id	sid	tid	token	lemma	pos
esrj-37073	1	1	119	119	NUM
esrj-37073	1	2	earth	earth	NOUN
esrj-37073	1	3	sciences	sciences	PROPN
esrj-37073	1	4	research	research	PROPN
esrj-37073	1	5	journal	journal	PROPN
esrj-37073	1	6	earth	earth	PROPN
esrj-37073	1	7	sci	sci	PROPN
esrj-37073	1	8	.	.	PUNCT
esrj-37073	2	1	res	res	PROPN
esrj-37073	2	2	.	.	PUNCT
esrj-37073	3	1	sj	sj	PROPN
esrj-37073	3	2	.	.	PUNCT
esrj-37073	3	3	vol	vol	NOUN
esrj-37073	3	4	.	.	PROPN
esrj-37073	4	1	17	17	NUM
esrj-37073	4	2	,	,	PUNCT
esrj-37073	4	3	no	no	INTJ
esrj-37073	4	4	.	.	NOUN
esrj-37073	4	5	2	2	NUM
esrj-37073	4	6	(	(	PUNCT
esrj-37073	4	7	december	december	PROPN
esrj-37073	4	8	,	,	PUNCT
esrj-37073	4	9	2013	2013	NUM
esrj-37073	4	10	):	):	PUNCT
esrj-37073	4	11	119	119	NUM
esrj-37073	4	12	126	126	NUM
esrj-37073	4	13	nonlinear	nonlinear	ADJ
esrj-37073	4	14	forecasting	forecasting	NOUN
esrj-37073	4	15	of	of	ADP
esrj-37073	4	16	stream	stream	NOUN
esrj-37073	4	17	flows	flow	NOUN
esrj-37073	4	18	using	use	VERB
esrj-37073	4	19	a	a	DET
esrj-37073	4	20	chaotic	chaotic	ADJ
esrj-37073	4	21	approach	approach	NOUN
esrj-37073	4	22	and	and	CCONJ
esrj-37073	4	23	artificial	artificial	ADJ
esrj-37073	4	24	neural	neural	ADJ
esrj-37073	4	25	networks	network	NOUN
esrj-37073	4	26	hakan	hakan	VERB
esrj-37073	5	1	tongal	tongal	ADJ
esrj-37073	5	2	engineering	engineering	NOUN
esrj-37073	5	3	faculty	faculty	NOUN
esrj-37073	5	4	,	,	PUNCT
esrj-37073	5	5	civil	civil	ADJ
esrj-37073	5	6	engineering	engineering	NOUN
esrj-37073	5	7	department	department	PROPN
esrj-37073	5	8	,	,	PUNCT
esrj-37073	5	9	süleyman	süleyman	NOUN
esrj-37073	5	10	demirel	demirel	PROPN
esrj-37073	5	11	university	university	PROPN
esrj-37073	5	12	,	,	PUNCT
esrj-37073	5	13	turkey	turkey	NOUN
esrj-37073	5	14	fluid	fluid	NOUN
esrj-37073	5	15	dynamics	dynamic	NOUN
esrj-37073	5	16	this	this	DET
esrj-37073	5	17	paper	paper	NOUN
esrj-37073	5	18	evaluates	evaluate	VERB
esrj-37073	5	19	the	the	DET
esrj-37073	5	20	forecasting	forecasting	NOUN
esrj-37073	5	21	performance	performance	NOUN
esrj-37073	5	22	of	of	ADP
esrj-37073	5	23	two	two	NUM
esrj-37073	5	24	nonlinear	nonlinear	ADJ
esrj-37073	5	25	models	model	NOUN
esrj-37073	5	26	,	,	PUNCT
esrj-37073	5	27	k	k	X
esrj-37073	5	28	-	-	PUNCT
esrj-37073	5	29	nearest	near	ADJ
esrj-37073	5	30	neighbor	neighbor	NOUN
esrj-37073	5	31	(	(	PUNCT
esrj-37073	5	32	knn	knn	PROPN
esrj-37073	5	33	)	)	PUNCT
esrj-37073	5	34	and	and	CCONJ
esrj-37073	5	35	feed	feed	NOUN
esrj-37073	5	36	-	-	PUNCT
esrj-37073	5	37	forward	forward	NOUN
esrj-37073	5	38	neural	neural	ADJ
esrj-37073	5	39	networks	network	NOUN
esrj-37073	5	40	(	(	PUNCT
esrj-37073	5	41	ffnn	ffnn	NOUN
esrj-37073	5	42	)	)	PUNCT
esrj-37073	5	43	,	,	PUNCT
esrj-37073	5	44	using	use	VERB
esrj-37073	5	45	stream	stream	NOUN
esrj-37073	5	46	flow	flow	NOUN
esrj-37073	5	47	data	datum	NOUN
esrj-37073	5	48	of	of	ADP
esrj-37073	5	49	the	the	DET
esrj-37073	5	50	kızılırmak	kızılırmak	PROPN
esrj-37073	5	51	river	river	PROPN
esrj-37073	5	52	,	,	PUNCT
esrj-37073	5	53	the	the	DET
esrj-37073	5	54	longest	long	ADJ
esrj-37073	5	55	river	river	NOUN
esrj-37073	5	56	in	in	ADP
esrj-37073	5	57	turkey	turkey	NOUN
esrj-37073	5	58	.	.	PUNCT
esrj-37073	6	1	for	for	ADP
esrj-37073	6	2	the	the	DET
esrj-37073	6	3	knn	knn	PROPN
esrj-37073	6	4	model	model	PROPN
esrj-37073	6	5	,	,	PUNCT
esrj-37073	6	6	the	the	DET
esrj-37073	6	7	required	require	VERB
esrj-37073	6	8	parameters	parameter	NOUN
esrj-37073	6	9	are	be	AUX
esrj-37073	6	10	delay	delay	NOUN
esrj-37073	6	11	time	time	NOUN
esrj-37073	6	12	,	,	PUNCT
esrj-37073	6	13	number	number	NOUN
esrj-37073	6	14	of	of	ADP
esrj-37073	6	15	nearest	near	ADJ
esrj-37073	6	16	neighbors	neighbor	NOUN
esrj-37073	6	17	and	and	CCONJ
esrj-37073	6	18	embedding	embed	VERB
esrj-37073	6	19	dimension	dimension	NOUN
esrj-37073	6	20	.	.	PUNCT
esrj-37073	7	1	the	the	DET
esrj-37073	7	2	optimal	optimal	ADJ
esrj-37073	7	3	delay	delay	NOUN
esrj-37073	7	4	time	time	NOUN
esrj-37073	7	5	was	be	AUX
esrj-37073	7	6	obtained	obtain	VERB
esrj-37073	7	7	with	with	ADP
esrj-37073	7	8	the	the	DET
esrj-37073	7	9	mutual	mutual	ADJ
esrj-37073	7	10	information	information	NOUN
esrj-37073	7	11	function	function	NOUN
esrj-37073	7	12	;	;	PUNCT
esrj-37073	7	13	the	the	DET
esrj-37073	7	14	number	number	NOUN
esrj-37073	7	15	of	of	ADP
esrj-37073	7	16	nearest	near	ADJ
esrj-37073	7	17	neighbors	neighbor	NOUN
esrj-37073	7	18	was	be	AUX
esrj-37073	7	19	obtained	obtain	VERB
esrj-37073	7	20	with	with	ADP
esrj-37073	7	21	the	the	DET
esrj-37073	7	22	optimization	optimization	NOUN
esrj-37073	7	23	process	process	NOUN
esrj-37073	7	24	that	that	PRON
esrj-37073	7	25	minimizes	minimize	VERB
esrj-37073	7	26	rmse	rmse	NOUN
esrj-37073	7	27	as	as	ADP
esrj-37073	7	28	a	a	DET
esrj-37073	7	29	function	function	NOUN
esrj-37073	7	30	of	of	ADP
esrj-37073	7	31	the	the	DET
esrj-37073	7	32	neighbor	neighbor	NOUN
esrj-37073	7	33	number	number	NOUN
esrj-37073	7	34	and	and	CCONJ
esrj-37073	7	35	the	the	DET
esrj-37073	7	36	embedding	embed	VERB
esrj-37073	7	37	dimension	dimension	NOUN
esrj-37073	7	38	was	be	AUX
esrj-37073	7	39	obtained	obtain	VERB
esrj-37073	7	40	with	with	ADP
esrj-37073	7	41	the	the	DET
esrj-37073	7	42	correlation	correlation	NOUN
esrj-37073	7	43	dimension	dimension	NOUN
esrj-37073	7	44	method	method	NOUN
esrj-37073	7	45	.	.	PUNCT
esrj-37073	8	1	the	the	DET
esrj-37073	8	2	correlation	correlation	NOUN
esrj-37073	8	3	dimension	dimension	NOUN
esrj-37073	8	4	of	of	ADP
esrj-37073	8	5	the	the	DET
esrj-37073	8	6	kızılırmak	kızılırmak	PROPN
esrj-37073	8	7	river	river	PROPN
esrj-37073	8	8	was	be	AUX
esrj-37073	8	9	2.702d	2.702d	NOUN
esrj-37073	8	10	=	=	SYM
esrj-37073	8	11	,	,	PUNCT
esrj-37073	8	12	which	which	PRON
esrj-37073	8	13	was	be	AUX
esrj-37073	8	14	used	use	VERB
esrj-37073	8	15	in	in	ADP
esrj-37073	8	16	forming	form	VERB
esrj-37073	8	17	the	the	DET
esrj-37073	8	18	input	input	NOUN
esrj-37073	8	19	structure	structure	NOUN
esrj-37073	8	20	of	of	ADP
esrj-37073	8	21	the	the	DET
esrj-37073	8	22	ffnn	ffnn	NOUN
esrj-37073	8	23	.	.	PUNCT
esrj-37073	9	1	the	the	DET
esrj-37073	9	2	nearest	near	ADJ
esrj-37073	9	3	integer	integer	NOUN
esrj-37073	9	4	above	above	ADP
esrj-37073	9	5	the	the	DET
esrj-37073	9	6	correlation	correlation	NOUN
esrj-37073	9	7	dimension	dimension	NOUN
esrj-37073	9	8	(	(	PUNCT
esrj-37073	9	9	i.e.	i.e.	X
esrj-37073	9	10	,	,	PUNCT
esrj-37073	9	11	3	3	X
esrj-37073	9	12	)	)	PUNCT
esrj-37073	9	13	provided	provide	VERB
esrj-37073	9	14	the	the	DET
esrj-37073	9	15	minimal	minimal	ADJ
esrj-37073	9	16	number	number	NOUN
esrj-37073	9	17	of	of	ADP
esrj-37073	9	18	required	require	VERB
esrj-37073	9	19	variables	variable	NOUN
esrj-37073	9	20	to	to	PART
esrj-37073	9	21	characterize	characterize	VERB
esrj-37073	9	22	the	the	DET
esrj-37073	9	23	system	system	NOUN
esrj-37073	9	24	,	,	PUNCT
esrj-37073	9	25	and	and	CCONJ
esrj-37073	9	26	the	the	DET
esrj-37073	9	27	maximum	maximum	ADJ
esrj-37073	9	28	number	number	NOUN
esrj-37073	9	29	of	of	ADP
esrj-37073	9	30	required	require	VERB
esrj-37073	9	31	variables	variable	NOUN
esrj-37073	9	32	was	be	AUX
esrj-37073	9	33	obtained	obtain	VERB
esrj-37073	9	34	with	with	ADP
esrj-37073	9	35	the	the	DET
esrj-37073	9	36	nearest	near	ADJ
esrj-37073	9	37	integer	integer	NOUN
esrj-37073	9	38	above	above	ADP
esrj-37073	9	39	the	the	DET
esrj-37073	9	40	value	value	NOUN
esrj-37073	9	41	2	2	NUM
esrj-37073	9	42	1d	1d	NUM
esrj-37073	10	1	+	+	CCONJ
esrj-37073	10	2	(	(	PUNCT
esrj-37073	10	3	takens	taken	NOUN
esrj-37073	10	4	,	,	PUNCT
esrj-37073	10	5	1981	1981	NUM
esrj-37073	10	6	)	)	PUNCT
esrj-37073	10	7	(	(	PUNCT
esrj-37073	10	8	i.e.	i.e.	X
esrj-37073	10	9	,	,	PUNCT
esrj-37073	10	10	7	7	NUM
esrj-37073	10	11	)	)	PUNCT
esrj-37073	10	12	.	.	PUNCT
esrj-37073	11	1	two	two	NUM
esrj-37073	11	2	ffnn	ffnn	NOUN
esrj-37073	11	3	models	model	NOUN
esrj-37073	11	4	were	be	AUX
esrj-37073	11	5	developed	develop	VERB
esrj-37073	11	6	that	that	PRON
esrj-37073	11	7	incorporate	incorporate	VERB
esrj-37073	11	8	3	3	NUM
esrj-37073	11	9	and	and	CCONJ
esrj-37073	11	10	7	7	NUM
esrj-37073	11	11	lagged	lag	VERB
esrj-37073	11	12	discharge	discharge	NOUN
esrj-37073	11	13	values	value	NOUN
esrj-37073	11	14	and	and	CCONJ
esrj-37073	11	15	the	the	DET
esrj-37073	11	16	predicted	predict	VERB
esrj-37073	11	17	performance	performance	NOUN
esrj-37073	11	18	compared	compare	VERB
esrj-37073	11	19	to	to	ADP
esrj-37073	11	20	that	that	PRON
esrj-37073	11	21	of	of	ADP
esrj-37073	11	22	the	the	DET
esrj-37073	11	23	knn	knn	PROPN
esrj-37073	11	24	model	model	PROPN
esrj-37073	11	25	.	.	PUNCT
esrj-37073	12	1	the	the	DET
esrj-37073	12	2	results	result	NOUN
esrj-37073	12	3	showed	show	VERB
esrj-37073	12	4	that	that	SCONJ
esrj-37073	12	5	the	the	DET
esrj-37073	12	6	knn	knn	PROPN
esrj-37073	12	7	model	model	NOUN
esrj-37073	12	8	was	be	AUX
esrj-37073	12	9	superior	superior	ADJ
esrj-37073	12	10	to	to	ADP
esrj-37073	12	11	the	the	DET
esrj-37073	12	12	ffnn	ffnn	NOUN
esrj-37073	12	13	model	model	NOUN
esrj-37073	12	14	in	in	ADP
esrj-37073	12	15	stream	stream	NOUN
esrj-37073	12	16	flow	flow	NOUN
esrj-37073	12	17	forecasting	forecasting	NOUN
esrj-37073	12	18	.	.	PUNCT
esrj-37073	13	1	however	however	ADV
esrj-37073	13	2	,	,	PUNCT
esrj-37073	13	3	as	as	ADP
esrj-37073	13	4	a	a	DET
esrj-37073	13	5	result	result	NOUN
esrj-37073	13	6	from	from	ADP
esrj-37073	13	7	the	the	DET
esrj-37073	13	8	knn	knn	PROPN
esrj-37073	13	9	model	model	PROPN
esrj-37073	13	10	structure	structure	NOUN
esrj-37073	13	11	,	,	PUNCT
esrj-37073	13	12	the	the	DET
esrj-37073	13	13	model	model	NOUN
esrj-37073	13	14	failed	fail	VERB
esrj-37073	13	15	in	in	ADP
esrj-37073	13	16	the	the	DET
esrj-37073	13	17	prediction	prediction	NOUN
esrj-37073	13	18	of	of	ADP
esrj-37073	13	19	peak	peak	NOUN
esrj-37073	13	20	values	value	NOUN
esrj-37073	13	21	.	.	PUNCT
esrj-37073	14	1	additionally	additionally	ADV
esrj-37073	14	2	,	,	PUNCT
esrj-37073	14	3	it	it	PRON
esrj-37073	14	4	was	be	AUX
esrj-37073	14	5	found	find	VERB
esrj-37073	14	6	that	that	SCONJ
esrj-37073	14	7	the	the	DET
esrj-37073	14	8	correlation	correlation	NOUN
esrj-37073	14	9	dimension	dimension	NOUN
esrj-37073	14	10	(	(	PUNCT
esrj-37073	14	11	if	if	SCONJ
esrj-37073	14	12	it	it	PRON
esrj-37073	14	13	existed	exist	VERB
esrj-37073	14	14	)	)	PUNCT
esrj-37073	14	15	could	could	AUX
esrj-37073	14	16	successfully	successfully	ADV
esrj-37073	14	17	be	be	AUX
esrj-37073	14	18	used	use	VERB
esrj-37073	14	19	in	in	ADP
esrj-37073	14	20	time	time	NOUN
esrj-37073	14	21	series	series	NOUN
esrj-37073	14	22	where	where	SCONJ
esrj-37073	14	23	the	the	DET
esrj-37073	14	24	determination	determination	NOUN
esrj-37073	14	25	of	of	ADP
esrj-37073	14	26	the	the	DET
esrj-37073	14	27	input	input	NOUN
esrj-37073	14	28	structure	structure	NOUN
esrj-37073	14	29	is	be	AUX
esrj-37073	14	30	difficult	difficult	ADJ
esrj-37073	14	31	because	because	SCONJ
esrj-37073	14	32	of	of	ADP
esrj-37073	14	33	high	high	ADJ
esrj-37073	14	34	inter	inter	ADJ
esrj-37073	14	35	-	-	NOUN
esrj-37073	14	36	dependency	dependency	NOUN
esrj-37073	14	37	,	,	PUNCT
esrj-37073	14	38	as	as	ADP
esrj-37073	14	39	in	in	ADP
esrj-37073	14	40	stream	stream	NOUN
esrj-37073	14	41	flow	flow	NOUN
esrj-37073	14	42	time	time	NOUN
esrj-37073	14	43	series	series	PROPN
esrj-37073	14	44	.	.	PUNCT
esrj-37073	15	1	este	este	PROPN
esrj-37073	15	2	trabajo	trabajo	PROPN
esrj-37073	15	3	evalúa	evalúa	PROPN
esrj-37073	15	4	el	el	PROPN
esrj-37073	15	5	desempeño	desempeño	PROPN
esrj-37073	15	6	de	de	X
esrj-37073	15	7	pronóstico	pronóstico	PROPN
esrj-37073	15	8	de	de	X
esrj-37073	15	9	dos	dos	PROPN
esrj-37073	15	10	modelos	modelo	NOUN
esrj-37073	15	11	no	no	DET
esrj-37073	15	12	lineares	lineare	NOUN
esrj-37073	15	13	,	,	PUNCT
esrj-37073	15	14	de	de	X
esrj-37073	15	15	método	método	X
esrj-37073	15	16	de	de	PROPN
esrj-37073	15	17	clasificación	clasificación	PROPN
esrj-37073	15	18	no	no	DET
esrj-37073	15	19	paramétrico	paramétrico	NOUN
esrj-37073	15	20	knn	knn	VERB
esrj-37073	15	21	y	y	PROPN
esrj-37073	15	22	de	de	PROPN
esrj-37073	15	23	redes	redes	PROPN
esrj-37073	15	24	neuronales	neuronales	PROPN
esrj-37073	15	25	con	con	PROPN
esrj-37073	15	26	alimentación	alimentación	PROPN
esrj-37073	15	27	avanzada	avanzada	PROPN
esrj-37073	15	28	(	(	PUNCT
esrj-37073	15	29	fnnn	fnnn	PROPN
esrj-37073	15	30	)	)	PUNCT
esrj-37073	15	31	,	,	PUNCT
esrj-37073	15	32	usando	usando	PROPN
esrj-37073	15	33	datos	datos	PROPN
esrj-37073	15	34	de	de	PROPN
esrj-37073	15	35	flujo	flujo	PROPN
esrj-37073	15	36	del	del	PROPN
esrj-37073	15	37	río	río	PROPN
esrj-37073	15	38	kizilirmak	kizilirmak	PROPN
esrj-37073	15	39	,	,	PUNCT
esrj-37073	15	40	el	el	PROPN
esrj-37073	15	41	mayor	mayor	PROPN
esrj-37073	15	42	de	de	PROPN
esrj-37073	15	43	turquía	turquía	PROPN
esrj-37073	15	44	.	.	PUNCT
esrj-37073	16	1	para	para	PROPN
esrj-37073	16	2	el	el	PROPN
esrj-37073	16	3	modelo	modelo	PROPN
esrj-37073	16	4	knn	knn	PROPN
esrj-37073	16	5	,	,	PUNCT
esrj-37073	16	6	los	los	PROPN
esrj-37073	16	7	parámetros	parámetros	PROPN
esrj-37073	16	8	requeridos	requerido	VERB
esrj-37073	16	9	son	son	PROPN
esrj-37073	16	10	tiempo	tiempo	PROPN
esrj-37073	16	11	de	de	PROPN
esrj-37073	16	12	retraso	retraso	PROPN
esrj-37073	16	13	,	,	PUNCT
esrj-37073	16	14	número	número	PROPN
esrj-37073	16	15	de	de	ADP
esrj-37073	16	16	vecindarios	vecindarios	PROPN
esrj-37073	16	17	cercanos	cercano	VERB
esrj-37073	16	18	y	y	PROPN
esrj-37073	16	19	dimensión	dimensión	PROPN
esrj-37073	16	20	de	de	X
esrj-37073	16	21	encrustamiento	encrustamiento	PROPN
esrj-37073	16	22	.	.	PUNCT
esrj-37073	17	1	el	el	PROPN
esrj-37073	17	2	tiempo	tiempo	PROPN
esrj-37073	17	3	óptimo	óptimo	PROPN
esrj-37073	17	4	de	de	X
esrj-37073	17	5	retraso	retraso	PROPN
esrj-37073	17	6	fue	fue	PROPN
esrj-37073	17	7	obtenido	obtenido	VERB
esrj-37073	17	8	con	con	PROPN
esrj-37073	17	9	la	la	X
esrj-37073	17	10	función	función	PROPN
esrj-37073	17	11	de	de	PROPN
esrj-37073	17	12	información	información	PROPN
esrj-37073	17	13	mutua	mutua	PROPN
esrj-37073	17	14	;	;	PUNCT
esrj-37073	17	15	el	el	PROPN
esrj-37073	17	16	número	número	PROPN
esrj-37073	17	17	de	de	ADP
esrj-37073	17	18	vecindarios	vecindarios	PROPN
esrj-37073	17	19	cercanos	cercano	VERB
esrj-37073	17	20	fue	fue	PROPN
esrj-37073	17	21	obtenido	obtenido	VERB
esrj-37073	17	22	con	con	PROPN
esrj-37073	17	23	la	la	PROPN
esrj-37073	17	24	optimización	optimización	PROPN
esrj-37073	17	25	de	de	X
esrj-37073	17	26	procesos	procesos	PROPN
esrj-37073	17	27	que	que	PROPN
esrj-37073	17	28	minimizan	minimizan	PROPN
esrj-37073	17	29	el	el	PROPN
esrj-37073	17	30	rmse	rmse	PROPN
esrj-37073	17	31	como	como	PROPN
esrj-37073	17	32	una	una	PROPN
esrj-37073	17	33	función	función	PROPN
esrj-37073	17	34	del	del	PROPN
esrj-37073	17	35	número	número	PROPN
esrj-37073	17	36	de	de	X
esrj-37073	17	37	vecindarios	vecindarios	PROPN
esrj-37073	17	38	y	y	PROPN
esrj-37073	17	39	la	la	PROPN
esrj-37073	17	40	dimensión	dimensión	PROPN
esrj-37073	17	41	de	de	PROPN
esrj-37073	17	42	incrustación	incrustación	PROPN
esrj-37073	17	43	fue	fue	PROPN
esrj-37073	17	44	obtenida	obtenida	PROPN
esrj-37073	17	45	con	con	PROPN
esrj-37073	17	46	el	el	PROPN
esrj-37073	17	47	método	método	PROPN
esrj-37073	17	48	de	de	PROPN
esrj-37073	17	49	dimensión	dimensión	PROPN
esrj-37073	17	50	correlativa	correlativa	PROPN
esrj-37073	17	51	.	.	PUNCT
esrj-37073	18	1	la	la	PROPN
esrj-37073	18	2	dimensión	dimensión	PROPN
esrj-37073	18	3	de	de	PROPN
esrj-37073	18	4	correlación	correlación	PROPN
esrj-37073	18	5	del	del	PROPN
esrj-37073	18	6	río	río	PROPN
esrj-37073	18	7	kizilirmak	kizilirmak	PROPN
esrj-37073	18	8	fue	fue	PROPN
esrj-37073	18	9	utilizado	utilizado	PROPN
esrj-37073	18	10	en	en	ADP
esrj-37073	18	11	la	la	PROPN
esrj-37073	18	12	formación	formación	PROPN
esrj-37073	18	13	de	de	PROPN
esrj-37073	18	14	la	la	X
esrj-37073	18	15	estructura	estructura	PROPN
esrj-37073	18	16	de	de	X
esrj-37073	18	17	ingreso	ingreso	PROPN
esrj-37073	18	18	de	de	PROPN
esrj-37073	18	19	las	las	PROPN
esrj-37073	18	20	redes	redes	PROPN
esrj-37073	18	21	ffnn	ffnn	PROPN
esrj-37073	18	22	.	.	PUNCT
esrj-37073	19	1	la	la	PROPN
esrj-37073	19	2	integración	integración	PROPN
esrj-37073	19	3	cercana	cercana	PROPN
esrj-37073	19	4	sobre	sobre	PROPN
esrj-37073	19	5	la	la	PROPN
esrj-37073	19	6	dimensión	dimensión	PROPN
esrj-37073	19	7	de	de	PROPN
esrj-37073	19	8	correlación	correlación	PROPN
esrj-37073	19	9	proveyó	proveyó	PROPN
esrj-37073	19	10	el	el	PROPN
esrj-37073	19	11	número	número	PROPN
esrj-37073	19	12	mínimo	mínimo	PROPN
esrj-37073	19	13	de	de	PROPN
esrj-37073	19	14	variables	variables	PROPN
esrj-37073	19	15	requeridas	requeridas	VERB
esrj-37073	19	16	para	para	PROPN
esrj-37073	19	17	caracterizar	caracterizar	PROPN
esrj-37073	19	18	el	el	PROPN
esrj-37073	19	19	sistema	sistema	PROPN
esrj-37073	19	20	y	y	PROPN
esrj-37073	19	21	el	el	PROPN
esrj-37073	19	22	número	número	PROPN
esrj-37073	19	23	máximo	máximo	PROPN
esrj-37073	19	24	de	de	PROPN
esrj-37073	19	25	variables	variables	PROPN
esrj-37073	19	26	requeridas	requeridas	AUX
esrj-37073	19	27	fue	fue	PROPN
esrj-37073	19	28	obtenido	obtenido	VERB
esrj-37073	19	29	con	con	PROPN
esrj-37073	19	30	el	el	PROPN
esrj-37073	19	31	número	número	PROPN
esrj-37073	19	32	entero	entero	PROPN
esrj-37073	19	33	por	por	PROPN
esrj-37073	19	34	encima	encima	PROPN
esrj-37073	19	35	del	del	PROPN
esrj-37073	19	36	valor	valor	NOUN
esrj-37073	19	37	(	(	PUNCT
esrj-37073	19	38	takens	taken	NOUN
esrj-37073	19	39	,	,	PUNCT
esrj-37073	19	40	1981	1981	NUM
esrj-37073	19	41	)	)	PUNCT
esrj-37073	19	42	.	.	PUNCT
esrj-37073	20	1	se	se	PROPN
esrj-37073	20	2	desarrollaron	desarrollaron	PROPN
esrj-37073	20	3	dos	dos	PROPN
esrj-37073	20	4	modelos	modelos	PROPN
esrj-37073	20	5	de	de	PROPN
esrj-37073	20	6	redes	redes	PROPN
esrj-37073	20	7	fnnn	fnnn	PROPN
esrj-37073	20	8	que	que	PROPN
esrj-37073	20	9	incorporan	incorporan	PROPN
esrj-37073	20	10	3	3	NUM
esrj-37073	20	11	y	y	PROPN
esrj-37073	20	12	7	7	NUM
esrj-37073	20	13	valores	valores	X
esrj-37073	20	14	de	de	X
esrj-37073	20	15	descargas	descargas	PROPN
esrj-37073	20	16	retrasadas	retrasadas	PROPN
esrj-37073	20	17	y	y	PROPN
esrj-37073	20	18	el	el	PROPN
esrj-37073	20	19	desempeño	desempeño	PROPN
esrj-37073	20	20	de	de	PROPN
esrj-37073	20	21	predicción	predicción	PROPN
esrj-37073	20	22	comparado	comparado	PROPN
esrj-37073	20	23	con	con	PROPN
esrj-37073	20	24	el	el	PROPN
esrj-37073	20	25	modelo	modelo	PROPN
esrj-37073	20	26	knn	knn	PROPN
esrj-37073	20	27	.	.	PUNCT
esrj-37073	21	1	los	los	PROPN
esrj-37073	21	2	resultados	resultado	VERB
esrj-37073	21	3	muestran	muestran	ADJ
esrj-37073	21	4	que	que	PROPN
esrj-37073	21	5	el	el	PROPN
esrj-37073	21	6	modelo	modelo	PROPN
esrj-37073	21	7	knn	knn	PROPN
esrj-37073	21	8	fue	fue	PROPN
esrj-37073	21	9	superior	superior	PROPN
esrj-37073	21	10	al	al	PROPN
esrj-37073	21	11	modelo	modelo	PROPN
esrj-37073	21	12	de	de	PROPN
esrj-37073	21	13	redes	redes	PROPN
esrj-37073	21	14	ffnn	ffnn	PROPN
esrj-37073	21	15	en	en	PROPN
esrj-37073	21	16	el	el	PROPN
esrj-37073	21	17	flujo	flujo	PROPN
esrj-37073	21	18	de	de	PROPN
esrj-37073	21	19	pronósticos	pronósticos	PROPN
esrj-37073	21	20	.	.	PUNCT
esrj-37073	22	1	sin	sin	PROPN
esrj-37073	22	2	embargo	embargo	PROPN
esrj-37073	22	3	,	,	PUNCT
esrj-37073	22	4	como	como	PROPN
esrj-37073	22	5	un	un	PROPN
esrj-37073	22	6	resultado	resultado	PROPN
esrj-37073	22	7	del	del	PROPN
esrj-37073	22	8	modelo	modelo	PROPN
esrj-37073	22	9	de	de	PROPN
esrj-37073	22	10	estructura	estructura	PROPN
esrj-37073	22	11	knn	knn	PROPN
esrj-37073	22	12	,	,	PUNCT
esrj-37073	22	13	el	el	PROPN
esrj-37073	22	14	modelo	modelo	PROPN
esrj-37073	22	15	falla	falla	PROPN
esrj-37073	22	16	en	en	PROPN
esrj-37073	22	17	los	los	PROPN
esrj-37073	22	18	valores	valores	PROPN
esrj-37073	22	19	pico	pico	PROPN
esrj-37073	22	20	.	.	PROPN
esrj-37073	22	21	adicionalmente	adicionalmente	PROPN
esrj-37073	22	22	,	,	PUNCT
esrj-37073	22	23	se	se	PROPN
esrj-37073	22	24	encontró	encontró	PROPN
esrj-37073	22	25	que	que	PROPN
esrj-37073	22	26	la	la	PROPN
esrj-37073	22	27	dimensión	dimensión	PROPN
esrj-37073	22	28	de	de	PROPN
esrj-37073	22	29	correlación	correlación	PROPN
esrj-37073	22	30	(	(	PUNCT
esrj-37073	22	31	de	de	X
esrj-37073	22	32	existir	existir	ADJ
esrj-37073	22	33	)	)	PUNCT
esrj-37073	22	34	podría	podría	NOUN
esrj-37073	22	35	ser	ser	NOUN
esrj-37073	22	36	usada	usada	PROPN
esrj-37073	22	37	eficientemente	eficientemente	PROPN
esrj-37073	22	38	en	en	PROPN
esrj-37073	22	39	series	series	PROPN
esrj-37073	22	40	temporales	temporales	PROPN
esrj-37073	22	41	donde	donde	PROPN
esrj-37073	22	42	la	la	PROPN
esrj-37073	22	43	determinación	determinación	PROPN
esrj-37073	22	44	de	de	PROPN
esrj-37073	22	45	estructura	estructura	PROPN
esrj-37073	22	46	de	de	X
esrj-37073	22	47	ingreso	ingreso	PROPN
esrj-37073	22	48	es	es	X
esrj-37073	22	49	difícil	difícil	PROPN
esrj-37073	22	50	por	por	PROPN
esrj-37073	22	51	la	la	PROPN
esrj-37073	22	52	gran	gran	PROPN
esrj-37073	22	53	interdependencia	interdependencia	PROPN
esrj-37073	22	54	,	,	PUNCT
esrj-37073	22	55	como	como	PROPN
esrj-37073	22	56	en	en	PROPN
esrj-37073	22	57	las	las	PROPN
esrj-37073	22	58	series	series	PROPN
esrj-37073	22	59	temporales	temporales	PROPN
esrj-37073	22	60	de	de	PROPN
esrj-37073	22	61	flujo	flujo	PROPN
esrj-37073	22	62	.	.	PUNCT
esrj-37073	23	1	palabras	palabras	PROPN
esrj-37073	23	2	clave	clave	PROPN
esrj-37073	23	3	:	:	PUNCT
esrj-37073	23	4	kizilirmak	kizilirmak	PROPN
esrj-37073	23	5	,	,	PUNCT
esrj-37073	23	6	método	método	X
esrj-37073	23	7	de	de	PROPN
esrj-37073	23	8	clasificación	clasificación	PROPN
esrj-37073	23	9	no	no	DET
esrj-37073	23	10	paramétrico	paramétrico	NOUN
esrj-37073	23	11	knn	knn	PROPN
esrj-37073	23	12	,	,	PUNCT
esrj-37073	23	13	redes	redes	PROPN
esrj-37073	23	14	neuronales	neuronale	VERB
esrj-37073	23	15	con	con	PROPN
esrj-37073	23	16	alimentación	alimentación	PROPN
esrj-37073	23	17	avanzada	avanzada	PROPN
esrj-37073	23	18	,	,	PUNCT
esrj-37073	23	19	funciones	funciones	PROPN
esrj-37073	23	20	de	de	PROPN
esrj-37073	23	21	información	información	PROPN
esrj-37073	23	22	mutua	mutua	PROPN
esrj-37073	23	23	,	,	PUNCT
esrj-37073	23	24	dimensión	dimensión	PROPN
esrj-37073	23	25	de	de	PROPN
esrj-37073	23	26	correlación	correlación	PROPN
esrj-37073	23	27	.	.	PUNCT
esrj-37073	24	1	record	record	PROPN
esrj-37073	24	2	manuscript	manuscript	NOUN
esrj-37073	24	3	received	receive	VERB
esrj-37073	24	4	:	:	PUNCT
esrj-37073	24	5	11/02/2013	11/02/2013	NUM
esrj-37073	24	6	accepted	accept	VERB
esrj-37073	24	7	for	for	ADP
esrj-37073	24	8	publication	publication	NOUN
esrj-37073	24	9	:	:	PUNCT
esrj-37073	24	10	01/11/2013	01/11/2013	NUM
esrj-37073	24	11	abstract	abstract	ADJ
esrj-37073	24	12	resumen	resuman	NOUN
esrj-37073	24	13	key	key	ADJ
esrj-37073	24	14	words	word	NOUN
esrj-37073	24	15	:	:	PUNCT
esrj-37073	24	16	kızılırmak	kızılırmak	PROPN
esrj-37073	24	17	,	,	PUNCT
esrj-37073	24	18	k	k	X
esrj-37073	24	19	-	-	PUNCT
esrj-37073	24	20	nearest	near	ADJ
esrj-37073	24	21	neighbor	neighbor	NOUN
esrj-37073	24	22	,	,	PUNCT
esrj-37073	24	23	feedforward	feedforward	ADJ
esrj-37073	24	24	neural	neural	ADJ
esrj-37073	24	25	networks	network	NOUN
esrj-37073	24	26	,	,	PUNCT
esrj-37073	24	27	mutual	mutual	ADJ
esrj-37073	24	28	information	information	NOUN
esrj-37073	24	29	function	function	NOUN
esrj-37073	24	30	,	,	PUNCT
esrj-37073	24	31	correlation	correlation	NOUN
esrj-37073	24	32	dimension	dimension	NOUN
esrj-37073	24	33	1	1	NUM
esrj-37073	24	34	.	.	PUNCT
esrj-37073	25	1	introduction	introduction	NOUN
esrj-37073	25	2	reliable	reliable	ADJ
esrj-37073	25	3	and	and	CCONJ
esrj-37073	25	4	accurate	accurate	ADJ
esrj-37073	25	5	stream	stream	NOUN
esrj-37073	25	6	flow	flow	NOUN
esrj-37073	25	7	forecasting	forecasting	NOUN
esrj-37073	25	8	is	be	AUX
esrj-37073	25	9	essential	essential	ADJ
esrj-37073	25	10	for	for	ADP
esrj-37073	25	11	water	water	NOUN
esrj-37073	25	12	resources	resource	NOUN
esrj-37073	25	13	management	management	NOUN
esrj-37073	25	14	.	.	PUNCT
esrj-37073	26	1	stream	stream	NOUN
esrj-37073	26	2	flow	flow	NOUN
esrj-37073	26	3	simulations	simulation	NOUN
esrj-37073	26	4	and	and	CCONJ
esrj-37073	26	5	forecasts	forecast	NOUN
esrj-37073	26	6	are	be	AUX
esrj-37073	26	7	also	also	ADV
esrj-37073	26	8	important	important	ADJ
esrj-37073	26	9	for	for	ADP
esrj-37073	26	10	optimization	optimization	NOUN
esrj-37073	26	11	of	of	ADP
esrj-37073	26	12	water	water	NOUN
esrj-37073	26	13	resources	resource	NOUN
esrj-37073	26	14	planning	planning	NOUN
esrj-37073	26	15	and	and	CCONJ
esrj-37073	26	16	allocation	allocation	NOUN
esrj-37073	26	17	.	.	PUNCT
esrj-37073	27	1	therefore	therefore	ADV
esrj-37073	27	2	,	,	PUNCT
esrj-37073	27	3	in	in	ADP
esrj-37073	27	4	addition	addition	NOUN
esrj-37073	27	5	to	to	ADP
esrj-37073	27	6	many	many	ADJ
esrj-37073	27	7	other	other	ADJ
esrj-37073	27	8	reasons	reason	NOUN
esrj-37073	27	9	,	,	PUNCT
esrj-37073	27	10	understanding	understand	VERB
esrj-37073	27	11	stream	stream	NOUN
esrj-37073	27	12	flow	flow	NOUN
esrj-37073	27	13	dynamics	dynamic	NOUN
esrj-37073	27	14	constitutes	constitute	VERB
esrj-37073	27	15	one	one	NUM
esrj-37073	27	16	of	of	ADP
esrj-37073	27	17	the	the	DET
esrj-37073	27	18	most	most	ADV
esrj-37073	27	19	important	important	ADJ
esrj-37073	27	20	problems	problem	NOUN
esrj-37073	27	21	in	in	ADP
esrj-37073	27	22	hydrology	hydrology	NOUN
esrj-37073	27	23	and	and	CCONJ
esrj-37073	27	24	water	water	NOUN
esrj-37073	27	25	resources	resource	NOUN
esrj-37073	27	26	.	.	PUNCT
esrj-37073	28	1	for	for	ADP
esrj-37073	28	2	this	this	DET
esrj-37073	28	3	purpose	purpose	NOUN
esrj-37073	28	4	,	,	PUNCT
esrj-37073	28	5	many	many	ADJ
esrj-37073	28	6	data	data	NOUN
esrj-37073	28	7	-	-	PUNCT
esrj-37073	28	8	driven	drive	VERB
esrj-37073	28	9	models	model	NOUN
esrj-37073	28	10	have	have	AUX
esrj-37073	28	11	been	be	AUX
esrj-37073	28	12	developed	develop	VERB
esrj-37073	28	13	,	,	PUNCT
esrj-37073	28	14	including	include	VERB
esrj-37073	28	15	linear	linear	PROPN
esrj-37073	28	16	,	,	PUNCT
esrj-37073	28	17	nonlinear	nonlinear	ADJ
esrj-37073	28	18	,	,	PUNCT
esrj-37073	28	19	parametric	parametric	ADJ
esrj-37073	28	20	and	and	CCONJ
esrj-37073	28	21	nonparametric	nonparametric	NOUN
esrj-37073	28	22	models	model	NOUN
esrj-37073	28	23	for	for	ADP
esrj-37073	28	24	hydrologic	hydrologic	ADJ
esrj-37073	28	25	time	time	NOUN
esrj-37073	28	26	series	series	PROPN
esrj-37073	28	27	prediction	prediction	NOUN
esrj-37073	28	28	in	in	ADP
esrj-37073	28	29	the	the	DET
esrj-37073	28	30	past	past	ADJ
esrj-37073	28	31	decades	decade	NOUN
esrj-37073	28	32	(	(	PUNCT
esrj-37073	28	33	marques	marques	X
esrj-37073	28	34	et	et	NOUN
esrj-37073	28	35	120	120	NUM
esrj-37073	28	36	al	al	PROPN
esrj-37073	28	37	.	.	PROPN
esrj-37073	28	38	,	,	PUNCT
esrj-37073	28	39	2006	2006	NUM
esrj-37073	28	40	)	)	PUNCT
esrj-37073	28	41	.	.	PUNCT
esrj-37073	29	1	generally	generally	ADV
esrj-37073	29	2	,	,	PUNCT
esrj-37073	29	3	in	in	ADP
esrj-37073	29	4	regard	regard	NOUN
esrj-37073	29	5	to	to	ADP
esrj-37073	29	6	system	system	NOUN
esrj-37073	29	7	dynamics	dynamic	NOUN
esrj-37073	29	8	,	,	PUNCT
esrj-37073	29	9	there	there	PRON
esrj-37073	29	10	are	be	VERB
esrj-37073	29	11	two	two	NUM
esrj-37073	29	12	basic	basic	ADJ
esrj-37073	29	13	assumptions	assumption	NOUN
esrj-37073	29	14	that	that	PRON
esrj-37073	29	15	underlie	underlie	VERB
esrj-37073	29	16	different	different	ADJ
esrj-37073	29	17	modeling	modeling	NOUN
esrj-37073	29	18	techniques	technique	NOUN
esrj-37073	29	19	,	,	PUNCT
esrj-37073	29	20	stochastic	stochastic	ADJ
esrj-37073	29	21	and	and	CCONJ
esrj-37073	29	22	chaotic	chaotic	ADJ
esrj-37073	29	23	dynamics	dynamic	NOUN
esrj-37073	29	24	.	.	PUNCT
esrj-37073	30	1	regarding	regard	VERB
esrj-37073	30	2	the	the	DET
esrj-37073	30	3	former	former	ADJ
esrj-37073	30	4	assumption	assumption	NOUN
esrj-37073	30	5	,	,	PUNCT
esrj-37073	30	6	the	the	DET
esrj-37073	30	7	observed	observe	VERB
esrj-37073	30	8	hydrologic	hydrologic	NOUN
esrj-37073	30	9	time	time	NOUN
esrj-37073	30	10	series	series	PROPN
esrj-37073	30	11	originated	originate	VERB
esrj-37073	30	12	from	from	ADP
esrj-37073	30	13	a	a	DET
esrj-37073	30	14	stochastic	stochastic	ADJ
esrj-37073	30	15	process	process	NOUN
esrj-37073	30	16	with	with	ADP
esrj-37073	30	17	an	an	DET
esrj-37073	30	18	infinite	infinite	ADJ
esrj-37073	30	19	number	number	NOUN
esrj-37073	30	20	of	of	ADP
esrj-37073	30	21	degrees	degree	NOUN
esrj-37073	30	22	of	of	ADP
esrj-37073	30	23	freedom	freedom	NOUN
esrj-37073	30	24	.	.	PUNCT
esrj-37073	31	1	to	to	ADP
esrj-37073	31	2	this	this	DET
esrj-37073	31	3	assumption	assumption	NOUN
esrj-37073	31	4	,	,	PUNCT
esrj-37073	31	5	the	the	DET
esrj-37073	31	6	mean	mean	ADJ
esrj-37073	31	7	behavior	behavior	NOUN
esrj-37073	31	8	of	of	ADP
esrj-37073	31	9	a	a	DET
esrj-37073	31	10	time	time	NOUN
esrj-37073	31	11	series	series	NOUN
esrj-37073	31	12	could	could	AUX
esrj-37073	31	13	be	be	AUX
esrj-37073	31	14	captured	capture	VERB
esrj-37073	31	15	with	with	ADP
esrj-37073	31	16	linear	linear	ADJ
esrj-37073	31	17	models	model	NOUN
esrj-37073	31	18	such	such	ADJ
esrj-37073	31	19	as	as	ADP
esrj-37073	31	20	autoregressive	autoregressive	ADJ
esrj-37073	31	21	,	,	PUNCT
esrj-37073	31	22	autoregressive	autoregressive	ADJ
esrj-37073	31	23	moving	move	VERB
esrj-37073	31	24	-	-	PUNCT
esrj-37073	31	25	average	average	NOUN
esrj-37073	31	26	(	(	PUNCT
esrj-37073	31	27	al	al	PROPN
esrj-37073	31	28	-	-	PUNCT
esrj-37073	31	29	awadhi	awadhi	PROPN
esrj-37073	31	30	and	and	CCONJ
esrj-37073	31	31	jolliffe	jolliffe	VERB
esrj-37073	31	32	,	,	PUNCT
esrj-37073	31	33	1998	1998	NUM
esrj-37073	31	34	;	;	PUNCT
esrj-37073	31	35	toth	toth	PROPN
esrj-37073	31	36	et	et	PROPN
esrj-37073	31	37	al	al	PROPN
esrj-37073	31	38	.	.	PROPN
esrj-37073	31	39	,	,	PUNCT
esrj-37073	31	40	2000	2000	NUM
esrj-37073	31	41	)	)	PUNCT
esrj-37073	31	42	,	,	PUNCT
esrj-37073	31	43	autoregressive	autoregressive	ADJ
esrj-37073	31	44	integrated	integrated	ADJ
esrj-37073	31	45	moving	moving	NOUN
esrj-37073	31	46	-	-	PUNCT
esrj-37073	31	47	average	average	NOUN
esrj-37073	31	48	(	(	PUNCT
esrj-37073	31	49	chang	chang	PROPN
esrj-37073	31	50	et	et	PROPN
esrj-37073	31	51	al	al	PROPN
esrj-37073	31	52	.	.	PROPN
esrj-37073	31	53	,	,	PUNCT
esrj-37073	31	54	2002	2002	NUM
esrj-37073	31	55	;	;	PUNCT
esrj-37073	31	56	lisi	lisi	NOUN
esrj-37073	31	57	and	and	CCONJ
esrj-37073	31	58	villi	villi	NOUN
esrj-37073	31	59	,	,	PUNCT
esrj-37073	31	60	2001	2001	NUM
esrj-37073	31	61	)	)	PUNCT
esrj-37073	31	62	and	and	CCONJ
esrj-37073	31	63	seasonal	seasonal	ADJ
esrj-37073	31	64	autoregressive	autoregressive	ADJ
esrj-37073	31	65	integrated	integrated	ADJ
esrj-37073	31	66	moving	moving	NOUN
esrj-37073	31	67	-	-	PUNCT
esrj-37073	31	68	average	average	NOUN
esrj-37073	31	69	(	(	PUNCT
esrj-37073	31	70	modarres	modarre	NOUN
esrj-37073	31	71	,	,	PUNCT
esrj-37073	31	72	2007	2007	NUM
esrj-37073	31	73	;	;	PUNCT
esrj-37073	31	74	ooms	oom	NOUN
esrj-37073	31	75	and	and	CCONJ
esrj-37073	31	76	franses	franse	NOUN
esrj-37073	31	77	,	,	PUNCT
esrj-37073	31	78	2001	2001	NUM
esrj-37073	31	79	;	;	PUNCT
esrj-37073	31	80	pekárová	pekárová	PROPN
esrj-37073	31	81	et	et	PROPN
esrj-37073	31	82	al	al	PROPN
esrj-37073	31	83	.	.	PROPN
esrj-37073	31	84	,	,	PUNCT
esrj-37073	31	85	2009	2009	NUM
esrj-37073	31	86	)	)	PUNCT
esrj-37073	31	87	,	,	PUNCT
esrj-37073	31	88	from	from	ADP
esrj-37073	31	89	which	which	PRON
esrj-37073	31	90	great	great	ADJ
esrj-37073	31	91	results	result	NOUN
esrj-37073	31	92	have	have	AUX
esrj-37073	31	93	been	be	AUX
esrj-37073	31	94	obtained	obtain	VERB
esrj-37073	31	95	.	.	PUNCT
esrj-37073	32	1	however	however	ADV
esrj-37073	32	2	,	,	PUNCT
esrj-37073	32	3	to	to	PART
esrj-37073	32	4	utilize	utilize	VERB
esrj-37073	32	5	these	these	DET
esrj-37073	32	6	models	model	NOUN
esrj-37073	32	7	,	,	PUNCT
esrj-37073	32	8	a	a	DET
esrj-37073	32	9	priori	priori	ADJ
esrj-37073	32	10	assumptions	assumption	NOUN
esrj-37073	32	11	are	be	AUX
esrj-37073	32	12	required	require	VERB
esrj-37073	32	13	,	,	PUNCT
esrj-37073	32	14	such	such	ADJ
esrj-37073	32	15	as	as	ADP
esrj-37073	32	16	stationarity	stationarity	NOUN
esrj-37073	32	17	and	and	CCONJ
esrj-37073	32	18	gaussian	gaussian	ADJ
esrj-37073	32	19	distribution	distribution	NOUN
esrj-37073	32	20	.	.	PUNCT
esrj-37073	33	1	as	as	SCONJ
esrj-37073	33	2	most	most	ADJ
esrj-37073	33	3	hydrological	hydrological	ADJ
esrj-37073	33	4	time	time	NOUN
esrj-37073	33	5	series	series	PROPN
esrj-37073	33	6	involve	involve	VERB
esrj-37073	33	7	non	non	ADJ
esrj-37073	33	8	-	-	ADJ
esrj-37073	33	9	stationarity	stationarity	ADJ
esrj-37073	33	10	and	and	CCONJ
esrj-37073	33	11	non	non	ADJ
esrj-37073	33	12	-	-	ADJ
esrj-37073	33	13	gaussian	gaussian	ADJ
esrj-37073	33	14	conditions	condition	NOUN
esrj-37073	33	15	,	,	PUNCT
esrj-37073	33	16	the	the	DET
esrj-37073	33	17	data	datum	NOUN
esrj-37073	33	18	should	should	AUX
esrj-37073	33	19	be	be	AUX
esrj-37073	33	20	transformed	transform	VERB
esrj-37073	33	21	before	before	SCONJ
esrj-37073	33	22	it	it	PRON
esrj-37073	33	23	can	can	AUX
esrj-37073	33	24	be	be	AUX
esrj-37073	33	25	used	use	VERB
esrj-37073	33	26	in	in	ADP
esrj-37073	33	27	stochastic	stochastic	ADJ
esrj-37073	33	28	models	model	NOUN
esrj-37073	33	29	.	.	PUNCT
esrj-37073	34	1	however	however	ADV
esrj-37073	34	2	,	,	PUNCT
esrj-37073	34	3	after	after	ADP
esrj-37073	34	4	this	this	DET
esrj-37073	34	5	transformation	transformation	NOUN
esrj-37073	34	6	,	,	PUNCT
esrj-37073	34	7	nonlinearity	nonlinearity	NOUN
esrj-37073	34	8	still	still	ADV
esrj-37073	34	9	exists	exist	VERB
esrj-37073	34	10	,	,	PUNCT
esrj-37073	34	11	and	and	CCONJ
esrj-37073	34	12	time	time	NOUN
esrj-37073	34	13	series	series	PROPN
esrj-37073	34	14	are	be	AUX
esrj-37073	34	15	processed	process	VERB
esrj-37073	34	16	with	with	ADP
esrj-37073	34	17	a	a	DET
esrj-37073	34	18	linearity	linearity	NOUN
esrj-37073	34	19	assumption	assumption	NOUN
esrj-37073	34	20	(	(	PUNCT
esrj-37073	34	21	chen	chen	PROPN
esrj-37073	34	22	et	et	PROPN
esrj-37073	34	23	al	al	PROPN
esrj-37073	34	24	.	.	PROPN
esrj-37073	34	25	,	,	PUNCT
esrj-37073	34	26	2008	2008	NUM
esrj-37073	34	27	)	)	PUNCT
esrj-37073	34	28	.	.	PUNCT
esrj-37073	35	1	recent	recent	ADJ
esrj-37073	35	2	studies	study	NOUN
esrj-37073	35	3	have	have	AUX
esrj-37073	35	4	shown	show	VERB
esrj-37073	35	5	that	that	SCONJ
esrj-37073	35	6	the	the	DET
esrj-37073	35	7	complex	complex	ADJ
esrj-37073	35	8	nonlinear	nonlinear	ADJ
esrj-37073	35	9	behavior	behavior	NOUN
esrj-37073	35	10	of	of	ADP
esrj-37073	35	11	stream	stream	NOUN
esrj-37073	35	12	flow	flow	NOUN
esrj-37073	35	13	dynamics	dynamic	NOUN
esrj-37073	35	14	should	should	AUX
esrj-37073	35	15	not	not	PART
esrj-37073	35	16	necessarily	necessarily	ADV
esrj-37073	35	17	be	be	AUX
esrj-37073	35	18	the	the	DET
esrj-37073	35	19	outcome	outcome	NOUN
esrj-37073	35	20	of	of	ADP
esrj-37073	35	21	a	a	DET
esrj-37073	35	22	stochastic	stochastic	ADJ
esrj-37073	35	23	process	process	NOUN
esrj-37073	35	24	.	.	PUNCT
esrj-37073	36	1	with	with	ADP
esrj-37073	36	2	the	the	DET
esrj-37073	36	3	advent	advent	NOUN
esrj-37073	36	4	of	of	ADP
esrj-37073	36	5	deterministic	deterministic	ADJ
esrj-37073	36	6	chaos	chaos	NOUN
esrj-37073	36	7	theory	theory	NOUN
esrj-37073	36	8	,	,	PUNCT
esrj-37073	36	9	a	a	DET
esrj-37073	36	10	few	few	ADJ
esrj-37073	36	11	hydrologic	hydrologic	NOUN
esrj-37073	36	12	modeling	modeling	NOUN
esrj-37073	36	13	studies	study	NOUN
esrj-37073	36	14	have	have	AUX
esrj-37073	36	15	suggested	suggest	VERB
esrj-37073	36	16	irregular	irregular	ADJ
esrj-37073	36	17	behavior	behavior	NOUN
esrj-37073	36	18	could	could	AUX
esrj-37073	36	19	be	be	AUX
esrj-37073	36	20	the	the	DET
esrj-37073	36	21	outcome	outcome	NOUN
esrj-37073	36	22	of	of	ADP
esrj-37073	36	23	simple	simple	ADJ
esrj-37073	36	24	deterministic	deterministic	ADJ
esrj-37073	36	25	systems	system	NOUN
esrj-37073	36	26	influenced	influence	VERB
esrj-37073	36	27	by	by	ADP
esrj-37073	36	28	a	a	DET
esrj-37073	36	29	few	few	ADJ
esrj-37073	36	30	nonlinear	nonlinear	ADJ
esrj-37073	36	31	interdependent	interdependent	ADJ
esrj-37073	36	32	variables	variable	NOUN
esrj-37073	36	33	(	(	PUNCT
esrj-37073	36	34	khokhlov	khokhlov	PROPN
esrj-37073	36	35	et	et	PROPN
esrj-37073	36	36	al	al	PROPN
esrj-37073	36	37	.	.	PROPN
esrj-37073	36	38	,	,	PUNCT
esrj-37073	36	39	2008	2008	NUM
esrj-37073	36	40	;	;	PUNCT
esrj-37073	36	41	sivakumar	sivakumar	PROPN
esrj-37073	36	42	,	,	PUNCT
esrj-37073	36	43	2003	2003	NUM
esrj-37073	36	44	;	;	PUNCT
esrj-37073	36	45	yu	yu	PROPN
esrj-37073	36	46	et	et	PROPN
esrj-37073	36	47	al	al	PROPN
esrj-37073	36	48	.	.	PROPN
esrj-37073	36	49	,	,	PUNCT
esrj-37073	36	50	2011	2011	NUM
esrj-37073	36	51	)	)	PUNCT
esrj-37073	36	52	.	.	PUNCT
esrj-37073	37	1	numerous	numerous	ADJ
esrj-37073	37	2	researchers	researcher	NOUN
esrj-37073	37	3	have	have	AUX
esrj-37073	37	4	tried	try	VERB
esrj-37073	37	5	to	to	PART
esrj-37073	37	6	reveal	reveal	VERB
esrj-37073	37	7	chaotic	chaotic	ADJ
esrj-37073	37	8	behavior	behavior	NOUN
esrj-37073	37	9	in	in	ADP
esrj-37073	37	10	hydrologic	hydrologic	ADJ
esrj-37073	37	11	time	time	NOUN
esrj-37073	37	12	series	series	NOUN
esrj-37073	37	13	,	,	PUNCT
esrj-37073	37	14	such	such	ADJ
esrj-37073	37	15	as	as	ADP
esrj-37073	37	16	river	river	NOUN
esrj-37073	37	17	flow	flow	NOUN
esrj-37073	37	18	(	(	PUNCT
esrj-37073	37	19	ng	ng	PROPN
esrj-37073	37	20	et	et	PROPN
esrj-37073	37	21	al	al	PROPN
esrj-37073	37	22	.	.	PROPN
esrj-37073	37	23	,	,	PUNCT
esrj-37073	37	24	2007	2007	NUM
esrj-37073	37	25	;	;	PUNCT
esrj-37073	37	26	sivakumar	sivakumar	PROPN
esrj-37073	37	27	,	,	PUNCT
esrj-37073	37	28	2007	2007	NUM
esrj-37073	37	29	;	;	PUNCT
esrj-37073	37	30	sivakumar	sivakumar	PROPN
esrj-37073	37	31	et	et	PROPN
esrj-37073	37	32	al	al	PROPN
esrj-37073	37	33	.	.	PROPN
esrj-37073	37	34	,	,	PUNCT
esrj-37073	37	35	2001	2001	NUM
esrj-37073	37	36	)	)	PUNCT
esrj-37073	37	37	,	,	PUNCT
esrj-37073	37	38	lake	lake	NOUN
esrj-37073	37	39	level	level	NOUN
esrj-37073	37	40	(	(	PUNCT
esrj-37073	37	41	frison	frison	NOUN
esrj-37073	37	42	et	et	PROPN
esrj-37073	37	43	al	al	PROPN
esrj-37073	37	44	.	.	PROPN
esrj-37073	37	45	,	,	PUNCT
esrj-37073	37	46	1999	1999	NUM
esrj-37073	37	47	;	;	PUNCT
esrj-37073	37	48	khokhlov	khokhlov	PROPN
esrj-37073	37	49	et	et	PROPN
esrj-37073	37	50	al	al	PROPN
esrj-37073	37	51	.	.	PROPN
esrj-37073	37	52	,	,	PUNCT
esrj-37073	37	53	2008	2008	NUM
esrj-37073	37	54	)	)	PUNCT
esrj-37073	37	55	and	and	CCONJ
esrj-37073	37	56	rainfall	rainfall	NOUN
esrj-37073	37	57	(	(	PUNCT
esrj-37073	37	58	dhanya	dhanya	NOUN
esrj-37073	37	59	and	and	CCONJ
esrj-37073	37	60	kumar	kumar	PROPN
esrj-37073	37	61	,	,	PUNCT
esrj-37073	37	62	2011	2011	NUM
esrj-37073	37	63	;	;	PUNCT
esrj-37073	37	64	sivakumar	sivakumar	PROPN
esrj-37073	37	65	et	et	PROPN
esrj-37073	37	66	al	al	PROPN
esrj-37073	37	67	.	.	PROPN
esrj-37073	37	68	,	,	PUNCT
esrj-37073	37	69	2006	2006	NUM
esrj-37073	37	70	)	)	PUNCT
esrj-37073	37	71	.	.	PUNCT
esrj-37073	38	1	because	because	SCONJ
esrj-37073	38	2	the	the	DET
esrj-37073	38	3	studies	study	NOUN
esrj-37073	38	4	revealed	reveal	VERB
esrj-37073	38	5	possible	possible	ADJ
esrj-37073	38	6	chaotic	chaotic	ADJ
esrj-37073	38	7	behavior	behavior	NOUN
esrj-37073	38	8	in	in	ADP
esrj-37073	38	9	stream	stream	NOUN
esrj-37073	38	10	flow	flow	NOUN
esrj-37073	38	11	dynamics	dynamic	NOUN
esrj-37073	38	12	,	,	PUNCT
esrj-37073	38	13	the	the	DET
esrj-37073	38	14	requisition	requisition	NOUN
esrj-37073	38	15	for	for	ADP
esrj-37073	38	16	chaotic	chaotic	ADJ
esrj-37073	38	17	prediction	prediction	NOUN
esrj-37073	38	18	methods	method	NOUN
esrj-37073	38	19	in	in	ADP
esrj-37073	38	20	stream	stream	NOUN
esrj-37073	38	21	flow	flow	NOUN
esrj-37073	38	22	was	be	AUX
esrj-37073	38	23	obvious	obvious	ADJ
esrj-37073	38	24	.	.	PUNCT
esrj-37073	39	1	the	the	DET
esrj-37073	39	2	most	most	ADV
esrj-37073	39	3	employed	employ	VERB
esrj-37073	39	4	prediction	prediction	NOUN
esrj-37073	39	5	method	method	NOUN
esrj-37073	39	6	for	for	ADP
esrj-37073	39	7	chaotic	chaotic	ADJ
esrj-37073	39	8	hydrological	hydrological	ADJ
esrj-37073	39	9	time	time	NOUN
esrj-37073	39	10	series	series	PROPN
esrj-37073	39	11	is	be	AUX
esrj-37073	39	12	the	the	DET
esrj-37073	39	13	k	k	PROPN
esrj-37073	39	14	-	-	PUNCT
esrj-37073	39	15	nearest	near	ADJ
esrj-37073	39	16	neighbor	neighbor	NOUN
esrj-37073	39	17	(	(	PUNCT
esrj-37073	39	18	k	k	NOUN
esrj-37073	39	19	-	-	PUNCT
esrj-37073	39	20	nn	nn	NOUN
esrj-37073	39	21	)	)	PUNCT
esrj-37073	39	22	,	,	PUNCT
esrj-37073	39	23	which	which	PRON
esrj-37073	39	24	was	be	AUX
esrj-37073	39	25	used	use	VERB
esrj-37073	39	26	in	in	ADP
esrj-37073	39	27	this	this	DET
esrj-37073	39	28	study	study	NOUN
esrj-37073	39	29	(	(	PUNCT
esrj-37073	39	30	elshorbagy	elshorbagy	NOUN
esrj-37073	39	31	et	et	PROPN
esrj-37073	39	32	al	al	PROPN
esrj-37073	39	33	.	.	PROPN
esrj-37073	39	34	,	,	PUNCT
esrj-37073	39	35	2002	2002	NUM
esrj-37073	39	36	;	;	PUNCT
esrj-37073	39	37	liu	liu	PROPN
esrj-37073	39	38	et	et	PROPN
esrj-37073	39	39	al	al	PROPN
esrj-37073	39	40	.	.	PROPN
esrj-37073	39	41	,	,	PUNCT
esrj-37073	39	42	1998	1998	NUM
esrj-37073	39	43	;	;	PUNCT
esrj-37073	39	44	sivakumar	sivakumar	PROPN
esrj-37073	39	45	,	,	PUNCT
esrj-37073	39	46	2003	2003	NUM
esrj-37073	39	47	;	;	PUNCT
esrj-37073	39	48	wu	wu	PROPN
esrj-37073	39	49	et	et	PROPN
esrj-37073	39	50	al	al	PROPN
esrj-37073	39	51	.	.	PROPN
esrj-37073	39	52	,	,	PUNCT
esrj-37073	39	53	2009	2009	NUM
esrj-37073	39	54	)	)	PUNCT
esrj-37073	39	55	.	.	PUNCT
esrj-37073	40	1	however	however	ADV
esrj-37073	40	2	,	,	PUNCT
esrj-37073	40	3	in	in	ADP
esrj-37073	40	4	the	the	DET
esrj-37073	40	5	hydrology	hydrology	NOUN
esrj-37073	40	6	literature	literature	NOUN
esrj-37073	40	7	,	,	PUNCT
esrj-37073	40	8	the	the	DET
esrj-37073	40	9	studies	study	NOUN
esrj-37073	40	10	that	that	PRON
esrj-37073	40	11	compare	compare	VERB
esrj-37073	40	12	the	the	DET
esrj-37073	40	13	modeling	modeling	NOUN
esrj-37073	40	14	capability	capability	NOUN
esrj-37073	40	15	of	of	ADP
esrj-37073	40	16	the	the	DET
esrj-37073	40	17	k	k	PROPN
esrj-37073	40	18	-	-	PUNCT
esrj-37073	40	19	nn	nn	ADJ
esrj-37073	40	20	approach	approach	NOUN
esrj-37073	40	21	with	with	ADP
esrj-37073	40	22	other	other	ADJ
esrj-37073	40	23	nonlinear	nonlinear	ADJ
esrj-37073	40	24	modeling	modeling	NOUN
esrj-37073	40	25	techniques	technique	NOUN
esrj-37073	40	26	are	be	AUX
esrj-37073	40	27	limited	limited	ADJ
esrj-37073	40	28	.	.	PUNCT
esrj-37073	41	1	to	to	PART
esrj-37073	41	2	obtain	obtain	VERB
esrj-37073	41	3	more	more	ADJ
esrj-37073	41	4	insight	insight	NOUN
esrj-37073	41	5	into	into	ADP
esrj-37073	41	6	the	the	DET
esrj-37073	41	7	modeling	modeling	NOUN
esrj-37073	41	8	capability	capability	NOUN
esrj-37073	41	9	of	of	ADP
esrj-37073	41	10	k	k	PROPN
esrj-37073	41	11	-	-	PUNCT
esrj-37073	41	12	nn	nn	PROPN
esrj-37073	41	13	,	,	PUNCT
esrj-37073	41	14	another	another	DET
esrj-37073	41	15	widely	widely	ADV
esrj-37073	41	16	used	use	VERB
esrj-37073	41	17	nonlinear	nonlinear	ADJ
esrj-37073	41	18	modeling	modeling	NOUN
esrj-37073	41	19	technique	technique	NOUN
esrj-37073	41	20	the	the	DET
esrj-37073	41	21	feed	feed	NOUN
esrj-37073	41	22	-	-	PUNCT
esrj-37073	41	23	forward	forward	ADV
esrj-37073	41	24	neural	neural	ADJ
esrj-37073	41	25	network	network	NOUN
esrj-37073	41	26	(	(	PUNCT
esrj-37073	41	27	ffnn	ffnn	PROPN
esrj-37073	41	28	)	)	PUNCT
esrj-37073	41	29	(	(	PUNCT
esrj-37073	41	30	araghinejad	araghinejad	PROPN
esrj-37073	41	31	et	et	PROPN
esrj-37073	41	32	al	al	PROPN
esrj-37073	41	33	.	.	PROPN
esrj-37073	41	34	,	,	PUNCT
esrj-37073	41	35	2011	2011	NUM
esrj-37073	41	36	;	;	PUNCT
esrj-37073	41	37	deka	deka	NOUN
esrj-37073	41	38	et	et	PROPN
esrj-37073	41	39	al	al	PROPN
esrj-37073	41	40	.	.	PROPN
esrj-37073	41	41	,	,	PUNCT
esrj-37073	41	42	2012	2012	NUM
esrj-37073	41	43	;	;	PUNCT
esrj-37073	41	44	kuo	kuo	PROPN
esrj-37073	41	45	-	-	PUNCT
esrj-37073	41	46	lin	lin	PROPN
esrj-37073	41	47	,	,	PUNCT
esrj-37073	41	48	2011	2011	NUM
esrj-37073	41	49	;	;	PUNCT
esrj-37073	41	50	vafakhah	vafakhah	NOUN
esrj-37073	41	51	,	,	PUNCT
esrj-37073	41	52	2012	2012	NUM
esrj-37073	41	53	;	;	PUNCT
esrj-37073	41	54	wu	wu	PROPN
esrj-37073	41	55	and	and	CCONJ
esrj-37073	41	56	chau	chau	NOUN
esrj-37073	41	57	,	,	PUNCT
esrj-37073	41	58	2010	2010	NUM
esrj-37073	41	59	)	)	PUNCT
esrj-37073	41	60	was	be	AUX
esrj-37073	41	61	employed	employ	VERB
esrj-37073	41	62	.	.	PUNCT
esrj-37073	42	1	additionally	additionally	ADV
esrj-37073	42	2	,	,	PUNCT
esrj-37073	42	3	in	in	ADP
esrj-37073	42	4	determining	determine	VERB
esrj-37073	42	5	the	the	DET
esrj-37073	42	6	number	number	NOUN
esrj-37073	42	7	of	of	ADP
esrj-37073	42	8	input	input	NOUN
esrj-37073	42	9	parameters	parameter	NOUN
esrj-37073	42	10	for	for	ADP
esrj-37073	42	11	ffnn	ffnn	NOUN
esrj-37073	42	12	,	,	PUNCT
esrj-37073	42	13	to	to	ADP
esrj-37073	42	14	the	the	DET
esrj-37073	42	15	author	author	NOUN
esrj-37073	42	16	’s	’s	PART
esrj-37073	42	17	knowledge	knowledge	NOUN
esrj-37073	42	18	,	,	PUNCT
esrj-37073	42	19	the	the	DET
esrj-37073	42	20	chaotic	chaotic	ADJ
esrj-37073	42	21	procedure	procedure	NOUN
esrj-37073	42	22	in	in	ADP
esrj-37073	42	23	this	this	DET
esrj-37073	42	24	study	study	NOUN
esrj-37073	42	25	is	be	AUX
esrj-37073	42	26	the	the	DET
esrj-37073	42	27	first	first	ADJ
esrj-37073	42	28	proposed	propose	VERB
esrj-37073	42	29	.	.	PUNCT
esrj-37073	43	1	the	the	DET
esrj-37073	43	2	values	value	NOUN
esrj-37073	43	3	for	for	ADP
esrj-37073	43	4	the	the	DET
esrj-37073	43	5	dominant	dominant	ADJ
esrj-37073	43	6	variables	variable	NOUN
esrj-37073	43	7	obtained	obtain	VERB
esrj-37073	43	8	from	from	ADP
esrj-37073	43	9	the	the	DET
esrj-37073	43	10	chaos	chaos	NOUN
esrj-37073	43	11	analysis	analysis	NOUN
esrj-37073	43	12	were	be	AUX
esrj-37073	43	13	used	use	VERB
esrj-37073	43	14	as	as	ADP
esrj-37073	43	15	the	the	DET
esrj-37073	43	16	minimum	minimum	ADJ
esrj-37073	43	17	and	and	CCONJ
esrj-37073	43	18	maximum	maximum	ADJ
esrj-37073	43	19	input	input	NOUN
esrj-37073	43	20	parameters	parameter	NOUN
esrj-37073	43	21	in	in	ADP
esrj-37073	43	22	the	the	DET
esrj-37073	43	23	ffnn	ffnn	NOUN
esrj-37073	43	24	.	.	PUNCT
esrj-37073	44	1	generally	generally	ADV
esrj-37073	44	2	,	,	PUNCT
esrj-37073	44	3	the	the	DET
esrj-37073	44	4	prediction	prediction	NOUN
esrj-37073	44	5	techniques	technique	NOUN
esrj-37073	44	6	for	for	ADP
esrj-37073	44	7	a	a	DET
esrj-37073	44	8	dynamic	dynamic	ADJ
esrj-37073	44	9	system	system	NOUN
esrj-37073	44	10	can	can	AUX
esrj-37073	44	11	generally	generally	ADV
esrj-37073	44	12	be	be	AUX
esrj-37073	44	13	divided	divide	VERB
esrj-37073	44	14	into	into	ADP
esrj-37073	44	15	two	two	NUM
esrj-37073	44	16	approaches	approach	NOUN
esrj-37073	44	17	:	:	PUNCT
esrj-37073	44	18	local	local	ADJ
esrj-37073	44	19	and	and	CCONJ
esrj-37073	44	20	global	global	ADJ
esrj-37073	44	21	(	(	PUNCT
esrj-37073	44	22	wu	wu	PROPN
esrj-37073	44	23	and	and	CCONJ
esrj-37073	44	24	chau	chau	NOUN
esrj-37073	44	25	,	,	PUNCT
esrj-37073	44	26	2010	2010	NUM
esrj-37073	44	27	)	)	PUNCT
esrj-37073	44	28	.	.	PUNCT
esrj-37073	45	1	because	because	SCONJ
esrj-37073	45	2	the	the	DET
esrj-37073	45	3	local	local	ADJ
esrj-37073	45	4	approach	approach	NOUN
esrj-37073	45	5	uses	use	VERB
esrj-37073	45	6	only	only	ADV
esrj-37073	45	7	nearby	nearby	ADJ
esrj-37073	45	8	states	state	NOUN
esrj-37073	45	9	to	to	PART
esrj-37073	45	10	make	make	VERB
esrj-37073	45	11	predictions	prediction	NOUN
esrj-37073	45	12	,	,	PUNCT
esrj-37073	45	13	the	the	DET
esrj-37073	45	14	k	k	NOUN
esrj-37073	45	15	-	-	PUNCT
esrj-37073	45	16	nearest	near	ADJ
esrj-37073	45	17	neighbor	neighbor	NOUN
esrj-37073	45	18	can	can	AUX
esrj-37073	45	19	be	be	AUX
esrj-37073	45	20	included	include	VERB
esrj-37073	45	21	in	in	ADP
esrj-37073	45	22	this	this	DET
esrj-37073	45	23	class	class	NOUN
esrj-37073	45	24	,	,	PUNCT
esrj-37073	45	25	and	and	CCONJ
esrj-37073	45	26	ffnn	ffnn	NOUN
esrj-37073	45	27	can	can	AUX
esrj-37073	45	28	be	be	AUX
esrj-37073	45	29	classified	classify	VERB
esrj-37073	45	30	as	as	ADP
esrj-37073	45	31	the	the	DET
esrj-37073	45	32	latter	latter	ADJ
esrj-37073	45	33	one	one	NUM
esrj-37073	45	34	.	.	PUNCT
esrj-37073	46	1	therefore	therefore	ADV
esrj-37073	46	2	,	,	PUNCT
esrj-37073	46	3	in	in	ADP
esrj-37073	46	4	this	this	DET
esrj-37073	46	5	study	study	NOUN
esrj-37073	46	6	,	,	PUNCT
esrj-37073	46	7	we	we	PRON
esrj-37073	46	8	preliminarily	preliminarily	ADV
esrj-37073	46	9	evaluate	evaluate	VERB
esrj-37073	46	10	which	which	DET
esrj-37073	46	11	nonlinear	nonlinear	ADJ
esrj-37073	46	12	approach	approach	NOUN
esrj-37073	46	13	,	,	PUNCT
esrj-37073	46	14	local	local	ADJ
esrj-37073	46	15	or	or	CCONJ
esrj-37073	46	16	global	global	ADJ
esrj-37073	46	17	,	,	PUNCT
esrj-37073	46	18	is	be	AUX
esrj-37073	46	19	more	more	ADV
esrj-37073	46	20	efficient	efficient	ADJ
esrj-37073	46	21	in	in	ADP
esrj-37073	46	22	forecasting	forecasting	NOUN
esrj-37073	46	23	stream	stream	NOUN
esrj-37073	46	24	flow	flow	NOUN
esrj-37073	46	25	time	time	NOUN
esrj-37073	46	26	series	series	NOUN
esrj-37073	46	27	.	.	PUNCT
esrj-37073	47	1	the	the	DET
esrj-37073	47	2	two	two	NUM
esrj-37073	47	3	nonlinear	nonlinear	ADJ
esrj-37073	47	4	approaches	approach	NOUN
esrj-37073	47	5	’	'	PUNCT
esrj-37073	47	6	modeling	modeling	NOUN
esrj-37073	47	7	capabilities	capability	NOUN
esrj-37073	47	8	are	be	AUX
esrj-37073	47	9	compared	compare	VERB
esrj-37073	47	10	for	for	ADP
esrj-37073	47	11	the	the	DET
esrj-37073	47	12	kızılırmak	kızılırmak	PROPN
esrj-37073	47	13	river	river	PROPN
esrj-37073	47	14	,	,	PUNCT
esrj-37073	47	15	the	the	DET
esrj-37073	47	16	longest	long	ADJ
esrj-37073	47	17	river	river	NOUN
esrj-37073	47	18	in	in	ADP
esrj-37073	47	19	turkey	turkey	NOUN
esrj-37073	47	20	.	.	PUNCT
esrj-37073	48	1	the	the	DET
esrj-37073	48	2	paper	paper	NOUN
esrj-37073	48	3	is	be	AUX
esrj-37073	48	4	organized	organize	VERB
esrj-37073	48	5	as	as	SCONJ
esrj-37073	48	6	follows	follow	VERB
esrj-37073	48	7	.	.	PUNCT
esrj-37073	49	1	section	section	NOUN
esrj-37073	49	2	2	2	NUM
esrj-37073	49	3	introduces	introduce	NOUN
esrj-37073	49	4	the	the	DET
esrj-37073	49	5	study	study	NOUN
esrj-37073	49	6	area	area	NOUN
esrj-37073	49	7	and	and	CCONJ
esrj-37073	49	8	the	the	DET
esrj-37073	49	9	stream	stream	NOUN
esrj-37073	49	10	flow	flow	NOUN
esrj-37073	49	11	time	time	NOUN
esrj-37073	49	12	series	series	NOUN
esrj-37073	49	13	that	that	PRON
esrj-37073	49	14	are	be	AUX
esrj-37073	49	15	used	use	VERB
esrj-37073	49	16	.	.	PUNCT
esrj-37073	50	1	in	in	ADP
esrj-37073	50	2	section	section	NOUN
esrj-37073	50	3	3	3	NUM
esrj-37073	50	4	,	,	PUNCT
esrj-37073	50	5	the	the	DET
esrj-37073	50	6	basic	basic	ADJ
esrj-37073	50	7	principles	principle	NOUN
esrj-37073	50	8	of	of	ADP
esrj-37073	50	9	the	the	DET
esrj-37073	50	10	k	k	PROPN
esrj-37073	50	11	-	-	PROPN
esrj-37073	50	12	nn	nn	PROPN
esrj-37073	50	13	and	and	CCONJ
esrj-37073	50	14	the	the	DET
esrj-37073	50	15	feed	feed	NOUN
esrj-37073	50	16	-	-	PUNCT
esrj-37073	50	17	forward	forward	ADV
esrj-37073	50	18	neural	neural	ADJ
esrj-37073	50	19	network	network	NOUN
esrj-37073	50	20	as	as	ADP
esrj-37073	50	21	a	a	DET
esrj-37073	50	22	sub	sub	NOUN
esrj-37073	50	23	-	-	NOUN
esrj-37073	50	24	class	class	NOUN
esrj-37073	50	25	of	of	ADP
esrj-37073	50	26	ann	ann	PROPN
esrj-37073	50	27	are	be	AUX
esrj-37073	50	28	described	describe	VERB
esrj-37073	50	29	.	.	PUNCT
esrj-37073	51	1	following	follow	VERB
esrj-37073	51	2	this	this	PRON
esrj-37073	51	3	,	,	PUNCT
esrj-37073	51	4	in	in	ADP
esrj-37073	51	5	section	section	NOUN
esrj-37073	51	6	4	4	NUM
esrj-37073	51	7	,	,	PUNCT
esrj-37073	51	8	the	the	DET
esrj-37073	51	9	obtained	obtain	VERB
esrj-37073	51	10	results	result	NOUN
esrj-37073	51	11	are	be	AUX
esrj-37073	51	12	given	give	VERB
esrj-37073	51	13	with	with	ADP
esrj-37073	51	14	a	a	DET
esrj-37073	51	15	detailed	detailed	ADJ
esrj-37073	51	16	discussion	discussion	NOUN
esrj-37073	51	17	.	.	PUNCT
esrj-37073	52	1	the	the	DET
esrj-37073	52	2	conclusions	conclusion	NOUN
esrj-37073	52	3	of	of	ADP
esrj-37073	52	4	the	the	DET
esrj-37073	52	5	paper	paper	NOUN
esrj-37073	52	6	are	be	AUX
esrj-37073	52	7	presented	present	VERB
esrj-37073	52	8	in	in	ADP
esrj-37073	52	9	section	section	NOUN
esrj-37073	52	10	5	5	NUM
esrj-37073	52	11	.	.	SYM
esrj-37073	52	12	2	2	NUM
esrj-37073	52	13	.	.	X
esrj-37073	52	14	study	study	NOUN
esrj-37073	52	15	area	area	NOUN
esrj-37073	52	16	and	and	CCONJ
esrj-37073	52	17	data	data	VERB
esrj-37073	52	18	the	the	DET
esrj-37073	52	19	kızılırmak	kızılırmak	PROPN
esrj-37073	52	20	river	river	NOUN
esrj-37073	52	21	basin	basin	NOUN
esrj-37073	52	22	is	be	AUX
esrj-37073	52	23	located	locate	VERB
esrj-37073	52	24	between	between	ADP
esrj-37073	52	25	37	37	NUM
esrj-37073	52	26	°	°	NOUN
esrj-37073	52	27	58'-41	58'-41	NOUN
esrj-37073	52	28	°	°	ADP
esrj-37073	52	29	44	44	NUM
esrj-37073	52	30	'	'	PART
esrj-37073	52	31	north	north	NOUN
esrj-37073	52	32	latitudes	latitude	NOUN
esrj-37073	52	33	and	and	CCONJ
esrj-37073	52	34	32	32	NUM
esrj-37073	52	35	°	°	NUM
esrj-37073	52	36	48'-38	48'-38	NOUN
esrj-37073	52	37	°	°	NOUN
esrj-37073	52	38	22	22	NUM
esrj-37073	52	39	'	'	PART
esrj-37073	52	40	east	east	NOUN
esrj-37073	52	41	longitudes	longitude	NOUN
esrj-37073	52	42	.	.	PUNCT
esrj-37073	53	1	the	the	DET
esrj-37073	53	2	kızılırmak	kızılırmak	PROPN
esrj-37073	53	3	river	river	NOUN
esrj-37073	53	4	flows	flow	VERB
esrj-37073	53	5	through	through	ADP
esrj-37073	53	6	a	a	DET
esrj-37073	53	7	1,355	1,355	NUM
esrj-37073	53	8	km	km	NOUN
esrj-37073	53	9	long	long	ADJ
esrj-37073	53	10	course	course	NOUN
esrj-37073	53	11	,	,	PUNCT
esrj-37073	53	12	the	the	DET
esrj-37073	53	13	longest	long	ADJ
esrj-37073	53	14	in	in	ADP
esrj-37073	53	15	turkey	turkey	NOUN
esrj-37073	53	16	.	.	PUNCT
esrj-37073	54	1	in	in	ADP
esrj-37073	54	2	the	the	DET
esrj-37073	54	3	basin	basin	NOUN
esrj-37073	54	4	,	,	PUNCT
esrj-37073	54	5	the	the	DET
esrj-37073	54	6	continental	continental	ADJ
esrj-37073	54	7	climate	climate	NOUN
esrj-37073	54	8	is	be	AUX
esrj-37073	54	9	dominant	dominant	ADJ
esrj-37073	54	10	,	,	PUNCT
esrj-37073	54	11	for	for	ADP
esrj-37073	54	12	which	which	PRON
esrj-37073	54	13	summers	summer	NOUN
esrj-37073	54	14	are	be	AUX
esrj-37073	54	15	characterized	characterize	VERB
esrj-37073	54	16	with	with	ADP
esrj-37073	54	17	moderate	moderate	ADJ
esrj-37073	54	18	precipitation	precipitation	NOUN
esrj-37073	54	19	and	and	CCONJ
esrj-37073	54	20	winters	winter	NOUN
esrj-37073	54	21	are	be	AUX
esrj-37073	54	22	characterized	characterize	VERB
esrj-37073	54	23	with	with	ADP
esrj-37073	54	24	severe	severe	ADJ
esrj-37073	54	25	cold	cold	NOUN
esrj-37073	54	26	.	.	PUNCT
esrj-37073	55	1	the	the	DET
esrj-37073	55	2	annual	annual	ADJ
esrj-37073	55	3	mean	mean	ADJ
esrj-37073	55	4	precipitation	precipitation	NOUN
esrj-37073	55	5	and	and	CCONJ
esrj-37073	55	6	temperature	temperature	NOUN
esrj-37073	55	7	are	be	AUX
esrj-37073	55	8	446.1	446.1	NUM
esrj-37073	55	9	mm	mm	NOUN
esrj-37073	55	10	and	and	CCONJ
esrj-37073	55	11	13.7	13.7	NUM
esrj-37073	55	12	°	°	NOUN
esrj-37073	55	13	c	c	NOUN
esrj-37073	55	14	,	,	PUNCT
esrj-37073	55	15	respectively	respectively	ADV
esrj-37073	55	16	.	.	PUNCT
esrj-37073	56	1	the	the	DET
esrj-37073	56	2	flow	flow	NOUN
esrj-37073	56	3	regime	regime	NOUN
esrj-37073	56	4	of	of	ADP
esrj-37073	56	5	the	the	DET
esrj-37073	56	6	river	river	NOUN
esrj-37073	56	7	is	be	AUX
esrj-37073	56	8	irregular	irregular	ADJ
esrj-37073	56	9	resulting	result	VERB
esrj-37073	56	10	from	from	ADP
esrj-37073	56	11	rainfall	rainfall	NOUN
esrj-37073	56	12	and	and	CCONJ
esrj-37073	56	13	snow	snow	NOUN
esrj-37073	56	14	-	-	PUNCT
esrj-37073	56	15	melt	melt	NOUN
esrj-37073	56	16	.	.	PUNCT
esrj-37073	57	1	the	the	DET
esrj-37073	57	2	lowest	low	ADJ
esrj-37073	57	3	discharges	discharge	NOUN
esrj-37073	57	4	are	be	AUX
esrj-37073	57	5	observed	observe	VERB
esrj-37073	57	6	between	between	ADP
esrj-37073	57	7	july	july	PROPN
esrj-37073	57	8	and	and	CCONJ
esrj-37073	57	9	february	february	PROPN
esrj-37073	57	10	,	,	PUNCT
esrj-37073	57	11	and	and	CCONJ
esrj-37073	57	12	the	the	DET
esrj-37073	57	13	river	river	NOUN
esrj-37073	57	14	starts	start	VERB
esrj-37073	57	15	to	to	PART
esrj-37073	57	16	rise	rise	VERB
esrj-37073	57	17	in	in	ADP
esrj-37073	57	18	the	the	DET
esrj-37073	57	19	beginning	beginning	NOUN
esrj-37073	57	20	of	of	ADP
esrj-37073	57	21	march	march	PROPN
esrj-37073	57	22	and	and	CCONJ
esrj-37073	57	23	reaches	reach	VERB
esrj-37073	57	24	its	its	PRON
esrj-37073	57	25	highest	high	ADJ
esrj-37073	57	26	level	level	NOUN
esrj-37073	57	27	in	in	ADP
esrj-37073	57	28	april	april	PROPN
esrj-37073	57	29	(	(	PUNCT
esrj-37073	57	30	çakmak	çakmak	PROPN
esrj-37073	57	31	et	et	PROPN
esrj-37073	57	32	al	al	PROPN
esrj-37073	57	33	.	.	PROPN
esrj-37073	57	34	,	,	PUNCT
esrj-37073	57	35	2007	2007	NUM
esrj-37073	57	36	)	)	PUNCT
esrj-37073	57	37	.	.	PUNCT
esrj-37073	58	1	the	the	DET
esrj-37073	58	2	data	datum	NOUN
esrj-37073	58	3	that	that	PRON
esrj-37073	58	4	were	be	AUX
esrj-37073	58	5	used	use	VERB
esrj-37073	58	6	cover	cover	VERB
esrj-37073	58	7	the	the	DET
esrj-37073	58	8	period	period	NOUN
esrj-37073	58	9	of	of	ADP
esrj-37073	58	10	january	january	PROPN
esrj-37073	58	11	1960	1960	NUM
esrj-37073	58	12	to	to	ADP
esrj-37073	58	13	september	september	PROPN
esrj-37073	58	14	2004	2004	NUM
esrj-37073	58	15	(	(	PUNCT
esrj-37073	58	16	figure	figure	NOUN
esrj-37073	58	17	1	1	NUM
esrj-37073	58	18	)	)	PUNCT
esrj-37073	58	19	,	,	PUNCT
esrj-37073	58	20	and	and	CCONJ
esrj-37073	58	21	the	the	DET
esrj-37073	58	22	main	main	ADJ
esrj-37073	58	23	statistical	statistical	ADJ
esrj-37073	58	24	parameters	parameter	NOUN
esrj-37073	58	25	of	of	ADP
esrj-37073	58	26	the	the	DET
esrj-37073	58	27	stream	stream	NOUN
esrj-37073	58	28	flow	flow	NOUN
esrj-37073	58	29	time	time	NOUN
esrj-37073	58	30	series	series	NOUN
esrj-37073	58	31	are	be	AUX
esrj-37073	58	32	given	give	VERB
esrj-37073	58	33	in	in	ADP
esrj-37073	58	34	table	table	NOUN
esrj-37073	58	35	1	1	NUM
esrj-37073	58	36	.	.	PUNCT
esrj-37073	58	37	figure	figure	NOUN
esrj-37073	58	38	1	1	NUM
esrj-37073	58	39	.	.	PUNCT
esrj-37073	58	40	daily	daily	ADJ
esrj-37073	58	41	discharge	discharge	NOUN
esrj-37073	58	42	data	datum	NOUN
esrj-37073	58	43	at	at	ADP
esrj-37073	58	44	the	the	DET
esrj-37073	58	45	15	15	NUM
esrj-37073	58	46	-	-	SYM
esrj-37073	58	47	1501	1501	NUM
esrj-37073	58	48	(	(	PUNCT
esrj-37073	58	49	yamula	yamula	ADJ
esrj-37073	58	50	)	)	PUNCT
esrj-37073	58	51	gauge	gauge	NOUN
esrj-37073	58	52	station	station	NOUN
esrj-37073	58	53	of	of	ADP
esrj-37073	58	54	the	the	DET
esrj-37073	58	55	kızılırmak	kızılırmak	PROPN
esrj-37073	58	56	river	river	PROPN
esrj-37073	58	57	3	3	NUM
esrj-37073	58	58	.	.	PUNCT
esrj-37073	58	59	methodology	methodology	NOUN
esrj-37073	58	60	3.1	3.1	NUM
esrj-37073	58	61	.	.	PUNCT
esrj-37073	59	1	k	k	X
esrj-37073	59	2	-	-	PUNCT
esrj-37073	59	3	nearest	near	ADJ
esrj-37073	59	4	neighbor	neighbor	NOUN
esrj-37073	59	5	approach	approach	VERB
esrj-37073	59	6	the	the	DET
esrj-37073	59	7	temporal	temporal	ADJ
esrj-37073	59	8	evolution	evolution	NOUN
esrj-37073	59	9	of	of	ADP
esrj-37073	59	10	a	a	DET
esrj-37073	59	11	system	system	NOUN
esrj-37073	59	12	can	can	AUX
esrj-37073	59	13	be	be	AUX
esrj-37073	59	14	described	describe	VERB
esrj-37073	59	15	by	by	ADP
esrj-37073	59	16	a	a	DET
esrj-37073	59	17	multi	multi	ADJ
esrj-37073	59	18	-	-	ADJ
esrj-37073	59	19	dimensional	dimensional	ADJ
esrj-37073	59	20	phase	phase	NOUN
esrj-37073	59	21	space	space	NOUN
esrj-37073	59	22	.	.	PUNCT
esrj-37073	60	1	the	the	DET
esrj-37073	60	2	most	most	ADV
esrj-37073	60	3	frequently	frequently	ADV
esrj-37073	60	4	used	use	VERB
esrj-37073	60	5	reconstruction	reconstruction	NOUN
esrj-37073	60	6	method	method	NOUN
esrj-37073	60	7	for	for	ADP
esrj-37073	60	8	a	a	DET
esrj-37073	60	9	univariate	univariate	ADJ
esrj-37073	60	10	or	or	CCONJ
esrj-37073	60	11	multivariate	multivariate	NOUN
esrj-37073	60	12	time	time	NOUN
esrj-37073	60	13	series	series	NOUN
esrj-37073	60	14	is	be	AUX
esrj-37073	60	15	the	the	DET
esrj-37073	60	16	delay	delay	NOUN
esrj-37073	60	17	time	time	NOUN
esrj-37073	60	18	method	method	NOUN
esrj-37073	60	19	which	which	PRON
esrj-37073	60	20	was	be	AUX
esrj-37073	60	21	developed	develop	VERB
esrj-37073	60	22	by	by	ADP
esrj-37073	60	23	packard	packard	PROPN
esrj-37073	60	24	et	et	PROPN
esrj-37073	60	25	al	al	PROPN
esrj-37073	60	26	.	.	PROPN
esrj-37073	61	1	(	(	PUNCT
esrj-37073	61	2	1980	1980	NUM
esrj-37073	61	3	)	)	PUNCT
esrj-37073	61	4	and	and	CCONJ
esrj-37073	61	5	takens	taken	NOUN
esrj-37073	61	6	(	(	PUNCT
esrj-37073	61	7	1981	1981	NUM
esrj-37073	61	8	)	)	PUNCT
esrj-37073	61	9	.	.	PUNCT
esrj-37073	62	1	the	the	DET
esrj-37073	62	2	main	main	ADJ
esrj-37073	62	3	idea	idea	NOUN
esrj-37073	62	4	behind	behind	ADP
esrj-37073	62	5	phase	phase	NOUN
esrj-37073	62	6	-	-	PUNCT
esrj-37073	62	7	space	space	NOUN
esrj-37073	62	8	reconstruction	reconstruction	NOUN
esrj-37073	62	9	is	be	AUX
esrj-37073	62	10	that	that	SCONJ
esrj-37073	62	11	the	the	DET
esrj-37073	62	12	system	system	NOUN
esrj-37073	62	13	is	be	AUX
esrj-37073	62	14	characterized	characterize	VERB
esrj-37073	62	15	by	by	ADP
esrj-37073	62	16	selfinteraction	selfinteraction	NOUN
esrj-37073	62	17	,	,	PUNCT
esrj-37073	62	18	and	and	CCONJ
esrj-37073	62	19	the	the	DET
esrj-37073	62	20	observed	observe	VERB
esrj-37073	62	21	time	time	NOUN
esrj-37073	62	22	series	series	PROPN
esrj-37073	62	23	can	can	AUX
esrj-37073	62	24	hold	hold	VERB
esrj-37073	62	25	the	the	DET
esrj-37073	62	26	information	information	NOUN
esrj-37073	62	27	about	about	ADP
esrj-37073	62	28	the	the	DET
esrj-37073	62	29	dynamics	dynamic	NOUN
esrj-37073	62	30	of	of	ADP
esrj-37073	62	31	the	the	DET
esrj-37073	62	32	entire	entire	ADJ
esrj-37073	62	33	system	system	NOUN
esrj-37073	62	34	(	(	PUNCT
esrj-37073	62	35	sivakumar	sivakumar	PROPN
esrj-37073	62	36	et	et	PROPN
esrj-37073	62	37	al	al	PROPN
esrj-37073	62	38	.	.	PROPN
esrj-37073	62	39	,	,	PUNCT
esrj-37073	62	40	2002	2002	NUM
esrj-37073	62	41	)	)	PUNCT
esrj-37073	62	42	.	.	PUNCT
esrj-37073	63	1	the	the	DET
esrj-37073	63	2	past	past	ADJ
esrj-37073	63	3	observations	observation	NOUN
esrj-37073	63	4	can	can	AUX
esrj-37073	63	5	be	be	AUX
esrj-37073	63	6	embedded	embed	VERB
esrj-37073	63	7	in	in	ADP
esrj-37073	63	8	an	an	DET
esrj-37073	63	9	m	m	ADV
esrj-37073	63	10	-	-	ADJ
esrj-37073	63	11	dimensional	dimensional	ADJ
esrj-37073	63	12	state	state	NOUN
esrj-37073	63	13	space	space	NOUN
esrj-37073	63	14	according	accord	VERB
esrj-37073	63	15	to	to	ADP
esrj-37073	63	16	:	:	PUNCT
esrj-37073	63	17	where	where	SCONJ
esrj-37073	63	18	,	,	PUNCT
esrj-37073	63	19	m	m	VERB
esrj-37073	63	20	is	be	AUX
esrj-37073	63	21	the	the	DET
esrj-37073	63	22	embedding	embed	VERB
esrj-37073	63	23	dimension	dimension	NOUN
esrj-37073	63	24	of	of	ADP
esrj-37073	63	25	the	the	DET
esrj-37073	63	26	vector	vector	NOUN
esrj-37073	63	27	and	and	CCONJ
esrj-37073	63	28	is	be	AUX
esrj-37073	63	29	the	the	DET
esrj-37073	63	30	delay	delay	NOUN
esrj-37073	63	31	time	time	NOUN
esrj-37073	63	32	.	.	PUNCT
esrj-37073	64	1	to	to	PART
esrj-37073	64	2	characterize	characterize	VERB
esrj-37073	64	3	a	a	DET
esrj-37073	64	4	dynamic	dynamic	ADJ
esrj-37073	64	5	system	system	NOUN
esrj-37073	64	6	with	with	ADP
esrj-37073	64	7	an	an	DET
esrj-37073	64	8	attractor	attractor	NOUN
esrj-37073	64	9	dimension	dimension	NOUN
esrj-37073	64	10	d	d	NOUN
esrj-37073	64	11	,	,	PUNCT
esrj-37073	64	12	(	(	PUNCT
esrj-37073	64	13	)	)	PUNCT
esrj-37073	64	14	-dimensional	-dimensional	ADJ
esrj-37073	64	15	space	space	NOUN
esrj-37073	64	16	is	be	AUX
esrj-37073	64	17	required	require	VERB
esrj-37073	64	18	(	(	PUNCT
esrj-37073	64	19	takens	taken	NOUN
esrj-37073	64	20	,	,	PUNCT
esrj-37073	64	21	table	table	NOUN
esrj-37073	64	22	1	1	NUM
esrj-37073	64	23	.	.	PUNCT
esrj-37073	65	1	the	the	DET
esrj-37073	65	2	statistics	statistic	NOUN
esrj-37073	65	3	of	of	ADP
esrj-37073	65	4	the	the	DET
esrj-37073	65	5	kızılırmak	kızılırmak	PROPN
esrj-37073	65	6	river	river	NOUN
esrj-37073	65	7	discharge	discharge	NOUN
esrj-37073	65	8	data	datum	NOUN
esrj-37073	65	9	station	station	NOUN
esrj-37073	65	10	no	no	DET
esrj-37073	65	11	/	/	SYM
esrj-37073	65	12	name	name	NOUN
esrj-37073	65	13	obs	obs	PROPN
esrj-37073	65	14	.	.	PROPN
esrj-37073	65	15	period	period	NOUN
esrj-37073	65	16	drainage	drainage	NOUN
esrj-37073	65	17	area	area	NOUN
esrj-37073	65	18	(	(	PUNCT
esrj-37073	65	19	km2	km2	NOUN
esrj-37073	65	20	)	)	PUNCT
esrj-37073	65	21	elevation	elevation	NOUN
esrj-37073	65	22	above	above	ADP
esrj-37073	65	23	sea	sea	NOUN
esrj-37073	65	24	(	(	PUNCT
esrj-37073	65	25	m	m	NOUN
esrj-37073	65	26	)	)	PUNCT
esrj-37073	65	27	mean	mean	NOUN
esrj-37073	65	28	(	(	PUNCT
esrj-37073	65	29	m3	m3	PROPN
esrj-37073	65	30	/	/	SYM
esrj-37073	65	31	s	s	NOUN
esrj-37073	65	32	)	)	PUNCT
esrj-37073	65	33	std	std	PROPN
esrj-37073	65	34	.	.	PUNCT
esrj-37073	65	35	dev	dev	PROPN
esrj-37073	65	36	.	.	PUNCT
esrj-37073	66	1	(	(	PUNCT
esrj-37073	66	2	m3	m3	PROPN
esrj-37073	66	3	/	/	SYM
esrj-37073	66	4	s	s	PROPN
esrj-37073	66	5	)	)	PUNCT
esrj-37073	66	6	median	median	NOUN
esrj-37073	66	7	(	(	PUNCT
esrj-37073	66	8	m3	m3	PROPN
esrj-37073	66	9	/	/	SYM
esrj-37073	66	10	s	s	PROPN
esrj-37073	66	11	)	)	PUNCT
esrj-37073	66	12	coeff	coeff	PROPN
esrj-37073	66	13	.	.	PROPN
esrj-37073	67	1	of	of	ADP
esrj-37073	67	2	variation	variation	NOUN
esrj-37073	67	3	skewness	skewness	NOUN
esrj-37073	67	4	kurtosis	kurtosis	VERB
esrj-37073	67	5	151501	151501	NUM
esrj-37073	67	6	/	/	SYM
esrj-37073	67	7	yamula	yamula	NOUN
esrj-37073	67	8	19602004	19602004	NUM
esrj-37073	67	9	15182	15182	NUM
esrj-37073	67	10	990	990	NUM
esrj-37073	67	11	66.47	66.47	NUM
esrj-37073	67	12	87.66	87.66	NUM
esrj-37073	67	13	31.20	31.20	NUM
esrj-37073	67	14	1.32	1.32	NUM
esrj-37073	67	15	2.94	2.94	NUM
esrj-37073	67	16	14.59	14.59	NUM
esrj-37073	67	17	hakan	hakan	PROPN
esrj-37073	67	18	tongal	tongal	PROPN
esrj-37073	67	19	(	(	PUNCT
esrj-37073	67	20	1	1	NUM
esrj-37073	67	21	)	)	PUNCT
esrj-37073	67	22	121	121	NUM
esrj-37073	67	23	1981	1981	NUM
esrj-37073	67	24	)	)	PUNCT
esrj-37073	67	25	.	.	PUNCT
esrj-37073	68	1	however	however	ADV
esrj-37073	68	2	,	,	PUNCT
esrj-37073	68	3	abarbanel	abarbanel	PROPN
esrj-37073	68	4	et	et	PROPN
esrj-37073	68	5	al	al	PROPN
esrj-37073	68	6	.	.	PROPN
esrj-37073	69	1	(	(	PUNCT
esrj-37073	69	2	1990	1990	NUM
esrj-37073	69	3	)	)	PUNCT
esrj-37073	69	4	proposed	propose	VERB
esrj-37073	69	5	that	that	SCONJ
esrj-37073	69	6	m	m	PROPN
esrj-37073	69	7	d	d	X
esrj-37073	69	8	>	>	X
esrj-37073	69	9	would	would	AUX
esrj-37073	69	10	be	be	AUX
esrj-37073	69	11	sufficient	sufficient	ADJ
esrj-37073	69	12	.	.	PUNCT
esrj-37073	70	1	as	as	SCONJ
esrj-37073	70	2	it	it	PRON
esrj-37073	70	3	is	be	AUX
esrj-37073	70	4	seen	see	VERB
esrj-37073	70	5	in	in	ADP
esrj-37073	70	6	eq	eq	ADP
esrj-37073	70	7	.	.	PUNCT
esrj-37073	71	1	(	(	PUNCT
esrj-37073	71	2	1	1	NUM
esrj-37073	71	3	)	)	PUNCT
esrj-37073	71	4	,	,	PUNCT
esrj-37073	71	5	the	the	DET
esrj-37073	71	6	main	main	ADJ
esrj-37073	71	7	parameters	parameter	NOUN
esrj-37073	71	8	that	that	PRON
esrj-37073	71	9	should	should	AUX
esrj-37073	71	10	be	be	AUX
esrj-37073	71	11	determined	determine	VERB
esrj-37073	71	12	in	in	ADP
esrj-37073	71	13	the	the	DET
esrj-37073	71	14	phase	phase	NOUN
esrj-37073	71	15	-	-	PUNCT
esrj-37073	71	16	space	space	NOUN
esrj-37073	71	17	reconstruction	reconstruction	NOUN
esrj-37073	71	18	method	method	NOUN
esrj-37073	71	19	are	be	AUX
esrj-37073	71	20	the	the	DET
esrj-37073	71	21	delay	delay	NOUN
esrj-37073	71	22	and	and	CCONJ
esrj-37073	71	23	the	the	DET
esrj-37073	71	24	embedding	embed	VERB
esrj-37073	71	25	dimension	dimension	NOUN
esrj-37073	71	26	parameters	parameter	NOUN
esrj-37073	71	27	.	.	PUNCT
esrj-37073	72	1	the	the	DET
esrj-37073	72	2	most	most	ADV
esrj-37073	72	3	commonly	commonly	ADV
esrj-37073	72	4	used	use	VERB
esrj-37073	72	5	methods	method	NOUN
esrj-37073	72	6	for	for	ADP
esrj-37073	72	7	determining	determine	VERB
esrj-37073	72	8	these	these	DET
esrj-37073	72	9	parameters	parameter	NOUN
esrj-37073	72	10	are	be	AUX
esrj-37073	72	11	the	the	DET
esrj-37073	72	12	mutual	mutual	ADJ
esrj-37073	72	13	information	information	NOUN
esrj-37073	72	14	(	(	PUNCT
esrj-37073	72	15	mi	mi	NOUN
esrj-37073	72	16	)	)	PUNCT
esrj-37073	72	17	and	and	CCONJ
esrj-37073	72	18	the	the	DET
esrj-37073	72	19	correlation	correlation	NOUN
esrj-37073	72	20	dimension	dimension	NOUN
esrj-37073	72	21	methods	method	NOUN
esrj-37073	72	22	,	,	PUNCT
esrj-37073	72	23	respectively	respectively	ADV
esrj-37073	72	24	.	.	PUNCT
esrj-37073	73	1	another	another	DET
esrj-37073	73	2	commonly	commonly	ADV
esrj-37073	73	3	used	use	VERB
esrj-37073	73	4	method	method	NOUN
esrj-37073	73	5	for	for	ADP
esrj-37073	73	6	determining	determine	VERB
esrj-37073	73	7	the	the	DET
esrj-37073	73	8	delay	delay	NOUN
esrj-37073	73	9	parameter	parameter	NOUN
esrj-37073	73	10	is	be	AUX
esrj-37073	73	11	the	the	DET
esrj-37073	73	12	autocorrelation	autocorrelation	NOUN
esrj-37073	73	13	function	function	NOUN
esrj-37073	73	14	(	(	PUNCT
esrj-37073	73	15	acf	acf	PROPN
esrj-37073	73	16	)	)	PUNCT
esrj-37073	73	17	.	.	PUNCT
esrj-37073	74	1	however	however	ADV
esrj-37073	74	2	,	,	PUNCT
esrj-37073	74	3	because	because	SCONJ
esrj-37073	74	4	the	the	DET
esrj-37073	74	5	acf	acf	NOUN
esrj-37073	74	6	does	do	AUX
esrj-37073	74	7	not	not	PART
esrj-37073	74	8	measure	measure	VERB
esrj-37073	74	9	the	the	DET
esrj-37073	74	10	nonlinear	nonlinear	ADJ
esrj-37073	74	11	dependence	dependence	NOUN
esrj-37073	74	12	,	,	PUNCT
esrj-37073	74	13	in	in	ADP
esrj-37073	74	14	this	this	DET
esrj-37073	74	15	study	study	NOUN
esrj-37073	74	16	,	,	PUNCT
esrj-37073	74	17	we	we	PRON
esrj-37073	74	18	employed	employ	VERB
esrj-37073	74	19	a	a	DET
esrj-37073	74	20	mi	mi	NOUN
esrj-37073	74	21	function	function	NOUN
esrj-37073	74	22	that	that	PRON
esrj-37073	74	23	was	be	AUX
esrj-37073	74	24	based	base	VERB
esrj-37073	74	25	on	on	ADP
esrj-37073	74	26	joint	joint	ADJ
esrj-37073	74	27	probabilities	probability	NOUN
esrj-37073	74	28	that	that	PRON
esrj-37073	74	29	enabled	enable	VERB
esrj-37073	74	30	us	we	PRON
esrj-37073	74	31	to	to	PART
esrj-37073	74	32	measure	measure	VERB
esrj-37073	74	33	the	the	DET
esrj-37073	74	34	nonlinear	nonlinear	ADJ
esrj-37073	74	35	dependency	dependency	NOUN
esrj-37073	74	36	beyond	beyond	ADP
esrj-37073	74	37	linear	linear	ADJ
esrj-37073	74	38	correlation	correlation	NOUN
esrj-37073	74	39	.	.	PUNCT
esrj-37073	75	1	the	the	DET
esrj-37073	75	2	mutual	mutual	ADJ
esrj-37073	75	3	information	information	NOUN
esrj-37073	75	4	was	be	AUX
esrj-37073	75	5	computed	compute	VERB
esrj-37073	75	6	according	accord	VERB
esrj-37073	75	7	to	to	ADP
esrj-37073	75	8	:	:	PUNCT
esrj-37073	75	9	where	where	SCONJ
esrj-37073	75	10	and	and	CCONJ
esrj-37073	75	11	are	be	AUX
esrj-37073	75	12	successive	successive	ADJ
esrj-37073	75	13	values	value	NOUN
esrj-37073	75	14	,	,	PUNCT
esrj-37073	75	15	and	and	CCONJ
esrj-37073	75	16	are	be	AUX
esrj-37073	75	17	the	the	DET
esrj-37073	75	18	individual	individual	ADJ
esrj-37073	75	19	probabilities	probability	NOUN
esrj-37073	75	20	of	of	ADP
esrj-37073	75	21	and	and	CCONJ
esrj-37073	75	22	,	,	PUNCT
esrj-37073	75	23	respectively	respectively	ADV
esrj-37073	75	24	and	and	CCONJ
esrj-37073	75	25	is	be	AUX
esrj-37073	75	26	the	the	DET
esrj-37073	75	27	joint	joint	ADJ
esrj-37073	75	28	probability	probability	NOUN
esrj-37073	75	29	density	density	NOUN
esrj-37073	75	30	.	.	PUNCT
esrj-37073	76	1	to	to	PART
esrj-37073	76	2	determine	determine	VERB
esrj-37073	76	3	the	the	DET
esrj-37073	76	4	optimal	optimal	ADJ
esrj-37073	76	5	delay	delay	NOUN
esrj-37073	76	6	time	time	NOUN
esrj-37073	76	7	parameter	parameter	NOUN
esrj-37073	76	8	,	,	PUNCT
esrj-37073	76	9	it	it	PRON
esrj-37073	76	10	is	be	AUX
esrj-37073	76	11	advised	advise	VERB
esrj-37073	76	12	to	to	PART
esrj-37073	76	13	use	use	VERB
esrj-37073	76	14	the	the	DET
esrj-37073	76	15	local	local	ADJ
esrj-37073	76	16	minimum	minimum	NOUN
esrj-37073	76	17	of	of	ADP
esrj-37073	76	18	the	the	DET
esrj-37073	76	19	mi	mi	PROPN
esrj-37073	76	20	(	(	PUNCT
esrj-37073	76	21	frazer	frazer	PROPN
esrj-37073	76	22	and	and	CCONJ
esrj-37073	76	23	swinney	swinney	PROPN
esrj-37073	76	24	,	,	PUNCT
esrj-37073	76	25	1986	1986	NUM
esrj-37073	76	26	)	)	PUNCT
esrj-37073	76	27	,	,	PUNCT
esrj-37073	76	28	i.e.	i.e.	X
esrj-37073	76	29	,	,	PUNCT
esrj-37073	76	30	no	no	DET
esrj-37073	76	31	increase	increase	NOUN
esrj-37073	76	32	or	or	CCONJ
esrj-37073	76	33	decrease	decrease	NOUN
esrj-37073	76	34	in	in	ADP
esrj-37073	76	35	the	the	DET
esrj-37073	76	36	mutual	mutual	ADJ
esrj-37073	76	37	information	information	NOUN
esrj-37073	76	38	function	function	NOUN
esrj-37073	76	39	’s	’s	PART
esrj-37073	76	40	successive	successive	ADJ
esrj-37073	76	41	values	value	NOUN
esrj-37073	76	42	for	for	ADP
esrj-37073	76	43	a	a	DET
esrj-37073	76	44	specific	specific	ADJ
esrj-37073	76	45	lag	lag	NOUN
esrj-37073	76	46	time	time	NOUN
esrj-37073	76	47	.	.	PUNCT
esrj-37073	77	1	however	however	ADV
esrj-37073	77	2	,	,	PUNCT
esrj-37073	77	3	in	in	ADP
esrj-37073	77	4	some	some	DET
esrj-37073	77	5	mi	mi	PROPN
esrj-37073	77	6	functions	function	NOUN
esrj-37073	77	7	,	,	PUNCT
esrj-37073	77	8	it	it	PRON
esrj-37073	77	9	is	be	AUX
esrj-37073	77	10	rather	rather	ADV
esrj-37073	77	11	difficult	difficult	ADJ
esrj-37073	77	12	to	to	PART
esrj-37073	77	13	determine	determine	VERB
esrj-37073	77	14	a	a	DET
esrj-37073	77	15	local	local	ADJ
esrj-37073	77	16	minimum	minimum	NOUN
esrj-37073	77	17	.	.	PUNCT
esrj-37073	78	1	therefore	therefore	ADV
esrj-37073	78	2	,	,	PUNCT
esrj-37073	78	3	to	to	PART
esrj-37073	78	4	determine	determine	VERB
esrj-37073	78	5	the	the	DET
esrj-37073	78	6	optimal	optimal	ADJ
esrj-37073	78	7	delay	delay	NOUN
esrj-37073	78	8	time	time	NOUN
esrj-37073	78	9	,	,	PUNCT
esrj-37073	78	10	we	we	PRON
esrj-37073	78	11	recommend	recommend	VERB
esrj-37073	78	12	using	use	VERB
esrj-37073	78	13	the	the	DET
esrj-37073	78	14	following	follow	VERB
esrj-37073	78	15	formula	formula	NOUN
esrj-37073	78	16	to	to	PART
esrj-37073	78	17	amplify	amplify	VERB
esrj-37073	78	18	the	the	DET
esrj-37073	78	19	successive	successive	ADJ
esrj-37073	78	20	differences	difference	NOUN
esrj-37073	78	21	between	between	ADP
esrj-37073	78	22	the	the	DET
esrj-37073	78	23	calculated	calculate	VERB
esrj-37073	78	24	mi	mi	PROPN
esrj-37073	78	25	function	function	NOUN
esrj-37073	78	26	values	value	NOUN
esrj-37073	78	27	(	(	PUNCT
esrj-37073	78	28	tongal	tongal	PROPN
esrj-37073	78	29	et	et	PROPN
esrj-37073	78	30	al	al	PROPN
esrj-37073	78	31	.	.	PROPN
esrj-37073	78	32	,	,	PUNCT
esrj-37073	78	33	2013	2013	NUM
esrj-37073	78	34	):	):	PUNCT
esrj-37073	78	35	where	where	SCONJ
esrj-37073	78	36	currentmi	currentmi	NOUN
esrj-37073	78	37	is	be	AUX
esrj-37073	78	38	the	the	DET
esrj-37073	78	39	mutual	mutual	ADJ
esrj-37073	78	40	information	information	NOUN
esrj-37073	78	41	value	value	NOUN
esrj-37073	78	42	of	of	ADP
esrj-37073	78	43	which	which	PRON
esrj-37073	78	44	relative	relative	ADJ
esrj-37073	78	45	change	change	NOUN
esrj-37073	78	46	will	will	AUX
esrj-37073	78	47	be	be	AUX
esrj-37073	78	48	calculated	calculate	VERB
esrj-37073	78	49	,	,	PUNCT
esrj-37073	78	50	nextmi	nextmi	NOUN
esrj-37073	78	51	is	be	AUX
esrj-37073	78	52	the	the	DET
esrj-37073	78	53	successive	successive	ADJ
esrj-37073	78	54	value	value	NOUN
esrj-37073	78	55	of	of	ADP
esrj-37073	78	56	currentmi	currentmi	NOUN
esrj-37073	78	57	the	the	DET
esrj-37073	78	58	first	first	ADJ
esrj-37073	78	59	local	local	ADJ
esrj-37073	78	60	minimum	minimum	NOUN
esrj-37073	78	61	could	could	AUX
esrj-37073	78	62	be	be	AUX
esrj-37073	78	63	taken	take	VERB
esrj-37073	78	64	where	where	SCONJ
esrj-37073	78	65	the	the	DET
esrj-37073	78	66	relative	relative	ADJ
esrj-37073	78	67	change	change	NOUN
esrj-37073	78	68	of	of	ADP
esrj-37073	78	69	mutual	mutual	ADJ
esrj-37073	78	70	information	information	NOUN
esrj-37073	78	71	as	as	ADP
esrj-37073	78	72	a	a	DET
esrj-37073	78	73	function	function	NOUN
esrj-37073	78	74	of	of	ADP
esrj-37073	78	75	delay	delay	NOUN
esrj-37073	78	76	time	time	NOUN
esrj-37073	78	77	started	start	VERB
esrj-37073	78	78	to	to	PART
esrj-37073	78	79	become	become	VERB
esrj-37073	78	80	constant	constant	ADJ
esrj-37073	78	81	with	with	ADP
esrj-37073	78	82	lag	lag	NOUN
esrj-37073	78	83	time	time	NOUN
esrj-37073	78	84	.	.	PUNCT
esrj-37073	79	1	with	with	ADP
esrj-37073	79	2	a	a	DET
esrj-37073	79	3	properly	properly	ADV
esrj-37073	79	4	selected	select	VERB
esrj-37073	79	5	time	time	NOUN
esrj-37073	79	6	delay	delay	NOUN
esrj-37073	79	7	,	,	PUNCT
esrj-37073	79	8	the	the	DET
esrj-37073	79	9	considered	consider	VERB
esrj-37073	79	10	time	time	NOUN
esrj-37073	79	11	series	series	PROPN
esrj-37073	79	12	can	can	AUX
esrj-37073	79	13	be	be	AUX
esrj-37073	79	14	reconstructed	reconstruct	VERB
esrj-37073	79	15	in	in	ADP
esrj-37073	79	16	the	the	DET
esrj-37073	79	17	m	m	ADJ
esrj-37073	79	18	-	-	ADJ
esrj-37073	79	19	dimensional	dimensional	ADJ
esrj-37073	79	20	phase	phase	NOUN
esrj-37073	79	21	space	space	NOUN
esrj-37073	79	22	by	by	ADP
esrj-37073	79	23	calculating	calculate	VERB
esrj-37073	79	24	the	the	DET
esrj-37073	79	25	correlation	correlation	NOUN
esrj-37073	79	26	exponent	exponent	NOUN
esrj-37073	79	27	from	from	ADP
esrj-37073	79	28	the	the	DET
esrj-37073	79	29	correlation	correlation	NOUN
esrj-37073	79	30	integral	integral	ADJ
esrj-37073	79	31	(	(	PUNCT
esrj-37073	79	32	(	(	PUNCT
esrj-37073	79	33	)	)	PUNCT
esrj-37073	79	34	c	c	NOUN
esrj-37073	79	35	r	r	NOUN
esrj-37073	79	36	)	)	PUNCT
esrj-37073	79	37	as	as	SCONJ
esrj-37073	79	38	follows	follow	VERB
esrj-37073	79	39	:	:	PUNCT
esrj-37073	79	40	where	where	SCONJ
esrj-37073	79	41	h	h	NOUN
esrj-37073	79	42	is	be	AUX
esrj-37073	79	43	the	the	DET
esrj-37073	79	44	heaviside	heaviside	ADJ
esrj-37073	79	45	step	step	NOUN
esrj-37073	79	46	function	function	NOUN
esrj-37073	79	47	with	with	ADP
esrj-37073	79	48	(	(	PUNCT
esrj-37073	79	49	)	)	PUNCT
esrj-37073	79	50	1h	1h	NUM
esrj-37073	79	51	u	u	NOUN
esrj-37073	79	52	=	=	PUNCT
esrj-37073	79	53	for	for	ADP
esrj-37073	79	54	0u	0u	PROPN
esrj-37073	79	55	>	>	X
esrj-37073	79	56	,	,	PUNCT
esrj-37073	79	57	and	and	CCONJ
esrj-37073	79	58	(	(	PUNCT
esrj-37073	79	59	)	)	PUNCT
esrj-37073	79	60	0h	0h	PROPN
esrj-37073	79	61	u	u	NOUN
esrj-37073	79	62	=	=	PUNCT
esrj-37073	79	63	for	for	ADP
esrj-37073	79	64	,	,	PUNCT
esrj-37073	79	65	,	,	PUNCT
esrj-37073	79	66	r	r	NOUN
esrj-37073	79	67	is	be	AUX
esrj-37073	79	68	the	the	DET
esrj-37073	79	69	radius	radius	NOUN
esrj-37073	79	70	of	of	ADP
esrj-37073	79	71	a	a	DET
esrj-37073	79	72	sphere	sphere	NOUN
esrj-37073	79	73	centered	center	VERB
esrj-37073	79	74	on	on	ADP
esrj-37073	79	75	iy	iy	PROPN
esrj-37073	79	76	or	or	CCONJ
esrj-37073	79	77	jy	jy	PROPN
esrj-37073	79	78	,	,	PUNCT
esrj-37073	79	79	is	be	AUX
esrj-37073	79	80	the	the	DET
esrj-37073	79	81	euclidean	euclidean	ADJ
esrj-37073	79	82	norm	norm	NOUN
esrj-37073	79	83	,	,	PUNCT
esrj-37073	79	84	and	and	CCONJ
esrj-37073	79	85	n	n	PRON
esrj-37073	79	86	is	be	AUX
esrj-37073	79	87	the	the	DET
esrj-37073	79	88	number	number	NOUN
esrj-37073	79	89	of	of	ADP
esrj-37073	79	90	data	datum	NOUN
esrj-37073	79	91	points	point	NOUN
esrj-37073	79	92	.	.	PUNCT
esrj-37073	80	1	(	(	PUNCT
esrj-37073	80	2	)	)	PUNCT
esrj-37073	80	3	c	c	NOUN
esrj-37073	80	4	r	r	NOUN
esrj-37073	80	5	gives	give	VERB
esrj-37073	80	6	the	the	DET
esrj-37073	80	7	probability	probability	NOUN
esrj-37073	80	8	of	of	ADP
esrj-37073	80	9	two	two	NUM
esrj-37073	80	10	randomly	randomly	ADV
esrj-37073	80	11	selected	select	VERB
esrj-37073	80	12	vectors	vector	NOUN
esrj-37073	80	13	that	that	PRON
esrj-37073	80	14	lie	lie	VERB
esrj-37073	80	15	within	within	ADP
esrj-37073	80	16	a	a	DET
esrj-37073	80	17	certain	certain	ADJ
esrj-37073	80	18	distance	distance	NOUN
esrj-37073	80	19	(	(	PUNCT
esrj-37073	80	20	ng	ng	PROPN
esrj-37073	80	21	et	et	PROPN
esrj-37073	80	22	al	al	PROPN
esrj-37073	80	23	.	.	PROPN
esrj-37073	80	24	,	,	PUNCT
esrj-37073	80	25	2007	2007	NUM
esrj-37073	80	26	)	)	PUNCT
esrj-37073	80	27	.	.	PUNCT
esrj-37073	81	1	the	the	DET
esrj-37073	81	2	dimension	dimension	NOUN
esrj-37073	81	3	d	d	PROPN
esrj-37073	81	4	of	of	ADP
esrj-37073	81	5	the	the	DET
esrj-37073	81	6	state	state	NOUN
esrj-37073	81	7	space	space	NOUN
esrj-37073	81	8	is	be	AUX
esrj-37073	81	9	related	relate	VERB
esrj-37073	81	10	to	to	ADP
esrj-37073	81	11	the	the	DET
esrj-37073	81	12	correlation	correlation	NOUN
esrj-37073	81	13	integral	integral	ADJ
esrj-37073	81	14	as	as	ADP
esrj-37073	81	15	:	:	PUNCT
esrj-37073	81	16	additionally	additionally	ADV
esrj-37073	81	17	,	,	PUNCT
esrj-37073	81	18	the	the	DET
esrj-37073	81	19	logarithm	logarithm	NOUN
esrj-37073	81	20	of	of	ADP
esrj-37073	81	21	both	both	DET
esrj-37073	81	22	sides	side	NOUN
esrj-37073	81	23	of	of	ADP
esrj-37073	81	24	eq	eq	PROPN
esrj-37073	81	25	.	.	PUNCT
esrj-37073	82	1	(	(	PUNCT
esrj-37073	82	2	5	5	X
esrj-37073	82	3	)	)	PUNCT
esrj-37073	82	4	gives	give	VERB
esrj-37073	82	5	a	a	DET
esrj-37073	82	6	linear	linear	ADJ
esrj-37073	82	7	relationship	relationship	NOUN
esrj-37073	82	8	where	where	SCONJ
esrj-37073	82	9	the	the	DET
esrj-37073	82	10	slope	slope	NOUN
esrj-37073	82	11	equals	equal	VERB
esrj-37073	82	12	to	to	ADP
esrj-37073	82	13	the	the	DET
esrj-37073	82	14	correlation	correlation	NOUN
esrj-37073	82	15	exponent	exponent	NOUN
esrj-37073	82	16	d.	d.	PROPN
esrj-37073	82	17	if	if	SCONJ
esrj-37073	82	18	the	the	DET
esrj-37073	82	19	correlation	correlation	NOUN
esrj-37073	82	20	exponents	exponent	NOUN
esrj-37073	82	21	increase	increase	VERB
esrj-37073	82	22	as	as	ADP
esrj-37073	82	23	a	a	DET
esrj-37073	82	24	function	function	NOUN
esrj-37073	82	25	of	of	ADP
esrj-37073	82	26	embedding	embed	VERB
esrj-37073	82	27	dimension	dimension	NOUN
esrj-37073	82	28	,	,	PUNCT
esrj-37073	82	29	then	then	ADV
esrj-37073	82	30	the	the	DET
esrj-37073	82	31	considered	consider	VERB
esrj-37073	82	32	system	system	NOUN
esrj-37073	82	33	can	can	AUX
esrj-37073	82	34	be	be	AUX
esrj-37073	82	35	thought	think	VERB
esrj-37073	82	36	of	of	ADP
esrj-37073	82	37	as	as	ADP
esrj-37073	82	38	stochastic	stochastic	ADJ
esrj-37073	82	39	,	,	PUNCT
esrj-37073	82	40	otherwise	otherwise	ADV
esrj-37073	82	41	it	it	PRON
esrj-37073	82	42	is	be	AUX
esrj-37073	82	43	chaotic	chaotic	ADJ
esrj-37073	82	44	.	.	PUNCT
esrj-37073	83	1	in	in	ADP
esrj-37073	83	2	the	the	DET
esrj-37073	83	3	latter	latter	ADJ
esrj-37073	83	4	situation	situation	NOUN
esrj-37073	83	5	,	,	PUNCT
esrj-37073	83	6	the	the	DET
esrj-37073	83	7	correlation	correlation	NOUN
esrj-37073	83	8	exponents	exponent	NOUN
esrj-37073	83	9	reach	reach	VERB
esrj-37073	83	10	a	a	DET
esrj-37073	83	11	saturation	saturation	NOUN
esrj-37073	83	12	value	value	NOUN
esrj-37073	83	13	,	,	PUNCT
esrj-37073	83	14	which	which	PRON
esrj-37073	83	15	provides	provide	VERB
esrj-37073	83	16	the	the	DET
esrj-37073	83	17	correlation	correlation	NOUN
esrj-37073	83	18	dimension	dimension	NOUN
esrj-37073	83	19	of	of	ADP
esrj-37073	83	20	the	the	DET
esrj-37073	83	21	system	system	NOUN
esrj-37073	83	22	.	.	PUNCT
esrj-37073	84	1	the	the	DET
esrj-37073	84	2	correlation	correlation	NOUN
esrj-37073	84	3	dimension	dimension	NOUN
esrj-37073	84	4	is	be	AUX
esrj-37073	84	5	a	a	DET
esrj-37073	84	6	parameter	parameter	NOUN
esrj-37073	84	7	that	that	PRON
esrj-37073	84	8	gives	give	VERB
esrj-37073	84	9	the	the	DET
esrj-37073	84	10	number	number	NOUN
esrj-37073	84	11	of	of	ADP
esrj-37073	84	12	dominant	dominant	ADJ
esrj-37073	84	13	processes	process	NOUN
esrj-37073	84	14	that	that	PRON
esrj-37073	84	15	are	be	AUX
esrj-37073	84	16	acting	act	VERB
esrj-37073	84	17	in	in	ADP
esrj-37073	84	18	the	the	DET
esrj-37073	84	19	system	system	NOUN
esrj-37073	84	20	dynamics	dynamic	NOUN
esrj-37073	84	21	(	(	PUNCT
esrj-37073	84	22	sivakumar	sivakumar	NOUN
esrj-37073	84	23	and	and	CCONJ
esrj-37073	84	24	jayawardena	jayawardena	PROPN
esrj-37073	84	25	,	,	PUNCT
esrj-37073	84	26	2002	2002	NUM
esrj-37073	84	27	)	)	PUNCT
esrj-37073	84	28	.	.	PUNCT
esrj-37073	85	1	with	with	ADP
esrj-37073	85	2	the	the	DET
esrj-37073	85	3	determination	determination	NOUN
esrj-37073	85	4	of	of	ADP
esrj-37073	85	5	the	the	DET
esrj-37073	85	6	optimal	optimal	ADJ
esrj-37073	85	7	delay	delay	NOUN
esrj-37073	85	8	time	time	NOUN
esrj-37073	85	9	and	and	CCONJ
esrj-37073	85	10	embedding	embed	VERB
esrj-37073	85	11	dimension	dimension	NOUN
esrj-37073	85	12	,	,	PUNCT
esrj-37073	85	13	the	the	DET
esrj-37073	85	14	state	state	NOUN
esrj-37073	85	15	space	space	NOUN
esrj-37073	85	16	of	of	ADP
esrj-37073	85	17	the	the	DET
esrj-37073	85	18	system	system	NOUN
esrj-37073	85	19	can	can	AUX
esrj-37073	85	20	be	be	AUX
esrj-37073	85	21	constructed	construct	VERB
esrj-37073	85	22	,	,	PUNCT
esrj-37073	85	23	from	from	ADP
esrj-37073	85	24	which	which	PRON
esrj-37073	85	25	interpreting	interpret	VERB
esrj-37073	85	26	the	the	DET
esrj-37073	85	27	dynamics	dynamic	NOUN
esrj-37073	85	28	of	of	ADP
esrj-37073	85	29	an	an	DET
esrj-37073	85	30	m	m	ADJ
esrj-37073	85	31	-	-	ADJ
esrj-37073	85	32	dimensional	dimensional	ADJ
esrj-37073	85	33	map	map	NOUN
esrj-37073	85	34	is	be	AUX
esrj-37073	85	35	possible	possible	ADJ
esrj-37073	85	36	using	use	VERB
esrj-37073	85	37	the	the	DET
esrj-37073	85	38	following	follow	VERB
esrj-37073	85	39	equation	equation	NOUN
esrj-37073	85	40	:	:	PUNCT
esrj-37073	85	41	where	where	SCONJ
esrj-37073	85	42	te	te	PROPN
esrj-37073	85	43	is	be	AUX
esrj-37073	85	44	a	a	DET
esrj-37073	85	45	noise	noise	NOUN
esrj-37073	85	46	term	term	NOUN
esrj-37073	85	47	and	and	CCONJ
esrj-37073	85	48	and	and	CCONJ
esrj-37073	85	49	are	be	AUX
esrj-37073	85	50	vectors	vector	NOUN
esrj-37073	85	51	of	of	ADP
esrj-37073	85	52	dimension	dimension	NOUN
esrj-37073	85	53	m	m	VERB
esrj-37073	85	54	that	that	PRON
esrj-37073	85	55	describe	describe	VERB
esrj-37073	85	56	the	the	DET
esrj-37073	85	57	state	state	NOUN
esrj-37073	85	58	of	of	ADP
esrj-37073	85	59	the	the	DET
esrj-37073	85	60	system	system	NOUN
esrj-37073	85	61	at	at	ADP
esrj-37073	85	62	times	times	PROPN
esrj-37073	85	63	t	t	PROPN
esrj-37073	85	64	(	(	PUNCT
esrj-37073	85	65	current	current	ADJ
esrj-37073	85	66	state	state	NOUN
esrj-37073	85	67	)	)	PUNCT
esrj-37073	85	68	and	and	CCONJ
esrj-37073	85	69	t	t	PROPN
esrj-37073	86	1	t+	t+	PRON
esrj-37073	86	2	(	(	PUNCT
esrj-37073	86	3	future	future	ADJ
esrj-37073	86	4	state	state	NOUN
esrj-37073	86	5	)	)	PUNCT
esrj-37073	86	6	,	,	PUNCT
esrj-37073	86	7	respectively	respectively	ADV
esrj-37073	86	8	.	.	PUNCT
esrj-37073	87	1	if	if	SCONJ
esrj-37073	87	2	the	the	DET
esrj-37073	87	3	function	function	NOUN
esrj-37073	87	4	is	be	AUX
esrj-37073	87	5	known	know	VERB
esrj-37073	87	6	,	,	PUNCT
esrj-37073	87	7	it	it	PRON
esrj-37073	87	8	is	be	AUX
esrj-37073	87	9	possible	possible	ADJ
esrj-37073	87	10	to	to	PART
esrj-37073	87	11	predict	predict	VERB
esrj-37073	87	12	the	the	DET
esrj-37073	87	13	future	future	ADJ
esrj-37073	87	14	trajectory	trajectory	NOUN
esrj-37073	87	15	of	of	ADP
esrj-37073	87	16	a	a	DET
esrj-37073	87	17	system	system	NOUN
esrj-37073	87	18	.	.	PUNCT
esrj-37073	88	1	the	the	DET
esrj-37073	88	2	function	function	NOUN
esrj-37073	88	3	can	can	AUX
esrj-37073	88	4	be	be	AUX
esrj-37073	88	5	found	find	VERB
esrj-37073	88	6	with	with	ADP
esrj-37073	88	7	the	the	DET
esrj-37073	88	8	k	k	NOUN
esrj-37073	88	9	-	-	PUNCT
esrj-37073	88	10	nearest	near	ADJ
esrj-37073	88	11	neighbor	neighbor	NOUN
esrj-37073	88	12	(	(	PUNCT
esrj-37073	88	13	k	k	PROPN
esrj-37073	88	14	-	-	PUNCT
esrj-37073	88	15	nn	nn	NOUN
esrj-37073	88	16	)	)	PUNCT
esrj-37073	88	17	approach	approach	NOUN
esrj-37073	88	18	which	which	PRON
esrj-37073	88	19	was	be	AUX
esrj-37073	88	20	proposed	propose	VERB
esrj-37073	88	21	by	by	ADP
esrj-37073	88	22	farmer	farmer	NOUN
esrj-37073	88	23	and	and	CCONJ
esrj-37073	88	24	sidorowich	sidorowich	PROPN
esrj-37073	88	25	(	(	PUNCT
esrj-37073	88	26	1987	1987	NUM
esrj-37073	88	27	)	)	PUNCT
esrj-37073	88	28	.	.	PUNCT
esrj-37073	89	1	in	in	ADP
esrj-37073	89	2	this	this	DET
esrj-37073	89	3	approach	approach	NOUN
esrj-37073	89	4	,	,	PUNCT
esrj-37073	89	5	the	the	DET
esrj-37073	89	6	nearby	nearby	ADJ
esrj-37073	89	7	states	state	NOUN
esrj-37073	89	8	are	be	AUX
esrj-37073	89	9	used	use	VERB
esrj-37073	89	10	to	to	PART
esrj-37073	89	11	obtain	obtain	VERB
esrj-37073	89	12	future	future	ADJ
esrj-37073	89	13	forecasts	forecast	NOUN
esrj-37073	89	14	.	.	PUNCT
esrj-37073	90	1	one	one	NUM
esrj-37073	90	2	of	of	ADP
esrj-37073	90	3	the	the	DET
esrj-37073	90	4	most	most	ADV
esrj-37073	90	5	commonly	commonly	ADV
esrj-37073	90	6	used	use	VERB
esrj-37073	90	7	functions	function	NOUN
esrj-37073	90	8	for	for	ADP
esrj-37073	90	9	k	k	PROPN
esrj-37073	90	10	-	-	PUNCT
esrj-37073	90	11	nn	nn	PROPN
esrj-37073	90	12	is	be	AUX
esrj-37073	90	13	the	the	DET
esrj-37073	90	14	weighted	weighted	ADJ
esrj-37073	90	15	form	form	NOUN
esrj-37073	90	16	:	:	PUNCT
esrj-37073	90	17	where	where	SCONJ
esrj-37073	90	18	(	(	PUNCT
esrj-37073	90	19	)	)	PUNCT
esrj-37073	90	20	ia	ia	PROPN
esrj-37073	90	21	t	t	PROPN
esrj-37073	90	22	are	be	AUX
esrj-37073	90	23	the	the	DET
esrj-37073	90	24	nearest	near	ADJ
esrj-37073	90	25	neighbors	neighbor	NOUN
esrj-37073	90	26	of	of	ADP
esrj-37073	90	27	the	the	DET
esrj-37073	90	28	last	last	ADJ
esrj-37073	90	29	observed	observe	VERB
esrj-37073	90	30	value	value	NOUN
esrj-37073	90	31	(	(	PUNCT
esrj-37073	90	32	i.e.	i.e.	X
esrj-37073	90	33	,	,	PUNCT
esrj-37073	90	34	prediction	prediction	NOUN
esrj-37073	90	35	starting	starting	NOUN
esrj-37073	90	36	point	point	NOUN
esrj-37073	90	37	)	)	PUNCT
esrj-37073	90	38	and	and	CCONJ
esrj-37073	90	39	are	be	AUX
esrj-37073	90	40	the	the	DET
esrj-37073	90	41	weights	weight	NOUN
esrj-37073	90	42	to	to	PART
esrj-37073	90	43	be	be	AUX
esrj-37073	90	44	adjusted	adjust	VERB
esrj-37073	90	45	using	use	VERB
esrj-37073	90	46	the	the	DET
esrj-37073	90	47	information	information	NOUN
esrj-37073	90	48	from	from	ADP
esrj-37073	90	49	the	the	DET
esrj-37073	90	50	n	n	ADV
esrj-37073	90	51	-	-	PUNCT
esrj-37073	90	52	nearest	near	ADJ
esrj-37073	90	53	points	point	NOUN
esrj-37073	90	54	.	.	PUNCT
esrj-37073	91	1	l	l	NOUN
esrj-37073	91	2	denotes	denote	VERB
esrj-37073	91	3	that	that	SCONJ
esrj-37073	91	4	these	these	DET
esrj-37073	91	5	weights	weight	NOUN
esrj-37073	91	6	are	be	AUX
esrj-37073	91	7	different	different	ADJ
esrj-37073	91	8	for	for	ADP
esrj-37073	91	9	each	each	DET
esrj-37073	91	10	forecasted	forecast	VERB
esrj-37073	91	11	point	point	NOUN
esrj-37073	91	12	.	.	PUNCT
esrj-37073	92	1	for	for	ADP
esrj-37073	92	2	more	more	ADJ
esrj-37073	92	3	details	detail	NOUN
esrj-37073	92	4	,	,	PUNCT
esrj-37073	92	5	please	please	INTJ
esrj-37073	92	6	refer	refer	VERB
esrj-37073	92	7	to	to	ADP
esrj-37073	92	8	wu	wu	PROPN
esrj-37073	92	9	and	and	CCONJ
esrj-37073	92	10	chau	chau	NOUN
esrj-37073	92	11	(	(	PUNCT
esrj-37073	92	12	2010	2010	NUM
esrj-37073	92	13	)	)	PUNCT
esrj-37073	92	14	,	,	PUNCT
esrj-37073	92	15	ng	ng	PROPN
esrj-37073	92	16	et	et	PROPN
esrj-37073	92	17	al	al	PROPN
esrj-37073	92	18	.	.	PROPN
esrj-37073	93	1	(	(	PUNCT
esrj-37073	93	2	2007	2007	NUM
esrj-37073	93	3	)	)	PUNCT
esrj-37073	93	4	,	,	PUNCT
esrj-37073	93	5	laio	laio	NOUN
esrj-37073	93	6	et	et	PROPN
esrj-37073	93	7	al	al	PROPN
esrj-37073	93	8	.	.	PROPN
esrj-37073	93	9	,	,	PUNCT
esrj-37073	93	10	(	(	PUNCT
esrj-37073	93	11	2003	2003	NUM
esrj-37073	93	12	)	)	PUNCT
esrj-37073	93	13	and	and	CCONJ
esrj-37073	93	14	liu	liu	PROPN
esrj-37073	93	15	et	et	PROPN
esrj-37073	93	16	al	al	PROPN
esrj-37073	93	17	.	.	PUNCT
esrj-37073	94	1	(	(	PUNCT
esrj-37073	94	2	1998	1998	NUM
esrj-37073	94	3	)	)	PUNCT
esrj-37073	94	4	.	.	PUNCT
esrj-37073	95	1	3.2	3.2	NUM
esrj-37073	95	2	.	.	PUNCT
esrj-37073	95	3	feed	feed	NOUN
esrj-37073	95	4	-	-	PUNCT
esrj-37073	95	5	forward	forward	NOUN
esrj-37073	95	6	neural	neural	ADJ
esrj-37073	95	7	networks	network	NOUN
esrj-37073	95	8	artificial	artificial	ADJ
esrj-37073	95	9	neural	neural	ADJ
esrj-37073	95	10	networks	network	NOUN
esrj-37073	95	11	(	(	PUNCT
esrj-37073	95	12	ann	ann	PROPN
esrj-37073	95	13	)	)	PUNCT
esrj-37073	95	14	use	use	VERB
esrj-37073	95	15	a	a	DET
esrj-37073	95	16	multilayered	multilayered	ADJ
esrj-37073	95	17	approach	approach	NOUN
esrj-37073	95	18	that	that	PRON
esrj-37073	95	19	approximates	approximate	VERB
esrj-37073	95	20	complex	complex	ADJ
esrj-37073	95	21	mathematical	mathematical	ADJ
esrj-37073	95	22	functions	function	NOUN
esrj-37073	95	23	to	to	PART
esrj-37073	95	24	process	process	VERB
esrj-37073	95	25	data	datum	NOUN
esrj-37073	95	26	.	.	PUNCT
esrj-37073	96	1	an	an	DET
esrj-37073	96	2	ann	ann	PROPN
esrj-37073	96	3	is	be	AUX
esrj-37073	96	4	a	a	DET
esrj-37073	96	5	system	system	NOUN
esrj-37073	96	6	that	that	PRON
esrj-37073	96	7	is	be	AUX
esrj-37073	96	8	composed	compose	VERB
esrj-37073	96	9	of	of	ADP
esrj-37073	96	10	discrete	discrete	ADJ
esrj-37073	96	11	layers	layer	NOUN
esrj-37073	96	12	with	with	ADP
esrj-37073	96	13	each	each	DET
esrj-37073	96	14	layer	layer	NOUN
esrj-37073	96	15	including	include	VERB
esrj-37073	96	16	at	at	ADV
esrj-37073	96	17	least	least	ADV
esrj-37073	96	18	one	one	NUM
esrj-37073	96	19	neuron	neuron	NOUN
esrj-37073	96	20	.	.	PUNCT
esrj-37073	97	1	with	with	ADP
esrj-37073	97	2	a	a	DET
esrj-37073	97	3	connection	connection	NOUN
esrj-37073	97	4	weight	weight	NOUN
esrj-37073	97	5	,	,	PUNCT
esrj-37073	97	6	each	each	DET
esrj-37073	97	7	node	node	NOUN
esrj-37073	97	8	of	of	ADP
esrj-37073	97	9	a	a	DET
esrj-37073	97	10	layer	layer	NOUN
esrj-37073	97	11	is	be	AUX
esrj-37073	97	12	connected	connect	VERB
esrj-37073	97	13	to	to	ADP
esrj-37073	97	14	the	the	DET
esrj-37073	97	15	node(s	node(s	NOUN
esrj-37073	97	16	)	)	PUNCT
esrj-37073	97	17	of	of	ADP
esrj-37073	97	18	the	the	DET
esrj-37073	97	19	preceding	precede	VERB
esrj-37073	97	20	layer	layer	NOUN
esrj-37073	97	21	but	but	CCONJ
esrj-37073	97	22	not	not	PART
esrj-37073	97	23	to	to	ADP
esrj-37073	97	24	nodes	node	NOUN
esrj-37073	97	25	of	of	ADP
esrj-37073	97	26	the	the	DET
esrj-37073	97	27	same	same	ADJ
esrj-37073	97	28	layer	layer	NOUN
esrj-37073	97	29	(	(	PUNCT
esrj-37073	97	30	sahoo	sahoo	PROPN
esrj-37073	97	31	et	et	PROPN
esrj-37073	97	32	al	al	PROPN
esrj-37073	97	33	.	.	PROPN
esrj-37073	97	34	,	,	PUNCT
esrj-37073	97	35	2009	2009	NUM
esrj-37073	97	36	)	)	PUNCT
esrj-37073	97	37	.	.	PUNCT
esrj-37073	98	1	considering	consider	VERB
esrj-37073	98	2	the	the	DET
esrj-37073	98	3	feed	feed	NOUN
esrj-37073	98	4	forward	forward	ADV
esrj-37073	98	5	neural	neural	ADJ
esrj-37073	98	6	network	network	NOUN
esrj-37073	98	7	architecture	architecture	NOUN
esrj-37073	98	8	in	in	ADP
esrj-37073	98	9	figure	figure	NOUN
esrj-37073	98	10	2	2	NUM
esrj-37073	98	11	,	,	PUNCT
esrj-37073	98	12	if	if	SCONJ
esrj-37073	98	13	the	the	DET
esrj-37073	98	14	layers	layer	NOUN
esrj-37073	98	15	and	and	CCONJ
esrj-37073	98	16	the	the	DET
esrj-37073	98	17	neurons	neuron	NOUN
esrj-37073	98	18	in	in	ADP
esrj-37073	98	19	the	the	DET
esrj-37073	98	20	layers	layer	NOUN
esrj-37073	98	21	increase	increase	NOUN
esrj-37073	98	22	,	,	PUNCT
esrj-37073	98	23	the	the	DET
esrj-37073	98	24	architecture	architecture	NOUN
esrj-37073	98	25	of	of	ADP
esrj-37073	98	26	the	the	DET
esrj-37073	98	27	ann	ann	PROPN
esrj-37073	98	28	becomes	become	VERB
esrj-37073	98	29	more	more	ADV
esrj-37073	98	30	complex	complex	ADJ
esrj-37073	98	31	,	,	PUNCT
esrj-37073	98	32	which	which	PRON
esrj-37073	98	33	complicates	complicate	VERB
esrj-37073	98	34	the	the	DET
esrj-37073	98	35	solution	solution	NOUN
esrj-37073	98	36	process	process	NOUN
esrj-37073	98	37	.	.	PUNCT
esrj-37073	99	1	therefore	therefore	ADV
esrj-37073	99	2	,	,	PUNCT
esrj-37073	99	3	it	it	PRON
esrj-37073	99	4	is	be	AUX
esrj-37073	99	5	important	important	ADJ
esrj-37073	99	6	to	to	PART
esrj-37073	99	7	select	select	VERB
esrj-37073	99	8	an	an	DET
esrj-37073	99	9	optimal	optimal	ADJ
esrj-37073	99	10	ann	ann	NOUN
esrj-37073	99	11	architecture	architecture	NOUN
esrj-37073	99	12	.	.	PUNCT
esrj-37073	100	1	in	in	ADP
esrj-37073	100	2	this	this	DET
esrj-37073	100	3	study	study	NOUN
esrj-37073	100	4	,	,	PUNCT
esrj-37073	100	5	the	the	DET
esrj-37073	100	6	numbers	number	NOUN
esrj-37073	100	7	of	of	ADP
esrj-37073	100	8	neurons	neuron	NOUN
esrj-37073	100	9	in	in	ADP
esrj-37073	100	10	the	the	DET
esrj-37073	100	11	layers	layer	NOUN
esrj-37073	100	12	were	be	AUX
esrj-37073	100	13	determined	determine	VERB
esrj-37073	100	14	with	with	ADP
esrj-37073	100	15	a	a	DET
esrj-37073	100	16	trial	trial	NOUN
esrj-37073	100	17	and	and	CCONJ
esrj-37073	100	18	error	error	NOUN
esrj-37073	100	19	process	process	NOUN
esrj-37073	100	20	that	that	PRON
esrj-37073	100	21	minimized	minimize	VERB
esrj-37073	100	22	the	the	DET
esrj-37073	100	23	root	root	NOUN
esrj-37073	100	24	mean	mean	VERB
esrj-37073	100	25	square	square	ADJ
esrj-37073	100	26	error	error	NOUN
esrj-37073	100	27	calculated	calculate	VERB
esrj-37073	100	28	from	from	ADP
esrj-37073	100	29	the	the	DET
esrj-37073	100	30	differences	difference	NOUN
esrj-37073	100	31	between	between	ADP
esrj-37073	100	32	the	the	DET
esrj-37073	100	33	predicted	predict	VERB
esrj-37073	100	34	and	and	CCONJ
esrj-37073	100	35	observed	observed	ADJ
esrj-37073	100	36	values	value	NOUN
esrj-37073	100	37	.	.	PUNCT
esrj-37073	101	1	figure	figure	NOUN
esrj-37073	101	2	2	2	NUM
esrj-37073	101	3	.	.	PUNCT
esrj-37073	102	1	a	a	DET
esrj-37073	102	2	typical	typical	ADJ
esrj-37073	102	3	feed	feed	NOUN
esrj-37073	102	4	forward	forward	ADV
esrj-37073	102	5	neural	neural	ADJ
esrj-37073	102	6	network	network	NOUN
esrj-37073	102	7	architecture	architecture	NOUN
esrj-37073	102	8	in	in	ADP
esrj-37073	102	9	figure	figure	NOUN
esrj-37073	102	10	2	2	NUM
esrj-37073	102	11	,	,	PUNCT
esrj-37073	102	12	the	the	DET
esrj-37073	102	13	input	input	NOUN
esrj-37073	102	14	signal	signal	NOUN
esrj-37073	102	15	propagates	propagate	VERB
esrj-37073	102	16	from	from	ADP
esrj-37073	102	17	layer	layer	NOUN
esrj-37073	102	18	to	to	ADP
esrj-37073	102	19	layer	layer	NOUN
esrj-37073	102	20	through	through	ADP
esrj-37073	102	21	the	the	DET
esrj-37073	102	22	network	network	NOUN
esrj-37073	102	23	in	in	ADP
esrj-37073	102	24	a	a	DET
esrj-37073	102	25	forward	forward	ADJ
esrj-37073	102	26	direction	direction	NOUN
esrj-37073	102	27	.	.	PUNCT
esrj-37073	103	1	the	the	DET
esrj-37073	103	2	weight	weight	NOUN
esrj-37073	103	3	vectors	vector	NOUN
esrj-37073	103	4	between	between	ADP
esrj-37073	103	5	the	the	DET
esrj-37073	103	6	layers	layer	NOUN
esrj-37073	103	7	(	(	PUNCT
esrj-37073	103	8	ijw	ijw	VERB
esrj-37073	103	9	and	and	CCONJ
esrj-37073	103	10	jkw	jkw	NOUN
esrj-37073	103	11	)	)	PUNCT
esrj-37073	103	12	were	be	AUX
esrj-37073	103	13	randomly	randomly	ADV
esrj-37073	103	14	generated	generate	VERB
esrj-37073	103	15	in	in	ADP
esrj-37073	103	16	the	the	DET
esrj-37073	103	17	range	range	NOUN
esrj-37073	103	18	between	between	ADP
esrj-37073	103	19	-1	-1	PUNCT
esrj-37073	103	20	and	and	CCONJ
esrj-37073	103	21	1	1	X
esrj-37073	103	22	.	.	X
esrj-37073	104	1	the	the	DET
esrj-37073	104	2	total	total	ADJ
esrj-37073	104	3	output	output	NOUN
esrj-37073	104	4	of	of	ADP
esrj-37073	104	5	a	a	DET
esrj-37073	104	6	jth	jth	PROPN
esrj-37073	104	7	hidden	hide	VERB
esrj-37073	104	8	neuron	neuron	NOUN
esrj-37073	104	9	was	be	AUX
esrj-37073	104	10	computed	compute	VERB
esrj-37073	104	11	according	accord	VERB
esrj-37073	104	12	to	to	ADP
esrj-37073	104	13	:	:	PUNCT
esrj-37073	104	14	where	where	SCONJ
esrj-37073	104	15	iq	iq	NOUN
esrj-37073	104	16	is	be	AUX
esrj-37073	104	17	the	the	DET
esrj-37073	104	18	value	value	NOUN
esrj-37073	104	19	of	of	ADP
esrj-37073	104	20	the	the	DET
esrj-37073	104	21	ith	ith	PROPN
esrj-37073	104	22	input	input	NOUN
esrj-37073	104	23	parameter	parameter	NOUN
esrj-37073	104	24	to	to	ADP
esrj-37073	104	25	the	the	DET
esrj-37073	104	26	hidden	hide	VERB
esrj-37073	104	27	layer	layer	NOUN
esrj-37073	104	28	neurons	neuron	NOUN
esrj-37073	104	29	,	,	PUNCT
esrj-37073	104	30	jb	jb	PROPN
esrj-37073	104	31	is	be	AUX
esrj-37073	104	32	the	the	DET
esrj-37073	104	33	bias	bias	NOUN
esrj-37073	104	34	for	for	ADP
esrj-37073	104	35	the	the	DET
esrj-37073	104	36	jth	jth	PROPN
esrj-37073	104	37	hidden	hide	VERB
esrj-37073	104	38	layer	layer	NOUN
esrj-37073	104	39	neuron	neuron	NOUN
esrj-37073	104	40	and	and	CCONJ
esrj-37073	104	41	n	n	PRON
esrj-37073	104	42	is	be	AUX
esrj-37073	104	43	the	the	DET
esrj-37073	104	44	total	total	ADJ
esrj-37073	104	45	number	number	NOUN
esrj-37073	104	46	of	of	ADP
esrj-37073	104	47	input	input	NOUN
esrj-37073	104	48	neurons	neuron	NOUN
esrj-37073	104	49	.	.	PUNCT
esrj-37073	105	1	the	the	DET
esrj-37073	105	2	calculated	calculate	VERB
esrj-37073	105	3	total	total	ADJ
esrj-37073	105	4	input	input	NOUN
esrj-37073	105	5	signal	signal	NOUN
esrj-37073	105	6	,	,	PUNCT
esrj-37073	105	7	js	js	INTJ
esrj-37073	105	8	,	,	PUNCT
esrj-37073	105	9	that	that	PRON
esrj-37073	105	10	received	receive	VERB
esrj-37073	105	11	the	the	DET
esrj-37073	105	12	jth	jth	PROPN
esrj-37073	105	13	hidden	hide	VERB
esrj-37073	105	14	layer	layer	NOUN
esrj-37073	105	15	neuron	neuron	NOUN
esrj-37073	105	16	was	be	AUX
esrj-37073	105	17	converted	convert	VERB
esrj-37073	105	18	to	to	ADP
esrj-37073	105	19	an	an	DET
esrj-37073	105	20	output	output	NOUN
esrj-37073	105	21	signal	signal	NOUN
esrj-37073	105	22	using	use	VERB
esrj-37073	105	23	an	an	DET
esrj-37073	105	24	activation	activation	NOUN
esrj-37073	105	25	function	function	NOUN
esrj-37073	105	26	.	.	PUNCT
esrj-37073	106	1	the	the	DET
esrj-37073	106	2	output	output	NOUN
esrj-37073	106	3	signal	signal	NOUN
esrj-37073	106	4	of	of	ADP
esrj-37073	106	5	the	the	DET
esrj-37073	106	6	jth	jth	PROPN
esrj-37073	106	7	hidden	hide	VERB
esrj-37073	106	8	layer	layer	NOUN
esrj-37073	106	9	neuron	neuron	NOUN
esrj-37073	106	10	was	be	AUX
esrj-37073	106	11	for	for	ADP
esrj-37073	106	12	the	the	DET
esrj-37073	106	13	n	n	PRON
esrj-37073	106	14	th	th	NOUN
esrj-37073	106	15	pattern	pattern	NOUN
esrj-37073	106	16	of	of	ADP
esrj-37073	106	17	the	the	DET
esrj-37073	106	18	training	training	NOUN
esrj-37073	106	19	data	datum	NOUN
esrj-37073	106	20	set	set	VERB
esrj-37073	106	21	.	.	PUNCT
esrj-37073	107	1	nonlinear	nonlinear	ADJ
esrj-37073	107	2	forecasting	forecasting	NOUN
esrj-37073	107	3	of	of	ADP
esrj-37073	107	4	stream	stream	NOUN
esrj-37073	107	5	flows	flow	NOUN
esrj-37073	107	6	using	use	VERB
esrj-37073	107	7	a	a	DET
esrj-37073	107	8	chaotic	chaotic	ADJ
esrj-37073	107	9	approach	approach	NOUN
esrj-37073	107	10	and	and	CCONJ
esrj-37073	107	11	artificial	artificial	ADJ
esrj-37073	107	12	neural	neural	ADJ
esrj-37073	107	13	networks	network	NOUN
esrj-37073	107	14	(	(	PUNCT
esrj-37073	107	15	2	2	NUM
esrj-37073	107	16	)	)	PUNCT
esrj-37073	107	17	(	(	PUNCT
esrj-37073	107	18	3	3	X
esrj-37073	107	19	)	)	PUNCT
esrj-37073	107	20	(	(	PUNCT
esrj-37073	107	21	4	4	NUM
esrj-37073	107	22	)	)	PUNCT
esrj-37073	107	23	(	(	PUNCT
esrj-37073	107	24	5	5	NUM
esrj-37073	107	25	)	)	PUNCT
esrj-37073	107	26	(	(	PUNCT
esrj-37073	107	27	6	6	NUM
esrj-37073	107	28	)	)	PUNCT
esrj-37073	107	29	(	(	PUNCT
esrj-37073	107	30	7	7	NUM
esrj-37073	107	31	)	)	PUNCT
esrj-37073	107	32	(	(	PUNCT
esrj-37073	107	33	8)	8)	NUM
esrj-37073	107	34	122	122	NUM
esrj-37073	107	35	the	the	DET
esrj-37073	107	36	output	output	NOUN
esrj-37073	107	37	neuron	neuron	NOUN
esrj-37073	107	38	received	receive	VERB
esrj-37073	107	39	signals	signal	NOUN
esrj-37073	107	40	from	from	ADP
esrj-37073	107	41	all	all	DET
esrj-37073	107	42	hidden	hide	VERB
esrj-37073	107	43	-	-	PUNCT
esrj-37073	107	44	layer	layer	NOUN
esrj-37073	107	45	neurons	neuron	NOUN
esrj-37073	107	46	and	and	CCONJ
esrj-37073	107	47	converted	convert	VERB
esrj-37073	107	48	them	they	PRON
esrj-37073	107	49	to	to	ADP
esrj-37073	107	50	a	a	DET
esrj-37073	107	51	single	single	ADJ
esrj-37073	107	52	signal	signal	NOUN
esrj-37073	107	53	as	as	ADP
esrj-37073	107	54	output	output	NOUN
esrj-37073	107	55	using	use	VERB
esrj-37073	107	56	an	an	DET
esrj-37073	107	57	activation	activation	NOUN
esrj-37073	107	58	function	function	NOUN
esrj-37073	107	59	.	.	PUNCT
esrj-37073	108	1	thus	thus	ADV
esrj-37073	108	2	,	,	PUNCT
esrj-37073	108	3	the	the	DET
esrj-37073	108	4	input	input	NOUN
esrj-37073	108	5	and	and	CCONJ
esrj-37073	108	6	output	output	NOUN
esrj-37073	108	7	signal	signal	NOUN
esrj-37073	108	8	of	of	ADP
esrj-37073	108	9	the	the	DET
esrj-37073	108	10	kth	kth	PROPN
esrj-37073	108	11	output	output	PROPN
esrj-37073	108	12	neuron	neuron	PROPN
esrj-37073	108	13	were	be	AUX
esrj-37073	108	14	,	,	PUNCT
esrj-37073	108	15	respectively	respectively	ADV
esrj-37073	108	16	:	:	PUNCT
esrj-37073	108	17	where	where	SCONJ
esrj-37073	108	18	kb	kb	PROPN
esrj-37073	108	19	is	be	AUX
esrj-37073	108	20	the	the	DET
esrj-37073	108	21	bias	bias	NOUN
esrj-37073	108	22	and	and	CCONJ
esrj-37073	108	23	n	n	NOUN
esrj-37073	108	24	is	be	AUX
esrj-37073	108	25	the	the	DET
esrj-37073	108	26	total	total	ADJ
esrj-37073	108	27	number	number	NOUN
esrj-37073	108	28	of	of	ADP
esrj-37073	108	29	neurons	neuron	NOUN
esrj-37073	108	30	in	in	ADP
esrj-37073	108	31	the	the	DET
esrj-37073	108	32	hidden	hide	VERB
esrj-37073	108	33	layer	layer	NOUN
esrj-37073	108	34	(	(	PUNCT
esrj-37073	108	35	sahoo	sahoo	PROPN
esrj-37073	108	36	et	et	PROPN
esrj-37073	108	37	al	al	PROPN
esrj-37073	108	38	.	.	PROPN
esrj-37073	108	39	,	,	PUNCT
esrj-37073	108	40	2009	2009	NUM
esrj-37073	108	41	)	)	PUNCT
esrj-37073	108	42	.	.	PUNCT
esrj-37073	109	1	by	by	ADP
esrj-37073	109	2	comparing	compare	VERB
esrj-37073	109	3	the	the	DET
esrj-37073	109	4	estimated	estimate	VERB
esrj-37073	109	5	output	output	NOUN
esrj-37073	109	6	with	with	ADP
esrj-37073	109	7	the	the	DET
esrj-37073	109	8	desired	desire	VERB
esrj-37073	109	9	output	output	NOUN
esrj-37073	109	10	,	,	PUNCT
esrj-37073	109	11	the	the	DET
esrj-37073	109	12	weights	weight	NOUN
esrj-37073	109	13	were	be	AUX
esrj-37073	109	14	adjusted	adjust	VERB
esrj-37073	109	15	with	with	ADP
esrj-37073	109	16	well	well	ADV
esrj-37073	109	17	-	-	PUNCT
esrj-37073	109	18	known	know	VERB
esrj-37073	109	19	error	error	NOUN
esrj-37073	109	20	propagation	propagation	NOUN
esrj-37073	109	21	algorithms	algorithm	NOUN
esrj-37073	109	22	including	include	VERB
esrj-37073	109	23	levenberg	levenberg	PROPN
esrj-37073	109	24	-	-	PUNCT
esrj-37073	109	25	marquardt	marquardt	PROPN
esrj-37073	109	26	(	(	PUNCT
esrj-37073	109	27	lm	lm	PROPN
esrj-37073	109	28	)	)	PUNCT
esrj-37073	109	29	,	,	PUNCT
esrj-37073	109	30	bayesian	bayesian	NOUN
esrj-37073	109	31	regularization	regularization	NOUN
esrj-37073	109	32	(	(	PUNCT
esrj-37073	109	33	br	br	NOUN
esrj-37073	109	34	)	)	PUNCT
esrj-37073	109	35	and	and	CCONJ
esrj-37073	109	36	gradient	gradient	ADJ
esrj-37073	109	37	descent	descent	NOUN
esrj-37073	109	38	with	with	ADP
esrj-37073	109	39	momentum	momentum	NOUN
esrj-37073	109	40	and	and	CCONJ
esrj-37073	109	41	adaptive	adaptive	ADJ
esrj-37073	109	42	learning	learning	NOUN
esrj-37073	109	43	rate	rate	NOUN
esrj-37073	109	44	back	back	ADJ
esrj-37073	109	45	-	-	PUNCT
esrj-37073	109	46	propagation	propagation	NOUN
esrj-37073	109	47	algorithm	algorithm	NOUN
esrj-37073	109	48	(	(	PUNCT
esrj-37073	109	49	gdx	gdx	NOUN
esrj-37073	109	50	)	)	PUNCT
esrj-37073	109	51	.	.	PUNCT
esrj-37073	110	1	in	in	ADP
esrj-37073	110	2	this	this	DET
esrj-37073	110	3	study	study	NOUN
esrj-37073	110	4	,	,	PUNCT
esrj-37073	110	5	we	we	PRON
esrj-37073	110	6	employed	employ	VERB
esrj-37073	110	7	the	the	DET
esrj-37073	110	8	lm	lm	ADJ
esrj-37073	110	9	algorithm	algorithm	NOUN
esrj-37073	110	10	as	as	ADP
esrj-37073	110	11	a	a	DET
esrj-37073	110	12	learning	learning	NOUN
esrj-37073	110	13	algorithm	algorithm	NOUN
esrj-37073	110	14	.	.	PUNCT
esrj-37073	111	1	detailed	detailed	ADJ
esrj-37073	111	2	information	information	NOUN
esrj-37073	111	3	about	about	ADP
esrj-37073	111	4	the	the	DET
esrj-37073	111	5	lm	lm	ADJ
esrj-37073	111	6	algorithm	algorithm	NOUN
esrj-37073	111	7	can	can	AUX
esrj-37073	111	8	be	be	AUX
esrj-37073	111	9	found	find	VERB
esrj-37073	111	10	elsewhere	elsewhere	ADV
esrj-37073	111	11	(	(	PUNCT
esrj-37073	111	12	aqil	aqil	PROPN
esrj-37073	111	13	et	et	PROPN
esrj-37073	111	14	al	al	PROPN
esrj-37073	111	15	.	.	PROPN
esrj-37073	111	16	,	,	PUNCT
esrj-37073	111	17	2007	2007	NUM
esrj-37073	111	18	;	;	PUNCT
esrj-37073	111	19	daliakopoulos	daliakopoulo	NOUN
esrj-37073	111	20	et	et	PROPN
esrj-37073	111	21	al	al	PROPN
esrj-37073	111	22	.	.	PROPN
esrj-37073	111	23	,	,	PUNCT
esrj-37073	111	24	2005	2005	NUM
esrj-37073	111	25	)	)	PUNCT
esrj-37073	111	26	.	.	PUNCT
esrj-37073	112	1	in	in	ADP
esrj-37073	112	2	this	this	DET
esrj-37073	112	3	study	study	NOUN
esrj-37073	112	4	,	,	PUNCT
esrj-37073	112	5	the	the	DET
esrj-37073	112	6	tangent	tangent	NOUN
esrj-37073	112	7	sigmoid	sigmoid	NOUN
esrj-37073	112	8	transfer	transfer	NOUN
esrj-37073	112	9	function	function	NOUN
esrj-37073	112	10	,	,	PUNCT
esrj-37073	112	11	of	of	ADP
esrj-37073	112	12	which	which	PRON
esrj-37073	112	13	the	the	DET
esrj-37073	112	14	validity	validity	NOUN
esrj-37073	112	15	has	have	AUX
esrj-37073	112	16	been	be	AUX
esrj-37073	112	17	proven	prove	VERB
esrj-37073	112	18	in	in	ADP
esrj-37073	112	19	hydrological	hydrological	ADJ
esrj-37073	112	20	applications	application	NOUN
esrj-37073	112	21	,	,	PUNCT
esrj-37073	112	22	was	be	AUX
esrj-37073	112	23	used	use	VERB
esrj-37073	112	24	:	:	PUNCT
esrj-37073	112	25	where	where	SCONJ
esrj-37073	112	26	u	u	NOUN
esrj-37073	112	27	is	be	AUX
esrj-37073	112	28	the	the	DET
esrj-37073	112	29	js	js	ADJ
esrj-37073	112	30	and	and	CCONJ
esrj-37073	112	31	ks	ks	PROPN
esrj-37073	112	32	in	in	ADP
esrj-37073	112	33	the	the	DET
esrj-37073	112	34	hidden	hide	VERB
esrj-37073	112	35	layer	layer	NOUN
esrj-37073	112	36	and	and	CCONJ
esrj-37073	112	37	output	output	NOUN
esrj-37073	112	38	layer	layer	NOUN
esrj-37073	112	39	,	,	PUNCT
esrj-37073	112	40	respectively	respectively	ADV
esrj-37073	112	41	.	.	PUNCT
esrj-37073	113	1	3.3	3.3	NUM
esrj-37073	113	2	.	.	PUNCT
esrj-37073	114	1	performance	performance	NOUN
esrj-37073	114	2	indices	index	NOUN
esrj-37073	114	3	to	to	PART
esrj-37073	114	4	evaluate	evaluate	VERB
esrj-37073	114	5	the	the	DET
esrj-37073	114	6	model	model	NOUN
esrj-37073	114	7	performances	performance	NOUN
esrj-37073	114	8	,	,	PUNCT
esrj-37073	114	9	the	the	DET
esrj-37073	114	10	following	follow	VERB
esrj-37073	114	11	performance	performance	NOUN
esrj-37073	114	12	indices	index	NOUN
esrj-37073	114	13	were	be	AUX
esrj-37073	114	14	used	use	VERB
esrj-37073	114	15	;	;	PUNCT
esrj-37073	114	16	nash	nash	NOUN
esrj-37073	114	17	-	-	PUNCT
esrj-37073	114	18	sutcliffe	sutcliffe	PROPN
esrj-37073	114	19	coefficient	coefficient	NOUN
esrj-37073	114	20	of	of	ADP
esrj-37073	114	21	efficiency	efficiency	NOUN
esrj-37073	114	22	(	(	PUNCT
esrj-37073	114	23	ce	ce	PROPN
esrj-37073	114	24	)	)	PUNCT
esrj-37073	114	25	,	,	PUNCT
esrj-37073	114	26	mean	mean	VERB
esrj-37073	114	27	absolute	absolute	ADJ
esrj-37073	114	28	error	error	NOUN
esrj-37073	114	29	(	(	PUNCT
esrj-37073	114	30	mae	mae	PROPN
esrj-37073	114	31	)	)	PUNCT
esrj-37073	114	32	,	,	PUNCT
esrj-37073	114	33	persistence	persistence	NOUN
esrj-37073	114	34	index	index	NOUN
esrj-37073	114	35	(	(	PUNCT
esrj-37073	114	36	pi	pi	NOUN
esrj-37073	114	37	)	)	PUNCT
esrj-37073	114	38	,	,	PUNCT
esrj-37073	114	39	root	root	NOUN
esrj-37073	114	40	mean	mean	VERB
esrj-37073	114	41	square	square	ADJ
esrj-37073	114	42	error	error	NOUN
esrj-37073	114	43	(	(	PUNCT
esrj-37073	114	44	rmse	rmse	NOUN
esrj-37073	114	45	)	)	PUNCT
esrj-37073	114	46	,	,	PUNCT
esrj-37073	114	47	relative	relative	ADJ
esrj-37073	114	48	volume	volume	NOUN
esrj-37073	114	49	error	error	NOUN
esrj-37073	114	50	(	(	PUNCT
esrj-37073	114	51	rve	rve	PROPN
esrj-37073	114	52	)	)	PUNCT
esrj-37073	114	53	and	and	CCONJ
esrj-37073	114	54	coefficient	coefficient	NOUN
esrj-37073	114	55	of	of	ADP
esrj-37073	114	56	determination	determination	NOUN
esrj-37073	114	57	(	(	PUNCT
esrj-37073	114	58	r2	r2	PROPN
esrj-37073	114	59	)	)	PUNCT
esrj-37073	114	60	.	.	PUNCT
esrj-37073	115	1	nash	nash	PROPN
esrj-37073	115	2	and	and	CCONJ
esrj-37073	115	3	sutcliffe	sutcliffe	PROPN
esrj-37073	115	4	(	(	PUNCT
esrj-37073	115	5	1970	1970	NUM
esrj-37073	115	6	)	)	PUNCT
esrj-37073	115	7	proposed	propose	VERB
esrj-37073	115	8	the	the	DET
esrj-37073	115	9	coefficient	coefficient	NOUN
esrj-37073	115	10	of	of	ADP
esrj-37073	115	11	efficiency	efficiency	NOUN
esrj-37073	115	12	in	in	ADP
esrj-37073	115	13	the	the	DET
esrj-37073	115	14	following	follow	VERB
esrj-37073	115	15	form	form	NOUN
esrj-37073	115	16	:	:	PUNCT
esrj-37073	115	17	where	where	SCONJ
esrj-37073	115	18	io	io	NOUN
esrj-37073	115	19	and	and	CCONJ
esrj-37073	115	20	ip	ip	NOUN
esrj-37073	115	21	are	be	AUX
esrj-37073	115	22	the	the	DET
esrj-37073	115	23	observed	observe	VERB
esrj-37073	115	24	and	and	CCONJ
esrj-37073	115	25	predicted	predict	VERB
esrj-37073	115	26	values	value	NOUN
esrj-37073	115	27	,	,	PUNCT
esrj-37073	115	28	respectively	respectively	ADV
esrj-37073	115	29	,	,	PUNCT
esrj-37073	115	30	and	and	CCONJ
esrj-37073	115	31	o	o	NOUN
esrj-37073	115	32	is	be	AUX
esrj-37073	115	33	the	the	DET
esrj-37073	115	34	mean	mean	ADJ
esrj-37073	115	35	value	value	NOUN
esrj-37073	115	36	of	of	ADP
esrj-37073	115	37	the	the	DET
esrj-37073	115	38	observed	observe	VERB
esrj-37073	115	39	values	value	NOUN
esrj-37073	115	40	.	.	PUNCT
esrj-37073	116	1	mean	mean	VERB
esrj-37073	116	2	absolute	absolute	ADJ
esrj-37073	116	3	error	error	NOUN
esrj-37073	116	4	is	be	AUX
esrj-37073	116	5	a	a	DET
esrj-37073	116	6	measure	measure	NOUN
esrj-37073	116	7	that	that	PRON
esrj-37073	116	8	evaluates	evaluate	VERB
esrj-37073	116	9	the	the	DET
esrj-37073	116	10	absolute	absolute	ADJ
esrj-37073	116	11	deviation	deviation	NOUN
esrj-37073	116	12	of	of	ADP
esrj-37073	116	13	the	the	DET
esrj-37073	116	14	predicted	predict	VERB
esrj-37073	116	15	values	value	NOUN
esrj-37073	116	16	from	from	ADP
esrj-37073	116	17	the	the	DET
esrj-37073	116	18	observed	observe	VERB
esrj-37073	116	19	ones	one	NOUN
esrj-37073	116	20	.	.	PUNCT
esrj-37073	117	1	it	it	PRON
esrj-37073	117	2	is	be	AUX
esrj-37073	117	3	calculated	calculate	VERB
esrj-37073	117	4	as	as	ADP
esrj-37073	117	5	:	:	PUNCT
esrj-37073	117	6	the	the	DET
esrj-37073	117	7	persistence	persistence	NOUN
esrj-37073	117	8	index	index	NOUN
esrj-37073	117	9	(	(	PUNCT
esrj-37073	117	10	pi	pi	NOUN
esrj-37073	117	11	)	)	PUNCT
esrj-37073	117	12	proposed	propose	VERB
esrj-37073	117	13	by	by	ADP
esrj-37073	117	14	kitanidis	kitanidis	PROPN
esrj-37073	117	15	and	and	CCONJ
esrj-37073	117	16	bras	bras	NOUN
esrj-37073	117	17	(	(	PUNCT
esrj-37073	117	18	1980	1980	NUM
esrj-37073	117	19	)	)	PUNCT
esrj-37073	117	20	,	,	PUNCT
esrj-37073	117	21	compares	compare	VERB
esrj-37073	117	22	the	the	DET
esrj-37073	117	23	predictions	prediction	NOUN
esrj-37073	117	24	of	of	ADP
esrj-37073	117	25	a	a	DET
esrj-37073	117	26	model	model	NOUN
esrj-37073	117	27	with	with	ADP
esrj-37073	117	28	the	the	DET
esrj-37073	117	29	best	good	ADJ
esrj-37073	117	30	estimate	estimate	NOUN
esrj-37073	117	31	for	for	ADP
esrj-37073	117	32	the	the	DET
esrj-37073	117	33	future	future	NOUN
esrj-37073	117	34	,	,	PUNCT
esrj-37073	117	35	which	which	PRON
esrj-37073	117	36	is	be	AUX
esrj-37073	117	37	given	give	VERB
esrj-37073	117	38	by	by	ADP
esrj-37073	117	39	the	the	DET
esrj-37073	117	40	last	last	ADJ
esrj-37073	117	41	observation	observation	NOUN
esrj-37073	117	42	(	(	PUNCT
esrj-37073	117	43	randrianasolo	randrianasolo	NOUN
esrj-37073	117	44	et	et	PROPN
esrj-37073	117	45	al	al	PROPN
esrj-37073	117	46	.	.	PROPN
esrj-37073	117	47	,	,	PUNCT
esrj-37073	117	48	2011	2011	NUM
esrj-37073	117	49	)	)	PUNCT
esrj-37073	117	50	.	.	PUNCT
esrj-37073	118	1	the	the	DET
esrj-37073	118	2	index	index	NOUN
esrj-37073	118	3	has	have	VERB
esrj-37073	118	4	the	the	DET
esrj-37073	118	5	following	follow	VERB
esrj-37073	118	6	form	form	NOUN
esrj-37073	118	7	:	:	PUNCT
esrj-37073	118	8	where	where	SCONJ
esrj-37073	118	9	is	be	AUX
esrj-37073	118	10	the	the	DET
esrj-37073	118	11	last	last	ADJ
esrj-37073	118	12	observed	observe	VERB
esrj-37073	118	13	value	value	NOUN
esrj-37073	118	14	at	at	ADP
esrj-37073	118	15	time	time	NOUN
esrj-37073	118	16	i	i	PRON
esrj-37073	118	17	minus	minus	ADP
esrj-37073	118	18	the	the	DET
esrj-37073	118	19	lead	lead	ADJ
esrj-37073	118	20	time	time	NOUN
esrj-37073	118	21	l.	l.	PROPN
esrj-37073	118	22	rmse	rmse	PROPN
esrj-37073	118	23	is	be	AUX
esrj-37073	118	24	one	one	NUM
esrj-37073	118	25	of	of	ADP
esrj-37073	118	26	the	the	DET
esrj-37073	118	27	most	most	ADV
esrj-37073	118	28	widely	widely	ADV
esrj-37073	118	29	used	use	VERB
esrj-37073	118	30	criterions	criterion	NOUN
esrj-37073	118	31	to	to	PART
esrj-37073	118	32	assess	assess	VERB
esrj-37073	118	33	model	model	NOUN
esrj-37073	118	34	efficiency	efficiency	NOUN
esrj-37073	118	35	,	,	PUNCT
esrj-37073	118	36	and	and	CCONJ
esrj-37073	118	37	it	it	PRON
esrj-37073	118	38	evaluates	evaluate	VERB
esrj-37073	118	39	the	the	DET
esrj-37073	118	40	forecast	forecast	NOUN
esrj-37073	118	41	errors	error	NOUN
esrj-37073	118	42	with	with	ADP
esrj-37073	118	43	the	the	DET
esrj-37073	118	44	following	follow	VERB
esrj-37073	118	45	form	form	NOUN
esrj-37073	118	46	:	:	PUNCT
esrj-37073	118	47	because	because	SCONJ
esrj-37073	118	48	this	this	DET
esrj-37073	118	49	criterion	criterion	NOUN
esrj-37073	118	50	is	be	AUX
esrj-37073	118	51	sensitive	sensitive	ADJ
esrj-37073	118	52	to	to	ADP
esrj-37073	118	53	large	large	ADJ
esrj-37073	118	54	forecast	forecast	NOUN
esrj-37073	118	55	errors	error	NOUN
esrj-37073	118	56	(	(	PUNCT
esrj-37073	118	57	i.e.	i.e.	X
esrj-37073	118	58	,	,	PUNCT
esrj-37073	118	59	the	the	DET
esrj-37073	118	60	errors	error	NOUN
esrj-37073	118	61	are	be	AUX
esrj-37073	118	62	amplified	amplify	VERB
esrj-37073	118	63	by	by	ADP
esrj-37073	118	64	squaring	square	VERB
esrj-37073	118	65	)	)	PUNCT
esrj-37073	118	66	,	,	PUNCT
esrj-37073	118	67	it	it	PRON
esrj-37073	118	68	provides	provide	VERB
esrj-37073	118	69	a	a	DET
esrj-37073	118	70	good	good	ADJ
esrj-37073	118	71	measure	measure	NOUN
esrj-37073	118	72	for	for	ADP
esrj-37073	118	73	the	the	DET
esrj-37073	118	74	goodness	goodness	NOUN
esrj-37073	118	75	-	-	PUNCT
esrj-37073	118	76	of	of	ADP
esrj-37073	118	77	-	-	PUNCT
esrj-37073	118	78	fit	fit	NOUN
esrj-37073	118	79	at	at	ADP
esrj-37073	118	80	high	high	ADJ
esrj-37073	118	81	flows	flow	NOUN
esrj-37073	118	82	.	.	PUNCT
esrj-37073	119	1	additionally	additionally	ADV
esrj-37073	119	2	,	,	PUNCT
esrj-37073	119	3	it	it	PRON
esrj-37073	119	4	has	have	VERB
esrj-37073	119	5	the	the	DET
esrj-37073	119	6	same	same	ADJ
esrj-37073	119	7	units	unit	NOUN
esrj-37073	119	8	as	as	ADP
esrj-37073	119	9	the	the	DET
esrj-37073	119	10	observed	observed	ADJ
esrj-37073	119	11	values	value	NOUN
esrj-37073	119	12	;	;	PUNCT
esrj-37073	119	13	thus	thus	ADV
esrj-37073	119	14	,	,	PUNCT
esrj-37073	119	15	it	it	PRON
esrj-37073	119	16	enables	enable	VERB
esrj-37073	119	17	the	the	DET
esrj-37073	119	18	interpretation	interpretation	NOUN
esrj-37073	119	19	of	of	ADP
esrj-37073	119	20	the	the	DET
esrj-37073	119	21	magnitude	magnitude	NOUN
esrj-37073	119	22	of	of	ADP
esrj-37073	119	23	error	error	NOUN
esrj-37073	119	24	.	.	PUNCT
esrj-37073	120	1	the	the	DET
esrj-37073	120	2	rve	rve	PROPN
esrj-37073	120	3	criterion	criterion	NOUN
esrj-37073	120	4	shows	show	VERB
esrj-37073	120	5	the	the	DET
esrj-37073	120	6	total	total	ADJ
esrj-37073	120	7	relative	relative	ADJ
esrj-37073	120	8	error	error	NOUN
esrj-37073	120	9	resulting	result	VERB
esrj-37073	120	10	from	from	ADP
esrj-37073	120	11	the	the	DET
esrj-37073	120	12	model	model	NOUN
esrj-37073	120	13	predictions	prediction	NOUN
esrj-37073	120	14	as	as	ADP
esrj-37073	120	15	:	:	PUNCT
esrj-37073	120	16	r2	r2	PROPN
esrj-37073	120	17	describes	describe	VERB
esrj-37073	120	18	the	the	DET
esrj-37073	120	19	proportion	proportion	NOUN
esrj-37073	120	20	of	of	ADP
esrj-37073	120	21	the	the	DET
esrj-37073	120	22	total	total	ADJ
esrj-37073	120	23	variance	variance	NOUN
esrj-37073	120	24	in	in	ADP
esrj-37073	120	25	the	the	DET
esrj-37073	120	26	observed	observe	VERB
esrj-37073	120	27	data	datum	NOUN
esrj-37073	120	28	that	that	PRON
esrj-37073	120	29	can	can	AUX
esrj-37073	120	30	be	be	AUX
esrj-37073	120	31	explained	explain	VERB
esrj-37073	120	32	by	by	ADP
esrj-37073	120	33	the	the	DET
esrj-37073	120	34	model	model	NOUN
esrj-37073	120	35	and	and	CCONJ
esrj-37073	120	36	is	be	AUX
esrj-37073	120	37	formulated	formulate	VERB
esrj-37073	120	38	as	as	ADP
esrj-37073	120	39	below	below	ADV
esrj-37073	120	40	:	:	PUNCT
esrj-37073	120	41	r2	r2	NOUN
esrj-37073	120	42	changes	change	NOUN
esrj-37073	120	43	between	between	ADP
esrj-37073	120	44	0	0	NUM
esrj-37073	120	45	(	(	PUNCT
esrj-37073	120	46	no	no	DET
esrj-37073	120	47	relation	relation	NOUN
esrj-37073	120	48	)	)	PUNCT
esrj-37073	120	49	and	and	CCONJ
esrj-37073	120	50	1	1	NUM
esrj-37073	120	51	(	(	PUNCT
esrj-37073	120	52	perfect	perfect	ADJ
esrj-37073	120	53	fit	fit	NOUN
esrj-37073	120	54	)	)	PUNCT
esrj-37073	120	55	,	,	PUNCT
esrj-37073	120	56	which	which	PRON
esrj-37073	120	57	describes	describe	VERB
esrj-37073	120	58	how	how	SCONJ
esrj-37073	120	59	much	much	ADJ
esrj-37073	120	60	of	of	ADP
esrj-37073	120	61	the	the	DET
esrj-37073	120	62	observed	observed	ADJ
esrj-37073	120	63	dispersion	dispersion	NOUN
esrj-37073	120	64	is	be	AUX
esrj-37073	120	65	explained	explain	VERB
esrj-37073	120	66	by	by	ADP
esrj-37073	120	67	the	the	DET
esrj-37073	120	68	model	model	NOUN
esrj-37073	120	69	.	.	PUNCT
esrj-37073	121	1	4	4	X
esrj-37073	121	2	.	.	NOUN
esrj-37073	121	3	results	result	NOUN
esrj-37073	121	4	and	and	CCONJ
esrj-37073	121	5	discussion	discussion	NOUN
esrj-37073	121	6	to	to	PART
esrj-37073	121	7	determine	determine	VERB
esrj-37073	121	8	the	the	DET
esrj-37073	121	9	chaotic	chaotic	ADJ
esrj-37073	121	10	dynamics	dynamic	NOUN
esrj-37073	121	11	within	within	ADP
esrj-37073	121	12	the	the	DET
esrj-37073	121	13	stream	stream	NOUN
esrj-37073	121	14	flows	flow	VERB
esrj-37073	121	15	,	,	PUNCT
esrj-37073	121	16	the	the	DET
esrj-37073	121	17	correlation	correlation	NOUN
esrj-37073	121	18	dimension	dimension	NOUN
esrj-37073	121	19	method	method	NOUN
esrj-37073	121	20	was	be	AUX
esrj-37073	121	21	applied	apply	VERB
esrj-37073	121	22	.	.	PUNCT
esrj-37073	122	1	to	to	PART
esrj-37073	122	2	calculate	calculate	VERB
esrj-37073	122	3	the	the	DET
esrj-37073	122	4	correlation	correlation	NOUN
esrj-37073	122	5	integrals	integral	NOUN
esrj-37073	122	6	,	,	PUNCT
esrj-37073	122	7	the	the	DET
esrj-37073	122	8	delay	delay	NOUN
esrj-37073	122	9	time	time	NOUN
esrj-37073	122	10	(	(	PUNCT
esrj-37073	122	11	)	)	PUNCT
esrj-37073	122	12	was	be	AUX
esrj-37073	122	13	computed	compute	VERB
esrj-37073	122	14	using	use	VERB
esrj-37073	122	15	the	the	DET
esrj-37073	122	16	mutual	mutual	ADJ
esrj-37073	122	17	information	information	NOUN
esrj-37073	122	18	function	function	NOUN
esrj-37073	122	19	and	and	CCONJ
esrj-37073	122	20	its	its	PRON
esrj-37073	122	21	relative	relative	ADJ
esrj-37073	122	22	change	change	NOUN
esrj-37073	122	23	with	with	ADP
esrj-37073	122	24	lag	lag	NOUN
esrj-37073	122	25	time	time	NOUN
esrj-37073	122	26	(	(	PUNCT
esrj-37073	122	27	figure	figure	NOUN
esrj-37073	122	28	3	3	NUM
esrj-37073	122	29	)	)	PUNCT
esrj-37073	122	30	.	.	PUNCT
esrj-37073	123	1	figure	figure	VERB
esrj-37073	123	2	3	3	NUM
esrj-37073	123	3	.	.	PUNCT
esrj-37073	123	4	mutual	mutual	ADJ
esrj-37073	123	5	information	information	NOUN
esrj-37073	123	6	function	function	NOUN
esrj-37073	123	7	and	and	CCONJ
esrj-37073	123	8	its	its	PRON
esrj-37073	123	9	relative	relative	ADJ
esrj-37073	123	10	change	change	NOUN
esrj-37073	123	11	with	with	ADP
esrj-37073	123	12	lag	lag	PROPN
esrj-37073	123	13	hakan	hakan	PROPN
esrj-37073	123	14	tongal	tongal	PROPN
esrj-37073	123	15	(	(	PUNCT
esrj-37073	123	16	9	9	NUM
esrj-37073	123	17	)	)	PUNCT
esrj-37073	123	18	(	(	PUNCT
esrj-37073	123	19	10	10	NUM
esrj-37073	123	20	)	)	PUNCT
esrj-37073	123	21	(	(	PUNCT
esrj-37073	123	22	11	11	NUM
esrj-37073	123	23	)	)	PUNCT
esrj-37073	123	24	(	(	PUNCT
esrj-37073	123	25	12	12	NUM
esrj-37073	123	26	)	)	PUNCT
esrj-37073	123	27	(	(	PUNCT
esrj-37073	123	28	13	13	NUM
esrj-37073	123	29	)	)	PUNCT
esrj-37073	123	30	(	(	PUNCT
esrj-37073	123	31	14	14	NUM
esrj-37073	123	32	)	)	PUNCT
esrj-37073	123	33	(	(	PUNCT
esrj-37073	123	34	15	15	NUM
esrj-37073	123	35	)	)	PUNCT
esrj-37073	123	36	(	(	PUNCT
esrj-37073	123	37	16	16	NUM
esrj-37073	123	38	)	)	PUNCT
esrj-37073	123	39	(	(	PUNCT
esrj-37073	123	40	17	17	NUM
esrj-37073	123	41	)	)	PUNCT
esrj-37073	123	42	123	123	NUM
esrj-37073	123	43	in	in	ADP
esrj-37073	123	44	figure	figure	NOUN
esrj-37073	123	45	3	3	NUM
esrj-37073	123	46	,	,	PUNCT
esrj-37073	123	47	it	it	PRON
esrj-37073	123	48	was	be	AUX
esrj-37073	123	49	difficult	difficult	ADJ
esrj-37073	123	50	to	to	PART
esrj-37073	123	51	select	select	VERB
esrj-37073	123	52	the	the	DET
esrj-37073	123	53	first	first	ADJ
esrj-37073	123	54	local	local	ADJ
esrj-37073	123	55	minimum	minimum	NOUN
esrj-37073	123	56	from	from	ADP
esrj-37073	123	57	the	the	DET
esrj-37073	123	58	original	original	ADJ
esrj-37073	123	59	mi	mi	NOUN
esrj-37073	123	60	function	function	NOUN
esrj-37073	123	61	.	.	PUNCT
esrj-37073	124	1	the	the	DET
esrj-37073	124	2	amplified	amplified	ADJ
esrj-37073	124	3	differences	difference	NOUN
esrj-37073	124	4	(	(	PUNCT
esrj-37073	124	5	i.e.	i.e.	X
esrj-37073	124	6	,	,	PUNCT
esrj-37073	124	7	the	the	DET
esrj-37073	124	8	relative	relative	ADJ
esrj-37073	124	9	change	change	NOUN
esrj-37073	124	10	of	of	ADP
esrj-37073	124	11	the	the	DET
esrj-37073	124	12	mi	mi	PROPN
esrj-37073	124	13	)	)	PUNCT
esrj-37073	124	14	between	between	ADP
esrj-37073	124	15	the	the	DET
esrj-37073	124	16	successive	successive	ADJ
esrj-37073	124	17	values	value	NOUN
esrj-37073	124	18	were	be	AUX
esrj-37073	124	19	more	more	ADV
esrj-37073	124	20	informative	informative	ADJ
esrj-37073	124	21	about	about	ADP
esrj-37073	124	22	where	where	SCONJ
esrj-37073	124	23	the	the	DET
esrj-37073	124	24	first	first	ADJ
esrj-37073	124	25	local	local	ADJ
esrj-37073	124	26	minimum	minimum	NOUN
esrj-37073	124	27	could	could	AUX
esrj-37073	124	28	be	be	AUX
esrj-37073	124	29	found	find	VERB
esrj-37073	124	30	.	.	PUNCT
esrj-37073	125	1	in	in	ADP
esrj-37073	125	2	the	the	DET
esrj-37073	125	3	mi	mi	PROPN
esrj-37073	125	4	relative	relative	PROPN
esrj-37073	125	5	change	change	PROPN
esrj-37073	125	6	,	,	PUNCT
esrj-37073	125	7	the	the	DET
esrj-37073	125	8	mutual	mutual	ADJ
esrj-37073	125	9	information	information	NOUN
esrj-37073	125	10	function	function	NOUN
esrj-37073	125	11	was	be	AUX
esrj-37073	125	12	stable	stable	ADJ
esrj-37073	125	13	and	and	CCONJ
esrj-37073	125	14	fluctuated	fluctuate	VERB
esrj-37073	125	15	around	around	ADP
esrj-37073	125	16	a	a	DET
esrj-37073	125	17	constant	constant	ADJ
esrj-37073	125	18	value	value	NOUN
esrj-37073	125	19	after	after	ADP
esrj-37073	125	20	30	30	NUM
esrj-37073	125	21	days	day	NOUN
esrj-37073	125	22	.	.	PUNCT
esrj-37073	126	1	by	by	ADP
esrj-37073	126	2	determining	determine	VERB
esrj-37073	126	3	the	the	DET
esrj-37073	126	4	delay	delay	NOUN
esrj-37073	126	5	value	value	NOUN
esrj-37073	126	6	,	,	PUNCT
esrj-37073	126	7	the	the	DET
esrj-37073	126	8	correlation	correlation	NOUN
esrj-37073	126	9	integrals	integral	NOUN
esrj-37073	126	10	were	be	AUX
esrj-37073	126	11	computed	compute	VERB
esrj-37073	126	12	by	by	ADP
esrj-37073	126	13	the	the	DET
esrj-37073	126	14	grassberger	grassberger	NOUN
esrj-37073	126	15	-	-	PUNCT
esrj-37073	126	16	procaccia	procaccia	NOUN
esrj-37073	126	17	algorithm	algorithm	NOUN
esrj-37073	126	18	for	for	ADP
esrj-37073	126	19	different	different	ADJ
esrj-37073	126	20	embedding	embed	VERB
esrj-37073	126	21	dimensions	dimension	NOUN
esrj-37073	126	22	(	(	PUNCT
esrj-37073	126	23	m	m	NOUN
esrj-37073	126	24	)	)	PUNCT
esrj-37073	126	25	from	from	ADP
esrj-37073	126	26	1	1	NUM
esrj-37073	126	27	m	m	NOUN
esrj-37073	126	28	=	=	PUNCT
esrj-37073	126	29	to	to	ADP
esrj-37073	126	30	25	25	NUM
esrj-37073	126	31	m	m	NOUN
esrj-37073	126	32	=	=	PUNCT
esrj-37073	126	33	(	(	PUNCT
esrj-37073	126	34	figure	figure	NOUN
esrj-37073	126	35	4a	4a	NUM
esrj-37073	126	36	)	)	PUNCT
esrj-37073	126	37	.	.	PUNCT
esrj-37073	127	1	(	(	PUNCT
esrj-37073	127	2	a	a	X
esrj-37073	127	3	)	)	PUNCT
esrj-37073	127	4	(	(	PUNCT
esrj-37073	127	5	b	b	X
esrj-37073	127	6	)	)	PUNCT
esrj-37073	127	7	figure	figure	NOUN
esrj-37073	127	8	4	4	NUM
esrj-37073	127	9	.	.	PUNCT
esrj-37073	128	1	(	(	PUNCT
esrj-37073	128	2	a	a	X
esrj-37073	128	3	)	)	PUNCT
esrj-37073	128	4	correlation	correlation	NOUN
esrj-37073	128	5	integrals	integral	NOUN
esrj-37073	128	6	as	as	ADP
esrj-37073	128	7	a	a	DET
esrj-37073	128	8	function	function	NOUN
esrj-37073	128	9	of	of	ADP
esrj-37073	128	10	different	different	ADJ
esrj-37073	128	11	embedding	embed	VERB
esrj-37073	128	12	dimensions	dimension	NOUN
esrj-37073	128	13	(	(	PUNCT
esrj-37073	128	14	m	m	NOUN
esrj-37073	128	15	)	)	PUNCT
esrj-37073	128	16	(	(	PUNCT
esrj-37073	128	17	b	b	X
esrj-37073	128	18	)	)	PUNCT
esrj-37073	128	19	correlation	correlation	NOUN
esrj-37073	128	20	exponents	exponent	NOUN
esrj-37073	128	21	obtained	obtain	VERB
esrj-37073	128	22	from	from	ADP
esrj-37073	128	23	correlation	correlation	NOUN
esrj-37073	128	24	integrals	integral	NOUN
esrj-37073	128	25	as	as	ADP
esrj-37073	128	26	a	a	DET
esrj-37073	128	27	function	function	NOUN
esrj-37073	128	28	of	of	ADP
esrj-37073	128	29	embedding	embed	VERB
esrj-37073	128	30	dimensions	dimension	NOUN
esrj-37073	128	31	from	from	ADP
esrj-37073	128	32	the	the	DET
esrj-37073	128	33	scaling	scaling	ADJ
esrj-37073	128	34	regions	region	NOUN
esrj-37073	128	35	(	(	PUNCT
esrj-37073	128	36	i.e.	i.e.	X
esrj-37073	128	37	,	,	PUNCT
esrj-37073	128	38	nearly	nearly	ADV
esrj-37073	128	39	linear	linear	ADJ
esrj-37073	128	40	sections	section	NOUN
esrj-37073	128	41	of	of	ADP
esrj-37073	128	42	each	each	DET
esrj-37073	128	43	integral	integral	ADJ
esrj-37073	128	44	plots	plot	NOUN
esrj-37073	128	45	)	)	PUNCT
esrj-37073	128	46	of	of	ADP
esrj-37073	128	47	the	the	DET
esrj-37073	128	48	calculated	calculate	VERB
esrj-37073	128	49	correlation	correlation	NOUN
esrj-37073	128	50	integrals	integral	NOUN
esrj-37073	128	51	,	,	PUNCT
esrj-37073	128	52	the	the	DET
esrj-37073	128	53	correlation	correlation	NOUN
esrj-37073	128	54	exponents	exponent	NOUN
esrj-37073	128	55	were	be	AUX
esrj-37073	128	56	calculated	calculate	VERB
esrj-37073	128	57	with	with	ADP
esrj-37073	128	58	the	the	DET
esrj-37073	128	59	least	least	ADJ
esrj-37073	128	60	squares	square	NOUN
esrj-37073	128	61	estimation	estimation	NOUN
esrj-37073	128	62	method	method	NOUN
esrj-37073	128	63	and	and	CCONJ
esrj-37073	128	64	each	each	DET
esrj-37073	128	65	calculated	calculate	VERB
esrj-37073	128	66	correlation	correlation	NOUN
esrj-37073	128	67	exponent	exponent	NOUN
esrj-37073	128	68	was	be	AUX
esrj-37073	128	69	plotted	plot	VERB
esrj-37073	128	70	against	against	ADP
esrj-37073	128	71	its	its	PRON
esrj-37073	128	72	embedding	embed	VERB
esrj-37073	128	73	dimension	dimension	NOUN
esrj-37073	128	74	as	as	SCONJ
esrj-37073	128	75	seen	see	VERB
esrj-37073	128	76	in	in	ADP
esrj-37073	128	77	figure	figure	NOUN
esrj-37073	128	78	4b	4b	PROPN
esrj-37073	128	79	.	.	PUNCT
esrj-37073	129	1	because	because	SCONJ
esrj-37073	129	2	the	the	DET
esrj-37073	129	3	correlation	correlation	NOUN
esrj-37073	129	4	exponent	exponent	NOUN
esrj-37073	129	5	values	value	NOUN
esrj-37073	129	6	increased	increase	VERB
esrj-37073	129	7	with	with	ADP
esrj-37073	129	8	the	the	DET
esrj-37073	129	9	embedding	embed	VERB
esrj-37073	129	10	dimension	dimension	NOUN
esrj-37073	129	11	up	up	ADP
esrj-37073	129	12	to	to	ADP
esrj-37073	129	13	a	a	DET
esrj-37073	129	14	certain	certain	ADJ
esrj-37073	129	15	value	value	NOUN
esrj-37073	129	16	(	(	PUNCT
esrj-37073	129	17	i.e.	i.e.	X
esrj-37073	129	18	2.702d	2.702d	NOUN
esrj-37073	129	19	=	=	PUNCT
esrj-37073	129	20	)	)	PUNCT
esrj-37073	129	21	and	and	CCONJ
esrj-37073	129	22	then	then	ADV
esrj-37073	129	23	fluctuated	fluctuate	VERB
esrj-37073	129	24	around	around	ADP
esrj-37073	129	25	this	this	DET
esrj-37073	129	26	value	value	NOUN
esrj-37073	129	27	,	,	PUNCT
esrj-37073	129	28	chaotic	chaotic	ADJ
esrj-37073	129	29	behavior	behavior	NOUN
esrj-37073	129	30	was	be	AUX
esrj-37073	129	31	indicated	indicate	VERB
esrj-37073	129	32	.	.	PUNCT
esrj-37073	130	1	this	this	DET
esrj-37073	130	2	value	value	NOUN
esrj-37073	130	3	was	be	AUX
esrj-37073	130	4	the	the	DET
esrj-37073	130	5	correlation	correlation	NOUN
esrj-37073	130	6	dimension	dimension	NOUN
esrj-37073	130	7	calculated	calculate	VERB
esrj-37073	130	8	for	for	ADP
esrj-37073	130	9	the	the	DET
esrj-37073	130	10	kızılırmak	kızılırmak	PROPN
esrj-37073	130	11	river	river	PROPN
esrj-37073	130	12	and	and	CCONJ
esrj-37073	130	13	the	the	DET
esrj-37073	130	14	nearest	near	ADJ
esrj-37073	130	15	integer	integer	NOUN
esrj-37073	130	16	above	above	ADP
esrj-37073	130	17	this	this	DET
esrj-37073	130	18	value	value	NOUN
esrj-37073	130	19	provided	provide	VERB
esrj-37073	130	20	the	the	DET
esrj-37073	130	21	minimum	minimum	NOUN
esrj-37073	130	22	embedding	embed	VERB
esrj-37073	130	23	dimension	dimension	NOUN
esrj-37073	130	24	for	for	ADP
esrj-37073	130	25	reconstructing	reconstruct	VERB
esrj-37073	130	26	the	the	DET
esrj-37073	130	27	phase	phase	NOUN
esrj-37073	130	28	-	-	PUNCT
esrj-37073	130	29	space	space	NOUN
esrj-37073	130	30	or	or	CCONJ
esrj-37073	130	31	the	the	DET
esrj-37073	130	32	number	number	NOUN
esrj-37073	130	33	of	of	ADP
esrj-37073	130	34	variables	variable	NOUN
esrj-37073	130	35	(	(	PUNCT
esrj-37073	130	36	i.e.	i.e.	X
esrj-37073	130	37	,	,	PUNCT
esrj-37073	130	38	the	the	DET
esrj-37073	130	39	number	number	NOUN
esrj-37073	130	40	of	of	ADP
esrj-37073	130	41	dominant	dominant	ADJ
esrj-37073	130	42	variables	variable	NOUN
esrj-37073	130	43	)	)	PUNCT
esrj-37073	130	44	necessary	necessary	ADJ
esrj-37073	130	45	to	to	PART
esrj-37073	130	46	model	model	VERB
esrj-37073	130	47	the	the	DET
esrj-37073	130	48	dynamics	dynamic	NOUN
esrj-37073	130	49	of	of	ADP
esrj-37073	130	50	the	the	DET
esrj-37073	130	51	system	system	NOUN
esrj-37073	130	52	(	(	PUNCT
esrj-37073	130	53	khokhlov	khokhlov	NOUN
esrj-37073	130	54	et	et	PROPN
esrj-37073	130	55	al	al	PROPN
esrj-37073	130	56	.	.	PROPN
esrj-37073	130	57	,	,	PUNCT
esrj-37073	130	58	2008	2008	NUM
esrj-37073	130	59	;	;	PUNCT
esrj-37073	130	60	sivakumar	sivakumar	PROPN
esrj-37073	130	61	and	and	CCONJ
esrj-37073	130	62	jayawardena	jayawardena	PROPN
esrj-37073	130	63	,	,	PUNCT
esrj-37073	130	64	2002	2002	NUM
esrj-37073	130	65	;	;	PUNCT
esrj-37073	130	66	stehlik	stehlik	PROPN
esrj-37073	130	67	,	,	PUNCT
esrj-37073	130	68	1999	1999	NUM
esrj-37073	130	69	)	)	PUNCT
esrj-37073	130	70	.	.	PUNCT
esrj-37073	131	1	thus	thus	ADV
esrj-37073	131	2	,	,	PUNCT
esrj-37073	131	3	the	the	DET
esrj-37073	131	4	results	result	NOUN
esrj-37073	131	5	from	from	ADP
esrj-37073	131	6	these	these	DET
esrj-37073	131	7	analyses	analysis	NOUN
esrj-37073	131	8	showed	show	VERB
esrj-37073	131	9	that	that	SCONJ
esrj-37073	131	10	the	the	DET
esrj-37073	131	11	required	require	VERB
esrj-37073	131	12	minimum	minimum	ADJ
esrj-37073	131	13	number	number	NOUN
esrj-37073	131	14	of	of	ADP
esrj-37073	131	15	variables	variable	NOUN
esrj-37073	131	16	to	to	PART
esrj-37073	131	17	model	model	VERB
esrj-37073	131	18	the	the	DET
esrj-37073	131	19	system	system	NOUN
esrj-37073	131	20	dynamics	dynamic	NOUN
esrj-37073	131	21	was	be	AUX
esrj-37073	131	22	3	3	NUM
esrj-37073	131	23	(	(	PUNCT
esrj-37073	131	24	3	3	NUM
esrj-37073	131	25	2.702	2.702	NUM
esrj-37073	131	26	>	>	X
esrj-37073	131	27	)	)	PUNCT
esrj-37073	131	28	and	and	CCONJ
esrj-37073	131	29	the	the	DET
esrj-37073	131	30	maximum	maximum	ADJ
esrj-37073	131	31	number	number	NOUN
esrj-37073	131	32	of	of	ADP
esrj-37073	131	33	variables	variable	NOUN
esrj-37073	131	34	to	to	PART
esrj-37073	131	35	model	model	VERB
esrj-37073	131	36	the	the	DET
esrj-37073	131	37	system	system	NOUN
esrj-37073	131	38	dynamics	dynamic	NOUN
esrj-37073	131	39	was	be	AUX
esrj-37073	131	40	7	7	NUM
esrj-37073	131	41	(	(	PUNCT
esrj-37073	131	42	)	)	PUNCT
esrj-37073	131	43	.	.	PUNCT
esrj-37073	132	1	in	in	ADP
esrj-37073	132	2	the	the	DET
esrj-37073	132	3	k	k	PROPN
esrj-37073	132	4	-	-	PUNCT
esrj-37073	132	5	nn	nn	PROPN
esrj-37073	132	6	model	model	PROPN
esrj-37073	132	7	development	development	NOUN
esrj-37073	132	8	,	,	PUNCT
esrj-37073	132	9	the	the	DET
esrj-37073	132	10	embedding	embed	VERB
esrj-37073	132	11	dimension	dimension	NOUN
esrj-37073	132	12	was	be	AUX
esrj-37073	132	13	taken	take	VERB
esrj-37073	132	14	as	as	ADP
esrj-37073	132	15	3	3	NUM
esrj-37073	132	16	by	by	ADP
esrj-37073	132	17	considering	consider	VERB
esrj-37073	132	18	the	the	DET
esrj-37073	132	19	required	require	VERB
esrj-37073	132	20	minimum	minimum	NOUN
esrj-37073	132	21	embedding	embed	VERB
esrj-37073	132	22	dimension	dimension	NOUN
esrj-37073	132	23	obtained	obtain	VERB
esrj-37073	132	24	from	from	ADP
esrj-37073	132	25	the	the	DET
esrj-37073	132	26	above	above	ADJ
esrj-37073	132	27	analysis	analysis	NOUN
esrj-37073	132	28	.	.	PUNCT
esrj-37073	133	1	the	the	DET
esrj-37073	133	2	required	require	VERB
esrj-37073	133	3	nearest	near	ADJ
esrj-37073	133	4	neighbor	neighbor	NOUN
esrj-37073	133	5	numbers	number	NOUN
esrj-37073	133	6	for	for	ADP
esrj-37073	133	7	k	k	PROPN
esrj-37073	133	8	-	-	PUNCT
esrj-37073	133	9	nn	nn	ADJ
esrj-37073	133	10	analysis	analysis	NOUN
esrj-37073	133	11	was	be	AUX
esrj-37073	133	12	determined	determine	VERB
esrj-37073	133	13	with	with	ADP
esrj-37073	133	14	a	a	DET
esrj-37073	133	15	trial	trial	NOUN
esrj-37073	133	16	and	and	CCONJ
esrj-37073	133	17	error	error	NOUN
esrj-37073	133	18	process	process	NOUN
esrj-37073	133	19	that	that	PRON
esrj-37073	133	20	minimized	minimize	VERB
esrj-37073	133	21	rmse	rmse	NOUN
esrj-37073	133	22	as	as	ADP
esrj-37073	133	23	a	a	DET
esrj-37073	133	24	function	function	NOUN
esrj-37073	133	25	of	of	ADP
esrj-37073	133	26	nearest	near	ADJ
esrj-37073	133	27	neighbor	neighbor	ADJ
esrj-37073	133	28	number	number	NOUN
esrj-37073	133	29	.	.	PUNCT
esrj-37073	134	1	figure	figure	NOUN
esrj-37073	134	2	5	5	NUM
esrj-37073	134	3	shows	show	VERB
esrj-37073	134	4	that	that	SCONJ
esrj-37073	134	5	the	the	DET
esrj-37073	134	6	rmse	rmse	NOUN
esrj-37073	134	7	decreased	decrease	VERB
esrj-37073	134	8	as	as	ADP
esrj-37073	134	9	a	a	DET
esrj-37073	134	10	function	function	NOUN
esrj-37073	134	11	of	of	ADP
esrj-37073	134	12	nearest	near	ADJ
esrj-37073	134	13	neighbor	neighbor	NOUN
esrj-37073	134	14	number	number	NOUN
esrj-37073	134	15	until	until	SCONJ
esrj-37073	134	16	nearest	near	ADJ
esrj-37073	134	17	neighbor	neighbor	NOUN
esrj-37073	134	18	number	number	NOUN
esrj-37073	134	19	equaled	equal	VERB
esrj-37073	134	20	33	33	NUM
esrj-37073	134	21	days	day	NOUN
esrj-37073	134	22	and	and	CCONJ
esrj-37073	134	23	after	after	ADP
esrj-37073	134	24	this	this	DET
esrj-37073	134	25	value	value	NOUN
esrj-37073	134	26	,	,	PUNCT
esrj-37073	134	27	rmse	rmse	PROPN
esrj-37073	134	28	started	start	VERB
esrj-37073	134	29	to	to	PART
esrj-37073	134	30	increase	increase	VERB
esrj-37073	134	31	.	.	PUNCT
esrj-37073	135	1	therefore	therefore	ADV
esrj-37073	135	2	,	,	PUNCT
esrj-37073	135	3	the	the	DET
esrj-37073	135	4	optimal	optimal	ADJ
esrj-37073	135	5	nearest	near	ADJ
esrj-37073	135	6	neighbor	neighbor	NOUN
esrj-37073	135	7	number	number	NOUN
esrj-37073	135	8	was	be	AUX
esrj-37073	135	9	selected	select	VERB
esrj-37073	135	10	as	as	ADP
esrj-37073	135	11	33	33	NUM
esrj-37073	135	12	days	day	NOUN
esrj-37073	135	13	.	.	PUNCT
esrj-37073	136	1	figure	figure	NOUN
esrj-37073	136	2	5	5	NUM
esrj-37073	136	3	.	.	PUNCT
esrj-37073	137	1	determination	determination	NOUN
esrj-37073	137	2	of	of	ADP
esrj-37073	137	3	the	the	DET
esrj-37073	137	4	nearest	near	ADJ
esrj-37073	137	5	neighbor	neighbor	NOUN
esrj-37073	137	6	number	number	NOUN
esrj-37073	137	7	as	as	ADP
esrj-37073	137	8	a	a	DET
esrj-37073	137	9	function	function	NOUN
esrj-37073	137	10	of	of	ADP
esrj-37073	137	11	rmse	rmse	ADJ
esrj-37073	137	12	criterion	criterion	NOUN
esrj-37073	137	13	with	with	ADP
esrj-37073	137	14	these	these	DET
esrj-37073	137	15	results	result	NOUN
esrj-37073	137	16	,	,	PUNCT
esrj-37073	137	17	the	the	DET
esrj-37073	137	18	required	require	VERB
esrj-37073	137	19	parameters	parameter	NOUN
esrj-37073	137	20	for	for	ADP
esrj-37073	137	21	the	the	DET
esrj-37073	137	22	k	k	PROPN
esrj-37073	137	23	-	-	PUNCT
esrj-37073	137	24	nn	nn	ADJ
esrj-37073	137	25	model	model	NOUN
esrj-37073	137	26	were	be	AUX
esrj-37073	137	27	obtained	obtain	VERB
esrj-37073	137	28	.	.	PUNCT
esrj-37073	138	1	to	to	PART
esrj-37073	138	2	determine	determine	VERB
esrj-37073	138	3	whether	whether	SCONJ
esrj-37073	138	4	the	the	DET
esrj-37073	138	5	obtained	obtain	VERB
esrj-37073	138	6	correlation	correlation	NOUN
esrj-37073	138	7	dimension	dimension	NOUN
esrj-37073	138	8	could	could	AUX
esrj-37073	138	9	be	be	AUX
esrj-37073	138	10	used	use	VERB
esrj-37073	138	11	as	as	ADP
esrj-37073	138	12	the	the	DET
esrj-37073	138	13	lag	lag	NOUN
esrj-37073	138	14	value	value	NOUN
esrj-37073	138	15	for	for	ADP
esrj-37073	138	16	the	the	DET
esrj-37073	138	17	discharges	discharge	NOUN
esrj-37073	138	18	,	,	PUNCT
esrj-37073	138	19	the	the	DET
esrj-37073	138	20	following	follow	VERB
esrj-37073	138	21	model	model	NOUN
esrj-37073	138	22	structures	structure	NOUN
esrj-37073	138	23	were	be	AUX
esrj-37073	138	24	built	build	VERB
esrj-37073	138	25	.	.	PUNCT
esrj-37073	139	1	to	to	ADP
esrj-37073	139	2	the	the	DET
esrj-37073	139	3	author	author	NOUN
esrj-37073	139	4	’	'	PUNCT
esrj-37073	139	5	knowledge	knowledge	NOUN
esrj-37073	139	6	,	,	PUNCT
esrj-37073	139	7	this	this	DET
esrj-37073	139	8	study	study	NOUN
esrj-37073	139	9	was	be	AUX
esrj-37073	139	10	the	the	DET
esrj-37073	139	11	first	first	ADJ
esrj-37073	139	12	to	to	PART
esrj-37073	139	13	take	take	VERB
esrj-37073	139	14	the	the	DET
esrj-37073	139	15	correlation	correlation	NOUN
esrj-37073	139	16	dimension	dimension	NOUN
esrj-37073	139	17	as	as	ADP
esrj-37073	139	18	the	the	PRON
esrj-37073	139	19	of	of	ADP
esrj-37073	139	20	required	require	VERB
esrj-37073	139	21	lag	lag	NOUN
esrj-37073	139	22	value	value	NOUN
esrj-37073	139	23	for	for	ADP
esrj-37073	139	24	the	the	DET
esrj-37073	139	25	discharges	discharge	NOUN
esrj-37073	139	26	.	.	PUNCT
esrj-37073	140	1	by	by	ADP
esrj-37073	140	2	considering	consider	VERB
esrj-37073	140	3	the	the	DET
esrj-37073	140	4	correlation	correlation	NOUN
esrj-37073	140	5	dimension	dimension	NOUN
esrj-37073	140	6	value	value	NOUN
esrj-37073	140	7	as	as	ADP
esrj-37073	140	8	the	the	DET
esrj-37073	140	9	required	required	ADJ
esrj-37073	140	10	number	number	NOUN
esrj-37073	140	11	of	of	ADP
esrj-37073	140	12	variables	variable	NOUN
esrj-37073	140	13	that	that	PRON
esrj-37073	140	14	characterize	characterize	VERB
esrj-37073	140	15	the	the	DET
esrj-37073	140	16	system	system	NOUN
esrj-37073	140	17	,	,	PUNCT
esrj-37073	140	18	the	the	DET
esrj-37073	140	19	following	follow	VERB
esrj-37073	140	20	ffnn	ffnn	NOUN
esrj-37073	140	21	model	model	NOUN
esrj-37073	140	22	structures	structure	NOUN
esrj-37073	140	23	were	be	AUX
esrj-37073	140	24	constructed	construct	VERB
esrj-37073	140	25	that	that	PRON
esrj-37073	140	26	incorporate	incorporate	VERB
esrj-37073	140	27	a	a	DET
esrj-37073	140	28	minimum	minimum	NOUN
esrj-37073	140	29	of	of	ADP
esrj-37073	140	30	3	3	NUM
esrj-37073	140	31	(	(	PUNCT
esrj-37073	140	32	3	3	NUM
esrj-37073	140	33	2.702	2.702	NUM
esrj-37073	140	34	>	>	X
esrj-37073	140	35	)	)	PUNCT
esrj-37073	140	36	and	and	CCONJ
esrj-37073	140	37	maximum	maximum	NOUN
esrj-37073	140	38	of	of	ADP
esrj-37073	140	39	7	7	NUM
esrj-37073	140	40	(	(	PUNCT
esrj-37073	140	41	)	)	PUNCT
esrj-37073	140	42	lagged	lag	VERB
esrj-37073	140	43	values	value	NOUN
esrj-37073	140	44	.	.	PUNCT
esrj-37073	141	1	typically	typically	ADV
esrj-37073	141	2	,	,	PUNCT
esrj-37073	141	3	the	the	DET
esrj-37073	141	4	training	training	NOUN
esrj-37073	141	5	data	datum	NOUN
esrj-37073	141	6	set	set	VERB
esrj-37073	141	7	is	be	AUX
esrj-37073	141	8	selected	select	VERB
esrj-37073	141	9	as	as	ADP
esrj-37073	141	10	70%-80	70%-80	NUM
esrj-37073	141	11	%	%	NOUN
esrj-37073	141	12	of	of	ADP
esrj-37073	141	13	a	a	DET
esrj-37073	141	14	time	time	NOUN
esrj-37073	141	15	series	series	NOUN
esrj-37073	141	16	and	and	CCONJ
esrj-37073	141	17	the	the	DET
esrj-37073	141	18	remaining	remain	VERB
esrj-37073	141	19	part	part	NOUN
esrj-37073	141	20	is	be	AUX
esrj-37073	141	21	used	use	VERB
esrj-37073	141	22	as	as	ADP
esrj-37073	141	23	the	the	DET
esrj-37073	141	24	calibration	calibration	NOUN
esrj-37073	141	25	and	and	CCONJ
esrj-37073	141	26	test	test	NOUN
esrj-37073	141	27	period	period	NOUN
esrj-37073	141	28	(	(	PUNCT
esrj-37073	141	29	banerjee	banerjee	PROPN
esrj-37073	141	30	et	et	PROPN
esrj-37073	141	31	al	al	PROPN
esrj-37073	141	32	.	.	PROPN
esrj-37073	141	33	,	,	PUNCT
esrj-37073	141	34	2011	2011	NUM
esrj-37073	141	35	;	;	PUNCT
esrj-37073	141	36	daliakopoulos	daliakopoulo	NOUN
esrj-37073	141	37	et	et	PROPN
esrj-37073	141	38	al	al	PROPN
esrj-37073	141	39	.	.	PROPN
esrj-37073	141	40	,	,	PUNCT
esrj-37073	141	41	2005	2005	NUM
esrj-37073	141	42	;	;	PUNCT
esrj-37073	141	43	riad	riad	PROPN
esrj-37073	141	44	et	et	PROPN
esrj-37073	141	45	al	al	PROPN
esrj-37073	141	46	.	.	PROPN
esrj-37073	141	47	,	,	PUNCT
esrj-37073	141	48	2004	2004	NUM
esrj-37073	141	49	)	)	PUNCT
esrj-37073	141	50	.	.	PUNCT
esrj-37073	142	1	in	in	ADP
esrj-37073	142	2	this	this	DET
esrj-37073	142	3	study	study	NOUN
esrj-37073	142	4	,	,	PUNCT
esrj-37073	142	5	approximately	approximately	ADV
esrj-37073	142	6	78	78	NUM
esrj-37073	142	7	%	%	NOUN
esrj-37073	142	8	(	(	PUNCT
esrj-37073	142	9	36	36	NUM
esrj-37073	142	10	years	year	NOUN
esrj-37073	142	11	)	)	PUNCT
esrj-37073	142	12	of	of	ADP
esrj-37073	142	13	the	the	DET
esrj-37073	142	14	entire	entire	ADJ
esrj-37073	142	15	data	datum	NOUN
esrj-37073	142	16	set	set	VERB
esrj-37073	142	17	was	be	AUX
esrj-37073	142	18	selected	select	VERB
esrj-37073	142	19	as	as	ADP
esrj-37073	142	20	the	the	DET
esrj-37073	142	21	training	training	NOUN
esrj-37073	142	22	period	period	NOUN
esrj-37073	142	23	,	,	PUNCT
esrj-37073	142	24	and	and	CCONJ
esrj-37073	142	25	the	the	DET
esrj-37073	142	26	remaining	remain	VERB
esrj-37073	142	27	part	part	NOUN
esrj-37073	142	28	,	,	PUNCT
esrj-37073	142	29	approximately	approximately	ADV
esrj-37073	142	30	22	22	NUM
esrj-37073	142	31	%	%	NOUN
esrj-37073	142	32	(	(	PUNCT
esrj-37073	142	33	10	10	NUM
esrj-37073	142	34	years	year	NOUN
esrj-37073	142	35	)	)	PUNCT
esrj-37073	142	36	,	,	PUNCT
esrj-37073	142	37	was	be	AUX
esrj-37073	142	38	selected	select	VERB
esrj-37073	142	39	for	for	ADP
esrj-37073	142	40	the	the	DET
esrj-37073	142	41	test	test	NOUN
esrj-37073	142	42	period	period	NOUN
esrj-37073	142	43	.	.	PUNCT
esrj-37073	143	1	table	table	NOUN
esrj-37073	143	2	2	2	NUM
esrj-37073	143	3	.	.	PUNCT
esrj-37073	144	1	the	the	DET
esrj-37073	144	2	model	model	NOUN
esrj-37073	144	3	structures	structure	NOUN
esrj-37073	144	4	that	that	PRON
esrj-37073	144	5	considered	consider	VERB
esrj-37073	144	6	minimum	minimum	ADJ
esrj-37073	144	7	and	and	CCONJ
esrj-37073	144	8	maximum	maximum	ADJ
esrj-37073	144	9	lagged	lag	VERB
esrj-37073	144	10	discharges	discharge	NOUN
esrj-37073	144	11	ffnn	ffnn	NOUN
esrj-37073	144	12	model	model	NOUN
esrj-37073	144	13	structures	structure	NOUN
esrj-37073	144	14	with	with	ADP
esrj-37073	144	15	minimum	minimum	ADJ
esrj-37073	144	16	and	and	CCONJ
esrj-37073	144	17	maximum	maximum	ADJ
esrj-37073	144	18	variables	variables	ADJ
esrj-37073	144	19	variable	variable	ADJ
esrj-37073	144	20	numbers	number	NOUN
esrj-37073	144	21	ffnn	ffnn	NOUN
esrj-37073	144	22	-	-	PUNCT
esrj-37073	144	23	i	i	PRON
esrj-37073	144	24	model	model	VERB
esrj-37073	144	25	3	3	NUM
esrj-37073	144	26	ffnn	ffnn	NOUN
esrj-37073	144	27	-	-	PUNCT
esrj-37073	144	28	ii	ii	NOUN
esrj-37073	144	29	model	model	NOUN
esrj-37073	144	30	7	7	NUM
esrj-37073	144	31	nonlinear	nonlinear	ADJ
esrj-37073	144	32	forecasting	forecasting	NOUN
esrj-37073	144	33	of	of	ADP
esrj-37073	144	34	stream	stream	NOUN
esrj-37073	144	35	flows	flow	NOUN
esrj-37073	144	36	using	use	VERB
esrj-37073	144	37	a	a	DET
esrj-37073	144	38	chaotic	chaotic	ADJ
esrj-37073	144	39	approach	approach	NOUN
esrj-37073	144	40	and	and	CCONJ
esrj-37073	144	41	artificial	artificial	ADJ
esrj-37073	144	42	neural	neural	ADJ
esrj-37073	144	43	networks	network	NOUN
esrj-37073	144	44	124	124	NUM
esrj-37073	144	45	(	(	PUNCT
esrj-37073	144	46	a	a	NOUN
esrj-37073	144	47	)	)	PUNCT
esrj-37073	144	48	(	(	PUNCT
esrj-37073	144	49	b	b	X
esrj-37073	144	50	)	)	PUNCT
esrj-37073	144	51	figure	figure	NOUN
esrj-37073	144	52	6	6	NUM
esrj-37073	144	53	.	.	PUNCT
esrj-37073	145	1	determination	determination	NOUN
esrj-37073	145	2	of	of	ADP
esrj-37073	145	3	the	the	DET
esrj-37073	145	4	number	number	NOUN
esrj-37073	145	5	of	of	ADP
esrj-37073	145	6	neurons	neuron	NOUN
esrj-37073	145	7	in	in	ADP
esrj-37073	145	8	the	the	DET
esrj-37073	145	9	hidden	hidden	ADJ
esrj-37073	145	10	layers	layer	NOUN
esrj-37073	145	11	for	for	ADP
esrj-37073	145	12	the	the	DET
esrj-37073	145	13	(	(	PUNCT
esrj-37073	145	14	a	a	NOUN
esrj-37073	145	15	)	)	PUNCT
esrj-37073	145	16	ffnn	ffnn	NOUN
esrj-37073	145	17	-	-	PUNCT
esrj-37073	145	18	i	i	PRON
esrj-37073	145	19	and	and	CCONJ
esrj-37073	145	20	(	(	PUNCT
esrj-37073	145	21	b	b	NOUN
esrj-37073	145	22	)	)	PUNCT
esrj-37073	145	23	ffnn	ffnn	NOUN
esrj-37073	145	24	-	-	PUNCT
esrj-37073	145	25	ii	ii	NOUN
esrj-37073	145	26	models	model	NOUN
esrj-37073	145	27	as	as	ADP
esrj-37073	145	28	a	a	DET
esrj-37073	145	29	function	function	NOUN
esrj-37073	145	30	of	of	ADP
esrj-37073	145	31	rmse	rmse	NOUN
esrj-37073	145	32	the	the	DET
esrj-37073	145	33	ffnn	ffnn	NOUN
esrj-37073	145	34	model	model	NOUN
esrj-37073	145	35	structures	structure	NOUN
esrj-37073	145	36	contained	contain	VERB
esrj-37073	145	37	one	one	NUM
esrj-37073	145	38	input	input	NOUN
esrj-37073	145	39	layer	layer	NOUN
esrj-37073	145	40	,	,	PUNCT
esrj-37073	145	41	two	two	NUM
esrj-37073	145	42	hidden	hidden	ADJ
esrj-37073	145	43	layers	layer	NOUN
esrj-37073	145	44	and	and	CCONJ
esrj-37073	145	45	one	one	NUM
esrj-37073	145	46	output	output	NOUN
esrj-37073	145	47	layer	layer	NOUN
esrj-37073	145	48	.	.	PUNCT
esrj-37073	146	1	the	the	DET
esrj-37073	146	2	number	number	NOUN
esrj-37073	146	3	of	of	ADP
esrj-37073	146	4	neurons	neuron	NOUN
esrj-37073	146	5	in	in	ADP
esrj-37073	146	6	the	the	DET
esrj-37073	146	7	hidden	hidden	ADJ
esrj-37073	146	8	layers	layer	NOUN
esrj-37073	146	9	was	be	AUX
esrj-37073	146	10	determined	determine	VERB
esrj-37073	146	11	using	use	VERB
esrj-37073	146	12	an	an	DET
esrj-37073	146	13	optimization	optimization	NOUN
esrj-37073	146	14	process	process	NOUN
esrj-37073	146	15	that	that	PRON
esrj-37073	146	16	minimized	minimize	VERB
esrj-37073	146	17	rmse	rmse	NOUN
esrj-37073	146	18	as	as	ADP
esrj-37073	146	19	a	a	DET
esrj-37073	146	20	function	function	NOUN
esrj-37073	146	21	of	of	ADP
esrj-37073	146	22	the	the	DET
esrj-37073	146	23	number	number	NOUN
esrj-37073	146	24	of	of	ADP
esrj-37073	146	25	neurons	neuron	NOUN
esrj-37073	146	26	(	(	PUNCT
esrj-37073	146	27	figure	figure	NOUN
esrj-37073	146	28	6	6	NUM
esrj-37073	146	29	)	)	PUNCT
esrj-37073	146	30	.	.	PUNCT
esrj-37073	147	1	the	the	DET
esrj-37073	147	2	results	result	NOUN
esrj-37073	147	3	from	from	ADP
esrj-37073	147	4	these	these	DET
esrj-37073	147	5	models	model	NOUN
esrj-37073	147	6	are	be	AUX
esrj-37073	147	7	given	give	VERB
esrj-37073	147	8	in	in	ADP
esrj-37073	147	9	figure	figure	NOUN
esrj-37073	147	10	7	7	NUM
esrj-37073	147	11	.	.	PUNCT
esrj-37073	147	12	from	from	ADP
esrj-37073	147	13	figure	figure	NOUN
esrj-37073	147	14	7	7	NUM
esrj-37073	147	15	,	,	PUNCT
esrj-37073	147	16	the	the	DET
esrj-37073	147	17	inadequacy	inadequacy	NOUN
esrj-37073	147	18	of	of	ADP
esrj-37073	147	19	the	the	DET
esrj-37073	147	20	k	k	PROPN
esrj-37073	147	21	-	-	PUNCT
esrj-37073	147	22	nn	nn	ADJ
esrj-37073	147	23	model	model	NOUN
esrj-37073	147	24	is	be	AUX
esrj-37073	147	25	obvious	obvious	ADJ
esrj-37073	147	26	;	;	PUNCT
esrj-37073	147	27	failing	fail	VERB
esrj-37073	147	28	to	to	PART
esrj-37073	147	29	capture	capture	VERB
esrj-37073	147	30	the	the	DET
esrj-37073	147	31	peak	peak	NOUN
esrj-37073	147	32	flows	flow	VERB
esrj-37073	147	33	.	.	PUNCT
esrj-37073	148	1	the	the	DET
esrj-37073	148	2	reason	reason	NOUN
esrj-37073	148	3	for	for	ADP
esrj-37073	148	4	this	this	PRON
esrj-37073	148	5	is	be	AUX
esrj-37073	148	6	that	that	SCONJ
esrj-37073	148	7	the	the	DET
esrj-37073	148	8	k	k	PROPN
esrj-37073	148	9	-	-	PUNCT
esrj-37073	148	10	nn	nn	PROPN
esrj-37073	148	11	model	model	NOUN
esrj-37073	148	12	predicted	predict	VERB
esrj-37073	148	13	the	the	DET
esrj-37073	148	14	next	next	ADJ
esrj-37073	148	15	value	value	NOUN
esrj-37073	148	16	by	by	ADP
esrj-37073	148	17	considering	consider	VERB
esrj-37073	148	18	the	the	DET
esrj-37073	148	19	past	past	ADJ
esrj-37073	148	20	observed	observed	ADJ
esrj-37073	148	21	values	value	NOUN
esrj-37073	148	22	as	as	ADV
esrj-37073	148	23	much	much	ADV
esrj-37073	148	24	as	as	ADP
esrj-37073	148	25	the	the	DET
esrj-37073	148	26	number	number	NOUN
esrj-37073	148	27	of	of	ADP
esrj-37073	148	28	nearest	near	ADJ
esrj-37073	148	29	neighbors	neighbor	NOUN
esrj-37073	148	30	.	.	PUNCT
esrj-37073	149	1	to	to	PART
esrj-37073	149	2	obtain	obtain	VERB
esrj-37073	149	3	accurate	accurate	ADJ
esrj-37073	149	4	peak	peak	NOUN
esrj-37073	149	5	flow	flow	NOUN
esrj-37073	149	6	prediction	prediction	NOUN
esrj-37073	149	7	,	,	PUNCT
esrj-37073	149	8	the	the	DET
esrj-37073	149	9	number	number	NOUN
esrj-37073	149	10	of	of	ADP
esrj-37073	149	11	peak	peak	NOUN
esrj-37073	149	12	values	value	NOUN
esrj-37073	149	13	in	in	ADP
esrj-37073	149	14	the	the	DET
esrj-37073	149	15	past	past	ADJ
esrj-37073	149	16	observed	observe	VERB
esrj-37073	149	17	period	period	NOUN
esrj-37073	149	18	should	should	AUX
esrj-37073	149	19	be	be	AUX
esrj-37073	149	20	as	as	ADV
esrj-37073	149	21	much	much	ADJ
esrj-37073	149	22	as	as	ADP
esrj-37073	149	23	the	the	DET
esrj-37073	149	24	nearest	near	ADJ
esrj-37073	149	25	neighbor	neighbor	ADJ
esrj-37073	149	26	number	number	NOUN
esrj-37073	149	27	.	.	PUNCT
esrj-37073	150	1	if	if	SCONJ
esrj-37073	150	2	the	the	DET
esrj-37073	150	3	number	number	NOUN
esrj-37073	150	4	of	of	ADP
esrj-37073	150	5	observations	observation	NOUN
esrj-37073	150	6	of	of	ADP
esrj-37073	150	7	peak	peak	NOUN
esrj-37073	150	8	flow	flow	NOUN
esrj-37073	150	9	in	in	ADP
esrj-37073	150	10	the	the	DET
esrj-37073	150	11	training	training	NOUN
esrj-37073	150	12	period	period	NOUN
esrj-37073	150	13	is	be	AUX
esrj-37073	150	14	smaller	small	ADJ
esrj-37073	150	15	than	than	ADP
esrj-37073	150	16	the	the	DET
esrj-37073	150	17	nearest	near	ADJ
esrj-37073	150	18	neighbor	neighbor	NOUN
esrj-37073	150	19	number	number	NOUN
esrj-37073	150	20	,	,	PUNCT
esrj-37073	150	21	than	than	SCONJ
esrj-37073	150	22	the	the	DET
esrj-37073	150	23	model	model	NOUN
esrj-37073	150	24	fails	fail	VERB
esrj-37073	150	25	in	in	ADP
esrj-37073	150	26	the	the	DET
esrj-37073	150	27	accurate	accurate	ADJ
esrj-37073	150	28	prediction	prediction	NOUN
esrj-37073	150	29	of	of	ADP
esrj-37073	150	30	peak	peak	NOUN
esrj-37073	150	31	flows	flow	NOUN
esrj-37073	150	32	.	.	PUNCT
esrj-37073	151	1	this	this	PRON
esrj-37073	151	2	is	be	AUX
esrj-37073	151	3	also	also	ADV
esrj-37073	151	4	valid	valid	ADJ
esrj-37073	151	5	for	for	ADP
esrj-37073	151	6	low	low	ADJ
esrj-37073	151	7	flow	flow	NOUN
esrj-37073	151	8	predictions	prediction	NOUN
esrj-37073	151	9	.	.	PUNCT
esrj-37073	152	1	from	from	ADP
esrj-37073	152	2	figure	figure	NOUN
esrj-37073	152	3	7	7	NUM
esrj-37073	152	4	,	,	PUNCT
esrj-37073	152	5	there	there	PRON
esrj-37073	152	6	is	be	VERB
esrj-37073	152	7	a	a	DET
esrj-37073	152	8	section	section	NOUN
esrj-37073	152	9	at	at	ADP
esrj-37073	152	10	the	the	DET
esrj-37073	152	11	end	end	NOUN
esrj-37073	152	12	of	of	ADP
esrj-37073	152	13	the	the	DET
esrj-37073	152	14	test	test	NOUN
esrj-37073	152	15	period	period	NOUN
esrj-37073	152	16	in	in	ADP
esrj-37073	152	17	which	which	PRON
esrj-37073	152	18	no	no	DET
esrj-37073	152	19	flow	flow	NOUN
esrj-37073	152	20	was	be	AUX
esrj-37073	152	21	observed	observe	VERB
esrj-37073	152	22	.	.	PUNCT
esrj-37073	153	1	the	the	DET
esrj-37073	153	2	k	k	PROPN
esrj-37073	153	3	-	-	PUNCT
esrj-37073	153	4	nn	nn	ADJ
esrj-37073	153	5	model	model	NOUN
esrj-37073	153	6	constantly	constantly	ADV
esrj-37073	153	7	over	over	ADV
esrj-37073	153	8	-	-	PUNCT
esrj-37073	153	9	predicted	predict	VERB
esrj-37073	153	10	this	this	DET
esrj-37073	153	11	period	period	NOUN
esrj-37073	153	12	.	.	PUNCT
esrj-37073	154	1	however	however	ADV
esrj-37073	154	2	,	,	PUNCT
esrj-37073	154	3	the	the	DET
esrj-37073	154	4	ffnn	ffnn	NOUN
esrj-37073	154	5	models	model	NOUN
esrj-37073	154	6	performed	perform	VERB
esrj-37073	154	7	better	well	ADV
esrj-37073	154	8	in	in	ADP
esrj-37073	154	9	peak	peak	NOUN
esrj-37073	154	10	flow	flow	NOUN
esrj-37073	154	11	predictions	prediction	NOUN
esrj-37073	154	12	than	than	ADP
esrj-37073	154	13	the	the	DET
esrj-37073	154	14	k	k	PROPN
esrj-37073	154	15	-	-	PUNCT
esrj-37073	154	16	nn	nn	PROPN
esrj-37073	154	17	model	model	NOUN
esrj-37073	154	18	.	.	PUNCT
esrj-37073	155	1	to	to	PART
esrj-37073	155	2	acquire	acquire	VERB
esrj-37073	155	3	more	more	ADJ
esrj-37073	155	4	insight	insight	NOUN
esrj-37073	155	5	into	into	ADP
esrj-37073	155	6	the	the	DET
esrj-37073	155	7	models	model	NOUN
esrj-37073	155	8	’	'	PUNCT
esrj-37073	155	9	performance	performance	NOUN
esrj-37073	155	10	,	,	PUNCT
esrj-37073	155	11	the	the	DET
esrj-37073	155	12	performance	performance	NOUN
esrj-37073	155	13	indices	index	NOUN
esrj-37073	155	14	were	be	AUX
esrj-37073	155	15	calculated	calculate	VERB
esrj-37073	155	16	and	and	CCONJ
esrj-37073	155	17	are	be	AUX
esrj-37073	155	18	given	give	VERB
esrj-37073	155	19	in	in	ADP
esrj-37073	155	20	table	table	NOUN
esrj-37073	155	21	3	3	NUM
esrj-37073	155	22	.	.	PUNCT
esrj-37073	156	1	(	(	PUNCT
esrj-37073	156	2	a	a	X
esrj-37073	156	3	)	)	PUNCT
esrj-37073	156	4	(	(	PUNCT
esrj-37073	156	5	b	b	X
esrj-37073	156	6	)	)	PUNCT
esrj-37073	156	7	(	(	PUNCT
esrj-37073	156	8	c	c	X
esrj-37073	156	9	)	)	PUNCT
esrj-37073	156	10	figure	figure	NOUN
esrj-37073	156	11	7	7	NUM
esrj-37073	156	12	.	.	PUNCT
esrj-37073	157	1	the	the	DET
esrj-37073	157	2	observed	observe	VERB
esrj-37073	157	3	river	river	NOUN
esrj-37073	157	4	flow	flow	NOUN
esrj-37073	157	5	and	and	CCONJ
esrj-37073	157	6	predicted	predict	VERB
esrj-37073	157	7	river	river	NOUN
esrj-37073	157	8	flow	flow	NOUN
esrj-37073	157	9	for	for	ADP
esrj-37073	157	10	the	the	DET
esrj-37073	157	11	entire	entire	ADJ
esrj-37073	157	12	test	test	NOUN
esrj-37073	157	13	period	period	NOUN
esrj-37073	157	14	for	for	ADP
esrj-37073	157	15	the	the	DET
esrj-37073	157	16	(	(	PUNCT
esrj-37073	157	17	a	a	NOUN
esrj-37073	157	18	)	)	PUNCT
esrj-37073	157	19	k	k	PROPN
esrj-37073	157	20	-	-	PUNCT
esrj-37073	157	21	nn	nn	PROPN
esrj-37073	157	22	(	(	PUNCT
esrj-37073	157	23	b	b	NOUN
esrj-37073	157	24	)	)	PUNCT
esrj-37073	157	25	ffnn	ffnn	NOUN
esrj-37073	157	26	-	-	PUNCT
esrj-37073	157	27	i	i	PRON
esrj-37073	157	28	and	and	CCONJ
esrj-37073	157	29	(	(	PUNCT
esrj-37073	157	30	c	c	NOUN
esrj-37073	157	31	)	)	PUNCT
esrj-37073	157	32	ffnn	ffnn	NOUN
esrj-37073	157	33	-	-	PUNCT
esrj-37073	157	34	ii	ii	NOUN
esrj-37073	157	35	models	model	NOUN
esrj-37073	157	36	by	by	ADP
esrj-37073	157	37	means	mean	NOUN
esrj-37073	157	38	of	of	ADP
esrj-37073	157	39	the	the	DET
esrj-37073	157	40	performance	performance	NOUN
esrj-37073	157	41	indices	index	NOUN
esrj-37073	157	42	,	,	PUNCT
esrj-37073	157	43	the	the	DET
esrj-37073	157	44	best	good	ADJ
esrj-37073	157	45	model	model	NOUN
esrj-37073	157	46	was	be	AUX
esrj-37073	157	47	selected	select	VERB
esrj-37073	157	48	as	as	ADP
esrj-37073	157	49	the	the	DET
esrj-37073	157	50	k	k	PROPN
esrj-37073	157	51	-	-	PUNCT
esrj-37073	157	52	nn	nn	ADJ
esrj-37073	157	53	model	model	NOUN
esrj-37073	157	54	and	and	CCONJ
esrj-37073	157	55	the	the	DET
esrj-37073	157	56	worst	bad	ADJ
esrj-37073	157	57	model	model	NOUN
esrj-37073	157	58	was	be	AUX
esrj-37073	157	59	selected	select	VERB
esrj-37073	157	60	as	as	ADP
esrj-37073	157	61	the	the	DET
esrj-37073	157	62	ffnn	ffnn	NOUN
esrj-37073	157	63	-	-	PUNCT
esrj-37073	157	64	i	i	PRON
esrj-37073	157	65	model	model	NOUN
esrj-37073	157	66	.	.	PUNCT
esrj-37073	158	1	the	the	DET
esrj-37073	158	2	highest	high	ADJ
esrj-37073	158	3	pi	pi	NOUN
esrj-37073	158	4	,	,	PUNCT
esrj-37073	158	5	ce	ce	PROPN
esrj-37073	158	6	and	and	CCONJ
esrj-37073	158	7	r2	r2	PROPN
esrj-37073	158	8	and	and	CCONJ
esrj-37073	158	9	the	the	DET
esrj-37073	158	10	lowest	low	ADJ
esrj-37073	158	11	rmse	rmse	NOUN
esrj-37073	158	12	,	,	PUNCT
esrj-37073	158	13	rve	rve	PROPN
esrj-37073	158	14	and	and	CCONJ
esrj-37073	158	15	mae	mae	PROPN
esrj-37073	158	16	values	value	NOUN
esrj-37073	158	17	were	be	AUX
esrj-37073	158	18	obtained	obtain	VERB
esrj-37073	158	19	with	with	ADP
esrj-37073	158	20	the	the	DET
esrj-37073	158	21	k	k	PROPN
esrj-37073	158	22	-	-	PUNCT
esrj-37073	158	23	nn	nn	PROPN
esrj-37073	158	24	model	model	NOUN
esrj-37073	158	25	.	.	PUNCT
esrj-37073	159	1	as	as	SCONJ
esrj-37073	159	2	the	the	DET
esrj-37073	159	3	results	result	NOUN
esrj-37073	159	4	showed	show	VERB
esrj-37073	159	5	,	,	PUNCT
esrj-37073	159	6	there	there	PRON
esrj-37073	159	7	was	be	VERB
esrj-37073	159	8	not	not	PART
esrj-37073	159	9	much	much	ADJ
esrj-37073	159	10	difference	difference	NOUN
esrj-37073	159	11	between	between	ADP
esrj-37073	159	12	the	the	DET
esrj-37073	159	13	ce	ce	PROPN
esrj-37073	159	14	and	and	CCONJ
esrj-37073	159	15	r2	r2	PROPN
esrj-37073	159	16	values	value	NOUN
esrj-37073	159	17	,	,	PUNCT
esrj-37073	159	18	and	and	CCONJ
esrj-37073	159	19	stand	stand	VERB
esrj-37073	159	20	-	-	PUNCT
esrj-37073	159	21	alone	alone	ADV
esrj-37073	159	22	evaluation	evaluation	NOUN
esrj-37073	159	23	of	of	ADP
esrj-37073	159	24	these	these	DET
esrj-37073	159	25	performance	performance	NOUN
esrj-37073	159	26	indices	index	NOUN
esrj-37073	159	27	does	do	AUX
esrj-37073	159	28	not	not	PART
esrj-37073	159	29	give	give	VERB
esrj-37073	159	30	much	much	ADJ
esrj-37073	159	31	insight	insight	NOUN
esrj-37073	159	32	into	into	ADP
esrj-37073	159	33	the	the	DET
esrj-37073	159	34	model	model	NOUN
esrj-37073	159	35	comparison	comparison	NOUN
esrj-37073	159	36	.	.	PUNCT
esrj-37073	160	1	in	in	ADP
esrj-37073	160	2	addition	addition	NOUN
esrj-37073	160	3	to	to	ADP
esrj-37073	160	4	these	these	DET
esrj-37073	160	5	criteria	criterion	NOUN
esrj-37073	160	6	,	,	PUNCT
esrj-37073	160	7	rmse	rmse	PROPN
esrj-37073	160	8	,	,	PUNCT
esrj-37073	160	9	rve	rve	PROPN
esrj-37073	160	10	,	,	PUNCT
esrj-37073	160	11	mae	mae	PROPN
esrj-37073	160	12	and	and	CCONJ
esrj-37073	160	13	pi	pi	PROPN
esrj-37073	160	14	demonstrated	demonstrate	VERB
esrj-37073	160	15	the	the	DET
esrj-37073	160	16	clear	clear	ADJ
esrj-37073	160	17	superiority	superiority	NOUN
esrj-37073	160	18	(	(	PUNCT
esrj-37073	160	19	nearly	nearly	ADV
esrj-37073	160	20	twice	twice	DET
esrj-37073	160	21	as	as	ADV
esrj-37073	160	22	much	much	ADJ
esrj-37073	160	23	)	)	PUNCT
esrj-37073	160	24	of	of	ADP
esrj-37073	160	25	the	the	DET
esrj-37073	160	26	k	k	PROPN
esrj-37073	160	27	-	-	PUNCT
esrj-37073	160	28	nn	nn	PROPN
esrj-37073	160	29	model	model	NOUN
esrj-37073	160	30	over	over	ADP
esrj-37073	160	31	the	the	DET
esrj-37073	160	32	ffnn	ffnn	NOUN
esrj-37073	160	33	model	model	NOUN
esrj-37073	160	34	.	.	PUNCT
esrj-37073	161	1	therefore	therefore	ADV
esrj-37073	161	2	,	,	PUNCT
esrj-37073	161	3	in	in	ADP
esrj-37073	161	4	the	the	DET
esrj-37073	161	5	model	model	NOUN
esrj-37073	161	6	comparison	comparison	NOUN
esrj-37073	161	7	,	,	PUNCT
esrj-37073	161	8	it	it	PRON
esrj-37073	161	9	was	be	AUX
esrj-37073	161	10	important	important	ADJ
esrj-37073	161	11	to	to	PART
esrj-37073	161	12	take	take	VERB
esrj-37073	161	13	into	into	ADP
esrj-37073	161	14	account	account	NOUN
esrj-37073	161	15	other	other	ADJ
esrj-37073	161	16	performance	performance	NOUN
esrj-37073	161	17	indices	index	NOUN
esrj-37073	161	18	that	that	PRON
esrj-37073	161	19	emphasized	emphasize	VERB
esrj-37073	161	20	different	different	ADJ
esrj-37073	161	21	features	feature	NOUN
esrj-37073	161	22	of	of	ADP
esrj-37073	161	23	the	the	DET
esrj-37073	161	24	predicted	predict	VERB
esrj-37073	161	25	values	value	NOUN
esrj-37073	161	26	.	.	PUNCT
esrj-37073	162	1	table	table	NOUN
esrj-37073	162	2	3	3	NUM
esrj-37073	162	3	.	.	PUNCT
esrj-37073	163	1	forecasting	forecasting	NOUN
esrj-37073	163	2	performance	performance	NOUN
esrj-37073	163	3	of	of	ADP
esrj-37073	163	4	the	the	DET
esrj-37073	163	5	nonlinear	nonlinear	ADJ
esrj-37073	163	6	models	model	NOUN
esrj-37073	163	7	kızılırmak	kızılırmak	PROPN
esrj-37073	163	8	river	river	NOUN
esrj-37073	163	9	performance	performance	NOUN
esrj-37073	163	10	indices	index	NOUN
esrj-37073	163	11	rmse	rmse	PROPN
esrj-37073	163	12	rve	rve	PROPN
esrj-37073	163	13	mae	mae	PROPN
esrj-37073	163	14	pi	pi	PROPN
esrj-37073	163	15	ce	ce	PROPN
esrj-37073	163	16	r2	r2	PROPN
esrj-37073	163	17	k	k	PROPN
esrj-37073	163	18	-	-	PUNCT
esrj-37073	163	19	nn	nn	PROPN
esrj-37073	163	20	model	model	NOUN
esrj-37073	163	21	4.4776	4.4776	NUM
esrj-37073	163	22	10,634	10,634	NUM
esrj-37073	163	23	1.6686	1.6686	NUM
esrj-37073	163	24	0.8803	0.8803	NUM
esrj-37073	163	25	0.9965	0.9965	NUM
esrj-37073	163	26	0.9970	0.9970	NUM
esrj-37073	163	27	ffnn	ffnn	NOUN
esrj-37073	163	28	-	-	PUNCT
esrj-37073	163	29	i	i	PRON
esrj-37073	163	30	model	model	NOUN
esrj-37073	163	31	(	(	PUNCT
esrj-37073	163	32	3	3	NUM
esrj-37073	163	33	-	-	SYM
esrj-37073	163	34	7	7	NUM
esrj-37073	163	35	-	-	PUNCT
esrj-37073	163	36	3	3	NUM
esrj-37073	163	37	-	-	SYM
esrj-37073	163	38	1	1	NUM
esrj-37073	163	39	)	)	PUNCT
esrj-37073	163	40	13.2685	13.2685	NUM
esrj-37073	163	41	23,571	23,571	NUM
esrj-37073	163	42	4.3124	4.3124	NUM
esrj-37073	163	43	-0.0511	-0.0511	NOUN
esrj-37073	163	44	0.9689	0.9689	NUM
esrj-37073	163	45	0.9699	0.9699	NUM
esrj-37073	163	46	ffnn	ffnn	NOUN
esrj-37073	163	47	-	-	PUNCT
esrj-37073	163	48	ii	ii	NOUN
esrj-37073	163	49	model	model	NOUN
esrj-37073	163	50	(	(	PUNCT
esrj-37073	163	51	7	7	NUM
esrj-37073	163	52	-	-	SYM
esrj-37073	163	53	6	6	NUM
esrj-37073	163	54	-	-	PUNCT
esrj-37073	163	55	7	7	NUM
esrj-37073	163	56	-	-	PUNCT
esrj-37073	163	57	1	1	NUM
esrj-37073	163	58	)	)	PUNCT
esrj-37073	163	59	9.8451	9.8451	NUM
esrj-37073	163	60	20,838	20,838	NUM
esrj-37073	163	61	3.4546	3.4546	NUM
esrj-37073	163	62	0.4219	0.4219	NUM
esrj-37073	163	63	0.9829	0.9829	NUM
esrj-37073	163	64	0.9829	0.9829	NUM
esrj-37073	163	65	hakan	hakan	PROPN
esrj-37073	163	66	tongal	tongal	ADJ
esrj-37073	163	67	125	125	NUM
esrj-37073	163	68	these	these	DET
esrj-37073	163	69	results	result	NOUN
esrj-37073	163	70	showed	show	VERB
esrj-37073	163	71	that	that	SCONJ
esrj-37073	163	72	the	the	DET
esrj-37073	163	73	correlation	correlation	NOUN
esrj-37073	163	74	dimension	dimension	NOUN
esrj-37073	163	75	could	could	AUX
esrj-37073	163	76	be	be	AUX
esrj-37073	163	77	used	use	VERB
esrj-37073	163	78	in	in	ADP
esrj-37073	163	79	the	the	DET
esrj-37073	163	80	determination	determination	NOUN
esrj-37073	163	81	of	of	ADP
esrj-37073	163	82	the	the	DET
esrj-37073	163	83	ffnn	ffnn	NOUN
esrj-37073	163	84	model	model	NOUN
esrj-37073	163	85	structure	structure	NOUN
esrj-37073	163	86	by	by	ADP
esrj-37073	163	87	taking	take	VERB
esrj-37073	163	88	the	the	DET
esrj-37073	163	89	lagged	lag	VERB
esrj-37073	163	90	values	value	NOUN
esrj-37073	163	91	as	as	ADP
esrj-37073	163	92	the	the	DET
esrj-37073	163	93	minimum	minimum	ADJ
esrj-37073	163	94	and	and	CCONJ
esrj-37073	163	95	maximum	maximum	ADJ
esrj-37073	163	96	dominant	dominant	ADJ
esrj-37073	163	97	variable	variable	ADJ
esrj-37073	163	98	number	number	NOUN
esrj-37073	163	99	.	.	PUNCT
esrj-37073	164	1	to	to	ADP
esrj-37073	164	2	the	the	DET
esrj-37073	164	3	authors	author	NOUN
esrj-37073	164	4	’	’	PART
esrj-37073	164	5	knowledge	knowledge	NOUN
esrj-37073	164	6	,	,	PUNCT
esrj-37073	164	7	this	this	DET
esrj-37073	164	8	study	study	NOUN
esrj-37073	164	9	is	be	AUX
esrj-37073	164	10	the	the	DET
esrj-37073	164	11	first	first	ADJ
esrj-37073	164	12	to	to	PART
esrj-37073	164	13	show	show	VERB
esrj-37073	164	14	that	that	SCONJ
esrj-37073	164	15	the	the	DET
esrj-37073	164	16	correlation	correlation	NOUN
esrj-37073	164	17	dimension	dimension	NOUN
esrj-37073	164	18	could	could	AUX
esrj-37073	164	19	be	be	AUX
esrj-37073	164	20	used	use	VERB
esrj-37073	164	21	in	in	ADP
esrj-37073	164	22	determining	determine	VERB
esrj-37073	164	23	of	of	ADP
esrj-37073	164	24	number	number	NOUN
esrj-37073	164	25	of	of	ADP
esrj-37073	164	26	lagged	lag	VERB
esrj-37073	164	27	values	value	NOUN
esrj-37073	164	28	of	of	ADP
esrj-37073	164	29	the	the	DET
esrj-37073	164	30	discharges	discharge	NOUN
esrj-37073	164	31	.	.	PUNCT
esrj-37073	165	1	this	this	PRON
esrj-37073	165	2	is	be	AUX
esrj-37073	165	3	important	important	ADJ
esrj-37073	165	4	where	where	SCONJ
esrj-37073	165	5	the	the	DET
esrj-37073	165	6	autocorrelation	autocorrelation	NOUN
esrj-37073	165	7	function	function	NOUN
esrj-37073	165	8	remains	remain	VERB
esrj-37073	165	9	high	high	ADJ
esrj-37073	165	10	for	for	ADP
esrj-37073	165	11	higher	high	ADJ
esrj-37073	165	12	lags	lag	NOUN
esrj-37073	165	13	such	such	ADJ
esrj-37073	165	14	as	as	ADP
esrj-37073	165	15	in	in	ADP
esrj-37073	165	16	this	this	DET
esrj-37073	165	17	case	case	NOUN
esrj-37073	165	18	(	(	PUNCT
esrj-37073	165	19	figure	figure	NOUN
esrj-37073	165	20	8)	8)	NUM
esrj-37073	165	21	.	.	PUNCT
esrj-37073	166	1	figure	figure	NOUN
esrj-37073	166	2	8	8	NUM
esrj-37073	166	3	.	.	PUNCT
esrj-37073	166	4	autocorrelation	autocorrelation	NOUN
esrj-37073	166	5	function	function	NOUN
esrj-37073	166	6	of	of	ADP
esrj-37073	166	7	the	the	DET
esrj-37073	166	8	kızılırmak	kızılırmak	PROPN
esrj-37073	166	9	river	river	NOUN
esrj-37073	166	10	it	it	PRON
esrj-37073	166	11	is	be	AUX
esrj-37073	166	12	difficult	difficult	ADJ
esrj-37073	166	13	to	to	PART
esrj-37073	166	14	determine	determine	VERB
esrj-37073	166	15	the	the	DET
esrj-37073	166	16	optimal	optimal	ADJ
esrj-37073	166	17	lag	lag	NOUN
esrj-37073	166	18	values	value	NOUN
esrj-37073	166	19	in	in	ADP
esrj-37073	166	20	the	the	DET
esrj-37073	166	21	model	model	NOUN
esrj-37073	166	22	structure	structure	NOUN
esrj-37073	166	23	where	where	SCONJ
esrj-37073	166	24	the	the	DET
esrj-37073	166	25	autocorrelation	autocorrelation	NOUN
esrj-37073	166	26	function	function	NOUN
esrj-37073	166	27	values	value	NOUN
esrj-37073	166	28	start	start	VERB
esrj-37073	166	29	to	to	PART
esrj-37073	166	30	become	become	VERB
esrj-37073	166	31	statistically	statistically	ADV
esrj-37073	166	32	insignificant	insignificant	ADJ
esrj-37073	166	33	.	.	PUNCT
esrj-37073	167	1	for	for	ADP
esrj-37073	167	2	instance	instance	NOUN
esrj-37073	167	3	,	,	PUNCT
esrj-37073	167	4	in	in	ADP
esrj-37073	167	5	figure	figure	NOUN
esrj-37073	167	6	8	8	NUM
esrj-37073	167	7	,	,	PUNCT
esrj-37073	167	8	the	the	DET
esrj-37073	167	9	autocorrelation	autocorrelation	NOUN
esrj-37073	167	10	function	function	NOUN
esrj-37073	167	11	becomes	become	VERB
esrj-37073	167	12	statistically	statistically	ADV
esrj-37073	167	13	insignificant	insignificant	ADJ
esrj-37073	167	14	on	on	ADP
esrj-37073	167	15	the	the	DET
esrj-37073	167	16	90th	90th	ADJ
esrj-37073	167	17	day	day	NOUN
esrj-37073	167	18	.	.	PUNCT
esrj-37073	168	1	to	to	PART
esrj-37073	168	2	determine	determine	VERB
esrj-37073	168	3	the	the	DET
esrj-37073	168	4	optimal	optimal	ADJ
esrj-37073	168	5	lag	lag	NOUN
esrj-37073	168	6	values	value	NOUN
esrj-37073	168	7	that	that	PRON
esrj-37073	168	8	will	will	AUX
esrj-37073	168	9	be	be	AUX
esrj-37073	168	10	considered	consider	VERB
esrj-37073	168	11	in	in	ADP
esrj-37073	168	12	the	the	DET
esrj-37073	168	13	model	model	NOUN
esrj-37073	168	14	structure	structure	NOUN
esrj-37073	168	15	,	,	PUNCT
esrj-37073	168	16	various	various	ADJ
esrj-37073	168	17	models	model	NOUN
esrj-37073	168	18	should	should	AUX
esrj-37073	168	19	be	be	AUX
esrj-37073	168	20	considered	consider	VERB
esrj-37073	168	21	that	that	PRON
esrj-37073	168	22	incorporate	incorporate	VERB
esrj-37073	168	23	combinations	combination	NOUN
esrj-37073	168	24	of	of	ADP
esrj-37073	168	25	lag	lag	NOUN
esrj-37073	168	26	values	value	NOUN
esrj-37073	168	27	up	up	ADP
esrj-37073	168	28	to	to	ADP
esrj-37073	168	29	90	90	NUM
esrj-37073	168	30	.	.	PUNCT
esrj-37073	169	1	obviously	obviously	ADV
esrj-37073	169	2	,	,	PUNCT
esrj-37073	169	3	this	this	PRON
esrj-37073	169	4	is	be	AUX
esrj-37073	169	5	quite	quite	ADV
esrj-37073	169	6	time	time	NOUN
esrj-37073	169	7	consuming	consume	VERB
esrj-37073	169	8	.	.	PUNCT
esrj-37073	170	1	however	however	ADV
esrj-37073	170	2	,	,	PUNCT
esrj-37073	170	3	by	by	ADP
esrj-37073	170	4	considering	consider	VERB
esrj-37073	170	5	the	the	DET
esrj-37073	170	6	correlation	correlation	NOUN
esrj-37073	170	7	dimension	dimension	NOUN
esrj-37073	170	8	of	of	ADP
esrj-37073	170	9	the	the	DET
esrj-37073	170	10	examined	examine	VERB
esrj-37073	170	11	system	system	NOUN
esrj-37073	170	12	,	,	PUNCT
esrj-37073	170	13	it	it	PRON
esrj-37073	170	14	is	be	AUX
esrj-37073	170	15	possible	possible	ADJ
esrj-37073	170	16	to	to	PART
esrj-37073	170	17	construct	construct	VERB
esrj-37073	170	18	two	two	NUM
esrj-37073	170	19	models	model	NOUN
esrj-37073	170	20	that	that	PRON
esrj-37073	170	21	incorporate	incorporate	VERB
esrj-37073	170	22	minimum	minimum	ADJ
esrj-37073	170	23	and	and	CCONJ
esrj-37073	170	24	maximum	maximum	ADJ
esrj-37073	170	25	lagged	lag	VERB
esrj-37073	170	26	values	value	NOUN
esrj-37073	170	27	that	that	PRON
esrj-37073	170	28	are	be	AUX
esrj-37073	170	29	determined	determine	VERB
esrj-37073	170	30	from	from	ADP
esrj-37073	170	31	the	the	DET
esrj-37073	170	32	correlation	correlation	NOUN
esrj-37073	170	33	dimension	dimension	NOUN
esrj-37073	170	34	.	.	PUNCT
esrj-37073	171	1	this	this	DET
esrj-37073	171	2	result	result	NOUN
esrj-37073	171	3	is	be	AUX
esrj-37073	171	4	evidence	evidence	NOUN
esrj-37073	171	5	that	that	SCONJ
esrj-37073	171	6	chaos	chaos	NOUN
esrj-37073	171	7	theory	theory	NOUN
esrj-37073	171	8	could	could	AUX
esrj-37073	171	9	be	be	AUX
esrj-37073	171	10	used	use	VERB
esrj-37073	171	11	in	in	ADP
esrj-37073	171	12	simplifying	simplify	VERB
esrj-37073	171	13	the	the	DET
esrj-37073	171	14	modeling	modeling	NOUN
esrj-37073	171	15	procedure	procedure	NOUN
esrj-37073	171	16	,	,	PUNCT
esrj-37073	171	17	in	in	ADP
esrj-37073	171	18	which	which	PRON
esrj-37073	171	19	the	the	DET
esrj-37073	171	20	determination	determination	NOUN
esrj-37073	171	21	of	of	ADP
esrj-37073	171	22	the	the	DET
esrj-37073	171	23	input	input	NOUN
esrj-37073	171	24	structure	structure	NOUN
esrj-37073	171	25	is	be	AUX
esrj-37073	171	26	rather	rather	ADV
esrj-37073	171	27	difficult	difficult	ADJ
esrj-37073	171	28	.	.	PUNCT
esrj-37073	172	1	5	5	X
esrj-37073	172	2	.	.	X
esrj-37073	172	3	conclusions	conclusion	NOUN
esrj-37073	172	4	hydrological	hydrological	ADJ
esrj-37073	172	5	systems	system	NOUN
esrj-37073	172	6	are	be	AUX
esrj-37073	172	7	complex	complex	ADJ
esrj-37073	172	8	and	and	CCONJ
esrj-37073	172	9	dynamic	dynamic	ADJ
esrj-37073	172	10	in	in	ADP
esrj-37073	172	11	nature	nature	NOUN
esrj-37073	172	12	as	as	SCONJ
esrj-37073	172	13	their	their	PRON
esrj-37073	172	14	current	current	ADJ
esrj-37073	172	15	and	and	CCONJ
esrj-37073	172	16	future	future	ADJ
esrj-37073	172	17	states	state	NOUN
esrj-37073	172	18	depend	depend	VERB
esrj-37073	172	19	on	on	ADP
esrj-37073	172	20	numerous	numerous	ADJ
esrj-37073	172	21	variables	variable	NOUN
esrj-37073	172	22	(	(	PUNCT
esrj-37073	172	23	tongal	tongal	PROPN
esrj-37073	172	24	et	et	PROPN
esrj-37073	172	25	al	al	PROPN
esrj-37073	172	26	.	.	PROPN
esrj-37073	172	27	,	,	PUNCT
esrj-37073	172	28	2013	2013	NUM
esrj-37073	172	29	)	)	PUNCT
esrj-37073	172	30	.	.	PUNCT
esrj-37073	173	1	therefore	therefore	ADV
esrj-37073	173	2	,	,	PUNCT
esrj-37073	173	3	it	it	PRON
esrj-37073	173	4	is	be	AUX
esrj-37073	173	5	important	important	ADJ
esrj-37073	173	6	to	to	PART
esrj-37073	173	7	determine	determine	VERB
esrj-37073	173	8	the	the	DET
esrj-37073	173	9	number	number	NOUN
esrj-37073	173	10	of	of	ADP
esrj-37073	173	11	dominant	dominant	ADJ
esrj-37073	173	12	variables	variable	NOUN
esrj-37073	173	13	acting	act	VERB
esrj-37073	173	14	within	within	ADP
esrj-37073	173	15	the	the	DET
esrj-37073	173	16	system	system	NOUN
esrj-37073	173	17	dynamics	dynamic	NOUN
esrj-37073	173	18	.	.	PUNCT
esrj-37073	174	1	in	in	ADP
esrj-37073	174	2	regards	regard	NOUN
esrj-37073	174	3	to	to	ADP
esrj-37073	174	4	this	this	PRON
esrj-37073	174	5	,	,	PUNCT
esrj-37073	174	6	the	the	DET
esrj-37073	174	7	methods	method	NOUN
esrj-37073	174	8	from	from	ADP
esrj-37073	174	9	chaos	chaos	NOUN
esrj-37073	174	10	theory	theory	NOUN
esrj-37073	174	11	provided	provide	VERB
esrj-37073	174	12	us	we	PRON
esrj-37073	174	13	a	a	DET
esrj-37073	174	14	proper	proper	ADJ
esrj-37073	174	15	framework	framework	NOUN
esrj-37073	174	16	.	.	PUNCT
esrj-37073	175	1	in	in	ADP
esrj-37073	175	2	this	this	DET
esrj-37073	175	3	study	study	NOUN
esrj-37073	175	4	,	,	PUNCT
esrj-37073	175	5	one	one	NUM
esrj-37073	175	6	of	of	ADP
esrj-37073	175	7	the	the	DET
esrj-37073	175	8	chaotic	chaotic	ADJ
esrj-37073	175	9	forecasting	forecasting	NOUN
esrj-37073	175	10	methods	method	NOUN
esrj-37073	175	11	,	,	PUNCT
esrj-37073	175	12	the	the	DET
esrj-37073	175	13	k	k	PROPN
esrj-37073	175	14	-	-	PUNCT
esrj-37073	175	15	nn	nn	PROPN
esrj-37073	175	16	method	method	NOUN
esrj-37073	175	17	,	,	PUNCT
esrj-37073	175	18	was	be	AUX
esrj-37073	175	19	employed	employ	VERB
esrj-37073	175	20	for	for	ADP
esrj-37073	175	21	the	the	DET
esrj-37073	175	22	kızılırmak	kızılırmak	PROPN
esrj-37073	175	23	river	river	PROPN
esrj-37073	175	24	,	,	PUNCT
esrj-37073	175	25	the	the	DET
esrj-37073	175	26	longest	long	ADJ
esrj-37073	175	27	river	river	NOUN
esrj-37073	175	28	in	in	ADP
esrj-37073	175	29	turkey	turkey	NOUN
esrj-37073	175	30	.	.	PUNCT
esrj-37073	176	1	the	the	DET
esrj-37073	176	2	necessary	necessary	ADJ
esrj-37073	176	3	parameters	parameter	NOUN
esrj-37073	176	4	for	for	ADP
esrj-37073	176	5	this	this	DET
esrj-37073	176	6	method	method	NOUN
esrj-37073	176	7	are	be	AUX
esrj-37073	176	8	the	the	DET
esrj-37073	176	9	delay	delay	NOUN
esrj-37073	176	10	time	time	NOUN
esrj-37073	176	11	,	,	PUNCT
esrj-37073	176	12	the	the	DET
esrj-37073	176	13	embedding	embed	VERB
esrj-37073	176	14	dimension	dimension	NOUN
esrj-37073	176	15	and	and	CCONJ
esrj-37073	176	16	the	the	DET
esrj-37073	176	17	nearest	near	ADJ
esrj-37073	176	18	neighbor	neighbor	ADJ
esrj-37073	176	19	number	number	NOUN
esrj-37073	176	20	.	.	PUNCT
esrj-37073	177	1	the	the	DET
esrj-37073	177	2	optimal	optimal	ADJ
esrj-37073	177	3	delay	delay	NOUN
esrj-37073	177	4	time	time	NOUN
esrj-37073	177	5	was	be	AUX
esrj-37073	177	6	determined	determine	VERB
esrj-37073	177	7	from	from	ADP
esrj-37073	177	8	the	the	DET
esrj-37073	177	9	mutual	mutual	ADJ
esrj-37073	177	10	information	information	NOUN
esrj-37073	177	11	function	function	NOUN
esrj-37073	177	12	and	and	CCONJ
esrj-37073	177	13	the	the	DET
esrj-37073	177	14	nearest	near	ADJ
esrj-37073	177	15	neighbor	neighbor	NOUN
esrj-37073	177	16	number	number	NOUN
esrj-37073	177	17	was	be	AUX
esrj-37073	177	18	determined	determine	VERB
esrj-37073	177	19	from	from	ADP
esrj-37073	177	20	the	the	DET
esrj-37073	177	21	optimization	optimization	NOUN
esrj-37073	177	22	process	process	NOUN
esrj-37073	177	23	that	that	PRON
esrj-37073	177	24	minimized	minimize	VERB
esrj-37073	177	25	rmse	rmse	NOUN
esrj-37073	177	26	as	as	ADP
esrj-37073	177	27	a	a	DET
esrj-37073	177	28	function	function	NOUN
esrj-37073	177	29	of	of	ADP
esrj-37073	177	30	the	the	DET
esrj-37073	177	31	nearest	near	ADJ
esrj-37073	177	32	neighbor	neighbor	ADJ
esrj-37073	177	33	number	number	NOUN
esrj-37073	177	34	.	.	PUNCT
esrj-37073	178	1	in	in	ADP
esrj-37073	178	2	determining	determine	VERB
esrj-37073	178	3	the	the	DET
esrj-37073	178	4	optimal	optimal	ADJ
esrj-37073	178	5	delay	delay	NOUN
esrj-37073	178	6	time	time	NOUN
esrj-37073	178	7	from	from	ADP
esrj-37073	178	8	the	the	DET
esrj-37073	178	9	mi	mi	PROPN
esrj-37073	178	10	function	function	NOUN
esrj-37073	178	11	,	,	PUNCT
esrj-37073	178	12	we	we	PRON
esrj-37073	178	13	calculated	calculate	VERB
esrj-37073	178	14	the	the	DET
esrj-37073	178	15	relative	relative	ADJ
esrj-37073	178	16	differences	difference	NOUN
esrj-37073	178	17	between	between	ADP
esrj-37073	178	18	the	the	DET
esrj-37073	178	19	successive	successive	ADJ
esrj-37073	178	20	values	value	NOUN
esrj-37073	178	21	of	of	ADP
esrj-37073	178	22	the	the	DET
esrj-37073	178	23	mi	mi	PROPN
esrj-37073	178	24	function	function	NOUN
esrj-37073	178	25	.	.	PUNCT
esrj-37073	179	1	the	the	DET
esrj-37073	179	2	optimal	optimal	ADJ
esrj-37073	179	3	delay	delay	NOUN
esrj-37073	179	4	time	time	NOUN
esrj-37073	179	5	was	be	AUX
esrj-37073	179	6	selected	select	VERB
esrj-37073	179	7	as	as	ADP
esrj-37073	179	8	30	30	NUM
esrj-37073	179	9	days	day	NOUN
esrj-37073	179	10	.	.	PUNCT
esrj-37073	180	1	to	to	PART
esrj-37073	180	2	determine	determine	VERB
esrj-37073	180	3	the	the	DET
esrj-37073	180	4	embedding	embed	VERB
esrj-37073	180	5	dimension	dimension	NOUN
esrj-37073	180	6	for	for	ADP
esrj-37073	180	7	the	the	DET
esrj-37073	180	8	k	k	PROPN
esrj-37073	180	9	-	-	PUNCT
esrj-37073	180	10	nn	nn	PROPN
esrj-37073	180	11	method	method	NOUN
esrj-37073	180	12	,	,	PUNCT
esrj-37073	180	13	the	the	DET
esrj-37073	180	14	correlation	correlation	NOUN
esrj-37073	180	15	integrals	integral	NOUN
esrj-37073	180	16	were	be	AUX
esrj-37073	180	17	calculated	calculate	VERB
esrj-37073	180	18	for	for	ADP
esrj-37073	180	19	various	various	ADJ
esrj-37073	180	20	embedding	embed	VERB
esrj-37073	180	21	dimensions	dimension	NOUN
esrj-37073	180	22	,	,	PUNCT
esrj-37073	180	23	i.e.	i.e.	X
esrj-37073	180	24	,	,	PUNCT
esrj-37073	180	25	1	1	NUM
esrj-37073	180	26	m	m	NOUN
esrj-37073	180	27	=	=	PUNCT
esrj-37073	180	28	to	to	ADP
esrj-37073	180	29	25	25	NUM
esrj-37073	180	30	m	m	NOUN
esrj-37073	180	31	=	=	NOUN
esrj-37073	180	32	.	.	PUNCT
esrj-37073	181	1	when	when	SCONJ
esrj-37073	181	2	the	the	DET
esrj-37073	181	3	obtained	obtain	VERB
esrj-37073	181	4	correlation	correlation	NOUN
esrj-37073	181	5	exponents	exponent	NOUN
esrj-37073	181	6	from	from	ADP
esrj-37073	181	7	the	the	DET
esrj-37073	181	8	correlation	correlation	NOUN
esrj-37073	181	9	integrals	integral	NOUN
esrj-37073	181	10	were	be	AUX
esrj-37073	181	11	plotted	plot	VERB
esrj-37073	181	12	as	as	ADP
esrj-37073	181	13	a	a	DET
esrj-37073	181	14	function	function	NOUN
esrj-37073	181	15	of	of	ADP
esrj-37073	181	16	the	the	DET
esrj-37073	181	17	embedding	embed	VERB
esrj-37073	181	18	dimension	dimension	NOUN
esrj-37073	181	19	,	,	PUNCT
esrj-37073	181	20	the	the	DET
esrj-37073	181	21	correlation	correlation	NOUN
esrj-37073	181	22	exponents	exponent	NOUN
esrj-37073	181	23	reached	reach	VERB
esrj-37073	181	24	a	a	DET
esrj-37073	181	25	value	value	NOUN
esrj-37073	181	26	(	(	PUNCT
esrj-37073	181	27	correlation	correlation	NOUN
esrj-37073	181	28	dimension	dimension	NOUN
esrj-37073	181	29	,	,	PUNCT
esrj-37073	181	30	2.702d	2.702d	NOUN
esrj-37073	181	31	=	=	SYM
esrj-37073	181	32	)	)	PUNCT
esrj-37073	181	33	,	,	PUNCT
esrj-37073	181	34	which	which	PRON
esrj-37073	181	35	gave	give	VERB
esrj-37073	181	36	us	we	PRON
esrj-37073	181	37	the	the	DET
esrj-37073	181	38	dimension	dimension	NOUN
esrj-37073	181	39	of	of	ADP
esrj-37073	181	40	the	the	DET
esrj-37073	181	41	system	system	NOUN
esrj-37073	181	42	.	.	PUNCT
esrj-37073	182	1	the	the	DET
esrj-37073	182	2	dimension	dimension	NOUN
esrj-37073	182	3	of	of	ADP
esrj-37073	182	4	the	the	DET
esrj-37073	182	5	system	system	NOUN
esrj-37073	182	6	shows	show	VERB
esrj-37073	182	7	the	the	DET
esrj-37073	182	8	number	number	NOUN
esrj-37073	182	9	of	of	ADP
esrj-37073	182	10	dominant	dominant	ADJ
esrj-37073	182	11	variables	variable	NOUN
esrj-37073	182	12	that	that	PRON
esrj-37073	182	13	are	be	AUX
esrj-37073	182	14	acting	act	VERB
esrj-37073	182	15	within	within	ADP
esrj-37073	182	16	the	the	DET
esrj-37073	182	17	system	system	NOUN
esrj-37073	182	18	dynamics	dynamic	NOUN
esrj-37073	182	19	.	.	PUNCT
esrj-37073	183	1	for	for	ADP
esrj-37073	183	2	this	this	DET
esrj-37073	183	3	system	system	NOUN
esrj-37073	183	4	,	,	PUNCT
esrj-37073	183	5	the	the	DET
esrj-37073	183	6	minimal	minimal	ADJ
esrj-37073	183	7	number	number	NOUN
esrj-37073	183	8	of	of	ADP
esrj-37073	183	9	dominant	dominant	ADJ
esrj-37073	183	10	variables	variable	NOUN
esrj-37073	183	11	was	be	AUX
esrj-37073	183	12	3	3	NUM
esrj-37073	183	13	(	(	PUNCT
esrj-37073	183	14	3	3	NUM
esrj-37073	183	15	2.702	2.702	NUM
esrj-37073	183	16	>	>	X
esrj-37073	183	17	)	)	PUNCT
esrj-37073	183	18	and	and	CCONJ
esrj-37073	183	19	the	the	DET
esrj-37073	183	20	maximum	maximum	NOUN
esrj-37073	183	21	was	be	AUX
esrj-37073	183	22	7	7	NUM
esrj-37073	183	23	(	(	PUNCT
esrj-37073	183	24	)	)	PUNCT
esrj-37073	183	25	.	.	PUNCT
esrj-37073	184	1	to	to	ADP
esrj-37073	184	2	the	the	DET
esrj-37073	184	3	author	author	NOUN
esrj-37073	184	4	’	'	PUNCT
esrj-37073	184	5	knowledge	knowledge	NOUN
esrj-37073	184	6	,	,	PUNCT
esrj-37073	184	7	this	this	DET
esrj-37073	184	8	study	study	NOUN
esrj-37073	184	9	is	be	AUX
esrj-37073	184	10	the	the	DET
esrj-37073	184	11	first	first	ADJ
esrj-37073	184	12	to	to	PART
esrj-37073	184	13	examine	examine	VERB
esrj-37073	184	14	whether	whether	SCONJ
esrj-37073	184	15	the	the	DET
esrj-37073	184	16	obtained	obtain	VERB
esrj-37073	184	17	correlation	correlation	NOUN
esrj-37073	184	18	dimension	dimension	NOUN
esrj-37073	184	19	could	could	AUX
esrj-37073	184	20	be	be	AUX
esrj-37073	184	21	used	use	VERB
esrj-37073	184	22	in	in	ADP
esrj-37073	184	23	the	the	DET
esrj-37073	184	24	model	model	NOUN
esrj-37073	184	25	development	development	NOUN
esrj-37073	184	26	phase	phase	NOUN
esrj-37073	184	27	.	.	PUNCT
esrj-37073	185	1	in	in	ADP
esrj-37073	185	2	feed	feed	NOUN
esrj-37073	185	3	-	-	PUNCT
esrj-37073	185	4	forward	forward	ADV
esrj-37073	185	5	neural	neural	ADJ
esrj-37073	185	6	network	network	NOUN
esrj-37073	185	7	input	input	NOUN
esrj-37073	185	8	parameter	parameter	NOUN
esrj-37073	185	9	determination	determination	NOUN
esrj-37073	185	10	,	,	PUNCT
esrj-37073	185	11	the	the	DET
esrj-37073	185	12	two	two	NUM
esrj-37073	185	13	models	model	NOUN
esrj-37073	185	14	(	(	PUNCT
esrj-37073	185	15	ffnn	ffnn	NOUN
esrj-37073	185	16	-	-	PUNCT
esrj-37073	185	17	i	i	PRON
esrj-37073	185	18	and	and	CCONJ
esrj-37073	185	19	ffnn	ffnn	NOUN
esrj-37073	185	20	-	-	PUNCT
esrj-37073	185	21	ii	ii	NOUN
esrj-37073	185	22	)	)	PUNCT
esrj-37073	185	23	that	that	PRON
esrj-37073	185	24	were	be	AUX
esrj-37073	185	25	described	describe	VERB
esrj-37073	185	26	incorporated	incorporate	VERB
esrj-37073	185	27	lagged	lag	VERB
esrj-37073	185	28	discharge	discharge	NOUN
esrj-37073	185	29	values	value	NOUN
esrj-37073	185	30	of	of	ADP
esrj-37073	185	31	3	3	NUM
esrj-37073	185	32	and	and	CCONJ
esrj-37073	185	33	7	7	NUM
esrj-37073	185	34	,	,	PUNCT
esrj-37073	185	35	respectively	respectively	ADV
esrj-37073	185	36	.	.	PUNCT
esrj-37073	186	1	the	the	DET
esrj-37073	186	2	number	number	NOUN
esrj-37073	186	3	of	of	ADP
esrj-37073	186	4	hidden	hide	VERB
esrj-37073	186	5	layer	layer	NOUN
esrj-37073	186	6	neurons	neuron	NOUN
esrj-37073	186	7	was	be	AUX
esrj-37073	186	8	determined	determine	VERB
esrj-37073	186	9	from	from	ADP
esrj-37073	186	10	a	a	DET
esrj-37073	186	11	trial	trial	NOUN
esrj-37073	186	12	and	and	CCONJ
esrj-37073	186	13	error	error	NOUN
esrj-37073	186	14	process	process	NOUN
esrj-37073	186	15	that	that	PRON
esrj-37073	186	16	minimized	minimized	ADJ
esrj-37073	186	17	rmse	rmse	NOUN
esrj-37073	186	18	.	.	PUNCT
esrj-37073	187	1	the	the	DET
esrj-37073	187	2	predictions	prediction	NOUN
esrj-37073	187	3	obtained	obtain	VERB
esrj-37073	187	4	from	from	ADP
esrj-37073	187	5	the	the	DET
esrj-37073	187	6	models	model	NOUN
esrj-37073	187	7	showed	show	VERB
esrj-37073	187	8	that	that	SCONJ
esrj-37073	187	9	the	the	DET
esrj-37073	187	10	k	k	PROPN
esrj-37073	187	11	-	-	PUNCT
esrj-37073	187	12	nn	nn	PROPN
esrj-37073	187	13	model	model	NOUN
esrj-37073	187	14	,	,	PUNCT
esrj-37073	187	15	which	which	PRON
esrj-37073	187	16	is	be	AUX
esrj-37073	187	17	one	one	NUM
esrj-37073	187	18	of	of	ADP
esrj-37073	187	19	the	the	DET
esrj-37073	187	20	most	most	ADV
esrj-37073	187	21	commonly	commonly	ADV
esrj-37073	187	22	used	use	VERB
esrj-37073	187	23	chaotic	chaotic	ADJ
esrj-37073	187	24	prediction	prediction	NOUN
esrj-37073	187	25	approaches	approach	NOUN
esrj-37073	187	26	,	,	PUNCT
esrj-37073	187	27	was	be	AUX
esrj-37073	187	28	superior	superior	ADJ
esrj-37073	187	29	to	to	ADP
esrj-37073	187	30	the	the	DET
esrj-37073	187	31	ffnn	ffnn	NOUN
esrj-37073	187	32	models	model	NOUN
esrj-37073	187	33	,	,	PUNCT
esrj-37073	187	34	which	which	PRON
esrj-37073	187	35	are	be	AUX
esrj-37073	187	36	a	a	DET
esrj-37073	187	37	sub	sub	NOUN
esrj-37073	187	38	-	-	NOUN
esrj-37073	187	39	class	class	NOUN
esrj-37073	187	40	of	of	ADP
esrj-37073	187	41	another	another	DET
esrj-37073	187	42	nonlinear	nonlinear	ADJ
esrj-37073	187	43	prediction	prediction	NOUN
esrj-37073	187	44	approach	approach	NOUN
esrj-37073	187	45	,	,	PUNCT
esrj-37073	187	46	the	the	DET
esrj-37073	187	47	artificial	artificial	ADJ
esrj-37073	187	48	neural	neural	ADJ
esrj-37073	187	49	networks	network	NOUN
esrj-37073	187	50	.	.	PUNCT
esrj-37073	188	1	however	however	ADV
esrj-37073	188	2	,	,	PUNCT
esrj-37073	188	3	the	the	DET
esrj-37073	188	4	k	k	PROPN
esrj-37073	188	5	-	-	PUNCT
esrj-37073	188	6	nn	nn	PROPN
esrj-37073	188	7	model	model	NOUN
esrj-37073	188	8	failed	fail	VERB
esrj-37073	188	9	to	to	PART
esrj-37073	188	10	predict	predict	VERB
esrj-37073	188	11	the	the	DET
esrj-37073	188	12	peak	peak	NOUN
esrj-37073	188	13	flows	flow	VERB
esrj-37073	188	14	,	,	PUNCT
esrj-37073	188	15	in	in	ADP
esrj-37073	188	16	which	which	PRON
esrj-37073	188	17	the	the	DET
esrj-37073	188	18	ffnn	ffnn	NOUN
esrj-37073	188	19	demonstrated	demonstrate	VERB
esrj-37073	188	20	better	well	ADJ
esrj-37073	188	21	performance	performance	NOUN
esrj-37073	188	22	.	.	PUNCT
esrj-37073	189	1	therefore	therefore	ADV
esrj-37073	189	2	,	,	PUNCT
esrj-37073	189	3	the	the	DET
esrj-37073	189	4	k	k	PROPN
esrj-37073	189	5	-	-	PUNCT
esrj-37073	189	6	nn	nn	ADJ
esrj-37073	189	7	model	model	NOUN
esrj-37073	189	8	(	(	PUNCT
esrj-37073	189	9	with	with	ADP
esrj-37073	189	10	averaging	average	VERB
esrj-37073	189	11	method	method	NOUN
esrj-37073	189	12	)	)	PUNCT
esrj-37073	189	13	should	should	AUX
esrj-37073	189	14	not	not	PART
esrj-37073	189	15	be	be	AUX
esrj-37073	189	16	used	use	VERB
esrj-37073	189	17	,	,	PUNCT
esrj-37073	189	18	when	when	SCONJ
esrj-37073	189	19	peak	peak	NOUN
esrj-37073	189	20	flow	flow	NOUN
esrj-37073	189	21	forecasting	forecasting	NOUN
esrj-37073	189	22	is	be	AUX
esrj-37073	189	23	important	important	ADJ
esrj-37073	189	24	.	.	PUNCT
esrj-37073	190	1	additionally	additionally	ADV
esrj-37073	190	2	,	,	PUNCT
esrj-37073	190	3	the	the	DET
esrj-37073	190	4	results	result	NOUN
esrj-37073	190	5	showed	show	VERB
esrj-37073	190	6	that	that	SCONJ
esrj-37073	190	7	the	the	DET
esrj-37073	190	8	correlation	correlation	NOUN
esrj-37073	190	9	dimension	dimension	NOUN
esrj-37073	190	10	method	method	NOUN
esrj-37073	190	11	can	can	AUX
esrj-37073	190	12	successfully	successfully	ADV
esrj-37073	190	13	be	be	AUX
esrj-37073	190	14	used	use	VERB
esrj-37073	190	15	instead	instead	ADV
esrj-37073	190	16	of	of	ADP
esrj-37073	190	17	the	the	DET
esrj-37073	190	18	time	time	NOUN
esrj-37073	190	19	-	-	PUNCT
esrj-37073	190	20	consuming	consume	VERB
esrj-37073	190	21	trial	trial	NOUN
esrj-37073	190	22	and	and	CCONJ
esrj-37073	190	23	error	error	NOUN
esrj-37073	190	24	process	process	NOUN
esrj-37073	190	25	to	to	PART
esrj-37073	190	26	determine	determine	VERB
esrj-37073	190	27	input	input	NOUN
esrj-37073	190	28	parameters	parameter	NOUN
esrj-37073	190	29	for	for	ADP
esrj-37073	190	30	ann	ann	PROPN
esrj-37073	190	31	,	,	PUNCT
esrj-37073	190	32	where	where	SCONJ
esrj-37073	190	33	the	the	DET
esrj-37073	190	34	interdependency	interdependency	NOUN
esrj-37073	190	35	of	of	ADP
esrj-37073	190	36	time	time	NOUN
esrj-37073	190	37	series	series	NOUN
esrj-37073	190	38	is	be	AUX
esrj-37073	190	39	high	high	ADJ
esrj-37073	190	40	.	.	PUNCT
esrj-37073	191	1	references	reference	NOUN
esrj-37073	191	2	abarbanel	abarbanel	NOUN
esrj-37073	191	3	,	,	PUNCT
esrj-37073	191	4	h.d.i	h.d.i	NOUN
esrj-37073	191	5	.	.	PUNCT
esrj-37073	191	6	,	,	PUNCT
esrj-37073	191	7	brown	brown	PROPN
esrj-37073	191	8	,	,	PUNCT
esrj-37073	191	9	r.	r.	PROPN
esrj-37073	191	10	and	and	CCONJ
esrj-37073	191	11	kadtke	kadtke	PROPN
esrj-37073	191	12	,	,	PUNCT
esrj-37073	191	13	j.b	j.b	PROPN
esrj-37073	191	14	.	.	PROPN
esrj-37073	191	15	,	,	PUNCT
esrj-37073	191	16	(	(	PUNCT
esrj-37073	191	17	1990	1990	NUM
esrj-37073	191	18	)	)	PUNCT
esrj-37073	191	19	.	.	PUNCT
esrj-37073	192	1	prediction	prediction	NOUN
esrj-37073	192	2	in	in	ADP
esrj-37073	192	3	chaotic	chaotic	ADJ
esrj-37073	192	4	nonlinear	nonlinear	ADJ
esrj-37073	192	5	systems	system	NOUN
esrj-37073	192	6	:	:	PUNCT
esrj-37073	192	7	methods	method	NOUN
esrj-37073	192	8	for	for	ADP
esrj-37073	192	9	time	time	NOUN
esrj-37073	192	10	series	series	NOUN
esrj-37073	192	11	with	with	ADP
esrj-37073	192	12	broadband	broadband	NOUN
esrj-37073	192	13	fourier	fourier	X
esrj-37073	192	14	spectra	spectra	PROPN
esrj-37073	192	15	.	.	PUNCT
esrj-37073	193	1	physical	physical	PROPN
esrj-37073	193	2	review	review	PROPN
esrj-37073	193	3	a	a	PRON
esrj-37073	193	4	,	,	PUNCT
esrj-37073	193	5	41	41	NUM
esrj-37073	193	6	:	:	SYM
esrj-37073	193	7	1782	1782	NUM
esrj-37073	193	8	-	-	SYM
esrj-37073	193	9	1807	1807	NUM
esrj-37073	193	10	.	.	PUNCT
esrj-37073	194	1	al	al	PROPN
esrj-37073	194	2	-	-	PUNCT
esrj-37073	194	3	awadhi	awadhi	PROPN
esrj-37073	194	4	,	,	PUNCT
esrj-37073	194	5	s.	s.	PROPN
esrj-37073	194	6	and	and	CCONJ
esrj-37073	194	7	jolliffe	jolliffe	PROPN
esrj-37073	194	8	,	,	PUNCT
esrj-37073	194	9	i.	i.	PROPN
esrj-37073	194	10	,	,	PUNCT
esrj-37073	194	11	(	(	PUNCT
esrj-37073	194	12	1998	1998	NUM
esrj-37073	194	13	)	)	PUNCT
esrj-37073	194	14	.	.	PUNCT
esrj-37073	195	1	time	time	NOUN
esrj-37073	195	2	series	series	PROPN
esrj-37073	195	3	modelling	modelling	NOUN
esrj-37073	195	4	of	of	ADP
esrj-37073	195	5	surface	surface	NOUN
esrj-37073	195	6	pressure	pressure	NOUN
esrj-37073	195	7	data	datum	NOUN
esrj-37073	195	8	.	.	PUNCT
esrj-37073	196	1	international	international	ADJ
esrj-37073	196	2	journal	journal	PROPN
esrj-37073	196	3	of	of	ADP
esrj-37073	196	4	climatology	climatology	NOUN
esrj-37073	196	5	,	,	PUNCT
esrj-37073	196	6	18	18	NUM
esrj-37073	196	7	:	:	SYM
esrj-37073	196	8	443	443	NUM
esrj-37073	196	9	-	-	SYM
esrj-37073	196	10	455	455	NUM
esrj-37073	196	11	.	.	PUNCT
esrj-37073	197	1	aqil	aqil	PROPN
esrj-37073	197	2	,	,	PUNCT
esrj-37073	197	3	m.	m.	NOUN
esrj-37073	197	4	,	,	PUNCT
esrj-37073	197	5	kita	kita	PROPN
esrj-37073	197	6	,	,	PUNCT
esrj-37073	197	7	i.	i.	PROPN
esrj-37073	197	8	,	,	PUNCT
esrj-37073	197	9	yano	yano	PROPN
esrj-37073	197	10	,	,	PUNCT
esrj-37073	197	11	a.	a.	NOUN
esrj-37073	197	12	and	and	CCONJ
esrj-37073	197	13	nishiyama	nishiyama	NOUN
esrj-37073	197	14	,	,	PUNCT
esrj-37073	197	15	s.	s.	PROPN
esrj-37073	197	16	,	,	PUNCT
esrj-37073	197	17	(	(	PUNCT
esrj-37073	197	18	2007	2007	NUM
esrj-37073	197	19	)	)	PUNCT
esrj-37073	197	20	.	.	PUNCT
esrj-37073	198	1	a	a	DET
esrj-37073	198	2	comparative	comparative	ADJ
esrj-37073	198	3	study	study	NOUN
esrj-37073	198	4	of	of	ADP
esrj-37073	198	5	artificial	artificial	ADJ
esrj-37073	198	6	neural	neural	ADJ
esrj-37073	198	7	networks	network	NOUN
esrj-37073	198	8	and	and	CCONJ
esrj-37073	198	9	neuro	neuro	NOUN
esrj-37073	198	10	-	-	PUNCT
esrj-37073	198	11	fuzzy	fuzzy	ADJ
esrj-37073	198	12	in	in	ADP
esrj-37073	198	13	continuous	continuous	ADJ
esrj-37073	198	14	modeling	modeling	NOUN
esrj-37073	198	15	of	of	ADP
esrj-37073	198	16	the	the	DET
esrj-37073	198	17	daily	daily	ADJ
esrj-37073	198	18	and	and	CCONJ
esrj-37073	198	19	hourly	hourly	ADJ
esrj-37073	198	20	behaviour	behaviour	NOUN
esrj-37073	198	21	of	of	ADP
esrj-37073	198	22	runoff	runoff	NOUN
esrj-37073	198	23	.	.	PUNCT
esrj-37073	199	1	journal	journal	PROPN
esrj-37073	199	2	of	of	ADP
esrj-37073	199	3	hydrology	hydrology	NOUN
esrj-37073	199	4	,	,	PUNCT
esrj-37073	199	5	337(1–2	337(1–2	NUM
esrj-37073	199	6	):	):	PUNCT
esrj-37073	199	7	22	22	NUM
esrj-37073	199	8	-	-	SYM
esrj-37073	199	9	34	34	NUM
esrj-37073	199	10	.	.	PUNCT
esrj-37073	200	1	araghinejad	araghinejad	PROPN
esrj-37073	200	2	,	,	PUNCT
esrj-37073	200	3	s.	s.	PROPN
esrj-37073	200	4	,	,	PUNCT
esrj-37073	200	5	azmi	azmi	PROPN
esrj-37073	200	6	,	,	PUNCT
esrj-37073	200	7	m.	m.	NOUN
esrj-37073	200	8	and	and	CCONJ
esrj-37073	200	9	kholghi	kholghi	PROPN
esrj-37073	200	10	,	,	PUNCT
esrj-37073	200	11	m.	m.	NOUN
esrj-37073	200	12	,	,	PUNCT
esrj-37073	200	13	(	(	PUNCT
esrj-37073	200	14	2011	2011	NUM
esrj-37073	200	15	)	)	PUNCT
esrj-37073	200	16	.	.	PUNCT
esrj-37073	201	1	application	application	NOUN
esrj-37073	201	2	of	of	ADP
esrj-37073	201	3	artificial	artificial	ADJ
esrj-37073	201	4	neural	neural	ADJ
esrj-37073	201	5	network	network	NOUN
esrj-37073	201	6	ensembles	ensemble	NOUN
esrj-37073	201	7	in	in	ADP
esrj-37073	201	8	probabilistic	probabilistic	ADJ
esrj-37073	201	9	hydrological	hydrological	ADJ
esrj-37073	201	10	forecasting	forecasting	NOUN
esrj-37073	201	11	.	.	PUNCT
esrj-37073	202	1	journal	journal	PROPN
esrj-37073	202	2	of	of	ADP
esrj-37073	202	3	hydrology	hydrology	NOUN
esrj-37073	202	4	,	,	PUNCT
esrj-37073	202	5	407(1	407(1	NUM
esrj-37073	202	6	-	-	SYM
esrj-37073	202	7	4	4	NUM
esrj-37073	202	8	):	):	PUNCT
esrj-37073	202	9	94	94	NUM
esrj-37073	202	10	-	-	SYM
esrj-37073	202	11	104	104	NUM
esrj-37073	202	12	.	.	PUNCT
esrj-37073	203	1	banerjee	banerjee	PROPN
esrj-37073	203	2	,	,	PUNCT
esrj-37073	203	3	p.	p.	NOUN
esrj-37073	203	4	,	,	PUNCT
esrj-37073	203	5	singh	singh	PROPN
esrj-37073	203	6	,	,	PUNCT
esrj-37073	203	7	v.s.	v.s.	ADJ
esrj-37073	203	8	,	,	PUNCT
esrj-37073	203	9	chatttopadhyay	chatttopadhyay	PROPN
esrj-37073	203	10	,	,	PUNCT
esrj-37073	203	11	k.	k.	PROPN
esrj-37073	203	12	,	,	PUNCT
esrj-37073	203	13	chandra	chandra	PROPN
esrj-37073	203	14	,	,	PUNCT
esrj-37073	203	15	p.c	p.c	PROPN
esrj-37073	203	16	.	.	PROPN
esrj-37073	203	17	and	and	CCONJ
esrj-37073	203	18	singh	singh	PROPN
esrj-37073	203	19	,	,	PUNCT
esrj-37073	203	20	b.	b.	PROPN
esrj-37073	203	21	,	,	PUNCT
esrj-37073	203	22	(	(	PUNCT
esrj-37073	203	23	2011	2011	NUM
esrj-37073	203	24	)	)	PUNCT
esrj-37073	203	25	.	.	PUNCT
esrj-37073	204	1	artificial	artificial	ADJ
esrj-37073	204	2	neural	neural	ADJ
esrj-37073	204	3	network	network	NOUN
esrj-37073	204	4	model	model	NOUN
esrj-37073	204	5	as	as	ADP
esrj-37073	204	6	a	a	DET
esrj-37073	204	7	potential	potential	ADJ
esrj-37073	204	8	alternative	alternative	NOUN
esrj-37073	204	9	for	for	ADP
esrj-37073	204	10	groundwater	groundwater	NOUN
esrj-37073	204	11	salinity	salinity	NOUN
esrj-37073	204	12	forecasting	forecasting	NOUN
esrj-37073	204	13	.	.	PUNCT
esrj-37073	205	1	journal	journal	NOUN
esrj-37073	205	2	of	of	ADP
esrj-37073	205	3	hydrology	hydrology	NOUN
esrj-37073	205	4	,	,	PUNCT
esrj-37073	205	5	398(3–4	398(3–4	NUM
esrj-37073	205	6	):	):	PUNCT
esrj-37073	205	7	212	212	NUM
esrj-37073	205	8	-	-	SYM
esrj-37073	205	9	220	220	NUM
esrj-37073	205	10	.	.	PUNCT
esrj-37073	206	1	chang	chang	PROPN
esrj-37073	206	2	,	,	PUNCT
esrj-37073	206	3	f.j	f.j	PROPN
esrj-37073	206	4	.	.	PROPN
esrj-37073	206	5	,	,	PUNCT
esrj-37073	206	6	chang	chang	PROPN
esrj-37073	206	7	,	,	PUNCT
esrj-37073	206	8	l.-c	l.-c	PROPN
esrj-37073	206	9	.	.	PUNCT
esrj-37073	207	1	and	and	CCONJ
esrj-37073	207	2	huang	huang	PROPN
esrj-37073	207	3	,	,	PUNCT
esrj-37073	207	4	h.-l	h.-l	PROPN
esrj-37073	207	5	.	.	PUNCT
esrj-37073	207	6	,	,	PUNCT
esrj-37073	207	7	(	(	PUNCT
esrj-37073	207	8	2002	2002	NUM
esrj-37073	207	9	)	)	PUNCT
esrj-37073	207	10	.	.	PUNCT
esrj-37073	208	1	real	real	ADJ
esrj-37073	208	2	-	-	PUNCT
esrj-37073	208	3	time	time	NOUN
esrj-37073	208	4	recurrent	recurrent	ADJ
esrj-37073	208	5	learning	learn	VERB
esrj-37073	208	6	neural	neural	ADJ
esrj-37073	208	7	network	network	NOUN
esrj-37073	208	8	for	for	ADP
esrj-37073	208	9	stream	stream	NOUN
esrj-37073	208	10	-	-	PUNCT
esrj-37073	208	11	flow	flow	NOUN
esrj-37073	208	12	forecasting	forecasting	NOUN
esrj-37073	208	13	.	.	PUNCT
esrj-37073	209	1	hydrological	hydrological	ADJ
esrj-37073	209	2	processes	process	NOUN
esrj-37073	209	3	,	,	PUNCT
esrj-37073	209	4	16(13	16(13	NUM
esrj-37073	209	5	):	):	PUNCT
esrj-37073	209	6	2577	2577	NUM
esrj-37073	209	7	-	-	SYM
esrj-37073	209	8	2588	2588	NUM
esrj-37073	209	9	.	.	PUNCT
esrj-37073	210	1	chen	chen	PROPN
esrj-37073	210	2	,	,	PUNCT
esrj-37073	210	3	c.s	c.s	PROPN
esrj-37073	210	4	.	.	PROPN
esrj-37073	210	5	,	,	PUNCT
esrj-37073	210	6	liu	liu	PROPN
esrj-37073	210	7	,	,	PUNCT
esrj-37073	210	8	c.h	c.h	PROPN
esrj-37073	210	9	.	.	PROPN
esrj-37073	210	10	and	and	CCONJ
esrj-37073	210	11	su	su	PROPN
esrj-37073	210	12	,	,	PUNCT
esrj-37073	210	13	h.c	h.c	PROPN
esrj-37073	210	14	.	.	PROPN
esrj-37073	210	15	,	,	PUNCT
esrj-37073	210	16	(	(	PUNCT
esrj-37073	210	17	2008	2008	NUM
esrj-37073	210	18	)	)	PUNCT
esrj-37073	210	19	.	.	PUNCT
esrj-37073	211	1	a	a	DET
esrj-37073	211	2	nonlinear	nonlinear	ADJ
esrj-37073	211	3	time	time	NOUN
esrj-37073	211	4	series	series	NOUN
esrj-37073	211	5	analysis	analysis	NOUN
esrj-37073	211	6	using	use	VERB
esrj-37073	211	7	two	two	NUM
esrj-37073	211	8	-	-	PUNCT
esrj-37073	211	9	stage	stage	NOUN
esrj-37073	211	10	genetic	genetic	ADJ
esrj-37073	211	11	algorithms	algorithm	NOUN
esrj-37073	211	12	for	for	ADP
esrj-37073	211	13	streamflow	streamflow	NOUN
esrj-37073	211	14	forecasting	forecasting	NOUN
esrj-37073	211	15	.	.	PUNCT
esrj-37073	212	1	hydrological	hydrological	ADJ
esrj-37073	212	2	processes	process	NOUN
esrj-37073	212	3	,	,	PUNCT
esrj-37073	212	4	22	22	NUM
esrj-37073	212	5	:	:	SYM
esrj-37073	212	6	3697	3697	NUM
esrj-37073	212	7	-	-	SYM
esrj-37073	212	8	3711	3711	NUM
esrj-37073	212	9	.	.	PUNCT
esrj-37073	213	1	çakmak	çakmak	PROPN
esrj-37073	213	2	,	,	PUNCT
esrj-37073	213	3	b.	b.	PROPN
esrj-37073	213	4	,	,	PUNCT
esrj-37073	213	5	kendirli	kendirli	PROPN
esrj-37073	213	6	,	,	PUNCT
esrj-37073	213	7	b.	b.	PROPN
esrj-37073	213	8	and	and	CCONJ
esrj-37073	213	9	ucar	ucar	PROPN
esrj-37073	213	10	,	,	PUNCT
esrj-37073	213	11	y.	y.	PROPN
esrj-37073	213	12	,	,	PUNCT
esrj-37073	213	13	(	(	PUNCT
esrj-37073	213	14	2007	2007	NUM
esrj-37073	213	15	)	)	PUNCT
esrj-37073	213	16	.	.	PUNCT
esrj-37073	214	1	evaluation	evaluation	NOUN
esrj-37073	214	2	of	of	ADP
esrj-37073	214	3	agricultural	agricultural	ADJ
esrj-37073	214	4	water	water	NOUN
esrj-37073	214	5	use	use	NOUN
esrj-37073	214	6	:	:	PUNCT
esrj-37073	214	7	a	a	DET
esrj-37073	214	8	case	case	NOUN
esrj-37073	214	9	study	study	NOUN
esrj-37073	214	10	for	for	ADP
esrj-37073	214	11	kizilirmak	kizilirmak	PROPN
esrj-37073	214	12	.	.	PUNCT
esrj-37073	215	1	journal	journal	PROPN
esrj-37073	215	2	of	of	ADP
esrj-37073	215	3	tekirdag	tekirdag	PROPN
esrj-37073	215	4	agricultural	agricultural	ADJ
esrj-37073	215	5	faculty	faculty	NOUN
esrj-37073	215	6	,	,	PUNCT
esrj-37073	215	7	4(2	4(2	NUM
esrj-37073	215	8	):	):	PUNCT
esrj-37073	215	9	175	175	NUM
esrj-37073	215	10	-	-	SYM
esrj-37073	215	11	185	185	NUM
esrj-37073	215	12	.	.	PUNCT
esrj-37073	216	1	daliakopoulos	daliakopoulo	NOUN
esrj-37073	216	2	,	,	PUNCT
esrj-37073	216	3	i.n	i.n	PROPN
esrj-37073	216	4	.	.	PROPN
esrj-37073	216	5	,	,	PUNCT
esrj-37073	216	6	coulibaly	coulibaly	NOUN
esrj-37073	216	7	,	,	PUNCT
esrj-37073	216	8	p.	p.	NOUN
esrj-37073	216	9	and	and	CCONJ
esrj-37073	216	10	tsanis	tsani	NOUN
esrj-37073	216	11	,	,	PUNCT
esrj-37073	216	12	i.k	i.k	PROPN
esrj-37073	216	13	.	.	PROPN
esrj-37073	216	14	,	,	PUNCT
esrj-37073	216	15	(	(	PUNCT
esrj-37073	216	16	2005	2005	NUM
esrj-37073	216	17	)	)	PUNCT
esrj-37073	216	18	.	.	PUNCT
esrj-37073	217	1	groundwater	groundwater	NOUN
esrj-37073	217	2	level	level	NOUN
esrj-37073	217	3	forecasting	forecasting	NOUN
esrj-37073	217	4	using	use	VERB
esrj-37073	217	5	artificial	artificial	ADJ
esrj-37073	217	6	neural	neural	ADJ
esrj-37073	217	7	networks	network	NOUN
esrj-37073	217	8	.	.	PUNCT
esrj-37073	218	1	journal	journal	NOUN
esrj-37073	218	2	of	of	ADP
esrj-37073	218	3	hydrology	hydrology	NOUN
esrj-37073	218	4	,	,	PUNCT
esrj-37073	218	5	309(1–4	309(1–4	NUM
esrj-37073	218	6	):	):	PUNCT
esrj-37073	218	7	229	229	NUM
esrj-37073	218	8	-	-	SYM
esrj-37073	218	9	240	240	NUM
esrj-37073	218	10	.	.	PUNCT
esrj-37073	219	1	deka	deka	PROPN
esrj-37073	219	2	,	,	PUNCT
esrj-37073	219	3	p.c	p.c	PROPN
esrj-37073	219	4	.	.	PROPN
esrj-37073	219	5	,	,	PUNCT
esrj-37073	219	6	haque	haque	PROPN
esrj-37073	219	7	,	,	PUNCT
esrj-37073	219	8	l.	l.	PROPN
esrj-37073	219	9	and	and	CCONJ
esrj-37073	219	10	banhatti	banhatti	PROPN
esrj-37073	219	11	,	,	PUNCT
esrj-37073	219	12	a.g	a.g	PROPN
esrj-37073	219	13	.	.	PROPN
esrj-37073	219	14	,	,	PUNCT
esrj-37073	219	15	(	(	PUNCT
esrj-37073	219	16	2012	2012	NUM
esrj-37073	219	17	)	)	PUNCT
esrj-37073	219	18	.	.	PUNCT
esrj-37073	220	1	discrete	discrete	ADJ
esrj-37073	220	2	wavelet	wavelet	NOUN
esrj-37073	220	3	-	-	PUNCT
esrj-37073	220	4	ann	ann	PROPN
esrj-37073	220	5	approach	approach	NOUN
esrj-37073	220	6	in	in	ADP
esrj-37073	220	7	time	time	NOUN
esrj-37073	220	8	series	series	PROPN
esrj-37073	220	9	flow	flow	PROPN
esrj-37073	220	10	forecasting	forecasting	NOUN
esrj-37073	220	11	-	-	PUNCT
esrj-37073	220	12	a	a	DET
esrj-37073	220	13	case	case	NOUN
esrj-37073	220	14	study	study	NOUN
esrj-37073	220	15	of	of	ADP
esrj-37073	220	16	brahmaputra	brahmaputra	PROPN
esrj-37073	220	17	river	river	PROPN
esrj-37073	220	18	.	.	PUNCT
esrj-37073	221	1	international	international	ADJ
esrj-37073	221	2	journal	journal	PROPN
esrj-37073	221	3	of	of	ADP
esrj-37073	221	4	earth	earth	PROPN
esrj-37073	221	5	sciences	science	NOUN
esrj-37073	221	6	and	and	CCONJ
esrj-37073	221	7	engineering	engineering	NOUN
esrj-37073	221	8	,	,	PUNCT
esrj-37073	221	9	5(4	5(4	NUM
esrj-37073	221	10	):	):	PUNCT
esrj-37073	221	11	673	673	NUM
esrj-37073	221	12	-	-	SYM
esrj-37073	221	13	685	685	NUM
esrj-37073	221	14	.	.	PUNCT
esrj-37073	222	1	dhanya	dhanya	NOUN
esrj-37073	222	2	,	,	PUNCT
esrj-37073	222	3	c.t	c.t	PROPN
esrj-37073	222	4	.	.	PROPN
esrj-37073	222	5	and	and	CCONJ
esrj-37073	222	6	kumar	kumar	PROPN
esrj-37073	222	7	,	,	PUNCT
esrj-37073	222	8	d.n	d.n	PROPN
esrj-37073	222	9	.	.	PROPN
esrj-37073	222	10	,	,	PUNCT
esrj-37073	222	11	(	(	PUNCT
esrj-37073	222	12	2011	2011	NUM
esrj-37073	222	13	)	)	PUNCT
esrj-37073	222	14	.	.	PUNCT
esrj-37073	223	1	multivariate	multivariate	VERB
esrj-37073	223	2	nonlinear	nonlinear	ADJ
esrj-37073	223	3	ensemble	ensemble	ADJ
esrj-37073	223	4	prediction	prediction	NOUN
esrj-37073	223	5	of	of	ADP
esrj-37073	223	6	daily	daily	ADJ
esrj-37073	223	7	chaotic	chaotic	ADJ
esrj-37073	223	8	rainfall	rainfall	NOUN
esrj-37073	223	9	with	with	ADP
esrj-37073	223	10	climate	climate	NOUN
esrj-37073	223	11	inputs	input	NOUN
esrj-37073	223	12	.	.	PUNCT
esrj-37073	224	1	journal	journal	NOUN
esrj-37073	224	2	of	of	ADP
esrj-37073	224	3	hydrology	hydrology	NOUN
esrj-37073	224	4	,	,	PUNCT
esrj-37073	224	5	403	403	NUM
esrj-37073	224	6	:	:	PUNCT
esrj-37073	224	7	292	292	NUM
esrj-37073	224	8	-	-	SYM
esrj-37073	224	9	306	306	NUM
esrj-37073	224	10	.	.	PUNCT
esrj-37073	225	1	elshorbagy	elshorbagy	PROPN
esrj-37073	225	2	,	,	PUNCT
esrj-37073	225	3	a.	a.	NOUN
esrj-37073	225	4	,	,	PUNCT
esrj-37073	225	5	simonovic	simonovic	VERB
esrj-37073	225	6	,	,	PUNCT
esrj-37073	225	7	s.p	s.p	PROPN
esrj-37073	225	8	.	.	PROPN
esrj-37073	225	9	and	and	CCONJ
esrj-37073	225	10	panu	panu	PROPN
esrj-37073	225	11	,	,	PUNCT
esrj-37073	225	12	u.s	u.s	PROPN
esrj-37073	225	13	.	.	PROPN
esrj-37073	225	14	,	,	PUNCT
esrj-37073	225	15	(	(	PUNCT
esrj-37073	225	16	2002	2002	NUM
esrj-37073	225	17	)	)	PUNCT
esrj-37073	225	18	.	.	PUNCT
esrj-37073	226	1	estimation	estimation	NOUN
esrj-37073	226	2	of	of	ADP
esrj-37073	226	3	missing	miss	VERB
esrj-37073	226	4	streamflow	streamflow	NOUN
esrj-37073	226	5	data	datum	NOUN
esrj-37073	226	6	using	use	VERB
esrj-37073	226	7	principles	principle	NOUN
esrj-37073	226	8	of	of	ADP
esrj-37073	226	9	chaos	chaos	NOUN
esrj-37073	226	10	theory	theory	NOUN
esrj-37073	226	11	.	.	PUNCT
esrj-37073	227	1	journal	journal	PROPN
esrj-37073	227	2	of	of	ADP
esrj-37073	227	3	hydrology	hydrology	NOUN
esrj-37073	227	4	,	,	PUNCT
esrj-37073	227	5	255(1–4	255(1–4	NUM
esrj-37073	227	6	):	):	PUNCT
esrj-37073	227	7	123	123	NUM
esrj-37073	227	8	-	-	SYM
esrj-37073	227	9	133	133	NUM
esrj-37073	227	10	.	.	PUNCT
esrj-37073	228	1	farmer	farmer	NOUN
esrj-37073	228	2	,	,	PUNCT
esrj-37073	228	3	d.j	d.j	PROPN
esrj-37073	228	4	.	.	PROPN
esrj-37073	228	5	and	and	CCONJ
esrj-37073	228	6	sidorowich	sidorowich	PROPN
esrj-37073	228	7	,	,	PUNCT
esrj-37073	228	8	j.j	j.j	PROPN
esrj-37073	228	9	.	.	PROPN
esrj-37073	228	10	,	,	PUNCT
esrj-37073	228	11	(	(	PUNCT
esrj-37073	228	12	1987	1987	NUM
esrj-37073	228	13	)	)	PUNCT
esrj-37073	228	14	.	.	PUNCT
esrj-37073	229	1	predicting	predict	VERB
esrj-37073	229	2	chaotic	chaotic	ADJ
esrj-37073	229	3	time	time	NOUN
esrj-37073	229	4	series	series	PROPN
esrj-37073	229	5	.	.	PUNCT
esrj-37073	230	1	physical	physical	ADJ
esrj-37073	230	2	review	review	NOUN
esrj-37073	230	3	letters	letter	NOUN
esrj-37073	230	4	,	,	PUNCT
esrj-37073	230	5	59	59	NUM
esrj-37073	230	6	:	:	PUNCT
esrj-37073	230	7	845	845	NUM
esrj-37073	230	8	-	-	SYM
esrj-37073	230	9	848	848	NUM
esrj-37073	230	10	.	.	PUNCT
esrj-37073	231	1	frazer	frazer	PROPN
esrj-37073	231	2	,	,	PUNCT
esrj-37073	231	3	a.m.	a.m.	PROPN
esrj-37073	231	4	and	and	CCONJ
esrj-37073	231	5	swinney	swinney	PROPN
esrj-37073	231	6	,	,	PUNCT
esrj-37073	231	7	h.l	h.l	PROPN
esrj-37073	231	8	.	.	PROPN
esrj-37073	231	9	,	,	PUNCT
esrj-37073	231	10	(	(	PUNCT
esrj-37073	231	11	1986	1986	NUM
esrj-37073	231	12	)	)	PUNCT
esrj-37073	231	13	.	.	PUNCT
esrj-37073	232	1	independent	independent	ADJ
esrj-37073	232	2	coordinates	coordinate	NOUN
esrj-37073	232	3	for	for	ADP
esrj-37073	232	4	strange	strange	ADJ
esrj-37073	232	5	attractors	attractor	NOUN
esrj-37073	232	6	from	from	ADP
esrj-37073	232	7	mutual	mutual	ADJ
esrj-37073	232	8	information	information	NOUN
esrj-37073	232	9	.	.	PUNCT
esrj-37073	233	1	physical	physical	ADJ
esrj-37073	233	2	review	review	PROPN
esrj-37073	233	3	a	a	DET
esrj-37073	233	4	,	,	PUNCT
esrj-37073	233	5	33(2	33(2	NUM
esrj-37073	233	6	):	):	PUNCT
esrj-37073	234	1	1134–1140	1134–1140	NUM
esrj-37073	234	2	.	.	PUNCT
esrj-37073	234	3	frison	frison	PROPN
esrj-37073	234	4	,	,	PUNCT
esrj-37073	234	5	t.	t.	PROPN
esrj-37073	234	6	,	,	PUNCT
esrj-37073	234	7	abarbanel	abarbanel	PROPN
esrj-37073	234	8	,	,	PUNCT
esrj-37073	234	9	h.	h.	PROPN
esrj-37073	234	10	,	,	PUNCT
esrj-37073	234	11	earle	earle	PROPN
esrj-37073	234	12	,	,	PUNCT
esrj-37073	234	13	m.	m.	NOUN
esrj-37073	234	14	,	,	PUNCT
esrj-37073	234	15	schultz	schultz	PROPN
esrj-37073	234	16	,	,	PUNCT
esrj-37073	234	17	j.	j.	PROPN
esrj-37073	234	18	and	and	CCONJ
esrj-37073	234	19	sheerer	sheer	ADJ
esrj-37073	234	20	,	,	PUNCT
esrj-37073	234	21	w.	w.	PROPN
esrj-37073	234	22	,	,	PUNCT
esrj-37073	234	23	(	(	PUNCT
esrj-37073	234	24	1999	1999	NUM
esrj-37073	234	25	)	)	PUNCT
esrj-37073	234	26	.	.	PUNCT
esrj-37073	235	1	chaos	chaos	NOUN
esrj-37073	235	2	and	and	CCONJ
esrj-37073	235	3	predictability	predictability	NOUN
esrj-37073	235	4	in	in	ADP
esrj-37073	235	5	ocean	ocean	NOUN
esrj-37073	235	6	water	water	NOUN
esrj-37073	235	7	level	level	NOUN
esrj-37073	235	8	measurements	measurement	NOUN
esrj-37073	235	9	.	.	PUNCT
esrj-37073	235	10	.	.	PUNCT
esrj-37073	236	1	journal	journal	PROPN
esrj-37073	236	2	nonlinear	nonlinear	PROPN
esrj-37073	236	3	forecasting	forecasting	NOUN
esrj-37073	236	4	of	of	ADP
esrj-37073	236	5	stream	stream	NOUN
esrj-37073	236	6	flows	flow	NOUN
esrj-37073	236	7	using	use	VERB
esrj-37073	236	8	a	a	DET
esrj-37073	236	9	chaotic	chaotic	ADJ
esrj-37073	236	10	approach	approach	NOUN
esrj-37073	236	11	and	and	CCONJ
esrj-37073	236	12	artificial	artificial	ADJ
esrj-37073	236	13	neural	neural	ADJ
esrj-37073	236	14	networks	network	NOUN
esrj-37073	236	15	126	126	NUM
esrj-37073	236	16	of	of	ADP
esrj-37073	236	17	geophysical	geophysical	ADJ
esrj-37073	236	18	research	research	NOUN
esrj-37073	236	19	oceans	ocean	NOUN
esrj-37073	236	20	,	,	PUNCT
esrj-37073	236	21	104	104	NUM
esrj-37073	236	22	:	:	SYM
esrj-37073	236	23	7935	7935	NUM
esrj-37073	236	24	-	-	SYM
esrj-37073	236	25	7951	7951	NUM
esrj-37073	236	26	.	.	PUNCT
esrj-37073	237	1	khokhlov	khokhlov	PROPN
esrj-37073	237	2	,	,	PUNCT
esrj-37073	237	3	v.	v.	PROPN
esrj-37073	237	4	,	,	PUNCT
esrj-37073	237	5	glushkov	glushkov	PROPN
esrj-37073	237	6	,	,	PUNCT
esrj-37073	237	7	a.	a.	PROPN
esrj-37073	237	8	,	,	PUNCT
esrj-37073	237	9	loboda	loboda	PROPN
esrj-37073	237	10	,	,	PUNCT
esrj-37073	237	11	n.	n.	NOUN
esrj-37073	237	12	,	,	PUNCT
esrj-37073	237	13	serbov	serbov	NOUN
esrj-37073	237	14	,	,	PUNCT
esrj-37073	237	15	n.	n.	NOUN
esrj-37073	237	16	and	and	CCONJ
esrj-37073	237	17	zhurbenko	zhurbenko	NOUN
esrj-37073	237	18	,	,	PUNCT
esrj-37073	237	19	k.	k.	PROPN
esrj-37073	237	20	,	,	PUNCT
esrj-37073	237	21	(	(	PUNCT
esrj-37073	237	22	2008	2008	NUM
esrj-37073	237	23	)	)	PUNCT
esrj-37073	237	24	.	.	PUNCT
esrj-37073	238	1	signatures	signature	NOUN
esrj-37073	238	2	of	of	ADP
esrj-37073	238	3	low	low	ADJ
esrj-37073	238	4	-	-	PUNCT
esrj-37073	238	5	dimensional	dimensional	ADJ
esrj-37073	238	6	chaos	chaos	NOUN
esrj-37073	238	7	in	in	ADP
esrj-37073	238	8	hourly	hourly	ADJ
esrj-37073	238	9	water	water	NOUN
esrj-37073	238	10	level	level	NOUN
esrj-37073	238	11	measurements	measurement	NOUN
esrj-37073	238	12	at	at	ADP
esrj-37073	238	13	coastal	coastal	ADJ
esrj-37073	238	14	site	site	NOUN
esrj-37073	238	15	of	of	ADP
esrj-37073	238	16	mariupol	mariupol	NOUN
esrj-37073	238	17	,	,	PUNCT
esrj-37073	238	18	ukraine	ukraine	NOUN
esrj-37073	238	19	.	.	PUNCT
esrj-37073	239	1	stochastic	stochastic	ADJ
esrj-37073	239	2	environmental	environmental	ADJ
esrj-37073	239	3	research	research	NOUN
esrj-37073	239	4	and	and	CCONJ
esrj-37073	239	5	risk	risk	NOUN
esrj-37073	239	6	assessment	assessment	NOUN
esrj-37073	239	7	22	22	NUM
esrj-37073	239	8	:	:	PUNCT
esrj-37073	239	9	777	777	NUM
esrj-37073	239	10	-	-	SYM
esrj-37073	239	11	787	787	NUM
esrj-37073	239	12	.	.	PUNCT
esrj-37073	240	1	kitanidis	kitanidis	PROPN
esrj-37073	240	2	,	,	PUNCT
esrj-37073	240	3	p.k	p.k	PROPN
esrj-37073	240	4	.	.	PROPN
esrj-37073	240	5	and	and	CCONJ
esrj-37073	240	6	bras	bras	PROPN
esrj-37073	240	7	,	,	PUNCT
esrj-37073	240	8	r.l	r.l	PROPN
esrj-37073	240	9	.	.	PROPN
esrj-37073	240	10	,	,	PUNCT
esrj-37073	240	11	(	(	PUNCT
esrj-37073	240	12	1980	1980	NUM
esrj-37073	240	13	)	)	PUNCT
esrj-37073	240	14	.	.	PUNCT
esrj-37073	241	1	real	real	ADJ
esrj-37073	241	2	-	-	PUNCT
esrj-37073	241	3	time	time	NOUN
esrj-37073	241	4	forecasting	forecasting	NOUN
esrj-37073	241	5	with	with	ADP
esrj-37073	241	6	a	a	DET
esrj-37073	241	7	conceptual	conceptual	ADJ
esrj-37073	241	8	hydrologic	hydrologic	NOUN
esrj-37073	241	9	model	model	NOUN
esrj-37073	241	10	2	2	NUM
esrj-37073	241	11	.	.	PUNCT
esrj-37073	241	12	applications	application	NOUN
esrj-37073	241	13	and	and	CCONJ
esrj-37073	241	14	results	result	NOUN
esrj-37073	241	15	,	,	PUNCT
esrj-37073	241	16	.	.	PUNCT
esrj-37073	242	1	water	water	NOUN
esrj-37073	242	2	resources	resource	NOUN
esrj-37073	242	3	research	research	NOUN
esrj-37073	242	4	,	,	PUNCT
esrj-37073	242	5	16	16	NUM
esrj-37073	242	6	:	:	SYM
esrj-37073	242	7	1034	1034	NUM
esrj-37073	242	8	-	-	SYM
esrj-37073	242	9	1044	1044	NUM
esrj-37073	242	10	.	.	PUNCT
esrj-37073	243	1	kuo	kuo	PROPN
esrj-37073	243	2	-	-	PUNCT
esrj-37073	243	3	lin	lin	PROPN
esrj-37073	243	4	,	,	PUNCT
esrj-37073	243	5	h.	h.	PROPN
esrj-37073	243	6	,	,	PUNCT
esrj-37073	243	7	(	(	PUNCT
esrj-37073	243	8	2011	2011	NUM
esrj-37073	243	9	)	)	PUNCT
esrj-37073	243	10	.	.	PUNCT
esrj-37073	244	1	hydrologic	hydrologic	NOUN
esrj-37073	244	2	forecasting	forecasting	NOUN
esrj-37073	244	3	using	use	VERB
esrj-37073	244	4	artificial	artificial	ADJ
esrj-37073	244	5	neural	neural	ADJ
esrj-37073	244	6	networks	network	NOUN
esrj-37073	244	7	:	:	PUNCT
esrj-37073	244	8	a	a	DET
esrj-37073	244	9	bayesian	bayesian	NOUN
esrj-37073	244	10	sequential	sequential	ADJ
esrj-37073	244	11	monte	monte	PROPN
esrj-37073	244	12	carlo	carlo	PROPN
esrj-37073	244	13	approach	approach	NOUN
esrj-37073	244	14	.	.	PUNCT
esrj-37073	245	1	journal	journal	NOUN
esrj-37073	245	2	of	of	ADP
esrj-37073	245	3	hydroinformatics	hydroinformatic	NOUN
esrj-37073	245	4	,	,	PUNCT
esrj-37073	245	5	13(1	13(1	NUM
esrj-37073	245	6	):	):	PUNCT
esrj-37073	245	7	25	25	NUM
esrj-37073	245	8	-	-	SYM
esrj-37073	245	9	35	35	NUM
esrj-37073	245	10	.	.	PUNCT
esrj-37073	246	1	laio	laio	PROPN
esrj-37073	246	2	,	,	PUNCT
esrj-37073	246	3	f.	f.	PROPN
esrj-37073	246	4	,	,	PUNCT
esrj-37073	246	5	porporato	porporato	PROPN
esrj-37073	246	6	,	,	PUNCT
esrj-37073	246	7	a.	a.	NOUN
esrj-37073	246	8	,	,	PUNCT
esrj-37073	246	9	revelli	revelli	PROPN
esrj-37073	246	10	,	,	PUNCT
esrj-37073	246	11	r.	r.	PROPN
esrj-37073	246	12	and	and	CCONJ
esrj-37073	246	13	ridolfi	ridolfi	NOUN
esrj-37073	246	14	,	,	PUNCT
esrj-37073	246	15	l.	l.	PROPN
esrj-37073	246	16	,	,	PUNCT
esrj-37073	246	17	(	(	PUNCT
esrj-37073	246	18	2003	2003	NUM
esrj-37073	246	19	)	)	PUNCT
esrj-37073	246	20	.	.	PUNCT
esrj-37073	247	1	a	a	DET
esrj-37073	247	2	comparison	comparison	NOUN
esrj-37073	247	3	of	of	ADP
esrj-37073	247	4	nonlinear	nonlinear	ADJ
esrj-37073	247	5	flood	flood	NOUN
esrj-37073	247	6	forecasting	forecasting	NOUN
esrj-37073	247	7	methods	method	NOUN
esrj-37073	247	8	.	.	PUNCT
esrj-37073	248	1	water	water	NOUN
esrj-37073	248	2	resources	resource	NOUN
esrj-37073	248	3	research	research	NOUN
esrj-37073	248	4	,	,	PUNCT
esrj-37073	248	5	39(5	39(5	NUM
esrj-37073	248	6	):	):	PUNCT
esrj-37073	248	7	1129	1129	NUM
esrj-37073	248	8	.	.	PUNCT
esrj-37073	249	1	lisi	lisi	PROPN
esrj-37073	249	2	,	,	PUNCT
esrj-37073	249	3	f.	f.	PROPN
esrj-37073	249	4	and	and	CCONJ
esrj-37073	249	5	villi	villi	NOUN
esrj-37073	249	6	,	,	PUNCT
esrj-37073	249	7	v.	v.	ADV
esrj-37073	249	8	,	,	PUNCT
esrj-37073	249	9	(	(	PUNCT
esrj-37073	249	10	2001	2001	NUM
esrj-37073	249	11	)	)	PUNCT
esrj-37073	249	12	.	.	PUNCT
esrj-37073	250	1	chaotic	chaotic	ADJ
esrj-37073	250	2	forecasting	forecasting	NOUN
esrj-37073	250	3	of	of	ADP
esrj-37073	250	4	discharge	discharge	NOUN
esrj-37073	250	5	time	time	NOUN
esrj-37073	250	6	series	series	NOUN
esrj-37073	250	7	:	:	PUNCT
esrj-37073	250	8	a	a	DET
esrj-37073	250	9	case	case	NOUN
esrj-37073	250	10	study	study	NOUN
esrj-37073	250	11	.	.	PUNCT
esrj-37073	251	1	journal	journal	NOUN
esrj-37073	251	2	of	of	ADP
esrj-37073	251	3	the	the	DET
esrj-37073	251	4	american	american	PROPN
esrj-37073	251	5	water	water	PROPN
esrj-37073	251	6	resources	resources	PROPN
esrj-37073	251	7	association	association	PROPN
esrj-37073	251	8	,	,	PUNCT
esrj-37073	251	9	37(2	37(2	PROPN
esrj-37073	251	10	):	):	PUNCT
esrj-37073	251	11	271	271	NUM
esrj-37073	251	12	-	-	SYM
esrj-37073	251	13	279	279	NUM
esrj-37073	251	14	.	.	PUNCT
esrj-37073	252	1	liu	liu	PROPN
esrj-37073	252	2	,	,	PUNCT
esrj-37073	252	3	q.	q.	PROPN
esrj-37073	252	4	,	,	PUNCT
esrj-37073	252	5	islam	islam	PROPN
esrj-37073	252	6	,	,	PUNCT
esrj-37073	252	7	s.	s.	PROPN
esrj-37073	252	8	,	,	PUNCT
esrj-37073	252	9	rodriguez	rodriguez	NOUN
esrj-37073	252	10	-	-	PUNCT
esrj-37073	252	11	iturbe	iturbe	PROPN
esrj-37073	252	12	,	,	PUNCT
esrj-37073	252	13	i.	i.	NOUN
esrj-37073	252	14	and	and	CCONJ
esrj-37073	252	15	le	le	PROPN
esrj-37073	252	16	,	,	PUNCT
esrj-37073	252	17	y.	y.	PROPN
esrj-37073	252	18	,	,	PUNCT
esrj-37073	252	19	(	(	PUNCT
esrj-37073	252	20	1998	1998	NUM
esrj-37073	252	21	)	)	PUNCT
esrj-37073	252	22	.	.	PUNCT
esrj-37073	253	1	phase	phase	NOUN
esrj-37073	253	2	-	-	PUNCT
esrj-37073	253	3	space	space	NOUN
esrj-37073	253	4	analysis	analysis	NOUN
esrj-37073	253	5	of	of	ADP
esrj-37073	253	6	daily	daily	ADJ
esrj-37073	253	7	streamflow	streamflow	NOUN
esrj-37073	253	8	:	:	PUNCT
esrj-37073	253	9	characterization	characterization	NOUN
esrj-37073	253	10	and	and	CCONJ
esrj-37073	253	11	prediction	prediction	NOUN
esrj-37073	253	12	.	.	PUNCT
esrj-37073	254	1	advances	advance	NOUN
esrj-37073	254	2	in	in	ADP
esrj-37073	254	3	water	water	NOUN
esrj-37073	254	4	resources	resource	NOUN
esrj-37073	254	5	,	,	PUNCT
esrj-37073	254	6	21(6	21(6	NUM
esrj-37073	254	7	):	):	PUNCT
esrj-37073	254	8	463	463	NUM
esrj-37073	254	9	-	-	SYM
esrj-37073	254	10	475	475	NUM
esrj-37073	254	11	.	.	PUNCT
esrj-37073	255	1	marques	marques	PROPN
esrj-37073	255	2	,	,	PUNCT
esrj-37073	255	3	c.a.f	c.a.f	PROPN
esrj-37073	255	4	.	.	PUNCT
esrj-37073	255	5	et	et	PROPN
esrj-37073	256	1	al	al	PROPN
esrj-37073	256	2	.	.	PROPN
esrj-37073	256	3	,	,	PUNCT
esrj-37073	256	4	(	(	PUNCT
esrj-37073	256	5	2006	2006	NUM
esrj-37073	256	6	)	)	PUNCT
esrj-37073	256	7	.	.	PUNCT
esrj-37073	257	1	singular	singular	PROPN
esrj-37073	257	2	spectrum	spectrum	VERB
esrj-37073	257	3	analysis	analysis	NOUN
esrj-37073	257	4	and	and	CCONJ
esrj-37073	257	5	forecasting	forecasting	NOUN
esrj-37073	257	6	of	of	ADP
esrj-37073	257	7	hydrological	hydrological	ADJ
esrj-37073	257	8	time	time	NOUN
esrj-37073	257	9	series	series	PROPN
esrj-37073	257	10	.	.	PUNCT
esrj-37073	258	1	physics	physics	NOUN
esrj-37073	258	2	and	and	CCONJ
esrj-37073	258	3	chemistry	chemistry	NOUN
esrj-37073	258	4	of	of	ADP
esrj-37073	258	5	the	the	DET
esrj-37073	258	6	earth	earth	NOUN
esrj-37073	258	7	,	,	PUNCT
esrj-37073	258	8	parts	part	VERB
esrj-37073	258	9	a	a	DET
esrj-37073	258	10	/	/	SYM
esrj-37073	258	11	b	b	NOUN
esrj-37073	258	12	/	/	SYM
esrj-37073	258	13	c	c	NOUN
esrj-37073	258	14	,	,	PUNCT
esrj-37073	258	15	31(18	31(18	NUM
esrj-37073	258	16	):	):	PUNCT
esrj-37073	258	17	1172	1172	NUM
esrj-37073	258	18	-	-	SYM
esrj-37073	258	19	1179	1179	NUM
esrj-37073	258	20	.	.	PUNCT
esrj-37073	259	1	modarres	modarre	NOUN
esrj-37073	259	2	,	,	PUNCT
esrj-37073	259	3	r.	r.	PROPN
esrj-37073	259	4	,	,	PUNCT
esrj-37073	259	5	(	(	PUNCT
esrj-37073	259	6	2007	2007	NUM
esrj-37073	259	7	)	)	PUNCT
esrj-37073	259	8	.	.	PUNCT
esrj-37073	260	1	streamflow	streamflow	PROPN
esrj-37073	260	2	drought	drought	PROPN
esrj-37073	260	3	time	time	PROPN
esrj-37073	260	4	series	series	PROPN
esrj-37073	260	5	forecasting	forecasting	PROPN
esrj-37073	260	6	.	.	PUNCT
esrj-37073	261	1	stochastic	stochastic	ADJ
esrj-37073	261	2	environmental	environmental	ADJ
esrj-37073	261	3	research	research	NOUN
esrj-37073	261	4	and	and	CCONJ
esrj-37073	261	5	risk	risk	NOUN
esrj-37073	261	6	assessment	assessment	NOUN
esrj-37073	261	7	,	,	PUNCT
esrj-37073	261	8	21(3	21(3	NUM
esrj-37073	261	9	):	):	PUNCT
esrj-37073	261	10	223	223	NUM
esrj-37073	261	11	-	-	SYM
esrj-37073	261	12	233	233	NUM
esrj-37073	261	13	.	.	PUNCT
esrj-37073	261	14	nash	nash	PROPN
esrj-37073	261	15	,	,	PUNCT
esrj-37073	261	16	j.e	j.e	PROPN
esrj-37073	261	17	.	.	PROPN
esrj-37073	261	18	and	and	CCONJ
esrj-37073	261	19	sutcliffe	sutcliffe	PROPN
esrj-37073	261	20	,	,	PUNCT
esrj-37073	261	21	j.v	j.v	PROPN
esrj-37073	261	22	.	.	PROPN
esrj-37073	261	23	,	,	PUNCT
esrj-37073	261	24	(	(	PUNCT
esrj-37073	261	25	1970	1970	NUM
esrj-37073	261	26	)	)	PUNCT
esrj-37073	261	27	.	.	PUNCT
esrj-37073	262	1	river	river	NOUN
esrj-37073	262	2	flow	flow	NOUN
esrj-37073	262	3	forecasting	forecasting	NOUN
esrj-37073	262	4	through	through	ADP
esrj-37073	262	5	conceptual	conceptual	ADJ
esrj-37073	262	6	models	model	NOUN
esrj-37073	262	7	,	,	PUNCT
esrj-37073	262	8	part	part	NOUN
esrj-37073	262	9	ia	ia	PROPN
esrj-37073	262	10	discussion	discussion	NOUN
esrj-37073	262	11	of	of	ADP
esrj-37073	262	12	principles	principle	NOUN
esrj-37073	262	13	.	.	PUNCT
esrj-37073	263	1	journal	journal	NOUN
esrj-37073	263	2	of	of	ADP
esrj-37073	263	3	hydrology	hydrology	NOUN
esrj-37073	263	4	,	,	PUNCT
esrj-37073	263	5	10	10	NUM
esrj-37073	263	6	:	:	SYM
esrj-37073	263	7	282	282	NUM
esrj-37073	263	8	-	-	SYM
esrj-37073	263	9	290	290	NUM
esrj-37073	263	10	.	.	PUNCT
esrj-37073	264	1	ng	ng	PROPN
esrj-37073	264	2	,	,	PUNCT
esrj-37073	264	3	w.w	w.w	PROPN
esrj-37073	264	4	.	.	PROPN
esrj-37073	264	5	,	,	PUNCT
esrj-37073	264	6	panu	panu	PROPN
esrj-37073	264	7	,	,	PUNCT
esrj-37073	264	8	u.s	u.s	PROPN
esrj-37073	264	9	.	.	PROPN
esrj-37073	264	10	and	and	CCONJ
esrj-37073	264	11	lennox	lennox	PROPN
esrj-37073	264	12	,	,	PUNCT
esrj-37073	264	13	w.c	w.c	PROPN
esrj-37073	264	14	.	.	PROPN
esrj-37073	264	15	,	,	PUNCT
esrj-37073	264	16	(	(	PUNCT
esrj-37073	264	17	2007	2007	NUM
esrj-37073	264	18	)	)	PUNCT
esrj-37073	264	19	.	.	PUNCT
esrj-37073	265	1	chaos	chaos	NOUN
esrj-37073	265	2	based	base	VERB
esrj-37073	265	3	analytical	analytical	ADJ
esrj-37073	265	4	techniques	technique	NOUN
esrj-37073	265	5	for	for	ADP
esrj-37073	265	6	daily	daily	ADJ
esrj-37073	265	7	extreme	extreme	ADJ
esrj-37073	265	8	hydrological	hydrological	ADJ
esrj-37073	265	9	observations	observation	NOUN
esrj-37073	265	10	.	.	PUNCT
esrj-37073	266	1	journal	journal	NOUN
esrj-37073	266	2	of	of	ADP
esrj-37073	266	3	hydrology	hydrology	NOUN
esrj-37073	266	4	,	,	PUNCT
esrj-37073	266	5	342	342	NUM
esrj-37073	266	6	:	:	PUNCT
esrj-37073	266	7	17	17	NUM
esrj-37073	266	8	-	-	SYM
esrj-37073	266	9	41	41	NUM
esrj-37073	266	10	.	.	PUNCT
esrj-37073	267	1	ooms	oom	NOUN
esrj-37073	267	2	,	,	PUNCT
esrj-37073	267	3	m.	m.	NOUN
esrj-37073	267	4	and	and	CCONJ
esrj-37073	267	5	franses	franse	NOUN
esrj-37073	267	6	,	,	PUNCT
esrj-37073	267	7	p.h	p.h	PROPN
esrj-37073	267	8	.	.	PROPN
esrj-37073	267	9	,	,	PUNCT
esrj-37073	267	10	(	(	PUNCT
esrj-37073	267	11	2001	2001	NUM
esrj-37073	267	12	)	)	PUNCT
esrj-37073	267	13	.	.	PUNCT
esrj-37073	268	1	a	a	DET
esrj-37073	268	2	seasonal	seasonal	ADJ
esrj-37073	268	3	periodic	periodic	ADJ
esrj-37073	268	4	long	long	ADJ
esrj-37073	268	5	memory	memory	NOUN
esrj-37073	268	6	model	model	NOUN
esrj-37073	268	7	for	for	ADP
esrj-37073	268	8	monthly	monthly	ADJ
esrj-37073	268	9	river	river	NOUN
esrj-37073	268	10	flows	flow	NOUN
esrj-37073	268	11	.	.	PUNCT
esrj-37073	269	1	environmental	environmental	ADJ
esrj-37073	269	2	modelling	modelling	NOUN
esrj-37073	269	3	&	&	CCONJ
esrj-37073	269	4	software	software	NOUN
esrj-37073	269	5	,	,	PUNCT
esrj-37073	269	6	16	16	NUM
esrj-37073	269	7	:	:	SYM
esrj-37073	269	8	559	559	NUM
esrj-37073	269	9	-	-	SYM
esrj-37073	269	10	569	569	NUM
esrj-37073	269	11	.	.	PUNCT
esrj-37073	270	1	packard	packard	PROPN
esrj-37073	270	2	,	,	PUNCT
esrj-37073	270	3	n.h	n.h	PROPN
esrj-37073	270	4	.	.	PROPN
esrj-37073	270	5	,	,	PUNCT
esrj-37073	270	6	crutchfield	crutchfield	PROPN
esrj-37073	270	7	,	,	PUNCT
esrj-37073	270	8	j.p	j.p	PROPN
esrj-37073	270	9	.	.	PROPN
esrj-37073	270	10	,	,	PUNCT
esrj-37073	270	11	farmer	farmer	PROPN
esrj-37073	270	12	,	,	PUNCT
esrj-37073	270	13	j.d	j.d	PROPN
esrj-37073	270	14	.	.	PROPN
esrj-37073	270	15	and	and	CCONJ
esrj-37073	270	16	r.s	r.s	PROPN
esrj-37073	270	17	.	.	PROPN
esrj-37073	270	18	,	,	PUNCT
esrj-37073	270	19	s.	s.	PROPN
esrj-37073	270	20	,	,	PUNCT
esrj-37073	270	21	(	(	PUNCT
esrj-37073	270	22	1980	1980	NUM
esrj-37073	270	23	)	)	PUNCT
esrj-37073	270	24	.	.	PUNCT
esrj-37073	271	1	geometry	geometry	NOUN
esrj-37073	271	2	from	from	ADP
esrj-37073	271	3	a	a	DET
esrj-37073	271	4	time	time	NOUN
esrj-37073	271	5	series	series	NOUN
esrj-37073	271	6	.	.	PUNCT
esrj-37073	272	1	physical	physical	ADJ
esrj-37073	272	2	review	review	PROPN
esrj-37073	272	3	letters	letter	VERB
esrj-37073	272	4	45(9	45(9	NOUN
esrj-37073	272	5	):	):	PUNCT
esrj-37073	272	6	712–716	712–716	NUM
esrj-37073	272	7	.	.	PUNCT
esrj-37073	273	1	pekárová	pekárová	PROPN
esrj-37073	273	2	,	,	PUNCT
esrj-37073	273	3	p.	p.	NOUN
esrj-37073	273	4	,	,	PUNCT
esrj-37073	273	5	onderka	onderka	PROPN
esrj-37073	273	6	,	,	PUNCT
esrj-37073	273	7	m.	m.	NOUN
esrj-37073	273	8	,	,	PUNCT
esrj-37073	273	9	pekár	pekár	ADV
esrj-37073	273	10	,	,	PUNCT
esrj-37073	273	11	j.	j.	PROPN
esrj-37073	273	12	,	,	PUNCT
esrj-37073	273	13	rončák	rončák	PROPN
esrj-37073	273	14	,	,	PUNCT
esrj-37073	273	15	p.	p.	NOUN
esrj-37073	273	16	and	and	CCONJ
esrj-37073	273	17	miklánek	miklánek	ADJ
esrj-37073	273	18	,	,	PUNCT
esrj-37073	273	19	p.	p.	PROPN
esrj-37073	273	20	,	,	PUNCT
esrj-37073	273	21	(	(	PUNCT
esrj-37073	273	22	2009	2009	NUM
esrj-37073	273	23	)	)	PUNCT
esrj-37073	273	24	.	.	PUNCT
esrj-37073	274	1	prediction	prediction	NOUN
esrj-37073	274	2	of	of	ADP
esrj-37073	274	3	water	water	NOUN
esrj-37073	274	4	quality	quality	NOUN
esrj-37073	274	5	in	in	ADP
esrj-37073	274	6	the	the	DET
esrj-37073	274	7	danube	danube	PROPN
esrj-37073	274	8	river	river	PROPN
esrj-37073	274	9	under	under	ADP
esrj-37073	274	10	extreme	extreme	ADJ
esrj-37073	274	11	hydrological	hydrological	ADJ
esrj-37073	274	12	and	and	CCONJ
esrj-37073	274	13	temperature	temperature	NOUN
esrj-37073	274	14	conditions	condition	NOUN
esrj-37073	274	15	.	.	PUNCT
esrj-37073	275	1	journal	journal	NOUN
esrj-37073	275	2	of	of	ADP
esrj-37073	275	3	hydrology	hydrology	NOUN
esrj-37073	275	4	and	and	CCONJ
esrj-37073	275	5	hydromechanics	hydromechanic	NOUN
esrj-37073	275	6	,	,	PUNCT
esrj-37073	275	7	57(1	57(1	NUM
esrj-37073	275	8	):	):	PUNCT
esrj-37073	275	9	3	3	NUM
esrj-37073	275	10	-	-	SYM
esrj-37073	275	11	15	15	NUM
esrj-37073	275	12	.	.	PUNCT
esrj-37073	276	1	randrianasolo	randrianasolo	PROPN
esrj-37073	276	2	,	,	PUNCT
esrj-37073	276	3	a.	a.	NOUN
esrj-37073	276	4	,	,	PUNCT
esrj-37073	276	5	ramos	ramos	PROPN
esrj-37073	276	6	,	,	PUNCT
esrj-37073	276	7	m.h	m.h	PROPN
esrj-37073	276	8	.	.	PROPN
esrj-37073	276	9	and	and	CCONJ
esrj-37073	276	10	andréassian	andréassian	PROPN
esrj-37073	276	11	,	,	PUNCT
esrj-37073	276	12	v.	v.	ADV
esrj-37073	276	13	,	,	PUNCT
esrj-37073	276	14	(	(	PUNCT
esrj-37073	276	15	2011	2011	NUM
esrj-37073	276	16	)	)	PUNCT
esrj-37073	276	17	.	.	PUNCT
esrj-37073	277	1	hydrological	hydrological	PROPN
esrj-37073	277	2	ensemble	ensemble	ADJ
esrj-37073	277	3	forecasting	forecasting	NOUN
esrj-37073	277	4	at	at	ADP
esrj-37073	277	5	ungauged	ungauged	ADJ
esrj-37073	277	6	basins	basin	NOUN
esrj-37073	277	7	:	:	PUNCT
esrj-37073	277	8	using	use	VERB
esrj-37073	277	9	neighbour	neighbour	ADJ
esrj-37073	277	10	catchments	catchment	NOUN
esrj-37073	277	11	for	for	ADP
esrj-37073	277	12	model	model	NOUN
esrj-37073	277	13	setup	setup	NOUN
esrj-37073	277	14	and	and	CCONJ
esrj-37073	277	15	updating	updating	NOUN
esrj-37073	277	16	.	.	PUNCT
esrj-37073	278	1	adv	adv	PROPN
esrj-37073	278	2	.	.	PUNCT
esrj-37073	279	1	geosci	geosci	PROPN
esrj-37073	279	2	.	.	PUNCT
esrj-37073	279	3	,	,	PUNCT
esrj-37073	279	4	29	29	NUM
esrj-37073	279	5	:	:	SYM
esrj-37073	279	6	1	1	NUM
esrj-37073	279	7	-	-	SYM
esrj-37073	279	8	11	11	NUM
esrj-37073	279	9	.	.	PUNCT
esrj-37073	280	1	riad	riad	PROPN
esrj-37073	280	2	,	,	PUNCT
esrj-37073	280	3	s.	s.	PROPN
esrj-37073	280	4	,	,	PUNCT
esrj-37073	280	5	mania	mania	PROPN
esrj-37073	280	6	,	,	PUNCT
esrj-37073	280	7	j.	j.	PROPN
esrj-37073	280	8	,	,	PUNCT
esrj-37073	280	9	bouchaou	bouchaou	PROPN
esrj-37073	280	10	,	,	PUNCT
esrj-37073	280	11	l.	l.	PROPN
esrj-37073	280	12	and	and	CCONJ
esrj-37073	280	13	najjar	najjar	PROPN
esrj-37073	280	14	,	,	PUNCT
esrj-37073	280	15	y.	y.	PROPN
esrj-37073	280	16	,	,	PUNCT
esrj-37073	280	17	(	(	PUNCT
esrj-37073	280	18	2004	2004	NUM
esrj-37073	280	19	)	)	PUNCT
esrj-37073	280	20	.	.	PUNCT
esrj-37073	281	1	rainfall	rainfall	NOUN
esrj-37073	281	2	-	-	PUNCT
esrj-37073	281	3	runoff	runoff	NOUN
esrj-37073	281	4	model	model	NOUN
esrj-37073	281	5	using	use	VERB
esrj-37073	281	6	an	an	DET
esrj-37073	281	7	artificial	artificial	ADJ
esrj-37073	281	8	neural	neural	ADJ
esrj-37073	281	9	network	network	NOUN
esrj-37073	281	10	approach	approach	NOUN
esrj-37073	281	11	.	.	PUNCT
esrj-37073	282	1	mathematical	mathematical	ADJ
esrj-37073	282	2	and	and	CCONJ
esrj-37073	282	3	computer	computer	NOUN
esrj-37073	282	4	modelling	model	VERB
esrj-37073	282	5	40	40	NUM
esrj-37073	282	6	:	:	PUNCT
esrj-37073	282	7	839–846	839–846	NUM
esrj-37073	282	8	.	.	PUNCT
esrj-37073	283	1	sahoo	sahoo	PROPN
esrj-37073	283	2	,	,	PUNCT
esrj-37073	283	3	g.b	g.b	PROPN
esrj-37073	283	4	.	.	PROPN
esrj-37073	283	5	,	,	PUNCT
esrj-37073	283	6	schladow	schladow	NOUN
esrj-37073	283	7	,	,	PUNCT
esrj-37073	283	8	s.g	s.g	PROPN
esrj-37073	283	9	.	.	PROPN
esrj-37073	283	10	and	and	CCONJ
esrj-37073	283	11	reuter	reuter	PROPN
esrj-37073	283	12	,	,	PUNCT
esrj-37073	283	13	j.e	j.e	PROPN
esrj-37073	283	14	.	.	PROPN
esrj-37073	283	15	,	,	PUNCT
esrj-37073	283	16	(	(	PUNCT
esrj-37073	283	17	2009	2009	NUM
esrj-37073	283	18	)	)	PUNCT
esrj-37073	283	19	.	.	PUNCT
esrj-37073	284	1	forecasting	forecasting	NOUN
esrj-37073	284	2	stream	stream	NOUN
esrj-37073	284	3	water	water	NOUN
esrj-37073	284	4	temperature	temperature	NOUN
esrj-37073	284	5	using	use	VERB
esrj-37073	284	6	regression	regression	NOUN
esrj-37073	284	7	analysis	analysis	NOUN
esrj-37073	284	8	,	,	PUNCT
esrj-37073	284	9	artificial	artificial	ADJ
esrj-37073	284	10	neural	neural	ADJ
esrj-37073	284	11	network	network	NOUN
esrj-37073	284	12	,	,	PUNCT
esrj-37073	284	13	and	and	CCONJ
esrj-37073	284	14	chaotic	chaotic	ADJ
esrj-37073	284	15	non	non	ADJ
esrj-37073	284	16	-	-	ADJ
esrj-37073	284	17	linear	linear	ADJ
esrj-37073	284	18	dynamic	dynamic	ADJ
esrj-37073	284	19	models	model	NOUN
esrj-37073	284	20	.	.	PUNCT
esrj-37073	285	1	journal	journal	NOUN
esrj-37073	285	2	of	of	ADP
esrj-37073	285	3	hydrology	hydrology	NOUN
esrj-37073	285	4	,	,	PUNCT
esrj-37073	285	5	378(3–4	378(3–4	NUM
esrj-37073	285	6	):	):	PUNCT
esrj-37073	285	7	325	325	NUM
esrj-37073	285	8	-	-	SYM
esrj-37073	285	9	342	342	NUM
esrj-37073	285	10	.	.	PUNCT
esrj-37073	286	1	sivakumar	sivakumar	PROPN
esrj-37073	286	2	,	,	PUNCT
esrj-37073	286	3	b.	b.	PROPN
esrj-37073	286	4	,	,	PUNCT
esrj-37073	286	5	(	(	PUNCT
esrj-37073	286	6	2003	2003	NUM
esrj-37073	286	7	)	)	PUNCT
esrj-37073	286	8	.	.	PUNCT
esrj-37073	287	1	forecasting	forecast	VERB
esrj-37073	287	2	monthly	monthly	ADJ
esrj-37073	287	3	streamflow	streamflow	NOUN
esrj-37073	287	4	dynamics	dynamic	NOUN
esrj-37073	287	5	in	in	ADP
esrj-37073	287	6	the	the	DET
esrj-37073	287	7	western	western	ADJ
esrj-37073	287	8	united	united	PROPN
esrj-37073	287	9	states	states	PROPN
esrj-37073	287	10	:	:	PUNCT
esrj-37073	287	11	a	a	DET
esrj-37073	287	12	nonlinear	nonlinear	ADJ
esrj-37073	287	13	dynamical	dynamical	ADJ
esrj-37073	287	14	approach	approach	NOUN
esrj-37073	287	15	.	.	PUNCT
esrj-37073	288	1	environmental	environmental	ADJ
esrj-37073	288	2	modelling	modelling	NOUN
esrj-37073	288	3	&	&	CCONJ
esrj-37073	288	4	software	software	NOUN
esrj-37073	288	5	,	,	PUNCT
esrj-37073	288	6	18(8	18(8	NUM
esrj-37073	288	7	-	-	SYM
esrj-37073	288	8	9	9	NUM
esrj-37073	288	9	):	):	PUNCT
esrj-37073	288	10	721	721	NUM
esrj-37073	288	11	-	-	SYM
esrj-37073	288	12	728	728	NUM
esrj-37073	288	13	.	.	PUNCT
esrj-37073	288	14	sivakumar	sivakumar	PROPN
esrj-37073	288	15	,	,	PUNCT
esrj-37073	288	16	b.	b.	PROPN
esrj-37073	288	17	,	,	PUNCT
esrj-37073	288	18	(	(	PUNCT
esrj-37073	288	19	2007	2007	NUM
esrj-37073	288	20	)	)	PUNCT
esrj-37073	288	21	.	.	PUNCT
esrj-37073	289	1	nonlinear	nonlinear	ADJ
esrj-37073	289	2	determinism	determinism	NOUN
esrj-37073	289	3	in	in	ADP
esrj-37073	289	4	river	river	NOUN
esrj-37073	289	5	flow	flow	NOUN
esrj-37073	289	6	:	:	PUNCT
esrj-37073	289	7	prediction	prediction	NOUN
esrj-37073	289	8	as	as	ADP
esrj-37073	289	9	a	a	DET
esrj-37073	289	10	possible	possible	ADJ
esrj-37073	289	11	indicator	indicator	NOUN
esrj-37073	289	12	.	.	PUNCT
esrj-37073	290	1	earth	earth	NOUN
esrj-37073	290	2	surface	surface	NOUN
esrj-37073	290	3	processes	process	NOUN
esrj-37073	290	4	and	and	CCONJ
esrj-37073	290	5	landforms(32	landforms(32	NUM
esrj-37073	290	6	):	):	PUNCT
esrj-37073	290	7	969	969	NUM
esrj-37073	290	8	-	-	SYM
esrj-37073	290	9	979	979	NUM
esrj-37073	290	10	.	.	PUNCT
esrj-37073	291	1	sivakumar	sivakumar	PROPN
esrj-37073	291	2	,	,	PUNCT
esrj-37073	291	3	b.	b.	PROPN
esrj-37073	291	4	,	,	PUNCT
esrj-37073	291	5	berndtsson	berndtsson	PROPN
esrj-37073	291	6	,	,	PUNCT
esrj-37073	291	7	r.	r.	PROPN
esrj-37073	291	8	and	and	CCONJ
esrj-37073	291	9	persson	persson	PROPN
esrj-37073	291	10	,	,	PUNCT
esrj-37073	291	11	m.	m.	NOUN
esrj-37073	291	12	,	,	PUNCT
esrj-37073	291	13	(	(	PUNCT
esrj-37073	291	14	2001	2001	NUM
esrj-37073	291	15	)	)	PUNCT
esrj-37073	291	16	.	.	PUNCT
esrj-37073	292	1	monthly	monthly	ADJ
esrj-37073	292	2	runoff	runoff	NOUN
esrj-37073	292	3	prediction	prediction	NOUN
esrj-37073	292	4	using	use	VERB
esrj-37073	292	5	phase	phase	NOUN
esrj-37073	292	6	space	space	NOUN
esrj-37073	292	7	reconstruction	reconstruction	NOUN
esrj-37073	292	8	.	.	PUNCT
esrj-37073	293	1	hydrological	hydrological	ADJ
esrj-37073	293	2	sciences	sciences	PROPN
esrj-37073	293	3	journal	journal	PROPN
esrj-37073	293	4	,	,	PUNCT
esrj-37073	293	5	46(3	46(3	NOUN
esrj-37073	293	6	):	):	PUNCT
esrj-37073	293	7	377	377	NUM
esrj-37073	293	8	-	-	SYM
esrj-37073	293	9	388	388	NUM
esrj-37073	293	10	.	.	PUNCT
esrj-37073	293	11	sivakumar	sivakumar	PROPN
esrj-37073	293	12	,	,	PUNCT
esrj-37073	293	13	b.	b.	PROPN
esrj-37073	293	14	and	and	CCONJ
esrj-37073	293	15	jayawardena	jayawardena	PROPN
esrj-37073	293	16	,	,	PUNCT
esrj-37073	293	17	a.w	a.w	PROPN
esrj-37073	293	18	.	.	PROPN
esrj-37073	293	19	,	,	PUNCT
esrj-37073	293	20	(	(	PUNCT
esrj-37073	293	21	2002	2002	NUM
esrj-37073	293	22	)	)	PUNCT
esrj-37073	293	23	.	.	PUNCT
esrj-37073	294	1	an	an	DET
esrj-37073	294	2	investigation	investigation	NOUN
esrj-37073	294	3	of	of	ADP
esrj-37073	294	4	the	the	DET
esrj-37073	294	5	presence	presence	NOUN
esrj-37073	294	6	of	of	ADP
esrj-37073	294	7	low	low	ADJ
esrj-37073	294	8	-	-	PUNCT
esrj-37073	294	9	dimensional	dimensional	ADJ
esrj-37073	294	10	chaotic	chaotic	ADJ
esrj-37073	294	11	behaviour	behaviour	NOUN
esrj-37073	294	12	in	in	ADP
esrj-37073	294	13	the	the	DET
esrj-37073	294	14	sediment	sediment	NOUN
esrj-37073	294	15	transport	transport	NOUN
esrj-37073	294	16	phenomenon	phenomenon	NOUN
esrj-37073	294	17	.	.	PUNCT
esrj-37073	295	1	hydrological	hydrological	ADJ
esrj-37073	295	2	sciences	sciences	PROPN
esrj-37073	295	3	journal	journal	PROPN
esrj-37073	295	4	,	,	PUNCT
esrj-37073	295	5	47(3	47(3	NUM
esrj-37073	295	6	):	):	PUNCT
esrj-37073	295	7	405	405	NUM
esrj-37073	295	8	-	-	SYM
esrj-37073	295	9	416	416	NUM
esrj-37073	295	10	.	.	PUNCT
esrj-37073	296	1	sivakumar	sivakumar	PROPN
esrj-37073	296	2	,	,	PUNCT
esrj-37073	296	3	b.	b.	PROPN
esrj-37073	296	4	,	,	PUNCT
esrj-37073	296	5	jayawardena	jayawardena	PROPN
esrj-37073	296	6	,	,	PUNCT
esrj-37073	296	7	a.w	a.w	PROPN
esrj-37073	296	8	.	.	PROPN
esrj-37073	296	9	and	and	CCONJ
esrj-37073	296	10	fernando	fernando	PROPN
esrj-37073	296	11	,	,	PUNCT
esrj-37073	296	12	t.m.k.g	t.m.k.g	PROPN
esrj-37073	296	13	.	.	PROPN
esrj-37073	296	14	,	,	PUNCT
esrj-37073	296	15	(	(	PUNCT
esrj-37073	296	16	2002	2002	NUM
esrj-37073	296	17	)	)	PUNCT
esrj-37073	296	18	.	.	PUNCT
esrj-37073	297	1	river	river	NOUN
esrj-37073	297	2	flow	flow	NOUN
esrj-37073	297	3	forecasting	forecasting	NOUN
esrj-37073	297	4	:	:	PUNCT
esrj-37073	297	5	use	use	NOUN
esrj-37073	297	6	of	of	ADP
esrj-37073	297	7	phase	phase	NOUN
esrj-37073	297	8	-	-	PUNCT
esrj-37073	297	9	space	space	NOUN
esrj-37073	297	10	reconstruction	reconstruction	NOUN
esrj-37073	297	11	and	and	CCONJ
esrj-37073	297	12	artificial	artificial	ADJ
esrj-37073	297	13	neural	neural	ADJ
esrj-37073	297	14	networks	network	NOUN
esrj-37073	297	15	approaches	approach	NOUN
esrj-37073	297	16	.	.	PUNCT
esrj-37073	298	1	journal	journal	NOUN
esrj-37073	298	2	of	of	ADP
esrj-37073	298	3	hydrology	hydrology	NOUN
esrj-37073	298	4	,	,	PUNCT
esrj-37073	298	5	265(1	265(1	NUM
esrj-37073	298	6	-	-	SYM
esrj-37073	298	7	4	4	NUM
esrj-37073	298	8	):	):	PUNCT
esrj-37073	298	9	225	225	NUM
esrj-37073	298	10	-	-	SYM
esrj-37073	298	11	245	245	NUM
esrj-37073	298	12	.	.	PUNCT
esrj-37073	298	13	sivakumar	sivakumar	PROPN
esrj-37073	298	14	,	,	PUNCT
esrj-37073	298	15	b.	b.	PROPN
esrj-37073	298	16	et	et	PROPN
esrj-37073	298	17	al	al	PROPN
esrj-37073	298	18	.	.	PROPN
esrj-37073	298	19	,	,	PUNCT
esrj-37073	298	20	(	(	PUNCT
esrj-37073	298	21	2006	2006	NUM
esrj-37073	298	22	)	)	PUNCT
esrj-37073	298	23	.	.	PUNCT
esrj-37073	299	1	nonlinear	nonlinear	ADJ
esrj-37073	299	2	analysis	analysis	NOUN
esrj-37073	299	3	of	of	ADP
esrj-37073	299	4	rainfall	rainfall	NOUN
esrj-37073	299	5	dynamics	dynamic	NOUN
esrj-37073	299	6	in	in	ADP
esrj-37073	299	7	california	california	PROPN
esrj-37073	299	8	’s	’s	PART
esrj-37073	299	9	sacramento	sacramento	PROPN
esrj-37073	299	10	valley	valley	PROPN
esrj-37073	299	11	.	.	PUNCT
esrj-37073	300	1	hydrological	hydrological	ADJ
esrj-37073	300	2	processes	process	NOUN
esrj-37073	300	3	,	,	PUNCT
esrj-37073	300	4	20	20	NUM
esrj-37073	300	5	:	:	SYM
esrj-37073	300	6	17231736	17231736	NUM
esrj-37073	300	7	.	.	PUNCT
esrj-37073	301	1	stehlik	stehlik	PROPN
esrj-37073	301	2	,	,	PUNCT
esrj-37073	301	3	j.	j.	PROPN
esrj-37073	301	4	,	,	PUNCT
esrj-37073	301	5	(	(	PUNCT
esrj-37073	301	6	1999	1999	NUM
esrj-37073	301	7	)	)	PUNCT
esrj-37073	301	8	.	.	PUNCT
esrj-37073	302	1	deterministic	deterministic	ADJ
esrj-37073	302	2	chaos	chaos	NOUN
esrj-37073	302	3	in	in	ADP
esrj-37073	302	4	runoff	runoff	NOUN
esrj-37073	302	5	series	series	NOUN
esrj-37073	302	6	.	.	PUNCT
esrj-37073	303	1	journal	journal	PROPN
esrj-37073	303	2	of	of	ADP
esrj-37073	303	3	hydrology	hydrology	NOUN
esrj-37073	303	4	and	and	CCONJ
esrj-37073	303	5	hydromechanics	hydromechanic	NOUN
esrj-37073	303	6	,	,	PUNCT
esrj-37073	303	7	47(4	47(4	NUM
esrj-37073	303	8	):	):	PUNCT
esrj-37073	303	9	271	271	NUM
esrj-37073	303	10	-	-	SYM
esrj-37073	303	11	287	287	NUM
esrj-37073	303	12	.	.	PUNCT
esrj-37073	304	1	takens	takens	PROPN
esrj-37073	304	2	,	,	PUNCT
esrj-37073	304	3	f.	f.	PROPN
esrj-37073	304	4	,	,	PUNCT
esrj-37073	304	5	(	(	PUNCT
esrj-37073	304	6	1981	1981	NUM
esrj-37073	304	7	)	)	PUNCT
esrj-37073	304	8	.	.	PUNCT
esrj-37073	305	1	detecting	detect	VERB
esrj-37073	305	2	strange	strange	ADJ
esrj-37073	305	3	attractors	attractor	NOUN
esrj-37073	305	4	in	in	ADP
esrj-37073	305	5	turbulence	turbulence	NOUN
esrj-37073	305	6	.	.	PUNCT
esrj-37073	306	1	in	in	ADP
esrj-37073	306	2	:	:	PUNCT
esrj-37073	306	3	d.a	d.a	PROPN
esrj-37073	306	4	.	.	PROPN
esrj-37073	306	5	rand	rand	PROPN
esrj-37073	306	6	,	,	PUNCT
esrj-37073	306	7	jung	jung	PROPN
esrj-37073	306	8	,	,	PUNCT
esrj-37073	306	9	l.s	l.s	PROPN
esrj-37073	306	10	.	.	PUNCT
esrj-37073	306	11	(	(	PUNCT
esrj-37073	306	12	editor	editor	NOUN
esrj-37073	306	13	)	)	PUNCT
esrj-37073	306	14	,	,	PUNCT
esrj-37073	306	15	dynamical	dynamical	ADJ
esrj-37073	306	16	systems	system	NOUN
esrj-37073	306	17	and	and	CCONJ
esrj-37073	306	18	turbulence	turbulence	NOUN
esrj-37073	306	19	,	,	PUNCT
esrj-37073	306	20	lecture	lecture	NOUN
esrj-37073	306	21	notes	note	NOUN
esrj-37073	306	22	in	in	ADP
esrj-37073	306	23	mathematics	mathematic	NOUN
esrj-37073	306	24	.	.	PUNCT
esrj-37073	307	1	springer	springer	NOUN
esrj-37073	307	2	-	-	PUNCT
esrj-37073	307	3	verlag	verlag	PROPN
esrj-37073	307	4	,	,	PUNCT
esrj-37073	307	5	berlin	berlin	PROPN
esrj-37073	307	6	,	,	PUNCT
esrj-37073	307	7	pp	pp	PROPN
esrj-37073	307	8	.	.	PUNCT
esrj-37073	308	1	366	366	NUM
esrj-37073	308	2	-	-	SYM
esrj-37073	308	3	381	381	NUM
esrj-37073	308	4	.	.	PUNCT
esrj-37073	309	1	tongal	tongal	ADJ
esrj-37073	309	2	,	,	PUNCT
esrj-37073	309	3	h.	h.	PROPN
esrj-37073	309	4	,	,	PUNCT
esrj-37073	309	5	demirel	demirel	NOUN
esrj-37073	309	6	,	,	PUNCT
esrj-37073	309	7	m.c	m.c	PROPN
esrj-37073	309	8	.	.	PROPN
esrj-37073	309	9	and	and	CCONJ
esrj-37073	309	10	booij	booij	PROPN
esrj-37073	309	11	,	,	PUNCT
esrj-37073	309	12	m.j	m.j	PROPN
esrj-37073	309	13	.	.	PROPN
esrj-37073	309	14	,	,	PUNCT
esrj-37073	309	15	(	(	PUNCT
esrj-37073	309	16	2013	2013	NUM
esrj-37073	309	17	)	)	PUNCT
esrj-37073	309	18	.	.	PUNCT
esrj-37073	310	1	seasonality	seasonality	NOUN
esrj-37073	310	2	of	of	ADP
esrj-37073	310	3	low	low	ADJ
esrj-37073	310	4	flows	flow	NOUN
esrj-37073	310	5	and	and	CCONJ
esrj-37073	310	6	dominant	dominant	ADJ
esrj-37073	310	7	processes	process	NOUN
esrj-37073	310	8	in	in	ADP
esrj-37073	310	9	the	the	DET
esrj-37073	310	10	rhine	rhine	PROPN
esrj-37073	310	11	river	river	PROPN
esrj-37073	310	12	.	.	PUNCT
esrj-37073	311	1	stochastic	stochastic	ADJ
esrj-37073	311	2	environmental	environmental	ADJ
esrj-37073	311	3	research	research	NOUN
esrj-37073	311	4	and	and	CCONJ
esrj-37073	311	5	risk	risk	NOUN
esrj-37073	311	6	assessment	assessment	NOUN
esrj-37073	311	7	,	,	PUNCT
esrj-37073	311	8	27(2	27(2	PROPN
esrj-37073	311	9	):	):	PUNCT
esrj-37073	311	10	489	489	NUM
esrj-37073	311	11	-	-	SYM
esrj-37073	311	12	503	503	NUM
esrj-37073	311	13	.	.	PUNCT
esrj-37073	312	1	toth	toth	PROPN
esrj-37073	312	2	,	,	PUNCT
esrj-37073	312	3	e.	e.	PROPN
esrj-37073	312	4	,	,	PUNCT
esrj-37073	312	5	brath	brath	PROPN
esrj-37073	312	6	,	,	PUNCT
esrj-37073	312	7	a.	a.	NOUN
esrj-37073	312	8	and	and	CCONJ
esrj-37073	312	9	montanari	montanari	PROPN
esrj-37073	312	10	,	,	PUNCT
esrj-37073	312	11	a.	a.	NOUN
esrj-37073	312	12	,	,	PUNCT
esrj-37073	312	13	(	(	PUNCT
esrj-37073	312	14	2000	2000	NUM
esrj-37073	312	15	)	)	PUNCT
esrj-37073	312	16	.	.	PUNCT
esrj-37073	313	1	comparison	comparison	NOUN
esrj-37073	313	2	of	of	ADP
esrj-37073	313	3	short	short	ADJ
esrj-37073	313	4	-	-	PUNCT
esrj-37073	313	5	term	term	NOUN
esrj-37073	313	6	rainfall	rainfall	NOUN
esrj-37073	313	7	prediction	prediction	NOUN
esrj-37073	313	8	models	model	NOUN
esrj-37073	313	9	for	for	ADP
esrj-37073	313	10	real	real	ADJ
esrj-37073	313	11	-	-	PUNCT
esrj-37073	313	12	time	time	NOUN
esrj-37073	313	13	flood	flood	NOUN
esrj-37073	313	14	forecasting	forecasting	NOUN
esrj-37073	313	15	.	.	PUNCT
esrj-37073	314	1	journal	journal	NOUN
esrj-37073	314	2	of	of	ADP
esrj-37073	314	3	hydrology	hydrology	NOUN
esrj-37073	314	4	,	,	PUNCT
esrj-37073	314	5	239(1–4	239(1–4	NUM
esrj-37073	314	6	):	):	PUNCT
esrj-37073	314	7	132	132	NUM
esrj-37073	314	8	-	-	SYM
esrj-37073	314	9	147	147	NUM
esrj-37073	314	10	.	.	PUNCT
esrj-37073	315	1	vafakhah	vafakhah	PROPN
esrj-37073	315	2	,	,	PUNCT
esrj-37073	315	3	m.	m.	NOUN
esrj-37073	315	4	,	,	PUNCT
esrj-37073	315	5	(	(	PUNCT
esrj-37073	315	6	2012	2012	NUM
esrj-37073	315	7	)	)	PUNCT
esrj-37073	315	8	.	.	PUNCT
esrj-37073	316	1	application	application	NOUN
esrj-37073	316	2	of	of	ADP
esrj-37073	316	3	artificial	artificial	ADJ
esrj-37073	316	4	neural	neural	ADJ
esrj-37073	316	5	networks	network	NOUN
esrj-37073	316	6	and	and	CCONJ
esrj-37073	316	7	adaptive	adaptive	ADJ
esrj-37073	316	8	neuro	neuro	NOUN
esrj-37073	316	9	-	-	PUNCT
esrj-37073	316	10	fuzzy	fuzzy	ADJ
esrj-37073	316	11	inference	inference	NOUN
esrj-37073	316	12	system	system	NOUN
esrj-37073	316	13	models	model	NOUN
esrj-37073	316	14	to	to	ADP
esrj-37073	316	15	short	short	ADJ
esrj-37073	316	16	-	-	PUNCT
esrj-37073	316	17	term	term	NOUN
esrj-37073	316	18	streamflow	streamflow	NOUN
esrj-37073	316	19	forecasting	forecasting	NOUN
esrj-37073	316	20	.	.	PUNCT
esrj-37073	317	1	canadian	canadian	ADJ
esrj-37073	317	2	journal	journal	NOUN
esrj-37073	317	3	of	of	ADP
esrj-37073	317	4	civil	civil	ADJ
esrj-37073	317	5	engineering	engineering	NOUN
esrj-37073	317	6	,	,	PUNCT
esrj-37073	317	7	39(4	39(4	NUM
esrj-37073	317	8	):	):	PUNCT
esrj-37073	317	9	402	402	NUM
esrj-37073	317	10	-	-	SYM
esrj-37073	317	11	414	414	NUM
esrj-37073	317	12	.	.	PUNCT
esrj-37073	318	1	wu	wu	PROPN
esrj-37073	318	2	,	,	PUNCT
esrj-37073	318	3	c.l	c.l	PROPN
esrj-37073	318	4	.	.	PROPN
esrj-37073	318	5	and	and	CCONJ
esrj-37073	318	6	chau	chau	PROPN
esrj-37073	318	7	,	,	PUNCT
esrj-37073	318	8	k.w	k.w	PROPN
esrj-37073	318	9	.	.	PROPN
esrj-37073	318	10	,	,	PUNCT
esrj-37073	318	11	(	(	PUNCT
esrj-37073	318	12	2010	2010	NUM
esrj-37073	318	13	)	)	PUNCT
esrj-37073	318	14	.	.	PUNCT
esrj-37073	319	1	data	data	NOUN
esrj-37073	319	2	-	-	PUNCT
esrj-37073	319	3	driven	drive	VERB
esrj-37073	319	4	models	model	NOUN
esrj-37073	319	5	for	for	ADP
esrj-37073	319	6	monthly	monthly	ADJ
esrj-37073	319	7	streamflow	streamflow	PROPN
esrj-37073	319	8	time	time	NOUN
esrj-37073	319	9	series	series	PROPN
esrj-37073	319	10	prediction	prediction	PROPN
esrj-37073	319	11	.	.	PUNCT
esrj-37073	320	1	engineering	engineering	NOUN
esrj-37073	320	2	applications	application	NOUN
esrj-37073	320	3	of	of	ADP
esrj-37073	320	4	artificial	artificial	ADJ
esrj-37073	320	5	intelligence	intelligence	NOUN
esrj-37073	320	6	,	,	PUNCT
esrj-37073	320	7	23	23	NUM
esrj-37073	320	8	:	:	PUNCT
esrj-37073	320	9	1350	1350	NUM
esrj-37073	320	10	-	-	SYM
esrj-37073	320	11	1367	1367	NUM
esrj-37073	320	12	.	.	PUNCT
esrj-37073	321	1	wu	wu	PROPN
esrj-37073	321	2	,	,	PUNCT
esrj-37073	321	3	c.l	c.l	PROPN
esrj-37073	321	4	.	.	PROPN
esrj-37073	321	5	,	,	PUNCT
esrj-37073	321	6	chau	chau	PROPN
esrj-37073	321	7	,	,	PUNCT
esrj-37073	321	8	k.w	k.w	PROPN
esrj-37073	321	9	.	.	PROPN
esrj-37073	321	10	and	and	CCONJ
esrj-37073	321	11	li	li	PROPN
esrj-37073	321	12	,	,	PUNCT
esrj-37073	321	13	y.s	y.s	PROPN
esrj-37073	321	14	.	.	PROPN
esrj-37073	321	15	,	,	PUNCT
esrj-37073	321	16	(	(	PUNCT
esrj-37073	321	17	2009	2009	NUM
esrj-37073	321	18	)	)	PUNCT
esrj-37073	321	19	.	.	PUNCT
esrj-37073	322	1	predicting	predict	VERB
esrj-37073	322	2	monthly	monthly	ADJ
esrj-37073	322	3	streamflow	streamflow	NOUN
esrj-37073	322	4	using	use	VERB
esrj-37073	322	5	data	data	NOUN
esrj-37073	322	6	-	-	PUNCT
esrj-37073	322	7	driven	drive	VERB
esrj-37073	322	8	models	model	NOUN
esrj-37073	322	9	coupled	couple	VERB
esrj-37073	322	10	with	with	ADP
esrj-37073	322	11	data	data	NOUN
esrj-37073	322	12	-	-	PUNCT
esrj-37073	322	13	preprocessing	preprocesse	VERB
esrj-37073	322	14	techniques	technique	NOUN
esrj-37073	322	15	.	.	PUNCT
esrj-37073	323	1	water	water	NOUN
esrj-37073	323	2	resour	resour	NOUN
esrj-37073	323	3	.	.	PUNCT
esrj-37073	324	1	res	re	NOUN
esrj-37073	324	2	.	.	PROPN
esrj-37073	324	3	,	,	PUNCT
esrj-37073	324	4	45(8	45(8	NOUN
esrj-37073	324	5	):	):	PUNCT
esrj-37073	324	6	w08432	w08432	PROPN
esrj-37073	324	7	.	.	PUNCT
esrj-37073	324	8	yu	yu	PROPN
esrj-37073	324	9	,	,	PUNCT
esrj-37073	324	10	b.	b.	PROPN
esrj-37073	324	11	,	,	PUNCT
esrj-37073	324	12	huang	huang	PROPN
esrj-37073	324	13	,	,	PUNCT
esrj-37073	324	14	c.	c.	PROPN
esrj-37073	324	15	,	,	PUNCT
esrj-37073	324	16	liu	liu	PROPN
esrj-37073	324	17	,	,	PUNCT
esrj-37073	324	18	z.	z.	PROPN
esrj-37073	324	19	,	,	PUNCT
esrj-37073	324	20	wang	wang	PROPN
esrj-37073	324	21	,	,	PUNCT
esrj-37073	324	22	h.	h.	PROPN
esrj-37073	324	23	and	and	CCONJ
esrj-37073	324	24	wang	wang	PROPN
esrj-37073	324	25	,	,	PUNCT
esrj-37073	324	26	l.	l.	PROPN
esrj-37073	324	27	,	,	PUNCT
esrj-37073	324	28	(	(	PUNCT
esrj-37073	324	29	2011	2011	NUM
esrj-37073	324	30	)	)	PUNCT
esrj-37073	324	31	.	.	PUNCT
esrj-37073	325	1	a	a	DET
esrj-37073	325	2	chaotic	chaotic	ADJ
esrj-37073	325	3	analysis	analysis	NOUN
esrj-37073	325	4	on	on	ADP
esrj-37073	325	5	air	air	NOUN
esrj-37073	325	6	pollution	pollution	NOUN
esrj-37073	325	7	index	index	NOUN
esrj-37073	325	8	change	change	NOUN
esrj-37073	325	9	over	over	ADP
esrj-37073	325	10	past	past	ADJ
esrj-37073	325	11	10	10	NUM
esrj-37073	325	12	years	year	NOUN
esrj-37073	325	13	in	in	ADP
esrj-37073	325	14	lanzhou	lanzhou	PROPN
esrj-37073	325	15	,	,	PUNCT
esrj-37073	325	16	northwest	northwest	PROPN
esrj-37073	325	17	china	china	PROPN
esrj-37073	325	18	.	.	PUNCT
esrj-37073	326	1	stochastic	stochastic	ADJ
esrj-37073	326	2	environmental	environmental	ADJ
esrj-37073	326	3	research	research	NOUN
esrj-37073	326	4	and	and	CCONJ
esrj-37073	326	5	risk	risk	NOUN
esrj-37073	326	6	assessment	assessment	NOUN
esrj-37073	326	7	,	,	PUNCT
esrj-37073	326	8	25	25	NUM
esrj-37073	326	9	:	:	PUNCT
esrj-37073	326	10	643	643	NUM
esrj-37073	326	11	-	-	SYM
esrj-37073	326	12	653	653	NUM
esrj-37073	326	13	.	.	PUNCT
esrj-37073	327	1	hakan	hakan	PROPN
esrj-37073	327	2	tongal	tongal	PROPN