id	sid	tid	token	lemma	pos
ajst-19160	1	1	academic	academic	ADJ
ajst-19160	1	2	journal	journal	NOUN
ajst-19160	1	3	of	of	ADP
ajst-19160	1	4	science	science	NOUN
ajst-19160	1	5	and	and	CCONJ
ajst-19160	1	6	technology	technology	NOUN
ajst-19160	1	7	issn	issn	NOUN
ajst-19160	1	8	:	:	PUNCT
ajst-19160	1	9	2771	2771	NUM
ajst-19160	1	10	-	-	SYM
ajst-19160	1	11	3032	3032	NUM
ajst-19160	1	12	|	|	NOUN
ajst-19160	1	13	vol	vol	NOUN
ajst-19160	1	14	.	.	PROPN
ajst-19160	2	1	10	10	NUM
ajst-19160	2	2	,	,	PUNCT
ajst-19160	2	3	no	no	INTJ
ajst-19160	2	4	.	.	NOUN
ajst-19160	2	5	1	1	NUM
ajst-19160	2	6	,	,	PUNCT
ajst-19160	2	7	2024	2024	NUM
ajst-19160	2	8	118	118	NUM
ajst-19160	2	9	application	application	NOUN
ajst-19160	2	10	of	of	ADP
ajst-19160	2	11	improved	improved	ADJ
ajst-19160	2	12	support	support	NOUN
ajst-19160	2	13	vector	vector	NOUN
ajst-19160	2	14	machine	machine	NOUN
ajst-19160	2	15	in	in	ADP
ajst-19160	2	16	predicting	predict	VERB
ajst-19160	2	17	failure	failure	NOUN
ajst-19160	2	18	pressure	pressure	NOUN
ajst-19160	2	19	of	of	ADP
ajst-19160	2	20	oil	oil	NOUN
ajst-19160	2	21	and	and	CCONJ
ajst-19160	2	22	gas	gas	NOUN
ajst-19160	2	23	pipelines	pipeline	NOUN
ajst-19160	2	24	with	with	ADP
ajst-19160	2	25	internal	internal	ADJ
ajst-19160	2	26	corrosion	corrosion	NOUN
ajst-19160	2	27	defects	defect	NOUN
ajst-19160	2	28	wei	wei	PROPN
ajst-19160	2	29	yuan	yuan	PROPN
ajst-19160	2	30	,	,	PUNCT
ajst-19160	2	31	liang	liang	PROPN
ajst-19160	2	32	zhang	zhang	PROPN
ajst-19160	3	1	*	*	PROPN
ajst-19160	3	2	,	,	PUNCT
ajst-19160	3	3	hao	hao	PROPN
ajst-19160	3	4	ren	ren	PROPN
ajst-19160	3	5	school	school	PROPN
ajst-19160	3	6	of	of	ADP
ajst-19160	3	7	mechanical	mechanical	ADJ
ajst-19160	3	8	engineering	engineering	NOUN
ajst-19160	3	9	,	,	PUNCT
ajst-19160	3	10	southwest	southwest	ADJ
ajst-19160	3	11	petroleum	petroleum	PROPN
ajst-19160	3	12	university	university	PROPN
ajst-19160	3	13	,	,	PUNCT
ajst-19160	3	14	chengdu	chengdu	PROPN
ajst-19160	3	15	sichuan	sichuan	PROPN
ajst-19160	3	16	610500	610500	NUM
ajst-19160	3	17	,	,	PUNCT
ajst-19160	3	18	china	china	PROPN
ajst-19160	3	19	*	*	PUNCT
ajst-19160	3	20	corresponding	correspond	VERB
ajst-19160	3	21	author	author	NOUN
ajst-19160	3	22	:	:	PUNCT
ajst-19160	3	23	liang	liang	PROPN
ajst-19160	3	24	zhang	zhang	PROPN
ajst-19160	3	25	abstract	abstract	PROPN
ajst-19160	3	26	:	:	PUNCT
ajst-19160	3	27	in	in	ADP
ajst-19160	3	28	this	this	DET
ajst-19160	3	29	study	study	NOUN
ajst-19160	3	30	,	,	PUNCT
ajst-19160	3	31	the	the	DET
ajst-19160	3	32	failure	failure	NOUN
ajst-19160	3	33	pressure	pressure	NOUN
ajst-19160	3	34	of	of	ADP
ajst-19160	3	35	submarine	submarine	NOUN
ajst-19160	3	36	oil	oil	NOUN
ajst-19160	3	37	and	and	CCONJ
ajst-19160	3	38	gas	gas	NOUN
ajst-19160	3	39	pipelines	pipeline	NOUN
ajst-19160	3	40	was	be	AUX
ajst-19160	3	41	predicted	predict	VERB
ajst-19160	3	42	by	by	ADP
ajst-19160	3	43	using	use	VERB
ajst-19160	3	44	five	five	NUM
ajst-19160	3	45	commonly	commonly	ADV
ajst-19160	3	46	used	use	VERB
ajst-19160	3	47	machine	machine	NOUN
ajst-19160	3	48	learning	learning	NOUN
ajst-19160	3	49	models	model	NOUN
ajst-19160	3	50	and	and	CCONJ
ajst-19160	3	51	derivative	derivative	ADJ
ajst-19160	3	52	models	model	NOUN
ajst-19160	3	53	.	.	PUNCT
ajst-19160	4	1	firstly	firstly	ADV
ajst-19160	4	2	,	,	PUNCT
ajst-19160	4	3	an	an	DET
ajst-19160	4	4	efficient	efficient	ADJ
ajst-19160	4	5	local	local	ADJ
ajst-19160	4	6	time	time	NOUN
ajst-19160	4	7	-	-	PUNCT
ajst-19160	4	8	intensive	intensive	ADJ
ajst-19160	4	9	finite	finite	ADJ
ajst-19160	4	10	element	element	NOUN
ajst-19160	4	11	algorithm	algorithm	NOUN
ajst-19160	4	12	is	be	AUX
ajst-19160	4	13	constructed	construct	VERB
ajst-19160	4	14	and	and	CCONJ
ajst-19160	4	15	used	use	VERB
ajst-19160	4	16	to	to	PART
ajst-19160	4	17	generate	generate	VERB
ajst-19160	4	18	a	a	DET
ajst-19160	4	19	machine	machine	NOUN
ajst-19160	4	20	learning	learn	VERB
ajst-19160	4	21	database	database	NOUN
ajst-19160	4	22	.	.	PUNCT
ajst-19160	5	1	secondly	secondly	ADV
ajst-19160	5	2	,	,	PUNCT
ajst-19160	5	3	in	in	ADP
ajst-19160	5	4	order	order	NOUN
ajst-19160	5	5	to	to	PART
ajst-19160	5	6	improve	improve	VERB
ajst-19160	5	7	the	the	DET
ajst-19160	5	8	accuracy	accuracy	NOUN
ajst-19160	5	9	of	of	ADP
ajst-19160	5	10	machine	machine	NOUN
ajst-19160	5	11	learning	learning	NOUN
ajst-19160	5	12	algorithm	algorithm	NOUN
ajst-19160	5	13	,	,	PUNCT
ajst-19160	5	14	the	the	DET
ajst-19160	5	15	frontier	frontier	NOUN
ajst-19160	5	16	optimization	optimization	NOUN
ajst-19160	5	17	algorithm	algorithm	NOUN
ajst-19160	5	18	is	be	AUX
ajst-19160	5	19	improved	improve	VERB
ajst-19160	5	20	to	to	PART
ajst-19160	5	21	form	form	VERB
ajst-19160	5	22	a	a	DET
ajst-19160	5	23	new	new	ADJ
ajst-19160	5	24	predictive	predictive	ADJ
ajst-19160	5	25	regression	regression	NOUN
ajst-19160	5	26	model	model	NOUN
ajst-19160	5	27	iaeo	iaeo	PROPN
ajst-19160	5	28	-	-	PUNCT
ajst-19160	5	29	svm	svm	PROPN
ajst-19160	5	30	model	model	NOUN
ajst-19160	5	31	.	.	PUNCT
ajst-19160	6	1	to	to	PART
ajst-19160	6	2	compare	compare	VERB
ajst-19160	6	3	the	the	DET
ajst-19160	6	4	accuracy	accuracy	NOUN
ajst-19160	6	5	of	of	ADP
ajst-19160	6	6	commonly	commonly	ADV
ajst-19160	6	7	used	use	VERB
ajst-19160	6	8	machine	machine	NOUN
ajst-19160	6	9	learning	learning	NOUN
ajst-19160	6	10	models	model	NOUN
ajst-19160	6	11	and	and	CCONJ
ajst-19160	6	12	iaeo	iaeo	NOUN
ajst-19160	6	13	-	-	PUNCT
ajst-19160	6	14	svm	svm	NOUN
ajst-19160	6	15	models	model	NOUN
ajst-19160	6	16	,	,	PUNCT
ajst-19160	6	17	a	a	DET
ajst-19160	6	18	comprehensive	comprehensive	ADJ
ajst-19160	6	19	evaluation	evaluation	NOUN
ajst-19160	6	20	standard	standard	NOUN
ajst-19160	6	21	consisting	consist	VERB
ajst-19160	6	22	of	of	ADP
ajst-19160	6	23	k	k	ADJ
ajst-19160	6	24	-	-	ADJ
ajst-19160	6	25	fold	fold	ADJ
ajst-19160	6	26	cross	cross	NOUN
ajst-19160	6	27	-	-	NOUN
ajst-19160	6	28	validation	validation	ADJ
ajst-19160	6	29	and	and	CCONJ
ajst-19160	6	30	three	three	NUM
ajst-19160	6	31	statistical	statistical	ADJ
ajst-19160	6	32	indicators	indicator	NOUN
ajst-19160	6	33	was	be	AUX
ajst-19160	6	34	used	use	VERB
ajst-19160	6	35	.	.	PUNCT
ajst-19160	7	1	finally	finally	ADV
ajst-19160	7	2	,	,	PUNCT
ajst-19160	7	3	the	the	DET
ajst-19160	7	4	influence	influence	NOUN
ajst-19160	7	5	of	of	ADP
ajst-19160	7	6	seawater	seawater	NOUN
ajst-19160	7	7	depth	depth	NOUN
ajst-19160	7	8	and	and	CCONJ
ajst-19160	7	9	geometric	geometric	ADJ
ajst-19160	7	10	factors	factor	NOUN
ajst-19160	7	11	of	of	ADP
ajst-19160	7	12	corrosion	corrosion	NOUN
ajst-19160	7	13	defects	defect	NOUN
ajst-19160	7	14	on	on	ADP
ajst-19160	7	15	the	the	DET
ajst-19160	7	16	blasting	blast	VERB
ajst-19160	7	17	pressure	pressure	NOUN
ajst-19160	7	18	of	of	ADP
ajst-19160	7	19	submarine	submarine	NOUN
ajst-19160	7	20	oil	oil	NOUN
ajst-19160	7	21	and	and	CCONJ
ajst-19160	7	22	gas	gas	NOUN
ajst-19160	7	23	pipelines	pipeline	NOUN
ajst-19160	7	24	was	be	AUX
ajst-19160	7	25	comprehensively	comprehensively	ADV
ajst-19160	7	26	analyzed	analyze	VERB
ajst-19160	7	27	through	through	ADP
ajst-19160	7	28	the	the	DET
ajst-19160	7	29	highdimensional	highdimensional	ADJ
ajst-19160	7	30	surface	surface	NOUN
ajst-19160	7	31	built	build	VERB
ajst-19160	7	32	by	by	ADP
ajst-19160	7	33	the	the	DET
ajst-19160	7	34	iaeo	iaeo	NOUN
ajst-19160	7	35	-	-	PUNCT
ajst-19160	7	36	svm	svm	PROPN
ajst-19160	7	37	model	model	NOUN
ajst-19160	7	38	.	.	PUNCT
ajst-19160	8	1	the	the	DET
ajst-19160	8	2	iaeo	iaeo	NOUN
ajst-19160	8	3	-	-	PUNCT
ajst-19160	8	4	svm	svm	PROPN
ajst-19160	8	5	model	model	NOUN
ajst-19160	8	6	shows	show	VERB
ajst-19160	8	7	superior	superior	ADJ
ajst-19160	8	8	stability	stability	NOUN
ajst-19160	8	9	and	and	CCONJ
ajst-19160	8	10	accuracy	accuracy	NOUN
ajst-19160	8	11	compared	compare	VERB
ajst-19160	8	12	to	to	ADP
ajst-19160	8	13	the	the	DET
ajst-19160	8	14	comparison	comparison	NOUN
ajst-19160	8	15	model	model	NOUN
ajst-19160	8	16	,	,	PUNCT
ajst-19160	8	17	as	as	SCONJ
ajst-19160	8	18	demonstrated	demonstrate	VERB
ajst-19160	8	19	by	by	ADP
ajst-19160	8	20	its	its	PRON
ajst-19160	8	21	mse	mse	NOUN
ajst-19160	8	22	’	'	PUNCT
ajst-19160	8	23	of	of	ADP
ajst-19160	8	24	0.0482	0.0482	NUM
ajst-19160	8	25	,	,	PUNCT
ajst-19160	8	26	r2	r2	PROPN
ajst-19160	8	27	’	'	PUNCT
ajst-19160	8	28	of	of	ADP
ajst-19160	8	29	0.9982	0.9982	NUM
ajst-19160	8	30	,	,	PUNCT
ajst-19160	8	31	mae	mae	PROPN
ajst-19160	8	32	’	'	PUNCT
ajst-19160	8	33	of	of	ADP
ajst-19160	8	34	0.1295	0.1295	NUM
ajst-19160	8	35	,	,	PUNCT
ajst-19160	8	36	and	and	CCONJ
ajst-19160	8	37	sd	sd	NOUN
ajst-19160	8	38	of	of	ADP
ajst-19160	8	39	0.2198	0.2198	NUM
ajst-19160	8	40	.	.	PUNCT
ajst-19160	9	1	the	the	DET
ajst-19160	9	2	highdimensional	highdimensional	PROPN
ajst-19160	9	3	surface	surface	NOUN
ajst-19160	9	4	obtained	obtain	VERB
ajst-19160	9	5	through	through	ADP
ajst-19160	9	6	inversion	inversion	NOUN
ajst-19160	9	7	shows	show	VERB
ajst-19160	9	8	a	a	DET
ajst-19160	9	9	linear	linear	ADJ
ajst-19160	9	10	relationship	relationship	NOUN
ajst-19160	9	11	between	between	ADP
ajst-19160	9	12	seawater	seawater	NOUN
ajst-19160	9	13	depth	depth	NOUN
ajst-19160	9	14	and	and	CCONJ
ajst-19160	9	15	failure	failure	NOUN
ajst-19160	9	16	pressure	pressure	NOUN
ajst-19160	9	17	.	.	PUNCT
ajst-19160	10	1	meanwhile	meanwhile	ADV
ajst-19160	10	2	,	,	PUNCT
ajst-19160	10	3	the	the	DET
ajst-19160	10	4	width	width	NOUN
ajst-19160	10	5	of	of	ADP
ajst-19160	10	6	corrosion	corrosion	NOUN
ajst-19160	10	7	defects	defect	NOUN
ajst-19160	10	8	has	have	VERB
ajst-19160	10	9	a	a	DET
ajst-19160	10	10	significant	significant	ADJ
ajst-19160	10	11	impact	impact	NOUN
ajst-19160	10	12	on	on	ADP
ajst-19160	10	13	failure	failure	NOUN
ajst-19160	10	14	pressure	pressure	NOUN
ajst-19160	10	15	,	,	PUNCT
ajst-19160	10	16	accounting	account	VERB
ajst-19160	10	17	for	for	ADP
ajst-19160	10	18	up	up	ADP
ajst-19160	10	19	to	to	PART
ajst-19160	10	20	23	23	NUM
ajst-19160	10	21	%	%	NOUN
ajst-19160	10	22	and	and	CCONJ
ajst-19160	10	23	thus	thus	ADV
ajst-19160	10	24	can	can	AUX
ajst-19160	10	25	not	not	PART
ajst-19160	10	26	be	be	AUX
ajst-19160	10	27	overlooked	overlook	VERB
ajst-19160	10	28	.	.	PUNCT
ajst-19160	11	1	keywords	keyword	NOUN
ajst-19160	11	2	:	:	PUNCT
ajst-19160	11	3	improved	improve	VERB
ajst-19160	11	4	support	support	NOUN
ajst-19160	11	5	vector	vector	NOUN
ajst-19160	11	6	machine	machine	NOUN
ajst-19160	11	7	,	,	PUNCT
ajst-19160	11	8	submarine	submarine	NOUN
ajst-19160	11	9	oil	oil	NOUN
ajst-19160	11	10	and	and	CCONJ
ajst-19160	11	11	gas	gas	NOUN
ajst-19160	11	12	pipelines	pipeline	NOUN
ajst-19160	11	13	,	,	PUNCT
ajst-19160	11	14	pipeline	pipeline	NOUN
ajst-19160	11	15	internal	internal	ADJ
ajst-19160	11	16	corrosion	corrosion	NOUN
ajst-19160	11	17	,	,	PUNCT
ajst-19160	11	18	machine	machine	NOUN
ajst-19160	11	19	learning	learning	NOUN
ajst-19160	11	20	,	,	PUNCT
ajst-19160	11	21	finite	finite	PROPN
ajst-19160	11	22	element	element	NOUN
ajst-19160	11	23	method	method	NOUN
ajst-19160	11	24	.	.	PUNCT
ajst-19160	12	1	1	1	X
ajst-19160	12	2	.	.	X
ajst-19160	12	3	introduction	introduction	NOUN
ajst-19160	12	4	according	accord	VERB
ajst-19160	12	5	to	to	ADP
ajst-19160	12	6	a	a	DET
ajst-19160	12	7	2017	2017	NUM
ajst-19160	12	8	report	report	NOUN
ajst-19160	12	9	from	from	ADP
ajst-19160	12	10	the	the	DET
ajst-19160	12	11	american	american	ADJ
ajst-19160	12	12	society	society	NOUN
ajst-19160	12	13	of	of	ADP
ajst-19160	12	14	corrosion	corrosion	NOUN
ajst-19160	12	15	engineers	engineer	NOUN
ajst-19160	12	16	[	[	X
ajst-19160	12	17	1	1	NUM
ajst-19160	12	18	]	]	PUNCT
ajst-19160	12	19	,	,	PUNCT
ajst-19160	12	20	the	the	DET
ajst-19160	12	21	global	global	ADJ
ajst-19160	12	22	economic	economic	ADJ
ajst-19160	12	23	loss	loss	NOUN
ajst-19160	12	24	caused	cause	VERB
ajst-19160	12	25	by	by	ADP
ajst-19160	12	26	corrosion	corrosion	NOUN
ajst-19160	12	27	was	be	AUX
ajst-19160	12	28	estimated	estimate	VERB
ajst-19160	12	29	to	to	PART
ajst-19160	12	30	be	be	AUX
ajst-19160	12	31	approximately	approximately	ADV
ajst-19160	12	32	2.5	2.5	NUM
ajst-19160	12	33	trillion	trillion	NUM
ajst-19160	12	34	us	us	PROPN
ajst-19160	12	35	dollars	dollar	NOUN
ajst-19160	12	36	.	.	PUNCT
ajst-19160	13	1	in	in	ADP
ajst-19160	13	2	addition	addition	NOUN
ajst-19160	13	3	,	,	PUNCT
ajst-19160	13	4	the	the	DET
ajst-19160	13	5	seabed	seabed	NOUN
ajst-19160	13	6	environment	environment	NOUN
ajst-19160	13	7	is	be	AUX
ajst-19160	13	8	more	more	ADV
ajst-19160	13	9	susceptible	susceptible	ADJ
ajst-19160	13	10	to	to	ADP
ajst-19160	13	11	erosion	erosion	NOUN
ajst-19160	13	12	than	than	ADP
ajst-19160	13	13	land	land	NOUN
ajst-19160	13	14	[	[	X
ajst-19160	13	15	2	2	NUM
ajst-19160	13	16	]	]	PUNCT
ajst-19160	13	17	,	,	PUNCT
ajst-19160	13	18	which	which	PRON
ajst-19160	13	19	makes	make	VERB
ajst-19160	13	20	the	the	DET
ajst-19160	13	21	maintenance	maintenance	NOUN
ajst-19160	13	22	and	and	CCONJ
ajst-19160	13	23	replacement	replacement	NOUN
ajst-19160	13	24	of	of	ADP
ajst-19160	13	25	submarine	submarine	NOUN
ajst-19160	13	26	pipelines	pipeline	NOUN
ajst-19160	13	27	more	more	ADV
ajst-19160	13	28	expensive	expensive	ADJ
ajst-19160	13	29	and	and	CCONJ
ajst-19160	13	30	complex	complex	ADJ
ajst-19160	13	31	[	[	X
ajst-19160	13	32	3	3	NUM
ajst-19160	13	33	]	]	PUNCT
ajst-19160	13	34	.	.	PUNCT
ajst-19160	14	1	therefore	therefore	ADV
ajst-19160	14	2	,	,	PUNCT
ajst-19160	14	3	studying	study	VERB
ajst-19160	14	4	the	the	DET
ajst-19160	14	5	failure	failure	NOUN
ajst-19160	14	6	pressure	pressure	NOUN
ajst-19160	14	7	of	of	ADP
ajst-19160	14	8	submarine	submarine	NOUN
ajst-19160	14	9	pipelines	pipeline	NOUN
ajst-19160	14	10	with	with	ADP
ajst-19160	14	11	corrosion	corrosion	NOUN
ajst-19160	14	12	defects	defect	NOUN
ajst-19160	14	13	is	be	AUX
ajst-19160	14	14	of	of	ADP
ajst-19160	14	15	great	great	ADJ
ajst-19160	14	16	significance	significance	NOUN
ajst-19160	14	17	.	.	PUNCT
ajst-19160	15	1	it	it	PRON
ajst-19160	15	2	can	can	AUX
ajst-19160	15	3	not	not	PART
ajst-19160	15	4	only	only	ADV
ajst-19160	15	5	predict	predict	VERB
ajst-19160	15	6	the	the	DET
ajst-19160	15	7	probability	probability	NOUN
ajst-19160	15	8	of	of	ADP
ajst-19160	15	9	accidents	accident	NOUN
ajst-19160	15	10	more	more	ADV
ajst-19160	15	11	scientifically	scientifically	ADV
ajst-19160	15	12	and	and	CCONJ
ajst-19160	15	13	effectively	effectively	ADV
ajst-19160	15	14	but	but	CCONJ
ajst-19160	15	15	also	also	ADV
ajst-19160	15	16	provide	provide	VERB
ajst-19160	15	17	reliable	reliable	ADJ
ajst-19160	15	18	decision	decision	NOUN
ajst-19160	15	19	support	support	NOUN
ajst-19160	15	20	for	for	ADP
ajst-19160	15	21	pipeline	pipeline	NOUN
ajst-19160	15	22	transportation	transportation	NOUN
ajst-19160	15	23	deployment	deployment	NOUN
ajst-19160	15	24	and	and	CCONJ
ajst-19160	15	25	maintenance	maintenance	NOUN
ajst-19160	15	26	detection	detection	NOUN
ajst-19160	15	27	[	[	X
ajst-19160	15	28	4	4	NUM
ajst-19160	15	29	]	]	PUNCT
ajst-19160	15	30	.	.	PUNCT
ajst-19160	16	1	at	at	ADP
ajst-19160	16	2	present	present	ADJ
ajst-19160	16	3	,	,	PUNCT
ajst-19160	16	4	a	a	DET
ajst-19160	16	5	plethora	plethora	NOUN
ajst-19160	16	6	of	of	ADP
ajst-19160	16	7	scholars	scholar	NOUN
ajst-19160	16	8	have	have	AUX
ajst-19160	16	9	conducted	conduct	VERB
ajst-19160	16	10	extensive	extensive	ADJ
ajst-19160	16	11	research	research	NOUN
ajst-19160	16	12	on	on	ADP
ajst-19160	16	13	the	the	DET
ajst-19160	16	14	failure	failure	NOUN
ajst-19160	16	15	pressure	pressure	NOUN
ajst-19160	16	16	of	of	ADP
ajst-19160	16	17	corrosion	corrosion	NOUN
ajst-19160	16	18	defects	defect	NOUN
ajst-19160	16	19	.	.	PUNCT
ajst-19160	17	1	gao	gao	PROPN
ajst-19160	17	2	j	j	PROPN
ajst-19160	18	1	[	[	X
ajst-19160	18	2	5	5	NUM
ajst-19160	18	3	]	]	PUNCT
ajst-19160	18	4	utilized	utilize	VERB
ajst-19160	18	5	the	the	DET
ajst-19160	18	6	finite	finite	ADJ
ajst-19160	18	7	element	element	NOUN
ajst-19160	18	8	method	method	NOUN
ajst-19160	18	9	(	(	PUNCT
ajst-19160	18	10	fem	fem	NOUN
ajst-19160	18	11	)	)	PUNCT
ajst-19160	18	12	to	to	PART
ajst-19160	18	13	conduct	conduct	VERB
ajst-19160	18	14	a	a	DET
ajst-19160	18	15	fullscale	fullscale	ADJ
ajst-19160	18	16	blasting	blast	VERB
ajst-19160	18	17	test	test	NOUN
ajst-19160	18	18	and	and	CCONJ
ajst-19160	18	19	obtained	obtain	VERB
ajst-19160	18	20	multiple	multiple	ADJ
ajst-19160	18	21	sets	set	NOUN
ajst-19160	18	22	of	of	ADP
ajst-19160	18	23	failure	failure	NOUN
ajst-19160	18	24	pressure	pressure	NOUN
ajst-19160	18	25	data	datum	NOUN
ajst-19160	18	26	,	,	PUNCT
ajst-19160	18	27	suggesting	suggest	VERB
ajst-19160	18	28	that	that	SCONJ
ajst-19160	18	29	fem	fem	NOUN
ajst-19160	18	30	is	be	AUX
ajst-19160	18	31	a	a	DET
ajst-19160	18	32	viable	viable	ADJ
ajst-19160	18	33	approach	approach	NOUN
ajst-19160	18	34	for	for	ADP
ajst-19160	18	35	predicting	predict	VERB
ajst-19160	18	36	the	the	DET
ajst-19160	18	37	failure	failure	NOUN
ajst-19160	18	38	pressure	pressure	NOUN
ajst-19160	18	39	of	of	ADP
ajst-19160	18	40	corroded	corroded	ADJ
ajst-19160	18	41	pipelines	pipeline	NOUN
ajst-19160	18	42	.	.	PUNCT
ajst-19160	19	1	abyani	abyani	ADJ
ajst-19160	19	2	m	m	VERB
ajst-19160	20	1	[	[	X
ajst-19160	20	2	6	6	NUM
ajst-19160	20	3	]	]	PUNCT
ajst-19160	20	4	deployed	deploy	VERB
ajst-19160	20	5	fem	fem	NOUN
ajst-19160	20	6	to	to	PART
ajst-19160	20	7	assess	assess	VERB
ajst-19160	20	8	the	the	DET
ajst-19160	20	9	reliability	reliability	NOUN
ajst-19160	20	10	of	of	ADP
ajst-19160	20	11	a	a	DET
ajst-19160	20	12	single	single	ADJ
ajst-19160	20	13	corrosion	corrosion	NOUN
ajst-19160	20	14	defect	defect	NOUN
ajst-19160	20	15	in	in	ADP
ajst-19160	20	16	a	a	DET
ajst-19160	20	17	submarine	submarine	NOUN
ajst-19160	20	18	pipeline	pipeline	NOUN
ajst-19160	20	19	.	.	PUNCT
ajst-19160	21	1	however	however	ADV
ajst-19160	21	2	,	,	PUNCT
ajst-19160	21	3	this	this	DET
ajst-19160	21	4	method	method	NOUN
ajst-19160	21	5	is	be	AUX
ajst-19160	21	6	intricate	intricate	ADJ
ajst-19160	21	7	to	to	PART
ajst-19160	21	8	construct	construct	VERB
ajst-19160	21	9	the	the	DET
ajst-19160	21	10	model	model	NOUN
ajst-19160	21	11	and	and	CCONJ
ajst-19160	21	12	consumes	consume	VERB
ajst-19160	21	13	a	a	DET
ajst-19160	21	14	significant	significant	ADJ
ajst-19160	21	15	amount	amount	NOUN
ajst-19160	21	16	of	of	ADP
ajst-19160	21	17	time	time	NOUN
ajst-19160	21	18	,	,	PUNCT
ajst-19160	21	19	indicating	indicate	VERB
ajst-19160	21	20	that	that	SCONJ
ajst-19160	21	21	it	it	PRON
ajst-19160	21	22	can	can	AUX
ajst-19160	21	23	not	not	PART
ajst-19160	21	24	be	be	AUX
ajst-19160	21	25	utilized	utilize	VERB
ajst-19160	21	26	for	for	ADP
ajst-19160	21	27	large	large	ADJ
ajst-19160	21	28	-	-	PUNCT
ajst-19160	21	29	scale	scale	NOUN
ajst-19160	21	30	corrosion	corrosion	NOUN
ajst-19160	21	31	assessments	assessment	NOUN
ajst-19160	21	32	.	.	PUNCT
ajst-19160	22	1	sun	sun	NOUN
ajst-19160	22	2	m	m	PROPN
ajst-19160	23	1	[	[	X
ajst-19160	23	2	7	7	X
ajst-19160	23	3	]	]	PUNCT
ajst-19160	23	4	and	and	CCONJ
ajst-19160	23	5	chen	chen	PROPN
ajst-19160	23	6	y	y	PROPN
ajst-19160	23	7	f	f	PROPN
ajst-19160	24	1	[	[	X
ajst-19160	24	2	8	8	NUM
ajst-19160	24	3	]	]	PUNCT
ajst-19160	24	4	simplified	simplify	VERB
ajst-19160	24	5	the	the	DET
ajst-19160	24	6	corrosion	corrosion	NOUN
ajst-19160	24	7	defect	defect	NOUN
ajst-19160	24	8	morphology	morphology	NOUN
ajst-19160	24	9	into	into	ADP
ajst-19160	24	10	a	a	DET
ajst-19160	24	11	threedimensional	threedimensional	ADJ
ajst-19160	24	12	cuboid	cuboid	NOUN
ajst-19160	24	13	shape	shape	NOUN
ajst-19160	24	14	with	with	ADP
ajst-19160	24	15	only	only	ADJ
ajst-19160	24	16	length	length	NOUN
ajst-19160	24	17	,	,	PUNCT
ajst-19160	24	18	width	width	ADJ
ajst-19160	24	19	and	and	CCONJ
ajst-19160	24	20	height	height	NOUN
ajst-19160	24	21	,	,	PUNCT
ajst-19160	24	22	which	which	PRON
ajst-19160	24	23	greatly	greatly	ADV
ajst-19160	24	24	simplifies	simplify	VERB
ajst-19160	24	25	the	the	DET
ajst-19160	24	26	calculation	calculation	NOUN
ajst-19160	24	27	of	of	ADP
ajst-19160	24	28	finite	finite	PROPN
ajst-19160	24	29	element	element	PROPN
ajst-19160	24	30	simulation	simulation	PROPN
ajst-19160	24	31	.	.	PUNCT
ajst-19160	25	1	asme	asme	PROPN
ajst-19160	25	2	b31g-2009	b31g-2009	PROPN
ajst-19160	26	1	[	[	X
ajst-19160	26	2	9	9	NUM
ajst-19160	26	3	]	]	PUNCT
ajst-19160	26	4	,	,	PUNCT
ajst-19160	26	5	dnvrp	dnvrp	NOUN
ajst-19160	26	6	-	-	PUNCT
ajst-19160	26	7	f101	f101	PROPN
ajst-19160	26	8	[	[	X
ajst-19160	26	9	10	10	NUM
ajst-19160	26	10	]	]	PUNCT
ajst-19160	26	11	are	be	AUX
ajst-19160	26	12	commonly	commonly	ADV
ajst-19160	26	13	used	use	VERB
ajst-19160	26	14	methods	method	NOUN
ajst-19160	26	15	in	in	ADP
ajst-19160	26	16	the	the	DET
ajst-19160	26	17	industry	industry	NOUN
ajst-19160	26	18	for	for	ADP
ajst-19160	26	19	estimating	estimate	VERB
ajst-19160	26	20	the	the	DET
ajst-19160	26	21	burst	burst	ADJ
ajst-19160	26	22	pressure	pressure	NOUN
ajst-19160	26	23	of	of	ADP
ajst-19160	26	24	corroded	corroded	ADJ
ajst-19160	26	25	pipelines	pipeline	NOUN
ajst-19160	26	26	.	.	PUNCT
ajst-19160	27	1	however	however	ADV
ajst-19160	27	2	,	,	PUNCT
ajst-19160	27	3	these	these	DET
ajst-19160	27	4	methods	method	NOUN
ajst-19160	27	5	only	only	ADV
ajst-19160	27	6	consider	consider	VERB
ajst-19160	27	7	the	the	DET
ajst-19160	27	8	length	length	NOUN
ajst-19160	27	9	and	and	CCONJ
ajst-19160	27	10	depth	depth	NOUN
ajst-19160	27	11	of	of	ADP
ajst-19160	27	12	corrosion	corrosion	NOUN
ajst-19160	27	13	defects	defect	NOUN
ajst-19160	27	14	,	,	PUNCT
ajst-19160	27	15	and	and	CCONJ
ajst-19160	27	16	do	do	AUX
ajst-19160	27	17	not	not	PART
ajst-19160	27	18	take	take	VERB
ajst-19160	27	19	into	into	ADP
ajst-19160	27	20	account	account	NOUN
ajst-19160	27	21	all	all	DET
ajst-19160	27	22	geometric	geometric	ADJ
ajst-19160	27	23	parameters	parameter	NOUN
ajst-19160	27	24	of	of	ADP
ajst-19160	27	25	defects	defect	NOUN
ajst-19160	27	26	.	.	PUNCT
ajst-19160	28	1	as	as	SCONJ
ajst-19160	28	2	confirmed	confirm	VERB
ajst-19160	28	3	by	by	ADP
ajst-19160	28	4	ma	ma	PROPN
ajst-19160	28	5	b	b	PROPN
ajst-19160	29	1	[	[	X
ajst-19160	29	2	11	11	NUM
ajst-19160	29	3	]	]	PUNCT
ajst-19160	29	4	,	,	PUNCT
ajst-19160	29	5	the	the	DET
ajst-19160	29	6	estimated	estimate	VERB
ajst-19160	29	7	burst	burst	ADJ
ajst-19160	29	8	pressure	pressure	NOUN
ajst-19160	29	9	is	be	AUX
ajst-19160	29	10	too	too	ADV
ajst-19160	29	11	conservative	conservative	ADJ
ajst-19160	29	12	,	,	PUNCT
ajst-19160	29	13	leading	lead	VERB
ajst-19160	29	14	to	to	ADP
ajst-19160	29	15	early	early	ADJ
ajst-19160	29	16	pipeline	pipeline	NOUN
ajst-19160	29	17	replacement	replacement	NOUN
ajst-19160	29	18	and	and	CCONJ
ajst-19160	29	19	economic	economic	ADJ
ajst-19160	29	20	losses	loss	NOUN
ajst-19160	29	21	for	for	ADP
ajst-19160	29	22	enterprises	enterprise	NOUN
ajst-19160	29	23	.	.	PUNCT
ajst-19160	30	1	xu	xu	PROPN
ajst-19160	30	2	w	w	PROPN
ajst-19160	31	1	[	[	X
ajst-19160	31	2	12	12	NUM
ajst-19160	31	3	]	]	PUNCT
ajst-19160	31	4	employed	employ	VERB
ajst-19160	31	5	abaqus	abaqus	NOUN
ajst-19160	31	6	software	software	NOUN
ajst-19160	31	7	to	to	PART
ajst-19160	31	8	generate	generate	VERB
ajst-19160	31	9	various	various	ADJ
ajst-19160	31	10	finite	finite	ADJ
ajst-19160	31	11	element	element	NOUN
ajst-19160	31	12	models	model	NOUN
ajst-19160	31	13	and	and	CCONJ
ajst-19160	31	14	utilized	utilize	VERB
ajst-19160	31	15	the	the	DET
ajst-19160	31	16	numerical	numerical	ADJ
ajst-19160	31	17	outcomes	outcome	NOUN
ajst-19160	31	18	to	to	PART
ajst-19160	31	19	establish	establish	VERB
ajst-19160	31	20	a	a	DET
ajst-19160	31	21	neural	neural	ADJ
ajst-19160	31	22	network	network	NOUN
ajst-19160	31	23	model	model	NOUN
ajst-19160	31	24	for	for	ADP
ajst-19160	31	25	predicting	predict	VERB
ajst-19160	31	26	the	the	DET
ajst-19160	31	27	failure	failure	NOUN
ajst-19160	31	28	pressure	pressure	NOUN
ajst-19160	31	29	of	of	ADP
ajst-19160	31	30	externally	externally	ADV
ajst-19160	31	31	corroded	corroded	ADJ
ajst-19160	31	32	pipelines	pipeline	NOUN
ajst-19160	31	33	.	.	PUNCT
ajst-19160	32	1	nevertheless	nevertheless	ADV
ajst-19160	32	2	,	,	PUNCT
ajst-19160	32	3	the	the	DET
ajst-19160	32	4	neural	neural	ADJ
ajst-19160	32	5	network	network	NOUN
ajst-19160	32	6	model	model	NOUN
ajst-19160	32	7	comprises	comprise	VERB
ajst-19160	32	8	multiple	multiple	ADJ
ajst-19160	32	9	random	random	ADJ
ajst-19160	32	10	initial	initial	ADJ
ajst-19160	32	11	weight	weight	NOUN
ajst-19160	32	12	thresholds	threshold	NOUN
ajst-19160	32	13	,	,	PUNCT
ajst-19160	32	14	which	which	PRON
ajst-19160	32	15	significantly	significantly	ADV
ajst-19160	32	16	impact	impact	VERB
ajst-19160	32	17	the	the	DET
ajst-19160	32	18	optimization	optimization	NOUN
ajst-19160	32	19	accuracy	accuracy	NOUN
ajst-19160	32	20	and	and	CCONJ
ajst-19160	32	21	efficiency	efficiency	NOUN
ajst-19160	32	22	.	.	PUNCT
ajst-19160	33	1	in	in	ADP
ajst-19160	33	2	summary	summary	NOUN
ajst-19160	33	3	,	,	PUNCT
ajst-19160	33	4	constructing	construct	VERB
ajst-19160	33	5	a	a	DET
ajst-19160	33	6	three	three	NUM
ajst-19160	33	7	-	-	PUNCT
ajst-19160	33	8	dimensional	dimensional	ADJ
ajst-19160	33	9	numerical	numerical	ADJ
ajst-19160	33	10	model	model	NOUN
ajst-19160	33	11	of	of	ADP
ajst-19160	33	12	corrosion	corrosion	NOUN
ajst-19160	33	13	defects	defect	NOUN
ajst-19160	33	14	in	in	ADP
ajst-19160	33	15	fem	fem	NOUN
ajst-19160	33	16	analysis	analysis	NOUN
ajst-19160	33	17	is	be	AUX
ajst-19160	33	18	a	a	DET
ajst-19160	33	19	challenging	challenging	ADJ
ajst-19160	33	20	task	task	NOUN
ajst-19160	33	21	,	,	PUNCT
ajst-19160	33	22	and	and	CCONJ
ajst-19160	33	23	the	the	DET
ajst-19160	33	24	nonlinear	nonlinear	ADJ
ajst-19160	33	25	calculation	calculation	NOUN
ajst-19160	33	26	time	time	NOUN
ajst-19160	33	27	and	and	CCONJ
ajst-19160	33	28	cost	cost	NOUN
ajst-19160	33	29	associated	associate	VERB
ajst-19160	33	30	with	with	ADP
ajst-19160	33	31	it	it	PRON
ajst-19160	33	32	are	be	AUX
ajst-19160	33	33	exceedingly	exceedingly	ADV
ajst-19160	33	34	high	high	ADJ
ajst-19160	33	35	.	.	PUNCT
ajst-19160	34	1	the	the	DET
ajst-19160	34	2	outcomes	outcome	NOUN
ajst-19160	34	3	obtained	obtain	VERB
ajst-19160	34	4	through	through	ADP
ajst-19160	34	5	the	the	DET
ajst-19160	34	6	traditional	traditional	ADJ
ajst-19160	34	7	formula	formula	NOUN
ajst-19160	34	8	method	method	NOUN
ajst-19160	34	9	are	be	AUX
ajst-19160	34	10	overly	overly	ADV
ajst-19160	34	11	conservative	conservative	ADJ
ajst-19160	34	12	,	,	PUNCT
ajst-19160	34	13	which	which	PRON
ajst-19160	34	14	deviates	deviate	VERB
ajst-19160	34	15	from	from	ADP
ajst-19160	34	16	the	the	DET
ajst-19160	34	17	objective	objective	NOUN
ajst-19160	34	18	of	of	ADP
ajst-19160	34	19	reducing	reduce	VERB
ajst-19160	34	20	operation	operation	NOUN
ajst-19160	34	21	and	and	CCONJ
ajst-19160	34	22	maintenance	maintenance	NOUN
ajst-19160	34	23	expenses	expense	NOUN
ajst-19160	34	24	.	.	PUNCT
ajst-19160	35	1	the	the	DET
ajst-19160	35	2	initial	initial	ADJ
ajst-19160	35	3	random	random	ADJ
ajst-19160	35	4	weight	weight	NOUN
ajst-19160	35	5	threshold	threshold	NOUN
ajst-19160	35	6	of	of	ADP
ajst-19160	35	7	the	the	DET
ajst-19160	35	8	neural	neural	ADJ
ajst-19160	35	9	network	network	NOUN
ajst-19160	35	10	will	will	AUX
ajst-19160	35	11	bring	bring	VERB
ajst-19160	35	12	some	some	DET
ajst-19160	35	13	instability	instability	NOUN
ajst-19160	35	14	to	to	ADP
ajst-19160	35	15	the	the	DET
ajst-19160	35	16	operation	operation	NOUN
ajst-19160	35	17	results	result	NOUN
ajst-19160	35	18	.	.	PUNCT
ajst-19160	36	1	currently	currently	ADV
ajst-19160	36	2	,	,	PUNCT
ajst-19160	36	3	numerous	numerous	ADJ
ajst-19160	36	4	studies	study	NOUN
ajst-19160	36	5	solely	solely	ADV
ajst-19160	36	6	focus	focus	VERB
ajst-19160	36	7	on	on	ADP
ajst-19160	36	8	the	the	DET
ajst-19160	36	9	depth	depth	NOUN
ajst-19160	36	10	and	and	CCONJ
ajst-19160	36	11	length	length	NOUN
ajst-19160	36	12	of	of	ADP
ajst-19160	36	13	corrosion	corrosion	NOUN
ajst-19160	36	14	defects	defect	NOUN
ajst-19160	36	15	,	,	PUNCT
ajst-19160	36	16	while	while	SCONJ
ajst-19160	36	17	neglecting	neglect	VERB
ajst-19160	36	18	the	the	DET
ajst-19160	36	19	impact	impact	NOUN
ajst-19160	36	20	of	of	ADP
ajst-19160	36	21	the	the	DET
ajst-19160	36	22	width	width	NOUN
ajst-19160	36	23	of	of	ADP
ajst-19160	36	24	the	the	DET
ajst-19160	36	25	corrosion	corrosion	NOUN
ajst-19160	36	26	defect	defect	NOUN
ajst-19160	36	27	and	and	CCONJ
ajst-19160	36	28	external	external	ADJ
ajst-19160	36	29	hydrostatic	hydrostatic	ADJ
ajst-19160	36	30	pressure	pressure	NOUN
ajst-19160	36	31	on	on	ADP
ajst-19160	36	32	pipelines	pipeline	NOUN
ajst-19160	36	33	.	.	PUNCT
ajst-19160	37	1	however	however	ADV
ajst-19160	37	2	,	,	PUNCT
ajst-19160	37	3	this	this	DET
ajst-19160	37	4	study	study	NOUN
ajst-19160	37	5	reveals	reveal	VERB
ajst-19160	37	6	that	that	SCONJ
ajst-19160	37	7	the	the	DET
ajst-19160	37	8	influence	influence	NOUN
ajst-19160	37	9	of	of	ADP
ajst-19160	37	10	corrosion	corrosion	NOUN
ajst-19160	37	11	width	width	NOUN
ajst-19160	37	12	on	on	ADP
ajst-19160	37	13	blasting	blast	VERB
ajst-19160	37	14	pressure	pressure	NOUN
ajst-19160	37	15	intensifies	intensifie	NOUN
ajst-19160	37	16	with	with	ADP
ajst-19160	37	17	increasing	increase	VERB
ajst-19160	37	18	corrosion	corrosion	NOUN
ajst-19160	37	19	depth	depth	NOUN
ajst-19160	37	20	and	and	CCONJ
ajst-19160	37	21	length	length	NOUN
ajst-19160	37	22	.	.	PUNCT
ajst-19160	38	1	moreover	moreover	ADV
ajst-19160	38	2	,	,	PUNCT
ajst-19160	38	3	the	the	DET
ajst-19160	38	4	influence	influence	NOUN
ajst-19160	38	5	of	of	ADP
ajst-19160	38	6	external	external	ADJ
ajst-19160	38	7	hydrostatic	hydrostatic	ADJ
ajst-19160	38	8	pressure	pressure	NOUN
ajst-19160	38	9	on	on	ADP
ajst-19160	38	10	the	the	DET
ajst-19160	38	11	burst	burst	ADJ
ajst-19160	38	12	pressure	pressure	NOUN
ajst-19160	38	13	can	can	AUX
ajst-19160	38	14	not	not	PART
ajst-19160	38	15	be	be	AUX
ajst-19160	38	16	disregarded	disregard	VERB
ajst-19160	38	17	.	.	PUNCT
ajst-19160	39	1	initially	initially	ADV
ajst-19160	39	2	,	,	PUNCT
ajst-19160	39	3	considering	consider	VERB
ajst-19160	39	4	that	that	SCONJ
ajst-19160	39	5	machine	machine	NOUN
ajst-19160	39	6	learning	learning	NOUN
ajst-19160	39	7	needs	need	VERB
ajst-19160	39	8	to	to	PART
ajst-19160	39	9	build	build	VERB
ajst-19160	39	10	a	a	DET
ajst-19160	39	11	large	large	ADJ
ajst-19160	39	12	number	number	NOUN
ajst-19160	39	13	of	of	ADP
ajst-19160	39	14	samples	sample	NOUN
ajst-19160	39	15	.	.	PUNCT
ajst-19160	40	1	a	a	DET
ajst-19160	40	2	novel	novel	NOUN
ajst-19160	40	3	,	,	PUNCT
ajst-19160	40	4	efficient	efficient	ADJ
ajst-19160	40	5	python	python	NOUN
ajst-19160	40	6	batch	batch	NOUN
ajst-19160	40	7	generation	generation	NOUN
ajst-19160	40	8	model	model	NOUN
ajst-19160	40	9	(	(	PUNCT
ajst-19160	40	10	chapter	chapter	NOUN
ajst-19160	40	11	1.2	1.2	NUM
ajst-19160	40	12	)	)	PUNCT
ajst-19160	40	13	was	be	AUX
ajst-19160	40	14	proposed	propose	VERB
ajst-19160	40	15	and	and	CCONJ
ajst-19160	40	16	verified	verify	VERB
ajst-19160	40	17	via	via	ADP
ajst-19160	40	18	a	a	DET
ajst-19160	40	19	blasting	blast	VERB
ajst-19160	40	20	test	test	NOUN
ajst-19160	40	21	conducted	conduct	VERB
ajst-19160	40	22	by	by	ADP
ajst-19160	40	23	kang	kang	PROPN
ajst-19160	40	24	k	k	PROPN
ajst-19160	40	25	y	y	PROPN
ajst-19160	41	1	[	[	X
ajst-19160	41	2	13	13	NUM
ajst-19160	41	3	]	]	PUNCT
ajst-19160	41	4	.	.	PUNCT
ajst-19160	42	1	in	in	ADP
ajst-19160	42	2	this	this	DET
ajst-19160	42	3	modeling	modeling	NOUN
ajst-19160	42	4	process	process	NOUN
ajst-19160	42	5	,	,	PUNCT
ajst-19160	42	6	we	we	PRON
ajst-19160	42	7	studied	study	VERB
ajst-19160	42	8	the	the	DET
ajst-19160	42	9	effects	effect	NOUN
ajst-19160	42	10	of	of	ADP
ajst-19160	42	11	four	four	NUM
ajst-19160	42	12	parameters	parameter	NOUN
ajst-19160	42	13	,	,	PUNCT
ajst-19160	42	14	namely	namely	ADV
ajst-19160	42	15	seawater	seawater	NOUN
ajst-19160	42	16	depth	depth	NOUN
ajst-19160	42	17	,	,	PUNCT
ajst-19160	42	18	corrosion	corrosion	NOUN
ajst-19160	42	19	defect	defect	NOUN
ajst-19160	42	20	depth	depth	NOUN
ajst-19160	42	21	,	,	PUNCT
ajst-19160	42	22	corrosion	corrosion	NOUN
ajst-19160	42	23	defect	defect	NOUN
ajst-19160	42	24	length	length	NOUN
ajst-19160	42	25	,	,	PUNCT
ajst-19160	42	26	and	and	CCONJ
ajst-19160	42	27	corrosion	corrosion	NOUN
ajst-19160	42	28	defect	defect	NOUN
ajst-19160	42	29	width	width	NOUN
ajst-19160	42	30	,	,	PUNCT
ajst-19160	42	31	on	on	ADP
ajst-19160	42	32	the	the	DET
ajst-19160	42	33	failure	failure	NOUN
ajst-19160	42	34	pressure	pressure	NOUN
ajst-19160	42	35	of	of	ADP
ajst-19160	42	36	119	119	NUM
ajst-19160	42	37	submarine	submarine	NOUN
ajst-19160	42	38	pipelines	pipeline	NOUN
ajst-19160	42	39	affected	affect	VERB
ajst-19160	42	40	by	by	ADP
ajst-19160	42	41	corrosion	corrosion	NOUN
ajst-19160	42	42	defects	defect	NOUN
ajst-19160	42	43	.	.	PUNCT
ajst-19160	43	1	secondly	secondly	ADV
ajst-19160	43	2	,	,	PUNCT
ajst-19160	43	3	the	the	DET
ajst-19160	43	4	current	current	ADJ
ajst-19160	43	5	machine	machine	NOUN
ajst-19160	43	6	learning	learn	VERB
ajst-19160	43	7	algorithms	algorithm	NOUN
ajst-19160	43	8	exhibit	exhibit	VERB
ajst-19160	43	9	low	low	ADJ
ajst-19160	43	10	accuracy	accuracy	NOUN
ajst-19160	43	11	.	.	PUNCT
ajst-19160	44	1	therefore	therefore	ADV
ajst-19160	44	2	,	,	PUNCT
ajst-19160	44	3	this	this	DET
ajst-19160	44	4	research	research	NOUN
ajst-19160	44	5	proposes	propose	VERB
ajst-19160	44	6	an	an	DET
ajst-19160	44	7	improved	improved	ADJ
ajst-19160	44	8	machine	machine	NOUN
ajst-19160	44	9	learning	learning	NOUN
ajst-19160	44	10	method	method	NOUN
ajst-19160	44	11	to	to	PART
ajst-19160	44	12	replace	replace	VERB
ajst-19160	44	13	the	the	DET
ajst-19160	44	14	traditional	traditional	ADJ
ajst-19160	44	15	prediction	prediction	NOUN
ajst-19160	44	16	technology	technology	NOUN
ajst-19160	44	17	.	.	PUNCT
ajst-19160	45	1	the	the	DET
ajst-19160	45	2	conventional	conventional	ADJ
ajst-19160	45	3	support	support	NOUN
ajst-19160	45	4	vector	vector	NOUN
ajst-19160	45	5	machine	machine	NOUN
ajst-19160	45	6	(	(	PUNCT
ajst-19160	45	7	svm	svm	PROPN
ajst-19160	45	8	)	)	PUNCT
ajst-19160	45	9	employs	employ	VERB
ajst-19160	45	10	artificially	artificially	ADV
ajst-19160	45	11	set	set	VERB
ajst-19160	45	12	penalty	penalty	NOUN
ajst-19160	45	13	and	and	CCONJ
ajst-19160	45	14	loose	loose	ADJ
ajst-19160	45	15	factors	factor	NOUN
ajst-19160	45	16	or	or	CCONJ
ajst-19160	45	17	traditional	traditional	ADJ
ajst-19160	45	18	optimization	optimization	NOUN
ajst-19160	45	19	algorithms	algorithm	NOUN
ajst-19160	45	20	,	,	PUNCT
ajst-19160	45	21	which	which	PRON
ajst-19160	45	22	results	result	VERB
ajst-19160	45	23	in	in	ADP
ajst-19160	45	24	unstable	unstable	ADJ
ajst-19160	45	25	calculation	calculation	NOUN
ajst-19160	45	26	results	result	NOUN
ajst-19160	45	27	and	and	CCONJ
ajst-19160	45	28	low	low	ADJ
ajst-19160	45	29	accuracy	accuracy	NOUN
ajst-19160	45	30	.	.	PUNCT
ajst-19160	46	1	the	the	DET
ajst-19160	46	2	artificial	artificial	ADJ
ajst-19160	46	3	ecological	ecological	ADJ
ajst-19160	46	4	optimization	optimization	NOUN
ajst-19160	46	5	algorithm	algorithm	NOUN
ajst-19160	46	6	(	(	PUNCT
ajst-19160	46	7	aeo	aeo	PROPN
ajst-19160	46	8	)	)	PUNCT
ajst-19160	46	9	was	be	AUX
ajst-19160	46	10	proposed	propose	VERB
ajst-19160	46	11	by	by	ADP
ajst-19160	46	12	zhao	zhao	PROPN
ajst-19160	46	13	s	s	PART
ajst-19160	46	14	j	j	PROPN
ajst-19160	47	1	[	[	X
ajst-19160	47	2	14	14	NUM
ajst-19160	47	3	]	]	PUNCT
ajst-19160	47	4	as	as	ADP
ajst-19160	47	5	a	a	DET
ajst-19160	47	6	meta	meta	ADJ
ajst-19160	47	7	-	-	PUNCT
ajst-19160	47	8	heuristic	heuristic	ADJ
ajst-19160	47	9	algorithm	algorithm	NOUN
ajst-19160	47	10	that	that	PRON
ajst-19160	47	11	has	have	AUX
ajst-19160	47	12	shown	show	VERB
ajst-19160	47	13	stronger	strong	ADJ
ajst-19160	47	14	optimization	optimization	NOUN
ajst-19160	47	15	capabilities	capability	NOUN
ajst-19160	47	16	and	and	CCONJ
ajst-19160	47	17	a	a	DET
ajst-19160	47	18	shorter	short	ADJ
ajst-19160	47	19	iteration	iteration	NOUN
ajst-19160	47	20	process	process	NOUN
ajst-19160	47	21	when	when	SCONJ
ajst-19160	47	22	compared	compare	VERB
ajst-19160	47	23	to	to	ADP
ajst-19160	47	24	genetic	genetic	ADJ
ajst-19160	47	25	algorithm	algorithm	NOUN
ajst-19160	47	26	(	(	PUNCT
ajst-19160	47	27	ga	ga	PROPN
ajst-19160	47	28	)	)	PUNCT
ajst-19160	47	29	,	,	PUNCT
ajst-19160	47	30	particle	particle	NOUN
ajst-19160	47	31	swarm	swarm	NOUN
ajst-19160	47	32	optimization	optimization	NOUN
ajst-19160	47	33	(	(	PUNCT
ajst-19160	47	34	pso	pso	NOUN
ajst-19160	47	35	)	)	PUNCT
ajst-19160	47	36	,	,	PUNCT
ajst-19160	47	37	and	and	CCONJ
ajst-19160	47	38	whale	whale	NOUN
ajst-19160	47	39	optimization	optimization	NOUN
ajst-19160	47	40	algorithm	algorithm	NOUN
ajst-19160	47	41	(	(	PUNCT
ajst-19160	47	42	woa	woa	NOUN
ajst-19160	47	43	)	)	PUNCT
ajst-19160	47	44	.	.	PUNCT
ajst-19160	48	1	utilizing	utilize	VERB
ajst-19160	48	2	aeo	aeo	PROPN
ajst-19160	48	3	to	to	PART
ajst-19160	48	4	optimize	optimize	VERB
ajst-19160	48	5	svm	svm	NOUN
ajst-19160	48	6	and	and	CCONJ
ajst-19160	48	7	form	form	VERB
ajst-19160	48	8	the	the	DET
ajst-19160	48	9	aeosvm	aeosvm	NOUN
ajst-19160	48	10	prediction	prediction	NOUN
ajst-19160	48	11	model	model	NOUN
ajst-19160	48	12	can	can	AUX
ajst-19160	48	13	significantly	significantly	ADV
ajst-19160	48	14	mitigate	mitigate	VERB
ajst-19160	48	15	the	the	DET
ajst-19160	48	16	instability	instability	NOUN
ajst-19160	48	17	of	of	ADP
ajst-19160	48	18	the	the	DET
ajst-19160	48	19	result	result	NOUN
ajst-19160	48	20	.	.	PUNCT
ajst-19160	49	1	nevertheless	nevertheless	ADV
ajst-19160	49	2	,	,	PUNCT
ajst-19160	49	3	aeo	aeo	PROPN
ajst-19160	49	4	is	be	AUX
ajst-19160	49	5	prone	prone	ADJ
ajst-19160	49	6	to	to	ADP
ajst-19160	49	7	falling	fall	VERB
ajst-19160	49	8	into	into	ADP
ajst-19160	49	9	local	local	ADJ
ajst-19160	49	10	optima	optima	NOUN
ajst-19160	49	11	and	and	CCONJ
ajst-19160	49	12	exhibits	exhibit	VERB
ajst-19160	49	13	low	low	ADJ
ajst-19160	49	14	convergence	convergence	NOUN
ajst-19160	49	15	speed	speed	NOUN
ajst-19160	49	16	.	.	PUNCT
ajst-19160	50	1	hence	hence	ADV
ajst-19160	50	2	,	,	PUNCT
ajst-19160	50	3	the	the	DET
ajst-19160	50	4	author	author	NOUN
ajst-19160	50	5	proposes	propose	VERB
ajst-19160	50	6	an	an	DET
ajst-19160	50	7	improved	improved	ADJ
ajst-19160	50	8	strategy	strategy	NOUN
ajst-19160	50	9	that	that	PRON
ajst-19160	50	10	incorporates	incorporate	VERB
ajst-19160	50	11	reverse	reverse	ADJ
ajst-19160	50	12	backtracking	backtracking	NOUN
ajst-19160	50	13	(	(	PUNCT
ajst-19160	50	14	lbes	lbe	NOUN
ajst-19160	50	15	)	)	PUNCT
ajst-19160	50	16	and	and	CCONJ
ajst-19160	50	17	elite	elite	NOUN
ajst-19160	50	18	learning	learn	VERB
ajst-19160	50	19	to	to	PART
ajst-19160	50	20	avoid	avoid	VERB
ajst-19160	50	21	the	the	DET
ajst-19160	50	22	aforementioned	aforementioned	ADJ
ajst-19160	50	23	limitations	limitation	NOUN
ajst-19160	50	24	.	.	PUNCT
ajst-19160	51	1	the	the	DET
ajst-19160	51	2	resulting	result	VERB
ajst-19160	51	3	enhanced	enhanced	ADJ
ajst-19160	51	4	algorithm	algorithm	NOUN
ajst-19160	51	5	is	be	AUX
ajst-19160	51	6	called	call	VERB
ajst-19160	51	7	the	the	DET
ajst-19160	51	8	improved	improve	VERB
ajst-19160	51	9	artificial	artificial	ADJ
ajst-19160	51	10	ecological	ecological	ADJ
ajst-19160	51	11	optimization	optimization	NOUN
ajst-19160	51	12	algorithm	algorithm	NOUN
ajst-19160	51	13	(	(	PUNCT
ajst-19160	51	14	iaeo	iaeo	NOUN
ajst-19160	51	15	)	)	PUNCT
ajst-19160	51	16	.	.	PUNCT
ajst-19160	52	1	ultimately	ultimately	ADV
ajst-19160	52	2	,	,	PUNCT
ajst-19160	52	3	the	the	DET
ajst-19160	52	4	iaeo	iaeo	NOUN
ajst-19160	52	5	-	-	PUNCT
ajst-19160	52	6	svm	svm	PROPN
ajst-19160	52	7	prediction	prediction	NOUN
ajst-19160	52	8	model	model	NOUN
ajst-19160	52	9	was	be	AUX
ajst-19160	52	10	formulated	formulate	VERB
ajst-19160	52	11	.	.	PUNCT
ajst-19160	53	1	next	next	ADJ
ajst-19160	53	2	,	,	PUNCT
ajst-19160	53	3	351	351	NUM
ajst-19160	53	4	sets	set	NOUN
ajst-19160	53	5	of	of	ADP
ajst-19160	53	6	finite	finite	ADJ
ajst-19160	53	7	element	element	NOUN
ajst-19160	53	8	analysis	analysis	NOUN
ajst-19160	53	9	results	result	NOUN
ajst-19160	53	10	were	be	AUX
ajst-19160	53	11	utilized	utilize	VERB
ajst-19160	53	12	in	in	ADP
ajst-19160	53	13	seven	seven	NUM
ajst-19160	53	14	machine	machine	NOUN
ajst-19160	53	15	learning	learning	NOUN
ajst-19160	53	16	models	model	NOUN
ajst-19160	53	17	:	:	PUNCT
ajst-19160	53	18	iaeo	iaeo	NOUN
ajst-19160	53	19	-	-	PUNCT
ajst-19160	53	20	svm	svm	PROPN
ajst-19160	53	21	,	,	PUNCT
ajst-19160	53	22	aeo	aeo	PROPN
ajst-19160	53	23	-	-	PUNCT
ajst-19160	53	24	svm	svm	PROPN
ajst-19160	53	25	,	,	PUNCT
ajst-19160	53	26	svm	svm	ADJ
ajst-19160	53	27	,	,	PUNCT
ajst-19160	53	28	artificial	artificial	ADJ
ajst-19160	53	29	neural	neural	ADJ
ajst-19160	53	30	network	network	NOUN
ajst-19160	53	31	using	use	VERB
ajst-19160	53	32	levenbergmarquardt	levenbergmarquardt	ADJ
ajst-19160	53	33	algorithm	algorithm	NOUN
ajst-19160	53	34	(	(	PUNCT
ajst-19160	53	35	ann	ann	PROPN
ajst-19160	53	36	-	-	PUNCT
ajst-19160	53	37	lm	lm	PROPN
ajst-19160	53	38	)	)	PUNCT
ajst-19160	53	39	,	,	PUNCT
ajst-19160	53	40	radial	radial	ADJ
ajst-19160	53	41	basis	basis	NOUN
ajst-19160	53	42	function	function	NOUN
ajst-19160	53	43	neural	neural	ADJ
ajst-19160	53	44	network	network	NOUN
ajst-19160	53	45	(	(	PUNCT
ajst-19160	53	46	rbf	rbf	PROPN
ajst-19160	53	47	)	)	PUNCT
ajst-19160	53	48	,	,	PUNCT
ajst-19160	53	49	extreme	extreme	ADJ
ajst-19160	53	50	learning	learning	NOUN
ajst-19160	53	51	machine	machine	NOUN
ajst-19160	53	52	(	(	PUNCT
ajst-19160	53	53	elm	elm	PROPN
ajst-19160	53	54	)	)	PUNCT
ajst-19160	53	55	,	,	PUNCT
ajst-19160	53	56	and	and	CCONJ
ajst-19160	53	57	generalized	generalized	ADJ
ajst-19160	53	58	regression	regression	NOUN
ajst-19160	53	59	neural	neural	ADJ
ajst-19160	53	60	network	network	NOUN
ajst-19160	53	61	(	(	PUNCT
ajst-19160	53	62	grnn	grnn	PROPN
ajst-19160	53	63	)	)	PUNCT
ajst-19160	53	64	.	.	PUNCT
ajst-19160	54	1	the	the	DET
ajst-19160	54	2	selection	selection	NOUN
ajst-19160	54	3	of	of	ADP
ajst-19160	54	4	the	the	DET
ajst-19160	54	5	best	good	ADJ
ajst-19160	54	6	prediction	prediction	NOUN
ajst-19160	54	7	model	model	NOUN
ajst-19160	54	8	was	be	AUX
ajst-19160	54	9	based	base	VERB
ajst-19160	54	10	on	on	ADP
ajst-19160	54	11	a	a	DET
ajst-19160	54	12	comprehensive	comprehensive	ADJ
ajst-19160	54	13	index	index	NOUN
ajst-19160	54	14	formed	form	VERB
ajst-19160	54	15	via	via	ADP
ajst-19160	54	16	k	k	ADJ
ajst-19160	54	17	-	-	ADJ
ajst-19160	54	18	fold	fold	ADJ
ajst-19160	54	19	cross	cross	NOUN
ajst-19160	54	20	-	-	NOUN
ajst-19160	54	21	validation	validation	ADJ
ajst-19160	54	22	and	and	CCONJ
ajst-19160	54	23	three	three	NUM
ajst-19160	54	24	statistical	statistical	ADJ
ajst-19160	54	25	evaluation	evaluation	NOUN
ajst-19160	54	26	indexes	index	NOUN
ajst-19160	54	27	.	.	PUNCT
ajst-19160	55	1	finally	finally	ADV
ajst-19160	55	2	,	,	PUNCT
ajst-19160	55	3	mathematical	mathematical	ADJ
ajst-19160	55	4	analysis	analysis	NOUN
ajst-19160	55	5	was	be	AUX
ajst-19160	55	6	conducted	conduct	VERB
ajst-19160	55	7	to	to	PART
ajst-19160	55	8	interpret	interpret	VERB
ajst-19160	55	9	the	the	DET
ajst-19160	55	10	results	result	NOUN
ajst-19160	55	11	.	.	PUNCT
ajst-19160	56	1	2	2	X
ajst-19160	56	2	.	.	X
ajst-19160	56	3	finite	finite	PROPN
ajst-19160	56	4	element	element	PROPN
ajst-19160	56	5	model	model	NOUN
ajst-19160	56	6	and	and	CCONJ
ajst-19160	56	7	database	database	NOUN
ajst-19160	56	8	construction	construction	NOUN
ajst-19160	56	9	2.1	2.1	NUM
ajst-19160	56	10	.	.	PUNCT
ajst-19160	57	1	construction	construction	NOUN
ajst-19160	57	2	of	of	ADP
ajst-19160	57	3	3d	3d	PROPN
ajst-19160	57	4	model	model	NOUN
ajst-19160	57	5	conventional	conventional	ADJ
ajst-19160	57	6	corrosion	corrosion	NOUN
ajst-19160	57	7	defects	defect	NOUN
ajst-19160	57	8	are	be	AUX
ajst-19160	57	9	irregular	irregular	ADJ
ajst-19160	57	10	,	,	PUNCT
ajst-19160	57	11	so	so	SCONJ
ajst-19160	57	12	this	this	DET
ajst-19160	57	13	paper	paper	NOUN
ajst-19160	57	14	simplifies	simplify	VERB
ajst-19160	57	15	them	they	PRON
ajst-19160	57	16	,	,	PUNCT
ajst-19160	57	17	and	and	CCONJ
ajst-19160	57	18	the	the	DET
ajst-19160	57	19	axial	axial	ADJ
ajst-19160	57	20	projection	projection	NOUN
ajst-19160	57	21	of	of	ADP
ajst-19160	57	22	corrosion	corrosion	NOUN
ajst-19160	57	23	defects	defect	NOUN
ajst-19160	57	24	is	be	AUX
ajst-19160	57	25	shown	show	VERB
ajst-19160	57	26	in	in	ADP
ajst-19160	57	27	fig	fig	NOUN
ajst-19160	57	28	.	.	PUNCT
ajst-19160	58	1	1	1	X
ajst-19160	58	2	.	.	PUNCT
ajst-19160	58	3	then	then	ADV
ajst-19160	58	4	,	,	PUNCT
ajst-19160	58	5	the	the	DET
ajst-19160	58	6	internal	internal	ADJ
ajst-19160	58	7	corrosion	corrosion	NOUN
ajst-19160	58	8	defect	defect	NOUN
ajst-19160	58	9	model	model	NOUN
ajst-19160	58	10	was	be	AUX
ajst-19160	58	11	established	establish	VERB
ajst-19160	58	12	in	in	ADP
ajst-19160	58	13	abaqus	abaqus	NOUN
ajst-19160	58	14	by	by	ADP
ajst-19160	58	15	using	use	VERB
ajst-19160	58	16	solid	solid	ADJ
ajst-19160	58	17	element	element	NOUN
ajst-19160	58	18	.	.	PUNCT
ajst-19160	59	1	the	the	DET
ajst-19160	59	2	relevant	relevant	ADJ
ajst-19160	59	3	parameters	parameter	NOUN
ajst-19160	59	4	of	of	ADP
ajst-19160	59	5	the	the	DET
ajst-19160	59	6	three	three	NUM
ajst-19160	59	7	-	-	PUNCT
ajst-19160	59	8	dimensional	dimensional	ADJ
ajst-19160	59	9	solid	solid	ADJ
ajst-19160	59	10	model	model	NOUN
ajst-19160	59	11	are	be	AUX
ajst-19160	59	12	defined	define	VERB
ajst-19160	59	13	as	as	SCONJ
ajst-19160	59	14	follows	follow	VERB
ajst-19160	59	15	:	:	PUNCT
ajst-19160	59	16	1	1	NUM
ajst-19160	59	17	)	)	PUNCT
ajst-19160	59	18	defect	defect	VERB
ajst-19160	59	19	geometric	geometric	ADJ
ajst-19160	59	20	parameters	parameter	NOUN
ajst-19160	59	21	:	:	PUNCT
ajst-19160	59	22	the	the	DET
ajst-19160	59	23	pipeline	pipeline	NOUN
ajst-19160	59	24	has	have	VERB
ajst-19160	59	25	good	good	ADJ
ajst-19160	59	26	symmetry	symmetry	NOUN
ajst-19160	59	27	.	.	PUNCT
ajst-19160	60	1	in	in	ADP
ajst-19160	60	2	order	order	NOUN
ajst-19160	60	3	to	to	PART
ajst-19160	60	4	improve	improve	VERB
ajst-19160	60	5	the	the	DET
ajst-19160	60	6	calculation	calculation	NOUN
ajst-19160	60	7	efficiency	efficiency	NOUN
ajst-19160	60	8	,	,	PUNCT
ajst-19160	60	9	1/	1/	NUM
ajst-19160	60	10	4	4	NUM
ajst-19160	60	11	of	of	ADP
ajst-19160	60	12	the	the	DET
ajst-19160	60	13	pipeline	pipeline	NOUN
ajst-19160	60	14	with	with	ADP
ajst-19160	60	15	uniform	uniform	ADJ
ajst-19160	60	16	internal	internal	ADJ
ajst-19160	60	17	corrosion	corrosion	NOUN
ajst-19160	60	18	defects	defect	NOUN
ajst-19160	60	19	is	be	AUX
ajst-19160	60	20	taken	take	VERB
ajst-19160	60	21	.	.	PUNCT
ajst-19160	61	1	in	in	ADP
ajst-19160	61	2	fig	fig	NOUN
ajst-19160	61	3	.	.	PUNCT
ajst-19160	62	1	2	2	NUM
ajst-19160	62	2	,	,	PUNCT
ajst-19160	62	3	d	d	NOUN
ajst-19160	62	4	,	,	PUNCT
ajst-19160	62	5	l	l	NOUN
ajst-19160	62	6	,	,	PUNCT
ajst-19160	62	7	and	and	CCONJ
ajst-19160	62	8	w	w	PART
ajst-19160	62	9	represent	represent	VERB
ajst-19160	62	10	the	the	DET
ajst-19160	62	11	depth	depth	NOUN
ajst-19160	62	12	,	,	PUNCT
ajst-19160	62	13	length	length	NOUN
ajst-19160	62	14	and	and	CCONJ
ajst-19160	62	15	width	width	NOUN
ajst-19160	62	16	of	of	ADP
ajst-19160	62	17	the	the	DET
ajst-19160	62	18	defect	defect	NOUN
ajst-19160	62	19	respectively	respectively	ADV
ajst-19160	62	20	.	.	PUNCT
ajst-19160	63	1	2	2	X
ajst-19160	63	2	)	)	PUNCT
ajst-19160	63	3	the	the	DET
ajst-19160	63	4	definition	definition	NOUN
ajst-19160	63	5	of	of	ADP
ajst-19160	63	6	material	material	NOUN
ajst-19160	63	7	and	and	CCONJ
ajst-19160	63	8	damage	damage	NOUN
ajst-19160	63	9	:	:	PUNCT
ajst-19160	63	10	this	this	DET
ajst-19160	63	11	paper	paper	NOUN
ajst-19160	63	12	takes	take	VERB
ajst-19160	63	13	api	api	NOUN
ajst-19160	64	1	5l	5l	NUM
ajst-19160	64	2	x65	x65	NOUN
ajst-19160	64	3	pipeline	pipeline	NOUN
ajst-19160	64	4	as	as	ADP
ajst-19160	64	5	an	an	DET
ajst-19160	64	6	example	example	NOUN
ajst-19160	64	7	,	,	PUNCT
ajst-19160	64	8	which	which	PRON
ajst-19160	64	9	has	have	AUX
ajst-19160	64	10	been	be	AUX
ajst-19160	64	11	widely	widely	ADV
ajst-19160	64	12	used	use	VERB
ajst-19160	64	13	in	in	ADP
ajst-19160	64	14	submarine	submarine	NOUN
ajst-19160	64	15	pipeline	pipeline	NOUN
ajst-19160	64	16	projects	project	NOUN
ajst-19160	64	17	[	[	X
ajst-19160	64	18	15	15	NUM
ajst-19160	64	19	]	]	PUNCT
ajst-19160	64	20	.	.	PUNCT
ajst-19160	65	1	in	in	ADP
ajst-19160	65	2	the	the	DET
ajst-19160	65	3	isotropic	isotropic	ADJ
ajst-19160	65	4	plastic	plastic	NOUN
ajst-19160	65	5	zone	zone	NOUN
ajst-19160	65	6	of	of	ADP
ajst-19160	65	7	material	material	PROPN
ajst-19160	65	8	nonlinear	nonlinear	ADJ
ajst-19160	65	9	behavior	behavior	NOUN
ajst-19160	65	10	,	,	PUNCT
ajst-19160	65	11	nlgeom	nlgeom	PROPN
ajst-19160	65	12	in	in	ADP
ajst-19160	65	13	abaqus	abaqus	NOUN
ajst-19160	65	14	is	be	AUX
ajst-19160	65	15	used	use	VERB
ajst-19160	65	16	to	to	PART
ajst-19160	65	17	consider	consider	VERB
ajst-19160	65	18	geometric	geometric	ADJ
ajst-19160	65	19	nonlinearity	nonlinearity	NOUN
ajst-19160	65	20	.	.	PUNCT
ajst-19160	66	1	the	the	DET
ajst-19160	66	2	ultimate	ultimate	ADJ
ajst-19160	66	3	condition	condition	NOUN
ajst-19160	66	4	for	for	ADP
ajst-19160	66	5	the	the	DET
ajst-19160	66	6	failure	failure	NOUN
ajst-19160	66	7	of	of	ADP
ajst-19160	66	8	the	the	DET
ajst-19160	66	9	pipeline	pipeline	NOUN
ajst-19160	66	10	is	be	AUX
ajst-19160	66	11	:	:	PUNCT
ajst-19160	66	12	the	the	DET
ajst-19160	66	13	defective	defective	ADJ
ajst-19160	66	14	pipeline	pipeline	NOUN
ajst-19160	66	15	is	be	AUX
ajst-19160	66	16	subjected	subject	VERB
ajst-19160	66	17	to	to	ADP
ajst-19160	66	18	ultimate	ultimate	ADJ
ajst-19160	66	19	internal	internal	ADJ
ajst-19160	66	20	pressure	pressure	NOUN
ajst-19160	66	21	,	,	PUNCT
ajst-19160	66	22	and	and	CCONJ
ajst-19160	66	23	the	the	DET
ajst-19160	66	24	pipeline	pipeline	NOUN
ajst-19160	66	25	material	material	PROPN
ajst-19160	66	26	von	von	PROPN
ajst-19160	66	27	-	-	PUNCT
ajst-19160	66	28	mises	mises	PROPN
ajst-19160	66	29	stress	stress	NOUN
ajst-19160	66	30	reaches	reach	VERB
ajst-19160	66	31	the	the	DET
ajst-19160	66	32	ultimate	ultimate	ADJ
ajst-19160	66	33	tensile	tensile	NOUN
ajst-19160	66	34	strength	strength	NOUN
ajst-19160	66	35	,	,	PUNCT
ajst-19160	66	36	and	and	CCONJ
ajst-19160	66	37	the	the	DET
ajst-19160	66	38	pipeline	pipeline	NOUN
ajst-19160	66	39	is	be	AUX
ajst-19160	66	40	destroyed	destroy	VERB
ajst-19160	66	41	[	[	PUNCT
ajst-19160	66	42	16	16	NUM
ajst-19160	66	43	]	]	PUNCT
ajst-19160	66	44	.	.	PUNCT
ajst-19160	67	1	the	the	DET
ajst-19160	67	2	remaining	remain	VERB
ajst-19160	67	3	mechanical	mechanical	ADJ
ajst-19160	67	4	properties	property	NOUN
ajst-19160	67	5	and	and	CCONJ
ajst-19160	67	6	physical	physical	ADJ
ajst-19160	67	7	properties	property	NOUN
ajst-19160	67	8	are	be	AUX
ajst-19160	67	9	shown	show	VERB
ajst-19160	67	10	in	in	ADP
ajst-19160	67	11	table	table	NOUN
ajst-19160	67	12	1	1	NUM
ajst-19160	67	13	.	.	NOUN
ajst-19160	67	14	3	3	X
ajst-19160	67	15	)	)	PUNCT
ajst-19160	67	16	material	material	NOUN
ajst-19160	67	17	boundary	boundary	ADJ
ajst-19160	67	18	conditions	condition	NOUN
ajst-19160	67	19	and	and	CCONJ
ajst-19160	67	20	loads	load	NOUN
ajst-19160	67	21	:	:	PUNCT
ajst-19160	67	22	fig	fig	NOUN
ajst-19160	67	23	.	.	PUNCT
ajst-19160	68	1	3	3	NUM
ajst-19160	68	2	shows	show	VERB
ajst-19160	68	3	that	that	SCONJ
ajst-19160	68	4	both	both	DET
ajst-19160	68	5	surfaces	surface	NOUN
ajst-19160	68	6	a	a	PRON
ajst-19160	68	7	and	and	CCONJ
ajst-19160	68	8	b	b	NOUN
ajst-19160	68	9	are	be	AUX
ajst-19160	68	10	subject	subject	ADJ
ajst-19160	68	11	to	to	ADP
ajst-19160	68	12	displacement	displacement	ADJ
ajst-19160	68	13	constraints	constraint	NOUN
ajst-19160	68	14	from	from	ADP
ajst-19160	68	15	the	the	DET
ajst-19160	68	16	z	z	NOUN
ajst-19160	68	17	direction	direction	NOUN
ajst-19160	68	18	;	;	PUNCT
ajst-19160	68	19	the	the	DET
ajst-19160	68	20	c	c	NOUN
ajst-19160	68	21	and	and	CCONJ
ajst-19160	68	22	d	d	PROPN
ajst-19160	68	23	surfaces	surface	NOUN
ajst-19160	68	24	are	be	AUX
ajst-19160	68	25	constrained	constrain	VERB
ajst-19160	68	26	by	by	ADP
ajst-19160	68	27	displacements	displacement	NOUN
ajst-19160	68	28	from	from	ADP
ajst-19160	68	29	the	the	DET
ajst-19160	68	30	x	x	NOUN
ajst-19160	68	31	and	and	CCONJ
ajst-19160	68	32	y	y	PROPN
ajst-19160	68	33	directions	direction	NOUN
ajst-19160	68	34	,	,	PUNCT
ajst-19160	68	35	respectively	respectively	ADV
ajst-19160	68	36	.	.	PUNCT
ajst-19160	69	1	the	the	DET
ajst-19160	69	2	hydrostatic	hydrostatic	ADJ
ajst-19160	69	3	pressure	pressure	NOUN
ajst-19160	69	4	p	p	NOUN
ajst-19160	69	5	outside	outside	ADP
ajst-19160	69	6	the	the	DET
ajst-19160	69	7	pipeline	pipeline	NOUN
ajst-19160	69	8	is	be	AUX
ajst-19160	69	9	also	also	ADV
ajst-19160	69	10	affected	affect	VERB
ajst-19160	69	11	by	by	ADP
ajst-19160	69	12	seawater	seawater	NOUN
ajst-19160	69	13	,	,	PUNCT
ajst-19160	69	14	which	which	PRON
ajst-19160	69	15	is	be	AUX
ajst-19160	69	16	calculated	calculate	VERB
ajst-19160	69	17	by	by	ADP
ajst-19160	69	18	formula	formula	NOUN
ajst-19160	69	19	p	p	PROPN
ajst-19160	69	20	gh	gh	PROPN
ajst-19160	69	21	.	.	PUNCT
ajst-19160	70	1	4	4	X
ajst-19160	70	2	)	)	PUNCT
ajst-19160	70	3	mesh	mesh	NOUN
ajst-19160	70	4	parameters	parameter	NOUN
ajst-19160	70	5	:	:	PUNCT
ajst-19160	70	6	the	the	DET
ajst-19160	70	7	mesh	mesh	NOUN
ajst-19160	70	8	network	network	NOUN
ajst-19160	70	9	is	be	AUX
ajst-19160	70	10	constructed	construct	VERB
ajst-19160	70	11	utilizing	utilize	VERB
ajst-19160	70	12	eight	eight	NUM
ajst-19160	70	13	-	-	PUNCT
ajst-19160	70	14	node	node	ADJ
ajst-19160	70	15	linear	linear	ADJ
ajst-19160	70	16	hexahedral	hexahedral	ADJ
ajst-19160	70	17	simplified	simplified	ADJ
ajst-19160	70	18	integral	integral	ADJ
ajst-19160	70	19	elements	element	NOUN
ajst-19160	70	20	.	.	PUNCT
ajst-19160	71	1	when	when	SCONJ
ajst-19160	71	2	compared	compare	VERB
ajst-19160	71	3	with	with	ADP
ajst-19160	71	4	tetrahedral	tetrahedral	ADJ
ajst-19160	71	5	elements	element	NOUN
ajst-19160	71	6	,	,	PUNCT
ajst-19160	71	7	their	their	PRON
ajst-19160	71	8	calculation	calculation	NOUN
ajst-19160	71	9	outcomes	outcome	NOUN
ajst-19160	71	10	are	be	AUX
ajst-19160	71	11	more	more	ADV
ajst-19160	71	12	accurate	accurate	ADJ
ajst-19160	71	13	[	[	X
ajst-19160	71	14	17	17	NUM
ajst-19160	71	15	]	]	PUNCT
ajst-19160	71	16	.	.	PUNCT
ajst-19160	72	1	to	to	PART
ajst-19160	72	2	account	account	VERB
ajst-19160	72	3	for	for	ADP
ajst-19160	72	4	the	the	DET
ajst-19160	72	5	quality	quality	NOUN
ajst-19160	72	6	of	of	ADP
ajst-19160	72	7	the	the	DET
ajst-19160	72	8	grid	grid	NOUN
ajst-19160	72	9	,	,	PUNCT
ajst-19160	72	10	the	the	DET
ajst-19160	72	11	numerical	numerical	ADJ
ajst-19160	72	12	model	model	NOUN
ajst-19160	72	13	is	be	AUX
ajst-19160	72	14	partitioned	partition	VERB
ajst-19160	72	15	into	into	ADP
ajst-19160	72	16	dense	dense	ADJ
ajst-19160	72	17	and	and	CCONJ
ajst-19160	72	18	sparse	sparse	ADJ
ajst-19160	72	19	areas	area	NOUN
ajst-19160	72	20	,	,	PUNCT
ajst-19160	72	21	as	as	SCONJ
ajst-19160	72	22	depicted	depict	VERB
ajst-19160	72	23	in	in	ADP
ajst-19160	72	24	fig	fig	NOUN
ajst-19160	72	25	.	.	PUNCT
ajst-19160	73	1	4	4	X
ajst-19160	73	2	.	.	X
ajst-19160	73	3	the	the	DET
ajst-19160	73	4	dense	dense	ADJ
ajst-19160	73	5	area	area	NOUN
ajst-19160	73	6	employs	employ	VERB
ajst-19160	73	7	a	a	DET
ajst-19160	73	8	mesh	mesh	NOUN
ajst-19160	73	9	size	size	NOUN
ajst-19160	73	10	of	of	ADP
ajst-19160	73	11	0.5	0.5	NUM
ajst-19160	73	12	-	-	SYM
ajst-19160	73	13	1.2	1.2	NUM
ajst-19160	73	14	mm	mm	NOUN
ajst-19160	73	15	.	.	PUNCT
ajst-19160	74	1	a	a	DET
ajst-19160	74	2	blasting	blast	VERB
ajst-19160	74	3	test	test	NOUN
ajst-19160	74	4	was	be	AUX
ajst-19160	74	5	conducted	conduct	VERB
ajst-19160	74	6	on	on	ADP
ajst-19160	74	7	x65	x65	NOUN
ajst-19160	74	8	pipeline	pipeline	NOUN
ajst-19160	74	9	by	by	ADP
ajst-19160	74	10	kang	kang	PROPN
ajst-19160	74	11	,	,	PUNCT
ajst-19160	74	12	and	and	CCONJ
ajst-19160	74	13	the	the	DET
ajst-19160	74	14	experimental	experimental	ADJ
ajst-19160	74	15	results	result	NOUN
ajst-19160	74	16	were	be	AUX
ajst-19160	74	17	compared	compare	VERB
ajst-19160	74	18	with	with	ADP
ajst-19160	74	19	the	the	DET
ajst-19160	74	20	simulation	simulation	NOUN
ajst-19160	74	21	outcomes	outcome	NOUN
ajst-19160	74	22	,	,	PUNCT
ajst-19160	74	23	as	as	SCONJ
ajst-19160	74	24	shown	show	VERB
ajst-19160	74	25	in	in	ADP
ajst-19160	74	26	table	table	NOUN
ajst-19160	74	27	2	2	NUM
ajst-19160	74	28	.	.	PUNCT
ajst-19160	74	29	figure	figure	NOUN
ajst-19160	74	30	1	1	NUM
ajst-19160	74	31	.	.	PUNCT
ajst-19160	74	32	simplified	simplify	VERB
ajst-19160	74	33	schematic	schematic	ADJ
ajst-19160	74	34	diagram	diagram	NOUN
ajst-19160	74	35	of	of	ADP
ajst-19160	74	36	corrosion	corrosion	NOUN
ajst-19160	74	37	defects	defect	NOUN
ajst-19160	74	38	.	.	PUNCT
ajst-19160	75	1	figure	figure	NOUN
ajst-19160	75	2	2	2	NUM
ajst-19160	75	3	.	.	PUNCT
ajst-19160	75	4	geometric	geometric	ADJ
ajst-19160	75	5	parameters	parameter	NOUN
ajst-19160	75	6	of	of	ADP
ajst-19160	75	7	corrosion	corrosion	NOUN
ajst-19160	75	8	defects	defect	NOUN
ajst-19160	75	9	.	.	PUNCT
ajst-19160	76	1	figure	figure	VERB
ajst-19160	76	2	3	3	NUM
ajst-19160	76	3	.	.	PUNCT
ajst-19160	77	1	boundary	boundary	ADJ
ajst-19160	77	2	condition	condition	NOUN
ajst-19160	77	3	diagram	diagram	NOUN
ajst-19160	77	4	.	.	PUNCT
ajst-19160	78	1	figure	figure	NOUN
ajst-19160	78	2	4	4	NUM
ajst-19160	78	3	.	.	PUNCT
ajst-19160	78	4	grid	grid	NOUN
ajst-19160	78	5	division	division	NOUN
ajst-19160	78	6	diagram	diagram	VERB
ajst-19160	78	7	120	120	NUM
ajst-19160	78	8	table	table	NOUN
ajst-19160	78	9	1	1	NUM
ajst-19160	78	10	.	.	PUNCT
ajst-19160	79	1	mechanical	mechanical	ADJ
ajst-19160	79	2	and	and	CCONJ
ajst-19160	79	3	physical	physical	ADJ
ajst-19160	79	4	properties	property	NOUN
ajst-19160	79	5	of	of	ADP
ajst-19160	79	6	corrosion	corrosion	NOUN
ajst-19160	79	7	defects	defect	NOUN
ajst-19160	79	8	.	.	PUNCT
ajst-19160	80	1	parameter	parameter	NOUN
ajst-19160	80	2	symbol	symbol	NOUN
ajst-19160	80	3	value	value	NOUN
ajst-19160	80	4	parameter	parameter	NOUN
ajst-19160	80	5	symbol	symbol	NOUN
ajst-19160	80	6	value	value	NOUN
ajst-19160	80	7	pipeline	pipeline	NOUN
ajst-19160	80	8	outer	outer	ADJ
ajst-19160	80	9	diameter	diameter	NOUN
ajst-19160	80	10	od	od	ADV
ajst-19160	80	11	762	762	NUM
ajst-19160	80	12	mm	mm	PROPN
ajst-19160	80	13	steel	steel	NOUN
ajst-19160	80	14	poisson	poisson	NOUN
ajst-19160	80	15	’s	’s	PART
ajst-19160	80	16	ratio	ratio	NOUN
ajst-19160	80	17			NOUN
ajst-19160	80	18	0.3	0.3	NUM
ajst-19160	80	19	young	young	PROPN
ajst-19160	80	20	’s	’s	PART
ajst-19160	80	21	modulus	modulus	NOUN
ajst-19160	80	22	e	e	PROPN
ajst-19160	80	23	2.1gpa	2.1gpa	NUM
ajst-19160	80	24	steel	steel	NOUN
ajst-19160	80	25	density	density	NOUN
ajst-19160	80	26	s	s	NOUN
ajst-19160	80	27	7850	7850	NUM
ajst-19160	80	28	kg	kg	NOUN
ajst-19160	80	29	/	/	SYM
ajst-19160	80	30	m3	m3	PROPN
ajst-19160	80	31	engineering	engineering	NOUN
ajst-19160	80	32	yield	yield	NOUN
ajst-19160	80	33	stress	stress	NOUN
ajst-19160	80	34	e	e	PROPN
ajst-19160	80	35	ys	ys	PROPN
ajst-19160	80	36	464.5mpa	464.5mpa	PROPN
ajst-19160	80	37	sea	sea	PROPN
ajst-19160	80	38	water	water	NOUN
ajst-19160	80	39	density	density	NOUN
ajst-19160	80	40	w	w	VERB
ajst-19160	80	41	1020kg	1020kg	PROPN
ajst-19160	80	42	/	/	SYM
ajst-19160	80	43	m3	m3	PROPN
ajst-19160	80	44	engineering	engineering	NOUN
ajst-19160	80	45	ultimate	ultimate	ADJ
ajst-19160	80	46	stress	stress	NOUN
ajst-19160	80	47	eus	eus	NOUN
ajst-19160	80	48	563.8mpa	563.8mpa	DET
ajst-19160	80	49	table	table	NOUN
ajst-19160	80	50	2	2	NUM
ajst-19160	80	51	.	.	PUNCT
ajst-19160	80	52	simulation	simulation	NOUN
ajst-19160	80	53	results	result	VERB
ajst-19160	80	54	verification	verification	NOUN
ajst-19160	80	55	number	number	NOUN
ajst-19160	80	56	corrosion	corrosion	NOUN
ajst-19160	80	57	width	width	NOUN
ajst-19160	80	58	w	w	ADP
ajst-19160	80	59	(	(	PUNCT
ajst-19160	80	60			PROPN
ajst-19160	80	61	)	)	PUNCT
ajst-19160	80	62	corrosion	corrosion	NOUN
ajst-19160	80	63	length	length	NOUN
ajst-19160	80	64	l	l	PROPN
ajst-19160	80	65	(	(	PUNCT
ajst-19160	80	66	mm	mm	NOUN
ajst-19160	80	67	)	)	PUNCT
ajst-19160	80	68	corrosion	corrosion	NOUN
ajst-19160	80	69	depth	depth	NOUN
ajst-19160	80	70	d	d	NOUN
ajst-19160	80	71	(	(	PUNCT
ajst-19160	80	72	mm	mm	NOUN
ajst-19160	80	73	)	)	PUNCT
ajst-19160	80	74	pipeline	pipeline	NOUN
ajst-19160	80	75	outer	outer	ADJ
ajst-19160	80	76	diameter	diameter	NOUN
ajst-19160	80	77	od	od	PROPN
ajst-19160	80	78	(	(	PUNCT
ajst-19160	80	79	mm	mm	NOUN
ajst-19160	80	80	)	)	PUNCT
ajst-19160	80	81	pipeline	pipeline	NOUN
ajst-19160	80	82	wall	wall	NOUN
ajst-19160	80	83	thickness	thickness	PROPN
ajst-19160	80	84	t	t	PROPN
ajst-19160	80	85	(	(	PUNCT
ajst-19160	80	86	mm	mm	NOUN
ajst-19160	80	87	)	)	PUNCT
ajst-19160	80	88	experiment	experiment	NOUN
ajst-19160	80	89	(	(	PUNCT
ajst-19160	80	90	mpa	mpa	PROPN
ajst-19160	80	91	)	)	PUNCT
ajst-19160	80	92	finite	finite	PROPN
ajst-19160	80	93	element	element	PROPN
ajst-19160	80	94	simulation	simulation	PROPN
ajst-19160	80	95	(	(	PUNCT
ajst-19160	80	96	mpa	mpa	PROPN
ajst-19160	80	97	)	)	PUNCT
ajst-19160	80	98	relative	relative	ADJ
ajst-19160	80	99	error	error	NOUN
ajst-19160	80	100	(	(	PUNCT
ajst-19160	80	101	%	%	NOUN
ajst-19160	80	102	)	)	PUNCT
ajst-19160	80	103	no.1	no.1	VERB
ajst-19160	80	104	10	10	NUM
ajst-19160	80	105	200	200	NUM
ajst-19160	80	106	4.4	4.4	NUM
ajst-19160	80	107	762	762	NUM
ajst-19160	80	108	17.5	17.5	NUM
ajst-19160	80	109	24.11	24.11	NUM
ajst-19160	80	110	24.90	24.90	NUM
ajst-19160	80	111	0.03	0.03	NUM
ajst-19160	80	112	%	%	NOUN
ajst-19160	80	113	no.2	no.2	PROPN
ajst-19160	80	114	10	10	NUM
ajst-19160	80	115	200	200	NUM
ajst-19160	80	116	8.8	8.8	NUM
ajst-19160	80	117	762	762	NUM
ajst-19160	80	118	17.5	17.5	NUM
ajst-19160	80	119	21.74	21.74	NUM
ajst-19160	80	120	21.30	21.30	NUM
ajst-19160	80	121	2.02	2.02	NUM
ajst-19160	80	122	%	%	NOUN
ajst-19160	80	123	no.3	no.3	NOUN
ajst-19160	80	124	10	10	NUM
ajst-19160	80	125	100	100	NUM
ajst-19160	80	126	8.8	8.8	NUM
ajst-19160	80	127	762	762	NUM
ajst-19160	80	128	17.5	17.5	NUM
ajst-19160	80	129	24.30	24.30	NUM
ajst-19160	80	130	24.30	24.30	NUM
ajst-19160	80	131	0	0	NUM
ajst-19160	80	132	no.4	no.4	PROPN
ajst-19160	80	133	10	10	NUM
ajst-19160	80	134	300	300	NUM
ajst-19160	80	135	8.8	8.8	NUM
ajst-19160	80	136	762	762	NUM
ajst-19160	80	137	17.5	17.5	NUM
ajst-19160	80	138	19.08	19.08	NUM
ajst-19160	80	139	18.70	18.70	NUM
ajst-19160	80	140	-1.99	-1.99	NOUN
ajst-19160	80	141	%	%	NOUN
ajst-19160	80	142	2.2	2.2	NUM
ajst-19160	80	143	.	.	PUNCT
ajst-19160	81	1	database	database	NOUN
ajst-19160	81	2	construction	construction	NOUN
ajst-19160	81	3	of	of	ADP
ajst-19160	81	4	machine	machine	NOUN
ajst-19160	81	5	learning	learning	NOUN
ajst-19160	81	6	prediction	prediction	NOUN
ajst-19160	81	7	model	model	NOUN
ajst-19160	81	8	based	base	VERB
ajst-19160	81	9	on	on	ADP
ajst-19160	81	10	the	the	DET
ajst-19160	81	11	aforementioned	aforementioned	ADJ
ajst-19160	81	12	analysis	analysis	NOUN
ajst-19160	81	13	,	,	PUNCT
ajst-19160	81	14	it	it	PRON
ajst-19160	81	15	is	be	AUX
ajst-19160	81	16	evident	evident	ADJ
ajst-19160	81	17	that	that	SCONJ
ajst-19160	81	18	the	the	DET
ajst-19160	81	19	computational	computational	ADJ
ajst-19160	81	20	expense	expense	NOUN
ajst-19160	81	21	of	of	ADP
ajst-19160	81	22	fem	fem	NOUN
ajst-19160	81	23	is	be	AUX
ajst-19160	81	24	substantial	substantial	ADJ
ajst-19160	81	25	.	.	PUNCT
ajst-19160	82	1	therefore	therefore	ADV
ajst-19160	82	2	,	,	PUNCT
ajst-19160	82	3	the	the	DET
ajst-19160	82	4	svm	svm	ADJ
ajst-19160	82	5	model	model	NOUN
ajst-19160	82	6	,	,	PUNCT
ajst-19160	82	7	which	which	PRON
ajst-19160	82	8	exhibits	exhibit	VERB
ajst-19160	82	9	exceptional	exceptional	ADJ
ajst-19160	82	10	nonlinear	nonlinear	ADJ
ajst-19160	82	11	fitting	fitting	ADJ
ajst-19160	82	12	capabilities	capability	NOUN
ajst-19160	82	13	,	,	PUNCT
ajst-19160	82	14	is	be	AUX
ajst-19160	82	15	an	an	DET
ajst-19160	82	16	optimal	optimal	ADJ
ajst-19160	82	17	choice	choice	NOUN
ajst-19160	82	18	for	for	ADP
ajst-19160	82	19	enhancing	enhance	VERB
ajst-19160	82	20	computational	computational	ADJ
ajst-19160	82	21	efficiency	efficiency	NOUN
ajst-19160	82	22	[	[	X
ajst-19160	82	23	18	18	NUM
ajst-19160	82	24	]	]	PUNCT
ajst-19160	82	25	.	.	PUNCT
ajst-19160	83	1	to	to	PART
ajst-19160	83	2	generate	generate	VERB
ajst-19160	83	3	the	the	DET
ajst-19160	83	4	internal	internal	ADJ
ajst-19160	83	5	corrosion	corrosion	NOUN
ajst-19160	83	6	defect	defect	NOUN
ajst-19160	83	7	model	model	NOUN
ajst-19160	83	8	in	in	ADP
ajst-19160	83	9	batches	batch	NOUN
ajst-19160	83	10	,	,	PUNCT
ajst-19160	83	11	the	the	DET
ajst-19160	83	12	methodology	methodology	NOUN
ajst-19160	83	13	outlined	outline	VERB
ajst-19160	83	14	in	in	ADP
ajst-19160	83	15	chapter	chapter	NOUN
ajst-19160	83	16	1.1	1.1	NUM
ajst-19160	83	17	is	be	AUX
ajst-19160	83	18	implemented	implement	VERB
ajst-19160	83	19	using	use	VERB
ajst-19160	83	20	a	a	DET
ajst-19160	83	21	python	python	NOUN
ajst-19160	83	22	script	script	NOUN
ajst-19160	83	23	.	.	PUNCT
ajst-19160	84	1	it	it	PRON
ajst-19160	84	2	is	be	AUX
ajst-19160	84	3	worth	worth	ADJ
ajst-19160	84	4	noting	note	VERB
ajst-19160	84	5	that	that	SCONJ
ajst-19160	84	6	the	the	DET
ajst-19160	84	7	script	script	NOUN
ajst-19160	84	8	construction	construction	NOUN
ajst-19160	84	9	steps	step	NOUN
ajst-19160	84	10	are	be	AUX
ajst-19160	84	11	:	:	PUNCT
ajst-19160	84	12	1	1	X
ajst-19160	84	13	)	)	PUNCT
ajst-19160	84	14	firstly	firstly	ADV
ajst-19160	84	15	,	,	PUNCT
ajst-19160	84	16	the	the	DET
ajst-19160	84	17	model	model	NOUN
ajst-19160	84	18	is	be	AUX
ajst-19160	84	19	established	establish	VERB
ajst-19160	84	20	in	in	ADP
ajst-19160	84	21	accordance	accordance	NOUN
ajst-19160	84	22	with	with	ADP
ajst-19160	84	23	chapter	chapter	NOUN
ajst-19160	84	24	1.1	1.1	NUM
ajst-19160	84	25	,	,	PUNCT
ajst-19160	84	26	and	and	CCONJ
ajst-19160	84	27	the	the	DET
ajst-19160	84	28	python	python	NOUN
ajst-19160	84	29	script	script	NOUN
ajst-19160	84	30	for	for	ADP
ajst-19160	84	31	the	the	DET
ajst-19160	84	32	generated	generate	VERB
ajst-19160	84	33	model	model	NOUN
ajst-19160	84	34	is	be	AUX
ajst-19160	84	35	parameterized	parameterized	ADJ
ajst-19160	84	36	.	.	PUNCT
ajst-19160	85	1	2	2	X
ajst-19160	85	2	)	)	PUNCT
ajst-19160	85	3	the	the	DET
ajst-19160	85	4	model	model	NOUN
ajst-19160	85	5	is	be	AUX
ajst-19160	85	6	set	set	VERB
ajst-19160	85	7	to	to	PART
ajst-19160	85	8	comprise	comprise	VERB
ajst-19160	85	9	of	of	ADP
ajst-19160	85	10	two	two	NUM
ajst-19160	85	11	load	load	NOUN
ajst-19160	85	12	steps	step	NOUN
ajst-19160	85	13	.	.	PUNCT
ajst-19160	86	1	the	the	DET
ajst-19160	86	2	first	first	ADJ
ajst-19160	86	3	load	load	NOUN
ajst-19160	86	4	step	step	NOUN
ajst-19160	86	5	is	be	AUX
ajst-19160	86	6	designed	design	VERB
ajst-19160	86	7	to	to	PART
ajst-19160	86	8	apply	apply	VERB
ajst-19160	86	9	the	the	DET
ajst-19160	86	10	seawater	seawater	NOUN
ajst-19160	86	11	pressure	pressure	NOUN
ajst-19160	86	12	,	,	PUNCT
ajst-19160	86	13	with	with	ADP
ajst-19160	86	14	a	a	DET
ajst-19160	86	15	total	total	ADJ
ajst-19160	86	16	loading	loading	NOUN
ajst-19160	86	17	time	time	NOUN
ajst-19160	86	18	of	of	ADP
ajst-19160	86	19	1	1	NUM
ajst-19160	86	20	second	second	ADJ
ajst-19160	86	21	.	.	PUNCT
ajst-19160	87	1	the	the	DET
ajst-19160	87	2	second	second	ADJ
ajst-19160	87	3	load	load	NOUN
ajst-19160	87	4	step	step	NOUN
ajst-19160	87	5	is	be	AUX
ajst-19160	87	6	used	use	VERB
ajst-19160	87	7	to	to	PART
ajst-19160	87	8	apply	apply	VERB
ajst-19160	87	9	pressure	pressure	NOUN
ajst-19160	87	10	inside	inside	ADP
ajst-19160	87	11	the	the	DET
ajst-19160	87	12	tube	tube	NOUN
ajst-19160	87	13	,	,	PUNCT
ajst-19160	87	14	with	with	ADP
ajst-19160	87	15	a	a	DET
ajst-19160	87	16	total	total	ADJ
ajst-19160	87	17	loading	loading	NOUN
ajst-19160	87	18	time	time	NOUN
ajst-19160	87	19	of	of	ADP
ajst-19160	87	20	1	1	NUM
ajst-19160	87	21	second	second	NOUN
ajst-19160	87	22	.	.	PUNCT
ajst-19160	88	1	3	3	X
ajst-19160	88	2	)	)	PUNCT
ajst-19160	88	3	to	to	PART
ajst-19160	88	4	achieve	achieve	VERB
ajst-19160	88	5	a	a	DET
ajst-19160	88	6	balance	balance	NOUN
ajst-19160	88	7	between	between	ADP
ajst-19160	88	8	computational	computational	ADJ
ajst-19160	88	9	efficiency	efficiency	NOUN
ajst-19160	88	10	and	and	CCONJ
ajst-19160	88	11	accuracy	accuracy	NOUN
ajst-19160	88	12	,	,	PUNCT
ajst-19160	88	13	the	the	DET
ajst-19160	88	14	internal	internal	ADJ
ajst-19160	88	15	pressure	pressure	NOUN
ajst-19160	88	16	was	be	AUX
ajst-19160	88	17	set	set	VERB
ajst-19160	88	18	at	at	ADP
ajst-19160	88	19	a	a	DET
ajst-19160	88	20	fixed	fix	VERB
ajst-19160	88	21	value	value	NOUN
ajst-19160	88	22	of	of	ADP
ajst-19160	88	23	100	100	NUM
ajst-19160	88	24	mpa	mpa	NOUN
ajst-19160	88	25	,	,	PUNCT
ajst-19160	88	26	and	and	CCONJ
ajst-19160	88	27	a	a	DET
ajst-19160	88	28	linear	linear	ADJ
ajst-19160	88	29	loading	loading	NOUN
ajst-19160	88	30	approach	approach	NOUN
ajst-19160	88	31	was	be	AUX
ajst-19160	88	32	adopted	adopt	VERB
ajst-19160	88	33	.	.	PUNCT
ajst-19160	89	1	given	give	VERB
ajst-19160	89	2	that	that	SCONJ
ajst-19160	89	3	the	the	DET
ajst-19160	89	4	pipeline	pipeline	NOUN
ajst-19160	89	5	can	can	AUX
ajst-19160	89	6	not	not	PART
ajst-19160	89	7	withstand	withstand	VERB
ajst-19160	89	8	the	the	DET
ajst-19160	89	9	internal	internal	ADJ
ajst-19160	89	10	pressure	pressure	NOUN
ajst-19160	89	11	,	,	PUNCT
ajst-19160	89	12	an	an	DET
ajst-19160	89	13	local	local	ADJ
ajst-19160	89	14	intensive	intensive	ADJ
ajst-19160	89	15	time	time	NOUN
ajst-19160	89	16	step	step	NOUN
ajst-19160	89	17	was	be	AUX
ajst-19160	89	18	employed	employ	VERB
ajst-19160	89	19	,	,	PUNCT
ajst-19160	89	20	which	which	PRON
ajst-19160	89	21	enabled	enable	VERB
ajst-19160	89	22	the	the	DET
ajst-19160	89	23	pipeline	pipeline	NOUN
ajst-19160	89	24	to	to	PART
ajst-19160	89	25	be	be	AUX
ajst-19160	89	26	destroyed	destroy	VERB
ajst-19160	89	27	within	within	ADP
ajst-19160	89	28	the	the	DET
ajst-19160	89	29	local	local	ADJ
ajst-19160	89	30	intensive	intensive	ADJ
ajst-19160	89	31	time	time	NOUN
ajst-19160	89	32	interval	interval	NOUN
ajst-19160	89	33	.	.	PUNCT
ajst-19160	90	1	the	the	DET
ajst-19160	90	2	local	local	ADJ
ajst-19160	90	3	intensive	intensive	ADJ
ajst-19160	90	4	time	time	NOUN
ajst-19160	90	5	interval	interval	NOUN
ajst-19160	90	6	was	be	AUX
ajst-19160	90	7	determined	determine	VERB
ajst-19160	90	8	using	use	VERB
ajst-19160	90	9	eq	eq	ADP
ajst-19160	90	10	.	.	PUNCT
ajst-19160	91	1	(	(	PUNCT
ajst-19160	91	2	1	1	NUM
ajst-19160	91	3	)	)	PUNCT
ajst-19160	91	4	.	.	PUNCT
ajst-19160	92	1	the	the	DET
ajst-19160	92	2	time	time	NOUN
ajst-19160	92	3	interval	interval	NOUN
ajst-19160	92	4	of	of	ADP
ajst-19160	92	5	the	the	DET
ajst-19160	92	6	local	local	ADJ
ajst-19160	92	7	intensive	intensive	ADJ
ajst-19160	92	8	interval	interval	NOUN
ajst-19160	92	9	was	be	AUX
ajst-19160	92	10	set	set	VERB
ajst-19160	92	11	to	to	ADP
ajst-19160	92	12	0.001	0.001	NUM
ajst-19160	92	13	,	,	PUNCT
ajst-19160	92	14	which	which	PRON
ajst-19160	92	15	allowed	allow	VERB
ajst-19160	92	16	for	for	ADP
ajst-19160	92	17	the	the	DET
ajst-19160	92	18	calculation	calculation	NOUN
ajst-19160	92	19	result	result	NOUN
ajst-19160	92	20	to	to	PART
ajst-19160	92	21	attain	attain	VERB
ajst-19160	92	22	an	an	DET
ajst-19160	92	23	accuracy	accuracy	NOUN
ajst-19160	92	24	of	of	ADP
ajst-19160	92	25	0.1	0.1	NUM
ajst-19160	92	26	mpa	mpa	NOUN
ajst-19160	92	27	.	.	PUNCT
ajst-19160	93	1			NOUN
ajst-19160	94	1			PUNCT
ajst-19160	94	2			NOUN
ajst-19160	94	3			PROPN
ajst-19160	94	4	12	12	NUM
ajst-19160	94	5	time_start	time_start	NOUN
ajst-19160	94	6	=	=	SYM
ajst-19160	94	7	1	1	NUM
ajst-19160	94	8	-	-	SYM
ajst-19160	94	9	20	20	NUM
ajst-19160	94	10	%	%	NOUN
ajst-19160	94	11	/100	/100	PUNCT
ajst-19160	95	1	_	_	PUNCT
ajst-19160	95	2	/10000	/10000	PUNCT
ajst-19160	96	1	1	1	NUM
ajst-19160	96	2	u	u	NOUN
ajst-19160	96	3	dt	dt	X
ajst-19160	96	4	t	t	PROPN
ajst-19160	96	5	s	s	PROPN
ajst-19160	96	6	t	t	PROPN
ajst-19160	96	7	dd	dd	PROPN
ajst-19160	96	8	t	t	PROPN
ajst-19160	96	9	tm	tm	PRON
ajst-19160	96	10			PROPN
ajst-19160	96	11			PROPN
ajst-19160	96	12			PROPN
ajst-19160	96	13			NOUN
ajst-19160	96	14			PROPN
ajst-19160	96	15			SYM
ajst-19160	96	16			NOUN
ajst-19160	96	17			NOUN
ajst-19160	96	18			NOUN
ajst-19160	96	19			PROPN
ajst-19160	96	20			NUM
ajst-19160	96	21	(	(	PUNCT
ajst-19160	96	22	1	1	NUM
ajst-19160	96	23	)	)	PUNCT
ajst-19160	96	24	where	where	SCONJ
ajst-19160	96	25	:	:	PUNCT
ajst-19160	96	26	time_start	time_start	PRON
ajst-19160	96	27	is	be	AUX
ajst-19160	96	28	the	the	DET
ajst-19160	96	29	starting	starting	NOUN
ajst-19160	96	30	point	point	NOUN
ajst-19160	96	31	of	of	ADP
ajst-19160	96	32	time	time	NOUN
ajst-19160	96	33	,	,	PUNCT
ajst-19160	96	34	where	where	SCONJ
ajst-19160	96	35			NOUN
ajst-19160	96	36			PROPN
ajst-19160	96	37	12	12	NUM
ajst-19160	96	38	1	1	NUM
ajst-19160	96	39	u	u	NOUN
ajst-19160	96	40	dt	dt	X
ajst-19160	96	41	t	t	PROPN
ajst-19160	96	42	dd	dd	PROPN
ajst-19160	96	43	t	t	PROPN
ajst-19160	96	44	tm	tm	PRON
ajst-19160	96	45			PROPN
ajst-19160	96	46			PROPN
ajst-19160	96	47			PROPN
ajst-19160	96	48			NOUN
ajst-19160	96	49			NOUN
ajst-19160	96	50			NOUN
ajst-19160	96	51			NOUN
ajst-19160	96	52			NOUN
ajst-19160	96	53			PROPN
ajst-19160	96	54	is	be	AUX
ajst-19160	96	55	the	the	DET
ajst-19160	96	56	pressure	pressure	NOUN
ajst-19160	96	57	value	value	NOUN
ajst-19160	96	58	obtained	obtain	VERB
ajst-19160	96	59	by	by	ADP
ajst-19160	96	60	the	the	DET
ajst-19160	96	61	dnv	dnv	PROPN
ajst-19160	96	62	-	-	PUNCT
ajst-19160	96	63	rf	rf	NOUN
ajst-19160	96	64	-	-	PUNCT
ajst-19160	96	65	f01	f01	NOUN
ajst-19160	96	66	formula	formula	NOUN
ajst-19160	96	67	method	method	NOUN
ajst-19160	96	68	,	,	PUNCT
ajst-19160	96	69			PROPN
ajst-19160	96	70	1	1	NOUN
ajst-19160	96	71	-	-	PUNCT
ajst-19160	96	72	20	20	NUM
ajst-19160	96	73	%	%	NOUN
ajst-19160	96	74	is	be	AUX
ajst-19160	96	75	the	the	DET
ajst-19160	96	76	80	80	NUM
ajst-19160	96	77	%	%	NOUN
ajst-19160	96	78	pressure	pressure	NOUN
ajst-19160	96	79	value	value	NOUN
ajst-19160	96	80	of	of	ADP
ajst-19160	96	81	the	the	DET
ajst-19160	96	82	formula	formula	NOUN
ajst-19160	96	83	method	method	NOUN
ajst-19160	96	84	,	,	PUNCT
ajst-19160	96	85	and	and	CCONJ
ajst-19160	96	86	the	the	DET
ajst-19160	96	87	formula	formula	NOUN
ajst-19160	96	88	method	method	NOUN
ajst-19160	96	89	is	be	AUX
ajst-19160	96	90	divided	divide	VERB
ajst-19160	96	91	by	by	ADP
ajst-19160	96	92	100	100	NUM
ajst-19160	96	93	to	to	PART
ajst-19160	96	94	convert	convert	VERB
ajst-19160	96	95	the	the	DET
ajst-19160	96	96	time	time	NOUN
ajst-19160	96	97	unit	unit	NOUN
ajst-19160	96	98	to	to	ADP
ajst-19160	96	99	0	0	NUM
ajst-19160	96	100	-	-	SYM
ajst-19160	96	101	1s	1s	NUM
ajst-19160	96	102	.	.	PUNCT
ajst-19160	97	1	2	2	NUM
ajst-19160	97	2	1	1	NUM
ajst-19160	97	3	0.31	0.31	NUM
ajst-19160	97	4	l	l	NOUN
ajst-19160	97	5	m	m	VERB
ajst-19160	98	1	dt	dt	NOUN
ajst-19160	98	2			PROPN
ajst-19160	98	3			PUNCT
ajst-19160	98	4	.	.	PUNCT
ajst-19160	99	1	the	the	DET
ajst-19160	99	2	same	same	ADJ
ajst-19160	99	3	is	be	AUX
ajst-19160	99	4	true	true	ADJ
ajst-19160	99	5	for	for	ADP
ajst-19160	99	6	the	the	DET
ajst-19160	99	7	depth	depth	NOUN
ajst-19160	99	8	of	of	ADP
ajst-19160	99	9	the	the	DET
ajst-19160	99	10	ocean	ocean	NOUN
ajst-19160	99	11	.	.	PUNCT
ajst-19160	100	1	_	_	PRON
ajst-19160	100	2	/10000s	/10000s	PUNCT
ajst-19160	101	1	t	t	PROPN
ajst-19160	101	2	is	be	AUX
ajst-19160	101	3	the	the	DET
ajst-19160	101	4	time	time	NOUN
ajst-19160	101	5	node	node	ADJ
ajst-19160	101	6	effect	effect	NOUN
ajst-19160	101	7	of	of	ADP
ajst-19160	101	8	ocean	ocean	NOUN
ajst-19160	101	9	depth	depth	NOUN
ajst-19160	101	10	estimation	estimation	NOUN
ajst-19160	101	11	.	.	PUNCT
ajst-19160	102	1	the	the	DET
ajst-19160	102	2	end	end	NOUN
ajst-19160	102	3	node	node	NOUN
ajst-19160	102	4	of	of	ADP
ajst-19160	102	5	local	local	ADJ
ajst-19160	102	6	intensive	intensive	ADJ
ajst-19160	102	7	time	time	NOUN
ajst-19160	102	8	is	be	AUX
ajst-19160	102	9	uniformly	uniformly	ADV
ajst-19160	102	10	set	set	VERB
ajst-19160	102	11	to	to	ADP
ajst-19160	102	12	time_end	time_end	VERB
ajst-19160	102	13	=	=	PROPN
ajst-19160	102	14	0.40	0.40	NUM
ajst-19160	102	15	.	.	PUNCT
ajst-19160	103	1	4	4	NUM
ajst-19160	103	2	)	)	PUNCT
ajst-19160	103	3	upon	upon	SCONJ
ajst-19160	103	4	reaching	reach	VERB
ajst-19160	103	5	a	a	DET
ajst-19160	103	6	certain	certain	ADJ
ajst-19160	103	7	period	period	NOUN
ajst-19160	103	8	of	of	ADP
ajst-19160	103	9	time	time	NOUN
ajst-19160	103	10	,	,	PUNCT
ajst-19160	103	11	the	the	DET
ajst-19160	103	12	limit	limit	NOUN
ajst-19160	103	13	tensile	tensile	NOUN
ajst-19160	103	14	stress	stress	NOUN
ajst-19160	103	15	is	be	AUX
ajst-19160	103	16	assessed	assess	VERB
ajst-19160	103	17	to	to	PART
ajst-19160	103	18	determine	determine	VERB
ajst-19160	103	19	whether	whether	SCONJ
ajst-19160	103	20	it	it	PRON
ajst-19160	103	21	has	have	AUX
ajst-19160	103	22	been	be	AUX
ajst-19160	103	23	reached	reach	VERB
ajst-19160	103	24	.	.	PUNCT
ajst-19160	104	1	if	if	SCONJ
ajst-19160	104	2	this	this	PRON
ajst-19160	104	3	is	be	AUX
ajst-19160	104	4	the	the	DET
ajst-19160	104	5	case	case	NOUN
ajst-19160	104	6	,	,	PUNCT
ajst-19160	104	7	proceed	proceed	VERB
ajst-19160	104	8	to	to	PART
ajst-19160	104	9	step	step	VERB
ajst-19160	104	10	1	1	NUM
ajst-19160	104	11	and	and	CCONJ
ajst-19160	104	12	solve	solve	VERB
ajst-19160	104	13	the	the	DET
ajst-19160	104	14	next	next	ADJ
ajst-19160	104	15	inp	inp	PROPN
ajst-19160	104	16	file	file	NOUN
ajst-19160	104	17	.	.	PUNCT
ajst-19160	105	1	on	on	ADP
ajst-19160	105	2	the	the	DET
ajst-19160	105	3	other	other	ADJ
ajst-19160	105	4	hand	hand	NOUN
ajst-19160	105	5	,	,	PUNCT
ajst-19160	105	6	if	if	SCONJ
ajst-19160	105	7	the	the	DET
ajst-19160	105	8	limit	limit	NOUN
ajst-19160	105	9	tensile	tensile	NOUN
ajst-19160	105	10	stress	stress	NOUN
ajst-19160	105	11	has	have	AUX
ajst-19160	105	12	not	not	PART
ajst-19160	105	13	been	be	AUX
ajst-19160	105	14	reached	reach	VERB
ajst-19160	105	15	,	,	PUNCT
ajst-19160	105	16	return	return	VERB
ajst-19160	105	17	to	to	ADP
ajst-19160	105	18	the	the	DET
ajst-19160	105	19	step	step	NOUN
ajst-19160	105	20	3	3	NUM
ajst-19160	105	21	solution	solution	NOUN
ajst-19160	105	22	.	.	PUNCT
ajst-19160	106	1	5	5	X
ajst-19160	106	2	)	)	PUNCT
ajst-19160	106	3	retrieve	retrieve	VERB
ajst-19160	106	4	the	the	DET
ajst-19160	106	5	frame	frame	NOUN
ajst-19160	106	6	number	number	NOUN
ajst-19160	106	7	for	for	ADP
ajst-19160	106	8	the	the	DET
ajst-19160	106	9	maximum	maximum	ADJ
ajst-19160	106	10	stress	stress	NOUN
ajst-19160	106	11	from	from	ADP
ajst-19160	106	12	the	the	DET
ajst-19160	106	13	odb	odb	NOUN
ajst-19160	106	14	file	file	NOUN
ajst-19160	106	15	,	,	PUNCT
ajst-19160	106	16	obtain	obtain	VERB
ajst-19160	106	17	the	the	DET
ajst-19160	106	18	corresponding	corresponding	ADJ
ajst-19160	106	19	time	time	NOUN
ajst-19160	106	20	for	for	ADP
ajst-19160	106	21	this	this	DET
ajst-19160	106	22	frame	frame	NOUN
ajst-19160	106	23	number	number	NOUN
ajst-19160	106	24	,	,	PUNCT
ajst-19160	106	25	and	and	CCONJ
ajst-19160	106	26	decode	decode	VERB
ajst-19160	106	27	this	this	DET
ajst-19160	106	28	time	time	NOUN
ajst-19160	106	29	by	by	ADP
ajst-19160	106	30	multiplying	multiply	VERB
ajst-19160	106	31	it	it	PRON
ajst-19160	106	32	by	by	ADP
ajst-19160	106	33	100	100	NUM
ajst-19160	106	34	to	to	PART
ajst-19160	106	35	obtain	obtain	VERB
ajst-19160	106	36	the	the	DET
ajst-19160	106	37	final	final	ADJ
ajst-19160	106	38	burst	burst	ADJ
ajst-19160	106	39	pressure	pressure	NOUN
ajst-19160	106	40	of	of	ADP
ajst-19160	106	41	the	the	DET
ajst-19160	106	42	pipeline	pipeline	NOUN
ajst-19160	106	43	.	.	PUNCT
ajst-19160	107	1	the	the	DET
ajst-19160	107	2	outer	outer	ADJ
ajst-19160	107	3	diameter	diameter	NOUN
ajst-19160	107	4	od	od	PROPN
ajst-19160	107	5	was	be	AUX
ajst-19160	107	6	762	762	NUM
ajst-19160	107	7	mm	mm	NOUN
ajst-19160	107	8	.	.	PUNCT
ajst-19160	108	1	the	the	DET
ajst-19160	108	2	pipeline	pipeline	NOUN
ajst-19160	108	3	length	length	NOUN
ajst-19160	108	4	is	be	AUX
ajst-19160	108	5	3	3	NUM
ajst-19160	108	6	/	/	SYM
ajst-19160	108	7	2od	2od	NUM
ajst-19160	108	8	;	;	PUNCT
ajst-19160	108	9	the	the	DET
ajst-19160	108	10	length	length	NOUN
ajst-19160	108	11	will	will	AUX
ajst-19160	108	12	not	not	PART
ajst-19160	108	13	affect	affect	VERB
ajst-19160	108	14	the	the	DET
ajst-19160	108	15	analysis	analysis	NOUN
ajst-19160	108	16	[	[	X
ajst-19160	108	17	21	21	NUM
ajst-19160	108	18	]	]	PUNCT
ajst-19160	108	19	.	.	PUNCT
ajst-19160	109	1	the	the	DET
ajst-19160	109	2	thickness	thickness	PROPN
ajst-19160	109	3	t	t	PROPN
ajst-19160	109	4	of	of	ADP
ajst-19160	109	5	x65	x65	PROPN
ajst-19160	109	6	pipeline	pipeline	NOUN
ajst-19160	109	7	is	be	AUX
ajst-19160	109	8	17.5	17.5	NUM
ajst-19160	109	9	mm	mm	NOUN
ajst-19160	109	10	.	.	PUNCT
ajst-19160	110	1	it	it	PRON
ajst-19160	110	2	should	should	AUX
ajst-19160	110	3	be	be	AUX
ajst-19160	110	4	noted	note	VERB
ajst-19160	110	5	that	that	SCONJ
ajst-19160	110	6	the	the	DET
ajst-19160	110	7	model	model	NOUN
ajst-19160	110	8	is	be	AUX
ajst-19160	110	9	highly	highly	ADV
ajst-19160	110	10	symmetrical	symmetrical	ADJ
ajst-19160	110	11	,	,	PUNCT
ajst-19160	110	12	so	so	ADV
ajst-19160	110	13	only	only	ADV
ajst-19160	110	14	1/4	1/4	NUM
ajst-19160	110	15	of	of	ADP
ajst-19160	110	16	the	the	DET
ajst-19160	110	17	corrosion	corrosion	NOUN
ajst-19160	110	18	defects	defect	NOUN
ajst-19160	110	19	can	can	AUX
ajst-19160	110	20	be	be	AUX
ajst-19160	110	21	analyzed	analyze	VERB
ajst-19160	110	22	.	.	PUNCT
ajst-19160	111	1	numerical	numerical	ADJ
ajst-19160	111	2	calculations	calculation	NOUN
ajst-19160	111	3	for	for	ADP
ajst-19160	111	4	fluid	fluid	ADJ
ajst-19160	111	5	pressure	pressure	NOUN
ajst-19160	111	6	are	be	AUX
ajst-19160	111	7	performed	perform	VERB
ajst-19160	111	8	on	on	ADP
ajst-19160	111	9	351	351	NUM
ajst-19160	111	10	sets	set	NOUN
ajst-19160	111	11	of	of	ADP
ajst-19160	111	12	diverse	diverse	ADJ
ajst-19160	111	13	inputs	input	NOUN
ajst-19160	111	14	,	,	PUNCT
ajst-19160	111	15	as	as	SCONJ
ajst-19160	111	16	provided	provide	VERB
ajst-19160	111	17	in	in	ADP
ajst-19160	111	18	table	table	NOUN
ajst-19160	111	19	3	3	NUM
ajst-19160	111	20	.	.	PUNCT
ajst-19160	112	1	the	the	DET
ajst-19160	112	2	range	range	NOUN
ajst-19160	112	3	of	of	ADP
ajst-19160	112	4	defect	defect	ADJ
ajst-19160	112	5	length	length	NOUN
ajst-19160	112	6	and	and	CCONJ
ajst-19160	112	7	depth	depth	NOUN
ajst-19160	112	8	was	be	AUX
ajst-19160	112	9	mainly	mainly	ADV
ajst-19160	112	10	referenced	reference	VERB
ajst-19160	112	11	from	from	ADP
ajst-19160	112	12	previous	previous	ADJ
ajst-19160	112	13	studies	study	NOUN
ajst-19160	112	14	[	[	X
ajst-19160	112	15	22	22	NUM
ajst-19160	112	16	]	]	PUNCT
ajst-19160	112	17	.	.	PUNCT
ajst-19160	113	1	however	however	ADV
ajst-19160	113	2	,	,	PUNCT
ajst-19160	113	3	the	the	DET
ajst-19160	113	4	starting	starting	NOUN
ajst-19160	113	5	point	point	NOUN
ajst-19160	113	6	for	for	ADP
ajst-19160	113	7	defect	defect	ADJ
ajst-19160	113	8	length	length	NOUN
ajst-19160	113	9	in	in	ADP
ajst-19160	113	10	this	this	DET
ajst-19160	113	11	study	study	NOUN
ajst-19160	113	12	is	be	AUX
ajst-19160	113	13	150	150	NUM
ajst-19160	113	14	mm	mm	NOUN
ajst-19160	113	15	,	,	PUNCT
ajst-19160	113	16	which	which	PRON
ajst-19160	113	17	may	may	AUX
ajst-19160	113	18	not	not	PART
ajst-19160	113	19	accurately	accurately	ADV
ajst-19160	113	20	reflect	reflect	VERB
ajst-19160	113	21	the	the	DET
ajst-19160	113	22	influence	influence	NOUN
ajst-19160	113	23	of	of	ADP
ajst-19160	113	24	corrosion	corrosion	NOUN
ajst-19160	113	25	parameters	parameter	NOUN
ajst-19160	113	26	and	and	CCONJ
ajst-19160	113	27	seawater	seawater	NOUN
ajst-19160	113	28	depth	depth	NOUN
ajst-19160	113	29	on	on	ADP
ajst-19160	113	30	blasting	blast	VERB
ajst-19160	113	31	pressure	pressure	NOUN
ajst-19160	113	32	.	.	PUNCT
ajst-19160	114	1	in	in	ADP
ajst-19160	114	2	this	this	DET
ajst-19160	114	3	paper	paper	NOUN
ajst-19160	114	4	,	,	PUNCT
ajst-19160	114	5	through	through	ADP
ajst-19160	114	6	multiple	multiple	ADJ
ajst-19160	114	7	orthogonal	orthogonal	ADJ
ajst-19160	114	8	experiments	experiment	NOUN
ajst-19160	114	9	,	,	PUNCT
ajst-19160	114	10	we	we	PRON
ajst-19160	114	11	present	present	VERB
ajst-19160	114	12	the	the	DET
ajst-19160	114	13	ideal	ideal	ADJ
ajst-19160	114	14	ranges	range	NOUN
ajst-19160	114	15	of	of	ADP
ajst-19160	114	16	influence	influence	NOUN
ajst-19160	114	17	caused	cause	VERB
ajst-19160	114	18	by	by	ADP
ajst-19160	114	19	each	each	DET
ajst-19160	114	20	defect	defect	NOUN
ajst-19160	114	21	value	value	NOUN
ajst-19160	114	22	on	on	ADP
ajst-19160	114	23	blasting	blast	VERB
ajst-19160	114	24	pressure	pressure	NOUN
ajst-19160	114	25	in	in	ADP
ajst-19160	114	26	table	table	NOUN
ajst-19160	114	27	3	3	NUM
ajst-19160	114	28	.	.	PUNCT
ajst-19160	115	1	it	it	PRON
ajst-19160	115	2	should	should	AUX
ajst-19160	115	3	be	be	AUX
ajst-19160	115	4	noted	note	VERB
ajst-19160	115	5	that	that	SCONJ
ajst-19160	115	6	the	the	DET
ajst-19160	115	7	machine	machine	NOUN
ajst-19160	115	8	learning	learn	VERB
ajst-19160	115	9	database	database	NOUN
ajst-19160	115	10	is	be	AUX
ajst-19160	115	11	limited	limit	VERB
ajst-19160	115	12	to	to	ADP
ajst-19160	115	13	this	this	DET
ajst-19160	115	14	range	range	NOUN
ajst-19160	115	15	,	,	PUNCT
ajst-19160	115	16	which	which	PRON
ajst-19160	115	17	also	also	ADV
ajst-19160	115	18	characterizes	characterize	VERB
ajst-19160	115	19	the	the	DET
ajst-19160	115	20	limitations	limitation	NOUN
ajst-19160	115	21	of	of	ADP
ajst-19160	115	22	the	the	DET
ajst-19160	115	23	application	application	NOUN
ajst-19160	115	24	model	model	NOUN
ajst-19160	115	25	in	in	ADP
ajst-19160	115	26	this	this	DET
ajst-19160	115	27	study	study	NOUN
ajst-19160	115	28	.	.	PUNCT
ajst-19160	116	1	121	121	NUM
ajst-19160	116	2	table	table	NOUN
ajst-19160	116	3	3	3	NUM
ajst-19160	116	4	.	.	PUNCT
ajst-19160	116	5	corrosion	corrosion	NOUN
ajst-19160	116	6	shape	shape	NOUN
ajst-19160	116	7	parameters	parameter	NOUN
ajst-19160	116	8	defect	defect	VERB
ajst-19160	116	9	length	length	NOUN
ajst-19160	116	10	l	l	PROPN
ajst-19160	116	11	(	(	PUNCT
ajst-19160	116	12	mm	mm	NOUN
ajst-19160	116	13	)	)	PUNCT
ajst-19160	116	14	defect	defect	NOUN
ajst-19160	116	15	depth	depth	NOUN
ajst-19160	116	16	d(mm	d(mm	NOUN
ajst-19160	116	17	)	)	PUNCT
ajst-19160	116	18	corrosion	corrosion	NOUN
ajst-19160	116	19	width	width	NOUN
ajst-19160	116	20			X
ajst-19160	116	21	(	(	PUNCT
ajst-19160	116	22	mm	mm	NOUN
ajst-19160	116	23	)	)	PUNCT
ajst-19160	116	24	sea	sea	NOUN
ajst-19160	116	25	depth	depth	NOUN
ajst-19160	117	1	_	_	PROPN
ajst-19160	117	2	s	s	PART
ajst-19160	117	3	t	t	X
ajst-19160	117	4	(	(	PUNCT
ajst-19160	117	5	m	m	NOUN
ajst-19160	117	6	)	)	PUNCT
ajst-19160	117	7	value	value	NOUN
ajst-19160	117	8	ranges	range	VERB
ajst-19160	117	9	60	60	NUM
ajst-19160	117	10	:	:	SYM
ajst-19160	117	11	20	20	NUM
ajst-19160	117	12	:	:	SYM
ajst-19160	117	13	300	300	NUM
ajst-19160	117	14	0.3	0.3	NUM
ajst-19160	117	15	t	t	NOUN
ajst-19160	117	16	:	:	PUNCT
ajst-19160	117	17	0.2	0.2	NUM
ajst-19160	117	18	t	t	NOUN
ajst-19160	117	19	:	:	PUNCT
ajst-19160	117	20	0.7	0.7	NUM
ajst-19160	117	21	t	t	NOUN
ajst-19160	117	22	10	10	NUM
ajst-19160	117	23	:	:	SYM
ajst-19160	117	24	10	10	NUM
ajst-19160	117	25	:	:	SYM
ajst-19160	117	26	30	30	NUM
ajst-19160	117	27	100	100	NUM
ajst-19160	117	28	,	,	PUNCT
ajst-19160	117	29	250	250	NUM
ajst-19160	117	30	,	,	PUNCT
ajst-19160	117	31	500	500	NUM
ajst-19160	117	32	3	3	NUM
ajst-19160	117	33	.	.	PUNCT
ajst-19160	118	1	support	support	NOUN
ajst-19160	118	2	vector	vector	NOUN
ajst-19160	118	3	machine	machine	NOUN
ajst-19160	118	4	and	and	CCONJ
ajst-19160	118	5	the	the	DET
ajst-19160	118	6	theoretical	theoretical	ADJ
ajst-19160	118	7	basis	basis	NOUN
ajst-19160	118	8	of	of	ADP
ajst-19160	118	9	iaeo	iaeo	NOUN
ajst-19160	118	10	algorithm	algorithm	PROPN
ajst-19160	118	11	3.1	3.1	NUM
ajst-19160	118	12	.	.	PUNCT
ajst-19160	119	1	theoretical	theoretical	ADJ
ajst-19160	119	2	basis	basis	NOUN
ajst-19160	119	3	of	of	ADP
ajst-19160	119	4	support	support	NOUN
ajst-19160	119	5	vector	vector	NOUN
ajst-19160	119	6	machine	machine	NOUN
ajst-19160	119	7	support	support	NOUN
ajst-19160	119	8	vector	vector	NOUN
ajst-19160	119	9	machine	machine	NOUN
ajst-19160	119	10	is	be	AUX
ajst-19160	119	11	proposed	propose	VERB
ajst-19160	119	12	by	by	ADP
ajst-19160	119	13	sain	sain	PROPN
ajst-19160	119	14	s	s	PART
ajst-19160	120	1	[	[	X
ajst-19160	120	2	23	23	NUM
ajst-19160	120	3	]	]	PUNCT
ajst-19160	120	4	,	,	PUNCT
ajst-19160	120	5	which	which	PRON
ajst-19160	120	6	regresses	regress	VERB
ajst-19160	120	7	and	and	CCONJ
ajst-19160	120	8	classifies	classify	VERB
ajst-19160	120	9	data	datum	NOUN
ajst-19160	120	10	through	through	ADP
ajst-19160	120	11	supervised	supervised	ADJ
ajst-19160	120	12	learning	learning	NOUN
ajst-19160	120	13	.	.	PUNCT
ajst-19160	121	1	suppose	suppose	VERB
ajst-19160	121	2	there	there	PRON
ajst-19160	121	3	exists	exist	VERB
ajst-19160	121	4	a	a	DET
ajst-19160	121	5	sample	sample	NOUN
ajst-19160	121	6	data	datum	NOUN
ajst-19160	121	7	set	set	VERB
ajst-19160	121	8			NOUN
ajst-19160	122	1			SYM
ajst-19160	122	2			NOUN
ajst-19160	122	3			SYM
ajst-19160	122	4			NOUN
ajst-19160	122	5			NOUN
ajst-19160	122	6	1	1	PROPN
ajst-19160	122	7	1	1	NUM
ajst-19160	122	8	2	2	NUM
ajst-19160	122	9	2	2	NUM
ajst-19160	122	10	,	,	PUNCT
ajst-19160	122	11	,	,	PUNCT
ajst-19160	122	12	,	,	PUNCT
ajst-19160	122	13	,	,	PUNCT
ajst-19160	122	14	...	...	PUNCT
ajst-19160	122	15	,	,	PUNCT
ajst-19160	122	16	n	n	CCONJ
ajst-19160	122	17	nx	nx	NOUN
ajst-19160	122	18	y	y	PROPN
ajst-19160	122	19	x	x	PROPN
ajst-19160	122	20	y	y	PROPN
ajst-19160	122	21	x	x	SYM
ajst-19160	122	22	y	y	PROPN
ajst-19160	122	23	,	,	PUNCT
ajst-19160	122	24	where	where	SCONJ
ajst-19160	122	25	n	n	X
ajst-19160	122	26	ix	ix	ADP
ajst-19160	122	27	r	r	PROPN
ajst-19160	122	28	and	and	CCONJ
ajst-19160	122	29	n	n	PRON
ajst-19160	122	30	are	be	AUX
ajst-19160	122	31	the	the	DET
ajst-19160	122	32	number	number	NOUN
ajst-19160	122	33	of	of	ADP
ajst-19160	122	34	samples	sample	NOUN
ajst-19160	122	35	,	,	PUNCT
ajst-19160	122	36	and	and	CCONJ
ajst-19160	122	37	the	the	DET
ajst-19160	122	38	data	datum	NOUN
ajst-19160	122	39	set	set	VERB
ajst-19160	122	40	is	be	AUX
ajst-19160	122	41	linearly	linearly	ADV
ajst-19160	122	42	separable	separable	ADJ
ajst-19160	122	43	.	.	PUNCT
ajst-19160	123	1	the	the	DET
ajst-19160	123	2	discriminant	discriminant	ADJ
ajst-19160	123	3	function	function	NOUN
ajst-19160	123	4	can	can	AUX
ajst-19160	123	5	be	be	AUX
ajst-19160	123	6	expressed	express	VERB
ajst-19160	123	7	as	as	ADP
ajst-19160	123	8	:	:	PUNCT
ajst-19160	123	9			NOUN
ajst-19160	123	10			PUNCT
ajst-19160	123	11	=	=	PUNCT
ajst-19160	124	1	+	+	NUM
ajst-19160	124	2	f	f	X
ajst-19160	124	3	x	x	SYM
ajst-19160	124	4	w	w	NOUN
ajst-19160	124	5	x	x	VERB
ajst-19160	124	6	b	b	NOUN
ajst-19160	124	7	(	(	PUNCT
ajst-19160	124	8	2	2	NUM
ajst-19160	124	9	)	)	PUNCT
ajst-19160	124	10	where	where	SCONJ
ajst-19160	124	11	:	:	PUNCT
ajst-19160	124	12	w	w	NOUN
ajst-19160	124	13	is	be	AUX
ajst-19160	124	14	the	the	DET
ajst-19160	124	15	inertia	inertia	NOUN
ajst-19160	124	16	weight	weight	NOUN
ajst-19160	124	17	;	;	PUNCT
ajst-19160	124	18	b	b	X
ajst-19160	124	19	is	be	AUX
ajst-19160	124	20	the	the	DET
ajst-19160	124	21	intercept	intercept	NOUN
ajst-19160	124	22	of	of	ADP
ajst-19160	124	23	hyperplane	hyperplane	NOUN
ajst-19160	124	24	.	.	PUNCT
ajst-19160	125	1	the	the	DET
ajst-19160	125	2	classification	classification	NOUN
ajst-19160	125	3	hyperplane	hyperplane	NOUN
ajst-19160	125	4	expression	expression	NOUN
ajst-19160	125	5	corresponding	correspond	VERB
ajst-19160	125	6	to	to	ADP
ajst-19160	125	7	the	the	DET
ajst-19160	125	8	discriminant	discriminant	NOUN
ajst-19160	125	9	function	function	NOUN
ajst-19160	125	10	is	be	AUX
ajst-19160	125	11	eq	eq	ADJ
ajst-19160	125	12	.	.	PUNCT
ajst-19160	126	1	(	(	PUNCT
ajst-19160	126	2	3	3	NUM
ajst-19160	126	3	)	)	PUNCT
ajst-19160	126	4	.	.	PUNCT
ajst-19160	127	1	+	+	PUNCT
ajst-19160	127	2	=	=	SYM
ajst-19160	127	3	0w	0w	NUM
ajst-19160	127	4	x	x	X
ajst-19160	127	5	b	b	X
ajst-19160	127	6	(	(	PUNCT
ajst-19160	127	7	3	3	X
ajst-19160	127	8	)	)	PUNCT
ajst-19160	127	9	normalize	normalize	VERB
ajst-19160	127	10			NOUN
ajst-19160	127	11	f	f	PUNCT
ajst-19160	127	12	x	x	PUNCT
ajst-19160	127	13	so	so	SCONJ
ajst-19160	127	14	that	that	SCONJ
ajst-19160	127	15	any	any	DET
ajst-19160	127	16	sample	sample	NOUN
ajst-19160	127	17	satisfies	satisfy	VERB
ajst-19160	127	18			NOUN
ajst-19160	127	19			PROPN
ajst-19160	127	20	1f	1f	NUM
ajst-19160	127	21	x	x	SYM
ajst-19160	127	22			NUM
ajst-19160	127	23	,	,	PUNCT
ajst-19160	127	24	then	then	ADV
ajst-19160	127	25	the	the	DET
ajst-19160	127	26	sample	sample	NOUN
ajst-19160	127	27			NOUN
ajst-19160	127	28			PUNCT
ajst-19160	127	29	=	=	SYM
ajst-19160	127	30	1f	1f	NUM
ajst-19160	127	31	x	x	SYM
ajst-19160	127	32	closest	close	ADJ
ajst-19160	127	33	to	to	ADP
ajst-19160	127	34	the	the	DET
ajst-19160	127	35	decision	decision	NOUN
ajst-19160	127	36	surface	surface	NOUN
ajst-19160	127	37	satisfies	satisfy	VERB
ajst-19160	127	38	the	the	DET
ajst-19160	127	39	condition	condition	NOUN
ajst-19160	127	40	:	:	PUNCT
ajst-19160	127	41			NOUN
ajst-19160	127	42			PUNCT
ajst-19160	128	1	+	+	CCONJ
ajst-19160	128	2	1	1	NUM
ajst-19160	128	3	0	0	NUM
ajst-19160	128	4	=	=	SYM
ajst-19160	128	5	1	1	NUM
ajst-19160	128	6	,	,	PUNCT
ajst-19160	128	7	2	2	NUM
ajst-19160	128	8	,	,	PUNCT
ajst-19160	128	9	3	3	NUM
ajst-19160	128	10	,	,	PUNCT
ajst-19160	128	11	...	...	PUNCT
ajst-19160	128	12	,	,	PUNCT
ajst-19160	128	13	iy	iy	PROPN
ajst-19160	128	14	w	w	PROPN
ajst-19160	128	15	x	x	PROPN
ajst-19160	128	16	b	b	PROPN
ajst-19160	128	17	i	i	PRON
ajst-19160	128	18	n	n	VERB
ajst-19160	128	19			ADJ
ajst-19160	128	20	，	，	PUNCT
ajst-19160	128	21	(	(	PUNCT
ajst-19160	128	22	4	4	X
ajst-19160	128	23	)	)	PUNCT
ajst-19160	128	24	the	the	DET
ajst-19160	128	25	interval	interval	NOUN
ajst-19160	128	26	surface	surface	NOUN
ajst-19160	128	27	distance	distance	NOUN
ajst-19160	128	28	is	be	AUX
ajst-19160	128	29	:	:	PUNCT
ajst-19160	128	30	2	2	NUM
ajst-19160	128	31	/	/	SYM
ajst-19160	128	32	w	w	NOUN
ajst-19160	128	33	.	.	PUNCT
ajst-19160	129	1	in	in	ADP
ajst-19160	129	2	order	order	NOUN
ajst-19160	129	3	to	to	PART
ajst-19160	129	4	maximize	maximize	VERB
ajst-19160	129	5	the	the	DET
ajst-19160	129	6	interval	interval	NOUN
ajst-19160	129	7	distance	distance	NOUN
ajst-19160	129	8	,	,	PUNCT
ajst-19160	129	9	it	it	PRON
ajst-19160	129	10	is	be	AUX
ajst-19160	129	11	necessary	necessary	ADJ
ajst-19160	129	12	to	to	PART
ajst-19160	129	13	find	find	VERB
ajst-19160	129	14	the	the	DET
ajst-19160	129	15	minimum	minimum	ADJ
ajst-19160	129	16	value	value	NOUN
ajst-19160	129	17	of	of	ADP
ajst-19160	129	18	w	w	PROPN
ajst-19160	129	19	.	.	PUNCT
ajst-19160	130	1	for	for	ADP
ajst-19160	130	2	the	the	DET
ajst-19160	130	3	linearly	linearly	ADV
ajst-19160	130	4	inseparable	inseparable	ADJ
ajst-19160	130	5	case	case	NOUN
ajst-19160	130	6	,	,	PUNCT
ajst-19160	130	7	the	the	DET
ajst-19160	130	8	slack	slack	NOUN
ajst-19160	130	9	variable	variable	ADJ
ajst-19160	130	10	i	i	PROPN
ajst-19160	130	11	can	can	AUX
ajst-19160	130	12	be	be	AUX
ajst-19160	130	13	introduced	introduce	VERB
ajst-19160	130	14	to	to	PART
ajst-19160	130	15	achieve	achieve	VERB
ajst-19160	130	16	the	the	DET
ajst-19160	130	17	purpose	purpose	NOUN
ajst-19160	130	18	of	of	ADP
ajst-19160	130	19	accurately	accurately	ADV
ajst-19160	130	20	dividing	divide	VERB
ajst-19160	130	21	the	the	DET
ajst-19160	130	22	training	training	NOUN
ajst-19160	130	23	samples	sample	NOUN
ajst-19160	130	24	,	,	PUNCT
ajst-19160	130	25	which	which	PRON
ajst-19160	130	26	can	can	AUX
ajst-19160	130	27	be	be	AUX
ajst-19160	130	28	expressed	express	VERB
ajst-19160	130	29	as	as	ADP
ajst-19160	130	30	the	the	DET
ajst-19160	130	31	optimization	optimization	NOUN
ajst-19160	130	32	problem	problem	NOUN
ajst-19160	130	33	shown	show	VERB
ajst-19160	130	34	in	in	ADP
ajst-19160	130	35	eq	eq	ADP
ajst-19160	130	36	.	.	PUNCT
ajst-19160	131	1	(	(	PUNCT
ajst-19160	131	2	5	5	NUM
ajst-19160	131	3	):	):	PUNCT
ajst-19160	131	4			NOUN
ajst-19160	131	5			SYM
ajst-19160	131	6	2	2	NUM
ajst-19160	131	7	=	=	SYM
ajst-19160	131	8	1	1	NUM
ajst-19160	131	9	1	1	NUM
ajst-19160	131	10	=	=	SYM
ajst-19160	131	11	min	min	NOUN
ajst-19160	131	12	2	2	NUM
ajst-19160	131	13	s.t	s.t	PROPN
ajst-19160	131	14	.	.	PUNCT
ajst-19160	132	1	+	+	CCONJ
ajst-19160	132	2	1	1	NUM
ajst-19160	132	3	l	l	NOUN
ajst-19160	133	1	i	i	NOUN
ajst-19160	133	2	w	w	PROPN
ajst-19160	133	3	b	b	NOUN
ajst-19160	134	1	i	i	PRON
ajst-19160	134	2	i	i	PRON
ajst-19160	135	1	i	i	PRON
ajst-19160	135	2	f	f	VERB
ajst-19160	136	1	w	w	PROPN
ajst-19160	136	2	c	c	PROPN
ajst-19160	136	3	y	y	PROPN
ajst-19160	136	4	w	w	PROPN
ajst-19160	136	5	x	x	NOUN
ajst-19160	136	6	b	b	X
ajst-19160	136	7			NOUN
ajst-19160	136	8			NOUN
ajst-19160	136	9			X
ajst-19160	136	10			X
ajst-19160	136	11			PROPN
ajst-19160	136	12			X
ajst-19160	136	13			NUM
ajst-19160	136	14	，	，	PUNCT
ajst-19160	136	15	(	(	PUNCT
ajst-19160	136	16	5	5	X
ajst-19160	136	17	)	)	PUNCT
ajst-19160	136	18	where	where	SCONJ
ajst-19160	136	19	:	:	PUNCT
ajst-19160	136	20	0i	0i	PROPN
ajst-19160	136	21			NUM
ajst-19160	136	22	,	,	PUNCT
ajst-19160	136	23	c	c	PROPN
ajst-19160	136	24	are	be	AUX
ajst-19160	136	25	penalty	penalty	NOUN
ajst-19160	136	26	factors	factor	NOUN
ajst-19160	136	27	,	,	PUNCT
ajst-19160	136	28	0c	0c	NUM
ajst-19160	136	29	.	.	PUNCT
ajst-19160	137	1	for	for	ADP
ajst-19160	137	2	nonlinear	nonlinear	ADJ
ajst-19160	137	3	problems	problem	NOUN
ajst-19160	137	4	,	,	PUNCT
ajst-19160	137	5	the	the	DET
ajst-19160	137	6	kernel	kernel	NOUN
ajst-19160	137	7	function	function	NOUN
ajst-19160	137	8	is	be	AUX
ajst-19160	137	9	introduced	introduce	VERB
ajst-19160	137	10	:	:	PUNCT
ajst-19160	137	11			NOUN
ajst-19160	137	12			SYM
ajst-19160	137	13			NOUN
ajst-19160	137	14			PUNCT
ajst-19160	137	15			NOUN
ajst-19160	138	1			PROPN
ajst-19160	138	2	,	,	PUNCT
ajst-19160	138	3	i	i	PRON
ajst-19160	138	4	j	j	VERB
ajst-19160	139	1	i	i	PRON
ajst-19160	139	2	jk	jk	VERB
ajst-19160	139	3	x	x	PUNCT
ajst-19160	140	1	x	x	PUNCT
ajst-19160	140	2	x	x	SYM
ajst-19160	140	3	x	x	X
ajst-19160	140	4			NOUN
ajst-19160	140	5			PROPN
ajst-19160	140	6	(	(	PUNCT
ajst-19160	140	7	6	6	NUM
ajst-19160	140	8	)	)	PUNCT
ajst-19160	140	9	where	where	SCONJ
ajst-19160	140	10	:	:	PUNCT
ajst-19160	140	11			NOUN
ajst-19160	140	12	is	be	AUX
ajst-19160	140	13	the	the	DET
ajst-19160	140	14	mapping	mapping	NOUN
ajst-19160	140	15	from	from	ADP
ajst-19160	140	16	the	the	DET
ajst-19160	140	17	original	original	ADJ
ajst-19160	140	18	space	space	NOUN
ajst-19160	140	19	to	to	ADP
ajst-19160	140	20	the	the	DET
ajst-19160	140	21	feature	feature	NOUN
ajst-19160	140	22	space	space	NOUN
ajst-19160	140	23	,	,	PUNCT
ajst-19160	140	24	fig	fig	NOUN
ajst-19160	140	25	.	.	PUNCT
ajst-19160	140	26	5	5	NUM
ajst-19160	140	27	is	be	AUX
ajst-19160	140	28	the	the	DET
ajst-19160	140	29	schematic	schematic	ADJ
ajst-19160	140	30	diagram	diagram	NOUN
ajst-19160	140	31	of	of	ADP
ajst-19160	140	32	the	the	DET
ajst-19160	140	33	mapping	mapping	NOUN
ajst-19160	140	34	space	space	NOUN
ajst-19160	140	35	.	.	PUNCT
ajst-19160	141	1	figure	figure	NOUN
ajst-19160	141	2	5	5	NUM
ajst-19160	141	3	.	.	PUNCT
ajst-19160	141	4	schematic	schematic	ADJ
ajst-19160	141	5	diagram	diagram	NOUN
ajst-19160	141	6	of	of	ADP
ajst-19160	141	7	transformation	transformation	NOUN
ajst-19160	141	8	from	from	ADP
ajst-19160	141	9	original	original	ADJ
ajst-19160	141	10	space	space	NOUN
ajst-19160	141	11	to	to	PART
ajst-19160	141	12	feature	feature	VERB
ajst-19160	141	13	space	space	NOUN
ajst-19160	141	14	the	the	DET
ajst-19160	141	15	objective	objective	ADJ
ajst-19160	141	16	function	function	NOUN
ajst-19160	141	17	of	of	ADP
ajst-19160	141	18	nonlinear	nonlinear	ADJ
ajst-19160	141	19	regression	regression	NOUN
ajst-19160	141	20	svm	svm	NOUN
ajst-19160	141	21	is	be	AUX
ajst-19160	141	22	:	:	PUNCT
ajst-19160	141	23			NOUN
ajst-19160	142	1			PUNCT
ajst-19160	142	2	=	=	SYM
ajst-19160	142	3	0	0	NUM
ajst-19160	142	4	1	1	NUM
ajst-19160	142	5	1	1	NUM
ajst-19160	142	6	=	=	SYM
ajst-19160	142	7	0	0	SYM
ajst-19160	142	8	1	1	NUM
ajst-19160	142	9	=	=	SYM
ajst-19160	142	10	max	max	PROPN
ajst-19160	142	11	,	,	PUNCT
ajst-19160	142	12	2	2	NUM
ajst-19160	142	13	=	=	SYM
ajst-19160	142	14	0	0	NUM
ajst-19160	143	1	l	l	NOUN
ajst-19160	143	2	l	l	NOUN
ajst-19160	143	3	l	l	NOUN
ajst-19160	144	1	i	i	PRON
ajst-19160	144	2	i	i	INTJ
ajst-19160	145	1	j	j	VERB
ajst-19160	146	1	i	i	PRON
ajst-19160	146	2	j	j	VERB
ajst-19160	147	1	i	i	PRON
ajst-19160	147	2	j	j	VERB
ajst-19160	148	1	i	i	PRON
ajst-19160	148	2	i	i	INTJ
ajst-19160	149	1	j	j	VERB
ajst-19160	150	1	l	l	NOUN
ajst-19160	151	1	i	i	PRON
ajst-19160	151	2	i	i	INTJ
ajst-19160	152	1	i	i	PRON
ajst-19160	152	2	f	f	VERB
ajst-19160	153	1	y	y	PROPN
ajst-19160	153	2	y	y	PROPN
ajst-19160	153	3	k	k	PROPN
ajst-19160	153	4	x	x	PUNCT
ajst-19160	153	5	x	x	PUNCT
ajst-19160	153	6	y	y	NOUN
ajst-19160	153	7			X
ajst-19160	153	8			X
ajst-19160	153	9			X
ajst-19160	153	10			X
ajst-19160	153	11			NOUN
ajst-19160	153	12			NUM
ajst-19160	154	1			NOUN
ajst-19160	154	2			VERB
ajst-19160	154	3			X
ajst-19160	154	4	(	(	PUNCT
ajst-19160	154	5	7	7	NUM
ajst-19160	154	6	)	)	PUNCT
ajst-19160	154	7	where	where	SCONJ
ajst-19160	154	8	:	:	PUNCT
ajst-19160	154	9	0	0	NUM
ajst-19160	154	10	;	;	PUNCT
ajst-19160	154	11	=	=	NOUN
ajst-19160	154	12	1	1	NUM
ajst-19160	154	13	,	,	PUNCT
ajst-19160	154	14	2	2	NUM
ajst-19160	154	15	...	...	PUNCT
ajst-19160	154	16	.c	.c	PUNCT
ajst-19160	155	1	i	i	PRON
ajst-19160	155	2	l	l	ADJ
ajst-19160	155	3			NOUN
ajst-19160	155	4	，	，	PUNCT
ajst-19160	155	5	，	，	PUNCT
ajst-19160	155	6	in	in	ADP
ajst-19160	155	7	solving	solve	VERB
ajst-19160	155	8	practical	practical	ADJ
ajst-19160	155	9	problems	problem	NOUN
ajst-19160	155	10	,	,	PUNCT
ajst-19160	155	11	rbf	rbf	PROPN
ajst-19160	155	12	is	be	AUX
ajst-19160	155	13	widely	widely	ADV
ajst-19160	155	14	used	use	VERB
ajst-19160	155	15	in	in	ADP
ajst-19160	155	16	svm	svm	ADJ
ajst-19160	155	17	regression	regression	NOUN
ajst-19160	155	18	because	because	SCONJ
ajst-19160	155	19	of	of	ADP
ajst-19160	155	20	its	its	PRON
ajst-19160	155	21	excellent	excellent	ADJ
ajst-19160	155	22	kernel	kernel	NOUN
ajst-19160	155	23	function	function	NOUN
ajst-19160	155	24	performance	performance	NOUN
ajst-19160	155	25	.	.	PUNCT
ajst-19160	156	1	its	its	PRON
ajst-19160	156	2	mathematical	mathematical	ADJ
ajst-19160	156	3	expression	expression	NOUN
ajst-19160	156	4	is	be	AUX
ajst-19160	156	5	as	as	SCONJ
ajst-19160	156	6	follows	follow	VERB
ajst-19160	156	7	:	:	PUNCT
ajst-19160	156	8			NOUN
ajst-19160	156	9			PROPN
ajst-19160	156	10	2	2	NUM
ajst-19160	156	11	2	2	NUM
ajst-19160	156	12	,	,	PUNCT
ajst-19160	156	13	=	=	PUNCT
ajst-19160	156	14	exp	exp	NOUN
ajst-19160	157	1	i	i	PRON
ajst-19160	157	2	j	j	PROPN
ajst-19160	158	1	i	i	PRON
ajst-19160	158	2	j	j	VERB
ajst-19160	159	1	x	x	PUNCT
ajst-19160	159	2	x	x	X
ajst-19160	159	3	k	k	NOUN
ajst-19160	159	4	x	x	PUNCT
ajst-19160	159	5	x	x	X
ajst-19160	159	6			PROPN
ajst-19160	159	7			PROPN
ajst-19160	159	8			PROPN
ajst-19160	159	9			NOUN
ajst-19160	159	10			PROPN
ajst-19160	159	11			NOUN
ajst-19160	159	12			NOUN
ajst-19160	159	13			PROPN
ajst-19160	159	14	(	(	PUNCT
ajst-19160	159	15	8)	8)	NUM
ajst-19160	159	16	where	where	SCONJ
ajst-19160	159	17	:	:	PUNCT
ajst-19160	159	18			PROPN
ajst-19160	159	19	is	be	AUX
ajst-19160	159	20	the	the	DET
ajst-19160	159	21	radius	radius	NOUN
ajst-19160	159	22	of	of	ADP
ajst-19160	159	23	the	the	DET
ajst-19160	159	24	radial	radial	ADJ
ajst-19160	159	25	basis	basis	NOUN
ajst-19160	159	26	,	,	PUNCT
ajst-19160	159	27	let	let	VERB
ajst-19160	159	28	2=1	2=1	NUM
ajst-19160	159	29	/	/	SYM
ajst-19160	159	30			PUNCT
ajst-19160	159	31	,	,	PUNCT
ajst-19160	159	32	into	into	ADP
ajst-19160	159	33	eq	eq	NOUN
ajst-19160	159	34	.	.	PUNCT
ajst-19160	160	1	(	(	PUNCT
ajst-19160	160	2	8)	8)	NUM
ajst-19160	160	3	:	:	PUNCT
ajst-19160	160	4			NOUN
ajst-19160	160	5			PROPN
ajst-19160	160	6	2	2	NUM
ajst-19160	160	7	,	,	PUNCT
ajst-19160	160	8	=	=	SYM
ajst-19160	160	9	expi	expi	PROPN
ajst-19160	161	1	j	j	PROPN
ajst-19160	162	1	i	i	PRON
ajst-19160	162	2	jk	jk	VERB
ajst-19160	162	3	x	x	PUNCT
ajst-19160	163	1	x	x	PUNCT
ajst-19160	163	2	x	x	X
ajst-19160	163	3	x	x	PROPN
ajst-19160	163	4			PROPN
ajst-19160	164	1			PROPN
ajst-19160	164	2			PROPN
ajst-19160	164	3			PROPN
ajst-19160	164	4	(	(	PUNCT
ajst-19160	164	5	9	9	NUM
ajst-19160	164	6	)	)	PUNCT
ajst-19160	164	7	according	accord	VERB
ajst-19160	164	8	to	to	ADP
ajst-19160	164	9	the	the	DET
ajst-19160	164	10	eqs	eqs	PROPN
ajst-19160	164	11	.	.	PUNCT
ajst-19160	165	1	(	(	PUNCT
ajst-19160	165	2	5	5	NUM
ajst-19160	165	3	-	-	SYM
ajst-19160	165	4	9	9	NUM
ajst-19160	165	5	)	)	PUNCT
ajst-19160	165	6	,	,	PUNCT
ajst-19160	165	7	the	the	DET
ajst-19160	165	8	core	core	NOUN
ajst-19160	165	9	point	point	NOUN
ajst-19160	165	10	of	of	ADP
ajst-19160	165	11	the	the	DET
ajst-19160	165	12	svm	svm	ADJ
ajst-19160	165	13	algorithm	algorithm	NOUN
ajst-19160	165	14	is	be	AUX
ajst-19160	165	15	to	to	PART
ajst-19160	165	16	find	find	VERB
ajst-19160	165	17	the	the	DET
ajst-19160	165	18	appropriate	appropriate	ADJ
ajst-19160	165	19	penalty	penalty	NOUN
ajst-19160	165	20	factor	factor	NOUN
ajst-19160	165	21	c	c	PROPN
ajst-19160	165	22	and	and	CCONJ
ajst-19160	165	23	the	the	DET
ajst-19160	165	24	appropriate	appropriate	ADJ
ajst-19160	165	25	radial	radial	ADJ
ajst-19160	165	26	basis	basis	NOUN
ajst-19160	165	27	kernel	kernel	NOUN
ajst-19160	165	28	function	function	NOUN
ajst-19160	165	29	parameters	parameters	NOUN
ajst-19160	165	30	.	.	PUNCT
ajst-19160	166	1	122	122	NUM
ajst-19160	166	2	3.2	3.2	NUM
ajst-19160	166	3	.	.	PUNCT
ajst-19160	167	1	aeo	aeo	PROPN
ajst-19160	167	2	algorithm	algorithm	PROPN
ajst-19160	167	3	as	as	SCONJ
ajst-19160	167	4	demonstrated	demonstrate	VERB
ajst-19160	167	5	in	in	ADP
ajst-19160	167	6	chapter	chapter	NOUN
ajst-19160	167	7	2.1	2.1	NUM
ajst-19160	167	8	,	,	PUNCT
ajst-19160	167	9	the	the	DET
ajst-19160	167	10	prediction	prediction	NOUN
ajst-19160	167	11	accuracy	accuracy	NOUN
ajst-19160	167	12	of	of	ADP
ajst-19160	167	13	svm	svm	PROPN
ajst-19160	167	14	is	be	AUX
ajst-19160	167	15	influenced	influence	VERB
ajst-19160	167	16	by	by	ADP
ajst-19160	167	17	the	the	DET
ajst-19160	167	18	penalty	penalty	NOUN
ajst-19160	167	19	factor	factor	NOUN
ajst-19160	167	20	and	and	CCONJ
ajst-19160	167	21	the	the	DET
ajst-19160	167	22	parameters	parameter	NOUN
ajst-19160	167	23	of	of	ADP
ajst-19160	167	24	the	the	DET
ajst-19160	167	25	radial	radial	ADJ
ajst-19160	167	26	basis	basis	NOUN
ajst-19160	167	27	kernel	kernel	NOUN
ajst-19160	167	28	function	function	PROPN
ajst-19160	167	29	.	.	PUNCT
ajst-19160	168	1	research	research	NOUN
ajst-19160	168	2	has	have	AUX
ajst-19160	168	3	shown	show	VERB
ajst-19160	168	4	that	that	SCONJ
ajst-19160	168	5	optimization	optimization	NOUN
ajst-19160	168	6	algorithms	algorithm	NOUN
ajst-19160	168	7	can	can	AUX
ajst-19160	168	8	considerably	considerably	ADV
ajst-19160	168	9	enhance	enhance	VERB
ajst-19160	168	10	the	the	DET
ajst-19160	168	11	accuracy	accuracy	NOUN
ajst-19160	168	12	of	of	ADP
ajst-19160	168	13	svm	svm	PROPN
ajst-19160	168	14	.	.	PUNCT
ajst-19160	169	1	the	the	DET
ajst-19160	169	2	aeo	aeo	PROPN
ajst-19160	169	3	algorithm	algorithm	PROPN
ajst-19160	169	4	,	,	PUNCT
ajst-19160	169	5	a	a	DET
ajst-19160	169	6	new	new	ADJ
ajst-19160	169	7	meta	meta	ADJ
ajst-19160	169	8	-	-	PUNCT
ajst-19160	169	9	heuristic	heuristic	ADJ
ajst-19160	169	10	algorithm	algorithm	NOUN
ajst-19160	169	11	proposed	propose	VERB
ajst-19160	169	12	by	by	ADP
ajst-19160	169	13	zhao	zhao	PROPN
ajst-19160	169	14	w	w	PROPN
ajst-19160	170	1	[	[	X
ajst-19160	170	2	24	24	NUM
ajst-19160	170	3	]	]	PUNCT
ajst-19160	170	4	,	,	PUNCT
ajst-19160	170	5	is	be	AUX
ajst-19160	170	6	inspired	inspire	VERB
ajst-19160	170	7	by	by	ADP
ajst-19160	170	8	the	the	DET
ajst-19160	170	9	energy	energy	NOUN
ajst-19160	170	10	flow	flow	NOUN
ajst-19160	170	11	in	in	ADP
ajst-19160	170	12	ecosystems	ecosystem	NOUN
ajst-19160	170	13	and	and	CCONJ
ajst-19160	170	14	the	the	DET
ajst-19160	170	15	behavior	behavior	NOUN
ajst-19160	170	16	of	of	ADP
ajst-19160	170	17	producers	producer	NOUN
ajst-19160	170	18	,	,	PUNCT
ajst-19160	170	19	consumers	consumer	NOUN
ajst-19160	170	20	,	,	PUNCT
ajst-19160	170	21	and	and	CCONJ
ajst-19160	170	22	decomposers	decomposer	NOUN
ajst-19160	170	23	.	.	PUNCT
ajst-19160	171	1	it	it	PRON
ajst-19160	171	2	primarily	primarily	ADV
ajst-19160	171	3	consists	consist	VERB
ajst-19160	171	4	of	of	ADP
ajst-19160	171	5	the	the	DET
ajst-19160	171	6	production	production	NOUN
ajst-19160	171	7	stage	stage	NOUN
ajst-19160	171	8	,	,	PUNCT
ajst-19160	171	9	consumption	consumption	NOUN
ajst-19160	171	10	stage	stage	NOUN
ajst-19160	171	11	,	,	PUNCT
ajst-19160	171	12	and	and	CCONJ
ajst-19160	171	13	decomposition	decomposition	NOUN
ajst-19160	171	14	stage	stage	NOUN
ajst-19160	171	15	.	.	PUNCT
ajst-19160	172	1	the	the	DET
ajst-19160	172	2	organisms	organism	NOUN
ajst-19160	172	3	in	in	ADP
ajst-19160	172	4	each	each	DET
ajst-19160	172	5	stage	stage	NOUN
ajst-19160	172	6	represent	represent	VERB
ajst-19160	172	7	feasible	feasible	ADJ
ajst-19160	172	8	solutions	solution	NOUN
ajst-19160	172	9	to	to	ADP
ajst-19160	172	10	the	the	DET
ajst-19160	172	11	optimization	optimization	NOUN
ajst-19160	172	12	problem	problem	NOUN
ajst-19160	172	13	.	.	PUNCT
ajst-19160	173	1	through	through	ADP
ajst-19160	173	2	the	the	DET
ajst-19160	173	3	process	process	NOUN
ajst-19160	173	4	of	of	ADP
ajst-19160	173	5	energy	energy	NOUN
ajst-19160	173	6	flow	flow	NOUN
ajst-19160	173	7	,	,	PUNCT
ajst-19160	173	8	the	the	DET
ajst-19160	173	9	theoretical	theoretical	ADJ
ajst-19160	173	10	optimal	optimal	ADJ
ajst-19160	173	11	solution	solution	NOUN
ajst-19160	173	12	is	be	AUX
ajst-19160	173	13	gradually	gradually	ADV
ajst-19160	173	14	approached	approach	VERB
ajst-19160	173	15	through	through	ADP
ajst-19160	173	16	iteration	iteration	NOUN
ajst-19160	173	17	.	.	PUNCT
ajst-19160	174	1	1	1	X
ajst-19160	174	2	)	)	PUNCT
ajst-19160	174	3	production	production	NOUN
ajst-19160	174	4	stage	stage	NOUN
ajst-19160	174	5	:	:	PUNCT
ajst-19160	174	6	the	the	DET
ajst-19160	174	7	producer	producer	NOUN
ajst-19160	174	8	1x	1x	NUM
ajst-19160	174	9	(	(	PUNCT
ajst-19160	174	10	the	the	DET
ajst-19160	174	11	worst	bad	ADJ
ajst-19160	174	12	solution	solution	NOUN
ajst-19160	174	13	in	in	ADP
ajst-19160	174	14	the	the	DET
ajst-19160	174	15	iterative	iterative	NOUN
ajst-19160	174	16	process	process	NOUN
ajst-19160	174	17	)	)	PUNCT
ajst-19160	174	18	is	be	AUX
ajst-19160	174	19	iteratively	iteratively	ADV
ajst-19160	174	20	updated	update	VERB
ajst-19160	174	21	by	by	ADP
ajst-19160	174	22	the	the	DET
ajst-19160	174	23	linear	linear	PROPN
ajst-19160	174	24	coupling	coupling	NOUN
ajst-19160	174	25	of	of	ADP
ajst-19160	174	26	the	the	DET
ajst-19160	174	27	decomposer	decomposer	NOUN
ajst-19160	174	28	nx	nx	X
ajst-19160	174	29	(	(	PUNCT
ajst-19160	174	30	the	the	DET
ajst-19160	174	31	best	good	ADJ
ajst-19160	174	32	individual	individual	NOUN
ajst-19160	174	33	in	in	ADP
ajst-19160	174	34	the	the	DET
ajst-19160	174	35	iterative	iterative	NOUN
ajst-19160	174	36	process	process	NOUN
ajst-19160	174	37	)	)	PUNCT
ajst-19160	174	38	and	and	CCONJ
ajst-19160	174	39	the	the	DET
ajst-19160	174	40	random	random	ADJ
ajst-19160	174	41	individual	individual	ADJ
ajst-19160	174	42	randx	randx	NOUN
ajst-19160	174	43	,	,	PUNCT
ajst-19160	174	44	which	which	PRON
ajst-19160	174	45	is	be	AUX
ajst-19160	174	46	used	use	VERB
ajst-19160	174	47	to	to	PART
ajst-19160	174	48	guide	guide	VERB
ajst-19160	174	49	the	the	DET
ajst-19160	174	50	evolution	evolution	NOUN
ajst-19160	174	51	direction	direction	NOUN
ajst-19160	174	52	of	of	ADP
ajst-19160	174	53	the	the	DET
ajst-19160	174	54	consumer	consumer	NOUN
ajst-19160	174	55	.	.	PUNCT
ajst-19160	175	1	its	its	PRON
ajst-19160	175	2	expression	expression	NOUN
ajst-19160	175	3	is	be	AUX
ajst-19160	175	4	:	:	PUNCT
ajst-19160	175	5			NOUN
ajst-19160	175	6			SYM
ajst-19160	175	7			NOUN
ajst-19160	175	8			SYM
ajst-19160	175	9			NOUN
ajst-19160	175	10	1	1	ADJ
ajst-19160	175	11	rand	rand	NOUN
ajst-19160	175	12	+	+	CCONJ
ajst-19160	175	13	1	1	NUM
ajst-19160	175	14	=	=	SYM
ajst-19160	175	15	1	1	NUM
ajst-19160	175	16	nx	nx	NOUN
ajst-19160	175	17	t	t	PROPN
ajst-19160	175	18	x	x	PROPN
ajst-19160	175	19	t	t	PROPN
ajst-19160	175	20	x	x	X
ajst-19160	175	21	t	t	NOUN
ajst-19160	175	22			X
ajst-19160	175	23	（	（	PUNCT
ajst-19160	175	24	）	）	PUNCT
ajst-19160	176	1	+	+	CCONJ
ajst-19160	176	2	(	(	PUNCT
ajst-19160	176	3	10	10	NUM
ajst-19160	176	4	)	)	PUNCT
ajst-19160	176	5	where	where	SCONJ
ajst-19160	176	6	:	:	PUNCT
ajst-19160	176	7	n	n	PRON
ajst-19160	176	8	is	be	AUX
ajst-19160	176	9	the	the	DET
ajst-19160	176	10	population	population	NOUN
ajst-19160	176	11	size	size	NOUN
ajst-19160	176	12	,	,	PUNCT
ajst-19160	176	13			NOUN
ajst-19160	176	14			PUNCT
ajst-19160	176	15	1=	1=	SYM
ajst-19160	176	16	1	1	NUM
ajst-19160	176	17	/	/	SYM
ajst-19160	176	18	t	t	NOUN
ajst-19160	176	19	t	t	PROPN
ajst-19160	176	20	r	r	PROPN
ajst-19160	176	21			PROPN
ajst-19160	176	22			PROPN
ajst-19160	176	23	,	,	PUNCT
ajst-19160	176	24	where	where	SCONJ
ajst-19160	176	25	1r	1r	NOUN
ajst-19160	176	26	is	be	AUX
ajst-19160	176	27	the	the	DET
ajst-19160	176	28	weighted	weighted	ADJ
ajst-19160	176	29	coefficient	coefficient	NOUN
ajst-19160	176	30	,	,	PUNCT
ajst-19160	176	31	and	and	CCONJ
ajst-19160	176	32	1	1	NUM
ajst-19160	176	33	0	0	NUM
ajst-19160	176	34	,	,	PUNCT
ajst-19160	176	35	1r	1r	NUM
ajst-19160	176	36			PROPN
ajst-19160	176	37	.	.	PROPN
ajst-19160	176	38	t	t	PROPN
ajst-19160	176	39	and	and	CCONJ
ajst-19160	176	40	t	t	PROPN
ajst-19160	176	41	are	be	AUX
ajst-19160	176	42	the	the	DET
ajst-19160	176	43	current	current	ADJ
ajst-19160	176	44	iteration	iteration	NOUN
ajst-19160	176	45	number	number	NOUN
ajst-19160	176	46	and	and	CCONJ
ajst-19160	176	47	the	the	DET
ajst-19160	176	48	maximum	maximum	ADJ
ajst-19160	176	49	iteration	iteration	NOUN
ajst-19160	176	50	number	number	NOUN
ajst-19160	176	51	.	.	PUNCT
ajst-19160	177	1	randx	randx	PROPN
ajst-19160	177	2	is	be	AUX
ajst-19160	177	3	the	the	DET
ajst-19160	177	4	vector	vector	NOUN
ajst-19160	177	5	of	of	ADP
ajst-19160	177	6	random	random	ADJ
ajst-19160	177	7	position	position	NOUN
ajst-19160	177	8	in	in	ADP
ajst-19160	177	9	the	the	DET
ajst-19160	177	10	boundary	boundary	ADJ
ajst-19160	177	11	interval	interval	NOUN
ajst-19160	177	12	.	.	PUNCT
ajst-19160	178	1	2	2	X
ajst-19160	178	2	)	)	PUNCT
ajst-19160	178	3	consumption	consumption	NOUN
ajst-19160	178	4	stage	stage	NOUN
ajst-19160	178	5	:	:	PUNCT
ajst-19160	178	6	consumers	consumer	NOUN
ajst-19160	178	7	are	be	AUX
ajst-19160	178	8	herbivores	herbivore	NOUN
ajst-19160	178	9	,	,	PUNCT
ajst-19160	178	10	carnivores	carnivore	NOUN
ajst-19160	178	11	and	and	CCONJ
ajst-19160	178	12	omnivores	omnivore	NOUN
ajst-19160	178	13	,	,	PUNCT
ajst-19160	178	14	which	which	PRON
ajst-19160	178	15	are	be	AUX
ajst-19160	178	16	divided	divide	VERB
ajst-19160	178	17	according	accord	VERB
ajst-19160	178	18	to	to	ADP
ajst-19160	178	19	a	a	DET
ajst-19160	178	20	certain	certain	ADJ
ajst-19160	178	21	proportion	proportion	NOUN
ajst-19160	178	22	in	in	ADP
ajst-19160	178	23	the	the	DET
ajst-19160	178	24	model	model	NOUN
ajst-19160	178	25	.	.	PUNCT
ajst-19160	179	1	and	and	CCONJ
ajst-19160	179	2	iterative	iterative	VERB
ajst-19160	179	3	evolution	evolution	NOUN
ajst-19160	179	4	in	in	ADP
ajst-19160	179	5	three	three	NUM
ajst-19160	179	6	different	different	ADJ
ajst-19160	179	7	postures	posture	NOUN
ajst-19160	179	8	.	.	PUNCT
ajst-19160	180	1	case1	case1	PROPN
ajst-19160	180	2	:	:	PUNCT
ajst-19160	180	3	herbivores	herbivore	NOUN
ajst-19160	180	4	ix	ix	ADJ
ajst-19160	180	5	are	be	AUX
ajst-19160	180	6	updated	update	VERB
ajst-19160	180	7	only	only	ADV
ajst-19160	180	8	by	by	ADP
ajst-19160	180	9	producers	producer	NOUN
ajst-19160	180	10	1x	1x	NUM
ajst-19160	180	11	,	,	PUNCT
ajst-19160	180	12	and	and	CCONJ
ajst-19160	180	13	the	the	DET
ajst-19160	180	14	mathematical	mathematical	ADJ
ajst-19160	180	15	expression	expression	NOUN
ajst-19160	180	16	of	of	ADP
ajst-19160	180	17	their	their	PRON
ajst-19160	180	18	behavior	behavior	NOUN
ajst-19160	180	19	is	be	AUX
ajst-19160	180	20	:	:	PUNCT
ajst-19160	180	21			NOUN
ajst-19160	181	1			SYM
ajst-19160	181	2			NOUN
ajst-19160	181	3			SYM
ajst-19160	181	4			NOUN
ajst-19160	181	5			PUNCT
ajst-19160	181	6			NOUN
ajst-19160	182	1			NOUN
ajst-19160	182	2	1	1	NOUN
ajst-19160	183	1	+	+	CCONJ
ajst-19160	183	2	1	1	NUM
ajst-19160	184	1	=	=	SYM
ajst-19160	184	2	i	i	PRON
ajst-19160	185	1	i	i	PRON
ajst-19160	185	2	ix	ix	INTJ
ajst-19160	185	3	t	t	PROPN
ajst-19160	185	4	x	x	X
ajst-19160	185	5	t	t	NOUN
ajst-19160	185	6	c	c	NOUN
ajst-19160	185	7	x	x	SYM
ajst-19160	185	8	t	t	NOUN
ajst-19160	185	9	x	x	PUNCT
ajst-19160	185	10	t	t	PRON
ajst-19160	185	11			ADJ
ajst-19160	185	12			NOUN
ajst-19160	185	13	(	(	PUNCT
ajst-19160	185	14	11	11	NUM
ajst-19160	185	15	)	)	PUNCT
ajst-19160	185	16	where	where	SCONJ
ajst-19160	185	17	:	:	PUNCT
ajst-19160	185	18	1	1	NUM
ajst-19160	185	19	2[2	2[2	NUM
ajst-19160	185	20	,	,	PUNCT
ajst-19160	185	21	]	]	PUNCT
ajst-19160	185	22	,	,	PUNCT
ajst-19160	185	23	=	=	PUNCT
ajst-19160	185	24	/	/	SYM
ajst-19160	185	25	2i	2i	PROPN
ajst-19160	186	1	n	n	NOUN
ajst-19160	186	2	c	c	NOUN
ajst-19160	186	3	v	v	X
ajst-19160	186	4	v	v	NOUN
ajst-19160	186	5	,	,	PUNCT
ajst-19160	186	6	which	which	PRON
ajst-19160	186	7	1v	1v	NUM
ajst-19160	186	8	and	and	CCONJ
ajst-19160	186	9	2v	2v	PROPN
ajst-19160	186	10	obey	obey	VERB
ajst-19160	186	11	normal	normal	ADJ
ajst-19160	186	12	distribution	distribution	NOUN
ajst-19160	186	13	,	,	PUNCT
ajst-19160	186	14	c	c	PROPN
ajst-19160	186	15	is	be	AUX
ajst-19160	186	16	the	the	DET
ajst-19160	186	17	improved	improve	VERB
ajst-19160	186	18	multiplication	multiplication	NOUN
ajst-19160	186	19	operator	operator	NOUN
ajst-19160	186	20	of	of	ADP
ajst-19160	186	21	levy	levy	NOUN
ajst-19160	186	22	flight	flight	NOUN
ajst-19160	186	23	.	.	PUNCT
ajst-19160	187	1	case	case	NOUN
ajst-19160	187	2	2	2	NUM
ajst-19160	187	3	:	:	PUNCT
ajst-19160	187	4	carnivores	carnivore	NOUN
ajst-19160	187	5	ix	ix	ADP
ajst-19160	187	6	randomly	randomly	ADV
ajst-19160	187	7	prey	prey	NOUN
ajst-19160	187	8	on	on	ADP
ajst-19160	187	9	animals	animal	NOUN
ajst-19160	187	10	jx	jx	PROPN
ajst-19160	187	11	with	with	ADP
ajst-19160	187	12	higher	high	ADJ
ajst-19160	187	13	energy	energy	NOUN
ajst-19160	187	14	levels	level	NOUN
ajst-19160	187	15	than	than	ADP
ajst-19160	187	16	themselves	themselves	PRON
ajst-19160	187	17	.	.	PUNCT
ajst-19160	188	1	the	the	DET
ajst-19160	188	2	mathematical	mathematical	ADJ
ajst-19160	188	3	expression	expression	NOUN
ajst-19160	188	4	of	of	ADP
ajst-19160	188	5	their	their	PRON
ajst-19160	188	6	behavior	behavior	NOUN
ajst-19160	188	7	is	be	AUX
ajst-19160	188	8	:	:	PUNCT
ajst-19160	188	9			NOUN
ajst-19160	188	10			SYM
ajst-19160	188	11			NOUN
ajst-19160	188	12			SYM
ajst-19160	188	13			NOUN
ajst-19160	188	14			PUNCT
ajst-19160	188	15			NOUN
ajst-19160	188	16			NOUN
ajst-19160	188	17			PUNCT
ajst-19160	189	1	+	+	CCONJ
ajst-19160	189	2	1	1	NUM
ajst-19160	190	1	=	=	NOUN
ajst-19160	190	2	i	i	PRON
ajst-19160	191	1	i	i	PRON
ajst-19160	192	1	i	i	PRON
ajst-19160	192	2	jx	jx	PROPN
ajst-19160	193	1	t	t	PROPN
ajst-19160	193	2	x	x	X
ajst-19160	193	3	t	t	NOUN
ajst-19160	193	4	c	c	NOUN
ajst-19160	193	5	x	x	SYM
ajst-19160	193	6	t	t	NOUN
ajst-19160	193	7	x	x	PUNCT
ajst-19160	193	8	t	t	PRON
ajst-19160	193	9			ADJ
ajst-19160	193	10			NOUN
ajst-19160	193	11	(	(	PUNCT
ajst-19160	193	12	12	12	NUM
ajst-19160	193	13	)	)	PUNCT
ajst-19160	193	14	where	where	SCONJ
ajst-19160	193	15	:	:	PUNCT
ajst-19160	194	1	[	[	X
ajst-19160	194	2	3	3	NUM
ajst-19160	194	3	,	,	PUNCT
ajst-19160	194	4	]	]	PUNCT
ajst-19160	194	5	,	,	PUNCT
ajst-19160	194	6	i	i	PRON
ajst-19160	194	7	n	n	VERB
ajst-19160	194	8			NOUN
ajst-19160	194	9	randi	randi	PUNCT
ajst-19160	195	1	[	[	X
ajst-19160	195	2	2	2	NUM
ajst-19160	195	3	,	,	PUNCT
ajst-19160	195	4	1]j	1]j	PROPN
ajst-19160	195	5	i	i	PROPN
ajst-19160	195	6			PROPN
ajst-19160	195	7	.	.	PUNCT
ajst-19160	196	1	case3	case3	PROPN
ajst-19160	196	2	:	:	PUNCT
ajst-19160	196	3	omnivores	omnivore	NOUN
ajst-19160	196	4	ix	ix	ADV
ajst-19160	196	5	can	can	AUX
ajst-19160	196	6	prey	prey	VERB
ajst-19160	196	7	on	on	ADP
ajst-19160	196	8	producers	producer	NOUN
ajst-19160	196	9	1x	1x	NUM
ajst-19160	196	10	and	and	CCONJ
ajst-19160	196	11	an	an	DET
ajst-19160	196	12	animal	animal	NOUN
ajst-19160	196	13	jx	jx	NOUN
ajst-19160	196	14	with	with	ADP
ajst-19160	196	15	a	a	DET
ajst-19160	196	16	higher	high	ADJ
ajst-19160	196	17	energy	energy	NOUN
ajst-19160	196	18	level	level	NOUN
ajst-19160	196	19	than	than	ADP
ajst-19160	196	20	itself	itself	PRON
ajst-19160	196	21	.	.	PUNCT
ajst-19160	197	1	the	the	DET
ajst-19160	197	2	mathematical	mathematical	ADJ
ajst-19160	197	3	expression	expression	NOUN
ajst-19160	197	4	of	of	ADP
ajst-19160	197	5	its	its	PRON
ajst-19160	197	6	behavior	behavior	NOUN
ajst-19160	197	7	is	be	AUX
ajst-19160	197	8	:	:	PUNCT
ajst-19160	197	9			NOUN
ajst-19160	197	10			SYM
ajst-19160	197	11			NOUN
ajst-19160	197	12			SYM
ajst-19160	197	13			NOUN
ajst-19160	197	14			PUNCT
ajst-19160	197	15			NOUN
ajst-19160	198	1			NOUN
ajst-19160	199	1			PUNCT
ajst-19160	199	2			NOUN
ajst-19160	199	3			SYM
ajst-19160	199	4			NOUN
ajst-19160	199	5			PUNCT
ajst-19160	199	6			NOUN
ajst-19160	200	1			NOUN
ajst-19160	200	2			NOUN
ajst-19160	200	3	2	2	ADJ
ajst-19160	200	4	1	1	NUM
ajst-19160	200	5	2	2	NUM
ajst-19160	200	6	+	+	CCONJ
ajst-19160	200	7	1	1	NUM
ajst-19160	200	8	=	=	NOUN
ajst-19160	200	9	1i	1i	NOUN
ajst-19160	201	1	i	i	PRON
ajst-19160	201	2	i	i	PRON
ajst-19160	202	1	i	i	PRON
ajst-19160	202	2	jx	jx	PROPN
ajst-19160	203	1	t	t	PROPN
ajst-19160	203	2	x	x	X
ajst-19160	203	3	t	t	NOUN
ajst-19160	203	4	c	c	NOUN
ajst-19160	203	5	r	r	NOUN
ajst-19160	203	6	x	x	SYM
ajst-19160	203	7	t	t	NOUN
ajst-19160	203	8	x	x	SYM
ajst-19160	203	9	t	t	NOUN
ajst-19160	203	10	r	r	NOUN
ajst-19160	203	11	x	x	SYM
ajst-19160	203	12	t	t	NOUN
ajst-19160	203	13	x	x	PUNCT
ajst-19160	203	14	t	t	PRON
ajst-19160	203	15			ADJ
ajst-19160	203	16			ADJ
ajst-19160	203	17			NOUN
ajst-19160	203	18			PUNCT
ajst-19160	203	19			PROPN
ajst-19160	203	20			NOUN
ajst-19160	203	21	(	(	PUNCT
ajst-19160	203	22	13	13	NUM
ajst-19160	203	23	)	)	PUNCT
ajst-19160	204	1	where	where	SCONJ
ajst-19160	204	2	:	:	PUNCT
ajst-19160	204	3			NOUN
ajst-19160	204	4	randi	randi	PUNCT
ajst-19160	205	1	[	[	X
ajst-19160	205	2	2	2	NUM
ajst-19160	205	3	,	,	PUNCT
ajst-19160	205	4	1]j	1]j	PROPN
ajst-19160	205	5	i	i	PROPN
ajst-19160	205	6			PROPN
ajst-19160	205	7	,	,	PUNCT
ajst-19160	205	8	2	2	NUM
ajst-19160	205	9	0	0	NUM
ajst-19160	205	10	,	,	PUNCT
ajst-19160	205	11	1r	1r	NUM
ajst-19160	205	12			PROPN
ajst-19160	205	13			PROPN
ajst-19160	205	14			PROPN
ajst-19160	205	15	is	be	AUX
ajst-19160	205	16	herbivorous	herbivorous	ADJ
ajst-19160	205	17	proportion	proportion	NOUN
ajst-19160	205	18	.	.	PUNCT
ajst-19160	206	1	3	3	X
ajst-19160	206	2	)	)	PUNCT
ajst-19160	206	3	decomposition	decomposition	NOUN
ajst-19160	206	4	stage	stage	NOUN
ajst-19160	206	5	:	:	PUNCT
ajst-19160	206	6	the	the	DET
ajst-19160	206	7	organisms	organism	NOUN
ajst-19160	206	8	in	in	ADP
ajst-19160	206	9	the	the	DET
ajst-19160	206	10	ecosystem	ecosystem	NOUN
ajst-19160	206	11	will	will	AUX
ajst-19160	206	12	eventually	eventually	ADV
ajst-19160	206	13	be	be	AUX
ajst-19160	206	14	decomposed	decompose	VERB
ajst-19160	206	15	by	by	ADP
ajst-19160	206	16	the	the	DET
ajst-19160	206	17	decomposer	decomposer	NOUN
ajst-19160	206	18	nx	nx	NOUN
ajst-19160	206	19	,	,	PUNCT
ajst-19160	206	20	and	and	CCONJ
ajst-19160	206	21	the	the	DET
ajst-19160	206	22	mathematical	mathematical	ADJ
ajst-19160	206	23	expression	expression	NOUN
ajst-19160	206	24	of	of	ADP
ajst-19160	206	25	their	their	PRON
ajst-19160	206	26	behavior	behavior	NOUN
ajst-19160	206	27	is	be	AUX
ajst-19160	206	28	:	:	PUNCT
ajst-19160	206	29			NOUN
ajst-19160	207	1			SYM
ajst-19160	207	2			NOUN
ajst-19160	207	3			SYM
ajst-19160	207	4			NOUN
ajst-19160	207	5			PUNCT
ajst-19160	207	6			NOUN
ajst-19160	207	7			NOUN
ajst-19160	207	8	n	n	PROPN
ajst-19160	207	9	+	+	CCONJ
ajst-19160	207	10	1	1	X
ajst-19160	207	11	=	=	NOUN
ajst-19160	207	12	i	i	PRON
ajst-19160	207	13	n	n	VERB
ajst-19160	207	14	ix	ix	ADV
ajst-19160	207	15	t	t	PROPN
ajst-19160	207	16	x	x	PROPN
ajst-19160	207	17	t	t	PROPN
ajst-19160	207	18	b	b	PROPN
ajst-19160	207	19	e	e	X
ajst-19160	207	20	x	x	PROPN
ajst-19160	207	21	t	t	NOUN
ajst-19160	207	22	h	h	NOUN
ajst-19160	207	23	x	x	PUNCT
ajst-19160	207	24	t	t	PRON
ajst-19160	207	25			ADJ
ajst-19160	207	26			ADJ
ajst-19160	207	27			NOUN
ajst-19160	207	28			NUM
ajst-19160	207	29	(	(	PUNCT
ajst-19160	207	30	14	14	NUM
ajst-19160	207	31	)	)	PUNCT
ajst-19160	208	1	where	where	SCONJ
ajst-19160	208	2	:	:	PUNCT
ajst-19160	209	1	[	[	X
ajst-19160	209	2	1	1	NUM
ajst-19160	209	3	,	,	PUNCT
ajst-19160	209	4	]	]	PUNCT
ajst-19160	209	5	,	,	PUNCT
ajst-19160	209	6	i	i	PRON
ajst-19160	209	7	n	n	VERB
ajst-19160	209	8	=	=	PRON
ajst-19160	209	9	3b	3b	NUM
ajst-19160	209	10	u	u	NOUN
ajst-19160	209	11	is	be	AUX
ajst-19160	209	12	the	the	DET
ajst-19160	209	13	decomposition	decomposition	NOUN
ajst-19160	209	14	factor	factor	NOUN
ajst-19160	209	15	,	,	PUNCT
ajst-19160	209	16	which	which	PRON
ajst-19160	209	17	u	u	PRON
ajst-19160	209	18	obeys	obey	VERB
ajst-19160	209	19	the	the	DET
ajst-19160	209	20	standard	standard	ADJ
ajst-19160	209	21	normal	normal	ADJ
ajst-19160	209	22	distribution	distribution	NOUN
ajst-19160	209	23	.	.	PUNCT
ajst-19160	210	1			PROPN
ajst-19160	210	2	3	3	ADJ
ajst-19160	211	1	=	=	PUNCT
ajst-19160	211	2	randi	randi	NOUN
ajst-19160	211	3	1,2	1,2	NUM
ajst-19160	211	4	1e	1e	NOUN
ajst-19160	211	5	r	r	NOUN
ajst-19160	211	6			VERB
ajst-19160	211	7			NOUN
ajst-19160	211	8	,	,	PUNCT
ajst-19160	211	9	3	3	NUM
ajst-19160	211	10	=	=	SYM
ajst-19160	211	11	2	2	NUM
ajst-19160	211	12	1h	1h	NUM
ajst-19160	211	13	r	r	NOUN
ajst-19160	211	14			NOUN
ajst-19160	211	15	,	,	PUNCT
ajst-19160	211	16	3	3	NUM
ajst-19160	211	17	0	0	NUM
ajst-19160	211	18	,	,	PUNCT
ajst-19160	211	19	1r	1r	NUM
ajst-19160	211	20			PROPN
ajst-19160	211	21			PROPN
ajst-19160	211	22			PROPN
ajst-19160	211	23	is	be	AUX
ajst-19160	211	24	the	the	DET
ajst-19160	211	25	weight	weight	NOUN
ajst-19160	211	26	factor	factor	NOUN
ajst-19160	211	27	.	.	PUNCT
ajst-19160	212	1	after	after	ADP
ajst-19160	212	2	the	the	DET
ajst-19160	212	3	above	above	ADJ
ajst-19160	212	4	iteration	iteration	NOUN
ajst-19160	212	5	,	,	PUNCT
ajst-19160	212	6	if	if	SCONJ
ajst-19160	212	7	the	the	DET
ajst-19160	212	8	optimal	optimal	ADJ
ajst-19160	212	9	solution	solution	NOUN
ajst-19160	212	10	does	do	AUX
ajst-19160	212	11	not	not	PART
ajst-19160	212	12	meet	meet	VERB
ajst-19160	212	13	the	the	DET
ajst-19160	212	14	accuracy	accuracy	NOUN
ajst-19160	212	15	condition	condition	NOUN
ajst-19160	212	16	or	or	CCONJ
ajst-19160	212	17	the	the	DET
ajst-19160	212	18	maximum	maximum	ADJ
ajst-19160	212	19	number	number	NOUN
ajst-19160	212	20	of	of	ADP
ajst-19160	212	21	iterations	iteration	NOUN
ajst-19160	212	22	,	,	PUNCT
ajst-19160	212	23	the	the	DET
ajst-19160	212	24	process	process	NOUN
ajst-19160	212	25	is	be	AUX
ajst-19160	212	26	repeated	repeat	VERB
ajst-19160	212	27	until	until	SCONJ
ajst-19160	212	28	the	the	DET
ajst-19160	212	29	conditions	condition	NOUN
ajst-19160	212	30	are	be	AUX
ajst-19160	212	31	met	meet	VERB
ajst-19160	212	32	.	.	PUNCT
ajst-19160	213	1	however	however	ADV
ajst-19160	213	2	,	,	PUNCT
ajst-19160	213	3	in	in	ADP
ajst-19160	213	4	terms	term	NOUN
ajst-19160	213	5	of	of	ADP
ajst-19160	213	6	optimization	optimization	NOUN
ajst-19160	213	7	strategy	strategy	NOUN
ajst-19160	213	8	,	,	PUNCT
ajst-19160	213	9	the	the	DET
ajst-19160	213	10	linear	linear	ADJ
ajst-19160	213	11	decrease	decrease	NOUN
ajst-19160	213	12	in	in	ADP
ajst-19160	213	13	the	the	DET
ajst-19160	213	14	producer	producer	NOUN
ajst-19160	213	15	's	's	PART
ajst-19160	213	16	convergence	convergence	NOUN
ajst-19160	213	17	factor	factor	NOUN
ajst-19160	213	18	is	be	AUX
ajst-19160	213	19	insufficient	insufficient	ADJ
ajst-19160	213	20	to	to	PART
ajst-19160	213	21	provide	provide	VERB
ajst-19160	213	22	a	a	DET
ajst-19160	213	23	wide	wide	ADJ
ajst-19160	213	24	search	search	NOUN
ajst-19160	213	25	range	range	NOUN
ajst-19160	213	26	in	in	ADP
ajst-19160	213	27	the	the	DET
ajst-19160	213	28	early	early	ADJ
ajst-19160	213	29	stage	stage	NOUN
ajst-19160	213	30	of	of	ADP
ajst-19160	213	31	the	the	DET
ajst-19160	213	32	search	search	NOUN
ajst-19160	213	33	,	,	PUNCT
ajst-19160	213	34	which	which	PRON
ajst-19160	213	35	limits	limit	VERB
ajst-19160	213	36	the	the	DET
ajst-19160	213	37	algorithm	algorithm	NOUN
ajst-19160	213	38	's	's	PART
ajst-19160	213	39	accuracy	accuracy	NOUN
ajst-19160	213	40	.	.	PUNCT
ajst-19160	214	1	therefore	therefore	ADV
ajst-19160	214	2	,	,	PUNCT
ajst-19160	214	3	we	we	PRON
ajst-19160	214	4	propose	propose	VERB
ajst-19160	214	5	two	two	NUM
ajst-19160	214	6	improvement	improvement	NOUN
ajst-19160	214	7	strategies	strategy	NOUN
ajst-19160	214	8	to	to	PART
ajst-19160	214	9	address	address	VERB
ajst-19160	214	10	the	the	DET
ajst-19160	214	11	drawbacks	drawback	NOUN
ajst-19160	214	12	of	of	ADP
ajst-19160	214	13	linear	linear	ADJ
ajst-19160	214	14	convergence	convergence	NOUN
ajst-19160	214	15	.	.	PUNCT
ajst-19160	215	1	3.3	3.3	NUM
ajst-19160	215	2	.	.	PUNCT
ajst-19160	216	1	improvement	improvement	NOUN
ajst-19160	216	2	strategy	strategy	NOUN
ajst-19160	216	3	3.3.1	3.3.1	X
ajst-19160	216	4	.	.	PUNCT
ajst-19160	216	5	local	local	ADJ
ajst-19160	216	6	backtracking	backtrack	VERB
ajst-19160	216	7	mining	mining	NOUN
ajst-19160	216	8	strategy	strategy	NOUN
ajst-19160	216	9	(	(	PUNCT
ajst-19160	216	10	lbes	lbe	NOUN
ajst-19160	216	11	)	)	PUNCT
ajst-19160	216	12	it	it	PRON
ajst-19160	216	13	has	have	AUX
ajst-19160	216	14	been	be	AUX
ajst-19160	216	15	confirmed	confirm	VERB
ajst-19160	216	16	by	by	ADP
ajst-19160	216	17	zhao	zhao	PROPN
ajst-19160	216	18	that	that	SCONJ
ajst-19160	216	19	the	the	DET
ajst-19160	216	20	aeo	aeo	PROPN
ajst-19160	216	21	algorithm	algorithm	PROPN
ajst-19160	216	22	can	can	AUX
ajst-19160	216	23	further	far	ADV
ajst-19160	216	24	improve	improve	VERB
ajst-19160	216	25	local	local	ADJ
ajst-19160	216	26	development	development	NOUN
ajst-19160	216	27	capabilities	capability	NOUN
ajst-19160	216	28	.	.	PUNCT
ajst-19160	217	1	the	the	DET
ajst-19160	217	2	decomposer	decomposer	NOUN
ajst-19160	217	3	is	be	AUX
ajst-19160	217	4	the	the	DET
ajst-19160	217	5	optimal	optimal	ADJ
ajst-19160	217	6	solution	solution	NOUN
ajst-19160	217	7	after	after	ADP
ajst-19160	217	8	each	each	DET
ajst-19160	217	9	iteration	iteration	NOUN
ajst-19160	217	10	,	,	PUNCT
ajst-19160	217	11	and	and	CCONJ
ajst-19160	217	12	its	its	PRON
ajst-19160	217	13	historical	historical	ADJ
ajst-19160	217	14	sequence	sequence	NOUN
ajst-19160	217	15	contains	contain	VERB
ajst-19160	217	16	important	important	ADJ
ajst-19160	217	17	optimization	optimization	NOUN
ajst-19160	217	18	information	information	NOUN
ajst-19160	217	19	.	.	PUNCT
ajst-19160	218	1	the	the	DET
ajst-19160	218	2	local	local	ADJ
ajst-19160	218	3	backtracking	backtrack	VERB
ajst-19160	218	4	exploitation	exploitation	NOUN
ajst-19160	218	5	strategy	strategy	NOUN
ajst-19160	218	6	(	(	PUNCT
ajst-19160	218	7	lbes	lbes	PROPN
ajst-19160	218	8	)	)	PUNCT
ajst-19160	218	9	can	can	AUX
ajst-19160	218	10	be	be	AUX
ajst-19160	218	11	used	use	VERB
ajst-19160	218	12	to	to	PART
ajst-19160	218	13	achieve	achieve	VERB
ajst-19160	218	14	re	re	NOUN
ajst-19160	218	15	-	-	NOUN
ajst-19160	218	16	mining	mining	NOUN
ajst-19160	218	17	in	in	ADP
ajst-19160	218	18	the	the	DET
ajst-19160	218	19	local	local	ADJ
ajst-19160	218	20	area	area	NOUN
ajst-19160	218	21	through	through	ADP
ajst-19160	218	22	inheritance	inheritance	NOUN
ajst-19160	218	23	learning	learning	NOUN
ajst-19160	218	24	,	,	PUNCT
ajst-19160	218	25	as	as	SCONJ
ajst-19160	218	26	shown	show	VERB
ajst-19160	218	27	in	in	ADP
ajst-19160	218	28	fig	fig	NOUN
ajst-19160	218	29	.	.	PUNCT
ajst-19160	219	1	6	6	X
ajst-19160	219	2	.	.	X
ajst-19160	219	3	figure	figure	NOUN
ajst-19160	219	4	6	6	NUM
ajst-19160	219	5	.	.	PUNCT
ajst-19160	220	1	the	the	DET
ajst-19160	220	2	schematic	schematic	ADJ
ajst-19160	220	3	diagram	diagram	NOUN
ajst-19160	220	4	of	of	ADP
ajst-19160	220	5	lbes	lbe	NOUN
ajst-19160	220	6	strategy	strategy	NOUN
ajst-19160	220	7	with	with	ADP
ajst-19160	220	8	backtracking	backtrack	VERB
ajst-19160	220	9	step	step	NOUN
ajst-19160	220	10	of	of	ADP
ajst-19160	220	11	three	three	NUM
ajst-19160	220	12	.	.	PUNCT
ajst-19160	221	1	the	the	DET
ajst-19160	221	2	darker	dark	ADJ
ajst-19160	221	3	the	the	DET
ajst-19160	221	4	blue	blue	NOUN
ajst-19160	221	5	in	in	ADP
ajst-19160	221	6	the	the	DET
ajst-19160	221	7	figure	figure	NOUN
ajst-19160	221	8	,	,	PUNCT
ajst-19160	221	9	the	the	PRON
ajst-19160	221	10	closer	close	ADJ
ajst-19160	221	11	it	it	PRON
ajst-19160	221	12	is	be	AUX
ajst-19160	221	13	to	to	ADP
ajst-19160	221	14	the	the	DET
ajst-19160	221	15	real	real	ADJ
ajst-19160	221	16	global	global	ADJ
ajst-19160	221	17	optimal	optimal	ADJ
ajst-19160	221	18	value	value	NOUN
ajst-19160	221	19	.	.	PUNCT
ajst-19160	222	1	when	when	SCONJ
ajst-19160	222	2	the	the	DET
ajst-19160	222	3	length	length	NOUN
ajst-19160	222	4	n	n	PROPN
ajst-19160	222	5	of	of	ADP
ajst-19160	222	6	the	the	DET
ajst-19160	222	7	historical	historical	ADJ
ajst-19160	222	8	optimal	optimal	ADJ
ajst-19160	222	9	solution	solution	NOUN
ajst-19160	222	10	sequence	sequence	NOUN
ajst-19160	222	11	*	*	NOUN
ajst-19160	222	12	hisx	hisx	NOUN
ajst-19160	222	13	exceeds	exceed	VERB
ajst-19160	222	14	the	the	DET
ajst-19160	222	15	local	local	ADJ
ajst-19160	222	16	backtracking	backtrack	VERB
ajst-19160	222	17	step	step	NOUN
ajst-19160	222	18	s	s	PART
ajst-19160	222	19	,	,	PUNCT
ajst-19160	222	20	the	the	DET
ajst-19160	222	21	lbes	lbes	NOUN
ajst-19160	222	22	strategy	strategy	NOUN
ajst-19160	222	23	will	will	AUX
ajst-19160	222	24	be	be	AUX
ajst-19160	222	25	excited	excite	VERB
ajst-19160	222	26	and	and	CCONJ
ajst-19160	222	27	reversely	reversely	ADV
ajst-19160	222	28	select	select	VERB
ajst-19160	222	29	the	the	DET
ajst-19160	222	30	backtracking	backtrack	VERB
ajst-19160	222	31	step	step	NOUN
ajst-19160	222	32	s	s	VERB
ajst-19160	222	33	in	in	ADP
ajst-19160	222	34	*	*	NOUN
ajst-19160	222	35	hisx	hisx	NOUN
ajst-19160	222	36	.	.	PUNCT
ajst-19160	223	1	the	the	DET
ajst-19160	223	2	optimal	optimal	ADJ
ajst-19160	223	3	solution	solution	NOUN
ajst-19160	223	4	sequence	sequence	NOUN
ajst-19160	223	5	*	*	NOUN
ajst-19160	223	6	hisx	hisx	NOUN
ajst-19160	223	7	,	,	PUNCT
ajst-19160	223	8	calculate	calculate	VERB
ajst-19160	223	9	its	its	PRON
ajst-19160	223	10	mean	mean	ADJ
ajst-19160	223	11	value	value	NOUN
ajst-19160	223	12	m	m	NOUN
ajst-19160	223	13	and	and	CCONJ
ajst-19160	223	14	act	act	VERB
ajst-19160	223	15	on	on	ADP
ajst-19160	223	16	the	the	DET
ajst-19160	223	17	current	current	ADJ
ajst-19160	223	18	decomposer	decomposer	NOUN
ajst-19160	223	19	*	*	NOUN
ajst-19160	223	20	x	x	VERB
ajst-19160	223	21	to	to	PART
ajst-19160	223	22	generate	generate	VERB
ajst-19160	223	23	a	a	DET
ajst-19160	223	24	new	new	ADJ
ajst-19160	223	25	decomposer	decomposer	NOUN
ajst-19160	223	26	*	*	PUNCT
ajst-19160	223	27	newx	newx	NOUN
ajst-19160	223	28	.	.	PUNCT
ajst-19160	224	1	the	the	DET
ajst-19160	224	2	corresponding	corresponding	ADJ
ajst-19160	224	3	expression	expression	NOUN
ajst-19160	224	4	is	be	AUX
ajst-19160	224	5	:	:	PUNCT
ajst-19160	224	6	123	123	NUM
ajst-19160	224	7			NOUN
ajst-19160	224	8			SYM
ajst-19160	224	9			NOUN
ajst-19160	224	10			PUNCT
ajst-19160	224	11	*	*	PUNCT
ajst-19160	225	1	*	*	PUNCT
ajst-19160	225	2	*	*	PUNCT
ajst-19160	225	3	new	new	ADJ
ajst-19160	225	4	*	*	PUNCT
ajst-19160	225	5	=	=	SYM
ajst-19160	225	6	1	1	NUM
ajst-19160	225	7	:	:	PUNCT
ajst-19160	225	8	x	x	SYM
ajst-19160	225	9	x	x	PUNCT
ajst-19160	225	10	rand	rand	NOUN
ajst-19160	225	11	m	m	VERB
ajst-19160	225	12	x	x	NOUN
ajst-19160	225	13	m	m	PROPN
ajst-19160	225	14	hisx	hisx	NOUN
ajst-19160	225	15	n	n	PROPN
ajst-19160	225	16	s	s	NOUN
ajst-19160	225	17	n	n	PRON
ajst-19160	225	18			NOUN
ajst-19160	225	19			VERB
ajst-19160	225	20			PROPN
ajst-19160	225	21			NOUN
ajst-19160	225	22			NUM
ajst-19160	225	23			NUM
ajst-19160	225	24			PROPN
ajst-19160	225	25			PROPN
ajst-19160	225	26			NOUN
ajst-19160	225	27	(	(	PUNCT
ajst-19160	225	28	15	15	NUM
ajst-19160	225	29	)	)	PUNCT
ajst-19160	225	30	where	where	SCONJ
ajst-19160	225	31	:	:	PUNCT
ajst-19160	226	1	[	[	X
ajst-19160	226	2	0	0	NUM
ajst-19160	226	3	,	,	PUNCT
ajst-19160	226	4	1]rand	1]rand	NUM
ajst-19160	226	5	,	,	PUNCT
ajst-19160	226	6	whether	whether	SCONJ
ajst-19160	226	7	the	the	DET
ajst-19160	226	8	new	new	ADJ
ajst-19160	226	9	decomposer	decomposer	NOUN
ajst-19160	226	10	*	*	PUNCT
ajst-19160	226	11	newx	newx	PROPN
ajst-19160	226	12	is	be	AUX
ajst-19160	226	13	retained	retain	VERB
ajst-19160	226	14	will	will	AUX
ajst-19160	226	15	be	be	AUX
ajst-19160	226	16	determined	determine	VERB
ajst-19160	226	17	by	by	ADP
ajst-19160	226	18	eq	eq	PROPN
ajst-19160	226	19	.	.	PUNCT
ajst-19160	227	1	(	(	PUNCT
ajst-19160	227	2	16	16	NUM
ajst-19160	227	3	)	)	PUNCT
ajst-19160	227	4	:	:	PUNCT
ajst-19160	228	1			NOUN
ajst-19160	228	2			PUNCT
ajst-19160	228	3			NOUN
ajst-19160	229	1			PUNCT
ajst-19160	229	2	*	*	PUNCT
ajst-19160	229	3	*	*	PUNCT
ajst-19160	229	4	*	*	PUNCT
ajst-19160	229	5	new	new	ADJ
ajst-19160	229	6	new	new	ADJ
ajst-19160	229	7	*	*	PUNCT
ajst-19160	229	8	*	*	PUNCT
ajst-19160	229	9	,	,	PUNCT
ajst-19160	229	10	x	x	PUNCT
ajst-19160	229	11	f	f	NOUN
ajst-19160	229	12	x	x	X
ajst-19160	229	13	f	f	NOUN
ajst-19160	229	14	x	x	PUNCT
ajst-19160	229	15	x	x	PUNCT
ajst-19160	229	16	x	x	X
ajst-19160	229	17	otherwise	otherwise	ADV
ajst-19160	229	18			ADV
ajst-19160	229	19			VERB
ajst-19160	229	20			NUM
ajst-19160	229	21			NOUN
ajst-19160	229	22	，	，	PUNCT
ajst-19160	229	23	(	(	PUNCT
ajst-19160	229	24	16	16	NUM
ajst-19160	229	25	)	)	PUNCT
ajst-19160	229	26	it	it	PRON
ajst-19160	229	27	is	be	AUX
ajst-19160	229	28	noteworthy	noteworthy	ADJ
ajst-19160	229	29	,	,	PUNCT
ajst-19160	229	30	the	the	PRON
ajst-19160	229	31	larger	large	ADJ
ajst-19160	229	32	the	the	DET
ajst-19160	229	33	value	value	NOUN
ajst-19160	229	34	of	of	ADP
ajst-19160	229	35	the	the	DET
ajst-19160	229	36	backtracking	backtrack	VERB
ajst-19160	229	37	step	step	NOUN
ajst-19160	229	38	s	s	VERB
ajst-19160	229	39	is	be	AUX
ajst-19160	229	40	,	,	PUNCT
ajst-19160	229	41	the	the	DET
ajst-19160	229	42	more	more	ADV
ajst-19160	229	43	historical	historical	ADJ
ajst-19160	229	44	information	information	NOUN
ajst-19160	229	45	is	be	AUX
ajst-19160	229	46	used	use	VERB
ajst-19160	229	47	,	,	PUNCT
ajst-19160	229	48	the	the	DET
ajst-19160	229	49	more	more	ADJ
ajst-19160	229	50	noise	noise	NOUN
ajst-19160	229	51	is	be	AUX
ajst-19160	229	52	contained	contain	VERB
ajst-19160	229	53	,	,	PUNCT
ajst-19160	229	54	and	and	CCONJ
ajst-19160	229	55	the	the	PRON
ajst-19160	229	56	higher	high	ADJ
ajst-19160	229	57	the	the	DET
ajst-19160	229	58	complexity	complexity	NOUN
ajst-19160	229	59	.	.	PUNCT
ajst-19160	230	1	3.3.2	3.3.2	X
ajst-19160	230	2	.	.	X
ajst-19160	231	1	elite	elite	ADJ
ajst-19160	231	2	reverse	reverse	NOUN
ajst-19160	231	3	learning	learn	VERB
ajst-19160	231	4	strategy	strategy	NOUN
ajst-19160	232	1	tizhoosh	tizhoosh	INTJ
ajst-19160	232	2	h	h	NOUN
ajst-19160	233	1	r	r	NOUN
ajst-19160	234	1	[	[	X
ajst-19160	234	2	25	25	NUM
ajst-19160	234	3	]	]	PUNCT
ajst-19160	234	4	proposed	propose	VERB
ajst-19160	234	5	a	a	DET
ajst-19160	234	6	reverse	reverse	ADJ
ajst-19160	234	7	solution	solution	NOUN
ajst-19160	234	8	that	that	PRON
ajst-19160	234	9	is	be	AUX
ajst-19160	234	10	closer	close	ADJ
ajst-19160	234	11	to	to	ADP
ajst-19160	234	12	the	the	DET
ajst-19160	234	13	global	global	ADJ
ajst-19160	234	14	optimal	optimal	ADJ
ajst-19160	234	15	.	.	PUNCT
ajst-19160	235	1	the	the	DET
ajst-19160	235	2	main	main	ADJ
ajst-19160	235	3	update	update	NOUN
ajst-19160	235	4	principle	principle	NOUN
ajst-19160	235	5	is	be	AUX
ajst-19160	235	6	to	to	PART
ajst-19160	235	7	sort	sort	VERB
ajst-19160	235	8	the	the	DET
ajst-19160	235	9	excellent	excellent	ADJ
ajst-19160	235	10	individual	individual	ADJ
ajst-19160	235	11	n	n	NOUN
ajst-19160	235	12	and	and	CCONJ
ajst-19160	235	13	the	the	DET
ajst-19160	235	14	excellent	excellent	ADJ
ajst-19160	235	15	individual	individual	ADJ
ajst-19160	235	16	reverse	reverse	NOUN
ajst-19160	235	17	solution	solution	NOUN
ajst-19160	235	18	.	.	PUNCT
ajst-19160	236	1	the	the	DET
ajst-19160	236	2	individuals	individual	NOUN
ajst-19160	236	3	with	with	ADP
ajst-19160	236	4	lower	low	ADJ
ajst-19160	236	5	fitness	fitness	NOUN
ajst-19160	236	6	are	be	AUX
ajst-19160	236	7	selected	select	VERB
ajst-19160	236	8	as	as	ADP
ajst-19160	236	9	the	the	DET
ajst-19160	236	10	pre	pre	ADJ
ajst-19160	236	11	-	-	ADJ
ajst-19160	236	12	iteration	iteration	ADJ
ajst-19160	236	13	individuals	individual	NOUN
ajst-19160	236	14	.	.	PUNCT
ajst-19160	237	1	the	the	DET
ajst-19160	237	2	definition	definition	NOUN
ajst-19160	237	3	is	be	AUX
ajst-19160	237	4	:	:	PUNCT
ajst-19160	237	5	elite	elite	ADJ
ajst-19160	237	6	elito	elito	NOUN
ajst-19160	237	7	e	e	X
ajst-19160	237	8	*	*	PUNCT
ajst-19160	237	9	*	*	PUNCT
ajst-19160	237	10	new	new	ADJ
ajst-19160	237	11	_	_	PUNCT
ajst-19160	237	12	ld	ld	X
ajst-19160	237	13	_	_	PRON
ajst-19160	237	14	(	(	PUNCT
ajst-19160	237	15	)	)	PUNCT
ajst-19160	237	16	x	x	SYM
ajst-19160	237	17	rand	rand	NOUN
ajst-19160	237	18	x	x	PROPN
ajst-19160	237	19			VERB
ajst-19160	237	20			PROPN
ajst-19160	237	21			PUNCT
ajst-19160	237	22			NOUN
ajst-19160	237	23	(	(	PUNCT
ajst-19160	237	24	17	17	NUM
ajst-19160	237	25	)	)	PUNCT
ajst-19160	238	1	where	where	SCONJ
ajst-19160	238	2	:	:	PUNCT
ajst-19160	238	3	l	l	NOUN
ajst-19160	238	4	*	*	PUNCT
ajst-19160	238	5	ine	ine	PROPN
ajst-19160	238	6	ew	ew	PRON
ajst-19160	238	7	_	_	NOUN
ajst-19160	238	8	te	te	PROPN
ajst-19160	238	9	x	x	SYM
ajst-19160	238	10			X
ajst-19160	238	11			PROPN
ajst-19160	238	12			PROPN
ajst-19160	238	13			PROPN
ajst-19160	238	14	，	，	PUNCT
ajst-19160	238	15	,	,	PUNCT
ajst-19160	238	16			X
ajst-19160	238	17	,	,	PUNCT
ajst-19160	238	18			PROPN
ajst-19160	238	19	are	be	AUX
ajst-19160	238	20	the	the	DET
ajst-19160	238	21	upper	upper	ADJ
ajst-19160	238	22	and	and	CCONJ
ajst-19160	238	23	lower	low	ADJ
ajst-19160	238	24	boundaries	boundary	NOUN
ajst-19160	238	25	.	.	PUNCT
ajst-19160	239	1	the	the	DET
ajst-19160	239	2	dynamic	dynamic	ADJ
ajst-19160	239	3	boundary	boundary	NOUN
ajst-19160	239	4	overcomes	overcome	VERB
ajst-19160	239	5	the	the	DET
ajst-19160	239	6	disadvantage	disadvantage	NOUN
ajst-19160	239	7	of	of	ADP
ajst-19160	239	8	fixed	fix	VERB
ajst-19160	239	9	boundary	boundary	NOUN
ajst-19160	239	10	's	's	PART
ajst-19160	239	11	difficulty	difficulty	NOUN
ajst-19160	239	12	in	in	ADP
ajst-19160	239	13	preserving	preserve	VERB
ajst-19160	239	14	search	search	NOUN
ajst-19160	239	15	experience	experience	NOUN
ajst-19160	239	16	,	,	PUNCT
ajst-19160	239	17	enabling	enable	VERB
ajst-19160	239	18	it	it	PRON
ajst-19160	239	19	to	to	PART
ajst-19160	239	20	search	search	VERB
ajst-19160	239	21	in	in	ADP
ajst-19160	239	22	narrower	narrow	ADJ
ajst-19160	239	23	spaces	space	NOUN
ajst-19160	239	24	and	and	CCONJ
ajst-19160	239	25	improve	improve	VERB
ajst-19160	239	26	convergence	convergence	NOUN
ajst-19160	239	27	speed	speed	NOUN
ajst-19160	239	28	.	.	PUNCT
ajst-19160	240	1	however	however	ADV
ajst-19160	240	2	,	,	PUNCT
ajst-19160	240	3	the	the	DET
ajst-19160	240	4	fixed	fix	VERB
ajst-19160	240	5	boundary	boundary	NOUN
ajst-19160	240	6	can	can	AUX
ajst-19160	240	7	avoid	avoid	VERB
ajst-19160	240	8	getting	getting	AUX
ajst-19160	240	9	trapped	trap	VERB
ajst-19160	240	10	in	in	ADP
ajst-19160	240	11	local	local	ADJ
ajst-19160	240	12	optima	optima	NOUN
ajst-19160	240	13	during	during	ADP
ajst-19160	240	14	the	the	DET
ajst-19160	240	15	optimization	optimization	NOUN
ajst-19160	240	16	process	process	NOUN
ajst-19160	240	17	.	.	PUNCT
ajst-19160	241	1	as	as	SCONJ
ajst-19160	241	2	lbes	lbe	NOUN
ajst-19160	241	3	enhances	enhance	VERB
ajst-19160	241	4	local	local	ADJ
ajst-19160	241	5	optimization	optimization	NOUN
ajst-19160	241	6	capability	capability	NOUN
ajst-19160	241	7	in	in	ADP
ajst-19160	241	8	this	this	DET
ajst-19160	241	9	paper	paper	NOUN
ajst-19160	241	10	,	,	PUNCT
ajst-19160	241	11	we	we	PRON
ajst-19160	241	12	choose	choose	VERB
ajst-19160	241	13	the	the	DET
ajst-19160	241	14	fixed	fix	VERB
ajst-19160	241	15	boundary	boundary	ADJ
ajst-19160	241	16	strategy	strategy	NOUN
ajst-19160	241	17	to	to	PART
ajst-19160	241	18	strengthen	strengthen	VERB
ajst-19160	241	19	our	our	PRON
ajst-19160	241	20	ability	ability	NOUN
ajst-19160	241	21	to	to	PART
ajst-19160	241	22	escape	escape	VERB
ajst-19160	241	23	local	local	ADJ
ajst-19160	241	24	optima	optima	NOUN
ajst-19160	241	25	.	.	PUNCT
ajst-19160	242	1	the	the	DET
ajst-19160	242	2	optimization	optimization	NOUN
ajst-19160	242	3	principle	principle	NOUN
ajst-19160	242	4	is	be	AUX
ajst-19160	242	5	illustrated	illustrate	VERB
ajst-19160	242	6	in	in	ADP
ajst-19160	242	7	fig	fig	NOUN
ajst-19160	242	8	.	.	PUNCT
ajst-19160	243	1	7	7	X
ajst-19160	243	2	.	.	X
ajst-19160	243	3	although	although	SCONJ
ajst-19160	243	4	the	the	DET
ajst-19160	243	5	dynamic	dynamic	ADJ
ajst-19160	243	6	boundary	boundary	NOUN
ajst-19160	243	7	improves	improve	VERB
ajst-19160	243	8	convergence	convergence	NOUN
ajst-19160	243	9	speed	speed	NOUN
ajst-19160	243	10	,	,	PUNCT
ajst-19160	243	11	it	it	PRON
ajst-19160	243	12	may	may	AUX
ajst-19160	243	13	lead	lead	VERB
ajst-19160	243	14	to	to	ADP
ajst-19160	243	15	getting	getting	AUX
ajst-19160	243	16	trapped	trap	VERB
ajst-19160	243	17	in	in	ADP
ajst-19160	243	18	local	local	ADJ
ajst-19160	243	19	optima	optima	PROPN
ajst-19160	243	20	.	.	PUNCT
ajst-19160	244	1	figure	figure	NOUN
ajst-19160	244	2	7	7	NUM
ajst-19160	244	3	.	.	PUNCT
ajst-19160	245	1	elite	elite	ADJ
ajst-19160	245	2	reverse	reverse	NOUN
ajst-19160	245	3	learning	learn	VERB
ajst-19160	245	4	dynamic	dynamic	ADJ
ajst-19160	245	5	boundary	boundary	NOUN
ajst-19160	245	6	and	and	CCONJ
ajst-19160	245	7	fixed	fix	VERB
ajst-19160	245	8	boundary	boundary	ADJ
ajst-19160	245	9	diagram	diagram	PROPN
ajst-19160	245	10	3.4	3.4	NUM
ajst-19160	245	11	.	.	PUNCT
ajst-19160	246	1	iaeo	iaeo	NOUN
ajst-19160	246	2	-	-	PUNCT
ajst-19160	246	3	svm	svm	PROPN
ajst-19160	246	4	model	model	NOUN
ajst-19160	246	5	construction	construction	NOUN
ajst-19160	246	6	and	and	CCONJ
ajst-19160	246	7	experimental	experimental	ADJ
ajst-19160	246	8	process	process	NOUN
ajst-19160	246	9	to	to	PART
ajst-19160	246	10	avoid	avoid	VERB
ajst-19160	246	11	the	the	DET
ajst-19160	246	12	influence	influence	NOUN
ajst-19160	246	13	of	of	ADP
ajst-19160	246	14	data	datum	NOUN
ajst-19160	246	15	on	on	ADP
ajst-19160	246	16	each	each	DET
ajst-19160	246	17	other	other	ADJ
ajst-19160	246	18	,	,	PUNCT
ajst-19160	246	19	it	it	PRON
ajst-19160	246	20	is	be	AUX
ajst-19160	246	21	necessary	necessary	ADJ
ajst-19160	246	22	to	to	PART
ajst-19160	246	23	normalize	normalize	VERB
ajst-19160	246	24	all	all	DET
ajst-19160	246	25	the	the	DET
ajst-19160	246	26	data	datum	NOUN
ajst-19160	246	27	due	due	ADP
ajst-19160	246	28	to	to	ADP
ajst-19160	246	29	their	their	PRON
ajst-19160	246	30	varying	vary	VERB
ajst-19160	246	31	dimensions	dimension	NOUN
ajst-19160	246	32	.	.	PUNCT
ajst-19160	247	1	2	2	NUM
ajst-19160	247	2	1	1	NUM
ajst-19160	247	3	x	x	SYM
ajst-19160	247	4	x	x	PUNCT
ajst-19160	247	5	y	y	NOUN
ajst-19160	247	6	x	x	PUNCT
ajst-19160	247	7	x	x	SYM
ajst-19160	247	8			PROPN
ajst-19160	247	9			NUM
ajst-19160	247	10			PROPN
ajst-19160	247	11			PROPN
ajst-19160	247	12	min	min	PROPN
ajst-19160	247	13	max	max	PROPN
ajst-19160	247	14	min	min	PROPN
ajst-19160	247	15	(	(	PUNCT
ajst-19160	247	16	18	18	NUM
ajst-19160	247	17	)	)	PUNCT
ajst-19160	247	18			NOUN
ajst-19160	247	19			NOUN
ajst-19160	247	20	1	1	VERB
ajst-19160	247	21	1	1	NUM
ajst-19160	247	22	2ry	2ry	NOUN
ajst-19160	247	23	x	x	PUNCT
ajst-19160	248	1	x	x	PUNCT
ajst-19160	248	2	x	x	X
ajst-19160	248	3	x	x	PROPN
ajst-19160	248	4			PUNCT
ajst-19160	248	5			PROPN
ajst-19160	248	6	sim	sim	PROPN
ajst-19160	248	7	max	max	PROPN
ajst-19160	248	8	min	min	PROPN
ajst-19160	248	9	min	min	PROPN
ajst-19160	248	10	(	(	PUNCT
ajst-19160	248	11	19	19	NUM
ajst-19160	248	12	)	)	PUNCT
ajst-19160	248	13	where	where	SCONJ
ajst-19160	248	14	:	:	PUNCT
ajst-19160	248	15	x	x	PRON
ajst-19160	248	16	represents	represent	VERB
ajst-19160	248	17	the	the	DET
ajst-19160	248	18	parameter	parameter	NOUN
ajst-19160	248	19	to	to	PART
ajst-19160	248	20	be	be	AUX
ajst-19160	248	21	normalized	normalize	VERB
ajst-19160	248	22	,	,	PUNCT
ajst-19160	248	23	while	while	SCONJ
ajst-19160	248	24	xmin	xmin	PROPN
ajst-19160	248	25	and	and	CCONJ
ajst-19160	248	26	xmax	xmax	PROPN
ajst-19160	248	27	respectively	respectively	ADV
ajst-19160	248	28	denote	denote	VERB
ajst-19160	248	29	the	the	DET
ajst-19160	248	30	maximum	maximum	ADJ
ajst-19160	248	31	and	and	CCONJ
ajst-19160	248	32	minimum	minimum	ADJ
ajst-19160	248	33	values	value	NOUN
ajst-19160	248	34	of	of	ADP
ajst-19160	248	35	the	the	DET
ajst-19160	248	36	variable	variable	NOUN
ajst-19160	248	37	.	.	PUNCT
ajst-19160	249	1	y	y	PROPN
ajst-19160	249	2	represents	represent	VERB
ajst-19160	249	3	the	the	DET
ajst-19160	249	4	normalized	normalized	ADJ
ajst-19160	249	5	value	value	NOUN
ajst-19160	249	6	of	of	ADP
ajst-19160	249	7	the	the	DET
ajst-19160	249	8	variable	variable	NOUN
ajst-19160	249	9	,	,	PUNCT
ajst-19160	249	10	xsim	xsim	PROPN
ajst-19160	249	11	denotes	denote	VERB
ajst-19160	249	12	the	the	DET
ajst-19160	249	13	fitted	fit	VERB
ajst-19160	249	14	output	output	NOUN
ajst-19160	249	15	value	value	NOUN
ajst-19160	249	16	,	,	PUNCT
ajst-19160	249	17	and	and	CCONJ
ajst-19160	249	18	ry	ry	AUX
ajst-19160	249	19	represents	represent	VERB
ajst-19160	249	20	the	the	DET
ajst-19160	249	21	model	model	NOUN
ajst-19160	249	22	prediction	prediction	NOUN
ajst-19160	249	23	value	value	NOUN
ajst-19160	249	24	obtained	obtain	VERB
ajst-19160	249	25	through	through	ADP
ajst-19160	249	26	reverse	reverse	ADJ
ajst-19160	249	27	normalization	normalization	NOUN
ajst-19160	249	28	.	.	PUNCT
ajst-19160	250	1	from	from	ADP
ajst-19160	250	2	the	the	DET
ajst-19160	250	3	svm	svm	PROPN
ajst-19160	250	4	theoretical	theoretical	ADJ
ajst-19160	250	5	knowledge	knowledge	NOUN
ajst-19160	250	6	presented	present	VERB
ajst-19160	250	7	in	in	ADP
ajst-19160	250	8	section	section	NOUN
ajst-19160	250	9	2.1	2.1	NUM
ajst-19160	250	10	,	,	PUNCT
ajst-19160	250	11	it	it	PRON
ajst-19160	250	12	is	be	AUX
ajst-19160	250	13	apparent	apparent	ADJ
ajst-19160	250	14	that	that	SCONJ
ajst-19160	250	15	the	the	DET
ajst-19160	250	16	penalty	penalty	NOUN
ajst-19160	250	17	factor	factor	NOUN
ajst-19160	250	18	and	and	CCONJ
ajst-19160	250	19	the	the	DET
ajst-19160	250	20	slack	slack	NOUN
ajst-19160	250	21	variable	variable	NOUN
ajst-19160	250	22	of	of	ADP
ajst-19160	250	23	the	the	DET
ajst-19160	250	24	svm	svm	ADJ
ajst-19160	250	25	model	model	NOUN
ajst-19160	250	26	are	be	AUX
ajst-19160	250	27	manually	manually	ADV
ajst-19160	250	28	set	set	VERB
ajst-19160	250	29	or	or	CCONJ
ajst-19160	250	30	optimized	optimize	VERB
ajst-19160	250	31	using	use	VERB
ajst-19160	250	32	an	an	DET
ajst-19160	250	33	optimization	optimization	NOUN
ajst-19160	250	34	algorithm	algorithm	NOUN
ajst-19160	250	35	.	.	PUNCT
ajst-19160	251	1	currently	currently	ADV
ajst-19160	251	2	,	,	PUNCT
ajst-19160	251	3	the	the	DET
ajst-19160	251	4	optimization	optimization	NOUN
ajst-19160	251	5	algorithms	algorithm	NOUN
ajst-19160	251	6	commonly	commonly	ADV
ajst-19160	251	7	employed	employ	VERB
ajst-19160	251	8	fail	fail	VERB
ajst-19160	251	9	to	to	PART
ajst-19160	251	10	satisfy	satisfy	VERB
ajst-19160	251	11	the	the	DET
ajst-19160	251	12	prediction	prediction	NOUN
ajst-19160	251	13	accuracy	accuracy	NOUN
ajst-19160	251	14	requirements	requirement	NOUN
ajst-19160	251	15	of	of	ADP
ajst-19160	251	16	svm	svm	PROPN
ajst-19160	251	17	.	.	PUNCT
ajst-19160	252	1	consequently	consequently	ADV
ajst-19160	252	2	,	,	PUNCT
ajst-19160	252	3	this	this	DET
ajst-19160	252	4	paper	paper	NOUN
ajst-19160	252	5	proposes	propose	VERB
ajst-19160	252	6	an	an	DET
ajst-19160	252	7	improved	improved	ADJ
ajst-19160	252	8	optimization	optimization	NOUN
ajst-19160	252	9	algorithm	algorithm	NOUN
ajst-19160	252	10	,	,	PUNCT
ajst-19160	252	11	the	the	DET
ajst-19160	252	12	iaeo	iaeo	NOUN
ajst-19160	252	13	algorithm	algorithm	NOUN
ajst-19160	252	14	,	,	PUNCT
ajst-19160	252	15	to	to	PART
ajst-19160	252	16	optimize	optimize	VERB
ajst-19160	252	17	svm	svm	PROPN
ajst-19160	252	18	.	.	PUNCT
ajst-19160	253	1	the	the	DET
ajst-19160	253	2	flow	flow	NOUN
ajst-19160	253	3	chart	chart	NOUN
ajst-19160	253	4	of	of	ADP
ajst-19160	253	5	the	the	DET
ajst-19160	253	6	iaeosvm	iaeosvm	ADJ
ajst-19160	253	7	optimization	optimization	NOUN
ajst-19160	253	8	model	model	NOUN
ajst-19160	253	9	is	be	AUX
ajst-19160	253	10	illustrated	illustrate	VERB
ajst-19160	253	11	in	in	ADP
ajst-19160	253	12	fig	fig	NOUN
ajst-19160	253	13	.	.	PUNCT
ajst-19160	254	1	8	8	X
ajst-19160	254	2	.	.	PUNCT
ajst-19160	255	1	it	it	PRON
ajst-19160	255	2	is	be	AUX
ajst-19160	255	3	worth	worth	ADJ
ajst-19160	255	4	noting	note	VERB
ajst-19160	255	5	that	that	SCONJ
ajst-19160	255	6	in	in	ADP
ajst-19160	255	7	order	order	NOUN
ajst-19160	255	8	to	to	PART
ajst-19160	255	9	ensure	ensure	VERB
ajst-19160	255	10	the	the	DET
ajst-19160	255	11	fairness	fairness	NOUN
ajst-19160	255	12	of	of	ADP
ajst-19160	255	13	the	the	DET
ajst-19160	255	14	comparison	comparison	NOUN
ajst-19160	255	15	between	between	ADP
ajst-19160	255	16	the	the	DET
ajst-19160	255	17	iaeo	iaeo	NOUN
ajst-19160	255	18	-	-	PUNCT
ajst-19160	255	19	svm	svm	NOUN
ajst-19160	255	20	model	model	NOUN
ajst-19160	255	21	and	and	CCONJ
ajst-19160	255	22	the	the	DET
ajst-19160	255	23	aeo	aeo	PROPN
ajst-19160	255	24	-	-	PUNCT
ajst-19160	255	25	svm	svm	PROPN
ajst-19160	255	26	model	model	NOUN
ajst-19160	255	27	,	,	PUNCT
ajst-19160	255	28	this	this	DET
ajst-19160	255	29	paper	paper	NOUN
ajst-19160	255	30	sets	set	VERB
ajst-19160	255	31	the	the	DET
ajst-19160	255	32	population	population	NOUN
ajst-19160	255	33	number	number	NOUN
ajst-19160	255	34	of	of	ADP
ajst-19160	255	35	the	the	DET
ajst-19160	255	36	optimization	optimization	NOUN
ajst-19160	255	37	algorithm	algorithm	NOUN
ajst-19160	255	38	to	to	ADP
ajst-19160	255	39	10	10	NUM
ajst-19160	255	40	,	,	PUNCT
ajst-19160	255	41	iterates	iterate	VERB
ajst-19160	255	42	20	20	NUM
ajst-19160	255	43	times	time	NOUN
ajst-19160	255	44	,	,	PUNCT
ajst-19160	255	45	and	and	CCONJ
ajst-19160	255	46	the	the	DET
ajst-19160	255	47	optimization	optimization	NOUN
ajst-19160	255	48	boundary	boundary	NOUN
ajst-19160	255	49	is	be	AUX
ajst-19160	255	50	set	set	VERB
ajst-19160	255	51	to	to	ADP
ajst-19160	255	52	[	[	PUNCT
ajst-19160	255	53	0.1	0.1	NUM
ajst-19160	255	54	,	,	PUNCT
ajst-19160	255	55	100	100	NUM
ajst-19160	255	56	]	]	PUNCT
ajst-19160	255	57	.	.	PUNCT
ajst-19160	256	1	124	124	NUM
ajst-19160	256	2	figure	figure	NOUN
ajst-19160	256	3	8	8	NUM
ajst-19160	256	4	.	.	PUNCT
ajst-19160	256	5	iaeo	iaeo	NOUN
ajst-19160	256	6	-	-	PUNCT
ajst-19160	256	7	svm	svm	PROPN
ajst-19160	256	8	model	model	NOUN
ajst-19160	256	9	flow	flow	NOUN
ajst-19160	256	10	chart	chart	NOUN
ajst-19160	256	11	4	4	NUM
ajst-19160	256	12	.	.	PUNCT
ajst-19160	256	13	key	key	ADJ
ajst-19160	256	14	parameters	parameter	NOUN
ajst-19160	256	15	setting	set	VERB
ajst-19160	256	16	and	and	CCONJ
ajst-19160	256	17	evaluation	evaluation	NOUN
ajst-19160	256	18	index	index	NOUN
ajst-19160	256	19	of	of	ADP
ajst-19160	256	20	machine	machine	NOUN
ajst-19160	256	21	learning	learn	VERB
ajst-19160	256	22	model	model	NOUN
ajst-19160	256	23	4.1	4.1	NUM
ajst-19160	256	24	.	.	PUNCT
ajst-19160	257	1	key	key	ADJ
ajst-19160	257	2	parameter	parameter	NOUN
ajst-19160	257	3	settings	setting	NOUN
ajst-19160	257	4	of	of	ADP
ajst-19160	257	5	machine	machine	NOUN
ajst-19160	257	6	learning	learning	NOUN
ajst-19160	257	7	model	model	NOUN
ajst-19160	257	8	the	the	DET
ajst-19160	257	9	parameter	parameter	NOUN
ajst-19160	257	10	settings	setting	NOUN
ajst-19160	257	11	of	of	ADP
ajst-19160	257	12	the	the	DET
ajst-19160	257	13	machine	machine	NOUN
ajst-19160	257	14	learning	learning	NOUN
ajst-19160	257	15	model	model	NOUN
ajst-19160	257	16	can	can	AUX
ajst-19160	257	17	greatly	greatly	ADV
ajst-19160	257	18	affect	affect	VERB
ajst-19160	257	19	the	the	DET
ajst-19160	257	20	final	final	ADJ
ajst-19160	257	21	results	result	NOUN
ajst-19160	257	22	[	[	X
ajst-19160	257	23	26	26	NUM
ajst-19160	257	24	]	]	PUNCT
ajst-19160	257	25	.	.	PUNCT
ajst-19160	258	1	after	after	ADP
ajst-19160	258	2	repeated	repeat	VERB
ajst-19160	258	3	testing	testing	NOUN
ajst-19160	258	4	,	,	PUNCT
ajst-19160	258	5	the	the	DET
ajst-19160	258	6	final	final	ADJ
ajst-19160	258	7	model	model	NOUN
ajst-19160	258	8	's	's	PART
ajst-19160	258	9	parameters	parameter	NOUN
ajst-19160	258	10	are	be	AUX
ajst-19160	258	11	determined	determine	VERB
ajst-19160	258	12	as	as	SCONJ
ajst-19160	258	13	shown	show	VERB
ajst-19160	258	14	in	in	ADP
ajst-19160	258	15	table	table	NOUN
ajst-19160	258	16	4	4	NUM
ajst-19160	258	17	.	.	PUNCT
ajst-19160	259	1	it	it	PRON
ajst-19160	259	2	is	be	AUX
ajst-19160	259	3	noteworthy	noteworthy	ADJ
ajst-19160	259	4	that	that	SCONJ
ajst-19160	259	5	the	the	DET
ajst-19160	259	6	ann	ann	PROPN
ajst-19160	259	7	training	training	NOUN
ajst-19160	259	8	will	will	AUX
ajst-19160	259	9	not	not	PART
ajst-19160	259	10	use	use	VERB
ajst-19160	259	11	the	the	DET
ajst-19160	259	12	traditional	traditional	ADJ
ajst-19160	259	13	gradient	gradient	ADJ
ajst-19160	259	14	descent	descent	NOUN
ajst-19160	259	15	algorithm	algorithm	NOUN
ajst-19160	259	16	,	,	PUNCT
ajst-19160	259	17	as	as	SCONJ
ajst-19160	259	18	this	this	DET
ajst-19160	259	19	algorithm	algorithm	NOUN
ajst-19160	259	20	can	can	AUX
ajst-19160	259	21	be	be	AUX
ajst-19160	259	22	easily	easily	ADV
ajst-19160	259	23	influenced	influence	VERB
ajst-19160	259	24	by	by	ADP
ajst-19160	259	25	the	the	DET
ajst-19160	259	26	initial	initial	ADJ
ajst-19160	259	27	values	value	NOUN
ajst-19160	259	28	[	[	X
ajst-19160	259	29	28	28	NUM
ajst-19160	259	30	]	]	PUNCT
ajst-19160	259	31	,	,	PUNCT
ajst-19160	259	32	which	which	PRON
ajst-19160	259	33	can	can	AUX
ajst-19160	259	34	lead	lead	VERB
ajst-19160	259	35	to	to	ADP
ajst-19160	259	36	premature	premature	ADJ
ajst-19160	259	37	convergence	convergence	NOUN
ajst-19160	259	38	in	in	ADP
ajst-19160	259	39	regions	region	NOUN
ajst-19160	259	40	with	with	ADP
ajst-19160	259	41	gentle	gentle	ADJ
ajst-19160	259	42	gradients	gradient	NOUN
ajst-19160	259	43	.	.	PUNCT
ajst-19160	260	1	the	the	DET
ajst-19160	260	2	lm	lm	PROPN
ajst-19160	260	3	algorithm	algorithm	NOUN
ajst-19160	260	4	,	,	PUNCT
ajst-19160	260	5	proposed	propose	VERB
ajst-19160	260	6	by	by	ADP
ajst-19160	260	7	wilamowski	wilamowski	PROPN
ajst-19160	260	8	b	b	PROPN
ajst-19160	260	9	m	m	PROPN
ajst-19160	260	10	[	[	X
ajst-19160	260	11	29	29	NUM
ajst-19160	260	12	]	]	PUNCT
ajst-19160	260	13	,	,	PUNCT
ajst-19160	260	14	can	can	AUX
ajst-19160	260	15	significantly	significantly	ADV
ajst-19160	260	16	improve	improve	VERB
ajst-19160	260	17	convergence	convergence	NOUN
ajst-19160	260	18	speed	speed	NOUN
ajst-19160	260	19	and	and	CCONJ
ajst-19160	260	20	accuracy	accuracy	NOUN
ajst-19160	260	21	compared	compare	VERB
ajst-19160	260	22	to	to	ADP
ajst-19160	260	23	gradient	gradient	ADJ
ajst-19160	260	24	descent	descent	NOUN
ajst-19160	260	25	.	.	PUNCT
ajst-19160	261	1	therefore	therefore	ADV
ajst-19160	261	2	,	,	PUNCT
ajst-19160	261	3	in	in	ADP
ajst-19160	261	4	this	this	DET
ajst-19160	261	5	paper	paper	NOUN
ajst-19160	261	6	,	,	PUNCT
ajst-19160	261	7	we	we	PRON
ajst-19160	261	8	use	use	VERB
ajst-19160	261	9	the	the	DET
ajst-19160	261	10	lm	lm	ADJ
ajst-19160	261	11	algorithm	algorithm	NOUN
ajst-19160	261	12	instead	instead	ADV
ajst-19160	261	13	of	of	ADP
ajst-19160	261	14	the	the	DET
ajst-19160	261	15	ann	ann	PROPN
ajst-19160	261	16	gradient	gradient	PROPN
ajst-19160	261	17	descent	descent	NOUN
ajst-19160	261	18	algorithm	algorithm	NOUN
ajst-19160	261	19	.	.	PUNCT
ajst-19160	262	1	elm	elm	NOUN
ajst-19160	262	2	is	be	AUX
ajst-19160	262	3	widely	widely	ADV
ajst-19160	262	4	used	use	VERB
ajst-19160	262	5	in	in	ADP
ajst-19160	262	6	the	the	DET
ajst-19160	262	7	fields	field	NOUN
ajst-19160	262	8	of	of	ADP
ajst-19160	262	9	image	image	NOUN
ajst-19160	262	10	recognition	recognition	NOUN
ajst-19160	262	11	and	and	CCONJ
ajst-19160	262	12	fault	fault	VERB
ajst-19160	262	13	diagnosis	diagnosis	NOUN
ajst-19160	262	14	[	[	X
ajst-19160	262	15	30	30	NUM
ajst-19160	262	16	]	]	PUNCT
ajst-19160	262	17	.	.	PUNCT
ajst-19160	263	1	rbf	rbf	PROPN
ajst-19160	263	2	and	and	CCONJ
ajst-19160	263	3	grnn	grnn	PROPN
ajst-19160	263	4	have	have	VERB
ajst-19160	263	5	excellent	excellent	ADJ
ajst-19160	263	6	performance	performance	NOUN
ajst-19160	263	7	in	in	ADP
ajst-19160	263	8	nonlinear	nonlinear	NOUN
ajst-19160	263	9	fitting	fitting	ADJ
ajst-19160	263	10	in	in	ADP
ajst-19160	263	11	engineering	engineering	NOUN
ajst-19160	263	12	field	field	NOUN
ajst-19160	263	13	.	.	PUNCT
ajst-19160	264	1	table	table	NOUN
ajst-19160	264	2	4	4	NUM
ajst-19160	264	3	.	.	PUNCT
ajst-19160	264	4	machine	machine	NOUN
ajst-19160	264	5	learning	learning	NOUN
ajst-19160	264	6	model	model	NOUN
ajst-19160	264	7	related	relate	VERB
ajst-19160	264	8	parameter	parameter	NOUN
ajst-19160	264	9	settings	setting	NOUN
ajst-19160	264	10	.	.	PUNCT
ajst-19160	265	1	model	model	PROPN
ajst-19160	265	2	parameter	parameter	PROPN
ajst-19160	265	3	ann	ann	PROPN
ajst-19160	265	4	-	-	PUNCT
ajst-19160	265	5	lm	lm	PROPN
ajst-19160	265	6	activation	activation	NOUN
ajst-19160	265	7	function	function	NOUN
ajst-19160	265	8	from	from	ADP
ajst-19160	265	9	input	input	NOUN
ajst-19160	265	10	layer	layer	NOUN
ajst-19160	265	11	to	to	ADP
ajst-19160	265	12	hidden	hide	VERB
ajst-19160	265	13	layer	layer	NOUN
ajst-19160	265	14	:	:	PUNCT
ajst-19160	265	15	logsig	logsig	VERB
ajst-19160	265	16	hidden	hide	VERB
ajst-19160	265	17	layer	layer	NOUN
ajst-19160	265	18	to	to	PART
ajst-19160	265	19	output	output	VERB
ajst-19160	265	20	layer	layer	NOUN
ajst-19160	265	21	activation	activation	NOUN
ajst-19160	265	22	function	function	NOUN
ajst-19160	265	23	:	:	PUNCT
ajst-19160	265	24	purlin	purlin	NOUN
ajst-19160	265	25	number	number	NOUN
ajst-19160	265	26	of	of	ADP
ajst-19160	265	27	hidden	hide	VERB
ajst-19160	265	28	layer	layer	NOUN
ajst-19160	265	29	neurons	neuron	NOUN
ajst-19160	265	30	:	:	PUNCT
ajst-19160	265	31	8	8	NUM
ajst-19160	265	32	learning	learn	VERB
ajst-19160	265	33	goals	goal	NOUN
ajst-19160	265	34	:	:	PUNCT
ajst-19160	265	35	1e-8	1e-8	NUM
ajst-19160	265	36	learning	learning	NOUN
ajst-19160	265	37	rate	rate	NOUN
ajst-19160	265	38	:	:	PUNCT
ajst-19160	265	39	0.1	0.1	NUM
ajst-19160	265	40	maximum	maximum	ADJ
ajst-19160	265	41	number	number	NOUN
ajst-19160	265	42	of	of	ADP
ajst-19160	265	43	iterations	iteration	NOUN
ajst-19160	265	44	:	:	PUNCT
ajst-19160	265	45	1000	1000	NUM
ajst-19160	265	46	training	training	NOUN
ajst-19160	265	47	function	function	NOUN
ajst-19160	265	48	:	:	PUNCT
ajst-19160	265	49	trainlm	trainlm	NOUN
ajst-19160	265	50	svm	svm	PROPN
ajst-19160	265	51	kernel	kernel	PROPN
ajst-19160	265	52	function	function	PROPN
ajst-19160	265	53	:	:	PUNCT
ajst-19160	265	54	radial	radial	ADJ
ajst-19160	265	55	basis	basis	NOUN
ajst-19160	265	56	c	c	NOUN
ajst-19160	265	57	:	:	PUNCT
ajst-19160	265	58	2.1	2.1	NUM
ajst-19160	265	59	g	g	NOUN
ajst-19160	265	60	:	:	PUNCT
ajst-19160	265	61	2.1	2.1	NUM
ajst-19160	265	62	rbf	rbf	PROPN
ajst-19160	265	63	the	the	DET
ajst-19160	265	64	extension	extension	NOUN
ajst-19160	265	65	speed	speed	NOUN
ajst-19160	265	66	of	of	ADP
ajst-19160	265	67	radial	radial	ADJ
ajst-19160	265	68	basis	basis	NOUN
ajst-19160	265	69	function	function	NOUN
ajst-19160	265	70	:	:	PUNCT
ajst-19160	265	71	1.5	1.5	NUM
ajst-19160	265	72	hidden	hide	VERB
ajst-19160	265	73	layer	layer	NOUN
ajst-19160	265	74	neurons	neuron	NOUN
ajst-19160	265	75	:	:	PUNCT
ajst-19160	265	76	8	8	NUM
ajst-19160	265	77	grnn	grnn	NOUN
ajst-19160	265	78	smooth	smooth	ADJ
ajst-19160	265	79	factor	factor	NOUN
ajst-19160	265	80	value	value	NOUN
ajst-19160	265	81	:	:	PUNCT
ajst-19160	265	82	1.0	1.0	NUM
ajst-19160	265	83	elm	elm	NOUN
ajst-19160	265	84	activation	activation	NOUN
ajst-19160	265	85	function	function	NOUN
ajst-19160	265	86	from	from	ADP
ajst-19160	265	87	input	input	NOUN
ajst-19160	265	88	layer	layer	NOUN
ajst-19160	265	89	to	to	ADP
ajst-19160	265	90	hidden	hide	VERB
ajst-19160	265	91	layer	layer	NOUN
ajst-19160	265	92	:	:	PUNCT
ajst-19160	265	93	sig	sig	ADJ
ajst-19160	265	94	number	number	NOUN
ajst-19160	265	95	of	of	ADP
ajst-19160	265	96	hidden	hide	VERB
ajst-19160	265	97	layer	layer	NOUN
ajst-19160	265	98	neurons	neuron	NOUN
ajst-19160	265	99	:	:	PUNCT
ajst-19160	265	100	8	8	NUM
ajst-19160	265	101	4.2	4.2	NUM
ajst-19160	265	102	.	.	PUNCT
ajst-19160	266	1	evaluation	evaluation	NOUN
ajst-19160	266	2	indicators	indicator	NOUN
ajst-19160	266	3	verify	verify	VERB
ajst-19160	266	4	the	the	DET
ajst-19160	266	5	pros	pro	NOUN
ajst-19160	266	6	and	and	CCONJ
ajst-19160	266	7	cons	con	NOUN
ajst-19160	266	8	of	of	ADP
ajst-19160	266	9	the	the	DET
ajst-19160	266	10	model	model	NOUN
ajst-19160	266	11	usually	usually	ADV
ajst-19160	266	12	means	mean	VERB
ajst-19160	266	13	absolute	absolute	ADJ
ajst-19160	266	14	error	error	NOUN
ajst-19160	266	15	(	(	PUNCT
ajst-19160	266	16	mae	mae	PROPN
ajst-19160	266	17	)	)	PUNCT
ajst-19160	266	18	,	,	PUNCT
ajst-19160	266	19	means	mean	VERB
ajst-19160	266	20	square	square	ADJ
ajst-19160	266	21	error	error	NOUN
ajst-19160	266	22	(	(	PUNCT
ajst-19160	266	23	mse	mse	NOUN
ajst-19160	266	24	)	)	PUNCT
ajst-19160	266	25	,	,	PUNCT
ajst-19160	266	26	and	and	CCONJ
ajst-19160	266	27	coefficient	coefficient	NOUN
ajst-19160	266	28	of	of	ADP
ajst-19160	266	29	determination	determination	NOUN
ajst-19160	266	30	(	(	PUNCT
ajst-19160	266	31	r2	r2	PROPN
ajst-19160	266	32	)	)	PUNCT
ajst-19160	266	33	are	be	AUX
ajst-19160	266	34	three	three	NUM
ajst-19160	266	35	indicators	indicator	NOUN
ajst-19160	266	36	to	to	PART
ajst-19160	266	37	measure	measure	VERB
ajst-19160	266	38	.	.	PUNCT
ajst-19160	267	1	evaluating	evaluate	VERB
ajst-19160	267	2	indicators	indicator	NOUN
ajst-19160	267	3	can	can	AUX
ajst-19160	267	4	effectively	effectively	ADV
ajst-19160	267	5	reflect	reflect	VERB
ajst-19160	267	6	the	the	DET
ajst-19160	267	7	accuracy	accuracy	NOUN
ajst-19160	267	8	of	of	ADP
ajst-19160	267	9	model	model	NOUN
ajst-19160	267	10	prediction	prediction	NOUN
ajst-19160	267	11	and	and	CCONJ
ajst-19160	267	12	fitting	fitting	ADJ
ajst-19160	267	13	degree	degree	NOUN
ajst-19160	267	14	,	,	PUNCT
ajst-19160	267	15	the	the	DET
ajst-19160	267	16	eqs	eqs	X
ajst-19160	267	17	.	.	PUNCT
ajst-19160	268	1	(	(	PUNCT
ajst-19160	268	2	2022	2022	NUM
ajst-19160	268	3	)	)	PUNCT
ajst-19160	268	4	is	be	AUX
ajst-19160	268	5	:	:	PUNCT
ajst-19160	268	6	1	1	NUM
ajst-19160	268	7	1	1	NUM
ajst-19160	268	8	n	n	NUM
ajst-19160	268	9	mae	mae	PROPN
ajst-19160	269	1	i	i	PRON
ajst-19160	269	2	i	i	PRON
ajst-19160	270	1	i	i	VERB
ajst-19160	270	2	e	e	VERB
ajst-19160	270	3	y	y	PROPN
ajst-19160	270	4	p	p	PROPN
ajst-19160	271	1	n	n	CCONJ
ajst-19160	271	2			NUM
ajst-19160	271	3			NUM
ajst-19160	272	1			NOUN
ajst-19160	272	2	(	(	PUNCT
ajst-19160	272	3	20	20	NUM
ajst-19160	272	4	)	)	PUNCT
ajst-19160	272	5			NOUN
ajst-19160	272	6	2	2	ADJ
ajst-19160	272	7	1	1	NUM
ajst-19160	272	8	1	1	NUM
ajst-19160	272	9	n	n	NUM
ajst-19160	272	10	mse	mse	NOUN
ajst-19160	273	1	i	i	PRON
ajst-19160	273	2	i	i	PRON
ajst-19160	274	1	i	i	PRON
ajst-19160	274	2	e	e	VERB
ajst-19160	274	3	y	y	PROPN
ajst-19160	274	4	p	p	PROPN
ajst-19160	275	1	n	n	CCONJ
ajst-19160	275	2			NUM
ajst-19160	275	3			NUM
ajst-19160	276	1			NOUN
ajst-19160	276	2	(	(	PUNCT
ajst-19160	276	3	21	21	NUM
ajst-19160	276	4	)	)	PUNCT
ajst-19160	276	5			NOUN
ajst-19160	276	6			PUNCT
ajst-19160	276	7			NOUN
ajst-19160	276	8			NOUN
ajst-19160	276	9	2	2	NUM
ajst-19160	276	10	2	2	NUM
ajst-19160	276	11	1	1	NUM
ajst-19160	276	12	2	2	NUM
ajst-19160	276	13	1	1	NUM
ajst-19160	276	14	n	n	NUM
ajst-19160	277	1	i	i	PRON
ajst-19160	277	2	i	i	PRON
ajst-19160	277	3	n	n	VERB
ajst-19160	278	1	i	i	PRON
ajst-19160	278	2	i	i	PRON
ajst-19160	279	1	p	p	X
ajst-19160	279	2	y	y	NOUN
ajst-19160	279	3	r	r	NOUN
ajst-19160	279	4	y	y	PROPN
ajst-19160	280	1	y	y	PROPN
ajst-19160	280	2			PROPN
ajst-19160	280	3			PROPN
ajst-19160	280	4			PROPN
ajst-19160	280	5			PROPN
ajst-19160	280	6			PROPN
ajst-19160	280	7			X
ajst-19160	280	8			X
ajst-19160	280	9	(	(	PUNCT
ajst-19160	280	10	22	22	NUM
ajst-19160	280	11	)	)	PUNCT
ajst-19160	280	12	where	where	SCONJ
ajst-19160	280	13	ip	ip	NOUN
ajst-19160	280	14	is	be	AUX
ajst-19160	280	15	the	the	DET
ajst-19160	280	16	prediction	prediction	NOUN
ajst-19160	280	17	result	result	NOUN
ajst-19160	280	18	,	,	PUNCT
ajst-19160	280	19	iy	iy	PROPN
ajst-19160	280	20	is	be	AUX
ajst-19160	280	21	the	the	DET
ajst-19160	280	22	sample	sample	NOUN
ajst-19160	280	23	label	label	NOUN
ajst-19160	280	24	,	,	PUNCT
ajst-19160	280	25	y	y	PROPN
ajst-19160	280	26	is	be	AUX
ajst-19160	280	27	the	the	DET
ajst-19160	280	28	sample	sample	NOUN
ajst-19160	280	29	mean	mean	NOUN
ajst-19160	280	30	value	value	NOUN
ajst-19160	280	31	,	,	PUNCT
ajst-19160	280	32	and	and	CCONJ
ajst-19160	280	33	n	n	PRON
ajst-19160	280	34	is	be	AUX
ajst-19160	280	35	the	the	DET
ajst-19160	280	36	number	number	NOUN
ajst-19160	280	37	of	of	ADP
ajst-19160	280	38	125	125	NUM
ajst-19160	280	39	samples	sample	NOUN
ajst-19160	280	40	.	.	PUNCT
ajst-19160	281	1	the	the	DET
ajst-19160	281	2	hold	hold	VERB
ajst-19160	281	3	-	-	PUNCT
ajst-19160	281	4	on	on	ADP
ajst-19160	281	5	verification	verification	NOUN
ajst-19160	281	6	method	method	NOUN
ajst-19160	281	7	has	have	VERB
ajst-19160	281	8	a	a	DET
ajst-19160	281	9	strong	strong	ADJ
ajst-19160	281	10	correlation	correlation	NOUN
ajst-19160	281	11	with	with	ADP
ajst-19160	281	12	data	datum	NOUN
ajst-19160	281	13	grouping	grouping	NOUN
ajst-19160	281	14	,	,	PUNCT
ajst-19160	281	15	resulting	result	VERB
ajst-19160	281	16	in	in	ADP
ajst-19160	281	17	a	a	DET
ajst-19160	281	18	better	well	ADJ
ajst-19160	281	19	regression	regression	NOUN
ajst-19160	281	20	effect	effect	NOUN
ajst-19160	281	21	.	.	PUNCT
ajst-19160	282	1	however	however	ADV
ajst-19160	282	2	,	,	PUNCT
ajst-19160	282	3	to	to	PART
ajst-19160	282	4	avoid	avoid	VERB
ajst-19160	282	5	incomplete	incomplete	ADJ
ajst-19160	282	6	utilization	utilization	NOUN
ajst-19160	282	7	of	of	ADP
ajst-19160	282	8	data	datum	NOUN
ajst-19160	282	9	information	information	NOUN
ajst-19160	282	10	,	,	PUNCT
ajst-19160	282	11	this	this	DET
ajst-19160	282	12	paper	paper	NOUN
ajst-19160	282	13	uses	use	VERB
ajst-19160	282	14	the	the	DET
ajst-19160	282	15	k	k	ADJ
ajst-19160	282	16	-	-	ADJ
ajst-19160	282	17	fold	fold	ADJ
ajst-19160	282	18	cross	cross	ADJ
ajst-19160	282	19	-	-	ADJ
ajst-19160	282	20	validation	validation	ADJ
ajst-19160	282	21	method	method	NOUN
ajst-19160	282	22	to	to	PART
ajst-19160	282	23	calculate	calculate	VERB
ajst-19160	282	24	the	the	DET
ajst-19160	282	25	mean	mean	ADJ
ajst-19160	282	26	value	value	NOUN
ajst-19160	282	27	of	of	ADP
ajst-19160	282	28	the	the	DET
ajst-19160	282	29	evaluation	evaluation	NOUN
ajst-19160	282	30	index	index	NOUN
ajst-19160	282	31	.	.	PUNCT
ajst-19160	283	1	therefore	therefore	ADV
ajst-19160	283	2	,	,	PUNCT
ajst-19160	283	3	the	the	DET
ajst-19160	283	4	evaluation	evaluation	NOUN
ajst-19160	283	5	formula	formula	NOUN
ajst-19160	283	6	presented	present	VERB
ajst-19160	283	7	above	above	ADV
ajst-19160	283	8	is	be	AUX
ajst-19160	283	9	derived	derive	VERB
ajst-19160	283	10	as	as	ADP
ajst-19160	283	11	equation	equation	NOUN
ajst-19160	283	12	(	(	PUNCT
ajst-19160	283	13	23	23	NUM
ajst-19160	283	14	-	-	SYM
ajst-19160	283	15	25	25	NUM
ajst-19160	283	16	)	)	PUNCT
ajst-19160	283	17	.	.	PUNCT
ajst-19160	284	1	1	1	NUM
ajst-19160	284	2	1	1	NUM
ajst-19160	284	3	1	1	NUM
ajst-19160	284	4	1	1	NUM
ajst-19160	284	5	k	k	NOUN
ajst-19160	284	6	n	n	NUM
ajst-19160	284	7	mae	mae	PROPN
ajst-19160	285	1	i	i	PRON
ajst-19160	285	2	i	i	INTJ
ajst-19160	286	1	j	j	VERB
ajst-19160	287	1	i	i	PRON
ajst-19160	287	2	e	e	VERB
ajst-19160	287	3	y	y	PROPN
ajst-19160	287	4	p	p	X
ajst-19160	287	5	k	k	PROPN
ajst-19160	287	6	n	n	PROPN
ajst-19160	288	1			PROPN
ajst-19160	289	1			ADJ
ajst-19160	289	2			NUM
ajst-19160	289	3			NOUN
ajst-19160	289	4			X
ajst-19160	289	5	(	(	PUNCT
ajst-19160	289	6	23	23	NUM
ajst-19160	289	7	)	)	PUNCT
ajst-19160	289	8			NOUN
ajst-19160	289	9	2	2	ADJ
ajst-19160	289	10	1	1	NUM
ajst-19160	289	11	1	1	NUM
ajst-19160	289	12	1	1	NUM
ajst-19160	289	13	1	1	NUM
ajst-19160	289	14	k	k	NOUN
ajst-19160	289	15	n	n	CCONJ
ajst-19160	289	16	mse	mse	NOUN
ajst-19160	290	1	i	i	PRON
ajst-19160	290	2	i	i	PRON
ajst-19160	291	1	j	j	VERB
ajst-19160	292	1	i	i	PRON
ajst-19160	292	2	e	e	VERB
ajst-19160	292	3	y	y	PROPN
ajst-19160	292	4	p	p	X
ajst-19160	292	5	k	k	PROPN
ajst-19160	292	6	n	n	PROPN
ajst-19160	293	1			PROPN
ajst-19160	294	1			ADJ
ajst-19160	294	2			NUM
ajst-19160	294	3			NOUN
ajst-19160	294	4			X
ajst-19160	294	5	(	(	PUNCT
ajst-19160	294	6	24	24	NUM
ajst-19160	294	7	)	)	PUNCT
ajst-19160	294	8			NOUN
ajst-19160	294	9			PUNCT
ajst-19160	294	10			NOUN
ajst-19160	294	11			NOUN
ajst-19160	294	12	2	2	NUM
ajst-19160	294	13	2	2	NUM
ajst-19160	294	14	1	1	NUM
ajst-19160	294	15	21	21	NUM
ajst-19160	294	16	1	1	NUM
ajst-19160	294	17	1	1	NUM
ajst-19160	294	18	n	n	NUM
ajst-19160	294	19	ik	ik	X
ajst-19160	295	1	i	i	PROPN
ajst-19160	295	2	n	n	CCONJ
ajst-19160	295	3	j	j	NOUN
ajst-19160	296	1	i	i	PRON
ajst-19160	296	2	i	i	PRON
ajst-19160	297	1	p	p	VERB
ajst-19160	297	2	y	y	NOUN
ajst-19160	297	3	r	r	NOUN
ajst-19160	297	4	k	k	PROPN
ajst-19160	298	1	y	y	PROPN
ajst-19160	298	2	y	y	PROPN
ajst-19160	298	3			NUM
ajst-19160	298	4			NUM
ajst-19160	298	5			PROPN
ajst-19160	298	6			NOUN
ajst-19160	298	7			CCONJ
ajst-19160	298	8			PROPN
ajst-19160	298	9			PROPN
ajst-19160	298	10			X
ajst-19160	298	11			X
ajst-19160	298	12			X
ajst-19160	298	13	(	(	PUNCT
ajst-19160	298	14	25	25	NUM
ajst-19160	298	15	)	)	PUNCT
ajst-19160	298	16	where	where	SCONJ
ajst-19160	298	17	j	j	PROPN
ajst-19160	298	18	is	be	AUX
ajst-19160	298	19	the	the	DET
ajst-19160	298	20	k	k	NOUN
ajst-19160	298	21	-	-	NOUN
ajst-19160	298	22	fold	fold	NOUN
ajst-19160	298	23	of	of	ADP
ajst-19160	298	24	j	j	PROPN
ajst-19160	298	25	-fold	-fold	PROPN
ajst-19160	298	26	cross	cross	NOUN
ajst-19160	298	27	-	-	NOUN
ajst-19160	298	28	validation	validation	NOUN
ajst-19160	298	29	.	.	PUNCT
ajst-19160	299	1	5	5	X
ajst-19160	299	2	.	.	X
ajst-19160	299	3	results	result	NOUN
ajst-19160	299	4	and	and	CCONJ
ajst-19160	299	5	numerical	numerical	ADJ
ajst-19160	299	6	analysis	analysis	NOUN
ajst-19160	299	7	5.1	5.1	NUM
ajst-19160	299	8	.	.	PUNCT
ajst-19160	300	1	comparison	comparison	NOUN
ajst-19160	300	2	of	of	ADP
ajst-19160	300	3	various	various	ADJ
ajst-19160	300	4	machine	machine	NOUN
ajst-19160	300	5	learning	learning	NOUN
ajst-19160	300	6	methods	method	NOUN
ajst-19160	300	7	the	the	DET
ajst-19160	300	8	k	k	PROPN
ajst-19160	300	9	value	value	NOUN
ajst-19160	300	10	in	in	ADP
ajst-19160	300	11	k	k	ADJ
ajst-19160	300	12	-	-	ADJ
ajst-19160	300	13	fold	fold	ADJ
ajst-19160	300	14	cross	cross	NOUN
ajst-19160	300	15	-	-	ADJ
ajst-19160	300	16	validation	validation	NOUN
ajst-19160	300	17	is	be	AUX
ajst-19160	300	18	set	set	VERB
ajst-19160	300	19	to	to	ADP
ajst-19160	300	20	9	9	NUM
ajst-19160	300	21	to	to	PART
ajst-19160	300	22	ensure	ensure	VERB
ajst-19160	300	23	a	a	DET
ajst-19160	300	24	more	more	ADV
ajst-19160	300	25	uniform	uniform	ADJ
ajst-19160	300	26	distribution	distribution	NOUN
ajst-19160	300	27	of	of	ADP
ajst-19160	300	28	data	datum	NOUN
ajst-19160	300	29	between	between	ADP
ajst-19160	300	30	the	the	DET
ajst-19160	300	31	test	test	NOUN
ajst-19160	300	32	and	and	CCONJ
ajst-19160	300	33	training	training	NOUN
ajst-19160	300	34	sets	set	NOUN
ajst-19160	300	35	.	.	PUNCT
ajst-19160	301	1	the	the	DET
ajst-19160	301	2	comprehensive	comprehensive	ADJ
ajst-19160	301	3	evaluation	evaluation	NOUN
ajst-19160	301	4	index	index	NOUN
ajst-19160	301	5	in	in	ADP
ajst-19160	301	6	chapter	chapter	NOUN
ajst-19160	301	7	3.2	3.2	NUM
ajst-19160	301	8	is	be	AUX
ajst-19160	301	9	utilized	utilize	VERB
ajst-19160	301	10	to	to	PART
ajst-19160	301	11	assess	assess	VERB
ajst-19160	301	12	the	the	DET
ajst-19160	301	13	performance	performance	NOUN
ajst-19160	301	14	of	of	ADP
ajst-19160	301	15	the	the	DET
ajst-19160	301	16	seven	seven	NUM
ajst-19160	301	17	machine	machine	NOUN
ajst-19160	301	18	learning	learning	NOUN
ajst-19160	301	19	models	model	NOUN
ajst-19160	301	20	.	.	PUNCT
ajst-19160	302	1	a	a	DET
ajst-19160	302	2	smaller	small	ADJ
ajst-19160	302	3	value	value	NOUN
ajst-19160	302	4	of	of	ADP
ajst-19160	302	5	comprehensive	comprehensive	ADJ
ajst-19160	302	6	indicators	indicator	NOUN
ajst-19160	302	7	maee	maee	ADV
ajst-19160	302	8	and	and	CCONJ
ajst-19160	302	9	msee	msee	PROPN
ajst-19160	302	10	indicates	indicate	VERB
ajst-19160	302	11	better	well	ADJ
ajst-19160	302	12	performance	performance	NOUN
ajst-19160	302	13	,	,	PUNCT
ajst-19160	302	14	while	while	SCONJ
ajst-19160	302	15	a	a	DET
ajst-19160	302	16	value	value	NOUN
ajst-19160	302	17	of	of	ADP
ajst-19160	302	18	2r	2r	NUM
ajst-19160	302	19			ADV
ajst-19160	302	20	closer	close	ADJ
ajst-19160	302	21	to	to	ADP
ajst-19160	302	22	1	1	NUM
ajst-19160	302	23	is	be	AUX
ajst-19160	302	24	also	also	ADV
ajst-19160	302	25	desirable	desirable	ADJ
ajst-19160	302	26	.	.	PUNCT
ajst-19160	303	1	notably	notably	ADV
ajst-19160	303	2	,	,	PUNCT
ajst-19160	303	3	the	the	DET
ajst-19160	303	4	2r	2r	NUM
ajst-19160	303	5			ADJ
ajst-19160	303	6	value	value	NOUN
ajst-19160	303	7	of	of	ADP
ajst-19160	303	8	svm	svm	PROPN
ajst-19160	303	9	,	,	PUNCT
ajst-19160	303	10	iaeo	iaeo	NOUN
ajst-19160	303	11	-	-	PUNCT
ajst-19160	303	12	svm	svm	PROPN
ajst-19160	303	13	,	,	PUNCT
ajst-19160	303	14	aeo	aeo	PROPN
ajst-19160	303	15	-	-	PUNCT
ajst-19160	303	16	svm	svm	PROPN
ajst-19160	303	17	,	,	PUNCT
ajst-19160	303	18	and	and	CCONJ
ajst-19160	303	19	ann	ann	PROPN
ajst-19160	303	20	-	-	PUNCT
ajst-19160	303	21	lm	lm	PROPN
ajst-19160	303	22	in	in	ADP
ajst-19160	303	23	the	the	DET
ajst-19160	303	24	seven	seven	NUM
ajst-19160	303	25	machine	machine	NOUN
ajst-19160	303	26	learning	learn	VERB
ajst-19160	303	27	algorithms	algorithm	NOUN
ajst-19160	303	28	exceeds	exceed	VERB
ajst-19160	303	29	0.99	0.99	NUM
ajst-19160	303	30	.	.	PUNCT
ajst-19160	304	1	moreover	moreover	ADV
ajst-19160	304	2	,	,	PUNCT
ajst-19160	304	3	based	base	VERB
ajst-19160	304	4	on	on	ADP
ajst-19160	304	5	the	the	DET
ajst-19160	304	6	maee	maee	NOUN
ajst-19160	304	7	and	and	CCONJ
ajst-19160	304	8	msee	msee	ADJ
ajst-19160	304	9	indicators	indicator	NOUN
ajst-19160	304	10	,	,	PUNCT
ajst-19160	304	11	these	these	DET
ajst-19160	304	12	models	model	NOUN
ajst-19160	304	13	outperform	outperform	VERB
ajst-19160	304	14	elm	elm	PROPN
ajst-19160	304	15	,	,	PUNCT
ajst-19160	304	16	rbf	rbf	PROPN
ajst-19160	304	17	,	,	PUNCT
ajst-19160	304	18	and	and	CCONJ
ajst-19160	304	19	grnn	grnn	NOUN
ajst-19160	304	20	.	.	PUNCT
ajst-19160	305	1	consequently	consequently	ADV
ajst-19160	305	2	,	,	PUNCT
ajst-19160	305	3	the	the	DET
ajst-19160	305	4	following	follow	VERB
ajst-19160	305	5	analysis	analysis	NOUN
ajst-19160	305	6	is	be	AUX
ajst-19160	305	7	focused	focus	VERB
ajst-19160	305	8	on	on	ADP
ajst-19160	305	9	the	the	DET
ajst-19160	305	10	four	four	NUM
ajst-19160	305	11	superior	superior	ADJ
ajst-19160	305	12	models	model	NOUN
ajst-19160	305	13	.	.	PUNCT
ajst-19160	306	1	the	the	DET
ajst-19160	306	2	training	training	NOUN
ajst-19160	306	3	set	set	NOUN
ajst-19160	306	4	(	(	PUNCT
ajst-19160	306	5	see	see	VERB
ajst-19160	306	6	table	table	NOUN
ajst-19160	306	7	5	5	NUM
ajst-19160	306	8	)	)	PUNCT
ajst-19160	306	9	maee	maee	NOUN
ajst-19160	306	10	and	and	CCONJ
ajst-19160	306	11	msee	msee	ADJ
ajst-19160	306	12	values	value	NOUN
ajst-19160	306	13	of	of	ADP
ajst-19160	306	14	the	the	DET
ajst-19160	306	15	ann	ann	PROPN
ajst-19160	306	16	-	-	PUNCT
ajst-19160	306	17	lm	lm	PROPN
ajst-19160	306	18	model	model	NOUN
ajst-19160	306	19	were	be	AUX
ajst-19160	306	20	higher	high	ADJ
ajst-19160	306	21	than	than	ADP
ajst-19160	306	22	those	those	PRON
ajst-19160	306	23	of	of	ADP
ajst-19160	306	24	the	the	DET
ajst-19160	306	25	svm	svm	ADJ
ajst-19160	306	26	model	model	NOUN
ajst-19160	306	27	and	and	CCONJ
ajst-19160	306	28	its	its	PRON
ajst-19160	306	29	derivative	derivative	ADJ
ajst-19160	306	30	models	model	NOUN
ajst-19160	306	31	(	(	PUNCT
ajst-19160	306	32	aeo	aeo	PROPN
ajst-19160	306	33	-	-	PUNCT
ajst-19160	306	34	svm	svm	PROPN
ajst-19160	306	35	,	,	PUNCT
ajst-19160	306	36	iaeo	iaeo	NOUN
ajst-19160	306	37	-	-	PUNCT
ajst-19160	306	38	svm	svm	NOUN
ajst-19160	306	39	)	)	PUNCT
ajst-19160	306	40	.	.	PUNCT
ajst-19160	307	1	this	this	DET
ajst-19160	307	2	finding	finding	NOUN
ajst-19160	307	3	suggests	suggest	VERB
ajst-19160	307	4	that	that	SCONJ
ajst-19160	307	5	the	the	DET
ajst-19160	307	6	ann	ann	PROPN
ajst-19160	307	7	-	-	PUNCT
ajst-19160	307	8	lm	lm	PROPN
ajst-19160	307	9	model	model	NOUN
ajst-19160	307	10	may	may	AUX
ajst-19160	307	11	not	not	PART
ajst-19160	307	12	have	have	AUX
ajst-19160	307	13	fully	fully	ADV
ajst-19160	307	14	learned	learn	VERB
ajst-19160	307	15	the	the	DET
ajst-19160	307	16	experiential	experiential	ADJ
ajst-19160	307	17	knowledge	knowledge	NOUN
ajst-19160	307	18	embedded	embed	VERB
ajst-19160	307	19	in	in	ADP
ajst-19160	307	20	the	the	DET
ajst-19160	307	21	training	training	NOUN
ajst-19160	307	22	data	datum	NOUN
ajst-19160	307	23	,	,	PUNCT
ajst-19160	307	24	resulting	result	VERB
ajst-19160	307	25	in	in	ADP
ajst-19160	307	26	a	a	DET
ajst-19160	307	27	lower	low	ADJ
ajst-19160	307	28	training	training	NOUN
ajst-19160	307	29	efficacy	efficacy	NOUN
ajst-19160	307	30	compared	compare	VERB
ajst-19160	307	31	to	to	ADP
ajst-19160	307	32	svm	svm	VERB
ajst-19160	307	33	and	and	CCONJ
ajst-19160	307	34	its	its	PRON
ajst-19160	307	35	derivatives	derivative	NOUN
ajst-19160	307	36	.	.	PUNCT
ajst-19160	308	1	the	the	DET
ajst-19160	308	2	performance	performance	NOUN
ajst-19160	308	3	of	of	ADP
ajst-19160	308	4	ann	ann	PROPN
ajst-19160	308	5	-	-	PUNCT
ajst-19160	308	6	lm	lm	PROPN
ajst-19160	308	7	in	in	ADP
ajst-19160	308	8	the	the	DET
ajst-19160	308	9	test	test	NOUN
ajst-19160	308	10	set	set	NOUN
ajst-19160	308	11	is	be	AUX
ajst-19160	308	12	similar	similar	ADJ
ajst-19160	308	13	to	to	ADP
ajst-19160	308	14	that	that	PRON
ajst-19160	308	15	of	of	ADP
ajst-19160	308	16	svm	svm	PROPN
ajst-19160	308	17	,	,	PUNCT
ajst-19160	308	18	but	but	CCONJ
ajst-19160	308	19	much	much	ADV
ajst-19160	308	20	lower	low	ADJ
ajst-19160	308	21	than	than	ADP
ajst-19160	308	22	that	that	PRON
ajst-19160	308	23	of	of	ADP
ajst-19160	308	24	svm	svm	ADJ
ajst-19160	308	25	derivative	derivative	ADJ
ajst-19160	308	26	model	model	NOUN
ajst-19160	308	27	,	,	PUNCT
ajst-19160	308	28	which	which	PRON
ajst-19160	308	29	confirms	confirm	VERB
ajst-19160	308	30	its	its	PRON
ajst-19160	308	31	under	under	ADV
ajst-19160	308	32	-	-	PUNCT
ajst-19160	308	33	fitting	fitting	NOUN
ajst-19160	308	34	in	in	ADP
ajst-19160	308	35	the	the	DET
ajst-19160	308	36	training	training	NOUN
ajst-19160	308	37	stage	stage	NOUN
ajst-19160	308	38	.	.	PUNCT
ajst-19160	309	1	table	table	NOUN
ajst-19160	309	2	5	5	NUM
ajst-19160	309	3	presents	present	VERB
ajst-19160	309	4	the	the	DET
ajst-19160	309	5	outcomes	outcome	NOUN
ajst-19160	309	6	of	of	ADP
ajst-19160	309	7	the	the	DET
ajst-19160	309	8	training	training	NOUN
ajst-19160	309	9	set	set	NOUN
ajst-19160	309	10	,	,	PUNCT
ajst-19160	309	11	and	and	CCONJ
ajst-19160	309	12	the	the	DET
ajst-19160	309	13	optimal	optimal	ADJ
ajst-19160	309	14	machine	machine	NOUN
ajst-19160	309	15	learning	learning	NOUN
ajst-19160	309	16	model	model	NOUN
ajst-19160	309	17	is	be	AUX
ajst-19160	309	18	svm	svm	ADJ
ajst-19160	309	19	.	.	PUNCT
ajst-19160	310	1	however	however	ADV
ajst-19160	310	2	,	,	PUNCT
ajst-19160	310	3	it	it	PRON
ajst-19160	310	4	is	be	AUX
ajst-19160	310	5	noteworthy	noteworthy	ADJ
ajst-19160	310	6	that	that	SCONJ
ajst-19160	310	7	the	the	DET
ajst-19160	310	8	penalty	penalty	NOUN
ajst-19160	310	9	factor	factor	NOUN
ajst-19160	310	10	and	and	CCONJ
ajst-19160	310	11	relaxation	relaxation	NOUN
ajst-19160	310	12	factor	factor	NOUN
ajst-19160	310	13	of	of	ADP
ajst-19160	310	14	svm	svm	PROPN
ajst-19160	310	15	are	be	AUX
ajst-19160	310	16	artificially	artificially	ADV
ajst-19160	310	17	designated	designate	VERB
ajst-19160	310	18	,	,	PUNCT
ajst-19160	310	19	thereby	thereby	ADV
ajst-19160	310	20	resulting	result	VERB
ajst-19160	310	21	in	in	ADP
ajst-19160	310	22	an	an	DET
ajst-19160	310	23	over	over	ADV
ajst-19160	310	24	-	-	PUNCT
ajst-19160	310	25	fitting	fit	VERB
ajst-19160	310	26	state	state	NOUN
ajst-19160	310	27	that	that	PRON
ajst-19160	310	28	undermines	undermine	VERB
ajst-19160	310	29	the	the	DET
ajst-19160	310	30	accuracy	accuracy	NOUN
ajst-19160	310	31	of	of	ADP
ajst-19160	310	32	machine	machine	NOUN
ajst-19160	310	33	learning	learning	NOUN
ajst-19160	310	34	.	.	PUNCT
ajst-19160	311	1	by	by	ADP
ajst-19160	311	2	comparing	compare	VERB
ajst-19160	311	3	the	the	DET
ajst-19160	311	4	results	result	NOUN
ajst-19160	311	5	of	of	ADP
ajst-19160	311	6	the	the	DET
ajst-19160	311	7	training	training	NOUN
ajst-19160	311	8	set	set	NOUN
ajst-19160	311	9	and	and	CCONJ
ajst-19160	311	10	test	test	NOUN
ajst-19160	311	11	set	set	NOUN
ajst-19160	311	12	of	of	ADP
ajst-19160	311	13	svm	svm	PROPN
ajst-19160	311	14	,	,	PUNCT
ajst-19160	311	15	we	we	PRON
ajst-19160	311	16	observe	observe	VERB
ajst-19160	311	17	a	a	DET
ajst-19160	311	18	decline	decline	NOUN
ajst-19160	311	19	in	in	ADP
ajst-19160	311	20	the	the	DET
ajst-19160	311	21	average	average	ADJ
ajst-19160	311	22	coefficient	coefficient	NOUN
ajst-19160	311	23	of	of	ADP
ajst-19160	311	24	determination	determination	NOUN
ajst-19160	311	25	2r	2r	NUM
ajst-19160	311	26			ADV
ajst-19160	311	27	from	from	ADP
ajst-19160	311	28	0.9997	0.9997	NUM
ajst-19160	311	29	to	to	ADP
ajst-19160	311	30	0.9961	0.9961	NUM
ajst-19160	311	31	.	.	PUNCT
ajst-19160	312	1	the	the	DET
ajst-19160	312	2	aeo	aeo	PROPN
ajst-19160	312	3	-	-	PUNCT
ajst-19160	312	4	svm	svm	PROPN
ajst-19160	312	5	model	model	NOUN
ajst-19160	312	6	mitigates	mitigate	VERB
ajst-19160	312	7	the	the	DET
ajst-19160	312	8	occurrence	occurrence	NOUN
ajst-19160	312	9	of	of	ADP
ajst-19160	312	10	the	the	DET
ajst-19160	312	11	over	over	ADV
ajst-19160	312	12	-	-	PUNCT
ajst-19160	312	13	fitting	fit	VERB
ajst-19160	312	14	state	state	NOUN
ajst-19160	312	15	to	to	ADP
ajst-19160	312	16	a	a	DET
ajst-19160	312	17	certain	certain	ADJ
ajst-19160	312	18	extent	extent	NOUN
ajst-19160	312	19	,	,	PUNCT
ajst-19160	312	20	leading	lead	VERB
ajst-19160	312	21	to	to	ADP
ajst-19160	312	22	an	an	DET
ajst-19160	312	23	increase	increase	NOUN
ajst-19160	312	24	in	in	ADP
ajst-19160	312	25	the	the	DET
ajst-19160	312	26	2r	2r	NUM
ajst-19160	312	27			ADJ
ajst-19160	312	28	value	value	NOUN
ajst-19160	312	29	of	of	ADP
ajst-19160	312	30	the	the	DET
ajst-19160	312	31	test	test	NOUN
ajst-19160	312	32	set	set	VERB
ajst-19160	312	33	to	to	ADP
ajst-19160	312	34	0.9980	0.9980	NUM
ajst-19160	312	35	.	.	PUNCT
ajst-19160	313	1	nevertheless	nevertheless	ADV
ajst-19160	313	2	,	,	PUNCT
ajst-19160	313	3	this	this	DET
ajst-19160	313	4	improvement	improvement	NOUN
ajst-19160	313	5	comes	come	VERB
ajst-19160	313	6	at	at	ADP
ajst-19160	313	7	the	the	DET
ajst-19160	313	8	cost	cost	NOUN
ajst-19160	313	9	of	of	ADP
ajst-19160	313	10	an	an	DET
ajst-19160	313	11	increase	increase	NOUN
ajst-19160	313	12	in	in	ADP
ajst-19160	313	13	the	the	DET
ajst-19160	313	14	maee	maee	NOUN
ajst-19160	313	15	and	and	CCONJ
ajst-19160	313	16	msee	msee	ADJ
ajst-19160	313	17	values	value	NOUN
ajst-19160	313	18	of	of	ADP
ajst-19160	313	19	the	the	DET
ajst-19160	313	20	training	training	NOUN
ajst-19160	313	21	set	set	NOUN
ajst-19160	313	22	and	and	CCONJ
ajst-19160	313	23	a	a	DET
ajst-19160	313	24	decrease	decrease	NOUN
ajst-19160	313	25	in	in	ADP
ajst-19160	313	26	the	the	DET
ajst-19160	313	27	2r	2r	NUM
ajst-19160	313	28			ADJ
ajst-19160	313	29	value	value	NOUN
ajst-19160	313	30	,	,	PUNCT
ajst-19160	313	31	resulting	result	VERB
ajst-19160	313	32	in	in	ADP
ajst-19160	313	33	an	an	DET
ajst-19160	313	34	under	under	ADV
ajst-19160	313	35	-	-	PUNCT
ajst-19160	313	36	fitting	fit	VERB
ajst-19160	313	37	state	state	NOUN
ajst-19160	313	38	.	.	PUNCT
ajst-19160	314	1	as	as	SCONJ
ajst-19160	314	2	chapter	chapter	NOUN
ajst-19160	314	3	2	2	NUM
ajst-19160	314	4	illustrates	illustrate	VERB
ajst-19160	314	5	,	,	PUNCT
ajst-19160	314	6	this	this	DET
ajst-19160	314	7	issue	issue	NOUN
ajst-19160	314	8	stems	stem	VERB
ajst-19160	314	9	from	from	ADP
ajst-19160	314	10	the	the	DET
ajst-19160	314	11	aeo	aeo	PROPN
ajst-19160	314	12	algorithm	algorithm	NOUN
ajst-19160	314	13	falling	fall	VERB
ajst-19160	314	14	into	into	ADP
ajst-19160	314	15	a	a	DET
ajst-19160	314	16	local	local	ADJ
ajst-19160	314	17	optimum	optimum	NOUN
ajst-19160	314	18	.	.	PUNCT
ajst-19160	315	1	conversely	conversely	ADV
ajst-19160	315	2	,	,	PUNCT
ajst-19160	315	3	the	the	DET
ajst-19160	315	4	comprehensive	comprehensive	ADJ
ajst-19160	315	5	evaluation	evaluation	NOUN
ajst-19160	315	6	index	index	NOUN
ajst-19160	315	7	maee	maee	NOUN
ajst-19160	315	8	and	and	CCONJ
ajst-19160	315	9	msee	msee	ADJ
ajst-19160	315	10	values	value	NOUN
ajst-19160	315	11	of	of	ADP
ajst-19160	315	12	the	the	DET
ajst-19160	315	13	iaeo	iaeo	NOUN
ajst-19160	315	14	-	-	PUNCT
ajst-19160	315	15	svm	svm	ADJ
ajst-19160	315	16	model	model	NOUN
ajst-19160	315	17	in	in	ADP
ajst-19160	315	18	the	the	DET
ajst-19160	315	19	training	training	NOUN
ajst-19160	315	20	set	set	NOUN
ajst-19160	315	21	are	be	AUX
ajst-19160	315	22	lower	low	ADJ
ajst-19160	315	23	than	than	ADP
ajst-19160	315	24	aeo	aeo	PROPN
ajst-19160	315	25	-	-	PUNCT
ajst-19160	315	26	svm	svm	PROPN
ajst-19160	315	27	,	,	PUNCT
ajst-19160	315	28	while	while	SCONJ
ajst-19160	315	29	the	the	DET
ajst-19160	315	30	2r	2r	NUM
ajst-19160	315	31			ADJ
ajst-19160	315	32	value	value	NOUN
ajst-19160	315	33	of	of	ADP
ajst-19160	315	34	iaeo	iaeo	NOUN
ajst-19160	315	35	-	-	PUNCT
ajst-19160	315	36	svm	svm	ADJ
ajst-19160	315	37	model	model	NOUN
ajst-19160	315	38	is	be	AUX
ajst-19160	315	39	better	well	ADJ
ajst-19160	315	40	than	than	ADP
ajst-19160	315	41	aeo	aeo	PROPN
ajst-19160	315	42	-	-	PUNCT
ajst-19160	315	43	svm	svm	PROPN
ajst-19160	315	44	.	.	PUNCT
ajst-19160	316	1	these	these	DET
ajst-19160	316	2	results	result	NOUN
ajst-19160	316	3	suggest	suggest	VERB
ajst-19160	316	4	that	that	SCONJ
ajst-19160	316	5	the	the	DET
ajst-19160	316	6	iaeo	iaeo	NOUN
ajst-19160	316	7	-	-	PUNCT
ajst-19160	316	8	svm	svm	ADJ
ajst-19160	316	9	model	model	NOUN
ajst-19160	316	10	identifies	identify	VERB
ajst-19160	316	11	better	well	ADJ
ajst-19160	316	12	support	support	NOUN
ajst-19160	316	13	vectors	vector	NOUN
ajst-19160	316	14	during	during	ADP
ajst-19160	316	15	the	the	DET
ajst-19160	316	16	training	training	NOUN
ajst-19160	316	17	process	process	NOUN
ajst-19160	316	18	and	and	CCONJ
ajst-19160	316	19	acquires	acquire	VERB
ajst-19160	316	20	more	more	ADJ
ajst-19160	316	21	experiential	experiential	ADJ
ajst-19160	316	22	knowledge	knowledge	NOUN
ajst-19160	316	23	.	.	PUNCT
ajst-19160	317	1	table	table	NOUN
ajst-19160	317	2	6	6	NUM
ajst-19160	317	3	displays	display	VERB
ajst-19160	317	4	the	the	DET
ajst-19160	317	5	outcomes	outcome	NOUN
ajst-19160	317	6	of	of	ADP
ajst-19160	317	7	the	the	DET
ajst-19160	317	8	test	test	NOUN
ajst-19160	317	9	set	set	NOUN
ajst-19160	317	10	,	,	PUNCT
ajst-19160	317	11	which	which	PRON
ajst-19160	317	12	depict	depict	VERB
ajst-19160	317	13	lower	low	ADJ
ajst-19160	317	14	comprehensive	comprehensive	ADJ
ajst-19160	317	15	evaluation	evaluation	NOUN
ajst-19160	317	16	indicator	indicator	NOUN
ajst-19160	317	17	maee	maee	PROPN
ajst-19160	317	18	and	and	CCONJ
ajst-19160	317	19	msee	msee	ADJ
ajst-19160	317	20	values	value	NOUN
ajst-19160	317	21	for	for	ADP
ajst-19160	317	22	the	the	DET
ajst-19160	317	23	iaeo	iaeo	NOUN
ajst-19160	317	24	-	-	PUNCT
ajst-19160	317	25	svm	svm	ADJ
ajst-19160	317	26	model	model	NOUN
ajst-19160	317	27	relative	relative	ADJ
ajst-19160	317	28	to	to	ADP
ajst-19160	317	29	aeo	aeo	PROPN
ajst-19160	317	30	-	-	PUNCT
ajst-19160	317	31	svm	svm	PROPN
ajst-19160	317	32	,	,	PUNCT
ajst-19160	317	33	while	while	SCONJ
ajst-19160	317	34	the	the	DET
ajst-19160	317	35	2r	2r	NUM
ajst-19160	317	36			ADJ
ajst-19160	317	37	value	value	NOUN
ajst-19160	317	38	of	of	ADP
ajst-19160	317	39	iaeo	iaeo	NOUN
ajst-19160	317	40	-	-	PUNCT
ajst-19160	317	41	svm	svm	ADJ
ajst-19160	317	42	model	model	NOUN
ajst-19160	317	43	exceeds	exceed	VERB
ajst-19160	317	44	that	that	PRON
ajst-19160	317	45	of	of	ADP
ajst-19160	317	46	aeo	aeo	PROPN
ajst-19160	317	47	-	-	PUNCT
ajst-19160	317	48	svm	svm	PROPN
ajst-19160	317	49	.	.	PUNCT
ajst-19160	318	1	these	these	DET
ajst-19160	318	2	findings	finding	NOUN
ajst-19160	318	3	indicate	indicate	VERB
ajst-19160	318	4	that	that	SCONJ
ajst-19160	318	5	the	the	DET
ajst-19160	318	6	iaeo	iaeo	NOUN
ajst-19160	318	7	-	-	PUNCT
ajst-19160	318	8	svm	svm	PROPN
ajst-19160	318	9	model	model	NOUN
ajst-19160	318	10	exhibits	exhibit	VERB
ajst-19160	318	11	superior	superior	ADJ
ajst-19160	318	12	robustness	robustness	NOUN
ajst-19160	318	13	compared	compare	VERB
ajst-19160	318	14	to	to	ADP
ajst-19160	318	15	aeo	aeo	PROPN
ajst-19160	318	16	-	-	PUNCT
ajst-19160	318	17	svm	svm	PROPN
ajst-19160	318	18	,	,	PUNCT
ajst-19160	318	19	and	and	CCONJ
ajst-19160	318	20	can	can	AUX
ajst-19160	318	21	effectively	effectively	ADV
ajst-19160	318	22	mitigate	mitigate	VERB
ajst-19160	318	23	the	the	DET
ajst-19160	318	24	over	over	ADV
ajst-19160	318	25	-	-	PUNCT
ajst-19160	318	26	fitting	fitting	NOUN
ajst-19160	318	27	caused	cause	VERB
ajst-19160	318	28	by	by	ADP
ajst-19160	318	29	the	the	DET
ajst-19160	318	30	artificial	artificial	ADJ
ajst-19160	318	31	setting	setting	NOUN
ajst-19160	318	32	of	of	ADP
ajst-19160	318	33	the	the	DET
ajst-19160	318	34	svm	svm	ADJ
ajst-19160	318	35	model	model	NOUN
ajst-19160	318	36	and	and	CCONJ
ajst-19160	318	37	the	the	DET
ajst-19160	318	38	under	under	ADV
ajst-19160	318	39	-	-	PUNCT
ajst-19160	318	40	fitting	fit	VERB
ajst-19160	318	41	resulting	result	VERB
ajst-19160	318	42	from	from	ADP
ajst-19160	318	43	the	the	DET
ajst-19160	318	44	local	local	ADJ
ajst-19160	318	45	optimum	optimum	NOUN
ajst-19160	318	46	of	of	ADP
ajst-19160	318	47	the	the	DET
ajst-19160	318	48	aeo	aeo	PROPN
ajst-19160	318	49	-	-	PUNCT
ajst-19160	318	50	svm	svm	PROPN
ajst-19160	318	51	model	model	NOUN
ajst-19160	318	52	.	.	PUNCT
ajst-19160	318	53	table	table	NOUN
ajst-19160	318	54	5	5	NUM
ajst-19160	318	55	.	.	PUNCT
ajst-19160	319	1	k	k	ADJ
ajst-19160	319	2	-	-	ADJ
ajst-19160	319	3	fold	fold	ADJ
ajst-19160	319	4	cross	cross	NOUN
ajst-19160	319	5	validation	validation	NOUN
ajst-19160	319	6	of	of	ADP
ajst-19160	319	7	training	training	NOUN
ajst-19160	319	8	set	set	VERB
ajst-19160	319	9	evaluation	evaluation	NOUN
ajst-19160	319	10	index	index	NOUN
ajst-19160	319	11	training	training	NOUN
ajst-19160	319	12	ann	ann	PROPN
ajst-19160	319	13	-	-	PUNCT
ajst-19160	319	14	lm	lm	PROPN
ajst-19160	319	15	elm	elm	PROPN
ajst-19160	319	16	rbf	rbf	PROPN
ajst-19160	319	17	grnn	grnn	PROPN
ajst-19160	319	18	svm	svm	PROPN
ajst-19160	319	19	aeo	aeo	PROPN
ajst-19160	319	20	-	-	PUNCT
ajst-19160	319	21	svm	svm	PROPN
ajst-19160	319	22	iaeo	iaeo	NOUN
ajst-19160	319	23	-	-	PUNCT
ajst-19160	319	24	svm	svm	NOUN
ajst-19160	319	25	maee	maee	NOUN
ajst-19160	319	26	0.1727	0.1727	NUM
ajst-19160	319	27	0.0837	0.0837	NUM
ajst-19160	319	28	1.71554	1.71554	NUM
ajst-19160	319	29	2.2922	2.2922	NUM
ajst-19160	319	30	1.2993	1.2993	NUM
ajst-19160	319	31	0.0837	0.0837	NUM
ajst-19160	319	32	0.0835	0.0835	NUM
ajst-19160	319	33	msee	msee	PROPN
ajst-19160	319	34	0.0641	0.0641	NUM
ajst-19160	319	35	3.0193	3.0193	NUM
ajst-19160	319	36	4.2836	4.2836	NUM
ajst-19160	319	37	7.7402	7.7402	NUM
ajst-19160	319	38	0.0088	0.0088	NUM
ajst-19160	319	39	0.0138	0.0138	NUM
ajst-19160	319	40	0.0135	0.0135	NUM
ajst-19160	319	41	2r	2r	NUM
ajst-19160	319	42			CCONJ
ajst-19160	319	43	0.9978	0.9978	NUM
ajst-19160	319	44	0.9005	0.9005	NUM
ajst-19160	319	45	0.8584	0.8584	NUM
ajst-19160	319	46	0.7442	0.7442	NUM
ajst-19160	319	47	0.9997	0.9997	NUM
ajst-19160	319	48	0.9995	0.9995	NUM
ajst-19160	319	49	0.9996	0.9996	NUM
ajst-19160	319	50	table	table	NOUN
ajst-19160	319	51	6	6	NUM
ajst-19160	319	52	.	.	PUNCT
ajst-19160	320	1	k	k	ADJ
ajst-19160	320	2	-	-	ADJ
ajst-19160	320	3	fold	fold	ADJ
ajst-19160	320	4	cross	cross	NOUN
ajst-19160	320	5	validation	validation	NOUN
ajst-19160	320	6	test	test	NOUN
ajst-19160	320	7	set	set	VERB
ajst-19160	320	8	evaluation	evaluation	NOUN
ajst-19160	320	9	index	index	NOUN
ajst-19160	320	10	testing	testing	NOUN
ajst-19160	320	11	ann	ann	PROPN
ajst-19160	320	12	-	-	PUNCT
ajst-19160	320	13	lm	lm	PROPN
ajst-19160	320	14	elm	elm	PROPN
ajst-19160	320	15	rbf	rbf	PROPN
ajst-19160	320	16	grnn	grnn	PROPN
ajst-19160	320	17	svm	svm	PROPN
ajst-19160	320	18	aeo	aeo	PROPN
ajst-19160	320	19	-	-	PUNCT
ajst-19160	320	20	svm	svm	PROPN
ajst-19160	320	21	iaeosvm	iaeosvm	NOUN
ajst-19160	320	22	maee	maee	PROPN
ajst-19160	320	23	0.2088	0.2088	NUM
ajst-19160	320	24	0.1886	0.1886	NUM
ajst-19160	320	25	1.7408	1.7408	NUM
ajst-19160	320	26	2.3811	2.3811	NUM
ajst-19160	320	27	1.3378	1.3378	NUM
ajst-19160	320	28	0.1343	0.1343	NUM
ajst-19160	320	29	0.1295	0.1295	NUM
ajst-19160	320	30	msee	msee	NOUN
ajst-19160	320	31	0.1010	0.1010	NUM
ajst-19160	321	1	3.2047	3.2047	NUM
ajst-19160	321	2	4.4492	4.4492	NUM
ajst-19160	321	3	8.4077	8.4077	NUM
ajst-19160	321	4	0.1043	0.1043	NUM
ajst-19160	321	5	0.0520	0.0520	NUM
ajst-19160	321	6	0.0482	0.0482	NUM
ajst-19160	321	7	2r	2r	NUM
ajst-19160	322	1			ADJ
ajst-19160	322	2	0.9961	0.9961	NUM
ajst-19160	322	3	0.8823	0.8823	NUM
ajst-19160	322	4	0.8389	0.8389	NUM
ajst-19160	322	5	0.7034	0.7034	NUM
ajst-19160	322	6	0.9961	0.9961	NUM
ajst-19160	322	7	0.9980	0.9980	NUM
ajst-19160	322	8	0.9982	0.9982	NUM
ajst-19160	322	9	based	base	VERB
ajst-19160	322	10	on	on	ADP
ajst-19160	322	11	statistical	statistical	ADJ
ajst-19160	322	12	indicators	indicator	NOUN
ajst-19160	322	13	,	,	PUNCT
ajst-19160	322	14	it	it	PRON
ajst-19160	322	15	is	be	AUX
ajst-19160	322	16	evident	evident	ADJ
ajst-19160	322	17	that	that	SCONJ
ajst-19160	322	18	among	among	ADP
ajst-19160	322	19	the	the	DET
ajst-19160	322	20	aforementioned	aforementioned	ADJ
ajst-19160	322	21	machine	machine	NOUN
ajst-19160	322	22	learning	learning	NOUN
ajst-19160	322	23	models	model	NOUN
ajst-19160	322	24	,	,	PUNCT
ajst-19160	322	25	the	the	DET
ajst-19160	322	26	iaeo	iaeo	NOUN
ajst-19160	322	27	-	-	PUNCT
ajst-19160	322	28	svm	svm	PROPN
ajst-19160	322	29	,	,	PUNCT
ajst-19160	322	30	svm	svm	ADJ
ajst-19160	322	31	,	,	PUNCT
ajst-19160	322	32	and	and	CCONJ
ajst-19160	322	33	ann	ann	PROPN
ajst-19160	322	34	-	-	PUNCT
ajst-19160	322	35	lm	lm	PROPN
ajst-19160	322	36	models	model	NOUN
ajst-19160	322	37	exhibit	exhibit	VERB
ajst-19160	322	38	superior	superior	ADJ
ajst-19160	322	39	performance	performance	NOUN
ajst-19160	322	40	.	.	PUNCT
ajst-19160	323	1	to	to	PART
ajst-19160	323	2	gain	gain	VERB
ajst-19160	323	3	a	a	DET
ajst-19160	323	4	more	more	ADV
ajst-19160	323	5	intuitive	intuitive	ADJ
ajst-19160	323	6	understanding	understanding	NOUN
ajst-19160	323	7	of	of	ADP
ajst-19160	323	8	the	the	DET
ajst-19160	323	9	error	error	NOUN
ajst-19160	323	10	distribution	distribution	NOUN
ajst-19160	323	11	of	of	ADP
ajst-19160	323	12	these	these	DET
ajst-19160	323	13	three	three	NUM
ajst-19160	323	14	models	model	NOUN
ajst-19160	323	15	,	,	PUNCT
ajst-19160	323	16	the	the	DET
ajst-19160	323	17	true	true	ADJ
ajst-19160	323	18	values	value	NOUN
ajst-19160	323	19	of	of	ADP
ajst-19160	323	20	the	the	DET
ajst-19160	323	21	nine	nine	NUM
ajst-19160	323	22	test	test	NOUN
ajst-19160	323	23	sets	set	NOUN
ajst-19160	323	24	are	be	AUX
ajst-19160	323	25	subjected	subject	VERB
ajst-19160	323	26	to	to	PART
ajst-19160	323	27	linear	linear	VERB
ajst-19160	323	28	regression	regression	NOUN
ajst-19160	323	29	analysis	analysis	NOUN
ajst-19160	323	30	with	with	ADP
ajst-19160	323	31	the	the	DET
ajst-19160	323	32	predicted	predict	VERB
ajst-19160	323	33	126	126	NUM
ajst-19160	323	34	values	value	NOUN
ajst-19160	323	35	of	of	ADP
ajst-19160	323	36	the	the	DET
ajst-19160	323	37	models	model	NOUN
ajst-19160	323	38	.	.	PUNCT
ajst-19160	324	1	notably	notably	ADV
ajst-19160	324	2	,	,	PUNCT
ajst-19160	324	3	the	the	DET
ajst-19160	324	4	application	application	NOUN
ajst-19160	324	5	of	of	ADP
ajst-19160	324	6	the	the	DET
ajst-19160	324	7	iaeo	iaeo	NOUN
ajst-19160	324	8	algorithm	algorithm	NOUN
ajst-19160	324	9	has	have	AUX
ajst-19160	324	10	optimized	optimize	VERB
ajst-19160	324	11	the	the	DET
ajst-19160	324	12	goodness	goodness	NOUN
ajst-19160	324	13	of	of	ADP
ajst-19160	324	14	fit	fit	ADJ
ajst-19160	324	15	2r	2r	NUM
ajst-19160	324	16	of	of	ADP
ajst-19160	324	17	the	the	DET
ajst-19160	324	18	svm	svm	ADJ
ajst-19160	324	19	model	model	NOUN
ajst-19160	324	20	,	,	PUNCT
ajst-19160	324	21	increasing	increase	VERB
ajst-19160	324	22	it	it	PRON
ajst-19160	324	23	from	from	ADP
ajst-19160	324	24	0.9969	0.9969	NUM
ajst-19160	324	25	to	to	ADP
ajst-19160	324	26	0.9984	0.9984	NUM
ajst-19160	324	27	(	(	PUNCT
ajst-19160	324	28	see	see	VERB
ajst-19160	324	29	fig	fig	NOUN
ajst-19160	324	30	.	.	PUNCT
ajst-19160	325	1	10(a	10(a	NUM
ajst-19160	325	2	)	)	PUNCT
ajst-19160	325	3	,	,	PUNCT
ajst-19160	325	4	(	(	PUNCT
ajst-19160	325	5	c	c	NOUN
ajst-19160	325	6	)	)	PUNCT
ajst-19160	325	7	)	)	PUNCT
ajst-19160	325	8	,	,	PUNCT
ajst-19160	325	9	thereby	thereby	ADV
ajst-19160	325	10	enhancing	enhance	VERB
ajst-19160	325	11	its	its	PRON
ajst-19160	325	12	accuracy	accuracy	NOUN
ajst-19160	325	13	.	.	PUNCT
ajst-19160	326	1	the	the	DET
ajst-19160	326	2	residual	residual	ADJ
ajst-19160	326	3	analysis	analysis	NOUN
ajst-19160	326	4	of	of	ADP
ajst-19160	326	5	test	test	NOUN
ajst-19160	326	6	set	set	VERB
ajst-19160	326	7	1	1	NUM
ajst-19160	326	8	reveals	reveal	VERB
ajst-19160	326	9	that	that	SCONJ
ajst-19160	326	10	the	the	DET
ajst-19160	326	11	errors	error	NOUN
ajst-19160	326	12	of	of	ADP
ajst-19160	326	13	the	the	DET
ajst-19160	326	14	three	three	NUM
ajst-19160	326	15	models	model	NOUN
ajst-19160	326	16	conform	conform	VERB
ajst-19160	326	17	to	to	ADP
ajst-19160	326	18	the	the	DET
ajst-19160	326	19	normal	normal	ADJ
ajst-19160	326	20	distribution	distribution	NOUN
ajst-19160	326	21	.	.	PUNCT
ajst-19160	327	1	specifically	specifically	ADV
ajst-19160	327	2	,	,	PUNCT
ajst-19160	327	3	the	the	DET
ajst-19160	327	4	iaeo	iaeo	NOUN
ajst-19160	327	5	-	-	PUNCT
ajst-19160	327	6	svm	svm	PROPN
ajst-19160	327	7	model	model	NOUN
ajst-19160	327	8	exhibits	exhibit	VERB
ajst-19160	327	9	a	a	DET
ajst-19160	327	10	mean	mean	ADJ
ajst-19160	327	11	residual	residual	ADJ
ajst-19160	327	12	error	error	NOUN
ajst-19160	327	13	of	of	ADP
ajst-19160	327	14	-0.0081	-0.0081	NOUN
ajst-19160	327	15	mpa	mpa	PROPN
ajst-19160	327	16	in	in	ADP
ajst-19160	327	17	fig	fig	NOUN
ajst-19160	327	18	.	.	PUNCT
ajst-19160	328	1	10	10	NUM
ajst-19160	328	2	(	(	PUNCT
ajst-19160	328	3	a	a	NOUN
ajst-19160	328	4	)	)	PUNCT
ajst-19160	328	5	,	,	PUNCT
ajst-19160	328	6	which	which	PRON
ajst-19160	328	7	is	be	AUX
ajst-19160	328	8	an	an	DET
ajst-19160	328	9	order	order	NOUN
ajst-19160	328	10	of	of	ADP
ajst-19160	328	11	magnitude	magnitude	NOUN
ajst-19160	328	12	greater	great	ADJ
ajst-19160	328	13	than	than	ADP
ajst-19160	328	14	the	the	DET
ajst-19160	328	15	accuracy	accuracy	NOUN
ajst-19160	328	16	of	of	ADP
ajst-19160	328	17	the	the	DET
ajst-19160	328	18	svm	svm	ADJ
ajst-19160	328	19	model	model	NOUN
ajst-19160	328	20	.	.	PUNCT
ajst-19160	329	1	analysis	analysis	NOUN
ajst-19160	329	2	of	of	ADP
ajst-19160	329	3	variance	variance	NOUN
ajst-19160	329	4	(	(	PUNCT
ajst-19160	329	5	sd	sd	NOUN
ajst-19160	329	6	)	)	PUNCT
ajst-19160	329	7	indicates	indicate	VERB
ajst-19160	329	8	that	that	SCONJ
ajst-19160	329	9	only	only	ADV
ajst-19160	329	10	the	the	DET
ajst-19160	329	11	variance	variance	NOUN
ajst-19160	329	12	of	of	ADP
ajst-19160	329	13	the	the	DET
ajst-19160	329	14	iaeo	iaeo	NOUN
ajst-19160	329	15	-	-	PUNCT
ajst-19160	329	16	svm	svm	ADJ
ajst-19160	329	17	model	model	NOUN
ajst-19160	329	18	is	be	AUX
ajst-19160	329	19	less	less	ADJ
ajst-19160	329	20	than	than	ADP
ajst-19160	329	21	0.3	0.3	NUM
ajst-19160	329	22	in	in	ADP
ajst-19160	329	23	fig	fig	NOUN
ajst-19160	329	24	.	.	PUNCT
ajst-19160	330	1	11	11	NUM
ajst-19160	330	2	(	(	PUNCT
ajst-19160	330	3	a	a	NOUN
ajst-19160	330	4	)	)	PUNCT
ajst-19160	330	5	,	,	PUNCT
ajst-19160	330	6	while	while	SCONJ
ajst-19160	330	7	the	the	DET
ajst-19160	330	8	other	other	ADJ
ajst-19160	330	9	models	model	NOUN
ajst-19160	330	10	exceed	exceed	VERB
ajst-19160	330	11	0.3	0.3	NUM
ajst-19160	330	12	,	,	PUNCT
ajst-19160	330	13	underscoring	underscore	VERB
ajst-19160	330	14	the	the	DET
ajst-19160	330	15	superior	superior	ADJ
ajst-19160	330	16	robustness	robustness	NOUN
ajst-19160	330	17	of	of	ADP
ajst-19160	330	18	the	the	DET
ajst-19160	330	19	iaeo	iaeo	NOUN
ajst-19160	330	20	-	-	PUNCT
ajst-19160	330	21	svm	svm	PROPN
ajst-19160	330	22	model	model	NOUN
ajst-19160	330	23	.	.	PUNCT
ajst-19160	331	1	figure	figure	NOUN
ajst-19160	331	2	9	9	NUM
ajst-19160	331	3	.	.	PUNCT
ajst-19160	332	1	goodness	goodness	NOUN
ajst-19160	332	2	of	of	ADP
ajst-19160	332	3	fit	fit	NOUN
ajst-19160	332	4	of	of	ADP
ajst-19160	332	5	iaeo	iaeo	NOUN
ajst-19160	332	6	-	-	PUNCT
ajst-19160	332	7	svm	svm	PROPN
ajst-19160	332	8	(	(	PUNCT
ajst-19160	332	9	a	a	NOUN
ajst-19160	332	10	)	)	PUNCT
ajst-19160	332	11	,	,	PUNCT
ajst-19160	332	12	ann	ann	PROPN
ajst-19160	332	13	-	-	PUNCT
ajst-19160	332	14	lm	lm	PROPN
ajst-19160	332	15	(	(	PUNCT
ajst-19160	332	16	b	b	NOUN
ajst-19160	332	17	)	)	PUNCT
ajst-19160	332	18	and	and	CCONJ
ajst-19160	332	19	svm	svm	ADJ
ajst-19160	332	20	(	(	PUNCT
ajst-19160	332	21	c	c	NOUN
ajst-19160	332	22	)	)	PUNCT
ajst-19160	332	23	models	model	NOUN
ajst-19160	332	24	.	.	PUNCT
ajst-19160	333	1	figure	figure	NOUN
ajst-19160	333	2	10	10	NUM
ajst-19160	333	3	.	.	PUNCT
ajst-19160	334	1	residual	residual	ADJ
ajst-19160	334	2	and	and	CCONJ
ajst-19160	334	3	variance	variance	NOUN
ajst-19160	334	4	plots	plot	NOUN
ajst-19160	334	5	of	of	ADP
ajst-19160	334	6	iaeo	iaeo	NOUN
ajst-19160	334	7	-	-	PUNCT
ajst-19160	334	8	svm	svm	PROPN
ajst-19160	334	9	(	(	PUNCT
ajst-19160	334	10	a	a	NOUN
ajst-19160	334	11	)	)	PUNCT
ajst-19160	334	12	,	,	PUNCT
ajst-19160	334	13	ann	ann	PROPN
ajst-19160	334	14	-	-	PUNCT
ajst-19160	334	15	lm	lm	PROPN
ajst-19160	334	16	(	(	PUNCT
ajst-19160	334	17	b	b	NOUN
ajst-19160	334	18	)	)	PUNCT
ajst-19160	334	19	and	and	CCONJ
ajst-19160	334	20	svm	svm	ADJ
ajst-19160	334	21	(	(	PUNCT
ajst-19160	334	22	c	c	NOUN
ajst-19160	334	23	)	)	PUNCT
ajst-19160	334	24	models	model	NOUN
ajst-19160	334	25	.	.	PUNCT
ajst-19160	335	1	5.2	5.2	NUM
ajst-19160	335	2	.	.	PUNCT
ajst-19160	335	3	mathematical	mathematical	ADJ
ajst-19160	335	4	analysis	analysis	NOUN
ajst-19160	335	5	of	of	ADP
ajst-19160	335	6	iaeo	iaeo	NOUN
ajst-19160	335	7	-	-	PUNCT
ajst-19160	335	8	svm	svm	PROPN
ajst-19160	335	9	fitting	fitting	ADJ
ajst-19160	335	10	high	high	ADJ
ajst-19160	335	11	-	-	PUNCT
ajst-19160	335	12	dimensional	dimensional	ADJ
ajst-19160	335	13	surface	surface	NOUN
ajst-19160	335	14	the	the	DET
ajst-19160	335	15	input	input	NOUN
ajst-19160	335	16	data	datum	NOUN
ajst-19160	335	17	is	be	AUX
ajst-19160	335	18	inwardly	inwardly	ADV
ajst-19160	335	19	interpolated	interpolate	VERB
ajst-19160	335	20	based	base	VERB
ajst-19160	335	21	on	on	ADP
ajst-19160	335	22	the	the	DET
ajst-19160	335	23	poles	pole	NOUN
ajst-19160	335	24	used	use	VERB
ajst-19160	335	25	to	to	PART
ajst-19160	335	26	fit	fit	VERB
ajst-19160	335	27	the	the	DET
ajst-19160	335	28	geometric	geometric	ADJ
ajst-19160	335	29	parameters	parameter	NOUN
ajst-19160	335	30	of	of	ADP
ajst-19160	335	31	corrosion	corrosion	NOUN
ajst-19160	335	32	defects	defect	NOUN
ajst-19160	335	33	,	,	PUNCT
ajst-19160	335	34	with	with	ADP
ajst-19160	335	35	the	the	DET
ajst-19160	335	36	number	number	NOUN
ajst-19160	335	37	of	of	ADP
ajst-19160	335	38	interpolations	interpolation	NOUN
ajst-19160	335	39	set	set	VERB
ajst-19160	335	40	at	at	ADP
ajst-19160	335	41	100	100	NUM
ajst-19160	335	42	.	.	PUNCT
ajst-19160	336	1	subsequently	subsequently	ADV
ajst-19160	336	2	,	,	PUNCT
ajst-19160	336	3	the	the	DET
ajst-19160	336	4	interpolated	interpolate	VERB
ajst-19160	336	5	data	data	NOUN
ajst-19160	336	6	is	be	AUX
ajst-19160	336	7	fed	feed	VERB
ajst-19160	336	8	into	into	ADP
ajst-19160	336	9	the	the	DET
ajst-19160	336	10	iaeo	iaeo	NOUN
ajst-19160	336	11	-	-	PUNCT
ajst-19160	336	12	svm	svm	PROPN
ajst-19160	336	13	model	model	NOUN
ajst-19160	336	14	,	,	PUNCT
ajst-19160	336	15	resulting	result	VERB
ajst-19160	336	16	in	in	ADP
ajst-19160	336	17	high	high	ADJ
ajst-19160	336	18	-	-	PUNCT
ajst-19160	336	19	dimensional	dimensional	ADJ
ajst-19160	336	20	spatial	spatial	ADJ
ajst-19160	336	21	surfaces	surface	NOUN
ajst-19160	336	22	with	with	ADP
ajst-19160	336	23	seawater	seawater	NOUN
ajst-19160	336	24	depths	depth	NOUN
ajst-19160	336	25	of	of	ADP
ajst-19160	336	26	100	100	NUM
ajst-19160	336	27	m	m	NOUN
ajst-19160	336	28	,	,	PUNCT
ajst-19160	336	29	250	250	NUM
ajst-19160	336	30	m	m	NOUN
ajst-19160	336	31	and	and	CCONJ
ajst-19160	336	32	500	500	NUM
ajst-19160	336	33	m	m	NOUN
ajst-19160	336	34	(	(	PUNCT
ajst-19160	336	35	see	see	VERB
ajst-19160	336	36	fig	fig	NOUN
ajst-19160	336	37	11	11	NUM
ajst-19160	336	38	)	)	PUNCT
ajst-19160	336	39	.	.	PUNCT
ajst-19160	337	1	127	127	NUM
ajst-19160	337	2	figure	figure	NOUN
ajst-19160	337	3	11	11	NUM
ajst-19160	337	4	.	.	PUNCT
ajst-19160	338	1	the	the	DET
ajst-19160	338	2	effect	effect	NOUN
ajst-19160	338	3	of	of	ADP
ajst-19160	338	4	seawater	seawater	NOUN
ajst-19160	338	5	depth	depth	NOUN
ajst-19160	338	6	and	and	CCONJ
ajst-19160	338	7	corrosion	corrosion	NOUN
ajst-19160	338	8	defects	defect	NOUN
ajst-19160	338	9	on	on	ADP
ajst-19160	338	10	blasting	blast	VERB
ajst-19160	338	11	pressure	pressure	NOUN
ajst-19160	338	12	.	.	PUNCT
ajst-19160	339	1	a)100	a)100	NUM
ajst-19160	339	2	m	m	PROPN
ajst-19160	339	3	,	,	PUNCT
ajst-19160	339	4	b	b	NOUN
ajst-19160	339	5	)	)	PUNCT
ajst-19160	339	6	250	250	NUM
ajst-19160	339	7	m	m	PROPN
ajst-19160	339	8	,	,	PUNCT
ajst-19160	339	9	c)500	c)500	NOUN
ajst-19160	339	10	m	m	VERB
ajst-19160	339	11	upon	upon	SCONJ
ajst-19160	339	12	observing	observe	VERB
ajst-19160	339	13	fig	fig	NOUN
ajst-19160	339	14	.	.	PUNCT
ajst-19160	340	1	11	11	NUM
ajst-19160	340	2	,	,	PUNCT
ajst-19160	340	3	it	it	PRON
ajst-19160	340	4	is	be	AUX
ajst-19160	340	5	evident	evident	ADJ
ajst-19160	340	6	that	that	SCONJ
ajst-19160	340	7	blasting	blast	VERB
ajst-19160	340	8	pressure	pressure	NOUN
ajst-19160	340	9	exhibits	exhibit	VERB
ajst-19160	340	10	a	a	DET
ajst-19160	340	11	linear	linear	ADJ
ajst-19160	340	12	increase	increase	NOUN
ajst-19160	340	13	as	as	ADP
ajst-19160	340	14	ocean	ocean	NOUN
ajst-19160	340	15	depth	depth	NOUN
ajst-19160	340	16	increases	increase	NOUN
ajst-19160	340	17	.	.	PUNCT
ajst-19160	341	1	this	this	PRON
ajst-19160	341	2	indicates	indicate	VERB
ajst-19160	341	3	that	that	SCONJ
ajst-19160	341	4	greater	great	ADJ
ajst-19160	341	5	ocean	ocean	NOUN
ajst-19160	341	6	depths	depth	NOUN
ajst-19160	341	7	can	can	AUX
ajst-19160	341	8	aid	aid	VERB
ajst-19160	341	9	in	in	ADP
ajst-19160	341	10	safeguarding	safeguard	VERB
ajst-19160	341	11	defective	defective	ADJ
ajst-19160	341	12	pipelines	pipeline	NOUN
ajst-19160	341	13	to	to	ADP
ajst-19160	341	14	a	a	DET
ajst-19160	341	15	certain	certain	ADJ
ajst-19160	341	16	extent	extent	NOUN
ajst-19160	341	17	.	.	PUNCT
ajst-19160	342	1	128	128	NUM
ajst-19160	342	2	figure	figure	NOUN
ajst-19160	342	3	12	12	NUM
ajst-19160	342	4	.	.	PUNCT
ajst-19160	343	1	trend	trend	NOUN
ajst-19160	343	2	diagram	diagram	NOUN
ajst-19160	343	3	of	of	ADP
ajst-19160	343	4	the	the	DET
ajst-19160	343	5	influence	influence	NOUN
ajst-19160	343	6	of	of	ADP
ajst-19160	343	7	length(a	length(a	NOUN
ajst-19160	343	8	)	)	PUNCT
ajst-19160	343	9	,	,	PUNCT
ajst-19160	343	10	depth(b	depth(b	PROPN
ajst-19160	343	11	)	)	PUNCT
ajst-19160	343	12	and	and	CCONJ
ajst-19160	343	13	width(c	width(c	PROPN
ajst-19160	343	14	)	)	PUNCT
ajst-19160	343	15	of	of	ADP
ajst-19160	343	16	defects	defect	NOUN
ajst-19160	343	17	on	on	ADP
ajst-19160	343	18	blasting	blast	VERB
ajst-19160	343	19	pressure	pressure	NOUN
ajst-19160	343	20	.	.	PUNCT
ajst-19160	344	1	upon	upon	SCONJ
ajst-19160	344	2	examining	examine	VERB
ajst-19160	344	3	fig	fig	NOUN
ajst-19160	344	4	12	12	NUM
ajst-19160	344	5	,	,	PUNCT
ajst-19160	344	6	it	it	PRON
ajst-19160	344	7	is	be	AUX
ajst-19160	344	8	evident	evident	ADJ
ajst-19160	344	9	that	that	SCONJ
ajst-19160	344	10	blasting	blast	VERB
ajst-19160	344	11	pressure	pressure	NOUN
ajst-19160	344	12	exhibits	exhibit	VERB
ajst-19160	344	13	the	the	DET
ajst-19160	344	14	characteristics	characteristic	NOUN
ajst-19160	344	15	of	of	ADP
ajst-19160	344	16	a	a	DET
ajst-19160	344	17	downward	downward	ADV
ajst-19160	344	18	-	-	PUNCT
ajst-19160	344	19	opening	open	VERB
ajst-19160	344	20	quadratic	quadratic	ADJ
ajst-19160	344	21	function	function	NOUN
ajst-19160	344	22	with	with	ADP
ajst-19160	344	23	an	an	DET
ajst-19160	344	24	increase	increase	NOUN
ajst-19160	344	25	in	in	ADP
ajst-19160	344	26	defect	defect	ADJ
ajst-19160	344	27	depth	depth	NOUN
ajst-19160	344	28	.	.	PUNCT
ajst-19160	345	1	the	the	DET
ajst-19160	345	2	steepness	steepness	NOUN
ajst-19160	345	3	of	of	ADP
ajst-19160	345	4	this	this	DET
ajst-19160	345	5	feature	feature	NOUN
ajst-19160	345	6	demonstrates	demonstrate	VERB
ajst-19160	345	7	significant	significant	ADJ
ajst-19160	345	8	positive	positive	ADJ
ajst-19160	345	9	correlation	correlation	NOUN
ajst-19160	345	10	with	with	ADP
ajst-19160	345	11	corrosion	corrosion	NOUN
ajst-19160	345	12	width	width	NOUN
ajst-19160	345	13	and	and	CCONJ
ajst-19160	345	14	length	length	NOUN
ajst-19160	345	15	.	.	PUNCT
ajst-19160	346	1	this	this	PRON
ajst-19160	346	2	indicates	indicate	VERB
ajst-19160	346	3	that	that	SCONJ
ajst-19160	346	4	an	an	DET
ajst-19160	346	5	increase	increase	NOUN
ajst-19160	346	6	in	in	ADP
ajst-19160	346	7	corrosion	corrosion	NOUN
ajst-19160	346	8	width	width	NOUN
ajst-19160	346	9	and	and	CCONJ
ajst-19160	346	10	length	length	NOUN
ajst-19160	346	11	can	can	AUX
ajst-19160	346	12	accelerate	accelerate	VERB
ajst-19160	346	13	the	the	DET
ajst-19160	346	14	decrease	decrease	NOUN
ajst-19160	346	15	of	of	ADP
ajst-19160	346	16	blasting	blast	VERB
ajst-19160	346	17	pressure	pressure	NOUN
ajst-19160	346	18	.	.	PUNCT
ajst-19160	347	1	similarly	similarly	ADV
ajst-19160	347	2	,	,	PUNCT
ajst-19160	347	3	an	an	DET
ajst-19160	347	4	increase	increase	NOUN
ajst-19160	347	5	in	in	ADP
ajst-19160	347	6	corrosion	corrosion	NOUN
ajst-19160	347	7	defect	defect	NOUN
ajst-19160	347	8	length	length	NOUN
ajst-19160	347	9	causes	cause	VERB
ajst-19160	347	10	blasting	blast	VERB
ajst-19160	347	11	pressure	pressure	NOUN
ajst-19160	347	12	to	to	PART
ajst-19160	347	13	exhibit	exhibit	VERB
ajst-19160	347	14	the	the	DET
ajst-19160	347	15	characteristics	characteristic	NOUN
ajst-19160	347	16	of	of	ADP
ajst-19160	347	17	an	an	DET
ajst-19160	347	18	upward	upward	ADV
ajst-19160	347	19	-	-	PUNCT
ajst-19160	347	20	opening	open	VERB
ajst-19160	347	21	quadratic	quadratic	ADJ
ajst-19160	347	22	function	function	NOUN
ajst-19160	347	23	.	.	PUNCT
ajst-19160	348	1	the	the	DET
ajst-19160	348	2	steepness	steepness	NOUN
ajst-19160	348	3	of	of	ADP
ajst-19160	348	4	this	this	DET
ajst-19160	348	5	feature	feature	NOUN
ajst-19160	348	6	also	also	ADV
ajst-19160	348	7	bears	bear	VERB
ajst-19160	348	8	significant	significant	ADJ
ajst-19160	348	9	positive	positive	ADJ
ajst-19160	348	10	correlation	correlation	NOUN
ajst-19160	348	11	with	with	ADP
ajst-19160	348	12	the	the	DET
ajst-19160	348	13	depth	depth	NOUN
ajst-19160	348	14	and	and	CCONJ
ajst-19160	348	15	width	width	NOUN
ajst-19160	348	16	of	of	ADP
ajst-19160	348	17	the	the	DET
ajst-19160	348	18	corrosion	corrosion	NOUN
ajst-19160	348	19	defect	defect	NOUN
ajst-19160	348	20	.	.	PUNCT
ajst-19160	349	1	the	the	DET
ajst-19160	349	2	upward	upward	ADV
ajst-19160	349	3	-	-	PUNCT
ajst-19160	349	4	opening	opening	NOUN
ajst-19160	349	5	suggests	suggest	VERB
ajst-19160	349	6	the	the	DET
ajst-19160	349	7	existence	existence	NOUN
ajst-19160	349	8	of	of	ADP
ajst-19160	349	9	a	a	DET
ajst-19160	349	10	limit	limit	NOUN
ajst-19160	349	11	threshold	threshold	NOUN
ajst-19160	349	12	,	,	PUNCT
ajst-19160	349	13	beyond	beyond	ADP
ajst-19160	349	14	which	which	PRON
ajst-19160	349	15	the	the	DET
ajst-19160	349	16	burst	burst	ADJ
ajst-19160	349	17	pressure	pressure	NOUN
ajst-19160	349	18	of	of	ADP
ajst-19160	349	19	the	the	DET
ajst-19160	349	20	pipeline	pipeline	NOUN
ajst-19160	349	21	remains	remain	VERB
ajst-19160	349	22	unaffected	unaffected	ADJ
ajst-19160	349	23	.	.	PUNCT
ajst-19160	350	1	on	on	ADP
ajst-19160	350	2	this	this	DET
ajst-19160	350	3	basis	basis	NOUN
ajst-19160	350	4	,	,	PUNCT
ajst-19160	350	5	the	the	DET
ajst-19160	350	6	influence	influence	NOUN
ajst-19160	350	7	of	of	ADP
ajst-19160	350	8	corrosion	corrosion	NOUN
ajst-19160	350	9	width	width	NOUN
ajst-19160	350	10	is	be	AUX
ajst-19160	350	11	observed	observe	VERB
ajst-19160	350	12	.	.	PUNCT
ajst-19160	351	1	with	with	ADP
ajst-19160	351	2	the	the	DET
ajst-19160	351	3	increase	increase	NOUN
ajst-19160	351	4	of	of	ADP
ajst-19160	351	5	width	width	NOUN
ajst-19160	351	6	,	,	PUNCT
ajst-19160	351	7	the	the	DET
ajst-19160	351	8	reduction	reduction	NOUN
ajst-19160	351	9	rate	rate	NOUN
ajst-19160	351	10	of	of	ADP
ajst-19160	351	11	blasting	blast	VERB
ajst-19160	351	12	pressure	pressure	NOUN
ajst-19160	351	13	increases	increase	NOUN
ajst-19160	351	14	first	first	ADV
ajst-19160	351	15	and	and	CCONJ
ajst-19160	351	16	then	then	ADV
ajst-19160	351	17	decreases	decrease	VERB
ajst-19160	351	18	.	.	PUNCT
ajst-19160	352	1	it	it	PRON
ajst-19160	352	2	shows	show	VERB
ajst-19160	352	3	that	that	SCONJ
ajst-19160	352	4	the	the	DET
ajst-19160	352	5	influence	influence	NOUN
ajst-19160	352	6	of	of	ADP
ajst-19160	352	7	corrosion	corrosion	NOUN
ajst-19160	352	8	defect	defect	NOUN
ajst-19160	352	9	width	width	NOUN
ajst-19160	352	10	on	on	ADP
ajst-19160	352	11	blasting	blast	VERB
ajst-19160	352	12	pressure	pressure	NOUN
ajst-19160	352	13	will	will	AUX
ajst-19160	352	14	increase	increase	VERB
ajst-19160	352	15	with	with	ADP
ajst-19160	352	16	the	the	DET
ajst-19160	352	17	increase	increase	NOUN
ajst-19160	352	18	of	of	ADP
ajst-19160	352	19	width	width	NOUN
ajst-19160	352	20	,	,	PUNCT
ajst-19160	352	21	and	and	CCONJ
ajst-19160	352	22	the	the	DET
ajst-19160	352	23	influence	influence	NOUN
ajst-19160	352	24	will	will	AUX
ajst-19160	352	25	gradually	gradually	ADV
ajst-19160	352	26	disappear	disappear	VERB
ajst-19160	352	27	after	after	ADP
ajst-19160	352	28	increasing	increase	VERB
ajst-19160	352	29	to	to	ADP
ajst-19160	352	30	a	a	DET
ajst-19160	352	31	certain	certain	ADJ
ajst-19160	352	32	value	value	NOUN
ajst-19160	352	33	.	.	PUNCT
ajst-19160	353	1	the	the	DET
ajst-19160	353	2	change	change	NOUN
ajst-19160	353	3	trend	trend	NOUN
ajst-19160	353	4	is	be	AUX
ajst-19160	353	5	similar	similar	ADJ
ajst-19160	353	6	to	to	ADP
ajst-19160	353	7	the	the	DET
ajst-19160	353	8	influence	influence	NOUN
ajst-19160	353	9	of	of	ADP
ajst-19160	353	10	corrosion	corrosion	NOUN
ajst-19160	353	11	length	length	NOUN
ajst-19160	353	12	on	on	ADP
ajst-19160	353	13	blasting	blast	VERB
ajst-19160	353	14	pressure	pressure	NOUN
ajst-19160	353	15	.	.	PUNCT
ajst-19160	354	1	there	there	PRON
ajst-19160	354	2	is	be	VERB
ajst-19160	354	3	a	a	DET
ajst-19160	354	4	limit	limit	NOUN
ajst-19160	354	5	threshold	threshold	NOUN
ajst-19160	354	6	for	for	ADP
ajst-19160	354	7	the	the	DET
ajst-19160	354	8	width	width	NOUN
ajst-19160	354	9	of	of	ADP
ajst-19160	354	10	the	the	DET
ajst-19160	354	11	corrosion	corrosion	NOUN
ajst-19160	354	12	defect	defect	NOUN
ajst-19160	354	13	after	after	ADP
ajst-19160	354	14	30	30	NUM
ajst-19160	354	15	°	°	NOUN
ajst-19160	354	16	.	.	PUNCT
ajst-19160	355	1	after	after	ADP
ajst-19160	355	2	exceeding	exceed	VERB
ajst-19160	355	3	this	this	DET
ajst-19160	355	4	threshold	threshold	NOUN
ajst-19160	355	5	,	,	PUNCT
ajst-19160	355	6	it	it	PRON
ajst-19160	355	7	can	can	AUX
ajst-19160	355	8	be	be	AUX
ajst-19160	355	9	approximated	approximate	VERB
ajst-19160	355	10	as	as	ADP
ajst-19160	355	11	having	have	VERB
ajst-19160	355	12	no	no	DET
ajst-19160	355	13	effect	effect	NOUN
ajst-19160	355	14	on	on	ADP
ajst-19160	355	15	the	the	DET
ajst-19160	355	16	burst	burst	ADJ
ajst-19160	355	17	pressure	pressure	NOUN
ajst-19160	355	18	of	of	ADP
ajst-19160	355	19	the	the	DET
ajst-19160	355	20	pipeline	pipeline	NOUN
ajst-19160	355	21	.	.	PUNCT
ajst-19160	356	1	when	when	SCONJ
ajst-19160	356	2	the	the	DET
ajst-19160	356	3	length	length	NOUN
ajst-19160	356	4	of	of	ADP
ajst-19160	356	5	the	the	DET
ajst-19160	356	6	corrosion	corrosion	NOUN
ajst-19160	356	7	defect	defect	NOUN
ajst-19160	356	8	is	be	AUX
ajst-19160	356	9	fixed	fix	VERB
ajst-19160	356	10	at	at	ADP
ajst-19160	356	11	200	200	NUM
ajst-19160	356	12	mm	mm	NOUN
ajst-19160	356	13	and	and	CCONJ
ajst-19160	356	14	the	the	DET
ajst-19160	356	15	depth	depth	NOUN
ajst-19160	356	16	is	be	AUX
ajst-19160	356	17	0.7	0.7	NUM
ajst-19160	356	18	times	time	NOUN
ajst-19160	356	19	the	the	DET
ajst-19160	356	20	wall	wall	PROPN
ajst-19160	356	21	thickness	thickness	NOUN
ajst-19160	356	22	,	,	PUNCT
ajst-19160	356	23	the	the	DET
ajst-19160	356	24	width	width	NOUN
ajst-19160	356	25	of	of	ADP
ajst-19160	356	26	the	the	DET
ajst-19160	356	27	corrosion	corrosion	NOUN
ajst-19160	356	28	defect	defect	NOUN
ajst-19160	356	29	changes	change	NOUN
ajst-19160	356	30	from	from	ADP
ajst-19160	356	31	10	10	NUM
ajst-19160	356	32	°	°	NOUN
ajst-19160	356	33	to	to	ADP
ajst-19160	356	34	30	30	NUM
ajst-19160	356	35	°	°	NOUN
ajst-19160	356	36	,	,	PUNCT
ajst-19160	356	37	which	which	PRON
ajst-19160	356	38	will	will	AUX
ajst-19160	356	39	cause	cause	VERB
ajst-19160	356	40	the	the	DET
ajst-19160	356	41	relative	relative	ADJ
ajst-19160	356	42	change	change	NOUN
ajst-19160	356	43	of	of	ADP
ajst-19160	356	44	the	the	DET
ajst-19160	356	45	failure	failure	NOUN
ajst-19160	356	46	pressure	pressure	NOUN
ajst-19160	356	47	to	to	PART
ajst-19160	356	48	exceed	exceed	VERB
ajst-19160	356	49	23	23	NUM
ajst-19160	356	50	%	%	NOUN
ajst-19160	356	51	.	.	PUNCT
ajst-19160	357	1	it	it	PRON
ajst-19160	357	2	shows	show	VERB
ajst-19160	357	3	that	that	SCONJ
ajst-19160	357	4	the	the	DET
ajst-19160	357	5	influence	influence	NOUN
ajst-19160	357	6	of	of	ADP
ajst-19160	357	7	corrosion	corrosion	NOUN
ajst-19160	357	8	width	width	NOUN
ajst-19160	357	9	on	on	ADP
ajst-19160	357	10	blasting	blast	VERB
ajst-19160	357	11	pressure	pressure	NOUN
ajst-19160	357	12	can	can	AUX
ajst-19160	357	13	not	not	PART
ajst-19160	357	14	be	be	AUX
ajst-19160	357	15	ignored	ignore	VERB
ajst-19160	357	16	when	when	SCONJ
ajst-19160	357	17	the	the	DET
ajst-19160	357	18	defect	defect	NOUN
ajst-19160	357	19	length	length	NOUN
ajst-19160	357	20	is	be	AUX
ajst-19160	357	21	long	long	ADJ
ajst-19160	357	22	and	and	CCONJ
ajst-19160	357	23	the	the	DET
ajst-19160	357	24	defect	defect	NOUN
ajst-19160	357	25	depth	depth	NOUN
ajst-19160	357	26	is	be	AUX
ajst-19160	357	27	deep	deep	ADJ
ajst-19160	357	28	.	.	PUNCT
ajst-19160	358	1	this	this	DET
ajst-19160	358	2	finding	finding	NOUN
ajst-19160	358	3	can	can	AUX
ajst-19160	358	4	also	also	ADV
ajst-19160	358	5	be	be	AUX
ajst-19160	358	6	seen	see	VERB
ajst-19160	358	7	from	from	ADP
ajst-19160	358	8	fig.11	fig.11	PROPN
ajst-19160	358	9	(	(	PUNCT
ajst-19160	358	10	b	b	PROPN
ajst-19160	358	11	,	,	PUNCT
ajst-19160	358	12	c	c	NOUN
ajst-19160	358	13	)	)	PUNCT
ajst-19160	358	14	.	.	PUNCT
ajst-19160	359	1	6	6	X
ajst-19160	359	2	.	.	X
ajst-19160	359	3	conclusion	conclusion	NOUN
ajst-19160	359	4	the	the	DET
ajst-19160	359	5	conclusion	conclusion	NOUN
ajst-19160	359	6	is	be	AUX
ajst-19160	359	7	summarized	summarize	VERB
ajst-19160	359	8	as	as	ADP
ajst-19160	359	9	the	the	DET
ajst-19160	359	10	following	follow	VERB
ajst-19160	359	11	four	four	NUM
ajst-19160	359	12	points	point	NOUN
ajst-19160	359	13	:	:	PUNCT
ajst-19160	359	14	1	1	X
ajst-19160	359	15	)	)	PUNCT
ajst-19160	359	16	the	the	DET
ajst-19160	359	17	iaeo	iaeo	NOUN
ajst-19160	359	18	algorithm	algorithm	NOUN
ajst-19160	359	19	is	be	AUX
ajst-19160	359	20	obtained	obtain	VERB
ajst-19160	359	21	by	by	ADP
ajst-19160	359	22	improving	improve	VERB
ajst-19160	359	23	the	the	DET
ajst-19160	359	24	aeo	aeo	PROPN
ajst-19160	359	25	algorithm	algorithm	NOUN
ajst-19160	359	26	with	with	ADP
ajst-19160	359	27	lbes	lbe	NOUN
ajst-19160	359	28	strategy	strategy	NOUN
ajst-19160	359	29	and	and	CCONJ
ajst-19160	359	30	reverse	reverse	ADJ
ajst-19160	359	31	elite	elite	ADJ
ajst-19160	359	32	strategy	strategy	NOUN
ajst-19160	359	33	.	.	PUNCT
ajst-19160	360	1	lbes	lbe	NOUN
ajst-19160	360	2	improves	improve	VERB
ajst-19160	360	3	the	the	DET
ajst-19160	360	4	accuracy	accuracy	NOUN
ajst-19160	360	5	of	of	ADP
ajst-19160	360	6	the	the	DET
ajst-19160	360	7	algorithm	algorithm	NOUN
ajst-19160	360	8	in	in	ADP
ajst-19160	360	9	the	the	DET
ajst-19160	360	10	later	later	ADJ
ajst-19160	360	11	stage	stage	NOUN
ajst-19160	360	12	,	,	PUNCT
ajst-19160	360	13	and	and	CCONJ
ajst-19160	360	14	the	the	DET
ajst-19160	360	15	reverse	reverse	ADJ
ajst-19160	360	16	elite	elite	ADJ
ajst-19160	360	17	strategy	strategy	NOUN
ajst-19160	360	18	improves	improve	VERB
ajst-19160	360	19	the	the	DET
ajst-19160	360	20	diversity	diversity	NOUN
ajst-19160	360	21	of	of	ADP
ajst-19160	360	22	the	the	DET
ajst-19160	360	23	population	population	NOUN
ajst-19160	360	24	.	.	PUNCT
ajst-19160	361	1	the	the	DET
ajst-19160	361	2	two	two	NUM
ajst-19160	361	3	algorithms	algorithm	NOUN
ajst-19160	361	4	are	be	AUX
ajst-19160	361	5	applied	apply	VERB
ajst-19160	361	6	to	to	ADP
ajst-19160	361	7	the	the	DET
ajst-19160	361	8	svm	svm	ADJ
ajst-19160	361	9	model	model	NOUN
ajst-19160	361	10	respectively	respectively	ADV
ajst-19160	361	11	.	.	PUNCT
ajst-19160	362	1	experiments	experiment	NOUN
ajst-19160	362	2	show	show	VERB
ajst-19160	362	3	that	that	SCONJ
ajst-19160	362	4	the	the	DET
ajst-19160	362	5	calculation	calculation	NOUN
ajst-19160	362	6	accuracy	accuracy	NOUN
ajst-19160	362	7	,	,	PUNCT
ajst-19160	362	8	stability	stability	NOUN
ajst-19160	362	9	and	and	CCONJ
ajst-19160	362	10	robustness	robustness	NOUN
ajst-19160	362	11	of	of	ADP
ajst-19160	362	12	the	the	DET
ajst-19160	362	13	iaeo	iaeo	NOUN
ajst-19160	362	14	algorithm	algorithm	NOUN
ajst-19160	362	15	are	be	AUX
ajst-19160	362	16	improved	improve	VERB
ajst-19160	362	17	.	.	PUNCT
ajst-19160	363	1	2	2	X
ajst-19160	363	2	)	)	PUNCT
ajst-19160	363	3	the	the	DET
ajst-19160	363	4	average	average	ADJ
ajst-19160	363	5	goodness	goodness	NOUN
ajst-19160	363	6	of	of	ADP
ajst-19160	363	7	fit	fit	NOUN
ajst-19160	363	8	of	of	ADP
ajst-19160	363	9	rbf	rbf	PROPN
ajst-19160	363	10	,	,	PUNCT
ajst-19160	363	11	grnn	grnn	PROPN
ajst-19160	363	12	and	and	CCONJ
ajst-19160	363	13	elm	elm	NOUN
ajst-19160	363	14	models	model	NOUN
ajst-19160	363	15	is	be	AUX
ajst-19160	363	16	less	less	ADJ
ajst-19160	363	17	than	than	ADP
ajst-19160	363	18	0.9	0.9	NUM
ajst-19160	363	19	,	,	PUNCT
ajst-19160	363	20	and	and	CCONJ
ajst-19160	363	21	the	the	DET
ajst-19160	363	22	average	average	ADJ
ajst-19160	363	23	mse	mse	NOUN
ajst-19160	363	24	is	be	AUX
ajst-19160	363	25	greater	great	ADJ
ajst-19160	363	26	than	than	ADP
ajst-19160	363	27	3.0	3.0	NUM
ajst-19160	363	28	,	,	PUNCT
ajst-19160	363	29	indicating	indicate	VERB
ajst-19160	363	30	that	that	SCONJ
ajst-19160	363	31	these	these	DET
ajst-19160	363	32	models	model	NOUN
ajst-19160	363	33	are	be	AUX
ajst-19160	363	34	not	not	PART
ajst-19160	363	35	suitable	suitable	ADJ
ajst-19160	363	36	for	for	ADP
ajst-19160	363	37	the	the	DET
ajst-19160	363	38	failure	failure	NOUN
ajst-19160	363	39	pressure	pressure	NOUN
ajst-19160	363	40	prediction	prediction	NOUN
ajst-19160	363	41	of	of	ADP
ajst-19160	363	42	submarine	submarine	NOUN
ajst-19160	363	43	oil	oil	NOUN
ajst-19160	363	44	and	and	CCONJ
ajst-19160	363	45	gas	gas	NOUN
ajst-19160	363	46	pipelines	pipeline	NOUN
ajst-19160	363	47	.	.	PUNCT
ajst-19160	364	1	compared	compare	VERB
ajst-19160	364	2	with	with	ADP
ajst-19160	364	3	the	the	DET
ajst-19160	364	4	svm	svm	ADJ
ajst-19160	364	5	model	model	NOUN
ajst-19160	364	6	,	,	PUNCT
ajst-19160	364	7	the	the	DET
ajst-19160	364	8	iaeo	iaeo	NOUN
ajst-19160	364	9	-	-	PUNCT
ajst-19160	364	10	svm	svm	ADJ
ajst-19160	364	11	model	model	NOUN
ajst-19160	364	12	can	can	AUX
ajst-19160	364	13	better	well	ADV
ajst-19160	364	14	avoid	avoid	VERB
ajst-19160	364	15	the	the	DET
ajst-19160	364	16	occurrence	occurrence	NOUN
ajst-19160	364	17	of	of	ADP
ajst-19160	364	18	'	'	PUNCT
ajst-19160	364	19	over	over	ADV
ajst-19160	364	20	-	-	PUNCT
ajst-19160	364	21	fitting	fitting	NOUN
ajst-19160	364	22	'	'	PUNCT
ajst-19160	364	23	.	.	PUNCT
ajst-19160	365	1	compared	compare	VERB
ajst-19160	365	2	with	with	ADP
ajst-19160	365	3	the	the	DET
ajst-19160	365	4	aeo	aeo	PROPN
ajst-19160	365	5	-	-	PUNCT
ajst-19160	365	6	svm	svm	PROPN
ajst-19160	365	7	model	model	NOUN
ajst-19160	365	8	,	,	PUNCT
ajst-19160	365	9	the	the	DET
ajst-19160	365	10	determination	determination	NOUN
ajst-19160	365	11	coefficient	coefficient	NOUN
ajst-19160	365	12	and	and	CCONJ
ajst-19160	365	13	relative	relative	ADJ
ajst-19160	365	14	error	error	NOUN
ajst-19160	365	15	of	of	ADP
ajst-19160	365	16	both	both	CCONJ
ajst-19160	365	17	the	the	DET
ajst-19160	365	18	training	training	NOUN
ajst-19160	365	19	set	set	NOUN
ajst-19160	365	20	and	and	CCONJ
ajst-19160	365	21	the	the	DET
ajst-19160	365	22	test	test	NOUN
ajst-19160	365	23	set	set	NOUN
ajst-19160	365	24	are	be	AUX
ajst-19160	365	25	greatly	greatly	ADV
ajst-19160	365	26	improved	improve	VERB
ajst-19160	365	27	.	.	PUNCT
ajst-19160	366	1	compared	compare	VERB
ajst-19160	366	2	with	with	ADP
ajst-19160	366	3	the	the	DET
ajst-19160	366	4	ann	ann	PROPN
ajst-19160	366	5	-	-	PUNCT
ajst-19160	366	6	lm	lm	PROPN
ajst-19160	366	7	model	model	NOUN
ajst-19160	366	8	,	,	PUNCT
ajst-19160	366	9	the	the	DET
ajst-19160	366	10	iaeosvm	iaeosvm	ADJ
ajst-19160	366	11	model	model	NOUN
ajst-19160	366	12	has	have	VERB
ajst-19160	366	13	smaller	small	ADJ
ajst-19160	366	14	variances	variance	NOUN
ajst-19160	366	15	,	,	PUNCT
ajst-19160	366	16	indicating	indicate	VERB
ajst-19160	366	17	that	that	SCONJ
ajst-19160	366	18	iaeosvm	iaeosvm	NOUN
ajst-19160	366	19	has	have	VERB
ajst-19160	366	20	better	well	ADJ
ajst-19160	366	21	robustness	robustness	NOUN
ajst-19160	366	22	.	.	PUNCT
ajst-19160	367	1	considering	consider	VERB
ajst-19160	367	2	the	the	DET
ajst-19160	367	3	iaeo	iaeo	NOUN
ajst-19160	367	4	-	-	PUNCT
ajst-19160	367	5	svm	svm	PROPN
ajst-19160	367	6	is	be	AUX
ajst-19160	367	7	a	a	DET
ajst-19160	367	8	kind	kind	NOUN
ajst-19160	367	9	of	of	ADP
ajst-19160	367	10	high	high	ADJ
ajst-19160	367	11	precision	precision	NOUN
ajst-19160	367	12	,	,	PUNCT
ajst-19160	367	13	more	more	ADV
ajst-19160	367	14	stable	stable	ADJ
ajst-19160	367	15	submarine	submarine	NOUN
ajst-19160	367	16	oil	oil	NOUN
ajst-19160	367	17	and	and	CCONJ
ajst-19160	367	18	gas	gas	NOUN
ajst-19160	367	19	pipeline	pipeline	NOUN
ajst-19160	367	20	failure	failure	NOUN
ajst-19160	367	21	pressure	pressure	NOUN
ajst-19160	367	22	prediction	prediction	NOUN
ajst-19160	367	23	model	model	NOUN
ajst-19160	367	24	.	.	PUNCT
ajst-19160	368	1	3	3	NUM
ajst-19160	368	2	)	)	PUNCT
ajst-19160	368	3	with	with	ADP
ajst-19160	368	4	the	the	DET
ajst-19160	368	5	increase	increase	NOUN
ajst-19160	368	6	of	of	ADP
ajst-19160	368	7	width	width	NOUN
ajst-19160	368	8	,	,	PUNCT
ajst-19160	368	9	the	the	DET
ajst-19160	368	10	reduction	reduction	NOUN
ajst-19160	368	11	rate	rate	NOUN
ajst-19160	368	12	of	of	ADP
ajst-19160	368	13	blasting	blast	VERB
ajst-19160	368	14	pressure	pressure	NOUN
ajst-19160	368	15	increases	increase	NOUN
ajst-19160	368	16	first	first	ADV
ajst-19160	368	17	and	and	CCONJ
ajst-19160	368	18	then	then	ADV
ajst-19160	368	19	decreases	decrease	VERB
ajst-19160	368	20	.	.	PUNCT
ajst-19160	369	1	it	it	PRON
ajst-19160	369	2	shows	show	VERB
ajst-19160	369	3	that	that	SCONJ
ajst-19160	369	4	the	the	DET
ajst-19160	369	5	influence	influence	NOUN
ajst-19160	369	6	of	of	ADP
ajst-19160	369	7	corrosion	corrosion	NOUN
ajst-19160	369	8	defect	defect	NOUN
ajst-19160	369	9	width	width	NOUN
ajst-19160	369	10	on	on	ADP
ajst-19160	369	11	blasting	blast	VERB
ajst-19160	369	12	pressure	pressure	NOUN
ajst-19160	369	13	will	will	AUX
ajst-19160	369	14	increase	increase	VERB
ajst-19160	369	15	with	with	ADP
ajst-19160	369	16	the	the	DET
ajst-19160	369	17	increase	increase	NOUN
ajst-19160	369	18	of	of	ADP
ajst-19160	369	19	width	width	NOUN
ajst-19160	369	20	,	,	PUNCT
ajst-19160	369	21	and	and	CCONJ
ajst-19160	369	22	the	the	DET
ajst-19160	369	23	influence	influence	NOUN
ajst-19160	369	24	will	will	AUX
ajst-19160	369	25	gradually	gradually	ADV
ajst-19160	369	26	disappear	disappear	VERB
ajst-19160	369	27	after	after	ADP
ajst-19160	369	28	increasing	increase	VERB
ajst-19160	369	29	to	to	ADP
ajst-19160	369	30	a	a	DET
ajst-19160	369	31	certain	certain	ADJ
ajst-19160	369	32	value	value	NOUN
ajst-19160	369	33	.	.	PUNCT
ajst-19160	370	1	4	4	X
ajst-19160	370	2	)	)	PUNCT
ajst-19160	370	3	the	the	DET
ajst-19160	370	4	existing	exist	VERB
ajst-19160	370	5	empirical	empirical	ADJ
ajst-19160	370	6	methods	method	NOUN
ajst-19160	370	7	advocate	advocate	VERB
ajst-19160	370	8	neglecting	neglect	VERB
ajst-19160	370	9	the	the	DET
ajst-19160	370	10	width	width	NOUN
ajst-19160	370	11	of	of	ADP
ajst-19160	370	12	corrosion	corrosion	NOUN
ajst-19160	370	13	defects	defect	NOUN
ajst-19160	370	14	,	,	PUNCT
ajst-19160	370	15	but	but	CCONJ
ajst-19160	370	16	through	through	ADP
ajst-19160	370	17	the	the	DET
ajst-19160	370	18	research	research	NOUN
ajst-19160	370	19	129	129	NUM
ajst-19160	370	20	conducted	conduct	VERB
ajst-19160	370	21	in	in	ADP
ajst-19160	370	22	this	this	DET
ajst-19160	370	23	paper	paper	NOUN
ajst-19160	370	24	,	,	PUNCT
ajst-19160	370	25	it	it	PRON
ajst-19160	370	26	has	have	AUX
ajst-19160	370	27	been	be	AUX
ajst-19160	370	28	found	find	VERB
ajst-19160	370	29	that	that	SCONJ
ajst-19160	370	30	:	:	PUNCT
ajst-19160	370	31	when	when	SCONJ
ajst-19160	370	32	the	the	DET
ajst-19160	370	33	depth	depth	NOUN
ajst-19160	370	34	of	of	ADP
ajst-19160	370	35	seawater	seawater	NOUN
ajst-19160	370	36	,	,	PUNCT
ajst-19160	370	37	the	the	DET
ajst-19160	370	38	length	length	NOUN
ajst-19160	370	39	and	and	CCONJ
ajst-19160	370	40	depth	depth	NOUN
ajst-19160	370	41	of	of	ADP
ajst-19160	370	42	corrosion	corrosion	NOUN
ajst-19160	370	43	defects	defect	NOUN
ajst-19160	370	44	are	be	AUX
ajst-19160	370	45	fixed	fix	VERB
ajst-19160	370	46	,	,	PUNCT
ajst-19160	370	47	and	and	CCONJ
ajst-19160	370	48	the	the	DET
ajst-19160	370	49	width	width	NOUN
ajst-19160	370	50	of	of	ADP
ajst-19160	370	51	corrosion	corrosion	NOUN
ajst-19160	370	52	defects	defect	NOUN
ajst-19160	370	53	changes	change	NOUN
ajst-19160	370	54	from	from	ADP
ajst-19160	370	55	10	10	NUM
ajst-19160	370	56	°	°	NOUN
ajst-19160	370	57	to	to	ADP
ajst-19160	370	58	30	30	NUM
ajst-19160	370	59	°	°	NOUN
ajst-19160	370	60	,	,	PUNCT
ajst-19160	370	61	the	the	DET
ajst-19160	370	62	maximum	maximum	ADJ
ajst-19160	370	63	relative	relative	ADJ
ajst-19160	370	64	change	change	NOUN
ajst-19160	370	65	of	of	ADP
ajst-19160	370	66	blasting	blast	VERB
ajst-19160	370	67	pressure	pressure	NOUN
ajst-19160	370	68	will	will	AUX
ajst-19160	370	69	exceed	exceed	VERB
ajst-19160	370	70	23	23	NUM
ajst-19160	370	71	%	%	NOUN
ajst-19160	370	72	.	.	PUNCT
ajst-19160	371	1	it	it	PRON
ajst-19160	371	2	shows	show	VERB
ajst-19160	371	3	that	that	SCONJ
ajst-19160	371	4	the	the	DET
ajst-19160	371	5	influence	influence	NOUN
ajst-19160	371	6	of	of	ADP
ajst-19160	371	7	corrosion	corrosion	NOUN
ajst-19160	371	8	width	width	NOUN
ajst-19160	371	9	on	on	ADP
ajst-19160	371	10	blasting	blast	VERB
ajst-19160	371	11	pressure	pressure	NOUN
ajst-19160	371	12	can	can	AUX
ajst-19160	371	13	not	not	PART
ajst-19160	371	14	be	be	AUX
ajst-19160	371	15	ignored	ignore	VERB
ajst-19160	371	16	.	.	PUNCT
ajst-19160	372	1	7	7	X
ajst-19160	372	2	.	.	X
ajst-19160	372	3	conflict	conflict	NOUN
ajst-19160	372	4	of	of	ADP
ajst-19160	372	5	interest	interest	NOUN
ajst-19160	372	6	there	there	PRON
ajst-19160	372	7	are	be	VERB
ajst-19160	372	8	no	no	DET
ajst-19160	372	9	known	known	ADJ
ajst-19160	372	10	competing	compete	VERB
ajst-19160	372	11	economic	economic	ADJ
ajst-19160	372	12	interests	interest	NOUN
ajst-19160	372	13	or	or	CCONJ
ajst-19160	372	14	personal	personal	ADJ
ajst-19160	372	15	relationships	relationship	NOUN
ajst-19160	372	16	.	.	PUNCT
ajst-19160	373	1	acknowledgment	acknowledgment	NOUN
ajst-19160	373	2	thank	thank	VERB
ajst-19160	373	3	you	you	PRON
ajst-19160	373	4	for	for	ADP
ajst-19160	373	5	the	the	DET
ajst-19160	373	6	experimental	experimental	ADJ
ajst-19160	373	7	environment	environment	NOUN
ajst-19160	373	8	provided	provide	VERB
ajst-19160	373	9	by	by	ADP
ajst-19160	373	10	the	the	DET
ajst-19160	373	11	key	key	ADJ
ajst-19160	373	12	laboratory	laboratory	NOUN
ajst-19160	373	13	of	of	ADP
ajst-19160	373	14	the	the	DET
ajst-19160	373	15	ministry	ministry	PROPN
ajst-19160	373	16	of	of	ADP
ajst-19160	373	17	education	education	PROPN
ajst-19160	373	18	of	of	ADP
ajst-19160	373	19	southwest	southwest	ADJ
ajst-19160	373	20	petroleum	petroleum	NOUN
ajst-19160	373	21	university	university	NOUN
ajst-19160	373	22	,	,	PUNCT
ajst-19160	373	23	as	as	ADV
ajst-19160	373	24	well	well	ADV
ajst-19160	373	25	as	as	ADP
ajst-19160	373	26	the	the	DET
ajst-19160	373	27	hard	hard	ADJ
ajst-19160	373	28	work	work	NOUN
ajst-19160	373	29	of	of	ADP
ajst-19160	373	30	the	the	DET
ajst-19160	373	31	editing	edit	VERB
ajst-19160	373	32	teacher	teacher	NOUN
ajst-19160	373	33	and	and	CCONJ
ajst-19160	373	34	the	the	DET
ajst-19160	373	35	review	review	NOUN
ajst-19160	373	36	teacher	teacher	NOUN
ajst-19160	373	37	.	.	PUNCT
ajst-19160	374	1	references	reference	NOUN
ajst-19160	374	2	[	[	X
ajst-19160	374	3	1	1	NUM
ajst-19160	374	4	]	]	PUNCT
ajst-19160	374	5	g.	g.	PROPN
ajst-19160	374	6	teran	teran	PROPN
ajst-19160	374	7	,	,	PUNCT
ajst-19160	374	8	s.	s.	PROPN
ajst-19160	374	9	capula	capula	PROPN
ajst-19160	374	10	-	-	PUNCT
ajst-19160	374	11	colindres	colindre	NOUN
ajst-19160	374	12	,	,	PUNCT
ajst-19160	374	13	j.c	j.c	PROPN
ajst-19160	374	14	.	.	PROPN
ajst-19160	374	15	velazquez	velazquez	PROPN
ajst-19160	374	16	,	,	PUNCT
ajst-19160	374	17	m.j	m.j	PROPN
ajst-19160	374	18	.	.	PROPN
ajst-19160	374	19	fernandez	fernandez	PROPN
ajst-19160	374	20	-	-	PUNCT
ajst-19160	374	21	cueto	cueto	PROPN
ajst-19160	374	22	,	,	PUNCT
ajst-19160	374	23	d.	d.	PROPN
ajst-19160	374	24	angeles	angeles	PROPN
ajst-19160	374	25	-	-	PUNCT
ajst-19160	374	26	herrera	herrera	PROPN
ajst-19160	374	27	,	,	PUNCT
ajst-19160	374	28	h.	h.	PROPN
ajst-19160	374	29	herrera	herrera	PROPN
ajst-19160	374	30	-	-	PUNCT
ajst-19160	374	31	hernandez	hernandez	PROPN
ajst-19160	374	32	,	,	PUNCT
ajst-19160	374	33	failure	failure	NOUN
ajst-19160	374	34	pressure	pressure	NOUN
ajst-19160	374	35	estimations	estimation	NOUN
ajst-19160	374	36	for	for	ADP
ajst-19160	374	37	pipes	pipe	NOUN
ajst-19160	374	38	with	with	ADP
ajst-19160	374	39	combined	combined	ADJ
ajst-19160	374	40	corrosion	corrosion	NOUN
ajst-19160	374	41	defects	defect	NOUN
ajst-19160	374	42	on	on	ADP
ajst-19160	374	43	the	the	DET
ajst-19160	374	44	external	external	ADJ
ajst-19160	374	45	surface	surface	NOUN
ajst-19160	374	46	:	:	PUNCT
ajst-19160	374	47	a	a	DET
ajst-19160	374	48	comparative	comparative	ADJ
ajst-19160	374	49	study	study	NOUN
ajst-19160	374	50	,	,	PUNCT
ajst-19160	374	51	international	international	ADJ
ajst-19160	374	52	journal	journal	NOUN
ajst-19160	374	53	of	of	ADP
ajst-19160	374	54	electrochemical	electrochemical	ADJ
ajst-19160	374	55	science	science	NOUN
ajst-19160	374	56	,	,	PUNCT
ajst-19160	374	57	(	(	PUNCT
ajst-19160	374	58	2017	2017	NUM
ajst-19160	374	59	)	)	PUNCT
ajst-19160	374	60	10152	10152	NUM
ajst-19160	374	61	-	-	SYM
ajst-19160	374	62	10176	10176	NUM
ajst-19160	374	63	.	.	PUNCT
ajst-19160	375	1	[	[	X
ajst-19160	375	2	2	2	NUM
ajst-19160	375	3	]	]	PUNCT
ajst-19160	375	4	c.	c.	PROPN
ajst-19160	375	5	bao	bao	PROPN
ajst-19160	375	6	-	-	PUNCT
ajst-19160	375	7	ping	ping	PROPN
ajst-19160	375	8	,	,	PUNCT
ajst-19160	375	9	z.	z.	PROPN
ajst-19160	375	10	yan	yan	PROPN
ajst-19160	375	11	-	-	PROPN
ajst-19160	375	12	ping	ping	PROPN
ajst-19160	375	13	,	,	PUNCT
ajst-19160	375	14	y.	y.	PROPN
ajst-19160	375	15	xiao	xiao	PROPN
ajst-19160	375	16	-	-	PUNCT
ajst-19160	375	17	bing	bing	PROPN
ajst-19160	375	18	,	,	PUNCT
ajst-19160	375	19	g.	g.	PROPN
ajst-19160	375	20	chun	chun	PROPN
ajst-19160	375	21	-	-	PROPN
ajst-19160	375	22	tan	tan	PROPN
ajst-19160	375	23	,	,	PUNCT
ajst-19160	375	24	l.	l.	PROPN
ajst-19160	375	25	yong	yong	PROPN
ajst-19160	375	26	-	-	PUNCT
ajst-19160	375	27	hong	hong	PROPN
ajst-19160	375	28	,	,	PUNCT
ajst-19160	375	29	c.	c.	PROPN
ajst-19160	375	30	guo	guo	PROPN
ajst-19160	375	31	-	-	PUNCT
ajst-19160	375	32	ming	ming	PROPN
ajst-19160	375	33	,	,	PUNCT
ajst-19160	375	34	l.	l.	PROPN
ajst-19160	375	35	zeng	zeng	PROPN
ajst-19160	375	36	-	-	PUNCT
ajst-19160	375	37	kai	kai	PROPN
ajst-19160	375	38	,	,	PUNCT
ajst-19160	375	39	j.i	j.i	PROPN
ajst-19160	375	40	.	.	PROPN
ajst-19160	375	41	ren	ren	PROPN
ajst-19160	375	42	-	-	PUNCT
ajst-19160	375	43	jie	jie	PROPN
ajst-19160	375	44	,	,	PUNCT
ajst-19160	375	45	a	a	DET
ajst-19160	375	46	dynamic	dynamic	ADJ
ajst-19160	375	47	-	-	PUNCT
ajst-19160	375	48	bayesian	bayesian	NOUN
ajst-19160	375	49	-	-	PUNCT
ajst-19160	375	50	networks	network	NOUN
ajst-19160	375	51	-	-	PUNCT
ajst-19160	375	52	based	base	VERB
ajst-19160	375	53	resilience	resilience	NOUN
ajst-19160	375	54	assessment	assessment	NOUN
ajst-19160	375	55	approach	approach	NOUN
ajst-19160	375	56	of	of	ADP
ajst-19160	375	57	structure	structure	NOUN
ajst-19160	375	58	systems	system	NOUN
ajst-19160	375	59	:	:	PUNCT
ajst-19160	375	60	subsea	subsea	NOUN
ajst-19160	375	61	oil	oil	NOUN
ajst-19160	375	62	and	and	CCONJ
ajst-19160	375	63	gas	gas	NOUN
ajst-19160	375	64	pipelines	pipeline	NOUN
ajst-19160	375	65	as	as	ADP
ajst-19160	375	66	a	a	DET
ajst-19160	375	67	case	case	NOUN
ajst-19160	375	68	study	study	NOUN
ajst-19160	375	69	,	,	PUNCT
ajst-19160	375	70	china	china	PROPN
ajst-19160	375	71	ocean	ocean	PROPN
ajst-19160	375	72	engineering	engineering	PROPN
ajst-19160	375	73	,	,	PUNCT
ajst-19160	375	74	(	(	PUNCT
ajst-19160	375	75	2020	2020	NUM
ajst-19160	375	76	)	)	PUNCT
ajst-19160	375	77	597	597	NUM
ajst-19160	375	78	-	-	NUM
ajst-19160	375	79	607	607	NUM
ajst-19160	375	80	.	.	PUNCT
ajst-19160	376	1	[	[	X
ajst-19160	376	2	3	3	X
ajst-19160	376	3	]	]	PUNCT
ajst-19160	376	4	m.	m.	NOUN
ajst-19160	376	5	pourahmadi	pourahmadi	NOUN
ajst-19160	376	6	,	,	PUNCT
ajst-19160	376	7	m.	m.	NOUN
ajst-19160	376	8	saybani	saybani	NOUN
ajst-19160	376	9	,	,	PUNCT
ajst-19160	376	10	reliability	reliability	NOUN
ajst-19160	376	11	analysis	analysis	NOUN
ajst-19160	376	12	with	with	ADP
ajst-19160	376	13	corrosion	corrosion	NOUN
ajst-19160	376	14	defects	defect	NOUN
ajst-19160	376	15	in	in	ADP
ajst-19160	376	16	submarine	submarine	NOUN
ajst-19160	376	17	pipeline	pipeline	NOUN
ajst-19160	376	18	case	case	NOUN
ajst-19160	376	19	study	study	NOUN
ajst-19160	376	20	:	:	PUNCT
ajst-19160	376	21	oil	oil	NOUN
ajst-19160	376	22	pipeline	pipeline	NOUN
ajst-19160	376	23	in	in	ADP
ajst-19160	376	24	ab	ab	PROPN
ajst-19160	376	25	-	-	PUNCT
ajst-19160	376	26	khark	khark	PROPN
ajst-19160	376	27	island	island	NOUN
ajst-19160	376	28	.	.	PUNCT
ajst-19160	376	29	,	,	PUNCT
ajst-19160	376	30	ocean	ocean	PROPN
ajst-19160	376	31	engineering	engineering	NOUN
ajst-19160	376	32	,	,	PUNCT
ajst-19160	376	33	(	(	PUNCT
ajst-19160	376	34	2022	2022	NUM
ajst-19160	376	35	)	)	PUNCT
ajst-19160	376	36	.	.	PUNCT
ajst-19160	377	1	[	[	X
ajst-19160	377	2	4	4	X
ajst-19160	377	3	]	]	PUNCT
ajst-19160	377	4	l.	l.	PROPN
ajst-19160	377	5	zhang	zhang	PROPN
ajst-19160	377	6	,	,	PUNCT
ajst-19160	377	7	y.	y.	PROPN
ajst-19160	377	8	gao	gao	PROPN
ajst-19160	377	9	,	,	PUNCT
ajst-19160	377	10	improvement	improvement	NOUN
ajst-19160	377	11	of	of	ADP
ajst-19160	377	12	bp	bp	PROPN
ajst-19160	377	13	neural	neural	ADJ
ajst-19160	377	14	network	network	NOUN
ajst-19160	377	15	model	model	NOUN
ajst-19160	377	16	and	and	CCONJ
ajst-19160	377	17	its	its	PRON
ajst-19160	377	18	application	application	NOUN
ajst-19160	377	19	in	in	ADP
ajst-19160	377	20	predicting	predict	VERB
ajst-19160	377	21	external	external	ADJ
ajst-19160	377	22	corrosion	corrosion	NOUN
ajst-19160	377	23	rate	rate	NOUN
ajst-19160	377	24	of	of	ADP
ajst-19160	377	25	submarine	submarine	NOUN
ajst-19160	377	26	pipeline	pipeline	NOUN
ajst-19160	377	27	,	,	PUNCT
ajst-19160	377	28	journal	journal	NOUN
ajst-19160	377	29	of	of	ADP
ajst-19160	377	30	safety	safety	NOUN
ajst-19160	377	31	and	and	CCONJ
ajst-19160	377	32	environment	environment	NOUN
ajst-19160	377	33	,	,	PUNCT
ajst-19160	377	34	(	(	PUNCT
ajst-19160	377	35	2022	2022	NUM
ajst-19160	377	36	)	)	PUNCT
ajst-19160	377	37	.	.	PUNCT
ajst-19160	378	1	https://doi.org/10.13637/j.issn.1009-6094.2022.1608	https://doi.org/10.13637/j.issn.1009-6094.2022.1608	X
ajst-19160	378	2	.	.	PUNCT
ajst-19160	379	1	[	[	X
ajst-19160	379	2	5	5	X
ajst-19160	379	3	]	]	X
ajst-19160	379	4	j.a	j.a	PROPN
ajst-19160	379	5	.	.	PROPN
ajst-19160	379	6	gao	gao	PROPN
ajst-19160	379	7	,	,	PUNCT
ajst-19160	379	8	p.a	p.a	PROPN
ajst-19160	379	9	.	.	PROPN
ajst-19160	379	10	yang	yang	PROPN
ajst-19160	379	11	,	,	PUNCT
ajst-19160	379	12	x.a.l.d	x.a.l.d	PROPN
ajst-19160	379	13	.	.	PUNCT
ajst-19160	380	1	li	li	PROPN
ajst-19160	380	2	,	,	PUNCT
ajst-19160	380	3	j.a	j.a	PROPN
ajst-19160	380	4	.	.	PROPN
ajst-19160	380	5	zhou	zhou	PROPN
ajst-19160	380	6	,	,	PUNCT
ajst-19160	380	7	j.a	j.a	PROPN
ajst-19160	380	8	.	.	PROPN
ajst-19160	380	9	liu	liu	PROPN
ajst-19160	380	10	,	,	PUNCT
ajst-19160	380	11	analytical	analytical	ADJ
ajst-19160	380	12	prediction	prediction	NOUN
ajst-19160	380	13	of	of	ADP
ajst-19160	380	14	failure	failure	NOUN
ajst-19160	380	15	pressure	pressure	NOUN
ajst-19160	380	16	for	for	ADP
ajst-19160	380	17	pipeline	pipeline	NOUN
ajst-19160	380	18	with	with	ADP
ajst-19160	380	19	long	long	ADJ
ajst-19160	380	20	corrosion	corrosion	NOUN
ajst-19160	380	21	defect	defect	NOUN
ajst-19160	380	22	.	.	PUNCT
ajst-19160	380	23	,	,	PUNCT
ajst-19160	380	24	ocean	ocean	PROPN
ajst-19160	380	25	engineering	engineering	NOUN
ajst-19160	380	26	,	,	PUNCT
ajst-19160	380	27	(	(	PUNCT
ajst-19160	380	28	2019	2019	NUM
ajst-19160	380	29	)	)	PUNCT
ajst-19160	380	30	106497	106497	NUM
ajst-19160	380	31	.	.	PUNCT
ajst-19160	381	1	[	[	X
ajst-19160	381	2	6	6	NUM
ajst-19160	381	3	]	]	PUNCT
ajst-19160	381	4	m.	m.	NOUN
ajst-19160	381	5	abyani	abyani	NOUN
ajst-19160	381	6	,	,	PUNCT
ajst-19160	381	7	m.r	m.r	PROPN
ajst-19160	381	8	.	.	PROPN
ajst-19160	381	9	bahaari	bahaari	PROPN
ajst-19160	381	10	,	,	PUNCT
ajst-19160	381	11	a	a	DET
ajst-19160	381	12	new	new	ADJ
ajst-19160	381	13	approach	approach	NOUN
ajst-19160	381	14	for	for	ADP
ajst-19160	381	15	finite	finite	ADJ
ajst-19160	381	16	element	element	NOUN
ajst-19160	381	17	based	base	VERB
ajst-19160	381	18	reliability	reliability	NOUN
ajst-19160	381	19	evaluation	evaluation	NOUN
ajst-19160	381	20	of	of	ADP
ajst-19160	381	21	offshore	offshore	ADJ
ajst-19160	381	22	corroded	corroded	ADJ
ajst-19160	381	23	pipelines	pipeline	NOUN
ajst-19160	381	24	.	.	PUNCT
ajst-19160	381	25	,	,	PUNCT
ajst-19160	381	26	international	international	ADJ
ajst-19160	381	27	journal	journal	NOUN
ajst-19160	381	28	of	of	ADP
ajst-19160	381	29	pressure	pressure	NOUN
ajst-19160	381	30	vessels	vessel	NOUN
ajst-19160	381	31	&	&	CCONJ
ajst-19160	381	32	piping	piping	NOUN
ajst-19160	381	33	,	,	PUNCT
ajst-19160	381	34	(	(	PUNCT
ajst-19160	381	35	2021	2021	NUM
ajst-19160	381	36	)	)	PUNCT
ajst-19160	381	37	104449	104449	NUM
ajst-19160	381	38	.	.	PUNCT
ajst-19160	382	1	[	[	X
ajst-19160	382	2	7	7	X
ajst-19160	382	3	]	]	X
ajst-19160	382	4	m.	m.	NOUN
ajst-19160	382	5	sun	sun	PROPN
ajst-19160	382	6	,	,	PUNCT
ajst-19160	382	7	h.	h.	PROPN
ajst-19160	382	8	zhao	zhao	PROPN
ajst-19160	382	9	,	,	PUNCT
ajst-19160	382	10	x.	x.	PROPN
ajst-19160	382	11	li	li	PROPN
ajst-19160	382	12	,	,	PUNCT
ajst-19160	382	13	j.	j.	PROPN
ajst-19160	382	14	liu	liu	PROPN
ajst-19160	382	15	,	,	PUNCT
ajst-19160	382	16	z.	z.	PROPN
ajst-19160	382	17	xu	xu	PROPN
ajst-19160	382	18	,	,	PUNCT
ajst-19160	382	19	a	a	DET
ajst-19160	382	20	new	new	ADJ
ajst-19160	382	21	evaluation	evaluation	NOUN
ajst-19160	382	22	method	method	NOUN
ajst-19160	382	23	for	for	ADP
ajst-19160	382	24	burst	burst	ADJ
ajst-19160	382	25	pressure	pressure	NOUN
ajst-19160	382	26	of	of	ADP
ajst-19160	382	27	pipeline	pipeline	NOUN
ajst-19160	382	28	with	with	ADP
ajst-19160	382	29	colonies	colony	NOUN
ajst-19160	382	30	of	of	ADP
ajst-19160	382	31	circumferentially	circumferentially	ADV
ajst-19160	382	32	aligned	align	VERB
ajst-19160	382	33	defects	defect	NOUN
ajst-19160	382	34	.	.	PUNCT
ajst-19160	382	35	,	,	PUNCT
ajst-19160	382	36	ocean	ocean	PROPN
ajst-19160	382	37	engineering	engineering	NOUN
ajst-19160	382	38	,	,	PUNCT
ajst-19160	382	39	(	(	PUNCT
ajst-19160	382	40	2021	2021	NUM
ajst-19160	382	41	)	)	PUNCT
ajst-19160	382	42	108628	108628	NUM
ajst-19160	382	43	.	.	PUNCT
ajst-19160	383	1	[	[	X
ajst-19160	383	2	8	8	NUM
ajst-19160	383	3	]	]	X
ajst-19160	383	4	y.	y.	PROPN
ajst-19160	383	5	chen	chen	PROPN
ajst-19160	383	6	,	,	PUNCT
ajst-19160	383	7	f.	f.	PROPN
ajst-19160	383	8	hou	hou	PROPN
ajst-19160	383	9	,	,	PUNCT
ajst-19160	383	10	s.	s.	PROPN
ajst-19160	383	11	dong	dong	PROPN
ajst-19160	383	12	,	,	PUNCT
ajst-19160	383	13	l.	l.	PROPN
ajst-19160	383	14	guo	guo	PROPN
ajst-19160	383	15	,	,	PUNCT
ajst-19160	383	16	t.	t.	PROPN
ajst-19160	383	17	xia	xia	PROPN
ajst-19160	383	18	,	,	PUNCT
ajst-19160	383	19	g.	g.	PROPN
ajst-19160	383	20	he	he	PRON
ajst-19160	383	21	,	,	PUNCT
ajst-19160	383	22	reliability	reliability	NOUN
ajst-19160	383	23	evaluation	evaluation	NOUN
ajst-19160	383	24	of	of	ADP
ajst-19160	383	25	corroded	corroded	ADJ
ajst-19160	383	26	pipeline	pipeline	NOUN
ajst-19160	383	27	under	under	ADP
ajst-19160	383	28	combined	combine	VERB
ajst-19160	383	29	loadings	loading	NOUN
ajst-19160	383	30	based	base	VERB
ajst-19160	383	31	on	on	ADP
ajst-19160	383	32	back	back	ADJ
ajst-19160	383	33	propagation	propagation	NOUN
ajst-19160	383	34	neural	neural	ADJ
ajst-19160	383	35	network	network	NOUN
ajst-19160	383	36	method	method	NOUN
ajst-19160	383	37	,	,	PUNCT
ajst-19160	383	38	ocean	ocean	NOUN
ajst-19160	383	39	engineering	engineering	NOUN
ajst-19160	383	40	,	,	PUNCT
ajst-19160	383	41	(	(	PUNCT
ajst-19160	383	42	2022	2022	NUM
ajst-19160	383	43	)	)	PUNCT
ajst-19160	383	44	111910	111910	NUM
ajst-19160	383	45	.	.	PUNCT
ajst-19160	384	1	[	[	X
ajst-19160	384	2	9	9	NUM
ajst-19160	384	3	]	]	PUNCT
ajst-19160	384	4	b.	b.	PROPN
ajst-19160	384	5	ma	ma	PROPN
ajst-19160	384	6	,	,	PUNCT
ajst-19160	384	7	j.	j.	PROPN
ajst-19160	384	8	shuai	shuai	PROPN
ajst-19160	384	9	,	,	PUNCT
ajst-19160	384	10	j.	j.	PROPN
ajst-19160	384	11	wang	wang	PROPN
ajst-19160	384	12	,	,	PUNCT
ajst-19160	384	13	k.	k.	PROPN
ajst-19160	384	14	han	han	PROPN
ajst-19160	384	15	,	,	PUNCT
ajst-19160	384	16	analysis	analysis	NOUN
ajst-19160	384	17	on	on	ADP
ajst-19160	384	18	the	the	DET
ajst-19160	384	19	latest	late	ADJ
ajst-19160	384	20	assessment	assessment	NOUN
ajst-19160	384	21	criteria	criterion	NOUN
ajst-19160	384	22	of	of	ADP
ajst-19160	384	23	asme	asme	PROPN
ajst-19160	384	24	b31g-2009	b31g-2009	PROPN
ajst-19160	384	25	for	for	ADP
ajst-19160	384	26	the	the	DET
ajst-19160	384	27	remaining	remain	VERB
ajst-19160	384	28	strength	strength	NOUN
ajst-19160	384	29	of	of	ADP
ajst-19160	384	30	corroded	corroded	ADJ
ajst-19160	384	31	pipelines	pipeline	NOUN
ajst-19160	384	32	,	,	PUNCT
ajst-19160	384	33	journal	journal	NOUN
ajst-19160	384	34	of	of	ADP
ajst-19160	384	35	failure	failure	NOUN
ajst-19160	384	36	analysis	analysis	NOUN
ajst-19160	384	37	and	and	CCONJ
ajst-19160	384	38	prevention	prevention	NOUN
ajst-19160	384	39	,	,	PUNCT
ajst-19160	384	40	(	(	PUNCT
ajst-19160	384	41	2011	2011	NUM
ajst-19160	384	42	)	)	PUNCT
ajst-19160	384	43	666	666	NUM
ajst-19160	384	44	-	-	NUM
ajst-19160	384	45	671	671	NUM
ajst-19160	384	46	.	.	PUNCT
ajst-19160	385	1	[	[	X
ajst-19160	385	2	10	10	NUM
ajst-19160	385	3	]	]	X
ajst-19160	385	4	r.	r.	PROPN
ajst-19160	385	5	zhou	zhou	PROPN
ajst-19160	385	6	,	,	PUNCT
ajst-19160	385	7	x.	x.	PROPN
ajst-19160	385	8	gu	gu	PROPN
ajst-19160	385	9	,	,	PUNCT
ajst-19160	385	10	x.	x.	PROPN
ajst-19160	385	11	luo	luo	PROPN
ajst-19160	385	12	,	,	PUNCT
ajst-19160	385	13	residual	residual	ADJ
ajst-19160	385	14	strength	strength	NOUN
ajst-19160	385	15	prediction	prediction	NOUN
ajst-19160	385	16	of	of	ADP
ajst-19160	385	17	x80	x80	PROPN
ajst-19160	385	18	steel	steel	NOUN
ajst-19160	385	19	pipelines	pipeline	NOUN
ajst-19160	385	20	containing	contain	VERB
ajst-19160	385	21	group	group	NOUN
ajst-19160	385	22	corrosion	corrosion	NOUN
ajst-19160	385	23	defects	defect	NOUN
ajst-19160	385	24	,	,	PUNCT
ajst-19160	385	25	ocean	ocean	NOUN
ajst-19160	385	26	engineering	engineering	NOUN
ajst-19160	385	27	,	,	PUNCT
ajst-19160	385	28	(	(	PUNCT
ajst-19160	385	29	2023	2023	NUM
ajst-19160	385	30	)	)	PUNCT
ajst-19160	385	31	114077	114077	NUM
ajst-19160	385	32	.	.	PUNCT
ajst-19160	386	1	[	[	X
ajst-19160	386	2	11	11	NUM
ajst-19160	386	3	]	]	SYM
ajst-19160	386	4	b.m.b	b.m.b	NOUN
ajst-19160	386	5	.	.	PUNCT
ajst-19160	387	1	ma	ma	PROPN
ajst-19160	387	2	,	,	PUNCT
ajst-19160	387	3	j.s.j	j.s.j	PROPN
ajst-19160	387	4	.	.	PROPN
ajst-19160	387	5	shuai	shuai	PROPN
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ajst-19160	387	8	.	.	PUNCT
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ajst-19160	388	2	,	,	PUNCT
ajst-19160	388	3	k.x.k	k.x.k	PROPN
ajst-19160	388	4	.	.	PUNCT
ajst-19160	388	5	xu	xu	PROPN
ajst-19160	388	6	,	,	PUNCT
ajst-19160	388	7	assessment	assessment	NOUN
ajst-19160	388	8	on	on	ADP
ajst-19160	388	9	failure	failure	NOUN
ajst-19160	388	10	pressure	pressure	NOUN
ajst-19160	388	11	of	of	ADP
ajst-19160	388	12	high	high	ADJ
ajst-19160	388	13	strength	strength	NOUN
ajst-19160	388	14	pipeline	pipeline	NOUN
ajst-19160	388	15	with	with	ADP
ajst-19160	388	16	corrosion	corrosion	NOUN
ajst-19160	388	17	defects	defect	NOUN
ajst-19160	388	18	,	,	PUNCT
ajst-19160	388	19	engineering	engineering	NOUN
ajst-19160	388	20	failure	failure	NOUN
ajst-19160	388	21	analysis	analysis	NOUN
ajst-19160	388	22	,	,	PUNCT
ajst-19160	388	23	(	(	PUNCT
ajst-19160	388	24	2013	2013	NUM
ajst-19160	388	25	)	)	PUNCT
ajst-19160	388	26	209219	209219	NUM
ajst-19160	388	27	.	.	PUNCT
ajst-19160	389	1	[	[	X
ajst-19160	389	2	12	12	NUM
ajst-19160	389	3	]	]	X
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ajst-19160	389	6	,	,	PUNCT
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ajst-19160	389	8	.	.	PROPN
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ajst-19160	389	14	j.	j.	PROPN
ajst-19160	389	15	lee	lee	PROPN
ajst-19160	389	16	,	,	PUNCT
ajst-19160	389	17	corroded	corroded	ADJ
ajst-19160	389	18	pipeline	pipeline	NOUN
ajst-19160	389	19	failure	failure	NOUN
ajst-19160	389	20	analysis	analysis	NOUN
ajst-19160	389	21	using	use	VERB
ajst-19160	389	22	artificial	artificial	ADJ
ajst-19160	389	23	neural	neural	ADJ
ajst-19160	389	24	network	network	NOUN
ajst-19160	389	25	scheme	scheme	NOUN
ajst-19160	389	26	,	,	PUNCT
ajst-19160	389	27	advances	advance	NOUN
ajst-19160	389	28	in	in	ADP
ajst-19160	389	29	engineering	engineering	NOUN
ajst-19160	389	30	software	software	NOUN
ajst-19160	389	31	,	,	PUNCT
ajst-19160	389	32	(	(	PUNCT
ajst-19160	389	33	2017	2017	NUM
ajst-19160	389	34	)	)	PUNCT
ajst-19160	389	35	255	255	NUM
ajst-19160	389	36	-	-	SYM
ajst-19160	389	37	266	266	NUM
ajst-19160	389	38	.	.	PUNCT
ajst-19160	390	1	[	[	X
ajst-19160	390	2	13	13	NUM
ajst-19160	390	3	]	]	X
ajst-19160	390	4	k.y	k.y	PROPN
ajst-19160	390	5	.	.	PROPN
ajst-19160	390	6	kang	kang	PROPN
ajst-19160	390	7	,	,	PUNCT
ajst-19160	390	8	2022	2022	NUM
ajst-19160	390	9	.	.	PUNCT
ajst-19160	391	1	research	research	NOUN
ajst-19160	391	2	on	on	ADP
ajst-19160	391	3	residual	residual	ADJ
ajst-19160	391	4	strength	strength	NOUN
ajst-19160	391	5	of	of	ADP
ajst-19160	391	6	corrosion	corrosion	NOUN
ajst-19160	391	7	defect	defect	NOUN
ajst-19160	391	8	pressure	pressure	NOUN
ajst-19160	391	9	piping	piping	NOUN
ajst-19160	391	10	based	base	VERB
ajst-19160	391	11	on	on	ADP
ajst-19160	391	12	ansys	ansys	PROPN
ajst-19160	391	13	.	.	PUNCT
ajst-19160	392	1	shenyang	shenyang	PROPN
ajst-19160	392	2	university	university	PROPN
ajst-19160	392	3	of	of	ADP
ajst-19160	392	4	chemical	chemical	PROPN
ajst-19160	392	5	technology	technology	NOUN
ajst-19160	392	6	.	.	PUNCT
ajst-19160	393	1	https://kns.cnki.net/kcms/detail/detail.aspx?dbname=cmfd	https://kns.cnki.net/kcms/detail/detail.aspx?dbname=cmfd	X
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ajst-19160	394	1	[	[	X
ajst-19160	394	2	14	14	NUM
ajst-19160	394	3	]	]	X
ajst-19160	394	4	s.j	s.j	PROPN
ajst-19160	394	5	.	.	PROPN
ajst-19160	394	6	zhao	zhao	PROPN
ajst-19160	394	7	,	,	PUNCT
ajst-19160	394	8	s.l	s.l	PROPN
ajst-19160	394	9	.	.	PROPN
ajst-19160	394	10	ma	ma	PROPN
ajst-19160	394	11	,	,	PUNCT
ajst-19160	394	12	m.c	m.c	PROPN
ajst-19160	394	13	.	.	PROPN
ajst-19160	394	14	wang	wang	PROPN
ajst-19160	394	15	,	,	PUNCT
ajst-19160	394	16	super	super	ADJ
ajst-19160	394	17	parameter	parameter	NOUN
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ajst-19160	394	19	of	of	ADP
ajst-19160	394	20	elm	elm	NOUN
ajst-19160	394	21	by	by	ADP
ajst-19160	394	22	artificial	artificial	ADJ
ajst-19160	394	23	ecosystem	ecosystem	NOUN
ajst-19160	394	24	-	-	PUNCT
ajst-19160	394	25	based	base	VERB
ajst-19160	394	26	optimization	optimization	NOUN
ajst-19160	394	27	with	with	ADP
ajst-19160	394	28	crowding	crowd	VERB
ajst-19160	394	29	forward	forward	ADV
ajst-19160	394	30	-	-	PUNCT
ajst-19160	394	31	backward	backward	ADJ
ajst-19160	394	32	and	and	CCONJ
ajst-19160	394	33	backtracking	backtrack	VERB
ajst-19160	394	34	tips	tip	NOUN
ajst-19160	394	35	.	.	PUNCT
ajst-19160	395	1	control	control	NOUN
ajst-19160	395	2	and	and	CCONJ
ajst-19160	395	3	decision	decision	NOUN
ajst-19160	395	4	,	,	PUNCT
ajst-19160	395	5	(	(	PUNCT
ajst-19160	395	6	2022	2022	NUM
ajst-19160	395	7	)	)	PUNCT
ajst-19160	395	8	https://kns.cnki.net/kcms/detail/21.1124.tp.20220301.0948.005.html	https://kns.cnki.net/kcms/detail/21.1124.tp.20220301.0948.005.html	VERB
ajst-19160	396	1	[	[	X
ajst-19160	396	2	15	15	NUM
ajst-19160	396	3	]	]	X
ajst-19160	396	4	d.	d.	PROPN
ajst-19160	396	5	oh	oh	INTJ
ajst-19160	396	6	,	,	PUNCT
ajst-19160	396	7	j.	j.	PROPN
ajst-19160	396	8	race	race	PROPN
ajst-19160	396	9	,	,	PUNCT
ajst-19160	396	10	s.o.a.b	s.o.a.b	PROPN
ajst-19160	396	11	.	.	PROPN
ajst-19160	396	12	koo	koo	PROPN
ajst-19160	396	13	,	,	PUNCT
ajst-19160	396	14	burst	burst	ADJ
ajst-19160	396	15	pressure	pressure	NOUN
ajst-19160	396	16	prediction	prediction	NOUN
ajst-19160	396	17	of	of	ADP
ajst-19160	396	18	api	api	NOUN
ajst-19160	396	19	5l	5l	NUM
ajst-19160	396	20	x	x	ADJ
ajst-19160	396	21	-	-	ADJ
ajst-19160	396	22	grade	grade	ADJ
ajst-19160	396	23	dented	dent	VERB
ajst-19160	396	24	pipelines	pipeline	NOUN
ajst-19160	396	25	using	use	VERB
ajst-19160	396	26	deep	deep	ADJ
ajst-19160	396	27	neural	neural	ADJ
ajst-19160	396	28	network	network	NOUN
ajst-19160	396	29	,	,	PUNCT
ajst-19160	396	30	journal	journal	NOUN
ajst-19160	396	31	of	of	ADP
ajst-19160	396	32	marine	marine	PROPN
ajst-19160	396	33	science	science	NOUN
ajst-19160	396	34	and	and	CCONJ
ajst-19160	396	35	engineering	engineering	NOUN
ajst-19160	396	36	,	,	PUNCT
ajst-19160	396	37	(	(	PUNCT
ajst-19160	396	38	2020	2020	NUM
ajst-19160	396	39	)	)	PUNCT
ajst-19160	396	40	766	766	NUM
ajst-19160	396	41	.	.	PUNCT
ajst-19160	397	1	[	[	X
ajst-19160	397	2	16	16	NUM
ajst-19160	397	3	]	]	X
ajst-19160	397	4	r.c.c	r.c.c	NOUN
ajst-19160	397	5	.	.	PUNCT
ajst-19160	397	6	silva	silva	PROPN
ajst-19160	397	7	,	,	PUNCT
ajst-19160	397	8	j.n.c	j.n.c	PROPN
ajst-19160	397	9	.	.	PUNCT
ajst-19160	398	1	guerreiro	guerreiro	PROPN
ajst-19160	398	2	,	,	PUNCT
ajst-19160	398	3	a.f.d	a.f.d	NOUN
ajst-19160	398	4	.	.	PUNCT
ajst-19160	399	1	loula	loula	PROPN
ajst-19160	399	2	,	,	PUNCT
ajst-19160	399	3	a	a	DET
ajst-19160	399	4	study	study	NOUN
ajst-19160	399	5	of	of	ADP
ajst-19160	399	6	pipe	pipe	NOUN
ajst-19160	399	7	interacting	interact	VERB
ajst-19160	399	8	corrosion	corrosion	NOUN
ajst-19160	399	9	defects	defect	NOUN
ajst-19160	399	10	using	use	VERB
ajst-19160	399	11	the	the	DET
ajst-19160	399	12	fem	fem	NOUN
ajst-19160	399	13	and	and	CCONJ
ajst-19160	399	14	neural	neural	ADJ
ajst-19160	399	15	networks	network	NOUN
ajst-19160	399	16	,	,	PUNCT
ajst-19160	399	17	advances	advance	NOUN
ajst-19160	399	18	in	in	ADP
ajst-19160	399	19	engineering	engineering	NOUN
ajst-19160	399	20	software	software	NOUN
ajst-19160	399	21	,	,	PUNCT
ajst-19160	399	22	(	(	PUNCT
ajst-19160	399	23	2007	2007	NUM
ajst-19160	399	24	)	)	PUNCT
ajst-19160	399	25	868	868	NUM
ajst-19160	399	26	-	-	SYM
ajst-19160	399	27	875	875	NUM
ajst-19160	399	28	.	.	PUNCT
ajst-19160	400	1	[	[	X
ajst-19160	400	2	17	17	NUM
ajst-19160	400	3	]	]	X
ajst-19160	400	4	v.	v.	X
ajst-19160	400	5	chauhan	chauhan	PROPN
ajst-19160	400	6	,	,	PUNCT
ajst-19160	400	7	advances	advance	NOUN
ajst-19160	400	8	in	in	ADP
ajst-19160	400	9	interaction	interaction	NOUN
ajst-19160	400	10	rules	rule	NOUN
ajst-19160	400	11	for	for	ADP
ajst-19160	400	12	corrosion	corrosion	NOUN
ajst-19160	400	13	defects	defect	NOUN
ajst-19160	400	14	in	in	ADP
ajst-19160	400	15	pipelines	pipeline	NOUN
ajst-19160	400	16	.	.	PUNCT
ajst-19160	401	1	in	in	ADP
ajst-19160	401	2	:	:	PUNCT
ajst-19160	401	3	proceedings	proceeding	NOUN
ajst-19160	401	4	of	of	ADP
ajst-19160	401	5	the	the	DET
ajst-19160	401	6	international	international	ADJ
ajst-19160	401	7	gas	gas	NOUN
ajst-19160	401	8	research	research	NOUN
ajst-19160	401	9	conference	conference	NOUN
ajst-19160	401	10	,	,	PUNCT
ajst-19160	401	11	(	(	PUNCT
ajst-19160	401	12	2004	2004	NUM
ajst-19160	401	13	)	)	PUNCT
ajst-19160	401	14	.	.	PUNCT
ajst-19160	402	1	vancouver	vancouver	PROPN
ajst-19160	402	2	,	,	PUNCT
ajst-19160	402	3	canada	canada	PROPN
ajst-19160	402	4	.	.	PUNCT
ajst-19160	403	1	[	[	X
ajst-19160	403	2	18	18	NUM
ajst-19160	403	3	]	]	X
ajst-19160	403	4	y.	y.	PROPN
ajst-19160	403	5	xü	xü	PROPN
ajst-19160	403	6	,	,	PUNCT
ajst-19160	403	7	a.	a.	NOUN
ajst-19160	403	8	fenerci	fenerci	PROPN
ajst-19160	403	9	,	,	PUNCT
ajst-19160	403	10	o.a	o.a	PROPN
ajst-19160	403	11	.	.	PROPN
ajst-19160	403	12	øiseth	øiseth	PROPN
ajst-19160	403	13	,	,	PUNCT
ajst-19160	403	14	t.	t.	PROPN
ajst-19160	403	15	moan	moan	NOUN
ajst-19160	403	16	,	,	PUNCT
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ajst-19160	403	18	prediction	prediction	NOUN
ajst-19160	403	19	of	of	ADP
ajst-19160	403	20	wind	wind	NOUN
ajst-19160	403	21	and	and	CCONJ
ajst-19160	403	22	wave	wave	NOUN
ajst-19160	403	23	induced	induce	VERB
ajst-19160	403	24	long	long	ADJ
ajst-19160	403	25	-	-	PUNCT
ajst-19160	403	26	term	term	NOUN
ajst-19160	403	27	extreme	extreme	ADJ
ajst-19160	403	28	load	load	NOUN
ajst-19160	403	29	effects	effect	NOUN
ajst-19160	403	30	of	of	ADP
ajst-19160	403	31	floating	float	VERB
ajst-19160	403	32	suspension	suspension	NOUN
ajst-19160	403	33	bridges	bridge	NOUN
ajst-19160	403	34	using	use	VERB
ajst-19160	403	35	artificial	artificial	ADJ
ajst-19160	403	36	neural	neural	ADJ
ajst-19160	403	37	networks	network	NOUN
ajst-19160	403	38	and	and	CCONJ
ajst-19160	403	39	support	support	VERB
ajst-19160	403	40	vector	vector	PROPN
ajst-19160	403	41	machines(article	machines(article	PROPN
ajst-19160	403	42	)	)	PUNCT
ajst-19160	403	43	,	,	PUNCT
ajst-19160	403	44	ocean	ocean	NOUN
ajst-19160	403	45	engineering	engineering	NOUN
ajst-19160	403	46	,	,	PUNCT
ajst-19160	403	47	(	(	PUNCT
ajst-19160	403	48	2020	2020	NUM
ajst-19160	403	49	)	)	PUNCT
ajst-19160	403	50	107888	107888	NUM
ajst-19160	403	51	.	.	PUNCT
ajst-19160	404	1	[	[	X
ajst-19160	404	2	19	19	NUM
ajst-19160	404	3	]	]	X
ajst-19160	404	4	a.j	a.j	PROPN
ajst-19160	404	5	.	.	PROPN
ajst-19160	404	6	smola	smola	PROPN
ajst-19160	404	7	,	,	PUNCT
ajst-19160	404	8	b.	b.	PROPN
ajst-19160	404	9	scholkopf	scholkopf	PROPN
ajst-19160	404	10	,	,	PUNCT
ajst-19160	404	11	a	a	DET
ajst-19160	404	12	tutorial	tutorial	NOUN
ajst-19160	404	13	on	on	ADP
ajst-19160	404	14	support	support	NOUN
ajst-19160	404	15	vector	vector	NOUN
ajst-19160	404	16	regression	regression	NOUN
ajst-19160	404	17	,	,	PUNCT
ajst-19160	404	18	statistics	statistic	NOUN
ajst-19160	404	19	and	and	CCONJ
ajst-19160	404	20	computing	computing	NOUN
ajst-19160	404	21	,	,	PUNCT
ajst-19160	404	22	(	(	PUNCT
ajst-19160	404	23	2004	2004	NUM
ajst-19160	404	24	)	)	PUNCT
ajst-19160	404	25	199222	199222	NUM
ajst-19160	404	26	.	.	PUNCT
ajst-19160	405	1	[	[	X
ajst-19160	405	2	20	20	NUM
ajst-19160	405	3	]	]	PUNCT
ajst-19160	405	4	a.m.	a.m.	PROPN
ajst-19160	405	5	andrew	andrew	PROPN
ajst-19160	405	6	,	,	PUNCT
ajst-19160	405	7	an	an	DET
ajst-19160	405	8	introduction	introduction	NOUN
ajst-19160	405	9	to	to	PART
ajst-19160	405	10	support	support	VERB
ajst-19160	405	11	vector	vector	NOUN
ajst-19160	405	12	machines	machine	NOUN
ajst-19160	405	13	and	and	CCONJ
ajst-19160	405	14	other	other	ADJ
ajst-19160	405	15	kernel‐based	kernel‐based	ADJ
ajst-19160	405	16	learning	learning	NOUN
ajst-19160	405	17	methods	method	NOUN
ajst-19160	405	18	,	,	PUNCT
ajst-19160	405	19	kybernetes	kybernete	NOUN
ajst-19160	405	20	,	,	PUNCT
ajst-19160	405	21	(	(	PUNCT
ajst-19160	405	22	2001	2001	NUM
ajst-19160	405	23	)	)	PUNCT
ajst-19160	405	24	103	103	NUM
ajst-19160	405	25	-	-	SYM
ajst-19160	405	26	115	115	NUM
ajst-19160	405	27	.	.	PUNCT
ajst-19160	406	1	[	[	X
ajst-19160	406	2	21	21	NUM
ajst-19160	406	3	]	]	X
ajst-19160	406	4	c.j	c.j	PROPN
ajst-19160	406	5	.	.	PROPN
ajst-19160	406	6	evans	evans	PROPN
ajst-19160	406	7	,	,	PUNCT
ajst-19160	406	8	t.f	t.f	PROPN
ajst-19160	406	9	.	.	PROPN
ajst-19160	406	10	miller	miller	PROPN
ajst-19160	406	11	,	,	PUNCT
ajst-19160	406	12	failure	failure	NOUN
ajst-19160	406	13	prediction	prediction	NOUN
ajst-19160	406	14	of	of	ADP
ajst-19160	406	15	pressure	pressure	NOUN
ajst-19160	406	16	vessels	vessel	NOUN
ajst-19160	406	17	using	use	VERB
ajst-19160	406	18	finite	finite	PROPN
ajst-19160	406	19	element	element	PROPN
ajst-19160	406	20	analysis(article	analysis(article	PROPN
ajst-19160	406	21	)	)	PUNCT
ajst-19160	406	22	,	,	PUNCT
ajst-19160	406	23	journal	journal	NOUN
ajst-19160	406	24	of	of	ADP
ajst-19160	406	25	pressure	pressure	NOUN
ajst-19160	406	26	vessel	vessel	NOUN
ajst-19160	406	27	technology	technology	NOUN
ajst-19160	406	28	,	,	PUNCT
ajst-19160	406	29	transactions	transaction	NOUN
ajst-19160	406	30	of	of	ADP
ajst-19160	406	31	the	the	DET
ajst-19160	406	32	asme	asme	PROPN
ajst-19160	406	33	,	,	PUNCT
ajst-19160	406	34	(	(	PUNCT
ajst-19160	406	35	2015	2015	NUM
ajst-19160	406	36	)	)	PUNCT
ajst-19160	406	37	51206	51206	NUM
ajst-19160	406	38	.	.	PUNCT
ajst-19160	407	1	[	[	X
ajst-19160	407	2	22	22	NUM
ajst-19160	407	3	]	]	PUNCT
ajst-19160	407	4	m.	m.	NOUN
ajst-19160	407	5	abyani	abyani	PROPN
ajst-19160	407	6	,	,	PUNCT
ajst-19160	407	7	m.r	m.r	PROPN
ajst-19160	407	8	.	.	PROPN
ajst-19160	407	9	bahaari	bahaari	PROPN
ajst-19160	407	10	,	,	PUNCT
ajst-19160	407	11	m.	m.	NOUN
ajst-19160	407	12	zarrin	zarrin	PROPN
ajst-19160	407	13	,	,	PUNCT
ajst-19160	407	14	m.	m.	NOUN
ajst-19160	407	15	nasseri	nasseri	PROPN
ajst-19160	407	16	,	,	PUNCT
ajst-19160	407	17	predicting	predict	VERB
ajst-19160	407	18	failure	failure	NOUN
ajst-19160	407	19	pressure	pressure	NOUN
ajst-19160	407	20	of	of	ADP
ajst-19160	407	21	the	the	DET
ajst-19160	407	22	corroded	corroded	ADJ
ajst-19160	407	23	offshore	offshore	ADJ
ajst-19160	407	24	pipelines	pipeline	NOUN
ajst-19160	407	25	using	use	VERB
ajst-19160	407	26	an	an	DET
ajst-19160	407	27	efficient	efficient	ADJ
ajst-19160	407	28	finite	finite	NOUN
ajst-19160	407	29	element	element	NOUN
ajst-19160	407	30	based	base	VERB
ajst-19160	407	31	algorithm	algorithm	NOUN
ajst-19160	407	32	and	and	CCONJ
ajst-19160	407	33	machine	machine	NOUN
ajst-19160	407	34	learning	learn	VERB
ajst-19160	407	35	techniques	technique	NOUN
ajst-19160	407	36	.	.	PUNCT
ajst-19160	407	37	,	,	PUNCT
ajst-19160	407	38	ocean	ocean	PROPN
ajst-19160	407	39	engineering	engineering	NOUN
ajst-19160	407	40	,	,	PUNCT
ajst-19160	407	41	(	(	PUNCT
ajst-19160	407	42	2022	2022	NUM
ajst-19160	407	43	)	)	PUNCT
ajst-19160	407	44	111382	111382	NUM
ajst-19160	407	45	.	.	PUNCT
ajst-19160	408	1	[	[	X
ajst-19160	408	2	23	23	NUM
ajst-19160	408	3	]	]	X
ajst-19160	408	4	s.	s.	PROPN
ajst-19160	408	5	sain	sain	PROPN
ajst-19160	408	6	,	,	PUNCT
ajst-19160	408	7	the	the	DET
ajst-19160	408	8	nature	nature	NOUN
ajst-19160	408	9	of	of	ADP
ajst-19160	408	10	statistical	statistical	ADJ
ajst-19160	408	11	learning	learning	NOUN
ajst-19160	408	12	theory	theory	NOUN
ajst-19160	408	13	,	,	PUNCT
ajst-19160	408	14	technometrics	technometric	NOUN
ajst-19160	408	15	,	,	PUNCT
ajst-19160	408	16	(	(	PUNCT
ajst-19160	408	17	1996	1996	NUM
ajst-19160	408	18	)	)	PUNCT
ajst-19160	408	19	409	409	NUM
ajst-19160	408	20	.	.	PUNCT
ajst-19160	409	1	[	[	X
ajst-19160	409	2	24	24	NUM
ajst-19160	409	3	]	]	PUNCT
ajst-19160	409	4	w.	w.	PROPN
ajst-19160	409	5	zhao	zhao	PROPN
ajst-19160	409	6	,	,	PUNCT
ajst-19160	409	7	l.	l.	PROPN
ajst-19160	409	8	wang	wang	PROPN
ajst-19160	409	9	,	,	PUNCT
ajst-19160	409	10	z.	z.	PROPN
ajst-19160	409	11	zhang	zhang	PROPN
ajst-19160	409	12	,	,	PUNCT
ajst-19160	409	13	artificial	artificial	ADJ
ajst-19160	409	14	ecosystem	ecosystem	NOUN
ajst-19160	409	15	-	-	PUNCT
ajst-19160	409	16	based	base	VERB
ajst-19160	409	17	optimization	optimization	NOUN
ajst-19160	409	18	:	:	PUNCT
ajst-19160	409	19	a	a	DET
ajst-19160	409	20	novel	novel	ADJ
ajst-19160	409	21	nature	nature	NOUN
ajst-19160	409	22	-	-	PUNCT
ajst-19160	409	23	inspired	inspire	VERB
ajst-19160	409	24	meta	meta	ADJ
ajst-19160	409	25	-	-	PUNCT
ajst-19160	409	26	heuristic	heuristic	ADJ
ajst-19160	409	27	algorithm	algorithm	NOUN
ajst-19160	409	28	,	,	PUNCT
ajst-19160	409	29	neural	neural	ADJ
ajst-19160	409	30	computing	computing	NOUN
ajst-19160	409	31	and	and	CCONJ
ajst-19160	409	32	applications	application	NOUN
ajst-19160	409	33	,	,	PUNCT
ajst-19160	409	34	(	(	PUNCT
ajst-19160	409	35	2020	2020	NUM
ajst-19160	409	36	)	)	PUNCT
ajst-19160	409	37	9383	9383	NUM
ajst-19160	409	38	-	-	SYM
ajst-19160	409	39	9425	9425	NUM
ajst-19160	409	40	.	.	PUNCT
ajst-19160	410	1	[	[	X
ajst-19160	410	2	25	25	NUM
ajst-19160	410	3	]	]	X
ajst-19160	410	4	h.r	h.r	PROPN
ajst-19160	410	5	.	.	PROPN
ajst-19160	410	6	tizhoosh	tizhoosh	PROPN
ajst-19160	410	7	,	,	PUNCT
ajst-19160	410	8	opposition	opposition	NOUN
ajst-19160	410	9	-	-	PUNCT
ajst-19160	410	10	based	base	VERB
ajst-19160	410	11	learning	learning	NOUN
ajst-19160	410	12	:	:	PUNCT
ajst-19160	410	13	a	a	DET
ajst-19160	410	14	new	new	ADJ
ajst-19160	410	15	scheme	scheme	NOUN
ajst-19160	410	16	for	for	ADP
ajst-19160	410	17	machine	machine	NOUN
ajst-19160	410	18	intelligence	intelligence	NOUN
ajst-19160	410	19	,	,	PUNCT
ajst-19160	410	20	international	international	ADJ
ajst-19160	410	21	conference	conference	NOUN
ajst-19160	410	22	on	on	ADP
ajst-19160	410	23	computational	computational	ADJ
ajst-19160	410	24	intelligence	intelligence	NOUN
ajst-19160	410	25	for	for	ADP
ajst-19160	410	26	modelling	modelling	NOUN
ajst-19160	410	27	,	,	PUNCT
ajst-19160	410	28	control	control	NOUN
ajst-19160	410	29	and	and	CCONJ
ajst-19160	410	30	automation	automation	NOUN
ajst-19160	410	31	and	and	CCONJ
ajst-19160	410	32	international	international	ADJ
ajst-19160	410	33	conference	conference	NOUN
ajst-19160	410	34	on	on	ADP
ajst-19160	410	35	intelligent	intelligent	ADJ
ajst-19160	410	36	agents	agent	NOUN
ajst-19160	410	37	,	,	PUNCT
ajst-19160	410	38	web	web	NOUN
ajst-19160	410	39	technologies	technology	NOUN
ajst-19160	410	40	and	and	CCONJ
ajst-19160	410	41	internet	internet	NOUN
ajst-19160	410	42	commerce	commerce	NOUN
ajst-19160	410	43	(	(	PUNCT
ajst-19160	410	44	cimcaiawtic'06	cimcaiawtic'06	PROPN
ajst-19160	410	45	)	)	PUNCT
ajst-19160	410	46	,	,	PUNCT
ajst-19160	410	47	vienna	vienna	PROPN
ajst-19160	410	48	,	,	PUNCT
ajst-19160	410	49	austria	austria	PROPN
ajst-19160	410	50	,	,	PUNCT
ajst-19160	410	51	2005	2005	NUM
ajst-19160	410	52	.	.	PUNCT
ajst-19160	411	1	[	[	X
ajst-19160	411	2	26	26	NUM
ajst-19160	411	3	]	]	X
ajst-19160	411	4	g.	g.	PROPN
ajst-19160	411	5	louppe	louppe	PROPN
ajst-19160	411	6	,	,	PUNCT
ajst-19160	411	7	understanding	understand	VERB
ajst-19160	411	8	random	random	ADJ
ajst-19160	411	9	forests	forest	NOUN
ajst-19160	411	10	:	:	PUNCT
ajst-19160	411	11	from	from	ADP
ajst-19160	411	12	theory	theory	NOUN
ajst-19160	411	13	to	to	ADP
ajst-19160	411	14	practice	practice	NOUN
ajst-19160	411	15	,	,	PUNCT
ajst-19160	411	16	university	university	NOUN
ajst-19160	411	17	of	of	ADP
ajst-19160	411	18	liège	liège	PROPN
ajst-19160	411	19	,	,	PUNCT
ajst-19160	411	20	2014	2014	NUM
ajst-19160	411	21	.	.	PUNCT
ajst-19160	412	1	[	[	X
ajst-19160	412	2	27	27	NUM
ajst-19160	412	3	]	]	X
ajst-19160	412	4	y.	y.	PROPN
ajst-19160	412	5	mahmutoglu	mahmutoglu	PROPN
ajst-19160	412	6	,	,	PUNCT
ajst-19160	412	7	k.	k.	PROPN
ajst-19160	412	8	turk	turk	PROPN
ajst-19160	412	9	,	,	PUNCT
ajst-19160	412	10	positioning	positioning	NOUN
ajst-19160	412	11	of	of	ADP
ajst-19160	412	12	leakages	leakage	NOUN
ajst-19160	412	13	in	in	ADP
ajst-19160	412	14	underwater	underwater	ADJ
ajst-19160	412	15	natural	natural	ADJ
ajst-19160	412	16	gas	gas	NOUN
ajst-19160	412	17	pipelines	pipeline	NOUN
ajst-19160	412	18	for	for	ADP
ajst-19160	412	19	time	time	NOUN
ajst-19160	412	20	-	-	PUNCT
ajst-19160	412	21	varying	vary	VERB
ajst-19160	412	22	multipath	multipath	NOUN
ajst-19160	412	23	environment	environment	NOUN
ajst-19160	412	24	.	.	PUNCT
ajst-19160	412	25	,	,	PUNCT
ajst-19160	412	26	ocean	ocean	PROPN
ajst-19160	412	27	engineering	engineering	NOUN
ajst-19160	412	28	,	,	PUNCT
ajst-19160	412	29	(	(	PUNCT
ajst-19160	412	30	2020	2020	NUM
ajst-19160	412	31	)	)	PUNCT
ajst-19160	412	32	.	.	PUNCT
ajst-19160	413	1	[	[	X
ajst-19160	413	2	28	28	NUM
ajst-19160	413	3	]	]	X
ajst-19160	413	4	x.a	x.a	PROPN
ajst-19160	413	5	.	.	PROPN
ajst-19160	414	1	liu	liu	PROPN
ajst-19160	414	2	,	,	PUNCT
ajst-19160	414	3	m.a	m.a	PROPN
ajst-19160	414	4	.	.	PROPN
ajst-19160	414	5	xia	xia	PROPN
ajst-19160	414	6	,	,	PUNCT
ajst-19160	414	7	d.a	d.a	PROPN
ajst-19160	414	8	.	.	PROPN
ajst-19160	414	9	bolati	bolati	PROPN
ajst-19160	414	10	,	,	PUNCT
ajst-19160	414	11	j.a	j.a	PROPN
ajst-19160	414	12	.	.	PROPN
ajst-19160	414	13	liu	liu	PROPN
ajst-19160	414	14	,	,	PUNCT
ajst-19160	414	15	q.a	q.a	PROPN
ajst-19160	414	16	.	.	PROPN
ajst-19160	414	17	zheng	zheng	PROPN
ajst-19160	414	18	,	,	PUNCT
ajst-19160	414	19	h.a.h.c	h.a.h.c	PROPN
ajst-19160	414	20	.	.	PROPN
ajst-19160	414	21	zhang	zhang	PROPN
ajst-19160	414	22	,	,	PUNCT
ajst-19160	414	23	an	an	DET
ajst-19160	414	24	ann‐based	ann‐base	VERB
ajst-19160	414	25	failure	failure	NOUN
ajst-19160	414	26	pressure	pressure	NOUN
ajst-19160	414	27	prediction	prediction	NOUN
ajst-19160	414	28	method	method	NOUN
ajst-19160	414	29	for	for	ADP
ajst-19160	414	30	buried	bury	VERB
ajst-19160	414	31	high‐strength	high‐strength	NOUN
ajst-19160	414	32	pipes	pipe	NOUN
ajst-19160	414	33	with	with	ADP
ajst-19160	414	34	stray	stray	ADJ
ajst-19160	414	35	current	current	ADJ
ajst-19160	414	36	corrosion	corrosion	NOUN
ajst-19160	414	37	defect	defect	NOUN
ajst-19160	414	38	.	.	PUNCT
ajst-19160	414	39	,	,	PUNCT
ajst-19160	414	40	energy	energy	NOUN
ajst-19160	414	41	science	science	NOUN
ajst-19160	414	42	&	&	CCONJ
ajst-19160	414	43	engineering	engineering	PROPN
ajst-19160	414	44	,	,	PUNCT
ajst-19160	414	45	(	(	PUNCT
ajst-19160	414	46	2020	2020	NUM
ajst-19160	414	47	)	)	PUNCT
ajst-19160	414	48	248259	248259	NUM
ajst-19160	414	49	.	.	PUNCT
ajst-19160	415	1	130	130	NUM
ajst-19160	416	1	[	[	SYM
ajst-19160	416	2	29	29	NUM
ajst-19160	416	3	]	]	X
ajst-19160	416	4	b.m	b.m	PROPN
ajst-19160	416	5	.	.	PROPN
ajst-19160	416	6	wilamowski	wilamowski	PROPN
ajst-19160	416	7	,	,	PUNCT
ajst-19160	416	8	h.	h.	PROPN
ajst-19160	416	9	yu	yu	PROPN
ajst-19160	416	10	,	,	PUNCT
ajst-19160	416	11	improved	improved	ADJ
ajst-19160	416	12	computation	computation	NOUN
ajst-19160	416	13	for	for	ADP
ajst-19160	416	14	levenberg	levenberg	PROPN
ajst-19160	416	15	-	-	PUNCT
ajst-19160	416	16	marquardt	marquardt	PROPN
ajst-19160	416	17	training	training	NOUN
ajst-19160	416	18	.	.	PUNCT
ajst-19160	416	19	,	,	PUNCT
ajst-19160	416	20	ieee	ieee	NOUN
ajst-19160	416	21	transactions	transaction	NOUN
ajst-19160	416	22	on	on	ADP
ajst-19160	416	23	neural	neural	ADJ
ajst-19160	416	24	networks	network	NOUN
ajst-19160	416	25	,	,	PUNCT
ajst-19160	416	26	(	(	PUNCT
ajst-19160	416	27	2010	2010	NUM
ajst-19160	416	28	)	)	PUNCT
ajst-19160	416	29	930	930	NUM
ajst-19160	416	30	-	-	SYM
ajst-19160	416	31	937	937	NUM
ajst-19160	416	32	.	.	PUNCT
ajst-19160	417	1	[	[	X
ajst-19160	417	2	30	30	NUM
ajst-19160	417	3	]	]	X
ajst-19160	417	4	j.	j.	PROPN
ajst-19160	417	5	li	li	PROPN
ajst-19160	417	6	,	,	PUNCT
ajst-19160	417	7	y.	y.	PROPN
ajst-19160	417	8	wu	wu	PROPN
ajst-19160	417	9	,	,	PUNCT
ajst-19160	417	10	improved	improve	VERB
ajst-19160	417	11	sparrow	sparrow	ADJ
ajst-19160	417	12	search	search	NOUN
ajst-19160	417	13	algorithm	algorithm	NOUN
ajst-19160	417	14	with	with	ADP
ajst-19160	417	15	the	the	DET
ajst-19160	417	16	extreme	extreme	ADJ
ajst-19160	417	17	learning	learning	NOUN
ajst-19160	417	18	machine	machine	NOUN
ajst-19160	417	19	and	and	CCONJ
ajst-19160	417	20	its	its	PRON
ajst-19160	417	21	application	application	NOUN
ajst-19160	417	22	for	for	ADP
ajst-19160	417	23	prediction	prediction	NOUN
ajst-19160	417	24	,	,	PUNCT
ajst-19160	417	25	neural	neural	ADJ
ajst-19160	417	26	processing	processing	NOUN
ajst-19160	417	27	letters	letter	NOUN
ajst-19160	417	28	,	,	PUNCT
ajst-19160	417	29	(	(	PUNCT
ajst-19160	417	30	2022	2022	NUM
ajst-19160	417	31	)	)	PUNCT
ajst-19160	417	32	4189	4189	NUM
ajst-19160	417	33	-	-	SYM
ajst-19160	417	34	4209	4209	NUM
ajst-19160	417	35	.	.	PUNCT
ajst-19160	418	1	https://doi.org/10.1007/s11063-022-10804-x	https://doi.org/10.1007/s11063-022-10804-x	PROPN
ajst-19160	418	2	[	[	X
ajst-19160	418	3	31	31	NUM
ajst-19160	418	4	]	]	PUNCT
ajst-19160	418	5	s.	s.	PROPN
ajst-19160	418	6	mirjalili	mirjalili	PROPN
ajst-19160	418	7	,	,	PUNCT
ajst-19160	418	8	dragonfly	dragonfly	PROPN
ajst-19160	418	9	algorithm	algorithm	PROPN
ajst-19160	418	10	:	:	PUNCT
ajst-19160	418	11	a	a	DET
ajst-19160	418	12	new	new	ADJ
ajst-19160	418	13	meta	meta	ADJ
ajst-19160	418	14	-	-	PUNCT
ajst-19160	418	15	heuristic	heuristic	ADJ
ajst-19160	418	16	optimization	optimization	NOUN
ajst-19160	418	17	technique	technique	NOUN
ajst-19160	418	18	for	for	ADP
ajst-19160	418	19	solving	solve	VERB
ajst-19160	418	20	single	single	ADJ
ajst-19160	418	21	-	-	PUNCT
ajst-19160	418	22	objective	objective	NOUN
ajst-19160	418	23	,	,	PUNCT
ajst-19160	418	24	discrete	discrete	ADJ
ajst-19160	418	25	,	,	PUNCT
ajst-19160	418	26	and	and	CCONJ
ajst-19160	418	27	multi	multi	ADJ
ajst-19160	418	28	-	-	ADJ
ajst-19160	418	29	objective	objective	ADJ
ajst-19160	418	30	problems(article	problems(article	NOUN
ajst-19160	418	31	)	)	PUNCT
ajst-19160	418	32	,	,	PUNCT
ajst-19160	418	33	neural	neural	ADJ
ajst-19160	418	34	computing	computing	NOUN
ajst-19160	418	35	and	and	CCONJ
ajst-19160	418	36	applications	application	NOUN
ajst-19160	418	37	,	,	PUNCT
ajst-19160	418	38	(	(	PUNCT
ajst-19160	418	39	2016	2016	NUM
ajst-19160	418	40	)	)	PUNCT
ajst-19160	418	41	1053	1053	NUM
ajst-19160	418	42	-	-	SYM
ajst-19160	418	43	1073	1073	NUM
ajst-19160	418	44	.	.	PUNCT