id	sid	tid	token	lemma	pos
fcis-2489	1	1	frontiers	frontier	NOUN
fcis-2489	1	2	in	in	ADP
fcis-2489	1	3	computing	computing	NOUN
fcis-2489	1	4	and	and	CCONJ
fcis-2489	1	5	intelligent	intelligent	ADJ
fcis-2489	1	6	systems	system	NOUN
fcis-2489	1	7	issn	issn	VERB
fcis-2489	1	8	:	:	PUNCT
fcis-2489	1	9	2832	2832	NUM
fcis-2489	1	10	-	-	SYM
fcis-2489	1	11	6024	6024	NUM
fcis-2489	1	12	|	|	NOUN
fcis-2489	1	13	vol	vol	NOUN
fcis-2489	1	14	.	.	PROPN
fcis-2489	2	1	2	2	NUM
fcis-2489	2	2	,	,	PUNCT
fcis-2489	2	3	no	no	INTJ
fcis-2489	2	4	.	.	NOUN
fcis-2489	2	5	1	1	NUM
fcis-2489	2	6	,	,	PUNCT
fcis-2489	2	7	2022	2022	NUM
fcis-2489	2	8	26	26	NUM
fcis-2489	2	9	research	research	NOUN
fcis-2489	2	10	of	of	ADP
fcis-2489	2	11	bp	bp	PROPN
fcis-2489	2	12	neural	neural	PROPN
fcis-2489	2	13	network	network	NOUN
fcis-2489	2	14	based	base	VERB
fcis-2489	2	15	on	on	ADP
fcis-2489	2	16	ga	ga	PROPN
fcis-2489	2	17	-	-	PUNCT
fcis-2489	2	18	woa	woa	VERB
fcis-2489	2	19	algorithm	algorithm	NOUN
fcis-2489	2	20	optimization	optimization	NOUN
fcis-2489	2	21	in	in	ADP
fcis-2489	2	22	mbr	mbr	PROPN
fcis-2489	2	23	membrane	membrane	NOUN
fcis-2489	2	24	pollution	pollution	NOUN
fcis-2489	2	25	simulation	simulation	PROPN
fcis-2489	2	26	mengyuan	mengyuan	PROPN
fcis-2489	2	27	wang	wang	PROPN
fcis-2489	2	28	,	,	PUNCT
fcis-2489	2	29	chunqing	chunqe	VERB
fcis-2489	2	30	li	li	PROPN
fcis-2489	2	31	school	school	PROPN
fcis-2489	2	32	of	of	ADP
fcis-2489	2	33	software	software	NOUN
fcis-2489	2	34	,	,	PUNCT
fcis-2489	2	35	tiangong	tiangong	PROPN
fcis-2489	2	36	university	university	PROPN
fcis-2489	2	37	,	,	PUNCT
fcis-2489	2	38	tianjin	tianjin	PROPN
fcis-2489	2	39	300387	300387	NUM
fcis-2489	2	40	,	,	PUNCT
fcis-2489	2	41	china	china	PROPN
fcis-2489	2	42	abstract	abstract	NOUN
fcis-2489	2	43	:	:	PUNCT
fcis-2489	2	44	for	for	ADP
fcis-2489	2	45	the	the	DET
fcis-2489	2	46	membrane	membrane	NOUN
fcis-2489	2	47	fouling	fouling	NOUN
fcis-2489	2	48	problem	problem	NOUN
fcis-2489	2	49	faced	face	VERB
fcis-2489	2	50	by	by	ADP
fcis-2489	2	51	the	the	DET
fcis-2489	2	52	mbr	mbr	PROPN
fcis-2489	2	53	(	(	PUNCT
fcis-2489	2	54	membrane	membrane	NOUN
fcis-2489	2	55	bio	bio	NOUN
fcis-2489	2	56	-	-	NOUN
fcis-2489	2	57	reactor	reactor	NOUN
fcis-2489	2	58	)	)	PUNCT
fcis-2489	2	59	system	system	NOUN
fcis-2489	2	60	,	,	PUNCT
fcis-2489	2	61	an	an	DET
fcis-2489	2	62	intelligent	intelligent	ADJ
fcis-2489	2	63	model	model	NOUN
fcis-2489	2	64	is	be	AUX
fcis-2489	2	65	constructed	construct	VERB
fcis-2489	2	66	to	to	PART
fcis-2489	2	67	predict	predict	VERB
fcis-2489	2	68	the	the	DET
fcis-2489	2	69	membrane	membrane	NOUN
fcis-2489	2	70	fouling	fouling	NOUN
fcis-2489	2	71	.	.	PUNCT
fcis-2489	3	1	the	the	DET
fcis-2489	3	2	bp	bp	PROPN
fcis-2489	3	3	neural	neural	PROPN
fcis-2489	3	4	network	network	NOUN
fcis-2489	3	5	has	have	VERB
fcis-2489	3	6	strong	strong	ADJ
fcis-2489	3	7	self	self	NOUN
fcis-2489	3	8	-	-	PUNCT
fcis-2489	3	9	learning	learning	NOUN
fcis-2489	3	10	,	,	PUNCT
fcis-2489	3	11	self	self	NOUN
fcis-2489	3	12	-	-	PUNCT
fcis-2489	3	13	adaptive	adaptive	ADJ
fcis-2489	3	14	and	and	CCONJ
fcis-2489	3	15	generalization	generalization	NOUN
fcis-2489	3	16	capabilities	capability	NOUN
fcis-2489	3	17	and	and	CCONJ
fcis-2489	3	18	is	be	AUX
fcis-2489	3	19	widely	widely	ADV
fcis-2489	3	20	used	use	VERB
fcis-2489	3	21	in	in	ADP
fcis-2489	3	22	the	the	DET
fcis-2489	3	23	prediction	prediction	NOUN
fcis-2489	3	24	of	of	ADP
fcis-2489	3	25	mbr	mbr	ADJ
fcis-2489	3	26	membrane	membrane	NOUN
fcis-2489	3	27	pollution	pollution	NOUN
fcis-2489	3	28	,	,	PUNCT
fcis-2489	3	29	but	but	CCONJ
fcis-2489	3	30	membrane	membrane	NOUN
fcis-2489	3	31	fouling	fouling	NOUN
fcis-2489	3	32	is	be	AUX
fcis-2489	3	33	a	a	DET
fcis-2489	3	34	complex	complex	ADJ
fcis-2489	3	35	dynamic	dynamic	ADJ
fcis-2489	3	36	process	process	NOUN
fcis-2489	3	37	,	,	PUNCT
fcis-2489	3	38	which	which	PRON
fcis-2489	3	39	is	be	AUX
fcis-2489	3	40	difficult	difficult	ADJ
fcis-2489	3	41	to	to	PART
fcis-2489	3	42	simulate	simulate	VERB
fcis-2489	3	43	accurately	accurately	ADV
fcis-2489	3	44	by	by	ADP
fcis-2489	3	45	classical	classical	ADJ
fcis-2489	3	46	mathematical	mathematical	ADJ
fcis-2489	3	47	models	model	NOUN
fcis-2489	3	48	.	.	PUNCT
fcis-2489	4	1	aiming	aim	VERB
fcis-2489	4	2	at	at	ADP
fcis-2489	4	3	this	this	DET
fcis-2489	4	4	problem	problem	NOUN
fcis-2489	4	5	,	,	PUNCT
fcis-2489	4	6	the	the	DET
fcis-2489	4	7	ga	ga	PROPN
fcis-2489	4	8	-	-	PUNCT
fcis-2489	4	9	woa	woa	VERB
fcis-2489	4	10	hybrid	hybrid	ADJ
fcis-2489	4	11	algorithm	algorithm	NOUN
fcis-2489	4	12	was	be	AUX
fcis-2489	4	13	introduced	introduce	VERB
fcis-2489	4	14	to	to	PART
fcis-2489	4	15	optimize	optimize	VERB
fcis-2489	4	16	the	the	DET
fcis-2489	4	17	bp	bp	PROPN
fcis-2489	4	18	neural	neural	ADJ
fcis-2489	4	19	network	network	NOUN
fcis-2489	4	20	,	,	PUNCT
fcis-2489	4	21	and	and	CCONJ
fcis-2489	4	22	the	the	DET
fcis-2489	4	23	mbr	mbr	PROPN
fcis-2489	4	24	membrane	membrane	NOUN
fcis-2489	4	25	fouling	fouling	NOUN
fcis-2489	4	26	prediction	prediction	NOUN
fcis-2489	4	27	model	model	NOUN
fcis-2489	4	28	was	be	AUX
fcis-2489	4	29	constructed	construct	VERB
fcis-2489	4	30	.	.	PUNCT
fcis-2489	5	1	the	the	DET
fcis-2489	5	2	simulation	simulation	NOUN
fcis-2489	5	3	results	result	NOUN
fcis-2489	5	4	show	show	VERB
fcis-2489	5	5	that	that	SCONJ
fcis-2489	5	6	the	the	DET
fcis-2489	5	7	bp	bp	PROPN
fcis-2489	5	8	neural	neural	PROPN
fcis-2489	5	9	network	network	NOUN
fcis-2489	5	10	model	model	NOUN
fcis-2489	5	11	optimized	optimize	VERB
fcis-2489	5	12	by	by	ADP
fcis-2489	5	13	ga	ga	PROPN
fcis-2489	5	14	-	-	PUNCT
fcis-2489	5	15	woa	woa	VERB
fcis-2489	5	16	hybrid	hybrid	ADJ
fcis-2489	5	17	algorithm	algorithm	NOUN
fcis-2489	5	18	is	be	AUX
fcis-2489	5	19	more	more	ADV
fcis-2489	5	20	suitable	suitable	ADJ
fcis-2489	5	21	and	and	CCONJ
fcis-2489	5	22	accurate	accurate	ADJ
fcis-2489	5	23	than	than	ADP
fcis-2489	5	24	that	that	PRON
fcis-2489	5	25	optimized	optimize	VERB
fcis-2489	5	26	by	by	ADP
fcis-2489	5	27	whale	whale	NOUN
fcis-2489	5	28	optimization	optimization	NOUN
fcis-2489	5	29	algorithm	algorithm	NOUN
fcis-2489	5	30	in	in	ADP
fcis-2489	5	31	predicting	predict	VERB
fcis-2489	5	32	mbr	mbr	ADJ
fcis-2489	5	33	membrane	membrane	NOUN
fcis-2489	5	34	fouling	fouling	NOUN
fcis-2489	5	35	.	.	PUNCT
fcis-2489	6	1	keywords	keyword	NOUN
fcis-2489	6	2	:	:	PUNCT
fcis-2489	6	3	bp	bp	PROPN
fcis-2489	6	4	neural	neural	ADJ
fcis-2489	6	5	network	network	PROPN
fcis-2489	6	6	;	;	PUNCT
fcis-2489	6	7	ga	ga	PROPN
fcis-2489	6	8	-	-	PUNCT
fcis-2489	6	9	woa	woa	VERB
fcis-2489	6	10	hybrid	hybrid	ADJ
fcis-2489	6	11	algorithm	algorithm	NOUN
fcis-2489	6	12	;	;	PUNCT
fcis-2489	6	13	mbr	mbr	NOUN
fcis-2489	6	14	system	system	NOUN
fcis-2489	6	15	.	.	PUNCT
fcis-2489	7	1	1	1	X
fcis-2489	7	2	.	.	X
fcis-2489	7	3	introduction	introduction	NOUN
fcis-2489	7	4	with	with	ADP
fcis-2489	7	5	the	the	DET
fcis-2489	7	6	increase	increase	NOUN
fcis-2489	7	7	of	of	ADP
fcis-2489	7	8	urban	urban	ADJ
fcis-2489	7	9	population	population	NOUN
fcis-2489	7	10	and	and	CCONJ
fcis-2489	7	11	social	social	ADJ
fcis-2489	7	12	economic	economic	ADJ
fcis-2489	7	13	development	development	NOUN
fcis-2489	7	14	,	,	PUNCT
fcis-2489	7	15	the	the	DET
fcis-2489	7	16	social	social	ADJ
fcis-2489	7	17	problem	problem	NOUN
fcis-2489	7	18	of	of	ADP
fcis-2489	7	19	water	water	NOUN
fcis-2489	7	20	scarcity	scarcity	NOUN
fcis-2489	7	21	has	have	AUX
fcis-2489	7	22	become	become	VERB
fcis-2489	7	23	increasingly	increasingly	ADV
fcis-2489	7	24	prominent	prominent	ADJ
fcis-2489	7	25	.	.	PUNCT
fcis-2489	8	1	based	base	VERB
fcis-2489	8	2	on	on	ADP
fcis-2489	8	3	the	the	DET
fcis-2489	8	4	traditional	traditional	ADJ
fcis-2489	8	5	biological	biological	ADJ
fcis-2489	8	6	treatment	treatment	NOUN
fcis-2489	8	7	system	system	NOUN
fcis-2489	8	8	,	,	PUNCT
fcis-2489	8	9	combined	combine	VERB
fcis-2489	8	10	with	with	ADP
fcis-2489	8	11	membrane	membrane	NOUN
fcis-2489	8	12	separation	separation	NOUN
fcis-2489	8	13	technology	technology	NOUN
fcis-2489	8	14	,	,	PUNCT
fcis-2489	8	15	membrane	membrane	NOUN
fcis-2489	8	16	bio	bio	NOUN
fcis-2489	8	17	-	-	NOUN
fcis-2489	8	18	reactor	reactor	NOUN
fcis-2489	8	19	has	have	VERB
fcis-2489	8	20	the	the	DET
fcis-2489	8	21	advantages	advantage	NOUN
fcis-2489	8	22	of	of	ADP
fcis-2489	8	23	small	small	ADJ
fcis-2489	8	24	floor	floor	NOUN
fcis-2489	8	25	area	area	NOUN
fcis-2489	8	26	and	and	CCONJ
fcis-2489	8	27	good	good	ADJ
fcis-2489	8	28	effluent	effluent	ADJ
fcis-2489	8	29	quality	quality	NOUN
fcis-2489	8	30	[	[	X
fcis-2489	8	31	1	1	NUM
fcis-2489	8	32	]	]	PUNCT
fcis-2489	8	33	.	.	PUNCT
fcis-2489	9	1	the	the	DET
fcis-2489	9	2	mbr	mbr	PROPN
fcis-2489	9	3	system	system	NOUN
fcis-2489	9	4	is	be	AUX
fcis-2489	9	5	also	also	ADV
fcis-2489	9	6	widely	widely	ADV
fcis-2489	9	7	used	use	VERB
fcis-2489	9	8	in	in	ADP
fcis-2489	9	9	daily	daily	ADJ
fcis-2489	9	10	sewage	sewage	NOUN
fcis-2489	9	11	treatment	treatment	NOUN
fcis-2489	9	12	process	process	NOUN
fcis-2489	9	13	and	and	CCONJ
fcis-2489	9	14	the	the	DET
fcis-2489	9	15	sewage	sewage	NOUN
fcis-2489	9	16	industrial	industrial	ADJ
fcis-2489	9	17	production	production	NOUN
fcis-2489	9	18	and	and	CCONJ
fcis-2489	9	19	treatment	treatment	NOUN
fcis-2489	9	20	process	process	NOUN
fcis-2489	9	21	.	.	PUNCT
fcis-2489	10	1	the	the	DET
fcis-2489	10	2	mbr	mbr	PROPN
fcis-2489	10	3	system	system	NOUN
fcis-2489	10	4	is	be	AUX
fcis-2489	10	5	mainly	mainly	ADV
fcis-2489	10	6	composed	compose	VERB
fcis-2489	10	7	of	of	ADP
fcis-2489	10	8	membrane	membrane	ADJ
fcis-2489	10	9	biological	biological	ADJ
fcis-2489	10	10	system	system	NOUN
fcis-2489	10	11	and	and	CCONJ
fcis-2489	10	12	membrane	membrane	NOUN
fcis-2489	10	13	modules	module	NOUN
fcis-2489	10	14	[	[	X
fcis-2489	10	15	2	2	NUM
fcis-2489	10	16	]	]	PUNCT
fcis-2489	10	17	.	.	PUNCT
fcis-2489	11	1	when	when	SCONJ
fcis-2489	11	2	the	the	DET
fcis-2489	11	3	mbr	mbr	NOUN
fcis-2489	11	4	system	system	NOUN
fcis-2489	11	5	is	be	AUX
fcis-2489	11	6	running	run	VERB
fcis-2489	11	7	,	,	PUNCT
fcis-2489	11	8	the	the	DET
fcis-2489	11	9	wastewater	wastewater	NOUN
fcis-2489	11	10	flows	flow	VERB
fcis-2489	11	11	to	to	ADP
fcis-2489	11	12	each	each	DET
fcis-2489	11	13	membrane	membrane	NOUN
fcis-2489	11	14	module	module	NOUN
fcis-2489	11	15	,	,	PUNCT
fcis-2489	11	16	and	and	CCONJ
fcis-2489	11	17	the	the	DET
fcis-2489	11	18	membrane	membrane	NOUN
fcis-2489	11	19	modules	module	NOUN
fcis-2489	11	20	will	will	AUX
fcis-2489	11	21	filter	filter	VERB
fcis-2489	11	22	out	out	ADP
fcis-2489	11	23	macro	macro	ADV
fcis-2489	11	24	molecular	molecular	ADJ
fcis-2489	11	25	particles	particle	NOUN
fcis-2489	11	26	to	to	PART
fcis-2489	11	27	achieve	achieve	VERB
fcis-2489	11	28	the	the	DET
fcis-2489	11	29	purpose	purpose	NOUN
fcis-2489	11	30	of	of	ADP
fcis-2489	11	31	filtering	filter	VERB
fcis-2489	11	32	sewage	sewage	NOUN
fcis-2489	11	33	[	[	X
fcis-2489	11	34	3	3	NUM
fcis-2489	11	35	]	]	PUNCT
fcis-2489	11	36	.	.	PUNCT
fcis-2489	12	1	but	but	CCONJ
fcis-2489	12	2	in	in	ADP
fcis-2489	12	3	this	this	DET
fcis-2489	12	4	process	process	NOUN
fcis-2489	12	5	,	,	PUNCT
fcis-2489	12	6	membrane	membrane	NOUN
fcis-2489	12	7	fouling	fouling	NOUN
fcis-2489	12	8	causes	cause	VERB
fcis-2489	12	9	membrane	membrane	NOUN
fcis-2489	12	10	filtration	filtration	NOUN
fcis-2489	12	11	.	.	PUNCT
fcis-2489	13	1	due	due	ADP
fcis-2489	13	2	to	to	ADP
fcis-2489	13	3	the	the	DET
fcis-2489	13	4	serious	serious	ADJ
fcis-2489	13	5	attenuation	attenuation	NOUN
fcis-2489	13	6	of	of	ADP
fcis-2489	13	7	membrane	membrane	NOUN
fcis-2489	13	8	flux	flux	NOUN
fcis-2489	13	9	,	,	PUNCT
fcis-2489	13	10	the	the	DET
fcis-2489	13	11	main	main	ADJ
fcis-2489	13	12	obstacle	obstacle	NOUN
fcis-2489	13	13	to	to	ADP
fcis-2489	13	14	the	the	DET
fcis-2489	13	15	application	application	NOUN
fcis-2489	13	16	of	of	ADP
fcis-2489	13	17	membrane	membrane	NOUN
fcis-2489	13	18	bio	bio	NOUN
fcis-2489	13	19	-	-	NOUN
fcis-2489	13	20	reactor	reactor	NOUN
fcis-2489	13	21	is	be	AUX
fcis-2489	13	22	membrane	membrane	NOUN
fcis-2489	13	23	pollution	pollution	NOUN
fcis-2489	13	24	,	,	PUNCT
fcis-2489	13	25	which	which	PRON
fcis-2489	13	26	seriously	seriously	ADV
fcis-2489	13	27	affects	affect	VERB
fcis-2489	13	28	the	the	DET
fcis-2489	13	29	sewage	sewage	NOUN
fcis-2489	13	30	treatment	treatment	NOUN
fcis-2489	13	31	efficiency	efficiency	NOUN
fcis-2489	13	32	of	of	ADP
fcis-2489	13	33	membrane	membrane	NOUN
fcis-2489	13	34	bio	bio	NOUN
fcis-2489	13	35	-	-	ADJ
fcis-2489	13	36	reactor	reactor	NOUN
fcis-2489	13	37	system	system	NOUN
fcis-2489	13	38	[	[	X
fcis-2489	13	39	4	4	NUM
fcis-2489	13	40	]	]	PUNCT
fcis-2489	13	41	.	.	PUNCT
fcis-2489	14	1	the	the	DET
fcis-2489	14	2	bp	bp	PROPN
fcis-2489	14	3	neural	neural	PROPN
fcis-2489	14	4	network	network	NOUN
fcis-2489	14	5	is	be	AUX
fcis-2489	14	6	used	use	VERB
fcis-2489	14	7	as	as	ADP
fcis-2489	14	8	the	the	DET
fcis-2489	14	9	main	main	ADJ
fcis-2489	14	10	body	body	NOUN
fcis-2489	14	11	of	of	ADP
fcis-2489	14	12	the	the	DET
fcis-2489	14	13	algorithm	algorithm	NOUN
fcis-2489	14	14	,	,	PUNCT
fcis-2489	14	15	and	and	CCONJ
fcis-2489	14	16	genetic	genetic	ADJ
fcis-2489	14	17	and	and	CCONJ
fcis-2489	14	18	whale	whale	NOUN
fcis-2489	14	19	optimization	optimization	NOUN
fcis-2489	14	20	algorithms	algorithm	NOUN
fcis-2489	14	21	are	be	AUX
fcis-2489	14	22	introduced	introduce	VERB
fcis-2489	14	23	to	to	PART
fcis-2489	14	24	optimize	optimize	VERB
fcis-2489	14	25	the	the	DET
fcis-2489	14	26	initial	initial	ADJ
fcis-2489	14	27	weights	weight	NOUN
fcis-2489	14	28	and	and	CCONJ
fcis-2489	14	29	thresholds	threshold	NOUN
fcis-2489	14	30	of	of	ADP
fcis-2489	14	31	bp	bp	PROPN
fcis-2489	14	32	neural	neural	ADJ
fcis-2489	14	33	network	network	NOUN
fcis-2489	15	1	[	[	X
fcis-2489	15	2	5	5	NUM
fcis-2489	15	3	]	]	PUNCT
fcis-2489	15	4	.	.	PUNCT
fcis-2489	16	1	the	the	DET
fcis-2489	16	2	results	result	NOUN
fcis-2489	16	3	show	show	VERB
fcis-2489	16	4	that	that	SCONJ
fcis-2489	16	5	the	the	DET
fcis-2489	16	6	training	training	NOUN
fcis-2489	16	7	efficiency	efficiency	NOUN
fcis-2489	16	8	and	and	CCONJ
fcis-2489	16	9	accuracy	accuracy	NOUN
fcis-2489	16	10	of	of	ADP
fcis-2489	16	11	the	the	DET
fcis-2489	16	12	model	model	NOUN
fcis-2489	16	13	are	be	AUX
fcis-2489	16	14	significantly	significantly	ADV
fcis-2489	16	15	improved	improve	VERB
fcis-2489	16	16	.	.	PUNCT
fcis-2489	17	1	2	2	X
fcis-2489	17	2	.	.	X
fcis-2489	17	3	algorithm	algorithm	NOUN
fcis-2489	17	4	2.1	2.1	NUM
fcis-2489	17	5	.	.	PUNCT
fcis-2489	18	1	genetic	genetic	ADJ
fcis-2489	18	2	algorithm	algorithm	NOUN
fcis-2489	18	3	the	the	DET
fcis-2489	18	4	genetic	genetic	ADJ
fcis-2489	18	5	algorithm	algorithm	NOUN
fcis-2489	18	6	(	(	PUNCT
fcis-2489	18	7	ga	ga	NOUN
fcis-2489	18	8	)	)	PUNCT
fcis-2489	18	9	is	be	AUX
fcis-2489	18	10	a	a	DET
fcis-2489	18	11	computational	computational	ADJ
fcis-2489	18	12	model	model	NOUN
fcis-2489	18	13	of	of	ADP
fcis-2489	18	14	the	the	DET
fcis-2489	18	15	biological	biological	ADJ
fcis-2489	18	16	evolution	evolution	NOUN
fcis-2489	18	17	process	process	NOUN
fcis-2489	18	18	imitating	imitate	VERB
fcis-2489	18	19	the	the	DET
fcis-2489	18	20	natural	natural	ADJ
fcis-2489	18	21	selection	selection	NOUN
fcis-2489	18	22	theory	theory	NOUN
fcis-2489	18	23	and	and	CCONJ
fcis-2489	18	24	genetic	genetic	ADJ
fcis-2489	18	25	principles	principle	NOUN
fcis-2489	18	26	in	in	ADP
fcis-2489	18	27	darwin	darwin	PROPN
fcis-2489	18	28	's	's	PART
fcis-2489	18	29	theory	theory	NOUN
fcis-2489	18	30	of	of	ADP
fcis-2489	18	31	biological	biological	ADJ
fcis-2489	18	32	evolution	evolution	NOUN
fcis-2489	18	33	.	.	PUNCT
fcis-2489	19	1	the	the	DET
fcis-2489	19	2	algorithm	algorithm	NOUN
fcis-2489	19	3	has	have	VERB
fcis-2489	19	4	excellent	excellent	ADJ
fcis-2489	19	5	global	global	ADJ
fcis-2489	19	6	optimization	optimization	NOUN
fcis-2489	19	7	ability	ability	NOUN
fcis-2489	19	8	and	and	CCONJ
fcis-2489	19	9	adaptive	adaptive	ADJ
fcis-2489	19	10	search	search	NOUN
fcis-2489	19	11	direction	direction	NOUN
fcis-2489	19	12	selection	selection	NOUN
fcis-2489	19	13	ability	ability	NOUN
fcis-2489	19	14	,	,	PUNCT
fcis-2489	19	15	and	and	CCONJ
fcis-2489	19	16	finds	find	VERB
fcis-2489	19	17	the	the	DET
fcis-2489	19	18	way	way	NOUN
fcis-2489	19	19	to	to	PART
fcis-2489	19	20	ask	ask	VERB
fcis-2489	19	21	the	the	DET
fcis-2489	19	22	optimal	optimal	ADJ
fcis-2489	19	23	prediction	prediction	NOUN
fcis-2489	19	24	solution	solution	NOUN
fcis-2489	19	25	by	by	ADP
fcis-2489	19	26	imitating	imitate	VERB
fcis-2489	19	27	the	the	DET
fcis-2489	19	28	natural	natural	ADJ
fcis-2489	19	29	evolution	evolution	NOUN
fcis-2489	19	30	process	process	NOUN
fcis-2489	19	31	.	.	PUNCT
fcis-2489	20	1	the	the	DET
fcis-2489	20	2	basic	basic	ADJ
fcis-2489	20	3	operation	operation	NOUN
fcis-2489	20	4	process	process	NOUN
fcis-2489	20	5	is	be	AUX
fcis-2489	20	6	:	:	PUNCT
fcis-2489	20	7	(	(	PUNCT
fcis-2489	20	8	1	1	X
fcis-2489	20	9	)	)	PUNCT
fcis-2489	20	10	using	use	VERB
fcis-2489	20	11	random	random	ADJ
fcis-2489	20	12	methods	method	NOUN
fcis-2489	20	13	or	or	CCONJ
fcis-2489	20	14	other	other	ADJ
fcis-2489	20	15	methods	method	NOUN
fcis-2489	20	16	to	to	PART
fcis-2489	20	17	generate	generate	VERB
fcis-2489	20	18	an	an	DET
fcis-2489	20	19	initial	initial	ADJ
fcis-2489	20	20	population	population	NOUN
fcis-2489	20	21	;	;	PUNCT
fcis-2489	20	22	(	(	PUNCT
fcis-2489	20	23	2	2	X
fcis-2489	20	24	)	)	PUNCT
fcis-2489	20	25	construct	construct	VERB
fcis-2489	20	26	the	the	DET
fcis-2489	20	27	fitness	fitness	NOUN
fcis-2489	20	28	function	function	NOUN
fcis-2489	20	29	according	accord	VERB
fcis-2489	20	30	to	to	ADP
fcis-2489	20	31	the	the	DET
fcis-2489	20	32	objective	objective	ADJ
fcis-2489	20	33	function	function	NOUN
fcis-2489	20	34	of	of	ADP
fcis-2489	20	35	the	the	DET
fcis-2489	20	36	problem	problem	NOUN
fcis-2489	20	37	.	.	PUNCT
fcis-2489	21	1	the	the	DET
fcis-2489	21	2	fitness	fitness	NOUN
fcis-2489	21	3	function	function	NOUN
fcis-2489	21	4	is	be	AUX
fcis-2489	21	5	used	use	VERB
fcis-2489	21	6	to	to	PART
fcis-2489	21	7	characterize	characterize	VERB
fcis-2489	21	8	the	the	DET
fcis-2489	21	9	adaptability	adaptability	NOUN
fcis-2489	21	10	of	of	ADP
fcis-2489	21	11	each	each	DET
fcis-2489	21	12	individual	individual	NOUN
fcis-2489	21	13	of	of	ADP
fcis-2489	21	14	the	the	DET
fcis-2489	21	15	population	population	NOUN
fcis-2489	21	16	to	to	ADP
fcis-2489	21	17	its	its	PRON
fcis-2489	21	18	living	living	NOUN
fcis-2489	21	19	environment	environment	NOUN
fcis-2489	21	20	;	;	PUNCT
fcis-2489	21	21	(	(	PUNCT
fcis-2489	21	22	3	3	X
fcis-2489	21	23	)	)	PUNCT
fcis-2489	21	24	according	accord	VERB
fcis-2489	21	25	to	to	ADP
fcis-2489	21	26	the	the	DET
fcis-2489	21	27	fitness	fitness	NOUN
fcis-2489	21	28	value	value	NOUN
fcis-2489	21	29	,	,	PUNCT
fcis-2489	21	30	it	it	PRON
fcis-2489	21	31	continuously	continuously	ADV
fcis-2489	21	32	selects	select	VERB
fcis-2489	21	33	and	and	CCONJ
fcis-2489	21	34	reproduces	reproduce	NOUN
fcis-2489	21	35	,	,	PUNCT
fcis-2489	21	36	and	and	CCONJ
fcis-2489	21	37	genes	gene	NOUN
fcis-2489	21	38	are	be	AUX
fcis-2489	21	39	updated	update	VERB
fcis-2489	21	40	through	through	ADP
fcis-2489	21	41	crossover	crossover	NOUN
fcis-2489	21	42	and	and	CCONJ
fcis-2489	21	43	mutation	mutation	NOUN
fcis-2489	21	44	;	;	PUNCT
fcis-2489	21	45	(	(	PUNCT
fcis-2489	21	46	4	4	X
fcis-2489	21	47	)	)	PUNCT
fcis-2489	21	48	the	the	DET
fcis-2489	21	49	individual	individual	NOUN
fcis-2489	21	50	with	with	ADP
fcis-2489	21	51	the	the	DET
fcis-2489	21	52	best	good	ADJ
fcis-2489	21	53	fitness	fitness	NOUN
fcis-2489	21	54	value	value	NOUN
fcis-2489	21	55	after	after	SCONJ
fcis-2489	21	56	several	several	ADJ
fcis-2489	21	57	generations	generation	NOUN
fcis-2489	21	58	is	be	AUX
fcis-2489	21	59	the	the	DET
fcis-2489	21	60	optimal	optimal	ADJ
fcis-2489	21	61	solution	solution	NOUN
fcis-2489	21	62	.	.	PUNCT
fcis-2489	22	1	the	the	DET
fcis-2489	22	2	algorithm	algorithm	NOUN
fcis-2489	22	3	flow	flow	NOUN
fcis-2489	22	4	is	be	AUX
fcis-2489	22	5	shown	show	VERB
fcis-2489	22	6	in	in	ADP
fcis-2489	22	7	figure	figure	NOUN
fcis-2489	22	8	1	1	NUM
fcis-2489	22	9	.	.	PUNCT
fcis-2489	23	1	figure	figure	NOUN
fcis-2489	23	2	1	1	NUM
fcis-2489	23	3	.	.	PUNCT
fcis-2489	23	4	ga	ga	PROPN
fcis-2489	23	5	optimizes	optimize	VERB
fcis-2489	23	6	the	the	DET
fcis-2489	23	7	flow	flow	NOUN
fcis-2489	23	8	of	of	ADP
fcis-2489	23	9	bp	bp	PROPN
fcis-2489	23	10	neural	neural	PROPN
fcis-2489	23	11	network	network	PROPN
fcis-2489	23	12	2.2	2.2	NUM
fcis-2489	23	13	.	.	PUNCT
fcis-2489	24	1	optimization	optimization	NOUN
fcis-2489	24	2	algorithm	algorithm	NOUN
fcis-2489	24	3	whale	whale	NOUN
fcis-2489	24	4	optimization	optimization	NOUN
fcis-2489	24	5	algorithm	algorithm	NOUN
fcis-2489	24	6	(	(	PUNCT
fcis-2489	24	7	woa	woa	INTJ
fcis-2489	24	8	)	)	PUNCT
fcis-2489	24	9	is	be	AUX
fcis-2489	24	10	proposed	propose	VERB
fcis-2489	24	11	based	base	VERB
fcis-2489	24	12	on	on	ADP
fcis-2489	24	13	the	the	DET
fcis-2489	24	14	behavior	behavior	NOUN
fcis-2489	24	15	of	of	ADP
fcis-2489	24	16	whales	whale	NOUN
fcis-2489	24	17	to	to	PART
fcis-2489	24	18	hunt	hunt	NOUN
fcis-2489	24	19	prey	prey	NOUN
fcis-2489	24	20	.	.	PUNCT
fcis-2489	25	1	during	during	ADP
fcis-2489	25	2	the	the	DET
fcis-2489	25	3	hunting	hunting	NOUN
fcis-2489	25	4	period	period	NOUN
fcis-2489	25	5	,	,	PUNCT
fcis-2489	25	6	whales	whale	NOUN
fcis-2489	25	7	use	use	VERB
fcis-2489	25	8	mutual	mutual	ADJ
fcis-2489	25	9	cooperation	cooperation	NOUN
fcis-2489	25	10	to	to	PART
fcis-2489	25	11	drive	drive	VERB
fcis-2489	25	12	and	and	CCONJ
fcis-2489	25	13	round	round	VERB
fcis-2489	25	14	up	up	ADP
fcis-2489	25	15	their	their	PRON
fcis-2489	25	16	prey	prey	NOUN
fcis-2489	25	17	.	.	PUNCT
fcis-2489	26	1	the	the	DET
fcis-2489	26	2	whale	whale	NOUN
fcis-2489	26	3	optimization	optimization	NOUN
fcis-2489	26	4	algorithm	algorithm	NOUN
fcis-2489	26	5	divides	divide	VERB
fcis-2489	26	6	the	the	DET
fcis-2489	26	7	algorithm	algorithm	NOUN
fcis-2489	26	8	into	into	ADP
fcis-2489	26	9	three	three	NUM
fcis-2489	26	10	stages	stage	NOUN
fcis-2489	26	11	:	:	PUNCT
fcis-2489	26	12	the	the	DET
fcis-2489	26	13	surrounding	surround	VERB
fcis-2489	26	14	predation	predation	NOUN
fcis-2489	26	15	stage	stage	NOUN
fcis-2489	26	16	,	,	PUNCT
fcis-2489	26	17	the	the	DET
fcis-2489	26	18	spiral	spiral	ADJ
fcis-2489	26	19	renewal	renewal	NOUN
fcis-2489	26	20	stage	stage	NOUN
fcis-2489	26	21	,	,	PUNCT
fcis-2489	26	22	and	and	CCONJ
fcis-2489	26	23	the	the	DET
fcis-2489	26	24	hunting	hunt	VERB
fcis-2489	26	25	stage	stage	NOUN
fcis-2489	26	26	.	.	PUNCT
fcis-2489	27	1	the	the	DET
fcis-2489	27	2	algorithm	algorithm	NOUN
fcis-2489	27	3	27	27	NUM
fcis-2489	27	4	has	have	VERB
fcis-2489	27	5	the	the	DET
fcis-2489	27	6	advantages	advantage	NOUN
fcis-2489	27	7	of	of	ADP
fcis-2489	27	8	less	less	ADJ
fcis-2489	27	9	adjustment	adjustment	NOUN
fcis-2489	27	10	parameters	parameter	NOUN
fcis-2489	27	11	and	and	CCONJ
fcis-2489	27	12	simple	simple	ADJ
fcis-2489	27	13	operation	operation	NOUN
fcis-2489	28	1	[	[	X
fcis-2489	28	2	6	6	NUM
fcis-2489	28	3	]	]	PUNCT
fcis-2489	28	4	.	.	PUNCT
fcis-2489	29	1	2.2.1	2.2.1	NUM
fcis-2489	29	2	.	.	X
fcis-2489	29	3	surrounding	surround	VERB
fcis-2489	29	4	predation	predation	NOUN
fcis-2489	29	5	stage	stage	NOUN
fcis-2489	29	6	during	during	ADP
fcis-2489	29	7	the	the	DET
fcis-2489	29	8	search	search	NOUN
fcis-2489	29	9	for	for	ADP
fcis-2489	29	10	prey	prey	NOUN
fcis-2489	29	11	,	,	PUNCT
fcis-2489	29	12	whales	whale	NOUN
fcis-2489	29	13	constantly	constantly	ADV
fcis-2489	29	14	approach	approach	VERB
fcis-2489	29	15	the	the	DET
fcis-2489	29	16	next	next	ADJ
fcis-2489	29	17	prey	prey	NOUN
fcis-2489	29	18	through	through	ADP
fcis-2489	29	19	continuous	continuous	ADJ
fcis-2489	29	20	communication	communication	NOUN
fcis-2489	29	21	of	of	ADP
fcis-2489	29	22	the	the	DET
fcis-2489	29	23	whole	whole	ADJ
fcis-2489	29	24	group	group	NOUN
fcis-2489	29	25	and	and	CCONJ
fcis-2489	29	26	then	then	ADV
fcis-2489	29	27	try	try	VERB
fcis-2489	29	28	to	to	PART
fcis-2489	29	29	approach	approach	VERB
fcis-2489	29	30	the	the	DET
fcis-2489	29	31	closer	close	ADJ
fcis-2489	29	32	prey	prey	NOUN
fcis-2489	29	33	by	by	ADP
fcis-2489	29	34	random	random	ADJ
fcis-2489	29	35	selection	selection	NOUN
fcis-2489	29	36	.	.	PUNCT
fcis-2489	30	1	the	the	DET
fcis-2489	30	2	mathematical	mathematical	ADJ
fcis-2489	30	3	model	model	NOUN
fcis-2489	30	4	surrounding	surround	VERB
fcis-2489	30	5	the	the	DET
fcis-2489	30	6	predation	predation	NOUN
fcis-2489	30	7	stage	stage	NOUN
fcis-2489	30	8	is	be	AUX
fcis-2489	30	9	:	:	PUNCT
fcis-2489	30	10	d=|c·xp(t)-x(t)|	d=|c·xp(t)-x(t)|	PROPN
fcis-2489	30	11	(	(	PUNCT
fcis-2489	30	12	1	1	NUM
fcis-2489	30	13	)	)	PUNCT
fcis-2489	30	14	x(t+1)=xp(t)-a·d	x(t+1)=xp(t)-a·d	NUM
fcis-2489	30	15	(	(	PUNCT
fcis-2489	30	16	2	2	X
fcis-2489	30	17	)	)	PUNCT
fcis-2489	30	18	we	we	PRON
fcis-2489	30	19	measure	measure	VERB
fcis-2489	30	20	the	the	DET
fcis-2489	30	21	size	size	NOUN
fcis-2489	30	22	of	of	ADP
fcis-2489	30	23	the	the	DET
fcis-2489	30	24	fish	fish	NOUN
fcis-2489	30	25	population	population	NOUN
fcis-2489	30	26	as	as	ADP
fcis-2489	30	27	n	n	NUM
fcis-2489	30	28	,	,	PUNCT
fcis-2489	30	29	ddimension	ddimension	NOUN
fcis-2489	30	30	is	be	AUX
fcis-2489	30	31	the	the	DET
fcis-2489	30	32	search	search	NOUN
fcis-2489	30	33	space	space	NOUN
fcis-2489	30	34	,	,	PUNCT
fcis-2489	30	35	xi=(xi	xi=(xi	PROPN
fcis-2489	30	36	1	1	NUM
fcis-2489	30	37	,	,	PUNCT
fcis-2489	30	38	xi	xi	ADP
fcis-2489	30	39	2	2	NUM
fcis-2489	30	40	,	,	PUNCT
fcis-2489	30	41	…	…	PUNCT
fcis-2489	30	42	,	,	PUNCT
fcis-2489	30	43	xi	xi	X
fcis-2489	30	44	d	d	PROPN
fcis-2489	30	45	)	)	PUNCT
fcis-2489	30	46	,	,	PUNCT
fcis-2489	30	47	i-1	i-1	NUM
fcis-2489	30	48	,	,	PUNCT
fcis-2489	30	49	2	2	NUM
fcis-2489	30	50	,	,	PUNCT
fcis-2489	30	51	…	…	PUNCT
fcis-2489	30	52	,	,	PUNCT
fcis-2489	30	53	n	n	CCONJ
fcis-2489	30	54	,	,	PUNCT
fcis-2489	30	55	is	be	AUX
fcis-2489	30	56	the	the	DET
fcis-2489	30	57	position	position	NOUN
fcis-2489	30	58	of	of	ADP
fcis-2489	30	59	the	the	DET
fcis-2489	30	60	whale	whale	NOUN
fcis-2489	30	61	in	in	ADP
fcis-2489	30	62	d	d	ADJ
fcis-2489	30	63	-	-	ADJ
fcis-2489	30	64	dimension	dimension	NOUN
fcis-2489	30	65	space	space	NOUN
fcis-2489	30	66	,	,	PUNCT
fcis-2489	30	67	and	and	CCONJ
fcis-2489	30	68	the	the	DET
fcis-2489	30	69	global	global	ADJ
fcis-2489	30	70	optimal	optimal	ADJ
fcis-2489	30	71	solution	solution	NOUN
fcis-2489	30	72	to	to	ADP
fcis-2489	30	73	the	the	DET
fcis-2489	30	74	problem	problem	NOUN
fcis-2489	30	75	is	be	AUX
fcis-2489	30	76	the	the	DET
fcis-2489	30	77	position	position	NOUN
fcis-2489	30	78	of	of	ADP
fcis-2489	30	79	the	the	DET
fcis-2489	30	80	corresponding	corresponding	ADJ
fcis-2489	30	81	prey	prey	NOUN
fcis-2489	30	82	.	.	PUNCT
fcis-2489	31	1	where	where	SCONJ
fcis-2489	31	2	,	,	PUNCT
fcis-2489	31	3	t	t	PROPN
fcis-2489	31	4	is	be	AUX
fcis-2489	31	5	the	the	DET
fcis-2489	31	6	current	current	ADJ
fcis-2489	31	7	number	number	NOUN
fcis-2489	31	8	of	of	ADP
fcis-2489	31	9	iterations	iteration	NOUN
fcis-2489	31	10	;	;	PUNCT
fcis-2489	31	11	x(t	x(t	PROPN
fcis-2489	31	12	)	)	PUNCT
fcis-2489	31	13	is	be	AUX
fcis-2489	31	14	ta	ta	ADP
fcis-2489	31	15	single	single	ADJ
fcis-2489	31	16	position	position	NOUN
fcis-2489	31	17	vector	vector	NOUN
fcis-2489	31	18	;	;	PUNCT
fcis-2489	31	19	xp(t	xp(t	NUM
fcis-2489	31	20	)	)	PUNCT
fcis-2489	32	1	is	be	AUX
fcis-2489	32	2	the	the	DET
fcis-2489	32	3	position	position	NOUN
fcis-2489	32	4	vector	vector	NOUN
fcis-2489	32	5	of	of	ADP
fcis-2489	32	6	prey	prey	NOUN
fcis-2489	32	7	(	(	PUNCT
fcis-2489	32	8	current	current	ADJ
fcis-2489	32	9	optimal	optimal	ADJ
fcis-2489	32	10	solution	solution	NOUN
fcis-2489	32	11	)	)	PUNCT
fcis-2489	32	12	;	;	PUNCT
fcis-2489	32	13	a	a	PRON
fcis-2489	32	14	and	and	CCONJ
fcis-2489	32	15	d	d	NOUN
fcis-2489	32	16	are	be	AUX
fcis-2489	32	17	coefficient	coefficient	ADJ
fcis-2489	32	18	vectors	vector	NOUN
fcis-2489	32	19	respectively	respectively	ADV
fcis-2489	32	20	,	,	PUNCT
fcis-2489	32	21	and	and	CCONJ
fcis-2489	32	22	:	:	PUNCT
fcis-2489	32	23	a=2a·r1	a=2a·r1	NOUN
fcis-2489	32	24	-	-	PUNCT
fcis-2489	32	25	a	a	DET
fcis-2489	32	26	(	(	PUNCT
fcis-2489	32	27	3	3	NUM
fcis-2489	32	28	)	)	PUNCT
fcis-2489	32	29	c=2·r2	c=2·r2	NOUN
fcis-2489	32	30	(	(	PUNCT
fcis-2489	32	31	4	4	NUM
fcis-2489	32	32	)	)	PUNCT
fcis-2489	32	33	where	where	SCONJ
fcis-2489	32	34	r1	r1	PROPN
fcis-2489	32	35	and	and	CCONJ
fcis-2489	32	36	r2	r2	PROPN
fcis-2489	32	37	are	be	AUX
fcis-2489	32	38	random	random	ADJ
fcis-2489	32	39	numbers	number	NOUN
fcis-2489	32	40	of	of	ADP
fcis-2489	32	41	[	[	X
fcis-2489	32	42	0,1	0,1	NUM
fcis-2489	32	43	]	]	PUNCT
fcis-2489	32	44	respectively	respectively	ADV
fcis-2489	32	45	;	;	PUNCT
fcis-2489	32	46	a	a	PRON
fcis-2489	32	47	is	be	AUX
fcis-2489	32	48	the	the	DET
fcis-2489	32	49	control	control	NOUN
fcis-2489	32	50	parameter	parameter	NOUN
fcis-2489	32	51	,	,	PUNCT
fcis-2489	32	52	which	which	PRON
fcis-2489	32	53	decreases	decrease	VERB
fcis-2489	32	54	linearly	linearly	ADV
fcis-2489	32	55	from	from	ADP
fcis-2489	32	56	2	2	NUM
fcis-2489	32	57	to	to	ADP
fcis-2489	32	58	0	0	NUM
fcis-2489	32	59	with	with	ADP
fcis-2489	32	60	the	the	DET
fcis-2489	32	61	increase	increase	NOUN
fcis-2489	32	62	of	of	ADP
fcis-2489	32	63	iteration	iteration	NOUN
fcis-2489	32	64	times	time	NOUN
fcis-2489	32	65	,	,	PUNCT
fcis-2489	32	66	that	that	PRON
fcis-2489	32	67	is	be	AUX
fcis-2489	32	68	:	:	PUNCT
fcis-2489	32	69	a(t)=2	a(t)=2	NOUN
fcis-2489	32	70	2	2	NUM
fcis-2489	32	71	t	t	NOUN
fcis-2489	32	72	max_iter	max_iter	NOUN
fcis-2489	32	73	(	(	PUNCT
fcis-2489	32	74	5	5	NUM
fcis-2489	32	75	)	)	PUNCT
fcis-2489	32	76	2.2.2	2.2.2	NUM
fcis-2489	32	77	.	.	PUNCT
fcis-2489	32	78	spiral	spiral	ADJ
fcis-2489	32	79	renewal	renewal	NOUN
fcis-2489	32	80	stage	stage	NOUN
fcis-2489	32	81	at	at	ADP
fcis-2489	32	82	this	this	DET
fcis-2489	32	83	stage	stage	NOUN
fcis-2489	32	84	,	,	PUNCT
fcis-2489	32	85	the	the	DET
fcis-2489	32	86	whale	whale	NOUN
fcis-2489	32	87	uses	use	VERB
fcis-2489	32	88	a	a	DET
fcis-2489	32	89	spiral	spiral	ADJ
fcis-2489	32	90	approach	approach	NOUN
fcis-2489	32	91	to	to	PART
fcis-2489	32	92	approach	approach	VERB
fcis-2489	32	93	the	the	DET
fcis-2489	32	94	prey	prey	NOUN
fcis-2489	32	95	,	,	PUNCT
fcis-2489	32	96	in	in	ADP
fcis-2489	32	97	order	order	NOUN
fcis-2489	32	98	to	to	PART
fcis-2489	32	99	achieve	achieve	VERB
fcis-2489	32	100	the	the	DET
fcis-2489	32	101	purpose	purpose	NOUN
fcis-2489	32	102	of	of	ADP
fcis-2489	32	103	capturing	capture	VERB
fcis-2489	32	104	the	the	DET
fcis-2489	32	105	prey	prey	NOUN
fcis-2489	32	106	.	.	PUNCT
fcis-2489	33	1	before	before	SCONJ
fcis-2489	33	2	the	the	DET
fcis-2489	33	3	individual	individual	ADJ
fcis-2489	33	4	whale	whale	NOUN
fcis-2489	33	5	approaches	approach	VERB
fcis-2489	33	6	the	the	DET
fcis-2489	33	7	prey	prey	NOUN
fcis-2489	33	8	in	in	ADP
fcis-2489	33	9	a	a	DET
fcis-2489	33	10	spiral	spiral	ADJ
fcis-2489	33	11	manner	manner	NOUN
fcis-2489	33	12	,	,	PUNCT
fcis-2489	33	13	it	it	PRON
fcis-2489	33	14	first	first	ADV
fcis-2489	33	15	estimates	estimate	VERB
fcis-2489	33	16	the	the	DET
fcis-2489	33	17	distance	distance	NOUN
fcis-2489	33	18	to	to	ADP
fcis-2489	33	19	the	the	DET
fcis-2489	33	20	prey	prey	NOUN
fcis-2489	33	21	.	.	PUNCT
fcis-2489	34	1	the	the	DET
fcis-2489	34	2	mathematical	mathematical	ADJ
fcis-2489	34	3	model	model	NOUN
fcis-2489	34	4	is	be	AUX
fcis-2489	34	5	:	:	PUNCT
fcis-2489	34	6	x(t+1)=d·ebl·cos(2πl)+xp(t	x(t+1)=d·ebl·cos(2πl)+xp(t	NUM
fcis-2489	34	7	)	)	PUNCT
fcis-2489	34	8	(	(	PUNCT
fcis-2489	34	9	6	6	X
fcis-2489	34	10	)	)	PUNCT
fcis-2489	34	11	b	b	NOUN
fcis-2489	34	12	is	be	AUX
fcis-2489	34	13	the	the	DET
fcis-2489	34	14	constant	constant	ADJ
fcis-2489	34	15	that	that	PRON
fcis-2489	34	16	specifies	specify	VERB
fcis-2489	34	17	the	the	DET
fcis-2489	34	18	shape	shape	NOUN
fcis-2489	34	19	of	of	ADP
fcis-2489	34	20	the	the	DET
fcis-2489	34	21	logarithmic	logarithmic	ADJ
fcis-2489	34	22	helix	helix	NOUN
fcis-2489	34	23	;	;	PUNCT
fcis-2489	34	24	1	1	NUM
fcis-2489	34	25	is	be	AUX
fcis-2489	34	26	a	a	DET
fcis-2489	34	27	random	random	ADJ
fcis-2489	34	28	number	number	NOUN
fcis-2489	34	29	of	of	ADP
fcis-2489	34	30	[	[	X
fcis-2489	34	31	-1	-1	X
fcis-2489	34	32	,	,	PUNCT
fcis-2489	34	33	1	1	NUM
fcis-2489	34	34	]	]	PUNCT
fcis-2489	34	35	.	.	PUNCT
fcis-2489	35	1	among	among	ADP
fcis-2489	35	2	them	they	PRON
fcis-2489	35	3	,	,	PUNCT
fcis-2489	35	4	p	p	NOUN
fcis-2489	35	5	is	be	AUX
fcis-2489	35	6	used	use	VERB
fcis-2489	35	7	to	to	PART
fcis-2489	35	8	determine	determine	VERB
fcis-2489	35	9	the	the	DET
fcis-2489	35	10	probability	probability	NOUN
fcis-2489	35	11	of	of	ADP
fcis-2489	35	12	which	which	DET
fcis-2489	35	13	position	position	NOUN
fcis-2489	35	14	update	update	NOUN
fcis-2489	35	15	method	method	NOUN
fcis-2489	35	16	the	the	DET
fcis-2489	35	17	whale	whale	NOUN
fcis-2489	35	18	individual	individual	NOUN
fcis-2489	35	19	performs	perform	VERB
fcis-2489	35	20	.	.	PUNCT
fcis-2489	36	1	the	the	DET
fcis-2489	36	2	purpose	purpose	NOUN
fcis-2489	36	3	is	be	AUX
fcis-2489	36	4	to	to	PART
fcis-2489	36	5	realize	realize	VERB
fcis-2489	36	6	the	the	DET
fcis-2489	36	7	synchronization	synchronization	NOUN
fcis-2489	36	8	of	of	ADP
fcis-2489	36	9	contraction	contraction	NOUN
fcis-2489	36	10	enclosure	enclosure	NOUN
fcis-2489	36	11	and	and	CCONJ
fcis-2489	36	12	spiral	spiral	ADJ
fcis-2489	36	13	update	update	NOUN
fcis-2489	36	14	.	.	PUNCT
fcis-2489	37	1	its	its	PRON
fcis-2489	37	2	model	model	NOUN
fcis-2489	37	3	is	be	AUX
fcis-2489	37	4	as	as	SCONJ
fcis-2489	37	5	follows	follow	VERB
fcis-2489	37	6	:	:	PUNCT
fcis-2489	37	7	x(t+1)=xp(t)-a·d（p<0.5	x(t+1)=xp(t)-a·d（p<0.5	NOUN
fcis-2489	37	8	）	）	PROPN
fcis-2489	37	9	(	(	PUNCT
fcis-2489	37	10	7	7	NUM
fcis-2489	37	11	)	)	PUNCT
fcis-2489	37	12	x(t+1)=d·ebl·cos(2πl)+xp(t)（p≥0.5	x(t+1)=d·ebl·cos(2πl)+xp(t)（p≥0.5	PROPN
fcis-2489	37	13	）	）	PROPN
fcis-2489	37	14	(	(	PUNCT
fcis-2489	37	15	8)	8)	NUM
fcis-2489	37	16	2.2.3	2.2.3	NUM
fcis-2489	37	17	.	.	PUNCT
fcis-2489	38	1	hunting	hunt	VERB
fcis-2489	38	2	stage	stage	NOUN
fcis-2489	38	3	whales	whale	NOUN
fcis-2489	38	4	use	use	VERB
fcis-2489	38	5	the	the	DET
fcis-2489	38	6	value	value	NOUN
fcis-2489	38	7	of	of	ADP
fcis-2489	38	8	|a|	|a|	NOUN
fcis-2489	38	9	to	to	PART
fcis-2489	38	10	control	control	VERB
fcis-2489	38	11	whether	whether	SCONJ
fcis-2489	38	12	to	to	PART
fcis-2489	38	13	hunt	hunt	VERB
fcis-2489	38	14	for	for	ADP
fcis-2489	38	15	prey	prey	NOUN
fcis-2489	38	16	or	or	CCONJ
fcis-2489	38	17	surround	surround	VERB
fcis-2489	38	18	prey	prey	NOUN
fcis-2489	38	19	.	.	PUNCT
fcis-2489	39	1	the	the	DET
fcis-2489	39	2	model	model	NOUN
fcis-2489	39	3	is	be	AUX
fcis-2489	39	4	as	as	SCONJ
fcis-2489	39	5	follows	follow	VERB
fcis-2489	39	6	:	:	PUNCT
fcis-2489	39	7	d=|c·xrand(t)-x(t)|	d=|c·xrand(t)-x(t)|	VERB
fcis-2489	39	8	(	(	PUNCT
fcis-2489	39	9	9	9	NUM
fcis-2489	39	10	)	)	PUNCT
fcis-2489	39	11	x(t+1)=xrand(t)-a·d	x(t+1)=xrand(t)-a·d	PROPN
fcis-2489	39	12	(	(	PUNCT
fcis-2489	39	13	10	10	NUM
fcis-2489	39	14	)	)	PUNCT
fcis-2489	39	15	2.3	2.3	NUM
fcis-2489	39	16	.	.	PUNCT
fcis-2489	40	1	ga	ga	NOUN
fcis-2489	40	2	-	-	PUNCT
fcis-2489	40	3	woa	woa	VERB
fcis-2489	40	4	hybrid	hybrid	ADJ
fcis-2489	40	5	algorithm	algorithm	NOUN
fcis-2489	40	6	to	to	PART
fcis-2489	40	7	optimize	optimize	VERB
fcis-2489	40	8	bp	bp	PROPN
fcis-2489	40	9	neural	neural	ADJ
fcis-2489	40	10	network	network	NOUN
fcis-2489	40	11	as	as	ADP
fcis-2489	40	12	a	a	DET
fcis-2489	40	13	feed	feed	NOUN
fcis-2489	40	14	-	-	PUNCT
fcis-2489	40	15	forward	forward	ADV
fcis-2489	40	16	neural	neural	ADJ
fcis-2489	40	17	network	network	NOUN
fcis-2489	40	18	,	,	PUNCT
fcis-2489	40	19	bp	bp	PROPN
fcis-2489	40	20	neural	neural	ADJ
fcis-2489	40	21	network	network	NOUN
fcis-2489	40	22	is	be	AUX
fcis-2489	40	23	mainly	mainly	ADV
fcis-2489	40	24	characterized	characterize	VERB
fcis-2489	40	25	by	by	ADP
fcis-2489	40	26	forward	forward	ADJ
fcis-2489	40	27	transmission	transmission	NOUN
fcis-2489	40	28	of	of	ADP
fcis-2489	40	29	signals	signal	NOUN
fcis-2489	40	30	while	while	SCONJ
fcis-2489	40	31	reverse	reverse	VERB
fcis-2489	40	32	transmission	transmission	NOUN
fcis-2489	40	33	of	of	ADP
fcis-2489	40	34	error	error	NOUN
fcis-2489	40	35	information	information	NOUN
fcis-2489	40	36	.	.	PUNCT
fcis-2489	41	1	bp	bp	PROPN
fcis-2489	41	2	neural	neural	PROPN
fcis-2489	41	3	network	network	NOUN
fcis-2489	41	4	has	have	VERB
fcis-2489	41	5	the	the	DET
fcis-2489	41	6	ability	ability	NOUN
fcis-2489	41	7	of	of	ADP
fcis-2489	41	8	self	self	NOUN
fcis-2489	41	9	-	-	PUNCT
fcis-2489	41	10	learning	learning	NOUN
fcis-2489	41	11	and	and	CCONJ
fcis-2489	41	12	generalization	generalization	NOUN
fcis-2489	41	13	,	,	PUNCT
fcis-2489	41	14	so	so	CCONJ
fcis-2489	41	15	it	it	PRON
fcis-2489	41	16	is	be	AUX
fcis-2489	41	17	widely	widely	ADV
fcis-2489	41	18	used	use	VERB
fcis-2489	41	19	,	,	PUNCT
fcis-2489	41	20	but	but	CCONJ
fcis-2489	41	21	it	it	PRON
fcis-2489	41	22	also	also	ADV
fcis-2489	41	23	has	have	VERB
fcis-2489	41	24	disadvantages	disadvantage	NOUN
fcis-2489	41	25	such	such	ADJ
fcis-2489	41	26	as	as	ADP
fcis-2489	41	27	slow	slow	ADJ
fcis-2489	41	28	self	self	NOUN
fcis-2489	41	29	-	-	PUNCT
fcis-2489	41	30	learning	learn	VERB
fcis-2489	41	31	speed	speed	NOUN
fcis-2489	41	32	and	and	CCONJ
fcis-2489	41	33	high	high	ADJ
fcis-2489	41	34	possibility	possibility	NOUN
fcis-2489	41	35	of	of	ADP
fcis-2489	41	36	training	training	NOUN
fcis-2489	41	37	failure	failure	NOUN
fcis-2489	41	38	.	.	PUNCT
fcis-2489	42	1	the	the	DET
fcis-2489	42	2	basic	basic	ADJ
fcis-2489	42	3	idea	idea	NOUN
fcis-2489	42	4	of	of	ADP
fcis-2489	42	5	ga	ga	PROPN
fcis-2489	42	6	-	-	PUNCT
fcis-2489	42	7	woa	woa	VERB
fcis-2489	42	8	hybrid	hybrid	ADJ
fcis-2489	42	9	algorithm	algorithm	NOUN
fcis-2489	42	10	to	to	PART
fcis-2489	42	11	optimize	optimize	VERB
fcis-2489	42	12	the	the	DET
fcis-2489	42	13	bp	bp	PROPN
fcis-2489	42	14	neural	neural	ADJ
fcis-2489	42	15	network	network	NOUN
fcis-2489	42	16	is	be	AUX
fcis-2489	42	17	to	to	PART
fcis-2489	42	18	optimize	optimize	VERB
fcis-2489	42	19	the	the	DET
fcis-2489	42	20	initial	initial	ADJ
fcis-2489	42	21	weights	weight	NOUN
fcis-2489	42	22	and	and	CCONJ
fcis-2489	42	23	thresholds	threshold	NOUN
fcis-2489	42	24	of	of	ADP
fcis-2489	42	25	the	the	DET
fcis-2489	42	26	bp	bp	PROPN
fcis-2489	42	27	neural	neural	PROPN
fcis-2489	42	28	network	network	NOUN
fcis-2489	42	29	through	through	ADP
fcis-2489	42	30	the	the	DET
fcis-2489	42	31	ga	ga	PROPN
fcis-2489	42	32	and	and	CCONJ
fcis-2489	42	33	the	the	DET
fcis-2489	42	34	woa	woa	NOUN
fcis-2489	42	35	,	,	PUNCT
fcis-2489	42	36	thereby	thereby	ADV
fcis-2489	42	37	reducing	reduce	VERB
fcis-2489	42	38	the	the	DET
fcis-2489	42	39	training	training	NOUN
fcis-2489	42	40	error	error	NOUN
fcis-2489	42	41	,	,	PUNCT
fcis-2489	42	42	improve	improve	VERB
fcis-2489	42	43	the	the	DET
fcis-2489	42	44	training	training	NOUN
fcis-2489	42	45	rate	rate	NOUN
fcis-2489	42	46	and	and	CCONJ
fcis-2489	42	47	accuracy	accuracy	NOUN
fcis-2489	42	48	,	,	PUNCT
fcis-2489	42	49	and	and	CCONJ
fcis-2489	42	50	finally	finally	ADV
fcis-2489	42	51	improve	improve	VERB
fcis-2489	42	52	the	the	DET
fcis-2489	42	53	network	network	NOUN
fcis-2489	42	54	detection	detection	NOUN
fcis-2489	42	55	rate	rate	NOUN
fcis-2489	42	56	and	and	CCONJ
fcis-2489	42	57	network	network	NOUN
fcis-2489	42	58	recognition	recognition	NOUN
fcis-2489	42	59	rate	rate	NOUN
fcis-2489	42	60	,	,	PUNCT
fcis-2489	42	61	so	so	SCONJ
fcis-2489	42	62	as	as	SCONJ
fcis-2489	42	63	to	to	PART
fcis-2489	42	64	achieve	achieve	VERB
fcis-2489	42	65	the	the	DET
fcis-2489	42	66	ultimate	ultimate	ADJ
fcis-2489	42	67	goal	goal	NOUN
fcis-2489	42	68	of	of	ADP
fcis-2489	42	69	optimizing	optimize	VERB
fcis-2489	42	70	the	the	DET
fcis-2489	42	71	network	network	NOUN
fcis-2489	42	72	[	[	X
fcis-2489	42	73	7	7	NUM
fcis-2489	42	74	]	]	PUNCT
fcis-2489	42	75	.	.	PUNCT
fcis-2489	43	1	the	the	DET
fcis-2489	43	2	process	process	NOUN
fcis-2489	43	3	is	be	AUX
fcis-2489	43	4	:	:	PUNCT
fcis-2489	43	5	(	(	PUNCT
fcis-2489	43	6	1	1	X
fcis-2489	43	7	)	)	PUNCT
fcis-2489	43	8	the	the	DET
fcis-2489	43	9	neural	neural	ADJ
fcis-2489	43	10	bp	bp	PROPN
fcis-2489	43	11	network	network	NOUN
fcis-2489	43	12	is	be	AUX
fcis-2489	43	13	initialized	initialize	VERB
fcis-2489	43	14	to	to	PART
fcis-2489	43	15	determine	determine	VERB
fcis-2489	43	16	the	the	DET
fcis-2489	43	17	input	input	NOUN
fcis-2489	43	18	-	-	PUNCT
fcis-2489	43	19	output	output	NOUN
fcis-2489	43	20	structure	structure	NOUN
fcis-2489	43	21	,	,	PUNCT
fcis-2489	43	22	initial	initial	ADJ
fcis-2489	43	23	connection	connection	NOUN
fcis-2489	43	24	weight	weight	NOUN
fcis-2489	43	25	and	and	CCONJ
fcis-2489	43	26	threshold	threshold	NOUN
fcis-2489	43	27	of	of	ADP
fcis-2489	43	28	the	the	DET
fcis-2489	43	29	network	network	NOUN
fcis-2489	43	30	;	;	PUNCT
fcis-2489	43	31	(	(	PUNCT
fcis-2489	43	32	2	2	X
fcis-2489	43	33	)	)	PUNCT
fcis-2489	43	34	initialize	initialize	VERB
fcis-2489	43	35	the	the	DET
fcis-2489	43	36	ga	ga	PROPN
fcis-2489	43	37	-	-	PUNCT
fcis-2489	43	38	woa	woa	VERB
fcis-2489	43	39	hybrid	hybrid	ADJ
fcis-2489	43	40	algorithm	algorithm	NOUN
fcis-2489	43	41	and	and	CCONJ
fcis-2489	43	42	encode	encode	VERB
fcis-2489	43	43	the	the	DET
fcis-2489	43	44	initial	initial	ADJ
fcis-2489	43	45	value	value	NOUN
fcis-2489	43	46	of	of	ADP
fcis-2489	43	47	ga	ga	PROPN
fcis-2489	43	48	according	accord	VERB
fcis-2489	43	49	to	to	ADP
fcis-2489	43	50	the	the	DET
fcis-2489	43	51	initial	initial	ADJ
fcis-2489	43	52	value	value	NOUN
fcis-2489	43	53	and	and	CCONJ
fcis-2489	43	54	threshold	threshold	NOUN
fcis-2489	43	55	;	;	PUNCT
fcis-2489	43	56	(	(	PUNCT
fcis-2489	43	57	3	3	X
fcis-2489	43	58	)	)	PUNCT
fcis-2489	43	59	taking	take	VERB
fcis-2489	43	60	the	the	DET
fcis-2489	43	61	training	training	NOUN
fcis-2489	43	62	error	error	NOUN
fcis-2489	43	63	of	of	ADP
fcis-2489	43	64	the	the	DET
fcis-2489	43	65	neural	neural	ADJ
fcis-2489	43	66	bp	bp	PROPN
fcis-2489	43	67	network	network	PROPN
fcis-2489	43	68	as	as	ADP
fcis-2489	43	69	fitness	fitness	NOUN
fcis-2489	43	70	value	value	NOUN
fcis-2489	43	71	,	,	PUNCT
fcis-2489	43	72	selection	selection	NOUN
fcis-2489	43	73	and	and	CCONJ
fcis-2489	43	74	other	other	ADJ
fcis-2489	43	75	operations	operation	NOUN
fcis-2489	43	76	are	be	AUX
fcis-2489	43	77	performed	perform	VERB
fcis-2489	43	78	until	until	SCONJ
fcis-2489	43	79	the	the	DET
fcis-2489	43	80	conditions	condition	NOUN
fcis-2489	43	81	are	be	AUX
fcis-2489	43	82	met	meet	VERB
fcis-2489	43	83	;	;	PUNCT
fcis-2489	43	84	(	(	PUNCT
fcis-2489	43	85	4	4	X
fcis-2489	43	86	)	)	PUNCT
fcis-2489	43	87	obtain	obtain	VERB
fcis-2489	43	88	the	the	DET
fcis-2489	43	89	optimal	optimal	ADJ
fcis-2489	43	90	weights	weight	NOUN
fcis-2489	43	91	and	and	CCONJ
fcis-2489	43	92	thresholds	threshold	NOUN
fcis-2489	43	93	;	;	PUNCT
fcis-2489	43	94	(	(	PUNCT
fcis-2489	43	95	5	5	X
fcis-2489	43	96	)	)	PUNCT
fcis-2489	43	97	calculate	calculate	VERB
fcis-2489	43	98	the	the	DET
fcis-2489	43	99	error	error	NOUN
fcis-2489	43	100	update	update	NOUN
fcis-2489	43	101	weight	weight	NOUN
fcis-2489	43	102	and	and	CCONJ
fcis-2489	43	103	threshold	threshold	NOUN
fcis-2489	43	104	;	;	PUNCT
fcis-2489	43	105	(	(	PUNCT
fcis-2489	43	106	6	6	X
fcis-2489	43	107	)	)	PUNCT
fcis-2489	43	108	output	output	NOUN
fcis-2489	43	109	the	the	DET
fcis-2489	43	110	error	error	NOUN
fcis-2489	43	111	result	result	NOUN
fcis-2489	43	112	.	.	PUNCT
fcis-2489	44	1	the	the	DET
fcis-2489	44	2	algorithm	algorithm	NOUN
fcis-2489	44	3	flow	flow	NOUN
fcis-2489	44	4	chart	chart	NOUN
fcis-2489	44	5	is	be	AUX
fcis-2489	44	6	shown	show	VERB
fcis-2489	44	7	in	in	ADP
fcis-2489	44	8	figure	figure	NOUN
fcis-2489	44	9	2	2	NUM
fcis-2489	44	10	.	.	PUNCT
fcis-2489	44	11	figure	figure	NOUN
fcis-2489	44	12	2	2	NUM
fcis-2489	44	13	.	.	PUNCT
fcis-2489	44	14	ga	ga	PROPN
fcis-2489	44	15	-	-	PUNCT
fcis-2489	44	16	woa	woa	VERB
fcis-2489	44	17	hybrid	hybrid	ADJ
fcis-2489	44	18	algorithm	algorithm	NOUN
fcis-2489	44	19	to	to	PART
fcis-2489	44	20	optimize	optimize	VERB
fcis-2489	44	21	bp	bp	PROPN
fcis-2489	44	22	neural	neural	ADJ
fcis-2489	44	23	network	network	NOUN
fcis-2489	44	24	flow	flow	NOUN
fcis-2489	44	25	chart	chart	NOUN
fcis-2489	44	26	3	3	NUM
fcis-2489	44	27	.	.	X
fcis-2489	44	28	simulation	simulation	NOUN
fcis-2489	44	29	experiment	experiment	NOUN
fcis-2489	44	30	results	result	NOUN
fcis-2489	44	31	and	and	CCONJ
fcis-2489	44	32	analysis	analysis	NOUN
fcis-2489	44	33	this	this	DET
fcis-2489	44	34	experiment	experiment	NOUN
fcis-2489	44	35	selects	select	VERB
fcis-2489	44	36	the	the	DET
fcis-2489	44	37	actual	actual	ADJ
fcis-2489	44	38	mbr	mbr	NOUN
fcis-2489	44	39	system	system	NOUN
fcis-2489	44	40	operating	operate	VERB
fcis-2489	44	41	data	datum	NOUN
fcis-2489	44	42	of	of	ADP
fcis-2489	44	43	shijiazhuang	shijiazhuang	PROPN
fcis-2489	44	44	sewage	sewage	PROPN
fcis-2489	44	45	treatment	treatment	NOUN
fcis-2489	44	46	plant	plant	NOUN
fcis-2489	44	47	.	.	PUNCT
fcis-2489	45	1	the	the	DET
fcis-2489	45	2	filtration	filtration	NOUN
fcis-2489	45	3	membrane	membrane	NOUN
fcis-2489	45	4	is	be	AUX
fcis-2489	45	5	a	a	DET
fcis-2489	45	6	polyvinylidene	polyvinylidene	NOUN
fcis-2489	45	7	fluoride	fluoride	NOUN
fcis-2489	45	8	micro	micro	ADJ
fcis-2489	45	9	filtration	filtration	NOUN
fcis-2489	45	10	membrane	membrane	NOUN
fcis-2489	45	11	with	with	ADP
fcis-2489	45	12	a	a	DET
fcis-2489	45	13	pore	pore	ADJ
fcis-2489	45	14	size	size	NOUN
fcis-2489	45	15	of	of	ADP
fcis-2489	45	16	0.2μm	0.2μm	PROPN
fcis-2489	45	17	.	.	PUNCT
fcis-2489	45	18	35	35	NUM
fcis-2489	45	19	sets	set	NOUN
fcis-2489	45	20	of	of	ADP
fcis-2489	45	21	experimental	experimental	ADJ
fcis-2489	45	22	data	datum	NOUN
fcis-2489	45	23	are	be	AUX
fcis-2489	45	24	used	use	VERB
fcis-2489	45	25	as	as	ADP
fcis-2489	45	26	training	training	NOUN
fcis-2489	45	27	samples	sample	NOUN
fcis-2489	45	28	,	,	PUNCT
fcis-2489	45	29	and	and	CCONJ
fcis-2489	45	30	12	12	NUM
fcis-2489	45	31	sets	set	NOUN
fcis-2489	45	32	of	of	ADP
fcis-2489	45	33	experimental	experimental	ADJ
fcis-2489	45	34	data	datum	NOUN
fcis-2489	45	35	are	be	AUX
fcis-2489	45	36	used	use	VERB
fcis-2489	45	37	as	as	ADP
fcis-2489	45	38	verification	verification	NOUN
fcis-2489	45	39	samples	sample	NOUN
fcis-2489	45	40	.	.	PUNCT
fcis-2489	46	1	figure	figure	NOUN
fcis-2489	46	2	3	3	NUM
fcis-2489	46	3	.	.	NOUN
fcis-2489	46	4	comparison	comparison	NOUN
fcis-2489	46	5	between	between	ADP
fcis-2489	46	6	predicted	predict	VERB
fcis-2489	46	7	value	value	NOUN
fcis-2489	46	8	and	and	CCONJ
fcis-2489	46	9	real	real	ADJ
fcis-2489	46	10	value	value	NOUN
fcis-2489	46	11	of	of	ADP
fcis-2489	46	12	neural	neural	ADJ
fcis-2489	46	13	network	network	NOUN
fcis-2489	46	14	28	28	NUM
fcis-2489	46	15	the	the	DET
fcis-2489	46	16	comparison	comparison	NOUN
fcis-2489	46	17	line	line	NOUN
fcis-2489	46	18	between	between	ADP
fcis-2489	46	19	the	the	DET
fcis-2489	46	20	prediction	prediction	NOUN
fcis-2489	46	21	result	result	NOUN
fcis-2489	46	22	of	of	ADP
fcis-2489	46	23	the	the	DET
fcis-2489	46	24	model	model	NOUN
fcis-2489	46	25	and	and	CCONJ
fcis-2489	46	26	the	the	DET
fcis-2489	46	27	real	real	ADJ
fcis-2489	46	28	value	value	NOUN
fcis-2489	46	29	is	be	AUX
fcis-2489	46	30	shown	show	VERB
fcis-2489	46	31	in	in	ADP
fcis-2489	46	32	figure	figure	NOUN
fcis-2489	46	33	3	3	NUM
fcis-2489	46	34	.	.	PUNCT
fcis-2489	47	1	the	the	DET
fcis-2489	47	2	comparison	comparison	NOUN
fcis-2489	47	3	of	of	ADP
fcis-2489	47	4	the	the	DET
fcis-2489	47	5	two	two	NUM
fcis-2489	47	6	models	model	NOUN
fcis-2489	47	7	from	from	ADP
fcis-2489	47	8	the	the	DET
fcis-2489	47	9	broken	break	VERB
fcis-2489	47	10	line	line	NOUN
fcis-2489	47	11	diagram	diagram	NOUN
fcis-2489	47	12	shows	show	VERB
fcis-2489	47	13	that	that	SCONJ
fcis-2489	47	14	the	the	DET
fcis-2489	47	15	change	change	NOUN
fcis-2489	47	16	trend	trend	NOUN
fcis-2489	47	17	and	and	CCONJ
fcis-2489	47	18	accuracy	accuracy	NOUN
fcis-2489	47	19	of	of	ADP
fcis-2489	47	20	the	the	DET
fcis-2489	47	21	bp	bp	PROPN
fcis-2489	47	22	neural	neural	PROPN
fcis-2489	47	23	networks	network	NOUN
fcis-2489	47	24	model	model	NOUN
fcis-2489	47	25	optimized	optimize	VERB
fcis-2489	47	26	by	by	ADP
fcis-2489	47	27	the	the	DET
fcis-2489	47	28	ga	ga	PROPN
fcis-2489	47	29	-	-	PUNCT
fcis-2489	47	30	woa	woa	VERB
fcis-2489	47	31	hybrid	hybrid	ADJ
fcis-2489	47	32	algorithm	algorithm	NOUN
fcis-2489	47	33	are	be	AUX
fcis-2489	47	34	significantly	significantly	ADV
fcis-2489	47	35	better	well	ADJ
fcis-2489	47	36	than	than	ADP
fcis-2489	47	37	those	those	PRON
fcis-2489	47	38	of	of	ADP
fcis-2489	47	39	bp	bp	PROPN
fcis-2489	47	40	neural	neural	PROPN
fcis-2489	47	41	networks	network	NOUN
fcis-2489	47	42	optimized	optimize	VERB
fcis-2489	47	43	by	by	ADP
fcis-2489	47	44	the	the	DET
fcis-2489	47	45	woa	woa	PROPN
fcis-2489	48	1	.	.	PUNCT
fcis-2489	48	2	figure	figure	NOUN
fcis-2489	48	3	4	4	NUM
fcis-2489	48	4	.	.	PUNCT
fcis-2489	49	1	comparison	comparison	NOUN
fcis-2489	49	2	of	of	ADP
fcis-2489	49	3	model	model	NOUN
fcis-2489	49	4	prediction	prediction	NOUN
fcis-2489	49	5	errorst	errorst	NOUN
fcis-2489	49	6	figure	figure	NOUN
fcis-2489	49	7	4	4	NUM
fcis-2489	49	8	shows	show	VERB
fcis-2489	49	9	the	the	DET
fcis-2489	49	10	prediction	prediction	NOUN
fcis-2489	49	11	error	error	NOUN
fcis-2489	49	12	of	of	ADP
fcis-2489	49	13	woa	woa	PROPN
fcis-2489	49	14	-	-	PUNCT
fcis-2489	49	15	bp	bp	PROPN
fcis-2489	49	16	neural	neural	ADJ
fcis-2489	49	17	network	network	NOUN
fcis-2489	49	18	model	model	NOUN
fcis-2489	49	19	and	and	CCONJ
fcis-2489	49	20	ga	ga	PROPN
fcis-2489	49	21	-	-	PUNCT
fcis-2489	49	22	woa	woa	VERB
fcis-2489	49	23	hybrid	hybrid	ADJ
fcis-2489	49	24	algorithm	algorithm	NOUN
fcis-2489	49	25	to	to	PART
fcis-2489	49	26	optimize	optimize	VERB
fcis-2489	49	27	bp	bp	PROPN
fcis-2489	49	28	neural	neural	PROPN
fcis-2489	49	29	network	network	PROPN
fcis-2489	49	30	model	model	NOUN
fcis-2489	49	31	.	.	PUNCT
fcis-2489	50	1	comparing	compare	VERB
fcis-2489	50	2	the	the	DET
fcis-2489	50	3	prediction	prediction	NOUN
fcis-2489	50	4	errors	error	NOUN
fcis-2489	50	5	of	of	ADP
fcis-2489	50	6	the	the	DET
fcis-2489	50	7	two	two	NUM
fcis-2489	50	8	groups	group	NOUN
fcis-2489	50	9	of	of	ADP
fcis-2489	50	10	models	model	NOUN
fcis-2489	50	11	,	,	PUNCT
fcis-2489	50	12	it	it	PRON
fcis-2489	50	13	can	can	AUX
fcis-2489	50	14	be	be	AUX
fcis-2489	50	15	seen	see	VERB
fcis-2489	50	16	that	that	SCONJ
fcis-2489	50	17	the	the	DET
fcis-2489	50	18	neural	neural	ADJ
fcis-2489	50	19	network	network	NOUN
fcis-2489	50	20	model	model	NOUN
fcis-2489	50	21	optimized	optimize	VERB
fcis-2489	50	22	by	by	ADP
fcis-2489	50	23	ga	ga	PROPN
fcis-2489	50	24	-	-	PUNCT
fcis-2489	50	25	woa	woa	VERB
fcis-2489	50	26	hybrid	hybrid	ADJ
fcis-2489	50	27	algorithm	algorithm	NOUN
fcis-2489	50	28	and	and	CCONJ
fcis-2489	50	29	the	the	DET
fcis-2489	50	30	prediction	prediction	NOUN
fcis-2489	50	31	data	data	NOUN
fcis-2489	50	32	accuracy	accuracy	NOUN
fcis-2489	50	33	are	be	AUX
fcis-2489	50	34	more	more	ADJ
fcis-2489	50	35	than	than	ADP
fcis-2489	50	36	0.95	0.95	NUM
fcis-2489	50	37	.	.	PUNCT
fcis-2489	51	1	the	the	DET
fcis-2489	51	2	broken	broken	ADJ
fcis-2489	51	3	line	line	NOUN
fcis-2489	51	4	diagram	diagram	NOUN
fcis-2489	51	5	shows	show	VERB
fcis-2489	51	6	that	that	SCONJ
fcis-2489	51	7	the	the	DET
fcis-2489	51	8	model	model	NOUN
fcis-2489	51	9	has	have	VERB
fcis-2489	51	10	high	high	ADJ
fcis-2489	51	11	accuracy	accuracy	NOUN
fcis-2489	51	12	and	and	CCONJ
fcis-2489	51	13	achieves	achieve	VERB
fcis-2489	51	14	the	the	DET
fcis-2489	51	15	expected	expect	VERB
fcis-2489	51	16	goal	goal	NOUN
fcis-2489	51	17	of	of	ADP
fcis-2489	51	18	accurately	accurately	ADV
fcis-2489	51	19	predicting	predict	VERB
fcis-2489	51	20	membrane	membrane	NOUN
fcis-2489	51	21	flow	flow	NOUN
fcis-2489	51	22	.	.	PUNCT
fcis-2489	52	1	as	as	SCONJ
fcis-2489	52	2	shown	show	VERB
fcis-2489	52	3	in	in	ADP
fcis-2489	52	4	figure	figure	NOUN
fcis-2489	52	5	5	5	NUM
fcis-2489	52	6	,	,	PUNCT
fcis-2489	52	7	the	the	DET
fcis-2489	52	8	adaptive	adaptive	ADJ
fcis-2489	52	9	convergence	convergence	NOUN
fcis-2489	52	10	curve	curve	NOUN
fcis-2489	52	11	results	result	NOUN
fcis-2489	52	12	of	of	ADP
fcis-2489	52	13	woa	woa	NOUN
fcis-2489	52	14	and	and	CCONJ
fcis-2489	52	15	ga	ga	PROPN
fcis-2489	52	16	-	-	PUNCT
fcis-2489	52	17	woa	woa	VERB
fcis-2489	52	18	hybrid	hybrid	ADJ
fcis-2489	52	19	algorithm	algorithm	NOUN
fcis-2489	52	20	.	.	PUNCT
fcis-2489	53	1	compared	compare	VERB
fcis-2489	53	2	with	with	ADP
fcis-2489	53	3	woa	woa	PROPN
fcis-2489	53	4	,	,	PUNCT
fcis-2489	53	5	ga	ga	PROPN
fcis-2489	53	6	-	-	PUNCT
fcis-2489	53	7	woa	woa	VERB
fcis-2489	53	8	hybrid	hybrid	ADJ
fcis-2489	53	9	algorithm	algorithm	NOUN
fcis-2489	53	10	can	can	AUX
fcis-2489	53	11	be	be	AUX
fcis-2489	53	12	the	the	DET
fcis-2489	53	13	optimal	optimal	ADJ
fcis-2489	53	14	solution	solution	NOUN
fcis-2489	53	15	with	with	ADP
fcis-2489	53	16	the	the	DET
fcis-2489	53	17	least	least	ADJ
fcis-2489	53	18	number	number	NOUN
fcis-2489	53	19	of	of	ADP
fcis-2489	53	20	iterations	iteration	NOUN
fcis-2489	53	21	.	.	PUNCT
fcis-2489	54	1	compared	compare	VERB
fcis-2489	54	2	with	with	ADP
fcis-2489	54	3	ga	ga	PROPN
fcis-2489	54	4	-	-	PUNCT
fcis-2489	54	5	woa	woa	VERB
fcis-2489	54	6	hybrid	hybrid	ADJ
fcis-2489	54	7	algorithm	algorithm	NOUN
fcis-2489	54	8	,	,	PUNCT
fcis-2489	54	9	woa	woa	PROPN
fcis-2489	54	10	has	have	VERB
fcis-2489	54	11	higher	high	ADJ
fcis-2489	54	12	convergence	convergence	NOUN
fcis-2489	54	13	speed	speed	NOUN
fcis-2489	54	14	,	,	PUNCT
fcis-2489	54	15	but	but	CCONJ
fcis-2489	54	16	it	it	PRON
fcis-2489	54	17	has	have	VERB
fcis-2489	54	18	the	the	DET
fcis-2489	54	19	defect	defect	NOUN
fcis-2489	54	20	of	of	ADP
fcis-2489	54	21	exiting	exit	VERB
fcis-2489	54	22	the	the	DET
fcis-2489	54	23	local	local	ADJ
fcis-2489	54	24	optimal	optimal	ADJ
fcis-2489	54	25	resolution	resolution	NOUN
fcis-2489	54	26	.	.	PUNCT
fcis-2489	55	1	the	the	DET
fcis-2489	55	2	results	result	NOUN
fcis-2489	55	3	show	show	VERB
fcis-2489	55	4	that	that	SCONJ
fcis-2489	55	5	ga	ga	PROPN
fcis-2489	55	6	-	-	PUNCT
fcis-2489	55	7	woa	woa	VERB
fcis-2489	55	8	hybrid	hybrid	ADJ
fcis-2489	55	9	algorithm	algorithm	NOUN
fcis-2489	55	10	is	be	AUX
fcis-2489	55	11	more	more	ADV
fcis-2489	55	12	suitable	suitable	ADJ
fcis-2489	55	13	for	for	ADP
fcis-2489	55	14	thin	thin	ADJ
fcis-2489	55	15	film	film	NOUN
fcis-2489	55	16	flow	flow	NOUN
fcis-2489	55	17	prediction	prediction	NOUN
fcis-2489	55	18	.	.	PUNCT
fcis-2489	56	1	figure	figure	NOUN
fcis-2489	56	2	5	5	NUM
fcis-2489	56	3	.	.	PUNCT
fcis-2489	56	4	comparison	comparison	NOUN
fcis-2489	56	5	of	of	ADP
fcis-2489	56	6	model	model	NOUN
fcis-2489	56	7	fitness	fitness	NOUN
fcis-2489	56	8	values	value	NOUN
fcis-2489	56	9	the	the	DET
fcis-2489	56	10	experimental	experimental	ADJ
fcis-2489	56	11	results	result	NOUN
fcis-2489	56	12	show	show	VERB
fcis-2489	56	13	that	that	SCONJ
fcis-2489	56	14	the	the	DET
fcis-2489	56	15	bp	bp	PROPN
fcis-2489	56	16	neural	neural	PROPN
fcis-2489	56	17	network	network	PROPN
fcis-2489	56	18	model	model	NOUN
fcis-2489	56	19	,	,	PUNCT
fcis-2489	56	20	optimized	optimize	VERB
fcis-2489	56	21	by	by	ADP
fcis-2489	56	22	the	the	DET
fcis-2489	56	23	ga	ga	PROPN
fcis-2489	56	24	-	-	PUNCT
fcis-2489	56	25	woa	woa	VERB
fcis-2489	56	26	hybrid	hybrid	ADJ
fcis-2489	56	27	algorithm	algorithm	NOUN
fcis-2489	56	28	,	,	PUNCT
fcis-2489	56	29	is	be	AUX
fcis-2489	56	30	significantly	significantly	ADV
fcis-2489	56	31	improved	improve	VERB
fcis-2489	56	32	in	in	ADP
fcis-2489	56	33	terms	term	NOUN
fcis-2489	56	34	of	of	ADP
fcis-2489	56	35	predictive	predictive	ADJ
fcis-2489	56	36	value	value	NOUN
fcis-2489	56	37	and	and	CCONJ
fcis-2489	56	38	error	error	NOUN
fcis-2489	56	39	value	value	NOUN
fcis-2489	56	40	compared	compare	VERB
fcis-2489	56	41	to	to	ADP
fcis-2489	56	42	the	the	DET
fcis-2489	56	43	original	original	ADJ
fcis-2489	56	44	method	method	NOUN
fcis-2489	56	45	.	.	PUNCT
fcis-2489	57	1	4	4	X
fcis-2489	57	2	.	.	X
fcis-2489	57	3	conclusion	conclusion	NOUN
fcis-2489	57	4	mbr	mbr	PROPN
fcis-2489	57	5	treatment	treatment	NOUN
fcis-2489	57	6	of	of	ADP
fcis-2489	57	7	sewage	sewage	NOUN
fcis-2489	57	8	is	be	AUX
fcis-2489	57	9	a	a	DET
fcis-2489	57	10	complex	complex	ADJ
fcis-2489	57	11	dynamic	dynamic	ADJ
fcis-2489	57	12	process	process	NOUN
fcis-2489	57	13	with	with	ADP
fcis-2489	57	14	multi	multi	ADJ
fcis-2489	57	15	-	-	NOUN
fcis-2489	57	16	process	process	NOUN
fcis-2489	57	17	,	,	PUNCT
fcis-2489	57	18	time	time	NOUN
fcis-2489	57	19	-	-	PUNCT
fcis-2489	57	20	varying	vary	VERB
fcis-2489	57	21	,	,	PUNCT
fcis-2489	57	22	uncertain	uncertain	ADJ
fcis-2489	57	23	and	and	CCONJ
fcis-2489	57	24	other	other	ADJ
fcis-2489	57	25	characteristics	characteristic	NOUN
fcis-2489	57	26	,	,	PUNCT
fcis-2489	57	27	and	and	CCONJ
fcis-2489	57	28	it	it	PRON
fcis-2489	57	29	is	be	AUX
fcis-2489	57	30	difficult	difficult	ADJ
fcis-2489	57	31	to	to	PART
fcis-2489	57	32	model	model	VERB
fcis-2489	57	33	directly	directly	ADV
fcis-2489	57	34	with	with	ADP
fcis-2489	57	35	mathematical	mathematical	ADJ
fcis-2489	57	36	models	model	NOUN
fcis-2489	57	37	.	.	PUNCT
fcis-2489	58	1	the	the	DET
fcis-2489	58	2	genetic	genetic	ADJ
fcis-2489	58	3	algorithm	algorithm	NOUN
fcis-2489	58	4	and	and	CCONJ
fcis-2489	58	5	the	the	DET
fcis-2489	58	6	whale	whale	NOUN
fcis-2489	58	7	algorithm	algorithm	NOUN
fcis-2489	58	8	have	have	VERB
fcis-2489	58	9	the	the	DET
fcis-2489	58	10	advantages	advantage	NOUN
fcis-2489	58	11	of	of	ADP
fcis-2489	58	12	stronger	strong	ADJ
fcis-2489	58	13	search	search	NOUN
fcis-2489	58	14	ability	ability	NOUN
fcis-2489	58	15	and	and	CCONJ
fcis-2489	58	16	the	the	DET
fcis-2489	58	17	ability	ability	NOUN
fcis-2489	58	18	to	to	PART
fcis-2489	58	19	jump	jump	VERB
fcis-2489	58	20	out	out	ADP
fcis-2489	58	21	of	of	ADP
fcis-2489	58	22	the	the	DET
fcis-2489	58	23	local	local	ADJ
fcis-2489	58	24	optimal	optimal	ADJ
fcis-2489	58	25	solution	solution	NOUN
fcis-2489	58	26	.	.	PUNCT
fcis-2489	59	1	therefore	therefore	ADV
fcis-2489	59	2	,	,	PUNCT
fcis-2489	59	3	this	this	DET
fcis-2489	59	4	paper	paper	NOUN
fcis-2489	59	5	proposes	propose	VERB
fcis-2489	59	6	to	to	PART
fcis-2489	59	7	use	use	VERB
fcis-2489	59	8	the	the	DET
fcis-2489	59	9	ga	ga	PROPN
fcis-2489	59	10	-	-	PUNCT
fcis-2489	59	11	woa	woa	VERB
fcis-2489	59	12	hybrid	hybrid	ADJ
fcis-2489	59	13	algorithm	algorithm	NOUN
fcis-2489	59	14	to	to	PART
fcis-2489	59	15	optimize	optimize	VERB
fcis-2489	59	16	the	the	DET
fcis-2489	59	17	bp	bp	PROPN
fcis-2489	59	18	neural	neural	ADJ
fcis-2489	59	19	network	network	NOUN
fcis-2489	59	20	,	,	PUNCT
fcis-2489	59	21	and	and	CCONJ
fcis-2489	59	22	builds	build	VERB
fcis-2489	59	23	a	a	DET
fcis-2489	59	24	membrane	membrane	NOUN
fcis-2489	59	25	fouling	fouling	NOUN
fcis-2489	59	26	prediction	prediction	NOUN
fcis-2489	59	27	model	model	NOUN
fcis-2489	59	28	.	.	PUNCT
fcis-2489	60	1	the	the	DET
fcis-2489	60	2	network	network	NOUN
fcis-2489	60	3	has	have	VERB
fcis-2489	60	4	a	a	DET
fcis-2489	60	5	positive	positive	ADJ
fcis-2489	60	6	effect	effect	NOUN
fcis-2489	60	7	on	on	ADP
fcis-2489	60	8	improving	improve	VERB
fcis-2489	60	9	the	the	DET
fcis-2489	60	10	accuracy	accuracy	NOUN
fcis-2489	60	11	and	and	CCONJ
fcis-2489	60	12	fitness	fitness	NOUN
fcis-2489	60	13	,	,	PUNCT
fcis-2489	60	14	and	and	CCONJ
fcis-2489	60	15	is	be	AUX
fcis-2489	60	16	obviously	obviously	ADV
fcis-2489	60	17	effective	effective	ADJ
fcis-2489	60	18	for	for	ADP
fcis-2489	60	19	model	model	NOUN
fcis-2489	60	20	optimization	optimization	NOUN
fcis-2489	60	21	.	.	PUNCT
fcis-2489	61	1	the	the	DET
fcis-2489	61	2	research	research	NOUN
fcis-2489	61	3	of	of	ADP
fcis-2489	61	4	this	this	DET
fcis-2489	61	5	work	work	NOUN
fcis-2489	61	6	has	have	VERB
fcis-2489	61	7	a	a	DET
fcis-2489	61	8	certain	certain	ADJ
fcis-2489	61	9	theoretical	theoretical	ADJ
fcis-2489	61	10	value	value	NOUN
fcis-2489	61	11	and	and	CCONJ
fcis-2489	61	12	practical	practical	ADJ
fcis-2489	61	13	significance	significance	NOUN
fcis-2489	61	14	and	and	CCONJ
fcis-2489	61	15	provides	provide	VERB
fcis-2489	61	16	a	a	DET
fcis-2489	61	17	certain	certain	ADJ
fcis-2489	61	18	basis	basis	NOUN
fcis-2489	61	19	for	for	ADP
fcis-2489	61	20	the	the	DET
fcis-2489	61	21	related	related	ADJ
fcis-2489	61	22	research	research	NOUN
fcis-2489	61	23	in	in	ADP
fcis-2489	61	24	the	the	DET
fcis-2489	61	25	field	field	NOUN
fcis-2489	61	26	of	of	ADP
fcis-2489	61	27	membrane	membrane	NOUN
fcis-2489	61	28	fouling	fouling	NOUN
fcis-2489	61	29	in	in	ADP
fcis-2489	61	30	the	the	DET
fcis-2489	61	31	mbr	mbr	NOUN
fcis-2489	61	32	in	in	ADP
fcis-2489	61	33	the	the	DET
fcis-2489	61	34	future	future	NOUN
fcis-2489	61	35	.	.	PUNCT
fcis-2489	62	1	references	reference	NOUN
fcis-2489	62	2	[	[	X
fcis-2489	62	3	1	1	NUM
fcis-2489	62	4	]	]	PUNCT
fcis-2489	62	5	xue	xue	PROPN
fcis-2489	62	6	wanze	wanze	PROPN
fcis-2489	62	7	.	.	PUNCT
fcis-2489	63	1	application	application	NOUN
fcis-2489	63	2	of	of	ADP
fcis-2489	63	3	membrane	membrane	NOUN
fcis-2489	63	4	bio	bio	NOUN
fcis-2489	63	5	-	-	NOUN
fcis-2489	63	6	reactor	reactor	NOUN
fcis-2489	63	7	in	in	ADP
fcis-2489	63	8	wastewater	wastewater	NOUN
fcis-2489	63	9	treatment[j	treatment[j	PROPN
fcis-2489	63	10	]	]	PUNCT
fcis-2489	63	11	.	.	PUNCT
fcis-2489	64	1	theoretical	theoretical	ADJ
fcis-2489	64	2	research	research	NOUN
fcis-2489	64	3	in	in	ADP
fcis-2489	64	4	urban	urban	ADJ
fcis-2489	64	5	construction	construction	NOUN
fcis-2489	64	6	,	,	PUNCT
fcis-2489	64	7	2015	2015	NUM
fcis-2489	64	8	,	,	PUNCT
fcis-2489	64	9	5(34	5(34	NUM
fcis-2489	64	10	)	)	PUNCT
fcis-2489	64	11	.	.	PUNCT
fcis-2489	65	1	[	[	X
fcis-2489	65	2	2	2	NUM
fcis-2489	65	3	]	]	X
fcis-2489	65	4	zhang	zhang	PROPN
fcis-2489	65	5	y	y	PROPN
fcis-2489	65	6	,	,	PUNCT
fcis-2489	65	7	chen	chen	PROPN
fcis-2489	65	8	z	z	PROPN
fcis-2489	65	9	,	,	PUNCT
fcis-2489	65	10	an	an	DET
fcis-2489	65	11	w	w	PROPN
fcis-2489	65	12	,	,	PUNCT
fcis-2489	65	13	et	et	PROPN
fcis-2489	65	14	al	al	PROPN
fcis-2489	65	15	.	.	PROPN
fcis-2489	65	16	membrane	membrane	NOUN
fcis-2489	65	17	integrity	integrity	NOUN
fcis-2489	65	18	risk	risk	NOUN
fcis-2489	65	19	assessment	assessment	NOUN
fcis-2489	65	20	of	of	ADP
fcis-2489	65	21	fully	fully	ADV
fcis-2489	65	22	installed	instal	VERB
fcis-2489	65	23	mbr	mbr	PROPN
fcis-2489	65	24	sewage	sewage	NOUN
fcis-2489	65	25	treatment	treatment	NOUN
fcis-2489	65	26	plant[j	plant[j	NOUN
fcis-2489	65	27	]	]	PUNCT
fcis-2489	65	28	.	.	PUNCT
fcis-2489	66	1	journal	journal	PROPN
fcis-2489	66	2	of	of	ADP
fcis-2489	66	3	environmental	environmental	ADJ
fcis-2489	66	4	sciences	science	NOUN
fcis-2489	66	5	,	,	PUNCT
fcis-2489	66	6	2015	2015	NUM
fcis-2489	66	7	.	.	PUNCT
fcis-2489	67	1	[	[	X
fcis-2489	67	2	3	3	X
fcis-2489	67	3	]	]	X
fcis-2489	67	4	tang	tang	X
fcis-2489	67	5	chaochun	chaochun	PROPN
fcis-2489	67	6	,	,	PUNCT
fcis-2489	67	7	duanxianyue	duanxianyue	NOUN
fcis-2489	67	8	,	,	PUNCT
fcis-2489	67	9	ye	ye	PROPN
fcis-2489	67	10	xin	xin	PROPN
fcis-2489	67	11	,	,	PUNCT
fcis-2489	67	12	et	et	PROPN
fcis-2489	67	13	al	al	PROPN
fcis-2489	67	14	.	.	PUNCT
fcis-2489	67	15	research	research	NOUN
fcis-2489	67	16	progress	progress	NOUN
fcis-2489	67	17	on	on	ADP
fcis-2489	67	18	the	the	DET
fcis-2489	67	19	mechanism	mechanism	NOUN
fcis-2489	67	20	and	and	CCONJ
fcis-2489	67	21	influencing	influence	VERB
fcis-2489	67	22	factors	factor	NOUN
fcis-2489	67	23	of	of	ADP
fcis-2489	67	24	mbr	mbr	ADJ
fcis-2489	67	25	membrane	membrane	NOUN
fcis-2489	67	26	fouling[j	fouling[j	NOUN
fcis-2489	67	27	]	]	PUNCT
fcis-2489	67	28	.	.	PUNCT
fcis-2489	68	1	industrial	industrial	ADJ
fcis-2489	68	2	water	water	NOUN
fcis-2489	68	3	treatment	treatment	NOUN
fcis-2489	68	4	,	,	PUNCT
fcis-2489	68	5	2017	2017	NUM
fcis-2489	68	6	,	,	PUNCT
fcis-2489	68	7	37(4):4	37(4):4	PROPN
fcis-2489	68	8	.	.	PUNCT
fcis-2489	69	1	[	[	X
fcis-2489	69	2	4	4	NUM
fcis-2489	69	3	]	]	X
fcis-2489	69	4	han	han	PROPN
fcis-2489	69	5	yongping	yongping	PROPN
fcis-2489	69	6	,	,	PUNCT
fcis-2489	69	7	xiao	xiao	PROPN
fcis-2489	69	8	yan	yan	PROPN
fcis-2489	69	9	,	,	PUNCT
fcis-2489	69	10	song	song	PROPN
fcis-2489	69	11	lei	lei	PROPN
fcis-2489	69	12	,	,	PUNCT
fcis-2489	69	13	et	et	PROPN
fcis-2489	69	14	al	al	PROPN
fcis-2489	69	15	.	.	PUNCT
fcis-2489	70	1	research	research	NOUN
fcis-2489	70	2	progress	progress	NOUN
fcis-2489	70	3	on	on	ADP
fcis-2489	70	4	the	the	DET
fcis-2489	70	5	formation	formation	NOUN
fcis-2489	70	6	of	of	ADP
fcis-2489	70	7	mbr	mbr	PRON
fcis-2489	70	8	membrane	membrane	NOUN
fcis-2489	70	9	fouling	fouling	NOUN
fcis-2489	70	10	and	and	CCONJ
fcis-2489	70	11	its	its	PRON
fcis-2489	70	12	influencing	influence	VERB
fcis-2489	70	13	factors[j	factors[j	PROPN
fcis-2489	70	14	]	]	PUNCT
fcis-2489	70	15	.	.	PUNCT
fcis-2489	71	1	membrane	membrane	NOUN
fcis-2489	71	2	science	science	NOUN
fcis-2489	71	3	and	and	CCONJ
fcis-2489	71	4	technology	technology	NOUN
fcis-2489	71	5	,	,	PUNCT
fcis-2489	71	6	2013(1):9	2013(1):9	PROPN
fcis-2489	71	7	.	.	PUNCT
fcis-2489	72	1	[	[	X
fcis-2489	72	2	5	5	X
fcis-2489	72	3	]	]	X
fcis-2489	72	4	kaneko	kaneko	PROPN
fcis-2489	72	5	h	h	PROPN
fcis-2489	72	6	,	,	PUNCT
fcis-2489	72	7	funatsu	funatsu	PROPN
fcis-2489	72	8	k.	k.	PROPN
fcis-2489	72	9	physical	physical	PROPN
fcis-2489	72	10	and	and	CCONJ
fcis-2489	72	11	statistical	statistical	ADJ
fcis-2489	72	12	model	model	NOUN
fcis-2489	72	13	for	for	ADP
fcis-2489	72	14	predicting	predict	VERB
fcis-2489	72	15	a	a	DET
fcis-2489	72	16	transmembrane	transmembrane	ADJ
fcis-2489	72	17	pressure	pressure	NOUN
fcis-2489	72	18	jump	jump	NOUN
fcis-2489	72	19	for	for	ADP
fcis-2489	72	20	a	a	DET
fcis-2489	72	21	membrane	membrane	NOUN
fcis-2489	72	22	bioreactor[j	bioreactor[j	NOUN
fcis-2489	72	23	]	]	PUNCT
fcis-2489	72	24	.	.	PUNCT
fcis-2489	73	1	chemometrics	chemometric	NOUN
fcis-2489	73	2	&	&	CCONJ
fcis-2489	73	3	intelligent	intelligent	ADJ
fcis-2489	73	4	laboratory	laboratory	NOUN
fcis-2489	73	5	systems	system	NOUN
fcis-2489	73	6	,	,	PUNCT
fcis-2489	73	7	2013	2013	NUM
fcis-2489	73	8	,	,	PUNCT
fcis-2489	73	9	121(complete):66	121(complete):66	NUM
fcis-2489	73	10	-	-	SYM
fcis-2489	73	11	74	74	NUM
fcis-2489	73	12	.	.	PUNCT
fcis-2489	74	1	[	[	X
fcis-2489	74	2	6	6	NUM
fcis-2489	74	3	]	]	PUNCT
fcis-2489	74	4	ma	ma	PROPN
fcis-2489	74	5	chuang	chuang	PROPN
fcis-2489	74	6	,	,	PUNCT
fcis-2489	74	7	zhou	zhou	PROPN
fcis-2489	74	8	daiqi	daiqi	PROPN
fcis-2489	74	9	,	,	PUNCT
fcis-2489	74	10	zhang	zhang	PROPN
fcis-2489	74	11	ye	ye	PROPN
fcis-2489	74	12	.	.	PROPN
fcis-2489	74	13	bp	bp	PROPN
fcis-2489	74	14	neural	neural	PROPN
fcis-2489	74	15	network	network	NOUN
fcis-2489	74	16	water	water	NOUN
fcis-2489	74	17	resource	resource	NOUN
fcis-2489	74	18	demand	demand	NOUN
fcis-2489	74	19	forecasting	forecasting	NOUN
fcis-2489	74	20	method	method	NOUN
fcis-2489	74	21	based	base	VERB
fcis-2489	74	22	on	on	ADP
fcis-2489	74	23	improved	improved	ADJ
fcis-2489	74	24	whale	whale	NOUN
fcis-2489	74	25	algorithm[j	algorithm[j	PROPN
fcis-2489	74	26	]	]	PUNCT
fcis-2489	74	27	.	.	PUNCT
fcis-2489	75	1	computer	computer	NOUN
fcis-2489	75	2	science	science	NOUN
fcis-2489	75	3	,	,	PUNCT
fcis-2489	75	4	2020	2020	NUM
fcis-2489	75	5	,	,	PUNCT
fcis-2489	75	6	47(s02):5	47(s02):5	NUM
fcis-2489	75	7	.	.	PUNCT
fcis-2489	76	1	[	[	X
fcis-2489	76	2	7	7	X
fcis-2489	76	3	]	]	X
fcis-2489	76	4	chen	chen	PROPN
fcis-2489	76	5	zhiwei	zhiwei	PROPN
fcis-2489	76	6	.	.	PUNCT
fcis-2489	76	7	soil	soil	NOUN
fcis-2489	76	8	parameter	parameter	PROPN
fcis-2489	76	9	prediction	prediction	NOUN
fcis-2489	76	10	based	base	VERB
fcis-2489	76	11	on	on	ADP
fcis-2489	76	12	genetic	genetic	ADJ
fcis-2489	76	13	algorithm	algorithm	NOUN
fcis-2489	76	14	-	-	PUNCT
fcis-2489	76	15	whale	whale	NOUN
fcis-2489	76	16	algorithm	algorithm	NOUN
fcis-2489	76	17	optimizing	optimize	VERB
fcis-2489	76	18	backpropagation	backpropagation	NOUN
fcis-2489	76	19	neural	neural	ADJ
fcis-2489	76	20	network[j	network[j	PROPN
fcis-2489	76	21	]	]	PUNCT
fcis-2489	76	22	.	.	PUNCT
fcis-2489	77	1	zhejiang	zhejiang	PROPN
fcis-2489	77	2	agricultural	agricultural	PROPN
fcis-2489	77	3	science	science	PROPN
fcis-2489	77	4	,	,	PUNCT
fcis-2489	77	5	2019	2019	NUM
fcis-2489	77	6	,	,	PUNCT
fcis-2489	77	7	60(1):5	60(1):5	PROPN
fcis-2489	77	8	.	.	PUNCT