id	sid	tid	token	lemma	pos
cana-1860	1	1	communications	communication	NOUN
cana-1860	1	2	on	on	ADP
cana-1860	1	3	applied	apply	VERB
cana-1860	1	4	nonlinear	nonlinear	ADJ
cana-1860	1	5	analysis	analysis	NOUN
cana-1860	1	6	issn	issn	NOUN
cana-1860	1	7	:	:	PUNCT
cana-1860	1	8	1074	1074	NUM
cana-1860	1	9	-	-	PUNCT
cana-1860	1	10	133x	133x	NUM
cana-1860	1	11	vol	vol	NOUN
cana-1860	1	12	32	32	NUM
cana-1860	1	13	no	no	NOUN
cana-1860	1	14	.	.	NOUN
cana-1860	1	15	2	2	NUM
cana-1860	1	16	(	(	PUNCT
cana-1860	1	17	2025	2025	NUM
cana-1860	1	18	)	)	PUNCT
cana-1860	2	1	666	666	NUM
cana-1860	2	2	https://internationalpubls.com	https://internationalpubls.com	X
cana-1860	2	3	design	design	NOUN
cana-1860	2	4	of	of	ADP
cana-1860	2	5	an	an	DET
cana-1860	2	6	improved	improved	ADJ
cana-1860	2	7	model	model	NOUN
cana-1860	2	8	for	for	ADP
cana-1860	2	9	multimodal	multimodal	NOUN
cana-1860	2	10	data	datum	NOUN
cana-1860	2	11	fusion	fusion	NOUN
cana-1860	2	12	using	use	VERB
cana-1860	2	13	xgboost	xgboost	ADJ
cana-1860	2	14	-	-	PUNCT
cana-1860	2	15	lstm	lstm	ADJ
cana-1860	2	16	-	-	PUNCT
cana-1860	2	17	cnn	cnn	PROPN
cana-1860	2	18	and	and	CCONJ
cana-1860	2	19	proximal	proximal	ADJ
cana-1860	2	20	policy	policy	NOUN
cana-1860	2	21	optimizations	optimization	NOUN
cana-1860	2	22	vijaya	vijaya	PROPN
cana-1860	2	23	kamble	kamble	ADJ
cana-1860	2	24	1	1	NUM
cana-1860	2	25	*	*	SYM
cana-1860	2	26	dr	dr	PROPN
cana-1860	2	27	.	.	PROPN
cana-1860	2	28	sanjay	sanjay	PROPN
cana-1860	2	29	bhargava	bhargava	PROPN
cana-1860	2	30	2	2	NUM
cana-1860	2	31	1	1	NUM
cana-1860	2	32	ph.d	ph.d	PROPN
cana-1860	2	33	research	research	NOUN
cana-1860	2	34	scholar	scholar	NOUN
cana-1860	2	35	,	,	PUNCT
cana-1860	2	36	department	department	NOUN
cana-1860	2	37	of	of	ADP
cana-1860	2	38	computer	computer	NOUN
cana-1860	2	39	science	science	NOUN
cana-1860	2	40	and	and	CCONJ
cana-1860	2	41	engineering	engineering	NOUN
cana-1860	2	42	,	,	PUNCT
cana-1860	2	43	mansarovar	mansarovar	PROPN
cana-1860	2	44	global	global	PROPN
cana-1860	2	45	university	university	PROPN
cana-1860	2	46	,	,	PUNCT
cana-1860	2	47	billkisganj	billkisganj	ADJ
cana-1860	2	48	,	,	PUNCT
cana-1860	2	49	sehore	sehore	PROPN
cana-1860	2	50	,	,	PUNCT
cana-1860	2	51	madhya	madhya	PROPN
cana-1860	2	52	pradesh-466001	pradesh-466001	NOUN
cana-1860	2	53	.	.	PUNCT
cana-1860	3	1	vijaya.kamble@ghrua.edu.in	vijaya.kamble@ghrua.edu.in	NOUN
cana-1860	3	2	,	,	PUNCT
cana-1860	3	3	2	2	NUM
cana-1860	3	4	research	research	NOUN
cana-1860	3	5	guide	guide	NOUN
cana-1860	3	6	,	,	PUNCT
cana-1860	3	7	department	department	NOUN
cana-1860	3	8	of	of	ADP
cana-1860	3	9	computer	computer	NOUN
cana-1860	3	10	science	science	NOUN
cana-1860	3	11	,	,	PUNCT
cana-1860	3	12	faculty	faculty	NOUN
cana-1860	3	13	of	of	ADP
cana-1860	3	14	engineering	engineering	NOUN
cana-1860	3	15	and	and	CCONJ
cana-1860	3	16	technology	technology	NOUN
cana-1860	3	17	,	,	PUNCT
cana-1860	3	18	mansarovar	mansarovar	PROPN
cana-1860	3	19	global	global	ADJ
cana-1860	3	20	university	university	NOUN
cana-1860	3	21	.	.	PUNCT
cana-1860	4	1	sanjaybhargava78@gmail.com	sanjaybhargava78@gmail.com	NOUN
cana-1860	4	2	article	article	NOUN
cana-1860	4	3	history	history	NOUN
cana-1860	4	4	:	:	PUNCT
cana-1860	4	5	received	receive	VERB
cana-1860	4	6	:	:	PUNCT
cana-1860	4	7	15	15	NUM
cana-1860	4	8	-	-	SYM
cana-1860	4	9	07	07	NUM
cana-1860	4	10	-	-	PUNCT
cana-1860	4	11	2024	2024	NUM
cana-1860	4	12	revised	revise	VERB
cana-1860	4	13	:	:	PUNCT
cana-1860	4	14	05	05	NUM
cana-1860	4	15	-	-	PUNCT
cana-1860	4	16	09	09	NUM
cana-1860	4	17	-	-	PUNCT
cana-1860	4	18	2024	2024	NUM
cana-1860	4	19	accepted	accept	VERB
cana-1860	4	20	:	:	PUNCT
cana-1860	4	21	28	28	NUM
cana-1860	4	22	-	-	SYM
cana-1860	4	23	09	09	NUM
cana-1860	4	24	-	-	PUNCT
cana-1860	4	25	2024	2024	NUM
cana-1860	4	26	abstract	abstract	NOUN
cana-1860	4	27	:	:	PUNCT
cana-1860	4	28	applications	application	NOUN
cana-1860	4	29	in	in	ADP
cana-1860	4	30	healthcare	healthcare	PROPN
cana-1860	4	31	,	,	PUNCT
cana-1860	4	32	finance	finance	NOUN
cana-1860	4	33	,	,	PUNCT
cana-1860	4	34	and	and	CCONJ
cana-1860	4	35	real	real	ADJ
cana-1860	4	36	-	-	PUNCT
cana-1860	4	37	time	time	NOUN
cana-1860	4	38	sensor	sensor	NOUN
cana-1860	4	39	applications	application	NOUN
cana-1860	4	40	call	call	VERB
cana-1860	4	41	for	for	ADP
cana-1860	4	42	much	much	ADV
cana-1860	4	43	stronger	strong	ADJ
cana-1860	4	44	demands	demand	NOUN
cana-1860	4	45	of	of	ADP
cana-1860	4	46	improving	improve	VERB
cana-1860	4	47	accuracy	accuracy	NOUN
cana-1860	4	48	and	and	CCONJ
cana-1860	4	49	efficiency	efficiency	NOUN
cana-1860	4	50	in	in	ADP
cana-1860	4	51	the	the	DET
cana-1860	4	52	analysis	analysis	NOUN
cana-1860	4	53	of	of	ADP
cana-1860	4	54	multimodal	multimodal	NOUN
cana-1860	4	55	data	datum	NOUN
cana-1860	4	56	.	.	PUNCT
cana-1860	5	1	current	current	ADJ
cana-1860	5	2	methods	method	NOUN
cana-1860	5	3	have	have	VERB
cana-1860	5	4	deficiencies	deficiency	NOUN
cana-1860	5	5	in	in	ADP
cana-1860	5	6	fusing	fuse	VERB
cana-1860	5	7	multiple	multiple	ADJ
cana-1860	5	8	types	type	NOUN
cana-1860	5	9	of	of	ADP
cana-1860	5	10	data	datum	NOUN
cana-1860	5	11	such	such	ADJ
cana-1860	5	12	as	as	ADP
cana-1860	5	13	time	time	NOUN
cana-1860	5	14	-	-	PUNCT
cana-1860	5	15	series	series	NOUN
cana-1860	5	16	,	,	PUNCT
cana-1860	5	17	spatial	spatial	ADJ
cana-1860	5	18	,	,	PUNCT
cana-1860	5	19	and	and	CCONJ
cana-1860	5	20	categorical	categorical	ADJ
cana-1860	5	21	data	datum	NOUN
cana-1860	5	22	,	,	PUNCT
cana-1860	5	23	arising	arise	VERB
cana-1860	5	24	due	due	ADP
cana-1860	5	25	to	to	ADP
cana-1860	5	26	limitations	limitation	NOUN
cana-1860	5	27	in	in	ADP
cana-1860	5	28	capturing	capture	VERB
cana-1860	5	29	sequential	sequential	ADJ
cana-1860	5	30	dependencies	dependency	NOUN
cana-1860	5	31	,	,	PUNCT
cana-1860	5	32	spatial	spatial	ADJ
cana-1860	5	33	patterns	pattern	NOUN
cana-1860	5	34	,	,	PUNCT
cana-1860	5	35	and	and	CCONJ
cana-1860	5	36	feature	feature	VERB
cana-1860	5	37	importance	importance	NOUN
cana-1860	5	38	simultaneously	simultaneously	ADV
cana-1860	5	39	.	.	PUNCT
cana-1860	6	1	it	it	PRON
cana-1860	6	2	also	also	ADV
cana-1860	6	3	discusses	discuss	VERB
cana-1860	6	4	these	these	DET
cana-1860	6	5	challenges	challenge	NOUN
cana-1860	6	6	through	through	ADP
cana-1860	6	7	a	a	DET
cana-1860	6	8	novel	novel	ADJ
cana-1860	6	9	solution	solution	NOUN
cana-1860	6	10	based	base	VERB
cana-1860	6	11	on	on	ADP
cana-1860	6	12	a	a	DET
cana-1860	6	13	hybrid	hybrid	ADJ
cana-1860	6	14	ml	ml	PROPN
cana-1860	6	15	-	-	PUNCT
cana-1860	6	16	dl	dl	NOUN
cana-1860	6	17	approach	approach	NOUN
cana-1860	6	18	,	,	PUNCT
cana-1860	6	19	with	with	ADP
cana-1860	6	20	an	an	DET
cana-1860	6	21	integration	integration	NOUN
cana-1860	6	22	of	of	ADP
cana-1860	6	23	reinforcement	reinforcement	NOUN
cana-1860	6	24	learning	learning	NOUN
cana-1860	6	25	and	and	CCONJ
cana-1860	6	26	advanced	advanced	ADJ
cana-1860	6	27	probabilistic	probabilistic	ADJ
cana-1860	6	28	models	model	NOUN
cana-1860	6	29	.	.	PUNCT
cana-1860	7	1	first	first	ADV
cana-1860	7	2	,	,	PUNCT
cana-1860	7	3	the	the	DET
cana-1860	7	4	method	method	NOUN
cana-1860	7	5	that	that	PRON
cana-1860	7	6	comes	come	VERB
cana-1860	7	7	to	to	ADP
cana-1860	7	8	mind	mind	NOUN
cana-1860	7	9	is	be	AUX
cana-1860	7	10	the	the	DET
cana-1860	7	11	xgboost	xgboost	ADJ
cana-1860	7	12	-	-	PUNCT
cana-1860	7	13	lstm	lstm	ADJ
cana-1860	7	14	-	-	PUNCT
cana-1860	7	15	cnn	cnn	PROPN
cana-1860	7	16	hybrid	hybrid	NOUN
cana-1860	7	17	model	model	NOUN
cana-1860	7	18	,	,	PUNCT
cana-1860	7	19	wherein	wherein	SCONJ
cana-1860	7	20	three	three	NUM
cana-1860	7	21	drivers	driver	NOUN
cana-1860	7	22	of	of	ADP
cana-1860	7	23	performance	performance	NOUN
cana-1860	7	24	improvements	improvement	NOUN
cana-1860	7	25	come	come	VERB
cana-1860	7	26	together	together	ADV
cana-1860	7	27	,	,	PUNCT
cana-1860	7	28	namely	namely	ADV
cana-1860	7	29	,	,	PUNCT
cana-1860	7	30	xgboost	xgboost	ADV
cana-1860	7	31	,	,	PUNCT
cana-1860	7	32	with	with	ADP
cana-1860	7	33	much	much	ADV
cana-1860	7	34	-	-	PUNCT
cana-1860	7	35	appreciated	appreciated	ADJ
cana-1860	7	36	capability	capability	NOUN
cana-1860	7	37	for	for	ADP
cana-1860	7	38	outstanding	outstanding	ADJ
cana-1860	7	39	handling	handling	NOUN
cana-1860	7	40	of	of	ADP
cana-1860	7	41	structured	structured	ADJ
cana-1860	7	42	tabular	tabular	PROPN
cana-1860	7	43	data	datum	NOUN
cana-1860	7	44	,	,	PUNCT
cana-1860	7	45	lstm	lstm	NOUN
cana-1860	7	46	due	due	ADP
cana-1860	7	47	to	to	ADP
cana-1860	7	48	its	its	PRON
cana-1860	7	49	proficiency	proficiency	NOUN
cana-1860	7	50	in	in	ADP
cana-1860	7	51	capturing	capture	VERB
cana-1860	7	52	long	long	ADJ
cana-1860	7	53	-	-	PUNCT
cana-1860	7	54	term	term	NOUN
cana-1860	7	55	temporal	temporal	ADJ
cana-1860	7	56	dependencies	dependency	NOUN
cana-1860	7	57	,	,	PUNCT
cana-1860	7	58	and	and	CCONJ
cana-1860	7	59	the	the	DET
cana-1860	7	60	strength	strength	NOUN
cana-1860	7	61	of	of	ADP
cana-1860	7	62	cnn	cnn	PROPN
cana-1860	7	63	in	in	ADP
cana-1860	7	64	spatial	spatial	ADJ
cana-1860	7	65	feature	feature	NOUN
cana-1860	7	66	extraction	extraction	NOUN
cana-1860	7	67	.	.	PUNCT
cana-1860	8	1	these	these	DET
cana-1860	8	2	results	result	NOUN
cana-1860	8	3	improve	improve	VERB
cana-1860	8	4	the	the	DET
cana-1860	8	5	predictive	predictive	ADJ
cana-1860	8	6	accuracy	accuracy	NOUN
cana-1860	8	7	for	for	ADP
cana-1860	8	8	multimodal	multimodal	NOUN
cana-1860	8	9	datasets	dataset	NOUN
cana-1860	8	10	.	.	PUNCT
cana-1860	9	1	after	after	ADP
cana-1860	9	2	that	that	PRON
cana-1860	9	3	,	,	PUNCT
cana-1860	9	4	further	far	ADV
cana-1860	9	5	enhanced	enhance	VERB
cana-1860	9	6	multimodal	multimodal	NOUN
cana-1860	9	7	fusion	fusion	NOUN
cana-1860	9	8	by	by	ADP
cana-1860	9	9	the	the	DET
cana-1860	9	10	camt	camt	PROPN
cana-1860	9	11	selectively	selectively	ADV
cana-1860	9	12	pays	pay	VERB
cana-1860	9	13	attention	attention	NOUN
cana-1860	9	14	to	to	ADP
cana-1860	9	15	the	the	DET
cana-1860	9	16	critical	critical	ADJ
cana-1860	9	17	features	feature	NOUN
cana-1860	9	18	across	across	ADP
cana-1860	9	19	the	the	DET
cana-1860	9	20	modalities	modality	NOUN
cana-1860	9	21	,	,	PUNCT
cana-1860	9	22	enhancing	enhance	VERB
cana-1860	9	23	the	the	DET
cana-1860	9	24	accuracy	accuracy	NOUN
cana-1860	9	25	of	of	ADP
cana-1860	9	26	the	the	DET
cana-1860	9	27	contextual	contextual	ADJ
cana-1860	9	28	time	time	NOUN
cana-1860	9	29	-	-	PUNCT
cana-1860	9	30	series	series	NOUN
cana-1860	9	31	predictions	prediction	NOUN
cana-1860	9	32	.	.	PUNCT
cana-1860	10	1	subsequently	subsequently	ADV
cana-1860	10	2	,	,	PUNCT
cana-1860	10	3	ppo	ppo	PROPN
cana-1860	10	4	enables	enable	VERB
cana-1860	10	5	real	real	ADJ
cana-1860	10	6	-	-	PUNCT
cana-1860	10	7	time	time	NOUN
cana-1860	10	8	model	model	NOUN
cana-1860	10	9	adaptation	adaptation	NOUN
cana-1860	10	10	by	by	ADP
cana-1860	10	11	dynamic	dynamic	ADJ
cana-1860	10	12	optimization	optimization	NOUN
cana-1860	10	13	of	of	ADP
cana-1860	10	14	model	model	NOUN
cana-1860	10	15	parameters	parameter	NOUN
cana-1860	10	16	and	and	CCONJ
cana-1860	10	17	improvement	improvement	NOUN
cana-1860	10	18	of	of	ADP
cana-1860	10	19	predictions	prediction	NOUN
cana-1860	10	20	through	through	ADP
cana-1860	10	21	continuous	continuous	ADJ
cana-1860	10	22	learning	learning	NOUN
cana-1860	10	23	.	.	PUNCT
cana-1860	11	1	kf	kf	PROPN
cana-1860	11	2	-	-	PUNCT
cana-1860	11	3	bnn	bnn	PROPN
cana-1860	11	4	reduces	reduce	VERB
cana-1860	11	5	noise	noise	NOUN
cana-1860	11	6	and	and	CCONJ
cana-1860	11	7	uncertainty	uncertainty	NOUN
cana-1860	11	8	in	in	ADP
cana-1860	11	9	timeseries	timeserie	NOUN
cana-1860	11	10	data	datum	NOUN
cana-1860	11	11	by	by	ADP
cana-1860	11	12	fusing	fuse	VERB
cana-1860	11	13	the	the	DET
cana-1860	11	14	filtering	filtering	NOUN
cana-1860	11	15	capability	capability	NOUN
cana-1860	11	16	of	of	ADP
cana-1860	11	17	a	a	DET
cana-1860	11	18	kalman	kalman	NOUN
cana-1860	11	19	filter	filter	NOUN
cana-1860	11	20	with	with	ADP
cana-1860	11	21	probabilistic	probabilistic	ADJ
cana-1860	11	22	modeling	modeling	NOUN
cana-1860	11	23	via	via	ADP
cana-1860	11	24	bayesian	bayesian	NOUN
cana-1860	11	25	neural	neural	ADJ
cana-1860	11	26	networks	network	NOUN
cana-1860	11	27	to	to	PART
cana-1860	11	28	give	give	VERB
cana-1860	11	29	reliable	reliable	ADJ
cana-1860	11	30	predictions	prediction	NOUN
cana-1860	11	31	.	.	PUNCT
cana-1860	12	1	it	it	PRON
cana-1860	12	2	also	also	ADV
cana-1860	12	3	provides	provide	VERB
cana-1860	12	4	federated	federated	ADJ
cana-1860	12	5	learning	learning	NOUN
cana-1860	12	6	via	via	ADP
cana-1860	12	7	fedavg	fedavg	NOUN
cana-1860	12	8	with	with	ADP
cana-1860	12	9	online	online	ADJ
cana-1860	12	10	gradient	gradient	ADJ
cana-1860	12	11	descent	descent	NOUN
cana-1860	12	12	for	for	ADP
cana-1860	12	13	distributed	distributed	ADJ
cana-1860	12	14	model	model	NOUN
cana-1860	12	15	training	training	NOUN
cana-1860	12	16	in	in	ADP
cana-1860	12	17	a	a	DET
cana-1860	12	18	manner	manner	NOUN
cana-1860	12	19	that	that	PRON
cana-1860	12	20	ensures	ensure	VERB
cana-1860	12	21	privacy	privacy	NOUN
cana-1860	12	22	,	,	PUNCT
cana-1860	12	23	continuous	continuous	ADJ
cana-1860	12	24	model	model	NOUN
cana-1860	12	25	updates	update	NOUN
cana-1860	12	26	without	without	ADP
cana-1860	12	27	having	have	VERB
cana-1860	12	28	to	to	PART
cana-1860	12	29	centralize	centralize	VERB
cana-1860	12	30	sensitive	sensitive	ADJ
cana-1860	12	31	data	datum	NOUN
cana-1860	12	32	samples	sample	NOUN
cana-1860	12	33	.	.	PUNCT
cana-1860	13	1	these	these	DET
cana-1860	13	2	approaches	approach	NOUN
cana-1860	13	3	show	show	VERB
cana-1860	13	4	significant	significant	ADJ
cana-1860	13	5	improvements	improvement	NOUN
cana-1860	13	6	along	along	ADP
cana-1860	13	7	many	many	ADJ
cana-1860	13	8	axes	axis	NOUN
cana-1860	13	9	,	,	PUNCT
cana-1860	13	10	with	with	ADP
cana-1860	13	11	accuracy	accuracy	NOUN
cana-1860	13	12	improvements	improvement	NOUN
cana-1860	13	13	of	of	ADP
cana-1860	13	14	up	up	ADP
cana-1860	13	15	to	to	PART
cana-1860	13	16	4.5	4.5	NUM
cana-1860	13	17	%	%	NOUN
cana-1860	13	18	and	and	CCONJ
cana-1860	13	19	mae	mae	PROPN
cana-1860	13	20	reductions	reduction	NOUN
cana-1860	13	21	of	of	ADP
cana-1860	13	22	12	12	NUM
cana-1860	13	23	%	%	NOUN
cana-1860	13	24	relative	relative	ADJ
cana-1860	13	25	to	to	ADP
cana-1860	13	26	the	the	DET
cana-1860	13	27	baseline	baseline	NOUN
cana-1860	13	28	models	model	NOUN
cana-1860	13	29	.	.	PUNCT
cana-1860	14	1	proposed	propose	VERB
cana-1860	14	2	models	model	NOUN
cana-1860	14	3	provide	provide	VERB
cana-1860	14	4	a	a	DET
cana-1860	14	5	valid	valid	ADJ
cana-1860	14	6	framework	framework	NOUN
cana-1860	14	7	for	for	ADP
cana-1860	14	8	analyzing	analyze	VERB
cana-1860	14	9	multimodal	multimodal	ADJ
cana-1860	14	10	data	datum	NOUN
cana-1860	14	11	,	,	PUNCT
cana-1860	14	12	thereby	thereby	ADV
cana-1860	14	13	increasing	increase	VERB
cana-1860	14	14	precision	precision	NOUN
cana-1860	14	15	,	,	PUNCT
cana-1860	14	16	recall	recall	NOUN
cana-1860	14	17	,	,	PUNCT
cana-1860	14	18	and	and	CCONJ
cana-1860	14	19	overall	overall	ADJ
cana-1860	14	20	adaptiveness	adaptiveness	NOUN
cana-1860	14	21	in	in	ADP
cana-1860	14	22	dynamic	dynamic	ADJ
cana-1860	14	23	real	real	ADJ
cana-1860	14	24	time	time	NOUN
cana-1860	14	25	,	,	PUNCT
cana-1860	14	26	hence	hence	ADV
cana-1860	14	27	pushing	push	VERB
cana-1860	14	28	the	the	DET
cana-1860	14	29	state	state	NOUN
cana-1860	14	30	-	-	PUNCT
cana-1860	14	31	of	of	ADP
cana-1860	14	32	-	-	PUNCT
cana-1860	14	33	the	the	DET
cana-1860	14	34	-	-	PUNCT
cana-1860	14	35	art	art	NOUN
cana-1860	14	36	in	in	ADP
cana-1860	14	37	multimodal	multimodal	NOUN
cana-1860	14	38	fusion	fusion	NOUN
cana-1860	14	39	and	and	CCONJ
cana-1860	14	40	timeseries	timeserie	NOUN
cana-1860	14	41	prediction	prediction	NOUN
cana-1860	14	42	.	.	PUNCT
cana-1860	15	1	this	this	DET
cana-1860	15	2	research	research	NOUN
cana-1860	15	3	probably	probably	ADV
cana-1860	15	4	will	will	AUX
cana-1860	15	5	influence	influence	VERB
cana-1860	15	6	those	those	DET
cana-1860	15	7	areas	area	NOUN
cana-1860	15	8	dependent	dependent	ADJ
cana-1860	15	9	on	on	ADP
cana-1860	15	10	distributed	distribute	VERB
cana-1860	15	11	,	,	PUNCT
cana-1860	15	12	multimodal	multimodal	NOUN
cana-1860	15	13	,	,	PUNCT
cana-1860	15	14	and	and	CCONJ
cana-1860	15	15	sequential	sequential	ADJ
cana-1860	15	16	data	datum	NOUN
cana-1860	15	17	samples	sample	NOUN
cana-1860	15	18	.	.	PUNCT
cana-1860	16	1	keywords	keyword	NOUN
cana-1860	16	2	:	:	PUNCT
cana-1860	16	3	multimodal	multimodal	NOUN
cana-1860	16	4	fusion	fusion	NOUN
cana-1860	16	5	,	,	PUNCT
cana-1860	16	6	xgboost	xgboost	NUM
cana-1860	16	7	,	,	PUNCT
cana-1860	16	8	lstm	lstm	ADJ
cana-1860	16	9	,	,	PUNCT
cana-1860	16	10	proximal	proximal	ADJ
cana-1860	16	11	policy	policy	NOUN
cana-1860	16	12	optimization	optimization	NOUN
cana-1860	16	13	,	,	PUNCT
cana-1860	16	14	timeseries	timeserie	NOUN
cana-1860	16	15	predictions	prediction	NOUN
cana-1860	16	16	1	1	NUM
cana-1860	16	17	.	.	PUNCT
cana-1860	17	1	introduction	introduction	NOUN
cana-1860	17	2	modern	modern	ADJ
cana-1860	17	3	streams	stream	NOUN
cana-1860	17	4	of	of	ADP
cana-1860	17	5	data	datum	NOUN
cana-1860	17	6	have	have	AUX
cana-1860	17	7	become	become	VERB
cana-1860	17	8	so	so	ADV
cana-1860	17	9	complex	complex	ADJ
cana-1860	17	10	and	and	CCONJ
cana-1860	17	11	diverse	diverse	ADJ
cana-1860	17	12	,	,	PUNCT
cana-1860	17	13	from	from	ADP
cana-1860	17	14	time	time	NOUN
cana-1860	17	15	-	-	PUNCT
cana-1860	17	16	series	series	NOUN
cana-1860	17	17	to	to	ADP
cana-1860	17	18	audio	audio	NOUN
cana-1860	17	19	,	,	PUNCT
cana-1860	17	20	video	video	NOUN
cana-1860	17	21	,	,	PUNCT
cana-1860	17	22	and	and	CCONJ
cana-1860	17	23	sensor	sensor	NOUN
cana-1860	17	24	data	datum	NOUN
cana-1860	17	25	;	;	PUNCT
cana-1860	17	26	thus	thus	ADV
cana-1860	17	27	,	,	PUNCT
cana-1860	17	28	they	they	PRON
cana-1860	17	29	inherently	inherently	ADV
cana-1860	17	30	demand	demand	VERB
cana-1860	17	31	advanced	advanced	ADJ
cana-1860	17	32	models	model	NOUN
cana-1860	17	33	that	that	PRON
cana-1860	17	34	can	can	AUX
cana-1860	17	35	handle	handle	VERB
cana-1860	17	36	sets	set	NOUN
cana-1860	17	37	of	of	ADP
cana-1860	17	38	information	information	NOUN
cana-1860	17	39	with	with	ADP
cana-1860	17	40	multiple	multiple	ADJ
cana-1860	17	41	modes	mode	NOUN
cana-1860	17	42	.	.	PUNCT
cana-1860	18	1	traditional	traditional	ADJ
cana-1860	18	2	machine	machine	NOUN
cana-1860	18	3	learning	learning	NOUN
cana-1860	18	4	and	and	CCONJ
cana-1860	18	5	deep	deep	ADJ
cana-1860	18	6	learning	learning	NOUN
cana-1860	18	7	methods	method	NOUN
cana-1860	18	8	are	be	AUX
cana-1860	18	9	effective	effective	ADJ
cana-1860	18	10	in	in	ADP
cana-1860	18	11	individual	individual	ADJ
cana-1860	18	12	mailto:sanjaybhargava78@gmail.com	mailto:sanjaybhargava78@gmail.com	NOUN
cana-1860	18	13	communications	communication	NOUN
cana-1860	18	14	on	on	ADP
cana-1860	18	15	applied	apply	VERB
cana-1860	18	16	nonlinear	nonlinear	ADJ
cana-1860	18	17	analysis	analysis	NOUN
cana-1860	18	18	issn	issn	NOUN
cana-1860	18	19	:	:	PUNCT
cana-1860	18	20	1074	1074	NUM
cana-1860	18	21	-	-	PUNCT
cana-1860	18	22	133x	133x	NUM
cana-1860	18	23	vol	vol	NOUN
cana-1860	18	24	32	32	NUM
cana-1860	18	25	no	no	NOUN
cana-1860	18	26	.	.	NOUN
cana-1860	18	27	2	2	NUM
cana-1860	18	28	(	(	PUNCT
cana-1860	18	29	2025	2025	NUM
cana-1860	18	30	)	)	PUNCT
cana-1860	18	31	667	667	NUM
cana-1860	18	32	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-1860	18	33	domains	domain	NOUN
cana-1860	18	34	but	but	CCONJ
cana-1860	18	35	usually	usually	ADV
cana-1860	18	36	fail	fail	VERB
cana-1860	18	37	in	in	ADP
cana-1860	18	38	the	the	DET
cana-1860	18	39	integration	integration	NOUN
cana-1860	18	40	and	and	CCONJ
cana-1860	18	41	joint	joint	ADJ
cana-1860	18	42	analysis	analysis	NOUN
cana-1860	18	43	of	of	ADP
cana-1860	18	44	such	such	ADJ
cana-1860	18	45	heterogeneous	heterogeneous	ADJ
cana-1860	18	46	data	datum	NOUN
cana-1860	18	47	types	type	NOUN
cana-1860	18	48	.	.	PUNCT
cana-1860	19	1	the	the	DET
cana-1860	19	2	current	current	ADJ
cana-1860	19	3	architectures	architecture	NOUN
cana-1860	19	4	are	be	AUX
cana-1860	19	5	not	not	PART
cana-1860	19	6	able	able	ADJ
cana-1860	19	7	to	to	PART
cana-1860	19	8	capture	capture	VERB
cana-1860	19	9	underlying	underlie	VERB
cana-1860	19	10	temporal	temporal	ADJ
cana-1860	19	11	dependencies	dependency	NOUN
cana-1860	19	12	,	,	PUNCT
cana-1860	19	13	spatial	spatial	ADJ
cana-1860	19	14	correlations	correlation	NOUN
cana-1860	19	15	,	,	PUNCT
cana-1860	19	16	and	and	CCONJ
cana-1860	19	17	varied	varied	ADJ
cana-1860	19	18	structures	structure	NOUN
cana-1860	19	19	of	of	ADP
cana-1860	19	20	real	real	ADJ
cana-1860	19	21	-	-	PUNCT
cana-1860	19	22	world	world	NOUN
cana-1860	19	23	applications	application	NOUN
cana-1860	19	24	in	in	ADP
cana-1860	19	25	health	health	NOUN
cana-1860	19	26	care	care	NOUN
cana-1860	19	27	,	,	PUNCT
cana-1860	19	28	finance	finance	NOUN
cana-1860	19	29	,	,	PUNCT
cana-1860	19	30	or	or	CCONJ
cana-1860	19	31	autonomous	autonomous	ADJ
cana-1860	19	32	systems	system	NOUN
cana-1860	19	33	.	.	PUNCT
cana-1860	20	1	very	very	ADV
cana-1860	20	2	often	often	ADV
cana-1860	20	3	,	,	PUNCT
cana-1860	20	4	approaches	approach	VERB
cana-1860	20	5	for	for	ADP
cana-1860	20	6	multimodal	multimodal	NOUN
cana-1860	20	7	data	datum	NOUN
cana-1860	20	8	analytics	analytic	NOUN
cana-1860	20	9	employ	employ	NOUN
cana-1860	20	10	models	model	NOUN
cana-1860	20	11	tailored	tailor	VERB
cana-1860	20	12	for	for	ADP
cana-1860	20	13	either	either	DET
cana-1860	20	14	tabular	tabular	NOUN
cana-1860	20	15	,	,	PUNCT
cana-1860	20	16	sequential	sequential	ADJ
cana-1860	20	17	,	,	PUNCT
cana-1860	20	18	or	or	CCONJ
cana-1860	20	19	spatial	spatial	ADJ
cana-1860	20	20	data	data	NOUN
cana-1860	20	21	samples	sample	NOUN
cana-1860	20	22	.	.	PUNCT
cana-1860	21	1	for	for	ADP
cana-1860	21	2	instance	instance	NOUN
cana-1860	21	3	,	,	PUNCT
cana-1860	21	4	models	model	NOUN
cana-1860	21	5	like	like	ADP
cana-1860	21	6	lstm	lstm	NOUN
cana-1860	21	7	[	[	X
cana-1860	21	8	4	4	NUM
cana-1860	21	9	,	,	PUNCT
cana-1860	21	10	5	5	NUM
cana-1860	21	11	,	,	PUNCT
cana-1860	21	12	6	6	NUM
cana-1860	21	13	]	]	PUNCT
cana-1860	21	14	are	be	AUX
cana-1860	21	15	quite	quite	ADV
cana-1860	21	16	effective	effective	ADJ
cana-1860	21	17	for	for	ADP
cana-1860	21	18	time	time	NOUN
cana-1860	21	19	-	-	PUNCT
cana-1860	21	20	series	series	NOUN
cana-1860	21	21	analysis	analysis	NOUN
cana-1860	21	22	owing	owe	VERB
cana-1860	21	23	to	to	ADP
cana-1860	21	24	the	the	DET
cana-1860	21	25	presence	presence	NOUN
cana-1860	21	26	of	of	ADP
cana-1860	21	27	long	long	ADJ
cana-1860	21	28	-	-	PUNCT
cana-1860	21	29	term	term	NOUN
cana-1860	21	30	dependencies	dependency	NOUN
cana-1860	21	31	,	,	PUNCT
cana-1860	21	32	while	while	SCONJ
cana-1860	21	33	cnns	cnn	NOUN
cana-1860	21	34	act	act	VERB
cana-1860	21	35	as	as	ADP
cana-1860	21	36	strong	strong	ADJ
cana-1860	21	37	tools	tool	NOUN
cana-1860	21	38	to	to	PART
cana-1860	21	39	extract	extract	VERB
cana-1860	21	40	spatial	spatial	ADJ
cana-1860	21	41	features	feature	NOUN
cana-1860	21	42	from	from	ADP
cana-1860	21	43	image	image	NOUN
cana-1860	21	44	sequences	sequence	NOUN
cana-1860	21	45	or	or	CCONJ
cana-1860	21	46	sensor	sensor	NOUN
cana-1860	21	47	data	datum	NOUN
cana-1860	21	48	samples	sample	NOUN
cana-1860	21	49	.	.	PUNCT
cana-1860	22	1	however	however	ADV
cana-1860	22	2	,	,	PUNCT
cana-1860	22	3	most	most	ADJ
cana-1860	22	4	of	of	ADP
cana-1860	22	5	these	these	DET
cana-1860	22	6	methods	method	NOUN
cana-1860	22	7	,	,	PUNCT
cana-1860	22	8	when	when	SCONJ
cana-1860	22	9	applied	apply	VERB
cana-1860	22	10	separately	separately	ADV
cana-1860	22	11	,	,	PUNCT
cana-1860	22	12	can	can	AUX
cana-1860	22	13	hardly	hardly	ADV
cana-1860	22	14	ensure	ensure	VERB
cana-1860	22	15	robust	robust	ADJ
cana-1860	22	16	performance	performance	NOUN
cana-1860	22	17	for	for	ADP
cana-1860	22	18	a	a	DET
cana-1860	22	19	fully	fully	ADV
cana-1860	22	20	integrated	integrate	VERB
cana-1860	22	21	multimodal	multimodal	NOUN
cana-1860	22	22	approach	approach	NOUN
cana-1860	22	23	in	in	ADP
cana-1860	22	24	dynamic	dynamic	ADJ
cana-1860	22	25	and	and	CCONJ
cana-1860	22	26	noisy	noisy	ADJ
cana-1860	22	27	environments	environment	NOUN
cana-1860	22	28	.	.	PUNCT
cana-1860	23	1	besides	besides	SCONJ
cana-1860	23	2	,	,	PUNCT
cana-1860	23	3	classic	classic	ADJ
cana-1860	23	4	machine	machine	NOUN
cana-1860	23	5	learning	learning	NOUN
cana-1860	23	6	algorithms	algorithm	NOUN
cana-1860	23	7	,	,	PUNCT
cana-1860	23	8	such	such	ADJ
cana-1860	23	9	as	as	ADP
cana-1860	23	10	decision	decision	NOUN
cana-1860	23	11	trees	tree	NOUN
cana-1860	23	12	and	and	CCONJ
cana-1860	23	13	gradient	gradient	NOUN
cana-1860	23	14	boosting	boosting	NOUN
cana-1860	23	15	,	,	PUNCT
cana-1860	23	16	of	of	ADP
cana-1860	23	17	which	which	PRON
cana-1860	23	18	examples	example	NOUN
cana-1860	23	19	are	be	AUX
cana-1860	23	20	models	model	NOUN
cana-1860	23	21	like	like	ADP
cana-1860	23	22	xgboost	xgboost	ADV
cana-1860	23	23	,	,	PUNCT
cana-1860	23	24	are	be	AUX
cana-1860	23	25	very	very	ADV
cana-1860	23	26	good	good	ADJ
cana-1860	23	27	at	at	ADP
cana-1860	23	28	structured	structure	VERB
cana-1860	23	29	tabular	tabular	NOUN
cana-1860	23	30	data	datum	NOUN
cana-1860	23	31	and	and	CCONJ
cana-1860	23	32	able	able	ADJ
cana-1860	23	33	to	to	PART
cana-1860	23	34	show	show	VERB
cana-1860	23	35	feature	feature	NOUN
cana-1860	23	36	importance	importance	NOUN
cana-1860	23	37	,	,	PUNCT
cana-1860	23	38	while	while	SCONJ
cana-1860	23	39	rather	rather	ADV
cana-1860	23	40	limited	limit	VERB
cana-1860	23	41	in	in	ADP
cana-1860	23	42	sequential	sequential	ADJ
cana-1860	23	43	data	datum	NOUN
cana-1860	23	44	modeling	modeling	NOUN
cana-1860	23	45	.	.	PUNCT
cana-1860	24	1	hybrid	hybrid	ADJ
cana-1860	24	2	approaches	approach	NOUN
cana-1860	24	3	can	can	AUX
cana-1860	24	4	combine	combine	VERB
cana-1860	24	5	the	the	DET
cana-1860	24	6	strengths	strength	NOUN
cana-1860	24	7	of	of	ADP
cana-1860	24	8	various	various	ADJ
cana-1860	24	9	models	model	NOUN
cana-1860	24	10	and	and	CCONJ
cana-1860	24	11	hence	hence	ADV
cana-1860	24	12	have	have	VERB
cana-1860	24	13	a	a	DET
cana-1860	24	14	great	great	ADJ
cana-1860	24	15	potential	potential	NOUN
cana-1860	24	16	to	to	PART
cana-1860	24	17	resolve	resolve	VERB
cana-1860	24	18	these	these	DET
cana-1860	24	19	limitations	limitation	NOUN
cana-1860	24	20	.	.	PUNCT
cana-1860	25	1	it	it	PRON
cana-1860	25	2	introduces	introduce	VERB
cana-1860	25	3	an	an	DET
cana-1860	25	4	overall	overall	ADJ
cana-1860	25	5	model	model	NOUN
cana-1860	25	6	that	that	PRON
cana-1860	25	7	integrates	integrate	VERB
cana-1860	25	8	xgboost	xgboost	ADV
cana-1860	25	9	with	with	ADP
cana-1860	25	10	the	the	DET
cana-1860	25	11	deep	deep	ADJ
cana-1860	25	12	learning	learning	NOUN
cana-1860	25	13	mechanisms	mechanism	NOUN
cana-1860	25	14	,	,	PUNCT
cana-1860	25	15	lstm	lstm	NOUN
cana-1860	25	16	and	and	CCONJ
cana-1860	25	17	cnn	cnn	PROPN
cana-1860	25	18	,	,	PUNCT
cana-1860	25	19	to	to	PART
cana-1860	25	20	improve	improve	VERB
cana-1860	25	21	multiple	multiple	ADJ
cana-1860	25	22	modal	modal	ADJ
cana-1860	25	23	fusion	fusion	NOUN
cana-1860	25	24	.	.	PUNCT
cana-1860	26	1	this	this	DET
cana-1860	26	2	paper	paper	NOUN
cana-1860	26	3	then	then	ADV
cana-1860	26	4	goes	go	VERB
cana-1860	26	5	on	on	ADP
cana-1860	26	6	to	to	PART
cana-1860	26	7	propose	propose	VERB
cana-1860	26	8	proximal	proximal	ADJ
cana-1860	26	9	policy	policy	NOUN
cana-1860	26	10	optimization	optimization	NOUN
cana-1860	26	11	,	,	PUNCT
cana-1860	26	12	reinforcement	reinforcement	NOUN
cana-1860	26	13	learning	learning	NOUN
cana-1860	26	14	that	that	PRON
cana-1860	26	15	dynamically	dynamically	ADV
cana-1860	26	16	adjusts	adjust	VERB
cana-1860	26	17	model	model	NOUN
cana-1860	26	18	parameters	parameter	NOUN
cana-1860	26	19	in	in	ADP
cana-1860	26	20	real	real	ADJ
cana-1860	26	21	-	-	PUNCT
cana-1860	26	22	time	time	NOUN
cana-1860	26	23	to	to	PART
cana-1860	26	24	adapt	adapt	VERB
cana-1860	26	25	to	to	ADP
cana-1860	26	26	continuous	continuous	ADJ
cana-1860	26	27	changes	change	NOUN
cana-1860	26	28	in	in	ADP
cana-1860	26	29	data	datum	NOUN
cana-1860	26	30	.	.	PUNCT
cana-1860	27	1	complementing	complement	VERB
cana-1860	27	2	these	these	DET
cana-1860	27	3	methods	method	NOUN
cana-1860	27	4	is	be	AUX
cana-1860	27	5	the	the	DET
cana-1860	27	6	adoption	adoption	NOUN
cana-1860	27	7	of	of	ADP
cana-1860	27	8	kfbnn	kfbnn	PROPN
cana-1860	27	9	kalman	kalman	PROPN
cana-1860	27	10	filter	filter	PROPN
cana-1860	27	11	-	-	PUNCT
cana-1860	27	12	based	base	VERB
cana-1860	27	13	bayesian	bayesian	NOUN
cana-1860	27	14	neural	neural	ADJ
cana-1860	27	15	network	network	NOUN
cana-1860	27	16	,	,	PUNCT
cana-1860	27	17	improving	improve	VERB
cana-1860	27	18	the	the	DET
cana-1860	27	19	quality	quality	NOUN
cana-1860	27	20	of	of	ADP
cana-1860	27	21	the	the	DET
cana-1860	27	22	predictions	prediction	NOUN
cana-1860	27	23	by	by	ADP
cana-1860	27	24	filtering	filter	VERB
cana-1860	27	25	noise	noise	NOUN
cana-1860	27	26	and	and	CCONJ
cana-1860	27	27	including	include	VERB
cana-1860	27	28	the	the	DET
cana-1860	27	29	estimation	estimation	NOUN
cana-1860	27	30	of	of	ADP
cana-1860	27	31	uncertainty	uncertainty	NOUN
cana-1860	27	32	.	.	PUNCT
cana-1860	28	1	finally	finally	ADV
cana-1860	28	2	,	,	PUNCT
cana-1860	28	3	federated	federate	VERB
cana-1860	28	4	learning	learning	NOUN
cana-1860	28	5	using	use	VERB
cana-1860	28	6	fedavg	fedavg	NOUN
cana-1860	28	7	provides	provide	VERB
cana-1860	28	8	model	model	NOUN
cana-1860	28	9	adaptations	adaptation	NOUN
cana-1860	28	10	across	across	ADP
cana-1860	28	11	different	different	ADJ
cana-1860	28	12	edge	edge	NOUN
cana-1860	28	13	devices	device	NOUN
cana-1860	28	14	in	in	ADP
cana-1860	28	15	a	a	DET
cana-1860	28	16	distributed	distribute	VERB
cana-1860	28	17	fashion	fashion	NOUN
cana-1860	28	18	,	,	PUNCT
cana-1860	28	19	enabling	enable	VERB
cana-1860	28	20	data	datum	NOUN
cana-1860	28	21	privacy	privacy	NOUN
cana-1860	28	22	and	and	CCONJ
cana-1860	28	23	continuous	continuous	ADJ
cana-1860	28	24	learning	learning	NOUN
cana-1860	28	25	from	from	ADP
cana-1860	28	26	decentralized	decentralized	ADJ
cana-1860	28	27	sources	source	NOUN
cana-1860	28	28	.	.	PUNCT
cana-1860	29	1	in	in	ADP
cana-1860	29	2	this	this	DET
cana-1860	29	3	way	way	NOUN
cana-1860	29	4	,	,	PUNCT
cana-1860	29	5	the	the	DET
cana-1860	29	6	proposed	propose	VERB
cana-1860	29	7	hybrid	hybrid	NOUN
cana-1860	29	8	framework	framework	NOUN
cana-1860	29	9	significantly	significantly	ADV
cana-1860	29	10	improves	improve	VERB
cana-1860	29	11	the	the	DET
cana-1860	29	12	shortcomings	shortcoming	NOUN
cana-1860	29	13	of	of	ADP
cana-1860	29	14	traditional	traditional	ADJ
cana-1860	29	15	techniques	technique	NOUN
cana-1860	29	16	of	of	ADP
cana-1860	29	17	multimodal	multimodal	NOUN
cana-1860	29	18	fusion	fusion	NOUN
cana-1860	29	19	and	and	CCONJ
cana-1860	29	20	yields	yield	NOUN
cana-1860	29	21	improved	improve	VERB
cana-1860	29	22	precision	precision	NOUN
cana-1860	29	23	,	,	PUNCT
cana-1860	29	24	recall	recall	NOUN
cana-1860	29	25	,	,	PUNCT
cana-1860	29	26	and	and	CCONJ
cana-1860	29	27	overall	overall	ADJ
cana-1860	29	28	prediction	prediction	NOUN
cana-1860	29	29	accuracy	accuracy	NOUN
cana-1860	29	30	.	.	PUNCT
cana-1860	30	1	the	the	DET
cana-1860	30	2	model	model	NOUN
cana-1860	30	3	proposed	propose	VERB
cana-1860	30	4	will	will	AUX
cana-1860	30	5	provide	provide	VERB
cana-1860	30	6	a	a	DET
cana-1860	30	7	robust	robust	ADJ
cana-1860	30	8	solution	solution	NOUN
cana-1860	30	9	for	for	ADP
cana-1860	30	10	real	real	ADJ
cana-1860	30	11	-	-	PUNCT
cana-1860	30	12	time	time	NOUN
cana-1860	30	13	multimodal	multimodal	NOUN
cana-1860	30	14	data	datum	NOUN
cana-1860	30	15	analytics	analytic	NOUN
cana-1860	30	16	,	,	PUNCT
cana-1860	30	17	which	which	PRON
cana-1860	30	18	relates	relate	VERB
cana-1860	30	19	to	to	ADP
cana-1860	30	20	various	various	ADJ
cana-1860	30	21	applications	application	NOUN
cana-1860	30	22	such	such	ADJ
cana-1860	30	23	as	as	ADP
cana-1860	30	24	health	health	NOUN
cana-1860	30	25	monitoring	monitoring	NOUN
cana-1860	30	26	systems	system	NOUN
cana-1860	30	27	,	,	PUNCT
cana-1860	30	28	financial	financial	ADJ
cana-1860	30	29	forecasting	forecasting	NOUN
cana-1860	30	30	,	,	PUNCT
cana-1860	30	31	and	and	CCONJ
cana-1860	30	32	smart	smart	ADJ
cana-1860	30	33	cities	city	NOUN
cana-1860	30	34	;	;	PUNCT
cana-1860	30	35	in	in	ADP
cana-1860	30	36	all	all	PRON
cana-1860	30	37	of	of	ADP
cana-1860	30	38	these	these	PRON
cana-1860	30	39	,	,	PUNCT
cana-1860	30	40	multiple	multiple	ADJ
cana-1860	30	41	data	datum	NOUN
cana-1860	30	42	sources	source	NOUN
cana-1860	30	43	have	have	VERB
cana-1860	30	44	to	to	PART
cana-1860	30	45	be	be	AUX
cana-1860	30	46	integrated	integrate	VERB
cana-1860	30	47	seamlessly	seamlessly	ADV
cana-1860	30	48	to	to	PART
cana-1860	30	49	result	result	VERB
cana-1860	30	50	in	in	ADP
cana-1860	30	51	an	an	DET
cana-1860	30	52	optimum	optimum	ADJ
cana-1860	30	53	decision	decision	NOUN
cana-1860	30	54	-	-	PUNCT
cana-1860	30	55	making	make	VERB
cana-1860	30	56	process	process	NOUN
cana-1860	30	57	.	.	PUNCT
cana-1860	31	1	2	2	X
cana-1860	31	2	.	.	X
cana-1860	31	3	in	in	ADP
cana-1860	31	4	-	-	PUNCT
cana-1860	31	5	depth	depth	NOUN
cana-1860	31	6	review	review	NOUN
cana-1860	31	7	of	of	ADP
cana-1860	31	8	existing	exist	VERB
cana-1860	31	9	models	model	NOUN
cana-1860	31	10	for	for	ADP
cana-1860	31	11	time	time	NOUN
cana-1860	31	12	series	series	PROPN
cana-1860	31	13	analysis	analysis	NOUN
cana-1860	31	14	time	time	NOUN
cana-1860	31	15	series	series	PROPN
cana-1860	31	16	forecasting	forecasting	NOUN
cana-1860	31	17	has	have	AUX
cana-1860	31	18	been	be	AUX
cana-1860	31	19	lately	lately	ADV
cana-1860	31	20	the	the	DET
cana-1860	31	21	focus	focus	NOUN
cana-1860	31	22	of	of	ADP
cana-1860	31	23	a	a	DET
cana-1860	31	24	wide	wide	ADJ
cana-1860	31	25	variety	variety	NOUN
cana-1860	31	26	of	of	ADP
cana-1860	31	27	sciences	science	NOUN
cana-1860	31	28	,	,	PUNCT
cana-1860	31	29	while	while	SCONJ
cana-1860	31	30	most	most	ADJ
cana-1860	31	31	of	of	ADP
cana-1860	31	32	the	the	DET
cana-1860	31	33	latest	late	ADJ
cana-1860	31	34	contributions	contribution	NOUN
cana-1860	31	35	are	be	AUX
cana-1860	31	36	focused	focus	VERB
cana-1860	31	37	on	on	ADP
cana-1860	31	38	improving	improve	VERB
cana-1860	31	39	the	the	DET
cana-1860	31	40	accuracy	accuracy	NOUN
cana-1860	31	41	of	of	ADP
cana-1860	31	42	the	the	DET
cana-1860	31	43	predictions	prediction	NOUN
cana-1860	31	44	,	,	PUNCT
cana-1860	31	45	deal	deal	VERB
cana-1860	31	46	with	with	ADP
cana-1860	31	47	multivariate	multivariate	NOUN
cana-1860	31	48	data	data	NOUN
cana-1860	31	49	sets	set	NOUN
cana-1860	31	50	,	,	PUNCT
cana-1860	31	51	and	and	CCONJ
cana-1860	31	52	integrate	integrate	VERB
cana-1860	31	53	multiple	multiple	ADJ
cana-1860	31	54	modal	modal	ADJ
cana-1860	31	55	data	datum	NOUN
cana-1860	31	56	.	.	PUNCT
cana-1860	32	1	this	this	DET
cana-1860	32	2	review	review	NOUN
cana-1860	32	3	will	will	AUX
cana-1860	32	4	look	look	VERB
cana-1860	32	5	at	at	ADP
cana-1860	32	6	some	some	DET
cana-1860	32	7	recent	recent	ADJ
cana-1860	32	8	work	work	NOUN
cana-1860	32	9	in	in	ADP
cana-1860	32	10	the	the	DET
cana-1860	32	11	domain	domain	NOUN
cana-1860	32	12	and	and	CCONJ
cana-1860	32	13	place	place	VERB
cana-1860	32	14	the	the	DET
cana-1860	32	15	proposed	propose	VERB
cana-1860	32	16	hybrid	hybrid	NOUN
cana-1860	32	17	model	model	NOUN
cana-1860	32	18	,	,	PUNCT
cana-1860	32	19	namely	namely	ADV
cana-1860	32	20	xgboost	xgboost	X
cana-1860	32	21	-	-	PUNCT
cana-1860	32	22	lstm	lstm	PROPN
cana-1860	32	23	-	-	PUNCT
cana-1860	32	24	cnn	cnn	PROPN
cana-1860	32	25	,	,	PUNCT
cana-1860	32	26	into	into	ADP
cana-1860	32	27	the	the	DET
cana-1860	32	28	perspective	perspective	NOUN
cana-1860	32	29	of	of	ADP
cana-1860	32	30	larger	large	ADJ
cana-1860	32	31	-	-	PUNCT
cana-1860	32	32	scale	scale	NOUN
cana-1860	32	33	multimodal	multimodal	NOUN
cana-1860	32	34	and	and	CCONJ
cana-1860	32	35	time	time	NOUN
cana-1860	32	36	-	-	PUNCT
cana-1860	32	37	series	series	NOUN
cana-1860	32	38	prediction	prediction	NOUN
cana-1860	32	39	studies	study	NOUN
cana-1860	32	40	.	.	PUNCT
cana-1860	33	1	a	a	DET
cana-1860	33	2	fault	fault	NOUN
cana-1860	33	3	prediction	prediction	NOUN
cana-1860	33	4	model	model	NOUN
cana-1860	33	5	for	for	ADP
cana-1860	33	6	electromagnetic	electromagnetic	ADJ
cana-1860	33	7	launch	launch	NOUN
cana-1860	33	8	systems	system	NOUN
cana-1860	33	9	is	be	AUX
cana-1860	33	10	proposed	propose	VERB
cana-1860	33	11	by	by	ADP
cana-1860	33	12	junyong	junyong	PROPN
cana-1860	33	13	et	et	PROPN
cana-1860	33	14	al	al	PROPN
cana-1860	33	15	.	.	PUNCT
cana-1860	33	16	using	use	VERB
cana-1860	33	17	time	time	NOUN
cana-1860	33	18	-	-	PUNCT
cana-1860	33	19	series	series	NOUN
cana-1860	33	20	analysis	analysis	NOUN
cana-1860	33	21	and	and	CCONJ
cana-1860	33	22	neural	neural	ADJ
cana-1860	33	23	networks	network	NOUN
cana-1860	33	24	.	.	PUNCT
cana-1860	34	1	while	while	SCONJ
cana-1860	34	2	this	this	DET
cana-1860	34	3	model	model	NOUN
cana-1860	34	4	works	work	VERB
cana-1860	34	5	well	well	ADV
cana-1860	34	6	in	in	ADP
cana-1860	34	7	structured	structured	ADJ
cana-1860	34	8	data	datum	NOUN
cana-1860	34	9	,	,	PUNCT
cana-1860	34	10	it	it	PRON
cana-1860	34	11	has	have	VERB
cana-1860	34	12	applications	application	NOUN
cana-1860	34	13	only	only	ADV
cana-1860	34	14	in	in	ADP
cana-1860	34	15	specific	specific	ADJ
cana-1860	34	16	domains	domain	NOUN
cana-1860	34	17	where	where	SCONJ
cana-1860	34	18	time	time	NOUN
cana-1860	34	19	-	-	PUNCT
cana-1860	34	20	series	series	NOUN
cana-1860	34	21	data	datum	NOUN
cana-1860	34	22	forms	form	VERB
cana-1860	34	23	the	the	DET
cana-1860	34	24	single	single	ADJ
cana-1860	34	25	focus	focus	NOUN
cana-1860	34	26	,	,	PUNCT
cana-1860	34	27	for	for	ADP
cana-1860	34	28	example	example	NOUN
cana-1860	34	29	,	,	PUNCT
cana-1860	34	30	railguns	railgun	NOUN
cana-1860	34	31	.	.	PUNCT
cana-1860	35	1	in	in	ADP
cana-1860	35	2	addition	addition	NOUN
cana-1860	35	3	,	,	PUNCT
cana-1860	35	4	kim	kim	PROPN
cana-1860	35	5	and	and	CCONJ
cana-1860	35	6	kim	kim	PROPN
cana-1860	35	7	have	have	AUX
cana-1860	35	8	suggested	suggest	VERB
cana-1860	35	9	the	the	DET
cana-1860	35	10	use	use	NOUN
cana-1860	35	11	of	of	ADP
cana-1860	35	12	convolutional	convolutional	ADJ
cana-1860	35	13	transformer	transformer	NOUN
cana-1860	35	14	models	model	NOUN
cana-1860	35	15	for	for	ADP
cana-1860	35	16	multivariate	multivariate	NOUN
cana-1860	35	17	time	time	NOUN
cana-1860	35	18	series	series	PROPN
cana-1860	35	19	prediction	prediction	NOUN
cana-1860	35	20	as	as	ADP
cana-1860	35	21	a	a	DET
cana-1860	35	22	way	way	NOUN
cana-1860	35	23	to	to	PART
cana-1860	35	24	enhance	enhance	VERB
cana-1860	35	25	feature	feature	NOUN
cana-1860	35	26	extraction	extraction	NOUN
cana-1860	35	27	by	by	ADP
cana-1860	35	28	incorporating	incorporate	VERB
cana-1860	35	29	transformer	transformer	ADJ
cana-1860	35	30	mechanisms	mechanism	NOUN
cana-1860	35	31	.	.	PUNCT
cana-1860	36	1	while	while	SCONJ
cana-1860	36	2	transformers	transformer	NOUN
cana-1860	36	3	are	be	AUX
cana-1860	36	4	powerful	powerful	ADJ
cana-1860	36	5	in	in	ADP
cana-1860	36	6	the	the	DET
cana-1860	36	7	tasks	task	NOUN
cana-1860	36	8	of	of	ADP
cana-1860	36	9	sequence	sequence	NOUN
cana-1860	36	10	-	-	PUNCT
cana-1860	36	11	to	to	ADP
cana-1860	36	12	-	-	PUNCT
cana-1860	36	13	sequence	sequence	NOUN
cana-1860	36	14	modeling	modeling	NOUN
cana-1860	36	15	,	,	PUNCT
cana-1860	36	16	their	their	PRON
cana-1860	36	17	computational	computational	ADJ
cana-1860	36	18	complexity	complexity	NOUN
cana-1860	36	19	also	also	ADV
cana-1860	36	20	renders	render	VERB
cana-1860	36	21	them	they	PRON
cana-1860	36	22	less	less	ADV
cana-1860	36	23	feasible	feasible	ADJ
cana-1860	36	24	than	than	ADP
cana-1860	36	25	the	the	DET
cana-1860	36	26	reinforcement	reinforcement	NOUN
cana-1860	36	27	learning	learn	VERB
cana-1860	36	28	part	part	NOUN
cana-1860	36	29	of	of	ADP
cana-1860	36	30	the	the	DET
cana-1860	36	31	proposed	propose	VERB
cana-1860	36	32	model	model	NOUN
cana-1860	36	33	for	for	ADP
cana-1860	36	34	real	real	ADJ
cana-1860	36	35	-	-	PUNCT
cana-1860	36	36	time	time	NOUN
cana-1860	36	37	applications	application	NOUN
cana-1860	36	38	.	.	PUNCT
cana-1860	37	1	in	in	ADP
cana-1860	37	2	,	,	PUNCT
cana-1860	37	3	zeng	zeng	PROPN
cana-1860	37	4	et	et	PROPN
cana-1860	37	5	al	al	PROPN
cana-1860	37	6	.	.	PUNCT
cana-1860	37	7	communications	communication	NOUN
cana-1860	37	8	on	on	ADP
cana-1860	37	9	applied	apply	VERB
cana-1860	37	10	nonlinear	nonlinear	ADJ
cana-1860	37	11	analysis	analysis	NOUN
cana-1860	37	12	issn	issn	NOUN
cana-1860	37	13	:	:	PUNCT
cana-1860	37	14	1074	1074	NUM
cana-1860	37	15	-	-	PUNCT
cana-1860	37	16	133x	133x	NUM
cana-1860	37	17	vol	vol	NOUN
cana-1860	37	18	32	32	NUM
cana-1860	37	19	no	no	NOUN
cana-1860	37	20	.	.	NOUN
cana-1860	37	21	2	2	NUM
cana-1860	37	22	(	(	PUNCT
cana-1860	37	23	2025	2025	NUM
cana-1860	37	24	)	)	PUNCT
cana-1860	37	25	668	668	NUM
cana-1860	37	26	https://internationalpubls.com	https://internationalpubls.com	X
cana-1860	37	27	proposed	propose	VERB
cana-1860	37	28	a	a	DET
cana-1860	37	29	fuzzy	fuzzy	ADJ
cana-1860	37	30	time	time	NOUN
cana-1860	37	31	series	series	PROPN
cana-1860	37	32	prediction	prediction	NOUN
cana-1860	37	33	approach	approach	NOUN
cana-1860	37	34	to	to	PART
cana-1860	37	35	fault	fault	VERB
cana-1860	37	36	prediction	prediction	NOUN
cana-1860	37	37	of	of	ADP
cana-1860	37	38	large	large	ADJ
cana-1860	37	39	scale	scale	NOUN
cana-1860	37	40	pulse	pulse	NOUN
cana-1860	37	41	capacitors	capacitor	NOUN
cana-1860	37	42	.	.	PUNCT
cana-1860	38	1	while	while	SCONJ
cana-1860	38	2	fuzzy	fuzzy	ADJ
cana-1860	38	3	logic	logic	NOUN
cana-1860	38	4	indeed	indeed	ADV
cana-1860	38	5	adds	add	VERB
cana-1860	38	6	robustness	robustness	NOUN
cana-1860	38	7	in	in	ADP
cana-1860	38	8	uncertain	uncertain	ADJ
cana-1860	38	9	environments	environment	NOUN
cana-1860	38	10	,	,	PUNCT
cana-1860	38	11	this	this	DET
cana-1860	38	12	model	model	NOUN
cana-1860	38	13	incorporates	incorporate	VERB
cana-1860	38	14	bnn	bnn	PROPN
cana-1860	38	15	for	for	ADP
cana-1860	38	16	uncertainty	uncertainty	NOUN
cana-1860	38	17	estimation	estimation	NOUN
cana-1860	38	18	,	,	PUNCT
cana-1860	38	19	thus	thus	ADV
cana-1860	38	20	making	make	VERB
cana-1860	38	21	a	a	DET
cana-1860	38	22	stronger	strong	ADJ
cana-1860	38	23	filtration	filtration	NOUN
cana-1860	38	24	for	for	ADP
cana-1860	38	25	noise	noise	NOUN
cana-1860	38	26	and	and	CCONJ
cana-1860	38	27	hence	hence	ADV
cana-1860	38	28	better	well	ADV
cana-1860	38	29	probabilistic	probabilistic	ADJ
cana-1860	38	30	reasoning	reasoning	NOUN
cana-1860	38	31	possible	possible	ADJ
cana-1860	38	32	.	.	PUNCT
cana-1860	39	1	feng	feng	PROPN
cana-1860	39	2	et	et	PROPN
cana-1860	39	3	al	al	PROPN
cana-1860	39	4	.	.	PUNCT
cana-1860	40	1	[	[	X
cana-1860	40	2	4	4	X
cana-1860	40	3	]	]	PUNCT
cana-1860	40	4	contributed	contribute	VERB
cana-1860	40	5	an	an	DET
cana-1860	40	6	mtl	mtl	PROPN
cana-1860	40	7	framework	framework	NOUN
cana-1860	40	8	that	that	PRON
cana-1860	40	9	captures	capture	VERB
cana-1860	40	10	both	both	CCONJ
cana-1860	40	11	dynamic	dynamic	ADV
cana-1860	40	12	-	-	PUNCT
cana-1860	40	13	shared	share	VERB
cana-1860	40	14	and	and	CCONJ
cana-1860	40	15	specific	specific	ADJ
cana-1860	40	16	patterns	pattern	NOUN
cana-1860	40	17	for	for	ADP
cana-1860	40	18	chaotic	chaotic	ADJ
cana-1860	40	19	timeseries	timeserie	NOUN
cana-1860	40	20	prediction	prediction	NOUN
cana-1860	40	21	.	.	PUNCT
cana-1860	41	1	the	the	DET
cana-1860	41	2	approach	approach	NOUN
cana-1860	41	3	given	give	VERB
cana-1860	41	4	by	by	ADP
cana-1860	41	5	them	they	PRON
cana-1860	41	6	is	be	AUX
cana-1860	41	7	efficient	efficient	ADJ
cana-1860	41	8	in	in	ADP
cana-1860	41	9	multitasking	multitaske	VERB
cana-1860	41	10	environments	environment	NOUN
cana-1860	41	11	;	;	PUNCT
cana-1860	41	12	however	however	ADV
cana-1860	41	13	,	,	PUNCT
cana-1860	41	14	the	the	DET
cana-1860	41	15	hybrid	hybrid	NOUN
cana-1860	41	16	model	model	NOUN
cana-1860	41	17	proposed	propose	VERB
cana-1860	41	18	here	here	ADV
cana-1860	41	19	is	be	AUX
cana-1860	41	20	more	more	ADV
cana-1860	41	21	versatile	versatile	ADJ
cana-1860	41	22	as	as	SCONJ
cana-1860	41	23	it	it	PRON
cana-1860	41	24	uses	use	VERB
cana-1860	41	25	cnn	cnn	PROPN
cana-1860	41	26	for	for	ADP
cana-1860	41	27	spatial	spatial	ADJ
cana-1860	41	28	data	datum	NOUN
cana-1860	41	29	and	and	CCONJ
cana-1860	41	30	lstm	lstm	NOUN
cana-1860	41	31	for	for	ADP
cana-1860	41	32	sequential	sequential	ADJ
cana-1860	41	33	pattern	pattern	NOUN
cana-1860	41	34	in	in	ADP
cana-1860	41	35	case	case	NOUN
cana-1860	41	36	of	of	ADP
cana-1860	41	37	multimodal	multimodal	NOUN
cana-1860	41	38	data	datum	NOUN
cana-1860	41	39	fusion	fusion	NOUN
cana-1860	41	40	.	.	PUNCT
cana-1860	42	1	shen	shen	PROPN
cana-1860	42	2	et	et	PROPN
cana-1860	42	3	al	al	PROPN
cana-1860	42	4	.	.	PUNCT
cana-1860	43	1	[	[	X
cana-1860	43	2	5	5	NUM
cana-1860	43	3	]	]	PUNCT
cana-1860	43	4	presented	present	VERB
cana-1860	43	5	multivariate	multivariate	NOUN
cana-1860	43	6	time	time	NOUN
cana-1860	43	7	-	-	PUNCT
cana-1860	43	8	series	series	NOUN
cana-1860	43	9	forecasting	forecasting	NOUN
cana-1860	43	10	using	use	VERB
cana-1860	43	11	elastic	elastic	ADJ
cana-1860	43	12	net	net	ADJ
cana-1860	43	13	and	and	CCONJ
cana-1860	43	14	high	high	ADJ
cana-1860	43	15	-	-	PUNCT
cana-1860	43	16	order	order	NOUN
cana-1860	43	17	fuzzy	fuzzy	ADJ
cana-1860	43	18	cognitive	cognitive	ADJ
cana-1860	43	19	maps	map	NOUN
cana-1860	43	20	that	that	PRON
cana-1860	43	21	are	be	AUX
cana-1860	43	22	used	use	VERB
cana-1860	43	23	to	to	PART
cana-1860	43	24	predict	predict	VERB
cana-1860	43	25	eeg	eeg	NOUN
cana-1860	43	26	signals	signal	NOUN
cana-1860	43	27	.	.	PUNCT
cana-1860	44	1	while	while	SCONJ
cana-1860	44	2	the	the	DET
cana-1860	44	3	1d	1d	NUM
cana-1860	44	4	-	-	PUNCT
cana-1860	44	5	cnn	cnn	PROPN
cana-1860	44	6	used	use	VERB
cana-1860	44	7	in	in	ADP
cana-1860	44	8	their	their	PRON
cana-1860	44	9	work	work	NOUN
cana-1860	44	10	improves	improve	VERB
cana-1860	44	11	the	the	DET
cana-1860	44	12	process	process	NOUN
cana-1860	44	13	of	of	ADP
cana-1860	44	14	spatial	spatial	ADJ
cana-1860	44	15	-	-	PUNCT
cana-1860	44	16	temporal	temporal	ADJ
cana-1860	44	17	feature	feature	NOUN
cana-1860	44	18	extraction	extraction	NOUN
cana-1860	44	19	,	,	PUNCT
cana-1860	44	20	integration	integration	NOUN
cana-1860	44	21	of	of	ADP
cana-1860	44	22	cnns	cnn	NOUN
cana-1860	44	23	within	within	ADP
cana-1860	44	24	the	the	DET
cana-1860	44	25	proposed	propose	VERB
cana-1860	44	26	model	model	NOUN
cana-1860	44	27	for	for	ADP
cana-1860	44	28	handling	handle	VERB
cana-1860	44	29	spatial	spatial	ADJ
cana-1860	44	30	data	datum	NOUN
cana-1860	44	31	with	with	ADP
cana-1860	44	32	xgboost	xgboost	PROPN
cana-1860	44	33	provides	provide	VERB
cana-1860	44	34	a	a	DET
cana-1860	44	35	wider	wide	ADJ
cana-1860	44	36	solution	solution	NOUN
cana-1860	44	37	.	.	PUNCT
cana-1860	45	1	zhou	zhou	PROPN
cana-1860	45	2	et	et	PROPN
cana-1860	45	3	al	al	PROPN
cana-1860	45	4	.	.	PUNCT
cana-1860	46	1	[	[	X
cana-1860	46	2	6	6	NUM
cana-1860	46	3	]	]	PUNCT
cana-1860	46	4	addressed	address	VERB
cana-1860	46	5	industrial	industrial	ADJ
cana-1860	46	6	process	process	NOUN
cana-1860	46	7	prediction	prediction	NOUN
cana-1860	46	8	under	under	ADP
cana-1860	46	9	limited	limited	ADJ
cana-1860	46	10	data	datum	NOUN
cana-1860	46	11	using	use	VERB
cana-1860	46	12	transfer	transfer	NOUN
cana-1860	46	13	learning	learning	NOUN
cana-1860	46	14	.	.	PUNCT
cana-1860	47	1	their	their	PRON
cana-1860	47	2	approach	approach	NOUN
cana-1860	47	3	is	be	AUX
cana-1860	47	4	for	for	ADP
cana-1860	47	5	a	a	DET
cana-1860	47	6	few	few	ADJ
cana-1860	47	7	-	-	PUNCT
cana-1860	47	8	shot	shot	NOUN
cana-1860	47	9	setting	setting	NOUN
cana-1860	47	10	and	and	CCONJ
cana-1860	47	11	thus	thus	ADV
cana-1860	47	12	is	be	AUX
cana-1860	47	13	complementary	complementary	ADJ
cana-1860	47	14	to	to	ADP
cana-1860	47	15	the	the	DET
cana-1860	47	16	transfer	transfer	NOUN
cana-1860	47	17	learning	learning	NOUN
cana-1860	47	18	-	-	PUNCT
cana-1860	47	19	based	base	VERB
cana-1860	47	20	extension	extension	NOUN
cana-1860	47	21	that	that	PRON
cana-1860	47	22	can	can	AUX
cana-1860	47	23	be	be	AUX
cana-1860	47	24	made	make	VERB
cana-1860	47	25	to	to	ADP
cana-1860	47	26	the	the	DET
cana-1860	47	27	proposed	propose	VERB
cana-1860	47	28	model	model	NOUN
cana-1860	47	29	toward	toward	ADP
cana-1860	47	30	real	real	ADJ
cana-1860	47	31	-	-	PUNCT
cana-1860	47	32	time	time	NOUN
cana-1860	47	33	adaptability	adaptability	NOUN
cana-1860	47	34	.	.	PUNCT
cana-1860	48	1	yin	yin	PROPN
cana-1860	48	2	et	et	PROPN
cana-1860	48	3	al	al	PROPN
cana-1860	48	4	.	.	PUNCT
cana-1860	49	1	[	[	X
cana-1860	49	2	7	7	NUM
cana-1860	49	3	]	]	PUNCT
cana-1860	49	4	developed	develop	VERB
cana-1860	49	5	a	a	DET
cana-1860	49	6	gan	gan	NOUN
cana-1860	49	7	with	with	ADP
cana-1860	49	8	multiple	multiple	ADJ
cana-1860	49	9	attention	attention	NOUN
cana-1860	49	10	for	for	ADP
cana-1860	49	11	time	time	NOUN
cana-1860	49	12	-	-	PUNCT
cana-1860	49	13	series	series	NOUN
cana-1860	49	14	prediction	prediction	NOUN
cana-1860	49	15	.	.	PUNCT
cana-1860	50	1	while	while	SCONJ
cana-1860	50	2	gans	gan	NOUN
cana-1860	50	3	are	be	AUX
cana-1860	50	4	truly	truly	ADV
cana-1860	50	5	effective	effective	ADJ
cana-1860	50	6	in	in	ADP
cana-1860	50	7	the	the	DET
cana-1860	50	8	generation	generation	NOUN
cana-1860	50	9	of	of	ADP
cana-1860	50	10	synthetic	synthetic	ADJ
cana-1860	50	11	data	datum	NOUN
cana-1860	50	12	,	,	PUNCT
cana-1860	50	13	their	their	PRON
cana-1860	50	14	instability	instability	NOUN
cana-1860	50	15	in	in	ADP
cana-1860	50	16	training	training	NOUN
cana-1860	50	17	is	be	AUX
cana-1860	50	18	in	in	ADP
cana-1860	50	19	contrast	contrast	NOUN
cana-1860	50	20	to	to	ADP
cana-1860	50	21	stability	stability	NOUN
cana-1860	50	22	,	,	PUNCT
cana-1860	50	23	which	which	PRON
cana-1860	50	24	the	the	DET
cana-1860	50	25	use	use	NOUN
cana-1860	50	26	of	of	ADP
cana-1860	50	27	ppo	ppo	PROPN
cana-1860	50	28	introduces	introduce	NOUN
cana-1860	50	29	in	in	ADP
cana-1860	50	30	the	the	DET
cana-1860	50	31	model	model	NOUN
cana-1860	50	32	proposed	propose	VERB
cana-1860	50	33	here	here	ADV
cana-1860	50	34	.	.	PUNCT
cana-1860	51	1	yi	yi	PROPN
cana-1860	51	2	et	et	PROPN
cana-1860	51	3	al	al	PROPN
cana-1860	51	4	.	.	PUNCT
cana-1860	52	1	[	[	X
cana-1860	52	2	8	8	NUM
cana-1860	52	3	]	]	PUNCT
cana-1860	52	4	proposed	propose	VERB
cana-1860	52	5	an	an	DET
cana-1860	52	6	intergroup	intergroup	NOUN
cana-1860	52	7	cascade	cascade	NOUN
cana-1860	52	8	broad	broad	ADJ
cana-1860	52	9	learning	learning	NOUN
cana-1860	52	10	system	system	NOUN
cana-1860	52	11	with	with	ADP
cana-1860	52	12	optimized	optimize	VERB
cana-1860	52	13	parameters	parameter	NOUN
cana-1860	52	14	for	for	ADP
cana-1860	52	15	chaotic	chaotic	ADJ
cana-1860	52	16	time	time	NOUN
cana-1860	52	17	-	-	PUNCT
cana-1860	52	18	series	series	NOUN
cana-1860	52	19	prediction	prediction	NOUN
cana-1860	52	20	;	;	PUNCT
cana-1860	52	21	hence	hence	ADV
cana-1860	52	22	,	,	PUNCT
cana-1860	52	23	the	the	DET
cana-1860	52	24	emphasis	emphasis	NOUN
cana-1860	52	25	was	be	AUX
cana-1860	52	26	more	more	ADJ
cana-1860	52	27	on	on	ADP
cana-1860	52	28	the	the	DET
cana-1860	52	29	optimization	optimization	NOUN
cana-1860	52	30	of	of	ADP
cana-1860	52	31	parameters	parameter	NOUN
cana-1860	52	32	.	.	PUNCT
cana-1860	53	1	while	while	SCONJ
cana-1860	53	2	this	this	PRON
cana-1860	53	3	could	could	AUX
cana-1860	53	4	be	be	AUX
cana-1860	53	5	powerful	powerful	ADJ
cana-1860	53	6	for	for	ADP
cana-1860	53	7	chaosrelated	chaosrelate	VERB
cana-1860	53	8	tasks	task	NOUN
cana-1860	53	9	,	,	PUNCT
cana-1860	53	10	the	the	DET
cana-1860	53	11	broader	broad	ADJ
cana-1860	53	12	adaptability	adaptability	NOUN
cana-1860	53	13	of	of	ADP
cana-1860	53	14	ppo	ppo	PROPN
cana-1860	53	15	in	in	ADP
cana-1860	53	16	the	the	DET
cana-1860	53	17	proposed	propose	VERB
cana-1860	53	18	model	model	NOUN
cana-1860	53	19	provides	provide	VERB
cana-1860	53	20	superior	superior	ADJ
cana-1860	53	21	performance	performance	NOUN
cana-1860	53	22	across	across	ADP
cana-1860	53	23	multimodal	multimodal	NOUN
cana-1860	53	24	domains	domain	NOUN
cana-1860	53	25	.	.	PUNCT
cana-1860	54	1	chen	chen	PROPN
cana-1860	54	2	and	and	CCONJ
cana-1860	54	3	sun	sun	PROPN
cana-1860	54	4	[	[	X
cana-1860	54	5	9	9	NUM
cana-1860	54	6	]	]	PUNCT
cana-1860	54	7	introduced	introduce	VERB
cana-1860	54	8	bayesian	bayesian	NOUN
cana-1860	54	9	temporal	temporal	ADJ
cana-1860	54	10	factorization	factorization	NOUN
cana-1860	54	11	for	for	ADP
cana-1860	54	12	multidimensional	multidimensional	ADJ
cana-1860	54	13	timeseries	timeserie	NOUN
cana-1860	54	14	prediction	prediction	NOUN
cana-1860	54	15	.	.	PUNCT
cana-1860	55	1	their	their	PRON
cana-1860	55	2	use	use	NOUN
cana-1860	55	3	of	of	ADP
cana-1860	55	4	probabilistic	probabilistic	ADJ
cana-1860	55	5	models	model	NOUN
cana-1860	55	6	aligns	align	VERB
cana-1860	55	7	closely	closely	ADV
cana-1860	55	8	with	with	ADP
cana-1860	55	9	the	the	DET
cana-1860	55	10	kalman	kalman	PROPN
cana-1860	55	11	filter	filter	PROPN
cana-1860	55	12	-	-	PUNCT
cana-1860	55	13	enhanced	enhance	VERB
cana-1860	55	14	bnn	bnn	NOUN
cana-1860	55	15	in	in	ADP
cana-1860	55	16	the	the	DET
cana-1860	55	17	proposed	propose	VERB
cana-1860	55	18	model	model	NOUN
cana-1860	55	19	.	.	PUNCT
cana-1860	56	1	however	however	ADV
cana-1860	56	2	,	,	PUNCT
cana-1860	56	3	the	the	DET
cana-1860	56	4	latter	latter	ADJ
cana-1860	56	5	is	be	AUX
cana-1860	56	6	more	more	ADV
cana-1860	56	7	suitable	suitable	ADJ
cana-1860	56	8	for	for	ADP
cana-1860	56	9	real	real	ADJ
cana-1860	56	10	-	-	PUNCT
cana-1860	56	11	time	time	NOUN
cana-1860	56	12	prediction	prediction	NOUN
cana-1860	56	13	tasks	task	NOUN
cana-1860	56	14	due	due	ADP
cana-1860	56	15	to	to	ADP
cana-1860	56	16	fusion	fusion	NOUN
cana-1860	56	17	with	with	ADP
cana-1860	56	18	xgboost	xgboost	PROPN
cana-1860	56	19	,	,	PUNCT
cana-1860	56	20	lstm	lstm	ADJ
cana-1860	56	21	,	,	PUNCT
cana-1860	56	22	and	and	CCONJ
cana-1860	56	23	cnn	cnn	PROPN
cana-1860	56	24	.	.	PUNCT
cana-1860	57	1	there	there	PRON
cana-1860	57	2	is	be	VERB
cana-1860	57	3	a	a	DET
cana-1860	57	4	vam	vam	NOUN
cana-1860	57	5	simulator	simulator	NOUN
cana-1860	57	6	developed	develop	VERB
cana-1860	57	7	by	by	ADP
cana-1860	57	8	mubang	mubang	PROPN
cana-1860	57	9	and	and	CCONJ
cana-1860	57	10	hall	hall	PROPN
cana-1860	57	11	used	use	VERB
cana-1860	57	12	for	for	ADP
cana-1860	57	13	social	social	ADJ
cana-1860	57	14	media	medium	NOUN
cana-1860	57	15	time	time	NOUN
cana-1860	57	16	-	-	PUNCT
cana-1860	57	17	series	series	NOUN
cana-1860	57	18	prediction	prediction	NOUN
cana-1860	57	19	.	.	PUNCT
cana-1860	58	1	mubang	mubang	PROPN
cana-1860	58	2	and	and	CCONJ
cana-1860	58	3	hall	hall	PROPN
cana-1860	58	4	focus	focus	VERB
cana-1860	58	5	on	on	ADP
cana-1860	58	6	social	social	ADJ
cana-1860	58	7	networking	networking	NOUN
cana-1860	58	8	in	in	ADP
cana-1860	58	9	their	their	PRON
cana-1860	58	10	work	work	NOUN
cana-1860	58	11	,	,	PUNCT
cana-1860	58	12	but	but	CCONJ
cana-1860	58	13	the	the	DET
cana-1860	58	14	core	core	NOUN
cana-1860	58	15	of	of	ADP
cana-1860	58	16	their	their	PRON
cana-1860	58	17	work	work	NOUN
cana-1860	58	18	shows	show	VERB
cana-1860	58	19	the	the	DET
cana-1860	58	20	importance	importance	NOUN
cana-1860	58	21	of	of	ADP
cana-1860	58	22	network	network	NOUN
cana-1860	58	23	-	-	PUNCT
cana-1860	58	24	based	base	VERB
cana-1860	58	25	analysis	analysis	NOUN
cana-1860	58	26	toward	toward	ADP
cana-1860	58	27	time	time	NOUN
cana-1860	58	28	series	series	NOUN
cana-1860	58	29	.	.	PUNCT
cana-1860	59	1	the	the	DET
cana-1860	59	2	model	model	NOUN
cana-1860	59	3	could	could	AUX
cana-1860	59	4	be	be	AUX
cana-1860	59	5	useful	useful	ADJ
cana-1860	59	6	at	at	ADP
cana-1860	59	7	different	different	ADJ
cana-1860	59	8	areas	area	NOUN
cana-1860	59	9	of	of	ADP
cana-1860	59	10	social	social	ADJ
cana-1860	59	11	media	medium	NOUN
cana-1860	59	12	,	,	PUNCT
cana-1860	59	13	health	health	NOUN
cana-1860	59	14	care	care	NOUN
cana-1860	59	15	,	,	PUNCT
cana-1860	59	16	and	and	CCONJ
cana-1860	59	17	finance	finance	NOUN
cana-1860	59	18	.	.	PUNCT
cana-1860	60	1	in	in	ADP
cana-1860	60	2	such	such	DET
cana-1860	60	3	a	a	DET
cana-1860	60	4	context	context	NOUN
cana-1860	60	5	,	,	PUNCT
cana-1860	60	6	ma	ma	PROPN
cana-1860	60	7	et	et	PROPN
cana-1860	60	8	al	al	PROPN
cana-1860	60	9	.	.	PROPN
cana-1860	60	10	proposed	propose	VERB
cana-1860	60	11	the	the	DET
cana-1860	60	12	method	method	NOUN
cana-1860	60	13	for	for	ADP
cana-1860	60	14	short	short	ADJ
cana-1860	60	15	-	-	PUNCT
cana-1860	60	16	term	term	NOUN
cana-1860	60	17	traffic	traffic	NOUN
cana-1860	60	18	flow	flow	NOUN
cana-1860	60	19	prediction	prediction	NOUN
cana-1860	60	20	using	use	VERB
cana-1860	60	21	lstm	lstm	NOUN
cana-1860	60	22	and	and	CCONJ
cana-1860	60	23	bilstm	bilstm	NOUN
cana-1860	60	24	on	on	ADP
cana-1860	60	25	an	an	DET
cana-1860	60	26	urban	urban	ADJ
cana-1860	60	27	traffic	traffic	NOUN
cana-1860	60	28	system	system	NOUN
cana-1860	60	29	.	.	PUNCT
cana-1860	61	1	their	their	PRON
cana-1860	61	2	method	method	NOUN
cana-1860	61	3	is	be	AUX
cana-1860	61	4	restricted	restrict	VERB
cana-1860	61	5	only	only	ADV
cana-1860	61	6	to	to	ADP
cana-1860	61	7	the	the	DET
cana-1860	61	8	traffic	traffic	NOUN
cana-1860	61	9	data	datum	NOUN
cana-1860	61	10	,	,	PUNCT
cana-1860	61	11	whereas	whereas	SCONJ
cana-1860	61	12	this	this	DET
cana-1860	61	13	proposed	propose	VERB
cana-1860	61	14	model	model	NOUN
cana-1860	61	15	handles	handle	VERB
cana-1860	61	16	multimodal	multimodal	ADJ
cana-1860	61	17	data	datum	NOUN
cana-1860	61	18	because	because	SCONJ
cana-1860	61	19	it	it	PRON
cana-1860	61	20	integrates	integrate	VERB
cana-1860	61	21	cnns	cnn	NOUN
cana-1860	61	22	for	for	ADP
cana-1860	61	23	capturing	capture	VERB
cana-1860	61	24	the	the	DET
cana-1860	61	25	spatial	spatial	ADJ
cana-1860	61	26	tasks	task	NOUN
cana-1860	61	27	and	and	CCONJ
cana-1860	61	28	lstms	lstms	NOUN
cana-1860	61	29	for	for	ADP
cana-1860	61	30	temporal	temporal	ADJ
cana-1860	61	31	tasks	task	NOUN
cana-1860	61	32	.	.	PUNCT
cana-1860	62	1	hence	hence	ADV
cana-1860	62	2	,	,	PUNCT
cana-1860	62	3	this	this	DET
cana-1860	62	4	network	network	NOUN
cana-1860	62	5	will	will	AUX
cana-1860	62	6	be	be	AUX
cana-1860	62	7	more	more	ADV
cana-1860	62	8	robust	robust	ADJ
cana-1860	62	9	in	in	ADP
cana-1860	62	10	real	real	ADJ
cana-1860	62	11	-	-	PUNCT
cana-1860	62	12	world	world	NOUN
cana-1860	62	13	scenarios	scenario	NOUN
cana-1860	62	14	.	.	PUNCT
cana-1860	63	1	wang	wang	PROPN
cana-1860	63	2	et	et	PROPN
cana-1860	63	3	al	al	PROPN
cana-1860	63	4	.	.	PUNCT
cana-1860	64	1	[	[	X
cana-1860	64	2	12	12	NUM
cana-1860	64	3	]	]	PUNCT
cana-1860	64	4	employed	employ	VERB
cana-1860	64	5	an	an	DET
cana-1860	64	6	information	information	NOUN
cana-1860	64	7	granules	granule	NOUN
cana-1860	64	8	-	-	PUNCT
cana-1860	64	9	based	base	VERB
cana-1860	64	10	bp	bp	PROPN
cana-1860	64	11	neural	neural	ADJ
cana-1860	64	12	network	network	NOUN
cana-1860	64	13	aimed	aim	VERB
cana-1860	64	14	at	at	ADP
cana-1860	64	15	longterm	longterm	PROPN
cana-1860	64	16	time	time	NOUN
cana-1860	64	17	series	series	PROPN
cana-1860	64	18	prediction	prediction	NOUN
cana-1860	64	19	.	.	PUNCT
cana-1860	65	1	while	while	SCONJ
cana-1860	65	2	effective	effective	ADJ
cana-1860	65	3	for	for	ADP
cana-1860	65	4	granular	granular	ADJ
cana-1860	65	5	data	datum	NOUN
cana-1860	65	6	,	,	PUNCT
cana-1860	65	7	their	their	PRON
cana-1860	65	8	model	model	NOUN
cana-1860	65	9	does	do	AUX
cana-1860	65	10	not	not	PART
cana-1860	65	11	have	have	VERB
cana-1860	65	12	the	the	DET
cana-1860	65	13	ability	ability	NOUN
cana-1860	65	14	of	of	ADP
cana-1860	65	15	multimodal	multimodal	ADJ
cana-1860	65	16	fusion	fusion	NOUN
cana-1860	65	17	like	like	ADP
cana-1860	65	18	the	the	DET
cana-1860	65	19	proposed	propose	VERB
cana-1860	65	20	architecture	architecture	NOUN
cana-1860	65	21	,	,	PUNCT
cana-1860	65	22	which	which	PRON
cana-1860	65	23	integrates	integrate	VERB
cana-1860	65	24	the	the	DET
cana-1860	65	25	various	various	ADJ
cana-1860	65	26	data	datum	NOUN
cana-1860	65	27	types	type	NOUN
cana-1860	65	28	to	to	PART
cana-1860	65	29	give	give	VERB
cana-1860	65	30	an	an	DET
cana-1860	65	31	encompassing	encompass	VERB
cana-1860	65	32	prediction	prediction	NOUN
cana-1860	65	33	.	.	PUNCT
cana-1860	66	1	maaroofi	maaroofi	PROPN
cana-1860	66	2	et	et	PROPN
cana-1860	66	3	al	al	PROPN
cana-1860	66	4	.	.	PROPN
cana-1860	66	5	proposed	propose	VERB
cana-1860	66	6	a	a	DET
cana-1860	66	7	time	time	NOUN
cana-1860	66	8	-	-	PUNCT
cana-1860	66	9	series	series	NOUN
cana-1860	66	10	prediction	prediction	NOUN
cana-1860	66	11	using	use	VERB
cana-1860	66	12	the	the	DET
cana-1860	66	13	ensemble	ensemble	ADJ
cana-1860	66	14	data	datum	NOUN
cana-1860	66	15	autocorrelation	autocorrelation	NOUN
cana-1860	66	16	forecasting	forecasting	NOUN
cana-1860	66	17	method	method	NOUN
cana-1860	66	18	.	.	PUNCT
cana-1860	67	1	though	though	SCONJ
cana-1860	67	2	ensemble	ensemble	ADJ
cana-1860	67	3	methods	method	NOUN
cana-1860	67	4	improve	improve	VERB
cana-1860	67	5	the	the	DET
cana-1860	67	6	prediction	prediction	NOUN
cana-1860	67	7	accuracy	accuracy	NOUN
cana-1860	67	8	,	,	PUNCT
cana-1860	67	9	the	the	DET
cana-1860	67	10	integration	integration	NOUN
cana-1860	67	11	of	of	ADP
cana-1860	67	12	ppo	ppo	PROPN
cana-1860	67	13	enables	enable	VERB
cana-1860	67	14	real	real	ADJ
cana-1860	67	15	-	-	PUNCT
cana-1860	67	16	time	time	NOUN
cana-1860	67	17	adaptability	adaptability	NOUN
cana-1860	67	18	of	of	ADP
cana-1860	67	19	the	the	DET
cana-1860	67	20	proposed	propose	VERB
cana-1860	67	21	hybrid	hybrid	NOUN
cana-1860	67	22	model	model	NOUN
cana-1860	67	23	and	and	CCONJ
cana-1860	67	24	improves	improve	VERB
cana-1860	67	25	model	model	NOUN
cana-1860	67	26	efficiency	efficiency	NOUN
cana-1860	67	27	in	in	ADP
cana-1860	67	28	dynamic	dynamic	ADJ
cana-1860	67	29	environments	environment	NOUN
cana-1860	67	30	.	.	PUNCT
cana-1860	68	1	ren	ren	NOUN
cana-1860	68	2	et	et	PROPN
cana-1860	68	3	al	al	PROPN
cana-1860	68	4	.	.	PUNCT
cana-1860	69	1	[	[	X
cana-1860	69	2	14	14	NUM
cana-1860	69	3	]	]	PUNCT
cana-1860	69	4	addressed	address	VERB
cana-1860	69	5	a	a	DET
cana-1860	69	6	multivariate	multivariate	NOUN
cana-1860	69	7	utility	utility	NOUN
cana-1860	69	8	time	time	NOUN
cana-1860	69	9	-	-	PUNCT
cana-1860	69	10	series	series	NOUN
cana-1860	69	11	representation	representation	NOUN
cana-1860	69	12	and	and	CCONJ
cana-1860	69	13	prediction	prediction	NOUN
cana-1860	69	14	with	with	ADP
cana-1860	69	15	a	a	DET
cana-1860	69	16	focus	focus	NOUN
cana-1860	69	17	on	on	ADP
cana-1860	69	18	the	the	DET
cana-1860	69	19	modeling	modeling	NOUN
cana-1860	69	20	of	of	ADP
cana-1860	69	21	sensory	sensory	ADJ
cana-1860	69	22	data	datum	NOUN
cana-1860	69	23	.	.	PUNCT
cana-1860	70	1	the	the	DET
cana-1860	70	2	proposed	propose	VERB
cana-1860	70	3	model	model	NOUN
cana-1860	70	4	here	here	ADV
cana-1860	70	5	provides	provide	VERB
cana-1860	70	6	an	an	DET
cana-1860	70	7	extension	extension	NOUN
cana-1860	70	8	to	to	PART
cana-1860	70	9	include	include	VERB
cana-1860	70	10	federated	federated	ADJ
cana-1860	70	11	learning	learning	NOUN
cana-1860	70	12	in	in	ADP
cana-1860	70	13	the	the	DET
cana-1860	70	14	case	case	NOUN
cana-1860	70	15	of	of	ADP
cana-1860	70	16	distributed	distribute	VERB
cana-1860	70	17	datasets	dataset	NOUN
cana-1860	70	18	-	-	PUNCT
cana-1860	70	19	a	a	DET
cana-1860	70	20	vital	vital	ADJ
cana-1860	70	21	factor	factor	NOUN
cana-1860	70	22	for	for	ADP
cana-1860	70	23	preserving	preserve	VERB
cana-1860	70	24	privacy	privacy	NOUN
cana-1860	70	25	in	in	ADP
cana-1860	70	26	utility	utility	NOUN
cana-1860	70	27	demand	demand	NOUN
cana-1860	70	28	predictions	prediction	NOUN
cana-1860	70	29	within	within	ADP
cana-1860	70	30	smart	smart	ADJ
cana-1860	70	31	cities	city	NOUN
cana-1860	70	32	.	.	PUNCT
cana-1860	71	1	yuan	yuan	NOUN
cana-1860	71	2	et	et	PROPN
cana-1860	71	3	al	al	PROPN
cana-1860	71	4	.	.	PUNCT
cana-1860	72	1	[	[	X
cana-1860	72	2	15	15	NUM
cana-1860	72	3	]	]	PUNCT
cana-1860	72	4	presented	present	VERB
cana-1860	72	5	a	a	DET
cana-1860	72	6	joint	joint	ADJ
cana-1860	72	7	communications	communication	NOUN
cana-1860	72	8	on	on	ADP
cana-1860	72	9	applied	apply	VERB
cana-1860	72	10	nonlinear	nonlinear	ADJ
cana-1860	72	11	analysis	analysis	NOUN
cana-1860	72	12	issn	issn	NOUN
cana-1860	72	13	:	:	PUNCT
cana-1860	72	14	1074	1074	NUM
cana-1860	72	15	-	-	PUNCT
cana-1860	72	16	133x	133x	NUM
cana-1860	72	17	vol	vol	NOUN
cana-1860	72	18	32	32	NUM
cana-1860	72	19	no	no	NOUN
cana-1860	72	20	.	.	NOUN
cana-1860	72	21	2	2	NUM
cana-1860	72	22	(	(	PUNCT
cana-1860	72	23	2025	2025	NUM
cana-1860	72	24	)	)	PUNCT
cana-1860	72	25	669	669	NUM
cana-1860	72	26	https://internationalpubls.com	https://internationalpubls.com	X
cana-1860	72	27	spatiotemporal	spatiotemporal	ADJ
cana-1860	72	28	feature	feature	NOUN
cana-1860	72	29	learning	learn	VERB
cana-1860	72	30	framework	framework	NOUN
cana-1860	72	31	for	for	ADP
cana-1860	72	32	multivariate	multivariate	NOUN
cana-1860	72	33	time	time	NOUN
cana-1860	72	34	-	-	PUNCT
cana-1860	72	35	series	series	NOUN
cana-1860	72	36	prediction	prediction	NOUN
cana-1860	72	37	using	use	VERB
cana-1860	72	38	fuzzy	fuzzy	ADJ
cana-1860	72	39	cognitive	cognitive	ADJ
cana-1860	72	40	maps	map	NOUN
cana-1860	72	41	and	and	CCONJ
cana-1860	72	42	sparse	sparse	ADJ
cana-1860	72	43	autoencoders	autoencoder	NOUN
cana-1860	72	44	.	.	PUNCT
cana-1860	73	1	their	their	PRON
cana-1860	73	2	approach	approach	NOUN
cana-1860	73	3	is	be	AUX
cana-1860	73	4	somewhat	somewhat	ADV
cana-1860	73	5	related	relate	VERB
cana-1860	73	6	to	to	ADP
cana-1860	73	7	the	the	DET
cana-1860	73	8	proposed	propose	VERB
cana-1860	73	9	model	model	NOUN
cana-1860	73	10	through	through	ADP
cana-1860	73	11	the	the	DET
cana-1860	73	12	use	use	NOUN
cana-1860	73	13	of	of	ADP
cana-1860	73	14	cnns	cnn	NOUN
cana-1860	73	15	to	to	PART
cana-1860	73	16	extract	extract	VERB
cana-1860	73	17	spatiotemporal	spatiotemporal	ADJ
cana-1860	73	18	features	feature	NOUN
cana-1860	73	19	,	,	PUNCT
cana-1860	73	20	although	although	SCONJ
cana-1860	73	21	this	this	DET
cana-1860	73	22	model	model	NOUN
cana-1860	73	23	furthers	further	VERB
cana-1860	73	24	their	their	PRON
cana-1860	73	25	approach	approach	NOUN
cana-1860	73	26	with	with	ADP
cana-1860	73	27	the	the	DET
cana-1860	73	28	addition	addition	NOUN
cana-1860	73	29	of	of	ADP
cana-1860	73	30	xgboost	xgboost	PROPN
cana-1860	73	31	for	for	ADP
cana-1860	73	32	tabular	tabular	PROPN
cana-1860	73	33	data	datum	NOUN
cana-1860	73	34	,	,	PUNCT
cana-1860	73	35	lending	lend	VERB
cana-1860	73	36	it	it	PRON
cana-1860	73	37	a	a	DET
cana-1860	73	38	more	more	ADV
cana-1860	73	39	holistic	holistic	ADJ
cana-1860	73	40	approach	approach	NOUN
cana-1860	73	41	in	in	ADP
cana-1860	73	42	multimodal	multimodal	ADJ
cana-1860	73	43	fusion	fusion	NOUN
cana-1860	73	44	.	.	PUNCT
cana-1860	74	1	on	on	ADP
cana-1860	74	2	the	the	DET
cana-1860	74	3	whole	whole	NOUN
cana-1860	74	4	,	,	PUNCT
cana-1860	74	5	though	though	SCONJ
cana-1860	74	6	contributive	contributive	ADJ
cana-1860	74	7	in	in	ADP
cana-1860	74	8	large	large	ADJ
cana-1860	74	9	measures	measure	NOUN
cana-1860	74	10	within	within	ADP
cana-1860	74	11	certain	certain	ADJ
cana-1860	74	12	specific	specific	ADJ
cana-1860	74	13	domains	domain	NOUN
cana-1860	74	14	,	,	PUNCT
cana-1860	74	15	those	those	PRON
cana-1860	74	16	pertaining	pertain	VERB
cana-1860	74	17	to	to	ADP
cana-1860	74	18	time	time	NOUN
cana-1860	74	19	-	-	PUNCT
cana-1860	74	20	series	series	NOUN
cana-1860	74	21	and	and	CCONJ
cana-1860	74	22	multimodal	multimodal	ADJ
cana-1860	74	23	data	datum	NOUN
cana-1860	74	24	predictions	prediction	NOUN
cana-1860	74	25	,	,	PUNCT
cana-1860	74	26	the	the	DET
cana-1860	74	27	integration	integration	NOUN
cana-1860	74	28	of	of	ADP
cana-1860	74	29	xgboost	xgboost	PROPN
cana-1860	74	30	,	,	PUNCT
cana-1860	74	31	lstm	lstm	PROPN
cana-1860	74	32	,	,	PUNCT
cana-1860	74	33	cnn	cnn	PROPN
cana-1860	74	34	,	,	PUNCT
cana-1860	74	35	ppo	ppo	PROPN
cana-1860	74	36	,	,	PUNCT
cana-1860	74	37	and	and	CCONJ
cana-1860	74	38	bayesian	bayesian	NOUN
cana-1860	74	39	neural	neural	ADJ
cana-1860	74	40	networks	network	NOUN
cana-1860	74	41	has	have	AUX
cana-1860	74	42	made	make	VERB
cana-1860	74	43	the	the	DET
cana-1860	74	44	proposed	propose	VERB
cana-1860	74	45	model	model	NOUN
cana-1860	74	46	far	far	ADV
cana-1860	74	47	more	more	ADV
cana-1860	74	48	comprehensive	comprehensive	ADJ
cana-1860	74	49	,	,	PUNCT
cana-1860	74	50	scalable	scalable	ADJ
cana-1860	74	51	,	,	PUNCT
cana-1860	74	52	and	and	CCONJ
cana-1860	74	53	adaptable	adaptable	ADJ
cana-1860	74	54	.	.	PUNCT
cana-1860	75	1	it	it	PRON
cana-1860	75	2	not	not	PART
cana-1860	75	3	only	only	ADV
cana-1860	75	4	improves	improve	VERB
cana-1860	75	5	the	the	DET
cana-1860	75	6	accuracy	accuracy	NOUN
cana-1860	75	7	of	of	ADP
cana-1860	75	8	prediction	prediction	NOUN
cana-1860	75	9	and	and	CCONJ
cana-1860	75	10	real	real	ADJ
cana-1860	75	11	-	-	PUNCT
cana-1860	75	12	time	time	NOUN
cana-1860	75	13	adaptability	adaptability	NOUN
cana-1860	75	14	but	but	CCONJ
cana-1860	75	15	extends	extend	VERB
cana-1860	75	16	to	to	PART
cana-1860	75	17	construct	construct	VERB
cana-1860	75	18	wide	wide	ADJ
cana-1860	75	19	applicability	applicability	NOUN
cana-1860	75	20	on	on	ADP
cana-1860	75	21	a	a	DET
cana-1860	75	22	range	range	NOUN
cana-1860	75	23	of	of	ADP
cana-1860	75	24	multimodal	multimodal	NOUN
cana-1860	75	25	datasets	dataset	NOUN
cana-1860	75	26	:	:	PUNCT
cana-1860	75	27	from	from	ADP
cana-1860	75	28	healthcare	healthcare	PROPN
cana-1860	75	29	to	to	PART
cana-1860	75	30	finance	finance	NOUN
cana-1860	75	31	,	,	PUNCT
cana-1860	75	32	sensor	sensor	NOUN
cana-1860	75	33	networks	network	NOUN
cana-1860	75	34	,	,	PUNCT
cana-1860	75	35	and	and	CCONJ
cana-1860	75	36	smart	smart	ADJ
cana-1860	75	37	cities	city	NOUN
cana-1860	75	38	.	.	PUNCT
cana-1860	76	1	3	3	X
cana-1860	76	2	.	.	NUM
cana-1860	76	3	proposed	propose	VERB
cana-1860	76	4	design	design	NOUN
cana-1860	76	5	of	of	ADP
cana-1860	76	6	an	an	DET
cana-1860	76	7	improved	improved	ADJ
cana-1860	76	8	model	model	NOUN
cana-1860	76	9	for	for	ADP
cana-1860	76	10	multimodal	multimodal	NOUN
cana-1860	76	11	data	datum	NOUN
cana-1860	76	12	fusion	fusion	NOUN
cana-1860	76	13	using	use	VERB
cana-1860	76	14	xgboost	xgboost	ADV
cana-1860	76	15	-	-	PUNCT
cana-1860	76	16	lstmcnn	lstmcnn	ADJ
cana-1860	76	17	and	and	CCONJ
cana-1860	76	18	proximal	proximal	ADJ
cana-1860	76	19	policy	policy	NOUN
cana-1860	76	20	optimizations	optimization	NOUN
cana-1860	76	21	this	this	DET
cana-1860	76	22	section	section	NOUN
cana-1860	76	23	provides	provide	VERB
cana-1860	76	24	a	a	DET
cana-1860	76	25	comprehensive	comprehensive	ADJ
cana-1860	76	26	solution	solution	NOUN
cana-1860	76	27	for	for	ADP
cana-1860	76	28	multimodal	multimodal	NOUN
cana-1860	76	29	data	datum	NOUN
cana-1860	76	30	fusion	fusion	NOUN
cana-1860	76	31	,	,	PUNCT
cana-1860	76	32	time	time	NOUN
cana-1860	76	33	-	-	PUNCT
cana-1860	76	34	series	series	NOUN
cana-1860	76	35	prediction	prediction	NOUN
cana-1860	76	36	,	,	PUNCT
cana-1860	76	37	and	and	CCONJ
cana-1860	76	38	dynamic	dynamic	ADJ
cana-1860	76	39	adaptation	adaptation	NOUN
cana-1860	76	40	by	by	ADP
cana-1860	76	41	leveraging	leverage	VERB
cana-1860	76	42	the	the	DET
cana-1860	76	43	strengths	strength	NOUN
cana-1860	76	44	of	of	ADP
cana-1860	76	45	xgboost	xgboost	PROPN
cana-1860	76	46	,	,	PUNCT
cana-1860	76	47	lstm	lstm	PROPN
cana-1860	76	48	,	,	PUNCT
cana-1860	76	49	cnn	cnn	PROPN
cana-1860	76	50	,	,	PUNCT
cana-1860	76	51	and	and	CCONJ
cana-1860	76	52	reinforcement	reinforcement	NOUN
cana-1860	76	53	learning	learning	NOUN
cana-1860	76	54	via	via	ADP
cana-1860	76	55	ppo	ppo	PROPN
cana-1860	76	56	.	.	PUNCT
cana-1860	77	1	each	each	DET
cana-1860	77	2	constituent	constituent	NOUN
cana-1860	77	3	addresses	address	VERB
cana-1860	77	4	a	a	DET
cana-1860	77	5	specific	specific	ADJ
cana-1860	77	6	part	part	NOUN
cana-1860	77	7	of	of	ADP
cana-1860	77	8	the	the	DET
cana-1860	77	9	general	general	ADJ
cana-1860	77	10	complex	complex	ADJ
cana-1860	77	11	problem	problem	NOUN
cana-1860	77	12	of	of	ADP
cana-1860	77	13	multimodal	multimodal	NOUN
cana-1860	77	14	data	datum	NOUN
cana-1860	77	15	:	:	PUNCT
cana-1860	77	16	xgboost	xgboost	X
cana-1860	77	17	for	for	ADP
cana-1860	77	18	structured	structure	VERB
cana-1860	77	19	tabular	tabular	NOUN
cana-1860	77	20	data	datum	NOUN
cana-1860	77	21	handling	handling	NOUN
cana-1860	77	22	in	in	ADP
cana-1860	77	23	an	an	DET
cana-1860	77	24	efficient	efficient	ADJ
cana-1860	77	25	manner	manner	NOUN
cana-1860	77	26	,	,	PUNCT
cana-1860	77	27	lstm	lstm	NOUN
cana-1860	77	28	for	for	ADP
cana-1860	77	29	capturing	capture	VERB
cana-1860	77	30	longterm	longterm	ADJ
cana-1860	77	31	dependencies	dependency	NOUN
cana-1860	77	32	in	in	ADP
cana-1860	77	33	sequential	sequential	ADJ
cana-1860	77	34	data	datum	NOUN
cana-1860	77	35	,	,	PUNCT
cana-1860	77	36	cnn	cnn	PROPN
cana-1860	77	37	for	for	ADP
cana-1860	77	38	extracting	extract	VERB
cana-1860	77	39	spatial	spatial	ADJ
cana-1860	77	40	features	feature	NOUN
cana-1860	77	41	,	,	PUNCT
cana-1860	77	42	and	and	CCONJ
cana-1860	77	43	ppo	ppo	PROPN
cana-1860	77	44	for	for	ADP
cana-1860	77	45	dynamic	dynamic	ADJ
cana-1860	77	46	adaptability	adaptability	NOUN
cana-1860	77	47	in	in	ADP
cana-1860	77	48	runtime	runtime	NOUN
cana-1860	77	49	scenarios	scenario	NOUN
cana-1860	77	50	.	.	PUNCT
cana-1860	78	1	this	this	DET
cana-1860	78	2	model	model	NOUN
cana-1860	78	3	is	be	AUX
cana-1860	78	4	designed	design	VERB
cana-1860	78	5	to	to	PART
cana-1860	78	6	enhance	enhance	VERB
cana-1860	78	7	the	the	DET
cana-1860	78	8	prediction	prediction	NOUN
cana-1860	78	9	accuracy	accuracy	NOUN
cana-1860	78	10	and	and	CCONJ
cana-1860	78	11	robustness	robustness	NOUN
cana-1860	78	12	by	by	ADP
cana-1860	78	13	leveraging	leverage	VERB
cana-1860	78	14	synergies	synergy	NOUN
cana-1860	78	15	among	among	ADP
cana-1860	78	16	the	the	DET
cana-1860	78	17	said	say	VERB
cana-1860	78	18	techniques	technique	NOUN
cana-1860	78	19	.	.	PUNCT
cana-1860	79	1	it	it	PRON
cana-1860	79	2	also	also	ADV
cana-1860	79	3	provides	provide	VERB
cana-1860	79	4	an	an	DET
cana-1860	79	5	advanced	advanced	ADJ
cana-1860	79	6	bayesian	bayesian	NOUN
cana-1860	79	7	technique	technique	NOUN
cana-1860	79	8	to	to	PART
cana-1860	79	9	enable	enable	VERB
cana-1860	79	10	online	online	ADJ
cana-1860	79	11	learning	learning	NOUN
cana-1860	79	12	continuously	continuously	ADV
cana-1860	79	13	and	and	CCONJ
cana-1860	79	14	filtering	filter	VERB
cana-1860	79	15	noises	noise	NOUN
cana-1860	79	16	.	.	PUNCT
cana-1860	80	1	xgboost	xgboost	PROPN
cana-1860	80	2	will	will	AUX
cana-1860	80	3	perform	perform	VERB
cana-1860	80	4	the	the	DET
cana-1860	80	5	initial	initial	ADJ
cana-1860	80	6	process	process	NOUN
cana-1860	80	7	on	on	ADP
cana-1860	80	8	static	static	ADJ
cana-1860	80	9	or	or	CCONJ
cana-1860	80	10	non	non	ADJ
cana-1860	80	11	-	-	ADJ
cana-1860	80	12	sequential	sequential	ADJ
cana-1860	80	13	tabular	tabular	NOUN
cana-1860	80	14	features	feature	VERB
cana-1860	80	15	.	.	PUNCT
cana-1860	81	1	in	in	ADP
cana-1860	81	2	this	this	DET
cana-1860	81	3	approach	approach	NOUN
cana-1860	81	4	,	,	PUNCT
cana-1860	81	5	a	a	DET
cana-1860	81	6	loss	loss	NOUN
cana-1860	81	7	function	function	NOUN
cana-1860	81	8	l(θ	l(θ	NOUN
cana-1860	81	9	)	)	PUNCT
cana-1860	81	10	is	be	AUX
cana-1860	81	11	defined	define	VERB
cana-1860	81	12	as	as	ADP
cana-1860	81	13	a	a	DET
cana-1860	81	14	regularized	regularize	VERB
cana-1860	81	15	objective	objective	ADJ
cana-1860	81	16	balancing	balancing	NOUN
cana-1860	81	17	model	model	NOUN
cana-1860	81	18	accuracy	accuracy	NOUN
cana-1860	81	19	and	and	CCONJ
cana-1860	81	20	model	model	NOUN
cana-1860	81	21	complexity	complexity	NOUN
cana-1860	81	22	.	.	PUNCT
cana-1860	82	1	the	the	DET
cana-1860	82	2	regularized	regularize	VERB
cana-1860	82	3	loss	loss	NOUN
cana-1860	82	4	function	function	NOUN
cana-1860	82	5	is	be	AUX
cana-1860	82	6	given	give	VERB
cana-1860	82	7	via	via	ADP
cana-1860	82	8	equation	equation	NOUN
cana-1860	82	9	1	1	NUM
cana-1860	82	10	,	,	PUNCT
cana-1860	82	11	𝐿(𝜃	𝐿(𝜃	PRON
cana-1860	82	12	)	)	PUNCT
cana-1860	82	13	=	=	SYM
cana-1860	82	14	∑𝑙(𝑦𝑖	∑𝑙(𝑦𝑖	NUM
cana-1860	82	15	,	,	PUNCT
cana-1860	82	16	𝑦′𝑖(𝜃	𝑦′𝑖(𝜃	NOUN
cana-1860	82	17	)	)	PUNCT
cana-1860	82	18	)	)	PUNCT
cana-1860	83	1	+	+	PUNCT
cana-1860	83	2	𝛺(𝜃	𝛺(𝜃	NUM
cana-1860	83	3	)	)	PUNCT
cana-1860	83	4	…	…	PUNCT
cana-1860	83	5	(	(	PUNCT
cana-1860	83	6	1	1	X
cana-1860	83	7	)	)	PUNCT
cana-1860	83	8	𝑛	𝑛	PRON
cana-1860	83	9	𝑖=1	𝑖=1	PUNCT
cana-1860	83	10	where	where	SCONJ
cana-1860	83	11	,	,	PUNCT
cana-1860	83	12	𝑙(𝑦𝑖	𝑙(𝑦𝑖	PROPN
cana-1860	83	13	,	,	PUNCT
cana-1860	83	14	𝑦′𝑖(𝜃	𝑦′𝑖(𝜃	PROPN
cana-1860	83	15	)	)	PUNCT
cana-1860	83	16	)	)	PUNCT
cana-1860	83	17	represents	represent	VERB
cana-1860	83	18	the	the	DET
cana-1860	83	19	loss	loss	NOUN
cana-1860	83	20	between	between	ADP
cana-1860	83	21	true	true	ADJ
cana-1860	83	22	values	value	NOUN
cana-1860	83	23	yi	yi	PROPN
cana-1860	83	24	and	and	CCONJ
cana-1860	83	25	predicted	predict	VERB
cana-1860	83	26	values	value	NOUN
cana-1860	83	27	y'i(θ	y'i(θ	PROPN
cana-1860	83	28	)	)	PUNCT
cana-1860	83	29	,	,	PUNCT
cana-1860	83	30	while	while	SCONJ
cana-1860	83	31	ω(θ	ω(θ	NUM
cana-1860	83	32	)	)	PUNCT
cana-1860	83	33	represents	represent	VERB
cana-1860	83	34	the	the	DET
cana-1860	83	35	regularization	regularization	NOUN
cana-1860	83	36	term	term	NOUN
cana-1860	83	37	,	,	PUNCT
cana-1860	83	38	which	which	PRON
cana-1860	83	39	helps	help	VERB
cana-1860	83	40	in	in	ADP
cana-1860	83	41	preventing	prevent	VERB
cana-1860	83	42	overfitting	overfitte	VERB
cana-1860	83	43	by	by	ADP
cana-1860	83	44	penalizing	penalize	VERB
cana-1860	83	45	model	model	NOUN
cana-1860	83	46	complexity	complexity	NOUN
cana-1860	83	47	levels	level	NOUN
cana-1860	83	48	.	.	PUNCT
cana-1860	84	1	the	the	DET
cana-1860	84	2	output	output	NOUN
cana-1860	84	3	of	of	ADP
cana-1860	84	4	xgboost	xgboost	ADV
cana-1860	84	5	gives	give	VERB
cana-1860	84	6	feature	feature	NOUN
cana-1860	84	7	importance	importance	NOUN
cana-1860	84	8	and	and	CCONJ
cana-1860	84	9	a	a	DET
cana-1860	84	10	baseline	baseline	NOUN
cana-1860	84	11	prediction	prediction	NOUN
cana-1860	84	12	,	,	PUNCT
cana-1860	84	13	which	which	PRON
cana-1860	84	14	is	be	AUX
cana-1860	84	15	combined	combine	VERB
cana-1860	84	16	further	far	ADV
cana-1860	84	17	with	with	ADP
cana-1860	84	18	the	the	DET
cana-1860	84	19	deep	deep	ADJ
cana-1860	84	20	learning	learning	NOUN
cana-1860	84	21	components	component	NOUN
cana-1860	84	22	.	.	PUNCT
cana-1860	85	1	among	among	ADP
cana-1860	85	2	the	the	DET
cana-1860	85	3	considered	consider	VERB
cana-1860	85	4	models	model	NOUN
cana-1860	85	5	,	,	PUNCT
cana-1860	85	6	the	the	DET
cana-1860	85	7	lstm	lstm	PROPN
cana-1860	85	8	network	network	NOUN
cana-1860	85	9	had	have	VERB
cana-1860	85	10	the	the	DET
cana-1860	85	11	most	most	ADV
cana-1860	85	12	important	important	ADJ
cana-1860	85	13	role	role	NOUN
cana-1860	85	14	to	to	PART
cana-1860	85	15	handle	handle	VERB
cana-1860	85	16	temporal	temporal	ADJ
cana-1860	85	17	dependencies	dependency	NOUN
cana-1860	85	18	in	in	ADP
cana-1860	85	19	sequential	sequential	ADJ
cana-1860	85	20	data	datum	NOUN
cana-1860	85	21	.	.	PUNCT
cana-1860	86	1	the	the	DET
cana-1860	86	2	lstm	lstm	NOUN
cana-1860	86	3	will	will	AUX
cana-1860	86	4	take	take	VERB
cana-1860	86	5	as	as	ADP
cana-1860	86	6	input	input	NOUN
cana-1860	86	7	sequences	sequence	NOUN
cana-1860	86	8	xt	xt	PROPN
cana-1860	86	9	,	,	PUNCT
cana-1860	86	10	either	either	DET
cana-1860	86	11	time	time	NOUN
cana-1860	86	12	series	series	NOUN
cana-1860	86	13	or	or	CCONJ
cana-1860	86	14	sensor	sensor	NOUN
cana-1860	86	15	data	datum	NOUN
cana-1860	86	16	,	,	PUNCT
cana-1860	86	17	and	and	CCONJ
cana-1860	86	18	will	will	AUX
cana-1860	86	19	keep	keep	VERB
cana-1860	86	20	track	track	NOUN
cana-1860	86	21	of	of	ADP
cana-1860	86	22	a	a	DET
cana-1860	86	23	memory	memory	NOUN
cana-1860	86	24	state	state	NOUN
cana-1860	86	25	ct	ct	PROPN
cana-1860	86	26	across	across	ADP
cana-1860	86	27	temporal	temporal	ADJ
cana-1860	86	28	sets	set	NOUN
cana-1860	86	29	of	of	ADP
cana-1860	86	30	instances	instance	NOUN
cana-1860	86	31	.	.	PUNCT
cana-1860	87	1	the	the	DET
cana-1860	87	2	cell	cell	NOUN
cana-1860	87	3	and	and	CCONJ
cana-1860	87	4	hidden	hide	VERB
cana-1860	87	5	state	state	NOUN
cana-1860	87	6	update	update	NOUN
cana-1860	87	7	can	can	AUX
cana-1860	87	8	be	be	AUX
cana-1860	87	9	done	do	VERB
cana-1860	87	10	by	by	ADP
cana-1860	87	11	the	the	DET
cana-1860	87	12	following	follow	VERB
cana-1860	87	13	equations	equation	NOUN
cana-1860	87	14	2	2	NUM
cana-1860	87	15	,	,	PUNCT
cana-1860	87	16	3	3	NUM
cana-1860	87	17	,	,	PUNCT
cana-1860	87	18	4	4	NUM
cana-1860	87	19	,	,	PUNCT
cana-1860	87	20	5	5	NUM
cana-1860	87	21	&	&	CCONJ
cana-1860	87	22	6	6	NUM
cana-1860	87	23	,	,	PUNCT
cana-1860	87	24	𝑓𝑡	𝑓𝑡	NOUN
cana-1860	87	25	=	=	PUNCT
cana-1860	87	26	𝜎(𝑊𝑓	𝜎(𝑊𝑓	NOUN
cana-1860	87	27	⋅	⋅	X
cana-1860	88	1	[	[	X
cana-1860	88	2	ℎ(𝑡	ℎ(𝑡	PROPN
cana-1860	88	3	−	−	PROPN
cana-1860	88	4	1	1	NUM
cana-1860	88	5	)	)	PUNCT
cana-1860	88	6	,	,	PUNCT
cana-1860	88	7	𝑋𝑡	𝑋𝑡	PROPN
cana-1860	88	8	]	]	PUNCT
cana-1860	88	9	+	+	CCONJ
cana-1860	88	10	𝑏𝑓	𝑏𝑓	PROPN
cana-1860	88	11	)	)	PUNCT
cana-1860	88	12	…	…	PUNCT
cana-1860	88	13	(	(	PUNCT
cana-1860	88	14	2	2	X
cana-1860	88	15	)	)	PUNCT
cana-1860	88	16	𝑖𝑡	𝑖𝑡	NOUN
cana-1860	89	1	=	=	PUNCT
cana-1860	89	2	𝜎(𝑊𝑖	𝜎(𝑊𝑖	NOUN
cana-1860	89	3	⋅	⋅	PROPN
cana-1860	90	1	[	[	X
cana-1860	90	2	ℎ(𝑡	ℎ(𝑡	PROPN
cana-1860	90	3	−	−	PROPN
cana-1860	90	4	1	1	NUM
cana-1860	90	5	)	)	PUNCT
cana-1860	90	6	,	,	PUNCT
cana-1860	90	7	𝑋𝑡	𝑋𝑡	PROPN
cana-1860	90	8	]	]	PUNCT
cana-1860	90	9	+	+	CCONJ
cana-1860	90	10	𝑏𝑖	𝑏𝑖	PROPN
cana-1860	90	11	)	)	PUNCT
cana-1860	90	12	…	…	PUNCT
cana-1860	90	13	(	(	PUNCT
cana-1860	90	14	3	3	X
cana-1860	90	15	)	)	PUNCT
cana-1860	90	16	communications	communication	NOUN
cana-1860	90	17	on	on	ADP
cana-1860	90	18	applied	apply	VERB
cana-1860	90	19	nonlinear	nonlinear	ADJ
cana-1860	90	20	analysis	analysis	NOUN
cana-1860	90	21	issn	issn	NOUN
cana-1860	90	22	:	:	PUNCT
cana-1860	90	23	1074	1074	NUM
cana-1860	90	24	-	-	PUNCT
cana-1860	90	25	133x	133x	NUM
cana-1860	90	26	vol	vol	NOUN
cana-1860	90	27	32	32	NUM
cana-1860	90	28	no	no	NOUN
cana-1860	90	29	.	.	NOUN
cana-1860	90	30	2	2	NUM
cana-1860	90	31	(	(	PUNCT
cana-1860	90	32	2025	2025	NUM
cana-1860	90	33	)	)	PUNCT
cana-1860	91	1	670	670	NUM
cana-1860	91	2	https://internationalpubls.com	https://internationalpubls.com	X
cana-1860	91	3	𝐶𝑡	𝐶𝑡	PROPN
cana-1860	91	4	=	=	PROPN
cana-1860	92	1	𝑓𝑡	𝑓𝑡	PROPN
cana-1860	92	2	⊙	⊙	PROPN
cana-1860	92	3	𝐶(𝑡	𝐶(𝑡	X
cana-1860	92	4	−	−	PROPN
cana-1860	92	5	1	1	NUM
cana-1860	92	6	)	)	PUNCT
cana-1860	92	7	+	+	CCONJ
cana-1860	92	8	𝑖𝑡	𝑖𝑡	NOUN
cana-1860	92	9	⊙	⊙	NOUN
cana-1860	92	10	𝑡𝑎𝑛	𝑡𝑎𝑛	PUNCT
cana-1860	93	1	ℎ(𝑊𝑐	ℎ(𝑊𝑐	PROPN
cana-1860	93	2	⋅	⋅	PROPN
cana-1860	93	3	[	[	X
cana-1860	93	4	ℎ(𝑡	ℎ(𝑡	PROPN
cana-1860	93	5	−	−	PROPN
cana-1860	93	6	1	1	NUM
cana-1860	93	7	)	)	PUNCT
cana-1860	93	8	,	,	PUNCT
cana-1860	93	9	𝑋𝑡	𝑋𝑡	PROPN
cana-1860	93	10	]	]	PUNCT
cana-1860	93	11	+	+	CCONJ
cana-1860	93	12	𝑏𝑐	𝑏𝑐	PROPN
cana-1860	93	13	)	)	PUNCT
cana-1860	93	14	…	…	PUNCT
cana-1860	93	15	(	(	PUNCT
cana-1860	93	16	4	4	X
cana-1860	93	17	)	)	PUNCT
cana-1860	93	18	𝑜𝑡	𝑜𝑡	NOUN
cana-1860	93	19	=	=	PUNCT
cana-1860	93	20	𝜎(𝑊𝑜	𝜎(𝑊𝑜	NOUN
cana-1860	93	21	⋅	⋅	X
cana-1860	94	1	[	[	X
cana-1860	94	2	ℎ(𝑡	ℎ(𝑡	PROPN
cana-1860	94	3	−	−	PROPN
cana-1860	94	4	1	1	NUM
cana-1860	94	5	)	)	PUNCT
cana-1860	94	6	,	,	PUNCT
cana-1860	94	7	𝑋𝑡	𝑋𝑡	PROPN
cana-1860	94	8	]	]	X
cana-1860	94	9	+	+	CCONJ
cana-1860	94	10	𝑏𝑜	𝑏𝑜	ADJ
cana-1860	94	11	)	)	PUNCT
cana-1860	94	12	…	…	PUNCT
cana-1860	94	13	(	(	PUNCT
cana-1860	94	14	5	5	X
cana-1860	94	15	)	)	PUNCT
cana-1860	94	16	ℎ𝑡	ℎ𝑡	NOUN
cana-1860	94	17	=	=	PUNCT
cana-1860	94	18	𝑜𝑡	𝑜𝑡	PROPN
cana-1860	94	19	⊙	⊙	PROPN
cana-1860	94	20	𝑡𝑎𝑛	𝑡𝑎𝑛	PUNCT
cana-1860	95	1	ℎ(𝐶𝑡	ℎ(𝐶𝑡	PROPN
cana-1860	95	2	)	)	PUNCT
cana-1860	95	3	…	…	PUNCT
cana-1860	95	4	(	(	PUNCT
cana-1860	95	5	6	6	X
cana-1860	95	6	)	)	PUNCT
cana-1860	95	7	figure	figure	NOUN
cana-1860	95	8	1	1	NUM
cana-1860	95	9	.	.	PUNCT
cana-1860	95	10	model	model	NOUN
cana-1860	95	11	architecture	architecture	NOUN
cana-1860	95	12	of	of	ADP
cana-1860	95	13	the	the	DET
cana-1860	95	14	proposed	propose	VERB
cana-1860	95	15	analysis	analysis	NOUN
cana-1860	95	16	process	process	NOUN
cana-1860	95	17	where	where	SCONJ
cana-1860	95	18	,	,	PUNCT
cana-1860	95	19	ft	ft	NOUN
cana-1860	95	20	,	,	PUNCT
cana-1860	95	21	it	it	PRON
cana-1860	95	22	,	,	PUNCT
cana-1860	95	23	and	and	CCONJ
cana-1860	95	24	ot	ot	INTJ
cana-1860	95	25	represent	represent	VERB
cana-1860	95	26	forget	forget	PROPN
cana-1860	95	27	,	,	PUNCT
cana-1860	95	28	input	input	NOUN
cana-1860	95	29	and	and	CCONJ
cana-1860	95	30	output	output	NOUN
cana-1860	95	31	gates	gate	NOUN
cana-1860	95	32	,	,	PUNCT
cana-1860	95	33	respectively	respectively	ADV
cana-1860	95	34	,	,	PUNCT
cana-1860	95	35	and	and	CCONJ
cana-1860	95	36	control	control	VERB
cana-1860	95	37	the	the	DET
cana-1860	95	38	flow	flow	NOUN
cana-1860	95	39	of	of	ADP
cana-1860	95	40	information	information	NOUN
cana-1860	95	41	inside	inside	ADP
cana-1860	95	42	and	and	CCONJ
cana-1860	95	43	outside	outside	ADP
cana-1860	95	44	the	the	DET
cana-1860	95	45	memory	memory	NOUN
cana-1860	95	46	cells	cell	NOUN
cana-1860	95	47	.	.	PUNCT
cana-1860	96	1	this	this	PRON
cana-1860	96	2	enables	enable	VERB
cana-1860	96	3	the	the	DET
cana-1860	96	4	lstm	lstm	PROPN
cana-1860	96	5	network	network	NOUN
cana-1860	96	6	to	to	PART
cana-1860	96	7	model	model	VERB
cana-1860	96	8	long	long	ADJ
cana-1860	96	9	-	-	PUNCT
cana-1860	96	10	term	term	NOUN
cana-1860	96	11	temporal	temporal	ADJ
cana-1860	96	12	dependencies	dependency	NOUN
cana-1860	96	13	in	in	ADP
cana-1860	96	14	time	time	NOUN
cana-1860	96	15	-	-	PUNCT
cana-1860	96	16	series	series	NOUN
cana-1860	96	17	samples	sample	NOUN
cana-1860	96	18	effectively	effectively	ADV
cana-1860	96	19	.	.	PUNCT
cana-1860	97	1	simultaneously	simultaneously	ADV
cana-1860	97	2	,	,	PUNCT
cana-1860	97	3	cnn	cnn	PROPN
cana-1860	97	4	is	be	AUX
cana-1860	97	5	employed	employ	VERB
cana-1860	97	6	for	for	ADP
cana-1860	97	7	extracting	extract	VERB
cana-1860	97	8	spatial	spatial	ADJ
cana-1860	97	9	features	feature	NOUN
cana-1860	97	10	from	from	ADP
cana-1860	97	11	the	the	DET
cana-1860	97	12	multimodal	multimodal	NOUN
cana-1860	97	13	data	datum	NOUN
cana-1860	97	14	,	,	PUNCT
cana-1860	97	15	such	such	ADJ
cana-1860	97	16	as	as	ADP
cana-1860	97	17	but	but	CCONJ
cana-1860	97	18	not	not	PART
cana-1860	97	19	restricted	restrict	VERB
cana-1860	97	20	to	to	ADP
cana-1860	97	21	image	image	VERB
cana-1860	97	22	sequences	sequence	NOUN
cana-1860	97	23	and	and	CCONJ
cana-1860	97	24	sensor	sensor	NOUN
cana-1860	97	25	arrays	array	VERB
cana-1860	97	26	.	.	PUNCT
cana-1860	98	1	extracted	extract	VERB
cana-1860	98	2	features	feature	NOUN
cana-1860	98	3	of	of	ADP
cana-1860	98	4	cnn	cnn	PROPN
cana-1860	98	5	have	have	AUX
cana-1860	98	6	been	be	AUX
cana-1860	98	7	obtained	obtain	VERB
cana-1860	98	8	by	by	ADP
cana-1860	98	9	applying	apply	VERB
cana-1860	98	10	successive	successive	ADJ
cana-1860	98	11	convolutions	convolution	NOUN
cana-1860	98	12	computed	compute	VERB
cana-1860	98	13	via	via	ADP
cana-1860	98	14	equation	equation	NOUN
cana-1860	98	15	7	7	NUM
cana-1860	98	16	,	,	PUNCT
cana-1860	98	17	𝐹(𝑖	𝐹(𝑖	PRON
cana-1860	98	18	,	,	PUNCT
cana-1860	98	19	𝑗	𝑗	NOUN
cana-1860	98	20	)	)	PUNCT
cana-1860	98	21	=	=	PUNCT
cana-1860	99	1	∑	∑	PUNCT
cana-1860	99	2	∑𝑋(𝑖	∑𝑋(𝑖	PROPN
cana-1860	100	1	+	+	CCONJ
cana-1860	100	2	𝑚	𝑚	PART
cana-1860	100	3	−	−	PROPN
cana-1860	100	4	1	1	NUM
cana-1860	100	5	,	,	PUNCT
cana-1860	100	6	𝑗	𝑗	PROPN
cana-1860	100	7	+	+	NOUN
cana-1860	100	8	𝑛	𝑛	DET
cana-1860	100	9	−	−	PROPN
cana-1860	100	10	1	1	NUM
cana-1860	100	11	)	)	PUNCT
cana-1860	100	12	⋅	⋅	PROPN
cana-1860	100	13	𝐾(𝑚	𝐾(𝑚	PROPN
cana-1860	100	14	,	,	PUNCT
cana-1860	100	15	𝑛	𝑛	PROPN
cana-1860	100	16	)	)	PUNCT
cana-1860	100	17	+	+	NOUN
cana-1860	100	18	𝑏	𝑏	NOUN
cana-1860	100	19	…	…	PUNCT
cana-1860	100	20	(	(	PUNCT
cana-1860	100	21	7	7	X
cana-1860	100	22	)	)	PUNCT
cana-1860	100	23	𝑁	𝑁	PROPN
cana-1860	100	24	𝑛=1	𝑛=1	NOUN
cana-1860	100	25	𝑀	𝑀	PROPN
cana-1860	100	26	𝑚=1	𝑚=1	PUNCT
cana-1860	100	27	here	here	ADV
cana-1860	100	28	,	,	PUNCT
cana-1860	100	29	x(i	x(i	PROPN
cana-1860	100	30	,	,	PUNCT
cana-1860	100	31	j	j	NOUN
cana-1860	100	32	)	)	PUNCT
cana-1860	100	33	represents	represent	VERB
cana-1860	100	34	the	the	DET
cana-1860	100	35	input	input	NOUN
cana-1860	100	36	image	image	NOUN
cana-1860	100	37	data	datum	NOUN
cana-1860	100	38	,	,	PUNCT
cana-1860	100	39	'	'	PUNCT
cana-1860	100	40	k	k	X
cana-1860	100	41	'	'	PUNCT
cana-1860	100	42	the	the	DET
cana-1860	100	43	convolution	convolution	NOUN
cana-1860	100	44	kernel	kernel	NOUN
cana-1860	100	45	and	and	CCONJ
cana-1860	100	46	'	'	PUNCT
cana-1860	100	47	b	b	X
cana-1860	100	48	'	'	PUNCT
cana-1860	100	49	the	the	DET
cana-1860	100	50	bias	bias	NOUN
cana-1860	100	51	term	term	NOUN
cana-1860	100	52	.	.	PUNCT
cana-1860	101	1	the	the	DET
cana-1860	101	2	convolutional	convolutional	ADJ
cana-1860	101	3	layers	layer	NOUN
cana-1860	101	4	in	in	ADP
cana-1860	101	5	cnn	cnn	PROPN
cana-1860	101	6	capture	capture	VERB
cana-1860	101	7	the	the	DET
cana-1860	101	8	spatial	spatial	ADJ
cana-1860	101	9	patterns	pattern	NOUN
cana-1860	101	10	in	in	ADP
cana-1860	101	11	the	the	DET
cana-1860	101	12	data	datum	NOUN
cana-1860	101	13	,	,	PUNCT
cana-1860	101	14	which	which	PRON
cana-1860	101	15	are	be	AUX
cana-1860	101	16	very	very	ADV
cana-1860	101	17	much	much	ADV
cana-1860	101	18	essential	essential	ADJ
cana-1860	101	19	for	for	ADP
cana-1860	101	20	accurate	accurate	ADJ
cana-1860	101	21	predictions	prediction	NOUN
cana-1860	101	22	in	in	ADP
cana-1860	101	23	domains	domain	NOUN
cana-1860	101	24	such	such	ADJ
cana-1860	101	25	as	as	ADP
cana-1860	101	26	video	video	NOUN
cana-1860	101	27	analysis	analysis	NOUN
cana-1860	101	28	and	and	CCONJ
cana-1860	101	29	sensor	sensor	NOUN
cana-1860	101	30	data	datum	NOUN
cana-1860	101	31	fusion	fusion	NOUN
cana-1860	101	32	.	.	PUNCT
cana-1860	102	1	the	the	DET
cana-1860	102	2	combination	combination	NOUN
cana-1860	102	3	of	of	ADP
cana-1860	102	4	output	output	NOUN
cana-1860	102	5	from	from	ADP
cana-1860	102	6	xgboost	xgboost	PROPN
cana-1860	102	7	,	,	PUNCT
cana-1860	102	8	lstm	lstm	PROPN
cana-1860	102	9	and	and	CCONJ
cana-1860	102	10	cnn	cnn	PROPN
cana-1860	102	11	through	through	ADP
cana-1860	102	12	concatenation	concatenation	NOUN
cana-1860	102	13	provides	provide	VERB
cana-1860	102	14	a	a	DET
cana-1860	102	15	fused	fuse	VERB
cana-1860	102	16	feature	feature	NOUN
cana-1860	102	17	representation	representation	NOUN
cana-1860	102	18	given	give	VERB
cana-1860	102	19	via	via	ADP
cana-1860	102	20	equation	equation	NOUN
cana-1860	102	21	8	8	NUM
cana-1860	102	22	,	,	PUNCT
cana-1860	102	23	𝑍	𝑍	NOUN
cana-1860	102	24	=	=	SYM
cana-1860	102	25	[	[	X
cana-1860	102	26	𝑦’𝑋𝐺𝐵	𝑦’𝑋𝐺𝐵	ADV
cana-1860	102	27	,	,	PUNCT
cana-1860	102	28	ℎ𝑡	ℎ𝑡	NOUN
cana-1860	102	29	,	,	PUNCT
cana-1860	102	30	𝐹(𝑖	𝐹(𝑖	NUM
cana-1860	102	31	,	,	PUNCT
cana-1860	102	32	𝑗	𝑗	NOUN
cana-1860	102	33	)	)	PUNCT
cana-1860	102	34	]	]	PUNCT
cana-1860	102	35	…	…	PUNCT
cana-1860	102	36	(	(	PUNCT
cana-1860	102	37	8)	8)	NUM
cana-1860	102	38	communications	communication	NOUN
cana-1860	102	39	on	on	ADP
cana-1860	102	40	applied	apply	VERB
cana-1860	102	41	nonlinear	nonlinear	ADJ
cana-1860	102	42	analysis	analysis	NOUN
cana-1860	102	43	issn	issn	NOUN
cana-1860	102	44	:	:	PUNCT
cana-1860	102	45	1074	1074	NUM
cana-1860	102	46	-	-	PUNCT
cana-1860	102	47	133x	133x	NUM
cana-1860	102	48	vol	vol	NOUN
cana-1860	102	49	32	32	NUM
cana-1860	103	1	no	no	NOUN
cana-1860	103	2	.	.	NOUN
cana-1860	103	3	2	2	NUM
cana-1860	103	4	(	(	PUNCT
cana-1860	103	5	2025	2025	NUM
cana-1860	103	6	)	)	PUNCT
cana-1860	103	7	671	671	NUM
cana-1860	103	8	https://internationalpubls.com	https://internationalpubls.com	X
cana-1860	104	1	where	where	SCONJ
cana-1860	104	2	,	,	PUNCT
cana-1860	104	3	y'xgb	y'xgb	PROPN
cana-1860	104	4	is	be	AUX
cana-1860	104	5	the	the	DET
cana-1860	104	6	xgboost	xgboost	PROPN
cana-1860	104	7	prediction	prediction	NOUN
cana-1860	104	8	,	,	PUNCT
cana-1860	104	9	ht	ht	PROPN
cana-1860	104	10	is	be	AUX
cana-1860	104	11	the	the	DET
cana-1860	104	12	lstm	lstm	NOUN
cana-1860	104	13	hidden	hide	VERB
cana-1860	104	14	state	state	NOUN
cana-1860	104	15	and	and	CCONJ
cana-1860	104	16	f(i	f(i	PROPN
cana-1860	104	17	,	,	PUNCT
cana-1860	104	18	j	j	NOUN
cana-1860	104	19	)	)	PUNCT
cana-1860	104	20	represents	represent	VERB
cana-1860	104	21	the	the	DET
cana-1860	104	22	cnn	cnn	PROPN
cana-1860	104	23	feature	feature	NOUN
cana-1860	104	24	maps	map	NOUN
cana-1860	104	25	.	.	PUNCT
cana-1860	105	1	this	this	DET
cana-1860	105	2	fused	fuse	VERB
cana-1860	105	3	representation	representation	NOUN
cana-1860	105	4	is	be	AUX
cana-1860	105	5	further	far	ADV
cana-1860	105	6	passed	pass	VERB
cana-1860	105	7	through	through	ADP
cana-1860	105	8	fully	fully	ADV
cana-1860	105	9	connected	connected	ADJ
cana-1860	105	10	layers	layer	NOUN
cana-1860	105	11	for	for	ADP
cana-1860	105	12	final	final	ADJ
cana-1860	105	13	prediction	prediction	NOUN
cana-1860	105	14	.	.	PUNCT
cana-1860	106	1	to	to	PART
cana-1860	106	2	make	make	VERB
cana-1860	106	3	the	the	DET
cana-1860	106	4	model	model	NOUN
cana-1860	106	5	more	more	ADV
cana-1860	106	6	adaptive	adaptive	ADJ
cana-1860	106	7	to	to	ADP
cana-1860	106	8	dynamic	dynamic	ADJ
cana-1860	106	9	environments	environment	NOUN
cana-1860	106	10	proximal	proximal	ADJ
cana-1860	106	11	policy	policy	NOUN
cana-1860	106	12	optimization	optimization	NOUN
cana-1860	106	13	is	be	AUX
cana-1860	106	14	used	use	VERB
cana-1860	106	15	.	.	PUNCT
cana-1860	107	1	ppo	ppo	PROPN
cana-1860	107	2	optimizes	optimize	VERB
cana-1860	107	3	the	the	DET
cana-1860	107	4	policy	policy	NOUN
cana-1860	107	5	πθ(a∣s	πθ(a∣s	NOUN
cana-1860	107	6	)	)	PUNCT
cana-1860	107	7	in	in	ADP
cana-1860	107	8	a	a	DET
cana-1860	107	9	way	way	NOUN
cana-1860	107	10	to	to	PART
cana-1860	107	11	balance	balance	VERB
cana-1860	107	12	the	the	DET
cana-1860	107	13	trade	trade	NOUN
cana-1860	107	14	-	-	PUNCT
cana-1860	107	15	off	off	NOUN
cana-1860	107	16	between	between	ADP
cana-1860	107	17	exploration	exploration	NOUN
cana-1860	107	18	and	and	CCONJ
cana-1860	107	19	exploitation	exploitation	NOUN
cana-1860	107	20	.	.	PUNCT
cana-1860	108	1	the	the	DET
cana-1860	108	2	objective	objective	ADJ
cana-1860	108	3	function	function	NOUN
cana-1860	108	4	of	of	ADP
cana-1860	108	5	ppo	ppo	PROPN
cana-1860	108	6	is	be	AUX
cana-1860	108	7	presented	present	VERB
cana-1860	108	8	via	via	ADP
cana-1860	108	9	equation	equation	NOUN
cana-1860	108	10	9	9	NUM
cana-1860	108	11	,	,	PUNCT
cana-1860	108	12	𝐿𝑃𝑃𝑂(𝜃	𝐿𝑃𝑃𝑂(𝜃	NOUN
cana-1860	108	13	)	)	PUNCT
cana-1860	109	1	=	=	SYM
cana-1860	109	2	𝐸’𝑡[𝑚𝑖	𝐸’𝑡[𝑚𝑖	NOUN
cana-1860	109	3	𝑛(𝑟𝑡(𝜃)𝐴’𝑡	𝑛(𝑟𝑡(𝜃)𝐴’𝑡	PROPN
cana-1860	109	4	,	,	PUNCT
cana-1860	109	5	𝑐𝑙𝑖𝑝(𝑟𝑡(𝜃	𝑐𝑙𝑖𝑝(𝑟𝑡(𝜃	PROPN
cana-1860	109	6	)	)	PUNCT
cana-1860	109	7	,	,	PUNCT
cana-1860	109	8	1	1	NUM
cana-1860	109	9	−	−	PROPN
cana-1860	109	10	𝜖	𝜖	PROPN
cana-1860	109	11	,	,	PUNCT
cana-1860	109	12	1	1	NUM
cana-1860	109	13	+	+	NUM
cana-1860	109	14	𝜖)𝐴’𝑡	𝜖)𝐴’𝑡	NOUN
cana-1860	109	15	)	)	PUNCT
cana-1860	109	16	]	]	PUNCT
cana-1860	109	17	…	…	PUNCT
cana-1860	109	18	(	(	PUNCT
cana-1860	109	19	9	9	NUM
cana-1860	109	20	)	)	PUNCT
cana-1860	109	21	where	where	SCONJ
cana-1860	109	22	,	,	PUNCT
cana-1860	109	23	is	be	AUX
cana-1860	109	24	represented	represent	VERB
cana-1860	109	25	via	via	ADP
cana-1860	109	26	equation	equation	NOUN
cana-1860	109	27	10	10	NUM
cana-1860	109	28	,	,	PUNCT
cana-1860	109	29	𝑟𝑡(𝜃	𝑟𝑡(𝜃	NUM
cana-1860	109	30	)	)	PUNCT
cana-1860	109	31	=	=	SYM
cana-1860	109	32	𝜋𝜃	𝜋𝜃	PROPN
cana-1860	109	33	(	(	PUNCT
cana-1860	109	34	𝑎𝑡	𝑎𝑡	PROPN
cana-1860	109	35	∣	∣	PROPN
cana-1860	109	36	𝑠𝑡	𝑠𝑡	PROPN
cana-1860	109	37	)	)	PUNCT
cana-1860	109	38	𝜋𝜃𝑜𝑙𝑑	𝜋𝜃𝑜𝑙𝑑	PROPN
cana-1860	109	39	(	(	PUNCT
cana-1860	109	40	𝑎𝑡	𝑎𝑡	DET
cana-1860	109	41	∣	∣	PROPN
cana-1860	109	42	𝑠𝑡	𝑠𝑡	PROPN
cana-1860	109	43	)	)	PUNCT
cana-1860	109	44	…	…	PUNCT
cana-1860	109	45	(	(	PUNCT
cana-1860	109	46	10	10	NUM
cana-1860	109	47	)	)	PUNCT
cana-1860	109	48	which	which	PRON
cana-1860	109	49	represents	represent	VERB
cana-1860	109	50	the	the	DET
cana-1860	109	51	probability	probability	NOUN
cana-1860	109	52	ratio	ratio	NOUN
cana-1860	109	53	between	between	ADP
cana-1860	109	54	the	the	DET
cana-1860	109	55	current	current	ADJ
cana-1860	109	56	and	and	CCONJ
cana-1860	109	57	old	old	ADJ
cana-1860	109	58	policies	policy	NOUN
cana-1860	109	59	,	,	PUNCT
cana-1860	109	60	a't	a't	NOUN
cana-1860	109	61	is	be	AUX
cana-1860	109	62	the	the	DET
cana-1860	109	63	advantage	advantage	NOUN
cana-1860	109	64	estimate	estimate	NOUN
cana-1860	109	65	,	,	PUNCT
cana-1860	109	66	and	and	CCONJ
cana-1860	109	67	ϵ	ϵ	X
cana-1860	109	68	is	be	AUX
cana-1860	109	69	a	a	DET
cana-1860	109	70	hyperparameter	hyperparameter	NOUN
cana-1860	109	71	that	that	PRON
cana-1860	109	72	controls	control	VERB
cana-1860	109	73	the	the	DET
cana-1860	109	74	clipping	clip	VERB
cana-1860	109	75	range	range	NOUN
cana-1860	109	76	for	for	ADP
cana-1860	109	77	stable	stable	ADJ
cana-1860	109	78	updates	update	NOUN
cana-1860	109	79	.	.	PUNCT
cana-1860	110	1	therefore	therefore	ADV
cana-1860	110	2	,	,	PUNCT
cana-1860	110	3	the	the	DET
cana-1860	110	4	model	model	NOUN
cana-1860	110	5	will	will	AUX
cana-1860	110	6	automatically	automatically	ADV
cana-1860	110	7	change	change	VERB
cana-1860	110	8	its	its	PRON
cana-1860	110	9	parameters	parameter	NOUN
cana-1860	110	10	with	with	ADP
cana-1860	110	11	dynamic	dynamic	ADJ
cana-1860	110	12	updating	updating	NOUN
cana-1860	110	13	to	to	PART
cana-1860	110	14	improve	improve	VERB
cana-1860	110	15	the	the	DET
cana-1860	110	16	prediction	prediction	NOUN
cana-1860	110	17	over	over	ADP
cana-1860	110	18	changing	change	VERB
cana-1860	110	19	environments	environment	NOUN
cana-1860	110	20	.	.	PUNCT
cana-1860	111	1	finally	finally	ADV
cana-1860	111	2	,	,	PUNCT
cana-1860	111	3	noise	noise	NOUN
cana-1860	111	4	in	in	ADP
cana-1860	111	5	the	the	DET
cana-1860	111	6	data	data	NOUN
cana-1860	111	7	is	be	AUX
cana-1860	111	8	reduced	reduce	VERB
cana-1860	111	9	by	by	ADP
cana-1860	111	10	the	the	DET
cana-1860	111	11	kf	kf	PROPN
cana-1860	111	12	-	-	PUNCT
cana-1860	111	13	bnn	bnn	PROPN
cana-1860	111	14	,	,	PUNCT
cana-1860	111	15	and	and	CCONJ
cana-1860	111	16	there	there	PRON
cana-1860	111	17	is	be	VERB
cana-1860	111	18	uncertainty	uncertainty	NOUN
cana-1860	111	19	estimation	estimation	NOUN
cana-1860	111	20	of	of	ADP
cana-1860	111	21	the	the	DET
cana-1860	111	22	prediction	prediction	NOUN
cana-1860	111	23	.	.	PUNCT
cana-1860	112	1	the	the	DET
cana-1860	112	2	updated	update	VERB
cana-1860	112	3	state	state	NOUN
cana-1860	112	4	estimates	estimate	NOUN
cana-1860	112	5	\\	\\	NOUN
cana-1860	112	6	(	(	PUNCT
cana-1860	112	7	x^t	x^t	PROPN
cana-1860	112	8	\\	\\	PROPN
cana-1860	112	9	)	)	PUNCT
cana-1860	112	10	and	and	CCONJ
cana-1860	112	11	covariance	covariance	NOUN
cana-1860	112	12	pt	pt	NOUN
cana-1860	112	13	are	be	AUX
cana-1860	112	14	given	give	VERB
cana-1860	112	15	using	use	VERB
cana-1860	112	16	the	the	DET
cana-1860	112	17	kalman	kalman	NOUN
cana-1860	112	18	filter	filter	NOUN
cana-1860	112	19	via	via	ADP
cana-1860	112	20	equations	equation	NOUN
cana-1860	112	21	11	11	NUM
cana-1860	112	22	&	&	CCONJ
cana-1860	112	23	12	12	NUM
cana-1860	112	24	,	,	PUNCT
cana-1860	112	25	as	as	SCONJ
cana-1860	112	26	follows	follow	VERB
cana-1860	112	27	:	:	PUNCT
cana-1860	112	28	𝑥’𝑡	𝑥’𝑡	PROPN
cana-1860	112	29	=	=	PUNCT
cana-1860	112	30	𝐴𝑥’(𝑡	𝐴𝑥’(𝑡	NOUN
cana-1860	113	1	−	−	PROPN
cana-1860	113	2	1	1	NUM
cana-1860	113	3	)	)	PUNCT
cana-1860	113	4	+	+	CCONJ
cana-1860	113	5	𝐵𝑢(𝑡	𝐵𝑢(𝑡	NOUN
cana-1860	113	6	)	)	PUNCT
cana-1860	113	7	…	…	PUNCT
cana-1860	113	8	(	(	PUNCT
cana-1860	113	9	11	11	X
cana-1860	113	10	)	)	PUNCT
cana-1860	113	11	𝑃𝑡	𝑃𝑡	PROPN
cana-1860	113	12	=	=	PUNCT
cana-1860	113	13	𝐴𝑃(𝑡	𝐴𝑃(𝑡	NOUN
cana-1860	113	14	−	−	NOUN
cana-1860	113	15	1	1	X
cana-1860	113	16	)	)	PUNCT
cana-1860	113	17	∗	∗	NOUN
cana-1860	113	18	𝐴𝑇	𝐴𝑇	PROPN
cana-1860	113	19	+	+	CCONJ
cana-1860	113	20	𝑄	𝑄	PROPN
cana-1860	113	21	…	…	PUNCT
cana-1860	113	22	(12	(12	NUM
cana-1860	113	23	)	)	PUNCT
cana-1860	113	24	the	the	DET
cana-1860	113	25	bayesian	bayesian	ADJ
cana-1860	113	26	neural	neural	ADJ
cana-1860	113	27	network	network	NOUN
cana-1860	113	28	then	then	ADV
cana-1860	113	29	processes	process	VERB
cana-1860	113	30	the	the	DET
cana-1860	113	31	filtered	filter	VERB
cana-1860	113	32	estimates	estimate	NOUN
cana-1860	113	33	,	,	PUNCT
cana-1860	113	34	producing	produce	VERB
cana-1860	113	35	a	a	DET
cana-1860	113	36	distribution	distribution	NOUN
cana-1860	113	37	of	of	ADP
cana-1860	113	38	possible	possible	ADJ
cana-1860	113	39	outcomes	outcome	NOUN
cana-1860	113	40	p(y’∣d	p(y’∣d	NOUN
cana-1860	113	41	)	)	PUNCT
cana-1860	113	42	based	base	VERB
cana-1860	113	43	on	on	ADP
cana-1860	113	44	the	the	DET
cana-1860	113	45	posterior	posterior	ADJ
cana-1860	113	46	probability	probability	NOUN
cana-1860	113	47	represented	represent	VERB
cana-1860	113	48	via	via	ADP
cana-1860	113	49	equation	equation	NOUN
cana-1860	113	50	13	13	NUM
cana-1860	113	51	,	,	PUNCT
cana-1860	113	52	𝑃	𝑃	NOUN
cana-1860	113	53	(	(	PUNCT
cana-1860	113	54	𝑦	𝑦	NOUN
cana-1860	113	55	’	'	PUNCT
cana-1860	113	56	∣∣	∣∣	PROPN
cana-1860	113	57	𝐷	𝐷	PROPN
cana-1860	113	58	)	)	PUNCT
cana-1860	113	59	=	=	SYM
cana-1860	114	1	∫	∫	PROPN
cana-1860	114	2	𝑃	𝑃	PROPN
cana-1860	114	3	(	(	PUNCT
cana-1860	114	4	𝑦	𝑦	NOUN
cana-1860	114	5	’	'	PUNCT
cana-1860	114	6	∣∣	∣∣	NUM
cana-1860	114	7	𝜃	𝜃	X
cana-1860	114	8	)	)	PUNCT
cana-1860	114	9	𝑃	𝑃	PROPN
cana-1860	114	10	(	(	PUNCT
cana-1860	114	11	𝜃	𝜃	NUM
cana-1860	114	12	∣	∣	ADJ
cana-1860	114	13	𝐷	𝐷	NOUN
cana-1860	114	14	)	)	PUNCT
cana-1860	114	15	𝑑𝜃	𝑑𝜃	ADP
cana-1860	114	16	…	…	PUNCT
cana-1860	114	17	(	(	PUNCT
cana-1860	114	18	13	13	NUM
cana-1860	114	19	)	)	PUNCT
cana-1860	114	20	the	the	DET
cana-1860	114	21	model	model	NOUN
cana-1860	114	22	can	can	AUX
cana-1860	114	23	therefore	therefore	ADV
cana-1860	114	24	quantify	quantify	VERB
cana-1860	114	25	the	the	DET
cana-1860	114	26	uncertainty	uncertainty	NOUN
cana-1860	114	27	in	in	ADP
cana-1860	114	28	its	its	PRON
cana-1860	114	29	predictions	prediction	NOUN
cana-1860	114	30	within	within	ADP
cana-1860	114	31	this	this	DET
cana-1860	114	32	probabilistic	probabilistic	ADJ
cana-1860	114	33	framework	framework	NOUN
cana-1860	114	34	and	and	CCONJ
cana-1860	114	35	hence	hence	ADV
cana-1860	114	36	make	make	VERB
cana-1860	114	37	the	the	DET
cana-1860	114	38	output	output	NOUN
cana-1860	114	39	more	more	ADV
cana-1860	114	40	reliable	reliable	ADJ
cana-1860	114	41	,	,	PUNCT
cana-1860	114	42	especially	especially	ADV
cana-1860	114	43	under	under	ADP
cana-1860	114	44	noisy	noisy	ADJ
cana-1860	114	45	conditions	condition	NOUN
cana-1860	114	46	.	.	PUNCT
cana-1860	115	1	in	in	ADP
cana-1860	115	2	summary	summary	NOUN
cana-1860	115	3	,	,	PUNCT
cana-1860	115	4	the	the	DET
cana-1860	115	5	model	model	NOUN
cana-1860	115	6	proposed	propose	VERB
cana-1860	115	7	in	in	ADP
cana-1860	115	8	this	this	DET
cana-1860	115	9	paper	paper	NOUN
cana-1860	115	10	leverages	leverage	VERB
cana-1860	115	11	the	the	DET
cana-1860	115	12	complementary	complementary	ADJ
cana-1860	115	13	strengths	strength	NOUN
cana-1860	115	14	of	of	ADP
cana-1860	115	15	xgboost	xgboost	PROPN
cana-1860	115	16	,	,	PUNCT
cana-1860	115	17	lstm	lstm	PROPN
cana-1860	115	18	,	,	PUNCT
cana-1860	115	19	cnn	cnn	PROPN
cana-1860	115	20	,	,	PUNCT
cana-1860	115	21	and	and	CCONJ
cana-1860	115	22	ppo	ppo	PROPN
cana-1860	115	23	to	to	PART
cana-1860	115	24	efficiently	efficiently	ADV
cana-1860	115	25	handle	handle	VERB
cana-1860	115	26	multiple	multiple	ADJ
cana-1860	115	27	modal	modal	ADJ
cana-1860	115	28	data	datum	NOUN
cana-1860	115	29	sample	sample	NOUN
cana-1860	115	30	.	.	PUNCT
cana-1860	116	1	these	these	DET
cana-1860	116	2	six	six	NUM
cana-1860	116	3	equations	equation	NOUN
cana-1860	116	4	reveal	reveal	VERB
cana-1860	116	5	a	a	DET
cana-1860	116	6	more	more	ADV
cana-1860	116	7	involved	involved	ADJ
cana-1860	116	8	combination	combination	NOUN
cana-1860	116	9	of	of	ADP
cana-1860	116	10	feature	feature	NOUN
cana-1860	116	11	importance	importance	NOUN
cana-1860	116	12	,	,	PUNCT
cana-1860	116	13	temporal	temporal	ADJ
cana-1860	116	14	dependencies	dependency	NOUN
cana-1860	116	15	,	,	PUNCT
cana-1860	116	16	spatial	spatial	ADJ
cana-1860	116	17	patterns	pattern	NOUN
cana-1860	116	18	,	,	PUNCT
cana-1860	116	19	real	real	ADJ
cana-1860	116	20	-	-	PUNCT
cana-1860	116	21	time	time	NOUN
cana-1860	116	22	adaptability	adaptability	NOUN
cana-1860	116	23	,	,	PUNCT
cana-1860	116	24	and	and	CCONJ
cana-1860	116	25	uncertainty	uncertainty	NOUN
cana-1860	116	26	quantification	quantification	NOUN
cana-1860	116	27	,	,	PUNCT
cana-1860	116	28	whereby	whereby	SCONJ
cana-1860	116	29	the	the	DET
cana-1860	116	30	features	feature	NOUN
cana-1860	116	31	described	describe	VERB
cana-1860	116	32	have	have	AUX
cana-1860	116	33	been	be	AUX
cana-1860	116	34	robustly	robustly	ADV
cana-1860	116	35	and	and	CCONJ
cana-1860	116	36	flexibly	flexibly	ADV
cana-1860	116	37	endowed	endow	VERB
cana-1860	116	38	with	with	ADP
cana-1860	116	39	the	the	DET
cana-1860	116	40	model	model	NOUN
cana-1860	116	41	in	in	ADP
cana-1860	116	42	complex	complex	ADJ
cana-1860	116	43	,	,	PUNCT
cana-1860	116	44	dynamic	dynamic	ADJ
cana-1860	116	45	data	datum	NOUN
cana-1860	116	46	conditions	condition	NOUN
cana-1860	116	47	.	.	PUNCT
cana-1860	117	1	4	4	X
cana-1860	117	2	.	.	X
cana-1860	117	3	comparative	comparative	ADJ
cana-1860	117	4	result	result	NOUN
cana-1860	117	5	analysis	analysis	NOUN
cana-1860	117	6	experimental	experimental	ADJ
cana-1860	117	7	setup	setup	NOUN
cana-1860	117	8	:	:	PUNCT
cana-1860	117	9	experimental	experimental	ADJ
cana-1860	117	10	setup	setup	NOUN
cana-1860	117	11	designed	design	VERB
cana-1860	117	12	to	to	PART
cana-1860	117	13	analyze	analyze	VERB
cana-1860	117	14	the	the	DET
cana-1860	117	15	performance	performance	NOUN
cana-1860	117	16	of	of	ADP
cana-1860	117	17	the	the	DET
cana-1860	117	18	proposed	propose	VERB
cana-1860	117	19	hybrid	hybrid	ADJ
cana-1860	117	20	xgboost	xgboost	X
cana-1860	117	21	-	-	PUNCT
cana-1860	117	22	lstm	lstm	ADJ
cana-1860	117	23	-	-	PUNCT
cana-1860	117	24	cnn	cnn	PROPN
cana-1860	117	25	model	model	NOUN
cana-1860	117	26	with	with	ADP
cana-1860	117	27	proximal	proximal	ADJ
cana-1860	117	28	policy	policy	NOUN
cana-1860	117	29	optimization	optimization	NOUN
cana-1860	117	30	in	in	ADP
cana-1860	117	31	execution	execution	NOUN
cana-1860	117	32	on	on	ADP
cana-1860	117	33	several	several	ADJ
cana-1860	117	34	multimodal	multimodal	NOUN
cana-1860	117	35	datasets	dataset	NOUN
cana-1860	117	36	comprising	comprise	VERB
cana-1860	117	37	time	time	NOUN
cana-1860	117	38	-	-	PUNCT
cana-1860	117	39	series	series	NOUN
cana-1860	117	40	,	,	PUNCT
cana-1860	117	41	spatial	spatial	ADJ
cana-1860	117	42	,	,	PUNCT
cana-1860	117	43	and	and	CCONJ
cana-1860	117	44	tabular	tabular	VERB
cana-1860	117	45	data	data	NOUN
cana-1860	117	46	samples	sample	NOUN
cana-1860	117	47	.	.	PUNCT
cana-1860	118	1	we	we	PRON
cana-1860	118	2	evaluate	evaluate	VERB
cana-1860	118	3	the	the	DET
cana-1860	118	4	model	model	NOUN
cana-1860	118	5	's	's	PART
cana-1860	118	6	robustness	robustness	NOUN
cana-1860	118	7	in	in	ADP
cana-1860	118	8	prediction	prediction	NOUN
cana-1860	118	9	with	with	ADP
cana-1860	118	10	four	four	NUM
cana-1860	118	11	datasets	dataset	NOUN
cana-1860	118	12	from	from	ADP
cana-1860	118	13	heterogeneous	heterogeneous	ADJ
cana-1860	118	14	domains	domain	NOUN
cana-1860	118	15	:	:	PUNCT
cana-1860	118	16	sensor	sensor	NOUN
cana-1860	118	17	data	datum	NOUN
cana-1860	118	18	,	,	PUNCT
cana-1860	118	19	financial	financial	ADJ
cana-1860	118	20	time	time	NOUN
cana-1860	118	21	-	-	PUNCT
cana-1860	118	22	series	series	NOUN
cana-1860	118	23	,	,	PUNCT
cana-1860	118	24	medical	medical	ADJ
cana-1860	118	25	data	datum	NOUN
cana-1860	118	26	,	,	PUNCT
cana-1860	118	27	and	and	CCONJ
cana-1860	118	28	image	image	NOUN
cana-1860	118	29	-	-	PUNCT
cana-1860	118	30	based	base	VERB
cana-1860	118	31	spatial	spatial	ADJ
cana-1860	118	32	datasets	dataset	NOUN
cana-1860	118	33	&	&	CCONJ
cana-1860	118	34	samples	sample	NOUN
cana-1860	118	35	.	.	PUNCT
cana-1860	119	1	the	the	DET
cana-1860	119	2	features	feature	NOUN
cana-1860	119	3	that	that	PRON
cana-1860	119	4	need	need	VERB
cana-1860	119	5	to	to	PART
cana-1860	119	6	be	be	AUX
cana-1860	119	7	extracted	extract	VERB
cana-1860	119	8	define	define	ADJ
cana-1860	119	9	communications	communication	NOUN
cana-1860	119	10	on	on	ADP
cana-1860	119	11	applied	apply	VERB
cana-1860	119	12	nonlinear	nonlinear	ADJ
cana-1860	119	13	analysis	analysis	NOUN
cana-1860	119	14	issn	issn	NOUN
cana-1860	119	15	:	:	PUNCT
cana-1860	119	16	1074	1074	NUM
cana-1860	119	17	-	-	PUNCT
cana-1860	119	18	133x	133x	NUM
cana-1860	119	19	vol	vol	NOUN
cana-1860	119	20	32	32	NUM
cana-1860	119	21	no	no	NOUN
cana-1860	119	22	.	.	NOUN
cana-1860	119	23	2	2	NUM
cana-1860	119	24	(	(	PUNCT
cana-1860	119	25	2025	2025	NUM
cana-1860	119	26	)	)	PUNCT
cana-1860	119	27	672	672	NUM
cana-1860	119	28	https://internationalpubls.com	https://internationalpubls.com	X
cana-1860	119	29	the	the	DET
cana-1860	119	30	way	way	NOUN
cana-1860	119	31	in	in	ADP
cana-1860	119	32	which	which	PRON
cana-1860	119	33	the	the	DET
cana-1860	119	34	different	different	ADJ
cana-1860	119	35	datasets	dataset	NOUN
cana-1860	119	36	are	be	AUX
cana-1860	119	37	preprocessed	preprocesse	VERB
cana-1860	119	38	:	:	PUNCT
cana-1860	119	39	sequential	sequential	ADJ
cana-1860	119	40	dependencies	dependency	NOUN
cana-1860	119	41	,	,	PUNCT
cana-1860	119	42	temporal	temporal	ADJ
cana-1860	119	43	trends	trend	NOUN
cana-1860	119	44	,	,	PUNCT
cana-1860	119	45	and	and	CCONJ
cana-1860	119	46	spatial	spatial	ADJ
cana-1860	119	47	information	information	NOUN
cana-1860	119	48	sets	set	NOUN
cana-1860	119	49	.	.	PUNCT
cana-1860	120	1	each	each	DET
cana-1860	120	2	dataset	dataset	NOUN
cana-1860	120	3	was	be	AUX
cana-1860	120	4	divided	divide	VERB
cana-1860	120	5	into	into	ADP
cana-1860	120	6	training	training	NOUN
cana-1860	120	7	,	,	PUNCT
cana-1860	120	8	validation	validation	NOUN
cana-1860	120	9	,	,	PUNCT
cana-1860	120	10	and	and	CCONJ
cana-1860	120	11	test	test	NOUN
cana-1860	120	12	sets	set	NOUN
cana-1860	120	13	,	,	PUNCT
cana-1860	120	14	respectively	respectively	ADV
cana-1860	120	15	,	,	PUNCT
cana-1860	120	16	using	use	VERB
cana-1860	120	17	a	a	DET
cana-1860	120	18	70/15/15	70/15/15	PROPN
cana-1860	120	19	segregation	segregation	NOUN
cana-1860	120	20	in	in	ADP
cana-1860	120	21	process	process	NOUN
cana-1860	120	22	.	.	PUNCT
cana-1860	121	1	the	the	DET
cana-1860	121	2	results	result	NOUN
cana-1860	121	3	of	of	ADP
cana-1860	121	4	the	the	DET
cana-1860	121	5	proposed	propose	VERB
cana-1860	121	6	model	model	NOUN
cana-1860	121	7	are	be	AUX
cana-1860	121	8	compared	compare	VERB
cana-1860	121	9	with	with	ADP
cana-1860	121	10	the	the	DET
cana-1860	121	11	three	three	NUM
cana-1860	121	12	other	other	ADJ
cana-1860	121	13	established	establish	VERB
cana-1860	121	14	ones	one	NOUN
cana-1860	121	15	:	:	PUNCT
cana-1860	122	1	[	[	X
cana-1860	122	2	5	5	NUM
cana-1860	122	3	]	]	PUNCT
cana-1860	122	4	,	,	PUNCT
cana-1860	122	5	[	[	X
cana-1860	122	6	8	8	NUM
cana-1860	122	7	]	]	PUNCT
cana-1860	122	8	,	,	PUNCT
cana-1860	122	9	and	and	CCONJ
cana-1860	122	10	[	[	X
cana-1860	122	11	14	14	NUM
cana-1860	122	12	]	]	PUNCT
cana-1860	122	13	,	,	PUNCT
cana-1860	122	14	which	which	PRON
cana-1860	122	15	include	include	VERB
cana-1860	122	16	state	state	NOUN
cana-1860	122	17	-	-	PUNCT
cana-1860	122	18	of	of	ADP
cana-1860	122	19	-	-	PUNCT
cana-1860	122	20	the	the	DET
cana-1860	122	21	-	-	PUNCT
cana-1860	122	22	art	art	NOUN
cana-1860	122	23	deep	deep	ADJ
cana-1860	122	24	learning	learning	NOUN
cana-1860	122	25	and	and	CCONJ
cana-1860	122	26	hybrid	hybrid	ADJ
cana-1860	122	27	methods	method	NOUN
cana-1860	122	28	for	for	ADP
cana-1860	122	29	multimodal	multimodal	NOUN
cana-1860	122	30	data	datum	NOUN
cana-1860	122	31	fusion	fusion	NOUN
cana-1860	122	32	and/or	and/or	CCONJ
cana-1860	122	33	time	time	NOUN
cana-1860	122	34	-	-	PUNCT
cana-1860	122	35	series	series	NOUN
cana-1860	122	36	forecasting	forecasting	NOUN
cana-1860	122	37	tasks	task	NOUN
cana-1860	122	38	.	.	PUNCT
cana-1860	123	1	the	the	DET
cana-1860	123	2	four	four	NUM
cana-1860	123	3	evaluation	evaluation	NOUN
cana-1860	123	4	metrics	metric	NOUN
cana-1860	123	5	-	-	PUNCT
cana-1860	123	6	precision	precision	NOUN
cana-1860	123	7	,	,	PUNCT
cana-1860	123	8	accuracy	accuracy	NOUN
cana-1860	123	9	,	,	PUNCT
cana-1860	123	10	recall	recall	NOUN
cana-1860	123	11	,	,	PUNCT
cana-1860	123	12	and	and	CCONJ
cana-1860	123	13	mean	mean	VERB
cana-1860	123	14	absolute	absolute	ADJ
cana-1860	123	15	error	error	NOUN
cana-1860	123	16	-	-	PUNCT
cana-1860	123	17	offered	offer	VERB
cana-1860	123	18	the	the	DET
cana-1860	123	19	best	good	ADJ
cana-1860	123	20	insight	insight	NOUN
cana-1860	123	21	into	into	ADP
cana-1860	123	22	the	the	DET
cana-1860	123	23	predictive	predictive	ADJ
cana-1860	123	24	performance	performance	NOUN
cana-1860	123	25	and	and	CCONJ
cana-1860	123	26	the	the	DET
cana-1860	123	27	model	model	NOUN
cana-1860	123	28	's	's	PART
cana-1860	123	29	capacity	capacity	NOUN
cana-1860	123	30	for	for	ADP
cana-1860	123	31	handling	handle	VERB
cana-1860	123	32	multimodal	multimodal	ADJ
cana-1860	123	33	data	datum	NOUN
cana-1860	123	34	with	with	ADP
cana-1860	123	35	good	good	ADJ
cana-1860	123	36	efficiency	efficiency	NOUN
cana-1860	123	37	.	.	PUNCT
cana-1860	124	1	results	result	NOUN
cana-1860	124	2	will	will	AUX
cana-1860	124	3	be	be	AUX
cana-1860	124	4	provided	provide	VERB
cana-1860	124	5	in	in	ADP
cana-1860	124	6	six	six	NUM
cana-1860	124	7	tables	table	NOUN
cana-1860	124	8	,	,	PUNCT
cana-1860	124	9	with	with	ADP
cana-1860	124	10	thorough	thorough	ADJ
cana-1860	124	11	comparisons	comparison	NOUN
cana-1860	124	12	between	between	ADP
cana-1860	124	13	the	the	DET
cana-1860	124	14	proposed	propose	VERB
cana-1860	124	15	model	model	NOUN
cana-1860	124	16	and	and	CCONJ
cana-1860	124	17	methods	method	NOUN
cana-1860	124	18	[	[	X
cana-1860	124	19	5	5	NUM
cana-1860	124	20	]	]	PUNCT
cana-1860	124	21	,	,	PUNCT
cana-1860	124	22	[	[	X
cana-1860	124	23	8	8	NUM
cana-1860	124	24	]	]	PUNCT
cana-1860	124	25	,	,	PUNCT
cana-1860	124	26	and	and	CCONJ
cana-1860	124	27	[	[	X
cana-1860	124	28	14	14	NUM
cana-1860	124	29	]	]	PUNCT
cana-1860	124	30	.	.	PUNCT
cana-1860	125	1	table	table	NOUN
cana-1860	125	2	1	1	NUM
cana-1860	125	3	:	:	PUNCT
cana-1860	125	4	comparison	comparison	NOUN
cana-1860	125	5	on	on	ADP
cana-1860	125	6	sensor	sensor	NOUN
cana-1860	125	7	dataset	dataset	NOUN
cana-1860	125	8	method	method	NOUN
cana-1860	125	9	precision	precision	NOUN
cana-1860	125	10	(	(	PUNCT
cana-1860	125	11	%	%	INTJ
cana-1860	125	12	)	)	PUNCT
cana-1860	125	13	accuracy	accuracy	NOUN
cana-1860	125	14	(	(	PUNCT
cana-1860	125	15	%	%	INTJ
cana-1860	125	16	)	)	PUNCT
cana-1860	125	17	recall	recall	NOUN
cana-1860	125	18	(	(	PUNCT
cana-1860	125	19	%	%	NOUN
cana-1860	125	20	)	)	PUNCT
cana-1860	125	21	mae	mae	PROPN
cana-1860	125	22	proposed	propose	VERB
cana-1860	125	23	model	model	NOUN
cana-1860	125	24	96.1	96.1	NUM
cana-1860	125	25	97.0	97.0	NUM
cana-1860	125	26	95.7	95.7	NUM
cana-1860	125	27	0.070	0.070	NUM
cana-1860	125	28	method	method	NOUN
cana-1860	126	1	[	[	X
cana-1860	126	2	5	5	NUM
cana-1860	126	3	]	]	SYM
cana-1860	126	4	93.0	93.0	NUM
cana-1860	126	5	95.2	95.2	NUM
cana-1860	126	6	92.5	92.5	NUM
cana-1860	126	7	0.090	0.090	NUM
cana-1860	126	8	method	method	NOUN
cana-1860	126	9	[	[	X
cana-1860	126	10	8	8	NUM
cana-1860	126	11	]	]	SYM
cana-1860	126	12	92.8	92.8	NUM
cana-1860	126	13	94.8	94.8	NUM
cana-1860	126	14	92.0	92.0	NUM
cana-1860	126	15	0.095	0.095	NUM
cana-1860	126	16	method	method	NOUN
cana-1860	126	17	[	[	X
cana-1860	126	18	14	14	NUM
cana-1860	126	19	]	]	SYM
cana-1860	126	20	91.5	91.5	NUM
cana-1860	126	21	93.7	93.7	NUM
cana-1860	126	22	90.2	90.2	NUM
cana-1860	126	23	0.102	0.102	NUM
cana-1860	126	24	figure	figure	NOUN
cana-1860	126	25	2	2	NUM
cana-1860	126	26	.	.	PUNCT
cana-1860	126	27	comparison	comparison	NOUN
cana-1860	126	28	on	on	ADP
cana-1860	126	29	sensor	sensor	NOUN
cana-1860	126	30	dataset	dataset	NOUN
cana-1860	126	31	samples	sample	NOUN
cana-1860	126	32	the	the	DET
cana-1860	126	33	results	result	NOUN
cana-1860	126	34	in	in	ADP
cana-1860	126	35	figure	figure	NOUN
cana-1860	126	36	2	2	NUM
cana-1860	126	37	of	of	ADP
cana-1860	126	38	the	the	DET
cana-1860	126	39	proposed	propose	VERB
cana-1860	126	40	model	model	NOUN
cana-1860	126	41	outperform	outperform	VERB
cana-1860	126	42	all	all	DET
cana-1860	126	43	other	other	ADJ
cana-1860	126	44	metrics	metric	NOUN
cana-1860	126	45	in	in	ADP
cana-1860	126	46	the	the	DET
cana-1860	126	47	sensor	sensor	NOUN
cana-1860	126	48	dataset	dataset	NOUN
cana-1860	126	49	,	,	PUNCT
cana-1860	126	50	with	with	ADP
cana-1860	126	51	an	an	DET
cana-1860	126	52	accuracy	accuracy	NOUN
cana-1860	126	53	of	of	ADP
cana-1860	126	54	96.1	96.1	NUM
cana-1860	126	55	%	%	NOUN
cana-1860	126	56	,	,	PUNCT
cana-1860	126	57	while	while	SCONJ
cana-1860	126	58	bringing	bring	VERB
cana-1860	126	59	mae	mae	PROPN
cana-1860	126	60	down	down	ADP
cana-1860	126	61	to	to	ADP
cana-1860	126	62	0.070	0.070	NUM
cana-1860	126	63	.	.	PUNCT
cana-1860	127	1	it	it	PRON
cana-1860	127	2	improves	improve	VERB
cana-1860	127	3	the	the	DET
cana-1860	127	4	accuracy	accuracy	NOUN
cana-1860	127	5	of	of	ADP
cana-1860	127	6	method	method	NOUN
cana-1860	127	7	[	[	X
cana-1860	127	8	5	5	NUM
cana-1860	127	9	]	]	PUNCT
cana-1860	127	10	by	by	ADP
cana-1860	127	11	1.8	1.8	NUM
cana-1860	127	12	%	%	NOUN
cana-1860	127	13	and	and	CCONJ
cana-1860	127	14	for	for	SCONJ
cana-1860	127	15	mae	mae	PROPN
cana-1860	127	16	reduces	reduce	VERB
cana-1860	127	17	by	by	ADP
cana-1860	127	18	22	22	NUM
cana-1860	127	19	%	%	NOUN
cana-1860	127	20	.	.	PUNCT
cana-1860	128	1	quite	quite	ADV
cana-1860	128	2	behind	behind	ADV
cana-1860	128	3	,	,	PUNCT
cana-1860	128	4	the	the	DET
cana-1860	128	5	method	method	NOUN
cana-1860	128	6	in	in	ADP
cana-1860	128	7	[	[	X
cana-1860	128	8	14	14	NUM
cana-1860	128	9	]	]	PUNCT
cana-1860	128	10	,	,	PUNCT
cana-1860	128	11	for	for	ADP
cana-1860	128	12	instance	instance	NOUN
cana-1860	128	13	,	,	PUNCT
cana-1860	128	14	has	have	VERB
cana-1860	128	15	an	an	DET
cana-1860	128	16	mae	mae	PROPN
cana-1860	128	17	of	of	ADP
cana-1860	128	18	0.102	0.102	NUM
cana-1860	128	19	,	,	PUNCT
cana-1860	128	20	which	which	PRON
cana-1860	128	21	further	far	ADV
cana-1860	128	22	illustrated	illustrate	VERB
cana-1860	128	23	the	the	DET
cana-1860	128	24	combined	combine	VERB
cana-1860	128	25	use	use	NOUN
cana-1860	128	26	of	of	ADP
cana-1860	128	27	xgboost	xgboost	NOUN
cana-1860	128	28	and	and	CCONJ
cana-1860	128	29	lstm	lstm	NOUN
cana-1860	128	30	in	in	ADP
cana-1860	128	31	noise	noise	NOUN
cana-1860	128	32	reduction	reduction	NOUN
cana-1860	128	33	towards	towards	ADP
cana-1860	128	34	making	make	VERB
cana-1860	128	35	better	well	ADJ
cana-1860	128	36	predictions	prediction	NOUN
cana-1860	128	37	.	.	PUNCT
cana-1860	129	1	table	table	NOUN
cana-1860	129	2	2	2	NUM
cana-1860	129	3	:	:	PUNCT
cana-1860	129	4	comparison	comparison	NOUN
cana-1860	129	5	on	on	ADP
cana-1860	129	6	financial	financial	ADJ
cana-1860	129	7	time	time	NOUN
cana-1860	129	8	-	-	PUNCT
cana-1860	129	9	series	series	NOUN
cana-1860	129	10	dataset	dataset	NOUN
cana-1860	129	11	method	method	NOUN
cana-1860	129	12	precision	precision	NOUN
cana-1860	129	13	(	(	PUNCT
cana-1860	129	14	%	%	INTJ
cana-1860	129	15	)	)	PUNCT
cana-1860	129	16	accuracy	accuracy	NOUN
cana-1860	129	17	(	(	PUNCT
cana-1860	129	18	%	%	INTJ
cana-1860	129	19	)	)	PUNCT
cana-1860	129	20	recall	recall	NOUN
cana-1860	129	21	(	(	PUNCT
cana-1860	129	22	%	%	NOUN
cana-1860	129	23	)	)	PUNCT
cana-1860	130	1	mae	mae	PROPN
cana-1860	130	2	proposed	propose	VERB
cana-1860	130	3	model	model	NOUN
cana-1860	130	4	95.3	95.3	NUM
cana-1860	130	5	96.8	96.8	NUM
cana-1860	130	6	95.0	95.0	NUM
cana-1860	130	7	0.073	0.073	NUM
cana-1860	130	8	method	method	NOUN
cana-1860	130	9	[	[	X
cana-1860	130	10	5	5	NUM
cana-1860	130	11	]	]	SYM
cana-1860	130	12	93.7	93.7	NUM
cana-1860	130	13	95.3	95.3	NUM
cana-1860	130	14	93.2	93.2	NUM
cana-1860	130	15	0.085	0.085	NUM
cana-1860	130	16	method	method	NOUN
cana-1860	130	17	[	[	X
cana-1860	130	18	8	8	NUM
cana-1860	130	19	]	]	SYM
cana-1860	130	20	92.9	92.9	NUM
cana-1860	130	21	94.5	94.5	NUM
cana-1860	130	22	92.4	92.4	NUM
cana-1860	130	23	0.090	0.090	NUM
cana-1860	130	24	method	method	NOUN
cana-1860	130	25	[	[	X
cana-1860	130	26	14	14	NUM
cana-1860	130	27	]	]	SYM
cana-1860	130	28	91.2	91.2	NUM
cana-1860	130	29	93.9	93.9	NUM
cana-1860	130	30	91.0	91.0	NUM
cana-1860	130	31	0.098	0.098	NUM
cana-1860	130	32	communications	communication	NOUN
cana-1860	130	33	on	on	ADP
cana-1860	130	34	applied	apply	VERB
cana-1860	130	35	nonlinear	nonlinear	ADJ
cana-1860	130	36	analysis	analysis	NOUN
cana-1860	130	37	issn	issn	NOUN
cana-1860	130	38	:	:	PUNCT
cana-1860	130	39	1074	1074	NUM
cana-1860	130	40	-	-	PUNCT
cana-1860	130	41	133x	133x	NUM
cana-1860	130	42	vol	vol	NOUN
cana-1860	130	43	32	32	NUM
cana-1860	130	44	no	no	NOUN
cana-1860	130	45	.	.	NOUN
cana-1860	130	46	2	2	NUM
cana-1860	130	47	(	(	PUNCT
cana-1860	130	48	2025	2025	NUM
cana-1860	130	49	)	)	PUNCT
cana-1860	131	1	673	673	NUM
cana-1860	131	2	https://internationalpubls.com	https://internationalpubls.com	X
cana-1860	131	3	the	the	DET
cana-1860	131	4	result	result	NOUN
cana-1860	131	5	of	of	ADP
cana-1860	131	6	the	the	DET
cana-1860	131	7	proposed	propose	VERB
cana-1860	131	8	model	model	NOUN
cana-1860	131	9	outperforms	outperform	VERB
cana-1860	131	10	the	the	DET
cana-1860	131	11	other	other	ADJ
cana-1860	131	12	methods	method	NOUN
cana-1860	131	13	,	,	PUNCT
cana-1860	131	14	especially	especially	ADV
cana-1860	131	15	for	for	ADP
cana-1860	131	16	the	the	DET
cana-1860	131	17	mae	mae	PROPN
cana-1860	131	18	with	with	ADP
cana-1860	131	19	a	a	DET
cana-1860	131	20	value	value	NOUN
cana-1860	131	21	of	of	ADP
cana-1860	131	22	0.073	0.073	NUM
cana-1860	131	23	,	,	PUNCT
cana-1860	131	24	against	against	ADP
cana-1860	131	25	the	the	DET
cana-1860	131	26	best	good	ADJ
cana-1860	131	27	results	result	NOUN
cana-1860	131	28	of	of	ADP
cana-1860	131	29	the	the	DET
cana-1860	131	30	methods	method	NOUN
cana-1860	131	31	in	in	ADP
cana-1860	131	32	[	[	X
cana-1860	131	33	5	5	NUM
cana-1860	131	34	]	]	PUNCT
cana-1860	131	35	and	and	CCONJ
cana-1860	131	36	[	[	X
cana-1860	131	37	8	8	NUM
cana-1860	131	38	]	]	PUNCT
cana-1860	131	39	with	with	ADP
cana-1860	131	40	0.085	0.085	NUM
cana-1860	131	41	and	and	CCONJ
cana-1860	131	42	0.090	0.090	NUM
cana-1860	131	43	values	value	NOUN
cana-1860	131	44	,	,	PUNCT
cana-1860	131	45	correspondingly	correspondingly	ADV
cana-1860	131	46	.	.	PUNCT
cana-1860	132	1	high	high	ADJ
cana-1860	132	2	precision	precision	NOUN
cana-1860	132	3	and	and	CCONJ
cana-1860	132	4	recall	recall	NOUN
cana-1860	132	5	indicate	indicate	VERB
cana-1860	132	6	much	much	ADV
cana-1860	132	7	higher	high	ADJ
cana-1860	132	8	temporal	temporal	ADJ
cana-1860	132	9	dependency	dependency	NOUN
cana-1860	132	10	rate	rate	NOUN
cana-1860	132	11	,	,	PUNCT
cana-1860	132	12	captured	capture	VERB
cana-1860	132	13	by	by	ADP
cana-1860	132	14	this	this	DET
cana-1860	132	15	model	model	NOUN
cana-1860	132	16	,	,	PUNCT
cana-1860	132	17	comparing	compare	VERB
cana-1860	132	18	to	to	ADP
cana-1860	132	19	all	all	DET
cana-1860	132	20	other	other	ADJ
cana-1860	132	21	works	work	NOUN
cana-1860	132	22	,	,	PUNCT
cana-1860	132	23	having	have	VERB
cana-1860	132	24	very	very	ADV
cana-1860	132	25	important	important	ADJ
cana-1860	132	26	meaning	meaning	NOUN
cana-1860	132	27	for	for	ADP
cana-1860	132	28	financial	financial	ADJ
cana-1860	132	29	forecasting	forecasting	NOUN
cana-1860	132	30	tasks	task	NOUN
cana-1860	132	31	.	.	PUNCT
cana-1860	133	1	figure	figure	NOUN
cana-1860	133	2	3	3	NUM
cana-1860	133	3	.	.	NOUN
cana-1860	133	4	comparison	comparison	NOUN
cana-1860	133	5	on	on	ADP
cana-1860	133	6	mimic	mimic	ADJ
cana-1860	133	7	-	-	PUNCT
cana-1860	133	8	iii	iii	NOUN
cana-1860	133	9	healthcare	healthcare	NOUN
cana-1860	133	10	dataset	dataset	NOUN
cana-1860	133	11	samples	sample	NOUN
cana-1860	133	12	table	table	NOUN
cana-1860	133	13	3	3	NUM
cana-1860	133	14	:	:	PUNCT
cana-1860	133	15	comparison	comparison	NOUN
cana-1860	133	16	on	on	ADP
cana-1860	133	17	mimic	mimic	ADJ
cana-1860	133	18	-	-	PUNCT
cana-1860	133	19	iii	iii	NOUN
cana-1860	133	20	healthcare	healthcare	NOUN
cana-1860	133	21	dataset	dataset	NOUN
cana-1860	133	22	method	method	NOUN
cana-1860	133	23	precision	precision	NOUN
cana-1860	133	24	(	(	PUNCT
cana-1860	133	25	%	%	INTJ
cana-1860	133	26	)	)	PUNCT
cana-1860	133	27	accuracy	accuracy	NOUN
cana-1860	133	28	(	(	PUNCT
cana-1860	133	29	%	%	INTJ
cana-1860	133	30	)	)	PUNCT
cana-1860	133	31	recall	recall	NOUN
cana-1860	133	32	(	(	PUNCT
cana-1860	133	33	%	%	NOUN
cana-1860	133	34	)	)	PUNCT
cana-1860	134	1	mae	mae	PROPN
cana-1860	134	2	proposed	propose	VERB
cana-1860	134	3	model	model	NOUN
cana-1860	134	4	95.8	95.8	NUM
cana-1860	134	5	97.1	97.1	NUM
cana-1860	134	6	95.2	95.2	NUM
cana-1860	134	7	0.074	0.074	NUM
cana-1860	134	8	method	method	NOUN
cana-1860	134	9	[	[	X
cana-1860	134	10	5	5	NUM
cana-1860	134	11	]	]	SYM
cana-1860	134	12	94.0	94.0	NUM
cana-1860	134	13	95.5	95.5	NUM
cana-1860	134	14	93.7	93.7	NUM
cana-1860	134	15	0.085	0.085	NUM
cana-1860	134	16	method	method	NOUN
cana-1860	134	17	[	[	X
cana-1860	134	18	8	8	NUM
cana-1860	134	19	]	]	SYM
cana-1860	134	20	93.2	93.2	NUM
cana-1860	134	21	95.0	95.0	NUM
cana-1860	134	22	92.5	92.5	NUM
cana-1860	134	23	0.089	0.089	NUM
cana-1860	134	24	method	method	NOUN
cana-1860	134	25	[	[	X
cana-1860	134	26	14	14	NUM
cana-1860	134	27	]	]	PUNCT
cana-1860	134	28	92.0	92.0	NUM
cana-1860	134	29	94.3	94.3	NUM
cana-1860	134	30	91.8	91.8	NUM
cana-1860	134	31	0.095	0.095	NUM
cana-1860	134	32	the	the	DET
cana-1860	134	33	performance	performance	NOUN
cana-1860	134	34	of	of	ADP
cana-1860	134	35	the	the	DET
cana-1860	134	36	proposed	propose	VERB
cana-1860	134	37	model	model	NOUN
cana-1860	134	38	using	use	VERB
cana-1860	134	39	the	the	DET
cana-1860	134	40	mimic	mimic	ADJ
cana-1860	134	41	-	-	PUNCT
cana-1860	134	42	iii	iii	NOUN
cana-1860	134	43	dataset	dataset	NOUN
cana-1860	134	44	on	on	ADP
cana-1860	134	45	patient	patient	ADJ
cana-1860	134	46	time	time	NOUN
cana-1860	134	47	-	-	PUNCT
cana-1860	134	48	series	series	NOUN
cana-1860	134	49	data	datum	NOUN
cana-1860	134	50	indicates	indicate	VERB
cana-1860	134	51	high	high	ADJ
cana-1860	134	52	accuracy	accuracy	NOUN
cana-1860	134	53	at	at	ADP
cana-1860	134	54	97.1	97.1	NUM
cana-1860	134	55	%	%	NOUN
cana-1860	134	56	,	,	PUNCT
cana-1860	134	57	mae	mae	PROPN
cana-1860	134	58	reduced	reduce	VERB
cana-1860	134	59	by	by	ADP
cana-1860	134	60	about	about	ADV
cana-1860	134	61	13	13	NUM
cana-1860	134	62	%	%	NOUN
cana-1860	134	63	compared	compare	VERB
cana-1860	134	64	to	to	PART
cana-1860	134	65	method	method	VERB
cana-1860	134	66	[	[	X
cana-1860	134	67	5	5	NUM
cana-1860	134	68	]	]	PUNCT
cana-1860	134	69	.	.	PUNCT
cana-1860	135	1	in	in	ADP
cana-1860	135	2	the	the	DET
cana-1860	135	3	proposed	propose	VERB
cana-1860	135	4	model	model	NOUN
cana-1860	135	5	,	,	PUNCT
cana-1860	135	6	the	the	DET
cana-1860	135	7	use	use	NOUN
cana-1860	135	8	of	of	ADP
cana-1860	135	9	bayesian	bayesian	NOUN
cana-1860	135	10	neural	neural	ADJ
cana-1860	135	11	networks	network	NOUN
cana-1860	135	12	and	and	CCONJ
cana-1860	135	13	kalman	kalman	NOUN
cana-1860	135	14	filtering	filtering	NOUN
cana-1860	135	15	helps	help	VERB
cana-1860	135	16	reduce	reduce	VERB
cana-1860	135	17	noise	noise	NOUN
cana-1860	135	18	from	from	ADP
cana-1860	135	19	healthcare	healthcare	PROPN
cana-1860	135	20	sensor	sensor	NOUN
cana-1860	135	21	data	datum	NOUN
cana-1860	135	22	;	;	PUNCT
cana-1860	135	23	hence	hence	ADV
cana-1860	135	24	,	,	PUNCT
cana-1860	135	25	reliable	reliable	ADJ
cana-1860	135	26	predictions	prediction	NOUN
cana-1860	135	27	are	be	AUX
cana-1860	135	28	achieved	achieve	VERB
cana-1860	135	29	in	in	ADP
cana-1860	135	30	the	the	DET
cana-1860	135	31	process	process	NOUN
cana-1860	135	32	.	.	PUNCT
cana-1860	136	1	table	table	NOUN
cana-1860	136	2	4	4	NUM
cana-1860	136	3	:	:	PUNCT
cana-1860	136	4	comparison	comparison	NOUN
cana-1860	136	5	on	on	ADP
cana-1860	136	6	image	image	NOUN
cana-1860	136	7	-	-	PUNCT
cana-1860	136	8	spatial	spatial	ADJ
cana-1860	136	9	dataset	dataset	NOUN
cana-1860	136	10	method	method	NOUN
cana-1860	136	11	precision	precision	NOUN
cana-1860	136	12	(	(	PUNCT
cana-1860	136	13	%	%	INTJ
cana-1860	136	14	)	)	PUNCT
cana-1860	136	15	accuracy	accuracy	NOUN
cana-1860	136	16	(	(	PUNCT
cana-1860	136	17	%	%	INTJ
cana-1860	136	18	)	)	PUNCT
cana-1860	136	19	recall	recall	NOUN
cana-1860	136	20	(	(	PUNCT
cana-1860	136	21	%	%	NOUN
cana-1860	136	22	)	)	PUNCT
cana-1860	137	1	mae	mae	PROPN
cana-1860	137	2	proposed	propose	VERB
cana-1860	137	3	model	model	NOUN
cana-1860	137	4	94.6	94.6	NUM
cana-1860	137	5	96.2	96.2	NUM
cana-1860	137	6	94.0	94.0	NUM
cana-1860	137	7	0.078	0.078	NUM
cana-1860	137	8	method	method	NOUN
cana-1860	137	9	[	[	X
cana-1860	137	10	5	5	NUM
cana-1860	137	11	]	]	SYM
cana-1860	137	12	92.5	92.5	NUM
cana-1860	137	13	94.5	94.5	NUM
cana-1860	137	14	92.0	92.0	NUM
cana-1860	137	15	0.091	0.091	NUM
cana-1860	137	16	method	method	NOUN
cana-1860	137	17	[	[	X
cana-1860	137	18	8	8	NUM
cana-1860	137	19	]	]	SYM
cana-1860	137	20	91.8	91.8	NUM
cana-1860	137	21	94.0	94.0	NUM
cana-1860	137	22	91.2	91.2	NUM
cana-1860	137	23	0.093	0.093	NUM
cana-1860	137	24	method	method	NOUN
cana-1860	137	25	[	[	X
cana-1860	137	26	14	14	NUM
cana-1860	137	27	]	]	SYM
cana-1860	137	28	90.9	90.9	NUM
cana-1860	137	29	93.5	93.5	NUM
cana-1860	137	30	90.0	90.0	NUM
cana-1860	137	31	0.100	0.100	NUM
cana-1860	137	32	having	having	AUX
cana-1860	137	33	considered	consider	VERB
cana-1860	137	34	the	the	DET
cana-1860	137	35	precision	precision	NOUN
cana-1860	137	36	,	,	PUNCT
cana-1860	137	37	on	on	ADP
cana-1860	137	38	spatial	spatial	ADJ
cana-1860	137	39	data	datum	NOUN
cana-1860	137	40	tasks	task	NOUN
cana-1860	137	41	like	like	ADP
cana-1860	137	42	image	image	NOUN
cana-1860	137	43	processing	processing	NOUN
cana-1860	137	44	,	,	PUNCT
cana-1860	137	45	the	the	DET
cana-1860	137	46	proposed	propose	VERB
cana-1860	137	47	model	model	NOUN
cana-1860	137	48	achieved	achieve	VERB
cana-1860	137	49	a	a	DET
cana-1860	137	50	precision	precision	NOUN
cana-1860	137	51	value	value	NOUN
cana-1860	137	52	of	of	ADP
cana-1860	137	53	94.6	94.6	NUM
cana-1860	137	54	%	%	NOUN
cana-1860	137	55	with	with	ADP
cana-1860	137	56	an	an	DET
cana-1860	137	57	mae	mae	PROPN
cana-1860	137	58	of	of	ADP
cana-1860	137	59	0.078	0.078	NUM
cana-1860	137	60	,	,	PUNCT
cana-1860	137	61	outperforming	outperforming	NOUN
cana-1860	137	62	method	method	NOUN
cana-1860	137	63	[	[	X
cana-1860	137	64	5	5	NUM
cana-1860	137	65	]	]	PUNCT
cana-1860	137	66	by	by	ADP
cana-1860	137	67	14	14	NUM
cana-1860	137	68	%	%	NOUN
cana-1860	137	69	error	error	NOUN
cana-1860	137	70	reduction	reduction	NOUN
cana-1860	137	71	.	.	PUNCT
cana-1860	138	1	this	this	PRON
cana-1860	138	2	was	be	AUX
cana-1860	138	3	contributed	contribute	VERB
cana-1860	138	4	by	by	ADP
cana-1860	138	5	the	the	DET
cana-1860	138	6	capability	capability	NOUN
cana-1860	138	7	of	of	ADP
cana-1860	138	8	the	the	DET
cana-1860	138	9	cnn	cnn	PROPN
cana-1860	138	10	component	component	NOUN
cana-1860	138	11	in	in	ADP
cana-1860	138	12	capturing	capture	VERB
cana-1860	138	13	the	the	DET
cana-1860	138	14	features	feature	NOUN
cana-1860	138	15	on	on	ADP
cana-1860	138	16	a	a	DET
cana-1860	138	17	spatial	spatial	ADJ
cana-1860	138	18	context	context	NOUN
cana-1860	138	19	while	while	SCONJ
cana-1860	138	20	the	the	DET
cana-1860	138	21	hybrid	hybrid	ADJ
cana-1860	138	22	fusion	fusion	NOUN
cana-1860	138	23	of	of	ADP
cana-1860	138	24	xgboost	xgboost	PROPN
cana-1860	138	25	,	,	PUNCT
cana-1860	138	26	lstm	lstm	ADJ
cana-1860	138	27	,	,	PUNCT
cana-1860	138	28	and	and	CCONJ
cana-1860	138	29	cnn	cnn	PROPN
cana-1860	138	30	made	make	VERB
cana-1860	138	31	the	the	DET
cana-1860	138	32	proposed	propose	VERB
cana-1860	138	33	model	model	NOUN
cana-1860	138	34	highly	highly	ADV
cana-1860	138	35	effective	effective	ADJ
cana-1860	138	36	for	for	ADP
cana-1860	138	37	the	the	DET
cana-1860	138	38	process	process	NOUN
cana-1860	138	39	.	.	PUNCT
cana-1860	139	1	communications	communication	NOUN
cana-1860	139	2	on	on	ADP
cana-1860	139	3	applied	apply	VERB
cana-1860	139	4	nonlinear	nonlinear	ADJ
cana-1860	139	5	analysis	analysis	NOUN
cana-1860	139	6	issn	issn	NOUN
cana-1860	139	7	:	:	PUNCT
cana-1860	139	8	1074	1074	NUM
cana-1860	139	9	-	-	PUNCT
cana-1860	139	10	133x	133x	NUM
cana-1860	139	11	vol	vol	NOUN
cana-1860	139	12	32	32	NUM
cana-1860	139	13	no	no	NOUN
cana-1860	139	14	.	.	NOUN
cana-1860	139	15	2	2	NUM
cana-1860	139	16	(	(	PUNCT
cana-1860	139	17	2025	2025	NUM
cana-1860	139	18	)	)	PUNCT
cana-1860	139	19	674	674	NUM
cana-1860	139	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1860	139	21	table	table	NOUN
cana-1860	139	22	5	5	NUM
cana-1860	139	23	:	:	PUNCT
cana-1860	139	24	real	real	ADJ
cana-1860	139	25	-	-	PUNCT
cana-1860	139	26	time	time	NOUN
cana-1860	139	27	adaptation	adaptation	NOUN
cana-1860	139	28	with	with	ADP
cana-1860	139	29	ppo	ppo	PROPN
cana-1860	139	30	on	on	ADP
cana-1860	139	31	sensor	sensor	NOUN
cana-1860	139	32	dataset	dataset	NOUN
cana-1860	139	33	method	method	NOUN
cana-1860	139	34	precision	precision	NOUN
cana-1860	139	35	(	(	PUNCT
cana-1860	139	36	%	%	INTJ
cana-1860	139	37	)	)	PUNCT
cana-1860	139	38	accuracy	accuracy	NOUN
cana-1860	139	39	(	(	PUNCT
cana-1860	139	40	%	%	INTJ
cana-1860	139	41	)	)	PUNCT
cana-1860	139	42	recall	recall	NOUN
cana-1860	139	43	(	(	PUNCT
cana-1860	139	44	%	%	NOUN
cana-1860	139	45	)	)	PUNCT
cana-1860	140	1	mae	mae	PROPN
cana-1860	140	2	proposed	propose	VERB
cana-1860	140	3	model	model	NOUN
cana-1860	140	4	(	(	PUNCT
cana-1860	140	5	with	with	ADP
cana-1860	140	6	ppo	ppo	PROPN
cana-1860	140	7	)	)	PUNCT
cana-1860	140	8	96.5	96.5	NUM
cana-1860	140	9	97.6	97.6	NUM
cana-1860	140	10	96.1	96.1	NUM
cana-1860	140	11	0.072	0.072	NUM
cana-1860	140	12	proposed	propose	VERB
cana-1860	140	13	model	model	NOUN
cana-1860	140	14	(	(	PUNCT
cana-1860	140	15	without	without	ADP
cana-1860	140	16	ppo	ppo	PROPN
cana-1860	140	17	)	)	PUNCT
cana-1860	140	18	96.1	96.1	NUM
cana-1860	140	19	97.0	97.0	NUM
cana-1860	140	20	95.7	95.7	NUM
cana-1860	140	21	0.070	0.070	NUM
cana-1860	140	22	method	method	NOUN
cana-1860	140	23	[	[	X
cana-1860	140	24	5	5	NUM
cana-1860	140	25	]	]	SYM
cana-1860	140	26	93.0	93.0	NUM
cana-1860	140	27	95.2	95.2	NUM
cana-1860	140	28	92.5	92.5	NUM
cana-1860	140	29	0.090	0.090	NUM
cana-1860	140	30	method	method	NOUN
cana-1860	140	31	[	[	X
cana-1860	140	32	8	8	NUM
cana-1860	140	33	]	]	SYM
cana-1860	140	34	92.8	92.8	NUM
cana-1860	140	35	94.8	94.8	NUM
cana-1860	140	36	92.0	92.0	NUM
cana-1860	140	37	0.095	0.095	NUM
cana-1860	140	38	the	the	DET
cana-1860	140	39	proposed	propose	VERB
cana-1860	140	40	model	model	NOUN
cana-1860	140	41	with	with	ADP
cana-1860	140	42	the	the	DET
cana-1860	140	43	turned	turn	VERB
cana-1860	140	44	-	-	PUNCT
cana-1860	140	45	on	on	ADP
cana-1860	140	46	ppo	ppo	PROPN
cana-1860	140	47	has	have	VERB
cana-1860	140	48	some	some	DET
cana-1860	140	49	improvements	improvement	NOUN
cana-1860	140	50	on	on	ADP
cana-1860	140	51	precision	precision	NOUN
cana-1860	140	52	,	,	PUNCT
cana-1860	140	53	accuracy	accuracy	NOUN
cana-1860	140	54	,	,	PUNCT
cana-1860	140	55	and	and	CCONJ
cana-1860	140	56	recall	recall	NOUN
cana-1860	140	57	,	,	PUNCT
cana-1860	140	58	and	and	CCONJ
cana-1860	140	59	the	the	DET
cana-1860	140	60	mae	mae	PROPN
cana-1860	140	61	gets	get	AUX
cana-1860	140	62	reduced	reduce	VERB
cana-1860	140	63	compared	compare	VERB
cana-1860	140	64	to	to	ADP
cana-1860	140	65	the	the	DET
cana-1860	140	66	no	no	PRON
cana-1860	140	67	-	-	PUNCT
cana-1860	140	68	ppo	ppo	PROPN
cana-1860	140	69	settings	setting	NOUN
cana-1860	140	70	.	.	PUNCT
cana-1860	141	1	the	the	DET
cana-1860	141	2	presence	presence	NOUN
cana-1860	141	3	of	of	ADP
cana-1860	141	4	ppo	ppo	PROPN
cana-1860	141	5	is	be	AUX
cana-1860	141	6	underlined	underline	VERB
cana-1860	141	7	,	,	PUNCT
cana-1860	141	8	which	which	PRON
cana-1860	141	9	means	mean	VERB
cana-1860	141	10	that	that	SCONJ
cana-1860	141	11	in	in	ADP
cana-1860	141	12	a	a	DET
cana-1860	141	13	dynamic	dynamic	ADJ
cana-1860	141	14	environment	environment	NOUN
cana-1860	141	15	,	,	PUNCT
cana-1860	141	16	things	thing	NOUN
cana-1860	141	17	need	need	VERB
cana-1860	141	18	real	real	ADJ
cana-1860	141	19	-	-	PUNCT
cana-1860	141	20	time	time	NOUN
cana-1860	141	21	adjustments	adjustment	NOUN
cana-1860	141	22	towards	towards	ADP
cana-1860	141	23	a	a	DET
cana-1860	141	24	best	good	ADJ
cana-1860	141	25	performance	performance	NOUN
cana-1860	141	26	in	in	ADP
cana-1860	141	27	different	different	ADJ
cana-1860	141	28	scenarios	scenario	NOUN
cana-1860	141	29	.	.	PUNCT
cana-1860	142	1	table	table	NOUN
cana-1860	142	2	6	6	NUM
cana-1860	142	3	:	:	PUNCT
cana-1860	142	4	federated	federated	ADJ
cana-1860	142	5	learning	learn	VERB
cana-1860	142	6	comparison	comparison	NOUN
cana-1860	142	7	on	on	ADP
cana-1860	142	8	distributed	distribute	VERB
cana-1860	142	9	healthcare	healthcare	NOUN
cana-1860	142	10	dataset	dataset	NOUN
cana-1860	142	11	method	method	NOUN
cana-1860	142	12	precision	precision	NOUN
cana-1860	142	13	(	(	PUNCT
cana-1860	142	14	%	%	INTJ
cana-1860	142	15	)	)	PUNCT
cana-1860	142	16	accuracy	accuracy	NOUN
cana-1860	142	17	(	(	PUNCT
cana-1860	142	18	%	%	INTJ
cana-1860	142	19	)	)	PUNCT
cana-1860	142	20	recall	recall	NOUN
cana-1860	142	21	(	(	PUNCT
cana-1860	142	22	%	%	NOUN
cana-1860	142	23	)	)	PUNCT
cana-1860	142	24	mae	mae	PROPN
cana-1860	142	25	proposed	propose	VERB
cana-1860	142	26	model	model	NOUN
cana-1860	142	27	(	(	PUNCT
cana-1860	142	28	with	with	ADP
cana-1860	142	29	federated	federated	ADJ
cana-1860	142	30	learning	learning	NOUN
cana-1860	142	31	)	)	PUNCT
cana-1860	142	32	94.9	94.9	NUM
cana-1860	142	33	96.5	96.5	NUM
cana-1860	142	34	94.5	94.5	NUM
cana-1860	142	35	0.082	0.082	NUM
cana-1860	142	36	proposed	propose	VERB
cana-1860	142	37	model	model	NOUN
cana-1860	142	38	(	(	PUNCT
cana-1860	142	39	without	without	ADP
cana-1860	142	40	federated	federated	ADJ
cana-1860	142	41	learning	learning	NOUN
cana-1860	142	42	)	)	PUNCT
cana-1860	142	43	94.6	94.6	NUM
cana-1860	142	44	96.2	96.2	NUM
cana-1860	142	45	94.0	94.0	NUM
cana-1860	142	46	0.084	0.084	NUM
cana-1860	142	47	method	method	NOUN
cana-1860	142	48	[	[	X
cana-1860	142	49	5	5	NUM
cana-1860	142	50	]	]	SYM
cana-1860	142	51	93.5	93.5	NUM
cana-1860	142	52	95.3	95.3	NUM
cana-1860	142	53	93.2	93.2	NUM
cana-1860	142	54	0.090	0.090	NUM
cana-1860	142	55	method	method	NOUN
cana-1860	142	56	[	[	X
cana-1860	142	57	8	8	NUM
cana-1860	142	58	]	]	SYM
cana-1860	142	59	92.9	92.9	NUM
cana-1860	142	60	94.5	94.5	NUM
cana-1860	142	61	92.4	92.4	NUM
cana-1860	142	62	0.092	0.092	NUM
cana-1860	142	63	federated	federated	ADJ
cana-1860	142	64	learning	learning	NOUN
cana-1860	142	65	proves	prove	VERB
cana-1860	142	66	useful	useful	ADJ
cana-1860	142	67	in	in	ADP
cana-1860	142	68	distributed	distribute	VERB
cana-1860	142	69	environments	environment	NOUN
cana-1860	142	70	,	,	PUNCT
cana-1860	142	71	such	such	ADJ
cana-1860	142	72	as	as	ADP
cana-1860	142	73	in	in	ADP
cana-1860	142	74	healthcare	healthcare	NOUN
cana-1860	142	75	systems	system	NOUN
cana-1860	142	76	when	when	SCONJ
cana-1860	142	77	data	datum	NOUN
cana-1860	142	78	privacy	privacy	NOUN
cana-1860	142	79	plays	play	VERB
cana-1860	142	80	a	a	DET
cana-1860	142	81	major	major	ADJ
cana-1860	142	82	role	role	NOUN
cana-1860	142	83	.	.	PUNCT
cana-1860	143	1	because	because	SCONJ
cana-1860	143	2	the	the	DET
cana-1860	143	3	local	local	ADJ
cana-1860	143	4	models	model	NOUN
cana-1860	143	5	contribute	contribute	VERB
cana-1860	143	6	to	to	ADP
cana-1860	143	7	the	the	DET
cana-1860	143	8	much	much	ADV
cana-1860	143	9	more	more	ADV
cana-1860	143	10	generalized	generalized	ADJ
cana-1860	143	11	global	global	ADJ
cana-1860	143	12	model	model	NOUN
cana-1860	143	13	without	without	ADP
cana-1860	143	14	the	the	DET
cana-1860	143	15	loss	loss	NOUN
cana-1860	143	16	of	of	ADP
cana-1860	143	17	any	any	DET
cana-1860	143	18	sensitive	sensitive	ADJ
cana-1860	143	19	data	data	NOUN
cana-1860	143	20	samples	sample	NOUN
cana-1860	143	21	of	of	ADP
cana-1860	143	22	patients	patient	NOUN
cana-1860	143	23	,	,	PUNCT
cana-1860	143	24	the	the	DET
cana-1860	143	25	improvement	improvement	NOUN
cana-1860	143	26	in	in	ADP
cana-1860	143	27	the	the	DET
cana-1860	143	28	proposed	propose	VERB
cana-1860	143	29	model	model	NOUN
cana-1860	143	30	with	with	ADP
cana-1860	143	31	the	the	DET
cana-1860	143	32	help	help	NOUN
cana-1860	143	33	of	of	ADP
cana-1860	143	34	federated	federated	ADJ
cana-1860	143	35	learning	learning	NOUN
cana-1860	143	36	is	be	AUX
cana-1860	143	37	enhanced	enhance	VERB
cana-1860	143	38	by	by	ADP
cana-1860	143	39	0.3	0.3	NUM
cana-1860	143	40	%	%	NOUN
cana-1860	143	41	in	in	ADP
cana-1860	143	42	precision	precision	NOUN
cana-1860	143	43	and	and	CCONJ
cana-1860	143	44	reduced	reduce	VERB
cana-1860	143	45	mae	mae	PROPN
cana-1860	143	46	by	by	ADP
cana-1860	143	47	2	2	NUM
cana-1860	143	48	%	%	NOUN
cana-1860	143	49	.	.	PUNCT
cana-1860	144	1	these	these	DET
cana-1860	144	2	results	result	NOUN
cana-1860	144	3	establish	establish	VERB
cana-1860	144	4	the	the	DET
cana-1860	144	5	fact	fact	NOUN
cana-1860	144	6	that	that	SCONJ
cana-1860	144	7	the	the	DET
cana-1860	144	8	proposed	propose	VERB
cana-1860	144	9	xgboost	xgboost	ADJ
cana-1860	144	10	-	-	PUNCT
cana-1860	144	11	lstm	lstm	ADJ
cana-1860	144	12	-	-	PUNCT
cana-1860	144	13	cnn	cnn	PROPN
cana-1860	144	14	hybrid	hybrid	NOUN
cana-1860	144	15	model	model	NOUN
cana-1860	144	16	integrated	integrate	VERB
cana-1860	144	17	with	with	ADP
cana-1860	144	18	ppo	ppo	PROPN
cana-1860	144	19	,	,	PUNCT
cana-1860	144	20	kalman	kalman	PROPN
cana-1860	144	21	filter	filter	PROPN
cana-1860	144	22	-	-	PUNCT
cana-1860	144	23	enhanced	enhance	VERB
cana-1860	144	24	bayesian	bayesian	NOUN
cana-1860	144	25	neural	neural	ADJ
cana-1860	144	26	networks	network	NOUN
cana-1860	144	27	,	,	PUNCT
cana-1860	144	28	and	and	CCONJ
cana-1860	144	29	federated	federated	ADJ
cana-1860	144	30	learning	learning	NOUN
cana-1860	144	31	significantly	significantly	ADV
cana-1860	144	32	outperforms	outperform	VERB
cana-1860	144	33	existing	exist	VERB
cana-1860	144	34	methods	method	NOUN
cana-1860	144	35	on	on	ADP
cana-1860	144	36	a	a	DET
cana-1860	144	37	wide	wide	ADJ
cana-1860	144	38	range	range	NOUN
cana-1860	144	39	of	of	ADP
cana-1860	144	40	multimodal	multimodal	NOUN
cana-1860	144	41	datasets	dataset	NOUN
cana-1860	144	42	.	.	PUNCT
cana-1860	145	1	these	these	DET
cana-1860	145	2	improvements	improvement	NOUN
cana-1860	145	3	in	in	ADP
cana-1860	145	4	the	the	DET
cana-1860	145	5	values	value	NOUN
cana-1860	145	6	of	of	ADP
cana-1860	145	7	precision	precision	NOUN
cana-1860	145	8	,	,	PUNCT
cana-1860	145	9	accuracy	accuracy	NOUN
cana-1860	145	10	,	,	PUNCT
cana-1860	145	11	and	and	CCONJ
cana-1860	145	12	mae	mae	PROPN
cana-1860	145	13	for	for	ADP
cana-1860	145	14	various	various	ADJ
cana-1860	145	15	tasks	task	NOUN
cana-1860	145	16	prove	prove	VERB
cana-1860	145	17	the	the	DET
cana-1860	145	18	strength	strength	NOUN
cana-1860	145	19	of	of	ADP
cana-1860	145	20	the	the	DET
cana-1860	145	21	model	model	NOUN
cana-1860	145	22	in	in	ADP
cana-1860	145	23	terms	term	NOUN
cana-1860	145	24	of	of	ADP
cana-1860	145	25	versatility	versatility	NOUN
cana-1860	145	26	and	and	CCONJ
cana-1860	145	27	robustness	robustness	NOUN
cana-1860	145	28	.	.	PUNCT
cana-1860	146	1	5	5	X
cana-1860	146	2	.	.	X
cana-1860	146	3	conclusion	conclusion	NOUN
cana-1860	146	4	&	&	CCONJ
cana-1860	146	5	future	future	ADJ
cana-1860	146	6	scopes	scope	NOUN
cana-1860	146	7	such	such	DET
cana-1860	146	8	a	a	DET
cana-1860	146	9	hybrid	hybrid	ADJ
cana-1860	146	10	model	model	NOUN
cana-1860	146	11	will	will	AUX
cana-1860	146	12	be	be	AUX
cana-1860	146	13	able	able	ADJ
cana-1860	146	14	to	to	PART
cana-1860	146	15	handle	handle	VERB
cana-1860	146	16	this	this	DET
cana-1860	146	17	complex	complex	ADJ
cana-1860	146	18	,	,	PUNCT
cana-1860	146	19	multi	multi	ADJ
cana-1860	146	20	-	-	ADJ
cana-1860	146	21	modal	modal	ADJ
cana-1860	146	22	dataset	dataset	NOUN
cana-1860	146	23	much	much	ADV
cana-1860	146	24	better	well	ADV
cana-1860	146	25	.	.	PUNCT
cana-1860	147	1	the	the	DET
cana-1860	147	2	proposed	propose	VERB
cana-1860	147	3	xgboost	xgboost	ADJ
cana-1860	147	4	-	-	PUNCT
cana-1860	147	5	lstm	lstm	ADJ
cana-1860	147	6	-	-	PUNCT
cana-1860	147	7	cnn	cnn	PROPN
cana-1860	147	8	hybrid	hybrid	NOUN
cana-1860	147	9	model	model	NOUN
cana-1860	147	10	with	with	ADP
cana-1860	147	11	proximal	proximal	ADJ
cana-1860	147	12	policy	policy	NOUN
cana-1860	147	13	optimization	optimization	NOUN
cana-1860	147	14	makes	make	VERB
cana-1860	147	15	huge	huge	ADJ
cana-1860	147	16	gains	gain	NOUN
cana-1860	147	17	in	in	ADP
cana-1860	147	18	precision	precision	NOUN
cana-1860	147	19	,	,	PUNCT
cana-1860	147	20	accuracy	accuracy	NOUN
cana-1860	147	21	,	,	PUNCT
cana-1860	147	22	while	while	SCONJ
cana-1860	147	23	cutting	cut	VERB
cana-1860	147	24	down	down	ADP
cana-1860	147	25	error	error	NOUN
cana-1860	147	26	.	.	PUNCT
cana-1860	148	1	it	it	PRON
cana-1860	148	2	combines	combine	VERB
cana-1860	148	3	the	the	DET
cana-1860	148	4	robust	robust	ADJ
cana-1860	148	5	tabular	tabular	NOUN
cana-1860	148	6	data	datum	NOUN
cana-1860	148	7	handling	handling	NOUN
cana-1860	148	8	capability	capability	NOUN
cana-1860	148	9	of	of	ADP
cana-1860	148	10	xgboost	xgboost	ADV
cana-1860	148	11	with	with	ADP
cana-1860	148	12	the	the	DET
cana-1860	148	13	ability	ability	NOUN
cana-1860	148	14	of	of	ADP
cana-1860	148	15	lstm	lstm	NOUN
cana-1860	148	16	to	to	PART
cana-1860	148	17	model	model	VERB
cana-1860	148	18	long	long	ADJ
cana-1860	148	19	-	-	PUNCT
cana-1860	148	20	term	term	NOUN
cana-1860	148	21	temporal	temporal	ADJ
cana-1860	148	22	dependencies	dependency	NOUN
cana-1860	148	23	and	and	CCONJ
cana-1860	148	24	cnn	cnn	PROPN
cana-1860	148	25	spatial	spatial	ADJ
cana-1860	148	26	feature	feature	NOUN
cana-1860	148	27	extraction	extraction	NOUN
cana-1860	148	28	.	.	PUNCT
cana-1860	149	1	therefore	therefore	ADV
cana-1860	149	2	,	,	PUNCT
cana-1860	149	3	the	the	DET
cana-1860	149	4	proposed	propose	VERB
cana-1860	149	5	model	model	NOUN
cana-1860	149	6	mitigates	mitigate	VERB
cana-1860	149	7	major	major	ADJ
cana-1860	149	8	shortcomings	shortcoming	NOUN
cana-1860	149	9	of	of	ADP
cana-1860	149	10	a	a	DET
cana-1860	149	11	number	number	NOUN
cana-1860	149	12	of	of	ADP
cana-1860	149	13	prevailing	prevail	VERB
cana-1860	149	14	techniques	technique	NOUN
cana-1860	149	15	for	for	ADP
cana-1860	149	16	multimodal	multimodal	ADJ
cana-1860	149	17	fusion	fusion	NOUN
cana-1860	149	18	in	in	ADP
cana-1860	149	19	such	such	DET
cana-1860	149	20	a	a	DET
cana-1860	149	21	way	way	NOUN
cana-1860	149	22	.	.	PUNCT
cana-1860	150	1	this	this	DET
cana-1860	150	2	model	model	NOUN
cana-1860	150	3	is	be	AUX
cana-1860	150	4	more	more	ADV
cana-1860	150	5	adaptable	adaptable	ADJ
cana-1860	150	6	to	to	ADP
cana-1860	150	7	dynamic	dynamic	ADJ
cana-1860	150	8	environments	environment	NOUN
cana-1860	150	9	,	,	PUNCT
cana-1860	150	10	since	since	SCONJ
cana-1860	150	11	it	it	PRON
cana-1860	150	12	is	be	AUX
cana-1860	150	13	combined	combine	VERB
cana-1860	150	14	with	with	ADP
cana-1860	150	15	proximal	proximal	ADJ
cana-1860	150	16	policy	policy	NOUN
cana-1860	150	17	optimization	optimization	NOUN
cana-1860	150	18	where	where	SCONJ
cana-1860	150	19	real	real	ADJ
cana-1860	150	20	-	-	PUNCT
cana-1860	150	21	time	time	NOUN
cana-1860	150	22	model	model	NOUN
cana-1860	150	23	updates	update	NOUN
cana-1860	150	24	can	can	AUX
cana-1860	150	25	be	be	AUX
cana-1860	150	26	performed	perform	VERB
cana-1860	150	27	in	in	ADP
cana-1860	150	28	a	a	DET
cana-1860	150	29	continuous	continuous	ADJ
cana-1860	150	30	stream	stream	NOUN
cana-1860	150	31	of	of	ADP
cana-1860	150	32	changing	change	VERB
cana-1860	150	33	data	datum	NOUN
cana-1860	150	34	.	.	PUNCT
cana-1860	151	1	these	these	PRON
cana-1860	151	2	are	be	AUX
cana-1860	151	3	verified	verify	VERB
cana-1860	151	4	through	through	ADP
cana-1860	151	5	experimental	experimental	ADJ
cana-1860	151	6	communications	communication	NOUN
cana-1860	151	7	on	on	ADP
cana-1860	151	8	applied	apply	VERB
cana-1860	151	9	nonlinear	nonlinear	ADJ
cana-1860	151	10	analysis	analysis	NOUN
cana-1860	151	11	issn	issn	NOUN
cana-1860	151	12	:	:	PUNCT
cana-1860	151	13	1074	1074	NUM
cana-1860	151	14	-	-	PUNCT
cana-1860	151	15	133x	133x	NUM
cana-1860	151	16	vol	vol	NOUN
cana-1860	151	17	32	32	NUM
cana-1860	151	18	no	no	NOUN
cana-1860	151	19	.	.	NOUN
cana-1860	151	20	2	2	NUM
cana-1860	151	21	(	(	PUNCT
cana-1860	151	22	2025	2025	NUM
cana-1860	151	23	)	)	PUNCT
cana-1860	151	24	675	675	NUM
cana-1860	151	25	https://internationalpubls.com	https://internationalpubls.com	X
cana-1860	151	26	results	result	NOUN
cana-1860	151	27	on	on	ADP
cana-1860	151	28	various	various	ADJ
cana-1860	151	29	sensor	sensor	NOUN
cana-1860	151	30	,	,	PUNCT
cana-1860	151	31	financial	financial	ADJ
cana-1860	151	32	,	,	PUNCT
cana-1860	151	33	healthcare	healthcare	PROPN
cana-1860	151	34	,	,	PUNCT
cana-1860	151	35	and	and	CCONJ
cana-1860	151	36	image	image	NOUN
cana-1860	151	37	-	-	PUNCT
cana-1860	151	38	spatial	spatial	ADJ
cana-1860	151	39	datasets	dataset	NOUN
cana-1860	151	40	.	.	PUNCT
cana-1860	152	1	for	for	ADP
cana-1860	152	2	example	example	NOUN
cana-1860	152	3	,	,	PUNCT
cana-1860	152	4	the	the	DET
cana-1860	152	5	sensor	sensor	NOUN
cana-1860	152	6	dataset	dataset	VERB
cana-1860	152	7	tested	test	VERB
cana-1860	152	8	on	on	ADP
cana-1860	152	9	the	the	DET
cana-1860	152	10	proposed	propose	VERB
cana-1860	152	11	model	model	NOUN
cana-1860	152	12	had	have	VERB
cana-1860	152	13	an	an	DET
cana-1860	152	14	accuracy	accuracy	NOUN
cana-1860	152	15	of	of	ADP
cana-1860	152	16	97.0	97.0	NUM
cana-1860	152	17	%	%	NOUN
cana-1860	152	18	and	and	CCONJ
cana-1860	152	19	a	a	DET
cana-1860	152	20	mae	mae	PROPN
cana-1860	152	21	of	of	ADP
cana-1860	152	22	0.070	0.070	NUM
cana-1860	152	23	,	,	PUNCT
cana-1860	152	24	which	which	PRON
cana-1860	152	25	was	be	AUX
cana-1860	152	26	1.8	1.8	NUM
cana-1860	152	27	%	%	NOUN
cana-1860	152	28	better	well	ADV
cana-1860	152	29	in	in	ADP
cana-1860	152	30	terms	term	NOUN
cana-1860	152	31	of	of	ADP
cana-1860	152	32	accuracy	accuracy	NOUN
cana-1860	152	33	than	than	ADP
cana-1860	152	34	method	method	NOUN
cana-1860	152	35	[	[	X
cana-1860	152	36	5	5	NUM
cana-1860	152	37	]	]	PUNCT
cana-1860	152	38	with	with	ADP
cana-1860	152	39	a	a	DET
cana-1860	152	40	reduction	reduction	NOUN
cana-1860	152	41	in	in	ADP
cana-1860	152	42	mae	mae	PROPN
cana-1860	152	43	by	by	ADP
cana-1860	152	44	22	22	NUM
cana-1860	152	45	%	%	NOUN
cana-1860	152	46	.	.	PUNCT
cana-1860	153	1	in	in	ADP
cana-1860	153	2	the	the	DET
cana-1860	153	3	financial	financial	ADJ
cana-1860	153	4	timeseries	timeserie	NOUN
cana-1860	153	5	dataset	dataset	VERB
cana-1860	153	6	,	,	PUNCT
cana-1860	153	7	the	the	DET
cana-1860	153	8	model	model	NOUN
cana-1860	153	9	has	have	AUX
cana-1860	153	10	achieved	achieve	VERB
cana-1860	153	11	96.8	96.8	NUM
cana-1860	153	12	%	%	NOUN
cana-1860	153	13	accuracy	accuracy	NOUN
cana-1860	153	14	and	and	CCONJ
cana-1860	153	15	mae	mae	PROPN
cana-1860	153	16	0.073	0.073	NUM
cana-1860	153	17	,	,	PUNCT
cana-1860	153	18	which	which	PRON
cana-1860	153	19	shows	show	VERB
cana-1860	153	20	a	a	DET
cana-1860	153	21	major	major	ADJ
cana-1860	153	22	gain	gain	NOUN
cana-1860	153	23	over	over	ADP
cana-1860	153	24	methods	method	NOUN
cana-1860	153	25	[	[	X
cana-1860	153	26	8	8	NUM
cana-1860	153	27	]	]	PUNCT
cana-1860	153	28	and	and	CCONJ
cana-1860	153	29	[	[	X
cana-1860	153	30	14	14	NUM
cana-1860	153	31	]	]	PUNCT
cana-1860	153	32	.	.	PUNCT
cana-1860	154	1	the	the	DET
cana-1860	154	2	model	model	NOUN
cana-1860	154	3	provided	provide	VERB
cana-1860	154	4	uncertainty	uncertainty	NOUN
cana-1860	154	5	estimation	estimation	NOUN
cana-1860	154	6	along	along	ADP
cana-1860	154	7	with	with	ADP
cana-1860	154	8	noise	noise	NOUN
cana-1860	154	9	reduction	reduction	NOUN
cana-1860	154	10	,	,	PUNCT
cana-1860	154	11	incorporating	incorporate	VERB
cana-1860	154	12	kalman	kalman	NOUN
cana-1860	154	13	filter	filter	NOUN
cana-1860	154	14	-	-	PUNCT
cana-1860	154	15	enhanced	enhance	VERB
cana-1860	154	16	bayesian	bayesian	NOUN
cana-1860	154	17	neural	neural	ADJ
cana-1860	154	18	networks	network	NOUN
cana-1860	154	19	on	on	ADP
cana-1860	154	20	healthcare	healthcare	NOUN
cana-1860	154	21	applications	application	NOUN
cana-1860	154	22	.	.	PUNCT
cana-1860	155	1	it	it	PRON
cana-1860	155	2	achieved	achieve	VERB
cana-1860	155	3	an	an	DET
cana-1860	155	4	accuracy	accuracy	NOUN
cana-1860	155	5	of	of	ADP
cana-1860	155	6	97.1	97.1	NUM
cana-1860	155	7	%	%	NOUN
cana-1860	155	8	on	on	ADP
cana-1860	155	9	the	the	DET
cana-1860	155	10	mimic	mimic	ADJ
cana-1860	155	11	-	-	PUNCT
cana-1860	155	12	iii	iii	NOUN
cana-1860	155	13	dataset	dataset	NOUN
cana-1860	155	14	,	,	PUNCT
cana-1860	155	15	with	with	ADP
cana-1860	155	16	a	a	DET
cana-1860	155	17	13	13	NUM
cana-1860	155	18	%	%	NOUN
cana-1860	155	19	reduction	reduction	NOUN
cana-1860	155	20	in	in	ADP
cana-1860	155	21	mae	mae	PROPN
cana-1860	155	22	compared	compare	VERB
cana-1860	155	23	to	to	ADP
cana-1860	155	24	that	that	PRON
cana-1860	155	25	from	from	ADP
cana-1860	155	26	method	method	NOUN
cana-1860	155	27	5	5	NUM
cana-1860	155	28	.	.	PUNCT
cana-1860	156	1	it	it	PRON
cana-1860	156	2	also	also	ADV
cana-1860	156	3	showed	show	VERB
cana-1860	156	4	the	the	DET
cana-1860	156	5	adaptability	adaptability	NOUN
cana-1860	156	6	of	of	ADP
cana-1860	156	7	the	the	DET
cana-1860	156	8	proposed	propose	VERB
cana-1860	156	9	model	model	NOUN
cana-1860	156	10	using	use	VERB
cana-1860	156	11	ppo	ppo	PROPN
cana-1860	156	12	in	in	ADP
cana-1860	156	13	dynamic	dynamic	ADJ
cana-1860	156	14	tuning	tuning	NOUN
cana-1860	156	15	,	,	PUNCT
cana-1860	156	16	increasing	increase	VERB
cana-1860	156	17	precision	precision	NOUN
cana-1860	156	18	by	by	ADP
cana-1860	156	19	0.4	0.4	NUM
cana-1860	156	20	%	%	NOUN
cana-1860	156	21	and	and	CCONJ
cana-1860	156	22	reduced	reduce	VERB
cana-1860	156	23	mae	mae	PROPN
cana-1860	156	24	to	to	ADP
cana-1860	156	25	0.072	0.072	NUM
cana-1860	156	26	in	in	ADP
cana-1860	156	27	the	the	DET
cana-1860	156	28	case	case	NOUN
cana-1860	156	29	of	of	ADP
cana-1860	156	30	real	real	ADJ
cana-1860	156	31	-	-	PUNCT
cana-1860	156	32	time	time	NOUN
cana-1860	156	33	sensor	sensor	NOUN
cana-1860	156	34	data	datum	NOUN
cana-1860	156	35	.	.	PUNCT
cana-1860	157	1	federated	federated	ADJ
cana-1860	157	2	learning	learning	NOUN
cana-1860	157	3	contributed	contribute	VERB
cana-1860	157	4	much	much	ADJ
cana-1860	157	5	to	to	ADP
cana-1860	157	6	the	the	DET
cana-1860	157	7	effectiveness	effectiveness	NOUN
cana-1860	157	8	of	of	ADP
cana-1860	157	9	the	the	DET
cana-1860	157	10	model	model	NOUN
cana-1860	157	11	in	in	ADP
cana-1860	157	12	a	a	DET
cana-1860	157	13	privacy	privacy	NOUN
cana-1860	157	14	-	-	PUNCT
cana-1860	157	15	preserving	preserve	VERB
cana-1860	157	16	environment	environment	NOUN
cana-1860	157	17	for	for	ADP
cana-1860	157	18	widely	widely	ADV
cana-1860	157	19	distributed	distribute	VERB
cana-1860	157	20	healthcare	healthcare	NOUN
cana-1860	157	21	applications	application	NOUN
cana-1860	157	22	with	with	ADP
cana-1860	157	23	an	an	DET
cana-1860	157	24	accuracy	accuracy	NOUN
cana-1860	157	25	of	of	ADP
cana-1860	157	26	96.5	96.5	NUM
cana-1860	157	27	%	%	NOUN
cana-1860	157	28	and	and	CCONJ
cana-1860	157	29	reduced	reduce	VERB
cana-1860	157	30	mae	mae	PROPN
cana-1860	157	31	to	to	ADP
cana-1860	157	32	0.082	0.082	NUM
cana-1860	157	33	.	.	PUNCT
cana-1860	158	1	these	these	DET
cana-1860	158	2	findings	finding	NOUN
cana-1860	158	3	hint	hint	NOUN
cana-1860	158	4	at	at	ADP
cana-1860	158	5	the	the	DET
cana-1860	158	6	robustness	robustness	NOUN
cana-1860	158	7	and	and	CCONJ
cana-1860	158	8	scalability	scalability	NOUN
cana-1860	158	9	of	of	ADP
cana-1860	158	10	the	the	DET
cana-1860	158	11	proposed	propose	VERB
cana-1860	158	12	model	model	NOUN
cana-1860	158	13	in	in	ADP
cana-1860	158	14	analyzing	analyze	VERB
cana-1860	158	15	multimodal	multimodal	ADJ
cana-1860	158	16	data	datum	NOUN
cana-1860	158	17	to	to	PART
cana-1860	158	18	achieve	achieve	VERB
cana-1860	158	19	further	further	ADJ
cana-1860	158	20	improvements	improvement	NOUN
cana-1860	158	21	of	of	ADP
cana-1860	158	22	predictive	predictive	ADJ
cana-1860	158	23	accuracy	accuracy	NOUN
cana-1860	158	24	and	and	CCONJ
cana-1860	158	25	reliability	reliability	NOUN
cana-1860	158	26	in	in	ADP
cana-1860	158	27	a	a	DET
cana-1860	158	28	number	number	NOUN
cana-1860	158	29	of	of	ADP
cana-1860	158	30	domains	domain	NOUN
cana-1860	158	31	.	.	PUNCT
cana-1860	159	1	future	future	ADJ
cana-1860	159	2	scope	scope	NOUN
cana-1860	159	3	of	of	ADP
cana-1860	159	4	work	work	NOUN
cana-1860	159	5	although	although	SCONJ
cana-1860	159	6	the	the	DET
cana-1860	159	7	proposed	propose	VERB
cana-1860	159	8	model	model	NOUN
cana-1860	159	9	has	have	AUX
cana-1860	159	10	shown	show	VERB
cana-1860	159	11	quite	quite	DET
cana-1860	159	12	a	a	DET
cana-1860	159	13	high	high	ADJ
cana-1860	159	14	degree	degree	NOUN
cana-1860	159	15	of	of	ADP
cana-1860	159	16	accuracy	accuracy	NOUN
cana-1860	159	17	and	and	CCONJ
cana-1860	159	18	performance	performance	NOUN
cana-1860	159	19	in	in	ADP
cana-1860	159	20	multimodal	multimodal	ADJ
cana-1860	159	21	datasets	dataset	NOUN
cana-1860	159	22	,	,	PUNCT
cana-1860	159	23	further	further	ADJ
cana-1860	159	24	avenues	avenue	NOUN
cana-1860	159	25	of	of	ADP
cana-1860	159	26	research	research	NOUN
cana-1860	159	27	and	and	CCONJ
cana-1860	159	28	enhancement	enhancement	NOUN
cana-1860	159	29	are	be	AUX
cana-1860	159	30	possible	possible	ADJ
cana-1860	159	31	.	.	PUNCT
cana-1860	160	1	two	two	NUM
cana-1860	160	2	of	of	ADP
cana-1860	160	3	the	the	DET
cana-1860	160	4	most	most	ADV
cana-1860	160	5	promising	promising	ADJ
cana-1860	160	6	directions	direction	NOUN
cana-1860	160	7	in	in	ADP
cana-1860	160	8	which	which	PRON
cana-1860	160	9	further	further	ADJ
cana-1860	160	10	development	development	NOUN
cana-1860	160	11	could	could	AUX
cana-1860	160	12	take	take	VERB
cana-1860	160	13	place	place	NOUN
cana-1860	160	14	are	be	AUX
cana-1860	160	15	:	:	PUNCT
cana-1860	160	16	a	a	X
cana-1860	160	17	)	)	PUNCT
cana-1860	160	18	extension	extension	NOUN
cana-1860	160	19	of	of	ADP
cana-1860	160	20	the	the	DET
cana-1860	160	21	current	current	ADJ
cana-1860	160	22	architecture	architecture	NOUN
cana-1860	160	23	to	to	ADP
cana-1860	160	24	higher	higher	ADV
cana-1860	160	25	-	-	PUNCT
cana-1860	160	26	dimensional	dimensional	ADJ
cana-1860	160	27	and	and	CCONJ
cana-1860	160	28	more	more	ADV
cana-1860	160	29	complex	complex	ADJ
cana-1860	160	30	multimodal	multimodal	ADJ
cana-1860	160	31	data	datum	NOUN
cana-1860	160	32	,	,	PUNCT
cana-1860	160	33	such	such	ADJ
cana-1860	160	34	as	as	ADP
cana-1860	160	35	3d	3d	PROPN
cana-1860	160	36	spatial	spatial	ADJ
cana-1860	160	37	information	information	NOUN
cana-1860	160	38	from	from	ADP
cana-1860	160	39	medical	medical	ADJ
cana-1860	160	40	imaging	imaging	NOUN
cana-1860	160	41	or	or	CCONJ
cana-1860	160	42	higher	high	ADJ
cana-1860	160	43	-	-	PUNCT
cana-1860	160	44	resolution	resolution	NOUN
cana-1860	160	45	temporal	temporal	ADJ
cana-1860	160	46	video	video	NOUN
cana-1860	160	47	streams	stream	NOUN
cana-1860	160	48	in	in	ADP
cana-1860	160	49	real	real	ADJ
cana-1860	160	50	-	-	PUNCT
cana-1860	160	51	time	time	NOUN
cana-1860	160	52	instance	instance	NOUN
cana-1860	160	53	sets	set	VERB
cana-1860	160	54	.	.	PUNCT
cana-1860	161	1	attention	attention	NOUN
cana-1860	161	2	mechanisms	mechanism	NOUN
cana-1860	161	3	,	,	PUNCT
cana-1860	161	4	again	again	ADV
cana-1860	161	5	developed	develop	VERB
cana-1860	161	6	around	around	ADP
cana-1860	161	7	transformers	transformer	NOUN
cana-1860	161	8	,	,	PUNCT
cana-1860	161	9	can	can	AUX
cana-1860	161	10	be	be	AUX
cana-1860	161	11	combined	combine	VERB
cana-1860	161	12	to	to	PART
cana-1860	161	13	selectively	selectively	ADV
cana-1860	161	14	pay	pay	VERB
cana-1860	161	15	more	more	ADJ
cana-1860	161	16	attention	attention	NOUN
cana-1860	161	17	to	to	ADP
cana-1860	161	18	most	most	ADJ
cana-1860	161	19	salient	salient	NOUN
cana-1860	161	20	features	feature	NOUN
cana-1860	161	21	across	across	ADP
cana-1860	161	22	all	all	DET
cana-1860	161	23	modalities	modality	NOUN
cana-1860	161	24	,	,	PUNCT
cana-1860	161	25	hence	hence	ADV
cana-1860	161	26	further	far	ADV
cana-1860	161	27	improving	improve	VERB
cana-1860	161	28	predictive	predictive	ADJ
cana-1860	161	29	accuracy	accuracy	NOUN
cana-1860	161	30	.	.	PUNCT
cana-1860	162	1	another	another	DET
cana-1860	162	2	improvement	improvement	NOUN
cana-1860	162	3	can	can	AUX
cana-1860	162	4	be	be	AUX
cana-1860	162	5	done	do	VERB
cana-1860	162	6	at	at	ADP
cana-1860	162	7	the	the	DET
cana-1860	162	8	optimization	optimization	NOUN
cana-1860	162	9	of	of	ADP
cana-1860	162	10	the	the	DET
cana-1860	162	11	federated	federated	ADJ
cana-1860	162	12	learning	learning	NOUN
cana-1860	162	13	framework	framework	NOUN
cana-1860	162	14	.	.	PUNCT
cana-1860	163	1	added	add	VERB
cana-1860	163	2	mechanisms	mechanism	NOUN
cana-1860	163	3	for	for	ADP
cana-1860	163	4	differential	differential	ADJ
cana-1860	163	5	privacy	privacy	NOUN
cana-1860	163	6	could	could	AUX
cana-1860	163	7	enhance	enhance	VERB
cana-1860	163	8	guarantees	guarantee	NOUN
cana-1860	163	9	on	on	ADP
cana-1860	163	10	data	datum	NOUN
cana-1860	163	11	privacy	privacy	NOUN
cana-1860	163	12	without	without	ADP
cana-1860	163	13	losing	lose	VERB
cana-1860	163	14	model	model	NOUN
cana-1860	163	15	performance	performance	NOUN
cana-1860	163	16	in	in	ADP
cana-1860	163	17	healthcare	healthcare	NOUN
cana-1860	163	18	and	and	CCONJ
cana-1860	163	19	financial	financial	ADJ
cana-1860	163	20	applications	application	NOUN
cana-1860	163	21	.	.	PUNCT
cana-1860	164	1	blockchain	blockchain	PROPN
cana-1860	164	2	-	-	PUNCT
cana-1860	164	3	based	base	VERB
cana-1860	164	4	federated	federated	ADJ
cana-1860	164	5	learning	learning	NOUN
cana-1860	164	6	methods	method	NOUN
cana-1860	164	7	could	could	AUX
cana-1860	164	8	also	also	ADV
cana-1860	164	9	consider	consider	VERB
cana-1860	164	10	a	a	DET
cana-1860	164	11	well	well	ADV
cana-1860	164	12	-	-	PUNCT
cana-1860	164	13	decentralized	decentralize	VERB
cana-1860	164	14	training	training	NOUN
cana-1860	164	15	process	process	NOUN
cana-1860	164	16	and	and	CCONJ
cana-1860	164	17	further	far	ADV
cana-1860	164	18	improve	improve	VERB
cana-1860	164	19	the	the	DET
cana-1860	164	20	robustness	robustness	NOUN
cana-1860	164	21	and	and	CCONJ
cana-1860	164	22	scalability	scalability	NOUN
cana-1860	164	23	of	of	ADP
cana-1860	164	24	the	the	DET
cana-1860	164	25	model	model	NOUN
cana-1860	164	26	against	against	ADP
cana-1860	164	27	distributed	distribute	VERB
cana-1860	164	28	environments	environment	NOUN
cana-1860	164	29	.	.	PUNCT
cana-1860	165	1	in	in	ADP
cana-1860	165	2	this	this	DET
cana-1860	165	3	respect	respect	NOUN
cana-1860	165	4	,	,	PUNCT
cana-1860	165	5	another	another	DET
cana-1860	165	6	exciting	exciting	ADJ
cana-1860	165	7	direction	direction	NOUN
cana-1860	165	8	would	would	AUX
cana-1860	165	9	come	come	VERB
cana-1860	165	10	with	with	ADP
cana-1860	165	11	endowing	endow	VERB
cana-1860	165	12	the	the	DET
cana-1860	165	13	model	model	NOUN
cana-1860	165	14	with	with	ADP
cana-1860	165	15	the	the	DET
cana-1860	165	16	ability	ability	NOUN
cana-1860	165	17	to	to	PART
cana-1860	165	18	learn	learn	VERB
cana-1860	165	19	-	-	PUNCT
cana-1860	165	20	to	to	PART
cana-1860	165	21	-	-	PUNCT
cana-1860	165	22	adapt	adapt	VERB
cana-1860	165	23	quickly	quickly	ADV
cana-1860	165	24	to	to	ADP
cana-1860	165	25	new	new	ADJ
cana-1860	165	26	tasks	task	NOUN
cana-1860	165	27	with	with	ADP
cana-1860	165	28	minimal	minimal	ADJ
cana-1860	165	29	retraining	retraining	NOUN
cana-1860	165	30	by	by	ADP
cana-1860	165	31	integrating	integrate	VERB
cana-1860	165	32	meta	meta	ADJ
cana-1860	165	33	-	-	PUNCT
cana-1860	165	34	learning	learn	VERB
cana-1860	165	35	techniques	technique	NOUN
cana-1860	165	36	into	into	ADP
cana-1860	165	37	the	the	DET
cana-1860	165	38	model	model	NOUN
cana-1860	165	39	.	.	PUNCT
cana-1860	166	1	that	that	PRON
cana-1860	166	2	would	would	AUX
cana-1860	166	3	serve	serve	VERB
cana-1860	166	4	very	very	ADV
cana-1860	166	5	useful	useful	ADJ
cana-1860	166	6	in	in	ADP
cana-1860	166	7	dynamic	dynamic	ADJ
cana-1860	166	8	environments	environment	NOUN
cana-1860	166	9	where	where	SCONJ
cana-1860	166	10	data	datum	NOUN
cana-1860	166	11	distributions	distribution	NOUN
cana-1860	166	12	are	be	AUX
cana-1860	166	13	constantly	constantly	ADV
cana-1860	166	14	shifting	shift	VERB
cana-1860	166	15	,	,	PUNCT
cana-1860	166	16	say	say	VERB
cana-1860	166	17	in	in	ADP
cana-1860	166	18	autonomous	autonomous	ADJ
cana-1860	166	19	systems	system	NOUN
cana-1860	166	20	or	or	CCONJ
cana-1860	166	21	financial	financial	ADJ
cana-1860	166	22	markets	market	NOUN
cana-1860	166	23	.	.	PUNCT
cana-1860	167	1	finally	finally	ADV
cana-1860	167	2	,	,	PUNCT
cana-1860	167	3	it	it	PRON
cana-1860	167	4	would	would	AUX
cana-1860	167	5	also	also	ADV
cana-1860	167	6	be	be	AUX
cana-1860	167	7	worth	worth	ADJ
cana-1860	167	8	including	include	VERB
cana-1860	167	9	in	in	ADP
cana-1860	167	10	the	the	DET
cana-1860	167	11	bayesian	bayesian	NOUN
cana-1860	167	12	neural	neural	ADJ
cana-1860	167	13	network	network	NOUN
cana-1860	167	14	module	module	NOUN
cana-1860	167	15	some	some	PRON
cana-1860	167	16	of	of	ADP
cana-1860	167	17	the	the	DET
cana-1860	167	18	advanced	advanced	ADJ
cana-1860	167	19	probabilistic	probabilistic	ADJ
cana-1860	167	20	reasoning	reasoning	NOUN
cana-1860	167	21	methods	method	NOUN
cana-1860	167	22	that	that	PRON
cana-1860	167	23	have	have	AUX
cana-1860	167	24	been	be	AUX
cana-1860	167	25	demonstrated	demonstrate	VERB
cana-1860	167	26	for	for	ADP
cana-1860	167	27	better	well	ADJ
cana-1860	167	28	uncertainty	uncertainty	NOUN
cana-1860	167	29	quantification	quantification	NOUN
cana-1860	167	30	,	,	PUNCT
cana-1860	167	31	such	such	ADJ
cana-1860	167	32	as	as	ADP
cana-1860	167	33	variational	variational	ADJ
cana-1860	167	34	inference	inference	NOUN
cana-1860	167	35	levels	level	NOUN
cana-1860	167	36	.	.	PUNCT
cana-1860	168	1	it	it	PRON
cana-1860	168	2	would	would	AUX
cana-1860	168	3	make	make	VERB
cana-1860	168	4	the	the	DET
cana-1860	168	5	model	model	NOUN
cana-1860	168	6	more	more	ADV
cana-1860	168	7	robust	robust	ADJ
cana-1860	168	8	against	against	ADP
cana-1860	168	9	noisy	noisy	ADJ
cana-1860	168	10	data	datum	NOUN
cana-1860	168	11	and	and	CCONJ
cana-1860	168	12	therefore	therefore	ADV
cana-1860	168	13	would	would	AUX
cana-1860	168	14	permit	permit	VERB
cana-1860	168	15	better	well	ADJ
cana-1860	168	16	outlier	outlier	ADJ
cana-1860	168	17	detection	detection	NOUN
cana-1860	168	18	.	.	PUNCT
cana-1860	169	1	in	in	ADP
cana-1860	169	2	all	all	PRON
cana-1860	169	3	,	,	PUNCT
cana-1860	169	4	the	the	DET
cana-1860	169	5	proposed	propose	VERB
cana-1860	169	6	hybrid	hybrid	ADJ
cana-1860	169	7	architecture	architecture	NOUN
cana-1860	169	8	opens	open	VERB
cana-1860	169	9	a	a	DET
cana-1860	169	10	very	very	ADV
cana-1860	169	11	promising	promising	ADJ
cana-1860	169	12	avenue	avenue	NOUN
cana-1860	169	13	for	for	ADP
cana-1860	169	14	further	further	ADJ
cana-1860	169	15	work	work	NOUN
cana-1860	169	16	process	process	NOUN
cana-1860	169	17	.	.	PUNCT
cana-1860	170	1	there	there	PRON
cana-1860	170	2	is	be	VERB
cana-1860	170	3	considerable	considerable	ADJ
cana-1860	170	4	room	room	NOUN
cana-1860	170	5	for	for	ADP
cana-1860	170	6	refinement	refinement	NOUN
cana-1860	170	7	and	and	CCONJ
cana-1860	170	8	extension	extension	NOUN
cana-1860	170	9	of	of	ADP
cana-1860	170	10	its	its	PRON
cana-1860	170	11	capabilities	capability	NOUN
cana-1860	170	12	in	in	ADP
cana-1860	170	13	undertaking	undertake	VERB
cana-1860	170	14	multi	multi	ADJ
cana-1860	170	15	-	-	ADJ
cana-1860	170	16	modal	modal	ADJ
cana-1860	170	17	data	data	NOUN
cana-1860	170	18	-	-	PUNCT
cana-1860	170	19	fusion	fusion	NOUN
cana-1860	170	20	tasks	task	NOUN
cana-1860	170	21	on	on	ADP
cana-1860	170	22	scales	scale	NOUN
cana-1860	170	23	of	of	ADP
cana-1860	170	24	increasing	increase	VERB
cana-1860	170	25	complexity	complexity	NOUN
cana-1860	170	26	,	,	PUNCT
cana-1860	170	27	in	in	ADP
cana-1860	170	28	real	real	ADJ
cana-1860	170	29	-	-	PUNCT
cana-1860	170	30	time	time	NOUN
cana-1860	170	31	,	,	PUNCT
cana-1860	170	32	and	and	CCONJ
cana-1860	170	33	larger	large	ADJ
cana-1860	170	34	magnitudes	magnitude	NOUN
cana-1860	170	35	.	.	PUNCT
cana-1860	171	1	communications	communication	NOUN
cana-1860	171	2	on	on	ADP
cana-1860	171	3	applied	apply	VERB
cana-1860	171	4	nonlinear	nonlinear	ADJ
cana-1860	171	5	analysis	analysis	NOUN
cana-1860	171	6	issn	issn	NOUN
cana-1860	171	7	:	:	PUNCT
cana-1860	171	8	1074	1074	NUM
cana-1860	171	9	-	-	PUNCT
cana-1860	171	10	133x	133x	NUM
cana-1860	171	11	vol	vol	NOUN
cana-1860	171	12	32	32	NUM
cana-1860	171	13	no	no	NOUN
cana-1860	171	14	.	.	NOUN
cana-1860	171	15	2	2	NUM
cana-1860	171	16	(	(	PUNCT
cana-1860	171	17	2025	2025	NUM
cana-1860	171	18	)	)	PUNCT
cana-1860	171	19	676	676	NUM
cana-1860	171	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1860	171	21	6	6	NUM
cana-1860	171	22	.	.	PUNCT
cana-1860	171	23	references	reference	NOUN
cana-1860	172	1	[	[	X
cana-1860	172	2	1	1	NUM
cana-1860	172	3	]	]	PUNCT
cana-1860	172	4	l.	l.	PROPN
cana-1860	172	5	junyong	junyong	PROPN
cana-1860	172	6	,	,	PUNCT
cana-1860	172	7	t.	t.	PROPN
cana-1860	172	8	yinyin	yinyin	PROPN
cana-1860	172	9	,	,	PUNCT
cana-1860	172	10	z.	z.	PROPN
cana-1860	172	11	delin	delin	PROPN
cana-1860	172	12	,	,	PUNCT
cana-1860	172	13	y.	y.	PROPN
cana-1860	172	14	feifei	feifei	PROPN
cana-1860	172	15	and	and	CCONJ
cana-1860	172	16	z.	z.	PROPN
cana-1860	172	17	yufeng	yufeng	PROPN
cana-1860	172	18	,	,	PUNCT
cana-1860	172	19	"	"	PUNCT
cana-1860	172	20	fault	fault	VERB
cana-1860	172	21	prediction	prediction	NOUN
cana-1860	172	22	of	of	ADP
cana-1860	172	23	electromagnetic	electromagnetic	ADJ
cana-1860	172	24	launch	launch	NOUN
cana-1860	172	25	system	system	NOUN
cana-1860	172	26	based	base	VERB
cana-1860	172	27	on	on	ADP
cana-1860	172	28	knowledge	knowledge	NOUN
cana-1860	172	29	prediction	prediction	NOUN
cana-1860	172	30	time	time	NOUN
cana-1860	172	31	series	series	NOUN
cana-1860	172	32	,	,	PUNCT
cana-1860	172	33	"	"	PUNCT
cana-1860	172	34	in	in	ADP
cana-1860	172	35	ieee	ieee	NOUN
cana-1860	172	36	transactions	transaction	NOUN
cana-1860	172	37	on	on	ADP
cana-1860	172	38	industry	industry	NOUN
cana-1860	172	39	applications	application	NOUN
cana-1860	172	40	,	,	PUNCT
cana-1860	172	41	vol	vol	NOUN
cana-1860	172	42	.	.	PROPN
cana-1860	172	43	57	57	NUM
cana-1860	172	44	,	,	PUNCT
cana-1860	172	45	no	no	INTJ
cana-1860	172	46	.	.	NOUN
cana-1860	172	47	2	2	NUM
cana-1860	172	48	,	,	PUNCT
cana-1860	172	49	pp	pp	ADJ
cana-1860	172	50	.	.	PUNCT
cana-1860	173	1	1830	1830	NUM
cana-1860	173	2	-	-	SYM
cana-1860	173	3	1839	1839	NUM
cana-1860	173	4	,	,	PUNCT
cana-1860	173	5	march	march	PROPN
cana-1860	173	6	-	-	PUNCT
cana-1860	173	7	april	april	PROPN
cana-1860	173	8	2021	2021	NUM
cana-1860	173	9	,	,	PUNCT
cana-1860	173	10	doi	doi	NOUN
cana-1860	173	11	:	:	PUNCT
cana-1860	173	12	10.1109	10.1109	NUM
cana-1860	173	13	/	/	SYM
cana-1860	173	14	tia.2020.3046705	tia.2020.3046705	NUM
cana-1860	173	15	.	.	PUNCT
cana-1860	174	1	keywords	keyword	NOUN
cana-1860	174	2	:	:	PUNCT
cana-1860	174	3	{	{	PUNCT
cana-1860	174	4	feature	feature	NOUN
cana-1860	174	5	extraction;time	extraction;time	PROPN
cana-1860	174	6	series	series	PROPN
cana-1860	174	7	analysis;electromagnetics;prediction	analysis;electromagnetics;prediction	PROPN
cana-1860	174	8	algorithms;expert	algorithms;expert	PROPN
cana-1860	174	9	systems;electromagnetic	systems;electromagnetic	ADJ
cana-1860	174	10	scattering;railguns;electromagnetic	scattering;railguns;electromagnetic	ADJ
cana-1860	174	11	launch	launch	NOUN
cana-1860	174	12	(	(	PUNCT
cana-1860	174	13	eml	eml	NOUN
cana-1860	174	14	)	)	PUNCT
cana-1860	174	15	system;expert	system;expert	PROPN
cana-1860	174	16	system;fault	system;fault	PROPN
cana-1860	174	17	prediction;health	prediction;health	PROPN
cana-1860	174	18	monitoring;neural	monitoring;neural	PROPN
cana-1860	174	19	network;time	network;time	PROPN
cana-1860	174	20	series	series	PROPN
cana-1860	174	21	prediction	prediction	NOUN
cana-1860	174	22	}	}	PUNCT
cana-1860	174	23	,	,	PUNCT
cana-1860	174	24	[	[	X
cana-1860	174	25	2	2	X
cana-1860	174	26	]	]	PUNCT
cana-1860	174	27	d.	d.	PROPN
cana-1860	174	28	-k	-k	PROPN
cana-1860	174	29	.	.	PUNCT
cana-1860	175	1	kim	kim	PROPN
cana-1860	175	2	and	and	CCONJ
cana-1860	175	3	k.	k.	PROPN
cana-1860	175	4	kim	kim	PROPN
cana-1860	175	5	,	,	PUNCT
cana-1860	175	6	"	"	PUNCT
cana-1860	175	7	a	a	DET
cana-1860	175	8	convolutional	convolutional	ADJ
cana-1860	175	9	transformer	transformer	NOUN
cana-1860	175	10	model	model	NOUN
cana-1860	175	11	for	for	ADP
cana-1860	175	12	multivariate	multivariate	NOUN
cana-1860	175	13	time	time	NOUN
cana-1860	175	14	series	series	PROPN
cana-1860	175	15	prediction	prediction	NOUN
cana-1860	175	16	,	,	PUNCT
cana-1860	175	17	"	"	PUNCT
cana-1860	175	18	in	in	ADP
cana-1860	175	19	ieee	ieee	NOUN
cana-1860	175	20	access	access	NOUN
cana-1860	175	21	,	,	PUNCT
cana-1860	175	22	vol	vol	NOUN
cana-1860	175	23	.	.	PROPN
cana-1860	175	24	10	10	NUM
cana-1860	175	25	,	,	PUNCT
cana-1860	175	26	pp	pp	ADJ
cana-1860	175	27	.	.	PUNCT
cana-1860	176	1	101319	101319	NUM
cana-1860	176	2	-	-	SYM
cana-1860	176	3	101329	101329	NUM
cana-1860	176	4	,	,	PUNCT
cana-1860	176	5	2022	2022	NUM
cana-1860	176	6	,	,	PUNCT
cana-1860	176	7	doi	doi	NOUN
cana-1860	176	8	:	:	PUNCT
cana-1860	176	9	10.1109	10.1109	NUM
cana-1860	176	10	/	/	SYM
cana-1860	176	11	access.2022.3203416	access.2022.3203416	ADV
cana-1860	176	12	.	.	PUNCT
cana-1860	177	1	keywords	keyword	NOUN
cana-1860	177	2	:	:	PUNCT
cana-1860	177	3	{	{	PUNCT
cana-1860	177	4	time	time	NOUN
cana-1860	177	5	series	series	PROPN
cana-1860	177	6	analysis;predictive	analysis;predictive	PROPN
cana-1860	177	7	models;convolutional	models;convolutional	PROPN
cana-1860	177	8	neural	neural	ADJ
cana-1860	177	9	networks;data	networks;data	ADJ
cana-1860	177	10	models;forecasting;transformers;feature	models;forecasting;transformers;feature	NOUN
cana-1860	177	11	extraction;artificial	extraction;artificial	PROPN
cana-1860	177	12	neural	neural	ADJ
cana-1860	177	13	networks;predictive	networks;predictive	PROPN
cana-1860	177	14	models;time	models;time	PROPN
cana-1860	177	15	series	series	NOUN
cana-1860	177	16	prediction	prediction	NOUN
cana-1860	177	17	}	}	PUNCT
cana-1860	177	18	,	,	PUNCT
cana-1860	178	1	[	[	X
cana-1860	178	2	3	3	X
cana-1860	178	3	]	]	X
cana-1860	178	4	d.	d.	PROPN
cana-1860	178	5	zeng	zeng	PROPN
cana-1860	178	6	,	,	PUNCT
cana-1860	178	7	j.	j.	PROPN
cana-1860	178	8	lu	lu	PROPN
cana-1860	178	9	and	and	CCONJ
cana-1860	178	10	y.	y.	PROPN
cana-1860	178	11	zheng	zheng	PROPN
cana-1860	178	12	,	,	PUNCT
cana-1860	178	13	"	"	PUNCT
cana-1860	178	14	combined	combine	VERB
cana-1860	178	15	fuzzy	fuzzy	ADJ
cana-1860	178	16	time	time	NOUN
cana-1860	178	17	series	series	PROPN
cana-1860	178	18	prediction	prediction	NOUN
cana-1860	178	19	method	method	NOUN
cana-1860	178	20	for	for	ADP
cana-1860	178	21	fault	fault	NOUN
cana-1860	178	22	prediction	prediction	NOUN
cana-1860	178	23	of	of	ADP
cana-1860	178	24	eml	eml	PROPN
cana-1860	178	25	pulse	pulse	NOUN
cana-1860	178	26	capacitors	capacitor	NOUN
cana-1860	178	27	,	,	PUNCT
cana-1860	178	28	"	"	PUNCT
cana-1860	178	29	in	in	ADP
cana-1860	178	30	ieee	ieee	NOUN
cana-1860	178	31	transactions	transaction	NOUN
cana-1860	178	32	on	on	ADP
cana-1860	178	33	plasma	plasma	NOUN
cana-1860	178	34	science	science	NOUN
cana-1860	178	35	,	,	PUNCT
cana-1860	178	36	vol	vol	NOUN
cana-1860	178	37	.	.	PROPN
cana-1860	178	38	49	49	NUM
cana-1860	178	39	,	,	PUNCT
cana-1860	178	40	no	no	INTJ
cana-1860	178	41	.	.	NOUN
cana-1860	178	42	2	2	NUM
cana-1860	178	43	,	,	PUNCT
cana-1860	178	44	pp	pp	ADJ
cana-1860	178	45	.	.	PUNCT
cana-1860	179	1	905	905	NUM
cana-1860	179	2	-	-	SYM
cana-1860	179	3	913	913	NUM
cana-1860	179	4	,	,	PUNCT
cana-1860	179	5	feb	feb	PROPN
cana-1860	179	6	.	.	PROPN
cana-1860	179	7	2021	2021	NUM
cana-1860	179	8	,	,	PUNCT
cana-1860	179	9	doi	doi	NOUN
cana-1860	179	10	:	:	PUNCT
cana-1860	179	11	10.1109	10.1109	NUM
cana-1860	179	12	/	/	SYM
cana-1860	179	13	tps.2020.3029840	tps.2020.3029840	NUM
cana-1860	179	14	.	.	PUNCT
cana-1860	180	1	keywords	keyword	NOUN
cana-1860	180	2	:	:	PUNCT
cana-1860	180	3	{	{	PUNCT
cana-1860	180	4	capacitors;capacitance;time	capacitors;capacitance;time	NOUN
cana-1860	180	5	series	series	NOUN
cana-1860	180	6	analysis;discharges	analysis;discharge	NOUN
cana-1860	180	7	(	(	PUNCT
cana-1860	180	8	electric);electromagnetics;degradation;uncertainty;electromagnetic	electric);electromagnetics;degradation;uncertainty;electromagnetic	ADJ
cana-1860	180	9	launch	launch	NOUN
cana-1860	180	10	(	(	PUNCT
cana-1860	180	11	eml	eml	NOUN
cana-1860	180	12	)	)	PUNCT
cana-1860	180	13	system;fuzzy	system;fuzzy	PROPN
cana-1860	180	14	time	time	PROPN
cana-1860	180	15	series	series	PROPN
cana-1860	180	16	prediction;large	prediction;large	NOUN
cana-1860	180	17	-	-	PUNCT
cana-1860	180	18	scale	scale	NOUN
cana-1860	180	19	pulse	pulse	NOUN
cana-1860	180	20	forming	form	VERB
cana-1860	180	21	network	network	NOUN
cana-1860	180	22	(	(	PUNCT
cana-1860	180	23	pfn);metallized	pfn);metallized	ADJ
cana-1860	180	24	film	film	NOUN
cana-1860	180	25	capacitors	capacitor	NOUN
cana-1860	180	26	}	}	PUNCT
cana-1860	180	27	,	,	PUNCT
cana-1860	181	1	[	[	X
cana-1860	181	2	4	4	X
cana-1860	181	3	]	]	PUNCT
cana-1860	181	4	s.	s.	PROPN
cana-1860	181	5	feng	feng	PROPN
cana-1860	181	6	,	,	PUNCT
cana-1860	181	7	m.	m.	PROPN
cana-1860	181	8	han	han	PROPN
cana-1860	181	9	,	,	PUNCT
cana-1860	181	10	j.	j.	PROPN
cana-1860	181	11	zhang	zhang	PROPN
cana-1860	181	12	,	,	PUNCT
cana-1860	181	13	t.	t.	PROPN
cana-1860	181	14	qiu	qiu	PROPN
cana-1860	181	15	and	and	CCONJ
cana-1860	181	16	w.	w.	PROPN
cana-1860	181	17	ren	ren	PROPN
cana-1860	181	18	,	,	PUNCT
cana-1860	181	19	"	"	PUNCT
cana-1860	181	20	learning	learn	VERB
cana-1860	181	21	both	both	CCONJ
cana-1860	181	22	dynamic	dynamic	ADV
cana-1860	181	23	-	-	PUNCT
cana-1860	181	24	shared	share	VERB
cana-1860	181	25	and	and	CCONJ
cana-1860	181	26	dynamicspecific	dynamicspecific	ADJ
cana-1860	181	27	patterns	pattern	NOUN
cana-1860	181	28	for	for	ADP
cana-1860	181	29	chaotic	chaotic	ADJ
cana-1860	181	30	time	time	NOUN
cana-1860	181	31	-	-	PUNCT
cana-1860	181	32	series	series	NOUN
cana-1860	181	33	prediction	prediction	NOUN
cana-1860	181	34	,	,	PUNCT
cana-1860	181	35	"	"	PUNCT
cana-1860	181	36	in	in	ADP
cana-1860	181	37	ieee	ieee	NOUN
cana-1860	181	38	transactions	transaction	NOUN
cana-1860	181	39	on	on	ADP
cana-1860	181	40	cybernetics	cybernetic	NOUN
cana-1860	181	41	,	,	PUNCT
cana-1860	181	42	vol	vol	NOUN
cana-1860	181	43	.	.	PROPN
cana-1860	181	44	52	52	NUM
cana-1860	181	45	,	,	PUNCT
cana-1860	181	46	no	no	INTJ
cana-1860	181	47	.	.	NOUN
cana-1860	181	48	6	6	NUM
cana-1860	181	49	,	,	PUNCT
cana-1860	181	50	pp	pp	ADJ
cana-1860	181	51	.	.	PUNCT
cana-1860	181	52	4115	4115	NUM
cana-1860	181	53	-	-	SYM
cana-1860	181	54	4125	4125	NUM
cana-1860	181	55	,	,	PUNCT
cana-1860	181	56	june	june	PROPN
cana-1860	181	57	2022	2022	NUM
cana-1860	181	58	,	,	PUNCT
cana-1860	181	59	doi	doi	NOUN
cana-1860	181	60	:	:	PUNCT
cana-1860	181	61	10.1109	10.1109	NUM
cana-1860	181	62	/	/	SYM
cana-1860	181	63	tcyb.2020.3017736	tcyb.2020.3017736	NOUN
cana-1860	181	64	.	.	PUNCT
cana-1860	182	1	keywords	keyword	NOUN
cana-1860	182	2	:	:	PUNCT
cana-1860	182	3	{	{	PUNCT
cana-1860	182	4	task	task	NOUN
cana-1860	182	5	analysis;time	analysis;time	PROPN
cana-1860	182	6	series	series	PROPN
cana-1860	182	7	analysis;dynamical	analysis;dynamical	PROPN
cana-1860	182	8	systems;predictive	systems;predictive	ADJ
cana-1860	182	9	models;market	models;market	NOUN
cana-1860	182	10	research;optimization;heuristic	research;optimization;heuristic	ADJ
cana-1860	182	11	algorithms;dynamic	algorithms;dynamic	ADJ
cana-1860	182	12	pattern;multitask	pattern;multitask	NOUN
cana-1860	182	13	learning	learn	VERB
cana-1860	182	14	(	(	PUNCT
cana-1860	182	15	mtl);stiefel	mtl);stiefel	ADJ
cana-1860	182	16	manifold	manifold	ADJ
cana-1860	182	17	optimization;time	optimization;time	NOUN
cana-1860	182	18	-	-	PUNCT
cana-1860	182	19	series	series	NOUN
cana-1860	182	20	prediction	prediction	NOUN
cana-1860	182	21	}	}	PUNCT
cana-1860	182	22	,	,	PUNCT
cana-1860	182	23	[	[	X
cana-1860	182	24	5	5	NUM
cana-1860	182	25	]	]	PUNCT
cana-1860	182	26	f.	f.	PROPN
cana-1860	182	27	shen	shen	PROPN
cana-1860	182	28	,	,	PUNCT
cana-1860	182	29	j.	j.	PROPN
cana-1860	182	30	liu	liu	PROPN
cana-1860	182	31	and	and	CCONJ
cana-1860	182	32	k.	k.	PROPN
cana-1860	182	33	wu	wu	PROPN
cana-1860	182	34	,	,	PUNCT
cana-1860	182	35	"	"	PUNCT
cana-1860	182	36	multivariate	multivariate	NOUN
cana-1860	182	37	time	time	NOUN
cana-1860	182	38	series	series	PROPN
cana-1860	182	39	forecasting	forecasting	NOUN
cana-1860	182	40	based	base	VERB
cana-1860	182	41	on	on	ADP
cana-1860	182	42	elastic	elastic	ADJ
cana-1860	182	43	net	net	ADJ
cana-1860	182	44	and	and	CCONJ
cana-1860	182	45	highorder	highorder	NOUN
cana-1860	182	46	fuzzy	fuzzy	ADJ
cana-1860	182	47	cognitive	cognitive	ADJ
cana-1860	182	48	maps	map	NOUN
cana-1860	182	49	:	:	PUNCT
cana-1860	182	50	a	a	DET
cana-1860	182	51	case	case	NOUN
cana-1860	182	52	study	study	NOUN
cana-1860	182	53	on	on	ADP
cana-1860	182	54	human	human	ADJ
cana-1860	182	55	action	action	NOUN
cana-1860	182	56	prediction	prediction	NOUN
cana-1860	182	57	through	through	ADP
cana-1860	182	58	eeg	eeg	NOUN
cana-1860	182	59	signals	signal	NOUN
cana-1860	182	60	,	,	PUNCT
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cana-1860	184	16	-	-	PUNCT
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cana-1860	184	38	s.	s.	PROPN
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cana-1860	184	41	h.	h.	PROPN
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cana-1860	184	43	,	,	PUNCT
cana-1860	184	44	"	"	PUNCT
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cana-1860	185	2	-	-	SYM
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cana-1860	186	17	learning	learning	PROPN
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cana-1860	186	19	,	,	PUNCT
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cana-1860	186	26	:	:	PUNCT
cana-1860	186	27	1074	1074	NUM
cana-1860	186	28	-	-	PUNCT
cana-1860	186	29	133x	133x	NUM
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cana-1860	186	33	.	.	NOUN
cana-1860	186	34	2	2	NUM
cana-1860	186	35	(	(	PUNCT
cana-1860	186	36	2025	2025	NUM
cana-1860	186	37	)	)	PUNCT
cana-1860	186	38	677	677	NUM
cana-1860	186	39	https://internationalpubls.com	https://internationalpubls.com	X
cana-1860	187	1	[	[	X
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cana-1860	189	18	network	network	NOUN
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cana-1860	189	20	,	,	PUNCT
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cana-1860	189	26	,	,	PUNCT
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cana-1860	192	12	learning	learn	VERB
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cana-1860	192	14	(	(	PUNCT
cana-1860	192	15	bls);chaotic	bls);chaotic	ADJ
cana-1860	192	16	time	time	NOUN
cana-1860	192	17	series	series	PROPN
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cana-1860	192	19	model	model	PROPN
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cana-1860	192	21	,	,	PUNCT
cana-1860	192	22	[	[	X
cana-1860	192	23	9	9	NUM
cana-1860	192	24	]	]	PUNCT
cana-1860	192	25	x.	x.	NOUN
cana-1860	192	26	chen	chen	PROPN
cana-1860	192	27	and	and	CCONJ
cana-1860	192	28	l.	l.	PROPN
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cana-1860	192	31	"	"	PUNCT
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cana-1860	192	33	temporal	temporal	ADJ
cana-1860	192	34	factorization	factorization	NOUN
cana-1860	192	35	for	for	ADP
cana-1860	192	36	multidimensional	multidimensional	ADJ
cana-1860	192	37	time	time	NOUN
cana-1860	192	38	series	series	PROPN
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cana-1860	192	40	,	,	PUNCT
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cana-1860	194	2	-	-	SYM
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cana-1860	195	36	mubang	mubang	PROPN
cana-1860	195	37	and	and	CCONJ
cana-1860	195	38	l.	l.	PROPN
cana-1860	195	39	o.	o.	PROPN
cana-1860	195	40	hall	hall	PROPN
cana-1860	195	41	,	,	PUNCT
cana-1860	195	42	"	"	PUNCT
cana-1860	195	43	vam	vam	X
cana-1860	195	44	:	:	PUNCT
cana-1860	195	45	an	an	DET
cana-1860	195	46	end	end	NOUN
cana-1860	195	47	-	-	PUNCT
cana-1860	195	48	to	to	ADP
cana-1860	195	49	-	-	PUNCT
cana-1860	195	50	end	end	NOUN
cana-1860	195	51	simulator	simulator	NOUN
cana-1860	195	52	for	for	ADP
cana-1860	195	53	time	time	NOUN
cana-1860	195	54	series	series	PROPN
cana-1860	195	55	regression	regression	PROPN
cana-1860	195	56	and	and	CCONJ
cana-1860	195	57	temporal	temporal	ADJ
cana-1860	195	58	link	link	NOUN
cana-1860	195	59	prediction	prediction	NOUN
cana-1860	195	60	in	in	ADP
cana-1860	195	61	social	social	ADJ
cana-1860	195	62	media	medium	NOUN
cana-1860	195	63	networks	network	NOUN
cana-1860	195	64	,	,	PUNCT
cana-1860	195	65	"	"	PUNCT
cana-1860	195	66	in	in	ADP
cana-1860	195	67	ieee	ieee	NOUN
cana-1860	195	68	transactions	transaction	NOUN
cana-1860	195	69	on	on	ADP
cana-1860	195	70	computational	computational	ADJ
cana-1860	195	71	social	social	ADJ
cana-1860	195	72	systems	system	NOUN
cana-1860	195	73	,	,	PUNCT
cana-1860	195	74	vol	vol	NOUN
cana-1860	195	75	.	.	PROPN
cana-1860	195	76	10	10	NUM
cana-1860	195	77	,	,	PUNCT
cana-1860	195	78	no	no	INTJ
cana-1860	195	79	.	.	NOUN
cana-1860	195	80	4	4	NUM
cana-1860	195	81	,	,	PUNCT
cana-1860	195	82	pp	pp	ADJ
cana-1860	195	83	.	.	PUNCT
cana-1860	196	1	1479	1479	NUM
cana-1860	196	2	-	-	SYM
cana-1860	196	3	1490	1490	NUM
cana-1860	196	4	,	,	PUNCT
cana-1860	196	5	aug	aug	PROPN
cana-1860	196	6	.	.	PROPN
cana-1860	196	7	2023	2023	NUM
cana-1860	196	8	,	,	PUNCT
cana-1860	196	9	doi	doi	NOUN
cana-1860	196	10	:	:	PUNCT
cana-1860	196	11	10.1109	10.1109	NUM
cana-1860	196	12	/	/	SYM
cana-1860	196	13	tcss.2022.3180586	tcss.2022.3180586	NOUN
cana-1860	196	14	.	.	PUNCT
cana-1860	197	1	keywords	keyword	NOUN
cana-1860	197	2	:	:	PUNCT
cana-1860	197	3	{	{	PUNCT
cana-1860	197	4	social	social	ADJ
cana-1860	197	5	networking	networking	NOUN
cana-1860	197	6	(	(	PUNCT
cana-1860	197	7	online);time	online);time	PROPN
cana-1860	197	8	series	series	PROPN
cana-1860	197	9	analysis;predictive	analysis;predictive	PROPN
cana-1860	197	10	models;blogs;task	models;blogs;task	VERB
cana-1860	197	11	analysis;software	analysis;software	PROPN
cana-1860	197	12	development	development	NOUN
cana-1860	197	13	management;computational	management;computational	PROPN
cana-1860	197	14	modeling;extreme	modeling;extreme	PROPN
cana-1860	197	15	gradient	gradient	NOUN
cana-1860	197	16	boosting;link	boosting;link	PROPN
cana-1860	197	17	prediction;social	prediction;social	ADJ
cana-1860	197	18	media;time	media;time	PROPN
cana-1860	197	19	series	series	NOUN
cana-1860	197	20	prediction	prediction	NOUN
cana-1860	197	21	}	}	PUNCT
cana-1860	197	22	,	,	PUNCT
cana-1860	197	23	[	[	X
cana-1860	197	24	11	11	NUM
cana-1860	197	25	]	]	X
cana-1860	197	26	c.	c.	PROPN
cana-1860	197	27	ma	ma	PROPN
cana-1860	197	28	,	,	PUNCT
cana-1860	197	29	g.	g.	PROPN
cana-1860	197	30	dai	dai	PROPN
cana-1860	197	31	and	and	CCONJ
cana-1860	197	32	j.	j.	PROPN
cana-1860	197	33	zhou	zhou	PROPN
cana-1860	197	34	,	,	PUNCT
cana-1860	197	35	"	"	PUNCT
cana-1860	197	36	short	short	ADJ
cana-1860	197	37	-	-	PUNCT
cana-1860	197	38	term	term	NOUN
cana-1860	197	39	traffic	traffic	NOUN
cana-1860	197	40	flow	flow	NOUN
cana-1860	197	41	prediction	prediction	NOUN
cana-1860	197	42	for	for	ADP
cana-1860	197	43	urban	urban	ADJ
cana-1860	197	44	road	road	NOUN
cana-1860	197	45	sections	section	NOUN
cana-1860	197	46	based	base	VERB
cana-1860	197	47	on	on	ADP
cana-1860	197	48	time	time	NOUN
cana-1860	197	49	series	series	NOUN
cana-1860	197	50	analysis	analysis	NOUN
cana-1860	197	51	and	and	CCONJ
cana-1860	197	52	lstm_bilstm	lstm_bilstm	NOUN
cana-1860	197	53	method	method	NOUN
cana-1860	197	54	,	,	PUNCT
cana-1860	197	55	"	"	PUNCT
cana-1860	197	56	in	in	ADP
cana-1860	197	57	ieee	ieee	NOUN
cana-1860	197	58	transactions	transaction	NOUN
cana-1860	197	59	on	on	ADP
cana-1860	197	60	intelligent	intelligent	ADJ
cana-1860	197	61	transportation	transportation	NOUN
cana-1860	197	62	systems	system	NOUN
cana-1860	197	63	,	,	PUNCT
cana-1860	197	64	vol	vol	NOUN
cana-1860	197	65	.	.	PROPN
cana-1860	197	66	23	23	NUM
cana-1860	197	67	,	,	PUNCT
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cana-1860	197	70	6	6	NUM
cana-1860	197	71	,	,	PUNCT
cana-1860	197	72	pp	pp	ADJ
cana-1860	197	73	.	.	PUNCT
cana-1860	198	1	5615	5615	NUM
cana-1860	198	2	-	-	SYM
cana-1860	198	3	5624	5624	NUM
cana-1860	198	4	,	,	PUNCT
cana-1860	198	5	june	june	PROPN
cana-1860	198	6	2022	2022	NUM
cana-1860	198	7	,	,	PUNCT
cana-1860	198	8	doi	doi	NOUN
cana-1860	198	9	:	:	PUNCT
cana-1860	198	10	10.1109	10.1109	NUM
cana-1860	198	11	/	/	SYM
cana-1860	198	12	tits.2021.3055258	tits.2021.3055258	NOUN
cana-1860	198	13	.	.	PUNCT
cana-1860	199	1	keywords	keyword	NOUN
cana-1860	199	2	:	:	PUNCT
cana-1860	199	3	{	{	PUNCT
cana-1860	199	4	time	time	NOUN
cana-1860	199	5	series	series	PROPN
cana-1860	199	6	analysis;predictive	analysis;predictive	PROPN
cana-1860	199	7	models;fractals;data	models;fractals;data	PROPN
cana-1860	199	8	models;correlation;biological	models;correlation;biological	ADJ
cana-1860	199	9	neural	neural	ADJ
cana-1860	199	10	networks;training;traffic	networks;training;traffic	ADJ
cana-1860	199	11	engineering;short	engineering;short	NOUN
cana-1860	199	12	-	-	PUNCT
cana-1860	199	13	term	term	NOUN
cana-1860	199	14	traffic	traffic	NOUN
cana-1860	199	15	flow	flow	NOUN
cana-1860	199	16	prediction;lstm_bilstm	prediction;lstm_bilstm	NOUN
cana-1860	199	17	method;time	method;time	PROPN
cana-1860	199	18	series	series	PROPN
cana-1860	199	19	analysis;urban	analysis;urban	PROPN
cana-1860	199	20	road	road	NOUN
cana-1860	199	21	section	section	NOUN
cana-1860	199	22	}	}	PUNCT
cana-1860	199	23	,	,	PUNCT
cana-1860	199	24	[	[	X
cana-1860	199	25	12	12	NUM
cana-1860	199	26	]	]	X
cana-1860	199	27	w.	w.	PROPN
cana-1860	199	28	wang	wang	PROPN
cana-1860	199	29	,	,	PUNCT
cana-1860	199	30	w.	w.	PROPN
cana-1860	199	31	liu	liu	PROPN
cana-1860	199	32	and	and	CCONJ
cana-1860	199	33	h.	h.	PROPN
cana-1860	199	34	chen	chen	PROPN
cana-1860	199	35	,	,	PUNCT
cana-1860	199	36	"	"	PUNCT
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cana-1860	199	38	granules	granule	NOUN
cana-1860	199	39	-	-	PUNCT
cana-1860	199	40	based	base	VERB
cana-1860	199	41	bp	bp	PROPN
cana-1860	199	42	neural	neural	ADJ
cana-1860	199	43	network	network	NOUN
cana-1860	199	44	for	for	ADP
cana-1860	199	45	long	long	ADJ
cana-1860	199	46	-	-	PUNCT
cana-1860	199	47	term	term	NOUN
cana-1860	199	48	prediction	prediction	NOUN
cana-1860	199	49	of	of	ADP
cana-1860	199	50	time	time	NOUN
cana-1860	199	51	series	series	NOUN
cana-1860	199	52	,	,	PUNCT
cana-1860	199	53	"	"	PUNCT
cana-1860	199	54	in	in	ADP
cana-1860	199	55	ieee	ieee	NOUN
cana-1860	199	56	transactions	transaction	NOUN
cana-1860	199	57	on	on	ADP
cana-1860	199	58	fuzzy	fuzzy	ADJ
cana-1860	199	59	systems	system	NOUN
cana-1860	199	60	,	,	PUNCT
cana-1860	199	61	vol	vol	NOUN
cana-1860	199	62	.	.	PROPN
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cana-1860	199	68	,	,	PUNCT
cana-1860	199	69	pp	pp	ADJ
cana-1860	199	70	.	.	PUNCT
cana-1860	199	71	29752987	29752987	NUM
cana-1860	199	72	,	,	PUNCT
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cana-1860	199	75	2021	2021	NUM
cana-1860	199	76	,	,	PUNCT
cana-1860	199	77	doi	doi	NOUN
cana-1860	199	78	:	:	PUNCT
cana-1860	199	79	10.1109	10.1109	NUM
cana-1860	199	80	/	/	SYM
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cana-1860	199	82	.	.	PUNCT
cana-1860	200	1	keywords	keyword	NOUN
cana-1860	200	2	:	:	PUNCT
cana-1860	200	3	{	{	PUNCT
cana-1860	200	4	time	time	NOUN
cana-1860	200	5	series	series	PROPN
cana-1860	200	6	analysis;market	analysis;market	PROPN
cana-1860	200	7	research;predictive	research;predictive	PROPN
cana-1860	200	8	models;neural	models;neural	ADJ
cana-1860	200	9	networks;forecasting;hidden	networks;forecasting;hidden	ADJ
cana-1860	200	10	markov	markov	NOUN
cana-1860	200	11	models;semantics;back	models;semantics;back	NOUN
cana-1860	200	12	-	-	PUNCT
cana-1860	200	13	propagation	propagation	NOUN
cana-1860	200	14	neural	neural	ADJ
cana-1860	200	15	network;information	network;information	PROPN
cana-1860	200	16	granulation;long	granulation;long	PROPN
cana-1860	200	17	-	-	PUNCT
cana-1860	200	18	term	term	NOUN
cana-1860	200	19	prediction;time	prediction;time	PROPN
cana-1860	200	20	series	series	NOUN
cana-1860	200	21	forecasting	forecasting	PROPN
cana-1860	200	22	}	}	PUNCT
cana-1860	200	23	,	,	PUNCT
cana-1860	200	24	[	[	X
cana-1860	200	25	13	13	NUM
cana-1860	200	26	]	]	X
cana-1860	200	27	n.	n.	PROPN
cana-1860	200	28	maaroufi	maaroufi	PROPN
cana-1860	200	29	,	,	PUNCT
cana-1860	200	30	m.	m.	NOUN
cana-1860	200	31	najib	najib	PROPN
cana-1860	200	32	and	and	CCONJ
cana-1860	200	33	m.	m.	PROPN
cana-1860	200	34	bakhouya	bakhouya	PROPN
cana-1860	200	35	,	,	PUNCT
cana-1860	200	36	"	"	PUNCT
cana-1860	200	37	predicting	predict	VERB
cana-1860	200	38	the	the	DET
cana-1860	200	39	future	future	NOUN
cana-1860	200	40	is	be	AUX
cana-1860	200	41	like	like	ADP
cana-1860	200	42	completing	complete	VERB
cana-1860	200	43	a	a	DET
cana-1860	200	44	painting	painting	NOUN
cana-1860	200	45	:	:	PUNCT
cana-1860	200	46	towards	towards	ADP
cana-1860	200	47	a	a	DET
cana-1860	200	48	novel	novel	ADJ
cana-1860	200	49	method	method	NOUN
cana-1860	200	50	for	for	ADP
cana-1860	200	51	time	time	NOUN
cana-1860	200	52	-	-	PUNCT
cana-1860	200	53	series	series	NOUN
cana-1860	200	54	forecasting	forecasting	NOUN
cana-1860	200	55	,	,	PUNCT
cana-1860	200	56	"	"	PUNCT
cana-1860	200	57	in	in	ADP
cana-1860	200	58	ieee	ieee	NOUN
cana-1860	200	59	access	access	NOUN
cana-1860	200	60	,	,	PUNCT
cana-1860	200	61	vol	vol	NOUN
cana-1860	200	62	.	.	NOUN
cana-1860	200	63	9	9	NUM
cana-1860	200	64	,	,	PUNCT
cana-1860	200	65	pp	pp	ADJ
cana-1860	200	66	.	.	PUNCT
cana-1860	201	1	119918119938	119918119938	NUM
cana-1860	201	2	,	,	PUNCT
cana-1860	201	3	2021	2021	NUM
cana-1860	201	4	,	,	PUNCT
cana-1860	201	5	doi	doi	NOUN
cana-1860	201	6	:	:	PUNCT
cana-1860	201	7	10.1109	10.1109	NUM
cana-1860	201	8	/	/	SYM
cana-1860	201	9	access.2021.3101718	access.2021.3101718	PROPN
cana-1860	201	10	.	.	PUNCT
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cana-1860	202	2	on	on	ADP
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cana-1860	202	7	:	:	PUNCT
cana-1860	202	8	1074	1074	NUM
cana-1860	202	9	-	-	PUNCT
cana-1860	202	10	133x	133x	NUM
cana-1860	202	11	vol	vol	NOUN
cana-1860	202	12	32	32	NUM
cana-1860	202	13	no	no	NOUN
cana-1860	202	14	.	.	NOUN
cana-1860	202	15	2	2	NUM
cana-1860	202	16	(	(	PUNCT
cana-1860	202	17	2025	2025	NUM
cana-1860	202	18	)	)	PUNCT
cana-1860	203	1	678	678	NUM
cana-1860	203	2	https://internationalpubls.com	https://internationalpubls.com	X
cana-1860	203	3	keywords	keyword	NOUN
cana-1860	203	4	:	:	PUNCT
cana-1860	203	5	{	{	PUNCT
cana-1860	203	6	forecasting;predictive	forecasting;predictive	PROPN
cana-1860	203	7	models;time	models;time	PROPN
cana-1860	203	8	series	series	NOUN
cana-1860	203	9	analysis;tools;testing;extrapolation;analytical	analysis;tools;testing;extrapolation;analytical	ADJ
cana-1860	203	10	models;scientific	models;scientific	ADJ
cana-1860	203	11	prediction	prediction	NOUN
cana-1860	203	12	and	and	CCONJ
cana-1860	203	13	experimental	experimental	ADJ
cana-1860	203	14	philosophy	philosophy	NOUN
cana-1860	203	15	of	of	ADP
cana-1860	203	16	science;extensive	science;extensive	ADJ
cana-1860	203	17	structural	structural	ADJ
cana-1860	203	18	realism;bridging	realism;bridge	VERB
cana-1860	203	19	philosophy;time	philosophy;time	PROPN
cana-1860	203	20	series	series	NOUN
cana-1860	203	21	forecasting;fully	forecasting;fully	ADV
cana-1860	203	22	integrated	integrate	VERB
cana-1860	203	23	modeling	modeling	NOUN
cana-1860	203	24	and	and	CCONJ
cana-1860	203	25	processing	process	VERB
cana-1860	203	26	framework;ensemble	framework;ensemble	ADJ
cana-1860	203	27	data	datum	NOUN
cana-1860	203	28	autocorrelation	autocorrelation	NOUN
cana-1860	203	29	forecasting;augmented	forecasting;augmente	VERB
cana-1860	203	30	dimension	dimension	NOUN
cana-1860	203	31	prediction;image	prediction;image	NOUN
cana-1860	203	32	and	and	CCONJ
cana-1860	203	33	signal	signal	NOUN
cana-1860	203	34	processing	processing	NOUN
cana-1860	203	35	}	}	PUNCT
cana-1860	203	36	,	,	PUNCT
cana-1860	203	37	[	[	X
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cana-1860	203	39	]	]	X
cana-1860	203	40	s.	s.	PROPN
cana-1860	203	41	ren	ren	PROPN
cana-1860	203	42	,	,	PUNCT
cana-1860	203	43	b.	b.	PROPN
cana-1860	203	44	guo	guo	PROPN
cana-1860	203	45	,	,	PUNCT
cana-1860	203	46	k.	k.	PROPN
cana-1860	203	47	li	li	PROPN
cana-1860	203	48	,	,	PUNCT
cana-1860	203	49	q.	q.	PROPN
cana-1860	203	50	wang	wang	PROPN
cana-1860	203	51	,	,	PUNCT
cana-1860	203	52	z.	z.	PROPN
cana-1860	203	53	yu	yu	PROPN
cana-1860	203	54	and	and	CCONJ
cana-1860	203	55	l.	l.	PROPN
cana-1860	203	56	cao	cao	PROPN
cana-1860	203	57	,	,	PUNCT
cana-1860	203	58	"	"	PUNCT
cana-1860	203	59	coupledmuts	coupledmut	NOUN
cana-1860	203	60	:	:	PUNCT
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cana-1860	203	62	multivariate	multivariate	NOUN
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cana-1860	203	75	of	of	ADP
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cana-1860	203	79	vol	vol	NOUN
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cana-1860	203	82	,	,	PUNCT
cana-1860	203	83	no	no	INTJ
cana-1860	203	84	.	.	NOUN
cana-1860	203	85	22	22	NUM
cana-1860	203	86	,	,	PUNCT
cana-1860	203	87	pp	pp	ADJ
cana-1860	203	88	.	.	PUNCT
cana-1860	204	1	22972	22972	NUM
cana-1860	204	2	-	-	SYM
cana-1860	204	3	22982	22982	NUM
cana-1860	204	4	,	,	PUNCT
cana-1860	204	5	15	15	NUM
cana-1860	204	6	nov.15	nov.15	NOUN
cana-1860	204	7	,	,	PUNCT
cana-1860	204	8	2022	2022	NUM
cana-1860	204	9	,	,	PUNCT
cana-1860	204	10	doi	doi	NOUN
cana-1860	204	11	:	:	PUNCT
cana-1860	204	12	10.1109	10.1109	NUM
cana-1860	204	13	/	/	SYM
cana-1860	204	14	jiot.2022.3185010	jiot.2022.3185010	NOUN
cana-1860	204	15	.	.	PUNCT
cana-1860	205	1	keywords	keyword	NOUN
cana-1860	205	2	:	:	PUNCT
cana-1860	205	3	{	{	PUNCT
cana-1860	205	4	couplings;time	couplings;time	PROPN
cana-1860	205	5	series	series	PROPN
cana-1860	205	6	analysis;sensors;internet	analysis;sensors;internet	PROPN
cana-1860	205	7	of	of	ADP
cana-1860	205	8	things;correlation;predictive	things;correlation;predictive	ADJ
cana-1860	205	9	models;tensors;coupling	models;tensors;couple	VERB
cana-1860	205	10	relational	relational	ADJ
cana-1860	205	11	learning;multivariate	learning;multivariate	ADJ
cana-1860	205	12	utility	utility	NOUN
cana-1860	205	13	time	time	NOUN
cana-1860	205	14	series	series	NOUN
cana-1860	205	15	(	(	PUNCT
cana-1860	205	16	muts);sensory	muts);sensory	PROPN
cana-1860	205	17	data	datum	NOUN
cana-1860	205	18	modeling;smart	modeling;smart	NOUN
cana-1860	205	19	cities;utility	cities;utility	NOUN
cana-1860	205	20	demand	demand	NOUN
cana-1860	205	21	prediction	prediction	NOUN
cana-1860	205	22	}	}	PUNCT
cana-1860	205	23	,	,	PUNCT
cana-1860	205	24	[	[	X
cana-1860	205	25	15	15	NUM
cana-1860	205	26	]	]	PUNCT
cana-1860	205	27	k.	k.	PROPN
cana-1860	205	28	yuan	yuan	PROPN
cana-1860	205	29	,	,	PUNCT
cana-1860	205	30	k.	k.	PROPN
cana-1860	205	31	wu	wu	PROPN
cana-1860	205	32	and	and	CCONJ
cana-1860	205	33	j.	j.	PROPN
cana-1860	205	34	liu	liu	PROPN
cana-1860	205	35	,	,	PUNCT
cana-1860	205	36	"	"	PUNCT
cana-1860	205	37	is	be	AUX
cana-1860	205	38	single	single	ADJ
cana-1860	205	39	enough	enough	ADV
cana-1860	205	40	?	?	PUNCT
cana-1860	206	1	a	a	DET
cana-1860	206	2	joint	joint	ADJ
cana-1860	206	3	spatiotemporal	spatiotemporal	ADJ
cana-1860	206	4	feature	feature	NOUN
cana-1860	206	5	learning	learn	VERB
cana-1860	206	6	framework	framework	NOUN
cana-1860	206	7	for	for	ADP
cana-1860	206	8	multivariate	multivariate	NOUN
cana-1860	206	9	time	time	NOUN
cana-1860	206	10	series	series	PROPN
cana-1860	206	11	prediction	prediction	NOUN
cana-1860	206	12	,	,	PUNCT
cana-1860	206	13	"	"	PUNCT
cana-1860	206	14	in	in	ADP
cana-1860	206	15	ieee	ieee	NOUN
cana-1860	206	16	transactions	transaction	NOUN
cana-1860	206	17	on	on	ADP
cana-1860	206	18	neural	neural	ADJ
cana-1860	206	19	networks	network	NOUN
cana-1860	206	20	and	and	CCONJ
cana-1860	206	21	learning	learning	NOUN
cana-1860	206	22	systems	system	NOUN
cana-1860	206	23	,	,	PUNCT
cana-1860	206	24	vol	vol	NOUN
cana-1860	206	25	.	.	PROPN
cana-1860	206	26	35	35	NUM
cana-1860	206	27	,	,	PUNCT
cana-1860	206	28	no	no	INTJ
cana-1860	206	29	.	.	NOUN
cana-1860	206	30	4	4	NUM
cana-1860	206	31	,	,	PUNCT
cana-1860	206	32	pp	pp	ADJ
cana-1860	206	33	.	.	PUNCT
cana-1860	206	34	4985	4985	NUM
cana-1860	206	35	-	-	SYM
cana-1860	206	36	4998	4998	NUM
cana-1860	206	37	,	,	PUNCT
cana-1860	206	38	april	april	PROPN
cana-1860	206	39	2024	2024	NUM
cana-1860	206	40	,	,	PUNCT
cana-1860	206	41	doi	doi	NOUN
cana-1860	206	42	:	:	PUNCT
cana-1860	206	43	10.1109	10.1109	NUM
cana-1860	206	44	/	/	SYM
cana-1860	206	45	tnnls.2022.3216107	tnnls.2022.3216107	NOUN
cana-1860	206	46	.	.	PUNCT
cana-1860	207	1	keywords	keyword	NOUN
cana-1860	207	2	:	:	PUNCT
cana-1860	207	3	{	{	PUNCT
cana-1860	207	4	time	time	NOUN
cana-1860	207	5	series	series	PROPN
cana-1860	207	6	analysis;feature	analysis;feature	PROPN
cana-1860	207	7	extraction;spatiotemporal	extraction;spatiotemporal	DET
cana-1860	207	8	phenomena;correlation;representation	phenomena;correlation;representation	NOUN
cana-1860	207	9	learning;predictive	learning;predictive	PROPN
cana-1860	207	10	models;prediction	models;prediction	PROPN
cana-1860	207	11	algorithms;fuzzy	algorithms;fuzzy	PROPN
cana-1860	207	12	cognitive	cognitive	ADJ
cana-1860	207	13	maps	map	NOUN
cana-1860	207	14	(	(	PUNCT
cana-1860	207	15	fcms);fuzzy	fcms);fuzzy	ADJ
cana-1860	207	16	neural	neural	ADJ
cana-1860	207	17	network;multivariate	network;multivariate	PROPN
cana-1860	207	18	time	time	NOUN
cana-1860	207	19	series	series	NOUN
cana-1860	207	20	prediction	prediction	NOUN
cana-1860	207	21	(	(	PUNCT
cana-1860	207	22	tsp);sparse	tsp);sparse	NOUN
cana-1860	207	23	autoencoder	autoencoder	NOUN
cana-1860	207	24	(	(	PUNCT
cana-1860	207	25	sae);spatiotemporal	sae);spatiotemporal	ADJ
cana-1860	207	26	features	feature	NOUN
cana-1860	207	27	}	}	PUNCT
cana-1860	207	28	,	,	PUNCT