cana-1705	439	2	applications	application	NOUN
cana-1705	439	3	of	of	ADP
cana-1705	439	4	this	this	DET
cana-1705	439	5	research	research	NOUN
cana-1705	439	6	are	be	AUX
cana-1705	439	7	widespread	widespread	ADJ
cana-1705	439	8	,	,	PUNCT
cana-1705	439	9	particularly	particularly	ADV
cana-1705	439	10	related	relate	VERB
cana-1705	439	11	to	to	ADP
cana-1705	439	12	urban	urban	ADJ
cana-1705	439	13	transportation	transportation	NOUN
cana-1705	439	14	planners	planner	NOUN
cana-1705	439	15	and	and	CCONJ
cana-1705	439	16	the	the	DET
cana-1705	439	17	policies	policy	NOUN
cana-1705	439	18	they	they	PRON
cana-1705	439	19	would	would	AUX
cana-1705	439	20	should	should	AUX
cana-1705	439	21	implement	implement	VERB
cana-1705	439	22	in	in	ADP
cana-1705	439	23	providing	provide	VERB
cana-1705	439	24	better	well	ADJ
cana-1705	439	25	urban	urban	ADJ
cana-1705	439	26	mobility	mobility	NOUN
cana-1705	439	27	.	.	PUNCT
cana-1705	440	1	being	be	AUX
cana-1705	440	2	able	able	ADJ
cana-1705	440	3	to	to	PART
cana-1705	440	4	predict	predict	VERB
cana-1705	440	5	the	the	DET
cana-1705	440	6	flow	flow	NOUN
cana-1705	440	7	of	of	ADP
cana-1705	440	8	traffic	traffic	NOUN
cana-1705	440	9	in	in	ADP
cana-1705	440	10	real	real	ADJ
cana-1705	440	11	time	time	NOUN
cana-1705	440	12	is	be	AUX
cana-1705	440	13	opening	open	VERB
cana-1705	440	14	new	new	ADJ
cana-1705	440	15	ways	way	NOUN
cana-1705	440	16	for	for	ADP
cana-1705	440	17	how	how	SCONJ
cana-1705	440	18	transportation	transportation	NOUN
cana-1705	440	19	systems	system	NOUN
cana-1705	440	20	can	can	AUX
cana-1705	440	21	be	be	AUX
cana-1705	440	22	optimized	optimize	VERB
cana-1705	440	23	,	,	PUNCT
cana-1705	440	24	congestion	congestion	NOUN
cana-1705	440	25	mitigated	mitigate	VERB
cana-1705	440	26	and	and	CCONJ
cana-1705	440	27	urban	urban	ADJ
cana-1705	440	28	infrastructure	infrastructure	NOUN
cana-1705	440	29	operates	operate	VERB
cana-1705	440	30	efficiently	efficiently	ADV
cana-1705	440	31	.	.	PUNCT
cana-1705	441	1	by	by	ADP
cana-1705	441	2	incorporating	incorporate	VERB
cana-1705	441	3	lstm	lstm	ADJ
cana-1705	441	4	-	-	PUNCT
cana-1705	441	5	powered	power	VERB
cana-1705	441	6	prediction	prediction	NOUN
cana-1705	441	7	models	model	NOUN
cana-1705	441	8	in	in	ADP
cana-1705	441	9	smart	smart	ADJ
cana-1705	441	10	traffic	traffic	NOUN
cana-1705	441	11	management	management	NOUN
cana-1705	441	12	systems	system	NOUN
cana-1705	441	13	,	,	PUNCT
cana-1705	441	14	cities	city	NOUN
cana-1705	441	15	can	can	AUX
cana-1705	441	16	improve	improve	VERB
cana-1705	441	17	how	how	SCONJ
cana-1705	441	18	they	they	PRON
cana-1705	441	19	control	control	VERB
cana-1705	441	20	traffic	traffic	NOUN
cana-1705	441	21	signals	signal	NOUN
cana-1705	441	22	,	,	PUNCT
cana-1705	441	23	divert	divert	NOUN
cana-1705	441	24	vehicles	vehicle	NOUN
cana-1705	441	25	and	and	CCONJ
cana-1705	441	26	handle	handle	VERB
cana-1705	441	27	traffic	traffic	NOUN
cana-1705	441	28	incidents	incident	NOUN
cana-1705	441	29	on	on	ADP
cana-1705	441	30	-	-	PUNCT
cana-1705	441	31	the	the	DET
cana-1705	441	32	-	-	PUNCT
cana-1705	441	33	fly	fly	NOUN
cana-1705	441	34	as	as	ADV
cana-1705	441	35	well	well	ADV
cana-1705	441	36	as	as	ADP
cana-1705	441	37	reduce	reduce	VERB
cana-1705	441	38	travel	travel	NOUN
cana-1705	441	39	times	time	NOUN
cana-1705	441	40	and	and	CCONJ
cana-1705	441	41	lessen	lessen	VERB
cana-1705	441	42	the	the	DET
cana-1705	441	43	impact	impact	NOUN
cana-1705	441	44	of	of	ADP
cana-1705	441	45	congestion	congestion	NOUN
cana-1705	441	46	.	.	PUNCT
cana-1705	442	1	in	in	ADP
cana-1705	442	2	addition	addition	NOUN
cana-1705	442	3	,	,	PUNCT
cana-1705	442	4	because	because	SCONJ
cana-1705	442	5	using	use	VERB
cana-1705	442	6	lstm	lstm	ADJ
cana-1705	442	7	networks	network	NOUN
cana-1705	442	8	for	for	ADP
cana-1705	442	9	traffic	traffic	NOUN
cana-1705	442	10	flow	flow	NOUN
cana-1705	442	11	forecasting	forecasting	NOUN
cana-1705	442	12	is	be	AUX
cana-1705	442	13	just	just	ADV
cana-1705	442	14	one	one	NUM
cana-1705	442	15	example	example	NOUN
cana-1705	442	16	of	of	ADP
cana-1705	442	17	increasing	increase	VERB
cana-1705	442	18	citywide	citywide	ADJ
cana-1705	442	19	and	and	CCONJ
cana-1705	442	20	data	datum	NOUN
cana-1705	442	21	-	-	PUNCT
cana-1705	442	22	driven	drive	VERB
cana-1705	442	23	smartness	smartness	NOUN
cana-1705	442	24	to	to	PART
cana-1705	442	25	improve	improve	VERB
cana-1705	442	26	the	the	DET
cana-1705	442	27	quality	quality	NOUN
cana-1705	442	28	of	of	ADP
cana-1705	442	29	life	life	NOUN
cana-1705	442	30	and	and	CCONJ
cana-1705	442	31	efficiency	efficiency	NOUN
cana-1705	442	32	of	of	ADP
cana-1705	442	33	urban	urban	ADJ
cana-1705	442	34	areas	area	NOUN
cana-1705	442	35	in	in	ADP
cana-1705	442	36	general	general	ADJ
cana-1705	442	37	.	.	PUNCT
cana-1705	443	1	the	the	DET
cana-1705	443	2	cities	city	NOUN
cana-1705	443	3	can	can	AUX
cana-1705	443	4	quickly	quickly	ADV
cana-1705	443	5	learn	learn	VERB
cana-1705	443	6	real	real	ADJ
cana-1705	443	7	-	-	PUNCT
cana-1705	443	8	time	time	NOUN
cana-1705	443	9	traffic	traffic	NOUN
cana-1705	443	10	predictions	prediction	NOUN
cana-1705	443	11	and	and	CCONJ
cana-1705	443	12	can	can	AUX
cana-1705	443	13	make	make	VERB
cana-1705	443	14	better	well	ADJ
cana-1705	443	15	decisions	decision	NOUN
cana-1705	443	16	about	about	ADP
cana-1705	443	17	infrastructure	infrastructure	NOUN
cana-1705	443	18	investments	investment	NOUN
cana-1705	443	19	,	,	PUNCT
cana-1705	443	20	public	public	ADJ
cana-1705	443	21	transit	transit	NOUN
cana-1705	443	22	planning	planning	NOUN
cana-1705	443	23	,	,	PUNCT
cana-1705	443	24	and	and	CCONJ
cana-1705	443	25	the	the	DET
cana-1705	443	26	deployment	deployment	NOUN
cana-1705	443	27	of	of	ADP
cana-1705	443	28	new	new	ADJ
cana-1705	443	29	technologies	technology	NOUN
cana-1705	443	30	such	such	ADJ
cana-1705	443	31	as	as	ADP
cana-1705	443	32	automated	automate	VERB
cana-1705	443	33	vehicles	vehicle	NOUN
cana-1705	443	34	in	in	ADP
cana-1705	443	35	urban	urban	ADJ
cana-1705	443	36	mobility	mobility	NOUN
cana-1705	443	37	planning	plan	VERB
cana-1705	443	38	gang	gang	NOUN
cana-1705	443	39	.	.	PUNCT
cana-1705	444	1	with	with	ADP
cana-1705	444	2	the	the	DET
cana-1705	444	3	ongoing	ongoing	ADJ
cana-1705	444	4	rapid	rapid	ADJ
cana-1705	444	5	urbanization	urbanization	NOUN
cana-1705	444	6	,	,	PUNCT
cana-1705	444	7	and	and	CCONJ
cana-1705	444	8	due	due	ADP
cana-1705	444	9	to	to	ADP
cana-1705	444	10	the	the	DET
cana-1705	444	11	huge	huge	ADJ
cana-1705	444	12	increase	increase	NOUN
cana-1705	444	13	in	in	ADP
cana-1705	444	14	population	population	NOUN
cana-1705	444	15	in	in	ADP
cana-1705	444	16	all	all	DET
cana-1705	444	17	these	these	DET
cana-1705	444	18	cities	city	NOUN
cana-1705	444	19	;	;	PUNCT
cana-1705	444	20	it	it	PRON
cana-1705	444	21	is	be	AUX
cana-1705	444	22	crucial	crucial	ADJ
cana-1705	444	23	that	that	SCONJ
cana-1705	444	24	traffic	traffic	NOUN
cana-1705	444	25	congestion	congestion	NOUN
cana-1705	444	26	flow	flow	NOUN
cana-1705	444	27	will	will	AUX
cana-1705	444	28	be	be	AUX
cana-1705	444	29	managed	manage	VERB
cana-1705	444	30	well	well	ADV
cana-1705	444	31	as	as	SCONJ
cana-1705	444	32	city	city	NOUN
cana-1705	444	33	grows	grow	VERB
cana-1705	444	34	are	be	AUX
cana-1705	444	35	continous	continous	ADJ
cana-1705	444	36	,	,	PUNCT
cana-1705	444	37	year	year	NOUN
cana-1705	444	38	after	after	ADP
cana-1705	444	39	year	year	NOUN
cana-1705	444	40	.	.	PUNCT
cana-1705	445	1	in	in	ADP
cana-1705	445	2	summary	summary	NOUN
cana-1705	445	3	,	,	PUNCT
cana-1705	445	4	this	this	DET
cana-1705	445	5	paper	paper	NOUN
cana-1705	445	6	shows	show	VERB
cana-1705	445	7	that	that	SCONJ
cana-1705	445	8	the	the	DET
cana-1705	445	9	lstm	lstm	PROPN
cana-1705	445	10	model	model	NOUN
cana-1705	445	11	is	be	AUX
cana-1705	445	12	an	an	DET
cana-1705	445	13	effective	effective	ADJ
cana-1705	445	14	method	method	NOUN
cana-1705	445	15	for	for	ADP
cana-1705	445	16	real	real	ADJ
cana-1705	445	17	-	-	PUNCT
cana-1705	445	18	time	time	NOUN
cana-1705	445	19	traffic	traffic	NOUN
cana-1705	445	20	flow	flow	NOUN
cana-1705	445	21	forecasting	forecasting	NOUN
cana-1705	445	22	and	and	CCONJ
cana-1705	445	23	outperforms	outperform	NOUN
cana-1705	445	24	arima	arima	NOUN
cana-1705	445	25	,	,	PUNCT
cana-1705	445	26	svm	svm	NOUN
cana-1705	445	27	and	and	CCONJ
cana-1705	445	28	mlp	mlp	PROPN
cana-1705	445	29	.	.	PUNCT
cana-1705	446	1	given	give	VERB
cana-1705	446	2	the	the	DET
cana-1705	446	3	power	power	NOUN
cana-1705	446	4	of	of	ADP
cana-1705	446	5	lstm	lstm	ADJ
cana-1705	446	6	networks	network	NOUN
cana-1705	446	7	to	to	PART
cana-1705	446	8	model	model	VERB
cana-1705	446	9	spatiotemporal	spatiotemporal	ADJ
cana-1705	446	10	dependencies	dependency	NOUN
cana-1705	446	11	in	in	ADP
cana-1705	446	12	traffic	traffic	NOUN
cana-1705	446	13	flows	flow	NOUN
cana-1705	446	14	,	,	PUNCT
cana-1705	446	15	as	as	ADV
cana-1705	446	16	well	well	ADV
cana-1705	446	17	as	as	ADP
cana-1705	446	18	their	their	PRON
cana-1705	446	19	ability	ability	NOUN
cana-1705	446	20	to	to	PART
cana-1705	446	21	take	take	VERB
cana-1705	446	22	into	into	ADP
cana-1705	446	23	account	account	NOUN
cana-1705	446	24	external	external	ADJ
cana-1705	446	25	variables	variable	NOUN
cana-1705	446	26	such	such	ADJ
cana-1705	446	27	as	as	ADP
cana-1705	446	28	weather	weather	NOUN
cana-1705	446	29	and	and	CCONJ
cana-1705	446	30	incidents	incident	NOUN
cana-1705	446	31	,	,	PUNCT
cana-1705	446	32	they	they	PRON
cana-1705	446	33	are	be	AUX
cana-1705	446	34	ideal	ideal	ADJ
cana-1705	446	35	for	for	ADP
cana-1705	446	36	urban	urban	ADJ
cana-1705	446	37	mobility	mobility	NOUN
cana-1705	446	38	optimization	optimization	NOUN
cana-1705	446	39	.	.	PUNCT
cana-1705	447	1	indeed	indeed	ADV
cana-1705	447	2	,	,	PUNCT
cana-1705	447	3	the	the	DET
cana-1705	447	4	communications	communication	NOUN
cana-1705	447	5	on	on	ADP
cana-1705	447	6	applied	apply	VERB
cana-1705	447	7	nonlinear	nonlinear	ADJ
cana-1705	447	8	analysis	analysis	NOUN
cana-1705	447	9	issn	issn	NOUN
cana-1705	447	10	:	:	PUNCT
cana-1705	447	11	1074	1074	NUM
cana-1705	447	12	-	-	PUNCT
cana-1705	447	13	133x	133x	NUM
cana-1705	447	14	vol	vol	NOUN
cana-1705	447	15	32	32	NUM
cana-1705	447	16	no	no	NOUN
cana-1705	447	17	.	.	NOUN
cana-1705	447	18	2	2	NUM
cana-1705	447	19	(	(	PUNCT
cana-1705	447	20	2025	2025	NUM
cana-1705	447	21	)	)	PUNCT
cana-1705	447	22	26	26	NUM
cana-1705	447	23	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	447	24	results	result	NOUN
cana-1705	447	25	have	have	AUX
cana-1705	447	26	confirmed	confirm	VERB
cana-1705	447	27	that	that	SCONJ
cana-1705	447	28	the	the	DET
cana-1705	447	29	lstm	lstm	NOUN
cana-1705	447	30	model	model	NOUN
cana-1705	447	31	could	could	AUX
cana-1705	447	32	achieve	achieve	VERB
cana-1705	447	33	substantially	substantially	ADV
cana-1705	447	34	better	well	ADJ
cana-1705	447	35	demand	demand	VERB
cana-1705	447	36	forecasts	forecast	NOUN
cana-1705	447	37	than	than	ADP
cana-1705	447	38	baseline	baseline	NOUN
cana-1705	447	39	models	model	NOUN
cana-1705	447	40	under	under	ADP
cana-1705	447	41	different	different	ADJ
cana-1705	447	42	traffic	traffic	NOUN
cana-1705	447	43	conditions	condition	NOUN
cana-1705	447	44	represented	represent	VERB
cana-1705	447	45	by	by	ADP
cana-1705	447	46	the	the	DET
cana-1705	447	47	naturalistic	naturalistic	ADJ
cana-1705	447	48	test	test	NOUN
cana-1705	447	49	data	datum	NOUN
cana-1705	447	50	sets	set	NOUN
cana-1705	447	51	.	.	PUNCT
cana-1705	448	1	they	they	PRON
cana-1705	448	2	report	report	VERB
cana-1705	448	3	that	that	SCONJ
cana-1705	448	4	while	while	SCONJ
cana-1705	448	5	data	datum	NOUN
cana-1705	448	6	quality	quality	NOUN
cana-1705	448	7	and	and	CCONJ
cana-1705	448	8	complexity	complexity	NOUN
cana-1705	448	9	of	of	ADP
cana-1705	448	10	the	the	DET
cana-1705	448	11	computations	computation	NOUN
cana-1705	448	12	involved	involve	VERB
cana-1705	448	13	pose	pose	NOUN
cana-1705	448	14	challenges	challenge	NOUN
cana-1705	448	15	,	,	PUNCT
cana-1705	448	16	their	their	PRON
cana-1705	448	17	findings	finding	NOUN
cana-1705	448	18	suggest	suggest	VERB
cana-1705	448	19	lstms	lstms	NOUN
cana-1705	448	20	can	can	AUX
cana-1705	448	21	substantially	substantially	ADV
cana-1705	448	22	improve	improve	VERB
cana-1705	448	23	our	our	PRON
cana-1705	448	24	urban	urban	ADJ
cana-1705	448	25	-	-	PUNCT
cana-1705	448	26	traffic	traffic	NOUN
cana-1705	448	27	controllers	controller	NOUN
cana-1705	448	28	.	.	PUNCT
cana-1705	449	1	with	with	ADP
cana-1705	449	2	the	the	DET
cana-1705	449	3	ability	ability	NOUN
cana-1705	449	4	to	to	PART
cana-1705	449	5	now	now	ADV
cana-1705	449	6	deliver	deliver	VERB
cana-1705	449	7	on	on	ADP
cana-1705	449	8	-	-	PUNCT
cana-1705	449	9	the	the	DET
cana-1705	449	10	-	-	PUNCT
cana-1705	449	11	fly	fly	NOUN
cana-1705	449	12	predictions	prediction	NOUN
cana-1705	449	13	that	that	PRON
cana-1705	449	14	can	can	AUX
cana-1705	449	15	be	be	AUX
cana-1705	449	16	used	use	VERB
cana-1705	449	17	to	to	ADP
cana-1705	449	18	fine	fine	ADJ
cana-1705	449	19	-	-	PUNCT
cana-1705	449	20	tune	tune	NOUN
cana-1705	449	21	traffic	traffic	NOUN
cana-1705	449	22	signals	signal	NOUN
cana-1705	449	23	and	and	CCONJ
cana-1705	449	24	route	route	NOUN
cana-1705	449	25	vehicles	vehicle	NOUN
cana-1705	449	26	based	base	VERB
cana-1705	449	27	,	,	PUNCT
cana-1705	449	28	lstm	lstm	NOUN
cana-1705	449	29	models	model	NOUN
cana-1705	449	30	offer	offer	VERB
cana-1705	449	31	a	a	DET
cana-1705	449	32	key	key	ADJ
cana-1705	449	33	technological	technological	ADJ
cana-1705	449	34	approach	approach	NOUN
cana-1705	449	35	for	for	ADP
cana-1705	449	36	easing	ease	VERB
cana-1705	449	37	congestion	congestion	NOUN
cana-1705	449	38	and	and	CCONJ
cana-1705	449	39	improving	improve	VERB
cana-1705	449	40	urban	urban	ADJ
cana-1705	449	41	mobility	mobility	NOUN
cana-1705	449	42	.	.	PUNCT
cana-1705	450	1	future	future	ADJ
cana-1705	450	2	work	work	NOUN
cana-1705	450	3	should	should	AUX
cana-1705	450	4	continue	continue	VERB
cana-1705	450	5	to	to	PART
cana-1705	450	6	explore	explore	VERB
cana-1705	450	7	the	the	DET
cana-1705	450	8	enrichment	enrichment	NOUN
cana-1705	450	9	of	of	ADP
cana-1705	450	10	these	these	DET
cana-1705	450	11	models	model	NOUN
cana-1705	450	12	through	through	ADP
cana-1705	450	13	the	the	DET
cana-1705	450	14	combination	combination	NOUN
cana-1705	450	15	with	with	ADP
cana-1705	450	16	reinforcement	reinforcement	NOUN
cana-1705	450	17	learning	learning	NOUN
cana-1705	450	18	,	,	PUNCT
cana-1705	450	19	by	by	ADP
cana-1705	450	20	taking	take	VERB
cana-1705	450	21	advantage	advantage	NOUN
cana-1705	450	22	of	of	ADP
cana-1705	450	23	multi	multi	ADJ
cana-1705	450	24	-	-	ADJ
cana-1705	450	25	modal	modal	ADJ
cana-1705	450	26	transportation	transportation	NOUN
cana-1705	450	27	data	datum	NOUN
cana-1705	450	28	sources	source	NOUN
cana-1705	450	29	or	or	CCONJ
cana-1705	450	30	including	include	VERB
cana-1705	450	31	more	more	ADV
cana-1705	450	32	real	real	ADJ
cana-1705	450	33	time	time	NOUN
cana-1705	450	34	iot	iot	ADJ
cana-1705	450	35	sensors	sensor	NOUN
cana-1705	450	36	and	and	CCONJ
cana-1705	450	37	social	social	ADJ
cana-1705	450	38	media	medium	NOUN
cana-1705	450	39	platforms	platform	NOUN
cana-1705	450	40	.	.	PUNCT
cana-1705	451	1	when	when	SCONJ
cana-1705	451	2	it	it	PRON
cana-1705	451	3	comes	come	VERB
cana-1705	451	4	to	to	ADP
cana-1705	451	5	building	build	VERB
cana-1705	451	6	smart	smart	ADJ
cana-1705	451	7	cities	city	NOUN
cana-1705	451	8	of	of	ADP
cana-1705	451	9	the	the	DET
cana-1705	451	10	future	future	NOUN
cana-1705	451	11	we	we	PRON
cana-1705	451	12	need	need	VERB
cana-1705	451	13	more	more	ADV
cana-1705	451	14	sophisticated	sophisticated	ADJ
cana-1705	451	15	prediction	prediction	NOUN
cana-1705	451	16	systems	system	NOUN
cana-1705	451	17	,	,	PUNCT
cana-1705	451	18	if	if	SCONJ
cana-1705	451	19	traffic	traffic	NOUN
cana-1705	451	20	will	will	AUX
cana-1705	451	21	be	be	AUX
cana-1705	451	22	effectively	effectively	ADV
cana-1705	451	23	managed	manage	VERB
cana-1705	451	24	.	.	PUNCT
cana-1705	452	1	references	reference	NOUN
cana-1705	452	2	[	[	X
cana-1705	452	3	1	1	NUM
cana-1705	452	4	]	]	PUNCT
cana-1705	452	5	naheliya	naheliya	PROPN
cana-1705	452	6	,	,	PUNCT
cana-1705	452	7	bharti	bharti	PROPN
cana-1705	452	8	,	,	PUNCT
cana-1705	452	9	poonam	poonam	PROPN
cana-1705	452	10	redhu	redhu	PROPN
cana-1705	452	11	,	,	PUNCT
cana-1705	452	12	and	and	CCONJ
cana-1705	452	13	kranti	kranti	PROPN
cana-1705	452	14	kumar	kumar	PROPN
cana-1705	452	15	.	.	PUNCT
cana-1705	453	1	"	"	PUNCT
cana-1705	453	2	mfoa	mfoa	PROPN
cana-1705	453	3	-	-	PUNCT
cana-1705	453	4	bi	bi	NOUN
cana-1705	453	5	-	-	ADJ
cana-1705	453	6	lstm	lstm	NOUN
cana-1705	453	7	:	:	PUNCT
cana-1705	453	8	an	an	DET
cana-1705	453	9	optimized	optimize	VERB
cana-1705	453	10	bidirectional	bidirectional	NOUN
cana-1705	453	11	long	long	ADJ
cana-1705	453	12	shortterm	shortterm	PROPN
cana-1705	453	13	memory	memory	NOUN
cana-1705	453	14	model	model	NOUN
cana-1705	453	15	for	for	ADP
cana-1705	453	16	short	short	ADJ
cana-1705	453	17	-	-	PUNCT
cana-1705	453	18	term	term	NOUN
cana-1705	453	19	traffic	traffic	NOUN
cana-1705	453	20	flow	flow	NOUN
cana-1705	453	21	prediction	prediction	NOUN
cana-1705	453	22	.	.	PUNCT
cana-1705	453	23	"	"	PUNCT
cana-1705	454	1	physica	physica	VERB
cana-1705	454	2	a	a	DET
cana-1705	454	3	:	:	PUNCT
cana-1705	454	4	statistical	statistical	ADJ
cana-1705	454	5	mechanics	mechanic	NOUN
cana-1705	454	6	and	and	CCONJ
cana-1705	454	7	its	its	PRON
cana-1705	454	8	applications	application	NOUN
cana-1705	454	9	634	634	NUM
cana-1705	454	10	(	(	PUNCT
cana-1705	454	11	2024	2024	NUM
cana-1705	454	12	):	):	PUNCT
cana-1705	454	13	129448	129448	NUM
cana-1705	454	14	.	.	PUNCT
cana-1705	455	1	[	[	X
cana-1705	455	2	2	2	NUM
cana-1705	455	3	]	]	SYM
cana-1705	455	4	yang	yang	PROPN
cana-1705	455	5	,	,	PUNCT
cana-1705	455	6	zhaohui	zhaohui	PROPN
cana-1705	455	7	,	,	PUNCT
cana-1705	455	8	and	and	CCONJ
cana-1705	455	9	kshitij	kshitij	PROPN
cana-1705	455	10	jerath	jerath	PROPN
cana-1705	455	11	.	.	PUNCT
cana-1705	456	1	"	"	PUNCT
cana-1705	456	2	deep	deep	ADJ
cana-1705	456	3	learning	learning	NOUN
cana-1705	456	4	for	for	ADP
cana-1705	456	5	traffic	traffic	NOUN
cana-1705	456	6	flow	flow	NOUN
cana-1705	456	7	prediction	prediction	NOUN
cana-1705	456	8	using	use	VERB
cana-1705	456	9	cellular	cellular	ADJ
cana-1705	456	10	automata	automata	NOUN
cana-1705	456	11	-	-	PUNCT
cana-1705	456	12	based	base	VERB
cana-1705	456	13	model	model	NOUN
cana-1705	456	14	and	and	CCONJ
cana-1705	456	15	cnn	cnn	PROPN
cana-1705	456	16	-	-	PUNCT
cana-1705	456	17	lstm	lstm	ADJ
cana-1705	456	18	architecture	architecture	NOUN
cana-1705	456	19	.	.	PUNCT
cana-1705	456	20	"	"	PUNCT
cana-1705	457	1	arxiv	arxiv	PROPN
cana-1705	457	2	preprint	preprint	PROPN
cana-1705	457	3	arxiv:2403.18710	arxiv:2403.18710	X
cana-1705	457	4	(	(	PUNCT
cana-1705	457	5	2024	2024	NUM
cana-1705	457	6	)	)	PUNCT
cana-1705	457	7	.	.	PUNCT
cana-1705	458	1	[	[	X
cana-1705	458	2	3	3	NUM
cana-1705	458	3	]	]	SYM
cana-1705	458	4	xu	xu	PROPN
cana-1705	458	5	,	,	PUNCT
cana-1705	458	6	zhihao	zhihao	PROPN
cana-1705	458	7	,	,	PUNCT
cana-1705	458	8	et	et	PROPN
cana-1705	458	9	al	al	PROPN
cana-1705	458	10	.	.	PUNCT
cana-1705	459	1	"	"	PUNCT
cana-1705	459	2	a	a	DET
cana-1705	459	3	fast	fast	ADJ
cana-1705	459	4	spatial	spatial	ADJ
cana-1705	459	5	-	-	PUNCT
cana-1705	459	6	temporal	temporal	ADJ
cana-1705	459	7	information	information	NOUN
cana-1705	459	8	compression	compression	NOUN
cana-1705	459	9	algorithm	algorithm	NOUN
cana-1705	459	10	for	for	ADP
cana-1705	459	11	online	online	ADJ
cana-1705	459	12	real	real	ADJ
cana-1705	459	13	-	-	PUNCT
cana-1705	459	14	time	time	NOUN
cana-1705	459	15	forecasting	forecasting	NOUN
cana-1705	459	16	of	of	ADP
cana-1705	459	17	traffic	traffic	NOUN
cana-1705	459	18	flow	flow	NOUN
cana-1705	459	19	with	with	ADP
cana-1705	459	20	complex	complex	ADJ
cana-1705	459	21	nonlinear	nonlinear	ADJ
cana-1705	459	22	patterns	pattern	NOUN
cana-1705	459	23	.	.	PUNCT
cana-1705	459	24	"	"	PUNCT
cana-1705	460	1	chaos	chaos	NOUN
cana-1705	460	2	,	,	PUNCT
cana-1705	460	3	solitons	soliton	NOUN
cana-1705	460	4	&	&	CCONJ
cana-1705	460	5	fractals	fractal	NOUN
cana-1705	460	6	182	182	NUM
cana-1705	460	7	(	(	PUNCT
cana-1705	460	8	2024	2024	NUM
cana-1705	460	9	):	):	PUNCT
cana-1705	460	10	114852	114852	NUM
cana-1705	460	11	.	.	PUNCT
cana-1705	461	1	[	[	X
cana-1705	461	2	4	4	NUM
cana-1705	461	3	]	]	X
cana-1705	461	4	kaur	kaur	NOUN
cana-1705	461	5	,	,	PUNCT
cana-1705	461	6	gaganbir	gaganbir	NOUN
cana-1705	461	7	,	,	PUNCT
cana-1705	461	8	surender	surender	PROPN
cana-1705	461	9	k.	k.	PROPN
cana-1705	461	10	grewal	grewal	PROPN
cana-1705	461	11	,	,	PUNCT
cana-1705	461	12	and	and	CCONJ
cana-1705	461	13	aarti	aarti	PROPN
cana-1705	461	14	jain	jain	PROPN
cana-1705	461	15	.	.	PUNCT
cana-1705	462	1	"	"	PUNCT
cana-1705	462	2	federated	federated	ADJ
cana-1705	462	3	learning	learning	NOUN
cana-1705	462	4	based	base	VERB
cana-1705	462	5	spatio	spatio	PROPN
cana-1705	462	6	-	-	PUNCT
cana-1705	462	7	temporal	temporal	ADJ
cana-1705	462	8	framework	framework	NOUN
cana-1705	462	9	for	for	ADP
cana-1705	462	10	real	real	ADJ
cana-1705	462	11	-	-	PUNCT
cana-1705	462	12	time	time	NOUN
cana-1705	462	13	traffic	traffic	NOUN
cana-1705	462	14	prediction	prediction	NOUN
cana-1705	462	15	.	.	PUNCT
cana-1705	462	16	"	"	PUNCT
cana-1705	463	1	wireless	wireless	ADJ
cana-1705	463	2	personal	personal	ADJ
cana-1705	463	3	communications	communication	NOUN
cana-1705	463	4	136.2	136.2	NUM
cana-1705	463	5	(	(	PUNCT
cana-1705	463	6	2024	2024	NUM
cana-1705	463	7	):	):	PUNCT
cana-1705	463	8	849	849	NUM
cana-1705	463	9	-	-	SYM
cana-1705	463	10	865	865	NUM
cana-1705	463	11	.	.	PUNCT
cana-1705	464	1	[	[	X
cana-1705	464	2	5	5	NUM
cana-1705	464	3	]	]	X
cana-1705	464	4	guo	guo	PROPN
cana-1705	464	5	,	,	PUNCT
cana-1705	464	6	chang	chang	PROPN
cana-1705	464	7	,	,	PUNCT
cana-1705	464	8	jianfeng	jianfeng	PROPN
cana-1705	464	9	zhu	zhu	PROPN
cana-1705	464	10	,	,	PUNCT
cana-1705	464	11	and	and	CCONJ
cana-1705	464	12	xiaoming	xiaoming	PROPN
cana-1705	464	13	wang	wang	PROPN
cana-1705	464	14	.	.	PUNCT
cana-1705	465	1	"	"	PUNCT
cana-1705	465	2	mvhs	mvhs	NOUN
cana-1705	465	3	-	-	PUNCT
cana-1705	465	4	lstm	lstm	NOUN
cana-1705	465	5	:	:	PUNCT
cana-1705	465	6	the	the	DET
cana-1705	465	7	comprehensive	comprehensive	ADJ
cana-1705	465	8	traffic	traffic	NOUN
cana-1705	465	9	flow	flow	NOUN
cana-1705	465	10	prediction	prediction	NOUN
cana-1705	465	11	based	base	VERB
cana-1705	465	12	on	on	ADP
cana-1705	465	13	improved	improved	ADJ
cana-1705	465	14	lstm	lstm	NOUN
cana-1705	465	15	via	via	ADP
cana-1705	465	16	multiple	multiple	ADJ
cana-1705	465	17	variables	variable	NOUN
cana-1705	465	18	heuristic	heuristic	ADJ
cana-1705	465	19	selection	selection	NOUN
cana-1705	465	20	.	.	PUNCT
cana-1705	465	21	"	"	PUNCT
cana-1705	465	22	applied	apply	VERB
cana-1705	465	23	sciences	science	NOUN
cana-1705	465	24	14.7	14.7	NUM
cana-1705	465	25	(	(	PUNCT
cana-1705	465	26	2024	2024	NUM
cana-1705	465	27	):	):	PUNCT
cana-1705	465	28	2959	2959	NUM
cana-1705	465	29	.	.	PUNCT
cana-1705	466	1	[	[	X
cana-1705	466	2	6	6	NUM
cana-1705	466	3	]	]	X
cana-1705	466	4	al	al	PROPN
cana-1705	466	5	-	-	PUNCT
cana-1705	466	6	huthaifi	huthaifi	PROPN
cana-1705	466	7	,	,	PUNCT
cana-1705	466	8	rasha	rasha	PROPN
cana-1705	466	9	,	,	PUNCT
cana-1705	466	10	et	et	PROPN
cana-1705	466	11	al	al	PROPN
cana-1705	466	12	.	.	PUNCT
cana-1705	467	1	"	"	PUNCT
cana-1705	467	2	fedagat	fedagat	ADJ
cana-1705	467	3	:	:	PUNCT
cana-1705	467	4	real	real	ADJ
cana-1705	467	5	-	-	PUNCT
cana-1705	467	6	time	time	NOUN
cana-1705	467	7	traffic	traffic	NOUN
cana-1705	467	8	flow	flow	NOUN
cana-1705	467	9	prediction	prediction	NOUN
cana-1705	467	10	based	base	VERB
cana-1705	467	11	on	on	ADP
cana-1705	467	12	federated	federated	ADJ
cana-1705	467	13	community	community	NOUN
cana-1705	467	14	and	and	CCONJ
cana-1705	467	15	adaptive	adaptive	ADJ
cana-1705	467	16	graph	graph	NOUN
cana-1705	467	17	attention	attention	NOUN
cana-1705	467	18	network	network	NOUN
cana-1705	467	19	.	.	PUNCT
cana-1705	467	20	"	"	PUNCT
cana-1705	468	1	information	information	NOUN
cana-1705	468	2	sciences	science	NOUN
cana-1705	468	3	667	667	NUM
cana-1705	468	4	(	(	PUNCT
cana-1705	468	5	2024	2024	NUM
cana-1705	468	6	):	):	PUNCT
cana-1705	468	7	120482	120482	NUM
cana-1705	468	8	.	.	PUNCT
cana-1705	469	1	[	[	X
cana-1705	469	2	7	7	NUM
cana-1705	469	3	]	]	X
cana-1705	469	4	zhang	zhang	PROPN
cana-1705	469	5	,	,	PUNCT
cana-1705	469	6	ce	ce	PROPN
cana-1705	469	7	,	,	PUNCT
cana-1705	469	8	guangyuan	guangyuan	PROPN
cana-1705	469	9	pan	pan	PROPN
cana-1705	469	10	,	,	PUNCT
cana-1705	469	11	and	and	CCONJ
cana-1705	469	12	liping	liping	PROPN
cana-1705	469	13	fu	fu	PROPN
cana-1705	469	14	.	.	PUNCT
cana-1705	470	1	"	"	PUNCT
cana-1705	470	2	real	real	ADJ
cana-1705	470	3	-	-	PUNCT
cana-1705	470	4	time	time	NOUN
cana-1705	470	5	intersection	intersection	NOUN
cana-1705	470	6	turning	turning	NOUN
cana-1705	470	7	movement	movement	NOUN
cana-1705	470	8	flow	flow	NOUN
cana-1705	470	9	forecasting	forecasting	NOUN
cana-1705	470	10	using	use	VERB
cana-1705	470	11	a	a	DET
cana-1705	470	12	parallel	parallel	ADJ
cana-1705	470	13	bidirectional	bidirectional	ADJ
cana-1705	470	14	long	long	ADJ
cana-1705	470	15	short	short	ADJ
cana-1705	470	16	-	-	PUNCT
cana-1705	470	17	term	term	NOUN
cana-1705	470	18	memory	memory	NOUN
cana-1705	470	19	neural	neural	ADJ
cana-1705	470	20	network	network	NOUN
cana-1705	470	21	model	model	NOUN
cana-1705	470	22	.	.	PUNCT
cana-1705	470	23	"	"	PUNCT
cana-1705	471	1	transportation	transportation	NOUN
cana-1705	471	2	research	research	NOUN
cana-1705	471	3	record	record	NOUN
cana-1705	471	4	2678.2	2678.2	NUM
cana-1705	471	5	(	(	PUNCT
cana-1705	471	6	2024	2024	NUM
cana-1705	471	7	):	):	PUNCT
cana-1705	471	8	167	167	NUM
cana-1705	471	9	-	-	SYM
cana-1705	471	10	183	183	NUM
cana-1705	471	11	.	.	PUNCT
cana-1705	472	1	[	[	X
cana-1705	472	2	8	8	NUM
cana-1705	472	3	]	]	X
cana-1705	472	4	shi	shi	PROPN
cana-1705	472	5	,	,	PUNCT
cana-1705	472	6	mo	mo	PROPN
cana-1705	472	7	,	,	PUNCT
cana-1705	472	8	et	et	PROPN
cana-1705	472	9	al	al	PROPN
cana-1705	472	10	.	.	PUNCT
cana-1705	472	11	"	"	PUNCT
cana-1705	472	12	prediction	prediction	NOUN
cana-1705	472	13	and	and	CCONJ
cana-1705	472	14	analysis	analysis	NOUN
cana-1705	472	15	of	of	ADP
cana-1705	472	16	elevator	elevator	NOUN
cana-1705	472	17	traffic	traffic	NOUN
cana-1705	472	18	flow	flow	NOUN
cana-1705	472	19	under	under	ADP
cana-1705	472	20	the	the	DET
cana-1705	472	21	lstm	lstm	ADJ
cana-1705	472	22	neural	neural	ADJ
cana-1705	472	23	network	network	NOUN
cana-1705	472	24	.	.	PUNCT
cana-1705	472	25	"	"	PUNCT
cana-1705	473	1	intelligent	intelligent	ADJ
cana-1705	473	2	control	control	NOUN
cana-1705	473	3	and	and	CCONJ
cana-1705	473	4	automation	automation	NOUN
cana-1705	473	5	15.2	15.2	NUM
cana-1705	473	6	(	(	PUNCT
cana-1705	473	7	2024	2024	NUM
cana-1705	473	8	):	):	PUNCT
cana-1705	473	9	63	63	NUM
cana-1705	473	10	-	-	SYM
cana-1705	473	11	82	82	NUM
cana-1705	473	12	.	.	PUNCT
cana-1705	474	1	[	[	X
cana-1705	474	2	9	9	NUM
cana-1705	474	3	]	]	SYM
cana-1705	474	4	li	li	PROPN
cana-1705	474	5	,	,	PUNCT
cana-1705	474	6	zhihong	zhihong	PROPN
cana-1705	474	7	,	,	PUNCT
cana-1705	474	8	et	et	PROPN
cana-1705	474	9	al	al	PROPN
cana-1705	474	10	.	.	PUNCT
cana-1705	474	11	"	"	PUNCT
cana-1705	474	12	fusion	fusion	NOUN
cana-1705	474	13	attention	attention	NOUN
cana-1705	474	14	mechanism	mechanism	NOUN
cana-1705	474	15	bidirectional	bidirectional	ADJ
cana-1705	474	16	lstm	lstm	NOUN
cana-1705	474	17	for	for	ADP
cana-1705	474	18	short	short	ADJ
cana-1705	474	19	-	-	PUNCT
cana-1705	474	20	term	term	NOUN
cana-1705	474	21	traffic	traffic	NOUN
cana-1705	474	22	flow	flow	NOUN
cana-1705	474	23	prediction	prediction	NOUN
cana-1705	474	24	.	.	PUNCT
cana-1705	474	25	"	"	PUNCT
cana-1705	475	1	journal	journal	NOUN
cana-1705	475	2	of	of	ADP
cana-1705	475	3	intelligent	intelligent	ADJ
cana-1705	475	4	transportation	transportation	NOUN
cana-1705	475	5	systems	system	NOUN
cana-1705	475	6	28.4	28.4	NUM
cana-1705	475	7	(	(	PUNCT
cana-1705	475	8	2024	2024	NUM
cana-1705	475	9	):	):	PUNCT
cana-1705	475	10	511	511	NUM
cana-1705	475	11	-	-	SYM
cana-1705	475	12	524	524	NUM
cana-1705	475	13	.	.	PUNCT
cana-1705	476	1	[	[	X
cana-1705	476	2	10	10	NUM
cana-1705	476	3	]	]	X
cana-1705	476	4	soni	soni	ADJ
cana-1705	476	5	,	,	PUNCT
cana-1705	476	6	ravikant	ravikant	ADJ
cana-1705	476	7	,	,	PUNCT
cana-1705	476	8	partha	partha	PROPN
cana-1705	476	9	roy	roy	PROPN
cana-1705	476	10	,	,	PUNCT
cana-1705	476	11	and	and	CCONJ
cana-1705	476	12	kapil	kapil	PROPN
cana-1705	476	13	kumar	kumar	PROPN
cana-1705	476	14	nagwanshi	nagwanshi	PROPN
cana-1705	476	15	.	.	PUNCT
cana-1705	477	1	"	"	PUNCT
cana-1705	477	2	wknn	wknn	NOUN
cana-1705	477	3	-	-	PUNCT
cana-1705	477	4	fdcnn	fdcnn	PROPN
cana-1705	477	5	method	method	NOUN
cana-1705	477	6	for	for	ADP
cana-1705	477	7	big	big	ADJ
cana-1705	477	8	data	datum	NOUN
cana-1705	477	9	driven	drive	VERB
cana-1705	477	10	traffic	traffic	NOUN
cana-1705	477	11	flow	flow	NOUN
cana-1705	477	12	prediction	prediction	NOUN
cana-1705	477	13	in	in	ADP
cana-1705	477	14	its	its	PRON
cana-1705	477	15	.	.	PUNCT
cana-1705	477	16	"	"	PUNCT
cana-1705	477	17	multimedia	multimedia	NOUN
cana-1705	477	18	tools	tool	NOUN
cana-1705	477	19	and	and	CCONJ
cana-1705	477	20	applications	application	NOUN
cana-1705	477	21	83.9	83.9	NUM
cana-1705	477	22	(	(	PUNCT
cana-1705	477	23	2024	2024	NUM
cana-1705	477	24	):	):	PUNCT
cana-1705	477	25	25261	25261	NUM
cana-1705	477	26	-	-	SYM
cana-1705	477	27	25286	25286	NUM
cana-1705	477	28	.	.	PUNCT
cana-1705	478	1	[	[	X
cana-1705	478	2	11	11	NUM
cana-1705	478	3	]	]	X
cana-1705	478	4	wang	wang	PROPN
cana-1705	478	5	,	,	PUNCT
cana-1705	478	6	yinpu	yinpu	PROPN
cana-1705	478	7	,	,	PUNCT
cana-1705	478	8	et	et	PROPN
cana-1705	478	9	al	al	PROPN
cana-1705	478	10	.	.	PUNCT
cana-1705	479	1	"	"	PUNCT
cana-1705	479	2	a	a	DET
cana-1705	479	3	hybrid	hybrid	ADJ
cana-1705	479	4	framework	framework	NOUN
cana-1705	479	5	combining	combine	VERB
cana-1705	479	6	lstm	lstm	PROPN
cana-1705	479	7	nn	nn	PROPN
cana-1705	479	8	and	and	CCONJ
cana-1705	479	9	bnn	bnn	PROPN
cana-1705	479	10	for	for	ADP
cana-1705	479	11	short	short	ADJ
cana-1705	479	12	-	-	PUNCT
cana-1705	479	13	term	term	NOUN
cana-1705	479	14	traffic	traffic	NOUN
cana-1705	479	15	flow	flow	NOUN
cana-1705	479	16	prediction	prediction	NOUN
cana-1705	479	17	and	and	CCONJ
cana-1705	479	18	uncertainty	uncertainty	NOUN
cana-1705	479	19	quantification	quantification	NOUN
cana-1705	479	20	.	.	PUNCT
cana-1705	479	21	"	"	PUNCT
cana-1705	480	1	ksce	ksce	PROPN
cana-1705	480	2	journal	journal	NOUN
cana-1705	480	3	of	of	ADP
cana-1705	480	4	civil	civil	ADJ
cana-1705	480	5	engineering	engineering	NOUN
cana-1705	480	6	28.1	28.1	NUM
cana-1705	480	7	(	(	PUNCT
cana-1705	480	8	2024	2024	NUM
cana-1705	480	9	):	):	PUNCT
cana-1705	480	10	363	363	NUM
cana-1705	480	11	-	-	SYM
cana-1705	480	12	374	374	NUM
cana-1705	480	13	.	.	PUNCT
cana-1705	481	1	[	[	X
cana-1705	481	2	12	12	NUM
cana-1705	481	3	]	]	PUNCT
cana-1705	481	4	sarooraj	sarooraj	VERB
cana-1705	481	5	,	,	PUNCT
cana-1705	481	6	r.	r.	PROPN
cana-1705	481	7	b.	b.	PROPN
cana-1705	481	8	,	,	PUNCT
cana-1705	481	9	and	and	CCONJ
cana-1705	481	10	s.	s.	PROPN
cana-1705	481	11	prayla	prayla	PROPN
cana-1705	481	12	shyry	shyry	PROPN
cana-1705	481	13	.	.	PUNCT
cana-1705	482	1	"	"	PUNCT
cana-1705	482	2	analysis	analysis	NOUN
cana-1705	482	3	of	of	ADP
cana-1705	482	4	traffic	traffic	NOUN
cana-1705	482	5	flow	flow	NOUN
cana-1705	482	6	prediction	prediction	NOUN
cana-1705	482	7	from	from	ADP
cana-1705	482	8	spatial	spatial	ADJ
cana-1705	482	9	-	-	PUNCT
cana-1705	482	10	temporal	temporal	ADJ
cana-1705	482	11	data	datum	NOUN
cana-1705	482	12	using	use	VERB
cana-1705	482	13	hybrid	hybrid	ADJ
cana-1705	482	14	gsa	gsa	PROPN
cana-1705	482	15	-	-	PUNCT
cana-1705	482	16	adam	adam	PROPN
cana-1705	482	17	optimizer	optimizer	NOUN
cana-1705	482	18	based	base	VERB
cana-1705	482	19	lstm	lstm	PROPN
cana-1705	482	20	network	network	NOUN
cana-1705	482	21	for	for	ADP
cana-1705	482	22	intelligent	intelligent	ADJ
cana-1705	482	23	transport	transport	NOUN
cana-1705	482	24	system	system	NOUN
cana-1705	482	25	.	.	PUNCT
cana-1705	482	26	"	"	PUNCT
cana-1705	482	27	multimedia	multimedia	NOUN
cana-1705	482	28	tools	tool	NOUN
cana-1705	482	29	and	and	CCONJ
cana-1705	482	30	applications	application	NOUN
cana-1705	482	31	83.6	83.6	NUM
cana-1705	482	32	(	(	PUNCT
cana-1705	482	33	2024	2024	NUM
cana-1705	482	34	):	):	PUNCT
cana-1705	482	35	16735	16735	NUM
cana-1705	482	36	-	-	SYM
cana-1705	482	37	16761	16761	NUM
cana-1705	482	38	.	.	PUNCT
cana-1705	483	1	[	[	X
cana-1705	483	2	13	13	NUM
cana-1705	483	3	]	]	SYM
cana-1705	483	4	xia	xia	PROPN
cana-1705	483	5	,	,	PUNCT
cana-1705	483	6	zhichao	zhichao	ADV
cana-1705	483	7	,	,	PUNCT
cana-1705	483	8	et	et	PROPN
cana-1705	483	9	al	al	PROPN
cana-1705	483	10	.	.	PUNCT
cana-1705	484	1	"	"	PUNCT
cana-1705	484	2	dynamic	dynamic	ADJ
cana-1705	484	3	spatial	spatial	ADJ
cana-1705	484	4	–	–	PUNCT
cana-1705	484	5	temporal	temporal	ADJ
cana-1705	484	6	graph	graph	NOUN
cana-1705	484	7	convolutional	convolutional	ADJ
cana-1705	484	8	recurrent	recurrent	ADJ
cana-1705	484	9	networks	network	NOUN
cana-1705	484	10	for	for	ADP
cana-1705	484	11	traffic	traffic	NOUN
cana-1705	484	12	flow	flow	NOUN
cana-1705	484	13	forecasting	forecasting	NOUN
cana-1705	484	14	.	.	PUNCT
cana-1705	484	15	"	"	PUNCT
cana-1705	485	1	expert	expert	ADJ
cana-1705	485	2	systems	system	NOUN
cana-1705	485	3	with	with	ADP
cana-1705	485	4	applications	application	NOUN
cana-1705	485	5	240	240	NUM
cana-1705	485	6	(	(	PUNCT
cana-1705	485	7	2024	2024	NUM
cana-1705	485	8	):	):	PUNCT
cana-1705	485	9	122381	122381	NUM
cana-1705	485	10	.	.	PUNCT
cana-1705	486	1	[	[	X
cana-1705	486	2	14	14	NUM
cana-1705	486	3	]	]	X
cana-1705	486	4	harrou	harrou	NOUN
cana-1705	486	5	,	,	PUNCT
cana-1705	486	6	fouzi	fouzi	PROPN
cana-1705	486	7	,	,	PUNCT
cana-1705	486	8	et	et	PROPN
cana-1705	486	9	al	al	PROPN
cana-1705	486	10	.	.	PUNCT
cana-1705	487	1	"	"	PUNCT
cana-1705	487	2	enhancing	enhance	VERB
cana-1705	487	3	road	road	NOUN
cana-1705	487	4	traffic	traffic	NOUN
cana-1705	487	5	flow	flow	NOUN
cana-1705	487	6	prediction	prediction	NOUN
cana-1705	487	7	with	with	ADP
cana-1705	487	8	improved	improved	ADJ
cana-1705	487	9	deep	deep	ADJ
cana-1705	487	10	learning	learning	NOUN
cana-1705	487	11	using	use	VERB
cana-1705	487	12	wavelet	wavelet	NOUN
cana-1705	487	13	transforms	transform	NOUN
cana-1705	487	14	.	.	PUNCT
cana-1705	487	15	"	"	PUNCT
cana-1705	487	16	results	result	NOUN
cana-1705	487	17	in	in	ADP
cana-1705	487	18	engineering	engineering	NOUN
cana-1705	487	19	(	(	PUNCT
cana-1705	487	20	2024	2024	NUM
cana-1705	487	21	):	):	PUNCT
cana-1705	487	22	102342	102342	NUM
cana-1705	487	23	.	.	PUNCT
cana-1705	488	1	[	[	X
cana-1705	488	2	15	15	NUM
cana-1705	488	3	]	]	X
cana-1705	488	4	wang	wang	PROPN
cana-1705	488	5	,	,	PUNCT
cana-1705	488	6	xinqiang	xinqiang	PROPN
cana-1705	488	7	,	,	PUNCT
cana-1705	488	8	yihui	yihui	PROPN
cana-1705	488	9	shang	shang	PROPN
cana-1705	488	10	,	,	PUNCT
cana-1705	488	11	and	and	CCONJ
cana-1705	488	12	guoyan	guoyan	PROPN
cana-1705	488	13	li	li	PROPN
cana-1705	488	14	.	.	PUNCT
cana-1705	489	1	"	"	PUNCT
cana-1705	489	2	dtm	dtm	PROPN
cana-1705	489	3	-	-	PUNCT
cana-1705	489	4	gcn	gcn	NOUN
cana-1705	489	5	:	:	PUNCT
cana-1705	489	6	a	a	DET
cana-1705	489	7	traffic	traffic	NOUN
cana-1705	489	8	flow	flow	NOUN
cana-1705	489	9	prediction	prediction	NOUN
cana-1705	489	10	model	model	NOUN
cana-1705	489	11	based	base	VERB
cana-1705	489	12	on	on	ADP
cana-1705	489	13	dynamic	dynamic	ADJ
cana-1705	489	14	graph	graph	NOUN
cana-1705	489	15	convolutional	convolutional	ADJ
cana-1705	489	16	network	network	NOUN
cana-1705	489	17	.	.	PUNCT
cana-1705	489	18	"	"	PUNCT
cana-1705	490	1	multimedia	multimedia	NOUN
cana-1705	490	2	tools	tool	NOUN
cana-1705	490	3	and	and	CCONJ
cana-1705	490	4	applications	application	NOUN
cana-1705	490	5	(	(	PUNCT
cana-1705	490	6	2024	2024	NUM
cana-1705	490	7	):	):	PUNCT
cana-1705	490	8	1	1	NUM
cana-1705	490	9	-	-	SYM
cana-1705	490	10	17	17	NUM
cana-1705	490	11	.	.	PUNCT
cana-1705	491	1	[	[	X
cana-1705	491	2	16	16	NUM
cana-1705	491	3	]	]	PUNCT
cana-1705	491	4	moumen	mouman	NOUN
cana-1705	491	5	,	,	PUNCT
cana-1705	491	6	idriss	idriss	PROPN
cana-1705	491	7	,	,	PUNCT
cana-1705	491	8	et	et	PROPN
cana-1705	491	9	al	al	PROPN
cana-1705	491	10	.	.	PUNCT
cana-1705	492	1	"	"	PUNCT
cana-1705	492	2	distributed	distribute	VERB
cana-1705	492	3	multi	multi	ADJ
cana-1705	492	4	-	-	ADJ
cana-1705	492	5	intersection	intersection	ADJ
cana-1705	492	6	traffic	traffic	NOUN
cana-1705	492	7	flow	flow	NOUN
cana-1705	492	8	prediction	prediction	NOUN
cana-1705	492	9	using	use	VERB
cana-1705	492	10	deep	deep	ADJ
cana-1705	492	11	learning	learning	NOUN
cana-1705	492	12	.	.	PUNCT
cana-1705	492	13	"	"	PUNCT
cana-1705	493	1	e3s	e3s	PROPN
cana-1705	493	2	web	web	NOUN
cana-1705	493	3	of	of	ADP
cana-1705	493	4	conferences	conference	NOUN
cana-1705	493	5	.	.	PUNCT
cana-1705	494	1	vol	vol	NOUN
cana-1705	494	2	.	.	PUNCT
cana-1705	495	1	477	477	NUM
cana-1705	495	2	.	.	PUNCT
cana-1705	496	1	edp	edp	PROPN
cana-1705	496	2	sciences	sciences	PROPN
cana-1705	496	3	,	,	PUNCT
cana-1705	496	4	2024	2024	NUM
cana-1705	496	5	.	.	PUNCT
cana-1705	497	1	communications	communication	NOUN
cana-1705	497	2	on	on	ADP
cana-1705	497	3	applied	apply	VERB
cana-1705	497	4	nonlinear	nonlinear	ADJ
cana-1705	497	5	analysis	analysis	NOUN
cana-1705	497	6	issn	issn	NOUN
cana-1705	497	7	:	:	PUNCT
cana-1705	497	8	1074	1074	NUM
cana-1705	497	9	-	-	PUNCT
cana-1705	497	10	133x	133x	NUM
cana-1705	497	11	vol	vol	NOUN
cana-1705	497	12	32	32	NUM
cana-1705	497	13	no	no	NOUN
cana-1705	497	14	.	.	NOUN
cana-1705	497	15	2	2	NUM
cana-1705	497	16	(	(	PUNCT
cana-1705	497	17	2025	2025	NUM
cana-1705	497	18	)	)	PUNCT
cana-1705	497	19	27	27	NUM
cana-1705	497	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1705	498	1	[	[	X
cana-1705	498	2	17	17	NUM
cana-1705	498	3	]	]	X
cana-1705	498	4	chaoura	chaoura	NOUN
cana-1705	498	5	,	,	PUNCT
cana-1705	498	6	chaimaa	chaimaa	PROPN
cana-1705	498	7	,	,	PUNCT
cana-1705	498	8	hajar	hajar	PROPN
cana-1705	498	9	lazar	lazar	PROPN
cana-1705	498	10	,	,	PUNCT
cana-1705	498	11	and	and	CCONJ
cana-1705	498	12	zahi	zahi	NUM
cana-1705	498	13	jarir	jarir	NOUN
cana-1705	498	14	.	.	PUNCT
cana-1705	499	1	"	"	PUNCT
cana-1705	499	2	traffic	traffic	NOUN
cana-1705	499	3	flow	flow	NOUN
cana-1705	499	4	prediction	prediction	NOUN
cana-1705	499	5	at	at	ADP
cana-1705	499	6	intersections	intersection	NOUN
cana-1705	499	7	:	:	PUNCT
cana-1705	499	8	enhancing	enhance	VERB
cana-1705	499	9	with	with	ADP
cana-1705	499	10	a	a	DET
cana-1705	499	11	hybrid	hybrid	ADJ
cana-1705	499	12	lstm	lstm	ADJ
cana-1705	499	13	-	-	PUNCT
cana-1705	499	14	pso	pso	NOUN
cana-1705	499	15	approach	approach	NOUN
cana-1705	499	16	.	.	PUNCT
cana-1705	499	17	"	"	PUNCT
cana-1705	500	1	international	international	ADJ
cana-1705	500	2	journal	journal	NOUN
cana-1705	500	3	of	of	ADP
cana-1705	500	4	advanced	advanced	ADJ
cana-1705	500	5	computer	computer	NOUN
cana-1705	500	6	science	science	NOUN
cana-1705	500	7	&	&	CCONJ
cana-1705	500	8	applications	application	NOUN
cana-1705	500	9	15.5	15.5	NUM
cana-1705	500	10	(	(	PUNCT
cana-1705	500	11	2024	2024	NUM
cana-1705	500	12	)	)	PUNCT
cana-1705	500	13	.	.	PUNCT
cana-1705	501	1	[	[	X
cana-1705	501	2	18	18	NUM
cana-1705	501	3	]	]	X
cana-1705	501	4	kumari	kumari	PROPN
cana-1705	501	5	,	,	PUNCT
cana-1705	501	6	mamta	mamta	PROPN
cana-1705	501	7	,	,	PUNCT
cana-1705	501	8	et	et	PROPN
cana-1705	501	9	al	al	PROPN
cana-1705	501	10	.	.	PUNCT
cana-1705	502	1	"	"	PUNCT
cana-1705	502	2	utilizing	utilize	VERB
cana-1705	502	3	federated	federated	ADJ
cana-1705	502	4	learning	learning	NOUN
cana-1705	502	5	for	for	ADP
cana-1705	502	6	enhanced	enhanced	ADJ
cana-1705	502	7	real	real	ADJ
cana-1705	502	8	-	-	PUNCT
cana-1705	502	9	time	time	NOUN
cana-1705	502	10	traffic	traffic	NOUN
cana-1705	502	11	prediction	prediction	NOUN
cana-1705	502	12	in	in	ADP
cana-1705	502	13	smart	smart	ADJ
cana-1705	502	14	urban	urban	ADJ
cana-1705	502	15	environments	environment	NOUN
cana-1705	502	16	.	.	PUNCT
cana-1705	502	17	"	"	PUNCT
cana-1705	503	1	international	international	ADJ
cana-1705	503	2	journal	journal	NOUN
cana-1705	503	3	of	of	ADP
cana-1705	503	4	advanced	advanced	ADJ
cana-1705	503	5	computer	computer	NOUN
cana-1705	503	6	science	science	NOUN
cana-1705	503	7	&	&	CCONJ
cana-1705	503	8	applications	application	NOUN
cana-1705	503	9	15.2	15.2	NUM
cana-1705	503	10	(	(	PUNCT
cana-1705	503	11	2024	2024	NUM
cana-1705	503	12	)	)	PUNCT
cana-1705	503	13	.	.	PUNCT
cana-1705	504	1	[	[	X
cana-1705	504	2	19	19	NUM
cana-1705	504	3	]	]	SYM
cana-1705	504	4	xu	xu	PROPN
cana-1705	504	5	,	,	PUNCT
cana-1705	504	6	zheng	zheng	PROPN
cana-1705	504	7	,	,	PUNCT
cana-1705	504	8	et	et	PROPN
cana-1705	504	9	al	al	PROPN
cana-1705	504	10	.	.	PUNCT
cana-1705	505	1	"	"	PUNCT
cana-1705	505	2	machine	machine	NOUN
cana-1705	505	3	learning	learning	NOUN
cana-1705	505	4	-	-	PUNCT
cana-1705	505	5	based	base	VERB
cana-1705	505	6	traffic	traffic	NOUN
cana-1705	505	7	flow	flow	NOUN
cana-1705	505	8	prediction	prediction	NOUN
cana-1705	505	9	and	and	CCONJ
cana-1705	505	10	intelligent	intelligent	ADJ
cana-1705	505	11	traffic	traffic	NOUN
cana-1705	505	12	management	management	NOUN
cana-1705	505	13	.	.	PUNCT
cana-1705	505	14	"	"	PUNCT
cana-1705	506	1	international	international	ADJ
cana-1705	506	2	journal	journal	NOUN
cana-1705	506	3	of	of	ADP
cana-1705	506	4	computer	computer	NOUN
cana-1705	506	5	science	science	NOUN
cana-1705	506	6	and	and	CCONJ
cana-1705	506	7	information	information	NOUN
cana-1705	506	8	technology	technology	NOUN
cana-1705	506	9	2.1	2.1	NUM
cana-1705	506	10	(	(	PUNCT
cana-1705	506	11	2024	2024	NUM
cana-1705	506	12	):	):	PUNCT
cana-1705	506	13	18	18	NUM
cana-1705	506	14	-	-	SYM
cana-1705	506	15	27	27	NUM
cana-1705	506	16	.	.	PUNCT
cana-1705	507	1	[	[	X
cana-1705	507	2	20	20	NUM
cana-1705	507	3	]	]	X
cana-1705	507	4	wang	wang	PROPN
cana-1705	507	5	,	,	PUNCT
cana-1705	507	6	qingrong	qingrong	PROPN
cana-1705	507	7	,	,	PUNCT
cana-1705	507	8	et	et	PROPN
cana-1705	507	9	al	al	PROPN
cana-1705	507	10	.	.	PUNCT
cana-1705	508	1	"	"	PUNCT
cana-1705	508	2	short	short	ADJ
cana-1705	508	3	-	-	PUNCT
cana-1705	508	4	term	term	NOUN
cana-1705	508	5	traffic	traffic	NOUN
cana-1705	508	6	flow	flow	NOUN
cana-1705	508	7	prediction	prediction	NOUN
cana-1705	508	8	based	base	VERB
cana-1705	508	9	on	on	ADP
cana-1705	508	10	spatiotemporal	spatiotemporal	ADJ
cana-1705	508	11	and	and	CCONJ
cana-1705	508	12	periodic	periodic	ADJ
cana-1705	508	13	feature	feature	NOUN
cana-1705	508	14	fusion	fusion	NOUN
cana-1705	508	15	.	.	PUNCT
cana-1705	508	16	"	"	PUNCT
cana-1705	509	1	engineering	engineering	NOUN
cana-1705	509	2	letters	letter	NOUN
cana-1705	509	3	32.1	32.1	NUM
cana-1705	509	4	(	(	PUNCT
cana-1705	509	5	2024	2024	NUM
cana-1705	509	6	)	)	PUNCT
cana-1705	509	7	.	.	PUNCT
cana-1705	510	1	[	[	X
cana-1705	510	2	21	21	NUM
cana-1705	510	3	]	]	X
cana-1705	510	4	zhang	zhang	PROPN
cana-1705	510	5	,	,	PUNCT
cana-1705	510	6	ying	ying	PROPN
cana-1705	510	7	,	,	PUNCT
cana-1705	510	8	et	et	PROPN
cana-1705	510	9	al	al	PROPN
cana-1705	510	10	.	.	PUNCT
cana-1705	510	11	"	"	PUNCT
cana-1705	510	12	short	short	ADJ
cana-1705	510	13	-	-	PUNCT
cana-1705	510	14	term	term	NOUN
cana-1705	510	15	multi	multi	ADJ
cana-1705	510	16	-	-	ADJ
cana-1705	510	17	step	step	NOUN
cana-1705	510	18	-	-	PUNCT
cana-1705	510	19	ahead	ahead	NOUN
cana-1705	510	20	sector	sector	NOUN
cana-1705	510	21	-	-	PUNCT
cana-1705	510	22	based	base	VERB
cana-1705	510	23	traffic	traffic	NOUN
cana-1705	510	24	flow	flow	NOUN
cana-1705	510	25	prediction	prediction	NOUN
cana-1705	510	26	based	base	VERB
cana-1705	510	27	on	on	ADP
cana-1705	510	28	the	the	DET
cana-1705	510	29	attentionenhanced	attentionenhanced	ADJ
cana-1705	510	30	graph	graph	NOUN
cana-1705	510	31	convolutional	convolutional	ADJ
cana-1705	510	32	lstm	lstm	NOUN
cana-1705	510	33	network	network	NOUN
cana-1705	510	34	(	(	PUNCT
cana-1705	510	35	agc	agc	NOUN
cana-1705	510	36	-	-	PUNCT
cana-1705	510	37	lstm	lstm	NOUN
cana-1705	510	38	)	)	PUNCT
cana-1705	510	39	.	.	PUNCT
cana-1705	510	40	"	"	PUNCT
cana-1705	511	1	neural	neural	ADJ
cana-1705	511	2	computing	computing	NOUN
cana-1705	511	3	and	and	CCONJ
cana-1705	511	4	applications	application	NOUN
cana-1705	511	5	(	(	PUNCT
cana-1705	511	6	2024	2024	NUM
cana-1705	511	7	):	):	PUNCT
cana-1705	511	8	1	1	NUM
cana-1705	511	9	-	-	SYM
cana-1705	511	10	20	20	NUM
cana-1705	511	11	.	.	PUNCT
cana-1705	512	1	[	[	X
cana-1705	512	2	22	22	NUM
cana-1705	512	3	]	]	X
cana-1705	512	4	wang	wang	PROPN
cana-1705	512	5	,	,	PUNCT
cana-1705	512	6	ting	ting	PROPN
cana-1705	512	7	,	,	PUNCT
cana-1705	512	8	et	et	PROPN
cana-1705	512	9	al	al	PROPN
cana-1705	512	10	.	.	PUNCT
cana-1705	513	1	"	"	PUNCT
cana-1705	513	2	pi	pi	NOUN
cana-1705	513	3	-	-	PUNCT
cana-1705	513	4	stgnet	stgnet	NOUN
cana-1705	513	5	:	:	PUNCT
cana-1705	513	6	physics	physics	NOUN
cana-1705	513	7	-	-	PUNCT
cana-1705	513	8	integrated	integrate	VERB
cana-1705	513	9	spatiotemporal	spatiotemporal	ADJ
cana-1705	513	10	graph	graph	NOUN
cana-1705	513	11	neural	neural	ADJ
cana-1705	513	12	network	network	NOUN
cana-1705	513	13	with	with	ADP
cana-1705	513	14	fundamental	fundamental	ADJ
cana-1705	513	15	diagram	diagram	NOUN
cana-1705	513	16	learner	learner	NOUN
cana-1705	513	17	for	for	ADP
cana-1705	513	18	highway	highway	NOUN
cana-1705	513	19	traffic	traffic	NOUN
cana-1705	513	20	flow	flow	NOUN
cana-1705	513	21	prediction	prediction	NOUN
cana-1705	513	22	.	.	PUNCT
cana-1705	513	23	"	"	PUNCT
cana-1705	514	1	expert	expert	ADJ
cana-1705	514	2	systems	system	NOUN
cana-1705	514	3	with	with	ADP
cana-1705	514	4	applications	application	NOUN
cana-1705	514	5	(	(	PUNCT
cana-1705	514	6	2024	2024	NUM
cana-1705	514	7	):	):	PUNCT
cana-1705	514	8	125144	125144	NUM
cana-1705	514	9	.	.	PUNCT
cana-1705	515	1	[	[	X
cana-1705	515	2	23	23	NUM
cana-1705	515	3	]	]	X
cana-1705	515	4	wang	wang	PROPN
cana-1705	515	5	,	,	PUNCT
cana-1705	515	6	ting	ting	PROPN
cana-1705	515	7	,	,	PUNCT
cana-1705	515	8	et	et	PROPN
cana-1705	515	9	al	al	PROPN
cana-1705	515	10	.	.	PUNCT
cana-1705	516	1	"	"	PUNCT
cana-1705	516	2	pi	pi	NOUN
cana-1705	516	3	-	-	PUNCT
cana-1705	516	4	stgnet	stgnet	NOUN
cana-1705	516	5	:	:	PUNCT
cana-1705	516	6	physics	physics	NOUN
cana-1705	516	7	-	-	PUNCT
cana-1705	516	8	integrated	integrate	VERB
cana-1705	516	9	spatiotemporal	spatiotemporal	ADJ
cana-1705	516	10	graph	graph	NOUN
cana-1705	516	11	neural	neural	ADJ
cana-1705	516	12	network	network	NOUN
cana-1705	516	13	with	with	ADP
cana-1705	516	14	fundamental	fundamental	ADJ
cana-1705	516	15	diagram	diagram	NOUN
cana-1705	516	16	learner	learner	NOUN
cana-1705	516	17	for	for	ADP
cana-1705	516	18	highway	highway	NOUN
cana-1705	516	19	traffic	traffic	NOUN
cana-1705	516	20	flow	flow	NOUN
cana-1705	516	21	prediction	prediction	NOUN
cana-1705	516	22	.	.	PUNCT
cana-1705	516	23	"	"	PUNCT
cana-1705	517	1	expert	expert	ADJ
cana-1705	517	2	systems	system	NOUN
cana-1705	517	3	with	with	ADP
cana-1705	517	4	applications	application	NOUN
cana-1705	517	5	(	(	PUNCT
cana-1705	517	6	2024	2024	NUM
cana-1705	517	7	):	):	PUNCT
cana-1705	517	8	125144	125144	NUM
cana-1705	517	9	.	.	PUNCT
cana-1705	518	1	[	[	X
cana-1705	518	2	24	24	NUM
cana-1705	518	3	]	]	SYM
cana-1705	518	4	choudhary	choudhary	PROPN
cana-1705	518	5	,	,	PUNCT
cana-1705	518	6	himanshu	himanshu	PROPN
cana-1705	518	7	,	,	PUNCT
cana-1705	518	8	and	and	CCONJ
cana-1705	518	9	marwan	marwan	PROPN
cana-1705	518	10	hassani	hassani	PROPN
cana-1705	518	11	.	.	PUNCT
cana-1705	519	1	"	"	PUNCT
cana-1705	519	2	autoencoder	autoencoder	NOUN
cana-1705	519	3	-	-	PUNCT
cana-1705	519	4	based	base	VERB
cana-1705	519	5	continual	continual	ADJ
cana-1705	519	6	outlier	outlier	NOUN
cana-1705	519	7	correlation	correlation	NOUN
cana-1705	519	8	detection	detection	NOUN
cana-1705	519	9	for	for	ADP
cana-1705	519	10	real	real	ADJ
cana-1705	519	11	-	-	PUNCT
cana-1705	519	12	time	time	NOUN
cana-1705	519	13	traffic	traffic	NOUN
cana-1705	519	14	flow	flow	NOUN
cana-1705	519	15	prediction	prediction	NOUN
cana-1705	519	16	.	.	PUNCT
cana-1705	519	17	"	"	PUNCT
cana-1705	520	1	proceedings	proceeding	NOUN
cana-1705	520	2	of	of	ADP
cana-1705	520	3	the	the	DET
cana-1705	520	4	39th	39th	ADJ
cana-1705	520	5	acm	acm	NOUN
cana-1705	520	6	/	/	SYM
cana-1705	520	7	sigapp	sigapp	NOUN
cana-1705	520	8	symposium	symposium	NOUN
cana-1705	520	9	on	on	ADP
cana-1705	520	10	applied	apply	VERB
cana-1705	520	11	computing	computing	NOUN
cana-1705	520	12	.	.	PUNCT
cana-1705	521	1	2024	2024	NUM
cana-1705	521	2	.	.	PUNCT