id	sid	tid	token	lemma	pos
ajst-11303	1	1	academic	academic	ADJ
ajst-11303	1	2	journal	journal	NOUN
ajst-11303	1	3	of	of	ADP
ajst-11303	1	4	science	science	NOUN
ajst-11303	1	5	and	and	CCONJ
ajst-11303	1	6	technology	technology	NOUN
ajst-11303	1	7	issn	issn	NOUN
ajst-11303	1	8	:	:	PUNCT
ajst-11303	1	9	2771	2771	NUM
ajst-11303	1	10	-	-	SYM
ajst-11303	1	11	3032	3032	NUM
ajst-11303	1	12	|	|	NOUN
ajst-11303	1	13	vol	vol	NOUN
ajst-11303	1	14	.	.	PROPN
ajst-11303	2	1	7	7	NUM
ajst-11303	2	2	,	,	PUNCT
ajst-11303	2	3	no	no	INTJ
ajst-11303	2	4	.	.	NOUN
ajst-11303	2	5	1	1	NUM
ajst-11303	2	6	,	,	PUNCT
ajst-11303	2	7	2023	2023	NUM
ajst-11303	2	8	156	156	NUM
ajst-11303	2	9	prediction	prediction	NOUN
ajst-11303	2	10	of	of	ADP
ajst-11303	2	11	cement	cement	NOUN
ajst-11303	2	12	slurry	slurry	NOUN
ajst-11303	2	13	density	density	NOUN
ajst-11303	2	14	based	base	VERB
ajst-11303	2	15	on	on	ADP
ajst-11303	2	16	amindrnn	amindrnn	PROPN
ajst-11303	2	17	ruohuan	ruohuan	PROPN
ajst-11303	2	18	liu	liu	PROPN
ajst-11303	2	19	,	,	PUNCT
ajst-11303	2	20	yazhi	yazhi	PROPN
ajst-11303	2	21	yang	yang	PROPN
ajst-11303	2	22	,	,	PUNCT
ajst-11303	2	23	bin	bin	PROPN
ajst-11303	2	24	wang	wang	PROPN
ajst-11303	2	25	and	and	CCONJ
ajst-11303	2	26	xingpeng	xingpeng	PROPN
ajst-11303	2	27	zhang	zhang	PROPN
ajst-11303	2	28	school	school	PROPN
ajst-11303	2	29	of	of	ADP
ajst-11303	2	30	intelligent	intelligent	ADJ
ajst-11303	2	31	terminal	terminal	ADJ
ajst-11303	2	32	industry	industry	NOUN
ajst-11303	2	33	,	,	PUNCT
ajst-11303	2	34	chengdu	chengdu	PROPN
ajst-11303	2	35	technological	technological	PROPN
ajst-11303	2	36	university	university	NOUN
ajst-11303	2	37	,	,	PUNCT
ajst-11303	2	38	611730	611730	NUM
ajst-11303	2	39	,	,	PUNCT
ajst-11303	2	40	china	china	PROPN
ajst-11303	2	41	abstract	abstract	NOUN
ajst-11303	2	42	:	:	PUNCT
ajst-11303	2	43	cement	cement	NOUN
ajst-11303	2	44	slurry	slurry	NOUN
ajst-11303	2	45	density	density	NOUN
ajst-11303	2	46	is	be	AUX
ajst-11303	2	47	one	one	NUM
ajst-11303	2	48	of	of	ADP
ajst-11303	2	49	the	the	DET
ajst-11303	2	50	key	key	ADJ
ajst-11303	2	51	factors	factor	NOUN
ajst-11303	2	52	affecting	affect	VERB
ajst-11303	2	53	the	the	DET
ajst-11303	2	54	consolidation	consolidation	NOUN
ajst-11303	2	55	effect	effect	NOUN
ajst-11303	2	56	of	of	ADP
ajst-11303	2	57	oil	oil	NOUN
ajst-11303	2	58	casing	casing	NOUN
ajst-11303	2	59	and	and	CCONJ
ajst-11303	2	60	wellbore	wellbore	NOUN
ajst-11303	2	61	,	,	PUNCT
ajst-11303	2	62	and	and	CCONJ
ajst-11303	2	63	its	its	PRON
ajst-11303	2	64	value	value	NOUN
ajst-11303	2	65	has	have	VERB
ajst-11303	2	66	a	a	DET
ajst-11303	2	67	direct	direct	ADJ
ajst-11303	2	68	impact	impact	NOUN
ajst-11303	2	69	on	on	ADP
ajst-11303	2	70	the	the	DET
ajst-11303	2	71	quality	quality	NOUN
ajst-11303	2	72	of	of	ADP
ajst-11303	2	73	cementing	cement	VERB
ajst-11303	2	74	and	and	CCONJ
ajst-11303	2	75	construction	construction	NOUN
ajst-11303	2	76	safety	safety	NOUN
ajst-11303	2	77	.	.	PUNCT
ajst-11303	3	1	in	in	ADP
ajst-11303	3	2	the	the	DET
ajst-11303	3	3	traditional	traditional	ADJ
ajst-11303	3	4	cementing	cement	VERB
ajst-11303	3	5	operation	operation	NOUN
ajst-11303	3	6	,	,	PUNCT
ajst-11303	3	7	the	the	DET
ajst-11303	3	8	professionals	professional	NOUN
ajst-11303	3	9	perform	perform	VERB
ajst-11303	3	10	experiments	experiment	NOUN
ajst-11303	3	11	based	base	VERB
ajst-11303	3	12	on	on	ADP
ajst-11303	3	13	information	information	NOUN
ajst-11303	3	14	from	from	ADP
ajst-11303	3	15	adjacent	adjacent	ADJ
ajst-11303	3	16	wells	well	NOUN
ajst-11303	3	17	to	to	PART
ajst-11303	3	18	obtain	obtain	VERB
ajst-11303	3	19	fuzzy	fuzzy	ADJ
ajst-11303	3	20	cement	cement	NOUN
ajst-11303	3	21	density	density	NOUN
ajst-11303	3	22	,	,	PUNCT
ajst-11303	3	23	and	and	CCONJ
ajst-11303	3	24	then	then	ADV
ajst-11303	3	25	constantly	constantly	ADV
ajst-11303	3	26	adjust	adjust	VERB
ajst-11303	3	27	the	the	DET
ajst-11303	3	28	final	final	ADJ
ajst-11303	3	29	cement	cement	NOUN
ajst-11303	3	30	density	density	NOUN
ajst-11303	3	31	in	in	ADP
ajst-11303	3	32	the	the	DET
ajst-11303	3	33	actual	actual	ADJ
ajst-11303	3	34	operation	operation	NOUN
ajst-11303	3	35	,	,	PUNCT
ajst-11303	3	36	which	which	PRON
ajst-11303	3	37	costs	cost	VERB
ajst-11303	3	38	a	a	DET
ajst-11303	3	39	lot	lot	NOUN
ajst-11303	3	40	of	of	ADP
ajst-11303	3	41	labor	labor	NOUN
ajst-11303	3	42	and	and	CCONJ
ajst-11303	3	43	time	time	NOUN
ajst-11303	3	44	,	,	PUNCT
ajst-11303	3	45	and	and	CCONJ
ajst-11303	3	46	is	be	AUX
ajst-11303	3	47	not	not	PART
ajst-11303	3	48	good	good	ADJ
ajst-11303	3	49	for	for	ADP
ajst-11303	3	50	real	real	ADJ
ajst-11303	3	51	-	-	PUNCT
ajst-11303	3	52	time	time	NOUN
ajst-11303	3	53	operation	operation	NOUN
ajst-11303	3	54	.	.	PUNCT
ajst-11303	4	1	in	in	ADP
ajst-11303	4	2	response	response	NOUN
ajst-11303	4	3	to	to	ADP
ajst-11303	4	4	the	the	DET
ajst-11303	4	5	above	above	ADJ
ajst-11303	4	6	problems	problem	NOUN
ajst-11303	4	7	,	,	PUNCT
ajst-11303	4	8	this	this	DET
ajst-11303	4	9	paper	paper	NOUN
ajst-11303	4	10	proposes	propose	VERB
ajst-11303	4	11	amindrnn(attention	amindrnn(attention	NOUN
ajst-11303	4	12	mechanism	mechanism	NOUN
ajst-11303	4	13	combined	combine	VERB
ajst-11303	4	14	with	with	ADP
ajst-11303	4	15	independently	independently	ADV
ajst-11303	4	16	recurrent	recurrent	ADJ
ajst-11303	4	17	neural	neural	ADJ
ajst-11303	4	18	network	network	NOUN
ajst-11303	4	19	)	)	PUNCT
ajst-11303	4	20	for	for	ADP
ajst-11303	4	21	cement	cement	NOUN
ajst-11303	4	22	slurry	slurry	NOUN
ajst-11303	4	23	density	density	NOUN
ajst-11303	4	24	prediction	prediction	NOUN
ajst-11303	4	25	,	,	PUNCT
ajst-11303	4	26	and	and	CCONJ
ajst-11303	4	27	optimizes	optimize	VERB
ajst-11303	4	28	indrnn	indrnn	NOUN
ajst-11303	4	29	by	by	ADP
ajst-11303	4	30	introducing	introduce	VERB
ajst-11303	4	31	smu	smu	NOUN
ajst-11303	4	32	activation	activation	NOUN
ajst-11303	4	33	function	function	NOUN
ajst-11303	4	34	.	.	PUNCT
ajst-11303	5	1	the	the	DET
ajst-11303	5	2	comparison	comparison	NOUN
ajst-11303	5	3	experiment	experiment	NOUN
ajst-11303	5	4	between	between	ADP
ajst-11303	5	5	amindrnn	amindrnn	NOUN
ajst-11303	5	6	model	model	NOUN
ajst-11303	5	7	and	and	CCONJ
ajst-11303	5	8	baseline	baseline	PROPN
ajst-11303	5	9	model	model	NOUN
ajst-11303	5	10	shows	show	NOUN
ajst-11303	5	11	that	that	PRON
ajst-11303	5	12	amindrnn	amindrnn	VERB
ajst-11303	5	13	model	model	NOUN
ajst-11303	5	14	has	have	VERB
ajst-11303	5	15	obvious	obvious	ADJ
ajst-11303	5	16	advantages	advantage	NOUN
ajst-11303	5	17	in	in	ADP
ajst-11303	5	18	various	various	ADJ
ajst-11303	5	19	performance	performance	NOUN
ajst-11303	5	20	indexes	index	NOUN
ajst-11303	5	21	,	,	PUNCT
ajst-11303	5	22	which	which	PRON
ajst-11303	5	23	can	can	AUX
ajst-11303	5	24	be	be	AUX
ajst-11303	5	25	used	use	VERB
ajst-11303	5	26	to	to	PART
ajst-11303	5	27	guide	guide	VERB
ajst-11303	5	28	the	the	DET
ajst-11303	5	29	design	design	NOUN
ajst-11303	5	30	of	of	ADP
ajst-11303	5	31	actual	actual	ADJ
ajst-11303	5	32	cement	cement	NOUN
ajst-11303	5	33	slurry	slurry	NOUN
ajst-11303	5	34	density	density	NOUN
ajst-11303	5	35	.	.	PUNCT
ajst-11303	6	1	keywords	keyword	NOUN
ajst-11303	6	2	:	:	PUNCT
ajst-11303	6	3	cementing	cement	VERB
ajst-11303	6	4	operation	operation	NOUN
ajst-11303	6	5	,	,	PUNCT
ajst-11303	6	6	cement	cement	NOUN
ajst-11303	6	7	slurry	slurry	NOUN
ajst-11303	6	8	density	density	NOUN
ajst-11303	6	9	,	,	PUNCT
ajst-11303	6	10	attention	attention	NOUN
ajst-11303	6	11	mechanism	mechanism	NOUN
ajst-11303	6	12	,	,	PUNCT
ajst-11303	6	13	independently	independently	ADV
ajst-11303	6	14	recurrent	recurrent	ADJ
ajst-11303	6	15	neural	neural	ADJ
ajst-11303	6	16	network	network	NOUN
ajst-11303	6	17	(	(	PUNCT
ajst-11303	6	18	indrnn	indrnn	NOUN
ajst-11303	6	19	)	)	PUNCT
ajst-11303	6	20	.	.	PUNCT
ajst-11303	7	1	1	1	X
ajst-11303	7	2	.	.	X
ajst-11303	7	3	introduction	introduction	NOUN
ajst-11303	7	4	cementing	cement	VERB
ajst-11303	7	5	cement	cement	NOUN
ajst-11303	7	6	slurry	slurry	NOUN
ajst-11303	7	7	density	density	NOUN
ajst-11303	7	8	is	be	AUX
ajst-11303	7	9	an	an	DET
ajst-11303	7	10	important	important	ADJ
ajst-11303	7	11	factor	factor	NOUN
ajst-11303	7	12	affecting	affect	VERB
ajst-11303	7	13	the	the	DET
ajst-11303	7	14	production	production	NOUN
ajst-11303	7	15	life	life	NOUN
ajst-11303	7	16	and	and	CCONJ
ajst-11303	7	17	production	production	NOUN
ajst-11303	7	18	speed	speed	NOUN
ajst-11303	7	19	of	of	ADP
ajst-11303	7	20	oil	oil	NOUN
ajst-11303	7	21	and	and	CCONJ
ajst-11303	7	22	gas	gas	NOUN
ajst-11303	7	23	fields	field	NOUN
ajst-11303	7	24	,	,	PUNCT
ajst-11303	7	25	and	and	CCONJ
ajst-11303	7	26	its	its	PRON
ajst-11303	7	27	value	value	NOUN
ajst-11303	7	28	is	be	AUX
ajst-11303	7	29	too	too	ADV
ajst-11303	7	30	high	high	ADJ
ajst-11303	7	31	or	or	CCONJ
ajst-11303	7	32	too	too	ADV
ajst-11303	7	33	low	low	ADJ
ajst-11303	7	34	will	will	AUX
ajst-11303	7	35	directly	directly	ADV
ajst-11303	7	36	affect	affect	VERB
ajst-11303	7	37	the	the	DET
ajst-11303	7	38	quality	quality	NOUN
ajst-11303	7	39	of	of	ADP
ajst-11303	7	40	cementing	cement	VERB
ajst-11303	7	41	and	and	CCONJ
ajst-11303	7	42	construction	construction	NOUN
ajst-11303	7	43	safety[1	safety[1	PROPN
ajst-11303	7	44	]	]	PUNCT
ajst-11303	7	45	.	.	PUNCT
ajst-11303	8	1	in	in	ADP
ajst-11303	8	2	order	order	NOUN
ajst-11303	8	3	to	to	PART
ajst-11303	8	4	ensure	ensure	VERB
ajst-11303	8	5	the	the	DET
ajst-11303	8	6	safe	safe	ADJ
ajst-11303	8	7	and	and	CCONJ
ajst-11303	8	8	effective	effective	ADJ
ajst-11303	8	9	cementing	cement	VERB
ajst-11303	8	10	operation	operation	NOUN
ajst-11303	8	11	in	in	ADP
ajst-11303	8	12	oil	oil	NOUN
ajst-11303	8	13	field	field	NOUN
ajst-11303	8	14	,	,	PUNCT
ajst-11303	8	15	the	the	DET
ajst-11303	8	16	accurate	accurate	ADJ
ajst-11303	8	17	prediction	prediction	NOUN
ajst-11303	8	18	of	of	ADP
ajst-11303	8	19	cement	cement	NOUN
ajst-11303	8	20	slurry	slurry	NOUN
ajst-11303	8	21	density	density	NOUN
ajst-11303	8	22	plays	play	VERB
ajst-11303	8	23	a	a	DET
ajst-11303	8	24	crucial	crucial	ADJ
ajst-11303	8	25	role	role	NOUN
ajst-11303	8	26	in	in	ADP
ajst-11303	8	27	improving	improve	VERB
ajst-11303	8	28	cementing	cement	VERB
ajst-11303	8	29	efficiency	efficiency	NOUN
ajst-11303	8	30	and	and	CCONJ
ajst-11303	8	31	reducing	reduce	VERB
ajst-11303	8	32	safety	safety	NOUN
ajst-11303	8	33	accidents	accident	NOUN
ajst-11303	8	34	.	.	PUNCT
ajst-11303	9	1	although	although	SCONJ
ajst-11303	9	2	a	a	DET
ajst-11303	9	3	large	large	ADJ
ajst-11303	9	4	number	number	NOUN
ajst-11303	9	5	of	of	ADP
ajst-11303	9	6	researchers	researcher	NOUN
ajst-11303	9	7	at	at	ADP
ajst-11303	9	8	home	home	ADV
ajst-11303	9	9	and	and	CCONJ
ajst-11303	9	10	abroad	abroad	ADV
ajst-11303	9	11	have	have	AUX
ajst-11303	9	12	done	do	VERB
ajst-11303	9	13	many	many	ADJ
ajst-11303	9	14	researches	research	NOUN
ajst-11303	9	15	on	on	ADP
ajst-11303	9	16	cementing	cement	VERB
ajst-11303	9	17	operation	operation	NOUN
ajst-11303	9	18	,	,	PUNCT
ajst-11303	9	19	the	the	DET
ajst-11303	9	20	technical	technical	ADJ
ajst-11303	9	21	level	level	NOUN
ajst-11303	9	22	of	of	ADP
ajst-11303	9	23	cementing	cement	VERB
ajst-11303	9	24	operation	operation	NOUN
ajst-11303	9	25	is	be	AUX
ajst-11303	9	26	still	still	ADV
ajst-11303	9	27	in	in	ADP
ajst-11303	9	28	the	the	DET
ajst-11303	9	29	primary	primary	ADJ
ajst-11303	9	30	stage	stage	NOUN
ajst-11303	9	31	.	.	PUNCT
ajst-11303	10	1	high	high	ADJ
ajst-11303	10	2	cementing	cement	VERB
ajst-11303	10	3	cost	cost	NOUN
ajst-11303	10	4	,	,	PUNCT
ajst-11303	10	5	low	low	ADJ
ajst-11303	10	6	production	production	NOUN
ajst-11303	10	7	efficiency	efficiency	NOUN
ajst-11303	10	8	and	and	CCONJ
ajst-11303	10	9	environmental	environmental	ADJ
ajst-11303	10	10	damage[2	damage[2	NOUN
ajst-11303	10	11	]	]	PUNCT
ajst-11303	10	12	are	be	AUX
ajst-11303	10	13	common	common	ADJ
ajst-11303	10	14	problems	problem	NOUN
ajst-11303	10	15	in	in	ADP
ajst-11303	10	16	oil	oil	NOUN
ajst-11303	10	17	field	field	NOUN
ajst-11303	10	18	cementing	cement	VERB
ajst-11303	10	19	operations	operation	NOUN
ajst-11303	10	20	.	.	PUNCT
ajst-11303	11	1	the	the	DET
ajst-11303	11	2	successful	successful	ADJ
ajst-11303	11	3	application	application	NOUN
ajst-11303	11	4	of	of	ADP
ajst-11303	11	5	deep	deep	ADJ
ajst-11303	11	6	learning	learning	NOUN
ajst-11303	11	7	in	in	ADP
ajst-11303	11	8	agriculture	agriculture	NOUN
ajst-11303	11	9	,	,	PUNCT
ajst-11303	11	10	machinery	machinery	NOUN
ajst-11303	11	11	,	,	PUNCT
ajst-11303	11	12	biology	biology	NOUN
ajst-11303	11	13	and	and	CCONJ
ajst-11303	11	14	other	other	ADJ
ajst-11303	11	15	fields	field	NOUN
ajst-11303	11	16	provides	provide	VERB
ajst-11303	11	17	the	the	DET
ajst-11303	11	18	possibility	possibility	NOUN
ajst-11303	11	19	for	for	ADP
ajst-11303	11	20	its	its	PRON
ajst-11303	11	21	application	application	NOUN
ajst-11303	11	22	in	in	ADP
ajst-11303	11	23	the	the	DET
ajst-11303	11	24	field	field	NOUN
ajst-11303	11	25	of	of	ADP
ajst-11303	11	26	cementing	cement	VERB
ajst-11303	11	27	operations	operation	NOUN
ajst-11303	11	28	.	.	PUNCT
ajst-11303	12	1	for	for	ADP
ajst-11303	12	2	example	example	NOUN
ajst-11303	12	3	,	,	PUNCT
ajst-11303	12	4	shang	shang	PROPN
ajst-11303	12	5	fuhua	fuhua	PROPN
ajst-11303	12	6	et	et	PROPN
ajst-11303	12	7	al[3	al[3	PROPN
ajst-11303	12	8	]	]	PUNCT
ajst-11303	12	9	.	.	PUNCT
ajst-11303	13	1	applied	apply	VERB
ajst-11303	13	2	feedforward	feedforward	ADJ
ajst-11303	13	3	neural	neural	ADJ
ajst-11303	13	4	network	network	NOUN
ajst-11303	13	5	to	to	PART
ajst-11303	13	6	cement	cement	NOUN
ajst-11303	13	7	bonding	bonding	NOUN
ajst-11303	13	8	quality	quality	NOUN
ajst-11303	13	9	identification	identification	NOUN
ajst-11303	13	10	,	,	PUNCT
ajst-11303	13	11	providing	provide	VERB
ajst-11303	13	12	valuable	valuable	ADJ
ajst-11303	13	13	technical	technical	ADJ
ajst-11303	13	14	support	support	NOUN
ajst-11303	13	15	for	for	ADP
ajst-11303	13	16	the	the	DET
ajst-11303	13	17	engineering	engineering	NOUN
ajst-11303	13	18	application	application	NOUN
ajst-11303	13	19	of	of	ADP
ajst-11303	13	20	cement	cement	NOUN
ajst-11303	13	21	bonding	bonding	NOUN
ajst-11303	13	22	.	.	PUNCT
ajst-11303	14	1	therefore	therefore	ADV
ajst-11303	14	2	,	,	PUNCT
ajst-11303	14	3	it	it	PRON
ajst-11303	14	4	is	be	AUX
ajst-11303	14	5	of	of	ADP
ajst-11303	14	6	great	great	ADJ
ajst-11303	14	7	significance	significance	NOUN
ajst-11303	14	8	to	to	PART
ajst-11303	14	9	establish	establish	VERB
ajst-11303	14	10	a	a	DET
ajst-11303	14	11	prediction	prediction	NOUN
ajst-11303	14	12	model	model	NOUN
ajst-11303	14	13	of	of	ADP
ajst-11303	14	14	cement	cement	NOUN
ajst-11303	14	15	density	density	NOUN
ajst-11303	14	16	based	base	VERB
ajst-11303	14	17	on	on	ADP
ajst-11303	14	18	deep	deep	ADJ
ajst-11303	14	19	learning	learning	NOUN
ajst-11303	14	20	for	for	ADP
ajst-11303	14	21	cement	cement	NOUN
ajst-11303	14	22	density	density	NOUN
ajst-11303	14	23	design	design	NOUN
ajst-11303	14	24	in	in	ADP
ajst-11303	14	25	actual	actual	ADJ
ajst-11303	14	26	cementing	cement	VERB
ajst-11303	14	27	operations	operation	NOUN
ajst-11303	14	28	.	.	PUNCT
ajst-11303	15	1	finding	find	VERB
ajst-11303	15	2	the	the	DET
ajst-11303	15	3	quantitative	quantitative	ADJ
ajst-11303	15	4	relationship	relationship	NOUN
ajst-11303	15	5	of	of	ADP
ajst-11303	15	6	complex	complex	ADJ
ajst-11303	15	7	causality	causality	NOUN
ajst-11303	15	8	in	in	ADP
ajst-11303	15	9	cement	cement	NOUN
ajst-11303	15	10	slurry	slurry	NOUN
ajst-11303	15	11	density	density	NOUN
ajst-11303	15	12	,	,	PUNCT
ajst-11303	15	13	realizing	realize	VERB
ajst-11303	15	14	scientific	scientific	ADJ
ajst-11303	15	15	cement	cement	NOUN
ajst-11303	15	16	slurry	slurry	NOUN
ajst-11303	15	17	density	density	NOUN
ajst-11303	15	18	prediction	prediction	NOUN
ajst-11303	15	19	,	,	PUNCT
ajst-11303	15	20	saying	say	VERB
ajst-11303	15	21	goodbye	goodbye	NOUN
ajst-11303	15	22	to	to	ADP
ajst-11303	15	23	the	the	DET
ajst-11303	15	24	experience	experience	NOUN
ajst-11303	15	25	-	-	PUNCT
ajst-11303	15	26	based	base	VERB
ajst-11303	15	27	density	density	NOUN
ajst-11303	15	28	design	design	NOUN
ajst-11303	15	29	method	method	NOUN
ajst-11303	15	30	,	,	PUNCT
ajst-11303	15	31	can	can	AUX
ajst-11303	15	32	not	not	PART
ajst-11303	15	33	only	only	ADV
ajst-11303	15	34	save	save	VERB
ajst-11303	15	35	labor	labor	NOUN
ajst-11303	15	36	and	and	CCONJ
ajst-11303	15	37	time	time	NOUN
ajst-11303	15	38	costs	cost	NOUN
ajst-11303	15	39	,	,	PUNCT
ajst-11303	15	40	improve	improve	VERB
ajst-11303	15	41	cementing	cement	VERB
ajst-11303	15	42	quality	quality	NOUN
ajst-11303	15	43	,	,	PUNCT
ajst-11303	15	44	but	but	CCONJ
ajst-11303	15	45	also	also	ADV
ajst-11303	15	46	keep	keep	VERB
ajst-11303	15	47	up	up	ADP
ajst-11303	15	48	with	with	ADP
ajst-11303	15	49	the	the	DET
ajst-11303	15	50	pace	pace	NOUN
ajst-11303	15	51	of	of	ADP
ajst-11303	15	52	modern	modern	ADJ
ajst-11303	15	53	science	science	NOUN
ajst-11303	15	54	and	and	CCONJ
ajst-11303	15	55	technology	technology	NOUN
ajst-11303	15	56	.	.	PUNCT
ajst-11303	16	1	based	base	VERB
ajst-11303	16	2	on	on	ADP
ajst-11303	16	3	the	the	DET
ajst-11303	16	4	above	above	ADJ
ajst-11303	16	5	background	background	NOUN
ajst-11303	16	6	,	,	PUNCT
ajst-11303	16	7	this	this	DET
ajst-11303	16	8	paper	paper	NOUN
ajst-11303	16	9	proposes	propose	VERB
ajst-11303	16	10	a	a	DET
ajst-11303	16	11	composite	composite	ADJ
ajst-11303	16	12	model	model	NOUN
ajst-11303	16	13	amindrnn	amindrnn	NOUN
ajst-11303	16	14	,	,	PUNCT
ajst-11303	16	15	which	which	PRON
ajst-11303	16	16	is	be	AUX
ajst-11303	16	17	composed	compose	VERB
ajst-11303	16	18	of	of	ADP
ajst-11303	16	19	optimized	optimize	VERB
ajst-11303	16	20	independently	independently	ADV
ajst-11303	16	21	recurrent	recurrent	ADJ
ajst-11303	16	22	neural	neural	ADJ
ajst-11303	16	23	network	network	NOUN
ajst-11303	16	24	(	(	PUNCT
ajst-11303	16	25	indrnn	indrnn	NOUN
ajst-11303	16	26	)	)	PUNCT
ajst-11303	16	27	and	and	CCONJ
ajst-11303	16	28	attention	attention	NOUN
ajst-11303	16	29	mechanism	mechanism	NOUN
ajst-11303	16	30	(	(	PUNCT
ajst-11303	16	31	am	be	AUX
ajst-11303	16	32	)	)	PUNCT
ajst-11303	16	33	to	to	PART
ajst-11303	16	34	achieve	achieve	VERB
ajst-11303	16	35	cement	cement	NOUN
ajst-11303	16	36	slurry	slurry	NOUN
ajst-11303	16	37	density	density	NOUN
ajst-11303	16	38	prediction	prediction	NOUN
ajst-11303	16	39	.	.	PUNCT
ajst-11303	17	1	the	the	DET
ajst-11303	17	2	innovation	innovation	NOUN
ajst-11303	17	3	of	of	ADP
ajst-11303	17	4	amindrnn	amindrnn	NOUN
ajst-11303	17	5	model	model	NOUN
ajst-11303	17	6	is	be	AUX
ajst-11303	17	7	reflected	reflect	VERB
ajst-11303	17	8	in	in	ADP
ajst-11303	17	9	the	the	DET
ajst-11303	17	10	introduction	introduction	NOUN
ajst-11303	17	11	of	of	ADP
ajst-11303	17	12	smu	smu	NOUN
ajst-11303	17	13	activation	activation	NOUN
ajst-11303	17	14	function	function	VERB
ajst-11303	17	15	to	to	PART
ajst-11303	17	16	optimize	optimize	VERB
ajst-11303	17	17	indrnn	indrnn	NOUN
ajst-11303	17	18	,	,	PUNCT
ajst-11303	17	19	and	and	CCONJ
ajst-11303	17	20	the	the	DET
ajst-11303	17	21	extraction	extraction	NOUN
ajst-11303	17	22	of	of	ADP
ajst-11303	17	23	cementing	cement	VERB
ajst-11303	17	24	data	datum	NOUN
ajst-11303	17	25	features	feature	NOUN
ajst-11303	17	26	by	by	ADP
ajst-11303	17	27	adding	add	VERB
ajst-11303	17	28	am	be	AUX
ajst-11303	17	29	.	.	PUNCT
ajst-11303	18	1	the	the	DET
ajst-11303	18	2	designed	design	VERB
ajst-11303	18	3	and	and	CCONJ
ajst-11303	18	4	implemented	implement	VERB
ajst-11303	18	5	amindrnn	amindrnn	NOUN
ajst-11303	18	6	model	model	NOUN
ajst-11303	18	7	can	can	AUX
ajst-11303	18	8	extract	extract	VERB
ajst-11303	18	9	the	the	DET
ajst-11303	18	10	important	important	ADJ
ajst-11303	18	11	features	feature	NOUN
ajst-11303	18	12	in	in	ADP
ajst-11303	18	13	the	the	DET
ajst-11303	18	14	input	input	NOUN
ajst-11303	18	15	data	datum	NOUN
ajst-11303	18	16	to	to	ADP
ajst-11303	18	17	the	the	DET
ajst-11303	18	18	greatest	great	ADJ
ajst-11303	18	19	extent	extent	NOUN
ajst-11303	18	20	.	.	PUNCT
ajst-11303	19	1	in	in	ADP
ajst-11303	19	2	this	this	DET
ajst-11303	19	3	paper	paper	NOUN
ajst-11303	19	4	,	,	PUNCT
ajst-11303	19	5	the	the	DET
ajst-11303	19	6	experiment	experiment	NOUN
ajst-11303	19	7	is	be	AUX
ajst-11303	19	8	carried	carry	VERB
ajst-11303	19	9	out	out	ADP
ajst-11303	19	10	on	on	ADP
ajst-11303	19	11	the	the	DET
ajst-11303	19	12	historical	historical	ADJ
ajst-11303	19	13	cementing	cement	VERB
ajst-11303	19	14	data	datum	NOUN
ajst-11303	19	15	set	set	VERB
ajst-11303	19	16	of	of	ADP
ajst-11303	19	17	a	a	DET
ajst-11303	19	18	certain	certain	ADJ
ajst-11303	19	19	offshore	offshore	ADJ
ajst-11303	19	20	oil	oil	NOUN
ajst-11303	19	21	company	company	NOUN
ajst-11303	19	22	.	.	PUNCT
ajst-11303	20	1	the	the	DET
ajst-11303	20	2	experimental	experimental	ADJ
ajst-11303	20	3	results	result	NOUN
ajst-11303	20	4	show	show	VERB
ajst-11303	20	5	that	that	SCONJ
ajst-11303	20	6	the	the	DET
ajst-11303	20	7	error	error	NOUN
ajst-11303	20	8	between	between	ADP
ajst-11303	20	9	the	the	DET
ajst-11303	20	10	predicted	predict	VERB
ajst-11303	20	11	value	value	NOUN
ajst-11303	20	12	and	and	CCONJ
ajst-11303	20	13	the	the	DET
ajst-11303	20	14	actual	actual	ADJ
ajst-11303	20	15	value	value	NOUN
ajst-11303	20	16	is	be	AUX
ajst-11303	20	17	small	small	ADJ
ajst-11303	20	18	.	.	PUNCT
ajst-11303	21	1	the	the	DET
ajst-11303	21	2	final	final	ADJ
ajst-11303	21	3	rmse	rmse	NOUN
ajst-11303	21	4	value	value	NOUN
ajst-11303	21	5	is	be	AUX
ajst-11303	21	6	0.138	0.138	NUM
ajst-11303	21	7	and	and	CCONJ
ajst-11303	21	8	the	the	DET
ajst-11303	21	9	mae	mae	PROPN
ajst-11303	21	10	value	value	NOUN
ajst-11303	21	11	is	be	AUX
ajst-11303	21	12	0.019	0.019	NUM
ajst-11303	21	13	,	,	PUNCT
ajst-11303	21	14	which	which	PRON
ajst-11303	21	15	is	be	AUX
ajst-11303	21	16	better	well	ADJ
ajst-11303	21	17	than	than	ADP
ajst-11303	21	18	the	the	DET
ajst-11303	21	19	baseline	baseline	ADJ
ajst-11303	21	20	neural	neural	ADJ
ajst-11303	21	21	network	network	NOUN
ajst-11303	21	22	model	model	NOUN
ajst-11303	21	23	.	.	PUNCT
ajst-11303	22	1	the	the	DET
ajst-11303	22	2	method	method	NOUN
ajst-11303	22	3	proposed	propose	VERB
ajst-11303	22	4	in	in	ADP
ajst-11303	22	5	this	this	DET
ajst-11303	22	6	paper	paper	NOUN
ajst-11303	22	7	can	can	AUX
ajst-11303	22	8	be	be	AUX
ajst-11303	22	9	applied	apply	VERB
ajst-11303	22	10	to	to	ADP
ajst-11303	22	11	the	the	DET
ajst-11303	22	12	prediction	prediction	NOUN
ajst-11303	22	13	of	of	ADP
ajst-11303	22	14	cement	cement	NOUN
ajst-11303	22	15	slurry	slurry	NOUN
ajst-11303	22	16	density	density	NOUN
ajst-11303	22	17	,	,	PUNCT
ajst-11303	22	18	which	which	PRON
ajst-11303	22	19	is	be	AUX
ajst-11303	22	20	of	of	ADP
ajst-11303	22	21	great	great	ADJ
ajst-11303	22	22	significance	significance	NOUN
ajst-11303	22	23	for	for	ADP
ajst-11303	22	24	improving	improve	VERB
ajst-11303	22	25	cementing	cement	VERB
ajst-11303	22	26	efficiency	efficiency	NOUN
ajst-11303	22	27	and	and	CCONJ
ajst-11303	22	28	reducing	reduce	VERB
ajst-11303	22	29	cementing	cement	VERB
ajst-11303	22	30	cost	cost	NOUN
ajst-11303	22	31	.	.	PUNCT
ajst-11303	23	1	2	2	X
ajst-11303	23	2	.	.	X
ajst-11303	23	3	related	relate	VERB
ajst-11303	23	4	work	work	NOUN
ajst-11303	23	5	through	through	ADP
ajst-11303	23	6	the	the	DET
ajst-11303	23	7	review	review	NOUN
ajst-11303	23	8	of	of	ADP
ajst-11303	23	9	the	the	DET
ajst-11303	23	10	related	relate	VERB
ajst-11303	23	11	research	research	NOUN
ajst-11303	23	12	results	result	NOUN
ajst-11303	23	13	of	of	ADP
ajst-11303	23	14	oil	oil	NOUN
ajst-11303	23	15	cementing	cement	VERB
ajst-11303	23	16	operation	operation	NOUN
ajst-11303	23	17	,	,	PUNCT
ajst-11303	23	18	the	the	DET
ajst-11303	23	19	related	related	ADJ
ajst-11303	23	20	research	research	NOUN
ajst-11303	23	21	methods	method	NOUN
ajst-11303	23	22	in	in	ADP
ajst-11303	23	23	this	this	DET
ajst-11303	23	24	field	field	NOUN
ajst-11303	23	25	can	can	AUX
ajst-11303	23	26	be	be	AUX
ajst-11303	23	27	divided	divide	VERB
ajst-11303	23	28	into	into	ADP
ajst-11303	23	29	three	three	NUM
ajst-11303	23	30	categories	category	NOUN
ajst-11303	23	31	.	.	PUNCT
ajst-11303	24	1	1	1	NUM
ajst-11303	24	2	)	)	PUNCT
ajst-11303	24	3	methods	method	NOUN
ajst-11303	24	4	based	base	VERB
ajst-11303	24	5	on	on	ADP
ajst-11303	24	6	petroleum	petroleum	NOUN
ajst-11303	24	7	engineering	engineering	NOUN
ajst-11303	24	8	expertise	expertise	NOUN
ajst-11303	24	9	.	.	PUNCT
ajst-11303	25	1	he	he	PRON
ajst-11303	25	2	yingwei	yingwei	VERB
ajst-11303	25	3	,	,	PUNCT
ajst-11303	25	4	yi	yi	PROPN
ajst-11303	25	5	hao	hao	PROPN
ajst-11303	25	6	et	et	PROPN
ajst-11303	25	7	al[4	al[4	PROPN
ajst-11303	25	8	]	]	PUNCT
ajst-11303	25	9	.	.	PUNCT
ajst-11303	26	1	developed	develop	VERB
ajst-11303	26	2	a	a	DET
ajst-11303	26	3	set	set	NOUN
ajst-11303	26	4	of	of	ADP
ajst-11303	26	5	water	water	NOUN
ajst-11303	26	6	-	-	PUNCT
ajst-11303	26	7	soluble	soluble	ADJ
ajst-11303	26	8	resin	resin	NOUN
ajst-11303	26	9	cement	cement	NOUN
ajst-11303	26	10	-	-	PUNCT
ajst-11303	26	11	working	work	VERB
ajst-11303	26	12	fluid	fluid	NOUN
ajst-11303	26	13	system	system	NOUN
ajst-11303	26	14	for	for	ADP
ajst-11303	26	15	medium	medium	ADJ
ajst-11303	26	16	-	-	PUNCT
ajst-11303	26	17	high	high	ADJ
ajst-11303	26	18	pressure	pressure	NOUN
ajst-11303	26	19	,	,	PUNCT
ajst-11303	26	20	late	late	ADJ
ajst-11303	26	21	fracturing	fracturing	NOUN
ajst-11303	26	22	,	,	PUNCT
ajst-11303	26	23	and	and	CCONJ
ajst-11303	26	24	periodic	periodic	ADJ
ajst-11303	26	25	pressure	pressure	NOUN
ajst-11303	26	26	change	change	NOUN
ajst-11303	26	27	of	of	ADP
ajst-11303	26	28	gas	gas	NOUN
ajst-11303	26	29	storage	storage	NOUN
ajst-11303	26	30	.	.	PUNCT
ajst-11303	27	1	aiming	aim	VERB
ajst-11303	27	2	at	at	ADP
ajst-11303	27	3	the	the	DET
ajst-11303	27	4	problem	problem	NOUN
ajst-11303	27	5	of	of	ADP
ajst-11303	27	6	annulus	annulus	NOUN
ajst-11303	27	7	pressure	pressure	NOUN
ajst-11303	27	8	in	in	ADP
ajst-11303	27	9	deep	deep	ADJ
ajst-11303	27	10	shale	shale	NOUN
ajst-11303	27	11	horizontal	horizontal	ADJ
ajst-11303	27	12	wells	wells	PROPN
ajst-11303	27	13	,	,	PUNCT
ajst-11303	27	14	xi	xi	PROPN
ajst-11303	27	15	yan	yan	PROPN
ajst-11303	27	16	et	et	PROPN
ajst-11303	27	17	al[5].analyzed	al[5].analyze	VERB
ajst-11303	27	18	the	the	DET
ajst-11303	27	19	generation	generation	NOUN
ajst-11303	27	20	and	and	CCONJ
ajst-11303	27	21	development	development	NOUN
ajst-11303	27	22	of	of	ADP
ajst-11303	27	23	micro	micro	NOUN
ajst-11303	27	24	-	-	NOUN
ajst-11303	27	25	annulus	annulus	NOUN
ajst-11303	27	26	under	under	ADP
ajst-11303	27	27	the	the	DET
ajst-11303	27	28	condition	condition	NOUN
ajst-11303	27	29	of	of	ADP
ajst-11303	27	30	prestressed	prestressed	ADJ
ajst-11303	27	31	cementing	cementing	NOUN
ajst-11303	27	32	by	by	ADP
ajst-11303	27	33	means	mean	NOUN
ajst-11303	27	34	of	of	ADP
ajst-11303	27	35	mechanical	mechanical	ADJ
ajst-11303	27	36	experiment	experiment	NOUN
ajst-11303	27	37	and	and	CCONJ
ajst-11303	27	38	numerical	numerical	PROPN
ajst-11303	27	39	simulation	simulation	NOUN
ajst-11303	27	40	,	,	PUNCT
ajst-11303	27	41	and	and	CCONJ
ajst-11303	27	42	clarified	clarify	VERB
ajst-11303	27	43	the	the	DET
ajst-11303	27	44	number	number	NOUN
ajst-11303	27	45	of	of	ADP
ajst-11303	27	46	fracturing	fracturing	NOUN
ajst-11303	27	47	sections	section	NOUN
ajst-11303	27	48	of	of	ADP
ajst-11303	27	49	cement	cement	NOUN
ajst-11303	27	50	sheath	sheath	NOUN
ajst-11303	27	51	under	under	ADP
ajst-11303	27	52	different	different	ADJ
ajst-11303	27	53	pre	pre	ADJ
ajst-11303	27	54	-	-	ADJ
ajst-11303	27	55	stress	stress	ADJ
ajst-11303	27	56	conditions	condition	NOUN
ajst-11303	27	57	.	.	PUNCT
ajst-11303	28	1	luo	luo	PROPN
ajst-11303	28	2	jing	jing	PROPN
ajst-11303	28	3	et	et	PROPN
ajst-11303	28	4	al[6].developed	al[6].develope	VERB
ajst-11303	28	5	a	a	DET
ajst-11303	28	6	set	set	NOUN
ajst-11303	28	7	of	of	ADP
ajst-11303	28	8	systematic	systematic	ADJ
ajst-11303	28	9	and	and	CCONJ
ajst-11303	28	10	mature	mature	VERB
ajst-11303	28	11	large	large	ADJ
ajst-11303	28	12	displacement	displacement	NOUN
ajst-11303	28	13	cementing	cement	VERB
ajst-11303	28	14	technology	technology	NOUN
ajst-11303	28	15	for	for	ADP
ajst-11303	28	16	the	the	DET
ajst-11303	28	17	shallow	shallow	ADJ
ajst-11303	28	18	geological	geological	ADJ
ajst-11303	28	19	conditions	condition	NOUN
ajst-11303	28	20	of	of	ADP
ajst-11303	28	21	bohai	bohai	NOUN
ajst-11303	28	22	bay	bay	NOUN
ajst-11303	28	23	,	,	PUNCT
ajst-11303	28	24	which	which	PRON
ajst-11303	28	25	has	have	AUX
ajst-11303	28	26	achieved	achieve	VERB
ajst-11303	28	27	remarkable	remarkable	ADJ
ajst-11303	28	28	results	result	NOUN
ajst-11303	28	29	in	in	ADP
ajst-11303	28	30	field	field	NOUN
ajst-11303	28	31	practice	practice	NOUN
ajst-11303	28	32	and	and	CCONJ
ajst-11303	28	33	guaranteed	guarantee	VERB
ajst-11303	28	34	the	the	DET
ajst-11303	28	35	cementing	cement	VERB
ajst-11303	28	36	quality	quality	NOUN
ajst-11303	28	37	of	of	ADP
ajst-11303	28	38	large	large	ADJ
ajst-11303	28	39	displacement	displacement	ADJ
ajst-11303	28	40	wells	well	NOUN
ajst-11303	28	41	in	in	ADP
ajst-11303	28	42	this	this	DET
ajst-11303	28	43	block	block	NOUN
ajst-11303	28	44	.	.	PUNCT
ajst-11303	29	1	2	2	NUM
ajst-11303	29	2	)	)	PUNCT
ajst-11303	29	3	methods	method	NOUN
ajst-11303	29	4	based	base	VERB
ajst-11303	29	5	on	on	ADP
ajst-11303	29	6	traditional	traditional	ADJ
ajst-11303	29	7	machine	machine	NOUN
ajst-11303	29	8	learning	learning	NOUN
ajst-11303	29	9	and	and	CCONJ
ajst-11303	29	10	statistics	statistic	NOUN
ajst-11303	29	11	.	.	PUNCT
ajst-11303	30	1	guan	guan	PROPN
ajst-11303	30	2	rongliang[7	rongliang[7	PROPN
ajst-11303	30	3	]	]	PUNCT
ajst-11303	30	4	proposed	propose	VERB
ajst-11303	30	5	to	to	PART
ajst-11303	30	6	use	use	VERB
ajst-11303	30	7	the	the	DET
ajst-11303	30	8	least	least	ADJ
ajst-11303	30	9	squares	square	NOUN
ajst-11303	30	10	support	support	NOUN
ajst-11303	30	11	vector	vector	NOUN
ajst-11303	30	12	machine	machine	NOUN
ajst-11303	30	13	to	to	PART
ajst-11303	30	14	predict	predict	VERB
ajst-11303	30	15	the	the	DET
ajst-11303	30	16	cementing	cement	VERB
ajst-11303	30	17	quality	quality	NOUN
ajst-11303	30	18	.	.	PUNCT
ajst-11303	31	1	the	the	DET
ajst-11303	31	2	wavelet	wavelet	NOUN
ajst-11303	31	3	packet	packet	NOUN
ajst-11303	31	4	decomposition	decomposition	NOUN
ajst-11303	31	5	method	method	NOUN
ajst-11303	31	6	is	be	AUX
ajst-11303	31	7	used	use	VERB
ajst-11303	31	8	to	to	PART
ajst-11303	31	9	extract	extract	VERB
ajst-11303	31	10	the	the	DET
ajst-11303	31	11	formation	formation	NOUN
ajst-11303	31	12	echo	echo	NOUN
ajst-11303	31	13	information	information	NOUN
ajst-11303	31	14	signal	signal	NOUN
ajst-11303	31	15	,	,	PUNCT
ajst-11303	31	16	which	which	PRON
ajst-11303	31	17	is	be	AUX
ajst-11303	31	18	used	use	VERB
ajst-11303	31	19	as	as	ADP
ajst-11303	31	20	the	the	DET
ajst-11303	31	21	input	input	NOUN
ajst-11303	31	22	of	of	ADP
ajst-11303	31	23	the	the	DET
ajst-11303	31	24	model	model	NOUN
ajst-11303	31	25	,	,	PUNCT
ajst-11303	31	26	and	and	CCONJ
ajst-11303	31	27	the	the	DET
ajst-11303	31	28	cementing	cement	VERB
ajst-11303	31	29	quality	quality	NOUN
ajst-11303	31	30	of	of	ADP
ajst-11303	31	31	the	the	DET
ajst-11303	31	32	sample	sample	NOUN
ajst-11303	31	33	is	be	AUX
ajst-11303	31	34	used	use	VERB
ajst-11303	31	35	as	as	ADP
ajst-11303	31	36	the	the	DET
ajst-11303	31	37	output	output	NOUN
ajst-11303	31	38	of	of	ADP
ajst-11303	31	39	the	the	DET
ajst-11303	31	40	sample	sample	NOUN
ajst-11303	31	41	.	.	PUNCT
ajst-11303	32	1	kong	kong	PROPN
ajst-11303	32	2	chao[8	chao[8	PROPN
ajst-11303	32	3	]	]	X
ajst-11303	32	4	uses	use	VERB
ajst-11303	32	5	grey	grey	ADJ
ajst-11303	32	6	correlation	correlation	NOUN
ajst-11303	32	7	analysis	analysis	NOUN
ajst-11303	32	8	to	to	PART
ajst-11303	32	9	sort	sort	VERB
ajst-11303	32	10	the	the	DET
ajst-11303	32	11	correlation	correlation	NOUN
ajst-11303	32	12	degree	degree	NOUN
ajst-11303	32	13	of	of	ADP
ajst-11303	32	14	factors	factor	NOUN
ajst-11303	32	15	affecting	affect	VERB
ajst-11303	32	16	cementing	cement	VERB
ajst-11303	32	17	quality	quality	NOUN
ajst-11303	32	18	,	,	PUNCT
ajst-11303	32	19	and	and	CCONJ
ajst-11303	32	20	determines	determine	VERB
ajst-11303	32	21	the	the	DET
ajst-11303	32	22	main	main	ADJ
ajst-11303	32	23	157	157	NUM
ajst-11303	32	24	influencing	influence	VERB
ajst-11303	32	25	factors	factor	NOUN
ajst-11303	32	26	.	.	PUNCT
ajst-11303	33	1	the	the	DET
ajst-11303	33	2	final	final	ADJ
ajst-11303	33	3	prediction	prediction	NOUN
ajst-11303	33	4	model	model	NOUN
ajst-11303	33	5	is	be	AUX
ajst-11303	33	6	established	establish	VERB
ajst-11303	33	7	by	by	ADP
ajst-11303	33	8	combining	combine	VERB
ajst-11303	33	9	grey	grey	ADJ
ajst-11303	33	10	method	method	NOUN
ajst-11303	33	11	and	and	CCONJ
ajst-11303	33	12	fuzzy	fuzzy	ADJ
ajst-11303	33	13	neural	neural	ADJ
ajst-11303	33	14	network	network	NOUN
ajst-11303	33	15	.	.	PUNCT
ajst-11303	34	1	the	the	DET
ajst-11303	34	2	prediction	prediction	NOUN
ajst-11303	34	3	accuracy	accuracy	NOUN
ajst-11303	34	4	is	be	AUX
ajst-11303	34	5	high	high	ADJ
ajst-11303	34	6	,	,	PUNCT
ajst-11303	34	7	and	and	CCONJ
ajst-11303	34	8	it	it	PRON
ajst-11303	34	9	can	can	AUX
ajst-11303	34	10	be	be	AUX
ajst-11303	34	11	used	use	VERB
ajst-11303	34	12	to	to	PART
ajst-11303	34	13	guide	guide	VERB
ajst-11303	34	14	the	the	DET
ajst-11303	34	15	field	field	NOUN
ajst-11303	34	16	cementing	cement	VERB
ajst-11303	34	17	construction	construction	NOUN
ajst-11303	34	18	.	.	PUNCT
ajst-11303	35	1	tang	tang	PROPN
ajst-11303	35	2	mingyue[9]established	mingyue[9]establishe	VERB
ajst-11303	35	3	a	a	DET
ajst-11303	35	4	model	model	NOUN
ajst-11303	35	5	combining	combine	VERB
ajst-11303	35	6	extreme	extreme	ADJ
ajst-11303	35	7	learning	learning	NOUN
ajst-11303	35	8	machine	machine	NOUN
ajst-11303	35	9	and	and	CCONJ
ajst-11303	35	10	k	k	NOUN
ajst-11303	35	11	-	-	PUNCT
ajst-11303	35	12	nearest	near	ADJ
ajst-11303	35	13	neighbor	neighbor	NOUN
ajst-11303	35	14	to	to	PART
ajst-11303	35	15	predict	predict	VERB
ajst-11303	35	16	the	the	DET
ajst-11303	35	17	drilling	drilling	NOUN
ajst-11303	35	18	fluid	fluid	ADJ
ajst-11303	35	19	density	density	NOUN
ajst-11303	35	20	of	of	ADP
ajst-11303	35	21	high	high	ADJ
ajst-11303	35	22	temperature	temperature	NOUN
ajst-11303	35	23	and	and	CCONJ
ajst-11303	35	24	high	high	ADJ
ajst-11303	35	25	pressure	pressure	NOUN
ajst-11303	35	26	wells	well	NOUN
ajst-11303	35	27	.	.	PUNCT
ajst-11303	36	1	the	the	DET
ajst-11303	36	2	results	result	NOUN
ajst-11303	36	3	show	show	VERB
ajst-11303	36	4	that	that	SCONJ
ajst-11303	36	5	the	the	DET
ajst-11303	36	6	model	model	NOUN
ajst-11303	36	7	has	have	VERB
ajst-11303	36	8	good	good	ADJ
ajst-11303	36	9	generalization	generalization	NOUN
ajst-11303	36	10	and	and	CCONJ
ajst-11303	36	11	fast	fast	ADJ
ajst-11303	36	12	learning	learning	NOUN
ajst-11303	36	13	speed	speed	NOUN
ajst-11303	36	14	.	.	PUNCT
ajst-11303	37	1	3	3	X
ajst-11303	37	2	)	)	PUNCT
ajst-11303	37	3	method	method	NOUN
ajst-11303	37	4	based	base	VERB
ajst-11303	37	5	on	on	ADP
ajst-11303	37	6	deep	deep	ADJ
ajst-11303	37	7	learning	learning	NOUN
ajst-11303	37	8	.	.	PUNCT
ajst-11303	38	1	du	du	PROPN
ajst-11303	38	2	dongnan	dongnan	PROPN
ajst-11303	38	3	et	et	PROPN
ajst-11303	38	4	al[10].established	al[10].establishe	VERB
ajst-11303	38	5	a	a	DET
ajst-11303	38	6	cementing	cement	VERB
ajst-11303	38	7	quality	quality	NOUN
ajst-11303	38	8	prediction	prediction	NOUN
ajst-11303	38	9	model	model	NOUN
ajst-11303	38	10	based	base	VERB
ajst-11303	38	11	on	on	ADP
ajst-11303	38	12	lm	lm	INTJ
ajst-11303	38	13	optimized	optimize	VERB
ajst-11303	38	14	neural	neural	ADJ
ajst-11303	38	15	network	network	NOUN
ajst-11303	38	16	method	method	NOUN
ajst-11303	38	17	,	,	PUNCT
ajst-11303	38	18	which	which	PRON
ajst-11303	38	19	provided	provide	VERB
ajst-11303	38	20	technical	technical	ADJ
ajst-11303	38	21	guidance	guidance	NOUN
ajst-11303	38	22	for	for	ADP
ajst-11303	38	23	on	on	ADP
ajst-11303	38	24	-	-	PUNCT
ajst-11303	38	25	site	site	NOUN
ajst-11303	38	26	cementing	cement	VERB
ajst-11303	38	27	quality	quality	NOUN
ajst-11303	38	28	prediction	prediction	NOUN
ajst-11303	38	29	and	and	CCONJ
ajst-11303	38	30	cementing	cement	VERB
ajst-11303	38	31	construction	construction	NOUN
ajst-11303	38	32	scheme	scheme	NOUN
ajst-11303	38	33	optimization	optimization	NOUN
ajst-11303	38	34	.	.	PUNCT
ajst-11303	39	1	based	base	VERB
ajst-11303	39	2	on	on	ADP
ajst-11303	39	3	the	the	DET
ajst-11303	39	4	analysis	analysis	NOUN
ajst-11303	39	5	of	of	ADP
ajst-11303	39	6	the	the	DET
ajst-11303	39	7	importance	importance	NOUN
ajst-11303	39	8	of	of	ADP
ajst-11303	39	9	cementing	cement	VERB
ajst-11303	39	10	engineering	engineering	NOUN
ajst-11303	39	11	and	and	CCONJ
ajst-11303	39	12	cementing	cement	VERB
ajst-11303	39	13	quality	quality	NOUN
ajst-11303	39	14	,	,	PUNCT
ajst-11303	39	15	lyu	lyu	NOUN
ajst-11303	39	16	heyu[11	heyu[11	X
ajst-11303	39	17	]	]	PUNCT
ajst-11303	39	18	established	establish	VERB
ajst-11303	39	19	a	a	DET
ajst-11303	39	20	bp	bp	PROPN
ajst-11303	39	21	neural	neural	ADJ
ajst-11303	39	22	network	network	NOUN
ajst-11303	39	23	prediction	prediction	NOUN
ajst-11303	39	24	model	model	NOUN
ajst-11303	39	25	to	to	PART
ajst-11303	39	26	predict	predict	VERB
ajst-11303	39	27	cementing	cement	VERB
ajst-11303	39	28	quality	quality	NOUN
ajst-11303	39	29	,	,	PUNCT
ajst-11303	39	30	which	which	PRON
ajst-11303	39	31	provides	provide	VERB
ajst-11303	39	32	a	a	DET
ajst-11303	39	33	new	new	ADJ
ajst-11303	39	34	way	way	NOUN
ajst-11303	39	35	for	for	ADP
ajst-11303	39	36	its	its	PRON
ajst-11303	39	37	high	high	ADJ
ajst-11303	39	38	prediction	prediction	NOUN
ajst-11303	39	39	accuracy	accuracy	NOUN
ajst-11303	39	40	and	and	CCONJ
ajst-11303	39	41	improvement	improvement	NOUN
ajst-11303	39	42	of	of	ADP
ajst-11303	39	43	cementing	cement	VERB
ajst-11303	39	44	quality	quality	NOUN
ajst-11303	39	45	.	.	PUNCT
ajst-11303	40	1	deng	deng	PROPN
ajst-11303	40	2	yaping	yaping	PROPN
ajst-11303	40	3	and	and	CCONJ
ajst-11303	40	4	duan	duan	PROPN
ajst-11303	40	5	jiandong	jiandong	PROPN
ajst-11303	40	6	et	et	PROPN
ajst-11303	40	7	al[12].used	al[12].use	VERB
ajst-11303	40	8	cuckoo	cuckoo	NOUN
ajst-11303	40	9	algorithm	algorithm	NOUN
ajst-11303	40	10	to	to	PART
ajst-11303	40	11	optimize	optimize	VERB
ajst-11303	40	12	independent	independent	ADJ
ajst-11303	40	13	recurrent	recurrent	ADJ
ajst-11303	40	14	neural	neural	ADJ
ajst-11303	40	15	network	network	NOUN
ajst-11303	40	16	to	to	PART
ajst-11303	40	17	predict	predict	VERB
ajst-11303	40	18	wind	wind	NOUN
ajst-11303	40	19	power	power	NOUN
ajst-11303	40	20	,	,	PUNCT
ajst-11303	40	21	and	and	CCONJ
ajst-11303	40	22	the	the	DET
ajst-11303	40	23	final	final	ADJ
ajst-11303	40	24	prediction	prediction	NOUN
ajst-11303	40	25	accuracy	accuracy	NOUN
ajst-11303	40	26	was	be	AUX
ajst-11303	40	27	good	good	ADJ
ajst-11303	40	28	.	.	PUNCT
ajst-11303	41	1	zhao	zhao	PROPN
ajst-11303	41	2	et	et	PROPN
ajst-11303	41	3	al[13].proposed	al[13].propose	VERB
ajst-11303	41	4	a	a	DET
ajst-11303	41	5	new	new	ADJ
ajst-11303	41	6	framework	framework	NOUN
ajst-11303	41	7	for	for	ADP
ajst-11303	41	8	activity	activity	NOUN
ajst-11303	41	9	recognition	recognition	NOUN
ajst-11303	41	10	combining	combine	VERB
ajst-11303	41	11	short	short	ADJ
ajst-11303	41	12	-	-	PUNCT
ajst-11303	41	13	term	term	NOUN
ajst-11303	41	14	spatial	spatial	ADJ
ajst-11303	41	15	/	/	SYM
ajst-11303	41	16	frequency	frequency	NOUN
ajst-11303	41	17	feature	feature	NOUN
ajst-11303	41	18	extraction	extraction	NOUN
ajst-11303	41	19	and	and	CCONJ
ajst-11303	41	20	long	long	ADJ
ajst-11303	41	21	-	-	PUNCT
ajst-11303	41	22	term	term	NOUN
ajst-11303	41	23	independent	independent	ADJ
ajst-11303	41	24	recurrent	recurrent	ADJ
ajst-11303	41	25	neural	neural	ADJ
ajst-11303	41	26	networks	network	NOUN
ajst-11303	41	27	to	to	PART
ajst-11303	41	28	solve	solve	VERB
ajst-11303	41	29	the	the	DET
ajst-11303	41	30	time	time	NOUN
ajst-11303	41	31	recognition	recognition	NOUN
ajst-11303	41	32	problem	problem	NOUN
ajst-11303	41	33	of	of	ADP
ajst-11303	41	34	large	large	ADJ
ajst-11303	41	35	intra	intra	ADJ
ajst-11303	41	36	-	-	ADJ
ajst-11303	41	37	class	class	ADJ
ajst-11303	41	38	distance	distance	NOUN
ajst-11303	41	39	and	and	CCONJ
ajst-11303	41	40	small	small	ADJ
ajst-11303	41	41	intra	intra	ADJ
ajst-11303	41	42	-	-	ADJ
ajst-11303	41	43	class	class	ADJ
ajst-11303	41	44	distance	distance	NOUN
ajst-11303	41	45	.	.	PUNCT
ajst-11303	42	1	li	li	PROPN
ajst-11303	42	2	jia	jia	PROPN
ajst-11303	42	3	and	and	CCONJ
ajst-11303	42	4	huang	huang	PROPN
ajst-11303	42	5	zhihao	zhihao	PROPN
ajst-11303	42	6	et	et	PROPN
ajst-11303	42	7	al[14	al[14	PROPN
ajst-11303	42	8	]	]	PUNCT
ajst-11303	42	9	.	.	PUNCT
ajst-11303	42	10	established	establish	VERB
ajst-11303	42	11	a	a	DET
ajst-11303	42	12	model	model	NOUN
ajst-11303	42	13	of	of	ADP
ajst-11303	42	14	accurate	accurate	ADJ
ajst-11303	42	15	gdp	gdp	NOUN
ajst-11303	42	16	prediction	prediction	NOUN
ajst-11303	42	17	based	base	VERB
ajst-11303	42	18	on	on	ADP
ajst-11303	42	19	independent	independent	ADJ
ajst-11303	42	20	recurrent	recurrent	ADJ
ajst-11303	42	21	neural	neural	ADJ
ajst-11303	42	22	networks	network	NOUN
ajst-11303	42	23	,	,	PUNCT
ajst-11303	42	24	which	which	PRON
ajst-11303	42	25	provides	provide	VERB
ajst-11303	42	26	great	great	ADJ
ajst-11303	42	27	application	application	NOUN
ajst-11303	42	28	value	value	NOUN
ajst-11303	42	29	for	for	ADP
ajst-11303	42	30	economic	economic	ADJ
ajst-11303	42	31	forecasting	forecasting	NOUN
ajst-11303	42	32	.	.	PUNCT
ajst-11303	43	1	wu	wu	PROPN
ajst-11303	43	2	zhangyu	zhangyu	PROPN
ajst-11303	43	3	,	,	PUNCT
ajst-11303	43	4	zhu	zhu	PROPN
ajst-11303	43	5	chengjie	chengjie	PROPN
ajst-11303	43	6	et	et	PROPN
ajst-11303	43	7	al[15	al[15	PROPN
ajst-11303	43	8	]	]	PUNCT
ajst-11303	43	9	.	.	PUNCT
ajst-11303	44	1	used	use	VERB
ajst-11303	44	2	rnn	rnn	NOUN
ajst-11303	44	3	to	to	PART
ajst-11303	44	4	predict	predict	VERB
ajst-11303	44	5	the	the	DET
ajst-11303	44	6	health	health	NOUN
ajst-11303	44	7	status	status	NOUN
ajst-11303	44	8	of	of	ADP
ajst-11303	44	9	lithium	lithium	NOUN
ajst-11303	44	10	batteries	battery	NOUN
ajst-11303	44	11	,	,	PUNCT
ajst-11303	44	12	and	and	CCONJ
ajst-11303	44	13	the	the	DET
ajst-11303	44	14	error	error	NOUN
ajst-11303	44	15	of	of	ADP
ajst-11303	44	16	the	the	DET
ajst-11303	44	17	prediction	prediction	NOUN
ajst-11303	44	18	result	result	NOUN
ajst-11303	44	19	was	be	AUX
ajst-11303	44	20	small	small	ADJ
ajst-11303	44	21	,	,	PUNCT
ajst-11303	44	22	no	no	DET
ajst-11303	44	23	more	more	ADJ
ajst-11303	44	24	than	than	ADP
ajst-11303	44	25	0.02	0.02	NUM
ajst-11303	44	26	;	;	PUNCT
ajst-11303	45	1	wu	wu	PROPN
ajst-11303	45	2	lifen	lifen	NOUN
ajst-11303	45	3	et	et	NOUN
ajst-11303	45	4	al[16].applied	al[16].applie	VERB
ajst-11303	45	5	the	the	DET
ajst-11303	45	6	model	model	NOUN
ajst-11303	45	7	combining	combine	VERB
ajst-11303	45	8	rnn	rnn	PROPN
ajst-11303	45	9	and	and	CCONJ
ajst-11303	45	10	lstm	lstm	NOUN
ajst-11303	45	11	to	to	ADP
ajst-11303	45	12	the	the	DET
ajst-11303	45	13	machine	machine	NOUN
ajst-11303	45	14	poetry	poetry	NOUN
ajst-11303	45	15	writing	write	VERB
ajst-11303	45	16	system	system	NOUN
ajst-11303	45	17	,	,	PUNCT
ajst-11303	45	18	and	and	CCONJ
ajst-11303	45	19	the	the	DET
ajst-11303	45	20	effect	effect	NOUN
ajst-11303	45	21	was	be	AUX
ajst-11303	45	22	good	good	ADJ
ajst-11303	45	23	.	.	PUNCT
ajst-11303	46	1	tong	tong	PROPN
ajst-11303	46	2	et	et	PROPN
ajst-11303	46	3	al[17].established	al[17].establishe	VERB
ajst-11303	46	4	a	a	DET
ajst-11303	46	5	liquid	liquid	ADJ
ajst-11303	46	6	phase	phase	NOUN
ajst-11303	46	7	flow	flow	NOUN
ajst-11303	46	8	measurement	measurement	NOUN
ajst-11303	46	9	method	method	NOUN
ajst-11303	46	10	based	base	VERB
ajst-11303	46	11	on	on	ADP
ajst-11303	46	12	lstm	lstm	NOUN
ajst-11303	46	13	for	for	ADP
ajst-11303	46	14	gas	gas	NOUN
ajst-11303	46	15	-	-	PUNCT
ajst-11303	46	16	liquid	liquid	ADJ
ajst-11303	46	17	two	two	NUM
ajst-11303	46	18	-	-	PUNCT
ajst-11303	46	19	phase	phase	NOUN
ajst-11303	46	20	flow	flow	NOUN
ajst-11303	46	21	.	.	PUNCT
ajst-11303	47	1	the	the	DET
ajst-11303	47	2	root	root	NOUN
ajst-11303	47	3	mean	mean	VERB
ajst-11303	47	4	square	square	ADJ
ajst-11303	47	5	error	error	NOUN
ajst-11303	47	6	is	be	AUX
ajst-11303	47	7	small	small	ADJ
ajst-11303	47	8	,	,	PUNCT
ajst-11303	47	9	and	and	CCONJ
ajst-11303	47	10	the	the	DET
ajst-11303	47	11	measurement	measurement	NOUN
ajst-11303	47	12	accuracy	accuracy	NOUN
ajst-11303	47	13	and	and	CCONJ
ajst-11303	47	14	speed	speed	NOUN
ajst-11303	47	15	are	be	AUX
ajst-11303	47	16	better	well	ADJ
ajst-11303	47	17	.	.	PUNCT
ajst-11303	48	1	3	3	X
ajst-11303	48	2	.	.	NOUN
ajst-11303	48	3	prediction	prediction	NOUN
ajst-11303	48	4	model	model	NOUN
ajst-11303	48	5	of	of	ADP
ajst-11303	48	6	cement	cement	NOUN
ajst-11303	48	7	slurry	slurry	NOUN
ajst-11303	48	8	density	density	NOUN
ajst-11303	48	9	based	base	VERB
ajst-11303	48	10	on	on	ADP
ajst-11303	48	11	amindrnn	amindrnn	NOUN
ajst-11303	48	12	as	as	SCONJ
ajst-11303	48	13	shown	show	VERB
ajst-11303	48	14	in	in	ADP
ajst-11303	48	15	figure	figure	NOUN
ajst-11303	48	16	1	1	NUM
ajst-11303	48	17	,	,	PUNCT
ajst-11303	48	18	the	the	DET
ajst-11303	48	19	architecture	architecture	NOUN
ajst-11303	48	20	of	of	ADP
ajst-11303	48	21	amindrnn	amindrnn	PROPN
ajst-11303	48	22	model	model	NOUN
ajst-11303	48	23	proposed	propose	VERB
ajst-11303	48	24	in	in	ADP
ajst-11303	48	25	this	this	DET
ajst-11303	48	26	paper	paper	NOUN
ajst-11303	48	27	consists	consist	VERB
ajst-11303	48	28	of	of	ADP
ajst-11303	48	29	input	input	NOUN
ajst-11303	48	30	layer	layer	NOUN
ajst-11303	48	31	,	,	PUNCT
ajst-11303	48	32	indrnn	indrnn	VERB
ajst-11303	48	33	layer	layer	NOUN
ajst-11303	48	34	,	,	PUNCT
ajst-11303	48	35	attention	attention	NOUN
ajst-11303	48	36	layer	layer	NOUN
ajst-11303	48	37	and	and	CCONJ
ajst-11303	48	38	output	output	NOUN
ajst-11303	48	39	layer	layer	NOUN
ajst-11303	48	40	.	.	PUNCT
ajst-11303	49	1	固井泥浆数据	固井泥浆数据	NOUN
ajst-11303	50	1	x1	x1	PROPN
ajst-11303	51	1	x2	x2	PROPN
ajst-11303	51	2	x3	x3	PROPN
ajst-11303	51	3	xn输入层	xn输入层	PROPN
ajst-11303	51	4	...	...	PUNCT
ajst-11303	52	1	indrnn第一层	indrnn第一层	ADJ
ajst-11303	52	2	indrnn	indrnn	NOUN
ajst-11303	52	3	indrnn	indrnn	PROPN
ajst-11303	52	4	indrnn	indrnn	NOUN
ajst-11303	53	1	indrnn第二层	indrnn第二层	PROPN
ajst-11303	53	2	indrnn	indrnn	VERB
ajst-11303	53	3	indrnn	indrnn	NOUN
ajst-11303	53	4	indrnn	indrnn	NOUN
ajst-11303	53	5	indrnn第l层	indrnn第l层	PROPN
ajst-11303	53	6	indrnn	indrnn	VERB
ajst-11303	53	7	indrnn	indrnn	NOUN
ajst-11303	53	8	indrnn	indrnn	NOUN
ajst-11303	53	9	..	..	PUNCT
ajst-11303	53	10	.	.	PUNCT
ajst-11303	54	1	..	..	PUNCT
ajst-11303	54	2	.	.	PUNCT
ajst-11303	55	1	..	..	PUNCT
ajst-11303	55	2	.	.	PUNCT
ajst-11303	56	1	..	..	PUNCT
ajst-11303	56	2	.	.	PUNCT
ajst-11303	57	1	indrnn	indrnn	NOUN
ajst-11303	57	2	层	层	INTJ
ajst-11303	58	1	注意力层	注意力层	PROPN
ajst-11303	58	2	dense_2	dense_2	NOUN
ajst-11303	58	3	dense_1	dense_1	VERB
ajst-11303	58	4	注意力层	注意力层	PROPN
ajst-11303	58	5	输出层	输出层	ADP
ajst-11303	58	6	固井水泥浆密度值	固井水泥浆密度值	PROPN
ajst-11303	58	7	linear	linear	PROPN
ajst-11303	58	8	...	...	PUNCT
ajst-11303	58	9	...	...	PUNCT
ajst-11303	58	10	...	...	PUNCT
ajst-11303	58	11	...	...	PUNCT
ajst-11303	58	12	...	...	PUNCT
ajst-11303	59	1	figure	figure	NOUN
ajst-11303	59	2	1	1	NUM
ajst-11303	59	3	.	.	NUM
ajst-11303	59	4	amindrnn	amindrnn	AUX
ajst-11303	59	5	structure	structure	NOUN
ajst-11303	59	6	3.1	3.1	NUM
ajst-11303	59	7	.	.	PUNCT
ajst-11303	60	1	input	input	NOUN
ajst-11303	60	2	layer	layer	NOUN
ajst-11303	60	3	the	the	DET
ajst-11303	60	4	input	input	NOUN
ajst-11303	60	5	layer	layer	NOUN
ajst-11303	60	6	is	be	AUX
ajst-11303	60	7	used	use	VERB
ajst-11303	60	8	to	to	PART
ajst-11303	60	9	receive	receive	VERB
ajst-11303	60	10	the	the	DET
ajst-11303	60	11	collected	collect	VERB
ajst-11303	60	12	cement	cement	NOUN
ajst-11303	60	13	slurry	slurry	NOUN
ajst-11303	60	14	density	density	NOUN
ajst-11303	60	15	data	datum	NOUN
ajst-11303	60	16	.	.	PUNCT
ajst-11303	61	1	first	first	ADV
ajst-11303	61	2	,	,	PUNCT
ajst-11303	61	3	standardize	standardize	VERB
ajst-11303	61	4	the	the	DET
ajst-11303	61	5	input	input	NOUN
ajst-11303	61	6	data	datum	NOUN
ajst-11303	61	7	.	.	PUNCT
ajst-11303	62	1	due	due	ADP
ajst-11303	62	2	to	to	ADP
ajst-11303	62	3	the	the	DET
ajst-11303	62	4	different	different	ADJ
ajst-11303	62	5	units	unit	NOUN
ajst-11303	62	6	of	of	ADP
ajst-11303	62	7	each	each	DET
ajst-11303	62	8	data	datum	NOUN
ajst-11303	62	9	feature	feature	NOUN
ajst-11303	62	10	,	,	PUNCT
ajst-11303	62	11	this	this	DET
ajst-11303	62	12	section	section	NOUN
ajst-11303	62	13	uses	use	VERB
ajst-11303	62	14	the	the	DET
ajst-11303	62	15	min	min	PROPN
ajst-11303	62	16	-	-	ADJ
ajst-11303	62	17	max	max	PROPN
ajst-11303	62	18	function	function	NOUN
ajst-11303	62	19	to	to	PART
ajst-11303	62	20	perform	perform	VERB
ajst-11303	62	21	linear	linear	ADJ
ajst-11303	62	22	transformation	transformation	NOUN
ajst-11303	62	23	on	on	ADP
ajst-11303	62	24	the	the	DET
ajst-11303	62	25	data	datum	NOUN
ajst-11303	62	26	to	to	PART
ajst-11303	62	27	eliminate	eliminate	VERB
ajst-11303	62	28	the	the	DET
ajst-11303	62	29	influence	influence	NOUN
ajst-11303	62	30	of	of	ADP
ajst-11303	62	31	the	the	DET
ajst-11303	62	32	dimension	dimension	NOUN
ajst-11303	62	33	and	and	CCONJ
ajst-11303	62	34	order	order	NOUN
ajst-11303	62	35	of	of	ADP
ajst-11303	62	36	magnitude	magnitude	NOUN
ajst-11303	62	37	of	of	ADP
ajst-11303	62	38	the	the	DET
ajst-11303	62	39	data	datum	NOUN
ajst-11303	62	40	.	.	PUNCT
ajst-11303	63	1	the	the	DET
ajst-11303	63	2	min	min	PROPN
ajst-11303	63	3	-	-	ADJ
ajst-11303	63	4	max	max	PROPN
ajst-11303	63	5	function	function	NOUN
ajst-11303	63	6	formula	formula	NOUN
ajst-11303	63	7	is	be	AUX
ajst-11303	63	8	shown	show	VERB
ajst-11303	63	9	in	in	ADP
ajst-11303	63	10	(	(	PUNCT
ajst-11303	63	11	1	1	NUM
ajst-11303	63	12	)	)	PUNCT
ajst-11303	63	13	.	.	PUNCT
ajst-11303	64	1	158	158	NUM
ajst-11303	65	1			NUM
ajst-11303	65	2	*	*	PUNCT
ajst-11303	65	3	x	x	X
ajst-11303	65	4	-min	-min	PUNCT
ajst-11303	65	5	x	x	SYM
ajst-11303	65	6	max	max	PROPN
ajst-11303	65	7	-min	-min	PUNCT
ajst-11303	65	8	(	(	PUNCT
ajst-11303	65	9	1	1	X
ajst-11303	65	10	)	)	PUNCT
ajst-11303	65	11	where	where	SCONJ
ajst-11303	65	12	x	x	PRON
ajst-11303	65	13	is	be	AUX
ajst-11303	65	14	the	the	DET
ajst-11303	65	15	sample	sample	NOUN
ajst-11303	65	16	data	datum	NOUN
ajst-11303	65	17	,	,	PUNCT
ajst-11303	65	18	min	min	PROPN
ajst-11303	65	19	is	be	AUX
ajst-11303	65	20	the	the	DET
ajst-11303	65	21	minimum	minimum	ADJ
ajst-11303	65	22	value	value	NOUN
ajst-11303	65	23	of	of	ADP
ajst-11303	65	24	the	the	DET
ajst-11303	65	25	sample	sample	NOUN
ajst-11303	65	26	data	datum	NOUN
ajst-11303	65	27	,	,	PUNCT
ajst-11303	65	28	andmax	andmax	PROPN
ajst-11303	65	29	is	be	AUX
ajst-11303	65	30	the	the	DET
ajst-11303	65	31	maximum	maximum	ADJ
ajst-11303	65	32	value	value	NOUN
ajst-11303	65	33	of	of	ADP
ajst-11303	65	34	the	the	DET
ajst-11303	65	35	sample	sample	NOUN
ajst-11303	65	36	data	datum	NOUN
ajst-11303	65	37	,	,	PUNCT
ajst-11303	65	38	*	*	PUNCT
ajst-11303	65	39	x	x	PROPN
ajst-11303	65	40	represents	represent	VERB
ajst-11303	65	41	the	the	DET
ajst-11303	65	42	converted	converted	ADJ
ajst-11303	65	43	data	datum	NOUN
ajst-11303	65	44	.	.	PUNCT
ajst-11303	66	1	suppose	suppose	VERB
ajst-11303	66	2	the	the	DET
ajst-11303	66	3	input	input	NOUN
ajst-11303	66	4	data	data	NOUN
ajst-11303	66	5	is	be	AUX
ajst-11303	66	6	d	d	NOUN
ajst-11303	66	7	ix	ix	ADV
ajst-11303	66	8	,	,	PUNCT
ajst-11303	66	9	d	d	X
ajst-11303	66	10	is	be	AUX
ajst-11303	66	11	the	the	DET
ajst-11303	66	12	characteristic	characteristic	ADJ
ajst-11303	66	13	dimension	dimension	NOUN
ajst-11303	66	14	.	.	PUNCT
ajst-11303	67	1	for	for	ADP
ajst-11303	67	2	n	n	NOUN
ajst-11303	67	3	training	training	NOUN
ajst-11303	67	4	samples	sample	NOUN
ajst-11303	67	5	,	,	PUNCT
ajst-11303	67	6	the	the	DET
ajst-11303	67	7	input	input	NOUN
ajst-11303	67	8	feature	feature	NOUN
ajst-11303	67	9	tensor	tensor	NOUN
ajst-11303	67	10	d	d	NOUN
ajst-11303	67	11	ix	ix	PROPN
ajst-11303	67	12	can	can	AUX
ajst-11303	67	13	be	be	AUX
ajst-11303	67	14	expressed	express	VERB
ajst-11303	67	15	as	as	ADP
ajst-11303	67	16	:	:	PUNCT
ajst-11303	67	17	d	d	PROPN
ajst-11303	68	1	d	d	X
ajst-11303	69	1	d	d	X
ajst-11303	70	1	d	d	X
ajst-11303	71	1	i	i	NOUN
ajst-11303	72	1	1	1	NUM
ajst-11303	72	2	2	2	NUM
ajst-11303	72	3	nx	nx	NOUN
ajst-11303	72	4	=	=	PUNCT
ajst-11303	73	1	[	[	X
ajst-11303	73	2	x	x	X
ajst-11303	73	3	,	,	PUNCT
ajst-11303	73	4	x	x	INTJ
ajst-11303	73	5	,	,	PUNCT
ajst-11303	73	6	...	...	PUNCT
ajst-11303	73	7	,	,	PUNCT
ajst-11303	73	8	x	x	X
ajst-11303	73	9	]	]	X
ajst-11303	73	10	,	,	PUNCT
ajst-11303	73	11	i	i	PRON
ajst-11303	73	12	=	=	NOUN
ajst-11303	73	13	1,2,	1,2,	NUM
ajst-11303	73	14	...	...	PUNCT
ajst-11303	73	15	,n	,n	PUNCT
ajst-11303	73	16	.	.	PUNCT
ajst-11303	74	1	3.2	3.2	NUM
ajst-11303	74	2	.	.	PUNCT
ajst-11303	74	3	indrnn	indrnn	VERB
ajst-11303	74	4	layer	layer	NOUN
ajst-11303	74	5	as	as	ADP
ajst-11303	74	6	one	one	NUM
ajst-11303	74	7	of	of	ADP
ajst-11303	74	8	the	the	DET
ajst-11303	74	9	traditional	traditional	ADJ
ajst-11303	74	10	deep	deep	ADJ
ajst-11303	74	11	learning	learning	NOUN
ajst-11303	74	12	methods	method	NOUN
ajst-11303	74	13	,	,	PUNCT
ajst-11303	74	14	recurrent	recurrent	ADJ
ajst-11303	74	15	neural	neural	ADJ
ajst-11303	74	16	network	network	NOUN
ajst-11303	74	17	(	(	PUNCT
ajst-11303	74	18	rnn	rnn	PROPN
ajst-11303	74	19	)	)	PUNCT
ajst-11303	74	20	is	be	AUX
ajst-11303	74	21	applied	apply	VERB
ajst-11303	74	22	to	to	ADP
ajst-11303	74	23	a	a	DET
ajst-11303	74	24	variety	variety	NOUN
ajst-11303	74	25	of	of	ADP
ajst-11303	74	26	scenarios	scenario	NOUN
ajst-11303	74	27	,	,	PUNCT
ajst-11303	74	28	such	such	ADJ
ajst-11303	74	29	as	as	ADP
ajst-11303	74	30	text	text	NOUN
ajst-11303	74	31	generation	generation	NOUN
ajst-11303	74	32	,	,	PUNCT
ajst-11303	74	33	speech	speech	NOUN
ajst-11303	74	34	recognition	recognition	NOUN
ajst-11303	74	35	,	,	PUNCT
ajst-11303	74	36	etc	etc	X
ajst-11303	74	37	.	.	X
ajst-11303	75	1	rnn	rnn	PROPN
ajst-11303	75	2	has	have	VERB
ajst-11303	75	3	some	some	DET
ajst-11303	75	4	limitations	limitation	NOUN
ajst-11303	75	5	due	due	ADP
ajst-11303	75	6	to	to	ADP
ajst-11303	75	7	the	the	DET
ajst-11303	75	8	problems	problem	NOUN
ajst-11303	75	9	of	of	ADP
ajst-11303	75	10	gradient	gradient	ADJ
ajst-11303	75	11	disappearance	disappearance	NOUN
ajst-11303	75	12	and	and	CCONJ
ajst-11303	75	13	gradient	gradient	NOUN
ajst-11303	75	14	explosion	explosion	NOUN
ajst-11303	75	15	.	.	PUNCT
ajst-11303	76	1	as	as	ADP
ajst-11303	76	2	variants	variant	NOUN
ajst-11303	76	3	of	of	ADP
ajst-11303	76	4	rnn	rnn	PROPN
ajst-11303	76	5	,	,	PUNCT
ajst-11303	76	6	lstm	lstm	NOUN
ajst-11303	76	7	and	and	CCONJ
ajst-11303	76	8	gru	gru	PROPN
ajst-11303	76	9	solve	solve	VERB
ajst-11303	76	10	the	the	DET
ajst-11303	76	11	above	above	ADJ
ajst-11303	76	12	problems	problem	NOUN
ajst-11303	76	13	to	to	ADP
ajst-11303	76	14	a	a	DET
ajst-11303	76	15	certain	certain	ADJ
ajst-11303	76	16	extent	extent	NOUN
ajst-11303	76	17	,	,	PUNCT
ajst-11303	76	18	but	but	CCONJ
ajst-11303	76	19	in	in	ADP
ajst-11303	76	20	multi	multi	ADJ
ajst-11303	76	21	-	-	ADJ
ajst-11303	76	22	layer	layer	ADJ
ajst-11303	76	23	neural	neural	ADJ
ajst-11303	76	24	networks	network	NOUN
ajst-11303	76	25	,	,	PUNCT
ajst-11303	76	26	the	the	DET
ajst-11303	76	27	disappearance	disappearance	NOUN
ajst-11303	76	28	of	of	ADP
ajst-11303	76	29	gradients	gradient	NOUN
ajst-11303	76	30	is	be	AUX
ajst-11303	76	31	still	still	ADV
ajst-11303	76	32	inevitable	inevitable	ADJ
ajst-11303	76	33	.	.	PUNCT
ajst-11303	77	1	reference	reference	NOUN
ajst-11303	78	1	[	[	X
ajst-11303	78	2	18	18	NUM
ajst-11303	78	3	]	]	PUNCT
ajst-11303	78	4	proposed	propose	VERB
ajst-11303	78	5	the	the	DET
ajst-11303	78	6	indrnn	indrnn	NOUN
ajst-11303	78	7	model	model	NOUN
ajst-11303	78	8	,	,	PUNCT
ajst-11303	78	9	which	which	PRON
ajst-11303	78	10	can	can	AUX
ajst-11303	78	11	be	be	AUX
ajst-11303	78	12	combined	combine	VERB
ajst-11303	78	13	with	with	ADP
ajst-11303	78	14	the	the	DET
ajst-11303	78	15	unsaturated	unsaturated	ADJ
ajst-11303	78	16	activation	activation	NOUN
ajst-11303	78	17	function	function	NOUN
ajst-11303	78	18	relu	relu	NOUN
ajst-11303	78	19	to	to	PART
ajst-11303	78	20	carry	carry	VERB
ajst-11303	78	21	out	out	ADP
ajst-11303	78	22	more	more	ADV
ajst-11303	78	23	robust	robust	ADJ
ajst-11303	78	24	training	training	NOUN
ajst-11303	78	25	.	.	PUNCT
ajst-11303	79	1	the	the	DET
ajst-11303	79	2	problem	problem	NOUN
ajst-11303	79	3	of	of	ADP
ajst-11303	79	4	gradient	gradient	ADJ
ajst-11303	79	5	disappearance	disappearance	NOUN
ajst-11303	79	6	and	and	CCONJ
ajst-11303	79	7	gradient	gradient	NOUN
ajst-11303	79	8	explosion	explosion	NOUN
ajst-11303	79	9	is	be	AUX
ajst-11303	79	10	solved	solve	VERB
ajst-11303	79	11	to	to	ADP
ajst-11303	79	12	a	a	DET
ajst-11303	79	13	certain	certain	ADJ
ajst-11303	79	14	extent	extent	NOUN
ajst-11303	79	15	by	by	ADP
ajst-11303	79	16	gradient	gradient	NOUN
ajst-11303	79	17	back	back	NOUN
ajst-11303	79	18	propagation	propagation	NOUN
ajst-11303	79	19	adjustment[19	adjustment[19	NOUN
ajst-11303	79	20	]	]	PUNCT
ajst-11303	79	21	.	.	PUNCT
ajst-11303	80	1	the	the	DET
ajst-11303	80	2	formula	formula	NOUN
ajst-11303	80	3	of	of	ADP
ajst-11303	80	4	the	the	DET
ajst-11303	80	5	model	model	NOUN
ajst-11303	80	6	is	be	AUX
ajst-11303	80	7	shown	show	VERB
ajst-11303	80	8	in	in	ADP
ajst-11303	80	9	(	(	PUNCT
ajst-11303	80	10	2	2	NUM
ajst-11303	80	11	)	)	PUNCT
ajst-11303	80	12	.	.	PUNCT
ajst-11303	81	1			PROPN
ajst-11303	81	2	�	�	PROPN
ajst-11303	81	3	t	t	PROPN
ajst-11303	81	4	t	t	NOUN
ajst-11303	81	5	t-1h	t-1h	PROPN
ajst-11303	81	6	=	=	SYM
ajst-11303	81	7	(	(	PUNCT
ajst-11303	81	8	wx	wx	PROPN
ajst-11303	81	9	+	+	NOUN
ajst-11303	81	10	u	u	NOUN
ajst-11303	81	11	h	h	NOUN
ajst-11303	81	12	+	+	NOUN
ajst-11303	81	13	b	b	NOUN
ajst-11303	81	14	)	)	PUNCT
ajst-11303	81	15	(	(	PUNCT
ajst-11303	81	16	2	2	X
ajst-11303	81	17	)	)	PUNCT
ajst-11303	81	18	where	where	SCONJ
ajst-11303	81	19	�	�	PROPN
ajst-11303	81	20	represents	represent	VERB
ajst-11303	81	21	the	the	DET
ajst-11303	81	22	hadamard	hadamard	ADJ
ajst-11303	81	23	product	product	NOUN
ajst-11303	81	24	,	,	PUNCT
ajst-11303	81	25	w	w	PROPN
ajst-11303	81	26	represents	represent	VERB
ajst-11303	81	27	the	the	DET
ajst-11303	81	28	current	current	ADJ
ajst-11303	81	29	input	input	NOUN
ajst-11303	81	30	weight	weight	NOUN
ajst-11303	81	31	,	,	PUNCT
ajst-11303	81	32	u	u	NOUN
ajst-11303	81	33	represents	represent	VERB
ajst-11303	81	34	the	the	DET
ajst-11303	81	35	weight	weight	NOUN
ajst-11303	81	36	vector	vector	NOUN
ajst-11303	81	37	of	of	ADP
ajst-11303	81	38	1th	1th	NUM
ajst-11303	81	39	,	,	PUNCT
ajst-11303	81	40	b	b	PROPN
ajst-11303	81	41	represents	represent	VERB
ajst-11303	81	42	the	the	DET
ajst-11303	81	43	bias	bias	NOUN
ajst-11303	81	44	vector	vector	NOUN
ajst-11303	81	45	,	,	PUNCT
ajst-11303	81	46	tx	tx	PROPN
ajst-11303	81	47	represents	represent	VERB
ajst-11303	81	48	the	the	DET
ajst-11303	81	49	input	input	NOUN
ajst-11303	81	50	at	at	ADP
ajst-11303	81	51	time	time	NOUN
ajst-11303	81	52	t	t	PROPN
ajst-11303	81	53	,	,	PUNCT
ajst-11303	81	54	1th	1th	PROPN
ajst-11303	81	55	represents	represent	VERB
ajst-11303	81	56	the	the	DET
ajst-11303	81	57	hidden	hidden	ADJ
ajst-11303	81	58	state	state	NOUN
ajst-11303	81	59	at	at	ADP
ajst-11303	81	60	time	time	NOUN
ajst-11303	81	61	t	t	PROPN
ajst-11303	81	62	1	1	NUM
ajst-11303	81	63	,	,	PUNCT
ajst-11303	81	64	and	and	CCONJ
ajst-11303	81	65			PROPN
ajst-11303	81	66	is	be	AUX
ajst-11303	81	67	the	the	DET
ajst-11303	81	68	activation	activation	NOUN
ajst-11303	81	69	function	function	NOUN
ajst-11303	81	70	.	.	PUNCT
ajst-11303	82	1	the	the	DET
ajst-11303	82	2	neural	neural	ADJ
ajst-11303	82	3	network	network	NOUN
ajst-11303	82	4	structure	structure	NOUN
ajst-11303	82	5	in	in	ADP
ajst-11303	82	6	the	the	DET
ajst-11303	82	7	model	model	NOUN
ajst-11303	82	8	is	be	AUX
ajst-11303	82	9	independent	independent	ADJ
ajst-11303	82	10	of	of	ADP
ajst-11303	82	11	each	each	DET
ajst-11303	82	12	other	other	ADJ
ajst-11303	82	13	when	when	SCONJ
ajst-11303	82	14	processing	processing	NOUN
ajst-11303	82	15	input	input	NOUN
ajst-11303	82	16	data	datum	NOUN
ajst-11303	82	17	,	,	PUNCT
ajst-11303	82	18	and	and	CCONJ
ajst-11303	82	19	can	can	AUX
ajst-11303	82	20	realize	realize	VERB
ajst-11303	82	21	parallel	parallel	ADJ
ajst-11303	82	22	operation	operation	NOUN
ajst-11303	82	23	.	.	PUNCT
ajst-11303	83	1	in	in	ADP
ajst-11303	83	2	addition	addition	NOUN
ajst-11303	83	3	,	,	PUNCT
ajst-11303	83	4	the	the	DET
ajst-11303	83	5	neurons	neuron	NOUN
ajst-11303	83	6	of	of	ADP
ajst-11303	83	7	each	each	DET
ajst-11303	83	8	layer	layer	NOUN
ajst-11303	83	9	are	be	AUX
ajst-11303	83	10	also	also	ADV
ajst-11303	83	11	independent	independent	ADJ
ajst-11303	83	12	of	of	ADP
ajst-11303	83	13	each	each	DET
ajst-11303	83	14	other	other	ADJ
ajst-11303	83	15	,	,	PUNCT
ajst-11303	83	16	and	and	CCONJ
ajst-11303	83	17	the	the	DET
ajst-11303	83	18	output	output	NOUN
ajst-11303	83	19	of	of	ADP
ajst-11303	83	20	the	the	DET
ajst-11303	83	21	hidden	hidden	ADJ
ajst-11303	83	22	state	state	NOUN
ajst-11303	83	23	,	,	PUNCT
ajst-11303	83	24	n	n	CCONJ
ajst-11303	83	25	th	th	X
ajst-11303	83	26	at	at	ADP
ajst-11303	83	27	time	time	NOUN
ajst-11303	83	28	t	t	PROPN
ajst-11303	83	29	in	in	ADP
ajst-11303	83	30	the	the	DET
ajst-11303	83	31	n	n	PRON
ajst-11303	83	32	neuron	neuron	NOUN
ajst-11303	83	33	is	be	AUX
ajst-11303	83	34	shown	show	VERB
ajst-11303	83	35	in	in	ADP
ajst-11303	83	36	formula	formula	NOUN
ajst-11303	83	37	(	(	PUNCT
ajst-11303	83	38	3	3	NUM
ajst-11303	83	39	)	)	PUNCT
ajst-11303	83	40	.	.	PUNCT
ajst-11303	84	1	,	,	PUNCT
ajst-11303	84	2	,	,	PUNCT
ajst-11303	84	3	n	n	PROPN
ajst-11303	84	4	t	t	PROPN
ajst-11303	84	5	n	n	ADP
ajst-11303	84	6	t	t	PROPN
ajst-11303	84	7	n	n	CCONJ
ajst-11303	84	8	n	n	PROPN
ajst-11303	84	9	t-1	t-1	PROPN
ajst-11303	84	10	nh	nh	PROPN
ajst-11303	84	11	=	=	PUNCT
ajst-11303	84	12	(	(	PUNCT
ajst-11303	84	13	w	w	NOUN
ajst-11303	84	14	x	x	SYM
ajst-11303	84	15	+	+	NOUN
ajst-11303	84	16	u	u	NOUN
ajst-11303	84	17	h	h	NOUN
ajst-11303	84	18	+	+	NOUN
ajst-11303	84	19	b	b	NOUN
ajst-11303	84	20	)	)	PUNCT
ajst-11303	84	21	(	(	PUNCT
ajst-11303	84	22	3	3	X
ajst-11303	84	23	)	)	PUNCT
ajst-11303	84	24	where	where	SCONJ
ajst-11303	84	25	nw	nw	PROPN
ajst-11303	84	26	represents	represent	VERB
ajst-11303	84	27	the	the	DET
ajst-11303	84	28	input	input	NOUN
ajst-11303	84	29	weight	weight	NOUN
ajst-11303	84	30	of	of	ADP
ajst-11303	84	31	the	the	DET
ajst-11303	84	32	n	n	DET
ajst-11303	84	33	layer	layer	NOUN
ajst-11303	84	34	,	,	PUNCT
ajst-11303	84	35	nu	nu	PROPN
ajst-11303	84	36	represents	represent	VERB
ajst-11303	84	37	the	the	DET
ajst-11303	84	38	current	current	ADJ
ajst-11303	84	39	weight	weight	NOUN
ajst-11303	84	40	,	,	PUNCT
ajst-11303	84	41	and	and	CCONJ
ajst-11303	84	42	nb	nb	PROPN
ajst-11303	84	43	brepresents	brepresent	NOUN
ajst-11303	84	44	bias	bias	PROPN
ajst-11303	84	45	.	.	PUNCT
ajst-11303	85	1	the	the	DET
ajst-11303	85	2	disadvantage	disadvantage	NOUN
ajst-11303	85	3	of	of	ADP
ajst-11303	85	4	the	the	DET
ajst-11303	85	5	relu	relu	NOUN
ajst-11303	85	6	function	function	NOUN
ajst-11303	85	7	is	be	AUX
ajst-11303	85	8	that	that	SCONJ
ajst-11303	85	9	the	the	DET
ajst-11303	85	10	output	output	NOUN
ajst-11303	85	11	is	be	AUX
ajst-11303	85	12	always	always	ADV
ajst-11303	85	13	greater	great	ADJ
ajst-11303	85	14	than	than	ADP
ajst-11303	85	15	0	0	NUM
ajst-11303	85	16	,	,	PUNCT
ajst-11303	85	17	ignoring	ignore	VERB
ajst-11303	85	18	the	the	DET
ajst-11303	85	19	input	input	NOUN
ajst-11303	85	20	of	of	ADP
ajst-11303	85	21	negative	negative	ADJ
ajst-11303	85	22	numbers	number	NOUN
ajst-11303	85	23	.	.	PUNCT
ajst-11303	86	1	in	in	ADP
ajst-11303	86	2	order	order	NOUN
ajst-11303	86	3	to	to	PART
ajst-11303	86	4	better	well	ADV
ajst-11303	86	5	extract	extract	VERB
ajst-11303	86	6	the	the	DET
ajst-11303	86	7	characteristics	characteristic	NOUN
ajst-11303	86	8	of	of	ADP
ajst-11303	86	9	cement	cement	NOUN
ajst-11303	86	10	slurry	slurry	NOUN
ajst-11303	86	11	data	datum	NOUN
ajst-11303	86	12	,	,	PUNCT
ajst-11303	86	13	this	this	DET
ajst-11303	86	14	paper	paper	NOUN
ajst-11303	86	15	introduces	introduce	VERB
ajst-11303	86	16	the	the	DET
ajst-11303	86	17	smu	smu	NOUN
ajst-11303	86	18	activation	activation	NOUN
ajst-11303	86	19	function[20	function[20	VERB
ajst-11303	86	20	]	]	PUNCT
ajst-11303	86	21	as	as	ADP
ajst-11303	86	22	the	the	DET
ajst-11303	86	23	activation	activation	NOUN
ajst-11303	86	24	function	function	NOUN
ajst-11303	86	25	of	of	ADP
ajst-11303	86	26	indrnn	indrnn	NOUN
ajst-11303	86	27	.	.	PUNCT
ajst-11303	87	1	its	its	PRON
ajst-11303	87	2	formula	formula	NOUN
ajst-11303	87	3	is	be	AUX
ajst-11303	87	4	shown	show	VERB
ajst-11303	87	5	in	in	ADP
ajst-11303	87	6	(	(	PUNCT
ajst-11303	87	7	4	4	NUM
ajst-11303	87	8	)	)	PUNCT
ajst-11303	87	9	.	.	PUNCT
ajst-11303	88	1	(	(	PUNCT
ajst-11303	88	2	1	1	X
ajst-11303	88	3	)	)	PUNCT
ajst-11303	88	4	(	(	PUNCT
ajst-11303	88	5	1	1	X
ajst-11303	88	6	)	)	PUNCT
ajst-11303	88	7	(	(	PUNCT
ajst-11303	88	8	(	(	PUNCT
ajst-11303	88	9	1	1	NUM
ajst-11303	88	10	)	)	PUNCT
ajst-11303	88	11	)	)	PUNCT
ajst-11303	88	12	(	(	PUNCT
ajst-11303	88	13	,	,	PUNCT
ajst-11303	88	14	,	,	PUNCT
ajst-11303	88	15	)	)	PUNCT
ajst-11303	88	16	2	2	NUM
ajst-11303	88	17			NOUN
ajst-11303	88	18			X
ajst-11303	88	19			NOUN
ajst-11303	88	20			PRON
ajst-11303	88	21			NOUN
ajst-11303	88	22			ADV
ajst-11303	88	23			PUNCT
ajst-11303	88	24			PROPN
ajst-11303	88	25	x	x	PROPN
ajst-11303	88	26	xerf	xerf	NOUN
ajst-11303	89	1	x	x	X
ajst-11303	89	2	f	f	NOUN
ajst-11303	89	3	x	x	PUNCT
ajst-11303	89	4	x	x	SYM
ajst-11303	89	5	=	=	SYM
ajst-11303	89	6	(	(	PUNCT
ajst-11303	89	7	4	4	X
ajst-11303	89	8	)	)	PUNCT
ajst-11303	89	9	the	the	DET
ajst-11303	89	10	optimized	optimize	VERB
ajst-11303	89	11	model	model	NOUN
ajst-11303	89	12	structure	structure	NOUN
ajst-11303	89	13	is	be	AUX
ajst-11303	89	14	shown	show	VERB
ajst-11303	89	15	in	in	ADP
ajst-11303	89	16	figure	figure	NOUN
ajst-11303	89	17	2	2	NUM
ajst-11303	89	18	.	.	PUNCT
ajst-11303	89	19	xt-1	xt-1	NUM
ajst-11303	90	1	xt	xt	PROPN
ajst-11303	90	2	layer1	layer1	PROPN
ajst-11303	90	3	weight	weight	NOUN
ajst-11303	90	4	recurrent+smu	recurrent+smu	NOUN
ajst-11303	90	5	weight	weight	NOUN
ajst-11303	90	6	recurrent+smu	recurrent+smu	PROPN
ajst-11303	90	7	layer2	layer2	PROPN
ajst-11303	90	8	weight	weight	PROPN
ajst-11303	90	9	recurrent+smu	recurrent+smu	PROPN
ajst-11303	90	10	layer3	layer3	PROPN
ajst-11303	90	11	ot-1	ot-1	PART
ajst-11303	90	12	weight	weight	PROPN
ajst-11303	90	13	recurrent+smuht-1	recurrent+smuht-1	ADJ
ajst-11303	90	14	weight	weight	PROPN
ajst-11303	90	15	recurrent+smuht-1	recurrent+smuht-1	PROPN
ajst-11303	90	16	weight	weight	PROPN
ajst-11303	90	17	recurrent+smuht-1	recurrent+smuht-1	PROPN
ajst-11303	90	18	ot	ot	INTJ
ajst-11303	90	19	·	·	PUNCT
ajst-11303	90	20	·	·	PUNCT
ajst-11303	90	21	·	·	PUNCT
ajst-11303	90	22	·	·	PUNCT
ajst-11303	90	23	·	·	PUNCT
ajst-11303	90	24	·	·	PUNCT
ajst-11303	90	25	·	·	PUNCT
ajst-11303	90	26	·	·	PUNCT
ajst-11303	90	27	·	·	PUNCT
ajst-11303	90	28	figure	figure	NOUN
ajst-11303	90	29	2	2	NUM
ajst-11303	90	30	.	.	NUM
ajst-11303	91	1	amindrnn	amindrnn	AUX
ajst-11303	91	2	structure	structure	NOUN
ajst-11303	91	3	3.3	3.3	NUM
ajst-11303	91	4	.	.	PUNCT
ajst-11303	92	1	attention	attention	NOUN
ajst-11303	92	2	layer	layer	NOUN
ajst-11303	92	3	159	159	NUM
ajst-11303	92	4	query	query	NOUN
ajst-11303	92	5	attention	attention	NOUN
ajst-11303	92	6	value	value	NOUN
ajst-11303	92	7	key1	key1	PROPN
ajst-11303	92	8	key2	key2	PROPN
ajst-11303	92	9	key3	key3	VERB
ajst-11303	92	10	key4	key4	PROPN
ajst-11303	92	11	value1	value1	PROPN
ajst-11303	92	12	source	source	NOUN
ajst-11303	92	13	value2	value2	NOUN
ajst-11303	92	14	value3	value3	PROPN
ajst-11303	93	1	value4	value4	X
ajst-11303	93	2	figure	figure	NOUN
ajst-11303	93	3	3	3	NUM
ajst-11303	93	4	.	.	PUNCT
ajst-11303	93	5	attention	attention	NOUN
ajst-11303	93	6	mechanism	mechanism	NOUN
ajst-11303	93	7	structure	structure	VERB
ajst-11303	93	8	the	the	DET
ajst-11303	93	9	mechanism	mechanism	NOUN
ajst-11303	93	10	of	of	ADP
ajst-11303	93	11	human	human	ADJ
ajst-11303	93	12	vision	vision	NOUN
ajst-11303	93	13	,	,	PUNCT
ajst-11303	93	14	in	in	ADP
ajst-11303	93	15	which	which	PRON
ajst-11303	93	16	humans	human	NOUN
ajst-11303	93	17	can	can	AUX
ajst-11303	93	18	quickly	quickly	ADV
ajst-11303	93	19	filter	filter	VERB
ajst-11303	93	20	out	out	ADP
ajst-11303	93	21	valuable	valuable	ADJ
ajst-11303	93	22	information	information	NOUN
ajst-11303	93	23	from	from	ADP
ajst-11303	93	24	a	a	DET
ajst-11303	93	25	large	large	ADJ
ajst-11303	93	26	amount	amount	NOUN
ajst-11303	93	27	of	of	ADP
ajst-11303	93	28	information	information	NOUN
ajst-11303	93	29	,	,	PUNCT
ajst-11303	93	30	provides	provide	VERB
ajst-11303	93	31	a	a	DET
ajst-11303	93	32	source	source	NOUN
ajst-11303	93	33	of	of	ADP
ajst-11303	93	34	ideas	idea	NOUN
ajst-11303	93	35	for	for	ADP
ajst-11303	93	36	the	the	DET
ajst-11303	93	37	attention	attention	NOUN
ajst-11303	93	38	mechanism[21	mechanism[21	PROPN
ajst-11303	93	39	]	]	PUNCT
ajst-11303	93	40	,	,	PUNCT
ajst-11303	93	41	giving	give	VERB
ajst-11303	93	42	different	different	ADJ
ajst-11303	93	43	weights	weight	NOUN
ajst-11303	93	44	to	to	ADP
ajst-11303	93	45	the	the	DET
ajst-11303	93	46	importance	importance	NOUN
ajst-11303	93	47	of	of	ADP
ajst-11303	93	48	different	different	ADJ
ajst-11303	93	49	inputs[22	inputs[22	NOUN
ajst-11303	93	50	]	]	X
ajst-11303	93	51	.	.	PUNCT
ajst-11303	94	1	filtering	filter	VERB
ajst-11303	94	2	a	a	DET
ajst-11303	94	3	small	small	ADJ
ajst-11303	94	4	amount	amount	NOUN
ajst-11303	94	5	of	of	ADP
ajst-11303	94	6	important	important	ADJ
ajst-11303	94	7	information	information	NOUN
ajst-11303	94	8	from	from	ADP
ajst-11303	94	9	a	a	DET
ajst-11303	94	10	large	large	ADJ
ajst-11303	94	11	amount	amount	NOUN
ajst-11303	94	12	of	of	ADP
ajst-11303	94	13	information	information	NOUN
ajst-11303	94	14	can	can	AUX
ajst-11303	94	15	ignore	ignore	VERB
ajst-11303	94	16	a	a	DET
ajst-11303	94	17	lot	lot	NOUN
ajst-11303	94	18	of	of	ADP
ajst-11303	94	19	irrelevant	irrelevant	ADJ
ajst-11303	94	20	information	information	NOUN
ajst-11303	94	21	.	.	PUNCT
ajst-11303	95	1	the	the	DET
ajst-11303	95	2	basic	basic	ADJ
ajst-11303	95	3	structure	structure	NOUN
ajst-11303	95	4	is	be	AUX
ajst-11303	95	5	shown	show	VERB
ajst-11303	95	6	in	in	ADP
ajst-11303	95	7	figure	figure	NOUN
ajst-11303	95	8	3	3	NUM
ajst-11303	95	9	.	.	PUNCT
ajst-11303	96	1	the	the	DET
ajst-11303	96	2	transform	transform	NOUN
ajst-11303	96	3	model	model	NOUN
ajst-11303	96	4	uses	use	VERB
ajst-11303	96	5	a	a	DET
ajst-11303	96	6	complete	complete	ADJ
ajst-11303	96	7	attention	attention	NOUN
ajst-11303	96	8	mechanism	mechanism	NOUN
ajst-11303	96	9	to	to	PART
ajst-11303	96	10	replace	replace	VERB
ajst-11303	96	11	the	the	DET
ajst-11303	96	12	traditional	traditional	ADJ
ajst-11303	96	13	structure	structure	NOUN
ajst-11303	96	14	.	.	PUNCT
ajst-11303	97	1	although	although	SCONJ
ajst-11303	97	2	it	it	PRON
ajst-11303	97	3	is	be	AUX
ajst-11303	97	4	mainly	mainly	ADV
ajst-11303	97	5	composed	compose	VERB
ajst-11303	97	6	of	of	ADP
ajst-11303	97	7	encoders	encoder	NOUN
ajst-11303	97	8	and	and	CCONJ
ajst-11303	97	9	decoders	decoder	NOUN
ajst-11303	97	10	,	,	PUNCT
ajst-11303	97	11	the	the	DET
ajst-11303	97	12	internal	internal	ADJ
ajst-11303	97	13	mechanism	mechanism	NOUN
ajst-11303	97	14	of	of	ADP
ajst-11303	97	15	each	each	DET
ajst-11303	97	16	encoder	encoder	NOUN
ajst-11303	97	17	is	be	AUX
ajst-11303	97	18	the	the	DET
ajst-11303	97	19	attention	attention	NOUN
ajst-11303	97	20	mechanism	mechanism	NOUN
ajst-11303	97	21	,	,	PUNCT
ajst-11303	97	22	and	and	CCONJ
ajst-11303	97	23	the	the	DET
ajst-11303	97	24	weight	weight	NOUN
ajst-11303	97	25	value	value	NOUN
ajst-11303	97	26	is	be	AUX
ajst-11303	97	27	not	not	PART
ajst-11303	97	28	shared	share	VERB
ajst-11303	97	29	between	between	ADP
ajst-11303	97	30	each	each	DET
ajst-11303	97	31	layer	layer	NOUN
ajst-11303	97	32	,	,	PUNCT
ajst-11303	97	33	and	and	CCONJ
ajst-11303	97	34	each	each	DET
ajst-11303	97	35	layer	layer	NOUN
ajst-11303	97	36	is	be	AUX
ajst-11303	97	37	divided	divide	VERB
ajst-11303	97	38	into	into	ADP
ajst-11303	97	39	two	two	NUM
ajst-11303	97	40	sub	sub	NOUN
ajst-11303	97	41	-	-	NOUN
ajst-11303	97	42	layers	layer	NOUN
ajst-11303	97	43	,	,	PUNCT
ajst-11303	97	44	namely	namely	ADV
ajst-11303	97	45	,	,	PUNCT
ajst-11303	97	46	the	the	DET
ajst-11303	97	47	feedforward	feedforward	ADJ
ajst-11303	97	48	neural	neural	ADJ
ajst-11303	97	49	network	network	NOUN
ajst-11303	97	50	layer	layer	NOUN
ajst-11303	97	51	and	and	CCONJ
ajst-11303	97	52	the	the	DET
ajst-11303	97	53	multi	multi	ADJ
ajst-11303	97	54	-	-	ADJ
ajst-11303	97	55	head	head	ADJ
ajst-11303	97	56	self	self	NOUN
ajst-11303	97	57	-	-	PUNCT
ajst-11303	97	58	attention	attention	NOUN
ajst-11303	97	59	layer	layer	NOUN
ajst-11303	97	60	.	.	PUNCT
ajst-11303	98	1	the	the	DET
ajst-11303	98	2	prediction	prediction	NOUN
ajst-11303	98	3	of	of	ADP
ajst-11303	98	4	cement	cement	NOUN
ajst-11303	98	5	slurry	slurry	NOUN
ajst-11303	98	6	density	density	NOUN
ajst-11303	98	7	can	can	AUX
ajst-11303	98	8	be	be	AUX
ajst-11303	98	9	regarded	regard	VERB
ajst-11303	98	10	as	as	ADP
ajst-11303	98	11	a	a	DET
ajst-11303	98	12	regression	regression	NOUN
ajst-11303	98	13	problem	problem	NOUN
ajst-11303	98	14	to	to	PART
ajst-11303	98	15	be	be	AUX
ajst-11303	98	16	solved	solve	VERB
ajst-11303	98	17	.	.	PUNCT
ajst-11303	99	1	the	the	DET
ajst-11303	99	2	attention	attention	NOUN
ajst-11303	99	3	layer	layer	NOUN
ajst-11303	99	4	is	be	AUX
ajst-11303	99	5	introduced	introduce	VERB
ajst-11303	99	6	to	to	PART
ajst-11303	99	7	further	far	ADV
ajst-11303	99	8	filter	filter	VERB
ajst-11303	99	9	the	the	DET
ajst-11303	99	10	feature	feature	NOUN
ajst-11303	99	11	vectors	vector	NOUN
ajst-11303	99	12	extracted	extract	VERB
ajst-11303	99	13	from	from	ADP
ajst-11303	99	14	the	the	DET
ajst-11303	99	15	indrnn	indrnn	NOUN
ajst-11303	99	16	layer	layer	NOUN
ajst-11303	99	17	,	,	PUNCT
ajst-11303	99	18	which	which	PRON
ajst-11303	99	19	can	can	AUX
ajst-11303	99	20	help	help	VERB
ajst-11303	99	21	the	the	DET
ajst-11303	99	22	model	model	NOUN
ajst-11303	99	23	capture	capture	VERB
ajst-11303	99	24	more	more	ADV
ajst-11303	99	25	important	important	ADJ
ajst-11303	99	26	high	high	ADJ
ajst-11303	99	27	-	-	PUNCT
ajst-11303	99	28	order	order	NOUN
ajst-11303	99	29	data	datum	NOUN
ajst-11303	99	30	features	feature	NOUN
ajst-11303	99	31	,	,	PUNCT
ajst-11303	99	32	thereby	thereby	ADV
ajst-11303	99	33	strengthening	strengthen	VERB
ajst-11303	99	34	the	the	DET
ajst-11303	99	35	connection	connection	NOUN
ajst-11303	99	36	between	between	ADP
ajst-11303	99	37	the	the	DET
ajst-11303	99	38	layers	layer	NOUN
ajst-11303	99	39	of	of	ADP
ajst-11303	99	40	data	datum	NOUN
ajst-11303	99	41	.	.	PUNCT
ajst-11303	100	1	assuming	assume	VERB
ajst-11303	100	2	that	that	SCONJ
ajst-11303	100	3	the	the	DET
ajst-11303	100	4	output	output	NOUN
ajst-11303	100	5	of	of	ADP
ajst-11303	100	6	the	the	DET
ajst-11303	100	7	indrnn	indrnn	NOUN
ajst-11303	100	8	layer	layer	NOUN
ajst-11303	100	9	is	be	AUX
ajst-11303	100	10	th	th	X
ajst-11303	100	11	,	,	PUNCT
ajst-11303	100	12	its	its	PRON
ajst-11303	100	13	attention	attention	NOUN
ajst-11303	100	14	weight	weight	NOUN
ajst-11303	100	15	can	can	AUX
ajst-11303	100	16	be	be	AUX
ajst-11303	100	17	calculated	calculate	VERB
ajst-11303	100	18	by	by	ADP
ajst-11303	100	19	the	the	DET
ajst-11303	100	20	following	follow	VERB
ajst-11303	100	21	function	function	NOUN
ajst-11303	100	22	.	.	PUNCT
ajst-11303	101	1	exp	exp	NOUN
ajst-11303	101	2	(	(	PUNCT
ajst-11303	101	3	(	(	PUNCT
ajst-11303	101	4	,	,	PUNCT
ajst-11303	101	5	)	)	PUNCT
ajst-11303	101	6	)	)	PUNCT
ajst-11303	101	7	(	(	PUNCT
ajst-11303	101	8	,	,	PUNCT
ajst-11303	101	9	)	)	PUNCT
ajst-11303	101	10	exp	exp	NOUN
ajst-11303	101	11	(	(	PUNCT
ajst-11303	101	12	(	(	PUNCT
ajst-11303	101	13	,	,	PUNCT
ajst-11303	101	14	)	)	PUNCT
ajst-11303	101	15	)	)	PUNCT
ajst-11303	101	16			PROPN
ajst-11303	101	17			X
ajst-11303	101	18	l	l	NOUN
ajst-11303	101	19	l	l	NOUN
ajst-11303	101	20	t	t	PROPN
ajst-11303	101	21	l	l	NOUN
ajst-11303	101	22	t	t	NOUN
ajst-11303	101	23	t	t	PROPN
ajst-11303	101	24	s	s	X
ajst-11303	101	25	h	h	NOUN
ajst-11303	101	26	q	q	NOUN
ajst-11303	101	27	h	h	NOUN
ajst-11303	101	28	q	q	NOUN
ajst-11303	102	1	=	=	SYM
ajst-11303	102	2	s	s	NOUN
ajst-11303	102	3	h	h	NOUN
ajst-11303	102	4	q	q	X
ajst-11303	102	5	(	(	PUNCT
ajst-11303	102	6	5	5	NUM
ajst-11303	102	7	)	)	PUNCT
ajst-11303	102	8	(	(	PUNCT
ajst-11303	102	9	,	,	PUNCT
ajst-11303	102	10	)	)	PUNCT
ajst-11303	102	11			PROPN
ajst-11303	102	12	i	i	PROPN
ajst-11303	102	13	l	l	PROPN
ajst-11303	102	14	t	t	NOUN
ajst-11303	102	15	ta	ta	X
ajst-11303	102	16	h	h	NOUN
ajst-11303	103	1	=	=	NOUN
ajst-11303	103	2	h	h	PROPN
ajst-11303	103	3	(	(	PUNCT
ajst-11303	103	4	6	6	NUM
ajst-11303	103	5	)	)	PUNCT
ajst-11303	103	6	where	where	SCONJ
ajst-11303	103	7	(	(	PUNCT
ajst-11303	103	8	,	,	PUNCT
ajst-11303	103	9	)	)	PUNCT
ajst-11303	103	10			PROPN
ajst-11303	103	11	lh	lh	PROPN
ajst-11303	103	12	q	q	PROPN
ajst-11303	103	13	is	be	AUX
ajst-11303	103	14	the	the	DET
ajst-11303	103	15	attention	attention	NOUN
ajst-11303	103	16	weight	weight	NOUN
ajst-11303	103	17	,	,	PUNCT
ajst-11303	103	18	(	(	PUNCT
ajst-11303	103	19	,	,	PUNCT
ajst-11303	103	20	)	)	PUNCT
ajst-11303	103	21	ta	ta	NOUN
ajst-11303	103	22	h	h	NOUN
ajst-11303	103	23	is	be	AUX
ajst-11303	103	24	the	the	DET
ajst-11303	103	25	output	output	NOUN
ajst-11303	103	26	of	of	ADP
ajst-11303	103	27	the	the	DET
ajst-11303	103	28	attention	attention	NOUN
ajst-11303	103	29	layer	layer	NOUN
ajst-11303	103	30	,	,	PUNCT
ajst-11303	103	31	(	(	PUNCT
ajst-11303	103	32	,	,	PUNCT
ajst-11303	103	33	)	)	PUNCT
ajst-11303	104	1	l	l	NOUN
ajst-11303	104	2	ts	ts	ADP
ajst-11303	104	3	h	h	PROPN
ajst-11303	104	4	q	q	PROPN
ajst-11303	104	5	is	be	AUX
ajst-11303	104	6	the	the	DET
ajst-11303	104	7	scoring	scoring	NOUN
ajst-11303	104	8	function	function	NOUN
ajst-11303	104	9	,	,	PUNCT
ajst-11303	104	10	q	q	PUNCT
ajst-11303	104	11	is	be	AUX
ajst-11303	104	12	the	the	DET
ajst-11303	104	13	attention	attention	NOUN
ajst-11303	104	14	matrix	matrix	NOUN
ajst-11303	104	15	.	.	PUNCT
ajst-11303	105	1	the	the	DET
ajst-11303	105	2	scoring	scoring	NOUN
ajst-11303	105	3	function	function	NOUN
ajst-11303	105	4	formula	formula	NOUN
ajst-11303	105	5	is	be	AUX
ajst-11303	105	6	shown	show	VERB
ajst-11303	105	7	in	in	ADP
ajst-11303	105	8	(	(	PUNCT
ajst-11303	105	9	7	7	NUM
ajst-11303	105	10	)	)	PUNCT
ajst-11303	105	11	.	.	PUNCT
ajst-11303	106	1	dot	dot	NOUN
ajst-11303	106	2	(	(	PUNCT
ajst-11303	106	3	,	,	PUNCT
ajst-11303	106	4	)	)	PUNCT
ajst-11303	106	5	(	(	PUNCT
ajst-11303	106	6	)	)	PUNCT
ajst-11303	106	7	l	l	NOUN
ajst-11303	106	8	l	l	NOUN
ajst-11303	106	9	t	t	NOUN
ajst-11303	106	10	t	t	X
ajst-11303	106	11	ts	ts	ADP
ajst-11303	106	12	h	h	NOUN
ajst-11303	106	13	q	q	NOUN
ajst-11303	107	1	=	=	PUNCT
ajst-11303	107	2	h	h	NOUN
ajst-11303	107	3	q	q	NOUN
ajst-11303	107	4	(	(	PUNCT
ajst-11303	107	5	7	7	NUM
ajst-11303	107	6	)	)	PUNCT
ajst-11303	107	7	3.4	3.4	NUM
ajst-11303	107	8	.	.	PUNCT
ajst-11303	108	1	output	output	NOUN
ajst-11303	108	2	layer	layer	NOUN
ajst-11303	108	3	the	the	DET
ajst-11303	108	4	output	output	NOUN
ajst-11303	108	5	layer	layer	NOUN
ajst-11303	108	6	first	first	ADV
ajst-11303	108	7	inputs	input	VERB
ajst-11303	108	8	the	the	DET
ajst-11303	108	9	feature	feature	NOUN
ajst-11303	108	10	vector	vector	NOUN
ajst-11303	108	11	extracted	extract	VERB
ajst-11303	108	12	from	from	ADP
ajst-11303	108	13	the	the	DET
ajst-11303	108	14	attention	attention	NOUN
ajst-11303	108	15	layer	layer	NOUN
ajst-11303	108	16	into	into	ADP
ajst-11303	108	17	a	a	DET
ajst-11303	108	18	fully	fully	ADV
ajst-11303	108	19	connected	connect	VERB
ajst-11303	108	20	layer	layer	NOUN
ajst-11303	108	21	,	,	PUNCT
ajst-11303	108	22	and	and	CCONJ
ajst-11303	108	23	takes	take	VERB
ajst-11303	108	24	the	the	DET
ajst-11303	108	25	output	output	NOUN
ajst-11303	108	26	of	of	ADP
ajst-11303	108	27	the	the	DET
ajst-11303	108	28	fully	fully	ADV
ajst-11303	108	29	connected	connect	VERB
ajst-11303	108	30	layer	layer	NOUN
ajst-11303	108	31	as	as	ADP
ajst-11303	108	32	the	the	DET
ajst-11303	108	33	output	output	NOUN
ajst-11303	108	34	feature	feature	NOUN
ajst-11303	108	35	,	,	PUNCT
ajst-11303	108	36	and	and	CCONJ
ajst-11303	108	37	then	then	ADV
ajst-11303	108	38	inputs	input	VERB
ajst-11303	108	39	it	it	PRON
ajst-11303	108	40	into	into	ADP
ajst-11303	108	41	the	the	DET
ajst-11303	108	42	linear	linear	ADJ
ajst-11303	108	43	layer	layer	NOUN
ajst-11303	108	44	to	to	PART
ajst-11303	108	45	output	output	VERB
ajst-11303	108	46	the	the	DET
ajst-11303	108	47	prediction	prediction	NOUN
ajst-11303	108	48	of	of	ADP
ajst-11303	108	49	cement	cement	NOUN
ajst-11303	108	50	slurry	slurry	NOUN
ajst-11303	108	51	density	density	NOUN
ajst-11303	108	52	.	.	PUNCT
ajst-11303	109	1	the	the	DET
ajst-11303	109	2	calculation	calculation	NOUN
ajst-11303	109	3	formula	formula	NOUN
ajst-11303	109	4	is	be	AUX
ajst-11303	109	5	shown	show	VERB
ajst-11303	109	6	in	in	ADP
ajst-11303	109	7	(	(	PUNCT
ajst-11303	109	8	8	8	NUM
ajst-11303	109	9	)	)	PUNCT
ajst-11303	109	10	.	.	PUNCT
ajst-11303	110	1	(	(	PUNCT
ajst-11303	110	2	)	)	PUNCT
ajst-11303	110	3			NUM
ajst-11303	110	4	linearf	linearf	PROPN
ajst-11303	110	5	a	a	DET
ajst-11303	110	6	(	(	PUNCT
ajst-11303	110	7	8)	8)	NUM
ajst-11303	110	8	among	among	ADP
ajst-11303	110	9	them	they	PRON
ajst-11303	110	10	,	,	PUNCT
ajst-11303	110	11	the	the	DET
ajst-11303	110	12	training	training	NOUN
ajst-11303	110	13	of	of	ADP
ajst-11303	110	14	the	the	DET
ajst-11303	110	15	whole	whole	ADJ
ajst-11303	110	16	model	model	NOUN
ajst-11303	110	17	uses	use	VERB
ajst-11303	110	18	adam	adam	PROPN
ajst-11303	110	19	optimizer	optimizer	NOUN
ajst-11303	110	20	to	to	PART
ajst-11303	110	21	optimize	optimize	VERB
ajst-11303	110	22	the	the	DET
ajst-11303	110	23	mse	mse	NOUN
ajst-11303	110	24	loss	loss	NOUN
ajst-11303	110	25	function	function	NOUN
ajst-11303	110	26	.	.	PUNCT
ajst-11303	111	1	4	4	X
ajst-11303	111	2	.	.	X
ajst-11303	111	3	experiment	experiment	NOUN
ajst-11303	111	4	and	and	CCONJ
ajst-11303	111	5	result	result	VERB
ajst-11303	111	6	analysis	analysis	NOUN
ajst-11303	111	7	4.1	4.1	NUM
ajst-11303	111	8	.	.	PUNCT
ajst-11303	112	1	experimental	experimental	ADJ
ajst-11303	112	2	data	datum	NOUN
ajst-11303	112	3	in	in	ADP
ajst-11303	112	4	this	this	DET
ajst-11303	112	5	paper	paper	NOUN
ajst-11303	112	6	,	,	PUNCT
ajst-11303	112	7	the	the	DET
ajst-11303	112	8	cementing	cement	VERB
ajst-11303	112	9	data	datum	NOUN
ajst-11303	112	10	from	from	ADP
ajst-11303	112	11	a	a	DET
ajst-11303	112	12	certain	certain	ADJ
ajst-11303	112	13	offshore	offshore	ADJ
ajst-11303	112	14	oil	oil	NOUN
ajst-11303	112	15	company	company	NOUN
ajst-11303	112	16	are	be	AUX
ajst-11303	112	17	used	use	VERB
ajst-11303	112	18	.	.	PUNCT
ajst-11303	113	1	the	the	DET
ajst-11303	113	2	cement	cement	NOUN
ajst-11303	113	3	slurry	slurry	NOUN
ajst-11303	113	4	density	density	NOUN
ajst-11303	113	5	data	datum	NOUN
ajst-11303	113	6	from	from	ADP
ajst-11303	113	7	february	february	PROPN
ajst-11303	113	8	2016	2016	NUM
ajst-11303	113	9	to	to	ADP
ajst-11303	113	10	august	august	PROPN
ajst-11303	113	11	2018	2018	NUM
ajst-11303	113	12	are	be	AUX
ajst-11303	113	13	mainly	mainly	ADV
ajst-11303	113	14	selected	select	VERB
ajst-11303	113	15	,	,	PUNCT
ajst-11303	113	16	including	include	VERB
ajst-11303	113	17	the	the	DET
ajst-11303	113	18	size	size	NOUN
ajst-11303	113	19	,	,	PUNCT
ajst-11303	113	20	depth	depth	NOUN
ajst-11303	113	21	,	,	PUNCT
ajst-11303	113	22	pressure	pressure	NOUN
ajst-11303	113	23	,	,	PUNCT
ajst-11303	113	24	circulation	circulation	NOUN
ajst-11303	113	25	temperature	temperature	NOUN
ajst-11303	113	26	,	,	PUNCT
ajst-11303	113	27	static	static	ADJ
ajst-11303	113	28	temperature	temperature	NOUN
ajst-11303	113	29	,	,	PUNCT
ajst-11303	113	30	temperature	temperature	NOUN
ajst-11303	113	31	gradient	gradient	NOUN
ajst-11303	113	32	,	,	PUNCT
ajst-11303	113	33	time	time	NOUN
ajst-11303	113	34	to	to	ADP
ajst-11303	113	35	the	the	DET
ajst-11303	113	36	bottom	bottom	NOUN
ajst-11303	113	37	of	of	ADP
ajst-11303	113	38	the	the	DET
ajst-11303	113	39	well	well	NOUN
ajst-11303	113	40	,	,	PUNCT
ajst-11303	113	41	thickening	thickening	NOUN
ajst-11303	113	42	time	time	NOUN
ajst-11303	113	43	,	,	PUNCT
ajst-11303	113	44	compressive	compressive	ADJ
ajst-11303	113	45	strength	strength	NOUN
ajst-11303	113	46	,	,	PUNCT
ajst-11303	113	47	water	water	NOUN
ajst-11303	113	48	loss	loss	NOUN
ajst-11303	113	49	and	and	CCONJ
ajst-11303	113	50	other	other	ADJ
ajst-11303	113	51	characteristics	characteristic	NOUN
ajst-11303	113	52	of	of	ADP
ajst-11303	113	53	the	the	DET
ajst-11303	113	54	well	well	NOUN
ajst-11303	113	55	,	,	PUNCT
ajst-11303	113	56	and	and	CCONJ
ajst-11303	113	57	the	the	DET
ajst-11303	113	58	predicted	predict	VERB
ajst-11303	113	59	label	label	NOUN
ajst-11303	113	60	is	be	AUX
ajst-11303	113	61	density	density	NOUN
ajst-11303	113	62	.	.	PUNCT
ajst-11303	114	1	the	the	DET
ajst-11303	114	2	specific	specific	ADJ
ajst-11303	114	3	data	data	NOUN
ajst-11303	114	4	description	description	NOUN
ajst-11303	114	5	is	be	AUX
ajst-11303	114	6	shown	show	VERB
ajst-11303	114	7	in	in	ADP
ajst-11303	114	8	table	table	NOUN
ajst-11303	114	9	1	1	NUM
ajst-11303	114	10	.	.	PUNCT
ajst-11303	114	11	table	table	NOUN
ajst-11303	114	12	1	1	NUM
ajst-11303	114	13	.	.	PUNCT
ajst-11303	114	14	influencing	influence	VERB
ajst-11303	114	15	factors	factor	NOUN
ajst-11303	114	16	of	of	ADP
ajst-11303	114	17	cement	cement	NOUN
ajst-11303	114	18	slurry	slurry	NOUN
ajst-11303	114	19	density	density	NOUN
ajst-11303	114	20	prediction	prediction	NOUN
ajst-11303	114	21	factor	factor	NOUN
ajst-11303	114	22	name	name	NOUN
ajst-11303	114	23	data	datum	NOUN
ajst-11303	114	24	value	value	NOUN
ajst-11303	114	25	unit	unit	NOUN
ajst-11303	114	26	casing	casing	NOUN
ajst-11303	114	27	size	size	NOUN
ajst-11303	114	28	339.725	339.725	NUM
ajst-11303	114	29	mm	mm	NOUN
ajst-11303	114	30	well	well	INTJ
ajst-11303	114	31	depth	depth	NOUN
ajst-11303	114	32	700	700	NUM
ajst-11303	114	33	m	m	NOUN
ajst-11303	114	34	bottom	bottom	ADJ
ajst-11303	114	35	hole	hole	NOUN
ajst-11303	114	36	pressure	pressure	NOUN
ajst-11303	114	37	1000	1000	NUM
ajst-11303	114	38	psi	psi	NOUN
ajst-11303	114	39	static	static	ADJ
ajst-11303	114	40	temperature	temperature	NOUN
ajst-11303	114	41	44	44	NUM
ajst-11303	114	42	℃	℃	PROPN
ajst-11303	114	43	circulation	circulation	NOUN
ajst-11303	114	44	temperature	temperature	NOUN
ajst-11303	114	45	34	34	NUM
ajst-11303	114	46	℃	℃	PROPN
ajst-11303	114	47	temperature	temperature	NOUN
ajst-11303	114	48	gradient	gradient	NOUN
ajst-11303	114	49	4.18	4.18	NUM
ajst-11303	114	50	℃	℃	PROPN
ajst-11303	114	51	time	time	NOUN
ajst-11303	114	52	to	to	PART
ajst-11303	114	53	reach	reach	VERB
ajst-11303	114	54	the	the	DET
ajst-11303	114	55	bottom	bottom	ADJ
ajst-11303	114	56	18	18	NUM
ajst-11303	114	57	min	min	NOUN
ajst-11303	114	58	thickening	thickening	NOUN
ajst-11303	114	59	time	time	NOUN
ajst-11303	114	60	503	503	NUM
ajst-11303	114	61	min	min	PROPN
ajst-11303	114	62	waterloss	waterloss	PROPN
ajst-11303	114	63	1019	1019	NUM
ajst-11303	114	64	gal	gal	ADJ
ajst-11303	114	65	/	/	SYM
ajst-11303	114	66	sk	sk	ADP
ajst-11303	114	67	compressive	compressive	ADJ
ajst-11303	114	68	strength	strength	NOUN
ajst-11303	114	69	479	479	NUM
ajst-11303	114	70	psi	psi	VERB
ajst-11303	114	71	160	160	NUM
ajst-11303	114	72	4.2	4.2	NUM
ajst-11303	114	73	.	.	PUNCT
ajst-11303	115	1	evaluating	evaluate	VERB
ajst-11303	115	2	indicator	indicator	NOUN
ajst-11303	115	3	mean	mean	VERB
ajst-11303	115	4	absolute	absolute	ADJ
ajst-11303	115	5	error	error	NOUN
ajst-11303	115	6	(	(	PUNCT
ajst-11303	115	7	mae	mae	PROPN
ajst-11303	115	8	)	)	PUNCT
ajst-11303	115	9	and	and	CCONJ
ajst-11303	115	10	root	root	NOUN
ajst-11303	115	11	mean	mean	VERB
ajst-11303	115	12	squard	squard	NOUN
ajst-11303	115	13	error	error	NOUN
ajst-11303	115	14	(	(	PUNCT
ajst-11303	115	15	rmse	rmse	PROPN
ajst-11303	115	16	)	)	PUNCT
ajst-11303	115	17	are	be	AUX
ajst-11303	115	18	the	the	DET
ajst-11303	115	19	performance	performance	NOUN
ajst-11303	115	20	evaluation	evaluation	NOUN
ajst-11303	115	21	indexes	index	NOUN
ajst-11303	115	22	of	of	ADP
ajst-11303	115	23	the	the	DET
ajst-11303	115	24	model	model	NOUN
ajst-11303	115	25	in	in	ADP
ajst-11303	115	26	this	this	DET
ajst-11303	115	27	paper	paper	NOUN
ajst-11303	115	28	.	.	PUNCT
ajst-11303	116	1	its	its	PRON
ajst-11303	116	2	specific	specific	ADJ
ajst-11303	116	3	formula	formula	NOUN
ajst-11303	116	4	definition	definition	NOUN
ajst-11303	116	5	is	be	AUX
ajst-11303	116	6	shown	show	VERB
ajst-11303	116	7	in	in	ADP
ajst-11303	116	8	9	9	NUM
ajst-11303	116	9	~	~	SYM
ajst-11303	116	10	10	10	NUM
ajst-11303	116	11	.	.	SYM
ajst-11303	116	12	2	2	NUM
ajst-11303	116	13	1	1	NUM
ajst-11303	116	14	1	1	NUM
ajst-11303	116	15	ˆ	ˆ	NOUN
ajst-11303	116	16	(	(	PUNCT
ajst-11303	116	17	)	)	PUNCT
ajst-11303	117	1			NUM
ajst-11303	117	2			NUM
ajst-11303	118	1			PROPN
ajst-11303	118	2	n	n	INTJ
ajst-11303	119	1	i	i	PRON
ajst-11303	119	2	i	i	PRON
ajst-11303	120	1	i	i	PRON
ajst-11303	120	2	rmse	rmse	VERB
ajst-11303	120	3	y	y	PROPN
ajst-11303	120	4	y	y	PROPN
ajst-11303	120	5	n	n	PROPN
ajst-11303	120	6	(	(	PUNCT
ajst-11303	120	7	9	9	NUM
ajst-11303	120	8	)	)	SYM
ajst-11303	120	9	1	1	NUM
ajst-11303	120	10	1	1	NUM
ajst-11303	120	11	ˆ	ˆ	NOUN
ajst-11303	120	12			NOUN
ajst-11303	120	13			NOUN
ajst-11303	121	1			PROPN
ajst-11303	121	2	n	n	NOUN
ajst-11303	122	1	i	i	PRON
ajst-11303	122	2	i	i	PRON
ajst-11303	123	1	i	i	PRON
ajst-11303	123	2	mae	mae	PROPN
ajst-11303	123	3	y	y	PROPN
ajst-11303	123	4	y	y	PROPN
ajst-11303	123	5	n	n	PROPN
ajst-11303	123	6	(	(	PUNCT
ajst-11303	123	7	10	10	NUM
ajst-11303	123	8	)	)	PUNCT
ajst-11303	123	9	in	in	ADP
ajst-11303	123	10	the	the	DET
ajst-11303	123	11	formula	formula	NOUN
ajst-11303	123	12	,	,	PUNCT
ajst-11303	123	13	iy	iy	PROPN
ajst-11303	123	14	represents	represent	VERB
ajst-11303	123	15	the	the	DET
ajst-11303	123	16	true	true	ADJ
ajst-11303	123	17	value	value	NOUN
ajst-11303	123	18	,	,	PUNCT
ajst-11303	123	19	ˆiy	ˆiy	NOUN
ajst-11303	123	20	represents	represent	VERB
ajst-11303	123	21	the	the	DET
ajst-11303	123	22	predicted	predict	VERB
ajst-11303	123	23	value	value	NOUN
ajst-11303	123	24	of	of	ADP
ajst-11303	123	25	the	the	DET
ajst-11303	123	26	model	model	NOUN
ajst-11303	123	27	,	,	PUNCT
ajst-11303	123	28	and	and	CCONJ
ajst-11303	123	29	n	n	CCONJ
ajst-11303	123	30	represents	represent	VERB
ajst-11303	123	31	the	the	DET
ajst-11303	123	32	number	number	NOUN
ajst-11303	123	33	of	of	ADP
ajst-11303	123	34	samples	sample	NOUN
ajst-11303	123	35	.	.	PUNCT
ajst-11303	124	1	among	among	ADP
ajst-11303	124	2	them	they	PRON
ajst-11303	124	3	,	,	PUNCT
ajst-11303	124	4	the	the	PRON
ajst-11303	124	5	higher	high	ADJ
ajst-11303	124	6	the	the	DET
ajst-11303	124	7	prediction	prediction	NOUN
ajst-11303	124	8	accuracy	accuracy	NOUN
ajst-11303	124	9	of	of	ADP
ajst-11303	124	10	the	the	DET
ajst-11303	124	11	model	model	NOUN
ajst-11303	124	12	,	,	PUNCT
ajst-11303	124	13	the	the	PRON
ajst-11303	124	14	smaller	small	ADJ
ajst-11303	124	15	the	the	DET
ajst-11303	124	16	values	value	NOUN
ajst-11303	124	17	of	of	ADP
ajst-11303	124	18	rmse	rmse	NOUN
ajst-11303	124	19	and	and	CCONJ
ajst-11303	124	20	mae	mae	PROPN
ajst-11303	124	21	.	.	PROPN
ajst-11303	124	22	4.3	4.3	NUM
ajst-11303	124	23	.	.	PUNCT
ajst-11303	125	1	evaluating	evaluate	VERB
ajst-11303	125	2	indicator	indicator	NOUN
ajst-11303	125	3	4.3.1	4.3.1	X
ajst-11303	125	4	.	.	PUNCT
ajst-11303	126	1	experiment	experiment	NOUN
ajst-11303	126	2	setting	set	VERB
ajst-11303	126	3	the	the	DET
ajst-11303	126	4	experimental	experimental	ADJ
ajst-11303	126	5	data	datum	NOUN
ajst-11303	126	6	is	be	AUX
ajst-11303	126	7	divided	divide	VERB
ajst-11303	126	8	into	into	ADP
ajst-11303	126	9	training	training	NOUN
ajst-11303	126	10	set	set	NOUN
ajst-11303	126	11	and	and	CCONJ
ajst-11303	126	12	test	test	NOUN
ajst-11303	126	13	set	set	VERB
ajst-11303	126	14	according	accord	VERB
ajst-11303	126	15	to	to	ADP
ajst-11303	126	16	the	the	DET
ajst-11303	126	17	ratio	ratio	NOUN
ajst-11303	126	18	of	of	ADP
ajst-11303	126	19	7	7	NUM
ajst-11303	126	20	:	:	SYM
ajst-11303	126	21	3	3	X
ajst-11303	126	22	.	.	X
ajst-11303	127	1	the	the	DET
ajst-11303	127	2	training	training	NOUN
ajst-11303	127	3	data	datum	NOUN
ajst-11303	127	4	of	of	ADP
ajst-11303	127	5	the	the	DET
ajst-11303	127	6	model	model	NOUN
ajst-11303	127	7	is	be	AUX
ajst-11303	127	8	the	the	DET
ajst-11303	127	9	training	training	NOUN
ajst-11303	127	10	set	set	NOUN
ajst-11303	127	11	,	,	PUNCT
ajst-11303	127	12	and	and	CCONJ
ajst-11303	127	13	the	the	DET
ajst-11303	127	14	prediction	prediction	NOUN
ajst-11303	127	15	accuracy	accuracy	NOUN
ajst-11303	127	16	after	after	SCONJ
ajst-11303	127	17	the	the	DET
ajst-11303	127	18	model	model	NOUN
ajst-11303	127	19	training	training	NOUN
ajst-11303	127	20	is	be	AUX
ajst-11303	127	21	tested	test	VERB
ajst-11303	127	22	with	with	ADP
ajst-11303	127	23	the	the	DET
ajst-11303	127	24	test	test	NOUN
ajst-11303	127	25	set	set	NOUN
ajst-11303	127	26	.	.	PUNCT
ajst-11303	128	1	the	the	DET
ajst-11303	128	2	model	model	NOUN
ajst-11303	128	3	parameters	parameter	NOUN
ajst-11303	128	4	in	in	ADP
ajst-11303	128	5	the	the	DET
ajst-11303	128	6	experiment	experiment	NOUN
ajst-11303	128	7	are	be	AUX
ajst-11303	128	8	shown	show	VERB
ajst-11303	128	9	in	in	ADP
ajst-11303	128	10	table	table	NOUN
ajst-11303	128	11	2	2	NUM
ajst-11303	128	12	.	.	PUNCT
ajst-11303	128	13	table	table	NOUN
ajst-11303	128	14	2	2	NUM
ajst-11303	128	15	.	.	PUNCT
ajst-11303	129	1	parameters	parameter	NOUN
ajst-11303	129	2	of	of	ADP
ajst-11303	129	3	each	each	DET
ajst-11303	129	4	model	model	NOUN
ajst-11303	129	5	name	name	NOUN
ajst-11303	129	6	value	value	NOUN
ajst-11303	129	7	dimensions	dimension	NOUN
ajst-11303	129	8	10	10	NUM
ajst-11303	129	9	batch_size	batch_size	VERB
ajst-11303	129	10	300	300	NUM
ajst-11303	129	11	learing	learing	NOUN
ajst-11303	129	12	rate	rate	NOUN
ajst-11303	129	13	0.001	0.001	NUM
ajst-11303	129	14	nindrnn	nindrnn	NOUN
ajst-11303	129	15	4	4	NUM
ajst-11303	129	16	epochs	epoch	NOUN
ajst-11303	129	17	200	200	NUM
ajst-11303	129	18	activation	activation	NOUN
ajst-11303	129	19	function	function	NOUN
ajst-11303	129	20	smu	smu	NOUN
ajst-11303	129	21	/	/	SYM
ajst-11303	129	22	relu	relu	NOUN
ajst-11303	129	23	in	in	ADP
ajst-11303	129	24	table	table	NOUN
ajst-11303	129	25	2	2	NUM
ajst-11303	129	26	,	,	PUNCT
ajst-11303	129	27	dimensions	dimension	NOUN
ajst-11303	129	28	represents	represent	VERB
ajst-11303	129	29	the	the	DET
ajst-11303	129	30	dimension	dimension	NOUN
ajst-11303	129	31	of	of	ADP
ajst-11303	129	32	the	the	DET
ajst-11303	129	33	data	datum	NOUN
ajst-11303	129	34	,	,	PUNCT
ajst-11303	129	35	batch	batch	VERB
ajst-11303	129	36	_	_	PRON
ajst-11303	129	37	size	size	NOUN
ajst-11303	129	38	represents	represent	VERB
ajst-11303	129	39	the	the	DET
ajst-11303	129	40	number	number	NOUN
ajst-11303	129	41	of	of	ADP
ajst-11303	129	42	data	datum	NOUN
ajst-11303	129	43	processed	process	VERB
ajst-11303	129	44	in	in	ADP
ajst-11303	129	45	batches	batch	NOUN
ajst-11303	129	46	during	during	ADP
ajst-11303	129	47	each	each	DET
ajst-11303	129	48	training	training	NOUN
ajst-11303	129	49	,	,	PUNCT
ajst-11303	129	50	learing	leare	VERB
ajst-11303	129	51	rate	rate	NOUN
ajst-11303	129	52	represents	represent	VERB
ajst-11303	129	53	the	the	DET
ajst-11303	129	54	learning	learning	NOUN
ajst-11303	129	55	rate	rate	NOUN
ajst-11303	129	56	during	during	ADP
ajst-11303	129	57	the	the	DET
ajst-11303	129	58	training	training	NOUN
ajst-11303	129	59	process	process	NOUN
ajst-11303	129	60	,	,	PUNCT
ajst-11303	129	61	nindrnn	nindrnn	NOUN
ajst-11303	129	62	represents	represent	VERB
ajst-11303	129	63	the	the	DET
ajst-11303	129	64	number	number	NOUN
ajst-11303	129	65	of	of	ADP
ajst-11303	129	66	layers	layer	NOUN
ajst-11303	129	67	of	of	ADP
ajst-11303	129	68	indrnn	indrnn	NOUN
ajst-11303	129	69	,	,	PUNCT
ajst-11303	129	70	epochs	epoch	NOUN
ajst-11303	129	71	represents	represent	VERB
ajst-11303	129	72	the	the	DET
ajst-11303	129	73	number	number	NOUN
ajst-11303	129	74	of	of	ADP
ajst-11303	129	75	iterations	iteration	NOUN
ajst-11303	129	76	,	,	PUNCT
ajst-11303	129	77	and	and	CCONJ
ajst-11303	129	78	activation	activation	NOUN
ajst-11303	129	79	function	function	NOUN
ajst-11303	129	80	represents	represent	VERB
ajst-11303	129	81	the	the	DET
ajst-11303	129	82	activation	activation	NOUN
ajst-11303	129	83	function	function	NOUN
ajst-11303	129	84	.	.	PUNCT
ajst-11303	130	1	4.3.2	4.3.2	X
ajst-11303	130	2	.	.	PUNCT
ajst-11303	131	1	experimental	experimental	ADJ
ajst-11303	131	2	analysis	analysis	NOUN
ajst-11303	131	3	firstly	firstly	ADV
ajst-11303	131	4	,	,	PUNCT
ajst-11303	131	5	the	the	DET
ajst-11303	131	6	performance	performance	NOUN
ajst-11303	131	7	of	of	ADP
ajst-11303	131	8	the	the	DET
ajst-11303	131	9	optimized	optimize	VERB
ajst-11303	131	10	indrnn	indrnn	NOUN
ajst-11303	131	11	model	model	NOUN
ajst-11303	131	12	is	be	AUX
ajst-11303	131	13	verified	verify	VERB
ajst-11303	131	14	.	.	PUNCT
ajst-11303	132	1	after	after	ADP
ajst-11303	132	2	the	the	DET
ajst-11303	132	3	experiment	experiment	NOUN
ajst-11303	132	4	of	of	ADP
ajst-11303	132	5	the	the	DET
ajst-11303	132	6	traditional	traditional	ADJ
ajst-11303	132	7	indrnn	indrnn	NOUN
ajst-11303	132	8	model	model	NOUN
ajst-11303	132	9	,	,	PUNCT
ajst-11303	132	10	the	the	DET
ajst-11303	132	11	smu	smu	NOUN
ajst-11303	132	12	is	be	AUX
ajst-11303	132	13	used	use	VERB
ajst-11303	132	14	to	to	PART
ajst-11303	132	15	replace	replace	VERB
ajst-11303	132	16	the	the	DET
ajst-11303	132	17	relu	relu	NOUN
ajst-11303	132	18	to	to	PART
ajst-11303	132	19	conduct	conduct	VERB
ajst-11303	132	20	the	the	DET
ajst-11303	132	21	experiment	experiment	NOUN
ajst-11303	132	22	again	again	ADV
ajst-11303	132	23	.	.	PUNCT
ajst-11303	133	1	the	the	DET
ajst-11303	133	2	prediction	prediction	NOUN
ajst-11303	133	3	results	result	NOUN
ajst-11303	133	4	of	of	ADP
ajst-11303	133	5	two	two	NUM
ajst-11303	133	6	different	different	ADJ
ajst-11303	133	7	activation	activation	NOUN
ajst-11303	133	8	functions	function	NOUN
ajst-11303	133	9	are	be	AUX
ajst-11303	133	10	shown	show	VERB
ajst-11303	133	11	in	in	ADP
ajst-11303	133	12	table	table	NOUN
ajst-11303	133	13	3	3	NUM
ajst-11303	133	14	.	.	PUNCT
ajst-11303	134	1	the	the	DET
ajst-11303	134	2	experimental	experimental	ADJ
ajst-11303	134	3	results	result	NOUN
ajst-11303	134	4	show	show	VERB
ajst-11303	134	5	that	that	SCONJ
ajst-11303	134	6	under	under	ADP
ajst-11303	134	7	the	the	DET
ajst-11303	134	8	same	same	ADJ
ajst-11303	134	9	training	training	NOUN
ajst-11303	134	10	times	time	NOUN
ajst-11303	134	11	,	,	PUNCT
ajst-11303	134	12	the	the	DET
ajst-11303	134	13	rmse	rmse	NOUN
ajst-11303	134	14	and	and	CCONJ
ajst-11303	134	15	mae	mae	PROPN
ajst-11303	134	16	values	value	NOUN
ajst-11303	134	17	of	of	ADP
ajst-11303	134	18	the	the	DET
ajst-11303	134	19	indrnn	indrnn	NOUN
ajst-11303	134	20	model	model	NOUN
ajst-11303	134	21	using	use	VERB
ajst-11303	134	22	the	the	DET
ajst-11303	134	23	smu	smu	NOUN
ajst-11303	134	24	activation	activation	NOUN
ajst-11303	134	25	function	function	NOUN
ajst-11303	134	26	are	be	AUX
ajst-11303	134	27	lower	low	ADJ
ajst-11303	134	28	.	.	PUNCT
ajst-11303	135	1	compared	compare	VERB
ajst-11303	135	2	with	with	ADP
ajst-11303	135	3	the	the	DET
ajst-11303	135	4	traditional	traditional	ADJ
ajst-11303	135	5	indrnn	indrnn	NOUN
ajst-11303	135	6	,	,	PUNCT
ajst-11303	135	7	its	its	PRON
ajst-11303	135	8	rmse	rmse	NOUN
ajst-11303	135	9	and	and	CCONJ
ajst-11303	135	10	mae	mae	PROPN
ajst-11303	135	11	are	be	AUX
ajst-11303	135	12	reduced	reduce	VERB
ajst-11303	135	13	by	by	ADP
ajst-11303	135	14	12	12	NUM
ajst-11303	135	15	%	%	NOUN
ajst-11303	135	16	and	and	CCONJ
ajst-11303	135	17	0.04	0.04	NUM
ajst-11303	135	18	%	%	NOUN
ajst-11303	135	19	,	,	PUNCT
ajst-11303	135	20	respectively	respectively	ADV
ajst-11303	135	21	.	.	PUNCT
ajst-11303	136	1	this	this	PRON
ajst-11303	136	2	is	be	AUX
ajst-11303	136	3	enough	enough	ADJ
ajst-11303	136	4	to	to	PART
ajst-11303	136	5	show	show	VERB
ajst-11303	136	6	that	that	SCONJ
ajst-11303	136	7	the	the	DET
ajst-11303	136	8	introduction	introduction	NOUN
ajst-11303	136	9	of	of	ADP
ajst-11303	136	10	smu	smu	NOUN
ajst-11303	136	11	activation	activation	NOUN
ajst-11303	136	12	function	function	NOUN
ajst-11303	136	13	can	can	AUX
ajst-11303	136	14	improve	improve	VERB
ajst-11303	136	15	the	the	DET
ajst-11303	136	16	network	network	NOUN
ajst-11303	136	17	performance	performance	NOUN
ajst-11303	136	18	of	of	ADP
ajst-11303	136	19	indrnn	indrnn	NOUN
ajst-11303	136	20	model	model	NOUN
ajst-11303	136	21	.	.	PUNCT
ajst-11303	136	22	table	table	NOUN
ajst-11303	137	1	3	3	NUM
ajst-11303	137	2	.	.	PUNCT
ajst-11303	137	3	comparison	comparison	NOUN
ajst-11303	137	4	of	of	ADP
ajst-11303	137	5	smu	smu	PROPN
ajst-11303	137	6	and	and	CCONJ
ajst-11303	137	7	relu	relu	NOUN
ajst-11303	137	8	results	result	NOUN
ajst-11303	137	9	model	model	PROPN
ajst-11303	137	10	name	name	PROPN
ajst-11303	137	11	rmse	rmse	PROPN
ajst-11303	137	12	mae	mae	PROPN
ajst-11303	137	13	indrnn+relu	indrnn+relu	PROPN
ajst-11303	137	14	0.36	0.36	NUM
ajst-11303	137	15	0.15	0.15	NUM
ajst-11303	137	16	indrnn+smu	indrnn+smu	NOUN
ajst-11303	137	17	0.24	0.24	NUM
ajst-11303	137	18	0.11	0.11	NUM
ajst-11303	137	19	secondly	secondly	ADV
ajst-11303	137	20	,	,	PUNCT
ajst-11303	137	21	the	the	DET
ajst-11303	137	22	feature	feature	NOUN
ajst-11303	137	23	extraction	extraction	NOUN
ajst-11303	137	24	ability	ability	NOUN
ajst-11303	137	25	of	of	ADP
ajst-11303	137	26	amindrnn	amindrnn	NOUN
ajst-11303	137	27	model	model	NOUN
ajst-11303	137	28	on	on	ADP
ajst-11303	137	29	cement	cement	NOUN
ajst-11303	137	30	slurry	slurry	NOUN
ajst-11303	137	31	data	datum	NOUN
ajst-11303	137	32	is	be	AUX
ajst-11303	137	33	verified	verify	VERB
ajst-11303	137	34	.	.	PUNCT
ajst-11303	138	1	for	for	ADP
ajst-11303	138	2	this	this	DET
ajst-11303	138	3	reason	reason	NOUN
ajst-11303	138	4	,	,	PUNCT
ajst-11303	138	5	in	in	ADP
ajst-11303	138	6	the	the	DET
ajst-11303	138	7	case	case	NOUN
ajst-11303	138	8	of	of	ADP
ajst-11303	138	9	the	the	DET
ajst-11303	138	10	same	same	ADJ
ajst-11303	138	11	features	feature	NOUN
ajst-11303	138	12	,	,	PUNCT
ajst-11303	138	13	three	three	NUM
ajst-11303	138	14	baseline	baseline	NOUN
ajst-11303	138	15	models	model	NOUN
ajst-11303	138	16	rnn	rnn	VERB
ajst-11303	138	17	,	,	PUNCT
ajst-11303	138	18	lstm	lstm	ADJ
ajst-11303	138	19	,	,	PUNCT
ajst-11303	138	20	and	and	CCONJ
ajst-11303	138	21	indrnn	indrnn	NOUN
ajst-11303	138	22	were	be	AUX
ajst-11303	138	23	used	use	VERB
ajst-11303	138	24	for	for	ADP
ajst-11303	138	25	comparative	comparative	ADJ
ajst-11303	138	26	experiments	experiment	NOUN
ajst-11303	138	27	.	.	PUNCT
ajst-11303	139	1	their	their	PRON
ajst-11303	139	2	predictive	predictive	ADJ
ajst-11303	139	3	analysis	analysis	NOUN
ajst-11303	139	4	results	result	NOUN
ajst-11303	139	5	are	be	AUX
ajst-11303	139	6	shown	show	VERB
ajst-11303	139	7	in	in	ADP
ajst-11303	139	8	table	table	NOUN
ajst-11303	139	9	4	4	NUM
ajst-11303	139	10	.	.	PUNCT
ajst-11303	140	1	the	the	DET
ajst-11303	140	2	experimental	experimental	ADJ
ajst-11303	140	3	results	result	NOUN
ajst-11303	140	4	show	show	VERB
ajst-11303	140	5	that	that	SCONJ
ajst-11303	140	6	under	under	ADP
ajst-11303	140	7	the	the	DET
ajst-11303	140	8	same	same	ADJ
ajst-11303	140	9	features	feature	NOUN
ajst-11303	140	10	and	and	CCONJ
ajst-11303	140	11	the	the	DET
ajst-11303	140	12	optimal	optimal	ADJ
ajst-11303	140	13	parameters	parameter	NOUN
ajst-11303	140	14	of	of	ADP
ajst-11303	140	15	each	each	DET
ajst-11303	140	16	model	model	NOUN
ajst-11303	140	17	,	,	PUNCT
ajst-11303	140	18	the	the	DET
ajst-11303	140	19	rmse	rmse	NOUN
ajst-11303	140	20	and	and	CCONJ
ajst-11303	140	21	mae	mae	PROPN
ajst-11303	140	22	values	value	NOUN
ajst-11303	140	23	of	of	ADP
ajst-11303	140	24	amindrnn	amindrnn	NOUN
ajst-11303	140	25	are	be	AUX
ajst-11303	140	26	the	the	DET
ajst-11303	140	27	lowest	low	ADJ
ajst-11303	140	28	,	,	PUNCT
ajst-11303	140	29	and	and	CCONJ
ajst-11303	140	30	the	the	DET
ajst-11303	140	31	prediction	prediction	NOUN
ajst-11303	140	32	ability	ability	NOUN
ajst-11303	140	33	is	be	AUX
ajst-11303	140	34	stronger	strong	ADJ
ajst-11303	140	35	than	than	ADP
ajst-11303	140	36	that	that	PRON
ajst-11303	140	37	of	of	ADP
ajst-11303	140	38	the	the	DET
ajst-11303	140	39	baseline	baseline	PROPN
ajst-11303	140	40	model	model	NOUN
ajst-11303	140	41	.	.	PUNCT
ajst-11303	141	1	table	table	NOUN
ajst-11303	141	2	4	4	NUM
ajst-11303	141	3	.	.	PUNCT
ajst-11303	141	4	comparison	comparison	NOUN
ajst-11303	141	5	of	of	ADP
ajst-11303	141	6	the	the	DET
ajst-11303	141	7	results	result	NOUN
ajst-11303	141	8	of	of	ADP
ajst-11303	141	9	each	each	DET
ajst-11303	141	10	model	model	NOUN
ajst-11303	141	11	model	model	NOUN
ajst-11303	141	12	name	name	PROPN
ajst-11303	141	13	rmse	rmse	PROPN
ajst-11303	141	14	mae	mae	PROPN
ajst-11303	141	15	rnn	rnn	VERB
ajst-11303	141	16	0.162	0.162	NUM
ajst-11303	141	17	0.123	0.123	NUM
ajst-11303	141	18	lstm	lstm	NOUN
ajst-11303	141	19	0.157	0.157	NUM
ajst-11303	141	20	0.112	0.112	NUM
ajst-11303	141	21	indrnn	indrnn	NOUN
ajst-11303	141	22	0.154	0.154	NUM
ajst-11303	141	23	0.111	0.111	NUM
ajst-11303	141	24	amindrnn	amindrnn	VERB
ajst-11303	141	25	0.138	0.138	NUM
ajst-11303	141	26	0.019	0.019	NUM
ajst-11303	141	27	from	from	ADP
ajst-11303	141	28	table	table	NOUN
ajst-11303	141	29	4	4	NUM
ajst-11303	141	30	,	,	PUNCT
ajst-11303	141	31	it	it	PRON
ajst-11303	141	32	can	can	AUX
ajst-11303	141	33	be	be	AUX
ajst-11303	141	34	seen	see	VERB
ajst-11303	141	35	that	that	SCONJ
ajst-11303	141	36	the	the	DET
ajst-11303	141	37	indrnn	indrnn	NOUN
ajst-11303	141	38	model	model	NOUN
ajst-11303	141	39	has	have	VERB
ajst-11303	141	40	lower	low	ADJ
ajst-11303	141	41	rmse	rmse	NOUN
ajst-11303	141	42	and	and	CCONJ
ajst-11303	141	43	mae	mae	PROPN
ajst-11303	141	44	values	value	NOUN
ajst-11303	141	45	than	than	ADP
ajst-11303	141	46	rnn	rnn	NOUN
ajst-11303	141	47	and	and	CCONJ
ajst-11303	141	48	lstm	lstm	NOUN
ajst-11303	141	49	,	,	PUNCT
ajst-11303	141	50	and	and	CCONJ
ajst-11303	141	51	the	the	DET
ajst-11303	141	52	effect	effect	NOUN
ajst-11303	141	53	is	be	AUX
ajst-11303	141	54	better	well	ADJ
ajst-11303	141	55	.	.	PUNCT
ajst-11303	142	1	it	it	PRON
ajst-11303	142	2	shows	show	VERB
ajst-11303	142	3	that	that	SCONJ
ajst-11303	142	4	indrnn	indrnn	NOUN
ajst-11303	142	5	can	can	AUX
ajst-11303	142	6	better	well	ADV
ajst-11303	142	7	extract	extract	VERB
ajst-11303	142	8	the	the	DET
ajst-11303	142	9	potential	potential	ADJ
ajst-11303	142	10	characteristics	characteristic	NOUN
ajst-11303	142	11	of	of	ADP
ajst-11303	142	12	cement	cement	NOUN
ajst-11303	142	13	slurry	slurry	NOUN
ajst-11303	142	14	density	density	NOUN
ajst-11303	142	15	data	datum	NOUN
ajst-11303	142	16	,	,	PUNCT
ajst-11303	142	17	and	and	CCONJ
ajst-11303	142	18	solve	solve	VERB
ajst-11303	142	19	the	the	DET
ajst-11303	142	20	problem	problem	NOUN
ajst-11303	142	21	of	of	ADP
ajst-11303	142	22	gradient	gradient	ADJ
ajst-11303	142	23	explosion	explosion	NOUN
ajst-11303	142	24	and	and	CCONJ
ajst-11303	142	25	gradient	gradient	ADJ
ajst-11303	142	26	disappearance	disappearance	NOUN
ajst-11303	142	27	of	of	ADP
ajst-11303	142	28	rnn	rnn	NOUN
ajst-11303	142	29	and	and	CCONJ
ajst-11303	142	30	lstm	lstm	PROPN
ajst-11303	142	31	,	,	PUNCT
ajst-11303	142	32	which	which	PRON
ajst-11303	142	33	proves	prove	VERB
ajst-11303	142	34	that	that	SCONJ
ajst-11303	142	35	the	the	DET
ajst-11303	142	36	model	model	NOUN
ajst-11303	142	37	has	have	VERB
ajst-11303	142	38	good	good	ADJ
ajst-11303	142	39	performance	performance	NOUN
ajst-11303	142	40	in	in	ADP
ajst-11303	142	41	the	the	DET
ajst-11303	142	42	field	field	NOUN
ajst-11303	142	43	of	of	ADP
ajst-11303	142	44	oilfield	oilfield	NOUN
ajst-11303	142	45	cementing	cement	VERB
ajst-11303	142	46	operation	operation	NOUN
ajst-11303	142	47	.	.	PUNCT
ajst-11303	143	1	finally	finally	ADV
ajst-11303	143	2	,	,	PUNCT
ajst-11303	143	3	the	the	DET
ajst-11303	143	4	rmse	rmse	ADJ
ajst-11303	143	5	value	value	NOUN
ajst-11303	143	6	of	of	ADP
ajst-11303	143	7	amindrnn	amindrnn	NOUN
ajst-11303	143	8	proposed	propose	VERB
ajst-11303	143	9	in	in	ADP
ajst-11303	143	10	this	this	DET
ajst-11303	143	11	paper	paper	NOUN
ajst-11303	143	12	is	be	AUX
ajst-11303	143	13	0.054	0.054	NUM
ajst-11303	143	14	lower	low	ADJ
ajst-11303	143	15	than	than	ADP
ajst-11303	143	16	that	that	PRON
ajst-11303	143	17	of	of	ADP
ajst-11303	143	18	indrnn	indrnn	NOUN
ajst-11303	143	19	,	,	PUNCT
ajst-11303	143	20	and	and	CCONJ
ajst-11303	143	21	the	the	DET
ajst-11303	143	22	mae	mae	PROPN
ajst-11303	143	23	value	value	NOUN
ajst-11303	143	24	is	be	AUX
ajst-11303	143	25	0.092	0.092	NUM
ajst-11303	143	26	lower	low	ADJ
ajst-11303	143	27	,	,	PUNCT
ajst-11303	143	28	which	which	PRON
ajst-11303	143	29	is	be	AUX
ajst-11303	143	30	more	more	ADV
ajst-11303	143	31	accurate	accurate	ADJ
ajst-11303	143	32	and	and	CCONJ
ajst-11303	143	33	better	well	ADJ
ajst-11303	143	34	.	.	PUNCT
ajst-11303	144	1	this	this	PRON
ajst-11303	144	2	shows	show	VERB
ajst-11303	144	3	that	that	SCONJ
ajst-11303	144	4	amindrnn	amindrnn	VERB
ajst-11303	144	5	can	can	AUX
ajst-11303	144	6	not	not	PART
ajst-11303	144	7	only	only	ADV
ajst-11303	144	8	solve	solve	VERB
ajst-11303	144	9	the	the	DET
ajst-11303	144	10	gradient	gradient	ADJ
ajst-11303	144	11	problem	problem	NOUN
ajst-11303	144	12	of	of	ADP
ajst-11303	144	13	traditional	traditional	ADJ
ajst-11303	144	14	rnn	rnn	NOUN
ajst-11303	144	15	and	and	CCONJ
ajst-11303	144	16	its	its	PRON
ajst-11303	144	17	variant	variant	ADJ
ajst-11303	144	18	lstm	lstm	NOUN
ajst-11303	144	19	,	,	PUNCT
ajst-11303	144	20	but	but	CCONJ
ajst-11303	144	21	also	also	ADV
ajst-11303	144	22	effectively	effectively	ADV
ajst-11303	144	23	extract	extract	VERB
ajst-11303	144	24	the	the	DET
ajst-11303	144	25	characteristics	characteristic	NOUN
ajst-11303	144	26	of	of	ADP
ajst-11303	144	27	cement	cement	NOUN
ajst-11303	144	28	slurry	slurry	NOUN
ajst-11303	144	29	input	input	NOUN
ajst-11303	144	30	data	datum	NOUN
ajst-11303	144	31	and	and	CCONJ
ajst-11303	144	32	161	161	NUM
ajst-11303	144	33	improve	improve	VERB
ajst-11303	144	34	the	the	DET
ajst-11303	144	35	prediction	prediction	NOUN
ajst-11303	144	36	accuracy	accuracy	NOUN
ajst-11303	144	37	of	of	ADP
ajst-11303	144	38	cement	cement	NOUN
ajst-11303	144	39	slurry	slurry	NOUN
ajst-11303	144	40	density	density	NOUN
ajst-11303	144	41	.	.	PUNCT
ajst-11303	145	1	5	5	X
ajst-11303	145	2	.	.	X
ajst-11303	145	3	summary	summary	NOUN
ajst-11303	145	4	in	in	ADP
ajst-11303	145	5	order	order	NOUN
ajst-11303	145	6	to	to	PART
ajst-11303	145	7	solve	solve	VERB
ajst-11303	145	8	the	the	DET
ajst-11303	145	9	demand	demand	NOUN
ajst-11303	145	10	of	of	ADP
ajst-11303	145	11	cement	cement	NOUN
ajst-11303	145	12	slurry	slurry	NOUN
ajst-11303	145	13	density	density	NOUN
ajst-11303	145	14	prediction	prediction	NOUN
ajst-11303	145	15	in	in	ADP
ajst-11303	145	16	cementing	cement	VERB
ajst-11303	145	17	operation	operation	NOUN
ajst-11303	145	18	,	,	PUNCT
ajst-11303	145	19	this	this	DET
ajst-11303	145	20	paper	paper	NOUN
ajst-11303	145	21	proposes	propose	VERB
ajst-11303	145	22	amindrnn	amindrnn	VERB
ajst-11303	145	23	model	model	NOUN
ajst-11303	145	24	for	for	ADP
ajst-11303	145	25	cement	cement	NOUN
ajst-11303	145	26	slurry	slurry	NOUN
ajst-11303	145	27	density	density	NOUN
ajst-11303	145	28	prediction	prediction	NOUN
ajst-11303	145	29	.	.	PUNCT
ajst-11303	146	1	the	the	DET
ajst-11303	146	2	experimental	experimental	ADJ
ajst-11303	146	3	results	result	NOUN
ajst-11303	146	4	on	on	ADP
ajst-11303	146	5	the	the	DET
ajst-11303	146	6	historical	historical	ADJ
ajst-11303	146	7	cementing	cement	VERB
ajst-11303	146	8	data	datum	NOUN
ajst-11303	146	9	of	of	ADP
ajst-11303	146	10	a	a	DET
ajst-11303	146	11	certain	certain	ADJ
ajst-11303	146	12	offshore	offshore	ADJ
ajst-11303	146	13	oil	oil	NOUN
ajst-11303	146	14	company	company	NOUN
ajst-11303	146	15	show	show	VERB
ajst-11303	146	16	that	that	SCONJ
ajst-11303	146	17	the	the	DET
ajst-11303	146	18	rmse	rmse	NOUN
ajst-11303	146	19	and	and	CCONJ
ajst-11303	146	20	mae	mae	PROPN
ajst-11303	146	21	values	value	NOUN
ajst-11303	146	22	are	be	AUX
ajst-11303	146	23	0.0014	0.0014	NUM
ajst-11303	146	24	and	and	CCONJ
ajst-11303	146	25	0.11	0.11	NUM
ajst-11303	146	26	,	,	PUNCT
ajst-11303	146	27	respectively	respectively	ADV
ajst-11303	146	28	,	,	PUNCT
ajst-11303	146	29	which	which	PRON
ajst-11303	146	30	are	be	AUX
ajst-11303	146	31	more	more	ADV
ajst-11303	146	32	competitive	competitive	ADJ
ajst-11303	146	33	than	than	ADP
ajst-11303	146	34	the	the	DET
ajst-11303	146	35	baseline	baseline	NOUN
ajst-11303	146	36	model	model	NOUN
ajst-11303	146	37	.	.	PUNCT
ajst-11303	147	1	it	it	PRON
ajst-11303	147	2	shows	show	VERB
ajst-11303	147	3	that	that	SCONJ
ajst-11303	147	4	the	the	DET
ajst-11303	147	5	model	model	NOUN
ajst-11303	147	6	can	can	AUX
ajst-11303	147	7	effectively	effectively	ADV
ajst-11303	147	8	predict	predict	VERB
ajst-11303	147	9	the	the	DET
ajst-11303	147	10	density	density	NOUN
ajst-11303	147	11	of	of	ADP
ajst-11303	147	12	cement	cement	NOUN
ajst-11303	147	13	slurry	slurry	NOUN
ajst-11303	147	14	accurately	accurately	ADV
ajst-11303	147	15	.	.	PUNCT
ajst-11303	148	1	this	this	PRON
ajst-11303	148	2	is	be	AUX
ajst-11303	148	3	of	of	ADP
ajst-11303	148	4	great	great	ADJ
ajst-11303	148	5	significance	significance	NOUN
ajst-11303	148	6	for	for	ADP
ajst-11303	148	7	reducing	reduce	VERB
ajst-11303	148	8	oilfield	oilfield	NOUN
ajst-11303	148	9	cementing	cement	VERB
ajst-11303	148	10	time	time	NOUN
ajst-11303	148	11	and	and	CCONJ
ajst-11303	148	12	labor	labor	NOUN
ajst-11303	148	13	costs	cost	NOUN
ajst-11303	148	14	.	.	PUNCT
ajst-11303	149	1	in	in	ADP
ajst-11303	149	2	the	the	DET
ajst-11303	149	3	follow	follow	VERB
ajst-11303	149	4	-	-	PUNCT
ajst-11303	149	5	up	up	ADP
ajst-11303	149	6	study	study	NOUN
ajst-11303	149	7	,	,	PUNCT
ajst-11303	149	8	we	we	PRON
ajst-11303	149	9	will	will	AUX
ajst-11303	149	10	try	try	VERB
ajst-11303	149	11	to	to	PART
ajst-11303	149	12	collect	collect	VERB
ajst-11303	149	13	more	more	ADV
ajst-11303	149	14	high	high	ADJ
ajst-11303	149	15	-	-	PUNCT
ajst-11303	149	16	quality	quality	NOUN
ajst-11303	149	17	data	datum	NOUN
ajst-11303	149	18	,	,	PUNCT
ajst-11303	149	19	and	and	CCONJ
ajst-11303	149	20	compare	compare	VERB
ajst-11303	149	21	and	and	CCONJ
ajst-11303	149	22	improve	improve	VERB
ajst-11303	149	23	the	the	DET
ajst-11303	149	24	experiment	experiment	NOUN
ajst-11303	149	25	based	base	VERB
ajst-11303	149	26	on	on	ADP
ajst-11303	149	27	the	the	DET
ajst-11303	149	28	feature	feature	NOUN
ajst-11303	149	29	difference	difference	NOUN
ajst-11303	149	30	of	of	ADP
ajst-11303	149	31	the	the	DET
ajst-11303	149	32	data	datum	NOUN
ajst-11303	149	33	,	,	PUNCT
ajst-11303	149	34	so	so	SCONJ
ajst-11303	149	35	as	as	SCONJ
ajst-11303	149	36	to	to	PART
ajst-11303	149	37	further	far	ADV
ajst-11303	149	38	improve	improve	VERB
ajst-11303	149	39	the	the	DET
ajst-11303	149	40	stability	stability	NOUN
ajst-11303	149	41	and	and	CCONJ
ajst-11303	149	42	accuracy	accuracy	NOUN
ajst-11303	149	43	of	of	ADP
ajst-11303	149	44	the	the	DET
ajst-11303	149	45	experimental	experimental	ADJ
ajst-11303	149	46	results	result	NOUN
ajst-11303	149	47	.	.	PUNCT
ajst-11303	150	1	acknowledgment	acknowledgment	NOUN
ajst-11303	150	2	research	research	NOUN
ajst-11303	150	3	on	on	ADP
ajst-11303	150	4	virtual	virtual	ADJ
ajst-11303	150	5	chemistry	chemistry	NOUN
ajst-11303	150	6	experiment	experiment	NOUN
ajst-11303	150	7	teaching	teaching	NOUN
ajst-11303	150	8	platform	platform	NOUN
ajst-11303	150	9	based	base	VERB
ajst-11303	150	10	on	on	ADP
ajst-11303	150	11	web3d	web3d	PROPN
ajst-11303	150	12	2023yb023	2023yb023	NUM
ajst-11303	150	13	.	.	PUNCT
ajst-11303	151	1	references	reference	NOUN
ajst-11303	151	2	[	[	X
ajst-11303	151	3	1	1	NUM
ajst-11303	151	4	]	]	X
ajst-11303	151	5	fan	fan	PROPN
ajst-11303	151	6	heng	heng	PROPN
ajst-11303	151	7	,	,	PUNCT
ajst-11303	151	8	liu	liu	PROPN
ajst-11303	151	9	meng	meng	PROPN
ajst-11303	151	10	,	,	PUNCT
ajst-11303	151	11	chen	chen	PROPN
ajst-11303	151	12	jia	jia	PROPN
ajst-11303	151	13	,	,	PUNCT
ajst-11303	151	14	et	et	PROPN
ajst-11303	151	15	al	al	PROPN
ajst-11303	151	16	.	.	PUNCT
ajst-11303	151	17	cementing	cement	VERB
ajst-11303	151	18	slurry	slurry	NOUN
ajst-11303	151	19	density	density	NOUN
ajst-11303	151	20	monitoring	monitoring	NOUN
ajst-11303	151	21	system	system	NOUN
ajst-11303	151	22	based	base	VERB
ajst-11303	151	23	on	on	ADP
ajst-11303	151	24	arm	arm	NOUN
ajst-11303	151	25	.	.	PUNCT
ajst-11303	152	1	modern	modern	ADJ
ajst-11303	152	2	electric	electric	ADJ
ajst-11303	152	3	technique	technique	NOUN
ajst-11303	152	4	.	.	PUNCT
ajst-11303	153	1	vol	vol	NOUN
ajst-11303	153	2	.	.	PROPN
ajst-11303	154	1	45	45	NUM
ajst-11303	154	2	(	(	PUNCT
ajst-11303	154	3	2022	2022	NUM
ajst-11303	154	4	)	)	PUNCT
ajst-11303	155	1	no	no	INTJ
ajst-11303	155	2	.	.	NOUN
ajst-11303	155	3	08	08	NUM
ajst-11303	155	4	,	,	PUNCT
ajst-11303	155	5	p.	p.	NOUN
ajst-11303	155	6	13	13	NUM
ajst-11303	155	7	-	-	SYM
ajst-11303	155	8	17	17	NUM
ajst-11303	155	9	.	.	PUNCT
ajst-11303	156	1	[	[	X
ajst-11303	156	2	2	2	NUM
ajst-11303	156	3	]	]	PUNCT
ajst-11303	156	4	yang	yang	PROPN
ajst-11303	156	5	jian	jian	PROPN
ajst-11303	156	6	.	.	PROPN
ajst-11303	156	7	development	development	NOUN
ajst-11303	156	8	status	status	NOUN
ajst-11303	156	9	and	and	CCONJ
ajst-11303	156	10	prospect	prospect	NOUN
ajst-11303	156	11	of	of	ADP
ajst-11303	156	12	offshore	offshore	ADJ
ajst-11303	156	13	oil	oil	NOUN
ajst-11303	156	14	cementing	cement	VERB
ajst-11303	156	15	technology	technology	NOUN
ajst-11303	156	16	.	.	PUNCT
ajst-11303	157	1	chemical	chemical	NOUN
ajst-11303	157	2	industry	industry	NOUN
ajst-11303	157	3	management.2020	management.2020	VERB
ajst-11303	157	4	no.11,p.120	no.11,p.120	NOUN
ajst-11303	157	5	-	-	PUNCT
ajst-11303	157	6	121	121	NUM
ajst-11303	157	7	.	.	PUNCT
ajst-11303	158	1	[	[	X
ajst-11303	158	2	3	3	X
ajst-11303	158	3	]	]	X
ajst-11303	158	4	shang	shang	PROPN
ajst-11303	158	5	fuhua	fuhua	PROPN
ajst-11303	158	6	,	,	PUNCT
ajst-11303	158	7	yu	yu	PROPN
ajst-11303	158	8	zhidong	zhidong	PROPN
ajst-11303	158	9	,	,	PUNCT
ajst-11303	158	10	cao	cao	PROPN
ajst-11303	158	11	maojun	maojun	PROPN
ajst-11303	158	12	.	.	PUNCT
ajst-11303	159	1	application	application	NOUN
ajst-11303	159	2	of	of	ADP
ajst-11303	159	3	feedforward	feedforward	ADJ
ajst-11303	159	4	neural	neural	ADJ
ajst-11303	159	5	network	network	NOUN
ajst-11303	159	6	in	in	ADP
ajst-11303	159	7	cement	cement	NOUN
ajst-11303	159	8	bond	bond	NOUN
ajst-11303	159	9	recognition	recognition	NOUN
ajst-11303	159	10	.	.	PUNCT
ajst-11303	160	1	computer	computer	NOUN
ajst-11303	160	2	technology	technology	NOUN
ajst-11303	160	3	and	and	CCONJ
ajst-11303	160	4	development	development	NOUN
ajst-11303	160	5	.	.	PUNCT
ajst-11303	161	1	vol	vol	NOUN
ajst-11303	161	2	.	.	PUNCT
ajst-11303	162	1	23	23	NUM
ajst-11303	162	2	(	(	PUNCT
ajst-11303	162	3	2013	2013	NUM
ajst-11303	162	4	)	)	PUNCT
ajst-11303	163	1	no	no	INTJ
ajst-11303	163	2	.	.	NOUN
ajst-11303	163	3	09	09	NUM
ajst-11303	163	4	,	,	PUNCT
ajst-11303	163	5	p.	p.	NOUN
ajst-11303	163	6	223	223	NUM
ajst-11303	163	7	-	-	SYM
ajst-11303	163	8	226	226	NUM
ajst-11303	163	9	.	.	PUNCT
ajst-11303	164	1	[	[	X
ajst-11303	164	2	4	4	X
ajst-11303	164	3	]	]	PUNCT
ajst-11303	164	4	he	he	PRON
ajst-11303	164	5	yingxing	yingxing	PROPN
ajst-11303	164	6	,	,	PUNCT
ajst-11303	164	7	yi	yi	PROPN
ajst-11303	164	8	hao	hao	PROPN
ajst-11303	164	9	,	,	PUNCT
ajst-11303	164	10	li	li	PROPN
ajst-11303	164	11	fei	fei	PROPN
ajst-11303	164	12	,	,	PUNCT
ajst-11303	164	13	et	et	PROPN
ajst-11303	164	14	al	al	PROPN
ajst-11303	164	15	.	.	PUNCT
ajst-11303	165	1	performance	performance	NOUN
ajst-11303	165	2	evaluation	evaluation	NOUN
ajst-11303	165	3	of	of	ADP
ajst-11303	165	4	water	water	NOUN
ajst-11303	165	5	-	-	PUNCT
ajst-11303	165	6	soluble	soluble	ADJ
ajst-11303	165	7	resin	resin	NOUN
ajst-11303	165	8	cementing	cement	VERB
ajst-11303	165	9	working	work	VERB
ajst-11303	165	10	fluid	fluid	NOUN
ajst-11303	165	11	system	system	NOUN
ajst-11303	165	12	.	.	PUNCT
ajst-11303	166	1	oilfield	oilfield	NOUN
ajst-11303	166	2	chemistry	chemistry	NOUN
ajst-11303	166	3	.	.	PUNCT
ajst-11303	167	1	vol	vol	NOUN
ajst-11303	167	2	.	.	PUNCT
ajst-11303	168	1	38	38	NUM
ajst-11303	168	2	(	(	PUNCT
ajst-11303	168	3	2021	2021	NUM
ajst-11303	168	4	)	)	PUNCT
ajst-11303	169	1	no	no	INTJ
ajst-11303	169	2	.	.	NOUN
ajst-11303	169	3	04	04	NUM
ajst-11303	169	4	,	,	PUNCT
ajst-11303	170	1	p.	p.	NOUN
ajst-11303	170	2	595	595	NUM
ajst-11303	170	3	-	-	SYM
ajst-11303	170	4	602	602	NUM
ajst-11303	170	5	.	.	PUNCT
ajst-11303	171	1	[	[	X
ajst-11303	171	2	5	5	NUM
ajst-11303	171	3	]	]	PUNCT
ajst-11303	171	4	xi	xi	X
ajst-11303	171	5	yan	yan	PROPN
ajst-11303	171	6	,	,	PUNCT
ajst-11303	171	7	li	li	PROPN
ajst-11303	171	8	fangyuan	fangyuan	PROPN
ajst-11303	171	9	,	,	PUNCT
ajst-11303	171	10	wang	wang	PROPN
ajst-11303	171	11	song	song	PROPN
ajst-11303	171	12	,	,	PUNCT
ajst-11303	171	13	et	et	PROPN
ajst-11303	171	14	al	al	PROPN
ajst-11303	171	15	.	.	PROPN
ajst-11303	171	16	study	study	NOUN
ajst-11303	171	17	on	on	ADP
ajst-11303	171	18	the	the	DET
ajst-11303	171	19	prevention	prevention	NOUN
ajst-11303	171	20	of	of	ADP
ajst-11303	171	21	cement	cement	NOUN
ajst-11303	171	22	ring	ring	NOUN
ajst-11303	171	23	micro	micro	NOUN
ajst-11303	171	24	-	-	NOUN
ajst-11303	171	25	annulus	annulus	ADJ
ajst-11303	171	26	by	by	ADP
ajst-11303	171	27	pre	pre	ADJ
ajst-11303	171	28	-	-	ADJ
ajst-11303	171	29	stressed	stressed	ADJ
ajst-11303	171	30	cementing	cement	VERB
ajst-11303	171	31	method	method	NOUN
ajst-11303	171	32	.	.	PUNCT
ajst-11303	172	1	specialty	specialty	NOUN
ajst-11303	172	2	reservoir	reservoir	PROPN
ajst-11303	172	3	.	.	PUNCT
ajst-11303	173	1	vol	vol	NOUN
ajst-11303	173	2	.	.	PROPN
ajst-11303	174	1	28	28	NUM
ajst-11303	174	2	(	(	PUNCT
ajst-11303	174	3	2021	2021	NUM
ajst-11303	174	4	)	)	PUNCT
ajst-11303	175	1	no	no	INTJ
ajst-11303	175	2	.	.	NOUN
ajst-11303	175	3	06	06	NUM
ajst-11303	175	4	,	,	PUNCT
ajst-11303	175	5	p.	p.	NOUN
ajst-11303	175	6	144	144	NUM
ajst-11303	175	7	-	-	SYM
ajst-11303	175	8	150	150	NUM
ajst-11303	175	9	.	.	PUNCT
ajst-11303	176	1	[	[	X
ajst-11303	176	2	6	6	NUM
ajst-11303	176	3	]	]	X
ajst-11303	176	4	luo	luo	PROPN
ajst-11303	176	5	jing	jing	PROPN
ajst-11303	176	6	,	,	PUNCT
ajst-11303	176	7	wang	wang	PROPN
ajst-11303	176	8	hening	hening	PROPN
ajst-11303	176	9	,	,	PUNCT
ajst-11303	176	10	hua	hua	PROPN
ajst-11303	176	11	zhiyuan	zhiyuan	PROPN
ajst-11303	176	12	,	,	PUNCT
ajst-11303	176	13	et	et	PROPN
ajst-11303	176	14	al	al	PROPN
ajst-11303	176	15	.	.	PUNCT
ajst-11303	176	16	cementing	cement	VERB
ajst-11303	176	17	technology	technology	NOUN
ajst-11303	176	18	for	for	ADP
ajst-11303	176	19	shallow	shallow	ADJ
ajst-11303	176	20	and	and	CCONJ
ajst-11303	176	21	large	large	ADJ
ajst-11303	176	22	displacement	displacement	ADJ
ajst-11303	176	23	wells	well	NOUN
ajst-11303	176	24	in	in	ADP
ajst-11303	176	25	bohai	bohai	PROPN
ajst-11303	176	26	bay	bay	PROPN
ajst-11303	176	27	.	.	PUNCT
ajst-11303	177	1	henan	henan	PROPN
ajst-11303	177	2	science	science	PROPN
ajst-11303	177	3	and	and	CCONJ
ajst-11303	177	4	technology	technology	NOUN
ajst-11303	177	5	.	.	PUNCT
ajst-11303	178	1	vol	vol	NOUN
ajst-11303	178	2	.	.	PROPN
ajst-11303	179	1	40	40	NUM
ajst-11303	179	2	(	(	PUNCT
ajst-11303	179	3	2021	2021	NUM
ajst-11303	179	4	)	)	PUNCT
ajst-11303	180	1	no	no	INTJ
ajst-11303	180	2	.	.	NOUN
ajst-11303	180	3	30	30	NUM
ajst-11303	180	4	,	,	PUNCT
ajst-11303	180	5	p.	p.	NOUN
ajst-11303	180	6	68	68	NUM
ajst-11303	180	7	-	-	SYM
ajst-11303	180	8	71	71	NUM
ajst-11303	180	9	.	.	PUNCT
ajst-11303	181	1	[	[	X
ajst-11303	181	2	7	7	X
ajst-11303	181	3	]	]	X
ajst-11303	181	4	guan	guan	PROPN
ajst-11303	181	5	rongliang	rongliang	PROPN
ajst-11303	181	6	.	.	PUNCT
ajst-11303	182	1	cementing	cement	VERB
ajst-11303	182	2	quality	quality	NOUN
ajst-11303	182	3	prediction	prediction	NOUN
ajst-11303	182	4	based	base	VERB
ajst-11303	182	5	on	on	ADP
ajst-11303	182	6	least	least	ADJ
ajst-11303	182	7	squares	square	NOUN
ajst-11303	182	8	support	support	NOUN
ajst-11303	182	9	vector	vector	NOUN
ajst-11303	182	10	machine	machine	NOUN
ajst-11303	182	11	.	.	PUNCT
ajst-11303	183	1	xinjiang	xinjiang	PROPN
ajst-11303	183	2	oil	oil	PROPN
ajst-11303	183	3	and	and	CCONJ
ajst-11303	183	4	gas	gas	NOUN
ajst-11303	183	5	.	.	PUNCT
ajst-11303	184	1	vol	vol	NOUN
ajst-11303	184	2	.	.	PUNCT
ajst-11303	185	1	14	14	NUM
ajst-11303	185	2	(	(	PUNCT
ajst-11303	185	3	2018	2018	NUM
ajst-11303	185	4	)	)	PUNCT
ajst-11303	186	1	no	no	INTJ
ajst-11303	186	2	.	.	NOUN
ajst-11303	186	3	04	04	NUM
ajst-11303	186	4	,	,	PUNCT
ajst-11303	186	5	p.	p.	NOUN
ajst-11303	186	6	43	43	NUM
ajst-11303	186	7	-	-	SYM
ajst-11303	186	8	46	46	NUM
ajst-11303	186	9	+	+	NOUN
ajst-11303	186	10	3	3	NUM
ajst-11303	186	11	.	.	PUNCT
ajst-11303	187	1	[	[	X
ajst-11303	187	2	8	8	NUM
ajst-11303	187	3	]	]	X
ajst-11303	187	4	kong	kong	PROPN
ajst-11303	187	5	chao	chao	PROPN
ajst-11303	187	6	:	:	PUNCT
ajst-11303	187	7	cementing	cement	VERB
ajst-11303	187	8	quality	quality	NOUN
ajst-11303	187	9	prediction	prediction	NOUN
ajst-11303	187	10	and	and	CCONJ
ajst-11303	187	11	safety	safety	NOUN
ajst-11303	187	12	evaluation	evaluation	NOUN
ajst-11303	187	13	based	base	VERB
ajst-11303	187	14	on	on	ADP
ajst-11303	187	15	gray	gray	ADJ
ajst-11303	187	16	fuzzy	fuzzy	ADJ
ajst-11303	187	17	neural	neural	ADJ
ajst-11303	187	18	network(master	network(master	PROPN
ajst-11303	187	19	,	,	PUNCT
ajst-11303	187	20	china	china	PROPN
ajst-11303	187	21	university	university	PROPN
ajst-11303	187	22	of	of	ADP
ajst-11303	187	23	petroleum	petroleum	NOUN
ajst-11303	187	24	(	(	PUNCT
ajst-11303	187	25	east	east	PROPN
ajst-11303	187	26	china	china	PROPN
ajst-11303	187	27	)	)	PUNCT
ajst-11303	187	28	,	,	PUNCT
ajst-11303	187	29	china	china	PROPN
ajst-11303	187	30	2017).p.12	2017).p.12	PROPN
ajst-11303	187	31	-	-	SYM
ajst-11303	187	32	17	17	NUM
ajst-11303	187	33	.	.	PUNCT
ajst-11303	188	1	[	[	X
ajst-11303	188	2	9	9	NUM
ajst-11303	188	3	]	]	X
ajst-11303	188	4	tang	tang	X
ajst-11303	188	5	mingyue	mingyue	PROPN
ajst-11303	188	6	.	.	PUNCT
ajst-11303	189	1	density	density	NOUN
ajst-11303	189	2	prediction	prediction	NOUN
ajst-11303	189	3	of	of	ADP
ajst-11303	189	4	oil	oil	NOUN
ajst-11303	189	5	-	-	PUNCT
ajst-11303	189	6	based	base	VERB
ajst-11303	189	7	drilling	drilling	NOUN
ajst-11303	189	8	fluids	fluid	NOUN
ajst-11303	189	9	at	at	ADP
ajst-11303	189	10	high	high	ADJ
ajst-11303	189	11	temperatures	temperature	NOUN
ajst-11303	189	12	and	and	CCONJ
ajst-11303	189	13	pressures	pressure	NOUN
ajst-11303	189	14	based	base	VERB
ajst-11303	189	15	on	on	ADP
ajst-11303	189	16	adaptive	adaptive	ADJ
ajst-11303	189	17	limit	limit	NOUN
ajst-11303	189	18	learning	learn	VERB
ajst-11303	189	19	machine	machine	NOUN
ajst-11303	189	20	modeling	modeling	NOUN
ajst-11303	189	21	.	.	PUNCT
ajst-11303	190	1	xinjiang	xinjiang	PROPN
ajst-11303	190	2	oil	oil	PROPN
ajst-11303	190	3	and	and	CCONJ
ajst-11303	190	4	gas	gas	NOUN
ajst-11303	190	5	.	.	PUNCT
ajst-11303	191	1	vol	vol	NOUN
ajst-11303	191	2	.	.	PROPN
ajst-11303	191	3	15	15	NUM
ajst-11303	191	4	(	(	PUNCT
ajst-11303	191	5	2019	2019	NUM
ajst-11303	191	6	)	)	PUNCT
ajst-11303	192	1	no	no	INTJ
ajst-11303	192	2	.	.	NOUN
ajst-11303	192	3	02	02	NUM
ajst-11303	192	4	,	,	PUNCT
ajst-11303	192	5	p.	p.	NOUN
ajst-11303	192	6	40	40	NUM
ajst-11303	192	7	-	-	SYM
ajst-11303	192	8	43	43	NUM
ajst-11303	192	9	+	+	NOUN
ajst-11303	192	10	3	3	NUM
ajst-11303	192	11	.	.	PUNCT
ajst-11303	193	1	[	[	X
ajst-11303	193	2	10	10	NUM
ajst-11303	193	3	]	]	X
ajst-11303	193	4	du	du	X
ajst-11303	193	5	dongnan	dongnan	PROPN
ajst-11303	193	6	,	,	PUNCT
ajst-11303	193	7	zheng	zheng	PROPN
ajst-11303	193	8	shuangjin	shuangjin	PROPN
ajst-11303	193	9	,	,	PUNCT
ajst-11303	193	10	he	he	PRON
ajst-11303	193	11	yingzhuang	yingzhuang	PROPN
ajst-11303	193	12	,	,	PUNCT
ajst-11303	193	13	et	et	PROPN
ajst-11303	193	14	al	al	PROPN
ajst-11303	193	15	.	.	PUNCT
ajst-11303	194	1	cementing	cement	VERB
ajst-11303	194	2	quality	quality	NOUN
ajst-11303	194	3	prediction	prediction	NOUN
ajst-11303	194	4	method	method	NOUN
ajst-11303	194	5	based	base	VERB
ajst-11303	194	6	on	on	ADP
ajst-11303	194	7	lm	lm	INTJ
ajst-11303	194	8	optimization	optimization	NOUN
ajst-11303	194	9	neural	neural	ADJ
ajst-11303	194	10	network	network	NOUN
ajst-11303	194	11	:	:	PUNCT
ajst-11303	194	12	taking	take	VERB
ajst-11303	194	13	x	x	SYM
ajst-11303	194	14	block	block	NOUN
ajst-11303	194	15	of	of	ADP
ajst-11303	194	16	shunbei	shunbei	NOUN
ajst-11303	194	17	oilfield	oilfield	NOUN
ajst-11303	194	18	as	as	ADP
ajst-11303	194	19	an	an	DET
ajst-11303	194	20	example	example	NOUN
ajst-11303	194	21	.	.	PUNCT
ajst-11303	195	1	petroleum	petroleum	NOUN
ajst-11303	195	2	geology	geology	NOUN
ajst-11303	195	3	and	and	CCONJ
ajst-11303	195	4	engineering	engineering	NOUN
ajst-11303	195	5	.	.	PUNCT
ajst-11303	196	1	vol	vol	NOUN
ajst-11303	196	2	.	.	PROPN
ajst-11303	196	3	35	35	NUM
ajst-11303	196	4	(	(	PUNCT
ajst-11303	196	5	2021	2021	NUM
ajst-11303	196	6	)	)	PUNCT
ajst-11303	197	1	no	no	INTJ
ajst-11303	197	2	.	.	NOUN
ajst-11303	197	3	03	03	NUM
ajst-11303	197	4	,	,	PUNCT
ajst-11303	197	5	p.	p.	NOUN
ajst-11303	197	6	123	123	NUM
ajst-11303	197	7	-	-	SYM
ajst-11303	197	8	126	126	NUM
ajst-11303	197	9	.	.	PUNCT
ajst-11303	198	1	[	[	X
ajst-11303	198	2	11	11	NUM
ajst-11303	198	3	]	]	PUNCT
ajst-11303	198	4	lv	lv	PROPN
ajst-11303	198	5	heyu	heyu	NOUN
ajst-11303	198	6	.	.	PUNCT
ajst-11303	199	1	application	application	NOUN
ajst-11303	199	2	of	of	ADP
ajst-11303	199	3	neural	neural	ADJ
ajst-11303	199	4	network	network	NOUN
ajst-11303	199	5	in	in	ADP
ajst-11303	199	6	cementing	cement	VERB
ajst-11303	199	7	quality	quality	NOUN
ajst-11303	199	8	prediction	prediction	NOUN
ajst-11303	199	9	.	.	PUNCT
ajst-11303	200	1	oil	oil	NOUN
ajst-11303	200	2	drilling	drilling	NOUN
ajst-11303	200	3	technology	technology	NOUN
ajst-11303	200	4	.	.	PUNCT
ajst-11303	201	1	2002	2002	NUM
ajst-11303	202	1	no	no	INTJ
ajst-11303	202	2	.	.	NOUN
ajst-11303	202	3	03	03	NUM
ajst-11303	202	4	,	,	PUNCT
ajst-11303	202	5	p.	p.	NOUN
ajst-11303	202	6	24	24	NUM
ajst-11303	202	7	-	-	SYM
ajst-11303	202	8	26	26	NUM
ajst-11303	202	9	.	.	PUNCT
ajst-11303	203	1	[	[	X
ajst-11303	203	2	12	12	NUM
ajst-11303	203	3	]	]	X
ajst-11303	203	4	deng	deng	PROPN
ajst-11303	203	5	yaping	yaping	PROPN
ajst-11303	203	6	,	,	PUNCT
ajst-11303	203	7	duan	duan	PROPN
ajst-11303	203	8	jiandong	jiandong	PROPN
ajst-11303	203	9	,	,	PUNCT
ajst-11303	203	10	jia	jia	PROPN
ajst-11303	203	11	hao	hao	PROPN
ajst-11303	203	12	,	,	PUNCT
ajst-11303	203	13	et	et	PROPN
ajst-11303	203	14	al	al	PROPN
ajst-11303	203	15	.	.	PUNCT
ajst-11303	203	16	optimization	optimization	NOUN
ajst-11303	203	17	of	of	ADP
ajst-11303	203	18	independent	independent	ADJ
ajst-11303	203	19	recurrent	recurrent	ADJ
ajst-11303	203	20	neural	neural	ADJ
ajst-11303	203	21	network	network	NOUN
ajst-11303	203	22	deep	deep	ADJ
ajst-11303	203	23	learning	learning	NOUN
ajst-11303	203	24	for	for	ADP
ajst-11303	203	25	ultrashort	ultrashort	NOUN
ajst-11303	203	26	term	term	NOUN
ajst-11303	203	27	wind	wind	NOUN
ajst-11303	203	28	power	power	NOUN
ajst-11303	203	29	prediction	prediction	NOUN
ajst-11303	203	30	based	base	VERB
ajst-11303	203	31	on	on	ADP
ajst-11303	203	32	cuckoo	cuckoo	NOUN
ajst-11303	203	33	algorithm	algorithm	NOUN
ajst-11303	203	34	.	.	PUNCT
ajst-11303	204	1	power	power	NOUN
ajst-11303	204	2	grids	grid	NOUN
ajst-11303	204	3	and	and	CCONJ
ajst-11303	204	4	clean	clean	ADJ
ajst-11303	204	5	energy	energy	NOUN
ajst-11303	204	6	.	.	PUNCT
ajst-11303	205	1	vol	vol	NOUN
ajst-11303	205	2	.	.	PUNCT
ajst-11303	206	1	37	37	NUM
ajst-11303	206	2	(	(	PUNCT
ajst-11303	206	3	2021	2021	NUM
ajst-11303	206	4	)	)	PUNCT
ajst-11303	207	1	no	no	INTJ
ajst-11303	207	2	.	.	NOUN
ajst-11303	207	3	09	09	NUM
ajst-11303	207	4	,	,	PUNCT
ajst-11303	207	5	p.	p.	NOUN
ajst-11303	207	6	18	18	NUM
ajst-11303	207	7	-	-	SYM
ajst-11303	207	8	26	26	NUM
ajst-11303	207	9	.	.	PUNCT
ajst-11303	208	1	[	[	X
ajst-11303	208	2	13	13	NUM
ajst-11303	208	3	]	]	X
ajst-11303	208	4	zhao	zhao	PROPN
ajst-11303	208	5	beidi	beidi	PROPN
ajst-11303	208	6	,	,	PUNCT
ajst-11303	208	7	li	li	PROPN
ajst-11303	208	8	,	,	PUNCT
ajst-11303	208	9	shuai	shuai	PROPN
ajst-11303	208	10	,	,	PUNCT
ajst-11303	208	11	gao	gao	PROPN
ajst-11303	208	12	,	,	PUNCT
ajst-11303	208	13	yanbo	yanbo	NOUN
ajst-11303	208	14	,	,	PUNCT
ajst-11303	208	15	et	et	PROPN
ajst-11303	208	16	al	al	PROPN
ajst-11303	208	17	.	.	PUNCT
ajst-11303	209	1	a	a	DET
ajst-11303	209	2	framework	framework	NOUN
ajst-11303	209	3	of	of	ADP
ajst-11303	209	4	combining	combine	VERB
ajst-11303	209	5	short	short	ADJ
ajst-11303	209	6	-	-	PUNCT
ajst-11303	209	7	term	term	NOUN
ajst-11303	209	8	spatial	spatial	ADJ
ajst-11303	209	9	/	/	SYM
ajst-11303	209	10	frequency	frequency	NOUN
ajst-11303	209	11	feature	feature	NOUN
ajst-11303	209	12	extraction	extraction	NOUN
ajst-11303	209	13	and	and	CCONJ
ajst-11303	209	14	long	long	ADJ
ajst-11303	209	15	-	-	PUNCT
ajst-11303	209	16	term	term	NOUN
ajst-11303	209	17	indrnn	indrnn	NOUN
ajst-11303	209	18	for	for	ADP
ajst-11303	209	19	activity	activity	NOUN
ajst-11303	209	20	recognition	recognition	NOUN
ajst-11303	209	21	.	.	PUNCT
ajst-11303	210	1	sensors	sensor	NOUN
ajst-11303	210	2	(	(	PUNCT
ajst-11303	210	3	basel	basel	PROPN
ajst-11303	210	4	,	,	PUNCT
ajst-11303	210	5	switzerland	switzerland	PROPN
ajst-11303	210	6	)	)	PUNCT
ajst-11303	210	7	.	.	PUNCT
ajst-11303	211	1	vol	vol	NOUN
ajst-11303	211	2	.	.	PROPN
ajst-11303	211	3	20	20	NUM
ajst-11303	211	4	(	(	PUNCT
ajst-11303	211	5	2020	2020	NUM
ajst-11303	211	6	)	)	PUNCT
ajst-11303	211	7	no	no	INTJ
ajst-11303	211	8	.	.	NOUN
ajst-11303	211	9	23	23	NUM
ajst-11303	211	10	,	,	PUNCT
ajst-11303	211	11	p.	p.	NOUN
ajst-11303	211	12	6984	6984	NUM
ajst-11303	211	13	.	.	PUNCT
ajst-11303	212	1	[	[	X
ajst-11303	212	2	14	14	NUM
ajst-11303	212	3	]	]	X
ajst-11303	212	4	li	li	PROPN
ajst-11303	212	5	jia	jia	PROPN
ajst-11303	212	6	,	,	PUNCT
ajst-11303	212	7	huang	huang	PROPN
ajst-11303	212	8	zhihao	zhihao	PROPN
ajst-11303	212	9	,	,	PUNCT
ajst-11303	212	10	wang	wang	PROPN
ajst-11303	212	11	jiahui	jiahui	PROPN
ajst-11303	212	12	.	.	PUNCT
ajst-11303	213	1	gdp	gdp	NOUN
ajst-11303	213	2	forecasting	forecasting	NOUN
ajst-11303	213	3	based	base	VERB
ajst-11303	213	4	on	on	ADP
ajst-11303	213	5	independent	independent	ADJ
ajst-11303	213	6	recurrent	recurrent	ADJ
ajst-11303	213	7	neural	neural	ADJ
ajst-11303	213	8	network	network	NOUN
ajst-11303	213	9	approach	approach	NOUN
ajst-11303	213	10	.	.	PUNCT
ajst-11303	214	1	statistics	statistic	NOUN
ajst-11303	214	2	and	and	CCONJ
ajst-11303	214	3	decision	decision	NOUN
ajst-11303	214	4	-	-	PUNCT
ajst-11303	214	5	making	making	NOUN
ajst-11303	214	6	.	.	PUNCT
ajst-11303	215	1	vol	vol	NOUN
ajst-11303	215	2	.	.	PROPN
ajst-11303	216	1	36	36	NUM
ajst-11303	216	2	(	(	PUNCT
ajst-11303	216	3	2020	2020	NUM
ajst-11303	216	4	)	)	PUNCT
ajst-11303	217	1	no	no	INTJ
ajst-11303	217	2	.	.	NOUN
ajst-11303	218	1	14	14	NUM
ajst-11303	218	2	,	,	PUNCT
ajst-11303	218	3	p.	p.	NOUN
ajst-11303	218	4	24	24	NUM
ajst-11303	218	5	-	-	SYM
ajst-11303	218	6	28	28	NUM
ajst-11303	218	7	.	.	PUNCT
ajst-11303	219	1	[	[	X
ajst-11303	219	2	15	15	NUM
ajst-11303	219	3	]	]	X
ajst-11303	219	4	wu	wu	PROPN
ajst-11303	219	5	zhangyu	zhangyu	PROPN
ajst-11303	219	6	,	,	PUNCT
ajst-11303	219	7	zhu	zhu	PROPN
ajst-11303	219	8	chengjie	chengjie	PROPN
ajst-11303	219	9	,	,	PUNCT
ajst-11303	219	10	wang	wang	PROPN
ajst-11303	219	11	mingyan	mingyan	PROPN
ajst-11303	219	12	.	.	PUNCT
ajst-11303	220	1	rnn	rnn	PROPN
ajst-11303	220	2	-	-	PUNCT
ajst-11303	220	3	based	base	VERB
ajst-11303	220	4	lithium	lithium	NOUN
ajst-11303	220	5	battery	battery	NOUN
ajst-11303	220	6	health	health	NOUN
ajst-11303	220	7	prediction	prediction	NOUN
ajst-11303	220	8	.	.	PUNCT
ajst-11303	221	1	green	green	ADJ
ajst-11303	221	2	technology	technology	PROPN
ajst-11303	221	3	.	.	PUNCT
ajst-11303	222	1	vol	vol	NOUN
ajst-11303	222	2	.	.	PUNCT
ajst-11303	223	1	23	23	NUM
ajst-11303	223	2	(	(	PUNCT
ajst-11303	223	3	2021	2021	NUM
ajst-11303	223	4	)	)	PUNCT
ajst-11303	224	1	no	no	INTJ
ajst-11303	224	2	.	.	NOUN
ajst-11303	224	3	18	18	NUM
ajst-11303	224	4	,	,	PUNCT
ajst-11303	224	5	p.	p.	NOUN
ajst-11303	224	6	201	201	NUM
ajst-11303	224	7	-	-	SYM
ajst-11303	224	8	203	203	NUM
ajst-11303	224	9	.	.	PUNCT
ajst-11303	225	1	[	[	X
ajst-11303	225	2	16	16	NUM
ajst-11303	225	3	]	]	X
ajst-11303	225	4	wu	wu	PROPN
ajst-11303	225	5	lifen	lifen	PROPN
ajst-11303	225	6	,	,	PUNCT
ajst-11303	225	7	yan	yan	PROPN
ajst-11303	225	8	xueyong	xueyong	PROPN
ajst-11303	225	9	,	,	PUNCT
ajst-11303	225	10	zhao	zhao	PROPN
ajst-11303	225	11	ji	ji	PROPN
ajst-11303	225	12	.	.	PROPN
ajst-11303	225	13	research	research	PROPN
ajst-11303	225	14	on	on	ADP
ajst-11303	225	15	machine	machine	NOUN
ajst-11303	225	16	poetry	poetry	NOUN
ajst-11303	225	17	composition	composition	NOUN
ajst-11303	225	18	based	base	VERB
ajst-11303	225	19	on	on	ADP
ajst-11303	225	20	rnn	rnn	NOUN
ajst-11303	225	21	models	model	NOUN
ajst-11303	225	22	and	and	CCONJ
ajst-11303	225	23	lstm	lstm	NOUN
ajst-11303	225	24	models	model	NOUN
ajst-11303	225	25	.	.	PUNCT
ajst-11303	226	1	science	science	NOUN
ajst-11303	226	2	technology	technology	NOUN
ajst-11303	226	3	innovation	innovation	NOUN
ajst-11303	226	4	and	and	CCONJ
ajst-11303	226	5	application	application	NOUN
ajst-11303	226	6	.	.	PUNCT
ajst-11303	227	1	vol	vol	NOUN
ajst-11303	227	2	.	.	PROPN
ajst-11303	227	3	11	11	NUM
ajst-11303	227	4	(	(	PUNCT
ajst-11303	227	5	2021	2021	NUM
ajst-11303	227	6	)	)	PUNCT
ajst-11303	228	1	no	no	INTJ
ajst-11303	228	2	.	.	NOUN
ajst-11303	228	3	27	27	NUM
ajst-11303	228	4	,	,	PUNCT
ajst-11303	228	5	p.	p.	NOUN
ajst-11303	228	6	48	48	NUM
ajst-11303	228	7	-	-	SYM
ajst-11303	228	8	50	50	NUM
ajst-11303	228	9	.	.	PUNCT
ajst-11303	229	1	[	[	X
ajst-11303	229	2	17	17	NUM
ajst-11303	229	3	]	]	X
ajst-11303	229	4	tong	tong	PROPN
ajst-11303	229	5	weiguo	weiguo	PROPN
ajst-11303	229	6	,	,	PUNCT
ajst-11303	229	7	zeng	zeng	PROPN
ajst-11303	229	8	shichao	shichao	NOUN
ajst-11303	229	9	,	,	PUNCT
ajst-11303	229	10	li	li	PROPN
ajst-11303	229	11	zhixiang	zhixiang	PROPN
ajst-11303	229	12	,	,	PUNCT
ajst-11303	229	13	et	et	PROPN
ajst-11303	229	14	al	al	PROPN
ajst-11303	229	15	.	.	PUNCT
ajst-11303	229	16	lstm	lstm	PROPN
ajst-11303	229	17	-	-	PUNCT
ajst-11303	229	18	based	base	VERB
ajst-11303	229	19	liquid	liquid	NOUN
ajst-11303	229	20	-	-	PUNCT
ajst-11303	229	21	phase	phase	NOUN
ajst-11303	229	22	flow	flow	NOUN
ajst-11303	229	23	measurement	measurement	NOUN
ajst-11303	229	24	for	for	ADP
ajst-11303	229	25	gas	gas	NOUN
ajst-11303	229	26	-	-	PUNCT
ajst-11303	229	27	liquid	liquid	ADJ
ajst-11303	229	28	two	two	NUM
ajst-11303	229	29	-	-	PUNCT
ajst-11303	229	30	phase	phase	NOUN
ajst-11303	229	31	flow	flow	NOUN
ajst-11303	229	32	.	.	PUNCT
ajst-11303	230	1	instrumentation	instrumentation	NOUN
ajst-11303	230	2	technology	technology	NOUN
ajst-11303	230	3	and	and	CCONJ
ajst-11303	230	4	sensors	sensor	NOUN
ajst-11303	230	5	.	.	PUNCT
ajst-11303	231	1	2021	2021	NUM
ajst-11303	231	2	no	no	NOUN
ajst-11303	231	3	.	.	NOUN
ajst-11303	231	4	11	11	NUM
ajst-11303	231	5	,	,	PUNCT
ajst-11303	231	6	p.	p.	NOUN
ajst-11303	231	7	9498	9498	NUM
ajst-11303	231	8	.	.	PUNCT
ajst-11303	232	1	[	[	X
ajst-11303	232	2	18	18	NUM
ajst-11303	232	3	]	]	X
ajst-11303	232	4	li	li	PROPN
ajst-11303	232	5	shuai	shuai	PROPN
ajst-11303	232	6	,	,	PUNCT
ajst-11303	232	7	li	li	PROPN
ajst-11303	232	8	wanqing	wanqe	VERB
ajst-11303	232	9	,	,	PUNCT
ajst-11303	232	10	cook	cook	PROPN
ajst-11303	232	11	chris	chris	PROPN
ajst-11303	232	12	,	,	PUNCT
ajst-11303	232	13	et	et	PROPN
ajst-11303	232	14	al	al	PROPN
ajst-11303	232	15	.	.	PUNCT
ajst-11303	232	16	independently	independently	ADV
ajst-11303	232	17	recurrent	recurrent	ADJ
ajst-11303	232	18	neural	neural	ADJ
ajst-11303	232	19	network	network	NOUN
ajst-11303	232	20	(	(	PUNCT
ajst-11303	232	21	indrnn	indrnn	NOUN
ajst-11303	232	22	):	):	PUNCT
ajst-11303	232	23	building	build	VERB
ajst-11303	232	24	a	a	PRON
ajst-11303	232	25	longer	long	ADJ
ajst-11303	232	26	and	and	CCONJ
ajst-11303	232	27	deeper	deep	ADJ
ajst-11303	232	28	rnn	rnn	NOUN
ajst-11303	232	29	.	.	PUNCT
ajst-11303	232	30	2018	2018	NUM
ajst-11303	232	31	ieee	ieee	NOUN
ajst-11303	232	32	/	/	SYM
ajst-11303	232	33	cvf	cvf	NOUN
ajst-11303	232	34	conference	conference	NOUN
ajst-11303	232	35	on	on	ADP
ajst-11303	232	36	computer	computer	NOUN
ajst-11303	232	37	vision	vision	NOUN
ajst-11303	232	38	and	and	CCONJ
ajst-11303	232	39	pattern	pattern	NOUN
ajst-11303	232	40	recognition	recognition	NOUN
ajst-11303	232	41	(	(	PUNCT
ajst-11303	232	42	cvpr).p	cvpr).p	NOUN
ajst-11303	232	43	.	.	NOUN
ajst-11303	232	44	5457	5457	NUM
ajst-11303	232	45	-	-	SYM
ajst-11303	232	46	5466	5466	NUM
ajst-11303	232	47	.	.	PUNCT
ajst-11303	233	1	[	[	X
ajst-11303	233	2	19	19	NUM
ajst-11303	233	3	]	]	X
ajst-11303	233	4	d	d	X
ajst-11303	233	5	stursa	stursa	NOUN
ajst-11303	233	6	,	,	PUNCT
ajst-11303	233	7	p	p	PROPN
ajst-11303	233	8	dolezel	dolezel	PROPN
ajst-11303	233	9	.	.	PUNCT
ajst-11303	233	10	comparison	comparison	NOUN
ajst-11303	233	11	of	of	ADP
ajst-11303	233	12	relu	relu	NOUN
ajst-11303	233	13	and	and	CCONJ
ajst-11303	233	14	linear	linear	ADJ
ajst-11303	233	15	saturated	saturate	VERB
ajst-11303	233	16	activation	activation	NOUN
ajst-11303	233	17	functions	function	NOUN
ajst-11303	233	18	in	in	ADP
ajst-11303	233	19	neural	neural	ADJ
ajst-11303	233	20	network	network	NOUN
ajst-11303	233	21	for	for	ADP
ajst-11303	233	22	universal	universal	ADJ
ajst-11303	233	23	approximation	approximation	NOUN
ajst-11303	233	24	.	.	PUNCT
ajst-11303	234	1	2019	2019	NUM
ajst-11303	234	2	22nd	22nd	NOUN
ajst-11303	234	3	international	international	ADJ
ajst-11303	234	4	conference	conference	NOUN
ajst-11303	234	5	on	on	ADP
ajst-11303	234	6	process	process	NOUN
ajst-11303	234	7	control	control	NOUN
ajst-11303	234	8	(	(	PUNCT
ajst-11303	234	9	pc19	pc19	PROPN
ajst-11303	234	10	)	)	PUNCT
ajst-11303	234	11	.	.	PUNCT
ajst-11303	235	1	2019,p	2019,p	PROPN
ajst-11303	235	2	.	.	PUNCT
ajst-11303	236	1	146	146	NUM
ajst-11303	236	2	-	-	SYM
ajst-11303	236	3	151	151	NUM
ajst-11303	236	4	.	.	PUNCT
ajst-11303	237	1	[	[	X
ajst-11303	237	2	20	20	NUM
ajst-11303	237	3	]	]	PUNCT
ajst-11303	237	4	biswas	biswas	PROPN
ajst-11303	237	5	koushik	koushik	PROPN
ajst-11303	237	6	,	,	PUNCT
ajst-11303	237	7	kumar	kumar	PROPN
ajst-11303	237	8	sandeep	sandeep	PROPN
ajst-11303	237	9	,	,	PUNCT
ajst-11303	237	10	banerjee	banerjee	PROPN
ajst-11303	237	11	shilpak	shilpak	PROPN
ajst-11303	237	12	,	,	PUNCT
ajst-11303	237	13	et	et	PROPN
ajst-11303	237	14	al	al	PROPN
ajst-11303	237	15	.	.	PUNCT
ajst-11303	238	1	smu	smu	PROPN
ajst-11303	238	2	:	:	PUNCT
ajst-11303	238	3	smooth	smooth	ADJ
ajst-11303	238	4	activation	activation	NOUN
ajst-11303	238	5	function	function	NOUN
ajst-11303	238	6	for	for	ADP
ajst-11303	238	7	deep	deep	ADJ
ajst-11303	238	8	networks	network	NOUN
ajst-11303	238	9	using	use	VERB
ajst-11303	238	10	smoothing	smooth	VERB
ajst-11303	238	11	maximum	maximum	ADJ
ajst-11303	238	12	technique	technique	NOUN
ajst-11303	238	13	.	.	PUNCT
ajst-11303	239	1	[	[	X
ajst-11303	239	2	21	21	NUM
ajst-11303	239	3	]	]	X
ajst-11303	239	4	shi	shi	PROPN
ajst-11303	239	5	lei	lei	PROPN
ajst-11303	239	6	,	,	PUNCT
ajst-11303	239	7	wang	wang	PROPN
ajst-11303	239	8	yi	yi	PROPN
ajst-11303	239	9	,	,	PUNCT
ajst-11303	239	10	cheng	cheng	PROPN
ajst-11303	239	11	ying	ying	PROPN
ajst-11303	239	12	,	,	PUNCT
ajst-11303	239	13	et	et	PROPN
ajst-11303	239	14	al	al	PROPN
ajst-11303	239	15	.	.	PUNCT
ajst-11303	240	1	a	a	DET
ajst-11303	240	2	review	review	NOUN
ajst-11303	240	3	of	of	ADP
ajst-11303	240	4	research	research	NOUN
ajst-11303	240	5	on	on	ADP
ajst-11303	240	6	attention	attention	NOUN
ajst-11303	240	7	mechanisms	mechanism	NOUN
ajst-11303	240	8	in	in	ADP
ajst-11303	240	9	natural	natural	ADJ
ajst-11303	240	10	language	language	NOUN
ajst-11303	240	11	processing	processing	NOUN
ajst-11303	240	12	.	.	PUNCT
ajst-11303	241	1	data	datum	NOUN
ajst-11303	241	2	analysis	analysis	NOUN
ajst-11303	241	3	and	and	CCONJ
ajst-11303	241	4	knowledge	knowledge	NOUN
ajst-11303	241	5	discovery	discovery	NOUN
ajst-11303	241	6	.	.	PUNCT
ajst-11303	242	1	vol	vol	NOUN
ajst-11303	242	2	.	.	PROPN
ajst-11303	242	3	4	4	NUM
ajst-11303	242	4	(	(	PUNCT
ajst-11303	242	5	2020	2020	NUM
ajst-11303	242	6	)	)	PUNCT
ajst-11303	243	1	no	no	INTJ
ajst-11303	243	2	.	.	NOUN
ajst-11303	244	1	05	05	NUM
ajst-11303	244	2	,	,	PUNCT
ajst-11303	245	1	p.	p.	NOUN
ajst-11303	245	2	1	1	NUM
ajst-11303	245	3	-	-	SYM
ajst-11303	245	4	14	14	NUM
ajst-11303	245	5	.	.	PUNCT
ajst-11303	246	1	[	[	X
ajst-11303	246	2	22	22	NUM
ajst-11303	246	3	]	]	X
ajst-11303	246	4	kaiyou	kaiyou	NOUN
ajst-11303	246	5	song	song	PROPN
ajst-11303	246	6	,	,	PUNCT
ajst-11303	246	7	hua	hua	PROPN
ajst-11303	246	8	yang	yang	PROPN
ajst-11303	246	9	,	,	PUNCT
ajst-11303	246	10	zhouping	zhouping	NOUN
ajst-11303	246	11	yin	yin	PROPN
ajst-11303	246	12	.	.	PUNCT
ajst-11303	247	1	multi	multi	ADJ
ajst-11303	247	2	-	-	ADJ
ajst-11303	247	3	scale	scale	ADJ
ajst-11303	247	4	attention	attention	NOUN
ajst-11303	247	5	deep	deep	ADJ
ajst-11303	247	6	neural	neural	ADJ
ajst-11303	247	7	network	network	NOUN
ajst-11303	247	8	for	for	ADP
ajst-11303	247	9	fast	fast	ADJ
ajst-11303	247	10	accurate	accurate	ADJ
ajst-11303	247	11	object	object	NOUN
ajst-11303	247	12	detection	detection	NOUN
ajst-11303	247	13	.	.	PUNCT
ajst-11303	248	1	ieee	ieee	PROPN
ajst-11303	248	2	trans	trans	PROPN
ajst-11303	248	3	.	.	PUNCT
ajst-11303	249	1	circuits	circuit	NOUN
ajst-11303	249	2	syst	syst	PROPN
ajst-11303	249	3	.	.	PUNCT
ajst-11303	250	1	video	video	PROPN
ajst-11303	250	2	techn	techn	PROPN
ajst-11303	250	3	.	.	PUNCT
ajst-11303	250	4	vol	vol	NOUN
ajst-11303	250	5	.	.	PROPN
ajst-11303	250	6	29	29	NUM
ajst-11303	250	7	(	(	PUNCT
ajst-11303	250	8	2019	2019	NUM
ajst-11303	250	9	)	)	PUNCT
ajst-11303	251	1	no	no	INTJ
ajst-11303	251	2	.	.	NOUN
ajst-11303	251	3	10	10	NUM
ajst-11303	251	4	,	,	PUNCT
ajst-11303	251	5	p.	p.	NOUN
ajst-11303	251	6	2972	2972	NUM
ajst-11303	251	7	-	-	SYM
ajst-11303	251	8	2985	2985	NUM
ajst-11303	251	9	.	.	PUNCT