id	sid	tid	token	lemma	pos
ajst-21789	1	1	academic	academic	ADJ
ajst-21789	1	2	journal	journal	NOUN
ajst-21789	1	3	of	of	ADP
ajst-21789	1	4	science	science	NOUN
ajst-21789	1	5	and	and	CCONJ
ajst-21789	1	6	technology	technology	NOUN
ajst-21789	1	7	issn	issn	NOUN
ajst-21789	1	8	:	:	PUNCT
ajst-21789	1	9	2771	2771	NUM
ajst-21789	1	10	-	-	SYM
ajst-21789	1	11	3032	3032	NUM
ajst-21789	1	12	|	|	NOUN
ajst-21789	1	13	vol	vol	NOUN
ajst-21789	1	14	.	.	PROPN
ajst-21789	2	1	11	11	NUM
ajst-21789	2	2	,	,	PUNCT
ajst-21789	2	3	no	no	INTJ
ajst-21789	2	4	.	.	NOUN
ajst-21789	2	5	1	1	NUM
ajst-21789	2	6	,	,	PUNCT
ajst-21789	2	7	2024	2024	NUM
ajst-21789	2	8	197	197	NUM
ajst-21789	2	9	a	a	DET
ajst-21789	2	10	new	new	ADJ
ajst-21789	2	11	ipca‐cpso‐bp	ipca‐cpso‐bp	NOUN
ajst-21789	2	12	model	model	NOUN
ajst-21789	2	13	for	for	ADP
ajst-21789	2	14	predicting	predict	VERB
ajst-21789	2	15	gas	gas	NOUN
ajst-21789	2	16	emission	emission	NOUN
ajst-21789	2	17	in	in	ADP
ajst-21789	2	18	underground	underground	ADJ
ajst-21789	2	19	coal	coal	NOUN
ajst-21789	2	20	mines	mine	NOUN
ajst-21789	2	21	guangsheng	guangsheng	PROPN
ajst-21789	2	22	chen	chen	PROPN
ajst-21789	2	23	school	school	PROPN
ajst-21789	2	24	of	of	ADP
ajst-21789	2	25	energy	energy	NOUN
ajst-21789	2	26	science	science	NOUN
ajst-21789	2	27	and	and	CCONJ
ajst-21789	2	28	engineering	engineering	NOUN
ajst-21789	2	29	,	,	PUNCT
ajst-21789	2	30	henan	henan	PROPN
ajst-21789	2	31	polytechnic	polytechnic	PROPN
ajst-21789	2	32	university	university	PROPN
ajst-21789	2	33	,	,	PUNCT
ajst-21789	2	34	jiaozuo	jiaozuo	PROPN
ajst-21789	2	35	,	,	PUNCT
ajst-21789	2	36	henan	henan	PROPN
ajst-21789	2	37	,	,	PUNCT
ajst-21789	2	38	454003	454003	NUM
ajst-21789	2	39	china	china	PROPN
ajst-21789	2	40	abstract	abstract	NOUN
ajst-21789	2	41	:	:	PUNCT
ajst-21789	3	1	gas	gas	NOUN
ajst-21789	3	2	has	have	AUX
ajst-21789	3	3	become	become	VERB
ajst-21789	3	4	the	the	DET
ajst-21789	3	5	primary	primary	ADJ
ajst-21789	3	6	factor	factor	NOUN
ajst-21789	3	7	restricting	restrict	VERB
ajst-21789	3	8	the	the	DET
ajst-21789	3	9	safe	safe	ADJ
ajst-21789	3	10	and	and	CCONJ
ajst-21789	3	11	efficient	efficient	ADJ
ajst-21789	3	12	production	production	NOUN
ajst-21789	3	13	of	of	ADP
ajst-21789	3	14	coal	coal	NOUN
ajst-21789	3	15	mines	mine	NOUN
ajst-21789	3	16	.	.	PUNCT
ajst-21789	4	1	gas	gas	NOUN
ajst-21789	4	2	emission	emission	NOUN
ajst-21789	4	3	prediction	prediction	NOUN
ajst-21789	4	4	model	model	NOUN
ajst-21789	4	5	is	be	AUX
ajst-21789	4	6	very	very	ADV
ajst-21789	4	7	important	important	ADJ
ajst-21789	4	8	for	for	ADP
ajst-21789	4	9	mine	mine	NOUN
ajst-21789	4	10	gas	gas	NOUN
ajst-21789	4	11	emission	emission	NOUN
ajst-21789	4	12	prediction	prediction	NOUN
ajst-21789	4	13	and	and	CCONJ
ajst-21789	4	14	gas	gas	NOUN
ajst-21789	4	15	disaster	disaster	NOUN
ajst-21789	4	16	prevention	prevention	NOUN
ajst-21789	4	17	.	.	PUNCT
ajst-21789	5	1	the	the	DET
ajst-21789	5	2	improved	improve	VERB
ajst-21789	5	3	principal	principal	ADJ
ajst-21789	5	4	component	component	NOUN
ajst-21789	5	5	analysis	analysis	NOUN
ajst-21789	5	6	(	(	PUNCT
ajst-21789	5	7	ipca	ipca	PROPN
ajst-21789	5	8	)	)	PUNCT
ajst-21789	5	9	was	be	AUX
ajst-21789	5	10	used	use	VERB
ajst-21789	5	11	to	to	PART
ajst-21789	5	12	reduce	reduce	VERB
ajst-21789	5	13	the	the	DET
ajst-21789	5	14	dimension	dimension	NOUN
ajst-21789	5	15	of	of	ADP
ajst-21789	5	16	13	13	NUM
ajst-21789	5	17	influencing	influence	VERB
ajst-21789	5	18	factors	factor	NOUN
ajst-21789	5	19	of	of	ADP
ajst-21789	5	20	gas	gas	NOUN
ajst-21789	5	21	emission	emission	NOUN
ajst-21789	5	22	,	,	PUNCT
ajst-21789	5	23	and	and	CCONJ
ajst-21789	5	24	the	the	DET
ajst-21789	5	25	cpso	cpso	NOUN
ajst-21789	5	26	-	-	PUNCT
ajst-21789	5	27	bp	bp	PROPN
ajst-21789	5	28	neural	neural	ADJ
ajst-21789	5	29	network	network	NOUN
ajst-21789	5	30	prediction	prediction	NOUN
ajst-21789	5	31	model	model	NOUN
ajst-21789	5	32	was	be	AUX
ajst-21789	5	33	built	build	VERB
ajst-21789	5	34	with	with	ADP
ajst-21789	5	35	matlab	matlab	PROPN
ajst-21789	5	36	software	software	NOUN
ajst-21789	5	37	to	to	PART
ajst-21789	5	38	predict	predict	VERB
ajst-21789	5	39	the	the	DET
ajst-21789	5	40	absolute	absolute	ADJ
ajst-21789	5	41	gas	gas	NOUN
ajst-21789	5	42	emission	emission	NOUN
ajst-21789	5	43	of	of	ADP
ajst-21789	5	44	zhongtai	zhongtai	ADJ
ajst-21789	5	45	mining.the	mining.the	PROPN
ajst-21789	5	46	results	result	NOUN
ajst-21789	5	47	show	show	VERB
ajst-21789	5	48	that	that	SCONJ
ajst-21789	5	49	the	the	DET
ajst-21789	5	50	cumulative	cumulative	ADJ
ajst-21789	5	51	contribution	contribution	NOUN
ajst-21789	5	52	rate	rate	NOUN
ajst-21789	5	53	of	of	ADP
ajst-21789	5	54	principal	principal	ADJ
ajst-21789	5	55	components	component	NOUN
ajst-21789	5	56	is	be	AUX
ajst-21789	5	57	not	not	PART
ajst-21789	5	58	less	less	ADJ
ajst-21789	5	59	than	than	ADP
ajst-21789	5	60	95	95	NUM
ajst-21789	5	61	%	%	NOUN
ajst-21789	5	62	,	,	PUNCT
ajst-21789	5	63	and	and	CCONJ
ajst-21789	5	64	the	the	DET
ajst-21789	5	65	number	number	NOUN
ajst-21789	5	66	of	of	ADP
ajst-21789	5	67	principal	principal	ADJ
ajst-21789	5	68	components	component	NOUN
ajst-21789	5	69	after	after	ADP
ajst-21789	5	70	improvement	improvement	NOUN
ajst-21789	5	71	is	be	AUX
ajst-21789	5	72	reduced	reduce	VERB
ajst-21789	5	73	from	from	ADP
ajst-21789	5	74	the	the	DET
ajst-21789	5	75	original	original	ADJ
ajst-21789	5	76	6	6	NUM
ajst-21789	5	77	to	to	PART
ajst-21789	5	78	3	3	NUM
ajst-21789	5	79	,	,	PUNCT
ajst-21789	5	80	which	which	PRON
ajst-21789	5	81	effectively	effectively	ADV
ajst-21789	5	82	solves	solve	VERB
ajst-21789	5	83	the	the	DET
ajst-21789	5	84	problem	problem	NOUN
ajst-21789	5	85	of	of	ADP
ajst-21789	5	86	excessive	excessive	ADJ
ajst-21789	5	87	principal	principal	ADJ
ajst-21789	5	88	components	component	NOUN
ajst-21789	5	89	and	and	CCONJ
ajst-21789	5	90	data	datum	NOUN
ajst-21789	5	91	redundancy	redundancy	NOUN
ajst-21789	5	92	caused	cause	VERB
ajst-21789	5	93	by	by	ADP
ajst-21789	5	94	the	the	DET
ajst-21789	5	95	correlation	correlation	NOUN
ajst-21789	5	96	difference	difference	NOUN
ajst-21789	5	97	between	between	ADP
ajst-21789	5	98	various	various	ADJ
ajst-21789	5	99	influencing	influence	VERB
ajst-21789	5	100	factors	factor	NOUN
ajst-21789	5	101	and	and	CCONJ
ajst-21789	5	102	gas	gas	NOUN
ajst-21789	5	103	emission	emission	NOUN
ajst-21789	5	104	amount	amount	NOUN
ajst-21789	5	105	.	.	PUNCT
ajst-21789	6	1	at	at	ADP
ajst-21789	6	2	the	the	DET
ajst-21789	6	3	same	same	ADJ
ajst-21789	6	4	time	time	NOUN
ajst-21789	6	5	,	,	PUNCT
ajst-21789	6	6	the	the	DET
ajst-21789	6	7	optimized	optimize	VERB
ajst-21789	6	8	particle	particle	NOUN
ajst-21789	6	9	swarm	swarm	NOUN
ajst-21789	6	10	optimization	optimization	NOUN
ajst-21789	6	11	algorithm	algorithm	NOUN
ajst-21789	6	12	alleviates	alleviate	VERB
ajst-21789	6	13	the	the	DET
ajst-21789	6	14	trouble	trouble	NOUN
ajst-21789	6	15	that	that	PRON
ajst-21789	6	16	the	the	DET
ajst-21789	6	17	particle	particle	NOUN
ajst-21789	6	18	swarm	swarm	NOUN
ajst-21789	6	19	optimization	optimization	NOUN
ajst-21789	6	20	algorithm	algorithm	NOUN
ajst-21789	6	21	is	be	AUX
ajst-21789	6	22	prone	prone	ADJ
ajst-21789	6	23	to	to	PART
ajst-21789	6	24	fall	fall	VERB
ajst-21789	6	25	into	into	ADP
ajst-21789	6	26	the	the	DET
ajst-21789	6	27	local	local	ADJ
ajst-21789	6	28	optimal	optimal	ADJ
ajst-21789	6	29	solution	solution	NOUN
ajst-21789	6	30	.	.	PUNCT
ajst-21789	7	1	by	by	ADP
ajst-21789	7	2	coupling	couple	VERB
ajst-21789	7	3	the	the	DET
ajst-21789	7	4	improved	improve	VERB
ajst-21789	7	5	particle	particle	NOUN
ajst-21789	7	6	swarm	swarm	NOUN
ajst-21789	7	7	optimization	optimization	NOUN
ajst-21789	7	8	algorithm	algorithm	NOUN
ajst-21789	7	9	with	with	ADP
ajst-21789	7	10	bp	bp	PROPN
ajst-21789	7	11	neural	neural	ADJ
ajst-21789	7	12	network	network	NOUN
ajst-21789	7	13	,	,	PUNCT
ajst-21789	7	14	the	the	DET
ajst-21789	7	15	problem	problem	NOUN
ajst-21789	7	16	of	of	ADP
ajst-21789	7	17	bp	bp	PROPN
ajst-21789	7	18	neural	neural	PROPN
ajst-21789	7	19	network	network	NOUN
ajst-21789	7	20	's	's	PART
ajst-21789	7	21	over	over	NOUN
ajst-21789	7	22	-	-	PUNCT
ajst-21789	7	23	dependence	dependence	NOUN
ajst-21789	7	24	on	on	ADP
ajst-21789	7	25	the	the	DET
ajst-21789	7	26	initial	initial	ADJ
ajst-21789	7	27	value	value	NOUN
ajst-21789	7	28	of	of	ADP
ajst-21789	7	29	weights	weight	NOUN
ajst-21789	7	30	and	and	CCONJ
ajst-21789	7	31	thresholds	threshold	NOUN
ajst-21789	7	32	is	be	AUX
ajst-21789	7	33	solved	solve	VERB
ajst-21789	7	34	,	,	PUNCT
ajst-21789	7	35	and	and	CCONJ
ajst-21789	7	36	the	the	DET
ajst-21789	7	37	optimal	optimal	ADJ
ajst-21789	7	38	initial	initial	ADJ
ajst-21789	7	39	weights	weight	NOUN
ajst-21789	7	40	and	and	CCONJ
ajst-21789	7	41	thresholds	threshold	NOUN
ajst-21789	7	42	are	be	AUX
ajst-21789	7	43	provided	provide	VERB
ajst-21789	7	44	for	for	ADP
ajst-21789	7	45	bp	bp	PROPN
ajst-21789	7	46	neural	neural	ADJ
ajst-21789	7	47	network	network	NOUN
ajst-21789	7	48	,	,	PUNCT
ajst-21789	7	49	improving	improve	VERB
ajst-21789	7	50	the	the	DET
ajst-21789	7	51	accuracy	accuracy	NOUN
ajst-21789	7	52	of	of	ADP
ajst-21789	7	53	model	model	NOUN
ajst-21789	7	54	prediction	prediction	NOUN
ajst-21789	7	55	results	result	NOUN
ajst-21789	7	56	.	.	PUNCT
ajst-21789	8	1	the	the	DET
ajst-21789	8	2	average	average	ADJ
ajst-21789	8	3	relative	relative	ADJ
ajst-21789	8	4	error	error	NOUN
ajst-21789	8	5	of	of	ADP
ajst-21789	8	6	the	the	DET
ajst-21789	8	7	original	original	ADJ
ajst-21789	8	8	bp	bp	PROPN
ajst-21789	8	9	neural	neural	ADJ
ajst-21789	8	10	network	network	NOUN
ajst-21789	8	11	is	be	AUX
ajst-21789	8	12	1.6638	1.6638	NUM
ajst-21789	8	13	%	%	NOUN
ajst-21789	8	14	,	,	PUNCT
ajst-21789	8	15	the	the	DET
ajst-21789	8	16	normalized	normalize	VERB
ajst-21789	8	17	mean	mean	ADJ
ajst-21789	8	18	square	square	ADJ
ajst-21789	8	19	error	error	NOUN
ajst-21789	8	20	is	be	AUX
ajst-21789	8	21	0.3155	0.3155	NUM
ajst-21789	8	22	,	,	PUNCT
ajst-21789	8	23	and	and	CCONJ
ajst-21789	8	24	the	the	DET
ajst-21789	8	25	regression	regression	NOUN
ajst-21789	8	26	correlation	correlation	NOUN
ajst-21789	8	27	index	index	NOUN
ajst-21789	8	28	is	be	AUX
ajst-21789	8	29	0.8157	0.8157	NUM
ajst-21789	8	30	.	.	PUNCT
ajst-21789	9	1	the	the	DET
ajst-21789	9	2	ipca	ipca	PROPN
ajst-21789	9	3	-	-	PUNCT
ajst-21789	9	4	cpso	cpso	NOUN
ajst-21789	9	5	-	-	PUNCT
ajst-21789	9	6	bp	bp	PROPN
ajst-21789	9	7	prediction	prediction	NOUN
ajst-21789	9	8	model	model	NOUN
ajst-21789	9	9	decreased	decrease	VERB
ajst-21789	9	10	to	to	ADP
ajst-21789	9	11	0.5749	0.5749	NUM
ajst-21789	9	12	%	%	NOUN
ajst-21789	9	13	,	,	PUNCT
ajst-21789	9	14	0.1143	0.1143	NOUN
ajst-21789	9	15	and	and	CCONJ
ajst-21789	9	16	0.9758	0.9758	NUM
ajst-21789	9	17	,	,	PUNCT
ajst-21789	9	18	respectively	respectively	ADV
ajst-21789	9	19	.	.	PUNCT
ajst-21789	10	1	ipca	ipca	PROPN
ajst-21789	10	2	improves	improve	VERB
ajst-21789	10	3	the	the	DET
ajst-21789	10	4	data	datum	NOUN
ajst-21789	10	5	dimensionality	dimensionality	NOUN
ajst-21789	10	6	reduction	reduction	NOUN
ajst-21789	10	7	ability	ability	NOUN
ajst-21789	10	8	of	of	ADP
ajst-21789	10	9	principal	principal	ADJ
ajst-21789	10	10	component	component	NOUN
ajst-21789	10	11	analysis	analysis	NOUN
ajst-21789	10	12	,	,	PUNCT
ajst-21789	10	13	ipca	ipca	NOUN
ajst-21789	10	14	-	-	PUNCT
ajst-21789	10	15	cpso	cpso	NOUN
ajst-21789	10	16	-	-	PUNCT
ajst-21789	10	17	bp	bp	PROPN
ajst-21789	10	18	enhances	enhance	VERB
ajst-21789	10	19	the	the	DET
ajst-21789	10	20	stability	stability	NOUN
ajst-21789	10	21	of	of	ADP
ajst-21789	10	22	particle	particle	NOUN
ajst-21789	10	23	swarm	swarm	NOUN
ajst-21789	10	24	optimization	optimization	NOUN
ajst-21789	10	25	algorithm	algorithm	NOUN
ajst-21789	10	26	,	,	PUNCT
ajst-21789	10	27	and	and	CCONJ
ajst-21789	10	28	significantly	significantly	ADV
ajst-21789	10	29	improves	improve	VERB
ajst-21789	10	30	the	the	DET
ajst-21789	10	31	prediction	prediction	NOUN
ajst-21789	10	32	accuracy	accuracy	NOUN
ajst-21789	10	33	of	of	ADP
ajst-21789	10	34	bp	bp	PROPN
ajst-21789	10	35	model	model	PROPN
ajst-21789	10	36	.	.	PUNCT
ajst-21789	11	1	the	the	DET
ajst-21789	11	2	prediction	prediction	NOUN
ajst-21789	11	3	trend	trend	NOUN
ajst-21789	11	4	is	be	AUX
ajst-21789	11	5	highly	highly	ADV
ajst-21789	11	6	consistent	consistent	ADJ
ajst-21789	11	7	with	with	ADP
ajst-21789	11	8	the	the	DET
ajst-21789	11	9	actual	actual	ADJ
ajst-21789	11	10	value	value	NOUN
ajst-21789	11	11	,	,	PUNCT
ajst-21789	11	12	which	which	PRON
ajst-21789	11	13	verifies	verify	VERB
ajst-21789	11	14	the	the	DET
ajst-21789	11	15	reliability	reliability	NOUN
ajst-21789	11	16	of	of	ADP
ajst-21789	11	17	the	the	DET
ajst-21789	11	18	model	model	NOUN
ajst-21789	11	19	and	and	CCONJ
ajst-21789	11	20	provides	provide	VERB
ajst-21789	11	21	strong	strong	ADJ
ajst-21789	11	22	data	datum	NOUN
ajst-21789	11	23	support	support	NOUN
ajst-21789	11	24	for	for	ADP
ajst-21789	11	25	mine	mine	NOUN
ajst-21789	11	26	gas	gas	NOUN
ajst-21789	11	27	prevention	prevention	NOUN
ajst-21789	11	28	and	and	CCONJ
ajst-21789	11	29	control	control	NOUN
ajst-21789	11	30	.	.	PUNCT
ajst-21789	12	1	keywords	keyword	NOUN
ajst-21789	12	2	:	:	PUNCT
ajst-21789	12	3	keywords	keyword	NOUN
ajst-21789	12	4	:	:	PUNCT
ajst-21789	12	5	prediction	prediction	NOUN
ajst-21789	12	6	of	of	ADP
ajst-21789	12	7	gas	gas	NOUN
ajst-21789	12	8	emission	emission	NOUN
ajst-21789	12	9	;	;	PUNCT
ajst-21789	12	10	spearman	spearman	NOUN
ajst-21789	12	11	correlation	correlation	NOUN
ajst-21789	12	12	coefficient	coefficient	NOUN
ajst-21789	12	13	;	;	PUNCT
ajst-21789	12	14	principal	principal	ADJ
ajst-21789	12	15	component	component	NOUN
ajst-21789	12	16	analysis	analysis	NOUN
ajst-21789	12	17	;	;	PUNCT
ajst-21789	12	18	particle	particle	NOUN
ajst-21789	12	19	swarm	swarm	NOUN
ajst-21789	12	20	optimization	optimization	NOUN
ajst-21789	12	21	;	;	PUNCT
ajst-21789	12	22	bp	bp	PROPN
ajst-21789	12	23	neural	neural	ADJ
ajst-21789	12	24	network	network	NOUN
ajst-21789	12	25	.	.	PUNCT
ajst-21789	13	1	1	1	X
ajst-21789	13	2	.	.	X
ajst-21789	13	3	introduction	introduction	NOUN
ajst-21789	13	4	mine	mine	NOUN
ajst-21789	13	5	gas	gas	NOUN
ajst-21789	13	6	gushing	gushing	NOUN
ajst-21789	13	7	is	be	AUX
ajst-21789	13	8	one	one	NUM
ajst-21789	13	9	of	of	ADP
ajst-21789	13	10	the	the	DET
ajst-21789	13	11	main	main	ADJ
ajst-21789	13	12	causes	cause	NOUN
ajst-21789	13	13	of	of	ADP
ajst-21789	13	14	gas	gas	NOUN
ajst-21789	13	15	accidents	accident	NOUN
ajst-21789	13	16	.	.	PUNCT
ajst-21789	14	1	according	accord	VERB
ajst-21789	14	2	to	to	ADP
ajst-21789	14	3	the	the	DET
ajst-21789	14	4	requirements	requirement	NOUN
ajst-21789	14	5	of	of	ADP
ajst-21789	14	6	coal	coal	NOUN
ajst-21789	14	7	mine	mine	NOUN
ajst-21789	14	8	safety	safety	NOUN
ajst-21789	14	9	regulations	regulation	NOUN
ajst-21789	14	10	,	,	PUNCT
ajst-21789	14	11	it	it	PRON
ajst-21789	14	12	is	be	AUX
ajst-21789	14	13	necessary	necessary	ADJ
ajst-21789	14	14	to	to	PART
ajst-21789	14	15	predict	predict	VERB
ajst-21789	14	16	the	the	DET
ajst-21789	14	17	gas	gas	NOUN
ajst-21789	14	18	emission	emission	NOUN
ajst-21789	14	19	quantity	quantity	NOUN
ajst-21789	14	20	of	of	ADP
ajst-21789	14	21	coal	coal	NOUN
ajst-21789	14	22	mining	mining	NOUN
ajst-21789	14	23	face	face	NOUN
ajst-21789	14	24	before	before	ADP
ajst-21789	14	25	mining	mining	NOUN
ajst-21789	14	26	,	,	PUNCT
ajst-21789	14	27	so	so	CCONJ
ajst-21789	14	28	the	the	DET
ajst-21789	14	29	prediction	prediction	NOUN
ajst-21789	14	30	research	research	NOUN
ajst-21789	14	31	of	of	ADP
ajst-21789	14	32	gas	gas	NOUN
ajst-21789	14	33	emission	emission	NOUN
ajst-21789	14	34	quantity	quantity	NOUN
ajst-21789	14	35	is	be	AUX
ajst-21789	14	36	very	very	ADV
ajst-21789	14	37	important	important	ADJ
ajst-21789	15	1	[	[	X
ajst-21789	15	2	1	1	NUM
ajst-21789	15	3	-	-	SYM
ajst-21789	15	4	3].at	3].at	NUM
ajst-21789	15	5	present	present	NOUN
ajst-21789	15	6	,	,	PUNCT
ajst-21789	15	7	many	many	ADJ
ajst-21789	15	8	scholars	scholar	NOUN
ajst-21789	15	9	have	have	AUX
ajst-21789	15	10	carried	carry	VERB
ajst-21789	15	11	out	out	ADP
ajst-21789	15	12	a	a	DET
ajst-21789	15	13	lot	lot	NOUN
ajst-21789	15	14	of	of	ADP
ajst-21789	15	15	work	work	NOUN
ajst-21789	15	16	on	on	ADP
ajst-21789	15	17	the	the	DET
ajst-21789	15	18	prediction	prediction	NOUN
ajst-21789	15	19	of	of	ADP
ajst-21789	15	20	gas	gas	NOUN
ajst-21789	15	21	emission	emission	NOUN
ajst-21789	15	22	and	and	CCONJ
ajst-21789	15	23	obtained	obtain	VERB
ajst-21789	15	24	a	a	DET
ajst-21789	15	25	lot	lot	NOUN
ajst-21789	15	26	of	of	ADP
ajst-21789	15	27	results	result	NOUN
ajst-21789	15	28	.	.	PUNCT
ajst-21789	16	1	xie	xie	PROPN
ajst-21789	16	2	minglu	minglu	PROPN
ajst-21789	16	3	et	et	PROPN
ajst-21789	16	4	al.[4	al.[4	PROPN
ajst-21789	16	5	]	]	PUNCT
ajst-21789	16	6	used	use	VERB
ajst-21789	16	7	the	the	DET
ajst-21789	16	8	method	method	NOUN
ajst-21789	16	9	of	of	ADP
ajst-21789	16	10	multiple	multiple	ADJ
ajst-21789	16	11	linear	linear	ADJ
ajst-21789	16	12	regression	regression	NOUN
ajst-21789	16	13	and	and	CCONJ
ajst-21789	16	14	spss	spss	PROPN
ajst-21789	16	15	software	software	NOUN
ajst-21789	16	16	to	to	PART
ajst-21789	16	17	process	process	VERB
ajst-21789	16	18	the	the	DET
ajst-21789	16	19	data	datum	NOUN
ajst-21789	16	20	,	,	PUNCT
ajst-21789	16	21	carried	carry	VERB
ajst-21789	16	22	out	out	ADP
ajst-21789	16	23	multiple	multiple	ADJ
ajst-21789	16	24	regression	regression	NOUN
ajst-21789	16	25	analysis	analysis	NOUN
ajst-21789	16	26	on	on	ADP
ajst-21789	16	27	the	the	DET
ajst-21789	16	28	influencing	influence	VERB
ajst-21789	16	29	factors	factor	NOUN
ajst-21789	16	30	of	of	ADP
ajst-21789	16	31	gas	gas	NOUN
ajst-21789	16	32	emission	emission	NOUN
ajst-21789	16	33	,	,	PUNCT
ajst-21789	16	34	and	and	CCONJ
ajst-21789	16	35	worked	work	VERB
ajst-21789	16	36	out	out	ADP
ajst-21789	16	37	the	the	DET
ajst-21789	16	38	regression	regression	NOUN
ajst-21789	16	39	equation	equation	NOUN
ajst-21789	16	40	for	for	ADP
ajst-21789	16	41	prediction	prediction	NOUN
ajst-21789	16	42	;	;	PUNCT
ajst-21789	16	43	lu	lu	PROPN
ajst-21789	16	44	guobin	guobin	PROPN
ajst-21789	16	45	et	et	PROPN
ajst-21789	16	46	al	al	PROPN
ajst-21789	16	47	.	.	PUNCT
ajst-21789	17	1	[	[	X
ajst-21789	17	2	6	6	NUM
ajst-21789	17	3	]	]	PUNCT
ajst-21789	17	4	used	use	VERB
ajst-21789	17	5	the	the	DET
ajst-21789	17	6	pca	pca	PROPN
ajst-21789	17	7	-	-	PUNCT
ajst-21789	17	8	bp	bp	PROPN
ajst-21789	17	9	model	model	NOUN
ajst-21789	17	10	to	to	PART
ajst-21789	17	11	predict	predict	VERB
ajst-21789	17	12	the	the	DET
ajst-21789	17	13	amount	amount	NOUN
ajst-21789	17	14	of	of	ADP
ajst-21789	17	15	gas	gas	NOUN
ajst-21789	17	16	emission	emission	NOUN
ajst-21789	17	17	in	in	ADP
ajst-21789	17	18	the	the	DET
ajst-21789	17	19	mining	mining	NOUN
ajst-21789	17	20	face	face	NOUN
ajst-21789	17	21	;	;	PUNCT
ajst-21789	17	22	zhou	zhou	PROPN
ajst-21789	17	23	xihua	xihua	PROPN
ajst-21789	17	24	et	et	PROPN
ajst-21789	17	25	al.[7	al.[7	PROPN
ajst-21789	17	26	]	]	PUNCT
ajst-21789	17	27	established	establish	VERB
ajst-21789	17	28	ga	ga	PROPN
ajst-21789	17	29	-	-	PUNCT
ajst-21789	17	30	bp	bp	PROPN
ajst-21789	17	31	neural	neural	ADJ
ajst-21789	17	32	network	network	NOUN
ajst-21789	17	33	prediction	prediction	NOUN
ajst-21789	17	34	model	model	NOUN
ajst-21789	17	35	based	base	VERB
ajst-21789	17	36	on	on	ADP
ajst-21789	17	37	principal	principal	ADJ
ajst-21789	17	38	factor	factor	NOUN
ajst-21789	17	39	analysis	analysis	NOUN
ajst-21789	17	40	,	,	PUNCT
ajst-21789	17	41	and	and	CCONJ
ajst-21789	17	42	introduced	introduce	VERB
ajst-21789	17	43	momentum	momentum	NOUN
ajst-21789	17	44	term	term	NOUN
ajst-21789	17	45	in	in	ADP
ajst-21789	17	46	the	the	DET
ajst-21789	17	47	process	process	NOUN
ajst-21789	17	48	of	of	ADP
ajst-21789	17	49	weight	weight	NOUN
ajst-21789	17	50	reverse	reverse	NOUN
ajst-21789	17	51	updating	update	VERB
ajst-21789	17	52	;	;	PUNCT
ajst-21789	17	53	xie	xie	PROPN
ajst-21789	17	54	xingjun	xingjun	PROPN
ajst-21789	17	55	et	et	PROPN
ajst-21789	17	56	al.[8	al.[8	PROPN
ajst-21789	17	57	]	]	PUNCT
ajst-21789	17	58	used	use	VERB
ajst-21789	17	59	kernel	kernel	PROPN
ajst-21789	17	60	principal	principal	PROPN
ajst-21789	17	61	component	component	NOUN
ajst-21789	17	62	analysis	analysis	NOUN
ajst-21789	17	63	(	(	PUNCT
ajst-21789	17	64	kpca	kpca	NOUN
ajst-21789	17	65	)	)	PUNCT
ajst-21789	17	66	to	to	PART
ajst-21789	17	67	reduce	reduce	VERB
ajst-21789	17	68	the	the	DET
ajst-21789	17	69	dimensionality	dimensionality	NOUN
ajst-21789	17	70	of	of	ADP
ajst-21789	17	71	the	the	DET
ajst-21789	17	72	influencing	influence	VERB
ajst-21789	17	73	factors	factor	NOUN
ajst-21789	17	74	.	.	PUNCT
ajst-21789	18	1	to	to	PART
ajst-21789	18	2	solve	solve	VERB
ajst-21789	18	3	the	the	DET
ajst-21789	18	4	problems	problem	NOUN
ajst-21789	18	5	of	of	ADP
ajst-21789	18	6	slow	slow	ADJ
ajst-21789	18	7	convergence	convergence	NOUN
ajst-21789	18	8	and	and	CCONJ
ajst-21789	18	9	easy	easy	ADJ
ajst-21789	18	10	to	to	PART
ajst-21789	18	11	fall	fall	VERB
ajst-21789	18	12	into	into	ADP
ajst-21789	18	13	local	local	ADJ
ajst-21789	18	14	optimal	optimal	ADJ
ajst-21789	18	15	solution	solution	NOUN
ajst-21789	18	16	in	in	ADP
ajst-21789	18	17	bp	bp	PROPN
ajst-21789	18	18	neural	neural	ADJ
ajst-21789	18	19	network	network	NOUN
ajst-21789	18	20	(	(	PUNCT
ajst-21789	18	21	bpnn	bpnn	NOUN
ajst-21789	18	22	)	)	PUNCT
ajst-21789	18	23	,	,	PUNCT
ajst-21789	18	24	they	they	PRON
ajst-21789	18	25	used	use	VERB
ajst-21789	18	26	cmga	cmga	PROPN
ajst-21789	18	27	to	to	PART
ajst-21789	18	28	optimize	optimize	VERB
ajst-21789	18	29	bpnn	bpnn	PROPN
ajst-21789	18	30	.	.	PUNCT
ajst-21789	19	1	the	the	DET
ajst-21789	19	2	coupled	couple	VERB
ajst-21789	19	3	algorithm	algorithm	NOUN
ajst-21789	19	4	of	of	ADP
ajst-21789	19	5	cmga	cmga	PROPN
ajst-21789	19	6	and	and	CCONJ
ajst-21789	19	7	bpnn	bpnn	NOUN
ajst-21789	19	8	(	(	PUNCT
ajst-21789	19	9	cmgann	cmgann	NOUN
ajst-21789	19	10	)	)	PUNCT
ajst-21789	19	11	was	be	AUX
ajst-21789	19	12	constructed	construct	VERB
ajst-21789	19	13	to	to	PART
ajst-21789	19	14	predict	predict	VERB
ajst-21789	19	15	the	the	DET
ajst-21789	19	16	gas	gas	NOUN
ajst-21789	19	17	emission	emission	NOUN
ajst-21789	19	18	;	;	PUNCT
ajst-21789	19	19	lin	lin	PROPN
ajst-21789	19	20	haifei	haifei	PROPN
ajst-21789	19	21	et	et	PROPN
ajst-21789	19	22	al.[9	al.[9	PROPN
ajst-21789	19	23	]	]	PUNCT
ajst-21789	19	24	based	base	VERB
ajst-21789	19	25	on	on	ADP
ajst-21789	19	26	the	the	DET
ajst-21789	19	27	monitoring	monitoring	NOUN
ajst-21789	19	28	data	datum	NOUN
ajst-21789	19	29	of	of	ADP
ajst-21789	19	30	absolute	absolute	ADJ
ajst-21789	19	31	gas	gas	NOUN
ajst-21789	19	32	emission	emission	NOUN
ajst-21789	19	33	at	at	ADP
ajst-21789	19	34	a	a	DET
ajst-21789	19	35	coal	coal	NOUN
ajst-21789	19	36	face	face	NOUN
ajst-21789	19	37	in	in	ADP
ajst-21789	19	38	huangling	huangling	PROPN
ajst-21789	19	39	,	,	PUNCT
ajst-21789	19	40	shaanxi	shaanxi	PROPN
ajst-21789	19	41	province	province	PROPN
ajst-21789	19	42	,	,	PUNCT
ajst-21789	19	43	applied	apply	VERB
ajst-21789	19	44	periodic	periodic	ADJ
ajst-21789	19	45	trend	trend	NOUN
ajst-21789	19	46	decomposition	decomposition	NOUN
ajst-21789	19	47	based	base	VERB
ajst-21789	19	48	on	on	ADP
ajst-21789	19	49	local	local	ADJ
ajst-21789	19	50	weighted	weight	VERB
ajst-21789	19	51	regression	regression	NOUN
ajst-21789	19	52	and	and	CCONJ
ajst-21789	19	53	integrated	integrate	VERB
ajst-21789	19	54	empirical	empirical	ADJ
ajst-21789	19	55	mode	mode	NOUN
ajst-21789	19	56	decomposition	decomposition	NOUN
ajst-21789	19	57	to	to	PART
ajst-21789	19	58	construct	construct	VERB
ajst-21789	19	59	a	a	DET
ajst-21789	19	60	segs	segs	NOUN
ajst-21789	19	61	model	model	NOUN
ajst-21789	19	62	by	by	ADP
ajst-21789	19	63	optimizing	optimize	VERB
ajst-21789	19	64	parameters	parameter	NOUN
ajst-21789	19	65	of	of	ADP
ajst-21789	19	66	support	support	NOUN
ajst-21789	19	67	vector	vector	NOUN
ajst-21789	19	68	regression	regression	NOUN
ajst-21789	19	69	machine	machine	NOUN
ajst-21789	19	70	through	through	ADP
ajst-21789	19	71	genetic	genetic	ADJ
ajst-21789	19	72	algorithm	algorithm	NOUN
ajst-21789	19	73	,	,	PUNCT
ajst-21789	19	74	and	and	CCONJ
ajst-21789	19	75	obtained	obtain	VERB
ajst-21789	19	76	the	the	DET
ajst-21789	19	77	final	final	ADJ
ajst-21789	19	78	prediction	prediction	NOUN
ajst-21789	19	79	result	result	NOUN
ajst-21789	19	80	of	of	ADP
ajst-21789	19	81	gas	gas	NOUN
ajst-21789	19	82	emission	emission	NOUN
ajst-21789	19	83	.	.	PUNCT
ajst-21789	20	1	feng	feng	PROPN
ajst-21789	20	2	shengcheng	shengcheng	PROPN
ajst-21789	20	3	et	et	PROPN
ajst-21789	20	4	al.[10	al.[10	PROPN
ajst-21789	20	5	]	]	PUNCT
ajst-21789	20	6	established	establish	VERB
ajst-21789	20	7	a	a	DET
ajst-21789	20	8	prediction	prediction	NOUN
ajst-21789	20	9	model	model	NOUN
ajst-21789	20	10	of	of	ADP
ajst-21789	20	11	gas	gas	NOUN
ajst-21789	20	12	emission	emission	NOUN
ajst-21789	20	13	in	in	ADP
ajst-21789	20	14	mining	mining	NOUN
ajst-21789	20	15	face	face	NOUN
ajst-21789	20	16	based	base	VERB
ajst-21789	20	17	on	on	ADP
ajst-21789	20	18	pca	pca	PROPN
ajst-21789	20	19	and	and	CCONJ
ajst-21789	20	20	pso	pso	NOUN
ajst-21789	20	21	-	-	PUNCT
ajst-21789	20	22	ls	ls	NOUN
ajst-21789	20	23	-	-	PUNCT
ajst-21789	20	24	svm	svm	NOUN
ajst-21789	20	25	by	by	ADP
ajst-21789	20	26	taking	take	VERB
ajst-21789	20	27	advantage	advantage	NOUN
ajst-21789	20	28	of	of	ADP
ajst-21789	20	29	the	the	DET
ajst-21789	20	30	characteristics	characteristic	NOUN
ajst-21789	20	31	of	of	ADP
ajst-21789	20	32	fast	fast	ADJ
ajst-21789	20	33	training	training	NOUN
ajst-21789	20	34	speed	speed	NOUN
ajst-21789	20	35	,	,	PUNCT
ajst-21789	20	36	global	global	ADJ
ajst-21789	20	37	optimal	optimal	ADJ
ajst-21789	20	38	solution	solution	NOUN
ajst-21789	20	39	and	and	CCONJ
ajst-21789	20	40	good	good	ADJ
ajst-21789	20	41	generalization	generalization	NOUN
ajst-21789	20	42	of	of	ADP
ajst-21789	20	43	vector	vector	NOUN
ajst-21789	20	44	machine	machine	NOUN
ajst-21789	20	45	,	,	PUNCT
ajst-21789	20	46	and	and	CCONJ
ajst-21789	20	47	successfully	successfully	ADV
ajst-21789	20	48	applied	apply	VERB
ajst-21789	20	49	it	it	PRON
ajst-21789	20	50	in	in	ADP
ajst-21789	20	51	practice	practice	NOUN
ajst-21789	20	52	.	.	PUNCT
ajst-21789	20	53	;	;	PUNCT
ajst-21789	21	1	xiao	xiao	PROPN
ajst-21789	21	2	peng	peng	PROPN
ajst-21789	21	3	et	et	PROPN
ajst-21789	21	4	al	al	PROPN
ajst-21789	22	1	[	[	X
ajst-21789	22	2	11	11	NUM
ajst-21789	22	3	]	]	PUNCT
ajst-21789	22	4	proposed	propose	VERB
ajst-21789	22	5	to	to	PART
ajst-21789	22	6	combine	combine	VERB
ajst-21789	22	7	the	the	DET
ajst-21789	22	8	wavelet	wavelet	NOUN
ajst-21789	22	9	packet	packet	NOUN
ajst-21789	22	10	decomposition	decomposition	NOUN
ajst-21789	22	11	method	method	NOUN
ajst-21789	22	12	with	with	ADP
ajst-21789	22	13	the	the	DET
ajst-21789	22	14	extreme	extreme	ADJ
ajst-21789	22	15	learning	learn	VERB
ajst-21789	22	16	machine	machine	NOUN
ajst-21789	22	17	to	to	PART
ajst-21789	22	18	build	build	VERB
ajst-21789	22	19	a	a	DET
ajst-21789	22	20	time	time	NOUN
ajst-21789	22	21	-	-	PUNCT
ajst-21789	22	22	varying	vary	VERB
ajst-21789	22	23	prediction	prediction	NOUN
ajst-21789	22	24	model	model	NOUN
ajst-21789	22	25	of	of	ADP
ajst-21789	22	26	the	the	DET
ajst-21789	22	27	gas	gas	NOUN
ajst-21789	22	28	emission	emission	NOUN
ajst-21789	22	29	quantity	quantity	NOUN
ajst-21789	22	30	,	,	PUNCT
ajst-21789	22	31	so	so	SCONJ
ajst-21789	22	32	as	as	SCONJ
ajst-21789	22	33	to	to	PART
ajst-21789	22	34	improve	improve	VERB
ajst-21789	22	35	the	the	DET
ajst-21789	22	36	prediction	prediction	NOUN
ajst-21789	22	37	accuracy	accuracy	NOUN
ajst-21789	22	38	and	and	CCONJ
ajst-21789	22	39	reliability	reliability	NOUN
ajst-21789	22	40	of	of	ADP
ajst-21789	22	41	the	the	DET
ajst-21789	22	42	gas	gas	NOUN
ajst-21789	22	43	emission	emission	NOUN
ajst-21789	22	44	quantity	quantity	NOUN
ajst-21789	22	45	.	.	PUNCT
ajst-21789	23	1	;	;	PUNCT
ajst-21789	23	2	liu	liu	PROPN
ajst-21789	23	3	feng	feng	PROPN
ajst-21789	23	4	[	[	X
ajst-21789	23	5	12	12	NUM
ajst-21789	23	6	]	]	PUNCT
ajst-21789	23	7	used	use	VERB
ajst-21789	23	8	simulated	simulated	ADJ
ajst-21789	23	9	annealing	anneal	VERB
ajst-21789	23	10	algorithm	algorithm	NOUN
ajst-21789	23	11	to	to	PART
ajst-21789	23	12	optimize	optimize	VERB
ajst-21789	23	13	particle	particle	NOUN
ajst-21789	23	14	swarm	swarm	NOUN
ajst-21789	23	15	optimization	optimization	NOUN
ajst-21789	23	16	and	and	CCONJ
ajst-21789	23	17	established	establish	VERB
ajst-21789	23	18	pca	pca	PROPN
ajst-21789	23	19	-	-	PUNCT
ajst-21789	23	20	sapsobp	sapsobp	PROPN
ajst-21789	23	21	model	model	NOUN
ajst-21789	23	22	to	to	PART
ajst-21789	23	23	predict	predict	VERB
ajst-21789	23	24	the	the	DET
ajst-21789	23	25	amount	amount	NOUN
ajst-21789	23	26	of	of	ADP
ajst-21789	23	27	gas	gas	NOUN
ajst-21789	23	28	emission	emission	NOUN
ajst-21789	23	29	,	,	PUNCT
ajst-21789	23	30	and	and	CCONJ
ajst-21789	23	31	the	the	DET
ajst-21789	23	32	prediction	prediction	NOUN
ajst-21789	23	33	results	result	NOUN
ajst-21789	23	34	showed	show	VERB
ajst-21789	23	35	that	that	SCONJ
ajst-21789	23	36	the	the	DET
ajst-21789	23	37	model	model	NOUN
ajst-21789	23	38	had	have	VERB
ajst-21789	23	39	fast	fast	ADJ
ajst-21789	23	40	convergence	convergence	NOUN
ajst-21789	23	41	speed	speed	NOUN
ajst-21789	23	42	and	and	CCONJ
ajst-21789	23	43	high	high	ADJ
ajst-21789	23	44	accuracy	accuracy	NOUN
ajst-21789	23	45	.	.	PUNCT
ajst-21789	23	46	;	;	PUNCT
ajst-21789	23	47	fu	fu	PROPN
ajst-21789	23	48	hua	hua	PROPN
ajst-21789	23	49	et	et	PROPN
ajst-21789	23	50	al.[13	al.[13	PROPN
ajst-21789	23	51	]	]	PUNCT
ajst-21789	23	52	proposed	propose	VERB
ajst-21789	23	53	an	an	DET
ajst-21789	23	54	algorithm	algorithm	NOUN
ajst-21789	23	55	combining	combine	VERB
ajst-21789	23	56	kernel	kernel	PROPN
ajst-21789	23	57	principal	principal	ADJ
ajst-21789	23	58	component	component	NOUN
ajst-21789	23	59	analysis	analysis	NOUN
ajst-21789	23	60	and	and	CCONJ
ajst-21789	23	61	autoregressive	autoregressive	ADJ
ajst-21789	23	62	integral	integral	ADJ
ajst-21789	23	63	moving	move	VERB
ajst-21789	23	64	average	average	ADJ
ajst-21789	23	65	model	model	NOUN
ajst-21789	23	66	,	,	PUNCT
ajst-21789	23	67	expressed	express	VERB
ajst-21789	23	68	the	the	DET
ajst-21789	23	69	gas	gas	NOUN
ajst-21789	23	70	emission	emission	NOUN
ajst-21789	23	71	amount	amount	NOUN
ajst-21789	23	72	as	as	ADP
ajst-21789	23	73	a	a	DET
ajst-21789	23	74	time	time	NOUN
ajst-21789	23	75	series	series	NOUN
ajst-21789	23	76	,	,	PUNCT
ajst-21789	23	77	and	and	CCONJ
ajst-21789	23	78	established	establish	VERB
ajst-21789	23	79	a	a	DET
ajst-21789	23	80	prediction	prediction	NOUN
ajst-21789	23	81	model	model	NOUN
ajst-21789	23	82	of	of	ADP
ajst-21789	23	83	the	the	DET
ajst-21789	23	84	gas	gas	NOUN
ajst-21789	23	85	emission	emission	NOUN
ajst-21789	23	86	amount	amount	NOUN
ajst-21789	23	87	with	with	ADP
ajst-21789	23	88	autoregressive	autoregressive	ADJ
ajst-21789	23	89	integral	integral	ADJ
ajst-21789	23	90	moving	move	VERB
ajst-21789	23	91	average	average	NOUN
ajst-21789	23	92	,	,	PUNCT
ajst-21789	23	93	which	which	PRON
ajst-21789	23	94	has	have	VERB
ajst-21789	23	95	high	high	ADJ
ajst-21789	23	96	prediction	prediction	NOUN
ajst-21789	23	97	accuracy	accuracy	NOUN
ajst-21789	23	98	.	.	PUNCT
ajst-21789	24	1	zhang	zhang	PROPN
ajst-21789	24	2	yucai	yucai	PROPN
ajst-21789	24	3	et	et	PROPN
ajst-21789	24	4	al.[14	al.[14	PROPN
ajst-21789	24	5	]	]	PUNCT
ajst-21789	24	6	used	use	VERB
ajst-21789	24	7	woa	woa	PROPN
ajst-21789	24	8	,	,	PUNCT
ajst-21789	24	9	a	a	DET
ajst-21789	24	10	whale	whale	NOUN
ajst-21789	24	11	optimization	optimization	NOUN
ajst-21789	24	12	algorithm	algorithm	NOUN
ajst-21789	24	13	,	,	PUNCT
ajst-21789	24	14	to	to	PART
ajst-21789	24	15	optimize	optimize	VERB
ajst-21789	24	16	lstm	lstm	NOUN
ajst-21789	24	17	to	to	PART
ajst-21789	24	18	predict	predict	VERB
ajst-21789	24	19	the	the	DET
ajst-21789	24	20	amount	amount	NOUN
ajst-21789	24	21	of	of	ADP
ajst-21789	24	22	gas	gas	NOUN
ajst-21789	24	23	emission	emission	NOUN
ajst-21789	24	24	.	.	PUNCT
ajst-21789	25	1	by	by	ADP
ajst-21789	25	2	comparing	compare	VERB
ajst-21789	25	3	the	the	DET
ajst-21789	25	4	experimental	experimental	ADJ
ajst-21789	25	5	results	result	NOUN
ajst-21789	25	6	of	of	ADP
ajst-21789	25	7	different	different	ADJ
ajst-21789	25	8	time	time	NOUN
ajst-21789	25	9	steps	step	NOUN
ajst-21789	25	10	,	,	PUNCT
ajst-21789	25	11	they	they	PRON
ajst-21789	25	12	found	find	VERB
ajst-21789	25	13	that	that	SCONJ
ajst-21789	25	14	the	the	DET
ajst-21789	25	15	model	model	NOUN
ajst-21789	25	16	had	have	VERB
ajst-21789	25	17	strong	strong	ADJ
ajst-21789	25	18	robustness	robustness	NOUN
ajst-21789	25	19	and	and	CCONJ
ajst-21789	25	20	high	high	ADJ
ajst-21789	25	21	accuracy	accuracy	NOUN
ajst-21789	25	22	;	;	PUNCT
ajst-21789	25	23	zhou	zhou	PROPN
ajst-21789	25	24	xu	xu	PROPN
ajst-21789	25	25	et	et	PROPN
ajst-21789	25	26	al.[15	al.[15	PROPN
ajst-21789	25	27	]	]	PUNCT
ajst-21789	25	28	proposed	propose	VERB
ajst-21789	25	29	a	a	DET
ajst-21789	25	30	combination	combination	NOUN
ajst-21789	25	31	of	of	ADP
ajst-21789	25	32	non	non	ADJ
ajst-21789	25	33	-	-	ADJ
ajst-21789	25	34	negative	negative	ADJ
ajst-21789	25	35	matrix	matrix	NOUN
ajst-21789	25	36	decomposition	decomposition	NOUN
ajst-21789	25	37	nmf	nmf	NOUN
ajst-21789	25	38	and	and	CCONJ
ajst-21789	25	39	random	random	ADJ
ajst-21789	25	40	forest	forest	NOUN
ajst-21789	25	41	rf	rf	NOUN
ajst-21789	25	42	,	,	PUNCT
ajst-21789	25	43	and	and	CCONJ
ajst-21789	25	44	used	use	VERB
ajst-21789	25	45	the	the	DET
ajst-21789	25	46	hunger	hunger	NOUN
ajst-21789	25	47	games	game	NOUN
ajst-21789	25	48	search	search	NOUN
ajst-21789	25	49	algorithm	algorithm	NOUN
ajst-21789	25	50	hgs	hgs	PROPN
ajst-21789	25	51	to	to	PART
ajst-21789	25	52	optimize	optimize	VERB
ajst-21789	25	53	rf	rf	NOUN
ajst-21789	25	54	parameters	parameter	NOUN
ajst-21789	25	55	,	,	PUNCT
ajst-21789	25	56	and	and	CCONJ
ajst-21789	25	57	established	establish	VERB
ajst-21789	25	58	a	a	DET
ajst-21789	25	59	coal	coal	NOUN
ajst-21789	25	60	seam	seam	NOUN
ajst-21789	25	61	gas	gas	NOUN
ajst-21789	25	62	emission	emission	NOUN
ajst-21789	25	63	prediction	prediction	NOUN
ajst-21789	25	64	model	model	NOUN
ajst-21789	25	65	with	with	ADP
ajst-21789	25	66	stable	stable	ADJ
ajst-21789	25	67	operating	operating	NOUN
ajst-21789	25	68	results	result	NOUN
ajst-21789	25	69	and	and	CCONJ
ajst-21789	25	70	high	high	ADJ
ajst-21789	25	71	precision	precision	NOUN
ajst-21789	25	72	.	.	PUNCT
ajst-21789	26	1	198	198	NUM
ajst-21789	26	2	the	the	DET
ajst-21789	26	3	above	above	ADP
ajst-21789	26	4	gas	gas	NOUN
ajst-21789	26	5	emission	emission	NOUN
ajst-21789	26	6	prediction	prediction	NOUN
ajst-21789	26	7	methods	method	NOUN
ajst-21789	26	8	have	have	AUX
ajst-21789	26	9	achieved	achieve	VERB
ajst-21789	26	10	results	result	NOUN
ajst-21789	26	11	to	to	ADP
ajst-21789	26	12	a	a	DET
ajst-21789	26	13	certain	certain	ADJ
ajst-21789	26	14	extent	extent	NOUN
ajst-21789	26	15	,	,	PUNCT
ajst-21789	26	16	but	but	CCONJ
ajst-21789	26	17	the	the	DET
ajst-21789	26	18	factors	factor	NOUN
ajst-21789	26	19	affecting	affect	VERB
ajst-21789	26	20	the	the	DET
ajst-21789	26	21	gas	gas	NOUN
ajst-21789	26	22	emission	emission	NOUN
ajst-21789	26	23	amount	amount	NOUN
ajst-21789	26	24	are	be	AUX
ajst-21789	26	25	complex	complex	ADJ
ajst-21789	26	26	and	and	CCONJ
ajst-21789	26	27	diverse	diverse	ADJ
ajst-21789	26	28	,	,	PUNCT
ajst-21789	26	29	and	and	CCONJ
ajst-21789	26	30	many	many	ADJ
ajst-21789	26	31	influencing	influence	VERB
ajst-21789	26	32	factors	factor	NOUN
ajst-21789	26	33	carry	carry	VERB
ajst-21789	26	34	a	a	DET
ajst-21789	26	35	large	large	ADJ
ajst-21789	26	36	amount	amount	NOUN
ajst-21789	26	37	of	of	ADP
ajst-21789	26	38	redundant	redundant	ADJ
ajst-21789	26	39	information	information	NOUN
ajst-21789	26	40	to	to	PART
ajst-21789	26	41	affect	affect	VERB
ajst-21789	26	42	the	the	DET
ajst-21789	26	43	prediction	prediction	NOUN
ajst-21789	26	44	accuracy	accuracy	NOUN
ajst-21789	26	45	and	and	CCONJ
ajst-21789	26	46	running	run	VERB
ajst-21789	26	47	speed	speed	NOUN
ajst-21789	26	48	of	of	ADP
ajst-21789	26	49	the	the	DET
ajst-21789	26	50	model	model	NOUN
ajst-21789	26	51	.	.	PUNCT
ajst-21789	27	1	how	how	SCONJ
ajst-21789	27	2	to	to	PART
ajst-21789	27	3	optimize	optimize	VERB
ajst-21789	27	4	the	the	DET
ajst-21789	27	5	data	datum	NOUN
ajst-21789	27	6	pre	pre	ADJ
ajst-21789	27	7	-	-	ADJ
ajst-21789	27	8	processing	processing	ADJ
ajst-21789	27	9	algorithm	algorithm	NOUN
ajst-21789	27	10	and	and	CCONJ
ajst-21789	27	11	improve	improve	VERB
ajst-21789	27	12	the	the	DET
ajst-21789	27	13	accuracy	accuracy	NOUN
ajst-21789	27	14	of	of	ADP
ajst-21789	27	15	the	the	DET
ajst-21789	27	16	prediction	prediction	NOUN
ajst-21789	27	17	results	result	NOUN
ajst-21789	27	18	has	have	AUX
ajst-21789	27	19	become	become	VERB
ajst-21789	27	20	an	an	DET
ajst-21789	27	21	urgent	urgent	ADJ
ajst-21789	27	22	task	task	NOUN
ajst-21789	27	23	for	for	ADP
ajst-21789	27	24	the	the	DET
ajst-21789	27	25	research	research	NOUN
ajst-21789	27	26	of	of	ADP
ajst-21789	27	27	prediction	prediction	NOUN
ajst-21789	27	28	models	model	NOUN
ajst-21789	27	29	.	.	PUNCT
ajst-21789	28	1	in	in	ADP
ajst-21789	28	2	order	order	NOUN
ajst-21789	28	3	to	to	PART
ajst-21789	28	4	solve	solve	VERB
ajst-21789	28	5	the	the	DET
ajst-21789	28	6	shortcomings	shortcoming	NOUN
ajst-21789	28	7	of	of	ADP
ajst-21789	28	8	the	the	DET
ajst-21789	28	9	above	above	ADJ
ajst-21789	28	10	prediction	prediction	NOUN
ajst-21789	28	11	models	model	NOUN
ajst-21789	28	12	and	and	CCONJ
ajst-21789	28	13	improve	improve	VERB
ajst-21789	28	14	the	the	DET
ajst-21789	28	15	prediction	prediction	NOUN
ajst-21789	28	16	accuracy	accuracy	NOUN
ajst-21789	28	17	,	,	PUNCT
ajst-21789	28	18	the	the	DET
ajst-21789	28	19	ipcacpso	ipcacpso	ADJ
ajst-21789	28	20	-	-	PUNCT
ajst-21789	28	21	bp	bp	NOUN
ajst-21789	28	22	model	model	NOUN
ajst-21789	28	23	of	of	ADP
ajst-21789	28	24	gas	gas	NOUN
ajst-21789	28	25	emission	emission	NOUN
ajst-21789	28	26	prediction	prediction	NOUN
ajst-21789	28	27	is	be	AUX
ajst-21789	28	28	proposed	propose	VERB
ajst-21789	28	29	in	in	ADP
ajst-21789	28	30	this	this	DET
ajst-21789	28	31	paper	paper	NOUN
ajst-21789	28	32	.	.	PUNCT
ajst-21789	29	1	by	by	ADP
ajst-21789	29	2	introducing	introduce	VERB
ajst-21789	29	3	spearman	spearman	NOUN
ajst-21789	29	4	correlation	correlation	NOUN
ajst-21789	29	5	coefficient	coefficient	NOUN
ajst-21789	29	6	into	into	ADP
ajst-21789	29	7	the	the	DET
ajst-21789	29	8	traditional	traditional	ADJ
ajst-21789	29	9	principal	principal	ADJ
ajst-21789	29	10	component	component	NOUN
ajst-21789	29	11	analysis	analysis	NOUN
ajst-21789	29	12	method	method	NOUN
ajst-21789	29	13	,	,	PUNCT
ajst-21789	29	14	the	the	DET
ajst-21789	29	15	number	number	NOUN
ajst-21789	29	16	of	of	ADP
ajst-21789	29	17	principal	principal	ADJ
ajst-21789	29	18	components	component	NOUN
ajst-21789	29	19	decreases	decrease	NOUN
ajst-21789	29	20	and	and	CCONJ
ajst-21789	29	21	the	the	DET
ajst-21789	29	22	information	information	NOUN
ajst-21789	29	23	carried	carry	VERB
ajst-21789	29	24	by	by	ADP
ajst-21789	29	25	the	the	DET
ajst-21789	29	26	first	first	ADJ
ajst-21789	29	27	principal	principal	ADJ
ajst-21789	29	28	component	component	NOUN
ajst-21789	29	29	increases	increase	NOUN
ajst-21789	29	30	after	after	ADP
ajst-21789	29	31	data	data	NOUN
ajst-21789	29	32	dimensionality	dimensionality	NOUN
ajst-21789	29	33	reduction	reduction	NOUN
ajst-21789	29	34	.	.	PUNCT
ajst-21789	30	1	adaptive	adaptive	ADJ
ajst-21789	30	2	inertia	inertia	NOUN
ajst-21789	30	3	weight	weight	NOUN
ajst-21789	30	4	and	and	CCONJ
ajst-21789	30	5	contraction	contraction	NOUN
ajst-21789	30	6	factor	factor	NOUN
ajst-21789	30	7	are	be	AUX
ajst-21789	30	8	added	add	VERB
ajst-21789	30	9	to	to	ADP
ajst-21789	30	10	the	the	DET
ajst-21789	30	11	pso	pso	NOUN
ajst-21789	30	12	algorithm	algorithm	NOUN
ajst-21789	30	13	to	to	PART
ajst-21789	30	14	ensure	ensure	VERB
ajst-21789	30	15	that	that	SCONJ
ajst-21789	30	16	the	the	DET
ajst-21789	30	17	pso	pso	NOUN
ajst-21789	30	18	algorithm	algorithm	NOUN
ajst-21789	30	19	has	have	VERB
ajst-21789	30	20	a	a	DET
ajst-21789	30	21	good	good	ADJ
ajst-21789	30	22	search	search	NOUN
ajst-21789	30	23	effect	effect	NOUN
ajst-21789	30	24	before	before	ADV
ajst-21789	30	25	and	and	CCONJ
ajst-21789	30	26	after	after	ADV
ajst-21789	30	27	.	.	PUNCT
ajst-21789	31	1	it	it	PRON
ajst-21789	31	2	is	be	AUX
ajst-21789	31	3	used	use	VERB
ajst-21789	31	4	to	to	PART
ajst-21789	31	5	optimize	optimize	VERB
ajst-21789	31	6	the	the	DET
ajst-21789	31	7	defects	defect	NOUN
ajst-21789	31	8	of	of	ADP
ajst-21789	31	9	bp	bp	PROPN
ajst-21789	31	10	neural	neural	ADJ
ajst-21789	31	11	network	network	NOUN
ajst-21789	31	12	,	,	PUNCT
ajst-21789	31	13	such	such	ADJ
ajst-21789	31	14	as	as	ADP
ajst-21789	31	15	excessive	excessive	ADJ
ajst-21789	31	16	dependence	dependence	NOUN
ajst-21789	31	17	on	on	ADP
ajst-21789	31	18	initial	initial	ADJ
ajst-21789	31	19	weights	weight	NOUN
ajst-21789	31	20	and	and	CCONJ
ajst-21789	31	21	thresholds	threshold	NOUN
ajst-21789	31	22	,	,	PUNCT
ajst-21789	31	23	and	and	CCONJ
ajst-21789	31	24	slow	slow	ADJ
ajst-21789	31	25	convergence	convergence	NOUN
ajst-21789	31	26	,	,	PUNCT
ajst-21789	31	27	so	so	SCONJ
ajst-21789	31	28	as	as	SCONJ
ajst-21789	31	29	to	to	PART
ajst-21789	31	30	improve	improve	VERB
ajst-21789	31	31	the	the	DET
ajst-21789	31	32	prediction	prediction	NOUN
ajst-21789	31	33	accuracy	accuracy	NOUN
ajst-21789	31	34	.	.	PUNCT
ajst-21789	32	1	2	2	X
ajst-21789	32	2	.	.	X
ajst-21789	32	3	principal	principal	ADJ
ajst-21789	32	4	component	component	NOUN
ajst-21789	32	5	analysis	analysis	NOUN
ajst-21789	32	6	(	(	PUNCT
ajst-21789	32	7	pca	pca	NOUN
ajst-21789	32	8	)	)	PUNCT
ajst-21789	32	9	method	method	NOUN
ajst-21789	32	10	improved	improve	VERB
ajst-21789	32	11	principal	principal	ADJ
ajst-21789	32	12	component	component	NOUN
ajst-21789	32	13	analysis	analysis	NOUN
ajst-21789	32	14	(	(	PUNCT
ajst-21789	32	15	pca	pca	NOUN
ajst-21789	32	16	)	)	PUNCT
ajst-21789	32	17	is	be	AUX
ajst-21789	32	18	a	a	DET
ajst-21789	32	19	common	common	ADJ
ajst-21789	32	20	data	data	NOUN
ajst-21789	32	21	dimensionality	dimensionality	NOUN
ajst-21789	32	22	reduction	reduction	NOUN
ajst-21789	32	23	method	method	NOUN
ajst-21789	32	24	,	,	PUNCT
ajst-21789	32	25	which	which	PRON
ajst-21789	32	26	has	have	VERB
ajst-21789	32	27	obvious	obvious	ADJ
ajst-21789	32	28	dimensionality	dimensionality	NOUN
ajst-21789	32	29	reduction	reduction	NOUN
ajst-21789	32	30	effect	effect	NOUN
ajst-21789	32	31	in	in	ADP
ajst-21789	32	32	data	data	NOUN
ajst-21789	32	33	processing	processing	NOUN
ajst-21789	32	34	,	,	PUNCT
ajst-21789	32	35	small	small	ADJ
ajst-21789	32	36	error	error	NOUN
ajst-21789	32	37	,	,	PUNCT
ajst-21789	32	38	simple	simple	ADJ
ajst-21789	32	39	operation	operation	NOUN
ajst-21789	32	40	,	,	PUNCT
ajst-21789	32	41	easy	easy	ADJ
ajst-21789	32	42	implementation	implementation	NOUN
ajst-21789	32	43	and	and	CCONJ
ajst-21789	32	44	strong	strong	ADJ
ajst-21789	32	45	practicability	practicability	NOUN
ajst-21789	32	46	,	,	PUNCT
ajst-21789	32	47	and	and	CCONJ
ajst-21789	32	48	is	be	AUX
ajst-21789	32	49	widely	widely	ADV
ajst-21789	32	50	used	use	VERB
ajst-21789	32	51	in	in	ADP
ajst-21789	32	52	the	the	DET
ajst-21789	32	53	field	field	NOUN
ajst-21789	32	54	of	of	ADP
ajst-21789	32	55	gas	gas	NOUN
ajst-21789	32	56	emission	emission	NOUN
ajst-21789	32	57	prediction	prediction	NOUN
ajst-21789	32	58	.	.	PUNCT
ajst-21789	33	1	2.1	2.1	NUM
ajst-21789	33	2	.	.	PUNCT
ajst-21789	33	3	influencing	influence	VERB
ajst-21789	33	4	factors	factor	NOUN
ajst-21789	33	5	of	of	ADP
ajst-21789	33	6	gas	gas	NOUN
ajst-21789	33	7	emission	emission	NOUN
ajst-21789	33	8	quantity	quantity	NOUN
ajst-21789	33	9	the	the	DET
ajst-21789	33	10	approved	approve	VERB
ajst-21789	33	11	production	production	NOUN
ajst-21789	33	12	capacity	capacity	NOUN
ajst-21789	33	13	of	of	ADP
ajst-21789	33	14	zhongtai	zhongtai	NOUN
ajst-21789	33	15	mining	mining	NOUN
ajst-21789	33	16	mine	mine	NOUN
ajst-21789	33	17	is	be	AUX
ajst-21789	33	18	1.5	1.5	NUM
ajst-21789	33	19	million	million	NUM
ajst-21789	33	20	tons	ton	NOUN
ajst-21789	33	21	/	/	SYM
ajst-21789	33	22	year	year	NOUN
ajst-21789	33	23	.	.	PUNCT
ajst-21789	34	1	it	it	PRON
ajst-21789	34	2	adopts	adopt	VERB
ajst-21789	34	3	underground	underground	ADJ
ajst-21789	34	4	mining	mining	NOUN
ajst-21789	34	5	(	(	PUNCT
ajst-21789	34	6	longwall	longwall	ADJ
ajst-21789	34	7	caving	caving	NOUN
ajst-21789	34	8	and	and	CCONJ
ajst-21789	34	9	falling	fall	VERB
ajst-21789	34	10	mining	mining	NOUN
ajst-21789	34	11	method	method	NOUN
ajst-21789	34	12	)	)	PUNCT
ajst-21789	34	13	,	,	PUNCT
ajst-21789	34	14	multi	multi	ADJ
ajst-21789	34	15	-	-	ADJ
ajst-21789	34	16	level	level	ADJ
ajst-21789	34	17	down	down	ADP
ajst-21789	34	18	-	-	PUNCT
ajst-21789	34	19	hill	hill	NOUN
ajst-21789	34	20	development	development	NOUN
ajst-21789	34	21	of	of	ADP
ajst-21789	34	22	vertical	vertical	ADJ
ajst-21789	34	23	shaft	shaft	NOUN
ajst-21789	34	24	and	and	CCONJ
ajst-21789	34	25	multi	multi	ADJ
ajst-21789	34	26	-	-	ADJ
ajst-21789	34	27	level	level	ADJ
ajst-21789	34	28	down	down	ADP
ajst-21789	34	29	-	-	PUNCT
ajst-21789	34	30	hill	hill	NOUN
ajst-21789	34	31	mining	mining	NOUN
ajst-21789	34	32	of	of	ADP
ajst-21789	34	33	permian	permian	PROPN
ajst-21789	34	34	shanxi	shanxi	PROPN
ajst-21789	34	35	formation	formation	PROPN
ajst-21789	34	36	21	21	NUM
ajst-21789	34	37	coal	coal	NOUN
ajst-21789	34	38	seam	seam	NOUN
ajst-21789	34	39	.	.	PUNCT
ajst-21789	35	1	there	there	PRON
ajst-21789	35	2	are	be	VERB
ajst-21789	35	3	5	5	NUM
ajst-21789	35	4	vertical	vertical	ADJ
ajst-21789	35	5	shafts	shafts	ADJ
ajst-21789	35	6	and	and	CCONJ
ajst-21789	35	7	shafts	shafts	ADJ
ajst-21789	35	8	,	,	PUNCT
ajst-21789	35	9	and	and	CCONJ
ajst-21789	35	10	the	the	DET
ajst-21789	35	11	ventilation	ventilation	NOUN
ajst-21789	35	12	method	method	NOUN
ajst-21789	35	13	of	of	ADP
ajst-21789	35	14	mine	mine	NOUN
ajst-21789	35	15	is	be	AUX
ajst-21789	35	16	mixed	mixed	ADJ
ajst-21789	35	17	type	type	NOUN
ajst-21789	35	18	and	and	CCONJ
ajst-21789	35	19	extraction	extraction	NOUN
ajst-21789	35	20	type	type	NOUN
ajst-21789	35	21	.	.	PUNCT
ajst-21789	36	1	the	the	DET
ajst-21789	36	2	ventilation	ventilation	NOUN
ajst-21789	36	3	system	system	NOUN
ajst-21789	36	4	of	of	ADP
ajst-21789	36	5	the	the	DET
ajst-21789	36	6	mine	mine	NOUN
ajst-21789	36	7	is	be	AUX
ajst-21789	36	8	regionalized	regionalize	VERB
ajst-21789	36	9	,	,	PUNCT
ajst-21789	36	10	and	and	CCONJ
ajst-21789	36	11	the	the	DET
ajst-21789	36	12	gas	gas	NOUN
ajst-21789	36	13	grade	grade	NOUN
ajst-21789	36	14	evaluation	evaluation	NOUN
ajst-21789	36	15	of	of	ADP
ajst-21789	36	16	the	the	DET
ajst-21789	36	17	mine	mine	NOUN
ajst-21789	36	18	from	from	ADP
ajst-21789	36	19	2017	2017	NUM
ajst-21789	36	20	to	to	ADP
ajst-21789	36	21	2022	2022	NUM
ajst-21789	36	22	is	be	AUX
ajst-21789	36	23	all	all	DET
ajst-21789	36	24	outburst	outburst	NOUN
ajst-21789	36	25	mine	mine	NOUN
ajst-21789	36	26	.	.	PUNCT
ajst-21789	37	1	based	base	VERB
ajst-21789	37	2	on	on	ADP
ajst-21789	37	3	the	the	DET
ajst-21789	37	4	field	field	NOUN
ajst-21789	37	5	investigation	investigation	NOUN
ajst-21789	37	6	of	of	ADP
ajst-21789	37	7	gas	gas	NOUN
ajst-21789	37	8	emission	emission	NOUN
ajst-21789	37	9	in	in	ADP
ajst-21789	37	10	ⅱ1	ⅱ1	NOUN
ajst-21789	37	11	coal	coal	NOUN
ajst-21789	37	12	seam	seam	NOUN
ajst-21789	37	13	of	of	ADP
ajst-21789	37	14	zhongtai	zhongtai	PROPN
ajst-21789	37	15	mining	mining	NOUN
ajst-21789	37	16	,	,	PUNCT
ajst-21789	37	17	the	the	DET
ajst-21789	37	18	influencing	influence	VERB
ajst-21789	37	19	factors	factor	NOUN
ajst-21789	37	20	of	of	ADP
ajst-21789	37	21	gas	gas	NOUN
ajst-21789	37	22	emission	emission	NOUN
ajst-21789	37	23	are	be	AUX
ajst-21789	37	24	selected	select	VERB
ajst-21789	37	25	from	from	ADP
ajst-21789	37	26	geological	geological	ADJ
ajst-21789	37	27	factors	factor	NOUN
ajst-21789	37	28	and	and	CCONJ
ajst-21789	37	29	mining	mining	NOUN
ajst-21789	37	30	factors	factor	NOUN
ajst-21789	37	31	[	[	X
ajst-21789	37	32	16	16	NUM
ajst-21789	37	33	,	,	PUNCT
ajst-21789	37	34	17]：x1	17]：x1	NUM
ajst-21789	37	35	promotion	promotion	NOUN
ajst-21789	37	36	degree	degree	NOUN
ajst-21789	37	37	,	,	PUNCT
ajst-21789	37	38	x2	x2	PROPN
ajst-21789	37	39	recovery	recovery	NOUN
ajst-21789	37	40	rate	rate	NOUN
ajst-21789	37	41	,	,	PUNCT
ajst-21789	37	42	x3	x3	ADJ
ajst-21789	37	43	coal	coal	NOUN
ajst-21789	37	44	thickness	thickness	NOUN
ajst-21789	37	45	,	,	PUNCT
ajst-21789	37	46	x4	x4	ADJ
ajst-21789	37	47	burial	burial	NOUN
ajst-21789	37	48	depth	depth	NOUN
ajst-21789	37	49	,	,	PUNCT
ajst-21789	37	50	x5	x5	NOUN
ajst-21789	37	51	mining	mining	NOUN
ajst-21789	37	52	height	height	NOUN
ajst-21789	37	53	,	,	PUNCT
ajst-21789	37	54	x6	x6	NOUN
ajst-21789	37	55	temperature	temperature	NOUN
ajst-21789	37	56	,	,	PUNCT
ajst-21789	37	57	x7	x7	VERB
ajst-21789	37	58	underground	underground	ADJ
ajst-21789	37	59	pressure	pressure	NOUN
ajst-21789	37	60	,	,	PUNCT
ajst-21789	37	61	x8	x8	PROPN
ajst-21789	37	62	adjacent	adjacent	ADJ
ajst-21789	37	63	coal	coal	NOUN
ajst-21789	37	64	seam	seam	NOUN
ajst-21789	37	65	spacing	spacing	NOUN
ajst-21789	37	66	,	,	PUNCT
ajst-21789	37	67	x9	x9	PROPN
ajst-21789	37	68	air	air	NOUN
ajst-21789	37	69	volume	volume	NOUN
ajst-21789	37	70	,	,	PUNCT
ajst-21789	37	71	x10	x10	PRON
ajst-21789	37	72	daily	daily	ADJ
ajst-21789	37	73	production	production	NOUN
ajst-21789	37	74	,	,	PUNCT
ajst-21789	37	75	x11	x11	PROPN
ajst-21789	37	76	coal	coal	NOUN
ajst-21789	37	77	seam	seam	NOUN
ajst-21789	37	78	inclination	inclination	NOUN
ajst-21789	37	79	,	,	PUNCT
ajst-21789	37	80	x12	x12	NUM
ajst-21789	37	81	adjacent	adjacent	ADJ
ajst-21789	37	82	layer	layer	NOUN
ajst-21789	37	83	gas	gas	NOUN
ajst-21789	37	84	content	content	NOUN
ajst-21789	37	85	and	and	CCONJ
ajst-21789	37	86	x13	x13	PROPN
ajst-21789	37	87	mining	mining	NOUN
ajst-21789	37	88	coal	coal	NOUN
ajst-21789	37	89	seam	seam	NOUN
ajst-21789	37	90	gas	gas	NOUN
ajst-21789	37	91	content	content	NOUN
ajst-21789	37	92	,	,	PUNCT
ajst-21789	37	93	the	the	DET
ajst-21789	37	94	prediction	prediction	NOUN
ajst-21789	37	95	work	work	NOUN
ajst-21789	37	96	of	of	ADP
ajst-21789	37	97	gas	gas	NOUN
ajst-21789	37	98	emission	emission	NOUN
ajst-21789	37	99	y	y	PROPN
ajst-21789	37	100	of	of	ADP
ajst-21789	37	101	zhongtai	zhongtai	NOUN
ajst-21789	37	102	mining	mining	NOUN
ajst-21789	37	103	industry	industry	NOUN
ajst-21789	37	104	is	be	AUX
ajst-21789	37	105	studied	study	VERB
ajst-21789	37	106	.	.	PUNCT
ajst-21789	38	1	the	the	DET
ajst-21789	38	2	original	original	ADJ
ajst-21789	38	3	data	datum	NOUN
ajst-21789	38	4	are	be	AUX
ajst-21789	38	5	shown	show	VERB
ajst-21789	38	6	in	in	ADP
ajst-21789	38	7	table	table	NOUN
ajst-21789	38	8	1	1	NUM
ajst-21789	38	9	:	:	PUNCT
ajst-21789	38	10	table	table	NOUN
ajst-21789	38	11	1	1	NUM
ajst-21789	38	12	.	.	PUNCT
ajst-21789	39	1	data	datum	NOUN
ajst-21789	39	2	of	of	ADP
ajst-21789	39	3	influencing	influence	VERB
ajst-21789	39	4	factors	factor	NOUN
ajst-21789	39	5	of	of	ADP
ajst-21789	39	6	gas	gas	NOUN
ajst-21789	39	7	emission	emission	NOUN
ajst-21789	39	8	group	group	NOUN
ajst-21789	39	9	x1/	x1/	PROPN
ajst-21789	39	10	（	（	PUNCT
ajst-21789	39	11	m	m	PROPN
ajst-21789	39	12	/	/	SYM
ajst-21789	39	13	d	d	PROPN
ajst-21789	39	14	）	）	PUNCT
ajst-21789	39	15	x2/	x2/	PROPN
ajst-21789	40	1	%	%	INTJ
ajst-21789	40	2	x3/	x3/	PROPN
ajst-21789	41	1	m	m	PROPN
ajst-21789	41	2	x4/	x4/	PROPN
ajst-21789	41	3	m	m	VERB
ajst-21789	41	4	x5/	x5/	PROPN
ajst-21789	41	5	m	m	PROPN
ajst-21789	41	6	x6/	x6/	PUNCT
ajst-21789	42	1	℃	℃	PROPN
ajst-21789	42	2	x7/	x7/	PROPN
ajst-21789	42	3	kpa	kpa	PROPN
ajst-21789	42	4	x8/	x8/	PROPN
ajst-21789	42	5	m	m	VERB
ajst-21789	42	6	x9/	x9/	PRON
ajst-21789	42	7	（	（	PUNCT
ajst-21789	42	8	m3	m3	PROPN
ajst-21789	42	9	/	/	SYM
ajst-21789	42	10	min	min	PROPN
ajst-21789	42	11	）	）	PROPN
ajst-21789	42	12	x10/	x10/	PROPN
ajst-21789	43	1	（	（	PROPN
ajst-21789	43	2	t	t	PROPN
ajst-21789	43	3	/	/	SYM
ajst-21789	43	4	d	d	PROPN
ajst-21789	43	5	）	）	PROPN
ajst-21789	43	6	x11/	x11/	PROPN
ajst-21789	44	1	°	°	NUM
ajst-21789	44	2	x12/	x12/	X
ajst-21789	45	1	（	（	PUNCT
ajst-21789	45	2	m3	m3	PROPN
ajst-21789	45	3	/	/	SYM
ajst-21789	45	4	t	t	PROPN
ajst-21789	45	5	）	）	PROPN
ajst-21789	45	6	x13/	x13/	PROPN
ajst-21789	46	1	（	（	PUNCT
ajst-21789	46	2	m3	m3	PROPN
ajst-21789	46	3	/	/	SYM
ajst-21789	46	4	t	t	PROPN
ajst-21789	46	5	）	）	PROPN
ajst-21789	46	6	1	1	NUM
ajst-21789	46	7	4	4	NUM
ajst-21789	46	8	84.5	84.5	NUM
ajst-21789	46	9	5.85	5.85	NUM
ajst-21789	46	10	625.17	625.17	NUM
ajst-21789	46	11	3	3	NUM
ajst-21789	46	12	19	19	NUM
ajst-21789	46	13	87.26	87.26	NUM
ajst-21789	46	14	3	3	NUM
ajst-21789	46	15	1000	1000	NUM
ajst-21789	46	16	3591	3591	NUM
ajst-21789	46	17	8	8	NUM
ajst-21789	46	18	5.2	5.2	NUM
ajst-21789	46	19	4.93	4.93	NUM
ajst-21789	46	20	2	2	NUM
ajst-21789	46	21	4.3	4.3	NUM
ajst-21789	46	22	85.7	85.7	NUM
ajst-21789	46	23	8.87	8.87	NUM
ajst-21789	46	24	640.01	640.01	NUM
ajst-21789	46	25	3	3	NUM
ajst-21789	46	26	20	20	NUM
ajst-21789	46	27	87.14	87.14	NUM
ajst-21789	46	28	4	4	NUM
ajst-21789	46	29	1008	1008	NUM
ajst-21789	46	30	3857	3857	NUM
ajst-21789	46	31	9	9	NUM
ajst-21789	46	32	5.63	5.63	NUM
ajst-21789	46	33	4.98	4.98	NUM
ajst-21789	46	34	30	30	NUM
ajst-21789	46	35	3	3	NUM
ajst-21789	46	36	84.7	84.7	NUM
ajst-21789	46	37	5.04	5.04	NUM
ajst-21789	46	38	636.17	636.17	NUM
ajst-21789	46	39	3	3	NUM
ajst-21789	46	40	21	21	NUM
ajst-21789	46	41	86.95	86.95	NUM
ajst-21789	46	42	4.3	4.3	NUM
ajst-21789	46	43	967	967	NUM
ajst-21789	46	44	2856	2856	NUM
ajst-21789	46	45	9	9	NUM
ajst-21789	46	46	5.41	5.41	NUM
ajst-21789	46	47	4.72	4.72	NUM
ajst-21789	46	48	2.2	2.2	NUM
ajst-21789	46	49	.	.	PUNCT
ajst-21789	47	1	spearman	spearman	NOUN
ajst-21789	47	2	correlation	correlation	NOUN
ajst-21789	47	3	coefficient	coefficient	NOUN
ajst-21789	47	4	improved	improve	VERB
ajst-21789	47	5	principal	principal	ADJ
ajst-21789	47	6	component	component	NOUN
ajst-21789	47	7	analysis	analysis	NOUN
ajst-21789	47	8	(	(	PUNCT
ajst-21789	47	9	pca	pca	NOUN
ajst-21789	47	10	)	)	PUNCT
ajst-21789	47	11	as	as	SCONJ
ajst-21789	47	12	principal	principal	ADJ
ajst-21789	47	13	component	component	NOUN
ajst-21789	47	14	analysis	analysis	NOUN
ajst-21789	47	15	(	(	PUNCT
ajst-21789	47	16	pca	pca	NOUN
ajst-21789	47	17	)	)	PUNCT
ajst-21789	47	18	treats	treat	VERB
ajst-21789	47	19	each	each	DET
ajst-21789	47	20	influencing	influence	VERB
ajst-21789	47	21	factor	factor	NOUN
ajst-21789	47	22	equally	equally	ADV
ajst-21789	47	23	in	in	ADP
ajst-21789	47	24	the	the	DET
ajst-21789	47	25	process	process	NOUN
ajst-21789	47	26	of	of	ADP
ajst-21789	47	27	data	datum	NOUN
ajst-21789	47	28	processing	processing	NOUN
ajst-21789	47	29	,	,	PUNCT
ajst-21789	47	30	the	the	DET
ajst-21789	47	31	impact	impact	NOUN
ajst-21789	47	32	of	of	ADP
ajst-21789	47	33	the	the	DET
ajst-21789	47	34	influencing	influence	VERB
ajst-21789	47	35	factor	factor	NOUN
ajst-21789	47	36	that	that	PRON
ajst-21789	47	37	is	be	AUX
ajst-21789	47	38	not	not	PART
ajst-21789	47	39	strongly	strongly	ADV
ajst-21789	47	40	correlated	correlate	VERB
ajst-21789	47	41	with	with	ADP
ajst-21789	47	42	the	the	DET
ajst-21789	47	43	target	target	NOUN
ajst-21789	47	44	variable	variable	NOUN
ajst-21789	47	45	becomes	become	VERB
ajst-21789	47	46	greater	great	ADJ
ajst-21789	47	47	after	after	ADP
ajst-21789	47	48	dimensionality	dimensionality	NOUN
ajst-21789	47	49	reduction	reduction	NOUN
ajst-21789	47	50	.	.	PUNCT
ajst-21789	48	1	in	in	ADP
ajst-21789	48	2	order	order	NOUN
ajst-21789	48	3	to	to	PART
ajst-21789	48	4	reduce	reduce	VERB
ajst-21789	48	5	this	this	DET
ajst-21789	48	6	impact	impact	NOUN
ajst-21789	48	7	,	,	PUNCT
ajst-21789	48	8	spearman	spearman	NOUN
ajst-21789	48	9	correlation	correlation	NOUN
ajst-21789	48	10	coefficient	coefficient	NOUN
ajst-21789	48	11	is	be	AUX
ajst-21789	48	12	used	use	VERB
ajst-21789	48	13	to	to	PART
ajst-21789	48	14	assign	assign	VERB
ajst-21789	48	15	weight	weight	NOUN
ajst-21789	48	16	to	to	ADP
ajst-21789	48	17	each	each	DET
ajst-21789	48	18	influencing	influence	VERB
ajst-21789	48	19	factor	factor	NOUN
ajst-21789	48	20	.	.	PUNCT
ajst-21789	49	1	if	if	SCONJ
ajst-21789	49	2	the	the	DET
ajst-21789	49	3	influencing	influence	VERB
ajst-21789	49	4	factor	factor	NOUN
ajst-21789	49	5	is	be	AUX
ajst-21789	49	6	strongly	strongly	ADV
ajst-21789	49	7	correlated	correlate	VERB
ajst-21789	49	8	with	with	ADP
ajst-21789	49	9	the	the	DET
ajst-21789	49	10	target	target	NOUN
ajst-21789	49	11	variable	variable	NOUN
ajst-21789	49	12	,	,	PUNCT
ajst-21789	49	13	the	the	DET
ajst-21789	49	14	weight	weight	NOUN
ajst-21789	49	15	is	be	AUX
ajst-21789	49	16	significant	significant	ADJ
ajst-21789	49	17	.	.	PUNCT
ajst-21789	50	1	small	small	ADJ
ajst-21789	50	2	weight	weight	NOUN
ajst-21789	50	3	,	,	PUNCT
ajst-21789	50	4	this	this	DET
ajst-21789	50	5	method	method	NOUN
ajst-21789	50	6	has	have	VERB
ajst-21789	50	7	no	no	DET
ajst-21789	50	8	specific	specific	ADJ
ajst-21789	50	9	requirements	requirement	NOUN
ajst-21789	50	10	on	on	ADP
ajst-21789	50	11	the	the	DET
ajst-21789	50	12	distribution	distribution	NOUN
ajst-21789	50	13	of	of	ADP
ajst-21789	50	14	variables	variable	NOUN
ajst-21789	50	15	,	,	PUNCT
ajst-21789	50	16	can	can	AUX
ajst-21789	50	17	be	be	AUX
ajst-21789	50	18	applied	apply	VERB
ajst-21789	50	19	to	to	ADP
ajst-21789	50	20	small	small	ADJ
ajst-21789	50	21	samples	sample	NOUN
ajst-21789	50	22	(	(	PUNCT
ajst-21789	50	23	sample	sample	NOUN
ajst-21789	50	24	size	size	NOUN
ajst-21789	50	25	does	do	AUX
ajst-21789	50	26	not	not	PART
ajst-21789	50	27	exceed	exceed	VERB
ajst-21789	50	28	30	30	NUM
ajst-21789	50	29	)	)	PUNCT
ajst-21789	50	30	and	and	CCONJ
ajst-21789	50	31	large	large	ADJ
ajst-21789	50	32	sample	sample	NOUN
ajst-21789	50	33	range	range	NOUN
ajst-21789	50	34	.	.	PUNCT
ajst-21789	51	1	2.2.1	2.2.1	X
ajst-21789	51	2	.	.	PUNCT
ajst-21789	51	3	spearman	spearman	NOUN
ajst-21789	51	4	correlation	correlation	NOUN
ajst-21789	51	5	coefficient	coefficient	NOUN
ajst-21789	51	6	spearman	spearman	NOUN
ajst-21789	51	7	's	's	PART
ajst-21789	51	8	correlation	correlation	NOUN
ajst-21789	51	9	coefficient	coefficient	NOUN
ajst-21789	51	10	calculation	calculation	NOUN
ajst-21789	51	11	method	method	NOUN
ajst-21789	51	12	first	first	ADJ
ajst-21789	51	13	arranges	arrange	NOUN
ajst-21789	51	14	n	n	DET
ajst-21789	51	15	samples	sample	NOUN
ajst-21789	51	16	according	accord	VERB
ajst-21789	51	17	to	to	ADP
ajst-21789	51	18	the	the	DET
ajst-21789	51	19	value	value	NOUN
ajst-21789	51	20	size	size	NOUN
ajst-21789	51	21	of	of	ADP
ajst-21789	51	22	the	the	DET
ajst-21789	51	23	impact	impact	NOUN
ajst-21789	51	24	factor	factor	NOUN
ajst-21789	51	25	from	from	ADP
ajst-21789	51	26	small	small	ADJ
ajst-21789	51	27	to	to	AUX
ajst-21789	51	28	large	large	ADJ
ajst-21789	51	29	,	,	PUNCT
ajst-21789	51	30	and	and	CCONJ
ajst-21789	51	31	then	then	ADV
ajst-21789	51	32	arranges	arrange	VERB
ajst-21789	51	33	the	the	DET
ajst-21789	51	34	target	target	NOUN
ajst-21789	51	35	variables	variable	NOUN
ajst-21789	51	36	in	in	ADP
ajst-21789	51	37	the	the	DET
ajst-21789	51	38	same	same	ADJ
ajst-21789	51	39	way	way	NOUN
ajst-21789	51	40	,	,	PUNCT
ajst-21789	51	41	which	which	PRON
ajst-21789	51	42	can	can	AUX
ajst-21789	51	43	be	be	AUX
ajst-21789	51	44	evaluated	evaluate	VERB
ajst-21789	51	45	by	by	ADP
ajst-21789	51	46	substituting	substitute	VERB
ajst-21789	51	47	them	they	PRON
ajst-21789	51	48	into	into	ADP
ajst-21789	51	49	formula	formula	NOUN
ajst-21789	51	50	(	(	PUNCT
ajst-21789	51	51	1	1	NUM
ajst-21789	51	52	):	):	PUNCT
ajst-21789	51	53	(	(	PUNCT
ajst-21789	51	54	1	1	X
ajst-21789	51	55	)	)	PUNCT
ajst-21789	51	56	where	where	SCONJ
ajst-21789	51	57	:	:	PUNCT
ajst-21789	51	58	represents	represent	VERB
ajst-21789	51	59	the	the	DET
ajst-21789	51	60	correlation	correlation	NOUN
ajst-21789	51	61	between	between	ADP
ajst-21789	51	62	the	the	DET
ajst-21789	51	63	feature	feature	NOUN
ajst-21789	51	64	variable	variable	NOUN
ajst-21789	51	65	and	and	CCONJ
ajst-21789	51	66	the	the	DET
ajst-21789	51	67	target	target	NOUN
ajst-21789	51	68	variable	variable	NOUN
ajst-21789	51	69	,	,	PUNCT
ajst-21789	51	70	and	and	CCONJ
ajst-21789	51	71	the	the	PRON
ajst-21789	51	72	larger	large	ADJ
ajst-21789	51	73	the	the	DET
ajst-21789	51	74	correlation	correlation	NOUN
ajst-21789	51	75	,	,	PUNCT
ajst-21789	51	76	the	the	PRON
ajst-21789	51	77	stronger	strong	ADJ
ajst-21789	51	78	the	the	DET
ajst-21789	51	79	correlation	correlation	NOUN
ajst-21789	51	80	;	;	PUNCT
ajst-21789	51	81	n	n	PRON
ajst-21789	51	82	represents	represent	VERB
ajst-21789	51	83	the	the	DET
ajst-21789	51	84	number	number	NOUN
ajst-21789	51	85	of	of	ADP
ajst-21789	51	86	samples	sample	NOUN
ajst-21789	51	87	;	;	PUNCT
ajst-21789	51	88	represents	represent	VERB
ajst-21789	51	89	the	the	DET
ajst-21789	51	90	ranking	ranking	ADJ
ajst-21789	51	91	difference	difference	NOUN
ajst-21789	51	92	between	between	ADP
ajst-21789	51	93	the	the	DET
ajst-21789	51	94	feature	feature	NOUN
ajst-21789	51	95	variable	variable	NOUN
ajst-21789	51	96	and	and	CCONJ
ajst-21789	51	97	the	the	DET
ajst-21789	51	98	target	target	NOUN
ajst-21789	51	99	variable	variable	NOUN
ajst-21789	51	100	.	.	PUNCT
ajst-21789	52	1	2.2.2	2.2.2	X
ajst-21789	52	2	.	.	X
ajst-21789	52	3	improvement	improvement	NOUN
ajst-21789	52	4	step	step	VERB
ajst-21789	52	5	the	the	DET
ajst-21789	52	6	main	main	ADJ
ajst-21789	52	7	steps	step	NOUN
ajst-21789	52	8	of	of	ADP
ajst-21789	52	9	spearman	spearman	NOUN
ajst-21789	52	10	correlation	correlation	NOUN
ajst-21789	52	11	coefficient	coefficient	NOUN
ajst-21789	52	12	to	to	PART
ajst-21789	52	13	improve	improve	VERB
ajst-21789	52	14	pca	pca	PROPN
ajst-21789	52	15	are	be	AUX
ajst-21789	52	16	as	as	SCONJ
ajst-21789	52	17	follows	follow	VERB
ajst-21789	52	18	:	:	PUNCT
ajst-21789	52	19	step	step	NOUN
ajst-21789	52	20	1	1	NUM
ajst-21789	52	21	:	:	PUNCT
ajst-21789	52	22	select	select	VERB
ajst-21789	52	23	the	the	DET
ajst-21789	52	24	original	original	ADJ
ajst-21789	52	25	sample	sample	NOUN
ajst-21789	52	26	matrix	matrix	NOUN
ajst-21789	52	27	，	，	PROPN
ajst-21789	52	28	where	where	SCONJ
ajst-21789	52	29	n	n	PRON
ajst-21789	52	30	represents	represent	VERB
ajst-21789	52	31	the	the	DET
ajst-21789	52	32	number	number	NOUN
ajst-21789	52	33	of	of	ADP
ajst-21789	52	34	samples	sample	NOUN
ajst-21789	52	35	and	and	CCONJ
ajst-21789	52	36	m	m	VERB
ajst-21789	52	37	represents	represent	VERB
ajst-21789	52	38	the	the	DET
ajst-21789	52	39	number	number	NOUN
ajst-21789	52	40	of	of	ADP
ajst-21789	52	41	impact	impact	NOUN
ajst-21789	52	42	factor	factor	NOUN
ajst-21789	52	43	variables	variable	NOUN
ajst-21789	52	44	.	.	PUNCT
ajst-21789	53	1	step	step	NOUN
ajst-21789	53	2	2	2	NUM
ajst-21789	53	3	:	:	PUNCT
ajst-21789	53	4	spearman	spearman	NOUN
ajst-21789	53	5	correlation	correlation	NOUN
ajst-21789	53	6	coefficient	coefficient	NOUN
ajst-21789	53	7	is	be	AUX
ajst-21789	53	8	calculated	calculate	VERB
ajst-21789	53	9	between	between	ADP
ajst-21789	53	10	each	each	DET
ajst-21789	53	11	impact	impact	NOUN
ajst-21789	53	12	factor	factor	NOUN
ajst-21789	53	13	variable	variable	NOUN
ajst-21789	53	14	and	and	CCONJ
ajst-21789	53	15	target	target	VERB
ajst-21789	53	16	variable	variable	NOUN
ajst-21789	53	17	,	,	PUNCT
ajst-21789	53	18	and	and	CCONJ
ajst-21789	53	19	the	the	DET
ajst-21789	53	20	diagonal	diagonal	ADJ
ajst-21789	53	21	matrix	matrix	NOUN
ajst-21789	53	22	formed	form	VERB
ajst-21789	53	23	by	by	ADP
ajst-21789	53	24	the	the	DET
ajst-21789	53	25	calculation	calculation	NOUN
ajst-21789	53	26	result	result	NOUN
ajst-21789	53	27	is	be	AUX
ajst-21789	53	28	denoted	denote	VERB
ajst-21789	53	29	as	as	ADP
ajst-21789	53	30	,	,	PUNCT
ajst-21789	53	31	as	as	SCONJ
ajst-21789	53	32	follows	follow	VERB
ajst-21789	53	33	:	:	PUNCT
ajst-21789	53	34	(	(	PUNCT
ajst-21789	53	35	2	2	X
ajst-21789	53	36	)	)	PUNCT
ajst-21789	53	37	where	where	SCONJ
ajst-21789	53	38	:	:	PUNCT
ajst-21789	53	39	is	be	AUX
ajst-21789	53	40	the	the	DET
ajst-21789	53	41	spearman	spearman	NOUN
ajst-21789	53	42	correlation	correlation	NOUN
ajst-21789	53	43	coefficient	coefficient	NOUN
ajst-21789	53	44	between	between	ADP
ajst-21789	53	45	199	199	NUM
ajst-21789	53	46	the	the	DET
ajst-21789	53	47	impact	impact	NOUN
ajst-21789	53	48	factor	factor	NOUN
ajst-21789	53	49	and	and	CCONJ
ajst-21789	53	50	the	the	DET
ajst-21789	53	51	target	target	NOUN
ajst-21789	53	52	variable	variable	NOUN
ajst-21789	53	53	.	.	PUNCT
ajst-21789	54	1	step	step	VERB
ajst-21789	54	2	3	3	NUM
ajst-21789	54	3	:	:	PUNCT
ajst-21789	54	4	the	the	DET
ajst-21789	54	5	original	original	ADJ
ajst-21789	54	6	sample	sample	NOUN
ajst-21789	54	7	matrix	matrix	NOUN
ajst-21789	54	8	is	be	AUX
ajst-21789	54	9	normalized	normalize	VERB
ajst-21789	54	10	(	(	PUNCT
ajst-21789	54	11	de	de	ADJ
ajst-21789	54	12	-	-	ADJ
ajst-21789	54	13	dimensional	dimensional	ADJ
ajst-21789	54	14	)	)	PUNCT
ajst-21789	54	15	according	accord	VERB
ajst-21789	54	16	to	to	ADP
ajst-21789	54	17	formula	formula	NOUN
ajst-21789	54	18	(	(	PUNCT
ajst-21789	54	19	3	3	NUM
ajst-21789	54	20	)	)	PUNCT
ajst-21789	54	21	to	to	PART
ajst-21789	54	22	obtain	obtain	VERB
ajst-21789	54	23	the	the	DET
ajst-21789	54	24	matrix	matrix	NOUN
ajst-21789	54	25	.	.	PUNCT
ajst-21789	54	26	.	.	PUNCT
ajst-21789	55	1	(	(	PUNCT
ajst-21789	55	2	3	3	X
ajst-21789	55	3	)	)	PUNCT
ajst-21789	55	4	step	step	NOUN
ajst-21789	55	5	4	4	NUM
ajst-21789	55	6	:	:	PUNCT
ajst-21789	55	7	multiply	multiply	VERB
ajst-21789	55	8	the	the	DET
ajst-21789	55	9	normalized	normalize	VERB
ajst-21789	55	10	matrix	matrix	NOUN
ajst-21789	55	11	with	with	ADP
ajst-21789	55	12	the	the	DET
ajst-21789	55	13	diagonal	diagonal	ADJ
ajst-21789	55	14	matrix	matrix	NOUN
ajst-21789	55	15	of	of	ADP
ajst-21789	55	16	spearman	spearman	NOUN
ajst-21789	55	17	correlation	correlation	NOUN
ajst-21789	55	18	coefficient	coefficient	NOUN
ajst-21789	55	19	to	to	PART
ajst-21789	55	20	get	get	VERB
ajst-21789	55	21	the	the	DET
ajst-21789	55	22	improved	improve	VERB
ajst-21789	55	23	pca	pca	NOUN
ajst-21789	55	24	initial	initial	ADJ
ajst-21789	55	25	feature	feature	NOUN
ajst-21789	55	26	variable	variable	ADJ
ajst-21789	55	27	matrix	matrix	NOUN
ajst-21789	55	28	.	.	PUNCT
ajst-21789	56	1	step	step	NOUN
ajst-21789	56	2	5	5	NUM
ajst-21789	56	3	:	:	PUNCT
ajst-21789	56	4	calculate	calculate	VERB
ajst-21789	56	5	the	the	DET
ajst-21789	56	6	covariance	covariance	NOUN
ajst-21789	56	7	matrix	matrix	NOUN
ajst-21789	56	8	of	of	ADP
ajst-21789	56	9	the	the	DET
ajst-21789	56	10	eigenvariable	eigenvariable	ADJ
ajst-21789	56	11	matrix	matrix	NOUN
ajst-21789	56	12	.	.	PUNCT
ajst-21789	57	1	step	step	NOUN
ajst-21789	57	2	6	6	NUM
ajst-21789	57	3	:	:	PUNCT
ajst-21789	57	4	calculate	calculate	VERB
ajst-21789	57	5	the	the	DET
ajst-21789	57	6	eigenvalues	eigenvalue	NOUN
ajst-21789	57	7	and	and	CCONJ
ajst-21789	57	8	eigenvectors	eigenvector	NOUN
ajst-21789	57	9	of	of	ADP
ajst-21789	57	10	the	the	DET
ajst-21789	57	11	covariance	covariance	NOUN
ajst-21789	57	12	matrix	matrix	NOUN
ajst-21789	57	13	..	..	PUNCT
ajst-21789	57	14	step	step	NOUN
ajst-21789	57	15	7	7	NUM
ajst-21789	57	16	:	:	PUNCT
ajst-21789	57	17	calculate	calculate	VERB
ajst-21789	57	18	the	the	DET
ajst-21789	57	19	principal	principal	ADJ
ajst-21789	57	20	component	component	NOUN
ajst-21789	57	21	contribution	contribution	NOUN
ajst-21789	57	22	rate	rate	NOUN
ajst-21789	57	23	of	of	ADP
ajst-21789	57	24	each	each	DET
ajst-21789	57	25	characteristic	characteristic	ADJ
ajst-21789	57	26	variable	variable	NOUN
ajst-21789	57	27	,	,	PUNCT
ajst-21789	57	28	and	and	CCONJ
ajst-21789	57	29	obtain	obtain	VERB
ajst-21789	57	30	the	the	DET
ajst-21789	57	31	final	final	ADJ
ajst-21789	57	32	principal	principal	ADJ
ajst-21789	57	33	component	component	NOUN
ajst-21789	57	34	as	as	ADP
ajst-21789	57	35	the	the	DET
ajst-21789	57	36	prediction	prediction	NOUN
ajst-21789	57	37	index	index	NOUN
ajst-21789	57	38	according	accord	VERB
ajst-21789	57	39	to	to	ADP
ajst-21789	57	40	the	the	DET
ajst-21789	57	41	cumulative	cumulative	ADJ
ajst-21789	57	42	contribution	contribution	NOUN
ajst-21789	57	43	rate	rate	NOUN
ajst-21789	57	44	greater	great	ADJ
ajst-21789	57	45	than	than	ADP
ajst-21789	57	46	or	or	CCONJ
ajst-21789	57	47	equal	equal	ADJ
ajst-21789	57	48	to	to	ADP
ajst-21789	57	49	95	95	NUM
ajst-21789	57	50	%	%	NOUN
ajst-21789	57	51	.	.	PUNCT
ajst-21789	58	1	2.3	2.3	NUM
ajst-21789	58	2	.	.	PUNCT
ajst-21789	59	1	comparison	comparison	NOUN
ajst-21789	59	2	of	of	ADP
ajst-21789	59	3	data	datum	NOUN
ajst-21789	59	4	dimensionality	dimensionality	NOUN
ajst-21789	59	5	reduction	reduction	NOUN
ajst-21789	59	6	before	before	ADP
ajst-21789	59	7	and	and	CCONJ
ajst-21789	59	8	after	after	ADP
ajst-21789	59	9	improvement	improvement	NOUN
ajst-21789	59	10	13	13	NUM
ajst-21789	59	11	principal	principal	ADJ
ajst-21789	59	12	components	component	NOUN
ajst-21789	59	13	were	be	AUX
ajst-21789	59	14	obtained	obtain	VERB
ajst-21789	59	15	by	by	ADP
ajst-21789	59	16	principal	principal	ADJ
ajst-21789	59	17	component	component	NOUN
ajst-21789	59	18	analysis	analysis	NOUN
ajst-21789	59	19	(	(	PUNCT
ajst-21789	59	20	pca	pca	NOUN
ajst-21789	59	21	)	)	PUNCT
ajst-21789	59	22	and	and	CCONJ
ajst-21789	59	23	improved	improve	VERB
ajst-21789	59	24	principal	principal	ADJ
ajst-21789	59	25	component	component	NOUN
ajst-21789	59	26	analysis	analysis	NOUN
ajst-21789	59	27	(	(	PUNCT
ajst-21789	59	28	ipca	ipca	PROPN
ajst-21789	59	29	)	)	PUNCT
ajst-21789	59	30	after	after	ADP
ajst-21789	59	31	dimensionality	dimensionality	NOUN
ajst-21789	59	32	reduction	reduction	NOUN
ajst-21789	59	33	.	.	PUNCT
ajst-21789	60	1	the	the	DET
ajst-21789	60	2	results	result	NOUN
ajst-21789	60	3	are	be	AUX
ajst-21789	60	4	shown	show	VERB
ajst-21789	60	5	in	in	ADP
ajst-21789	60	6	table	table	NOUN
ajst-21789	60	7	2	2	NUM
ajst-21789	60	8	and	and	CCONJ
ajst-21789	60	9	figure	figure	VERB
ajst-21789	60	10	1	1	NUM
ajst-21789	60	11	table	table	NOUN
ajst-21789	60	12	2	2	NUM
ajst-21789	60	13	.	.	PUNCT
ajst-21789	60	14	changes	change	NOUN
ajst-21789	60	15	in	in	ADP
ajst-21789	60	16	the	the	DET
ajst-21789	60	17	contribution	contribution	NOUN
ajst-21789	60	18	rate	rate	NOUN
ajst-21789	60	19	of	of	ADP
ajst-21789	60	20	principal	principal	ADJ
ajst-21789	60	21	component	component	NOUN
ajst-21789	60	22	analysis	analysis	NOUN
ajst-21789	60	23	before	before	ADV
ajst-21789	60	24	and	and	CCONJ
ajst-21789	60	25	after	after	ADP
ajst-21789	60	26	improvement	improvement	NOUN
ajst-21789	60	27	principal	principal	ADJ
ajst-21789	60	28	component	component	NOUN
ajst-21789	60	29	pca	pca	PROPN
ajst-21789	60	30	ipca	ipca	PROPN
ajst-21789	60	31	contribution	contribution	NOUN
ajst-21789	60	32	contribution	contribution	NOUN
ajst-21789	60	33	(	(	PUNCT
ajst-21789	60	34	%	%	INTJ
ajst-21789	60	35	)	)	PUNCT
ajst-21789	60	36	cumulative	cumulative	ADJ
ajst-21789	60	37	contribution	contribution	NOUN
ajst-21789	60	38	rate	rate	NOUN
ajst-21789	60	39	(	(	PUNCT
ajst-21789	60	40	%	%	INTJ
ajst-21789	60	41	)	)	PUNCT
ajst-21789	60	42	contribution	contribution	NOUN
ajst-21789	60	43	contribution	contribution	NOUN
ajst-21789	60	44	(	(	PUNCT
ajst-21789	60	45	%	%	INTJ
ajst-21789	60	46	)	)	PUNCT
ajst-21789	60	47	cumulative	cumulative	ADJ
ajst-21789	60	48	contribution	contribution	NOUN
ajst-21789	60	49	rate	rate	NOUN
ajst-21789	60	50	(	(	PUNCT
ajst-21789	60	51	%	%	INTJ
ajst-21789	60	52	)	)	PUNCT
ajst-21789	60	53	z1	z1	NOUN
ajst-21789	60	54	61.2484	61.2484	NUM
ajst-21789	60	55	61.2484	61.2484	NUM
ajst-21789	60	56	89.6354	89.6354	NUM
ajst-21789	60	57	89.6354	89.6354	NUM
ajst-21789	60	58	z2	z2	PROPN
ajst-21789	60	59	9.7231	9.7231	NUM
ajst-21789	60	60	70.9714	70.9714	NUM
ajst-21789	60	61	3.1107	3.1107	NUM
ajst-21789	60	62	92.7461	92.7461	NUM
ajst-21789	60	63	z3	z3	NOUN
ajst-21789	60	64	8.6822	8.6822	NUM
ajst-21789	60	65	79.6536	79.6536	NUM
ajst-21789	60	66	2.4600	2.4600	NUM
ajst-21789	60	67	95.2060	95.2060	NUM
ajst-21789	60	68	z4	z4	PROPN
ajst-21789	60	69	8.4483	8.4483	NUM
ajst-21789	60	70	88.1019	88.1019	NUM
ajst-21789	60	71	1.6003	1.6003	NUM
ajst-21789	60	72	96.8063	96.8063	NUM
ajst-21789	60	73	z5	z5	PROPN
ajst-21789	60	74	4.5867	4.5867	NUM
ajst-21789	60	75	92.6886	92.6886	NUM
ajst-21789	60	76	0.8557	0.8557	NUM
ajst-21789	60	77	97.6620	97.6620	NUM
ajst-21789	60	78	z6	z6	NOUN
ajst-21789	60	79	4.3779	4.3779	NUM
ajst-21789	60	80	97.0665	97.0665	NUM
ajst-21789	60	81	0.7171	0.7171	NUM
ajst-21789	60	82	98.3791	98.3791	NUM
ajst-21789	60	83	z7	z7	PROPN
ajst-21789	60	84	1.5388	1.5388	NUM
ajst-21789	60	85	98.6053	98.6053	NUM
ajst-21789	60	86	0.5624	0.5624	NUM
ajst-21789	60	87	98.9415	98.9415	NUM
ajst-21789	60	88	z8	z8	NOUN
ajst-21789	60	89	0.8199	0.8199	NUM
ajst-21789	60	90	99.4252	99.4252	NUM
ajst-21789	60	91	0.4102	0.4102	NUM
ajst-21789	60	92	99.3517	99.3517	NUM
ajst-21789	60	93	z9	z9	PROPN
ajst-21789	60	94	0.2569	0.2569	NUM
ajst-21789	60	95	99.6821	99.6821	NUM
ajst-21789	60	96	0.2513	0.2513	NUM
ajst-21789	60	97	99.6030	99.6030	NUM
ajst-21789	60	98	z10	z10	NOUN
ajst-21789	60	99	0.1154	0.1154	NUM
ajst-21789	60	100	99.7975	99.7975	NUM
ajst-21789	60	101	0.1499	0.1499	NUM
ajst-21789	60	102	99.7529	99.7529	NUM
ajst-21789	60	103	z11	z11	NOUN
ajst-21789	60	104	0.0939	0.0939	NUM
ajst-21789	60	105	99.8914	99.8914	NUM
ajst-21789	60	106	0.1316	0.1316	NUM
ajst-21789	60	107	99.8845	99.8845	NUM
ajst-21789	60	108	z12	z12	NUM
ajst-21789	60	109	0.0779	0.0779	NUM
ajst-21789	60	110	99.9694	99.9694	NUM
ajst-21789	60	111	0.0683	0.0683	NUM
ajst-21789	60	112	99.9528	99.9528	NUM
ajst-21789	60	113	z13	z13	NUM
ajst-21789	60	114	0.0306	0.0306	NUM
ajst-21789	60	115	100.0000	100.0000	NUM
ajst-21789	60	116	0.0472	0.0472	NUM
ajst-21789	60	117	100.0000	100.0000	NUM
ajst-21789	60	118	(	(	PUNCT
ajst-21789	60	119	a	a	NOUN
ajst-21789	60	120	)	)	PUNCT
ajst-21789	60	121	(	(	PUNCT
ajst-21789	60	122	b	b	X
ajst-21789	60	123	)	)	PUNCT
ajst-21789	60	124	figure	figure	NOUN
ajst-21789	60	125	1	1	NUM
ajst-21789	60	126	.	.	PUNCT
ajst-21789	60	127	effect	effect	NOUN
ajst-21789	60	128	diagram	diagram	NOUN
ajst-21789	60	129	of	of	ADP
ajst-21789	60	130	principal	principal	ADJ
ajst-21789	60	131	component	component	NOUN
ajst-21789	60	132	analysis	analysis	NOUN
ajst-21789	60	133	before	before	ADV
ajst-21789	60	134	and	and	CCONJ
ajst-21789	60	135	after	after	ADP
ajst-21789	60	136	improvement	improvement	NOUN
ajst-21789	60	137	compared	compare	VERB
ajst-21789	60	138	with	with	ADP
ajst-21789	60	139	the	the	DET
ajst-21789	60	140	effect	effect	NOUN
ajst-21789	60	141	before	before	ADP
ajst-21789	60	142	and	and	CCONJ
ajst-21789	60	143	after	after	ADP
ajst-21789	60	144	the	the	DET
ajst-21789	60	145	improvement	improvement	NOUN
ajst-21789	60	146	of	of	ADP
ajst-21789	60	147	principal	principal	ADJ
ajst-21789	60	148	component	component	NOUN
ajst-21789	60	149	analysis	analysis	NOUN
ajst-21789	60	150	,	,	PUNCT
ajst-21789	60	151	principal	principal	ADJ
ajst-21789	60	152	components	component	NOUN
ajst-21789	60	153	were	be	AUX
ajst-21789	60	154	selected	select	VERB
ajst-21789	60	155	according	accord	VERB
ajst-21789	60	156	to	to	ADP
ajst-21789	60	157	the	the	DET
ajst-21789	60	158	cumulative	cumulative	ADJ
ajst-21789	60	159	principal	principal	ADJ
ajst-21789	60	160	component	component	NOUN
ajst-21789	60	161	was	be	AUX
ajst-21789	60	162	greater	great	ADJ
ajst-21789	60	163	than	than	ADP
ajst-21789	60	164	or	or	CCONJ
ajst-21789	60	165	equal	equal	ADJ
ajst-21789	60	166	to	to	ADP
ajst-21789	60	167	95	95	NUM
ajst-21789	60	168	%	%	NOUN
ajst-21789	60	169	.	.	PUNCT
ajst-21789	61	1	principal	principal	ADJ
ajst-21789	61	2	component	component	NOUN
ajst-21789	61	3	analysis	analysis	NOUN
ajst-21789	61	4	extracted	extract	VERB
ajst-21789	61	5	6	6	NUM
ajst-21789	61	6	principal	principal	ADJ
ajst-21789	61	7	components	component	NOUN
ajst-21789	61	8	with	with	ADP
ajst-21789	61	9	a	a	DET
ajst-21789	61	10	cumulative	cumulative	ADJ
ajst-21789	61	11	contribution	contribution	NOUN
ajst-21789	61	12	rate	rate	NOUN
ajst-21789	61	13	of	of	ADP
ajst-21789	61	14	97.0665	97.0665	NUM
ajst-21789	61	15	%	%	NOUN
ajst-21789	61	16	,	,	PUNCT
ajst-21789	61	17	while	while	SCONJ
ajst-21789	61	18	the	the	DET
ajst-21789	61	19	improved	improve	VERB
ajst-21789	61	20	principal	principal	ADJ
ajst-21789	61	21	component	component	NOUN
ajst-21789	61	22	analysis	analysis	NOUN
ajst-21789	61	23	only	only	ADV
ajst-21789	61	24	needed	need	VERB
ajst-21789	61	25	to	to	PART
ajst-21789	61	26	extract	extract	VERB
ajst-21789	61	27	3	3	NUM
ajst-21789	61	28	principal	principal	ADJ
ajst-21789	61	29	components	component	NOUN
ajst-21789	61	30	with	with	ADP
ajst-21789	61	31	a	a	DET
ajst-21789	61	32	cumulative	cumulative	ADJ
ajst-21789	61	33	contribution	contribution	NOUN
ajst-21789	61	34	rate	rate	NOUN
ajst-21789	61	35	of	of	ADP
ajst-21789	61	36	95.2060	95.2060	NUM
ajst-21789	61	37	%	%	NOUN
ajst-21789	61	38	.	.	PUNCT
ajst-21789	62	1	although	although	SCONJ
ajst-21789	62	2	the	the	DET
ajst-21789	62	3	cumulative	cumulative	ADJ
ajst-21789	62	4	contribution	contribution	NOUN
ajst-21789	62	5	rate	rate	NOUN
ajst-21789	62	6	of	of	ADP
ajst-21789	62	7	pca	pca	NOUN
ajst-21789	62	8	is	be	AUX
ajst-21789	62	9	greater	great	ADJ
ajst-21789	62	10	than	than	ADP
ajst-21789	62	11	that	that	PRON
ajst-21789	62	12	of	of	ADP
ajst-21789	62	13	ipca	ipca	PROPN
ajst-21789	62	14	,	,	PUNCT
ajst-21789	62	15	the	the	DET
ajst-21789	62	16	first	first	ADJ
ajst-21789	62	17	principal	principal	ADJ
ajst-21789	62	18	component	component	NOUN
ajst-21789	62	19	of	of	ADP
ajst-21789	62	20	ipca	ipca	NOUN
ajst-21789	62	21	carries	carry	VERB
ajst-21789	62	22	more	more	ADJ
ajst-21789	62	23	information	information	NOUN
ajst-21789	62	24	.	.	PUNCT
ajst-21789	63	1	while	while	SCONJ
ajst-21789	63	2	the	the	DET
ajst-21789	63	3	cumulative	cumulative	ADJ
ajst-21789	63	4	contribution	contribution	NOUN
ajst-21789	63	5	rate	rate	NOUN
ajst-21789	63	6	is	be	AUX
ajst-21789	63	7	greater	great	ADJ
ajst-21789	63	8	than	than	ADP
ajst-21789	63	9	or	or	CCONJ
ajst-21789	63	10	equal	equal	ADJ
ajst-21789	63	11	to	to	ADP
ajst-21789	63	12	95	95	NUM
ajst-21789	63	13	%	%	NOUN
ajst-21789	63	14	,	,	PUNCT
ajst-21789	63	15	the	the	DET
ajst-21789	63	16	number	number	NOUN
ajst-21789	63	17	of	of	ADP
ajst-21789	63	18	principal	principal	ADJ
ajst-21789	63	19	components	component	NOUN
ajst-21789	63	20	is	be	AUX
ajst-21789	63	21	reduced	reduce	VERB
ajst-21789	63	22	,	,	PUNCT
ajst-21789	63	23	the	the	DET
ajst-21789	63	24	calculation	calculation	NOUN
ajst-21789	63	25	accuracy	accuracy	NOUN
ajst-21789	63	26	of	of	ADP
ajst-21789	63	27	the	the	DET
ajst-21789	63	28	model	model	NOUN
ajst-21789	63	29	is	be	AUX
ajst-21789	63	30	improved	improve	VERB
ajst-21789	63	31	,	,	PUNCT
ajst-21789	63	32	and	and	CCONJ
ajst-21789	63	33	the	the	DET
ajst-21789	63	34	calculation	calculation	NOUN
ajst-21789	63	35	amount	amount	NOUN
ajst-21789	63	36	of	of	ADP
ajst-21789	63	37	the	the	DET
ajst-21789	63	38	model	model	NOUN
ajst-21789	63	39	is	be	AUX
ajst-21789	63	40	effectively	effectively	ADV
ajst-21789	63	41	reduced	reduce	VERB
ajst-21789	63	42	and	and	CCONJ
ajst-21789	63	43	the	the	DET
ajst-21789	63	44	calculation	calculation	NOUN
ajst-21789	63	45	speed	speed	NOUN
ajst-21789	63	46	of	of	ADP
ajst-21789	63	47	the	the	DET
ajst-21789	63	48	model	model	NOUN
ajst-21789	63	49	is	be	AUX
ajst-21789	63	50	increased	increase	VERB
ajst-21789	63	51	.	.	PUNCT
ajst-21789	64	1	the	the	DET
ajst-21789	64	2	improved	improve	VERB
ajst-21789	64	3	principal	principal	ADJ
ajst-21789	64	4	component	component	NOUN
ajst-21789	64	5	analysis	analysis	NOUN
ajst-21789	64	6	method	method	NOUN
ajst-21789	64	7	has	have	VERB
ajst-21789	64	8	better	well	ADJ
ajst-21789	64	9	effect	effect	NOUN
ajst-21789	64	10	on	on	ADP
ajst-21789	64	11	dimensionality	dimensionality	NOUN
ajst-21789	64	12	reduction	reduction	NOUN
ajst-21789	64	13	.	.	PUNCT
ajst-21789	65	1	ipca	ipca	PROPN
ajst-21789	65	2	method	method	PROPN
ajst-21789	65	3	is	be	AUX
ajst-21789	65	4	superior	superior	ADJ
ajst-21789	65	5	to	to	ADP
ajst-21789	65	6	pca	pca	NOUN
ajst-21789	65	7	method	method	NOUN
ajst-21789	65	8	,	,	PUNCT
ajst-21789	65	9	and	and	CCONJ
ajst-21789	65	10	can	can	AUX
ajst-21789	65	11	be	be	AUX
ajst-21789	65	12	used	use	VERB
ajst-21789	65	13	as	as	ADP
ajst-21789	65	14	the	the	DET
ajst-21789	65	15	1	1	NUM
ajst-21789	65	16	2	2	NUM
ajst-21789	65	17	3	3	NUM
ajst-21789	65	18	4	4	NUM
ajst-21789	65	19	5	5	NUM
ajst-21789	65	20	6	6	NUM
ajst-21789	65	21	7	7	NUM
ajst-21789	65	22	8	8	NUM
ajst-21789	65	23	9	9	NUM
ajst-21789	65	24	10	10	NUM
ajst-21789	65	25	11	11	NUM
ajst-21789	65	26	12	12	NUM
ajst-21789	65	27	13	13	NUM
ajst-21789	65	28	0	0	NUM
ajst-21789	65	29	20	20	NUM
ajst-21789	65	30	40	40	NUM
ajst-21789	65	31	60	60	NUM
ajst-21789	65	32	80	80	NUM
ajst-21789	65	33	100	100	NUM
ajst-21789	65	34	c	c	NOUN
ajst-21789	65	35	on	on	ADP
ajst-21789	65	36	tr	tr	NOUN
ajst-21789	65	37	ib	ib	PROPN
ajst-21789	65	38	ut	ut	PROPN
ajst-21789	65	39	io	io	PROPN
ajst-21789	65	40	n	n	ADV
ajst-21789	65	41	ra	ra	INTJ
ajst-21789	65	42	te	te	INTJ
ajst-21789	65	43	o	o	X
ajst-21789	66	1	f	f	X
ajst-21789	67	1	i	i	PRON
ajst-21789	67	2	m	m	VERB
ajst-21789	67	3	pa	pa	PROPN
ajst-21789	67	4	ct	ct	PROPN
ajst-21789	67	5	f	f	PROPN
ajst-21789	67	6	ac	ac	PROPN
ajst-21789	67	7	to	to	ADP
ajst-21789	67	8	r	r	NOUN
ajst-21789	67	9	(	(	PUNCT
ajst-21789	67	10	%	%	NOUN
ajst-21789	67	11	)	)	PUNCT
ajst-21789	67	12	principal	principal	ADJ
ajst-21789	67	13	component	component	NOUN
ajst-21789	67	14	pca	pca	PROPN
ajst-21789	67	15	cumulative	cumulative	ADJ
ajst-21789	67	16	contribution	contribution	NOUN
ajst-21789	67	17	rate	rate	NOUN
ajst-21789	67	18	1	1	NUM
ajst-21789	67	19	2	2	NUM
ajst-21789	67	20	3	3	NUM
ajst-21789	67	21	4	4	NUM
ajst-21789	67	22	5	5	NUM
ajst-21789	67	23	6	6	NUM
ajst-21789	67	24	7	7	NUM
ajst-21789	67	25	8	8	NUM
ajst-21789	67	26	9	9	NUM
ajst-21789	67	27	10	10	NUM
ajst-21789	67	28	11	11	NUM
ajst-21789	67	29	12	12	NUM
ajst-21789	67	30	13	13	NUM
ajst-21789	67	31	0	0	NUM
ajst-21789	67	32	20	20	NUM
ajst-21789	67	33	40	40	NUM
ajst-21789	67	34	60	60	NUM
ajst-21789	67	35	80	80	NUM
ajst-21789	67	36	100	100	NUM
ajst-21789	67	37	c	c	NOUN
ajst-21789	67	38	on	on	ADP
ajst-21789	67	39	tr	tr	NOUN
ajst-21789	67	40	ib	ib	PROPN
ajst-21789	67	41	ut	ut	PROPN
ajst-21789	67	42	io	io	PROPN
ajst-21789	67	43	n	n	ADV
ajst-21789	67	44	ra	ra	INTJ
ajst-21789	68	1	te	te	INTJ
ajst-21789	68	2	o	o	X
ajst-21789	68	3	f	f	X
ajst-21789	69	1	i	i	PRON
ajst-21789	69	2	m	m	VERB
ajst-21789	69	3	pa	pa	PROPN
ajst-21789	69	4	ct	ct	PROPN
ajst-21789	69	5	f	f	PROPN
ajst-21789	69	6	ac	ac	PROPN
ajst-21789	69	7	to	to	ADP
ajst-21789	69	8	r	r	NOUN
ajst-21789	69	9	(	(	PUNCT
ajst-21789	69	10	%	%	NOUN
ajst-21789	69	11	)	)	PUNCT
ajst-21789	69	12	principal	principal	ADJ
ajst-21789	69	13	component	component	NOUN
ajst-21789	69	14	ipca	ipca	PROPN
ajst-21789	69	15	cumulative	cumulative	ADJ
ajst-21789	69	16	contribution	contribution	NOUN
ajst-21789	69	17	rate	rate	NOUN
ajst-21789	69	18	200	200	NUM
ajst-21789	69	19	final	final	ADJ
ajst-21789	69	20	method	method	NOUN
ajst-21789	69	21	to	to	PART
ajst-21789	69	22	reduce	reduce	VERB
ajst-21789	69	23	the	the	DET
ajst-21789	69	24	dimension	dimension	NOUN
ajst-21789	69	25	of	of	ADP
ajst-21789	69	26	gas	gas	NOUN
ajst-21789	69	27	emission	emission	NOUN
ajst-21789	69	28	prediction	prediction	NOUN
ajst-21789	69	29	index	index	NOUN
ajst-21789	69	30	.	.	PUNCT
ajst-21789	70	1	3	3	X
ajst-21789	70	2	.	.	X
ajst-21789	70	3	bp	bp	PROPN
ajst-21789	70	4	neural	neural	PROPN
ajst-21789	70	5	network	network	PROPN
ajst-21789	70	6	model	model	NOUN
ajst-21789	70	7	based	base	VERB
ajst-21789	70	8	on	on	ADP
ajst-21789	70	9	cp	cp	PROPN
ajst-21789	70	10	-	-	PUNCT
ajst-21789	70	11	so	so	ADV
ajst-21789	70	12	optimization	optimization	NOUN
ajst-21789	70	13	3.1	3.1	NUM
ajst-21789	70	14	.	.	PUNCT
ajst-21789	71	1	pso	pso	NOUN
ajst-21789	71	2	algorithm	algorithm	PROPN
ajst-21789	71	3	improvement	improvement	NOUN
ajst-21789	71	4	particle	particle	NOUN
ajst-21789	71	5	swarm	swarm	NOUN
ajst-21789	71	6	optimization	optimization	NOUN
ajst-21789	71	7	(	(	PUNCT
ajst-21789	71	8	pso	pso	NOUN
ajst-21789	71	9	)	)	PUNCT
ajst-21789	71	10	is	be	AUX
ajst-21789	71	11	a	a	DET
ajst-21789	71	12	stochastic	stochastic	ADJ
ajst-21789	71	13	global	global	ADJ
ajst-21789	71	14	optimization	optimization	NOUN
ajst-21789	71	15	algorithm	algorithm	NOUN
ajst-21789	71	16	first	first	ADV
ajst-21789	71	17	proposed	propose	VERB
ajst-21789	71	18	by	by	ADP
ajst-21789	71	19	kennedy	kennedy	PROPN
ajst-21789	71	20	and	and	CCONJ
ajst-21789	71	21	eberhart	eberhart	NOUN
ajst-21789	71	22	in	in	ADP
ajst-21789	71	23	1995[18	1995[18	NUM
ajst-21789	71	24	]	]	PUNCT
ajst-21789	71	25	.	.	PUNCT
ajst-21789	72	1	3.1.1	3.1.1	X
ajst-21789	72	2	.	.	PUNCT
ajst-21789	72	3	basic	basic	ADJ
ajst-21789	72	4	pso	pso	NOUN
ajst-21789	72	5	algorithm	algorithm	NOUN
ajst-21789	72	6	the	the	DET
ajst-21789	72	7	basic	basic	ADJ
ajst-21789	72	8	pso	pso	NOUN
ajst-21789	72	9	algorithm	algorithm	NOUN
ajst-21789	72	10	uses	use	VERB
ajst-21789	72	11	formulas	formula	NOUN
ajst-21789	72	12	(	(	PUNCT
ajst-21789	72	13	4	4	NUM
ajst-21789	72	14	)	)	PUNCT
ajst-21789	72	15	(	(	PUNCT
ajst-21789	72	16	5	5	NUM
ajst-21789	72	17	)	)	PUNCT
ajst-21789	72	18	to	to	PART
ajst-21789	72	19	operate	operate	VERB
ajst-21789	72	20	on	on	ADP
ajst-21789	72	21	particles	particle	NOUN
ajst-21789	72	22	:	:	PUNCT
ajst-21789	72	23	(	(	PUNCT
ajst-21789	72	24	4	4	NUM
ajst-21789	72	25	)	)	PUNCT
ajst-21789	72	26	(	(	PUNCT
ajst-21789	72	27	5	5	NUM
ajst-21789	72	28	)	)	PUNCT
ajst-21789	72	29	where	where	SCONJ
ajst-21789	72	30	:	:	PUNCT
ajst-21789	72	31	called	call	VERB
ajst-21789	72	32	inertia	inertia	NOUN
ajst-21789	72	33	factor	factor	NOUN
ajst-21789	72	34	,	,	PUNCT
ajst-21789	72	35	is	be	AUX
ajst-21789	72	36	non	non	ADJ
ajst-21789	72	37	-	-	ADJ
ajst-21789	72	38	negative	negative	ADJ
ajst-21789	72	39	;	;	PUNCT
ajst-21789	72	40	and	and	CCONJ
ajst-21789	72	41	are	be	AUX
ajst-21789	72	42	called	call	VERB
ajst-21789	72	43	learning	learn	VERB
ajst-21789	72	44	factor	factor	NOUN
ajst-21789	72	45	and	and	CCONJ
ajst-21789	72	46	is	be	AUX
ajst-21789	72	47	usually	usually	ADV
ajst-21789	72	48	2	2	NUM
ajst-21789	72	49	;	;	PUNCT
ajst-21789	72	50	and	and	CCONJ
ajst-21789	72	51	are	be	AUX
ajst-21789	72	52	random	random	ADJ
ajst-21789	72	53	number	number	NOUN
ajst-21789	72	54	between	between	ADP
ajst-21789	72	55	0	0	NUM
ajst-21789	72	56	and	and	CCONJ
ajst-21789	72	57	1;𝑥	1;𝑥	NUM
ajst-21789	72	58	is	be	AUX
ajst-21789	72	59	the	the	DET
ajst-21789	72	60	position	position	NOUN
ajst-21789	72	61	of	of	ADP
ajst-21789	72	62	the	the	DET
ajst-21789	72	63	i	i	PROPN
ajst-21789	72	64	-	-	PUNCT
ajst-21789	72	65	th	th	X
ajst-21789	72	66	particle	particle	NOUN
ajst-21789	72	67	at	at	ADP
ajst-21789	72	68	step	step	NOUN
ajst-21789	72	69	d.	d.	PROPN
ajst-21789	72	70	the	the	DET
ajst-21789	72	71	velocity	velocity	NOUN
ajst-21789	72	72	evolution	evolution	NOUN
ajst-21789	72	73	equation	equation	NOUN
ajst-21789	72	74	expressed	express	VERB
ajst-21789	72	75	in	in	ADP
ajst-21789	72	76	formula	formula	NOUN
ajst-21789	72	77	(	(	PUNCT
ajst-21789	72	78	4	4	NUM
ajst-21789	72	79	)	)	PUNCT
ajst-21789	72	80	and	and	CCONJ
ajst-21789	72	81	(	(	PUNCT
ajst-21789	72	82	5	5	X
ajst-21789	72	83	)	)	PUNCT
ajst-21789	72	84	consists	consist	VERB
ajst-21789	72	85	of	of	ADP
ajst-21789	72	86	three	three	NUM
ajst-21789	72	87	parts	part	NOUN
ajst-21789	72	88	.	.	PUNCT
ajst-21789	73	1	the	the	DET
ajst-21789	73	2	first	first	ADJ
ajst-21789	73	3	part	part	NOUN
ajst-21789	73	4	is	be	AUX
ajst-21789	73	5	the	the	DET
ajst-21789	73	6	inertia	inertia	NOUN
ajst-21789	73	7	of	of	ADP
ajst-21789	73	8	the	the	DET
ajst-21789	73	9	particle	particle	NOUN
ajst-21789	73	10	itself	itself	PRON
ajst-21789	73	11	,	,	PUNCT
ajst-21789	73	12	and	and	CCONJ
ajst-21789	73	13	the	the	DET
ajst-21789	73	14	velocity	velocity	NOUN
ajst-21789	73	15	in	in	ADP
ajst-21789	73	16	a	a	DET
ajst-21789	73	17	certain	certain	ADJ
ajst-21789	73	18	direction	direction	NOUN
ajst-21789	73	19	when	when	SCONJ
ajst-21789	73	20	the	the	DET
ajst-21789	73	21	particle	particle	NOUN
ajst-21789	73	22	carries	carry	VERB
ajst-21789	73	23	out	out	ADP
ajst-21789	73	24	the	the	DET
ajst-21789	73	25	next	next	ADJ
ajst-21789	73	26	search	search	NOUN
ajst-21789	73	27	;	;	PUNCT
ajst-21789	73	28	the	the	DET
ajst-21789	73	29	second	second	ADJ
ajst-21789	73	30	part	part	NOUN
ajst-21789	73	31	is	be	AUX
ajst-21789	73	32	the	the	DET
ajst-21789	73	33	learning	learning	NOUN
ajst-21789	73	34	of	of	ADP
ajst-21789	73	35	the	the	DET
ajst-21789	73	36	particle	particle	NOUN
ajst-21789	73	37	itself	itself	PRON
ajst-21789	73	38	,	,	PUNCT
ajst-21789	73	39	which	which	PRON
ajst-21789	73	40	comes	come	VERB
ajst-21789	73	41	from	from	ADP
ajst-21789	73	42	the	the	DET
ajst-21789	73	43	"	"	PUNCT
ajst-21789	73	44	experience	experience	NOUN
ajst-21789	73	45	"	"	PUNCT
ajst-21789	73	46	of	of	ADP
ajst-21789	73	47	the	the	DET
ajst-21789	73	48	particle	particle	NOUN
ajst-21789	73	49	's	's	PART
ajst-21789	73	50	previous	previous	ADJ
ajst-21789	73	51	flight	flight	NOUN
ajst-21789	73	52	,	,	PUNCT
ajst-21789	73	53	namely	namely	ADV
ajst-21789	73	54	the	the	DET
ajst-21789	73	55	local	local	ADJ
ajst-21789	73	56	optimal	optimal	ADJ
ajst-21789	73	57	solution	solution	NOUN
ajst-21789	73	58	.	.	PUNCT
ajst-21789	74	1	the	the	DET
ajst-21789	74	2	third	third	ADJ
ajst-21789	74	3	part	part	NOUN
ajst-21789	74	4	is	be	AUX
ajst-21789	74	5	the	the	DET
ajst-21789	74	6	information	information	NOUN
ajst-21789	74	7	sharing	share	VERB
ajst-21789	74	8	among	among	ADP
ajst-21789	74	9	particles	particle	NOUN
ajst-21789	74	10	,	,	PUNCT
ajst-21789	74	11	that	that	ADV
ajst-21789	74	12	is	is	ADV
ajst-21789	74	13	,	,	PUNCT
ajst-21789	74	14	the	the	DET
ajst-21789	74	15	global	global	ADJ
ajst-21789	74	16	optimal	optimal	ADJ
ajst-21789	74	17	solution	solution	NOUN
ajst-21789	74	18	.	.	PUNCT
ajst-21789	75	1	in	in	ADP
ajst-21789	75	2	addition	addition	NOUN
ajst-21789	75	3	,	,	PUNCT
ajst-21789	75	4	when	when	SCONJ
ajst-21789	75	5	the	the	DET
ajst-21789	75	6	particle	particle	NOUN
ajst-21789	75	7	is	be	AUX
ajst-21789	75	8	constantly	constantly	ADV
ajst-21789	75	9	adjusting	adjust	VERB
ajst-21789	75	10	its	its	PRON
ajst-21789	75	11	position	position	NOUN
ajst-21789	75	12	according	accord	VERB
ajst-21789	75	13	to	to	ADP
ajst-21789	75	14	the	the	DET
ajst-21789	75	15	speed	speed	NOUN
ajst-21789	75	16	,	,	PUNCT
ajst-21789	75	17	it	it	PRON
ajst-21789	75	18	is	be	AUX
ajst-21789	75	19	also	also	ADV
ajst-21789	75	20	limited	limit	VERB
ajst-21789	75	21	by	by	ADP
ajst-21789	75	22	the	the	DET
ajst-21789	75	23	maximum	maximum	ADJ
ajst-21789	75	24	speed	speed	NOUN
ajst-21789	75	25	𝑣	𝑣	X
ajst-21789	75	26	.	.	PUNCT
ajst-21789	76	1	the	the	DET
ajst-21789	76	2	termination	termination	NOUN
ajst-21789	76	3	condition	condition	NOUN
ajst-21789	76	4	of	of	ADP
ajst-21789	76	5	iteration	iteration	NOUN
ajst-21789	76	6	is	be	AUX
ajst-21789	76	7	generally	generally	ADV
ajst-21789	76	8	selected	select	VERB
ajst-21789	76	9	as	as	SCONJ
ajst-21789	76	10	the	the	DET
ajst-21789	76	11	maximum	maximum	ADJ
ajst-21789	76	12	number	number	NOUN
ajst-21789	76	13	of	of	ADP
ajst-21789	76	14	iterations	iteration	NOUN
ajst-21789	76	15	or	or	CCONJ
ajst-21789	76	16	the	the	DET
ajst-21789	76	17	optimal	optimal	ADJ
ajst-21789	76	18	location	location	NOUN
ajst-21789	76	19	of	of	ADP
ajst-21789	76	20	the	the	DET
ajst-21789	76	21	current	current	ADJ
ajst-21789	76	22	location	location	NOUN
ajst-21789	76	23	of	of	ADP
ajst-21789	76	24	the	the	DET
ajst-21789	76	25	population	population	NOUN
ajst-21789	76	26	meets	meet	VERB
ajst-21789	76	27	the	the	DET
ajst-21789	76	28	predetermined	predetermined	ADJ
ajst-21789	76	29	minimum	minimum	NOUN
ajst-21789	76	30	fitness	fitness	NOUN
ajst-21789	76	31	threshold	threshold	NOUN
ajst-21789	76	32	.	.	PUNCT
ajst-21789	77	1	3.1.2	3.1.2	X
ajst-21789	77	2	.	.	PUNCT
ajst-21789	77	3	adaptive	adaptive	ADJ
ajst-21789	77	4	inertial	inertial	ADJ
ajst-21789	77	5	weight	weight	NOUN
ajst-21789	77	6	particle	particle	NOUN
ajst-21789	77	7	swarm	swarm	NOUN
ajst-21789	77	8	optimization	optimization	NOUN
ajst-21789	77	9	a	a	DET
ajst-21789	77	10	large	large	ADJ
ajst-21789	77	11	inertial	inertial	ADJ
ajst-21789	77	12	weight	weight	NOUN
ajst-21789	77	13	value	value	NOUN
ajst-21789	77	14	is	be	AUX
ajst-21789	77	15	conducive	conducive	ADJ
ajst-21789	77	16	to	to	ADP
ajst-21789	77	17	global	global	ADJ
ajst-21789	77	18	search	search	NOUN
ajst-21789	77	19	,	,	PUNCT
ajst-21789	77	20	while	while	SCONJ
ajst-21789	77	21	a	a	DET
ajst-21789	77	22	small	small	ADJ
ajst-21789	77	23	weight	weight	NOUN
ajst-21789	77	24	value	value	NOUN
ajst-21789	77	25	is	be	AUX
ajst-21789	77	26	more	more	ADV
ajst-21789	77	27	conducive	conducive	ADJ
ajst-21789	77	28	to	to	ADP
ajst-21789	77	29	local	local	ADJ
ajst-21789	77	30	search.[19	search.[19	NOUN
ajst-21789	77	31	,	,	PUNCT
ajst-21789	77	32	20	20	NUM
ajst-21789	77	33	]	]	PUNCT
ajst-21789	77	34	in	in	ADP
ajst-21789	77	35	order	order	NOUN
ajst-21789	77	36	to	to	PART
ajst-21789	77	37	make	make	VERB
ajst-21789	77	38	pso	pso	NOUN
ajst-21789	77	39	more	more	ADV
ajst-21789	77	40	stable	stable	ADJ
ajst-21789	77	41	,	,	PUNCT
ajst-21789	77	42	the	the	DET
ajst-21789	77	43	inertia	inertia	NOUN
ajst-21789	77	44	weight	weight	NOUN
ajst-21789	77	45	of	of	ADP
ajst-21789	77	46	pso	pso	NOUN
ajst-21789	77	47	is	be	AUX
ajst-21789	77	48	changed	change	VERB
ajst-21789	77	49	adaptively	adaptively	ADV
ajst-21789	77	50	.	.	PUNCT
ajst-21789	78	1	compared	compare	VERB
ajst-21789	78	2	with	with	ADP
ajst-21789	78	3	the	the	DET
ajst-21789	78	4	original	original	ADJ
ajst-21789	78	5	pso	pso	NOUN
ajst-21789	78	6	,	,	PUNCT
ajst-21789	78	7	the	the	DET
ajst-21789	78	8	inertia	inertia	NOUN
ajst-21789	78	9	weight	weight	NOUN
ajst-21789	78	10	and	and	CCONJ
ajst-21789	78	11	the	the	DET
ajst-21789	78	12	number	number	NOUN
ajst-21789	78	13	of	of	ADP
ajst-21789	78	14	iterations	iteration	NOUN
ajst-21789	78	15	are	be	AUX
ajst-21789	78	16	related	relate	VERB
ajst-21789	78	17	to	to	ADP
ajst-21789	78	18	the	the	DET
ajst-21789	78	19	fitness	fitness	NOUN
ajst-21789	78	20	of	of	ADP
ajst-21789	78	21	each	each	DET
ajst-21789	78	22	particle	particle	NOUN
ajst-21789	78	23	.	.	PUNCT
ajst-21789	79	1	for	for	ADP
ajst-21789	79	2	the	the	DET
ajst-21789	79	3	minimum	minimum	ADJ
ajst-21789	79	4	value	value	NOUN
ajst-21789	79	5	problem	problem	NOUN
ajst-21789	79	6	,	,	PUNCT
ajst-21789	79	7	the	the	DET
ajst-21789	79	8	change	change	NOUN
ajst-21789	79	9	rule	rule	NOUN
ajst-21789	79	10	of	of	ADP
ajst-21789	79	11	inertia	inertia	NOUN
ajst-21789	79	12	weight	weight	NOUN
ajst-21789	79	13	is	be	AUX
ajst-21789	79	14	shown	show	VERB
ajst-21789	79	15	in	in	ADP
ajst-21789	79	16	equation	equation	NOUN
ajst-21789	79	17	(	(	PUNCT
ajst-21789	79	18	6	6	NUM
ajst-21789	79	19	)	)	PUNCT
ajst-21789	79	20	.	.	PUNCT
ajst-21789	80	1	for	for	ADP
ajst-21789	80	2	the	the	DET
ajst-21789	80	3	maximum	maximum	ADJ
ajst-21789	80	4	value	value	NOUN
ajst-21789	80	5	problem	problem	NOUN
ajst-21789	80	6	,	,	PUNCT
ajst-21789	80	7	the	the	DET
ajst-21789	80	8	change	change	NOUN
ajst-21789	80	9	rule	rule	NOUN
ajst-21789	80	10	of	of	ADP
ajst-21789	80	11	inertia	inertia	NOUN
ajst-21789	80	12	weight	weight	NOUN
ajst-21789	80	13	is	be	AUX
ajst-21789	80	14	shown	show	VERB
ajst-21789	80	15	in	in	ADP
ajst-21789	80	16	equation	equation	NOUN
ajst-21789	80	17	(	(	PUNCT
ajst-21789	80	18	7	7	NUM
ajst-21789	80	19	)	)	PUNCT
ajst-21789	80	20	.	.	PUNCT
ajst-21789	81	1	(	(	PUNCT
ajst-21789	81	2	6	6	NUM
ajst-21789	81	3	)	)	PUNCT
ajst-21789	81	4	(	(	PUNCT
ajst-21789	81	5	7	7	NUM
ajst-21789	81	6	)	)	PUNCT
ajst-21789	81	7	where	where	SCONJ
ajst-21789	81	8	:	:	PUNCT
ajst-21789	81	9	𝑤	𝑤	X
ajst-21789	81	10	and	and	CCONJ
ajst-21789	81	11	𝑤	𝑤	PROPN
ajst-21789	81	12	are	be	AUX
ajst-21789	81	13	the	the	DET
ajst-21789	81	14	minimum	minimum	ADJ
ajst-21789	81	15	and	and	CCONJ
ajst-21789	81	16	maximum	maximum	ADJ
ajst-21789	81	17	inertia	inertia	NOUN
ajst-21789	81	18	coefficients	coefficient	NOUN
ajst-21789	81	19	given	give	VERB
ajst-21789	81	20	in	in	ADP
ajst-21789	81	21	advance	advance	NOUN
ajst-21789	81	22	,	,	PUNCT
ajst-21789	81	23	generally	generally	ADV
ajst-21789	81	24	0.4	0.4	NUM
ajst-21789	81	25	and	and	CCONJ
ajst-21789	81	26	0.9	0.9	NUM
ajst-21789	81	27	.	.	PUNCT
ajst-21789	82	1	the	the	DET
ajst-21789	82	2	average	average	ADJ
ajst-21789	82	3	fitness	fitness	NOUN
ajst-21789	82	4	of	of	ADP
ajst-21789	82	5	all	all	DET
ajst-21789	82	6	particles	particle	NOUN
ajst-21789	82	7	at	at	ADP
ajst-21789	82	8	the	the	DET
ajst-21789	82	9	dth	dth	ADJ
ajst-21789	82	10	iteration	iteration	NOUN
ajst-21789	82	11	is	be	AUX
ajst-21789	82	12	shown	show	VERB
ajst-21789	82	13	in	in	ADP
ajst-21789	82	14	equation	equation	NOUN
ajst-21789	82	15	(	(	PUNCT
ajst-21789	82	16	8)	8)	NUM
ajst-21789	82	17	:	:	PUNCT
ajst-21789	82	18	(	(	PUNCT
ajst-21789	82	19	8)	8)	NUM
ajst-21789	82	20	minimum	minimum	NOUN
ajst-21789	82	21	fitness	fitness	NOUN
ajst-21789	82	22	of	of	ADP
ajst-21789	82	23	all	all	DET
ajst-21789	82	24	particles	particle	NOUN
ajst-21789	82	25	at	at	ADP
ajst-21789	82	26	the	the	DET
ajst-21789	82	27	dth	dth	ADJ
ajst-21789	82	28	iteration	iteration	NOUN
ajst-21789	82	29	,	,	PUNCT
ajst-21789	82	30	as	as	SCONJ
ajst-21789	82	31	shown	show	VERB
ajst-21789	82	32	in	in	ADP
ajst-21789	82	33	equation	equation	NOUN
ajst-21789	82	34	(	(	PUNCT
ajst-21789	82	35	9	9	NUM
ajst-21789	82	36	)	)	PUNCT
ajst-21789	82	37	:	:	PUNCT
ajst-21789	82	38	(	(	PUNCT
ajst-21789	82	39	9	9	X
ajst-21789	82	40	)	)	PUNCT
ajst-21789	82	41	3.1.3	3.1.3	NUM
ajst-21789	82	42	.	.	PUNCT
ajst-21789	82	43	compression	compression	NOUN
ajst-21789	82	44	factor	factor	NOUN
ajst-21789	82	45	particle	particle	NOUN
ajst-21789	82	46	swarm	swarm	NOUN
ajst-21789	82	47	optimization	optimization	NOUN
ajst-21789	82	48	individual	individual	ADJ
ajst-21789	82	49	learning	learn	VERB
ajst-21789	82	50	factors	factor	NOUN
ajst-21789	82	51	and	and	CCONJ
ajst-21789	82	52	social	social	ADJ
ajst-21789	82	53	learning	learning	NOUN
ajst-21789	82	54	factors	factor	NOUN
ajst-21789	82	55	determine	determine	VERB
ajst-21789	82	56	the	the	DET
ajst-21789	82	57	influence	influence	NOUN
ajst-21789	82	58	of	of	ADP
ajst-21789	82	59	the	the	DET
ajst-21789	82	60	experiential	experiential	ADJ
ajst-21789	82	61	information	information	NOUN
ajst-21789	82	62	of	of	ADP
ajst-21789	82	63	particles	particle	NOUN
ajst-21789	82	64	and	and	CCONJ
ajst-21789	82	65	other	other	ADJ
ajst-21789	82	66	particles	particle	NOUN
ajst-21789	82	67	on	on	ADP
ajst-21789	82	68	the	the	DET
ajst-21789	82	69	trajectory	trajectory	NOUN
ajst-21789	82	70	of	of	ADP
ajst-21789	82	71	particles	particle	NOUN
ajst-21789	82	72	,	,	PUNCT
ajst-21789	82	73	which	which	PRON
ajst-21789	82	74	reflects	reflect	VERB
ajst-21789	82	75	the	the	DET
ajst-21789	82	76	information	information	NOUN
ajst-21789	82	77	exchange	exchange	NOUN
ajst-21789	82	78	between	between	ADP
ajst-21789	82	79	particle	particle	NOUN
ajst-21789	82	80	groups	group	NOUN
ajst-21789	82	81	[	[	X
ajst-21789	82	82	21	21	NUM
ajst-21789	82	83	-	-	SYM
ajst-21789	82	84	23].setting	23].sette	VERB
ajst-21789	82	85	a	a	DET
ajst-21789	82	86	large	large	ADJ
ajst-21789	82	87	𝑐	𝑐	NOUN
ajst-21789	82	88	value	value	NOUN
ajst-21789	82	89	will	will	AUX
ajst-21789	82	90	make	make	VERB
ajst-21789	82	91	the	the	DET
ajst-21789	82	92	particles	particle	NOUN
ajst-21789	82	93	search	search	VERB
ajst-21789	82	94	too	too	ADV
ajst-21789	82	95	much	much	ADV
ajst-21789	82	96	in	in	ADP
ajst-21789	82	97	their	their	PRON
ajst-21789	82	98	own	own	ADJ
ajst-21789	82	99	range	range	NOUN
ajst-21789	82	100	and	and	CCONJ
ajst-21789	82	101	converge	converge	VERB
ajst-21789	82	102	slowly	slowly	ADV
ajst-21789	82	103	,	,	PUNCT
ajst-21789	82	104	and	and	CCONJ
ajst-21789	82	105	a	a	DET
ajst-21789	82	106	large	large	ADJ
ajst-21789	82	107	𝑐	𝑐	NOUN
ajst-21789	82	108	value	value	NOUN
ajst-21789	82	109	will	will	AUX
ajst-21789	82	110	cause	cause	VERB
ajst-21789	82	111	the	the	DET
ajst-21789	82	112	particles	particle	NOUN
ajst-21789	82	113	to	to	PART
ajst-21789	82	114	converge	converge	VERB
ajst-21789	82	115	prematurely	prematurely	ADV
ajst-21789	82	116	to	to	ADP
ajst-21789	82	117	the	the	DET
ajst-21789	82	118	local	local	ADJ
ajst-21789	82	119	optimal	optimal	ADJ
ajst-21789	82	120	value	value	NOUN
ajst-21789	82	121	.	.	PUNCT
ajst-21789	83	1	setting	set	VERB
ajst-21789	83	2	a	a	DET
ajst-21789	83	3	compression	compression	NOUN
ajst-21789	83	4	factor	factor	NOUN
ajst-21789	83	5	k	k	NOUN
ajst-21789	83	6	,	,	PUNCT
ajst-21789	83	7	such	such	ADJ
ajst-21789	83	8	as	as	ADP
ajst-21789	83	9	equations	equation	NOUN
ajst-21789	83	10	(	(	PUNCT
ajst-21789	83	11	10	10	NUM
ajst-21789	83	12	)	)	PUNCT
ajst-21789	83	13	and	and	CCONJ
ajst-21789	83	14	(	(	PUNCT
ajst-21789	83	15	11	11	NUM
ajst-21789	83	16	)	)	PUNCT
ajst-21789	83	17	can	can	AUX
ajst-21789	83	18	delay	delay	VERB
ajst-21789	83	19	the	the	DET
ajst-21789	83	20	arrival	arrival	NOUN
ajst-21789	83	21	of	of	ADP
ajst-21789	83	22	the	the	DET
ajst-21789	83	23	local	local	ADJ
ajst-21789	83	24	optimal	optimal	ADJ
ajst-21789	83	25	solution	solution	NOUN
ajst-21789	83	26	.	.	PUNCT
ajst-21789	84	1	(	(	PUNCT
ajst-21789	84	2	10	10	NUM
ajst-21789	84	3	)	)	PUNCT
ajst-21789	84	4	(	(	PUNCT
ajst-21789	84	5	11	11	NUM
ajst-21789	84	6	)	)	PUNCT
ajst-21789	84	7	where	where	SCONJ
ajst-21789	84	8	:	:	PUNCT
ajst-21789	84	9	,	,	PUNCT
ajst-21789	84	10	.	.	PUNCT
ajst-21789	85	1	3.1.4	3.1.4	X
ajst-21789	85	2	.	.	PUNCT
ajst-21789	85	3	combinatorial	combinatorial	ADJ
ajst-21789	85	4	particle	particle	NOUN
ajst-21789	85	5	swarm	swarm	NOUN
ajst-21789	85	6	optimization	optimization	NOUN
ajst-21789	85	7	(	(	PUNCT
ajst-21789	85	8	cpso	cpso	NOUN
ajst-21789	85	9	)	)	PUNCT
ajst-21789	85	10	n	n	CCONJ
ajst-21789	85	11	the	the	DET
ajst-21789	85	12	early	early	ADJ
ajst-21789	85	13	stage	stage	NOUN
ajst-21789	85	14	,	,	PUNCT
ajst-21789	85	15	the	the	DET
ajst-21789	85	16	fitness	fitness	NOUN
ajst-21789	85	17	of	of	ADP
ajst-21789	85	18	particle	particle	NOUN
ajst-21789	85	19	swarm	swarm	NOUN
ajst-21789	85	20	is	be	AUX
ajst-21789	85	21	large	large	ADJ
ajst-21789	85	22	,	,	PUNCT
ajst-21789	85	23	and	and	CCONJ
ajst-21789	85	24	global	global	ADJ
ajst-21789	85	25	search	search	NOUN
ajst-21789	85	26	is	be	AUX
ajst-21789	85	27	more	more	ADV
ajst-21789	85	28	necessary	necessary	ADJ
ajst-21789	85	29	.	.	PUNCT
ajst-21789	86	1	corresponding	correspond	VERB
ajst-21789	86	2	to	to	ADP
ajst-21789	86	3	each	each	DET
ajst-21789	86	4	particle	particle	NOUN
ajst-21789	86	5	,	,	PUNCT
ajst-21789	86	6	it	it	PRON
ajst-21789	86	7	requires	require	VERB
ajst-21789	86	8	rapid	rapid	ADJ
ajst-21789	86	9	search	search	NOUN
ajst-21789	86	10	within	within	ADP
ajst-21789	86	11	its	its	PRON
ajst-21789	86	12	own	own	ADJ
ajst-21789	86	13	scope	scope	NOUN
ajst-21789	86	14	,	,	PUNCT
ajst-21789	86	15	and	and	CCONJ
ajst-21789	86	16	requires	require	VERB
ajst-21789	86	17	large	large	ADJ
ajst-21789	86	18	inertia	inertia	NOUN
ajst-21789	86	19	weight	weight	NOUN
ajst-21789	86	20	,	,	PUNCT
ajst-21789	86	21	individual	individual	ADJ
ajst-21789	86	22	learning	learning	NOUN
ajst-21789	86	23	factor	factor	NOUN
ajst-21789	86	24	and	and	CCONJ
ajst-21789	86	25	small	small	ADJ
ajst-21789	86	26	social	social	ADJ
ajst-21789	86	27	learning	learning	NOUN
ajst-21789	86	28	factor	factor	NOUN
ajst-21789	86	29	.	.	PUNCT
ajst-21789	87	1	in	in	ADP
ajst-21789	87	2	the	the	DET
ajst-21789	87	3	later	later	ADJ
ajst-21789	87	4	stage	stage	NOUN
ajst-21789	87	5	of	of	ADP
ajst-21789	87	6	particle	particle	NOUN
ajst-21789	87	7	swarm	swarm	NOUN
ajst-21789	87	8	search	search	NOUN
ajst-21789	87	9	,	,	PUNCT
ajst-21789	87	10	fitness	fitness	NOUN
ajst-21789	87	11	decreases	decrease	VERB
ajst-21789	87	12	gradually	gradually	ADV
ajst-21789	87	13	,	,	PUNCT
ajst-21789	87	14	so	so	ADV
ajst-21789	87	15	smaller	small	ADJ
ajst-21789	87	16	inertia	inertia	NOUN
ajst-21789	87	17	weights	weight	NOUN
ajst-21789	87	18	,	,	PUNCT
ajst-21789	87	19	individual	individual	ADJ
ajst-21789	87	20	learning	learning	NOUN
ajst-21789	87	21	factors	factor	NOUN
ajst-21789	87	22	and	and	CCONJ
ajst-21789	87	23	larger	large	ADJ
ajst-21789	87	24	social	social	ADJ
ajst-21789	87	25	learning	learning	NOUN
ajst-21789	87	26	factors	factor	NOUN
ajst-21789	87	27	are	be	AUX
ajst-21789	87	28	needed	need	VERB
ajst-21789	87	29	.	.	PUNCT
ajst-21789	88	1	however	however	ADV
ajst-21789	88	2	,	,	PUNCT
ajst-21789	88	3	in	in	ADP
ajst-21789	88	4	the	the	DET
ajst-21789	88	5	later	later	ADJ
ajst-21789	88	6	stage	stage	NOUN
ajst-21789	88	7	,	,	PUNCT
ajst-21789	88	8	particle	particle	NOUN
ajst-21789	88	9	swarm	swarm	NOUN
ajst-21789	88	10	will	will	AUX
ajst-21789	88	11	hover	hover	VERB
ajst-21789	88	12	around	around	ADP
ajst-21789	88	13	itself	itself	PRON
ajst-21789	88	14	too	too	ADV
ajst-21789	88	15	much	much	ADV
ajst-21789	88	16	and	and	CCONJ
ajst-21789	88	17	easily	easily	ADV
ajst-21789	88	18	fall	fall	VERB
ajst-21789	88	19	into	into	ADP
ajst-21789	88	20	the	the	DET
ajst-21789	88	21	local	local	ADJ
ajst-21789	88	22	optimal	optimal	ADJ
ajst-21789	88	23	solution	solution	NOUN
ajst-21789	88	24	.	.	PUNCT
ajst-21789	89	1	cpso	cpso	NOUN
ajst-21789	89	2	(	(	PUNCT
ajst-21789	89	3	combine	combine	VERB
ajst-21789	89	4	adaptive	adaptive	ADJ
ajst-21789	89	5	inertia	inertia	NOUN
ajst-21789	89	6	weights	weight	NOUN
ajst-21789	89	7	and	and	CCONJ
ajst-21789	89	8	learning	learn	VERB
ajst-21789	89	9	factors	factor	NOUN
ajst-21789	89	10	pso	pso	NOUN
ajst-21789	89	11	)	)	PUNCT
ajst-21789	89	12	algorithm	algorithm	NOUN
ajst-21789	89	13	combines	combine	VERB
ajst-21789	89	14	"	"	PUNCT
ajst-21789	89	15	adaptive	adaptive	ADJ
ajst-21789	89	16	inertia	inertia	NOUN
ajst-21789	89	17	weights	weight	NOUN
ajst-21789	89	18	"	"	PUNCT
ajst-21789	89	19	and	and	CCONJ
ajst-21789	89	20	"	"	PUNCT
ajst-21789	89	21	compression	compression	NOUN
ajst-21789	89	22	factor	factor	NOUN
ajst-21789	89	23	algorithm	algorithm	NOUN
ajst-21789	89	24	"	"	PUNCT
ajst-21789	89	25	.	.	PUNCT
ajst-21789	90	1	it	it	PRON
ajst-21789	90	2	can	can	AUX
ajst-21789	90	3	balance	balance	VERB
ajst-21789	90	4	the	the	DET
ajst-21789	90	5	local	local	ADJ
ajst-21789	90	6	search	search	NOUN
ajst-21789	90	7	and	and	CCONJ
ajst-21789	90	8	global	global	ADJ
ajst-21789	90	9	search	search	NOUN
ajst-21789	90	10	capabilities	capability	NOUN
ajst-21789	90	11	of	of	ADP
ajst-21789	90	12	pso	pso	NOUN
ajst-21789	90	13	algorithm	algorithm	NOUN
ajst-21789	90	14	to	to	PART
ajst-21789	90	15	avoid	avoid	VERB
ajst-21789	90	16	the	the	DET
ajst-21789	90	17	shortcomings	shortcoming	NOUN
ajst-21789	90	18	of	of	ADP
ajst-21789	90	19	premature	premature	ADJ
ajst-21789	90	20	convergence	convergence	NOUN
ajst-21789	90	21	of	of	ADP
ajst-21789	90	22	pso	pso	NOUN
ajst-21789	90	23	algorithm	algorithm	NOUN
ajst-21789	90	24	and	and	CCONJ
ajst-21789	90	25	falling	fall	VERB
ajst-21789	90	26	into	into	ADP
ajst-21789	90	27	local	local	ADJ
ajst-21789	90	28	optimal	optimal	ADJ
ajst-21789	90	29	solutions	solution	NOUN
ajst-21789	90	30	,	,	PUNCT
ajst-21789	90	31	and	and	CCONJ
ajst-21789	90	32	the	the	DET
ajst-21789	90	33	speed	speed	NOUN
ajst-21789	90	34	update	update	NOUN
ajst-21789	90	35	formula	formula	NOUN
ajst-21789	90	36	is	be	AUX
ajst-21789	90	37	shown	show	VERB
ajst-21789	90	38	in	in	ADP
ajst-21789	90	39	(	(	PUNCT
ajst-21789	90	40	12	12	NUM
ajst-21789	90	41	)	)	PUNCT
ajst-21789	90	42	.	.	PUNCT
ajst-21789	91	1	(	(	PUNCT
ajst-21789	91	2	12	12	NUM
ajst-21789	91	3	)	)	PUNCT
ajst-21789	91	4	3.2	3.2	NUM
ajst-21789	91	5	.	.	PUNCT
ajst-21789	92	1	bp	bp	PROPN
ajst-21789	92	2	neural	neural	PROPN
ajst-21789	92	3	network	network	PROPN
ajst-21789	92	4	bp	bp	PROPN
ajst-21789	92	5	neural	neural	PROPN
ajst-21789	92	6	network	network	NOUN
ajst-21789	92	7	is	be	AUX
ajst-21789	92	8	a	a	DET
ajst-21789	92	9	kind	kind	NOUN
ajst-21789	92	10	of	of	ADP
ajst-21789	92	11	multi	multi	ADJ
ajst-21789	92	12	-	-	ADJ
ajst-21789	92	13	layer	layer	ADJ
ajst-21789	92	14	feedforward	feedforward	NOUN
ajst-21789	92	15	neural	neural	ADJ
ajst-21789	92	16	network	network	NOUN
ajst-21789	92	17	which	which	PRON
ajst-21789	92	18	corrects	correct	VERB
ajst-21789	92	19	error	error	NOUN
ajst-21789	92	20	by	by	ADP
ajst-21789	92	21	error	error	NOUN
ajst-21789	92	22	backpropagation	backpropagation	NOUN
ajst-21789	92	23	algorithm	algorithm	NOUN
ajst-21789	92	24	.	.	PUNCT
ajst-21789	93	1	the	the	DET
ajst-21789	93	2	signal	signal	NOUN
ajst-21789	93	3	propagates	propagate	VERB
ajst-21789	93	4	forward	forward	ADV
ajst-21789	93	5	while	while	SCONJ
ajst-21789	93	6	the	the	DET
ajst-21789	93	7	error	error	NOUN
ajst-21789	93	8	201	201	NUM
ajst-21789	93	9	propagates	propagate	VERB
ajst-21789	93	10	back	back	ADV
ajst-21789	93	11	.	.	PUNCT
ajst-21789	94	1	in	in	ADP
ajst-21789	94	2	the	the	DET
ajst-21789	94	3	forward	forward	ADJ
ajst-21789	94	4	propagation	propagation	NOUN
ajst-21789	94	5	process	process	NOUN
ajst-21789	94	6	,	,	PUNCT
ajst-21789	94	7	the	the	DET
ajst-21789	94	8	input	input	NOUN
ajst-21789	94	9	signal	signal	NOUN
ajst-21789	94	10	is	be	AUX
ajst-21789	94	11	processed	process	VERB
ajst-21789	94	12	layer	layer	NOUN
ajst-21789	94	13	by	by	ADP
ajst-21789	94	14	layer	layer	NOUN
ajst-21789	94	15	through	through	ADP
ajst-21789	94	16	the	the	DET
ajst-21789	94	17	input	input	NOUN
ajst-21789	94	18	layer	layer	NOUN
ajst-21789	94	19	and	and	CCONJ
ajst-21789	94	20	hidden	hidden	ADJ
ajst-21789	94	21	layer	layer	NOUN
ajst-21789	94	22	.	.	PUNCT
ajst-21789	95	1	when	when	SCONJ
ajst-21789	95	2	reaching	reach	VERB
ajst-21789	95	3	the	the	DET
ajst-21789	95	4	output	output	NOUN
ajst-21789	95	5	layer	layer	NOUN
ajst-21789	95	6	,	,	PUNCT
ajst-21789	95	7	if	if	SCONJ
ajst-21789	95	8	the	the	DET
ajst-21789	95	9	result	result	NOUN
ajst-21789	95	10	or	or	CCONJ
ajst-21789	95	11	the	the	DET
ajst-21789	95	12	number	number	NOUN
ajst-21789	95	13	of	of	ADP
ajst-21789	95	14	iterations	iteration	NOUN
ajst-21789	95	15	does	do	AUX
ajst-21789	95	16	not	not	PART
ajst-21789	95	17	meet	meet	VERB
ajst-21789	95	18	the	the	DET
ajst-21789	95	19	requirements	requirement	NOUN
ajst-21789	95	20	,	,	PUNCT
ajst-21789	95	21	the	the	DET
ajst-21789	95	22	backpropagation	backpropagation	NOUN
ajst-21789	95	23	process	process	NOUN
ajst-21789	95	24	is	be	AUX
ajst-21789	95	25	entered	enter	VERB
ajst-21789	95	26	,	,	PUNCT
ajst-21789	95	27	the	the	DET
ajst-21789	95	28	error	error	NOUN
ajst-21789	95	29	signal	signal	NOUN
ajst-21789	95	30	is	be	AUX
ajst-21789	95	31	returned	return	VERB
ajst-21789	95	32	in	in	ADP
ajst-21789	95	33	the	the	DET
ajst-21789	95	34	original	original	ADJ
ajst-21789	95	35	way	way	NOUN
ajst-21789	95	36	,	,	PUNCT
ajst-21789	95	37	and	and	CCONJ
ajst-21789	95	38	the	the	DET
ajst-21789	95	39	weight	weight	NOUN
ajst-21789	95	40	of	of	ADP
ajst-21789	95	41	each	each	DET
ajst-21789	95	42	layer	layer	NOUN
ajst-21789	95	43	is	be	AUX
ajst-21789	95	44	modified	modify	VERB
ajst-21789	95	45	.	.	PUNCT
ajst-21789	96	1	the	the	DET
ajst-21789	96	2	number	number	NOUN
ajst-21789	96	3	of	of	ADP
ajst-21789	96	4	hidden	hide	VERB
ajst-21789	96	5	layer	layer	NOUN
ajst-21789	96	6	neurons	neuron	NOUN
ajst-21789	96	7	can	can	AUX
ajst-21789	96	8	be	be	AUX
ajst-21789	96	9	calculated	calculate	VERB
ajst-21789	96	10	by	by	ADP
ajst-21789	96	11	empirical	empirical	ADJ
ajst-21789	96	12	formula	formula	NOUN
ajst-21789	96	13	(	(	PUNCT
ajst-21789	96	14	13	13	NUM
ajst-21789	96	15	)	)	PUNCT
ajst-21789	97	1	[	[	X
ajst-21789	97	2	24	24	NUM
ajst-21789	97	3	]	]	X
ajst-21789	97	4	:	:	PUNCT
ajst-21789	97	5	(	(	PUNCT
ajst-21789	97	6	13	13	NUM
ajst-21789	97	7	)	)	PUNCT
ajst-21789	97	8	where	where	SCONJ
ajst-21789	97	9	:	:	PUNCT
ajst-21789	97	10	a	a	PRON
ajst-21789	97	11	is	be	AUX
ajst-21789	97	12	the	the	DET
ajst-21789	97	13	number	number	NOUN
ajst-21789	97	14	of	of	ADP
ajst-21789	97	15	hidden	hide	VERB
ajst-21789	97	16	layer	layer	NOUN
ajst-21789	97	17	nodes	node	NOUN
ajst-21789	97	18	;	;	PUNCT
ajst-21789	97	19	h	h	NOUN
ajst-21789	97	20	is	be	AUX
ajst-21789	97	21	the	the	DET
ajst-21789	97	22	number	number	NOUN
ajst-21789	97	23	of	of	ADP
ajst-21789	97	24	nodes	node	NOUN
ajst-21789	97	25	in	in	ADP
ajst-21789	97	26	the	the	DET
ajst-21789	97	27	output	output	NOUN
ajst-21789	97	28	layer	layer	NOUN
ajst-21789	97	29	;	;	PUNCT
ajst-21789	97	30	c	c	NOUN
ajst-21789	97	31	is	be	AUX
ajst-21789	97	32	the	the	DET
ajst-21789	97	33	number	number	NOUN
ajst-21789	97	34	of	of	ADP
ajst-21789	97	35	nodes	node	NOUN
ajst-21789	97	36	in	in	ADP
ajst-21789	97	37	the	the	DET
ajst-21789	97	38	input	input	NOUN
ajst-21789	97	39	layer	layer	NOUN
ajst-21789	97	40	;	;	PUNCT
ajst-21789	97	41	d	d	X
ajst-21789	97	42	is	be	AUX
ajst-21789	97	43	the	the	DET
ajst-21789	97	44	adjustment	adjustment	NOUN
ajst-21789	97	45	constant	constant	ADJ
ajst-21789	97	46	,	,	PUNCT
ajst-21789	97	47	generally	generally	ADV
ajst-21789	97	48	1,2	1,2	NUM
ajst-21789	97	49	,	,	PUNCT
ajst-21789	97	50	...	...	PUNCT
ajst-21789	98	1	10	10	NUM
ajst-21789	98	2	.	.	X
ajst-21789	98	3	3.3	3.3	NUM
ajst-21789	98	4	.	.	PUNCT
ajst-21789	99	1	calculation	calculation	NOUN
ajst-21789	99	2	steps	step	NOUN
ajst-21789	99	3	of	of	ADP
ajst-21789	99	4	cpso	cpso	NOUN
ajst-21789	99	5	-	-	PUNCT
ajst-21789	99	6	bp	bp	PROPN
ajst-21789	99	7	model	model	NOUN
ajst-21789	99	8	step	step	NOUN
ajst-21789	99	9	1	1	NUM
ajst-21789	99	10	:	:	PUNCT
ajst-21789	99	11	data	datum	NOUN
ajst-21789	99	12	normalization	normalization	NOUN
ajst-21789	99	13	,	,	PUNCT
ajst-21789	99	14	establish	establish	VERB
ajst-21789	99	15	bp	bp	PROPN
ajst-21789	99	16	neural	neural	ADJ
ajst-21789	99	17	network	network	NOUN
ajst-21789	99	18	structure	structure	NOUN
ajst-21789	99	19	;	;	PUNCT
ajst-21789	99	20	step	step	NOUN
ajst-21789	99	21	2	2	NUM
ajst-21789	99	22	:	:	PUNCT
ajst-21789	99	23	set	set	VERB
ajst-21789	99	24	the	the	DET
ajst-21789	99	25	particle	particle	NOUN
ajst-21789	99	26	swarm	swarm	NOUN
ajst-21789	99	27	hyperparameters	hyperparameter	NOUN
ajst-21789	99	28	;	;	PUNCT
ajst-21789	99	29	step	step	NOUN
ajst-21789	99	30	3	3	NUM
ajst-21789	99	31	:	:	PUNCT
ajst-21789	99	32	conduct	conduct	VERB
ajst-21789	99	33	training	training	NOUN
ajst-21789	99	34	according	accord	VERB
ajst-21789	99	35	to	to	AUX
ajst-21789	99	36	mean	mean	VERB
ajst-21789	99	37	square	square	ADJ
ajst-21789	99	38	error	error	NOUN
ajst-21789	99	39	as	as	ADP
ajst-21789	99	40	fitness	fitness	NOUN
ajst-21789	99	41	function	function	NOUN
ajst-21789	99	42	of	of	ADP
ajst-21789	99	43	cp	cp	PROPN
ajst-21789	99	44	-	-	PUNCT
ajst-21789	99	45	so	so	ADV
ajst-21789	99	46	objective	objective	ADJ
ajst-21789	99	47	function	function	NOUN
ajst-21789	99	48	(	(	PUNCT
ajst-21789	99	49	mse	mse	NOUN
ajst-21789	99	50	,	,	PUNCT
ajst-21789	99	51	as	as	SCONJ
ajst-21789	99	52	shown	show	VERB
ajst-21789	99	53	in	in	ADP
ajst-21789	99	54	equation	equation	NOUN
ajst-21789	99	55	(	(	PUNCT
ajst-21789	99	56	14	14	NUM
ajst-21789	99	57	)	)	PUNCT
ajst-21789	99	58	)	)	PUNCT
ajst-21789	99	59	,	,	PUNCT
ajst-21789	99	60	iteratively	iteratively	ADV
ajst-21789	99	61	optimize	optimize	VERB
ajst-21789	99	62	the	the	DET
ajst-21789	99	63	weights	weight	NOUN
ajst-21789	99	64	and	and	CCONJ
ajst-21789	99	65	thresholds	threshold	NOUN
ajst-21789	99	66	of	of	ADP
ajst-21789	99	67	bp	bp	PROPN
ajst-21789	99	68	algorithm	algorithm	PROPN
ajst-21789	99	69	;	;	PUNCT
ajst-21789	99	70	(	(	PUNCT
ajst-21789	99	71	14	14	NUM
ajst-21789	99	72	)	)	PUNCT
ajst-21789	99	73	where	where	SCONJ
ajst-21789	99	74	:	:	PUNCT
ajst-21789	99	75	is	be	AUX
ajst-21789	99	76	the	the	DET
ajst-21789	99	77	predicted	predict	VERB
ajst-21789	99	78	value	value	NOUN
ajst-21789	99	79	of	of	ADP
ajst-21789	99	80	the	the	DET
ajst-21789	99	81	training	training	NOUN
ajst-21789	99	82	group	group	NOUN
ajst-21789	99	83	,	,	PUNCT
ajst-21789	99	84	is	be	AUX
ajst-21789	99	85	the	the	DET
ajst-21789	99	86	actual	actual	ADJ
ajst-21789	99	87	value	value	NOUN
ajst-21789	99	88	of	of	ADP
ajst-21789	99	89	the	the	DET
ajst-21789	99	90	training	training	NOUN
ajst-21789	99	91	group	group	NOUN
ajst-21789	99	92	.	.	PUNCT
ajst-21789	100	1	step	step	NOUN
ajst-21789	100	2	4	4	NUM
ajst-21789	100	3	:	:	PUNCT
ajst-21789	100	4	calculate	calculate	VERB
ajst-21789	100	5	the	the	DET
ajst-21789	100	6	fitness	fitness	NOUN
ajst-21789	100	7	value	value	NOUN
ajst-21789	100	8	of	of	ADP
ajst-21789	100	9	the	the	DET
ajst-21789	100	10	particle	particle	NOUN
ajst-21789	100	11	swarm	swarm	NOUN
ajst-21789	100	12	,	,	PUNCT
ajst-21789	100	13	compare	compare	VERB
ajst-21789	100	14	and	and	CCONJ
ajst-21789	100	15	update	update	VERB
ajst-21789	100	16	the	the	DET
ajst-21789	100	17	sum	sum	NOUN
ajst-21789	100	18	after	after	ADP
ajst-21789	100	19	each	each	DET
ajst-21789	100	20	calculation	calculation	NOUN
ajst-21789	100	21	,	,	PUNCT
ajst-21789	100	22	and	and	CCONJ
ajst-21789	100	23	bring	bring	VERB
ajst-21789	100	24	the	the	DET
ajst-21789	100	25	speed	speed	NOUN
ajst-21789	100	26	and	and	CCONJ
ajst-21789	100	27	position	position	NOUN
ajst-21789	100	28	of	of	ADP
ajst-21789	100	29	updating	update	VERB
ajst-21789	100	30	the	the	DET
ajst-21789	100	31	particle	particle	NOUN
ajst-21789	100	32	swarm	swarm	NOUN
ajst-21789	100	33	into	into	ADP
ajst-21789	100	34	equation	equation	NOUN
ajst-21789	100	35	(	(	PUNCT
ajst-21789	100	36	9	9	NUM
ajst-21789	100	37	)	)	PUNCT
ajst-21789	100	38	and	and	CCONJ
ajst-21789	100	39	equation	equation	NOUN
ajst-21789	100	40	(	(	PUNCT
ajst-21789	100	41	2	2	NUM
ajst-21789	100	42	)	)	PUNCT
ajst-21789	100	43	until	until	SCONJ
ajst-21789	100	44	the	the	DET
ajst-21789	100	45	required	require	VERB
ajst-21789	100	46	accuracy	accuracy	NOUN
ajst-21789	100	47	or	or	CCONJ
ajst-21789	100	48	number	number	NOUN
ajst-21789	100	49	of	of	ADP
ajst-21789	100	50	iterations	iteration	NOUN
ajst-21789	100	51	are	be	AUX
ajst-21789	100	52	reached	reach	VERB
ajst-21789	100	53	,	,	PUNCT
ajst-21789	100	54	and	and	CCONJ
ajst-21789	100	55	the	the	DET
ajst-21789	100	56	final	final	ADJ
ajst-21789	100	57	,	,	PUNCT
ajst-21789	100	58	namely	namely	ADV
ajst-21789	100	59	the	the	DET
ajst-21789	100	60	optimal	optimal	ADJ
ajst-21789	100	61	weight	weight	NOUN
ajst-21789	100	62	value	value	NOUN
ajst-21789	100	63	and	and	CCONJ
ajst-21789	100	64	threshold	threshold	NOUN
ajst-21789	100	65	value	value	NOUN
ajst-21789	100	66	are	be	AUX
ajst-21789	100	67	obtained	obtain	VERB
ajst-21789	100	68	;	;	PUNCT
ajst-21789	100	69	step	step	NOUN
ajst-21789	100	70	5	5	NUM
ajst-21789	100	71	:	:	PUNCT
ajst-21789	100	72	bring	bring	VERB
ajst-21789	100	73	the	the	DET
ajst-21789	100	74	test	test	NOUN
ajst-21789	100	75	group	group	NOUN
ajst-21789	100	76	data	datum	NOUN
ajst-21789	100	77	into	into	ADP
ajst-21789	100	78	the	the	DET
ajst-21789	100	79	updated	update	VERB
ajst-21789	100	80	bp	bp	PROPN
ajst-21789	100	81	neural	neural	ADJ
ajst-21789	100	82	network	network	NOUN
ajst-21789	100	83	for	for	ADP
ajst-21789	100	84	calculation	calculation	NOUN
ajst-21789	100	85	until	until	SCONJ
ajst-21789	100	86	the	the	DET
ajst-21789	100	87	number	number	NOUN
ajst-21789	100	88	of	of	ADP
ajst-21789	100	89	iterations	iteration	NOUN
ajst-21789	100	90	ends	end	NOUN
ajst-21789	100	91	or	or	CCONJ
ajst-21789	100	92	the	the	DET
ajst-21789	100	93	error	error	NOUN
ajst-21789	100	94	condition	condition	NOUN
ajst-21789	100	95	is	be	AUX
ajst-21789	100	96	reached	reach	VERB
ajst-21789	100	97	,	,	PUNCT
ajst-21789	100	98	and	and	CCONJ
ajst-21789	100	99	the	the	DET
ajst-21789	100	100	predicted	predict	VERB
ajst-21789	100	101	results	result	NOUN
ajst-21789	100	102	are	be	AUX
ajst-21789	100	103	output	output	NOUN
ajst-21789	100	104	.	.	PUNCT
ajst-21789	101	1	4	4	X
ajst-21789	101	2	.	.	X
ajst-21789	101	3	ipca	ipca	NOUN
ajst-21789	101	4	-	-	PUNCT
ajst-21789	101	5	cpso	cpso	NOUN
ajst-21789	101	6	-	-	PUNCT
ajst-21789	101	7	bp	bp	PROPN
ajst-21789	101	8	model	model	NOUN
ajst-21789	101	9	application	application	NOUN
ajst-21789	101	10	4.1	4.1	NUM
ajst-21789	101	11	.	.	PUNCT
ajst-21789	102	1	ipca	ipca	PROPN
ajst-21789	102	2	principal	principal	ADJ
ajst-21789	102	3	component	component	NOUN
ajst-21789	102	4	analysis	analysis	NOUN
ajst-21789	102	5	through	through	ADP
ajst-21789	102	6	matlab	matlab	PROPN
ajst-21789	102	7	software	software	NOUN
ajst-21789	102	8	programming	programming	NOUN
ajst-21789	102	9	,	,	PUNCT
ajst-21789	102	10	the	the	DET
ajst-21789	102	11	ipca	ipca	PROPN
ajst-21789	102	12	algorithm	algorithm	PROPN
ajst-21789	102	13	was	be	AUX
ajst-21789	102	14	used	use	VERB
ajst-21789	102	15	to	to	PART
ajst-21789	102	16	reduce	reduce	VERB
ajst-21789	102	17	the	the	DET
ajst-21789	102	18	dimensionality	dimensionality	NOUN
ajst-21789	102	19	of	of	ADP
ajst-21789	102	20	the	the	DET
ajst-21789	102	21	original	original	ADJ
ajst-21789	102	22	data	datum	NOUN
ajst-21789	102	23	,	,	PUNCT
ajst-21789	102	24	and	and	CCONJ
ajst-21789	102	25	three	three	NUM
ajst-21789	102	26	principal	principal	ADJ
ajst-21789	102	27	component	component	NOUN
ajst-21789	102	28	feature	feature	NOUN
ajst-21789	102	29	variables	variable	NOUN
ajst-21789	102	30	were	be	AUX
ajst-21789	102	31	obtained	obtain	VERB
ajst-21789	102	32	.	.	PUNCT
ajst-21789	103	1	the	the	DET
ajst-21789	103	2	eigenvector	eigenvector	NOUN
ajst-21789	103	3	data	datum	NOUN
ajst-21789	103	4	of	of	ADP
ajst-21789	103	5	the	the	DET
ajst-21789	103	6	principal	principal	ADJ
ajst-21789	103	7	component	component	NOUN
ajst-21789	103	8	about	about	ADP
ajst-21789	103	9	the	the	DET
ajst-21789	103	10	impact	impact	NOUN
ajst-21789	103	11	factor	factor	NOUN
ajst-21789	103	12	are	be	AUX
ajst-21789	103	13	shown	show	VERB
ajst-21789	103	14	in	in	ADP
ajst-21789	103	15	table	table	NOUN
ajst-21789	103	16	3	3	NUM
ajst-21789	103	17	:	:	PUNCT
ajst-21789	103	18	table	table	NOUN
ajst-21789	103	19	3	3	NUM
ajst-21789	103	20	.	.	PUNCT
ajst-21789	103	21	improved	improve	VERB
ajst-21789	103	22	principal	principal	ADJ
ajst-21789	103	23	component	component	NOUN
ajst-21789	103	24	factor	factor	NOUN
ajst-21789	103	25	component	component	NOUN
ajst-21789	103	26	data	datum	NOUN
ajst-21789	103	27	influence	influence	NOUN
ajst-21789	103	28	factor	factor	NOUN
ajst-21789	103	29	f1	f1	NOUN
ajst-21789	103	30	f2	f2	PROPN
ajst-21789	103	31	f3	f3	PROPN
ajst-21789	103	32	x1	x1	PROPN
ajst-21789	103	33	0.0015	0.0015	NUM
ajst-21789	103	34	0.0008	0.0008	NUM
ajst-21789	103	35	-0.0011	-0.0011	PUNCT
ajst-21789	104	1	x2	x2	PROPN
ajst-21789	104	2	0.0024	0.0024	NUM
ajst-21789	104	3	0.0017	0.0017	NUM
ajst-21789	104	4	-0.0030	-0.0030	NOUN
ajst-21789	104	5	x3	x3	NOUN
ajst-21789	104	6	0.0088	0.0088	NUM
ajst-21789	104	7	0.0047	0.0047	NUM
ajst-21789	104	8	-0.0073	-0.0073	NOUN
ajst-21789	105	1	x4	x4	PROPN
ajst-21789	105	2	0.0038	0.0038	PROPN
ajst-21789	105	3	0.0064	0.0064	NUM
ajst-21789	105	4	-0.0088	-0.0088	NOUN
ajst-21789	105	5	x5	x5	PROPN
ajst-21789	105	6	-0.9266	-0.9266	PROPN
ajst-21789	105	7	0.3524	0.3524	NUM
ajst-21789	105	8	0.0779	0.0779	NUM
ajst-21789	105	9	x6	x6	PROPN
ajst-21789	105	10	0.0343	0.0343	NUM
ajst-21789	105	11	-0.1115	-0.1115	NOUN
ajst-21789	105	12	0.9913	0.9913	NUM
ajst-21789	105	13	x7	x7	NOUN
ajst-21789	105	14	0.0066	0.0066	PROPN
ajst-21789	105	15	0.0077	0.0077	NUM
ajst-21789	105	16	-0.0013	-0.0013	PROPN
ajst-21789	105	17	x8	x8	PROPN
ajst-21789	105	18	0.0008	0.0008	NUM
ajst-21789	105	19	0.0009	0.0009	NUM
ajst-21789	105	20	-0.0001	-0.0001	NOUN
ajst-21789	105	21	x9	x9	PROPN
ajst-21789	105	22	0.0046	0.0046	NUM
ajst-21789	105	23	-0.0068	-0.0068	NOUN
ajst-21789	105	24	-0.0079	-0.0079	NOUN
ajst-21789	105	25	x10	x10	ADP
ajst-21789	105	26	0.1036	0.1036	NUM
ajst-21789	105	27	-0.0358	-0.0358	PROPN
ajst-21789	105	28	0.0520	0.0520	NUM
ajst-21789	105	29	x11	x11	NOUN
ajst-21789	105	30	-0.3597	-0.3597	PROPN
ajst-21789	105	31	-0.9284	-0.9284	NOUN
ajst-21789	105	32	-0.0916	-0.0916	PROPN
ajst-21789	106	1	x12	x12	NUM
ajst-21789	107	1	0.0035	0.0035	NUM
ajst-21789	107	2	0.0084	0.0084	NUM
ajst-21789	107	3	-0.0071	-0.0071	NOUN
ajst-21789	107	4	x13	x13	PROPN
ajst-21789	107	5	0.0024	0.0024	NUM
ajst-21789	107	6	0.0015	0.0015	NUM
ajst-21789	107	7	0.0004	0.0004	NUM
ajst-21789	107	8	the	the	DET
ajst-21789	107	9	three	three	NUM
ajst-21789	107	10	principal	principal	ADJ
ajst-21789	107	11	components	component	NOUN
ajst-21789	107	12	obtained	obtain	VERB
ajst-21789	107	13	after	after	ADP
ajst-21789	107	14	dimensionality	dimensionality	NOUN
ajst-21789	107	15	reduction	reduction	NOUN
ajst-21789	107	16	by	by	ADP
ajst-21789	107	17	improved	improve	VERB
ajst-21789	107	18	principal	principal	ADJ
ajst-21789	107	19	component	component	NOUN
ajst-21789	107	20	analysis	analysis	NOUN
ajst-21789	107	21	become	become	VERB
ajst-21789	107	22	new	new	ADJ
ajst-21789	107	23	prediction	prediction	NOUN
ajst-21789	107	24	indexes	index	NOUN
ajst-21789	107	25	for	for	ADP
ajst-21789	107	26	gas	gas	NOUN
ajst-21789	107	27	emission	emission	NOUN
ajst-21789	107	28	prediction	prediction	NOUN
ajst-21789	107	29	.	.	PUNCT
ajst-21789	108	1	as	as	SCONJ
ajst-21789	108	2	can	can	AUX
ajst-21789	108	3	be	be	AUX
ajst-21789	108	4	seen	see	VERB
ajst-21789	108	5	in	in	ADP
ajst-21789	108	6	table	table	NOUN
ajst-21789	108	7	3.3	3.3	NUM
ajst-21789	108	8	of	of	ADP
ajst-21789	108	9	the	the	DET
ajst-21789	108	10	data	datum	NOUN
ajst-21789	108	11	obtained	obtain	VERB
ajst-21789	108	12	by	by	ADP
ajst-21789	108	13	matlab	matlab	PROPN
ajst-21789	108	14	analysis	analysis	NOUN
ajst-21789	108	15	,	,	PUNCT
ajst-21789	108	16	the	the	DET
ajst-21789	108	17	data	data	NOUN
ajst-21789	108	18	information	information	NOUN
ajst-21789	108	19	in	in	ADP
ajst-21789	108	20	the	the	DET
ajst-21789	108	21	first	first	ADJ
ajst-21789	108	22	principal	principal	ADJ
ajst-21789	108	23	component	component	NOUN
ajst-21789	108	24	mainly	mainly	ADV
ajst-21789	108	25	includes	include	VERB
ajst-21789	108	26	the	the	DET
ajst-21789	108	27	degree	degree	NOUN
ajst-21789	108	28	of	of	ADP
ajst-21789	108	29	advancement	advancement	NOUN
ajst-21789	108	30	of	of	ADP
ajst-21789	108	31	mining	mining	NOUN
ajst-21789	108	32	coal	coal	NOUN
ajst-21789	108	33	seam	seam	NOUN
ajst-21789	108	34	,	,	PUNCT
ajst-21789	108	35	coal	coal	NOUN
ajst-21789	108	36	thickness	thickness	NOUN
ajst-21789	108	37	,	,	PUNCT
ajst-21789	108	38	recovery	recovery	NOUN
ajst-21789	108	39	rate	rate	NOUN
ajst-21789	108	40	,	,	PUNCT
ajst-21789	108	41	mining	mining	NOUN
ajst-21789	108	42	height	height	NOUN
ajst-21789	108	43	,	,	PUNCT
ajst-21789	108	44	recovery	recovery	NOUN
ajst-21789	108	45	amount	amount	NOUN
ajst-21789	108	46	and	and	CCONJ
ajst-21789	108	47	gas	gas	NOUN
ajst-21789	108	48	content	content	NOUN
ajst-21789	108	49	of	of	ADP
ajst-21789	108	50	mining	mining	NOUN
ajst-21789	108	51	coal	coal	NOUN
ajst-21789	108	52	seam	seam	NOUN
ajst-21789	108	53	in	in	ADP
ajst-21789	108	54	the	the	DET
ajst-21789	108	55	original	original	ADJ
ajst-21789	108	56	prediction	prediction	NOUN
ajst-21789	108	57	index	index	NOUN
ajst-21789	108	58	.	.	PUNCT
ajst-21789	109	1	the	the	DET
ajst-21789	109	2	second	second	ADJ
ajst-21789	109	3	principal	principal	ADJ
ajst-21789	109	4	component	component	NOUN
ajst-21789	109	5	includes	include	VERB
ajst-21789	109	6	the	the	DET
ajst-21789	109	7	underground	underground	ADJ
ajst-21789	109	8	pressure	pressure	NOUN
ajst-21789	109	9	,	,	PUNCT
ajst-21789	109	10	the	the	DET
ajst-21789	109	11	spacing	spacing	NOUN
ajst-21789	109	12	of	of	ADP
ajst-21789	109	13	adjacent	adjacent	ADJ
ajst-21789	109	14	coal	coal	NOUN
ajst-21789	109	15	seams	seam	NOUN
ajst-21789	109	16	,	,	PUNCT
ajst-21789	109	17	the	the	DET
ajst-21789	109	18	inclination	inclination	NOUN
ajst-21789	109	19	of	of	ADP
ajst-21789	109	20	coal	coal	NOUN
ajst-21789	109	21	seams	seam	NOUN
ajst-21789	109	22	and	and	CCONJ
ajst-21789	109	23	the	the	DET
ajst-21789	109	24	gas	gas	NOUN
ajst-21789	109	25	content	content	NOUN
ajst-21789	109	26	of	of	ADP
ajst-21789	109	27	adjacent	adjacent	ADJ
ajst-21789	109	28	layers	layer	NOUN
ajst-21789	109	29	.	.	PUNCT
ajst-21789	110	1	the	the	DET
ajst-21789	110	2	third	third	ADJ
ajst-21789	110	3	principal	principal	ADJ
ajst-21789	110	4	component	component	NOUN
ajst-21789	110	5	includes	include	VERB
ajst-21789	110	6	burial	burial	NOUN
ajst-21789	110	7	depth	depth	NOUN
ajst-21789	110	8	,	,	PUNCT
ajst-21789	110	9	temperature	temperature	NOUN
ajst-21789	110	10	and	and	CCONJ
ajst-21789	110	11	air	air	NOUN
ajst-21789	110	12	volume	volume	NOUN
ajst-21789	110	13	.	.	PUNCT
ajst-21789	111	1	4.2	4.2	NUM
ajst-21789	111	2	.	.	PUNCT
ajst-21789	111	3	parameter	parameter	NOUN
ajst-21789	111	4	setting	set	VERB
ajst-21789	111	5	the	the	DET
ajst-21789	111	6	five	five	NUM
ajst-21789	111	7	algorithms	algorithm	NOUN
ajst-21789	111	8	bp	bp	PROPN
ajst-21789	111	9	,	,	PUNCT
ajst-21789	111	10	pso	pso	NOUN
ajst-21789	111	11	-	-	PUNCT
ajst-21789	111	12	bp	bp	PROPN
ajst-21789	111	13	,	,	PUNCT
ajst-21789	111	14	pca	pca	NOUN
ajst-21789	111	15	-	-	PUNCT
ajst-21789	111	16	pso	pso	NOUN
ajst-21789	111	17	-	-	PUNCT
ajst-21789	111	18	bp	bp	PROPN
ajst-21789	111	19	,	,	PUNCT
ajst-21789	111	20	ipcapso	ipcapso	NOUN
ajst-21789	111	21	-	-	PUNCT
ajst-21789	111	22	bp	bp	PROPN
ajst-21789	111	23	and	and	CCONJ
ajst-21789	111	24	ipca	ipca	PROPN
ajst-21789	111	25	-	-	PUNCT
ajst-21789	111	26	cpso	cpso	NOUN
ajst-21789	111	27	-	-	PUNCT
ajst-21789	111	28	bp	bp	PROPN
ajst-21789	111	29	were	be	AUX
ajst-21789	111	30	programmed	program	VERB
ajst-21789	111	31	and	and	CCONJ
ajst-21789	111	32	calculated	calculate	VERB
ajst-21789	111	33	with	with	ADP
ajst-21789	111	34	matlab	matlab	PROPN
ajst-21789	111	35	software	software	PROPN
ajst-21789	111	36	.	.	PUNCT
ajst-21789	112	1	bp	bp	PROPN
ajst-21789	112	2	neural	neural	PROPN
ajst-21789	112	3	network	network	NOUN
ajst-21789	112	4	was	be	AUX
ajst-21789	112	5	constructed	construct	VERB
ajst-21789	112	6	with	with	ADP
ajst-21789	112	7	newff	newff	PROPN
ajst-21789	112	8	function	function	PROPN
ajst-21789	112	9	,	,	PUNCT
ajst-21789	112	10	with	with	ADP
ajst-21789	112	11	the	the	DET
ajst-21789	112	12	maximum	maximum	ADJ
ajst-21789	112	13	training	training	NOUN
ajst-21789	112	14	times	time	NOUN
ajst-21789	112	15	of	of	ADP
ajst-21789	112	16	1000	1000	NUM
ajst-21789	112	17	and	and	CCONJ
ajst-21789	112	18	the	the	DET
ajst-21789	112	19	learning	learning	NOUN
ajst-21789	112	20	rate	rate	NOUN
ajst-21789	112	21	of	of	ADP
ajst-21789	112	22	0.01	0.01	NUM
ajst-21789	112	23	.	.	PUNCT
ajst-21789	113	1	training	training	NOUN
ajst-21789	113	2	requires	require	VERB
ajst-21789	113	3	an	an	DET
ajst-21789	113	4	accuracy	accuracy	NOUN
ajst-21789	113	5	of	of	ADP
ajst-21789	113	6	0.000001	0.000001	NUM
ajst-21789	113	7	.	.	PUNCT
ajst-21789	114	1	set	set	VERB
ajst-21789	114	2	groups	group	NOUN
ajst-21789	114	3	1	1	NUM
ajst-21789	114	4	-	-	SYM
ajst-21789	114	5	25	25	NUM
ajst-21789	114	6	as	as	ADP
ajst-21789	114	7	the	the	DET
ajst-21789	114	8	training	training	NOUN
ajst-21789	114	9	group	group	NOUN
ajst-21789	114	10	,	,	PUNCT
ajst-21789	114	11	26	26	NUM
ajst-21789	114	12	-	-	SYM
ajst-21789	114	13	30	30	NUM
ajst-21789	114	14	as	as	ADP
ajst-21789	114	15	the	the	DET
ajst-21789	114	16	test	test	NOUN
ajst-21789	114	17	group	group	NOUN
ajst-21789	114	18	,	,	PUNCT
ajst-21789	114	19	the	the	DET
ajst-21789	114	20	input	input	NOUN
ajst-21789	114	21	,	,	PUNCT
ajst-21789	114	22	hidden	hidden	ADJ
ajst-21789	114	23	and	and	CCONJ
ajst-21789	114	24	output	output	NOUN
ajst-21789	114	25	layers	layer	NOUN
ajst-21789	114	26	of	of	ADP
ajst-21789	114	27	the	the	DET
ajst-21789	114	28	first	first	ADJ
ajst-21789	114	29	two	two	NUM
ajst-21789	114	30	groups	group	NOUN
ajst-21789	114	31	as	as	ADP
ajst-21789	114	32	13	13	NUM
ajst-21789	114	33	,	,	PUNCT
ajst-21789	114	34	11	11	NUM
ajst-21789	114	35	and	and	CCONJ
ajst-21789	114	36	1	1	NUM
ajst-21789	114	37	,	,	PUNCT
ajst-21789	114	38	the	the	DET
ajst-21789	114	39	third	third	ADJ
ajst-21789	114	40	group	group	NOUN
ajst-21789	114	41	as	as	ADP
ajst-21789	114	42	8	8	NUM
ajst-21789	114	43	,	,	PUNCT
ajst-21789	114	44	9	9	NUM
ajst-21789	114	45	and	and	CCONJ
ajst-21789	114	46	1	1	NUM
ajst-21789	114	47	,	,	PUNCT
ajst-21789	114	48	and	and	CCONJ
ajst-21789	114	49	the	the	DET
ajst-21789	114	50	last	last	ADJ
ajst-21789	114	51	two	two	NUM
ajst-21789	114	52	groups	group	NOUN
ajst-21789	114	53	as	as	ADP
ajst-21789	114	54	4	4	NUM
ajst-21789	114	55	,	,	PUNCT
ajst-21789	114	56	6	6	NUM
ajst-21789	114	57	and	and	CCONJ
ajst-21789	114	58	1	1	NUM
ajst-21789	114	59	.	.	X
ajst-21789	114	60	4.3	4.3	NUM
ajst-21789	114	61	.	.	PUNCT
ajst-21789	115	1	prediction	prediction	NOUN
ajst-21789	115	2	result	result	NOUN
ajst-21789	115	3	analysis	analysis	NOUN
ajst-21789	115	4	the	the	DET
ajst-21789	115	5	predicted	predict	VERB
ajst-21789	115	6	values	value	NOUN
ajst-21789	115	7	and	and	CCONJ
ajst-21789	115	8	relative	relative	ADJ
ajst-21789	115	9	errors	error	NOUN
ajst-21789	115	10	(	(	PUNCT
ajst-21789	115	11	hereinafter	hereinafter	NOUN
ajst-21789	115	12	referred	refer	VERB
ajst-21789	115	13	to	to	ADP
ajst-21789	115	14	as	as	ADP
ajst-21789	115	15	errors	error	NOUN
ajst-21789	115	16	)	)	PUNCT
ajst-21789	115	17	of	of	ADP
ajst-21789	115	18	the	the	DET
ajst-21789	115	19	model	model	NOUN
ajst-21789	115	20	are	be	AUX
ajst-21789	115	21	shown	show	VERB
ajst-21789	115	22	in	in	ADP
ajst-21789	115	23	table	table	NOUN
ajst-21789	115	24	4	4	NUM
ajst-21789	115	25	:	:	SYM
ajst-21789	115	26	202	202	NUM
ajst-21789	115	27	table	table	NOUN
ajst-21789	115	28	4	4	NUM
ajst-21789	115	29	.	.	PUNCT
ajst-21789	115	30	test	test	NOUN
ajst-21789	115	31	data	data	PROPN
ajst-21789	115	32	results	result	VERB
ajst-21789	115	33	group	group	NOUN
ajst-21789	115	34	actual	actual	ADJ
ajst-21789	115	35	value	value	NOUN
ajst-21789	115	36	bp	bp	PROPN
ajst-21789	115	37	pso	pso	PROPN
ajst-21789	115	38	-	-	PUNCT
ajst-21789	115	39	bp	bp	PROPN
ajst-21789	115	40	pca	pca	PROPN
ajst-21789	115	41	-	-	PUNCT
ajst-21789	115	42	pso	pso	NOUN
ajst-21789	115	43	-	-	PUNCT
ajst-21789	115	44	bp	bp	PROPN
ajst-21789	115	45	ipca	ipca	PROPN
ajst-21789	115	46	-	-	PUNCT
ajst-21789	115	47	pso	pso	NOUN
ajst-21789	115	48	-	-	PUNCT
ajst-21789	115	49	bp	bp	PROPN
ajst-21789	115	50	ipca	ipca	PROPN
ajst-21789	115	51	-	-	PUNCT
ajst-21789	115	52	cpso	cpso	NOUN
ajst-21789	115	53	-	-	PUNCT
ajst-21789	115	54	bp	bp	PROPN
ajst-21789	115	55	forecast	forecast	NOUN
ajst-21789	115	56	error	error	NOUN
ajst-21789	115	57	forecast	forecast	NOUN
ajst-21789	115	58	error	error	NOUN
ajst-21789	115	59	forecast	forecast	NOUN
ajst-21789	115	60	error	error	NOUN
ajst-21789	115	61	forecast	forecast	NOUN
ajst-21789	115	62	error	error	NOUN
ajst-21789	115	63	forecast	forecast	NOUN
ajst-21789	115	64	error	error	NOUN
ajst-21789	115	65	26	26	NUM
ajst-21789	115	66	16.5	16.5	NUM
ajst-21789	115	67	17.0189	17.0189	NUM
ajst-21789	115	68	0.5189	0.5189	NUM
ajst-21789	115	69	16.7819	16.7819	NUM
ajst-21789	115	70	0.2819	0.2819	NUM
ajst-21789	115	71	16.6531	16.6531	NUM
ajst-21789	115	72	0.1531	0.1531	NUM
ajst-21789	115	73	16.4495	16.4495	NUM
ajst-21789	115	74	0.0505	0.0505	NUM
ajst-21789	115	75	16.6748	16.6748	NUM
ajst-21789	115	76	0.1748	0.1748	NUM
ajst-21789	115	77	27	27	NUM
ajst-21789	115	78	15.0	15.0	NUM
ajst-21789	115	79	14.8042	14.8042	NUM
ajst-21789	115	80	0.1958	0.1958	NUM
ajst-21789	115	81	15.4738	15.4738	NUM
ajst-21789	115	82	0.4738	0.4738	NUM
ajst-21789	115	83	15.2683	15.2683	NUM
ajst-21789	115	84	0.2683	0.2683	NUM
ajst-21789	115	85	15.0076	15.0076	NUM
ajst-21789	115	86	0.0076	0.0076	NUM
ajst-21789	115	87	14.9129	14.9129	NUM
ajst-21789	115	88	0.0871	0.0871	NUM
ajst-21789	115	89	28	28	NUM
ajst-21789	115	90	15.0	15.0	NUM
ajst-21789	115	91	15.0634	15.0634	NUM
ajst-21789	115	92	0.0634	0.0634	NUM
ajst-21789	115	93	15.0536	15.0536	NUM
ajst-21789	115	94	0.0536	0.0536	NUM
ajst-21789	115	95	15.3371	15.3371	NUM
ajst-21789	115	96	0.3371	0.3371	NUM
ajst-21789	115	97	14.7403	14.7403	NUM
ajst-21789	115	98	0.2597	0.2597	NUM
ajst-21789	115	99	14.9802	14.9802	NUM
ajst-21789	115	100	0.0198	0.0198	NUM
ajst-21789	115	101	29	29	NUM
ajst-21789	115	102	16.5	16.5	NUM
ajst-21789	115	103	16.6096	16.6096	NUM
ajst-21789	115	104	0.1096	0.1096	NUM
ajst-21789	115	105	16.7949	16.7949	NUM
ajst-21789	115	106	0.2949	0.2949	NUM
ajst-21789	115	107	16.3260	16.3260	NUM
ajst-21789	115	108	0.1740	0.1740	NUM
ajst-21789	115	109	16.1537	16.1537	NUM
ajst-21789	115	110	0.3463	0.3463	NUM
ajst-21789	115	111	16.3371	16.3371	NUM
ajst-21789	115	112	0.1629	0.1629	NUM
ajst-21789	115	113	30	30	NUM
ajst-21789	115	114	15.0	15.0	NUM
ajst-21789	115	115	14.5828	14.5828	NUM
ajst-21789	115	116	0.4172	0.4172	NUM
ajst-21789	115	117	14.9649	14.9649	NUM
ajst-21789	115	118	0.0351	0.0351	NUM
ajst-21789	115	119	15.2247	15.2247	NUM
ajst-21789	115	120	0.2247	0.2247	NUM
ajst-21789	115	121	15.2073	15.2073	NUM
ajst-21789	115	122	0.2073	0.2073	NUM
ajst-21789	115	123	14.9827	14.9827	NUM
ajst-21789	115	124	0.0173	0.0173	NUM
ajst-21789	115	125	average	average	ADJ
ajst-21789	115	126	relative	relative	ADJ
ajst-21789	115	127	error	error	NOUN
ajst-21789	115	128	mre	mre	PROPN
ajst-21789	115	129	,	,	PUNCT
ajst-21789	115	130	normalized	normalize	VERB
ajst-21789	115	131	root	root	NOUN
ajst-21789	115	132	-	-	PUNCT
ajst-21789	115	133	mean	mean	ADJ
ajst-21789	115	134	-	-	PUNCT
ajst-21789	115	135	square	square	NOUN
ajst-21789	115	136	error	error	NOUN
ajst-21789	115	137	nmse	nmse	NOUN
ajst-21789	115	138	and	and	CCONJ
ajst-21789	115	139	regression	regression	NOUN
ajst-21789	115	140	correlation	correlation	NOUN
ajst-21789	115	141	index	index	NOUN
ajst-21789	115	142	r2	r2	PROPN
ajst-21789	115	143	were	be	AUX
ajst-21789	115	144	introduced	introduce	VERB
ajst-21789	115	145	to	to	PART
ajst-21789	115	146	evaluate	evaluate	VERB
ajst-21789	115	147	the	the	DET
ajst-21789	115	148	prediction	prediction	NOUN
ajst-21789	115	149	results	result	NOUN
ajst-21789	115	150	,	,	PUNCT
ajst-21789	115	151	as	as	SCONJ
ajst-21789	115	152	shown	show	VERB
ajst-21789	115	153	in	in	ADP
ajst-21789	115	154	table	table	NOUN
ajst-21789	115	155	5	5	NUM
ajst-21789	115	156	:	:	PUNCT
ajst-21789	115	157	table	table	NOUN
ajst-21789	115	158	5	5	NUM
ajst-21789	115	159	.	.	PUNCT
ajst-21789	115	160	evaluation	evaluation	NOUN
ajst-21789	115	161	indezes	indeze	NOUN
ajst-21789	115	162	of	of	ADP
ajst-21789	115	163	prediction	prediction	NOUN
ajst-21789	115	164	results	result	NOUN
ajst-21789	115	165	of	of	ADP
ajst-21789	115	166	each	each	DET
ajst-21789	115	167	model	model	NOUN
ajst-21789	115	168	evaluation	evaluation	NOUN
ajst-21789	115	169	index	index	NOUN
ajst-21789	115	170	mre/%	mre/%	NOUN
ajst-21789	115	171	nmse	nmse	ADJ
ajst-21789	115	172	r2	r2	PROPN
ajst-21789	115	173	bp	bp	PROPN
ajst-21789	116	1	1.6638	1.6638	NUM
ajst-21789	116	2	0.3155	0.3155	NUM
ajst-21789	116	3	0.8157	0.8157	NUM
ajst-21789	116	4	pso	pso	NOUN
ajst-21789	116	5	-	-	PUNCT
ajst-21789	116	6	bp	bp	PROPN
ajst-21789	116	7	1.4491	1.4491	NUM
ajst-21789	116	8	0.2811	0.2811	NUM
ajst-21789	116	9	0.8537	0.8537	NUM
ajst-21789	116	10	pca	pca	NOUN
ajst-21789	116	11	-	-	PUNCT
ajst-21789	116	12	pso	pso	NOUN
ajst-21789	116	13	-	-	PUNCT
ajst-21789	116	14	bp	bp	PROPN
ajst-21789	116	15	1.5034	1.5034	NUM
ajst-21789	116	16	0.2408	0.2408	NUM
ajst-21789	116	17	0.8926	0.8926	NUM
ajst-21789	116	18	ipca	ipca	NOUN
ajst-21789	116	19	-	-	PUNCT
ajst-21789	116	20	pso	pso	NOUN
ajst-21789	116	21	-	-	PUNCT
ajst-21789	116	22	bp	bp	PROPN
ajst-21789	116	23	1.1138	1.1138	NUM
ajst-21789	116	24	0.2159	0.2159	NUM
ajst-21789	116	25	0.9137	0.9137	NUM
ajst-21789	116	26	ipca	ipca	NOUN
ajst-21789	116	27	-	-	PUNCT
ajst-21789	116	28	cpso	cpso	NOUN
ajst-21789	116	29	-	-	PUNCT
ajst-21789	116	30	bp	bp	PROPN
ajst-21789	116	31	0.5749	0.5749	PRON
ajst-21789	116	32	0.1143	0.1143	VERB
ajst-21789	116	33	0.9758	0.9758	NUM
ajst-21789	116	34	the	the	DET
ajst-21789	116	35	evaluation	evaluation	NOUN
ajst-21789	116	36	indicators	indicator	NOUN
ajst-21789	116	37	of	of	ADP
ajst-21789	116	38	different	different	ADJ
ajst-21789	116	39	models	model	NOUN
ajst-21789	116	40	were	be	AUX
ajst-21789	116	41	visualized	visualize	VERB
ajst-21789	116	42	,	,	PUNCT
ajst-21789	116	43	as	as	SCONJ
ajst-21789	116	44	shown	show	VERB
ajst-21789	116	45	in	in	ADP
ajst-21789	116	46	fig	fig	NOUN
ajst-21789	116	47	.	.	PUNCT
ajst-21789	116	48	2	2	NUM
ajst-21789	116	49	and	and	CCONJ
ajst-21789	116	50	fig	fig	NOUN
ajst-21789	116	51	.	.	PUNCT
ajst-21789	117	1	3	3	NUM
ajst-21789	117	2	are	be	AUX
ajst-21789	117	3	the	the	DET
ajst-21789	117	4	comparison	comparison	NOUN
ajst-21789	117	5	graphs	graph	NOUN
ajst-21789	117	6	between	between	ADP
ajst-21789	117	7	the	the	DET
ajst-21789	117	8	prediction	prediction	NOUN
ajst-21789	117	9	results	result	NOUN
ajst-21789	117	10	of	of	ADP
ajst-21789	117	11	different	different	ADJ
ajst-21789	117	12	models	model	NOUN
ajst-21789	117	13	and	and	CCONJ
ajst-21789	117	14	the	the	DET
ajst-21789	117	15	real	real	ADJ
ajst-21789	117	16	values	value	NOUN
ajst-21789	117	17	.	.	PUNCT
ajst-21789	118	1	with	with	ADP
ajst-21789	118	2	the	the	DET
ajst-21789	118	3	introduction	introduction	NOUN
ajst-21789	118	4	of	of	ADP
ajst-21789	118	5	different	different	ADJ
ajst-21789	118	6	algorithms	algorithm	NOUN
ajst-21789	118	7	and	and	CCONJ
ajst-21789	118	8	improved	improve	VERB
ajst-21789	118	9	algorithms	algorithm	NOUN
ajst-21789	118	10	in	in	ADP
ajst-21789	118	11	a	a	DET
ajst-21789	118	12	certain	certain	ADJ
ajst-21789	118	13	order	order	NOUN
ajst-21789	118	14	,	,	PUNCT
ajst-21789	118	15	the	the	DET
ajst-21789	118	16	average	average	ADJ
ajst-21789	118	17	relative	relative	ADJ
ajst-21789	118	18	error	error	NOUN
ajst-21789	118	19	mre	mre	PROPN
ajst-21789	118	20	increases	increase	VERB
ajst-21789	118	21	first	first	ADV
ajst-21789	118	22	and	and	CCONJ
ajst-21789	118	23	then	then	ADV
ajst-21789	118	24	decreases	decrease	VERB
ajst-21789	118	25	,	,	PUNCT
ajst-21789	118	26	and	and	CCONJ
ajst-21789	118	27	the	the	DET
ajst-21789	118	28	normalized	normalize	VERB
ajst-21789	118	29	rootmean	rootmean	ADJ
ajst-21789	118	30	-	-	PUNCT
ajst-21789	118	31	square	square	NOUN
ajst-21789	118	32	error	error	NOUN
ajst-21789	118	33	nmse	nmse	NOUN
ajst-21789	118	34	and	and	CCONJ
ajst-21789	118	35	the	the	DET
ajst-21789	118	36	regression	regression	NOUN
ajst-21789	118	37	correlation	correlation	NOUN
ajst-21789	118	38	index	index	NOUN
ajst-21789	118	39	r2	r2	NOUN
ajst-21789	118	40	change	change	NOUN
ajst-21789	118	41	monotonically	monotonically	ADV
ajst-21789	118	42	.	.	PUNCT
ajst-21789	119	1	the	the	PRON
ajst-21789	119	2	smaller	small	ADJ
ajst-21789	119	3	the	the	DET
ajst-21789	119	4	mean	mean	ADJ
ajst-21789	119	5	relative	relative	ADJ
ajst-21789	119	6	error	error	NOUN
ajst-21789	119	7	mre	mre	NOUN
ajst-21789	119	8	and	and	CCONJ
ajst-21789	119	9	the	the	DET
ajst-21789	119	10	normalized	normalize	VERB
ajst-21789	119	11	root	root	NOUN
ajst-21789	119	12	-	-	PUNCT
ajst-21789	119	13	mean	mean	ADJ
ajst-21789	119	14	-	-	PUNCT
ajst-21789	119	15	square	square	NOUN
ajst-21789	119	16	error	error	NOUN
ajst-21789	119	17	nmse	nmse	NOUN
ajst-21789	119	18	,	,	PUNCT
ajst-21789	119	19	the	the	DET
ajst-21789	119	20	more	more	ADV
ajst-21789	119	21	accurate	accurate	ADJ
ajst-21789	119	22	the	the	DET
ajst-21789	119	23	prediction	prediction	NOUN
ajst-21789	119	24	result	result	NOUN
ajst-21789	119	25	.	.	PUNCT
ajst-21789	120	1	the	the	DET
ajst-21789	120	2	optimization	optimization	NOUN
ajst-21789	120	3	effect	effect	NOUN
ajst-21789	120	4	of	of	ADP
ajst-21789	120	5	different	different	ADJ
ajst-21789	120	6	algorithms	algorithm	NOUN
ajst-21789	120	7	on	on	ADP
ajst-21789	120	8	bp	bp	PROPN
ajst-21789	120	9	neural	neural	ADJ
ajst-21789	120	10	network	network	NOUN
ajst-21789	120	11	is	be	AUX
ajst-21789	120	12	shown	show	VERB
ajst-21789	120	13	in	in	ADP
ajst-21789	120	14	figure	figure	NOUN
ajst-21789	120	15	2	2	NUM
ajst-21789	120	16	.	.	PUNCT
ajst-21789	121	1	the	the	DET
ajst-21789	121	2	ipca	ipca	PROPN
ajst-21789	121	3	-	-	PUNCT
ajst-21789	121	4	cpso	cpso	NOUN
ajst-21789	121	5	-	-	PUNCT
ajst-21789	121	6	bp	bp	PROPN
ajst-21789	121	7	model	model	NOUN
ajst-21789	121	8	is	be	AUX
ajst-21789	121	9	the	the	DET
ajst-21789	121	10	most	most	ADV
ajst-21789	121	11	accurate	accurate	ADJ
ajst-21789	121	12	in	in	ADP
ajst-21789	121	13	prediction	prediction	NOUN
ajst-21789	121	14	,	,	PUNCT
ajst-21789	121	15	with	with	ADP
ajst-21789	121	16	mre	mre	PROPN
ajst-21789	121	17	value	value	NOUN
ajst-21789	121	18	of	of	ADP
ajst-21789	121	19	0.5749	0.5749	NUM
ajst-21789	121	20	and	and	CCONJ
ajst-21789	121	21	nmse	nmse	ADJ
ajst-21789	121	22	value	value	NOUN
ajst-21789	121	23	of	of	ADP
ajst-21789	121	24	0.1143	0.1143	NOUN
ajst-21789	121	25	.	.	PUNCT
ajst-21789	122	1	compared	compare	VERB
ajst-21789	122	2	with	with	ADP
ajst-21789	122	3	bp	bp	PROPN
ajst-21789	122	4	prediction	prediction	NOUN
ajst-21789	122	5	model	model	NOUN
ajst-21789	122	6	,	,	PUNCT
ajst-21789	122	7	the	the	DET
ajst-21789	122	8	average	average	ADJ
ajst-21789	122	9	relative	relative	ADJ
ajst-21789	122	10	error	error	NOUN
ajst-21789	122	11	of	of	ADP
ajst-21789	122	12	ipca	ipca	NOUN
ajst-21789	122	13	-	-	PUNCT
ajst-21789	122	14	cpso	cpso	NOUN
ajst-21789	122	15	-	-	PUNCT
ajst-21789	122	16	bp	bp	PROPN
ajst-21789	122	17	model	model	NOUN
ajst-21789	122	18	is	be	AUX
ajst-21789	122	19	reduced	reduce	VERB
ajst-21789	122	20	by	by	ADP
ajst-21789	122	21	1.0889	1.0889	NUM
ajst-21789	122	22	%	%	NOUN
ajst-21789	122	23	,	,	PUNCT
ajst-21789	122	24	and	and	CCONJ
ajst-21789	122	25	the	the	DET
ajst-21789	122	26	average	average	ADJ
ajst-21789	122	27	relative	relative	ADJ
ajst-21789	122	28	error	error	NOUN
ajst-21789	122	29	of	of	ADP
ajst-21789	122	30	bp	bp	PROPN
ajst-21789	122	31	prediction	prediction	NOUN
ajst-21789	122	32	model	model	NOUN
ajst-21789	122	33	is	be	AUX
ajst-21789	122	34	about	about	ADV
ajst-21789	122	35	3	3	NUM
ajst-21789	122	36	times	time	NOUN
ajst-21789	122	37	that	that	PRON
ajst-21789	122	38	of	of	ADP
ajst-21789	122	39	ipca	ipca	PROPN
ajst-21789	122	40	-	-	PUNCT
ajst-21789	122	41	cpso	cpso	NOUN
ajst-21789	122	42	-	-	PUNCT
ajst-21789	122	43	bp	bp	PROPN
ajst-21789	122	44	model	model	NOUN
ajst-21789	122	45	.	.	PUNCT
ajst-21789	123	1	the	the	DET
ajst-21789	123	2	normalized	normalize	VERB
ajst-21789	123	3	root	root	NOUN
ajst-21789	123	4	-	-	PUNCT
ajst-21789	123	5	mean	mean	ADJ
ajst-21789	123	6	-	-	PUNCT
ajst-21789	123	7	square	square	NOUN
ajst-21789	123	8	error	error	NOUN
ajst-21789	123	9	is	be	AUX
ajst-21789	123	10	reduced	reduce	VERB
ajst-21789	123	11	by	by	ADP
ajst-21789	123	12	0.2012	0.2012	NUM
ajst-21789	123	13	,	,	PUNCT
ajst-21789	123	14	and	and	CCONJ
ajst-21789	123	15	the	the	DET
ajst-21789	123	16	normalized	normalize	VERB
ajst-21789	123	17	root	root	NOUN
ajst-21789	123	18	-	-	PUNCT
ajst-21789	123	19	mean	mean	ADJ
ajst-21789	123	20	-	-	PUNCT
ajst-21789	123	21	square	square	NOUN
ajst-21789	123	22	error	error	NOUN
ajst-21789	123	23	of	of	ADP
ajst-21789	123	24	bp	bp	PROPN
ajst-21789	123	25	prediction	prediction	NOUN
ajst-21789	123	26	model	model	NOUN
ajst-21789	123	27	is	be	AUX
ajst-21789	123	28	about	about	ADV
ajst-21789	123	29	2.8	2.8	NUM
ajst-21789	123	30	times	time	NOUN
ajst-21789	123	31	that	that	PRON
ajst-21789	123	32	of	of	ADP
ajst-21789	123	33	ipca	ipca	PROPN
ajst-21789	123	34	-	-	PUNCT
ajst-21789	123	35	cpso	cpso	NOUN
ajst-21789	123	36	-	-	PUNCT
ajst-21789	123	37	bp	bp	PROPN
ajst-21789	123	38	model	model	NOUN
ajst-21789	123	39	,	,	PUNCT
ajst-21789	123	40	which	which	PRON
ajst-21789	123	41	significantly	significantly	ADV
ajst-21789	123	42	improves	improve	VERB
ajst-21789	123	43	the	the	DET
ajst-21789	123	44	prediction	prediction	NOUN
ajst-21789	123	45	accuracy	accuracy	NOUN
ajst-21789	123	46	of	of	ADP
ajst-21789	123	47	ipca	ipca	PROPN
ajst-21789	123	48	-	-	PUNCT
ajst-21789	123	49	cpso	cpso	NOUN
ajst-21789	123	50	-	-	PUNCT
ajst-21789	123	51	bp	bp	PROPN
ajst-21789	123	52	model	model	NOUN
ajst-21789	123	53	.	.	PUNCT
ajst-21789	124	1	the	the	PRON
ajst-21789	124	2	closer	close	ADV
ajst-21789	124	3	the	the	DET
ajst-21789	124	4	regression	regression	NOUN
ajst-21789	124	5	correlation	correlation	NOUN
ajst-21789	124	6	index	index	NOUN
ajst-21789	124	7	r2	r2	NOUN
ajst-21789	124	8	is	be	AUX
ajst-21789	124	9	to	to	ADP
ajst-21789	124	10	1	1	NUM
ajst-21789	124	11	,	,	PUNCT
ajst-21789	124	12	the	the	PRON
ajst-21789	124	13	better	well	ADJ
ajst-21789	124	14	the	the	DET
ajst-21789	124	15	fitting	fitting	ADJ
ajst-21789	124	16	effect	effect	NOUN
ajst-21789	124	17	of	of	ADP
ajst-21789	124	18	the	the	DET
ajst-21789	124	19	model	model	NOUN
ajst-21789	124	20	is	be	AUX
ajst-21789	124	21	.	.	PUNCT
ajst-21789	125	1	as	as	SCONJ
ajst-21789	125	2	shown	show	VERB
ajst-21789	125	3	in	in	ADP
ajst-21789	125	4	figure	figure	NOUN
ajst-21789	125	5	2	2	NUM
ajst-21789	125	6	and	and	CCONJ
ajst-21789	125	7	3	3	NUM
ajst-21789	125	8	,	,	PUNCT
ajst-21789	125	9	ipca	ipca	NOUN
ajst-21789	125	10	-	-	PUNCT
ajst-21789	125	11	cpso	cpso	NOUN
ajst-21789	125	12	-	-	PUNCT
ajst-21789	125	13	bp	bp	PROPN
ajst-21789	125	14	model	model	NOUN
ajst-21789	125	15	has	have	VERB
ajst-21789	125	16	the	the	DET
ajst-21789	125	17	best	good	ADJ
ajst-21789	125	18	fitting	fitting	ADJ
ajst-21789	125	19	effect	effect	NOUN
ajst-21789	125	20	,	,	PUNCT
ajst-21789	125	21	and	and	CCONJ
ajst-21789	125	22	the	the	DET
ajst-21789	125	23	r2	r2	PROPN
ajst-21789	125	24	value	value	NOUN
ajst-21789	125	25	is	be	AUX
ajst-21789	125	26	0.9758	0.9758	NUM
ajst-21789	125	27	.	.	PUNCT
ajst-21789	126	1	after	after	SCONJ
ajst-21789	126	2	particle	particle	NOUN
ajst-21789	126	3	swarm	swarm	NOUN
ajst-21789	126	4	optimization	optimization	NOUN
ajst-21789	126	5	and	and	CCONJ
ajst-21789	126	6	improved	improve	VERB
ajst-21789	126	7	particle	particle	NOUN
ajst-21789	126	8	swarm	swarm	NOUN
ajst-21789	126	9	optimization	optimization	NOUN
ajst-21789	126	10	are	be	AUX
ajst-21789	126	11	added	add	VERB
ajst-21789	126	12	to	to	ADP
ajst-21789	126	13	the	the	DET
ajst-21789	126	14	model	model	NOUN
ajst-21789	126	15	,	,	PUNCT
ajst-21789	126	16	the	the	DET
ajst-21789	126	17	fitting	fitting	ADJ
ajst-21789	126	18	effect	effect	NOUN
ajst-21789	126	19	is	be	AUX
ajst-21789	126	20	improved	improve	VERB
ajst-21789	126	21	and	and	CCONJ
ajst-21789	126	22	the	the	DET
ajst-21789	126	23	dispersion	dispersion	NOUN
ajst-21789	126	24	of	of	ADP
ajst-21789	126	25	data	datum	NOUN
ajst-21789	126	26	distribution	distribution	NOUN
ajst-21789	126	27	is	be	AUX
ajst-21789	126	28	low	low	ADJ
ajst-21789	126	29	.	.	PUNCT
ajst-21789	127	1	the	the	DET
ajst-21789	127	2	lines	line	NOUN
ajst-21789	127	3	are	be	AUX
ajst-21789	127	4	more	more	ADV
ajst-21789	127	5	consistent	consistent	ADJ
ajst-21789	127	6	with	with	ADP
ajst-21789	127	7	the	the	DET
ajst-21789	127	8	true	true	ADJ
ajst-21789	127	9	value	value	NOUN
ajst-21789	127	10	.	.	PUNCT
ajst-21789	128	1	principal	principal	ADJ
ajst-21789	128	2	component	component	NOUN
ajst-21789	128	3	analysis	analysis	NOUN
ajst-21789	128	4	(	(	PUNCT
ajst-21789	128	5	pca	pca	NOUN
ajst-21789	128	6	)	)	PUNCT
ajst-21789	128	7	can	can	AUX
ajst-21789	128	8	more	more	ADV
ajst-21789	128	9	effectively	effectively	ADV
ajst-21789	128	10	remove	remove	VERB
ajst-21789	128	11	redundant	redundant	ADJ
ajst-21789	128	12	data	datum	NOUN
ajst-21789	128	13	information	information	NOUN
ajst-21789	128	14	and	and	CCONJ
ajst-21789	128	15	increase	increase	VERB
ajst-21789	128	16	the	the	DET
ajst-21789	128	17	accuracy	accuracy	NOUN
ajst-21789	128	18	of	of	ADP
ajst-21789	128	19	prediction	prediction	NOUN
ajst-21789	128	20	results	result	NOUN
ajst-21789	128	21	in	in	ADP
ajst-21789	128	22	the	the	DET
ajst-21789	128	23	whole	whole	ADJ
ajst-21789	128	24	model	model	NOUN
ajst-21789	128	25	.	.	PUNCT
ajst-21789	129	1	the	the	DET
ajst-21789	129	2	improved	improved	ADJ
ajst-21789	129	3	pca	pca	PROPN
ajst-21789	129	4	strengthens	strengthen	VERB
ajst-21789	129	5	this	this	DET
ajst-21789	129	6	feature	feature	NOUN
ajst-21789	129	7	.	.	PUNCT
ajst-21789	130	1	particle	particle	NOUN
ajst-21789	130	2	swarm	swarm	NOUN
ajst-21789	130	3	optimization	optimization	NOUN
ajst-21789	130	4	(	(	PUNCT
ajst-21789	130	5	pso	pso	NOUN
ajst-21789	130	6	)	)	PUNCT
ajst-21789	130	7	mainly	mainly	ADV
ajst-21789	130	8	controls	control	VERB
ajst-21789	130	9	the	the	DET
ajst-21789	130	10	stability	stability	NOUN
ajst-21789	130	11	of	of	ADP
ajst-21789	130	12	the	the	DET
ajst-21789	130	13	model	model	NOUN
ajst-21789	130	14	,	,	PUNCT
ajst-21789	130	15	and	and	CCONJ
ajst-21789	130	16	the	the	DET
ajst-21789	130	17	improved	improved	ADJ
ajst-21789	130	18	pso	pso	NOUN
ajst-21789	130	19	also	also	ADV
ajst-21789	130	20	strengthens	strengthen	VERB
ajst-21789	130	21	this	this	DET
ajst-21789	130	22	property	property	NOUN
ajst-21789	130	23	.	.	PUNCT
ajst-21789	131	1	figure	figure	NOUN
ajst-21789	131	2	2	2	NUM
ajst-21789	131	3	.	.	PUNCT
ajst-21789	131	4	evaluation	evaluation	NOUN
ajst-21789	131	5	indicators	indicator	NOUN
ajst-21789	131	6	of	of	ADP
ajst-21789	131	7	different	different	ADJ
ajst-21789	131	8	models	model	NOUN
ajst-21789	131	9	bp	bp	PROPN
ajst-21789	131	10	pso	pso	PROPN
ajst-21789	131	11	-	-	PUNCT
ajst-21789	131	12	bp	bp	PROPN
ajst-21789	131	13	pca	pca	PROPN
ajst-21789	131	14	-	-	PUNCT
ajst-21789	131	15	pso	pso	NOUN
ajst-21789	131	16	-	-	PUNCT
ajst-21789	131	17	bp	bp	PROPN
ajst-21789	131	18	ipca	ipca	PROPN
ajst-21789	131	19	-	-	PUNCT
ajst-21789	131	20	pso	pso	NOUN
ajst-21789	131	21	-	-	PUNCT
ajst-21789	131	22	bp	bp	PROPN
ajst-21789	131	23	ipca	ipca	PROPN
ajst-21789	131	24	-	-	PUNCT
ajst-21789	131	25	cpso	cpso	NOUN
ajst-21789	131	26	-	-	PUNCT
ajst-21789	131	27	bp	bp	PROPN
ajst-21789	131	28	0.0	0.0	NUM
ajst-21789	131	29	0.2	0.2	NUM
ajst-21789	131	30	0.4	0.4	NUM
ajst-21789	131	31	0.6	0.6	NUM
ajst-21789	131	32	0.8	0.8	NUM
ajst-21789	131	33	1.0	1.0	NUM
ajst-21789	131	34	1.2	1.2	NUM
ajst-21789	131	35	1.4	1.4	NUM
ajst-21789	131	36	1.6	1.6	NUM
ajst-21789	131	37	1.8	1.8	NUM
ajst-21789	131	38	1.66377	1.66377	NUM
ajst-21789	131	39	1.4491	1.4491	NUM
ajst-21789	131	40	1.50343	1.50343	NUM
ajst-21789	131	41	1.1138	1.1138	NUM
ajst-21789	131	42	0.5749	0.5749	NUM
ajst-21789	131	43	0.81565	0.81565	NUM
ajst-21789	131	44	0.85371	0.85371	NUM
ajst-21789	131	45	0.89263	0.89263	NUM
ajst-21789	131	46	0.91372	0.91372	NUM
ajst-21789	131	47	0.97579	0.97579	NUM
ajst-21789	131	48	0.31551	0.31551	NUM
ajst-21789	131	49	0.28106	0.28106	NUM
ajst-21789	131	50	0.24079	0.24079	NUM
ajst-21789	131	51	0.21585	0.21585	NUM
ajst-21789	131	52	0.11433	0.11433	NUM
ajst-21789	131	53	e	e	PROPN
ajst-21789	131	54	va	va	PROPN
ajst-21789	131	55	lu	lu	PROPN
ajst-21789	131	56	at	at	ADP
ajst-21789	131	57	io	io	PROPN
ajst-21789	131	58	n	n	X
ajst-21789	131	59	in	in	ADP
ajst-21789	131	60	de	de	X
ajst-21789	131	61	x	x	X
ajst-21789	131	62	va	va	PROPN
ajst-21789	131	63	lu	lu	PROPN
ajst-21789	131	64	e	e	PROPN
ajst-21789	131	65	different	different	ADJ
ajst-21789	131	66	prediction	prediction	NOUN
ajst-21789	131	67	models	model	NOUN
ajst-21789	131	68	mre（%	mre（%	NOUN
ajst-21789	131	69	）	）	PROPN
ajst-21789	131	70	r2	r2	PROPN
ajst-21789	131	71	n	n	PROPN
ajst-21789	131	72	mse	mse	NOUN
ajst-21789	131	73	203	203	NUM
ajst-21789	131	74	figure	figure	NOUN
ajst-21789	131	75	3	3	NUM
ajst-21789	131	76	.	.	NOUN
ajst-21789	131	77	comparison	comparison	NOUN
ajst-21789	131	78	between	between	ADP
ajst-21789	131	79	the	the	DET
ajst-21789	131	80	predicted	predict	VERB
ajst-21789	131	81	value	value	NOUN
ajst-21789	131	82	and	and	CCONJ
ajst-21789	131	83	the	the	DET
ajst-21789	131	84	real	real	ADJ
ajst-21789	131	85	value	value	NOUN
ajst-21789	131	86	of	of	ADP
ajst-21789	131	87	different	different	ADJ
ajst-21789	131	88	models	model	NOUN
ajst-21789	131	89	figure	figure	VERB
ajst-21789	131	90	4	4	NUM
ajst-21789	131	91	shows	show	VERB
ajst-21789	131	92	the	the	DET
ajst-21789	131	93	curve	curve	NOUN
ajst-21789	131	94	of	of	ADP
ajst-21789	131	95	pso	pso	NOUN
ajst-21789	131	96	iterations	iteration	NOUN
ajst-21789	131	97	of	of	ADP
ajst-21789	131	98	each	each	DET
ajst-21789	131	99	model	model	NOUN
ajst-21789	131	100	.	.	PUNCT
ajst-21789	132	1	the	the	DET
ajst-21789	132	2	model	model	NOUN
ajst-21789	132	3	iteration	iteration	NOUN
ajst-21789	132	4	curve	curve	NOUN
ajst-21789	132	5	is	be	AUX
ajst-21789	132	6	in	in	ADP
ajst-21789	132	7	the	the	DET
ajst-21789	132	8	shape	shape	NOUN
ajst-21789	132	9	of	of	ADP
ajst-21789	132	10	a	a	DET
ajst-21789	132	11	ladder	ladder	NOUN
ajst-21789	132	12	.	.	PUNCT
ajst-21789	133	1	the	the	DET
ajst-21789	133	2	model	model	NOUN
ajst-21789	133	3	with	with	ADP
ajst-21789	133	4	the	the	DET
ajst-21789	133	5	fastest	fast	ADJ
ajst-21789	133	6	convergence	convergence	NOUN
ajst-21789	133	7	speed	speed	NOUN
ajst-21789	133	8	is	be	AUX
ajst-21789	133	9	ipca	ipca	NOUN
ajst-21789	133	10	-	-	PUNCT
ajst-21789	133	11	pso	pso	NOUN
ajst-21789	133	12	-	-	PUNCT
ajst-21789	133	13	bp	bp	PROPN
ajst-21789	133	14	model	model	NOUN
ajst-21789	133	15	,	,	PUNCT
ajst-21789	133	16	which	which	PRON
ajst-21789	133	17	tends	tend	VERB
ajst-21789	133	18	to	to	PART
ajst-21789	133	19	converge	converge	VERB
ajst-21789	133	20	at	at	ADP
ajst-21789	133	21	the	the	DET
ajst-21789	133	22	25th	25th	ADJ
ajst-21789	133	23	step	step	NOUN
ajst-21789	133	24	after	after	ADP
ajst-21789	133	25	iteration	iteration	NOUN
ajst-21789	133	26	.	.	PUNCT
ajst-21789	134	1	the	the	DET
ajst-21789	134	2	convergence	convergence	NOUN
ajst-21789	134	3	speed	speed	NOUN
ajst-21789	134	4	of	of	ADP
ajst-21789	134	5	pso	pso	NOUN
ajst-21789	134	6	-	-	PUNCT
ajst-21789	134	7	bp	bp	PROPN
ajst-21789	134	8	model	model	NOUN
ajst-21789	134	9	and	and	CCONJ
ajst-21789	134	10	ipca	ipca	PROPN
ajst-21789	134	11	-	-	PUNCT
ajst-21789	134	12	cpsobp	cpsobp	NOUN
ajst-21789	134	13	model	model	NOUN
ajst-21789	134	14	is	be	AUX
ajst-21789	134	15	relatively	relatively	ADV
ajst-21789	134	16	slow	slow	ADJ
ajst-21789	134	17	,	,	PUNCT
ajst-21789	134	18	and	and	CCONJ
ajst-21789	134	19	the	the	DET
ajst-21789	134	20	hopping	hop	VERB
ajst-21789	134	21	amplitude	amplitude	NOUN
ajst-21789	134	22	of	of	ADP
ajst-21789	134	23	fitness	fitness	NOUN
ajst-21789	134	24	value	value	NOUN
ajst-21789	134	25	convergence	convergence	NOUN
ajst-21789	134	26	is	be	AUX
ajst-21789	134	27	relatively	relatively	ADV
ajst-21789	134	28	large	large	ADJ
ajst-21789	134	29	.	.	PUNCT
ajst-21789	135	1	because	because	SCONJ
ajst-21789	135	2	psobp	psobp	NOUN
ajst-21789	135	3	model	model	NOUN
ajst-21789	135	4	has	have	AUX
ajst-21789	135	5	not	not	PART
ajst-21789	135	6	undergone	undergo	VERB
ajst-21789	135	7	data	datum	NOUN
ajst-21789	135	8	dimensionality	dimensionality	NOUN
ajst-21789	135	9	reduction	reduction	NOUN
ajst-21789	135	10	,	,	PUNCT
ajst-21789	135	11	the	the	DET
ajst-21789	135	12	convergence	convergence	NOUN
ajst-21789	135	13	process	process	NOUN
ajst-21789	135	14	is	be	AUX
ajst-21789	135	15	random	random	ADJ
ajst-21789	135	16	,	,	PUNCT
ajst-21789	135	17	and	and	CCONJ
ajst-21789	135	18	the	the	DET
ajst-21789	135	19	number	number	NOUN
ajst-21789	135	20	of	of	ADP
ajst-21789	135	21	iterations	iteration	NOUN
ajst-21789	135	22	increases	increase	NOUN
ajst-21789	135	23	correspondingly	correspondingly	ADV
ajst-21789	135	24	.	.	PUNCT
ajst-21789	136	1	ipca	ipca	PROPN
ajst-21789	136	2	-	-	PUNCT
ajst-21789	136	3	cpso	cpso	NOUN
ajst-21789	136	4	-	-	PUNCT
ajst-21789	136	5	bp	bp	PROPN
ajst-21789	136	6	model	model	NOUN
ajst-21789	136	7	adds	add	VERB
ajst-21789	136	8	adaptive	adaptive	ADJ
ajst-21789	136	9	inertia	inertia	NOUN
ajst-21789	136	10	weight	weight	NOUN
ajst-21789	136	11	and	and	CCONJ
ajst-21789	136	12	shrinkage	shrinkage	NOUN
ajst-21789	136	13	factor	factor	NOUN
ajst-21789	136	14	.	.	PUNCT
ajst-21789	137	1	the	the	DET
ajst-21789	137	2	model	model	NOUN
ajst-21789	137	3	can	can	AUX
ajst-21789	137	4	have	have	VERB
ajst-21789	137	5	global	global	ADJ
ajst-21789	137	6	search	search	NOUN
ajst-21789	137	7	particles	particle	NOUN
ajst-21789	137	8	before	before	ADP
ajst-21789	137	9	and	and	CCONJ
ajst-21789	137	10	after	after	ADP
ajst-21789	137	11	the	the	DET
ajst-21789	137	12	search	search	NOUN
ajst-21789	137	13	,	,	PUNCT
ajst-21789	137	14	so	so	CCONJ
ajst-21789	137	15	it	it	PRON
ajst-21789	137	16	is	be	AUX
ajst-21789	137	17	not	not	PART
ajst-21789	137	18	easy	easy	ADJ
ajst-21789	137	19	to	to	PART
ajst-21789	137	20	fall	fall	VERB
ajst-21789	137	21	into	into	ADP
ajst-21789	137	22	the	the	DET
ajst-21789	137	23	local	local	ADJ
ajst-21789	137	24	optimal	optimal	ADJ
ajst-21789	137	25	solution	solution	NOUN
ajst-21789	137	26	,	,	PUNCT
ajst-21789	137	27	the	the	DET
ajst-21789	137	28	convergence	convergence	NOUN
ajst-21789	137	29	rate	rate	NOUN
ajst-21789	137	30	decreases	decrease	NOUN
ajst-21789	137	31	,	,	PUNCT
ajst-21789	137	32	and	and	CCONJ
ajst-21789	137	33	the	the	DET
ajst-21789	137	34	prediction	prediction	NOUN
ajst-21789	137	35	accuracy	accuracy	NOUN
ajst-21789	137	36	increases	increase	NOUN
ajst-21789	137	37	.	.	PUNCT
ajst-21789	138	1	figure	figure	VERB
ajst-21789	138	2	4	4	NUM
ajst-21789	138	3	.	.	PUNCT
ajst-21789	138	4	iteration	iteration	NOUN
ajst-21789	138	5	curves	curve	NOUN
ajst-21789	138	6	of	of	ADP
ajst-21789	138	7	different	different	ADJ
ajst-21789	138	8	models	model	NOUN
ajst-21789	138	9	bp	bp	PROPN
ajst-21789	138	10	model	model	PROPN
ajst-21789	138	11	relies	rely	VERB
ajst-21789	138	12	too	too	ADV
ajst-21789	138	13	much	much	ADV
ajst-21789	138	14	on	on	ADP
ajst-21789	138	15	initial	initial	ADJ
ajst-21789	138	16	parameter	parameter	NOUN
ajst-21789	138	17	values	value	NOUN
ajst-21789	138	18	in	in	ADP
ajst-21789	138	19	the	the	DET
ajst-21789	138	20	process	process	NOUN
ajst-21789	138	21	of	of	ADP
ajst-21789	138	22	use	use	NOUN
ajst-21789	138	23	,	,	PUNCT
ajst-21789	138	24	pso	pso	NOUN
ajst-21789	138	25	convergence	convergence	NOUN
ajst-21789	138	26	speed	speed	NOUN
ajst-21789	138	27	in	in	ADP
ajst-21789	138	28	the	the	DET
ajst-21789	138	29	process	process	NOUN
ajst-21789	138	30	of	of	ADP
ajst-21789	138	31	parameter	parameter	NOUN
ajst-21789	138	32	optimization	optimization	NOUN
ajst-21789	138	33	leads	lead	VERB
ajst-21789	138	34	to	to	PART
ajst-21789	138	35	easy	easy	ADJ
ajst-21789	138	36	to	to	PART
ajst-21789	138	37	fall	fall	VERB
ajst-21789	138	38	into	into	ADP
ajst-21789	138	39	the	the	DET
ajst-21789	138	40	local	local	ADJ
ajst-21789	138	41	optimal	optimal	ADJ
ajst-21789	138	42	solution	solution	NOUN
ajst-21789	138	43	,	,	PUNCT
ajst-21789	138	44	pca	pca	PROPN
ajst-21789	138	45	is	be	AUX
ajst-21789	138	46	not	not	PART
ajst-21789	138	47	strong	strong	ADJ
ajst-21789	138	48	enough	enough	ADV
ajst-21789	138	49	to	to	PART
ajst-21789	138	50	reduce	reduce	VERB
ajst-21789	138	51	the	the	DET
ajst-21789	138	52	dimension	dimension	NOUN
ajst-21789	138	53	of	of	ADP
ajst-21789	138	54	data	datum	NOUN
ajst-21789	138	55	,	,	PUNCT
ajst-21789	138	56	resulting	result	VERB
ajst-21789	138	57	in	in	ADP
ajst-21789	138	58	the	the	DET
ajst-21789	138	59	model	model	NOUN
ajst-21789	138	60	has	have	VERB
ajst-21789	138	61	randomness	randomness	NOUN
ajst-21789	138	62	in	in	ADP
ajst-21789	138	63	the	the	DET
ajst-21789	138	64	prediction	prediction	NOUN
ajst-21789	138	65	process	process	NOUN
ajst-21789	138	66	.	.	PUNCT
ajst-21789	139	1	ipca	ipca	PROPN
ajst-21789	139	2	-	-	PUNCT
ajst-21789	139	3	cpso	cpso	NOUN
ajst-21789	139	4	-	-	PUNCT
ajst-21789	139	5	bp	bp	PROPN
ajst-21789	139	6	model	model	NOUN
ajst-21789	139	7	improves	improve	VERB
ajst-21789	139	8	the	the	DET
ajst-21789	139	9	pre	pre	ADJ
ajst-21789	139	10	-	-	ADJ
ajst-21789	139	11	processing	processing	ADJ
ajst-21789	139	12	ability	ability	NOUN
ajst-21789	139	13	of	of	ADP
ajst-21789	139	14	data	datum	NOUN
ajst-21789	139	15	,	,	PUNCT
ajst-21789	139	16	slows	slow	VERB
ajst-21789	139	17	down	down	ADP
ajst-21789	139	18	the	the	DET
ajst-21789	139	19	convergence	convergence	NOUN
ajst-21789	139	20	speed	speed	NOUN
ajst-21789	139	21	and	and	CCONJ
ajst-21789	139	22	improves	improve	VERB
ajst-21789	139	23	the	the	DET
ajst-21789	139	24	prediction	prediction	NOUN
ajst-21789	139	25	accuracy	accuracy	NOUN
ajst-21789	139	26	.	.	PUNCT
ajst-21789	140	1	5	5	X
ajst-21789	140	2	.	.	X
ajst-21789	140	3	conclusion	conclusion	NOUN
ajst-21789	140	4	(	(	PUNCT
ajst-21789	140	5	1	1	X
ajst-21789	140	6	)	)	PUNCT
ajst-21789	140	7	the	the	DET
ajst-21789	140	8	spearman	spearman	NOUN
ajst-21789	140	9	correlation	correlation	NOUN
ajst-21789	140	10	coefficient	coefficient	NOUN
ajst-21789	140	11	(	(	PUNCT
ajst-21789	140	12	absolute	absolute	ADJ
ajst-21789	140	13	value	value	NOUN
ajst-21789	140	14	)	)	PUNCT
ajst-21789	140	15	was	be	AUX
ajst-21789	140	16	added	add	VERB
ajst-21789	140	17	to	to	ADP
ajst-21789	140	18	the	the	DET
ajst-21789	140	19	principal	principal	ADJ
ajst-21789	140	20	component	component	NOUN
ajst-21789	140	21	analysis	analysis	NOUN
ajst-21789	140	22	as	as	ADP
ajst-21789	140	23	the	the	DET
ajst-21789	140	24	weight	weight	NOUN
ajst-21789	140	25	of	of	ADP
ajst-21789	140	26	each	each	DET
ajst-21789	140	27	influencing	influence	VERB
ajst-21789	140	28	factor	factor	NOUN
ajst-21789	140	29	,	,	PUNCT
ajst-21789	140	30	which	which	PRON
ajst-21789	140	31	improved	improve	VERB
ajst-21789	140	32	the	the	DET
ajst-21789	140	33	principal	principal	ADJ
ajst-21789	140	34	component	component	NOUN
ajst-21789	140	35	analysis	analysis	NOUN
ajst-21789	140	36	.	.	PUNCT
ajst-21789	141	1	after	after	ADP
ajst-21789	141	2	dimensionality	dimensionality	NOUN
ajst-21789	141	3	reduction	reduction	NOUN
ajst-21789	141	4	,	,	PUNCT
ajst-21789	141	5	the	the	DET
ajst-21789	141	6	traditional	traditional	ADJ
ajst-21789	141	7	principal	principal	ADJ
ajst-21789	141	8	component	component	NOUN
ajst-21789	141	9	analysis	analysis	NOUN
ajst-21789	141	10	produced	produce	VERB
ajst-21789	141	11	6	6	NUM
ajst-21789	141	12	principal	principal	ADJ
ajst-21789	141	13	components	component	NOUN
ajst-21789	141	14	,	,	PUNCT
ajst-21789	141	15	with	with	ADP
ajst-21789	141	16	a	a	DET
ajst-21789	141	17	cumulative	cumulative	ADJ
ajst-21789	141	18	contribution	contribution	NOUN
ajst-21789	141	19	rate	rate	NOUN
ajst-21789	141	20	of	of	ADP
ajst-21789	141	21	97.0665	97.0665	NUM
ajst-21789	141	22	%	%	NOUN
ajst-21789	141	23	,	,	PUNCT
ajst-21789	141	24	while	while	SCONJ
ajst-21789	141	25	the	the	DET
ajst-21789	141	26	improved	improve	VERB
ajst-21789	141	27	principal	principal	ADJ
ajst-21789	141	28	component	component	NOUN
ajst-21789	141	29	analysis	analysis	NOUN
ajst-21789	141	30	had	have	VERB
ajst-21789	141	31	only	only	ADV
ajst-21789	141	32	3	3	NUM
ajst-21789	141	33	principal	principal	ADJ
ajst-21789	141	34	components	component	NOUN
ajst-21789	141	35	,	,	PUNCT
ajst-21789	141	36	with	with	ADP
ajst-21789	141	37	a	a	DET
ajst-21789	141	38	cumulative	cumulative	ADJ
ajst-21789	141	39	contribution	contribution	NOUN
ajst-21789	141	40	rate	rate	NOUN
ajst-21789	141	41	of	of	ADP
ajst-21789	141	42	95.2060	95.2060	NUM
ajst-21789	141	43	%	%	NOUN
ajst-21789	141	44	.	.	PUNCT
ajst-21789	142	1	the	the	DET
ajst-21789	142	2	improved	improve	VERB
ajst-21789	142	3	principal	principal	ADJ
ajst-21789	142	4	component	component	NOUN
ajst-21789	142	5	has	have	VERB
ajst-21789	142	6	better	well	ADJ
ajst-21789	142	7	dimensionality	dimensionality	NOUN
ajst-21789	142	8	reduction	reduction	NOUN
ajst-21789	142	9	under	under	ADP
ajst-21789	142	10	the	the	DET
ajst-21789	142	11	premise	premise	NOUN
ajst-21789	142	12	of	of	ADP
ajst-21789	142	13	preserving	preserve	VERB
ajst-21789	142	14	95	95	NUM
ajst-21789	142	15	%	%	NOUN
ajst-21789	142	16	information	information	NOUN
ajst-21789	142	17	.	.	PUNCT
ajst-21789	143	1	(	(	PUNCT
ajst-21789	143	2	2	2	X
ajst-21789	143	3	)	)	PUNCT
ajst-21789	143	4	the	the	DET
ajst-21789	143	5	traditional	traditional	ADJ
ajst-21789	143	6	particle	particle	NOUN
ajst-21789	143	7	swarm	swarm	NOUN
ajst-21789	143	8	optimization	optimization	NOUN
ajst-21789	143	9	(	(	PUNCT
ajst-21789	143	10	pso	pso	NOUN
ajst-21789	143	11	)	)	PUNCT
ajst-21789	143	12	algorithm	algorithm	NOUN
ajst-21789	143	13	is	be	AUX
ajst-21789	143	14	improved	improve	VERB
ajst-21789	143	15	by	by	ADP
ajst-21789	143	16	adding	add	VERB
ajst-21789	143	17	adaptive	adaptive	ADJ
ajst-21789	143	18	inertia	inertia	NOUN
ajst-21789	143	19	weights	weight	NOUN
ajst-21789	143	20	and	and	CCONJ
ajst-21789	143	21	factors	factor	NOUN
ajst-21789	143	22	of	of	ADP
ajst-21789	143	23	compressed	compressed	ADJ
ajst-21789	143	24	search	search	NOUN
ajst-21789	143	25	space.the	space.the	DET
ajst-21789	143	26	optimized	optimize	VERB
ajst-21789	143	27	algorithm	algorithm	NOUN
ajst-21789	143	28	not	not	PART
ajst-21789	143	29	only	only	ADV
ajst-21789	143	30	guarantees	guarantee	VERB
ajst-21789	143	31	the	the	DET
ajst-21789	143	32	search	search	NOUN
ajst-21789	143	33	accuracy	accuracy	NOUN
ajst-21789	143	34	,	,	PUNCT
ajst-21789	143	35	but	but	CCONJ
ajst-21789	143	36	also	also	ADV
ajst-21789	143	37	shows	show	VERB
ajst-21789	143	38	the	the	DET
ajst-21789	143	39	faster	fast	ADJ
ajst-21789	143	40	convergence	convergence	NOUN
ajst-21789	143	41	speed	speed	NOUN
ajst-21789	143	42	,	,	PUNCT
ajst-21789	143	43	thus	thus	ADV
ajst-21789	143	44	achieving	achieve	VERB
ajst-21789	143	45	double	double	ADJ
ajst-21789	143	46	improvement	improvement	NOUN
ajst-21789	143	47	in	in	ADP
ajst-21789	143	48	the	the	DET
ajst-21789	143	49	optimization	optimization	NOUN
ajst-21789	143	50	efficiency	efficiency	NOUN
ajst-21789	143	51	and	and	CCONJ
ajst-21789	143	52	the	the	DET
ajst-21789	143	53	accuracy	accuracy	NOUN
ajst-21789	143	54	of	of	ADP
ajst-21789	143	55	the	the	DET
ajst-21789	143	56	predicted	predict	VERB
ajst-21789	143	57	results	result	NOUN
ajst-21789	143	58	.	.	PUNCT
ajst-21789	144	1	(	(	PUNCT
ajst-21789	144	2	3	3	X
ajst-21789	144	3	)	)	PUNCT
ajst-21789	144	4	the	the	DET
ajst-21789	144	5	ipca	ipca	PROPN
ajst-21789	144	6	-	-	PUNCT
ajst-21789	144	7	cpso	cpso	NOUN
ajst-21789	144	8	-	-	PUNCT
ajst-21789	144	9	bp	bp	PROPN
ajst-21789	144	10	neural	neural	ADJ
ajst-21789	144	11	network	network	NOUN
ajst-21789	144	12	prediction	prediction	NOUN
ajst-21789	144	13	model	model	NOUN
ajst-21789	144	14	realized	realize	VERB
ajst-21789	144	15	the	the	DET
ajst-21789	144	16	prediction	prediction	NOUN
ajst-21789	144	17	of	of	ADP
ajst-21789	144	18	gas	gas	NOUN
ajst-21789	144	19	emission	emission	NOUN
ajst-21789	144	20	at	at	ADP
ajst-21789	144	21	3309	3309	NUM
ajst-21789	144	22	working	work	VERB
ajst-21789	144	23	face	face	NOUN
ajst-21789	144	24	of	of	ADP
ajst-21789	144	25	zhongtai	zhongtai	NOUN
ajst-21789	144	26	mining	mining	NOUN
ajst-21789	144	27	,	,	PUNCT
ajst-21789	144	28	and	and	CCONJ
ajst-21789	144	29	the	the	DET
ajst-21789	144	30	average	average	ADJ
ajst-21789	144	31	absolute	absolute	ADJ
ajst-21789	144	32	error	error	NOUN
ajst-21789	144	33	(	(	PUNCT
ajst-21789	144	34	mae	mae	PROPN
ajst-21789	144	35	)	)	PUNCT
ajst-21789	144	36	was	be	AUX
ajst-21789	144	37	0.0924	0.0924	NUM
ajst-21789	144	38	.	.	PUNCT
ajst-21789	145	1	the	the	DET
ajst-21789	145	2	mean	mean	ADJ
ajst-21789	145	3	relative	relative	ADJ
ajst-21789	145	4	error	error	NOUN
ajst-21789	145	5	(	(	PUNCT
ajst-21789	145	6	mape	mape	NOUN
ajst-21789	145	7	)	)	PUNCT
ajst-21789	145	8	was	be	AUX
ajst-21789	145	9	0.5749	0.5749	NUM
ajst-21789	145	10	%	%	NOUN
ajst-21789	145	11	.	.	PUNCT
ajst-21789	146	1	the	the	DET
ajst-21789	146	2	regression	regression	NOUN
ajst-21789	146	3	correlation	correlation	NOUN
ajst-21789	146	4	index	index	NOUN
ajst-21789	146	5	r2	r2	PROPN
ajst-21789	146	6	was	be	AUX
ajst-21789	146	7	0.9758	0.9758	NUM
ajst-21789	146	8	.	.	PUNCT
ajst-21789	147	1	(	(	PUNCT
ajst-21789	147	2	4	4	X
ajst-21789	147	3	)	)	PUNCT
ajst-21789	147	4	four	four	NUM
ajst-21789	147	5	models	model	NOUN
ajst-21789	147	6	,	,	PUNCT
ajst-21789	147	7	namely	namely	ADV
ajst-21789	147	8	bp	bp	PROPN
ajst-21789	147	9	model	model	PROPN
ajst-21789	147	10	,	,	PUNCT
ajst-21789	147	11	pso	pso	NOUN
ajst-21789	147	12	-	-	PUNCT
ajst-21789	147	13	bp	bp	PROPN
ajst-21789	147	14	model	model	NOUN
ajst-21789	147	15	,	,	PUNCT
ajst-21789	147	16	pcapso	pcapso	ADJ
ajst-21789	147	17	-	-	PUNCT
ajst-21789	147	18	bp	bp	PROPN
ajst-21789	147	19	model	model	NOUN
ajst-21789	147	20	and	and	CCONJ
ajst-21789	147	21	ipca	ipca	PROPN
ajst-21789	147	22	-	-	PUNCT
ajst-21789	147	23	pso	pso	NOUN
ajst-21789	147	24	-	-	PUNCT
ajst-21789	147	25	bp	bp	PROPN
ajst-21789	147	26	model	model	NOUN
ajst-21789	147	27	,	,	PUNCT
ajst-21789	147	28	were	be	AUX
ajst-21789	147	29	established	establish	VERB
ajst-21789	147	30	respectively	respectively	ADV
ajst-21789	147	31	,	,	PUNCT
ajst-21789	147	32	and	and	CCONJ
ajst-21789	147	33	the	the	DET
ajst-21789	147	34	amount	amount	NOUN
ajst-21789	147	35	of	of	ADP
ajst-21789	147	36	gas	gas	NOUN
ajst-21789	147	37	emission	emission	NOUN
ajst-21789	147	38	was	be	AUX
ajst-21789	147	39	predicted	predict	VERB
ajst-21789	147	40	,	,	PUNCT
ajst-21789	147	41	and	and	CCONJ
ajst-21789	147	42	the	the	DET
ajst-21789	147	43	predicted	predict	VERB
ajst-21789	147	44	results	result	NOUN
ajst-21789	147	45	were	be	AUX
ajst-21789	147	46	compared	compare	VERB
ajst-21789	147	47	with	with	ADP
ajst-21789	147	48	ipca	ipca	NOUN
ajst-21789	147	49	-	-	PUNCT
ajst-21789	147	50	cpsobp	cpsobp	NOUN
ajst-21789	147	51	algorithm	algorithm	NOUN
ajst-21789	147	52	.	.	PUNCT
ajst-21789	148	1	through	through	ADP
ajst-21789	148	2	the	the	DET
ajst-21789	148	3	result	result	NOUN
ajst-21789	148	4	analysis	analysis	NOUN
ajst-21789	148	5	,	,	PUNCT
ajst-21789	148	6	it	it	PRON
ajst-21789	148	7	is	be	AUX
ajst-21789	148	8	found	find	VERB
ajst-21789	148	9	that	that	SCONJ
ajst-21789	148	10	the	the	DET
ajst-21789	148	11	principal	principal	ADJ
ajst-21789	148	12	component	component	NOUN
ajst-21789	148	13	analysis	analysis	NOUN
ajst-21789	148	14	method	method	NOUN
ajst-21789	148	15	controls	control	VERB
ajst-21789	148	16	the	the	DET
ajst-21789	148	17	stability	stability	NOUN
ajst-21789	148	18	of	of	ADP
ajst-21789	148	19	the	the	DET
ajst-21789	148	20	model	model	NOUN
ajst-21789	148	21	operation	operation	NOUN
ajst-21789	148	22	,	,	PUNCT
ajst-21789	148	23	the	the	DET
ajst-21789	148	24	particle	particle	NOUN
ajst-21789	148	25	swarm	swarm	NOUN
ajst-21789	148	26	optimization	optimization	NOUN
ajst-21789	148	27	algorithm	algorithm	NOUN
ajst-21789	148	28	controls	control	VERB
ajst-21789	148	29	the	the	DET
ajst-21789	148	30	prediction	prediction	NOUN
ajst-21789	148	31	accuracy	accuracy	NOUN
ajst-21789	148	32	of	of	ADP
ajst-21789	148	33	the	the	DET
ajst-21789	148	34	model	model	NOUN
ajst-21789	148	35	,	,	PUNCT
ajst-21789	148	36	and	and	CCONJ
ajst-21789	148	37	the	the	DET
ajst-21789	148	38	calculation	calculation	NOUN
ajst-21789	148	39	accuracy	accuracy	NOUN
ajst-21789	148	40	of	of	ADP
ajst-21789	148	41	ipca	ipca	PROPN
ajst-21789	148	42	-	-	PUNCT
ajst-21789	148	43	cpso	cpso	NOUN
ajst-21789	148	44	-	-	PUNCT
ajst-21789	148	45	bp	bp	PROPN
ajst-21789	148	46	model	model	NOUN
ajst-21789	148	47	is	be	AUX
ajst-21789	148	48	about	about	ADV
ajst-21789	148	49	3	3	NUM
ajst-21789	148	50	times	time	NOUN
ajst-21789	148	51	that	that	DET
ajst-21789	148	52	of	of	ADP
ajst-21789	148	53	bp	bp	PROPN
ajst-21789	148	54	neural	neural	PROPN
ajst-21789	148	55	network	network	PROPN
ajst-21789	148	56	model	model	NOUN
ajst-21789	148	57	.	.	PUNCT
ajst-21789	149	1	the	the	DET
ajst-21789	149	2	data	datum	NOUN
ajst-21789	149	3	confirm	confirm	VERB
ajst-21789	149	4	the	the	DET
ajst-21789	149	5	feasibility	feasibility	NOUN
ajst-21789	149	6	of	of	ADP
ajst-21789	149	7	the	the	DET
ajst-21789	149	8	ipca	ipca	PROPN
ajst-21789	149	9	-	-	PUNCT
ajst-21789	149	10	cpso	cpso	NOUN
ajst-21789	149	11	-	-	PUNCT
ajst-21789	149	12	bp	bp	PROPN
ajst-21789	149	13	neural	neural	ADJ
ajst-21789	149	14	network	network	NOUN
ajst-21789	149	15	prediction	prediction	NOUN
ajst-21789	149	16	model	model	NOUN
ajst-21789	149	17	studied	study	VERB
ajst-21789	149	18	in	in	ADP
ajst-21789	149	19	this	this	DET
ajst-21789	149	20	paper	paper	NOUN
ajst-21789	149	21	in	in	ADP
ajst-21789	149	22	the	the	DET
ajst-21789	149	23	prediction	prediction	NOUN
ajst-21789	149	24	of	of	ADP
ajst-21789	149	25	gas	gas	NOUN
ajst-21789	149	26	emission	emission	NOUN
ajst-21789	149	27	quantity	quantity	NOUN
ajst-21789	149	28	,	,	PUNCT
ajst-21789	149	29	and	and	CCONJ
ajst-21789	149	30	also	also	ADV
ajst-21789	149	31	has	have	VERB
ajst-21789	149	32	a	a	DET
ajst-21789	149	33	certain	certain	ADJ
ajst-21789	149	34	reliability	reliability	NOUN
ajst-21789	149	35	in	in	ADP
ajst-21789	149	36	the	the	DET
ajst-21789	149	37	prediction	prediction	NOUN
ajst-21789	149	38	effect	effect	NOUN
ajst-21789	149	39	.	.	PUNCT
ajst-21789	150	1	references	reference	NOUN
ajst-21789	150	2	[	[	X
ajst-21789	150	3	1	1	X
ajst-21789	150	4	]	]	X
ajst-21789	150	5	qin	qin	PROPN
ajst-21789	150	6	y	y	PROPN
ajst-21789	150	7	j	j	PROPN
ajst-21789	150	8	,	,	PUNCT
ajst-21789	150	9	su	su	PROPN
ajst-21789	150	10	w	w	PROPN
ajst-21789	150	11	w	w	PROPN
ajst-21789	150	12	,	,	PUNCT
ajst-21789	150	13	jiang	jiang	PROPN
ajst-21789	150	14	w	w	PROPN
ajst-21789	150	15	z	z	PROPN
ajst-21789	150	16	,	,	PUNCT
ajst-21789	150	17	et	et	PROPN
ajst-21789	150	18	al	al	PROPN
ajst-21789	150	19	.	.	PUNCT
ajst-21789	150	20	research	research	NOUN
ajst-21789	150	21	progress	progress	NOUN
ajst-21789	150	22	and	and	CCONJ
ajst-21789	150	23	development	development	NOUN
ajst-21789	150	24	direction	direction	NOUN
ajst-21789	150	25	of	of	ADP
ajst-21789	150	26	mine	mine	ADJ
ajst-21789	150	27	gas	gas	NOUN
ajst-21789	150	28	emission	emission	NOUN
ajst-21789	150	29	forecast	forecast	NOUN
ajst-21789	150	30	technology	technology	NOUN
ajst-21789	150	31	in	in	ADP
ajst-21789	150	32	china[j	china[j	PROPN
ajst-21789	150	33	]	]	PUNCT
ajst-21789	150	34	.	.	PUNCT
ajst-21789	151	1	safety	safety	NOUN
ajst-21789	151	2	in	in	ADP
ajst-21789	151	3	coal	coal	NOUN
ajst-21789	151	4	mines	mine	NOUN
ajst-21789	151	5	.	.	PUNCT
ajst-21789	152	1	2020	2020	NUM
ajst-21789	152	2	,	,	PUNCT
ajst-21789	152	3	51(10	51(10	NUM
ajst-21789	152	4	):	):	PUNCT
ajst-21789	152	5	52	52	NUM
ajst-21789	152	6	-	-	SYM
ajst-21789	152	7	59	59	NUM
ajst-21789	152	8	.	.	PUNCT
ajst-21789	153	1	26	26	NUM
ajst-21789	153	2	27	27	NUM
ajst-21789	153	3	28	28	NUM
ajst-21789	153	4	29	29	NUM
ajst-21789	153	5	30	30	NUM
ajst-21789	153	6	14.5	14.5	NUM
ajst-21789	153	7	15.0	15.0	NUM
ajst-21789	153	8	15.5	15.5	NUM
ajst-21789	153	9	16.0	16.0	NUM
ajst-21789	153	10	16.5	16.5	NUM
ajst-21789	153	11	17.0	17.0	NUM
ajst-21789	153	12	g	g	NOUN
ajst-21789	153	13	as	as	SCONJ
ajst-21789	153	14	e	e	PROPN
ajst-21789	153	15	m	m	NOUN
ajst-21789	153	16	is	be	AUX
ajst-21789	153	17	si	si	X
ajst-21789	153	18	on	on	ADP
ajst-21789	153	19	(	(	PUNCT
ajst-21789	153	20	m	m	PROPN
ajst-21789	153	21	3	3	NUM
ajst-21789	153	22	/m	/m	PUNCT
ajst-21789	153	23	in	in	ADP
ajst-21789	153	24	)	)	PUNCT
ajst-21789	154	1	group	group	NOUN
ajst-21789	154	2	actual	actual	ADJ
ajst-21789	154	3	value	value	NOUN
ajst-21789	154	4	ipca	ipca	PROPN
ajst-21789	154	5	-	-	PUNCT
ajst-21789	154	6	cpso	cpso	NOUN
ajst-21789	154	7	-	-	PUNCT
ajst-21789	154	8	bp	bp	PROPN
ajst-21789	154	9	bp	bp	PROPN
ajst-21789	154	10	pso	pso	PROPN
ajst-21789	154	11	-	-	PUNCT
ajst-21789	154	12	bp	bp	PROPN
ajst-21789	154	13	pca	pca	PROPN
ajst-21789	154	14	-	-	PUNCT
ajst-21789	154	15	pso	pso	NOUN
ajst-21789	154	16	-	-	PUNCT
ajst-21789	154	17	bp	bp	PROPN
ajst-21789	154	18	ipca	ipca	PROPN
ajst-21789	154	19	-	-	PUNCT
ajst-21789	154	20	pso	pso	NOUN
ajst-21789	154	21	-	-	PUNCT
ajst-21789	154	22	bp	bp	PROPN
ajst-21789	154	23	0	0	NUM
ajst-21789	154	24	50	50	NUM
ajst-21789	154	25	100	100	NUM
ajst-21789	154	26	150	150	NUM
ajst-21789	154	27	200	200	NUM
ajst-21789	154	28	0.02	0.02	NUM
ajst-21789	154	29	0.04	0.04	NUM
ajst-21789	154	30	0.06	0.06	NUM
ajst-21789	154	31	0.08	0.08	NUM
ajst-21789	154	32	0.10	0.10	NUM
ajst-21789	154	33	f	f	NOUN
ajst-21789	154	34	itn	itn	NOUN
ajst-21789	154	35	es	es	X
ajst-21789	154	36	s	s	PROPN
ajst-21789	154	37	va	va	PROPN
ajst-21789	154	38	lu	lu	PROPN
ajst-21789	154	39	e	e	NOUN
ajst-21789	154	40	number	number	NOUN
ajst-21789	154	41	of	of	ADP
ajst-21789	154	42	iterations	iteration	NOUN
ajst-21789	154	43	pso	pso	NOUN
ajst-21789	154	44	-	-	PUNCT
ajst-21789	154	45	bp	bp	PROPN
ajst-21789	154	46	pca	pca	PROPN
ajst-21789	154	47	-	-	PUNCT
ajst-21789	154	48	pso	pso	NOUN
ajst-21789	154	49	-	-	PUNCT
ajst-21789	154	50	bp	bp	PROPN
ajst-21789	154	51	ipca	ipca	PROPN
ajst-21789	154	52	-	-	PUNCT
ajst-21789	154	53	pso	pso	NOUN
ajst-21789	154	54	-	-	PUNCT
ajst-21789	154	55	bp	bp	PROPN
ajst-21789	154	56	ipca	ipca	PROPN
ajst-21789	154	57	-	-	PUNCT
ajst-21789	154	58	cpso	cpso	NOUN
ajst-21789	154	59	-	-	PUNCT
ajst-21789	154	60	bp	bp	PROPN
ajst-21789	154	61	204	204	NUM
ajst-21789	154	62	[	[	X
ajst-21789	154	63	2	2	NUM
ajst-21789	154	64	]	]	SYM
ajst-21789	154	65	li	li	PROPN
ajst-21789	154	66	r	r	PROPN
ajst-21789	154	67	q	q	PROPN
ajst-21789	154	68	,	,	PUNCT
ajst-21789	154	69	shi	shi	PROPN
ajst-21789	154	70	s	s	PROPN
ajst-21789	154	71	l	l	NOUN
ajst-21789	154	72	,	,	PUNCT
ajst-21789	154	73	nian	nian	ADJ
ajst-21789	154	74	q	q	ADJ
ajst-21789	154	75	f	f	X
ajst-21789	154	76	,	,	PUNCT
ajst-21789	154	77	et	et	PROPN
ajst-21789	154	78	al	al	PROPN
ajst-21789	154	79	.	.	PROPN
ajst-21789	154	80	research	research	NOUN
ajst-21789	154	81	on	on	ADP
ajst-21789	154	82	coalmine	coalmine	NOUN
ajst-21789	154	83	gas	gas	NOUN
ajst-21789	154	84	accident	accident	NOUN
ajst-21789	154	85	rules	rule	NOUN
ajst-21789	154	86	in	in	ADP
ajst-21789	154	87	china	china	PROPN
ajst-21789	154	88	in	in	ADP
ajst-21789	154	89	recent	recent	ADJ
ajst-21789	154	90	decade[j	decade[j	PROPN
ajst-21789	154	91	]	]	PUNCT
ajst-21789	154	92	.	.	PUNCT
ajst-21789	155	1	china	china	PROPN
ajst-21789	155	2	safety	safety	PROPN
ajst-21789	155	3	science	science	PROPN
ajst-21789	155	4	journal	journal	PROPN
ajst-21789	155	5	.	.	PUNCT
ajst-21789	156	1	2011	2011	NUM
ajst-21789	156	2	,	,	PUNCT
ajst-21789	156	3	21(09	21(09	NUM
ajst-21789	156	4	):	):	PUNCT
ajst-21789	156	5	143	143	NUM
ajst-21789	156	6	-	-	SYM
ajst-21789	156	7	151	151	NUM
ajst-21789	156	8	.	.	PUNCT
ajst-21789	157	1	[	[	X
ajst-21789	157	2	3	3	X
ajst-21789	157	3	]	]	X
ajst-21789	157	4	wu	wu	PROPN
ajst-21789	157	5	s	s	PROPN
ajst-21789	157	6	y	y	PROPN
ajst-21789	157	7	,	,	PUNCT
ajst-21789	157	8	zhang	zhang	PROPN
ajst-21789	157	9	j	j	PROPN
ajst-21789	157	10	l	l	PROPN
ajst-21789	157	11	,	,	PUNCT
ajst-21789	157	12	han	han	PROPN
ajst-21789	157	13	t	t	PROPN
ajst-21789	157	14	t	t	PROPN
ajst-21789	157	15	,	,	PUNCT
ajst-21789	157	16	et	et	PROPN
ajst-21789	157	17	al	al	PROPN
ajst-21789	157	18	.	.	PUNCT
ajst-21789	157	19	revision	revision	NOUN
ajst-21789	157	20	suggestions	suggestion	NOUN
ajst-21789	157	21	on	on	ADP
ajst-21789	157	22	“	"	PUNCT
ajst-21789	157	23	prediction	prediction	NOUN
ajst-21789	157	24	methods	method	NOUN
ajst-21789	157	25	of	of	ADP
ajst-21789	157	26	mine	mine	ADJ
ajst-21789	157	27	gas	gas	NOUN
ajst-21789	157	28	emission	emission	NOUN
ajst-21789	157	29	rate	rate	NOUN
ajst-21789	157	30	”	"	PUNCT
ajst-21789	157	31	industry	industry	NOUN
ajst-21789	157	32	standard[j	standard[j	PROPN
ajst-21789	157	33	]	]	PUNCT
ajst-21789	157	34	.	.	PUNCT
ajst-21789	158	1	china	china	PROPN
ajst-21789	158	2	coal	coal	PROPN
ajst-21789	158	3	.	.	PUNCT
ajst-21789	159	1	2012	2012	NUM
ajst-21789	159	2	,	,	PUNCT
ajst-21789	159	3	38(09	38(09	NUM
ajst-21789	159	4	):	):	PUNCT
ajst-21789	159	5	117	117	NUM
ajst-21789	159	6	-	-	SYM
ajst-21789	159	7	120	120	NUM
ajst-21789	159	8	.	.	PUNCT
ajst-21789	160	1	[	[	X
ajst-21789	160	2	4	4	X
ajst-21789	160	3	]	]	PUNCT
ajst-21789	160	4	xie	xie	PROPN
ajst-21789	160	5	m	m	PROPN
ajst-21789	160	6	j	j	PROPN
ajst-21789	160	7	,	,	PUNCT
ajst-21789	160	8	ma	ma	PROPN
ajst-21789	160	9	s	s	PROPN
ajst-21789	160	10	q.	q.	PROPN
ajst-21789	160	11	prediction	prediction	NOUN
ajst-21789	160	12	of	of	ADP
ajst-21789	160	13	coal	coal	NOUN
ajst-21789	160	14	mine	mine	NOUN
ajst-21789	160	15	gas	gas	NOUN
ajst-21789	160	16	emission	emission	NOUN
ajst-21789	160	17	based	base	VERB
ajst-21789	160	18	on	on	ADP
ajst-21789	160	19	multiple	multiple	ADJ
ajst-21789	160	20	linear	linear	ADJ
ajst-21789	160	21	regression	regression	NOUN
ajst-21789	160	22	theory[j	theory[j	NOUN
ajst-21789	160	23	]	]	PUNCT
ajst-21789	160	24	.	.	PUNCT
ajst-21789	161	1	shaanxi	shaanxi	PROPN
ajst-21789	161	2	coal	coal	PROPN
ajst-21789	161	3	.	.	PUNCT
ajst-21789	162	1	2021	2021	NUM
ajst-21789	162	2	,	,	PUNCT
ajst-21789	162	3	40(01	40(01	NUM
ajst-21789	162	4	):	):	PUNCT
ajst-21789	162	5	26	26	NUM
ajst-21789	162	6	-	-	SYM
ajst-21789	162	7	29	29	NUM
ajst-21789	162	8	.	.	PUNCT
ajst-21789	163	1	[	[	X
ajst-21789	163	2	5	5	X
ajst-21789	163	3	]	]	X
ajst-21789	163	4	sun	sun	NOUN
ajst-21789	163	5	x	x	SYM
ajst-21789	163	6	y.	y.	PROPN
ajst-21789	163	7	research	research	PROPN
ajst-21789	163	8	and	and	CCONJ
ajst-21789	163	9	application	application	NOUN
ajst-21789	163	10	of	of	ADP
ajst-21789	163	11	neural	neural	ADJ
ajst-21789	163	12	network	network	NOUN
ajst-21789	163	13	gas	gas	NOUN
ajst-21789	163	14	emission	emission	NOUN
ajst-21789	163	15	prediction	prediction	NOUN
ajst-21789	163	16	system[j	system[j	NOUN
ajst-21789	163	17	]	]	PUNCT
ajst-21789	163	18	.	.	PUNCT
ajst-21789	164	1	coal	coal	NOUN
ajst-21789	164	2	mine	mine	PROPN
ajst-21789	164	3	modernization	modernization	NOUN
ajst-21789	164	4	.	.	PUNCT
ajst-21789	165	1	2023	2023	NUM
ajst-21789	165	2	,	,	PUNCT
ajst-21789	165	3	32(05	32(05	NUM
ajst-21789	165	4	):	):	PUNCT
ajst-21789	165	5	65	65	NUM
ajst-21789	165	6	-	-	SYM
ajst-21789	165	7	68	68	NUM
ajst-21789	165	8	.	.	PUNCT
ajst-21789	166	1	[	[	X
ajst-21789	166	2	6	6	NUM
ajst-21789	166	3	]	]	PUNCT
ajst-21789	166	4	lu	lu	PROPN
ajst-21789	166	5	g	g	PROPN
ajst-21789	166	6	b	b	PROPN
ajst-21789	166	7	,	,	PUNCT
ajst-21789	166	8	kang	kang	PROPN
ajst-21789	166	9	j	j	PROPN
ajst-21789	166	10	k	k	PROPN
ajst-21789	166	11	,	,	PUNCT
ajst-21789	166	12	bai	bai	PROPN
ajst-21789	166	13	g	g	PROPN
ajst-21789	166	14	,	,	PUNCT
ajst-21789	166	15	et	et	PROPN
ajst-21789	166	16	al	al	PROPN
ajst-21789	166	17	.	.	PUNCT
ajst-21789	166	18	application	application	NOUN
ajst-21789	166	19	of	of	ADP
ajst-21789	166	20	pca	pca	PROPN
ajst-21789	166	21	-	-	PUNCT
ajst-21789	166	22	bp	bp	PROPN
ajst-21789	166	23	to	to	ADP
ajst-21789	166	24	gas	gas	NOUN
ajst-21789	166	25	emission	emission	NOUN
ajst-21789	166	26	prediction	prediction	NOUN
ajst-21789	166	27	of	of	ADP
ajst-21789	166	28	mining	mining	NOUN
ajst-21789	166	29	working	work	VERB
ajst-21789	166	30	face[j	face[j	PROPN
ajst-21789	166	31	]	]	PUNCT
ajst-21789	166	32	.	.	PUNCT
ajst-21789	167	1	journal	journal	PROPN
ajst-21789	167	2	of	of	ADP
ajst-21789	167	3	liaoning	liaoning	PROPN
ajst-21789	167	4	technical	technical	PROPN
ajst-21789	167	5	university	university	PROPN
ajst-21789	167	6	(	(	PUNCT
ajst-21789	167	7	natural	natural	ADJ
ajst-21789	167	8	science	science	NOUN
ajst-21789	167	9	)	)	PUNCT
ajst-21789	167	10	.	.	PUNCT
ajst-21789	168	1	2015	2015	NUM
ajst-21789	168	2	,	,	PUNCT
ajst-21789	168	3	34(12	34(12	NUM
ajst-21789	168	4	):	):	PUNCT
ajst-21789	168	5	1329	1329	NUM
ajst-21789	168	6	-	-	SYM
ajst-21789	168	7	1334	1334	NUM
ajst-21789	168	8	.	.	PUNCT
ajst-21789	169	1	[	[	X
ajst-21789	169	2	7	7	X
ajst-21789	169	3	]	]	X
ajst-21789	169	4	zhou	zhou	NOUN
ajst-21789	169	5	x	x	SYM
ajst-21789	169	6	h	h	NOUN
ajst-21789	169	7	,	,	PUNCT
ajst-21789	169	8	sun	sun	PROPN
ajst-21789	169	9	j	j	PROPN
ajst-21789	169	10	z.	z.	PROPN
ajst-21789	169	11	prediction	prediction	NOUN
ajst-21789	169	12	of	of	ADP
ajst-21789	169	13	gas	gas	NOUN
ajst-21789	169	14	emission	emission	NOUN
ajst-21789	169	15	based	base	VERB
ajst-21789	169	16	on	on	ADP
ajst-21789	169	17	principal	principal	ADJ
ajst-21789	169	18	factor	factor	NOUN
ajst-21789	169	19	analysis	analysis	NOUN
ajst-21789	169	20	and	and	CCONJ
ajst-21789	169	21	improved	improve	VERB
ajst-21789	169	22	bp	bp	PROPN
ajst-21789	169	23	neural	neural	ADJ
ajst-21789	169	24	network[j	network[j	PROPN
ajst-21789	169	25	]	]	PUNCT
ajst-21789	169	26	.	.	PUNCT
ajst-21789	170	1	mining	mining	NOUN
ajst-21789	170	2	safety	safety	PROPN
ajst-21789	170	3	&	&	CCONJ
ajst-21789	170	4	environmental	environmental	ADJ
ajst-21789	170	5	protection	protection	NOUN
ajst-21789	170	6	.	.	PUNCT
ajst-21789	171	1	2018	2018	NUM
ajst-21789	171	2	,	,	PUNCT
ajst-21789	171	3	45(06	45(06	NUM
ajst-21789	171	4	):	):	PUNCT
ajst-21789	171	5	4347	4347	NUM
ajst-21789	171	6	.	.	PUNCT
ajst-21789	172	1	[	[	X
ajst-21789	172	2	8	8	NUM
ajst-21789	172	3	]	]	X
ajst-21789	172	4	xiao	xiao	PROPN
ajst-21789	172	5	p	p	X
ajst-21789	172	6	,	,	PUNCT
ajst-21789	172	7	xie	xie	PROPN
ajst-21789	172	8	x	x	PROPN
ajst-21789	172	9	j	j	PROPN
ajst-21789	172	10	,	,	PUNCT
ajst-21789	172	11	shuang	shuang	PROPN
ajst-21789	172	12	h	h	PROPN
ajst-21789	173	1	q	q	PROPN
ajst-21789	173	2	,	,	PUNCT
ajst-21789	173	3	et	et	PROPN
ajst-21789	173	4	al	al	PROPN
ajst-21789	173	5	.	.	PROPN
ajst-21789	173	6	prediction	prediction	NOUN
ajst-21789	173	7	of	of	ADP
ajst-21789	173	8	gas	gas	NOUN
ajst-21789	173	9	emission	emission	NOUN
ajst-21789	173	10	quantity	quantity	NOUN
ajst-21789	173	11	based	base	VERB
ajst-21789	173	12	on	on	ADP
ajst-21789	173	13	kpca	kpca	NOUN
ajst-21789	173	14	-	-	PUNCT
ajst-21789	173	15	cmgann	cmgann	NOUN
ajst-21789	173	16	algorithm[j	algorithm[j	PROPN
ajst-21789	173	17	]	]	PUNCT
ajst-21789	173	18	.	.	PUNCT
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ajst-21789	174	2	safety	safety	PROPN
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ajst-21789	174	5	.	.	PUNCT
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ajst-21789	175	2	,	,	PUNCT
ajst-21789	175	3	30(05	30(05	PROPN
ajst-21789	175	4	):	):	PUNCT
ajst-21789	175	5	39	39	NUM
ajst-21789	175	6	-	-	SYM
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ajst-21789	175	8	.	.	PUNCT
ajst-21789	176	1	[	[	X
ajst-21789	176	2	9	9	NUM
ajst-21789	176	3	]	]	PUNCT
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ajst-21789	176	5	h	h	PROPN
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ajst-21789	176	7	,	,	PUNCT
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ajst-21789	176	11	,	,	PUNCT
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ajst-21789	176	13	j	j	PROPN
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ajst-21789	176	19	method	method	NOUN
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ajst-21789	176	21	application	application	NOUN
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ajst-21789	176	24	emission	emission	NOUN
ajst-21789	176	25	from	from	ADP
ajst-21789	176	26	mining	mining	NOUN
ajst-21789	176	27	workface	workface	NOUN
ajst-21789	176	28	based	base	VERB
ajst-21789	176	29	on	on	ADP
ajst-21789	176	30	stl	stl	PROPN
ajst-21789	176	31	-	-	PUNCT
ajst-21789	176	32	eemd	eemd	PROPN
ajst-21789	176	33	-	-	PROPN
ajst-21789	176	34	ga	ga	NOUN
ajst-21789	176	35	-	-	PUNCT
ajst-21789	176	36	svr[j	svr[j	NOUN
ajst-21789	176	37	]	]	PUNCT
ajst-21789	176	38	.	.	PUNCT
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ajst-21789	176	43	.	.	PUNCT
ajst-21789	177	1	2022	2022	NUM
ajst-21789	177	2	,	,	PUNCT
ajst-21789	177	3	50(12	50(12	NUM
ajst-21789	177	4	):	):	PUNCT
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ajst-21789	177	6	-	-	SYM
ajst-21789	177	7	141	141	NUM
ajst-21789	177	8	.	.	PUNCT
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ajst-21789	178	7	,	,	PUNCT
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ajst-21789	178	9	l	l	PROPN
ajst-21789	178	10	s	s	PROPN
ajst-21789	178	11	,	,	PUNCT
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ajst-21789	178	14	j	j	PROPN
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ajst-21789	178	17	al	al	PROPN
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ajst-21789	178	20	of	of	ADP
ajst-21789	178	21	pcapso	pcapso	ADJ
ajst-21789	178	22	-	-	PUNCT
ajst-21789	178	23	lssvm	lssvm	NOUN
ajst-21789	178	24	model	model	NOUN
ajst-21789	178	25	in	in	ADP
ajst-21789	178	26	gas	gas	NOUN
ajst-21789	178	27	emission	emission	NOUN
ajst-21789	178	28	prediction[j	prediction[j	PROPN
ajst-21789	178	29	]	]	PUNCT
ajst-21789	178	30	.	.	PUNCT
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ajst-21789	179	3	liaoning	liaoning	PROPN
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ajst-21789	179	5	university	university	PROPN
ajst-21789	179	6	(	(	PUNCT
ajst-21789	179	7	natural	natural	ADJ
ajst-21789	179	8	science	science	NOUN
ajst-21789	179	9	)	)	PUNCT
ajst-21789	179	10	.	.	PUNCT
ajst-21789	180	1	2019	2019	NUM
ajst-21789	180	2	,	,	PUNCT
ajst-21789	180	3	38(02	38(02	NUM
ajst-21789	180	4	):	):	PUNCT
ajst-21789	180	5	124	124	NUM
ajst-21789	180	6	-	-	SYM
ajst-21789	180	7	129	129	NUM
ajst-21789	180	8	.	.	PUNCT
ajst-21789	181	1	[	[	X
ajst-21789	181	2	11	11	NUM
ajst-21789	181	3	]	]	PUNCT
ajst-21789	181	4	xiao	xiao	PROPN
ajst-21789	181	5	p	p	X
ajst-21789	181	6	,	,	PUNCT
ajst-21789	181	7	xie	xie	PROPN
ajst-21789	181	8	x	x	PROPN
ajst-21789	181	9	j	j	PROPN
ajst-21789	181	10	,	,	PUNCT
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ajst-21789	181	12	h	h	PROPN
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ajst-21789	181	14	,	,	PUNCT
ajst-21789	181	15	et	et	PROPN
ajst-21789	181	16	al	al	PROPN
ajst-21789	181	17	.	.	PUNCT
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ajst-21789	181	19	of	of	ADP
ajst-21789	181	20	wavelet	wavelet	NOUN
ajst-21789	181	21	-	-	PUNCT
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ajst-21789	181	24	machine	machine	NOUN
ajst-21789	181	25	in	in	ADP
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ajst-21789	181	27	-	-	PUNCT
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ajst-21789	181	29	series	series	NOUN
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ajst-21789	181	31	of	of	ADP
ajst-21789	181	32	gas	gas	NOUN
ajst-21789	181	33	emission	emission	NOUN
ajst-21789	181	34	quantity[j	quantity[j	NOUN
ajst-21789	181	35	]	]	PUNCT
ajst-21789	181	36	.	.	PUNCT
ajst-21789	182	1	journal	journal	PROPN
ajst-21789	182	2	of	of	ADP
ajst-21789	182	3	xi	xi	PROPN
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ajst-21789	182	8	science	science	PROPN
ajst-21789	182	9	andtechnology	andtechnology	PROPN
ajst-21789	182	10	.	.	PUNCT
ajst-21789	183	1	2020	2020	NUM
ajst-21789	183	2	,	,	PUNCT
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ajst-21789	183	4	):	):	PUNCT
ajst-21789	183	5	839	839	NUM
ajst-21789	183	6	-	-	NUM
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ajst-21789	183	8	.	.	PUNCT
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ajst-21789	184	3	]	]	X
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ajst-21789	184	5	f.	f.	PROPN
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ajst-21789	184	9	emission	emission	NOUN
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ajst-21789	184	13	-	-	PUNCT
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ajst-21789	184	15	-	-	PUNCT
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ajst-21789	184	18	network[j	network[j	PROPN
ajst-21789	184	19	]	]	PUNCT
ajst-21789	184	20	.	.	PUNCT
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ajst-21789	185	2	in	in	ADP
ajst-21789	185	3	coal	coal	NOUN
ajst-21789	185	4	mines	mine	NOUN
ajst-21789	185	5	.	.	PUNCT
ajst-21789	186	1	2023	2023	NUM
ajst-21789	186	2	,	,	PUNCT
ajst-21789	186	3	54(04	54(04	NUM
ajst-21789	186	4	):	):	PUNCT
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ajst-21789	186	6	-	-	SYM
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ajst-21789	186	8	.	.	PUNCT
ajst-21789	187	1	[	[	X
ajst-21789	187	2	13	13	NUM
ajst-21789	187	3	]	]	X
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ajst-21789	187	5	h	h	NOUN
ajst-21789	187	6	,	,	PUNCT
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ajst-21789	187	9	,	,	PUNCT
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ajst-21789	187	13	,	,	PUNCT
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ajst-21789	187	24	-	-	PUNCT
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ajst-21789	187	27	]	]	PUNCT
ajst-21789	187	28	.	.	PUNCT
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ajst-21789	188	5	university	university	PROPN
ajst-21789	188	6	(	(	PUNCT
ajst-21789	188	7	natural	natural	ADJ
ajst-21789	188	8	science	science	NOUN
ajst-21789	188	9	)	)	PUNCT
ajst-21789	188	10	.	.	PUNCT
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ajst-21789	189	2	,	,	PUNCT
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ajst-21789	189	4	):	):	PUNCT
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ajst-21789	189	6	-	-	SYM
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ajst-21789	189	8	.	.	PUNCT
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ajst-21789	190	26	-	-	PUNCT
ajst-21789	190	27	lstm[j	lstm[j	VERB
ajst-21789	190	28	]	]	PUNCT
ajst-21789	190	29	.	.	PUNCT
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ajst-21789	191	2	safety	safety	PROPN
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ajst-21789	191	6	.	.	PUNCT
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ajst-21789	192	3	1	1	NUM
ajst-21789	192	4	-	-	SYM
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ajst-21789	192	6	.	.	PUNCT
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ajst-21789	193	3	]	]	X
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ajst-21789	193	5	x	x	PROPN
ajst-21789	193	6	,	,	PUNCT
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ajst-21789	194	9	.	.	PUNCT
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ajst-21789	194	18	-	-	PUNCT
ajst-21789	194	19	rf[j	rf[j	PROPN
ajst-21789	194	20	]	]	PUNCT
ajst-21789	194	21	.	.	PUNCT
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ajst-21789	195	2	safety	safety	PROPN
ajst-21789	195	3	&	&	CCONJ
ajst-21789	195	4	environmental	environmental	ADJ
ajst-21789	195	5	protection	protection	NOUN
ajst-21789	195	6	.	.	PUNCT
ajst-21789	196	1	2023	2023	NUM
ajst-21789	196	2	,	,	PUNCT
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ajst-21789	196	4	):	):	PUNCT
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ajst-21789	196	6	-	-	SYM
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ajst-21789	196	8	.	.	PUNCT
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ajst-21789	197	7	,	,	PUNCT
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ajst-21789	197	10	,	,	PUNCT
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ajst-21789	197	13	,	,	PUNCT
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ajst-21789	197	15	al	al	PROPN
ajst-21789	197	16	.	.	PUNCT
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ajst-21789	197	22	gas	gas	NOUN
ajst-21789	197	23	in	in	ADP
ajst-21789	197	24	bintang	bintang	PROPN
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ajst-21789	197	26	area	area	NOUN
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ajst-21789	197	29	rank	rank	NOUN
ajst-21789	197	30	coal	coal	NOUN
ajst-21789	197	31	and	and	CCONJ
ajst-21789	197	32	high	high	ADJ
ajst-21789	197	33	mine	mine	ADJ
ajst-21789	197	34	gas[j	gas[j	PROPN
ajst-21789	197	35	]	]	PUNCT
ajst-21789	197	36	.	.	PUNCT
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ajst-21789	198	3	china	china	PROPN
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ajst-21789	198	5	society	society	NOUN
ajst-21789	198	6	.	.	PUNCT
ajst-21789	199	1	2019	2019	NUM
ajst-21789	199	2	,	,	PUNCT
ajst-21789	199	3	44(07	44(07	NUM
ajst-21789	199	4	):	):	PUNCT
ajst-21789	199	5	2151	2151	NUM
ajst-21789	199	6	-	-	SYM
ajst-21789	199	7	2158	2158	NUM
ajst-21789	199	8	.	.	PUNCT
ajst-21789	200	1	[	[	X
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ajst-21789	200	5	c	c	PROPN
ajst-21789	200	6	,	,	PUNCT
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ajst-21789	200	9	c	c	PROPN
ajst-21789	200	10	,	,	PUNCT
ajst-21789	200	11	sun	sun	PROPN
ajst-21789	200	12	x	x	SYM
ajst-21789	200	13	y	y	PROPN
ajst-21789	200	14	,	,	PUNCT
ajst-21789	200	15	et	et	PROPN
ajst-21789	200	16	al	al	PROPN
ajst-21789	200	17	.	.	PROPN
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ajst-21789	200	20	practice	practice	NOUN
ajst-21789	200	21	of	of	ADP
ajst-21789	200	22	gas	gas	NOUN
ajst-21789	200	23	geological	geological	ADJ
ajst-21789	200	24	grading	grading	NOUN
ajst-21789	200	25	evaluation	evaluation	NOUN
ajst-21789	200	26	on	on	ADP
ajst-21789	200	27	coal	coal	NOUN
ajst-21789	200	28	mining	mining	NOUN
ajst-21789	200	29	face	face	NOUN
ajst-21789	200	30	of	of	ADP
ajst-21789	200	31	high	high	ADJ
ajst-21789	200	32	gas	gas	NOUN
ajst-21789	200	33	m[j	m[j	NOUN
ajst-21789	200	34	]	]	PUNCT
ajst-21789	200	35	.	.	PUNCT
ajst-21789	201	1	journal	journal	PROPN
ajst-21789	201	2	of	of	ADP
ajst-21789	201	3	china	china	PROPN
ajst-21789	201	4	coal	coal	PROPN
ajst-21789	201	5	society	society	NOUN
ajst-21789	201	6	.	.	PUNCT
ajst-21789	202	1	2019	2019	NUM
ajst-21789	202	2	,	,	PUNCT
ajst-21789	202	3	44(08	44(08	NUM
ajst-21789	202	4	):	):	PUNCT
ajst-21789	202	5	2409	2409	NUM
ajst-21789	202	6	-	-	SYM
ajst-21789	202	7	2418	2418	NUM
ajst-21789	202	8	.	.	PUNCT
ajst-21789	203	1	[	[	X
ajst-21789	203	2	18	18	NUM
ajst-21789	203	3	]	]	SYM
ajst-21789	203	4	eberhart	eberhart	NOUN
ajst-21789	203	5	,	,	PUNCT
ajst-21789	203	6	kennedy	kennedy	PROPN
ajst-21789	203	7	.	.	PUNCT
ajst-21789	204	1	a	a	DET
ajst-21789	204	2	new	new	ADJ
ajst-21789	204	3	optimizer	optimizer	NOUN
ajst-21789	204	4	using	use	VERB
ajst-21789	204	5	particle	particle	NOUN
ajst-21789	204	6	swarm	swarm	NOUN
ajst-21789	204	7	theory[c	theory[c	NOUN
ajst-21789	204	8	]	]	PUNCT
ajst-21789	204	9	.	.	PUNCT
ajst-21789	205	1	nagoya	nagoya	PROPN
ajst-21789	205	2	,	,	PUNCT
ajst-21789	205	3	japan	japan	PROPN
ajst-21789	205	4	:	:	PUNCT
ajst-21789	205	5	ieee	ieee	NOUN
ajst-21789	205	6	,	,	PUNCT
ajst-21789	205	7	1995	1995	NUM
ajst-21789	205	8	.	.	PUNCT
ajst-21789	206	1	[	[	X
ajst-21789	206	2	19	19	NUM
ajst-21789	206	3	]	]	X
ajst-21789	206	4	kang	kang	PROPN
ajst-21789	206	5	y	y	PROPN
ajst-21789	206	6	s	s	PROPN
ajst-21789	206	7	,	,	PUNCT
ajst-21789	206	8	zang	zang	PROPN
ajst-21789	206	9	s	s	PROPN
ajst-21789	206	10	l.	l.	PROPN
ajst-21789	206	11	improved	improve	VERB
ajst-21789	206	12	particle	particle	NOUN
ajst-21789	206	13	swarm	swarm	NOUN
ajst-21789	206	14	optimization	optimization	NOUN
ajst-21789	206	15	algorithm	algorithm	NOUN
ajst-21789	206	16	based	base	VERB
ajst-21789	206	17	on	on	ADP
ajst-21789	206	18	multiple	multiple	ADJ
ajst-21789	206	19	strategies[j	strategies[j	NOUN
ajst-21789	206	20	]	]	PUNCT
ajst-21789	206	21	.	.	PUNCT
ajst-21789	207	1	journal	journal	PROPN
ajst-21789	207	2	of	of	ADP
ajst-21789	207	3	northeastern	northeastern	ADJ
ajst-21789	207	4	university	university	PROPN
ajst-21789	207	5	(	(	PUNCT
ajst-21789	207	6	natural	natural	ADJ
ajst-21789	207	7	science	science	NOUN
ajst-21789	207	8	)	)	PUNCT
ajst-21789	207	9	.	.	PUNCT
ajst-21789	208	1	2023	2023	NUM
ajst-21789	208	2	,	,	PUNCT
ajst-21789	208	3	44(08	44(08	NUM
ajst-21789	208	4	):	):	PUNCT
ajst-21789	208	5	1089	1089	NUM
ajst-21789	208	6	-	-	SYM
ajst-21789	208	7	1097	1097	NUM
ajst-21789	208	8	.	.	PUNCT
ajst-21789	209	1	[	[	X
ajst-21789	209	2	20	20	NUM
ajst-21789	209	3	]	]	X
ajst-21789	209	4	zhang	zhang	PROPN
ajst-21789	209	5	h	h	PROPN
ajst-21789	209	6	,	,	PUNCT
ajst-21789	209	7	wang	wang	PROPN
ajst-21789	209	8	x	x	PROPN
ajst-21789	209	9	l.	l.	PROPN
ajst-21789	209	10	adaptive	adaptive	PROPN
ajst-21789	209	11	inertia	inertia	PROPN
ajst-21789	209	12	weight	weight	NOUN
ajst-21789	209	13	particle	particle	NOUN
ajst-21789	209	14	swarm	swarm	NOUN
ajst-21789	209	15	optimization	optimization	NOUN
ajst-21789	209	16	algorithm[j	algorithm[j	PROPN
ajst-21789	209	17	]	]	PUNCT
ajst-21789	209	18	.	.	PUNCT
ajst-21789	210	1	intelligent	intelligent	ADJ
ajst-21789	210	2	computer	computer	NOUN
ajst-21789	210	3	and	and	CCONJ
ajst-21789	210	4	applications	application	NOUN
ajst-21789	210	5	.	.	PUNCT
ajst-21789	211	1	2023	2023	NUM
ajst-21789	211	2	,	,	PUNCT
ajst-21789	211	3	13(09	13(09	NUM
ajst-21789	211	4	):	):	PUNCT
ajst-21789	211	5	5	5	NUM
ajst-21789	211	6	-	-	SYM
ajst-21789	211	7	8	8	NUM
ajst-21789	211	8	.	.	PUNCT
ajst-21789	212	1	[	[	X
ajst-21789	212	2	21	21	NUM
ajst-21789	212	3	]	]	X
ajst-21789	212	4	eberhart	eberhart	NOUN
ajst-21789	212	5	,	,	PUNCT
ajst-21789	212	6	y.	y.	PROPN
ajst-21789	212	7	shi	shi	PROPN
ajst-21789	212	8	.	.	PUNCT
ajst-21789	212	9	comparing	compare	VERB
ajst-21789	212	10	inertia	inertia	NOUN
ajst-21789	212	11	weights	weight	NOUN
ajst-21789	212	12	and	and	CCONJ
ajst-21789	212	13	constriction	constriction	NOUN
ajst-21789	212	14	factors	factor	NOUN
ajst-21789	212	15	in	in	ADP
ajst-21789	212	16	particle	particle	NOUN
ajst-21789	212	17	swarm	swarm	NOUN
ajst-21789	212	18	optimization[c	optimization[c	ADV
ajst-21789	212	19	]	]	PUNCT
ajst-21789	212	20	.	.	PUNCT
ajst-21789	213	1	la	la	PROPN
ajst-21789	213	2	jolla	jolla	PROPN
ajst-21789	213	3	,	,	PUNCT
ajst-21789	213	4	ca	ca	PROPN
ajst-21789	213	5	,	,	PUNCT
ajst-21789	213	6	usa	usa	PROPN
ajst-21789	213	7	:	:	PUNCT
ajst-21789	213	8	cec00	cec00	PROPN
ajst-21789	213	9	,	,	PUNCT
ajst-21789	213	10	2000	2000	NUM
ajst-21789	213	11	.	.	PUNCT
ajst-21789	214	1	[	[	X
ajst-21789	214	2	22	22	NUM
ajst-21789	214	3	]	]	SYM
ajst-21789	214	4	vandenbergh	vandenbergh	NOUN
ajst-21789	214	5	,	,	PUNCT
ajst-21789	214	6	engelbrecht	engelbrecht	NOUN
ajst-21789	214	7	.	.	PUNCT
ajst-21789	215	1	a	a	DET
ajst-21789	215	2	cooperative	cooperative	ADJ
ajst-21789	215	3	approach	approach	NOUN
ajst-21789	215	4	to	to	ADP
ajst-21789	215	5	particle	particle	NOUN
ajst-21789	215	6	swarm	swarm	NOUN
ajst-21789	215	7	optimization[j	optimization[j	NOUN
ajst-21789	215	8	]	]	PUNCT
ajst-21789	215	9	.	.	PUNCT
ajst-21789	216	1	ieee	ieee	NOUN
ajst-21789	216	2	transactions	transaction	NOUN
ajst-21789	216	3	on	on	ADP
ajst-21789	216	4	evolutionary	evolutionary	ADJ
ajst-21789	216	5	computation	computation	NOUN
ajst-21789	216	6	.	.	PUNCT
ajst-21789	217	1	2004	2004	NUM
ajst-21789	217	2	,	,	PUNCT
ajst-21789	217	3	8(3	8(3	NUM
ajst-21789	217	4	):	):	PUNCT
ajst-21789	217	5	225239	225239	NUM
ajst-21789	217	6	.	.	PUNCT
ajst-21789	218	1	[	[	X
ajst-21789	218	2	23	23	NUM
ajst-21789	218	3	]	]	X
ajst-21789	218	4	liu	liu	PROPN
ajst-21789	218	5	y	y	PROPN
ajst-21789	218	6	d	d	PROPN
ajst-21789	218	7	,	,	PUNCT
ajst-21789	218	8	zhou	zhou	PROPN
ajst-21789	218	9	m	m	PROPN
ajst-21789	218	10	r	r	PROPN
ajst-21789	218	11	,	,	PUNCT
ajst-21789	218	12	xie	xie	PROPN
ajst-21789	218	13	j	j	PROPN
ajst-21789	218	14	y	y	PROPN
ajst-21789	218	15	,	,	PUNCT
ajst-21789	218	16	et	et	PROPN
ajst-21789	218	17	al	al	PROPN
ajst-21789	218	18	.	.	PROPN
ajst-21789	218	19	research	research	PROPN
ajst-21789	218	20	on	on	ADP
ajst-21789	218	21	simulation	simulation	NOUN
ajst-21789	218	22	model	model	NOUN
ajst-21789	218	23	for	for	ADP
ajst-21789	218	24	data	data	NOUN
ajst-21789	218	25	assimilation	assimilation	NOUN
ajst-21789	218	26	in	in	ADP
ajst-21789	218	27	solar	solar	ADJ
ajst-21789	218	28	radiation	radiation	NOUN
ajst-21789	218	29	prediction	prediction	NOUN
ajst-21789	218	30	based	base	VERB
ajst-21789	218	31	on	on	ADP
ajst-21789	218	32	particle	particle	NOUN
ajst-21789	218	33	swarm	swarm	NOUN
ajst-21789	218	34	optimizer	optimizer	NOUN
ajst-21789	218	35	with	with	ADP
ajst-21789	218	36	time	time	NOUN
ajst-21789	218	37	varying	vary	VERB
ajst-21789	218	38	constrict	constrict	ADJ
ajst-21789	218	39	factor[j	factor[j	NOUN
ajst-21789	218	40	]	]	PUNCT
ajst-21789	218	41	.	.	PUNCT
ajst-21789	219	1	acta	acta	PROPN
ajst-21789	219	2	energeia	energeia	PROPN
ajst-21789	219	3	solaris	solaris	PROPN
ajst-21789	219	4	sonica	sonica	PROPN
ajst-21789	219	5	.	.	PUNCT
ajst-21789	220	1	2021	2021	NUM
ajst-21789	220	2	,	,	PUNCT
ajst-21789	220	3	42(04	42(04	NOUN
ajst-21789	220	4	):	):	PUNCT
ajst-21789	220	5	181	181	NUM
ajst-21789	220	6	-	-	SYM
ajst-21789	220	7	185	185	NUM
ajst-21789	220	8	.	.	PUNCT
ajst-21789	221	1	[	[	X
ajst-21789	221	2	24	24	NUM
ajst-21789	221	3	]	]	X
ajst-21789	221	4	wang	wang	PROPN
ajst-21789	221	5	r	r	PROPN
ajst-21789	221	6	b	b	PROPN
ajst-21789	221	7	,	,	PUNCT
ajst-21789	221	8	xu	xu	PROPN
ajst-21789	221	9	h	h	PROPN
ajst-21789	221	10	y	y	PROPN
ajst-21789	221	11	,	,	PUNCT
ajst-21789	221	12	li	li	PROPN
ajst-21789	221	13	b	b	PROPN
ajst-21789	221	14	,	,	PUNCT
ajst-21789	221	15	et	et	PROPN
ajst-21789	221	16	al	al	PROPN
ajst-21789	221	17	.	.	PROPN
ajst-21789	221	18	research	research	NOUN
ajst-21789	221	19	on	on	ADP
ajst-21789	221	20	method	method	NOUN
ajst-21789	221	21	of	of	ADP
ajst-21789	221	22	determining	determine	VERB
ajst-21789	221	23	hidden	hidden	ADJ
ajst-21789	221	24	layer	layer	NOUN
ajst-21789	221	25	nodes	node	NOUN
ajst-21789	221	26	in	in	ADP
ajst-21789	221	27	bp	bp	PROPN
ajst-21789	221	28	neural	neural	PROPN
ajst-21789	221	29	network[j	network[j	PROPN
ajst-21789	221	30	]	]	PUNCT
ajst-21789	221	31	.	.	PUNCT
ajst-21789	222	1	computer	computer	NOUN
ajst-21789	222	2	technology	technology	NOUN
ajst-21789	222	3	and	and	CCONJ
ajst-21789	222	4	development	development	NOUN
ajst-21789	222	5	.	.	PUNCT
ajst-21789	223	1	2018	2018	NUM
ajst-21789	223	2	,	,	PUNCT
ajst-21789	223	3	28(04	28(04	NUM
ajst-21789	223	4	):	):	PUNCT
ajst-21789	223	5	31	31	NUM
ajst-21789	223	6	-	-	SYM
ajst-21789	223	7	35	35	NUM
ajst-21789	223	8	.	.	PUNCT