id	sid	tid	token	lemma	pos
esrj-49829	1	1	this	this	DET
esrj-49829	1	2	paper	paper	NOUN
esrj-49829	1	3	investigates	investigate	VERB
esrj-49829	1	4	the	the	DET
esrj-49829	1	5	potential	potential	NOUN
esrj-49829	1	6	of	of	ADP
esrj-49829	1	7	data	datum	NOUN
esrj-49829	1	8	mining	mining	NOUN
esrj-49829	1	9	techniques	technique	NOUN
esrj-49829	1	10	to	to	PART
esrj-49829	1	11	predict	predict	VERB
esrj-49829	1	12	daily	daily	ADJ
esrj-49829	1	13	soil	soil	NOUN
esrj-49829	1	14	temperatures	temperature	NOUN
esrj-49829	1	15	at	at	ADP
esrj-49829	1	16	5	5	NUM
esrj-49829	1	17	-	-	SYM
esrj-49829	1	18	100	100	NUM
esrj-49829	1	19	cm	cm	NOUN
esrj-49829	1	20	depths	depth	NOUN
esrj-49829	1	21	for	for	ADP
esrj-49829	1	22	agricultural	agricultural	ADJ
esrj-49829	1	23	purposes	purpose	NOUN
esrj-49829	1	24	.	.	PUNCT
esrj-49829	2	1	climatic	climatic	ADJ
esrj-49829	2	2	and	and	CCONJ
esrj-49829	2	3	soil	soil	NOUN
esrj-49829	2	4	temperature	temperature	NOUN
esrj-49829	2	5	data	datum	NOUN
esrj-49829	2	6	from	from	ADP
esrj-49829	2	7	isfahan	isfahan	PROPN
esrj-49829	2	8	province	province	NOUN
esrj-49829	2	9	located	locate	VERB
esrj-49829	2	10	in	in	ADP
esrj-49829	2	11	central	central	ADJ
esrj-49829	2	12	iran	iran	PROPN
esrj-49829	2	13	with	with	ADP
esrj-49829	2	14	a	a	DET
esrj-49829	2	15	semi	semi	ADJ
esrj-49829	2	16	-	-	ADJ
esrj-49829	2	17	arid	arid	ADJ
esrj-49829	2	18	climate	climate	NOUN
esrj-49829	2	19	was	be	AUX
esrj-49829	2	20	used	use	VERB
esrj-49829	2	21	for	for	ADP
esrj-49829	2	22	the	the	DET
esrj-49829	2	23	modeling	modeling	NOUN
esrj-49829	2	24	process	process	NOUN
esrj-49829	2	25	.	.	PUNCT
esrj-49829	3	1	a	a	DET
esrj-49829	3	2	subtractive	subtractive	NOUN
esrj-49829	3	3	clustering	cluster	VERB
esrj-49829	3	4	approach	approach	NOUN
esrj-49829	3	5	was	be	AUX
esrj-49829	3	6	used	use	VERB
esrj-49829	3	7	to	to	PART
esrj-49829	3	8	identify	identify	VERB
esrj-49829	3	9	the	the	DET
esrj-49829	3	10	structure	structure	NOUN
esrj-49829	3	11	of	of	ADP
esrj-49829	3	12	the	the	DET
esrj-49829	3	13	adaptive	adaptive	ADJ
esrj-49829	3	14	neuro	neuro	NOUN
esrj-49829	3	15	-	-	PUNCT
esrj-49829	3	16	fuzzy	fuzzy	ADJ
esrj-49829	3	17	inference	inference	NOUN
esrj-49829	3	18	system	system	NOUN
esrj-49829	3	19	(	(	PUNCT
esrj-49829	3	20	anfis	anfis	PROPN
esrj-49829	3	21	)	)	PUNCT
esrj-49829	3	22	,	,	PUNCT
esrj-49829	3	23	and	and	CCONJ
esrj-49829	3	24	the	the	DET
esrj-49829	3	25	result	result	NOUN
esrj-49829	3	26	of	of	ADP
esrj-49829	3	27	the	the	DET
esrj-49829	3	28	proposed	propose	VERB
esrj-49829	3	29	approach	approach	NOUN
esrj-49829	3	30	was	be	AUX
esrj-49829	3	31	compared	compare	VERB
esrj-49829	3	32	with	with	ADP
esrj-49829	3	33	artificial	artificial	ADJ
esrj-49829	3	34	neural	neural	ADJ
esrj-49829	3	35	networks	network	NOUN
esrj-49829	3	36	(	(	PUNCT
esrj-49829	3	37	anns	anns	PROPN
esrj-49829	3	38	)	)	PUNCT
esrj-49829	3	39	and	and	CCONJ
esrj-49829	3	40	an	an	DET
esrj-49829	3	41	m5	m5	PROPN
esrj-49829	3	42	tree	tree	NOUN
esrj-49829	3	43	model	model	NOUN
esrj-49829	3	44	.	.	PUNCT
esrj-49829	4	1	result	result	NOUN
esrj-49829	4	2	suggests	suggest	VERB
esrj-49829	4	3	an	an	DET
esrj-49829	4	4	improved	improved	ADJ
esrj-49829	4	5	performance	performance	NOUN
esrj-49829	4	6	using	use	VERB
esrj-49829	4	7	the	the	DET
esrj-49829	4	8	anfis	anfis	ADJ
esrj-49829	4	9	approach	approach	NOUN
esrj-49829	4	10	in	in	ADP
esrj-49829	4	11	predicting	predict	VERB
esrj-49829	4	12	soil	soil	NOUN
esrj-49829	4	13	temperatures	temperature	NOUN
esrj-49829	4	14	at	at	ADP
esrj-49829	4	15	various	various	ADJ
esrj-49829	4	16	soil	soil	NOUN
esrj-49829	4	17	depths	depth	NOUN
esrj-49829	4	18	except	except	SCONJ
esrj-49829	4	19	at	at	ADP
esrj-49829	4	20	100	100	NUM
esrj-49829	4	21	cm	cm	NOUN
esrj-49829	4	22	.	.	PUNCT
esrj-49829	5	1	the	the	DET
esrj-49829	5	2	performance	performance	NOUN
esrj-49829	5	3	of	of	ADP
esrj-49829	5	4	the	the	DET
esrj-49829	5	5	anns	anns	NOUN
esrj-49829	5	6	and	and	CCONJ
esrj-49829	5	7	m5	m5	NOUN
esrj-49829	5	8	tree	tree	NOUN
esrj-49829	5	9	models	model	NOUN
esrj-49829	5	10	were	be	AUX
esrj-49829	5	11	found	find	VERB
esrj-49829	5	12	to	to	PART
esrj-49829	5	13	be	be	AUX
esrj-49829	5	14	similar	similar	ADJ
esrj-49829	5	15	.	.	PUNCT
esrj-49829	6	1	however	however	ADV
esrj-49829	6	2	,	,	PUNCT
esrj-49829	6	3	the	the	DET
esrj-49829	6	4	m5	m5	PROPN
esrj-49829	6	5	tree	tree	NOUN
esrj-49829	6	6	model	model	NOUN
esrj-49829	6	7	provides	provide	VERB
esrj-49829	6	8	a	a	DET
esrj-49829	6	9	simple	simple	ADJ
esrj-49829	6	10	linear	linear	NOUN
esrj-49829	6	11	relation	relation	NOUN
esrj-49829	6	12	to	to	ADP
esrj-49829	6	13	predicting	predict	VERB
esrj-49829	6	14	the	the	DET
esrj-49829	6	15	soil	soil	NOUN
esrj-49829	6	16	temperature	temperature	NOUN
esrj-49829	6	17	for	for	ADP
esrj-49829	6	18	the	the	DET
esrj-49829	6	19	data	datum	NOUN
esrj-49829	6	20	ranges	range	NOUN
esrj-49829	6	21	used	use	VERB
esrj-49829	6	22	in	in	ADP
esrj-49829	6	23	this	this	DET
esrj-49829	6	24	study	study	NOUN
esrj-49829	6	25	.	.	PUNCT
esrj-49829	7	1	error	error	NOUN
esrj-49829	7	2	analyses	analysis	NOUN
esrj-49829	7	3	of	of	ADP
esrj-49829	7	4	the	the	DET
esrj-49829	7	5	predicted	predict	VERB
esrj-49829	7	6	values	value	NOUN
esrj-49829	7	7	at	at	ADP
esrj-49829	7	8	various	various	ADJ
esrj-49829	7	9	depths	depth	NOUN
esrj-49829	7	10	show	show	VERB
esrj-49829	7	11	that	that	SCONJ
esrj-49829	7	12	the	the	DET
esrj-49829	7	13	estimation	estimation	NOUN
esrj-49829	7	14	error	error	NOUN
esrj-49829	7	15	tends	tend	VERB
esrj-49829	7	16	to	to	PART
esrj-49829	7	17	increase	increase	VERB
esrj-49829	7	18	with	with	ADP
esrj-49829	7	19	the	the	DET
esrj-49829	7	20	depth	depth	NOUN
esrj-49829	7	21	.	.	PUNCT
esrj-49829	8	1	abstract	abstract	ADJ
esrj-49829	8	2	keywords	keyword	NOUN
esrj-49829	8	3	:	:	PUNCT
esrj-49829	8	4	soil	soil	NOUN
esrj-49829	8	5	temperature	temperature	NOUN
esrj-49829	8	6	;	;	PUNCT
esrj-49829	8	7	data	datum	NOUN
esrj-49829	8	8	mining	mining	NOUN
esrj-49829	8	9	;	;	PUNCT
esrj-49829	8	10	m5	m5	PROPN
esrj-49829	8	11	tree	tree	NOUN
esrj-49829	8	12	model	model	NOUN
esrj-49829	8	13	;	;	PUNCT
esrj-49829	8	14	anfis	anfis	PROPN
esrj-49829	8	15	;	;	PUNCT
esrj-49829	8	16	ann	ann	PROPN
esrj-49829	8	17	.	.	PROPN
esrj-49829	8	18	estimation	estimation	NOUN
esrj-49829	8	19	of	of	ADP
esrj-49829	8	20	daily	daily	ADJ
esrj-49829	8	21	soil	soil	NOUN
esrj-49829	8	22	temperature	temperature	NOUN
esrj-49829	8	23	via	via	ADP
esrj-49829	8	24	data	datum	NOUN
esrj-49829	8	25	mining	mining	NOUN
esrj-49829	8	26	techniques	technique	NOUN
esrj-49829	8	27	in	in	ADP
esrj-49829	8	28	semi	semi	ADJ
esrj-49829	8	29	-	-	ADJ
esrj-49829	8	30	arid	arid	ADJ
esrj-49829	8	31	climate	climate	NOUN
esrj-49829	8	32	conditions	condition	NOUN
esrj-49829	8	33	issn	issn	VERB
esrj-49829	8	34	1794	1794	NUM
esrj-49829	8	35	-	-	SYM
esrj-49829	8	36	6190	6190	NUM
esrj-49829	8	37	e	e	NOUN
esrj-49829	8	38	-	-	NOUN
esrj-49829	8	39	issn	issn	PROPN
esrj-49829	8	40	2339	2339	NUM
esrj-49829	8	41	-	-	SYM
esrj-49829	8	42	3459	3459	NUM
esrj-49829	8	43	http://dx.doi.org/10.15446/esrj.v21n2.49829	http://dx.doi.org/10.15446/esrj.v21n2.49829	PRON
esrj-49829	8	44	earth	earth	NOUN
esrj-49829	8	45	sciences	sciences	PROPN
esrj-49829	8	46	research	research	PROPN
esrj-49829	8	47	journal	journal	PROPN
esrj-49829	8	48	earth	earth	PROPN
esrj-49829	8	49	sci	sci	PROPN
esrj-49829	8	50	.	.	PUNCT
esrj-49829	9	1	res	res	PROPN
esrj-49829	9	2	.	.	PUNCT
esrj-49829	10	1	j.	j.	PROPN
esrj-49829	10	2	vol	vol	PROPN
esrj-49829	10	3	.	.	PROPN
esrj-49829	11	1	21	21	NUM
esrj-49829	11	2	,	,	PUNCT
esrj-49829	11	3	no	no	INTJ
esrj-49829	11	4	.	.	NOUN
esrj-49829	11	5	2	2	NUM
esrj-49829	11	6	(	(	PUNCT
esrj-49829	11	7	june	june	PROPN
esrj-49829	11	8	,	,	PUNCT
esrj-49829	11	9	2017	2017	NUM
esrj-49829	11	10	):	):	PUNCT
esrj-49829	11	11	85	85	NUM
esrj-49829	11	12	93	93	NUM
esrj-49829	11	13	m.	m.	NOUN
esrj-49829	11	14	taghi	taghi	NOUN
esrj-49829	11	15	sattari1	sattari1	PROPN
esrj-49829	11	16	*	*	PUNCT
esrj-49829	11	17	,	,	PUNCT
esrj-49829	11	18	esmaeel	esmaeel	VERB
esrj-49829	11	19	dodangeh2	dodangeh2	NOUN
esrj-49829	11	20	,	,	PUNCT
esrj-49829	11	21	john	john	PROPN
esrj-49829	11	22	abraham3	abraham3	PROPN
esrj-49829	12	1	*	*	PUNCT
esrj-49829	12	2	1department	1department	NUM
esrj-49829	12	3	of	of	ADP
esrj-49829	12	4	water	water	NOUN
esrj-49829	12	5	engineering	engineering	NOUN
esrj-49829	12	6	,	,	PUNCT
esrj-49829	12	7	faculty	faculty	NOUN
esrj-49829	12	8	of	of	ADP
esrj-49829	12	9	agriculture	agriculture	NOUN
esrj-49829	12	10	,	,	PUNCT
esrj-49829	12	11	university	university	NOUN
esrj-49829	12	12	of	of	ADP
esrj-49829	12	13	tabriz	tabriz	PROPN
esrj-49829	12	14	,	,	PUNCT
esrj-49829	12	15	tabriz	tabriz	NOUN
esrj-49829	12	16	,	,	PUNCT
esrj-49829	12	17	iran	iran	PROPN
esrj-49829	12	18	.	.	PUNCT
esrj-49829	13	1	email	email	NOUN
esrj-49829	13	2	:	:	PUNCT
esrj-49829	13	3	mtsattar@gmail.com	mtsattar@gmail.com	X
esrj-49829	13	4	(	(	PUNCT
esrj-49829	13	5	corresponding	corresponding	ADJ
esrj-49829	13	6	author	author	NOUN
esrj-49829	13	7	)	)	PUNCT
esrj-49829	13	8	,	,	PUNCT
esrj-49829	13	9	2department	2department	NUM
esrj-49829	13	10	of	of	ADP
esrj-49829	13	11	natural	natural	ADJ
esrj-49829	13	12	resources	resource	NOUN
esrj-49829	13	13	,	,	PUNCT
esrj-49829	13	14	sari	sari	ADJ
esrj-49829	13	15	university	university	NOUN
esrj-49829	13	16	of	of	ADP
esrj-49829	13	17	agriculture	agriculture	NOUN
esrj-49829	13	18	and	and	CCONJ
esrj-49829	13	19	natural	natural	ADJ
esrj-49829	13	20	resources	resource	NOUN
esrj-49829	13	21	,	,	PUNCT
esrj-49829	13	22	sari	sari	NOUN
esrj-49829	13	23	,	,	PUNCT
esrj-49829	13	24	iran	iran	PROPN
esrj-49829	13	25	.	.	PUNCT
esrj-49829	14	1	email	email	NOUN
esrj-49829	14	2	:	:	PUNCT
esrj-49829	14	3	smaeel.dodangeh@gmail.com	smaeel.dodangeh@gmail.com	PROPN
esrj-49829	14	4	3university	3university	PROPN
esrj-49829	14	5	of	of	ADP
esrj-49829	14	6	st	st	PROPN
esrj-49829	14	7	.	.	PROPN
esrj-49829	14	8	thomas	thomas	PROPN
esrj-49829	14	9	,	,	PUNCT
esrj-49829	14	10	minnesota	minnesota	PROPN
esrj-49829	14	11	,	,	PUNCT
esrj-49829	14	12	school	school	NOUN
esrj-49829	14	13	of	of	ADP
esrj-49829	14	14	engineering	engineering	NOUN
esrj-49829	14	15	2115	2115	NUM
esrj-49829	14	16	summit	summit	PROPN
esrj-49829	14	17	avenue	avenue	PROPN
esrj-49829	14	18	st	st	PROPN
esrj-49829	14	19	.	.	PROPN
esrj-49829	14	20	paul	paul	PROPN
esrj-49829	14	21	,	,	PUNCT
esrj-49829	14	22	minnesota	minnesota	PROPN
esrj-49829	14	23	55105	55105	NUM
esrj-49829	14	24	,	,	PUNCT
esrj-49829	14	25	usa	usa	PROPN
esrj-49829	14	26	.	.	PUNCT
esrj-49829	15	1	jpabraham@stthomas.edu	jpabraham@stthomas.edu	PROPN
esrj-49829	15	2	este	este	PROPN
esrj-49829	15	3	artículo	artículo	PROPN
esrj-49829	15	4	investiga	investiga	PROPN
esrj-49829	15	5	el	el	PROPN
esrj-49829	15	6	potencial	potencial	PROPN
esrj-49829	15	7	de	de	PROPN
esrj-49829	15	8	las	las	PROPN
esrj-49829	15	9	técnicas	técnicas	PROPN
esrj-49829	15	10	de	de	X
esrj-49829	15	11	búsqueda	búsqueda	PROPN
esrj-49829	15	12	y	y	PROPN
esrj-49829	15	13	procesamiento	procesamiento	PROPN
esrj-49829	15	14	de	de	X
esrj-49829	15	15	datos	datos	PROPN
esrj-49829	15	16	para	para	PROPN
esrj-49829	15	17	pronosticar	pronosticar	PROPN
esrj-49829	15	18	las	las	PROPN
esrj-49829	15	19	temperaturas	temperaturas	PROPN
esrj-49829	15	20	diarias	diarias	AUX
esrj-49829	15	21	del	del	PROPN
esrj-49829	15	22	suelo	suelo	NOUN
esrj-49829	15	23	a	a	DET
esrj-49829	15	24	profundidades	profundidade	NOUN
esrj-49829	15	25	que	que	PROPN
esrj-49829	15	26	van	van	PROPN
esrj-49829	15	27	de	de	X
esrj-49829	15	28	los	los	PROPN
esrj-49829	15	29	5	5	NUM
esrj-49829	15	30	a	a	DET
esrj-49829	15	31	los	los	PROPN
esrj-49829	15	32	100	100	NUM
esrj-49829	15	33	cm	cm	NOUN
esrj-49829	15	34	con	con	NOUN
esrj-49829	15	35	propósitos	propósito	NOUN
esrj-49829	15	36	agrícolas	agrícola	VERB
esrj-49829	15	37	.	.	PUNCT
esrj-49829	15	38	se	se	PROPN
esrj-49829	15	39	utilizó	utilizó	PROPN
esrj-49829	15	40	la	la	PROPN
esrj-49829	15	41	información	información	PROPN
esrj-49829	15	42	climática	climática	PROPN
esrj-49829	15	43	y	y	PROPN
esrj-49829	15	44	de	de	PROPN
esrj-49829	15	45	temperatura	temperatura	PROPN
esrj-49829	15	46	del	del	PROPN
esrj-49829	15	47	suelo	suelo	PROPN
esrj-49829	15	48	de	de	X
esrj-49829	15	49	la	la	X
esrj-49829	15	50	provincia	provincia	PROPN
esrj-49829	15	51	ishafan	ishafan	NOUN
esrj-49829	15	52	,	,	PUNCT
esrj-49829	15	53	ubicada	ubicada	PROPN
esrj-49829	15	54	en	en	PROPN
esrj-49829	15	55	el	el	PROPN
esrj-49829	15	56	centro	centro	PROPN
esrj-49829	15	57	de	de	X
esrj-49829	15	58	irán	irán	PROPN
esrj-49829	15	59	y	y	PROPN
esrj-49829	15	60	de	de	PROPN
esrj-49829	15	61	clima	clima	PROPN
esrj-49829	15	62	semiárido	semiárido	PROPN
esrj-49829	15	63	,	,	PUNCT
esrj-49829	15	64	para	para	PROPN
esrj-49829	15	65	el	el	PROPN
esrj-49829	15	66	proceso	proceso	PROPN
esrj-49829	15	67	de	de	X
esrj-49829	15	68	modelamiento	modelamiento	PROPN
esrj-49829	15	69	.	.	PUNCT
esrj-49829	16	1	se	se	PROPN
esrj-49829	16	2	usó	usó	PROPN
esrj-49829	16	3	un	un	PROPN
esrj-49829	16	4	enfoque	enfoque	PROPN
esrj-49829	16	5	de	de	PROPN
esrj-49829	16	6	agrupamiento	agrupamiento	ADP
esrj-49829	16	7	sustractivo	sustractivo	PROPN
esrj-49829	16	8	para	para	PROPN
esrj-49829	16	9	identificar	identificar	PROPN
esrj-49829	16	10	la	la	PROPN
esrj-49829	16	11	estructura	estructura	PROPN
esrj-49829	16	12	del	del	PROPN
esrj-49829	16	13	sistema	sistema	PROPN
esrj-49829	16	14	de	de	X
esrj-49829	16	15	inferencia	inferencia	NOUN
esrj-49829	16	16	neuronal	neuronal	ADJ
esrj-49829	16	17	difuso	difuso	NOUN
esrj-49829	16	18	adaptado	adaptado	NOUN
esrj-49829	16	19	(	(	PUNCT
esrj-49829	16	20	anfis	anfis	PROPN
esrj-49829	16	21	,	,	PUNCT
esrj-49829	16	22	del	del	PROPN
esrj-49829	16	23	inglés	inglés	PROPN
esrj-49829	16	24	adaptive	adaptive	ADJ
esrj-49829	16	25	neuro	neuro	NOUN
esrj-49829	16	26	-	-	PUNCT
esrj-49829	16	27	fuzzy	fuzzy	ADJ
esrj-49829	16	28	inference	inference	NOUN
esrj-49829	16	29	system	system	NOUN
esrj-49829	16	30	)	)	PUNCT
esrj-49829	17	1	y	y	PROPN
esrj-49829	17	2	el	el	PROPN
esrj-49829	17	3	resultado	resultado	VERB
esrj-49829	17	4	del	del	PROPN
esrj-49829	17	5	acercamiento	acercamiento	PROPN
esrj-49829	17	6	propuesto	propuesto	PROPN
esrj-49829	17	7	se	se	PROPN
esrj-49829	17	8	comparó	comparó	PROPN
esrj-49829	17	9	con	con	PROPN
esrj-49829	17	10	redes	redes	PROPN
esrj-49829	17	11	artificiales	artificiales	PROPN
esrj-49829	17	12	neuronales	neuronales	PROPN
esrj-49829	17	13	(	(	PUNCT
esrj-49829	17	14	ann	ann	PROPN
esrj-49829	17	15	)	)	PUNCT
esrj-49829	17	16	y	y	PROPN
esrj-49829	17	17	el	el	PROPN
esrj-49829	17	18	modelo	modelo	PROPN
esrj-49829	17	19	tipo	tipo	PROPN
esrj-49829	17	20	árbol	árbol	PROPN
esrj-49829	17	21	m5	m5	PROPN
esrj-49829	17	22	.	.	PUNCT
esrj-49829	18	1	los	los	PROPN
esrj-49829	18	2	resultados	resultados	PROPN
esrj-49829	18	3	sugieren	sugieren	PROPN
esrj-49829	18	4	un	un	PROPN
esrj-49829	18	5	desempeño	desempeño	PROPN
esrj-49829	18	6	mejorado	mejorado	PROPN
esrj-49829	18	7	al	al	PROPN
esrj-49829	18	8	usar	usar	PROPN
esrj-49829	18	9	el	el	PROPN
esrj-49829	18	10	enfoque	enfoque	PROPN
esrj-49829	18	11	anfis	anfi	VERB
esrj-49829	18	12	en	en	X
esrj-49829	18	13	la	la	PROPN
esrj-49829	18	14	predicción	predicción	PROPN
esrj-49829	18	15	de	de	PROPN
esrj-49829	18	16	las	las	PROPN
esrj-49829	18	17	temperaturas	temperaturas	PROPN
esrj-49829	18	18	del	del	PROPN
esrj-49829	18	19	suelo	suelo	PROPN
esrj-49829	18	20	en	en	ADP
esrj-49829	18	21	varios	vario	NOUN
esrj-49829	18	22	puntos	puntos	PROPN
esrj-49829	18	23	de	de	PROPN
esrj-49829	18	24	profundidad	profundidad	PROPN
esrj-49829	18	25	,	,	PUNCT
esrj-49829	18	26	excepto	excepto	X
esrj-49829	18	27	en	en	X
esrj-49829	18	28	los	los	PROPN
esrj-49829	18	29	100	100	NUM
esrj-49829	18	30	cm	cm	NOUN
esrj-49829	18	31	.	.	PUNCT
esrj-49829	19	1	el	el	PROPN
esrj-49829	19	2	desempeño	desempeño	PROPN
esrj-49829	19	3	de	de	PROPN
esrj-49829	19	4	las	las	PROPN
esrj-49829	19	5	redes	redes	PROPN
esrj-49829	19	6	artificiales	artificiales	PROPN
esrj-49829	19	7	neuronales	neuronales	PROPN
esrj-49829	19	8	y	y	PROPN
esrj-49829	19	9	los	los	PROPN
esrj-49829	19	10	modelos	modelos	PROPN
esrj-49829	19	11	de	de	X
esrj-49829	19	12	árbol	árbol	PROPN
esrj-49829	19	13	m5	m5	PROPN
esrj-49829	19	14	fueron	fueron	PROPN
esrj-49829	19	15	similares	similares	PROPN
esrj-49829	19	16	.	.	PUNCT
esrj-49829	20	1	sin	sin	PROPN
esrj-49829	20	2	embargo	embargo	PROPN
esrj-49829	20	3	,	,	PUNCT
esrj-49829	20	4	el	el	PROPN
esrj-49829	20	5	modelo	modelo	PROPN
esrj-49829	20	6	tipo	tipo	PROPN
esrj-49829	20	7	árbol	árbol	PROPN
esrj-49829	20	8	m5	m5	PROPN
esrj-49829	20	9	provee	provee	PROPN
esrj-49829	20	10	una	una	PROPN
esrj-49829	20	11	relación	relación	PROPN
esrj-49829	20	12	linear	linear	PROPN
esrj-49829	20	13	simple	simple	ADJ
esrj-49829	20	14	para	para	NOUN
esrj-49829	20	15	predecir	predecir	NOUN
esrj-49829	20	16	los	los	PROPN
esrj-49829	20	17	rangos	rangos	PROPN
esrj-49829	20	18	de	de	X
esrj-49829	20	19	datos	datos	X
esrj-49829	20	20	de	de	PROPN
esrj-49829	20	21	la	la	PROPN
esrj-49829	20	22	temperatura	temperatura	PROPN
esrj-49829	20	23	del	del	PROPN
esrj-49829	20	24	suelo	suelo	PROPN
esrj-49829	20	25	utilizados	utilizado	NOUN
esrj-49829	20	26	en	en	X
esrj-49829	20	27	este	este	X
esrj-49829	20	28	estudio	estudio	NOUN
esrj-49829	20	29	.	.	PUNCT
esrj-49829	21	1	los	los	PROPN
esrj-49829	21	2	análisis	análisis	PROPN
esrj-49829	21	3	de	de	X
esrj-49829	21	4	error	error	PROPN
esrj-49829	21	5	de	de	X
esrj-49829	21	6	los	los	PROPN
esrj-49829	21	7	valores	valores	PROPN
esrj-49829	21	8	predichos	predichos	PROPN
esrj-49829	21	9	a	a	DET
esrj-49829	21	10	varias	varias	PROPN
esrj-49829	21	11	profundidades	profundidade	NOUN
esrj-49829	21	12	muestran	muestran	ADJ
esrj-49829	21	13	que	que	X
esrj-49829	21	14	la	la	X
esrj-49829	21	15	estimación	estimación	X
esrj-49829	21	16	de	de	X
esrj-49829	21	17	error	error	NOUN
esrj-49829	21	18	tiende	tiende	VERB
esrj-49829	21	19	a	a	DET
esrj-49829	21	20	incrementarse	incrementarse	NOUN
esrj-49829	21	21	con	con	PROPN
esrj-49829	21	22	la	la	PROPN
esrj-49829	21	23	profundidad	profundidad	PROPN
esrj-49829	21	24	.	.	PUNCT
esrj-49829	22	1	resumen	resumen	PROPN
esrj-49829	22	2	palabras	palabras	PROPN
esrj-49829	22	3	clave	clave	PROPN
esrj-49829	22	4	:	:	PUNCT
esrj-49829	22	5	temperatura	temperatura	PROPN
esrj-49829	22	6	del	del	PROPN
esrj-49829	22	7	suelo	suelo	PROPN
esrj-49829	22	8	;	;	PUNCT
esrj-49829	22	9	minería	minería	PROPN
esrj-49829	22	10	de	de	X
esrj-49829	22	11	datos	dato	NOUN
esrj-49829	22	12	;	;	PUNCT
esrj-49829	22	13	modelo	modelo	PROPN
esrj-49829	22	14	tipo	tipo	PROPN
esrj-49829	22	15	árbol	árbol	PROPN
esrj-49829	22	16	m5	m5	PROPN
esrj-49829	22	17	;	;	PUNCT
esrj-49829	22	18	anfis	anfi	VERB
esrj-49829	22	19	;	;	PUNCT
esrj-49829	22	20	ann	ann	PROPN
esrj-49829	22	21	record	record	PROPN
esrj-49829	22	22	manuscript	manuscript	NOUN
esrj-49829	22	23	received	receive	VERB
esrj-49829	22	24	:	:	PUNCT
esrj-49829	22	25	26/03/2015	26/03/2015	NUM
esrj-49829	22	26	accepted	accept	VERB
esrj-49829	22	27	for	for	ADP
esrj-49829	22	28	publication	publication	NOUN
esrj-49829	22	29	:	:	PUNCT
esrj-49829	22	30	31/05/2017	31/05/2017	NUM
esrj-49829	22	31	how	how	SCONJ
esrj-49829	22	32	to	to	PART
esrj-49829	22	33	cite	cite	VERB
esrj-49829	22	34	item	item	NOUN
esrj-49829	22	35	:	:	PUNCT
esrj-49829	22	36	sattari	sattari	PROPN
esrj-49829	22	37	,	,	PUNCT
esrj-49829	22	38	m.	m.	NOUN
esrj-49829	22	39	t.	t.	PROPN
esrj-49829	22	40	,	,	PUNCT
esrj-49829	22	41	dodangeh	dodangeh	PROPN
esrj-49829	22	42	,	,	PUNCT
esrj-49829	22	43	e.	e.	PROPN
esrj-49829	22	44	,	,	PUNCT
esrj-49829	22	45	&	&	CCONJ
esrj-49829	22	46	abraham	abraham	PROPN
esrj-49829	22	47	,	,	PUNCT
esrj-49829	22	48	j.	j.	PROPN
esrj-49829	22	49	(	(	PUNCT
esrj-49829	22	50	2017	2017	NUM
esrj-49829	22	51	)	)	PUNCT
esrj-49829	22	52	.	.	PUNCT
esrj-49829	23	1	estimation	estimation	NOUN
esrj-49829	23	2	of	of	ADP
esrj-49829	23	3	daily	daily	ADJ
esrj-49829	23	4	soil	soil	NOUN
esrj-49829	23	5	temperature	temperature	NOUN
esrj-49829	23	6	via	via	ADP
esrj-49829	23	7	data	datum	NOUN
esrj-49829	23	8	mining	mining	NOUN
esrj-49829	23	9	techniques	technique	NOUN
esrj-49829	23	10	in	in	ADP
esrj-49829	23	11	semi	semi	ADJ
esrj-49829	23	12	-	-	ADJ
esrj-49829	23	13	arid	arid	ADJ
esrj-49829	23	14	climate	climate	NOUN
esrj-49829	23	15	conditions	condition	NOUN
esrj-49829	23	16	.	.	PUNCT
esrj-49829	24	1	earth	earth	NOUN
esrj-49829	24	2	sciences	sciences	PROPN
esrj-49829	24	3	research	research	PROPN
esrj-49829	24	4	journal	journal	PROPN
esrj-49829	24	5	,	,	PUNCT
esrj-49829	24	6	21(2	21(2	NUM
esrj-49829	24	7	)	)	PUNCT
esrj-49829	24	8	,	,	PUNCT
esrj-49829	24	9	85	85	NUM
esrj-49829	24	10	93	93	NUM
esrj-49829	24	11	.	.	PUNCT
esrj-49829	25	1	doi	doi	NOUN
esrj-49829	25	2	:	:	PUNCT
esrj-49829	25	3	http://dx.doi.org/10.15446	http://dx.doi.org/10.15446	NOUN
esrj-49829	25	4	/	/	SYM
esrj-49829	25	5	esrj.v21n2	esrj.v21n2	NOUN
esrj-49829	25	6	.	.	PUNCT
esrj-49829	26	1	49829	49829	NUM
esrj-49829	26	2	estimación	estimación	PROPN
esrj-49829	26	3	de	de	X
esrj-49829	26	4	la	la	PROPN
esrj-49829	26	5	temperatura	temperatura	PROPN
esrj-49829	26	6	diaria	diaria	PROPN
esrj-49829	26	7	del	del	PROPN
esrj-49829	26	8	suelo	suelo	VERB
esrj-49829	26	9	a	a	DET
esrj-49829	26	10	través	través	NOUN
esrj-49829	26	11	de	de	X
esrj-49829	26	12	técnicas	técnicas	PROPN
esrj-49829	26	13	de	de	X
esrj-49829	26	14	búsqueda	búsqueda	PROPN
esrj-49829	26	15	y	y	PROPN
esrj-49829	26	16	procesamiento	procesamiento	PROPN
esrj-49829	26	17	de	de	X
esrj-49829	26	18	datos	datos	X
esrj-49829	26	19	en	en	X
esrj-49829	26	20	condiciones	condicione	NOUN
esrj-49829	26	21	climáticas	climática	NOUN
esrj-49829	26	22	semiáridas	semiárida	VERB
esrj-49829	26	23	m	m	VERB
esrj-49829	26	24	e	e	NOUN
esrj-49829	26	25	t	t	NOUN
esrj-49829	26	26	e	e	X
esrj-49829	26	27	o	o	NOUN
esrj-49829	26	28	r	r	NOUN
esrj-49829	26	29	o	o	NOUN
esrj-49829	26	30	l	l	NOUN
esrj-49829	27	1	o	o	X
esrj-49829	27	2	g	g	NOUN
esrj-49829	27	3	y	y	PROPN
esrj-49829	27	4	86	86	NUM
esrj-49829	27	5	m.	m.	NOUN
esrj-49829	27	6	taghi	taghi	PROPN
esrj-49829	27	7	sattari	sattari	PROPN
esrj-49829	27	8	,	,	PUNCT
esrj-49829	27	9	esmaeel	esmaeel	NOUN
esrj-49829	27	10	dodangeh	dodangeh	NOUN
esrj-49829	27	11	,	,	PUNCT
esrj-49829	27	12	john	john	PROPN
esrj-49829	27	13	abraham	abraham	PROPN
esrj-49829	27	14	1	1	X
esrj-49829	27	15	.	.	PUNCT
esrj-49829	28	1	introduction	introduction	NOUN
esrj-49829	28	2	soil	soil	NOUN
esrj-49829	28	3	temperature	temperature	NOUN
esrj-49829	28	4	prediction	prediction	NOUN
esrj-49829	28	5	is	be	AUX
esrj-49829	28	6	important	important	ADJ
esrj-49829	28	7	for	for	ADP
esrj-49829	28	8	various	various	ADJ
esrj-49829	28	9	agricultural	agricultural	ADJ
esrj-49829	28	10	purposes	purpose	NOUN
esrj-49829	28	11	,	,	PUNCT
esrj-49829	28	12	especially	especially	ADV
esrj-49829	28	13	in	in	ADP
esrj-49829	28	14	arid	arid	NOUN
esrj-49829	28	15	and	and	CCONJ
esrj-49829	28	16	semi	semi	ADJ
esrj-49829	28	17	-	-	ADJ
esrj-49829	28	18	arid	arid	ADJ
esrj-49829	28	19	regions	region	NOUN
esrj-49829	28	20	,	,	PUNCT
esrj-49829	28	21	such	such	ADJ
esrj-49829	28	22	as	as	ADP
esrj-49829	28	23	iran	iran	PROPN
esrj-49829	28	24	.	.	PUNCT
esrj-49829	29	1	temporal	temporal	ADJ
esrj-49829	29	2	patterns	pattern	NOUN
esrj-49829	29	3	of	of	ADP
esrj-49829	29	4	soil	soil	NOUN
esrj-49829	29	5	temperatures	temperature	NOUN
esrj-49829	29	6	in	in	ADP
esrj-49829	29	7	these	these	DET
esrj-49829	29	8	regions	region	NOUN
esrj-49829	29	9	show	show	VERB
esrj-49829	29	10	large	large	ADJ
esrj-49829	29	11	seasonal	seasonal	ADJ
esrj-49829	29	12	and	and	CCONJ
esrj-49829	29	13	daily	daily	ADJ
esrj-49829	29	14	fluctuations	fluctuation	NOUN
esrj-49829	29	15	.	.	PUNCT
esrj-49829	30	1	these	these	DET
esrj-49829	30	2	variations	variation	NOUN
esrj-49829	30	3	in	in	ADP
esrj-49829	30	4	soil	soil	NOUN
esrj-49829	30	5	temperature	temperature	NOUN
esrj-49829	30	6	affect	affect	VERB
esrj-49829	30	7	plant	plant	NOUN
esrj-49829	30	8	growth	growth	NOUN
esrj-49829	30	9	directly	directly	ADV
esrj-49829	30	10	through	through	ADP
esrj-49829	30	11	their	their	PRON
esrj-49829	30	12	effect	effect	NOUN
esrj-49829	30	13	on	on	ADP
esrj-49829	30	14	physiological	physiological	ADJ
esrj-49829	30	15	activities	activity	NOUN
esrj-49829	30	16	and	and	CCONJ
esrj-49829	30	17	indirectly	indirectly	ADV
esrj-49829	30	18	through	through	ADP
esrj-49829	30	19	the	the	DET
esrj-49829	30	20	effect	effect	NOUN
esrj-49829	30	21	on	on	ADP
esrj-49829	30	22	soil	soil	NOUN
esrj-49829	30	23	nutrient	nutrient	NOUN
esrj-49829	30	24	availability	availability	NOUN
esrj-49829	30	25	(	(	PUNCT
esrj-49829	30	26	tuntiwaranurk	tuntiwaranurk	NOUN
esrj-49829	30	27	et	et	PROPN
esrj-49829	30	28	al	al	PROPN
esrj-49829	30	29	.	.	PROPN
esrj-49829	30	30	,	,	PUNCT
esrj-49829	30	31	2006	2006	NUM
esrj-49829	30	32	)	)	PUNCT
esrj-49829	30	33	.	.	PUNCT
esrj-49829	31	1	for	for	ADP
esrj-49829	31	2	example	example	NOUN
esrj-49829	31	3	,	,	PUNCT
esrj-49829	31	4	root	root	NOUN
esrj-49829	31	5	growth	growth	NOUN
esrj-49829	31	6	and	and	CCONJ
esrj-49829	31	7	biological	biological	ADJ
esrj-49829	31	8	soil	soil	NOUN
esrj-49829	31	9	activity	activity	NOUN
esrj-49829	31	10	are	be	AUX
esrj-49829	31	11	directly	directly	ADV
esrj-49829	31	12	influenced	influence	VERB
esrj-49829	31	13	by	by	ADP
esrj-49829	31	14	soil	soil	NOUN
esrj-49829	31	15	temperature	temperature	NOUN
esrj-49829	31	16	(	(	PUNCT
esrj-49829	31	17	kang	kang	PROPN
esrj-49829	31	18	et	et	PROPN
esrj-49829	31	19	al	al	PROPN
esrj-49829	31	20	.	.	PROPN
esrj-49829	31	21	,	,	PUNCT
esrj-49829	31	22	2000	2000	NUM
esrj-49829	31	23	)	)	PUNCT
esrj-49829	31	24	.	.	PUNCT
esrj-49829	32	1	soil	soil	NOUN
esrj-49829	32	2	temperature	temperature	NOUN
esrj-49829	32	3	fluctuations	fluctuation	NOUN
esrj-49829	32	4	affect	affect	VERB
esrj-49829	32	5	various	various	ADJ
esrj-49829	32	6	processes	process	NOUN
esrj-49829	32	7	within	within	ADP
esrj-49829	32	8	the	the	DET
esrj-49829	32	9	soil	soil	NOUN
esrj-49829	32	10	such	such	ADJ
esrj-49829	32	11	as	as	ADP
esrj-49829	32	12	microbial	microbial	ADJ
esrj-49829	32	13	decomposition	decomposition	NOUN
esrj-49829	32	14	,	,	PUNCT
esrj-49829	32	15	p	p	NOUN
esrj-49829	32	16	and	and	CCONJ
esrj-49829	32	17	k	k	PROPN
esrj-49829	32	18	absorption	absorption	NOUN
esrj-49829	32	19	,	,	PUNCT
esrj-49829	32	20	soil	soil	NOUN
esrj-49829	32	21	-	-	PUNCT
esrj-49829	32	22	moisture	moisture	NOUN
esrj-49829	32	23	content	content	NOUN
esrj-49829	32	24	(	(	PUNCT
esrj-49829	32	25	elshorbagy	elshorbagy	NOUN
esrj-49829	32	26	and	and	CCONJ
esrj-49829	32	27	parasuraman	parasuraman	NOUN
esrj-49829	32	28	,	,	PUNCT
esrj-49829	32	29	2008	2008	NUM
esrj-49829	32	30	)	)	PUNCT
esrj-49829	32	31	and	and	CCONJ
esrj-49829	32	32	soil	soil	NOUN
esrj-49829	32	33	respiration	respiration	NOUN
esrj-49829	32	34	(	(	PUNCT
esrj-49829	32	35	gaumont	gaumont	NOUN
esrj-49829	32	36	-	-	PUNCT
esrj-49829	32	37	guay	guay	NOUN
esrj-49829	32	38	et	et	NOUN
esrj-49829	32	39	al	al	PROPN
esrj-49829	32	40	.	.	PROPN
esrj-49829	32	41	,	,	PUNCT
esrj-49829	32	42	2006	2006	NUM
esrj-49829	32	43	)	)	PUNCT
esrj-49829	32	44	.	.	PUNCT
esrj-49829	33	1	the	the	DET
esrj-49829	33	2	success	success	NOUN
esrj-49829	33	3	of	of	ADP
esrj-49829	33	4	seeding	seed	VERB
esrj-49829	33	5	efforts	effort	NOUN
esrj-49829	33	6	depends	depend	VERB
esrj-49829	33	7	greatly	greatly	ADV
esrj-49829	33	8	on	on	ADP
esrj-49829	33	9	the	the	DET
esrj-49829	33	10	spatial	spatial	ADJ
esrj-49829	33	11	and	and	CCONJ
esrj-49829	33	12	temporal	temporal	ADJ
esrj-49829	33	13	distribution	distribution	NOUN
esrj-49829	33	14	of	of	ADP
esrj-49829	33	15	soil	soil	NOUN
esrj-49829	33	16	temperature	temperature	NOUN
esrj-49829	33	17	.	.	PUNCT
esrj-49829	34	1	thus	thus	ADV
esrj-49829	34	2	,	,	PUNCT
esrj-49829	34	3	the	the	DET
esrj-49829	34	4	temperature	temperature	NOUN
esrj-49829	34	5	predictions	prediction	NOUN
esrj-49829	34	6	help	help	VERB
esrj-49829	34	7	to	to	PART
esrj-49829	34	8	improve	improve	VERB
esrj-49829	34	9	the	the	DET
esrj-49829	34	10	understanding	understanding	NOUN
esrj-49829	34	11	of	of	ADP
esrj-49829	34	12	the	the	DET
esrj-49829	34	13	dynamics	dynamic	NOUN
esrj-49829	34	14	of	of	ADP
esrj-49829	34	15	vegetation	vegetation	NOUN
esrj-49829	34	16	(	(	PUNCT
esrj-49829	34	17	kang	kang	PROPN
esrj-49829	34	18	et	et	PROPN
esrj-49829	34	19	al	al	PROPN
esrj-49829	34	20	.	.	PROPN
esrj-49829	34	21	,	,	PUNCT
esrj-49829	34	22	2000	2000	NUM
esrj-49829	34	23	)	)	PUNCT
esrj-49829	34	24	.	.	PUNCT
esrj-49829	35	1	it	it	PRON
esrj-49829	35	2	also	also	ADV
esrj-49829	35	3	helps	help	VERB
esrj-49829	35	4	agronomists	agronomist	NOUN
esrj-49829	35	5	and	and	CCONJ
esrj-49829	35	6	engineers	engineer	NOUN
esrj-49829	35	7	to	to	PART
esrj-49829	35	8	decide	decide	VERB
esrj-49829	35	9	the	the	DET
esrj-49829	35	10	proper	proper	ADJ
esrj-49829	35	11	plantation	plantation	NOUN
esrj-49829	35	12	date	date	NOUN
esrj-49829	35	13	,	,	PUNCT
esrj-49829	35	14	design	design	NOUN
esrj-49829	35	15	drainage	drainage	NOUN
esrj-49829	35	16	and	and	CCONJ
esrj-49829	35	17	irrigation	irrigation	NOUN
esrj-49829	35	18	systems	system	NOUN
esrj-49829	35	19	,	,	PUNCT
esrj-49829	35	20	and	and	CCONJ
esrj-49829	35	21	to	to	PART
esrj-49829	35	22	optimize	optimize	VERB
esrj-49829	35	23	the	the	DET
esrj-49829	35	24	application	application	NOUN
esrj-49829	35	25	of	of	ADP
esrj-49829	35	26	pesticides	pesticide	NOUN
esrj-49829	35	27	and	and	CCONJ
esrj-49829	35	28	fertilizers	fertilizer	NOUN
esrj-49829	35	29	to	to	PART
esrj-49829	35	30	reduce	reduce	VERB
esrj-49829	35	31	chemical	chemical	NOUN
esrj-49829	35	32	pollution	pollution	NOUN
esrj-49829	35	33	of	of	ADP
esrj-49829	35	34	soils	soil	NOUN
esrj-49829	35	35	and	and	CCONJ
esrj-49829	35	36	groundwater	groundwater	NOUN
esrj-49829	35	37	.	.	PUNCT
esrj-49829	36	1	for	for	ADP
esrj-49829	36	2	these	these	DET
esrj-49829	36	3	reasons	reason	NOUN
esrj-49829	36	4	,	,	PUNCT
esrj-49829	36	5	understanding	understanding	NOUN
esrj-49829	36	6	of	of	ADP
esrj-49829	36	7	the	the	DET
esrj-49829	36	8	variation	variation	NOUN
esrj-49829	36	9	in	in	ADP
esrj-49829	36	10	soil	soil	NOUN
esrj-49829	36	11	temperature	temperature	NOUN
esrj-49829	36	12	is	be	AUX
esrj-49829	36	13	vital	vital	ADJ
esrj-49829	36	14	.	.	PUNCT
esrj-49829	37	1	however	however	ADV
esrj-49829	37	2	there	there	PRON
esrj-49829	37	3	are	be	VERB
esrj-49829	37	4	very	very	ADV
esrj-49829	37	5	few	few	ADJ
esrj-49829	37	6	climatologic	climatologic	ADJ
esrj-49829	37	7	stations	station	NOUN
esrj-49829	37	8	in	in	ADP
esrj-49829	37	9	arid	arid	NOUN
esrj-49829	37	10	and	and	CCONJ
esrj-49829	37	11	semi	semi	ADJ
esrj-49829	37	12	-	-	ADJ
esrj-49829	37	13	arid	arid	ADJ
esrj-49829	37	14	regions	region	NOUN
esrj-49829	37	15	where	where	SCONJ
esrj-49829	37	16	soil	soil	NOUN
esrj-49829	37	17	temperatures	temperature	NOUN
esrj-49829	37	18	are	be	AUX
esrj-49829	37	19	recorded	record	VERB
esrj-49829	37	20	at	at	ADP
esrj-49829	37	21	various	various	ADJ
esrj-49829	37	22	depths	depth	NOUN
esrj-49829	37	23	.	.	PUNCT
esrj-49829	38	1	it	it	PRON
esrj-49829	38	2	is	be	AUX
esrj-49829	38	3	usually	usually	ADV
esrj-49829	38	4	quite	quite	ADV
esrj-49829	38	5	difficult	difficult	ADJ
esrj-49829	38	6	to	to	PART
esrj-49829	38	7	measure	measure	VERB
esrj-49829	38	8	temperature	temperature	NOUN
esrj-49829	38	9	at	at	ADP
esrj-49829	38	10	depth	depth	NOUN
esrj-49829	38	11	.	.	PUNCT
esrj-49829	39	1	to	to	PART
esrj-49829	39	2	aid	aid	VERB
esrj-49829	39	3	in	in	ADP
esrj-49829	39	4	this	this	DET
esrj-49829	39	5	measurement	measurement	NOUN
esrj-49829	39	6	process	process	NOUN
esrj-49829	39	7	,	,	PUNCT
esrj-49829	39	8	application	application	NOUN
esrj-49829	39	9	of	of	ADP
esrj-49829	39	10	data	data	NOUN
esrj-49829	39	11	-	-	PUNCT
esrj-49829	39	12	driven	drive	VERB
esrj-49829	39	13	models	model	NOUN
esrj-49829	39	14	are	be	AUX
esrj-49829	39	15	used	use	VERB
esrj-49829	39	16	to	to	PART
esrj-49829	39	17	estimate	estimate	VERB
esrj-49829	39	18	daily	daily	ADJ
esrj-49829	39	19	soil	soil	NOUN
esrj-49829	39	20	temperatures	temperature	NOUN
esrj-49829	39	21	in	in	ADP
esrj-49829	39	22	ungaged	ungaged	ADJ
esrj-49829	39	23	homogeneous	homogeneous	ADJ
esrj-49829	39	24	regions	region	NOUN
esrj-49829	39	25	.	.	PUNCT
esrj-49829	40	1	temperatures	temperature	NOUN
esrj-49829	40	2	in	in	ADP
esrj-49829	40	3	soil	soil	NOUN
esrj-49829	40	4	are	be	AUX
esrj-49829	40	5	influenced	influence	VERB
esrj-49829	40	6	by	by	ADP
esrj-49829	40	7	a	a	DET
esrj-49829	40	8	number	number	NOUN
esrj-49829	40	9	of	of	ADP
esrj-49829	40	10	factors	factor	NOUN
esrj-49829	40	11	,	,	PUNCT
esrj-49829	40	12	such	such	ADJ
esrj-49829	40	13	as	as	ADP
esrj-49829	40	14	meteorological	meteorological	ADJ
esrj-49829	40	15	conditions	condition	NOUN
esrj-49829	40	16	(	(	PUNCT
esrj-49829	40	17	i.e.	i.e.	X
esrj-49829	40	18	solar	solar	ADJ
esrj-49829	40	19	radiation	radiation	NOUN
esrj-49829	40	20	and	and	CCONJ
esrj-49829	40	21	air	air	NOUN
esrj-49829	40	22	temperature	temperature	NOUN
esrj-49829	40	23	)	)	PUNCT
esrj-49829	40	24	,	,	PUNCT
esrj-49829	40	25	site	site	NOUN
esrj-49829	40	26	topography	topography	NOUN
esrj-49829	40	27	,	,	PUNCT
esrj-49829	40	28	soil	soil	NOUN
esrj-49829	40	29	water	water	NOUN
esrj-49829	40	30	content	content	NOUN
esrj-49829	40	31	,	,	PUNCT
esrj-49829	40	32	and	and	CCONJ
esrj-49829	40	33	whether	whether	SCONJ
esrj-49829	40	34	the	the	DET
esrj-49829	40	35	surface	surface	NOUN
esrj-49829	40	36	is	be	AUX
esrj-49829	40	37	covered	cover	VERB
esrj-49829	40	38	by	by	ADP
esrj-49829	40	39	litter	litter	NOUN
esrj-49829	40	40	and	and	CCONJ
esrj-49829	40	41	canopies	canopy	NOUN
esrj-49829	40	42	of	of	ADP
esrj-49829	40	43	plants	plant	NOUN
esrj-49829	40	44	.	.	PUNCT
esrj-49829	41	1	many	many	ADJ
esrj-49829	41	2	conceptual	conceptual	ADJ
esrj-49829	41	3	models	model	NOUN
esrj-49829	41	4	have	have	AUX
esrj-49829	41	5	been	be	AUX
esrj-49829	41	6	proposed	propose	VERB
esrj-49829	41	7	to	to	PART
esrj-49829	41	8	model	model	VERB
esrj-49829	41	9	soil	soil	NOUN
esrj-49829	41	10	temperature	temperature	NOUN
esrj-49829	41	11	based	base	VERB
esrj-49829	41	12	upon	upon	SCONJ
esrj-49829	41	13	the	the	DET
esrj-49829	41	14	meteorological	meteorological	ADJ
esrj-49829	41	15	parameters	parameter	NOUN
esrj-49829	41	16	such	such	ADJ
esrj-49829	41	17	as	as	ADP
esrj-49829	41	18	surface	surface	NOUN
esrj-49829	41	19	global	global	ADJ
esrj-49829	41	20	radiation	radiation	NOUN
esrj-49829	41	21	and	and	CCONJ
esrj-49829	41	22	air	air	NOUN
esrj-49829	41	23	temperature	temperature	NOUN
esrj-49829	41	24	(	(	PUNCT
esrj-49829	41	25	kang	kang	PROPN
esrj-49829	41	26	et	et	PROPN
esrj-49829	41	27	al	al	PROPN
esrj-49829	41	28	.	.	PROPN
esrj-49829	41	29	,	,	PUNCT
esrj-49829	41	30	2000	2000	NUM
esrj-49829	41	31	;	;	PUNCT
esrj-49829	41	32	shannon	shannon	PROPN
esrj-49829	41	33	et	et	PROPN
esrj-49829	41	34	al	al	PROPN
esrj-49829	41	35	.	.	PROPN
esrj-49829	41	36	,	,	PUNCT
esrj-49829	41	37	2000	2000	NUM
esrj-49829	41	38	;	;	PUNCT
esrj-49829	42	1	timlin	timlin	PROPN
esrj-49829	42	2	et	et	PROPN
esrj-49829	42	3	al	al	PROPN
esrj-49829	42	4	.	.	PROPN
esrj-49829	42	5	,	,	PUNCT
esrj-49829	42	6	2002	2002	NUM
esrj-49829	42	7	)	)	PUNCT
esrj-49829	42	8	,	,	PUNCT
esrj-49829	42	9	soil	soil	NOUN
esrj-49829	42	10	physical	physical	ADJ
esrj-49829	42	11	parameters	parameter	NOUN
esrj-49829	42	12	,	,	PUNCT
esrj-49829	42	13	such	such	ADJ
esrj-49829	42	14	as	as	ADP
esrj-49829	42	15	water	water	NOUN
esrj-49829	42	16	content	content	NOUN
esrj-49829	42	17	and	and	CCONJ
esrj-49829	42	18	texture	texture	ADJ
esrj-49829	42	19	,	,	PUNCT
esrj-49829	42	20	topographical	topographical	ADJ
esrj-49829	42	21	variables	variable	NOUN
esrj-49829	42	22	such	such	ADJ
esrj-49829	42	23	as	as	ADP
esrj-49829	42	24	elevation	elevation	NOUN
esrj-49829	42	25	,	,	PUNCT
esrj-49829	42	26	slope	slope	NOUN
esrj-49829	42	27	and	and	CCONJ
esrj-49829	42	28	aspect	aspect	NOUN
esrj-49829	42	29	(	(	PUNCT
esrj-49829	42	30	kang	kang	PROPN
esrj-49829	42	31	et	et	PROPN
esrj-49829	42	32	al	al	PROPN
esrj-49829	42	33	.	.	PROPN
esrj-49829	42	34	,	,	PUNCT
esrj-49829	42	35	2000	2000	NUM
esrj-49829	42	36	)	)	PUNCT
esrj-49829	42	37	,	,	PUNCT
esrj-49829	42	38	and	and	CCONJ
esrj-49829	42	39	other	other	ADJ
esrj-49829	42	40	surface	surface	NOUN
esrj-49829	42	41	characteristics	characteristic	NOUN
esrj-49829	42	42	such	such	ADJ
esrj-49829	42	43	as	as	ADP
esrj-49829	42	44	leaf	leaf	NOUN
esrj-49829	42	45	area	area	NOUN
esrj-49829	42	46	index	index	NOUN
esrj-49829	42	47	(	(	PUNCT
esrj-49829	42	48	lai	lai	PROPN
esrj-49829	42	49	)	)	PUNCT
esrj-49829	42	50	and	and	CCONJ
esrj-49829	42	51	ground	ground	NOUN
esrj-49829	42	52	litter	litter	NOUN
esrj-49829	42	53	stores	store	NOUN
esrj-49829	42	54	.	.	PUNCT
esrj-49829	43	1	other	other	ADJ
esrj-49829	43	2	models	model	NOUN
esrj-49829	43	3	such	such	ADJ
esrj-49829	43	4	as	as	ADP
esrj-49829	43	5	multiple	multiple	ADJ
esrj-49829	43	6	regression	regression	NOUN
esrj-49829	43	7	and	and	CCONJ
esrj-49829	43	8	fourier	fouri	ADJ
esrj-49829	43	9	analysis	analysis	NOUN
esrj-49829	43	10	have	have	AUX
esrj-49829	43	11	also	also	ADV
esrj-49829	43	12	been	be	AUX
esrj-49829	43	13	suggested	suggest	VERB
esrj-49829	43	14	with	with	ADP
esrj-49829	43	15	some	some	DET
esrj-49829	43	16	modification	modification	NOUN
esrj-49829	43	17	.	.	PUNCT
esrj-49829	44	1	most	most	ADJ
esrj-49829	44	2	of	of	ADP
esrj-49829	44	3	these	these	DET
esrj-49829	44	4	models	model	NOUN
esrj-49829	44	5	are	be	AUX
esrj-49829	44	6	based	base	VERB
esrj-49829	44	7	on	on	ADP
esrj-49829	44	8	several	several	ADJ
esrj-49829	44	9	assumptions	assumption	NOUN
esrj-49829	44	10	and	and	CCONJ
esrj-49829	44	11	boundary	boundary	ADJ
esrj-49829	44	12	conditions	condition	NOUN
esrj-49829	44	13	resulting	result	VERB
esrj-49829	44	14	in	in	ADP
esrj-49829	44	15	the	the	DET
esrj-49829	44	16	limitations	limitation	NOUN
esrj-49829	44	17	of	of	ADP
esrj-49829	44	18	their	their	PRON
esrj-49829	44	19	use	use	NOUN
esrj-49829	44	20	in	in	ADP
esrj-49829	44	21	practice	practice	NOUN
esrj-49829	44	22	.	.	PUNCT
esrj-49829	45	1	for	for	ADP
esrj-49829	45	2	instance	instance	NOUN
esrj-49829	45	3	,	,	PUNCT
esrj-49829	45	4	kang	kang	PROPN
esrj-49829	45	5	et	et	PROPN
esrj-49829	45	6	al	al	PROPN
esrj-49829	45	7	.	.	PROPN
esrj-49829	46	1	(	(	PUNCT
esrj-49829	46	2	2000	2000	NUM
esrj-49829	46	3	)	)	PUNCT
esrj-49829	46	4	developed	develop	VERB
esrj-49829	46	5	a	a	DET
esrj-49829	46	6	hybrid	hybrid	ADJ
esrj-49829	46	7	soil	soil	NOUN
esrj-49829	46	8	temperature	temperature	NOUN
esrj-49829	46	9	model	model	NOUN
esrj-49829	46	10	based	base	VERB
esrj-49829	46	11	on	on	ADP
esrj-49829	46	12	heat	heat	NOUN
esrj-49829	46	13	transfer	transfer	NOUN
esrj-49829	46	14	physics	physics	NOUN
esrj-49829	46	15	and	and	CCONJ
esrj-49829	46	16	a	a	DET
esrj-49829	46	17	relationship	relationship	NOUN
esrj-49829	46	18	between	between	ADP
esrj-49829	46	19	air	air	NOUN
esrj-49829	46	20	and	and	CCONJ
esrj-49829	46	21	soil	soil	NOUN
esrj-49829	46	22	temperature	temperature	NOUN
esrj-49829	46	23	to	to	PART
esrj-49829	46	24	predict	predict	VERB
esrj-49829	46	25	daily	daily	ADJ
esrj-49829	46	26	spatial	spatial	ADJ
esrj-49829	46	27	patterns	pattern	NOUN
esrj-49829	46	28	of	of	ADP
esrj-49829	46	29	soil	soil	NOUN
esrj-49829	46	30	temperature	temperature	NOUN
esrj-49829	46	31	in	in	ADP
esrj-49829	46	32	a	a	DET
esrj-49829	46	33	forested	forest	VERB
esrj-49829	46	34	landscape	landscape	NOUN
esrj-49829	46	35	.	.	PUNCT
esrj-49829	47	1	they	they	PRON
esrj-49829	47	2	incorporated	incorporate	VERB
esrj-49829	47	3	the	the	DET
esrj-49829	47	4	effects	effect	NOUN
esrj-49829	47	5	of	of	ADP
esrj-49829	47	6	topography	topography	NOUN
esrj-49829	47	7	,	,	PUNCT
esrj-49829	47	8	canopy	canopy	NOUN
esrj-49829	47	9	and	and	CCONJ
esrj-49829	47	10	ground	ground	NOUN
esrj-49829	47	11	litter	litter	NOUN
esrj-49829	47	12	.	.	PUNCT
esrj-49829	48	1	despite	despite	SCONJ
esrj-49829	48	2	of	of	ADP
esrj-49829	48	3	the	the	DET
esrj-49829	48	4	availability	availability	NOUN
esrj-49829	48	5	of	of	ADP
esrj-49829	48	6	different	different	ADJ
esrj-49829	48	7	models	model	NOUN
esrj-49829	48	8	to	to	PART
esrj-49829	48	9	predict	predict	VERB
esrj-49829	48	10	the	the	DET
esrj-49829	48	11	soil	soil	NOUN
esrj-49829	48	12	temperature	temperature	NOUN
esrj-49829	48	13	,	,	PUNCT
esrj-49829	48	14	these	these	DET
esrj-49829	48	15	models	model	NOUN
esrj-49829	48	16	are	be	AUX
esrj-49829	48	17	found	find	VERB
esrj-49829	48	18	to	to	PART
esrj-49829	48	19	work	work	VERB
esrj-49829	48	20	well	well	ADV
esrj-49829	48	21	only	only	ADV
esrj-49829	48	22	for	for	ADP
esrj-49829	48	23	specific	specific	ADJ
esrj-49829	48	24	climatic	climatic	ADJ
esrj-49829	48	25	and	and	CCONJ
esrj-49829	48	26	agronomic	agronomic	ADJ
esrj-49829	48	27	conditions	condition	NOUN
esrj-49829	48	28	under	under	ADP
esrj-49829	48	29	which	which	PRON
esrj-49829	48	30	they	they	PRON
esrj-49829	48	31	were	be	AUX
esrj-49829	48	32	originally	originally	ADV
esrj-49829	48	33	developed	develop	VERB
esrj-49829	48	34	.	.	PUNCT
esrj-49829	49	1	over	over	ADP
esrj-49829	49	2	past	past	ADJ
esrj-49829	49	3	decades	decade	NOUN
esrj-49829	49	4	,	,	PUNCT
esrj-49829	49	5	remote	remote	ADJ
esrj-49829	49	6	sensing	sensing	NOUN
esrj-49829	49	7	techniques	technique	NOUN
esrj-49829	49	8	have	have	AUX
esrj-49829	49	9	also	also	ADV
esrj-49829	49	10	been	be	AUX
esrj-49829	49	11	utilized	utilize	VERB
esrj-49829	49	12	to	to	PART
esrj-49829	49	13	measure	measure	VERB
esrj-49829	49	14	and	and	CCONJ
esrj-49829	49	15	predict	predict	VERB
esrj-49829	49	16	soil	soil	NOUN
esrj-49829	49	17	temperature	temperature	NOUN
esrj-49829	49	18	over	over	ADP
esrj-49829	49	19	large	large	ADJ
esrj-49829	49	20	areas	area	NOUN
esrj-49829	49	21	but	but	CCONJ
esrj-49829	49	22	a	a	DET
esrj-49829	49	23	major	major	ADJ
esrj-49829	49	24	drawback	drawback	NOUN
esrj-49829	49	25	of	of	ADP
esrj-49829	49	26	this	this	DET
esrj-49829	49	27	approach	approach	NOUN
esrj-49829	49	28	is	be	AUX
esrj-49829	49	29	the	the	DET
esrj-49829	49	30	availability	availability	NOUN
esrj-49829	49	31	of	of	ADP
esrj-49829	49	32	soil	soil	NOUN
esrj-49829	49	33	temperature	temperature	NOUN
esrj-49829	49	34	data	datum	NOUN
esrj-49829	49	35	in	in	ADP
esrj-49829	49	36	the	the	DET
esrj-49829	49	37	top	top	ADJ
esrj-49829	49	38	few	few	ADJ
esrj-49829	49	39	centimeters	centimeter	NOUN
esrj-49829	49	40	(	(	PUNCT
esrj-49829	49	41	elshorbagy	elshorbagy	NOUN
esrj-49829	49	42	and	and	CCONJ
esrj-49829	49	43	parasuraman	parasuraman	NOUN
esrj-49829	49	44	,	,	PUNCT
esrj-49829	49	45	2008	2008	NUM
esrj-49829	49	46	)	)	PUNCT
esrj-49829	49	47	.	.	PUNCT
esrj-49829	50	1	the	the	DET
esrj-49829	50	2	temperature	temperature	NOUN
esrj-49829	50	3	of	of	ADP
esrj-49829	50	4	the	the	DET
esrj-49829	50	5	soil	soil	NOUN
esrj-49829	50	6	profile	profile	NOUN
esrj-49829	50	7	with	with	ADP
esrj-49829	50	8	increasing	increase	VERB
esrj-49829	50	9	depth	depth	NOUN
esrj-49829	50	10	is	be	AUX
esrj-49829	50	11	difficult	difficult	ADJ
esrj-49829	50	12	to	to	PART
esrj-49829	50	13	predict	predict	VERB
esrj-49829	50	14	so	so	SCONJ
esrj-49829	50	15	that	that	SCONJ
esrj-49829	50	16	the	the	DET
esrj-49829	50	17	abovementioned	abovementioned	ADJ
esrj-49829	50	18	techniques	technique	NOUN
esrj-49829	50	19	are	be	AUX
esrj-49829	50	20	limited	limit	VERB
esrj-49829	50	21	to	to	ADP
esrj-49829	50	22	shallow	shallow	ADJ
esrj-49829	50	23	soils	soil	NOUN
esrj-49829	50	24	(	(	PUNCT
esrj-49829	50	25	tyronese	tyronese	NOUN
esrj-49829	50	26	et	et	NOUN
esrj-49829	50	27	al	al	PROPN
esrj-49829	50	28	.	.	PROPN
esrj-49829	50	29	,	,	PUNCT
esrj-49829	50	30	2008	2008	NUM
esrj-49829	50	31	)	)	PUNCT
esrj-49829	50	32	.	.	PUNCT
esrj-49829	51	1	within	within	ADP
esrj-49829	51	2	the	the	DET
esrj-49829	51	3	last	last	ADJ
esrj-49829	51	4	decade	decade	NOUN
esrj-49829	51	5	,	,	PUNCT
esrj-49829	51	6	artificial	artificial	ADJ
esrj-49829	51	7	intelligent	intelligent	ADJ
esrj-49829	51	8	(	(	PUNCT
esrj-49829	51	9	ai	ai	NOUN
esrj-49829	51	10	)	)	PUNCT
esrj-49829	51	11	systems	system	NOUN
esrj-49829	51	12	such	such	ADJ
esrj-49829	51	13	as	as	ADP
esrj-49829	51	14	fuzzy	fuzzy	ADJ
esrj-49829	51	15	logic	logic	NOUN
esrj-49829	51	16	(	(	PUNCT
esrj-49829	51	17	fl	fl	NOUN
esrj-49829	51	18	)	)	PUNCT
esrj-49829	51	19	and	and	CCONJ
esrj-49829	51	20	artificial	artificial	ADJ
esrj-49829	51	21	neural	neural	ADJ
esrj-49829	51	22	networks	network	NOUN
esrj-49829	51	23	(	(	PUNCT
esrj-49829	51	24	anns	anns	PROPN
esrj-49829	51	25	)	)	PUNCT
esrj-49829	51	26	have	have	AUX
esrj-49829	51	27	effectively	effectively	ADV
esrj-49829	51	28	been	be	AUX
esrj-49829	51	29	used	use	VERB
esrj-49829	51	30	to	to	PART
esrj-49829	51	31	model	model	VERB
esrj-49829	51	32	nonlinear	nonlinear	ADJ
esrj-49829	51	33	and	and	CCONJ
esrj-49829	51	34	non	non	ADJ
esrj-49829	51	35	-	-	ADJ
esrj-49829	51	36	stationary	stationary	ADJ
esrj-49829	51	37	process	process	NOUN
esrj-49829	51	38	(	(	PUNCT
esrj-49829	51	39	shiri	shiri	PROPN
esrj-49829	51	40	and	and	CCONJ
esrj-49829	51	41	kisi	kisi	PROPN
esrj-49829	51	42	,	,	PUNCT
esrj-49829	51	43	2011	2011	NUM
esrj-49829	51	44	)	)	PUNCT
esrj-49829	51	45	.	.	PUNCT
esrj-49829	52	1	anns	anns	PROPN
esrj-49829	52	2	are	be	AUX
esrj-49829	52	3	mathematical	mathematical	ADJ
esrj-49829	52	4	models	model	NOUN
esrj-49829	52	5	consisting	consist	VERB
esrj-49829	52	6	of	of	ADP
esrj-49829	52	7	a	a	DET
esrj-49829	52	8	network	network	NOUN
esrj-49829	52	9	of	of	ADP
esrj-49829	52	10	computation	computation	NOUN
esrj-49829	52	11	nodes	node	NOUN
esrj-49829	52	12	called	call	VERB
esrj-49829	52	13	neurons	neuron	NOUN
esrj-49829	52	14	with	with	ADP
esrj-49829	52	15	established	establish	VERB
esrj-49829	52	16	connections	connection	NOUN
esrj-49829	52	17	between	between	ADP
esrj-49829	52	18	them	they	PRON
esrj-49829	52	19	.	.	PUNCT
esrj-49829	53	1	fuzzy	fuzzy	ADJ
esrj-49829	53	2	logic	logic	NOUN
esrj-49829	53	3	is	be	AUX
esrj-49829	53	4	an	an	DET
esrj-49829	53	5	alternative	alternative	ADJ
esrj-49829	53	6	technique	technique	NOUN
esrj-49829	53	7	capable	capable	ADJ
esrj-49829	53	8	of	of	ADP
esrj-49829	53	9	generating	generating	NOUN
esrj-49829	53	10	models	model	NOUN
esrj-49829	53	11	that	that	PRON
esrj-49829	53	12	incorporate	incorporate	VERB
esrj-49829	53	13	expert	expert	ADJ
esrj-49829	53	14	knowledge	knowledge	NOUN
esrj-49829	53	15	and	and	CCONJ
esrj-49829	53	16	available	available	ADJ
esrj-49829	53	17	measurements	measurement	NOUN
esrj-49829	53	18	for	for	ADP
esrj-49829	53	19	a	a	DET
esrj-49829	53	20	system	system	NOUN
esrj-49829	53	21	by	by	ADP
esrj-49829	53	22	using	use	VERB
esrj-49829	53	23	a	a	DET
esrj-49829	53	24	set	set	NOUN
esrj-49829	53	25	of	of	ADP
esrj-49829	53	26	easily	easily	ADV
esrj-49829	53	27	comprehensible	comprehensible	ADJ
esrj-49829	53	28	rules	rule	NOUN
esrj-49829	53	29	in	in	ADP
esrj-49829	53	30	the	the	DET
esrj-49829	53	31	form	form	NOUN
esrj-49829	53	32	of	of	ADP
esrj-49829	53	33	a	a	DET
esrj-49829	53	34	fuzzy	fuzzy	ADJ
esrj-49829	53	35	inference	inference	NOUN
esrj-49829	53	36	system	system	NOUN
esrj-49829	53	37	(	(	PUNCT
esrj-49829	53	38	fis	fis	PROPN
esrj-49829	53	39	)	)	PUNCT
esrj-49829	53	40	(	(	PUNCT
esrj-49829	53	41	zadeh	zadeh	PROPN
esrj-49829	53	42	,	,	PUNCT
esrj-49829	53	43	1965	1965	NUM
esrj-49829	53	44	)	)	PUNCT
esrj-49829	53	45	.	.	PUNCT
esrj-49829	54	1	a	a	DET
esrj-49829	54	2	fis	fis	PROPN
esrj-49829	54	3	is	be	AUX
esrj-49829	54	4	a	a	DET
esrj-49829	54	5	nonlinear	nonlinear	ADJ
esrj-49829	54	6	mapping	mapping	NOUN
esrj-49829	54	7	of	of	ADP
esrj-49829	54	8	a	a	DET
esrj-49829	54	9	given	give	VERB
esrj-49829	54	10	input	input	NOUN
esrj-49829	54	11	vector	vector	NOUN
esrj-49829	54	12	to	to	ADP
esrj-49829	54	13	an	an	DET
esrj-49829	54	14	output	output	NOUN
esrj-49829	54	15	using	use	VERB
esrj-49829	54	16	fuzzy	fuzzy	ADJ
esrj-49829	54	17	logic	logic	NOUN
esrj-49829	54	18	based	base	VERB
esrj-49829	54	19	on	on	ADP
esrj-49829	54	20	a	a	DET
esrj-49829	54	21	set	set	NOUN
esrj-49829	54	22	of	of	ADP
esrj-49829	54	23	membership	membership	NOUN
esrj-49829	54	24	functions	function	NOUN
esrj-49829	54	25	and	and	CCONJ
esrj-49829	54	26	rules	rule	NOUN
esrj-49829	54	27	.	.	PUNCT
esrj-49829	55	1	improved	improved	ADJ
esrj-49829	55	2	performance	performance	NOUN
esrj-49829	55	3	can	can	AUX
esrj-49829	55	4	be	be	AUX
esrj-49829	55	5	obtained	obtain	VERB
esrj-49829	55	6	by	by	ADP
esrj-49829	55	7	integrating	integrate	VERB
esrj-49829	55	8	fuzzy	fuzzy	ADJ
esrj-49829	55	9	systems	system	NOUN
esrj-49829	55	10	and	and	CCONJ
esrj-49829	55	11	the	the	DET
esrj-49829	55	12	ann	ann	PROPN
esrj-49829	55	13	approach	approach	NOUN
esrj-49829	55	14	to	to	PART
esrj-49829	55	15	deal	deal	VERB
esrj-49829	55	16	with	with	ADP
esrj-49829	55	17	large	large	ADJ
esrj-49829	55	18	and	and	CCONJ
esrj-49829	55	19	imprecisely	imprecisely	ADV
esrj-49829	55	20	defined	define	VERB
esrj-49829	55	21	complex	complex	ADJ
esrj-49829	55	22	systems	system	NOUN
esrj-49829	55	23	.	.	PUNCT
esrj-49829	56	1	an	an	DET
esrj-49829	56	2	adaptive	adaptive	ADJ
esrj-49829	56	3	neuro	neuro	NOUN
esrj-49829	56	4	-	-	PUNCT
esrj-49829	56	5	fuzzy	fuzzy	ADJ
esrj-49829	56	6	inference	inference	NOUN
esrj-49829	56	7	system	system	NOUN
esrj-49829	56	8	(	(	PUNCT
esrj-49829	56	9	anfis	anfi	VERB
esrj-49829	56	10	)	)	PUNCT
esrj-49829	56	11	is	be	AUX
esrj-49829	56	12	one	one	NUM
esrj-49829	56	13	of	of	ADP
esrj-49829	56	14	the	the	DET
esrj-49829	56	15	most	most	ADV
esrj-49829	56	16	successful	successful	ADJ
esrj-49829	56	17	schemes	scheme	NOUN
esrj-49829	56	18	which	which	PRON
esrj-49829	56	19	combine	combine	VERB
esrj-49829	56	20	the	the	DET
esrj-49829	56	21	benefits	benefit	NOUN
esrj-49829	56	22	of	of	ADP
esrj-49829	56	23	these	these	DET
esrj-49829	56	24	two	two	NUM
esrj-49829	56	25	powerful	powerful	ADJ
esrj-49829	56	26	paradigms	paradigm	NOUN
esrj-49829	56	27	into	into	ADP
esrj-49829	56	28	a	a	DET
esrj-49829	56	29	single	single	ADJ
esrj-49829	56	30	model	model	NOUN
esrj-49829	56	31	.	.	PUNCT
esrj-49829	57	1	the	the	DET
esrj-49829	57	2	goal	goal	NOUN
esrj-49829	57	3	of	of	ADP
esrj-49829	57	4	the	the	DET
esrj-49829	57	5	anfis	anfis	PROPN
esrj-49829	57	6	is	be	AUX
esrj-49829	57	7	to	to	PART
esrj-49829	57	8	find	find	VERB
esrj-49829	57	9	a	a	DET
esrj-49829	57	10	model	model	NOUN
esrj-49829	57	11	or	or	CCONJ
esrj-49829	57	12	mapping	mapping	NOUN
esrj-49829	57	13	that	that	PRON
esrj-49829	57	14	will	will	AUX
esrj-49829	57	15	correctly	correctly	ADV
esrj-49829	57	16	associate	associate	VERB
esrj-49829	57	17	the	the	DET
esrj-49829	57	18	inputs	input	NOUN
esrj-49829	57	19	with	with	ADP
esrj-49829	57	20	the	the	DET
esrj-49829	57	21	output	output	NOUN
esrj-49829	57	22	.	.	PUNCT
esrj-49829	58	1	data	datum	NOUN
esrj-49829	58	2	mining	mining	NOUN
esrj-49829	58	3	refers	refer	VERB
esrj-49829	58	4	to	to	ADP
esrj-49829	58	5	the	the	DET
esrj-49829	58	6	process	process	NOUN
esrj-49829	58	7	of	of	ADP
esrj-49829	58	8	searching	search	VERB
esrj-49829	58	9	for	for	ADP
esrj-49829	58	10	and	and	CCONJ
esrj-49829	58	11	discovering	discover	VERB
esrj-49829	58	12	various	various	ADJ
esrj-49829	58	13	patterns	pattern	NOUN
esrj-49829	58	14	in	in	ADP
esrj-49829	58	15	data	datum	NOUN
esrj-49829	58	16	and	and	CCONJ
esrj-49829	58	17	of	of	ADP
esrj-49829	58	18	summarizing	summarize	VERB
esrj-49829	58	19	a	a	DET
esrj-49829	58	20	set	set	NOUN
esrj-49829	58	21	of	of	ADP
esrj-49829	58	22	known	know	VERB
esrj-49829	58	23	values	value	NOUN
esrj-49829	58	24	to	to	PART
esrj-49829	58	25	obtain	obtain	VERB
esrj-49829	58	26	the	the	DET
esrj-49829	58	27	most	most	ADV
esrj-49829	58	28	important	important	ADJ
esrj-49829	58	29	information	information	NOUN
esrj-49829	58	30	(	(	PUNCT
esrj-49829	58	31	quinlan	quinlan	PROPN
esrj-49829	58	32	,	,	PUNCT
esrj-49829	58	33	1992	1992	NUM
esrj-49829	58	34	)	)	PUNCT
esrj-49829	58	35	.	.	PUNCT
esrj-49829	59	1	tree	tree	NOUN
esrj-49829	59	2	-	-	PUNCT
esrj-49829	59	3	based	base	VERB
esrj-49829	59	4	methods	method	NOUN
esrj-49829	59	5	are	be	AUX
esrj-49829	59	6	one	one	NUM
esrj-49829	59	7	data	datum	NOUN
esrj-49829	59	8	mining	mining	NOUN
esrj-49829	59	9	technique	technique	NOUN
esrj-49829	59	10	and	and	CCONJ
esrj-49829	59	11	their	their	PRON
esrj-49829	59	12	output	output	NOUN
esrj-49829	59	13	is	be	AUX
esrj-49829	59	14	a	a	DET
esrj-49829	59	15	model	model	NOUN
esrj-49829	59	16	having	have	VERB
esrj-49829	59	17	the	the	DET
esrj-49829	59	18	structure	structure	NOUN
esrj-49829	59	19	of	of	ADP
esrj-49829	59	20	a	a	DET
esrj-49829	59	21	tree	tree	NOUN
esrj-49829	59	22	with	with	ADP
esrj-49829	59	23	input	input	NOUN
esrj-49829	59	24	and	and	CCONJ
esrj-49829	59	25	output	output	NOUN
esrj-49829	59	26	data	datum	NOUN
esrj-49829	59	27	.	.	PUNCT
esrj-49829	60	1	the	the	DET
esrj-49829	60	2	m5	m5	PROPN
esrj-49829	60	3	model	model	NOUN
esrj-49829	60	4	tree	tree	NOUN
esrj-49829	60	5	was	be	AUX
esrj-49829	60	6	introduced	introduce	VERB
esrj-49829	60	7	by	by	ADP
esrj-49829	60	8	quinlan	quinlan	PROPN
esrj-49829	60	9	in	in	ADP
esrj-49829	60	10	1992	1992	NUM
esrj-49829	60	11	and	and	CCONJ
esrj-49829	60	12	is	be	AUX
esrj-49829	60	13	a	a	DET
esrj-49829	60	14	subset	subset	NOUN
esrj-49829	60	15	of	of	ADP
esrj-49829	60	16	data	datum	NOUN
esrj-49829	60	17	mining	mining	NOUN
esrj-49829	60	18	methods	method	NOUN
esrj-49829	60	19	.	.	PUNCT
esrj-49829	61	1	the	the	DET
esrj-49829	61	2	m5	m5	PROPN
esrj-49829	61	3	algorithm	algorithm	NOUN
esrj-49829	61	4	is	be	AUX
esrj-49829	61	5	the	the	DET
esrj-49829	61	6	most	most	ADV
esrj-49829	61	7	common	common	ADJ
esrj-49829	61	8	classification	classification	NOUN
esrj-49829	61	9	used	use	VERB
esrj-49829	61	10	in	in	ADP
esrj-49829	61	11	the	the	DET
esrj-49829	61	12	family	family	NOUN
esrj-49829	61	13	of	of	ADP
esrj-49829	61	14	decision	decision	NOUN
esrj-49829	61	15	-	-	PUNCT
esrj-49829	61	16	making	make	VERB
esrj-49829	61	17	tree	tree	NOUN
esrj-49829	61	18	models	model	NOUN
esrj-49829	61	19	.	.	PUNCT
esrj-49829	62	1	a	a	DET
esrj-49829	62	2	decision	decision	NOUN
esrj-49829	62	3	tree	tree	NOUN
esrj-49829	62	4	model	model	NOUN
esrj-49829	62	5	is	be	AUX
esrj-49829	62	6	essentially	essentially	ADV
esrj-49829	62	7	a	a	DET
esrj-49829	62	8	decision	decision	NOUN
esrj-49829	62	9	-	-	PUNCT
esrj-49829	62	10	making	make	VERB
esrj-49829	62	11	tree	tree	NOUN
esrj-49829	62	12	in	in	ADP
esrj-49829	62	13	which	which	PRON
esrj-49829	62	14	linear	linear	ADJ
esrj-49829	62	15	regression	regression	NOUN
esrj-49829	62	16	equations	equation	NOUN
esrj-49829	62	17	at	at	ADP
esrj-49829	62	18	the	the	DET
esrj-49829	62	19	leaves	leave	NOUN
esrj-49829	62	20	replace	replace	VERB
esrj-49829	62	21	terminal	terminal	ADJ
esrj-49829	62	22	class	class	NOUN
esrj-49829	62	23	values	value	NOUN
esrj-49829	62	24	.	.	PUNCT
esrj-49829	63	1	within	within	ADP
esrj-49829	63	2	the	the	DET
esrj-49829	63	3	last	last	ADJ
esrj-49829	63	4	decade	decade	NOUN
esrj-49829	63	5	,	,	PUNCT
esrj-49829	63	6	several	several	ADJ
esrj-49829	63	7	studies	study	NOUN
esrj-49829	63	8	reported	report	VERB
esrj-49829	63	9	the	the	DET
esrj-49829	63	10	use	use	NOUN
esrj-49829	63	11	of	of	ADP
esrj-49829	63	12	data	datum	NOUN
esrj-49829	63	13	mining	mining	NOUN
esrj-49829	63	14	techniques	technique	NOUN
esrj-49829	63	15	such	such	ADJ
esrj-49829	63	16	as	as	ADP
esrj-49829	63	17	the	the	DET
esrj-49829	63	18	m5	m5	PROPN
esrj-49829	63	19	tree	tree	NOUN
esrj-49829	63	20	model	model	NOUN
esrj-49829	63	21	for	for	ADP
esrj-49829	63	22	water	water	NOUN
esrj-49829	63	23	resource	resource	NOUN
esrj-49829	63	24	issues	issue	NOUN
esrj-49829	63	25	applications	application	NOUN
esrj-49829	63	26	(	(	PUNCT
esrj-49829	63	27	solomantine	solomantine	NOUN
esrj-49829	63	28	and	and	CCONJ
esrj-49829	63	29	dulal	dulal	NOUN
esrj-49829	63	30	,	,	PUNCT
esrj-49829	63	31	2003	2003	NUM
esrj-49829	63	32	;	;	PUNCT
esrj-49829	63	33	bhattacharya	bhattacharya	PROPN
esrj-49829	63	34	and	and	CCONJ
esrj-49829	63	35	solomatine	solomatine	PROPN
esrj-49829	63	36	,	,	PUNCT
esrj-49829	63	37	2005	2005	NUM
esrj-49829	63	38	;	;	PUNCT
esrj-49829	63	39	stravs	stravs	ADJ
esrj-49829	63	40	and	and	CCONJ
esrj-49829	63	41	brilly	brilly	ADV
esrj-49829	63	42	,	,	PUNCT
esrj-49829	63	43	2007	2007	NUM
esrj-49829	63	44	;	;	PUNCT
esrj-49829	63	45	pal	pal	NOUN
esrj-49829	63	46	et	et	PROPN
esrj-49829	63	47	al	al	PROPN
esrj-49829	63	48	.	.	PROPN
esrj-49829	63	49	,	,	PUNCT
esrj-49829	63	50	2012	2012	NUM
esrj-49829	63	51	;	;	PUNCT
esrj-49829	63	52	sattari	sattari	PROPN
esrj-49829	63	53	et	et	PROPN
esrj-49829	63	54	al	al	PROPN
esrj-49829	63	55	.	.	PROPN
esrj-49829	63	56	,	,	PUNCT
esrj-49829	63	57	2013a	2013a	NUM
esrj-49829	63	58	;	;	PUNCT
esrj-49829	63	59	sattari	sattari	PROPN
esrj-49829	63	60	et	et	PROPN
esrj-49829	63	61	al	al	PROPN
esrj-49829	63	62	.	.	PROPN
esrj-49829	63	63	,	,	PUNCT
esrj-49829	63	64	2013b	2013b	NUM
esrj-49829	63	65	;	;	PUNCT
esrj-49829	63	66	sattari	sattari	NOUN
esrj-49829	63	67	,	,	PUNCT
esrj-49829	63	68	et	et	PROPN
esrj-49829	63	69	al	al	PROPN
esrj-49829	63	70	.	.	PROPN
esrj-49829	63	71	,	,	PUNCT
esrj-49829	63	72	2014	2014	NUM
esrj-49829	63	73	;	;	PUNCT
esrj-49829	63	74	esmailzadeh	esmailzadeh	NOUN
esrj-49829	63	75	and	and	CCONJ
esrj-49829	63	76	sattari	sattari	NOUN
esrj-49829	63	77	,	,	PUNCT
esrj-49829	63	78	2015	2015	NUM
esrj-49829	63	79	;	;	PUNCT
esrj-49829	63	80	biabani	biabani	PROPN
esrj-49829	63	81	et	et	PROPN
esrj-49829	63	82	al	al	PROPN
esrj-49829	63	83	.	.	PROPN
esrj-49829	63	84	,	,	PUNCT
esrj-49829	63	85	2016	2016	NUM
esrj-49829	63	86	;	;	PUNCT
esrj-49829	63	87	shortridge	shortridge	VERB
esrj-49829	63	88	et	et	PROPN
esrj-49829	63	89	al	al	PROPN
esrj-49829	63	90	.	.	PROPN
esrj-49829	63	91	,	,	PUNCT
esrj-49829	63	92	2016	2016	NUM
esrj-49829	63	93	;	;	PUNCT
esrj-49829	63	94	adnan	adnan	PROPN
esrj-49829	63	95	et	et	PROPN
esrj-49829	63	96	al	al	PROPN
esrj-49829	63	97	.	.	PROPN
esrj-49829	63	98	,	,	PUNCT
esrj-49829	63	99	2017	2017	NUM
esrj-49829	63	100	;	;	PUNCT
esrj-49829	63	101	sayagavi	sayagavi	PROPN
esrj-49829	63	102	et	et	PROPN
esrj-49829	63	103	al	al	PROPN
esrj-49829	63	104	.	.	PROPN
esrj-49829	63	105	,	,	PUNCT
esrj-49829	63	106	2016	2016	NUM
esrj-49829	63	107	;	;	PUNCT
esrj-49829	63	108	schnier	schnier	X
esrj-49829	63	109	,	,	PUNCT
esrj-49829	63	110	2016	2016	NUM
esrj-49829	63	111	)	)	PUNCT
esrj-49829	63	112	.	.	PUNCT
esrj-49829	64	1	however	however	ADV
esrj-49829	64	2	to	to	ADP
esrj-49829	64	3	the	the	DET
esrj-49829	64	4	best	good	ADJ
esrj-49829	64	5	knowledge	knowledge	NOUN
esrj-49829	64	6	of	of	ADP
esrj-49829	64	7	the	the	DET
esrj-49829	64	8	authors	author	NOUN
esrj-49829	64	9	,	,	PUNCT
esrj-49829	64	10	there	there	PRON
esrj-49829	64	11	has	have	AUX
esrj-49829	64	12	not	not	PART
esrj-49829	64	13	been	be	AUX
esrj-49829	64	14	an	an	DET
esrj-49829	64	15	application	application	NOUN
esrj-49829	64	16	of	of	ADP
esrj-49829	64	17	the	the	DET
esrj-49829	64	18	m5	m5	PROPN
esrj-49829	64	19	tree	tree	NOUN
esrj-49829	64	20	model	model	NOUN
esrj-49829	64	21	to	to	PART
esrj-49829	64	22	predict	predict	VERB
esrj-49829	64	23	soil	soil	NOUN
esrj-49829	64	24	temperatures	temperature	NOUN
esrj-49829	64	25	at	at	ADP
esrj-49829	64	26	various	various	ADJ
esrj-49829	64	27	soil	soil	NOUN
esrj-49829	64	28	depths	depth	NOUN
esrj-49829	64	29	,	,	PUNCT
esrj-49829	64	30	especially	especially	ADV
esrj-49829	64	31	in	in	ADP
esrj-49829	64	32	arid	arid	NOUN
esrj-49829	64	33	and	and	CCONJ
esrj-49829	64	34	semi	semi	ADJ
esrj-49829	64	35	-	-	ADJ
esrj-49829	64	36	arid	arid	ADJ
esrj-49829	64	37	climates	climate	NOUN
esrj-49829	64	38	.	.	PUNCT
esrj-49829	65	1	our	our	PRON
esrj-49829	65	2	primary	primary	ADJ
esrj-49829	65	3	motivation	motivation	NOUN
esrj-49829	65	4	in	in	ADP
esrj-49829	65	5	this	this	DET
esrj-49829	65	6	study	study	NOUN
esrj-49829	65	7	is	be	AUX
esrj-49829	65	8	to	to	PART
esrj-49829	65	9	simulate	simulate	VERB
esrj-49829	65	10	soil	soil	NOUN
esrj-49829	65	11	temperatures	temperature	NOUN
esrj-49829	65	12	at	at	ADP
esrj-49829	65	13	various	various	ADJ
esrj-49829	65	14	depths	depth	NOUN
esrj-49829	65	15	.	.	PUNCT
esrj-49829	66	1	in	in	ADP
esrj-49829	66	2	this	this	DET
esrj-49829	66	3	manner	manner	NOUN
esrj-49829	66	4	,	,	PUNCT
esrj-49829	66	5	it	it	PRON
esrj-49829	66	6	is	be	AUX
esrj-49829	66	7	possible	possible	ADJ
esrj-49829	66	8	to	to	PART
esrj-49829	66	9	predict	predict	VERB
esrj-49829	66	10	future	future	ADJ
esrj-49829	66	11	soil	soil	NOUN
esrj-49829	66	12	temperatures	temperature	NOUN
esrj-49829	66	13	by	by	ADP
esrj-49829	66	14	simply	simply	ADV
esrj-49829	66	15	acquiring	acquire	VERB
esrj-49829	66	16	the	the	DET
esrj-49829	66	17	climatic	climatic	ADJ
esrj-49829	66	18	data	datum	NOUN
esrj-49829	66	19	from	from	ADP
esrj-49829	66	20	the	the	DET
esrj-49829	66	21	meteorological	meteorological	ADJ
esrj-49829	66	22	stations	station	NOUN
esrj-49829	66	23	.	.	PUNCT
esrj-49829	67	1	this	this	PRON
esrj-49829	67	2	is	be	AUX
esrj-49829	67	3	particularly	particularly	ADV
esrj-49829	67	4	important	important	ADJ
esrj-49829	67	5	when	when	SCONJ
esrj-49829	67	6	planning	plan	VERB
esrj-49829	67	7	future	future	ADJ
esrj-49829	67	8	agriculture	agriculture	NOUN
esrj-49829	67	9	practices	practice	NOUN
esrj-49829	67	10	.	.	PUNCT
esrj-49829	68	1	this	this	DET
esrj-49829	68	2	study	study	NOUN
esrj-49829	68	3	will	will	AUX
esrj-49829	68	4	evaluate	evaluate	VERB
esrj-49829	68	5	the	the	DET
esrj-49829	68	6	performance	performance	NOUN
esrj-49829	68	7	of	of	ADP
esrj-49829	68	8	various	various	ADJ
esrj-49829	68	9	data	datum	NOUN
esrj-49829	68	10	mining	mining	NOUN
esrj-49829	68	11	techniques	technique	NOUN
esrj-49829	68	12	such	such	ADJ
esrj-49829	68	13	as	as	ADP
esrj-49829	68	14	anfis	anfis	ADJ
esrj-49829	68	15	,	,	PUNCT
esrj-49829	68	16	anns	ann	NOUN
esrj-49829	68	17	and	and	CCONJ
esrj-49829	68	18	the	the	DET
esrj-49829	68	19	m5	m5	ADJ
esrj-49829	68	20	tree	tree	NOUN
esrj-49829	68	21	model	model	NOUN
esrj-49829	68	22	for	for	ADP
esrj-49829	68	23	estimating	estimate	VERB
esrj-49829	68	24	daily	daily	ADJ
esrj-49829	68	25	soil	soil	NOUN
esrj-49829	68	26	temperature	temperature	NOUN
esrj-49829	68	27	at	at	ADP
esrj-49829	68	28	different	different	ADJ
esrj-49829	68	29	depths	depth	NOUN
esrj-49829	68	30	in	in	ADP
esrj-49829	68	31	semi	semi	ADJ
esrj-49829	68	32	arid	arid	ADJ
esrj-49829	68	33	regions	region	NOUN
esrj-49829	68	34	such	such	ADJ
esrj-49829	68	35	as	as	ADP
esrj-49829	68	36	iran	iran	PROPN
esrj-49829	68	37	.	.	PUNCT
esrj-49829	69	1	2	2	X
esrj-49829	69	2	.	.	X
esrj-49829	69	3	materials	material	NOUN
esrj-49829	69	4	and	and	CCONJ
esrj-49829	69	5	methods	method	NOUN
esrj-49829	69	6	2.1	2.1	NUM
esrj-49829	69	7	study	study	NOUN
esrj-49829	69	8	area	area	NOUN
esrj-49829	69	9	and	and	CCONJ
esrj-49829	69	10	data	datum	NOUN
esrj-49829	69	11	used	use	VERB
esrj-49829	69	12	located	locate	VERB
esrj-49829	69	13	in	in	ADP
esrj-49829	69	14	the	the	DET
esrj-49829	69	15	central	central	ADJ
esrj-49829	69	16	arid	arid	NOUN
esrj-49829	69	17	region	region	NOUN
esrj-49829	69	18	of	of	ADP
esrj-49829	69	19	the	the	DET
esrj-49829	69	20	country	country	NOUN
esrj-49829	69	21	,	,	PUNCT
esrj-49829	69	22	the	the	DET
esrj-49829	69	23	isfahan	isfahan	NOUN
esrj-49829	69	24	province	province	NOUN
esrj-49829	69	25	of	of	ADP
esrj-49829	69	26	iran	iran	PROPN
esrj-49829	69	27	lies	lie	VERB
esrj-49829	69	28	between	between	ADP
esrj-49829	69	29	30o	30o	PROPN
esrj-49829	69	30	42	42	NUM
esrj-49829	69	31	’	'	PUNCT
esrj-49829	69	32	to	to	ADP
esrj-49829	69	33	34o	34o	NOUN
esrj-49829	69	34	30’n	30’n	NUM
esrj-49829	69	35	and	and	CCONJ
esrj-49829	69	36	49o	49o	NUM
esrj-49829	69	37	36	36	NUM
esrj-49829	69	38	’	'	PUNCT
esrj-49829	69	39	to	to	ADP
esrj-49829	69	40	55o	55o	NUM
esrj-49829	69	41	e	e	NOUN
esrj-49829	69	42	(	(	PUNCT
esrj-49829	69	43	figure	figure	NOUN
esrj-49829	69	44	1	1	NUM
esrj-49829	69	45	)	)	PUNCT
esrj-49829	69	46	.	.	PUNCT
esrj-49829	70	1	the	the	DET
esrj-49829	70	2	altitude	altitude	NOUN
esrj-49829	70	3	in	in	ADP
esrj-49829	70	4	this	this	DET
esrj-49829	70	5	area	area	NOUN
esrj-49829	70	6	varies	vary	VERB
esrj-49829	70	7	from	from	ADP
esrj-49829	70	8	707	707	NUM
esrj-49829	70	9	to	to	ADP
esrj-49829	70	10	4000	4000	NUM
esrj-49829	70	11	m.	m.	NOUN
esrj-49829	70	12	the	the	DET
esrj-49829	70	13	significant	significant	ADJ
esrj-49829	70	14	change	change	NOUN
esrj-49829	70	15	in	in	ADP
esrj-49829	70	16	altitude	altitude	NOUN
esrj-49829	70	17	and	and	CCONJ
esrj-49829	70	18	its	its	PRON
esrj-49829	70	19	effect	effect	NOUN
esrj-49829	70	20	on	on	ADP
esrj-49829	70	21	climate	climate	NOUN
esrj-49829	70	22	provide	provide	VERB
esrj-49829	70	23	various	various	ADJ
esrj-49829	70	24	habitats	habitat	NOUN
esrj-49829	70	25	and	and	CCONJ
esrj-49829	70	26	diverse	diverse	ADJ
esrj-49829	70	27	plant	plant	NOUN
esrj-49829	70	28	species	specie	NOUN
esrj-49829	70	29	.	.	PUNCT
esrj-49829	71	1	the	the	DET
esrj-49829	71	2	experimentally	experimentally	ADV
esrj-49829	71	3	obtained	obtain	VERB
esrj-49829	71	4	daily	daily	ADJ
esrj-49829	71	5	soil	soil	NOUN
esrj-49829	71	6	temperature	temperature	NOUN
esrj-49829	71	7	and	and	CCONJ
esrj-49829	71	8	other	other	ADJ
esrj-49829	71	9	meteorological	meteorological	ADJ
esrj-49829	71	10	parameters	parameter	NOUN
esrj-49829	71	11	were	be	AUX
esrj-49829	71	12	measured	measure	VERB
esrj-49829	71	13	at	at	ADP
esrj-49829	71	14	the	the	DET
esrj-49829	71	15	weather	weather	NOUN
esrj-49829	71	16	station	station	NOUN
esrj-49829	71	17	of	of	ADP
esrj-49829	71	18	isfahan	isfahan	NOUN
esrj-49829	71	19	from	from	ADP
esrj-49829	71	20	1992	1992	NUM
esrj-49829	71	21	to	to	ADP
esrj-49829	71	22	2005	2005	NUM
esrj-49829	71	23	.	.	PUNCT
esrj-49829	72	1	the	the	DET
esrj-49829	72	2	soil	soil	NOUN
esrj-49829	72	3	temperature	temperature	NOUN
esrj-49829	72	4	data	datum	NOUN
esrj-49829	72	5	were	be	AUX
esrj-49829	72	6	obtained	obtain	VERB
esrj-49829	72	7	for	for	ADP
esrj-49829	72	8	soil	soil	NOUN
esrj-49829	72	9	profiles	profile	NOUN
esrj-49829	72	10	at	at	ADP
esrj-49829	72	11	various	various	ADJ
esrj-49829	72	12	depths	depth	NOUN
esrj-49829	72	13	(	(	PUNCT
esrj-49829	72	14	i.e.	i.e.	X
esrj-49829	72	15	5	5	NUM
esrj-49829	72	16	,	,	PUNCT
esrj-49829	72	17	10	10	NUM
esrj-49829	72	18	,	,	PUNCT
esrj-49829	72	19	20	20	NUM
esrj-49829	72	20	,	,	PUNCT
esrj-49829	72	21	30	30	NUM
esrj-49829	72	22	,	,	PUNCT
esrj-49829	72	23	50	50	NUM
esrj-49829	72	24	and	and	CCONJ
esrj-49829	72	25	100	100	NUM
esrj-49829	72	26	cm	cm	NOUN
esrj-49829	72	27	)	)	PUNCT
esrj-49829	72	28	.	.	PUNCT
esrj-49829	73	1	meteorological	meteorological	ADJ
esrj-49829	73	2	parameters	parameter	NOUN
esrj-49829	73	3	including	include	VERB
esrj-49829	73	4	:	:	PUNCT
esrj-49829	73	5	daily	daily	ADV
esrj-49829	73	6	mean	mean	NOUN
esrj-49829	73	7	,	,	PUNCT
esrj-49829	73	8	minimum	minimum	ADJ
esrj-49829	73	9	and	and	CCONJ
esrj-49829	73	10	maximum	maximum	ADJ
esrj-49829	73	11	air	air	NOUN
esrj-49829	73	12	temperature	temperature	NOUN
esrj-49829	73	13	(	(	PUNCT
esrj-49829	73	14	ave	ave	PROPN
esrj-49829	73	15	t	t	PROPN
esrj-49829	73	16	,	,	PUNCT
esrj-49829	73	17	min	min	PROPN
esrj-49829	73	18	t	t	PROPN
esrj-49829	73	19	,	,	PUNCT
esrj-49829	73	20	max	max	PROPN
esrj-49829	73	21	t	t	PROPN
esrj-49829	73	22	)	)	PUNCT
esrj-49829	73	23	,	,	PUNCT
esrj-49829	73	24	evaporation	evaporation	NOUN
esrj-49829	73	25	(	(	PUNCT
esrj-49829	73	26	ev	ev	NOUN
esrj-49829	73	27	)	)	PUNCT
esrj-49829	73	28	,	,	PUNCT
esrj-49829	73	29	daily	daily	ADJ
esrj-49829	73	30	sunshine	sunshine	NOUN
esrj-49829	73	31	hours	hour	NOUN
esrj-49829	73	32	(	(	PUNCT
esrj-49829	73	33	sunh	sunh	NOUN
esrj-49829	73	34	)	)	PUNCT
esrj-49829	73	35	and	and	CCONJ
esrj-49829	73	36	radiation	radiation	NOUN
esrj-49829	73	37	(	(	PUNCT
esrj-49829	73	38	ra	ra	NOUN
esrj-49829	73	39	)	)	PUNCT
esrj-49829	73	40	were	be	AUX
esrj-49829	73	41	also	also	ADV
esrj-49829	73	42	considered	consider	VERB
esrj-49829	73	43	as	as	ADP
esrj-49829	73	44	inputs	input	NOUN
esrj-49829	73	45	.	.	PUNCT
esrj-49829	74	1	figure	figure	NOUN
esrj-49829	74	2	1	1	NUM
esrj-49829	74	3	.	.	PUNCT
esrj-49829	75	1	location	location	NOUN
esrj-49829	75	2	of	of	ADP
esrj-49829	75	3	the	the	DET
esrj-49829	75	4	study	study	NOUN
esrj-49829	75	5	area	area	NOUN
esrj-49829	75	6	87estimation	87estimation	PROPN
esrj-49829	75	7	of	of	ADP
esrj-49829	75	8	daily	daily	ADJ
esrj-49829	75	9	soil	soil	NOUN
esrj-49829	75	10	temperature	temperature	NOUN
esrj-49829	75	11	via	via	ADP
esrj-49829	75	12	data	datum	NOUN
esrj-49829	75	13	mining	mining	NOUN
esrj-49829	75	14	techniques	technique	NOUN
esrj-49829	75	15	in	in	ADP
esrj-49829	75	16	semi	semi	ADJ
esrj-49829	75	17	-	-	ADJ
esrj-49829	75	18	arid	arid	ADJ
esrj-49829	75	19	climate	climate	NOUN
esrj-49829	75	20	conditions	condition	NOUN
esrj-49829	75	21	the	the	DET
esrj-49829	75	22	descriptive	descriptive	ADJ
esrj-49829	75	23	statistics	statistics	PROPN
esrj-49829	75	24	min	min	PROPN
esrj-49829	75	25	,	,	PUNCT
esrj-49829	75	26	max	max	PROPN
esrj-49829	75	27	,	,	PUNCT
esrj-49829	75	28	mean	mean	VERB
esrj-49829	75	29	,	,	PUNCT
esrj-49829	75	30	standard	standard	ADJ
esrj-49829	75	31	deviation	deviation	NOUN
esrj-49829	75	32	,	,	PUNCT
esrj-49829	75	33	coefficient	coefficient	NOUN
esrj-49829	75	34	of	of	ADP
esrj-49829	75	35	skewness	skewness	NOUN
esrj-49829	75	36	(	(	PUNCT
esrj-49829	75	37	cs	cs	PROPN
esrj-49829	75	38	)	)	PUNCT
esrj-49829	75	39	,	,	PUNCT
esrj-49829	75	40	coefficient	coefficient	NOUN
esrj-49829	75	41	of	of	ADP
esrj-49829	75	42	kurtosis	kurtosis	NOUN
esrj-49829	75	43	(	(	PUNCT
esrj-49829	75	44	ck	ck	NOUN
esrj-49829	75	45	)	)	PUNCT
esrj-49829	75	46	and	and	CCONJ
esrj-49829	75	47	coefficient	coefficient	NOUN
esrj-49829	75	48	of	of	ADP
esrj-49829	75	49	variation	variation	NOUN
esrj-49829	75	50	(	(	PUNCT
esrj-49829	75	51	cv	cv	NOUN
esrj-49829	75	52	)	)	PUNCT
esrj-49829	75	53	of	of	ADP
esrj-49829	75	54	the	the	DET
esrj-49829	75	55	soil	soil	NOUN
esrj-49829	75	56	temperature	temperature	NOUN
esrj-49829	75	57	and	and	CCONJ
esrj-49829	75	58	meteorological	meteorological	ADJ
esrj-49829	75	59	data	datum	NOUN
esrj-49829	75	60	time	time	NOUN
esrj-49829	75	61	series	series	PROPN
esrj-49829	75	62	,	,	PUNCT
esrj-49829	75	63	are	be	AUX
esrj-49829	75	64	provided	provide	VERB
esrj-49829	75	65	in	in	ADP
esrj-49829	75	66	table	table	NOUN
esrj-49829	75	67	1	1	NUM
esrj-49829	75	68	.	.	PUNCT
esrj-49829	75	69	table	table	NOUN
esrj-49829	76	1	1	1	NUM
esrj-49829	76	2	.	.	PUNCT
esrj-49829	76	3	descriptive	descriptive	ADJ
esrj-49829	76	4	statistics	statistic	NOUN
esrj-49829	76	5	of	of	ADP
esrj-49829	76	6	the	the	DET
esrj-49829	76	7	soil	soil	NOUN
esrj-49829	76	8	temperature	temperature	NOUN
esrj-49829	76	9	data	datum	NOUN
esrj-49829	76	10	the	the	DET
esrj-49829	76	11	available	available	ADJ
esrj-49829	76	12	data	datum	NOUN
esrj-49829	76	13	were	be	AUX
esrj-49829	76	14	split	split	VERB
esrj-49829	76	15	into	into	ADP
esrj-49829	76	16	two	two	NUM
esrj-49829	76	17	parts	part	NOUN
esrj-49829	76	18	.	.	PUNCT
esrj-49829	77	1	the	the	DET
esrj-49829	77	2	first	first	ADJ
esrj-49829	77	3	part	part	NOUN
esrj-49829	77	4	consists	consist	VERB
esrj-49829	77	5	of	of	ADP
esrj-49829	77	6	3028	3028	NUM
esrj-49829	77	7	samples	sample	NOUN
esrj-49829	77	8	between	between	ADP
esrj-49829	77	9	june	june	PROPN
esrj-49829	77	10	1992	1992	NUM
esrj-49829	77	11	and	and	CCONJ
esrj-49829	77	12	october	october	PROPN
esrj-49829	77	13	2004	2004	NUM
esrj-49829	77	14	and	and	CCONJ
esrj-49829	77	15	was	be	AUX
esrj-49829	77	16	used	use	VERB
esrj-49829	77	17	to	to	PART
esrj-49829	77	18	train	train	VERB
esrj-49829	77	19	different	different	ADJ
esrj-49829	77	20	models	model	NOUN
esrj-49829	77	21	.	.	PUNCT
esrj-49829	78	1	the	the	DET
esrj-49829	78	2	second	second	ADJ
esrj-49829	78	3	part	part	NOUN
esrj-49829	78	4	,	,	PUNCT
esrj-49829	78	5	consisting	consist	VERB
esrj-49829	78	6	of	of	ADP
esrj-49829	78	7	335	335	NUM
esrj-49829	78	8	samples	sample	NOUN
esrj-49829	78	9	between	between	ADP
esrj-49829	78	10	october	october	PROPN
esrj-49829	78	11	2004	2004	NUM
esrj-49829	78	12	and	and	CCONJ
esrj-49829	78	13	december	december	PROPN
esrj-49829	78	14	2005	2005	NUM
esrj-49829	78	15	was	be	AUX
esrj-49829	78	16	used	use	VERB
esrj-49829	78	17	for	for	ADP
esrj-49829	78	18	testing	testing	NOUN
esrj-49829	78	19	.	.	PUNCT
esrj-49829	79	1	the	the	DET
esrj-49829	79	2	coefficient	coefficient	NOUN
esrj-49829	79	3	of	of	ADP
esrj-49829	79	4	determination	determination	NOUN
esrj-49829	79	5	(	(	PUNCT
esrj-49829	79	6	r2	r2	PROPN
esrj-49829	79	7	)	)	PUNCT
esrj-49829	79	8	and	and	CCONJ
esrj-49829	79	9	root	root	NOUN
esrj-49829	79	10	mean	mean	NOUN
esrj-49829	79	11	square	square	ADJ
esrj-49829	79	12	error	error	NOUN
esrj-49829	79	13	(	(	PUNCT
esrj-49829	79	14	rmse	rmse	ADJ
esrj-49829	79	15	)	)	PUNCT
esrj-49829	79	16	statistics	statistic	NOUN
esrj-49829	79	17	were	be	AUX
esrj-49829	79	18	used	use	VERB
esrj-49829	79	19	to	to	PART
esrj-49829	79	20	compare	compare	VERB
esrj-49829	79	21	the	the	DET
esrj-49829	79	22	performance	performance	NOUN
esrj-49829	79	23	of	of	ADP
esrj-49829	79	24	various	various	ADJ
esrj-49829	79	25	modeling	modeling	NOUN
esrj-49829	79	26	approaches	approach	NOUN
esrj-49829	79	27	used	use	VERB
esrj-49829	79	28	in	in	ADP
esrj-49829	79	29	this	this	DET
esrj-49829	79	30	study	study	NOUN
esrj-49829	79	31	.	.	PUNCT
esrj-49829	80	1	it	it	PRON
esrj-49829	80	2	is	be	AUX
esrj-49829	80	3	often	often	ADV
esrj-49829	80	4	useful	useful	ADJ
esrj-49829	80	5	to	to	PART
esrj-49829	80	6	scale	scale	VERB
esrj-49829	80	7	the	the	DET
esrj-49829	80	8	input	input	NOUN
esrj-49829	80	9	and	and	CCONJ
esrj-49829	80	10	output	output	NOUN
esrj-49829	80	11	parameters	parameter	NOUN
esrj-49829	80	12	before	before	ADP
esrj-49829	80	13	using	use	VERB
esrj-49829	80	14	them	they	PRON
esrj-49829	80	15	with	with	ADP
esrj-49829	80	16	anns	ann	NOUN
esrj-49829	80	17	.	.	PUNCT
esrj-49829	81	1	in	in	ADP
esrj-49829	81	2	the	the	DET
esrj-49829	81	3	present	present	ADJ
esrj-49829	81	4	work	work	NOUN
esrj-49829	81	5	,	,	PUNCT
esrj-49829	81	6	input	input	NOUN
esrj-49829	81	7	and	and	CCONJ
esrj-49829	81	8	output	output	NOUN
esrj-49829	81	9	data	datum	NOUN
esrj-49829	81	10	were	be	AUX
esrj-49829	81	11	scaled	scale	VERB
esrj-49829	81	12	to	to	ADP
esrj-49829	81	13	a	a	DET
esrj-49829	81	14	range	range	NOUN
esrj-49829	81	15	from	from	ADP
esrj-49829	81	16	-1	-1	INTJ
esrj-49829	81	17	to	to	ADP
esrj-49829	81	18	+1	+1	PROPN
esrj-49829	81	19	,	,	PUNCT
esrj-49829	81	20	which	which	PRON
esrj-49829	81	21	is	be	AUX
esrj-49829	81	22	preferable	preferable	ADJ
esrj-49829	81	23	when	when	SCONJ
esrj-49829	81	24	tan	tan	NOUN
esrj-49829	81	25	-	-	PUNCT
esrj-49829	81	26	sigmoid	sigmoid	NOUN
esrj-49829	81	27	activation	activation	NOUN
esrj-49829	81	28	functions	function	NOUN
esrj-49829	81	29	are	be	AUX
esrj-49829	81	30	used	use	VERB
esrj-49829	81	31	with	with	ADP
esrj-49829	81	32	the	the	DET
esrj-49829	81	33	neural	neural	ADJ
esrj-49829	81	34	network	network	NOUN
esrj-49829	81	35	.	.	PUNCT
esrj-49829	82	1	the	the	DET
esrj-49829	82	2	following	follow	VERB
esrj-49829	82	3	normalization	normalization	NOUN
esrj-49829	82	4	equation	equation	NOUN
esrj-49829	82	5	was	be	AUX
esrj-49829	82	6	used	use	VERB
esrj-49829	82	7	(	(	PUNCT
esrj-49829	82	8	1	1	X
esrj-49829	82	9	)	)	PUNCT
esrj-49829	82	10	where	where	SCONJ
esrj-49829	82	11	z	z	NOUN
esrj-49829	82	12	is	be	AUX
esrj-49829	82	13	standardized	standardize	VERB
esrj-49829	82	14	input	input	NOUN
esrj-49829	82	15	values	value	NOUN
esrj-49829	82	16	lying	lie	VERB
esrj-49829	82	17	in	in	ADP
esrj-49829	82	18	the	the	DET
esrj-49829	82	19	range	range	NOUN
esrj-49829	82	20	of	of	ADP
esrj-49829	82	21	[	[	X
esrj-49829	82	22	-1	-1	X
esrj-49829	82	23	,	,	PUNCT
esrj-49829	82	24	+1	+1	PROPN
esrj-49829	82	25	]	]	X
esrj-49829	82	26	,	,	PUNCT
esrj-49829	82	27	and	and	CCONJ
esrj-49829	82	28	xmin	xmin	PROPN
esrj-49829	82	29	and	and	CCONJ
esrj-49829	82	30	xmax	xmax	PROPN
esrj-49829	82	31	are	be	AUX
esrj-49829	82	32	minimum	minimum	ADJ
esrj-49829	82	33	and	and	CCONJ
esrj-49829	82	34	maximum	maximum	ADJ
esrj-49829	82	35	input	input	NOUN
esrj-49829	82	36	values	value	NOUN
esrj-49829	82	37	,	,	PUNCT
esrj-49829	82	38	respectively	respectively	ADV
esrj-49829	82	39	.	.	PUNCT
esrj-49829	83	1	2.2	2.2	NUM
esrj-49829	83	2	adaptive	adaptive	ADJ
esrj-49829	83	3	neuro	neuro	NOUN
esrj-49829	83	4	-	-	PUNCT
esrj-49829	83	5	fuzzy	fuzzy	ADJ
esrj-49829	83	6	inference	inference	NOUN
esrj-49829	83	7	system	system	NOUN
esrj-49829	83	8	(	(	PUNCT
esrj-49829	83	9	anfis	anfis	ADJ
esrj-49829	83	10	)	)	PUNCT
esrj-49829	83	11	fuzzy	fuzzy	ADJ
esrj-49829	83	12	logic	logic	NOUN
esrj-49829	83	13	represents	represent	VERB
esrj-49829	83	14	knowledge	knowledge	NOUN
esrj-49829	83	15	using	use	VERB
esrj-49829	83	16	if	if	SCONJ
esrj-49829	83	17	–	–	PUNCT
esrj-49829	83	18	then	then	ADV
esrj-49829	83	19	rules	rule	NOUN
esrj-49829	83	20	in	in	ADP
esrj-49829	83	21	the	the	DET
esrj-49829	83	22	form	form	NOUN
esrj-49829	83	23	of	of	ADP
esrj-49829	83	24	“	"	PUNCT
esrj-49829	83	25	if	if	SCONJ
esrj-49829	83	26	x	x	X
esrj-49829	83	27	and	and	CCONJ
esrj-49829	83	28	y	y	PROPN
esrj-49829	83	29	then	then	ADV
esrj-49829	83	30	z	z	PROPN
esrj-49829	83	31	”	"	PUNCT
esrj-49829	83	32	(	(	PUNCT
esrj-49829	83	33	zadeh	zadeh	PROPN
esrj-49829	83	34	,	,	PUNCT
esrj-49829	83	35	1965	1965	NUM
esrj-49829	83	36	)	)	PUNCT
esrj-49829	83	37	.	.	PUNCT
esrj-49829	84	1	fis	fis	PROPN
esrj-49829	84	2	mainly	mainly	ADV
esrj-49829	84	3	consists	consist	VERB
esrj-49829	84	4	of	of	ADP
esrj-49829	84	5	fuzzy	fuzzy	ADJ
esrj-49829	84	6	rules	rule	NOUN
esrj-49829	84	7	and	and	CCONJ
esrj-49829	84	8	membership	membership	NOUN
esrj-49829	84	9	functions	function	NOUN
esrj-49829	84	10	and	and	CCONJ
esrj-49829	84	11	fuzzification	fuzzification	NOUN
esrj-49829	84	12	and	and	CCONJ
esrj-49829	84	13	de	de	ADJ
esrj-49829	84	14	-	-	NOUN
esrj-49829	84	15	fuzzification	fuzzification	NOUN
esrj-49829	84	16	operations	operation	NOUN
esrj-49829	84	17	(	(	PUNCT
esrj-49829	84	18	jang	jang	PROPN
esrj-49829	84	19	,	,	PUNCT
esrj-49829	84	20	1993	1993	NUM
esrj-49829	84	21	)	)	PUNCT
esrj-49829	84	22	.	.	PUNCT
esrj-49829	85	1	figure	figure	NOUN
esrj-49829	85	2	2	2	NUM
esrj-49829	85	3	shows	show	VERB
esrj-49829	85	4	a	a	DET
esrj-49829	85	5	typical	typical	ADJ
esrj-49829	85	6	architecture	architecture	NOUN
esrj-49829	85	7	of	of	ADP
esrj-49829	85	8	an	an	DET
esrj-49829	85	9	anfis	anfis	PROPN
esrj-49829	85	10	.	.	PUNCT
esrj-49829	86	1	in	in	ADP
esrj-49829	86	2	this	this	DET
esrj-49829	86	3	figure	figure	NOUN
esrj-49829	86	4	,	,	PUNCT
esrj-49829	86	5	circles	circle	NOUN
esrj-49829	86	6	represents	represent	VERB
esrj-49829	86	7	fixed	fix	VERB
esrj-49829	86	8	nodes	node	NOUN
esrj-49829	86	9	,	,	PUNCT
esrj-49829	86	10	whereas	whereas	SCONJ
esrj-49829	86	11	squares	square	NOUN
esrj-49829	86	12	indicate	indicate	VERB
esrj-49829	86	13	adaptive	adaptive	ADJ
esrj-49829	86	14	nodes	node	NOUN
esrj-49829	86	15	.	.	PUNCT
esrj-49829	87	1	the	the	DET
esrj-49829	87	2	input	input	NOUN
esrj-49829	87	3	and	and	CCONJ
esrj-49829	87	4	output	output	NOUN
esrj-49829	87	5	nodes	node	NOUN
esrj-49829	87	6	represent	represent	VERB
esrj-49829	87	7	the	the	DET
esrj-49829	87	8	meteorological	meteorological	ADJ
esrj-49829	87	9	parameters	parameter	NOUN
esrj-49829	87	10	and	and	CCONJ
esrj-49829	87	11	soil	soil	NOUN
esrj-49829	87	12	temperature	temperature	NOUN
esrj-49829	87	13	,	,	PUNCT
esrj-49829	87	14	respectively	respectively	ADV
esrj-49829	87	15	.	.	PUNCT
esrj-49829	88	1	the	the	DET
esrj-49829	88	2	nodes	node	NOUN
esrj-49829	88	3	in	in	ADP
esrj-49829	88	4	the	the	DET
esrj-49829	88	5	hidden	hide	VERB
esrj-49829	88	6	layers	layer	NOUN
esrj-49829	88	7	act	act	VERB
esrj-49829	88	8	as	as	ADP
esrj-49829	88	9	membership	membership	NOUN
esrj-49829	88	10	functions	function	NOUN
esrj-49829	88	11	(	(	PUNCT
esrj-49829	88	12	mfs	mfs	PROPN
esrj-49829	88	13	)	)	PUNCT
esrj-49829	88	14	and	and	CCONJ
esrj-49829	88	15	rules	rule	NOUN
esrj-49829	88	16	.	.	PUNCT
esrj-49829	89	1	for	for	ADP
esrj-49829	89	2	simplicity	simplicity	NOUN
esrj-49829	89	3	,	,	PUNCT
esrj-49829	89	4	it	it	PRON
esrj-49829	89	5	is	be	AUX
esrj-49829	89	6	assumed	assume	VERB
esrj-49829	89	7	that	that	SCONJ
esrj-49829	89	8	the	the	DET
esrj-49829	89	9	examined	examine	VERB
esrj-49829	89	10	fis	fis	PROPN
esrj-49829	89	11	has	have	VERB
esrj-49829	89	12	two	two	NUM
esrj-49829	89	13	inputs	input	NOUN
esrj-49829	89	14	and	and	CCONJ
esrj-49829	89	15	one	one	NUM
esrj-49829	89	16	output	output	NOUN
esrj-49829	89	17	.	.	PUNCT
esrj-49829	90	1	for	for	ADP
esrj-49829	90	2	a	a	DET
esrj-49829	90	3	first	first	ADJ
esrj-49829	90	4	-	-	PUNCT
esrj-49829	90	5	order	order	NOUN
esrj-49829	90	6	sugeno	sugeno	NOUN
esrj-49829	90	7	fuzzy	fuzzy	ADJ
esrj-49829	90	8	model	model	NOUN
esrj-49829	90	9	,	,	PUNCT
esrj-49829	90	10	a	a	DET
esrj-49829	90	11	typical	typical	ADJ
esrj-49829	90	12	rule	rule	NOUN
esrj-49829	90	13	set	set	VERB
esrj-49829	90	14	with	with	ADP
esrj-49829	90	15	two	two	NUM
esrj-49829	90	16	fuzzy	fuzzy	ADJ
esrj-49829	90	17	‘	'	PUNCT
esrj-49829	90	18	‘	'	PUNCT
esrj-49829	90	19	if	if	SCONJ
esrj-49829	90	20	-	-	PUNCT
esrj-49829	90	21	then	then	ADV
esrj-49829	90	22	’’	’'	PUNCT
esrj-49829	90	23	rules	rule	NOUN
esrj-49829	90	24	can	can	AUX
esrj-49829	90	25	be	be	AUX
esrj-49829	90	26	expressed	express	VERB
esrj-49829	90	27	as	as	SCONJ
esrj-49829	90	28	follows	follow	VERB
esrj-49829	90	29	:	:	PUNCT
esrj-49829	90	30	(	(	PUNCT
esrj-49829	90	31	2	2	X
esrj-49829	90	32	)	)	PUNCT
esrj-49829	90	33	(	(	PUNCT
esrj-49829	90	34	3	3	X
esrj-49829	90	35	)	)	PUNCT
esrj-49829	90	36	where	where	SCONJ
esrj-49829	90	37	x	x	PRON
esrj-49829	90	38	and	and	CCONJ
esrj-49829	90	39	y	y	PROPN
esrj-49829	90	40	are	be	AUX
esrj-49829	90	41	two	two	NUM
esrj-49829	90	42	crisp	crisp	ADJ
esrj-49829	90	43	inputs	input	NOUN
esrj-49829	90	44	,	,	PUNCT
esrj-49829	90	45	and	and	CCONJ
esrj-49829	90	46	ai	ai	VERB
esrj-49829	90	47	and	and	CCONJ
esrj-49829	90	48	bi	bi	NOUN
esrj-49829	90	49	are	be	AUX
esrj-49829	90	50	the	the	DET
esrj-49829	90	51	linguistic	linguistic	ADJ
esrj-49829	90	52	labels	label	NOUN
esrj-49829	90	53	associated	associate	VERB
esrj-49829	90	54	with	with	ADP
esrj-49829	90	55	the	the	DET
esrj-49829	90	56	node	node	ADJ
esrj-49829	90	57	function	function	NOUN
esrj-49829	90	58	.	.	PUNCT
esrj-49829	91	1	the	the	DET
esrj-49829	91	2	anfis	anfis	PROPN
esrj-49829	91	3	has	have	VERB
esrj-49829	91	4	the	the	DET
esrj-49829	91	5	multiple	multiple	ADJ
esrj-49829	91	6	layers	layer	NOUN
esrj-49829	91	7	,	,	PUNCT
esrj-49829	91	8	as	as	SCONJ
esrj-49829	91	9	displayed	display	VERB
esrj-49829	91	10	in	in	ADP
esrj-49829	91	11	figure	figure	NOUN
esrj-49829	91	12	2	2	NUM
esrj-49829	91	13	.	.	PUNCT
esrj-49829	91	14	figure	figure	NOUN
esrj-49829	91	15	2	2	NUM
esrj-49829	91	16	.	.	PUNCT
esrj-49829	91	17	architecture	architecture	NOUN
esrj-49829	91	18	of	of	ADP
esrj-49829	91	19	the	the	DET
esrj-49829	91	20	anfis	anfis	ADJ
esrj-49829	91	21	layer	layer	NOUN
esrj-49829	91	22	1	1	NUM
esrj-49829	91	23	:	:	PUNCT
esrj-49829	91	24	all	all	DET
esrj-49829	91	25	the	the	DET
esrj-49829	91	26	nodes	node	NOUN
esrj-49829	91	27	in	in	ADP
esrj-49829	91	28	this	this	DET
esrj-49829	91	29	layer	layer	NOUN
esrj-49829	91	30	are	be	AUX
esrj-49829	91	31	adaptive	adaptive	ADJ
esrj-49829	91	32	nodes	node	NOUN
esrj-49829	91	33	which	which	PRON
esrj-49829	91	34	mean	mean	VERB
esrj-49829	91	35	that	that	SCONJ
esrj-49829	91	36	the	the	DET
esrj-49829	91	37	outputs	output	NOUN
esrj-49829	91	38	of	of	ADP
esrj-49829	91	39	the	the	DET
esrj-49829	91	40	nodes	node	NOUN
esrj-49829	91	41	depend	depend	VERB
esrj-49829	91	42	on	on	ADP
esrj-49829	91	43	the	the	DET
esrj-49829	91	44	parameters	parameter	NOUN
esrj-49829	91	45	pertaining	pertain	VERB
esrj-49829	91	46	to	to	ADP
esrj-49829	91	47	these	these	DET
esrj-49829	91	48	nodes	node	NOUN
esrj-49829	91	49	.	.	PUNCT
esrj-49829	92	1	each	each	DET
esrj-49829	92	2	node	node	NOUN
esrj-49829	92	3	corresponds	correspond	VERB
esrj-49829	92	4	to	to	ADP
esrj-49829	92	5	a	a	DET
esrj-49829	92	6	linguistic	linguistic	ADJ
esrj-49829	92	7	label	label	NOUN
esrj-49829	92	8	which	which	PRON
esrj-49829	92	9	has	have	VERB
esrj-49829	92	10	a	a	DET
esrj-49829	92	11	membership	membership	NOUN
esrj-49829	92	12	function	function	NOUN
esrj-49829	92	13	that	that	PRON
esrj-49829	92	14	may	may	AUX
esrj-49829	92	15	be	be	AUX
esrj-49829	92	16	gaussian	gaussian	ADJ
esrj-49829	92	17	or	or	CCONJ
esrj-49829	92	18	any	any	DET
esrj-49829	92	19	other	other	ADJ
esrj-49829	92	20	mf	mf	NOUN
esrj-49829	92	21	.	.	PROPN
esrj-49829	92	22	layer	layer	NOUN
esrj-49829	92	23	2	2	NUM
esrj-49829	92	24	:	:	PUNCT
esrj-49829	92	25	every	every	DET
esrj-49829	92	26	node	node	NOUN
esrj-49829	92	27	in	in	ADP
esrj-49829	92	28	this	this	DET
esrj-49829	92	29	layer	layer	NOUN
esrj-49829	92	30	is	be	AUX
esrj-49829	92	31	a	a	DET
esrj-49829	92	32	fixed	fix	VERB
esrj-49829	92	33	node	node	NOUN
esrj-49829	92	34	labeled	label	VERB
esrj-49829	92	35	as	as	ADP
esrj-49829	92	36	ii	ii	PROPN
esrj-49829	92	37	,	,	PUNCT
esrj-49829	92	38	representing	represent	VERB
esrj-49829	92	39	the	the	DET
esrj-49829	92	40	firing	firing	NOUN
esrj-49829	92	41	strength	strength	NOUN
esrj-49829	92	42	of	of	ADP
esrj-49829	92	43	each	each	DET
esrj-49829	92	44	rule	rule	NOUN
esrj-49829	92	45	.	.	PUNCT
esrj-49829	93	1	layer	layer	NOUN
esrj-49829	93	2	3	3	NUM
esrj-49829	93	3	:	:	PUNCT
esrj-49829	93	4	every	every	DET
esrj-49829	93	5	node	node	NOUN
esrj-49829	93	6	in	in	ADP
esrj-49829	93	7	this	this	DET
esrj-49829	93	8	layer	layer	NOUN
esrj-49829	93	9	is	be	AUX
esrj-49829	93	10	a	a	DET
esrj-49829	93	11	fixed	fix	VERB
esrj-49829	93	12	node	node	NOUN
esrj-49829	93	13	labeled	label	VERB
esrj-49829	93	14	as	as	ADP
esrj-49829	93	15	n	n	NUM
esrj-49829	93	16	,	,	PUNCT
esrj-49829	93	17	representing	represent	VERB
esrj-49829	93	18	the	the	DET
esrj-49829	93	19	normalized	normalize	VERB
esrj-49829	93	20	firing	firing	NOUN
esrj-49829	93	21	strength	strength	NOUN
esrj-49829	93	22	of	of	ADP
esrj-49829	93	23	each	each	DET
esrj-49829	93	24	rule	rule	NOUN
esrj-49829	93	25	.	.	PUNCT
esrj-49829	94	1	layer	layer	NOUN
esrj-49829	94	2	4	4	NUM
esrj-49829	94	3	:	:	PUNCT
esrj-49829	94	4	every	every	DET
esrj-49829	94	5	node	node	NOUN
esrj-49829	94	6	i	i	PRON
esrj-49829	94	7	in	in	ADP
esrj-49829	94	8	this	this	DET
esrj-49829	94	9	layer	layer	NOUN
esrj-49829	94	10	is	be	AUX
esrj-49829	94	11	an	an	DET
esrj-49829	94	12	adaptive	adaptive	ADJ
esrj-49829	94	13	node	node	NOUN
esrj-49829	94	14	with	with	ADP
esrj-49829	94	15	a	a	DET
esrj-49829	94	16	node	node	ADJ
esrj-49829	94	17	function	function	NOUN
esrj-49829	94	18	defined	define	VERB
esrj-49829	94	19	as	as	ADP
esrj-49829	94	20	:	:	PUNCT
esrj-49829	94	21	(	(	PUNCT
esrj-49829	94	22	4	4	X
esrj-49829	94	23	)	)	PUNCT
esrj-49829	94	24	where	where	SCONJ
esrj-49829	94	25	oi4	oi4	NOUN
esrj-49829	94	26	is	be	AUX
esrj-49829	94	27	node	node	ADJ
esrj-49829	94	28	output	output	NOUN
esrj-49829	94	29	,	,	PUNCT
esrj-49829	94	30	wi	wi	PROPN
esrj-49829	94	31	is	be	AUX
esrj-49829	94	32	the	the	DET
esrj-49829	94	33	normalizing	normalizing	ADJ
esrj-49829	94	34	firing	firing	NOUN
esrj-49829	94	35	strength	strength	NOUN
esrj-49829	94	36	from	from	ADP
esrj-49829	94	37	layer	layer	NOUN
esrj-49829	94	38	3	3	NUM
esrj-49829	94	39	and	and	CCONJ
esrj-49829	94	40	{	{	PUNCT
esrj-49829	94	41	pi	pi	NOUN
esrj-49829	94	42	,	,	PUNCT
esrj-49829	94	43	qi	qi	PROPN
esrj-49829	94	44	,	,	PUNCT
esrj-49829	94	45	ri	ri	PROPN
esrj-49829	94	46	}	}	PUNCT
esrj-49829	94	47	are	be	AUX
esrj-49829	94	48	the	the	DET
esrj-49829	94	49	parameter	parameter	NOUN
esrj-49829	94	50	set	set	NOUN
esrj-49829	94	51	of	of	ADP
esrj-49829	94	52	this	this	DET
esrj-49829	94	53	node	node	NOUN
esrj-49829	94	54	.	.	PUNCT
esrj-49829	95	1	layer	layer	NOUN
esrj-49829	95	2	5	5	NUM
esrj-49829	95	3	:	:	PUNCT
esrj-49829	95	4	the	the	DET
esrj-49829	95	5	single	single	ADJ
esrj-49829	95	6	node	node	NOUN
esrj-49829	95	7	in	in	ADP
esrj-49829	95	8	this	this	DET
esrj-49829	95	9	layer	layer	NOUN
esrj-49829	95	10	is	be	AUX
esrj-49829	95	11	a	a	DET
esrj-49829	95	12	fixed	fix	VERB
esrj-49829	95	13	node	node	NOUN
esrj-49829	95	14	labeled	label	VERB
esrj-49829	95	15	σ	σ	NOUN
esrj-49829	95	16	which	which	PRON
esrj-49829	95	17	computes	compute	VERB
esrj-49829	95	18	the	the	DET
esrj-49829	95	19	overall	overall	ADJ
esrj-49829	95	20	output	output	NOUN
esrj-49829	95	21	by	by	ADP
esrj-49829	95	22	summing	sum	VERB
esrj-49829	95	23	all	all	DET
esrj-49829	95	24	incoming	incoming	ADJ
esrj-49829	95	25	signals	signal	NOUN
esrj-49829	95	26	and	and	CCONJ
esrj-49829	95	27	is	be	AUX
esrj-49829	95	28	the	the	DET
esrj-49829	95	29	last	last	ADJ
esrj-49829	95	30	step	step	NOUN
esrj-49829	95	31	of	of	ADP
esrj-49829	95	32	the	the	DET
esrj-49829	95	33	anfis	anfis	PROPN
esrj-49829	95	34	.	.	PUNCT
esrj-49829	96	1	the	the	DET
esrj-49829	96	2	output	output	NOUN
esrj-49829	96	3	of	of	ADP
esrj-49829	96	4	the	the	DET
esrj-49829	96	5	system	system	NOUN
esrj-49829	96	6	is	be	AUX
esrj-49829	96	7	calculated	calculate	VERB
esrj-49829	96	8	as	as	ADP
esrj-49829	96	9	:	:	PUNCT
esrj-49829	96	10	(	(	PUNCT
esrj-49829	96	11	5	5	X
esrj-49829	96	12	)	)	PUNCT
esrj-49829	96	13	where	where	SCONJ
esrj-49829	96	14	o15	o15	X
esrj-49829	96	15	(	(	PUNCT
esrj-49829	96	16	node	node	NOUN
esrj-49829	96	17	output	output	NOUN
esrj-49829	96	18	)	)	PUNCT
esrj-49829	96	19	,	,	PUNCT
esrj-49829	96	20	is	be	AUX
esrj-49829	96	21	the	the	DET
esrj-49829	96	22	weighted	weighted	ADJ
esrj-49829	96	23	sum	sum	NOUN
esrj-49829	96	24	of	of	ADP
esrj-49829	96	25	right	right	ADJ
esrj-49829	96	26	hand	hand	NOUN
esrj-49829	96	27	side	side	NOUN
esrj-49829	96	28	polynomials	polynomial	NOUN
esrj-49829	96	29	in	in	ADP
esrj-49829	96	30	equation	equation	NOUN
esrj-49829	96	31	5	5	NUM
esrj-49829	96	32	.	.	PUNCT
esrj-49829	97	1	the	the	DET
esrj-49829	97	2	implementation	implementation	NOUN
esrj-49829	97	3	of	of	ADP
esrj-49829	97	4	anfis	anfis	PROPN
esrj-49829	97	5	consists	consist	VERB
esrj-49829	97	6	of	of	ADP
esrj-49829	97	7	two	two	NUM
esrj-49829	97	8	major	major	ADJ
esrj-49829	97	9	phases	phase	NOUN
esrj-49829	97	10	;	;	PUNCT
esrj-49829	97	11	the	the	DET
esrj-49829	97	12	structure	structure	NOUN
esrj-49829	97	13	identification	identification	NOUN
esrj-49829	97	14	phase	phase	NOUN
esrj-49829	97	15	and	and	CCONJ
esrj-49829	97	16	the	the	DET
esrj-49829	97	17	parameter	parameter	NOUN
esrj-49829	97	18	identification	identification	NOUN
esrj-49829	97	19	phase	phase	NOUN
esrj-49829	97	20	.	.	PUNCT
esrj-49829	98	1	the	the	DET
esrj-49829	98	2	anfis	anfis	PROPN
esrj-49829	98	3	parameter	parameter	NOUN
esrj-49829	98	4	estimation	estimation	NOUN
esrj-49829	98	5	can	can	AUX
esrj-49829	98	6	be	be	AUX
esrj-49829	98	7	carried	carry	VERB
esrj-49829	98	8	out	out	ADP
esrj-49829	98	9	by	by	ADP
esrj-49829	98	10	training	train	VERB
esrj-49829	98	11	the	the	DET
esrj-49829	98	12	88	88	NUM
esrj-49829	98	13	m.	m.	NOUN
esrj-49829	98	14	taghi	taghi	NOUN
esrj-49829	98	15	sattari	sattari	NOUN
esrj-49829	98	16	,	,	PUNCT
esrj-49829	98	17	esmaeel	esmaeel	NOUN
esrj-49829	98	18	dodangeh	dodangeh	NOUN
esrj-49829	98	19	,	,	PUNCT
esrj-49829	98	20	john	john	PROPN
esrj-49829	98	21	abraham	abraham	PROPN
esrj-49829	98	22	anfis	anfi	VERB
esrj-49829	98	23	system	system	NOUN
esrj-49829	98	24	by	by	ADP
esrj-49829	98	25	using	use	VERB
esrj-49829	98	26	a	a	DET
esrj-49829	98	27	hybrid	hybrid	ADJ
esrj-49829	98	28	learning	learning	NOUN
esrj-49829	98	29	algorithm	algorithm	NOUN
esrj-49829	98	30	.	.	PUNCT
esrj-49829	99	1	the	the	DET
esrj-49829	99	2	hybrid	hybrid	ADJ
esrj-49829	99	3	learning	learn	VERB
esrj-49829	99	4	algorithm	algorithm	NOUN
esrj-49829	99	5	of	of	ADP
esrj-49829	99	6	anfis	anfis	PROPN
esrj-49829	99	7	consists	consist	VERB
esrj-49829	99	8	of	of	ADP
esrj-49829	99	9	the	the	DET
esrj-49829	99	10	two	two	NUM
esrj-49829	99	11	parts	part	NOUN
esrj-49829	99	12	:	:	PUNCT
esrj-49829	99	13	(	(	PUNCT
esrj-49829	99	14	a	a	X
esrj-49829	99	15	)	)	PUNCT
esrj-49829	99	16	the	the	DET
esrj-49829	99	17	learning	learning	NOUN
esrj-49829	99	18	of	of	ADP
esrj-49829	99	19	the	the	DET
esrj-49829	99	20	premise	premise	ADJ
esrj-49829	99	21	parameters	parameter	NOUN
esrj-49829	99	22	by	by	ADP
esrj-49829	99	23	back	back	ADJ
esrj-49829	99	24	-	-	PUNCT
esrj-49829	99	25	propagation	propagation	NOUN
esrj-49829	99	26	and	and	CCONJ
esrj-49829	99	27	(	(	PUNCT
esrj-49829	99	28	b	b	X
esrj-49829	99	29	)	)	PUNCT
esrj-49829	99	30	the	the	DET
esrj-49829	99	31	learning	learning	NOUN
esrj-49829	99	32	of	of	ADP
esrj-49829	99	33	the	the	DET
esrj-49829	99	34	consequence	consequence	NOUN
esrj-49829	99	35	parameters	parameter	NOUN
esrj-49829	99	36	by	by	ADP
esrj-49829	99	37	least	least	ADJ
esrj-49829	99	38	-	-	PUNCT
esrj-49829	99	39	squares	square	NOUN
esrj-49829	99	40	estimation	estimation	NOUN
esrj-49829	99	41	.	.	PUNCT
esrj-49829	100	1	in	in	ADP
esrj-49829	100	2	the	the	DET
esrj-49829	100	3	forward	forward	ADJ
esrj-49829	100	4	pass	pass	NOUN
esrj-49829	100	5	of	of	ADP
esrj-49829	100	6	the	the	DET
esrj-49829	100	7	hybrid	hybrid	ADJ
esrj-49829	100	8	learning	learning	NOUN
esrj-49829	100	9	algorithm	algorithm	NOUN
esrj-49829	100	10	,	,	PUNCT
esrj-49829	100	11	functional	functional	ADJ
esrj-49829	100	12	signals	signal	NOUN
esrj-49829	100	13	move	move	VERB
esrj-49829	100	14	forward	forward	ADV
esrj-49829	100	15	to	to	ADP
esrj-49829	100	16	layer	layer	NOUN
esrj-49829	100	17	4	4	NUM
esrj-49829	100	18	to	to	PART
esrj-49829	100	19	calculate	calculate	VERB
esrj-49829	100	20	each	each	DET
esrj-49829	100	21	node	node	ADJ
esrj-49829	100	22	output	output	NOUN
esrj-49829	100	23	.	.	PUNCT
esrj-49829	101	1	the	the	DET
esrj-49829	101	2	premise	premise	ADJ
esrj-49829	101	3	parameters	parameter	NOUN
esrj-49829	101	4	in	in	ADP
esrj-49829	101	5	layer	layer	NOUN
esrj-49829	101	6	2	2	NUM
esrj-49829	101	7	remain	remain	VERB
esrj-49829	101	8	fixed	fix	VERB
esrj-49829	101	9	in	in	ADP
esrj-49829	101	10	this	this	DET
esrj-49829	101	11	pass	pass	NOUN
esrj-49829	101	12	.	.	PUNCT
esrj-49829	102	1	the	the	DET
esrj-49829	102	2	consequent	consequent	ADJ
esrj-49829	102	3	parameters	parameter	NOUN
esrj-49829	102	4	are	be	AUX
esrj-49829	102	5	then	then	ADV
esrj-49829	102	6	identified	identify	VERB
esrj-49829	102	7	by	by	ADP
esrj-49829	102	8	the	the	DET
esrj-49829	102	9	least	least	ADJ
esrj-49829	102	10	-	-	PUNCT
esrj-49829	102	11	squares	square	NOUN
esrj-49829	102	12	estimate	estimate	NOUN
esrj-49829	102	13	.	.	PUNCT
esrj-49829	103	1	in	in	ADP
esrj-49829	103	2	the	the	DET
esrj-49829	103	3	backward	backward	ADJ
esrj-49829	103	4	pass	pass	NOUN
esrj-49829	103	5	,	,	PUNCT
esrj-49829	103	6	the	the	DET
esrj-49829	103	7	error	error	NOUN
esrj-49829	103	8	rates	rate	NOUN
esrj-49829	103	9	propagate	propagate	VERB
esrj-49829	103	10	backward	backward	ADV
esrj-49829	103	11	from	from	ADP
esrj-49829	103	12	the	the	DET
esrj-49829	103	13	output	output	NOUN
esrj-49829	103	14	towards	towards	ADP
esrj-49829	103	15	the	the	DET
esrj-49829	103	16	input	input	NOUN
esrj-49829	103	17	,	,	PUNCT
esrj-49829	103	18	and	and	CCONJ
esrj-49829	103	19	the	the	DET
esrj-49829	103	20	premise	premise	ADJ
esrj-49829	103	21	parameters	parameter	NOUN
esrj-49829	103	22	are	be	AUX
esrj-49829	103	23	updated	update	VERB
esrj-49829	103	24	by	by	ADP
esrj-49829	103	25	the	the	DET
esrj-49829	103	26	gradient	gradient	ADJ
esrj-49829	103	27	descent	descent	NOUN
esrj-49829	103	28	(	(	PUNCT
esrj-49829	103	29	shu	shu	PROPN
esrj-49829	103	30	,	,	PUNCT
esrj-49829	103	31	et	et	PROPN
esrj-49829	103	32	al	al	PROPN
esrj-49829	103	33	.	.	PROPN
esrj-49829	103	34	,	,	PUNCT
esrj-49829	103	35	2008	2008	NUM
esrj-49829	103	36	)	)	PUNCT
esrj-49829	103	37	.	.	PUNCT
esrj-49829	104	1	2.2.1	2.2.1	NUM
esrj-49829	104	2	subtractive	subtractive	NOUN
esrj-49829	104	3	clustering	clustering	NOUN
esrj-49829	104	4	subtractive	subtractive	NOUN
esrj-49829	104	5	clustering	clustering	NOUN
esrj-49829	104	6	is	be	AUX
esrj-49829	104	7	an	an	DET
esrj-49829	104	8	automated	automate	VERB
esrj-49829	104	9	data	data	NOUN
esrj-49829	104	10	-	-	PUNCT
esrj-49829	104	11	driven	drive	VERB
esrj-49829	104	12	approach	approach	NOUN
esrj-49829	104	13	to	to	PART
esrj-49829	104	14	generate	generate	VERB
esrj-49829	104	15	primary	primary	ADJ
esrj-49829	104	16	fuzzy	fuzzy	ADJ
esrj-49829	104	17	models	model	NOUN
esrj-49829	104	18	.	.	PUNCT
esrj-49829	105	1	the	the	DET
esrj-49829	105	2	subtractive	subtractive	NOUN
esrj-49829	105	3	clustering	cluster	VERB
esrj-49829	105	4	algorithm	algorithm	NOUN
esrj-49829	105	5	is	be	AUX
esrj-49829	105	6	used	use	VERB
esrj-49829	105	7	in	in	ADP
esrj-49829	105	8	case	case	NOUN
esrj-49829	105	9	the	the	DET
esrj-49829	105	10	number	number	NOUN
esrj-49829	105	11	of	of	ADP
esrj-49829	105	12	clusters	cluster	NOUN
esrj-49829	105	13	is	be	AUX
esrj-49829	105	14	not	not	PART
esrj-49829	105	15	clear	clear	ADJ
esrj-49829	105	16	.	.	PUNCT
esrj-49829	106	1	this	this	DET
esrj-49829	106	2	algorithm	algorithm	NOUN
esrj-49829	106	3	depends	depend	VERB
esrj-49829	106	4	on	on	ADP
esrj-49829	106	5	the	the	DET
esrj-49829	106	6	structure	structure	NOUN
esrj-49829	106	7	of	of	ADP
esrj-49829	106	8	the	the	DET
esrj-49829	106	9	data	datum	NOUN
esrj-49829	106	10	and	and	CCONJ
esrj-49829	106	11	can	can	AUX
esrj-49829	106	12	be	be	AUX
esrj-49829	106	13	used	use	VERB
esrj-49829	106	14	as	as	ADP
esrj-49829	106	15	a	a	DET
esrj-49829	106	16	dimensionality	dimensionality	NOUN
esrj-49829	106	17	reduction	reduction	NOUN
esrj-49829	106	18	tool	tool	NOUN
esrj-49829	106	19	.	.	PUNCT
esrj-49829	107	1	this	this	DET
esrj-49829	107	2	algorithm	algorithm	NOUN
esrj-49829	107	3	can	can	AUX
esrj-49829	107	4	also	also	ADV
esrj-49829	107	5	be	be	AUX
esrj-49829	107	6	used	use	VERB
esrj-49829	107	7	to	to	PART
esrj-49829	107	8	generate	generate	VERB
esrj-49829	107	9	a	a	DET
esrj-49829	107	10	fuzzy	fuzzy	ADJ
esrj-49829	107	11	system	system	NOUN
esrj-49829	107	12	with	with	ADP
esrj-49829	107	13	the	the	DET
esrj-49829	107	14	minimum	minimum	ADJ
esrj-49829	107	15	number	number	NOUN
esrj-49829	107	16	of	of	ADP
esrj-49829	107	17	rules	rule	NOUN
esrj-49829	107	18	required	require	VERB
esrj-49829	107	19	to	to	PART
esrj-49829	107	20	distinguish	distinguish	VERB
esrj-49829	107	21	the	the	DET
esrj-49829	107	22	fuzzy	fuzzy	ADJ
esrj-49829	107	23	qualities	quality	NOUN
esrj-49829	107	24	associated	associate	VERB
esrj-49829	107	25	with	with	ADP
esrj-49829	107	26	each	each	PRON
esrj-49829	107	27	of	of	ADP
esrj-49829	107	28	the	the	DET
esrj-49829	107	29	clusters	cluster	NOUN
esrj-49829	107	30	.	.	PUNCT
esrj-49829	108	1	subtractive	subtractive	NOUN
esrj-49829	108	2	clustering	clustering	NOUN
esrj-49829	108	3	is	be	AUX
esrj-49829	108	4	based	base	VERB
esrj-49829	108	5	on	on	ADP
esrj-49829	108	6	a	a	DET
esrj-49829	108	7	measure	measure	NOUN
esrj-49829	108	8	of	of	ADP
esrj-49829	108	9	the	the	DET
esrj-49829	108	10	density	density	NOUN
esrj-49829	108	11	of	of	ADP
esrj-49829	108	12	data	datum	NOUN
esrj-49829	108	13	points	point	NOUN
esrj-49829	108	14	in	in	ADP
esrj-49829	108	15	the	the	DET
esrj-49829	108	16	feature	feature	NOUN
esrj-49829	108	17	space	space	NOUN
esrj-49829	108	18	.	.	PUNCT
esrj-49829	109	1	the	the	DET
esrj-49829	109	2	idea	idea	NOUN
esrj-49829	109	3	here	here	ADV
esrj-49829	109	4	is	be	AUX
esrj-49829	109	5	to	to	PART
esrj-49829	109	6	find	find	VERB
esrj-49829	109	7	regions	region	NOUN
esrj-49829	109	8	in	in	ADP
esrj-49829	109	9	the	the	DET
esrj-49829	109	10	feature	feature	NOUN
esrj-49829	109	11	space	space	NOUN
esrj-49829	109	12	with	with	ADP
esrj-49829	109	13	high	high	ADJ
esrj-49829	109	14	densities	density	NOUN
esrj-49829	109	15	of	of	ADP
esrj-49829	109	16	data	datum	NOUN
esrj-49829	109	17	points	point	NOUN
esrj-49829	109	18	.	.	PUNCT
esrj-49829	110	1	consider	consider	VERB
esrj-49829	110	2	a	a	DET
esrj-49829	110	3	collection	collection	NOUN
esrj-49829	110	4	of	of	ADP
esrj-49829	110	5	n	n	PROPN
esrj-49829	110	6	data	data	NOUN
esrj-49829	110	7	points	point	NOUN
esrj-49829	110	8	{	{	PUNCT
esrj-49829	110	9	x1,	x1,	X
esrj-49829	110	10	…	…	X
esrj-49829	110	11	,xn	,xn	PUNCT
esrj-49829	110	12	}	}	PUNCT
esrj-49829	110	13	,	,	PUNCT
esrj-49829	110	14	subtractive	subtractive	ADJ
esrj-49829	110	15	clustering	cluster	VERB
esrj-49829	110	16	algorithm	algorithm	NOUN
esrj-49829	110	17	assumes	assume	VERB
esrj-49829	110	18	each	each	DET
esrj-49829	110	19	data	datum	NOUN
esrj-49829	110	20	point	point	NOUN
esrj-49829	110	21	as	as	ADP
esrj-49829	110	22	a	a	DET
esrj-49829	110	23	potential	potential	ADJ
esrj-49829	110	24	cluster	cluster	NOUN
esrj-49829	110	25	center	center	NOUN
esrj-49829	110	26	.	.	PUNCT
esrj-49829	111	1	a	a	DET
esrj-49829	111	2	density	density	NOUN
esrj-49829	111	3	measure	measure	NOUN
esrj-49829	111	4	at	at	ADP
esrj-49829	111	5	a	a	DET
esrj-49829	111	6	data	data	NOUN
esrj-49829	111	7	point	point	NOUN
esrj-49829	111	8	xi	xi	INTJ
esrj-49829	111	9	is	be	AUX
esrj-49829	111	10	then	then	ADV
esrj-49829	111	11	defined	define	VERB
esrj-49829	111	12	as	as	ADP
esrj-49829	111	13	:	:	PUNCT
esrj-49829	111	14	(	(	PUNCT
esrj-49829	111	15	6	6	NUM
esrj-49829	111	16	)	)	PUNCT
esrj-49829	111	17	where	where	SCONJ
esrj-49829	111	18	di	di	NOUN
esrj-49829	111	19	is	be	AUX
esrj-49829	111	20	the	the	DET
esrj-49829	111	21	density	density	NOUN
esrj-49829	111	22	measure	measure	NOUN
esrj-49829	111	23	and	and	CCONJ
esrj-49829	111	24	the	the	DET
esrj-49829	111	25	cluster	cluster	NOUN
esrj-49829	111	26	radius	radius	NOUN
esrj-49829	111	27	rα	rα	ADV
esrj-49829	111	28	is	be	AUX
esrj-49829	111	29	a	a	DET
esrj-49829	111	30	positive	positive	ADJ
esrj-49829	111	31	constant	constant	ADJ
esrj-49829	111	32	(	(	PUNCT
esrj-49829	111	33	rα	rα	INTJ
esrj-49829	111	34	>	>	X
esrj-49829	111	35	0	0	NUM
esrj-49829	111	36	)	)	PUNCT
esrj-49829	111	37	defining	define	VERB
esrj-49829	111	38	the	the	DET
esrj-49829	111	39	neighborhood	neighborhood	NOUN
esrj-49829	111	40	radius	radius	NOUN
esrj-49829	111	41	for	for	ADP
esrj-49829	111	42	each	each	DET
esrj-49829	111	43	cluster	cluster	NOUN
esrj-49829	111	44	center	center	NOUN
esrj-49829	111	45	.	.	PUNCT
esrj-49829	112	1	thus	thus	ADV
esrj-49829	112	2	,	,	PUNCT
esrj-49829	112	3	a	a	DET
esrj-49829	112	4	data	data	NOUN
esrj-49829	112	5	point	point	NOUN
esrj-49829	112	6	that	that	PRON
esrj-49829	112	7	has	have	VERB
esrj-49829	112	8	many	many	ADJ
esrj-49829	112	9	neighboring	neighboring	NOUN
esrj-49829	112	10	data	data	NOUN
esrj-49829	112	11	points	point	NOUN
esrj-49829	112	12	will	will	AUX
esrj-49829	112	13	have	have	VERB
esrj-49829	112	14	a	a	DET
esrj-49829	112	15	high	high	ADJ
esrj-49829	112	16	potential	potential	NOUN
esrj-49829	112	17	of	of	ADP
esrj-49829	112	18	being	be	AUX
esrj-49829	112	19	a	a	DET
esrj-49829	112	20	cluster	cluster	NOUN
esrj-49829	112	21	center	center	NOUN
esrj-49829	112	22	.	.	PUNCT
esrj-49829	113	1	data	datum	NOUN
esrj-49829	113	2	points	point	NOUN
esrj-49829	113	3	existing	exist	VERB
esrj-49829	113	4	outside	outside	ADP
esrj-49829	113	5	of	of	ADP
esrj-49829	113	6	this	this	DET
esrj-49829	113	7	radius	radius	NOUN
esrj-49829	113	8	have	have	VERB
esrj-49829	113	9	little	little	ADJ
esrj-49829	113	10	or	or	CCONJ
esrj-49829	113	11	no	no	PRON
esrj-49829	113	12	effect	effect	NOUN
esrj-49829	113	13	on	on	ADP
esrj-49829	113	14	the	the	DET
esrj-49829	113	15	density	density	NOUN
esrj-49829	113	16	measure	measure	NOUN
esrj-49829	113	17	.	.	PUNCT
esrj-49829	114	1	the	the	DET
esrj-49829	114	2	choice	choice	NOUN
esrj-49829	114	3	of	of	ADP
esrj-49829	114	4	rα	rα	ADJ
esrj-49829	114	5	is	be	AUX
esrj-49829	114	6	crucial	crucial	ADJ
esrj-49829	114	7	in	in	ADP
esrj-49829	114	8	determining	determine	VERB
esrj-49829	114	9	the	the	DET
esrj-49829	114	10	cluster	cluster	NOUN
esrj-49829	114	11	numbers	number	NOUN
esrj-49829	114	12	.	.	PUNCT
esrj-49829	115	1	large	large	ADJ
esrj-49829	115	2	value	value	NOUN
esrj-49829	115	3	of	of	ADP
esrj-49829	115	4	rα	rα	ADJ
esrj-49829	115	5	will	will	AUX
esrj-49829	115	6	generate	generate	VERB
esrj-49829	115	7	a	a	DET
esrj-49829	115	8	limited	limited	ADJ
esrj-49829	115	9	number	number	NOUN
esrj-49829	115	10	of	of	ADP
esrj-49829	115	11	clusters	cluster	NOUN
esrj-49829	115	12	,	,	PUNCT
esrj-49829	115	13	while	while	SCONJ
esrj-49829	115	14	small	small	ADJ
esrj-49829	115	15	values	value	NOUN
esrj-49829	115	16	of	of	ADP
esrj-49829	115	17	rα	rα	ADJ
esrj-49829	115	18	will	will	AUX
esrj-49829	115	19	generate	generate	VERB
esrj-49829	115	20	a	a	DET
esrj-49829	115	21	large	large	ADJ
esrj-49829	115	22	number	number	NOUN
esrj-49829	115	23	of	of	ADP
esrj-49829	115	24	clusters	cluster	NOUN
esrj-49829	115	25	.	.	PUNCT
esrj-49829	116	1	after	after	ADP
esrj-49829	116	2	calculation	calculation	NOUN
esrj-49829	116	3	of	of	ADP
esrj-49829	116	4	the	the	DET
esrj-49829	116	5	potential	potential	NOUN
esrj-49829	116	6	of	of	ADP
esrj-49829	116	7	each	each	DET
esrj-49829	116	8	vector	vector	NOUN
esrj-49829	116	9	,	,	PUNCT
esrj-49829	116	10	the	the	DET
esrj-49829	116	11	one	one	NOUN
esrj-49829	116	12	with	with	ADP
esrj-49829	116	13	the	the	DET
esrj-49829	116	14	highest	high	ADJ
esrj-49829	116	15	potential	potential	NOUN
esrj-49829	116	16	is	be	AUX
esrj-49829	116	17	selected	select	VERB
esrj-49829	116	18	as	as	ADP
esrj-49829	116	19	the	the	DET
esrj-49829	116	20	first	first	ADJ
esrj-49829	116	21	cluster	cluster	NOUN
esrj-49829	116	22	center	center	NOUN
esrj-49829	116	23	.	.	PUNCT
esrj-49829	117	1	suppose	suppose	VERB
esrj-49829	117	2	xc1	xc1	PROPN
esrj-49829	117	3	is	be	AUX
esrj-49829	117	4	the	the	DET
esrj-49829	117	5	point	point	NOUN
esrj-49829	117	6	selected	select	VERB
esrj-49829	117	7	and	and	CCONJ
esrj-49829	117	8	dc1	dc1	PROPN
esrj-49829	117	9	is	be	AUX
esrj-49829	117	10	its	its	PRON
esrj-49829	117	11	density	density	NOUN
esrj-49829	117	12	measure	measure	NOUN
esrj-49829	117	13	.	.	PUNCT
esrj-49829	118	1	the	the	DET
esrj-49829	118	2	density	density	NOUN
esrj-49829	118	3	measure	measure	NOUN
esrj-49829	118	4	for	for	ADP
esrj-49829	118	5	each	each	DET
esrj-49829	118	6	data	data	NOUN
esrj-49829	118	7	point	point	NOUN
esrj-49829	118	8	xi	xi	INTJ
esrj-49829	118	9	is	be	AUX
esrj-49829	118	10	revised	revise	VERB
esrj-49829	118	11	by	by	ADP
esrj-49829	118	12	the	the	DET
esrj-49829	118	13	formula	formula	NOUN
esrj-49829	118	14	:	:	PUNCT
esrj-49829	118	15	(	(	PUNCT
esrj-49829	118	16	7	7	X
esrj-49829	118	17	)	)	PUNCT
esrj-49829	118	18	where	where	SCONJ
esrj-49829	118	19	rb	rb	NOUN
esrj-49829	118	20	is	be	AUX
esrj-49829	118	21	a	a	DET
esrj-49829	118	22	positive	positive	ADJ
esrj-49829	118	23	constant	constant	ADJ
esrj-49829	118	24	(	(	PUNCT
esrj-49829	118	25	rb	rb	X
esrj-49829	118	26	>	>	X
esrj-49829	118	27	0	0	NUM
esrj-49829	118	28	)	)	PUNCT
esrj-49829	118	29	that	that	PRON
esrj-49829	118	30	represents	represent	VERB
esrj-49829	118	31	the	the	DET
esrj-49829	118	32	radius	radius	NOUN
esrj-49829	118	33	of	of	ADP
esrj-49829	118	34	the	the	DET
esrj-49829	118	35	neighborhood	neighborhood	NOUN
esrj-49829	118	36	for	for	ADP
esrj-49829	118	37	which	which	PRON
esrj-49829	118	38	considerable	considerable	ADJ
esrj-49829	118	39	potential	potential	ADJ
esrj-49829	118	40	reduction	reduction	NOUN
esrj-49829	118	41	will	will	AUX
esrj-49829	118	42	happen	happen	VERB
esrj-49829	118	43	in	in	ADP
esrj-49829	118	44	density	density	NOUN
esrj-49829	118	45	measure	measure	NOUN
esrj-49829	118	46	.	.	PUNCT
esrj-49829	119	1	in	in	ADP
esrj-49829	119	2	order	order	NOUN
esrj-49829	119	3	to	to	PART
esrj-49829	119	4	avoid	avoid	VERB
esrj-49829	119	5	obtaining	obtain	VERB
esrj-49829	119	6	closely	closely	ADV
esrj-49829	119	7	spaced	space	VERB
esrj-49829	119	8	cluster	cluster	NOUN
esrj-49829	119	9	centers	center	NOUN
esrj-49829	119	10	,	,	PUNCT
esrj-49829	119	11	the	the	DET
esrj-49829	119	12	constant	constant	ADJ
esrj-49829	119	13	rb	rb	NOUN
esrj-49829	119	14	is	be	AUX
esrj-49829	119	15	usually	usually	ADV
esrj-49829	119	16	1.5	1.5	NUM
esrj-49829	119	17	times	time	NOUN
esrj-49829	119	18	that	that	DET
esrj-49829	119	19	of	of	ADP
esrj-49829	119	20	rα	rα	ADJ
esrj-49829	119	21	.	.	PUNCT
esrj-49829	120	1	finally	finally	ADV
esrj-49829	120	2	,	,	PUNCT
esrj-49829	120	3	the	the	DET
esrj-49829	120	4	clusters	cluster	NOUN
esrj-49829	120	5	’	’	PART
esrj-49829	120	6	information	information	NOUN
esrj-49829	120	7	is	be	AUX
esrj-49829	120	8	used	use	VERB
esrj-49829	120	9	to	to	PART
esrj-49829	120	10	determine	determine	VERB
esrj-49829	120	11	the	the	DET
esrj-49829	120	12	initial	initial	ADJ
esrj-49829	120	13	number	number	NOUN
esrj-49829	120	14	of	of	ADP
esrj-49829	120	15	rules	rule	NOUN
esrj-49829	120	16	and	and	CCONJ
esrj-49829	120	17	antecedent	antecedent	NOUN
esrj-49829	120	18	membership	membership	NOUN
esrj-49829	120	19	function	function	NOUN
esrj-49829	120	20	that	that	PRON
esrj-49829	120	21	is	be	AUX
esrj-49829	120	22	used	use	VERB
esrj-49829	120	23	for	for	ADP
esrj-49829	120	24	identifying	identify	VERB
esrj-49829	120	25	the	the	DET
esrj-49829	120	26	fis	fis	PROPN
esrj-49829	120	27	(	(	PUNCT
esrj-49829	120	28	chiu	chiu	PROPN
esrj-49829	120	29	,	,	PUNCT
esrj-49829	120	30	1994	1994	NUM
esrj-49829	120	31	)	)	PUNCT
esrj-49829	120	32	.	.	PUNCT
esrj-49829	121	1	2.3	2.3	NUM
esrj-49829	121	2	.	.	PUNCT
esrj-49829	122	1	artificial	artificial	ADJ
esrj-49829	122	2	neural	neural	ADJ
esrj-49829	122	3	networks	network	NOUN
esrj-49829	122	4	(	(	PUNCT
esrj-49829	122	5	anns	anns	PROPN
esrj-49829	122	6	)	)	PUNCT
esrj-49829	122	7	the	the	DET
esrj-49829	122	8	anns	ann	NOUN
esrj-49829	122	9	are	be	AUX
esrj-49829	122	10	alternative	alternative	ADJ
esrj-49829	122	11	artificial	artificial	ADJ
esrj-49829	122	12	intelligent	intelligent	ADJ
esrj-49829	122	13	(	(	PUNCT
esrj-49829	122	14	ai	ai	NOUN
esrj-49829	122	15	)	)	PUNCT
esrj-49829	122	16	methods	method	NOUN
esrj-49829	122	17	and	and	CCONJ
esrj-49829	122	18	employed	employ	VERB
esrj-49829	122	19	in	in	ADP
esrj-49829	122	20	this	this	DET
esrj-49829	122	21	study	study	NOUN
esrj-49829	122	22	to	to	PART
esrj-49829	122	23	predict	predict	VERB
esrj-49829	122	24	soil	soil	NOUN
esrj-49829	122	25	temperature	temperature	NOUN
esrj-49829	122	26	.	.	PUNCT
esrj-49829	123	1	a	a	DET
esrj-49829	123	2	number	number	NOUN
esrj-49829	123	3	of	of	ADP
esrj-49829	123	4	network	network	NOUN
esrj-49829	123	5	and	and	CCONJ
esrj-49829	123	6	training	training	NOUN
esrj-49829	123	7	algorithms	algorithm	NOUN
esrj-49829	123	8	are	be	AUX
esrj-49829	123	9	reported	report	VERB
esrj-49829	123	10	in	in	ADP
esrj-49829	123	11	the	the	DET
esrj-49829	123	12	literature	literature	NOUN
esrj-49829	123	13	.	.	PUNCT
esrj-49829	124	1	the	the	DET
esrj-49829	124	2	multi	multi	ADJ
esrj-49829	124	3	-	-	ADJ
esrj-49829	124	4	layer	layer	ADJ
esrj-49829	124	5	perceptron	perceptron	NOUN
esrj-49829	124	6	(	(	PUNCT
esrj-49829	124	7	mlp	mlp	PROPN
esrj-49829	124	8	)	)	PUNCT
esrj-49829	124	9	is	be	AUX
esrj-49829	124	10	one	one	NUM
esrj-49829	124	11	of	of	ADP
esrj-49829	124	12	the	the	DET
esrj-49829	124	13	mostly	mostly	ADV
esrj-49829	124	14	used	use	VERB
esrj-49829	124	15	ann	ann	PROPN
esrj-49829	124	16	in	in	ADP
esrj-49829	124	17	many	many	ADJ
esrj-49829	124	18	research	research	NOUN
esrj-49829	124	19	areas	area	NOUN
esrj-49829	124	20	.	.	PUNCT
esrj-49829	125	1	this	this	DET
esrj-49829	125	2	study	study	NOUN
esrj-49829	125	3	uses	use	VERB
esrj-49829	125	4	mlp	mlp	NOUN
esrj-49829	125	5	possessing	possess	VERB
esrj-49829	125	6	a	a	DET
esrj-49829	125	7	three	three	NUM
esrj-49829	125	8	-	-	PUNCT
esrj-49829	125	9	layer	layer	NOUN
esrj-49829	125	10	learning	learn	VERB
esrj-49829	125	11	network	network	NOUN
esrj-49829	125	12	consisting	consist	VERB
esrj-49829	125	13	of	of	ADP
esrj-49829	125	14	an	an	DET
esrj-49829	125	15	input	input	NOUN
esrj-49829	125	16	layer	layer	NOUN
esrj-49829	125	17	,	,	PUNCT
esrj-49829	125	18	one	one	NUM
esrj-49829	125	19	hidden	hide	VERB
esrj-49829	125	20	layer	layer	NOUN
esrj-49829	125	21	,	,	PUNCT
esrj-49829	125	22	and	and	CCONJ
esrj-49829	125	23	one	one	NUM
esrj-49829	125	24	output	output	NOUN
esrj-49829	125	25	layer	layer	NOUN
esrj-49829	125	26	.	.	PUNCT
esrj-49829	126	1	the	the	DET
esrj-49829	126	2	input	input	NOUN
esrj-49829	126	3	layer	layer	NOUN
esrj-49829	126	4	accepts	accept	VERB
esrj-49829	126	5	values	value	NOUN
esrj-49829	126	6	of	of	ADP
esrj-49829	126	7	the	the	DET
esrj-49829	126	8	input	input	NOUN
esrj-49829	126	9	variables	variable	NOUN
esrj-49829	126	10	and	and	CCONJ
esrj-49829	126	11	the	the	DET
esrj-49829	126	12	output	output	NOUN
esrj-49829	126	13	layer	layer	NOUN
esrj-49829	126	14	provides	provide	VERB
esrj-49829	126	15	estimations	estimation	NOUN
esrj-49829	126	16	.	.	PUNCT
esrj-49829	127	1	the	the	DET
esrj-49829	127	2	hidden	hide	VERB
esrj-49829	127	3	layer	layer	NOUN
esrj-49829	127	4	which	which	PRON
esrj-49829	127	5	lies	lie	VERB
esrj-49829	127	6	between	between	ADP
esrj-49829	127	7	the	the	DET
esrj-49829	127	8	input	input	NOUN
esrj-49829	127	9	and	and	CCONJ
esrj-49829	127	10	output	output	NOUN
esrj-49829	127	11	layers	layer	NOUN
esrj-49829	127	12	contains	contain	VERB
esrj-49829	127	13	the	the	DET
esrj-49829	127	14	processing	processing	NOUN
esrj-49829	127	15	elements	element	NOUN
esrj-49829	127	16	called	call	VERB
esrj-49829	127	17	as	as	ADP
esrj-49829	127	18	neurons	neuron	NOUN
esrj-49829	127	19	.	.	PUNCT
esrj-49829	128	1	the	the	DET
esrj-49829	128	2	hidden	hide	VERB
esrj-49829	128	3	layer	layer	NOUN
esrj-49829	128	4	and	and	CCONJ
esrj-49829	128	5	nodes	node	NOUN
esrj-49829	128	6	play	play	VERB
esrj-49829	128	7	very	very	ADV
esrj-49829	128	8	important	important	ADJ
esrj-49829	128	9	roles	role	NOUN
esrj-49829	128	10	for	for	ADP
esrj-49829	128	11	successful	successful	ADJ
esrj-49829	128	12	application	application	NOUN
esrj-49829	128	13	of	of	ADP
esrj-49829	128	14	the	the	DET
esrj-49829	128	15	neural	neural	ADJ
esrj-49829	128	16	network	network	NOUN
esrj-49829	128	17	.	.	PUNCT
esrj-49829	129	1	the	the	DET
esrj-49829	129	2	nodes	node	NOUN
esrj-49829	129	3	in	in	ADP
esrj-49829	129	4	the	the	DET
esrj-49829	129	5	hidden	hide	VERB
esrj-49829	129	6	layer	layer	NOUN
esrj-49829	129	7	allow	allow	VERB
esrj-49829	129	8	neural	neural	ADJ
esrj-49829	129	9	networks	network	NOUN
esrj-49829	129	10	to	to	PART
esrj-49829	129	11	detect	detect	VERB
esrj-49829	129	12	the	the	DET
esrj-49829	129	13	feature	feature	NOUN
esrj-49829	129	14	,	,	PUNCT
esrj-49829	129	15	to	to	PART
esrj-49829	129	16	capture	capture	VERB
esrj-49829	129	17	the	the	DET
esrj-49829	129	18	pattern	pattern	NOUN
esrj-49829	129	19	in	in	ADP
esrj-49829	129	20	the	the	DET
esrj-49829	129	21	data	datum	NOUN
esrj-49829	129	22	,	,	PUNCT
esrj-49829	129	23	and	and	CCONJ
esrj-49829	129	24	to	to	PART
esrj-49829	129	25	perform	perform	VERB
esrj-49829	129	26	complicated	complicated	ADJ
esrj-49829	129	27	non	non	ADJ
esrj-49829	129	28	-	-	ADJ
esrj-49829	129	29	linear	linear	ADJ
esrj-49829	129	30	mapping	mapping	NOUN
esrj-49829	129	31	between	between	ADP
esrj-49829	129	32	input	input	NOUN
esrj-49829	129	33	and	and	CCONJ
esrj-49829	129	34	output	output	NOUN
esrj-49829	129	35	variables	variable	NOUN
esrj-49829	129	36	.	.	PUNCT
esrj-49829	130	1	it	it	PRON
esrj-49829	130	2	has	have	AUX
esrj-49829	130	3	been	be	AUX
esrj-49829	130	4	suggested	suggest	VERB
esrj-49829	130	5	that	that	SCONJ
esrj-49829	130	6	only	only	ADV
esrj-49829	130	7	one	one	NUM
esrj-49829	130	8	hidden	hide	VERB
esrj-49829	130	9	layer	layer	NOUN
esrj-49829	130	10	is	be	AUX
esrj-49829	130	11	sufficient	sufficient	ADJ
esrj-49829	130	12	for	for	ADP
esrj-49829	130	13	anns	anns	NOUN
esrj-49829	130	14	to	to	PART
esrj-49829	130	15	approximate	approximate	VERB
esrj-49829	130	16	any	any	DET
esrj-49829	130	17	complex	complex	ADJ
esrj-49829	130	18	nonlinear	nonlinear	ADJ
esrj-49829	130	19	function	function	NOUN
esrj-49829	130	20	within	within	ADP
esrj-49829	130	21	desired	desire	VERB
esrj-49829	130	22	degree	degree	NOUN
esrj-49829	130	23	of	of	ADP
esrj-49829	130	24	accuracy	accuracy	NOUN
esrj-49829	130	25	.	.	PUNCT
esrj-49829	131	1	in	in	ADP
esrj-49829	131	2	the	the	DET
esrj-49829	131	3	case	case	NOUN
esrj-49829	131	4	of	of	ADP
esrj-49829	131	5	the	the	DET
esrj-49829	131	6	hidden	hide	VERB
esrj-49829	131	7	layer	layer	NOUN
esrj-49829	131	8	,	,	PUNCT
esrj-49829	131	9	many	many	ADJ
esrj-49829	131	10	studies	study	NOUN
esrj-49829	131	11	suggest	suggest	VERB
esrj-49829	131	12	"	"	PUNCT
esrj-49829	131	13	2m+1	2m+1	PROPN
esrj-49829	131	14	"	"	PUNCT
esrj-49829	131	15	(	(	PUNCT
esrj-49829	131	16	hecht	hecht	PROPN
esrj-49829	131	17	-	-	PUNCT
esrj-49829	131	18	nielsen	nielsen	PROPN
esrj-49829	131	19	,	,	PUNCT
esrj-49829	131	20	1990	1990	NUM
esrj-49829	131	21	;	;	PUNCT
esrj-49829	131	22	lippmann	lippmann	PROPN
esrj-49829	131	23	,	,	PUNCT
esrj-49829	131	24	1987	1987	NUM
esrj-49829	131	25	)	)	PUNCT
esrj-49829	131	26	,	,	PUNCT
esrj-49829	131	27	"	"	PUNCT
esrj-49829	131	28	2	2	NUM
esrj-49829	131	29	m	m	NOUN
esrj-49829	131	30	"	"	PUNCT
esrj-49829	131	31	(	(	PUNCT
esrj-49829	131	32	wong	wong	PROPN
esrj-49829	131	33	,	,	PUNCT
esrj-49829	131	34	1991	1991	NUM
esrj-49829	131	35	)	)	PUNCT
esrj-49829	131	36	and	and	CCONJ
esrj-49829	131	37	"	"	PUNCT
esrj-49829	131	38	m	m	NOUN
esrj-49829	131	39	"	"	PUNCT
esrj-49829	131	40	(	(	PUNCT
esrj-49829	131	41	tang	tang	NOUN
esrj-49829	131	42	and	and	CCONJ
esrj-49829	131	43	fishwick	fishwick	NOUN
esrj-49829	131	44	,	,	PUNCT
esrj-49829	131	45	1993	1993	NUM
esrj-49829	131	46	)	)	PUNCT
esrj-49829	131	47	hidden	hide	VERB
esrj-49829	131	48	neurons	neuron	NOUN
esrj-49829	131	49	for	for	ADP
esrj-49829	131	50	better	well	ADJ
esrj-49829	131	51	forecasting	forecasting	NOUN
esrj-49829	131	52	accuracy	accuracy	NOUN
esrj-49829	131	53	,	,	PUNCT
esrj-49829	131	54	where	where	SCONJ
esrj-49829	131	55	m	m	NOUN
esrj-49829	131	56	is	be	AUX
esrj-49829	131	57	the	the	DET
esrj-49829	131	58	number	number	NOUN
esrj-49829	131	59	of	of	ADP
esrj-49829	131	60	input	input	NOUN
esrj-49829	131	61	nodes	node	NOUN
esrj-49829	131	62	.	.	PUNCT
esrj-49829	132	1	in	in	ADP
esrj-49829	132	2	the	the	DET
esrj-49829	132	3	current	current	ADJ
esrj-49829	132	4	study	study	NOUN
esrj-49829	132	5	,	,	PUNCT
esrj-49829	132	6	a	a	DET
esrj-49829	132	7	large	large	ADJ
esrj-49829	132	8	number	number	NOUN
esrj-49829	132	9	of	of	ADP
esrj-49829	132	10	trials	trial	NOUN
esrj-49829	132	11	were	be	AUX
esrj-49829	132	12	carried	carry	VERB
esrj-49829	132	13	out	out	ADP
esrj-49829	132	14	to	to	PART
esrj-49829	132	15	select	select	VERB
esrj-49829	132	16	the	the	DET
esrj-49829	132	17	optimal	optimal	ADJ
esrj-49829	132	18	number	number	NOUN
esrj-49829	132	19	of	of	ADP
esrj-49829	132	20	nodes	node	NOUN
esrj-49829	132	21	in	in	ADP
esrj-49829	132	22	the	the	DET
esrj-49829	132	23	hidden	hide	VERB
esrj-49829	132	24	layer	layer	NOUN
esrj-49829	132	25	.	.	PUNCT
esrj-49829	133	1	the	the	DET
esrj-49829	133	2	transfer	transfer	NOUN
esrj-49829	133	3	functions	function	NOUN
esrj-49829	133	4	used	use	VERB
esrj-49829	133	5	in	in	ADP
esrj-49829	133	6	this	this	DET
esrj-49829	133	7	study	study	NOUN
esrj-49829	133	8	include	include	VERB
esrj-49829	133	9	the	the	DET
esrj-49829	133	10	tan	tan	NOUN
esrj-49829	133	11	-	-	PUNCT
esrj-49829	133	12	sigmoid	sigmoid	NOUN
esrj-49829	133	13	in	in	ADP
esrj-49829	133	14	the	the	DET
esrj-49829	133	15	hidden	hide	VERB
esrj-49829	133	16	layer	layer	NOUN
esrj-49829	133	17	and	and	CCONJ
esrj-49829	133	18	the	the	DET
esrj-49829	133	19	linear	linear	ADJ
esrj-49829	133	20	transfer	transfer	NOUN
esrj-49829	133	21	function	function	NOUN
esrj-49829	133	22	in	in	ADP
esrj-49829	133	23	the	the	DET
esrj-49829	133	24	output	output	NOUN
esrj-49829	133	25	layer	layer	NOUN
esrj-49829	133	26	.	.	PUNCT
esrj-49829	134	1	the	the	DET
esrj-49829	134	2	levenbergmarquardt	levenbergmarquardt	PROPN
esrj-49829	134	3	training	training	NOUN
esrj-49829	134	4	algorithm	algorithm	NOUN
esrj-49829	134	5	was	be	AUX
esrj-49829	134	6	used	use	VERB
esrj-49829	134	7	for	for	ADP
esrj-49829	134	8	the	the	DET
esrj-49829	134	9	ann	ann	PROPN
esrj-49829	134	10	models	model	NOUN
esrj-49829	134	11	because	because	SCONJ
esrj-49829	134	12	this	this	DET
esrj-49829	134	13	technique	technique	NOUN
esrj-49829	134	14	is	be	AUX
esrj-49829	134	15	more	more	ADV
esrj-49829	134	16	powerful	powerful	ADJ
esrj-49829	134	17	and	and	CCONJ
esrj-49829	134	18	faster	fast	ADJ
esrj-49829	134	19	than	than	ADP
esrj-49829	134	20	the	the	DET
esrj-49829	134	21	gradient	gradient	ADJ
esrj-49829	134	22	descent	descent	NOUN
esrj-49829	134	23	algorithm	algorithm	NOUN
esrj-49829	134	24	.	.	PUNCT
esrj-49829	135	1	2.4	2.4	NUM
esrj-49829	135	2	m5	m5	PROPN
esrj-49829	135	3	model	model	NOUN
esrj-49829	135	4	tree	tree	NOUN
esrj-49829	135	5	model	model	NOUN
esrj-49829	135	6	trees	tree	NOUN
esrj-49829	135	7	generalize	generalize	VERB
esrj-49829	135	8	the	the	DET
esrj-49829	135	9	concepts	concept	NOUN
esrj-49829	135	10	of	of	ADP
esrj-49829	135	11	regression	regression	NOUN
esrj-49829	135	12	trees	tree	NOUN
esrj-49829	135	13	and	and	CCONJ
esrj-49829	135	14	are	be	AUX
esrj-49829	135	15	analogous	analogous	ADJ
esrj-49829	135	16	to	to	ADP
esrj-49829	135	17	piece	piece	NOUN
esrj-49829	135	18	-	-	PUNCT
esrj-49829	135	19	wise	wise	ADJ
esrj-49829	135	20	linear	linear	NOUN
esrj-49829	135	21	functions	function	NOUN
esrj-49829	135	22	.	.	PUNCT
esrj-49829	136	1	a	a	DET
esrj-49829	136	2	m5	m5	PROPN
esrj-49829	136	3	model	model	NOUN
esrj-49829	136	4	tree	tree	NOUN
esrj-49829	136	5	is	be	AUX
esrj-49829	136	6	a	a	DET
esrj-49829	136	7	binary	binary	ADJ
esrj-49829	136	8	decision	decision	NOUN
esrj-49829	136	9	tree	tree	NOUN
esrj-49829	136	10	having	have	VERB
esrj-49829	136	11	linear	linear	PROPN
esrj-49829	136	12	regression	regression	NOUN
esrj-49829	136	13	function	function	NOUN
esrj-49829	136	14	at	at	ADP
esrj-49829	136	15	the	the	DET
esrj-49829	136	16	terminal	terminal	ADJ
esrj-49829	136	17	nodes	node	NOUN
esrj-49829	136	18	,	,	PUNCT
esrj-49829	136	19	which	which	PRON
esrj-49829	136	20	can	can	AUX
esrj-49829	136	21	predict	predict	VERB
esrj-49829	136	22	continuous	continuous	ADJ
esrj-49829	136	23	numerical	numerical	ADJ
esrj-49829	136	24	attributes	attribute	NOUN
esrj-49829	136	25	(	(	PUNCT
esrj-49829	136	26	quinlan	quinlan	PROPN
esrj-49829	136	27	,	,	PUNCT
esrj-49829	136	28	1992	1992	NUM
esrj-49829	136	29	)	)	PUNCT
esrj-49829	136	30	.	.	PUNCT
esrj-49829	137	1	the	the	DET
esrj-49829	137	2	m5	m5	PROPN
esrj-49829	137	3	model	model	NOUN
esrj-49829	137	4	tree	tree	NOUN
esrj-49829	137	5	is	be	AUX
esrj-49829	137	6	an	an	DET
esrj-49829	137	7	algorithm	algorithm	NOUN
esrj-49829	137	8	for	for	ADP
esrj-49829	137	9	making	make	VERB
esrj-49829	137	10	numerical	numerical	ADJ
esrj-49829	137	11	predictions	prediction	NOUN
esrj-49829	137	12	,	,	PUNCT
esrj-49829	137	13	and	and	CCONJ
esrj-49829	137	14	the	the	DET
esrj-49829	137	15	selected	select	VERB
esrj-49829	137	16	tree	tree	NOUN
esrj-49829	137	17	nodes	node	NOUN
esrj-49829	137	18	have	have	VERB
esrj-49829	137	19	the	the	DET
esrj-49829	137	20	attribute	attribute	NOUN
esrj-49829	137	21	of	of	ADP
esrj-49829	137	22	maximum	maximum	ADJ
esrj-49829	137	23	expected	expect	VERB
esrj-49829	137	24	error	error	NOUN
esrj-49829	137	25	that	that	PRON
esrj-49829	137	26	is	be	AUX
esrj-49829	137	27	a	a	DET
esrj-49829	137	28	function	function	NOUN
esrj-49829	137	29	of	of	ADP
esrj-49829	137	30	the	the	DET
esrj-49829	137	31	standard	standard	ADJ
esrj-49829	137	32	deviation	deviation	NOUN
esrj-49829	137	33	in	in	ADP
esrj-49829	137	34	the	the	DET
esrj-49829	137	35	output	output	NOUN
esrj-49829	137	36	parameters	parameter	NOUN
esrj-49829	137	37	.	.	PUNCT
esrj-49829	138	1	a	a	DET
esrj-49829	138	2	model	model	NOUN
esrj-49829	138	3	tree	tree	NOUN
esrj-49829	138	4	based	base	VERB
esrj-49829	138	5	regression	regression	NOUN
esrj-49829	138	6	approach	approach	NOUN
esrj-49829	138	7	works	work	VERB
esrj-49829	138	8	in	in	ADP
esrj-49829	138	9	two	two	NUM
esrj-49829	138	10	different	different	ADJ
esrj-49829	138	11	stages	stage	NOUN
esrj-49829	138	12	.	.	PUNCT
esrj-49829	139	1	in	in	ADP
esrj-49829	139	2	the	the	DET
esrj-49829	139	3	first	first	ADJ
esrj-49829	139	4	stage	stage	NOUN
esrj-49829	139	5	,	,	PUNCT
esrj-49829	139	6	a	a	DET
esrj-49829	139	7	splitting	splitting	NOUN
esrj-49829	139	8	criterion	criterion	NOUN
esrj-49829	139	9	is	be	AUX
esrj-49829	139	10	used	use	VERB
esrj-49829	139	11	to	to	PART
esrj-49829	139	12	create	create	VERB
esrj-49829	139	13	a	a	DET
esrj-49829	139	14	decision	decision	NOUN
esrj-49829	139	15	tree	tree	NOUN
esrj-49829	139	16	.	.	PUNCT
esrj-49829	140	1	the	the	DET
esrj-49829	140	2	splitting	splitting	NOUN
esrj-49829	140	3	criterion	criterion	NOUN
esrj-49829	140	4	for	for	ADP
esrj-49829	140	5	the	the	DET
esrj-49829	140	6	m5	m5	PROPN
esrj-49829	140	7	model	model	NOUN
esrj-49829	140	8	tree	tree	NOUN
esrj-49829	140	9	algorithm	algorithm	NOUN
esrj-49829	140	10	is	be	AUX
esrj-49829	140	11	based	base	VERB
esrj-49829	140	12	on	on	ADP
esrj-49829	140	13	treating	treat	VERB
esrj-49829	140	14	the	the	DET
esrj-49829	140	15	standard	standard	ADJ
esrj-49829	140	16	deviation	deviation	NOUN
esrj-49829	140	17	of	of	ADP
esrj-49829	140	18	the	the	DET
esrj-49829	140	19	class	class	NOUN
esrj-49829	140	20	values	value	NOUN
esrj-49829	140	21	that	that	PRON
esrj-49829	140	22	reach	reach	VERB
esrj-49829	140	23	a	a	DET
esrj-49829	140	24	node	node	NOUN
esrj-49829	140	25	as	as	ADP
esrj-49829	140	26	a	a	DET
esrj-49829	140	27	measure	measure	NOUN
esrj-49829	140	28	of	of	ADP
esrj-49829	140	29	the	the	DET
esrj-49829	140	30	error	error	NOUN
esrj-49829	140	31	at	at	ADP
esrj-49829	140	32	that	that	DET
esrj-49829	140	33	node	node	NOUN
esrj-49829	140	34	and	and	CCONJ
esrj-49829	140	35	calculating	calculate	VERB
esrj-49829	140	36	the	the	DET
esrj-49829	140	37	expected	expect	VERB
esrj-49829	140	38	reduction	reduction	NOUN
esrj-49829	140	39	in	in	ADP
esrj-49829	140	40	this	this	DET
esrj-49829	140	41	error	error	NOUN
esrj-49829	140	42	as	as	ADP
esrj-49829	140	43	a	a	DET
esrj-49829	140	44	result	result	NOUN
esrj-49829	140	45	of	of	ADP
esrj-49829	140	46	testing	test	VERB
esrj-49829	140	47	each	each	DET
esrj-49829	140	48	attribute	attribute	NOUN
esrj-49829	140	49	at	at	ADP
esrj-49829	140	50	that	that	DET
esrj-49829	140	51	node	node	NOUN
esrj-49829	140	52	.	.	PUNCT
esrj-49829	141	1	the	the	DET
esrj-49829	141	2	formula	formula	NOUN
esrj-49829	141	3	for	for	ADP
esrj-49829	141	4	computing	compute	VERB
esrj-49829	141	5	the	the	DET
esrj-49829	141	6	standard	standard	ADJ
esrj-49829	141	7	deviation	deviation	NOUN
esrj-49829	141	8	reduction	reduction	NOUN
esrj-49829	141	9	(	(	PUNCT
esrj-49829	141	10	sdr	sdr	NOUN
esrj-49829	141	11	)	)	PUNCT
esrj-49829	141	12	is	be	AUX
esrj-49829	141	13	:	:	PUNCT
esrj-49829	141	14	(	(	PUNCT
esrj-49829	141	15	8)	8)	NUM
esrj-49829	141	16	(	(	PUNCT
esrj-49829	141	17	9	9	NUM
esrj-49829	141	18	)	)	PUNCT
esrj-49829	141	19	and	and	CCONJ
esrj-49829	141	20	t	t	PROPN
esrj-49829	141	21	is	be	AUX
esrj-49829	141	22	a	a	DET
esrj-49829	141	23	set	set	NOUN
esrj-49829	141	24	of	of	ADP
esrj-49829	141	25	samples	sample	NOUN
esrj-49829	141	26	entering	enter	VERB
esrj-49829	141	27	each	each	DET
esrj-49829	141	28	node	node	NOUN
esrj-49829	141	29	.	.	PUNCT
esrj-49829	142	1	the	the	DET
esrj-49829	142	2	symbol	symbol	NOUN
esrj-49829	142	3	ti	ti	NOUN
esrj-49829	142	4	represents	represent	VERB
esrj-49829	142	5	a	a	DET
esrj-49829	142	6	subset	subset	NOUN
esrj-49829	142	7	of	of	ADP
esrj-49829	142	8	the	the	DET
esrj-49829	142	9	samples	sample	NOUN
esrj-49829	142	10	that	that	PRON
esrj-49829	142	11	have	have	VERB
esrj-49829	142	12	the	the	DET
esrj-49829	142	13	ith	ith	PROPN
esrj-49829	142	14	result	result	NOUN
esrj-49829	142	15	of	of	ADP
esrj-49829	142	16	the	the	DET
esrj-49829	142	17	potentiality	potentiality	NOUN
esrj-49829	142	18	test	test	NOUN
esrj-49829	142	19	,	,	PUNCT
esrj-49829	142	20	sd	sd	X
esrj-49829	142	21	is	be	AUX
esrj-49829	142	22	the	the	DET
esrj-49829	142	23	standard	standard	ADJ
esrj-49829	142	24	deviation	deviation	NOUN
esrj-49829	142	25	,	,	PUNCT
esrj-49829	142	26	yi	yi	PROPN
esrj-49829	142	27	is	be	AUX
esrj-49829	142	28	the	the	DET
esrj-49829	142	29	numerical	numerical	ADJ
esrj-49829	142	30	value	value	NOUN
esrj-49829	142	31	of	of	ADP
esrj-49829	142	32	the	the	DET
esrj-49829	142	33	target	target	NOUN
esrj-49829	142	34	attribute	attribute	NOUN
esrj-49829	142	35	of	of	ADP
esrj-49829	142	36	sample	sample	NOUN
esrj-49829	142	37	i	i	PRON
esrj-49829	142	38	,	,	PUNCT
esrj-49829	142	39	and	and	CCONJ
esrj-49829	142	40	n	n	DET
esrj-49829	142	41	the	the	DET
esrj-49829	142	42	total	total	ADJ
esrj-49829	142	43	number	number	NOUN
esrj-49829	142	44	of	of	ADP
esrj-49829	142	45	data	datum	NOUN
esrj-49829	142	46	points	point	NOUN
esrj-49829	142	47	(	(	PUNCT
esrj-49829	142	48	alberg	alberg	PROPN
esrj-49829	142	49	et	et	PROPN
esrj-49829	142	50	al	al	PROPN
esrj-49829	142	51	.	.	PROPN
esrj-49829	142	52	,	,	PUNCT
esrj-49829	142	53	2012	2012	NUM
esrj-49829	142	54	)	)	PUNCT
esrj-49829	142	55	.	.	PUNCT
esrj-49829	143	1	the	the	DET
esrj-49829	143	2	splitting	splitting	NOUN
esrj-49829	143	3	process	process	NOUN
esrj-49829	143	4	allows	allow	VERB
esrj-49829	143	5	the	the	DET
esrj-49829	143	6	data	datum	NOUN
esrj-49829	143	7	in	in	ADP
esrj-49829	143	8	child	child	NOUN
esrj-49829	143	9	nodes	node	NOUN
esrj-49829	143	10	to	to	PART
esrj-49829	143	11	have	have	VERB
esrj-49829	143	12	a	a	DET
esrj-49829	143	13	lower	low	ADJ
esrj-49829	143	14	standard	standard	ADJ
esrj-49829	143	15	deviation	deviation	NOUN
esrj-49829	143	16	compared	compare	VERB
esrj-49829	143	17	to	to	ADP
esrj-49829	143	18	their	their	PRON
esrj-49829	143	19	parent	parent	NOUN
esrj-49829	143	20	node	node	NOUN
esrj-49829	143	21	and	and	CCONJ
esrj-49829	143	22	can	can	AUX
esrj-49829	143	23	be	be	AUX
esrj-49829	143	24	considered	consider	VERB
esrj-49829	143	25	as	as	ADP
esrj-49829	143	26	more	more	ADV
esrj-49829	143	27	pure	pure	ADJ
esrj-49829	143	28	.	.	PUNCT
esrj-49829	144	1	after	after	ADP
esrj-49829	144	2	examining	examine	VERB
esrj-49829	144	3	all	all	DET
esrj-49829	144	4	the	the	DET
esrj-49829	144	5	possible	possible	ADJ
esrj-49829	144	6	splits	split	NOUN
esrj-49829	144	7	,	,	PUNCT
esrj-49829	144	8	m5	m5	PROPN
esrj-49829	144	9	chooses	choose	VERB
esrj-49829	144	10	the	the	DET
esrj-49829	144	11	one	one	NOUN
esrj-49829	144	12	that	that	PRON
esrj-49829	144	13	maximizes	maximize	VERB
esrj-49829	144	14	the	the	DET
esrj-49829	144	15	expected	expect	VERB
esrj-49829	144	16	error	error	NOUN
esrj-49829	144	17	reduction	reduction	NOUN
esrj-49829	144	18	.	.	PUNCT
esrj-49829	145	1	the	the	DET
esrj-49829	145	2	division	division	NOUN
esrj-49829	145	3	of	of	ADP
esrj-49829	145	4	training	training	NOUN
esrj-49829	145	5	data	datum	NOUN
esrj-49829	145	6	with	with	ADP
esrj-49829	145	7	a	a	DET
esrj-49829	145	8	m5	m5	PROPN
esrj-49829	145	9	model	model	NOUN
esrj-49829	145	10	tree	tree	NOUN
esrj-49829	145	11	produces	produce	VERB
esrj-49829	145	12	a	a	DET
esrj-49829	145	13	large	large	ADJ
esrj-49829	145	14	tree	tree	NOUN
esrj-49829	145	15	-	-	PUNCT
esrj-49829	145	16	like	like	ADJ
esrj-49829	145	17	structure	structure	NOUN
esrj-49829	145	18	which	which	PRON
esrj-49829	145	19	may	may	AUX
esrj-49829	145	20	cause	cause	VERB
esrj-49829	145	21	overfitting	overfitting	NOUN
esrj-49829	145	22	of	of	ADP
esrj-49829	145	23	the	the	DET
esrj-49829	145	24	data	datum	NOUN
esrj-49829	145	25	.	.	PUNCT
esrj-49829	146	1	a	a	DET
esrj-49829	146	2	pruning	prune	VERB
esrj-49829	146	3	algorithm	algorithm	NOUN
esrj-49829	146	4	is	be	AUX
esrj-49829	146	5	used	use	VERB
esrj-49829	146	6	to	to	PART
esrj-49829	146	7	prune	prune	VERB
esrj-49829	146	8	back	back	ADV
esrj-49829	146	9	the	the	DET
esrj-49829	146	10	tree	tree	NOUN
esrj-49829	146	11	,	,	PUNCT
esrj-49829	146	12	for	for	ADP
esrj-49829	146	13	example	example	NOUN
esrj-49829	146	14	by	by	ADP
esrj-49829	146	15	replacing	replace	VERB
esrj-49829	146	16	a	a	DET
esrj-49829	146	17	sub	sub	NOUN
esrj-49829	146	18	tree	tree	NOUN
esrj-49829	146	19	with	with	ADP
esrj-49829	146	20	a	a	DET
esrj-49829	146	21	leaf	leaf	NOUN
esrj-49829	146	22	in	in	ADP
esrj-49829	146	23	order	order	NOUN
esrj-49829	146	24	to	to	PART
esrj-49829	146	25	remove	remove	VERB
esrj-49829	146	26	the	the	DET
esrj-49829	146	27	problem	problem	NOUN
esrj-49829	146	28	of	of	ADP
esrj-49829	146	29	overfitting	overfitte	VERB
esrj-49829	146	30	.	.	PUNCT
esrj-49829	147	1	thus	thus	ADV
esrj-49829	147	2	,	,	PUNCT
esrj-49829	147	3	the	the	DET
esrj-49829	147	4	second	second	ADJ
esrj-49829	147	5	stage	stage	NOUN
esrj-49829	147	6	in	in	ADP
esrj-49829	147	7	the	the	DET
esrj-49829	147	8	design	design	NOUN
esrj-49829	147	9	of	of	ADP
esrj-49829	147	10	the	the	DET
esrj-49829	147	11	model	model	NOUN
esrj-49829	147	12	tree	tree	NOUN
esrj-49829	147	13	involves	involve	VERB
esrj-49829	147	14	pruning	prune	VERB
esrj-49829	147	15	the	the	DET
esrj-49829	147	16	overgrown	overgrown	ADJ
esrj-49829	147	17	tree	tree	NOUN
esrj-49829	147	18	and	and	CCONJ
esrj-49829	147	19	replacing	replace	VERB
esrj-49829	147	20	the	the	DET
esrj-49829	147	21	sub	sub	NOUN
esrj-49829	147	22	trees	tree	NOUN
esrj-49829	147	23	with	with	ADP
esrj-49829	147	24	linear	linear	ADJ
esrj-49829	147	25	regression	regression	NOUN
esrj-49829	147	26	functions	function	NOUN
esrj-49829	147	27	.	.	PUNCT
esrj-49829	148	1	this	this	DET
esrj-49829	148	2	technique	technique	NOUN
esrj-49829	148	3	of	of	ADP
esrj-49829	148	4	generating	generate	VERB
esrj-49829	148	5	the	the	DET
esrj-49829	148	6	model	model	NOUN
esrj-49829	148	7	tree	tree	NOUN
esrj-49829	148	8	splits	split	VERB
esrj-49829	148	9	the	the	DET
esrj-49829	148	10	parameter	parameter	NOUN
esrj-49829	148	11	space	space	NOUN
esrj-49829	148	12	into	into	ADP
esrj-49829	148	13	areas	area	NOUN
esrj-49829	148	14	(	(	PUNCT
esrj-49829	148	15	subspaces	subspace	NOUN
esrj-49829	148	16	)	)	PUNCT
esrj-49829	148	17	and	and	CCONJ
esrj-49829	148	18	builds	build	VERB
esrj-49829	148	19	in	in	ADP
esrj-49829	148	20	each	each	PRON
esrj-49829	148	21	of	of	ADP
esrj-49829	148	22	them	they	PRON
esrj-49829	148	23	a	a	DET
esrj-49829	148	24	linear	linear	ADJ
esrj-49829	148	25	regression	regression	NOUN
esrj-49829	148	26	model	model	NOUN
esrj-49829	148	27	.	.	PUNCT
esrj-49829	149	1	for	for	ADP
esrj-49829	149	2	further	further	ADJ
esrj-49829	149	3	details	detail	NOUN
esrj-49829	149	4	of	of	ADP
esrj-49829	149	5	m5	m5	PROPN
esrj-49829	149	6	model	model	NOUN
esrj-49829	149	7	tree	tree	NOUN
esrj-49829	149	8	,	,	PUNCT
esrj-49829	149	9	readers	reader	NOUN
esrj-49829	149	10	are	be	AUX
esrj-49829	149	11	referred	refer	VERB
esrj-49829	149	12	to	to	ADP
esrj-49829	149	13	related	related	ADJ
esrj-49829	149	14	studies	study	NOUN
esrj-49829	149	15	(	(	PUNCT
esrj-49829	149	16	pal	pal	NOUN
esrj-49829	149	17	and	and	CCONJ
esrj-49829	149	18	surinder	surinder	PROPN
esrj-49829	149	19	,	,	PUNCT
esrj-49829	149	20	2009	2009	NUM
esrj-49829	149	21	;	;	PUNCT
esrj-49829	149	22	quinlan	quinlan	PROPN
esrj-49829	149	23	,	,	PUNCT
esrj-49829	149	24	1992	1992	NUM
esrj-49829	149	25	)	)	PUNCT
esrj-49829	149	26	.	.	PUNCT
esrj-49829	150	1	3	3	X
esrj-49829	150	2	.	.	NOUN
esrj-49829	150	3	results	result	NOUN
esrj-49829	150	4	and	and	CCONJ
esrj-49829	150	5	discussion	discussion	NOUN
esrj-49829	150	6	analysis	analysis	NOUN
esrj-49829	150	7	of	of	ADP
esrj-49829	150	8	table	table	NOUN
esrj-49829	150	9	1	1	NUM
esrj-49829	150	10	suggests	suggest	VERB
esrj-49829	150	11	a	a	DET
esrj-49829	150	12	noticeable	noticeable	ADJ
esrj-49829	150	13	change	change	NOUN
esrj-49829	150	14	in	in	ADP
esrj-49829	150	15	coefficient	coefficient	NOUN
esrj-49829	150	16	of	of	ADP
esrj-49829	150	17	variation	variation	NOUN
esrj-49829	150	18	(	(	PUNCT
esrj-49829	150	19	cv	cv	NOUN
esrj-49829	150	20	)	)	PUNCT
esrj-49829	150	21	value	value	NOUN
esrj-49829	150	22	of	of	ADP
esrj-49829	150	23	soil	soil	NOUN
esrj-49829	150	24	temperature	temperature	NOUN
esrj-49829	150	25	from	from	ADP
esrj-49829	150	26	the	the	DET
esrj-49829	150	27	surface	surface	NOUN
esrj-49829	150	28	to	to	ADP
esrj-49829	150	29	the	the	DET
esrj-49829	150	30	depth	depth	NOUN
esrj-49829	150	31	of	of	ADP
esrj-49829	150	32	100	100	NUM
esrj-49829	150	33	cm	cm	NOUN
esrj-49829	150	34	.	.	PUNCT
esrj-49829	151	1	the	the	DET
esrj-49829	151	2	highest	high	ADJ
esrj-49829	151	3	value	value	NOUN
esrj-49829	151	4	of	of	ADP
esrj-49829	151	5	the	the	DET
esrj-49829	151	6	coefficient	coefficient	NOUN
esrj-49829	151	7	of	of	ADP
esrj-49829	151	8	variation	variation	NOUN
esrj-49829	151	9	was	be	AUX
esrj-49829	151	10	observed	observe	VERB
esrj-49829	151	11	at	at	ADP
esrj-49829	151	12	a	a	DET
esrj-49829	151	13	5	5	NUM
esrj-49829	151	14	cm	cm	NOUN
esrj-49829	151	15	soil	soil	NOUN
esrj-49829	151	16	depth	depth	NOUN
esrj-49829	151	17	with	with	ADP
esrj-49829	151	18	a	a	DET
esrj-49829	151	19	continuous	continuous	ADJ
esrj-49829	151	20	decline	decline	NOUN
esrj-49829	151	21	in	in	ADP
esrj-49829	151	22	its	its	PRON
esrj-49829	151	23	value	value	NOUN
esrj-49829	151	24	with	with	ADP
esrj-49829	151	25	increasing	increase	VERB
esrj-49829	151	26	depth	depth	NOUN
esrj-49829	151	27	of	of	ADP
esrj-49829	151	28	the	the	DET
esrj-49829	151	29	soil	soil	NOUN
esrj-49829	151	30	.	.	PUNCT
esrj-49829	152	1	other	other	ADJ
esrj-49829	152	2	statistical	statistical	ADJ
esrj-49829	152	3	properties	property	NOUN
esrj-49829	152	4	such	such	ADJ
esrj-49829	152	5	as	as	ADP
esrj-49829	152	6	the	the	DET
esrj-49829	152	7	maximum	maximum	ADJ
esrj-49829	152	8	and	and	CCONJ
esrj-49829	152	9	mean	mean	ADJ
esrj-49829	152	10	soil	soil	NOUN
esrj-49829	152	11	temperatures	temperature	NOUN
esrj-49829	152	12	are	be	AUX
esrj-49829	152	13	also	also	ADV
esrj-49829	152	14	decreasing	decrease	VERB
esrj-49829	152	15	with	with	ADP
esrj-49829	152	16	increasing	increase	VERB
esrj-49829	152	17	soil	soil	NOUN
esrj-49829	152	18	depth	depth	NOUN
esrj-49829	152	19	.	.	PUNCT
esrj-49829	153	1	89estimation	89estimation	NUM
esrj-49829	153	2	of	of	ADP
esrj-49829	153	3	daily	daily	ADJ
esrj-49829	153	4	soil	soil	NOUN
esrj-49829	153	5	temperature	temperature	NOUN
esrj-49829	153	6	via	via	ADP
esrj-49829	153	7	data	datum	NOUN
esrj-49829	153	8	mining	mining	NOUN
esrj-49829	153	9	techniques	technique	NOUN
esrj-49829	153	10	in	in	ADP
esrj-49829	153	11	semi	semi	ADJ
esrj-49829	153	12	-	-	ADJ
esrj-49829	153	13	arid	arid	ADJ
esrj-49829	153	14	climate	climate	NOUN
esrj-49829	153	15	conditions	condition	NOUN
esrj-49829	153	16	it	it	PRON
esrj-49829	153	17	can	can	AUX
esrj-49829	153	18	be	be	AUX
esrj-49829	153	19	observed	observe	VERB
esrj-49829	153	20	that	that	SCONJ
esrj-49829	153	21	the	the	DET
esrj-49829	153	22	variability	variability	NOUN
esrj-49829	153	23	in	in	ADP
esrj-49829	153	24	thermal	thermal	ADJ
esrj-49829	153	25	behavior	behavior	NOUN
esrj-49829	153	26	of	of	ADP
esrj-49829	153	27	the	the	DET
esrj-49829	153	28	soil	soil	NOUN
esrj-49829	153	29	profile	profile	NOUN
esrj-49829	153	30	can	can	AUX
esrj-49829	153	31	be	be	AUX
esrj-49829	153	32	a	a	DET
esrj-49829	153	33	cause	cause	NOUN
esrj-49829	153	34	of	of	ADP
esrj-49829	153	35	this	this	DET
esrj-49829	153	36	change	change	NOUN
esrj-49829	153	37	.	.	PUNCT
esrj-49829	154	1	the	the	DET
esrj-49829	154	2	higher	high	ADJ
esrj-49829	154	3	values	value	NOUN
esrj-49829	154	4	of	of	ADP
esrj-49829	154	5	coefficients	coefficient	NOUN
esrj-49829	154	6	of	of	ADP
esrj-49829	154	7	variation	variation	NOUN
esrj-49829	154	8	in	in	ADP
esrj-49829	154	9	the	the	DET
esrj-49829	154	10	surface	surface	NOUN
esrj-49829	154	11	layers	layer	NOUN
esrj-49829	154	12	indicate	indicate	VERB
esrj-49829	154	13	that	that	SCONJ
esrj-49829	154	14	higher	high	ADJ
esrj-49829	154	15	variability	variability	NOUN
esrj-49829	154	16	of	of	ADP
esrj-49829	154	17	the	the	DET
esrj-49829	154	18	soil	soil	NOUN
esrj-49829	154	19	temperature	temperature	NOUN
esrj-49829	154	20	at	at	ADP
esrj-49829	154	21	this	this	DET
esrj-49829	154	22	level	level	NOUN
esrj-49829	154	23	is	be	AUX
esrj-49829	154	24	possibly	possibly	ADV
esrj-49829	154	25	due	due	ADJ
esrj-49829	154	26	to	to	ADP
esrj-49829	154	27	the	the	DET
esrj-49829	154	28	variety	variety	NOUN
esrj-49829	154	29	of	of	ADP
esrj-49829	154	30	causal	causal	ADJ
esrj-49829	154	31	mechanisms	mechanism	NOUN
esrj-49829	154	32	influencing	influence	VERB
esrj-49829	154	33	soil	soil	NOUN
esrj-49829	154	34	temperature	temperature	NOUN
esrj-49829	154	35	.	.	PUNCT
esrj-49829	155	1	figure	figure	NOUN
esrj-49829	155	2	3	3	NUM
esrj-49829	155	3	shows	show	VERB
esrj-49829	155	4	the	the	DET
esrj-49829	155	5	variation	variation	NOUN
esrj-49829	155	6	of	of	ADP
esrj-49829	155	7	soil	soil	NOUN
esrj-49829	155	8	temperature	temperature	NOUN
esrj-49829	155	9	at	at	ADP
esrj-49829	155	10	different	different	ADJ
esrj-49829	155	11	soil	soil	NOUN
esrj-49829	155	12	depths	depth	NOUN
esrj-49829	155	13	in	in	ADP
esrj-49829	155	14	the	the	DET
esrj-49829	155	15	study	study	NOUN
esrj-49829	155	16	area	area	NOUN
esrj-49829	155	17	.	.	PUNCT
esrj-49829	156	1	as	as	SCONJ
esrj-49829	156	2	can	can	AUX
esrj-49829	156	3	be	be	AUX
esrj-49829	156	4	seen	see	VERB
esrj-49829	156	5	from	from	ADP
esrj-49829	156	6	the	the	DET
esrj-49829	156	7	figure	figure	NOUN
esrj-49829	156	8	,	,	PUNCT
esrj-49829	156	9	a	a	DET
esrj-49829	156	10	wide	wide	ADJ
esrj-49829	156	11	range	range	NOUN
esrj-49829	156	12	of	of	ADP
esrj-49829	156	13	fluctuations	fluctuation	NOUN
esrj-49829	156	14	exists	exist	VERB
esrj-49829	156	15	for	for	ADP
esrj-49829	156	16	the	the	DET
esrj-49829	156	17	surface	surface	NOUN
esrj-49829	156	18	layers	layer	NOUN
esrj-49829	156	19	which	which	PRON
esrj-49829	156	20	decreases	decrease	VERB
esrj-49829	156	21	with	with	ADP
esrj-49829	156	22	increasing	increase	VERB
esrj-49829	156	23	depth	depth	NOUN
esrj-49829	156	24	.	.	PUNCT
esrj-49829	157	1	0	0	NUM
esrj-49829	158	1	500	500	NUM
esrj-49829	158	2	1000	1000	NUM
esrj-49829	158	3	1500	1500	NUM
esrj-49829	158	4	2000	2000	NUM
esrj-49829	158	5	2500	2500	NUM
esrj-49829	158	6	3000	3000	NUM
esrj-49829	158	7	3500	3500	NUM
esrj-49829	158	8	0	0	NUM
esrj-49829	158	9	10	10	NUM
esrj-49829	158	10	20	20	NUM
esrj-49829	158	11	30	30	NUM
esrj-49829	158	12	40	40	NUM
esrj-49829	158	13	50	50	NUM
esrj-49829	158	14	time	time	NOUN
esrj-49829	158	15	(	(	PUNCT
esrj-49829	158	16	day	day	NOUN
esrj-49829	158	17	)	)	PUNCT
esrj-49829	159	1	so	so	CCONJ
esrj-49829	159	2	il	il	PROPN
esrj-49829	159	3	te	te	PROPN
esrj-49829	159	4	m	m	PROPN
esrj-49829	159	5	pe	pe	INTJ
esrj-49829	159	6	ra	ra	PROPN
esrj-49829	159	7	tu	tu	X
esrj-49829	159	8	re	re	X
esrj-49829	159	9	(	(	PUNCT
esrj-49829	159	10	c	c	NOUN
esrj-49829	159	11	o	o	NOUN
esrj-49829	159	12	)	)	PUNCT
esrj-49829	159	13	depth	depth	NOUN
esrj-49829	159	14	5	5	NUM
esrj-49829	159	15	cm	cm	NOUN
esrj-49829	159	16	depth	depth	NOUN
esrj-49829	159	17	10	10	NUM
esrj-49829	159	18	cm	cm	NOUN
esrj-49829	159	19	depth	depth	NOUN
esrj-49829	159	20	20	20	NUM
esrj-49829	159	21	cm	cm	NOUN
esrj-49829	159	22	depth	depth	NOUN
esrj-49829	159	23	30	30	NUM
esrj-49829	159	24	cm	cm	NOUN
esrj-49829	159	25	depth	depth	NOUN
esrj-49829	159	26	50	50	NUM
esrj-49829	159	27	cm	cm	NOUN
esrj-49829	159	28	depth	depth	NOUN
esrj-49829	159	29	100	100	NUM
esrj-49829	159	30	cm	cm	NOUN
esrj-49829	159	31	figure	figure	NOUN
esrj-49829	159	32	3	3	NUM
esrj-49829	159	33	.	.	NOUN
esrj-49829	159	34	time	time	NOUN
esrj-49829	159	35	series	series	PROPN
esrj-49829	159	36	of	of	ADP
esrj-49829	159	37	observed	observe	VERB
esrj-49829	159	38	soil	soil	NOUN
esrj-49829	159	39	temperatures	temperature	NOUN
esrj-49829	159	40	at	at	ADP
esrj-49829	159	41	different	different	ADJ
esrj-49829	159	42	soil	soil	NOUN
esrj-49829	159	43	depths	depth	NOUN
esrj-49829	159	44	(	(	PUNCT
esrj-49829	159	45	5	5	NUM
esrj-49829	159	46	-	-	SYM
esrj-49829	159	47	100	100	NUM
esrj-49829	159	48	cm	cm	NOUN
esrj-49829	159	49	)	)	PUNCT
esrj-49829	159	50	the	the	DET
esrj-49829	159	51	three	three	NUM
esrj-49829	159	52	modeling	modeling	NOUN
esrj-49829	159	53	techniques	technique	NOUN
esrj-49829	159	54	;	;	PUNCT
esrj-49829	159	55	anfis	anfis	PROPN
esrj-49829	159	56	,	,	PUNCT
esrj-49829	159	57	ann	ann	PROPN
esrj-49829	159	58	and	and	CCONJ
esrj-49829	159	59	m5	m5	PROPN
esrj-49829	159	60	tree	tree	NOUN
esrj-49829	159	61	model	model	NOUN
esrj-49829	159	62	were	be	AUX
esrj-49829	159	63	used	use	VERB
esrj-49829	159	64	to	to	PART
esrj-49829	159	65	predict	predict	VERB
esrj-49829	159	66	the	the	DET
esrj-49829	159	67	soil	soil	NOUN
esrj-49829	159	68	temperature	temperature	NOUN
esrj-49829	159	69	at	at	ADP
esrj-49829	159	70	varying	vary	VERB
esrj-49829	159	71	depths	depth	NOUN
esrj-49829	159	72	.	.	PUNCT
esrj-49829	160	1	to	to	PART
esrj-49829	160	2	obtain	obtain	VERB
esrj-49829	160	3	optimal	optimal	ADJ
esrj-49829	160	4	network	network	NOUN
esrj-49829	160	5	architecture	architecture	NOUN
esrj-49829	160	6	in	in	ADP
esrj-49829	160	7	anns	ann	NOUN
esrj-49829	160	8	,	,	PUNCT
esrj-49829	160	9	the	the	DET
esrj-49829	160	10	number	number	NOUN
esrj-49829	160	11	of	of	ADP
esrj-49829	160	12	neurons	neuron	NOUN
esrj-49829	160	13	in	in	ADP
esrj-49829	160	14	the	the	DET
esrj-49829	160	15	hidden	hide	VERB
esrj-49829	160	16	layer	layer	NOUN
esrj-49829	160	17	was	be	AUX
esrj-49829	160	18	determined	determine	VERB
esrj-49829	160	19	by	by	ADP
esrj-49829	160	20	trial	trial	NOUN
esrj-49829	160	21	and	and	CCONJ
esrj-49829	160	22	error	error	NOUN
esrj-49829	160	23	.	.	PUNCT
esrj-49829	161	1	based	base	VERB
esrj-49829	161	2	on	on	ADP
esrj-49829	161	3	the	the	DET
esrj-49829	161	4	number	number	NOUN
esrj-49829	161	5	of	of	ADP
esrj-49829	161	6	input	input	NOUN
esrj-49829	161	7	neurons	neuron	NOUN
esrj-49829	161	8	(	(	PUNCT
esrj-49829	161	9	m	m	NOUN
esrj-49829	161	10	=	=	SYM
esrj-49829	161	11	6	6	NUM
esrj-49829	161	12	input	input	NOUN
esrj-49829	161	13	nodes	node	NOUN
esrj-49829	161	14	are	be	AUX
esrj-49829	161	15	included	include	VERB
esrj-49829	161	16	here	here	ADV
esrj-49829	161	17	)	)	PUNCT
esrj-49829	161	18	,	,	PUNCT
esrj-49829	161	19	the	the	DET
esrj-49829	161	20	number	number	NOUN
esrj-49829	161	21	of	of	ADP
esrj-49829	161	22	hidden	hide	VERB
esrj-49829	161	23	nodes	node	NOUN
esrj-49829	161	24	were	be	AUX
esrj-49829	161	25	varied	varied	ADJ
esrj-49829	161	26	from	from	ADP
esrj-49829	161	27	1	1	NUM
esrj-49829	161	28	to	to	ADP
esrj-49829	161	29	2m+1	2m+1	PROPN
esrj-49829	161	30	to	to	PART
esrj-49829	161	31	find	find	VERB
esrj-49829	161	32	optimal	optimal	ADJ
esrj-49829	161	33	number	number	NOUN
esrj-49829	161	34	of	of	ADP
esrj-49829	161	35	nodes	node	NOUN
esrj-49829	161	36	in	in	ADP
esrj-49829	161	37	hidden	hidden	ADJ
esrj-49829	161	38	layer	layer	NOUN
esrj-49829	161	39	.	.	PUNCT
esrj-49829	162	1	the	the	DET
esrj-49829	162	2	network	network	NOUN
esrj-49829	162	3	was	be	AUX
esrj-49829	162	4	trained	train	VERB
esrj-49829	162	5	for	for	ADP
esrj-49829	162	6	300	300	NUM
esrj-49829	162	7	epochs	epoch	NOUN
esrj-49829	162	8	using	use	VERB
esrj-49829	162	9	the	the	DET
esrj-49829	162	10	levenberg	levenberg	PROPN
esrj-49829	162	11	-	-	PUNCT
esrj-49829	162	12	marquardt	marquardt	PROPN
esrj-49829	162	13	training	training	NOUN
esrj-49829	162	14	algorithm	algorithm	NOUN
esrj-49829	162	15	.	.	PUNCT
esrj-49829	163	1	based	base	VERB
esrj-49829	163	2	on	on	ADP
esrj-49829	163	3	a	a	DET
esrj-49829	163	4	trial	trial	NOUN
esrj-49829	163	5	and	and	CCONJ
esrj-49829	163	6	error	error	NOUN
esrj-49829	163	7	process	process	NOUN
esrj-49829	163	8	(	(	PUNCT
esrj-49829	163	9	by	by	ADP
esrj-49829	163	10	exploring	explore	VERB
esrj-49829	163	11	1	1	NUM
esrj-49829	163	12	to	to	ADP
esrj-49829	163	13	2m+1	2m+1	PROPN
esrj-49829	163	14	hidden	hide	VERB
esrj-49829	163	15	neurons	neuron	NOUN
esrj-49829	163	16	)	)	PUNCT
esrj-49829	163	17	,	,	PUNCT
esrj-49829	163	18	hidden	hide	VERB
esrj-49829	163	19	layers	layer	NOUN
esrj-49829	163	20	with	with	ADP
esrj-49829	163	21	3	3	NUM
esrj-49829	163	22	,	,	PUNCT
esrj-49829	163	23	4	4	NUM
esrj-49829	163	24	,	,	PUNCT
esrj-49829	163	25	5	5	NUM
esrj-49829	163	26	,	,	PUNCT
esrj-49829	163	27	4	4	NUM
esrj-49829	163	28	,	,	PUNCT
esrj-49829	163	29	5	5	NUM
esrj-49829	163	30	and	and	CCONJ
esrj-49829	163	31	3	3	NUM
esrj-49829	163	32	neurons	neuron	NOUN
esrj-49829	163	33	were	be	AUX
esrj-49829	163	34	found	find	VERB
esrj-49829	163	35	to	to	PART
esrj-49829	163	36	be	be	AUX
esrj-49829	163	37	optimal	optimal	ADJ
esrj-49829	163	38	for	for	ADP
esrj-49829	163	39	the	the	DET
esrj-49829	163	40	5	5	NUM
esrj-49829	163	41	,	,	PUNCT
esrj-49829	163	42	10	10	NUM
esrj-49829	163	43	,	,	PUNCT
esrj-49829	163	44	20	20	NUM
esrj-49829	163	45	,	,	PUNCT
esrj-49829	163	46	30	30	NUM
esrj-49829	163	47	,	,	PUNCT
esrj-49829	163	48	50	50	NUM
esrj-49829	163	49	and	and	CCONJ
esrj-49829	163	50	100	100	NUM
esrj-49829	163	51	cm	cm	NOUN
esrj-49829	163	52	soil	soil	NOUN
esrj-49829	163	53	depths	depth	NOUN
esrj-49829	163	54	,	,	PUNCT
esrj-49829	163	55	respectively	respectively	ADV
esrj-49829	163	56	(	(	PUNCT
esrj-49829	163	57	see	see	VERB
esrj-49829	163	58	table	table	NOUN
esrj-49829	163	59	2	2	NUM
esrj-49829	163	60	for	for	ADP
esrj-49829	163	61	the	the	DET
esrj-49829	163	62	10	10	NUM
esrj-49829	163	63	and	and	CCONJ
esrj-49829	163	64	50	50	NUM
esrj-49829	163	65	cm	cm	NOUN
esrj-49829	163	66	soil	soil	NOUN
esrj-49829	163	67	depths	depth	NOUN
esrj-49829	163	68	)	)	PUNCT
esrj-49829	163	69	.	.	PUNCT
esrj-49829	164	1	table	table	NOUN
esrj-49829	164	2	2	2	NUM
esrj-49829	164	3	.	.	NUM
esrj-49829	164	4	tested	test	VERB
esrj-49829	164	5	model	model	NOUN
esrj-49829	164	6	structures	structure	NOUN
esrj-49829	164	7	and	and	CCONJ
esrj-49829	164	8	rmse	rmse	ADJ
esrj-49829	164	9	values	value	NOUN
esrj-49829	164	10	of	of	ADP
esrj-49829	164	11	the	the	DET
esrj-49829	164	12	anns	anns	NOUN
esrj-49829	164	13	models	model	NOUN
esrj-49829	164	14	.	.	PUNCT
esrj-49829	165	1	the	the	DET
esrj-49829	165	2	parameters	parameter	NOUN
esrj-49829	165	3	of	of	ADP
esrj-49829	165	4	the	the	DET
esrj-49829	165	5	subtractive	subtractive	NOUN
esrj-49829	165	6	clustering	cluster	VERB
esrj-49829	165	7	algorithm	algorithm	NOUN
esrj-49829	165	8	should	should	AUX
esrj-49829	165	9	be	be	AUX
esrj-49829	165	10	specified	specify	VERB
esrj-49829	165	11	in	in	ADP
esrj-49829	165	12	anfis	anfis	ADJ
esrj-49829	165	13	models	model	NOUN
esrj-49829	165	14	to	to	PART
esrj-49829	165	15	predict	predict	VERB
esrj-49829	165	16	soil	soil	NOUN
esrj-49829	165	17	temperatures	temperature	NOUN
esrj-49829	165	18	at	at	ADP
esrj-49829	165	19	various	various	ADJ
esrj-49829	165	20	depths	depth	NOUN
esrj-49829	165	21	.	.	PUNCT
esrj-49829	166	1	the	the	DET
esrj-49829	166	2	clustering	cluster	VERB
esrj-49829	166	3	radius	radius	NOUN
esrj-49829	166	4	(	(	PUNCT
esrj-49829	166	5	ra	ra	NOUN
esrj-49829	166	6	)	)	PUNCT
esrj-49829	166	7	is	be	AUX
esrj-49829	166	8	the	the	DET
esrj-49829	166	9	most	most	ADV
esrj-49829	166	10	important	important	ADJ
esrj-49829	166	11	parameter	parameter	NOUN
esrj-49829	166	12	in	in	ADP
esrj-49829	166	13	the	the	DET
esrj-49829	166	14	subtractive	subtractive	NOUN
esrj-49829	166	15	clustering	cluster	VERB
esrj-49829	166	16	algorithm	algorithm	NOUN
esrj-49829	166	17	and	and	CCONJ
esrj-49829	166	18	is	be	AUX
esrj-49829	166	19	optimally	optimally	ADV
esrj-49829	166	20	determined	determine	VERB
esrj-49829	166	21	through	through	ADP
esrj-49829	166	22	a	a	DET
esrj-49829	166	23	trial	trial	NOUN
esrj-49829	166	24	-	-	PUNCT
esrj-49829	166	25	and	and	CCONJ
esrj-49829	166	26	-	-	PUNCT
esrj-49829	166	27	error	error	NOUN
esrj-49829	166	28	procedure	procedure	NOUN
esrj-49829	166	29	.	.	PUNCT
esrj-49829	167	1	the	the	DET
esrj-49829	167	2	values	value	NOUN
esrj-49829	167	3	of	of	ADP
esrj-49829	167	4	ra	ra	PROPN
esrj-49829	167	5	ranging	range	VERB
esrj-49829	167	6	between	between	ADP
esrj-49829	167	7	0.2	0.2	NUM
esrj-49829	167	8	and	and	CCONJ
esrj-49829	167	9	1	1	NUM
esrj-49829	167	10	with	with	ADP
esrj-49829	167	11	a	a	DET
esrj-49829	167	12	step	step	NOUN
esrj-49829	167	13	size	size	NOUN
esrj-49829	167	14	of	of	ADP
esrj-49829	167	15	0.01	0.01	NUM
esrj-49829	167	16	were	be	AUX
esrj-49829	167	17	examined	examine	VERB
esrj-49829	167	18	to	to	PART
esrj-49829	167	19	minimize	minimize	VERB
esrj-49829	167	20	the	the	DET
esrj-49829	167	21	root	root	NOUN
esrj-49829	167	22	mean	mean	VERB
esrj-49829	167	23	squared	square	VERB
esrj-49829	167	24	error	error	NOUN
esrj-49829	167	25	(	(	PUNCT
esrj-49829	167	26	table	table	NOUN
esrj-49829	167	27	3	3	NUM
esrj-49829	167	28	)	)	PUNCT
esrj-49829	167	29	.	.	PUNCT
esrj-49829	168	1	for	for	ADP
esrj-49829	168	2	the	the	DET
esrj-49829	168	3	values	value	NOUN
esrj-49829	168	4	below	below	ADP
esrj-49829	168	5	0.2	0.2	NUM
esrj-49829	168	6	,	,	PUNCT
esrj-49829	168	7	network	network	NOUN
esrj-49829	168	8	training	training	NOUN
esrj-49829	168	9	was	be	AUX
esrj-49829	168	10	found	find	VERB
esrj-49829	168	11	to	to	PART
esrj-49829	168	12	be	be	AUX
esrj-49829	168	13	difficult	difficult	ADJ
esrj-49829	168	14	and	and	CCONJ
esrj-49829	168	15	for	for	ADP
esrj-49829	168	16	the	the	DET
esrj-49829	168	17	values	value	NOUN
esrj-49829	168	18	above	above	ADP
esrj-49829	168	19	1	1	NUM
esrj-49829	168	20	,	,	PUNCT
esrj-49829	168	21	no	no	DET
esrj-49829	168	22	remarkable	remarkable	ADJ
esrj-49829	168	23	change	change	NOUN
esrj-49829	168	24	in	in	ADP
esrj-49829	168	25	rmse	rmse	ADJ
esrj-49829	168	26	values	value	NOUN
esrj-49829	168	27	was	be	AUX
esrj-49829	168	28	achieved	achieve	VERB
esrj-49829	168	29	.	.	PUNCT
esrj-49829	169	1	clustering	cluster	VERB
esrj-49829	169	2	radius	radius	NOUN
esrj-49829	169	3	rb	rb	NOUN
esrj-49829	169	4	was	be	AUX
esrj-49829	169	5	selected	select	VERB
esrj-49829	169	6	as	as	ADP
esrj-49829	169	7	1.5ra	1.5ra	NUM
esrj-49829	169	8	and	and	CCONJ
esrj-49829	169	9	default	default	NOUN
esrj-49829	169	10	values	value	NOUN
esrj-49829	169	11	of	of	ADP
esrj-49829	169	12	the	the	DET
esrj-49829	169	13	other	other	ADJ
esrj-49829	169	14	parameters	parameter	NOUN
esrj-49829	169	15	given	give	VERB
esrj-49829	169	16	in	in	ADP
esrj-49829	169	17	the	the	DET
esrj-49829	169	18	matlab	matlab	NOUN
esrj-49829	169	19	were	be	AUX
esrj-49829	169	20	used	use	VERB
esrj-49829	169	21	.	.	PUNCT
esrj-49829	170	1	table	table	NOUN
esrj-49829	170	2	3	3	NUM
esrj-49829	170	3	.	.	PUNCT
esrj-49829	170	4	resulting	result	VERB
esrj-49829	170	5	model	model	NOUN
esrj-49829	170	6	structures	structure	NOUN
esrj-49829	170	7	and	and	CCONJ
esrj-49829	170	8	rmse	rmse	ADJ
esrj-49829	170	9	values	value	NOUN
esrj-49829	170	10	of	of	ADP
esrj-49829	170	11	the	the	DET
esrj-49829	170	12	anfis	anfis	PROPN
esrj-49829	170	13	models	model	NOUN
esrj-49829	170	14	.	.	PUNCT
esrj-49829	171	1	*	*	PUNCT
esrj-49829	171	2	shows	show	VERB
esrj-49829	171	3	optimal	optimal	ADJ
esrj-49829	171	4	clustering	clustering	ADJ
esrj-49829	171	5	radius	radius	NOUN
esrj-49829	171	6	(	(	PUNCT
esrj-49829	171	7	ra	ra	NOUN
esrj-49829	171	8	)	)	PUNCT
esrj-49829	171	9	gaussian	gaussian	ADJ
esrj-49829	171	10	membership	membership	NOUN
esrj-49829	171	11	functions	function	NOUN
esrj-49829	171	12	were	be	AUX
esrj-49829	171	13	used	use	VERB
esrj-49829	171	14	for	for	ADP
esrj-49829	171	15	each	each	DET
esrj-49829	171	16	fuzzy	fuzzy	ADJ
esrj-49829	171	17	set	set	VERB
esrj-49829	171	18	in	in	ADP
esrj-49829	171	19	the	the	DET
esrj-49829	171	20	fuzzy	fuzzy	ADJ
esrj-49829	171	21	system	system	NOUN
esrj-49829	171	22	.	.	PUNCT
esrj-49829	172	1	the	the	DET
esrj-49829	172	2	number	number	NOUN
esrj-49829	172	3	of	of	ADP
esrj-49829	172	4	membership	membership	NOUN
esrj-49829	172	5	functions	function	NOUN
esrj-49829	172	6	and	and	CCONJ
esrj-49829	172	7	fuzzy	fuzzy	ADJ
esrj-49829	172	8	rules	rule	NOUN
esrj-49829	172	9	required	require	VERB
esrj-49829	172	10	for	for	ADP
esrj-49829	172	11	a	a	DET
esrj-49829	172	12	particular	particular	ADJ
esrj-49829	172	13	anfis	anfis	ADJ
esrj-49829	172	14	model	model	NOUN
esrj-49829	172	15	were	be	AUX
esrj-49829	172	16	determined	determine	VERB
esrj-49829	172	17	through	through	ADP
esrj-49829	172	18	the	the	DET
esrj-49829	172	19	subtractive	subtractive	NOUN
esrj-49829	172	20	clustering	cluster	VERB
esrj-49829	172	21	algorithm	algorithm	NOUN
esrj-49829	172	22	.	.	PUNCT
esrj-49829	173	1	parameters	parameter	NOUN
esrj-49829	173	2	of	of	ADP
esrj-49829	173	3	the	the	DET
esrj-49829	173	4	gaussian	gaussian	ADJ
esrj-49829	173	5	membership	membership	NOUN
esrj-49829	173	6	function	function	NOUN
esrj-49829	173	7	were	be	AUX
esrj-49829	173	8	optimally	optimally	ADV
esrj-49829	173	9	determined	determine	VERB
esrj-49829	173	10	using	use	VERB
esrj-49829	173	11	the	the	DET
esrj-49829	173	12	hybrid	hybrid	ADJ
esrj-49829	173	13	learning	learning	NOUN
esrj-49829	173	14	algorithm	algorithm	NOUN
esrj-49829	173	15	.	.	PUNCT
esrj-49829	174	1	each	each	DET
esrj-49829	174	2	anfis	anfis	PROPN
esrj-49829	174	3	model	model	NOUN
esrj-49829	174	4	was	be	AUX
esrj-49829	174	5	trained	train	VERB
esrj-49829	174	6	for	for	ADP
esrj-49829	174	7	100	100	NUM
esrj-49829	174	8	epochs	epoch	NOUN
esrj-49829	174	9	.	.	PUNCT
esrj-49829	175	1	the	the	DET
esrj-49829	175	2	test	test	NOUN
esrj-49829	175	3	results	result	NOUN
esrj-49829	175	4	of	of	ADP
esrj-49829	175	5	the	the	DET
esrj-49829	175	6	anns	ann	NOUN
esrj-49829	175	7	,	,	PUNCT
esrj-49829	175	8	anfis	anfis	ADJ
esrj-49829	175	9	and	and	CCONJ
esrj-49829	175	10	m5	m5	PROPN
esrj-49829	175	11	model	model	NOUN
esrj-49829	175	12	trees	tree	NOUN
esrj-49829	175	13	are	be	AUX
esrj-49829	175	14	compared	compare	VERB
esrj-49829	175	15	with	with	ADP
esrj-49829	175	16	respect	respect	NOUN
esrj-49829	175	17	to	to	ADP
esrj-49829	175	18	r2	r2	PROPN
esrj-49829	175	19	and	and	CCONJ
esrj-49829	175	20	rmse	rmse	NOUN
esrj-49829	175	21	in	in	ADP
esrj-49829	175	22	table	table	NOUN
esrj-49829	175	23	4	4	NUM
esrj-49829	175	24	.	.	PUNCT
esrj-49829	175	25	table	table	NOUN
esrj-49829	175	26	4	4	NUM
esrj-49829	175	27	.	.	PUNCT
esrj-49829	176	1	the	the	DET
esrj-49829	176	2	test	test	NOUN
esrj-49829	176	3	results	result	NOUN
esrj-49829	176	4	of	of	ADP
esrj-49829	176	5	the	the	DET
esrj-49829	176	6	optimal	optimal	ADJ
esrj-49829	176	7	anns	ann	NOUN
esrj-49829	176	8	,	,	PUNCT
esrj-49829	176	9	anfis	anfis	ADJ
esrj-49829	176	10	and	and	CCONJ
esrj-49829	176	11	m5	m5	PROPN
esrj-49829	176	12	model	model	NOUN
esrj-49829	176	13	trees	tree	NOUN
esrj-49829	176	14	.	.	PUNCT
esrj-49829	177	1	results	result	NOUN
esrj-49829	177	2	indicates	indicate	VERB
esrj-49829	177	3	a	a	DET
esrj-49829	177	4	high	high	ADJ
esrj-49829	177	5	correlation	correlation	NOUN
esrj-49829	177	6	(	(	PUNCT
esrj-49829	177	7	r2	r2	NOUN
esrj-49829	177	8	value	value	NOUN
esrj-49829	177	9	changes	change	NOUN
esrj-49829	177	10	from	from	ADP
esrj-49829	177	11	0.98	0.98	NUM
esrj-49829	177	12	at	at	ADP
esrj-49829	177	13	5	5	NUM
esrj-49829	177	14	cm	cm	NOUN
esrj-49829	177	15	depth	depth	NOUN
esrj-49829	177	16	to	to	ADP
esrj-49829	177	17	0.80	0.80	NUM
esrj-49829	177	18	at	at	ADP
esrj-49829	177	19	100	100	NUM
esrj-49829	177	20	cm	cm	NUM
esrj-49829	177	21	depth	depth	NOUN
esrj-49829	177	22	)	)	PUNCT
esrj-49829	177	23	between	between	ADP
esrj-49829	177	24	the	the	DET
esrj-49829	177	25	actual	actual	ADJ
esrj-49829	177	26	and	and	CCONJ
esrj-49829	177	27	predicted	predict	VERB
esrj-49829	177	28	soil	soil	NOUN
esrj-49829	177	29	temperatures	temperature	NOUN
esrj-49829	177	30	suggesting	suggest	VERB
esrj-49829	177	31	that	that	SCONJ
esrj-49829	177	32	all	all	DET
esrj-49829	177	33	three	three	NUM
esrj-49829	177	34	models	model	NOUN
esrj-49829	177	35	achieved	achieve	VERB
esrj-49829	177	36	acceptable	acceptable	ADJ
esrj-49829	177	37	results	result	NOUN
esrj-49829	177	38	in	in	ADP
esrj-49829	177	39	predicting	predict	VERB
esrj-49829	177	40	the	the	DET
esrj-49829	177	41	soil	soil	NOUN
esrj-49829	177	42	temperatures	temperature	NOUN
esrj-49829	177	43	at	at	ADP
esrj-49829	177	44	varying	vary	VERB
esrj-49829	177	45	depths	depth	NOUN
esrj-49829	177	46	.	.	PUNCT
esrj-49829	178	1	time	time	NOUN
esrj-49829	178	2	variation	variation	NOUN
esrj-49829	178	3	and	and	CCONJ
esrj-49829	178	4	scatterplots	scatterplot	NOUN
esrj-49829	178	5	of	of	ADP
esrj-49829	178	6	the	the	DET
esrj-49829	178	7	test	test	NOUN
esrj-49829	178	8	results	result	NOUN
esrj-49829	178	9	obtained	obtain	VERB
esrj-49829	178	10	by	by	ADP
esrj-49829	178	11	m5	m5	PROPN
esrj-49829	178	12	tree	tree	NOUN
esrj-49829	178	13	model	model	NOUN
esrj-49829	178	14	,	,	PUNCT
esrj-49829	178	15	ann	ann	PROPN
esrj-49829	178	16	and	and	CCONJ
esrj-49829	178	17	anfis	anfis	PROPN
esrj-49829	178	18	models	model	NOUN
esrj-49829	178	19	are	be	AUX
esrj-49829	178	20	illustrated	illustrate	VERB
esrj-49829	178	21	in	in	ADP
esrj-49829	178	22	figures	figure	NOUN
esrj-49829	178	23	4	4	NUM
esrj-49829	178	24	-	-	SYM
esrj-49829	178	25	6	6	NUM
esrj-49829	178	26	.	.	NOUN
esrj-49829	178	27	90	90	NUM
esrj-49829	178	28	m.	m.	NOUN
esrj-49829	178	29	taghi	taghi	PROPN
esrj-49829	178	30	sattari	sattari	NOUN
esrj-49829	178	31	,	,	PUNCT
esrj-49829	178	32	esmaeel	esmaeel	NOUN
esrj-49829	178	33	dodangeh	dodangeh	NOUN
esrj-49829	178	34	,	,	PUNCT
esrj-49829	179	1	john	john	PROPN
esrj-49829	179	2	abraham	abraham	PROPN
esrj-49829	179	3	plot	plot	NOUN
esrj-49829	179	4	of	of	ADP
esrj-49829	179	5	observed	observe	VERB
esrj-49829	179	6	and	and	CCONJ
esrj-49829	179	7	predicted	predict	VERB
esrj-49829	179	8	soil	soil	NOUN
esrj-49829	179	9	temperature	temperature	NOUN
esrj-49829	179	10	values	value	NOUN
esrj-49829	179	11	suggests	suggest	VERB
esrj-49829	179	12	that	that	SCONJ
esrj-49829	179	13	all	all	DET
esrj-49829	179	14	three	three	NUM
esrj-49829	179	15	models	model	NOUN
esrj-49829	179	16	are	be	AUX
esrj-49829	179	17	suitable	suitable	ADJ
esrj-49829	179	18	in	in	ADP
esrj-49829	179	19	modeling	model	VERB
esrj-49829	179	20	soil	soil	NOUN
esrj-49829	179	21	temperatures	temperature	NOUN
esrj-49829	179	22	.	.	PUNCT
esrj-49829	180	1	figure	figure	VERB
esrj-49829	180	2	5	5	NUM
esrj-49829	180	3	.	.	PUNCT
esrj-49829	181	1	performance	performance	NOUN
esrj-49829	181	2	of	of	ADP
esrj-49829	181	3	ann	ann	PROPN
esrj-49829	181	4	model	model	NOUN
esrj-49829	181	5	at	at	ADP
esrj-49829	181	6	soil	soil	NOUN
esrj-49829	181	7	depths	depth	NOUN
esrj-49829	181	8	;	;	PUNCT
esrj-49829	181	9	5	5	NUM
esrj-49829	181	10	cm	cm	NOUN
esrj-49829	181	11	and	and	CCONJ
esrj-49829	181	12	100	100	NUM
esrj-49829	181	13	cm	cm	NOUN
esrj-49829	181	14	,	,	PUNCT
esrj-49829	181	15	with	with	ADP
esrj-49829	181	16	test	test	NOUN
esrj-49829	181	17	data	datum	NOUN
esrj-49829	181	18	set	set	VERB
esrj-49829	181	19	91estimation	91estimation	NUM
esrj-49829	181	20	of	of	ADP
esrj-49829	181	21	daily	daily	ADJ
esrj-49829	181	22	soil	soil	NOUN
esrj-49829	181	23	temperature	temperature	NOUN
esrj-49829	181	24	via	via	ADP
esrj-49829	181	25	data	datum	NOUN
esrj-49829	181	26	mining	mining	NOUN
esrj-49829	181	27	techniques	technique	NOUN
esrj-49829	181	28	in	in	ADP
esrj-49829	181	29	semi	semi	ADJ
esrj-49829	181	30	-	-	ADJ
esrj-49829	181	31	arid	arid	ADJ
esrj-49829	181	32	climate	climate	NOUN
esrj-49829	181	33	conditions	condition	NOUN
esrj-49829	181	34	as	as	SCONJ
esrj-49829	181	35	can	can	AUX
esrj-49829	181	36	be	be	AUX
esrj-49829	181	37	seen	see	VERB
esrj-49829	181	38	from	from	ADP
esrj-49829	181	39	the	the	DET
esrj-49829	181	40	table	table	NOUN
esrj-49829	181	41	4	4	NUM
esrj-49829	181	42	,	,	PUNCT
esrj-49829	181	43	the	the	DET
esrj-49829	181	44	rmse	rmse	ADJ
esrj-49829	181	45	values	value	NOUN
esrj-49829	181	46	also	also	ADV
esrj-49829	181	47	increase	increase	VERB
esrj-49829	181	48	with	with	ADP
esrj-49829	181	49	the	the	DET
esrj-49829	181	50	increasing	increase	VERB
esrj-49829	181	51	depth	depth	NOUN
esrj-49829	181	52	.	.	PUNCT
esrj-49829	182	1	the	the	DET
esrj-49829	182	2	lowest	low	ADJ
esrj-49829	182	3	and	and	CCONJ
esrj-49829	182	4	highest	high	ADJ
esrj-49829	182	5	rmse	rmse	ADJ
esrj-49829	182	6	values	value	NOUN
esrj-49829	182	7	achieved	achieve	VERB
esrj-49829	182	8	by	by	ADP
esrj-49829	182	9	the	the	DET
esrj-49829	182	10	anfis	anfis	PROPN
esrj-49829	182	11	,	,	PUNCT
esrj-49829	182	12	ann	ann	PROPN
esrj-49829	182	13	and	and	CCONJ
esrj-49829	182	14	m5	m5	PROPN
esrj-49829	182	15	tree	tree	NOUN
esrj-49829	182	16	model	model	NOUN
esrj-49829	182	17	are	be	AUX
esrj-49829	182	18	1.86	1.86	NUM
esrj-49829	182	19	,	,	PUNCT
esrj-49829	182	20	1.95	1.95	NUM
esrj-49829	182	21	,	,	PUNCT
esrj-49829	182	22	1.97	1.97	NUM
esrj-49829	182	23	(	(	PUNCT
esrj-49829	182	24	observed	observe	VERB
esrj-49829	182	25	at	at	ADP
esrj-49829	182	26	5	5	NUM
esrj-49829	182	27	cm	cm	NOUN
esrj-49829	182	28	soil	soil	NOUN
esrj-49829	182	29	depths	depth	NOUN
esrj-49829	182	30	)	)	PUNCT
esrj-49829	182	31	and	and	CCONJ
esrj-49829	182	32	2.39	2.39	NUM
esrj-49829	182	33	,	,	PUNCT
esrj-49829	182	34	2.44	2.44	NUM
esrj-49829	182	35	,	,	PUNCT
esrj-49829	182	36	2.37	2.37	NUM
esrj-49829	182	37	(	(	PUNCT
esrj-49829	182	38	observed	observe	VERB
esrj-49829	182	39	at	at	ADP
esrj-49829	182	40	100	100	NUM
esrj-49829	182	41	cm	cm	NOUN
esrj-49829	182	42	soil	soil	NOUN
esrj-49829	182	43	depths	depth	NOUN
esrj-49829	182	44	)	)	PUNCT
esrj-49829	182	45	respectively	respectively	ADV
esrj-49829	182	46	.	.	PUNCT
esrj-49829	183	1	the	the	DET
esrj-49829	183	2	plots	plot	NOUN
esrj-49829	183	3	of	of	ADP
esrj-49829	183	4	actual	actual	ADJ
esrj-49829	183	5	and	and	CCONJ
esrj-49829	183	6	predicted	predict	VERB
esrj-49829	183	7	soil	soil	NOUN
esrj-49829	183	8	temperature	temperature	NOUN
esrj-49829	183	9	in	in	ADP
esrj-49829	183	10	figures	figure	NOUN
esrj-49829	183	11	4	4	NUM
esrj-49829	183	12	,	,	PUNCT
esrj-49829	183	13	5	5	NUM
esrj-49829	183	14	and	and	CCONJ
esrj-49829	183	15	6	6	NUM
esrj-49829	183	16	as	as	ADV
esrj-49829	183	17	well	well	ADV
esrj-49829	183	18	as	as	ADP
esrj-49829	183	19	table	table	NOUN
esrj-49829	183	20	4	4	NUM
esrj-49829	183	21	suggest	suggest	VERB
esrj-49829	183	22	a	a	DET
esrj-49829	183	23	slightly	slightly	ADV
esrj-49829	183	24	improved	improve	VERB
esrj-49829	183	25	performance	performance	NOUN
esrj-49829	183	26	by	by	ADP
esrj-49829	183	27	anfis	anfis	PROPN
esrj-49829	183	28	in	in	ADP
esrj-49829	183	29	predicting	predict	VERB
esrj-49829	183	30	soil	soil	NOUN
esrj-49829	183	31	temperature	temperature	NOUN
esrj-49829	183	32	in	in	ADP
esrj-49829	183	33	comparison	comparison	NOUN
esrj-49829	183	34	to	to	ADP
esrj-49829	183	35	ann	ann	PROPN
esrj-49829	183	36	and	and	CCONJ
esrj-49829	183	37	m5	m5	PROPN
esrj-49829	183	38	models	model	NOUN
esrj-49829	183	39	except	except	SCONJ
esrj-49829	183	40	at	at	ADP
esrj-49829	183	41	the	the	DET
esrj-49829	183	42	depth	depth	NOUN
esrj-49829	183	43	of	of	ADP
esrj-49829	183	44	100	100	NUM
esrj-49829	183	45	cm	cm	NOUN
esrj-49829	183	46	.	.	PUNCT
esrj-49829	184	1	a	a	DET
esrj-49829	184	2	comparison	comparison	NOUN
esrj-49829	184	3	of	of	ADP
esrj-49829	184	4	results	result	NOUN
esrj-49829	184	5	from	from	ADP
esrj-49829	184	6	table	table	NOUN
esrj-49829	184	7	4	4	NUM
esrj-49829	184	8	also	also	ADV
esrj-49829	184	9	suggests	suggest	VERB
esrj-49829	184	10	that	that	SCONJ
esrj-49829	184	11	both	both	CCONJ
esrj-49829	184	12	the	the	DET
esrj-49829	184	13	ann	ann	PROPN
esrj-49829	184	14	and	and	CCONJ
esrj-49829	184	15	anfis	anfis	PROPN
esrj-49829	184	16	perform	perform	VERB
esrj-49829	184	17	better	well	ADV
esrj-49829	184	18	than	than	ADP
esrj-49829	184	19	the	the	DET
esrj-49829	184	20	m5	m5	PROPN
esrj-49829	184	21	model	model	NOUN
esrj-49829	184	22	tree	tree	NOUN
esrj-49829	184	23	approach	approach	NOUN
esrj-49829	184	24	in	in	ADP
esrj-49829	184	25	predicting	predict	VERB
esrj-49829	184	26	the	the	DET
esrj-49829	184	27	surface	surface	NOUN
esrj-49829	184	28	soil	soil	NOUN
esrj-49829	184	29	temperature	temperature	NOUN
esrj-49829	184	30	,	,	PUNCT
esrj-49829	184	31	however	however	ADV
esrj-49829	184	32	at	at	ADP
esrj-49829	184	33	depth	depth	NOUN
esrj-49829	184	34	of	of	ADP
esrj-49829	184	35	100	100	NUM
esrj-49829	184	36	cm	cm	NOUN
esrj-49829	184	37	,	,	PUNCT
esrj-49829	184	38	m5	m5	NOUN
esrj-49829	184	39	tree	tree	NOUN
esrj-49829	184	40	model	model	NOUN
esrj-49829	184	41	seems	seem	VERB
esrj-49829	184	42	to	to	PART
esrj-49829	184	43	be	be	AUX
esrj-49829	184	44	most	most	ADV
esrj-49829	184	45	robust	robust	ADJ
esrj-49829	184	46	.	.	PUNCT
esrj-49829	185	1	figure	figure	NOUN
esrj-49829	185	2	6	6	NUM
esrj-49829	185	3	.	.	PUNCT
esrj-49829	186	1	performance	performance	NOUN
esrj-49829	186	2	of	of	ADP
esrj-49829	186	3	m5	m5	PROPN
esrj-49829	186	4	model	model	NOUN
esrj-49829	186	5	tree	tree	NOUN
esrj-49829	186	6	at	at	ADP
esrj-49829	186	7	soil	soil	NOUN
esrj-49829	186	8	depths	depth	NOUN
esrj-49829	186	9	;	;	PUNCT
esrj-49829	186	10	5	5	NUM
esrj-49829	186	11	cm	cm	NOUN
esrj-49829	186	12	and	and	CCONJ
esrj-49829	186	13	100	100	NUM
esrj-49829	186	14	cm	cm	NOUN
esrj-49829	186	15	,	,	PUNCT
esrj-49829	186	16	with	with	ADP
esrj-49829	186	17	test	test	NOUN
esrj-49829	186	18	data	datum	NOUN
esrj-49829	186	19	set	set	VERB
esrj-49829	186	20	these	these	DET
esrj-49829	186	21	figures	figure	NOUN
esrj-49829	186	22	depict	depict	VERB
esrj-49829	186	23	good	good	ADJ
esrj-49829	186	24	agreement	agreement	NOUN
esrj-49829	186	25	between	between	ADP
esrj-49829	186	26	the	the	DET
esrj-49829	186	27	actual	actual	ADJ
esrj-49829	186	28	and	and	CCONJ
esrj-49829	186	29	predicted	predict	VERB
esrj-49829	186	30	soil	soil	NOUN
esrj-49829	186	31	temperature	temperature	NOUN
esrj-49829	186	32	values	value	NOUN
esrj-49829	186	33	of	of	ADP
esrj-49829	186	34	the	the	DET
esrj-49829	186	35	surface	surface	NOUN
esrj-49829	186	36	layers	layer	NOUN
esrj-49829	186	37	in	in	ADP
esrj-49829	186	38	comparison	comparison	NOUN
esrj-49829	186	39	to	to	ADP
esrj-49829	186	40	the	the	DET
esrj-49829	186	41	layers	layer	NOUN
esrj-49829	186	42	at	at	ADP
esrj-49829	186	43	increasing	increase	VERB
esrj-49829	186	44	depths	depth	NOUN
esrj-49829	186	45	.	.	PUNCT
esrj-49829	187	1	all	all	DET
esrj-49829	187	2	three	three	NUM
esrj-49829	187	3	models	model	NOUN
esrj-49829	187	4	tend	tend	VERB
esrj-49829	187	5	to	to	PART
esrj-49829	187	6	provide	provide	VERB
esrj-49829	187	7	less	less	ADV
esrj-49829	187	8	biased	biased	ADJ
esrj-49829	187	9	estimates	estimate	NOUN
esrj-49829	187	10	for	for	ADP
esrj-49829	187	11	the	the	DET
esrj-49829	187	12	surface	surface	NOUN
esrj-49829	187	13	layers	layer	NOUN
esrj-49829	187	14	in	in	ADP
esrj-49829	187	15	comparison	comparison	NOUN
esrj-49829	187	16	to	to	ADP
esrj-49829	187	17	the	the	DET
esrj-49829	187	18	predictions	prediction	NOUN
esrj-49829	187	19	for	for	ADP
esrj-49829	187	20	deeper	deep	ADJ
esrj-49829	187	21	layers	layer	NOUN
esrj-49829	187	22	(	(	PUNCT
esrj-49829	187	23	figure	figure	NOUN
esrj-49829	187	24	7	7	NUM
esrj-49829	187	25	)	)	PUNCT
esrj-49829	187	26	.	.	PUNCT
esrj-49829	188	1	figure	figure	VERB
esrj-49829	188	2	7	7	NUM
esrj-49829	188	3	.	.	PUNCT
esrj-49829	188	4	rmse	rmse	ADJ
esrj-49829	188	5	values	value	NOUN
esrj-49829	188	6	of	of	ADP
esrj-49829	188	7	the	the	DET
esrj-49829	188	8	evaluated	evaluate	VERB
esrj-49829	188	9	models	model	NOUN
esrj-49829	188	10	for	for	ADP
esrj-49829	188	11	different	different	ADJ
esrj-49829	188	12	soil	soil	NOUN
esrj-49829	188	13	depths	depth	VERB
esrj-49829	188	14	analysis	analysis	NOUN
esrj-49829	188	15	of	of	ADP
esrj-49829	188	16	predicted	predict	VERB
esrj-49829	188	17	soil	soil	NOUN
esrj-49829	188	18	temperature	temperature	NOUN
esrj-49829	188	19	values	value	NOUN
esrj-49829	188	20	by	by	ADP
esrj-49829	188	21	different	different	ADJ
esrj-49829	188	22	modeling	modeling	NOUN
esrj-49829	188	23	approaches	approach	NOUN
esrj-49829	188	24	(	(	PUNCT
esrj-49829	188	25	figure	figure	NOUN
esrj-49829	188	26	7	7	NUM
esrj-49829	188	27	)	)	PUNCT
esrj-49829	188	28	shows	show	VERB
esrj-49829	188	29	increasing	increase	VERB
esrj-49829	188	30	values	value	NOUN
esrj-49829	188	31	of	of	ADP
esrj-49829	188	32	rmse	rmse	NOUN
esrj-49829	188	33	with	with	ADP
esrj-49829	188	34	increasing	increase	VERB
esrj-49829	188	35	soil	soil	NOUN
esrj-49829	188	36	depth	depth	NOUN
esrj-49829	188	37	,	,	PUNCT
esrj-49829	188	38	thus	thus	ADV
esrj-49829	188	39	indicates	indicate	VERB
esrj-49829	188	40	that	that	SCONJ
esrj-49829	188	41	the	the	DET
esrj-49829	188	42	soil	soil	NOUN
esrj-49829	188	43	temperatures	temperature	NOUN
esrj-49829	188	44	predicted	predict	VERB
esrj-49829	188	45	by	by	ADP
esrj-49829	188	46	anfis	anfis	PROPN
esrj-49829	188	47	,	,	PUNCT
esrj-49829	188	48	ann	ann	PROPN
esrj-49829	188	49	and	and	CCONJ
esrj-49829	188	50	m5	m5	PROPN
esrj-49829	188	51	models	model	NOUN
esrj-49829	188	52	are	be	AUX
esrj-49829	188	53	more	more	ADV
esrj-49829	188	54	accurate	accurate	ADJ
esrj-49829	188	55	for	for	ADP
esrj-49829	188	56	the	the	DET
esrj-49829	188	57	surface	surface	NOUN
esrj-49829	188	58	temperatures	temperature	NOUN
esrj-49829	188	59	.	.	PUNCT
esrj-49829	189	1	the	the	DET
esrj-49829	189	2	reason	reason	NOUN
esrj-49829	189	3	for	for	ADP
esrj-49829	189	4	increasing	increase	VERB
esrj-49829	189	5	rmse	rmse	ADJ
esrj-49829	189	6	value	value	NOUN
esrj-49829	189	7	with	with	ADP
esrj-49829	189	8	increasing	increase	VERB
esrj-49829	189	9	depth	depth	NOUN
esrj-49829	189	10	may	may	AUX
esrj-49829	189	11	be	be	AUX
esrj-49829	189	12	mainly	mainly	ADV
esrj-49829	189	13	due	due	ADJ
esrj-49829	189	14	to	to	ADP
esrj-49829	189	15	the	the	DET
esrj-49829	189	16	reduction	reduction	NOUN
esrj-49829	189	17	in	in	ADP
esrj-49829	189	18	correlation	correlation	NOUN
esrj-49829	189	19	between	between	ADP
esrj-49829	189	20	the	the	DET
esrj-49829	189	21	input	input	NOUN
esrj-49829	189	22	climatic	climatic	ADJ
esrj-49829	189	23	variables	variable	NOUN
esrj-49829	189	24	and	and	CCONJ
esrj-49829	189	25	the	the	DET
esrj-49829	189	26	soil	soil	NOUN
esrj-49829	189	27	temperature	temperature	NOUN
esrj-49829	189	28	at	at	ADP
esrj-49829	189	29	increasing	increase	VERB
esrj-49829	189	30	depth	depth	NOUN
esrj-49829	189	31	.	.	PUNCT
esrj-49829	190	1	the	the	DET
esrj-49829	190	2	superior	superior	ADJ
esrj-49829	190	3	performance	performance	NOUN
esrj-49829	190	4	of	of	ADP
esrj-49829	190	5	the	the	DET
esrj-49829	190	6	anfis	anfis	PROPN
esrj-49829	190	7	and	and	CCONJ
esrj-49829	190	8	ann	ann	PROPN
esrj-49829	190	9	in	in	ADP
esrj-49829	190	10	modeling	model	VERB
esrj-49829	190	11	the	the	DET
esrj-49829	190	12	surface	surface	NOUN
esrj-49829	190	13	soil	soil	NOUN
esrj-49829	190	14	temperatures	temperature	NOUN
esrj-49829	190	15	may	may	AUX
esrj-49829	190	16	be	be	AUX
esrj-49829	190	17	attributed	attribute	VERB
esrj-49829	190	18	to	to	ADP
esrj-49829	190	19	the	the	DET
esrj-49829	190	20	increase	increase	NOUN
esrj-49829	190	21	in	in	ADP
esrj-49829	190	22	the	the	DET
esrj-49829	190	23	network	network	NOUN
esrj-49829	190	24	nonlinearity	nonlinearity	NOUN
esrj-49829	190	25	and	and	CCONJ
esrj-49829	190	26	the	the	DET
esrj-49829	190	27	better	well	ADJ
esrj-49829	190	28	correlation	correlation	NOUN
esrj-49829	190	29	between	between	ADP
esrj-49829	190	30	input	input	NOUN
esrj-49829	190	31	and	and	CCONJ
esrj-49829	190	32	output	output	NOUN
esrj-49829	190	33	values	value	NOUN
esrj-49829	190	34	(	(	PUNCT
esrj-49829	190	35	gao	gao	PROPN
esrj-49829	190	36	et	et	PROPN
esrj-49829	190	37	al	al	PROPN
esrj-49829	190	38	.	.	PROPN
esrj-49829	190	39	,	,	PUNCT
esrj-49829	190	40	2007	2007	NUM
esrj-49829	190	41	)	)	PUNCT
esrj-49829	190	42	.	.	PUNCT
esrj-49829	191	1	moreover	moreover	ADV
esrj-49829	191	2	it	it	PRON
esrj-49829	191	3	may	may	AUX
esrj-49829	191	4	be	be	AUX
esrj-49829	191	5	noted	note	VERB
esrj-49829	191	6	that	that	SCONJ
esrj-49829	191	7	a	a	DET
esrj-49829	191	8	trial	trial	NOUN
esrj-49829	191	9	-	-	PUNCT
esrj-49829	191	10	anderror	anderror	NOUN
esrj-49829	191	11	procedure	procedure	NOUN
esrj-49829	191	12	has	have	VERB
esrj-49829	191	13	to	to	PART
esrj-49829	191	14	be	be	AUX
esrj-49829	191	15	adopted	adopt	VERB
esrj-49829	191	16	to	to	PART
esrj-49829	191	17	select	select	VERB
esrj-49829	191	18	suitable	suitable	ADJ
esrj-49829	191	19	user	user	NOUN
esrj-49829	191	20	-	-	PUNCT
esrj-49829	191	21	defined	define	VERB
esrj-49829	191	22	parameters	parameter	NOUN
esrj-49829	191	23	for	for	ADP
esrj-49829	191	24	the	the	DET
esrj-49829	191	25	ann	ann	PROPN
esrj-49829	191	26	model	model	NOUN
esrj-49829	191	27	;	;	PUNCT
esrj-49829	191	28	this	this	DET
esrj-49829	191	29	process	process	NOUN
esrj-49829	191	30	is	be	AUX
esrj-49829	191	31	time	time	NOUN
esrj-49829	191	32	consuming	consume	VERB
esrj-49829	191	33	.	.	PUNCT
esrj-49829	192	1	on	on	ADP
esrj-49829	192	2	the	the	DET
esrj-49829	192	3	other	other	ADJ
esrj-49829	192	4	hand	hand	NOUN
esrj-49829	192	5	,	,	PUNCT
esrj-49829	192	6	no	no	DET
esrj-49829	192	7	such	such	ADJ
esrj-49829	192	8	procedure	procedure	NOUN
esrj-49829	192	9	is	be	AUX
esrj-49829	192	10	required	require	VERB
esrj-49829	192	11	to	to	PART
esrj-49829	192	12	develop	develop	VERB
esrj-49829	192	13	an	an	DET
esrj-49829	192	14	anfis	anfis	ADJ
esrj-49829	192	15	model	model	NOUN
esrj-49829	192	16	.	.	PUNCT
esrj-49829	193	1	although	although	SCONJ
esrj-49829	193	2	error	error	NOUN
esrj-49829	193	3	analysis	analysis	NOUN
esrj-49829	193	4	of	of	ADP
esrj-49829	193	5	predicted	predict	VERB
esrj-49829	193	6	values	value	NOUN
esrj-49829	193	7	confirmed	confirm	VERB
esrj-49829	193	8	better	well	ADJ
esrj-49829	193	9	performance	performance	NOUN
esrj-49829	193	10	for	for	ADP
esrj-49829	193	11	anfis	anfis	PROPN
esrj-49829	193	12	and	and	CCONJ
esrj-49829	193	13	ann	ann	PROPN
esrj-49829	193	14	approaches	approach	VERB
esrj-49829	193	15	for	for	ADP
esrj-49829	193	16	the	the	DET
esrj-49829	193	17	surface	surface	NOUN
esrj-49829	193	18	soil	soil	NOUN
esrj-49829	193	19	temperatures	temperature	NOUN
esrj-49829	193	20	,	,	PUNCT
esrj-49829	193	21	the	the	DET
esrj-49829	193	22	m5	m5	PROPN
esrj-49829	193	23	model	model	NOUN
esrj-49829	193	24	tree	tree	NOUN
esrj-49829	193	25	had	have	VERB
esrj-49829	193	26	slightly	slightly	ADV
esrj-49829	193	27	better	well	ADJ
esrj-49829	193	28	results	result	NOUN
esrj-49829	193	29	with	with	ADP
esrj-49829	193	30	increasing	increase	VERB
esrj-49829	193	31	depth	depth	NOUN
esrj-49829	193	32	.	.	PUNCT
esrj-49829	194	1	it	it	PRON
esrj-49829	194	2	is	be	AUX
esrj-49829	194	3	worth	worth	ADJ
esrj-49829	194	4	noting	note	VERB
esrj-49829	194	5	that	that	SCONJ
esrj-49829	194	6	m5	m5	PROPN
esrj-49829	194	7	model	model	NOUN
esrj-49829	194	8	trees	tree	NOUN
esrj-49829	194	9	being	be	AUX
esrj-49829	194	10	analogous	analogous	ADJ
esrj-49829	194	11	to	to	PART
esrj-49829	194	12	piecewise	piecewise	VERB
esrj-49829	194	13	linear	linear	NOUN
esrj-49829	194	14	functions	function	NOUN
esrj-49829	194	15	,	,	PUNCT
esrj-49829	194	16	provides	provide	VERB
esrj-49829	194	17	a	a	DET
esrj-49829	194	18	simple	simple	ADJ
esrj-49829	194	19	linear	linear	NOUN
esrj-49829	194	20	relation	relation	NOUN
esrj-49829	194	21	to	to	PART
esrj-49829	194	22	model	model	VERB
esrj-49829	194	23	the	the	DET
esrj-49829	194	24	soil	soil	NOUN
esrj-49829	194	25	temperatures	temperature	NOUN
esrj-49829	194	26	,	,	PUNCT
esrj-49829	194	27	as	as	SCONJ
esrj-49829	194	28	described	describe	VERB
esrj-49829	194	29	mathematically	mathematically	ADV
esrj-49829	194	30	in	in	ADP
esrj-49829	194	31	figure	figure	NOUN
esrj-49829	194	32	8	8	NUM
esrj-49829	194	33	.	.	X
esrj-49829	194	34	92	92	NUM
esrj-49829	194	35	m.	m.	NOUN
esrj-49829	194	36	taghi	taghi	PROPN
esrj-49829	194	37	sattari	sattari	NOUN
esrj-49829	194	38	,	,	PUNCT
esrj-49829	194	39	esmaeel	esmaeel	NOUN
esrj-49829	194	40	dodangeh	dodangeh	NOUN
esrj-49829	194	41	,	,	PUNCT
esrj-49829	194	42	john	john	PROPN
esrj-49829	194	43	abraham	abraham	PROPN
esrj-49829	194	44	figure	figure	VERB
esrj-49829	194	45	8	8	NUM
esrj-49829	194	46	.	.	PUNCT
esrj-49829	195	1	linear	linear	ADJ
esrj-49829	195	2	functions	function	NOUN
esrj-49829	195	3	for	for	ADP
esrj-49829	195	4	predicting	predict	VERB
esrj-49829	195	5	temperature	temperature	NOUN
esrj-49829	195	6	at	at	ADP
esrj-49829	195	7	5	5	NUM
esrj-49829	195	8	cm	cm	NOUN
esrj-49829	195	9	soil	soil	NOUN
esrj-49829	195	10	depth	depth	NOUN
esrj-49829	195	11	based	base	VERB
esrj-49829	195	12	on	on	ADP
esrj-49829	195	13	m5	m5	PROPN
esrj-49829	195	14	tree	tree	NOUN
esrj-49829	195	15	model	model	NOUN
esrj-49829	195	16	.	.	PUNCT
esrj-49829	196	1	4	4	X
esrj-49829	196	2	.	.	X
esrj-49829	196	3	conclusions	conclusion	NOUN
esrj-49829	196	4	the	the	DET
esrj-49829	196	5	anfis	anfis	PROPN
esrj-49829	196	6	,	,	PUNCT
esrj-49829	196	7	anns	anns	NOUN
esrj-49829	196	8	and	and	CCONJ
esrj-49829	196	9	m5	m5	PROPN
esrj-49829	196	10	tree	tree	NOUN
esrj-49829	196	11	model	model	NOUN
esrj-49829	196	12	approaches	approach	NOUN
esrj-49829	196	13	have	have	AUX
esrj-49829	196	14	been	be	AUX
esrj-49829	196	15	used	use	VERB
esrj-49829	196	16	to	to	PART
esrj-49829	196	17	predict	predict	VERB
esrj-49829	196	18	the	the	DET
esrj-49829	196	19	daily	daily	ADJ
esrj-49829	196	20	soil	soil	NOUN
esrj-49829	196	21	temperature	temperature	NOUN
esrj-49829	196	22	with	with	ADP
esrj-49829	196	23	increasing	increase	VERB
esrj-49829	196	24	depth	depth	NOUN
esrj-49829	196	25	in	in	ADP
esrj-49829	196	26	this	this	DET
esrj-49829	196	27	study	study	NOUN
esrj-49829	196	28	.	.	PUNCT
esrj-49829	197	1	the	the	DET
esrj-49829	197	2	results	result	NOUN
esrj-49829	197	3	presented	present	VERB
esrj-49829	197	4	here	here	ADV
esrj-49829	197	5	are	be	AUX
esrj-49829	197	6	quite	quite	ADV
esrj-49829	197	7	encouraging	encouraging	ADJ
esrj-49829	197	8	and	and	CCONJ
esrj-49829	197	9	confirm	confirm	VERB
esrj-49829	197	10	that	that	SCONJ
esrj-49829	197	11	all	all	DET
esrj-49829	197	12	three	three	NUM
esrj-49829	197	13	approaches	approach	NOUN
esrj-49829	197	14	work	work	VERB
esrj-49829	197	15	well	well	ADV
esrj-49829	197	16	in	in	ADP
esrj-49829	197	17	predicting	predict	VERB
esrj-49829	197	18	soil	soil	NOUN
esrj-49829	197	19	temperatures	temperature	NOUN
esrj-49829	197	20	at	at	ADP
esrj-49829	197	21	different	different	ADJ
esrj-49829	197	22	depths	depth	NOUN
esrj-49829	197	23	.	.	PUNCT
esrj-49829	198	1	a	a	DET
esrj-49829	198	2	comparison	comparison	NOUN
esrj-49829	198	3	among	among	ADP
esrj-49829	198	4	the	the	DET
esrj-49829	198	5	models	model	NOUN
esrj-49829	198	6	indicates	indicate	VERB
esrj-49829	198	7	that	that	SCONJ
esrj-49829	198	8	the	the	DET
esrj-49829	198	9	anfis	anfis	PROPN
esrj-49829	198	10	model	model	NOUN
esrj-49829	198	11	provides	provide	VERB
esrj-49829	198	12	more	more	ADV
esrj-49829	198	13	accurate	accurate	ADJ
esrj-49829	198	14	estimates	estimate	NOUN
esrj-49829	198	15	of	of	ADP
esrj-49829	198	16	soil	soil	NOUN
esrj-49829	198	17	temperature	temperature	NOUN
esrj-49829	198	18	than	than	ADP
esrj-49829	198	19	the	the	DET
esrj-49829	198	20	anns	anns	NOUN
esrj-49829	198	21	and	and	CCONJ
esrj-49829	198	22	m5	m5	PROPN
esrj-49829	198	23	tree	tree	NOUN
esrj-49829	198	24	model	model	NOUN
esrj-49829	198	25	.	.	PUNCT
esrj-49829	199	1	the	the	DET
esrj-49829	199	2	results	result	NOUN
esrj-49829	199	3	also	also	ADV
esrj-49829	199	4	suggests	suggest	VERB
esrj-49829	199	5	that	that	SCONJ
esrj-49829	199	6	both	both	CCONJ
esrj-49829	199	7	ann	ann	PROPN
esrj-49829	199	8	and	and	CCONJ
esrj-49829	199	9	m5	m5	PROPN
esrj-49829	199	10	tree	tree	NOUN
esrj-49829	199	11	model	model	NOUN
esrj-49829	199	12	approaches	approach	NOUN
esrj-49829	199	13	work	work	VERB
esrj-49829	199	14	well	well	ADV
esrj-49829	199	15	in	in	ADP
esrj-49829	199	16	predicting	predict	VERB
esrj-49829	199	17	daily	daily	ADJ
esrj-49829	199	18	soil	soil	NOUN
esrj-49829	199	19	temperatures	temperature	NOUN
esrj-49829	199	20	,	,	PUNCT
esrj-49829	199	21	however	however	ADV
esrj-49829	199	22	,	,	PUNCT
esrj-49829	199	23	m5	m5	PROPN
esrj-49829	199	24	tree	tree	NOUN
esrj-49829	199	25	model	model	NOUN
esrj-49829	199	26	has	have	VERB
esrj-49829	199	27	simple	simple	ADJ
esrj-49829	199	28	linear	linear	ADJ
esrj-49829	199	29	relations	relation	NOUN
esrj-49829	199	30	that	that	PRON
esrj-49829	199	31	can	can	AUX
esrj-49829	199	32	be	be	AUX
esrj-49829	199	33	easily	easily	ADV
esrj-49829	199	34	used	use	VERB
esrj-49829	199	35	to	to	PART
esrj-49829	199	36	predict	predict	VERB
esrj-49829	199	37	the	the	DET
esrj-49829	199	38	daily	daily	ADJ
esrj-49829	199	39	soil	soil	NOUN
esrj-49829	199	40	temperature	temperature	NOUN
esrj-49829	199	41	data	datum	NOUN
esrj-49829	199	42	by	by	ADP
esrj-49829	199	43	field	field	NOUN
esrj-49829	199	44	engineers	engineer	NOUN
esrj-49829	199	45	.	.	PUNCT
esrj-49829	200	1	error	error	NOUN
esrj-49829	200	2	analysis	analysis	NOUN
esrj-49829	200	3	of	of	ADP
esrj-49829	200	4	temperature	temperature	NOUN
esrj-49829	200	5	predictions	prediction	NOUN
esrj-49829	200	6	at	at	ADP
esrj-49829	200	7	different	different	ADJ
esrj-49829	200	8	soil	soil	NOUN
esrj-49829	200	9	depths	depth	NOUN
esrj-49829	200	10	indicates	indicate	VERB
esrj-49829	200	11	that	that	SCONJ
esrj-49829	200	12	all	all	DET
esrj-49829	200	13	three	three	NUM
esrj-49829	200	14	models	model	NOUN
esrj-49829	200	15	perform	perform	VERB
esrj-49829	200	16	well	well	ADV
esrj-49829	200	17	in	in	ADP
esrj-49829	200	18	predicting	predict	VERB
esrj-49829	200	19	surface	surface	NOUN
esrj-49829	200	20	soil	soil	NOUN
esrj-49829	200	21	temperature	temperature	NOUN
esrj-49829	200	22	data	datum	NOUN
esrj-49829	200	23	rather	rather	ADV
esrj-49829	200	24	than	than	ADP
esrj-49829	200	25	at	at	ADP
esrj-49829	200	26	deeper	deep	ADJ
esrj-49829	200	27	depths	depth	NOUN
esrj-49829	200	28	.	.	PUNCT
esrj-49829	201	1	the	the	DET
esrj-49829	201	2	reason	reason	NOUN
esrj-49829	201	3	behind	behind	ADP
esrj-49829	201	4	this	this	PRON
esrj-49829	201	5	may	may	AUX
esrj-49829	201	6	be	be	AUX
esrj-49829	201	7	the	the	DET
esrj-49829	201	8	fact	fact	NOUN
esrj-49829	201	9	that	that	SCONJ
esrj-49829	201	10	there	there	PRON
esrj-49829	201	11	is	be	VERB
esrj-49829	201	12	a	a	DET
esrj-49829	201	13	strong	strong	ADJ
esrj-49829	201	14	relationship	relationship	NOUN
esrj-49829	201	15	between	between	ADP
esrj-49829	201	16	climatic	climatic	ADJ
esrj-49829	201	17	parameters	parameter	NOUN
esrj-49829	201	18	and	and	CCONJ
esrj-49829	201	19	surface	surface	NOUN
esrj-49829	201	20	soil	soil	NOUN
esrj-49829	201	21	temperature	temperature	NOUN
esrj-49829	201	22	.	.	PUNCT
esrj-49829	202	1	the	the	DET
esrj-49829	202	2	results	result	NOUN
esrj-49829	202	3	of	of	ADP
esrj-49829	202	4	the	the	DET
esrj-49829	202	5	present	present	ADJ
esrj-49829	202	6	study	study	NOUN
esrj-49829	202	7	demonstrate	demonstrate	VERB
esrj-49829	202	8	that	that	SCONJ
esrj-49829	202	9	the	the	DET
esrj-49829	202	10	proposed	propose	VERB
esrj-49829	202	11	anfis	anfis	PROPN
esrj-49829	202	12	model	model	NOUN
esrj-49829	202	13	is	be	AUX
esrj-49829	202	14	quite	quite	ADV
esrj-49829	202	15	efficient	efficient	ADJ
esrj-49829	202	16	in	in	ADP
esrj-49829	202	17	predicting	predict	VERB
esrj-49829	202	18	soil	soil	NOUN
esrj-49829	202	19	temperature	temperature	NOUN
esrj-49829	202	20	for	for	ADP
esrj-49829	202	21	the	the	DET
esrj-49829	202	22	surface	surface	NOUN
esrj-49829	202	23	layers	layer	NOUN
esrj-49829	202	24	however	however	ADV
esrj-49829	202	25	further	further	ADJ
esrj-49829	202	26	investigation	investigation	NOUN
esrj-49829	202	27	is	be	AUX
esrj-49829	202	28	needed	need	VERB
esrj-49829	202	29	with	with	ADP
esrj-49829	202	30	different	different	ADJ
esrj-49829	202	31	data	datum	NOUN
esrj-49829	202	32	sets	set	NOUN
esrj-49829	202	33	to	to	PART
esrj-49829	202	34	compare	compare	VERB
esrj-49829	202	35	proposed	propose	VERB
esrj-49829	202	36	approach	approach	NOUN
esrj-49829	202	37	and	and	CCONJ
esrj-49829	202	38	other	other	ADJ
esrj-49829	202	39	mathematical	mathematical	ADJ
esrj-49829	202	40	methods	method	NOUN
esrj-49829	202	41	such	such	ADJ
esrj-49829	202	42	as	as	ADP
esrj-49829	202	43	time	time	NOUN
esrj-49829	202	44	series	series	PROPN
esrj-49829	202	45	modeling	modeling	NOUN
esrj-49829	202	46	to	to	PART
esrj-49829	202	47	model	model	VERB
esrj-49829	202	48	soil	soil	NOUN
esrj-49829	202	49	temperatures	temperature	NOUN
esrj-49829	202	50	in	in	ADP
esrj-49829	202	51	deeper	deep	ADJ
esrj-49829	202	52	layers	layer	NOUN
esrj-49829	202	53	.	.	PUNCT
esrj-49829	203	1	5	5	X
esrj-49829	203	2	.	.	X
esrj-49829	203	3	references	reference	NOUN
esrj-49829	203	4	adnan	adnan	PROPN
esrj-49829	203	5	,	,	PUNCT
esrj-49829	203	6	r.	r.	PROPN
esrj-49829	203	7	m.	m.	PROPN
esrj-49829	203	8	,	,	PUNCT
esrj-49829	203	9	yuan	yuan	PROPN
esrj-49829	203	10	,	,	PUNCT
esrj-49829	203	11	x.	x.	PROPN
esrj-49829	203	12	,	,	PUNCT
esrj-49829	203	13	kisi	kisi	PROPN
esrj-49829	203	14	,	,	PUNCT
esrj-49829	203	15	o.	o.	PROPN
esrj-49829	203	16	,	,	PUNCT
esrj-49829	203	17	&	&	CCONJ
esrj-49829	203	18	anam	anam	PROPN
esrj-49829	203	19	,	,	PUNCT
esrj-49829	203	20	r.	r.	PROPN
esrj-49829	203	21	(	(	PUNCT
esrj-49829	203	22	2017	2017	NUM
esrj-49829	203	23	)	)	PUNCT
esrj-49829	203	24	.	.	PUNCT
esrj-49829	204	1	improving	improve	VERB
esrj-49829	204	2	accuracy	accuracy	NOUN
esrj-49829	204	3	of	of	ADP
esrj-49829	204	4	river	river	NOUN
esrj-49829	204	5	floe	floe	NOUN
esrj-49829	204	6	forecasting	forecasting	NOUN
esrj-49829	204	7	using	use	VERB
esrj-49829	204	8	lssvr	lssvr	NOUN
esrj-49829	204	9	with	with	ADP
esrj-49829	204	10	gravitational	gravitational	ADJ
esrj-49829	204	11	search	search	NOUN
esrj-49829	204	12	algorithm	algorithm	NOUN
esrj-49829	204	13	.	.	PUNCT
esrj-49829	205	1	advances	advance	NOUN
esrj-49829	205	2	in	in	ADP
esrj-49829	205	3	meteorology	meteorology	NOUN
esrj-49829	205	4	.	.	PUNCT
esrj-49829	206	1	doi.org/10.1155/2017/2391621	doi.org/10.1155/2017/2391621	PROPN
esrj-49829	206	2	.	.	PUNCT
esrj-49829	207	1	bhattacharya	bhattacharya	PROPN
esrj-49829	207	2	,	,	PUNCT
esrj-49829	207	3	b.	b.	PROPN
esrj-49829	207	4	,	,	PUNCT
esrj-49829	207	5	&	&	CCONJ
esrj-49829	207	6	solomatine	solomatine	PROPN
esrj-49829	207	7	,	,	PUNCT
esrj-49829	207	8	d.	d.	PROPN
esrj-49829	207	9	p.	p.	PROPN
esrj-49829	207	10	(	(	PUNCT
esrj-49829	207	11	2005	2005	NUM
esrj-49829	207	12	)	)	PUNCT
esrj-49829	207	13	.	.	PUNCT
esrj-49829	208	1	neural	neural	ADJ
esrj-49829	208	2	networks	network	NOUN
esrj-49829	208	3	and	and	CCONJ
esrj-49829	208	4	m5	m5	PROPN
esrj-49829	208	5	model	model	NOUN
esrj-49829	208	6	trees	tree	NOUN
esrj-49829	208	7	in	in	ADP
esrj-49829	208	8	modeling	model	VERB
esrj-49829	208	9	water	water	NOUN
esrj-49829	208	10	level	level	NOUN
esrj-49829	208	11	–	–	PUNCT
esrj-49829	208	12	discharge	discharge	NOUN
esrj-49829	208	13	relationship	relationship	NOUN
esrj-49829	208	14	.	.	PUNCT
esrj-49829	209	1	neurocomputing	neurocomputing	NOUN
esrj-49829	209	2	,	,	PUNCT
esrj-49829	209	3	63	63	NUM
esrj-49829	209	4	,	,	PUNCT
esrj-49829	209	5	381–396	381–396	NUM
esrj-49829	209	6	.	.	PUNCT
esrj-49829	210	1	biabani	biabani	PROPN
esrj-49829	210	2	,	,	PUNCT
esrj-49829	210	3	r.	r.	PROPN
esrj-49829	210	4	,	,	PUNCT
esrj-49829	210	5	meftah	meftah	PROPN
esrj-49829	210	6	halaghi	halaghi	PROPN
esrj-49829	210	7	,	,	PUNCT
esrj-49829	210	8	m.	m.	NOUN
esrj-49829	210	9	,	,	PUNCT
esrj-49829	210	10	&	&	CCONJ
esrj-49829	210	11	ghorbani	ghorbani	PROPN
esrj-49829	210	12	,	,	PUNCT
esrj-49829	210	13	k.	k.	PROPN
esrj-49829	210	14	h.	h.	PROPN
esrj-49829	210	15	(	(	PUNCT
esrj-49829	210	16	2016	2016	NUM
esrj-49829	210	17	)	)	PUNCT
esrj-49829	210	18	.	.	PUNCT
esrj-49829	211	1	m5	m5	NOUN
esrj-49829	211	2	model	model	NOUN
esrj-49829	211	3	tree	tree	NOUN
esrj-49829	211	4	to	to	PART
esrj-49829	211	5	predict	predict	VERB
esrj-49829	211	6	temporal	temporal	ADJ
esrj-49829	211	7	evolution	evolution	NOUN
esrj-49829	211	8	of	of	ADP
esrj-49829	211	9	clear	clear	ADJ
esrj-49829	211	10	water	water	NOUN
esrj-49829	211	11	abutment	abutment	NOUN
esrj-49829	211	12	scour	scour	NOUN
esrj-49829	211	13	.	.	PUNCT
esrj-49829	212	1	journal	journal	NOUN
esrj-49829	212	2	of	of	ADP
esrj-49829	212	3	geology	geology	NOUN
esrj-49829	212	4	,	,	PUNCT
esrj-49829	212	5	6	6	NUM
esrj-49829	212	6	,	,	PUNCT
esrj-49829	212	7	1045	1045	NUM
esrj-49829	212	8	-	-	SYM
esrj-49829	212	9	1054	1054	NUM
esrj-49829	212	10	.	.	PUNCT
esrj-49829	213	1	bonng	bonng	ADJ
esrj-49829	213	2	,	,	PUNCT
esrj-49829	213	3	b.	b.	PROPN
esrj-49829	213	4	&	&	CCONJ
esrj-49829	213	5	vanclev	vanclev	PROPN
esrj-49829	213	6	,	,	PUNCT
esrj-49829	213	7	k.	k.	PROPN
esrj-49829	213	8	(	(	PUNCT
esrj-49829	213	9	1992	1992	NUM
esrj-49829	213	10	)	)	PUNCT
esrj-49829	213	11	.	.	PUNCT
esrj-49829	214	1	soil	soil	NOUN
esrj-49829	214	2	temperature	temperature	NOUN
esrj-49829	214	3	nitrogen	nitrogen	NOUN
esrj-49829	214	4	mineralization	mineralization	NOUN
esrj-49829	214	5	and	and	CCONJ
esrj-49829	214	6	carbon	carbon	NOUN
esrj-49829	214	7	source	source	NOUN
esrj-49829	214	8	-	-	PUNCT
esrj-49829	214	9	sink	sink	NOUN
esrj-49829	214	10	relationships	relationship	NOUN
esrj-49829	214	11	in	in	ADP
esrj-49829	214	12	boreal	boreal	ADJ
esrj-49829	214	13	forests	forest	NOUN
esrj-49829	214	14	.	.	PUNCT
esrj-49829	215	1	canadian	canadian	ADJ
esrj-49829	215	2	journal	journal	PROPN
esrj-49829	215	3	of	of	ADP
esrj-49829	215	4	forest	forest	NOUN
esrj-49829	215	5	research	research	NOUN
esrj-49829	215	6	,	,	PUNCT
esrj-49829	215	7	22	22	NUM
esrj-49829	215	8	,	,	PUNCT
esrj-49829	215	9	629	629	NUM
esrj-49829	215	10	-	-	SYM
esrj-49829	215	11	639	639	NUM
esrj-49829	215	12	.	.	PUNCT
esrj-49829	216	1	chio	chio	PROPN
esrj-49829	216	2	,	,	PUNCT
esrj-49829	216	3	j.	j.	PROPN
esrj-49829	216	4	s.	s.	PROPN
esrj-49829	216	5	,	,	PUNCT
esrj-49829	216	6	fermanian	fermanian	NOUN
esrj-49829	216	7	,	,	PUNCT
esrj-49829	216	8	t.	t.	PROPN
esrj-49829	216	9	w.	w.	PROPN
esrj-49829	216	10	,	,	PUNCT
esrj-49829	216	11	wehner	wehner	PROPN
esrj-49829	216	12	,	,	PUNCT
esrj-49829	216	13	d.	d.	PROPN
esrj-49829	216	14	j.	j.	PROPN
esrj-49829	216	15	&	&	CCONJ
esrj-49829	216	16	spomer	spomer	PROPN
esrj-49829	216	17	,	,	PUNCT
esrj-49829	216	18	l.	l.	PROPN
esrj-49829	216	19	a.	a.	PROPN
esrj-49829	216	20	(	(	PUNCT
esrj-49829	216	21	1988	1988	NUM
esrj-49829	216	22	)	)	PUNCT
esrj-49829	216	23	.	.	PUNCT
esrj-49829	217	1	effect	effect	NOUN
esrj-49829	217	2	of	of	ADP
esrj-49829	217	3	temperature	temperature	NOUN
esrj-49829	217	4	,	,	PUNCT
esrj-49829	217	5	moisture	moisture	NOUN
esrj-49829	217	6	and	and	CCONJ
esrj-49829	217	7	soil	soil	NOUN
esrj-49829	217	8	texture	texture	NOUN
esrj-49829	217	9	on	on	ADP
esrj-49829	217	10	dcpa	dcpa	ADJ
esrj-49829	217	11	degradation	degradation	NOUN
esrj-49829	217	12	.	.	PUNCT
esrj-49829	218	1	agronomy	agronomy	NOUN
esrj-49829	218	2	journal	journal	NOUN
esrj-49829	218	3	,	,	PUNCT
esrj-49829	218	4	80	80	NUM
esrj-49829	218	5	,	,	PUNCT
esrj-49829	218	6	108	108	NUM
esrj-49829	218	7	-	-	SYM
esrj-49829	218	8	111	111	NUM
esrj-49829	218	9	.	.	PUNCT
esrj-49829	219	1	chiu	chiu	PROPN
esrj-49829	219	2	,	,	PUNCT
esrj-49829	219	3	s.	s.	PROPN
esrj-49829	219	4	(	(	PUNCT
esrj-49829	219	5	1994	1994	NUM
esrj-49829	219	6	)	)	PUNCT
esrj-49829	219	7	.	.	PUNCT
esrj-49829	220	1	fuzzy	fuzzy	ADJ
esrj-49829	220	2	model	model	NOUN
esrj-49829	220	3	identification	identification	NOUN
esrj-49829	220	4	based	base	VERB
esrj-49829	220	5	on	on	ADP
esrj-49829	220	6	cluster	cluster	NOUN
esrj-49829	220	7	estimation	estimation	NOUN
esrj-49829	220	8	.	.	PUNCT
esrj-49829	221	1	journal	journal	NOUN
esrj-49829	221	2	of	of	ADP
esrj-49829	221	3	intelligent	intelligent	ADJ
esrj-49829	221	4	and	and	CCONJ
esrj-49829	221	5	fuzzy	fuzzy	ADJ
esrj-49829	221	6	systems	system	NOUN
esrj-49829	221	7	,	,	PUNCT
esrj-49829	221	8	2	2	NUM
esrj-49829	221	9	,	,	PUNCT
esrj-49829	221	10	762–767	762–767	NUM
esrj-49829	221	11	.	.	PUNCT
esrj-49829	222	1	elshorbagy	elshorbagy	PROPN
esrj-49829	222	2	,	,	PUNCT
esrj-49829	222	3	a.	a.	NOUN
esrj-49829	222	4	,	,	PUNCT
esrj-49829	222	5	&	&	CCONJ
esrj-49829	222	6	parasuraman	parasuraman	PROPN
esrj-49829	222	7	,	,	PUNCT
esrj-49829	222	8	k.	k.	PROPN
esrj-49829	222	9	(	(	PUNCT
esrj-49829	222	10	2008	2008	NUM
esrj-49829	222	11	)	)	PUNCT
esrj-49829	222	12	.	.	PUNCT
esrj-49829	223	1	on	on	ADP
esrj-49829	223	2	the	the	DET
esrj-49829	223	3	relevance	relevance	NOUN
esrj-49829	223	4	of	of	ADP
esrj-49829	223	5	using	use	VERB
esrj-49829	223	6	artificial	artificial	ADJ
esrj-49829	223	7	neural	neural	ADJ
esrj-49829	223	8	networks	network	NOUN
esrj-49829	223	9	for	for	ADP
esrj-49829	223	10	estimating	estimate	VERB
esrj-49829	223	11	soil	soil	NOUN
esrj-49829	223	12	moisture	moisture	NOUN
esrj-49829	223	13	content	content	NOUN
esrj-49829	223	14	.	.	PUNCT
esrj-49829	224	1	journal	journal	NOUN
esrj-49829	224	2	of	of	ADP
esrj-49829	224	3	hydrology	hydrology	NOUN
esrj-49829	224	4	,	,	PUNCT
esrj-49829	224	5	362	362	NUM
esrj-49829	224	6	,	,	PUNCT
esrj-49829	224	7	1	1	NUM
esrj-49829	224	8	–	–	SYM
esrj-49829	224	9	18	18	NUM
esrj-49829	224	10	.	.	X
esrj-49829	224	11	esmaeilzadeh	esmaeilzadeh	NOUN
esrj-49829	224	12	,	,	PUNCT
esrj-49829	224	13	b.	b.	PROPN
esrj-49829	224	14	,	,	PUNCT
esrj-49829	224	15	&	&	CCONJ
esrj-49829	224	16	sattari	sattari	PROPN
esrj-49829	224	17	,	,	PUNCT
esrj-49829	224	18	m.	m.	NOUN
esrj-49829	224	19	t.	t.	PROPN
esrj-49829	224	20	(	(	PUNCT
esrj-49829	224	21	2015	2015	NUM
esrj-49829	224	22	)	)	PUNCT
esrj-49829	224	23	.	.	PUNCT
esrj-49829	225	1	monthly	monthly	ADJ
esrj-49829	225	2	evapotranspiration	evapotranspiration	NOUN
esrj-49829	225	3	modeling	modeling	NOUN
esrj-49829	225	4	using	use	VERB
esrj-49829	225	5	intelligent	intelligent	ADJ
esrj-49829	225	6	systems	system	NOUN
esrj-49829	225	7	in	in	ADP
esrj-49829	225	8	tabriz	tabriz	NOUN
esrj-49829	225	9	,	,	PUNCT
esrj-49829	225	10	iran	iran	PROPN
esrj-49829	225	11	.	.	PUNCT
esrj-49829	226	1	agriculture	agriculture	NOUN
esrj-49829	226	2	science	science	NOUN
esrj-49829	226	3	developments	development	NOUN
esrj-49829	226	4	,	,	PUNCT
esrj-49829	226	5	4(3	4(3	NUM
esrj-49829	226	6	)	)	PUNCT
esrj-49829	226	7	,	,	PUNCT
esrj-49829	226	8	35	35	NUM
esrj-49829	226	9	-	-	SYM
esrj-49829	226	10	40	40	NUM
esrj-49829	226	11	.	.	PUNCT
esrj-49829	227	1	gao	gao	PROPN
esrj-49829	227	2	,	,	PUNCT
esrj-49829	227	3	z.	z.	PROPN
esrj-49829	227	4	,	,	PUNCT
esrj-49829	227	5	bian	bian	PROPN
esrj-49829	227	6	,	,	PUNCT
esrj-49829	227	7	l.	l.	PROPN
esrj-49829	227	8	,	,	PUNCT
esrj-49829	227	9	hu	hu	PROPN
esrj-49829	227	10	,	,	PUNCT
esrj-49829	227	11	y.	y.	PROPN
esrj-49829	227	12	,	,	PUNCT
esrj-49829	227	13	wang	wang	PROPN
esrj-49829	227	14	,	,	PUNCT
esrj-49829	227	15	l.	l.	PROPN
esrj-49829	227	16	&	&	CCONJ
esrj-49829	227	17	fan	fan	PROPN
esrj-49829	227	18	,	,	PUNCT
esrj-49829	227	19	j.	j.	PROPN
esrj-49829	227	20	(	(	PUNCT
esrj-49829	227	21	2007	2007	NUM
esrj-49829	227	22	)	)	PUNCT
esrj-49829	227	23	.	.	PUNCT
esrj-49829	228	1	determination	determination	NOUN
esrj-49829	228	2	of	of	ADP
esrj-49829	228	3	soil	soil	NOUN
esrj-49829	228	4	temperature	temperature	NOUN
esrj-49829	228	5	in	in	ADP
esrj-49829	228	6	an	an	DET
esrj-49829	228	7	arid	arid	NOUN
esrj-49829	228	8	region	region	NOUN
esrj-49829	228	9	.	.	PUNCT
esrj-49829	229	1	journal	journal	PROPN
esrj-49829	229	2	of	of	ADP
esrj-49829	229	3	arid	arid	ADJ
esrj-49829	229	4	environments	environment	NOUN
esrj-49829	229	5	,	,	PUNCT
esrj-49829	229	6	71	71	NUM
esrj-49829	229	7	,	,	PUNCT
esrj-49829	229	8	157	157	NUM
esrj-49829	229	9	-	-	SYM
esrj-49829	229	10	168	168	NUM
esrj-49829	229	11	.	.	PUNCT
esrj-49829	230	1	gaumont	gaumont	NOUN
esrj-49829	230	2	-	-	PUNCT
esrj-49829	230	3	guay	guay	NOUN
esrj-49829	230	4	,	,	PUNCT
esrj-49829	230	5	d.	d.	PROPN
esrj-49829	230	6	,	,	PUNCT
esrj-49829	230	7	black	black	ADJ
esrj-49829	230	8	,	,	PUNCT
esrj-49829	230	9	t.	t.	PROPN
esrj-49829	230	10	a.	a.	PROPN
esrj-49829	230	11	,	,	PUNCT
esrj-49829	230	12	griffis	griffis	PROPN
esrj-49829	230	13	,	,	PUNCT
esrj-49829	230	14	t.	t.	PROPN
esrj-49829	230	15	j.	j.	PROPN
esrj-49829	230	16	,	,	PUNCT
esrj-49829	230	17	barr	barr	PROPN
esrj-49829	230	18	,	,	PUNCT
esrj-49829	230	19	a.	a.	PROPN
esrj-49829	230	20	g.	g.	PROPN
esrj-49829	230	21	,	,	PUNCT
esrj-49829	230	22	jassal	jassal	PROPN
esrj-49829	230	23	,	,	PUNCT
esrj-49829	230	24	r.	r.	PROPN
esrj-49829	230	25	s.	s.	PROPN
esrj-49829	230	26	&	&	CCONJ
esrj-49829	230	27	nesic	nesic	PROPN
esrj-49829	230	28	,	,	PUNCT
esrj-49829	230	29	z.	z.	PROPN
esrj-49829	230	30	(	(	PUNCT
esrj-49829	230	31	2006	2006	NUM
esrj-49829	230	32	)	)	PUNCT
esrj-49829	230	33	.	.	PUNCT
esrj-49829	231	1	interpreting	interpret	VERB
esrj-49829	231	2	the	the	DET
esrj-49829	231	3	dependence	dependence	NOUN
esrj-49829	231	4	of	of	ADP
esrj-49829	231	5	soil	soil	NOUN
esrj-49829	231	6	respiration	respiration	NOUN
esrj-49829	231	7	on	on	ADP
esrj-49829	231	8	soil	soil	NOUN
esrj-49829	231	9	temperature	temperature	NOUN
esrj-49829	231	10	and	and	CCONJ
esrj-49829	231	11	water	water	NOUN
esrj-49829	231	12	content	content	NOUN
esrj-49829	231	13	in	in	ADP
esrj-49829	231	14	a	a	DET
esrj-49829	231	15	boreal	boreal	ADJ
esrj-49829	231	16	aspen	aspen	NOUN
esrj-49829	231	17	stand	stand	NOUN
esrj-49829	231	18	.	.	PUNCT
esrj-49829	232	1	agricultural	agricultural	ADJ
esrj-49829	232	2	and	and	CCONJ
esrj-49829	232	3	forest	forest	NOUN
esrj-49829	232	4	meteorology	meteorology	NOUN
esrj-49829	232	5	,	,	PUNCT
esrj-49829	232	6	140	140	NUM
esrj-49829	232	7	,	,	PUNCT
esrj-49829	232	8	220–235	220–235	NUM
esrj-49829	232	9	.	.	PUNCT
esrj-49829	233	1	hecht	hecht	PROPN
esrj-49829	233	2	-	-	PUNCT
esrj-49829	233	3	nielsen	nielsen	PROPN
esrj-49829	233	4	,	,	PUNCT
esrj-49829	233	5	r.	r.	PROPN
esrj-49829	233	6	(	(	PUNCT
esrj-49829	233	7	1990	1990	NUM
esrj-49829	233	8	)	)	PUNCT
esrj-49829	233	9	.	.	PUNCT
esrj-49829	234	1	neurocomputing	neurocomputing	PROPN
esrj-49829	234	2	.	.	PUNCT
esrj-49829	235	1	addison	addison	PROPN
esrj-49829	235	2	-	-	PUNCT
esrj-49829	235	3	wesley	wesley	PROPN
esrj-49829	235	4	,	,	PUNCT
esrj-49829	235	5	menlo	menlo	NOUN
esrj-49829	235	6	park	park	NOUN
esrj-49829	235	7	,	,	PUNCT
esrj-49829	235	8	ca	ca	PROPN
esrj-49829	235	9	,	,	PUNCT
esrj-49829	235	10	usa	usa	PROPN
esrj-49829	235	11	.	.	PROPN
esrj-49829	235	12	jang	jang	PROPN
esrj-49829	235	13	,	,	PUNCT
esrj-49829	235	14	j.	j.	PROPN
esrj-49829	235	15	s.	s.	PROPN
esrj-49829	235	16	r.	r.	PROPN
esrj-49829	235	17	(	(	PUNCT
esrj-49829	235	18	1993	1993	NUM
esrj-49829	235	19	)	)	PUNCT
esrj-49829	235	20	.	.	PUNCT
esrj-49829	236	1	anfis	anfis	PROPN
esrj-49829	236	2	:	:	PUNCT
esrj-49829	236	3	adaptive	adaptive	ADJ
esrj-49829	236	4	-	-	PUNCT
esrj-49829	236	5	network	network	NOUN
esrj-49829	236	6	-	-	PUNCT
esrj-49829	236	7	based	base	VERB
esrj-49829	236	8	fuzzy	fuzzy	ADJ
esrj-49829	236	9	inference	inference	NOUN
esrj-49829	236	10	system	system	NOUN
esrj-49829	236	11	.	.	PUNCT
esrj-49829	237	1	ieee	ieee	NOUN
esrj-49829	237	2	transactions	transaction	NOUN
esrj-49829	237	3	systems	system	NOUN
esrj-49829	237	4	,	,	PUNCT
esrj-49829	237	5	man	man	NOUN
esrj-49829	237	6	and	and	CCONJ
esrj-49829	237	7	cybernetics	cybernetic	NOUN
esrj-49829	237	8	,	,	PUNCT
esrj-49829	237	9	23(3	23(3	NUM
esrj-49829	237	10	)	)	PUNCT
esrj-49829	237	11	,	,	PUNCT
esrj-49829	237	12	665–685	665–685	NUM
esrj-49829	237	13	.	.	PUNCT
esrj-49829	238	1	kang	kang	PROPN
esrj-49829	238	2	,	,	PUNCT
esrj-49829	238	3	s.	s.	PROPN
esrj-49829	238	4	,	,	PUNCT
esrj-49829	238	5	kim	kim	PROPN
esrj-49829	238	6	,	,	PUNCT
esrj-49829	238	7	s.	s.	PROPN
esrj-49829	238	8	,	,	PUNCT
esrj-49829	238	9	oh	oh	INTJ
esrj-49829	238	10	,	,	PUNCT
esrj-49829	238	11	s.	s.	PROPN
esrj-49829	238	12	&	&	CCONJ
esrj-49829	238	13	lee	lee	PROPN
esrj-49829	238	14	,	,	PUNCT
esrj-49829	238	15	d.	d.	PROPN
esrj-49829	238	16	(	(	PUNCT
esrj-49829	238	17	2000a	2000a	NUM
esrj-49829	238	18	)	)	PUNCT
esrj-49829	238	19	.	.	PUNCT
esrj-49829	239	1	predicting	predict	VERB
esrj-49829	239	2	spatial	spatial	ADJ
esrj-49829	239	3	and	and	CCONJ
esrj-49829	239	4	temporal	temporal	ADJ
esrj-49829	239	5	patterns	pattern	NOUN
esrj-49829	239	6	of	of	ADP
esrj-49829	239	7	soil	soil	NOUN
esrj-49829	239	8	temperature	temperature	NOUN
esrj-49829	239	9	based	base	VERB
esrj-49829	239	10	on	on	ADP
esrj-49829	239	11	topography	topography	NOUN
esrj-49829	239	12	,	,	PUNCT
esrj-49829	239	13	surface	surface	NOUN
esrj-49829	239	14	cover	cover	NOUN
esrj-49829	239	15	and	and	CCONJ
esrj-49829	239	16	air	air	NOUN
esrj-49829	239	17	temperature	temperature	NOUN
esrj-49829	239	18	.	.	PUNCT
esrj-49829	240	1	forest	forest	NOUN
esrj-49829	240	2	ecology	ecology	NOUN
esrj-49829	240	3	and	and	CCONJ
esrj-49829	240	4	management	management	NOUN
esrj-49829	240	5	,	,	PUNCT
esrj-49829	240	6	136	136	NUM
esrj-49829	240	7	,	,	PUNCT
esrj-49829	240	8	173	173	NUM
esrj-49829	240	9	-	-	SYM
esrj-49829	240	10	184	184	NUM
esrj-49829	240	11	.	.	PUNCT
esrj-49829	241	1	lippmann	lippmann	PROPN
esrj-49829	241	2	,	,	PUNCT
esrj-49829	241	3	r.p	r.p	PROPN
esrj-49829	241	4	.	.	PROPN
esrj-49829	241	5	(	(	PUNCT
esrj-49829	241	6	1987	1987	NUM
esrj-49829	241	7	)	)	PUNCT
esrj-49829	241	8	.	.	PUNCT
esrj-49829	242	1	an	an	DET
esrj-49829	242	2	introduction	introduction	NOUN
esrj-49829	242	3	to	to	ADP
esrj-49829	242	4	computing	compute	VERB
esrj-49829	242	5	with	with	ADP
esrj-49829	242	6	neural	neural	ADJ
esrj-49829	242	7	nets	net	NOUN
esrj-49829	242	8	.	.	PUNCT
esrj-49829	243	1	ieee	ieee	PROPN
esrj-49829	243	2	assp	assp	PROPN
esrj-49829	243	3	magazine	magazine	PROPN
esrj-49829	243	4	,	,	PUNCT
esrj-49829	243	5	4–22	4–22	PROPN
esrj-49829	243	6	.	.	PUNCT
esrj-49829	244	1	pal	pal	PROPN
esrj-49829	244	2	,	,	PUNCT
esrj-49829	244	3	m.	m.	NOUN
esrj-49829	244	4	&	&	CCONJ
esrj-49829	244	5	surinder	surinder	PROPN
esrj-49829	244	6	,	,	PUNCT
esrj-49829	244	7	d.	d.	PROPN
esrj-49829	244	8	(	(	PUNCT
esrj-49829	244	9	2009	2009	NUM
esrj-49829	244	10	)	)	PUNCT
esrj-49829	244	11	.	.	PUNCT
esrj-49829	245	1	m5	m5	PROPN
esrj-49829	245	2	model	model	NOUN
esrj-49829	245	3	tree	tree	NOUN
esrj-49829	245	4	based	base	VERB
esrj-49829	245	5	modelling	modelling	NOUN
esrj-49829	245	6	of	of	ADP
esrj-49829	245	7	reference	reference	NOUN
esrj-49829	245	8	evapotranspiration	evapotranspiration	NOUN
esrj-49829	245	9	.	.	PUNCT
esrj-49829	246	1	hydrological	hydrological	ADJ
esrj-49829	246	2	processes	process	NOUN
esrj-49829	246	3	,	,	PUNCT
esrj-49829	246	4	23	23	NUM
esrj-49829	246	5	,	,	PUNCT
esrj-49829	246	6	1437–1443	1437–1443	NUM
esrj-49829	246	7	.	.	PUNCT
esrj-49829	247	1	pal	pal	NOUN
esrj-49829	247	2	,	,	PUNCT
esrj-49829	247	3	m.	m.	NOUN
esrj-49829	247	4	,	,	PUNCT
esrj-49829	247	5	singh	singh	PROPN
esrj-49829	247	6	n.	n.	PROPN
esrj-49829	247	7	k.	k.	PROPN
esrj-49829	247	8	,	,	PUNCT
esrj-49829	247	9	&	&	CCONJ
esrj-49829	247	10	tiwari	tiwari	PROPN
esrj-49829	247	11	,	,	PUNCT
esrj-49829	247	12	n.	n.	PROPN
esrj-49829	247	13	k.	k.	PROPN
esrj-49829	248	1	(	(	PUNCT
esrj-49829	248	2	2012	2012	NUM
esrj-49829	248	3	)	)	PUNCT
esrj-49829	248	4	.	.	PUNCT
esrj-49829	249	1	m5	m5	NOUN
esrj-49829	249	2	model	model	NOUN
esrj-49829	249	3	tree	tree	NOUN
esrj-49829	249	4	for	for	ADP
esrj-49829	249	5	pier	pier	NOUN
esrj-49829	249	6	scour	scour	NOUN
esrj-49829	249	7	prediction	prediction	NOUN
esrj-49829	249	8	using	use	VERB
esrj-49829	249	9	field	field	NOUN
esrj-49829	249	10	dataset	dataset	NOUN
esrj-49829	249	11	.	.	PUNCT
esrj-49829	250	1	ksce	ksce	PROPN
esrj-49829	250	2	,	,	PUNCT
esrj-49829	250	3	16(6	16(6	NUM
esrj-49829	250	4	)	)	PUNCT
esrj-49829	250	5	,	,	PUNCT
esrj-49829	250	6	1079	1079	NUM
esrj-49829	250	7	-	-	SYM
esrj-49829	250	8	1084	1084	NUM
esrj-49829	250	9	.	.	PUNCT
esrj-49829	251	1	quinlan	quinlan	PROPN
esrj-49829	251	2	,	,	PUNCT
esrj-49829	251	3	j.	j.	PROPN
esrj-49829	251	4	r.	r.	PROPN
esrj-49829	251	5	(	(	PUNCT
esrj-49829	251	6	1992	1992	NUM
esrj-49829	251	7	)	)	PUNCT
esrj-49829	251	8	.	.	PUNCT
esrj-49829	252	1	learning	learn	VERB
esrj-49829	252	2	with	with	ADP
esrj-49829	252	3	continuous	continuous	ADJ
esrj-49829	252	4	classes	class	NOUN
esrj-49829	252	5	.	.	PUNCT
esrj-49829	253	1	in	in	ADP
esrj-49829	253	2	:	:	PUNCT
esrj-49829	253	3	proc	proc	NOUN
esrj-49829	253	4	.	.	PUNCT
esrj-49829	254	1	ai’92	ai’92	PROPN
esrj-49829	254	2	(	(	PUNCT
esrj-49829	254	3	fifth	fifth	ADJ
esrj-49829	254	4	australian	australian	ADJ
esrj-49829	254	5	joint	joint	ADJ
esrj-49829	254	6	conf	conf	NOUN
esrj-49829	254	7	.	.	PUNCT
esrj-49829	255	1	on	on	ADP
esrj-49829	255	2	artificial	artificial	ADJ
esrj-49829	255	3	intelligence	intelligence	NOUN
esrj-49829	255	4	)	)	PUNCT
esrj-49829	255	5	(	(	PUNCT
esrj-49829	255	6	ed	ed	NOUN
esrj-49829	255	7	.	.	PUNCT
esrj-49829	255	8	by	by	ADP
esrj-49829	255	9	a.	a.	PROPN
esrj-49829	255	10	adams	adams	PROPN
esrj-49829	255	11	&	&	CCONJ
esrj-49829	255	12	l.	l.	PROPN
esrj-49829	255	13	sterling	sterling	PROPN
esrj-49829	255	14	)	)	PUNCT
esrj-49829	255	15	,	,	PUNCT
esrj-49829	255	16	343–348	343–348	NUM
esrj-49829	255	17	.	.	PUNCT
esrj-49829	256	1	world	world	PROPN
esrj-49829	256	2	scientific	scientific	PROPN
esrj-49829	256	3	,	,	PUNCT
esrj-49829	256	4	singapore	singapore	PROPN
esrj-49829	256	5	.	.	PUNCT
esrj-49829	257	1	raju	raju	PROPN
esrj-49829	257	2	,	,	PUNCT
esrj-49829	257	3	k.	k.	PROPN
esrj-49829	257	4	g.	g.	PROPN
esrj-49829	257	5	(	(	PUNCT
esrj-49829	257	6	2001	2001	NUM
esrj-49829	257	7	)	)	PUNCT
esrj-49829	257	8	.	.	PUNCT
esrj-49829	258	1	prediction	prediction	NOUN
esrj-49829	258	2	of	of	ADP
esrj-49829	258	3	soil	soil	NOUN
esrj-49829	258	4	temperature	temperature	NOUN
esrj-49829	258	5	by	by	ADP
esrj-49829	258	6	using	use	VERB
esrj-49829	258	7	artificial	artificial	ADJ
esrj-49829	258	8	neural	neural	ADJ
esrj-49829	258	9	networks	network	NOUN
esrj-49829	258	10	alghorithms	alghorithm	NOUN
esrj-49829	258	11	.	.	PUNCT
esrj-49829	259	1	nonlinear	nonlinear	ADJ
esrj-49829	259	2	analysis	analysis	NOUN
esrj-49829	259	3	,	,	PUNCT
esrj-49829	259	4	47	47	NUM
esrj-49829	259	5	,	,	PUNCT
esrj-49829	259	6	1737	1737	NUM
esrj-49829	259	7	-	-	SYM
esrj-49829	259	8	1748	1748	NUM
esrj-49829	259	9	.	.	PUNCT
esrj-49829	260	1	sattari	sattari	PROPN
esrj-49829	260	2	,	,	PUNCT
esrj-49829	260	3	m.	m.	NOUN
esrj-49829	260	4	t.	t.	PROPN
esrj-49829	260	5	,	,	PUNCT
esrj-49829	260	6	pal	pal	NOUN
esrj-49829	260	7	,	,	PUNCT
esrj-49829	260	8	m.	m.	NOUN
esrj-49829	260	9	,	,	PUNCT
esrj-49829	260	10	apaydin	apaydin	VERB
esrj-49829	260	11	,	,	PUNCT
esrj-49829	260	12	h.	h.	PROPN
esrj-49829	260	13	,	,	PUNCT
esrj-49829	260	14	&	&	CCONJ
esrj-49829	260	15	ozturk	ozturk	PROPN
esrj-49829	260	16	,	,	PUNCT
esrj-49829	260	17	f.	f.	PROPN
esrj-49829	260	18	(	(	PUNCT
esrj-49829	260	19	2013a	2013a	NUM
esrj-49829	260	20	)	)	PUNCT
esrj-49829	260	21	.	.	PUNCT
esrj-49829	261	1	m5	m5	NOUN
esrj-49829	261	2	model	model	NOUN
esrj-49829	261	3	tree	tree	NOUN
esrj-49829	261	4	application	application	NOUN
esrj-49829	261	5	in	in	ADP
esrj-49829	261	6	daily	daily	ADJ
esrj-49829	261	7	river	river	NOUN
esrj-49829	261	8	flow	flow	NOUN
esrj-49829	261	9	forecasting	forecasting	NOUN
esrj-49829	261	10	in	in	ADP
esrj-49829	261	11	sohu	sohu	PROPN
esrj-49829	261	12	stream	stream	PROPN
esrj-49829	261	13	,	,	PUNCT
esrj-49829	261	14	turkey	turkey	NOUN
esrj-49829	261	15	.	.	PUNCT
esrj-49829	262	1	water	water	NOUN
esrj-49829	262	2	resources	resource	NOUN
esrj-49829	262	3	,	,	PUNCT
esrj-49829	262	4	40(3	40(3	NOUN
esrj-49829	262	5	)	)	PUNCT
esrj-49829	262	6	,	,	PUNCT
esrj-49829	262	7	233	233	NUM
esrj-49829	262	8	-	-	SYM
esrj-49829	262	9	242	242	NUM
esrj-49829	262	10	.	.	PUNCT
esrj-49829	263	1	sattari	sattari	PROPN
esrj-49829	263	2	,	,	PUNCT
esrj-49829	263	3	m.	m.	NOUN
esrj-49829	263	4	t.	t.	PROPN
esrj-49829	263	5	,	,	PUNCT
esrj-49829	263	6	pal	pal	NOUN
esrj-49829	263	7	,	,	PUNCT
esrj-49829	263	8	m.	m.	NOUN
esrj-49829	263	9	,	,	PUNCT
esrj-49829	263	10	yurekli	yurekli	PROPN
esrj-49829	263	11	,	,	PUNCT
esrj-49829	263	12	k.	k.	PROPN
esrj-49829	263	13	,	,	PUNCT
esrj-49829	263	14	&	&	CCONJ
esrj-49829	263	15	unlukara	unlukara	PROPN
esrj-49829	263	16	,	,	PUNCT
esrj-49829	263	17	a.	a.	NOUN
esrj-49829	263	18	(	(	PUNCT
esrj-49829	263	19	2013b	2013b	NUM
esrj-49829	263	20	)	)	PUNCT
esrj-49829	263	21	.	.	PUNCT
esrj-49829	264	1	m5	m5	NOUN
esrj-49829	264	2	model	model	NOUN
esrj-49829	264	3	trees	tree	NOUN
esrj-49829	264	4	and	and	CCONJ
esrj-49829	264	5	neural	neural	ADJ
esrj-49829	264	6	network	network	NOUN
esrj-49829	264	7	based	base	VERB
esrj-49829	264	8	modelling	modelling	NOUN
esrj-49829	264	9	of	of	ADP
esrj-49829	264	10	et0	et0	NOUN
esrj-49829	264	11	in	in	ADP
esrj-49829	264	12	ankara	ankara	PROPN
esrj-49829	264	13	,	,	PUNCT
esrj-49829	264	14	turkey	turkey	PROPN
esrj-49829	264	15	.	.	PUNCT
esrj-49829	265	1	turkish	turkish	ADJ
esrj-49829	265	2	journal	journal	NOUN
esrj-49829	265	3	of	of	ADP
esrj-49829	265	4	engineering	engineering	NOUN
esrj-49829	265	5	and	and	CCONJ
esrj-49829	265	6	environmental	environmental	ADJ
esrj-49829	265	7	sciences	science	NOUN
esrj-49829	265	8	,	,	PUNCT
esrj-49829	265	9	37	37	NUM
esrj-49829	265	10	,	,	PUNCT
esrj-49829	265	11	211	211	NUM
esrj-49829	265	12	-	-	SYM
esrj-49829	265	13	219	219	NUM
esrj-49829	265	14	.	.	PUNCT
esrj-49829	266	1	sayagavi	sayagavi	PROPN
esrj-49829	266	2	,	,	PUNCT
esrj-49829	266	3	v.	v.	PROPN
esrj-49829	266	4	g.	g.	PROPN
esrj-49829	266	5	,	,	PUNCT
esrj-49829	266	6	charhate	charhate	NOUN
esrj-49829	266	7	,	,	PUNCT
esrj-49829	266	8	s.	s.	PROPN
esrj-49829	266	9	,	,	PUNCT
esrj-49829	266	10	&	&	CCONJ
esrj-49829	266	11	magar	magar	PROPN
esrj-49829	266	12	,	,	PUNCT
esrj-49829	266	13	r.	r.	PROPN
esrj-49829	266	14	(	(	PUNCT
esrj-49829	266	15	2016	2016	NUM
esrj-49829	266	16	)	)	PUNCT
esrj-49829	266	17	.	.	PUNCT
esrj-49829	267	1	estimation	estimation	NOUN
esrj-49829	267	2	of	of	ADP
esrj-49829	267	3	discharge	discharge	NOUN
esrj-49829	267	4	using	use	VERB
esrj-49829	267	5	ls	ls	ADJ
esrj-49829	267	6	-	-	PUNCT
esrj-49829	267	7	svm	svm	ADJ
esrj-49829	267	8	and	and	CCONJ
esrj-49829	267	9	model	model	NOUN
esrj-49829	267	10	trees	trees	PROPN
esrj-49829	267	11	.	.	PUNCT
esrj-49829	268	1	journal	journal	PROPN
esrj-49829	268	2	of	of	ADP
esrj-49829	268	3	water	water	NOUN
esrj-49829	268	4	resources	resource	NOUN
esrj-49829	268	5	and	and	CCONJ
esrj-49829	268	6	ocean	ocean	NOUN
esrj-49829	268	7	science	science	NOUN
esrj-49829	268	8	,	,	PUNCT
esrj-49829	268	9	5(6	5(6	NUM
esrj-49829	268	10	)	)	PUNCT
esrj-49829	268	11	,	,	PUNCT
esrj-49829	268	12	78	78	NUM
esrj-49829	268	13	-	-	SYM
esrj-49829	268	14	86	86	NUM
esrj-49829	268	15	.	.	PUNCT
esrj-49829	269	1	shannon	shannon	PROPN
esrj-49829	269	2	,	,	PUNCT
esrj-49829	269	3	e.	e.	PROPN
esrj-49829	269	4	b.	b.	PROPN
esrj-49829	269	5	,	,	PUNCT
esrj-49829	269	6	kurt	kurt	PROPN
esrj-49829	269	7	,	,	PUNCT
esrj-49829	269	8	s.	s.	PROPN
esrj-49829	269	9	p.	p.	PROPN
esrj-49829	269	10	,	,	PUNCT
esrj-49829	269	11	david	david	PROPN
esrj-49829	269	12	,	,	PUNCT
esrj-49829	269	13	d.	d.	PROPN
esrj-49829	269	14	r.	r.	PROPN
esrj-49829	269	15	&	&	CCONJ
esrj-49829	269	16	andrew	andrew	PROPN
esrj-49829	269	17	,	,	PUNCT
esrj-49829	269	18	j.	j.	PROPN
esrj-49829	269	19	b.	b.	PROPN
esrj-49829	269	20	(	(	PUNCT
esrj-49829	269	21	2000	2000	NUM
esrj-49829	269	22	)	)	PUNCT
esrj-49829	269	23	.	.	PUNCT
esrj-49829	270	1	predicting	predict	VERB
esrj-49829	270	2	daily	daily	ADJ
esrj-49829	270	3	mean	mean	VERB
esrj-49829	270	4	soil	soil	NOUN
esrj-49829	270	5	temperature	temperature	NOUN
esrj-49829	270	6	from	from	ADP
esrj-49829	270	7	daily	daily	ADJ
esrj-49829	270	8	mean	mean	NOUN
esrj-49829	270	9	air	air	NOUN
esrj-49829	270	10	temperature	temperature	NOUN
esrj-49829	270	11	in	in	ADP
esrj-49829	270	12	four	four	NUM
esrj-49829	270	13	northern	northern	ADJ
esrj-49829	270	14	hard	hard	ADJ
esrj-49829	270	15	wood	wood	NOUN
esrj-49829	270	16	forest	forest	NOUN
esrj-49829	270	17	stands	stand	NOUN
esrj-49829	270	18	.	.	PUNCT
esrj-49829	271	1	forest	forest	NOUN
esrj-49829	271	2	science	science	PROPN
esrj-49829	271	3	,	,	PUNCT
esrj-49829	271	4	46	46	NUM
esrj-49829	271	5	,	,	PUNCT
esrj-49829	271	6	297	297	NUM
esrj-49829	271	7	-	-	SYM
esrj-49829	271	8	301	301	NUM
esrj-49829	271	9	.	.	PUNCT
esrj-49829	272	1	shiri	shiri	PROPN
esrj-49829	272	2	,	,	PUNCT
esrj-49829	272	3	j.	j.	PROPN
esrj-49829	272	4	,	,	PUNCT
esrj-49829	272	5	&	&	CCONJ
esrj-49829	272	6	kishi	kishi	PROPN
esrj-49829	272	7	,	,	PUNCT
esrj-49829	272	8	o.	o.	PROPN
esrj-49829	272	9	(	(	PUNCT
esrj-49829	272	10	2011	2011	NUM
esrj-49829	272	11	)	)	PUNCT
esrj-49829	272	12	.	.	PUNCT
esrj-49829	273	1	comparison	comparison	NOUN
esrj-49829	273	2	of	of	ADP
esrj-49829	273	3	genetic	genetic	ADJ
esrj-49829	273	4	programming	programming	NOUN
esrj-49829	273	5	with	with	ADP
esrj-49829	273	6	neurofuzzy	neurofuzzy	ADJ
esrj-49829	273	7	systems	system	NOUN
esrj-49829	273	8	for	for	ADP
esrj-49829	273	9	predicting	predict	VERB
esrj-49829	273	10	.	.	PUNCT
esrj-49829	274	1	computers	computer	NOUN
esrj-49829	274	2	&	&	CCONJ
esrj-49829	274	3	geosciences	geoscience	NOUN
esrj-49829	274	4	,	,	PUNCT
esrj-49829	274	5	37	37	NUM
esrj-49829	274	6	,	,	PUNCT
esrj-49829	274	7	1692	1692	NUM
esrj-49829	274	8	-	-	SYM
esrj-49829	274	9	1701	1701	NUM
esrj-49829	274	10	.	.	PUNCT
esrj-49829	275	1	shortridge	shortridge	PROPN
esrj-49829	275	2	,	,	PUNCT
esrj-49829	275	3	j.	j.	PROPN
esrj-49829	275	4	e.	e.	PROPN
esrj-49829	275	5	,	,	PUNCT
esrj-49829	275	6	guikema	guikema	PROPN
esrj-49829	275	7	,	,	PUNCT
esrj-49829	275	8	s.	s.	PROPN
esrj-49829	275	9	d.	d.	PROPN
esrj-49829	275	10	,	,	PUNCT
esrj-49829	275	11	&	&	CCONJ
esrj-49829	275	12	zaitchik	zaitchik	PROPN
esrj-49829	275	13	,	,	PUNCT
esrj-49829	275	14	b.	b.	PROPN
esrj-49829	275	15	f.	f.	PROPN
esrj-49829	275	16	(	(	PUNCT
esrj-49829	275	17	2016	2016	NUM
esrj-49829	275	18	)	)	PUNCT
esrj-49829	275	19	.	.	PUNCT
esrj-49829	276	1	machine	machine	NOUN
esrj-49829	276	2	learning	learn	VERB
esrj-49829	276	3	methods	method	NOUN
esrj-49829	276	4	for	for	ADP
esrj-49829	276	5	empirical	empirical	ADJ
esrj-49829	276	6	streamflow	streamflow	NOUN
esrj-49829	276	7	simulation	simulation	NOUN
esrj-49829	276	8	:	:	PUNCT
esrj-49829	276	9	a	a	DET
esrj-49829	276	10	comparison	comparison	NOUN
esrj-49829	276	11	of	of	ADP
esrj-49829	276	12	model	model	NOUN
esrj-49829	276	13	accuracy	accuracy	NOUN
esrj-49829	276	14	,	,	PUNCT
esrj-49829	276	15	interpretability	interpretability	NOUN
esrj-49829	276	16	,	,	PUNCT
esrj-49829	276	17	and	and	CCONJ
esrj-49829	276	18	uncertainty	uncertainty	NOUN
esrj-49829	276	19	in	in	ADP
esrj-49829	276	20	seasonal	seasonal	ADJ
esrj-49829	276	21	watersheds	watershed	NOUN
esrj-49829	276	22	.	.	PUNCT
esrj-49829	277	1	hydrology	hydrology	NOUN
esrj-49829	277	2	and	and	CCONJ
esrj-49829	277	3	earth	earth	NOUN
esrj-49829	277	4	system	system	NOUN
esrj-49829	277	5	sciences	science	NOUN
esrj-49829	277	6	,	,	PUNCT
esrj-49829	277	7	20	20	NUM
esrj-49829	277	8	,	,	PUNCT
esrj-49829	277	9	2611	2611	NUM
esrj-49829	277	10	-	-	SYM
esrj-49829	277	11	2628	2628	NUM
esrj-49829	277	12	.	.	PUNCT
esrj-49829	278	1	schnier	schnier	PROPN
esrj-49829	278	2	,	,	PUNCT
esrj-49829	278	3	s.	s.	PROPN
esrj-49829	278	4	t.	t.	PROPN
esrj-49829	278	5	(	(	PUNCT
esrj-49829	278	6	2016	2016	NUM
esrj-49829	278	7	)	)	PUNCT
esrj-49829	278	8	.	.	PUNCT
esrj-49829	279	1	data	datum	NOUN
esrj-49829	279	2	driven	drive	VERB
esrj-49829	279	3	analyses	analysis	NOUN
esrj-49829	279	4	of	of	ADP
esrj-49829	279	5	watersheds	watershed	NOUN
esrj-49829	279	6	as	as	SCONJ
esrj-49829	279	7	coupled	couple	VERB
esrj-49829	279	8	humannature	humannature	NOUN
esrj-49829	279	9	systems	system	NOUN
esrj-49829	279	10	.	.	PUNCT
esrj-49829	280	1	unvisesity	unvisesity	NOUN
esrj-49829	280	2	of	of	ADP
esrj-49829	280	3	illinois	illinois	PROPN
esrj-49829	280	4	,	,	PUNCT
esrj-49829	280	5	urbana	urbana	PROPN
esrj-49829	280	6	,	,	PUNCT
esrj-49829	280	7	illinois	illinois	PROPN
esrj-49829	280	8	.	.	PROPN
esrj-49829	280	9	shu	shu	PROPN
esrj-49829	280	10	,	,	PUNCT
esrj-49829	280	11	c.	c.	PROPN
esrj-49829	280	12	,	,	PUNCT
esrj-49829	280	13	&	&	CCONJ
esrj-49829	280	14	ouarda	ouarda	PROPN
esrj-49829	280	15	tbmj	tbmj	NOUN
esrj-49829	280	16	.	.	PUNCT
esrj-49829	281	1	(	(	PUNCT
esrj-49829	281	2	2008	2008	NUM
esrj-49829	281	3	)	)	PUNCT
esrj-49829	281	4	.	.	PUNCT
esrj-49829	282	1	regional	regional	ADJ
esrj-49829	282	2	flood	flood	NOUN
esrj-49829	282	3	frequency	frequency	NOUN
esrj-49829	282	4	analysis	analysis	NOUN
esrj-49829	282	5	at	at	ADP
esrj-49829	282	6	ungauged	ungauged	ADJ
esrj-49829	282	7	sites	site	NOUN
esrj-49829	282	8	using	use	VERB
esrj-49829	282	9	the	the	DET
esrj-49829	282	10	adaptive	adaptive	ADJ
esrj-49829	282	11	neuro	neuro	NOUN
esrj-49829	282	12	-	-	PUNCT
esrj-49829	282	13	fuzzy	fuzzy	ADJ
esrj-49829	282	14	inference	inference	NOUN
esrj-49829	282	15	system	system	NOUN
esrj-49829	282	16	.	.	PUNCT
esrj-49829	283	1	journal	journal	NOUN
esrj-49829	283	2	of	of	ADP
esrj-49829	283	3	hydrology	hydrology	NOUN
esrj-49829	283	4	,	,	PUNCT
esrj-49829	283	5	349	349	NUM
esrj-49829	283	6	,	,	PUNCT
esrj-49829	283	7	31	31	NUM
esrj-49829	283	8	-	-	SYM
esrj-49829	283	9	43	43	NUM
esrj-49829	283	10	.	.	PUNCT
esrj-49829	284	1	siek	siek	NOUN
esrj-49829	284	2	,	,	PUNCT
esrj-49829	284	3	m.	m.	NOUN
esrj-49829	284	4	&	&	CCONJ
esrj-49829	284	5	solomantine	solomantine	PROPN
esrj-49829	284	6	,	,	PUNCT
esrj-49829	284	7	d.	d.	PROPN
esrj-49829	284	8	p.	p.	PROPN
esrj-49829	284	9	(	(	PUNCT
esrj-49829	284	10	2007	2007	NUM
esrj-49829	284	11	)	)	PUNCT
esrj-49829	284	12	.	.	PUNCT
esrj-49829	285	1	tree	tree	NOUN
esrj-49829	285	2	-	-	PUNCT
esrj-49829	285	3	like	like	ADJ
esrj-49829	285	4	machine	machine	NOUN
esrj-49829	285	5	learning	learning	NOUN
esrj-49829	285	6	models	model	NOUN
esrj-49829	285	7	in	in	ADP
esrj-49829	285	8	hydrologic	hydrologic	ADJ
esrj-49829	285	9	forecasting	forecasting	NOUN
esrj-49829	285	10	:	:	PUNCT
esrj-49829	285	11	optimality	optimality	NOUN
esrj-49829	285	12	and	and	CCONJ
esrj-49829	285	13	expert	expert	NOUN
esrj-49829	285	14	knowledge	knowledge	NOUN
esrj-49829	285	15	.	.	PUNCT
esrj-49829	286	1	geophysical	geophysical	ADJ
esrj-49829	286	2	research	research	NOUN
esrj-49829	286	3	abstracts	abstract	NOUN
esrj-49829	286	4	,	,	PUNCT
esrj-49829	286	5	9	9	NUM
esrj-49829	286	6	,	,	PUNCT
esrj-49829	286	7	2	2	NUM
esrj-49829	286	8	-	-	SYM
esrj-49829	286	9	5	5	NUM
esrj-49829	286	10	.	.	PUNCT
esrj-49829	286	11	93estimation	93estimation	NUM
esrj-49829	286	12	of	of	ADP
esrj-49829	286	13	daily	daily	ADJ
esrj-49829	286	14	soil	soil	NOUN
esrj-49829	286	15	temperature	temperature	NOUN
esrj-49829	286	16	via	via	ADP
esrj-49829	286	17	data	datum	NOUN
esrj-49829	286	18	mining	mining	NOUN
esrj-49829	286	19	techniques	technique	NOUN
esrj-49829	286	20	in	in	ADP
esrj-49829	286	21	semi	semi	ADJ
esrj-49829	286	22	-	-	ADJ
esrj-49829	286	23	arid	arid	ADJ
esrj-49829	286	24	climate	climate	NOUN
esrj-49829	286	25	conditions	condition	NOUN
esrj-49829	286	26	solomantine	solomantine	PROPN
esrj-49829	286	27	,	,	PUNCT
esrj-49829	286	28	d.	d.	PROPN
esrj-49829	286	29	p.	p.	PROPN
esrj-49829	286	30	&	&	CCONJ
esrj-49829	286	31	dulal	dulal	PROPN
esrj-49829	286	32	,	,	PUNCT
esrj-49829	286	33	k.	k.	PROPN
esrj-49829	286	34	n.	n.	PROPN
esrj-49829	286	35	(	(	PUNCT
esrj-49829	286	36	2003	2003	NUM
esrj-49829	286	37	)	)	PUNCT
esrj-49829	286	38	.	.	PUNCT
esrj-49829	287	1	model	model	NOUN
esrj-49829	287	2	trees	tree	NOUN
esrj-49829	287	3	as	as	ADP
esrj-49829	287	4	an	an	DET
esrj-49829	287	5	alternative	alternative	NOUN
esrj-49829	287	6	to	to	ADP
esrj-49829	287	7	neural	neural	ADJ
esrj-49829	287	8	networks	network	NOUN
esrj-49829	287	9	in	in	ADP
esrj-49829	287	10	rainfall	rainfall	NOUN
esrj-49829	287	11	-	-	PUNCT
esrj-49829	287	12	runoff	runoff	NOUN
esrj-49829	287	13	modeling	modeling	NOUN
esrj-49829	287	14	.	.	PUNCT
esrj-49829	288	1	hydrological	hydrological	ADJ
esrj-49829	288	2	sciences	sciences	PROPN
esrj-49829	288	3	journal	journal	NOUN
esrj-49829	288	4	,	,	PUNCT
esrj-49829	288	5	48	48	NUM
esrj-49829	288	6	,	,	PUNCT
esrj-49829	288	7	455	455	NUM
esrj-49829	288	8	-	-	SYM
esrj-49829	288	9	472	472	NUM
esrj-49829	288	10	.	.	PUNCT
esrj-49829	289	1	stravs	stravs	PROPN
esrj-49829	289	2	,	,	PUNCT
esrj-49829	289	3	l.	l.	PROPN
esrj-49829	289	4	,	,	PUNCT
esrj-49829	289	5	&	&	CCONJ
esrj-49829	289	6	brilly	brilly	ADV
esrj-49829	289	7	,	,	PUNCT
esrj-49829	289	8	m.	m.	NOUN
esrj-49829	289	9	(	(	PUNCT
esrj-49829	289	10	2007	2007	NUM
esrj-49829	289	11	)	)	PUNCT
esrj-49829	289	12	.	.	PUNCT
esrj-49829	290	1	development	development	NOUN
esrj-49829	290	2	of	of	ADP
esrj-49829	290	3	a	a	DET
esrj-49829	290	4	low	low	ADJ
esrj-49829	290	5	flow	flow	NOUN
esrj-49829	290	6	forecasting	forecasting	NOUN
esrj-49829	290	7	model	model	NOUN
esrj-49829	290	8	using	use	VERB
esrj-49829	290	9	the	the	DET
esrj-49829	290	10	m5	m5	ADJ
esrj-49829	290	11	machine	machine	NOUN
esrj-49829	290	12	learning	learning	NOUN
esrj-49829	290	13	method	method	NOUN
esrj-49829	290	14	.	.	PUNCT
esrj-49829	291	1	hydrological	hydrological	ADJ
esrj-49829	291	2	sciences	sciences	PROPN
esrj-49829	291	3	journal	journal	NOUN
esrj-49829	291	4	,	,	PUNCT
esrj-49829	291	5	52	52	NUM
esrj-49829	291	6	,	,	PUNCT
esrj-49829	291	7	466–477	466–477	NUM
esrj-49829	291	8	.	.	PUNCT
esrj-49829	291	9	tang	tang	PROPN
esrj-49829	291	10	,	,	PUNCT
esrj-49829	291	11	z.	z.	PROPN
esrj-49829	291	12	,	,	PUNCT
esrj-49829	291	13	&	&	CCONJ
esrj-49829	291	14	fishwick	fishwick	NOUN
esrj-49829	291	15	,	,	PUNCT
esrj-49829	291	16	p.	p.	NOUN
esrj-49829	291	17	a.	a.	NOUN
esrj-49829	292	1	(	(	PUNCT
esrj-49829	292	2	1993	1993	NUM
esrj-49829	292	3	)	)	PUNCT
esrj-49829	292	4	.	.	PUNCT
esrj-49829	293	1	feedforward	feedforward	ADJ
esrj-49829	293	2	neural	neural	ADJ
esrj-49829	293	3	nets	net	NOUN
esrj-49829	293	4	as	as	ADP
esrj-49829	293	5	models	model	NOUN
esrj-49829	293	6	for	for	ADP
esrj-49829	293	7	time	time	NOUN
esrj-49829	293	8	series	series	PROPN
esrj-49829	293	9	forecasting	forecasting	PROPN
esrj-49829	293	10	.	.	PUNCT
esrj-49829	294	1	orsa	orsa	PROPN
esrj-49829	294	2	journal	journal	PROPN
esrj-49829	294	3	of	of	ADP
esrj-49829	294	4	computing	computing	NOUN
esrj-49829	294	5	,	,	PUNCT
esrj-49829	294	6	5(4	5(4	NUM
esrj-49829	294	7	)	)	PUNCT
esrj-49829	294	8	,	,	PUNCT
esrj-49829	294	9	374–385	374–385	NUM
esrj-49829	294	10	.	.	PUNCT
esrj-49829	295	1	timlin	timlin	PROPN
esrj-49829	295	2	,	,	PUNCT
esrj-49829	295	3	d.	d.	PROPN
esrj-49829	295	4	j.	j.	PROPN
esrj-49829	295	5	,	,	PUNCT
esrj-49829	295	6	pachepsky	pachepsky	NOUN
esrj-49829	295	7	,	,	PUNCT
esrj-49829	295	8	y.	y.	PROPN
esrj-49829	295	9	,	,	PUNCT
esrj-49829	295	10	acock	acock	NOUN
esrj-49829	295	11	,	,	PUNCT
esrj-49829	295	12	b.	b.	PROPN
esrj-49829	295	13	a.	a.	PROPN
esrj-49829	295	14	,	,	PUNCT
esrj-49829	295	15	s'imunek	s'imunek	PROPN
esrj-49829	295	16	,	,	PUNCT
esrj-49829	295	17	j.	j.	PROPN
esrj-49829	295	18	,	,	PUNCT
esrj-49829	295	19	flerchinger	flerchinger	PROPN
esrj-49829	295	20	,	,	PUNCT
esrj-49829	295	21	g.	g.	PROPN
esrj-49829	295	22	&	&	CCONJ
esrj-49829	295	23	whisler	whisler	PROPN
esrj-49829	295	24	,	,	PUNCT
esrj-49829	295	25	f.	f.	PROPN
esrj-49829	295	26	(	(	PUNCT
esrj-49829	295	27	2002	2002	NUM
esrj-49829	295	28	)	)	PUNCT
esrj-49829	295	29	.	.	PUNCT
esrj-49829	296	1	error	error	NOUN
esrj-49829	296	2	analysis	analysis	NOUN
esrj-49829	296	3	of	of	ADP
esrj-49829	296	4	soil	soil	NOUN
esrj-49829	296	5	temperature	temperature	NOUN
esrj-49829	296	6	simulations	simulation	NOUN
esrj-49829	296	7	using	using	AUX
esrj-49829	296	8	measured	measure	VERB
esrj-49829	296	9	and	and	CCONJ
esrj-49829	296	10	estimated	estimate	VERB
esrj-49829	296	11	hourly	hourly	ADJ
esrj-49829	296	12	weather	weather	NOUN
esrj-49829	296	13	data	datum	NOUN
esrj-49829	296	14	with	with	ADP
esrj-49829	296	15	2dsoil	2dsoil	NUM
esrj-49829	296	16	.	.	PUNCT
esrj-49829	297	1	agricultural	agricultural	ADJ
esrj-49829	297	2	systems	system	NOUN
esrj-49829	297	3	,	,	PUNCT
esrj-49829	297	4	72	72	NUM
esrj-49829	297	5	,	,	PUNCT
esrj-49829	297	6	215–239	215–239	NUM
esrj-49829	297	7	.	.	PUNCT
esrj-49829	298	1	tuntiwaranuruk	tuntiwaranuruk	PROPN
esrj-49829	298	2	,	,	PUNCT
esrj-49829	298	3	u.	u.	PROPN
esrj-49829	298	4	,	,	PUNCT
esrj-49829	298	5	thepa	thepa	NOUN
esrj-49829	298	6	,	,	PUNCT
esrj-49829	298	7	s.	s.	PROPN
esrj-49829	298	8	,	,	PUNCT
esrj-49829	298	9	tia	tia	PROPN
esrj-49829	298	10	,	,	PUNCT
esrj-49829	298	11	s.	s.	PROPN
esrj-49829	298	12	,	,	PUNCT
esrj-49829	298	13	&	&	CCONJ
esrj-49829	298	14	bhumiratana	bhumiratana	PROPN
esrj-49829	298	15	,	,	PUNCT
esrj-49829	298	16	s.	s.	PROPN
esrj-49829	298	17	(	(	PUNCT
esrj-49829	298	18	2006	2006	NUM
esrj-49829	298	19	)	)	PUNCT
esrj-49829	298	20	.	.	PUNCT
esrj-49829	299	1	modeling	modeling	NOUN
esrj-49829	299	2	of	of	ADP
esrj-49829	299	3	soil	soil	NOUN
esrj-49829	299	4	temperature	temperature	NOUN
esrj-49829	299	5	and	and	CCONJ
esrj-49829	299	6	moisture	moisture	NOUN
esrj-49829	299	7	with	with	ADP
esrj-49829	299	8	and	and	CCONJ
esrj-49829	299	9	without	without	ADP
esrj-49829	299	10	rice	rice	NOUN
esrj-49829	299	11	husks	husk	NOUN
esrj-49829	299	12	in	in	ADP
esrj-49829	299	13	an	an	DET
esrj-49829	299	14	agriculture	agriculture	NOUN
esrj-49829	299	15	greenhouse	greenhouse	NOUN
esrj-49829	299	16	.	.	PUNCT
esrj-49829	300	1	renewable	renewable	ADJ
esrj-49829	300	2	energy	energy	NOUN
esrj-49829	300	3	,	,	PUNCT
esrj-49829	300	4	31	31	NUM
esrj-49829	300	5	,	,	PUNCT
esrj-49829	300	6	1934–1949	1934–1949	NUM
esrj-49829	300	7	.	.	PUNCT
esrj-49829	301	1	tyronese	tyronese	PROPN
esrj-49829	301	2	,	,	PUNCT
esrj-49829	301	3	j.	j.	PROPN
esrj-49829	301	4	,	,	PUNCT
esrj-49829	301	5	katrina	katrina	PROPN
esrj-49829	301	6	,	,	PUNCT
esrj-49829	301	7	m.	m.	NOUN
esrj-49829	301	8	,	,	PUNCT
esrj-49829	301	9	mohamed	mohamed	PROPN
esrj-49829	301	10	,	,	PUNCT
esrj-49829	301	11	s.	s.	PROPN
esrj-49829	301	12	,	,	PUNCT
esrj-49829	301	13	tommy	tommy	PROPN
esrj-49829	301	14	,	,	PUNCT
esrj-49829	301	15	c.	c.	PROPN
esrj-49829	301	16	&	&	CCONJ
esrj-49829	301	17	peter	peter	PROPN
esrj-49829	301	18	,	,	PUNCT
esrj-49829	301	19	r.	r.	PROPN
esrj-49829	301	20	(	(	PUNCT
esrj-49829	301	21	2008	2008	NUM
esrj-49829	301	22	)	)	PUNCT
esrj-49829	301	23	.	.	PUNCT
esrj-49829	302	1	measuring	measure	VERB
esrj-49829	302	2	soil	soil	NOUN
esrj-49829	302	3	temperature	temperature	NOUN
esrj-49829	302	4	and	and	CCONJ
esrj-49829	302	5	moisture	moisture	NOUN
esrj-49829	302	6	using	use	VERB
esrj-49829	302	7	wireless	wireless	ADJ
esrj-49829	302	8	mems	mem	NOUN
esrj-49829	302	9	sensors	sensor	NOUN
esrj-49829	302	10	.	.	PUNCT
esrj-49829	303	1	measurement	measurement	NOUN
esrj-49829	303	2	,	,	PUNCT
esrj-49829	303	3	41	41	NUM
esrj-49829	303	4	,	,	PUNCT
esrj-49829	303	5	381–390	381–390	NUM
esrj-49829	303	6	.	.	PUNCT
esrj-49829	303	7	winegardner	winegardner	NOUN
esrj-49829	303	8	,	,	PUNCT
esrj-49829	303	9	d.	d.	PROPN
esrj-49829	303	10	l.	l.	PROPN
esrj-49829	303	11	(	(	PUNCT
esrj-49829	303	12	1996	1996	NUM
esrj-49829	303	13	)	)	PUNCT
esrj-49829	303	14	.	.	PUNCT
esrj-49829	304	1	an	an	DET
esrj-49829	304	2	introduction	introduction	NOUN
esrj-49829	304	3	to	to	ADP
esrj-49829	304	4	soils	soil	NOUN
esrj-49829	304	5	for	for	ADP
esrj-49829	304	6	environmental	environmental	ADJ
esrj-49829	304	7	professionals	professional	NOUN
esrj-49829	304	8	.	.	PUNCT
esrj-49829	305	1	boca	boca	PROPN
esrj-49829	305	2	raton	raton	PROPN
esrj-49829	305	3	,	,	PUNCT
esrj-49829	305	4	fla	fla	PROPN
esrj-49829	305	5	.	.	PUNCT
esrj-49829	305	6	:	:	PUNCT
esrj-49829	306	1	lewis	lewis	PROPN
esrj-49829	306	2	publishers	publisher	NOUN
esrj-49829	306	3	.	.	PUNCT
esrj-49829	307	1	wong	wong	PROPN
esrj-49829	307	2	,	,	PUNCT
esrj-49829	307	3	f.	f.	PROPN
esrj-49829	307	4	s.	s.	PROPN
esrj-49829	307	5	(	(	PUNCT
esrj-49829	307	6	1991	1991	NUM
esrj-49829	307	7	)	)	PUNCT
esrj-49829	307	8	.	.	PUNCT
esrj-49829	308	1	time	time	NOUN
esrj-49829	308	2	series	series	PROPN
esrj-49829	308	3	forecasting	forecasting	NOUN
esrj-49829	308	4	using	use	VERB
esrj-49829	308	5	backpropagation	backpropagation	NOUN
esrj-49829	308	6	neural	neural	ADJ
esrj-49829	308	7	networks	network	NOUN
esrj-49829	308	8	.	.	PUNCT
esrj-49829	309	1	neurocomputing	neurocompute	VERB
esrj-49829	309	2	2	2	NUM
esrj-49829	309	3	,	,	PUNCT
esrj-49829	309	4	147–159	147–159	NUM
esrj-49829	309	5	.	.	PUNCT
esrj-49829	310	1	yang	yang	PROPN
esrj-49829	310	2	,	,	PUNCT
esrj-49829	310	3	c.	c.	PROPN
esrj-49829	310	4	c.	c.	PROPN
esrj-49829	310	5	,	,	PUNCT
esrj-49829	310	6	prasher	prasher	PROPN
esrj-49829	310	7	,	,	PUNCT
esrj-49829	310	8	s.	s.	PROPN
esrj-49829	310	9	o.	o.	PROPN
esrj-49829	310	10	,	,	PUNCT
esrj-49829	310	11	mehuys	mehuys	PROPN
esrj-49829	310	12	,	,	PUNCT
esrj-49829	310	13	g.	g.	PROPN
esrj-49829	310	14	r.	r.	PROPN
esrj-49829	310	15	&	&	CCONJ
esrj-49829	310	16	patni	patni	PROPN
esrj-49829	310	17	,	,	PUNCT
esrj-49829	310	18	n.	n.	PROPN
esrj-49829	310	19	k.	k.	PROPN
esrj-49829	310	20	(	(	PUNCT
esrj-49829	310	21	1997	1997	NUM
esrj-49829	310	22	)	)	PUNCT
esrj-49829	310	23	.	.	PUNCT
esrj-49829	311	1	application	application	NOUN
esrj-49829	311	2	of	of	ADP
esrj-49829	311	3	artificial	artificial	ADJ
esrj-49829	311	4	neural	neural	ADJ
esrj-49829	311	5	networks	network	NOUN
esrj-49829	311	6	for	for	ADP
esrj-49829	311	7	simulation	simulation	NOUN
esrj-49829	311	8	of	of	ADP
esrj-49829	311	9	soil	soil	NOUN
esrj-49829	311	10	temperature	temperature	NOUN
esrj-49829	311	11	.	.	PUNCT
esrj-49829	312	1	transactions	transaction	NOUN
esrj-49829	312	2	of	of	ADP
esrj-49829	312	3	the	the	DET
esrj-49829	312	4	asae	asae	NOUN
esrj-49829	312	5	,	,	PUNCT
esrj-49829	312	6	40	40	NUM
esrj-49829	312	7	,	,	PUNCT
esrj-49829	312	8	649	649	NUM
esrj-49829	312	9	-	-	SYM
esrj-49829	312	10	656	656	NUM
esrj-49829	312	11	.	.	PUNCT
esrj-49829	313	1	zadeh	zadeh	PROPN
esrj-49829	313	2	,	,	PUNCT
esrj-49829	313	3	l.	l.	PROPN
esrj-49829	313	4	a.	a.	PROPN
esrj-49829	313	5	(	(	PUNCT
esrj-49829	313	6	1965	1965	NUM
esrj-49829	313	7	)	)	PUNCT
esrj-49829	313	8	.	.	PUNCT
esrj-49829	314	1	fuzzy	fuzzy	ADJ
esrj-49829	314	2	sets	set	NOUN
esrj-49829	314	3	.	.	PUNCT
esrj-49829	315	1	information	information	NOUN
esrj-49829	315	2	control	control	NOUN
esrj-49829	315	3	,	,	PUNCT
esrj-49829	315	4	8	8	NUM
esrj-49829	315	5	,	,	PUNCT
esrj-49829	315	6	338–353	338–353	NUM
esrj-49829	315	7	.	.	PUNCT
esrj-49829	315	8	sensors	sensor	NOUN
esrj-49829	315	9	.	.	PUNCT
esrj-49829	316	1	measurement	measurement	NOUN
esrj-49829	316	2	,	,	PUNCT
esrj-49829	316	3	41	41	NUM
esrj-49829	316	4	,	,	PUNCT
esrj-49829	316	5	381–390	381–390	NUM
esrj-49829	316	6	.	.	PUNCT
esrj-49829	316	7	winegardner	winegardner	NOUN
esrj-49829	316	8	,	,	PUNCT
esrj-49829	316	9	d.	d.	PROPN
esrj-49829	316	10	l.	l.	PROPN
esrj-49829	316	11	(	(	PUNCT
esrj-49829	316	12	1996	1996	NUM
esrj-49829	316	13	)	)	PUNCT
esrj-49829	316	14	.	.	PUNCT
esrj-49829	317	1	an	an	DET
esrj-49829	317	2	introduction	introduction	NOUN
esrj-49829	317	3	to	to	ADP
esrj-49829	317	4	soils	soil	NOUN
esrj-49829	317	5	for	for	ADP
esrj-49829	317	6	environmental	environmental	ADJ
esrj-49829	317	7	professionals	professional	NOUN
esrj-49829	317	8	.	.	PUNCT
esrj-49829	318	1	boca	boca	PROPN
esrj-49829	318	2	raton	raton	PROPN
esrj-49829	318	3	,	,	PUNCT
esrj-49829	318	4	fla	fla	PROPN
esrj-49829	318	5	.	.	PUNCT
esrj-49829	318	6	:	:	PUNCT
esrj-49829	319	1	lewis	lewis	PROPN
esrj-49829	319	2	publishers	publisher	NOUN
esrj-49829	319	3	.	.	PUNCT
esrj-49829	320	1	wong	wong	PROPN
esrj-49829	320	2	,	,	PUNCT
esrj-49829	320	3	f.	f.	PROPN
esrj-49829	320	4	s.	s.	PROPN
esrj-49829	320	5	(	(	PUNCT
esrj-49829	320	6	1991	1991	NUM
esrj-49829	320	7	)	)	PUNCT
esrj-49829	320	8	.	.	PUNCT
esrj-49829	321	1	time	time	NOUN
esrj-49829	321	2	series	series	PROPN
esrj-49829	321	3	forecasting	forecasting	NOUN
esrj-49829	321	4	using	use	VERB
esrj-49829	321	5	backpropagation	backpropagation	NOUN
esrj-49829	321	6	neural	neural	ADJ
esrj-49829	321	7	networks	network	NOUN
esrj-49829	321	8	.	.	PUNCT
esrj-49829	322	1	neurocomputing	neurocompute	VERB
esrj-49829	322	2	2	2	NUM
esrj-49829	322	3	,	,	PUNCT
esrj-49829	322	4	147–159	147–159	NUM
esrj-49829	322	5	.	.	PUNCT
esrj-49829	323	1	yang	yang	PROPN
esrj-49829	323	2	,	,	PUNCT
esrj-49829	323	3	c.	c.	PROPN
esrj-49829	323	4	c.	c.	PROPN
esrj-49829	323	5	,	,	PUNCT
esrj-49829	323	6	prasher	prasher	PROPN
esrj-49829	323	7	,	,	PUNCT
esrj-49829	323	8	s.	s.	PROPN
esrj-49829	323	9	o.	o.	PROPN
esrj-49829	323	10	,	,	PUNCT
esrj-49829	323	11	mehuys	mehuys	PROPN
esrj-49829	323	12	,	,	PUNCT
esrj-49829	323	13	g.	g.	PROPN
esrj-49829	323	14	r.	r.	PROPN
esrj-49829	323	15	&	&	CCONJ
esrj-49829	323	16	patni	patni	PROPN
esrj-49829	323	17	,	,	PUNCT
esrj-49829	323	18	n.	n.	PROPN
esrj-49829	323	19	k.	k.	PROPN
esrj-49829	323	20	(	(	PUNCT
esrj-49829	323	21	1997	1997	NUM
esrj-49829	323	22	)	)	PUNCT
esrj-49829	323	23	.	.	PUNCT
esrj-49829	324	1	application	application	NOUN
esrj-49829	324	2	of	of	ADP
esrj-49829	324	3	artificial	artificial	ADJ
esrj-49829	324	4	neural	neural	ADJ
esrj-49829	324	5	networks	network	NOUN
esrj-49829	324	6	for	for	ADP
esrj-49829	324	7	simulation	simulation	NOUN
esrj-49829	324	8	of	of	ADP
esrj-49829	324	9	soil	soil	NOUN
esrj-49829	324	10	temperature	temperature	NOUN
esrj-49829	324	11	.	.	PUNCT
esrj-49829	325	1	transactions	transaction	NOUN
esrj-49829	325	2	of	of	ADP
esrj-49829	325	3	the	the	DET
esrj-49829	325	4	asae	asae	NOUN
esrj-49829	325	5	,	,	PUNCT
esrj-49829	325	6	40	40	NUM
esrj-49829	325	7	,	,	PUNCT
esrj-49829	325	8	649	649	NUM
esrj-49829	325	9	-	-	SYM
esrj-49829	325	10	656	656	NUM
esrj-49829	325	11	.	.	PUNCT
esrj-49829	326	1	zadeh	zadeh	PROPN
esrj-49829	326	2	,	,	PUNCT
esrj-49829	326	3	l.	l.	PROPN
esrj-49829	326	4	a.	a.	PROPN
esrj-49829	326	5	(	(	PUNCT
esrj-49829	326	6	1965	1965	NUM
esrj-49829	326	7	)	)	PUNCT
esrj-49829	326	8	.	.	PUNCT
esrj-49829	327	1	fuzzy	fuzzy	ADJ
esrj-49829	327	2	sets	set	NOUN
esrj-49829	327	3	.	.	PUNCT
esrj-49829	328	1	information	information	NOUN
esrj-49829	328	2	control	control	NOUN
esrj-49829	328	3	,	,	PUNCT
esrj-49829	328	4	8	8	NUM
esrj-49829	328	5	,	,	PUNCT
esrj-49829	328	6	338–353	338–353	NUM
esrj-49829	328	7	.	.	PUNCT