id	sid	tid	token	lemma	pos
ajst-28595	1	1	academic	academic	ADJ
ajst-28595	1	2	journal	journal	NOUN
ajst-28595	1	3	of	of	ADP
ajst-28595	1	4	science	science	NOUN
ajst-28595	1	5	and	and	CCONJ
ajst-28595	1	6	technology	technology	NOUN
ajst-28595	1	7	issn	issn	NOUN
ajst-28595	1	8	:	:	PUNCT
ajst-28595	1	9	2771	2771	NUM
ajst-28595	1	10	-	-	SYM
ajst-28595	1	11	3032	3032	NUM
ajst-28595	1	12	|	|	NOUN
ajst-28595	1	13	vol	vol	NOUN
ajst-28595	1	14	.	.	PROPN
ajst-28595	1	15	13	13	NUM
ajst-28595	1	16	,	,	PUNCT
ajst-28595	1	17	no	no	INTJ
ajst-28595	1	18	.	.	NOUN
ajst-28595	1	19	3	3	NUM
ajst-28595	1	20	,	,	PUNCT
ajst-28595	1	21	2024	2024	NUM
ajst-28595	1	22	78	78	NUM
ajst-28595	1	23	online	online	ADJ
ajst-28595	1	24	prediction	prediction	NOUN
ajst-28595	1	25	of	of	ADP
ajst-28595	1	26	tool	tool	NOUN
ajst-28595	1	27	life	life	NOUN
ajst-28595	1	28	based	base	VERB
ajst-28595	1	29	on	on	ADP
ajst-28595	1	30	multi‐source	multi‐source	PROPN
ajst-28595	1	31	data	datum	NOUN
ajst-28595	1	32	fusion	fusion	NOUN
ajst-28595	1	33	ling	ling	PROPN
ajst-28595	1	34	he1	he1	PROPN
ajst-28595	1	35	,	,	PUNCT
ajst-28595	1	36	yun	yun	PROPN
ajst-28595	1	37	xu1	xu1	PROPN
ajst-28595	1	38	,	,	PUNCT
ajst-28595	1	39	*	*	PUNCT
ajst-28595	1	40	,	,	PUNCT
ajst-28595	1	41	qi	qi	PROPN
ajst-28595	1	42	li2	li2	PROPN
ajst-28595	2	1	1school	1school	NUM
ajst-28595	2	2	of	of	ADP
ajst-28595	2	3	mechanical	mechanical	ADJ
ajst-28595	2	4	engineering	engineering	NOUN
ajst-28595	2	5	,	,	PUNCT
ajst-28595	2	6	sichuan	sichuan	PROPN
ajst-28595	2	7	university	university	PROPN
ajst-28595	2	8	of	of	ADP
ajst-28595	2	9	science	science	PROPN
ajst-28595	2	10	&	&	CCONJ
ajst-28595	2	11	engineering	engineering	PROPN
ajst-28595	2	12	,	,	PUNCT
ajst-28595	2	13	yibin	yibin	PROPN
ajst-28595	2	14	sichuan	sichuan	PROPN
ajst-28595	2	15	644000	644000	NUM
ajst-28595	2	16	,	,	PUNCT
ajst-28595	2	17	china	china	PROPN
ajst-28595	2	18	2sichuan	2sichuan	NUM
ajst-28595	2	19	changzheng	changzheng	PROPN
ajst-28595	2	20	machine	machine	PROPN
ajst-28595	2	21	tool	tool	PROPN
ajst-28595	2	22	group	group	PROPN
ajst-28595	2	23	co.	co.	PROPN
ajst-28595	2	24	,ltd	,ltd	PROPN
ajst-28595	2	25	.	.	PROPN
ajst-28595	2	26	,	,	PUNCT
ajst-28595	3	1	zigong	zigong	PROPN
ajst-28595	3	2	sichuan	sichuan	PROPN
ajst-28595	3	3	643000	643000	NUM
ajst-28595	3	4	,	,	PUNCT
ajst-28595	3	5	china	china	PROPN
ajst-28595	3	6	*	*	PUNCT
ajst-28595	3	7	corresponding	correspond	VERB
ajst-28595	3	8	author	author	NOUN
ajst-28595	3	9	abstract	abstract	NOUN
ajst-28595	3	10	:	:	PUNCT
ajst-28595	3	11	to	to	PART
ajst-28595	3	12	address	address	VERB
ajst-28595	3	13	the	the	DET
ajst-28595	3	14	challenges	challenge	NOUN
ajst-28595	3	15	of	of	ADP
ajst-28595	3	16	difficult	difficult	ADJ
ajst-28595	3	17	data	datum	NOUN
ajst-28595	3	18	acquisition	acquisition	NOUN
ajst-28595	3	19	and	and	CCONJ
ajst-28595	3	20	low	low	ADJ
ajst-28595	3	21	prediction	prediction	NOUN
ajst-28595	3	22	accuracy	accuracy	NOUN
ajst-28595	3	23	in	in	ADP
ajst-28595	3	24	tool	tool	NOUN
ajst-28595	3	25	life	life	NOUN
ajst-28595	3	26	prediction	prediction	NOUN
ajst-28595	3	27	,	,	PUNCT
ajst-28595	3	28	a	a	DET
ajst-28595	3	29	method	method	NOUN
ajst-28595	3	30	for	for	ADP
ajst-28595	3	31	data	data	NOUN
ajst-28595	3	32	collection	collection	NOUN
ajst-28595	3	33	from	from	ADP
ajst-28595	3	34	fanuc	fanuc	PROPN
ajst-28595	3	35	numerical	numerical	PROPN
ajst-28595	3	36	control	control	PROPN
ajst-28595	3	37	machine	machine	NOUN
ajst-28595	3	38	tools	tool	NOUN
ajst-28595	3	39	and	and	CCONJ
ajst-28595	3	40	prediction	prediction	NOUN
ajst-28595	3	41	of	of	ADP
ajst-28595	3	42	tool	tool	NOUN
ajst-28595	3	43	life	life	NOUN
ajst-28595	3	44	based	base	VERB
ajst-28595	3	45	on	on	ADP
ajst-28595	3	46	the	the	DET
ajst-28595	3	47	ssa	ssa	NOUN
ajst-28595	3	48	-	-	PUNCT
ajst-28595	3	49	bp	bp	PROPN
ajst-28595	3	50	neural	neural	ADJ
ajst-28595	3	51	network	network	NOUN
ajst-28595	3	52	is	be	AUX
ajst-28595	3	53	proposed	propose	VERB
ajst-28595	3	54	.	.	PUNCT
ajst-28595	4	1	data	datum	NOUN
ajst-28595	4	2	such	such	ADJ
ajst-28595	4	3	as	as	ADP
ajst-28595	4	4	tool	tool	NOUN
ajst-28595	4	5	running	running	NOUN
ajst-28595	4	6	time	time	NOUN
ajst-28595	4	7	,	,	PUNCT
ajst-28595	4	8	spindle	spindle	NOUN
ajst-28595	4	9	load	load	NOUN
ajst-28595	4	10	rate	rate	NOUN
ajst-28595	4	11	,	,	PUNCT
ajst-28595	4	12	spindle	spindle	NOUN
ajst-28595	4	13	load	load	NOUN
ajst-28595	4	14	,	,	PUNCT
ajst-28595	4	15	x	x	ADJ
ajst-28595	4	16	-	-	ADJ
ajst-28595	4	17	axis	axis	ADJ
ajst-28595	4	18	load	load	NOUN
ajst-28595	4	19	rate	rate	NOUN
ajst-28595	4	20	,	,	PUNCT
ajst-28595	4	21	y	y	NOUN
ajst-28595	4	22	-	-	PUNCT
ajst-28595	4	23	axis	axis	NOUN
ajst-28595	4	24	load	load	NOUN
ajst-28595	4	25	rate	rate	NOUN
ajst-28595	4	26	,	,	PUNCT
ajst-28595	4	27	z	z	NOUN
ajst-28595	4	28	-	-	PUNCT
ajst-28595	4	29	axis	axis	NOUN
ajst-28595	4	30	load	load	NOUN
ajst-28595	4	31	rate	rate	NOUN
ajst-28595	4	32	,	,	PUNCT
ajst-28595	4	33	x	x	ADJ
ajst-28595	4	34	-	-	ADJ
ajst-28595	4	35	axis	axis	ADJ
ajst-28595	4	36	current	current	ADJ
ajst-28595	4	37	,	,	PUNCT
ajst-28595	4	38	y	y	ADJ
ajst-28595	4	39	-	-	PUNCT
ajst-28595	4	40	axis	axis	NOUN
ajst-28595	4	41	current	current	NOUN
ajst-28595	4	42	,	,	PUNCT
ajst-28595	4	43	and	and	CCONJ
ajst-28595	4	44	z	z	NOUN
ajst-28595	4	45	-	-	PUNCT
ajst-28595	4	46	axis	axis	ADJ
ajst-28595	4	47	current	current	NOUN
ajst-28595	4	48	are	be	AUX
ajst-28595	4	49	collected	collect	VERB
ajst-28595	4	50	.	.	PUNCT
ajst-28595	5	1	by	by	ADP
ajst-28595	5	2	optimizing	optimize	VERB
ajst-28595	5	3	the	the	DET
ajst-28595	5	4	core	core	NOUN
ajst-28595	5	5	parameters	parameter	NOUN
ajst-28595	5	6	of	of	ADP
ajst-28595	5	7	the	the	DET
ajst-28595	5	8	bp	bp	PROPN
ajst-28595	5	9	neural	neural	ADJ
ajst-28595	5	10	network	network	NOUN
ajst-28595	5	11	with	with	ADP
ajst-28595	5	12	the	the	DET
ajst-28595	5	13	ssa	ssa	PROPN
ajst-28595	5	14	algorithm	algorithm	NOUN
ajst-28595	5	15	,	,	PUNCT
ajst-28595	5	16	a	a	DET
ajst-28595	5	17	tool	tool	NOUN
ajst-28595	5	18	life	life	NOUN
ajst-28595	5	19	prediction	prediction	NOUN
ajst-28595	5	20	model	model	NOUN
ajst-28595	5	21	is	be	AUX
ajst-28595	5	22	constructed	construct	VERB
ajst-28595	5	23	.	.	PUNCT
ajst-28595	6	1	compared	compare	VERB
ajst-28595	6	2	with	with	ADP
ajst-28595	6	3	traditional	traditional	ADJ
ajst-28595	6	4	bp	bp	PROPN
ajst-28595	6	5	neural	neural	ADJ
ajst-28595	6	6	networks	network	NOUN
ajst-28595	6	7	and	and	CCONJ
ajst-28595	6	8	gwo	gwo	PROPN
ajst-28595	6	9	-	-	PUNCT
ajst-28595	6	10	bp	bp	PROPN
ajst-28595	6	11	neural	neural	ADJ
ajst-28595	6	12	networks	network	NOUN
ajst-28595	6	13	,	,	PUNCT
ajst-28595	6	14	experimental	experimental	ADJ
ajst-28595	6	15	results	result	NOUN
ajst-28595	6	16	show	show	VERB
ajst-28595	6	17	that	that	SCONJ
ajst-28595	6	18	this	this	DET
ajst-28595	6	19	model	model	NOUN
ajst-28595	6	20	has	have	VERB
ajst-28595	6	21	the	the	DET
ajst-28595	6	22	closest	close	ADJ
ajst-28595	6	23	tool	tool	NOUN
ajst-28595	6	24	life	life	NOUN
ajst-28595	6	25	prediction	prediction	NOUN
ajst-28595	6	26	values	value	NOUN
ajst-28595	6	27	to	to	ADP
ajst-28595	6	28	the	the	DET
ajst-28595	6	29	actual	actual	ADJ
ajst-28595	6	30	values	value	NOUN
ajst-28595	6	31	and	and	CCONJ
ajst-28595	6	32	better	well	ADJ
ajst-28595	6	33	network	network	NOUN
ajst-28595	6	34	stability	stability	NOUN
ajst-28595	6	35	,	,	PUNCT
ajst-28595	6	36	making	make	VERB
ajst-28595	6	37	it	it	PRON
ajst-28595	6	38	more	more	ADV
ajst-28595	6	39	suitable	suitable	ADJ
ajst-28595	6	40	for	for	ADP
ajst-28595	6	41	tool	tool	NOUN
ajst-28595	6	42	life	life	NOUN
ajst-28595	6	43	prediction	prediction	NOUN
ajst-28595	6	44	.	.	PUNCT
ajst-28595	7	1	keywords	keyword	NOUN
ajst-28595	7	2	:	:	PUNCT
ajst-28595	7	3	tool	tool	NOUN
ajst-28595	7	4	life	life	NOUN
ajst-28595	7	5	prediction	prediction	NOUN
ajst-28595	7	6	;	;	PUNCT
ajst-28595	7	7	data	datum	NOUN
ajst-28595	7	8	acquisition	acquisition	NOUN
ajst-28595	7	9	;	;	PUNCT
ajst-28595	7	10	bp	bp	PROPN
ajst-28595	7	11	neural	neural	ADJ
ajst-28595	7	12	network	network	NOUN
ajst-28595	7	13	;	;	PUNCT
ajst-28595	7	14	sparrow	sparrow	NOUN
ajst-28595	7	15	search	search	NOUN
ajst-28595	7	16	algorithm	algorithm	NOUN
ajst-28595	7	17	.	.	PUNCT
ajst-28595	8	1	1	1	X
ajst-28595	8	2	.	.	X
ajst-28595	8	3	introduction	introduction	NOUN
ajst-28595	8	4	cutting	cutting	NOUN
ajst-28595	8	5	tools	tool	NOUN
ajst-28595	8	6	,	,	PUNCT
ajst-28595	8	7	as	as	ADP
ajst-28595	8	8	important	important	ADJ
ajst-28595	8	9	executive	executive	ADJ
ajst-28595	8	10	components	component	NOUN
ajst-28595	8	11	in	in	ADP
ajst-28595	8	12	cnc	cnc	PROPN
ajst-28595	8	13	machining	machining	NOUN
ajst-28595	8	14	,	,	PUNCT
ajst-28595	8	15	directly	directly	ADV
ajst-28595	8	16	affect	affect	VERB
ajst-28595	8	17	the	the	DET
ajst-28595	8	18	precision	precision	NOUN
ajst-28595	8	19	of	of	ADP
ajst-28595	8	20	the	the	DET
ajst-28595	8	21	machined	machine	VERB
ajst-28595	8	22	workpieces	workpiece	NOUN
ajst-28595	8	23	.	.	PUNCT
ajst-28595	9	1	research	research	NOUN
ajst-28595	9	2	indicates	indicate	VERB
ajst-28595	9	3	that	that	SCONJ
ajst-28595	9	4	the	the	DET
ajst-28595	9	5	reasonable	reasonable	ADJ
ajst-28595	9	6	utilization	utilization	NOUN
ajst-28595	9	7	rate	rate	NOUN
ajst-28595	9	8	of	of	ADP
ajst-28595	9	9	cnc	cnc	PROPN
ajst-28595	9	10	machining	machining	NOUN
ajst-28595	9	11	tool	tool	NOUN
ajst-28595	9	12	life	life	NOUN
ajst-28595	9	13	is	be	AUX
ajst-28595	9	14	only	only	ADV
ajst-28595	9	15	50	50	NUM
ajst-28595	9	16	-	-	SYM
ajst-28595	9	17	80	80	NUM
ajst-28595	9	18	%	%	NOUN
ajst-28595	9	19	,	,	PUNCT
ajst-28595	9	20	and	and	CCONJ
ajst-28595	9	21	if	if	SCONJ
ajst-28595	9	22	tools	tool	NOUN
ajst-28595	9	23	malfunction	malfunction	NOUN
ajst-28595	9	24	,	,	PUNCT
ajst-28595	9	25	the	the	DET
ajst-28595	9	26	downtime	downtime	NOUN
ajst-28595	9	27	of	of	ADP
ajst-28595	9	28	the	the	DET
ajst-28595	9	29	machine	machine	NOUN
ajst-28595	9	30	tools	tool	NOUN
ajst-28595	9	31	can	can	AUX
ajst-28595	9	32	account	account	VERB
ajst-28595	9	33	for	for	ADP
ajst-28595	9	34	10	10	NUM
ajst-28595	9	35	-	-	SYM
ajst-28595	9	36	40	40	NUM
ajst-28595	9	37	%	%	NOUN
ajst-28595	9	38	,	,	PUNCT
ajst-28595	9	39	with	with	ADP
ajst-28595	9	40	processing	processing	NOUN
ajst-28595	9	41	costs	cost	NOUN
ajst-28595	9	42	as	as	ADV
ajst-28595	9	43	high	high	ADJ
ajst-28595	10	1	as	as	ADP
ajst-28595	10	2	30	30	NUM
ajst-28595	10	3	%	%	NOUN
ajst-28595	10	4	[	[	X
ajst-28595	10	5	1	1	NUM
ajst-28595	10	6	]	]	PUNCT
ajst-28595	10	7	.	.	PUNCT
ajst-28595	11	1	therefore	therefore	ADV
ajst-28595	11	2	,	,	PUNCT
ajst-28595	11	3	predicting	predict	VERB
ajst-28595	11	4	the	the	DET
ajst-28595	11	5	life	life	NOUN
ajst-28595	11	6	of	of	ADP
ajst-28595	11	7	cutting	cut	VERB
ajst-28595	11	8	tools	tool	NOUN
ajst-28595	11	9	is	be	AUX
ajst-28595	11	10	extremely	extremely	ADV
ajst-28595	11	11	important	important	ADJ
ajst-28595	11	12	.	.	PUNCT
ajst-28595	12	1	shen	shen	PROPN
ajst-28595	12	2	yujie	yujie	PROPN
ajst-28595	13	1	[	[	X
ajst-28595	13	2	2	2	X
ajst-28595	13	3	]	]	PUNCT
ajst-28595	13	4	and	and	CCONJ
ajst-28595	13	5	others	other	NOUN
ajst-28595	13	6	,	,	PUNCT
ajst-28595	13	7	in	in	ADP
ajst-28595	13	8	response	response	NOUN
ajst-28595	13	9	to	to	ADP
ajst-28595	13	10	the	the	DET
ajst-28595	13	11	low	low	ADJ
ajst-28595	13	12	accuracy	accuracy	NOUN
ajst-28595	13	13	of	of	ADP
ajst-28595	13	14	single	single	ADJ
ajst-28595	13	15	sensor	sensor	NOUN
ajst-28595	13	16	data	datum	NOUN
ajst-28595	13	17	,	,	PUNCT
ajst-28595	13	18	proposed	propose	VERB
ajst-28595	13	19	a	a	DET
ajst-28595	13	20	cnn	cnn	PROPN
ajst-28595	13	21	-	-	PUNCT
ajst-28595	13	22	gru	gru	PROPN
ajst-28595	13	23	neural	neural	ADJ
ajst-28595	13	24	network	network	NOUN
ajst-28595	13	25	multi	multi	ADJ
ajst-28595	13	26	-	-	ADJ
ajst-28595	13	27	source	source	ADJ
ajst-28595	13	28	information	information	NOUN
ajst-28595	13	29	fusion	fusion	NOUN
ajst-28595	13	30	model	model	NOUN
ajst-28595	13	31	for	for	ADP
ajst-28595	13	32	predicting	predict	VERB
ajst-28595	13	33	the	the	DET
ajst-28595	13	34	remaining	remain	VERB
ajst-28595	13	35	life	life	NOUN
ajst-28595	13	36	of	of	ADP
ajst-28595	13	37	cutting	cut	VERB
ajst-28595	13	38	tools	tool	NOUN
ajst-28595	13	39	.	.	PUNCT
ajst-28595	14	1	the	the	DET
ajst-28595	14	2	experimental	experimental	ADJ
ajst-28595	14	3	results	result	NOUN
ajst-28595	14	4	verified	verify	VERB
ajst-28595	14	5	by	by	ADP
ajst-28595	14	6	the	the	DET
ajst-28595	14	7	public	public	ADJ
ajst-28595	14	8	tool	tool	NOUN
ajst-28595	14	9	dataset	dataset	NOUN
ajst-28595	14	10	phm2010	phm2010	NOUN
ajst-28595	14	11	showed	show	VERB
ajst-28595	14	12	that	that	SCONJ
ajst-28595	14	13	the	the	DET
ajst-28595	14	14	cnn	cnn	PROPN
ajst-28595	14	15	-	-	PUNCT
ajst-28595	14	16	gru	gru	PROPN
ajst-28595	14	17	model	model	NOUN
ajst-28595	14	18	improved	improve	VERB
ajst-28595	14	19	the	the	DET
ajst-28595	14	20	prediction	prediction	NOUN
ajst-28595	14	21	accuracy	accuracy	NOUN
ajst-28595	14	22	by	by	ADP
ajst-28595	14	23	21	21	NUM
ajst-28595	14	24	%	%	NOUN
ajst-28595	14	25	and	and	CCONJ
ajst-28595	14	26	22	22	NUM
ajst-28595	14	27	%	%	NOUN
ajst-28595	14	28	compared	compare	VERB
ajst-28595	14	29	to	to	ADP
ajst-28595	14	30	lstm	lstm	PROPN
ajst-28595	14	31	and	and	CCONJ
ajst-28595	14	32	gru	gru	NOUN
ajst-28595	14	33	models	model	NOUN
ajst-28595	14	34	,	,	PUNCT
ajst-28595	14	35	respectively	respectively	ADV
ajst-28595	14	36	.	.	PUNCT
ajst-28595	15	1	liu	liu	PROPN
ajst-28595	15	2	sichen	sichen	PROPN
ajst-28595	16	1	[	[	X
ajst-28595	16	2	3	3	X
ajst-28595	16	3	]	]	PUNCT
ajst-28595	16	4	and	and	CCONJ
ajst-28595	16	5	others	other	NOUN
ajst-28595	16	6	,	,	PUNCT
ajst-28595	16	7	in	in	ADP
ajst-28595	16	8	order	order	NOUN
ajst-28595	16	9	to	to	PART
ajst-28595	16	10	improve	improve	VERB
ajst-28595	16	11	the	the	DET
ajst-28595	16	12	accuracy	accuracy	NOUN
ajst-28595	16	13	of	of	ADP
ajst-28595	16	14	tool	tool	NOUN
ajst-28595	16	15	wear	wear	VERB
ajst-28595	16	16	prediction	prediction	NOUN
ajst-28595	16	17	,	,	PUNCT
ajst-28595	16	18	proposed	propose	VERB
ajst-28595	16	19	a	a	DET
ajst-28595	16	20	multi	multi	ADJ
ajst-28595	16	21	-	-	ADJ
ajst-28595	16	22	sensor	sensor	ADJ
ajst-28595	16	23	fusion	fusion	NOUN
ajst-28595	16	24	based	base	VERB
ajst-28595	16	25	on	on	ADP
ajst-28595	16	26	vibration	vibration	NOUN
ajst-28595	16	27	and	and	CCONJ
ajst-28595	16	28	current	current	ADJ
ajst-28595	16	29	,	,	PUNCT
ajst-28595	16	30	using	use	VERB
ajst-28595	16	31	a	a	DET
ajst-28595	16	32	deep	deep	ADJ
ajst-28595	16	33	neural	neural	ADJ
ajst-28595	16	34	network	network	NOUN
ajst-28595	16	35	model	model	NOUN
ajst-28595	16	36	to	to	PART
ajst-28595	16	37	predict	predict	VERB
ajst-28595	16	38	the	the	DET
ajst-28595	16	39	life	life	NOUN
ajst-28595	16	40	of	of	ADP
ajst-28595	16	41	cutting	cut	VERB
ajst-28595	16	42	tools	tool	NOUN
ajst-28595	16	43	.	.	PUNCT
ajst-28595	17	1	the	the	DET
ajst-28595	17	2	prediction	prediction	NOUN
ajst-28595	17	3	of	of	ADP
ajst-28595	17	4	the	the	DET
ajst-28595	17	5	remaining	remain	VERB
ajst-28595	17	6	life	life	NOUN
ajst-28595	17	7	of	of	ADP
ajst-28595	17	8	cutting	cut	VERB
ajst-28595	17	9	tools	tool	NOUN
ajst-28595	17	10	was	be	AUX
ajst-28595	17	11	verified	verify	VERB
ajst-28595	17	12	through	through	ADP
ajst-28595	17	13	the	the	DET
ajst-28595	17	14	public	public	ADJ
ajst-28595	17	15	dataset	dataset	NOUN
ajst-28595	17	16	of	of	ADP
ajst-28595	17	17	the	the	DET
ajst-28595	17	18	"	"	PUNCT
ajst-28595	17	19	empowerment	empowerment	NOUN
ajst-28595	17	20	and	and	CCONJ
ajst-28595	17	21	intelligence	intelligence	NOUN
ajst-28595	17	22	"	"	PUNCT
ajst-28595	17	23	second	second	ADJ
ajst-28595	17	24	industrial	industrial	ADJ
ajst-28595	17	25	big	big	ADJ
ajst-28595	17	26	data	datum	NOUN
ajst-28595	17	27	innovation	innovation	NOUN
ajst-28595	17	28	competition	competition	NOUN
ajst-28595	17	29	guided	guide	VERB
ajst-28595	17	30	by	by	ADP
ajst-28595	17	31	the	the	DET
ajst-28595	17	32	ministry	ministry	PROPN
ajst-28595	17	33	of	of	ADP
ajst-28595	17	34	industry	industry	NOUN
ajst-28595	17	35	and	and	CCONJ
ajst-28595	17	36	information	information	NOUN
ajst-28595	17	37	technology	technology	NOUN
ajst-28595	17	38	,	,	PUNCT
ajst-28595	17	39	and	and	CCONJ
ajst-28595	17	40	the	the	DET
ajst-28595	17	41	results	result	NOUN
ajst-28595	17	42	were	be	AUX
ajst-28595	17	43	relatively	relatively	ADV
ajst-28595	17	44	accurate	accurate	ADJ
ajst-28595	17	45	.	.	PUNCT
ajst-28595	18	1	wang	wang	PROPN
ajst-28595	18	2	yiwei	yiwei	NOUN
ajst-28595	19	1	[	[	X
ajst-28595	19	2	4	4	X
ajst-28595	19	3	]	]	PUNCT
ajst-28595	19	4	and	and	CCONJ
ajst-28595	19	5	others	other	NOUN
ajst-28595	19	6	,	,	PUNCT
ajst-28595	19	7	in	in	ADP
ajst-28595	19	8	response	response	NOUN
ajst-28595	19	9	to	to	ADP
ajst-28595	19	10	the	the	DET
ajst-28595	19	11	low	low	ADJ
ajst-28595	19	12	data	data	NOUN
ajst-28595	19	13	utilization	utilization	NOUN
ajst-28595	19	14	rate	rate	NOUN
ajst-28595	19	15	,	,	PUNCT
ajst-28595	19	16	proposed	propose	VERB
ajst-28595	19	17	a	a	DET
ajst-28595	19	18	multichannel	multichannel	ADJ
ajst-28595	19	19	signal	signal	NOUN
ajst-28595	19	20	fusion	fusion	NOUN
ajst-28595	19	21	and	and	CCONJ
ajst-28595	19	22	bayesian	bayesian	NOUN
ajst-28595	19	23	updating	updating	NOUN
ajst-28595	19	24	method	method	NOUN
ajst-28595	19	25	for	for	ADP
ajst-28595	19	26	predicting	predict	VERB
ajst-28595	19	27	the	the	DET
ajst-28595	19	28	remaining	remain	VERB
ajst-28595	19	29	life	life	NOUN
ajst-28595	19	30	of	of	ADP
ajst-28595	19	31	cutting	cut	VERB
ajst-28595	19	32	tools	tool	NOUN
ajst-28595	19	33	.	.	PUNCT
ajst-28595	20	1	this	this	DET
ajst-28595	20	2	method	method	NOUN
ajst-28595	20	3	effectively	effectively	ADV
ajst-28595	20	4	avoids	avoid	VERB
ajst-28595	20	5	dependence	dependence	NOUN
ajst-28595	20	6	on	on	ADP
ajst-28595	20	7	a	a	DET
ajst-28595	20	8	large	large	ADJ
ajst-28595	20	9	amount	amount	NOUN
ajst-28595	20	10	of	of	ADP
ajst-28595	20	11	data	datum	NOUN
ajst-28595	20	12	for	for	ADP
ajst-28595	20	13	training	training	NOUN
ajst-28595	20	14	and	and	CCONJ
ajst-28595	20	15	has	have	AUX
ajst-28595	20	16	achieved	achieve	VERB
ajst-28595	20	17	good	good	ADJ
ajst-28595	20	18	prediction	prediction	NOUN
ajst-28595	20	19	accuracy	accuracy	NOUN
ajst-28595	20	20	verified	verify	VERB
ajst-28595	20	21	by	by	ADP
ajst-28595	20	22	the	the	DET
ajst-28595	20	23	phm2010	phm2010	ADJ
ajst-28595	20	24	public	public	ADJ
ajst-28595	20	25	dataset	dataset	NOUN
ajst-28595	20	26	.	.	PUNCT
ajst-28595	21	1	chen	chen	PROPN
ajst-28595	21	2	xiaokang	xiaokang	PROPN
ajst-28595	22	1	[	[	X
ajst-28595	22	2	5	5	NUM
ajst-28595	22	3	]	]	PUNCT
ajst-28595	22	4	and	and	CCONJ
ajst-28595	22	5	others	other	NOUN
ajst-28595	22	6	integrated	integrate	VERB
ajst-28595	22	7	a	a	DET
ajst-28595	22	8	gaussian	gaussian	ADJ
ajst-28595	22	9	process	process	NOUN
ajst-28595	22	10	regression	regression	NOUN
ajst-28595	22	11	(	(	PUNCT
ajst-28595	22	12	gpr	gpr	PROPN
ajst-28595	22	13	)	)	PUNCT
ajst-28595	22	14	model	model	NOUN
ajst-28595	22	15	prediction	prediction	NOUN
ajst-28595	22	16	method	method	NOUN
ajst-28595	22	17	,	,	PUNCT
ajst-28595	22	18	which	which	PRON
ajst-28595	22	19	was	be	AUX
ajst-28595	22	20	verified	verify	VERB
ajst-28595	22	21	by	by	ADP
ajst-28595	22	22	the	the	DET
ajst-28595	22	23	phm2010	phm2010	ADJ
ajst-28595	22	24	public	public	NOUN
ajst-28595	22	25	dataset	dataset	NOUN
ajst-28595	22	26	and	and	CCONJ
ajst-28595	22	27	achieved	achieve	VERB
ajst-28595	22	28	good	good	ADJ
ajst-28595	22	29	prediction	prediction	NOUN
ajst-28595	22	30	accuracy	accuracy	NOUN
ajst-28595	22	31	.	.	PUNCT
ajst-28595	23	1	feng	feng	PROPN
ajst-28595	23	2	doudou	doudou	PROPN
ajst-28595	24	1	[	[	X
ajst-28595	24	2	6	6	NUM
ajst-28595	24	3	]	]	PUNCT
ajst-28595	24	4	extracted	extract	VERB
ajst-28595	24	5	features	feature	NOUN
ajst-28595	24	6	from	from	ADP
ajst-28595	24	7	the	the	DET
ajst-28595	24	8	signals	signal	NOUN
ajst-28595	24	9	in	in	ADP
ajst-28595	24	10	the	the	DET
ajst-28595	24	11	phm2010	phm2010	ADJ
ajst-28595	24	12	public	public	NOUN
ajst-28595	24	13	dataset	dataset	NOUN
ajst-28595	24	14	and	and	CCONJ
ajst-28595	24	15	used	use	VERB
ajst-28595	24	16	the	the	DET
ajst-28595	24	17	markov	markov	NOUN
ajst-28595	24	18	chain	chain	NOUN
ajst-28595	24	19	monte	monte	PROPN
ajst-28595	24	20	carlo	carlo	PROPN
ajst-28595	24	21	sampling	sample	VERB
ajst-28595	24	22	algorithm	algorithm	NOUN
ajst-28595	24	23	to	to	PART
ajst-28595	24	24	iteratively	iteratively	ADV
ajst-28595	24	25	predict	predict	VERB
ajst-28595	24	26	the	the	DET
ajst-28595	24	27	parameters	parameter	NOUN
ajst-28595	24	28	of	of	ADP
ajst-28595	24	29	the	the	DET
ajst-28595	24	30	tool	tool	NOUN
ajst-28595	24	31	life	life	NOUN
ajst-28595	24	32	degradation	degradation	NOUN
ajst-28595	24	33	model	model	NOUN
ajst-28595	24	34	,	,	PUNCT
ajst-28595	24	35	predicting	predict	VERB
ajst-28595	24	36	the	the	DET
ajst-28595	24	37	remaining	remain	VERB
ajst-28595	24	38	life	life	NOUN
ajst-28595	24	39	of	of	ADP
ajst-28595	24	40	the	the	DET
ajst-28595	24	41	tool	tool	NOUN
ajst-28595	24	42	at	at	ADP
ajst-28595	24	43	various	various	ADJ
ajst-28595	24	44	times	time	NOUN
ajst-28595	24	45	.	.	PUNCT
ajst-28595	25	1	huang	huang	PROPN
ajst-28595	25	2	xian	xian	PROPN
ajst-28595	25	3	zhen	zhen	PROPN
ajst-28595	26	1	[	[	X
ajst-28595	26	2	7	7	X
ajst-28595	26	3	]	]	PUNCT
ajst-28595	26	4	optimized	optimize	VERB
ajst-28595	26	5	the	the	DET
ajst-28595	26	6	parameters	parameter	NOUN
ajst-28595	26	7	of	of	ADP
ajst-28595	26	8	the	the	DET
ajst-28595	26	9	svr	svr	PROPN
ajst-28595	26	10	model	model	NOUN
ajst-28595	26	11	through	through	ADP
ajst-28595	26	12	the	the	DET
ajst-28595	26	13	random	random	ADJ
ajst-28595	26	14	fractal	fractal	ADJ
ajst-28595	26	15	search	search	NOUN
ajst-28595	26	16	algorithm	algorithm	NOUN
ajst-28595	26	17	,	,	PUNCT
ajst-28595	26	18	and	and	CCONJ
ajst-28595	26	19	verified	verify	VERB
ajst-28595	26	20	it	it	PRON
ajst-28595	26	21	with	with	ADP
ajst-28595	26	22	the	the	DET
ajst-28595	26	23	phm2010	phm2010	ADJ
ajst-28595	26	24	public	public	NOUN
ajst-28595	26	25	dataset	dataset	NOUN
ajst-28595	26	26	,	,	PUNCT
ajst-28595	26	27	achieving	achieve	VERB
ajst-28595	26	28	prediction	prediction	NOUN
ajst-28595	26	29	of	of	ADP
ajst-28595	26	30	the	the	DET
ajst-28595	26	31	remaining	remain	VERB
ajst-28595	26	32	service	service	NOUN
ajst-28595	26	33	life	life	NOUN
ajst-28595	26	34	of	of	ADP
ajst-28595	26	35	cutting	cut	VERB
ajst-28595	26	36	tools	tool	NOUN
ajst-28595	26	37	in	in	ADP
ajst-28595	26	38	a	a	DET
ajst-28595	26	39	small	small	ADJ
ajst-28595	26	40	sample	sample	NOUN
ajst-28595	26	41	space	space	NOUN
ajst-28595	26	42	.	.	PUNCT
ajst-28595	27	1	li	li	PROPN
ajst-28595	27	2	tao	tao	PROPN
ajst-28595	28	1	[	[	X
ajst-28595	28	2	8	8	NUM
ajst-28595	28	3	]	]	PUNCT
ajst-28595	28	4	proposed	propose	VERB
ajst-28595	28	5	a	a	DET
ajst-28595	28	6	multi	multi	ADJ
ajst-28595	28	7	-	-	ADJ
ajst-28595	28	8	scale	scale	ADJ
ajst-28595	28	9	recurrent	recurrent	ADJ
ajst-28595	28	10	convolutional	convolutional	ADJ
ajst-28595	28	11	neural	neural	ADJ
ajst-28595	28	12	network	network	NOUN
ajst-28595	28	13	(	(	PUNCT
ajst-28595	28	14	msrcnn	msrcnn	PROPN
ajst-28595	28	15	)	)	PUNCT
ajst-28595	28	16	for	for	ADP
ajst-28595	28	17	predicting	predict	VERB
ajst-28595	28	18	the	the	DET
ajst-28595	28	19	remaining	remain	VERB
ajst-28595	28	20	life	life	NOUN
ajst-28595	28	21	of	of	ADP
ajst-28595	28	22	high	high	ADJ
ajst-28595	28	23	-	-	PUNCT
ajst-28595	28	24	speed	speed	NOUN
ajst-28595	28	25	milling	milling	NOUN
ajst-28595	28	26	tools	tool	NOUN
ajst-28595	28	27	,	,	PUNCT
ajst-28595	28	28	verified	verify	VERB
ajst-28595	28	29	by	by	ADP
ajst-28595	28	30	the	the	DET
ajst-28595	28	31	phm2010	phm2010	ADJ
ajst-28595	28	32	public	public	ADJ
ajst-28595	28	33	dataset	dataset	NOUN
ajst-28595	28	34	,	,	PUNCT
ajst-28595	28	35	and	and	CCONJ
ajst-28595	28	36	the	the	DET
ajst-28595	28	37	msrcnn	msrcnn	PROPN
ajst-28595	28	38	model	model	NOUN
ajst-28595	28	39	has	have	VERB
ajst-28595	28	40	higher	high	ADJ
ajst-28595	28	41	accuracy	accuracy	NOUN
ajst-28595	28	42	and	and	CCONJ
ajst-28595	28	43	faster	fast	ADJ
ajst-28595	28	44	convergence	convergence	NOUN
ajst-28595	28	45	than	than	ADP
ajst-28595	28	46	the	the	DET
ajst-28595	28	47	cnn	cnn	PROPN
ajst-28595	28	48	and	and	CCONJ
ajst-28595	28	49	rnn	rnn	PROPN
ajst-28595	28	50	models	model	NOUN
ajst-28595	28	51	.	.	PUNCT
ajst-28595	29	1	hou	hou	PROPN
ajst-28595	29	2	chunming	chunme	VERB
ajst-28595	29	3	[	[	X
ajst-28595	29	4	9	9	NUM
ajst-28595	29	5	]	]	PUNCT
ajst-28595	29	6	and	and	CCONJ
ajst-28595	29	7	others	other	NOUN
ajst-28595	29	8	proposed	propose	VERB
ajst-28595	29	9	a	a	DET
ajst-28595	29	10	multi	multi	ADJ
ajst-28595	29	11	-	-	ADJ
ajst-28595	29	12	task	task	ADJ
ajst-28595	29	13	joint	joint	ADJ
ajst-28595	29	14	learning	learning	NOUN
ajst-28595	29	15	model	model	NOUN
ajst-28595	29	16	based	base	VERB
ajst-28595	29	17	on	on	ADP
ajst-28595	29	18	the	the	DET
ajst-28595	29	19	transformer	transformer	NOUN
ajst-28595	29	20	encoder	encoder	NOUN
ajst-28595	29	21	and	and	CCONJ
ajst-28595	29	22	custom	custom	NOUN
ajst-28595	29	23	gate	gate	PROPN
ajst-28595	29	24	control	control	PROPN
ajst-28595	29	25	(	(	PUNCT
ajst-28595	29	26	tecgc	tecgc	ADV
ajst-28595	29	27	)	)	PUNCT
ajst-28595	29	28	for	for	ADP
ajst-28595	29	29	simultaneously	simultaneously	ADV
ajst-28595	29	30	predicting	predict	VERB
ajst-28595	29	31	the	the	DET
ajst-28595	29	32	remaining	remain	VERB
ajst-28595	29	33	life	life	NOUN
ajst-28595	29	34	and	and	CCONJ
ajst-28595	29	35	wear	wear	VERB
ajst-28595	29	36	of	of	ADP
ajst-28595	29	37	cutting	cut	VERB
ajst-28595	29	38	tools	tool	NOUN
ajst-28595	29	39	.	.	PUNCT
ajst-28595	30	1	using	use	VERB
ajst-28595	30	2	the	the	DET
ajst-28595	30	3	phm2010	phm2010	ADJ
ajst-28595	30	4	public	public	ADJ
ajst-28595	30	5	dataset	dataset	NOUN
ajst-28595	30	6	,	,	PUNCT
ajst-28595	30	7	the	the	DET
ajst-28595	30	8	accuracy	accuracy	NOUN
ajst-28595	30	9	of	of	ADP
ajst-28595	30	10	the	the	DET
ajst-28595	30	11	remaining	remain	VERB
ajst-28595	30	12	life	life	NOUN
ajst-28595	30	13	and	and	CCONJ
ajst-28595	30	14	wear	wear	VERB
ajst-28595	30	15	amount	amount	NOUN
ajst-28595	30	16	of	of	ADP
ajst-28595	30	17	the	the	DET
ajst-28595	30	18	cutting	cut	VERB
ajst-28595	30	19	tools	tool	NOUN
ajst-28595	30	20	was	be	AUX
ajst-28595	30	21	verified	verify	VERB
ajst-28595	30	22	.	.	PUNCT
ajst-28595	31	1	mu	mu	PROPN
ajst-28595	31	2	quanlin	quanlin	PROPN
ajst-28595	32	1	[	[	X
ajst-28595	32	2	10	10	NUM
ajst-28595	32	3	]	]	PUNCT
ajst-28595	32	4	and	and	CCONJ
ajst-28595	32	5	others	other	NOUN
ajst-28595	32	6	proposed	propose	VERB
ajst-28595	32	7	establishing	establish	VERB
ajst-28595	32	8	a	a	DET
ajst-28595	32	9	non	non	ADJ
ajst-28595	32	10	-	-	ADJ
ajst-28595	32	11	linear	linear	ADJ
ajst-28595	32	12	relationship	relationship	NOUN
ajst-28595	32	13	between	between	ADP
ajst-28595	32	14	highdimensional	highdimensional	ADJ
ajst-28595	32	15	feature	feature	NOUN
ajst-28595	32	16	vectors	vector	NOUN
ajst-28595	32	17	and	and	CCONJ
ajst-28595	32	18	tool	tool	NOUN
ajst-28595	32	19	wear	wear	VERB
ajst-28595	32	20	based	base	VERB
ajst-28595	32	21	on	on	ADP
ajst-28595	32	22	the	the	DET
ajst-28595	32	23	evolutionary	evolutionary	ADJ
ajst-28595	32	24	connection	connection	NOUN
ajst-28595	32	25	system	system	NOUN
ajst-28595	32	26	(	(	PUNCT
ajst-28595	32	27	ecos	ecos	PROPN
ajst-28595	32	28	)	)	PUNCT
ajst-28595	32	29	,	,	PUNCT
ajst-28595	32	30	and	and	CCONJ
ajst-28595	32	31	real	real	ADJ
ajst-28595	32	32	-	-	PUNCT
ajst-28595	32	33	time	time	NOUN
ajst-28595	32	34	prediction	prediction	NOUN
ajst-28595	32	35	of	of	ADP
ajst-28595	32	36	tool	tool	NOUN
ajst-28595	32	37	wear	wear	VERB
ajst-28595	32	38	using	use	VERB
ajst-28595	32	39	incremental	incremental	ADJ
ajst-28595	32	40	learning	learning	NOUN
ajst-28595	32	41	algorithms	algorithm	NOUN
ajst-28595	32	42	.	.	PUNCT
ajst-28595	33	1	finally	finally	ADV
ajst-28595	33	2	,	,	PUNCT
ajst-28595	33	3	the	the	DET
ajst-28595	33	4	wear	wear	NOUN
ajst-28595	33	5	values	value	NOUN
ajst-28595	33	6	predicted	predict	VERB
ajst-28595	33	7	by	by	ADP
ajst-28595	33	8	ecos	ecos	PROPN
ajst-28595	33	9	were	be	AUX
ajst-28595	33	10	used	use	VERB
ajst-28595	33	11	as	as	ADP
ajst-28595	33	12	the	the	DET
ajst-28595	33	13	hidden	hidden	ADJ
ajst-28595	33	14	state	state	NOUN
ajst-28595	33	15	sequence	sequence	NOUN
ajst-28595	33	16	of	of	ADP
ajst-28595	33	17	the	the	DET
ajst-28595	33	18	hidden	hidden	ADJ
ajst-28595	33	19	semi	semi	ADJ
ajst-28595	33	20	-	-	ADJ
ajst-28595	33	21	markov	markov	ADJ
ajst-28595	33	22	model	model	NOUN
ajst-28595	33	23	(	(	PUNCT
ajst-28595	33	24	hsmm	hsmm	PROPN
ajst-28595	33	25	)	)	PUNCT
ajst-28595	33	26	,	,	PUNCT
ajst-28595	33	27	and	and	CCONJ
ajst-28595	33	28	the	the	DET
ajst-28595	33	29	stability	stability	NOUN
ajst-28595	33	30	of	of	ADP
ajst-28595	33	31	the	the	DET
ajst-28595	33	32	hsmm	hsmm	PROPN
ajst-28595	33	33	model	model	NOUN
ajst-28595	33	34	for	for	ADP
ajst-28595	33	35	predicting	predict	VERB
ajst-28595	33	36	the	the	DET
ajst-28595	33	37	remaining	remain	VERB
ajst-28595	33	38	life	life	NOUN
ajst-28595	33	39	of	of	ADP
ajst-28595	33	40	cutting	cut	VERB
ajst-28595	33	41	tools	tool	NOUN
ajst-28595	33	42	was	be	AUX
ajst-28595	33	43	verified	verify	VERB
ajst-28595	33	44	by	by	ADP
ajst-28595	33	45	the	the	DET
ajst-28595	33	46	phm2010	phm2010	ADJ
ajst-28595	33	47	public	public	ADJ
ajst-28595	33	48	dataset	dataset	NOUN
ajst-28595	33	49	.	.	PUNCT
ajst-28595	34	1	chen	chen	PROPN
ajst-28595	34	2	keyu	keyu	VERB
ajst-28595	35	1	[	[	X
ajst-28595	35	2	11	11	NUM
ajst-28595	35	3	]	]	PUNCT
ajst-28595	35	4	proposed	propose	VERB
ajst-28595	35	5	a	a	DET
ajst-28595	35	6	cnnbilstm	cnnbilstm	PROPN
ajst-28595	35	7	neural	neural	ADJ
ajst-28595	35	8	network	network	NOUN
ajst-28595	35	9	for	for	ADP
ajst-28595	35	10	predicting	predict	VERB
ajst-28595	35	11	the	the	DET
ajst-28595	35	12	remaining	remain	VERB
ajst-28595	35	13	service	service	NOUN
ajst-28595	35	14	life	life	NOUN
ajst-28595	35	15	of	of	ADP
ajst-28595	35	16	machining	machining	NOUN
ajst-28595	35	17	tools	tool	NOUN
ajst-28595	35	18	,	,	PUNCT
ajst-28595	35	19	and	and	CCONJ
ajst-28595	35	20	verified	verify	VERB
ajst-28595	35	21	the	the	DET
ajst-28595	35	22	cutting	cut	VERB
ajst-28595	35	23	tool	tool	NOUN
ajst-28595	35	24	vibration	vibration	NOUN
ajst-28595	35	25	signals	signal	NOUN
ajst-28595	35	26	in	in	ADP
ajst-28595	35	27	the	the	DET
ajst-28595	35	28	public	public	ADJ
ajst-28595	35	29	dataset	dataset	NOUN
ajst-28595	35	30	of	of	ADP
ajst-28595	35	31	the	the	DET
ajst-28595	35	32	"	"	PUNCT
ajst-28595	35	33	empowerment	empowerment	NOUN
ajst-28595	35	34	and	and	CCONJ
ajst-28595	35	35	intelligence	intelligence	NOUN
ajst-28595	35	36	"	"	PUNCT
ajst-28595	35	37	second	second	ADJ
ajst-28595	35	38	industrial	industrial	ADJ
ajst-28595	35	39	big	big	ADJ
ajst-28595	35	40	data	datum	NOUN
ajst-28595	35	41	innovation	innovation	NOUN
ajst-28595	35	42	competition	competition	NOUN
ajst-28595	35	43	guided	guide	VERB
ajst-28595	35	44	by	by	ADP
ajst-28595	35	45	the	the	DET
ajst-28595	35	46	ministry	ministry	PROPN
ajst-28595	35	47	of	of	ADP
ajst-28595	35	48	industry	industry	NOUN
ajst-28595	35	49	and	and	CCONJ
ajst-28595	35	50	information	information	NOUN
ajst-28595	35	51	technology	technology	NOUN
ajst-28595	35	52	,	,	PUNCT
ajst-28595	35	53	achieving	achieve	VERB
ajst-28595	35	54	high	high	ADJ
ajst-28595	35	55	-	-	PUNCT
ajst-28595	35	56	precision	precision	NOUN
ajst-28595	35	57	prediction	prediction	NOUN
ajst-28595	35	58	results	result	NOUN
ajst-28595	35	59	for	for	ADP
ajst-28595	35	60	the	the	DET
ajst-28595	35	61	remaining	remain	VERB
ajst-28595	35	62	service	service	NOUN
ajst-28595	35	63	life	life	NOUN
ajst-28595	35	64	.	.	PUNCT
ajst-28595	36	1	although	although	SCONJ
ajst-28595	36	2	the	the	DET
ajst-28595	36	3	aforementioned	aforementioned	ADJ
ajst-28595	36	4	studies	study	NOUN
ajst-28595	36	5	mostly	mostly	ADV
ajst-28595	36	6	utilize	utilize	VERB
ajst-28595	36	7	deep	deep	ADJ
ajst-28595	36	8	learning	learning	NOUN
ajst-28595	36	9	methods	method	NOUN
ajst-28595	36	10	for	for	ADP
ajst-28595	36	11	tool	tool	NOUN
ajst-28595	36	12	life	life	NOUN
ajst-28595	36	13	prediction	prediction	NOUN
ajst-28595	36	14	,	,	PUNCT
ajst-28595	36	15	they	they	PRON
ajst-28595	36	16	primarily	primarily	ADV
ajst-28595	36	17	focus	focus	VERB
ajst-28595	36	18	on	on	ADP
ajst-28595	36	19	research	research	NOUN
ajst-28595	36	20	using	use	VERB
ajst-28595	36	21	public	public	ADJ
ajst-28595	36	22	datasets	dataset	NOUN
ajst-28595	36	23	or	or	CCONJ
ajst-28595	36	24	rely	rely	VERB
ajst-28595	36	25	on	on	ADP
ajst-28595	36	26	externally	externally	ADV
ajst-28595	36	27	installed	instal	VERB
ajst-28595	36	28	vibration	vibration	NOUN
ajst-28595	36	29	sensors	sensor	NOUN
ajst-28595	36	30	,	,	PUNCT
ajst-28595	36	31	cutting	cut	VERB
ajst-28595	36	32	force	force	NOUN
ajst-28595	36	33	sensors	sensor	NOUN
ajst-28595	36	34	,	,	PUNCT
ajst-28595	36	35	acoustic	acoustic	ADJ
ajst-28595	36	36	emission	emission	NOUN
ajst-28595	36	37	sensors	sensor	NOUN
ajst-28595	36	38	,	,	PUNCT
ajst-28595	36	39	and	and	CCONJ
ajst-28595	36	40	current	current	ADJ
ajst-28595	36	41	sensors	sensor	NOUN
ajst-28595	36	42	.	.	PUNCT
ajst-28595	37	1	this	this	DET
ajst-28595	37	2	approach	approach	NOUN
ajst-28595	37	3	requires	require	VERB
ajst-28595	37	4	a	a	DET
ajst-28595	37	5	higher	high	ADJ
ajst-28595	37	6	investment	investment	NOUN
ajst-28595	37	7	and	and	CCONJ
ajst-28595	37	8	is	be	AUX
ajst-28595	37	9	less	less	ADV
ajst-28595	37	10	practical	practical	ADJ
ajst-28595	37	11	.	.	PUNCT
ajst-28595	38	1	in	in	ADP
ajst-28595	38	2	contrast	contrast	NOUN
ajst-28595	38	3	,	,	PUNCT
ajst-28595	38	4	collecting	collect	VERB
ajst-28595	38	5	data	datum	NOUN
ajst-28595	38	6	from	from	ADP
ajst-28595	38	7	built	build	VERB
ajst-28595	38	8	-	-	PUNCT
ajst-28595	38	9	in	in	ADP
ajst-28595	38	10	sensors	sensor	NOUN
ajst-28595	38	11	of	of	ADP
ajst-28595	38	12	cnc	cnc	PROPN
ajst-28595	38	13	machines	machine	NOUN
ajst-28595	38	14	can	can	AUX
ajst-28595	38	15	save	save	VERB
ajst-28595	38	16	costs	cost	NOUN
ajst-28595	38	17	and	and	CCONJ
ajst-28595	38	18	reduce	reduce	VERB
ajst-28595	38	19	the	the	DET
ajst-28595	38	20	hassle	hassle	NOUN
ajst-28595	38	21	associated	associate	VERB
ajst-28595	38	22	with	with	ADP
ajst-28595	38	23	installation	installation	NOUN
ajst-28595	38	24	.	.	PUNCT
ajst-28595	39	1	therefore	therefore	ADV
ajst-28595	39	2	,	,	PUNCT
ajst-28595	39	3	this	this	DET
ajst-28595	39	4	paper	paper	NOUN
ajst-28595	39	5	proposes	propose	VERB
ajst-28595	39	6	a	a	DET
ajst-28595	39	7	method	method	NOUN
ajst-28595	39	8	to	to	PART
ajst-28595	39	9	collect	collect	VERB
ajst-28595	39	10	multi	multi	NOUN
ajst-28595	39	11	79	79	NUM
ajst-28595	39	12	source	source	NOUN
ajst-28595	39	13	data	datum	NOUN
ajst-28595	39	14	during	during	ADP
ajst-28595	39	15	the	the	DET
ajst-28595	39	16	machining	machining	NOUN
ajst-28595	39	17	process	process	NOUN
ajst-28595	39	18	of	of	ADP
ajst-28595	39	19	cnc	cnc	ADJ
ajst-28595	39	20	machines	machine	NOUN
ajst-28595	39	21	and	and	CCONJ
ajst-28595	39	22	employs	employ	VERB
ajst-28595	39	23	the	the	DET
ajst-28595	39	24	ssa	ssa	PROPN
ajst-28595	39	25	-	-	PUNCT
ajst-28595	39	26	bp	bp	PROPN
ajst-28595	39	27	neural	neural	ADJ
ajst-28595	39	28	network	network	NOUN
ajst-28595	39	29	to	to	PART
ajst-28595	39	30	predict	predict	VERB
ajst-28595	39	31	the	the	DET
ajst-28595	39	32	remaining	remain	VERB
ajst-28595	39	33	life	life	NOUN
ajst-28595	39	34	of	of	ADP
ajst-28595	39	35	the	the	DET
ajst-28595	39	36	tool	tool	NOUN
ajst-28595	39	37	.	.	PUNCT
ajst-28595	40	1	by	by	ADP
ajst-28595	40	2	comparing	compare	VERB
ajst-28595	40	3	the	the	DET
ajst-28595	40	4	gwo	gwo	PROPN
ajst-28595	40	5	-	-	PUNCT
ajst-28595	40	6	bp	bp	PROPN
ajst-28595	40	7	and	and	CCONJ
ajst-28595	40	8	traditional	traditional	ADJ
ajst-28595	40	9	bp	bp	PROPN
ajst-28595	40	10	neural	neural	PROPN
ajst-28595	40	11	networks	network	NOUN
ajst-28595	40	12	,	,	PUNCT
ajst-28595	40	13	this	this	DET
ajst-28595	40	14	model	model	NOUN
ajst-28595	40	15	demonstrates	demonstrate	VERB
ajst-28595	40	16	better	well	ADJ
ajst-28595	40	17	practicality	practicality	NOUN
ajst-28595	40	18	and	and	CCONJ
ajst-28595	40	19	performs	perform	VERB
ajst-28595	40	20	online	online	ADJ
ajst-28595	40	21	data	datum	NOUN
ajst-28595	40	22	collection	collection	NOUN
ajst-28595	40	23	for	for	ADP
ajst-28595	40	24	tool	tool	NOUN
ajst-28595	40	25	life	life	NOUN
ajst-28595	40	26	prediction	prediction	NOUN
ajst-28595	40	27	.	.	PUNCT
ajst-28595	41	1	2	2	X
ajst-28595	41	2	.	.	X
ajst-28595	41	3	milling	mill	VERB
ajst-28595	41	4	experiment	experiment	NOUN
ajst-28595	41	5	2.1	2.1	NUM
ajst-28595	41	6	.	.	PUNCT
ajst-28595	42	1	experimental	experimental	ADJ
ajst-28595	42	2	condition	condition	NOUN
ajst-28595	42	3	plan	plan	NOUN
ajst-28595	42	4	setup	setup	VERB
ajst-28595	42	5	the	the	DET
ajst-28595	42	6	experiment	experiment	NOUN
ajst-28595	42	7	was	be	AUX
ajst-28595	42	8	conducted	conduct	VERB
ajst-28595	42	9	on	on	ADP
ajst-28595	42	10	an	an	DET
ajst-28595	42	11	xh718	xh718	PROPN
ajst-28595	42	12	numerical	numerical	PROPN
ajst-28595	42	13	control	control	PROPN
ajst-28595	42	14	machine	machine	NOUN
ajst-28595	42	15	tool	tool	NOUN
ajst-28595	42	16	,	,	PUNCT
ajst-28595	42	17	with	with	ADP
ajst-28595	42	18	cast	cast	NOUN
ajst-28595	42	19	iron	iron	NOUN
ajst-28595	42	20	as	as	ADP
ajst-28595	42	21	the	the	DET
ajst-28595	42	22	workpiece	workpiece	NOUN
ajst-28595	42	23	material	material	NOUN
ajst-28595	42	24	and	and	CCONJ
ajst-28595	42	25	cemented	cement	VERB
ajst-28595	42	26	carbide	carbide	NOUN
ajst-28595	42	27	inserts	insert	NOUN
ajst-28595	42	28	apmt113504	apmt113504	PROPN
ajst-28595	42	29	-	-	PUNCT
ajst-28595	42	30	h2	h2	NOUN
ajst-28595	42	31	as	as	ADP
ajst-28595	42	32	the	the	DET
ajst-28595	42	33	cutting	cut	VERB
ajst-28595	42	34	tool	tool	NOUN
ajst-28595	42	35	material	material	NOUN
ajst-28595	42	36	,	,	PUNCT
ajst-28595	42	37	as	as	SCONJ
ajst-28595	42	38	shown	show	VERB
ajst-28595	42	39	in	in	ADP
ajst-28595	42	40	the	the	DET
ajst-28595	42	41	collection	collection	NOUN
ajst-28595	42	42	platform	platform	NOUN
ajst-28595	42	43	in	in	ADP
ajst-28595	42	44	figure	figure	NOUN
ajst-28595	42	45	1	1	NUM
ajst-28595	42	46	.	.	PUNCT
ajst-28595	43	1	the	the	DET
ajst-28595	43	2	experiment	experiment	NOUN
ajst-28595	43	3	was	be	AUX
ajst-28595	43	4	carried	carry	VERB
ajst-28595	43	5	out	out	ADP
ajst-28595	43	6	on	on	ADP
ajst-28595	43	7	a	a	DET
ajst-28595	43	8	three	three	NUM
ajst-28595	43	9	-	-	PUNCT
ajst-28595	43	10	axis	axis	NOUN
ajst-28595	43	11	numerical	numerical	ADJ
ajst-28595	43	12	control	control	PROPN
ajst-28595	43	13	fanuc-0i	fanuc-0i	X
ajst-28595	43	14	-	-	PUNCT
ajst-28595	43	15	mf	mf	NOUN
ajst-28595	43	16	machining	machining	NOUN
ajst-28595	43	17	center	center	NOUN
ajst-28595	43	18	.	.	PUNCT
ajst-28595	44	1	the	the	DET
ajst-28595	44	2	focas	focas	NOUN
ajst-28595	44	3	function	function	NOUN
ajst-28595	44	4	library	library	NOUN
ajst-28595	44	5	provided	provide	VERB
ajst-28595	44	6	by	by	ADP
ajst-28595	44	7	fanuc	fanuc	PROPN
ajst-28595	44	8	corporation	corporation	NOUN
ajst-28595	44	9	was	be	AUX
ajst-28595	44	10	utilized	utilize	VERB
ajst-28595	44	11	to	to	PART
ajst-28595	44	12	collect	collect	VERB
ajst-28595	44	13	data	datum	NOUN
ajst-28595	44	14	from	from	ADP
ajst-28595	44	15	the	the	DET
ajst-28595	44	16	machining	machining	NOUN
ajst-28595	44	17	process	process	NOUN
ajst-28595	44	18	,	,	PUNCT
ajst-28595	44	19	and	and	CCONJ
ajst-28595	44	20	tcp	tcp	VERB
ajst-28595	44	21	/	/	SYM
ajst-28595	44	22	ip	ip	PROPN
ajst-28595	44	23	was	be	AUX
ajst-28595	44	24	used	use	VERB
ajst-28595	44	25	for	for	ADP
ajst-28595	44	26	communication	communication	NOUN
ajst-28595	44	27	between	between	ADP
ajst-28595	44	28	the	the	DET
ajst-28595	44	29	pc	pc	NOUN
ajst-28595	44	30	and	and	CCONJ
ajst-28595	44	31	the	the	DET
ajst-28595	44	32	machine	machine	NOUN
ajst-28595	44	33	tool	tool	NOUN
ajst-28595	44	34	,	,	PUNCT
ajst-28595	44	35	as	as	SCONJ
ajst-28595	44	36	shown	show	VERB
ajst-28595	44	37	in	in	ADP
ajst-28595	44	38	the	the	DET
ajst-28595	44	39	connection	connection	NOUN
ajst-28595	44	40	mechanism	mechanism	NOUN
ajst-28595	44	41	in	in	ADP
ajst-28595	44	42	figure	figure	NOUN
ajst-28595	44	43	2	2	NUM
ajst-28595	44	44	,	,	PUNCT
ajst-28595	44	45	to	to	PART
ajst-28595	44	46	achieve	achieve	VERB
ajst-28595	44	47	real	real	ADJ
ajst-28595	44	48	-	-	PUNCT
ajst-28595	44	49	time	time	NOUN
ajst-28595	44	50	data	datum	NOUN
ajst-28595	44	51	collection	collection	NOUN
ajst-28595	44	52	.	.	PUNCT
ajst-28595	45	1	connection	connection	NOUN
ajst-28595	45	2	status	status	PROPN
ajst-28595	45	3	indicator	indicator	PROPN
ajst-28595	45	4	light	light	ADJ
ajst-28595	45	5	network	network	NOUN
ajst-28595	45	6	cable	cable	NOUN
ajst-28595	45	7	pc	pc	NOUN
ajst-28595	45	8	data	datum	NOUN
ajst-28595	45	9	acquisition	acquisition	NOUN
ajst-28595	45	10	figure	figure	NOUN
ajst-28595	45	11	1	1	NUM
ajst-28595	45	12	.	.	PUNCT
ajst-28595	45	13	data	datum	NOUN
ajst-28595	45	14	acquisition	acquisition	NOUN
ajst-28595	45	15	experimental	experimental	ADJ
ajst-28595	45	16	platform	platform	NOUN
ajst-28595	45	17	for	for	ADP
ajst-28595	45	18	cnc	cnc	ADJ
ajst-28595	45	19	machine	machine	NOUN
ajst-28595	45	20	tools	tool	NOUN
ajst-28595	45	21	personal	personal	ADJ
ajst-28595	45	22	computer	computer	NOUN
ajst-28595	45	23	application	application	NOUN
ajst-28595	45	24	focas	foca	VERB
ajst-28595	45	25	fwlib64.dll	fwlib64.dll	PROPN
ajst-28595	45	26	tcp	tcp	PROPN
ajst-28595	45	27	/	/	SYM
ajst-28595	45	28	ip	ip	ADJ
ajst-28595	45	29	stack	stack	NOUN
ajst-28595	45	30	ethernet	ethernet	NOUN
ajst-28595	45	31	board	board	NOUN
ajst-28595	45	32	cnc	cnc	PROPN
ajst-28595	45	33	data	data	PROPN
ajst-28595	45	34	window	window	NOUN
ajst-28595	45	35	functions	function	NOUN
ajst-28595	45	36	open	open	VERB
ajst-28595	45	37	cnc	cnc	PROPN
ajst-28595	45	38	i	i	PROPN
ajst-28595	45	39	/	/	SYM
ajst-28595	45	40	f	f	PROPN
ajst-28595	45	41	tpc	tpc	PROPN
ajst-28595	45	42	/	/	SYM
ajst-28595	45	43	ip	ip	NOUN
ajst-28595	45	44	stack	stack	NOUN
ajst-28595	45	45	open	open	ADJ
ajst-28595	45	46	cnc	cnc	PROPN
ajst-28595	45	47	i	i	PROPN
ajst-28595	45	48	/	/	SYM
ajst-28595	45	49	f	f	PROPN
ajst-28595	45	50	personal	personal	ADJ
ajst-28595	45	51	computer	computer	NOUN
ajst-28595	45	52	proxy	proxy	NOUN
ajst-28595	45	53	functions	function	NOUN
ajst-28595	45	54	of	of	ADP
ajst-28595	45	55	data	datum	NOUN
ajst-28595	45	56	window	window	NOUN
ajst-28595	45	57	functions	function	NOUN
ajst-28595	45	58	ethernet	ethernet	NOUN
ajst-28595	45	59	board	board	NOUN
ajst-28595	45	60	bodies	body	NOUN
ajst-28595	45	61	of	of	ADP
ajst-28595	45	62	data	datum	NOUN
ajst-28595	45	63	window	window	NOUN
ajst-28595	45	64	functions	function	NOUN
ajst-28595	45	65	requst	requst	NOUN
ajst-28595	45	66	packet	packet	NOUN
ajst-28595	45	67	r	r	NOUN
ajst-28595	45	68	esponse	esponse	NOUN
ajst-28595	45	69	packet	packet	NOUN
ajst-28595	45	70	ethernet	ethernet	NOUN
ajst-28595	45	71	local	local	ADJ
ajst-28595	45	72	bus	bus	NOUN
ajst-28595	45	73	figure	figure	NOUN
ajst-28595	45	74	2	2	NUM
ajst-28595	45	75	.	.	PUNCT
ajst-28595	45	76	connection	connection	NOUN
ajst-28595	45	77	method	method	NOUN
ajst-28595	45	78	between	between	ADP
ajst-28595	45	79	machine	machine	NOUN
ajst-28595	45	80	tool	tool	NOUN
ajst-28595	45	81	and	and	CCONJ
ajst-28595	45	82	pc	pc	VERB
ajst-28595	45	83	the	the	DET
ajst-28595	45	84	machining	machining	NOUN
ajst-28595	45	85	cutting	cut	VERB
ajst-28595	45	86	parameters	parameter	NOUN
ajst-28595	45	87	are	be	AUX
ajst-28595	45	88	as	as	SCONJ
ajst-28595	45	89	shown	show	VERB
ajst-28595	45	90	in	in	ADP
ajst-28595	45	91	table	table	NOUN
ajst-28595	45	92	1	1	NUM
ajst-28595	45	93	.	.	PUNCT
ajst-28595	46	1	the	the	DET
ajst-28595	46	2	acquisition	acquisition	NOUN
ajst-28595	46	3	of	of	ADP
ajst-28595	46	4	signal	signal	ADJ
ajst-28595	46	5	stages	stage	NOUN
ajst-28595	46	6	mainly	mainly	ADV
ajst-28595	46	7	includes	include	VERB
ajst-28595	46	8	nine	nine	NUM
ajst-28595	46	9	data	datum	NOUN
ajst-28595	46	10	types	type	NOUN
ajst-28595	46	11	:	:	PUNCT
ajst-28595	46	12	tool	tool	NOUN
ajst-28595	46	13	running	running	NOUN
ajst-28595	46	14	time	time	NOUN
ajst-28595	46	15	,	,	PUNCT
ajst-28595	46	16	spindle	spindle	NOUN
ajst-28595	46	17	load	load	NOUN
ajst-28595	46	18	rate	rate	NOUN
ajst-28595	46	19	,	,	PUNCT
ajst-28595	46	20	spindle	spindle	NOUN
ajst-28595	46	21	load	load	NOUN
ajst-28595	46	22	,	,	PUNCT
ajst-28595	46	23	xaxis	xaxis	PROPN
ajst-28595	46	24	load	load	NOUN
ajst-28595	46	25	rate	rate	NOUN
ajst-28595	46	26	,	,	PUNCT
ajst-28595	46	27	y	y	NOUN
ajst-28595	46	28	-	-	PUNCT
ajst-28595	46	29	axis	axis	NOUN
ajst-28595	46	30	load	load	NOUN
ajst-28595	46	31	rate	rate	NOUN
ajst-28595	46	32	,	,	PUNCT
ajst-28595	46	33	z	z	NOUN
ajst-28595	46	34	-	-	PUNCT
ajst-28595	46	35	axis	axis	NOUN
ajst-28595	46	36	load	load	NOUN
ajst-28595	46	37	rate	rate	NOUN
ajst-28595	46	38	,	,	PUNCT
ajst-28595	46	39	x	x	ADJ
ajst-28595	46	40	-	-	ADJ
ajst-28595	46	41	axis	axis	ADJ
ajst-28595	46	42	current	current	ADJ
ajst-28595	46	43	,	,	PUNCT
ajst-28595	46	44	y	y	ADJ
ajst-28595	46	45	-	-	PUNCT
ajst-28595	46	46	axis	axis	NOUN
ajst-28595	46	47	current	current	NOUN
ajst-28595	46	48	,	,	PUNCT
ajst-28595	46	49	and	and	CCONJ
ajst-28595	46	50	z	z	NOUN
ajst-28595	46	51	-	-	PUNCT
ajst-28595	46	52	axis	axis	NOUN
ajst-28595	46	53	current	current	NOUN
ajst-28595	46	54	,	,	PUNCT
ajst-28595	46	55	with	with	ADP
ajst-28595	46	56	a	a	DET
ajst-28595	46	57	collection	collection	NOUN
ajst-28595	46	58	frequency	frequency	NOUN
ajst-28595	46	59	of	of	ADP
ajst-28595	46	60	once	once	ADV
ajst-28595	46	61	every	every	DET
ajst-28595	46	62	5	5	NUM
ajst-28595	46	63	seconds	second	NOUN
ajst-28595	46	64	.	.	PUNCT
ajst-28595	47	1	table	table	NOUN
ajst-28595	47	2	1	1	NUM
ajst-28595	47	3	.	.	PUNCT
ajst-28595	47	4	milling	milling	NOUN
ajst-28595	47	5	process	process	NOUN
ajst-28595	47	6	parameters	parameter	NOUN
ajst-28595	47	7	milling	mill	VERB
ajst-28595	47	8	parameters	parameter	NOUN
ajst-28595	47	9	value	value	NOUN
ajst-28595	47	10	spindle	spindle	NOUN
ajst-28595	47	11	speed	speed	NOUN
ajst-28595	47	12	950r	950r	NOUN
ajst-28595	47	13	/	/	SYM
ajst-28595	47	14	min	min	NOUN
ajst-28595	47	15	feed	feed	NOUN
ajst-28595	47	16	rate	rate	NOUN
ajst-28595	47	17	1500mm	1500mm	PROPN
ajst-28595	47	18	/	/	SYM
ajst-28595	47	19	min	min	NOUN
ajst-28595	47	20	milling	milling	NOUN
ajst-28595	47	21	depth	depth	NOUN
ajst-28595	47	22	1	1	NUM
ajst-28595	47	23	mm	mm	NOUN
ajst-28595	47	24	milling	milling	NOUN
ajst-28595	47	25	width	width	NOUN
ajst-28595	47	26	5	5	NUM
ajst-28595	47	27	mm	mm	NUM
ajst-28595	47	28	80	80	NUM
ajst-28595	47	29	2.2	2.2	NUM
ajst-28595	47	30	.	.	PUNCT
ajst-28595	48	1	data	datum	NOUN
ajst-28595	48	2	preprocessing	preprocessing	NOUN
ajst-28595	48	3	and	and	CCONJ
ajst-28595	48	4	setting	setting	NOUN
ajst-28595	48	5	of	of	ADP
ajst-28595	48	6	tool	tool	NOUN
ajst-28595	48	7	life	life	NOUN
ajst-28595	48	8	labels	label	NOUN
ajst-28595	48	9	due	due	ADP
ajst-28595	48	10	to	to	ADP
ajst-28595	48	11	the	the	DET
ajst-28595	48	12	fact	fact	NOUN
ajst-28595	48	13	that	that	SCONJ
ajst-28595	48	14	the	the	DET
ajst-28595	48	15	data	datum	NOUN
ajst-28595	48	16	originates	originate	VERB
ajst-28595	48	17	from	from	ADP
ajst-28595	48	18	actual	actual	ADJ
ajst-28595	48	19	industrial	industrial	ADJ
ajst-28595	48	20	processing	processing	NOUN
ajst-28595	48	21	,	,	PUNCT
ajst-28595	48	22	there	there	PRON
ajst-28595	48	23	are	be	VERB
ajst-28595	48	24	numerous	numerous	ADJ
ajst-28595	48	25	anomalies	anomaly	NOUN
ajst-28595	48	26	present	present	ADJ
ajst-28595	48	27	in	in	ADP
ajst-28595	48	28	the	the	DET
ajst-28595	48	29	data	datum	NOUN
ajst-28595	48	30	.	.	PUNCT
ajst-28595	49	1	as	as	SCONJ
ajst-28595	49	2	shown	show	VERB
ajst-28595	49	3	in	in	ADP
ajst-28595	49	4	figure	figure	NOUN
ajst-28595	49	5	3	3	NUM
ajst-28595	49	6	,	,	PUNCT
ajst-28595	49	7	this	this	PRON
ajst-28595	49	8	is	be	AUX
ajst-28595	49	9	the	the	DET
ajst-28595	49	10	raw	raw	ADJ
ajst-28595	49	11	data	datum	NOUN
ajst-28595	49	12	for	for	ADP
ajst-28595	49	13	tool	tool	NOUN
ajst-28595	49	14	a	a	NOUN
ajst-28595	49	15	,	,	PUNCT
ajst-28595	49	16	with	with	ADP
ajst-28595	49	17	the	the	DET
ajst-28595	49	18	red	red	PROPN
ajst-28595	49	19	box	box	PROPN
ajst-28595	49	20	highlighting	highlight	VERB
ajst-28595	49	21	the	the	DET
ajst-28595	49	22	anomalous	anomalous	ADJ
ajst-28595	49	23	data	datum	NOUN
ajst-28595	49	24	.	.	PUNCT
ajst-28595	50	1	anomalous	anomalous	ADJ
ajst-28595	50	2	values	value	NOUN
ajst-28595	50	3	refer	refer	VERB
ajst-28595	50	4	to	to	PART
ajst-28595	50	5	signal	signal	VERB
ajst-28595	50	6	points	point	NOUN
ajst-28595	50	7	that	that	PRON
ajst-28595	50	8	have	have	VERB
ajst-28595	50	9	unreasonable	unreasonable	ADJ
ajst-28595	50	10	assignments	assignment	NOUN
ajst-28595	50	11	,	,	PUNCT
ajst-28595	50	12	which	which	PRON
ajst-28595	50	13	occur	occur	VERB
ajst-28595	50	14	for	for	ADP
ajst-28595	50	15	the	the	DET
ajst-28595	50	16	following	follow	VERB
ajst-28595	50	17	reasons	reason	NOUN
ajst-28595	50	18	:	:	PUNCT
ajst-28595	50	19	(	(	PUNCT
ajst-28595	50	20	1	1	X
ajst-28595	50	21	)	)	PUNCT
ajst-28595	50	22	the	the	DET
ajst-28595	50	23	current	current	NOUN
ajst-28595	50	24	becomes	become	VERB
ajst-28595	50	25	very	very	ADV
ajst-28595	50	26	large	large	ADJ
ajst-28595	50	27	at	at	ADP
ajst-28595	50	28	the	the	DET
ajst-28595	50	29	moment	moment	NOUN
ajst-28595	50	30	the	the	DET
ajst-28595	50	31	tool	tool	NOUN
ajst-28595	50	32	cuts	cut	VERB
ajst-28595	50	33	into	into	ADP
ajst-28595	50	34	the	the	DET
ajst-28595	50	35	workpiece	workpiece	NOUN
ajst-28595	50	36	and	and	CCONJ
ajst-28595	50	37	the	the	DET
ajst-28595	50	38	moment	moment	NOUN
ajst-28595	50	39	the	the	DET
ajst-28595	50	40	tool	tool	NOUN
ajst-28595	50	41	cuts	cut	VERB
ajst-28595	50	42	past	past	ADP
ajst-28595	50	43	the	the	DET
ajst-28595	50	44	workpiece	workpiece	NOUN
ajst-28595	50	45	.	.	PUNCT
ajst-28595	51	1	(	(	PUNCT
ajst-28595	51	2	2	2	NUM
ajst-28595	51	3	)	)	PUNCT
ajst-28595	51	4	during	during	ADP
ajst-28595	51	5	processing	processing	NOUN
ajst-28595	51	6	,	,	PUNCT
ajst-28595	51	7	the	the	DET
ajst-28595	51	8	tool	tool	NOUN
ajst-28595	51	9	is	be	AUX
ajst-28595	51	10	not	not	PART
ajst-28595	51	11	always	always	ADV
ajst-28595	51	12	in	in	ADP
ajst-28595	51	13	contact	contact	NOUN
ajst-28595	51	14	with	with	ADP
ajst-28595	51	15	the	the	DET
ajst-28595	51	16	workpiece	workpiece	NOUN
ajst-28595	51	17	,	,	PUNCT
ajst-28595	51	18	resulting	result	VERB
ajst-28595	51	19	in	in	ADP
ajst-28595	51	20	the	the	DET
ajst-28595	51	21	tool	tool	NOUN
ajst-28595	51	22	running	run	VERB
ajst-28595	51	23	empty	empty	ADJ
ajst-28595	51	24	,	,	PUNCT
ajst-28595	51	25	which	which	PRON
ajst-28595	51	26	makes	make	VERB
ajst-28595	51	27	the	the	DET
ajst-28595	51	28	current	current	ADJ
ajst-28595	51	29	very	very	ADV
ajst-28595	51	30	small	small	ADJ
ajst-28595	51	31	.	.	PUNCT
ajst-28595	52	1	anomalous	anomalous	ADJ
ajst-28595	52	2	data	datum	NOUN
ajst-28595	52	3	can	can	AUX
ajst-28595	52	4	significantly	significantly	ADV
ajst-28595	52	5	affect	affect	VERB
ajst-28595	52	6	the	the	DET
ajst-28595	52	7	overall	overall	ADJ
ajst-28595	52	8	distribution	distribution	NOUN
ajst-28595	52	9	of	of	ADP
ajst-28595	52	10	the	the	DET
ajst-28595	52	11	data	datum	NOUN
ajst-28595	52	12	,	,	PUNCT
ajst-28595	52	13	leading	lead	VERB
ajst-28595	52	14	to	to	ADP
ajst-28595	52	15	the	the	DET
ajst-28595	52	16	tool	tool	NOUN
ajst-28595	52	17	life	life	NOUN
ajst-28595	52	18	prediction	prediction	NOUN
ajst-28595	52	19	model	model	NOUN
ajst-28595	52	20	learning	learn	VERB
ajst-28595	52	21	incorrect	incorrect	ADJ
ajst-28595	52	22	information	information	NOUN
ajst-28595	52	23	.	.	PUNCT
ajst-28595	53	1	therefore	therefore	ADV
ajst-28595	53	2	,	,	PUNCT
ajst-28595	53	3	it	it	PRON
ajst-28595	53	4	is	be	AUX
ajst-28595	53	5	necessary	necessary	ADJ
ajst-28595	53	6	to	to	PART
ajst-28595	53	7	preprocess	preprocess	VERB
ajst-28595	53	8	the	the	DET
ajst-28595	53	9	originally	originally	ADV
ajst-28595	53	10	collected	collect	VERB
ajst-28595	53	11	data	datum	NOUN
ajst-28595	53	12	.	.	PUNCT
ajst-28595	54	1	in	in	ADP
ajst-28595	54	2	this	this	DET
ajst-28595	54	3	paper	paper	NOUN
ajst-28595	54	4	,	,	PUNCT
ajst-28595	54	5	the	the	DET
ajst-28595	54	6	method	method	NOUN
ajst-28595	54	7	for	for	ADP
ajst-28595	54	8	handling	handle	VERB
ajst-28595	54	9	anomalous	anomalous	ADJ
ajst-28595	54	10	values	value	NOUN
ajst-28595	54	11	utilizes	utilize	VERB
ajst-28595	54	12	the	the	DET
ajst-28595	54	13	3𝜎	3𝜎	NUM
ajst-28595	54	14	criterion	criterion	NOUN
ajst-28595	54	15	and	and	CCONJ
ajst-28595	54	16	the	the	DET
ajst-28595	54	17	setting	setting	NOUN
ajst-28595	54	18	of	of	ADP
ajst-28595	54	19	a	a	DET
ajst-28595	54	20	spindle	spindle	NOUN
ajst-28595	54	21	load	load	NOUN
ajst-28595	54	22	threshold	threshold	NOUN
ajst-28595	54	23	method	method	NOUN
ajst-28595	54	24	[	[	X
ajst-28595	54	25	11	11	NUM
ajst-28595	54	26	]	]	PUNCT
ajst-28595	54	27	.	.	PUNCT
ajst-28595	55	1	the	the	DET
ajst-28595	55	2	spindle	spindle	NOUN
ajst-28595	55	3	load	load	NOUN
ajst-28595	55	4	threshold	threshold	NOUN
ajst-28595	55	5	method	method	NOUN
ajst-28595	55	6	involves	involve	VERB
ajst-28595	55	7	deleting	delete	VERB
ajst-28595	55	8	data	datum	NOUN
ajst-28595	55	9	where	where	SCONJ
ajst-28595	55	10	the	the	DET
ajst-28595	55	11	load	load	NOUN
ajst-28595	55	12	is	be	AUX
ajst-28595	55	13	less	less	ADJ
ajst-28595	55	14	than	than	ADP
ajst-28595	55	15	500	500	NUM
ajst-28595	55	16	,	,	PUNCT
ajst-28595	55	17	indicating	indicate	VERB
ajst-28595	55	18	that	that	SCONJ
ajst-28595	55	19	the	the	DET
ajst-28595	55	20	tool	tool	NOUN
ajst-28595	55	21	is	be	AUX
ajst-28595	55	22	running	run	VERB
ajst-28595	55	23	empty	empty	ADJ
ajst-28595	55	24	.	.	PUNCT
ajst-28595	56	1	the	the	DET
ajst-28595	56	2	current	current	ADJ
ajst-28595	56	3	signal	signal	NOUN
ajst-28595	56	4	after	after	SCONJ
ajst-28595	56	5	the	the	DET
ajst-28595	56	6	anomalous	anomalous	ADJ
ajst-28595	56	7	value	value	NOUN
ajst-28595	56	8	operation	operation	NOUN
ajst-28595	56	9	is	be	AUX
ajst-28595	56	10	shown	show	VERB
ajst-28595	56	11	in	in	ADP
ajst-28595	56	12	figure	figure	NOUN
ajst-28595	56	13	4	4	NUM
ajst-28595	56	14	.	.	PUNCT
ajst-28595	57	1	this	this	DET
ajst-28595	57	2	current	current	ADJ
ajst-28595	57	3	signal	signal	NOUN
ajst-28595	57	4	more	more	ADV
ajst-28595	57	5	accurately	accurately	ADV
ajst-28595	57	6	reflects	reflect	VERB
ajst-28595	57	7	the	the	DET
ajst-28595	57	8	signal	signal	ADJ
ajst-28595	57	9	fluctuations	fluctuation	NOUN
ajst-28595	57	10	during	during	ADP
ajst-28595	57	11	normal	normal	ADJ
ajst-28595	57	12	processing	processing	NOUN
ajst-28595	57	13	.	.	PUNCT
ajst-28595	58	1	a.x	a.x	NOUN
ajst-28595	58	2	-	-	ADJ
ajst-28595	58	3	axis	axis	ADJ
ajst-28595	58	4	servo	servo	NOUN
ajst-28595	58	5	current	current	ADJ
ajst-28595	58	6	b.y	b.y	NOUN
ajst-28595	58	7	-	-	PUNCT
ajst-28595	58	8	axis	axis	NOUN
ajst-28595	58	9	servo	servo	NOUN
ajst-28595	58	10	current	current	ADJ
ajst-28595	58	11	c.z	c.z	NOUN
ajst-28595	58	12	-	-	PUNCT
ajst-28595	58	13	axis	axis	NOUN
ajst-28595	58	14	servo	servo	NOUN
ajst-28595	58	15	current	current	ADJ
ajst-28595	58	16	figure	figure	NOUN
ajst-28595	58	17	3	3	NUM
ajst-28595	58	18	.	.	PUNCT
ajst-28595	58	19	data	datum	NOUN
ajst-28595	58	20	of	of	ADP
ajst-28595	58	21	currents	current	NOUN
ajst-28595	58	22	in	in	ADP
ajst-28595	58	23	each	each	DET
ajst-28595	58	24	axis	axis	NOUN
ajst-28595	58	25	before	before	ADP
ajst-28595	58	26	data	data	NOUN
ajst-28595	58	27	processing	process	VERB
ajst-28595	58	28	a.x	a.x	PROPN
ajst-28595	58	29	-	-	PUNCT
ajst-28595	58	30	axis	axis	ADJ
ajst-28595	58	31	servo	servo	NOUN
ajst-28595	58	32	current	current	ADJ
ajst-28595	58	33	b.y	b.y	NOUN
ajst-28595	58	34	-	-	PUNCT
ajst-28595	58	35	axis	axis	NOUN
ajst-28595	58	36	servo	servo	NOUN
ajst-28595	58	37	current	current	ADJ
ajst-28595	58	38	c.z	c.z	NOUN
ajst-28595	58	39	-	-	PUNCT
ajst-28595	58	40	axis	axis	NOUN
ajst-28595	58	41	servo	servo	NOUN
ajst-28595	58	42	current	current	ADJ
ajst-28595	58	43	figure	figure	NOUN
ajst-28595	58	44	4	4	NUM
ajst-28595	58	45	.	.	PUNCT
ajst-28595	58	46	data	datum	NOUN
ajst-28595	58	47	of	of	ADP
ajst-28595	58	48	currents	current	NOUN
ajst-28595	58	49	in	in	ADP
ajst-28595	58	50	each	each	DET
ajst-28595	58	51	axis	axis	NOUN
ajst-28595	58	52	after	after	SCONJ
ajst-28595	58	53	data	datum	NOUN
ajst-28595	58	54	processing	process	VERB
ajst-28595	58	55	this	this	DET
ajst-28595	58	56	paper	paper	NOUN
ajst-28595	58	57	takes	take	VERB
ajst-28595	58	58	the	the	DET
ajst-28595	58	59	data	datum	NOUN
ajst-28595	58	60	collected	collect	VERB
ajst-28595	58	61	from	from	ADP
ajst-28595	58	62	the	the	DET
ajst-28595	58	63	entire	entire	ADJ
ajst-28595	58	64	machining	machining	NOUN
ajst-28595	58	65	process	process	NOUN
ajst-28595	58	66	of	of	ADP
ajst-28595	58	67	a	a	DET
ajst-28595	58	68	brand	brand	NOUN
ajst-28595	58	69	-	-	PUNCT
ajst-28595	58	70	new	new	ADJ
ajst-28595	58	71	tool	tool	NOUN
ajst-28595	58	72	to	to	ADP
ajst-28595	58	73	the	the	DET
ajst-28595	58	74	point	point	NOUN
ajst-28595	58	75	of	of	ADP
ajst-28595	58	76	tool	tool	NOUN
ajst-28595	58	77	failure	failure	NOUN
ajst-28595	58	78	as	as	ADP
ajst-28595	58	79	the	the	DET
ajst-28595	58	80	basis	basis	NOUN
ajst-28595	58	81	for	for	ADP
ajst-28595	58	82	tool	tool	NOUN
ajst-28595	58	83	life	life	NOUN
ajst-28595	58	84	.	.	PUNCT
ajst-28595	59	1	the	the	DET
ajst-28595	59	2	setting	setting	NOUN
ajst-28595	59	3	of	of	ADP
ajst-28595	59	4	tool	tool	NOUN
ajst-28595	59	5	life	life	NOUN
ajst-28595	59	6	labels	label	NOUN
ajst-28595	59	7	is	be	AUX
ajst-28595	59	8	done	do	VERB
ajst-28595	59	9	before	before	ADP
ajst-28595	59	10	the	the	DET
ajst-28595	59	11	preprocessing	preprocessing	NOUN
ajst-28595	59	12	of	of	ADP
ajst-28595	59	13	the	the	DET
ajst-28595	59	14	tool	tool	NOUN
ajst-28595	59	15	data	datum	NOUN
ajst-28595	59	16	,	,	PUNCT
ajst-28595	59	17	where	where	SCONJ
ajst-28595	59	18	the	the	DET
ajst-28595	59	19	life	life	NOUN
ajst-28595	59	20	percentage	percentage	NOUN
ajst-28595	59	21	is	be	AUX
ajst-28595	59	22	set	set	VERB
ajst-28595	59	23	as	as	ADP
ajst-28595	59	24	the	the	DET
ajst-28595	59	25	life	life	NOUN
ajst-28595	59	26	label	label	NOUN
ajst-28595	59	27	.	.	PUNCT
ajst-28595	60	1	this	this	DET
ajst-28595	60	2	method	method	NOUN
ajst-28595	60	3	of	of	ADP
ajst-28595	60	4	label	label	NOUN
ajst-28595	60	5	setting	setting	NOUN
ajst-28595	60	6	transforms	transform	VERB
ajst-28595	60	7	the	the	DET
ajst-28595	60	8	operational	operational	ADJ
ajst-28595	60	9	life	life	NOUN
ajst-28595	60	10	of	of	ADP
ajst-28595	60	11	the	the	DET
ajst-28595	60	12	equipment	equipment	NOUN
ajst-28595	60	13	into	into	ADP
ajst-28595	60	14	a	a	DET
ajst-28595	60	15	percentage	percentage	NOUN
ajst-28595	60	16	,	,	PUNCT
ajst-28595	60	17	representing	represent	VERB
ajst-28595	60	18	the	the	DET
ajst-28595	60	19	process	process	NOUN
ajst-28595	60	20	from	from	ADP
ajst-28595	60	21	a	a	DET
ajst-28595	60	22	brand	brand	NOUN
ajst-28595	60	23	-	-	PUNCT
ajst-28595	60	24	new	new	ADJ
ajst-28595	60	25	tool	tool	NOUN
ajst-28595	60	26	to	to	ADP
ajst-28595	60	27	one	one	NUM
ajst-28595	60	28	that	that	PRON
ajst-28595	60	29	is	be	AUX
ajst-28595	60	30	completely	completely	ADV
ajst-28595	60	31	degraded	degraded	ADJ
ajst-28595	60	32	.	.	PUNCT
ajst-28595	61	1	since	since	SCONJ
ajst-28595	61	2	the	the	DET
ajst-28595	61	3	service	service	NOUN
ajst-28595	61	4	life	life	NOUN
ajst-28595	61	5	of	of	ADP
ajst-28595	61	6	tools	tool	NOUN
ajst-28595	61	7	of	of	ADP
ajst-28595	61	8	exactly	exactly	ADV
ajst-28595	61	9	the	the	DET
ajst-28595	61	10	same	same	ADJ
ajst-28595	61	11	specification	specification	NOUN
ajst-28595	61	12	is	be	AUX
ajst-28595	61	13	not	not	PART
ajst-28595	61	14	consistent	consistent	ADJ
ajst-28595	61	15	,	,	PUNCT
ajst-28595	61	16	each	each	DET
ajst-28595	61	17	tool	tool	NOUN
ajst-28595	61	18	's	's	PART
ajst-28595	61	19	life	life	NOUN
ajst-28595	61	20	data	datum	NOUN
ajst-28595	61	21	label	label	NOUN
ajst-28595	61	22	is	be	AUX
ajst-28595	61	23	set	set	VERB
ajst-28595	61	24	as	as	ADP
ajst-28595	61	25	a	a	DET
ajst-28595	61	26	value	value	NOUN
ajst-28595	61	27	between	between	ADP
ajst-28595	61	28	0	0	NUM
ajst-28595	61	29	-	-	SYM
ajst-28595	61	30	1	1	NUM
ajst-28595	61	31	,	,	PUNCT
ajst-28595	61	32	evenly	evenly	ADV
ajst-28595	61	33	distributed	distribute	VERB
ajst-28595	61	34	among	among	ADP
ajst-28595	61	35	each	each	DET
ajst-28595	61	36	set	set	NOUN
ajst-28595	61	37	of	of	ADP
ajst-28595	61	38	data	datum	NOUN
ajst-28595	61	39	[	[	X
ajst-28595	61	40	12	12	NUM
ajst-28595	61	41	]	]	PUNCT
ajst-28595	61	42	.	.	PUNCT
ajst-28595	62	1	3	3	X
ajst-28595	62	2	.	.	X
ajst-28595	62	3	tool	tool	NOUN
ajst-28595	62	4	life	life	NOUN
ajst-28595	62	5	prediction	prediction	NOUN
ajst-28595	62	6	algorithm	algorithm	NOUN
ajst-28595	62	7	3.1	3.1	NUM
ajst-28595	62	8	.	.	PUNCT
ajst-28595	63	1	bp	bp	PROPN
ajst-28595	63	2	neural	neural	PROPN
ajst-28595	63	3	network	network	NOUN
ajst-28595	63	4	prediction	prediction	NOUN
ajst-28595	63	5	algorithm	algorithm	NOUN
ajst-28595	63	6	the	the	DET
ajst-28595	63	7	bp	bp	PROPN
ajst-28595	63	8	(	(	PUNCT
ajst-28595	63	9	backpropagation	backpropagation	NOUN
ajst-28595	63	10	)	)	PUNCT
ajst-28595	63	11	neural	neural	ADJ
ajst-28595	63	12	network	network	NOUN
ajst-28595	64	1	[	[	X
ajst-28595	64	2	13	13	NUM
ajst-28595	64	3	]	]	PUNCT
ajst-28595	64	4	is	be	AUX
ajst-28595	64	5	a	a	DET
ajst-28595	64	6	multilayer	multilayer	ADJ
ajst-28595	64	7	feedforward	feedforward	NOUN
ajst-28595	64	8	artificial	artificial	ADJ
ajst-28595	64	9	neural	neural	ADJ
ajst-28595	64	10	network	network	NOUN
ajst-28595	64	11	that	that	PRON
ajst-28595	64	12	is	be	AUX
ajst-28595	64	13	trained	train	VERB
ajst-28595	64	14	through	through	ADP
ajst-28595	64	15	a	a	DET
ajst-28595	64	16	supervised	supervised	ADJ
ajst-28595	64	17	learning	learning	NOUN
ajst-28595	64	18	algorithm	algorithm	NOUN
ajst-28595	64	19	known	know	VERB
ajst-28595	64	20	as	as	ADP
ajst-28595	64	21	backpropagation	backpropagation	NOUN
ajst-28595	64	22	.	.	PUNCT
ajst-28595	65	1	the	the	DET
ajst-28595	65	2	bp	bp	PROPN
ajst-28595	65	3	neural	neural	PROPN
ajst-28595	65	4	network	network	NOUN
ajst-28595	65	5	mainly	mainly	ADV
ajst-28595	65	6	consists	consist	VERB
ajst-28595	65	7	of	of	ADP
ajst-28595	65	8	an	an	DET
ajst-28595	65	9	input	input	NOUN
ajst-28595	65	10	layer	layer	NOUN
ajst-28595	65	11	,	,	PUNCT
ajst-28595	65	12	hidden	hidden	ADJ
ajst-28595	65	13	layers	layer	NOUN
ajst-28595	65	14	,	,	PUNCT
ajst-28595	65	15	and	and	CCONJ
ajst-28595	65	16	an	an	DET
ajst-28595	65	17	output	output	NOUN
ajst-28595	65	18	layer	layer	NOUN
ajst-28595	65	19	,	,	PUNCT
ajst-28595	65	20	with	with	ADP
ajst-28595	65	21	each	each	DET
ajst-28595	65	22	layer	layer	NOUN
ajst-28595	65	23	comprising	comprise	VERB
ajst-28595	65	24	multiple	multiple	ADJ
ajst-28595	65	25	neurons	neuron	NOUN
ajst-28595	65	26	.	.	PUNCT
ajst-28595	66	1	each	each	DET
ajst-28595	66	2	neuron	neuron	NOUN
ajst-28595	66	3	can	can	AUX
ajst-28595	66	4	receive	receive	VERB
ajst-28595	66	5	input	input	NOUN
ajst-28595	66	6	from	from	ADP
ajst-28595	66	7	the	the	DET
ajst-28595	66	8	previous	previous	ADJ
ajst-28595	66	9	layer	layer	NOUN
ajst-28595	66	10	,	,	PUNCT
ajst-28595	66	11	transform	transform	VERB
ajst-28595	66	12	the	the	DET
ajst-28595	66	13	input	input	NOUN
ajst-28595	66	14	signals	signal	NOUN
ajst-28595	66	15	through	through	ADP
ajst-28595	66	16	an	an	DET
ajst-28595	66	17	activation	activation	NOUN
ajst-28595	66	18	function	function	NOUN
ajst-28595	66	19	,	,	PUNCT
ajst-28595	66	20	and	and	CCONJ
ajst-28595	66	21	then	then	ADV
ajst-28595	66	22	pass	pass	VERB
ajst-28595	66	23	them	they	PRON
ajst-28595	66	24	to	to	ADP
ajst-28595	66	25	the	the	DET
ajst-28595	66	26	next	next	ADJ
ajst-28595	66	27	layer	layer	NOUN
ajst-28595	66	28	.	.	PUNCT
ajst-28595	67	1	the	the	DET
ajst-28595	67	2	characteristics	characteristic	NOUN
ajst-28595	67	3	are	be	AUX
ajst-28595	67	4	:	:	PUNCT
ajst-28595	67	5	signals	signal	NOUN
ajst-28595	67	6	are	be	AUX
ajst-28595	67	7	propagated	propagate	VERB
ajst-28595	67	8	forward	forward	ADV
ajst-28595	67	9	,	,	PUNCT
ajst-28595	67	10	while	while	SCONJ
ajst-28595	67	11	errors	error	NOUN
ajst-28595	67	12	are	be	AUX
ajst-28595	67	13	propagated	propagate	VERB
ajst-28595	67	14	backward	backward	ADV
ajst-28595	67	15	.	.	PUNCT
ajst-28595	68	1	it	it	PRON
ajst-28595	68	2	has	have	VERB
ajst-28595	68	3	strong	strong	ADJ
ajst-28595	68	4	nonlinear	nonlinear	ADJ
ajst-28595	68	5	mapping	mapping	NOUN
ajst-28595	68	6	capabilities	capability	NOUN
ajst-28595	68	7	and	and	CCONJ
ajst-28595	68	8	a	a	DET
ajst-28595	68	9	flexible	flexible	ADJ
ajst-28595	68	10	network	network	NOUN
ajst-28595	68	11	structure	structure	NOUN
ajst-28595	68	12	,	,	PUNCT
ajst-28595	68	13	exhibiting	exhibit	VERB
ajst-28595	68	14	strong	strong	ADJ
ajst-28595	68	15	generalization	generalization	NOUN
ajst-28595	68	16	and	and	CCONJ
ajst-28595	68	17	fault	fault	VERB
ajst-28595	68	18	tolerance	tolerance	NOUN
ajst-28595	68	19	,	,	PUNCT
ajst-28595	68	20	allowing	allow	VERB
ajst-28595	68	21	for	for	ADP
ajst-28595	68	22	significant	significant	ADJ
ajst-28595	68	23	errors	error	NOUN
ajst-28595	68	24	or	or	CCONJ
ajst-28595	68	25	even	even	ADV
ajst-28595	68	26	individual	individual	ADJ
ajst-28595	68	27	mistakes	mistake	NOUN
ajst-28595	68	28	in	in	ADP
ajst-28595	68	29	input	input	NOUN
ajst-28595	68	30	samples	sample	NOUN
ajst-28595	68	31	.	.	PUNCT
ajst-28595	69	1	the	the	DET
ajst-28595	69	2	bp	bp	PROPN
ajst-28595	69	3	neural	neural	PROPN
ajst-28595	69	4	network	network	NOUN
ajst-28595	69	5	does	do	AUX
ajst-28595	69	6	not	not	PART
ajst-28595	69	7	require	require	VERB
ajst-28595	69	8	any	any	DET
ajst-28595	69	9	prior	prior	ADJ
ajst-28595	69	10	formulas	formula	NOUN
ajst-28595	69	11	and	and	CCONJ
ajst-28595	69	12	can	can	AUX
ajst-28595	69	13	automatically	automatically	ADV
ajst-28595	69	14	summarize	summarize	VERB
ajst-28595	69	15	the	the	DET
ajst-28595	69	16	functional	functional	ADJ
ajst-28595	69	17	relationships	relationship	NOUN
ajst-28595	69	18	between	between	ADP
ajst-28595	69	19	data	datum	NOUN
ajst-28595	69	20	through	through	ADP
ajst-28595	69	21	learning	learning	NOUN
ajst-28595	69	22	,	,	PUNCT
ajst-28595	69	23	making	make	VERB
ajst-28595	69	24	this	this	DET
ajst-28595	69	25	modeling	modeling	NOUN
ajst-28595	69	26	method	method	NOUN
ajst-28595	69	27	very	very	ADV
ajst-28595	69	28	effective	effective	ADJ
ajst-28595	69	29	.	.	PUNCT
ajst-28595	70	1	however	however	ADV
ajst-28595	70	2	,	,	PUNCT
ajst-28595	70	3	there	there	PRON
ajst-28595	70	4	are	be	VERB
ajst-28595	70	5	issues	issue	NOUN
ajst-28595	70	6	such	such	ADJ
ajst-28595	70	7	as	as	ADP
ajst-28595	70	8	the	the	DET
ajst-28595	70	9	training	training	NOUN
ajst-28595	70	10	process	process	NOUN
ajst-28595	70	11	of	of	ADP
ajst-28595	70	12	the	the	DET
ajst-28595	70	13	bp	bp	PROPN
ajst-28595	70	14	neural	neural	PROPN
ajst-28595	70	15	network	network	NOUN
ajst-28595	70	16	being	be	AUX
ajst-28595	70	17	potentially	potentially	ADV
ajst-28595	70	18	very	very	ADV
ajst-28595	70	19	time	time	NOUN
ajst-28595	70	20	-	-	PUNCT
ajst-28595	70	21	consuming	consume	VERB
ajst-28595	70	22	,	,	PUNCT
ajst-28595	70	23	especially	especially	ADV
ajst-28595	70	24	when	when	SCONJ
ajst-28595	70	25	dealing	deal	VERB
ajst-28595	70	26	with	with	ADP
ajst-28595	70	27	large	large	ADJ
ajst-28595	70	28	-	-	PUNCT
ajst-28595	70	29	scale	scale	NOUN
ajst-28595	70	30	datasets	dataset	NOUN
ajst-28595	70	31	,	,	PUNCT
ajst-28595	70	32	which	which	PRON
ajst-28595	70	33	may	may	AUX
ajst-28595	70	34	take	take	VERB
ajst-28595	70	35	hours	hour	NOUN
ajst-28595	70	36	or	or	CCONJ
ajst-28595	70	37	even	even	ADV
ajst-28595	70	38	days	day	NOUN
ajst-28595	70	39	to	to	PART
ajst-28595	70	40	achieve	achieve	VERB
ajst-28595	70	41	satisfactory	satisfactory	ADJ
ajst-28595	70	42	results	result	NOUN
ajst-28595	70	43	.	.	PUNCT
ajst-28595	71	1	it	it	PRON
ajst-28595	71	2	is	be	AUX
ajst-28595	71	3	also	also	ADV
ajst-28595	71	4	prone	prone	ADJ
ajst-28595	71	5	to	to	ADP
ajst-28595	71	6	getting	getting	AUX
ajst-28595	71	7	stuck	stick	VERB
ajst-28595	71	8	in	in	ADP
ajst-28595	71	9	local	local	ADJ
ajst-28595	71	10	optima	optima	NOUN
ajst-28595	71	11	.	.	PUNCT
ajst-28595	72	1	since	since	SCONJ
ajst-28595	72	2	the	the	DET
ajst-28595	72	3	bp	bp	PROPN
ajst-28595	72	4	algorithm	algorithm	PROPN
ajst-28595	72	5	essentially	essentially	ADV
ajst-28595	72	6	uses	use	VERB
ajst-28595	72	7	gradient	gradient	ADJ
ajst-28595	72	8	descent	descent	NOUN
ajst-28595	72	9	,	,	PUNCT
ajst-28595	72	10	the	the	DET
ajst-28595	72	11	objective	objective	ADJ
ajst-28595	72	12	function	function	NOUN
ajst-28595	72	13	to	to	PART
ajst-28595	72	14	be	be	AUX
ajst-28595	72	15	optimized	optimize	VERB
ajst-28595	72	16	is	be	AUX
ajst-28595	72	17	81	81	NUM
ajst-28595	72	18	very	very	ADV
ajst-28595	72	19	complex	complex	ADJ
ajst-28595	72	20	,	,	PUNCT
ajst-28595	72	21	leading	lead	VERB
ajst-28595	72	22	to	to	ADP
ajst-28595	72	23	low	low	ADJ
ajst-28595	72	24	training	training	NOUN
ajst-28595	72	25	efficiency	efficiency	NOUN
ajst-28595	72	26	and	and	CCONJ
ajst-28595	72	27	a	a	DET
ajst-28595	72	28	lack	lack	NOUN
ajst-28595	72	29	of	of	ADP
ajst-28595	72	30	global	global	ADJ
ajst-28595	72	31	search	search	NOUN
ajst-28595	72	32	capability	capability	NOUN
ajst-28595	72	33	,	,	PUNCT
ajst-28595	72	34	which	which	PRON
ajst-28595	72	35	can	can	AUX
ajst-28595	72	36	easily	easily	ADV
ajst-28595	72	37	result	result	VERB
ajst-28595	72	38	in	in	ADP
ajst-28595	72	39	the	the	DET
ajst-28595	72	40	training	training	NOUN
ajst-28595	72	41	being	be	AUX
ajst-28595	72	42	trapped	trap	VERB
ajst-28595	72	43	in	in	ADP
ajst-28595	72	44	local	local	ADJ
ajst-28595	72	45	areas	area	NOUN
ajst-28595	72	46	,	,	PUNCT
ajst-28595	72	47	leading	lead	VERB
ajst-28595	72	48	to	to	ADP
ajst-28595	72	49	local	local	ADJ
ajst-28595	72	50	optima	optima	NOUN
ajst-28595	72	51	and	and	CCONJ
ajst-28595	72	52	significant	significant	ADJ
ajst-28595	72	53	model	model	NOUN
ajst-28595	72	54	bias	bias	NOUN
ajst-28595	72	55	.	.	PUNCT
ajst-28595	73	1	the	the	DET
ajst-28595	73	2	bp	bp	PROPN
ajst-28595	73	3	neural	neural	PROPN
ajst-28595	73	4	network	network	NOUN
ajst-28595	73	5	used	use	VERB
ajst-28595	73	6	in	in	ADP
ajst-28595	73	7	this	this	DET
ajst-28595	73	8	paper	paper	NOUN
ajst-28595	73	9	is	be	AUX
ajst-28595	73	10	shown	show	VERB
ajst-28595	73	11	in	in	ADP
ajst-28595	73	12	figure	figure	NOUN
ajst-28595	73	13	5	5	NUM
ajst-28595	73	14	.	.	PUNCT
ajst-28595	73	15	spindle	spindle	NOUN
ajst-28595	73	16	load	load	NOUN
ajst-28595	73	17	spindle	spindle	NOUN
ajst-28595	73	18	load	load	NOUN
ajst-28595	73	19	ratio	ratio	NOUN
ajst-28595	73	20	tool	tool	NOUN
ajst-28595	73	21	running	running	NOUN
ajst-28595	73	22	time	time	NOUN
ajst-28595	73	23	x	x	NOUN
ajst-28595	73	24	-	-	ADJ
ajst-28595	73	25	axis	axis	ADJ
ajst-28595	73	26	current	current	ADJ
ajst-28595	73	27	y	y	ADJ
ajst-28595	73	28	-	-	PUNCT
ajst-28595	73	29	axis	axis	NOUN
ajst-28595	73	30	current	current	ADJ
ajst-28595	73	31	z	z	ADJ
ajst-28595	73	32	-	-	PUNCT
ajst-28595	73	33	axis	axis	ADJ
ajst-28595	73	34	current	current	ADJ
ajst-28595	73	35	input	input	NOUN
ajst-28595	73	36	layer	layer	NOUN
ajst-28595	73	37	hidden	hide	VERB
ajst-28595	73	38	layer	layer	NOUN
ajst-28595	73	39	output	output	NOUN
ajst-28595	73	40	layer	layer	NOUN
ajst-28595	73	41	.	.	PUNCT
ajst-28595	73	42	.	.	PUNCT
ajst-28595	73	43	.	.	PUNCT
ajst-28595	74	1	tool	tool	NOUN
ajst-28595	74	2	life	life	NOUN
ajst-28595	74	3	.	.	PUNCT
ajst-28595	74	4	.	.	PUNCT
ajst-28595	74	5	.	.	PUNCT
ajst-28595	74	6	.	.	PUNCT
ajst-28595	74	7	.	.	PUNCT
ajst-28595	74	8	.	.	PUNCT
ajst-28595	75	1	hidden	hide	VERB
ajst-28595	75	2	layer	layer	NOUN
ajst-28595	75	3	figure	figure	NOUN
ajst-28595	75	4	5	5	NUM
ajst-28595	75	5	.	.	PUNCT
ajst-28595	76	1	tool	tool	NOUN
ajst-28595	76	2	life	life	NOUN
ajst-28595	76	3	prediction	prediction	NOUN
ajst-28595	76	4	based	base	VERB
ajst-28595	76	5	on	on	ADP
ajst-28595	76	6	bp	bp	PROPN
ajst-28595	76	7	neural	neural	ADJ
ajst-28595	76	8	network	network	PROPN
ajst-28595	76	9	3.2	3.2	NUM
ajst-28595	76	10	.	.	PUNCT
ajst-28595	77	1	sparrow	sparrow	NOUN
ajst-28595	77	2	search	search	NOUN
ajst-28595	77	3	algorithm	algorithm	NOUN
ajst-28595	77	4	to	to	PART
ajst-28595	77	5	enhance	enhance	VERB
ajst-28595	77	6	the	the	DET
ajst-28595	77	7	global	global	ADJ
ajst-28595	77	8	search	search	NOUN
ajst-28595	77	9	capability	capability	NOUN
ajst-28595	77	10	and	and	CCONJ
ajst-28595	77	11	improve	improve	VERB
ajst-28595	77	12	the	the	DET
ajst-28595	77	13	accuracy	accuracy	NOUN
ajst-28595	77	14	of	of	ADP
ajst-28595	77	15	the	the	DET
ajst-28595	77	16	bp	bp	PROPN
ajst-28595	77	17	neural	neural	ADJ
ajst-28595	77	18	network	network	NOUN
ajst-28595	77	19	algorithm	algorithm	NOUN
ajst-28595	77	20	,	,	PUNCT
ajst-28595	77	21	the	the	DET
ajst-28595	77	22	sparrow	sparrow	ADJ
ajst-28595	77	23	search	search	NOUN
ajst-28595	77	24	algorithm	algorithm	NOUN
ajst-28595	77	25	(	(	PUNCT
ajst-28595	77	26	ssa	ssa	NOUN
ajst-28595	77	27	)	)	PUNCT
ajst-28595	78	1	[	[	X
ajst-28595	78	2	14	14	NUM
ajst-28595	78	3	]	]	X
ajst-28595	78	4	is	be	AUX
ajst-28595	78	5	utilized	utilize	VERB
ajst-28595	78	6	to	to	PART
ajst-28595	78	7	optimize	optimize	VERB
ajst-28595	78	8	the	the	DET
ajst-28595	78	9	weights	weight	NOUN
ajst-28595	78	10	and	and	CCONJ
ajst-28595	78	11	biases	bias	NOUN
ajst-28595	78	12	.	.	PUNCT
ajst-28595	79	1	the	the	DET
ajst-28595	79	2	ssa	ssa	NOUN
ajst-28595	79	3	is	be	AUX
ajst-28595	79	4	a	a	DET
ajst-28595	79	5	novel	novel	ADJ
ajst-28595	79	6	swarm	swarm	NOUN
ajst-28595	79	7	intelligence	intelligence	NOUN
ajst-28595	79	8	optimization	optimization	NOUN
ajst-28595	79	9	algorithm	algorithm	NOUN
ajst-28595	79	10	that	that	PRON
ajst-28595	79	11	simulates	simulate	VERB
ajst-28595	79	12	the	the	DET
ajst-28595	79	13	foraging	forage	VERB
ajst-28595	79	14	behavior	behavior	NOUN
ajst-28595	79	15	and	and	CCONJ
ajst-28595	79	16	anti	anti	ADJ
ajst-28595	79	17	-	-	ADJ
ajst-28595	79	18	predation	predation	ADJ
ajst-28595	79	19	behavior	behavior	NOUN
ajst-28595	79	20	of	of	ADP
ajst-28595	79	21	sparrows	sparrow	NOUN
ajst-28595	79	22	.	.	PUNCT
ajst-28595	80	1	the	the	DET
ajst-28595	80	2	basic	basic	ADJ
ajst-28595	80	3	principle	principle	NOUN
ajst-28595	80	4	is	be	AUX
ajst-28595	80	5	as	as	SCONJ
ajst-28595	80	6	follows	follow	VERB
ajst-28595	80	7	:	:	PUNCT
ajst-28595	80	8	in	in	ADP
ajst-28595	80	9	ssa	ssa	NOUN
ajst-28595	80	10	,	,	PUNCT
ajst-28595	80	11	the	the	DET
ajst-28595	80	12	position	position	NOUN
ajst-28595	80	13	of	of	ADP
ajst-28595	80	14	each	each	DET
ajst-28595	80	15	sparrow	sparrow	NOUN
ajst-28595	80	16	corresponds	correspond	VERB
ajst-28595	80	17	to	to	ADP
ajst-28595	80	18	one	one	NUM
ajst-28595	80	19	solution	solution	NOUN
ajst-28595	80	20	.	.	PUNCT
ajst-28595	81	1	during	during	ADP
ajst-28595	81	2	the	the	DET
ajst-28595	81	3	foraging	forage	VERB
ajst-28595	81	4	process	process	NOUN
ajst-28595	81	5	,	,	PUNCT
ajst-28595	81	6	sparrows	sparrow	NOUN
ajst-28595	81	7	exhibit	exhibit	VERB
ajst-28595	81	8	three	three	NUM
ajst-28595	81	9	types	type	NOUN
ajst-28595	81	10	of	of	ADP
ajst-28595	81	11	behaviors	behavior	NOUN
ajst-28595	81	12	:	:	PUNCT
ajst-28595	81	13	acting	act	VERB
ajst-28595	81	14	as	as	ADP
ajst-28595	81	15	discoverers	discoverer	NOUN
ajst-28595	81	16	to	to	PART
ajst-28595	81	17	search	search	VERB
ajst-28595	81	18	for	for	ADP
ajst-28595	81	19	food	food	NOUN
ajst-28595	81	20	;	;	PUNCT
ajst-28595	81	21	the	the	DET
ajst-28595	81	22	position	position	NOUN
ajst-28595	81	23	update	update	NOUN
ajst-28595	81	24	of	of	ADP
ajst-28595	81	25	discoverers	discoverer	NOUN
ajst-28595	81	26	can	can	AUX
ajst-28595	81	27	be	be	AUX
ajst-28595	81	28	represented	represent	VERB
ajst-28595	81	29	by	by	ADP
ajst-28595	81	30	the	the	DET
ajst-28595	81	31	following	follow	VERB
ajst-28595	81	32	formula	formula	NOUN
ajst-28595	81	33	:	:	PUNCT
ajst-28595	81	34	where	where	SCONJ
ajst-28595	81	35	1	1	X
ajst-28595	81	36	,	,	PUNCT
ajst-28595	81	37	x	x	PROPN
ajst-28595	81	38	t	t	NOUN
ajst-28595	82	1	i	i	PRON
ajst-28595	82	2	j	j	PROPN
ajst-28595	82	3			ADV
ajst-28595	82	4	is	be	AUX
ajst-28595	82	5	the	the	DET
ajst-28595	82	6	position	position	NOUN
ajst-28595	82	7	information	information	NOUN
ajst-28595	82	8	of	of	ADP
ajst-28595	82	9	the	the	DET
ajst-28595	82	10	i	i	PROPN
ajst-28595	82	11	sparrow	sparrow	VERB
ajst-28595	82	12	in	in	ADP
ajst-28595	82	13	the	the	DET
ajst-28595	82	14	population	population	NOUN
ajst-28595	82	15	at	at	ADP
ajst-28595	82	16	the	the	DET
ajst-28595	82	17	t	t	PROPN
ajst-28595	82	18	iteration	iteration	NOUN
ajst-28595	82	19	in	in	ADP
ajst-28595	82	20	the	the	DET
ajst-28595	82	21	search	search	NOUN
ajst-28595	82	22	space	space	NOUN
ajst-28595	82	23	of	of	ADP
ajst-28595	82	24	dimension	dimension	PROPN
ajst-28595	82	25	j	j	PROPN
ajst-28595	82	26	;	;	PUNCT
ajst-28595	82	27	ii	ii	PROPN
ajst-28595	82	28	is	be	AUX
ajst-28595	82	29	the	the	DET
ajst-28595	82	30	sparrow	sparrow	ADJ
ajst-28595	82	31	index	index	NOUN
ajst-28595	82	32	;	;	PUNCT
ajst-28595	82	33	maxiter	maxiter	X
ajst-28595	82	34	is	be	AUX
ajst-28595	82	35	the	the	DET
ajst-28595	82	36	maximum	maximum	ADJ
ajst-28595	82	37	number	number	NOUN
ajst-28595	82	38	of	of	ADP
ajst-28595	82	39	iterations	iteration	NOUN
ajst-28595	82	40	;	;	PUNCT
ajst-28595	82	41	δ	δ	PROPN
ajst-28595	82	42	is	be	AUX
ajst-28595	82	43	a	a	DET
ajst-28595	82	44	random	random	ADJ
ajst-28595	82	45	number	number	NOUN
ajst-28595	82	46	between	between	ADP
ajst-28595	82	47	(	(	PUNCT
ajst-28595	82	48	0	0	NUM
ajst-28595	82	49	,	,	PUNCT
ajst-28595	82	50	1	1	NUM
ajst-28595	82	51	]	]	PUNCT
ajst-28595	82	52	;	;	PUNCT
ajst-28595	82	53	q	q	X
ajst-28595	82	54	is	be	AUX
ajst-28595	82	55	a	a	DET
ajst-28595	82	56	random	random	ADJ
ajst-28595	82	57	number	number	NOUN
ajst-28595	82	58	following	follow	VERB
ajst-28595	82	59	a	a	DET
ajst-28595	82	60	normal	normal	ADJ
ajst-28595	82	61	distribution	distribution	NOUN
ajst-28595	82	62	;	;	PUNCT
ajst-28595	82	63	2r	2r	NUM
ajst-28595	82	64	is	be	AUX
ajst-28595	82	65	an	an	DET
ajst-28595	82	66	alert	alert	ADJ
ajst-28595	82	67	value	value	NOUN
ajst-28595	82	68	[	[	X
ajst-28595	82	69	0,1	0,1	NUM
ajst-28595	82	70	]	]	PUNCT
ajst-28595	82	71	;	;	PUNCT
ajst-28595	82	72	s	s	X
ajst-28595	82	73	is	be	AUX
ajst-28595	82	74	a	a	DET
ajst-28595	82	75	safety	safety	NOUN
ajst-28595	82	76	value	value	NOUN
ajst-28595	82	77	[	[	X
ajst-28595	82	78	0.5	0.5	NUM
ajst-28595	82	79	,	,	PUNCT
ajst-28595	82	80	1	1	NUM
ajst-28595	82	81	]	]	PUNCT
ajst-28595	82	82	.	.	PUNCT
ajst-28595	83	1	l	l	NOUN
ajst-28595	83	2	is	be	AUX
ajst-28595	83	3	a	a	DET
ajst-28595	83	4	1×d	1×d	NUM
ajst-28595	83	5	matrix	matrix	NOUN
ajst-28595	83	6	with	with	ADP
ajst-28595	83	7	internal	internal	ADJ
ajst-28595	83	8	elements	element	NOUN
ajst-28595	83	9	being	be	AUX
ajst-28595	83	10	1	1	NUM
ajst-28595	83	11	,	,	PUNCT
ajst-28595	83	12	and	and	CCONJ
ajst-28595	83	13	d	d	NOUN
ajst-28595	83	14	is	be	AUX
ajst-28595	83	15	the	the	DET
ajst-28595	83	16	dimension	dimension	NOUN
ajst-28595	83	17	.	.	PUNCT
ajst-28595	84	1	when	when	SCONJ
ajst-28595	84	2	r2	r2	PROPN
ajst-28595	84	3	<	<	X
ajst-28595	84	4	s	s	X
ajst-28595	84	5	,	,	PUNCT
ajst-28595	84	6	there	there	PRON
ajst-28595	84	7	are	be	VERB
ajst-28595	84	8	no	no	DET
ajst-28595	84	9	predators	predator	NOUN
ajst-28595	84	10	in	in	ADP
ajst-28595	84	11	the	the	DET
ajst-28595	84	12	foraging	forage	VERB
ajst-28595	84	13	environment	environment	NOUN
ajst-28595	84	14	,	,	PUNCT
ajst-28595	84	15	and	and	CCONJ
ajst-28595	84	16	discoverers	discoverer	NOUN
ajst-28595	84	17	will	will	AUX
ajst-28595	84	18	conduct	conduct	VERB
ajst-28595	84	19	a	a	DET
ajst-28595	84	20	broad	broad	ADJ
ajst-28595	84	21	search	search	NOUN
ajst-28595	84	22	within	within	ADP
ajst-28595	84	23	the	the	DET
ajst-28595	84	24	area	area	NOUN
ajst-28595	84	25	;	;	PUNCT
ajst-28595	84	26	when	when	SCONJ
ajst-28595	84	27	r2≥s	r2≥	NOUN
ajst-28595	84	28	,	,	PUNCT
ajst-28595	84	29	the	the	DET
ajst-28595	84	30	scouts	scout	NOUN
ajst-28595	84	31	detect	detect	VERB
ajst-28595	84	32	the	the	DET
ajst-28595	84	33	presence	presence	NOUN
ajst-28595	84	34	of	of	ADP
ajst-28595	84	35	predators	predator	NOUN
ajst-28595	84	36	,	,	PUNCT
ajst-28595	84	37	and	and	CCONJ
ajst-28595	84	38	the	the	DET
ajst-28595	84	39	flock	flock	NOUN
ajst-28595	84	40	quickly	quickly	ADV
ajst-28595	84	41	moves	move	VERB
ajst-28595	84	42	to	to	ADP
ajst-28595	84	43	a	a	DET
ajst-28595	84	44	safe	safe	ADJ
ajst-28595	84	45	area	area	NOUN
ajst-28595	84	46	.	.	PUNCT
ajst-28595	85	1	the	the	DET
ajst-28595	85	2	position	position	NOUN
ajst-28595	85	3	update	update	NOUN
ajst-28595	85	4	formula	formula	NOUN
ajst-28595	85	5	for	for	ADP
ajst-28595	85	6	the	the	DET
ajst-28595	85	7	followers	follower	NOUN
ajst-28595	85	8	is	be	AUX
ajst-28595	85	9	:	:	PUNCT
ajst-28595	85	10	,	,	PUNCT
ajst-28595	85	11	2	2	NUM
ajst-28595	85	12	1	1	NUM
ajst-28595	85	13	1	1	NUM
ajst-28595	85	14	,	,	PUNCT
ajst-28595	85	15	exp	exp	NOUN
ajst-28595	85	16	21	21	NUM
ajst-28595	85	17	,	,	PUNCT
ajst-28595	85	18	2	2	NUM
ajst-28595	85	19	t	t	NOUN
ajst-28595	85	20	t	t	NOUN
ajst-28595	86	1	wrost	wrost	ADV
ajst-28595	87	1	i	i	PRON
ajst-28595	87	2	j	j	PROPN
ajst-28595	88	1	t	t	PROPN
ajst-28595	88	2	t	t	PROPN
ajst-28595	88	3	t	t	PROPN
ajst-28595	88	4	p	p	X
ajst-28595	89	1	i	i	PRON
ajst-28595	89	2	j	j	PROPN
ajst-28595	90	1	p	p	X
ajst-28595	90	2	x	x	X
ajst-28595	90	3	x	x	PROPN
ajst-28595	90	4	n	n	PRON
ajst-28595	90	5	q	q	NOUN
ajst-28595	91	1	i	i	PRON
ajst-28595	91	2	it	it	PRON
ajst-28595	92	1	i	i	INTJ
ajst-28595	92	2	j	j	VERB
ajst-28595	93	1	n	n	INTJ
ajst-28595	93	2	x	x	NOUN
ajst-28595	93	3	x	x	PUNCT
ajst-28595	93	4	x	x	X
ajst-28595	93	5	a	a	DET
ajst-28595	93	6	l	l	NOUN
ajst-28595	94	1	i	i	NOUN
ajst-28595	94	2	x	x	PROPN
ajst-28595	94	3			PROPN
ajst-28595	94	4			VERB
ajst-28595	94	5			PUNCT
ajst-28595	94	6			NOUN
ajst-28595	94	7			PROPN
ajst-28595	94	8			PROPN
ajst-28595	94	9			PROPN
ajst-28595	95	1			VERB
ajst-28595	95	2			PROPN
ajst-28595	95	3			PROPN
ajst-28595	96	1			PROPN
ajst-28595	96	2			PROPN
ajst-28595	96	3			VERB
ajst-28595	96	4			VERB
ajst-28595	96	5			NOUN
ajst-28595	96	6			ADP
ajst-28595	96	7			PROPN
ajst-28595	96	8			NUM
ajst-28595	96	9			NOUN
ajst-28595	96	10	in	in	ADP
ajst-28595	96	11	the	the	DET
ajst-28595	96	12	formula	formula	NOUN
ajst-28595	96	13	:	:	PUNCT
ajst-28595	96	14	1	1	NUM
ajst-28595	96	15	t	t	NOUN
ajst-28595	96	16	px	px	PROPN
ajst-28595	96	17			ADV
ajst-28595	96	18	represents	represent	VERB
ajst-28595	96	19	the	the	DET
ajst-28595	96	20	position	position	NOUN
ajst-28595	96	21	with	with	ADP
ajst-28595	96	22	the	the	DET
ajst-28595	96	23	best	good	ADJ
ajst-28595	96	24	fitness	fitness	NOUN
ajst-28595	96	25	controlled	control	VERB
ajst-28595	96	26	by	by	ADP
ajst-28595	96	27	the	the	DET
ajst-28595	96	28	discoverer	discoverer	NOUN
ajst-28595	96	29	at	at	ADP
ajst-28595	96	30	the	the	DET
ajst-28595	96	31	t+1	t+1	PROPN
ajst-28595	96	32	iteration	iteration	NOUN
ajst-28595	96	33	;	;	PUNCT
ajst-28595	96	34	t	t	PROPN
ajst-28595	96	35	worstx	worstx	NOUN
ajst-28595	96	36	represents	represent	VERB
ajst-28595	96	37	the	the	DET
ajst-28595	96	38	current	current	ADJ
ajst-28595	96	39	global	global	ADJ
ajst-28595	96	40	worst	bad	ADJ
ajst-28595	96	41	position;n	position;n	NOUN
ajst-28595	96	42	indicates	indicate	VERB
ajst-28595	96	43	the	the	DET
ajst-28595	96	44	number	number	NOUN
ajst-28595	96	45	of	of	ADP
ajst-28595	96	46	individuals	individual	NOUN
ajst-28595	96	47	in	in	ADP
ajst-28595	96	48	the	the	DET
ajst-28595	96	49	sparrow	sparrow	NOUN
ajst-28595	96	50	flock	flock	NOUN
ajst-28595	96	51	.	.	PUNCT
ajst-28595	97	1	when	when	SCONJ
ajst-28595	97	2	i	i	PRON
ajst-28595	97	3	>	>	X
ajst-28595	97	4	n/2	n/2	PROPN
ajst-28595	97	5	,	,	PUNCT
ajst-28595	97	6	the	the	DET
ajst-28595	97	7	ii	ii	PROPN
ajst-28595	97	8	-	-	PUNCT
ajst-28595	97	9	th	th	VERB
ajst-28595	97	10	follower	follower	NOUN
ajst-28595	97	11	,	,	PUNCT
ajst-28595	97	12	unable	unable	ADJ
ajst-28595	97	13	to	to	PART
ajst-28595	97	14	acquire	acquire	VERB
ajst-28595	97	15	food	food	NOUN
ajst-28595	97	16	and	and	CCONJ
ajst-28595	97	17	with	with	ADP
ajst-28595	97	18	a	a	DET
ajst-28595	97	19	low	low	ADJ
ajst-28595	97	20	energy	energy	NOUN
ajst-28595	97	21	level	level	NOUN
ajst-28595	97	22	,	,	PUNCT
ajst-28595	97	23	needs	need	VERB
ajst-28595	97	24	to	to	PART
ajst-28595	97	25	move	move	VERB
ajst-28595	97	26	to	to	ADP
ajst-28595	97	27	another	another	DET
ajst-28595	97	28	area	area	NOUN
ajst-28595	97	29	to	to	PART
ajst-28595	97	30	forage	forage	VERB
ajst-28595	97	31	;	;	PUNCT
ajst-28595	97	32	when	when	SCONJ
ajst-28595	97	33	i≤2n	i≤2n	PROPN
ajst-28595	97	34	,	,	PUNCT
ajst-28595	97	35	the	the	DET
ajst-28595	97	36	i	i	PROPN
ajst-28595	97	37	follower	follower	NOUN
ajst-28595	97	38	will	will	AUX
ajst-28595	97	39	follow	follow	VERB
ajst-28595	97	40	the	the	DET
ajst-28595	97	41	foraging	forage	VERB
ajst-28595	97	42	center	center	NOUN
ajst-28595	97	43	of	of	ADP
ajst-28595	97	44	the	the	DET
ajst-28595	97	45	discoverers	discoverer	NOUN
ajst-28595	97	46	and	and	CCONJ
ajst-28595	97	47	forage	forage	NOUN
ajst-28595	97	48	randomly	randomly	ADV
ajst-28595	97	49	near	near	ADP
ajst-28595	97	50	the	the	DET
ajst-28595	97	51	center	center	NOUN
ajst-28595	97	52	.	.	PUNCT
ajst-28595	98	1	usually	usually	ADV
ajst-28595	98	2	,	,	PUNCT
ajst-28595	98	3	the	the	DET
ajst-28595	98	4	proportion	proportion	NOUN
ajst-28595	98	5	of	of	ADP
ajst-28595	98	6	sentinels	sentinel	NOUN
ajst-28595	98	7	in	in	ADP
ajst-28595	98	8	the	the	DET
ajst-28595	98	9	sparrow	sparrow	ADJ
ajst-28595	98	10	population	population	NOUN
ajst-28595	98	11	is	be	AUX
ajst-28595	98	12	only	only	ADV
ajst-28595	98	13	10	10	NUM
ajst-28595	98	14	%	%	NOUN
ajst-28595	98	15	to	to	PART
ajst-28595	98	16	20	20	NUM
ajst-28595	98	17	%	%	NOUN
ajst-28595	98	18	,	,	PUNCT
ajst-28595	98	19	and	and	CCONJ
ajst-28595	98	20	their	their	PRON
ajst-28595	98	21	position	position	NOUN
ajst-28595	98	22	update	update	NOUN
ajst-28595	98	23	is	be	AUX
ajst-28595	98	24	as	as	SCONJ
ajst-28595	98	25	follows	follow	VERB
ajst-28595	98	26	:	:	PUNCT
ajst-28595	98	27			NOUN
ajst-28595	98	28			PUNCT
ajst-28595	98	29	best	good	ADJ
ajst-28595	98	30	,	,	PUNCT
ajst-28595	98	31	,	,	PUNCT
ajst-28595	98	32	,	,	PUNCT
ajst-28595	98	33	1	1	NUM
ajst-28595	98	34	,	,	PUNCT
ajst-28595	99	1	t	t	PROPN
ajst-28595	99	2	t	t	PROPN
ajst-28595	99	3	t	t	PROPN
ajst-28595	100	1	i	i	PRON
ajst-28595	100	2	j	j	PROPN
ajst-28595	101	1	best	good	ADJ
ajst-28595	101	2	i	i	PRON
ajst-28595	101	3	g	g	PROPN
ajst-28595	102	1	t	t	PROPN
ajst-28595	102	2	t	t	PROPN
ajst-28595	103	1	i	i	PRON
ajst-28595	103	2	j	j	PROPN
ajst-28595	103	3	wrostt	wrostt	NOUN
ajst-28595	104	1	i	i	PRON
ajst-28595	104	2	j	j	VERB
ajst-28595	105	1	i	i	PRON
ajst-28595	105	2	g	g	VERB
ajst-28595	106	1	i	i	INTJ
ajst-28595	106	2	w	w	VERB
ajst-28595	107	1	x	x	X
ajst-28595	107	2	x	x	PUNCT
ajst-28595	107	3	x	x	SYM
ajst-28595	107	4	f	f	X
ajst-28595	107	5	ft	ft	NOUN
ajst-28595	108	1	i	i	INTJ
ajst-28595	108	2	j	j	PROPN
ajst-28595	109	1	x	x	PUNCT
ajst-28595	109	2	x	x	PUNCT
ajst-28595	109	3	x	x	PUNCT
ajst-28595	110	1	k	k	NOUN
ajst-28595	110	2	f	f	X
ajst-28595	111	1	f	f	X
ajst-28595	111	2	f	f	PROPN
ajst-28595	111	3	f	f	PROPN
ajst-28595	111	4	x	x	PROPN
ajst-28595	111	5			PROPN
ajst-28595	111	6			PROPN
ajst-28595	111	7			VERB
ajst-28595	111	8			PROPN
ajst-28595	111	9			PROPN
ajst-28595	111	10			PROPN
ajst-28595	111	11			PROPN
ajst-28595	111	12			NOUN
ajst-28595	111	13			ADV
ajst-28595	111	14			NUM
ajst-28595	111	15			NOUN
ajst-28595	111	16			NOUN
ajst-28595	111	17			ADV
ajst-28595	111	18			VERB
ajst-28595	111	19			PROPN
ajst-28595	111	20			ADP
ajst-28595	111	21			NUM
ajst-28595	111	22			NOUN
ajst-28595	111	23			NUM
ajst-28595	111	24			NUM
ajst-28595	111	25			NOUN
ajst-28595	111	26	in	in	ADP
ajst-28595	111	27	the	the	DET
ajst-28595	111	28	formula	formula	NOUN
ajst-28595	111	29	:	:	PUNCT
ajst-28595	111	30	t	t	PROPN
ajst-28595	111	31	bestx	bestx	NOUN
ajst-28595	111	32	represents	represent	VERB
ajst-28595	111	33	the	the	DET
ajst-28595	111	34	current	current	ADJ
ajst-28595	111	35	global	global	ADJ
ajst-28595	111	36	best	good	ADJ
ajst-28595	111	37	position	position	NOUN
ajst-28595	111	38	;	;	PUNCT
ajst-28595	111	39	β	β	X
ajst-28595	111	40	is	be	AUX
ajst-28595	111	41	a	a	DET
ajst-28595	111	42	random	random	ADJ
ajst-28595	111	43	number	number	NOUN
ajst-28595	111	44	following	follow	VERB
ajst-28595	111	45	a	a	DET
ajst-28595	111	46	standard	standard	ADJ
ajst-28595	111	47	normal	normal	ADJ
ajst-28595	111	48	distribution	distribution	NOUN
ajst-28595	111	49	,	,	PUNCT
ajst-28595	111	50	k	k	PROPN
ajst-28595	111	51	is	be	AUX
ajst-28595	111	52	the	the	DET
ajst-28595	111	53	direction	direction	NOUN
ajst-28595	111	54	of	of	ADP
ajst-28595	111	55	sparrow	sparrow	NOUN
ajst-28595	111	56	movement	movement	NOUN
ajst-28595	111	57	,	,	PUNCT
ajst-28595	111	58	and	and	CCONJ
ajst-28595	111	59	both	both	DET
ajst-28595	111	60	β	β	X
ajst-28595	111	61	and	and	CCONJ
ajst-28595	111	62	k	k	PROPN
ajst-28595	111	63	are	be	AUX
ajst-28595	111	64	step	step	NOUN
ajst-28595	111	65	size	size	NOUN
ajst-28595	111	66	control	control	NOUN
ajst-28595	111	67	parameters	parameter	NOUN
ajst-28595	111	68	;	;	PUNCT
ajst-28595	111	69	ε	ε	PROPN
ajst-28595	111	70	is	be	AUX
ajst-28595	111	71	a	a	DET
ajst-28595	111	72	constant	constant	ADJ
ajst-28595	111	73	used	use	VERB
ajst-28595	111	74	to	to	PART
ajst-28595	111	75	prevent	prevent	VERB
ajst-28595	111	76	division	division	NOUN
ajst-28595	111	77	by	by	ADP
ajst-28595	111	78	zero	zero	NUM
ajst-28595	111	79	;	;	PUNCT
ajst-28595	111	80	if	if	SCONJ
ajst-28595	111	81	is	be	AUX
ajst-28595	111	82	the	the	DET
ajst-28595	111	83	fitness	fitness	NOUN
ajst-28595	111	84	value	value	NOUN
ajst-28595	111	85	of	of	ADP
ajst-28595	111	86	the	the	DET
ajst-28595	111	87	i	i	PRON
ajst-28595	111	88	sparrow	sparrow	VERB
ajst-28595	111	89	;	;	PUNCT
ajst-28595	111	90	gf	gf	PROPN
ajst-28595	111	91	and	and	CCONJ
ajst-28595	111	92	wf	wf	PROPN
ajst-28595	111	93	are	be	AUX
ajst-28595	111	94	the	the	DET
ajst-28595	111	95	current	current	ADJ
ajst-28595	111	96	best	good	ADJ
ajst-28595	111	97	and	and	CCONJ
ajst-28595	111	98	worst	bad	ADJ
ajst-28595	111	99	fitness	fitness	NOUN
ajst-28595	111	100	values	value	NOUN
ajst-28595	111	101	,	,	PUNCT
ajst-28595	111	102	respectively	respectively	ADV
ajst-28595	111	103	.	.	PUNCT
ajst-28595	112	1	when	when	SCONJ
ajst-28595	112	2	if	if	SCONJ
ajst-28595	112	3	>	>	X
ajst-28595	112	4	gf	gf	NOUN
ajst-28595	112	5	,	,	PUNCT
ajst-28595	112	6	the	the	DET
ajst-28595	112	7	sparrow	sparrow	NOUN
ajst-28595	112	8	is	be	AUX
ajst-28595	112	9	at	at	ADP
ajst-28595	112	10	the	the	DET
ajst-28595	112	11	edge	edge	NOUN
ajst-28595	112	12	of	of	ADP
ajst-28595	112	13	the	the	DET
ajst-28595	112	14	population	population	NOUN
ajst-28595	112	15	and	and	CCONJ
ajst-28595	112	16	is	be	AUX
ajst-28595	112	17	more	more	ADV
ajst-28595	112	18	susceptible	susceptible	ADJ
ajst-28595	112	19	to	to	ADP
ajst-28595	112	20	predators	predator	NOUN
ajst-28595	112	21	;	;	PUNCT
ajst-28595	112	22	when	when	SCONJ
ajst-28595	112	23	if	if	SCONJ
ajst-28595	112	24	=	=	PRON
ajst-28595	112	25	gf	gf	NOUN
ajst-28595	112	26	,	,	PUNCT
ajst-28595	112	27	the	the	DET
ajst-28595	112	28	sparrow	sparrow	NOUN
ajst-28595	112	29	is	be	AUX
ajst-28595	112	30	at	at	ADP
ajst-28595	112	31	the	the	DET
ajst-28595	112	32	center	center	NOUN
ajst-28595	112	33	of	of	ADP
ajst-28595	112	34	the	the	DET
ajst-28595	112	35	population	population	NOUN
ajst-28595	112	36	and	and	CCONJ
ajst-28595	112	37	randomly	randomly	ADV
ajst-28595	112	38	moves	move	VERB
ajst-28595	112	39	closer	close	ADV
ajst-28595	112	40	to	to	ADP
ajst-28595	112	41	other	other	ADJ
ajst-28595	112	42	sparrows	sparrow	NOUN
ajst-28595	112	43	;	;	PUNCT
ajst-28595	112	44	when	when	SCONJ
ajst-28595	112	45	if	if	SCONJ
ajst-28595	112	46	<	<	X
ajst-28595	112	47	gf	gf	X
ajst-28595	112	48	,	,	PUNCT
ajst-28595	112	49	the	the	DET
ajst-28595	112	50	scout	scout	NOUN
ajst-28595	112	51	remains	remain	VERB
ajst-28595	112	52	inactive	inactive	ADJ
ajst-28595	112	53	.	.	PUNCT
ajst-28595	113	1	3.3	3.3	NUM
ajst-28595	113	2	.	.	PUNCT
ajst-28595	114	1	construction	construction	NOUN
ajst-28595	114	2	of	of	ADP
ajst-28595	114	3	tool	tool	NOUN
ajst-28595	114	4	remaining	remain	VERB
ajst-28595	114	5	life	life	NOUN
ajst-28595	114	6	prediction	prediction	NOUN
ajst-28595	114	7	model	model	NOUN
ajst-28595	114	8	based	base	VERB
ajst-28595	114	9	on	on	ADP
ajst-28595	114	10	ssa	ssa	PROPN
ajst-28595	114	11	-	-	PUNCT
ajst-28595	114	12	bp	bp	PROPN
ajst-28595	114	13	the	the	DET
ajst-28595	114	14	specific	specific	ADJ
ajst-28595	114	15	steps	step	NOUN
ajst-28595	114	16	for	for	ADP
ajst-28595	114	17	constructing	construct	VERB
ajst-28595	114	18	the	the	DET
ajst-28595	114	19	tool	tool	NOUN
ajst-28595	114	20	life	life	NOUN
ajst-28595	114	21	prediction	prediction	NOUN
ajst-28595	114	22	model	model	NOUN
ajst-28595	114	23	based	base	VERB
ajst-28595	114	24	on	on	ADP
ajst-28595	114	25	the	the	DET
ajst-28595	114	26	ssa	ssa	NOUN
ajst-28595	114	27	-	-	PUNCT
ajst-28595	114	28	bp	bp	PROPN
ajst-28595	114	29	neural	neural	ADJ
ajst-28595	114	30	network	network	NOUN
ajst-28595	114	31	are	be	AUX
ajst-28595	114	32	as	as	SCONJ
ajst-28595	114	33	follows	follow	VERB
ajst-28595	114	34	:	:	PUNCT
ajst-28595	114	35	step	step	NOUN
ajst-28595	114	36	1	1	NUM
ajst-28595	114	37	:	:	PUNCT
ajst-28595	114	38	load	load	VERB
ajst-28595	114	39	the	the	DET
ajst-28595	114	40	dataset	dataset	NOUN
ajst-28595	114	41	,	,	PUNCT
ajst-28595	114	42	dividing	divide	VERB
ajst-28595	114	43	it	it	PRON
ajst-28595	114	44	into	into	ADP
ajst-28595	114	45	a	a	DET
ajst-28595	114	46	training	training	NOUN
ajst-28595	114	47	set	set	NOUN
ajst-28595	114	48	(	(	PUNCT
ajst-28595	114	49	2/3	2/3	NUM
ajst-28595	114	50	)	)	PUNCT
ajst-28595	114	51	and	and	CCONJ
ajst-28595	114	52	a	a	DET
ajst-28595	114	53	testing	testing	NOUN
ajst-28595	114	54	set	set	NOUN
ajst-28595	114	55	(	(	PUNCT
ajst-28595	114	56	1/3	1/3	NUM
ajst-28595	114	57	)	)	PUNCT
ajst-28595	114	58	.	.	PUNCT
ajst-28595	115	1	that	that	PRON
ajst-28595	115	2	is	is	ADV
ajst-28595	115	3	,	,	PUNCT
ajst-28595	115	4	use	use	VERB
ajst-28595	115	5	the	the	DET
ajst-28595	115	6	data	datum	NOUN
ajst-28595	115	7	from	from	ADP
ajst-28595	115	8	the	the	DET
ajst-28595	115	9	first	first	ADJ
ajst-28595	115	10	two	two	NUM
ajst-28595	115	11	tools	tool	NOUN
ajst-28595	115	12	for	for	ADP
ajst-28595	115	13	training	training	NOUN
ajst-28595	115	14	and	and	CCONJ
ajst-28595	115	15	the	the	DET
ajst-28595	115	16	data	datum	NOUN
ajst-28595	115	17	from	from	ADP
ajst-28595	115	18	the	the	DET
ajst-28595	115	19	last	last	ADJ
ajst-28595	115	20	tool	tool	NOUN
ajst-28595	115	21	for	for	ADP
ajst-28595	115	22	testing	testing	NOUN
ajst-28595	115	23	.	.	PUNCT
ajst-28595	116	1	normalize	normalize	VERB
ajst-28595	116	2	the	the	DET
ajst-28595	116	3	features	feature	NOUN
ajst-28595	116	4	of	of	ADP
ajst-28595	116	5	the	the	DET
ajst-28595	116	6	training	training	NOUN
ajst-28595	116	7	and	and	CCONJ
ajst-28595	116	8	testing	testing	NOUN
ajst-28595	116	9	sets	set	NOUN
ajst-28595	116	10	to	to	PART
ajst-28595	116	11	eliminate	eliminate	VERB
ajst-28595	116	12	the	the	DET
ajst-28595	116	13	impact	impact	NOUN
ajst-28595	116	14	of	of	ADP
ajst-28595	116	15	different	different	ADJ
ajst-28595	116	16	scales	scale	NOUN
ajst-28595	116	17	.	.	PUNCT
ajst-28595	117	1	step	step	NOUN
ajst-28595	117	2	2	2	NUM
ajst-28595	117	3	:	:	PUNCT
ajst-28595	117	4	define	define	VERB
ajst-28595	117	5	the	the	DET
ajst-28595	117	6	structure	structure	NOUN
ajst-28595	117	7	of	of	ADP
ajst-28595	117	8	the	the	DET
ajst-28595	117	9	bp	bp	PROPN
ajst-28595	117	10	neural	neural	ADJ
ajst-28595	117	11	network	network	NOUN
ajst-28595	117	12	and	and	CCONJ
ajst-28595	117	13	the	the	DET
ajst-28595	117	14	settings	setting	NOUN
ajst-28595	117	15	for	for	ADP
ajst-28595	117	16	learning	learn	VERB
ajst-28595	117	17	parameters	parameter	NOUN
ajst-28595	117	18	.	.	PUNCT
ajst-28595	118	1	this	this	DET
ajst-28595	118	2	paper	paper	NOUN
ajst-28595	118	3	uses	use	VERB
ajst-28595	118	4	a	a	DET
ajst-28595	118	5	bp	bp	PROPN
ajst-28595	118	6	neural	neural	ADJ
ajst-28595	118	7	network	network	NOUN
ajst-28595	118	8	structure	structure	NOUN
ajst-28595	118	9	that	that	PRON
ajst-28595	118	10	includes	include	VERB
ajst-28595	118	11	2	2	NUM
ajst-28595	118	12	hidden	hidden	ADJ
ajst-28595	118	13	layers	layer	NOUN
ajst-28595	118	14	and	and	CCONJ
ajst-28595	118	15	1	1	NUM
ajst-28595	118	16	output	output	NOUN
ajst-28595	118	17	layer	layer	NOUN
ajst-28595	118	18	.	.	PUNCT
ajst-28595	119	1	the	the	DET
ajst-28595	119	2	parameter	parameter	NOUN
ajst-28595	119	3	settings	setting	NOUN
ajst-28595	119	4	are	be	AUX
ajst-28595	119	5	as	as	SCONJ
ajst-28595	119	6	follows	follow	VERB
ajst-28595	119	7	:	:	PUNCT
ajst-28595	119	8	the	the	DET
ajst-28595	119	9	first	first	ADJ
ajst-28595	119	10	hidden	hide	VERB
ajst-28595	119	11	layer	layer	NOUN
ajst-28595	119	12	has	have	VERB
ajst-28595	119	13	32	32	NUM
ajst-28595	119	14	neurons	neuron	NOUN
ajst-28595	119	15	with	with	ADP
ajst-28595	119	16	the	the	DET
ajst-28595	119	17	sigmoid	sigmoid	NOUN
ajst-28595	119	18	activation	activation	NOUN
ajst-28595	119	19	function	function	NOUN
ajst-28595	119	20	,	,	PUNCT
ajst-28595	119	21	the	the	DET
ajst-28595	119	22	number	number	NOUN
ajst-28595	119	23	of	of	ADP
ajst-28595	119	24	neurons	neuron	NOUN
ajst-28595	119	25	in	in	ADP
ajst-28595	119	26	the	the	DET
ajst-28595	119	27	second	second	ADJ
ajst-28595	119	28	layer	layer	NOUN
ajst-28595	119	29	is	be	AUX
ajst-28595	119	30	determined	determine	VERB
ajst-28595	119	31	by	by	ADP
ajst-28595	119	32	the	the	DET
ajst-28595	119	33	optimization	optimization	NOUN
ajst-28595	119	34	algorithm	algorithm	NOUN
ajst-28595	119	35	,	,	PUNCT
ajst-28595	119	36	also	also	ADV
ajst-28595	119	37	with	with	ADP
ajst-28595	119	38	the	the	DET
ajst-28595	119	39	sigmoid	sigmoid	NOUN
ajst-28595	119	40	activation	activation	NOUN
ajst-28595	119	41	function	function	NOUN
ajst-28595	119	42	,	,	PUNCT
ajst-28595	119	43	and	and	CCONJ
ajst-28595	119	44	the	the	DET
ajst-28595	119	45	output	output	NOUN
ajst-28595	119	46	layer	layer	NOUN
ajst-28595	119	47	includes	include	VERB
ajst-28595	119	48	1	1	NUM
ajst-28595	119	49	neuron	neuron	NOUN
ajst-28595	119	50	representing	represent	VERB
ajst-28595	119	51	the	the	DET
ajst-28595	119	52	model	model	NOUN
ajst-28595	119	53	's	's	PART
ajst-28595	119	54	output	output	NOUN
ajst-28595	119	55	.	.	PUNCT
ajst-28595	120	1	the	the	DET
ajst-28595	120	2	model	model	NOUN
ajst-28595	120	3	learning	learning	NOUN
ajst-28595	120	4	rate	rate	NOUN
ajst-28595	120	5	is	be	AUX
ajst-28595	120	6	0.001	0.001	NUM
ajst-28595	120	7	.	.	PUNCT
ajst-28595	121	1	step	step	NOUN
ajst-28595	121	2	3	3	NUM
ajst-28595	121	3	:	:	PUNCT
ajst-28595	121	4	train	train	VERB
ajst-28595	121	5	the	the	DET
ajst-28595	121	6	bp	bp	PROPN
ajst-28595	121	7	neural	neural	ADJ
ajst-28595	121	8	network	network	NOUN
ajst-28595	121	9	.	.	PUNCT
ajst-28595	122	1	during	during	ADP
ajst-28595	122	2	the	the	DET
ajst-28595	122	3	training	training	NOUN
ajst-28595	122	4	process	process	NOUN
ajst-28595	122	5	,	,	PUNCT
ajst-28595	122	6	the	the	DET
ajst-28595	122	7	network	network	NOUN
ajst-28595	122	8	continuously	continuously	ADV
ajst-28595	122	9	adjusts	adjust	VERB
ajst-28595	122	10	the	the	DET
ajst-28595	122	11	weights	weight	NOUN
ajst-28595	122	12	and	and	CCONJ
ajst-28595	122	13	thresholds	threshold	NOUN
ajst-28595	122	14	between	between	ADP
ajst-28595	122	15	layers	layer	NOUN
ajst-28595	122	16	to	to	PART
ajst-28595	122	17	minimize	minimize	VERB
ajst-28595	122	18	the	the	DET
ajst-28595	122	19	prediction	prediction	NOUN
ajst-28595	122	20	error	error	NOUN
ajst-28595	122	21	.	.	PUNCT
ajst-28595	123	1	the	the	DET
ajst-28595	123	2	training	training	NOUN
ajst-28595	123	3	process	process	NOUN
ajst-28595	123	4	will	will	AUX
ajst-28595	123	5	continue	continue	VERB
ajst-28595	123	6	until	until	SCONJ
ajst-28595	123	7	the	the	DET
ajst-28595	123	8	maximum	maximum	ADJ
ajst-28595	123	9	number	number	NOUN
ajst-28595	123	10	of	of	ADP
ajst-28595	123	11	training	training	NOUN
ajst-28595	123	12	iterations	iteration	NOUN
ajst-28595	123	13	is	be	AUX
ajst-28595	123	14	reached	reach	VERB
ajst-28595	123	15	or	or	CCONJ
ajst-28595	123	16	other	other	ADJ
ajst-28595	123	17	preset	preset	ADJ
ajst-28595	123	18	stopping	stop	VERB
ajst-28595	123	19	82	82	NUM
ajst-28595	123	20	conditions	condition	NOUN
ajst-28595	123	21	are	be	AUX
ajst-28595	123	22	met	meet	VERB
ajst-28595	123	23	.	.	PUNCT
ajst-28595	124	1	step	step	NOUN
ajst-28595	124	2	4	4	NUM
ajst-28595	124	3	:	:	PUNCT
ajst-28595	124	4	output	output	NOUN
ajst-28595	124	5	prediction	prediction	NOUN
ajst-28595	124	6	results	result	VERB
ajst-28595	124	7	:	:	PUNCT
ajst-28595	124	8	after	after	ADP
ajst-28595	124	9	completing	complete	VERB
ajst-28595	124	10	the	the	DET
ajst-28595	124	11	training	training	NOUN
ajst-28595	124	12	,	,	PUNCT
ajst-28595	124	13	use	use	VERB
ajst-28595	124	14	the	the	DET
ajst-28595	124	15	testing	testing	NOUN
ajst-28595	124	16	set	set	VERB
ajst-28595	124	17	data	datum	NOUN
ajst-28595	124	18	to	to	PART
ajst-28595	124	19	make	make	VERB
ajst-28595	124	20	predictions	prediction	NOUN
ajst-28595	124	21	with	with	ADP
ajst-28595	124	22	the	the	DET
ajst-28595	124	23	bp	bp	PROPN
ajst-28595	124	24	neural	neural	ADJ
ajst-28595	124	25	network	network	NOUN
ajst-28595	124	26	.	.	PUNCT
ajst-28595	125	1	the	the	DET
ajst-28595	125	2	prediction	prediction	NOUN
ajst-28595	125	3	results	result	VERB
ajst-28595	125	4	need	need	VERB
ajst-28595	125	5	to	to	PART
ajst-28595	125	6	be	be	AUX
ajst-28595	125	7	denormalized	denormalize	VERB
ajst-28595	125	8	to	to	PART
ajst-28595	125	9	restore	restore	VERB
ajst-28595	125	10	the	the	DET
ajst-28595	125	11	original	original	ADJ
ajst-28595	125	12	data	datum	NOUN
ajst-28595	125	13	values	value	NOUN
ajst-28595	125	14	.	.	PUNCT
ajst-28595	126	1	step	step	NOUN
ajst-28595	126	2	5	5	NUM
ajst-28595	126	3	:	:	PUNCT
ajst-28595	126	4	set	set	VERB
ajst-28595	126	5	the	the	DET
ajst-28595	126	6	parameters	parameter	NOUN
ajst-28595	126	7	for	for	ADP
ajst-28595	126	8	the	the	DET
ajst-28595	126	9	ssa	ssa	PROPN
ajst-28595	126	10	algorithm	algorithm	NOUN
ajst-28595	126	11	.	.	PUNCT
ajst-28595	127	1	determine	determine	VERB
ajst-28595	127	2	the	the	DET
ajst-28595	127	3	sparrow	sparrow	ADJ
ajst-28595	127	4	population	population	NOUN
ajst-28595	127	5	size	size	NOUN
ajst-28595	127	6	to	to	PART
ajst-28595	127	7	be	be	AUX
ajst-28595	127	8	14	14	NUM
ajst-28595	127	9	,	,	PUNCT
ajst-28595	127	10	the	the	DET
ajst-28595	127	11	number	number	NOUN
ajst-28595	127	12	of	of	ADP
ajst-28595	127	13	information	information	NOUN
ajst-28595	127	14	exchanges	exchange	NOUN
ajst-28595	127	15	between	between	ADP
ajst-28595	127	16	sparrows	sparrow	NOUN
ajst-28595	127	17	to	to	PART
ajst-28595	127	18	be	be	AUX
ajst-28595	127	19	30	30	NUM
ajst-28595	127	20	,	,	PUNCT
ajst-28595	127	21	the	the	DET
ajst-28595	127	22	proportion	proportion	NOUN
ajst-28595	127	23	of	of	ADP
ajst-28595	127	24	discoverers	discoverer	NOUN
ajst-28595	127	25	to	to	ADP
ajst-28595	127	26	the	the	DET
ajst-28595	127	27	total	total	ADJ
ajst-28595	127	28	sparrow	sparrow	ADJ
ajst-28595	127	29	population	population	NOUN
ajst-28595	127	30	to	to	PART
ajst-28595	127	31	be	be	AUX
ajst-28595	127	32	0.20	0.20	NUM
ajst-28595	127	33	,	,	PUNCT
ajst-28595	127	34	and	and	CCONJ
ajst-28595	127	35	set	set	VERB
ajst-28595	127	36	the	the	DET
ajst-28595	127	37	alert	alert	ADJ
ajst-28595	127	38	value	value	NOUN
ajst-28595	127	39	and	and	CCONJ
ajst-28595	127	40	the	the	DET
ajst-28595	127	41	number	number	NOUN
ajst-28595	127	42	of	of	ADP
ajst-28595	127	43	sentinels	sentinel	NOUN
ajst-28595	127	44	.	.	PUNCT
ajst-28595	128	1	step	step	NOUN
ajst-28595	128	2	6	6	NUM
ajst-28595	128	3	:	:	PUNCT
ajst-28595	128	4	invoke	invoke	VERB
ajst-28595	128	5	the	the	DET
ajst-28595	128	6	ssa	ssa	NOUN
ajst-28595	128	7	algorithm	algorithm	NOUN
ajst-28595	128	8	to	to	PART
ajst-28595	128	9	optimize	optimize	VERB
ajst-28595	128	10	the	the	DET
ajst-28595	128	11	neural	neural	ADJ
ajst-28595	128	12	network	network	NOUN
ajst-28595	128	13	parameters	parameter	NOUN
ajst-28595	128	14	.	.	PUNCT
ajst-28595	129	1	step	step	NOUN
ajst-28595	129	2	7	7	NUM
ajst-28595	129	3	:	:	PUNCT
ajst-28595	129	4	use	use	VERB
ajst-28595	129	5	the	the	DET
ajst-28595	129	6	optimized	optimize	VERB
ajst-28595	129	7	bp	bp	PROPN
ajst-28595	129	8	neural	neural	ADJ
ajst-28595	129	9	network	network	NOUN
ajst-28595	129	10	for	for	ADP
ajst-28595	129	11	training	training	NOUN
ajst-28595	129	12	and	and	CCONJ
ajst-28595	129	13	stop	stop	VERB
ajst-28595	129	14	the	the	DET
ajst-28595	129	15	computation	computation	NOUN
ajst-28595	129	16	to	to	PART
ajst-28595	129	17	output	output	VERB
ajst-28595	129	18	the	the	DET
ajst-28595	129	19	results	result	NOUN
ajst-28595	129	20	.	.	PUNCT
ajst-28595	130	1	the	the	DET
ajst-28595	130	2	algorithm	algorithm	NOUN
ajst-28595	130	3	flow	flow	NOUN
ajst-28595	130	4	is	be	AUX
ajst-28595	130	5	shown	show	VERB
ajst-28595	130	6	in	in	ADP
ajst-28595	130	7	figure	figure	NOUN
ajst-28595	130	8	6	6	NUM
ajst-28595	130	9	.	.	PUNCT
ajst-28595	130	10	ssa	ssa	PROPN
ajst-28595	130	11	-	-	PUNCT
ajst-28595	130	12	bp	bp	PROPN
ajst-28595	130	13	neural	neural	ADJ
ajst-28595	130	14	network	network	NOUN
ajst-28595	130	15	training	training	NOUN
ajst-28595	130	16	determine	determine	VERB
ajst-28595	130	17	the	the	DET
ajst-28595	130	18	structure	structure	NOUN
ajst-28595	130	19	of	of	ADP
ajst-28595	130	20	the	the	DET
ajst-28595	130	21	bp	bp	PROPN
ajst-28595	130	22	neural	neural	PROPN
ajst-28595	130	23	network	network	NOUN
ajst-28595	130	24	algorithm	algorithm	NOUN
ajst-28595	130	25	weights	weight	NOUN
ajst-28595	130	26	and	and	CCONJ
ajst-28595	130	27	thresholds	threshold	NOUN
ajst-28595	130	28	of	of	ADP
ajst-28595	130	29	the	the	DET
ajst-28595	130	30	bp	bp	PROPN
ajst-28595	130	31	neural	neural	PROPN
ajst-28595	130	32	network	network	NOUN
ajst-28595	130	33	after	after	SCONJ
ajst-28595	130	34	ssa	ssa	PROPN
ajst-28595	130	35	optimization	optimization	NOUN
ajst-28595	130	36	initialize	initialize	VERB
ajst-28595	130	37	the	the	DET
ajst-28595	130	38	weights	weight	NOUN
ajst-28595	130	39	and	and	CCONJ
ajst-28595	130	40	thresholds	threshold	NOUN
ajst-28595	130	41	of	of	ADP
ajst-28595	130	42	the	the	DET
ajst-28595	130	43	bp	bp	PROPN
ajst-28595	130	44	neural	neural	PROPN
ajst-28595	130	45	network	network	NOUN
ajst-28595	130	46	structure	structure	NOUN
ajst-28595	130	47	ssa	ssa	PROPN
ajst-28595	130	48	parameter	parameter	PROPN
ajst-28595	130	49	initializationnormalize	initializationnormalize	VERB
ajst-28595	130	50	the	the	DET
ajst-28595	130	51	input	input	NOUN
ajst-28595	130	52	data	datum	NOUN
ajst-28595	130	53	update	update	VERB
ajst-28595	130	54	the	the	DET
ajst-28595	130	55	discoverer	discoverer	NOUN
ajst-28595	130	56	's	's	PART
ajst-28595	130	57	position	position	NOUN
ajst-28595	130	58	update	update	VERB
ajst-28595	130	59	the	the	DET
ajst-28595	130	60	follower	follower	NOUN
ajst-28595	130	61	's	's	PART
ajst-28595	130	62	position	position	NOUN
ajst-28595	130	63	update	update	VERB
ajst-28595	130	64	the	the	DET
ajst-28595	130	65	sentinel	sentinel	NOUN
ajst-28595	130	66	's	's	PART
ajst-28595	130	67	position	position	NOUN
ajst-28595	130	68	satisfy	satisfy	VERB
ajst-28595	130	69	the	the	DET
ajst-28595	130	70	stopping	stopping	NOUN
ajst-28595	130	71	criteria	criterion	NOUN
ajst-28595	130	72	?	?	PUNCT
ajst-28595	131	1	predicted	predict	VERB
ajst-28595	131	2	remaining	remain	VERB
ajst-28595	131	3	life	life	NOUN
ajst-28595	131	4	of	of	ADP
ajst-28595	131	5	the	the	DET
ajst-28595	131	6	tool	tool	NOUN
ajst-28595	131	7	start	start	VERB
ajst-28595	131	8	end	end	NOUN
ajst-28595	131	9	y	y	PROPN
ajst-28595	131	10	n	n	PRON
ajst-28595	131	11	ssa	ssa	PROPN
ajst-28595	131	12	part	part	PROPN
ajst-28595	131	13	bp	bp	PROPN
ajst-28595	131	14	neural	neural	PROPN
ajst-28595	131	15	network	network	PROPN
ajst-28595	131	16	part	part	NOUN
ajst-28595	131	17	figure	figure	NOUN
ajst-28595	131	18	6	6	NUM
ajst-28595	131	19	.	.	PUNCT
ajst-28595	131	20	ssa	ssa	PROPN
ajst-28595	131	21	-	-	PUNCT
ajst-28595	131	22	bp	bp	PROPN
ajst-28595	131	23	algorithm	algorithm	PROPN
ajst-28595	131	24	flowchart	flowchart	NOUN
ajst-28595	131	25	3.4	3.4	NUM
ajst-28595	131	26	.	.	PUNCT
ajst-28595	132	1	model	model	NOUN
ajst-28595	132	2	performance	performance	NOUN
ajst-28595	132	3	validation	validation	NOUN
ajst-28595	132	4	in	in	ADP
ajst-28595	132	5	practical	practical	ADJ
ajst-28595	132	6	applications	application	NOUN
ajst-28595	132	7	,	,	PUNCT
ajst-28595	132	8	multiple	multiple	ADJ
ajst-28595	132	9	metrics	metric	NOUN
ajst-28595	132	10	are	be	AUX
ajst-28595	132	11	often	often	ADV
ajst-28595	132	12	combined	combine	VERB
ajst-28595	132	13	to	to	PART
ajst-28595	132	14	assess	assess	VERB
ajst-28595	132	15	model	model	NOUN
ajst-28595	132	16	performance	performance	NOUN
ajst-28595	132	17	in	in	ADP
ajst-28595	132	18	order	order	NOUN
ajst-28595	132	19	to	to	PART
ajst-28595	132	20	obtain	obtain	VERB
ajst-28595	132	21	a	a	DET
ajst-28595	132	22	comprehensive	comprehensive	ADJ
ajst-28595	132	23	evaluation	evaluation	NOUN
ajst-28595	132	24	.	.	PUNCT
ajst-28595	133	1	therefore	therefore	ADV
ajst-28595	133	2	,	,	PUNCT
ajst-28595	133	3	in	in	ADP
ajst-28595	133	4	this	this	DET
ajst-28595	133	5	paper	paper	NOUN
ajst-28595	133	6	,	,	PUNCT
ajst-28595	133	7	five	five	NUM
ajst-28595	133	8	main	main	ADJ
ajst-28595	133	9	evaluation	evaluation	NOUN
ajst-28595	133	10	indicators	indicator	NOUN
ajst-28595	133	11	are	be	AUX
ajst-28595	133	12	used	use	VERB
ajst-28595	133	13	to	to	PART
ajst-28595	133	14	assess	assess	VERB
ajst-28595	133	15	the	the	DET
ajst-28595	133	16	model	model	NOUN
ajst-28595	133	17	:	:	PUNCT
ajst-28595	133	18	coefficient	coefficient	NOUN
ajst-28595	133	19	of	of	ADP
ajst-28595	133	20	determination	determination	NOUN
ajst-28595	133	21	(	(	PUNCT
ajst-28595	133	22	r²	r²	PROPN
ajst-28595	133	23	)	)	PUNCT
ajst-28595	133	24	,	,	PUNCT
ajst-28595	133	25	explained	explain	VERB
ajst-28595	133	26	variance	variance	NOUN
ajst-28595	133	27	score	score	NOUN
ajst-28595	133	28	(	(	PUNCT
ajst-28595	133	29	evs	evs	PROPN
ajst-28595	133	30	)	)	PUNCT
ajst-28595	133	31	,	,	PUNCT
ajst-28595	133	32	mean	mean	VERB
ajst-28595	133	33	squared	square	VERB
ajst-28595	133	34	error	error	NOUN
ajst-28595	133	35	(	(	PUNCT
ajst-28595	133	36	mse	mse	NOUN
ajst-28595	133	37	)	)	PUNCT
ajst-28595	133	38	,	,	PUNCT
ajst-28595	133	39	mean	mean	VERB
ajst-28595	133	40	absolute	absolute	ADJ
ajst-28595	133	41	error	error	NOUN
ajst-28595	133	42	(	(	PUNCT
ajst-28595	133	43	mae	mae	PROPN
ajst-28595	133	44	)	)	PUNCT
ajst-28595	133	45	,	,	PUNCT
ajst-28595	133	46	and	and	CCONJ
ajst-28595	133	47	mean	mean	VERB
ajst-28595	133	48	absolute	absolute	ADJ
ajst-28595	133	49	percentage	percentage	NOUN
ajst-28595	133	50	error	error	NOUN
ajst-28595	133	51	(	(	PUNCT
ajst-28595	133	52	mape	mape	NOUN
ajst-28595	133	53	)	)	PUNCT
ajst-28595	133	54	.	.	PUNCT
ajst-28595	134	1	in	in	ADP
ajst-28595	134	2	the	the	DET
ajst-28595	134	3	formula	formula	NOUN
ajst-28595	134	4	:	:	PUNCT
ajst-28595	134	5	n	n	PRON
ajst-28595	134	6	is	be	AUX
ajst-28595	134	7	the	the	DET
ajst-28595	134	8	number	number	NOUN
ajst-28595	134	9	of	of	ADP
ajst-28595	134	10	samples	sample	NOUN
ajst-28595	134	11	,	,	PUNCT
ajst-28595	134	12	iy	iy	PROPN
ajst-28595	134	13	is	be	AUX
ajst-28595	134	14	the	the	DET
ajst-28595	134	15	i	i	PRON
ajst-28595	134	16	observed	observed	ADJ
ajst-28595	134	17	value	value	NOUN
ajst-28595	134	18	,	,	PUNCT
ajst-28595	134	19	iy	iy	PROPN
ajst-28595	134	20			PROPN
ajst-28595	134	21	is	be	AUX
ajst-28595	134	22	the	the	PRON
ajst-28595	134	23	i	i	PRON
ajst-28595	134	24	predicted	predict	VERB
ajst-28595	134	25	value	value	NOUN
ajst-28595	134	26	,	,	PUNCT
ajst-28595	134	27	and	and	CCONJ
ajst-28595	134	28	y	y	PROPN
ajst-28595	134	29	is	be	AUX
ajst-28595	134	30	the	the	DET
ajst-28595	134	31	average	average	ADJ
ajst-28595	134	32	value	value	NOUN
ajst-28595	134	33	of	of	ADP
ajst-28595	134	34	the	the	DET
ajst-28595	134	35	parameters	parameter	NOUN
ajst-28595	134	36	.	.	PUNCT
ajst-28595	135	1	when	when	SCONJ
ajst-28595	135	2	evaluating	evaluate	VERB
ajst-28595	135	3	the	the	DET
ajst-28595	135	4	performance	performance	NOUN
ajst-28595	135	5	indicators	indicator	NOUN
ajst-28595	135	6	,	,	PUNCT
ajst-28595	135	7	the	the	DET
ajst-28595	135	8	closer	close	ADJ
ajst-28595	135	9	r²	r²	NOUN
ajst-28595	135	10	and	and	CCONJ
ajst-28595	135	11	evs	evs	NOUN
ajst-28595	135	12	are	be	AUX
ajst-28595	135	13	to	to	ADP
ajst-28595	135	14	1	1	NUM
ajst-28595	135	15	,	,	PUNCT
ajst-28595	135	16	the	the	DET
ajst-28595	135	17	better	well	ADJ
ajst-28595	135	18	,	,	PUNCT
ajst-28595	135	19	while	while	SCONJ
ajst-28595	135	20	the	the	DET
ajst-28595	135	21	closer	close	ADJ
ajst-28595	135	22	mse	mse	NOUN
ajst-28595	135	23	,	,	PUNCT
ajst-28595	135	24	mae	mae	PROPN
ajst-28595	135	25	,	,	PUNCT
ajst-28595	135	26	and	and	CCONJ
ajst-28595	135	27	mape	mape	NOUN
ajst-28595	135	28	are	be	AUX
ajst-28595	135	29	to	to	ADP
ajst-28595	135	30	0	0	NUM
ajst-28595	135	31	,	,	PUNCT
ajst-28595	135	32	the	the	DET
ajst-28595	135	33	better	well	ADJ
ajst-28595	135	34	.	.	PUNCT
ajst-28595	136	1	4	4	X
ajst-28595	136	2	.	.	NOUN
ajst-28595	136	3	prediction	prediction	NOUN
ajst-28595	136	4	experiment	experiment	NOUN
ajst-28595	136	5	results	result	NOUN
ajst-28595	136	6	and	and	CCONJ
ajst-28595	136	7	analysis	analysis	NOUN
ajst-28595	136	8	of	of	ADP
ajst-28595	136	9	tool	tool	NOUN
ajst-28595	136	10	remaining	remain	VERB
ajst-28595	136	11	life	life	NOUN
ajst-28595	136	12	three	three	NUM
ajst-28595	136	13	brand	brand	NOUN
ajst-28595	136	14	-	-	PUNCT
ajst-28595	136	15	new	new	ADJ
ajst-28595	136	16	tools	tool	NOUN
ajst-28595	136	17	of	of	ADP
ajst-28595	136	18	the	the	DET
ajst-28595	136	19	same	same	ADJ
ajst-28595	136	20	specification	specification	NOUN
ajst-28595	136	21	were	be	AUX
ajst-28595	136	22	sequentially	sequentially	ADV
ajst-28595	136	23	started	start	VERB
ajst-28595	136	24	for	for	ADP
ajst-28595	136	25	normal	normal	ADJ
ajst-28595	136	26	machining	machining	NOUN
ajst-28595	136	27	operations	operation	NOUN
ajst-28595	136	28	,	,	PUNCT
ajst-28595	136	29	and	and	CCONJ
ajst-28595	136	30	data	datum	NOUN
ajst-28595	136	31	collection	collection	NOUN
ajst-28595	136	32	was	be	AUX
ajst-28595	136	33	stopped	stop	VERB
ajst-28595	136	34	when	when	SCONJ
ajst-28595	136	35	the	the	DET
ajst-28595	136	36	tool	tool	NOUN
ajst-28595	136	37	life	life	NOUN
ajst-28595	136	38	ended	end	VERB
ajst-28595	136	39	.	.	PUNCT
ajst-28595	137	1	the	the	DET
ajst-28595	137	2	working	work	VERB
ajst-28595	137	3	life	life	NOUN
ajst-28595	137	4	of	of	ADP
ajst-28595	137	5	tool	tool	NOUN
ajst-28595	137	6	a	a	PRON
ajst-28595	137	7	was	be	AUX
ajst-28595	137	8	167.5	167.5	NUM
ajst-28595	137	9	minutes	minute	NOUN
ajst-28595	137	10	,	,	PUNCT
ajst-28595	137	11	tool	tool	PROPN
ajst-28595	137	12	b	b	PROPN
ajst-28595	137	13	was	be	AUX
ajst-28595	137	14	205.3	205.3	NUM
ajst-28595	137	15	minutes	minute	NOUN
ajst-28595	137	16	,	,	PUNCT
ajst-28595	137	17	and	and	CCONJ
ajst-28595	137	18	tool	tool	NOUN
ajst-28595	137	19	c	c	PROPN
ajst-28595	137	20	was	be	AUX
ajst-28595	137	21	210.8	210.8	NUM
ajst-28595	137	22	minutes	minute	NOUN
ajst-28595	137	23	.	.	PUNCT
ajst-28595	138	1	the	the	DET
ajst-28595	138	2	preprocessed	preprocesse	VERB
ajst-28595	138	3	data	datum	NOUN
ajst-28595	138	4	of	of	ADP
ajst-28595	138	5	tools	tool	NOUN
ajst-28595	138	6	b	b	NOUN
ajst-28595	138	7	and	and	CCONJ
ajst-28595	138	8	c	c	PROPN
ajst-28595	138	9	were	be	AUX
ajst-28595	138	10	used	use	VERB
ajst-28595	138	11	as	as	ADP
ajst-28595	138	12	the	the	DET
ajst-28595	138	13	training	training	NOUN
ajst-28595	138	14	set	set	NOUN
ajst-28595	138	15	,	,	PUNCT
ajst-28595	138	16	and	and	CCONJ
ajst-28595	138	17	the	the	DET
ajst-28595	138	18	preprocessed	preprocesse	VERB
ajst-28595	138	19	data	datum	NOUN
ajst-28595	138	20	of	of	ADP
ajst-28595	138	21	tool	tool	NOUN
ajst-28595	138	22	a	a	PRON
ajst-28595	138	23	were	be	AUX
ajst-28595	138	24	used	use	VERB
ajst-28595	138	25	as	as	ADP
ajst-28595	138	26	the	the	DET
ajst-28595	138	27	testing	testing	NOUN
ajst-28595	138	28	set	set	VERB
ajst-28595	138	29	.	.	PUNCT
ajst-28595	139	1	to	to	PART
ajst-28595	139	2	verify	verify	VERB
ajst-28595	139	3	the	the	DET
ajst-28595	139	4	characteristics	characteristic	NOUN
ajst-28595	139	5	of	of	ADP
ajst-28595	139	6	the	the	DET
ajst-28595	139	7	ssa	ssa	NOUN
ajst-28595	139	8	-	-	PUNCT
ajst-28595	139	9	bp	bp	PROPN
ajst-28595	139	10	neural	neural	ADJ
ajst-28595	139	11	network	network	NOUN
ajst-28595	139	12	tool	tool	NOUN
ajst-28595	139	13	remaining	remain	VERB
ajst-28595	139	14	life	life	NOUN
ajst-28595	139	15	prediction	prediction	NOUN
ajst-28595	139	16	model	model	NOUN
ajst-28595	139	17	,	,	PUNCT
ajst-28595	139	18	the	the	DET
ajst-28595	139	19	gwo	gwo	PROPN
ajst-28595	139	20	-	-	PUNCT
ajst-28595	139	21	bp	bp	PROPN
ajst-28595	139	22	neural	neural	ADJ
ajst-28595	139	23	network	network	NOUN
ajst-28595	139	24	prediction	prediction	NOUN
ajst-28595	139	25	model	model	NOUN
ajst-28595	139	26	and	and	CCONJ
ajst-28595	139	27	the	the	DET
ajst-28595	139	28	bp	bp	PROPN
ajst-28595	139	29	neural	neural	PROPN
ajst-28595	139	30	network	network	NOUN
ajst-28595	139	31	prediction	prediction	NOUN
ajst-28595	139	32	model	model	NOUN
ajst-28595	139	33	were	be	AUX
ajst-28595	139	34	selected	select	VERB
ajst-28595	139	35	for	for	ADP
ajst-28595	139	36	simulation	simulation	NOUN
ajst-28595	139	37	experiments	experiment	NOUN
ajst-28595	139	38	.	.	PUNCT
ajst-28595	140	1	the	the	DET
ajst-28595	140	2	mean	mean	ADJ
ajst-28595	140	3	squared	square	VERB
ajst-28595	140	4	error	error	NOUN
ajst-28595	140	5	(	(	PUNCT
ajst-28595	140	6	mse	mse	NOUN
ajst-28595	140	7	)	)	PUNCT
ajst-28595	140	8	output	output	NOUN
ajst-28595	140	9	by	by	ADP
ajst-28595	140	10	the	the	DET
ajst-28595	140	11	neural	neural	ADJ
ajst-28595	140	12	network	network	NOUN
ajst-28595	140	13	models	model	NOUN
ajst-28595	140	14	was	be	AUX
ajst-28595	140	15	used	use	VERB
ajst-28595	140	16	as	as	ADP
ajst-28595	140	17	the	the	DET
ajst-28595	140	18	fitness	fitness	NOUN
ajst-28595	140	19	function	function	NOUN
ajst-28595	140	20	for	for	ADP
ajst-28595	140	21	comparison	comparison	NOUN
ajst-28595	140	22	.	.	PUNCT
ajst-28595	141	1	the	the	DET
ajst-28595	141	2	bp	bp	PROPN
ajst-28595	141	3	neural	neural	PROPN
ajst-28595	141	4	network	network	NOUN
ajst-28595	141	5	is	be	AUX
ajst-28595	141	6	a	a	DET
ajst-28595	141	7	neural	neural	ADJ
ajst-28595	141	8	network	network	NOUN
ajst-28595	141	9	model	model	NOUN
ajst-28595	141	10	with	with	ADP
ajst-28595	141	11	strong	strong	ADJ
ajst-28595	141	12	complex	complex	ADJ
ajst-28595	141	13	model	model	NOUN
ajst-28595	141	14	analysis	analysis	NOUN
ajst-28595	141	15	capabilities	capability	NOUN
ajst-28595	141	16	.	.	PUNCT
ajst-28595	142	1	in	in	ADP
ajst-28595	142	2	this	this	DET
ajst-28595	142	3	paper	paper	NOUN
ajst-28595	142	4	,	,	PUNCT
ajst-28595	142	5	the	the	DET
ajst-28595	142	6	number	number	NOUN
ajst-28595	142	7	of	of	ADP
ajst-28595	142	8	input	input	NOUN
ajst-28595	142	9	layer	layer	NOUN
ajst-28595	142	10	neurons	neuron	NOUN
ajst-28595	142	11	is	be	AUX
ajst-28595	142	12	9	9	NUM
ajst-28595	142	13	features	feature	NOUN
ajst-28595	142	14	,	,	PUNCT
ajst-28595	142	15	which	which	PRON
ajst-28595	142	16	are	be	AUX
ajst-28595	142	17	cutting	cut	VERB
ajst-28595	142	18	time	time	NOUN
ajst-28595	142	19	,	,	PUNCT
ajst-28595	142	20	spindle	spindle	NOUN
ajst-28595	142	21	load	load	NOUN
ajst-28595	142	22	rate	rate	NOUN
ajst-28595	142	23	,	,	PUNCT
ajst-28595	142	24	spindle	spindle	NOUN
ajst-28595	142	25	load	load	NOUN
ajst-28595	142	26	,	,	PUNCT
ajst-28595	142	27	x	x	ADJ
ajst-28595	142	28	-	-	ADJ
ajst-28595	142	29	axis	axis	ADJ
ajst-28595	142	30	load	load	NOUN
ajst-28595	142	31	rate	rate	NOUN
ajst-28595	142	32	,	,	PUNCT
ajst-28595	142	33	y	y	NOUN
ajst-28595	142	34	-	-	PUNCT
ajst-28595	142	35	axis	axis	NOUN
ajst-28595	142	36	load	load	NOUN
ajst-28595	142	37	rate	rate	NOUN
ajst-28595	142	38	,	,	PUNCT
ajst-28595	142	39	z	z	NOUN
ajst-28595	142	40	-	-	PUNCT
ajst-28595	142	41	axis	axis	NOUN
ajst-28595	142	42	load	load	NOUN
ajst-28595	142	43	rate	rate	NOUN
ajst-28595	142	44	,	,	PUNCT
ajst-28595	142	45	x	x	ADJ
ajst-28595	142	46	-	-	ADJ
ajst-28595	142	47	axis	axis	ADJ
ajst-28595	142	48	current	current	ADJ
ajst-28595	142	49	,	,	PUNCT
ajst-28595	142	50	y	y	ADJ
ajst-28595	142	51	-	-	PUNCT
ajst-28595	142	52	axis	axis	NOUN
ajst-28595	142	53	current	current	NOUN
ajst-28595	142	54	,	,	PUNCT
ajst-28595	142	55	and	and	CCONJ
ajst-28595	142	56	z	z	NOUN
ajst-28595	142	57	-	-	PUNCT
ajst-28595	142	58	axis	axis	NOUN
ajst-28595	142	59	current	current	NOUN
ajst-28595	142	60	.	.	PUNCT
ajst-28595	143	1	for	for	ADP
ajst-28595	143	2	the	the	DET
ajst-28595	143	3	hidden	hide	VERB
ajst-28595	143	4	layer	layer	NOUN
ajst-28595	143	5	,	,	PUNCT
ajst-28595	143	6	there	there	PRON
ajst-28595	143	7	are	be	VERB
ajst-28595	143	8	2	2	NUM
ajst-28595	143	9	hidden	hidden	ADJ
ajst-28595	143	10	layers	layer	NOUN
ajst-28595	143	11	with	with	ADP
ajst-28595	143	12	32	32	NUM
ajst-28595	143	13	neurons	neuron	NOUN
ajst-28595	143	14	each	each	PRON
ajst-28595	143	15	;	;	PUNCT
ajst-28595	143	16	the	the	DET
ajst-28595	143	17	output	output	NOUN
ajst-28595	143	18	layer	layer	NOUN
ajst-28595	143	19	outputs	output	VERB
ajst-28595	143	20	the	the	DET
ajst-28595	143	21	tool	tool	NOUN
ajst-28595	143	22	life	life	NOUN
ajst-28595	143	23	prediction	prediction	NOUN
ajst-28595	143	24	value	value	NOUN
ajst-28595	143	25	.	.	PUNCT
ajst-28595	144	1	the	the	DET
ajst-28595	144	2	training	training	NOUN
ajst-28595	144	3	number	number	NOUN
ajst-28595	144	4	is	be	AUX
ajst-28595	144	5	100	100	NUM
ajst-28595	144	6	times	time	NOUN
ajst-28595	144	7	,	,	PUNCT
ajst-28595	144	8	the	the	DET
ajst-28595	144	9	learning	learning	NOUN
ajst-28595	144	10	rate	rate	NOUN
ajst-28595	144	11	is	be	AUX
ajst-28595	144	12	0.001	0.001	NUM
ajst-28595	144	13	,	,	PUNCT
ajst-28595	144	14	and	and	CCONJ
ajst-28595	144	15	all	all	DET
ajst-28595	144	16	other	other	ADJ
ajst-28595	144	17	values	value	NOUN
ajst-28595	144	18	are	be	AUX
ajst-28595	144	19	default	default	NOUN
ajst-28595	144	20	.	.	PUNCT
ajst-28595	145	1	the	the	DET
ajst-28595	145	2	fitness	fitness	NOUN
ajst-28595	145	3	curve	curve	NOUN
ajst-28595	145	4	is	be	AUX
ajst-28595	145	5	shown	show	VERB
ajst-28595	145	6	in	in	ADP
ajst-28595	145	7	figure	figure	NOUN
ajst-28595	145	8	7a	7a	NUM
ajst-28595	145	9	.	.	PUNCT
ajst-28595	146	1	the	the	DET
ajst-28595	146	2	parameter	parameter	NOUN
ajst-28595	146	3	settings	setting	NOUN
ajst-28595	146	4	for	for	ADP
ajst-28595	146	5	the	the	DET
ajst-28595	146	6	gwo	gwo	PROPN
ajst-28595	146	7	-	-	PUNCT
ajst-28595	146	8	bp	bp	PROPN
ajst-28595	146	9	neural	neural	ADJ
ajst-28595	146	10	network	network	NOUN
ajst-28595	146	11	prediction	prediction	NOUN
ajst-28595	146	12	model	model	NOUN
ajst-28595	146	13	are	be	AUX
ajst-28595	146	14	:	:	PUNCT
ajst-28595	146	15	10	10	NUM
ajst-28595	146	16	grey	grey	ADJ
ajst-28595	146	17	wolves	wolf	NOUN
ajst-28595	146	18	,	,	PUNCT
ajst-28595	146	19	with	with	ADP
ajst-28595	146	20	a	a	DET
ajst-28595	146	21	maximum	maximum	NOUN
ajst-28595	146	22	of	of	ADP
ajst-28595	146	23	20	20	NUM
ajst-28595	146	24	iterations	iteration	NOUN
ajst-28595	146	25	.	.	PUNCT
ajst-28595	147	1	the	the	DET
ajst-28595	147	2	fitness	fitness	NOUN
ajst-28595	147	3	curve	curve	NOUN
ajst-28595	147	4	is	be	AUX
ajst-28595	147	5	shown	show	VERB
ajst-28595	147	6	in	in	ADP
ajst-28595	147	7	figure	figure	NOUN
ajst-28595	147	8	7b	7b	NOUN
ajst-28595	147	9	.	.	PUNCT
ajst-28595	148	1	the	the	DET
ajst-28595	148	2	parameter	parameter	NOUN
ajst-28595	148	3	settings	setting	NOUN
ajst-28595	148	4	for	for	ADP
ajst-28595	148	5	the	the	DET
ajst-28595	148	6	ssa	ssa	NOUN
ajst-28595	148	7	-	-	PUNCT
ajst-28595	148	8	bp	bp	PROPN
ajst-28595	148	9	neural	neural	ADJ
ajst-28595	148	10	network	network	NOUN
ajst-28595	148	11	prediction	prediction	NOUN
ajst-28595	148	12	model	model	NOUN
ajst-28595	148	13	are	be	AUX
ajst-28595	148	14	:	:	PUNCT
ajst-28595	148	15	a	a	DET
ajst-28595	148	16	sparrow	sparrow	ADJ
ajst-28595	148	17	population	population	NOUN
ajst-28595	148	18	size	size	NOUN
ajst-28595	148	19	of	of	ADP
ajst-28595	148	20	14	14	NUM
ajst-28595	148	21	,	,	PUNCT
ajst-28595	148	22	a	a	DET
ajst-28595	148	23	maximum	maximum	NOUN
ajst-28595	148	24	of	of	ADP
ajst-28595	148	25	30	30	NUM
ajst-28595	148	26	iterations	iteration	NOUN
ajst-28595	148	27	,	,	PUNCT
ajst-28595	148	28	20	20	NUM
ajst-28595	148	29	%	%	NOUN
ajst-28595	148	30	discoverers	discoverer	NOUN
ajst-28595	148	31	in	in	ADP
ajst-28595	148	32	the	the	DET
ajst-28595	148	33	population	population	NOUN
ajst-28595	148	34	,	,	PUNCT
ajst-28595	148	35	and	and	CCONJ
ajst-28595	148	36	a	a	DET
ajst-28595	148	37	maximum	maximum	ADJ
ajst-28595	148	38	safety	safety	NOUN
ajst-28595	148	39	threshold	threshold	NOUN
ajst-28595	148	40	of	of	ADP
ajst-28595	148	41	0.7	0.7	NUM
ajst-28595	148	42	.	.	PUNCT
ajst-28595	149	1	the	the	DET
ajst-28595	149	2	fitness	fitness	NOUN
ajst-28595	149	3	curve	curve	NOUN
ajst-28595	149	4	is	be	AUX
ajst-28595	149	5	shown	show	VERB
ajst-28595	149	6	in	in	ADP
ajst-28595	149	7	figure	figure	NOUN
ajst-28595	149	8	7c	7c	PROPN
ajst-28595	149	9	.	.	PUNCT
ajst-28595	150	1	83	83	NUM
ajst-28595	150	2	a.bp	a.bp	PROPN
ajst-28595	150	3	model	model	NOUN
ajst-28595	150	4	b.gwo	b.gwo	PROPN
ajst-28595	150	5	-	-	PUNCT
ajst-28595	150	6	bp	bp	PROPN
ajst-28595	150	7	model	model	NOUN
ajst-28595	150	8	c.ssa	c.ssa	PROPN
ajst-28595	150	9	-	-	PUNCT
ajst-28595	150	10	bp	bp	PROPN
ajst-28595	150	11	model	model	NOUN
ajst-28595	150	12	figure	figure	NOUN
ajst-28595	150	13	7	7	NUM
ajst-28595	150	14	.	.	PUNCT
ajst-28595	150	15	fitness	fitness	NOUN
ajst-28595	150	16	curves	curve	NOUN
ajst-28595	150	17	of	of	ADP
ajst-28595	150	18	various	various	ADJ
ajst-28595	150	19	models	model	NOUN
ajst-28595	150	20	the	the	DET
ajst-28595	150	21	relative	relative	ADJ
ajst-28595	150	22	errors	error	NOUN
ajst-28595	150	23	of	of	ADP
ajst-28595	150	24	the	the	DET
ajst-28595	150	25	three	three	NUM
ajst-28595	150	26	prediction	prediction	NOUN
ajst-28595	150	27	models	model	NOUN
ajst-28595	150	28	and	and	CCONJ
ajst-28595	150	29	the	the	DET
ajst-28595	150	30	comparison	comparison	NOUN
ajst-28595	150	31	between	between	ADP
ajst-28595	150	32	predicted	predict	VERB
ajst-28595	150	33	values	value	NOUN
ajst-28595	150	34	and	and	CCONJ
ajst-28595	150	35	actual	actual	ADJ
ajst-28595	150	36	values	value	NOUN
ajst-28595	150	37	are	be	AUX
ajst-28595	150	38	shown	show	VERB
ajst-28595	150	39	in	in	ADP
ajst-28595	150	40	figures	figure	NOUN
ajst-28595	150	41	8	8	NUM
ajst-28595	150	42	and	and	CCONJ
ajst-28595	150	43	9	9	NUM
ajst-28595	150	44	.	.	PUNCT
ajst-28595	150	45	from	from	ADP
ajst-28595	150	46	figures	figure	NOUN
ajst-28595	150	47	8	8	NUM
ajst-28595	150	48	and	and	CCONJ
ajst-28595	150	49	9	9	NUM
ajst-28595	150	50	,	,	PUNCT
ajst-28595	150	51	it	it	PRON
ajst-28595	150	52	can	can	AUX
ajst-28595	150	53	be	be	AUX
ajst-28595	150	54	seen	see	VERB
ajst-28595	150	55	that	that	SCONJ
ajst-28595	150	56	the	the	DET
ajst-28595	150	57	gwo	gwo	PROPN
ajst-28595	150	58	-	-	PUNCT
ajst-28595	150	59	bp	bp	PROPN
ajst-28595	150	60	model	model	NOUN
ajst-28595	150	61	has	have	VERB
ajst-28595	150	62	the	the	DET
ajst-28595	150	63	largest	large	ADJ
ajst-28595	150	64	error	error	NOUN
ajst-28595	150	65	fluctuation	fluctuation	NOUN
ajst-28595	150	66	range	range	NOUN
ajst-28595	150	67	,	,	PUNCT
ajst-28595	150	68	followed	follow	VERB
ajst-28595	150	69	by	by	ADP
ajst-28595	150	70	the	the	DET
ajst-28595	150	71	bp	bp	PROPN
ajst-28595	150	72	model	model	NOUN
ajst-28595	150	73	,	,	PUNCT
ajst-28595	150	74	while	while	SCONJ
ajst-28595	150	75	the	the	DET
ajst-28595	150	76	ssa	ssa	PROPN
ajst-28595	150	77	-	-	PUNCT
ajst-28595	150	78	bp	bp	PROPN
ajst-28595	150	79	model	model	NOUN
ajst-28595	150	80	has	have	VERB
ajst-28595	150	81	the	the	DET
ajst-28595	150	82	smallest	small	ADJ
ajst-28595	150	83	error	error	NOUN
ajst-28595	150	84	fluctuation	fluctuation	NOUN
ajst-28595	150	85	range	range	NOUN
ajst-28595	150	86	.	.	PUNCT
ajst-28595	151	1	therefore	therefore	ADV
ajst-28595	151	2	,	,	PUNCT
ajst-28595	151	3	the	the	DET
ajst-28595	151	4	ssabp	ssabp	NOUN
ajst-28595	151	5	model	model	NOUN
ajst-28595	151	6	's	's	PART
ajst-28595	151	7	prediction	prediction	NOUN
ajst-28595	151	8	performance	performance	NOUN
ajst-28595	151	9	is	be	AUX
ajst-28595	151	10	significantly	significantly	ADV
ajst-28595	151	11	better	well	ADJ
ajst-28595	151	12	;	;	PUNCT
ajst-28595	151	13	its	its	PRON
ajst-28595	151	14	predicted	predict	VERB
ajst-28595	151	15	values	value	NOUN
ajst-28595	151	16	are	be	AUX
ajst-28595	151	17	closer	close	ADJ
ajst-28595	151	18	to	to	ADP
ajst-28595	151	19	the	the	DET
ajst-28595	151	20	actual	actual	ADJ
ajst-28595	151	21	values	value	NOUN
ajst-28595	151	22	,	,	PUNCT
ajst-28595	151	23	with	with	ADP
ajst-28595	151	24	a	a	DET
ajst-28595	151	25	smaller	small	ADJ
ajst-28595	151	26	error	error	NOUN
ajst-28595	151	27	fluctuation	fluctuation	NOUN
ajst-28595	151	28	range	range	NOUN
ajst-28595	151	29	and	and	CCONJ
ajst-28595	151	30	higher	high	ADJ
ajst-28595	151	31	prediction	prediction	NOUN
ajst-28595	151	32	accuracy	accuracy	NOUN
ajst-28595	151	33	,	,	PUNCT
ajst-28595	151	34	resulting	result	VERB
ajst-28595	151	35	in	in	ADP
ajst-28595	151	36	a	a	DET
ajst-28595	151	37	better	well	ADV
ajst-28595	151	38	fitting	fitting	ADJ
ajst-28595	151	39	effect	effect	NOUN
ajst-28595	151	40	.	.	PUNCT
ajst-28595	152	1	figure	figure	VERB
ajst-28595	152	2	8	8	NUM
ajst-28595	152	3	.	.	PUNCT
ajst-28595	153	1	prediction	prediction	NOUN
ajst-28595	153	2	errors	error	NOUN
ajst-28595	153	3	of	of	ADP
ajst-28595	153	4	various	various	ADJ
ajst-28595	153	5	models	model	NOUN
ajst-28595	153	6	a.bp	a.bp	ADP
ajst-28595	153	7	model	model	NOUN
ajst-28595	153	8	b.gwo	b.gwo	PROPN
ajst-28595	153	9	-	-	PUNCT
ajst-28595	153	10	bp	bp	PROPN
ajst-28595	153	11	model	model	NOUN
ajst-28595	153	12	c.ssa	c.ssa	PROPN
ajst-28595	153	13	-	-	PUNCT
ajst-28595	153	14	bp	bp	PROPN
ajst-28595	153	15	model	model	NOUN
ajst-28595	153	16	figure	figure	NOUN
ajst-28595	153	17	9	9	NUM
ajst-28595	153	18	.	.	PUNCT
ajst-28595	153	19	prediction	prediction	NOUN
ajst-28595	153	20	errors	error	NOUN
ajst-28595	153	21	of	of	ADP
ajst-28595	153	22	various	various	ADJ
ajst-28595	153	23	models	model	NOUN
ajst-28595	153	24	84	84	NUM
ajst-28595	153	25	figure	figure	NOUN
ajst-28595	153	26	10	10	NUM
ajst-28595	153	27	.	.	PUNCT
ajst-28595	154	1	tool	tool	NOUN
ajst-28595	154	2	condition	condition	NOUN
ajst-28595	154	3	table	table	NOUN
ajst-28595	154	4	2	2	NUM
ajst-28595	154	5	presents	present	VERB
ajst-28595	154	6	a	a	DET
ajst-28595	154	7	comparison	comparison	NOUN
ajst-28595	154	8	of	of	ADP
ajst-28595	154	9	five	five	NUM
ajst-28595	154	10	evaluation	evaluation	NOUN
ajst-28595	154	11	indicators	indicator	NOUN
ajst-28595	154	12	for	for	ADP
ajst-28595	154	13	the	the	DET
ajst-28595	154	14	bp	bp	PROPN
ajst-28595	154	15	neural	neural	PROPN
ajst-28595	154	16	network	network	NOUN
ajst-28595	154	17	,	,	PUNCT
ajst-28595	154	18	ssa	ssa	NOUN
ajst-28595	154	19	-	-	PUNCT
ajst-28595	154	20	bp	bp	PROPN
ajst-28595	154	21	neural	neural	ADJ
ajst-28595	154	22	network	network	NOUN
ajst-28595	154	23	,	,	PUNCT
ajst-28595	154	24	and	and	CCONJ
ajst-28595	154	25	gwo	gwo	PROPN
ajst-28595	154	26	-	-	PUNCT
ajst-28595	154	27	bp	bp	PROPN
ajst-28595	154	28	neural	neural	ADJ
ajst-28595	154	29	network	network	NOUN
ajst-28595	154	30	.	.	PUNCT
ajst-28595	155	1	therefore	therefore	ADV
ajst-28595	155	2	,	,	PUNCT
ajst-28595	155	3	the	the	DET
ajst-28595	155	4	ssa	ssa	PROPN
ajst-28595	155	5	-	-	PUNCT
ajst-28595	155	6	bp	bp	PROPN
ajst-28595	155	7	neural	neural	ADJ
ajst-28595	155	8	network	network	NOUN
ajst-28595	155	9	prediction	prediction	NOUN
ajst-28595	155	10	model	model	NOUN
ajst-28595	155	11	has	have	VERB
ajst-28595	155	12	higher	high	ADJ
ajst-28595	155	13	predictive	predictive	ADJ
ajst-28595	155	14	accuracy	accuracy	NOUN
ajst-28595	155	15	than	than	ADP
ajst-28595	155	16	the	the	DET
ajst-28595	155	17	bp	bp	PROPN
ajst-28595	155	18	neural	neural	PROPN
ajst-28595	155	19	network	network	NOUN
ajst-28595	155	20	prediction	prediction	NOUN
ajst-28595	155	21	model	model	NOUN
ajst-28595	155	22	and	and	CCONJ
ajst-28595	155	23	the	the	DET
ajst-28595	155	24	gwo	gwo	PROPN
ajst-28595	155	25	-	-	PUNCT
ajst-28595	155	26	bp	bp	PROPN
ajst-28595	155	27	neural	neural	ADJ
ajst-28595	155	28	network	network	NOUN
ajst-28595	155	29	prediction	prediction	NOUN
ajst-28595	155	30	model	model	NOUN
ajst-28595	155	31	.	.	PUNCT
ajst-28595	156	1	specifically	specifically	ADV
ajst-28595	156	2	,	,	PUNCT
ajst-28595	156	3	the	the	DET
ajst-28595	156	4	coefficient	coefficient	NOUN
ajst-28595	156	5	of	of	ADP
ajst-28595	156	6	determination	determination	NOUN
ajst-28595	156	7	of	of	ADP
ajst-28595	156	8	the	the	DET
ajst-28595	156	9	ssa	ssa	PROPN
ajst-28595	156	10	-	-	PUNCT
ajst-28595	156	11	bp	bp	PROPN
ajst-28595	156	12	model	model	NOUN
ajst-28595	156	13	increased	increase	VERB
ajst-28595	156	14	by	by	ADP
ajst-28595	156	15	4.32	4.32	NUM
ajst-28595	156	16	%	%	NOUN
ajst-28595	156	17	and	and	CCONJ
ajst-28595	156	18	6.18	6.18	NUM
ajst-28595	156	19	%	%	NOUN
ajst-28595	156	20	;	;	PUNCT
ajst-28595	156	21	the	the	DET
ajst-28595	156	22	explained	explain	VERB
ajst-28595	156	23	variance	variance	NOUN
ajst-28595	156	24	score	score	NOUN
ajst-28595	156	25	increased	increase	VERB
ajst-28595	156	26	by	by	ADP
ajst-28595	156	27	0.22	0.22	NUM
ajst-28595	156	28	%	%	NOUN
ajst-28595	156	29	and	and	CCONJ
ajst-28595	156	30	3.13	3.13	NUM
ajst-28595	156	31	%	%	NOUN
ajst-28595	156	32	;	;	PUNCT
ajst-28595	156	33	the	the	DET
ajst-28595	156	34	mean	mean	NOUN
ajst-28595	156	35	squared	square	VERB
ajst-28595	156	36	error	error	NOUN
ajst-28595	156	37	decreased	decrease	VERB
ajst-28595	156	38	by	by	ADP
ajst-28595	156	39	63	63	NUM
ajst-28595	156	40	%	%	NOUN
ajst-28595	156	41	and	and	CCONJ
ajst-28595	156	42	71	71	NUM
ajst-28595	156	43	%	%	NOUN
ajst-28595	156	44	;	;	PUNCT
ajst-28595	156	45	the	the	DET
ajst-28595	156	46	mean	mean	ADJ
ajst-28595	156	47	absolute	absolute	ADJ
ajst-28595	156	48	error	error	NOUN
ajst-28595	156	49	decreased	decrease	VERB
ajst-28595	156	50	by	by	ADP
ajst-28595	156	51	44.26	44.26	NUM
ajst-28595	156	52	%	%	NOUN
ajst-28595	156	53	and	and	CCONJ
ajst-28595	156	54	44.5	44.5	NUM
ajst-28595	156	55	%	%	NOUN
ajst-28595	156	56	;	;	PUNCT
ajst-28595	156	57	the	the	DET
ajst-28595	156	58	mean	mean	ADJ
ajst-28595	156	59	absolute	absolute	ADJ
ajst-28595	156	60	percentage	percentage	NOUN
ajst-28595	156	61	error	error	NOUN
ajst-28595	156	62	decreased	decrease	VERB
ajst-28595	156	63	by	by	ADP
ajst-28595	156	64	0.1097	0.1097	NUM
ajst-28595	156	65	%	%	NOUN
ajst-28595	156	66	and	and	CCONJ
ajst-28595	156	67	0.0826	0.0826	NUM
ajst-28595	156	68	%	%	NOUN
ajst-28595	156	69	.	.	PUNCT
ajst-28595	157	1	from	from	ADP
ajst-28595	157	2	the	the	DET
ajst-28595	157	3	above	above	ADJ
ajst-28595	157	4	data	datum	NOUN
ajst-28595	157	5	,	,	PUNCT
ajst-28595	157	6	it	it	PRON
ajst-28595	157	7	is	be	AUX
ajst-28595	157	8	evident	evident	ADJ
ajst-28595	157	9	that	that	SCONJ
ajst-28595	157	10	the	the	DET
ajst-28595	157	11	ssa	ssa	PROPN
ajst-28595	157	12	-	-	PUNCT
ajst-28595	157	13	bp	bp	PROPN
ajst-28595	157	14	model	model	NOUN
ajst-28595	157	15	has	have	VERB
ajst-28595	157	16	higher	high	ADJ
ajst-28595	157	17	precision	precision	NOUN
ajst-28595	157	18	than	than	ADP
ajst-28595	157	19	the	the	DET
ajst-28595	157	20	bp	bp	PROPN
ajst-28595	157	21	model	model	NOUN
ajst-28595	157	22	and	and	CCONJ
ajst-28595	157	23	the	the	DET
ajst-28595	157	24	gwo	gwo	PROPN
ajst-28595	157	25	-	-	PUNCT
ajst-28595	157	26	bp	bp	PROPN
ajst-28595	157	27	model	model	NOUN
ajst-28595	157	28	.	.	PUNCT
ajst-28595	158	1	the	the	DET
ajst-28595	158	2	coefficient	coefficient	NOUN
ajst-28595	158	3	of	of	ADP
ajst-28595	158	4	determination	determination	NOUN
ajst-28595	158	5	of	of	ADP
ajst-28595	158	6	the	the	DET
ajst-28595	158	7	ssa	ssa	NOUN
ajst-28595	158	8	-	-	PUNCT
ajst-28595	158	9	bp	bp	PROPN
ajst-28595	158	10	neural	neural	ADJ
ajst-28595	158	11	network	network	NOUN
ajst-28595	158	12	model	model	NOUN
ajst-28595	158	13	reached	reach	VERB
ajst-28595	158	14	0.9756	0.9756	NUM
ajst-28595	158	15	,	,	PUNCT
ajst-28595	158	16	which	which	PRON
ajst-28595	158	17	is	be	AUX
ajst-28595	158	18	closer	close	ADJ
ajst-28595	158	19	to	to	ADP
ajst-28595	158	20	1	1	NUM
ajst-28595	158	21	than	than	ADP
ajst-28595	158	22	the	the	DET
ajst-28595	158	23	other	other	ADJ
ajst-28595	158	24	two	two	NUM
ajst-28595	158	25	models	model	NOUN
ajst-28595	158	26	,	,	PUNCT
ajst-28595	158	27	indicating	indicate	VERB
ajst-28595	158	28	that	that	SCONJ
ajst-28595	158	29	this	this	DET
ajst-28595	158	30	model	model	NOUN
ajst-28595	158	31	has	have	VERB
ajst-28595	158	32	a	a	DET
ajst-28595	158	33	better	well	ADV
ajst-28595	158	34	fitting	fitting	ADJ
ajst-28595	158	35	effect	effect	NOUN
ajst-28595	158	36	.	.	PUNCT
ajst-28595	159	1	the	the	DET
ajst-28595	159	2	actual	actual	ADJ
ajst-28595	159	3	state	state	NOUN
ajst-28595	159	4	of	of	ADP
ajst-28595	159	5	the	the	DET
ajst-28595	159	6	tool	tool	NOUN
ajst-28595	159	7	is	be	AUX
ajst-28595	159	8	shown	show	VERB
ajst-28595	159	9	in	in	ADP
ajst-28595	159	10	figure	figure	NOUN
ajst-28595	159	11	11	11	NUM
ajst-28595	159	12	.	.	PUNCT
ajst-28595	160	1	figure	figure	VERB
ajst-28595	160	2	11	11	NUM
ajst-28595	160	3	.	.	PUNCT
ajst-28595	161	1	accuracy	accuracy	NOUN
ajst-28595	161	2	comparison	comparison	NOUN
ajst-28595	161	3	of	of	ADP
ajst-28595	161	4	various	various	ADJ
ajst-28595	161	5	models	model	NOUN
ajst-28595	161	6	table	table	VERB
ajst-28595	161	7	2	2	NUM
ajst-28595	161	8	.	.	PUNCT
ajst-28595	161	9	evaluation	evaluation	NOUN
ajst-28595	161	10	metrics	metric	NOUN
ajst-28595	161	11	model	model	NOUN
ajst-28595	161	12	r2	r2	PROPN
ajst-28595	161	13	evs	evs	PROPN
ajst-28595	161	14	mes	mes	PROPN
ajst-28595	161	15	mae	mae	PROPN
ajst-28595	161	16	mape	mape	PROPN
ajst-28595	161	17	bp	bp	PROPN
ajst-28595	161	18	0.9335	0.9335	NUM
ajst-28595	161	19	0.9804	0.9804	NUM
ajst-28595	161	20	0.006	0.006	NUM
ajst-28595	161	21	0.0671	0.0671	NUM
ajst-28595	161	22	0.2056	0.2056	NUM
ajst-28595	161	23	%	%	NOUN
ajst-28595	161	24	ssa	ssa	NOUN
ajst-28595	161	25	-	-	PUNCT
ajst-28595	161	26	bp	bp	PROPN
ajst-28595	161	27	0.9756	0.9756	NUM
ajst-28595	161	28	0.9826	0.9826	NUM
ajst-28595	161	29	0.0022	0.0022	NUM
ajst-28595	161	30	0.0374	0.0374	NUM
ajst-28595	161	31	0.0959	0.0959	NUM
ajst-28595	161	32	%	%	NOUN
ajst-28595	161	33	gwo	gwo	PROPN
ajst-28595	161	34	-	-	NOUN
ajst-28595	161	35	bp	bp	PROPN
ajst-28595	161	36	0.9153	0.9153	NUM
ajst-28595	161	37	0.9518	0.9518	NUM
ajst-28595	161	38	0.0076	0.0076	NUM
ajst-28595	161	39	0.0674	0.0674	NUM
ajst-28595	161	40	0.1785	0.1785	NUM
ajst-28595	161	41	%	%	NOUN
ajst-28595	161	42	5	5	NUM
ajst-28595	161	43	.	.	PUNCT
ajst-28595	161	44	conclusion	conclusion	NOUN
ajst-28595	161	45	(	(	PUNCT
ajst-28595	161	46	1	1	X
ajst-28595	161	47	)	)	PUNCT
ajst-28595	161	48	this	this	DET
ajst-28595	161	49	paper	paper	NOUN
ajst-28595	161	50	starts	start	VERB
ajst-28595	161	51	from	from	ADP
ajst-28595	161	52	the	the	DET
ajst-28595	161	53	data	data	NOUN
ajst-28595	161	54	source	source	NOUN
ajst-28595	161	55	of	of	ADP
ajst-28595	161	56	the	the	DET
ajst-28595	161	57	machine	machine	NOUN
ajst-28595	161	58	tool	tool	NOUN
ajst-28595	161	59	,	,	PUNCT
ajst-28595	161	60	connects	connect	VERB
ajst-28595	161	61	to	to	ADP
ajst-28595	161	62	the	the	DET
ajst-28595	161	63	numerical	numerical	PROPN
ajst-28595	161	64	control	control	PROPN
ajst-28595	161	65	machine	machine	NOUN
ajst-28595	161	66	tool	tool	NOUN
ajst-28595	161	67	through	through	ADP
ajst-28595	161	68	communication	communication	NOUN
ajst-28595	161	69	protocols	protocol	NOUN
ajst-28595	161	70	to	to	PART
ajst-28595	161	71	achieve	achieve	VERB
ajst-28595	161	72	real	real	ADJ
ajst-28595	161	73	-	-	PUNCT
ajst-28595	161	74	time	time	NOUN
ajst-28595	161	75	data	datum	NOUN
ajst-28595	161	76	acquisition	acquisition	NOUN
ajst-28595	161	77	,	,	PUNCT
ajst-28595	161	78	mainly	mainly	ADV
ajst-28595	161	79	collecting	collect	VERB
ajst-28595	161	80	the	the	DET
ajst-28595	161	81	cutting	cutting	NOUN
ajst-28595	161	82	time	time	NOUN
ajst-28595	161	83	of	of	ADP
ajst-28595	161	84	machine	machine	NOUN
ajst-28595	161	85	tool	tool	NOUN
ajst-28595	161	86	tools	tool	NOUN
ajst-28595	161	87	,	,	PUNCT
ajst-28595	161	88	spindle	spindle	NOUN
ajst-28595	161	89	load	load	NOUN
ajst-28595	161	90	,	,	PUNCT
ajst-28595	161	91	spindle	spindle	NOUN
ajst-28595	161	92	load	load	NOUN
ajst-28595	161	93	rate	rate	NOUN
ajst-28595	161	94	,	,	PUNCT
ajst-28595	161	95	x	x	ADJ
ajst-28595	161	96	-	-	ADJ
ajst-28595	161	97	axis	axis	ADJ
ajst-28595	161	98	current	current	ADJ
ajst-28595	161	99	information	information	NOUN
ajst-28595	161	100	,	,	PUNCT
ajst-28595	161	101	y	y	NOUN
ajst-28595	161	102	-	-	PUNCT
ajst-28595	161	103	axis	axis	ADJ
ajst-28595	161	104	current	current	ADJ
ajst-28595	161	105	information	information	NOUN
ajst-28595	161	106	,	,	PUNCT
ajst-28595	161	107	z	z	NOUN
ajst-28595	161	108	-	-	PUNCT
ajst-28595	161	109	axis	axis	ADJ
ajst-28595	161	110	current	current	ADJ
ajst-28595	161	111	information	information	NOUN
ajst-28595	161	112	,	,	PUNCT
ajst-28595	161	113	x	x	ADJ
ajst-28595	161	114	-	-	ADJ
ajst-28595	161	115	axis	axis	ADJ
ajst-28595	161	116	load	load	NOUN
ajst-28595	161	117	rate	rate	NOUN
ajst-28595	161	118	,	,	PUNCT
ajst-28595	161	119	y	y	NOUN
ajst-28595	161	120	-	-	PUNCT
ajst-28595	161	121	axis	axis	NOUN
ajst-28595	161	122	load	load	NOUN
ajst-28595	161	123	rate	rate	NOUN
ajst-28595	161	124	,	,	PUNCT
ajst-28595	161	125	and	and	CCONJ
ajst-28595	161	126	z	z	NOUN
ajst-28595	161	127	-	-	PUNCT
ajst-28595	161	128	axis	axis	NOUN
ajst-28595	161	129	load	load	NOUN
ajst-28595	161	130	rate	rate	NOUN
ajst-28595	161	131	to	to	PART
ajst-28595	161	132	provide	provide	VERB
ajst-28595	161	133	data	datum	NOUN
ajst-28595	161	134	for	for	ADP
ajst-28595	161	135	the	the	DET
ajst-28595	161	136	tool	tool	NOUN
ajst-28595	161	137	life	life	NOUN
ajst-28595	161	138	prediction	prediction	NOUN
ajst-28595	161	139	model	model	NOUN
ajst-28595	161	140	.	.	PUNCT
ajst-28595	162	1	(	(	PUNCT
ajst-28595	162	2	2	2	X
ajst-28595	162	3	)	)	PUNCT
ajst-28595	162	4	the	the	DET
ajst-28595	162	5	initially	initially	ADV
ajst-28595	162	6	collected	collect	VERB
ajst-28595	162	7	data	datum	NOUN
ajst-28595	162	8	is	be	AUX
ajst-28595	162	9	preprocessed	preprocesse	VERB
ajst-28595	162	10	and	and	CCONJ
ajst-28595	162	11	labeled	label	VERB
ajst-28595	162	12	to	to	PART
ajst-28595	162	13	construct	construct	VERB
ajst-28595	162	14	an	an	DET
ajst-28595	162	15	ssa	ssa	NOUN
ajst-28595	162	16	-	-	PUNCT
ajst-28595	162	17	bp	bp	PROPN
ajst-28595	162	18	tool	tool	NOUN
ajst-28595	162	19	life	life	NOUN
ajst-28595	162	20	prediction	prediction	NOUN
ajst-28595	162	21	model	model	NOUN
ajst-28595	162	22	,	,	PUNCT
ajst-28595	162	23	which	which	PRON
ajst-28595	162	24	optimizes	optimize	VERB
ajst-28595	162	25	the	the	DET
ajst-28595	162	26	parameters	parameter	NOUN
ajst-28595	162	27	of	of	ADP
ajst-28595	162	28	the	the	DET
ajst-28595	162	29	bp	bp	PROPN
ajst-28595	162	30	neural	neural	PROPN
ajst-28595	162	31	network	network	PROPN
ajst-28595	162	32	model	model	NOUN
ajst-28595	162	33	through	through	ADP
ajst-28595	162	34	the	the	DET
ajst-28595	162	35	sparrow	sparrow	ADJ
ajst-28595	162	36	search	search	NOUN
ajst-28595	162	37	algorithm	algorithm	NOUN
ajst-28595	162	38	(	(	PUNCT
ajst-28595	162	39	ssa	ssa	NOUN
ajst-28595	162	40	)	)	PUNCT
ajst-28595	162	41	.	.	PUNCT
ajst-28595	163	1	to	to	PART
ajst-28595	163	2	explore	explore	VERB
ajst-28595	163	3	the	the	DET
ajst-28595	163	4	accuracy	accuracy	NOUN
ajst-28595	163	5	of	of	ADP
ajst-28595	163	6	the	the	DET
ajst-28595	163	7	ssa	ssa	PROPN
ajst-28595	163	8	-	-	PUNCT
ajst-28595	163	9	bp	bp	PROPN
ajst-28595	163	10	model	model	NOUN
ajst-28595	163	11	,	,	PUNCT
ajst-28595	163	12	bp	bp	PROPN
ajst-28595	163	13	and	and	CCONJ
ajst-28595	163	14	gwo	gwo	PROPN
ajst-28595	163	15	-	-	PUNCT
ajst-28595	163	16	bp	bp	PROPN
ajst-28595	163	17	are	be	AUX
ajst-28595	163	18	used	use	VERB
ajst-28595	163	19	as	as	ADP
ajst-28595	163	20	comparison	comparison	NOUN
ajst-28595	163	21	models	model	NOUN
ajst-28595	163	22	.	.	PUNCT
ajst-28595	164	1	the	the	DET
ajst-28595	164	2	experimental	experimental	ADJ
ajst-28595	164	3	results	result	NOUN
ajst-28595	164	4	show	show	VERB
ajst-28595	164	5	that	that	SCONJ
ajst-28595	164	6	compared	compare	VERB
ajst-28595	164	7	to	to	ADP
ajst-28595	164	8	bp	bp	PROPN
ajst-28595	164	9	and	and	CCONJ
ajst-28595	164	10	gwo	gwo	PROPN
ajst-28595	164	11	-	-	PUNCT
ajst-28595	164	12	bp	bp	PROPN
ajst-28595	164	13	,	,	PUNCT
ajst-28595	164	14	the	the	DET
ajst-28595	164	15	neural	neural	ADJ
ajst-28595	164	16	network	network	NOUN
ajst-28595	164	17	prediction	prediction	NOUN
ajst-28595	164	18	accuracy	accuracy	NOUN
ajst-28595	164	19	is	be	AUX
ajst-28595	164	20	increased	increase	VERB
ajst-28595	164	21	by	by	ADP
ajst-28595	164	22	4.32	4.32	NUM
ajst-28595	164	23	%	%	NOUN
ajst-28595	164	24	and	and	CCONJ
ajst-28595	164	25	6.18	6.18	NUM
ajst-28595	164	26	%	%	NOUN
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ajst-28595	164	28	and	and	CCONJ
ajst-28595	164	29	the	the	DET
ajst-28595	164	30	mean	mean	ADJ
ajst-28595	164	31	square	square	ADJ
ajst-28595	164	32	root	root	NOUN
ajst-28595	164	33	error	error	NOUN
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ajst-28595	164	35	reduced	reduce	VERB
ajst-28595	164	36	by	by	ADP
ajst-28595	164	37	an	an	DET
ajst-28595	164	38	average	average	NOUN
ajst-28595	164	39	of	of	ADP
ajst-28595	164	40	63	63	NUM
ajst-28595	164	41	%	%	NOUN
ajst-28595	164	42	and	and	CCONJ
ajst-28595	164	43	71	71	NUM
ajst-28595	164	44	%	%	NOUN
ajst-28595	164	45	,	,	PUNCT
ajst-28595	164	46	respectively	respectively	ADV
ajst-28595	164	47	.	.	PUNCT
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ajst-28595	165	2	ssa	ssa	PROPN
ajst-28595	165	3	-	-	PUNCT
ajst-28595	165	4	bp	bp	PROPN
ajst-28595	165	5	prediction	prediction	NOUN
ajst-28595	165	6	model	model	NOUN
ajst-28595	165	7	's	's	PART
ajst-28595	165	8	five	five	NUM
ajst-28595	165	9	performance	performance	NOUN
ajst-28595	165	10	indicators	indicator	NOUN
ajst-28595	165	11	(	(	PUNCT
ajst-28595	165	12	r²	r²	NOUN
ajst-28595	165	13	,	,	PUNCT
ajst-28595	165	14	evs	evs	PROPN
ajst-28595	165	15	,	,	PUNCT
ajst-28595	165	16	mse	mse	PROPN
ajst-28595	165	17	,	,	PUNCT
ajst-28595	165	18	mae	mae	PROPN
ajst-28595	165	19	,	,	PUNCT
ajst-28595	165	20	mape	mape	NOUN
ajst-28595	165	21	)	)	PUNCT
ajst-28595	165	22	are	be	AUX
ajst-28595	165	23	superior	superior	ADJ
ajst-28595	165	24	to	to	ADP
ajst-28595	165	25	other	other	ADJ
ajst-28595	165	26	prediction	prediction	NOUN
ajst-28595	165	27	models	model	NOUN
ajst-28595	165	28	,	,	PUNCT
ajst-28595	165	29	and	and	CCONJ
ajst-28595	165	30	the	the	DET
ajst-28595	165	31	method	method	NOUN
ajst-28595	165	32	is	be	AUX
ajst-28595	165	33	significantly	significantly	ADV
ajst-28595	165	34	effective	effective	ADJ
ajst-28595	165	35	in	in	ADP
ajst-28595	165	36	all	all	DET
ajst-28595	165	37	indicators	indicator	NOUN
ajst-28595	165	38	.	.	PUNCT
ajst-28595	166	1	clearly	clearly	ADV
ajst-28595	166	2	,	,	PUNCT
ajst-28595	166	3	the	the	DET
ajst-28595	166	4	ssa	ssa	PROPN
ajst-28595	166	5	-	-	PUNCT
ajst-28595	166	6	bp	bp	PROPN
ajst-28595	166	7	model	model	NOUN
ajst-28595	166	8	can	can	AUX
ajst-28595	166	9	achieve	achieve	VERB
ajst-28595	166	10	better	well	ADJ
ajst-28595	166	11	prediction	prediction	NOUN
ajst-28595	166	12	performance	performance	NOUN
ajst-28595	166	13	and	and	CCONJ
ajst-28595	166	14	has	have	VERB
ajst-28595	166	15	certain	certain	ADJ
ajst-28595	166	16	application	application	NOUN
ajst-28595	166	17	value	value	NOUN
ajst-28595	166	18	in	in	ADP
ajst-28595	166	19	tool	tool	NOUN
ajst-28595	166	20	life	life	NOUN
ajst-28595	166	21	prediction	prediction	NOUN
ajst-28595	166	22	.	.	PUNCT
ajst-28595	167	1	acknowledgments	acknowledgment	NOUN
ajst-28595	167	2	fund	fund	NOUN
ajst-28595	167	3	project	project	NOUN
ajst-28595	167	4	:	:	PUNCT
ajst-28595	167	5	zigong	zigong	PROPN
ajst-28595	167	6	city	city	PROPN
ajst-28595	167	7	science	science	PROPN
ajst-28595	167	8	and	and	CCONJ
ajst-28595	167	9	technology	technology	PROPN
ajst-28595	167	10	bureau	bureau	NOUN
ajst-28595	167	11	school	school	NOUN
ajst-28595	167	12	-	-	PUNCT
ajst-28595	167	13	local	local	ADJ
ajst-28595	167	14	cooperation	cooperation	NOUN
ajst-28595	167	15	project	project	NOUN
ajst-28595	167	16	:	:	PUNCT
ajst-28595	167	17	development	development	NOUN
ajst-28595	167	18	of	of	ADP
ajst-28595	167	19	aviation	aviation	NOUN
ajst-28595	167	20	five	five	NUM
ajst-28595	167	21	-	-	PUNCT
ajst-28595	167	22	axis	axis	NOUN
ajst-28595	167	23	bridge	bridge	NOUN
ajst-28595	167	24	gantry	gantry	NOUN
ajst-28595	167	25	processing	processing	NOUN
ajst-28595	167	26	equipment	equipment	NOUN
ajst-28595	167	27	(	(	PUNCT
ajst-28595	167	28	self	self	NOUN
ajst-28595	167	29	-	-	PUNCT
ajst-28595	167	30	study	study	NOUN
ajst-28595	168	1	[	[	X
ajst-28595	168	2	2022]43	2022]43	NUM
ajst-28595	168	3	references	reference	NOUN
ajst-28595	168	4	[	[	X
ajst-28595	168	5	1	1	NUM
ajst-28595	168	6	]	]	X
ajst-28595	168	7	liu	liu	PROPN
ajst-28595	168	8	c	c	PROPN
ajst-28595	168	9	q	q	PROPN
ajst-28595	168	10	,	,	PUNCT
ajst-28595	168	11	li	li	PROPN
ajst-28595	168	12	y	y	PROPN
ajst-28595	168	13	g	g	PROPN
ajst-28595	168	14	,	,	PUNCT
ajst-28595	168	15	hua	hua	PROPN
ajst-28595	169	1	j	j	PROPN
ajst-28595	170	1	q	q	PROPN
ajst-28595	170	2	,	,	PUNCT
ajst-28595	170	3	et	et	PROPN
ajst-28595	170	4	al	al	PROPN
ajst-28595	170	5	.	.	PUNCT
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ajst-28595	171	2	-	-	PUNCT
ajst-28595	171	3	time	time	NOUN
ajst-28595	171	4	cutting	cut	VERB
ajst-28595	171	5	tool	tool	NOUN
ajst-28595	171	6	state	state	NOUN
ajst-28595	171	7	recognition	recognition	NOUN
ajst-28595	171	8	approach	approach	NOUN
ajst-28595	171	9	based	base	VERB
ajst-28595	171	10	on	on	ADP
ajst-28595	171	11	machining	machine	VERB
ajst-28595	171	12	features	feature	NOUN
ajst-28595	171	13	in	in	ADP
ajst-28595	171	14	nc	nc	PROPN
ajst-28595	171	15	machining	machining	NOUN
ajst-28595	171	16	process	process	NOUN
ajst-28595	171	17	of	of	ADP
ajst-28595	171	18	complex	complex	ADJ
ajst-28595	171	19	structural	structural	ADJ
ajst-28595	171	20	parts[j	parts[j	NOUN
ajst-28595	171	21	]	]	PUNCT
ajst-28595	171	22	.	.	PUNCT
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ajst-28595	172	2	journal	journal	PROPN
ajst-28595	172	3	of	of	ADP
ajst-28595	172	4	advanced	advanced	ADJ
ajst-28595	172	5	manufacturing	manufacturing	NOUN
ajst-28595	172	6	technology	technology	NOUN
ajst-28595	172	7	,	,	PUNCT
ajst-28595	172	8	2018	2018	NUM
ajst-28595	172	9	,	,	PUNCT
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ajst-28595	172	11	):	):	PUNCT
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ajst-28595	172	13	-	-	SYM
ajst-28595	172	14	241	241	NUM
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ajst-28595	173	1	[	[	X
ajst-28595	173	2	2	2	NUM
ajst-28595	173	3	]	]	PUNCT
ajst-28595	173	4	shen	shen	PROPN
ajst-28595	173	5	yujie	yujie	PROPN
ajst-28595	173	6	,	,	PUNCT
ajst-28595	173	7	sun	sun	PROPN
ajst-28595	173	8	xiangbin	xiangbin	PROPN
ajst-28595	173	9	,	,	PUNCT
ajst-28595	173	10	liu	liu	PROPN
ajst-28595	173	11	lunming	lunming	PROPN
ajst-28595	173	12	,	,	PUNCT
ajst-28595	173	13	et	et	PROPN
ajst-28595	173	14	al	al	PROPN
ajst-28595	173	15	.	.	PUNCT
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ajst-28595	174	2	remaining	remain	VERB
ajst-28595	174	3	life	life	NOUN
ajst-28595	174	4	prediction	prediction	NOUN
ajst-28595	174	5	based	base	VERB
ajst-28595	174	6	on	on	ADP
ajst-28595	174	7	multi	multi	ADJ
ajst-28595	174	8	-	-	ADJ
ajst-28595	174	9	source	source	ADJ
ajst-28595	174	10	information	information	NOUN
ajst-28595	174	11	fusion[j	fusion[j	PROPN
ajst-28595	174	12	]	]	PUNCT
ajst-28595	174	13	.	.	PUNCT
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ajst-28595	175	2	machine	machine	NOUN
ajst-28595	175	3	tools	tool	NOUN
ajst-28595	175	4	and	and	CCONJ
ajst-28595	175	5	automatic	automatic	ADJ
ajst-28595	175	6	machining	machining	NOUN
ajst-28595	175	7	technology	technology	NOUN
ajst-28595	175	8	,	,	PUNCT
ajst-28595	175	9	2022	2022	NUM
ajst-28595	175	10	,	,	PUNCT
ajst-28595	175	11	(	(	PUNCT
ajst-28595	175	12	09	09	NUM
ajst-28595	175	13	):	):	PUNCT
ajst-28595	175	14	143	143	NUM
ajst-28595	175	15	-	-	SYM
ajst-28595	175	16	146	146	NUM
ajst-28595	175	17	+	+	NOUN
ajst-28595	175	18	150	150	NUM
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ajst-28595	176	2	3	3	NUM
ajst-28595	176	3	]	]	X
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ajst-28595	176	8	frain	frain	PROPN
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ajst-28595	177	1	tool	tool	PROPN
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ajst-28595	177	3	life	life	NOUN
ajst-28595	177	4	prediction	prediction	NOUN
ajst-28595	177	5	based	base	VERB
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ajst-28595	177	10	fusion[j	fusion[j	NOUN
ajst-28595	177	11	]	]	PUNCT
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ajst-28595	180	4	prediction	prediction	NOUN
ajst-28595	180	5	method	method	NOUN
ajst-28595	180	6	based	base	VERB
ajst-28595	180	7	on	on	ADP
ajst-28595	180	8	multi	multi	ADJ
ajst-28595	180	9	-	-	ADJ
ajst-28595	180	10	channel	channel	NOUN
ajst-28595	180	11	fusion	fusion	NOUN
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ajst-28595	180	15	]	]	PUNCT
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ajst-28595	181	5	,	,	PUNCT
ajst-28595	181	6	2021	2021	NUM
ajst-28595	181	7	,	,	PUNCT
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ajst-28595	181	9	):	):	PUNCT
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ajst-28595	182	20	on	on	ADP
ajst-28595	182	21	bagging	bag	VERB
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ajst-28595	185	7	life	life	NOUN
ajst-28595	185	8	prediction	prediction	NOUN
ajst-28595	185	9	method	method	NOUN
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ajst-28595	185	11	on	on	ADP
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ajst-28595	185	13	-	-	ADJ
ajst-28595	185	14	source	source	ADJ
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ajst-28595	185	16	fusion[d	fusion[d	NOUN
ajst-28595	185	17	]	]	PUNCT
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ajst-28595	186	2	university	university	PROPN
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ajst-28595	186	5	,	,	PUNCT
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ajst-28595	187	30	]	]	PUNCT
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ajst-28595	188	9	,	,	PUNCT
ajst-28595	188	10	2023	2023	NUM
ajst-28595	188	11	,	,	PUNCT
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ajst-28595	188	13	):	):	PUNCT
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ajst-28595	188	15	-	-	SYM
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ajst-28595	189	6	.	.	PUNCT
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ajst-28595	190	2	on	on	ADP
ajst-28595	190	3	tool	tool	NOUN
ajst-28595	190	4	wear	wear	VERB
ajst-28595	190	5	status	status	NOUN
ajst-28595	190	6	monitoring	monitoring	NOUN
ajst-28595	190	7	and	and	CCONJ
ajst-28595	190	8	remaining	remain	VERB
ajst-28595	190	9	life	life	NOUN
ajst-28595	190	10	prediction[d	prediction[d	NOUN
ajst-28595	190	11	]	]	PUNCT
ajst-28595	190	12	.	.	PUNCT
ajst-28595	191	1	east	east	PROPN
ajst-28595	191	2	china	china	PROPN
ajst-28595	191	3	jiaotong	jiaotong	PROPN
ajst-28595	191	4	university	university	PROPN
ajst-28595	191	5	,	,	PUNCT
ajst-28595	191	6	2022	2022	NUM
ajst-28595	191	7	.	.	PUNCT
ajst-28595	192	1	[	[	X
ajst-28595	192	2	9	9	NUM
ajst-28595	192	3	]	]	X
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ajst-28595	192	6	,	,	PUNCT
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ajst-28595	192	8	l.	l.	PROPN
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ajst-28595	192	15	model	model	NOUN
ajst-28595	192	16	based	base	VERB
ajst-28595	192	17	on	on	ADP
ajst-28595	192	18	transformer	transformer	NOUN
ajst-28595	192	19	and	and	CCONJ
ajst-28595	192	20	customized	customized	ADJ
ajst-28595	192	21	gate	gate	NOUN
ajst-28595	192	22	control	control	NOUN
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ajst-28595	192	24	predicting	predict	VERB
ajst-28595	192	25	remaining	remain	VERB
ajst-28595	192	26	useful	useful	ADJ
ajst-28595	192	27	life	life	NOUN
ajst-28595	192	28	and	and	CCONJ
ajst-28595	192	29	health	health	NOUN
ajst-28595	192	30	status	status	NOUN
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ajst-28595	192	32	tools[j	tools[j	PROPN
ajst-28595	192	33	]	]	PUNCT
ajst-28595	192	34	.	.	PUNCT
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ajst-28595	193	2	,	,	PUNCT
ajst-28595	193	3	2024	2024	NUM
ajst-28595	193	4	,	,	PUNCT
ajst-28595	193	5	24(13	24(13	NUM
ajst-28595	193	6	):	):	PUNCT
ajst-28595	193	7	4117	4117	NUM
ajst-28595	193	8	.	.	PUNCT
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ajst-28595	194	3	]	]	X
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ajst-28595	194	5	m	m	PROPN
ajst-28595	194	6	,	,	PUNCT
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ajst-28595	194	8	s	s	PROPN
ajst-28595	194	9	,	,	PUNCT
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ajst-28595	194	17	connectionist	connectionist	NOUN
ajst-28595	194	18	system	system	NOUN
ajst-28595	194	19	and	and	CCONJ
ajst-28595	194	20	hidden	hide	VERB
ajst-28595	194	21	semi	semi	ADJ
ajst-28595	194	22	-	-	ADJ
ajst-28595	194	23	markov	markov	ADJ
ajst-28595	194	24	model	model	NOUN
ajst-28595	194	25	for	for	ADP
ajst-28595	194	26	learning	learning	NOUN
ajst-28595	194	27	-	-	PUNCT
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ajst-28595	194	29	tool	tool	NOUN
ajst-28595	194	30	wear	wear	VERB
ajst-28595	194	31	monitoring	monitoring	NOUN
ajst-28595	194	32	and	and	CCONJ
ajst-28595	194	33	remaining	remain	VERB
ajst-28595	194	34	useful	useful	ADJ
ajst-28595	194	35	life	life	NOUN
ajst-28595	194	36	prediction[j	prediction[j	PROPN
ajst-28595	194	37	]	]	PUNCT
ajst-28595	194	38	.	.	PUNCT
ajst-28595	195	1	ieee	ieee	NOUN
ajst-28595	195	2	access	access	NOUN
ajst-28595	195	3	,	,	PUNCT
ajst-28595	195	4	2022	2022	NUM
ajst-28595	195	5	,	,	PUNCT
ajst-28595	195	6	10	10	NUM
ajst-28595	195	7	:	:	SYM
ajst-28595	195	8	82469	82469	NUM
ajst-28595	195	9	-	-	SYM
ajst-28595	195	10	82482	82482	NUM
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ajst-28595	196	1	[	[	X
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ajst-28595	196	4	chen	chen	PROPN
ajst-28595	196	5	keyu	keyu	PROPN
ajst-28595	196	6	.	.	PUNCT
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ajst-28595	197	2	for	for	ADP
ajst-28595	197	3	predicting	predict	VERB
ajst-28595	197	4	the	the	DET
ajst-28595	197	5	remaining	remain	VERB
ajst-28595	197	6	service	service	NOUN
ajst-28595	197	7	life	life	NOUN
ajst-28595	197	8	of	of	ADP
ajst-28595	197	9	machining	machining	NOUN
ajst-28595	197	10	tools	tool	NOUN
ajst-28595	197	11	based	base	VERB
ajst-28595	197	12	on	on	ADP
ajst-28595	197	13	integrated	integrate	VERB
ajst-28595	197	14	cnn	cnn	PROPN
ajst-28595	197	15	-	-	PUNCT
ajst-28595	197	16	bilstm[d	bilstm[d	PROPN
ajst-28595	197	17	]	]	PUNCT
ajst-28595	197	18	.	.	PUNCT
ajst-28595	198	1	hunan	hunan	PROPN
ajst-28595	198	2	university	university	PROPN
ajst-28595	198	3	of	of	ADP
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ajst-28595	198	5	,	,	PUNCT
ajst-28595	198	6	2023	2023	NUM
ajst-28595	198	7	.	.	PUNCT
ajst-28595	199	1	[	[	X
ajst-28595	199	2	12	12	NUM
ajst-28595	199	3	]	]	X
ajst-28595	199	4	liu	liu	PROPN
ajst-28595	199	5	rui	rui	PROPN
ajst-28595	199	6	,	,	PUNCT
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ajst-28595	199	8	mei	mei	PROPN
ajst-28595	199	9	,	,	PUNCT
ajst-28595	199	10	chen	chen	PROPN
ajst-28595	199	11	yong	yong	PROPN
ajst-28595	199	12	.	.	PUNCT
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ajst-28595	200	2	on	on	ADP
ajst-28595	200	3	milling	mill	VERB
ajst-28595	200	4	tool	tool	NOUN
ajst-28595	200	5	wear	wear	VERB
ajst-28595	200	6	monitoring	monitoring	NOUN
ajst-28595	200	7	and	and	CCONJ
ajst-28595	200	8	remaining	remain	VERB
ajst-28595	200	9	life	life	NOUN
ajst-28595	200	10	prediction	prediction	NOUN
ajst-28595	200	11	method[j	method[j	NOUN
ajst-28595	200	12	]	]	PUNCT
ajst-28595	200	13	.	.	PUNCT
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ajst-28595	201	2	manufacturing	manufacturing	NOUN
ajst-28595	201	3	engineering	engineering	NOUN
ajst-28595	201	4	,	,	PUNCT
ajst-28595	201	5	2010	2010	NUM
ajst-28595	201	6	,	,	PUNCT
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ajst-28595	201	11	-	-	SYM
ajst-28595	201	12	105	105	NUM
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ajst-28595	202	2	13	13	NUM
ajst-28595	202	3	]	]	PUNCT
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ajst-28595	202	5	yi	yi	PROPN
ajst-28595	202	6	,	,	PUNCT
ajst-28595	202	7	he	he	PRON
ajst-28595	202	8	weiping	weipe	VERB
ajst-28595	202	9	,	,	PUNCT
ajst-28595	202	10	zhang	zhang	PROPN
ajst-28595	202	11	wei	wei	PROPN
ajst-28595	202	12	,	,	PUNCT
ajst-28595	202	13	et	et	PROPN
ajst-28595	202	14	al	al	PROPN
ajst-28595	202	15	.	.	PUNCT
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ajst-28595	202	17	life	life	NOUN
ajst-28595	202	18	prediction	prediction	NOUN
ajst-28595	202	19	model	model	NOUN
ajst-28595	202	20	based	base	VERB
ajst-28595	202	21	on	on	ADP
ajst-28595	202	22	bp	bp	PROPN
ajst-28595	202	23	neural	neural	PROPN
ajst-28595	202	24	network[j	network[j	PROPN
ajst-28595	202	25	]	]	PUNCT
ajst-28595	202	26	.	.	PUNCT
ajst-28595	203	1	aeronautical	aeronautical	PROPN
ajst-28595	203	2	manufacturing	manufacturing	NOUN
ajst-28595	203	3	technology	technology	NOUN
ajst-28595	203	4	,	,	PUNCT
ajst-28595	203	5	2010	2010	NUM
ajst-28595	203	6	,	,	PUNCT
ajst-28595	203	7	(	(	PUNCT
ajst-28595	203	8	08	08	NUM
ajst-28595	203	9	):	):	PUNCT
ajst-28595	203	10	93	93	NUM
ajst-28595	203	11	-	-	SYM
ajst-28595	203	12	96	96	NUM
ajst-28595	203	13	.	.	PUNCT
ajst-28595	204	1	[	[	X
ajst-28595	204	2	14	14	NUM
ajst-28595	204	3	]	]	X
ajst-28595	204	4	wang	wang	PROPN
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ajst-28595	204	8	huan	huan	PROPN
ajst-28595	204	9	,	,	PUNCT
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ajst-28595	204	11	hong	hong	PROPN
ajst-28595	204	12	,	,	PUNCT
ajst-28595	204	13	et	et	PROPN
ajst-28595	204	14	al	al	PROPN
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ajst-28595	204	17	algorithm	algorithm	NOUN
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ajst-28595	204	19	araim	araim	NOUN
ajst-28595	204	20	fault	fault	NOUN
ajst-28595	204	21	subset	subset	VERB
ajst-28595	204	22	based	base	VERB
ajst-28595	204	23	on	on	ADP
ajst-28595	204	24	sparrow	sparrow	ADJ
ajst-28595	204	25	search	search	PROPN
ajst-28595	204	26	algorithm[j	algorithm[j	PROPN
ajst-28595	204	27	]	]	PUNCT
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ajst-28595	205	3	beijing	beijing	PROPN
ajst-28595	205	4	university	university	PROPN
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ajst-28595	205	13	):	):	PUNCT
ajst-28595	205	14	2066	2066	NUM
ajst-28595	205	15	-	-	SYM
ajst-28595	205	16	2073	2073	NUM
ajst-28595	205	17	.	.	PUNCT