id	sid	tid	token	lemma	pos
fcis-28393	1	1	frontiers	frontier	NOUN
fcis-28393	1	2	in	in	ADP
fcis-28393	1	3	computing	computing	NOUN
fcis-28393	1	4	and	and	CCONJ
fcis-28393	1	5	intelligent	intelligent	ADJ
fcis-28393	1	6	systems	system	NOUN
fcis-28393	1	7	issn	issn	VERB
fcis-28393	1	8	:	:	PUNCT
fcis-28393	1	9	2832	2832	NUM
fcis-28393	1	10	-	-	SYM
fcis-28393	1	11	6024	6024	NUM
fcis-28393	1	12	|	|	NOUN
fcis-28393	1	13	vol	vol	NOUN
fcis-28393	1	14	.	.	PROPN
fcis-28393	2	1	10	10	NUM
fcis-28393	2	2	,	,	PUNCT
fcis-28393	2	3	no	no	INTJ
fcis-28393	2	4	.	.	NOUN
fcis-28393	2	5	3	3	NUM
fcis-28393	2	6	,	,	PUNCT
fcis-28393	2	7	2024	2024	NUM
fcis-28393	2	8	48	48	NUM
fcis-28393	2	9	prediction	prediction	NOUN
fcis-28393	2	10	of	of	ADP
fcis-28393	2	11	runoff	runoff	NOUN
fcis-28393	2	12	in	in	ADP
fcis-28393	2	13	huayuankou	huayuankou	NOUN
fcis-28393	2	14	of	of	ADP
fcis-28393	2	15	the	the	DET
fcis-28393	2	16	yellow	yellow	PROPN
fcis-28393	2	17	river	river	NOUN
fcis-28393	2	18	based	base	VERB
fcis-28393	2	19	on	on	ADP
fcis-28393	2	20	autoformer‐lstm	autoformer‐lstm	PROPN
fcis-28393	2	21	feifei	feifei	PROPN
fcis-28393	2	22	yu	yu	PROPN
fcis-28393	2	23	school	school	PROPN
fcis-28393	2	24	of	of	ADP
fcis-28393	2	25	mathematics	mathematic	NOUN
fcis-28393	2	26	and	and	CCONJ
fcis-28393	2	27	statistics	statistic	NOUN
fcis-28393	2	28	,	,	PUNCT
fcis-28393	2	29	north	north	PROPN
fcis-28393	2	30	china	china	PROPN
fcis-28393	2	31	university	university	PROPN
fcis-28393	2	32	of	of	ADP
fcis-28393	2	33	water	water	NOUN
fcis-28393	2	34	resources	resource	NOUN
fcis-28393	2	35	and	and	CCONJ
fcis-28393	2	36	electric	electric	ADJ
fcis-28393	2	37	power	power	NOUN
fcis-28393	2	38	,	,	PUNCT
fcis-28393	2	39	zhengzhou	zhengzhou	PROPN
fcis-28393	2	40	henan	henan	PROPN
fcis-28393	2	41	,	,	PUNCT
fcis-28393	2	42	450046	450046	NUM
fcis-28393	2	43	,	,	PUNCT
fcis-28393	2	44	china	china	PROPN
fcis-28393	2	45	abstract	abstract	NOUN
fcis-28393	2	46	:	:	PUNCT
fcis-28393	2	47	to	to	PART
fcis-28393	2	48	effectively	effectively	ADV
fcis-28393	2	49	extract	extract	VERB
fcis-28393	2	50	information	information	NOUN
fcis-28393	2	51	features	feature	NOUN
fcis-28393	2	52	of	of	ADP
fcis-28393	2	53	runoff	runoff	NOUN
fcis-28393	2	54	time	time	NOUN
fcis-28393	2	55	series	series	NOUN
fcis-28393	2	56	and	and	CCONJ
fcis-28393	2	57	improve	improve	VERB
fcis-28393	2	58	the	the	DET
fcis-28393	2	59	accuracy	accuracy	NOUN
fcis-28393	2	60	of	of	ADP
fcis-28393	2	61	river	river	NOUN
fcis-28393	2	62	runoff	runoff	NOUN
fcis-28393	2	63	prediction	prediction	NOUN
fcis-28393	2	64	methods	method	NOUN
fcis-28393	2	65	.	.	PUNCT
fcis-28393	3	1	we	we	PRON
fcis-28393	3	2	integrated	integrate	VERB
fcis-28393	3	3	autoformer	autoformer	NOUN
fcis-28393	3	4	with	with	ADP
fcis-28393	3	5	long	long	ADJ
fcis-28393	3	6	short	short	ADJ
fcis-28393	3	7	-	-	PUNCT
fcis-28393	3	8	term	term	NOUN
fcis-28393	3	9	memory	memory	NOUN
fcis-28393	3	10	(	(	PUNCT
fcis-28393	3	11	lstm	lstm	NOUN
fcis-28393	3	12	)	)	PUNCT
fcis-28393	3	13	to	to	PART
fcis-28393	3	14	develop	develop	VERB
fcis-28393	3	15	an	an	DET
fcis-28393	3	16	autoformer	autoformer	NOUN
fcis-28393	3	17	-	-	PUNCT
fcis-28393	3	18	lstm	lstm	ADJ
fcis-28393	3	19	runoff	runoff	NOUN
fcis-28393	3	20	prediction	prediction	NOUN
fcis-28393	3	21	model	model	NOUN
fcis-28393	3	22	.	.	PUNCT
fcis-28393	4	1	we	we	PRON
fcis-28393	4	2	simulated	simulate	VERB
fcis-28393	4	3	and	and	CCONJ
fcis-28393	4	4	validated	validate	VERB
fcis-28393	4	5	the	the	DET
fcis-28393	4	6	model	model	NOUN
fcis-28393	4	7	using	use	VERB
fcis-28393	4	8	daily	daily	ADJ
fcis-28393	4	9	runoff	runoff	NOUN
fcis-28393	4	10	,	,	PUNCT
fcis-28393	4	11	precipitation	precipitation	NOUN
fcis-28393	4	12	,	,	PUNCT
fcis-28393	4	13	and	and	CCONJ
fcis-28393	4	14	average	average	ADJ
fcis-28393	4	15	water	water	NOUN
fcis-28393	4	16	level	level	NOUN
fcis-28393	4	17	data	datum	NOUN
fcis-28393	4	18	from	from	ADP
fcis-28393	4	19	january	january	PROPN
fcis-28393	4	20	1	1	NUM
fcis-28393	4	21	,	,	PUNCT
fcis-28393	4	22	2002	2002	NUM
fcis-28393	4	23	,	,	PUNCT
fcis-28393	4	24	to	to	ADP
fcis-28393	4	25	december	december	PROPN
fcis-28393	4	26	31	31	NUM
fcis-28393	4	27	,	,	PUNCT
fcis-28393	4	28	2022	2022	NUM
fcis-28393	4	29	,	,	PUNCT
fcis-28393	4	30	at	at	ADP
fcis-28393	4	31	huayuankou	huayuankou	NOUN
fcis-28393	4	32	hydrological	hydrological	ADJ
fcis-28393	4	33	station	station	NOUN
fcis-28393	4	34	,	,	PUNCT
fcis-28393	4	35	a	a	DET
fcis-28393	4	36	key	key	ADJ
fcis-28393	4	37	station	station	NOUN
fcis-28393	4	38	in	in	ADP
fcis-28393	4	39	the	the	DET
fcis-28393	4	40	lower	low	ADJ
fcis-28393	4	41	yellow	yellow	ADJ
fcis-28393	4	42	river	river	NOUN
fcis-28393	4	43	basin	basin	NOUN
fcis-28393	4	44	.	.	PUNCT
fcis-28393	5	1	and	and	CCONJ
fcis-28393	5	2	select	select	VERB
fcis-28393	5	3	autoformer	autoformer	PROPN
fcis-28393	5	4	model	model	NOUN
fcis-28393	5	5	,	,	PUNCT
fcis-28393	5	6	transformer	transformer	NOUN
fcis-28393	5	7	model	model	NOUN
fcis-28393	5	8	,	,	PUNCT
fcis-28393	5	9	and	and	CCONJ
fcis-28393	5	10	informer	informer	ADJ
fcis-28393	5	11	model	model	NOUN
fcis-28393	5	12	for	for	ADP
fcis-28393	5	13	comparative	comparative	ADJ
fcis-28393	5	14	prediction	prediction	NOUN
fcis-28393	5	15	experiments	experiment	NOUN
fcis-28393	5	16	.	.	PUNCT
fcis-28393	6	1	the	the	DET
fcis-28393	6	2	results	result	NOUN
fcis-28393	6	3	show	show	VERB
fcis-28393	6	4	that	that	SCONJ
fcis-28393	6	5	the	the	DET
fcis-28393	6	6	autoformer	autoformer	NOUN
fcis-28393	6	7	-	-	PUNCT
fcis-28393	6	8	lstm	lstm	PROPN
fcis-28393	6	9	and	and	CCONJ
fcis-28393	6	10	autoformer	autoformer	NOUN
fcis-28393	6	11	models	model	NOUN
fcis-28393	6	12	outperformed	outperform	VERB
fcis-28393	6	13	the	the	DET
fcis-28393	6	14	transformer	transformer	NOUN
fcis-28393	6	15	and	and	CCONJ
fcis-28393	6	16	informer	informer	NOUN
fcis-28393	6	17	models	model	NOUN
fcis-28393	6	18	in	in	ADP
fcis-28393	6	19	predictive	predictive	ADJ
fcis-28393	6	20	accuracy	accuracy	NOUN
fcis-28393	6	21	.	.	PUNCT
fcis-28393	7	1	furthermore	furthermore	ADV
fcis-28393	7	2	,	,	PUNCT
fcis-28393	7	3	compared	compare	VERB
fcis-28393	7	4	to	to	ADP
fcis-28393	7	5	the	the	DET
fcis-28393	7	6	autoformer	autoformer	PROPN
fcis-28393	7	7	model	model	NOUN
fcis-28393	7	8	,	,	PUNCT
fcis-28393	7	9	the	the	DET
fcis-28393	7	10	autoformer	autoformer	NOUN
fcis-28393	7	11	-	-	PUNCT
fcis-28393	7	12	lstm	lstm	PROPN
fcis-28393	7	13	model	model	NOUN
fcis-28393	7	14	reduced	reduce	VERB
fcis-28393	7	15	mean	mean	VERB
fcis-28393	7	16	absolute	absolute	ADJ
fcis-28393	7	17	error	error	NOUN
fcis-28393	7	18	(	(	PUNCT
fcis-28393	7	19	mae	mae	PROPN
fcis-28393	7	20	)	)	PUNCT
fcis-28393	7	21	,	,	PUNCT
fcis-28393	7	22	mean	mean	VERB
fcis-28393	7	23	squared	square	VERB
fcis-28393	7	24	error	error	NOUN
fcis-28393	7	25	(	(	PUNCT
fcis-28393	7	26	mse	mse	NOUN
fcis-28393	7	27	)	)	PUNCT
fcis-28393	7	28	,	,	PUNCT
fcis-28393	7	29	and	and	CCONJ
fcis-28393	7	30	root	root	NOUN
fcis-28393	7	31	mean	mean	VERB
fcis-28393	7	32	squared	square	VERB
fcis-28393	7	33	error	error	NOUN
fcis-28393	7	34	(	(	PUNCT
fcis-28393	7	35	rmse	rmse	NOUN
fcis-28393	7	36	)	)	PUNCT
fcis-28393	7	37	by	by	ADP
fcis-28393	7	38	13.1	13.1	NUM
fcis-28393	7	39	%	%	NOUN
fcis-28393	7	40	,	,	PUNCT
fcis-28393	7	41	78.7	78.7	NUM
fcis-28393	7	42	%	%	NOUN
fcis-28393	7	43	,	,	PUNCT
fcis-28393	7	44	and	and	CCONJ
fcis-28393	7	45	53.9	53.9	NUM
fcis-28393	7	46	%	%	NOUN
fcis-28393	7	47	.	.	PUNCT
fcis-28393	8	1	this	this	DET
fcis-28393	8	2	prediction	prediction	NOUN
fcis-28393	8	3	method	method	NOUN
fcis-28393	8	4	can	can	AUX
fcis-28393	8	5	fully	fully	ADV
fcis-28393	8	6	explore	explore	VERB
fcis-28393	8	7	the	the	DET
fcis-28393	8	8	inherent	inherent	ADJ
fcis-28393	8	9	laws	law	NOUN
fcis-28393	8	10	of	of	ADP
fcis-28393	8	11	hydrological	hydrological	ADJ
fcis-28393	8	12	time	time	NOUN
fcis-28393	8	13	series	series	PROPN
fcis-28393	8	14	data	data	PROPN
fcis-28393	8	15	,	,	PUNCT
fcis-28393	8	16	effectively	effectively	ADV
fcis-28393	8	17	utilize	utilize	VERB
fcis-28393	8	18	the	the	DET
fcis-28393	8	19	temporal	temporal	ADJ
fcis-28393	8	20	nature	nature	NOUN
fcis-28393	8	21	of	of	ADP
fcis-28393	8	22	hydrological	hydrological	ADJ
fcis-28393	8	23	information	information	NOUN
fcis-28393	8	24	,	,	PUNCT
fcis-28393	8	25	and	and	CCONJ
fcis-28393	8	26	improve	improve	VERB
fcis-28393	8	27	prediction	prediction	NOUN
fcis-28393	8	28	accuracy	accuracy	NOUN
fcis-28393	8	29	.	.	PUNCT
fcis-28393	9	1	keywords	keyword	NOUN
fcis-28393	9	2	:	:	PUNCT
fcis-28393	9	3	time	time	NOUN
fcis-28393	9	4	series	series	PROPN
fcis-28393	9	5	prediction	prediction	PROPN
fcis-28393	9	6	;	;	PUNCT
fcis-28393	9	7	autoformer	autoformer	NOUN
fcis-28393	9	8	;	;	PUNCT
fcis-28393	9	9	lstm	lstm	NOUN
fcis-28393	9	10	;	;	PUNCT
fcis-28393	9	11	huayuankou	huayuankou	NOUN
fcis-28393	9	12	hydrological	hydrological	ADJ
fcis-28393	9	13	station	station	NOUN
fcis-28393	9	14	.	.	PUNCT
fcis-28393	10	1	1	1	X
fcis-28393	10	2	.	.	X
fcis-28393	10	3	introduction	introduction	NOUN
fcis-28393	10	4	as	as	ADP
fcis-28393	10	5	one	one	NUM
fcis-28393	10	6	of	of	ADP
fcis-28393	10	7	the	the	DET
fcis-28393	10	8	core	core	NOUN
fcis-28393	10	9	issues	issue	NOUN
fcis-28393	10	10	in	in	ADP
fcis-28393	10	11	the	the	DET
fcis-28393	10	12	field	field	NOUN
fcis-28393	10	13	of	of	ADP
fcis-28393	10	14	hydrological	hydrological	ADJ
fcis-28393	10	15	prediction	prediction	NOUN
fcis-28393	10	16	,	,	PUNCT
fcis-28393	10	17	the	the	DET
fcis-28393	10	18	improvement	improvement	NOUN
fcis-28393	10	19	of	of	ADP
fcis-28393	10	20	runoff	runoff	NOUN
fcis-28393	10	21	prediction	prediction	NOUN
fcis-28393	10	22	accuracy	accuracy	NOUN
fcis-28393	10	23	is	be	AUX
fcis-28393	10	24	very	very	ADV
fcis-28393	10	25	important	important	ADJ
fcis-28393	10	26	for	for	ADP
fcis-28393	10	27	water	water	NOUN
fcis-28393	10	28	resources	resource	NOUN
fcis-28393	10	29	management	management	NOUN
fcis-28393	10	30	,	,	PUNCT
fcis-28393	10	31	optimal	optimal	ADJ
fcis-28393	10	32	allocation	allocation	NOUN
fcis-28393	10	33	of	of	ADP
fcis-28393	10	34	water	water	NOUN
fcis-28393	10	35	resources	resource	NOUN
fcis-28393	10	36	and	and	CCONJ
fcis-28393	10	37	drought	drought	NOUN
fcis-28393	10	38	and	and	CCONJ
fcis-28393	10	39	flood	flood	NOUN
fcis-28393	10	40	risk	risk	NOUN
fcis-28393	10	41	warning	warning	NOUN
fcis-28393	10	42	.	.	PUNCT
fcis-28393	11	1	the	the	DET
fcis-28393	11	2	formation	formation	NOUN
fcis-28393	11	3	mechanism	mechanism	NOUN
fcis-28393	11	4	of	of	ADP
fcis-28393	11	5	runoff	runoff	NOUN
fcis-28393	11	6	is	be	AUX
fcis-28393	11	7	affected	affect	VERB
fcis-28393	11	8	by	by	ADP
fcis-28393	11	9	environmental	environmental	ADJ
fcis-28393	11	10	topography	topography	NOUN
fcis-28393	11	11	,	,	PUNCT
fcis-28393	11	12	climate	climate	NOUN
fcis-28393	11	13	change	change	NOUN
fcis-28393	11	14	and	and	CCONJ
fcis-28393	11	15	human	human	ADJ
fcis-28393	11	16	activities	activity	NOUN
fcis-28393	11	17	,	,	PUNCT
fcis-28393	11	18	showing	show	VERB
fcis-28393	11	19	significant	significant	ADJ
fcis-28393	11	20	nonlinear	nonlinear	ADJ
fcis-28393	11	21	and	and	CCONJ
fcis-28393	11	22	non	non	ADJ
fcis-28393	11	23	-	-	ADJ
fcis-28393	11	24	stationary	stationary	ADJ
fcis-28393	11	25	characteristics	characteristic	NOUN
fcis-28393	11	26	,	,	PUNCT
fcis-28393	11	27	which	which	PRON
fcis-28393	11	28	makes	make	VERB
fcis-28393	11	29	the	the	DET
fcis-28393	11	30	study	study	NOUN
fcis-28393	11	31	of	of	ADP
fcis-28393	11	32	runoff	runoff	NOUN
fcis-28393	11	33	time	time	NOUN
fcis-28393	11	34	series	series	PROPN
fcis-28393	11	35	face	face	VERB
fcis-28393	11	36	complex	complex	ADJ
fcis-28393	11	37	and	and	CCONJ
fcis-28393	11	38	fuzzy	fuzzy	ADJ
fcis-28393	11	39	uncertainty[1	uncertainty[1	NOUN
fcis-28393	11	40	]	]	PUNCT
fcis-28393	11	41	.	.	PUNCT
fcis-28393	12	1	in	in	ADP
fcis-28393	12	2	order	order	NOUN
fcis-28393	12	3	to	to	PART
fcis-28393	12	4	improve	improve	VERB
fcis-28393	12	5	the	the	DET
fcis-28393	12	6	accuracy	accuracy	NOUN
fcis-28393	12	7	of	of	ADP
fcis-28393	12	8	runoff	runoff	NOUN
fcis-28393	12	9	prediction	prediction	NOUN
fcis-28393	12	10	,	,	PUNCT
fcis-28393	12	11	domestic	domestic	ADJ
fcis-28393	12	12	and	and	CCONJ
fcis-28393	12	13	foreign	foreign	ADJ
fcis-28393	12	14	scholars	scholar	NOUN
fcis-28393	12	15	have	have	AUX
fcis-28393	12	16	proposed	propose	VERB
fcis-28393	12	17	a	a	DET
fcis-28393	12	18	variety	variety	NOUN
fcis-28393	12	19	of	of	ADP
fcis-28393	12	20	prediction	prediction	NOUN
fcis-28393	12	21	models	model	NOUN
fcis-28393	12	22	,	,	PUNCT
fcis-28393	12	23	which	which	PRON
fcis-28393	12	24	can	can	AUX
fcis-28393	12	25	be	be	AUX
fcis-28393	12	26	broadly	broadly	ADV
fcis-28393	12	27	categorized	categorize	VERB
fcis-28393	12	28	into	into	ADP
fcis-28393	12	29	process	process	NOUN
fcis-28393	12	30	-	-	PUNCT
fcis-28393	12	31	driven	drive	VERB
fcis-28393	12	32	and	and	CCONJ
fcis-28393	12	33	data	data	NOUN
fcis-28393	12	34	-	-	PUNCT
fcis-28393	12	35	driven	drive	VERB
fcis-28393	12	36	models	model	NOUN
fcis-28393	12	37	based	base	VERB
fcis-28393	12	38	on	on	ADP
fcis-28393	12	39	their	their	PRON
fcis-28393	12	40	construction	construction	NOUN
fcis-28393	12	41	bases	basis	NOUN
fcis-28393	12	42	and	and	CCONJ
fcis-28393	12	43	core	core	NOUN
fcis-28393	12	44	logic[2	logic[2	NOUN
fcis-28393	12	45	]	]	X
fcis-28393	12	46	.	.	PUNCT
fcis-28393	13	1	the	the	DET
fcis-28393	13	2	process	process	NOUN
fcis-28393	13	3	-	-	PUNCT
fcis-28393	13	4	driven	drive	VERB
fcis-28393	13	5	model	model	NOUN
fcis-28393	13	6	relies	rely	VERB
fcis-28393	13	7	on	on	ADP
fcis-28393	13	8	detailed	detailed	ADJ
fcis-28393	13	9	hydrological	hydrological	ADJ
fcis-28393	13	10	and	and	CCONJ
fcis-28393	13	11	meteorological	meteorological	ADJ
fcis-28393	13	12	data	datum	NOUN
fcis-28393	13	13	and	and	CCONJ
fcis-28393	13	14	needs	need	NOUN
fcis-28393	13	15	to	to	PART
fcis-28393	13	16	consider	consider	VERB
fcis-28393	13	17	the	the	DET
fcis-28393	13	18	characteristics	characteristic	NOUN
fcis-28393	13	19	of	of	ADP
fcis-28393	13	20	spatial	spatial	ADJ
fcis-28393	13	21	and	and	CCONJ
fcis-28393	13	22	temporal	temporal	ADJ
fcis-28393	13	23	changes	change	NOUN
fcis-28393	13	24	,	,	PUNCT
fcis-28393	13	25	so	so	SCONJ
fcis-28393	13	26	it	it	PRON
fcis-28393	13	27	may	may	AUX
fcis-28393	13	28	face	face	VERB
fcis-28393	13	29	challenges	challenge	NOUN
fcis-28393	13	30	such	such	ADJ
fcis-28393	13	31	as	as	ADP
fcis-28393	13	32	insufficient	insufficient	ADJ
fcis-28393	13	33	generalization	generalization	NOUN
fcis-28393	13	34	ability	ability	NOUN
fcis-28393	13	35	and	and	CCONJ
fcis-28393	13	36	uncertainty	uncertainty	NOUN
fcis-28393	13	37	of	of	ADP
fcis-28393	13	38	parameter	parameter	PROPN
fcis-28393	13	39	setting[3	setting[3	PROPN
fcis-28393	13	40	]	]	PUNCT
fcis-28393	13	41	.	.	PUNCT
fcis-28393	14	1	however	however	ADV
fcis-28393	14	2	,	,	PUNCT
fcis-28393	14	3	data	data	NOUN
fcis-28393	14	4	-	-	PUNCT
fcis-28393	14	5	driven	drive	VERB
fcis-28393	14	6	models	model	NOUN
fcis-28393	14	7	do	do	AUX
fcis-28393	14	8	not	not	PART
fcis-28393	14	9	rely	rely	VERB
fcis-28393	14	10	on	on	ADP
fcis-28393	14	11	hydrological	hydrological	ADJ
fcis-28393	14	12	physical	physical	ADJ
fcis-28393	14	13	mechanisms	mechanism	NOUN
fcis-28393	14	14	and	and	CCONJ
fcis-28393	14	15	directly	directly	ADV
fcis-28393	14	16	utilize	utilize	VERB
fcis-28393	14	17	historical	historical	ADJ
fcis-28393	14	18	data	datum	NOUN
fcis-28393	14	19	of	of	ADP
fcis-28393	14	20	runoff	runoff	NOUN
fcis-28393	14	21	and	and	CCONJ
fcis-28393	14	22	its	its	PRON
fcis-28393	14	23	correlates	correlate	NOUN
fcis-28393	14	24	with	with	ADP
fcis-28393	14	25	the	the	DET
fcis-28393	14	26	goal	goal	NOUN
fcis-28393	14	27	of	of	ADP
fcis-28393	14	28	establishing	establish	VERB
fcis-28393	14	29	optimal	optimal	ADJ
fcis-28393	14	30	mathematical	mathematical	ADJ
fcis-28393	14	31	relationships	relationship	NOUN
fcis-28393	14	32	to	to	PART
fcis-28393	14	33	build	build	VERB
fcis-28393	14	34	a	a	DET
fcis-28393	14	35	black	black	ADJ
fcis-28393	14	36	-	-	PUNCT
fcis-28393	14	37	box	box	NOUN
fcis-28393	14	38	model	model	NOUN
fcis-28393	14	39	of	of	ADP
fcis-28393	14	40	the	the	DET
fcis-28393	14	41	relationship	relationship	NOUN
fcis-28393	14	42	between	between	ADP
fcis-28393	14	43	inputs	input	NOUN
fcis-28393	14	44	and	and	CCONJ
fcis-28393	14	45	outputs[4	outputs[4	NUM
fcis-28393	14	46	]	]	X
fcis-28393	14	47	.	.	PUNCT
fcis-28393	15	1	with	with	ADP
fcis-28393	15	2	the	the	DET
fcis-28393	15	3	increasing	increase	VERB
fcis-28393	15	4	maturity	maturity	NOUN
fcis-28393	15	5	of	of	ADP
fcis-28393	15	6	data	datum	NOUN
fcis-28393	15	7	science	science	NOUN
fcis-28393	15	8	and	and	CCONJ
fcis-28393	15	9	artificial	artificial	ADJ
fcis-28393	15	10	intelligence	intelligence	NOUN
fcis-28393	15	11	technology	technology	NOUN
fcis-28393	15	12	,	,	PUNCT
fcis-28393	15	13	data	data	NOUN
fcis-28393	15	14	-	-	PUNCT
fcis-28393	15	15	driven	drive	VERB
fcis-28393	15	16	model	model	NOUN
fcis-28393	15	17	provides	provide	VERB
fcis-28393	15	18	new	new	ADJ
fcis-28393	15	19	ideas	idea	NOUN
fcis-28393	15	20	and	and	CCONJ
fcis-28393	15	21	methods	method	NOUN
fcis-28393	15	22	for	for	ADP
fcis-28393	15	23	runoff	runoff	NOUN
fcis-28393	15	24	prediction	prediction	NOUN
fcis-28393	15	25	with	with	ADP
fcis-28393	15	26	its	its	PRON
fcis-28393	15	27	excellent	excellent	ADJ
fcis-28393	15	28	data	datum	NOUN
fcis-28393	15	29	processing	processing	NOUN
fcis-28393	15	30	ability	ability	NOUN
fcis-28393	15	31	and	and	CCONJ
fcis-28393	15	32	strong	strong	ADJ
fcis-28393	15	33	adaptive	adaptive	ADJ
fcis-28393	15	34	learning	learning	NOUN
fcis-28393	15	35	ability	ability	NOUN
fcis-28393	15	36	.	.	PUNCT
fcis-28393	16	1	for	for	ADP
fcis-28393	16	2	example	example	NOUN
fcis-28393	16	3	,	,	PUNCT
fcis-28393	16	4	in	in	ADP
fcis-28393	16	5	the	the	DET
fcis-28393	16	6	same	same	ADJ
fcis-28393	16	7	paper[5	paper[5	NOUN
fcis-28393	16	8	]	]	PUNCT
fcis-28393	16	9	,	,	PUNCT
fcis-28393	16	10	the	the	DET
fcis-28393	16	11	lstm	lstm	PROPN
fcis-28393	16	12	model	model	NOUN
fcis-28393	16	13	was	be	AUX
fcis-28393	16	14	established	establish	VERB
fcis-28393	16	15	by	by	ADP
fcis-28393	16	16	using	use	VERB
fcis-28393	16	17	the	the	DET
fcis-28393	16	18	measured	measured	ADJ
fcis-28393	16	19	daily	daily	ADJ
fcis-28393	16	20	runoff	runoff	NOUN
fcis-28393	16	21	of	of	ADP
fcis-28393	16	22	jingcun	jingcun	PROPN
fcis-28393	16	23	hydrological	hydrological	ADJ
fcis-28393	16	24	station	station	NOUN
fcis-28393	16	25	from	from	ADP
fcis-28393	16	26	1981	1981	NUM
fcis-28393	16	27	to	to	ADP
fcis-28393	16	28	2010	2010	NUM
fcis-28393	16	29	as	as	ADP
fcis-28393	16	30	a	a	DET
fcis-28393	16	31	sample	sample	NOUN
fcis-28393	16	32	,	,	PUNCT
fcis-28393	16	33	and	and	CCONJ
fcis-28393	16	34	the	the	DET
fcis-28393	16	35	effective	effective	ADJ
fcis-28393	16	36	prediction	prediction	NOUN
fcis-28393	16	37	of	of	ADP
fcis-28393	16	38	runoff	runoff	NOUN
fcis-28393	16	39	was	be	AUX
fcis-28393	16	40	realized	realize	VERB
fcis-28393	16	41	.	.	PUNCT
fcis-28393	17	1	based	base	VERB
fcis-28393	17	2	on	on	ADP
fcis-28393	17	3	the	the	DET
fcis-28393	17	4	historical	historical	ADJ
fcis-28393	17	5	observation	observation	NOUN
fcis-28393	17	6	data	datum	NOUN
fcis-28393	17	7	of	of	ADP
fcis-28393	17	8	huayuankou	huayuankou	NOUN
fcis-28393	17	9	hydrological	hydrological	ADJ
fcis-28393	17	10	station	station	NOUN
fcis-28393	17	11	,	,	PUNCT
fcis-28393	17	12	wang	wang	PROPN
fcis-28393	17	13	et	et	PROPN
fcis-28393	17	14	al.[3	al.[3	PROPN
fcis-28393	17	15	]	]	PUNCT
fcis-28393	17	16	established	establish	VERB
fcis-28393	17	17	a	a	DET
fcis-28393	17	18	multivariate	multivariate	NOUN
fcis-28393	17	19	runoff	runoff	NOUN
fcis-28393	17	20	prediction	prediction	NOUN
fcis-28393	17	21	model	model	NOUN
fcis-28393	17	22	of	of	ADP
fcis-28393	17	23	the	the	DET
fcis-28393	17	24	yellow	yellow	PROPN
fcis-28393	17	25	river	river	NOUN
fcis-28393	17	26	based	base	VERB
fcis-28393	17	27	on	on	ADP
fcis-28393	17	28	tcnattention	tcnattention	NOUN
fcis-28393	17	29	by	by	ADP
fcis-28393	17	30	integrating	integrate	VERB
fcis-28393	17	31	attention	attention	NOUN
fcis-28393	17	32	mechanism	mechanism	NOUN
fcis-28393	17	33	and	and	CCONJ
fcis-28393	17	34	time	time	NOUN
fcis-28393	17	35	convolutional	convolutional	ADJ
fcis-28393	17	36	neural	neural	ADJ
fcis-28393	17	37	network	network	NOUN
fcis-28393	17	38	.	.	PUNCT
fcis-28393	18	1	the	the	DET
fcis-28393	18	2	results	result	NOUN
fcis-28393	18	3	show	show	VERB
fcis-28393	18	4	that	that	SCONJ
fcis-28393	18	5	the	the	DET
fcis-28393	18	6	attention	attention	NOUN
fcis-28393	18	7	mechanism	mechanism	NOUN
fcis-28393	18	8	enhances	enhance	VERB
fcis-28393	18	9	the	the	DET
fcis-28393	18	10	prediction	prediction	NOUN
fcis-28393	18	11	accuracy	accuracy	NOUN
fcis-28393	18	12	of	of	ADP
fcis-28393	18	13	the	the	DET
fcis-28393	18	14	tcn	tcn	NOUN
fcis-28393	18	15	model	model	NOUN
fcis-28393	18	16	by	by	ADP
fcis-28393	18	17	optimizing	optimize	VERB
fcis-28393	18	18	the	the	DET
fcis-28393	18	19	feature	feature	NOUN
fcis-28393	18	20	weights	weight	NOUN
fcis-28393	18	21	.	.	PUNCT
fcis-28393	19	1	dou	dou	NOUN
fcis-28393	19	2	et	et	NOUN
fcis-28393	19	3	al.[6	al.[6	PROPN
fcis-28393	19	4	]	]	PUNCT
fcis-28393	19	5	applied	apply	VERB
fcis-28393	19	6	the	the	DET
fcis-28393	19	7	pca	pca	PROPN
fcis-28393	19	8	-	-	PUNCT
fcis-28393	19	9	mlp	mlp	PROPN
fcis-28393	19	10	neural	neural	ADJ
fcis-28393	19	11	network	network	NOUN
fcis-28393	19	12	model	model	NOUN
fcis-28393	19	13	to	to	ADP
fcis-28393	19	14	the	the	DET
fcis-28393	19	15	flood	flood	NOUN
fcis-28393	19	16	season	season	NOUN
fcis-28393	19	17	runoff	runoff	NOUN
fcis-28393	19	18	prediction	prediction	NOUN
fcis-28393	19	19	of	of	ADP
fcis-28393	19	20	the	the	DET
fcis-28393	19	21	ningxia	ningxia	PROPN
fcis-28393	19	22	section	section	NOUN
fcis-28393	19	23	of	of	ADP
fcis-28393	19	24	the	the	DET
fcis-28393	19	25	yellow	yellow	PROPN
fcis-28393	19	26	river	river	NOUN
fcis-28393	19	27	,	,	PUNCT
fcis-28393	19	28	which	which	PRON
fcis-28393	19	29	simplified	simplify	VERB
fcis-28393	19	30	the	the	DET
fcis-28393	19	31	model	model	NOUN
fcis-28393	19	32	structure	structure	NOUN
fcis-28393	19	33	of	of	ADP
fcis-28393	19	34	the	the	DET
fcis-28393	19	35	neural	neural	ADJ
fcis-28393	19	36	network	network	NOUN
fcis-28393	19	37	while	while	SCONJ
fcis-28393	19	38	improving	improve	VERB
fcis-28393	19	39	the	the	DET
fcis-28393	19	40	prediction	prediction	NOUN
fcis-28393	19	41	effect	effect	NOUN
fcis-28393	19	42	.	.	PUNCT
fcis-28393	20	1	these	these	DET
fcis-28393	20	2	models	model	NOUN
fcis-28393	20	3	have	have	AUX
fcis-28393	20	4	shown	show	VERB
fcis-28393	20	5	good	good	ADJ
fcis-28393	20	6	performance	performance	NOUN
fcis-28393	20	7	in	in	ADP
fcis-28393	20	8	predicting	predict	VERB
fcis-28393	20	9	runoff	runoff	NOUN
fcis-28393	20	10	,	,	PUNCT
fcis-28393	20	11	but	but	CCONJ
fcis-28393	20	12	the	the	DET
fcis-28393	20	13	extraction	extraction	NOUN
fcis-28393	20	14	of	of	ADP
fcis-28393	20	15	internal	internal	ADJ
fcis-28393	20	16	relations	relation	NOUN
fcis-28393	20	17	of	of	ADP
fcis-28393	20	18	complex	complex	ADJ
fcis-28393	20	19	runoff	runoff	NOUN
fcis-28393	20	20	time	time	NOUN
fcis-28393	20	21	series	series	NOUN
fcis-28393	20	22	is	be	AUX
fcis-28393	20	23	not	not	PART
fcis-28393	20	24	sufficient	sufficient	ADJ
fcis-28393	20	25	,	,	PUNCT
fcis-28393	20	26	and	and	CCONJ
fcis-28393	20	27	the	the	DET
fcis-28393	20	28	similarity	similarity	NOUN
fcis-28393	20	29	between	between	ADP
fcis-28393	20	30	runoff	runoff	NOUN
fcis-28393	20	31	subsequences	subsequence	NOUN
fcis-28393	20	32	is	be	AUX
fcis-28393	20	33	ignored	ignore	VERB
fcis-28393	20	34	,	,	PUNCT
fcis-28393	20	35	resulting	result	VERB
fcis-28393	20	36	in	in	ADP
fcis-28393	20	37	an	an	DET
fcis-28393	20	38	increase	increase	NOUN
fcis-28393	20	39	in	in	ADP
fcis-28393	20	40	errors	error	NOUN
fcis-28393	20	41	.	.	PUNCT
fcis-28393	21	1	in	in	ADP
fcis-28393	21	2	recent	recent	ADJ
fcis-28393	21	3	years	year	NOUN
fcis-28393	21	4	,	,	PUNCT
fcis-28393	21	5	the	the	DET
fcis-28393	21	6	autoformer	autoformer	NOUN
fcis-28393	21	7	model	model	NOUN
fcis-28393	21	8	has	have	AUX
fcis-28393	21	9	introduced	introduce	VERB
fcis-28393	21	10	a	a	DET
fcis-28393	21	11	time	time	NOUN
fcis-28393	21	12	series	series	NOUN
fcis-28393	21	13	decomposition	decomposition	NOUN
fcis-28393	21	14	architecture	architecture	NOUN
fcis-28393	21	15	with	with	ADP
fcis-28393	21	16	autocorrelation	autocorrelation	NOUN
fcis-28393	21	17	mechanism	mechanism	NOUN
fcis-28393	21	18	,	,	PUNCT
fcis-28393	21	19	which	which	PRON
fcis-28393	21	20	can	can	AUX
fcis-28393	21	21	discover	discover	VERB
fcis-28393	21	22	and	and	CCONJ
fcis-28393	21	23	represent	represent	VERB
fcis-28393	21	24	dependencies	dependency	NOUN
fcis-28393	21	25	at	at	ADP
fcis-28393	21	26	the	the	DET
fcis-28393	21	27	sub	sub	ADJ
fcis-28393	21	28	-	-	ADJ
fcis-28393	21	29	series	series	ADJ
fcis-28393	21	30	level	level	NOUN
fcis-28393	21	31	of	of	ADP
fcis-28393	21	32	the	the	DET
fcis-28393	21	33	same	same	ADJ
fcis-28393	21	34	phase[7	phase[7	NOUN
fcis-28393	21	35	]	]	PUNCT
fcis-28393	21	36	,	,	PUNCT
fcis-28393	21	37	so	so	SCONJ
fcis-28393	21	38	as	as	SCONJ
fcis-28393	21	39	to	to	PART
fcis-28393	21	40	obtain	obtain	VERB
fcis-28393	21	41	the	the	DET
fcis-28393	21	42	internal	internal	ADJ
fcis-28393	21	43	relationship	relationship	NOUN
fcis-28393	21	44	of	of	ADP
fcis-28393	21	45	complex	complex	ADJ
fcis-28393	21	46	time	time	NOUN
fcis-28393	21	47	series	series	NOUN
fcis-28393	21	48	more	more	ADV
fcis-28393	21	49	accurately	accurately	ADV
fcis-28393	21	50	.	.	PUNCT
fcis-28393	22	1	long	long	ADJ
fcis-28393	22	2	short	short	ADJ
fcis-28393	22	3	-	-	PUNCT
fcis-28393	22	4	term	term	NOUN
fcis-28393	22	5	memory	memory	NOUN
fcis-28393	22	6	(	(	PUNCT
fcis-28393	22	7	lstm	lstm	NOUN
fcis-28393	22	8	)	)	PUNCT
fcis-28393	22	9	network	network	NOUN
fcis-28393	22	10	uses	use	VERB
fcis-28393	22	11	multi	multi	ADJ
fcis-28393	22	12	-	-	ADJ
fcis-28393	22	13	gate	gate	ADJ
fcis-28393	22	14	mechanism	mechanism	NOUN
fcis-28393	22	15	to	to	PART
fcis-28393	22	16	effectively	effectively	ADV
fcis-28393	22	17	solve	solve	VERB
fcis-28393	22	18	the	the	DET
fcis-28393	22	19	common	common	ADJ
fcis-28393	22	20	gradient	gradient	NOUN
fcis-28393	22	21	disappearance	disappearance	NOUN
fcis-28393	22	22	problem	problem	NOUN
fcis-28393	22	23	of	of	ADP
fcis-28393	22	24	traditional	traditional	ADJ
fcis-28393	22	25	recurrent	recurrent	ADJ
fcis-28393	22	26	neural	neural	ADJ
fcis-28393	22	27	network	network	NOUN
fcis-28393	22	28	in	in	ADP
fcis-28393	22	29	processing	process	VERB
fcis-28393	22	30	long	long	ADJ
fcis-28393	22	31	sequence	sequence	NOUN
fcis-28393	22	32	data	datum	NOUN
fcis-28393	22	33	,	,	PUNCT
fcis-28393	22	34	and	and	CCONJ
fcis-28393	22	35	can	can	AUX
fcis-28393	22	36	effectively	effectively	ADV
fcis-28393	22	37	capture	capture	VERB
fcis-28393	22	38	and	and	CCONJ
fcis-28393	22	39	utilize	utilize	VERB
fcis-28393	22	40	various	various	ADJ
fcis-28393	22	41	patterns	pattern	NOUN
fcis-28393	22	42	and	and	CCONJ
fcis-28393	22	43	laws	law	NOUN
fcis-28393	22	44	in	in	ADP
fcis-28393	22	45	time	time	NOUN
fcis-28393	22	46	series	series	NOUN
fcis-28393	22	47	.	.	PUNCT
fcis-28393	23	1	it	it	PRON
fcis-28393	23	2	has	have	VERB
fcis-28393	23	3	obvious	obvious	ADJ
fcis-28393	23	4	advantages	advantage	NOUN
fcis-28393	23	5	in	in	ADP
fcis-28393	23	6	mining	mine	VERB
fcis-28393	23	7	long	long	ADJ
fcis-28393	23	8	-	-	PUNCT
fcis-28393	23	9	term	term	NOUN
fcis-28393	23	10	correlation	correlation	NOUN
fcis-28393	23	11	of	of	ADP
fcis-28393	23	12	time	time	NOUN
fcis-28393	23	13	series	series	PROPN
fcis-28393	23	14	data[8	data[8	PROPN
fcis-28393	23	15	]	]	PROPN
fcis-28393	23	16	.	.	PUNCT
fcis-28393	24	1	due	due	ADP
fcis-28393	24	2	to	to	ADP
fcis-28393	24	3	the	the	DET
fcis-28393	24	4	long	long	ADJ
fcis-28393	24	5	-	-	PUNCT
fcis-28393	24	6	time	time	NOUN
fcis-28393	24	7	dependence	dependence	NOUN
fcis-28393	24	8	in	in	ADP
fcis-28393	24	9	hydrological	hydrological	ADJ
fcis-28393	24	10	data	datum	NOUN
fcis-28393	24	11	,	,	PUNCT
fcis-28393	24	12	lstm	lstm	NOUN
fcis-28393	24	13	can	can	AUX
fcis-28393	24	14	capture	capture	VERB
fcis-28393	24	15	and	and	CCONJ
fcis-28393	24	16	utilize	utilize	VERB
fcis-28393	24	17	this	this	DET
fcis-28393	24	18	longterm	longterm	ADJ
fcis-28393	24	19	dependence	dependence	NOUN
fcis-28393	24	20	more	more	ADV
fcis-28393	24	21	effectively	effectively	ADV
fcis-28393	24	22	than	than	SCONJ
fcis-28393	24	23	feed	feed	VERB
fcis-28393	24	24	forward	forward	ADV
fcis-28393	24	25	through	through	ADP
fcis-28393	24	26	the	the	DET
fcis-28393	24	27	gating	gate	VERB
fcis-28393	24	28	mechanism	mechanism	NOUN
fcis-28393	24	29	,	,	PUNCT
fcis-28393	24	30	which	which	PRON
fcis-28393	24	31	is	be	AUX
fcis-28393	24	32	helpful	helpful	ADJ
fcis-28393	24	33	to	to	PART
fcis-28393	24	34	improve	improve	VERB
fcis-28393	24	35	the	the	DET
fcis-28393	24	36	accuracy	accuracy	NOUN
fcis-28393	24	37	of	of	ADP
fcis-28393	24	38	runoff	runoff	NOUN
fcis-28393	24	39	prediction	prediction	NOUN
fcis-28393	24	40	.	.	PUNCT
fcis-28393	25	1	therefore	therefore	ADV
fcis-28393	25	2	,	,	PUNCT
fcis-28393	25	3	this	this	DET
fcis-28393	25	4	paper	paper	NOUN
fcis-28393	25	5	proposes	propose	VERB
fcis-28393	25	6	a	a	DET
fcis-28393	25	7	runoff	runoff	NOUN
fcis-28393	25	8	prediction	prediction	NOUN
fcis-28393	25	9	model	model	NOUN
fcis-28393	25	10	based	base	VERB
fcis-28393	25	11	on	on	ADP
fcis-28393	25	12	autoformer	autoformer	NOUN
fcis-28393	25	13	-	-	PUNCT
fcis-28393	25	14	lstm	lstm	NOUN
fcis-28393	25	15	.	.	PUNCT
fcis-28393	26	1	the	the	DET
fcis-28393	26	2	measured	measure	VERB
fcis-28393	26	3	data	datum	NOUN
fcis-28393	26	4	of	of	ADP
fcis-28393	26	5	huayuankou	huayuankou	NOUN
fcis-28393	26	6	hydrological	hydrological	ADJ
fcis-28393	26	7	station	station	NOUN
fcis-28393	26	8	on	on	ADP
fcis-28393	26	9	the	the	DET
fcis-28393	26	10	yellow	yellow	PROPN
fcis-28393	26	11	river	river	NOUN
fcis-28393	26	12	from	from	ADP
fcis-28393	26	13	january	january	PROPN
fcis-28393	26	14	1,2002	1,2002	NUM
fcis-28393	26	15	to	to	ADP
fcis-28393	26	16	december	december	PROPN
fcis-28393	26	17	31,2022	31,2022	NUM
fcis-28393	26	18	were	be	AUX
fcis-28393	26	19	selected	select	VERB
fcis-28393	26	20	to	to	PART
fcis-28393	26	21	carry	carry	VERB
fcis-28393	26	22	out	out	ADP
fcis-28393	26	23	simulation	simulation	NOUN
fcis-28393	26	24	verification	verification	NOUN
fcis-28393	26	25	,	,	PUNCT
fcis-28393	26	26	and	and	CCONJ
fcis-28393	26	27	the	the	DET
fcis-28393	26	28	effectiveness	effectiveness	NOUN
fcis-28393	26	29	of	of	ADP
fcis-28393	26	30	various	various	ADJ
fcis-28393	26	31	runoff	runoff	NOUN
fcis-28393	26	32	prediction	prediction	NOUN
fcis-28393	26	33	models	model	NOUN
fcis-28393	26	34	was	be	AUX
fcis-28393	26	35	compared	compare	VERB
fcis-28393	26	36	and	and	CCONJ
fcis-28393	26	37	analyzed	analyze	VERB
fcis-28393	26	38	by	by	ADP
fcis-28393	26	39	ablation	ablation	NOUN
fcis-28393	26	40	method	method	NOUN
fcis-28393	26	41	.	.	PUNCT
fcis-28393	27	1	the	the	DET
fcis-28393	27	2	research	research	NOUN
fcis-28393	27	3	results	result	NOUN
fcis-28393	27	4	have	have	VERB
fcis-28393	27	5	important	important	ADJ
fcis-28393	27	6	reference	reference	NOUN
fcis-28393	27	7	value	value	NOUN
fcis-28393	27	8	for	for	ADP
fcis-28393	27	9	optimizing	optimize	VERB
fcis-28393	27	10	runoff	runoff	NOUN
fcis-28393	27	11	prediction	prediction	NOUN
fcis-28393	27	12	technology	technology	NOUN
fcis-28393	27	13	system	system	NOUN
fcis-28393	27	14	and	and	CCONJ
fcis-28393	27	15	scientific	scientific	ADJ
fcis-28393	27	16	management	management	NOUN
fcis-28393	27	17	of	of	ADP
fcis-28393	27	18	water	water	NOUN
fcis-28393	27	19	resources	resource	NOUN
fcis-28393	27	20	.	.	PUNCT
fcis-28393	28	1	2	2	X
fcis-28393	28	2	.	.	X
fcis-28393	28	3	research	research	NOUN
fcis-28393	28	4	method	method	NOUN
fcis-28393	28	5	2.1	2.1	NUM
fcis-28393	28	6	.	.	PUNCT
fcis-28393	29	1	autoformer	autoformer	PROPN
fcis-28393	29	2	model	model	VERB
fcis-28393	29	3	the	the	DET
fcis-28393	29	4	autoformer	autoformer	PROPN
fcis-28393	29	5	model	model	NOUN
fcis-28393	29	6	adopts	adopt	VERB
fcis-28393	29	7	the	the	DET
fcis-28393	29	8	design	design	NOUN
fcis-28393	29	9	architecture	architecture	NOUN
fcis-28393	29	10	of	of	ADP
fcis-28393	29	11	49	49	NUM
fcis-28393	29	12	encoder	encoder	NOUN
fcis-28393	29	13	-	-	PUNCT
fcis-28393	29	14	decoder	decoder	NOUN
fcis-28393	29	15	.	.	PUNCT
fcis-28393	30	1	the	the	DET
fcis-28393	30	2	encoder	encoder	NOUN
fcis-28393	30	3	is	be	AUX
fcis-28393	30	4	used	use	VERB
fcis-28393	30	5	to	to	PART
fcis-28393	30	6	encode	encode	VERB
fcis-28393	30	7	historical	historical	ADJ
fcis-28393	30	8	information	information	NOUN
fcis-28393	30	9	,	,	PUNCT
fcis-28393	30	10	and	and	CCONJ
fcis-28393	30	11	the	the	DET
fcis-28393	30	12	decoder	decoder	NOUN
fcis-28393	30	13	generates	generate	VERB
fcis-28393	30	14	future	future	ADJ
fcis-28393	30	15	long	long	ADJ
fcis-28393	30	16	sequence	sequence	NOUN
fcis-28393	30	17	prediction	prediction	NOUN
fcis-28393	30	18	.	.	PUNCT
fcis-28393	31	1	the	the	DET
fcis-28393	31	2	two	two	NUM
fcis-28393	31	3	are	be	AUX
fcis-28393	31	4	connected	connect	VERB
fcis-28393	31	5	by	by	ADP
fcis-28393	31	6	the	the	DET
fcis-28393	31	7	input	input	NOUN
fcis-28393	31	8	and	and	CCONJ
fcis-28393	31	9	output	output	NOUN
fcis-28393	31	10	of	of	ADP
fcis-28393	31	11	sequence	sequence	NOUN
fcis-28393	31	12	decomposition	decomposition	NOUN
fcis-28393	31	13	.	.	PUNCT
fcis-28393	32	1	the	the	DET
fcis-28393	32	2	core	core	NOUN
fcis-28393	32	3	mechanism	mechanism	NOUN
fcis-28393	32	4	sequence	sequence	NOUN
fcis-28393	32	5	decomposition	decomposition	NOUN
fcis-28393	32	6	and	and	CCONJ
fcis-28393	32	7	auto	auto	NOUN
fcis-28393	32	8	-	-	PUNCT
fcis-28393	32	9	correlation	correlation	NOUN
fcis-28393	32	10	mechanism	mechanism	NOUN
fcis-28393	32	11	are	be	AUX
fcis-28393	32	12	embedded	embed	VERB
fcis-28393	32	13	as	as	ADP
fcis-28393	32	14	independent	independent	ADJ
fcis-28393	32	15	modules	module	NOUN
fcis-28393	32	16	.	.	PUNCT
fcis-28393	33	1	(	(	PUNCT
fcis-28393	33	2	1	1	X
fcis-28393	33	3	)	)	PUNCT
fcis-28393	33	4	auto	auto	NOUN
fcis-28393	33	5	-	-	PUNCT
fcis-28393	33	6	correlation	correlation	NOUN
fcis-28393	33	7	mechanism	mechanism	NOUN
fcis-28393	33	8	the	the	DET
fcis-28393	33	9	auto	auto	NOUN
fcis-28393	33	10	-	-	PUNCT
fcis-28393	33	11	correlation	correlation	NOUN
fcis-28393	33	12	mechanism	mechanism	NOUN
fcis-28393	33	13	consists	consist	VERB
fcis-28393	33	14	of	of	ADP
fcis-28393	33	15	two	two	NUM
fcis-28393	33	16	parts	part	NOUN
fcis-28393	33	17	,	,	PUNCT
fcis-28393	33	18	one	one	NUM
fcis-28393	33	19	is	be	AUX
fcis-28393	33	20	the	the	DET
fcis-28393	33	21	cycle	cycle	NOUN
fcis-28393	33	22	-	-	PUNCT
fcis-28393	33	23	based	base	VERB
fcis-28393	33	24	dependency	dependency	NOUN
fcis-28393	33	25	discovery	discovery	NOUN
fcis-28393	33	26	,	,	PUNCT
fcis-28393	33	27	and	and	CCONJ
fcis-28393	33	28	the	the	DET
fcis-28393	33	29	other	other	ADJ
fcis-28393	33	30	is	be	AUX
fcis-28393	33	31	the	the	DET
fcis-28393	33	32	time	time	NOUN
fcis-28393	33	33	delay	delay	NOUN
fcis-28393	33	34	aggregation	aggregation	NOUN
fcis-28393	33	35	.	.	PUNCT
fcis-28393	34	1	based	base	VERB
fcis-28393	34	2	on	on	ADP
fcis-28393	34	3	the	the	DET
fcis-28393	34	4	theory	theory	NOUN
fcis-28393	34	5	of	of	ADP
fcis-28393	34	6	random	random	ADJ
fcis-28393	34	7	process	process	NOUN
fcis-28393	34	8	[	[	X
fcis-28393	34	9	9	9	NUM
fcis-28393	34	10	]	]	PUNCT
fcis-28393	34	11	,	,	PUNCT
fcis-28393	34	12	the	the	DET
fcis-28393	34	13	autocorrelation	autocorrelation	NOUN
fcis-28393	34	14	coefficient	coefficient	NOUN
fcis-28393	34	15	of	of	ADP
fcis-28393	34	16	the	the	DET
fcis-28393	34	17	discrete	discrete	ADJ
fcis-28393	34	18	time	time	NOUN
fcis-28393	34	19	process	process	NOUN
fcis-28393	34	20			PROPN
fcis-28393	34	21	tx	tx	NOUN
fcis-28393	34	22	can	can	AUX
fcis-28393	34	23	be	be	AUX
fcis-28393	34	24	obtained	obtain	VERB
fcis-28393	34	25	by	by	ADP
fcis-28393	34	26	the	the	DET
fcis-28393	34	27	following	follow	VERB
fcis-28393	34	28	formula	formula	NOUN
fcis-28393	34	29	.	.	PUNCT
fcis-28393	35	1	1	1	NUM
fcis-28393	35	2	1	1	NUM
fcis-28393	35	3	(	(	PUNCT
fcis-28393	35	4	)	)	PUNCT
fcis-28393	35	5	lim	lim	PROPN
fcis-28393	35	6	l	l	PROPN
fcis-28393	36	1	xx	xx	NUM
fcis-28393	37	1	t	t	X
fcis-28393	37	2	t	t	PROPN
fcis-28393	37	3	l	l	NOUN
fcis-28393	37	4	t	t	NOUN
fcis-28393	37	5	r	r	NOUN
fcis-28393	37	6	x	x	PUNCT
fcis-28393	37	7	x	x	X
fcis-28393	37	8	l	l	NOUN
fcis-28393	37	9			PUNCT
fcis-28393	37	10			NUM
fcis-28393	37	11			NUM
fcis-28393	37	12			NOUN
fcis-28393	37	13			X
fcis-28393	37	14	(	(	PUNCT
fcis-28393	37	15	1	1	X
fcis-28393	37	16	)	)	PUNCT
fcis-28393	37	17	where	where	SCONJ
fcis-28393	37	18	l	l	NOUN
fcis-28393	37	19	denotes	denote	VERB
fcis-28393	37	20	the	the	DET
fcis-28393	37	21	length	length	NOUN
fcis-28393	37	22	of	of	ADP
fcis-28393	37	23	tx	tx	PROPN
fcis-28393	37	24	,	,	PUNCT
fcis-28393	37	25	and	and	CCONJ
fcis-28393	37	26	(	(	PUNCT
fcis-28393	37	27	)	)	PUNCT
fcis-28393	37	28	xxr	xxr	PROPN
fcis-28393	37	29			PROPN
fcis-28393	37	30	denotes	denote	VERB
fcis-28393	37	31	the	the	DET
fcis-28393	37	32	time	time	NOUN
fcis-28393	37	33	delay	delay	NOUN
fcis-28393	37	34	similarity	similarity	NOUN
fcis-28393	37	35	between	between	ADP
fcis-28393	37	36	the	the	DET
fcis-28393	37	37	sequence	sequence	NOUN
fcis-28393	37	38			PROPN
fcis-28393	37	39	tx	tx	PROPN
fcis-28393	37	40	and	and	CCONJ
fcis-28393	37	41	its	its	PRON
fcis-28393	37	42	n	n	CCONJ
fcis-28393	37	43	-	-	PUNCT
fcis-28393	37	44	order	order	NOUN
fcis-28393	37	45	lagged	lag	VERB
fcis-28393	37	46	sequence	sequence	NOUN
fcis-28393	37	47			PROPN
fcis-28393	37	48	tx	tx	NOUN
fcis-28393	37	49			NUM
fcis-28393	37	50	.	.	PUNCT
fcis-28393	38	1	the	the	PRON
fcis-28393	38	2	higher	high	ADJ
fcis-28393	38	3	the	the	DET
fcis-28393	38	4	autocorrelation	autocorrelation	NOUN
fcis-28393	38	5	coefficient	coefficient	NOUN
fcis-28393	38	6	is	be	AUX
fcis-28393	38	7	,	,	PUNCT
fcis-28393	38	8	the	the	PRON
fcis-28393	38	9	more	more	ADV
fcis-28393	38	10	likely	likely	ADJ
fcis-28393	38	11	it	it	PRON
fcis-28393	38	12	is	be	AUX
fcis-28393	38	13	that	that	SCONJ
fcis-28393	38	14			NOUN
fcis-28393	38	15	is	be	AUX
fcis-28393	38	16	the	the	DET
fcis-28393	38	17	period	period	NOUN
fcis-28393	38	18	of	of	ADP
fcis-28393	38	19	the	the	DET
fcis-28393	38	20	input	input	NOUN
fcis-28393	38	21	,	,	PUNCT
fcis-28393	38	22	and	and	CCONJ
fcis-28393	38	23			NOUN
fcis-28393	38	24	r	r	DET
fcis-28393	38	25			NOUN
fcis-28393	38	26	can	can	AUX
fcis-28393	38	27	be	be	AUX
fcis-28393	38	28	regarded	regard	VERB
fcis-28393	38	29	as	as	ADP
fcis-28393	38	30	the	the	DET
fcis-28393	38	31	confidence	confidence	NOUN
fcis-28393	38	32	of	of	ADP
fcis-28393	38	33	the	the	DET
fcis-28393	38	34	unnormalized	unnormalized	ADJ
fcis-28393	38	35	period	period	NOUN
fcis-28393	38	36	estimation[10	estimation[10	NOUN
fcis-28393	38	37	]	]	PUNCT
fcis-28393	38	38	.	.	PUNCT
fcis-28393	39	1	in	in	ADP
fcis-28393	39	2	the	the	DET
fcis-28393	39	3	single	single	ADJ
fcis-28393	39	4	-	-	PUNCT
fcis-28393	39	5	head	head	NOUN
fcis-28393	39	6	autocorrelation	autocorrelation	NOUN
fcis-28393	39	7	mechanism	mechanism	NOUN
fcis-28393	39	8	,	,	PUNCT
fcis-28393	39	9	the	the	DET
fcis-28393	39	10	sequence	sequence	NOUN
fcis-28393	39	11	x	x	PUNCT
fcis-28393	39	12	with	with	ADP
fcis-28393	39	13	length	length	NOUN
fcis-28393	39	14	l	l	NOUN
fcis-28393	39	15	is	be	AUX
fcis-28393	39	16	mapped	map	VERB
fcis-28393	39	17	to	to	PART
fcis-28393	39	18	vectorsq	vectorsq	VERB
fcis-28393	39	19	,	,	PUNCT
fcis-28393	39	20	k	k	PROPN
fcis-28393	39	21	,	,	PUNCT
fcis-28393	39	22	and	and	CCONJ
fcis-28393	39	23	v	v	NOUN
fcis-28393	39	24	.	.	PUNCT
fcis-28393	40	1	then	then	ADV
fcis-28393	40	2	,	,	PUNCT
fcis-28393	40	3	the	the	DET
fcis-28393	40	4	period	period	NOUN
fcis-28393	40	5	in	in	ADP
fcis-28393	40	6	the	the	DET
fcis-28393	40	7	input	input	NOUN
fcis-28393	40	8	sequence	sequence	NOUN
fcis-28393	40	9	is	be	AUX
fcis-28393	40	10	captured	capture	VERB
fcis-28393	40	11	by	by	ADP
fcis-28393	40	12	calculating	calculate	VERB
fcis-28393	40	13	the	the	DET
fcis-28393	40	14	autocorrelation	autocorrelation	NOUN
fcis-28393	40	15	coefficient	coefficient	NOUN
fcis-28393	40	16	between	between	ADP
fcis-28393	40	17	q	q	PROPN
fcis-28393	40	18	and	and	CCONJ
fcis-28393	40	19	k	k	PROPN
fcis-28393	40	20	,	,	PUNCT
fcis-28393	40	21	and	and	CCONJ
fcis-28393	40	22	the	the	DET
fcis-28393	40	23	information	information	NOUN
fcis-28393	40	24	of	of	ADP
fcis-28393	40	25	similar	similar	ADJ
fcis-28393	40	26	subsequences	subsequence	NOUN
fcis-28393	40	27	is	be	AUX
fcis-28393	40	28	aggregated	aggregate	VERB
fcis-28393	40	29	based	base	VERB
fcis-28393	40	30	on	on	ADP
fcis-28393	40	31	the	the	DET
fcis-28393	40	32	correlation	correlation	NOUN
fcis-28393	40	33	between	between	ADP
fcis-28393	40	34	subsequences	subsequence	NOUN
fcis-28393	40	35	identified	identify	VERB
fcis-28393	40	36	by	by	ADP
fcis-28393	40	37	periodic	periodic	ADJ
fcis-28393	40	38	dependence	dependence	NOUN
fcis-28393	40	39	,	,	PUNCT
fcis-28393	40	40	so	so	SCONJ
fcis-28393	40	41	as	as	SCONJ
fcis-28393	40	42	to	to	PART
fcis-28393	40	43	realize	realize	VERB
fcis-28393	40	44	sequencelevel	sequencelevel	NOUN
fcis-28393	40	45	connection	connection	NOUN
fcis-28393	40	46	.	.	PUNCT
fcis-28393	41	1	then	then	ADV
fcis-28393	41	2	,	,	PUNCT
fcis-28393	41	3	the	the	DET
fcis-28393	41	4	confidence	confidence	NOUN
fcis-28393	41	5	is	be	AUX
fcis-28393	41	6	normalized	normalize	VERB
fcis-28393	41	7	.	.	PUNCT
fcis-28393	42	1	finally	finally	ADV
fcis-28393	42	2	,	,	PUNCT
fcis-28393	42	3	the	the	DET
fcis-28393	42	4	sequence	sequence	NOUN
fcis-28393	42	5	of	of	ADP
fcis-28393	42	6	v	v	NOUN
fcis-28393	42	7	is	be	AUX
fcis-28393	42	8	aligned	align	VERB
fcis-28393	42	9	by	by	ADP
fcis-28393	42	10	the	the	DET
fcis-28393	42	11			PROPN
fcis-28393	42	12	roll	roll	PROPN
fcis-28393	42	13			NUM
fcis-28393	42	14	function	function	NOUN
fcis-28393	42	15	according	accord	VERB
fcis-28393	42	16	to	to	ADP
fcis-28393	42	17	the	the	DET
fcis-28393	42	18	period	period	NOUN
fcis-28393	42	19	,	,	PUNCT
fcis-28393	42	20	and	and	CCONJ
fcis-28393	42	21	multiplied	multiply	VERB
fcis-28393	42	22	by	by	ADP
fcis-28393	42	23	the	the	DET
fcis-28393	42	24	normalized	normalize	VERB
fcis-28393	42	25	confidence[7	confidence[7	NOUN
fcis-28393	42	26	]	]	PUNCT
fcis-28393	42	27	.	.	PUNCT
fcis-28393	43	1	the	the	DET
fcis-28393	43	2	specific	specific	ADJ
fcis-28393	43	3	calculation	calculation	NOUN
fcis-28393	43	4	process	process	NOUN
fcis-28393	43	5	is	be	AUX
fcis-28393	43	6	as	as	SCONJ
fcis-28393	43	7	follows	follow	VERB
fcis-28393	43	8	:	:	PUNCT
fcis-28393	43	9			NOUN
fcis-28393	43	10	1	1	ADJ
fcis-28393	43	11	,	,	PUNCT
fcis-28393	43	12	{	{	PUNCT
fcis-28393	43	13	1	1	NUM
fcis-28393	43	14	,	,	PUNCT
fcis-28393	43	15	,	,	PUNCT
fcis-28393	43	16	}	}	PUNCT
fcis-28393	43	17	,	,	PUNCT
fcis-28393	43	18	,	,	PUNCT
fcis-28393	43	19	(	(	PUNCT
fcis-28393	43	20	)	)	PUNCT
fcis-28393	43	21	c	c	NOUN
fcis-28393	43	22	q	q	PROPN
fcis-28393	43	23	k	k	NOUN
fcis-28393	43	24	l	l	NOUN
fcis-28393	43	25	arg	arg	NOUN
fcis-28393	43	26	topc	topc	NOUN
fcis-28393	43	27	r	r	NOUN
fcis-28393	43	28			NOUN
fcis-28393	43	29			NOUN
fcis-28393	43	30			NOUN
fcis-28393	43	31			NOUN
fcis-28393	43	32			NOUN
fcis-28393	43	33			NOUN
fcis-28393	43	34			NOUN
fcis-28393	43	35			NOUN
fcis-28393	43	36	(	(	PUNCT
fcis-28393	43	37	2	2	NUM
fcis-28393	43	38	)	)	PUNCT
fcis-28393	43	39			NOUN
fcis-28393	43	40			PROPN
fcis-28393	43	41	,	,	PUNCT
fcis-28393	43	42	1	1	NUM
fcis-28393	43	43	,	,	PUNCT
fcis-28393	43	44	,	,	PUNCT
fcis-28393	43	45	1	1	NUM
fcis-28393	43	46	,	,	PUNCT
fcis-28393	43	47	ˆ	ˆ	PRON
fcis-28393	43	48	ˆ	ˆ	NOUN
fcis-28393	43	49	(	(	PUNCT
fcis-28393	43	50	)	)	PUNCT
fcis-28393	43	51	,	,	PUNCT
fcis-28393	43	52	,	,	PUNCT
fcis-28393	43	53	(	(	PUNCT
fcis-28393	43	54	)	)	PUNCT
fcis-28393	43	55	max	max	PROPN
fcis-28393	43	56	(	(	PUNCT
fcis-28393	43	57	)	)	PUNCT
fcis-28393	43	58	,	,	PUNCT
fcis-28393	43	59	,	,	PUNCT
fcis-28393	43	60	(	(	PUNCT
fcis-28393	43	61	)	)	PUNCT
fcis-28393	43	62	q	q	PROPN
fcis-28393	44	1	k	k	NOUN
fcis-28393	44	2	q	q	X
fcis-28393	45	1	k	k	NOUN
fcis-28393	45	2	c	c	NOUN
fcis-28393	45	3	q	q	PROPN
fcis-28393	46	1	k	k	X
fcis-28393	46	2	q	q	X
fcis-28393	47	1	k	k	NOUN
fcis-28393	47	2	c	c	NOUN
fcis-28393	47	3	r	r	NOUN
fcis-28393	47	4	r	r	NOUN
fcis-28393	47	5	soft	soft	ADJ
fcis-28393	47	6	r	r	NOUN
fcis-28393	47	7	r	r	NOUN
fcis-28393	47	8			NOUN
fcis-28393	47	9			NOUN
fcis-28393	47	10			NOUN
fcis-28393	47	11			NOUN
fcis-28393	47	12			NOUN
fcis-28393	47	13			NOUN
fcis-28393	47	14	(	(	PUNCT
fcis-28393	47	15	3	3	NUM
fcis-28393	47	16	)	)	PUNCT
fcis-28393	47	17	,	,	PUNCT
fcis-28393	47	18	1	1	NUM
fcis-28393	47	19	(	(	PUNCT
fcis-28393	47	20	,	,	PUNCT
fcis-28393	47	21	,	,	PUNCT
fcis-28393	47	22	)	)	PUNCT
fcis-28393	47	23	(	(	PUNCT
fcis-28393	47	24	,	,	PUNCT
fcis-28393	47	25	)	)	PUNCT
fcis-28393	47	26	)	)	PUNCT
fcis-28393	48	1	ˆ	ˆ	X
fcis-28393	48	2	(	(	PUNCT
fcis-28393	48	3	c	c	NOUN
fcis-28393	48	4	i	i	PRON
fcis-28393	48	5	q	q	PROPN
fcis-28393	49	1	k	k	INTJ
fcis-28393	49	2	i	i	PRON
fcis-28393	50	1	i	i	PRON
fcis-28393	50	2	auto	auto	NOUN
fcis-28393	50	3	correlation	correlation	NOUN
fcis-28393	50	4	q	q	PROPN
fcis-28393	51	1	k	k	NOUN
fcis-28393	51	2	v	v	NUM
fcis-28393	51	3	roll	roll	NOUN
fcis-28393	51	4	v	v	ADP
fcis-28393	51	5	r	r	PROPN
fcis-28393	51	6			PROPN
fcis-28393	51	7			PROPN
fcis-28393	51	8			PROPN
fcis-28393	51	9			NOUN
fcis-28393	51	10			X
fcis-28393	51	11	(	(	PUNCT
fcis-28393	51	12	4	4	NUM
fcis-28393	51	13	)	)	PUNCT
fcis-28393	51	14	among	among	ADP
fcis-28393	51	15	them	they	PRON
fcis-28393	51	16	,	,	PUNCT
fcis-28393	51	17			NOUN
fcis-28393	51	18	topc	topc	PUNCT
fcis-28393	51	19			PROPN
fcis-28393	51	20	is	be	AUX
fcis-28393	51	21	the	the	DET
fcis-28393	51	22	c	c	PROPN
fcis-28393	51	23	lag	lag	NOUN
fcis-28393	51	24	order	order	NOUN
fcis-28393	51	25	1	1	NUM
fcis-28393	51	26	,	,	PUNCT
fcis-28393	51	27	,	,	PUNCT
fcis-28393	51	28	c	c	X
fcis-28393	51	29			NOUN
fcis-28393	51	30	for	for	ADP
fcis-28393	51	31	selecting	select	VERB
fcis-28393	51	32	the	the	DET
fcis-28393	51	33	maximum	maximum	ADJ
fcis-28393	51	34	probability	probability	NOUN
fcis-28393	51	35	;	;	PUNCT
fcis-28393	51	36			PROPN
fcis-28393	52	1	maxsoft	maxsoft	ADV
fcis-28393	52	2			PROPN
fcis-28393	52	3	is	be	AUX
fcis-28393	52	4	a	a	DET
fcis-28393	52	5	normalized	normalized	ADJ
fcis-28393	52	6	function	function	NOUN
fcis-28393	52	7	;	;	PUNCT
fcis-28393	52	8	,	,	PUNCT
fcis-28393	52	9	q	q	PROPN
fcis-28393	52	10	kr	kr	PROPN
fcis-28393	52	11	represents	represent	VERB
fcis-28393	52	12	the	the	DET
fcis-28393	52	13	autocorrelation	autocorrelation	NOUN
fcis-28393	52	14	information	information	NOUN
fcis-28393	52	15	between	between	ADP
fcis-28393	52	16	the	the	DET
fcis-28393	52	17	sequence	sequence	NOUN
fcis-28393	52	18	q	q	NOUN
fcis-28393	53	1	and	and	CCONJ
fcis-28393	53	2	the	the	DET
fcis-28393	53	3	sequence	sequence	NOUN
fcis-28393	53	4	k	k	PROPN
fcis-28393	53	5	,	,	PUNCT
fcis-28393	53	6	(	(	PUNCT
fcis-28393	53	7	,	,	PUNCT
fcis-28393	53	8	)	)	PUNCT
fcis-28393	53	9	iroll	iroll	NOUN
fcis-28393	53	10	v	v	NOUN
fcis-28393	53	11			NOUN
fcis-28393	53	12	represents	represent	VERB
fcis-28393	53	13	the	the	DET
fcis-28393	53	14	i	i	ADJ
fcis-28393	53	15	-order	-order	PROPN
fcis-28393	53	16	lag	lag	NOUN
fcis-28393	53	17	processing	processing	NOUN
fcis-28393	53	18	of	of	ADP
fcis-28393	53	19	the	the	DET
fcis-28393	53	20	sequence	sequence	NOUN
fcis-28393	53	21	v	v	NOUN
fcis-28393	53	22	,	,	PUNCT
fcis-28393	53	23	and	and	CCONJ
fcis-28393	53	24	(	(	PUNCT
fcis-28393	53	25	,	,	PUNCT
fcis-28393	53	26	,	,	PUNCT
fcis-28393	53	27	)	)	PUNCT
fcis-28393	53	28	auto	auto	NOUN
fcis-28393	53	29	correlation	correlation	NOUN
fcis-28393	53	30	q	q	PROPN
fcis-28393	53	31	k	k	X
fcis-28393	53	32	v	v	NOUN
fcis-28393	53	33	represents	represent	VERB
fcis-28393	53	34	the	the	DET
fcis-28393	53	35	autocorrelation	autocorrelation	NOUN
fcis-28393	53	36	information	information	NOUN
fcis-28393	53	37	obtained	obtain	VERB
fcis-28393	53	38	by	by	ADP
fcis-28393	53	39	this	this	DET
fcis-28393	53	40	auto	auto	NOUN
fcis-28393	53	41	-	-	PUNCT
fcis-28393	53	42	correlation	correlation	NOUN
fcis-28393	53	43	mechanism[11	mechanism[11	NOUN
fcis-28393	53	44	]	]	PUNCT
fcis-28393	53	45	.	.	PUNCT
fcis-28393	54	1	(	(	PUNCT
fcis-28393	54	2	2	2	X
fcis-28393	54	3	)	)	PUNCT
fcis-28393	54	4	series	series	NOUN
fcis-28393	54	5	decomp	decomp	NOUN
fcis-28393	54	6	aiming	aim	VERB
fcis-28393	54	7	at	at	ADP
fcis-28393	54	8	the	the	DET
fcis-28393	54	9	complex	complex	ADJ
fcis-28393	54	10	time	time	NOUN
fcis-28393	54	11	pattern	pattern	NOUN
fcis-28393	54	12	in	in	ADP
fcis-28393	54	13	time	time	NOUN
fcis-28393	54	14	series	series	PROPN
fcis-28393	54	15	,	,	PUNCT
fcis-28393	54	16	autoformer	autoformer	PROPN
fcis-28393	54	17	uses	use	VERB
fcis-28393	54	18	the	the	DET
fcis-28393	54	19	idea	idea	NOUN
fcis-28393	54	20	of	of	ADP
fcis-28393	54	21	moving	move	VERB
fcis-28393	54	22	average	average	ADV
fcis-28393	54	23	to	to	PART
fcis-28393	54	24	decompose	decompose	VERB
fcis-28393	54	25	the	the	DET
fcis-28393	54	26	original	original	ADJ
fcis-28393	54	27	sequence	sequence	NOUN
fcis-28393	54	28	into	into	ADP
fcis-28393	54	29	trend	trend	NOUN
fcis-28393	54	30	term	term	NOUN
fcis-28393	54	31	and	and	CCONJ
fcis-28393	54	32	seasonal	seasonal	ADJ
fcis-28393	54	33	term	term	NOUN
fcis-28393	54	34	[	[	X
fcis-28393	54	35	12	12	NUM
fcis-28393	54	36	]	]	PUNCT
fcis-28393	54	37	.	.	PUNCT
fcis-28393	55	1	the	the	DET
fcis-28393	55	2	calculation	calculation	NOUN
fcis-28393	55	3	process	process	NOUN
fcis-28393	55	4	is	be	AUX
fcis-28393	55	5	as	as	SCONJ
fcis-28393	55	6	follows	follow	VERB
fcis-28393	55	7	:	:	PUNCT
fcis-28393	55	8	(	(	PUNCT
fcis-28393	55	9	(	(	PUNCT
fcis-28393	55	10	)	)	PUNCT
fcis-28393	55	11	)	)	PUNCT
fcis-28393	55	12	tx	tx	VERB
fcis-28393	55	13	a	a	DET
fcis-28393	55	14	gpool	gpool	NOUN
fcis-28393	55	15	padding	padding	NOUN
fcis-28393	55	16	x	x	PROPN
fcis-28393	55	17	(	(	PUNCT
fcis-28393	55	18	5	5	NUM
fcis-28393	55	19	)	)	PUNCT
fcis-28393	55	20	s	s	PART
fcis-28393	55	21	tx	tx	NOUN
fcis-28393	55	22	x	x	X
fcis-28393	55	23	x	x	PROPN
fcis-28393	55	24			NOUN
fcis-28393	55	25	(	(	PUNCT
fcis-28393	55	26	6	6	NUM
fcis-28393	55	27	)	)	PUNCT
fcis-28393	55	28	where	where	SCONJ
fcis-28393	55	29	x	x	PRON
fcis-28393	55	30	represents	represent	VERB
fcis-28393	55	31	the	the	DET
fcis-28393	55	32	original	original	ADJ
fcis-28393	55	33	sequence	sequence	NOUN
fcis-28393	55	34	to	to	PART
fcis-28393	55	35	be	be	AUX
fcis-28393	55	36	decomposed	decompose	VERB
fcis-28393	55	37	,	,	PUNCT
fcis-28393	55	38	tx	tx	PROPN
fcis-28393	55	39	represents	represent	VERB
fcis-28393	55	40	the	the	DET
fcis-28393	55	41	trend	trend	NOUN
fcis-28393	55	42	term	term	NOUN
fcis-28393	55	43	generated	generate	VERB
fcis-28393	55	44	by	by	ADP
fcis-28393	55	45	moving	move	VERB
fcis-28393	55	46	average	average	ADJ
fcis-28393	55	47	processing	processing	NOUN
fcis-28393	55	48	,	,	PUNCT
fcis-28393	55	49	sx	sx	PROPN
fcis-28393	55	50	is	be	AUX
fcis-28393	55	51	the	the	DET
fcis-28393	55	52	seasonal	seasonal	ADJ
fcis-28393	55	53	term	term	NOUN
fcis-28393	55	54	,	,	PUNCT
fcis-28393	55	55			NOUN
fcis-28393	55	56	padding	padde	VERB
fcis-28393	55	57			VERB
fcis-28393	55	58	represents	represent	VERB
fcis-28393	55	59	the	the	DET
fcis-28393	55	60	filling	filling	NOUN
fcis-28393	55	61	function	function	NOUN
fcis-28393	55	62	that	that	PRON
fcis-28393	55	63	maintains	maintain	VERB
fcis-28393	55	64	the	the	DET
fcis-28393	55	65	length	length	NOUN
fcis-28393	55	66	of	of	ADP
fcis-28393	55	67	the	the	DET
fcis-28393	55	68	sequence	sequence	NOUN
fcis-28393	55	69	,	,	PUNCT
fcis-28393	55	70	and	and	CCONJ
fcis-28393	55	71			NOUN
fcis-28393	56	1	avgpool	avgpool	NOUN
fcis-28393	56	2			PROPN
fcis-28393	56	3	is	be	AUX
fcis-28393	56	4	the	the	DET
fcis-28393	56	5	average	average	ADJ
fcis-28393	56	6	pooling	pool	VERB
fcis-28393	56	7	function	function	NOUN
fcis-28393	56	8	.	.	PUNCT
fcis-28393	57	1	2.2	2.2	NUM
fcis-28393	57	2	.	.	PUNCT
fcis-28393	58	1	lstm	lstm	NOUN
fcis-28393	58	2	model	model	PROPN
fcis-28393	58	3	lstm	lstm	PROPN
fcis-28393	58	4	is	be	AUX
fcis-28393	58	5	a	a	DET
fcis-28393	58	6	special	special	ADJ
fcis-28393	58	7	recurrent	recurrent	ADJ
fcis-28393	58	8	neural	neural	ADJ
fcis-28393	58	9	network[13	network[13	PROPN
fcis-28393	58	10	]	]	PUNCT
fcis-28393	58	11	.	.	PUNCT
fcis-28393	59	1	it	it	PRON
fcis-28393	59	2	achieves	achieve	VERB
fcis-28393	59	3	the	the	DET
fcis-28393	59	4	ability	ability	NOUN
fcis-28393	59	5	of	of	ADP
fcis-28393	59	6	long	long	ADJ
fcis-28393	59	7	-	-	PUNCT
fcis-28393	59	8	term	term	NOUN
fcis-28393	59	9	memory	memory	NOUN
fcis-28393	59	10	by	by	ADP
fcis-28393	59	11	introducing	introduce	VERB
fcis-28393	59	12	three	three	NUM
fcis-28393	59	13	special	special	ADJ
fcis-28393	59	14	'	'	PUNCT
fcis-28393	59	15	gate	gate	NOUN
fcis-28393	59	16	'	'	PUNCT
fcis-28393	59	17	mechanisms	mechanism	NOUN
fcis-28393	59	18	.	.	PUNCT
fcis-28393	60	1	the	the	DET
fcis-28393	60	2	specific	specific	ADJ
fcis-28393	60	3	process	process	NOUN
fcis-28393	60	4	and	and	CCONJ
fcis-28393	60	5	calculation	calculation	NOUN
fcis-28393	60	6	are	be	AUX
fcis-28393	60	7	as	as	SCONJ
fcis-28393	60	8	follows	follow	VERB
fcis-28393	60	9	:	:	PUNCT
fcis-28393	60	10	(	(	PUNCT
fcis-28393	60	11	1	1	X
fcis-28393	60	12	)	)	PUNCT
fcis-28393	60	13	the	the	DET
fcis-28393	60	14	forgetting	forget	VERB
fcis-28393	60	15	gate	gate	NOUN
fcis-28393	60	16	is	be	AUX
fcis-28393	60	17	responsible	responsible	ADJ
fcis-28393	60	18	for	for	ADP
fcis-28393	60	19	managing	manage	VERB
fcis-28393	60	20	the	the	DET
fcis-28393	60	21	discarding	discarding	NOUN
fcis-28393	60	22	of	of	ADP
fcis-28393	60	23	information	information	NOUN
fcis-28393	60	24	in	in	ADP
fcis-28393	60	25	the	the	DET
fcis-28393	60	26	memory	memory	NOUN
fcis-28393	60	27	unit	unit	NOUN
fcis-28393	60	28	,	,	PUNCT
fcis-28393	60	29	and	and	CCONJ
fcis-28393	60	30	determining	determine	VERB
fcis-28393	60	31	which	which	DET
fcis-28393	60	32	information	information	NOUN
fcis-28393	60	33	to	to	PART
fcis-28393	60	34	discard	discard	VERB
fcis-28393	60	35	the	the	DET
fcis-28393	60	36	memory	memory	NOUN
fcis-28393	60	37	unit	unit	NOUN
fcis-28393	60	38	based	base	VERB
fcis-28393	60	39	on	on	ADP
fcis-28393	60	40	the	the	DET
fcis-28393	60	41	previous	previous	ADJ
fcis-28393	60	42	time	time	NOUN
fcis-28393	60	43	step	step	NOUN
fcis-28393	60	44	unit	unit	NOUN
fcis-28393	60	45	state	state	PROPN
fcis-28393	60	46	1ts	1ts	ADJ
fcis-28393	60	47			PROPN
fcis-28393	60	48	and	and	CCONJ
fcis-28393	60	49	the	the	DET
fcis-28393	60	50	current	current	ADJ
fcis-28393	60	51	input	input	NOUN
fcis-28393	60	52	tx	tx	PROPN
fcis-28393	60	53	.	.	PUNCT
fcis-28393	61	1	the	the	DET
fcis-28393	61	2	formula	formula	NOUN
fcis-28393	61	3	is	be	AUX
fcis-28393	61	4	:	:	PUNCT
fcis-28393	61	5	1	1	NUM
fcis-28393	61	6	(	(	PUNCT
fcis-28393	61	7	[	[	PUNCT
fcis-28393	61	8	,	,	PUNCT
fcis-28393	61	9	]	]	PUNCT
fcis-28393	61	10	)	)	PUNCT
fcis-28393	62	1	t	t	PROPN
fcis-28393	62	2	f	f	PROPN
fcis-28393	62	3	t	t	PROPN
fcis-28393	62	4	t	t	PROPN
fcis-28393	62	5	ff	ff	NOUN
fcis-28393	62	6	w	w	PROPN
fcis-28393	62	7	s	s	PROPN
fcis-28393	62	8	x	x	PROPN
fcis-28393	62	9	b	b	NOUN
fcis-28393	62	10			ADJ
fcis-28393	62	11			PROPN
fcis-28393	62	12			X
fcis-28393	62	13	(	(	PUNCT
fcis-28393	62	14	7	7	NUM
fcis-28393	62	15	)	)	PUNCT
fcis-28393	62	16	among	among	ADP
fcis-28393	62	17	them	they	PRON
fcis-28393	62	18	,	,	PUNCT
fcis-28393	62	19			NOUN
fcis-28393	62	20			VERB
fcis-28393	62	21			NUM
fcis-28393	62	22	is	be	AUX
fcis-28393	62	23	sigmoid	sigmoid	NOUN
fcis-28393	62	24	activation	activation	NOUN
fcis-28393	62	25	function	function	NOUN
fcis-28393	62	26	;	;	PUNCT
fcis-28393	62	27	fw	fw	X
fcis-28393	62	28	is	be	AUX
fcis-28393	62	29	the	the	DET
fcis-28393	62	30	weight	weight	NOUN
fcis-28393	62	31	matrix	matrix	NOUN
fcis-28393	62	32	of	of	ADP
fcis-28393	62	33	forgetting	forget	VERB
fcis-28393	62	34	gate	gate	NOUN
fcis-28393	62	35	;	;	PUNCT
fcis-28393	62	36	fb	fb	INTJ
fcis-28393	62	37	is	be	AUX
fcis-28393	62	38	the	the	DET
fcis-28393	62	39	bias	bias	NOUN
fcis-28393	62	40	matrix	matrix	NOUN
fcis-28393	62	41	of	of	ADP
fcis-28393	62	42	the	the	DET
fcis-28393	62	43	forgetting	forget	VERB
fcis-28393	62	44	gate	gate	NOUN
fcis-28393	62	45	.	.	PUNCT
fcis-28393	63	1	(	(	PUNCT
fcis-28393	63	2	2	2	X
fcis-28393	63	3	)	)	PUNCT
fcis-28393	63	4	the	the	DET
fcis-28393	63	5	input	input	NOUN
fcis-28393	63	6	of	of	ADP
fcis-28393	63	7	the	the	DET
fcis-28393	63	8	input	input	NOUN
fcis-28393	63	9	gate	gate	PROPN
fcis-28393	63	10	control	control	PROPN
fcis-28393	63	11	information	information	NOUN
fcis-28393	63	12	is	be	AUX
fcis-28393	63	13	based	base	VERB
fcis-28393	63	14	on	on	ADP
fcis-28393	63	15	the	the	DET
fcis-28393	63	16	state	state	NOUN
fcis-28393	63	17	1tc	1tc	ADJ
fcis-28393	63	18			NOUN
fcis-28393	63	19	of	of	ADP
fcis-28393	63	20	the	the	DET
fcis-28393	63	21	previous	previous	ADJ
fcis-28393	63	22	time	time	NOUN
fcis-28393	63	23	step	step	NOUN
fcis-28393	63	24	and	and	CCONJ
fcis-28393	63	25	the	the	DET
fcis-28393	63	26	current	current	ADJ
fcis-28393	63	27	input	input	NOUN
fcis-28393	63	28	information	information	NOUN
fcis-28393	63	29	tx	tx	PROPN
fcis-28393	63	30	,	,	PUNCT
fcis-28393	63	31	and	and	CCONJ
fcis-28393	63	32	selectively	selectively	ADV
fcis-28393	63	33	retains	retain	VERB
fcis-28393	63	34	part	part	NOUN
fcis-28393	63	35	of	of	ADP
fcis-28393	63	36	the	the	DET
fcis-28393	63	37	information	information	NOUN
fcis-28393	63	38	to	to	ADP
fcis-28393	63	39	the	the	DET
fcis-28393	63	40	current	current	ADJ
fcis-28393	63	41	state	state	NOUN
fcis-28393	63	42	tc	tc	NOUN
fcis-28393	63	43	.	.	PUNCT
fcis-28393	64	1	the	the	DET
fcis-28393	64	2	formula	formula	NOUN
fcis-28393	64	3	is	be	AUX
fcis-28393	64	4	:	:	PUNCT
fcis-28393	64	5	1	1	NUM
fcis-28393	64	6	(	(	PUNCT
fcis-28393	64	7	[	[	PUNCT
fcis-28393	64	8	,	,	PUNCT
fcis-28393	64	9	]	]	PUNCT
fcis-28393	64	10	)	)	PUNCT
fcis-28393	65	1	t	t	NOUN
fcis-28393	66	1	i	i	PRON
fcis-28393	66	2	t	t	PROPN
fcis-28393	66	3	t	t	PROPN
fcis-28393	66	4	ii	ii	PROPN
fcis-28393	67	1	w	w	PROPN
fcis-28393	67	2	s	s	PROPN
fcis-28393	67	3	x	x	PROPN
fcis-28393	67	4	b	b	NOUN
fcis-28393	67	5			ADJ
fcis-28393	67	6			PROPN
fcis-28393	67	7			X
fcis-28393	67	8	(	(	PUNCT
fcis-28393	67	9	8)	8)	NUM
fcis-28393	67	10	1	1	NUM
fcis-28393	67	11	(	(	PUNCT
fcis-28393	67	12	[	[	PUNCT
fcis-28393	67	13	,	,	PUNCT
fcis-28393	67	14	]	]	PUNCT
fcis-28393	67	15	)	)	PUNCT
fcis-28393	68	1	t	t	PROPN
fcis-28393	68	2	c	c	PROPN
fcis-28393	68	3	t	t	PROPN
fcis-28393	68	4	t	t	X
fcis-28393	68	5	cc	cc	PROPN
fcis-28393	68	6	tanh	tanh	PROPN
fcis-28393	68	7	w	w	PROPN
fcis-28393	68	8	s	s	PROPN
fcis-28393	68	9	x	x	PUNCT
fcis-28393	68	10	b	b	NUM
fcis-28393	68	11			ADJ
fcis-28393	68	12			NOUN
fcis-28393	68	13	(	(	PUNCT
fcis-28393	68	14	9	9	NUM
fcis-28393	68	15	)	)	PUNCT
fcis-28393	68	16	among	among	ADP
fcis-28393	68	17	them	they	PRON
fcis-28393	68	18	,	,	PUNCT
fcis-28393	68	19	iw	iw	PROPN
fcis-28393	68	20	and	and	CCONJ
fcis-28393	68	21	cw	cw	NOUN
fcis-28393	68	22	are	be	AUX
fcis-28393	68	23	the	the	DET
fcis-28393	68	24	weight	weight	NOUN
fcis-28393	68	25	matrices	matrix	NOUN
fcis-28393	68	26	of	of	ADP
fcis-28393	68	27	input	input	NOUN
fcis-28393	68	28	gates	gate	NOUN
fcis-28393	68	29	and	and	CCONJ
fcis-28393	68	30	candidate	candidate	NOUN
fcis-28393	68	31	vectors	vector	NOUN
fcis-28393	68	32	,	,	PUNCT
fcis-28393	68	33	respectively	respectively	ADV
fcis-28393	68	34	;	;	PUNCT
fcis-28393	68	35	ib	ib	PROPN
fcis-28393	68	36	and	and	CCONJ
fcis-28393	68	37	cb	cb	PROPN
fcis-28393	68	38	are	be	AUX
fcis-28393	68	39	input	input	ADJ
fcis-28393	68	40	gate	gate	NOUN
fcis-28393	68	41	bias	bias	NOUN
fcis-28393	68	42	matrices	matrix	NOUN
fcis-28393	68	43	.	.	PUNCT
fcis-28393	69	1	tc	tc	PROPN
fcis-28393	69	2	is	be	AUX
fcis-28393	69	3	a	a	DET
fcis-28393	69	4	candidate	candidate	NOUN
fcis-28393	69	5	memory	memory	NOUN
fcis-28393	69	6	unit	unit	NOUN
fcis-28393	69	7	.	.	PUNCT
fcis-28393	70	1	through	through	ADP
fcis-28393	70	2	tf	tf	PROPN
fcis-28393	70	3	,	,	PUNCT
fcis-28393	70	4	ti	ti	PROPN
fcis-28393	70	5	and	and	CCONJ
fcis-28393	70	6	tc	tc	NOUN
fcis-28393	70	7	combined	combine	VERB
fcis-28393	70	8	with	with	ADP
fcis-28393	70	9	long	long	ADJ
fcis-28393	70	10	-	-	PUNCT
fcis-28393	70	11	term	term	NOUN
fcis-28393	70	12	memory	memory	NOUN
fcis-28393	70	13	and	and	CCONJ
fcis-28393	70	14	current	current	ADJ
fcis-28393	70	15	data	datum	NOUN
fcis-28393	70	16	,	,	PUNCT
fcis-28393	70	17	the	the	DET
fcis-28393	70	18	current	current	ADJ
fcis-28393	70	19	state	state	NOUN
fcis-28393	70	20	tc	tc	NOUN
fcis-28393	70	21	is	be	AUX
fcis-28393	70	22	obtained	obtain	VERB
fcis-28393	70	23	by	by	ADP
fcis-28393	70	24	weighted	weight	VERB
fcis-28393	70	25	calculation	calculation	NOUN
fcis-28393	70	26	.	.	PUNCT
fcis-28393	71	1	the	the	DET
fcis-28393	71	2	formula	formula	NOUN
fcis-28393	71	3	is	be	AUX
fcis-28393	71	4	:	:	PUNCT
fcis-28393	71	5	1	1	NUM
fcis-28393	71	6	t	t	NOUN
fcis-28393	71	7	t	t	PROPN
fcis-28393	71	8	t	t	PROPN
fcis-28393	71	9	t	t	PROPN
fcis-28393	72	1	tc	tc	INTJ
fcis-28393	72	2	f	f	PROPN
fcis-28393	73	1	c	c	VERB
fcis-28393	74	1	i	i	PRON
fcis-28393	74	2	c	c	PROPN
fcis-28393	74	3			ADP
fcis-28393	74	4			ADJ
fcis-28393	74	5			X
fcis-28393	74	6			NOUN
fcis-28393	74	7	(	(	PUNCT
fcis-28393	74	8	10	10	NUM
fcis-28393	74	9	)	)	PUNCT
fcis-28393	74	10	where	where	SCONJ
fcis-28393	74	11			ADJ
fcis-28393	74	12	denotes	denote	VERB
fcis-28393	74	13	the	the	DET
fcis-28393	74	14	multiplication	multiplication	NOUN
fcis-28393	74	15	of	of	ADP
fcis-28393	74	16	matrices	matrix	NOUN
fcis-28393	74	17	by	by	ADP
fcis-28393	74	18	elements	element	NOUN
fcis-28393	74	19	.	.	PUNCT
fcis-28393	75	1	(	(	PUNCT
fcis-28393	75	2	3	3	X
fcis-28393	75	3	)	)	PUNCT
fcis-28393	75	4	the	the	DET
fcis-28393	75	5	output	output	NOUN
fcis-28393	75	6	of	of	ADP
fcis-28393	75	7	the	the	DET
fcis-28393	75	8	gate	gate	PROPN
fcis-28393	75	9	control	control	PROPN
fcis-28393	75	10	data	data	PROPN
fcis-28393	75	11	information	information	NOUN
fcis-28393	75	12	determines	determine	VERB
fcis-28393	75	13	how	how	SCONJ
fcis-28393	75	14	much	much	ADJ
fcis-28393	75	15	information	information	NOUN
fcis-28393	75	16	is	be	AUX
fcis-28393	75	17	output	output	NOUN
fcis-28393	75	18	from	from	ADP
fcis-28393	75	19	the	the	DET
fcis-28393	75	20	current	current	ADJ
fcis-28393	75	21	state	state	NOUN
fcis-28393	75	22	tc	tc	NOUN
fcis-28393	75	23	to	to	ADP
fcis-28393	75	24	the	the	DET
fcis-28393	75	25	current	current	ADJ
fcis-28393	75	26	unit	unit	NOUN
fcis-28393	75	27	state	state	NOUN
fcis-28393	75	28	ts	ts	X
fcis-28393	75	29	.	.	PUNCT
fcis-28393	76	1	the	the	DET
fcis-28393	76	2	formula	formula	NOUN
fcis-28393	76	3	is	be	AUX
fcis-28393	76	4	:	:	PUNCT
fcis-28393	76	5	1	1	NUM
fcis-28393	76	6	(	(	PUNCT
fcis-28393	76	7	[	[	PUNCT
fcis-28393	76	8	,	,	PUNCT
fcis-28393	76	9	]	]	PUNCT
fcis-28393	76	10	)	)	PUNCT
fcis-28393	77	1	t	t	NOUN
fcis-28393	77	2	o	o	X
fcis-28393	77	3	t	t	NOUN
fcis-28393	77	4	t	t	X
fcis-28393	77	5	oo	oo	INTJ
fcis-28393	77	6	w	w	PROPN
fcis-28393	77	7	s	s	PROPN
fcis-28393	77	8	x	x	PROPN
fcis-28393	77	9	b	b	NOUN
fcis-28393	77	10			ADJ
fcis-28393	77	11			PROPN
fcis-28393	77	12			X
fcis-28393	77	13	(	(	PUNCT
fcis-28393	77	14	11	11	NUM
fcis-28393	77	15	)	)	PUNCT
fcis-28393	77	16	where	where	SCONJ
fcis-28393	77	17	ow	ow	PROPN
fcis-28393	77	18	is	be	AUX
fcis-28393	77	19	the	the	DET
fcis-28393	77	20	weight	weight	NOUN
fcis-28393	77	21	matrix	matrix	NOUN
fcis-28393	77	22	of	of	ADP
fcis-28393	77	23	the	the	DET
fcis-28393	77	24	output	output	NOUN
fcis-28393	77	25	gate	gate	NOUN
fcis-28393	77	26	.	.	PUNCT
fcis-28393	78	1	50	50	NUM
fcis-28393	78	2	finally	finally	ADV
fcis-28393	78	3	,	,	PUNCT
fcis-28393	78	4	the	the	DET
fcis-28393	78	5	output	output	NOUN
fcis-28393	78	6	ts	ts	X
fcis-28393	78	7	of	of	ADP
fcis-28393	78	8	the	the	DET
fcis-28393	78	9	hidden	hide	VERB
fcis-28393	78	10	layer	layer	NOUN
fcis-28393	78	11	at	at	ADP
fcis-28393	78	12	the	the	DET
fcis-28393	78	13	current	current	ADJ
fcis-28393	78	14	time	time	NOUN
fcis-28393	78	15	is	be	AUX
fcis-28393	78	16	obtained	obtain	VERB
fcis-28393	78	17	by	by	ADP
fcis-28393	78	18	to	to	ADP
fcis-28393	78	19	and	and	CCONJ
fcis-28393	78	20	tc	tc	VERB
fcis-28393	78	21	,	,	PUNCT
fcis-28393	78	22	and	and	CCONJ
fcis-28393	78	23	the	the	DET
fcis-28393	78	24	calculation	calculation	NOUN
fcis-28393	78	25	formula	formula	NOUN
fcis-28393	78	26	is	be	AUX
fcis-28393	78	27	:	:	PUNCT
fcis-28393	78	28	tanh	tanh	PROPN
fcis-28393	78	29	(	(	PUNCT
fcis-28393	78	30	)	)	PUNCT
fcis-28393	78	31	t	t	NOUN
fcis-28393	78	32	t	t	NOUN
fcis-28393	78	33	ts	ts	ADP
fcis-28393	78	34	o	o	X
fcis-28393	78	35	c	c	PROPN
fcis-28393	78	36			PROPN
fcis-28393	78	37	(	(	PUNCT
fcis-28393	78	38	12	12	NUM
fcis-28393	78	39	)	)	PUNCT
fcis-28393	78	40	2.3	2.3	NUM
fcis-28393	78	41	.	.	PUNCT
fcis-28393	79	1	autoformer	autoformer	NOUN
fcis-28393	79	2	-	-	PUNCT
fcis-28393	79	3	lstm	lstm	PROPN
fcis-28393	79	4	model	model	NOUN
fcis-28393	79	5	in	in	ADP
fcis-28393	79	6	order	order	NOUN
fcis-28393	79	7	to	to	PART
fcis-28393	79	8	deal	deal	VERB
fcis-28393	79	9	with	with	ADP
fcis-28393	79	10	the	the	DET
fcis-28393	79	11	periodicity	periodicity	NOUN
fcis-28393	79	12	,	,	PUNCT
fcis-28393	79	13	seasonality	seasonality	NOUN
fcis-28393	79	14	and	and	CCONJ
fcis-28393	79	15	nonstationarity	nonstationarity	NOUN
fcis-28393	79	16	of	of	ADP
fcis-28393	79	17	runoff	runoff	NOUN
fcis-28393	79	18	time	time	NOUN
fcis-28393	79	19	series	series	PROPN
fcis-28393	79	20	,	,	PUNCT
fcis-28393	79	21	this	this	DET
fcis-28393	79	22	paper	paper	NOUN
fcis-28393	79	23	constructs	construct	VERB
fcis-28393	79	24	a	a	DET
fcis-28393	79	25	runoff	runoff	NOUN
fcis-28393	79	26	prediction	prediction	NOUN
fcis-28393	79	27	model	model	NOUN
fcis-28393	79	28	based	base	VERB
fcis-28393	79	29	on	on	ADP
fcis-28393	79	30	autoformer	autoformer	NOUN
fcis-28393	79	31	-	-	PUNCT
fcis-28393	79	32	lstm	lstm	NOUN
fcis-28393	79	33	.	.	PUNCT
fcis-28393	80	1	the	the	DET
fcis-28393	80	2	overall	overall	ADJ
fcis-28393	80	3	structure	structure	NOUN
fcis-28393	80	4	of	of	ADP
fcis-28393	80	5	the	the	DET
fcis-28393	80	6	model	model	NOUN
fcis-28393	80	7	is	be	AUX
fcis-28393	80	8	shown	show	VERB
fcis-28393	80	9	in	in	ADP
fcis-28393	80	10	figure	figure	NOUN
fcis-28393	80	11	1	1	NUM
fcis-28393	80	12	.	.	PUNCT
fcis-28393	81	1	its	its	PRON
fcis-28393	81	2	core	core	ADJ
fcis-28393	81	3	mechanism	mechanism	NOUN
fcis-28393	81	4	autocorrelation	autocorrelation	NOUN
fcis-28393	81	5	mechanism	mechanism	NOUN
fcis-28393	81	6	,	,	PUNCT
fcis-28393	81	7	sequence	sequence	NOUN
fcis-28393	81	8	decomposition	decomposition	NOUN
fcis-28393	81	9	and	and	CCONJ
fcis-28393	81	10	long	long	ADJ
fcis-28393	81	11	short	short	ADJ
fcis-28393	81	12	-	-	PUNCT
fcis-28393	81	13	term	term	NOUN
fcis-28393	81	14	memory	memory	NOUN
fcis-28393	81	15	neural	neural	ADJ
fcis-28393	81	16	network	network	NOUN
fcis-28393	81	17	are	be	AUX
fcis-28393	81	18	embedded	embed	VERB
fcis-28393	81	19	into	into	ADP
fcis-28393	81	20	the	the	DET
fcis-28393	81	21	encoder	encoder	NOUN
fcis-28393	81	22	and	and	CCONJ
fcis-28393	81	23	decoder	decoder	NOUN
fcis-28393	81	24	as	as	ADP
fcis-28393	81	25	three	three	NUM
fcis-28393	81	26	independent	independent	ADJ
fcis-28393	81	27	modules	module	NOUN
fcis-28393	81	28	.	.	PUNCT
fcis-28393	82	1	the	the	DET
fcis-28393	82	2	autoformer	autoformer	PROPN
fcis-28393	82	3	model	model	NOUN
fcis-28393	82	4	has	have	VERB
fcis-28393	82	5	significant	significant	ADJ
fcis-28393	82	6	advantages	advantage	NOUN
fcis-28393	82	7	in	in	ADP
fcis-28393	82	8	capturing	capture	VERB
fcis-28393	82	9	long	long	ADJ
fcis-28393	82	10	-	-	PUNCT
fcis-28393	82	11	term	term	NOUN
fcis-28393	82	12	dependencies	dependency	NOUN
fcis-28393	82	13	and	and	CCONJ
fcis-28393	82	14	multi	multi	ADJ
fcis-28393	82	15	-	-	ADJ
fcis-28393	82	16	scale	scale	ADJ
fcis-28393	82	17	patterns	pattern	NOUN
fcis-28393	82	18	of	of	ADP
fcis-28393	82	19	time	time	NOUN
fcis-28393	82	20	series	series	NOUN
fcis-28393	82	21	,	,	PUNCT
fcis-28393	82	22	while	while	SCONJ
fcis-28393	82	23	lstm	lstm	NOUN
fcis-28393	82	24	effectively	effectively	ADV
fcis-28393	82	25	optimizes	optimize	VERB
fcis-28393	82	26	the	the	DET
fcis-28393	82	27	extraction	extraction	NOUN
fcis-28393	82	28	of	of	ADP
fcis-28393	82	29	local	local	ADJ
fcis-28393	82	30	features	feature	NOUN
fcis-28393	82	31	through	through	ADP
fcis-28393	82	32	its	its	PRON
fcis-28393	82	33	gating	gate	VERB
fcis-28393	82	34	mechanism	mechanism	NOUN
fcis-28393	82	35	.	.	PUNCT
fcis-28393	83	1	the	the	DET
fcis-28393	83	2	autoformer	autoformer	NOUN
fcis-28393	83	3	-	-	PUNCT
fcis-28393	83	4	lstm	lstm	PROPN
fcis-28393	83	5	model	model	NOUN
fcis-28393	83	6	replaces	replace	VERB
fcis-28393	83	7	the	the	DET
fcis-28393	83	8	feed	feed	NOUN
fcis-28393	83	9	forward	forward	ADV
fcis-28393	83	10	feedforward	feedforward	ADJ
fcis-28393	83	11	neural	neural	ADJ
fcis-28393	83	12	network	network	NOUN
fcis-28393	83	13	in	in	ADP
fcis-28393	83	14	autoformer	autoformer	NOUN
fcis-28393	83	15	with	with	ADP
fcis-28393	83	16	long	long	ADJ
fcis-28393	83	17	short	short	ADJ
fcis-28393	83	18	-	-	PUNCT
fcis-28393	83	19	term	term	NOUN
fcis-28393	83	20	memory	memory	NOUN
fcis-28393	83	21	(	(	PUNCT
fcis-28393	83	22	lstm	lstm	ADJ
fcis-28393	83	23	)	)	PUNCT
fcis-28393	83	24	neural	neural	ADJ
fcis-28393	83	25	network	network	NOUN
fcis-28393	83	26	,	,	PUNCT
fcis-28393	83	27	which	which	PRON
fcis-28393	83	28	further	far	ADV
fcis-28393	83	29	enhances	enhance	VERB
fcis-28393	83	30	the	the	DET
fcis-28393	83	31	feature	feature	NOUN
fcis-28393	83	32	extraction	extraction	NOUN
fcis-28393	83	33	ability	ability	NOUN
fcis-28393	83	34	of	of	ADP
fcis-28393	83	35	complex	complex	ADJ
fcis-28393	83	36	time	time	NOUN
fcis-28393	83	37	series	series	PROPN
fcis-28393	83	38	data	data	PROPN
fcis-28393	83	39	.	.	PUNCT
fcis-28393	84	1	at	at	ADP
fcis-28393	84	2	the	the	DET
fcis-28393	84	3	same	same	ADJ
fcis-28393	84	4	time	time	NOUN
fcis-28393	84	5	,	,	PUNCT
fcis-28393	84	6	the	the	DET
fcis-28393	84	7	noise	noise	NOUN
fcis-28393	84	8	suppression	suppression	NOUN
fcis-28393	84	9	ability	ability	NOUN
fcis-28393	84	10	of	of	ADP
fcis-28393	84	11	lstm	lstm	NOUN
fcis-28393	84	12	effectively	effectively	ADV
fcis-28393	84	13	reduces	reduce	VERB
fcis-28393	84	14	the	the	DET
fcis-28393	84	15	potential	potential	ADJ
fcis-28393	84	16	interference	interference	NOUN
fcis-28393	84	17	of	of	ADP
fcis-28393	84	18	data	datum	NOUN
fcis-28393	84	19	noise	noise	NOUN
fcis-28393	84	20	on	on	ADP
fcis-28393	84	21	the	the	DET
fcis-28393	84	22	prediction	prediction	NOUN
fcis-28393	84	23	performance	performance	NOUN
fcis-28393	84	24	of	of	ADP
fcis-28393	84	25	the	the	DET
fcis-28393	84	26	model	model	NOUN
fcis-28393	84	27	,	,	PUNCT
fcis-28393	84	28	and	and	CCONJ
fcis-28393	84	29	enhances	enhance	VERB
fcis-28393	84	30	the	the	DET
fcis-28393	84	31	robustness	robustness	NOUN
fcis-28393	84	32	of	of	ADP
fcis-28393	84	33	the	the	DET
fcis-28393	84	34	model	model	NOUN
fcis-28393	84	35	while	while	SCONJ
fcis-28393	84	36	improving	improve	VERB
fcis-28393	84	37	the	the	DET
fcis-28393	84	38	prediction	prediction	NOUN
fcis-28393	84	39	accuracy	accuracy	NOUN
fcis-28393	84	40	.	.	PUNCT
fcis-28393	85	1	fig	fig	NOUN
fcis-28393	85	2	1	1	NUM
fcis-28393	85	3	.	.	PUNCT
fcis-28393	86	1	autoformer	autoformer	NOUN
fcis-28393	86	2	-	-	PUNCT
fcis-28393	86	3	lstm	lstm	PROPN
fcis-28393	86	4	model	model	NOUN
fcis-28393	86	5	structure	structure	NOUN
fcis-28393	86	6	diagram	diagram	PROPN
fcis-28393	86	7	3	3	NUM
fcis-28393	86	8	.	.	PUNCT
fcis-28393	86	9	application	application	NOUN
fcis-28393	86	10	example	example	NOUN
fcis-28393	87	1	3.1	3.1	NUM
fcis-28393	87	2	.	.	PUNCT
fcis-28393	88	1	research	research	NOUN
fcis-28393	88	2	object	object	VERB
fcis-28393	88	3	the	the	DET
fcis-28393	88	4	huayuankou	huayuankou	NOUN
fcis-28393	88	5	hydrological	hydrological	ADJ
fcis-28393	88	6	station	station	NOUN
fcis-28393	88	7	is	be	AUX
fcis-28393	88	8	the	the	DET
fcis-28393	88	9	key	key	ADJ
fcis-28393	88	10	control	control	NOUN
fcis-28393	88	11	station	station	NOUN
fcis-28393	88	12	of	of	ADP
fcis-28393	88	13	the	the	DET
fcis-28393	88	14	main	main	ADJ
fcis-28393	88	15	stream	stream	NOUN
fcis-28393	88	16	of	of	ADP
fcis-28393	88	17	the	the	DET
fcis-28393	88	18	yellow	yellow	PROPN
fcis-28393	88	19	river	river	PROPN
fcis-28393	88	20	and	and	CCONJ
fcis-28393	88	21	the	the	DET
fcis-28393	88	22	standard	standard	ADJ
fcis-28393	88	23	station	station	NOUN
fcis-28393	88	24	for	for	ADP
fcis-28393	88	25	flood	flood	NOUN
fcis-28393	88	26	control	control	NOUN
fcis-28393	88	27	in	in	ADP
fcis-28393	88	28	the	the	DET
fcis-28393	88	29	lower	low	ADJ
fcis-28393	88	30	reaches	reach	NOUN
fcis-28393	88	31	.	.	PUNCT
fcis-28393	89	1	the	the	DET
fcis-28393	89	2	control	control	PROPN
fcis-28393	89	3	basin	basin	PROPN
fcis-28393	89	4	area	area	NOUN
fcis-28393	89	5	is	be	AUX
fcis-28393	89	6	730,000	730,000	NUM
fcis-28393	89	7	km2	km2	NOUN
fcis-28393	89	8	,	,	PUNCT
fcis-28393	89	9	accounting	account	VERB
fcis-28393	89	10	for	for	ADP
fcis-28393	89	11	97	97	NUM
fcis-28393	89	12	%	%	NOUN
fcis-28393	89	13	of	of	ADP
fcis-28393	89	14	the	the	DET
fcis-28393	89	15	total	total	ADJ
fcis-28393	89	16	area	area	NOUN
fcis-28393	89	17	of	of	ADP
fcis-28393	89	18	the	the	DET
fcis-28393	89	19	yellow	yellow	PROPN
fcis-28393	89	20	river	river	NOUN
fcis-28393	89	21	basin	basin	NOUN
fcis-28393	89	22	.	.	PUNCT
fcis-28393	90	1	it	it	PRON
fcis-28393	90	2	is	be	AUX
fcis-28393	90	3	an	an	DET
fcis-28393	90	4	important	important	ADJ
fcis-28393	90	5	hydrological	hydrological	ADJ
fcis-28393	90	6	station	station	NOUN
fcis-28393	90	7	at	at	ADP
fcis-28393	90	8	the	the	DET
fcis-28393	90	9	national	national	ADJ
fcis-28393	90	10	level	level	NOUN
fcis-28393	90	11	[	[	X
fcis-28393	90	12	14	14	NUM
fcis-28393	90	13	]	]	PUNCT
fcis-28393	90	14	.	.	PUNCT
fcis-28393	91	1	the	the	DET
fcis-28393	91	2	monitoring	monitoring	NOUN
fcis-28393	91	3	flow	flow	NOUN
fcis-28393	91	4	of	of	ADP
fcis-28393	91	5	the	the	DET
fcis-28393	91	6	station	station	NOUN
fcis-28393	91	7	has	have	AUX
fcis-28393	91	8	always	always	ADV
fcis-28393	91	9	been	be	AUX
fcis-28393	91	10	an	an	DET
fcis-28393	91	11	important	important	ADJ
fcis-28393	91	12	basis	basis	NOUN
fcis-28393	91	13	for	for	ADP
fcis-28393	91	14	downstream	downstream	ADJ
fcis-28393	91	15	flood	flood	NOUN
fcis-28393	91	16	control	control	NOUN
fcis-28393	91	17	.	.	PUNCT
fcis-28393	92	1	in	in	ADP
fcis-28393	92	2	this	this	DET
fcis-28393	92	3	paper	paper	NOUN
fcis-28393	92	4	,	,	PUNCT
fcis-28393	92	5	the	the	DET
fcis-28393	92	6	daily	daily	ADJ
fcis-28393	92	7	runoff	runoff	NOUN
fcis-28393	92	8	and	and	CCONJ
fcis-28393	92	9	daily	daily	ADJ
fcis-28393	92	10	average	average	ADJ
fcis-28393	92	11	water	water	NOUN
fcis-28393	92	12	level	level	NOUN
fcis-28393	92	13	data	datum	NOUN
fcis-28393	92	14	of	of	ADP
fcis-28393	92	15	huayuankou	huayuankou	NOUN
fcis-28393	92	16	hydrological	hydrological	ADJ
fcis-28393	92	17	station	station	NOUN
fcis-28393	92	18	from	from	ADP
fcis-28393	92	19	january	january	PROPN
fcis-28393	92	20	1,2002	1,2002	NUM
fcis-28393	92	21	to	to	ADP
fcis-28393	92	22	december	december	PROPN
fcis-28393	92	23	31,2022	31,2022	NUM
fcis-28393	92	24	are	be	AUX
fcis-28393	92	25	selected	select	VERB
fcis-28393	92	26	,	,	PUNCT
fcis-28393	92	27	and	and	CCONJ
fcis-28393	92	28	the	the	DET
fcis-28393	92	29	meteorological	meteorological	ADJ
fcis-28393	92	30	data	datum	NOUN
fcis-28393	92	31	are	be	AUX
fcis-28393	92	32	selected	select	VERB
fcis-28393	92	33	from	from	ADP
fcis-28393	92	34	zhengzhou	zhengzhou	PROPN
fcis-28393	92	35	station	station	PROPN
fcis-28393	92	36	(	(	PUNCT
fcis-28393	92	37	site	site	NOUN
fcis-28393	92	38	no.57083	no.57083	PROPN
fcis-28393	92	39	)	)	PUNCT
fcis-28393	92	40	from	from	ADP
fcis-28393	92	41	january	january	PROPN
fcis-28393	92	42	1,2002	1,2002	NUM
fcis-28393	92	43	to	to	ADP
fcis-28393	92	44	december	december	PROPN
fcis-28393	92	45	31,2022	31,2022	NUM
fcis-28393	92	46	.	.	PUNCT
fcis-28393	93	1	daily	daily	ADJ
fcis-28393	93	2	average	average	ADJ
fcis-28393	93	3	temperature	temperature	NOUN
fcis-28393	93	4	,	,	PUNCT
fcis-28393	93	5	daily	daily	ADJ
fcis-28393	93	6	precipitation	precipitation	NOUN
fcis-28393	93	7	,	,	PUNCT
fcis-28393	93	8	relative	relative	ADJ
fcis-28393	93	9	humidity	humidity	NOUN
fcis-28393	93	10	and	and	CCONJ
fcis-28393	93	11	daily	daily	ADJ
fcis-28393	93	12	average	average	ADJ
fcis-28393	93	13	wind	wind	NOUN
fcis-28393	93	14	speed	speed	NOUN
fcis-28393	93	15	data	datum	NOUN
fcis-28393	93	16	.	.	PUNCT
fcis-28393	94	1	the	the	DET
fcis-28393	94	2	hydrological	hydrological	ADJ
fcis-28393	94	3	station	station	NOUN
fcis-28393	94	4	data	datum	NOUN
fcis-28393	94	5	comes	come	VERB
fcis-28393	94	6	from	from	ADP
fcis-28393	94	7	the	the	DET
fcis-28393	94	8	yellow	yellow	PROPN
fcis-28393	94	9	river	river	NOUN
fcis-28393	94	10	water	water	NOUN
fcis-28393	94	11	conservancy	conservancy	NOUN
fcis-28393	94	12	commission	commission	NOUN
fcis-28393	94	13	of	of	ADP
fcis-28393	94	14	the	the	DET
fcis-28393	94	15	ministry	ministry	PROPN
fcis-28393	94	16	of	of	ADP
fcis-28393	94	17	water	water	NOUN
fcis-28393	94	18	resources	resource	NOUN
fcis-28393	94	19	of	of	ADP
fcis-28393	94	20	the	the	DET
fcis-28393	94	21	yellow	yellow	PROPN
fcis-28393	94	22	river	river	NOUN
fcis-28393	94	23	network	network	NOUN
fcis-28393	94	24	,	,	PUNCT
fcis-28393	94	25	and	and	CCONJ
fcis-28393	94	26	the	the	DET
fcis-28393	94	27	meteorological	meteorological	ADJ
fcis-28393	94	28	data	datum	NOUN
fcis-28393	94	29	comes	come	VERB
fcis-28393	94	30	from	from	ADP
fcis-28393	94	31	the	the	DET
fcis-28393	94	32	national	national	ADJ
fcis-28393	94	33	meteorological	meteorological	ADJ
fcis-28393	94	34	information	information	NOUN
fcis-28393	94	35	center	center	NOUN
fcis-28393	94	36	.	.	PUNCT
fcis-28393	95	1	the	the	DET
fcis-28393	95	2	random	random	ADJ
fcis-28393	95	3	forest	forest	NOUN
fcis-28393	95	4	model	model	NOUN
fcis-28393	95	5	and	and	CCONJ
fcis-28393	95	6	the	the	DET
fcis-28393	95	7	mean	mean	ADJ
fcis-28393	95	8	substitution	substitution	NOUN
fcis-28393	95	9	method	method	NOUN
fcis-28393	95	10	are	be	AUX
fcis-28393	95	11	used	use	VERB
fcis-28393	95	12	to	to	PART
fcis-28393	95	13	deal	deal	VERB
fcis-28393	95	14	with	with	ADP
fcis-28393	95	15	some	some	DET
fcis-28393	95	16	missing	missing	ADJ
fcis-28393	95	17	and	and	CCONJ
fcis-28393	95	18	abnormal	abnormal	ADJ
fcis-28393	95	19	data	datum	NOUN
fcis-28393	95	20	.	.	PUNCT
fcis-28393	96	1	3.2	3.2	NUM
fcis-28393	96	2	.	.	PUNCT
fcis-28393	97	1	analysis	analysis	NOUN
fcis-28393	97	2	of	of	ADP
fcis-28393	97	3	relationship	relationship	NOUN
fcis-28393	97	4	fig	fig	NOUN
fcis-28393	97	5	2	2	NUM
fcis-28393	97	6	.	.	PUNCT
fcis-28393	97	7	related	relate	VERB
fcis-28393	97	8	heat	heat	NOUN
fcis-28393	97	9	maps	map	NOUN
fcis-28393	97	10	51	51	NUM
fcis-28393	97	11	in	in	ADP
fcis-28393	97	12	this	this	DET
fcis-28393	97	13	paper	paper	NOUN
fcis-28393	97	14	,	,	PUNCT
fcis-28393	97	15	six	six	NUM
fcis-28393	97	16	factors	factor	NOUN
fcis-28393	97	17	of	of	ADP
fcis-28393	97	18	daily	daily	ADJ
fcis-28393	97	19	average	average	ADJ
fcis-28393	97	20	flow	flow	NOUN
fcis-28393	97	21	,	,	PUNCT
fcis-28393	97	22	daily	daily	ADJ
fcis-28393	97	23	average	average	ADJ
fcis-28393	97	24	water	water	NOUN
fcis-28393	97	25	level	level	NOUN
fcis-28393	97	26	,	,	PUNCT
fcis-28393	97	27	daily	daily	ADJ
fcis-28393	97	28	precipitation	precipitation	NOUN
fcis-28393	97	29	,	,	PUNCT
fcis-28393	97	30	daily	daily	ADJ
fcis-28393	97	31	average	average	ADJ
fcis-28393	97	32	temperature	temperature	NOUN
fcis-28393	97	33	,	,	PUNCT
fcis-28393	97	34	relative	relative	ADJ
fcis-28393	97	35	humidity	humidity	NOUN
fcis-28393	97	36	and	and	CCONJ
fcis-28393	97	37	average	average	ADJ
fcis-28393	97	38	wind	wind	NOUN
fcis-28393	97	39	speed	speed	NOUN
fcis-28393	97	40	of	of	ADP
fcis-28393	97	41	huayuankou	huayuankou	NOUN
fcis-28393	97	42	station	station	NOUN
fcis-28393	97	43	are	be	AUX
fcis-28393	97	44	selected	select	VERB
fcis-28393	97	45	to	to	PART
fcis-28393	97	46	explore	explore	VERB
fcis-28393	97	47	the	the	DET
fcis-28393	97	48	prediction	prediction	NOUN
fcis-28393	97	49	of	of	ADP
fcis-28393	97	50	runoff	runoff	NOUN
fcis-28393	97	51	.	.	PUNCT
fcis-28393	98	1	in	in	ADP
fcis-28393	98	2	order	order	NOUN
fcis-28393	98	3	to	to	PART
fcis-28393	98	4	better	well	ADV
fcis-28393	98	5	explore	explore	VERB
fcis-28393	98	6	the	the	DET
fcis-28393	98	7	influence	influence	NOUN
fcis-28393	98	8	degree	degree	NOUN
fcis-28393	98	9	of	of	ADP
fcis-28393	98	10	influencing	influence	VERB
fcis-28393	98	11	factors	factor	NOUN
fcis-28393	98	12	on	on	ADP
fcis-28393	98	13	runoff	runoff	NOUN
fcis-28393	98	14	prediction	prediction	NOUN
fcis-28393	98	15	research	research	NOUN
fcis-28393	98	16	,	,	PUNCT
fcis-28393	98	17	the	the	DET
fcis-28393	98	18	pearson	pearson	PROPN
fcis-28393	98	19	correlation	correlation	NOUN
fcis-28393	98	20	coefficient	coefficient	NOUN
fcis-28393	98	21	test	test	NOUN
fcis-28393	98	22	between	between	ADP
fcis-28393	98	23	each	each	DET
fcis-28393	98	24	factor	factor	NOUN
fcis-28393	98	25	is	be	AUX
fcis-28393	98	26	first	first	ADV
fcis-28393	98	27	carried	carry	VERB
fcis-28393	98	28	out	out	ADP
fcis-28393	98	29	[	[	X
fcis-28393	98	30	15	15	NUM
fcis-28393	98	31	]	]	PUNCT
fcis-28393	98	32	,	,	PUNCT
fcis-28393	98	33	and	and	CCONJ
fcis-28393	98	34	the	the	DET
fcis-28393	98	35	correlation	correlation	NOUN
fcis-28393	98	36	coefficient	coefficient	NOUN
fcis-28393	98	37	heat	heat	NOUN
fcis-28393	98	38	map	map	NOUN
fcis-28393	98	39	between	between	ADP
fcis-28393	98	40	the	the	DET
fcis-28393	98	41	obtained	obtain	VERB
fcis-28393	98	42	factors	factor	NOUN
fcis-28393	98	43	is	be	AUX
fcis-28393	98	44	shown	show	VERB
fcis-28393	98	45	in	in	ADP
fcis-28393	98	46	figure	figure	NOUN
fcis-28393	98	47	2	2	NUM
fcis-28393	98	48	.	.	PUNCT
fcis-28393	98	49	by	by	ADP
fcis-28393	98	50	observing	observe	VERB
fcis-28393	98	51	the	the	DET
fcis-28393	98	52	pearson	pearson	NOUN
fcis-28393	98	53	correlation	correlation	NOUN
fcis-28393	98	54	coefficient	coefficient	NOUN
fcis-28393	98	55	results	result	NOUN
fcis-28393	98	56	between	between	ADP
fcis-28393	98	57	the	the	DET
fcis-28393	98	58	characteristics	characteristic	NOUN
fcis-28393	98	59	and	and	CCONJ
fcis-28393	98	60	the	the	DET
fcis-28393	98	61	target	target	NOUN
fcis-28393	98	62	variables	variable	NOUN
fcis-28393	98	63	,	,	PUNCT
fcis-28393	98	64	it	it	PRON
fcis-28393	98	65	can	can	AUX
fcis-28393	98	66	be	be	AUX
fcis-28393	98	67	seen	see	VERB
fcis-28393	98	68	that	that	SCONJ
fcis-28393	98	69	the	the	DET
fcis-28393	98	70	correlation	correlation	NOUN
fcis-28393	98	71	between	between	ADP
fcis-28393	98	72	the	the	DET
fcis-28393	98	73	daily	daily	ADJ
fcis-28393	98	74	average	average	ADJ
fcis-28393	98	75	water	water	NOUN
fcis-28393	98	76	level	level	NOUN
fcis-28393	98	77	and	and	CCONJ
fcis-28393	98	78	the	the	DET
fcis-28393	98	79	daily	daily	ADJ
fcis-28393	98	80	average	average	ADJ
fcis-28393	98	81	temperature	temperature	NOUN
fcis-28393	98	82	and	and	CCONJ
fcis-28393	98	83	the	the	DET
fcis-28393	98	84	runoff	runoff	NOUN
fcis-28393	98	85	data	datum	NOUN
fcis-28393	98	86	is	be	AUX
fcis-28393	98	87	strong	strong	ADJ
fcis-28393	98	88	.	.	PUNCT
fcis-28393	99	1	the	the	DET
fcis-28393	99	2	specific	specific	ADJ
fcis-28393	99	3	correlation	correlation	NOUN
fcis-28393	99	4	scatter	scatter	NOUN
fcis-28393	99	5	plot	plot	NOUN
fcis-28393	99	6	is	be	AUX
fcis-28393	99	7	shown	show	VERB
fcis-28393	99	8	in	in	ADP
fcis-28393	99	9	figure	figure	NOUN
fcis-28393	99	10	3	3	NUM
fcis-28393	99	11	,	,	PUNCT
fcis-28393	99	12	and	and	CCONJ
fcis-28393	99	13	a	a	DET
fcis-28393	99	14	large	large	ADJ
fcis-28393	99	15	number	number	NOUN
fcis-28393	99	16	of	of	ADP
fcis-28393	99	17	data	datum	NOUN
fcis-28393	99	18	points	point	NOUN
fcis-28393	99	19	are	be	AUX
fcis-28393	99	20	close	close	ADJ
fcis-28393	99	21	to	to	ADP
fcis-28393	99	22	the	the	DET
fcis-28393	99	23	regression	regression	NOUN
fcis-28393	99	24	line	line	NOUN
fcis-28393	99	25	.	.	PUNCT
fcis-28393	100	1	the	the	DET
fcis-28393	100	2	second	second	ADJ
fcis-28393	100	3	is	be	AUX
fcis-28393	100	4	the	the	DET
fcis-28393	100	5	daily	daily	ADJ
fcis-28393	100	6	precipitation	precipitation	NOUN
fcis-28393	100	7	.	.	PUNCT
fcis-28393	101	1	the	the	DET
fcis-28393	101	2	correlation	correlation	NOUN
fcis-28393	101	3	between	between	ADP
fcis-28393	101	4	relative	relative	ADJ
fcis-28393	101	5	humidity	humidity	NOUN
fcis-28393	101	6	and	and	CCONJ
fcis-28393	101	7	average	average	ADJ
fcis-28393	101	8	wind	wind	NOUN
fcis-28393	101	9	speed	speed	NOUN
fcis-28393	101	10	and	and	CCONJ
fcis-28393	101	11	runoff	runoff	NOUN
fcis-28393	101	12	data	datum	NOUN
fcis-28393	101	13	is	be	AUX
fcis-28393	101	14	weak	weak	ADJ
fcis-28393	101	15	,	,	PUNCT
fcis-28393	101	16	and	and	CCONJ
fcis-28393	101	17	the	the	DET
fcis-28393	101	18	influence	influence	NOUN
fcis-28393	101	19	degree	degree	NOUN
fcis-28393	101	20	is	be	AUX
fcis-28393	101	21	small	small	ADJ
fcis-28393	101	22	,	,	PUNCT
fcis-28393	101	23	so	so	CCONJ
fcis-28393	101	24	it	it	PRON
fcis-28393	101	25	is	be	AUX
fcis-28393	101	26	not	not	PART
fcis-28393	101	27	used	use	VERB
fcis-28393	101	28	in	in	ADP
fcis-28393	101	29	the	the	DET
fcis-28393	101	30	final	final	ADJ
fcis-28393	101	31	prediction	prediction	NOUN
fcis-28393	101	32	.	.	PUNCT
fcis-28393	102	1	fig	fig	NOUN
fcis-28393	102	2	3	3	NUM
fcis-28393	102	3	.	.	PUNCT
fcis-28393	103	1	scatter	scatter	NOUN
fcis-28393	103	2	plot	plot	NOUN
fcis-28393	103	3	of	of	ADP
fcis-28393	103	4	correlation	correlation	NOUN
fcis-28393	103	5	between	between	ADP
fcis-28393	103	6	water	water	NOUN
fcis-28393	103	7	level	level	NOUN
fcis-28393	103	8	,	,	PUNCT
fcis-28393	103	9	temperature	temperature	NOUN
fcis-28393	103	10	and	and	CCONJ
fcis-28393	103	11	runoff	runoff	NOUN
fcis-28393	103	12	3.3	3.3	NUM
fcis-28393	103	13	.	.	PUNCT
fcis-28393	104	1	model	model	NOUN
fcis-28393	104	2	parameter	parameter	PROPN
fcis-28393	104	3	settings	setting	NOUN
fcis-28393	104	4	in	in	ADP
fcis-28393	104	5	order	order	NOUN
fcis-28393	104	6	to	to	PART
fcis-28393	104	7	evaluate	evaluate	VERB
fcis-28393	104	8	the	the	DET
fcis-28393	104	9	performance	performance	NOUN
fcis-28393	104	10	of	of	ADP
fcis-28393	104	11	multivariate	multivariate	NOUN
fcis-28393	104	12	autoformer	autoformer	NOUN
fcis-28393	104	13	-	-	PUNCT
fcis-28393	104	14	lstm	lstm	PROPN
fcis-28393	104	15	model	model	NOUN
fcis-28393	104	16	in	in	ADP
fcis-28393	104	17	daily	daily	ADJ
fcis-28393	104	18	average	average	ADJ
fcis-28393	104	19	flow	flow	NOUN
fcis-28393	104	20	prediction	prediction	NOUN
fcis-28393	104	21	,	,	PUNCT
fcis-28393	104	22	autoformer	autoformer	PROPN
fcis-28393	104	23	model	model	NOUN
fcis-28393	104	24	,	,	PUNCT
fcis-28393	104	25	transformer	transformer	NOUN
fcis-28393	104	26	model	model	NOUN
fcis-28393	104	27	and	and	CCONJ
fcis-28393	104	28	informer	informer	ADJ
fcis-28393	104	29	model	model	NOUN
fcis-28393	104	30	are	be	AUX
fcis-28393	104	31	set	set	VERB
fcis-28393	104	32	as	as	ADP
fcis-28393	104	33	comparative	comparative	ADJ
fcis-28393	104	34	prediction	prediction	NOUN
fcis-28393	104	35	models	model	NOUN
fcis-28393	104	36	.	.	PUNCT
fcis-28393	105	1	the	the	DET
fcis-28393	105	2	data	data	NOUN
fcis-28393	105	3	is	be	AUX
fcis-28393	105	4	divided	divide	VERB
fcis-28393	105	5	into	into	ADP
fcis-28393	105	6	training	training	NOUN
fcis-28393	105	7	set	set	NOUN
fcis-28393	105	8	,	,	PUNCT
fcis-28393	105	9	validation	validation	NOUN
fcis-28393	105	10	set	set	NOUN
fcis-28393	105	11	and	and	CCONJ
fcis-28393	105	12	test	test	NOUN
fcis-28393	105	13	set	set	VERB
fcis-28393	105	14	according	accord	VERB
fcis-28393	105	15	to	to	ADP
fcis-28393	105	16	7:1:2	7:1:2	PROPN
fcis-28393	105	17	.	.	PUNCT
fcis-28393	106	1	in	in	ADP
fcis-28393	106	2	the	the	DET
fcis-28393	106	3	model	model	NOUN
fcis-28393	106	4	parameter	parameter	NOUN
fcis-28393	106	5	setting	setting	NOUN
fcis-28393	106	6	,	,	PUNCT
fcis-28393	106	7	the	the	DET
fcis-28393	106	8	number	number	NOUN
fcis-28393	106	9	of	of	ADP
fcis-28393	106	10	nodes	node	NOUN
fcis-28393	106	11	in	in	ADP
fcis-28393	106	12	the	the	DET
fcis-28393	106	13	input	input	NOUN
fcis-28393	106	14	and	and	CCONJ
fcis-28393	106	15	output	output	NOUN
fcis-28393	106	16	layers	layer	NOUN
fcis-28393	106	17	of	of	ADP
fcis-28393	106	18	the	the	DET
fcis-28393	106	19	model	model	NOUN
fcis-28393	106	20	is	be	AUX
fcis-28393	106	21	equal	equal	ADJ
fcis-28393	106	22	to	to	ADP
fcis-28393	106	23	the	the	DET
fcis-28393	106	24	number	number	NOUN
fcis-28393	106	25	and	and	CCONJ
fcis-28393	106	26	1	1	NUM
fcis-28393	106	27	of	of	ADP
fcis-28393	106	28	the	the	DET
fcis-28393	106	29	input	input	NOUN
fcis-28393	106	30	variables	variable	NOUN
fcis-28393	106	31	,	,	PUNCT
fcis-28393	106	32	and	and	CCONJ
fcis-28393	106	33	the	the	DET
fcis-28393	106	34	iterative	iterative	NOUN
fcis-28393	106	35	update	update	NOUN
fcis-28393	106	36	is	be	AUX
fcis-28393	106	37	performed	perform	VERB
fcis-28393	106	38	on	on	ADP
fcis-28393	106	39	the	the	DET
fcis-28393	106	40	divided	divide	VERB
fcis-28393	106	41	training	training	NOUN
fcis-28393	106	42	set	set	NOUN
fcis-28393	106	43	.	.	PUNCT
fcis-28393	107	1	the	the	DET
fcis-28393	107	2	model	model	NOUN
fcis-28393	107	3	includes	include	VERB
fcis-28393	107	4	two	two	NUM
fcis-28393	107	5	encoder	encoder	NOUN
fcis-28393	107	6	layers	layer	NOUN
fcis-28393	107	7	and	and	CCONJ
fcis-28393	107	8	one	one	NUM
fcis-28393	107	9	decoder	decoder	NOUN
fcis-28393	107	10	layer	layer	NOUN
fcis-28393	107	11	.	.	PUNCT
fcis-28393	108	1	mse	mse	PROPN
fcis-28393	108	2	is	be	AUX
fcis-28393	108	3	used	use	VERB
fcis-28393	108	4	as	as	ADP
fcis-28393	108	5	the	the	DET
fcis-28393	108	6	loss	loss	NOUN
fcis-28393	108	7	function	function	NOUN
fcis-28393	108	8	,	,	PUNCT
fcis-28393	108	9	and	and	CCONJ
fcis-28393	108	10	adam	adam	PROPN
fcis-28393	108	11	optimizer	optimizer	NOUN
fcis-28393	108	12	is	be	AUX
fcis-28393	108	13	selected	select	VERB
fcis-28393	108	14	.	.	PUNCT
fcis-28393	109	1	the	the	DET
fcis-28393	109	2	initial	initial	ADJ
fcis-28393	109	3	learning	learning	NOUN
fcis-28393	109	4	rate	rate	NOUN
fcis-28393	109	5	is	be	AUX
fcis-28393	109	6	set	set	VERB
fcis-28393	109	7	to	to	ADP
fcis-28393	109	8	0.001	0.001	NUM
fcis-28393	109	9	,	,	PUNCT
fcis-28393	109	10	the	the	DET
fcis-28393	109	11	activation	activation	NOUN
fcis-28393	109	12	function	function	NOUN
fcis-28393	109	13	is	be	AUX
fcis-28393	109	14	gelu	gelu	ADJ
fcis-28393	109	15	,	,	PUNCT
fcis-28393	109	16	the	the	DET
fcis-28393	109	17	training	training	NOUN
fcis-28393	109	18	rounds	round	NOUN
fcis-28393	109	19	are	be	AUX
fcis-28393	109	20	50	50	NUM
fcis-28393	109	21	epochs	epoch	NOUN
fcis-28393	109	22	,	,	PUNCT
fcis-28393	109	23	and	and	CCONJ
fcis-28393	109	24	the	the	DET
fcis-28393	109	25	remaining	remain	VERB
fcis-28393	109	26	hyperparameters	hyperparameter	NOUN
fcis-28393	109	27	are	be	AUX
fcis-28393	109	28	obtained	obtain	VERB
fcis-28393	109	29	by	by	ADP
fcis-28393	109	30	trial	trial	NOUN
fcis-28393	109	31	-	-	PUNCT
fcis-28393	109	32	and	and	CCONJ
fcis-28393	109	33	-	-	PUNCT
fcis-28393	109	34	error	error	NOUN
fcis-28393	109	35	method	method	NOUN
fcis-28393	109	36	.	.	PUNCT
fcis-28393	110	1	3.4	3.4	NUM
fcis-28393	110	2	.	.	PUNCT
fcis-28393	110	3	evaluating	evaluate	VERB
fcis-28393	110	4	indicator	indicator	NOUN
fcis-28393	110	5	in	in	ADP
fcis-28393	110	6	order	order	NOUN
fcis-28393	110	7	to	to	PART
fcis-28393	110	8	accurately	accurately	ADV
fcis-28393	110	9	evaluate	evaluate	VERB
fcis-28393	110	10	the	the	DET
fcis-28393	110	11	prediction	prediction	NOUN
fcis-28393	110	12	effect	effect	NOUN
fcis-28393	110	13	of	of	ADP
fcis-28393	110	14	each	each	DET
fcis-28393	110	15	model	model	NOUN
fcis-28393	110	16	,	,	PUNCT
fcis-28393	110	17	this	this	DET
fcis-28393	110	18	paper	paper	NOUN
fcis-28393	110	19	selects	select	NOUN
fcis-28393	110	20	mean	mean	VERB
fcis-28393	110	21	absolute	absolute	ADJ
fcis-28393	110	22	error	error	NOUN
fcis-28393	110	23	(	(	PUNCT
fcis-28393	110	24	mae	mae	PROPN
fcis-28393	110	25	)	)	PUNCT
fcis-28393	110	26	,	,	PUNCT
fcis-28393	111	1	mean	mean	VERB
fcis-28393	111	2	square	square	ADJ
fcis-28393	111	3	error	error	NOUN
fcis-28393	111	4	(	(	PUNCT
fcis-28393	111	5	mse	mse	NOUN
fcis-28393	111	6	)	)	PUNCT
fcis-28393	111	7	,	,	PUNCT
fcis-28393	111	8	root	root	NOUN
fcis-28393	111	9	mean	mean	VERB
fcis-28393	111	10	square	square	ADJ
fcis-28393	111	11	error	error	NOUN
fcis-28393	111	12	(	(	PUNCT
fcis-28393	111	13	rmse	rmse	NOUN
fcis-28393	111	14	)	)	PUNCT
fcis-28393	111	15	and	and	CCONJ
fcis-28393	111	16	fitting	fitting	ADJ
fcis-28393	111	17	coefficient	coefficient	NOUN
fcis-28393	111	18	(	(	PUNCT
fcis-28393	111	19	2r	2r	NUM
fcis-28393	111	20	)	)	PUNCT
fcis-28393	111	21	to	to	PART
fcis-28393	111	22	evaluate	evaluate	VERB
fcis-28393	111	23	the	the	DET
fcis-28393	111	24	prediction	prediction	NOUN
fcis-28393	111	25	accuracy	accuracy	NOUN
fcis-28393	111	26	of	of	ADP
fcis-28393	111	27	various	various	ADJ
fcis-28393	111	28	prediction	prediction	NOUN
fcis-28393	111	29	models	model	NOUN
fcis-28393	111	30	.	.	PUNCT
fcis-28393	112	1	the	the	DET
fcis-28393	112	2	calculation	calculation	NOUN
fcis-28393	112	3	formulas	formula	NOUN
fcis-28393	112	4	of	of	ADP
fcis-28393	112	5	mae	mae	PROPN
fcis-28393	112	6	,	,	PUNCT
fcis-28393	112	7	mse	mse	PROPN
fcis-28393	112	8	,	,	PUNCT
fcis-28393	112	9	rmse	rmse	NOUN
fcis-28393	112	10	and	and	CCONJ
fcis-28393	112	11	2r	2r	NUM
fcis-28393	112	12	are	be	AUX
fcis-28393	112	13	as	as	SCONJ
fcis-28393	112	14	follows	follow	VERB
fcis-28393	112	15	:	:	PUNCT
fcis-28393	112	16	1	1	NUM
fcis-28393	112	17	1	1	NUM
fcis-28393	113	1	|	|	ADV
fcis-28393	114	1	|	|	ADV
fcis-28393	114	2	n	n	NOUN
fcis-28393	114	3	t	t	NOUN
fcis-28393	114	4	t	t	PROPN
fcis-28393	114	5	t	t	PROPN
fcis-28393	114	6	mae	mae	PROPN
fcis-28393	114	7	y	y	PROPN
fcis-28393	114	8	y	y	PROPN
fcis-28393	114	9	n	n	PROPN
fcis-28393	115	1			ADV
fcis-28393	116	1			NUM
fcis-28393	116	2			NUM
fcis-28393	116	3			NOUN
fcis-28393	116	4			NOUN
fcis-28393	116	5	(	(	PUNCT
fcis-28393	116	6	13	13	NUM
fcis-28393	116	7	)	)	SYM
fcis-28393	116	8	2	2	NUM
fcis-28393	116	9	1	1	NUM
fcis-28393	116	10	1	1	NUM
fcis-28393	116	11	(	(	PUNCT
fcis-28393	116	12	)	)	PUNCT
fcis-28393	117	1	n	n	ADP
fcis-28393	117	2	t	t	NOUN
fcis-28393	117	3	t	t	PROPN
fcis-28393	117	4	t	t	PROPN
fcis-28393	117	5	mse	mse	PROPN
fcis-28393	117	6	y	y	PROPN
fcis-28393	117	7	y	y	PROPN
fcis-28393	118	1	n	n	PROPN
fcis-28393	119	1			ADV
fcis-28393	120	1			NUM
fcis-28393	120	2			NUM
fcis-28393	120	3			NOUN
fcis-28393	120	4			NOUN
fcis-28393	120	5	(	(	PUNCT
fcis-28393	120	6	14	14	NUM
fcis-28393	120	7	)	)	SYM
fcis-28393	120	8	2	2	NUM
fcis-28393	120	9	1	1	NUM
fcis-28393	120	10	1	1	NUM
fcis-28393	120	11	(	(	PUNCT
fcis-28393	120	12	)	)	PUNCT
fcis-28393	120	13	n	n	ADP
fcis-28393	120	14	t	t	NOUN
fcis-28393	120	15	t	t	PROPN
fcis-28393	120	16	t	t	PROPN
fcis-28393	120	17	rmse	rmse	PROPN
fcis-28393	121	1	y	y	PROPN
fcis-28393	121	2	y	y	PROPN
fcis-28393	121	3	n	n	PROPN
fcis-28393	122	1			ADV
fcis-28393	123	1			NUM
fcis-28393	123	2			NUM
fcis-28393	123	3			NOUN
fcis-28393	123	4			NOUN
fcis-28393	123	5	(	(	PUNCT
fcis-28393	123	6	15	15	NUM
fcis-28393	123	7	)	)	PUNCT
fcis-28393	123	8			NOUN
fcis-28393	123	9	2	2	NUM
fcis-28393	123	10	2	2	NUM
fcis-28393	123	11	1	1	NUM
fcis-28393	123	12	2	2	NUM
fcis-28393	123	13	1	1	NUM
fcis-28393	123	14	(	(	PUNCT
fcis-28393	123	15	)	)	PUNCT
fcis-28393	123	16	1	1	NUM
fcis-28393	123	17	(	(	PUNCT
fcis-28393	123	18	)	)	PUNCT
fcis-28393	123	19	n	n	ADP
fcis-28393	123	20	t	t	NOUN
fcis-28393	123	21	t	t	PROPN
fcis-28393	123	22	t	t	PROPN
fcis-28393	123	23	n	n	ADP
fcis-28393	123	24	t	t	PROPN
fcis-28393	123	25	t	t	PROPN
fcis-28393	124	1	t	t	PROPN
fcis-28393	125	1	y	y	PROPN
fcis-28393	125	2	y	y	PROPN
fcis-28393	125	3	r	r	PROPN
fcis-28393	125	4	y	y	PROPN
fcis-28393	125	5	y	y	PROPN
fcis-28393	126	1			PROPN
fcis-28393	127	1			NUM
fcis-28393	127	2			NUM
fcis-28393	127	3			NUM
fcis-28393	128	1			VERB
fcis-28393	128	2			PROPN
fcis-28393	128	3			PROPN
fcis-28393	128	4			X
fcis-28393	128	5			PROPN
fcis-28393	128	6	(	(	PUNCT
fcis-28393	128	7	16	16	NUM
fcis-28393	128	8	)	)	PUNCT
fcis-28393	128	9	in	in	ADP
fcis-28393	128	10	the	the	DET
fcis-28393	128	11	formula	formula	NOUN
fcis-28393	128	12	:	:	PUNCT
fcis-28393	128	13	n	n	PRON
fcis-28393	128	14	is	be	AUX
fcis-28393	128	15	the	the	DET
fcis-28393	128	16	number	number	NOUN
fcis-28393	128	17	of	of	ADP
fcis-28393	128	18	time	time	NOUN
fcis-28393	128	19	series	series	PROPN
fcis-28393	128	20	data	data	PROPN
fcis-28393	128	21	,	,	PUNCT
fcis-28393	128	22	ty	ty	INTJ
fcis-28393	128	23	is	be	AUX
fcis-28393	128	24	the	the	DET
fcis-28393	128	25	observed	observe	VERB
fcis-28393	128	26	value	value	NOUN
fcis-28393	128	27	,	,	PUNCT
fcis-28393	128	28	ty	ty	INTJ
fcis-28393	128	29			ADJ
fcis-28393	128	30	is	be	AUX
fcis-28393	128	31	the	the	DET
fcis-28393	128	32	predicted	predict	VERB
fcis-28393	128	33	value	value	NOUN
fcis-28393	128	34	,	,	PUNCT
fcis-28393	128	35	and	and	CCONJ
fcis-28393	128	36	ty	ty	NOUN
fcis-28393	128	37	is	be	AUX
fcis-28393	128	38	the	the	DET
fcis-28393	128	39	arithmetic	arithmetic	ADJ
fcis-28393	128	40	mean	mean	NOUN
fcis-28393	128	41	value	value	NOUN
fcis-28393	128	42	of	of	ADP
fcis-28393	128	43	the	the	DET
fcis-28393	128	44	observed	observed	ADJ
fcis-28393	128	45	value	value	NOUN
fcis-28393	128	46	.	.	PUNCT
fcis-28393	129	1	3.5	3.5	NUM
fcis-28393	129	2	.	.	PUNCT
fcis-28393	129	3	model	model	NOUN
fcis-28393	129	4	prediction	prediction	NOUN
fcis-28393	129	5	results	result	NOUN
fcis-28393	129	6	and	and	CCONJ
fcis-28393	129	7	analysis	analysis	NOUN
fcis-28393	129	8	after	after	SCONJ
fcis-28393	129	9	the	the	DET
fcis-28393	129	10	training	training	NOUN
fcis-28393	129	11	of	of	ADP
fcis-28393	129	12	the	the	DET
fcis-28393	129	13	runoff	runoff	NOUN
fcis-28393	129	14	prediction	prediction	NOUN
fcis-28393	129	15	model	model	NOUN
fcis-28393	129	16	of	of	ADP
fcis-28393	129	17	huayuankou	huayuankou	PROPN
fcis-28393	129	18	hydrological	hydrological	ADJ
fcis-28393	129	19	station	station	NOUN
fcis-28393	129	20	established	establish	VERB
fcis-28393	129	21	by	by	ADP
fcis-28393	129	22	autoformerlstm	autoformerlstm	NOUN
fcis-28393	129	23	method	method	NOUN
fcis-28393	129	24	is	be	AUX
fcis-28393	129	25	completed	complete	VERB
fcis-28393	129	26	,	,	PUNCT
fcis-28393	129	27	the	the	DET
fcis-28393	129	28	comparison	comparison	NOUN
fcis-28393	129	29	line	line	NOUN
fcis-28393	129	30	chart	chart	NOUN
fcis-28393	129	31	between	between	ADP
fcis-28393	129	32	the	the	DET
fcis-28393	129	33	predicted	predict	VERB
fcis-28393	129	34	results	result	NOUN
fcis-28393	129	35	and	and	CCONJ
fcis-28393	129	36	the	the	DET
fcis-28393	129	37	corresponding	corresponding	ADJ
fcis-28393	129	38	real	real	ADJ
fcis-28393	129	39	values	value	NOUN
fcis-28393	129	40	on	on	ADP
fcis-28393	129	41	the	the	DET
fcis-28393	129	42	test	test	NOUN
fcis-28393	129	43	set	set	NOUN
fcis-28393	129	44	is	be	AUX
fcis-28393	129	45	shown	show	VERB
fcis-28393	129	46	in	in	ADP
fcis-28393	129	47	figure	figure	NOUN
fcis-28393	129	48	4	4	NUM
fcis-28393	129	49	.	.	PUNCT
fcis-28393	130	1	it	it	PRON
fcis-28393	130	2	can	can	AUX
fcis-28393	130	3	be	be	AUX
fcis-28393	130	4	seen	see	VERB
fcis-28393	130	5	that	that	SCONJ
fcis-28393	130	6	the	the	DET
fcis-28393	130	7	trend	trend	NOUN
fcis-28393	130	8	line	line	NOUN
fcis-28393	130	9	of	of	ADP
fcis-28393	130	10	the	the	DET
fcis-28393	130	11	predicted	predict	VERB
fcis-28393	130	12	value	value	NOUN
fcis-28393	130	13	of	of	ADP
fcis-28393	130	14	the	the	DET
fcis-28393	130	15	model	model	NOUN
fcis-28393	130	16	is	be	AUX
fcis-28393	130	17	generally	generally	ADV
fcis-28393	130	18	consistent	consistent	ADJ
fcis-28393	130	19	with	with	ADP
fcis-28393	130	20	the	the	DET
fcis-28393	130	21	fluctuation	fluctuation	NOUN
fcis-28393	130	22	trend	trend	NOUN
fcis-28393	130	23	of	of	ADP
fcis-28393	130	24	the	the	DET
fcis-28393	130	25	measured	measured	ADJ
fcis-28393	130	26	value	value	NOUN
fcis-28393	130	27	,	,	PUNCT
fcis-28393	130	28	and	and	CCONJ
fcis-28393	130	29	the	the	DET
fcis-28393	130	30	predicted	predict	VERB
fcis-28393	130	31	value	value	NOUN
fcis-28393	130	32	is	be	AUX
fcis-28393	130	33	in	in	ADP
fcis-28393	130	34	good	good	ADJ
fcis-28393	130	35	agreement	agreement	NOUN
fcis-28393	130	36	with	with	ADP
fcis-28393	130	37	the	the	DET
fcis-28393	130	38	real	real	ADJ
fcis-28393	130	39	value	value	NOUN
fcis-28393	130	40	.	.	PUNCT
fcis-28393	131	1	the	the	DET
fcis-28393	131	2	overall	overall	ADJ
fcis-28393	131	3	prediction	prediction	NOUN
fcis-28393	131	4	can	can	AUX
fcis-28393	131	5	basically	basically	ADV
fcis-28393	131	6	fit	fit	VERB
fcis-28393	131	7	the	the	DET
fcis-28393	131	8	change	change	NOUN
fcis-28393	131	9	trend	trend	NOUN
fcis-28393	131	10	of	of	ADP
fcis-28393	131	11	runoff	runoff	NOUN
fcis-28393	131	12	.	.	PUNCT
fcis-28393	132	1	fig	fig	NOUN
fcis-28393	132	2	4	4	NUM
fcis-28393	132	3	.	.	PUNCT
fcis-28393	132	4	autoformer	autoformer	NOUN
fcis-28393	132	5	-	-	PUNCT
fcis-28393	132	6	lstm	lstm	PROPN
fcis-28393	132	7	model	model	NOUN
fcis-28393	132	8	fitting	fitting	ADJ
fcis-28393	132	9	effect	effect	NOUN
fcis-28393	132	10	diagram	diagram	NOUN
fcis-28393	132	11	52	52	NUM
fcis-28393	132	12	in	in	ADP
fcis-28393	132	13	order	order	NOUN
fcis-28393	132	14	to	to	PART
fcis-28393	132	15	fully	fully	ADV
fcis-28393	132	16	evaluate	evaluate	VERB
fcis-28393	132	17	the	the	DET
fcis-28393	132	18	prediction	prediction	NOUN
fcis-28393	132	19	effect	effect	NOUN
fcis-28393	132	20	of	of	ADP
fcis-28393	132	21	autoformer	autoformer	NOUN
fcis-28393	132	22	-	-	PUNCT
fcis-28393	132	23	lstm	lstm	ADJ
fcis-28393	132	24	runoff	runoff	NOUN
fcis-28393	132	25	prediction	prediction	NOUN
fcis-28393	132	26	model	model	NOUN
fcis-28393	132	27	,	,	PUNCT
fcis-28393	132	28	this	this	DET
fcis-28393	132	29	paper	paper	NOUN
fcis-28393	132	30	selects	select	NOUN
fcis-28393	132	31	autoformer	autoformer	NOUN
fcis-28393	132	32	,	,	PUNCT
fcis-28393	132	33	transformer	transformer	NOUN
fcis-28393	132	34	and	and	CCONJ
fcis-28393	132	35	informer	informer	NOUN
fcis-28393	132	36	models	model	NOUN
fcis-28393	132	37	for	for	ADP
fcis-28393	132	38	comparative	comparative	ADJ
fcis-28393	132	39	verification	verification	NOUN
fcis-28393	132	40	,	,	PUNCT
fcis-28393	132	41	and	and	CCONJ
fcis-28393	132	42	uses	use	VERB
fcis-28393	132	43	mae	mae	PROPN
fcis-28393	132	44	,	,	PUNCT
fcis-28393	132	45	mse	mse	PROPN
fcis-28393	132	46	,	,	PUNCT
fcis-28393	132	47	rmse	rmse	NOUN
fcis-28393	132	48	and	and	CCONJ
fcis-28393	132	49	2r	2r	NUM
fcis-28393	132	50	to	to	PART
fcis-28393	132	51	evaluate	evaluate	VERB
fcis-28393	132	52	the	the	DET
fcis-28393	132	53	prediction	prediction	NOUN
fcis-28393	132	54	performance	performance	NOUN
fcis-28393	132	55	of	of	ADP
fcis-28393	132	56	each	each	DET
fcis-28393	132	57	model	model	NOUN
fcis-28393	132	58	.	.	PUNCT
fcis-28393	133	1	in	in	ADP
fcis-28393	133	2	order	order	NOUN
fcis-28393	133	3	to	to	PART
fcis-28393	133	4	reduce	reduce	VERB
fcis-28393	133	5	the	the	DET
fcis-28393	133	6	contingency	contingency	NOUN
fcis-28393	133	7	that	that	PRON
fcis-28393	133	8	may	may	AUX
fcis-28393	133	9	occur	occur	VERB
fcis-28393	133	10	during	during	ADP
fcis-28393	133	11	the	the	DET
fcis-28393	133	12	training	training	NOUN
fcis-28393	133	13	process	process	NOUN
fcis-28393	133	14	,	,	PUNCT
fcis-28393	133	15	multiple	multiple	ADJ
fcis-28393	133	16	training	training	NOUN
fcis-28393	133	17	methods	method	NOUN
fcis-28393	133	18	are	be	AUX
fcis-28393	133	19	used	use	VERB
fcis-28393	133	20	,	,	PUNCT
fcis-28393	133	21	and	and	CCONJ
fcis-28393	133	22	the	the	DET
fcis-28393	133	23	results	result	NOUN
fcis-28393	133	24	with	with	ADP
fcis-28393	133	25	the	the	DET
fcis-28393	133	26	best	good	ADJ
fcis-28393	133	27	training	training	NOUN
fcis-28393	133	28	performance	performance	NOUN
fcis-28393	133	29	of	of	ADP
fcis-28393	133	30	each	each	DET
fcis-28393	133	31	model	model	NOUN
fcis-28393	133	32	are	be	AUX
fcis-28393	133	33	selected	select	VERB
fcis-28393	133	34	for	for	ADP
fcis-28393	133	35	recording	recording	NOUN
fcis-28393	133	36	.	.	PUNCT
fcis-28393	134	1	the	the	DET
fcis-28393	134	2	results	result	NOUN
fcis-28393	134	3	are	be	AUX
fcis-28393	134	4	shown	show	VERB
fcis-28393	134	5	in	in	ADP
fcis-28393	134	6	table	table	NOUN
fcis-28393	134	7	1	1	NUM
fcis-28393	134	8	.	.	PUNCT
fcis-28393	134	9	table	table	NOUN
fcis-28393	134	10	1	1	NUM
fcis-28393	134	11	.	.	PUNCT
fcis-28393	134	12	comparison	comparison	NOUN
fcis-28393	134	13	of	of	ADP
fcis-28393	134	14	results	result	NOUN
fcis-28393	134	15	from	from	ADP
fcis-28393	134	16	multiple	multiple	ADJ
fcis-28393	134	17	prediction	prediction	NOUN
fcis-28393	134	18	models	model	NOUN
fcis-28393	134	19	model	model	VERB
fcis-28393	134	20	mae	mae	PROPN
fcis-28393	134	21	mse	mse	PROPN
fcis-28393	134	22	rmse	rmse	PROPN
fcis-28393	134	23	2r	2r	PROPN
fcis-28393	134	24	autoformerlstm	autoformerlstm	NOUN
fcis-28393	134	25	0.1423	0.1423	NUM
fcis-28393	134	26	0.0298	0.0298	NUM
fcis-28393	134	27	0.1728	0.1728	NUM
fcis-28393	134	28	0.9777	0.9777	NUM
fcis-28393	134	29	autoformer	autoformer	NOUN
fcis-28393	134	30	0.1638	0.1638	NUM
fcis-28393	134	31	0.1403	0.1403	NUM
fcis-28393	134	32	0.3746	0.3746	NUM
fcis-28393	134	33	0.8969	0.8969	NUM
fcis-28393	134	34	transformer	transformer	NOUN
fcis-28393	134	35	0.1833	0.1833	NUM
fcis-28393	134	36	0.1584	0.1584	NUM
fcis-28393	134	37	0.3980	0.3980	NUM
fcis-28393	134	38	0.8880	0.8880	NUM
fcis-28393	134	39	informer	informer	NOUN
fcis-28393	134	40	0.2170	0.2170	NUM
fcis-28393	134	41	0.1918	0.1918	NUM
fcis-28393	134	42	0.4380	0.4380	NUM
fcis-28393	134	43	0.8605	0.8605	NUM
fcis-28393	134	44	it	it	PRON
fcis-28393	134	45	can	can	AUX
fcis-28393	134	46	be	be	AUX
fcis-28393	134	47	seen	see	VERB
fcis-28393	134	48	from	from	ADP
fcis-28393	134	49	table	table	NOUN
fcis-28393	134	50	1	1	NUM
fcis-28393	134	51	that	that	SCONJ
fcis-28393	134	52	the	the	DET
fcis-28393	134	53	main	main	ADJ
fcis-28393	134	54	accuracy	accuracy	NOUN
fcis-28393	134	55	evaluation	evaluation	NOUN
fcis-28393	134	56	indexes	index	NOUN
fcis-28393	134	57	of	of	ADP
fcis-28393	134	58	the	the	DET
fcis-28393	134	59	autoformer	autoformer	NOUN
fcis-28393	134	60	-	-	PUNCT
fcis-28393	134	61	lstm	lstm	ADJ
fcis-28393	134	62	combined	combine	VERB
fcis-28393	134	63	prediction	prediction	NOUN
fcis-28393	134	64	model	model	NOUN
fcis-28393	134	65	proposed	propose	VERB
fcis-28393	134	66	in	in	ADP
fcis-28393	134	67	this	this	DET
fcis-28393	134	68	paper	paper	NOUN
fcis-28393	134	69	are	be	AUX
fcis-28393	134	70	better	well	ADJ
fcis-28393	134	71	than	than	ADP
fcis-28393	134	72	those	those	PRON
fcis-28393	134	73	of	of	ADP
fcis-28393	134	74	autoformer	autoformer	NOUN
fcis-28393	134	75	,	,	PUNCT
fcis-28393	134	76	transformer	transformer	NOUN
fcis-28393	134	77	and	and	CCONJ
fcis-28393	134	78	informer	informer	NOUN
fcis-28393	134	79	models	model	NOUN
fcis-28393	134	80	.	.	PUNCT
fcis-28393	135	1	the	the	DET
fcis-28393	135	2	mae	mae	PROPN
fcis-28393	135	3	value	value	NOUN
fcis-28393	135	4	of	of	ADP
fcis-28393	135	5	autoformer	autoformer	NOUN
fcis-28393	135	6	-	-	PUNCT
fcis-28393	135	7	lstm	lstm	PROPN
fcis-28393	135	8	model	model	NOUN
fcis-28393	135	9	is	be	AUX
fcis-28393	135	10	0.1423	0.1423	NUM
fcis-28393	135	11	,	,	PUNCT
fcis-28393	135	12	which	which	PRON
fcis-28393	135	13	is	be	AUX
fcis-28393	135	14	13.1	13.1	NUM
fcis-28393	135	15	%	%	NOUN
fcis-28393	135	16	,	,	PUNCT
fcis-28393	135	17	22.3%and	22.3%and	NUM
fcis-28393	135	18	34.4	34.4	NUM
fcis-28393	135	19	%	%	NOUN
fcis-28393	135	20	lower	low	ADJ
fcis-28393	135	21	than	than	ADP
fcis-28393	135	22	that	that	PRON
fcis-28393	135	23	of	of	ADP
fcis-28393	135	24	autoformer	autoformer	NOUN
fcis-28393	135	25	,	,	PUNCT
fcis-28393	135	26	transformer	transformer	NOUN
fcis-28393	135	27	and	and	CCONJ
fcis-28393	135	28	informer	informer	NOUN
fcis-28393	135	29	respectively	respectively	ADV
fcis-28393	135	30	.	.	PUNCT
fcis-28393	136	1	the	the	DET
fcis-28393	136	2	mse	mse	PROPN
fcis-28393	136	3	value	value	NOUN
fcis-28393	136	4	of	of	ADP
fcis-28393	136	5	autoformerlstm	autoformerlstm	NOUN
fcis-28393	136	6	model	model	NOUN
fcis-28393	136	7	is	be	AUX
fcis-28393	136	8	0.0298	0.0298	NUM
fcis-28393	136	9	,	,	PUNCT
fcis-28393	136	10	which	which	PRON
fcis-28393	136	11	is	be	AUX
fcis-28393	136	12	78.7	78.7	NUM
fcis-28393	136	13	%	%	NOUN
fcis-28393	136	14	,	,	PUNCT
fcis-28393	136	15	81.1	81.1	NUM
fcis-28393	136	16	%	%	NOUN
fcis-28393	136	17	and	and	CCONJ
fcis-28393	136	18	84.3	84.3	NUM
fcis-28393	136	19	%	%	NOUN
fcis-28393	136	20	lower	low	ADJ
fcis-28393	136	21	than	than	ADP
fcis-28393	136	22	that	that	PRON
fcis-28393	136	23	of	of	ADP
fcis-28393	136	24	autoformer	autoformer	NOUN
fcis-28393	136	25	,	,	PUNCT
fcis-28393	136	26	transformer	transformer	NOUN
fcis-28393	136	27	and	and	CCONJ
fcis-28393	136	28	informer	informer	NOUN
fcis-28393	136	29	respectively	respectively	ADV
fcis-28393	136	30	.	.	PUNCT
fcis-28393	137	1	the	the	DET
fcis-28393	137	2	autoformer	autoformer	NOUN
fcis-28393	137	3	-	-	PUNCT
fcis-28393	137	4	lstm	lstm	PROPN
fcis-28393	137	5	model	model	NOUN
fcis-28393	137	6	is	be	AUX
fcis-28393	137	7	also	also	ADV
fcis-28393	137	8	improved	improve	VERB
fcis-28393	137	9	compared	compare	VERB
fcis-28393	137	10	with	with	ADP
fcis-28393	137	11	the	the	DET
fcis-28393	137	12	other	other	ADJ
fcis-28393	137	13	three	three	NUM
fcis-28393	137	14	models	model	NOUN
fcis-28393	137	15	.	.	PUNCT
fcis-28393	138	1	fig	fig	NOUN
fcis-28393	138	2	5	5	NUM
fcis-28393	138	3	.	.	PUNCT
fcis-28393	138	4	comparison	comparison	NOUN
fcis-28393	138	5	radar	radar	NOUN
fcis-28393	138	6	chart	chart	NOUN
fcis-28393	138	7	of	of	ADP
fcis-28393	138	8	model	model	NOUN
fcis-28393	138	9	prediction	prediction	NOUN
fcis-28393	138	10	evaluation	evaluation	NOUN
fcis-28393	138	11	indicators	indicator	NOUN
fcis-28393	138	12	as	as	SCONJ
fcis-28393	138	13	shown	show	VERB
fcis-28393	138	14	in	in	ADP
fcis-28393	138	15	figure	figure	NOUN
fcis-28393	138	16	5	5	NUM
fcis-28393	138	17	,	,	PUNCT
fcis-28393	138	18	both	both	CCONJ
fcis-28393	138	19	the	the	DET
fcis-28393	138	20	autoformer	autoformer	NOUN
fcis-28393	138	21	-	-	PUNCT
fcis-28393	138	22	lstm	lstm	NOUN
fcis-28393	138	23	model	model	NOUN
fcis-28393	138	24	and	and	CCONJ
fcis-28393	138	25	the	the	DET
fcis-28393	138	26	autoformer	autoformer	PROPN
fcis-28393	138	27	model	model	NOUN
fcis-28393	138	28	show	show	VERB
fcis-28393	138	29	better	well	ADJ
fcis-28393	138	30	overall	overall	ADJ
fcis-28393	138	31	performance	performance	NOUN
fcis-28393	138	32	than	than	ADP
fcis-28393	138	33	the	the	DET
fcis-28393	138	34	transformer	transformer	NOUN
fcis-28393	138	35	model	model	NOUN
fcis-28393	138	36	and	and	CCONJ
fcis-28393	138	37	the	the	DET
fcis-28393	138	38	informer	informer	ADJ
fcis-28393	138	39	model	model	NOUN
fcis-28393	138	40	in	in	ADP
fcis-28393	138	41	terms	term	NOUN
fcis-28393	138	42	of	of	ADP
fcis-28393	138	43	prediction	prediction	NOUN
fcis-28393	138	44	performance	performance	NOUN
fcis-28393	138	45	.	.	PUNCT
fcis-28393	139	1	in	in	ADP
fcis-28393	139	2	particular	particular	ADJ
fcis-28393	139	3	,	,	PUNCT
fcis-28393	139	4	because	because	SCONJ
fcis-28393	139	5	lstm	lstm	NOUN
fcis-28393	139	6	is	be	AUX
fcis-28393	139	7	good	good	ADJ
fcis-28393	139	8	at	at	ADP
fcis-28393	139	9	dealing	deal	VERB
fcis-28393	139	10	with	with	ADP
fcis-28393	139	11	complex	complex	ADJ
fcis-28393	139	12	nonlinear	nonlinear	ADJ
fcis-28393	139	13	relationships	relationship	NOUN
fcis-28393	139	14	and	and	CCONJ
fcis-28393	139	15	effectively	effectively	ADV
fcis-28393	139	16	capturing	capture	VERB
fcis-28393	139	17	long	long	ADJ
fcis-28393	139	18	-	-	PUNCT
fcis-28393	139	19	term	term	NOUN
fcis-28393	139	20	dependencies	dependency	NOUN
fcis-28393	139	21	in	in	ADP
fcis-28393	139	22	time	time	NOUN
fcis-28393	139	23	series	series	PROPN
fcis-28393	139	24	,	,	PUNCT
fcis-28393	139	25	the	the	DET
fcis-28393	139	26	autoformer	autoformer	NOUN
fcis-28393	139	27	-	-	PUNCT
fcis-28393	139	28	lstm	lstm	PROPN
fcis-28393	139	29	model	model	NOUN
fcis-28393	139	30	combined	combine	VERB
fcis-28393	139	31	with	with	ADP
fcis-28393	139	32	lstm	lstm	NOUN
fcis-28393	139	33	significantly	significantly	ADV
fcis-28393	139	34	exceeds	exceed	VERB
fcis-28393	139	35	the	the	DET
fcis-28393	139	36	single	single	ADJ
fcis-28393	139	37	autoformer	autoformer	NOUN
fcis-28393	139	38	model	model	NOUN
fcis-28393	139	39	in	in	ADP
fcis-28393	139	40	prediction	prediction	NOUN
fcis-28393	139	41	accuracy	accuracy	NOUN
fcis-28393	139	42	,	,	PUNCT
fcis-28393	139	43	further	far	ADV
fcis-28393	139	44	improving	improve	VERB
fcis-28393	139	45	the	the	DET
fcis-28393	139	46	prediction	prediction	NOUN
fcis-28393	139	47	effect	effect	NOUN
fcis-28393	139	48	.	.	PUNCT
fcis-28393	140	1	the	the	DET
fcis-28393	140	2	above	above	ADJ
fcis-28393	140	3	analysis	analysis	NOUN
fcis-28393	140	4	fully	fully	ADV
fcis-28393	140	5	verifies	verifie	NOUN
fcis-28393	140	6	that	that	SCONJ
fcis-28393	140	7	the	the	DET
fcis-28393	140	8	autoformer	autoformer	NOUN
fcis-28393	140	9	-	-	PUNCT
fcis-28393	140	10	lstm	lstm	PROPN
fcis-28393	140	11	model	model	NOUN
fcis-28393	140	12	has	have	AUX
fcis-28393	140	13	higher	high	ADJ
fcis-28393	140	14	applicability	applicability	NOUN
fcis-28393	140	15	than	than	ADP
fcis-28393	140	16	other	other	ADJ
fcis-28393	140	17	models	model	NOUN
fcis-28393	140	18	in	in	ADP
fcis-28393	140	19	the	the	DET
fcis-28393	140	20	runoff	runoff	NOUN
fcis-28393	140	21	prediction	prediction	NOUN
fcis-28393	140	22	task	task	NOUN
fcis-28393	140	23	of	of	ADP
fcis-28393	140	24	multivariate	multivariate	NOUN
fcis-28393	140	25	time	time	NOUN
fcis-28393	140	26	series	series	PROPN
fcis-28393	140	27	.	.	PUNCT
fcis-28393	141	1	this	this	DET
fcis-28393	141	2	method	method	NOUN
fcis-28393	141	3	can	can	AUX
fcis-28393	141	4	not	not	PART
fcis-28393	141	5	only	only	ADV
fcis-28393	141	6	effectively	effectively	ADV
fcis-28393	141	7	capture	capture	VERB
fcis-28393	141	8	the	the	DET
fcis-28393	141	9	internal	internal	ADJ
fcis-28393	141	10	relationship	relationship	NOUN
fcis-28393	141	11	of	of	ADP
fcis-28393	141	12	complex	complex	ADJ
fcis-28393	141	13	runoff	runoff	NOUN
fcis-28393	141	14	time	time	NOUN
fcis-28393	141	15	series	series	PROPN
fcis-28393	141	16	data	data	PROPN
fcis-28393	141	17	,	,	PUNCT
fcis-28393	141	18	but	but	CCONJ
fcis-28393	141	19	also	also	ADV
fcis-28393	141	20	significantly	significantly	ADV
fcis-28393	141	21	improve	improve	VERB
fcis-28393	141	22	the	the	DET
fcis-28393	141	23	prediction	prediction	NOUN
fcis-28393	141	24	accuracy	accuracy	NOUN
fcis-28393	141	25	of	of	ADP
fcis-28393	141	26	runoff	runoff	NOUN
fcis-28393	141	27	prediction	prediction	NOUN
fcis-28393	141	28	,	,	PUNCT
fcis-28393	141	29	thus	thus	ADV
fcis-28393	141	30	proving	prove	VERB
fcis-28393	141	31	its	its	PRON
fcis-28393	141	32	superiority	superiority	NOUN
fcis-28393	141	33	and	and	CCONJ
fcis-28393	141	34	effectiveness	effectiveness	NOUN
fcis-28393	141	35	.	.	PUNCT
fcis-28393	142	1	4	4	X
fcis-28393	142	2	.	.	X
fcis-28393	142	3	conclusion	conclusion	NOUN
fcis-28393	142	4	aiming	aim	VERB
fcis-28393	142	5	at	at	ADP
fcis-28393	142	6	the	the	DET
fcis-28393	142	7	problem	problem	NOUN
fcis-28393	142	8	of	of	ADP
fcis-28393	142	9	river	river	NOUN
fcis-28393	142	10	runoff	runoff	NOUN
fcis-28393	142	11	prediction	prediction	NOUN
fcis-28393	142	12	,	,	PUNCT
fcis-28393	142	13	this	this	DET
fcis-28393	142	14	paper	paper	NOUN
fcis-28393	142	15	proposes	propose	VERB
fcis-28393	142	16	a	a	DET
fcis-28393	142	17	multivariate	multivariate	NOUN
fcis-28393	142	18	runoff	runoff	NOUN
fcis-28393	142	19	prediction	prediction	NOUN
fcis-28393	142	20	model	model	NOUN
fcis-28393	142	21	based	base	VERB
fcis-28393	142	22	on	on	ADP
fcis-28393	142	23	autoformer	autoformer	NOUN
fcis-28393	142	24	-	-	PUNCT
fcis-28393	142	25	lstm	lstm	NOUN
fcis-28393	142	26	.	.	PUNCT
fcis-28393	143	1	the	the	DET
fcis-28393	143	2	model	model	NOUN
fcis-28393	143	3	effectively	effectively	ADV
fcis-28393	143	4	captures	capture	VERB
fcis-28393	143	5	and	and	CCONJ
fcis-28393	143	6	utilizes	utilize	VERB
fcis-28393	143	7	various	various	ADJ
fcis-28393	143	8	patterns	pattern	NOUN
fcis-28393	143	9	and	and	CCONJ
fcis-28393	143	10	laws	law	NOUN
fcis-28393	143	11	in	in	ADP
fcis-28393	143	12	runoff	runoff	NOUN
fcis-28393	143	13	time	time	NOUN
fcis-28393	143	14	series	series	PROPN
fcis-28393	143	15	data	data	PROPN
fcis-28393	143	16	,	,	PUNCT
fcis-28393	143	17	and	and	CCONJ
fcis-28393	143	18	excavates	excavate	VERB
fcis-28393	143	19	the	the	DET
fcis-28393	143	20	long	long	ADJ
fcis-28393	143	21	-	-	PUNCT
fcis-28393	143	22	term	term	NOUN
fcis-28393	143	23	correlation	correlation	NOUN
fcis-28393	143	24	in	in	ADP
fcis-28393	143	25	runoff	runoff	NOUN
fcis-28393	143	26	time	time	NOUN
fcis-28393	143	27	series	series	PROPN
fcis-28393	143	28	data	data	PROPN
fcis-28393	143	29	,	,	PUNCT
fcis-28393	143	30	so	so	SCONJ
fcis-28393	143	31	as	as	SCONJ
fcis-28393	143	32	to	to	PART
fcis-28393	143	33	more	more	ADV
fcis-28393	143	34	accurately	accurately	ADV
fcis-28393	143	35	obtain	obtain	VERB
fcis-28393	143	36	the	the	DET
fcis-28393	143	37	internal	internal	ADJ
fcis-28393	143	38	relationship	relationship	NOUN
fcis-28393	143	39	of	of	ADP
fcis-28393	143	40	complex	complex	ADJ
fcis-28393	143	41	runoff	runoff	NOUN
fcis-28393	143	42	time	time	NOUN
fcis-28393	143	43	series	series	PROPN
fcis-28393	143	44	data	data	PROPN
fcis-28393	143	45	.	.	PUNCT
fcis-28393	144	1	the	the	DET
fcis-28393	144	2	runoff	runoff	NOUN
fcis-28393	144	3	data	datum	NOUN
fcis-28393	144	4	of	of	ADP
fcis-28393	144	5	huayuankou	huayuankou	NOUN
fcis-28393	144	6	hydrological	hydrological	ADJ
fcis-28393	144	7	station	station	NOUN
fcis-28393	144	8	of	of	ADP
fcis-28393	144	9	the	the	DET
fcis-28393	144	10	yellow	yellow	PROPN
fcis-28393	144	11	river	river	PROPN
fcis-28393	144	12	from	from	ADP
fcis-28393	144	13	january	january	PROPN
fcis-28393	144	14	1,2002	1,2002	NUM
fcis-28393	144	15	to	to	ADP
fcis-28393	144	16	december	december	PROPN
fcis-28393	144	17	31,2022	31,2022	NUM
fcis-28393	144	18	were	be	AUX
fcis-28393	144	19	taken	take	VERB
fcis-28393	144	20	as	as	ADP
fcis-28393	144	21	an	an	DET
fcis-28393	144	22	example	example	NOUN
fcis-28393	144	23	for	for	ADP
fcis-28393	144	24	verification	verification	NOUN
fcis-28393	144	25	and	and	CCONJ
fcis-28393	144	26	analysis	analysis	NOUN
fcis-28393	144	27	.	.	PUNCT
fcis-28393	145	1	the	the	DET
fcis-28393	145	2	main	main	ADJ
fcis-28393	145	3	conclusions	conclusion	NOUN
fcis-28393	145	4	are	be	AUX
fcis-28393	145	5	as	as	SCONJ
fcis-28393	145	6	follows	follow	VERB
fcis-28393	145	7	:	:	PUNCT
fcis-28393	145	8	(	(	PUNCT
fcis-28393	145	9	1	1	X
fcis-28393	145	10	)	)	PUNCT
fcis-28393	145	11	according	accord	VERB
fcis-28393	145	12	to	to	ADP
fcis-28393	145	13	the	the	DET
fcis-28393	145	14	results	result	NOUN
fcis-28393	145	15	of	of	ADP
fcis-28393	145	16	correlation	correlation	NOUN
fcis-28393	145	17	characterization	characterization	NOUN
fcis-28393	145	18	based	base	VERB
fcis-28393	145	19	on	on	ADP
fcis-28393	145	20	pearson	pearson	PROPN
fcis-28393	145	21	correlation	correlation	NOUN
fcis-28393	145	22	coefficient	coefficient	NOUN
fcis-28393	145	23	,	,	PUNCT
fcis-28393	145	24	it	it	PRON
fcis-28393	145	25	can	can	AUX
fcis-28393	145	26	be	be	AUX
fcis-28393	145	27	found	find	VERB
fcis-28393	145	28	that	that	SCONJ
fcis-28393	145	29	for	for	ADP
fcis-28393	145	30	the	the	DET
fcis-28393	145	31	hydrological	hydrological	ADJ
fcis-28393	145	32	data	datum	NOUN
fcis-28393	145	33	of	of	ADP
fcis-28393	145	34	huayuankou	huayuankou	NOUN
fcis-28393	145	35	hydrological	hydrological	ADJ
fcis-28393	145	36	station	station	NOUN
fcis-28393	145	37	,	,	PUNCT
fcis-28393	145	38	daily	daily	ADJ
fcis-28393	145	39	average	average	ADJ
fcis-28393	145	40	water	water	NOUN
fcis-28393	145	41	level	level	NOUN
fcis-28393	145	42	and	and	CCONJ
fcis-28393	145	43	daily	daily	ADJ
fcis-28393	145	44	average	average	ADJ
fcis-28393	145	45	temperature	temperature	NOUN
fcis-28393	145	46	are	be	AUX
fcis-28393	145	47	the	the	DET
fcis-28393	145	48	key	key	ADJ
fcis-28393	145	49	related	related	ADJ
fcis-28393	145	50	characteristic	characteristic	ADJ
fcis-28393	145	51	factors	factor	NOUN
fcis-28393	145	52	in	in	ADP
fcis-28393	145	53	runoff	runoff	NOUN
fcis-28393	145	54	prediction	prediction	NOUN
fcis-28393	145	55	,	,	PUNCT
fcis-28393	145	56	while	while	SCONJ
fcis-28393	145	57	other	other	ADJ
fcis-28393	145	58	characteristic	characteristic	ADJ
fcis-28393	145	59	factors	factor	NOUN
fcis-28393	145	60	such	such	ADJ
fcis-28393	145	61	as	as	ADP
fcis-28393	145	62	relative	relative	ADJ
fcis-28393	145	63	humidity	humidity	NOUN
fcis-28393	145	64	and	and	CCONJ
fcis-28393	145	65	daily	daily	ADJ
fcis-28393	145	66	average	average	ADJ
fcis-28393	145	67	wind	wind	NOUN
fcis-28393	145	68	speed	speed	NOUN
fcis-28393	145	69	have	have	VERB
fcis-28393	145	70	little	little	ADJ
fcis-28393	145	71	effect	effect	NOUN
fcis-28393	145	72	on	on	ADP
fcis-28393	145	73	runoff	runoff	NOUN
fcis-28393	145	74	prediction	prediction	NOUN
fcis-28393	145	75	.	.	PUNCT
fcis-28393	146	1	the	the	DET
fcis-28393	146	2	results	result	NOUN
fcis-28393	146	3	show	show	VERB
fcis-28393	146	4	that	that	SCONJ
fcis-28393	146	5	the	the	DET
fcis-28393	146	6	autoformer	autoformer	NOUN
fcis-28393	146	7	-	-	PUNCT
fcis-28393	146	8	lstm	lstm	NOUN
fcis-28393	146	9	model	model	NOUN
fcis-28393	146	10	and	and	CCONJ
fcis-28393	146	11	the	the	DET
fcis-28393	146	12	autoformer	autoformer	PROPN
fcis-28393	146	13	model	model	NOUN
fcis-28393	146	14	are	be	AUX
fcis-28393	146	15	significantly	significantly	ADV
fcis-28393	146	16	better	well	ADJ
fcis-28393	146	17	than	than	ADP
fcis-28393	146	18	the	the	DET
fcis-28393	146	19	transformer	transformer	NOUN
fcis-28393	146	20	model	model	NOUN
fcis-28393	146	21	and	and	CCONJ
fcis-28393	146	22	the	the	DET
fcis-28393	146	23	informer	informer	ADJ
fcis-28393	146	24	model	model	NOUN
fcis-28393	146	25	in	in	ADP
fcis-28393	146	26	prediction	prediction	NOUN
fcis-28393	146	27	performance	performance	NOUN
fcis-28393	146	28	.	.	PUNCT
fcis-28393	147	1	(	(	PUNCT
fcis-28393	147	2	2	2	NUM
fcis-28393	147	3	)	)	PUNCT
fcis-28393	147	4	from	from	ADP
fcis-28393	147	5	the	the	DET
fcis-28393	147	6	analysis	analysis	NOUN
fcis-28393	147	7	of	of	ADP
fcis-28393	147	8	the	the	DET
fcis-28393	147	9	case	case	NOUN
fcis-28393	147	10	verification	verification	NOUN
fcis-28393	147	11	results	result	NOUN
fcis-28393	147	12	of	of	ADP
fcis-28393	147	13	the	the	DET
fcis-28393	147	14	huayuankou	huayuankou	NOUN
fcis-28393	147	15	hydrological	hydrological	ADJ
fcis-28393	147	16	station	station	NOUN
fcis-28393	147	17	on	on	ADP
fcis-28393	147	18	the	the	DET
fcis-28393	147	19	yellow	yellow	PROPN
fcis-28393	147	20	river	river	NOUN
fcis-28393	147	21	,	,	PUNCT
fcis-28393	147	22	although	although	SCONJ
fcis-28393	147	23	the	the	DET
fcis-28393	147	24	autoformer	autoformer	NOUN
fcis-28393	147	25	,	,	PUNCT
fcis-28393	147	26	transformer	transformer	NOUN
fcis-28393	147	27	,	,	PUNCT
fcis-28393	147	28	informer	informer	NOUN
fcis-28393	147	29	and	and	CCONJ
fcis-28393	147	30	autoformer	autoformer	PROPN
fcis-28393	147	31	-	-	PUNCT
fcis-28393	147	32	lstm	lstm	NOUN
fcis-28393	147	33	models	model	NOUN
fcis-28393	147	34	can	can	AUX
fcis-28393	147	35	effectively	effectively	ADV
fcis-28393	147	36	capture	capture	VERB
fcis-28393	147	37	the	the	DET
fcis-28393	147	38	general	general	ADJ
fcis-28393	147	39	trend	trend	NOUN
fcis-28393	147	40	of	of	ADP
fcis-28393	147	41	the	the	DET
fcis-28393	147	42	daily	daily	ADJ
fcis-28393	147	43	average	average	ADJ
fcis-28393	147	44	flow	flow	NOUN
fcis-28393	147	45	,	,	PUNCT
fcis-28393	147	46	the	the	DET
fcis-28393	147	47	results	result	NOUN
fcis-28393	147	48	show	show	VERB
fcis-28393	147	49	that	that	SCONJ
fcis-28393	147	50	the	the	DET
fcis-28393	147	51	autoformer	autoformer	NOUN
fcis-28393	147	52	-	-	PUNCT
fcis-28393	147	53	lstm	lstm	NOUN
fcis-28393	147	54	model	model	NOUN
fcis-28393	147	55	and	and	CCONJ
fcis-28393	147	56	the	the	DET
fcis-28393	147	57	autoformer	autoformer	PROPN
fcis-28393	147	58	model	model	NOUN
fcis-28393	147	59	are	be	AUX
fcis-28393	147	60	significantly	significantly	ADV
fcis-28393	147	61	better	well	ADJ
fcis-28393	147	62	than	than	ADP
fcis-28393	147	63	the	the	DET
fcis-28393	147	64	transformer	transformer	NOUN
fcis-28393	147	65	model	model	NOUN
fcis-28393	147	66	and	and	CCONJ
fcis-28393	147	67	the	the	DET
fcis-28393	147	68	informer	informer	ADJ
fcis-28393	147	69	model	model	NOUN
fcis-28393	147	70	in	in	ADP
fcis-28393	147	71	prediction	prediction	NOUN
fcis-28393	147	72	performance	performance	NOUN
fcis-28393	147	73	.	.	PUNCT
fcis-28393	148	1	in	in	ADP
fcis-28393	148	2	addition	addition	NOUN
fcis-28393	148	3	,	,	PUNCT
fcis-28393	148	4	compared	compare	VERB
fcis-28393	148	5	with	with	ADP
fcis-28393	148	6	the	the	DET
fcis-28393	148	7	autoformer	autoformer	PROPN
fcis-28393	148	8	model	model	NOUN
fcis-28393	148	9	,	,	PUNCT
fcis-28393	148	10	the	the	DET
fcis-28393	148	11	values	value	NOUN
fcis-28393	148	12	of	of	ADP
fcis-28393	148	13	mae	mae	PROPN
fcis-28393	148	14	,	,	PUNCT
fcis-28393	148	15	mse	mse	PROPN
fcis-28393	148	16	and	and	CCONJ
fcis-28393	148	17	rmse	rmse	NOUN
fcis-28393	148	18	of	of	ADP
fcis-28393	148	19	the	the	DET
fcis-28393	148	20	autoformer	autoformer	NOUN
fcis-28393	148	21	-	-	PUNCT
fcis-28393	148	22	lstm	lstm	PROPN
fcis-28393	148	23	model	model	NOUN
fcis-28393	148	24	decreased	decrease	VERB
fcis-28393	148	25	by	by	ADP
fcis-28393	148	26	13.1	13.1	NUM
fcis-28393	148	27	%	%	NOUN
fcis-28393	148	28	,	,	PUNCT
fcis-28393	148	29	78.7	78.7	NUM
fcis-28393	148	30	%	%	NOUN
fcis-28393	148	31	and	and	CCONJ
fcis-28393	148	32	53.9	53.9	NUM
fcis-28393	148	33	%	%	NOUN
fcis-28393	148	34	,	,	PUNCT
fcis-28393	148	35	respectively	respectively	ADV
fcis-28393	148	36	.	.	PUNCT
fcis-28393	149	1	the	the	DET
fcis-28393	149	2	2r	2r	NUM
fcis-28393	149	3	of	of	ADP
fcis-28393	149	4	the	the	DET
fcis-28393	149	5	autoformer	autoformer	NOUN
fcis-28393	149	6	-	-	PUNCT
fcis-28393	149	7	lstm	lstm	PROPN
fcis-28393	149	8	model	model	NOUN
fcis-28393	149	9	is	be	AUX
fcis-28393	149	10	also	also	ADV
fcis-28393	149	11	8.3	8.3	NUM
fcis-28393	149	12	%	%	NOUN
fcis-28393	149	13	higher	high	ADJ
fcis-28393	149	14	than	than	ADP
fcis-28393	149	15	autoformer	autoformer	NOUN
fcis-28393	149	16	.	.	PUNCT
fcis-28393	150	1	in	in	ADP
fcis-28393	150	2	summary	summary	NOUN
fcis-28393	150	3	,	,	PUNCT
fcis-28393	150	4	the	the	DET
fcis-28393	150	5	autoformer	autoformer	NOUN
fcis-28393	150	6	-	-	PUNCT
fcis-28393	150	7	lstm	lstm	ADJ
fcis-28393	150	8	model	model	NOUN
fcis-28393	150	9	can	can	AUX
fcis-28393	150	10	better	well	ADV
fcis-28393	150	11	capture	capture	VERB
fcis-28393	150	12	the	the	DET
fcis-28393	150	13	complex	complex	ADJ
fcis-28393	150	14	internal	internal	ADJ
fcis-28393	150	15	relationship	relationship	NOUN
fcis-28393	150	16	and	and	CCONJ
fcis-28393	150	17	long	long	ADJ
fcis-28393	150	18	-	-	PUNCT
fcis-28393	150	19	term	term	NOUN
fcis-28393	150	20	correlation	correlation	NOUN
fcis-28393	150	21	between	between	ADP
fcis-28393	150	22	runoff	runoff	NOUN
fcis-28393	150	23	time	time	NOUN
fcis-28393	150	24	series	series	NOUN
fcis-28393	150	25	,	,	PUNCT
fcis-28393	150	26	thus	thus	ADV
fcis-28393	150	27	effectively	effectively	ADV
fcis-28393	150	28	improving	improve	VERB
fcis-28393	150	29	the	the	DET
fcis-28393	150	30	accuracy	accuracy	NOUN
fcis-28393	150	31	of	of	ADP
fcis-28393	150	32	runoff	runoff	NOUN
fcis-28393	150	33	prediction	prediction	NOUN
fcis-28393	150	34	.	.	PUNCT
fcis-28393	151	1	references	reference	NOUN
fcis-28393	151	2	[	[	X
fcis-28393	151	3	1	1	X
fcis-28393	151	4	]	]	PUNCT
fcis-28393	151	5	yang	yang	PROPN
fcis-28393	151	6	qiongbo	qiongbo	PROPN
fcis-28393	151	7	,	,	PUNCT
fcis-28393	151	8	cui	cui	PROPN
fcis-28393	151	9	dongwen	dongwen	NOUN
fcis-28393	151	10	,	,	PUNCT
fcis-28393	151	11	comparison	comparison	NOUN
fcis-28393	151	12	of	of	ADP
fcis-28393	151	13	wpd	wpd	PROPN
fcis-28393	151	14	-	-	PROPN
fcis-28393	151	15	rsoesn	rsoesn	PROPN
fcis-28393	151	16	and	and	CCONJ
fcis-28393	151	17	ssa	ssa	PROPN
fcis-28393	151	18	-	-	PUNCT
fcis-28393	151	19	rso	rso	PROPN
fcis-28393	151	20	-	-	PUNCT
fcis-28393	151	21	esn	esn	PROPN
fcis-28393	151	22	models	model	NOUN
fcis-28393	151	23	in	in	ADP
fcis-28393	151	24	runoff	runoff	NOUN
fcis-28393	151	25	time	time	NOUN
fcis-28393	151	26	series	series	PROPN
fcis-28393	151	27	prediction	prediction	NOUN
fcis-28393	152	1	[	[	X
fcis-28393	152	2	j	j	X
fcis-28393	152	3	]	]	X
fcis-28393	152	4	.	.	PUNCT
fcis-28393	153	1	china	china	PROPN
fcis-28393	153	2	rural	rural	ADJ
fcis-28393	153	3	water	water	NOUN
fcis-28393	153	4	conservancy	conservancy	NOUN
fcis-28393	153	5	and	and	CCONJ
fcis-28393	153	6	hydropower	hydropower	NOUN
fcis-28393	153	7	,	,	PUNCT
fcis-28393	153	8	2022,(02):61	2022,(02):61	NOUN
fcis-28393	153	9	-	-	PUNCT
fcis-28393	153	10	67	67	NUM
fcis-28393	153	11	+	+	NOUN
fcis-28393	153	12	75	75	NUM
fcis-28393	153	13	.	.	PUNCT
fcis-28393	154	1	[	[	X
fcis-28393	154	2	2	2	X
fcis-28393	154	3	]	]	PUNCT
fcis-28393	154	4	wang	wang	PROPN
fcis-28393	154	5	wen	wen	PROPN
fcis-28393	154	6	,	,	PUNCT
fcis-28393	154	7	ma	ma	PROPN
fcis-28393	154	8	jun	jun	PROPN
fcis-28393	154	9	.	.	PROPN
fcis-28393	154	10	summary	summary	NOUN
fcis-28393	154	11	of	of	ADP
fcis-28393	154	12	several	several	ADJ
fcis-28393	154	13	hydrological	hydrological	ADJ
fcis-28393	154	14	forecasting	forecasting	NOUN
fcis-28393	154	15	methods	method	NOUN
fcis-28393	154	16	[	[	X
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fcis-28393	159	16	-	-	SYM
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fcis-28393	159	18	.	.	PUNCT
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fcis-28393	159	22	-	-	PUNCT
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fcis-28393	161	21	.	.	PUNCT
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fcis-28393	161	25	.	.	PUNCT
fcis-28393	162	1	[	[	X
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fcis-28393	163	2	of	of	ADP
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fcis-28393	165	4	,	,	PUNCT
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fcis-28393	165	9	-	-	PUNCT
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fcis-28393	165	13	-	-	PUNCT
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fcis-28393	166	12	,	,	PUNCT
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fcis-28393	166	14	.	.	PUNCT
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fcis-28393	168	1	[	[	X
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fcis-28393	168	12	-	-	SYM
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fcis-28393	169	11	-	-	PUNCT
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fcis-28393	169	14	]	]	PUNCT
fcis-28393	169	15	.	.	PUNCT
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fcis-28393	170	3	,	,	PUNCT
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fcis-28393	170	5	-	-	SYM
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fcis-28393	170	7	.	.	PUNCT
fcis-28393	171	1	[	[	X
fcis-28393	171	2	9	9	NUM
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fcis-28393	185	1	[	[	X
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fcis-28393	186	6	,	,	PUNCT
fcis-28393	186	7	xu	xu	PROPN
fcis-28393	187	1	da	da	PROPN
fcis-28393	187	2	,	,	PUNCT
fcis-28393	187	3	lin	lin	PROPN
fcis-28393	187	4	xiuqing	xiuqing	PROPN
fcis-28393	187	5	,	,	PUNCT
fcis-28393	187	6	et	et	PROPN
fcis-28393	187	7	al	al	PROPN
fcis-28393	187	8	.	.	PROPN
fcis-28393	188	1	nonnegative	nonnegative	PROPN
fcis-28393	188	2	m	m	PROPN
fcis-28393	188	3	atrix	atrix	ADJ
fcis-28393	188	4	factorization	factorization	NOUN
fcis-28393	188	5	and	and	CCONJ
fcis-28393	188	6	improved	improve	VERB
fcis-28393	188	7	correlation	correlation	NOUN
fcis-28393	188	8	analysis	analysis	NOUN
fcis-28393	188	9	for	for	ADP
fcis-28393	188	10	low	low	ADJ
fcis-28393	188	11	voltage	voltage	NOUN
fcis-28393	188	12	area	area	NOUN
fcis-28393	188	13	topology	topology	NOUN
fcis-28393	188	14	identification	identification	NOUN
fcis-28393	189	1	[	[	X
fcis-28393	189	2	j	j	X
fcis-28393	189	3	]	]	X
fcis-28393	189	4	.	.	PUNCT
fcis-28393	190	1	journal	journal	PROPN
fcis-28393	190	2	of	of	ADP
fcis-28393	190	3	power	power	NOUN
fcis-28393	190	4	systems	system	NOUN
fcis-28393	190	5	and	and	CCONJ
fcis-28393	190	6	automation	automation	NOUN
fcis-28393	190	7	,	,	PUNCT
fcis-28393	190	8	2024,36(07):133	2024,36(07):133	NUM
fcis-28393	190	9	-	-	SYM
fcis-28393	190	10	139.doi	139.doi	NUM
fcis-28393	190	11	:	:	PUNCT
fcis-28393	190	12	10.19635	10.19635	NUM
fcis-28393	190	13	/	/	SYM
fcis-28393	190	14	j.cnki.csu	j.cnki.csu	NUM
fcis-28393	190	15	-	-	PUNCT
fcis-28393	190	16	epsa.001351	epsa.001351	NOUN
fcis-28393	190	17	.	.	PUNCT