id	sid	tid	token	lemma	pos
ajst-31456	1	1	academic	academic	ADJ
ajst-31456	1	2	journal	journal	NOUN
ajst-31456	1	3	of	of	ADP
ajst-31456	1	4	science	science	NOUN
ajst-31456	1	5	and	and	CCONJ
ajst-31456	1	6	technology	technology	NOUN
ajst-31456	1	7	issn	issn	NOUN
ajst-31456	1	8	:	:	PUNCT
ajst-31456	1	9	2771	2771	NUM
ajst-31456	1	10	-	-	SYM
ajst-31456	1	11	3032	3032	NUM
ajst-31456	1	12	|	|	NOUN
ajst-31456	1	13	vol	vol	NOUN
ajst-31456	1	14	.	.	PROPN
ajst-31456	2	1	16	16	NUM
ajst-31456	2	2	,	,	PUNCT
ajst-31456	2	3	no	no	INTJ
ajst-31456	2	4	.	.	NOUN
ajst-31456	2	5	1	1	NUM
ajst-31456	2	6	,	,	PUNCT
ajst-31456	2	7	2025	2025	NUM
ajst-31456	2	8	51	51	NUM
ajst-31456	2	9	prediction	prediction	NOUN
ajst-31456	2	10	of	of	ADP
ajst-31456	2	11	demand	demand	NOUN
ajst-31456	2	12	for	for	ADP
ajst-31456	2	13	shared	share	VERB
ajst-31456	2	14	bicycles	bicycle	NOUN
ajst-31456	2	15	based	base	VERB
ajst-31456	2	16	on	on	ADP
ajst-31456	2	17	machine	machine	NOUN
ajst-31456	2	18	learning	learn	VERB
ajst-31456	2	19	wenyu	wenyu	NOUN
ajst-31456	2	20	jiang1	jiang1	PROPN
ajst-31456	2	21	,	,	PUNCT
ajst-31456	2	22	a	a	DET
ajst-31456	2	23	1london	1london	NUM
ajst-31456	2	24	brunel	brunel	PROPN
ajst-31456	2	25	school	school	NOUN
ajst-31456	2	26	,	,	PUNCT
ajst-31456	2	27	north	north	PROPN
ajst-31456	2	28	china	china	PROPN
ajst-31456	2	29	university	university	PROPN
ajst-31456	2	30	of	of	ADP
ajst-31456	2	31	technology	technology	PROPN
ajst-31456	2	32	,	,	PUNCT
ajst-31456	2	33	beijing	beijing	PROPN
ajst-31456	2	34	100144	100144	NUM
ajst-31456	2	35	,	,	PUNCT
ajst-31456	2	36	china	china	PROPN
ajst-31456	2	37	ajiangwenyu123@mail.ncut.edu.cn	ajiangwenyu123@mail.ncut.edu.cn	PROPN
ajst-31456	2	38	abstract	abstract	NOUN
ajst-31456	2	39	:	:	PUNCT
ajst-31456	2	40	with	with	ADP
ajst-31456	2	41	the	the	DET
ajst-31456	2	42	acceleration	acceleration	NOUN
ajst-31456	2	43	of	of	ADP
ajst-31456	2	44	urbanization	urbanization	NOUN
ajst-31456	2	45	,	,	PUNCT
ajst-31456	2	46	shared	share	VERB
ajst-31456	2	47	bicycles	bicycle	NOUN
ajst-31456	2	48	have	have	AUX
ajst-31456	2	49	become	become	VERB
ajst-31456	2	50	an	an	DET
ajst-31456	2	51	indispensable	indispensable	ADJ
ajst-31456	2	52	component	component	NOUN
ajst-31456	2	53	of	of	ADP
ajst-31456	2	54	modern	modern	ADJ
ajst-31456	2	55	urban	urban	ADJ
ajst-31456	2	56	transportation	transportation	NOUN
ajst-31456	2	57	systems	system	NOUN
ajst-31456	2	58	,	,	PUNCT
ajst-31456	2	59	playing	play	VERB
ajst-31456	2	60	an	an	DET
ajst-31456	2	61	important	important	ADJ
ajst-31456	2	62	role	role	NOUN
ajst-31456	2	63	in	in	ADP
ajst-31456	2	64	improving	improve	VERB
ajst-31456	2	65	social	social	ADJ
ajst-31456	2	66	resource	resource	NOUN
ajst-31456	2	67	utilization	utilization	NOUN
ajst-31456	2	68	,	,	PUNCT
ajst-31456	2	69	alleviating	alleviate	VERB
ajst-31456	2	70	traffic	traffic	NOUN
ajst-31456	2	71	pressure	pressure	NOUN
ajst-31456	2	72	,	,	PUNCT
ajst-31456	2	73	and	and	CCONJ
ajst-31456	2	74	promoting	promote	VERB
ajst-31456	2	75	green	green	ADJ
ajst-31456	2	76	travel	travel	NOUN
ajst-31456	2	77	.	.	PUNCT
ajst-31456	3	1	however	however	ADV
ajst-31456	3	2	,	,	PUNCT
ajst-31456	3	3	a	a	DET
ajst-31456	3	4	common	common	ADJ
ajst-31456	3	5	problem	problem	NOUN
ajst-31456	3	6	of	of	ADP
ajst-31456	3	7	supply	supply	NOUN
ajst-31456	3	8	-	-	PUNCT
ajst-31456	3	9	demand	demand	NOUN
ajst-31456	3	10	imbalance	imbalance	NOUN
ajst-31456	3	11	exists	exist	VERB
ajst-31456	3	12	in	in	ADP
ajst-31456	3	13	the	the	DET
ajst-31456	3	14	spatial	spatial	ADJ
ajst-31456	3	15	and	and	CCONJ
ajst-31456	3	16	temporal	temporal	ADJ
ajst-31456	3	17	distribution	distribution	NOUN
ajst-31456	3	18	of	of	ADP
ajst-31456	3	19	vehicles	vehicle	NOUN
ajst-31456	3	20	,	,	PUNCT
ajst-31456	3	21	which	which	PRON
ajst-31456	3	22	not	not	PART
ajst-31456	3	23	only	only	ADV
ajst-31456	3	24	affects	affect	VERB
ajst-31456	3	25	user	user	NOUN
ajst-31456	3	26	experience	experience	NOUN
ajst-31456	3	27	but	but	CCONJ
ajst-31456	3	28	also	also	ADV
ajst-31456	3	29	increases	increase	VERB
ajst-31456	3	30	operating	operating	NOUN
ajst-31456	3	31	costs	cost	NOUN
ajst-31456	3	32	.	.	PUNCT
ajst-31456	4	1	in	in	ADP
ajst-31456	4	2	this	this	DET
ajst-31456	4	3	context	context	NOUN
ajst-31456	4	4	,	,	PUNCT
ajst-31456	4	5	accurate	accurate	ADJ
ajst-31456	4	6	prediction	prediction	NOUN
ajst-31456	4	7	of	of	ADP
ajst-31456	4	8	shared	share	VERB
ajst-31456	4	9	bicycle	bicycle	NOUN
ajst-31456	4	10	rental	rental	NOUN
ajst-31456	4	11	demand	demand	NOUN
ajst-31456	4	12	is	be	AUX
ajst-31456	4	13	crucial	crucial	ADJ
ajst-31456	4	14	for	for	ADP
ajst-31456	4	15	achieving	achieve	VERB
ajst-31456	4	16	refined	refined	ADJ
ajst-31456	4	17	operations	operation	NOUN
ajst-31456	4	18	.	.	PUNCT
ajst-31456	5	1	this	this	DET
ajst-31456	5	2	paper	paper	NOUN
ajst-31456	5	3	presents	present	VERB
ajst-31456	5	4	a	a	DET
ajst-31456	5	5	high	high	ADJ
ajst-31456	5	6	-	-	PUNCT
ajst-31456	5	7	precision	precision	NOUN
ajst-31456	5	8	prediction	prediction	NOUN
ajst-31456	5	9	model	model	NOUN
ajst-31456	5	10	constructed	construct	VERB
ajst-31456	5	11	using	use	VERB
ajst-31456	5	12	machine	machine	NOUN
ajst-31456	5	13	learning	learning	NOUN
ajst-31456	5	14	technology	technology	NOUN
ajst-31456	5	15	.	.	PUNCT
ajst-31456	6	1	the	the	DET
ajst-31456	6	2	proposed	propose	VERB
ajst-31456	6	3	methodology	methodology	NOUN
ajst-31456	6	4	,	,	PUNCT
ajst-31456	6	5	structured	structure	VERB
ajst-31456	6	6	into	into	ADP
ajst-31456	6	7	three	three	NUM
ajst-31456	6	8	distinct	distinct	ADJ
ajst-31456	6	9	modules	module	NOUN
ajst-31456	6	10	,	,	PUNCT
ajst-31456	6	11	begins	begin	VERB
ajst-31456	6	12	with	with	ADP
ajst-31456	6	13	detailed	detailed	ADJ
ajst-31456	6	14	exploratory	exploratory	ADJ
ajst-31456	6	15	data	datum	NOUN
ajst-31456	6	16	analysis	analysis	NOUN
ajst-31456	6	17	and	and	CCONJ
ajst-31456	6	18	comprehensive	comprehensive	ADJ
ajst-31456	6	19	feature	feature	NOUN
ajst-31456	6	20	engineering	engineering	NOUN
ajst-31456	6	21	.	.	PUNCT
ajst-31456	7	1	this	this	PRON
ajst-31456	7	2	includes	include	VERB
ajst-31456	7	3	logarithmic	logarithmic	ADJ
ajst-31456	7	4	transformation	transformation	NOUN
ajst-31456	7	5	of	of	ADP
ajst-31456	7	6	target	target	NOUN
ajst-31456	7	7	variables	variable	NOUN
ajst-31456	7	8	,	,	PUNCT
ajst-31456	7	9	encoding	encoding	NOUN
ajst-31456	7	10	of	of	ADP
ajst-31456	7	11	categorical	categorical	ADJ
ajst-31456	7	12	features	feature	NOUN
ajst-31456	7	13	,	,	PUNCT
ajst-31456	7	14	and	and	CCONJ
ajst-31456	7	15	critically	critically	ADV
ajst-31456	7	16	,	,	PUNCT
ajst-31456	7	17	the	the	DET
ajst-31456	7	18	construction	construction	NOUN
ajst-31456	7	19	of	of	ADP
ajst-31456	7	20	key	key	ADJ
ajst-31456	7	21	interaction	interaction	NOUN
ajst-31456	7	22	features	feature	VERB
ajst-31456	7	23	to	to	PART
ajst-31456	7	24	capture	capture	VERB
ajst-31456	7	25	the	the	DET
ajst-31456	7	26	complex	complex	ADJ
ajst-31456	7	27	relationship	relationship	NOUN
ajst-31456	7	28	between	between	ADP
ajst-31456	7	29	variables	variable	NOUN
ajst-31456	7	30	like	like	ADP
ajst-31456	7	31	temperature	temperature	NOUN
ajst-31456	7	32	and	and	CCONJ
ajst-31456	7	33	hour	hour	NOUN
ajst-31456	7	34	.	.	PUNCT
ajst-31456	8	1	on	on	ADP
ajst-31456	8	2	this	this	DET
ajst-31456	8	3	basis	basis	NOUN
ajst-31456	8	4	,	,	PUNCT
ajst-31456	8	5	the	the	DET
ajst-31456	8	6	xgboost	xgboost	PROPN
ajst-31456	8	7	model	model	NOUN
ajst-31456	8	8	is	be	AUX
ajst-31456	8	9	employed	employ	VERB
ajst-31456	8	10	to	to	PART
ajst-31456	8	11	evaluate	evaluate	VERB
ajst-31456	8	12	feature	feature	NOUN
ajst-31456	8	13	importance	importance	NOUN
ajst-31456	8	14	and	and	CCONJ
ajst-31456	8	15	select	select	VERB
ajst-31456	8	16	an	an	DET
ajst-31456	8	17	optimal	optimal	ADJ
ajst-31456	8	18	feature	feature	NOUN
ajst-31456	8	19	subset	subset	NOUN
ajst-31456	8	20	.	.	PUNCT
ajst-31456	9	1	subsequently	subsequently	ADV
ajst-31456	9	2	,	,	PUNCT
ajst-31456	9	3	through	through	ADP
ajst-31456	9	4	a	a	DET
ajst-31456	9	5	series	series	NOUN
ajst-31456	9	6	of	of	ADP
ajst-31456	9	7	comparative	comparative	ADJ
ajst-31456	9	8	experiments	experiment	NOUN
ajst-31456	9	9	,	,	PUNCT
ajst-31456	9	10	a	a	DET
ajst-31456	9	11	range	range	NOUN
ajst-31456	9	12	of	of	ADP
ajst-31456	9	13	machine	machine	NOUN
ajst-31456	9	14	learning	learn	VERB
ajst-31456	9	15	regression	regression	NOUN
ajst-31456	9	16	models	model	NOUN
ajst-31456	9	17	,	,	PUNCT
ajst-31456	9	18	including	include	VERB
ajst-31456	9	19	linear	linear	NOUN
ajst-31456	9	20	,	,	PUNCT
ajst-31456	9	21	tree	tree	NOUN
ajst-31456	9	22	-	-	PUNCT
ajst-31456	9	23	based	base	VERB
ajst-31456	9	24	,	,	PUNCT
ajst-31456	9	25	and	and	CCONJ
ajst-31456	9	26	gradient	gradient	ADJ
ajst-31456	9	27	boosting	boost	VERB
ajst-31456	9	28	models	model	NOUN
ajst-31456	9	29	,	,	PUNCT
ajst-31456	9	30	are	be	AUX
ajst-31456	9	31	systematically	systematically	ADV
ajst-31456	9	32	compared	compare	VERB
ajst-31456	9	33	.	.	PUNCT
ajst-31456	10	1	using	use	VERB
ajst-31456	10	2	a	a	DET
ajst-31456	10	3	time	time	NOUN
ajst-31456	10	4	-	-	PUNCT
ajst-31456	10	5	series	series	NOUN
ajst-31456	10	6	cross	cross	ADJ
ajst-31456	10	7	-	-	ADJ
ajst-31456	10	8	validation	validation	ADJ
ajst-31456	10	9	method	method	NOUN
ajst-31456	10	10	,	,	PUNCT
ajst-31456	10	11	each	each	DET
ajst-31456	10	12	model	model	NOUN
ajst-31456	10	13	is	be	AUX
ajst-31456	10	14	trained	train	VERB
ajst-31456	10	15	and	and	CCONJ
ajst-31456	10	16	evaluated	evaluate	VERB
ajst-31456	10	17	with	with	ADP
ajst-31456	10	18	root	root	NOUN
ajst-31456	10	19	mean	mean	ADJ
ajst-31456	10	20	square	square	ADJ
ajst-31456	10	21	logarithmic	logarithmic	ADJ
ajst-31456	10	22	error	error	NOUN
ajst-31456	10	23	(	(	PUNCT
ajst-31456	10	24	rmsle	rmsle	PROPN
ajst-31456	10	25	)	)	PUNCT
ajst-31456	10	26	and	and	CCONJ
ajst-31456	10	27	the	the	DET
ajst-31456	10	28	coefficient	coefficient	NOUN
ajst-31456	10	29	of	of	ADP
ajst-31456	10	30	determination	determination	NOUN
ajst-31456	10	31	(	(	PUNCT
ajst-31456	10	32	r2	r2	PROPN
ajst-31456	10	33	)	)	PUNCT
ajst-31456	10	34	as	as	ADP
ajst-31456	10	35	the	the	DET
ajst-31456	10	36	main	main	ADJ
ajst-31456	10	37	evaluation	evaluation	NOUN
ajst-31456	10	38	indicators	indicator	NOUN
ajst-31456	10	39	.	.	PUNCT
ajst-31456	11	1	finally	finally	ADV
ajst-31456	11	2	,	,	PUNCT
ajst-31456	11	3	hyperparameters	hyperparameter	NOUN
ajst-31456	11	4	for	for	ADP
ajst-31456	11	5	the	the	DET
ajst-31456	11	6	top	top	ADV
ajst-31456	11	7	-	-	PUNCT
ajst-31456	11	8	performing	perform	VERB
ajst-31456	11	9	models	model	NOUN
ajst-31456	11	10	are	be	AUX
ajst-31456	11	11	optimized	optimize	VERB
ajst-31456	11	12	to	to	PART
ajst-31456	11	13	further	far	ADV
ajst-31456	11	14	improve	improve	VERB
ajst-31456	11	15	prediction	prediction	NOUN
ajst-31456	11	16	accuracy	accuracy	NOUN
ajst-31456	11	17	and	and	CCONJ
ajst-31456	11	18	generalization	generalization	NOUN
ajst-31456	11	19	ability	ability	NOUN
ajst-31456	11	20	.	.	PUNCT
ajst-31456	12	1	the	the	DET
ajst-31456	12	2	results	result	NOUN
ajst-31456	12	3	indicate	indicate	VERB
ajst-31456	12	4	that	that	SCONJ
ajst-31456	12	5	the	the	DET
ajst-31456	12	6	tree	tree	NOUN
ajst-31456	12	7	-	-	PUNCT
ajst-31456	12	8	based	base	VERB
ajst-31456	12	9	ensemble	ensemble	ADJ
ajst-31456	12	10	model	model	NOUN
ajst-31456	12	11	lightgbm	lightgbm	VERB
ajst-31456	12	12	exhibits	exhibit	NOUN
ajst-31456	12	13	superior	superior	ADJ
ajst-31456	12	14	performance	performance	NOUN
ajst-31456	12	15	in	in	ADP
ajst-31456	12	16	the	the	DET
ajst-31456	12	17	task	task	NOUN
ajst-31456	12	18	of	of	ADP
ajst-31456	12	19	predicting	predict	VERB
ajst-31456	12	20	shared	share	VERB
ajst-31456	12	21	bicycle	bicycle	NOUN
ajst-31456	12	22	demand	demand	NOUN
ajst-31456	12	23	,	,	PUNCT
ajst-31456	12	24	with	with	SCONJ
ajst-31456	12	25	its	its	PRON
ajst-31456	12	26	accuracy	accuracy	NOUN
ajst-31456	12	27	further	far	ADV
ajst-31456	12	28	improved	improve	VERB
ajst-31456	12	29	after	after	ADP
ajst-31456	12	30	hyperparameter	hyperparameter	NOUN
ajst-31456	12	31	optimization	optimization	NOUN
ajst-31456	12	32	.	.	PUNCT
ajst-31456	13	1	this	this	DET
ajst-31456	13	2	study	study	NOUN
ajst-31456	13	3	not	not	PART
ajst-31456	13	4	only	only	ADV
ajst-31456	13	5	provides	provide	VERB
ajst-31456	13	6	an	an	DET
ajst-31456	13	7	effective	effective	ADJ
ajst-31456	13	8	demand	demand	NOUN
ajst-31456	13	9	forecasting	forecasting	NOUN
ajst-31456	13	10	solution	solution	NOUN
ajst-31456	13	11	for	for	ADP
ajst-31456	13	12	shared	shared	ADJ
ajst-31456	13	13	bicycle	bicycle	NOUN
ajst-31456	13	14	operators	operator	NOUN
ajst-31456	13	15	,	,	PUNCT
ajst-31456	13	16	but	but	CCONJ
ajst-31456	13	17	also	also	ADV
ajst-31456	13	18	offers	offer	VERB
ajst-31456	13	19	a	a	DET
ajst-31456	13	20	valuable	valuable	ADJ
ajst-31456	13	21	reference	reference	NOUN
ajst-31456	13	22	for	for	ADP
ajst-31456	13	23	similar	similar	ADJ
ajst-31456	13	24	time	time	NOUN
ajst-31456	13	25	series	series	PROPN
ajst-31456	13	26	forecasting	forecasting	NOUN
ajst-31456	13	27	problems	problem	NOUN
ajst-31456	13	28	.	.	PUNCT
ajst-31456	14	1	keywords	keyword	NOUN
ajst-31456	14	2	:	:	PUNCT
ajst-31456	14	3	shared	share	VERB
ajst-31456	14	4	bicycles	bicycle	NOUN
ajst-31456	14	5	;	;	PUNCT
ajst-31456	14	6	demand	demand	NOUN
ajst-31456	14	7	forecasting	forecasting	NOUN
ajst-31456	14	8	;	;	PUNCT
ajst-31456	14	9	machine	machine	NOUN
ajst-31456	14	10	learning	learning	NOUN
ajst-31456	14	11	;	;	PUNCT
ajst-31456	14	12	feature	feature	NOUN
ajst-31456	14	13	engineering	engineering	NOUN
ajst-31456	14	14	;	;	PUNCT
ajst-31456	14	15	xgboost	xgboost	ADV
ajst-31456	14	16	;	;	PUNCT
ajst-31456	14	17	lightgbm	lightgbm	ADJ
ajst-31456	14	18	;	;	PUNCT
ajst-31456	14	19	time	time	NOUN
ajst-31456	14	20	series	series	PROPN
ajst-31456	14	21	analysis	analysis	NOUN
ajst-31456	14	22	.	.	PUNCT
ajst-31456	15	1	1	1	X
ajst-31456	15	2	.	.	X
ajst-31456	15	3	introduction	introduction	NOUN
ajst-31456	15	4	in	in	ADP
ajst-31456	15	5	the	the	DET
ajst-31456	15	6	rapid	rapid	ADJ
ajst-31456	15	7	development	development	NOUN
ajst-31456	15	8	of	of	ADP
ajst-31456	15	9	shared	share	VERB
ajst-31456	15	10	bicycles	bicycle	NOUN
ajst-31456	15	11	,	,	PUNCT
ajst-31456	15	12	operational	operational	ADJ
ajst-31456	15	13	management	management	NOUN
ajst-31456	15	14	faces	face	VERB
ajst-31456	15	15	many	many	ADJ
ajst-31456	15	16	severe	severe	ADJ
ajst-31456	15	17	challenges	challenge	NOUN
ajst-31456	15	18	,	,	PUNCT
ajst-31456	15	19	among	among	ADP
ajst-31456	15	20	which	which	PRON
ajst-31456	15	21	the	the	DET
ajst-31456	15	22	most	most	ADV
ajst-31456	15	23	prominent	prominent	ADJ
ajst-31456	15	24	is	be	AUX
ajst-31456	15	25	the	the	DET
ajst-31456	15	26	extremely	extremely	ADV
ajst-31456	15	27	uneven	uneven	ADJ
ajst-31456	15	28	use	use	NOUN
ajst-31456	15	29	of	of	ADP
ajst-31456	15	30	vehicles	vehicle	NOUN
ajst-31456	15	31	in	in	ADP
ajst-31456	15	32	different	different	ADJ
ajst-31456	15	33	regions	region	NOUN
ajst-31456	15	34	and	and	CCONJ
ajst-31456	15	35	time	time	NOUN
ajst-31456	15	36	periods	period	NOUN
ajst-31456	15	37	.	.	PUNCT
ajst-31456	16	1	for	for	ADP
ajst-31456	16	2	example	example	NOUN
ajst-31456	16	3	,	,	PUNCT
ajst-31456	16	4	during	during	ADP
ajst-31456	16	5	the	the	DET
ajst-31456	16	6	morning	morning	NOUN
ajst-31456	16	7	rush	rush	NOUN
ajst-31456	16	8	hour	hour	NOUN
ajst-31456	16	9	on	on	ADP
ajst-31456	16	10	weekdays	weekday	NOUN
ajst-31456	16	11	,	,	PUNCT
ajst-31456	16	12	a	a	DET
ajst-31456	16	13	large	large	ADJ
ajst-31456	16	14	number	number	NOUN
ajst-31456	16	15	of	of	ADP
ajst-31456	16	16	citizens	citizen	NOUN
ajst-31456	16	17	ride	ride	VERB
ajst-31456	16	18	bicycles	bicycle	NOUN
ajst-31456	16	19	from	from	ADP
ajst-31456	16	20	residential	residential	ADJ
ajst-31456	16	21	areas	area	NOUN
ajst-31456	16	22	and	and	CCONJ
ajst-31456	16	23	subway	subway	NOUN
ajst-31456	16	24	stations	station	NOUN
ajst-31456	16	25	to	to	ADP
ajst-31456	16	26	commercial	commercial	ADJ
ajst-31456	16	27	centers	center	NOUN
ajst-31456	16	28	and	and	CCONJ
ajst-31456	16	29	office	office	NOUN
ajst-31456	16	30	areas	area	NOUN
ajst-31456	16	31	,	,	PUNCT
ajst-31456	16	32	resulting	result	VERB
ajst-31456	16	33	in	in	ADP
ajst-31456	16	34	the	the	DET
ajst-31456	16	35	former	former	ADJ
ajst-31456	16	36	having	have	VERB
ajst-31456	16	37	no	no	DET
ajst-31456	16	38	cars	car	NOUN
ajst-31456	16	39	to	to	PART
ajst-31456	16	40	rent	rent	VERB
ajst-31456	16	41	while	while	SCONJ
ajst-31456	16	42	the	the	DET
ajst-31456	16	43	latter	latter	ADJ
ajst-31456	16	44	have	have	VERB
ajst-31456	16	45	a	a	DET
ajst-31456	16	46	pile	pile	NOUN
ajst-31456	16	47	of	of	ADP
ajst-31456	16	48	vehicles	vehicle	NOUN
ajst-31456	16	49	;	;	PUNCT
ajst-31456	16	50	the	the	DET
ajst-31456	16	51	opposite	opposite	NOUN
ajst-31456	16	52	is	be	AUX
ajst-31456	16	53	true	true	ADJ
ajst-31456	16	54	during	during	ADP
ajst-31456	16	55	the	the	DET
ajst-31456	16	56	evening	evening	NOUN
ajst-31456	16	57	rush	rush	NOUN
ajst-31456	16	58	hour	hour	NOUN
ajst-31456	16	59	.	.	PUNCT
ajst-31456	17	1	to	to	PART
ajst-31456	17	2	address	address	VERB
ajst-31456	17	3	this	this	PRON
ajst-31456	17	4	,	,	PUNCT
ajst-31456	17	5	numerous	numerous	ADJ
ajst-31456	17	6	studies	study	NOUN
ajst-31456	17	7	have	have	AUX
ajst-31456	17	8	applied	apply	VERB
ajst-31456	17	9	machine	machine	NOUN
ajst-31456	17	10	learning	learning	NOUN
ajst-31456	17	11	and	and	CCONJ
ajst-31456	17	12	deep	deep	ADJ
ajst-31456	17	13	learning	learning	NOUN
ajst-31456	17	14	models	model	NOUN
ajst-31456	17	15	to	to	PART
ajst-31456	17	16	forecast	forecast	VERB
ajst-31456	17	17	demand	demand	NOUN
ajst-31456	17	18	,	,	PUNCT
ajst-31456	17	19	with	with	ADP
ajst-31456	17	20	empirical	empirical	ADJ
ajst-31456	17	21	evaluations	evaluation	NOUN
ajst-31456	17	22	comparing	compare	VERB
ajst-31456	17	23	their	their	PRON
ajst-31456	17	24	relative	relative	ADJ
ajst-31456	17	25	performance	performance	NOUN
ajst-31456	17	26	[	[	X
ajst-31456	17	27	1	1	NUM
ajst-31456	17	28	]	]	PUNCT
ajst-31456	17	29	.	.	PUNCT
ajst-31456	18	1	these	these	DET
ajst-31456	18	2	studies	study	NOUN
ajst-31456	18	3	indicate	indicate	VERB
ajst-31456	18	4	that	that	SCONJ
ajst-31456	18	5	the	the	DET
ajst-31456	18	6	optimal	optimal	ADJ
ajst-31456	18	7	model	model	NOUN
ajst-31456	18	8	often	often	ADV
ajst-31456	18	9	depends	depend	VERB
ajst-31456	18	10	on	on	ADP
ajst-31456	18	11	the	the	DET
ajst-31456	18	12	specific	specific	ADJ
ajst-31456	18	13	forecast	forecast	NOUN
ajst-31456	18	14	horizon	horizon	NOUN
ajst-31456	18	15	,	,	PUNCT
ajst-31456	18	16	with	with	ADP
ajst-31456	18	17	different	different	ADJ
ajst-31456	18	18	models	model	NOUN
ajst-31456	18	19	excelling	excel	VERB
ajst-31456	18	20	at	at	ADP
ajst-31456	18	21	short	short	ADJ
ajst-31456	18	22	-	-	PUNCT
ajst-31456	18	23	term	term	NOUN
ajst-31456	18	24	versus	versus	ADP
ajst-31456	18	25	long	long	ADJ
ajst-31456	18	26	-	-	PUNCT
ajst-31456	18	27	term	term	NOUN
ajst-31456	18	28	predictions	prediction	NOUN
ajst-31456	18	29	[	[	X
ajst-31456	18	30	2	2	NUM
ajst-31456	18	31	]	]	PUNCT
ajst-31456	18	32	.	.	PUNCT
ajst-31456	19	1	such	such	ADJ
ajst-31456	19	2	approaches	approach	NOUN
ajst-31456	19	3	often	often	ADV
ajst-31456	19	4	involve	involve	VERB
ajst-31456	19	5	extensive	extensive	ADJ
ajst-31456	19	6	feature	feature	NOUN
ajst-31456	19	7	engineering	engineering	NOUN
ajst-31456	19	8	and	and	CCONJ
ajst-31456	19	9	in	in	ADP
ajst-31456	19	10	-	-	PUNCT
ajst-31456	19	11	depth	depth	NOUN
ajst-31456	19	12	analysis	analysis	NOUN
ajst-31456	19	13	of	of	ADP
ajst-31456	19	14	various	various	ADJ
ajst-31456	19	15	ensemble	ensemble	ADJ
ajst-31456	19	16	techniques	technique	NOUN
ajst-31456	19	17	to	to	PART
ajst-31456	19	18	build	build	VERB
ajst-31456	19	19	a	a	DET
ajst-31456	19	20	robust	robust	ADJ
ajst-31456	19	21	predictive	predictive	ADJ
ajst-31456	19	22	pipeline	pipeline	NOUN
ajst-31456	19	23	[	[	X
ajst-31456	19	24	3	3	NUM
ajst-31456	19	25	]	]	PUNCT
ajst-31456	19	26	.	.	PUNCT
ajst-31456	20	1	in	in	ADP
ajst-31456	20	2	addition	addition	NOUN
ajst-31456	20	3	to	to	ADP
ajst-31456	20	4	operational	operational	ADJ
ajst-31456	20	5	issues	issue	NOUN
ajst-31456	20	6	,	,	PUNCT
ajst-31456	20	7	research	research	NOUN
ajst-31456	20	8	has	have	AUX
ajst-31456	20	9	also	also	ADV
ajst-31456	20	10	highlighted	highlight	VERB
ajst-31456	20	11	significant	significant	ADJ
ajst-31456	20	12	safety	safety	NOUN
ajst-31456	20	13	challenges	challenge	NOUN
ajst-31456	20	14	within	within	ADP
ajst-31456	20	15	these	these	DET
ajst-31456	20	16	systems	system	NOUN
ajst-31456	20	17	,	,	PUNCT
ajst-31456	20	18	which	which	PRON
ajst-31456	20	19	must	must	AUX
ajst-31456	20	20	be	be	AUX
ajst-31456	20	21	addressed	address	VERB
ajst-31456	20	22	to	to	PART
ajst-31456	20	23	ensure	ensure	VERB
ajst-31456	20	24	sustainable	sustainable	ADJ
ajst-31456	20	25	urban	urban	ADJ
ajst-31456	20	26	mobility	mobility	NOUN
ajst-31456	20	27	[	[	X
ajst-31456	20	28	4	4	NUM
ajst-31456	20	29	]	]	PUNCT
ajst-31456	20	30	.	.	PUNCT
ajst-31456	21	1	although	although	SCONJ
ajst-31456	21	2	these	these	DET
ajst-31456	21	3	researchers	researcher	NOUN
ajst-31456	21	4	have	have	AUX
ajst-31456	21	5	put	put	VERB
ajst-31456	21	6	forward	forward	ADV
ajst-31456	21	7	excellent	excellent	ADJ
ajst-31456	21	8	solutions	solution	NOUN
ajst-31456	21	9	for	for	ADP
ajst-31456	21	10	shared	share	VERB
ajst-31456	21	11	vehicle	vehicle	NOUN
ajst-31456	21	12	cost	cost	NOUN
ajst-31456	21	13	optimization	optimization	NOUN
ajst-31456	21	14	and	and	CCONJ
ajst-31456	21	15	demand	demand	NOUN
ajst-31456	21	16	forecasting	forecasting	NOUN
ajst-31456	21	17	,	,	PUNCT
ajst-31456	21	18	they	they	PRON
ajst-31456	21	19	have	have	AUX
ajst-31456	21	20	not	not	PART
ajst-31456	21	21	reached	reach	VERB
ajst-31456	21	22	a	a	DET
ajst-31456	21	23	fine	fine	ADJ
ajst-31456	21	24	level	level	NOUN
ajst-31456	21	25	in	in	ADP
ajst-31456	21	26	data	datum	NOUN
ajst-31456	21	27	pre	pre	X
ajst-31456	21	28	processing	processing	NOUN
ajst-31456	21	29	.	.	PUNCT
ajst-31456	22	1	in	in	ADP
ajst-31456	22	2	addition	addition	NOUN
ajst-31456	22	3	,	,	PUNCT
ajst-31456	22	4	the	the	DET
ajst-31456	22	5	above	above	ADV
ajst-31456	22	6	-	-	PUNCT
ajst-31456	22	7	mentioned	mention	VERB
ajst-31456	22	8	papers	paper	NOUN
ajst-31456	22	9	have	have	AUX
ajst-31456	22	10	not	not	PART
ajst-31456	22	11	further	far	ADV
ajst-31456	22	12	processed	process	VERB
ajst-31456	22	13	the	the	DET
ajst-31456	22	14	optimization	optimization	NOUN
ajst-31456	22	15	and	and	CCONJ
ajst-31456	22	16	processing	processing	NOUN
ajst-31456	22	17	methods	method	NOUN
ajst-31456	22	18	for	for	ADP
ajst-31456	22	19	features	feature	NOUN
ajst-31456	22	20	,	,	PUNCT
ajst-31456	22	21	so	so	SCONJ
ajst-31456	22	22	that	that	SCONJ
ajst-31456	22	23	the	the	DET
ajst-31456	22	24	model	model	NOUN
ajst-31456	22	25	still	still	ADV
ajst-31456	22	26	has	have	VERB
ajst-31456	22	27	room	room	NOUN
ajst-31456	22	28	for	for	ADP
ajst-31456	22	29	improvement	improvement	NOUN
ajst-31456	22	30	.	.	PUNCT
ajst-31456	23	1	and	and	CCONJ
ajst-31456	23	2	many	many	ADJ
ajst-31456	23	3	articles	article	NOUN
ajst-31456	23	4	do	do	AUX
ajst-31456	23	5	not	not	PART
ajst-31456	23	6	mention	mention	VERB
ajst-31456	23	7	how	how	SCONJ
ajst-31456	23	8	to	to	PART
ajst-31456	23	9	deal	deal	VERB
ajst-31456	23	10	with	with	ADP
ajst-31456	23	11	features	feature	NOUN
ajst-31456	23	12	and	and	CCONJ
ajst-31456	23	13	super	super	ADJ
ajst-31456	23	14	parameter	parameter	NOUN
ajst-31456	23	15	optimization	optimization	NOUN
ajst-31456	23	16	of	of	ADP
ajst-31456	23	17	the	the	DET
ajst-31456	23	18	model	model	NOUN
ajst-31456	23	19	.	.	PUNCT
ajst-31456	24	1	beyond	beyond	ADP
ajst-31456	24	2	transportation	transportation	NOUN
ajst-31456	24	3	,	,	PUNCT
ajst-31456	24	4	these	these	DET
ajst-31456	24	5	systems	system	NOUN
ajst-31456	24	6	are	be	AUX
ajst-31456	24	7	also	also	ADV
ajst-31456	24	8	being	be	AUX
ajst-31456	24	9	explored	explore	VERB
ajst-31456	24	10	as	as	ADP
ajst-31456	24	11	mobile	mobile	ADJ
ajst-31456	24	12	sensor	sensor	NOUN
ajst-31456	24	13	platforms	platform	NOUN
ajst-31456	24	14	for	for	ADP
ajst-31456	24	15	smart	smart	ADJ
ajst-31456	24	16	city	city	NOUN
ajst-31456	24	17	applications	application	NOUN
ajst-31456	24	18	,	,	PUNCT
ajst-31456	24	19	such	such	ADJ
ajst-31456	24	20	as	as	ADP
ajst-31456	24	21	using	use	VERB
ajst-31456	24	22	onbike	onbike	ADJ
ajst-31456	24	23	sensors	sensor	NOUN
ajst-31456	24	24	and	and	CCONJ
ajst-31456	24	25	ontologies	ontology	NOUN
ajst-31456	24	26	to	to	PART
ajst-31456	24	27	detect	detect	VERB
ajst-31456	24	28	urban	urban	ADJ
ajst-31456	24	29	events	event	NOUN
ajst-31456	24	30	like	like	ADP
ajst-31456	24	31	illegal	illegal	ADJ
ajst-31456	24	32	parking	parking	NOUN
ajst-31456	24	33	[	[	X
ajst-31456	24	34	5	5	NUM
ajst-31456	24	35	]	]	PUNCT
ajst-31456	24	36	.	.	PUNCT
ajst-31456	25	1	in	in	ADP
ajst-31456	25	2	order	order	NOUN
ajst-31456	25	3	to	to	PART
ajst-31456	25	4	solve	solve	VERB
ajst-31456	25	5	the	the	DET
ajst-31456	25	6	above	above	ADJ
ajst-31456	25	7	problems	problem	NOUN
ajst-31456	25	8	,	,	PUNCT
ajst-31456	25	9	this	this	DET
ajst-31456	25	10	paper	paper	NOUN
ajst-31456	25	11	proposes	propose	VERB
ajst-31456	25	12	an	an	DET
ajst-31456	25	13	integrated	integrate	VERB
ajst-31456	25	14	framework	framework	NOUN
ajst-31456	25	15	and	and	CCONJ
ajst-31456	25	16	data	datum	NOUN
ajst-31456	25	17	processing	processing	NOUN
ajst-31456	25	18	methods	method	NOUN
ajst-31456	25	19	to	to	PART
ajst-31456	25	20	maximize	maximize	VERB
ajst-31456	25	21	the	the	DET
ajst-31456	25	22	relationship	relationship	NOUN
ajst-31456	25	23	and	and	CCONJ
ajst-31456	25	24	use	use	NOUN
ajst-31456	25	25	of	of	ADP
ajst-31456	25	26	mining	mining	NOUN
ajst-31456	25	27	features.first	features.first	PROPN
ajst-31456	25	28	,	,	PUNCT
ajst-31456	25	29	after	after	ADP
ajst-31456	25	30	careful	careful	ADJ
ajst-31456	25	31	data	datum	NOUN
ajst-31456	25	32	analysis	analysis	NOUN
ajst-31456	25	33	,	,	PUNCT
ajst-31456	25	34	the	the	DET
ajst-31456	25	35	processing	processing	NOUN
ajst-31456	25	36	method	method	NOUN
ajst-31456	25	37	of	of	ADP
ajst-31456	25	38	each	each	DET
ajst-31456	25	39	feature	feature	NOUN
ajst-31456	25	40	is	be	AUX
ajst-31456	25	41	determined	determine	VERB
ajst-31456	25	42	.	.	PUNCT
ajst-31456	26	1	after	after	ADP
ajst-31456	26	2	that	that	PRON
ajst-31456	26	3	,	,	PUNCT
ajst-31456	26	4	the	the	DET
ajst-31456	26	5	missing	miss	VERB
ajst-31456	26	6	values	value	NOUN
ajst-31456	26	7	of	of	ADP
ajst-31456	26	8	each	each	DET
ajst-31456	26	9	feature	feature	NOUN
ajst-31456	26	10	are	be	AUX
ajst-31456	26	11	processed	process	VERB
ajst-31456	26	12	by	by	ADP
ajst-31456	26	13	the	the	DET
ajst-31456	26	14	capping	capping	NOUN
ajst-31456	26	15	method	method	NOUN
ajst-31456	26	16	.	.	PUNCT
ajst-31456	27	1	use	use	VERB
ajst-31456	27	2	feature	feature	NOUN
ajst-31456	27	3	engineering	engineering	NOUN
ajst-31456	27	4	to	to	PART
ajst-31456	27	5	disassemble	disassemble	VERB
ajst-31456	27	6	,	,	PUNCT
ajst-31456	27	7	construct	construct	VERB
ajst-31456	27	8	features.second	features.second	NOUN
ajst-31456	27	9	,	,	PUNCT
ajst-31456	27	10	because	because	SCONJ
ajst-31456	27	11	many	many	ADJ
ajst-31456	27	12	features	feature	NOUN
ajst-31456	27	13	are	be	AUX
ajst-31456	27	14	generated	generate	VERB
ajst-31456	27	15	in	in	ADP
ajst-31456	27	16	the	the	DET
ajst-31456	27	17	process	process	NOUN
ajst-31456	27	18	of	of	ADP
ajst-31456	27	19	constructing	construct	VERB
ajst-31456	27	20	interactive	interactive	ADJ
ajst-31456	27	21	features	feature	NOUN
ajst-31456	27	22	,	,	PUNCT
ajst-31456	27	23	this	this	DET
ajst-31456	27	24	paper	paper	NOUN
ajst-31456	27	25	uses	use	VERB
ajst-31456	27	26	xgboost	xgboost	PROPN
ajst-31456	27	27	model	model	PROPN
ajst-31456	27	28	to	to	ADP
ajst-31456	27	29	screen	screen	NOUN
ajst-31456	27	30	features	feature	NOUN
ajst-31456	27	31	,	,	PUNCT
ajst-31456	27	32	and	and	CCONJ
ajst-31456	27	33	selects	select	VERB
ajst-31456	27	34	the	the	DET
ajst-31456	27	35	best	good	ADJ
ajst-31456	27	36	top	top	ADJ
ajst-31456	27	37	100	100	NUM
ajst-31456	27	38	features	feature	NOUN
ajst-31456	27	39	for	for	ADP
ajst-31456	27	40	later	later	ADJ
ajst-31456	27	41	input	input	NOUN
ajst-31456	27	42	model	model	NOUN
ajst-31456	27	43	.	.	PUNCT
ajst-31456	28	1	finally	finally	ADV
ajst-31456	28	2	,	,	PUNCT
ajst-31456	28	3	many	many	ADJ
ajst-31456	28	4	models	model	NOUN
ajst-31456	28	5	are	be	AUX
ajst-31456	28	6	constructed	construct	VERB
ajst-31456	28	7	for	for	ADP
ajst-31456	28	8	evaluation	evaluation	NOUN
ajst-31456	28	9	and	and	CCONJ
ajst-31456	28	10	comparison	comparison	NOUN
ajst-31456	28	11	,	,	PUNCT
ajst-31456	28	12	and	and	CCONJ
ajst-31456	28	13	it	it	PRON
ajst-31456	28	14	is	be	AUX
ajst-31456	28	15	found	find	VERB
ajst-31456	28	16	that	that	SCONJ
ajst-31456	28	17	the	the	DET
ajst-31456	28	18	tree	tree	NOUN
ajst-31456	28	19	based	base	VERB
ajst-31456	28	20	model	model	NOUN
ajst-31456	28	21	lightgbm	lightgbm	VERB
ajst-31456	28	22	has	have	VERB
ajst-31456	28	23	the	the	DET
ajst-31456	28	24	best	good	ADJ
ajst-31456	28	25	effect	effect	NOUN
ajst-31456	28	26	.	.	PUNCT
ajst-31456	29	1	the	the	DET
ajst-31456	29	2	super	super	ADJ
ajst-31456	29	3	parameter	parameter	NOUN
ajst-31456	29	4	optimization	optimization	NOUN
ajst-31456	29	5	such	such	ADJ
ajst-31456	29	6	as	as	ADP
ajst-31456	29	7	grid	grid	NOUN
ajst-31456	29	8	search	search	NOUN
ajst-31456	29	9	is	be	AUX
ajst-31456	29	10	carried	carry	VERB
ajst-31456	29	11	out	out	ADP
ajst-31456	29	12	for	for	ADP
ajst-31456	29	13	multiple	multiple	ADJ
ajst-31456	29	14	parameters	parameter	NOUN
ajst-31456	29	15	of	of	ADP
ajst-31456	29	16	lightgbm	lightgbm	NOUN
ajst-31456	29	17	,	,	PUNCT
ajst-31456	29	18	which	which	PRON
ajst-31456	29	19	further	far	ADV
ajst-31456	29	20	improves	improve	VERB
ajst-31456	29	21	the	the	DET
ajst-31456	29	22	performance	performance	NOUN
ajst-31456	29	23	of	of	ADP
ajst-31456	29	24	the	the	DET
ajst-31456	29	25	model	model	NOUN
ajst-31456	29	26	.	.	PUNCT
ajst-31456	30	1	the	the	DET
ajst-31456	30	2	scope	scope	NOUN
ajst-31456	30	3	of	of	ADP
ajst-31456	30	4	these	these	DET
ajst-31456	30	5	forecasting	forecasting	NOUN
ajst-31456	30	6	challenges	challenge	NOUN
ajst-31456	30	7	is	be	AUX
ajst-31456	30	8	broad	broad	ADJ
ajst-31456	30	9	,	,	PUNCT
ajst-31456	30	10	ranging	range	VERB
ajst-31456	30	11	from	from	ADP
ajst-31456	30	12	short	short	ADJ
ajst-31456	30	13	-	-	PUNCT
ajst-31456	30	14	term	term	NOUN
ajst-31456	30	15	operational	operational	ADJ
ajst-31456	30	16	predictions	prediction	NOUN
ajst-31456	30	17	to	to	ADP
ajst-31456	30	18	long	long	ADJ
ajst-31456	30	19	-	-	PUNCT
ajst-31456	30	20	term	term	NOUN
ajst-31456	30	21	time	time	NOUN
ajst-31456	30	22	series	series	NOUN
ajst-31456	30	23	analysis	analysis	NOUN
ajst-31456	30	24	that	that	PRON
ajst-31456	30	25	must	must	AUX
ajst-31456	30	26	account	account	VERB
ajst-31456	30	27	for	for	ADP
ajst-31456	30	28	major	major	ADJ
ajst-31456	30	29	external	external	ADJ
ajst-31456	30	30	events	event	NOUN
ajst-31456	30	31	like	like	ADP
ajst-31456	30	32	the	the	DET
ajst-31456	30	33	covid-19	covid-19	PROPN
ajst-31456	30	34	pandemic	pandemic	NOUN
ajst-31456	31	1	[	[	X
ajst-31456	31	2	6	6	NUM
ajst-31456	31	3	]	]	PUNCT
ajst-31456	31	4	.	.	PUNCT
ajst-31456	32	1	comprehensive	comprehensive	ADJ
ajst-31456	32	2	data	data	PROPN
ajst-31456	32	3	analytics	analytic	NOUN
ajst-31456	32	4	systems	system	NOUN
ajst-31456	32	5	are	be	AUX
ajst-31456	32	6	therefore	therefore	ADV
ajst-31456	32	7	essential	essential	ADJ
ajst-31456	32	8	,	,	PUNCT
ajst-31456	32	9	providing	provide	VERB
ajst-31456	32	10	practical	practical	ADJ
ajst-31456	32	11	insights	insight	NOUN
ajst-31456	32	12	into	into	ADP
ajst-31456	32	13	usage	usage	NOUN
ajst-31456	32	14	trends	trend	NOUN
ajst-31456	32	15	for	for	ADP
ajst-31456	32	16	vendors	vendor	NOUN
ajst-31456	32	17	and	and	CCONJ
ajst-31456	32	18	city	city	NOUN
ajst-31456	32	19	planners	planner	NOUN
ajst-31456	32	20	alike	alike	ADV
ajst-31456	32	21	[	[	X
ajst-31456	32	22	7	7	NUM
ajst-31456	32	23	]	]	PUNCT
ajst-31456	32	24	.	.	PUNCT
ajst-31456	33	1	in	in	ADP
ajst-31456	33	2	order	order	NOUN
ajst-31456	33	3	to	to	PART
ajst-31456	33	4	verify	verify	VERB
ajst-31456	33	5	the	the	DET
ajst-31456	33	6	effectiveness	effectiveness	NOUN
ajst-31456	33	7	of	of	ADP
ajst-31456	33	8	our	our	PRON
ajst-31456	33	9	algorithm	algorithm	NOUN
ajst-31456	33	10	,	,	PUNCT
ajst-31456	33	11	we	we	PRON
ajst-31456	33	12	designed	design	VERB
ajst-31456	33	13	the	the	DET
ajst-31456	33	14	following	follow	VERB
ajst-31456	33	15	experiments	experiment	NOUN
ajst-31456	33	16	:	:	PUNCT
ajst-31456	33	17	1	1	X
ajst-31456	33	18	.	.	X
ajst-31456	33	19	comparative	comparative	ADJ
ajst-31456	33	20	experiment	experiment	NOUN
ajst-31456	33	21	:	:	PUNCT
ajst-31456	33	22	this	this	DET
ajst-31456	33	23	paper	paper	NOUN
ajst-31456	33	24	will	will	AUX
ajst-31456	33	25	compare	compare	VERB
ajst-31456	33	26	with	with	ADP
ajst-31456	33	27	52	52	NUM
ajst-31456	33	28	the	the	DET
ajst-31456	33	29	algorithms	algorithm	NOUN
ajst-31456	33	30	used	use	VERB
ajst-31456	33	31	in	in	ADP
ajst-31456	33	32	other	other	ADJ
ajst-31456	33	33	papers	paper	NOUN
ajst-31456	33	34	on	on	ADP
ajst-31456	33	35	the	the	DET
ajst-31456	33	36	same	same	ADJ
ajst-31456	33	37	data	datum	NOUN
ajst-31456	33	38	set	set	VERB
ajst-31456	33	39	and	and	CCONJ
ajst-31456	33	40	will	will	AUX
ajst-31456	33	41	use	use	VERB
ajst-31456	33	42	the	the	DET
ajst-31456	33	43	same	same	ADJ
ajst-31456	33	44	evaluation	evaluation	NOUN
ajst-31456	33	45	criteria	criterion	NOUN
ajst-31456	33	46	such	such	ADJ
ajst-31456	33	47	as	as	ADP
ajst-31456	33	48	rmse	rmse	NOUN
ajst-31456	33	49	,	,	PUNCT
ajst-31456	33	50	r2	r2	PROPN
ajst-31456	33	51	to	to	PART
ajst-31456	33	52	fairly	fairly	ADV
ajst-31456	33	53	show	show	VERB
ajst-31456	33	54	the	the	DET
ajst-31456	33	55	advantages	advantage	NOUN
ajst-31456	33	56	and	and	CCONJ
ajst-31456	33	57	disadvantages	disadvantage	NOUN
ajst-31456	33	58	of	of	ADP
ajst-31456	33	59	all	all	DET
ajst-31456	33	60	algorithms	algorithm	NOUN
ajst-31456	33	61	.	.	PUNCT
ajst-31456	34	1	2	2	X
ajst-31456	34	2	.	.	X
ajst-31456	34	3	ablation	ablation	NOUN
ajst-31456	34	4	experiment	experiment	NOUN
ajst-31456	34	5	:	:	PUNCT
ajst-31456	34	6	in	in	ADP
ajst-31456	34	7	the	the	DET
ajst-31456	34	8	ablation	ablation	NOUN
ajst-31456	34	9	experiment	experiment	NOUN
ajst-31456	34	10	,	,	PUNCT
ajst-31456	34	11	this	this	DET
ajst-31456	34	12	paper	paper	NOUN
ajst-31456	34	13	will	will	AUX
ajst-31456	34	14	compare	compare	VERB
ajst-31456	34	15	the	the	DET
ajst-31456	34	16	changes	change	NOUN
ajst-31456	34	17	of	of	ADP
ajst-31456	34	18	the	the	DET
ajst-31456	34	19	model	model	NOUN
ajst-31456	34	20	effect	effect	NOUN
ajst-31456	34	21	in	in	ADP
ajst-31456	34	22	the	the	DET
ajst-31456	34	23	case	case	NOUN
ajst-31456	34	24	of	of	ADP
ajst-31456	34	25	removing	remove	VERB
ajst-31456	34	26	different	different	ADJ
ajst-31456	34	27	modules	module	NOUN
ajst-31456	34	28	,	,	PUNCT
ajst-31456	34	29	in	in	ADP
ajst-31456	34	30	order	order	NOUN
ajst-31456	34	31	to	to	PART
ajst-31456	34	32	get	get	VERB
ajst-31456	34	33	the	the	DET
ajst-31456	34	34	best	good	ADJ
ajst-31456	34	35	effect	effect	NOUN
ajst-31456	34	36	only	only	ADV
ajst-31456	34	37	when	when	SCONJ
ajst-31456	34	38	the	the	DET
ajst-31456	34	39	three	three	NUM
ajst-31456	34	40	modules	module	NOUN
ajst-31456	34	41	work	work	VERB
ajst-31456	34	42	together	together	ADV
ajst-31456	34	43	.	.	PUNCT
ajst-31456	35	1	the	the	DET
ajst-31456	35	2	contributions	contribution	NOUN
ajst-31456	35	3	of	of	ADP
ajst-31456	35	4	this	this	DET
ajst-31456	35	5	paper	paper	NOUN
ajst-31456	35	6	are	be	AUX
ajst-31456	35	7	as	as	SCONJ
ajst-31456	35	8	follows	follow	VERB
ajst-31456	35	9	:	:	PUNCT
ajst-31456	36	1	1	1	X
ajst-31456	36	2	.	.	PUNCT
ajst-31456	36	3	this	this	DET
ajst-31456	36	4	paper	paper	NOUN
ajst-31456	36	5	analyzes	analyze	VERB
ajst-31456	36	6	the	the	DET
ajst-31456	36	7	shortcomings	shortcoming	NOUN
ajst-31456	36	8	of	of	ADP
ajst-31456	36	9	existing	exist	VERB
ajst-31456	36	10	methods	method	NOUN
ajst-31456	36	11	in	in	ADP
ajst-31456	36	12	data	datum	NOUN
ajst-31456	36	13	preprocessing	preprocessing	NOUN
ajst-31456	36	14	and	and	CCONJ
ajst-31456	36	15	feature	feature	NOUN
ajst-31456	36	16	engineering	engineering	NOUN
ajst-31456	36	17	in	in	ADP
ajst-31456	36	18	detail	detail	NOUN
ajst-31456	36	19	,	,	PUNCT
ajst-31456	36	20	and	and	CCONJ
ajst-31456	36	21	introduces	introduce	VERB
ajst-31456	36	22	the	the	DET
ajst-31456	36	23	detailed	detailed	ADJ
ajst-31456	36	24	data	datum	NOUN
ajst-31456	36	25	preprocessing	preprocessing	NOUN
ajst-31456	36	26	methods	method	NOUN
ajst-31456	36	27	and	and	CCONJ
ajst-31456	36	28	feature	feature	NOUN
ajst-31456	36	29	engineering	engineering	NOUN
ajst-31456	36	30	processing	processing	NOUN
ajst-31456	36	31	,	,	PUNCT
ajst-31456	36	32	especially	especially	ADV
ajst-31456	36	33	the	the	DET
ajst-31456	36	34	interval	interval	NOUN
ajst-31456	36	35	division	division	NOUN
ajst-31456	36	36	of	of	ADP
ajst-31456	36	37	different	different	ADJ
ajst-31456	36	38	natural	natural	ADJ
ajst-31456	36	39	variables	variable	NOUN
ajst-31456	36	40	and	and	CCONJ
ajst-31456	36	41	the	the	DET
ajst-31456	36	42	dynamic	dynamic	ADJ
ajst-31456	36	43	changes	change	NOUN
ajst-31456	36	44	of	of	ADP
ajst-31456	36	45	natural	natural	ADJ
ajst-31456	36	46	variables	variable	NOUN
ajst-31456	36	47	in	in	ADP
ajst-31456	36	48	different	different	ADJ
ajst-31456	36	49	time	time	NOUN
ajst-31456	36	50	,	,	PUNCT
ajst-31456	36	51	which	which	PRON
ajst-31456	36	52	provides	provide	VERB
ajst-31456	36	53	effective	effective	ADJ
ajst-31456	36	54	help	help	NOUN
ajst-31456	36	55	for	for	ADP
ajst-31456	36	56	subsequent	subsequent	ADJ
ajst-31456	36	57	researchers	researcher	NOUN
ajst-31456	36	58	.	.	PUNCT
ajst-31456	37	1	2	2	X
ajst-31456	37	2	.	.	X
ajst-31456	37	3	this	this	DET
ajst-31456	37	4	paper	paper	NOUN
ajst-31456	37	5	proposes	propose	VERB
ajst-31456	37	6	a	a	DET
ajst-31456	37	7	general	general	ADJ
ajst-31456	37	8	and	and	CCONJ
ajst-31456	37	9	detailed	detailed	ADJ
ajst-31456	37	10	framework	framework	NOUN
ajst-31456	37	11	of	of	ADP
ajst-31456	37	12	three	three	NUM
ajst-31456	37	13	modules	module	NOUN
ajst-31456	37	14	to	to	PART
ajst-31456	37	15	solve	solve	VERB
ajst-31456	37	16	the	the	DET
ajst-31456	37	17	problem	problem	NOUN
ajst-31456	37	18	of	of	ADP
ajst-31456	37	19	forecasting	forecast	VERB
ajst-31456	37	20	the	the	DET
ajst-31456	37	21	demand	demand	NOUN
ajst-31456	37	22	for	for	ADP
ajst-31456	37	23	shared	share	VERB
ajst-31456	37	24	single	single	ADJ
ajst-31456	37	25	vehicles	vehicle	NOUN
ajst-31456	37	26	.	.	PUNCT
ajst-31456	38	1	first	first	ADV
ajst-31456	38	2	,	,	PUNCT
ajst-31456	38	3	analysis	analysis	NOUN
ajst-31456	38	4	and	and	CCONJ
ajst-31456	38	5	processing	processing	NOUN
ajst-31456	38	6	,	,	PUNCT
ajst-31456	38	7	second	second	ADJ
ajst-31456	38	8	,	,	PUNCT
ajst-31456	38	9	feature	feature	NOUN
ajst-31456	38	10	selection	selection	NOUN
ajst-31456	38	11	,	,	PUNCT
ajst-31456	38	12	and	and	CCONJ
ajst-31456	38	13	finally	finally	ADV
ajst-31456	38	14	,	,	PUNCT
ajst-31456	38	15	model	model	NOUN
ajst-31456	38	16	construction	construction	NOUN
ajst-31456	38	17	and	and	CCONJ
ajst-31456	38	18	superparameter	superparameter	ADJ
ajst-31456	38	19	optimization	optimization	NOUN
ajst-31456	38	20	.	.	PUNCT
ajst-31456	39	1	this	this	DET
ajst-31456	39	2	framework	framework	NOUN
ajst-31456	39	3	process	process	NOUN
ajst-31456	39	4	can	can	AUX
ajst-31456	39	5	provide	provide	VERB
ajst-31456	39	6	clear	clear	ADJ
ajst-31456	39	7	ideas	idea	NOUN
ajst-31456	39	8	for	for	ADP
ajst-31456	39	9	other	other	ADJ
ajst-31456	39	10	researchers	researcher	NOUN
ajst-31456	39	11	.	.	PUNCT
ajst-31456	40	1	3	3	X
ajst-31456	40	2	.	.	X
ajst-31456	40	3	the	the	DET
ajst-31456	40	4	effectiveness	effectiveness	NOUN
ajst-31456	40	5	of	of	ADP
ajst-31456	40	6	the	the	DET
ajst-31456	40	7	results	result	NOUN
ajst-31456	40	8	is	be	AUX
ajst-31456	40	9	proved	prove	VERB
ajst-31456	40	10	by	by	ADP
ajst-31456	40	11	a	a	DET
ajst-31456	40	12	large	large	ADJ
ajst-31456	40	13	number	number	NOUN
ajst-31456	40	14	of	of	ADP
ajst-31456	40	15	experiments	experiment	NOUN
ajst-31456	40	16	,	,	PUNCT
ajst-31456	40	17	and	and	CCONJ
ajst-31456	40	18	the	the	DET
ajst-31456	40	19	effectiveness	effectiveness	NOUN
ajst-31456	40	20	and	and	CCONJ
ajst-31456	40	21	advance	advance	NOUN
ajst-31456	40	22	ment	ment	NOUN
ajst-31456	40	23	of	of	ADP
ajst-31456	40	24	the	the	DET
ajst-31456	40	25	framework	framework	NOUN
ajst-31456	40	26	algorithm	algorithm	NOUN
ajst-31456	40	27	are	be	AUX
ajst-31456	40	28	proved	prove	VERB
ajst-31456	40	29	by	by	ADP
ajst-31456	40	30	comparative	comparative	ADJ
ajst-31456	40	31	experiments	experiment	NOUN
ajst-31456	40	32	.	.	PUNCT
ajst-31456	41	1	at	at	ADP
ajst-31456	41	2	the	the	DET
ajst-31456	41	3	same	same	ADJ
ajst-31456	41	4	time	time	NOUN
ajst-31456	41	5	,	,	PUNCT
ajst-31456	41	6	the	the	DET
ajst-31456	41	7	ablation	ablation	NOUN
ajst-31456	41	8	experiment	experiment	NOUN
ajst-31456	41	9	shows	show	VERB
ajst-31456	41	10	that	that	SCONJ
ajst-31456	41	11	the	the	DET
ajst-31456	41	12	three	three	NUM
ajst-31456	41	13	modules	module	NOUN
ajst-31456	41	14	in	in	ADP
ajst-31456	41	15	the	the	DET
ajst-31456	41	16	framework	framework	NOUN
ajst-31456	41	17	are	be	AUX
ajst-31456	41	18	indispensable	indispensable	ADJ
ajst-31456	41	19	.	.	PUNCT
ajst-31456	42	1	2	2	X
ajst-31456	42	2	.	.	X
ajst-31456	42	3	related	relate	VERB
ajst-31456	42	4	work	work	NOUN
ajst-31456	42	5	[	[	X
ajst-31456	42	6	8	8	NUM
ajst-31456	42	7	]	]	PUNCT
ajst-31456	42	8	discussed	discuss	VERB
ajst-31456	42	9	the	the	DET
ajst-31456	42	10	main	main	ADJ
ajst-31456	42	11	influencing	influence	VERB
ajst-31456	42	12	factors	factor	NOUN
ajst-31456	42	13	of	of	ADP
ajst-31456	42	14	short	short	ADJ
ajst-31456	42	15	-	-	PUNCT
ajst-31456	42	16	term	term	NOUN
ajst-31456	42	17	(	(	PUNCT
ajst-31456	42	18	hour	hour	NOUN
ajst-31456	42	19	based	base	VERB
ajst-31456	42	20	)	)	PUNCT
ajst-31456	42	21	demand	demand	NOUN
ajst-31456	42	22	forecasting	forecasting	NOUN
ajst-31456	42	23	for	for	ADP
ajst-31456	42	24	shared	share	VERB
ajst-31456	42	25	bicycles	bicycle	NOUN
ajst-31456	42	26	based	base	VERB
ajst-31456	42	27	on	on	ADP
ajst-31456	42	28	the	the	DET
ajst-31456	42	29	multi	multi	ADJ
ajst-31456	42	30	-	-	ADJ
ajst-31456	42	31	dimensional	dimensional	ADJ
ajst-31456	42	32	large	large	ADJ
ajst-31456	42	33	sample	sample	NOUN
ajst-31456	42	34	data	datum	NOUN
ajst-31456	42	35	of	of	ADP
ajst-31456	42	36	shared	share	VERB
ajst-31456	42	37	bicycles	bicycle	NOUN
ajst-31456	42	38	,	,	PUNCT
ajst-31456	42	39	using	use	VERB
ajst-31456	42	40	machine	machine	NOUN
ajst-31456	42	41	learning	learning	NOUN
ajst-31456	42	42	models	model	NOUN
ajst-31456	42	43	such	such	ADJ
ajst-31456	42	44	as	as	ADP
ajst-31456	42	45	lasso	lasso	NOUN
ajst-31456	42	46	regression	regression	NOUN
ajst-31456	42	47	,	,	PUNCT
ajst-31456	42	48	ridge	ridge	NOUN
ajst-31456	42	49	regression	regression	NOUN
ajst-31456	42	50	,	,	PUNCT
ajst-31456	42	51	random	random	ADJ
ajst-31456	42	52	forest	forest	NOUN
ajst-31456	42	53	and	and	CCONJ
ajst-31456	42	54	iterative	iterative	NOUN
ajst-31456	42	55	decision	decision	NOUN
ajst-31456	42	56	tree	tree	NOUN
ajst-31456	42	57	,	,	PUNCT
ajst-31456	42	58	and	and	CCONJ
ajst-31456	42	59	compared	compare	VERB
ajst-31456	42	60	the	the	DET
ajst-31456	42	61	forecasting	forecasting	NOUN
ajst-31456	42	62	effects	effect	NOUN
ajst-31456	42	63	of	of	ADP
ajst-31456	42	64	different	different	ADJ
ajst-31456	42	65	models	model	NOUN
ajst-31456	42	66	.	.	PUNCT
ajst-31456	43	1	[	[	X
ajst-31456	43	2	8	8	NUM
ajst-31456	43	3	]	]	PUNCT
ajst-31456	43	4	have	have	AUX
ajst-31456	43	5	made	make	VERB
ajst-31456	43	6	important	important	ADJ
ajst-31456	43	7	contributions	contribution	NOUN
ajst-31456	43	8	to	to	PART
ajst-31456	43	9	feature	feature	VERB
ajst-31456	43	10	construction	construction	NOUN
ajst-31456	43	11	and	and	CCONJ
ajst-31456	43	12	processing	processing	NOUN
ajst-31456	43	13	by	by	ADP
ajst-31456	43	14	identifying	identify	VERB
ajst-31456	43	15	key	key	ADJ
ajst-31456	43	16	factors	factor	NOUN
ajst-31456	43	17	such	such	ADJ
ajst-31456	43	18	as	as	ADP
ajst-31456	43	19	time	time	NOUN
ajst-31456	43	20	,	,	PUNCT
ajst-31456	43	21	place	place	NOUN
ajst-31456	43	22	and	and	CCONJ
ajst-31456	43	23	weather	weather	NOUN
ajst-31456	43	24	,	,	PUNCT
ajst-31456	43	25	and	and	CCONJ
ajst-31456	43	26	dividing	divide	VERB
ajst-31456	43	27	dates	date	NOUN
ajst-31456	43	28	into	into	ADP
ajst-31456	43	29	weekdays	weekday	NOUN
ajst-31456	43	30	and	and	CCONJ
ajst-31456	43	31	weekends	weekend	NOUN
ajst-31456	43	32	,	,	PUNCT
ajst-31456	43	33	which	which	PRON
ajst-31456	43	34	makes	make	VERB
ajst-31456	43	35	the	the	DET
ajst-31456	43	36	feature	feature	NOUN
ajst-31456	43	37	division	division	NOUN
ajst-31456	43	38	very	very	ADV
ajst-31456	43	39	delicate	delicate	ADJ
ajst-31456	43	40	,	,	PUNCT
ajst-31456	43	41	but	but	CCONJ
ajst-31456	43	42	there	there	PRON
ajst-31456	43	43	is	be	VERB
ajst-31456	43	44	still	still	ADV
ajst-31456	43	45	a	a	DET
ajst-31456	43	46	lack	lack	NOUN
ajst-31456	43	47	of	of	ADP
ajst-31456	43	48	explicit	explicit	ADJ
ajst-31456	43	49	interactive	interactive	ADJ
ajst-31456	43	50	feature	feature	NOUN
ajst-31456	43	51	construction	construction	NOUN
ajst-31456	43	52	.	.	PUNCT
ajst-31456	44	1	their	their	PRON
ajst-31456	44	2	research	research	NOUN
ajst-31456	44	3	relies	rely	VERB
ajst-31456	44	4	on	on	ADP
ajst-31456	44	5	implicit	implicit	ADJ
ajst-31456	44	6	learning	learning	NOUN
ajst-31456	44	7	of	of	ADP
ajst-31456	44	8	these	these	DET
ajst-31456	44	9	relationships	relationship	NOUN
ajst-31456	44	10	such	such	ADJ
ajst-31456	44	11	as	as	ADP
ajst-31456	44	12	random	random	ADJ
ajst-31456	44	13	forests	forest	NOUN
ajst-31456	44	14	,	,	PUNCT
ajst-31456	44	15	and	and	CCONJ
ajst-31456	44	16	may	may	AUX
ajst-31456	44	17	not	not	PART
ajst-31456	44	18	be	be	AUX
ajst-31456	44	19	able	able	ADJ
ajst-31456	44	20	to	to	PART
ajst-31456	44	21	capture	capture	VERB
ajst-31456	44	22	obvious	obvious	ADJ
ajst-31456	44	23	interactive	interactive	ADJ
ajst-31456	44	24	relationships	relationship	NOUN
ajst-31456	44	25	,	,	PUNCT
ajst-31456	44	26	such	such	ADJ
ajst-31456	44	27	as	as	ADP
ajst-31456	44	28	time	time	NOUN
ajst-31456	44	29	and	and	CCONJ
ajst-31456	44	30	temperature	temperature	NOUN
ajst-31456	44	31	.	.	PUNCT
ajst-31456	45	1	the	the	DET
ajst-31456	45	2	first	first	ADJ
ajst-31456	45	3	module	module	NOUN
ajst-31456	45	4	of	of	ADP
ajst-31456	45	5	this	this	DET
ajst-31456	45	6	paper	paper	NOUN
ajst-31456	45	7	can	can	AUX
ajst-31456	45	8	accurately	accurately	ADV
ajst-31456	45	9	solve	solve	VERB
ajst-31456	45	10	these	these	DET
ajst-31456	45	11	relationships	relationship	NOUN
ajst-31456	45	12	.	.	PUNCT
ajst-31456	46	1	this	this	DET
ajst-31456	46	2	paper	paper	NOUN
ajst-31456	46	3	not	not	PART
ajst-31456	46	4	only	only	ADV
ajst-31456	46	5	constructs	construct	VERB
ajst-31456	46	6	the	the	DET
ajst-31456	46	7	random	random	ADJ
ajst-31456	46	8	forest	forest	NOUN
ajst-31456	46	9	model	model	NOUN
ajst-31456	46	10	to	to	PART
ajst-31456	46	11	implicitly	implicitly	ADV
ajst-31456	46	12	learn	learn	VERB
ajst-31456	46	13	the	the	DET
ajst-31456	46	14	nonlinear	nonlinear	ADJ
ajst-31456	46	15	relationship	relationship	NOUN
ajst-31456	46	16	,	,	PUNCT
ajst-31456	46	17	but	but	CCONJ
ajst-31456	46	18	also	also	ADV
ajst-31456	46	19	explicitly	explicitly	ADV
ajst-31456	46	20	constructs	construct	VERB
ajst-31456	46	21	the	the	DET
ajst-31456	46	22	interactive	interactive	ADJ
ajst-31456	46	23	characteristics	characteristic	NOUN
ajst-31456	46	24	,	,	PUNCT
ajst-31456	46	25	so	so	SCONJ
ajst-31456	46	26	that	that	SCONJ
ajst-31456	46	27	the	the	DET
ajst-31456	46	28	model	model	NOUN
ajst-31456	46	29	has	have	VERB
ajst-31456	46	30	a	a	DET
ajst-31456	46	31	higher	high	ADJ
ajst-31456	46	32	starting	starting	NOUN
ajst-31456	46	33	point	point	NOUN
ajst-31456	46	34	at	at	ADP
ajst-31456	46	35	the	the	DET
ajst-31456	46	36	beginning	beginning	NOUN
ajst-31456	46	37	,	,	PUNCT
ajst-31456	46	38	and	and	CCONJ
ajst-31456	46	39	can	can	AUX
ajst-31456	46	40	learn	learn	VERB
ajst-31456	46	41	the	the	DET
ajst-31456	46	42	shallow	shallow	ADJ
ajst-31456	46	43	and	and	CCONJ
ajst-31456	46	44	deep	deep	ADJ
ajst-31456	46	45	relationship	relationship	NOUN
ajst-31456	46	46	at	at	ADP
ajst-31456	46	47	the	the	DET
ajst-31456	46	48	same	same	ADJ
ajst-31456	46	49	time	time	NOUN
ajst-31456	46	50	.	.	PUNCT
ajst-31456	47	1	at	at	ADP
ajst-31456	47	2	the	the	DET
ajst-31456	47	3	same	same	ADJ
ajst-31456	47	4	time	time	NOUN
ajst-31456	47	5	[	[	X
ajst-31456	47	6	8	8	NUM
ajst-31456	47	7	]	]	PUNCT
ajst-31456	47	8	mentioned	mention	VERB
ajst-31456	47	9	that	that	SCONJ
ajst-31456	47	10	75	75	NUM
ajst-31456	47	11	explanatory	explanatory	ADJ
ajst-31456	47	12	variables	variable	NOUN
ajst-31456	47	13	were	be	AUX
ajst-31456	47	14	selected	select	VERB
ajst-31456	47	15	for	for	ADP
ajst-31456	47	16	the	the	DET
ajst-31456	47	17	ols	ol	NOUN
ajst-31456	47	18	model	model	NOUN
ajst-31456	47	19	,	,	PUNCT
ajst-31456	47	20	but	but	CCONJ
ajst-31456	47	21	no	no	DET
ajst-31456	47	22	special	special	ADJ
ajst-31456	47	23	screening	screening	NOUN
ajst-31456	47	24	was	be	AUX
ajst-31456	47	25	done	do	VERB
ajst-31456	47	26	,	,	PUNCT
ajst-31456	47	27	which	which	PRON
ajst-31456	47	28	may	may	AUX
ajst-31456	47	29	greatly	greatly	ADV
ajst-31456	47	30	increase	increase	VERB
ajst-31456	47	31	the	the	DET
ajst-31456	47	32	time	time	NOUN
ajst-31456	47	33	complexity	complexity	NOUN
ajst-31456	47	34	in	in	ADP
ajst-31456	47	35	general	general	ADJ
ajst-31456	47	36	,	,	PUNCT
ajst-31456	47	37	while	while	SCONJ
ajst-31456	47	38	allowing	allow	VERB
ajst-31456	47	39	the	the	DET
ajst-31456	47	40	model	model	NOUN
ajst-31456	47	41	to	to	PART
ajst-31456	47	42	learn	learn	VERB
ajst-31456	47	43	unimportant	unimportant	ADJ
ajst-31456	47	44	features	feature	NOUN
ajst-31456	47	45	and	and	CCONJ
ajst-31456	47	46	weaken	weaken	VERB
ajst-31456	47	47	the	the	DET
ajst-31456	47	48	performance	performance	NOUN
ajst-31456	47	49	.	.	PUNCT
ajst-31456	48	1	therefore	therefore	ADV
ajst-31456	48	2	,	,	PUNCT
ajst-31456	48	3	the	the	DET
ajst-31456	48	4	second	second	ADJ
ajst-31456	48	5	module	module	NOUN
ajst-31456	48	6	of	of	ADP
ajst-31456	48	7	this	this	DET
ajst-31456	48	8	paper	paper	NOUN
ajst-31456	48	9	can	can	AUX
ajst-31456	48	10	also	also	ADV
ajst-31456	48	11	perfectly	perfectly	ADV
ajst-31456	48	12	solve	solve	VERB
ajst-31456	48	13	this	this	DET
ajst-31456	48	14	problem	problem	NOUN
ajst-31456	48	15	by	by	ADP
ajst-31456	48	16	using	use	VERB
ajst-31456	48	17	xgboost	xgboost	PROPN
ajst-31456	48	18	model	model	NOUN
ajst-31456	48	19	to	to	PART
ajst-31456	48	20	screen	screen	VERB
ajst-31456	48	21	the	the	DET
ajst-31456	48	22	number	number	NOUN
ajst-31456	48	23	of	of	ADP
ajst-31456	48	24	features	feature	NOUN
ajst-31456	48	25	.	.	PUNCT
ajst-31456	49	1	similarly	similarly	ADV
ajst-31456	49	2	,	,	PUNCT
ajst-31456	49	3	other	other	ADJ
ajst-31456	49	4	studies	study	NOUN
ajst-31456	49	5	have	have	AUX
ajst-31456	49	6	also	also	ADV
ajst-31456	49	7	focused	focus	VERB
ajst-31456	49	8	on	on	ADP
ajst-31456	49	9	short	short	ADJ
ajst-31456	49	10	-	-	PUNCT
ajst-31456	49	11	term	term	NOUN
ajst-31456	49	12	forecasting	forecasting	NOUN
ajst-31456	49	13	by	by	ADP
ajst-31456	49	14	combining	combine	VERB
ajst-31456	49	15	machine	machine	NOUN
ajst-31456	49	16	learning	learning	NOUN
ajst-31456	49	17	with	with	ADP
ajst-31456	49	18	methods	method	NOUN
ajst-31456	49	19	like	like	ADP
ajst-31456	49	20	spatial	spatial	ADJ
ajst-31456	49	21	constraint	constraint	NOUN
ajst-31456	49	22	clustering	cluster	VERB
ajst-31456	49	23	to	to	ADP
ajst-31456	49	24	group	group	NOUN
ajst-31456	49	25	stations	station	NOUN
ajst-31456	49	26	before	before	ADP
ajst-31456	49	27	prediction	prediction	NOUN
ajst-31456	49	28	[	[	X
ajst-31456	49	29	9	9	NUM
ajst-31456	49	30	]	]	PUNCT
ajst-31456	49	31	.	.	PUNCT
ajst-31456	50	1	in	in	ADP
ajst-31456	50	2	contrast	contrast	NOUN
ajst-31456	50	3	,	,	PUNCT
ajst-31456	50	4	some	some	DET
ajst-31456	50	5	approaches	approach	NOUN
ajst-31456	50	6	argue	argue	VERB
ajst-31456	50	7	for	for	ADP
ajst-31456	50	8	simplicity	simplicity	NOUN
ajst-31456	50	9	,	,	PUNCT
ajst-31456	50	10	demonstrating	demonstrate	VERB
ajst-31456	50	11	that	that	SCONJ
ajst-31456	50	12	incremental	incremental	ADJ
ajst-31456	50	13	learning	learning	NOUN
ajst-31456	50	14	models	model	NOUN
ajst-31456	50	15	with	with	ADP
ajst-31456	50	16	minimal	minimal	ADJ
ajst-31456	50	17	features	feature	NOUN
ajst-31456	50	18	can	can	AUX
ajst-31456	50	19	achieve	achieve	VERB
ajst-31456	50	20	high	high	ADJ
ajst-31456	50	21	accuracy	accuracy	NOUN
ajst-31456	50	22	for	for	ADP
ajst-31456	50	23	short	short	ADJ
ajst-31456	50	24	-	-	PUNCT
ajst-31456	50	25	term	term	NOUN
ajst-31456	50	26	predictions	prediction	NOUN
ajst-31456	50	27	[	[	X
ajst-31456	50	28	10	10	NUM
ajst-31456	50	29	]	]	PUNCT
ajst-31456	50	30	.	.	PUNCT
ajst-31456	51	1	[	[	X
ajst-31456	51	2	11	11	NUM
ajst-31456	51	3	]	]	PUNCT
ajst-31456	51	4	proved	prove	VERB
ajst-31456	51	5	that	that	SCONJ
ajst-31456	51	6	within	within	ADP
ajst-31456	51	7	the	the	DET
ajst-31456	51	8	neural	neural	ADJ
ajst-31456	51	9	network	network	NOUN
ajst-31456	51	10	,	,	PUNCT
ajst-31456	51	11	the	the	DET
ajst-31456	51	12	lstm	lstm	NOUN
ajst-31456	51	13	with	with	ADP
ajst-31456	51	14	more	more	ADJ
ajst-31456	51	15	complex	complex	ADJ
ajst-31456	51	16	structure	structure	NOUN
ajst-31456	51	17	is	be	AUX
ajst-31456	51	18	superior	superior	ADJ
ajst-31456	51	19	to	to	ADP
ajst-31456	51	20	the	the	DET
ajst-31456	51	21	traditional	traditional	ADJ
ajst-31456	51	22	rnn	rnn	NOUN
ajst-31456	51	23	and	and	CCONJ
ajst-31456	51	24	bp	bp	PROPN
ajst-31456	51	25	network	network	PROPN
ajst-31456	51	26	,	,	PUNCT
ajst-31456	51	27	which	which	PRON
ajst-31456	51	28	is	be	AUX
ajst-31456	51	29	an	an	DET
ajst-31456	51	30	excellent	excellent	ADJ
ajst-31456	51	31	conclusion	conclusion	NOUN
ajst-31456	51	32	.	.	PUNCT
ajst-31456	52	1	however	however	ADV
ajst-31456	52	2	,	,	PUNCT
ajst-31456	52	3	it	it	PRON
ajst-31456	52	4	also	also	ADV
ajst-31456	52	5	has	have	VERB
ajst-31456	52	6	similar	similar	ADJ
ajst-31456	52	7	problems	problem	NOUN
ajst-31456	52	8	in	in	ADP
ajst-31456	52	9	the	the	DET
ajst-31456	52	10	processing	processing	NOUN
ajst-31456	52	11	of	of	ADP
ajst-31456	52	12	features	feature	NOUN
ajst-31456	52	13	,	,	PUNCT
ajst-31456	52	14	that	that	ADV
ajst-31456	52	15	is	is	ADV
ajst-31456	52	16	,	,	PUNCT
ajst-31456	52	17	it	it	PRON
ajst-31456	52	18	simply	simply	ADV
ajst-31456	52	19	carries	carry	VERB
ajst-31456	52	20	out	out	ADP
ajst-31456	52	21	data	data	NOUN
ajst-31456	52	22	standardization	standardization	NOUN
ajst-31456	52	23	and	and	CCONJ
ajst-31456	52	24	missing	miss	VERB
ajst-31456	52	25	value	value	NOUN
ajst-31456	52	26	filling	filling	NOUN
ajst-31456	52	27	,	,	PUNCT
ajst-31456	52	28	and	and	CCONJ
ajst-31456	52	29	does	do	AUX
ajst-31456	52	30	not	not	PART
ajst-31456	52	31	consider	consider	VERB
ajst-31456	52	32	the	the	DET
ajst-31456	52	33	relationship	relationship	NOUN
ajst-31456	52	34	and	and	CCONJ
ajst-31456	52	35	details	detail	NOUN
ajst-31456	52	36	of	of	ADP
ajst-31456	52	37	feature	feature	NOUN
ajst-31456	52	38	time	time	NOUN
ajst-31456	52	39	,	,	PUNCT
ajst-31456	52	40	which	which	PRON
ajst-31456	52	41	can	can	AUX
ajst-31456	52	42	be	be	AUX
ajst-31456	52	43	discussed	discuss	VERB
ajst-31456	52	44	in	in	ADP
ajst-31456	52	45	depth	depth	NOUN
ajst-31456	52	46	in	in	ADP
ajst-31456	52	47	this	this	DET
ajst-31456	52	48	module	module	NOUN
ajst-31456	52	49	.	.	PUNCT
ajst-31456	53	1	similarly	similarly	ADV
ajst-31456	53	2	,	,	PUNCT
ajst-31456	53	3	[	[	X
ajst-31456	53	4	11	11	NUM
ajst-31456	53	5	]	]	PUNCT
ajst-31456	53	6	did	do	AUX
ajst-31456	53	7	not	not	PART
ajst-31456	53	8	carry	carry	VERB
ajst-31456	53	9	out	out	ADP
ajst-31456	53	10	feature	feature	NOUN
ajst-31456	53	11	screening	screen	VERB
ajst-31456	53	12	work	work	NOUN
ajst-31456	53	13	,	,	PUNCT
ajst-31456	53	14	but	but	CCONJ
ajst-31456	53	15	directly	directly	ADV
ajst-31456	53	16	input	input	VERB
ajst-31456	53	17	60	60	NUM
ajst-31456	53	18	features	feature	NOUN
ajst-31456	53	19	into	into	ADP
ajst-31456	53	20	the	the	DET
ajst-31456	53	21	model	model	NOUN
ajst-31456	53	22	,	,	PUNCT
ajst-31456	53	23	which	which	PRON
ajst-31456	53	24	can	can	AUX
ajst-31456	53	25	also	also	ADV
ajst-31456	53	26	be	be	AUX
ajst-31456	53	27	solved	solve	VERB
ajst-31456	53	28	by	by	ADP
ajst-31456	53	29	applying	apply	VERB
ajst-31456	53	30	the	the	DET
ajst-31456	53	31	second	second	ADJ
ajst-31456	53	32	module	module	NOUN
ajst-31456	53	33	of	of	ADP
ajst-31456	53	34	this	this	DET
ajst-31456	53	35	paper	paper	NOUN
ajst-31456	53	36	.	.	PUNCT
ajst-31456	54	1	[	[	X
ajst-31456	54	2	12	12	NUM
ajst-31456	54	3	]	]	PUNCT
ajst-31456	54	4	have	have	AUX
ajst-31456	54	5	made	make	VERB
ajst-31456	54	6	great	great	ADJ
ajst-31456	54	7	breakthroughs	breakthrough	NOUN
ajst-31456	54	8	in	in	ADP
ajst-31456	54	9	the	the	DET
ajst-31456	54	10	innovation	innovation	NOUN
ajst-31456	54	11	of	of	ADP
ajst-31456	54	12	model	model	NOUN
ajst-31456	54	13	architecture	architecture	NOUN
ajst-31456	54	14	.	.	PUNCT
ajst-31456	55	1	they	they	PRON
ajst-31456	55	2	use	use	VERB
ajst-31456	55	3	convolutional	convolutional	ADJ
ajst-31456	55	4	network	network	NOUN
ajst-31456	55	5	(	(	PUNCT
ajst-31456	55	6	cnn	cnn	PROPN
ajst-31456	55	7	)	)	PUNCT
ajst-31456	55	8	to	to	PART
ajst-31456	55	9	extract	extract	VERB
ajst-31456	55	10	local	local	ADJ
ajst-31456	55	11	features	feature	NOUN
ajst-31456	55	12	,	,	PUNCT
ajst-31456	55	13	bidirectional	bidirectional	ADJ
ajst-31456	55	14	long	long	ADJ
ajst-31456	55	15	-	-	PUNCT
ajst-31456	55	16	term	term	NOUN
ajst-31456	55	17	and	and	CCONJ
ajst-31456	55	18	short	short	ADJ
ajst-31456	55	19	term	term	NOUN
ajst-31456	55	20	memory	memory	NOUN
ajst-31456	55	21	network	network	NOUN
ajst-31456	55	22	(	(	PUNCT
ajst-31456	55	23	bilstm	bilstm	NOUN
ajst-31456	55	24	)	)	PUNCT
ajst-31456	55	25	to	to	PART
ajst-31456	55	26	capture	capture	VERB
ajst-31456	55	27	long	long	ADJ
ajst-31456	55	28	-	-	PUNCT
ajst-31456	55	29	term	term	NOUN
ajst-31456	55	30	time	time	NOUN
ajst-31456	55	31	dependence	dependence	NOUN
ajst-31456	55	32	,	,	PUNCT
ajst-31456	55	33	and	and	CCONJ
ajst-31456	55	34	attention	attention	NOUN
ajst-31456	55	35	mechanism	mechanism	NOUN
ajst-31456	55	36	to	to	PART
ajst-31456	55	37	dynamically	dynamically	VERB
ajst-31456	55	38	allocate	allocate	VERB
ajst-31456	55	39	feature	feature	NOUN
ajst-31456	55	40	weights	weight	NOUN
ajst-31456	55	41	.	.	PUNCT
ajst-31456	56	1	this	this	PRON
ajst-31456	56	2	is	be	AUX
ajst-31456	56	3	a	a	DET
ajst-31456	56	4	very	very	ADV
ajst-31456	56	5	advanced	advanced	ADJ
ajst-31456	56	6	combination	combination	NOUN
ajst-31456	56	7	of	of	ADP
ajst-31456	56	8	algorithms	algorithm	NOUN
ajst-31456	56	9	,	,	PUNCT
ajst-31456	56	10	but	but	CCONJ
ajst-31456	56	11	the	the	DET
ajst-31456	56	12	above	above	ADJ
ajst-31456	56	13	problems	problem	NOUN
ajst-31456	56	14	still	still	ADV
ajst-31456	56	15	exist	exist	VERB
ajst-31456	56	16	in	in	ADP
ajst-31456	56	17	the	the	DET
ajst-31456	56	18	processing	processing	NOUN
ajst-31456	56	19	of	of	ADP
ajst-31456	56	20	features	feature	NOUN
ajst-31456	56	21	and	and	CCONJ
ajst-31456	56	22	target	target	NOUN
ajst-31456	56	23	variables	variable	NOUN
ajst-31456	56	24	.	.	PUNCT
ajst-31456	57	1	beyond	beyond	ADP
ajst-31456	57	2	mainstream	mainstream	NOUN
ajst-31456	57	3	learning	learning	NOUN
ajst-31456	57	4	models	model	NOUN
ajst-31456	57	5	,	,	PUNCT
ajst-31456	57	6	some	some	DET
ajst-31456	57	7	research	research	NOUN
ajst-31456	57	8	has	have	AUX
ajst-31456	57	9	applied	apply	VERB
ajst-31456	57	10	advanced	advanced	ADJ
ajst-31456	57	11	statistical	statistical	ADJ
ajst-31456	57	12	methods	method	NOUN
ajst-31456	57	13	,	,	PUNCT
ajst-31456	57	14	such	such	ADJ
ajst-31456	57	15	as	as	ADP
ajst-31456	57	16	bimodal	bimodal	NOUN
ajst-31456	57	17	gaussian	gaussian	NOUN
ajst-31456	57	18	inhomogeneous	inhomogeneous	ADJ
ajst-31456	57	19	poisson	poisson	NOUN
ajst-31456	57	20	processes	process	NOUN
ajst-31456	57	21	,	,	PUNCT
ajst-31456	57	22	to	to	PART
ajst-31456	57	23	predict	predict	VERB
ajst-31456	57	24	bike	bike	NOUN
ajst-31456	57	25	counts	count	NOUN
ajst-31456	57	26	[	[	X
ajst-31456	57	27	13	13	NUM
ajst-31456	57	28	]	]	PUNCT
ajst-31456	57	29	.	.	PUNCT
ajst-31456	58	1	to	to	PART
ajst-31456	58	2	tackle	tackle	VERB
ajst-31456	58	3	the	the	DET
ajst-31456	58	4	prediction	prediction	NOUN
ajst-31456	58	5	challenge	challenge	NOUN
ajst-31456	58	6	at	at	ADP
ajst-31456	58	7	different	different	ADJ
ajst-31456	58	8	spatial	spatial	ADJ
ajst-31456	58	9	scales	scale	NOUN
ajst-31456	58	10	,	,	PUNCT
ajst-31456	58	11	hierarchical	hierarchical	ADJ
ajst-31456	58	12	prediction	prediction	NOUN
ajst-31456	58	13	methods	method	NOUN
ajst-31456	58	14	have	have	AUX
ajst-31456	58	15	been	be	AUX
ajst-31456	58	16	proposed	propose	VERB
ajst-31456	58	17	,	,	PUNCT
ajst-31456	58	18	which	which	PRON
ajst-31456	58	19	ensure	ensure	VERB
ajst-31456	58	20	consistency	consistency	NOUN
ajst-31456	58	21	across	across	ADP
ajst-31456	58	22	various	various	ADJ
ajst-31456	58	23	levels	level	NOUN
ajst-31456	58	24	,	,	PUNCT
ajst-31456	58	25	from	from	ADP
ajst-31456	58	26	individual	individual	ADJ
ajst-31456	58	27	stations	station	NOUN
ajst-31456	58	28	and	and	CCONJ
ajst-31456	58	29	clusters	cluster	NOUN
ajst-31456	58	30	to	to	ADP
ajst-31456	58	31	the	the	DET
ajst-31456	58	32	entire	entire	ADJ
ajst-31456	58	33	city	city	NOUN
ajst-31456	58	34	[	[	X
ajst-31456	58	35	14	14	NUM
ajst-31456	58	36	]	]	PUNCT
ajst-31456	58	37	,	,	PUNCT
ajst-31456	58	38	[	[	X
ajst-31456	58	39	15	15	NUM
ajst-31456	58	40	]	]	PUNCT
ajst-31456	58	41	.	.	PUNCT
ajst-31456	59	1	in	in	ADP
ajst-31456	59	2	addition	addition	NOUN
ajst-31456	59	3	to	to	ADP
ajst-31456	59	4	rnn	rnn	PROPN
ajst-31456	59	5	-	-	PUNCT
ajst-31456	59	6	based	base	VERB
ajst-31456	59	7	architectures	architecture	NOUN
ajst-31456	59	8	,	,	PUNCT
ajst-31456	59	9	other	other	ADJ
ajst-31456	59	10	works	work	NOUN
ajst-31456	59	11	have	have	AUX
ajst-31456	59	12	explored	explore	VERB
ajst-31456	59	13	different	different	ADJ
ajst-31456	59	14	approaches	approach	NOUN
ajst-31456	59	15	.	.	PUNCT
ajst-31456	60	1	for	for	ADP
ajst-31456	60	2	instance	instance	NOUN
ajst-31456	60	3	,	,	PUNCT
ajst-31456	60	4	to	to	PART
ajst-31456	60	5	improve	improve	VERB
ajst-31456	60	6	training	training	NOUN
ajst-31456	60	7	efficiency	efficiency	NOUN
ajst-31456	60	8	,	,	PUNCT
ajst-31456	60	9	he	he	PRON
ajst-31456	60	10	et	et	PROPN
ajst-31456	60	11	al	al	PROPN
ajst-31456	60	12	.	.	PROPN
ajst-31456	60	13	introduced	introduce	VERB
ajst-31456	60	14	a	a	DET
ajst-31456	60	15	model	model	NOUN
ajst-31456	60	16	integrating	integrate	VERB
ajst-31456	60	17	a	a	DET
ajst-31456	60	18	temporal	temporal	ADJ
ajst-31456	60	19	convolutional	convolutional	ADJ
ajst-31456	60	20	network	network	NOUN
ajst-31456	60	21	(	(	PUNCT
ajst-31456	60	22	tcn	tcn	PROPN
ajst-31456	60	23	)	)	PUNCT
ajst-31456	60	24	with	with	ADP
ajst-31456	60	25	self	self	NOUN
ajst-31456	60	26	-	-	PUNCT
ajst-31456	60	27	attention	attention	NOUN
ajst-31456	60	28	,	,	PUNCT
ajst-31456	60	29	utilizing	utilize	VERB
ajst-31456	60	30	periodic	periodic	ADJ
ajst-31456	60	31	time	time	NOUN
ajst-31456	60	32	signals	signal	NOUN
ajst-31456	60	33	for	for	ADP
ajst-31456	60	34	better	well	ADJ
ajst-31456	60	35	feature	feature	NOUN
ajst-31456	60	36	representation	representation	NOUN
ajst-31456	60	37	[	[	X
ajst-31456	60	38	16	16	NUM
ajst-31456	60	39	]	]	PUNCT
ajst-31456	60	40	.	.	PUNCT
ajst-31456	61	1	to	to	PART
ajst-31456	61	2	provide	provide	VERB
ajst-31456	61	3	more	more	ADJ
ajst-31456	61	4	operational	operational	ADJ
ajst-31456	61	5	value	value	NOUN
ajst-31456	61	6	,	,	PUNCT
ajst-31456	61	7	yang	yang	PROPN
ajst-31456	61	8	et	et	PROPN
ajst-31456	61	9	al	al	PROPN
ajst-31456	61	10	.	.	PROPN
ajst-31456	61	11	developed	develop	VERB
ajst-31456	61	12	a	a	DET
ajst-31456	61	13	dual	dual	ADJ
ajst-31456	61	14	-	-	PUNCT
ajst-31456	61	15	branch	branch	NOUN
ajst-31456	61	16	neural	neural	ADJ
ajst-31456	61	17	network	network	NOUN
ajst-31456	61	18	to	to	PART
ajst-31456	61	19	simultaneously	simultaneously	ADV
ajst-31456	61	20	predict	predict	VERB
ajst-31456	61	21	bike	bike	NOUN
ajst-31456	61	22	counts	count	NOUN
ajst-31456	61	23	and	and	CCONJ
ajst-31456	61	24	classify	classify	VERB
ajst-31456	61	25	the	the	DET
ajst-31456	61	26	station	station	NOUN
ajst-31456	61	27	’s	’s	PART
ajst-31456	61	28	imbalance	imbalance	NOUN
ajst-31456	61	29	level	level	NOUN
ajst-31456	61	30	,	,	PUNCT
ajst-31456	61	31	offering	offer	VERB
ajst-31456	61	32	richer	rich	ADJ
ajst-31456	61	33	information	information	NOUN
ajst-31456	61	34	for	for	ADP
ajst-31456	61	35	rebalancing	rebalancing	NOUN
ajst-31456	61	36	[	[	X
ajst-31456	61	37	17	17	NUM
ajst-31456	61	38	]	]	PUNCT
ajst-31456	61	39	.	.	PUNCT
ajst-31456	62	1	moving	move	VERB
ajst-31456	62	2	beyond	beyond	ADP
ajst-31456	62	3	pure	pure	ADJ
ajst-31456	62	4	prediction	prediction	NOUN
ajst-31456	62	5	accuracy	accuracy	NOUN
ajst-31456	62	6	,	,	PUNCT
ajst-31456	62	7	some	some	DET
ajst-31456	62	8	research	research	NOUN
ajst-31456	62	9	aims	aim	VERB
ajst-31456	62	10	for	for	ADP
ajst-31456	62	11	model	model	NOUN
ajst-31456	62	12	interpretability	interpretability	NOUN
ajst-31456	62	13	.	.	PUNCT
ajst-31456	63	1	gu	gu	NOUN
ajst-31456	63	2	et	et	PROPN
ajst-31456	63	3	al	al	PROPN
ajst-31456	63	4	.	.	PROPN
ajst-31456	63	5	proposed	propose	VERB
ajst-31456	63	6	a	a	DET
ajst-31456	63	7	framework	framework	NOUN
ajst-31456	63	8	to	to	PART
ajst-31456	63	9	predict	predict	VERB
ajst-31456	63	10	bike	bike	NOUN
ajst-31456	63	11	flow	flow	NOUN
ajst-31456	63	12	patterns	pattern	NOUN
ajst-31456	63	13	between	between	ADP
ajst-31456	63	14	regions	region	NOUN
ajst-31456	63	15	by	by	ADP
ajst-31456	63	16	constructing	construct	VERB
ajst-31456	63	17	interpretable	interpretable	ADJ
ajst-31456	63	18	base	base	NOUN
ajst-31456	63	19	matrices	matrix	NOUN
ajst-31456	63	20	that	that	PRON
ajst-31456	63	21	represent	represent	VERB
ajst-31456	63	22	underlying	underlie	VERB
ajst-31456	63	23	traffic	traffic	NOUN
ajst-31456	63	24	modes	mode	NOUN
ajst-31456	63	25	[	[	X
ajst-31456	63	26	18	18	NUM
ajst-31456	63	27	]	]	PUNCT
ajst-31456	63	28	.	.	PUNCT
ajst-31456	64	1	other	other	ADJ
ajst-31456	64	2	research	research	NOUN
ajst-31456	64	3	has	have	AUX
ajst-31456	64	4	focused	focus	VERB
ajst-31456	64	5	on	on	ADP
ajst-31456	64	6	optimizing	optimize	VERB
ajst-31456	64	7	the	the	DET
ajst-31456	64	8	prediction	prediction	NOUN
ajst-31456	64	9	task	task	NOUN
ajst-31456	64	10	for	for	ADP
ajst-31456	64	11	operational	operational	ADJ
ajst-31456	64	12	efficiency	efficiency	NOUN
ajst-31456	64	13	.	.	PUNCT
ajst-31456	65	1	for	for	ADP
ajst-31456	65	2	example	example	NOUN
ajst-31456	65	3	,	,	PUNCT
ajst-31456	65	4	huang	huang	PROPN
ajst-31456	65	5	et	et	PROPN
ajst-31456	65	6	al	al	PROPN
ajst-31456	65	7	.	.	PROPN
ajst-31456	65	8	proposed	propose	VERB
ajst-31456	65	9	the	the	DET
ajst-31456	65	10	concept	concept	NOUN
ajst-31456	65	11	of	of	ADP
ajst-31456	65	12	”	"	PUNCT
ajst-31456	65	13	central	central	ADJ
ajst-31456	65	14	stations	station	NOUN
ajst-31456	65	15	”	"	PUNCT
ajst-31456	65	16	to	to	PART
ajst-31456	65	17	reduce	reduce	VERB
ajst-31456	65	18	computational	computational	ADJ
ajst-31456	65	19	and	and	CCONJ
ajst-31456	65	20	rebalancing	rebalancing	NOUN
ajst-31456	65	21	costs	cost	NOUN
ajst-31456	65	22	by	by	ADP
ajst-31456	65	23	focusing	focus	VERB
ajst-31456	65	24	prediction	prediction	NOUN
ajst-31456	65	25	efforts	effort	NOUN
ajst-31456	65	26	only	only	ADV
ajst-31456	65	27	on	on	ADP
ajst-31456	65	28	high	high	ADJ
ajst-31456	65	29	-	-	PUNCT
ajst-31456	65	30	demand	demand	NOUN
ajst-31456	65	31	locations	location	NOUN
ajst-31456	65	32	[	[	X
ajst-31456	65	33	19	19	NUM
ajst-31456	65	34	]	]	PUNCT
ajst-31456	65	35	.	.	PUNCT
ajst-31456	66	1	some	some	DET
ajst-31456	66	2	works	work	NOUN
ajst-31456	66	3	combine	combine	VERB
ajst-31456	66	4	geographic	geographic	ADJ
ajst-31456	66	5	information	information	NOUN
ajst-31456	66	6	systems	system	NOUN
ajst-31456	66	7	(	(	PUNCT
ajst-31456	66	8	gis	gis	NOUN
ajst-31456	66	9	)	)	PUNCT
ajst-31456	66	10	with	with	ADP
ajst-31456	66	11	deep	deep	ADJ
ajst-31456	66	12	learning	learning	NOUN
ajst-31456	66	13	,	,	PUNCT
ajst-31456	66	14	such	such	ADJ
ajst-31456	66	15	as	as	ADP
ajst-31456	66	16	gstnet	gstnet	NOUN
ajst-31456	66	17	,	,	PUNCT
ajst-31456	66	18	which	which	PRON
ajst-31456	66	19	uses	use	VERB
ajst-31456	66	20	gaussian	gaussian	ADJ
ajst-31456	66	21	mixture	mixture	NOUN
ajst-31456	66	22	model	model	NOUN
ajst-31456	66	23	clustering	cluster	VERB
ajst-31456	66	24	before	before	ADP
ajst-31456	66	25	applying	apply	VERB
ajst-31456	66	26	a	a	DET
ajst-31456	66	27	3d	3d	NOUN
ajst-31456	66	28	-	-	PUNCT
ajst-31456	66	29	cnn	cnn	NOUN
ajst-31456	66	30	to	to	PART
ajst-31456	66	31	predict	predict	VERB
ajst-31456	66	32	traffic	traffic	NOUN
ajst-31456	66	33	flow	flow	NOUN
ajst-31456	66	34	between	between	ADP
ajst-31456	66	35	station	station	NOUN
ajst-31456	66	36	groups	group	NOUN
ajst-31456	66	37	[	[	X
ajst-31456	66	38	20	20	NUM
ajst-31456	66	39	]	]	PUNCT
ajst-31456	66	40	.	.	PUNCT
ajst-31456	67	1	the	the	DET
ajst-31456	67	2	prediction	prediction	NOUN
ajst-31456	67	3	horizon	horizon	NOUN
ajst-31456	67	4	is	be	AUX
ajst-31456	67	5	also	also	ADV
ajst-31456	67	6	a	a	DET
ajst-31456	67	7	key	key	ADJ
ajst-31456	67	8	variable	variable	NOUN
ajst-31456	67	9	,	,	PUNCT
ajst-31456	67	10	with	with	SCONJ
ajst-31456	67	11	models	model	NOUN
ajst-31456	67	12	like	like	ADP
ajst-31456	67	13	bi	bi	NOUN
ajst-31456	67	14	-	-	ADJ
ajst-31456	67	15	lstm	lstm	ADJ
ajst-31456	67	16	being	be	AUX
ajst-31456	67	17	specifically	specifically	ADV
ajst-31456	67	18	evaluated	evaluate	VERB
ajst-31456	67	19	for	for	ADP
ajst-31456	67	20	very	very	ADV
ajst-31456	67	21	short	short	ADJ
ajst-31456	67	22	-	-	PUNCT
ajst-31456	67	23	term	term	NOUN
ajst-31456	67	24	forecasting	forecasting	NOUN
ajst-31456	67	25	(	(	PUNCT
ajst-31456	67	26	15	15	NUM
ajst-31456	67	27	-	-	SYM
ajst-31456	67	28	60	60	NUM
ajst-31456	67	29	minutes	minute	NOUN
ajst-31456	67	30	)	)	PUNCT
ajst-31456	67	31	,	,	PUNCT
ajst-31456	67	32	often	often	ADV
ajst-31456	67	33	incorporating	incorporate	VERB
ajst-31456	67	34	explainability	explainability	NOUN
ajst-31456	67	35	methods	method	NOUN
ajst-31456	67	36	like	like	ADP
ajst-31456	67	37	shap	shap	PROPN
ajst-31456	67	38	to	to	PART
ajst-31456	67	39	interpret	interpret	VERB
ajst-31456	67	40	feature	feature	NOUN
ajst-31456	67	41	importance	importance	NOUN
ajst-31456	67	42	[	[	X
ajst-31456	67	43	21	21	NUM
ajst-31456	67	44	]	]	PUNCT
ajst-31456	67	45	.	.	PUNCT
ajst-31456	68	1	a	a	DET
ajst-31456	68	2	completely	completely	ADV
ajst-31456	68	3	different	different	ADJ
ajst-31456	68	4	perspective	perspective	NOUN
ajst-31456	68	5	is	be	AUX
ajst-31456	68	6	to	to	PART
ajst-31456	68	7	predict	predict	VERB
ajst-31456	68	8	the	the	DET
ajst-31456	68	9	destination	destination	NOUN
ajst-31456	68	10	of	of	ADP
ajst-31456	68	11	an	an	DET
ajst-31456	68	12	individual	individual	ADJ
ajst-31456	68	13	trip	trip	NOUN
ajst-31456	68	14	rather	rather	ADV
ajst-31456	68	15	than	than	ADP
ajst-31456	68	16	station	station	NOUN
ajst-31456	68	17	-	-	PUNCT
ajst-31456	68	18	level	level	NOUN
ajst-31456	68	19	demand	demand	NOUN
ajst-31456	68	20	,	,	PUNCT
ajst-31456	68	21	framing	frame	VERB
ajst-31456	68	22	it	it	PRON
ajst-31456	68	23	as	as	ADP
ajst-31456	68	24	a	a	DET
ajst-31456	68	25	classification	classification	NOUN
ajst-31456	68	26	problem	problem	NOUN
ajst-31456	68	27	based	base	VERB
ajst-31456	68	28	on	on	ADP
ajst-31456	68	29	user	user	NOUN
ajst-31456	68	30	,	,	PUNCT
ajst-31456	68	31	time	time	NOUN
ajst-31456	68	32	,	,	PUNCT
ajst-31456	68	33	and	and	CCONJ
ajst-31456	68	34	location	location	NOUN
ajst-31456	68	35	features	feature	VERB
ajst-31456	68	36	[	[	X
ajst-31456	68	37	22	22	NUM
ajst-31456	68	38	]	]	PUNCT
ajst-31456	68	39	.	.	PUNCT
ajst-31456	69	1	further	far	ADV
ajst-31456	69	2	diversifying	diversify	VERB
ajst-31456	69	3	the	the	DET
ajst-31456	69	4	research	research	NOUN
ajst-31456	69	5	landscape	landscape	NOUN
ajst-31456	69	6	,	,	PUNCT
ajst-31456	69	7	some	some	DET
ajst-31456	69	8	works	work	NOUN
ajst-31456	69	9	shift	shift	VERB
ajst-31456	69	10	the	the	DET
ajst-31456	69	11	focus	focus	NOUN
ajst-31456	69	12	from	from	ADP
ajst-31456	69	13	operator	operator	NOUN
ajst-31456	69	14	-	-	PUNCT
ajst-31456	69	15	centric	centric	ADJ
ajst-31456	69	16	demand	demand	NOUN
ajst-31456	69	17	prediction	prediction	NOUN
ajst-31456	69	18	to	to	ADP
ajst-31456	69	19	user	user	NOUN
ajst-31456	69	20	-	-	PUNCT
ajst-31456	69	21	centric	centric	ADJ
ajst-31456	69	22	services	service	NOUN
ajst-31456	69	23	,	,	PUNCT
ajst-31456	69	24	such	such	ADJ
ajst-31456	69	25	as	as	ADP
ajst-31456	69	26	developing	develop	VERB
ajst-31456	69	27	machine	machine	NOUN
ajst-31456	69	28	learning	learning	NOUN
ajst-31456	69	29	systems	system	NOUN
ajst-31456	69	30	that	that	PRON
ajst-31456	69	31	recommend	recommend	VERB
ajst-31456	69	32	specific	specific	ADJ
ajst-31456	69	33	bikes	bike	NOUN
ajst-31456	69	34	to	to	ADP
ajst-31456	69	35	users	user	NOUN
ajst-31456	69	36	based	base	VERB
ajst-31456	69	37	on	on	ADP
ajst-31456	69	38	their	their	PRON
ajst-31456	69	39	travel	travel	NOUN
ajst-31456	69	40	needs	need	NOUN
ajst-31456	69	41	[	[	X
ajst-31456	69	42	23	23	NUM
ajst-31456	69	43	]	]	PUNCT
ajst-31456	69	44	.	.	PUNCT
ajst-31456	70	1	another	another	DET
ajst-31456	70	2	critical	critical	ADJ
ajst-31456	70	3	challenge	challenge	NOUN
ajst-31456	70	4	being	be	AUX
ajst-31456	70	5	addressed	address	VERB
ajst-31456	70	6	is	be	AUX
ajst-31456	70	7	the	the	DET
ajst-31456	70	8	’	'	PUNCT
ajst-31456	70	9	cold	cold	ADJ
ajst-31456	70	10	-	-	PUNCT
ajst-31456	70	11	start	start	NOUN
ajst-31456	70	12	’	'	PUNCT
ajst-31456	70	13	problem	problem	NOUN
ajst-31456	70	14	,	,	PUNCT
ajst-31456	70	15	where	where	SCONJ
ajst-31456	70	16	graph	graph	NOUN
ajst-31456	70	17	neural	neural	ADJ
ajst-31456	70	18	networks	network	NOUN
ajst-31456	70	19	are	be	AUX
ajst-31456	70	20	53	53	NUM
ajst-31456	70	21	utilized	utilize	VERB
ajst-31456	70	22	to	to	PART
ajst-31456	70	23	predict	predict	VERB
ajst-31456	70	24	traffic	traffic	NOUN
ajst-31456	70	25	flow	flow	NOUN
ajst-31456	70	26	for	for	ADP
ajst-31456	70	27	new	new	ADJ
ajst-31456	70	28	city	city	NOUN
ajst-31456	70	29	blocks	block	NOUN
ajst-31456	70	30	that	that	PRON
ajst-31456	70	31	lack	lack	VERB
ajst-31456	70	32	historical	historical	ADJ
ajst-31456	70	33	data	datum	NOUN
ajst-31456	70	34	,	,	PUNCT
ajst-31456	70	35	by	by	ADP
ajst-31456	70	36	modeling	model	VERB
ajst-31456	70	37	the	the	DET
ajst-31456	70	38	relationships	relationship	NOUN
ajst-31456	70	39	between	between	ADP
ajst-31456	70	40	them	they	PRON
ajst-31456	70	41	[	[	X
ajst-31456	70	42	24	24	NUM
ajst-31456	70	43	]	]	PUNCT
ajst-31456	70	44	.	.	PUNCT
ajst-31456	71	1	graph	graph	NOUN
ajst-31456	71	2	neural	neural	ADJ
ajst-31456	71	3	networks	network	NOUN
ajst-31456	71	4	(	(	PUNCT
ajst-31456	71	5	gnns	gnns	NOUN
ajst-31456	71	6	)	)	PUNCT
ajst-31456	71	7	have	have	AUX
ajst-31456	71	8	emerged	emerge	VERB
ajst-31456	71	9	as	as	ADP
ajst-31456	71	10	a	a	DET
ajst-31456	71	11	par	par	NOUN
ajst-31456	71	12	ticularly	ticularly	ADV
ajst-31456	71	13	powerful	powerful	ADJ
ajst-31456	71	14	tool	tool	NOUN
ajst-31456	71	15	for	for	ADP
ajst-31456	71	16	this	this	DET
ajst-31456	71	17	domain	domain	NOUN
ajst-31456	71	18	.	.	PUNCT
ajst-31456	72	1	for	for	ADP
ajst-31456	72	2	instance	instance	NOUN
ajst-31456	72	3	,	,	PUNCT
ajst-31456	72	4	guo	guo	PROPN
ajst-31456	72	5	et	et	PROPN
ajst-31456	72	6	al	al	PROPN
ajst-31456	72	7	.	.	PROPN
ajst-31456	72	8	proposed	propose	VERB
ajst-31456	72	9	bikenet	bikenet	PROPN
ajst-31456	72	10	,	,	PUNCT
ajst-31456	72	11	a	a	DET
ajst-31456	72	12	framework	framework	NOUN
ajst-31456	72	13	that	that	PRON
ajst-31456	72	14	uses	use	VERB
ajst-31456	72	15	a	a	DET
ajst-31456	72	16	spatiotemporal	spatiotemporal	ADJ
ajst-31456	72	17	gnn	gnn	NOUN
ajst-31456	72	18	to	to	PART
ajst-31456	72	19	predict	predict	VERB
ajst-31456	72	20	demand	demand	NOUN
ajst-31456	72	21	,	,	PUNCT
ajst-31456	72	22	which	which	PRON
ajst-31456	72	23	is	be	AUX
ajst-31456	72	24	then	then	ADV
ajst-31456	72	25	directly	directly	ADV
ajst-31456	72	26	used	use	VERB
ajst-31456	72	27	to	to	PART
ajst-31456	72	28	optimize	optimize	VERB
ajst-31456	72	29	station	station	NOUN
ajst-31456	72	30	rebalancing	rebalancing	NOUN
ajst-31456	72	31	via	via	ADP
ajst-31456	72	32	integer	integer	NOUN
ajst-31456	72	33	linear	linear	PROPN
ajst-31456	72	34	programming	programming	NOUN
ajst-31456	72	35	[	[	X
ajst-31456	72	36	25	25	NUM
ajst-31456	72	37	]	]	PUNCT
ajst-31456	72	38	.	.	PUNCT
ajst-31456	73	1	similarly	similarly	ADV
ajst-31456	73	2	,	,	PUNCT
ajst-31456	73	3	qin	qin	PROPN
ajst-31456	73	4	et	et	PROPN
ajst-31456	73	5	al	al	PROPN
ajst-31456	73	6	.	.	PROPN
ajst-31456	73	7	developed	develop	VERB
ajst-31456	73	8	a	a	DET
ajst-31456	73	9	two	two	NUM
ajst-31456	73	10	-	-	PUNCT
ajst-31456	73	11	step	step	NOUN
ajst-31456	73	12	solution	solution	NOUN
ajst-31456	73	13	using	use	VERB
ajst-31456	73	14	a	a	DET
ajst-31456	73	15	convolutional	convolutional	ADJ
ajst-31456	73	16	network	network	NOUN
ajst-31456	73	17	to	to	PART
ajst-31456	73	18	predict	predict	VERB
ajst-31456	73	19	flows	flow	NOUN
ajst-31456	73	20	and	and	CCONJ
ajst-31456	73	21	an	an	DET
ajst-31456	73	22	improved	improved	ADJ
ajst-31456	73	23	local	local	ADJ
ajst-31456	73	24	search	search	NOUN
ajst-31456	73	25	algorithm	algorithm	NOUN
ajst-31456	73	26	for	for	ADP
ajst-31456	73	27	multi	multi	ADJ
ajst-31456	73	28	-	-	ADJ
ajst-31456	73	29	carrier	carrier	NOUN
ajst-31456	73	30	path	path	NOUN
ajst-31456	73	31	planning	planning	NOUN
ajst-31456	73	32	[	[	X
ajst-31456	73	33	26	26	NUM
ajst-31456	73	34	]	]	PUNCT
ajst-31456	73	35	.	.	PUNCT
ajst-31456	74	1	to	to	PART
ajst-31456	74	2	further	far	ADV
ajst-31456	74	3	enrich	enrich	VERB
ajst-31456	74	4	the	the	DET
ajst-31456	74	5	model	model	NOUN
ajst-31456	74	6	’s	’s	PART
ajst-31456	74	7	context	context	NOUN
ajst-31456	74	8	,	,	PUNCT
ajst-31456	74	9	some	some	DET
ajst-31456	74	10	works	work	NOUN
ajst-31456	74	11	focus	focus	VERB
ajst-31456	74	12	on	on	ADP
ajst-31456	74	13	fusing	fuse	VERB
ajst-31456	74	14	heterogeneous	heterogeneous	ADJ
ajst-31456	74	15	data	datum	NOUN
ajst-31456	74	16	,	,	PUNCT
ajst-31456	74	17	such	such	ADJ
ajst-31456	74	18	as	as	ADP
ajst-31456	74	19	the	the	DET
ajst-31456	74	20	multi	multi	ADJ
ajst-31456	74	21	-	-	ADJ
ajst-31456	74	22	view	view	ADJ
ajst-31456	74	23	network	network	NOUN
ajst-31456	74	24	by	by	ADP
ajst-31456	74	25	chai	chai	NOUN
ajst-31456	74	26	et	et	PROPN
ajst-31456	74	27	al	al	PROPN
ajst-31456	74	28	.	.	PROPN
ajst-31456	74	29	,	,	PUNCT
ajst-31456	74	30	which	which	PRON
ajst-31456	74	31	integrates	integrate	VERB
ajst-31456	74	32	spatial	spatial	ADJ
ajst-31456	74	33	,	,	PUNCT
ajst-31456	74	34	temporal	temporal	ADJ
ajst-31456	74	35	,	,	PUNCT
ajst-31456	74	36	and	and	CCONJ
ajst-31456	74	37	semantic	semantic	ADJ
ajst-31456	74	38	information	information	NOUN
ajst-31456	74	39	[	[	X
ajst-31456	74	40	27	27	NUM
ajst-31456	74	41	]	]	PUNCT
ajst-31456	74	42	.	.	PUNCT
ajst-31456	75	1	a	a	DET
ajst-31456	75	2	more	more	ADV
ajst-31456	75	3	advanced	advanced	ADJ
ajst-31456	75	4	approach	approach	NOUN
ajst-31456	75	5	involves	involve	VERB
ajst-31456	75	6	crossmodal	crossmodal	ADJ
ajst-31456	75	7	knowledge	knowledge	NOUN
ajst-31456	75	8	transfer	transfer	NOUN
ajst-31456	75	9	,	,	PUNCT
ajst-31456	75	10	where	where	SCONJ
ajst-31456	75	11	domain	domain	NOUN
ajst-31456	75	12	-	-	PUNCT
ajst-31456	75	13	adversarial	adversarial	ADJ
ajst-31456	75	14	gnns	gnn	NOUN
ajst-31456	75	15	are	be	AUX
ajst-31456	75	16	used	use	VERB
ajst-31456	75	17	to	to	PART
ajst-31456	75	18	leverage	leverage	VERB
ajst-31456	75	19	data	datum	NOUN
ajst-31456	75	20	from	from	ADP
ajst-31456	75	21	other	other	ADJ
ajst-31456	75	22	transport	transport	NOUN
ajst-31456	75	23	systems	system	NOUN
ajst-31456	75	24	like	like	ADP
ajst-31456	75	25	subways	subway	NOUN
ajst-31456	75	26	and	and	CCONJ
ajst-31456	75	27	ride	ride	VERB
ajst-31456	75	28	-	-	PUNCT
ajst-31456	75	29	hailing	hail	VERB
ajst-31456	75	30	to	to	PART
ajst-31456	75	31	improve	improve	VERB
ajst-31456	75	32	bike	bike	NOUN
ajst-31456	75	33	demand	demand	NOUN
ajst-31456	75	34	prediction	prediction	NOUN
ajst-31456	75	35	,	,	PUNCT
ajst-31456	75	36	even	even	ADV
ajst-31456	75	37	when	when	SCONJ
ajst-31456	75	38	their	their	PRON
ajst-31456	75	39	demand	demand	NOUN
ajst-31456	75	40	patterns	pattern	NOUN
ajst-31456	75	41	differ	differ	VERB
ajst-31456	75	42	significantly	significantly	ADV
ajst-31456	75	43	[	[	X
ajst-31456	75	44	28	28	NUM
ajst-31456	75	45	]	]	PUNCT
ajst-31456	75	46	.	.	PUNCT
ajst-31456	76	1	beyond	beyond	ADP
ajst-31456	76	2	integrated	integrate	VERB
ajst-31456	76	3	frameworks	framework	NOUN
ajst-31456	76	4	,	,	PUNCT
ajst-31456	76	5	research	research	NOUN
ajst-31456	76	6	also	also	ADV
ajst-31456	76	7	investigates	investigate	VERB
ajst-31456	76	8	novel	novel	ADJ
ajst-31456	76	9	model	model	NOUN
ajst-31456	76	10	architectures	architecture	NOUN
ajst-31456	76	11	,	,	PUNCT
ajst-31456	76	12	such	such	ADJ
ajst-31456	76	13	as	as	ADP
ajst-31456	76	14	modular	modular	ADJ
ajst-31456	76	15	deep	deep	ADJ
ajst-31456	76	16	learning	learning	NOUN
ajst-31456	76	17	designs	design	NOUN
ajst-31456	76	18	that	that	PRON
ajst-31456	76	19	use	use	VERB
ajst-31456	76	20	separate	separate	ADJ
ajst-31456	76	21	components	component	NOUN
ajst-31456	76	22	like	like	ADP
ajst-31456	76	23	cnns	cnn	NOUN
ajst-31456	76	24	and	and	CCONJ
ajst-31456	76	25	lstms	lstms	NOUN
ajst-31456	76	26	to	to	PART
ajst-31456	76	27	capture	capture	VERB
ajst-31456	76	28	long	long	ADJ
ajst-31456	76	29	-	-	PUNCT
ajst-31456	76	30	term	term	NOUN
ajst-31456	76	31	and	and	CCONJ
ajst-31456	76	32	short	short	ADJ
ajst-31456	76	33	-	-	PUNCT
ajst-31456	76	34	term	term	NOUN
ajst-31456	76	35	patterns	pattern	NOUN
ajst-31456	76	36	respectively	respectively	ADV
ajst-31456	76	37	[	[	X
ajst-31456	76	38	29	29	NUM
ajst-31456	76	39	]	]	PUNCT
ajst-31456	76	40	.	.	PUNCT
ajst-31456	77	1	a	a	DET
ajst-31456	77	2	particularly	particularly	ADV
ajst-31456	77	3	novel	novel	ADJ
ajst-31456	77	4	approach	approach	NOUN
ajst-31456	77	5	tackles	tackle	VERB
ajst-31456	77	6	the	the	DET
ajst-31456	77	7	’	'	PUNCT
ajst-31456	77	8	cold	cold	ADJ
ajst-31456	77	9	-	-	PUNCT
ajst-31456	77	10	start	start	NOUN
ajst-31456	77	11	’	'	PUNCT
ajst-31456	77	12	prob	prob	NOUN
ajst-31456	77	13	lem	lem	NOUN
ajst-31456	77	14	for	for	ADP
ajst-31456	77	15	new	new	ADJ
ajst-31456	77	16	stations	station	NOUN
ajst-31456	77	17	by	by	ADP
ajst-31456	77	18	learning	learn	VERB
ajst-31456	77	19	’	'	PUNCT
ajst-31456	77	20	place	place	NOUN
ajst-31456	77	21	representations	representation	NOUN
ajst-31456	77	22	’	'	PUNCT
ajst-31456	77	23	.	.	PUNCT
ajst-31456	78	1	instead	instead	ADV
ajst-31456	78	2	of	of	ADP
ajst-31456	78	3	relying	rely	VERB
ajst-31456	78	4	on	on	ADP
ajst-31456	78	5	historical	historical	ADJ
ajst-31456	78	6	demand	demand	NOUN
ajst-31456	78	7	,	,	PUNCT
ajst-31456	78	8	models	model	NOUN
ajst-31456	78	9	like	like	ADP
ajst-31456	78	10	the	the	DET
ajst-31456	78	11	one	one	NOUN
ajst-31456	78	12	proposed	propose	VERB
ajst-31456	78	13	by	by	ADP
ajst-31456	78	14	zhou	zhou	PROPN
ajst-31456	78	15	and	and	CCONJ
ajst-31456	78	16	huang	huang	PROPN
ajst-31456	78	17	use	use	VERB
ajst-31456	78	18	large	large	ADJ
ajst-31456	78	19	-	-	PUNCT
ajst-31456	78	20	scale	scale	NOUN
ajst-31456	78	21	movement	movement	NOUN
ajst-31456	78	22	data	datum	NOUN
ajst-31456	78	23	from	from	ADP
ajst-31456	78	24	other	other	ADJ
ajst-31456	78	25	sources	source	NOUN
ajst-31456	78	26	(	(	PUNCT
ajst-31456	78	27	e.g.	e.g.	ADV
ajst-31456	78	28	,	,	PUNCT
ajst-31456	78	29	taxi	taxi	NOUN
ajst-31456	78	30	trips	trip	NOUN
ajst-31456	78	31	)	)	PUNCT
ajst-31456	78	32	to	to	PART
ajst-31456	78	33	create	create	VERB
ajst-31456	78	34	functional	functional	ADJ
ajst-31456	78	35	embeddings	embedding	NOUN
ajst-31456	78	36	for	for	ADP
ajst-31456	78	37	locations	location	NOUN
ajst-31456	78	38	,	,	PUNCT
ajst-31456	78	39	thereby	thereby	ADV
ajst-31456	78	40	enabling	enable	VERB
ajst-31456	78	41	demand	demand	NOUN
ajst-31456	78	42	prediction	prediction	NOUN
ajst-31456	78	43	for	for	ADP
ajst-31456	78	44	stations	station	NOUN
ajst-31456	78	45	with	with	ADP
ajst-31456	78	46	no	no	DET
ajst-31456	78	47	prior	prior	ADJ
ajst-31456	78	48	activity	activity	NOUN
ajst-31456	78	49	records	record	NOUN
ajst-31456	78	50	[	[	X
ajst-31456	78	51	30	30	NUM
ajst-31456	78	52	]	]	PUNCT
ajst-31456	78	53	.	.	PUNCT
ajst-31456	79	1	3	3	X
ajst-31456	79	2	.	.	X
ajst-31456	79	3	iii	iii	PROPN
ajst-31456	79	4	.	.	PROPN
ajst-31456	79	5	methodology	methodology	PROPN
ajst-31456	79	6	a.	a.	NOUN
ajst-31456	79	7	symbol	symbol	NOUN
ajst-31456	79	8	introduction	introduction	NOUN
ajst-31456	79	9	let	let	VERB
ajst-31456	79	10	𝑥	𝑥	PART
ajst-31456	79	11	represent	represent	VERB
ajst-31456	79	12	the	the	DET
ajst-31456	79	13	feature	feature	NOUN
ajst-31456	79	14	vectors	vector	NOUN
ajst-31456	79	15	.	.	PUNCT
ajst-31456	80	1	this	this	PRON
ajst-31456	80	2	is	be	AUX
ajst-31456	80	3	the	the	DET
ajst-31456	80	4	input	input	NOUN
ajst-31456	80	5	for	for	ADP
ajst-31456	80	6	all	all	DET
ajst-31456	80	7	models	model	NOUN
ajst-31456	80	8	,	,	PUNCT
ajst-31456	80	9	including	include	VERB
ajst-31456	80	10	all	all	DET
ajst-31456	80	11	independent	independent	ADJ
ajst-31456	80	12	variables	variable	NOUN
ajst-31456	80	13	used	use	VERB
ajst-31456	80	14	for	for	ADP
ajst-31456	80	15	prediction	prediction	NOUN
ajst-31456	80	16	such	such	ADJ
ajst-31456	80	17	as	as	ADP
ajst-31456	80	18	perceived	perceive	VERB
ajst-31456	80	19	temperature	temperature	NOUN
ajst-31456	80	20	,	,	PUNCT
ajst-31456	80	21	humidity	humidity	NOUN
ajst-31456	80	22	,	,	PUNCT
ajst-31456	80	23	hour	hour	NOUN
ajst-31456	80	24	,	,	PUNCT
ajst-31456	80	25	and	and	CCONJ
ajst-31456	80	26	day	day	NOUN
ajst-31456	80	27	of	of	ADP
ajst-31456	80	28	the	the	DET
ajst-31456	80	29	week	week	NOUN
ajst-31456	80	30	.	.	PUNCT
ajst-31456	81	1	𝑦	𝑦	X
ajst-31456	81	2	  	  	SPACE
ajst-31456	81	3	is	be	AUX
ajst-31456	81	4	the	the	DET
ajst-31456	81	5	dependent	dependent	ADJ
ajst-31456	81	6	variable	variable	ADJ
ajst-31456	81	7	output	output	NOUN
ajst-31456	81	8	by	by	ADP
ajst-31456	81	9	the	the	DET
ajst-31456	81	10	model	model	NOUN
ajst-31456	81	11	;	;	PUNCT
ajst-31456	81	12	it	it	PRON
ajst-31456	81	13	is	be	AUX
ajst-31456	81	14	the	the	DET
ajst-31456	81	15	desired	desire	VERB
ajst-31456	81	16	target	target	NOUN
ajst-31456	81	17	for	for	ADP
ajst-31456	81	18	the	the	DET
ajst-31456	81	19	model	model	NOUN
ajst-31456	81	20	to	to	PART
ajst-31456	81	21	predict	predict	VERB
ajst-31456	81	22	,	,	PUNCT
ajst-31456	81	23	which	which	PRON
ajst-31456	81	24	is	be	AUX
ajst-31456	81	25	the	the	DET
ajst-31456	81	26	actual	actual	ADJ
ajst-31456	81	27	number	number	NOUN
ajst-31456	81	28	of	of	ADP
ajst-31456	81	29	shared	share	VERB
ajst-31456	81	30	bike	bike	NOUN
ajst-31456	81	31	rentals	rental	NOUN
ajst-31456	81	32	.	.	PUNCT
ajst-31456	81	33	  	  	SPACE
ajst-31456	82	1	𝑦	𝑦	NOUN
ajst-31456	82	2	represents	represent	VERB
ajst-31456	82	3	the	the	DET
ajst-31456	82	4	predicted	predict	VERB
ajst-31456	82	5	value	value	NOUN
ajst-31456	82	6	.	.	PUNCT
ajst-31456	83	1	this	this	PRON
ajst-31456	83	2	is	be	AUX
ajst-31456	83	3	the	the	DET
ajst-31456	83	4	predicted	predict	VERB
ajst-31456	83	5	value	value	NOUN
ajst-31456	83	6	provided	provide	VERB
ajst-31456	83	7	by	by	ADP
ajst-31456	83	8	machine	machine	NOUN
ajst-31456	83	9	learning	learning	NOUN
ajst-31456	83	10	model	model	NOUN
ajst-31456	83	11	𝑀	𝑀	PROPN
ajst-31456	83	12	𝑥	𝑥	PROPN
ajst-31456	83	13	based	base	VERB
ajst-31456	83	14	on	on	ADP
ajst-31456	83	15	input	input	NOUN
ajst-31456	83	16	features	feature	NOUN
ajst-31456	83	17	.	.	PUNCT
ajst-31456	84	1	𝜃	𝜃	X
ajst-31456	84	2	  	  	SPACE
ajst-31456	84	3	represents	represent	VERB
ajst-31456	84	4	parameters	parameter	NOUN
ajst-31456	84	5	such	such	ADJ
ajst-31456	84	6	as	as	ADP
ajst-31456	84	7	model	model	NOUN
ajst-31456	84	8	weights	weight	NOUN
ajst-31456	84	9	and	and	CCONJ
ajst-31456	84	10	biases	bias	NOUN
ajst-31456	84	11	.	.	PUNCT
ajst-31456	85	1	the	the	DET
ajst-31456	85	2	model	model	NOUN
ajst-31456	85	3	needs	need	VERB
ajst-31456	85	4	to	to	PART
ajst-31456	85	5	be	be	AUX
ajst-31456	85	6	updated	update	VERB
ajst-31456	85	7	through	through	ADP
ajst-31456	85	8	training	training	NOUN
ajst-31456	85	9	data	datum	NOUN
ajst-31456	85	10	learning	learning	NOUN
ajst-31456	85	11	.	.	PUNCT
ajst-31456	86	1	the	the	DET
ajst-31456	86	2	value	value	NOUN
ajst-31456	86	3	of	of	ADP
ajst-31456	86	4	𝜃	𝜃	NOUN
ajst-31456	86	5	directly	directly	ADV
ajst-31456	86	6	determines	determine	VERB
ajst-31456	86	7	how	how	SCONJ
ajst-31456	86	8	the	the	DET
ajst-31456	86	9	model	model	NOUN
ajst-31456	86	10	learns	learn	VERB
ajst-31456	86	11	to	to	PART
ajst-31456	86	12	map	map	VERB
ajst-31456	86	13	the	the	DET
ajst-31456	86	14	input	input	NOUN
ajst-31456	86	15	𝑥	𝑥	NOUN
ajst-31456	86	16	  	  	SPACE
ajst-31456	86	17	to	to	ADP
ajst-31456	86	18	the	the	DET
ajst-31456	86	19	output	output	NOUN
ajst-31456	86	20	𝑦.	𝑦.	PROPN
ajst-31456	86	21	𝐽	𝐽	PROPN
ajst-31456	87	1	𝜃	𝜃	NOUN
ajst-31456	87	2	  	  	SPACE
ajst-31456	87	3	is	be	AUX
ajst-31456	87	4	the	the	DET
ajst-31456	87	5	cost	cost	NOUN
ajst-31456	87	6	function	function	NOUN
ajst-31456	87	7	.	.	PUNCT
ajst-31456	88	1	it	it	PRON
ajst-31456	88	2	measures	measure	VERB
ajst-31456	88	3	the	the	DET
ajst-31456	88	4	difference	difference	NOUN
ajst-31456	88	5	between	between	ADP
ajst-31456	88	6	all	all	DET
ajst-31456	88	7	predicted	predict	VERB
ajst-31456	88	8	values	value	NOUN
ajst-31456	88	9	and	and	CCONJ
ajst-31456	88	10	the	the	DET
ajst-31456	88	11	true	true	ADJ
ajst-31456	88	12	values	value	NOUN
ajst-31456	88	13	of	of	ADP
ajst-31456	88	14	the	the	DET
ajst-31456	88	15	model	model	NOUN
ajst-31456	88	16	.	.	PUNCT
ajst-31456	89	1	r2	r2	PROPN
ajst-31456	89	2	is	be	AUX
ajst-31456	89	3	the	the	DET
ajst-31456	89	4	determination	determination	NOUN
ajst-31456	89	5	coefficient	coefficient	NOUN
ajst-31456	89	6	.	.	PUNCT
ajst-31456	90	1	it	it	PRON
ajst-31456	90	2	measures	measure	VERB
ajst-31456	90	3	the	the	DET
ajst-31456	90	4	percentage	percentage	NOUN
ajst-31456	90	5	of	of	ADP
ajst-31456	90	6	variance	variance	NOUN
ajst-31456	90	7	in	in	ADP
ajst-31456	90	8	the	the	DET
ajst-31456	90	9	model	model	NOUN
ajst-31456	90	10	’s	’s	PART
ajst-31456	90	11	predicted	predict	VERB
ajst-31456	90	12	rental	rental	ADJ
ajst-31456	90	13	quantity	quantity	NOUN
ajst-31456	90	14	.	.	PUNCT
ajst-31456	91	1	the	the	DET
ajst-31456	91	2	closer	close	ADJ
ajst-31456	91	3	r2	r2	NOUN
ajst-31456	91	4	is	be	AUX
ajst-31456	91	5	to	to	ADP
ajst-31456	91	6	1	1	NUM
ajst-31456	91	7	,	,	PUNCT
ajst-31456	91	8	the	the	PRON
ajst-31456	91	9	better	well	ADJ
ajst-31456	91	10	the	the	DET
ajst-31456	91	11	fitting	fitting	ADJ
ajst-31456	91	12	effect	effect	NOUN
ajst-31456	91	13	of	of	ADP
ajst-31456	91	14	the	the	DET
ajst-31456	91	15	model	model	NOUN
ajst-31456	91	16	.	.	PUNCT
ajst-31456	92	1	rmsle	rmsle	PROPN
ajst-31456	92	2	stands	stand	VERB
ajst-31456	92	3	for	for	ADP
ajst-31456	92	4	root	root	NOUN
ajst-31456	92	5	mean	mean	NOUN
ajst-31456	92	6	square	square	ADJ
ajst-31456	92	7	logarithmic	logarithmic	ADJ
ajst-31456	92	8	error	error	NOUN
ajst-31456	92	9	.	.	PUNCT
ajst-31456	93	1	this	this	PRON
ajst-31456	93	2	is	be	AUX
ajst-31456	93	3	the	the	DET
ajst-31456	93	4	main	main	ADJ
ajst-31456	93	5	error	error	NOUN
ajst-31456	93	6	metric	metric	NOUN
ajst-31456	93	7	used	use	VERB
ajst-31456	93	8	in	in	ADP
ajst-31456	93	9	this	this	DET
ajst-31456	93	10	article	article	NOUN
ajst-31456	93	11	.	.	PUNCT
ajst-31456	94	1	it	it	PRON
ajst-31456	94	2	calculates	calculate	VERB
ajst-31456	94	3	the	the	DET
ajst-31456	94	4	root	root	NOUN
ajst-31456	94	5	mean	mean	NOUN
ajst-31456	94	6	square	square	NOUN
ajst-31456	94	7	of	of	ADP
ajst-31456	94	8	the	the	DET
ajst-31456	94	9	difference	difference	NOUN
ajst-31456	94	10	between	between	ADP
ajst-31456	94	11	the	the	DET
ajst-31456	94	12	logarithm	logarithm	NOUN
ajst-31456	94	13	of	of	ADP
ajst-31456	94	14	the	the	DET
ajst-31456	94	15	predicted	predict	VERB
ajst-31456	94	16	value	value	NOUN
ajst-31456	94	17	and	and	CCONJ
ajst-31456	94	18	the	the	DET
ajst-31456	94	19	true	true	ADJ
ajst-31456	94	20	value	value	NOUN
ajst-31456	94	21	.	.	PUNCT
ajst-31456	95	1	p(t	p(t	NOUN
ajst-31456	95	2	)	)	PUNCT
ajst-31456	95	3	 	 	SPACE
ajst-31456	95	4	is	be	AUX
ajst-31456	95	5	the	the	DET
ajst-31456	95	6	local	local	ADJ
ajst-31456	95	7	fitting	fitting	ADJ
ajst-31456	95	8	polynomial	polynomial	ADJ
ajst-31456	95	9	,	,	PUNCT
ajst-31456	95	10	used	use	VERB
ajst-31456	95	11	by	by	ADP
ajst-31456	95	12	the	the	DET
ajst-31456	95	13	savitzky	savitzky	NOUN
ajst-31456	95	14	-	-	PUNCT
ajst-31456	95	15	golay	golay	NOUN
ajst-31456	95	16	filter	filter	NOUN
ajst-31456	95	17	to	to	PART
ajst-31456	95	18	approximate	approximate	VERB
ajst-31456	95	19	the	the	DET
ajst-31456	95	20	data	datum	NOUN
ajst-31456	95	21	within	within	ADP
ajst-31456	95	22	a	a	DET
ajst-31456	95	23	sliding	slide	VERB
ajst-31456	95	24	window	window	NOUN
ajst-31456	95	25	.	.	PUNCT
ajst-31456	96	1	b.	b.	PROPN
ajst-31456	96	2	module	module	NOUN
ajst-31456	96	3	1	1	NUM
ajst-31456	96	4	:	:	PUNCT
ajst-31456	96	5	preprocess	preprocess	NOUN
ajst-31456	96	6	module	module	NOUN
ajst-31456	96	7	this	this	DET
ajst-31456	96	8	article	article	NOUN
ajst-31456	96	9	’s	’s	PART
ajst-31456	96	10	dataset	dataset	NOUN
ajst-31456	96	11	is	be	AUX
ajst-31456	96	12	from	from	ADP
ajst-31456	96	13	the	the	DET
ajst-31456	96	14	bike	bike	NOUN
ajst-31456	96	15	sharing	sharing	NOUN
ajst-31456	96	16	demands	demand	NOUN
ajst-31456	96	17	dataset	dataset	VERB
ajst-31456	96	18	on	on	ADP
ajst-31456	96	19	the	the	DET
ajst-31456	96	20	kaggle	kaggle	ADJ
ajst-31456	96	21	website	website	NOUN
ajst-31456	96	22	,	,	PUNCT
ajst-31456	96	23	available	available	ADJ
ajst-31456	96	24	at	at	ADP
ajst-31456	96	25	:	:	PUNCT
ajst-31456	96	26	https://www	https://www	PROPN
ajst-31456	96	27	.	.	PUNCT
ajst-31456	96	28	kaggle.com/c/bike-sharing-demand/data	kaggle.com/c/bike-sharing-demand/data	PROPN
ajst-31456	96	29	.	.	PUNCT
ajst-31456	97	1	working	work	VERB
ajst-31456	97	2	with	with	ADP
ajst-31456	97	3	such	such	ADJ
ajst-31456	97	4	real	real	ADJ
ajst-31456	97	5	-	-	PUNCT
ajst-31456	97	6	world	world	NOUN
ajst-31456	97	7	public	public	ADJ
ajst-31456	97	8	datasets	dataset	NOUN
ajst-31456	97	9	often	often	ADV
ajst-31456	97	10	presents	present	VERB
ajst-31456	97	11	challenges	challenge	NOUN
ajst-31456	97	12	related	relate	VERB
ajst-31456	97	13	to	to	ADP
ajst-31456	97	14	data	datum	NOUN
ajst-31456	97	15	quality	quality	NOUN
ajst-31456	97	16	and	and	CCONJ
ajst-31456	97	17	consistency	consistency	NOUN
ajst-31456	97	18	,	,	PUNCT
ajst-31456	97	19	necessitating	necessitate	VERB
ajst-31456	97	20	robust	robust	ADJ
ajst-31456	97	21	preprocessing	preprocessing	NOUN
ajst-31456	97	22	and	and	CCONJ
ajst-31456	97	23	exploratory	exploratory	ADJ
ajst-31456	97	24	analysis	analysis	NOUN
ajst-31456	97	25	to	to	PART
ajst-31456	97	26	distill	distill	VERB
ajst-31456	97	27	useful	useful	ADJ
ajst-31456	97	28	patterns	pattern	NOUN
ajst-31456	97	29	[	[	X
ajst-31456	97	30	31	31	NUM
ajst-31456	97	31	]	]	PUNCT
ajst-31456	97	32	.	.	PUNCT
ajst-31456	98	1	this	this	DET
ajst-31456	98	2	initial	initial	ADJ
ajst-31456	98	3	analysis	analysis	NOUN
ajst-31456	98	4	aligns	align	VERB
ajst-31456	98	5	with	with	ADP
ajst-31456	98	6	common	common	ADJ
ajst-31456	98	7	practice	practice	NOUN
ajst-31456	98	8	,	,	PUNCT
ajst-31456	98	9	where	where	SCONJ
ajst-31456	98	10	studies	study	NOUN
ajst-31456	98	11	investigate	investigate	VERB
ajst-31456	98	12	the	the	DET
ajst-31456	98	13	influence	influence	NOUN
ajst-31456	98	14	of	of	ADP
ajst-31456	98	15	various	various	ADJ
ajst-31456	98	16	factors	factor	NOUN
ajst-31456	98	17	,	,	PUNCT
ajst-31456	98	18	including	include	VERB
ajst-31456	98	19	the	the	DET
ajst-31456	98	20	built	build	VERB
ajst-31456	98	21	environment	environment	NOUN
ajst-31456	98	22	and	and	CCONJ
ajst-31456	98	23	social	social	ADJ
ajst-31456	98	24	-	-	PUNCT
ajst-31456	98	25	economic	economic	ADJ
ajst-31456	98	26	characteristics	characteristic	NOUN
ajst-31456	98	27	,	,	PUNCT
ajst-31456	98	28	on	on	ADP
ajst-31456	98	29	bike	bike	NOUN
ajst-31456	98	30	demand	demand	NOUN
ajst-31456	98	31	using	use	VERB
ajst-31456	98	32	data	datum	NOUN
ajst-31456	98	33	analytics	analytic	NOUN
ajst-31456	98	34	before	before	ADP
ajst-31456	98	35	model	model	NOUN
ajst-31456	98	36	construction	construction	NOUN
ajst-31456	98	37	[	[	X
ajst-31456	98	38	32	32	NUM
ajst-31456	98	39	]	]	PUNCT
ajst-31456	98	40	.	.	PUNCT
ajst-31456	99	1	with	with	ADP
ajst-31456	99	2	12	12	NUM
ajst-31456	99	3	attributes	attribute	NOUN
ajst-31456	99	4	,	,	PUNCT
ajst-31456	99	5	this	this	DET
ajst-31456	99	6	article	article	NOUN
ajst-31456	99	7	focuses	focus	VERB
ajst-31456	99	8	on	on	ADP
ajst-31456	99	9	the	the	DET
ajst-31456	99	10	10	10	NUM
ajst-31456	99	11	most	most	ADV
ajst-31456	99	12	important	important	ADJ
ajst-31456	99	13	attributes	attribute	NOUN
ajst-31456	99	14	for	for	ADP
ajst-31456	99	15	research	research	NOUN
ajst-31456	99	16	.	.	PUNCT
ajst-31456	100	1	table	table	NOUN
ajst-31456	100	2	i	i	PRON
ajst-31456	100	3	dataset	dataset	VERB
ajst-31456	100	4	atribute	atribute	NOUN
ajst-31456	100	5	description	description	NOUN
ajst-31456	100	6	name	name	NOUN
ajst-31456	100	7	meaning	mean	VERB
ajst-31456	100	8	description	description	NOUN
ajst-31456	100	9	datetime	datetime	NOUN
ajst-31456	100	10	date	date	NOUN
ajst-31456	100	11	and	and	CCONJ
ajst-31456	100	12	time	time	NOUN
ajst-31456	100	13	hourly	hourly	ADJ
ajst-31456	100	14	date	date	NOUN
ajst-31456	100	15	and	and	CCONJ
ajst-31456	100	16	time	time	NOUN
ajst-31456	100	17	data	datum	NOUN
ajst-31456	100	18	season	season	NOUN
ajst-31456	100	19	season	season	NOUN
ajst-31456	100	20	1	1	NUM
ajst-31456	100	21	-	-	SYM
ajst-31456	100	22	4	4	NUM
ajst-31456	100	23	:	:	PUNCT
ajst-31456	100	24	spring	spring	NOUN
ajst-31456	100	25	-	-	PUNCT
ajst-31456	100	26	winter	winter	NOUN
ajst-31456	100	27	holiday	holiday	NOUN
ajst-31456	100	28	holiday	holiday	NOUN
ajst-31456	100	29	1	1	NUM
ajst-31456	100	30	=	=	NOUN
ajst-31456	100	31	holiday	holiday	NOUN
ajst-31456	100	32	,	,	PUNCT
ajst-31456	100	33	0	0	PUNCT
ajst-31456	100	34	=	=	SYM
ajst-31456	100	35	not	not	PART
ajst-31456	100	36	a	a	DET
ajst-31456	100	37	holiday	holiday	NOUN
ajst-31456	100	38	workingday	workingday	NOUN
ajst-31456	100	39	working	working	NOUN
ajst-31456	100	40	day	day	NOUN
ajst-31456	100	41	1	1	NUM
ajst-31456	100	42	=	=	NOUN
ajst-31456	100	43	work	work	NOUN
ajst-31456	100	44	-	-	PUNCT
ajst-31456	100	45	day	day	NOUN
ajst-31456	100	46	,	,	PUNCT
ajst-31456	100	47	0	0	PUNCT
ajst-31456	100	48	=	=	NOUN
ajst-31456	100	49	not	not	PART
ajst-31456	100	50	work	work	NOUN
ajst-31456	100	51	-	-	PUNCT
ajst-31456	100	52	day	day	NOUN
ajst-31456	100	53	weather	weather	NOUN
ajst-31456	100	54	weather	weather	NOUN
ajst-31456	100	55	1	1	NUM
ajst-31456	101	1	=	=	NOUN
ajst-31456	101	2	clear	clear	ADJ
ajst-31456	101	3	,	,	PUNCT
ajst-31456	101	4	2	2	NUM
ajst-31456	101	5	=	=	NOUN
ajst-31456	101	6	cloudy	cloudy	ADJ
ajst-31456	101	7	,	,	PUNCT
ajst-31456	101	8	3	3	NUM
ajst-31456	101	9	=	=	NOUN
ajst-31456	101	10	snow	snow	NOUN
ajst-31456	101	11	,	,	PUNCT
ajst-31456	101	12	4	4	NUM
ajst-31456	101	13	=	=	NUM
ajst-31456	101	14	bad	bad	ADJ
ajst-31456	101	15	weather	weather	NOUN
ajst-31456	101	16	temp	temp	NOUN
ajst-31456	101	17	actual	actual	ADJ
ajst-31456	101	18	temperature	temperature	NOUN
ajst-31456	101	19	temperature(celsius	temperature(celsius	NOUN
ajst-31456	101	20	)	)	PUNCT
ajst-31456	101	21	atemp	atemp	NOUN
ajst-31456	101	22	apparent	apparent	ADJ
ajst-31456	101	23	temperature	temperature	NOUN
ajst-31456	101	24	apparent	apparent	ADJ
ajst-31456	101	25	temperature(celsius	temperature(celsius	NOUN
ajst-31456	101	26	)	)	PUNCT
ajst-31456	101	27	humidity	humidity	NOUN
ajst-31456	101	28	humidity	humidity	NOUN
ajst-31456	101	29	relative	relative	ADJ
ajst-31456	101	30	humidity	humidity	NOUN
ajst-31456	101	31	(	(	PUNCT
ajst-31456	101	32	%	%	INTJ
ajst-31456	101	33	)	)	PUNCT
ajst-31456	101	34	windspeed	windspeed	VERB
ajst-31456	101	35	wind	wind	NOUN
ajst-31456	101	36	speed	speed	NOUN
ajst-31456	101	37	wind	wind	NOUN
ajst-31456	101	38	speed	speed	NOUN
ajst-31456	101	39	(	(	PUNCT
ajst-31456	101	40	km	km	NOUN
ajst-31456	101	41	/	/	SYM
ajst-31456	101	42	h	h	NOUN
ajst-31456	101	43	)	)	PUNCT
ajst-31456	101	44	count	count	VERB
ajst-31456	101	45	total	total	ADJ
ajst-31456	101	46	number	number	NOUN
ajst-31456	101	47	of	of	ADP
ajst-31456	101	48	rentals	rental	NOUN
ajst-31456	101	49	total	total	ADJ
ajst-31456	101	50	number	number	NOUN
ajst-31456	101	51	of	of	ADP
ajst-31456	101	52	hourly	hourly	ADJ
ajst-31456	101	53	rentals	rental	NOUN
ajst-31456	101	54	at	at	ADP
ajst-31456	101	55	the	the	DET
ajst-31456	101	56	same	same	ADJ
ajst-31456	101	57	time	time	NOUN
ajst-31456	101	58	,	,	PUNCT
ajst-31456	101	59	this	this	DET
ajst-31456	101	60	study	study	NOUN
ajst-31456	101	61	also	also	ADV
ajst-31456	101	62	plotted	plot	VERB
ajst-31456	101	63	data	datum	NOUN
ajst-31456	101	64	distribution	distribution	NOUN
ajst-31456	101	65	graphs	graph	NOUN
ajst-31456	101	66	for	for	ADP
ajst-31456	101	67	14	14	NUM
ajst-31456	101	68	attributes	attribute	NOUN
ajst-31456	101	69	(	(	PUNCT
ajst-31456	101	70	as	as	SCONJ
ajst-31456	101	71	timestamps	timestamp	NOUN
ajst-31456	101	72	are	be	AUX
ajst-31456	101	73	high	high	ADJ
ajst-31456	101	74	cardinality	cardinality	NOUN
ajst-31456	101	75	timestamp	timestamp	NOUN
ajst-31456	101	76	sequences	sequence	NOUN
ajst-31456	101	77	,	,	PUNCT
ajst-31456	101	78	the	the	DET
ajst-31456	101	79	histograms	histogram	NOUN
ajst-31456	101	80	of	of	ADP
ajst-31456	101	81	their	their	PRON
ajst-31456	101	82	original	original	ADJ
ajst-31456	101	83	values	value	NOUN
ajst-31456	101	84	usually	usually	ADV
ajst-31456	101	85	do	do	AUX
ajst-31456	101	86	not	not	PART
ajst-31456	101	87	directly	directly	ADV
ajst-31456	101	88	reflect	reflect	VERB
ajst-31456	101	89	periodic	periodic	ADJ
ajst-31456	101	90	or	or	CCONJ
ajst-31456	101	91	easily	easily	ADV
ajst-31456	101	92	interpretable	interpretable	ADJ
ajst-31456	101	93	distribution	distribution	NOUN
ajst-31456	101	94	patterns	pattern	NOUN
ajst-31456	101	95	.	.	PUNCT
ajst-31456	102	1	it	it	PRON
ajst-31456	102	2	is	be	AUX
ajst-31456	102	3	better	well	ADJ
ajst-31456	102	4	to	to	PART
ajst-31456	102	5	break	break	VERB
ajst-31456	102	6	them	they	PRON
ajst-31456	102	7	down	down	ADP
ajst-31456	102	8	into	into	ADP
ajst-31456	102	9	more	more	ADV
ajst-31456	102	10	meaningful	meaningful	ADJ
ajst-31456	102	11	categories	category	NOUN
ajst-31456	102	12	or	or	CCONJ
ajst-31456	102	13	periodic	periodic	ADJ
ajst-31456	102	14	features	feature	NOUN
ajst-31456	102	15	such	such	ADJ
ajst-31456	102	16	as	as	ADP
ajst-31456	102	17	year	year	NOUN
ajst-31456	102	18	,	,	PUNCT
ajst-31456	102	19	month	month	NOUN
ajst-31456	102	20	,	,	PUNCT
ajst-31456	102	21	day	day	NOUN
ajst-31456	102	22	,	,	PUNCT
ajst-31456	102	23	and	and	CCONJ
ajst-31456	102	24	hour	hour	NOUN
ajst-31456	102	25	for	for	ADP
ajst-31456	102	26	analysis	analysis	NOUN
ajst-31456	102	27	,	,	PUNCT
ajst-31456	102	28	so	so	SCONJ
ajst-31456	102	29	their	their	PRON
ajst-31456	102	30	histograms	histogram	NOUN
ajst-31456	102	31	are	be	AUX
ajst-31456	102	32	not	not	PART
ajst-31456	102	33	directly	directly	ADV
ajst-31456	102	34	plotted	plot	VERB
ajst-31456	102	35	)	)	PUNCT
ajst-31456	102	36	.	.	PUNCT
ajst-31456	103	1	figure	figure	NOUN
ajst-31456	103	2	1	1	NUM
ajst-31456	103	3	.	.	PUNCT
ajst-31456	103	4	overall	overall	ADJ
ajst-31456	103	5	framework	framework	NOUN
ajst-31456	103	6	of	of	ADP
ajst-31456	103	7	the	the	DET
ajst-31456	103	8	proposed	propose	VERB
ajst-31456	103	9	model	model	NOUN
ajst-31456	103	10	.	.	PUNCT
ajst-31456	104	1	as	as	SCONJ
ajst-31456	104	2	shown	show	VERB
ajst-31456	104	3	in	in	ADP
ajst-31456	104	4	the	the	DET
ajst-31456	104	5	figure	figure	NOUN
ajst-31456	104	6	,	,	PUNCT
ajst-31456	104	7	the	the	DET
ajst-31456	104	8	target	target	NOUN
ajst-31456	104	9	variable	variable	NOUN
ajst-31456	104	10	of	of	ADP
ajst-31456	104	11	this	this	DET
ajst-31456	104	12	study	study	NOUN
ajst-31456	104	13	,	,	PUNCT
ajst-31456	104	14	the	the	DET
ajst-31456	104	15	hourly	hourly	ADJ
ajst-31456	104	16	count	count	NOUN
ajst-31456	104	17	of	of	ADP
ajst-31456	104	18	shared	share	VERB
ajst-31456	104	19	bicycle	bicycle	NOUN
ajst-31456	104	20	rentals	rental	NOUN
ajst-31456	104	21	(	(	PUNCT
ajst-31456	104	22	count	count	NOUN
ajst-31456	104	23	)	)	PUNCT
ajst-31456	104	24	,	,	PUNCT
ajst-31456	104	25	exhibits	exhibit	VERB
ajst-31456	104	26	a	a	DET
ajst-31456	104	27	significant	significant	ADJ
ajst-31456	104	28	right	right	ADJ
ajst-31456	104	29	-	-	PUNCT
ajst-31456	104	30	skewed	skewed	ADJ
ajst-31456	104	31	distribution	distribution	NOUN
ajst-31456	104	32	.	.	PUNCT
ajst-31456	105	1	such	such	DET
ajst-31456	105	2	a	a	DET
ajst-31456	105	3	skewed	skewed	ADJ
ajst-31456	105	4	dis	dis	PROPN
ajst-31456	105	5	tribution	tribution	NOUN
ajst-31456	105	6	can	can	AUX
ajst-31456	105	7	negatively	negatively	ADV
ajst-31456	105	8	impact	impact	VERB
ajst-31456	105	9	the	the	DET
ajst-31456	105	10	performance	performance	NOUN
ajst-31456	105	11	of	of	ADP
ajst-31456	105	12	many	many	ADJ
ajst-31456	105	13	machine	machine	NOUN
ajst-31456	105	14	learning	learning	NOUN
ajst-31456	105	15	models	model	NOUN
ajst-31456	105	16	,	,	PUNCT
ajst-31456	105	17	particularly	particularly	ADV
ajst-31456	105	18	those	those	PRON
ajst-31456	105	19	that	that	PRON
ajst-31456	105	20	assume	assume	VERB
ajst-31456	105	21	a	a	DET
ajst-31456	105	22	normal	normal	ADJ
ajst-31456	105	23	or	or	CCONJ
ajst-31456	105	24	symmetric	symmetric	ADJ
ajst-31456	105	25	distribution	distribution	NOUN
ajst-31456	105	26	.	.	PUNCT
ajst-31456	106	1	to	to	PART
ajst-31456	106	2	mitigate	mitigate	VERB
ajst-31456	106	3	this	this	DET
ajst-31456	106	4	issue	issue	NOUN
ajst-31456	106	5	,	,	PUNCT
ajst-31456	106	6	this	this	DET
ajst-31456	106	7	study	study	NOUN
ajst-31456	106	8	applies	apply	VERB
ajst-31456	106	9	a	a	DET
ajst-31456	106	10	logarithmic	logarithmic	ADJ
ajst-31456	106	11	transformation	transformation	NOUN
ajst-31456	106	12	to	to	ADP
ajst-31456	106	13	the	the	DET
ajst-31456	106	14	target	target	NOUN
ajst-31456	106	15	variable	variable	NOUN
ajst-31456	106	16	.	.	PUNCT
ajst-31456	107	1	specifically	specifically	ADV
ajst-31456	107	2	,	,	PUNCT
ajst-31456	107	3	it	it	PRON
ajst-31456	107	4	adopts	adopt	VERB
ajst-31456	107	5	the	the	DET
ajst-31456	107	6	form	form	NOUN
ajst-31456	107	7	of	of	ADP
ajst-31456	107	8	a	a	DET
ajst-31456	107	9	log	log	NOUN
ajst-31456	107	10	-	-	PUNCT
ajst-31456	107	11	plus	plus	CCONJ
ajst-31456	107	12	-	-	PUNCT
ajst-31456	107	13	one	one	NUM
ajst-31456	107	14	transformation	transformation	NOUN
ajst-31456	107	15	,	,	PUNCT
ajst-31456	107	16	log(1	log(1	NOUN
ajst-31456	107	17	+	+	CCONJ
ajst-31456	107	18	x	x	X
ajst-31456	107	19	)	)	PUNCT
ajst-31456	107	20	,	,	PUNCT
ajst-31456	107	21	as	as	SCONJ
ajst-31456	107	22	follows	follow	VERB
ajst-31456	107	23	:	:	PUNCT
ajst-31456	107	24	countlog	countlog	NOUN
ajst-31456	107	25	=	=	PUNCT
ajst-31456	107	26	ln(1	ln(1	NOUN
ajst-31456	107	27	+	+	NUM
ajst-31456	107	28	count	count	NOUN
ajst-31456	107	29	)	)	PUNCT
ajst-31456	107	30	(	(	PUNCT
ajst-31456	107	31	1	1	X
ajst-31456	107	32	)	)	PUNCT
ajst-31456	107	33	all	all	DET
ajst-31456	107	34	subsequent	subsequent	ADJ
ajst-31456	107	35	models	model	NOUN
ajst-31456	107	36	are	be	AUX
ajst-31456	107	37	trained	train	VERB
ajst-31456	107	38	using	use	VERB
ajst-31456	107	39	the	the	DET
ajst-31456	107	40	transformed	transform	VERB
ajst-31456	107	41	rental	rental	ADJ
ajst-31456	107	42	count	count	NOUN
ajst-31456	107	43	as	as	ADP
ajst-31456	107	44	the	the	DET
ajst-31456	107	45	dependent	dependent	ADJ
ajst-31456	107	46	variable	variable	NOUN
ajst-31456	107	47	.	.	PUNCT
ajst-31456	108	1	after	after	SCONJ
ajst-31456	108	2	a	a	DET
ajst-31456	108	3	prediction	prediction	NOUN
ajst-31456	108	4	is	be	AUX
ajst-31456	108	5	obtained	obtain	VERB
ajst-31456	108	6	from	from	ADP
ajst-31456	108	7	the	the	DET
ajst-31456	108	8	model	model	NOUN
ajst-31456	108	9	,	,	PUNCT
ajst-31456	108	10	denoted	denote	VERB
ajst-31456	108	11	as	as	ADP
ajst-31456	108	12	yˆlog	yˆlog	NOUN
ajst-31456	108	13	,	,	PUNCT
ajst-31456	108	14	it	it	PRON
ajst-31456	108	15	is	be	AUX
ajst-31456	108	16	restored	restore	VERB
ajst-31456	108	17	to	to	ADP
ajst-31456	108	18	the	the	DET
ajst-31456	108	19	original	original	ADJ
ajst-31456	108	20	scale	scale	NOUN
ajst-31456	108	21	by	by	ADP
ajst-31456	108	22	applying	apply	VERB
ajst-31456	108	23	the	the	DET
ajst-31456	108	24	inverse	inverse	NOUN
ajst-31456	108	25	transformation	transformation	NOUN
ajst-31456	108	26	:	:	PUNCT
ajst-31456	108	27	54	54	NUM
ajst-31456	108	28	𝑦	𝑦	NOUN
ajst-31456	108	29	𝑒	𝑒	PROPN
ajst-31456	108	30	1	1	NUM
ajst-31456	108	31	(	(	PUNCT
ajst-31456	108	32	2	2	NUM
ajst-31456	108	33	)	)	PUNCT
ajst-31456	108	34	as	as	SCONJ
ajst-31456	108	35	shown	show	VERB
ajst-31456	108	36	in	in	ADP
ajst-31456	108	37	figure	figure	NOUN
ajst-31456	108	38	3	3	NUM
ajst-31456	108	39	,	,	PUNCT
ajst-31456	108	40	the	the	DET
ajst-31456	108	41	right	right	ADJ
ajst-31456	108	42	subgraph	subgraph	NOUN
ajst-31456	108	43	displays	display	VERB
ajst-31456	108	44	the	the	DET
ajst-31456	108	45	dis	dis	PROPN
ajst-31456	108	46	tribution	tribution	NOUN
ajst-31456	108	47	of	of	ADP
ajst-31456	108	48	the	the	DET
ajst-31456	108	49	target	target	NOUN
ajst-31456	108	50	variable	variable	NOUN
ajst-31456	108	51	after	after	ADP
ajst-31456	108	52	applying	apply	VERB
ajst-31456	108	53	the	the	DET
ajst-31456	108	54	ln(1	ln(1	PROPN
ajst-31456	108	55	+	+	NOUN
ajst-31456	108	56	count	count	ADJ
ajst-31456	108	57	)	)	PUNCT
ajst-31456	108	58	logarithmic	logarithmic	ADJ
ajst-31456	108	59	transformation	transformation	NOUN
ajst-31456	108	60	.	.	PUNCT
ajst-31456	109	1	by	by	ADP
ajst-31456	109	2	comparison	comparison	NOUN
ajst-31456	109	3	,	,	PUNCT
ajst-31456	109	4	it	it	PRON
ajst-31456	109	5	is	be	AUX
ajst-31456	109	6	evident	evident	ADJ
ajst-31456	109	7	that	that	SCONJ
ajst-31456	109	8	the	the	DET
ajst-31456	109	9	transformation	transformation	NOUN
ajst-31456	109	10	substantially	substantially	ADV
ajst-31456	109	11	mitigates	mitigate	VERB
ajst-31456	109	12	the	the	DET
ajst-31456	109	13	right	right	NOUN
ajst-31456	109	14	-	-	PUNCT
ajst-31456	109	15	skewness	skewness	NOUN
ajst-31456	109	16	of	of	ADP
ajst-31456	109	17	the	the	DET
ajst-31456	109	18	original	original	ADJ
ajst-31456	109	19	data	datum	NOUN
ajst-31456	109	20	.	.	PUNCT
ajst-31456	110	1	in	in	ADP
ajst-31456	110	2	order	order	NOUN
ajst-31456	110	3	to	to	PART
ajst-31456	110	4	investigate	investigate	VERB
ajst-31456	110	5	whether	whether	SCONJ
ajst-31456	110	6	there	there	PRON
ajst-31456	110	7	is	be	VERB
ajst-31456	110	8	a	a	DET
ajst-31456	110	9	linear	linear	ADJ
ajst-31456	110	10	relationship	relationship	NOUN
ajst-31456	110	11	between	between	ADP
ajst-31456	110	12	different	different	ADJ
ajst-31456	110	13	features	feature	NOUN
ajst-31456	110	14	,	,	PUNCT
ajst-31456	110	15	this	this	DET
ajst-31456	110	16	article	article	NOUN
ajst-31456	110	17	has	have	AUX
ajst-31456	110	18	drawn	draw	VERB
ajst-31456	110	19	a	a	DET
ajst-31456	110	20	thermal	thermal	ADJ
ajst-31456	110	21	matrix	matrix	NOUN
ajst-31456	110	22	diagram	diagram	NOUN
ajst-31456	110	23	,	,	PUNCT
ajst-31456	110	24	as	as	SCONJ
ajst-31456	110	25	depicted	depict	VERB
ajst-31456	110	26	in	in	ADP
ajst-31456	110	27	fig	fig	NOUN
ajst-31456	110	28	.	.	PUNCT
ajst-31456	111	1	4	4	X
ajst-31456	111	2	.	.	X
ajst-31456	112	1	the	the	DET
ajst-31456	112	2	features	feature	NOUN
ajst-31456	112	3	contained	contain	VERB
ajst-31456	112	4	in	in	ADP
ajst-31456	112	5	the	the	DET
ajst-31456	112	6	original	original	ADJ
ajst-31456	112	7	dataset	dataset	NOUN
ajst-31456	112	8	are	be	AUX
ajst-31456	112	9	not	not	PART
ajst-31456	112	10	suitable	suitable	ADJ
ajst-31456	112	11	for	for	ADP
ajst-31456	112	12	direct	direct	ADJ
ajst-31456	112	13	input	input	NOUN
ajst-31456	112	14	into	into	ADP
ajst-31456	112	15	the	the	DET
ajst-31456	112	16	model	model	NOUN
ajst-31456	112	17	,	,	PUNCT
ajst-31456	112	18	and	and	CCONJ
ajst-31456	112	19	some	some	DET
ajst-31456	112	20	features	feature	NOUN
ajst-31456	112	21	have	have	VERB
ajst-31456	112	22	little	little	ADJ
ajst-31456	112	23	meaning	meaning	NOUN
ajst-31456	112	24	to	to	ADP
ajst-31456	112	25	the	the	DET
ajst-31456	112	26	model	model	NOUN
ajst-31456	112	27	.	.	PUNCT
ajst-31456	113	1	therefore	therefore	ADV
ajst-31456	113	2	,	,	PUNCT
ajst-31456	113	3	this	this	DET
ajst-31456	113	4	article	article	NOUN
ajst-31456	113	5	first	first	ADV
ajst-31456	113	6	extracted	extract	VERB
ajst-31456	113	7	structured	structured	ADJ
ajst-31456	113	8	temporal	temporal	ADJ
ajst-31456	113	9	features	feature	NOUN
ajst-31456	113	10	and	and	CCONJ
ajst-31456	113	11	preliminarily	preliminarily	ADV
ajst-31456	113	12	screened	screen	VERB
ajst-31456	113	13	some	some	PRON
ajst-31456	113	14	of	of	ADP
ajst-31456	113	15	the	the	DET
ajst-31456	113	16	original	original	ADJ
ajst-31456	113	17	features	feature	NOUN
ajst-31456	113	18	.	.	PUNCT
ajst-31456	114	1	1	1	X
ajst-31456	114	2	)	)	PUNCT
ajst-31456	114	3	time	time	NOUN
ajst-31456	114	4	feature	feature	NOUN
ajst-31456	114	5	extraction	extraction	NOUN
ajst-31456	114	6	:	:	PUNCT
ajst-31456	114	7	this	this	DET
ajst-31456	114	8	article	article	NOUN
ajst-31456	114	9	extracted	extract	VERB
ajst-31456	114	10	four	four	NUM
ajst-31456	114	11	vari	vari	ADJ
ajst-31456	114	12	ables	able	NOUN
ajst-31456	114	13	,	,	PUNCT
ajst-31456	114	14	year	year	NOUN
ajst-31456	114	15	,	,	PUNCT
ajst-31456	114	16	month	month	NOUN
ajst-31456	114	17	,	,	PUNCT
ajst-31456	114	18	hour	hour	NOUN
ajst-31456	114	19	,	,	PUNCT
ajst-31456	114	20	and	and	CCONJ
ajst-31456	114	21	dayofweek	dayofweek	PROPN
ajst-31456	114	22	,	,	PUNCT
ajst-31456	114	23	from	from	ADP
ajst-31456	114	24	the	the	DET
ajst-31456	114	25	original	original	ADJ
ajst-31456	114	26	timestamp	timestamp	NOUN
ajst-31456	114	27	features	feature	NOUN
ajst-31456	114	28	,	,	PUNCT
ajst-31456	114	29	and	and	CCONJ
ajst-31456	114	30	removed	remove	VERB
ajst-31456	114	31	the	the	DET
ajst-31456	114	32	original	original	ADJ
ajst-31456	114	33	datatime	datatime	NOUN
ajst-31456	114	34	vari	vari	X
ajst-31456	114	35	able	able	ADJ
ajst-31456	114	36	.	.	PUNCT
ajst-31456	115	1	2	2	X
ajst-31456	115	2	)	)	PUNCT
ajst-31456	115	3	daily	daily	ADJ
ajst-31456	115	4	feature	feature	NOUN
ajst-31456	115	5	removal	removal	NOUN
ajst-31456	115	6	:	:	PUNCT
ajst-31456	115	7	due	due	ADP
ajst-31456	115	8	to	to	ADP
ajst-31456	115	9	the	the	DET
ajst-31456	115	10	relatively	relatively	ADV
ajst-31456	115	11	limited	limited	ADJ
ajst-31456	115	12	contribution	contribution	NOUN
ajst-31456	115	13	of	of	ADP
ajst-31456	115	14	specific	specific	ADJ
ajst-31456	115	15	”	"	PUNCT
ajst-31456	115	16	days	day	NOUN
ajst-31456	115	17	”	"	PUNCT
ajst-31456	115	18	in	in	ADP
ajst-31456	115	19	the	the	DET
ajst-31456	115	20	month	month	NOUN
ajst-31456	115	21	to	to	ADP
ajst-31456	115	22	the	the	DET
ajst-31456	115	23	hourly	hourly	ADJ
ajst-31456	115	24	demand	demand	NOUN
ajst-31456	115	25	pattern	pattern	NOUN
ajst-31456	115	26	and	and	CCONJ
ajst-31456	115	27	the	the	DET
ajst-31456	115	28	introduction	introduction	NOUN
ajst-31456	115	29	of	of	ADP
ajst-31456	115	30	unnecessary	unnecessary	ADJ
ajst-31456	115	31	model	model	NOUN
ajst-31456	115	32	complexity	complexity	NOUN
ajst-31456	115	33	.	.	PUNCT
ajst-31456	116	1	therefore	therefore	ADV
ajst-31456	116	2	,	,	PUNCT
ajst-31456	116	3	this	this	DET
ajst-31456	116	4	article	article	NOUN
ajst-31456	116	5	will	will	AUX
ajst-31456	116	6	remove	remove	VERB
ajst-31456	116	7	daily	daily	ADJ
ajst-31456	116	8	features	feature	NOUN
ajst-31456	116	9	.	.	PUNCT
ajst-31456	117	1	3	3	X
ajst-31456	117	2	)	)	PUNCT
ajst-31456	117	3	actual	actual	ADJ
ajst-31456	117	4	temperature	temperature	NOUN
ajst-31456	117	5	feature	feature	NOUN
ajst-31456	117	6	removal	removal	NOUN
ajst-31456	117	7	:	:	PUNCT
ajst-31456	117	8	there	there	PRON
ajst-31456	117	9	is	be	VERB
ajst-31456	117	10	a	a	DET
ajst-31456	117	11	very	very	ADV
ajst-31456	117	12	high	high	ADJ
ajst-31456	117	13	pearson	pearson	NOUN
ajst-31456	117	14	correlation	correlation	NOUN
ajst-31456	117	15	coefficient	coefficient	NOUN
ajst-31456	117	16	between	between	ADP
ajst-31456	117	17	atemp	atemp	NOUN
ajst-31456	117	18	and	and	CCONJ
ajst-31456	117	19	temp	temp	NOUN
ajst-31456	117	20	,	,	PUNCT
ajst-31456	117	21	indicating	indicate	VERB
ajst-31456	117	22	a	a	DET
ajst-31456	117	23	serious	serious	ADJ
ajst-31456	117	24	collinearity	collinearity	NOUN
ajst-31456	117	25	issue	issue	NOUN
ajst-31456	117	26	between	between	ADP
ajst-31456	117	27	the	the	DET
ajst-31456	117	28	two	two	NUM
ajst-31456	117	29	.	.	PUNCT
ajst-31456	118	1	therefore	therefore	ADV
ajst-31456	118	2	,	,	PUNCT
ajst-31456	118	3	this	this	DET
ajst-31456	118	4	article	article	NOUN
ajst-31456	118	5	chooses	choose	VERB
ajst-31456	118	6	to	to	PART
ajst-31456	118	7	retain	retain	VERB
ajst-31456	118	8	the	the	DET
ajst-31456	118	9	perceived	perceive	VERB
ajst-31456	118	10	temperature	temperature	NOUN
ajst-31456	118	11	that	that	PRON
ajst-31456	118	12	has	have	VERB
ajst-31456	118	13	a	a	DET
ajst-31456	118	14	greater	great	ADJ
ajst-31456	118	15	impact	impact	NOUN
ajst-31456	118	16	on	on	ADP
ajst-31456	118	17	the	the	DET
ajst-31456	118	18	riding	ride	VERB
ajst-31456	118	19	experience	experience	NOUN
ajst-31456	118	20	.	.	PUNCT
ajst-31456	119	1	through	through	ADP
ajst-31456	119	2	exploratory	exploratory	ADJ
ajst-31456	119	3	data	datum	NOUN
ajst-31456	119	4	analysis	analysis	NOUN
ajst-31456	119	5	,	,	PUNCT
ajst-31456	119	6	it	it	PRON
ajst-31456	119	7	was	be	AUX
ajst-31456	119	8	found	find	VERB
ajst-31456	119	9	that	that	SCONJ
ajst-31456	119	10	there	there	PRON
ajst-31456	119	11	are	be	VERB
ajst-31456	119	12	many	many	ADJ
ajst-31456	119	13	outliers	outlier	NOUN
ajst-31456	119	14	in	in	ADP
ajst-31456	119	15	some	some	DET
ajst-31456	119	16	numerical	numerical	ADJ
ajst-31456	119	17	features	feature	NOUN
ajst-31456	119	18	.	.	PUNCT
ajst-31456	120	1	this	this	DET
ajst-31456	120	2	article	article	NOUN
ajst-31456	120	3	uses	use	VERB
ajst-31456	120	4	the	the	DET
ajst-31456	120	5	cap	cap	NOUN
ajst-31456	120	6	method	method	NOUN
ajst-31456	120	7	to	to	PART
ajst-31456	120	8	correct	correct	VERB
ajst-31456	120	9	these	these	DET
ajst-31456	120	10	special	special	ADJ
ajst-31456	120	11	observations	observation	NOUN
ajst-31456	120	12	.	.	PUNCT
ajst-31456	121	1	1	1	X
ajst-31456	121	2	)	)	PUNCT
ajst-31456	121	3	firstly	firstly	ADV
ajst-31456	121	4	,	,	PUNCT
ajst-31456	121	5	the	the	DET
ajst-31456	121	6	correction	correction	NOUN
ajst-31456	121	7	of	of	ADP
ajst-31456	121	8	humidity	humidity	NOUN
ajst-31456	121	9	values	value	NOUN
ajst-31456	121	10	:	:	PUNCT
ajst-31456	121	11	the	the	DET
ajst-31456	121	12	lower	low	ADJ
ajst-31456	121	13	bound	bind	VERB
ajst-31456	121	14	of	of	ADP
ajst-31456	121	15	the	the	DET
ajst-31456	121	16	outlier	outlier	NOUN
ajst-31456	121	17	calculated	calculate	VERB
ajst-31456	121	18	by	by	ADP
ajst-31456	121	19	the	the	DET
ajst-31456	121	20	anomaly	anomaly	NOUN
ajst-31456	121	21	detection	detection	NOUN
ajst-31456	121	22	method	method	NOUN
ajst-31456	121	23	based	base	VERB
ajst-31456	121	24	on	on	ADP
ajst-31456	121	25	quartile	quartile	ADJ
ajst-31456	121	26	range	range	NOUN
ajst-31456	121	27	is	be	AUX
ajst-31456	121	28	2	2	NUM
ajst-31456	121	29	%	%	NOUN
ajst-31456	121	30	,	,	PUNCT
ajst-31456	121	31	and	and	CCONJ
ajst-31456	121	32	humidity	humidity	NOUN
ajst-31456	121	33	observations	observation	NOUN
ajst-31456	121	34	below	below	ADP
ajst-31456	121	35	2	2	NUM
ajst-31456	121	36	%	%	NOUN
ajst-31456	121	37	are	be	AUX
ajst-31456	121	38	identified	identify	VERB
ajst-31456	121	39	as	as	ADP
ajst-31456	121	40	potential	potential	ADJ
ajst-31456	121	41	statistical	statistical	ADJ
ajst-31456	121	42	anomalies	anomaly	NOUN
ajst-31456	121	43	.	.	PUNCT
ajst-31456	122	1	the	the	DET
ajst-31456	122	2	correction	correction	NOUN
ajst-31456	122	3	formula	formula	NOUN
ajst-31456	122	4	is	be	AUX
ajst-31456	122	5	h′	h′	PROPN
ajst-31456	122	6	=	=	SYM
ajst-31456	122	7	max	max	PROPN
ajst-31456	122	8	(	(	PUNCT
ajst-31456	122	9	htarget_floor	htarget_floor	PROPN
ajst-31456	122	10	,	,	PUNCT
ajst-31456	122	11	hmin_valid	hmin_valid	ADV
ajst-31456	122	12	)	)	PUNCT
ajst-31456	122	13	,	,	PUNCT
ajst-31456	122	14	where	where	SCONJ
ajst-31456	122	15	htarget_floor	htarget_floor	PROPN
ajst-31456	122	16	is	be	AUX
ajst-31456	122	17	a	a	DET
ajst-31456	122	18	preset	preset	ADJ
ajst-31456	122	19	lower	low	ADJ
ajst-31456	122	20	limit	limit	NOUN
ajst-31456	122	21	for	for	ADP
ajst-31456	122	22	target	target	NOUN
ajst-31456	122	23	correction	correction	NOUN
ajst-31456	122	24	,	,	PUNCT
ajst-31456	122	25	set	set	VERB
ajst-31456	122	26	at	at	ADP
ajst-31456	122	27	5	5	NUM
ajst-31456	122	28	%	%	NOUN
ajst-31456	122	29	in	in	ADP
ajst-31456	122	30	this	this	DET
ajst-31456	122	31	study	study	NOUN
ajst-31456	122	32	.	.	PUNCT
ajst-31456	123	1	hmin_valid	hmin_valid	PROPN
ajst-31456	123	2	is	be	AUX
ajst-31456	123	3	the	the	DET
ajst-31456	123	4	minimum	minimum	ADJ
ajst-31456	123	5	value	value	NOUN
ajst-31456	123	6	among	among	ADP
ajst-31456	123	7	all	all	DET
ajst-31456	123	8	observations	observation	NOUN
ajst-31456	123	9	in	in	ADP
ajst-31456	123	10	the	the	DET
ajst-31456	123	11	training	training	NOUN
ajst-31456	123	12	dataset	dataset	NOUN
ajst-31456	123	13	where	where	SCONJ
ajst-31456	123	14	the	the	DET
ajst-31456	123	15	original	original	ADJ
ajst-31456	123	16	humidity	humidity	NOUN
ajst-31456	123	17	value	value	NOUN
ajst-31456	123	18	is	be	AUX
ajst-31456	123	19	not	not	PART
ajst-31456	123	20	lower	low	ADJ
ajst-31456	123	21	than	than	ADP
ajst-31456	123	22	the	the	DET
ajst-31456	123	23	threshold	threshold	NOUN
ajst-31456	123	24	(	(	PUNCT
ajst-31456	123	25	i.e.	i.e.	X
ajst-31456	123	26	,≥	,≥	PUNCT
ajst-31456	123	27	2	2	NUM
ajst-31456	123	28	%	%	NOUN
ajst-31456	123	29	)	)	PUNCT
ajst-31456	123	30	.	.	PUNCT
ajst-31456	124	1	therefore	therefore	ADV
ajst-31456	124	2	,	,	PUNCT
ajst-31456	124	3	the	the	DET
ajst-31456	124	4	final	final	ADJ
ajst-31456	124	5	cap	cap	NOUN
ajst-31456	124	6	value	value	NOUN
ajst-31456	124	7	hcap_value	hcap_value	NOUN
ajst-31456	124	8	is	be	AUX
ajst-31456	124	9	max(5	max(5	NOUN
ajst-31456	124	10	%	%	NOUN
ajst-31456	124	11	,	,	PUNCT
ajst-31456	124	12	hmin_valid	hmin_valid	PROPN
ajst-31456	124	13	)	)	PUNCT
ajst-31456	124	14	.	.	PUNCT
ajst-31456	125	1	2	2	X
ajst-31456	125	2	)	)	PUNCT
ajst-31456	125	3	wind	wind	NOUN
ajst-31456	125	4	speed	speed	NOUN
ajst-31456	125	5	processing	processing	NOUN
ajst-31456	125	6	:	:	PUNCT
ajst-31456	125	7	the	the	DET
ajst-31456	125	8	dataset	dataset	NOUN
ajst-31456	125	9	records	record	VERB
ajst-31456	125	10	some	some	DET
ajst-31456	125	11	extremely	extremely	ADV
ajst-31456	125	12	high	high	ADJ
ajst-31456	125	13	values	value	NOUN
ajst-31456	125	14	.	.	PUNCT
ajst-31456	126	1	there	there	PRON
ajst-31456	126	2	are	be	VERB
ajst-31456	126	3	1313	1313	NUM
ajst-31456	126	4	wind	wind	NOUN
ajst-31456	126	5	speed	speed	NOUN
ajst-31456	126	6	records	record	NOUN
ajst-31456	126	7	in	in	ADP
ajst-31456	126	8	the	the	DET
ajst-31456	126	9	original	original	ADJ
ajst-31456	126	10	dataset	dataset	NOUN
ajst-31456	126	11	with	with	ADP
ajst-31456	126	12	a	a	DET
ajst-31456	126	13	value	value	NOUN
ajst-31456	126	14	of	of	ADP
ajst-31456	126	15	0	0	NUM
ajst-31456	126	16	,	,	PUNCT
ajst-31456	126	17	and	and	CCONJ
ajst-31456	126	18	a	a	DET
ajst-31456	126	19	maximum	maximum	ADJ
ajst-31456	126	20	wind	wind	NOUN
ajst-31456	126	21	speed	speed	NOUN
ajst-31456	126	22	value	value	NOUN
ajst-31456	126	23	of	of	ADP
ajst-31456	126	24	56.9969	56.9969	NUM
ajst-31456	126	25	km	km	NOUN
ajst-31456	126	26	/	/	SYM
ajst-31456	126	27	h	h	NOUN
ajst-31456	126	28	,	,	PUNCT
ajst-31456	126	29	while	while	SCONJ
ajst-31456	126	30	the	the	DET
ajst-31456	126	31	99	99	NUM
ajst-31456	126	32	%	%	NOUN
ajst-31456	126	33	percentile	percentile	NOUN
ajst-31456	126	34	is	be	AUX
ajst-31456	126	35	35.0008	35.0008	NUM
ajst-31456	126	36	km	km	PROPN
ajst-31456	126	37	/	/	SYM
ajst-31456	126	38	h.	h.	PROPN
ajst-31456	126	39	in	in	ADP
ajst-31456	126	40	order	order	NOUN
ajst-31456	126	41	to	to	PART
ajst-31456	126	42	reduce	reduce	VERB
ajst-31456	126	43	the	the	DET
ajst-31456	126	44	impact	impact	NOUN
ajst-31456	126	45	of	of	ADP
ajst-31456	126	46	these	these	DET
ajst-31456	126	47	outliers	outlier	NOUN
ajst-31456	126	48	on	on	ADP
ajst-31456	126	49	the	the	DET
ajst-31456	126	50	model	model	NOUN
ajst-31456	126	51	,	,	PUNCT
ajst-31456	126	52	this	this	DET
ajst-31456	126	53	paper	paper	NOUN
ajst-31456	126	54	has	have	AUX
ajst-31456	126	55	processed	process	VERB
ajst-31456	126	56	them	they	PRON
ajst-31456	126	57	.	.	PUNCT
ajst-31456	127	1	based	base	VERB
ajst-31456	127	2	on	on	ADP
ajst-31456	127	3	the	the	DET
ajst-31456	127	4	above	above	ADJ
ajst-31456	127	5	two	two	NUM
ajst-31456	127	6	issues	issue	NOUN
ajst-31456	127	7	,	,	PUNCT
ajst-31456	127	8	the	the	DET
ajst-31456	127	9	corrected	correct	VERB
ajst-31456	127	10	wind	wind	NOUN
ajst-31456	127	11	speed	speed	NOUN
ajst-31456	127	12	w′	w′	PROPN
ajst-31456	127	13	is	be	AUX
ajst-31456	127	14	defined	define	VERB
ajst-31456	127	15	as	as	SCONJ
ajst-31456	127	16	follows	follow	VERB
ajst-31456	127	17	:	:	PUNCT
ajst-31456	128	1	w	w	NOUN
ajst-31456	128	2	’	'	PUNCT
ajst-31456	128	3	=	=	SYM
ajst-31456	128	4	𝑤	𝑤	PART
ajst-31456	128	5	%	%	INTJ
ajst-31456	128	6	𝑖𝑓	𝑖𝑓	ADP
ajst-31456	128	7	𝑤	𝑤	ADP
ajst-31456	128	8	0	0	NUM
ajst-31456	128	9	𝑤	𝑤	PRON
ajst-31456	128	10	%	%	NOUN
ajst-31456	129	1	6.0032	6.0032	NUM
ajst-31456	129	2	𝑘𝑚/ℎ	𝑘𝑚/ℎ	NOUN
ajst-31456	129	3	𝑤	𝑤	ADP
ajst-31456	129	4	_	_	PUNCT
ajst-31456	129	5	𝑖𝑓	𝑖𝑓	ADP
ajst-31456	130	1	𝑤	𝑤	VERB
ajst-31456	130	2	𝑤	𝑤	PART
ajst-31456	130	3	_	_	PUNCT
ajst-31456	130	4	𝑤	𝑤	PART
ajst-31456	130	5	_	_	PRON
ajst-31456	130	6	35	35	NUM
ajst-31456	130	7	𝑘𝑚/ℎ	𝑘𝑚/ℎ	NOUN
ajst-31456	130	8	𝑤	𝑤	ADP
ajst-31456	130	9	𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒	𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒	NOUN
ajst-31456	130	10	(	(	PUNCT
ajst-31456	130	11	3	3	X
ajst-31456	130	12	)	)	PUNCT
ajst-31456	130	13	figure	figure	NOUN
ajst-31456	130	14	2	2	NUM
ajst-31456	130	15	.	.	PUNCT
ajst-31456	130	16	distribution	distribution	NOUN
ajst-31456	130	17	diagram	diagram	NOUN
ajst-31456	130	18	of	of	ADP
ajst-31456	130	19	each	each	DET
ajst-31456	130	20	variable	variable	NOUN
ajst-31456	130	21	.	.	PUNCT
ajst-31456	131	1	in	in	ADP
ajst-31456	131	2	order	order	NOUN
ajst-31456	131	3	to	to	PART
ajst-31456	131	4	effectively	effectively	ADV
ajst-31456	131	5	utilize	utilize	VERB
ajst-31456	131	6	them	they	PRON
ajst-31456	131	7	by	by	ADP
ajst-31456	131	8	machine	machine	NOUN
ajst-31456	131	9	learning	learning	NOUN
ajst-31456	131	10	models	model	NOUN
ajst-31456	131	11	,	,	PUNCT
ajst-31456	131	12	this	this	DET
ajst-31456	131	13	study	study	NOUN
ajst-31456	131	14	first	first	ADV
ajst-31456	131	15	encodes	encode	VERB
ajst-31456	131	16	some	some	DET
ajst-31456	131	17	basic	basic	ADJ
ajst-31456	131	18	categorical	categorical	ADJ
ajst-31456	131	19	features	feature	NOUN
ajst-31456	131	20	:	:	PUNCT
ajst-31456	131	21	1	1	X
ajst-31456	131	22	)	)	PUNCT
ajst-31456	131	23	weather	weather	NOUN
ajst-31456	131	24	feature	feature	NOUN
ajst-31456	131	25	processing	processing	NOUN
ajst-31456	131	26	and	and	CCONJ
ajst-31456	131	27	encoding	encoding	NOUN
ajst-31456	131	28	:	:	PUNCT
ajst-31456	131	29	the	the	DET
ajst-31456	131	30	sample	sample	NOUN
ajst-31456	131	31	size	size	NOUN
ajst-31456	131	32	of	of	ADP
ajst-31456	131	33	category	category	NOUN
ajst-31456	131	34	4	4	NUM
ajst-31456	131	35	in	in	ADP
ajst-31456	131	36	the	the	DET
ajst-31456	131	37	original	original	ADJ
ajst-31456	131	38	weather	weather	NOUN
ajst-31456	131	39	features	feature	NOUN
ajst-31456	131	40	is	be	AUX
ajst-31456	131	41	extremely	extremely	ADV
ajst-31456	131	42	small	small	ADJ
ajst-31456	131	43	(	(	PUNCT
ajst-31456	131	44	only	only	ADV
ajst-31456	131	45	1	1	NUM
ajst-31456	131	46	case	case	NOUN
ajst-31456	131	47	appears	appear	VERB
ajst-31456	131	48	in	in	ADP
ajst-31456	131	49	the	the	DET
ajst-31456	131	50	training	training	NOUN
ajst-31456	131	51	set	set	NOUN
ajst-31456	131	52	)	)	PUNCT
ajst-31456	131	53	.	.	PUNCT
ajst-31456	132	1	to	to	PART
ajst-31456	132	2	avoid	avoid	VERB
ajst-31456	132	3	the	the	DET
ajst-31456	132	4	interference	interference	NOUN
ajst-31456	132	5	that	that	PRON
ajst-31456	132	6	sparse	sparse	ADJ
ajst-31456	132	7	categories	category	NOUN
ajst-31456	132	8	may	may	AUX
ajst-31456	132	9	cause	cause	VERB
ajst-31456	132	10	to	to	PART
ajst-31456	132	11	model	model	NOUN
ajst-31456	132	12	learning	learning	NOUN
ajst-31456	132	13	,	,	PUNCT
ajst-31456	132	14	category	category	NOUN
ajst-31456	132	15	4	4	NUM
ajst-31456	132	16	is	be	AUX
ajst-31456	132	17	merged	merge	VERB
ajst-31456	132	18	into	into	ADP
ajst-31456	132	19	category	category	NOUN
ajst-31456	132	20	3	3	NUM
ajst-31456	132	21	.	.	PUNCT
ajst-31456	133	1	subsequently	subsequently	ADV
ajst-31456	133	2	,	,	PUNCT
ajst-31456	133	3	the	the	DET
ajst-31456	133	4	one	one	NUM
ajst-31456	133	5	hot	hot	ADJ
ajst-31456	133	6	encoding	encoding	NOUN
ajst-31456	133	7	technique	technique	NOUN
ajst-31456	133	8	was	be	AUX
ajst-31456	133	9	used	use	VERB
ajst-31456	133	10	to	to	PART
ajst-31456	133	11	convert	convert	VERB
ajst-31456	133	12	it	it	PRON
ajst-31456	133	13	into	into	ADP
ajst-31456	133	14	multiple	multiple	ADJ
ajst-31456	133	15	binary	binary	ADJ
ajst-31456	133	16	indicator	indicator	NOUN
ajst-31456	133	17	variables	variable	NOUN
ajst-31456	133	18	.	.	PUNCT
ajst-31456	134	1	2	2	X
ajst-31456	134	2	)	)	PUNCT
ajst-31456	134	3	encoding	encoding	NOUN
ajst-31456	134	4	of	of	ADP
ajst-31456	134	5	other	other	ADJ
ajst-31456	134	6	time	time	NOUN
ajst-31456	134	7	category	category	NOUN
ajst-31456	134	8	features	feature	VERB
ajst-31456	134	9	:	:	PUNCT
ajst-31456	134	10	single	single	ADJ
ajst-31456	134	11	hot	hot	ADJ
ajst-31456	134	12	encoding	encoding	NOUN
ajst-31456	134	13	technology	technology	NOUN
ajst-31456	134	14	is	be	AUX
ajst-31456	134	15	also	also	ADV
ajst-31456	134	16	used	use	VERB
ajst-31456	134	17	for	for	ADP
ajst-31456	134	18	other	other	ADJ
ajst-31456	134	19	time	time	NOUN
ajst-31456	134	20	category	category	NOUN
ajst-31456	134	21	features	feature	VERB
ajst-31456	134	22	.	.	PUNCT
ajst-31456	135	1	to	to	PART
ajst-31456	135	2	precisely	precisely	ADV
ajst-31456	135	3	capture	capture	VERB
ajst-31456	135	4	the	the	DET
ajst-31456	135	5	complex	complex	ADJ
ajst-31456	135	6	,	,	PUNCT
ajst-31456	135	7	non	non	ADJ
ajst-31456	135	8	-	-	ADJ
ajst-31456	135	9	linear	linear	ADJ
ajst-31456	135	10	relationships	relationship	NOUN
ajst-31456	135	11	between	between	ADP
ajst-31456	135	12	continuous	continuous	ADJ
ajst-31456	135	13	features	feature	NOUN
ajst-31456	135	14	like	like	ADP
ajst-31456	135	15	apparent	apparent	ADJ
ajst-31456	135	16	temperature	temperature	NOUN
ajst-31456	135	17	(	(	PUNCT
ajst-31456	135	18	atemp	atemp	NOUN
ajst-31456	135	19	)	)	PUNCT
ajst-31456	135	20	and	and	CCONJ
ajst-31456	135	21	humidity	humidity	NOUN
ajst-31456	135	22	(	(	PUNCT
ajst-31456	135	23	humidity	humidity	NOUN
ajst-31456	135	24	)	)	PUNCT
ajst-31456	135	25	and	and	CCONJ
ajst-31456	135	26	the	the	DET
ajst-31456	135	27	rental	rental	ADJ
ajst-31456	135	28	counts	count	NOUN
ajst-31456	135	29	,	,	PUNCT
ajst-31456	135	30	a	a	DET
ajst-31456	135	31	datadriven	datadriven	ADJ
ajst-31456	135	32	binning	bin	VERB
ajst-31456	135	33	approach	approach	NOUN
ajst-31456	135	34	was	be	AUX
ajst-31456	135	35	adopted	adopt	VERB
ajst-31456	135	36	.	.	PUNCT
ajst-31456	136	1	this	this	DET
ajst-31456	136	2	method	method	NOUN
ajst-31456	136	3	automates	automate	VERB
ajst-31456	136	4	the	the	DET
ajst-31456	136	5	discovery	discovery	NOUN
ajst-31456	136	6	of	of	ADP
ajst-31456	136	7	meaningful	meaningful	ADJ
ajst-31456	136	8	thresholds	threshold	NOUN
ajst-31456	136	9	by	by	ADP
ajst-31456	136	10	analyzing	analyze	VERB
ajst-31456	136	11	the	the	DET
ajst-31456	136	12	trend	trend	NOUN
ajst-31456	136	13	of	of	ADP
ajst-31456	136	14	rental	rental	ADJ
ajst-31456	136	15	demand	demand	NOUN
ajst-31456	136	16	.	.	PUNCT
ajst-31456	137	1	the	the	DET
ajst-31456	137	2	core	core	NOUN
ajst-31456	137	3	of	of	ADP
ajst-31456	137	4	this	this	DET
ajst-31456	137	5	approach	approach	NOUN
ajst-31456	137	6	is	be	AUX
ajst-31456	137	7	the	the	DET
ajst-31456	137	8	savitzkygolay	savitzkygolay	NOUN
ajst-31456	137	9	(	(	PUNCT
ajst-31456	137	10	sg	sg	PROPN
ajst-31456	137	11	)	)	PUNCT
ajst-31456	137	12	filter	filter	NOUN
ajst-31456	137	13	,	,	PUNCT
ajst-31456	137	14	which	which	PRON
ajst-31456	137	15	is	be	AUX
ajst-31456	137	16	used	use	VERB
ajst-31456	137	17	to	to	PART
ajst-31456	137	18	smooth	smooth	VERB
ajst-31456	137	19	the	the	DET
ajst-31456	137	20	noisy	noisy	ADJ
ajst-31456	137	21	trend	trend	NOUN
ajst-31456	137	22	data	datum	NOUN
ajst-31456	137	23	.	.	PUNCT
ajst-31456	138	1	figure	figure	NOUN
ajst-31456	138	2	3	3	NUM
ajst-31456	138	3	.	.	NOUN
ajst-31456	138	4	comparison	comparison	NOUN
ajst-31456	138	5	chart	chart	NOUN
ajst-31456	138	6	before	before	ADV
ajst-31456	138	7	and	and	CCONJ
ajst-31456	138	8	after	after	ADP
ajst-31456	138	9	count	count	PROPN
ajst-31456	138	10	conversion	conversion	NOUN
ajst-31456	138	11	55	55	NUM
ajst-31456	138	12	figure	figure	NOUN
ajst-31456	138	13	4	4	NUM
ajst-31456	138	14	.	.	PUNCT
ajst-31456	139	1	heatmap	heatmap	NOUN
ajst-31456	139	2	of	of	ADP
ajst-31456	139	3	the	the	DET
ajst-31456	139	4	pearson	pearson	NOUN
ajst-31456	139	5	correlation	correlation	NOUN
ajst-31456	139	6	matrix	matrix	NOUN
ajst-31456	139	7	.	.	PUNCT
ajst-31456	140	1	the	the	DET
ajst-31456	140	2	sg	sg	PROPN
ajst-31456	140	3	filter	filter	NOUN
ajst-31456	140	4	works	work	NOUN
ajst-31456	140	5	by	by	ADP
ajst-31456	140	6	fitting	fit	VERB
ajst-31456	140	7	a	a	DET
ajst-31456	140	8	local	local	ADJ
ajst-31456	140	9	polynomial	polynomial	ADJ
ajst-31456	140	10	regression	regression	NOUN
ajst-31456	140	11	to	to	ADP
ajst-31456	140	12	the	the	DET
ajst-31456	140	13	data	datum	NOUN
ajst-31456	140	14	within	within	ADP
ajst-31456	140	15	a	a	DET
ajst-31456	140	16	sliding	slide	VERB
ajst-31456	140	17	window	window	NOUN
ajst-31456	140	18	.	.	PUNCT
ajst-31456	141	1	for	for	ADP
ajst-31456	141	2	a	a	DET
ajst-31456	141	3	given	give	VERB
ajst-31456	141	4	data	data	NOUN
ajst-31456	141	5	point	point	NOUN
ajst-31456	141	6	,	,	PUNCT
ajst-31456	141	7	its	its	PRON
ajst-31456	141	8	smoothed	smooth	VERB
ajst-31456	141	9	value	value	NOUN
ajst-31456	141	10	is	be	AUX
ajst-31456	141	11	the	the	DET
ajst-31456	141	12	value	value	NOUN
ajst-31456	141	13	of	of	ADP
ajst-31456	141	14	the	the	DET
ajst-31456	141	15	fitted	fit	VERB
ajst-31456	141	16	polynomial	polynomial	NOUN
ajst-31456	141	17	at	at	ADP
ajst-31456	141	18	that	that	DET
ajst-31456	141	19	point	point	NOUN
ajst-31456	141	20	’s	’s	PART
ajst-31456	141	21	location	location	NOUN
ajst-31456	141	22	.	.	PUNCT
ajst-31456	142	1	this	this	PRON
ajst-31456	142	2	can	can	AUX
ajst-31456	142	3	be	be	AUX
ajst-31456	142	4	represented	represent	VERB
ajst-31456	142	5	by	by	ADP
ajst-31456	142	6	fitting	fit	VERB
ajst-31456	142	7	a	a	DET
ajst-31456	142	8	polynomial	polynomial	NOUN
ajst-31456	142	9	of	of	ADP
ajst-31456	142	10	degree	degree	NOUN
ajst-31456	142	11	k	k	NOUN
ajst-31456	142	12	:	:	PUNCT
ajst-31456	142	13	p(t	p(t	NOUN
ajst-31456	142	14	)	)	PUNCT
ajst-31456	143	1	=	=	SYM
ajst-31456	143	2	a0	a0	PROPN
ajst-31456	143	3	+	+	CCONJ
ajst-31456	143	4	a1	a1	PROPN
ajst-31456	143	5	t	t	NOUN
ajst-31456	143	6	+	+	CCONJ
ajst-31456	143	7	a2t2	a2t2	PROPN
ajst-31456	143	8	+	+	CCONJ
ajst-31456	143	9	·	·	PUNCT
ajst-31456	143	10	·	·	PUNCT
ajst-31456	143	11	·	·	PUNCT
ajst-31456	144	1	+	+	CCONJ
ajst-31456	144	2	aktk	aktk	ADJ
ajst-31456	144	3	(	(	PUNCT
ajst-31456	144	4	4	4	NUM
ajst-31456	144	5	)	)	PUNCT
ajst-31456	144	6	the	the	DET
ajst-31456	144	7	key	key	ADJ
ajst-31456	144	8	idea	idea	NOUN
ajst-31456	144	9	is	be	AUX
ajst-31456	144	10	to	to	PART
ajst-31456	144	11	find	find	VERB
ajst-31456	144	12	the	the	DET
ajst-31456	144	13	coefficients	coefficient	NOUN
ajst-31456	144	14	aj	aj	PROPN
ajst-31456	144	15	that	that	PRON
ajst-31456	144	16	minimize	minimize	VERB
ajst-31456	144	17	the	the	DET
ajst-31456	144	18	least	least	ADJ
ajst-31456	144	19	-	-	PUNCT
ajst-31456	144	20	squares	square	NOUN
ajst-31456	144	21	error	error	NOUN
ajst-31456	144	22	between	between	ADP
ajst-31456	144	23	the	the	DET
ajst-31456	144	24	polynomial	polynomial	ADJ
ajst-31456	144	25	p(t	p(t	NOUN
ajst-31456	144	26	)	)	PUNCT
ajst-31456	144	27	and	and	CCONJ
ajst-31456	144	28	the	the	DET
ajst-31456	144	29	raw	raw	ADJ
ajst-31456	144	30	data	datum	NOUN
ajst-31456	144	31	within	within	ADP
ajst-31456	144	32	the	the	DET
ajst-31456	144	33	window	window	NOUN
ajst-31456	144	34	.	.	PUNCT
ajst-31456	145	1	this	this	PRON
ajst-31456	145	2	effectively	effectively	ADV
ajst-31456	145	3	removes	remove	VERB
ajst-31456	145	4	short	short	ADJ
ajst-31456	145	5	-	-	PUNCT
ajst-31456	145	6	term	term	NOUN
ajst-31456	145	7	noise	noise	NOUN
ajst-31456	145	8	while	while	SCONJ
ajst-31456	145	9	preserving	preserve	VERB
ajst-31456	145	10	significant	significant	ADJ
ajst-31456	145	11	features	feature	NOUN
ajst-31456	145	12	of	of	ADP
ajst-31456	145	13	the	the	DET
ajst-31456	145	14	trend	trend	NOUN
ajst-31456	145	15	,	,	PUNCT
ajst-31456	145	16	such	such	ADJ
ajst-31456	145	17	as	as	ADP
ajst-31456	145	18	peaks	peak	NOUN
ajst-31456	145	19	and	and	CCONJ
ajst-31456	145	20	turning	turning	NOUN
ajst-31456	145	21	points	point	NOUN
ajst-31456	145	22	.	.	PUNCT
ajst-31456	146	1	in	in	ADP
ajst-31456	146	2	this	this	DET
ajst-31456	146	3	study	study	NOUN
ajst-31456	146	4	,	,	PUNCT
ajst-31456	146	5	the	the	DET
ajst-31456	146	6	process	process	NOUN
ajst-31456	146	7	involved	involve	VERB
ajst-31456	146	8	first	first	ADV
ajst-31456	146	9	creating	create	VERB
ajst-31456	146	10	a	a	DET
ajst-31456	146	11	large	large	ADJ
ajst-31456	146	12	number	number	NOUN
ajst-31456	146	13	of	of	ADP
ajst-31456	146	14	fine	fine	ADV
ajst-31456	146	15	-	-	PUNCT
ajst-31456	146	16	grained	grain	VERB
ajst-31456	146	17	bins	bin	NOUN
ajst-31456	146	18	for	for	ADP
ajst-31456	146	19	atemp	atemp	NOUN
ajst-31456	146	20	and	and	CCONJ
ajst-31456	146	21	humidity	humidity	NOUN
ajst-31456	146	22	and	and	CCONJ
ajst-31456	146	23	calculating	calculate	VERB
ajst-31456	146	24	the	the	DET
ajst-31456	146	25	average	average	ADJ
ajst-31456	146	26	rental	rental	ADJ
ajst-31456	146	27	count	count	NOUN
ajst-31456	146	28	for	for	ADP
ajst-31456	146	29	each	each	PRON
ajst-31456	146	30	.	.	PUNCT
ajst-31456	147	1	the	the	DET
ajst-31456	147	2	sg	sg	PROPN
ajst-31456	147	3	filter	filter	NOUN
ajst-31456	147	4	was	be	AUX
ajst-31456	147	5	then	then	ADV
ajst-31456	147	6	applied	apply	VERB
ajst-31456	147	7	to	to	ADP
ajst-31456	147	8	this	this	DET
ajst-31456	147	9	noisy	noisy	ADJ
ajst-31456	147	10	sequence	sequence	NOUN
ajst-31456	147	11	.	.	PUNCT
ajst-31456	148	1	as	as	SCONJ
ajst-31456	148	2	shown	show	VERB
ajst-31456	148	3	in	in	ADP
ajst-31456	148	4	the	the	DET
ajst-31456	148	5	debugging	debugging	NOUN
ajst-31456	148	6	curves	curve	NOUN
ajst-31456	148	7	in	in	ADP
ajst-31456	148	8	fig	fig	NOUN
ajst-31456	148	9	.	.	PUNCT
ajst-31456	149	1	5	5	NUM
ajst-31456	149	2	,	,	PUNCT
ajst-31456	149	3	this	this	DET
ajst-31456	149	4	smoothing	smooth	VERB
ajst-31456	149	5	step	step	NOUN
ajst-31456	149	6	reveals	reveal	VERB
ajst-31456	149	7	the	the	DET
ajst-31456	149	8	underlying	underlie	VERB
ajst-31456	149	9	trend	trend	NOUN
ajst-31456	149	10	clearly	clearly	ADV
ajst-31456	149	11	.	.	PUNCT
ajst-31456	150	1	subsequently	subsequently	ADV
ajst-31456	150	2	,	,	PUNCT
ajst-31456	150	3	a	a	DET
ajst-31456	150	4	heuristic	heuristic	ADJ
ajst-31456	150	5	algorithm	algorithm	NOUN
ajst-31456	150	6	identified	identify	VERB
ajst-31456	150	7	key	key	ADJ
ajst-31456	150	8	turning	turning	NOUN
ajst-31456	150	9	points	point	NOUN
ajst-31456	150	10	on	on	ADP
ajst-31456	150	11	these	these	DET
ajst-31456	150	12	smoothed	smooth	VERB
ajst-31456	150	13	curves	curve	NOUN
ajst-31456	150	14	,	,	PUNCT
ajst-31456	150	15	which	which	PRON
ajst-31456	150	16	were	be	AUX
ajst-31456	150	17	then	then	ADV
ajst-31456	150	18	set	set	VERB
ajst-31456	150	19	as	as	ADP
ajst-31456	150	20	the	the	DET
ajst-31456	150	21	final	final	ADJ
ajst-31456	150	22	binning	binning	NOUN
ajst-31456	150	23	thresholds	threshold	NOUN
ajst-31456	150	24	.	.	PUNCT
ajst-31456	151	1	this	this	DET
ajst-31456	151	2	automated	automate	VERB
ajst-31456	151	3	process	process	NOUN
ajst-31456	151	4	allows	allow	VERB
ajst-31456	151	5	the	the	DET
ajst-31456	151	6	bins	bin	NOUN
ajst-31456	151	7	to	to	PART
ajst-31456	151	8	adapt	adapt	VERB
ajst-31456	151	9	to	to	ADP
ajst-31456	151	10	the	the	DET
ajst-31456	151	11	data	datum	NOUN
ajst-31456	151	12	’s	’s	PART
ajst-31456	151	13	intrinsic	intrinsic	ADJ
ajst-31456	151	14	structure	structure	NOUN
ajst-31456	151	15	,	,	PUNCT
ajst-31456	151	16	leading	lead	VERB
ajst-31456	151	17	to	to	ADP
ajst-31456	151	18	more	more	ADV
ajst-31456	151	19	meaningful	meaningful	ADJ
ajst-31456	151	20	feature	feature	NOUN
ajst-31456	151	21	engineering	engineering	NOUN
ajst-31456	151	22	.	.	PUNCT
ajst-31456	152	1	based	base	VERB
ajst-31456	152	2	on	on	ADP
ajst-31456	152	3	the	the	DET
ajst-31456	152	4	thresholds	threshold	NOUN
ajst-31456	152	5	automatically	automatically	ADV
ajst-31456	152	6	calculated	calculate	VERB
ajst-31456	152	7	,	,	PUNCT
ajst-31456	152	8	the	the	DET
ajst-31456	152	9	ap	ap	PROPN
ajst-31456	152	10	parent	parent	NOUN
ajst-31456	152	11	temperature	temperature	NOUN
ajst-31456	152	12	and	and	CCONJ
ajst-31456	152	13	humidity	humidity	NOUN
ajst-31456	152	14	features	feature	NOUN
ajst-31456	152	15	were	be	AUX
ajst-31456	152	16	binned	bin	VERB
ajst-31456	152	17	.	.	PUNCT
ajst-31456	153	1	the	the	DET
ajst-31456	153	2	statistical	statistical	ADJ
ajst-31456	153	3	characteristics	characteristic	NOUN
ajst-31456	153	4	of	of	ADP
ajst-31456	153	5	the	the	DET
ajst-31456	153	6	resulting	result	VERB
ajst-31456	153	7	new	new	ADJ
ajst-31456	153	8	categories	category	NOUN
ajst-31456	153	9	are	be	AUX
ajst-31456	153	10	summarized	summarize	VERB
ajst-31456	153	11	in	in	ADP
ajst-31456	153	12	table	table	NOUN
ajst-31456	153	13	ii	ii	NOUN
ajst-31456	153	14	and	and	CCONJ
ajst-31456	153	15	table	table	PROPN
ajst-31456	153	16	iii	iii	PROPN
ajst-31456	153	17	.	.	PROPN
ajst-31456	153	18	table	table	PROPN
ajst-31456	153	19	ii	ii	PROPN
ajst-31456	153	20	apparent	apparent	ADJ
ajst-31456	153	21	temperature	temperature	NOUN
ajst-31456	153	22	(	(	PUNCT
ajst-31456	153	23	atemp	atemp	NOUN
ajst-31456	153	24	)	)	PUNCT
ajst-31456	153	25	binned	bin	VERB
ajst-31456	153	26	statistics	statistic	NOUN
ajst-31456	153	27	atemp	atemp	NOUN
ajst-31456	153	28	mean	mean	VERB
ajst-31456	153	29	rentals	rental	NOUN
ajst-31456	153	30	median	median	ADJ
ajst-31456	153	31	rentals	rental	NOUN
ajst-31456	153	32	records	record	VERB
ajst-31456	153	33	low	low	ADJ
ajst-31456	153	34	(	(	PUNCT
ajst-31456	153	35	<	<	X
ajst-31456	153	36	11.04	11.04	NUM
ajst-31456	153	37	◦	◦	NOUN
ajst-31456	153	38	c	c	NOUN
ajst-31456	153	39	)	)	PUNCT
ajst-31456	153	40	73.72	73.72	NUM
ajst-31456	153	41	50.0	50.0	NUM
ajst-31456	153	42	743	743	NUM
ajst-31456	153	43	moderate	moderate	ADJ
ajst-31456	153	44	(	(	PUNCT
ajst-31456	153	45	11.04–38.74	11.04–38.74	NUM
ajst-31456	153	46	◦	◦	NOUN
ajst-31456	153	47	c	c	NOUN
ajst-31456	153	48	)	)	PUNCT
ajst-31456	153	49	197.57	197.57	NUM
ajst-31456	153	50	153.0	153.0	NUM
ajst-31456	153	51	9927	9927	NUM
ajst-31456	153	52	high	high	ADJ
ajst-31456	153	53	(	(	PUNCT
ajst-31456	153	54	≥	≥	NUM
ajst-31456	153	55	38.75	38.75	NUM
ajst-31456	153	56	◦	◦	NOUN
ajst-31456	153	57	c	c	NOUN
ajst-31456	153	58	)	)	PUNCT
ajst-31456	153	59	321.42	321.42	NUM
ajst-31456	153	60	289.0	289.0	NUM
ajst-31456	153	61	216	216	NUM
ajst-31456	153	62	to	to	PART
ajst-31456	153	63	capture	capture	VERB
ajst-31456	153	64	the	the	DET
ajst-31456	153	65	complex	complex	ADJ
ajst-31456	153	66	synergistic	synergistic	ADJ
ajst-31456	153	67	effects	effect	NOUN
ajst-31456	153	68	between	between	ADP
ajst-31456	153	69	vari	vari	ADJ
ajst-31456	153	70	ables	able	NOUN
ajst-31456	153	71	,	,	PUNCT
ajst-31456	153	72	this	this	DET
ajst-31456	153	73	study	study	NOUN
ajst-31456	153	74	constructed	construct	VERB
ajst-31456	153	75	several	several	ADJ
ajst-31456	153	76	interaction	interaction	NOUN
ajst-31456	153	77	features	feature	NOUN
ajst-31456	153	78	.	.	PUNCT
ajst-31456	154	1	the	the	DET
ajst-31456	154	2	core	core	NOUN
ajst-31456	154	3	rationale	rationale	NOUN
ajst-31456	154	4	is	be	AUX
ajst-31456	154	5	that	that	SCONJ
ajst-31456	154	6	the	the	DET
ajst-31456	154	7	impact	impact	NOUN
ajst-31456	154	8	of	of	ADP
ajst-31456	154	9	a	a	DET
ajst-31456	154	10	weather	weather	NOUN
ajst-31456	154	11	condition	condition	NOUN
ajst-31456	154	12	on	on	ADP
ajst-31456	154	13	bike	bike	NOUN
ajst-31456	154	14	rentals	rental	NOUN
ajst-31456	154	15	often	often	ADV
ajst-31456	154	16	depends	depend	VERB
ajst-31456	154	17	on	on	ADP
ajst-31456	154	18	the	the	DET
ajst-31456	154	19	time	time	NOUN
ajst-31456	154	20	of	of	ADP
ajst-31456	154	21	day	day	NOUN
ajst-31456	154	22	.	.	PUNCT
ajst-31456	155	1	for	for	ADP
ajst-31456	155	2	instance	instance	NOUN
ajst-31456	155	3	,	,	PUNCT
ajst-31456	155	4	a	a	DET
ajst-31456	155	5	’	'	PUNCT
ajst-31456	155	6	moderate	moderate	ADJ
ajst-31456	155	7	’	'	PUNCT
ajst-31456	155	8	temperature	temperature	NOUN
ajst-31456	155	9	during	during	ADP
ajst-31456	155	10	commute	commute	NOUN
ajst-31456	155	11	hours	hour	NOUN
ajst-31456	155	12	(	(	PUNCT
ajst-31456	155	13	e.g.	e.g.	ADV
ajst-31456	155	14	,	,	PUNCT
ajst-31456	155	15	8	8	NUM
ajst-31456	155	16	am	am	NOUN
ajst-31456	155	17	)	)	PUNCT
ajst-31456	155	18	likely	likely	ADV
ajst-31456	155	19	stimulates	stimulate	VERB
ajst-31456	155	20	more	more	ADJ
ajst-31456	155	21	demand	demand	NOUN
ajst-31456	155	22	than	than	ADP
ajst-31456	155	23	the	the	DET
ajst-31456	155	24	same	same	ADJ
ajst-31456	155	25	temperature	temperature	NOUN
ajst-31456	155	26	at	at	ADP
ajst-31456	155	27	midnight	midnight	NOUN
ajst-31456	155	28	.	.	PUNCT
ajst-31456	156	1	table	table	NOUN
ajst-31456	156	2	iii	iii	PROPN
ajst-31456	156	3	humidity	humidity	NOUN
ajst-31456	156	4	binned	bin	VERB
ajst-31456	156	5	statistics	statistics	PROPN
ajst-31456	156	6	humidity	humidity	NOUN
ajst-31456	156	7	mean	mean	VERB
ajst-31456	157	1	rentals	rental	NOUN
ajst-31456	157	2	median	median	ADJ
ajst-31456	157	3	rentals	rental	NOUN
ajst-31456	157	4	records	record	VERB
ajst-31456	157	5	very	very	ADV
ajst-31456	157	6	low	low	ADJ
ajst-31456	157	7	(	(	PUNCT
ajst-31456	157	8	<	<	X
ajst-31456	157	9	28.8	28.8	NUM
ajst-31456	157	10	%	%	NOUN
ajst-31456	157	11	)	)	PUNCT
ajst-31456	157	12	275.78	275.78	NUM
ajst-31456	157	13	242.0	242.0	NUM
ajst-31456	157	14	367	367	NUM
ajst-31456	157	15	mid	mid	ADJ
ajst-31456	157	16	-	-	ADJ
ajst-31456	157	17	low	low	ADJ
ajst-31456	157	18	(	(	PUNCT
ajst-31456	157	19	28.8–57.3	28.8–57.3	NUM
ajst-31456	157	20	%	%	NOUN
ajst-31456	157	21	)	)	PUNCT
ajst-31456	158	1	242.85	242.85	NUM
ajst-31456	158	2	203.0	203.0	NUM
ajst-31456	158	3	4327	4327	NUM
ajst-31456	158	4	mid	mid	ADJ
ajst-31456	158	5	-	-	ADJ
ajst-31456	158	6	high	high	ADJ
ajst-31456	158	7	(	(	PUNCT
ajst-31456	158	8	57.4–77.7	57.4–77.7	NUM
ajst-31456	158	9	%	%	NOUN
ajst-31456	158	10	)	)	PUNCT
ajst-31456	158	11	178.91	178.91	NUM
ajst-31456	158	12	132.0	132.0	NUM
ajst-31456	158	13	3489	3489	NUM
ajst-31456	158	14	very	very	ADV
ajst-31456	158	15	high	high	ADJ
ajst-31456	158	16	(	(	PUNCT
ajst-31456	158	17	≥	≥	NOUN
ajst-31456	158	18	77.8	77.8	NUM
ajst-31456	158	19	%	%	NOUN
ajst-31456	158	20	)	)	PUNCT
ajst-31456	158	21	114.41	114.41	NUM
ajst-31456	158	22	65.0	65.0	NUM
ajst-31456	158	23	2703	2703	NUM
ajst-31456	158	24	this	this	DET
ajst-31456	158	25	interaction	interaction	NOUN
ajst-31456	158	26	was	be	AUX
ajst-31456	158	27	systematically	systematically	ADV
ajst-31456	158	28	created	create	VERB
ajst-31456	158	29	by	by	ADP
ajst-31456	158	30	performing	perform	VERB
ajst-31456	158	31	an	an	DET
ajst-31456	158	32	element	element	ADJ
ajst-31456	158	33	-	-	PUNCT
ajst-31456	158	34	wise	wise	ADJ
ajst-31456	158	35	multiplication	multiplication	NOUN
ajst-31456	158	36	between	between	ADP
ajst-31456	158	37	the	the	DET
ajst-31456	158	38	one	one	NUM
ajst-31456	158	39	-	-	PUNCT
ajst-31456	158	40	hot	hot	ADJ
ajst-31456	158	41	encoded	encode	VERB
ajst-31456	158	42	vectors	vector	NOUN
ajst-31456	158	43	of	of	ADP
ajst-31456	158	44	the	the	DET
ajst-31456	158	45	binned	bin	VERB
ajst-31456	158	46	weather	weather	NOUN
ajst-31456	158	47	features	feature	NOUN
ajst-31456	158	48	and	and	CCONJ
ajst-31456	158	49	the	the	DET
ajst-31456	158	50	one	one	NUM
ajst-31456	158	51	-	-	PUNCT
ajst-31456	158	52	hot	hot	ADJ
ajst-31456	158	53	encoded	encode	VERB
ajst-31456	158	54	hourly	hourly	ADJ
ajst-31456	158	55	features	feature	NOUN
ajst-31456	158	56	.	.	PUNCT
ajst-31456	159	1	for	for	ADP
ajst-31456	159	2	an	an	DET
ajst-31456	159	3	interaction	interaction	NOUN
ajst-31456	159	4	between	between	ADP
ajst-31456	159	5	the	the	DET
ajst-31456	159	6	k	k	PROPN
ajst-31456	159	7	-	-	PUNCT
ajst-31456	159	8	th	th	VERB
ajst-31456	159	9	temperature	temperature	NOUN
ajst-31456	159	10	category	category	NOUN
ajst-31456	159	11	and	and	CCONJ
ajst-31456	159	12	the	the	DET
ajst-31456	159	13	j	j	PROPN
ajst-31456	159	14	-	-	PUNCT
ajst-31456	159	15	th	th	NUM
ajst-31456	159	16	hour	hour	NOUN
ajst-31456	159	17	,	,	PUNCT
ajst-31456	159	18	the	the	DET
ajst-31456	159	19	resulting	result	VERB
ajst-31456	159	20	feature	feature	NOUN
ajst-31456	159	21	is	be	AUX
ajst-31456	159	22	defined	define	VERB
ajst-31456	159	23	as	as	ADP
ajst-31456	159	24	:	:	PUNCT
ajst-31456	159	25	finteract	finteract	NOUN
ajst-31456	159	26	temp(k	temp(k	PROPN
ajst-31456	159	27	,	,	PUNCT
ajst-31456	159	28	j	j	NOUN
ajst-31456	159	29	)	)	PUNCT
ajst-31456	160	1	=	=	VERB
ajst-31456	160	2	itemp	itemp	NOUN
ajst-31456	161	1	k	k	X
ajst-31456	161	2	×	×	PROPN
ajst-31456	161	3	ihour	ihour	ADJ
ajst-31456	161	4	j	j	PROPN
ajst-31456	161	5	(	(	PUNCT
ajst-31456	161	6	5	5	NUM
ajst-31456	161	7	)	)	PUNCT
ajst-31456	161	8	where	where	SCONJ
ajst-31456	161	9	itemp	itemp	NOUN
ajst-31456	161	10	k	k	PROPN
ajst-31456	161	11	and	and	CCONJ
ajst-31456	161	12	ihour	ihour	PROPN
ajst-31456	161	13	j	j	PROPN
ajst-31456	161	14	are	be	AUX
ajst-31456	161	15	the	the	DET
ajst-31456	161	16	binary	binary	ADJ
ajst-31456	161	17	indicator	indicator	NOUN
ajst-31456	161	18	variables	variable	NOUN
ajst-31456	161	19	for	for	ADP
ajst-31456	161	20	the	the	DET
ajst-31456	161	21	respective	respective	ADJ
ajst-31456	161	22	categories	category	NOUN
ajst-31456	161	23	.	.	PUNCT
ajst-31456	162	1	a	a	DET
ajst-31456	162	2	similar	similar	ADJ
ajst-31456	162	3	logic	logic	NOUN
ajst-31456	162	4	was	be	AUX
ajst-31456	162	5	applied	apply	VERB
ajst-31456	162	6	to	to	PART
ajst-31456	162	7	create	create	VERB
ajst-31456	162	8	interactions	interaction	NOUN
ajst-31456	162	9	between	between	ADP
ajst-31456	162	10	humidity	humidity	NOUN
ajst-31456	162	11	bins	bin	NOUN
ajst-31456	162	12	and	and	CCONJ
ajst-31456	162	13	hours	hour	NOUN
ajst-31456	162	14	.	.	PUNCT
ajst-31456	163	1	this	this	DET
ajst-31456	163	2	data	data	NOUN
ajst-31456	163	3	-	-	PUNCT
ajst-31456	163	4	driven	drive	VERB
ajst-31456	163	5	approach	approach	NOUN
ajst-31456	163	6	automatically	automatically	ADV
ajst-31456	163	7	generated	generate	VERB
ajst-31456	163	8	a	a	DET
ajst-31456	163	9	total	total	NOUN
ajst-31456	163	10	of	of	ADP
ajst-31456	163	11	168	168	NUM
ajst-31456	163	12	new	new	ADJ
ajst-31456	163	13	interaction	interaction	NOUN
ajst-31456	163	14	features	feature	NOUN
ajst-31456	163	15	.	.	PUNCT
ajst-31456	164	1	these	these	DET
ajst-31456	164	2	features	feature	NOUN
ajst-31456	164	3	enable	enable	VERB
ajst-31456	164	4	the	the	DET
ajst-31456	164	5	model	model	NOUN
ajst-31456	164	6	to	to	PART
ajst-31456	164	7	learn	learn	VERB
ajst-31456	164	8	context	context	NOUN
ajst-31456	164	9	-	-	PUNCT
ajst-31456	164	10	dependent	dependent	ADJ
ajst-31456	164	11	patterns	pattern	NOUN
ajst-31456	164	12	,	,	PUNCT
ajst-31456	164	13	significantly	significantly	ADV
ajst-31456	164	14	enhancing	enhance	VERB
ajst-31456	164	15	its	its	PRON
ajst-31456	164	16	predictive	predictive	ADJ
ajst-31456	164	17	power	power	NOUN
ajst-31456	164	18	compared	compare	VERB
ajst-31456	164	19	to	to	ADP
ajst-31456	164	20	using	use	VERB
ajst-31456	164	21	the	the	DET
ajst-31456	164	22	base	base	NOUN
ajst-31456	164	23	features	feature	NOUN
ajst-31456	164	24	alone	alone	ADV
ajst-31456	164	25	.	.	PUNCT
ajst-31456	165	1	after	after	ADP
ajst-31456	165	2	completing	complete	VERB
ajst-31456	165	3	the	the	DET
ajst-31456	165	4	conversion	conversion	NOUN
ajst-31456	165	5	and	and	CCONJ
ajst-31456	165	6	encoding	encoding	NOUN
ajst-31456	165	7	of	of	ADP
ajst-31456	165	8	all	all	DET
ajst-31456	165	9	fea	fea	PROPN
ajst-31456	165	10	tures	ture	NOUN
ajst-31456	165	11	,	,	PUNCT
ajst-31456	165	12	in	in	ADP
ajst-31456	165	13	order	order	NOUN
ajst-31456	165	14	to	to	PART
ajst-31456	165	15	eliminate	eliminate	VERB
ajst-31456	165	16	the	the	DET
ajst-31456	165	17	adverse	adverse	ADJ
ajst-31456	165	18	effects	effect	NOUN
ajst-31456	165	19	that	that	PRON
ajst-31456	165	20	may	may	AUX
ajst-31456	165	21	arise	arise	VERB
ajst-31456	165	22	from	from	ADP
ajst-31456	165	23	differences	difference	NOUN
ajst-31456	165	24	in	in	ADP
ajst-31456	165	25	intrinsic	intrinsic	ADJ
ajst-31456	165	26	dimensions	dimension	NOUN
ajst-31456	165	27	and	and	CCONJ
ajst-31456	165	28	numerical	numerical	ADJ
ajst-31456	165	29	ranges	range	NOUN
ajst-31456	165	30	between	between	ADP
ajst-31456	165	31	different	different	ADJ
ajst-31456	165	32	numerical	numerical	ADJ
ajst-31456	165	33	input	input	NOUN
ajst-31456	165	34	features	feature	NOUN
ajst-31456	165	35	on	on	ADP
ajst-31456	165	36	model	model	NOUN
ajst-31456	165	37	training	training	NOUN
ajst-31456	165	38	,	,	PUNCT
ajst-31456	165	39	this	this	DET
ajst-31456	165	40	paper	paper	NOUN
ajst-31456	165	41	standardized	standardize	VERB
ajst-31456	165	42	them	they	PRON
ajst-31456	165	43	using	use	VERB
ajst-31456	165	44	z	z	NOUN
ajst-31456	165	45	-	-	PUNCT
ajst-31456	165	46	score	score	NOUN
ajst-31456	165	47	.	.	PUNCT
ajst-31456	166	1	the	the	DET
ajst-31456	166	2	conversion	conversion	NOUN
ajst-31456	166	3	formula	formula	NOUN
ajst-31456	166	4	is	be	AUX
ajst-31456	166	5	as	as	SCONJ
ajst-31456	166	6	follows	follow	VERB
ajst-31456	166	7	:	:	PUNCT
ajst-31456	166	8	xstd	xstd	NOUN
ajst-31456	166	9	=	=	SYM
ajst-31456	166	10	  	  	SPACE
ajst-31456	166	11	x	x	NOUN
ajst-31456	166	12	 	 	SPACE
ajst-31456	166	13	−	−	PROPN
ajst-31456	166	14	µtrain	µtrain	CCONJ
ajst-31456	166	15	σtrain	σtrain	NOUN
ajst-31456	166	16	(	(	PUNCT
ajst-31456	166	17	6	6	NUM
ajst-31456	166	18	)	)	PUNCT
ajst-31456	166	19	among	among	ADP
ajst-31456	166	20	them	they	PRON
ajst-31456	166	21	,	,	PUNCT
ajst-31456	166	22	xis	xis	PROPN
ajst-31456	166	23	the	the	DET
ajst-31456	166	24	original	original	ADJ
ajst-31456	166	25	feature	feature	NOUN
ajst-31456	166	26	value	value	NOUN
ajst-31456	166	27	,	,	PUNCT
ajst-31456	166	28	while	while	SCONJ
ajst-31456	166	29	µtrain	µtrain	CCONJ
ajst-31456	166	30	and	and	CCONJ
ajst-31456	166	31	σtrain	σtrain	NOUN
ajst-31456	166	32	are	be	AUX
ajst-31456	166	33	the	the	DET
ajst-31456	166	34	mean	mean	ADJ
ajst-31456	166	35	and	and	CCONJ
ajst-31456	166	36	standard	standard	ADJ
ajst-31456	166	37	deviation	deviation	NOUN
ajst-31456	166	38	of	of	ADP
ajst-31456	166	39	the	the	DET
ajst-31456	166	40	feature	feature	NOUN
ajst-31456	166	41	calculated	calculate	VERB
ajst-31456	166	42	on	on	ADP
ajst-31456	166	43	the	the	DET
ajst-31456	166	44	training	training	NOUN
ajst-31456	166	45	set	set	NOUN
ajst-31456	166	46	,	,	PUNCT
ajst-31456	166	47	respectively	respectively	ADV
ajst-31456	166	48	56	56	NUM
ajst-31456	166	49	figure	figure	NOUN
ajst-31456	166	50	5	5	NUM
ajst-31456	166	51	.	.	PUNCT
ajst-31456	166	52	sensory	sensory	ADJ
ajst-31456	166	53	temperature	temperature	NOUN
ajst-31456	166	54	and	and	CCONJ
ajst-31456	166	55	humidity	humidity	NOUN
ajst-31456	166	56	box	box	NOUN
ajst-31456	166	57	division	division	NOUN
ajst-31456	166	58	results	result	VERB
ajst-31456	166	59	.	.	PUNCT
ajst-31456	167	1	c.	c.	NOUN
ajst-31456	167	2	module	module	NOUN
ajst-31456	167	3	2	2	NUM
ajst-31456	167	4	:	:	PUNCT
ajst-31456	167	5	feature	feature	NOUN
ajst-31456	167	6	selection	selection	NOUN
ajst-31456	167	7	after	after	ADP
ajst-31456	167	8	preprocessing	preprocesse	VERB
ajst-31456	167	9	and	and	CCONJ
ajst-31456	167	10	feature	feature	NOUN
ajst-31456	167	11	engineering	engineering	NOUN
ajst-31456	167	12	,	,	PUNCT
ajst-31456	167	13	the	the	DET
ajst-31456	167	14	dimension	dimension	NOUN
ajst-31456	167	15	of	of	ADP
ajst-31456	167	16	the	the	DET
ajst-31456	167	17	new	new	ADJ
ajst-31456	167	18	feature	feature	NOUN
ajst-31456	167	19	set	set	VERB
ajst-31456	167	20	significantly	significantly	ADV
ajst-31456	167	21	increased	increase	VERB
ajst-31456	167	22	to	to	ADP
ajst-31456	167	23	232	232	NUM
ajst-31456	167	24	.	.	PUNCT
ajst-31456	168	1	although	although	SCONJ
ajst-31456	168	2	high	high	ADJ
ajst-31456	168	3	-	-	PUNCT
ajst-31456	168	4	dimensional	dimensional	ADJ
ajst-31456	168	5	feature	feature	NOUN
ajst-31456	168	6	spaces	space	NOUN
ajst-31456	168	7	may	may	AUX
ajst-31456	168	8	contain	contain	VERB
ajst-31456	168	9	richer	rich	ADJ
ajst-31456	168	10	information	information	NOUN
ajst-31456	168	11	,	,	PUNCT
ajst-31456	168	12	they	they	PRON
ajst-31456	168	13	can	can	AUX
ajst-31456	168	14	also	also	ADV
ajst-31456	168	15	introduce	introduce	VERB
ajst-31456	168	16	noise	noise	NOUN
ajst-31456	168	17	,	,	PUNCT
ajst-31456	168	18	increase	increase	VERB
ajst-31456	168	19	the	the	DET
ajst-31456	168	20	computational	computational	ADJ
ajst-31456	168	21	complexity	complexity	NOUN
ajst-31456	168	22	of	of	ADP
ajst-31456	168	23	model	model	NOUN
ajst-31456	168	24	training	training	NOUN
ajst-31456	168	25	,	,	PUNCT
ajst-31456	168	26	and	and	CCONJ
ajst-31456	168	27	increase	increase	VERB
ajst-31456	168	28	the	the	DET
ajst-31456	168	29	risk	risk	NOUN
ajst-31456	168	30	of	of	ADP
ajst-31456	168	31	overfitting	overfitte	VERB
ajst-31456	168	32	.	.	PUNCT
ajst-31456	169	1	therefore	therefore	ADV
ajst-31456	169	2	,	,	PUNCT
ajst-31456	169	3	it	it	PRON
ajst-31456	169	4	is	be	AUX
ajst-31456	169	5	necessary	necessary	ADJ
ajst-31456	169	6	to	to	PART
ajst-31456	169	7	perform	perform	VERB
ajst-31456	169	8	feature	feature	NOUN
ajst-31456	169	9	screening	screening	NOUN
ajst-31456	169	10	.	.	PUNCT
ajst-31456	170	1	this	this	DET
ajst-31456	170	2	article	article	NOUN
ajst-31456	170	3	uses	use	VERB
ajst-31456	170	4	the	the	DET
ajst-31456	170	5	feature	feature	NOUN
ajst-31456	170	6	importance	importance	NOUN
ajst-31456	170	7	evaluation	evaluation	NOUN
ajst-31456	170	8	function	function	NOUN
ajst-31456	170	9	built	build	VERB
ajst-31456	170	10	into	into	ADP
ajst-31456	170	11	the	the	DET
ajst-31456	170	12	xgboost	xgboost	PROPN
ajst-31456	170	13	model	model	NOUN
ajst-31456	170	14	for	for	ADP
ajst-31456	170	15	feature	feature	NOUN
ajst-31456	170	16	selection	selection	NOUN
ajst-31456	170	17	.	.	PUNCT
ajst-31456	171	1	we	we	PRON
ajst-31456	171	2	chose	choose	VERB
ajst-31456	171	3	gain	gain	NOUN
ajst-31456	171	4	as	as	ADP
ajst-31456	171	5	the	the	DET
ajst-31456	171	6	core	core	NOUN
ajst-31456	171	7	evaluation	evaluation	NOUN
ajst-31456	171	8	metric	metric	NOUN
ajst-31456	171	9	,	,	PUNCT
ajst-31456	171	10	which	which	PRON
ajst-31456	171	11	measures	measure	VERB
ajst-31456	171	12	the	the	DET
ajst-31456	171	13	reduction	reduction	NOUN
ajst-31456	171	14	of	of	ADP
ajst-31456	171	15	the	the	DET
ajst-31456	171	16	objective	objective	ADJ
ajst-31456	171	17	function	function	NOUN
ajst-31456	171	18	when	when	SCONJ
ajst-31456	171	19	each	each	DET
ajst-31456	171	20	feature	feature	NOUN
ajst-31456	171	21	is	be	AUX
ajst-31456	171	22	used	use	VERB
ajst-31456	171	23	as	as	ADP
ajst-31456	171	24	a	a	DET
ajst-31456	171	25	splitting	splitting	NOUN
ajst-31456	171	26	node	node	NOUN
ajst-31456	171	27	in	in	ADP
ajst-31456	171	28	all	all	DET
ajst-31456	171	29	decision	decision	NOUN
ajst-31456	171	30	trees	tree	NOUN
ajst-31456	171	31	of	of	ADP
ajst-31456	171	32	the	the	DET
ajst-31456	171	33	model	model	NOUN
ajst-31456	171	34	.	.	PUNCT
ajst-31456	172	1	after	after	ADP
ajst-31456	172	2	evaluating	evaluate	VERB
ajst-31456	172	3	all	all	DET
ajst-31456	172	4	232	232	NUM
ajst-31456	172	5	features	feature	NOUN
ajst-31456	172	6	,	,	PUNCT
ajst-31456	172	7	we	we	PRON
ajst-31456	172	8	found	find	VERB
ajst-31456	172	9	that	that	SCONJ
ajst-31456	172	10	their	their	PRON
ajst-31456	172	11	i	i	NOUN
ajst-31456	172	12	m	m	VERB
ajst-31456	172	13	portance	portance	NOUN
ajst-31456	172	14	scores	score	NOUN
ajst-31456	172	15	exhibited	exhibit	VERB
ajst-31456	172	16	a	a	DET
ajst-31456	172	17	typical	typical	ADJ
ajst-31456	172	18	long	long	ADJ
ajst-31456	172	19	tail	tail	NOUN
ajst-31456	172	20	distribution	distribution	NOUN
ajst-31456	172	21	:	:	PUNCT
ajst-31456	172	22	a	a	DET
ajst-31456	172	23	few	few	ADJ
ajst-31456	172	24	features	feature	NOUN
ajst-31456	172	25	contributed	contribute	VERB
ajst-31456	172	26	the	the	DET
ajst-31456	172	27	vast	vast	ADJ
ajst-31456	172	28	majority	majority	NOUN
ajst-31456	172	29	of	of	ADP
ajst-31456	172	30	predictive	predictive	ADJ
ajst-31456	172	31	power	power	NOUN
ajst-31456	172	32	,	,	PUNCT
ajst-31456	172	33	while	while	SCONJ
ajst-31456	172	34	the	the	DET
ajst-31456	172	35	contribution	contribution	NOUN
ajst-31456	172	36	of	of	ADP
ajst-31456	172	37	a	a	DET
ajst-31456	172	38	large	large	ADJ
ajst-31456	172	39	number	number	NOUN
ajst-31456	172	40	of	of	ADP
ajst-31456	172	41	features	feature	NOUN
ajst-31456	172	42	was	be	AUX
ajst-31456	172	43	negligible	negligible	ADJ
ajst-31456	172	44	.	.	PUNCT
ajst-31456	173	1	as	as	SCONJ
ajst-31456	173	2	shown	show	VERB
ajst-31456	173	3	in	in	ADP
ajst-31456	173	4	table	table	NOUN
ajst-31456	173	5	iv	iv	NOUN
ajst-31456	173	6	,	,	PUNCT
ajst-31456	173	7	some	some	DET
ajst-31456	173	8	interaction	interaction	NOUN
ajst-31456	173	9	features	feature	NOUN
ajst-31456	173	10	and	and	CCONJ
ajst-31456	173	11	temporal	temporal	ADJ
ajst-31456	173	12	features	feature	NOUN
ajst-31456	173	13	occupy	occupy	VERB
ajst-31456	173	14	the	the	DET
ajst-31456	173	15	top	top	ADJ
ajst-31456	173	16	positions	position	NOUN
ajst-31456	173	17	in	in	ADP
ajst-31456	173	18	importance	importance	NOUN
ajst-31456	173	19	ranking	ranking	NOUN
ajst-31456	173	20	.	.	PUNCT
ajst-31456	174	1	specifically	specifically	ADV
ajst-31456	174	2	,	,	PUNCT
ajst-31456	174	3	we	we	PRON
ajst-31456	174	4	observed	observe	VERB
ajst-31456	174	5	that	that	SCONJ
ajst-31456	174	6	80	80	NUM
ajst-31456	174	7	features	feature	NOUN
ajst-31456	174	8	had	have	VERB
ajst-31456	174	9	an	an	DET
ajst-31456	174	10	importance	importance	NOUN
ajst-31456	174	11	score	score	NOUN
ajst-31456	174	12	of	of	ADP
ajst-31456	174	13	0	0	NUM
ajst-31456	174	14	.	.	PUNCT
ajst-31456	175	1	based	base	VERB
ajst-31456	175	2	on	on	ADP
ajst-31456	175	3	the	the	DET
ajst-31456	175	4	above	above	ADJ
ajst-31456	175	5	analysis	analysis	NOUN
ajst-31456	175	6	,	,	PUNCT
ajst-31456	175	7	in	in	ADP
ajst-31456	175	8	order	order	NOUN
ajst-31456	175	9	to	to	PART
ajst-31456	175	10	strike	strike	VERB
ajst-31456	175	11	a	a	DET
ajst-31456	175	12	balance	balance	NOUN
ajst-31456	175	13	between	between	ADP
ajst-31456	175	14	retaining	retain	VERB
ajst-31456	175	15	key	key	ADJ
ajst-31456	175	16	information	information	NOUN
ajst-31456	175	17	and	and	CCONJ
ajst-31456	175	18	improving	improve	VERB
ajst-31456	175	19	model	model	NOUN
ajst-31456	175	20	efficiency	efficiency	NOUN
ajst-31456	175	21	,	,	PUNCT
ajst-31456	175	22	we	we	PRON
ajst-31456	175	23	ultimately	ultimately	ADV
ajst-31456	175	24	chose	choose	VERB
ajst-31456	175	25	to	to	PART
ajst-31456	175	26	retain	retain	VERB
ajst-31456	175	27	the	the	DET
ajst-31456	175	28	top	top	ADJ
ajst-31456	175	29	152	152	NUM
ajst-31456	175	30	most	most	ADV
ajst-31456	175	31	important	important	ADJ
ajst-31456	175	32	features	feature	NOUN
ajst-31456	175	33	for	for	ADP
ajst-31456	175	34	subsequent	subsequent	ADJ
ajst-31456	175	35	model	model	NOUN
ajst-31456	175	36	training	training	NOUN
ajst-31456	175	37	.	.	PUNCT
ajst-31456	176	1	table	table	NOUN
ajst-31456	176	2	iv	iv	NUM
ajst-31456	176	3	feature	feature	NOUN
ajst-31456	176	4	importance	importance	NOUN
ajst-31456	176	5	ranking	rank	VERB
ajst-31456	176	6	(	(	PUNCT
ajst-31456	176	7	partial	partial	ADJ
ajst-31456	176	8	example	example	NOUN
ajst-31456	176	9	top	top	ADJ
ajst-31456	176	10	10	10	NUM
ajst-31456	176	11	)	)	PUNCT
ajst-31456	176	12	ranking	rank	VERB
ajst-31456	176	13	feature	feature	NOUN
ajst-31456	176	14	names	name	NOUN
ajst-31456	176	15	importance	importance	NOUN
ajst-31456	176	16	(	(	PUNCT
ajst-31456	176	17	gain	gain	NOUN
ajst-31456	176	18	)	)	PUNCT
ajst-31456	176	19	1	1	NUM
ajst-31456	176	20	atemp	atemp	NOUN
ajst-31456	176	21	interval	interval	NOUN
ajst-31456	176	22	atemp	atemp	NOUN
ajst-31456	176	23	moderate	moderate	ADJ
ajst-31456	176	24	x	x	SYM
ajst-31456	176	25	hour	hour	NOUN
ajst-31456	176	26	1	1	NUM
ajst-31456	176	27	0.246892	0.246892	NUM
ajst-31456	176	28	2	2	NUM
ajst-31456	176	29	atemp	atemp	NOUN
ajst-31456	176	30	interval	interval	NOUN
ajst-31456	176	31	atemp	atemp	NOUN
ajst-31456	176	32	moderate	moderate	ADJ
ajst-31456	176	33	x	x	SYM
ajst-31456	176	34	hour	hour	NOUN
ajst-31456	176	35	4	4	NUM
ajst-31456	176	36	0.095076	0.095076	NUM
ajst-31456	176	37	3	3	NUM
ajst-31456	176	38	hour	hour	NOUN
ajst-31456	176	39	4	4	NUM
ajst-31456	176	40	0.083281	0.083281	NUM
ajst-31456	176	41	4	4	NUM
ajst-31456	176	42	hour	hour	NOUN
ajst-31456	176	43	3	3	NUM
ajst-31456	176	44	0.059399	0.059399	NUM
ajst-31456	176	45	5	5	NUM
ajst-31456	176	46	atemp	atemp	NOUN
ajst-31456	176	47	interval	interval	NOUN
ajst-31456	176	48	atemp	atemp	NOUN
ajst-31456	176	49	moderate	moderate	ADJ
ajst-31456	176	50	x	x	SYM
ajst-31456	176	51	hour	hour	NOUN
ajst-31456	176	52	3	3	NUM
ajst-31456	176	53	0.055435	0.055435	NUM
ajst-31456	176	54	6	6	NUM
ajst-31456	176	55	hour	hour	NOUN
ajst-31456	176	56	5	5	NUM
ajst-31456	176	57	0.048859	0.048859	NUM
ajst-31456	176	58	7	7	NUM
ajst-31456	176	59	hour	hour	NOUN
ajst-31456	176	60	2	2	NUM
ajst-31456	176	61	0.047714	0.047714	NUM
ajst-31456	176	62	8	8	NUM
ajst-31456	176	63	atemp	atemp	NOUN
ajst-31456	176	64	interval	interval	NOUN
ajst-31456	176	65	atemp	atemp	NOUN
ajst-31456	176	66	low	low	ADJ
ajst-31456	176	67	x	x	NOUN
ajst-31456	176	68	hour	hour	NOUN
ajst-31456	176	69	8	8	NUM
ajst-31456	176	70	0.039121	0.039121	NUM
ajst-31456	176	71	9	9	NUM
ajst-31456	176	72	hour	hour	NOUN
ajst-31456	176	73	1	1	NUM
ajst-31456	176	74	0.034995	0.034995	NUM
ajst-31456	176	75	10	10	NUM
ajst-31456	176	76	hour	hour	NOUN
ajst-31456	176	77	0	0	NUM
ajst-31456	176	78	0.016326	0.016326	NUM
ajst-31456	176	79	d.	d.	NOUN
ajst-31456	176	80	module	module	NOUN
ajst-31456	176	81	3	3	NUM
ajst-31456	176	82	:	:	PUNCT
ajst-31456	176	83	model	model	NOUN
ajst-31456	176	84	building	build	VERB
ajst-31456	176	85	the	the	DET
ajst-31456	176	86	construction	construction	NOUN
ajst-31456	176	87	,	,	PUNCT
ajst-31456	176	88	training	training	NOUN
ajst-31456	176	89	,	,	PUNCT
ajst-31456	176	90	and	and	CCONJ
ajst-31456	176	91	evaluation	evaluation	NOUN
ajst-31456	176	92	of	of	ADP
ajst-31456	176	93	all	all	DET
ajst-31456	176	94	machine	machine	NOUN
ajst-31456	176	95	learning	learning	NOUN
ajst-31456	176	96	models	model	NOUN
ajst-31456	176	97	in	in	ADP
ajst-31456	176	98	this	this	DET
ajst-31456	176	99	paper	paper	NOUN
ajst-31456	176	100	are	be	AUX
ajst-31456	176	101	based	base	VERB
ajst-31456	176	102	on	on	ADP
ajst-31456	176	103	the	the	DET
ajst-31456	176	104	python	python	NOUN
ajst-31456	176	105	pro	pro	X
ajst-31456	176	106	gramming	gramme	VERB
ajst-31456	176	107	language	language	NOUN
ajst-31456	176	108	and	and	CCONJ
ajst-31456	176	109	its	its	PRON
ajst-31456	176	110	powerful	powerful	ADJ
ajst-31456	176	111	scientific	scientific	ADJ
ajst-31456	176	112	computing	compute	VERB
ajst-31456	176	113	ecosystem	ecosystem	NOUN
ajst-31456	176	114	.	.	PUNCT
ajst-31456	177	1	specifically	specifically	ADV
ajst-31456	177	2	,	,	PUNCT
ajst-31456	177	3	it	it	PRON
ajst-31456	177	4	primarily	primarily	ADV
ajst-31456	177	5	relies	rely	VERB
ajst-31456	177	6	on	on	ADP
ajst-31456	177	7	scikit	scikit	NOUN
ajst-31456	177	8	-	-	PUNCT
ajst-31456	177	9	learn	learn	VERB
ajst-31456	177	10	,	,	PUNCT
ajst-31456	177	11	a	a	DET
ajst-31456	177	12	widely	widely	ADV
ajst-31456	177	13	used	use	VERB
ajst-31456	177	14	machine	machine	NOUN
ajst-31456	177	15	learning	learn	VERB
ajst-31456	177	16	library	library	NOUN
ajst-31456	177	17	.	.	PUNCT
ajst-31456	178	1	the	the	DET
ajst-31456	178	2	feature	feature	NOUN
ajst-31456	178	3	set	set	VERB
ajst-31456	178	4	for	for	ADP
ajst-31456	178	5	model	model	NOUN
ajst-31456	178	6	construction	construction	NOUN
ajst-31456	178	7	,	,	PUNCT
ajst-31456	178	8	xtrain	xtrain	PROPN
ajst-31456	178	9	,	,	PUNCT
ajst-31456	178	10	consists	consist	VERB
ajst-31456	178	11	of	of	ADP
ajst-31456	178	12	152	152	NUM
ajst-31456	178	13	feature	feature	NOUN
ajst-31456	178	14	columns	column	NOUN
ajst-31456	178	15	determined	determine	VERB
ajst-31456	178	16	after	after	ADP
ajst-31456	178	17	feature	feature	NOUN
ajst-31456	178	18	selection	selection	NOUN
ajst-31456	178	19	,	,	PUNCT
ajst-31456	178	20	with	with	ADP
ajst-31456	178	21	a	a	DET
ajst-31456	178	22	dimension	dimension	NOUN
ajst-31456	178	23	of	of	ADP
ajst-31456	178	24	m×	m×	PROPN
ajst-31456	178	25	152	152	NUM
ajst-31456	178	26	,	,	PUNCT
ajst-31456	178	27	where	where	SCONJ
ajst-31456	178	28	m	m	VERB
ajst-31456	178	29	  	  	SPACE
ajst-31456	178	30	is	be	AUX
ajst-31456	178	31	the	the	DET
ajst-31456	178	32	number	number	NOUN
ajst-31456	178	33	of	of	ADP
ajst-31456	178	34	training	training	NOUN
ajst-31456	178	35	samples	sample	NOUN
ajst-31456	178	36	,	,	PUNCT
ajst-31456	178	37	10886	10886	NUM
ajst-31456	178	38	.	.	PUNCT
ajst-31456	179	1	the	the	DET
ajst-31456	179	2	target	target	NOUN
ajst-31456	179	3	variable	variable	NOUN
ajst-31456	179	4	,	,	PUNCT
ajst-31456	179	5	ytrain_log	ytrain_log	PROPN
ajst-31456	179	6	,	,	PUNCT
ajst-31456	179	7	is	be	AUX
ajst-31456	179	8	the	the	DET
ajst-31456	179	9	log	log	NOUN
ajst-31456	179	10	-	-	PUNCT
ajst-31456	179	11	transformed	transform	VERB
ajst-31456	179	12	rental	rental	ADJ
ajst-31456	179	13	count	count	NOUN
ajst-31456	179	14	,	,	PUNCT
ajst-31456	179	15	with	with	ADP
ajst-31456	179	16	a	a	DET
ajst-31456	179	17	dimension	dimension	NOUN
ajst-31456	179	18	of	of	ADP
ajst-31456	179	19	m	m	NOUN
ajst-31456	179	20	  	  	SPACE
ajst-31456	179	21	×	×	NOUN
ajst-31456	179	22	1	1	NUM
ajst-31456	179	23	.	.	PUNCT
ajst-31456	180	1	for	for	ADP
ajst-31456	180	2	the	the	DET
ajst-31456	180	3	subsequent	subsequent	ADJ
ajst-31456	180	4	validation	validation	NOUN
ajst-31456	180	5	of	of	ADP
ajst-31456	180	6	the	the	DET
ajst-31456	180	7	model	model	NOUN
ajst-31456	180	8	’s	’s	PART
ajst-31456	180	9	generalization	generalization	NOUN
ajst-31456	180	10	ability	ability	NOUN
ajst-31456	180	11	,	,	PUNCT
ajst-31456	180	12	a	a	DET
ajst-31456	180	13	test	test	NOUN
ajst-31456	180	14	set	set	VERB
ajst-31456	180	15	57	57	NUM
ajst-31456	180	16	feature	feature	NOUN
ajst-31456	180	17	matrix	matrix	NOUN
ajst-31456	180	18	,	,	PUNCT
ajst-31456	180	19	xtest	xtest	PROPN
ajst-31456	180	20	,	,	PUNCT
ajst-31456	180	21	which	which	PRON
ajst-31456	180	22	has	have	AUX
ajst-31456	180	23	undergone	undergo	VERB
ajst-31456	180	24	consistent	consistent	ADJ
ajst-31456	180	25	processing	processing	NOUN
ajst-31456	180	26	and	and	CCONJ
ajst-31456	180	27	feature	feature	NOUN
ajst-31456	180	28	selection	selection	NOUN
ajst-31456	180	29	,	,	PUNCT
ajst-31456	180	30	was	be	AUX
ajst-31456	180	31	also	also	ADV
ajst-31456	180	32	prepared	prepare	VERB
ajst-31456	180	33	,	,	PUNCT
ajst-31456	180	34	with	with	ADP
ajst-31456	180	35	a	a	DET
ajst-31456	180	36	dimension	dimension	NOUN
ajst-31456	180	37	of	of	ADP
ajst-31456	180	38	6493	6493	NUM
ajst-31456	180	39	×	×	NOUN
ajst-31456	180	40	152	152	NUM
ajst-31456	180	41	.	.	PUNCT
ajst-31456	181	1	to	to	PART
ajst-31456	181	2	comprehensively	comprehensively	ADV
ajst-31456	181	3	explore	explore	VERB
ajst-31456	181	4	the	the	DET
ajst-31456	181	5	potential	potential	NOUN
ajst-31456	181	6	of	of	ADP
ajst-31456	181	7	various	various	ADJ
ajst-31456	181	8	algorithms	algorithm	NOUN
ajst-31456	181	9	for	for	ADP
ajst-31456	181	10	this	this	DET
ajst-31456	181	11	bike	bike	NOUN
ajst-31456	181	12	-	-	PUNCT
ajst-31456	181	13	sharing	share	VERB
ajst-31456	181	14	demand	demand	NOUN
ajst-31456	181	15	prediction	prediction	NOUN
ajst-31456	181	16	task	task	NOUN
ajst-31456	181	17	,	,	PUNCT
ajst-31456	181	18	this	this	DET
ajst-31456	181	19	study	study	NOUN
ajst-31456	181	20	selected	select	VERB
ajst-31456	181	21	a	a	DET
ajst-31456	181	22	range	range	NOUN
ajst-31456	181	23	of	of	ADP
ajst-31456	181	24	mainstream	mainstream	ADJ
ajst-31456	181	25	regression	regression	NOUN
ajst-31456	181	26	algorithms	algorithm	NOUN
ajst-31456	181	27	,	,	PUNCT
ajst-31456	181	28	including	include	VERB
ajst-31456	181	29	linear	linear	NOUN
ajst-31456	181	30	models	model	NOUN
ajst-31456	181	31	and	and	CCONJ
ajst-31456	181	32	tree	tree	NOUN
ajst-31456	181	33	-	-	PUNCT
ajst-31456	181	34	based	base	VERB
ajst-31456	181	35	ensemble	ensemble	ADJ
ajst-31456	181	36	models	model	NOUN
ajst-31456	181	37	,	,	PUNCT
ajst-31456	181	38	to	to	PART
ajst-31456	181	39	construct	construct	VERB
ajst-31456	181	40	a	a	DET
ajst-31456	181	41	suite	suite	NOUN
ajst-31456	181	42	of	of	ADP
ajst-31456	181	43	predictive	predictive	ADJ
ajst-31456	181	44	models	model	NOUN
ajst-31456	181	45	,	,	PUNCT
ajst-31456	181	46	as	as	SCONJ
ajst-31456	181	47	shown	show	VERB
ajst-31456	181	48	in	in	ADP
ajst-31456	181	49	table	table	NOUN
ajst-31456	181	50	v.	v.	ADP
ajst-31456	181	51	all	all	DET
ajst-31456	181	52	non	non	ADJ
ajst-31456	181	53	-	-	ADJ
ajst-31456	181	54	deterministic	deterministic	ADJ
ajst-31456	181	55	models	model	NOUN
ajst-31456	181	56	were	be	AUX
ajst-31456	181	57	configured	configure	VERB
ajst-31456	181	58	with	with	ADP
ajst-31456	181	59	a	a	DET
ajst-31456	181	60	fixed	fix	VERB
ajst-31456	181	61	random	random	ADJ
ajst-31456	181	62	seed	seed	NOUN
ajst-31456	181	63	(	(	PUNCT
ajst-31456	181	64	random	random	ADJ
ajst-31456	181	65	state=42	state=42	NOUN
ajst-31456	181	66	)	)	PUNCT
ajst-31456	181	67	to	to	PART
ajst-31456	181	68	ensure	ensure	VERB
ajst-31456	181	69	the	the	DET
ajst-31456	181	70	reproducibility	reproducibility	NOUN
ajst-31456	181	71	of	of	ADP
ajst-31456	181	72	the	the	DET
ajst-31456	181	73	experimental	experimental	ADJ
ajst-31456	181	74	results	result	NOUN
ajst-31456	181	75	.	.	PUNCT
ajst-31456	182	1	table	table	NOUN
ajst-31456	182	2	v	v	ADP
ajst-31456	182	3	baseline	baseline	NOUN
ajst-31456	182	4	models	model	NOUN
ajst-31456	182	5	and	and	CCONJ
ajst-31456	182	6	their	their	PRON
ajst-31456	182	7	general	general	ADJ
ajst-31456	182	8	setup	setup	NOUN
ajst-31456	182	9	model	model	NOUN
ajst-31456	182	10	name	name	PROPN
ajst-31456	182	11	general	general	ADJ
ajst-31456	182	12	setup	setup	NOUN
ajst-31456	182	13	description	description	NOUN
ajst-31456	182	14	linear	linear	PROPN
ajst-31456	182	15	regression	regression	PROPN
ajst-31456	182	16	standard	standard	ADJ
ajst-31456	182	17	implementation	implementation	NOUN
ajst-31456	182	18	with	with	ADP
ajst-31456	182	19	no	no	DET
ajst-31456	182	20	regularization	regularization	NOUN
ajst-31456	182	21	.	.	PUNCT
ajst-31456	183	1	lasso	lasso	NOUN
ajst-31456	183	2	regularized	regularize	VERB
ajst-31456	183	3	with	with	ADP
ajst-31456	183	4	a	a	DET
ajst-31456	183	5	small	small	ADJ
ajst-31456	183	6	l1	l1	PROPN
ajst-31456	183	7	penalty	penalty	NOUN
ajst-31456	183	8	.	.	PUNCT
ajst-31456	184	1	ridge	ridge	PROPN
ajst-31456	184	2	regularized	regularize	VERB
ajst-31456	184	3	with	with	ADP
ajst-31456	184	4	a	a	DET
ajst-31456	184	5	standard	standard	ADJ
ajst-31456	184	6	l2	l2	NOUN
ajst-31456	184	7	penalty	penalty	NOUN
ajst-31456	184	8	.	.	PUNCT
ajst-31456	185	1	elastic	elastic	ADJ
ajst-31456	185	2	net	net	NOUN
ajst-31456	185	3	a	a	DET
ajst-31456	185	4	combination	combination	NOUN
ajst-31456	185	5	of	of	ADP
ajst-31456	185	6	l1	l1	PROPN
ajst-31456	185	7	and	and	CCONJ
ajst-31456	185	8	l2	l2	NOUN
ajst-31456	185	9	regularization	regularization	NOUN
ajst-31456	185	10	.	.	PUNCT
ajst-31456	186	1	decision	decision	NOUN
ajst-31456	186	2	tree	tree	NOUN
ajst-31456	186	3	a	a	DET
ajst-31456	186	4	single	single	ADJ
ajst-31456	186	5	tree	tree	NOUN
ajst-31456	186	6	model	model	NOUN
ajst-31456	186	7	with	with	ADP
ajst-31456	186	8	baseline	baseline	NOUN
ajst-31456	186	9	parameters	parameter	NOUN
ajst-31456	186	10	.	.	PUNCT
ajst-31456	187	1	random	random	ADJ
ajst-31456	187	2	forest	forest	NOUN
ajst-31456	187	3	an	an	DET
ajst-31456	187	4	ensemble	ensemble	NOUN
ajst-31456	187	5	of	of	ADP
ajst-31456	187	6	100	100	NUM
ajst-31456	187	7	trees	tree	NOUN
ajst-31456	187	8	with	with	ADP
ajst-31456	187	9	baseline	baseline	ADJ
ajst-31456	187	10	settings	setting	NOUN
ajst-31456	187	11	.	.	PUNCT
ajst-31456	188	1	xgboost	xgboost	X
ajst-31456	189	1	gradient	gradient	ADJ
ajst-31456	189	2	boosting	boost	VERB
ajst-31456	189	3	with	with	ADP
ajst-31456	189	4	baseline	baseline	NOUN
ajst-31456	189	5	learning	learning	NOUN
ajst-31456	189	6	rate	rate	NOUN
ajst-31456	189	7	and	and	CCONJ
ajst-31456	189	8	depth	depth	NOUN
ajst-31456	189	9	.	.	PUNCT
ajst-31456	190	1	lightgbm	lightgbm	ADJ
ajst-31456	190	2	gradient	gradient	NOUN
ajst-31456	190	3	boosting	boost	VERB
ajst-31456	190	4	with	with	ADP
ajst-31456	190	5	baseline	baseline	NOUN
ajst-31456	190	6	learning	learning	NOUN
ajst-31456	190	7	rate	rate	NOUN
ajst-31456	190	8	and	and	CCONJ
ajst-31456	190	9	leaves	leave	NOUN
ajst-31456	190	10	.	.	PUNCT
ajst-31456	191	1	each	each	PRON
ajst-31456	191	2	of	of	ADP
ajst-31456	191	3	the	the	DET
ajst-31456	191	4	selected	select	VERB
ajst-31456	191	5	baseline	baseline	NOUN
ajst-31456	191	6	models	model	NOUN
ajst-31456	191	7	will	will	AUX
ajst-31456	191	8	be	be	AUX
ajst-31456	191	9	trained	train	VERB
ajst-31456	191	10	on	on	ADP
ajst-31456	191	11	the	the	DET
ajst-31456	191	12	prepared	prepare	VERB
ajst-31456	191	13	training	training	NOUN
ajst-31456	191	14	data	datum	NOUN
ajst-31456	191	15	.	.	PUNCT
ajst-31456	192	1	e.	e.	PROPN
ajst-31456	192	2	experiment	experiment	PROPN
ajst-31456	192	3	1	1	NUM
ajst-31456	192	4	)	)	PUNCT
ajst-31456	192	5	comparative	comparative	ADJ
ajst-31456	192	6	experiment	experiment	NOUN
ajst-31456	192	7	:	:	PUNCT
ajst-31456	192	8	in	in	ADP
ajst-31456	192	9	order	order	NOUN
ajst-31456	192	10	to	to	PART
ajst-31456	192	11	systematically	systematically	ADV
ajst-31456	192	12	and	and	CCONJ
ajst-31456	192	13	scientifically	scientifically	ADV
ajst-31456	192	14	evaluate	evaluate	VERB
ajst-31456	192	15	the	the	DET
ajst-31456	192	16	effectiveness	effectiveness	NOUN
ajst-31456	192	17	and	and	CCONJ
ajst-31456	192	18	progressiveness	progressiveness	NOUN
ajst-31456	192	19	of	of	ADP
ajst-31456	192	20	the	the	DET
ajst-31456	192	21	shared	share	VERB
ajst-31456	192	22	bicycle	bicycle	NOUN
ajst-31456	192	23	demand	demand	NOUN
ajst-31456	192	24	forecasting	forecasting	NOUN
ajst-31456	192	25	model	model	NOUN
ajst-31456	192	26	proposed	propose	VERB
ajst-31456	192	27	in	in	ADP
ajst-31456	192	28	this	this	DET
ajst-31456	192	29	paper	paper	NOUN
ajst-31456	192	30	,	,	PUNCT
ajst-31456	192	31	this	this	DET
ajst-31456	192	32	paper	paper	NOUN
ajst-31456	192	33	designs	design	VERB
ajst-31456	192	34	a	a	DET
ajst-31456	192	35	series	series	NOUN
ajst-31456	192	36	of	of	ADP
ajst-31456	192	37	strict	strict	ADJ
ajst-31456	192	38	contrast	contrast	NOUN
ajst-31456	192	39	experiments	experiment	NOUN
ajst-31456	192	40	.	.	PUNCT
ajst-31456	193	1	fair	fair	ADJ
ajst-31456	193	2	evaluation	evaluation	NOUN
ajst-31456	193	3	principle	principle	NOUN
ajst-31456	193	4	:	:	PUNCT
ajst-31456	193	5	all	all	DET
ajst-31456	193	6	models	model	NOUN
ajst-31456	193	7	run	run	VERB
ajst-31456	193	8	on	on	ADP
ajst-31456	193	9	the	the	DET
ajst-31456	193	10	same	same	ADJ
ajst-31456	193	11	dataset	dataset	NOUN
ajst-31456	193	12	and	and	CCONJ
ajst-31456	193	13	hardware	hardware	NOUN
ajst-31456	193	14	environment	environment	NOUN
ajst-31456	193	15	.	.	PUNCT
ajst-31456	194	1	the	the	DET
ajst-31456	194	2	evaluation	evaluation	NOUN
ajst-31456	194	3	indicators	indicator	NOUN
ajst-31456	194	4	are	be	AUX
ajst-31456	194	5	uniformly	uniformly	ADV
ajst-31456	194	6	rmsle	rmsle	NOUN
ajst-31456	194	7	and	and	CCONJ
ajst-31456	194	8	r2	r2	NOUN
ajst-31456	194	9	to	to	PART
ajst-31456	194	10	ensure	ensure	VERB
ajst-31456	194	11	horizontal	horizontal	ADJ
ajst-31456	194	12	comparison	comparison	NOUN
ajst-31456	194	13	under	under	ADP
ajst-31456	194	14	the	the	DET
ajst-31456	194	15	same	same	ADJ
ajst-31456	194	16	standard	standard	NOUN
ajst-31456	194	17	.	.	PUNCT
ajst-31456	195	1	adopting	adopt	VERB
ajst-31456	195	2	rigorous	rigorous	ADJ
ajst-31456	195	3	time	time	NOUN
ajst-31456	195	4	series	series	PROPN
ajst-31456	195	5	cross	cross	VERB
ajst-31456	195	6	validation	validation	NOUN
ajst-31456	195	7	for	for	ADP
ajst-31456	195	8	model	model	NOUN
ajst-31456	195	9	training	training	NOUN
ajst-31456	195	10	and	and	CCONJ
ajst-31456	195	11	evaluation	evaluation	NOUN
ajst-31456	195	12	.	.	PUNCT
ajst-31456	196	1	for	for	ADP
ajst-31456	196	2	a	a	DET
ajst-31456	196	3	robust	robust	ADJ
ajst-31456	196	4	performance	performance	NOUN
ajst-31456	196	5	evaluation	evaluation	NOUN
ajst-31456	196	6	,	,	PUNCT
ajst-31456	196	7	the	the	DET
ajst-31456	196	8	model	model	NOUN
ajst-31456	196	9	training	training	NOUN
ajst-31456	196	10	will	will	AUX
ajst-31456	196	11	incorporate	incorporate	VERB
ajst-31456	196	12	a	a	DET
ajst-31456	196	13	time	time	NOUN
ajst-31456	196	14	-	-	PUNCT
ajst-31456	196	15	series	series	NOUN
ajst-31456	196	16	cross	cross	ADJ
ajst-31456	196	17	-	-	ADJ
ajst-31456	196	18	validation	validation	ADJ
ajst-31456	196	19	strategy	strategy	NOUN
ajst-31456	196	20	.	.	PUNCT
ajst-31456	197	1	the	the	DET
ajst-31456	197	2	sklearn.mode_selection.timeseriessplit	sklearn.mode_selection.timeseriessplit	ADJ
ajst-31456	197	3	method	method	NOUN
ajst-31456	197	4	will	will	AUX
ajst-31456	197	5	be	be	AUX
ajst-31456	197	6	used	use	VERB
ajst-31456	197	7	to	to	PART
ajst-31456	197	8	divide	divide	VERB
ajst-31456	197	9	the	the	DET
ajst-31456	197	10	training	training	NOUN
ajst-31456	197	11	data	datum	NOUN
ajst-31456	197	12	into	into	ADP
ajst-31456	197	13	5	5	NUM
ajst-31456	197	14	(	(	PUNCT
ajst-31456	197	15	n	n	PRON
ajst-31456	197	16	splits=5	splits=5	PROPN
ajst-31456	197	17	)	)	PUNCT
ajst-31456	197	18	trainingvalidation	trainingvalidation	NOUN
ajst-31456	197	19	set	set	VERB
ajst-31456	197	20	pairs	pair	NOUN
ajst-31456	197	21	,	,	PUNCT
ajst-31456	197	22	ensuring	ensure	VERB
ajst-31456	197	23	that	that	SCONJ
ajst-31456	197	24	the	the	DET
ajst-31456	197	25	validation	validation	NOUN
ajst-31456	197	26	set	set	NOUN
ajst-31456	197	27	always	always	ADV
ajst-31456	197	28	follows	follow	VERB
ajst-31456	197	29	the	the	DET
ajst-31456	197	30	training	training	NOUN
ajst-31456	197	31	set	set	VERB
ajst-31456	197	32	in	in	ADP
ajst-31456	197	33	chronological	chronological	ADJ
ajst-31456	197	34	order	order	NOUN
ajst-31456	197	35	.	.	PUNCT
ajst-31456	198	1	at	at	ADP
ajst-31456	198	2	the	the	DET
ajst-31456	198	3	same	same	ADJ
ajst-31456	198	4	time	time	NOUN
ajst-31456	198	5	,	,	PUNCT
ajst-31456	198	6	in	in	ADP
ajst-31456	198	7	order	order	NOUN
ajst-31456	198	8	to	to	PART
ajst-31456	198	9	ensure	ensure	VERB
ajst-31456	198	10	that	that	SCONJ
ajst-31456	198	11	the	the	DET
ajst-31456	198	12	starting	starting	NOUN
ajst-31456	198	13	point	point	NOUN
ajst-31456	198	14	of	of	ADP
ajst-31456	198	15	all	all	DET
ajst-31456	198	16	model	model	NOUN
ajst-31456	198	17	algorithms	algorithms	NOUN
ajst-31456	198	18	is	be	AUX
ajst-31456	198	19	the	the	DET
ajst-31456	198	20	same	same	ADJ
ajst-31456	198	21	,	,	PUNCT
ajst-31456	198	22	this	this	DET
ajst-31456	198	23	article	article	NOUN
ajst-31456	198	24	sets	set	VERB
ajst-31456	198	25	the	the	DET
ajst-31456	198	26	hyperparameters	hyperparameter	NOUN
ajst-31456	198	27	of	of	ADP
ajst-31456	198	28	the	the	DET
ajst-31456	198	29	following	follow	VERB
ajst-31456	198	30	experimental	experimental	ADJ
ajst-31456	198	31	models	model	NOUN
ajst-31456	198	32	as	as	ADP
ajst-31456	198	33	random	random	ADJ
ajst-31456	198	34	hyperparameters	hyperparameter	NOUN
ajst-31456	198	35	.	.	PUNCT
ajst-31456	199	1	experimental	experimental	ADJ
ajst-31456	199	2	group	group	NOUN
ajst-31456	199	3	1	1	NUM
ajst-31456	199	4	:	:	PUNCT
ajst-31456	199	5	this	this	PRON
ajst-31456	199	6	is	be	AUX
ajst-31456	199	7	the	the	DET
ajst-31456	199	8	model	model	NOUN
ajst-31456	199	9	algorithm	algorithm	NOUN
ajst-31456	199	10	proposed	propose	VERB
ajst-31456	199	11	in	in	ADP
ajst-31456	199	12	this	this	DET
ajst-31456	199	13	article	article	NOUN
ajst-31456	199	14	,	,	PUNCT
ajst-31456	199	15	which	which	PRON
ajst-31456	199	16	is	be	AUX
ajst-31456	199	17	also	also	ADV
ajst-31456	199	18	the	the	DET
ajst-31456	199	19	core	core	ADJ
ajst-31456	199	20	comparative	comparative	ADJ
ajst-31456	199	21	experimental	experimental	ADJ
ajst-31456	199	22	algorithm	algorithm	NOUN
ajst-31456	199	23	.	.	PUNCT
ajst-31456	200	1	the	the	DET
ajst-31456	200	2	evaluation	evaluation	NOUN
ajst-31456	200	3	results	result	NOUN
ajst-31456	200	4	of	of	ADP
ajst-31456	200	5	this	this	DET
ajst-31456	200	6	experiment	experiment	NOUN
ajst-31456	200	7	will	will	AUX
ajst-31456	200	8	be	be	AUX
ajst-31456	200	9	compared	compare	VERB
ajst-31456	200	10	in	in	ADP
ajst-31456	200	11	depth	depth	NOUN
ajst-31456	200	12	with	with	ADP
ajst-31456	200	13	the	the	DET
ajst-31456	200	14	remaining	remain	VERB
ajst-31456	200	15	three	three	NUM
ajst-31456	200	16	experimental	experimental	ADJ
ajst-31456	200	17	groups	group	NOUN
ajst-31456	200	18	.	.	PUNCT
ajst-31456	201	1	the	the	DET
ajst-31456	201	2	table	table	NOUN
ajst-31456	201	3	clearly	clearly	ADV
ajst-31456	201	4	displays	display	VERB
ajst-31456	201	5	the	the	DET
ajst-31456	201	6	results	result	NOUN
ajst-31456	201	7	of	of	ADP
ajst-31456	201	8	group1	group1	PROPN
ajst-31456	201	9	,	,	PUNCT
ajst-31456	201	10	where	where	SCONJ
ajst-31456	201	11	the	the	DET
ajst-31456	201	12	performance	performance	NOUN
ajst-31456	201	13	of	of	ADP
ajst-31456	201	14	lightgbm	lightgbm	NOUN
ajst-31456	201	15	is	be	AUX
ajst-31456	201	16	particularly	particularly	ADV
ajst-31456	201	17	outstanding	outstanding	ADJ
ajst-31456	201	18	.	.	PUNCT
ajst-31456	202	1	table	table	NOUN
ajst-31456	202	2	vi	vi	PROPN
ajst-31456	202	3	model	model	NOUN
ajst-31456	202	4	performance	performance	NOUN
ajst-31456	202	5	model	model	NOUN
ajst-31456	202	6	name	name	PROPN
ajst-31456	202	7	cv	cv	PROPN
ajst-31456	202	8	mean	mean	PROPN
ajst-31456	202	9	rmsle	rmsle	PROPN
ajst-31456	202	10	cv	cv	PROPN
ajst-31456	202	11	mean	mean	PROPN
ajst-31456	202	12	r2	r2	PROPN
ajst-31456	202	13	lightgbm	lightgbm	VERB
ajst-31456	202	14	0.4653	0.4653	NUM
ajst-31456	202	15	0.8881	0.8881	NUM
ajst-31456	202	16	xgboost	xgboost	NOUN
ajst-31456	202	17	0.4756	0.4756	NUM
ajst-31456	202	18	0.8788	0.8788	NUM
ajst-31456	202	19	random	random	ADJ
ajst-31456	202	20	forest	forest	NOUN
ajst-31456	202	21	0.5236	0.5236	NUM
ajst-31456	202	22	0.8463	0.8463	NUM
ajst-31456	202	23	linear	linear	ADJ
ajst-31456	202	24	regression	regression	NOUN
ajst-31456	202	25	0.6189	0.6189	NUM
ajst-31456	202	26	0.7934	0.7934	NUM
ajst-31456	202	27	ridge	ridge	NOUN
ajst-31456	202	28	0.6196	0.6196	NUM
ajst-31456	202	29	0.7930	0.7930	NUM
ajst-31456	202	30	lasso	lasso	NOUN
ajst-31456	202	31	0.6300	0.6300	NUM
ajst-31456	202	32	0.7867	0.7867	NUM
ajst-31456	202	33	elastic	elastic	ADJ
ajst-31456	202	34	net	net	NOUN
ajst-31456	202	35	0.6308	0.6308	NUM
ajst-31456	202	36	0.7861	0.7861	NUM
ajst-31456	202	37	decision	decision	NOUN
ajst-31456	202	38	tree	tree	NOUN
ajst-31456	202	39	0.7081	0.7081	NUM
ajst-31456	202	40	0.7259	0.7259	NUM
ajst-31456	202	41	note	note	NOUN
ajst-31456	202	42	:	:	PUNCT
ajst-31456	202	43	both	both	DET
ajst-31456	202	44	metrics	metric	NOUN
ajst-31456	202	45	are	be	AUX
ajst-31456	202	46	calculated	calculate	VERB
ajst-31456	202	47	on	on	ADP
ajst-31456	202	48	the	the	DET
ajst-31456	202	49	log	log	NOUN
ajst-31456	202	50	-	-	PUNCT
ajst-31456	202	51	transformed	transform	VERB
ajst-31456	202	52	target	target	NOUN
ajst-31456	202	53	variable	variable	NOUN
ajst-31456	202	54	.	.	PUNCT
ajst-31456	203	1	the	the	DET
ajst-31456	203	2	cv	cv	PROPN
ajst-31456	203	3	mean	mean	NOUN
ajst-31456	203	4	rmsle	rmsle	PROPN
ajst-31456	203	5	is	be	AUX
ajst-31456	203	6	equivalent	equivalent	ADJ
ajst-31456	203	7	to	to	ADP
ajst-31456	203	8	the	the	DET
ajst-31456	203	9	rmse	rmse	NOUN
ajst-31456	203	10	of	of	ADP
ajst-31456	203	11	the	the	DET
ajst-31456	203	12	transformed	transform	VERB
ajst-31456	203	13	values	value	NOUN
ajst-31456	203	14	.	.	PUNCT
ajst-31456	204	1	experimental	experimental	ADJ
ajst-31456	204	2	group	group	NOUN
ajst-31456	204	3	2	2	NUM
ajst-31456	204	4	:	:	PUNCT
ajst-31456	204	5	compared	compare	VERB
ajst-31456	204	6	to	to	ADP
ajst-31456	204	7	the	the	DET
ajst-31456	204	8	method	method	NOUN
ajst-31456	204	9	in	in	ADP
ajst-31456	204	10	[	[	X
ajst-31456	204	11	8	8	NUM
ajst-31456	204	12	]	]	PUNCT
ajst-31456	204	13	.	.	PUNCT
ajst-31456	205	1	the	the	DET
ajst-31456	205	2	evaluation	evaluation	NOUN
ajst-31456	205	3	results	result	NOUN
ajst-31456	205	4	are	be	AUX
ajst-31456	205	5	shown	show	VERB
ajst-31456	205	6	in	in	ADP
ajst-31456	205	7	the	the	DET
ajst-31456	205	8	following	follow	VERB
ajst-31456	205	9	figure	figure	NOUN
ajst-31456	205	10	and	and	CCONJ
ajst-31456	205	11	table	table	NOUN
ajst-31456	205	12	:	:	PUNCT
ajst-31456	205	13	table	table	NOUN
ajst-31456	205	14	vii	vii	PROPN
ajst-31456	205	15	performance	performance	NOUN
ajst-31456	205	16	of	of	ADP
ajst-31456	205	17	the	the	DET
ajst-31456	205	18	model	model	NOUN
ajst-31456	205	19	proposed	propose	VERB
ajst-31456	205	20	by	by	ADP
ajst-31456	205	21	[	[	X
ajst-31456	205	22	8	8	NUM
ajst-31456	205	23	]	]	PUNCT
ajst-31456	205	24	model	model	NOUN
ajst-31456	205	25	cv	cv	PROPN
ajst-31456	205	26	mean	mean	PROPN
ajst-31456	205	27	rmsle	rmsle	PROPN
ajst-31456	206	1	cv	cv	PROPN
ajst-31456	206	2	mean	mean	PROPN
ajst-31456	206	3	r2	r2	PROPN
ajst-31456	206	4	random	random	ADJ
ajst-31456	206	5	forest	forest	NOUN
ajst-31456	206	6	0.524117	0.524117	NUM
ajst-31456	206	7	0.845876	0.845876	NUM
ajst-31456	206	8	gradient	gradient	NOUN
ajst-31456	206	9	boosting	boost	VERB
ajst-31456	206	10	0.608922	0.608922	NUM
ajst-31456	206	11	0.798118	0.798118	NUM
ajst-31456	206	12	linear	linear	ADJ
ajst-31456	206	13	regression	regression	NOUN
ajst-31456	206	14	0.619973	0.619973	NUM
ajst-31456	206	15	0.792532	0.792532	NUM
ajst-31456	206	16	ridge	ridge	NOUN
ajst-31456	206	17	0.620408	0.620408	NUM
ajst-31456	206	18	0.792309	0.792309	NUM
ajst-31456	206	19	decision	decision	NOUN
ajst-31456	206	20	tree	tree	NOUN
ajst-31456	206	21	0.660715	0.660715	NUM
ajst-31456	206	22	0.757237	0.757237	NUM
ajst-31456	206	23	elastic	elastic	ADJ
ajst-31456	206	24	net	net	NOUN
ajst-31456	206	25	1.261171	1.261171	NUM
ajst-31456	206	26	0.144826	0.144826	NUM
ajst-31456	206	27	lasso	lasso	NOUN
ajst-31456	206	28	1.267578	1.267578	NUM
ajst-31456	206	29	0.136411	0.136411	NUM
ajst-31456	206	30	from	from	ADP
ajst-31456	206	31	the	the	DET
ajst-31456	206	32	results	result	NOUN
ajst-31456	206	33	table	table	NOUN
ajst-31456	206	34	,	,	PUNCT
ajst-31456	206	35	even	even	ADV
ajst-31456	206	36	the	the	DET
ajst-31456	206	37	best	well	ADV
ajst-31456	206	38	performing	perform	VERB
ajst-31456	206	39	random	random	ADJ
ajst-31456	206	40	forest	forest	NOUN
ajst-31456	206	41	model	model	NOUN
ajst-31456	206	42	0.524117	0.524117	NUM
ajst-31456	206	43	did	do	AUX
ajst-31456	206	44	not	not	PART
ajst-31456	206	45	perform	perform	VERB
ajst-31456	206	46	as	as	ADV
ajst-31456	206	47	well	well	ADV
ajst-31456	206	48	as	as	ADP
ajst-31456	206	49	lightgbm	lightgbm	ADJ
ajst-31456	206	50	’s	’s	PART
ajst-31456	206	51	0.4653	0.4653	NUM
ajst-31456	206	52	in	in	ADP
ajst-31456	206	53	this	this	DET
ajst-31456	206	54	paper	paper	NOUN
ajst-31456	206	55	,	,	PUNCT
ajst-31456	206	56	which	which	PRON
ajst-31456	206	57	indirectly	indirectly	ADV
ajst-31456	206	58	reflects	reflect	VERB
ajst-31456	206	59	the	the	DET
ajst-31456	206	60	effectiveness	effectiveness	NOUN
ajst-31456	206	61	of	of	ADP
ajst-31456	206	62	module	module	NOUN
ajst-31456	206	63	3	3	NUM
ajst-31456	206	64	in	in	ADP
ajst-31456	206	65	this	this	DET
ajst-31456	206	66	paper	paper	NOUN
ajst-31456	206	67	.	.	PUNCT
ajst-31456	207	1	experimental	experimental	ADJ
ajst-31456	207	2	group	group	NOUN
ajst-31456	207	3	3	3	NUM
ajst-31456	207	4	:	:	PUNCT
ajst-31456	207	5	lstm	lstm	NOUN
ajst-31456	207	6	deep	deep	ADJ
ajst-31456	207	7	learning	learning	NOUN
ajst-31456	207	8	model	model	NOUN
ajst-31456	207	9	based	base	VERB
ajst-31456	207	10	on	on	ADP
ajst-31456	207	11	[	[	X
ajst-31456	207	12	11	11	NUM
ajst-31456	207	13	]	]	PUNCT
ajst-31456	207	14	.	.	PUNCT
ajst-31456	208	1	this	this	DET
ajst-31456	208	2	model	model	NOUN
ajst-31456	208	3	strictly	strictly	ADV
ajst-31456	208	4	replicates	replicate	VERB
ajst-31456	208	5	the	the	DET
ajst-31456	208	6	method	method	NOUN
ajst-31456	208	7	proposed	propose	VERB
ajst-31456	208	8	by	by	ADP
ajst-31456	208	9	this	this	DET
ajst-31456	208	10	group	group	NOUN
ajst-31456	208	11	in	in	ADP
ajst-31456	208	12	their	their	PRON
ajst-31456	208	13	paper	paper	NOUN
ajst-31456	208	14	,	,	PUNCT
ajst-31456	208	15	using	use	VERB
ajst-31456	208	16	a	a	DET
ajst-31456	208	17	single	single	ADJ
ajst-31456	208	18	-	-	PUNCT
ajst-31456	208	19	layer	layer	NOUN
ajst-31456	208	20	long	long	ADJ
ajst-31456	208	21	short	short	ADJ
ajst-31456	208	22	-	-	PUNCT
ajst-31456	208	23	term	term	NOUN
ajst-31456	208	24	memory	memory	NOUN
ajst-31456	208	25	network	network	NOUN
ajst-31456	208	26	(	(	PUNCT
ajst-31456	208	27	lstm	lstm	PROPN
ajst-31456	208	28	)	)	PUNCT
ajst-31456	208	29	for	for	ADP
ajst-31456	208	30	prediction	prediction	NOUN
ajst-31456	208	31	.	.	PUNCT
ajst-31456	209	1	data	datum	NOUN
ajst-31456	209	2	preprocessing	preprocessing	NOUN
ajst-31456	209	3	follows	follow	VERB
ajst-31456	209	4	the	the	DET
ajst-31456	209	5	original	original	ADJ
ajst-31456	209	6	text	text	NOUN
ajst-31456	209	7	,	,	PUNCT
ajst-31456	209	8	using	use	VERB
ajst-31456	209	9	minimum	minimum	ADJ
ajst-31456	209	10	maximum	maximum	ADJ
ajst-31456	209	11	normalization	normalization	NOUN
ajst-31456	209	12	and	and	CCONJ
ajst-31456	209	13	dividing	divide	VERB
ajst-31456	209	14	the	the	DET
ajst-31456	209	15	training	training	NOUN
ajst-31456	209	16	and	and	CCONJ
ajst-31456	209	17	testing	testing	NOUN
ajst-31456	209	18	sets	set	NOUN
ajst-31456	209	19	in	in	ADP
ajst-31456	209	20	chronological	chronological	ADJ
ajst-31456	209	21	order	order	NOUN
ajst-31456	209	22	.	.	PUNCT
ajst-31456	210	1	figure	figure	NOUN
ajst-31456	210	2	6	6	NUM
ajst-31456	210	3	.	.	PUNCT
ajst-31456	211	1	cv	cv	PROPN
ajst-31456	211	2	mean	mean	ADJ
ajst-31456	211	3	rmsle	rmsle	PROPN
ajst-31456	211	4	although	although	SCONJ
ajst-31456	211	5	the	the	DET
ajst-31456	211	6	results	result	NOUN
ajst-31456	211	7	of	of	ADP
ajst-31456	211	8	each	each	DET
ajst-31456	211	9	training	training	NOUN
ajst-31456	211	10	may	may	AUX
ajst-31456	211	11	differ	differ	VERB
ajst-31456	211	12	due	due	ADP
ajst-31456	211	13	to	to	ADP
ajst-31456	211	14	differences	difference	NOUN
ajst-31456	211	15	in	in	ADP
ajst-31456	211	16	algorithm	algorithm	NOUN
ajst-31456	211	17	settings	setting	NOUN
ajst-31456	211	18	and	and	CCONJ
ajst-31456	211	19	datasets	dataset	NOUN
ajst-31456	211	20	,	,	PUNCT
ajst-31456	211	21	overall	overall	ADV
ajst-31456	211	22	,	,	PUNCT
ajst-31456	211	23	the	the	DET
ajst-31456	211	24	training	training	NOUN
ajst-31456	211	25	results	result	NOUN
ajst-31456	211	26	using	use	VERB
ajst-31456	211	27	module	module	NOUN
ajst-31456	211	28	1	1	NUM
ajst-31456	211	29	are	be	AUX
ajst-31456	211	30	better	well	ADJ
ajst-31456	211	31	than	than	ADP
ajst-31456	211	32	the	the	DET
ajst-31456	211	33	original	original	ADJ
ajst-31456	211	34	algorithm	algorithm	NOUN
ajst-31456	211	35	without	without	ADP
ajst-31456	211	36	module	module	NOUN
ajst-31456	211	37	1	1	NUM
ajst-31456	211	38	.	.	PUNCT
ajst-31456	212	1	this	this	PRON
ajst-31456	212	2	proves	prove	VERB
ajst-31456	212	3	that	that	SCONJ
ajst-31456	212	4	the	the	DET
ajst-31456	212	5	data	datum	NOUN
ajst-31456	212	6	preprocessing	preprocessing	NOUN
ajst-31456	212	7	and	and	CCONJ
ajst-31456	212	8	feature	feature	NOUN
ajst-31456	212	9	engineering	engineering	NOUN
ajst-31456	212	10	in	in	ADP
ajst-31456	212	11	module	module	NOUN
ajst-31456	212	12	1	1	NUM
ajst-31456	212	13	have	have	AUX
ajst-31456	212	14	indeed	indeed	ADV
ajst-31456	212	15	excavated	excavate	VERB
ajst-31456	212	16	the	the	DET
ajst-31456	212	17	value	value	NOUN
ajst-31456	212	18	of	of	ADP
ajst-31456	212	19	the	the	DET
ajst-31456	212	20	data	datum	NOUN
ajst-31456	212	21	.	.	PUNCT
ajst-31456	213	1	experimental	experimental	ADJ
ajst-31456	213	2	group	group	NOUN
ajst-31456	213	3	4	4	NUM
ajst-31456	213	4	:	:	PUNCT
ajst-31456	213	5	based	base	VERB
ajst-31456	213	6	on	on	ADP
ajst-31456	213	7	the	the	DET
ajst-31456	213	8	cnn	cnn	PROPN
ajst-31456	213	9	bilstm	bilstm	NOUN
ajst-31456	213	10	atten	atten	PROPN
ajst-31456	213	11	tion	tion	PROPN
ajst-31456	213	12	deep	deep	ADJ
ajst-31456	213	13	learning	learning	NOUN
ajst-31456	213	14	benchmark	benchmark	NOUN
ajst-31456	213	15	proposed	propose	VERB
ajst-31456	213	16	by	by	ADP
ajst-31456	213	17	[	[	X
ajst-31456	213	18	12	12	NUM
ajst-31456	213	19	]	]	PUNCT
ajst-31456	213	20	.	.	PUNCT
ajst-31456	214	1	this	this	DET
ajst-31456	214	2	model	model	NOUN
ajst-31456	214	3	replicates	replicate	VERB
ajst-31456	214	4	the	the	DET
ajst-31456	214	5	more	more	ADJ
ajst-31456	214	6	cutting	cutting	NOUN
ajst-31456	214	7	-	-	PUNCT
ajst-31456	214	8	edge	edge	NOUN
ajst-31456	214	9	and	and	CCONJ
ajst-31456	214	10	com	com	NOUN
ajst-31456	214	11	plex	plex	PROPN
ajst-31456	214	12	deep	deep	ADJ
ajst-31456	214	13	learning	learning	NOUN
ajst-31456	214	14	architecture	architecture	NOUN
ajst-31456	214	15	proposed	propose	VERB
ajst-31456	214	16	by	by	ADP
ajst-31456	214	17	[	[	X
ajst-31456	214	18	12	12	NUM
ajst-31456	214	19	]	]	PUNCT
ajst-31456	214	20	in	in	ADP
ajst-31456	214	21	their	their	PRON
ajst-31456	214	22	paper	paper	NOUN
ajst-31456	214	23	,	,	PUNCT
ajst-31456	214	24	namely	namely	ADV
ajst-31456	214	25	cnn	cnn	PROPN
ajst-31456	214	26	-	-	PUNCT
ajst-31456	214	27	bilstm	bilstm	NOUN
ajst-31456	214	28	-	-	PUNCT
ajst-31456	214	29	attention	attention	NOUN
ajst-31456	214	30	.	.	PUNCT
ajst-31456	215	1	data	datum	NOUN
ajst-31456	215	2	preprocessing	preprocessing	NOUN
ajst-31456	215	3	and	and	CCONJ
ajst-31456	215	4	model	model	NOUN
ajst-31456	215	5	hyperparameters	hyperparameter	NOUN
ajst-31456	215	6	strictly	strictly	ADV
ajst-31456	215	7	follow	follow	VERB
ajst-31456	215	8	the	the	DET
ajst-31456	215	9	original	original	ADJ
ajst-31456	215	10	text	text	NOUN
ajst-31456	215	11	.	.	PUNCT
ajst-31456	216	1	the	the	DET
ajst-31456	216	2	final	final	ADJ
ajst-31456	216	3	evaluation	evaluation	NOUN
ajst-31456	216	4	result	result	NOUN
ajst-31456	216	5	of	of	ADP
ajst-31456	216	6	the	the	DET
ajst-31456	216	7	baseline	baseline	NOUN
ajst-31456	216	8	model	model	NOUN
ajst-31456	216	9	is	be	AUX
ajst-31456	216	10	as	as	SCONJ
ajst-31456	216	11	follows	follow	VERB
ajst-31456	216	12	:	:	PUNCT
ajst-31456	216	13	r2	r2	NOUN
ajst-31456	216	14	:	:	PUNCT
ajst-31456	216	15	0.9228	0.9228	NUM
ajst-31456	216	16	;	;	PUNCT
ajst-31456	216	17	rmsle	rmsle	NOUN
ajst-31456	216	18	:	:	PUNCT
ajst-31456	216	19	0.3891	0.3891	NUM
ajst-31456	216	20	.	.	PUNCT
ajst-31456	217	1	although	although	SCONJ
ajst-31456	217	2	the	the	DET
ajst-31456	217	3	ultimate	ultimate	ADJ
ajst-31456	217	4	performance	performance	NOUN
ajst-31456	217	5	of	of	ADP
ajst-31456	217	6	the	the	DET
ajst-31456	217	7	model	model	NOUN
ajst-31456	217	8	proposed	propose	VERB
ajst-31456	217	9	in	in	ADP
ajst-31456	217	10	this	this	DET
ajst-31456	217	11	article	article	NOUN
ajst-31456	217	12	might	might	AUX
ajst-31456	217	13	not	not	PART
ajst-31456	217	14	surpass	surpass	VERB
ajst-31456	217	15	that	that	PRON
ajst-31456	217	16	of	of	ADP
ajst-31456	217	17	this	this	DET
ajst-31456	217	18	baseline	baseline	NOUN
ajst-31456	217	19	model	model	NOUN
ajst-31456	217	20	,	,	PUNCT
ajst-31456	217	21	it	it	PRON
ajst-31456	217	22	does	do	AUX
ajst-31456	217	23	not	not	PART
ajst-31456	217	24	invalidate	invalidate	VERB
ajst-31456	217	25	the	the	DET
ajst-31456	217	26	effectiveness	effectiveness	NOUN
ajst-31456	217	27	of	of	ADP
ajst-31456	217	28	the	the	DET
ajst-31456	217	29	modules	module	NOUN
ajst-31456	217	30	proposed	propose	VERB
ajst-31456	217	31	herein	herein	NOUN
ajst-31456	217	32	.	.	PUNCT
ajst-31456	218	1	in	in	ADP
ajst-31456	218	2	order	order	NOUN
ajst-31456	218	3	to	to	PART
ajst-31456	218	4	verify	verify	VERB
ajst-31456	218	5	that	that	SCONJ
ajst-31456	218	6	modules	module	NOUN
ajst-31456	218	7	1	1	NUM
ajst-31456	218	8	and	and	CCONJ
ajst-31456	218	9	2	2	NUM
ajst-31456	218	10	can	can	AUX
ajst-31456	218	11	also	also	ADV
ajst-31456	218	12	enhance	enhance	VERB
ajst-31456	218	13	the	the	DET
ajst-31456	218	14	58	58	NUM
ajst-31456	218	15	performance	performance	NOUN
ajst-31456	218	16	of	of	ADP
ajst-31456	218	17	other	other	ADJ
ajst-31456	218	18	models	model	NOUN
ajst-31456	218	19	,	,	PUNCT
ajst-31456	218	20	this	this	DET
ajst-31456	218	21	paper	paper	NOUN
ajst-31456	218	22	integrates	integrate	VERB
ajst-31456	218	23	modules	module	NOUN
ajst-31456	218	24	1	1	NUM
ajst-31456	218	25	and	and	CCONJ
ajst-31456	218	26	2	2	NUM
ajst-31456	218	27	with	with	ADP
ajst-31456	218	28	the	the	DET
ajst-31456	218	29	algorithm	algorithm	NOUN
ajst-31456	218	30	proposed	propose	VERB
ajst-31456	218	31	by	by	ADP
ajst-31456	218	32	[	[	X
ajst-31456	218	33	12	12	NUM
ajst-31456	218	34	]	]	PUNCT
ajst-31456	218	35	,	,	PUNCT
ajst-31456	218	36	combining	combine	VERB
ajst-31456	218	37	our	our	PRON
ajst-31456	218	38	data	data	NOUN
ajst-31456	218	39	processing	processing	NOUN
ajst-31456	218	40	and	and	CCONJ
ajst-31456	218	41	feature	feature	NOUN
ajst-31456	218	42	engineering	engineering	NOUN
ajst-31456	218	43	techniques	technique	NOUN
ajst-31456	218	44	into	into	ADP
ajst-31456	218	45	their	their	PRON
ajst-31456	218	46	approach	approach	NOUN
ajst-31456	218	47	.	.	PUNCT
ajst-31456	219	1	the	the	DET
ajst-31456	219	2	final	final	ADJ
ajst-31456	219	3	evaluation	evaluation	NOUN
ajst-31456	219	4	results	result	NOUN
ajst-31456	219	5	for	for	ADP
ajst-31456	219	6	this	this	DET
ajst-31456	219	7	combined	combine	VERB
ajst-31456	219	8	approach	approach	NOUN
ajst-31456	219	9	are	be	AUX
ajst-31456	219	10	presented	present	VERB
ajst-31456	219	11	below	below	ADV
ajst-31456	219	12	,	,	PUNCT
ajst-31456	219	13	along	along	ADP
ajst-31456	219	14	with	with	ADP
ajst-31456	219	15	the	the	DET
ajst-31456	219	16	corresponding	correspond	VERB
ajst-31456	219	17	prediction	prediction	NOUN
ajst-31456	219	18	plot	plot	NOUN
ajst-31456	219	19	shown	show	VERB
ajst-31456	219	20	in	in	ADP
ajst-31456	219	21	figure	figure	NOUN
ajst-31456	219	22	7	7	NUM
ajst-31456	219	23	.	.	PUNCT
ajst-31456	219	24	‐	‐	NOUN
ajst-31456	219	25	 	 	SPACE
ajst-31456	219	26	r2	r2	NOUN
ajst-31456	219	27	:	:	PUNCT
ajst-31456	219	28	0.9324	0.9324	NUM
ajst-31456	219	29	rmsle	rmsle	NOUN
ajst-31456	219	30	:	:	PUNCT
ajst-31456	219	31	0.3765	0.3765	NUM
ajst-31456	219	32	as	as	SCONJ
ajst-31456	219	33	observed	observe	VERB
ajst-31456	219	34	,	,	PUNCT
ajst-31456	219	35	r2	r2	PROPN
ajst-31456	219	36	has	have	AUX
ajst-31456	219	37	significantly	significantly	ADV
ajst-31456	219	38	improved	improve	VERB
ajst-31456	219	39	and	and	CCONJ
ajst-31456	219	40	rmsle	rmsle	NOUN
ajst-31456	219	41	has	have	AUX
ajst-31456	219	42	notably	notably	ADV
ajst-31456	219	43	decreased	decrease	VERB
ajst-31456	219	44	,	,	PUNCT
ajst-31456	219	45	which	which	PRON
ajst-31456	219	46	directly	directly	ADV
ajst-31456	219	47	indicates	indicate	VERB
ajst-31456	219	48	the	the	DET
ajst-31456	219	49	significant	significant	ADJ
ajst-31456	219	50	role	role	NOUN
ajst-31456	219	51	of	of	ADP
ajst-31456	219	52	these	these	DET
ajst-31456	219	53	modules	module	NOUN
ajst-31456	219	54	.	.	PUNCT
ajst-31456	220	1	2	2	X
ajst-31456	220	2	)	)	PUNCT
ajst-31456	220	3	ablation	ablation	NOUN
ajst-31456	220	4	experiment	experiment	NOUN
ajst-31456	220	5	:	:	PUNCT
ajst-31456	220	6	in	in	ADP
ajst-31456	220	7	order	order	NOUN
ajst-31456	220	8	to	to	PART
ajst-31456	220	9	rigorously	rigorously	ADV
ajst-31456	220	10	verify	verify	VERB
ajst-31456	220	11	that	that	SCONJ
ajst-31456	220	12	different	different	ADJ
ajst-31456	220	13	modules	module	NOUN
ajst-31456	220	14	do	do	AUX
ajst-31456	220	15	indeed	indeed	ADV
ajst-31456	220	16	help	help	VERB
ajst-31456	220	17	improve	improve	VERB
ajst-31456	220	18	the	the	DET
ajst-31456	220	19	performance	performance	NOUN
ajst-31456	220	20	of	of	ADP
ajst-31456	220	21	the	the	DET
ajst-31456	220	22	model	model	NOUN
ajst-31456	220	23	,	,	PUNCT
ajst-31456	220	24	this	this	DET
ajst-31456	220	25	paper	paper	NOUN
ajst-31456	220	26	designed	design	VERB
ajst-31456	220	27	three	three	NUM
ajst-31456	220	28	different	different	ADJ
ajst-31456	220	29	ablation	ablation	NOUN
ajst-31456	220	30	experiments	experiment	NOUN
ajst-31456	220	31	,	,	PUNCT
ajst-31456	220	32	removing	remove	VERB
ajst-31456	220	33	different	different	ADJ
ajst-31456	220	34	modules	module	NOUN
ajst-31456	220	35	to	to	PART
ajst-31456	220	36	observe	observe	VERB
ajst-31456	220	37	the	the	DET
ajst-31456	220	38	predicted	predict	VERB
ajst-31456	220	39	results	result	NOUN
ajst-31456	220	40	.	.	PUNCT
ajst-31456	221	1	experimental	experimental	ADJ
ajst-31456	221	2	group	group	NOUN
ajst-31456	221	3	1	1	NUM
ajst-31456	221	4	:	:	PUNCT
ajst-31456	221	5	remove	remove	VERB
ajst-31456	221	6	module	module	NOUN
ajst-31456	221	7	1	1	NUM
ajst-31456	221	8	in	in	ADP
ajst-31456	221	9	this	this	DET
ajst-31456	221	10	experiment	experiment	NOUN
ajst-31456	221	11	,	,	PUNCT
ajst-31456	221	12	i	i	PRON
ajst-31456	221	13	will	will	AUX
ajst-31456	221	14	not	not	PART
ajst-31456	221	15	perform	perform	VERB
ajst-31456	221	16	any	any	DET
ajst-31456	221	17	additional	additional	ADJ
ajst-31456	221	18	pro	pro	ADJ
ajst-31456	221	19	cessing	cesse	VERB
ajst-31456	221	20	on	on	ADP
ajst-31456	221	21	the	the	DET
ajst-31456	221	22	initial	initial	ADJ
ajst-31456	221	23	data	datum	NOUN
ajst-31456	221	24	,	,	PUNCT
ajst-31456	221	25	but	but	CCONJ
ajst-31456	221	26	will	will	AUX
ajst-31456	221	27	only	only	ADV
ajst-31456	221	28	perform	perform	VERB
ajst-31456	221	29	basic	basic	ADJ
ajst-31456	221	30	feature	feature	NOUN
ajst-31456	221	31	splitting	splitting	NOUN
ajst-31456	221	32	and	and	CCONJ
ajst-31456	221	33	logarithmic	logarithmic	ADJ
ajst-31456	221	34	transformation	transformation	NOUN
ajst-31456	221	35	to	to	PART
ajst-31456	221	36	demonstrate	demonstrate	VERB
ajst-31456	221	37	the	the	DET
ajst-31456	221	38	effectiveness	effectiveness	NOUN
ajst-31456	221	39	of	of	ADP
ajst-31456	221	40	interactive	interactive	ADJ
ajst-31456	221	41	feature	feature	NOUN
ajst-31456	221	42	construction	construction	NOUN
ajst-31456	221	43	and	and	CCONJ
ajst-31456	221	44	automated	automated	ADJ
ajst-31456	221	45	binning	bin	VERB
ajst-31456	221	46	operations	operation	NOUN
ajst-31456	221	47	.	.	PUNCT
ajst-31456	222	1	figure	figure	VERB
ajst-31456	222	2	7	7	NUM
ajst-31456	222	3	.	.	PUNCT
ajst-31456	222	4	prediction	prediction	NOUN
ajst-31456	222	5	vs.	vs.	ADP
ajst-31456	222	6	true	true	ADJ
ajst-31456	222	7	values	value	NOUN
ajst-31456	222	8	for	for	ADP
ajst-31456	222	9	the	the	DET
ajst-31456	222	10	combined	combined	ADJ
ajst-31456	222	11	model	model	NOUN
ajst-31456	222	12	table	table	NOUN
ajst-31456	222	13	viii	viii	NOUN
ajst-31456	222	14	model	model	NOUN
ajst-31456	222	15	performance	performance	NOUN
ajst-31456	222	16	with	with	ADP
ajst-31456	222	17	baseline	baseline	PROPN
ajst-31456	222	18	features	feature	NOUN
ajst-31456	222	19	model	model	PROPN
ajst-31456	222	20	cv	cv	PROPN
ajst-31456	222	21	mean	mean	PROPN
ajst-31456	222	22	rmsle	rmsle	PROPN
ajst-31456	222	23	cv	cv	PROPN
ajst-31456	222	24	mean	mean	PROPN
ajst-31456	222	25	r2	r2	PROPN
ajst-31456	222	26	lightgbm	lightgbm	VERB
ajst-31456	222	27	0.474516	0.474516	NUM
ajst-31456	222	28	0.872277	0.872277	NUM
ajst-31456	223	1	xgboost	xgboost	ADV
ajst-31456	223	2	0.478621	0.478621	NUM
ajst-31456	223	3	0.872030	0.872030	NUM
ajst-31456	223	4	random	random	ADJ
ajst-31456	223	5	forest	forest	NOUN
ajst-31456	223	6	0.522100	0.522100	NUM
ajst-31456	223	7	0.846892	0.846892	NUM
ajst-31456	223	8	linear	linear	ADJ
ajst-31456	223	9	regression	regression	NOUN
ajst-31456	223	10	0.621773	0.621773	NUM
ajst-31456	223	11	0.791246	0.791246	NUM
ajst-31456	223	12	ridge	ridge	NOUN
ajst-31456	223	13	0.622055	0.622055	NUM
ajst-31456	223	14	0.791140	0.791140	NUM
ajst-31456	223	15	elastic	elastic	ADJ
ajst-31456	223	16	net	net	NOUN
ajst-31456	223	17	0.628228	0.628228	NUM
ajst-31456	223	18	0.788013	0.788013	NUM
ajst-31456	223	19	lasso	lasso	NOUN
ajst-31456	223	20	0.630166	0.630166	NUM
ajst-31456	223	21	0.786675	0.786675	NUM
ajst-31456	223	22	decision	decision	NOUN
ajst-31456	223	23	tree	tree	NOUN
ajst-31456	223	24	0.707639	0.707639	NUM
ajst-31456	223	25	0.728073	0.728073	NUM
ajst-31456	223	26	1	1	NUM
ajst-31456	223	27	)	)	PUNCT
ajst-31456	223	28	significant	significant	ADJ
ajst-31456	223	29	improvement	improvement	NOUN
ajst-31456	223	30	for	for	ADP
ajst-31456	223	31	lightgbm	lightgbm	ADJ
ajst-31456	223	32	model	model	NOUN
ajst-31456	223	33	:	:	PUNCT
ajst-31456	223	34	among	among	ADP
ajst-31456	223	35	all	all	DET
ajst-31456	223	36	models	model	NOUN
ajst-31456	223	37	,	,	PUNCT
ajst-31456	223	38	lightgbm	lightgbm	NOUN
ajst-31456	223	39	showed	show	VERB
ajst-31456	223	40	the	the	DET
ajst-31456	223	41	most	most	ADV
ajst-31456	223	42	prominent	prominent	ADJ
ajst-31456	223	43	performance	performance	NOUN
ajst-31456	223	44	improvement	improvement	NOUN
ajst-31456	223	45	after	after	ADP
ajst-31456	223	46	introducing	introduce	VERB
ajst-31456	223	47	optimized	optimize	VERB
ajst-31456	223	48	feature	feature	NOUN
ajst-31456	223	49	engineering	engineering	NOUN
ajst-31456	223	50	.	.	PUNCT
ajst-31456	224	1	its	its	PRON
ajst-31456	224	2	cv	cv	PROPN
ajst-31456	224	3	mean	mean	NOUN
ajst-31456	224	4	rmsle	rmsle	PROPN
ajst-31456	224	5	decreased	decrease	VERB
ajst-31456	224	6	from	from	ADP
ajst-31456	224	7	0.4745	0.4745	NUM
ajst-31456	224	8	  	  	SPACE
ajst-31456	224	9	with	with	ADP
ajst-31456	224	10	baseline	baseline	ADJ
ajst-31456	224	11	feature	feature	NOUN
ajst-31456	224	12	engineering	engineering	NOUN
ajst-31456	224	13	to	to	ADP
ajst-31456	224	14	0.4653	0.4653	NUM
ajst-31456	224	15	.	.	PUNCT
ajst-31456	225	1	this	this	PRON
ajst-31456	225	2	strongly	strongly	ADV
ajst-31456	225	3	demonstrates	demonstrate	VERB
ajst-31456	225	4	the	the	DET
ajst-31456	225	5	positive	positive	ADJ
ajst-31456	225	6	impact	impact	NOUN
ajst-31456	225	7	of	of	ADP
ajst-31456	225	8	the	the	DET
ajst-31456	225	9	advanced	advanced	ADJ
ajst-31456	225	10	feature	feature	NOUN
ajst-31456	225	11	engineering	engineering	NOUN
ajst-31456	225	12	strategy	strategy	NOUN
ajst-31456	225	13	proposed	propose	VERB
ajst-31456	225	14	in	in	ADP
ajst-31456	225	15	this	this	DET
ajst-31456	225	16	paper	paper	NOUN
ajst-31456	225	17	on	on	ADP
ajst-31456	225	18	lightgbm	lightgbm	PROPN
ajst-31456	225	19	’s	’s	PART
ajst-31456	225	20	model	model	NOUN
ajst-31456	225	21	performance	performance	NOUN
ajst-31456	225	22	.	.	PUNCT
ajst-31456	226	1	slight	slight	ADJ
ajst-31456	226	2	improvement	improvement	NOUN
ajst-31456	226	3	for	for	ADP
ajst-31456	226	4	linear	linear	ADJ
ajst-31456	226	5	models	model	NOUN
ajst-31456	226	6	:	:	PUNCT
ajst-31456	226	7	for	for	ADP
ajst-31456	226	8	linear	linear	ADJ
ajst-31456	226	9	models	model	NOUN
ajst-31456	226	10	,	,	PUNCT
ajst-31456	226	11	both	both	CCONJ
ajst-31456	226	12	rmsle	rmsle	NOUN
ajst-31456	226	13	and	and	CCONJ
ajst-31456	226	14	r2	r2	PROPN
ajst-31456	226	15	showed	show	VERB
ajst-31456	226	16	slight	slight	ADJ
ajst-31456	226	17	improvements	improvement	NOUN
ajst-31456	226	18	after	after	ADP
ajst-31456	226	19	introducing	introduce	VERB
ajst-31456	226	20	optimized	optimize	VERB
ajst-31456	226	21	feature	feature	NOUN
ajst-31456	226	22	engineering	engineering	NOUN
ajst-31456	226	23	,	,	PUNCT
ajst-31456	226	24	although	although	SCONJ
ajst-31456	226	25	the	the	DET
ajst-31456	226	26	magnitude	magnitude	NOUN
ajst-31456	226	27	of	of	ADP
ajst-31456	226	28	improvement	improvement	NOUN
ajst-31456	226	29	was	be	AUX
ajst-31456	226	30	relatively	relatively	ADV
ajst-31456	226	31	small	small	ADJ
ajst-31456	226	32	,	,	PUNCT
ajst-31456	226	33	there	there	PRON
ajst-31456	226	34	was	be	VERB
ajst-31456	226	35	still	still	ADV
ajst-31456	226	36	an	an	DET
ajst-31456	226	37	improvement	improvement	NOUN
ajst-31456	226	38	.	.	PUNCT
ajst-31456	227	1	conclusion	conclusion	NOUN
ajst-31456	227	2	:	:	PUNCT
ajst-31456	227	3	the	the	DET
ajst-31456	227	4	experimental	experimental	ADJ
ajst-31456	227	5	results	result	NOUN
ajst-31456	227	6	indicate	indicate	VERB
ajst-31456	227	7	that	that	SCONJ
ajst-31456	227	8	the	the	DET
ajst-31456	227	9	module	module	NOUN
ajst-31456	227	10	1	1	NUM
ajst-31456	227	11	operation	operation	NOUN
ajst-31456	227	12	proposed	propose	VERB
ajst-31456	227	13	in	in	ADP
ajst-31456	227	14	this	this	DET
ajst-31456	227	15	paper	paper	NOUN
ajst-31456	227	16	is	be	AUX
ajst-31456	227	17	most	most	ADV
ajst-31456	227	18	effective	effective	ADJ
ajst-31456	227	19	for	for	ADP
ajst-31456	227	20	improving	improve	VERB
ajst-31456	227	21	lightgbm	lightgbm	ADJ
ajst-31456	227	22	’s	’s	PART
ajst-31456	227	23	performance	performance	NOUN
ajst-31456	227	24	,	,	PUNCT
ajst-31456	227	25	capable	capable	ADJ
ajst-31456	227	26	of	of	ADP
ajst-31456	227	27	effectively	effectively	ADV
ajst-31456	227	28	reducing	reduce	VERB
ajst-31456	227	29	prediction	prediction	NOUN
ajst-31456	227	30	errors	error	NOUN
ajst-31456	227	31	and	and	CCONJ
ajst-31456	227	32	enhancing	enhance	VERB
ajst-31456	227	33	model	model	NOUN
ajst-31456	227	34	interpretability	interpretability	NOUN
ajst-31456	227	35	.	.	PUNCT
ajst-31456	228	1	experimental	experimental	ADJ
ajst-31456	228	2	group	group	NOUN
ajst-31456	228	3	2	2	NUM
ajst-31456	228	4	:	:	PUNCT
ajst-31456	228	5	remove	remove	VERB
ajst-31456	228	6	module	module	NOUN
ajst-31456	228	7	2	2	NUM
ajst-31456	228	8	in	in	ADP
ajst-31456	228	9	module	module	NOUN
ajst-31456	228	10	2	2	NUM
ajst-31456	228	11	,	,	PUNCT
ajst-31456	228	12	we	we	PRON
ajst-31456	228	13	removed	remove	VERB
ajst-31456	228	14	the	the	DET
ajst-31456	228	15	feature	feature	NOUN
ajst-31456	228	16	filtering	filter	VERB
ajst-31456	228	17	part	part	NOUN
ajst-31456	228	18	,	,	PUNCT
ajst-31456	228	19	and	and	CCONJ
ajst-31456	228	20	the	the	DET
ajst-31456	228	21	final	final	ADJ
ajst-31456	228	22	evaluation	evaluation	NOUN
ajst-31456	228	23	value	value	NOUN
ajst-31456	228	24	showed	show	VERB
ajst-31456	228	25	the	the	DET
ajst-31456	228	26	same	same	ADJ
ajst-31456	228	27	as	as	ADP
ajst-31456	228	28	the	the	DET
ajst-31456	228	29	unfiltered	unfiltered	ADJ
ajst-31456	228	30	result	result	NOUN
ajst-31456	228	31	.	.	PUNCT
ajst-31456	229	1	although	although	SCONJ
ajst-31456	229	2	the	the	DET
ajst-31456	229	3	value	value	NOUN
ajst-31456	229	4	did	do	AUX
ajst-31456	229	5	not	not	PART
ajst-31456	229	6	change	change	VERB
ajst-31456	229	7	,	,	PUNCT
ajst-31456	229	8	the	the	DET
ajst-31456	229	9	training	training	NOUN
ajst-31456	229	10	time	time	NOUN
ajst-31456	229	11	was	be	AUX
ajst-31456	229	12	increased	increase	VERB
ajst-31456	229	13	by	by	ADP
ajst-31456	229	14	1.2	1.2	NUM
ajst-31456	229	15	seconds	second	NOUN
ajst-31456	229	16	,	,	PUNCT
ajst-31456	229	17	which	which	PRON
ajst-31456	229	18	is	be	AUX
ajst-31456	229	19	equivalent	equivalent	ADJ
ajst-31456	229	20	to	to	ADP
ajst-31456	229	21	a	a	DET
ajst-31456	229	22	2.3	2.3	NUM
ajst-31456	229	23	percentage	percentage	NOUN
ajst-31456	229	24	reduction	reduction	NOUN
ajst-31456	229	25	in	in	ADP
ajst-31456	229	26	training	training	NOUN
ajst-31456	229	27	time	time	NOUN
ajst-31456	229	28	.	.	PUNCT
ajst-31456	230	1	therefore	therefore	ADV
ajst-31456	230	2	,	,	PUNCT
ajst-31456	230	3	it	it	PRON
ajst-31456	230	4	can	can	AUX
ajst-31456	230	5	also	also	ADV
ajst-31456	230	6	prove	prove	VERB
ajst-31456	230	7	that	that	SCONJ
ajst-31456	230	8	module	module	NOUN
ajst-31456	230	9	2	2	NUM
ajst-31456	230	10	is	be	AUX
ajst-31456	230	11	effective	effective	ADJ
ajst-31456	230	12	.	.	PUNCT
ajst-31456	231	1	experimental	experimental	ADJ
ajst-31456	231	2	group	group	NOUN
ajst-31456	231	3	3	3	NUM
ajst-31456	231	4	:	:	PUNCT
ajst-31456	231	5	verify	verify	VERB
ajst-31456	231	6	the	the	DET
ajst-31456	231	7	effectiveness	effectiveness	NOUN
ajst-31456	231	8	of	of	ADP
ajst-31456	231	9	module	module	NOUN
ajst-31456	231	10	3	3	NUM
ajst-31456	231	11	according	accord	VERB
ajst-31456	231	12	to	to	ADP
ajst-31456	231	13	the	the	DET
ajst-31456	231	14	evaluation	evaluation	NOUN
ajst-31456	231	15	results	result	NOUN
ajst-31456	231	16	in	in	ADP
ajst-31456	231	17	table	table	NOUN
ajst-31456	231	18	vi	vi	PROPN
ajst-31456	231	19	,	,	PUNCT
ajst-31456	231	20	the	the	DET
ajst-31456	231	21	tree	tree	NOUN
ajst-31456	231	22	based	base	VERB
ajst-31456	231	23	ensemble	ensemble	ADJ
ajst-31456	231	24	learning	learning	NOUN
ajst-31456	231	25	models	model	NOUN
ajst-31456	231	26	lightgbm	lightgbm	VERB
ajst-31456	231	27	and	and	CCONJ
ajst-31456	231	28	xgboost	xgboost	ADV
ajst-31456	231	29	have	have	VERB
ajst-31456	231	30	significantly	significantly	ADV
ajst-31456	231	31	better	well	ADJ
ajst-31456	231	32	performance	performance	NOUN
ajst-31456	231	33	than	than	ADP
ajst-31456	231	34	other	other	ADJ
ajst-31456	231	35	models	model	NOUN
ajst-31456	231	36	,	,	PUNCT
ajst-31456	231	37	which	which	PRON
ajst-31456	231	38	can	can	AUX
ajst-31456	231	39	significantly	significantly	ADV
ajst-31456	231	40	verify	verify	VERB
ajst-31456	231	41	the	the	DET
ajst-31456	231	42	effectiveness	effectiveness	NOUN
ajst-31456	231	43	of	of	ADP
ajst-31456	231	44	module	module	NOUN
ajst-31456	231	45	3	3	NUM
ajst-31456	231	46	.	.	NOUN
ajst-31456	231	47	3	3	NUM
ajst-31456	231	48	)	)	PUNCT
ajst-31456	231	49	hyperparameter	hyperparameter	NOUN
ajst-31456	231	50	optimization	optimization	NOUN
ajst-31456	231	51	:	:	PUNCT
ajst-31456	231	52	in	in	ADP
ajst-31456	231	53	order	order	NOUN
ajst-31456	231	54	to	to	PART
ajst-31456	231	55	optimize	optimize	VERB
ajst-31456	231	56	the	the	DET
ajst-31456	231	57	performance	performance	NOUN
ajst-31456	231	58	and	and	CCONJ
ajst-31456	231	59	prediction	prediction	NOUN
ajst-31456	231	60	accuracy	accuracy	NOUN
ajst-31456	231	61	of	of	ADP
ajst-31456	231	62	the	the	DET
ajst-31456	231	63	model	model	NOUN
ajst-31456	231	64	,	,	PUNCT
ajst-31456	231	65	this	this	DET
ajst-31456	231	66	article	article	NOUN
ajst-31456	231	67	has	have	AUX
ajst-31456	231	68	decided	decide	VERB
ajst-31456	231	69	to	to	PART
ajst-31456	231	70	choose	choose	VERB
ajst-31456	231	71	the	the	DET
ajst-31456	231	72	lightgbm	lightgbm	ADJ
ajst-31456	231	73	model	model	NOUN
ajst-31456	231	74	for	for	ADP
ajst-31456	231	75	hyperparameter	hyperparameter	NOUN
ajst-31456	231	76	tuning	tune	VERB
ajst-31456	231	77	.	.	PUNCT
ajst-31456	232	1	the	the	DET
ajst-31456	232	2	tuning	tuning	NOUN
ajst-31456	232	3	method	method	NOUN
ajst-31456	232	4	used	use	VERB
ajst-31456	232	5	is	be	AUX
ajst-31456	232	6	bayesian	bayesian	NOUN
ajst-31456	232	7	tuning	tuning	NOUN
ajst-31456	232	8	,	,	PUNCT
ajst-31456	232	9	and	and	CCONJ
ajst-31456	232	10	the	the	DET
ajst-31456	232	11	results	result	NOUN
ajst-31456	232	12	are	be	AUX
ajst-31456	232	13	shown	show	VERB
ajst-31456	232	14	in	in	ADP
ajst-31456	232	15	the	the	DET
ajst-31456	232	16	table	table	NOUN
ajst-31456	232	17	below	below	ADV
ajst-31456	232	18	.	.	PUNCT
ajst-31456	233	1	table	table	NOUN
ajst-31456	233	2	ix	ix	ADP
ajst-31456	233	3	lightgbm	lightgbm	ADJ
ajst-31456	233	4	model	model	NOUN
ajst-31456	233	5	performance	performance	NOUN
ajst-31456	233	6	after	after	ADP
ajst-31456	233	7	bayesian	bayesian	NOUN
ajst-31456	233	8	tuning	tune	VERB
ajst-31456	233	9	metric	metric	ADJ
ajst-31456	233	10	value	value	NOUN
ajst-31456	233	11	rmse	rmse	NOUN
ajst-31456	233	12	0.4109	0.4109	NUM
ajst-31456	233	13	±	±	NUM
ajst-31456	233	14	0.0839	0.0839	NUM
ajst-31456	233	15	r2	r2	PROPN
ajst-31456	233	16	0.9048	0.9048	NUM
ajst-31456	233	17	±	±	NUM
ajst-31456	233	18	0.0415	0.0415	NUM
ajst-31456	233	19	  	  	SPACE
ajst-31456	233	20	figure	figure	NOUN
ajst-31456	233	21	8	8	NUM
ajst-31456	233	22	.	.	PUNCT
ajst-31456	234	1	3d	3d	NUM
ajst-31456	234	2	bar	bar	NOUN
ajst-31456	234	3	charts	chart	NOUN
ajst-31456	234	4	of	of	ADP
ajst-31456	234	5	rmse	rmse	NOUN
ajst-31456	234	6	for	for	ADP
ajst-31456	234	7	lightgbm	lightgbm	ADJ
ajst-31456	234	8	hyperparameter	hyperparameter	NOUN
ajst-31456	234	9	combinations	combination	NOUN
ajst-31456	234	10	.	.	PUNCT
ajst-31456	235	1	from	from	ADP
ajst-31456	235	2	the	the	DET
ajst-31456	235	3	figure	figure	NOUN
ajst-31456	235	4	8	8	NUM
ajst-31456	235	5	,	,	PUNCT
ajst-31456	235	6	it	it	PRON
ajst-31456	235	7	can	can	AUX
ajst-31456	235	8	be	be	AUX
ajst-31456	235	9	seen	see	VERB
ajst-31456	235	10	that	that	SCONJ
ajst-31456	235	11	the	the	DET
ajst-31456	235	12	rmse	rmse	ADJ
ajst-31456	235	13	score	score	NOUN
ajst-31456	235	14	varies	vary	VERB
ajst-31456	235	15	with	with	ADP
ajst-31456	235	16	different	different	ADJ
ajst-31456	235	17	hyperparameters	hyperparameter	NOUN
ajst-31456	235	18	,	,	PUNCT
ajst-31456	235	19	but	but	CCONJ
ajst-31456	235	20	there	there	PRON
ajst-31456	235	21	is	be	VERB
ajst-31456	235	22	a	a	DET
ajst-31456	235	23	lowest	low	ADJ
ajst-31456	235	24	point	point	NOUN
ajst-31456	235	25	,	,	PUNCT
ajst-31456	235	26	which	which	PRON
ajst-31456	235	27	is	be	AUX
ajst-31456	235	28	the	the	DET
ajst-31456	235	29	locally	locally	ADV
ajst-31456	235	30	optimal	optimal	ADJ
ajst-31456	235	31	hyperparameter	hyperparameter	NOUN
ajst-31456	235	32	f.	f.	PROPN
ajst-31456	235	33	conclusion	conclusion	NOUN
ajst-31456	235	34	this	this	DET
ajst-31456	235	35	article	article	NOUN
ajst-31456	235	36	aims	aim	VERB
ajst-31456	235	37	to	to	PART
ajst-31456	235	38	solve	solve	VERB
ajst-31456	235	39	the	the	DET
ajst-31456	235	40	problem	problem	NOUN
ajst-31456	235	41	of	of	ADP
ajst-31456	235	42	hourly	hourly	ADJ
ajst-31456	235	43	level	level	NOUN
ajst-31456	235	44	prediction	prediction	NOUN
ajst-31456	235	45	of	of	ADP
ajst-31456	235	46	shared	share	VERB
ajst-31456	235	47	bicycle	bicycle	NOUN
ajst-31456	235	48	demand	demand	NOUN
ajst-31456	235	49	by	by	ADP
ajst-31456	235	50	using	use	VERB
ajst-31456	235	51	a	a	DET
ajst-31456	235	52	framework	framework	NOUN
ajst-31456	235	53	that	that	PRON
ajst-31456	235	54	combines	combine	VERB
ajst-31456	235	55	data	datum	NOUN
ajst-31456	235	56	processing	processing	NOUN
ajst-31456	235	57	,	,	PUNCT
ajst-31456	235	58	feature	feature	NOUN
ajst-31456	235	59	engineering	engineering	NOUN
ajst-31456	235	60	,	,	PUNCT
ajst-31456	235	61	feature	feature	NOUN
ajst-31456	235	62	filtering	filtering	NOUN
ajst-31456	235	63	,	,	PUNCT
ajst-31456	235	64	tree	tree	NOUN
ajst-31456	235	65	based	base	VERB
ajst-31456	235	66	model	model	NOUN
ajst-31456	235	67	construction	construction	NOUN
ajst-31456	235	68	,	,	PUNCT
ajst-31456	235	69	and	and	CCONJ
ajst-31456	235	70	hyperparameter	hyperparameter	NOUN
ajst-31456	235	71	optimization	optimization	NOUN
ajst-31456	235	72	.	.	PUNCT
ajst-31456	236	1	comparative	comparative	ADJ
ajst-31456	236	2	and	and	CCONJ
ajst-31456	236	3	ablation	ablation	NOUN
ajst-31456	236	4	experiments	experiment	NOUN
ajst-31456	236	5	have	have	AUX
ajst-31456	236	6	been	be	AUX
ajst-31456	236	7	conducted	conduct	VERB
ajst-31456	236	8	to	to	PART
ajst-31456	236	9	demonstrate	demonstrate	VERB
ajst-31456	236	10	the	the	DET
ajst-31456	236	11	effectiveness	effectiveness	NOUN
ajst-31456	236	12	of	of	ADP
ajst-31456	236	13	the	the	DET
ajst-31456	236	14	frameworks	framework	NOUN
ajst-31456	236	15	in	in	ADP
ajst-31456	236	16	this	this	DET
ajst-31456	236	17	module	module	NOUN
ajst-31456	236	18	.	.	PUNCT
ajst-31456	237	1	the	the	DET
ajst-31456	237	2	framework	framework	NOUN
ajst-31456	237	3	presented	present	VERB
ajst-31456	237	4	here	here	ADV
ajst-31456	237	5	can	can	AUX
ajst-31456	237	6	serve	serve	VERB
ajst-31456	237	7	as	as	ADP
ajst-31456	237	8	the	the	DET
ajst-31456	237	9	core	core	NOUN
ajst-31456	237	10	prediction	prediction	NOUN
ajst-31456	237	11	engine	engine	NOUN
ajst-31456	237	12	for	for	ADP
ajst-31456	237	13	a	a	DET
ajst-31456	237	14	real	real	ADJ
ajst-31456	237	15	-	-	PUNCT
ajst-31456	237	16	time	time	NOUN
ajst-31456	237	17	demand	demand	NOUN
ajst-31456	237	18	-	-	PUNCT
ajst-31456	237	19	supply	supply	NOUN
ajst-31456	237	20	tracking	tracking	NOUN
ajst-31456	237	21	system	system	NOUN
ajst-31456	237	22	,	,	PUNCT
ajst-31456	237	23	providing	provide	VERB
ajst-31456	237	24	operators	operator	NOUN
ajst-31456	237	25	with	with	ADP
ajst-31456	237	26	a	a	DET
ajst-31456	237	27	dashboard	dashboard	NOUN
ajst-31456	237	28	to	to	PART
ajst-31456	237	29	monitor	monitor	VERB
ajst-31456	237	30	and	and	CCONJ
ajst-31456	237	31	manage	manage	VERB
ajst-31456	237	32	station	station	NOUN
ajst-31456	237	33	-	-	PUNCT
ajst-31456	237	34	level	level	NOUN
ajst-31456	237	35	demand	demand	NOUN
ajst-31456	237	36	effectively	effectively	ADV
ajst-31456	237	37	[	[	X
ajst-31456	237	38	33	33	NUM
ajst-31456	237	39	]	]	PUNCT
ajst-31456	237	40	.	.	PUNCT
ajst-31456	238	1	59	59	NUM
ajst-31456	238	2	references	reference	NOUN
ajst-31456	238	3	[	[	X
ajst-31456	238	4	1	1	X
ajst-31456	238	5	]	]	PUNCT
ajst-31456	238	6	s.	s.	PROPN
ajst-31456	238	7	h.	h.	PROPN
ajst-31456	238	8	choi	choi	PROPN
ajst-31456	238	9	and	and	CCONJ
ajst-31456	238	10	m.	m.	PROPN
ajst-31456	238	11	k.	k.	PROPN
ajst-31456	238	12	han	han	PROPN
ajst-31456	238	13	,	,	PUNCT
ajst-31456	238	14	“	"	PUNCT
ajst-31456	238	15	the	the	DET
ajst-31456	238	16	empirical	empirical	ADJ
ajst-31456	238	17	evaluation	evaluation	NOUN
ajst-31456	238	18	of	of	ADP
ajst-31456	238	19	models	model	NOUN
ajst-31456	238	20	predicting	predict	VERB
ajst-31456	238	21	bike	bike	NOUN
ajst-31456	238	22	sharing	sharing	NOUN
ajst-31456	238	23	demand	demand	NOUN
ajst-31456	238	24	,	,	PUNCT
ajst-31456	238	25	”	"	PUNCT
ajst-31456	238	26	in	in	ADP
ajst-31456	238	27	2020	2020	NUM
ajst-31456	238	28	international	international	ADJ
ajst-31456	238	29	conference	conference	NOUN
ajst-31456	238	30	on	on	ADP
ajst-31456	238	31	information	information	NOUN
ajst-31456	238	32	and	and	CCONJ
ajst-31456	238	33	communication	communication	NOUN
ajst-31456	238	34	technology	technology	NOUN
ajst-31456	238	35	convergence	convergence	NOUN
ajst-31456	238	36	(	(	PUNCT
ajst-31456	238	37	ictc	ictc	NOUN
ajst-31456	238	38	)	)	PUNCT
ajst-31456	238	39	,	,	PUNCT
ajst-31456	238	40	2020	2020	NUM
ajst-31456	238	41	,	,	PUNCT
ajst-31456	238	42	pp	pp	ADJ
ajst-31456	238	43	.	.	PUNCT
ajst-31456	239	1	1560–1562	1560–1562	NUM
ajst-31456	239	2	.	.	PUNCT
ajst-31456	240	1	[	[	X
ajst-31456	240	2	2	2	NUM
ajst-31456	240	3	]	]	PUNCT
ajst-31456	240	4	m.	m.	NOUN
ajst-31456	240	5	m.	m.	NOUN
ajst-31456	240	6	isalm	isalm	PROPN
ajst-31456	240	7	,	,	PUNCT
ajst-31456	240	8	m.	m.	PROPN
ajst-31456	240	9	e.	e.	PROPN
ajst-31456	240	10	biswas	biswas	PROPN
ajst-31456	240	11	,	,	PUNCT
ajst-31456	240	12	m.	m.	NOUN
ajst-31456	240	13	shahzamal	shahzamal	ADJ
ajst-31456	240	14	,	,	PUNCT
ajst-31456	240	15	m.	m.	PROPN
ajst-31456	240	16	d.	d.	PROPN
ajst-31456	240	17	haque	haque	PROPN
ajst-31456	240	18	,	,	PUNCT
ajst-31456	240	19	and	and	CCONJ
ajst-31456	240	20	m.	m.	PROPN
ajst-31456	240	21	s.	s.	PROPN
ajst-31456	240	22	hossain	hossain	PROPN
ajst-31456	240	23	,	,	PUNCT
ajst-31456	240	24	“	"	PUNCT
ajst-31456	240	25	an	an	DET
ajst-31456	240	26	effective	effective	ADJ
ajst-31456	240	27	data	datum	NOUN
ajst-31456	240	28	driven	drive	VERB
ajst-31456	240	29	approach	approach	NOUN
ajst-31456	240	30	to	to	PART
ajst-31456	240	31	predict	predict	VERB
ajst-31456	240	32	bike	bike	NOUN
ajst-31456	240	33	rental	rental	NOUN
ajst-31456	240	34	demand	demand	NOUN
ajst-31456	240	35	,	,	PUNCT
ajst-31456	240	36	”	"	PUNCT
ajst-31456	240	37	in	in	ADP
ajst-31456	240	38	2023	2023	NUM
ajst-31456	240	39	5th	5th	ADJ
ajst-31456	240	40	international	international	ADJ
ajst-31456	240	41	conference	conference	NOUN
ajst-31456	240	42	on	on	ADP
ajst-31456	240	43	sustainable	sustainable	ADJ
ajst-31456	240	44	technologies	technology	NOUN
ajst-31456	240	45	for	for	ADP
ajst-31456	240	46	industry	industry	NOUN
ajst-31456	240	47	5.0	5.0	NUM
ajst-31456	240	48	(	(	PUNCT
ajst-31456	240	49	sti	sti	PROPN
ajst-31456	240	50	)	)	PUNCT
ajst-31456	240	51	,	,	PUNCT
ajst-31456	240	52	2023	2023	NUM
ajst-31456	240	53	,	,	PUNCT
ajst-31456	240	54	pp	pp	ADJ
ajst-31456	240	55	.	.	PUNCT
ajst-31456	241	1	1	1	NUM
ajst-31456	241	2	–	–	PUNCT
ajst-31456	241	3	5	5	NUM
ajst-31456	241	4	.	.	PUNCT
ajst-31456	242	1	[	[	X
ajst-31456	242	2	3	3	NUM
ajst-31456	242	3	]	]	PUNCT
ajst-31456	242	4	m.	m.	NOUN
ajst-31456	242	5	j.	j.	PROPN
ajst-31456	242	6	a.	a.	PROPN
ajst-31456	242	7	shanto	shanto	PROPN
ajst-31456	242	8	,	,	PUNCT
ajst-31456	242	9	r.	r.	PROPN
ajst-31456	242	10	akter	akter	PROPN
ajst-31456	242	11	,	,	PUNCT
ajst-31456	242	12	d.	d.	PROPN
ajst-31456	242	13	s.	s.	PROPN
ajst-31456	242	14	kim	kim	PROPN
ajst-31456	242	15	,	,	PUNCT
ajst-31456	242	16	and	and	CCONJ
ajst-31456	242	17	t.	t.	PROPN
ajst-31456	242	18	jun	jun	PROPN
ajst-31456	242	19	,	,	PUNCT
ajst-31456	242	20	“	"	PUNCT
ajst-31456	242	21	predicting	predict	VERB
ajst-31456	242	22	bikesharing	bikeshare	VERB
ajst-31456	242	23	demand	demand	NOUN
ajst-31456	242	24	:	:	PUNCT
ajst-31456	242	25	a	a	DET
ajst-31456	242	26	machine	machine	NOUN
ajst-31456	242	27	learning	learn	VERB
ajst-31456	242	28	approach	approach	NOUN
ajst-31456	242	29	for	for	ADP
ajst-31456	242	30	urban	urban	ADJ
ajst-31456	242	31	mobility	mobility	NOUN
ajst-31456	242	32	analysis	analysis	NOUN
ajst-31456	242	33	,	,	PUNCT
ajst-31456	242	34	”	"	PUNCT
ajst-31456	242	35	in	in	ADP
ajst-31456	242	36	2023	2023	NUM
ajst-31456	242	37	14th	14th	ADJ
ajst-31456	242	38	international	international	ADJ
ajst-31456	242	39	conference	conference	NOUN
ajst-31456	242	40	on	on	ADP
ajst-31456	242	41	information	information	NOUN
ajst-31456	242	42	and	and	CCONJ
ajst-31456	242	43	communication	communication	NOUN
ajst-31456	242	44	technology	technology	NOUN
ajst-31456	242	45	convergence	convergence	NOUN
ajst-31456	242	46	(	(	PUNCT
ajst-31456	242	47	ictc	ictc	NOUN
ajst-31456	242	48	)	)	PUNCT
ajst-31456	242	49	,	,	PUNCT
ajst-31456	242	50	2023	2023	NUM
ajst-31456	242	51	,	,	PUNCT
ajst-31456	242	52	pp	pp	ADJ
ajst-31456	242	53	.	.	PUNCT
ajst-31456	243	1	1079–1081	1079–1081	NUM
ajst-31456	243	2	.	.	PUNCT
ajst-31456	244	1	[	[	X
ajst-31456	244	2	4	4	NUM
ajst-31456	244	3	]	]	PUNCT
ajst-31456	244	4	a.	a.	NOUN
ajst-31456	244	5	kealy	kealy	PROPN
ajst-31456	244	6	and	and	CCONJ
ajst-31456	244	7	j.	j.	PROPN
ajst-31456	244	8	wu	wu	PROPN
ajst-31456	244	9	,	,	PUNCT
ajst-31456	244	10	“	"	PUNCT
ajst-31456	244	11	safety	safety	NOUN
ajst-31456	244	12	challenges	challenge	NOUN
ajst-31456	244	13	and	and	CCONJ
ajst-31456	244	14	solutions	solution	NOUN
ajst-31456	244	15	in	in	ADP
ajst-31456	244	16	bikesharing	bikesharing	NOUN
ajst-31456	244	17	systems	system	NOUN
ajst-31456	244	18	,	,	PUNCT
ajst-31456	244	19	”	"	PUNCT
ajst-31456	244	20	in	in	ADP
ajst-31456	244	21	2021	2021	NUM
ajst-31456	244	22	ieee	ieee	NOUN
ajst-31456	244	23	18th	18th	ADJ
ajst-31456	244	24	international	international	ADJ
ajst-31456	244	25	conference	conference	NOUN
ajst-31456	244	26	on	on	ADP
ajst-31456	244	27	mobile	mobile	ADJ
ajst-31456	244	28	ad	ad	X
ajst-31456	244	29	hoc	hoc	X
ajst-31456	244	30	and	and	CCONJ
ajst-31456	244	31	smart	smart	ADJ
ajst-31456	244	32	systems	system	NOUN
ajst-31456	244	33	(	(	PUNCT
ajst-31456	244	34	mass	mass	PROPN
ajst-31456	244	35	)	)	PUNCT
ajst-31456	244	36	,	,	PUNCT
ajst-31456	244	37	2021	2021	NUM
ajst-31456	244	38	,	,	PUNCT
ajst-31456	244	39	pp	pp	ADJ
ajst-31456	244	40	.	.	PUNCT
ajst-31456	245	1	651	651	NUM
ajst-31456	245	2	–	–	PUNCT
ajst-31456	245	3	656	656	NUM
ajst-31456	245	4	.	.	PUNCT
ajst-31456	246	1	[	[	X
ajst-31456	246	2	5	5	NUM
ajst-31456	246	3	]	]	PUNCT
ajst-31456	246	4	a.	a.	PROPN
ajst-31456	246	5	s.	s.	PROPN
ajst-31456	246	6	patel	patel	PROPN
ajst-31456	246	7	,	,	PUNCT
ajst-31456	246	8	m.	m.	NOUN
ajst-31456	246	9	ojha	ojha	PROPN
ajst-31456	246	10	,	,	PUNCT
ajst-31456	246	11	m.	m.	NOUN
ajst-31456	246	12	rani	rani	PROPN
ajst-31456	246	13	,	,	PUNCT
ajst-31456	246	14	a.	a.	PROPN
ajst-31456	246	15	khare	khare	PROPN
ajst-31456	246	16	,	,	PUNCT
ajst-31456	246	17	o.	o.	PROPN
ajst-31456	246	18	p.	p.	PROPN
ajst-31456	246	19	vyas	vyas	PROPN
ajst-31456	246	20	,	,	PUNCT
ajst-31456	246	21	and	and	CCONJ
ajst-31456	246	22	r.	r.	PROPN
ajst-31456	246	23	vyas	vyas	PROPN
ajst-31456	246	24	,	,	PUNCT
ajst-31456	246	25	“	"	PUNCT
ajst-31456	246	26	ontology	ontology	NOUN
ajst-31456	246	27	-	-	PUNCT
ajst-31456	246	28	based	base	VERB
ajst-31456	246	29	multi	multi	ADJ
ajst-31456	246	30	-	-	ADJ
ajst-31456	246	31	agent	agent	ADJ
ajst-31456	246	32	smart	smart	ADJ
ajst-31456	246	33	bike	bike	NOUN
ajst-31456	246	34	sharing	sharing	NOUN
ajst-31456	246	35	system	system	NOUN
ajst-31456	246	36	(	(	PUNCT
ajst-31456	246	37	sbss	sbss	NOUN
ajst-31456	246	38	)	)	PUNCT
ajst-31456	246	39	,	,	PUNCT
ajst-31456	246	40	”	"	PUNCT
ajst-31456	246	41	in	in	ADP
ajst-31456	246	42	2018	2018	NUM
ajst-31456	246	43	ieee	ieee	NOUN
ajst-31456	246	44	international	international	ADJ
ajst-31456	246	45	conference	conference	NOUN
ajst-31456	246	46	on	on	ADP
ajst-31456	246	47	smart	smart	ADJ
ajst-31456	246	48	computing	computing	NOUN
ajst-31456	246	49	(	(	PUNCT
ajst-31456	246	50	smartcomp	smartcomp	NOUN
ajst-31456	246	51	)	)	PUNCT
ajst-31456	246	52	,	,	PUNCT
ajst-31456	246	53	2018	2018	NUM
ajst-31456	246	54	,	,	PUNCT
ajst-31456	246	55	pp	pp	ADV
ajst-31456	246	56	.	.	PUNCT
ajst-31456	247	1	417–422	417–422	NUM
ajst-31456	247	2	.	.	PUNCT
ajst-31456	248	1	[	[	X
ajst-31456	248	2	6	6	NUM
ajst-31456	248	3	]	]	PUNCT
ajst-31456	248	4	a.	a.	NOUN
ajst-31456	248	5	jaber	jaber	PROPN
ajst-31456	248	6	,	,	PUNCT
ajst-31456	248	7	b.	b.	PROPN
ajst-31456	248	8	csonka	csonka	PROPN
ajst-31456	248	9	,	,	PUNCT
ajst-31456	248	10	and	and	CCONJ
ajst-31456	248	11	j.	j.	PROPN
ajst-31456	248	12	juha´sz	juha´sz	PROPN
ajst-31456	248	13	,	,	PUNCT
ajst-31456	248	14	“	"	PUNCT
ajst-31456	248	15	long	long	ADJ
ajst-31456	248	16	term	term	NOUN
ajst-31456	248	17	time	time	NOUN
ajst-31456	248	18	series	series	PROPN
ajst-31456	248	19	prediction	prediction	NOUN
ajst-31456	248	20	of	of	ADP
ajst-31456	248	21	bike	bike	NOUN
ajst-31456	248	22	sharing	sharing	NOUN
ajst-31456	248	23	trips	trip	NOUN
ajst-31456	248	24	:	:	PUNCT
ajst-31456	248	25	a	a	DET
ajst-31456	248	26	cast	cast	NOUN
ajst-31456	248	27	study	study	NOUN
ajst-31456	248	28	of	of	ADP
ajst-31456	248	29	budapest	budapest	PROPN
ajst-31456	248	30	city	city	NOUN
ajst-31456	248	31	,	,	PUNCT
ajst-31456	248	32	”	"	PUNCT
ajst-31456	248	33	in	in	ADP
ajst-31456	248	34	2022	2022	NUM
ajst-31456	248	35	smart	smart	ADJ
ajst-31456	248	36	city	city	NOUN
ajst-31456	248	37	symposium	symposium	NOUN
ajst-31456	248	38	prague	prague	NOUN
ajst-31456	248	39	(	(	PUNCT
ajst-31456	248	40	scsp	scsp	PROPN
ajst-31456	248	41	)	)	PUNCT
ajst-31456	248	42	,	,	PUNCT
ajst-31456	248	43	2022	2022	NUM
ajst-31456	248	44	,	,	PUNCT
ajst-31456	248	45	pp	pp	ADJ
ajst-31456	248	46	.	.	PUNCT
ajst-31456	249	1	1–5	1–5	X
ajst-31456	249	2	.	.	PUNCT
ajst-31456	250	1	[	[	X
ajst-31456	250	2	7	7	X
ajst-31456	250	3	]	]	PUNCT
ajst-31456	250	4	x.	x.	NOUN
ajst-31456	250	5	han	han	PROPN
ajst-31456	250	6	,	,	PUNCT
ajst-31456	250	7	p.	p.	PROPN
ajst-31456	250	8	wang	wang	PROPN
ajst-31456	250	9	,	,	PUNCT
ajst-31456	250	10	j.	j.	PROPN
ajst-31456	250	11	gao	gao	PROPN
ajst-31456	250	12	,	,	PUNCT
ajst-31456	250	13	m.	m.	NOUN
ajst-31456	250	14	shah	shah	PROPN
ajst-31456	250	15	,	,	PUNCT
ajst-31456	250	16	r.	r.	PROPN
ajst-31456	250	17	k.	k.	PROPN
ajst-31456	250	18	m.	m.	PROPN
ajst-31456	250	19	ambulgekar	ambulgekar	PROPN
ajst-31456	250	20	,	,	PUNCT
ajst-31456	250	21	a.	a.	NOUN
ajst-31456	250	22	jarandikar	jarandikar	PROPN
ajst-31456	250	23	,	,	PUNCT
ajst-31456	250	24	and	and	CCONJ
ajst-31456	250	25	s.	s.	PROPN
ajst-31456	250	26	dhar	dhar	PROPN
ajst-31456	250	27	,	,	PUNCT
ajst-31456	250	28	“	"	PUNCT
ajst-31456	250	29	bike	bike	NOUN
ajst-31456	250	30	sharing	sharing	NOUN
ajst-31456	250	31	data	datum	NOUN
ajst-31456	250	32	analytics	analytic	NOUN
ajst-31456	250	33	for	for	ADP
ajst-31456	250	34	silicon	silicon	NOUN
ajst-31456	250	35	valley	valley	PROPN
ajst-31456	250	36	in	in	ADP
ajst-31456	250	37	usa	usa	PROPN
ajst-31456	250	38	,	,	PUNCT
ajst-31456	250	39	”	"	PUNCT
ajst-31456	250	40	in	in	ADP
ajst-31456	250	41	2017	2017	NUM
ajst-31456	250	42	ieee	ieee	NOUN
ajst-31456	250	43	smartworld	smartworld	NOUN
ajst-31456	250	44	,	,	PUNCT
ajst-31456	250	45	ubiquitous	ubiquitous	ADJ
ajst-31456	250	46	intelligence	intelligence	NOUN
ajst-31456	250	47	&	&	CCONJ
ajst-31456	250	48	computing	computing	PROPN
ajst-31456	250	49	,	,	PUNCT
ajst-31456	250	50	advanced	advanced	ADJ
ajst-31456	250	51	trusted	trust	VERB
ajst-31456	250	52	computed	compute	VERB
ajst-31456	250	53	,	,	PUNCT
ajst-31456	250	54	scalable	scalable	ADJ
ajst-31456	250	55	computing	computing	NOUN
ajst-31456	250	56	communications	communication	NOUN
ajst-31456	250	57	,	,	PUNCT
ajst-31456	250	58	cloud	cloud	ADJ
ajst-31456	250	59	big	big	ADJ
ajst-31456	250	60	data	datum	NOUN
ajst-31456	250	61	computing	computing	NOUN
ajst-31456	250	62	,	,	PUNCT
ajst-31456	250	63	internet	internet	NOUN
ajst-31456	250	64	of	of	ADP
ajst-31456	250	65	people	people	NOUN
ajst-31456	250	66	and	and	CCONJ
ajst-31456	250	67	smart	smart	ADJ
ajst-31456	250	68	city	city	NOUN
ajst-31456	250	69	innovation	innovation	NOUN
ajst-31456	250	70	(	(	PUNCT
ajst-31456	250	71	smartworld	smartworld	NOUN
ajst-31456	250	72	/	/	SYM
ajst-31456	250	73	scalcom	scalcom	PROPN
ajst-31456	250	74	/	/	SYM
ajst-31456	250	75	uic	uic	PROPN
ajst-31456	250	76	/	/	SYM
ajst-31456	250	77	atc	atc	PROPN
ajst-31456	250	78	/	/	SYM
ajst-31456	250	79	cbdcom	cbdcom	PROPN
ajst-31456	250	80	/	/	SYM
ajst-31456	250	81	iop	iop	PROPN
ajst-31456	250	82	/	/	SYM
ajst-31456	250	83	sci	sci	PROPN
ajst-31456	250	84	)	)	PUNCT
ajst-31456	250	85	,	,	PUNCT
ajst-31456	250	86	2017	2017	NUM
ajst-31456	250	87	,	,	PUNCT
ajst-31456	250	88	pp	pp	ADJ
ajst-31456	250	89	.	.	PUNCT
ajst-31456	251	1	1–9	1–9	NOUN
ajst-31456	251	2	.	.	PUNCT
ajst-31456	252	1	[	[	X
ajst-31456	252	2	8	8	NUM
ajst-31456	252	3	]	]	PUNCT
ajst-31456	252	4	z.	z.	PROPN
ajst-31456	252	5	jiao	jiao	PROPN
ajst-31456	252	6	,	,	PUNCT
ajst-31456	252	7	h.	h.	PROPN
ajst-31456	252	8	jin	jin	PROPN
ajst-31456	252	9	,	,	PUNCT
ajst-31456	252	10	b.	b.	PROPN
ajst-31456	252	11	liu	liu	PROPN
ajst-31456	252	12	,	,	PUNCT
ajst-31456	252	13	and	and	CCONJ
ajst-31456	252	14	z.	z.	PROPN
ajst-31456	252	15	zhang	zhang	PROPN
ajst-31456	252	16	,	,	PUNCT
ajst-31456	252	17	“	"	PUNCT
ajst-31456	252	18	short	short	ADJ
ajst-31456	252	19	-	-	PUNCT
ajst-31456	252	20	term	term	NOUN
ajst-31456	252	21	demand	demand	NOUN
ajst-31456	252	22	forecasting	forecasting	NOUN
ajst-31456	252	23	of	of	ADP
ajst-31456	252	24	shared	share	VERB
ajst-31456	252	25	bicycles	bicycle	NOUN
ajst-31456	252	26	driven	drive	VERB
ajst-31456	252	27	by	by	ADP
ajst-31456	252	28	big	big	ADJ
ajst-31456	252	29	data	datum	NOUN
ajst-31456	252	30	:	:	PUNCT
ajst-31456	252	31	a	a	DET
ajst-31456	252	32	comparative	comparative	ADJ
ajst-31456	252	33	analysis	analysis	NOUN
ajst-31456	252	34	of	of	ADP
ajst-31456	252	35	machine	machine	NOUN
ajst-31456	252	36	learning	learning	NOUN
ajst-31456	252	37	models	model	NOUN
ajst-31456	252	38	,	,	PUNCT
ajst-31456	252	39	”	"	PUNCT
ajst-31456	252	40	journal	journal	NOUN
ajst-31456	252	41	of	of	ADP
ajst-31456	252	42	business	business	NOUN
ajst-31456	252	43	economics	economic	NOUN
ajst-31456	252	44	,	,	PUNCT
ajst-31456	252	45	vol	vol	NOUN
ajst-31456	252	46	.	.	PROPN
ajst-31456	252	47	322	322	NUM
ajst-31456	252	48	,	,	PUNCT
ajst-31456	252	49	no	no	INTJ
ajst-31456	252	50	.	.	NOUN
ajst-31456	252	51	8	8	NUM
ajst-31456	252	52	,	,	PUNCT
ajst-31456	252	53	pp	pp	ADJ
ajst-31456	252	54	.	.	PUNCT
ajst-31456	253	1	16–25	16–25	NUM
ajst-31456	253	2	,	,	PUNCT
ajst-31456	253	3	2018	2018	NUM
ajst-31456	253	4	,	,	PUNCT
ajst-31456	254	1	[	[	X
ajst-31456	254	2	in	in	ADP
ajst-31456	254	3	chinese	chinese	PROPN
ajst-31456	254	4	]	]	PUNCT
ajst-31456	254	5	.	.	PUNCT
ajst-31456	255	1	[	[	X
ajst-31456	255	2	9	9	NUM
ajst-31456	255	3	]	]	PUNCT
ajst-31456	255	4	h.	h.	PROPN
ajst-31456	255	5	yang	yang	PROPN
ajst-31456	255	6	,	,	PUNCT
ajst-31456	255	7	x.	x.	PROPN
ajst-31456	255	8	zhang	zhang	PROPN
ajst-31456	255	9	,	,	PUNCT
ajst-31456	255	10	l.	l.	PROPN
ajst-31456	255	11	zhong	zhong	PROPN
ajst-31456	255	12	,	,	PUNCT
ajst-31456	255	13	s.	s.	PROPN
ajst-31456	255	14	li	li	PROPN
ajst-31456	255	15	,	,	PUNCT
ajst-31456	255	16	x.	x.	PROPN
ajst-31456	255	17	zhang	zhang	PROPN
ajst-31456	255	18	,	,	PUNCT
ajst-31456	255	19	and	and	CCONJ
ajst-31456	255	20	j.	j.	PROPN
ajst-31456	255	21	hu	hu	PROPN
ajst-31456	255	22	,	,	PUNCT
ajst-31456	255	23	“	"	PUNCT
ajst-31456	255	24	short	short	ADJ
ajst-31456	255	25	-	-	PUNCT
ajst-31456	255	26	term	term	NOUN
ajst-31456	255	27	demand	demand	NOUN
ajst-31456	255	28	forecasting	forecasting	NOUN
ajst-31456	255	29	for	for	ADP
ajst-31456	255	30	bike	bike	NOUN
ajst-31456	255	31	sharing	sharing	NOUN
ajst-31456	255	32	system	system	NOUN
ajst-31456	255	33	based	base	VERB
ajst-31456	255	34	on	on	ADP
ajst-31456	255	35	machine	machine	NOUN
ajst-31456	255	36	learning	learning	NOUN
ajst-31456	255	37	,	,	PUNCT
ajst-31456	255	38	”	"	PUNCT
ajst-31456	255	39	in	in	ADP
ajst-31456	255	40	2019	2019	NUM
ajst-31456	255	41	5th	5th	ADJ
ajst-31456	255	42	international	international	ADJ
ajst-31456	255	43	conference	conference	NOUN
ajst-31456	255	44	on	on	ADP
ajst-31456	255	45	transportation	transportation	NOUN
ajst-31456	255	46	information	information	NOUN
ajst-31456	255	47	and	and	CCONJ
ajst-31456	255	48	safety	safety	NOUN
ajst-31456	255	49	(	(	PUNCT
ajst-31456	255	50	ictis	ictis	PROPN
ajst-31456	255	51	)	)	PUNCT
ajst-31456	255	52	,	,	PUNCT
ajst-31456	255	53	2019	2019	NUM
ajst-31456	255	54	,	,	PUNCT
ajst-31456	255	55	pp	pp	ADJ
ajst-31456	255	56	.	.	PUNCT
ajst-31456	256	1	1295–1300	1295–1300	NUM
ajst-31456	256	2	.	.	PUNCT
ajst-31456	257	1	[	[	X
ajst-31456	257	2	10	10	NUM
ajst-31456	257	3	]	]	PUNCT
ajst-31456	257	4	m.	m.	NOUN
ajst-31456	257	5	h.	h.	PROPN
ajst-31456	257	6	almannaa	almannaa	PROPN
ajst-31456	257	7	,	,	PUNCT
ajst-31456	257	8	m.	m.	NOUN
ajst-31456	257	9	elhenawy	elhenawy	PROPN
ajst-31456	257	10	,	,	PUNCT
ajst-31456	257	11	f.	f.	PROPN
ajst-31456	257	12	guo	guo	PROPN
ajst-31456	257	13	,	,	PUNCT
ajst-31456	257	14	and	and	CCONJ
ajst-31456	257	15	h.	h.	PROPN
ajst-31456	257	16	a.	a.	PROPN
ajst-31456	257	17	rakha	rakha	PROPN
ajst-31456	257	18	,	,	PUNCT
ajst-31456	257	19	“	"	PUNCT
ajst-31456	257	20	incremental	incremental	ADJ
ajst-31456	257	21	learning	learning	NOUN
ajst-31456	257	22	models	model	NOUN
ajst-31456	257	23	of	of	ADP
ajst-31456	257	24	bike	bike	NOUN
ajst-31456	257	25	counts	count	NOUN
ajst-31456	257	26	at	at	ADP
ajst-31456	257	27	bike	bike	NOUN
ajst-31456	257	28	sharing	sharing	NOUN
ajst-31456	257	29	systems	system	NOUN
ajst-31456	257	30	,	,	PUNCT
ajst-31456	257	31	”	"	PUNCT
ajst-31456	257	32	in	in	ADP
ajst-31456	257	33	2018	2018	NUM
ajst-31456	257	34	21st	21st	NOUN
ajst-31456	257	35	international	international	ADJ
ajst-31456	257	36	conference	conference	NOUN
ajst-31456	257	37	on	on	ADP
ajst-31456	257	38	intelligent	intelligent	ADJ
ajst-31456	257	39	transportation	transportation	NOUN
ajst-31456	257	40	systems	system	NOUN
ajst-31456	257	41	(	(	PUNCT
ajst-31456	257	42	itsc	itsc	PROPN
ajst-31456	257	43	)	)	PUNCT
ajst-31456	257	44	,	,	PUNCT
ajst-31456	257	45	2018	2018	NUM
ajst-31456	257	46	,	,	PUNCT
ajst-31456	257	47	pp	pp	ADJ
ajst-31456	257	48	.	.	PUNCT
ajst-31456	258	1	3712–3717	3712–3717	NUM
ajst-31456	258	2	.	.	PUNCT
ajst-31456	259	1	[	[	X
ajst-31456	259	2	11	11	NUM
ajst-31456	259	3	]	]	X
ajst-31456	259	4	d.	d.	PROPN
ajst-31456	259	5	cao	cao	PROPN
ajst-31456	259	6	,	,	PUNCT
ajst-31456	259	7	s.	s.	PROPN
ajst-31456	259	8	fan	fan	PROPN
ajst-31456	259	9	,	,	PUNCT
ajst-31456	259	10	y.	y.	PROPN
ajst-31456	259	11	zhang	zhang	PROPN
ajst-31456	259	12	,	,	PUNCT
ajst-31456	259	13	and	and	CCONJ
ajst-31456	259	14	k.	k.	PROPN
ajst-31456	259	15	xia	xia	PROPN
ajst-31456	259	16	,	,	PUNCT
ajst-31456	259	17	“	"	PUNCT
ajst-31456	259	18	short	short	ADJ
ajst-31456	259	19	-	-	PUNCT
ajst-31456	259	20	term	term	NOUN
ajst-31456	259	21	demand	demand	NOUN
ajst-31456	259	22	forecasting	forecasting	NOUN
ajst-31456	259	23	of	of	ADP
ajst-31456	259	24	shared	share	VERB
ajst-31456	259	25	bicycles	bicycle	NOUN
ajst-31456	259	26	based	base	VERB
ajst-31456	259	27	on	on	ADP
ajst-31456	259	28	long	long	ADJ
ajst-31456	259	29	short	short	ADJ
ajst-31456	259	30	-	-	PUNCT
ajst-31456	259	31	term	term	NOUN
ajst-31456	259	32	memory	memory	NOUN
ajst-31456	259	33	neural	neural	ADJ
ajst-31456	259	34	network	network	NOUN
ajst-31456	259	35	model	model	NOUN
ajst-31456	259	36	,	,	PUNCT
ajst-31456	259	37	”	"	PUNCT
ajst-31456	259	38	science	science	NOUN
ajst-31456	259	39	technology	technology	NOUN
ajst-31456	259	40	and	and	CCONJ
ajst-31456	259	41	engineering	engineering	NOUN
ajst-31456	259	42	,	,	PUNCT
ajst-31456	259	43	vol	vol	NOUN
ajst-31456	259	44	.	.	PROPN
ajst-31456	259	45	20	20	NUM
ajst-31456	259	46	,	,	PUNCT
ajst-31456	259	47	no	no	INTJ
ajst-31456	259	48	.	.	NOUN
ajst-31456	259	49	20	20	NUM
ajst-31456	259	50	,	,	PUNCT
ajst-31456	259	51	pp	pp	ADJ
ajst-31456	259	52	.	.	PUNCT
ajst-31456	260	1	8344–8349	8344–8349	NUM
ajst-31456	260	2	,	,	PUNCT
ajst-31456	260	3	2020	2020	NUM
ajst-31456	260	4	,	,	PUNCT
ajst-31456	261	1	[	[	X
ajst-31456	261	2	in	in	ADP
ajst-31456	261	3	chinese	chinese	PROPN
ajst-31456	261	4	]	]	PUNCT
ajst-31456	261	5	.	.	PUNCT
ajst-31456	262	1	[	[	X
ajst-31456	262	2	12	12	NUM
ajst-31456	262	3	]	]	PUNCT
ajst-31456	262	4	x.	x.	PROPN
ajst-31456	262	5	xing	xing	PROPN
ajst-31456	262	6	,	,	PUNCT
ajst-31456	262	7	z.	z.	PROPN
ajst-31456	262	8	yin	yin	PROPN
ajst-31456	262	9	,	,	PUNCT
ajst-31456	262	10	and	and	CCONJ
ajst-31456	262	11	l.	l.	PROPN
ajst-31456	262	12	fang	fang	PROPN
ajst-31456	262	13	,	,	PUNCT
ajst-31456	262	14	“	"	PUNCT
ajst-31456	262	15	shared	share	VERB
ajst-31456	262	16	bicycle	bicycle	NOUN
ajst-31456	262	17	demand	demand	NOUN
ajst-31456	262	18	prediction	prediction	NOUN
ajst-31456	262	19	incorporating	incorporate	VERB
ajst-31456	262	20	multivariate	multivariate	NOUN
ajst-31456	262	21	meteorological	meteorological	ADJ
ajst-31456	262	22	factors	factor	NOUN
ajst-31456	262	23	,	,	PUNCT
ajst-31456	262	24	”	"	PUNCT
ajst-31456	262	25	intelligent	intelligent	ADJ
ajst-31456	262	26	computer	computer	NOUN
ajst-31456	262	27	and	and	CCONJ
ajst-31456	262	28	applications	application	NOUN
ajst-31456	262	29	,	,	PUNCT
ajst-31456	262	30	vol	vol	NOUN
ajst-31456	262	31	.	.	PROPN
ajst-31456	262	32	15	15	NUM
ajst-31456	262	33	,	,	PUNCT
ajst-31456	262	34	no	no	INTJ
ajst-31456	262	35	.	.	NOUN
ajst-31456	262	36	1	1	NUM
ajst-31456	262	37	,	,	PUNCT
ajst-31456	262	38	pp	pp	ADJ
ajst-31456	262	39	.	.	PUNCT
ajst-31456	262	40	178	178	NUM
ajst-31456	262	41	–	–	PUNCT
ajst-31456	262	42	186	186	NUM
ajst-31456	262	43	,	,	PUNCT
ajst-31456	262	44	2025	2025	NUM
ajst-31456	262	45	,	,	PUNCT
ajst-31456	263	1	[	[	X
ajst-31456	263	2	in	in	ADP
ajst-31456	263	3	chinese	chinese	PROPN
ajst-31456	263	4	]	]	PUNCT
ajst-31456	263	5	.	.	PUNCT
ajst-31456	264	1	[	[	X
ajst-31456	264	2	13	13	NUM
ajst-31456	264	3	]	]	X
ajst-31456	264	4	f.	f.	PROPN
ajst-31456	264	5	huang	huang	PROPN
ajst-31456	264	6	,	,	PUNCT
ajst-31456	264	7	s.	s.	PROPN
ajst-31456	264	8	qiao	qiao	PROPN
ajst-31456	264	9	,	,	PUNCT
ajst-31456	264	10	j.	j.	PROPN
ajst-31456	264	11	peng	peng	PROPN
ajst-31456	264	12	,	,	PUNCT
ajst-31456	264	13	and	and	CCONJ
ajst-31456	264	14	b.	b.	PROPN
ajst-31456	264	15	guo	guo	PROPN
ajst-31456	264	16	,	,	PUNCT
ajst-31456	264	17	“	"	PUNCT
ajst-31456	264	18	a	a	DET
ajst-31456	264	19	bimodal	bimodal	NOUN
ajst-31456	264	20	gaussian	gaussian	VERB
ajst-31456	264	21	inhomogeneous	inhomogeneous	ADJ
ajst-31456	264	22	poisson	poisson	NOUN
ajst-31456	264	23	algorithm	algorithm	NOUN
ajst-31456	264	24	for	for	ADP
ajst-31456	264	25	bike	bike	NOUN
ajst-31456	264	26	number	number	NOUN
ajst-31456	264	27	prediction	prediction	NOUN
ajst-31456	264	28	in	in	ADP
ajst-31456	264	29	a	a	DET
ajst-31456	264	30	bikesharing	bikeshare	VERB
ajst-31456	264	31	system	system	NOUN
ajst-31456	264	32	,	,	PUNCT
ajst-31456	264	33	”	"	PUNCT
ajst-31456	264	34	ieee	ieee	NOUN
ajst-31456	264	35	transactions	transaction	NOUN
ajst-31456	264	36	on	on	ADP
ajst-31456	264	37	intelligent	intelligent	ADJ
ajst-31456	264	38	transportation	transportation	NOUN
ajst-31456	264	39	systems	system	NOUN
ajst-31456	264	40	,	,	PUNCT
ajst-31456	264	41	vol	vol	NOUN
ajst-31456	264	42	.	.	PROPN
ajst-31456	264	43	20	20	NUM
ajst-31456	264	44	,	,	PUNCT
ajst-31456	264	45	no	no	INTJ
ajst-31456	264	46	.	.	NOUN
ajst-31456	264	47	8	8	NUM
ajst-31456	264	48	,	,	PUNCT
ajst-31456	264	49	pp	pp	ADJ
ajst-31456	264	50	.	.	PUNCT
ajst-31456	265	1	2848–2857	2848–2857	NUM
ajst-31456	265	2	,	,	PUNCT
ajst-31456	265	3	2019	2019	NUM
ajst-31456	265	4	.	.	PUNCT
ajst-31456	266	1	[	[	X
ajst-31456	266	2	14	14	NUM
ajst-31456	266	3	]	]	X
ajst-31456	266	4	y.	y.	PROPN
ajst-31456	266	5	li	li	PROPN
ajst-31456	266	6	and	and	CCONJ
ajst-31456	266	7	y.	y.	PROPN
ajst-31456	266	8	zheng	zheng	PROPN
ajst-31456	266	9	,	,	PUNCT
ajst-31456	266	10	“	"	PUNCT
ajst-31456	266	11	citywide	citywide	ADJ
ajst-31456	266	12	bike	bike	NOUN
ajst-31456	266	13	usage	usage	NOUN
ajst-31456	266	14	prediction	prediction	NOUN
ajst-31456	266	15	in	in	ADP
ajst-31456	266	16	a	a	DET
ajst-31456	266	17	bike	bike	NOUN
ajst-31456	266	18	sharing	sharing	NOUN
ajst-31456	266	19	system	system	NOUN
ajst-31456	266	20	,	,	PUNCT
ajst-31456	266	21	”	"	PUNCT
ajst-31456	266	22	ieee	ieee	NOUN
ajst-31456	266	23	transactions	transaction	NOUN
ajst-31456	266	24	on	on	ADP
ajst-31456	266	25	knowledge	knowledge	NOUN
ajst-31456	266	26	and	and	CCONJ
ajst-31456	266	27	data	datum	NOUN
ajst-31456	266	28	engineering	engineering	NOUN
ajst-31456	266	29	,	,	PUNCT
ajst-31456	266	30	vol	vol	NOUN
ajst-31456	266	31	.	.	PROPN
ajst-31456	267	1	32	32	NUM
ajst-31456	267	2	,	,	PUNCT
ajst-31456	267	3	no	no	INTJ
ajst-31456	267	4	.	.	NOUN
ajst-31456	267	5	6	6	NUM
ajst-31456	267	6	,	,	PUNCT
ajst-31456	267	7	pp	pp	ADJ
ajst-31456	267	8	.	.	PUNCT
ajst-31456	268	1	1079–1091	1079–1091	NUM
ajst-31456	268	2	,	,	PUNCT
ajst-31456	268	3	2020	2020	NUM
ajst-31456	268	4	.	.	PUNCT
ajst-31456	269	1	[	[	X
ajst-31456	269	2	15	15	NUM
ajst-31456	269	3	]	]	X
ajst-31456	269	4	s.	s.	PROPN
ajst-31456	269	5	feng	feng	PROPN
ajst-31456	269	6	,	,	PUNCT
ajst-31456	269	7	h.	h.	PROPN
ajst-31456	269	8	chen	chen	PROPN
ajst-31456	269	9	,	,	PUNCT
ajst-31456	269	10	c.	c.	PROPN
ajst-31456	269	11	du	du	PROPN
ajst-31456	269	12	,	,	PUNCT
ajst-31456	269	13	j.	j.	PROPN
ajst-31456	269	14	li	li	PROPN
ajst-31456	269	15	,	,	PUNCT
ajst-31456	269	16	and	and	CCONJ
ajst-31456	269	17	n.	n.	PROPN
ajst-31456	269	18	jing	jing	PROPN
ajst-31456	269	19	,	,	PUNCT
ajst-31456	269	20	“	"	PUNCT
ajst-31456	269	21	a	a	DET
ajst-31456	269	22	hierarchical	hierarchical	ADJ
ajst-31456	269	23	demand	demand	NOUN
ajst-31456	269	24	prediction	prediction	NOUN
ajst-31456	269	25	method	method	NOUN
ajst-31456	269	26	with	with	ADP
ajst-31456	269	27	station	station	NOUN
ajst-31456	269	28	clustering	cluster	VERB
ajst-31456	269	29	for	for	ADP
ajst-31456	269	30	bike	bike	NOUN
ajst-31456	269	31	sharing	sharing	NOUN
ajst-31456	269	32	system	system	NOUN
ajst-31456	269	33	,	,	PUNCT
ajst-31456	269	34	”	"	PUNCT
ajst-31456	269	35	in	in	ADP
ajst-31456	269	36	2018	2018	NUM
ajst-31456	269	37	ieee	ieee	NOUN
ajst-31456	269	38	third	third	ADJ
ajst-31456	269	39	international	international	ADJ
ajst-31456	269	40	conference	conference	NOUN
ajst-31456	269	41	on	on	ADP
ajst-31456	269	42	data	datum	NOUN
ajst-31456	269	43	science	science	NOUN
ajst-31456	269	44	in	in	ADP
ajst-31456	269	45	cyberspace	cyberspace	NOUN
ajst-31456	269	46	(	(	PUNCT
ajst-31456	269	47	dsc	dsc	NOUN
ajst-31456	269	48	)	)	PUNCT
ajst-31456	269	49	,	,	PUNCT
ajst-31456	269	50	2018	2018	NUM
ajst-31456	269	51	,	,	PUNCT
ajst-31456	269	52	pp	pp	ADJ
ajst-31456	269	53	.	.	PUNCT
ajst-31456	270	1	829–836	829–836	NUM
ajst-31456	270	2	.	.	PUNCT
ajst-31456	271	1	[	[	X
ajst-31456	271	2	16	16	NUM
ajst-31456	271	3	]	]	PUNCT
ajst-31456	271	4	m.	m.	NOUN
ajst-31456	271	5	he	he	PRON
ajst-31456	271	6	,	,	PUNCT
ajst-31456	271	7	x.	x.	PROPN
ajst-31456	271	8	xue	xue	PROPN
ajst-31456	271	9	,	,	PUNCT
ajst-31456	271	10	x.	x.	PROPN
ajst-31456	271	11	zhang	zhang	PROPN
ajst-31456	271	12	,	,	PUNCT
ajst-31456	271	13	and	and	CCONJ
ajst-31456	271	14	c.	c.	PROPN
ajst-31456	271	15	zhou	zhou	PROPN
ajst-31456	271	16	,	,	PUNCT
ajst-31456	271	17	“	"	PUNCT
ajst-31456	271	18	a	a	DET
ajst-31456	271	19	bike	bike	NOUN
ajst-31456	271	20	-	-	PUNCT
ajst-31456	271	21	sharing	share	VERB
ajst-31456	271	22	demand	demand	NOUN
ajst-31456	271	23	predicting	predict	VERB
ajst-31456	271	24	model	model	NOUN
ajst-31456	271	25	with	with	ADP
ajst-31456	271	26	integrating	integrate	VERB
ajst-31456	271	27	temporal	temporal	ADJ
ajst-31456	271	28	convolutional	convolutional	ADJ
ajst-31456	271	29	network	network	NOUN
ajst-31456	271	30	and	and	CCONJ
ajst-31456	271	31	self	self	NOUN
ajst-31456	271	32	-	-	PUNCT
ajst-31456	271	33	attention	attention	NOUN
ajst-31456	271	34	,	,	PUNCT
ajst-31456	271	35	”	"	PUNCT
ajst-31456	271	36	in	in	ADP
ajst-31456	271	37	2021	2021	NUM
ajst-31456	271	38	international	international	ADJ
ajst-31456	271	39	conference	conference	NOUN
ajst-31456	271	40	on	on	ADP
ajst-31456	271	41	electronic	electronic	ADJ
ajst-31456	271	42	information	information	NOUN
ajst-31456	271	43	engineering	engineering	NOUN
ajst-31456	271	44	and	and	CCONJ
ajst-31456	271	45	computer	computer	NOUN
ajst-31456	271	46	science	science	NOUN
ajst-31456	271	47	(	(	PUNCT
ajst-31456	271	48	eiecs	eiecs	PROPN
ajst-31456	271	49	)	)	PUNCT
ajst-31456	271	50	,	,	PUNCT
ajst-31456	271	51	2021	2021	NUM
ajst-31456	271	52	,	,	PUNCT
ajst-31456	271	53	pp	pp	ADJ
ajst-31456	271	54	.	.	PUNCT
ajst-31456	272	1	278	278	NUM
ajst-31456	272	2	–	–	PUNCT
ajst-31456	272	3	281	281	NUM
ajst-31456	272	4	.	.	PUNCT
ajst-31456	273	1	[	[	X
ajst-31456	273	2	17	17	NUM
ajst-31456	273	3	]	]	X
ajst-31456	273	4	h.	h.	PROPN
ajst-31456	273	5	yang	yang	PROPN
ajst-31456	273	6	,	,	PUNCT
ajst-31456	273	7	s.	s.	PROPN
ajst-31456	273	8	m.	m.	PROPN
ajst-31456	273	9	raza	raza	PROPN
ajst-31456	273	10	,	,	PUNCT
ajst-31456	273	11	d.	d.	PROPN
ajst-31456	273	12	t.	t.	PROPN
ajst-31456	273	13	le	le	PROPN
ajst-31456	273	14	,	,	PUNCT
ajst-31456	273	15	d.	d.	PROPN
ajst-31456	273	16	s.	s.	PROPN
ajst-31456	273	17	kim	kim	PROPN
ajst-31456	273	18	,	,	PUNCT
ajst-31456	273	19	and	and	CCONJ
ajst-31456	273	20	h.	h.	PROPN
ajst-31456	273	21	choo	choo	PROPN
ajst-31456	273	22	,	,	PUNCT
ajst-31456	273	23	“	"	PUNCT
ajst-31456	273	24	dual	dual	ADJ
ajst-31456	273	25	branch	branch	NOUN
ajst-31456	273	26	neural	neural	ADJ
ajst-31456	273	27	networks	network	NOUN
ajst-31456	273	28	for	for	ADP
ajst-31456	273	29	predicting	predict	VERB
ajst-31456	273	30	shared	shared	ADJ
ajst-31456	273	31	bikes	bike	NOUN
ajst-31456	273	32	,	,	PUNCT
ajst-31456	273	33	”	"	PUNCT
ajst-31456	273	34	in	in	ADP
ajst-31456	273	35	2023	2023	NUM
ajst-31456	273	36	17th	17th	ADJ
ajst-31456	273	37	international	international	ADJ
ajst-31456	273	38	conference	conference	NOUN
ajst-31456	273	39	on	on	ADP
ajst-31456	273	40	ubiquitous	ubiquitous	ADJ
ajst-31456	273	41	information	information	NOUN
ajst-31456	273	42	management	management	NOUN
ajst-31456	273	43	and	and	CCONJ
ajst-31456	273	44	communication	communication	NOUN
ajst-31456	273	45	(	(	PUNCT
ajst-31456	273	46	imcom	imcom	PROPN
ajst-31456	273	47	)	)	PUNCT
ajst-31456	273	48	,	,	PUNCT
ajst-31456	273	49	2023	2023	NUM
ajst-31456	273	50	,	,	PUNCT
ajst-31456	273	51	pp	pp	ADV
ajst-31456	273	52	.	.	PUNCT
ajst-31456	274	1	1–4	1–4	NUM
ajst-31456	274	2	.	.	PUNCT
ajst-31456	275	1	[	[	X
ajst-31456	275	2	18	18	NUM
ajst-31456	275	3	]	]	X
ajst-31456	275	4	j.	j.	PROPN
ajst-31456	275	5	gu	gu	PROPN
ajst-31456	275	6	,	,	PUNCT
ajst-31456	275	7	q.	q.	PROPN
ajst-31456	275	8	zhou	zhou	PROPN
ajst-31456	275	9	,	,	PUNCT
ajst-31456	275	10	j.	j.	PROPN
ajst-31456	275	11	yang	yang	PROPN
ajst-31456	275	12	,	,	PUNCT
ajst-31456	275	13	y.	y.	PROPN
ajst-31456	275	14	liu	liu	PROPN
ajst-31456	275	15	,	,	PUNCT
ajst-31456	275	16	f.	f.	PROPN
ajst-31456	275	17	zhuang	zhuang	PROPN
ajst-31456	275	18	,	,	PUNCT
ajst-31456	275	19	y.	y.	PROPN
ajst-31456	275	20	zhao	zhao	PROPN
ajst-31456	275	21	,	,	PUNCT
ajst-31456	275	22	and	and	CCONJ
ajst-31456	275	23	h.	h.	PROPN
ajst-31456	275	24	xiong	xiong	PROPN
ajst-31456	275	25	,	,	PUNCT
ajst-31456	275	26	“	"	PUNCT
ajst-31456	275	27	exploiting	exploit	VERB
ajst-31456	275	28	interpretable	interpretable	ADJ
ajst-31456	275	29	patterns	pattern	NOUN
ajst-31456	275	30	for	for	ADP
ajst-31456	275	31	flow	flow	NOUN
ajst-31456	275	32	prediction	prediction	NOUN
ajst-31456	275	33	in	in	ADP
ajst-31456	275	34	dockless	dockless	ADJ
ajst-31456	275	35	bike	bike	NOUN
ajst-31456	275	36	sharing	sharing	NOUN
ajst-31456	275	37	systems	system	NOUN
ajst-31456	275	38	,	,	PUNCT
ajst-31456	275	39	”	"	PUNCT
ajst-31456	275	40	ieee	ieee	NOUN
ajst-31456	275	41	transactions	transaction	NOUN
ajst-31456	275	42	on	on	ADP
ajst-31456	275	43	knowledge	knowledge	NOUN
ajst-31456	275	44	and	and	CCONJ
ajst-31456	275	45	data	datum	NOUN
ajst-31456	275	46	engineering	engineering	NOUN
ajst-31456	275	47	,	,	PUNCT
ajst-31456	275	48	vol	vol	NOUN
ajst-31456	275	49	.	.	PROPN
ajst-31456	276	1	34	34	NUM
ajst-31456	276	2	,	,	PUNCT
ajst-31456	276	3	no	no	INTJ
ajst-31456	276	4	.	.	NOUN
ajst-31456	276	5	2	2	NUM
ajst-31456	276	6	,	,	PUNCT
ajst-31456	276	7	pp	pp	ADJ
ajst-31456	276	8	.	.	PUNCT
ajst-31456	277	1	640–652	640–652	NUM
ajst-31456	277	2	,	,	PUNCT
ajst-31456	277	3	2022	2022	NUM
ajst-31456	277	4	.	.	PUNCT
ajst-31456	278	1	[	[	X
ajst-31456	278	2	19	19	NUM
ajst-31456	278	3	]	]	X
ajst-31456	278	4	j.	j.	PROPN
ajst-31456	278	5	huang	huang	PROPN
ajst-31456	278	6	,	,	PUNCT
ajst-31456	278	7	x.	x.	PROPN
ajst-31456	278	8	wang	wang	PROPN
ajst-31456	278	9	,	,	PUNCT
ajst-31456	278	10	and	and	CCONJ
ajst-31456	278	11	h.	h.	PROPN
ajst-31456	278	12	sun	sun	PROPN
ajst-31456	278	13	,	,	PUNCT
ajst-31456	278	14	“	"	PUNCT
ajst-31456	278	15	central	central	ADJ
ajst-31456	278	16	station	station	NOUN
ajst-31456	278	17	based	base	VERB
ajst-31456	278	18	demand	demand	NOUN
ajst-31456	278	19	prediction	prediction	NOUN
ajst-31456	278	20	in	in	ADP
ajst-31456	278	21	a	a	DET
ajst-31456	278	22	bike	bike	NOUN
ajst-31456	278	23	sharing	sharing	NOUN
ajst-31456	278	24	system	system	NOUN
ajst-31456	278	25	,	,	PUNCT
ajst-31456	278	26	”	"	PUNCT
ajst-31456	278	27	in	in	ADP
ajst-31456	278	28	2019	2019	NUM
ajst-31456	278	29	20th	20th	ADJ
ajst-31456	278	30	ieee	ieee	NOUN
ajst-31456	278	31	international	international	ADJ
ajst-31456	278	32	conference	conference	NOUN
ajst-31456	278	33	on	on	ADP
ajst-31456	278	34	mobile	mobile	ADJ
ajst-31456	278	35	data	datum	NOUN
ajst-31456	278	36	management	management	NOUN
ajst-31456	278	37	(	(	PUNCT
ajst-31456	278	38	mdm	mdm	PROPN
ajst-31456	278	39	)	)	PUNCT
ajst-31456	278	40	,	,	PUNCT
ajst-31456	278	41	2019	2019	NUM
ajst-31456	278	42	,	,	PUNCT
ajst-31456	278	43	pp	pp	ADJ
ajst-31456	278	44	.	.	PUNCT
ajst-31456	279	1	346–348	346–348	NUM
ajst-31456	279	2	.	.	PUNCT
ajst-31456	280	1	[	[	X
ajst-31456	280	2	20	20	NUM
ajst-31456	280	3	]	]	PUNCT
ajst-31456	280	4	w.	w.	PROPN
ajst-31456	280	5	zheng	zheng	PROPN
ajst-31456	280	6	,	,	PUNCT
ajst-31456	280	7	h.	h.	PROPN
ajst-31456	280	8	deng	deng	PROPN
ajst-31456	280	9	,	,	PUNCT
ajst-31456	280	10	and	and	CCONJ
ajst-31456	280	11	f.	f.	PROPN
ajst-31456	280	12	han	han	PROPN
ajst-31456	280	13	,	,	PUNCT
ajst-31456	280	14	“	"	PUNCT
ajst-31456	280	15	gst	gst	NOUN
ajst-31456	280	16	-	-	PUNCT
ajst-31456	280	17	net	net	NOUN
ajst-31456	280	18	:	:	PUNCT
ajst-31456	280	19	a	a	DET
ajst-31456	280	20	gis	gis	NOUN
ajst-31456	280	21	-	-	PUNCT
ajst-31456	280	22	based	base	VERB
ajst-31456	280	23	hybrid	hybrid	ADJ
ajst-31456	280	24	prediction	prediction	NOUN
ajst-31456	280	25	model	model	NOUN
ajst-31456	280	26	for	for	ADP
ajst-31456	280	27	shared	share	VERB
ajst-31456	280	28	bike	bike	NOUN
ajst-31456	280	29	traffic	traffic	NOUN
ajst-31456	280	30	flow	flow	NOUN
ajst-31456	280	31	,	,	PUNCT
ajst-31456	280	32	”	"	PUNCT
ajst-31456	280	33	in	in	ADP
ajst-31456	280	34	2021	2021	NUM
ajst-31456	280	35	ieee	ieee	NOUN
ajst-31456	280	36	21st	21st	ADJ
ajst-31456	280	37	international	international	ADJ
ajst-31456	280	38	conference	conference	NOUN
ajst-31456	280	39	on	on	ADP
ajst-31456	280	40	software	software	NOUN
ajst-31456	280	41	quality	quality	NOUN
ajst-31456	280	42	,	,	PUNCT
ajst-31456	280	43	reliability	reliability	NOUN
ajst-31456	280	44	and	and	CCONJ
ajst-31456	280	45	security	security	NOUN
ajst-31456	280	46	companion	companion	NOUN
ajst-31456	280	47	(	(	PUNCT
ajst-31456	280	48	qrs	qrs	PROPN
ajst-31456	280	49	-	-	PUNCT
ajst-31456	280	50	c	c	NOUN
ajst-31456	280	51	)	)	PUNCT
ajst-31456	280	52	,	,	PUNCT
ajst-31456	280	53	2021	2021	NUM
ajst-31456	280	54	,	,	PUNCT
ajst-31456	280	55	pp	pp	ADJ
ajst-31456	280	56	.	.	PUNCT
ajst-31456	281	1	941–946	941–946	NUM
ajst-31456	281	2	.	.	PUNCT
ajst-31456	282	1	[	[	X
ajst-31456	282	2	21	21	NUM
ajst-31456	282	3	]	]	X
ajst-31456	282	4	e.	e.	PROPN
ajst-31456	282	5	collini	collini	PROPN
ajst-31456	282	6	,	,	PUNCT
ajst-31456	282	7	p.	p.	PROPN
ajst-31456	282	8	nesi	nesi	PROPN
ajst-31456	282	9	,	,	PUNCT
ajst-31456	282	10	and	and	CCONJ
ajst-31456	282	11	g.	g.	PROPN
ajst-31456	282	12	pantaleo	pantaleo	PROPN
ajst-31456	282	13	,	,	PUNCT
ajst-31456	282	14	“	"	PUNCT
ajst-31456	282	15	deep	deep	ADJ
ajst-31456	282	16	learning	learning	NOUN
ajst-31456	282	17	for	for	ADP
ajst-31456	282	18	shortterm	shortterm	PROPN
ajst-31456	282	19	prediction	prediction	NOUN
ajst-31456	282	20	of	of	ADP
ajst-31456	282	21	available	available	ADJ
ajst-31456	282	22	bikes	bike	NOUN
ajst-31456	282	23	on	on	ADP
ajst-31456	282	24	bike	bike	NOUN
ajst-31456	282	25	-	-	PUNCT
ajst-31456	282	26	sharing	share	VERB
ajst-31456	282	27	stations	station	NOUN
ajst-31456	282	28	,	,	PUNCT
ajst-31456	282	29	”	"	PUNCT
ajst-31456	282	30	ieee	ieee	NOUN
ajst-31456	282	31	access	access	NOUN
ajst-31456	282	32	,	,	PUNCT
ajst-31456	282	33	vol	vol	NOUN
ajst-31456	282	34	.	.	NOUN
ajst-31456	282	35	9	9	NUM
ajst-31456	282	36	,	,	PUNCT
ajst-31456	282	37	pp	pp	ADJ
ajst-31456	282	38	.	.	PUNCT
ajst-31456	282	39	124337–124347	124337–124347	NUM
ajst-31456	282	40	,	,	PUNCT
ajst-31456	282	41	2021	2021	NUM
ajst-31456	282	42	.	.	PUNCT
ajst-31456	283	1	[	[	X
ajst-31456	283	2	22	22	NUM
ajst-31456	283	3	]	]	X
ajst-31456	283	4	y.	y.	PROPN
ajst-31456	283	5	du	du	PROPN
ajst-31456	283	6	,	,	PUNCT
ajst-31456	283	7	b.	b.	PROPN
ajst-31456	283	8	xiao	xiao	PROPN
ajst-31456	283	9	,	,	PUNCT
ajst-31456	283	10	w.	w.	PROPN
ajst-31456	283	11	xu	xu	PROPN
ajst-31456	283	12	,	,	PUNCT
ajst-31456	283	13	d.	d.	PROPN
ajst-31456	283	14	cui	cui	PROPN
ajst-31456	283	15	,	,	PUNCT
ajst-31456	283	16	q.	q.	PROPN
ajst-31456	283	17	xu	xu	PROPN
ajst-31456	283	18	,	,	PUNCT
ajst-31456	283	19	and	and	CCONJ
ajst-31456	283	20	l.	l.	PROPN
ajst-31456	283	21	yan	yan	PROPN
ajst-31456	283	22	,	,	PUNCT
ajst-31456	283	23	“	"	PUNCT
ajst-31456	283	24	destination	destination	NOUN
ajst-31456	283	25	prediction	prediction	NOUN
ajst-31456	283	26	for	for	ADP
ajst-31456	283	27	sharing	sharing	NOUN
ajst-31456	283	28	-	-	PUNCT
ajst-31456	283	29	bikes	bike	NOUN
ajst-31456	283	30	’	'	PUNCT
ajst-31456	283	31	trips	trip	NOUN
ajst-31456	283	32	,	,	PUNCT
ajst-31456	283	33	”	"	PUNCT
ajst-31456	283	34	in	in	ADP
ajst-31456	283	35	2018	2018	NUM
ajst-31456	283	36	international	international	ADJ
ajst-31456	283	37	conference	conference	NOUN
ajst-31456	283	38	on	on	ADP
ajst-31456	283	39	network	network	NOUN
ajst-31456	283	40	infrastructure	infrastructure	NOUN
ajst-31456	283	41	and	and	CCONJ
ajst-31456	283	42	digital	digital	ADJ
ajst-31456	283	43	content	content	NOUN
ajst-31456	283	44	(	(	PUNCT
ajst-31456	283	45	ic	ic	NOUN
ajst-31456	283	46	-	-	PUNCT
ajst-31456	283	47	nidc	nidc	ADJ
ajst-31456	283	48	)	)	PUNCT
ajst-31456	283	49	,	,	PUNCT
ajst-31456	283	50	2018	2018	NUM
ajst-31456	283	51	,	,	PUNCT
ajst-31456	283	52	pp	pp	ADP
ajst-31456	283	53	.	.	PUNCT
ajst-31456	284	1	198–202	198–202	NUM
ajst-31456	284	2	.	.	PUNCT
ajst-31456	285	1	[	[	X
ajst-31456	285	2	23	23	NUM
ajst-31456	285	3	]	]	PUNCT
ajst-31456	285	4	a.	a.	PROPN
ajst-31456	285	5	k.	k.	PROPN
ajst-31456	285	6	das	das	PROPN
ajst-31456	285	7	,	,	PUNCT
ajst-31456	285	8	a.	a.	PROPN
ajst-31456	285	9	m.	m.	PROPN
ajst-31456	285	10	joshi	joshi	PROPN
ajst-31456	285	11	,	,	PUNCT
ajst-31456	285	12	and	and	CCONJ
ajst-31456	285	13	s.	s.	PROPN
ajst-31456	285	14	dhal	dhal	PROPN
ajst-31456	285	15	,	,	PUNCT
ajst-31456	285	16	“	"	PUNCT
ajst-31456	285	17	a	a	DET
ajst-31456	285	18	machine	machine	NOUN
ajst-31456	285	19	learning	learn	VERB
ajst-31456	285	20	based	base	VERB
ajst-31456	285	21	bike	bike	NOUN
ajst-31456	285	22	recommendation	recommendation	NOUN
ajst-31456	285	23	system	system	NOUN
ajst-31456	285	24	catering	cater	VERB
ajst-31456	285	25	to	to	ADP
ajst-31456	285	26	user	user	NOUN
ajst-31456	285	27	’s	’s	PART
ajst-31456	285	28	travel	travel	NOUN
ajst-31456	285	29	needs	need	NOUN
ajst-31456	285	30	,	,	PUNCT
ajst-31456	285	31	”	"	PUNCT
ajst-31456	285	32	in	in	ADP
ajst-31456	285	33	2020	2020	NUM
ajst-31456	285	34	ieee	ieee	PROPN
ajst-31456	285	35	17th	17th	ADJ
ajst-31456	285	36	india	india	PROPN
ajst-31456	285	37	council	council	PROPN
ajst-31456	285	38	international	international	PROPN
ajst-31456	285	39	conference	conference	PROPN
ajst-31456	285	40	(	(	PUNCT
ajst-31456	285	41	indicon	indicon	NOUN
ajst-31456	285	42	)	)	PUNCT
ajst-31456	285	43	,	,	PUNCT
ajst-31456	285	44	2020	2020	NUM
ajst-31456	285	45	,	,	PUNCT
ajst-31456	285	46	pp	pp	ADV
ajst-31456	285	47	.	.	PUNCT
ajst-31456	286	1	1–6	1–6	X
ajst-31456	286	2	.	.	PUNCT
ajst-31456	287	1	[	[	X
ajst-31456	287	2	24	24	NUM
ajst-31456	287	3	]	]	PUNCT
ajst-31456	287	4	m.	m.	PROPN
ajst-31456	287	5	jiang	jiang	PROPN
ajst-31456	287	6	,	,	PUNCT
ajst-31456	287	7	c.	c.	PROPN
ajst-31456	287	8	li	li	PROPN
ajst-31456	287	9	,	,	PUNCT
ajst-31456	287	10	k.	k.	PROPN
ajst-31456	287	11	li	li	PROPN
ajst-31456	287	12	,	,	PUNCT
ajst-31456	287	13	z.	z.	PROPN
ajst-31456	287	14	yang	yang	PROPN
ajst-31456	287	15	,	,	PUNCT
ajst-31456	287	16	and	and	CCONJ
ajst-31456	287	17	h.	h.	PROPN
ajst-31456	287	18	liu	liu	PROPN
ajst-31456	287	19	,	,	PUNCT
ajst-31456	287	20	“	"	PUNCT
ajst-31456	287	21	interblock	interblock	NOUN
ajst-31456	287	22	flow	flow	NOUN
ajst-31456	287	23	prediction	prediction	NOUN
ajst-31456	287	24	with	with	ADP
ajst-31456	287	25	relation	relation	NOUN
ajst-31456	287	26	graph	graph	NOUN
ajst-31456	287	27	network	network	NOUN
ajst-31456	287	28	for	for	ADP
ajst-31456	287	29	cold	cold	ADJ
ajst-31456	287	30	start	start	NOUN
ajst-31456	287	31	on	on	ADP
ajst-31456	287	32	bikesharing	bikeshare	VERB
ajst-31456	287	33	system	system	NOUN
ajst-31456	287	34	,	,	PUNCT
ajst-31456	287	35	”	"	PUNCT
ajst-31456	287	36	ieee	ieee	NOUN
ajst-31456	287	37	internet	internet	NOUN
ajst-31456	287	38	of	of	ADP
ajst-31456	287	39	things	thing	NOUN
ajst-31456	287	40	journal	journal	NOUN
ajst-31456	287	41	,	,	PUNCT
ajst-31456	287	42	vol	vol	NOUN
ajst-31456	287	43	.	.	PROPN
ajst-31456	287	44	9	9	NUM
ajst-31456	287	45	,	,	PUNCT
ajst-31456	287	46	no	no	INTJ
ajst-31456	287	47	.	.	NOUN
ajst-31456	287	48	15	15	NUM
ajst-31456	287	49	,	,	PUNCT
ajst-31456	287	50	pp	pp	ADJ
ajst-31456	287	51	.	.	PUNCT
ajst-31456	287	52	13390–13404	13390–13404	NUM
ajst-31456	287	53	,	,	PUNCT
ajst-31456	287	54	2022	2022	NUM
ajst-31456	287	55	.	.	PUNCT
ajst-31456	288	1	[	[	X
ajst-31456	288	2	25	25	NUM
ajst-31456	288	3	]	]	X
ajst-31456	288	4	r.	r.	PROPN
ajst-31456	288	5	guo	guo	PROPN
ajst-31456	288	6	,	,	PUNCT
ajst-31456	288	7	z.	z.	PROPN
ajst-31456	288	8	jiang	jiang	PROPN
ajst-31456	288	9	,	,	PUNCT
ajst-31456	288	10	j.	j.	PROPN
ajst-31456	288	11	huang	huang	PROPN
ajst-31456	288	12	,	,	PUNCT
ajst-31456	288	13	j.	j.	PROPN
ajst-31456	288	14	tao	tao	PROPN
ajst-31456	288	15	,	,	PUNCT
ajst-31456	288	16	c.	c.	PROPN
ajst-31456	288	17	wang	wang	PROPN
ajst-31456	288	18	,	,	PUNCT
ajst-31456	288	19	j.	j.	PROPN
ajst-31456	288	20	li	li	PROPN
ajst-31456	288	21	,	,	PUNCT
ajst-31456	288	22	and	and	CCONJ
ajst-31456	288	23	l.	l.	PROPN
ajst-31456	288	24	chen	chen	PROPN
ajst-31456	288	25	,	,	PUNCT
ajst-31456	288	26	“	"	PUNCT
ajst-31456	288	27	bikenet	bikenet	PROPN
ajst-31456	288	28	:	:	PUNCT
ajst-31456	288	29	accurate	accurate	ADJ
ajst-31456	288	30	bike	bike	NOUN
ajst-31456	288	31	demand	demand	NOUN
ajst-31456	288	32	prediction	prediction	NOUN
ajst-31456	288	33	using	use	VERB
ajst-31456	288	34	graph	graph	NOUN
ajst-31456	288	35	neural	neural	ADJ
ajst-31456	288	36	networks	network	NOUN
ajst-31456	288	37	for	for	ADP
ajst-31456	288	38	station	station	NOUN
ajst-31456	288	39	rebalancing	rebalancing	NOUN
ajst-31456	288	40	,	,	PUNCT
ajst-31456	288	41	”	"	PUNCT
ajst-31456	288	42	in	in	ADP
ajst-31456	288	43	2019	2019	NUM
ajst-31456	288	44	ieee	ieee	NOUN
ajst-31456	288	45	smartworld	smartworld	NOUN
ajst-31456	288	46	,	,	PUNCT
ajst-31456	288	47	ubiquitous	ubiquitous	ADJ
ajst-31456	288	48	intelligence	intelligence	NOUN
ajst-31456	288	49	&	&	CCONJ
ajst-31456	288	50	computing	computing	PROPN
ajst-31456	288	51	,	,	PUNCT
ajst-31456	288	52	advanced	advanced	ADJ
ajst-31456	288	53	&	&	CCONJ
ajst-31456	288	54	trusted	trust	VERB
ajst-31456	288	55	computing	computing	NOUN
ajst-31456	288	56	,	,	PUNCT
ajst-31456	288	57	scalable	scalable	ADJ
ajst-31456	288	58	computing	computing	NOUN
ajst-31456	288	59	&	&	CCONJ
ajst-31456	288	60	communications	communication	NOUN
ajst-31456	288	61	,	,	PUNCT
ajst-31456	288	62	cloud	cloud	NOUN
ajst-31456	288	63	&	&	CCONJ
ajst-31456	288	64	big	big	ADJ
ajst-31456	288	65	data	datum	NOUN
ajst-31456	288	66	computing	computing	NOUN
ajst-31456	288	67	,	,	PUNCT
ajst-31456	288	68	internet	internet	NOUN
ajst-31456	288	69	of	of	ADP
ajst-31456	288	70	people	people	NOUN
ajst-31456	288	71	and	and	CCONJ
ajst-31456	288	72	smart	smart	ADJ
ajst-31456	288	73	city	city	NOUN
ajst-31456	288	74	innovation	innovation	NOUN
ajst-31456	288	75	(	(	PUNCT
ajst-31456	288	76	smart	smart	ADJ
ajst-31456	288	77	world	world	NOUN
ajst-31456	288	78	/	/	SYM
ajst-31456	288	79	scalcom	scalcom	PROPN
ajst-31456	288	80	/	/	SYM
ajst-31456	288	81	uic	uic	PROPN
ajst-31456	288	82	/	/	SYM
ajst-31456	288	83	atc	atc	PROPN
ajst-31456	288	84	/	/	SYM
ajst-31456	288	85	cbdcom	cbdcom	PROPN
ajst-31456	288	86	/	/	SYM
ajst-31456	288	87	iop	iop	PROPN
ajst-31456	288	88	/	/	SYM
ajst-31456	288	89	sci	sci	PROPN
ajst-31456	288	90	)	)	PUNCT
ajst-31456	288	91	,	,	PUNCT
ajst-31456	288	92	2019	2019	NUM
ajst-31456	288	93	,	,	PUNCT
ajst-31456	288	94	pp	pp	ADJ
ajst-31456	288	95	.	.	PUNCT
ajst-31456	289	1	686–693	686–693	NUM
ajst-31456	289	2	.	.	PUNCT
ajst-31456	290	1	[	[	X
ajst-31456	290	2	26	26	NUM
ajst-31456	290	3	]	]	X
ajst-31456	290	4	r.	r.	PROPN
ajst-31456	290	5	qin	qin	PROPN
ajst-31456	290	6	,	,	PUNCT
ajst-31456	290	7	l.	l.	PROPN
ajst-31456	290	8	kong	kong	PROPN
ajst-31456	290	9	,	,	PUNCT
ajst-31456	290	10	m.	m.	PROPN
ajst-31456	290	11	guo	guo	PROPN
ajst-31456	290	12	,	,	PUNCT
ajst-31456	290	13	b.	b.	PROPN
ajst-31456	290	14	yao	yao	PROPN
ajst-31456	290	15	,	,	PUNCT
ajst-31456	290	16	and	and	CCONJ
ajst-31456	290	17	m.	m.	NOUN
ajst-31456	290	18	guizani	guizani	NOUN
ajst-31456	290	19	,	,	PUNCT
ajst-31456	290	20	“	"	PUNCT
ajst-31456	290	21	rebalance	rebalance	NOUN
ajst-31456	290	22	modern	modern	ADJ
ajst-31456	290	23	bike	bike	NOUN
ajst-31456	290	24	sharing	sharing	NOUN
ajst-31456	290	25	system	system	NOUN
ajst-31456	290	26	:	:	PUNCT
ajst-31456	290	27	spatio	spatio	ADJ
ajst-31456	290	28	-	-	PUNCT
ajst-31456	290	29	temporal	temporal	ADJ
ajst-31456	290	30	data	datum	NOUN
ajst-31456	290	31	prediction	prediction	NOUN
ajst-31456	290	32	and	and	CCONJ
ajst-31456	290	33	path	path	NOUN
ajst-31456	290	34	planning	planning	NOUN
ajst-31456	290	35	for	for	ADP
ajst-31456	290	36	multiple	multiple	ADJ
ajst-31456	290	37	carriers	carrier	NOUN
ajst-31456	290	38	,	,	PUNCT
ajst-31456	290	39	”	"	PUNCT
ajst-31456	290	40	in	in	ADP
ajst-31456	290	41	2018	2018	NUM
ajst-31456	290	42	ieee	ieee	NOUN
ajst-31456	290	43	24th	24th	ADJ
ajst-31456	290	44	international	international	ADJ
ajst-31456	290	45	conference	conference	NOUN
ajst-31456	290	46	on	on	ADP
ajst-31456	290	47	parallel	parallel	ADJ
ajst-31456	290	48	and	and	CCONJ
ajst-31456	290	49	distributed	distribute	VERB
ajst-31456	290	50	systems	system	NOUN
ajst-31456	290	51	(	(	PUNCT
ajst-31456	290	52	icpads	icpad	NOUN
ajst-31456	290	53	)	)	PUNCT
ajst-31456	290	54	,	,	PUNCT
ajst-31456	290	55	2018	2018	NUM
ajst-31456	290	56	,	,	PUNCT
ajst-31456	290	57	pp	pp	ADJ
ajst-31456	290	58	.	.	PUNCT
ajst-31456	291	1	1081–1086	1081–1086	NUM
ajst-31456	291	2	.	.	PUNCT
ajst-31456	292	1	[	[	X
ajst-31456	292	2	27	27	NUM
ajst-31456	292	3	]	]	PUNCT
ajst-31456	292	4	j.	j.	PROPN
ajst-31456	292	5	chai	chai	PROPN
ajst-31456	292	6	,	,	PUNCT
ajst-31456	292	7	j.	j.	PROPN
ajst-31456	292	8	song	song	PROPN
ajst-31456	292	9	,	,	PUNCT
ajst-31456	292	10	h.	h.	PROPN
ajst-31456	292	11	fan	fan	PROPN
ajst-31456	292	12	,	,	PUNCT
ajst-31456	292	13	y.	y.	PROPN
ajst-31456	292	14	xu	xu	PROPN
ajst-31456	292	15	,	,	PUNCT
ajst-31456	292	16	l.	l.	PROPN
ajst-31456	292	17	zhang	zhang	PROPN
ajst-31456	292	18	,	,	PUNCT
ajst-31456	292	19	b.	b.	PROPN
ajst-31456	292	20	guo	guo	PROPN
ajst-31456	292	21	,	,	PUNCT
ajst-31456	292	22	and	and	CCONJ
ajst-31456	292	23	y.	y.	PROPN
ajst-31456	292	24	xu	xu	PROPN
ajst-31456	292	25	,	,	PUNCT
ajst-31456	292	26	“	"	PUNCT
ajst-31456	292	27	st	st	NOUN
ajst-31456	292	28	-	-	PUNCT
ajst-31456	292	29	bikes	bike	NOUN
ajst-31456	292	30	:	:	PUNCT
ajst-31456	292	31	predicting	predict	VERB
ajst-31456	292	32	travel	travel	NOUN
ajst-31456	292	33	-	-	PUNCT
ajst-31456	292	34	behaviors	behavior	NOUN
ajst-31456	292	35	of	of	ADP
ajst-31456	292	36	sharing	sharing	NOUN
ajst-31456	292	37	-	-	PUNCT
ajst-31456	292	38	bikes	bike	NOUN
ajst-31456	292	39	exploiting	exploit	VERB
ajst-31456	292	40	urban	urban	ADJ
ajst-31456	292	41	big	big	ADJ
ajst-31456	292	42	data	datum	NOUN
ajst-31456	292	43	,	,	PUNCT
ajst-31456	292	44	”	"	PUNCT
ajst-31456	292	45	ieee	ieee	NOUN
ajst-31456	292	46	transactions	transaction	NOUN
ajst-31456	292	47	on	on	ADP
ajst-31456	292	48	intelligent	intelligent	ADJ
ajst-31456	292	49	transportation	transportation	NOUN
ajst-31456	292	50	systems	system	NOUN
ajst-31456	292	51	,	,	PUNCT
ajst-31456	292	52	vol	vol	NOUN
ajst-31456	292	53	.	.	PROPN
ajst-31456	292	54	24	24	NUM
ajst-31456	292	55	,	,	PUNCT
ajst-31456	292	56	no	no	INTJ
ajst-31456	292	57	.	.	NOUN
ajst-31456	292	58	7	7	NUM
ajst-31456	292	59	,	,	PUNCT
ajst-31456	292	60	pp	pp	ADJ
ajst-31456	292	61	.	.	PUNCT
ajst-31456	292	62	7676–7686	7676–7686	NUM
ajst-31456	292	63	,	,	PUNCT
ajst-31456	292	64	2023	2023	NUM
ajst-31456	292	65	.	.	PUNCT
ajst-31456	293	1	[	[	X
ajst-31456	293	2	28	28	NUM
ajst-31456	293	3	]	]	X
ajst-31456	293	4	y.	y.	PROPN
ajst-31456	293	5	liang	liang	PROPN
ajst-31456	293	6	,	,	PUNCT
ajst-31456	293	7	g.	g.	PROPN
ajst-31456	293	8	huang	huang	PROPN
ajst-31456	293	9	,	,	PUNCT
ajst-31456	293	10	and	and	CCONJ
ajst-31456	293	11	z.	z.	PROPN
ajst-31456	293	12	zhao	zhao	PROPN
ajst-31456	293	13	,	,	PUNCT
ajst-31456	293	14	“	"	PUNCT
ajst-31456	293	15	cross	cross	ADJ
ajst-31456	293	16	-	-	ADJ
ajst-31456	293	17	mode	mode	ADJ
ajst-31456	293	18	knowledge	knowledge	NOUN
ajst-31456	293	19	adaptation	adaptation	NOUN
ajst-31456	293	20	for	for	ADP
ajst-31456	293	21	bike	bike	NOUN
ajst-31456	293	22	sharing	sharing	NOUN
ajst-31456	293	23	demand	demand	NOUN
ajst-31456	293	24	prediction	prediction	NOUN
ajst-31456	293	25	using	use	VERB
ajst-31456	293	26	domainadversarial	domainadversarial	ADJ
ajst-31456	293	27	graph	graph	NOUN
ajst-31456	293	28	neural	neural	ADJ
ajst-31456	293	29	networks	network	NOUN
ajst-31456	293	30	,	,	PUNCT
ajst-31456	293	31	”	"	PUNCT
ajst-31456	293	32	ieee	ieee	NOUN
ajst-31456	293	33	transactions	transaction	NOUN
ajst-31456	293	34	on	on	ADP
ajst-31456	293	35	intelligent	intelligent	ADJ
ajst-31456	293	36	transportation	transportation	NOUN
ajst-31456	293	37	systems	system	NOUN
ajst-31456	293	38	,	,	PUNCT
ajst-31456	293	39	vol	vol	NOUN
ajst-31456	293	40	.	.	PROPN
ajst-31456	293	41	25	25	NUM
ajst-31456	293	42	,	,	PUNCT
ajst-31456	293	43	no	no	INTJ
ajst-31456	293	44	.	.	NOUN
ajst-31456	293	45	5	5	NUM
ajst-31456	293	46	,	,	PUNCT
ajst-31456	293	47	pp	pp	ADJ
ajst-31456	293	48	.	.	PUNCT
ajst-31456	294	1	3642	3642	NUM
ajst-31456	294	2	–	–	PUNCT
ajst-31456	294	3	3653	3653	NUM
ajst-31456	294	4	,	,	PUNCT
ajst-31456	294	5	2024	2024	NUM
ajst-31456	294	6	.	.	PUNCT
ajst-31456	295	1	60	60	NUM
ajst-31456	296	1	[	[	SYM
ajst-31456	296	2	29	29	NUM
ajst-31456	296	3	]	]	PUNCT
ajst-31456	296	4	m.	m.	NOUN
ajst-31456	296	5	tabandeh	tabandeh	PROPN
ajst-31456	296	6	,	,	PUNCT
ajst-31456	296	7	c.	c.	PROPN
ajst-31456	296	8	antoniou	antoniou	PROPN
ajst-31456	296	9	,	,	PUNCT
ajst-31456	296	10	and	and	CCONJ
ajst-31456	296	11	g.	g.	PROPN
ajst-31456	296	12	cantelmo	cantelmo	PROPN
ajst-31456	296	13	,	,	PUNCT
ajst-31456	296	14	“	"	PUNCT
ajst-31456	296	15	long	long	ADJ
ajst-31456	296	16	-	-	PUNCT
ajst-31456	296	17	term	term	NOUN
ajst-31456	296	18	&	&	CCONJ
ajst-31456	296	19	short	short	ADJ
ajst-31456	296	20	-	-	PUNCT
ajst-31456	296	21	term	term	NOUN
ajst-31456	296	22	bike	bike	NOUN
ajst-31456	296	23	sharing	sharing	NOUN
ajst-31456	296	24	demand	demand	NOUN
ajst-31456	296	25	predictions	prediction	NOUN
ajst-31456	296	26	using	use	VERB
ajst-31456	296	27	contextual	contextual	ADJ
ajst-31456	296	28	data	datum	NOUN
ajst-31456	296	29	,	,	PUNCT
ajst-31456	296	30	”	"	PUNCT
ajst-31456	296	31	in	in	ADP
ajst-31456	296	32	2023	2023	NUM
ajst-31456	296	33	8th	8th	ADJ
ajst-31456	296	34	international	international	ADJ
ajst-31456	296	35	conference	conference	NOUN
ajst-31456	296	36	on	on	ADP
ajst-31456	296	37	models	model	NOUN
ajst-31456	296	38	and	and	CCONJ
ajst-31456	296	39	technologies	technology	NOUN
ajst-31456	296	40	for	for	ADP
ajst-31456	296	41	intelligent	intelligent	ADJ
ajst-31456	296	42	transportation	transportation	NOUN
ajst-31456	296	43	systems	system	NOUN
ajst-31456	296	44	(	(	PUNCT
ajst-31456	296	45	mt	mt	PROPN
ajst-31456	296	46	-	-	PUNCT
ajst-31456	296	47	its	its	PRON
ajst-31456	296	48	)	)	PUNCT
ajst-31456	296	49	,	,	PUNCT
ajst-31456	296	50	2023	2023	NUM
ajst-31456	296	51	,	,	PUNCT
ajst-31456	296	52	pp	pp	ADJ
ajst-31456	296	53	.	.	PUNCT
ajst-31456	297	1	1–6	1–6	X
ajst-31456	297	2	.	.	PUNCT
ajst-31456	298	1	[	[	X
ajst-31456	298	2	30	30	NUM
ajst-31456	298	3	]	]	X
ajst-31456	298	4	y.	y.	PROPN
ajst-31456	298	5	zhou	zhou	PROPN
ajst-31456	298	6	and	and	CCONJ
ajst-31456	298	7	y.	y.	PROPN
ajst-31456	298	8	huang	huang	PROPN
ajst-31456	298	9	,	,	PUNCT
ajst-31456	298	10	“	"	PUNCT
ajst-31456	298	11	place	place	NOUN
ajst-31456	298	12	representation	representation	NOUN
ajst-31456	298	13	based	base	VERB
ajst-31456	298	14	bike	bike	NOUN
ajst-31456	298	15	demand	demand	NOUN
ajst-31456	298	16	prediction	prediction	NOUN
ajst-31456	298	17	,	,	PUNCT
ajst-31456	298	18	”	"	PUNCT
ajst-31456	298	19	in	in	ADP
ajst-31456	298	20	2019	2019	NUM
ajst-31456	298	21	ieee	ieee	NOUN
ajst-31456	298	22	international	international	ADJ
ajst-31456	298	23	conference	conference	NOUN
ajst-31456	298	24	on	on	ADP
ajst-31456	298	25	big	big	ADJ
ajst-31456	298	26	data	datum	NOUN
ajst-31456	298	27	(	(	PUNCT
ajst-31456	298	28	big	big	ADJ
ajst-31456	298	29	data	datum	NOUN
ajst-31456	298	30	)	)	PUNCT
ajst-31456	298	31	,	,	PUNCT
ajst-31456	298	32	2019	2019	NUM
ajst-31456	298	33	,	,	PUNCT
ajst-31456	298	34	pp	pp	ADJ
ajst-31456	298	35	.	.	PUNCT
ajst-31456	299	1	1577–1586	1577–1586	NUM
ajst-31456	299	2	.	.	PUNCT
ajst-31456	300	1	[	[	X
ajst-31456	300	2	31	31	NUM
ajst-31456	300	3	]	]	PUNCT
ajst-31456	300	4	s.	s.	PROPN
ajst-31456	300	5	s.	s.	PROPN
ajst-31456	300	6	chawathe	chawathe	PROPN
ajst-31456	300	7	,	,	PUNCT
ajst-31456	300	8	“	"	PUNCT
ajst-31456	300	9	mining	mining	NOUN
ajst-31456	300	10	bike	bike	NOUN
ajst-31456	300	11	-	-	PUNCT
ajst-31456	300	12	share	share	NOUN
ajst-31456	300	13	data	datum	NOUN
ajst-31456	300	14	,	,	PUNCT
ajst-31456	300	15	”	"	PUNCT
ajst-31456	300	16	in	in	ADP
ajst-31456	300	17	2020	2020	NUM
ajst-31456	300	18	ieee	ieee	NOUN
ajst-31456	300	19	international	international	ADJ
ajst-31456	300	20	smart	smart	ADJ
ajst-31456	300	21	cities	city	NOUN
ajst-31456	300	22	conference	conference	NOUN
ajst-31456	300	23	(	(	PUNCT
ajst-31456	300	24	isc2	isc2	PROPN
ajst-31456	300	25	)	)	PUNCT
ajst-31456	300	26	,	,	PUNCT
ajst-31456	300	27	2020	2020	NUM
ajst-31456	300	28	,	,	PUNCT
ajst-31456	300	29	pp	pp	ADV
ajst-31456	300	30	.	.	PUNCT
ajst-31456	301	1	1–8	1–8	X
ajst-31456	301	2	.	.	PUNCT
ajst-31456	302	1	[	[	X
ajst-31456	302	2	32	32	NUM
ajst-31456	302	3	]	]	PUNCT
ajst-31456	302	4	m.	m.	NOUN
ajst-31456	302	5	bencekri	bencekri	NOUN
ajst-31456	302	6	,	,	PUNCT
ajst-31456	302	7	a.	a.	NOUN
ajst-31456	302	8	founoun	founoun	PROPN
ajst-31456	302	9	,	,	PUNCT
ajst-31456	302	10	a.	a.	NOUN
ajst-31456	302	11	haqiq	haqiq	NOUN
ajst-31456	302	12	,	,	PUNCT
ajst-31456	302	13	and	and	CCONJ
ajst-31456	302	14	a.	a.	NOUN
ajst-31456	302	15	hayar	hayar	PROPN
ajst-31456	302	16	,	,	PUNCT
ajst-31456	302	17	“	"	PUNCT
ajst-31456	302	18	investigation	investigation	NOUN
ajst-31456	302	19	of	of	ADP
ajst-31456	302	20	shared	share	VERB
ajst-31456	302	21	-	-	PUNCT
ajst-31456	302	22	bike	bike	NOUN
ajst-31456	302	23	demand	demand	NOUN
ajst-31456	302	24	using	use	VERB
ajst-31456	302	25	data	datum	NOUN
ajst-31456	302	26	analytics	analytic	NOUN
ajst-31456	302	27	,	,	PUNCT
ajst-31456	302	28	”	"	PUNCT
ajst-31456	302	29	in	in	ADP
ajst-31456	302	30	2022	2022	NUM
ajst-31456	302	31	ieee	ieee	NOUN
ajst-31456	302	32	international	international	ADJ
ajst-31456	302	33	smart	smart	ADJ
ajst-31456	302	34	cities	city	NOUN
ajst-31456	302	35	conference	conference	NOUN
ajst-31456	302	36	(	(	PUNCT
ajst-31456	302	37	isc2	isc2	PROPN
ajst-31456	302	38	)	)	PUNCT
ajst-31456	302	39	,	,	PUNCT
ajst-31456	302	40	2022	2022	NUM
ajst-31456	302	41	,	,	PUNCT
ajst-31456	302	42	pp	pp	ADV
ajst-31456	302	43	.	.	PUNCT
ajst-31456	303	1	1–4	1–4	NUM
ajst-31456	303	2	.	.	PUNCT
ajst-31456	304	1	[	[	X
ajst-31456	304	2	33	33	NUM
ajst-31456	304	3	]	]	PUNCT
ajst-31456	304	4	a.	a.	NOUN
ajst-31456	304	5	a.	a.	PROPN
ajst-31456	304	6	ramesh	ramesh	PROPN
ajst-31456	304	7	,	,	PUNCT
ajst-31456	304	8	s.	s.	PROPN
ajst-31456	304	9	p.	p.	PROPN
ajst-31456	304	10	nagisetti	nagisetti	PROPN
ajst-31456	304	11	,	,	PUNCT
ajst-31456	304	12	n.	n.	NOUN
ajst-31456	304	13	sridhar	sridhar	PROPN
ajst-31456	304	14	,	,	PUNCT
ajst-31456	304	15	k.	k.	PROPN
ajst-31456	304	16	avery	avery	PROPN
ajst-31456	304	17	,	,	PUNCT
ajst-31456	304	18	and	and	CCONJ
ajst-31456	304	19	d.	d.	PROPN
ajst-31456	304	20	bein	bein	PROPN
ajst-31456	304	21	,	,	PUNCT
ajst-31456	304	22	“	"	PUNCT
ajst-31456	304	23	station	station	NOUN
ajst-31456	304	24	-	-	PUNCT
ajst-31456	304	25	level	level	NOUN
ajst-31456	304	26	demand	demand	NOUN
ajst-31456	304	27	prediction	prediction	NOUN
ajst-31456	304	28	for	for	ADP
ajst-31456	304	29	bike	bike	NOUN
ajst-31456	304	30	-	-	PUNCT
ajst-31456	304	31	sharing	share	VERB
ajst-31456	304	32	system	system	NOUN
ajst-31456	304	33	,	,	PUNCT
ajst-31456	304	34	”	"	PUNCT
ajst-31456	304	35	in	in	ADP
ajst-31456	304	36	2021	2021	NUM
ajst-31456	304	37	ieee	ieee	NOUN
ajst-31456	304	38	11th	11th	NOUN
ajst-31456	304	39	annual	annual	ADJ
ajst-31456	304	40	computing	computing	NOUN
ajst-31456	304	41	and	and	CCONJ
ajst-31456	304	42	communication	communication	NOUN
ajst-31456	304	43	workshop	workshop	NOUN
ajst-31456	304	44	and	and	CCONJ
ajst-31456	304	45	conference	conference	NOUN
ajst-31456	304	46	(	(	PUNCT
ajst-31456	304	47	ccwc	ccwc	PROPN
ajst-31456	304	48	)	)	PUNCT
ajst-31456	304	49	,	,	PUNCT
ajst-31456	304	50	2021	2021	NUM
ajst-31456	304	51	,	,	PUNCT
ajst-31456	304	52	pp	pp	ADV
ajst-31456	304	53	.	.	PUNCT
ajst-31456	305	1	0916–0921	0916–0921	NUM
ajst-31456	305	2	.	.	PUNCT