id	sid	tid	token	lemma	pos
ajst-28813	1	1	academic	academic	ADJ
ajst-28813	1	2	journal	journal	NOUN
ajst-28813	1	3	of	of	ADP
ajst-28813	1	4	science	science	NOUN
ajst-28813	1	5	and	and	CCONJ
ajst-28813	1	6	technology	technology	NOUN
ajst-28813	1	7	issn	issn	NOUN
ajst-28813	1	8	:	:	PUNCT
ajst-28813	1	9	2771	2771	NUM
ajst-28813	1	10	-	-	SYM
ajst-28813	1	11	3032	3032	NUM
ajst-28813	1	12	|	|	NOUN
ajst-28813	1	13	vol	vol	NOUN
ajst-28813	1	14	.	.	PROPN
ajst-28813	1	15	13	13	NUM
ajst-28813	1	16	,	,	PUNCT
ajst-28813	1	17	no	no	INTJ
ajst-28813	1	18	.	.	NOUN
ajst-28813	1	19	3	3	NUM
ajst-28813	1	20	,	,	PUNCT
ajst-28813	1	21	2024	2024	NUM
ajst-28813	1	22	244	244	NUM
ajst-28813	1	23	esn	esn	PROPN
ajst-28813	1	24	neural	neural	ADJ
ajst-28813	1	25	network‐based	network‐base	VERB
ajst-28813	1	26	electrical	electrical	ADJ
ajst-28813	1	27	submersible	submersible	ADJ
ajst-28813	1	28	pump	pump	NOUN
ajst-28813	1	29	model	model	NOUN
ajst-28813	1	30	chuan	chuan	PROPN
ajst-28813	1	31	wang	wang	PROPN
ajst-28813	1	32	,	,	PUNCT
ajst-28813	1	33	zhen	zhen	PROPN
ajst-28813	1	34	long	long	PROPN
ajst-28813	1	35	energy	energy	NOUN
ajst-28813	1	36	equipment	equipment	PROPN
ajst-28813	1	37	research	research	NOUN
ajst-28813	1	38	institute	institute	PROPN
ajst-28813	1	39	,	,	PUNCT
ajst-28813	1	40	southwest	southwest	ADJ
ajst-28813	1	41	petroleum	petroleum	PROPN
ajst-28813	1	42	university	university	PROPN
ajst-28813	1	43	,	,	PUNCT
ajst-28813	1	44	china	china	PROPN
ajst-28813	1	45	abstract	abstract	NOUN
ajst-28813	1	46	:	:	PUNCT
ajst-28813	1	47	this	this	DET
ajst-28813	1	48	paper	paper	NOUN
ajst-28813	1	49	introduces	introduce	VERB
ajst-28813	1	50	an	an	DET
ajst-28813	1	51	electrical	electrical	ADJ
ajst-28813	1	52	submersible	submersible	ADJ
ajst-28813	1	53	pump	pump	NOUN
ajst-28813	1	54	(	(	PUNCT
ajst-28813	1	55	esp	esp	ADJ
ajst-28813	1	56	)	)	PUNCT
ajst-28813	1	57	model	model	NOUN
ajst-28813	1	58	based	base	VERB
ajst-28813	1	59	on	on	ADP
ajst-28813	1	60	the	the	DET
ajst-28813	1	61	echo	echo	NOUN
ajst-28813	1	62	state	state	NOUN
ajst-28813	1	63	network	network	NOUN
ajst-28813	1	64	(	(	PUNCT
ajst-28813	1	65	esn	esn	PROPN
ajst-28813	1	66	)	)	PUNCT
ajst-28813	1	67	neural	neural	ADJ
ajst-28813	1	68	network	network	NOUN
ajst-28813	1	69	.	.	PUNCT
ajst-28813	2	1	esps	esps	PROPN
ajst-28813	2	2	are	be	AUX
ajst-28813	2	3	commonly	commonly	ADV
ajst-28813	2	4	used	use	VERB
ajst-28813	2	5	in	in	ADP
ajst-28813	2	6	oil	oil	NOUN
ajst-28813	2	7	extraction	extraction	NOUN
ajst-28813	2	8	,	,	PUNCT
ajst-28813	2	9	and	and	CCONJ
ajst-28813	2	10	their	their	PRON
ajst-28813	2	11	performance	performance	NOUN
ajst-28813	2	12	is	be	AUX
ajst-28813	2	13	influenced	influence	VERB
ajst-28813	2	14	by	by	ADP
ajst-28813	2	15	a	a	DET
ajst-28813	2	16	variety	variety	NOUN
ajst-28813	2	17	of	of	ADP
ajst-28813	2	18	factors	factor	NOUN
ajst-28813	2	19	,	,	PUNCT
ajst-28813	2	20	making	make	VERB
ajst-28813	2	21	accurate	accurate	ADJ
ajst-28813	2	22	modeling	modeling	NOUN
ajst-28813	2	23	crucial	crucial	ADJ
ajst-28813	2	24	for	for	ADP
ajst-28813	2	25	optimizing	optimize	VERB
ajst-28813	2	26	operations	operation	NOUN
ajst-28813	2	27	and	and	CCONJ
ajst-28813	2	28	maintenance	maintenance	NOUN
ajst-28813	2	29	.	.	PUNCT
ajst-28813	3	1	esn	esn	PROPN
ajst-28813	3	2	is	be	AUX
ajst-28813	3	3	a	a	DET
ajst-28813	3	4	type	type	NOUN
ajst-28813	3	5	of	of	ADP
ajst-28813	3	6	recurrent	recurrent	ADJ
ajst-28813	3	7	neural	neural	ADJ
ajst-28813	3	8	network	network	NOUN
ajst-28813	3	9	with	with	ADP
ajst-28813	3	10	unique	unique	ADJ
ajst-28813	3	11	dynamic	dynamic	ADJ
ajst-28813	3	12	memory	memory	NOUN
ajst-28813	3	13	capabilities	capability	NOUN
ajst-28813	3	14	,	,	PUNCT
ajst-28813	3	15	making	make	VERB
ajst-28813	3	16	it	it	PRON
ajst-28813	3	17	suitable	suitable	ADJ
ajst-28813	3	18	for	for	ADP
ajst-28813	3	19	handling	handle	VERB
ajst-28813	3	20	time	time	NOUN
ajst-28813	3	21	-	-	PUNCT
ajst-28813	3	22	series	series	NOUN
ajst-28813	3	23	data	datum	NOUN
ajst-28813	3	24	and	and	CCONJ
ajst-28813	3	25	modeling	model	VERB
ajst-28813	3	26	nonlinear	nonlinear	ADJ
ajst-28813	3	27	dynamic	dynamic	ADJ
ajst-28813	3	28	systems	system	NOUN
ajst-28813	3	29	.	.	PUNCT
ajst-28813	4	1	the	the	DET
ajst-28813	4	2	article	article	NOUN
ajst-28813	4	3	details	detail	VERB
ajst-28813	4	4	the	the	DET
ajst-28813	4	5	esn	esn	PROPN
ajst-28813	4	6	network	network	NOUN
ajst-28813	4	7	structure	structure	NOUN
ajst-28813	4	8	and	and	CCONJ
ajst-28813	4	9	its	its	PRON
ajst-28813	4	10	application	application	NOUN
ajst-28813	4	11	in	in	ADP
ajst-28813	4	12	the	the	DET
ajst-28813	4	13	esp	esp	ADJ
ajst-28813	4	14	model	model	NOUN
ajst-28813	4	15	,	,	PUNCT
ajst-28813	4	16	including	include	VERB
ajst-28813	4	17	how	how	SCONJ
ajst-28813	4	18	to	to	PART
ajst-28813	4	19	use	use	VERB
ajst-28813	4	20	esn	esn	PROPN
ajst-28813	4	21	to	to	PART
ajst-28813	4	22	predict	predict	VERB
ajst-28813	4	23	performance	performance	NOUN
ajst-28813	4	24	parameters	parameter	NOUN
ajst-28813	4	25	and	and	CCONJ
ajst-28813	4	26	diagnose	diagnose	NOUN
ajst-28813	4	27	faults	fault	NOUN
ajst-28813	4	28	in	in	ADP
ajst-28813	4	29	esps	esp	NOUN
ajst-28813	4	30	.	.	PUNCT
ajst-28813	5	1	compared	compare	VERB
ajst-28813	5	2	with	with	ADP
ajst-28813	5	3	traditional	traditional	ADJ
ajst-28813	5	4	models	model	NOUN
ajst-28813	5	5	,	,	PUNCT
ajst-28813	5	6	the	the	DET
ajst-28813	5	7	esn	esn	PROPN
ajst-28813	5	8	model	model	NOUN
ajst-28813	5	9	shows	show	VERB
ajst-28813	5	10	significant	significant	ADJ
ajst-28813	5	11	advantages	advantage	NOUN
ajst-28813	5	12	in	in	ADP
ajst-28813	5	13	prediction	prediction	NOUN
ajst-28813	5	14	accuracy	accuracy	NOUN
ajst-28813	5	15	and	and	CCONJ
ajst-28813	5	16	computational	computational	ADJ
ajst-28813	5	17	efficiency	efficiency	NOUN
ajst-28813	5	18	.	.	PUNCT
ajst-28813	6	1	the	the	DET
ajst-28813	6	2	results	result	NOUN
ajst-28813	6	3	indicate	indicate	VERB
ajst-28813	6	4	that	that	SCONJ
ajst-28813	6	5	the	the	DET
ajst-28813	6	6	esn	esn	PROPN
ajst-28813	6	7	-	-	PUNCT
ajst-28813	6	8	based	base	VERB
ajst-28813	6	9	esp	esp	ADJ
ajst-28813	6	10	model	model	NOUN
ajst-28813	6	11	can	can	AUX
ajst-28813	6	12	effectively	effectively	ADV
ajst-28813	6	13	simulate	simulate	VERB
ajst-28813	6	14	the	the	DET
ajst-28813	6	15	dynamic	dynamic	ADJ
ajst-28813	6	16	behavior	behavior	NOUN
ajst-28813	6	17	of	of	ADP
ajst-28813	6	18	esps	esps	PROPN
ajst-28813	6	19	,	,	PUNCT
ajst-28813	6	20	providing	provide	VERB
ajst-28813	6	21	a	a	DET
ajst-28813	6	22	powerful	powerful	ADJ
ajst-28813	6	23	tool	tool	NOUN
ajst-28813	6	24	for	for	ADP
ajst-28813	6	25	real	real	ADJ
ajst-28813	6	26	-	-	PUNCT
ajst-28813	6	27	time	time	NOUN
ajst-28813	6	28	monitoring	monitoring	NOUN
ajst-28813	6	29	and	and	CCONJ
ajst-28813	6	30	fault	fault	VERB
ajst-28813	6	31	prevention	prevention	NOUN
ajst-28813	6	32	of	of	ADP
ajst-28813	6	33	esps	esp	NOUN
ajst-28813	6	34	.	.	PUNCT
ajst-28813	7	1	keywords	keyword	NOUN
ajst-28813	7	2	:	:	PUNCT
ajst-28813	7	3	esn	esn	PROPN
ajst-28813	7	4	-	-	PUNCT
ajst-28813	7	5	rls	rls	PROPN
ajst-28813	7	6	network	network	NOUN
ajst-28813	7	7	;	;	PUNCT
ajst-28813	7	8	pso	pso	NOUN
ajst-28813	7	9	optimization	optimization	NOUN
ajst-28813	7	10	parameters	parameter	NOUN
ajst-28813	7	11	;	;	PUNCT
ajst-28813	7	12	kalman	kalman	NOUN
ajst-28813	7	13	filter	filter	NOUN
ajst-28813	7	14	method	method	NOUN
ajst-28813	7	15	.	.	PUNCT
ajst-28813	8	1	1	1	X
ajst-28813	8	2	.	.	X
ajst-28813	8	3	introduction	introduction	NOUN
ajst-28813	8	4	electric	electric	ADJ
ajst-28813	8	5	submersible	submersible	ADJ
ajst-28813	8	6	pump	pump	NOUN
ajst-28813	8	7	(	(	PUNCT
ajst-28813	8	8	electrical	electrical	ADJ
ajst-28813	8	9	submersible	submersible	ADJ
ajst-28813	8	10	pump	pump	NOUN
ajst-28813	8	11	,	,	PUNCT
ajst-28813	8	12	esp	esp	ADJ
ajst-28813	8	13	)	)	PUNCT
ajst-28813	8	14	is	be	AUX
ajst-28813	8	15	a	a	DET
ajst-28813	8	16	widely	widely	ADV
ajst-28813	8	17	used	use	VERB
ajst-28813	8	18	equipment	equipment	NOUN
ajst-28813	8	19	in	in	ADP
ajst-28813	8	20	the	the	DET
ajst-28813	8	21	petroleum	petroleum	NOUN
ajst-28813	8	22	industry	industry	NOUN
ajst-28813	8	23	to	to	PART
ajst-28813	8	24	transport	transport	VERB
ajst-28813	8	25	the	the	DET
ajst-28813	8	26	underground	underground	ADJ
ajst-28813	8	27	liquid	liquid	NOUN
ajst-28813	8	28	to	to	ADP
ajst-28813	8	29	the	the	DET
ajst-28813	8	30	ground	ground	NOUN
ajst-28813	8	31	.	.	PUNCT
ajst-28813	9	1	the	the	DET
ajst-28813	9	2	esn	esn	PROPN
ajst-28813	9	3	network	network	PROPN
ajst-28813	9	4	model	model	NOUN
ajst-28813	9	5	based	base	VERB
ajst-28813	9	6	on	on	ADP
ajst-28813	9	7	python3.9	python3.9	NOUN
ajst-28813	9	8	was	be	AUX
ajst-28813	9	9	constructed	construct	VERB
ajst-28813	9	10	according	accord	VERB
ajst-28813	9	11	to	to	ADP
ajst-28813	9	12	the	the	DET
ajst-28813	9	13	physical	physical	ADJ
ajst-28813	9	14	model	model	NOUN
ajst-28813	9	15	of	of	ADP
ajst-28813	9	16	the	the	DET
ajst-28813	9	17	electric	electric	ADJ
ajst-28813	9	18	submersible	submersible	ADJ
ajst-28813	9	19	pump	pump	NOUN
ajst-28813	9	20	,	,	PUNCT
ajst-28813	9	21	and	and	CCONJ
ajst-28813	9	22	wrote	write	VERB
ajst-28813	9	23	the	the	DET
ajst-28813	9	24	corresponding	corresponding	ADJ
ajst-28813	9	25	update	update	NOUN
ajst-28813	9	26	algorithm	algorithm	NOUN
ajst-28813	9	27	(	(	PUNCT
ajst-28813	9	28	rls	rls	PROPN
ajst-28813	9	29	)	)	PUNCT
ajst-28813	9	30	;	;	PUNCT
ajst-28813	9	31	and	and	CCONJ
ajst-28813	9	32	the	the	DET
ajst-28813	9	33	parameters	parameter	NOUN
ajst-28813	9	34	of	of	ADP
ajst-28813	9	35	optimizing	optimize	VERB
ajst-28813	9	36	the	the	DET
ajst-28813	9	37	network	network	NOUN
ajst-28813	9	38	via	via	ADP
ajst-28813	9	39	the	the	DET
ajst-28813	9	40	pso	pso	NOUN
ajst-28813	9	41	algorithm	algorithm	NOUN
ajst-28813	9	42	,	,	PUNCT
ajst-28813	9	43	bring	bring	VERB
ajst-28813	9	44	the	the	DET
ajst-28813	9	45	network	network	NOUN
ajst-28813	9	46	state	state	NOUN
ajst-28813	9	47	to	to	ADP
ajst-28813	9	48	the	the	DET
ajst-28813	9	49	current	current	ADJ
ajst-28813	9	50	optimum	optimum	NOUN
ajst-28813	9	51	,	,	PUNCT
ajst-28813	9	52	improve	improve	VERB
ajst-28813	9	53	the	the	DET
ajst-28813	9	54	robustness	robustness	NOUN
ajst-28813	9	55	of	of	ADP
ajst-28813	9	56	the	the	DET
ajst-28813	9	57	model	model	NOUN
ajst-28813	9	58	;	;	PUNCT
ajst-28813	9	59	then	then	ADV
ajst-28813	9	60	,	,	PUNCT
ajst-28813	9	61	through	through	ADP
ajst-28813	9	62	the	the	DET
ajst-28813	9	63	numpy	numpy	NOUN
ajst-28813	9	64	and	and	CCONJ
ajst-28813	9	65	casadi	casadi	VERB
ajst-28813	9	66	open	open	ADJ
ajst-28813	9	67	-	-	PUNCT
ajst-28813	9	68	source	source	NOUN
ajst-28813	9	69	libraries	library	NOUN
ajst-28813	9	70	in	in	ADP
ajst-28813	9	71	the	the	DET
ajst-28813	9	72	pycharm	pycharm	PROPN
ajst-28813	9	73	development	development	NOUN
ajst-28813	9	74	environment	environment	PROPN
ajst-28813	9	75	,	,	PUNCT
ajst-28813	9	76	write	write	VERB
ajst-28813	9	77	the	the	DET
ajst-28813	9	78	data	datum	NOUN
ajst-28813	9	79	set	set	VERB
ajst-28813	9	80	used	use	VERB
ajst-28813	9	81	for	for	ADP
ajst-28813	9	82	network	network	NOUN
ajst-28813	9	83	training	training	NOUN
ajst-28813	9	84	;	;	PUNCT
ajst-28813	9	85	in	in	ADP
ajst-28813	9	86	verifying	verify	VERB
ajst-28813	9	87	the	the	DET
ajst-28813	9	88	authenticity	authenticity	NOUN
ajst-28813	9	89	of	of	ADP
ajst-28813	9	90	the	the	DET
ajst-28813	9	91	model	model	NOUN
ajst-28813	9	92	,	,	PUNCT
ajst-28813	9	93	the	the	DET
ajst-28813	9	94	lstm	lstm	PROPN
ajst-28813	9	95	network	network	NOUN
ajst-28813	9	96	and	and	CCONJ
ajst-28813	9	97	gru	gru	NOUN
ajst-28813	9	98	network	network	NOUN
ajst-28813	9	99	model	model	NOUN
ajst-28813	9	100	and	and	CCONJ
ajst-28813	9	101	the	the	DET
ajst-28813	9	102	esn	esn	PROPN
ajst-28813	9	103	network	network	PROPN
ajst-28813	9	104	model	model	NOUN
ajst-28813	9	105	were	be	AUX
ajst-28813	9	106	written	write	VERB
ajst-28813	9	107	,	,	PUNCT
ajst-28813	9	108	the	the	DET
ajst-28813	9	109	authenticity	authenticity	NOUN
ajst-28813	9	110	of	of	ADP
ajst-28813	9	111	the	the	DET
ajst-28813	9	112	esn	esn	PROPN
ajst-28813	9	113	model	model	NOUN
ajst-28813	9	114	prediction	prediction	NOUN
ajst-28813	9	115	is	be	AUX
ajst-28813	9	116	obtained	obtain	VERB
ajst-28813	9	117	;	;	PUNCT
ajst-28813	9	118	finally	finally	ADV
ajst-28813	9	119	,	,	PUNCT
ajst-28813	9	120	it	it	PRON
ajst-28813	9	121	was	be	AUX
ajst-28813	9	122	compared	compare	VERB
ajst-28813	9	123	with	with	ADP
ajst-28813	9	124	the	the	DET
ajst-28813	9	125	real	real	ADJ
ajst-28813	9	126	value	value	NOUN
ajst-28813	9	127	according	accord	VERB
ajst-28813	9	128	to	to	ADP
ajst-28813	9	129	the	the	DET
ajst-28813	9	130	training	training	NOUN
ajst-28813	9	131	results	result	NOUN
ajst-28813	9	132	,	,	PUNCT
ajst-28813	9	133	expand	expand	VERB
ajst-28813	9	134	the	the	DET
ajst-28813	9	135	evaluation	evaluation	NOUN
ajst-28813	9	136	of	of	ADP
ajst-28813	9	137	this	this	DET
ajst-28813	9	138	network	network	NOUN
ajst-28813	9	139	model	model	NOUN
ajst-28813	9	140	.	.	PUNCT
ajst-28813	10	1	an	an	DET
ajst-28813	10	2	artificial	artificial	ADJ
ajst-28813	10	3	neural	neural	ADJ
ajst-28813	10	4	network	network	NOUN
ajst-28813	10	5	is	be	AUX
ajst-28813	10	6	a	a	DET
ajst-28813	10	7	machine	machine	NOUN
ajst-28813	10	8	learning	learn	VERB
ajst-28813	10	9	technology	technology	NOUN
ajst-28813	10	10	that	that	PRON
ajst-28813	10	11	is	be	AUX
ajst-28813	10	12	inspired	inspire	VERB
ajst-28813	10	13	by	by	ADP
ajst-28813	10	14	the	the	DET
ajst-28813	10	15	operation	operation	NOUN
ajst-28813	10	16	of	of	ADP
ajst-28813	10	17	neurons	neuron	NOUN
ajst-28813	10	18	in	in	ADP
ajst-28813	10	19	the	the	DET
ajst-28813	10	20	human	human	ADJ
ajst-28813	10	21	brain	brain	NOUN
ajst-28813	10	22	.	.	PUNCT
ajst-28813	11	1	this	this	DET
ajst-28813	11	2	technology	technology	NOUN
ajst-28813	11	3	excels	excel	VERB
ajst-28813	11	4	at	at	ADP
ajst-28813	11	5	handling	handle	VERB
ajst-28813	11	6	complex	complex	ADJ
ajst-28813	11	7	problems	problem	NOUN
ajst-28813	11	8	that	that	PRON
ajst-28813	11	9	are	be	AUX
ajst-28813	11	10	difficult	difficult	ADJ
ajst-28813	11	11	to	to	PART
ajst-28813	11	12	model	model	VERB
ajst-28813	11	13	precisely	precisely	ADV
ajst-28813	11	14	with	with	ADP
ajst-28813	11	15	traditional	traditional	ADJ
ajst-28813	11	16	algorithms	algorithm	NOUN
ajst-28813	11	17	,	,	PUNCT
ajst-28813	11	18	demonstrating	demonstrate	VERB
ajst-28813	11	19	exceptional	exceptional	ADJ
ajst-28813	11	20	flexibility	flexibility	NOUN
ajst-28813	11	21	and	and	CCONJ
ajst-28813	11	22	adaptability[1	adaptability[1	PROPN
ajst-28813	11	23	]	]	PUNCT
ajst-28813	11	24	.	.	PUNCT
ajst-28813	12	1	in	in	ADP
ajst-28813	12	2	various	various	ADJ
ajst-28813	12	3	fields	field	NOUN
ajst-28813	12	4	such	such	ADJ
ajst-28813	12	5	as	as	ADP
ajst-28813	12	6	automatic	automatic	ADJ
ajst-28813	12	7	handwriting	handwriting	NOUN
ajst-28813	12	8	recognition	recognition	NOUN
ajst-28813	12	9	,	,	PUNCT
ajst-28813	12	10	object	object	NOUN
ajst-28813	12	11	recognition	recognition	NOUN
ajst-28813	12	12	,	,	PUNCT
ajst-28813	12	13	autonomous	autonomous	ADJ
ajst-28813	12	14	driving	driving	NOUN
ajst-28813	12	15	technology	technology	NOUN
ajst-28813	12	16	,	,	PUNCT
ajst-28813	12	17	and	and	CCONJ
ajst-28813	12	18	many	many	ADJ
ajst-28813	12	19	others	other	NOUN
ajst-28813	12	20	,	,	PUNCT
ajst-28813	12	21	artificial	artificial	ADJ
ajst-28813	12	22	neural	neural	ADJ
ajst-28813	12	23	networks	network	NOUN
ajst-28813	12	24	play	play	VERB
ajst-28813	12	25	a	a	DET
ajst-28813	12	26	significant	significant	ADJ
ajst-28813	12	27	role	role	NOUN
ajst-28813	12	28	.	.	PUNCT
ajst-28813	13	1	their	their	PRON
ajst-28813	13	2	core	core	NOUN
ajst-28813	13	3	advantage	advantage	NOUN
ajst-28813	13	4	lies	lie	VERB
ajst-28813	13	5	in	in	ADP
ajst-28813	13	6	their	their	PRON
ajst-28813	13	7	powerful	powerful	ADJ
ajst-28813	13	8	learning	learning	NOUN
ajst-28813	13	9	ability	ability	NOUN
ajst-28813	13	10	,	,	PUNCT
ajst-28813	13	11	which	which	PRON
ajst-28813	13	12	stems	stem	VERB
ajst-28813	13	13	from	from	ADP
ajst-28813	13	14	the	the	DET
ajst-28813	13	15	deep	deep	ADJ
ajst-28813	13	16	analysis	analysis	NOUN
ajst-28813	13	17	and	and	CCONJ
ajst-28813	13	18	utilization	utilization	NOUN
ajst-28813	13	19	of	of	ADP
ajst-28813	13	20	large	large	ADJ
ajst-28813	13	21	-	-	PUNCT
ajst-28813	13	22	scale	scale	NOUN
ajst-28813	13	23	training	training	NOUN
ajst-28813	13	24	datasets	dataset	NOUN
ajst-28813	13	25	.	.	PUNCT
ajst-28813	14	1	neural	neural	ADJ
ajst-28813	14	2	networks	network	NOUN
ajst-28813	14	3	continuously	continuously	ADV
ajst-28813	14	4	optimize	optimize	VERB
ajst-28813	14	5	their	their	PRON
ajst-28813	14	6	internal	internal	ADJ
ajst-28813	14	7	parameters	parameter	NOUN
ajst-28813	14	8	,	,	PUNCT
ajst-28813	14	9	automatically	automatically	ADV
ajst-28813	14	10	learning	learn	VERB
ajst-28813	14	11	and	and	CCONJ
ajst-28813	14	12	identifying	identify	VERB
ajst-28813	14	13	potential	potential	ADJ
ajst-28813	14	14	patterns	pattern	NOUN
ajst-28813	14	15	and	and	CCONJ
ajst-28813	14	16	regularities	regularity	NOUN
ajst-28813	14	17	within	within	ADP
ajst-28813	14	18	the	the	DET
ajst-28813	14	19	data	datum	NOUN
ajst-28813	14	20	,	,	PUNCT
ajst-28813	14	21	thereby	thereby	ADV
ajst-28813	14	22	achieving	achieve	VERB
ajst-28813	14	23	accurate	accurate	ADJ
ajst-28813	14	24	predictions	prediction	NOUN
ajst-28813	14	25	for	for	ADP
ajst-28813	14	26	new	new	ADJ
ajst-28813	14	27	samples[6	samples[6	NOUN
ajst-28813	14	28	]	]	X
ajst-28813	14	29	.	.	PUNCT
ajst-28813	15	1	the	the	DET
ajst-28813	15	2	structure	structure	NOUN
ajst-28813	15	3	of	of	ADP
ajst-28813	15	4	a	a	DET
ajst-28813	15	5	neural	neural	ADJ
ajst-28813	15	6	network	network	NOUN
ajst-28813	15	7	consists	consist	VERB
ajst-28813	15	8	of	of	ADP
ajst-28813	15	9	neurons	neuron	NOUN
ajst-28813	15	10	designed	design	VERB
ajst-28813	15	11	in	in	ADP
ajst-28813	15	12	multiple	multiple	ADJ
ajst-28813	15	13	layers	layer	NOUN
ajst-28813	15	14	.	.	PUNCT
ajst-28813	16	1	each	each	DET
ajst-28813	16	2	layer	layer	NOUN
ajst-28813	16	3	of	of	ADP
ajst-28813	16	4	neurons	neuron	NOUN
ajst-28813	16	5	undertakes	undertake	VERB
ajst-28813	16	6	specific	specific	ADJ
ajst-28813	16	7	information	information	NOUN
ajst-28813	16	8	processing	processing	NOUN
ajst-28813	16	9	tasks	task	NOUN
ajst-28813	16	10	.	.	PUNCT
ajst-28813	17	1	as	as	ADP
ajst-28813	17	2	computational	computational	ADJ
ajst-28813	17	3	units	unit	NOUN
ajst-28813	17	4	,	,	PUNCT
ajst-28813	17	5	neurons	neuron	NOUN
ajst-28813	17	6	multiply	multiply	VERB
ajst-28813	17	7	the	the	DET
ajst-28813	17	8	system	system	NOUN
ajst-28813	17	9	input	input	NOUN
ajst-28813	17	10	values	value	NOUN
ajst-28813	17	11	by	by	ADP
ajst-28813	17	12	weights	weight	NOUN
ajst-28813	17	13	and	and	CCONJ
ajst-28813	17	14	accept	accept	VERB
ajst-28813	17	15	weighted	weight	VERB
ajst-28813	17	16	inputs	input	NOUN
ajst-28813	17	17	from	from	ADP
ajst-28813	17	18	the	the	DET
ajst-28813	17	19	previous	previous	ADJ
ajst-28813	17	20	layer	layer	NOUN
ajst-28813	17	21	of	of	ADP
ajst-28813	17	22	neurons	neuron	NOUN
ajst-28813	17	23	,	,	PUNCT
ajst-28813	17	24	adding	add	VERB
ajst-28813	17	25	a	a	DET
ajst-28813	17	26	bias	bias	NOUN
ajst-28813	17	27	term	term	NOUN
ajst-28813	17	28	to	to	PART
ajst-28813	17	29	increase	increase	VERB
ajst-28813	17	30	the	the	DET
ajst-28813	17	31	flexibility	flexibility	NOUN
ajst-28813	17	32	of	of	ADP
ajst-28813	17	33	the	the	DET
ajst-28813	17	34	model	model	NOUN
ajst-28813	17	35	.	.	PUNCT
ajst-28813	18	1	the	the	DET
ajst-28813	18	2	computation	computation	NOUN
ajst-28813	18	3	process	process	NOUN
ajst-28813	18	4	is	be	AUX
ajst-28813	18	5	shown	show	VERB
ajst-28813	18	6	in	in	ADP
ajst-28813	18	7	equation	equation	NOUN
ajst-28813	18	8	1	1	NUM
ajst-28813	18	9	-	-	SYM
ajst-28813	18	10	1	1	NUM
ajst-28813	18	11	.	.	NOUN
ajst-28813	18	12	1	1	NUM
ajst-28813	19	1	n	n	NOUN
ajst-28813	20	1	i	i	PRON
ajst-28813	21	1	i	i	INTJ
ajst-28813	22	1	i	i	VERB
ajst-28813	22	2	x	x	VERB
ajst-28813	23	1	w	w	PROPN
ajst-28813	23	2	b	b	PROPN
ajst-28813	23	3			PROPN
ajst-28813	23	4			NOUN
ajst-28813	23	5	(	(	PUNCT
ajst-28813	23	6	1	1	NUM
ajst-28813	23	7	-	-	SYM
ajst-28813	23	8	1	1	NUM
ajst-28813	23	9	)	)	PUNCT
ajst-28813	23	10	subsequently	subsequently	ADV
ajst-28813	23	11	,	,	PUNCT
ajst-28813	23	12	through	through	ADP
ajst-28813	23	13	the	the	DET
ajst-28813	23	14	action	action	NOUN
ajst-28813	23	15	of	of	ADP
ajst-28813	23	16	the	the	DET
ajst-28813	23	17	activation	activation	NOUN
ajst-28813	23	18	function	function	NOUN
ajst-28813	23	19	,	,	PUNCT
ajst-28813	23	20	the	the	DET
ajst-28813	23	21	neuron	neuron	NOUN
ajst-28813	23	22	produces	produce	VERB
ajst-28813	23	23	an	an	DET
ajst-28813	23	24	output	output	NOUN
ajst-28813	23	25	,	,	PUNCT
ajst-28813	23	26	which	which	PRON
ajst-28813	23	27	then	then	ADV
ajst-28813	23	28	serves	serve	VERB
ajst-28813	23	29	as	as	ADP
ajst-28813	23	30	input	input	NOUN
ajst-28813	23	31	for	for	ADP
ajst-28813	23	32	the	the	DET
ajst-28813	23	33	next	next	ADJ
ajst-28813	23	34	layer	layer	NOUN
ajst-28813	23	35	of	of	ADP
ajst-28813	23	36	neurons	neuron	NOUN
ajst-28813	23	37	,	,	PUNCT
ajst-28813	23	38	proceeding	proceeding	NOUN
ajst-28813	23	39	layer	layer	NOUN
ajst-28813	23	40	by	by	ADP
ajst-28813	23	41	layer	layer	NOUN
ajst-28813	23	42	until	until	ADP
ajst-28813	23	43	the	the	DET
ajst-28813	23	44	end	end	NOUN
ajst-28813	23	45	of	of	ADP
ajst-28813	23	46	the	the	DET
ajst-28813	23	47	network	network	NOUN
ajst-28813	23	48	.	.	PUNCT
ajst-28813	24	1	as	as	SCONJ
ajst-28813	24	2	shown	show	VERB
ajst-28813	24	3	in	in	ADP
ajst-28813	24	4	figure	figure	NOUN
ajst-28813	24	5	1	1	NUM
ajst-28813	24	6	-	-	SYM
ajst-28813	24	7	1	1	NUM
ajst-28813	24	8	,	,	PUNCT
ajst-28813	24	9	the	the	DET
ajst-28813	24	10	mechanism	mechanism	NOUN
ajst-28813	24	11	of	of	ADP
ajst-28813	24	12	information	information	NOUN
ajst-28813	24	13	flow	flow	NOUN
ajst-28813	24	14	between	between	ADP
ajst-28813	24	15	neurons	neuron	NOUN
ajst-28813	24	16	is	be	AUX
ajst-28813	24	17	depicted[7	depicted[7	NOUN
ajst-28813	24	18	]	]	PUNCT
ajst-28813	24	19	.	.	PUNCT
ajst-28813	25	1	figure	figure	VERB
ajst-28813	25	2	1	1	NUM
ajst-28813	25	3	-	-	SYM
ajst-28813	25	4	1	1	NUM
ajst-28813	25	5	.	.	PUNCT
ajst-28813	25	6	schematic	schematic	ADJ
ajst-28813	25	7	diagram	diagram	NOUN
ajst-28813	25	8	of	of	ADP
ajst-28813	25	9	neuronal	neuronal	ADJ
ajst-28813	25	10	information	information	NOUN
ajst-28813	25	11	flow	flow	NOUN
ajst-28813	25	12	this	this	DET
ajst-28813	25	13	article	article	NOUN
ajst-28813	25	14	will	will	AUX
ajst-28813	25	15	start	start	VERB
ajst-28813	25	16	from	from	ADP
ajst-28813	25	17	the	the	DET
ajst-28813	25	18	basic	basic	ADJ
ajst-28813	25	19	structure	structure	NOUN
ajst-28813	25	20	of	of	ADP
ajst-28813	25	21	artificial	artificial	ADJ
ajst-28813	25	22	neural	neural	NOUN
ajst-28813	25	23	networks[10	networks[10	NUM
ajst-28813	25	24	]	]	PUNCT
ajst-28813	25	25	,	,	PUNCT
ajst-28813	25	26	and	and	CCONJ
ajst-28813	25	27	through	through	ADP
ajst-28813	25	28	the	the	DET
ajst-28813	25	29	analysis	analysis	NOUN
ajst-28813	25	30	of	of	ADP
ajst-28813	25	31	three	three	NUM
ajst-28813	25	32	dimensions	dimension	NOUN
ajst-28813	25	33	:	:	PUNCT
ajst-28813	25	34	the	the	DET
ajst-28813	25	35	input	input	NOUN
ajst-28813	25	36	layer	layer	NOUN
ajst-28813	25	37	,	,	PUNCT
ajst-28813	25	38	the	the	DET
ajst-28813	25	39	hidden	hidden	ADJ
ajst-28813	25	40	analysis	analysis	NOUN
ajst-28813	25	41	layer	layer	NOUN
ajst-28813	25	42	composed	compose	VERB
ajst-28813	25	43	of	of	ADP
ajst-28813	25	44	multiple	multiple	ADJ
ajst-28813	25	45	neurons	neuron	NOUN
ajst-28813	25	46	,	,	PUNCT
ajst-28813	25	47	and	and	CCONJ
ajst-28813	25	48	the	the	DET
ajst-28813	25	49	output	output	NOUN
ajst-28813	25	50	layer	layer	NOUN
ajst-28813	25	51	,	,	PUNCT
ajst-28813	25	52	construct	construct	VERB
ajst-28813	25	53	245	245	NUM
ajst-28813	25	54	the	the	DET
ajst-28813	25	55	esn	esn	PROPN
ajst-28813	25	56	neural	neural	PROPN
ajst-28813	25	57	network	network	PROPN
ajst-28813	25	58	model	model	NOUN
ajst-28813	25	59	,	,	PUNCT
ajst-28813	25	60	where	where	SCONJ
ajst-28813	25	61	a	a	DET
ajst-28813	25	62	general	general	ADJ
ajst-28813	25	63	schematic	schematic	ADJ
ajst-28813	25	64	diagram	diagram	NOUN
ajst-28813	25	65	of	of	ADP
ajst-28813	25	66	a	a	DET
ajst-28813	25	67	deep	deep	ADJ
ajst-28813	25	68	neural	neural	ADJ
ajst-28813	25	69	network	network	NOUN
ajst-28813	25	70	structure	structure	NOUN
ajst-28813	25	71	is	be	AUX
ajst-28813	25	72	shown	show	VERB
ajst-28813	25	73	in	in	ADP
ajst-28813	25	74	figure	figure	NOUN
ajst-28813	25	75	1	1	NUM
ajst-28813	25	76	-	-	SYM
ajst-28813	25	77	2	2	NUM
ajst-28813	25	78	.	.	PUNCT
ajst-28813	25	79	figure	figure	NOUN
ajst-28813	25	80	1	1	NUM
ajst-28813	25	81	-	-	SYM
ajst-28813	25	82	2	2	NUM
ajst-28813	25	83	.	.	PUNCT
ajst-28813	25	84	schematic	schematic	ADJ
ajst-28813	25	85	diagram	diagram	NOUN
ajst-28813	25	86	of	of	ADP
ajst-28813	25	87	a	a	DET
ajst-28813	25	88	deep	deep	ADJ
ajst-28813	25	89	neural	neural	ADJ
ajst-28813	25	90	network	network	NOUN
ajst-28813	25	91	2	2	NUM
ajst-28813	25	92	.	.	PUNCT
ajst-28813	26	1	the	the	DET
ajst-28813	26	2	basic	basic	ADJ
ajst-28813	26	3	principles	principle	NOUN
ajst-28813	26	4	of	of	ADP
ajst-28813	26	5	esn	esn	PROPN
ajst-28813	26	6	neural	neural	PROPN
ajst-28813	26	7	networks	network	NOUN
ajst-28813	26	8	2.1	2.1	NUM
ajst-28813	26	9	.	.	PUNCT
ajst-28813	27	1	basic	basic	ADJ
ajst-28813	27	2	principles	principle	NOUN
ajst-28813	27	3	esn	esn	PROPN
ajst-28813	27	4	as	as	ADP
ajst-28813	27	5	a	a	DET
ajst-28813	27	6	special	special	ADJ
ajst-28813	27	7	type	type	NOUN
ajst-28813	27	8	of	of	ADP
ajst-28813	27	9	recurrent	recurrent	ADJ
ajst-28813	27	10	neural	neural	ADJ
ajst-28813	27	11	network	network	NOUN
ajst-28813	27	12	,	,	PUNCT
ajst-28813	27	13	has	have	VERB
ajst-28813	27	14	a	a	DET
ajst-28813	27	15	simple	simple	ADJ
ajst-28813	27	16	network	network	NOUN
ajst-28813	27	17	structure	structure	NOUN
ajst-28813	27	18	and	and	CCONJ
ajst-28813	27	19	lower	low	ADJ
ajst-28813	27	20	training	training	NOUN
ajst-28813	27	21	requirements	requirement	NOUN
ajst-28813	27	22	,	,	PUNCT
ajst-28813	27	23	while	while	SCONJ
ajst-28813	27	24	also	also	ADV
ajst-28813	27	25	possessing	possess	VERB
ajst-28813	27	26	strong	strong	ADJ
ajst-28813	27	27	capabilities	capability	NOUN
ajst-28813	27	28	for	for	ADP
ajst-28813	27	29	processing	processing	NOUN
ajst-28813	27	30	time	time	NOUN
ajst-28813	27	31	series	series	PROPN
ajst-28813	27	32	data	data	PROPN
ajst-28813	27	33	.	.	PUNCT
ajst-28813	28	1	its	its	PRON
ajst-28813	28	2	model	model	NOUN
ajst-28813	28	3	structure	structure	NOUN
ajst-28813	28	4	is	be	AUX
ajst-28813	28	5	shown	show	VERB
ajst-28813	28	6	in	in	ADP
ajst-28813	28	7	figure	figure	NOUN
ajst-28813	28	8	1	1	NUM
ajst-28813	28	9	-	-	SYM
ajst-28813	28	10	3	3	NUM
ajst-28813	28	11	,	,	PUNCT
ajst-28813	28	12	where	where	SCONJ
ajst-28813	28	13	the	the	DET
ajst-28813	28	14	blue	blue	ADJ
ajst-28813	28	15	circle	circle	NOUN
ajst-28813	28	16	part	part	NOUN
ajst-28813	28	17	in	in	ADP
ajst-28813	28	18	the	the	DET
ajst-28813	28	19	diagram	diagram	NOUN
ajst-28813	28	20	represents	represent	VERB
ajst-28813	28	21	the	the	DET
ajst-28813	28	22	hidden	hidden	ADJ
ajst-28813	28	23	layer	layer	NOUN
ajst-28813	28	24	of	of	ADP
ajst-28813	28	25	the	the	DET
ajst-28813	28	26	esn	esn	PROPN
ajst-28813	28	27	network	network	NOUN
ajst-28813	28	28	,	,	PUNCT
ajst-28813	28	29	consisting	consist	VERB
ajst-28813	28	30	of	of	ADP
ajst-28813	28	31	a	a	DET
ajst-28813	28	32	large	large	ADJ
ajst-28813	28	33	number	number	NOUN
ajst-28813	28	34	of	of	ADP
ajst-28813	28	35	neurons	neuron	NOUN
ajst-28813	28	36	.	.	PUNCT
ajst-28813	29	1	the	the	DET
ajst-28813	29	2	neurons	neuron	NOUN
ajst-28813	29	3	are	be	AUX
ajst-28813	29	4	sparsely	sparsely	ADV
ajst-28813	29	5	connected	connect	VERB
ajst-28813	29	6	with	with	ADP
ajst-28813	29	7	each	each	DET
ajst-28813	29	8	other	other	ADJ
ajst-28813	29	9	,	,	PUNCT
ajst-28813	29	10	and	and	CCONJ
ajst-28813	29	11	the	the	DET
ajst-28813	29	12	connection	connection	NOUN
ajst-28813	29	13	weights	weight	NOUN
ajst-28813	29	14	are	be	AUX
ajst-28813	29	15	randomly	randomly	ADV
ajst-28813	29	16	generated	generate	VERB
ajst-28813	29	17	and	and	CCONJ
ajst-28813	29	18	remain	remain	VERB
ajst-28813	29	19	fixed	fix	VERB
ajst-28813	29	20	after	after	ADP
ajst-28813	29	21	generation	generation	NOUN
ajst-28813	29	22	,	,	PUNCT
ajst-28813	29	23	meaning	mean	VERB
ajst-28813	29	24	that	that	SCONJ
ajst-28813	29	25	the	the	DET
ajst-28813	29	26	connection	connection	NOUN
ajst-28813	29	27	weights	weight	NOUN
ajst-28813	29	28	of	of	ADP
ajst-28813	29	29	the	the	DET
ajst-28813	29	30	hidden	hide	VERB
ajst-28813	29	31	layer	layer	NOUN
ajst-28813	29	32	do	do	AUX
ajst-28813	29	33	not	not	PART
ajst-28813	29	34	require	require	VERB
ajst-28813	29	35	training	training	NOUN
ajst-28813	29	36	.	.	PUNCT
ajst-28813	30	1	input	input	NOUN
ajst-28813	30	2	data	datum	NOUN
ajst-28813	30	3	enters	enter	VERB
ajst-28813	30	4	the	the	DET
ajst-28813	30	5	hidden	hide	VERB
ajst-28813	30	6	layer	layer	NOUN
ajst-28813	30	7	through	through	ADP
ajst-28813	30	8	the	the	DET
ajst-28813	30	9	input	input	NOUN
ajst-28813	30	10	layer	layer	NOUN
ajst-28813	30	11	,	,	PUNCT
ajst-28813	30	12	and	and	CCONJ
ajst-28813	30	13	the	the	DET
ajst-28813	30	14	hidden	hide	VERB
ajst-28813	30	15	layer	layer	NOUN
ajst-28813	30	16	then	then	ADV
ajst-28813	30	17	transforms	transform	VERB
ajst-28813	30	18	the	the	DET
ajst-28813	30	19	input	input	NOUN
ajst-28813	30	20	data	datum	NOUN
ajst-28813	30	21	into	into	ADP
ajst-28813	30	22	a	a	DET
ajst-28813	30	23	high	high	ADJ
ajst-28813	30	24	-	-	PUNCT
ajst-28813	30	25	dimensional	dimensional	ADJ
ajst-28813	30	26	space	space	NOUN
ajst-28813	30	27	,	,	PUNCT
ajst-28813	30	28	with	with	ADP
ajst-28813	30	29	the	the	DET
ajst-28813	30	30	final	final	ADJ
ajst-28813	30	31	results	result	NOUN
ajst-28813	30	32	output	output	NOUN
ajst-28813	30	33	by	by	ADP
ajst-28813	30	34	the	the	DET
ajst-28813	30	35	output	output	NOUN
ajst-28813	30	36	layer	layer	NOUN
ajst-28813	30	37	.	.	PUNCT
ajst-28813	31	1	the	the	DET
ajst-28813	31	2	esn	esn	PROPN
ajst-28813	31	3	network	network	PROPN
ajst-28813	31	4	serves	serve	VERB
ajst-28813	31	5	as	as	ADP
ajst-28813	31	6	a	a	DET
ajst-28813	31	7	black	black	ADJ
ajst-28813	31	8	-	-	PUNCT
ajst-28813	31	9	box	box	NOUN
ajst-28813	31	10	model	model	NOUN
ajst-28813	31	11	in	in	ADP
ajst-28813	31	12	electric	electric	ADJ
ajst-28813	31	13	submersible	submersible	ADJ
ajst-28813	31	14	pump	pump	NOUN
ajst-28813	31	15	control	control	NOUN
ajst-28813	31	16	systems	system	NOUN
ajst-28813	31	17	.	.	PUNCT
ajst-28813	32	1	in	in	ADP
ajst-28813	32	2	figure	figure	NOUN
ajst-28813	32	3	1	1	NUM
ajst-28813	32	4	-	-	SYM
ajst-28813	32	5	3	3	NUM
ajst-28813	32	6	,	,	PUNCT
ajst-28813	32	7	the	the	DET
ajst-28813	32	8	number	number	NOUN
ajst-28813	32	9	of	of	ADP
ajst-28813	32	10	nodes	node	NOUN
ajst-28813	32	11	in	in	ADP
ajst-28813	32	12	the	the	DET
ajst-28813	32	13	input	input	NOUN
ajst-28813	32	14	layer	layer	NOUN
ajst-28813	32	15	,	,	PUNCT
ajst-28813	32	16	hidden	hide	VERB
ajst-28813	32	17	layer	layer	NOUN
ajst-28813	32	18	,	,	PUNCT
ajst-28813	32	19	and	and	CCONJ
ajst-28813	32	20	output	output	NOUN
ajst-28813	32	21	layer	layer	NOUN
ajst-28813	32	22	are	be	AUX
ajst-28813	32	23	respectively	respectively	ADV
ajst-28813	32	24	in	in	ADV
ajst-28813	32	25	,	,	PUNCT
ajst-28813	32	26	rn	rn	PROPN
ajst-28813	32	27	,	,	PUNCT
ajst-28813	32	28	0n	0n	NOUN
ajst-28813	32	29	,	,	PUNCT
ajst-28813	32	30	with	with	ADP
ajst-28813	32	31	the	the	DET
ajst-28813	32	32	current	current	ADJ
ajst-28813	32	33	time	time	NOUN
ajst-28813	32	34	step	step	NOUN
ajst-28813	32	35	input	input	NOUN
ajst-28813	32	36	being	be	AUX
ajst-28813	32	37	in	in	ADP
ajst-28813	32	38	tx	tx	PROPN
ajst-28813	32	39	r	r	PROPN
ajst-28813	32	40	.	.	PUNCT
ajst-28813	33	1	the	the	DET
ajst-28813	33	2	outputs	output	NOUN
ajst-28813	33	3	of	of	ADP
ajst-28813	33	4	the	the	DET
ajst-28813	33	5	hidden	hide	VERB
ajst-28813	33	6	layer	layer	NOUN
ajst-28813	33	7	rn	rn	PROPN
ajst-28813	33	8	th	th	X
ajst-28813	33	9	r	r	PROPN
ajst-28813	33	10	and	and	CCONJ
ajst-28813	33	11	the	the	DET
ajst-28813	33	12	output	output	NOUN
ajst-28813	33	13	layer	layer	NOUN
ajst-28813	33	14	0n	0n	NOUN
ajst-28813	33	15	ty	ty	NUM
ajst-28813	33	16	r	r	PROPN
ajst-28813	33	17	can	can	AUX
ajst-28813	33	18	be	be	AUX
ajst-28813	33	19	calculated	calculate	VERB
ajst-28813	33	20	as	as	SCONJ
ajst-28813	33	21	follows	follow	VERB
ajst-28813	33	22	:	:	PUNCT
ajst-28813	33	23			NOUN
ajst-28813	34	1			SYM
ajst-28813	34	2			NOUN
ajst-28813	34	3			PUNCT
ajst-28813	34	4			NOUN
ajst-28813	34	5			NOUN
ajst-28813	34	6	1	1	VERB
ajst-28813	34	7	1	1	NUM
ajst-28813	34	8	t	t	NOUN
ajst-28813	34	9	t	t	NOUN
ajst-28813	34	10	ti	ti	NOUN
ajst-28813	34	11	r	r	NOUN
ajst-28813	34	12	b	b	PROPN
ajst-28813	34	13	r	r	NOUN
ajst-28813	34	14	t	t	PROPN
ajst-28813	34	15	t	t	NOUN
ajst-28813	34	16	t	t	PROPN
ajst-28813	34	17	th	th	X
ajst-28813	34	18	f	f	PROPN
ajst-28813	34	19	w	w	PROPN
ajst-28813	34	20	x	x	PROPN
ajst-28813	34	21	w	w	PROPN
ajst-28813	34	22	h	h	PROPN
ajst-28813	34	23	w	w	PROPN
ajst-28813	34	24	y	y	PROPN
ajst-28813	34	25	b	b	ADV
ajst-28813	34	26			PROPN
ajst-28813	34	27			PUNCT
ajst-28813	34	28			PROPN
ajst-28813	34	29			X
ajst-28813	34	30	(	(	PUNCT
ajst-28813	34	31	1	1	NUM
ajst-28813	34	32	-	-	SYM
ajst-28813	34	33	2	2	NUM
ajst-28813	34	34	)	)	PUNCT
ajst-28813	34	35	0	0	NUM
ajst-28813	34	36	0	0	NUM
ajst-28813	34	37	1	1	NUM
ajst-28813	34	38	1	1	NUM
ajst-28813	34	39	1	1	NUM
ajst-28813	34	40	,	,	PUNCT
ajst-28813	34	41	,	,	PUNCT
ajst-28813	34	42	t	t	PROPN
ajst-28813	34	43	tt	tt	PROPN
ajst-28813	34	44	t	t	PROPN
ajst-28813	34	45	t	t	PROPN
ajst-28813	34	46	tt	tt	PROPN
ajst-28813	35	1	t	t	PROPN
ajst-28813	35	2	t	t	PROPN
ajst-28813	35	3	t	t	PROPN
ajst-28813	35	4	ty	ty	INTJ
ajst-28813	35	5	w	w	NOUN
ajst-28813	35	6	x	x	PUNCT
ajst-28813	35	7	h	h	NOUN
ajst-28813	35	8	y	y	PROPN
ajst-28813	35	9	b	b	ADV
ajst-28813	35	10			PROPN
ajst-28813	35	11			PROPN
ajst-28813	35	12			NOUN
ajst-28813	35	13			PROPN
ajst-28813	35	14			PROPN
ajst-28813	36	1			PROPN
ajst-28813	36	2			PROPN
ajst-28813	37	1			PROPN
ajst-28813	37	2			PROPN
ajst-28813	37	3			PROPN
ajst-28813	37	4			PROPN
ajst-28813	37	5			VERB
ajst-28813	37	6			PROPN
ajst-28813	37	7			VERB
ajst-28813	37	8			NOUN
ajst-28813	37	9			NOUN
ajst-28813	37	10			PUNCT
ajst-28813	37	11	(	(	PUNCT
ajst-28813	37	12	1	1	NUM
ajst-28813	37	13	-	-	SYM
ajst-28813	37	14	3	3	NUM
ajst-28813	37	15	)	)	PUNCT
ajst-28813	37	16	among	among	ADP
ajst-28813	37	17	them	they	PRON
ajst-28813	37	18	,	,	PUNCT
ajst-28813	37	19			PROPN
ajst-28813	37	20	f	f	ADV
ajst-28813	37	21			PRON
ajst-28813	37	22	is	be	AUX
ajst-28813	37	23	the	the	DET
ajst-28813	37	24	activation	activation	NOUN
ajst-28813	37	25	function	function	NOUN
ajst-28813	37	26	of	of	ADP
ajst-28813	37	27	the	the	DET
ajst-28813	37	28	hidden	hide	VERB
ajst-28813	37	29	layer	layer	NOUN
ajst-28813	37	30	,	,	PUNCT
ajst-28813	37	31	usually	usually	ADV
ajst-28813	37	32	using	use	VERB
ajst-28813	37	33	a	a	DET
ajst-28813	37	34	nonlinear	nonlinear	ADJ
ajst-28813	37	35	function	function	NOUN
ajst-28813	37	36	(	(	PUNCT
ajst-28813	37	37	such	such	ADJ
ajst-28813	37	38	as	as	ADP
ajst-28813	37	39	the	the	DET
ajst-28813	37	40	tanh	tanh	PROPN
ajst-28813	37	41	function	function	NOUN
ajst-28813	37	42	,	,	PUNCT
ajst-28813	37	43	relu	relu	NOUN
ajst-28813	37	44	function	function	NOUN
ajst-28813	37	45	,	,	PUNCT
ajst-28813	37	46	and	and	CCONJ
ajst-28813	37	47	sigmoid	sigmoid	NOUN
ajst-28813	37	48	function	function	NOUN
ajst-28813	37	49	,	,	PUNCT
ajst-28813	37	50	etc	etc	X
ajst-28813	37	51	.	.	X
ajst-28813	37	52	,	,	PUNCT
ajst-28813	37	53	as	as	SCONJ
ajst-28813	37	54	shown	show	VERB
ajst-28813	37	55	in	in	ADP
ajst-28813	37	56	figure	figure	NOUN
ajst-28813	37	57	1	1	NUM
ajst-28813	37	58	-	-	SYM
ajst-28813	37	59	3)[13	3)[13	NOUN
ajst-28813	37	60	]	]	PUNCT
ajst-28813	37	61	,	,	PUNCT
ajst-28813	37	62	the	the	DET
ajst-28813	37	63	activation	activation	NOUN
ajst-28813	37	64	function	function	NOUN
ajst-28813	37	65	forces	force	VERB
ajst-28813	37	66	the	the	DET
ajst-28813	37	67	output	output	NOUN
ajst-28813	37	68	values	value	NOUN
ajst-28813	37	69	to	to	PART
ajst-28813	37	70	be	be	AUX
ajst-28813	37	71	between	between	ADP
ajst-28813	37	72	-1	-1	PUNCT
ajst-28813	37	73	and	and	CCONJ
ajst-28813	37	74	1	1	NUM
ajst-28813	37	75	;	;	PUNCT
ajst-28813	37	76			NOUN
ajst-28813	37	77			NUM
ajst-28813	37	78			PRON
ajst-28813	37	79	is	be	AUX
ajst-28813	37	80	the	the	DET
ajst-28813	37	81	activation	activation	NOUN
ajst-28813	37	82	function	function	NOUN
ajst-28813	37	83	of	of	ADP
ajst-28813	37	84	the	the	DET
ajst-28813	37	85	output	output	NOUN
ajst-28813	37	86	layer	layer	NOUN
ajst-28813	37	87	,	,	PUNCT
ajst-28813	37	88	generally	generally	ADV
ajst-28813	37	89	using	use	VERB
ajst-28813	37	90	a	a	DET
ajst-28813	37	91	linear	linear	ADJ
ajst-28813	37	92	function	function	NOUN
ajst-28813	37	93	or	or	CCONJ
ajst-28813	37	94	a	a	DET
ajst-28813	37	95	nonlinear	nonlinear	ADJ
ajst-28813	37	96	activation	activation	NOUN
ajst-28813	37	97	function	function	NOUN
ajst-28813	37	98	with	with	ADP
ajst-28813	37	99	an	an	DET
ajst-28813	37	100	inverse	inverse	NOUN
ajst-28813	37	101	function	function	NOUN
ajst-28813	37	102	;	;	PUNCT
ajst-28813	37	103	i	i	PROPN
ajst-28813	37	104	rn	rn	PROPN
ajst-28813	37	105	niw	niw	PROPN
ajst-28813	37	106	r	r	NOUN
ajst-28813	37	107			NOUN
ajst-28813	37	108	is	be	AUX
ajst-28813	37	109	the	the	DET
ajst-28813	37	110	connection	connection	NOUN
ajst-28813	37	111	weight	weight	NOUN
ajst-28813	37	112	matrix	matrix	NOUN
ajst-28813	37	113	from	from	ADP
ajst-28813	37	114	the	the	DET
ajst-28813	37	115	input	input	NOUN
ajst-28813	37	116	layer	layer	NOUN
ajst-28813	37	117	to	to	ADP
ajst-28813	37	118	the	the	DET
ajst-28813	37	119	hidden	hide	VERB
ajst-28813	37	120	layer	layer	NOUN
ajst-28813	37	121	;	;	PUNCT
ajst-28813	37	122	r	r	PROPN
ajst-28813	37	123	rn	rn	PROPN
ajst-28813	37	124	nrw	nrw	PROPN
ajst-28813	37	125	r	r	NOUN
ajst-28813	37	126			NOUN
ajst-28813	37	127	is	be	AUX
ajst-28813	37	128	the	the	DET
ajst-28813	37	129	connection	connection	NOUN
ajst-28813	37	130	weight	weight	NOUN
ajst-28813	37	131	matrix	matrix	NOUN
ajst-28813	37	132	from	from	ADP
ajst-28813	37	133	the	the	DET
ajst-28813	37	134	input	input	NOUN
ajst-28813	37	135	layer	layer	NOUN
ajst-28813	37	136	to	to	ADP
ajst-28813	37	137	the	the	DET
ajst-28813	37	138	hidden	hide	VERB
ajst-28813	37	139	layer	layer	NOUN
ajst-28813	37	140	;	;	PUNCT
ajst-28813	37	141	0	0	NUM
ajst-28813	37	142	rn	rn	NOUN
ajst-28813	37	143	nbw	nbw	ADV
ajst-28813	37	144	r	r	NOUN
ajst-28813	37	145			NOUN
ajst-28813	37	146	is	be	AUX
ajst-28813	37	147	the	the	DET
ajst-28813	37	148	connection	connection	NOUN
ajst-28813	37	149	weight	weight	NOUN
ajst-28813	37	150	matrix	matrix	NOUN
ajst-28813	37	151	from	from	ADP
ajst-28813	37	152	the	the	DET
ajst-28813	37	153	output	output	NOUN
ajst-28813	37	154	layer	layer	NOUN
ajst-28813	37	155	to	to	ADP
ajst-28813	37	156	the	the	DET
ajst-28813	37	157	hidden	hide	VERB
ajst-28813	37	158	layer	layer	NOUN
ajst-28813	37	159	;	;	PUNCT
ajst-28813	37	160			NOUN
ajst-28813	37	161	0	0	NOUN
ajst-28813	37	162	0	0	NUM
ajst-28813	37	163	0	0	NUM
ajst-28813	37	164	1	1	NUM
ajst-28813	37	165	i	i	NOUN
ajst-28813	37	166	rn	rn	PROPN
ajst-28813	37	167	n	n	PROPN
ajst-28813	37	168	n	n	CCONJ
ajst-28813	37	169	n	n	ADV
ajst-28813	37	170	tw	tw	NOUN
ajst-28813	37	171	r	r	NOUN
ajst-28813	37	172			ADV
ajst-28813	37	173			X
ajst-28813	37	174			AUX
ajst-28813	37	175			PROPN
ajst-28813	37	176			PROPN
ajst-28813	37	177			PRON
ajst-28813	37	178	is	be	AUX
ajst-28813	37	179	the	the	DET
ajst-28813	37	180	connection	connection	NOUN
ajst-28813	37	181	weight	weight	NOUN
ajst-28813	37	182	matrix	matrix	NOUN
ajst-28813	37	183	between	between	ADP
ajst-28813	37	184	the	the	DET
ajst-28813	37	185	input	input	NOUN
ajst-28813	37	186	layer	layer	NOUN
ajst-28813	37	187	to	to	ADP
ajst-28813	37	188	the	the	DET
ajst-28813	37	189	output	output	NOUN
ajst-28813	37	190	layer	layer	NOUN
ajst-28813	37	191	,	,	PUNCT
ajst-28813	37	192	the	the	DET
ajst-28813	37	193	output	output	NOUN
ajst-28813	37	194	layer	layer	NOUN
ajst-28813	37	195	to	to	ADP
ajst-28813	37	196	the	the	DET
ajst-28813	37	197	hidden	hide	VERB
ajst-28813	37	198	layer	layer	NOUN
ajst-28813	37	199	,	,	PUNCT
ajst-28813	37	200	and	and	CCONJ
ajst-28813	37	201	within	within	ADP
ajst-28813	37	202	the	the	DET
ajst-28813	37	203	output	output	NOUN
ajst-28813	37	204	layer	layer	NOUN
ajst-28813	37	205	neurons	neuron	NOUN
ajst-28813	37	206	;	;	PUNCT
ajst-28813	37	207	rn	rn	PROPN
ajst-28813	37	208	rb	rb	PROPN
ajst-28813	37	209	r	r	PROPN
ajst-28813	37	210	and	and	CCONJ
ajst-28813	37	211	00	00	NUM
ajst-28813	37	212	1	1	NUM
ajst-28813	37	213	n	n	NOUN
ajst-28813	37	214	tb	tb	ADP
ajst-28813	37	215	r	r	NOUN
ajst-28813	37	216			NOUN
ajst-28813	37	217	are	be	AUX
ajst-28813	37	218	the	the	DET
ajst-28813	37	219	bias	bias	NOUN
ajst-28813	37	220	vectors	vector	NOUN
ajst-28813	37	221	for	for	ADP
ajst-28813	37	222	the	the	DET
ajst-28813	37	223	hidden	hide	VERB
ajst-28813	37	224	layer	layer	NOUN
ajst-28813	37	225	and	and	CCONJ
ajst-28813	37	226	the	the	DET
ajst-28813	37	227	output	output	NOUN
ajst-28813	37	228	layer	layer	NOUN
ajst-28813	37	229	,	,	PUNCT
ajst-28813	37	230	respectively	respectively	ADV
ajst-28813	37	231	.	.	PUNCT
ajst-28813	38	1	figure	figure	VERB
ajst-28813	38	2	1	1	NUM
ajst-28813	38	3	-	-	SYM
ajst-28813	38	4	3	3	NUM
ajst-28813	38	5	.	.	PUNCT
ajst-28813	38	6	schematic	schematic	ADJ
ajst-28813	38	7	diagram	diagram	NOUN
ajst-28813	38	8	of	of	ADP
ajst-28813	38	9	the	the	DET
ajst-28813	38	10	esn	esn	PROPN
ajst-28813	38	11	network	network	NOUN
ajst-28813	38	12	structure	structure	NOUN
ajst-28813	38	13	it	it	PRON
ajst-28813	38	14	should	should	AUX
ajst-28813	38	15	be	be	AUX
ajst-28813	38	16	noted	note	VERB
ajst-28813	38	17	that	that	SCONJ
ajst-28813	38	18	the	the	DET
ajst-28813	38	19	connection	connection	NOUN
ajst-28813	38	20	weight	weight	NOUN
ajst-28813	38	21	matrix	matrix	NOUN
ajst-28813	38	22	246	246	NUM
ajst-28813	38	23	between	between	ADP
ajst-28813	38	24	the	the	DET
ajst-28813	38	25	internal	internal	ADJ
ajst-28813	38	26	neurons	neuron	NOUN
ajst-28813	38	27	of	of	ADP
ajst-28813	38	28	the	the	DET
ajst-28813	38	29	output	output	NOUN
ajst-28813	38	30	layer	layer	NOUN
ajst-28813	38	31	in	in	ADP
ajst-28813	38	32	figure	figure	NOUN
ajst-28813	38	33	1	1	NUM
ajst-28813	38	34	-	-	SYM
ajst-28813	38	35	3	3	NUM
ajst-28813	38	36	is	be	AUX
ajst-28813	38	37	generally	generally	ADV
ajst-28813	38	38	not	not	PART
ajst-28813	38	39	used	use	VERB
ajst-28813	38	40	,	,	PUNCT
ajst-28813	38	41	while	while	SCONJ
ajst-28813	38	42	the	the	DET
ajst-28813	38	43	connection	connection	NOUN
ajst-28813	38	44	weight	weight	NOUN
ajst-28813	38	45	matrix	matrix	NOUN
ajst-28813	38	46	from	from	ADP
ajst-28813	38	47	the	the	DET
ajst-28813	38	48	output	output	NOUN
ajst-28813	38	49	layer	layer	NOUN
ajst-28813	38	50	to	to	ADP
ajst-28813	38	51	the	the	DET
ajst-28813	38	52	hidden	hide	VERB
ajst-28813	38	53	layer	layer	NOUN
ajst-28813	38	54	is	be	AUX
ajst-28813	38	55	optional	optional	ADJ
ajst-28813	38	56	.	.	PUNCT
ajst-28813	39	1	in	in	ADP
ajst-28813	39	2	the	the	DET
ajst-28813	39	3	actual	actual	ADJ
ajst-28813	39	4	construction	construction	NOUN
ajst-28813	39	5	of	of	ADP
ajst-28813	39	6	the	the	DET
ajst-28813	39	7	model	model	NOUN
ajst-28813	39	8	,	,	PUNCT
ajst-28813	39	9	this	this	DET
ajst-28813	39	10	thesis	thesis	NOUN
ajst-28813	39	11	will	will	AUX
ajst-28813	39	12	not	not	PART
ajst-28813	39	13	consider	consider	VERB
ajst-28813	39	14	these	these	DET
ajst-28813	39	15	two	two	NUM
ajst-28813	39	16	parts	part	NOUN
ajst-28813	39	17	of	of	ADP
ajst-28813	39	18	the	the	DET
ajst-28813	39	19	connection	connection	NOUN
ajst-28813	39	20	weight	weight	NOUN
ajst-28813	39	21	matrix	matrix	NOUN
ajst-28813	39	22	,	,	PUNCT
ajst-28813	39	23	but	but	CCONJ
ajst-28813	39	24	instead	instead	ADV
ajst-28813	39	25	adopt	adopt	VERB
ajst-28813	39	26	only	only	ADV
ajst-28813	39	27	the	the	DET
ajst-28813	39	28	training	training	NOUN
ajst-28813	39	29	of	of	ADP
ajst-28813	39	30	the	the	DET
ajst-28813	39	31	connection	connection	NOUN
ajst-28813	39	32	weight	weight	NOUN
ajst-28813	39	33	matrix	matrix	NOUN
ajst-28813	39	34	from	from	ADP
ajst-28813	39	35	the	the	DET
ajst-28813	39	36	hidden	hide	VERB
ajst-28813	39	37	layer	layer	NOUN
ajst-28813	39	38	to	to	ADP
ajst-28813	39	39	the	the	DET
ajst-28813	39	40	output	output	NOUN
ajst-28813	39	41	layer	layer	NOUN
ajst-28813	39	42	.	.	PUNCT
ajst-28813	40	1	the	the	DET
ajst-28813	40	2	calculation	calculation	NOUN
ajst-28813	40	3	method	method	NOUN
ajst-28813	40	4	for	for	ADP
ajst-28813	40	5	the	the	DET
ajst-28813	40	6	hidden	hide	VERB
ajst-28813	40	7	layer	layer	NOUN
ajst-28813	40	8	output	output	NOUN
ajst-28813	40	9	and	and	CCONJ
ajst-28813	40	10	the	the	DET
ajst-28813	40	11	output	output	NOUN
ajst-28813	40	12	layer	layer	NOUN
ajst-28813	40	13	output	output	NOUN
ajst-28813	40	14	is	be	AUX
ajst-28813	40	15	changed	change	VERB
ajst-28813	40	16	to	to	ADP
ajst-28813	40	17	:	:	PUNCT
ajst-28813	40	18			NOUN
ajst-28813	40	19			SYM
ajst-28813	40	20			NOUN
ajst-28813	41	1			NOUN
ajst-28813	41	2	1	1	NOUN
ajst-28813	41	3	t	t	NOUN
ajst-28813	41	4	ti	ti	NOUN
ajst-28813	41	5	r	r	NOUN
ajst-28813	41	6	r	r	NOUN
ajst-28813	41	7	t	t	NOUN
ajst-28813	41	8	t	t	X
ajst-28813	41	9	th	th	X
ajst-28813	41	10	f	f	PROPN
ajst-28813	41	11	w	w	PROPN
ajst-28813	41	12	x	x	PROPN
ajst-28813	41	13	w	w	PROPN
ajst-28813	41	14	h	h	PROPN
ajst-28813	41	15	b	b	PROPN
ajst-28813	41	16			ADV
ajst-28813	41	17			X
ajst-28813	41	18	(	(	PUNCT
ajst-28813	41	19	1	1	NUM
ajst-28813	41	20	-	-	SYM
ajst-28813	41	21	4	4	NUM
ajst-28813	41	22	)	)	PUNCT
ajst-28813	41	23			NOUN
ajst-28813	41	24			NOUN
ajst-28813	42	1	0	0	NOUN
ajst-28813	42	2	0	0	NUM
ajst-28813	42	3	1	1	NUM
ajst-28813	42	4	1	1	NUM
ajst-28813	42	5	,	,	PUNCT
ajst-28813	42	6	t	t	PROPN
ajst-28813	42	7	tt	tt	PROPN
ajst-28813	42	8	t	t	PROPN
ajst-28813	42	9	t	t	PROPN
ajst-28813	42	10	t	t	PROPN
ajst-28813	42	11	t	t	PROPN
ajst-28813	42	12	t	t	PROPN
ajst-28813	42	13	ty	ty	INTJ
ajst-28813	42	14	w	w	NOUN
ajst-28813	42	15	x	x	PUNCT
ajst-28813	42	16	h	h	NOUN
ajst-28813	42	17	b	b	NOUN
ajst-28813	42	18			NOUN
ajst-28813	42	19			VERB
ajst-28813	42	20			PROPN
ajst-28813	42	21			NOUN
ajst-28813	42	22			NOUN
ajst-28813	42	23	(	(	PUNCT
ajst-28813	42	24	1	1	NUM
ajst-28813	42	25	-	-	SYM
ajst-28813	42	26	5	5	NUM
ajst-28813	42	27	)	)	PUNCT
ajst-28813	42	28	wherein	wherein	ADJ
ajst-28813	42	29	,	,	PUNCT
ajst-28813	42	30			PROPN
ajst-28813	42	31			PROPN
ajst-28813	42	32	00	00	PUNCT
ajst-28813	43	1	i	i	PRON
ajst-28813	43	2	rn	rn	PROPN
ajst-28813	43	3	n	n	PROPN
ajst-28813	43	4	nw	nw	PROPN
ajst-28813	43	5	r	r	NOUN
ajst-28813	43	6			X
ajst-28813	43	7			X
ajst-28813	43	8	represents	represent	VERB
ajst-28813	43	9	the	the	DET
ajst-28813	43	10	connection	connection	NOUN
ajst-28813	43	11	weight	weight	NOUN
ajst-28813	43	12	matrix	matrix	NOUN
ajst-28813	43	13	from	from	ADP
ajst-28813	43	14	the	the	DET
ajst-28813	43	15	input	input	NOUN
ajst-28813	43	16	layer	layer	NOUN
ajst-28813	43	17	and	and	CCONJ
ajst-28813	43	18	hidden	hidden	ADJ
ajst-28813	43	19	layers	layer	NOUN
ajst-28813	43	20	to	to	ADP
ajst-28813	43	21	the	the	DET
ajst-28813	43	22	output	output	NOUN
ajst-28813	43	23	layer[17	layer[17	PROPN
ajst-28813	43	24	]	]	PUNCT
ajst-28813	43	25	.	.	PUNCT
ajst-28813	44	1	unlike	unlike	ADP
ajst-28813	44	2	traditional	traditional	ADJ
ajst-28813	44	3	rnn	rnn	NOUN
ajst-28813	44	4	series	series	NOUN
ajst-28813	44	5	that	that	PRON
ajst-28813	44	6	require	require	VERB
ajst-28813	44	7	training	training	NOUN
ajst-28813	44	8	for	for	ADP
ajst-28813	44	9	all	all	DET
ajst-28813	44	10	connection	connection	NOUN
ajst-28813	44	11	weights	weight	NOUN
ajst-28813	44	12	,	,	PUNCT
ajst-28813	44	13	esn	esn	PROPN
ajst-28813	44	14	only	only	ADV
ajst-28813	44	15	requires	require	VERB
ajst-28813	44	16	training	training	NOUN
ajst-28813	44	17	for	for	ADP
ajst-28813	44	18	the	the	DET
ajst-28813	44	19	output	output	NOUN
ajst-28813	44	20	weight	weight	NOUN
ajst-28813	44	21	matrix	matrix	NOUN
ajst-28813	44	22	0w	0w	NOUN
ajst-28813	44	23	.	.	PUNCT
ajst-28813	45	1	the	the	DET
ajst-28813	45	2	input	input	NOUN
ajst-28813	45	3	weight	weight	NOUN
ajst-28813	45	4	matrix	matrix	NOUN
ajst-28813	45	5	iw	iw	PROPN
ajst-28813	45	6	of	of	ADP
ajst-28813	45	7	esn	esn	PROPN
ajst-28813	45	8	is	be	AUX
ajst-28813	45	9	determined	determine	VERB
ajst-28813	45	10	by	by	ADP
ajst-28813	45	11	random	random	ADJ
ajst-28813	45	12	generation	generation	NOUN
ajst-28813	45	13	during	during	ADP
ajst-28813	45	14	the	the	DET
ajst-28813	45	15	network	network	NOUN
ajst-28813	45	16	initialization	initialization	NOUN
ajst-28813	45	17	phase	phase	NOUN
ajst-28813	45	18	and	and	CCONJ
ajst-28813	45	19	remains	remain	VERB
ajst-28813	45	20	fixed	fix	VERB
ajst-28813	45	21	throughout	throughout	ADP
ajst-28813	45	22	subsequent	subsequent	ADJ
ajst-28813	45	23	training	training	NOUN
ajst-28813	45	24	processes	process	NOUN
ajst-28813	45	25	.	.	PUNCT
ajst-28813	46	1	these	these	DET
ajst-28813	46	2	weights	weight	NOUN
ajst-28813	46	3	are	be	AUX
ajst-28813	46	4	uniformly	uniformly	ADV
ajst-28813	46	5	distributed	distribute	VERB
ajst-28813	46	6	random	random	ADJ
ajst-28813	46	7	numbers	number	NOUN
ajst-28813	46	8	.	.	PUNCT
ajst-28813	47	1	they	they	PRON
ajst-28813	47	2	are	be	AUX
ajst-28813	47	3	also	also	ADV
ajst-28813	47	4	generated	generate	VERB
ajst-28813	47	5	randomly	randomly	ADV
ajst-28813	47	6	and	and	CCONJ
ajst-28813	47	7	remain	remain	VERB
ajst-28813	47	8	fixed	fix	VERB
ajst-28813	47	9	,	,	PUNCT
ajst-28813	47	10	but	but	CCONJ
ajst-28813	47	11	to	to	PART
ajst-28813	47	12	ensure	ensure	VERB
ajst-28813	47	13	the	the	DET
ajst-28813	47	14	echo	echo	NOUN
ajst-28813	47	15	state	state	NOUN
ajst-28813	47	16	property	property	NOUN
ajst-28813	47	17	of	of	ADP
ajst-28813	47	18	esn	esn	PROPN
ajst-28813	47	19	,	,	PUNCT
ajst-28813	47	20	the	the	DET
ajst-28813	47	21	spectral	spectral	ADJ
ajst-28813	47	22	radius	radius	PROPN
ajst-28813	47	23			PROPN
ajst-28813	47	24	rw	rw	NOUN
ajst-28813	47	25	must	must	AUX
ajst-28813	47	26	be	be	AUX
ajst-28813	47	27	less	less	ADJ
ajst-28813	47	28	than	than	ADP
ajst-28813	47	29	or	or	CCONJ
ajst-28813	47	30	equal	equal	ADJ
ajst-28813	47	31	to	to	ADP
ajst-28813	47	32	1	1	NUM
ajst-28813	47	33	.	.	PUNCT
ajst-28813	48	1	the	the	DET
ajst-28813	48	2	fewer	few	ADJ
ajst-28813	48	3	network	network	NOUN
ajst-28813	48	4	weight	weight	NOUN
ajst-28813	48	5	training	training	NOUN
ajst-28813	48	6	requirements	requirement	NOUN
ajst-28813	48	7	make	make	VERB
ajst-28813	48	8	the	the	DET
ajst-28813	48	9	structure	structure	NOUN
ajst-28813	48	10	of	of	ADP
ajst-28813	48	11	esn	esn	PROPN
ajst-28813	48	12	simpler	simple	ADJ
ajst-28813	48	13	and	and	CCONJ
ajst-28813	48	14	significantly	significantly	ADV
ajst-28813	48	15	reduce	reduce	VERB
ajst-28813	48	16	the	the	DET
ajst-28813	48	17	training	training	NOUN
ajst-28813	48	18	difficulty	difficulty	NOUN
ajst-28813	48	19	.	.	PUNCT
ajst-28813	49	1	figure	figure	VERB
ajst-28813	49	2	1	1	NUM
ajst-28813	49	3	-	-	SYM
ajst-28813	49	4	4	4	NUM
ajst-28813	49	5	.	.	PUNCT
ajst-28813	50	1	diagram	diagram	NOUN
ajst-28813	50	2	of	of	ADP
ajst-28813	50	3	different	different	ADJ
ajst-28813	50	4	types	type	NOUN
ajst-28813	50	5	of	of	ADP
ajst-28813	50	6	activation	activation	NOUN
ajst-28813	50	7	functions	function	NOUN
ajst-28813	50	8	2.2	2.2	NUM
ajst-28813	50	9	.	.	PUNCT
ajst-28813	51	1	key	key	ADJ
ajst-28813	51	2	parameters	parameter	NOUN
ajst-28813	51	3	of	of	ADP
ajst-28813	51	4	esn	esn	PROPN
ajst-28813	51	5	capacity	capacity	NOUN
ajst-28813	51	6	of	of	ADP
ajst-28813	51	7	the	the	DET
ajst-28813	51	8	hidden	hide	VERB
ajst-28813	51	9	layer．	layer．	NOUN
ajst-28813	51	10	the	the	DET
ajst-28813	51	11	hidden	hide	VERB
ajst-28813	51	12	layer	layer	NOUN
ajst-28813	51	13	is	be	AUX
ajst-28813	51	14	located	locate	VERB
ajst-28813	51	15	in	in	ADP
ajst-28813	51	16	the	the	DET
ajst-28813	51	17	middle	middle	NOUN
ajst-28813	51	18	of	of	ADP
ajst-28813	51	19	a	a	DET
ajst-28813	51	20	neural	neural	ADJ
ajst-28813	51	21	network	network	NOUN
ajst-28813	51	22	and	and	CCONJ
ajst-28813	51	23	is	be	AUX
ajst-28813	51	24	responsible	responsible	ADJ
ajst-28813	51	25	for	for	ADP
ajst-28813	51	26	information	information	NOUN
ajst-28813	51	27	processing	processing	NOUN
ajst-28813	51	28	and	and	CCONJ
ajst-28813	51	29	transmission	transmission	NOUN
ajst-28813	51	30	.	.	PUNCT
ajst-28813	52	1	the	the	DET
ajst-28813	52	2	capacity	capacity	NOUN
ajst-28813	52	3	of	of	ADP
ajst-28813	52	4	the	the	DET
ajst-28813	52	5	hidden	hide	VERB
ajst-28813	52	6	layer	layer	NOUN
ajst-28813	52	7	refers	refer	VERB
ajst-28813	52	8	to	to	ADP
ajst-28813	52	9	the	the	DET
ajst-28813	52	10	number	number	NOUN
ajst-28813	52	11	of	of	ADP
ajst-28813	52	12	neurons	neuron	NOUN
ajst-28813	52	13	within	within	ADP
ajst-28813	52	14	it	it	PRON
ajst-28813	52	15	,	,	PUNCT
ajst-28813	52	16	and	and	CCONJ
ajst-28813	52	17	generally	generally	ADV
ajst-28813	52	18	,	,	PUNCT
ajst-28813	52	19	the	the	PRON
ajst-28813	52	20	larger	large	ADJ
ajst-28813	52	21	the	the	DET
ajst-28813	52	22	scale	scale	NOUN
ajst-28813	52	23	,	,	PUNCT
ajst-28813	52	24	the	the	PRON
ajst-28813	52	25	higher	high	ADJ
ajst-28813	52	26	the	the	DET
ajst-28813	52	27	potential	potential	ADJ
ajst-28813	52	28	performance	performance	NOUN
ajst-28813	52	29	of	of	ADP
ajst-28813	52	30	the	the	DET
ajst-28813	52	31	network	network	NOUN
ajst-28813	52	32	.	.	PUNCT
ajst-28813	53	1	the	the	DET
ajst-28813	53	2	spectral	spectral	ADJ
ajst-28813	53	3	radius	radius	NOUN
ajst-28813	53	4	is	be	AUX
ajst-28813	53	5	the	the	DET
ajst-28813	53	6	spectral	spectral	ADJ
ajst-28813	53	7	radius	radius	NOUN
ajst-28813	53	8	of	of	ADP
ajst-28813	53	9	the	the	DET
ajst-28813	53	10	connection	connection	NOUN
ajst-28813	53	11	weight	weight	NOUN
ajst-28813	53	12	matrix	matrix	NOUN
ajst-28813	53	13	of	of	ADP
ajst-28813	53	14	the	the	DET
ajst-28813	53	15	hidden	hide	VERB
ajst-28813	53	16	layer	layer	NOUN
ajst-28813	53	17	,	,	PUNCT
ajst-28813	53	18	that	that	ADV
ajst-28813	53	19	is	is	ADV
ajst-28813	53	20	,	,	PUNCT
ajst-28813	53	21	the	the	DET
ajst-28813	53	22	maximum	maximum	NOUN
ajst-28813	53	23	of	of	ADP
ajst-28813	53	24	the	the	DET
ajst-28813	53	25	absolute	absolute	ADJ
ajst-28813	53	26	values	value	NOUN
ajst-28813	53	27	of	of	ADP
ajst-28813	53	28	all	all	DET
ajst-28813	53	29	eigenvalues	eigenvalue	NOUN
ajst-28813	53	30	.	.	PUNCT
ajst-28813	54	1	the	the	DET
ajst-28813	54	2	spectral	spectral	ADJ
ajst-28813	54	3	radius	radius	NOUN
ajst-28813	54	4	determines	determine	VERB
ajst-28813	54	5	the	the	DET
ajst-28813	54	6	speed	speed	NOUN
ajst-28813	54	7	at	at	ADP
ajst-28813	54	8	which	which	PRON
ajst-28813	54	9	the	the	DET
ajst-28813	54	10	input	input	NOUN
ajst-28813	54	11	causes	cause	VERB
ajst-28813	54	12	the	the	DET
ajst-28813	54	13	reservoir	reservoir	PROPN
ajst-28813	54	14	state	state	NOUN
ajst-28813	54	15	to	to	PART
ajst-28813	54	16	decay	decay	VERB
ajst-28813	54	17	over	over	ADP
ajst-28813	54	18	time	time	NOUN
ajst-28813	54	19	,	,	PUNCT
ajst-28813	54	20	as	as	ADV
ajst-28813	54	21	well	well	ADV
ajst-28813	54	22	as	as	ADP
ajst-28813	54	23	the	the	DET
ajst-28813	54	24	stability	stability	NOUN
ajst-28813	54	25	of	of	ADP
ajst-28813	54	26	the	the	DET
ajst-28813	54	27	hidden	hide	VERB
ajst-28813	54	28	layer	layer	NOUN
ajst-28813	54	29	.	.	PUNCT
ajst-28813	55	1	the	the	DET
ajst-28813	55	2	neurons	neuron	NOUN
ajst-28813	55	3	inside	inside	ADP
ajst-28813	55	4	the	the	DET
ajst-28813	55	5	hidden	hide	VERB
ajst-28813	55	6	layer	layer	NOUN
ajst-28813	55	7	are	be	AUX
ajst-28813	55	8	required	require	VERB
ajst-28813	55	9	to	to	PART
ajst-28813	55	10	be	be	AUX
ajst-28813	55	11	sparsely	sparsely	ADV
ajst-28813	55	12	connected	connect	VERB
ajst-28813	55	13	,	,	PUNCT
ajst-28813	55	14	and	and	CCONJ
ajst-28813	55	15	the	the	DET
ajst-28813	55	16	leakage	leakage	NOUN
ajst-28813	55	17	rate	rate	NOUN
ajst-28813	55	18	is	be	AUX
ajst-28813	55	19	to	to	PART
ajst-28813	55	20	measure	measure	VERB
ajst-28813	55	21	the	the	DET
ajst-28813	55	22	degree	degree	NOUN
ajst-28813	55	23	of	of	ADP
ajst-28813	55	24	the	the	DET
ajst-28813	55	25	connection	connection	NOUN
ajst-28813	55	26	between	between	ADP
ajst-28813	55	27	the	the	DET
ajst-28813	55	28	neurons	neuron	NOUN
ajst-28813	55	29	inside	inside	ADP
ajst-28813	55	30	the	the	DET
ajst-28813	55	31	hidden	hide	VERB
ajst-28813	55	32	layer	layer	NOUN
ajst-28813	55	33	.	.	PUNCT
ajst-28813	56	1	it	it	PRON
ajst-28813	56	2	is	be	AUX
ajst-28813	56	3	the	the	DET
ajst-28813	56	4	ratio	ratio	NOUN
ajst-28813	56	5	of	of	ADP
ajst-28813	56	6	the	the	DET
ajst-28813	56	7	number	number	NOUN
ajst-28813	56	8	of	of	ADP
ajst-28813	56	9	neurons	neuron	NOUN
ajst-28813	56	10	in	in	ADP
ajst-28813	56	11	the	the	DET
ajst-28813	56	12	hidden	hide	VERB
ajst-28813	56	13	layer	layer	NOUN
ajst-28813	56	14	and	and	CCONJ
ajst-28813	56	15	the	the	DET
ajst-28813	56	16	total	total	ADJ
ajst-28813	56	17	number	number	NOUN
ajst-28813	56	18	of	of	ADP
ajst-28813	56	19	neurons	neuron	NOUN
ajst-28813	56	20	in	in	ADP
ajst-28813	56	21	the	the	DET
ajst-28813	56	22	hidden	hide	VERB
ajst-28813	56	23	layer	layer	NOUN
ajst-28813	56	24	,	,	PUNCT
ajst-28813	56	25	that	that	ADV
ajst-28813	56	26	is	is	ADV
ajst-28813	56	27	,	,	PUNCT
ajst-28813	56	28	the	the	DET
ajst-28813	56	29	number	number	NOUN
ajst-28813	56	30	of	of	ADP
ajst-28813	56	31	non	non	ADJ
ajst-28813	56	32	-	-	ADJ
ajst-28813	56	33	zero	zero	NUM
ajst-28813	56	34	elements	element	NOUN
ajst-28813	56	35	,	,	PUNCT
ajst-28813	56	36	and	and	CCONJ
ajst-28813	56	37	the	the	DET
ajst-28813	56	38	value	value	NOUN
ajst-28813	56	39	is	be	AUX
ajst-28813	56	40	between	between	ADP
ajst-28813	56	41	(	(	PUNCT
ajst-28813	56	42	0,1	0,1	NUM
ajst-28813	56	43	)	)	PUNCT
ajst-28813	56	44	.	.	PUNCT
ajst-28813	57	1	enter	enter	VERB
ajst-28813	57	2	the	the	DET
ajst-28813	57	3	scaling	scale	VERB
ajst-28813	57	4	factor	factor	NOUN
ajst-28813	57	5	,	,	PUNCT
ajst-28813	57	6	input	input	NOUN
ajst-28813	57	7	scaling	scaling	NOUN
ajst-28813	57	8	factor	factor	NOUN
ajst-28813	57	9	regulates	regulate	VERB
ajst-28813	57	10	the	the	DET
ajst-28813	57	11	effect	effect	NOUN
ajst-28813	57	12	of	of	ADP
ajst-28813	57	13	the	the	DET
ajst-28813	57	14	input	input	NOUN
ajst-28813	57	15	weight	weight	NOUN
ajst-28813	57	16	matrix	matrix	NOUN
ajst-28813	57	17	on	on	ADP
ajst-28813	57	18	the	the	DET
ajst-28813	57	19	network	network	NOUN
ajst-28813	57	20	.	.	PUNCT
ajst-28813	58	1	2.3	2.3	NUM
ajst-28813	58	2	.	.	PUNCT
ajst-28813	59	1	esn	esn	PROPN
ajst-28813	59	2	online	online	PROPN
ajst-28813	59	3	learning	learning	PROPN
ajst-28813	59	4	because	because	SCONJ
ajst-28813	59	5	the	the	DET
ajst-28813	59	6	esn	esn	PROPN
ajst-28813	59	7	network	network	PROPN
ajst-28813	59	8	model	model	NOUN
ajst-28813	59	9	of	of	ADP
ajst-28813	59	10	electric	electric	ADJ
ajst-28813	59	11	submersible	submersible	ADJ
ajst-28813	59	12	pump	pump	NOUN
ajst-28813	59	13	has	have	VERB
ajst-28813	59	14	a	a	DET
ajst-28813	59	15	large	large	ADJ
ajst-28813	59	16	amount	amount	NOUN
ajst-28813	59	17	of	of	ADP
ajst-28813	59	18	actual	actual	ADJ
ajst-28813	59	19	required	require	VERB
ajst-28813	59	20	prediction	prediction	NOUN
ajst-28813	59	21	data	datum	NOUN
ajst-28813	59	22	,	,	PUNCT
ajst-28813	59	23	it	it	PRON
ajst-28813	59	24	is	be	AUX
ajst-28813	59	25	iw	iw	ADJ
ajst-28813	59	26	and	and	CCONJ
ajst-28813	59	27	rw	rw	NOUN
ajst-28813	59	28	fixed	fix	VERB
ajst-28813	59	29	in	in	ADP
ajst-28813	59	30	the	the	DET
ajst-28813	59	31	initialization	initialization	NOUN
ajst-28813	59	32	stage	stage	NOUN
ajst-28813	59	33	of	of	ADP
ajst-28813	59	34	the	the	DET
ajst-28813	59	35	network	network	NOUN
ajst-28813	59	36	.	.	PUNCT
ajst-28813	60	1	in	in	ADP
ajst-28813	60	2	order	order	NOUN
ajst-28813	60	3	to	to	PART
ajst-28813	60	4	better	well	ADV
ajst-28813	60	5	iteratively	iteratively	ADV
ajst-28813	60	6	update	update	VERB
ajst-28813	60	7	the	the	DET
ajst-28813	60	8	esn	esn	PROPN
ajst-28813	60	9	's	's	PART
ajst-28813	60	10	output	output	NOUN
ajst-28813	60	11	weight	weight	NOUN
ajst-28813	60	12	matrix	matrix	NOUN
ajst-28813	60	13	online	online	ADV
ajst-28813	60	14	,	,	PUNCT
ajst-28813	60	15	the	the	DET
ajst-28813	60	16	constant	constant	ADJ
ajst-28813	60	17	mode	mode	NOUN
ajst-28813	60	18	recursive	recursive	ADJ
ajst-28813	60	19	least	least	ADJ
ajst-28813	60	20	squares	square	NOUN
ajst-28813	60	21	method	method	NOUN
ajst-28813	60	22	(	(	PUNCT
ajst-28813	60	23	rls	rls	PROPN
ajst-28813	60	24	)	)	PUNCT
ajst-28813	60	25	is	be	AUX
ajst-28813	60	26	adopted	adopt	VERB
ajst-28813	60	27	.	.	PUNCT
ajst-28813	61	1	let	let	VERB
ajst-28813	61	2	the	the	DET
ajst-28813	61	3	input	input	NOUN
ajst-28813	61	4	data	datum	NOUN
ajst-28813	61	5	at	at	ADP
ajst-28813	61	6	the	the	DET
ajst-28813	61	7	current	current	ADJ
ajst-28813	61	8	moment	moment	NOUN
ajst-28813	61	9	be	be	AUX
ajst-28813	61	10	tr	tr	VERB
ajst-28813	61	11	and	and	CCONJ
ajst-28813	61	12	the	the	DET
ajst-28813	61	13	corresponding	corresponding	ADJ
ajst-28813	61	14	expected	expect	VERB
ajst-28813	61	15	output	output	NOUN
ajst-28813	61	16	is	be	AUX
ajst-28813	61	17	for	for	ADP
ajst-28813	61	18	ˆty	ˆty	PROPN
ajst-28813	61	19	,	,	PUNCT
ajst-28813	61	20	and	and	CCONJ
ajst-28813	61	21	the	the	DET
ajst-28813	61	22	predicted	predict	VERB
ajst-28813	61	23	target	target	NOUN
ajst-28813	61	24	output	output	NOUN
ajst-28813	61	25	,	,	PUNCT
ajst-28813	61	26	defining	define	VERB
ajst-28813	61	27	its	its	PRON
ajst-28813	61	28	objective	objective	ADJ
ajst-28813	61	29	function	function	NOUN
ajst-28813	61	30	as	as	ADP
ajst-28813	61	31	:	:	PUNCT
ajst-28813	61	32			NOUN
ajst-28813	61	33			SYM
ajst-28813	61	34			NOUN
ajst-28813	61	35			NOUN
ajst-28813	62	1	2	2	ADJ
ajst-28813	62	2	0	0	NUM
ajst-28813	62	3	0	0	NUM
ajst-28813	62	4	1	1	NUM
ajst-28813	62	5	1	1	NUM
ajst-28813	62	6	ˆ	ˆ	NOUN
ajst-28813	62	7	2	2	NUM
ajst-28813	62	8	t	t	NOUN
ajst-28813	62	9	tt	tt	PROPN
ajst-28813	62	10	t	t	PROPN
ajst-28813	62	11	l	l	PROPN
ajst-28813	62	12	w	w	PROPN
ajst-28813	62	13	y	y	PROPN
ajst-28813	62	14	w	w	PROPN
ajst-28813	62	15	r	r	NOUN
ajst-28813	62	16			NOUN
ajst-28813	62	17			NOUN
ajst-28813	62	18			PROPN
ajst-28813	62	19			PROPN
ajst-28813	62	20			X
ajst-28813	62	21			X
ajst-28813	62	22	(	(	PUNCT
ajst-28813	62	23	1	1	NUM
ajst-28813	62	24	-	-	SYM
ajst-28813	62	25	6	6	NUM
ajst-28813	62	26	)	)	PUNCT
ajst-28813	62	27	where	where	SCONJ
ajst-28813	62	28			NOUN
ajst-28813	62	29	0,1	0,1	X
ajst-28813	62	30	is	be	AUX
ajst-28813	62	31	the	the	DET
ajst-28813	62	32	forgetting	forget	VERB
ajst-28813	62	33	factor	factor	NOUN
ajst-28813	62	34	,	,	PUNCT
ajst-28813	62	35	when	when	SCONJ
ajst-28813	62	36	close	close	ADV
ajst-28813	62	37	to	to	ADP
ajst-28813	62	38	1	1	NUM
ajst-28813	62	39	,	,	PUNCT
ajst-28813	62	40	the	the	DET
ajst-28813	62	41	current	current	ADJ
ajst-28813	62	42	model	model	NOUN
ajst-28813	62	43	will	will	AUX
ajst-28813	62	44	consider	consider	VERB
ajst-28813	62	45	the	the	DET
ajst-28813	62	46	impact	impact	NOUN
ajst-28813	62	47	of	of	ADP
ajst-28813	62	48	historical	historical	ADJ
ajst-28813	62	49	data	datum	NOUN
ajst-28813	62	50	,	,	PUNCT
ajst-28813	62	51	the	the	DET
ajst-28813	62	52	model	model	NOUN
ajst-28813	62	53	changes	change	VERB
ajst-28813	62	54	slowly	slowly	ADV
ajst-28813	62	55	when	when	SCONJ
ajst-28813	62	56	adapting	adapt	VERB
ajst-28813	62	57	to	to	ADP
ajst-28813	62	58	the	the	DET
ajst-28813	62	59	new	new	ADJ
ajst-28813	62	60	data	datum	NOUN
ajst-28813	62	61	;	;	PUNCT
ajst-28813	62	62	247	247	NUM
ajst-28813	62	63	when	when	SCONJ
ajst-28813	62	64	close	close	ADJ
ajst-28813	62	65	to	to	ADP
ajst-28813	62	66	0	0	NUM
ajst-28813	62	67	,	,	PUNCT
ajst-28813	62	68	the	the	DET
ajst-28813	62	69	model	model	NOUN
ajst-28813	62	70	will	will	AUX
ajst-28813	62	71	reduce	reduce	VERB
ajst-28813	62	72	the	the	DET
ajst-28813	62	73	weight	weight	NOUN
ajst-28813	62	74	of	of	ADP
ajst-28813	62	75	the	the	DET
ajst-28813	62	76	historical	historical	ADJ
ajst-28813	62	77	data	datum	NOUN
ajst-28813	62	78	,	,	PUNCT
ajst-28813	62	79	so	so	SCONJ
ajst-28813	62	80	as	as	SCONJ
ajst-28813	62	81	to	to	PART
ajst-28813	62	82	adapt	adapt	VERB
ajst-28813	62	83	to	to	ADP
ajst-28813	62	84	the	the	DET
ajst-28813	62	85	new	new	ADJ
ajst-28813	62	86	input	input	NOUN
ajst-28813	62	87	faster	fast	ADV
ajst-28813	62	88	.	.	PUNCT
ajst-28813	63	1	order	order	NOUN
ajst-28813	63	2			NOUN
ajst-28813	64	1	0	0	NOUN
ajst-28813	64	2	0	0	NUM
ajst-28813	64	3	0	0	NUM
ajst-28813	64	4	w	w	PROPN
ajst-28813	64	5	l	l	NOUN
ajst-28813	64	6	w	w	PROPN
ajst-28813	64	7			NUM
ajst-28813	64	8	,	,	PUNCT
ajst-28813	64	9	can	can	AUX
ajst-28813	64	10	get	get	VERB
ajst-28813	64	11	:	:	PUNCT
ajst-28813	64	12			NOUN
ajst-28813	64	13			PROPN
ajst-28813	64	14			NOUN
ajst-28813	65	1			PROPN
ajst-28813	65	2	*	*	SYM
ajst-28813	65	3	10	10	NUM
ajst-28813	65	4	1	1	NUM
ajst-28813	65	5	ˆ	ˆ	NOUN
ajst-28813	65	6	t	t	PROPN
ajst-28813	65	7	t	t	PROPN
ajst-28813	65	8	t	t	PROPN
ajst-28813	65	9	t	t	PROPN
ajst-28813	65	10	w	w	NOUN
ajst-28813	65	11	r	r	NOUN
ajst-28813	65	12	r	r	NOUN
ajst-28813	65	13	r	r	NOUN
ajst-28813	65	14	y	y	PROPN
ajst-28813	65	15			PROPN
ajst-28813	65	16			NOUN
ajst-28813	65	17			NOUN
ajst-28813	65	18			NOUN
ajst-28813	65	19			NOUN
ajst-28813	65	20			PROPN
ajst-28813	65	21			ADV
ajst-28813	65	22			ADP
ajst-28813	65	23	(	(	PUNCT
ajst-28813	65	24	1	1	NUM
ajst-28813	65	25	-	-	SYM
ajst-28813	65	26	7	7	NUM
ajst-28813	65	27	)	)	PUNCT
ajst-28813	65	28	sorting	sort	VERB
ajst-28813	65	29	out	out	ADP
ajst-28813	65	30	available	available	ADJ
ajst-28813	65	31	:	:	PUNCT
ajst-28813	65	32			NOUN
ajst-28813	65	33	*0	*0	SYM
ajst-28813	65	34	0	0	NUM
ajst-28813	65	35	1	1	NUM
ajst-28813	65	36	t	t	NOUN
ajst-28813	65	37	t	t	PROPN
ajst-28813	65	38	tw	tw	INTJ
ajst-28813	65	39	w	w	ADP
ajst-28813	65	40	a	a	PROPN
ajst-28813	65	41	b	b	PROPN
ajst-28813	65	42			NOUN
ajst-28813	65	43	(	(	PUNCT
ajst-28813	65	44	1	1	NUM
ajst-28813	65	45	-	-	NUM
ajst-28813	65	46	8)	8)	NUM
ajst-28813	65	47	among	among	ADP
ajst-28813	65	48	:	:	PUNCT
ajst-28813	65	49	1	1	NUM
ajst-28813	65	50	t	t	NOUN
ajst-28813	65	51	t	t	NOUN
ajst-28813	65	52	t	t	NOUN
ajst-28813	65	53	ta	ta	ADP
ajst-28813	65	54	r	r	NOUN
ajst-28813	65	55	r	r	NOUN
ajst-28813	65	56			NOUN
ajst-28813	65	57			NOUN
ajst-28813	65	58			VERB
ajst-28813	65	59			ADJ
ajst-28813	65	60			PROPN
ajst-28813	65	61	(	(	PUNCT
ajst-28813	65	62	1	1	NUM
ajst-28813	65	63	-	-	SYM
ajst-28813	65	64	9	9	NUM
ajst-28813	65	65	)	)	PUNCT
ajst-28813	65	66	1	1	NUM
ajst-28813	65	67	ˆ	ˆ	NOUN
ajst-28813	65	68	t	t	NOUN
ajst-28813	65	69	t	t	NOUN
ajst-28813	65	70	tb	tb	ADP
ajst-28813	65	71	r	r	NOUN
ajst-28813	65	72	y	y	NOUN
ajst-28813	65	73			NOUN
ajst-28813	65	74			NOUN
ajst-28813	65	75			VERB
ajst-28813	65	76			ADJ
ajst-28813	65	77			PROPN
ajst-28813	65	78	(	(	PUNCT
ajst-28813	65	79	1	1	NUM
ajst-28813	65	80	-	-	SYM
ajst-28813	65	81	10	10	NUM
ajst-28813	65	82	)	)	PUNCT
ajst-28813	65	83	order	order	NOUN
ajst-28813	65	84	,	,	PUNCT
ajst-28813	65	85	form	form	NOUN
ajst-28813	65	86	(	(	PUNCT
ajst-28813	65	87	1	1	NUM
ajst-28813	65	88	-	-	SYM
ajst-28813	65	89	9	9	NUM
ajst-28813	65	90	)	)	PUNCT
ajst-28813	65	91	and	and	CCONJ
ajst-28813	65	92	(	(	PUNCT
ajst-28813	65	93	1	1	NUM
ajst-28813	65	94	-	-	SYM
ajst-28813	65	95	10	10	NUM
ajst-28813	65	96	)	)	PUNCT
ajst-28813	65	97	write	write	NOUN
ajst-28813	65	98	:	:	PUNCT
ajst-28813	65	99	1	1	NUM
ajst-28813	65	100	t	t	NOUN
ajst-28813	65	101	t	t	PROPN
ajst-28813	65	102	t	t	PROPN
ajst-28813	65	103	t	t	X
ajst-28813	65	104	ta	ta	PROPN
ajst-28813	65	105	a	a	DET
ajst-28813	65	106	r	r	NOUN
ajst-28813	65	107	r	r	PROPN
ajst-28813	65	108			NOUN
ajst-28813	65	109			X
ajst-28813	65	110	(	(	PUNCT
ajst-28813	65	111	1	1	NUM
ajst-28813	65	112	-	-	SYM
ajst-28813	65	113	11	11	NUM
ajst-28813	65	114	)	)	PUNCT
ajst-28813	65	115	1	1	NUM
ajst-28813	65	116	ˆt	ˆt	NOUN
ajst-28813	65	117	tb	tb	ADP
ajst-28813	65	118	b	b	PROPN
ajst-28813	65	119	r	r	NOUN
ajst-28813	65	120	y	y	NOUN
ajst-28813	65	121			NOUN
ajst-28813	65	122			VERB
ajst-28813	65	123			ADJ
ajst-28813	65	124			X
ajst-28813	65	125	(	(	PUNCT
ajst-28813	65	126	1	1	NUM
ajst-28813	65	127	-	-	SYM
ajst-28813	65	128	12	12	NUM
ajst-28813	65	129	)	)	PUNCT
ajst-28813	65	130	on	on	ADP
ajst-28813	65	131	the	the	DET
ajst-28813	65	132	basis	basis	NOUN
ajst-28813	65	133	of	of	ADP
ajst-28813	65	134	equation	equation	NOUN
ajst-28813	65	135	(	(	PUNCT
ajst-28813	65	136	1	1	NUM
ajst-28813	65	137	-	-	SYM
ajst-28813	65	138	11	11	NUM
ajst-28813	65	139	)	)	PUNCT
ajst-28813	65	140	,	,	PUNCT
ajst-28813	65	141	by	by	ADP
ajst-28813	65	142	sherman	sherman	PROPN
ajst-28813	65	143	-	-	PUNCT
ajst-28813	65	144	morrisonwoodbury	morrisonwoodbury	NOUN
ajst-28813	65	145	formula	formula	NOUN
ajst-28813	65	146	,	,	PUNCT
ajst-28813	65	147	the	the	DET
ajst-28813	65	148	recursion	recursion	NOUN
ajst-28813	65	149	is	be	AUX
ajst-28813	65	150	rewritten	rewrite	VERB
ajst-28813	65	151	as	as	ADP
ajst-28813	65	152	:	:	SYM
ajst-28813	65	153	1	1	NUM
ajst-28813	65	154	1	1	NUM
ajst-28813	65	155	1	1	NUM
ajst-28813	65	156	t	t	NOUN
ajst-28813	65	157	t	t	PROPN
ajst-28813	65	158	t	t	PROPN
ajst-28813	65	159	t	t	PROPN
ajst-28813	65	160	tp	tp	ADP
ajst-28813	65	161	p	p	PROPN
ajst-28813	65	162	g	g	PROPN
ajst-28813	66	1	u	u	PROPN
ajst-28813	66	2			PROPN
ajst-28813	66	3			X
ajst-28813	66	4			X
ajst-28813	66	5	(	(	PUNCT
ajst-28813	66	6	1	1	NUM
ajst-28813	66	7	-	-	SYM
ajst-28813	66	8	13	13	NUM
ajst-28813	66	9	)	)	PUNCT
ajst-28813	66	10	among	among	ADP
ajst-28813	66	11	:	:	PUNCT
ajst-28813	66	12	1	1	NUM
ajst-28813	66	13	t	t	NOUN
ajst-28813	66	14	t	t	X
ajst-28813	66	15	tu	tu	PROPN
ajst-28813	66	16	p	p	PROPN
ajst-28813	66	17	r	r	PROPN
ajst-28813	66	18	(	(	PUNCT
ajst-28813	66	19	1	1	NUM
ajst-28813	66	20	-	-	SYM
ajst-28813	66	21	14	14	NUM
ajst-28813	66	22	)	)	PUNCT
ajst-28813	66	23	t	t	NOUN
ajst-28813	66	24	t	t	PROPN
ajst-28813	66	25	t	t	PROPN
ajst-28813	66	26	t	t	PROPN
ajst-28813	66	27	t	t	PROPN
ajst-28813	66	28	u	u	NOUN
ajst-28813	66	29	g	g	PROPN
ajst-28813	66	30	u	u	NOUN
ajst-28813	66	31	r	r	PROPN
ajst-28813	66	32			PROPN
ajst-28813	66	33			X
ajst-28813	66	34			X
ajst-28813	66	35	(	(	PUNCT
ajst-28813	66	36	1	1	NUM
ajst-28813	66	37	-	-	SYM
ajst-28813	66	38	15	15	NUM
ajst-28813	66	39	)	)	PUNCT
ajst-28813	66	40	for	for	ADP
ajst-28813	66	41	the	the	DET
ajst-28813	66	42	gain	gain	NOUN
ajst-28813	66	43	vector	vector	NOUN
ajst-28813	66	44	tg	tg	PROPN
ajst-28813	66	45	.	.	PUNCT
ajst-28813	67	1	from(1	from(1	NOUN
ajst-28813	67	2	-	-	PUNCT
ajst-28813	67	3	11	11	NUM
ajst-28813	67	4	)	)	PUNCT
ajst-28813	67	5	,	,	PUNCT
ajst-28813	67	6	(	(	PUNCT
ajst-28813	67	7	1	1	NUM
ajst-28813	67	8	-	-	SYM
ajst-28813	67	9	13)in(1	13)in(1	NUM
ajst-28813	67	10	-	-	SYM
ajst-28813	67	11	8)	8)	NUM
ajst-28813	67	12	,	,	PUNCT
ajst-28813	67	13	the	the	DET
ajst-28813	67	14	final	final	ADJ
ajst-28813	67	15	updated	update	VERB
ajst-28813	67	16	weights	weight	NOUN
ajst-28813	67	17	are	be	AUX
ajst-28813	67	18	:	:	PUNCT
ajst-28813	67	19	0	0	NUM
ajst-28813	67	20	0	0	NUM
ajst-28813	67	21	1	1	NUM
ajst-28813	67	22	t	t	NOUN
ajst-28813	67	23	t	t	NOUN
ajst-28813	67	24	t	t	PROPN
ajst-28813	67	25	tw	tw	PROPN
ajst-28813	67	26	w	w	PROPN
ajst-28813	67	27	g	g	PROPN
ajst-28813	67	28	e	e	PROPN
ajst-28813	67	29			NOUN
ajst-28813	67	30	(	(	PUNCT
ajst-28813	67	31	1	1	NUM
ajst-28813	67	32	-	-	SYM
ajst-28813	67	33	16	16	NUM
ajst-28813	67	34	)	)	PUNCT
ajst-28813	67	35	inside	inside	ADP
ajst-28813	67	36			PROPN
ajst-28813	67	37			NOUN
ajst-28813	68	1	0	0	INTJ
ajst-28813	68	2	1	1	NUM
ajst-28813	68	3	ˆ	ˆ	NOUN
ajst-28813	68	4	t	t	PROPN
ajst-28813	68	5	t	t	PROPN
ajst-28813	68	6	t	t	PROPN
ajst-28813	68	7	t	t	X
ajst-28813	68	8	te	te	PROPN
ajst-28813	68	9	w	w	PROPN
ajst-28813	68	10	r	r	NOUN
ajst-28813	68	11	y	y	PUNCT
ajst-28813	68	12			NOUN
ajst-28813	68	13	.	.	PUNCT
ajst-28813	69	1	3	3	X
ajst-28813	69	2	.	.	X
ajst-28813	69	3	the	the	DET
ajst-28813	69	4	esn	esn	PROPN
ajst-28813	69	5	network	network	PROPN
ajst-28813	69	6	model	model	NOUN
ajst-28813	69	7	of	of	ADP
ajst-28813	69	8	the	the	DET
ajst-28813	69	9	electric	electric	ADJ
ajst-28813	69	10	submersible	submersible	ADJ
ajst-28813	69	11	pump	pump	NOUN
ajst-28813	69	12	3.1	3.1	NUM
ajst-28813	69	13	.	.	PUNCT
ajst-28813	70	1	data	datum	NOUN
ajst-28813	70	2	preprocessing	preprocessing	NOUN
ajst-28813	70	3	in	in	ADP
ajst-28813	70	4	the	the	DET
ajst-28813	70	5	process	process	NOUN
ajst-28813	70	6	of	of	ADP
ajst-28813	70	7	industrial	industrial	ADJ
ajst-28813	70	8	data	datum	NOUN
ajst-28813	70	9	collection	collection	NOUN
ajst-28813	70	10	,	,	PUNCT
ajst-28813	70	11	due	due	ADP
ajst-28813	70	12	to	to	ADP
ajst-28813	70	13	the	the	DET
ajst-28813	70	14	existence	existence	NOUN
ajst-28813	70	15	of	of	ADP
ajst-28813	70	16	various	various	ADJ
ajst-28813	70	17	interference	interference	NOUN
ajst-28813	70	18	factors	factor	NOUN
ajst-28813	70	19	,	,	PUNCT
ajst-28813	70	20	the	the	DET
ajst-28813	70	21	collected	collect	VERB
ajst-28813	70	22	data	datum	NOUN
ajst-28813	70	23	often	often	ADV
ajst-28813	70	24	contains	contain	VERB
ajst-28813	70	25	many	many	ADJ
ajst-28813	70	26	problems	problem	NOUN
ajst-28813	70	27	.	.	PUNCT
ajst-28813	71	1	to	to	PART
ajst-28813	71	2	improve	improve	VERB
ajst-28813	71	3	the	the	DET
ajst-28813	71	4	quality	quality	NOUN
ajst-28813	71	5	and	and	CCONJ
ajst-28813	71	6	usability	usability	NOUN
ajst-28813	71	7	of	of	ADP
ajst-28813	71	8	the	the	DET
ajst-28813	71	9	data	datum	NOUN
ajst-28813	71	10	,	,	PUNCT
ajst-28813	71	11	data	datum	NOUN
ajst-28813	71	12	preprocessing	preprocessing	NOUN
ajst-28813	71	13	is	be	AUX
ajst-28813	71	14	required	require	VERB
ajst-28813	71	15	,	,	PUNCT
ajst-28813	71	16	including	include	VERB
ajst-28813	71	17	but	but	CCONJ
ajst-28813	71	18	not	not	PART
ajst-28813	71	19	limited	limit	VERB
ajst-28813	71	20	to	to	ADP
ajst-28813	71	21	the	the	DET
ajst-28813	71	22	addition	addition	NOUN
ajst-28813	71	23	of	of	ADP
ajst-28813	71	24	new	new	ADJ
ajst-28813	71	25	features	feature	NOUN
ajst-28813	71	26	,	,	PUNCT
ajst-28813	71	27	removing	remove	VERB
ajst-28813	71	28	duplicates	duplicate	NOUN
ajst-28813	71	29	,	,	PUNCT
ajst-28813	71	30	transforming	transform	VERB
ajst-28813	71	31	data	datum	NOUN
ajst-28813	71	32	formats	format	NOUN
ajst-28813	71	33	,	,	PUNCT
ajst-28813	71	34	application	application	NOUN
ajst-28813	71	35	of	of	ADP
ajst-28813	71	36	interpolation	interpolation	NOUN
ajst-28813	71	37	techniques	technique	NOUN
ajst-28813	71	38	,	,	PUNCT
ajst-28813	71	39	and	and	CCONJ
ajst-28813	71	40	noise	noise	NOUN
ajst-28813	71	41	processing	processing	NOUN
ajst-28813	71	42	.	.	PUNCT
ajst-28813	72	1	these	these	DET
ajst-28813	72	2	operations	operation	NOUN
ajst-28813	72	3	help	help	VERB
ajst-28813	72	4	to	to	PART
ajst-28813	72	5	clean	clean	VERB
ajst-28813	72	6	and	and	CCONJ
ajst-28813	72	7	collate	collate	VERB
ajst-28813	72	8	the	the	DET
ajst-28813	72	9	data	datum	NOUN
ajst-28813	72	10	,	,	PUNCT
ajst-28813	72	11	making	make	VERB
ajst-28813	72	12	it	it	PRON
ajst-28813	72	13	more	more	ADV
ajst-28813	72	14	suitable	suitable	ADJ
ajst-28813	72	15	for	for	ADP
ajst-28813	72	16	expression	expression	NOUN
ajst-28813	72	17	and	and	CCONJ
ajst-28813	72	18	analysis	analysis	NOUN
ajst-28813	72	19	.	.	PUNCT
ajst-28813	73	1	in	in	ADP
ajst-28813	73	2	the	the	DET
ajst-28813	73	3	preprocessing	preprocessing	NOUN
ajst-28813	73	4	process	process	NOUN
ajst-28813	73	5	,	,	PUNCT
ajst-28813	73	6	mastering	master	VERB
ajst-28813	73	7	the	the	DET
ajst-28813	73	8	data	datum	NOUN
ajst-28813	73	9	characteristics	characteristic	NOUN
ajst-28813	73	10	,	,	PUNCT
ajst-28813	73	11	process	process	NOUN
ajst-28813	73	12	flow	flow	NOUN
ajst-28813	73	13	and	and	CCONJ
ajst-28813	73	14	equipment	equipment	NOUN
ajst-28813	73	15	operation	operation	NOUN
ajst-28813	73	16	rules	rule	NOUN
ajst-28813	73	17	of	of	ADP
ajst-28813	73	18	a	a	DET
ajst-28813	73	19	specific	specific	ADJ
ajst-28813	73	20	field	field	NOUN
ajst-28813	73	21	is	be	AUX
ajst-28813	73	22	crucial	crucial	ADJ
ajst-28813	73	23	to	to	PART
ajst-28813	73	24	accurately	accurately	ADV
ajst-28813	73	25	identify	identify	VERB
ajst-28813	73	26	and	and	CCONJ
ajst-28813	73	27	handle	handle	VERB
ajst-28813	73	28	outliers	outlier	NOUN
ajst-28813	73	29	.	.	PUNCT
ajst-28813	74	1	at	at	ADP
ajst-28813	74	2	the	the	DET
ajst-28813	74	3	same	same	ADJ
ajst-28813	74	4	time	time	NOUN
ajst-28813	74	5	,	,	PUNCT
ajst-28813	74	6	in	in	ADP
ajst-28813	74	7	order	order	NOUN
ajst-28813	74	8	to	to	PART
ajst-28813	74	9	meet	meet	VERB
ajst-28813	74	10	the	the	DET
ajst-28813	74	11	needs	need	NOUN
ajst-28813	74	12	of	of	ADP
ajst-28813	74	13	the	the	DET
ajst-28813	74	14	algorithm	algorithm	NOUN
ajst-28813	74	15	model	model	NOUN
ajst-28813	74	16	,	,	PUNCT
ajst-28813	74	17	the	the	DET
ajst-28813	74	18	scale	scale	NOUN
ajst-28813	74	19	and	and	CCONJ
ajst-28813	74	20	format	format	NOUN
ajst-28813	74	21	of	of	ADP
ajst-28813	74	22	the	the	DET
ajst-28813	74	23	data	datum	NOUN
ajst-28813	74	24	must	must	AUX
ajst-28813	74	25	be	be	AUX
ajst-28813	74	26	considered	consider	VERB
ajst-28813	74	27	to	to	PART
ajst-28813	74	28	ensure	ensure	VERB
ajst-28813	74	29	that	that	SCONJ
ajst-28813	74	30	the	the	DET
ajst-28813	74	31	data	data	NOUN
ajst-28813	74	32	input	input	NOUN
ajst-28813	74	33	meets	meet	VERB
ajst-28813	74	34	the	the	DET
ajst-28813	74	35	requirements	requirement	NOUN
ajst-28813	74	36	of	of	ADP
ajst-28813	74	37	the	the	DET
ajst-28813	74	38	model	model	NOUN
ajst-28813	74	39	,	,	PUNCT
ajst-28813	74	40	so	so	SCONJ
ajst-28813	74	41	as	as	SCONJ
ajst-28813	74	42	to	to	PART
ajst-28813	74	43	improve	improve	VERB
ajst-28813	74	44	the	the	DET
ajst-28813	74	45	training	training	NOUN
ajst-28813	74	46	and	and	CCONJ
ajst-28813	74	47	prediction	prediction	NOUN
ajst-28813	74	48	efficiency	efficiency	NOUN
ajst-28813	74	49	of	of	ADP
ajst-28813	74	50	the	the	DET
ajst-28813	74	51	model	model	NOUN
ajst-28813	74	52	.	.	PUNCT
ajst-28813	75	1	there	there	PRON
ajst-28813	75	2	may	may	AUX
ajst-28813	75	3	be	be	AUX
ajst-28813	75	4	a	a	DET
ajst-28813	75	5	strong	strong	ADJ
ajst-28813	75	6	intercorrelation	intercorrelation	NOUN
ajst-28813	75	7	between	between	ADP
ajst-28813	75	8	the	the	DET
ajst-28813	75	9	state	state	NOUN
ajst-28813	75	10	data	datum	NOUN
ajst-28813	75	11	of	of	ADP
ajst-28813	75	12	the	the	DET
ajst-28813	75	13	electric	electric	ADJ
ajst-28813	75	14	submersible	submersible	ADJ
ajst-28813	75	15	pump	pump	NOUN
ajst-28813	75	16	.	.	PUNCT
ajst-28813	76	1	for	for	SCONJ
ajst-28813	76	2	the	the	DET
ajst-28813	76	3	various	various	ADJ
ajst-28813	76	4	variables	variable	NOUN
ajst-28813	76	5	being	be	AUX
ajst-28813	76	6	continuously	continuously	ADV
ajst-28813	76	7	monitored	monitor	VERB
ajst-28813	76	8	,	,	PUNCT
ajst-28813	76	9	the	the	DET
ajst-28813	76	10	data	datum	NOUN
ajst-28813	76	11	between	between	ADP
ajst-28813	76	12	the	the	DET
ajst-28813	76	13	different	different	ADJ
ajst-28813	76	14	variables	variable	NOUN
ajst-28813	76	15	may	may	AUX
ajst-28813	76	16	show	show	VERB
ajst-28813	76	17	great	great	ADJ
ajst-28813	76	18	variability	variability	NOUN
ajst-28813	76	19	due	due	ADP
ajst-28813	76	20	to	to	ADP
ajst-28813	76	21	the	the	DET
ajst-28813	76	22	different	different	ADJ
ajst-28813	76	23	means	mean	NOUN
ajst-28813	76	24	of	of	ADP
ajst-28813	76	25	measurement	measurement	NOUN
ajst-28813	76	26	.	.	PUNCT
ajst-28813	77	1	to	to	PART
ajst-28813	77	2	reduce	reduce	VERB
ajst-28813	77	3	the	the	DET
ajst-28813	77	4	impact	impact	NOUN
ajst-28813	77	5	of	of	ADP
ajst-28813	77	6	this	this	DET
ajst-28813	77	7	variability	variability	NOUN
ajst-28813	77	8	,	,	PUNCT
ajst-28813	77	9	we	we	PRON
ajst-28813	77	10	need	need	VERB
ajst-28813	77	11	to	to	PART
ajst-28813	77	12	standardize	standardize	VERB
ajst-28813	77	13	and	and	CCONJ
ajst-28813	77	14	normalize	normalize	VERB
ajst-28813	77	15	the	the	DET
ajst-28813	77	16	values	value	NOUN
ajst-28813	77	17	of	of	ADP
ajst-28813	77	18	these	these	DET
ajst-28813	77	19	scalars	scalar	NOUN
ajst-28813	77	20	.	.	PUNCT
ajst-28813	78	1	(	(	PUNCT
ajst-28813	78	2	1	1	X
ajst-28813	78	3	)	)	PUNCT
ajst-28813	78	4	z	z	NOUN
ajst-28813	78	5	-	-	PUNCT
ajst-28813	78	6	score	score	NOUN
ajst-28813	78	7	standardization	standardization	NOUN
ajst-28813	78	8	for	for	ADP
ajst-28813	78	9	1	1	NUM
ajst-28813	78	10	2	2	NUM
ajst-28813	78	11	,	,	PUNCT
ajst-28813	78	12	,	,	PUNCT
ajst-28813	78	13	nx	nx	X
ajst-28813	78	14	x	x	X
ajst-28813	78	15	x	x	PROPN
ajst-28813	78	16	the	the	DET
ajst-28813	78	17	sequence	sequence	NOUN
ajst-28813	78	18	,	,	PUNCT
ajst-28813	78	19	its	its	PRON
ajst-28813	78	20	mathematical	mathematical	ADJ
ajst-28813	78	21	expression	expression	NOUN
ajst-28813	78	22	is	be	AUX
ajst-28813	78	23	:	:	PUNCT
ajst-28813	78	24	i	i	PRON
ajst-28813	78	25	i	i	VERB
ajst-28813	78	26	x	x	VERB
ajst-28813	78	27	x	x	VERB
ajst-28813	78	28	y	y	PROPN
ajst-28813	78	29	s	s	PROPN
ajst-28813	78	30			PROPN
ajst-28813	78	31			NUM
ajst-28813	78	32	(	(	PUNCT
ajst-28813	78	33	2	2	NUM
ajst-28813	78	34	-	-	SYM
ajst-28813	78	35	1	1	NUM
ajst-28813	78	36	)	)	PUNCT
ajst-28813	78	37	inside	inside	ADP
ajst-28813	78	38	1	1	NUM
ajst-28813	78	39	1	1	NUM
ajst-28813	78	40	n	n	NUM
ajst-28813	79	1	i	i	PRON
ajst-28813	80	1	i	i	INTJ
ajst-28813	80	2	x	x	VERB
ajst-28813	80	3	x	x	VERB
ajst-28813	80	4	n	n	CCONJ
ajst-28813	80	5			NUM
ajst-28813	80	6			ADJ
ajst-28813	80	7			NOUN
ajst-28813	80	8	,	,	PUNCT
ajst-28813	80	9			NOUN
ajst-28813	80	10	2	2	ADJ
ajst-28813	80	11	1	1	NUM
ajst-28813	80	12	1	1	NUM
ajst-28813	80	13	1	1	NUM
ajst-28813	80	14	n	n	NUM
ajst-28813	81	1	i	i	PRON
ajst-28813	81	2	i	i	PRON
ajst-28813	81	3	s	s	VERB
ajst-28813	81	4	x	x	PUNCT
ajst-28813	81	5	x	x	SYM
ajst-28813	81	6	n	n	CCONJ
ajst-28813	81	7			NUM
ajst-28813	81	8			PROPN
ajst-28813	81	9			PROPN
ajst-28813	81	10			PROPN
ajst-28813	81	11			X
ajst-28813	81	12	.	.	PUNCT
ajst-28813	82	1	(	(	PUNCT
ajst-28813	82	2	2	2	X
ajst-28813	82	3	)	)	PUNCT
ajst-28813	82	4	min	min	NOUN
ajst-28813	82	5	-	-	NOUN
ajst-28813	82	6	max	max	NOUN
ajst-28813	82	7	for	for	ADP
ajst-28813	82	8	normalization	normalization	NOUN
ajst-28813	82	9	since	since	SCONJ
ajst-28813	82	10	each	each	DET
ajst-28813	82	11	feature	feature	NOUN
ajst-28813	82	12	has	have	VERB
ajst-28813	82	13	different	different	ADJ
ajst-28813	82	14	meanings	meaning	NOUN
ajst-28813	82	15	,	,	PUNCT
ajst-28813	82	16	the	the	DET
ajst-28813	82	17	0	0	NUM
ajst-28813	82	18	-	-	SYM
ajst-28813	82	19	1	1	NUM
ajst-28813	82	20	normalization	normalization	NOUN
ajst-28813	82	21	should	should	AUX
ajst-28813	82	22	be	be	AUX
ajst-28813	82	23	applied	apply	VERB
ajst-28813	82	24	to	to	ADP
ajst-28813	82	25	the	the	DET
ajst-28813	82	26	sample	sample	NOUN
ajst-28813	82	27	set	set	NOUN
ajst-28813	82	28	.	.	PUNCT
ajst-28813	83	1	in	in	ADP
ajst-28813	83	2	neural	neural	ADJ
ajst-28813	83	3	network	network	NOUN
ajst-28813	83	4	deep	deep	ADJ
ajst-28813	83	5	learning	learning	NOUN
ajst-28813	83	6	,	,	PUNCT
ajst-28813	83	7	data	datum	NOUN
ajst-28813	83	8	normalization	normalization	NOUN
ajst-28813	83	9	is	be	AUX
ajst-28813	83	10	a	a	DET
ajst-28813	83	11	common	common	ADJ
ajst-28813	83	12	preprocessing	preprocessing	NOUN
ajst-28813	83	13	step	step	NOUN
ajst-28813	83	14	that	that	PRON
ajst-28813	83	15	ensures	ensure	VERB
ajst-28813	83	16	the	the	DET
ajst-28813	83	17	consistent	consistent	ADJ
ajst-28813	83	18	numerical	numerical	ADJ
ajst-28813	83	19	range	range	NOUN
ajst-28813	83	20	of	of	ADP
ajst-28813	83	21	different	different	ADJ
ajst-28813	83	22	features	feature	NOUN
ajst-28813	83	23	and	and	CCONJ
ajst-28813	83	24	guarantees	guarantee	VERB
ajst-28813	83	25	the	the	DET
ajst-28813	83	26	performance	performance	NOUN
ajst-28813	83	27	of	of	ADP
ajst-28813	83	28	the	the	DET
ajst-28813	83	29	model	model	NOUN
ajst-28813	83	30	.	.	PUNCT
ajst-28813	84	1	maximum	maximum	ADJ
ajst-28813	84	2	minimum	minimum	ADJ
ajst-28813	84	3	normalization	normalization	NOUN
ajst-28813	84	4	is	be	AUX
ajst-28813	84	5	a	a	DET
ajst-28813	84	6	common	common	ADJ
ajst-28813	84	7	method	method	NOUN
ajst-28813	84	8	to	to	PART
ajst-28813	84	9	deal	deal	VERB
ajst-28813	84	10	with	with	ADP
ajst-28813	84	11	large	large	ADJ
ajst-28813	84	12	differences	difference	NOUN
ajst-28813	84	13	between	between	ADP
ajst-28813	84	14	different	different	ADJ
ajst-28813	84	15	data	datum	NOUN
ajst-28813	84	16	.	.	PUNCT
ajst-28813	85	1	linear	linear	ADJ
ajst-28813	85	2	mapping	mapping	NOUN
ajst-28813	85	3	can	can	AUX
ajst-28813	85	4	reduce	reduce	VERB
ajst-28813	85	5	the	the	DET
ajst-28813	85	6	range	range	NOUN
ajst-28813	85	7	of	of	ADP
ajst-28813	85	8	required	require	VERB
ajst-28813	85	9	data	datum	NOUN
ajst-28813	85	10	to	to	ADP
ajst-28813	85	11	[	[	X
ajst-28813	85	12	0,1	0,1	NUM
ajst-28813	85	13	]	]	PUNCT
ajst-28813	85	14	,	,	PUNCT
ajst-28813	85	15	which	which	PRON
ajst-28813	85	16	can	can	AUX
ajst-28813	85	17	better	well	ADV
ajst-28813	85	18	adapt	adapt	VERB
ajst-28813	85	19	to	to	ADP
ajst-28813	85	20	various	various	ADJ
ajst-28813	85	21	machine	machine	NOUN
ajst-28813	85	22	learning	learning	NOUN
ajst-28813	85	23	models	model	NOUN
ajst-28813	85	24	.	.	PUNCT
ajst-28813	86	1	the	the	DET
ajst-28813	86	2	mathematical	mathematical	ADJ
ajst-28813	86	3	expression	expression	NOUN
ajst-28813	86	4	is	be	AUX
ajst-28813	86	5	provided	provide	VERB
ajst-28813	86	6	as	as	SCONJ
ajst-28813	86	7	follows	follow	VERB
ajst-28813	86	8	:	:	PUNCT
ajst-28813	87	1	min	min	PROPN
ajst-28813	87	2	max	max	PROPN
ajst-28813	87	3	min	min	PROPN
ajst-28813	88	1	ij	ij	INTJ
ajst-28813	89	1	ij	ij	INTJ
ajst-28813	89	2	x	x	X
ajst-28813	89	3	x	x	PUNCT
ajst-28813	89	4	x	x	PUNCT
ajst-28813	89	5	x	x	PUNCT
ajst-28813	89	6	x	x	SYM
ajst-28813	89	7			PROPN
ajst-28813	89	8			NUM
ajst-28813	89	9			NOUN
ajst-28813	89	10	(	(	PUNCT
ajst-28813	89	11	2	2	NUM
ajst-28813	89	12	-	-	SYM
ajst-28813	89	13	2	2	NUM
ajst-28813	89	14	)	)	PUNCT
ajst-28813	89	15	inside	inside	ADP
ajst-28813	89	16	1	1	NUM
ajst-28813	89	17	,	,	PUNCT
ajst-28813	89	18	2	2	NUM
ajst-28813	89	19	,	,	PUNCT
ajst-28813	89	20	...	...	PUNCT
ajst-28813	89	21	,	,	PUNCT
ajst-28813	89	22	1	1	NUM
ajst-28813	89	23	,	,	PUNCT
ajst-28813	89	24	2	2	NUM
ajst-28813	89	25	,	,	PUNCT
ajst-28813	89	26	...	...	PUNCT
ajst-28813	89	27	,	,	PUNCT
ajst-28813	89	28	i	i	PRON
ajst-28813	89	29	n	n	VERB
ajst-28813	89	30	j	j	PROPN
ajst-28813	89	31	m	m	VERB
ajst-28813	89	32			NOUN
ajst-28813	89	33			NUM
ajst-28813	89	34			NOUN
ajst-28813	89	35	,	,	PUNCT
ajst-28813	89	36	minx	minx	NOUN
ajst-28813	89	37	is	be	AUX
ajst-28813	89	38	the	the	DET
ajst-28813	89	39	minimum	minimum	ADJ
ajst-28813	89	40	value	value	NOUN
ajst-28813	89	41	in	in	ADP
ajst-28813	89	42	the	the	DET
ajst-28813	89	43	ijx	ijx	NOUN
ajst-28813	89	44	,	,	PUNCT
ajst-28813	89	45	maxx	maxx	PROPN
ajst-28813	89	46	is	be	AUX
ajst-28813	89	47	the	the	DET
ajst-28813	89	48	maximum	maximum	ADJ
ajst-28813	89	49	value	value	NOUN
ajst-28813	89	50	in	in	ADP
ajst-28813	89	51	the	the	DET
ajst-28813	89	52	ijx	ijx	NOUN
ajst-28813	89	53	,	,	PUNCT
ajst-28813	89	54	m	m	VERB
ajst-28813	89	55	is	be	AUX
ajst-28813	89	56	the	the	DET
ajst-28813	89	57	sample	sample	NOUN
ajst-28813	89	58	size	size	NOUN
ajst-28813	89	59	of	of	ADP
ajst-28813	89	60	the	the	DET
ajst-28813	89	61	data	datum	NOUN
ajst-28813	89	62	n	n	CCONJ
ajst-28813	89	63	is	be	AUX
ajst-28813	89	64	the	the	DET
ajst-28813	89	65	dimension	dimension	NOUN
ajst-28813	89	66	of	of	ADP
ajst-28813	89	67	the	the	DET
ajst-28813	89	68	data	data	NOUN
ajst-28813	89	69	characteristics	characteristic	NOUN
ajst-28813	89	70	.	.	PUNCT
ajst-28813	90	1	the	the	DET
ajst-28813	90	2	normalized	normalize	VERB
ajst-28813	90	3	matrix	matrix	NOUN
ajst-28813	90	4	z	z	NOUN
ajst-28813	90	5	was	be	AUX
ajst-28813	90	6	obtained	obtain	VERB
ajst-28813	90	7	as	as	SCONJ
ajst-28813	90	8	follows	follow	VERB
ajst-28813	90	9	:	:	PUNCT
ajst-28813	90	10	11	11	NUM
ajst-28813	90	11	12	12	NUM
ajst-28813	90	12	1	1	NUM
ajst-28813	90	13	21	21	NUM
ajst-28813	90	14	22	22	NUM
ajst-28813	90	15	2	2	NUM
ajst-28813	90	16	1	1	NUM
ajst-28813	90	17	3	3	NUM
ajst-28813	90	18	...	...	PUNCT
ajst-28813	90	19	...	...	PUNCT
ajst-28813	90	20	...	...	PUNCT
ajst-28813	90	21	...	...	PUNCT
ajst-28813	90	22	...	...	PUNCT
ajst-28813	90	23	...	...	PUNCT
ajst-28813	90	24	...	...	PUNCT
ajst-28813	91	1	n	n	CCONJ
ajst-28813	91	2	n	n	PRON
ajst-28813	91	3	m	m	VERB
ajst-28813	91	4	m	m	VERB
ajst-28813	91	5	mn	mn	PROPN
ajst-28813	91	6	z	z	PROPN
ajst-28813	91	7	z	z	PROPN
ajst-28813	92	1	z	z	NOUN
ajst-28813	92	2	z	z	NOUN
ajst-28813	93	1	z	z	NOUN
ajst-28813	93	2	z	z	NOUN
ajst-28813	93	3	z	z	NOUN
ajst-28813	93	4	z	z	NOUN
ajst-28813	93	5	z	z	NOUN
ajst-28813	93	6	z	z	NOUN
ajst-28813	93	7			NOUN
ajst-28813	94	1			PROPN
ajst-28813	94	2			PROPN
ajst-28813	94	3			PROPN
ajst-28813	95	1			PROPN
ajst-28813	95	2			NOUN
ajst-28813	96	1			PROPN
ajst-28813	96	2			PROPN
ajst-28813	97	1			PROPN
ajst-28813	97	2			PROPN
ajst-28813	98	1			ADJ
ajst-28813	98	2			NOUN
ajst-28813	98	3	after	after	ADP
ajst-28813	98	4	the	the	DET
ajst-28813	98	5	normalized	normalize	VERB
ajst-28813	98	6	data	datum	NOUN
ajst-28813	98	7	,	,	PUNCT
ajst-28813	98	8	it	it	PRON
ajst-28813	98	9	is	be	AUX
ajst-28813	98	10	necessary	necessary	ADJ
ajst-28813	98	11	to	to	PART
ajst-28813	98	12	ensure	ensure	VERB
ajst-28813	98	13	that	that	SCONJ
ajst-28813	98	14	the	the	DET
ajst-28813	98	15	individual	individual	ADJ
ajst-28813	98	16	features	feature	NOUN
ajst-28813	98	17	are	be	AUX
ajst-28813	98	18	compared	compare	VERB
ajst-28813	98	19	at	at	ADP
ajst-28813	98	20	the	the	DET
ajst-28813	98	21	same	same	ADJ
ajst-28813	98	22	scale	scale	NOUN
ajst-28813	98	23	.	.	PUNCT
ajst-28813	99	1	the	the	DET
ajst-28813	99	2	normalized	normalize	VERB
ajst-28813	99	3	data	datum	NOUN
ajst-28813	99	4	were	be	AUX
ajst-28813	99	5	divided	divide	VERB
ajst-28813	99	6	into	into	ADP
ajst-28813	99	7	training	training	NOUN
ajst-28813	99	8	,	,	PUNCT
ajst-28813	99	9	validation	validation	NOUN
ajst-28813	99	10	and	and	CCONJ
ajst-28813	99	11	test	test	NOUN
ajst-28813	99	12	set	set	VERB
ajst-28813	99	13	in	in	ADP
ajst-28813	99	14	a	a	DET
ajst-28813	99	15	certain	certain	ADJ
ajst-28813	99	16	proportion	proportion	NOUN
ajst-28813	99	17	.	.	PUNCT
ajst-28813	100	1	the	the	DET
ajst-28813	100	2	main	main	ADJ
ajst-28813	100	3	purpose	purpose	NOUN
ajst-28813	100	4	of	of	ADP
ajst-28813	100	5	the	the	DET
ajst-28813	100	6	training	training	NOUN
ajst-28813	100	7	248	248	NUM
ajst-28813	100	8	set	set	NOUN
ajst-28813	100	9	is	be	AUX
ajst-28813	100	10	to	to	PART
ajst-28813	100	11	train	train	VERB
ajst-28813	100	12	the	the	DET
ajst-28813	100	13	model	model	NOUN
ajst-28813	100	14	and	and	CCONJ
ajst-28813	100	15	build	build	VERB
ajst-28813	100	16	an	an	DET
ajst-28813	100	17	effective	effective	ADJ
ajst-28813	100	18	model	model	NOUN
ajst-28813	100	19	by	by	ADP
ajst-28813	100	20	learning	learn	VERB
ajst-28813	100	21	the	the	DET
ajst-28813	100	22	patterns	pattern	NOUN
ajst-28813	100	23	and	and	CCONJ
ajst-28813	100	24	features	feature	NOUN
ajst-28813	100	25	of	of	ADP
ajst-28813	100	26	the	the	DET
ajst-28813	100	27	data	datum	NOUN
ajst-28813	100	28	.	.	PUNCT
ajst-28813	101	1	the	the	DET
ajst-28813	101	2	validation	validation	NOUN
ajst-28813	101	3	set	set	NOUN
ajst-28813	101	4	plays	play	VERB
ajst-28813	101	5	an	an	DET
ajst-28813	101	6	important	important	ADJ
ajst-28813	101	7	role	role	NOUN
ajst-28813	101	8	in	in	ADP
ajst-28813	101	9	the	the	DET
ajst-28813	101	10	process	process	NOUN
ajst-28813	101	11	of	of	ADP
ajst-28813	101	12	model	model	NOUN
ajst-28813	101	13	training	training	NOUN
ajst-28813	101	14	.	.	PUNCT
ajst-28813	102	1	it	it	PRON
ajst-28813	102	2	is	be	AUX
ajst-28813	102	3	used	use	VERB
ajst-28813	102	4	to	to	PART
ajst-28813	102	5	evaluate	evaluate	VERB
ajst-28813	102	6	whether	whether	SCONJ
ajst-28813	102	7	the	the	DET
ajst-28813	102	8	performance	performance	NOUN
ajst-28813	102	9	of	of	ADP
ajst-28813	102	10	the	the	DET
ajst-28813	102	11	model	model	NOUN
ajst-28813	102	12	meets	meet	VERB
ajst-28813	102	13	the	the	DET
ajst-28813	102	14	expectation	expectation	NOUN
ajst-28813	102	15	,	,	PUNCT
ajst-28813	102	16	so	so	SCONJ
ajst-28813	102	17	as	as	SCONJ
ajst-28813	102	18	to	to	PART
ajst-28813	102	19	provide	provide	VERB
ajst-28813	102	20	a	a	DET
ajst-28813	102	21	reliable	reliable	ADJ
ajst-28813	102	22	reference	reference	NOUN
ajst-28813	102	23	for	for	ADP
ajst-28813	102	24	the	the	DET
ajst-28813	102	25	subsequent	subsequent	ADJ
ajst-28813	102	26	debugging	debugging	NOUN
ajst-28813	102	27	and	and	CCONJ
ajst-28813	102	28	optimization	optimization	NOUN
ajst-28813	102	29	of	of	ADP
ajst-28813	102	30	the	the	DET
ajst-28813	102	31	hyperparameters	hyperparameter	NOUN
ajst-28813	102	32	of	of	ADP
ajst-28813	102	33	the	the	DET
ajst-28813	102	34	network	network	NOUN
ajst-28813	102	35	model	model	NOUN
ajst-28813	102	36	,	,	PUNCT
ajst-28813	102	37	avoid	avoid	VERB
ajst-28813	102	38	overfitting	overfitte	VERB
ajst-28813	102	39	or	or	CCONJ
ajst-28813	102	40	underfitting	underfitting	NOUN
ajst-28813	102	41	problems	problem	NOUN
ajst-28813	102	42	,	,	PUNCT
ajst-28813	102	43	and	and	CCONJ
ajst-28813	102	44	ensure	ensure	VERB
ajst-28813	102	45	that	that	SCONJ
ajst-28813	102	46	the	the	DET
ajst-28813	102	47	model	model	NOUN
ajst-28813	102	48	has	have	VERB
ajst-28813	102	49	good	good	ADJ
ajst-28813	102	50	generalization	generalization	NOUN
ajst-28813	102	51	ability	ability	NOUN
ajst-28813	102	52	.	.	PUNCT
ajst-28813	103	1	the	the	DET
ajst-28813	103	2	final	final	ADJ
ajst-28813	103	3	test	test	NOUN
ajst-28813	103	4	set	set	NOUN
ajst-28813	103	5	was	be	AUX
ajst-28813	103	6	retained	retain	VERB
ajst-28813	103	7	to	to	PART
ajst-28813	103	8	evaluate	evaluate	VERB
ajst-28813	103	9	the	the	DET
ajst-28813	103	10	final	final	ADJ
ajst-28813	103	11	performance	performance	NOUN
ajst-28813	103	12	of	of	ADP
ajst-28813	103	13	the	the	DET
ajst-28813	103	14	model	model	NOUN
ajst-28813	103	15	,	,	PUNCT
ajst-28813	103	16	ensuring	ensure	VERB
ajst-28813	103	17	that	that	SCONJ
ajst-28813	103	18	the	the	DET
ajst-28813	103	19	model	model	NOUN
ajst-28813	103	20	performed	perform	VERB
ajst-28813	103	21	expected	expect	VERB
ajst-28813	103	22	on	on	ADP
ajst-28813	103	23	location	location	NOUN
ajst-28813	103	24	data	datum	NOUN
ajst-28813	103	25	.	.	PUNCT
ajst-28813	104	1	as	as	SCONJ
ajst-28813	104	2	shown	show	VERB
ajst-28813	104	3	in	in	ADP
ajst-28813	104	4	figure	figure	NOUN
ajst-28813	104	5	2	2	NUM
ajst-28813	104	6	-	-	SYM
ajst-28813	104	7	1	1	NUM
ajst-28813	104	8	,	,	PUNCT
ajst-28813	104	9	data	datum	NOUN
ajst-28813	104	10	trends	trend	NOUN
ajst-28813	104	11	of	of	ADP
ajst-28813	104	12	production	production	NOUN
ajst-28813	104	13	parameters	parameter	NOUN
ajst-28813	104	14	of	of	ADP
ajst-28813	104	15	well	well	INTJ
ajst-28813	104	16	a2	a2	PROPN
ajst-28813	104	17	under	under	ADP
ajst-28813	104	18	different	different	ADJ
ajst-28813	104	19	working	work	VERB
ajst-28813	104	20	conditions	condition	NOUN
ajst-28813	104	21	.	.	PUNCT
ajst-28813	105	1	these	these	DET
ajst-28813	105	2	data	datum	NOUN
ajst-28813	105	3	are	be	AUX
ajst-28813	105	4	collected	collect	VERB
ajst-28813	105	5	continuously	continuously	ADV
ajst-28813	105	6	,	,	PUNCT
ajst-28813	105	7	so	so	SCONJ
ajst-28813	105	8	as	as	SCONJ
ajst-28813	105	9	to	to	PART
ajst-28813	105	10	accurately	accurately	ADV
ajst-28813	105	11	capture	capture	VERB
ajst-28813	105	12	the	the	DET
ajst-28813	105	13	changes	change	NOUN
ajst-28813	105	14	of	of	ADP
ajst-28813	105	15	each	each	DET
ajst-28813	105	16	parameter	parameter	NOUN
ajst-28813	105	17	under	under	ADP
ajst-28813	105	18	different	different	ADJ
ajst-28813	105	19	working	work	VERB
ajst-28813	105	20	conditions	condition	NOUN
ajst-28813	105	21	.	.	PUNCT
ajst-28813	106	1	obviously	obviously	ADV
ajst-28813	106	2	,	,	PUNCT
ajst-28813	106	3	there	there	PRON
ajst-28813	106	4	are	be	VERB
ajst-28813	106	5	significant	significant	ADJ
ajst-28813	106	6	differences	difference	NOUN
ajst-28813	106	7	in	in	ADP
ajst-28813	106	8	each	each	DET
ajst-28813	106	9	parameter	parameter	NOUN
ajst-28813	106	10	under	under	ADP
ajst-28813	106	11	different	different	ADJ
ajst-28813	106	12	working	work	VERB
ajst-28813	106	13	conditions	condition	NOUN
ajst-28813	106	14	.	.	PUNCT
ajst-28813	107	1	in	in	ADP
ajst-28813	107	2	this	this	DET
ajst-28813	107	3	study	study	NOUN
ajst-28813	107	4	,	,	PUNCT
ajst-28813	107	5	sample	sample	NOUN
ajst-28813	107	6	data	datum	NOUN
ajst-28813	107	7	from	from	ADP
ajst-28813	107	8	the	the	DET
ajst-28813	107	9	normal	normal	ADJ
ajst-28813	107	10	and	and	CCONJ
ajst-28813	107	11	cumulative	cumulative	ADJ
ajst-28813	107	12	phases	phase	NOUN
ajst-28813	107	13	were	be	AUX
ajst-28813	107	14	used	use	VERB
ajst-28813	107	15	to	to	PART
ajst-28813	107	16	predict	predict	VERB
ajst-28813	107	17	trends	trend	NOUN
ajst-28813	107	18	in	in	ADP
ajst-28813	107	19	the	the	DET
ajst-28813	107	20	system	system	NOUN
ajst-28813	107	21	state	state	NOUN
ajst-28813	107	22	and	and	CCONJ
ajst-28813	107	23	draw	draw	VERB
ajst-28813	107	24	corresponding	correspond	VERB
ajst-28813	107	25	control	control	NOUN
ajst-28813	107	26	measures	measure	NOUN
ajst-28813	107	27	accordingly	accordingly	ADV
ajst-28813	107	28	.	.	PUNCT
ajst-28813	108	1	in	in	ADP
ajst-28813	108	2	this	this	DET
ajst-28813	108	3	way	way	NOUN
ajst-28813	108	4	,	,	PUNCT
ajst-28813	108	5	we	we	PRON
ajst-28813	108	6	can	can	AUX
ajst-28813	108	7	take	take	VERB
ajst-28813	108	8	measures	measure	NOUN
ajst-28813	108	9	to	to	PART
ajst-28813	108	10	adjust	adjust	VERB
ajst-28813	108	11	and	and	CCONJ
ajst-28813	108	12	optimize	optimize	VERB
ajst-28813	108	13	the	the	DET
ajst-28813	108	14	system	system	NOUN
ajst-28813	108	15	before	before	SCONJ
ajst-28813	108	16	the	the	DET
ajst-28813	108	17	state	state	NOUN
ajst-28813	108	18	deteriorto	deteriorto	VERB
ajst-28813	108	19	an	an	DET
ajst-28813	108	20	unacceptable	unacceptable	ADJ
ajst-28813	108	21	degree	degree	NOUN
ajst-28813	108	22	,	,	PUNCT
ajst-28813	108	23	so	so	SCONJ
ajst-28813	108	24	as	as	SCONJ
ajst-28813	108	25	to	to	PART
ajst-28813	108	26	ensure	ensure	VERB
ajst-28813	108	27	the	the	DET
ajst-28813	108	28	stable	stable	ADJ
ajst-28813	108	29	operation	operation	NOUN
ajst-28813	108	30	of	of	ADP
ajst-28813	108	31	the	the	DET
ajst-28813	108	32	system	system	NOUN
ajst-28813	108	33	.	.	PUNCT
ajst-28813	109	1	this	this	DET
ajst-28813	109	2	control	control	NOUN
ajst-28813	109	3	mode	mode	NOUN
ajst-28813	109	4	not	not	PART
ajst-28813	109	5	only	only	ADV
ajst-28813	109	6	improves	improve	VERB
ajst-28813	109	7	the	the	DET
ajst-28813	109	8	reliability	reliability	NOUN
ajst-28813	109	9	and	and	CCONJ
ajst-28813	109	10	security	security	NOUN
ajst-28813	109	11	of	of	ADP
ajst-28813	109	12	the	the	DET
ajst-28813	109	13	system	system	NOUN
ajst-28813	109	14	,	,	PUNCT
ajst-28813	109	15	but	but	CCONJ
ajst-28813	109	16	also	also	ADV
ajst-28813	109	17	effectively	effectively	ADV
ajst-28813	109	18	reduces	reduce	VERB
ajst-28813	109	19	the	the	DET
ajst-28813	109	20	maintenance	maintenance	NOUN
ajst-28813	109	21	cost	cost	NOUN
ajst-28813	109	22	.	.	PUNCT
ajst-28813	110	1	figure	figure	NOUN
ajst-28813	110	2	2	2	NUM
ajst-28813	110	3	-	-	SYM
ajst-28813	110	4	1	1	NUM
ajst-28813	110	5	.	.	PUNCT
ajst-28813	111	1	diagram	diagram	NOUN
ajst-28813	111	2	of	of	ADP
ajst-28813	111	3	different	different	ADJ
ajst-28813	111	4	types	type	NOUN
ajst-28813	111	5	of	of	ADP
ajst-28813	111	6	activation	activation	NOUN
ajst-28813	111	7	functions	function	NOUN
ajst-28813	111	8	(	(	PUNCT
ajst-28813	111	9	3	3	NUM
ajst-28813	111	10	)	)	PUNCT
ajst-28813	111	11	noise	noise	NOUN
ajst-28813	111	12	reduction	reduction	NOUN
ajst-28813	111	13	treatment	treatment	NOUN
ajst-28813	111	14	noise	noise	NOUN
ajst-28813	111	15	reduction	reduction	NOUN
ajst-28813	111	16	processing	processing	NOUN
ajst-28813	111	17	is	be	AUX
ajst-28813	111	18	an	an	DET
ajst-28813	111	19	important	important	ADJ
ajst-28813	111	20	step	step	NOUN
ajst-28813	111	21	in	in	ADP
ajst-28813	111	22	data	datum	NOUN
ajst-28813	111	23	preprocessing	preprocessing	NOUN
ajst-28813	111	24	,	,	PUNCT
ajst-28813	111	25	especially	especially	ADV
ajst-28813	111	26	in	in	ADP
ajst-28813	111	27	the	the	DET
ajst-28813	111	28	processing	processing	NOUN
ajst-28813	111	29	of	of	ADP
ajst-28813	111	30	industrial	industrial	ADJ
ajst-28813	111	31	field	field	NOUN
ajst-28813	111	32	data	datum	NOUN
ajst-28813	111	33	,	,	PUNCT
ajst-28813	111	34	due	due	ADP
ajst-28813	111	35	to	to	ADP
ajst-28813	111	36	the	the	DET
ajst-28813	111	37	influence	influence	NOUN
ajst-28813	111	38	of	of	ADP
ajst-28813	111	39	environmental	environmental	ADJ
ajst-28813	111	40	noise	noise	NOUN
ajst-28813	111	41	,	,	PUNCT
ajst-28813	111	42	equipment	equipment	NOUN
ajst-28813	111	43	aging	aging	NOUN
ajst-28813	111	44	or	or	CCONJ
ajst-28813	111	45	sensor	sensor	NOUN
ajst-28813	111	46	accuracy	accuracy	NOUN
ajst-28813	111	47	and	and	CCONJ
ajst-28813	111	48	other	other	ADJ
ajst-28813	111	49	factors	factor	NOUN
ajst-28813	111	50	,	,	PUNCT
ajst-28813	111	51	the	the	DET
ajst-28813	111	52	data	datum	NOUN
ajst-28813	111	53	often	often	ADV
ajst-28813	111	54	contains	contain	VERB
ajst-28813	111	55	a	a	DET
ajst-28813	111	56	lot	lot	NOUN
ajst-28813	111	57	of	of	ADP
ajst-28813	111	58	noise	noise	NOUN
ajst-28813	111	59	.	.	PUNCT
ajst-28813	112	1	the	the	DET
ajst-28813	112	2	presence	presence	NOUN
ajst-28813	112	3	of	of	ADP
ajst-28813	112	4	noise	noise	NOUN
ajst-28813	112	5	will	will	AUX
ajst-28813	112	6	disturb	disturb	VERB
ajst-28813	112	7	the	the	DET
ajst-28813	112	8	model	model	NOUN
ajst-28813	112	9	to	to	PART
ajst-28813	112	10	identify	identify	VERB
ajst-28813	112	11	the	the	DET
ajst-28813	112	12	real	real	ADJ
ajst-28813	112	13	signal	signal	NOUN
ajst-28813	112	14	and	and	CCONJ
ajst-28813	112	15	reduce	reduce	VERB
ajst-28813	112	16	the	the	DET
ajst-28813	112	17	prediction	prediction	NOUN
ajst-28813	112	18	accuracy	accuracy	NOUN
ajst-28813	112	19	and	and	CCONJ
ajst-28813	112	20	reliability	reliability	NOUN
ajst-28813	112	21	.	.	PUNCT
ajst-28813	113	1	therefore	therefore	ADV
ajst-28813	113	2	,	,	PUNCT
ajst-28813	113	3	sampling	sample	VERB
ajst-28813	113	4	effective	effective	ADJ
ajst-28813	113	5	noise	noise	NOUN
ajst-28813	113	6	reduction	reduction	NOUN
ajst-28813	113	7	techniques	technique	NOUN
ajst-28813	113	8	are	be	AUX
ajst-28813	113	9	crucial	crucial	ADJ
ajst-28813	113	10	to	to	PART
ajst-28813	113	11	improve	improve	VERB
ajst-28813	113	12	data	datum	NOUN
ajst-28813	113	13	quality	quality	NOUN
ajst-28813	113	14	and	and	CCONJ
ajst-28813	113	15	ensure	ensure	VERB
ajst-28813	113	16	model	model	NOUN
ajst-28813	113	17	performance	performance	NOUN
ajst-28813	113	18	.	.	PUNCT
ajst-28813	114	1	here	here	ADV
ajst-28813	114	2	,	,	PUNCT
ajst-28813	114	3	using	use	VERB
ajst-28813	114	4	matlab	matlab	PROPN
ajst-28813	114	5	for	for	ADP
ajst-28813	114	6	joint	joint	ADJ
ajst-28813	114	7	simulation	simulation	NOUN
ajst-28813	114	8	and	and	CCONJ
ajst-28813	114	9	simulink	simulink	NOUN
ajst-28813	114	10	to	to	PART
ajst-28813	114	11	import	import	VERB
ajst-28813	114	12	real	real	ADJ
ajst-28813	114	13	-	-	PUNCT
ajst-28813	114	14	time	time	NOUN
ajst-28813	114	15	data	datum	NOUN
ajst-28813	114	16	from	from	ADP
ajst-28813	114	17	the	the	DET
ajst-28813	114	18	electric	electric	ADJ
ajst-28813	114	19	submersible	submersible	ADJ
ajst-28813	114	20	pump	pump	NOUN
ajst-28813	114	21	,	,	PUNCT
ajst-28813	114	22	the	the	DET
ajst-28813	114	23	noise	noise	NOUN
ajst-28813	114	24	situation	situation	NOUN
ajst-28813	114	25	in	in	ADP
ajst-28813	114	26	the	the	DET
ajst-28813	114	27	data	data	NOUN
ajst-28813	114	28	is	be	AUX
ajst-28813	114	29	shown	show	VERB
ajst-28813	114	30	in	in	ADP
ajst-28813	114	31	figure	figure	NOUN
ajst-28813	114	32	2	2	NUM
ajst-28813	114	33	-	-	SYM
ajst-28813	114	34	2	2	NUM
ajst-28813	114	35	.	.	PUNCT
ajst-28813	114	36	figure	figure	NOUN
ajst-28813	114	37	2	2	NUM
ajst-28813	114	38	-	-	SYM
ajst-28813	114	39	2	2	NUM
ajst-28813	114	40	.	.	PUNCT
ajst-28813	114	41	schematic	schematic	ADJ
ajst-28813	114	42	diagram	diagram	NOUN
ajst-28813	114	43	of	of	ADP
ajst-28813	114	44	downhole	downhole	NOUN
ajst-28813	114	45	data	datum	NOUN
ajst-28813	114	46	(	(	PUNCT
ajst-28813	114	47	including	include	VERB
ajst-28813	114	48	noise	noise	NOUN
ajst-28813	114	49	)	)	PUNCT
ajst-28813	114	50	249	249	NUM
ajst-28813	114	51	in	in	ADP
ajst-28813	114	52	the	the	DET
ajst-28813	114	53	esn	esn	PROPN
ajst-28813	114	54	network	network	NOUN
ajst-28813	114	55	model	model	NOUN
ajst-28813	114	56	of	of	ADP
ajst-28813	114	57	the	the	DET
ajst-28813	114	58	electric	electric	ADJ
ajst-28813	114	59	submersible	submersible	ADJ
ajst-28813	114	60	pump	pump	NOUN
ajst-28813	114	61	,	,	PUNCT
ajst-28813	114	62	the	the	DET
ajst-28813	114	63	noise	noise	NOUN
ajst-28813	114	64	reduction	reduction	NOUN
ajst-28813	114	65	process	process	NOUN
ajst-28813	114	66	usually	usually	ADV
ajst-28813	114	67	includes	include	VERB
ajst-28813	114	68	the	the	DET
ajst-28813	114	69	following	follow	VERB
ajst-28813	114	70	aspects	aspect	NOUN
ajst-28813	114	71	:	:	PUNCT
ajst-28813	114	72	removing	remove	VERB
ajst-28813	114	73	abnormal	abnormal	ADJ
ajst-28813	114	74	values	value	NOUN
ajst-28813	114	75	due	due	ADP
ajst-28813	114	76	to	to	ADP
ajst-28813	114	77	measurement	measurement	NOUN
ajst-28813	114	78	errors	error	NOUN
ajst-28813	114	79	or	or	CCONJ
ajst-28813	114	80	interference	interference	NOUN
ajst-28813	114	81	during	during	ADP
ajst-28813	114	82	data	data	NOUN
ajst-28813	114	83	transmission	transmission	NOUN
ajst-28813	114	84	;	;	PUNCT
ajst-28813	114	85	a	a	DET
ajst-28813	114	86	filtering	filter	VERB
ajst-28813	114	87	technique	technique	NOUN
ajst-28813	114	88	that	that	PRON
ajst-28813	114	89	removes	remove	VERB
ajst-28813	114	90	the	the	DET
ajst-28813	114	91	unwanted	unwanted	ADJ
ajst-28813	114	92	noise	noise	NOUN
ajst-28813	114	93	components	component	NOUN
ajst-28813	114	94	based	base	VERB
ajst-28813	114	95	on	on	ADP
ajst-28813	114	96	the	the	DET
ajst-28813	114	97	frequency	frequency	NOUN
ajst-28813	114	98	characteristics	characteristic	NOUN
ajst-28813	114	99	of	of	ADP
ajst-28813	114	100	the	the	DET
ajst-28813	114	101	signal	signal	NOUN
ajst-28813	114	102	and	and	CCONJ
ajst-28813	114	103	an	an	DET
ajst-28813	114	104	adaptive	adaptive	ADJ
ajst-28813	114	105	filtering	filtering	NOUN
ajst-28813	114	106	technique	technique	NOUN
ajst-28813	114	107	that	that	PRON
ajst-28813	114	108	can	can	AUX
ajst-28813	114	109	automatically	automatically	ADV
ajst-28813	114	110	adjust	adjust	VERB
ajst-28813	114	111	its	its	PRON
ajst-28813	114	112	parameters	parameter	NOUN
ajst-28813	114	113	according	accord	VERB
ajst-28813	114	114	to	to	ADP
ajst-28813	114	115	the	the	DET
ajst-28813	114	116	statistical	statistical	ADJ
ajst-28813	114	117	characteristics	characteristic	NOUN
ajst-28813	114	118	of	of	ADP
ajst-28813	114	119	the	the	DET
ajst-28813	114	120	signal	signal	NOUN
ajst-28813	114	121	;	;	PUNCT
ajst-28813	114	122	or	or	CCONJ
ajst-28813	114	123	by	by	ADP
ajst-28813	114	124	wavelet	wavelet	NOUN
ajst-28813	114	125	transform	transform	NOUN
ajst-28813	114	126	,	,	PUNCT
ajst-28813	114	127	the	the	DET
ajst-28813	114	128	signal	signal	NOUN
ajst-28813	114	129	can	can	AUX
ajst-28813	114	130	be	be	AUX
ajst-28813	114	131	decomposed	decompose	VERB
ajst-28813	114	132	into	into	ADP
ajst-28813	114	133	components	component	NOUN
ajst-28813	114	134	of	of	ADP
ajst-28813	114	135	different	different	ADJ
ajst-28813	114	136	scales	scale	NOUN
ajst-28813	114	137	and	and	CCONJ
ajst-28813	114	138	effectively	effectively	ADV
ajst-28813	114	139	suppress	suppress	VERB
ajst-28813	114	140	the	the	DET
ajst-28813	114	141	noise	noise	NOUN
ajst-28813	114	142	components	component	NOUN
ajst-28813	114	143	.	.	PUNCT
ajst-28813	115	1	in	in	ADP
ajst-28813	115	2	this	this	DET
ajst-28813	115	3	study	study	NOUN
ajst-28813	115	4	,	,	PUNCT
ajst-28813	115	5	the	the	DET
ajst-28813	115	6	measured	measured	ADJ
ajst-28813	115	7	values	value	NOUN
ajst-28813	115	8	of	of	ADP
ajst-28813	115	9	wellhead	wellhead	NOUN
ajst-28813	115	10	pressure	pressure	NOUN
ajst-28813	115	11	(	(	PUNCT
ajst-28813	115	12	bhp	bhp	PROPN
ajst-28813	115	13	)	)	PUNCT
ajst-28813	115	14	,	,	PUNCT
ajst-28813	115	15	well	well	INTJ
ajst-28813	115	16	bottom	bottom	ADJ
ajst-28813	115	17	pressure	pressure	NOUN
ajst-28813	115	18	(	(	PUNCT
ajst-28813	115	19	whp	whp	ADJ
ajst-28813	115	20	)	)	PUNCT
ajst-28813	115	21	and	and	CCONJ
ajst-28813	115	22	flow	flow	NOUN
ajst-28813	115	23	rate	rate	NOUN
ajst-28813	115	24	q	q	PROPN
ajst-28813	115	25	,	,	PUNCT
ajst-28813	115	26	combined	combine	VERB
ajst-28813	115	27	with	with	ADP
ajst-28813	115	28	the	the	DET
ajst-28813	115	29	electric	electric	ADJ
ajst-28813	115	30	submersible	submersible	ADJ
ajst-28813	115	31	pump	pump	NOUN
ajst-28813	115	32	system	system	NOUN
ajst-28813	115	33	model	model	NOUN
ajst-28813	115	34	and	and	CCONJ
ajst-28813	115	35	the	the	DET
ajst-28813	115	36	filtering	filter	VERB
ajst-28813	115	37	results	result	NOUN
ajst-28813	115	38	will	will	AUX
ajst-28813	115	39	be	be	AUX
ajst-28813	115	40	used	use	VERB
ajst-28813	115	41	for	for	ADP
ajst-28813	115	42	the	the	DET
ajst-28813	115	43	prediction	prediction	NOUN
ajst-28813	115	44	system	system	NOUN
ajst-28813	115	45	for	for	ADP
ajst-28813	115	46	system	system	NOUN
ajst-28813	115	47	state	state	NOUN
ajst-28813	115	48	control	control	NOUN
ajst-28813	115	49	.	.	PUNCT
ajst-28813	116	1	the	the	DET
ajst-28813	116	2	spatial	spatial	ADJ
ajst-28813	116	3	equation	equation	NOUN
ajst-28813	116	4	of	of	ADP
ajst-28813	116	5	the	the	DET
ajst-28813	116	6	state	state	NOUN
ajst-28813	116	7	of	of	ADP
ajst-28813	116	8	the	the	DET
ajst-28813	116	9	system	system	NOUN
ajst-28813	116	10	is	be	AUX
ajst-28813	116	11	generally	generally	ADV
ajst-28813	116	12	formulated	formulate	VERB
ajst-28813	116	13	as	as	ADP
ajst-28813	116	14	a	a	DET
ajst-28813	116	15	discrete	discrete	ADJ
ajst-28813	116	16	nonlinearity	nonlinearity	NOUN
ajst-28813	116	17	,	,	PUNCT
ajst-28813	116	18	as	as	SCONJ
ajst-28813	116	19	shown	show	VERB
ajst-28813	116	20	in	in	ADP
ajst-28813	116	21	the	the	DET
ajst-28813	116	22	following	follow	VERB
ajst-28813	116	23	equation	equation	NOUN
ajst-28813	116	24	:	:	PUNCT
ajst-28813	116	25			PROPN
ajst-28813	116	26			PROPN
ajst-28813	116	27	,	,	PUNCT
ajst-28813	116	28	,	,	PUNCT
ajst-28813	116	29	x	x	PROPN
ajst-28813	116	30	f	f	NOUN
ajst-28813	116	31	x	x	SYM
ajst-28813	116	32	u	u	NOUN
ajst-28813	116	33	t	t	PROPN
ajst-28813	116	34	w	w	VERB
ajst-28813	116	35			PROPN
ajst-28813	116	36			PRON
ajst-28813	116	37	(	(	PUNCT
ajst-28813	116	38	2	2	NUM
ajst-28813	116	39	-	-	SYM
ajst-28813	116	40	3	3	NUM
ajst-28813	116	41	)	)	PUNCT
ajst-28813	116	42			NOUN
ajst-28813	116	43			PROPN
ajst-28813	116	44	,	,	PUNCT
ajst-28813	116	45	,	,	PUNCT
ajst-28813	116	46	y	y	PROPN
ajst-28813	116	47	g	g	NOUN
ajst-28813	116	48	x	x	SYM
ajst-28813	116	49	u	u	PROPN
ajst-28813	116	50	t	t	PROPN
ajst-28813	116	51	v	v	ADV
ajst-28813	116	52			X
ajst-28813	116	53	(	(	PUNCT
ajst-28813	116	54	2	2	NUM
ajst-28813	116	55	-	-	SYM
ajst-28813	116	56	4	4	NUM
ajst-28813	116	57	)	)	PUNCT
ajst-28813	116	58	in	in	ADP
ajst-28813	116	59	the	the	DET
ajst-28813	116	60	formula	formula	NOUN
ajst-28813	116	61	:	:	PUNCT
ajst-28813	116	62	x	x	X
ajst-28813	116	63	——	——	NOUN
ajst-28813	116	64	state	state	NOUN
ajst-28813	116	65	vector	vector	NOUN
ajst-28813	116	66	;	;	PUNCT
ajst-28813	116	67	u	u	NOUN
ajst-28813	116	68	——	——	NOUN
ajst-28813	116	69	system	system	NOUN
ajst-28813	116	70	input	input	NOUN
ajst-28813	116	71	variable	variable	NOUN
ajst-28813	116	72	;	;	PUNCT
ajst-28813	116	73	w	w	X
ajst-28813	116	74	,	,	PUNCT
ajst-28813	116	75	v	v	INTJ
ajst-28813	116	76	—	—	PUNCT
ajst-28813	116	77	—	—	PUNCT
ajst-28813	116	78	system	system	NOUN
ajst-28813	116	79	process	process	NOUN
ajst-28813	116	80	interference	interference	NOUN
ajst-28813	116	81	,	,	PUNCT
ajst-28813	116	82	and	and	CCONJ
ajst-28813	116	83	output	output	NOUN
ajst-28813	116	84	interference	interference	NOUN
ajst-28813	116	85	;	;	PUNCT
ajst-28813	116	86	the	the	DET
ajst-28813	116	87	system	system	NOUN
ajst-28813	116	88	state	state	NOUN
ajst-28813	116	89	variable	variable	NOUN
ajst-28813	116	90	was	be	AUX
ajst-28813	116	91	defined	define	VERB
ajst-28813	116	92	in	in	ADP
ajst-28813	116	93	this	this	DET
ajst-28813	116	94	study	study	NOUN
ajst-28813	116	95	as	as	ADP
ajst-28813	116	96	:	:	PUNCT
ajst-28813	116	97	[	[	PUNCT
ajst-28813	116	98	,	,	PUNCT
ajst-28813	116	99	,	,	PUNCT
ajst-28813	116	100	]	]	PUNCT
ajst-28813	116	101	bh	bh	PROPN
ajst-28813	116	102	whx	whx	NOUN
ajst-28813	116	103	p	p	PROPN
ajst-28813	116	104	p	p	X
ajst-28813	116	105	q	q	ADJ
ajst-28813	116	106	(	(	PUNCT
ajst-28813	116	107	2	2	NUM
ajst-28813	116	108	-	-	SYM
ajst-28813	116	109	5	5	NUM
ajst-28813	116	110	)	)	PUNCT
ajst-28813	116	111	the	the	DET
ajst-28813	116	112	main	main	ADJ
ajst-28813	116	113	state	state	NOUN
ajst-28813	116	114	of	of	ADP
ajst-28813	116	115	the	the	DET
ajst-28813	116	116	system	system	NOUN
ajst-28813	116	117	can	can	AUX
ajst-28813	116	118	be	be	AUX
ajst-28813	116	119	described	describe	VERB
ajst-28813	116	120	using	use	VERB
ajst-28813	116	121	the	the	DET
ajst-28813	116	122	following	follow	VERB
ajst-28813	116	123	equation	equation	NOUN
ajst-28813	116	124	:	:	PUNCT
ajst-28813	117	1			NOUN
ajst-28813	117	2			SYM
ajst-28813	117	3			NOUN
ajst-28813	117	4			SYM
ajst-28813	117	5			NOUN
ajst-28813	117	6			PUNCT
ajst-28813	117	7			NOUN
ajst-28813	117	8			NOUN
ajst-28813	117	9	1	1	NUM
ajst-28813	117	10	1	1	NUM
ajst-28813	117	11	2	2	NUM
ajst-28813	117	12	2	2	NUM
ajst-28813	117	13	3	3	NUM
ajst-28813	117	14	(	(	PUNCT
ajst-28813	117	15	)	)	PUNCT
ajst-28813	117	16	1	1	NUM
ajst-28813	117	17	(	(	PUNCT
ajst-28813	117	18	)	)	PUNCT
ajst-28813	117	19	bh	bh	NOUN
ajst-28813	118	1	r	r	NOUN
ajst-28813	118	2	wh	wh	NOUN
ajst-28813	118	3	c	c	NOUN
ajst-28813	118	4	bh	bh	PROPN
ajst-28813	118	5	wh	wh	PROPN
ajst-28813	118	6	w	w	PROPN
ajst-28813	118	7	f	f	PROPN
ajst-28813	118	8	p	p	NOUN
ajst-28813	118	9	dp	dp	NOUN
ajst-28813	118	10	v	v	ADP
ajst-28813	118	11	q	q	NOUN
ajst-28813	118	12	q	q	PROPN
ajst-28813	118	13	w	w	PROPN
ajst-28813	118	14	t	t	PROPN
ajst-28813	118	15	dt	dt	NOUN
ajst-28813	118	16	dp	dp	PROPN
ajst-28813	118	17	v	v	ADP
ajst-28813	118	18	q	q	X
ajst-28813	118	19	q	q	PROPN
ajst-28813	118	20	w	w	PROPN
ajst-28813	118	21	t	t	NOUN
ajst-28813	118	22	dt	dt	X
ajst-28813	118	23	dq	dq	ADP
ajst-28813	118	24	p	p	PROPN
ajst-28813	118	25	p	p	PROPN
ajst-28813	118	26	gh	gh	PROPN
ajst-28813	118	27	p	p	PROPN
ajst-28813	118	28	p	p	PROPN
ajst-28813	118	29	w	w	PROPN
ajst-28813	118	30	t	t	PROPN
ajst-28813	118	31	dt	dt	X
ajst-28813	118	32	m	m	PROPN
ajst-28813	118	33			PROPN
ajst-28813	118	34			PROPN
ajst-28813	118	35			ADP
ajst-28813	118	36			PROPN
ajst-28813	118	37			PROPN
ajst-28813	118	38			PROPN
ajst-28813	118	39			ADP
ajst-28813	118	40			PROPN
ajst-28813	118	41			PROPN
ajst-28813	118	42			PROPN
ajst-28813	118	43			PROPN
ajst-28813	118	44			PROPN
ajst-28813	118	45			PROPN
ajst-28813	118	46			X
ajst-28813	118	47	(	(	PUNCT
ajst-28813	118	48	2	2	NUM
ajst-28813	118	49	-	-	SYM
ajst-28813	118	50	6	6	NUM
ajst-28813	118	51	)	)	PUNCT
ajst-28813	118	52	in	in	ADP
ajst-28813	118	53	the	the	DET
ajst-28813	118	54	formula	formula	NOUN
ajst-28813	118	55	:	:	PUNCT
ajst-28813	118	56	(	(	PUNCT
ajst-28813	118	57	)	)	PUNCT
ajst-28813	118	58	iw	iw	PROPN
ajst-28813	118	59	t	t	PROPN
ajst-28813	118	60	—	—	PUNCT
ajst-28813	118	61	—	—	PUNCT
ajst-28813	118	62	internal	internal	ADJ
ajst-28813	118	63	interference	interference	NOUN
ajst-28813	118	64	of	of	ADP
ajst-28813	118	65	the	the	DET
ajst-28813	118	66	system	system	NOUN
ajst-28813	118	67	;	;	PUNCT
ajst-28813	118	68	kalman	kalman	PROPN
ajst-28813	118	69	filtering	filtering	NOUN
ajst-28813	118	70	is	be	AUX
ajst-28813	118	71	an	an	DET
ajst-28813	118	72	efficient	efficient	ADJ
ajst-28813	118	73	recursive	recursive	ADJ
ajst-28813	118	74	data	datum	NOUN
ajst-28813	118	75	fusion	fusion	NOUN
ajst-28813	118	76	method	method	NOUN
ajst-28813	118	77	to	to	PART
ajst-28813	118	78	estimate	estimate	VERB
ajst-28813	118	79	the	the	DET
ajst-28813	118	80	state	state	NOUN
ajst-28813	118	81	of	of	ADP
ajst-28813	118	82	the	the	DET
ajst-28813	118	83	model	model	NOUN
ajst-28813	118	84	by	by	ADP
ajst-28813	118	85	minimizing	minimize	VERB
ajst-28813	118	86	the	the	DET
ajst-28813	118	87	error	error	NOUN
ajst-28813	118	88	variance	variance	NOUN
ajst-28813	118	89	.	.	PUNCT
ajst-28813	119	1	here	here	ADV
ajst-28813	119	2	the	the	DET
ajst-28813	119	3	extended	extended	ADJ
ajst-28813	119	4	kalman	kalman	NOUN
ajst-28813	119	5	filter	filter	NOUN
ajst-28813	119	6	is	be	AUX
ajst-28813	119	7	used	use	VERB
ajst-28813	119	8	as	as	ADP
ajst-28813	119	9	a	a	DET
ajst-28813	119	10	systematic	systematic	ADJ
ajst-28813	119	11	observation	observation	NOUN
ajst-28813	119	12	strategy	strategy	NOUN
ajst-28813	119	13	,	,	PUNCT
ajst-28813	119	14	and	and	CCONJ
ajst-28813	119	15	the	the	DET
ajst-28813	119	16	flow	flow	NOUN
ajst-28813	119	17	chart	chart	NOUN
ajst-28813	119	18	is	be	AUX
ajst-28813	119	19	shown	show	VERB
ajst-28813	119	20	in	in	ADP
ajst-28813	119	21	figure	figure	NOUN
ajst-28813	119	22	2	2	NUM
ajst-28813	119	23	-	-	SYM
ajst-28813	119	24	3	3	NUM
ajst-28813	119	25	.	.	PUNCT
ajst-28813	119	26	figure	figure	NOUN
ajst-28813	119	27	2	2	NUM
ajst-28813	119	28	-	-	SYM
ajst-28813	119	29	3	3	NUM
ajst-28813	119	30	.	.	PUNCT
ajst-28813	119	31	flow	flow	NOUN
ajst-28813	119	32	chart	chart	NOUN
ajst-28813	119	33	of	of	ADP
ajst-28813	119	34	extended	extended	ADJ
ajst-28813	119	35	kalman	kalman	NOUN
ajst-28813	119	36	filter	filter	NOUN
ajst-28813	119	37	observations	observation	NOUN
ajst-28813	119	38	extended	extend	VERB
ajst-28813	119	39	kalman	kalman	NOUN
ajst-28813	119	40	filtering	filtering	NOUN
ajst-28813	119	41	involves	involve	VERB
ajst-28813	119	42	a	a	DET
ajst-28813	119	43	taylor	taylor	PROPN
ajst-28813	119	44	series	series	NOUN
ajst-28813	119	45	expansion	expansion	NOUN
ajst-28813	119	46	of	of	ADP
ajst-28813	119	47	the	the	DET
ajst-28813	119	48	model	model	NOUN
ajst-28813	119	49	of	of	ADP
ajst-28813	119	50	nonlinear	nonlinear	ADJ
ajst-28813	119	51	systems	system	NOUN
ajst-28813	119	52	and	and	CCONJ
ajst-28813	119	53	a	a	DET
ajst-28813	119	54	truncation	truncation	NOUN
ajst-28813	119	55	treatment	treatment	NOUN
ajst-28813	119	56	in	in	ADP
ajst-28813	119	57	the	the	DET
ajst-28813	119	58	expanded	expand	VERB
ajst-28813	119	59	equations	equation	NOUN
ajst-28813	119	60	,	,	PUNCT
ajst-28813	119	61	usually	usually	ADV
ajst-28813	119	62	choosing	choose	VERB
ajst-28813	119	63	the	the	DET
ajst-28813	119	64	first	first	ADJ
ajst-28813	119	65	order	order	NOUN
ajst-28813	119	66	truncation	truncation	NOUN
ajst-28813	119	67	.	.	PUNCT
ajst-28813	120	1	this	this	DET
ajst-28813	120	2	truncation	truncation	NOUN
ajst-28813	120	3	method	method	NOUN
ajst-28813	120	4	helps	help	VERB
ajst-28813	120	5	to	to	PART
ajst-28813	120	6	reduce	reduce	VERB
ajst-28813	120	7	the	the	DET
ajst-28813	120	8	computational	computational	ADJ
ajst-28813	120	9	burden	burden	NOUN
ajst-28813	120	10	of	of	ADP
ajst-28813	120	11	the	the	DET
ajst-28813	120	12	system	system	NOUN
ajst-28813	120	13	.	.	PUNCT
ajst-28813	121	1	when	when	SCONJ
ajst-28813	121	2	a	a	DET
ajst-28813	121	3	nonlinear	nonlinear	ADJ
ajst-28813	121	4	system	system	NOUN
ajst-28813	121	5	is	be	AUX
ajst-28813	121	6	approximately	approximately	ADV
ajst-28813	121	7	linear	linear	ADJ
ajst-28813	121	8	,	,	PUNCT
ajst-28813	121	9	the	the	DET
ajst-28813	121	10	system	system	NOUN
ajst-28813	121	11	can	can	AUX
ajst-28813	121	12	be	be	AUX
ajst-28813	121	13	described	describe	VERB
ajst-28813	121	14	as	as	ADP
ajst-28813	121	15	:	:	PUNCT
ajst-28813	121	16	1k	1k	NUM
ajst-28813	121	17	k	k	PROPN
ajst-28813	122	1	k	k	PROPN
ajst-28813	123	1	k	k	PROPN
ajst-28813	124	1	k	k	PROPN
ajst-28813	124	2	k	k	X
ajst-28813	124	3	x	x	PUNCT
ajst-28813	124	4	ax	ax	NOUN
ajst-28813	124	5	bu	bu	PROPN
ajst-28813	124	6	w	w	PROPN
ajst-28813	124	7	y	y	PROPN
ajst-28813	124	8	hx	hx	PROPN
ajst-28813	124	9	v	v	PROPN
ajst-28813	124	10			PROPN
ajst-28813	124	11			PUNCT
ajst-28813	124	12			PROPN
ajst-28813	124	13			PROPN
ajst-28813	124	14			X
ajst-28813	124	15	(	(	PUNCT
ajst-28813	124	16	2	2	NUM
ajst-28813	124	17	-	-	SYM
ajst-28813	124	18	7	7	NUM
ajst-28813	124	19	)	)	PUNCT
ajst-28813	124	20	according	accord	VERB
ajst-28813	124	21	to	to	ADP
ajst-28813	124	22	the	the	DET
ajst-28813	124	23	system	system	NOUN
ajst-28813	124	24	status	status	NOUN
ajst-28813	124	25	[	[	PUNCT
ajst-28813	124	26	,	,	PUNCT
ajst-28813	124	27	,	,	PUNCT
ajst-28813	124	28	]	]	PUNCT
ajst-28813	124	29	bh	bh	PROPN
ajst-28813	124	30	whx	whx	NOUN
ajst-28813	124	31	p	p	PROPN
ajst-28813	124	32	p	p	X
ajst-28813	124	33	q	q	PROPN
ajst-28813	124	34	,	,	PUNCT
ajst-28813	124	35	combined	combined	ADJ
ajst-28813	124	36	equation	equation	NOUN
ajst-28813	124	37	of	of	ADP
ajst-28813	124	38	state	state	NOUN
ajst-28813	124	39	of	of	ADP
ajst-28813	124	40	the	the	DET
ajst-28813	124	41	system	system	NOUN
ajst-28813	124	42	(	(	PUNCT
ajst-28813	124	43	2	2	NUM
ajst-28813	124	44	-	-	SYM
ajst-28813	124	45	8)	8)	NUM
ajst-28813	124	46	.	.	PUNCT
ajst-28813	125	1	the	the	DET
ajst-28813	125	2	extended	extended	ADJ
ajst-28813	125	3	kalman	kalman	NOUN
ajst-28813	125	4	algorithm	algorithm	PROPN
ajst-28813	125	5	is	be	AUX
ajst-28813	125	6	:	:	PUNCT
ajst-28813	125	7			NOUN
ajst-28813	125	8			SYM
ajst-28813	125	9			NOUN
ajst-28813	125	10			PUNCT
ajst-28813	125	11			NOUN
ajst-28813	125	12			NOUN
ajst-28813	125	13	1	1	NUM
ajst-28813	125	14	2	2	NUM
ajst-28813	125	15	1	1	NUM
ajst-28813	125	16	bh	bh	NOUN
ajst-28813	125	17	r	r	NOUN
ajst-28813	125	18	wh	wh	NOUN
ajst-28813	125	19	c	c	NOUN
ajst-28813	125	20	bh	bh	PROPN
ajst-28813	125	21	wh	wh	PROPN
ajst-28813	125	22	w	w	PROPN
ajst-28813	126	1	f	f	PROPN
ajst-28813	126	2	p	p	X
ajst-28813	126	3	v	v	ADP
ajst-28813	126	4	p	p	NOUN
ajst-28813	126	5	q	q	NOUN
ajst-28813	126	6	q	q	NOUN
ajst-28813	126	7	v	v	ADP
ajst-28813	126	8	p	p	NOUN
ajst-28813	126	9	q	q	X
ajst-28813	126	10	q	q	NOUN
ajst-28813	126	11	q	q	X
ajst-28813	126	12	p	p	X
ajst-28813	127	1	p	p	PROPN
ajst-28813	127	2	gh	gh	PROPN
ajst-28813	127	3	p	p	PROPN
ajst-28813	127	4	p	p	PROPN
ajst-28813	127	5	m	m	PROPN
ajst-28813	127	6			PROPN
ajst-28813	127	7			PROPN
ajst-28813	127	8			PROPN
ajst-28813	127	9			PROPN
ajst-28813	127	10			PROPN
ajst-28813	127	11			PROPN
ajst-28813	127	12			PROPN
ajst-28813	127	13			PROPN
ajst-28813	127	14			PROPN
ajst-28813	127	15			PROPN
ajst-28813	127	16			PROPN
ajst-28813	127	17			NUM
ajst-28813	127	18			NUM
ajst-28813	127	19			NUM
ajst-28813	127	20	(	(	PUNCT
ajst-28813	127	21	2	2	NUM
ajst-28813	127	22	-	-	SYM
ajst-28813	127	23	8)	8)	NUM
ajst-28813	127	24	step1	step1	PROPN
ajst-28813	127	25	calculate	calculate	VERB
ajst-28813	127	26	the	the	DET
ajst-28813	127	27	jacobian	jacobian	ADJ
ajst-28813	127	28	matrix	matrix	NOUN
ajst-28813	127	29	1kf	1kf	VERB
ajst-28813	127	30			PROPN
ajst-28813	127	31	,	,	PUNCT
ajst-28813	127	32	namely	namely	ADV
ajst-28813	127	33	,	,	PUNCT
ajst-28813	127	34	the	the	DET
ajst-28813	127	35	first	first	ADJ
ajst-28813	127	36	-	-	PUNCT
ajst-28813	127	37	order	order	NOUN
ajst-28813	127	38	taylor	taylor	NOUN
ajst-28813	127	39	expansion	expansion	NOUN
ajst-28813	127	40	at	at	ADP
ajst-28813	127	41	the	the	DET
ajst-28813	127	42	current	current	ADJ
ajst-28813	127	43	computation	computation	NOUN
ajst-28813	127	44	point	point	NOUN
ajst-28813	127	45	;	;	PUNCT
ajst-28813	127	46	𝐹	𝐹	PROPN
ajst-28813	127	47	𝜕𝑓	𝜕𝑓	ADJ
ajst-28813	127	48	𝜕𝑥	𝜕𝑥	NOUN
ajst-28813	127	49	|	|	NOUN
ajst-28813	127	50	in	in	ADP
ajst-28813	127	51	this	this	DET
ajst-28813	127	52	study	study	NOUN
ajst-28813	127	53	,	,	PUNCT
ajst-28813	127	54	the	the	DET
ajst-28813	127	55	nonlinear	nonlinear	ADJ
ajst-28813	127	56	model	model	NOUN
ajst-28813	127	57	of	of	ADP
ajst-28813	127	58	the	the	DET
ajst-28813	127	59	system	system	NOUN
ajst-28813	127	60	is	be	AUX
ajst-28813	127	61	described	describe	VERB
ajst-28813	127	62	by	by	ADP
ajst-28813	127	63	equation	equation	NOUN
ajst-28813	127	64	(	(	PUNCT
ajst-28813	127	65	3	3	NUM
ajst-28813	127	66	-	-	SYM
ajst-28813	127	67	10	10	NUM
ajst-28813	127	68	)	)	PUNCT
ajst-28813	127	69	.	.	PUNCT
ajst-28813	128	1	the	the	DET
ajst-28813	128	2	state	state	NOUN
ajst-28813	128	3	of	of	ADP
ajst-28813	128	4	the	the	DET
ajst-28813	128	5	system	system	NOUN
ajst-28813	128	6	in	in	ADP
ajst-28813	128	7	this	this	DET
ajst-28813	128	8	paper	paper	NOUN
ajst-28813	128	9	is	be	AUX
ajst-28813	128	10	a	a	DET
ajst-28813	128	11	3d	3d	NUM
ajst-28813	128	12	vector	vector	NOUN
ajst-28813	128	13	.	.	PUNCT
ajst-28813	129	1	the	the	DET
ajst-28813	129	2	linearization	linearization	NOUN
ajst-28813	129	3	of	of	ADP
ajst-28813	129	4	the	the	DET
ajst-28813	129	5	model	model	NOUN
ajst-28813	129	6	will	will	AUX
ajst-28813	129	7	be	be	AUX
ajst-28813	129	8	the	the	DET
ajst-28813	129	9	first	first	ADJ
ajst-28813	129	10	order	order	NOUN
ajst-28813	129	11	linear	linear	ADJ
ajst-28813	129	12	expansion	expansion	NOUN
ajst-28813	129	13	here	here	ADV
ajst-28813	129	14	to	to	PART
ajst-28813	129	15	obtain	obtain	VERB
ajst-28813	129	16	the	the	DET
ajst-28813	129	17	jacobian	jacobian	ADJ
ajst-28813	129	18	matrix	matrix	NOUN
ajst-28813	129	19	of	of	ADP
ajst-28813	129	20	250	250	NUM
ajst-28813	129	21	the	the	DET
ajst-28813	129	22	current	current	ADJ
ajst-28813	129	23	expansion	expansion	NOUN
ajst-28813	129	24	point	point	NOUN
ajst-28813	129	25	1kf	1kf	ADJ
ajst-28813	129	26			NOUN
ajst-28813	129	27	.	.	PUNCT
ajst-28813	130	1	step2	step2	PROPN
ajst-28813	130	2	estimation	estimation	NOUN
ajst-28813	130	3	error	error	NOUN
ajst-28813	130	4	matrix	matrix	NOUN
ajst-28813	130	5	and	and	CCONJ
ajst-28813	130	6	state	state	NOUN
ajst-28813	130	7	estimation	estimation	NOUN
ajst-28813	130	8	;	;	PUNCT
ajst-28813	130	9	let	let	VERB
ajst-28813	130	10	the	the	DET
ajst-28813	130	11	system	system	NOUN
ajst-28813	130	12	state	state	NOUN
ajst-28813	130	13	external	external	ADJ
ajst-28813	130	14	interference	interference	NOUN
ajst-28813	130	15	be	be	AUX
ajst-28813	130	16	kw	kw	INTJ
ajst-28813	130	17	,	,	PUNCT
ajst-28813	130	18	mark	mark	VERB
ajst-28813	130	19	its	its	PRON
ajst-28813	130	20	covariance	covariance	NOUN
ajst-28813	130	21	matrix	matrix	NOUN
ajst-28813	130	22	as	as	ADP
ajst-28813	130	23	q	q	NOUN
ajst-28813	130	24	,	,	PUNCT
ajst-28813	130	25	the	the	DET
ajst-28813	130	26	error	error	NOUN
ajst-28813	130	27	matrix	matrix	NOUN
ajst-28813	130	28	can	can	AUX
ajst-28813	130	29	be	be	AUX
ajst-28813	130	30	iterated	iterate	VERB
ajst-28813	130	31	as	as	SCONJ
ajst-28813	130	32	follows	follow	VERB
ajst-28813	130	33	.	.	PUNCT
ajst-28813	131	1	1	1	NUM
ajst-28813	131	2	1	1	NUM
ajst-28813	131	3	1	1	NUM
ajst-28813	131	4	1	1	NUM
ajst-28813	131	5	1	1	NUM
ajst-28813	131	6	1ˆ	1ˆ	NOUN
ajst-28813	131	7	ˆ	ˆ	ADP
ajst-28813	131	8	t	t	PROPN
ajst-28813	132	1	k	k	PROPN
ajst-28813	132	2	k	k	PROPN
ajst-28813	133	1	k	k	PROPN
ajst-28813	134	1	k	k	PROPN
ajst-28813	135	1	k	k	PROPN
ajst-28813	136	1	k	k	PROPN
ajst-28813	137	1	k	k	PROPN
ajst-28813	138	1	k	k	PROPN
ajst-28813	139	1	p	p	X
ajst-28813	139	2	f	f	X
ajst-28813	139	3	p	p	X
ajst-28813	139	4	f	f	X
ajst-28813	139	5	q	q	NOUN
ajst-28813	139	6	x	x	INTJ
ajst-28813	139	7	ax	ax	NOUN
ajst-28813	139	8	bu	bu	PROPN
ajst-28813	139	9			PROPN
ajst-28813	139	10			PUNCT
ajst-28813	139	11			PROPN
ajst-28813	139	12			PROPN
ajst-28813	139	13			PROPN
ajst-28813	139	14			PROPN
ajst-28813	139	15			PROPN
ajst-28813	139	16			PUNCT
ajst-28813	139	17			PROPN
ajst-28813	139	18			PROPN
ajst-28813	139	19			PRON
ajst-28813	139	20			ADV
ajst-28813	139	21			PROPN
ajst-28813	139	22			PUNCT
ajst-28813	139	23	step3	step3	PROPN
ajst-28813	139	24	measurement	measurement	PROPN
ajst-28813	139	25	update	update	NOUN
ajst-28813	139	26	for	for	ADP
ajst-28813	139	27	state	state	NOUN
ajst-28813	139	28	estimation	estimation	NOUN
ajst-28813	139	29	and	and	CCONJ
ajst-28813	139	30	estimated	estimate	VERB
ajst-28813	139	31	error	error	NOUN
ajst-28813	139	32	covariance	covariance	NOUN
ajst-28813	139	33	.	.	PUNCT
ajst-28813	140	1			NOUN
ajst-28813	141	1			PUNCT
ajst-28813	141	2			NOUN
ajst-28813	141	3			PROPN
ajst-28813	141	4	ˆ	ˆ	ADV
ajst-28813	141	5	1	1	NUM
ajst-28813	141	6	|	|	NOUN
ajst-28813	141	7	ˆ	ˆ	ADJ
ajst-28813	141	8	ˆ	ˆ	ADV
ajst-28813	141	9	[	[	PUNCT
ajst-28813	141	10	]	]	X
ajst-28813	141	11	k	k	PROPN
ajst-28813	142	1	k	k	PROPN
ajst-28813	142	2	k	k	PROPN
ajst-28813	142	3	x	x	PUNCT
ajst-28813	143	1	t	t	NOUN
ajst-28813	143	2	t	t	PROPN
ajst-28813	143	3	k	k	PROPN
ajst-28813	144	1	k	k	PROPN
ajst-28813	145	1	k	k	PROPN
ajst-28813	146	1	k	k	PROPN
ajst-28813	147	1	k	k	PROPN
ajst-28813	148	1	k	k	PROPN
ajst-28813	149	1	k	k	PROPN
ajst-28813	150	1	k	k	PROPN
ajst-28813	151	1	k	k	PROPN
ajst-28813	152	1	k	k	PROPN
ajst-28813	153	1	k	k	PROPN
ajst-28813	154	1	k	k	PROPN
ajst-28813	155	1	k	k	PROPN
ajst-28813	156	1	k	k	PROPN
ajst-28813	157	1	k	k	PROPN
ajst-28813	157	2	k	k	PROPN
ajst-28813	158	1	k	k	PROPN
ajst-28813	158	2	h	h	NOUN
ajst-28813	158	3	h	h	NOUN
ajst-28813	159	1	x	x	X
ajst-28813	160	1	k	k	X
ajst-28813	161	1	p	p	NOUN
ajst-28813	162	1	h	h	NOUN
ajst-28813	163	1	h	h	NOUN
ajst-28813	164	1	p	p	NOUN
ajst-28813	164	2	h	h	NOUN
ajst-28813	165	1	r	r	NOUN
ajst-28813	165	2	x	x	PUNCT
ajst-28813	165	3	x	x	X
ajst-28813	165	4	k	k	NOUN
ajst-28813	165	5	y	y	NOUN
ajst-28813	165	6	h	h	NOUN
ajst-28813	166	1	x	x	X
ajst-28813	166	2	p	p	X
ajst-28813	167	1	i	i	X
ajst-28813	167	2	k	k	PROPN
ajst-28813	167	3	h	h	NOUN
ajst-28813	168	1	p	p	X
ajst-28813	168	2			PROPN
ajst-28813	168	3			PUNCT
ajst-28813	168	4			PROPN
ajst-28813	168	5			CCONJ
ajst-28813	168	6			PROPN
ajst-28813	168	7			PROPN
ajst-28813	168	8			PUNCT
ajst-28813	168	9			PROPN
ajst-28813	168	10			PROPN
ajst-28813	168	11			PROPN
ajst-28813	168	12			PROPN
ajst-28813	168	13			PROPN
ajst-28813	168	14			ADJ
ajst-28813	168	15			PROPN
ajst-28813	168	16			ADV
ajst-28813	168	17			PROPN
ajst-28813	168	18			PRON
ajst-28813	168	19			NOUN
ajst-28813	168	20	by	by	ADP
ajst-28813	168	21	extending	extend	VERB
ajst-28813	168	22	the	the	DET
ajst-28813	168	23	method	method	NOUN
ajst-28813	168	24	of	of	ADP
ajst-28813	168	25	kalman	kalman	PROPN
ajst-28813	168	26	filter	filter	PROPN
ajst-28813	168	27	,	,	PUNCT
ajst-28813	168	28	the	the	DET
ajst-28813	168	29	data	datum	NOUN
ajst-28813	168	30	of	of	ADP
ajst-28813	168	31	the	the	DET
ajst-28813	168	32	downhole	downhole	NOUN
ajst-28813	168	33	data	datum	NOUN
ajst-28813	168	34	of	of	ADP
ajst-28813	168	35	the	the	DET
ajst-28813	168	36	electric	electric	ADJ
ajst-28813	168	37	submersible	submersible	ADJ
ajst-28813	168	38	pump	pump	NOUN
ajst-28813	168	39	after	after	ADP
ajst-28813	168	40	noise	noise	NOUN
ajst-28813	168	41	reduction	reduction	NOUN
ajst-28813	168	42	is	be	AUX
ajst-28813	168	43	shown	show	VERB
ajst-28813	168	44	in	in	ADP
ajst-28813	168	45	figure	figure	NOUN
ajst-28813	168	46	2	2	NUM
ajst-28813	168	47	-	-	SYM
ajst-28813	168	48	4	4	NUM
ajst-28813	168	49	,	,	PUNCT
ajst-28813	168	50	and	and	CCONJ
ajst-28813	168	51	the	the	DET
ajst-28813	168	52	signal	signal	NOUN
ajst-28813	168	53	to	to	PART
ajst-28813	168	54	noise	noise	NOUN
ajst-28813	168	55	ratio	ratio	NOUN
ajst-28813	168	56	is	be	AUX
ajst-28813	168	57	greatly	greatly	ADV
ajst-28813	168	58	improved	improve	VERB
ajst-28813	168	59	.	.	PUNCT
ajst-28813	169	1	the	the	DET
ajst-28813	169	2	data	data	NOUN
ajst-28813	169	3	is	be	AUX
ajst-28813	169	4	obvious	obvious	ADJ
ajst-28813	169	5	,	,	PUNCT
ajst-28813	169	6	which	which	PRON
ajst-28813	169	7	an	an	DET
ajst-28813	169	8	ideal	ideal	ADJ
ajst-28813	169	9	reference	reference	NOUN
ajst-28813	169	10	for	for	ADP
ajst-28813	169	11	subsequent	subsequent	ADJ
ajst-28813	169	12	feature	feature	NOUN
ajst-28813	169	13	extraction	extraction	NOUN
ajst-28813	169	14	.	.	PUNCT
ajst-28813	170	1	figure	figure	NOUN
ajst-28813	170	2	2	2	NUM
ajst-28813	170	3	-	-	SYM
ajst-28813	170	4	4	4	NUM
ajst-28813	170	5	.	.	PUNCT
ajst-28813	171	1	data	datum	NOUN
ajst-28813	171	2	signals	signal	NOUN
ajst-28813	171	3	after	after	ADP
ajst-28813	171	4	kalman	kalman	NOUN
ajst-28813	171	5	filtering	filter	VERB
ajst-28813	171	6	3.2	3.2	NUM
ajst-28813	171	7	.	.	PUNCT
ajst-28813	172	1	feature	feature	NOUN
ajst-28813	172	2	extraction	extraction	NOUN
ajst-28813	172	3	feature	feature	NOUN
ajst-28813	172	4	extraction	extraction	NOUN
ajst-28813	172	5	plays	play	VERB
ajst-28813	172	6	a	a	DET
ajst-28813	172	7	crucial	crucial	ADJ
ajst-28813	172	8	role	role	NOUN
ajst-28813	172	9	in	in	ADP
ajst-28813	172	10	the	the	DET
ajst-28813	172	11	applications	application	NOUN
ajst-28813	172	12	of	of	ADP
ajst-28813	172	13	machine	machine	NOUN
ajst-28813	172	14	learning	learning	NOUN
ajst-28813	172	15	.	.	PUNCT
ajst-28813	173	1	when	when	SCONJ
ajst-28813	173	2	dealing	deal	VERB
ajst-28813	173	3	with	with	ADP
ajst-28813	173	4	practical	practical	ADJ
ajst-28813	173	5	problems	problem	NOUN
ajst-28813	173	6	,	,	PUNCT
ajst-28813	173	7	large	large	ADJ
ajst-28813	173	8	amounts	amount	NOUN
ajst-28813	173	9	of	of	ADP
ajst-28813	173	10	raw	raw	ADJ
ajst-28813	173	11	data	datum	NOUN
ajst-28813	173	12	are	be	AUX
ajst-28813	173	13	often	often	ADV
ajst-28813	173	14	encountered	encounter	VERB
ajst-28813	173	15	,	,	PUNCT
ajst-28813	173	16	which	which	PRON
ajst-28813	173	17	are	be	AUX
ajst-28813	173	18	often	often	ADV
ajst-28813	173	19	complex	complex	ADJ
ajst-28813	173	20	and	and	CCONJ
ajst-28813	173	21	high	high	ADV
ajst-28813	173	22	-	-	PUNCT
ajst-28813	173	23	dimensional	dimensional	ADJ
ajst-28813	173	24	collections	collection	NOUN
ajst-28813	173	25	of	of	ADP
ajst-28813	173	26	information	information	NOUN
ajst-28813	173	27	.	.	PUNCT
ajst-28813	174	1	despite	despite	SCONJ
ajst-28813	174	2	the	the	DET
ajst-28813	174	3	wealth	wealth	NOUN
ajst-28813	174	4	of	of	ADP
ajst-28813	174	5	information	information	NOUN
ajst-28813	174	6	contained	contain	VERB
ajst-28813	174	7	in	in	ADP
ajst-28813	174	8	these	these	DET
ajst-28813	174	9	data	datum	NOUN
ajst-28813	174	10	,	,	PUNCT
ajst-28813	174	11	machine	machine	NOUN
ajst-28813	174	12	learning	learning	NOUN
ajst-28813	174	13	algorithms	algorithm	NOUN
ajst-28813	174	14	do	do	AUX
ajst-28813	174	15	not	not	PART
ajst-28813	174	16	directly	directly	ADV
ajst-28813	174	17	understand	understand	VERB
ajst-28813	174	18	the	the	DET
ajst-28813	174	19	implications	implication	NOUN
ajst-28813	174	20	of	of	ADP
ajst-28813	174	21	these	these	DET
ajst-28813	174	22	data	datum	NOUN
ajst-28813	174	23	.	.	PUNCT
ajst-28813	175	1	the	the	DET
ajst-28813	175	2	aim	aim	NOUN
ajst-28813	175	3	is	be	AUX
ajst-28813	175	4	to	to	PART
ajst-28813	175	5	extract	extract	VERB
ajst-28813	175	6	key	key	ADJ
ajst-28813	175	7	information	information	NOUN
ajst-28813	175	8	from	from	ADP
ajst-28813	175	9	the	the	DET
ajst-28813	175	10	raw	raw	ADJ
ajst-28813	175	11	data	datum	NOUN
ajst-28813	175	12	and	and	CCONJ
ajst-28813	175	13	retain	retain	VERB
ajst-28813	175	14	important	important	ADJ
ajst-28813	175	15	features	feature	NOUN
ajst-28813	175	16	of	of	ADP
ajst-28813	175	17	the	the	DET
ajst-28813	175	18	data	datum	NOUN
ajst-28813	175	19	while	while	SCONJ
ajst-28813	175	20	reducing	reduce	VERB
ajst-28813	175	21	redundant	redundant	ADJ
ajst-28813	175	22	information	information	NOUN
ajst-28813	175	23	.	.	PUNCT
ajst-28813	176	1	this	this	DET
ajst-28813	176	2	process	process	NOUN
ajst-28813	176	3	not	not	PART
ajst-28813	176	4	only	only	ADV
ajst-28813	176	5	helps	help	VERB
ajst-28813	176	6	to	to	PART
ajst-28813	176	7	translate	translate	VERB
ajst-28813	176	8	the	the	DET
ajst-28813	176	9	data	datum	NOUN
ajst-28813	176	10	into	into	ADP
ajst-28813	176	11	algorithmically	algorithmically	ADV
ajst-28813	176	12	interpretable	interpretable	ADJ
ajst-28813	176	13	forms	form	NOUN
ajst-28813	176	14	,	,	PUNCT
ajst-28813	176	15	but	but	CCONJ
ajst-28813	176	16	also	also	ADV
ajst-28813	176	17	provides	provide	VERB
ajst-28813	176	18	statistical	statistical	ADJ
ajst-28813	176	19	and	and	CCONJ
ajst-28813	176	20	physically	physically	ADV
ajst-28813	176	21	significant	significant	ADJ
ajst-28813	176	22	features	feature	NOUN
ajst-28813	176	23	for	for	ADP
ajst-28813	176	24	machine	machine	NOUN
ajst-28813	176	25	learning	learning	NOUN
ajst-28813	176	26	models	model	NOUN
ajst-28813	176	27	.	.	PUNCT
ajst-28813	177	1	through	through	ADP
ajst-28813	177	2	feature	feature	NOUN
ajst-28813	177	3	extraction	extraction	NOUN
ajst-28813	177	4	,	,	PUNCT
ajst-28813	177	5	we	we	PRON
ajst-28813	177	6	can	can	AUX
ajst-28813	177	7	effectively	effectively	ADV
ajst-28813	177	8	represent	represent	VERB
ajst-28813	177	9	the	the	DET
ajst-28813	177	10	features	feature	NOUN
ajst-28813	177	11	of	of	ADP
ajst-28813	177	12	the	the	DET
ajst-28813	177	13	original	original	ADJ
ajst-28813	177	14	data	datum	NOUN
ajst-28813	177	15	to	to	PART
ajst-28813	177	16	improve	improve	VERB
ajst-28813	177	17	the	the	DET
ajst-28813	177	18	performance	performance	NOUN
ajst-28813	177	19	of	of	ADP
ajst-28813	177	20	the	the	DET
ajst-28813	177	21	model	model	NOUN
ajst-28813	177	22	.	.	PUNCT
ajst-28813	178	1	moreover	moreover	ADV
ajst-28813	178	2	,	,	PUNCT
ajst-28813	178	3	feature	feature	NOUN
ajst-28813	178	4	extraction	extraction	NOUN
ajst-28813	178	5	also	also	ADV
ajst-28813	178	6	helps	help	VERB
ajst-28813	178	7	to	to	PART
ajst-28813	178	8	reduce	reduce	VERB
ajst-28813	178	9	the	the	DET
ajst-28813	178	10	computational	computational	ADJ
ajst-28813	178	11	amount	amount	NOUN
ajst-28813	178	12	of	of	ADP
ajst-28813	178	13	[	[	X
ajst-28813	178	14	55	55	NUM
ajst-28813	178	15	]	]	PUNCT
ajst-28813	178	16	.	.	PUNCT
ajst-28813	179	1	through	through	ADP
ajst-28813	179	2	feature	feature	NOUN
ajst-28813	179	3	extraction	extraction	NOUN
ajst-28813	179	4	,	,	PUNCT
ajst-28813	179	5	we	we	PRON
ajst-28813	179	6	can	can	AUX
ajst-28813	179	7	significantly	significantly	ADV
ajst-28813	179	8	reduce	reduce	VERB
ajst-28813	179	9	the	the	DET
ajst-28813	179	10	dimensionality	dimensionality	NOUN
ajst-28813	179	11	of	of	ADP
ajst-28813	179	12	the	the	DET
ajst-28813	179	13	data	datum	NOUN
ajst-28813	179	14	,	,	PUNCT
ajst-28813	179	15	thus	thus	ADV
ajst-28813	179	16	reducing	reduce	VERB
ajst-28813	179	17	the	the	DET
ajst-28813	179	18	computational	computational	ADJ
ajst-28813	179	19	resources	resource	NOUN
ajst-28813	179	20	required	require	VERB
ajst-28813	179	21	for	for	ADP
ajst-28813	179	22	model	model	NOUN
ajst-28813	179	23	training	training	NOUN
ajst-28813	179	24	and	and	CCONJ
ajst-28813	179	25	prediction	prediction	NOUN
ajst-28813	179	26	.	.	PUNCT
ajst-28813	180	1	this	this	PRON
ajst-28813	180	2	not	not	PART
ajst-28813	180	3	only	only	ADV
ajst-28813	180	4	improves	improve	VERB
ajst-28813	180	5	computational	computational	ADJ
ajst-28813	180	6	efficiency	efficiency	NOUN
ajst-28813	180	7	,	,	PUNCT
ajst-28813	180	8	but	but	CCONJ
ajst-28813	180	9	also	also	ADV
ajst-28813	180	10	reduces	reduce	VERB
ajst-28813	180	11	computational	computational	ADJ
ajst-28813	180	12	cost	cost	NOUN
ajst-28813	180	13	.	.	PUNCT
ajst-28813	181	1	feature	feature	NOUN
ajst-28813	181	2	extraction	extraction	NOUN
ajst-28813	181	3	is	be	AUX
ajst-28813	181	4	used	use	VERB
ajst-28813	181	5	as	as	ADP
ajst-28813	181	6	a	a	DET
ajst-28813	181	7	means	means	NOUN
ajst-28813	181	8	to	to	PART
ajst-28813	181	9	reduce	reduce	VERB
ajst-28813	181	10	the	the	DET
ajst-28813	181	11	noise	noise	NOUN
ajst-28813	181	12	contained	contain	VERB
ajst-28813	181	13	in	in	ADP
ajst-28813	181	14	the	the	DET
ajst-28813	181	15	sample	sample	NOUN
ajst-28813	181	16	data	datum	NOUN
ajst-28813	181	17	,	,	PUNCT
ajst-28813	181	18	and	and	CCONJ
ajst-28813	181	19	the	the	DET
ajst-28813	181	20	model	model	NOUN
ajst-28813	181	21	can	can	AUX
ajst-28813	181	22	better	well	ADV
ajst-28813	181	23	capture	capture	VERB
ajst-28813	181	24	the	the	DET
ajst-28813	181	25	key	key	ADJ
ajst-28813	181	26	information	information	NOUN
ajst-28813	181	27	in	in	ADP
ajst-28813	181	28	the	the	DET
ajst-28813	181	29	data	datum	NOUN
ajst-28813	181	30	and	and	CCONJ
ajst-28813	181	31	improve	improve	VERB
ajst-28813	181	32	the	the	DET
ajst-28813	181	33	accuracy	accuracy	NOUN
ajst-28813	181	34	and	and	CCONJ
ajst-28813	181	35	robustness	robustness	NOUN
ajst-28813	181	36	of	of	ADP
ajst-28813	181	37	its	its	PRON
ajst-28813	181	38	prediction	prediction	NOUN
ajst-28813	181	39	.	.	PUNCT
ajst-28813	182	1	the	the	DET
ajst-28813	182	2	specific	specific	ADJ
ajst-28813	182	3	parameters	parameter	NOUN
ajst-28813	182	4	of	of	ADP
ajst-28813	182	5	the	the	DET
ajst-28813	182	6	electric	electric	ADJ
ajst-28813	182	7	submersible	submersible	ADJ
ajst-28813	182	8	pump	pump	NOUN
ajst-28813	182	9	are	be	AUX
ajst-28813	182	10	formed	form	VERB
ajst-28813	182	11	n	n	PRON
ajst-28813	182	12	samples	sample	NOUN
ajst-28813	182	13	,	,	PUNCT
ajst-28813	182	14	form	form	VERB
ajst-28813	182	15	the	the	DET
ajst-28813	182	16	matrix	matrix	NOUN
ajst-28813	182	17	.	.	PUNCT
ajst-28813	183	1	for	for	ADP
ajst-28813	183	2	each	each	DET
ajst-28813	183	3	sample	sample	NOUN
ajst-28813	183	4	1	1	NUM
ajst-28813	183	5	2	2	NUM
ajst-28813	183	6	[	[	PUNCT
ajst-28813	183	7	,	,	PUNCT
ajst-28813	183	8	,	,	PUNCT
ajst-28813	183	9	...	...	PUNCT
ajst-28813	183	10	,	,	PUNCT
ajst-28813	183	11	]	]	X
ajst-28813	183	12	nx	nx	X
ajst-28813	183	13	x	x	X
ajst-28813	183	14	x	x	X
ajst-28813	183	15	x	x	PROPN
ajst-28813	183	16	,	,	PUNCT
ajst-28813	183	17	we	we	PRON
ajst-28813	183	18	extracted	extract	VERB
ajst-28813	183	19	individual	individual	ADJ
ajst-28813	183	20	features	feature	NOUN
ajst-28813	183	21	using	use	VERB
ajst-28813	183	22	the	the	DET
ajst-28813	183	23	statistical	statistical	ADJ
ajst-28813	183	24	methods	method	NOUN
ajst-28813	183	25	listed	list	VERB
ajst-28813	183	26	in	in	ADP
ajst-28813	183	27	table	table	NOUN
ajst-28813	183	28	2	2	NUM
ajst-28813	183	29	-	-	SYM
ajst-28813	183	30	1	1	NUM
ajst-28813	183	31	below	below	ADV
ajst-28813	183	32	.	.	PUNCT
ajst-28813	184	1	finally	finally	ADV
ajst-28813	184	2	,	,	PUNCT
ajst-28813	184	3	each	each	DET
ajst-28813	184	4	n	n	NOUN
ajst-28813	184	5	samples	sample	NOUN
ajst-28813	184	6	converted	convert	VERB
ajst-28813	184	7	to	to	ADP
ajst-28813	184	8	a	a	DET
ajst-28813	184	9	matrix	matrix	NOUN
ajst-28813	184	10	of	of	ADP
ajst-28813	184	11	11	11	NUM
ajst-28813	184	12	n	n	NOUN
ajst-28813	184	13	.	.	PUNCT
ajst-28813	185	1	a	a	DET
ajst-28813	185	2	complete	complete	ADJ
ajst-28813	185	3	data	data	NOUN
ajst-28813	185	4	collection	collection	NOUN
ajst-28813	185	5	matrix	matrix	NOUN
ajst-28813	185	6	can	can	AUX
ajst-28813	185	7	be	be	AUX
ajst-28813	185	8	denoted	denote	VERB
ajst-28813	185	9	as	as	ADP
ajst-28813	185	10	pm	pm	NOUN
ajst-28813	185	11	nr	nr	PROPN
ajst-28813	185	12			PROPN
ajst-28813	185	13	,	,	PUNCT
ajst-28813	185	14	insidem	insidem	PROPN
ajst-28813	185	15	*	*	PUNCT
ajst-28813	185	16	pn	pn	PROPN
ajst-28813	185	17	time	time	NOUN
ajst-28813	185	18	samples	sample	NOUN
ajst-28813	185	19	of	of	ADP
ajst-28813	185	20	the	the	DET
ajst-28813	185	21	resulting	result	VERB
ajst-28813	185	22	parameters	parameter	NOUN
ajst-28813	185	23	.	.	PUNCT
ajst-28813	186	1	251	251	NUM
ajst-28813	186	2	table	table	NOUN
ajst-28813	186	3	2	2	NUM
ajst-28813	186	4	-	-	SYM
ajst-28813	186	5	1	1	NUM
ajst-28813	186	6	.	.	PUNCT
ajst-28813	186	7	statistics	statistic	NOUN
ajst-28813	186	8	of	of	ADP
ajst-28813	186	9	the	the	DET
ajst-28813	186	10	characteristics	characteristic	NOUN
ajst-28813	186	11	feature	feature	NOUN
ajst-28813	186	12	formula	formula	NOUN
ajst-28813	186	13	statistical	statistical	ADJ
ajst-28813	186	14	significance	significance	NOUN
ajst-28813	186	15	average	average	ADJ
ajst-28813	186	16	1	1	NUM
ajst-28813	186	17	1	1	NUM
ajst-28813	186	18	n	n	NUM
ajst-28813	187	1	i	i	PRON
ajst-28813	187	2	i	i	INTJ
ajst-28813	187	3	x	x	VERB
ajst-28813	187	4	x	x	VERB
ajst-28813	187	5	n	n	CCONJ
ajst-28813	187	6			NUM
ajst-28813	187	7			ADJ
ajst-28813	187	8			NOUN
ajst-28813	187	9	trends	trend	NOUN
ajst-28813	187	10	in	in	ADP
ajst-28813	187	11	the	the	DET
ajst-28813	187	12	dataset	dataset	NOUN
ajst-28813	187	13	maximum	maximum	PROPN
ajst-28813	187	14	max	max	PROPN
ajst-28813	187	15	max	max	PROPN
ajst-28813	187	16	{	{	PUNCT
ajst-28813	187	17	}	}	PUNCT
ajst-28813	187	18	ix	ix	PROPN
ajst-28813	187	19	x	x	PROPN
ajst-28813	187	20	maximum	maximum	PROPN
ajst-28813	187	21	boundary	boundary	NOUN
ajst-28813	187	22	of	of	ADP
ajst-28813	187	23	the	the	DET
ajst-28813	187	24	data	data	NOUN
ajst-28813	187	25	distribution	distribution	NOUN
ajst-28813	187	26	minimum	minimum	NOUN
ajst-28813	187	27	min	min	NOUN
ajst-28813	187	28	min	min	PROPN
ajst-28813	187	29	{	{	PUNCT
ajst-28813	187	30	}	}	PUNCT
ajst-28813	187	31	ix	ix	PROPN
ajst-28813	187	32	x	x	PROPN
ajst-28813	187	33	minimum	minimum	ADJ
ajst-28813	187	34	boundary	boundary	NOUN
ajst-28813	187	35	of	of	ADP
ajst-28813	187	36	the	the	DET
ajst-28813	187	37	data	datum	NOUN
ajst-28813	187	38	distribution	distribution	NOUN
ajst-28813	187	39	variance	variance	NOUN
ajst-28813	187	40			NOUN
ajst-28813	187	41			PROPN
ajst-28813	187	42	2	2	NUM
ajst-28813	187	43	2	2	NUM
ajst-28813	187	44	1	1	NUM
ajst-28813	187	45	1	1	NUM
ajst-28813	187	46	n	n	NUM
ajst-28813	188	1	i	i	PRON
ajst-28813	188	2	i	i	INTJ
ajst-28813	189	1	d	d	NOUN
ajst-28813	189	2	x	x	X
ajst-28813	189	3	x	x	PUNCT
ajst-28813	189	4	n	n	CCONJ
ajst-28813	189	5			NOUN
ajst-28813	189	6			NOUN
ajst-28813	190	1			PROPN
ajst-28813	190	2	the	the	DET
ajst-28813	190	3	degree	degree	NOUN
ajst-28813	190	4	of	of	ADP
ajst-28813	190	5	deviation	deviation	NOUN
ajst-28813	190	6	between	between	ADP
ajst-28813	190	7	the	the	DET
ajst-28813	190	8	feature	feature	NOUN
ajst-28813	190	9	variable	variable	NOUN
ajst-28813	190	10	and	and	CCONJ
ajst-28813	190	11	the	the	DET
ajst-28813	190	12	mean	mean	ADJ
ajst-28813	190	13	standard	standard	ADJ
ajst-28813	190	14	deviation	deviation	NOUN
ajst-28813	190	15			NOUN
ajst-28813	190	16			PROPN
ajst-28813	190	17	2	2	NUM
ajst-28813	190	18	2	2	NUM
ajst-28813	190	19	1	1	NUM
ajst-28813	190	20	1	1	NUM
ajst-28813	190	21	n	n	NUM
ajst-28813	190	22	i	i	PRON
ajst-28813	191	1	i	i	INTJ
ajst-28813	192	1	d	d	NOUN
ajst-28813	192	2	x	x	X
ajst-28813	192	3	x	x	PUNCT
ajst-28813	192	4	n	n	CCONJ
ajst-28813	192	5			NOUN
ajst-28813	192	6			NUM
ajst-28813	192	7			PROPN
ajst-28813	192	8	reflect	reflect	VERB
ajst-28813	192	9	the	the	DET
ajst-28813	192	10	degree	degree	NOUN
ajst-28813	192	11	of	of	ADP
ajst-28813	192	12	dispersion	dispersion	NOUN
ajst-28813	192	13	of	of	ADP
ajst-28813	192	14	the	the	DET
ajst-28813	192	15	data	datum	NOUN
ajst-28813	192	16	mean	mean	VERB
ajst-28813	192	17	square	square	ADJ
ajst-28813	192	18	error	error	NOUN
ajst-28813	192	19			NOUN
ajst-28813	192	20	2	2	NOUN
ajst-28813	192	21	pr	pr	NOUN
ajst-28813	192	22	0	0	NUM
ajst-28813	192	23	1	1	NUM
ajst-28813	192	24	[	[	PUNCT
ajst-28813	192	25	]	]	X
ajst-28813	193	1	[	[	PUNCT
ajst-28813	193	2	]	]	X
ajst-28813	193	3	n	n	CCONJ
ajst-28813	193	4	ture	ture	NOUN
ajst-28813	193	5	ed	ed	NOUN
ajst-28813	194	1	i	i	PROPN
ajst-28813	194	2	mse	mse	VERB
ajst-28813	195	1	y	y	PROPN
ajst-28813	195	2	i	i	PRON
ajst-28813	196	1	y	y	VERB
ajst-28813	196	2	i	i	PRON
ajst-28813	197	1	n	n	VERB
ajst-28813	197	2			NUM
ajst-28813	197	3			NUM
ajst-28813	198	1			PROPN
ajst-28813	198	2	reflect	reflect	VERB
ajst-28813	198	3	the	the	DET
ajst-28813	198	4	prediction	prediction	NOUN
ajst-28813	198	5	accuracy	accuracy	NOUN
ajst-28813	198	6	of	of	ADP
ajst-28813	198	7	the	the	DET
ajst-28813	198	8	model	model	NOUN
ajst-28813	198	9	root	root	NOUN
ajst-28813	198	10	-	-	PUNCT
ajst-28813	198	11	meansquare	meansquare	NOUN
ajst-28813	198	12	-	-	PUNCT
ajst-28813	198	13	error	error	NOUN
ajst-28813	198	14			NOUN
ajst-28813	198	15	2	2	NOUN
ajst-28813	198	16	pr	pr	NOUN
ajst-28813	198	17	0	0	NUM
ajst-28813	198	18	1	1	NUM
ajst-28813	198	19	[	[	PUNCT
ajst-28813	198	20	]	]	X
ajst-28813	198	21	[	[	PUNCT
ajst-28813	198	22	]	]	X
ajst-28813	198	23	n	n	CCONJ
ajst-28813	198	24	ture	ture	NOUN
ajst-28813	198	25	ed	ed	INTJ
ajst-28813	199	1	i	i	PRON
ajst-28813	199	2	rmse	rmse	VERB
ajst-28813	200	1	y	y	PROPN
ajst-28813	200	2	i	i	PRON
ajst-28813	201	1	y	y	VERB
ajst-28813	201	2	i	i	PRON
ajst-28813	202	1	n	n	VERB
ajst-28813	203	1			NUM
ajst-28813	203	2			PROPN
ajst-28813	204	1			PROPN
ajst-28813	204	2	standard	standard	ADJ
ajst-28813	204	3	root	root	NOUN
ajst-28813	204	4	mean	mean	VERB
ajst-28813	204	5	square	square	ADJ
ajst-28813	204	6	error	error	NOUN
ajst-28813	204	7			NOUN
ajst-28813	204	8	2	2	ADP
ajst-28813	204	9	pr	pr	NOUN
ajst-28813	204	10	0	0	NUM
ajst-28813	204	11	max	max	PROPN
ajst-28813	204	12	min	min	PROPN
ajst-28813	204	13	1	1	NUM
ajst-28813	204	14	[	[	PUNCT
ajst-28813	204	15	]	]	X
ajst-28813	204	16	[	[	PUNCT
ajst-28813	204	17	]	]	X
ajst-28813	204	18	n	n	CCONJ
ajst-28813	204	19	ture	ture	NOUN
ajst-28813	205	1	ed	ed	NOUN
ajst-28813	206	1	i	i	PRON
ajst-28813	207	1	y	y	INTJ
ajst-28813	208	1	i	i	PRON
ajst-28813	208	2	y	y	VERB
ajst-28813	209	1	i	i	PRON
ajst-28813	209	2	n	n	VERB
ajst-28813	209	3	nrmse	nrmse	VERB
ajst-28813	209	4	y	y	PROPN
ajst-28813	209	5	y	y	PROPN
ajst-28813	209	6			PROPN
ajst-28813	209	7			PROPN
ajst-28813	209	8			PROPN
ajst-28813	209	9			PROPN
ajst-28813	209	10			X
ajst-28813	209	11	absolute	absolute	ADJ
ajst-28813	209	12	error	error	NOUN
ajst-28813	209	13			NOUN
ajst-28813	209	14	pr	pr	NOUN
ajst-28813	209	15	0	0	PUNCT
ajst-28813	210	1	[	[	PUNCT
ajst-28813	210	2	]	]	X
ajst-28813	210	3	[	[	PUNCT
ajst-28813	210	4	]	]	X
ajst-28813	210	5	n	n	CCONJ
ajst-28813	210	6	ture	ture	NOUN
ajst-28813	210	7	ed	ed	INTJ
ajst-28813	211	1	i	i	PRON
ajst-28813	211	2	iae	iae	VERB
ajst-28813	212	1	y	y	NOUN
ajst-28813	212	2	i	i	PRON
ajst-28813	213	1	y	y	INTJ
ajst-28813	214	1	i	i	PRON
ajst-28813	214	2			VERB
ajst-28813	214	3			VERB
ajst-28813	215	1			ADJ
ajst-28813	215	2	3.3	3.3	NUM
ajst-28813	215	3	.	.	PUNCT
ajst-28813	216	1	network	network	NOUN
ajst-28813	216	2	parameter	parameter	NOUN
ajst-28813	216	3	determination	determination	NOUN
ajst-28813	216	4	the	the	DET
ajst-28813	216	5	choice	choice	NOUN
ajst-28813	216	6	of	of	ADP
ajst-28813	216	7	hyperparameters	hyperparameter	NOUN
ajst-28813	216	8	of	of	ADP
ajst-28813	216	9	esn	esn	PROPN
ajst-28813	216	10	network	network	NOUN
ajst-28813	216	11	is	be	AUX
ajst-28813	216	12	important	important	ADJ
ajst-28813	216	13	for	for	ADP
ajst-28813	216	14	involving	involve	VERB
ajst-28813	216	15	optimal	optimal	ADJ
ajst-28813	216	16	network	network	NOUN
ajst-28813	216	17	solving	solving	NOUN
ajst-28813	216	18	,	,	PUNCT
ajst-28813	216	19	and	and	CCONJ
ajst-28813	216	20	a	a	DET
ajst-28813	216	21	good	good	ADJ
ajst-28813	216	22	way	way	NOUN
ajst-28813	216	23	to	to	PART
ajst-28813	216	24	find	find	VERB
ajst-28813	216	25	these	these	DET
ajst-28813	216	26	parameters	parameter	NOUN
ajst-28813	216	27	is	be	AUX
ajst-28813	216	28	to	to	PART
ajst-28813	216	29	grid	grid	VERB
ajst-28813	216	30	search	search	NOUN
ajst-28813	216	31	for	for	ADP
ajst-28813	216	32	different	different	ADJ
ajst-28813	216	33	parameters	parameter	NOUN
ajst-28813	216	34	.	.	PUNCT
ajst-28813	217	1	the	the	DET
ajst-28813	217	2	grid	grid	NOUN
ajst-28813	217	3	search	search	NOUN
ajst-28813	217	4	runs	run	VERB
ajst-28813	217	5	the	the	DET
ajst-28813	217	6	network	network	NOUN
ajst-28813	217	7	with	with	ADP
ajst-28813	217	8	different	different	ADJ
ajst-28813	217	9	hyperparameter	hyperparameter	NOUN
ajst-28813	217	10	values	value	NOUN
ajst-28813	217	11	and	and	CCONJ
ajst-28813	217	12	compares	compare	VERB
ajst-28813	217	13	the	the	DET
ajst-28813	217	14	results	result	NOUN
ajst-28813	217	15	to	to	PART
ajst-28813	217	16	find	find	VERB
ajst-28813	217	17	the	the	DET
ajst-28813	217	18	best	good	ADJ
ajst-28813	217	19	hyperparameter	hyperparameter	NOUN
ajst-28813	217	20	with	with	ADP
ajst-28813	217	21	minimal	minimal	ADJ
ajst-28813	217	22	generalization	generalization	NOUN
ajst-28813	217	23	error	error	NOUN
ajst-28813	217	24	.	.	PUNCT
ajst-28813	218	1	here	here	ADV
ajst-28813	218	2	,	,	PUNCT
ajst-28813	218	3	the	the	DET
ajst-28813	218	4	esn	esn	PROPN
ajst-28813	218	5	network	network	NOUN
ajst-28813	218	6	in	in	ADP
ajst-28813	218	7	this	this	DET
ajst-28813	218	8	paper	paper	NOUN
ajst-28813	218	9	uses	use	VERB
ajst-28813	218	10	the	the	DET
ajst-28813	218	11	particle	particle	NOUN
ajst-28813	218	12	swarm	swarm	NOUN
ajst-28813	218	13	optimization	optimization	NOUN
ajst-28813	218	14	algorithm	algorithm	NOUN
ajst-28813	218	15	(	(	PUNCT
ajst-28813	218	16	pso	pso	NOUN
ajst-28813	218	17	)	)	PUNCT
ajst-28813	219	1	[	[	X
ajst-28813	219	2	57	57	NUM
ajst-28813	219	3	]	]	PUNCT
ajst-28813	219	4	when	when	SCONJ
ajst-28813	219	5	selecting	select	VERB
ajst-28813	219	6	parameters	parameter	NOUN
ajst-28813	219	7	,	,	PUNCT
ajst-28813	219	8	which	which	PRON
ajst-28813	219	9	can	can	AUX
ajst-28813	219	10	efficiently	efficiently	ADV
ajst-28813	219	11	optimize	optimize	VERB
ajst-28813	219	12	the	the	DET
ajst-28813	219	13	leakage	leakage	NOUN
ajst-28813	219	14	rate	rate	NOUN
ajst-28813	219	15	of	of	ADP
ajst-28813	219	16	esn	esn	PROPN
ajst-28813	219	17	network	network	NOUN
ajst-28813	219	18	;	;	PUNCT
ajst-28813	219	19	the	the	DET
ajst-28813	219	20	main	main	ADJ
ajst-28813	219	21	structure	structure	NOUN
ajst-28813	219	22	of	of	ADP
ajst-28813	219	23	the	the	DET
ajst-28813	219	24	algorithm	algorithm	NOUN
ajst-28813	219	25	is	be	AUX
ajst-28813	219	26	the	the	DET
ajst-28813	219	27	number	number	NOUN
ajst-28813	219	28	of	of	ADP
ajst-28813	219	29	particles	particle	NOUN
ajst-28813	219	30	,	,	PUNCT
ajst-28813	219	31	dimension	dimension	NOUN
ajst-28813	219	32	,	,	PUNCT
ajst-28813	219	33	iteration	iteration	NOUN
ajst-28813	219	34	number	number	NOUN
ajst-28813	219	35	and	and	CCONJ
ajst-28813	219	36	the	the	DET
ajst-28813	219	37	initial	initial	ADJ
ajst-28813	219	38	value	value	NOUN
ajst-28813	219	39	of	of	ADP
ajst-28813	219	40	position	position	NOUN
ajst-28813	219	41	and	and	CCONJ
ajst-28813	219	42	speed	speed	NOUN
ajst-28813	219	43	.	.	PUNCT
ajst-28813	220	1	the	the	DET
ajst-28813	220	2	principle	principle	NOUN
ajst-28813	220	3	is	be	AUX
ajst-28813	220	4	to	to	PART
ajst-28813	220	5	find	find	VERB
ajst-28813	220	6	the	the	DET
ajst-28813	220	7	optimal	optimal	ADJ
ajst-28813	220	8	solution	solution	NOUN
ajst-28813	220	9	by	by	ADP
ajst-28813	220	10	simulating	simulate	VERB
ajst-28813	220	11	particles	particle	NOUN
ajst-28813	220	12	cooperating	cooperate	VERB
ajst-28813	220	13	in	in	ADP
ajst-28813	220	14	the	the	DET
ajst-28813	220	15	search	search	NOUN
ajst-28813	220	16	space	space	NOUN
ajst-28813	220	17	.	.	PUNCT
ajst-28813	221	1	the	the	DET
ajst-28813	221	2	algorithm	algorithm	NOUN
ajst-28813	221	3	process	process	NOUN
ajst-28813	221	4	is	be	AUX
ajst-28813	221	5	as	as	SCONJ
ajst-28813	221	6	follows	follow	VERB
ajst-28813	221	7	:	:	PUNCT
ajst-28813	221	8	let	let	VERB
ajst-28813	221	9	each	each	DET
ajst-28813	221	10	particle	particle	NOUN
ajst-28813	221	11	randomly	randomly	ADV
ajst-28813	221	12	initialize	initialize	VERB
ajst-28813	221	13	the	the	DET
ajst-28813	221	14	position	position	NOUN
ajst-28813	221	15	and	and	CCONJ
ajst-28813	221	16	velocity	velocity	NOUN
ajst-28813	221	17	and	and	CCONJ
ajst-28813	221	18	velocity	velocity	NOUN
ajst-28813	221	19	in	in	ADP
ajst-28813	221	20	the	the	DET
ajst-28813	221	21	hyperparameter	hyperparameter	NOUN
ajst-28813	221	22	space	space	NOUN
ajst-28813	221	23	(	(	PUNCT
ajst-28813	221	24	within	within	ADP
ajst-28813	221	25	the	the	DET
ajst-28813	221	26	range	range	NOUN
ajst-28813	221	27	of	of	ADP
ajst-28813	221	28	the	the	DET
ajst-28813	221	29	corresponding	correspond	VERB
ajst-28813	221	30	leakage	leakage	NOUN
ajst-28813	221	31	rate	rate	NOUN
ajst-28813	221	32	or	or	CCONJ
ajst-28813	221	33	the	the	DET
ajst-28813	221	34	range	range	NOUN
ajst-28813	221	35	of	of	ADP
ajst-28813	221	36	the	the	DET
ajst-28813	221	37	value	value	NOUN
ajst-28813	221	38	of	of	ADP
ajst-28813	221	39	the	the	DET
ajst-28813	221	40	number	number	NOUN
ajst-28813	221	41	of	of	ADP
ajst-28813	221	42	neurons	neuron	NOUN
ajst-28813	221	43	)	)	PUNCT
ajst-28813	221	44	,	,	PUNCT
ajst-28813	221	45			PROPN
ajst-28813	221	46	0ix	0ix	PUNCT
ajst-28813	221	47	and	and	CCONJ
ajst-28813	221	48			PROPN
ajst-28813	221	49	0iv	0iv	NOUN
ajst-28813	221	50	the	the	DET
ajst-28813	221	51	initial	initial	ADJ
ajst-28813	221	52	position	position	NOUN
ajst-28813	221	53	ip	ip	NOUN
ajst-28813	221	54	and	and	CCONJ
ajst-28813	221	55	the	the	DET
ajst-28813	221	56	global	global	ADJ
ajst-28813	221	57	optimal	optimal	ADJ
ajst-28813	221	58	position	position	NOUN
ajst-28813	221	59	of	of	ADP
ajst-28813	221	60	the	the	DET
ajst-28813	221	61	particle	particle	NOUN
ajst-28813	221	62	ig	ig	PROPN
ajst-28813	221	63	(	(	PUNCT
ajst-28813	221	64	initially	initially	ADV
ajst-28813	221	65	set	set	VERB
ajst-28813	221	66	to	to	ADP
ajst-28813	221	67	infinity	infinity	NOUN
ajst-28813	221	68	)	)	PUNCT
ajst-28813	221	69	.	.	PUNCT
ajst-28813	222	1	the	the	DET
ajst-28813	222	2	corresponding	correspond	VERB
ajst-28813	222	3	speed	speed	NOUN
ajst-28813	222	4	update	update	NOUN
ajst-28813	222	5	formula	formula	NOUN
ajst-28813	222	6	is	be	AUX
ajst-28813	222	7	:	:	PUNCT
ajst-28813	222	8			NOUN
ajst-28813	222	9			SYM
ajst-28813	222	10			NOUN
ajst-28813	222	11	1	1	VERB
ajst-28813	222	12	1	1	NUM
ajst-28813	222	13	2	2	NUM
ajst-28813	222	14	2	2	NUM
ajst-28813	222	15	new	new	ADJ
ajst-28813	222	16	old	old	ADJ
ajst-28813	223	1	i	i	PRON
ajst-28813	224	1	i	i	INTJ
ajst-28813	225	1	i	i	PRON
ajst-28813	226	1	i	i	PRON
ajst-28813	227	1	i	i	VERB
ajst-28813	227	2	iv	iv	VERB
ajst-28813	227	3	w	w	NOUN
ajst-28813	227	4	v	v	NOUN
ajst-28813	227	5	c	c	NOUN
ajst-28813	227	6	r	r	NOUN
ajst-28813	227	7	p	p	NOUN
ajst-28813	227	8	x	x	X
ajst-28813	227	9	c	c	NOUN
ajst-28813	227	10	r	r	NOUN
ajst-28813	227	11	g	g	NOUN
ajst-28813	227	12	x	x	PUNCT
ajst-28813	228	1			NUM
ajst-28813	228	2			PUNCT
ajst-28813	228	3			ADJ
ajst-28813	228	4			ADJ
ajst-28813	228	5			NOUN
ajst-28813	228	6			VERB
ajst-28813	228	7			ADJ
ajst-28813	228	8			ADJ
ajst-28813	228	9			NOUN
ajst-28813	228	10	(	(	PUNCT
ajst-28813	228	11	2	2	NUM
ajst-28813	228	12	-	-	SYM
ajst-28813	228	13	9	9	NUM
ajst-28813	228	14	)	)	PUNCT
ajst-28813	228	15	w	w	NOUN
ajst-28813	228	16	is	be	AUX
ajst-28813	228	17	the	the	DET
ajst-28813	228	18	inertial	inertial	ADJ
ajst-28813	228	19	weights	weight	NOUN
ajst-28813	228	20	that	that	PRON
ajst-28813	228	21	control	control	VERB
ajst-28813	228	22	the	the	DET
ajst-28813	228	23	influence	influence	NOUN
ajst-28813	228	24	on	on	ADP
ajst-28813	228	25	past	past	ADJ
ajst-28813	228	26	historical	historical	ADJ
ajst-28813	228	27	speed	speed	NOUN
ajst-28813	228	28	;	;	PUNCT
ajst-28813	228	29	1c	1c	NUM
ajst-28813	228	30	and	and	CCONJ
ajst-28813	228	31	2c	2c	NOUN
ajst-28813	228	32	are	be	AUX
ajst-28813	228	33	the	the	DET
ajst-28813	228	34	learning	learning	NOUN
ajst-28813	228	35	factor	factor	NOUN
ajst-28813	228	36	,	,	PUNCT
ajst-28813	228	37	usually	usually	ADV
ajst-28813	228	38	set	set	VERB
ajst-28813	228	39	to	to	ADP
ajst-28813	228	40	2	2	NUM
ajst-28813	228	41	,	,	PUNCT
ajst-28813	228	42	adjusting	adjust	VERB
ajst-28813	228	43	the	the	DET
ajst-28813	228	44	attraction	attraction	NOUN
ajst-28813	228	45	to	to	ADP
ajst-28813	228	46	the	the	DET
ajst-28813	228	47	current	current	ADJ
ajst-28813	228	48	best	good	ADJ
ajst-28813	228	49	and	and	CCONJ
ajst-28813	228	50	global	global	ADJ
ajst-28813	228	51	best	good	ADJ
ajst-28813	228	52	positions	position	NOUN
ajst-28813	228	53	;	;	PUNCT
ajst-28813	228	54	1r	1r	NUM
ajst-28813	228	55	and	and	CCONJ
ajst-28813	228	56	2r	2r	NUM
ajst-28813	228	57	are	be	AUX
ajst-28813	228	58	the	the	DET
ajst-28813	228	59	random	random	ADJ
ajst-28813	228	60	numbers	number	NOUN
ajst-28813	228	61	in	in	ADP
ajst-28813	228	62	the	the	DET
ajst-28813	228	63	[	[	NOUN
ajst-28813	228	64	0,1	0,1	NUM
ajst-28813	228	65	]	]	PUNCT
ajst-28813	228	66	range	range	NOUN
ajst-28813	228	67	.	.	PUNCT
ajst-28813	229	1	the	the	DET
ajst-28813	229	2	location	location	NOUN
ajst-28813	229	3	update	update	NOUN
ajst-28813	229	4	formula	formula	NOUN
ajst-28813	229	5	is	be	AUX
ajst-28813	229	6	:	:	PUNCT
ajst-28813	229	7	new	new	ADJ
ajst-28813	229	8	old	old	ADJ
ajst-28813	229	9	new	new	ADJ
ajst-28813	229	10	i	i	PRON
ajst-28813	230	1	i	i	PRON
ajst-28813	230	2	ix	ix	ADP
ajst-28813	230	3	x	x	X
ajst-28813	230	4	v	v	ADV
ajst-28813	230	5			X
ajst-28813	230	6	(	(	PUNCT
ajst-28813	230	7	2	2	NUM
ajst-28813	230	8	-	-	SYM
ajst-28813	230	9	10	10	NUM
ajst-28813	230	10	)	)	PUNCT
ajst-28813	230	11	for	for	ADP
ajst-28813	230	12	each	each	DET
ajst-28813	230	13	particle	particle	NOUN
ajst-28813	230	14	,	,	PUNCT
ajst-28813	230	15	the	the	DET
ajst-28813	230	16	esn	esn	PROPN
ajst-28813	230	17	network	network	NOUN
ajst-28813	230	18	is	be	AUX
ajst-28813	230	19	trained	train	VERB
ajst-28813	230	20	using	use	VERB
ajst-28813	230	21	its	its	PRON
ajst-28813	230	22	location	location	NOUN
ajst-28813	230	23	,	,	PUNCT
ajst-28813	230	24	usually	usually	ADV
ajst-28813	230	25	using	use	VERB
ajst-28813	230	26	the	the	DET
ajst-28813	230	27	mean	mean	ADJ
ajst-28813	230	28	square	square	NOUN
ajst-28813	230	29	error	error	NOUN
ajst-28813	230	30	(	(	PUNCT
ajst-28813	230	31	mse	mse	NOUN
ajst-28813	230	32	/	/	SYM
ajst-28813	230	33	nrmse	nrmse	PROPN
ajst-28813	230	34	,	,	PUNCT
ajst-28813	230	35	see	see	VERB
ajst-28813	230	36	table	table	NOUN
ajst-28813	230	37	2	2	NUM
ajst-28813	230	38	-	-	SYM
ajst-28813	230	39	1	1	NUM
ajst-28813	230	40	)	)	PUNCT
ajst-28813	230	41	to	to	PART
ajst-28813	230	42	indicate	indicate	VERB
ajst-28813	230	43	fitness.in	fitness.in	ADJ
ajst-28813	230	44	compliance	compliance	NOUN
ajst-28813	230	45	with	with	ADP
ajst-28813	230	46	:	:	PUNCT
ajst-28813	230	47			NOUN
ajst-28813	230	48			SYM
ajst-28813	230	49	2	2	NUM
ajst-28813	230	50	1	1	NUM
ajst-28813	230	51	1	1	NUM
ajst-28813	230	52	ˆ	ˆ	PROPN
ajst-28813	230	53	n	n	PRON
ajst-28813	230	54	j	j	PROPN
ajst-28813	230	55	j	j	PROPN
ajst-28813	230	56	j	j	PROPN
ajst-28813	230	57	mse	mse	PROPN
ajst-28813	230	58	y	y	PROPN
ajst-28813	230	59	y	y	PROPN
ajst-28813	231	1	n	n	CCONJ
ajst-28813	231	2			NUM
ajst-28813	231	3			NUM
ajst-28813	232	1			NOUN
ajst-28813	232	2	(	(	PUNCT
ajst-28813	232	3	2	2	NUM
ajst-28813	232	4	-	-	SYM
ajst-28813	232	5	11	11	NUM
ajst-28813	232	6	)	)	PUNCT
ajst-28813	232	7	for	for	ADP
ajst-28813	232	8	each	each	DET
ajst-28813	232	9	iteration	iteration	NOUN
ajst-28813	232	10	,	,	PUNCT
ajst-28813	232	11	repeated	repeat	VERB
ajst-28813	232	12	fitness	fitness	NOUN
ajst-28813	232	13	evaluation	evaluation	NOUN
ajst-28813	232	14	and	and	CCONJ
ajst-28813	232	15	particle	particle	NOUN
ajst-28813	232	16	information	information	NOUN
ajst-28813	232	17	are	be	AUX
ajst-28813	232	18	updated	update	VERB
ajst-28813	232	19	until	until	SCONJ
ajst-28813	232	20	the	the	DET
ajst-28813	232	21	preset	preset	ADJ
ajst-28813	232	22	number	number	NOUN
ajst-28813	232	23	of	of	ADP
ajst-28813	232	24	iterations	iteration	NOUN
ajst-28813	232	25	or	or	CCONJ
ajst-28813	232	26	fitness	fitness	NOUN
ajst-28813	232	27	convergence	convergence	NOUN
ajst-28813	232	28	is	be	AUX
ajst-28813	232	29	reached	reach	VERB
ajst-28813	232	30	,	,	PUNCT
ajst-28813	232	31	and	and	CCONJ
ajst-28813	232	32	the	the	DET
ajst-28813	232	33	final	final	ADJ
ajst-28813	232	34	output	output	NOUN
ajst-28813	232	35	optimized	optimize	VERB
ajst-28813	232	36	leakage	leakage	NOUN
ajst-28813	232	37	rate	rate	NOUN
ajst-28813	232	38	records	record	VERB
ajst-28813	232	39	the	the	DET
ajst-28813	232	40	corresponding	corresponding	ADJ
ajst-28813	232	41	best	good	ADJ
ajst-28813	232	42	mse	mse	NOUN
ajst-28813	232	43	for	for	ADP
ajst-28813	232	44	training	train	VERB
ajst-28813	232	45	the	the	DET
ajst-28813	232	46	final	final	ADJ
ajst-28813	232	47	esn	esn	PROPN
ajst-28813	232	48	network	network	PROPN
ajst-28813	232	49	model	model	NOUN
ajst-28813	232	50	.	.	PUNCT
ajst-28813	233	1	the	the	DET
ajst-28813	233	2	pso	pso	NOUN
ajst-28813	233	3	algorithm	algorithm	NOUN
ajst-28813	233	4	used	use	VERB
ajst-28813	233	5	in	in	ADP
ajst-28813	233	6	this	this	DET
ajst-28813	233	7	paper	paper	NOUN
ajst-28813	233	8	,	,	PUNCT
ajst-28813	233	9	and	and	CCONJ
ajst-28813	233	10	the	the	DET
ajst-28813	233	11	defined	define	VERB
ajst-28813	233	12	parameters	parameter	NOUN
ajst-28813	233	13	used	use	VERB
ajst-28813	233	14	are	be	AUX
ajst-28813	233	15	shown	show	VERB
ajst-28813	233	16	in	in	ADP
ajst-28813	233	17	table	table	NOUN
ajst-28813	233	18	2	2	NUM
ajst-28813	233	19	-	-	SYM
ajst-28813	233	20	2	2	NUM
ajst-28813	233	21	.	.	PUNCT
ajst-28813	233	22	table	table	NOUN
ajst-28813	233	23	2	2	NUM
ajst-28813	233	24	-	-	SYM
ajst-28813	233	25	2	2	NUM
ajst-28813	233	26	.	.	PUNCT
ajst-28813	233	27	definition	definition	NOUN
ajst-28813	233	28	parameters	parameter	NOUN
ajst-28813	233	29	of	of	ADP
ajst-28813	233	30	the	the	DET
ajst-28813	233	31	pso	pso	NOUN
ajst-28813	233	32	algorithm	algorithm	NOUN
ajst-28813	233	33	parameter	parameter	NOUN
ajst-28813	233	34	name	name	NOUN
ajst-28813	233	35	particle	particle	NOUN
ajst-28813	233	36	populations	population	NOUN
ajst-28813	233	37	50	50	NUM
ajst-28813	233	38	dimensions	dimension	NOUN
ajst-28813	233	39	2	2	NUM
ajst-28813	233	40	iterations	iteration	NOUN
ajst-28813	233	41	30	30	NUM
ajst-28813	233	42	initial	initial	ADJ
ajst-28813	233	43	values	value	NOUN
ajst-28813	233	44	for	for	ADP
ajst-28813	233	45	the	the	DET
ajst-28813	233	46	position	position	NOUN
ajst-28813	233	47	and	and	CCONJ
ajst-28813	233	48	velocity	velocity	NOUN
ajst-28813	233	49	(	(	PUNCT
ajst-28813	233	50	leakage	leakage	NOUN
ajst-28813	233	51	rate	rate	NOUN
ajst-28813	233	52	)	)	PUNCT
ajst-28813	233	53	(	(	PUNCT
ajst-28813	233	54	0.2	0.2	NUM
ajst-28813	233	55	,	,	PUNCT
ajst-28813	233	56	0.02	0.02	NUM
ajst-28813	233	57	)	)	PUNCT
ajst-28813	233	58	initial	initial	ADJ
ajst-28813	233	59	values	value	NOUN
ajst-28813	233	60	of	of	ADP
ajst-28813	233	61	position	position	NOUN
ajst-28813	233	62	and	and	CCONJ
ajst-28813	233	63	velocity	velocity	NOUN
ajst-28813	233	64	(	(	PUNCT
ajst-28813	233	65	number	number	NOUN
ajst-28813	233	66	of	of	ADP
ajst-28813	233	67	neurons	neuron	NOUN
ajst-28813	233	68	)	)	PUNCT
ajst-28813	233	69	(	(	PUNCT
ajst-28813	233	70	50	50	NUM
ajst-28813	233	71	,	,	PUNCT
ajst-28813	233	72	50	50	NUM
ajst-28813	233	73	)	)	PUNCT
ajst-28813	233	74	(	(	PUNCT
ajst-28813	233	75	1	1	X
ajst-28813	233	76	)	)	PUNCT
ajst-28813	233	77	disclosure	disclosure	NOUN
ajst-28813	233	78	rate	rate	NOUN
ajst-28813	233	79	the	the	DET
ajst-28813	233	80	value	value	NOUN
ajst-28813	233	81	range	range	NOUN
ajst-28813	233	82	of	of	ADP
ajst-28813	233	83	the	the	DET
ajst-28813	233	84	leakage	leakage	NOUN
ajst-28813	233	85	rate	rate	NOUN
ajst-28813	233	86	is	be	AUX
ajst-28813	233	87	between	between	ADP
ajst-28813	233	88	(	(	PUNCT
ajst-28813	233	89	0,1	0,1	NUM
ajst-28813	233	90	)	)	PUNCT
ajst-28813	233	91	,	,	PUNCT
ajst-28813	233	92	so	so	CCONJ
ajst-28813	233	93	when	when	SCONJ
ajst-28813	233	94	looking	look	VERB
ajst-28813	233	95	for	for	ADP
ajst-28813	233	96	the	the	DET
ajst-28813	233	97	best	good	ADJ
ajst-28813	233	98	leakage	leakage	NOUN
ajst-28813	233	99	rate	rate	NOUN
ajst-28813	233	100	of	of	ADP
ajst-28813	233	101	the	the	DET
ajst-28813	233	102	esn	esn	PROPN
ajst-28813	233	103	network	network	NOUN
ajst-28813	233	104	252	252	NUM
ajst-28813	233	105	model	model	NOUN
ajst-28813	233	106	,	,	PUNCT
ajst-28813	233	107	the	the	DET
ajst-28813	233	108	leakage	leakage	NOUN
ajst-28813	233	109	rate	rate	NOUN
ajst-28813	233	110	is	be	AUX
ajst-28813	233	111	searched	search	VERB
ajst-28813	233	112	through	through	ADP
ajst-28813	233	113	a	a	DET
ajst-28813	233	114	large	large	ADJ
ajst-28813	233	115	gap	gap	NOUN
ajst-28813	233	116	,	,	PUNCT
ajst-28813	233	117	and	and	CCONJ
ajst-28813	233	118	the	the	DET
ajst-28813	233	119	corresponding	correspond	VERB
ajst-28813	233	120	fitness	fitness	NOUN
ajst-28813	233	121	is	be	AUX
ajst-28813	233	122	recorded	record	VERB
ajst-28813	233	123	.	.	PUNCT
ajst-28813	234	1	as	as	SCONJ
ajst-28813	234	2	shown	show	VERB
ajst-28813	234	3	in	in	ADP
ajst-28813	234	4	figure	figure	NOUN
ajst-28813	234	5	25	25	NUM
ajst-28813	234	6	,	,	PUNCT
ajst-28813	234	7	in	in	ADP
ajst-28813	234	8	the	the	DET
ajst-28813	234	9	line	line	NOUN
ajst-28813	234	10	diagram	diagram	NOUN
ajst-28813	234	11	of	of	ADP
ajst-28813	234	12	the	the	DET
ajst-28813	234	13	leakage	leakage	NOUN
ajst-28813	234	14	rate	rate	NOUN
ajst-28813	234	15	and	and	CCONJ
ajst-28813	234	16	fitness	fitness	NOUN
ajst-28813	234	17	(	(	PUNCT
ajst-28813	234	18	mse	mse	NOUN
ajst-28813	234	19	)	)	PUNCT
ajst-28813	234	20	of	of	ADP
ajst-28813	234	21	large	large	ADJ
ajst-28813	234	22	gaps	gap	NOUN
ajst-28813	234	23	,	,	PUNCT
ajst-28813	234	24	the	the	DET
ajst-28813	234	25	optimal	optimal	ADJ
ajst-28813	234	26	leakage	leakage	NOUN
ajst-28813	234	27	rate	rate	NOUN
ajst-28813	234	28	of	of	ADP
ajst-28813	234	29	the	the	DET
ajst-28813	234	30	network	network	NOUN
ajst-28813	234	31	is	be	AUX
ajst-28813	234	32	around	around	ADP
ajst-28813	234	33	0.3	0.3	NUM
ajst-28813	234	34	.	.	PUNCT
ajst-28813	235	1	figure	figure	VERB
ajst-28813	235	2	2	2	NUM
ajst-28813	235	3	-	-	SYM
ajst-28813	235	4	5	5	NUM
ajst-28813	235	5	.	.	PUNCT
ajst-28813	236	1	leak	leak	NOUN
ajst-28813	236	2	rate	rate	NOUN
ajst-28813	236	3	search	search	NOUN
ajst-28813	236	4	next	next	ADV
ajst-28813	236	5	,	,	PUNCT
ajst-28813	236	6	narrow	narrow	VERB
ajst-28813	236	7	the	the	DET
ajst-28813	236	8	value	value	NOUN
ajst-28813	236	9	gap	gap	NOUN
ajst-28813	236	10	of	of	ADP
ajst-28813	236	11	the	the	DET
ajst-28813	236	12	leakage	leakage	NOUN
ajst-28813	236	13	rate	rate	NOUN
ajst-28813	236	14	,	,	PUNCT
ajst-28813	236	15	run	run	VERB
ajst-28813	236	16	the	the	DET
ajst-28813	236	17	code	code	NOUN
ajst-28813	236	18	again	again	ADV
ajst-28813	236	19	,	,	PUNCT
ajst-28813	236	20	and	and	CCONJ
ajst-28813	236	21	search	search	VERB
ajst-28813	236	22	the	the	DET
ajst-28813	236	23	area	area	NOUN
ajst-28813	236	24	near	near	ADP
ajst-28813	236	25	the	the	DET
ajst-28813	236	26	leakage	leakage	NOUN
ajst-28813	236	27	rate	rate	NOUN
ajst-28813	236	28	of	of	ADP
ajst-28813	236	29	0.3	0.3	NUM
ajst-28813	236	30	.	.	PUNCT
ajst-28813	237	1	figure	figure	VERB
ajst-28813	237	2	2	2	NUM
ajst-28813	237	3	-	-	SYM
ajst-28813	237	4	6	6	NUM
ajst-28813	237	5	.	.	PUNCT
ajst-28813	238	1	a	a	DET
ajst-28813	238	2	leak	leak	NOUN
ajst-28813	238	3	rate	rate	NOUN
ajst-28813	238	4	search	search	NOUN
ajst-28813	238	5	for	for	ADP
ajst-28813	238	6	ordinary	ordinary	ADJ
ajst-28813	238	7	methods	method	NOUN
ajst-28813	238	8	figure	figure	VERB
ajst-28813	238	9	2	2	NUM
ajst-28813	238	10	-	-	SYM
ajst-28813	238	11	7	7	NUM
ajst-28813	238	12	.	.	PUNCT
ajst-28813	239	1	a	a	DET
ajst-28813	239	2	leak	leak	NOUN
ajst-28813	239	3	rate	rate	NOUN
ajst-28813	239	4	search	search	NOUN
ajst-28813	239	5	using	use	VERB
ajst-28813	239	6	the	the	DET
ajst-28813	239	7	pso	pso	NOUN
ajst-28813	239	8	algorithm	algorithm	NOUN
ajst-28813	239	9	when	when	SCONJ
ajst-28813	239	10	the	the	DET
ajst-28813	239	11	value	value	NOUN
ajst-28813	239	12	gap	gap	NOUN
ajst-28813	239	13	of	of	ADP
ajst-28813	239	14	the	the	DET
ajst-28813	239	15	leakage	leakage	NOUN
ajst-28813	239	16	rate	rate	NOUN
ajst-28813	239	17	search	search	NOUN
ajst-28813	239	18	is	be	AUX
ajst-28813	239	19	taken	take	VERB
ajst-28813	239	20	to	to	ADP
ajst-28813	239	21	0.02	0.02	NUM
ajst-28813	239	22	,	,	PUNCT
ajst-28813	239	23	it	it	PRON
ajst-28813	239	24	can	can	AUX
ajst-28813	239	25	be	be	AUX
ajst-28813	239	26	observed	observe	VERB
ajst-28813	239	27	that	that	SCONJ
ajst-28813	239	28	the	the	DET
ajst-28813	239	29	best	good	ADJ
ajst-28813	239	30	leakage	leakage	NOUN
ajst-28813	239	31	rate	rate	NOUN
ajst-28813	239	32	obtained	obtain	VERB
ajst-28813	239	33	by	by	ADP
ajst-28813	239	34	the	the	DET
ajst-28813	239	35	conventional	conventional	ADJ
ajst-28813	239	36	method	method	NOUN
ajst-28813	239	37	is	be	AUX
ajst-28813	239	38	0.24	0.24	NUM
ajst-28813	239	39	,	,	PUNCT
ajst-28813	239	40	while	while	SCONJ
ajst-28813	239	41	the	the	DET
ajst-28813	239	42	corresponding	correspond	VERB
ajst-28813	239	43	mse	mse	NOUN
ajst-28813	239	44	value	value	NOUN
ajst-28813	239	45	is	be	AUX
ajst-28813	239	46	0.0794	0.0794	NUM
ajst-28813	239	47	,	,	PUNCT
ajst-28813	239	48	and	and	CCONJ
ajst-28813	239	49	the	the	DET
ajst-28813	239	50	best	good	ADJ
ajst-28813	239	51	leakage	leakage	NOUN
ajst-28813	239	52	rate	rate	NOUN
ajst-28813	239	53	optimized	optimize	VERB
ajst-28813	239	54	by	by	ADP
ajst-28813	239	55	pso	pso	NOUN
ajst-28813	239	56	algorithm	algorithm	NOUN
ajst-28813	239	57	is	be	AUX
ajst-28813	239	58	0.22	0.22	NUM
ajst-28813	239	59	,	,	PUNCT
ajst-28813	239	60	and	and	CCONJ
ajst-28813	239	61	the	the	DET
ajst-28813	239	62	corresponding	correspond	VERB
ajst-28813	239	63	mse	mse	NOUN
ajst-28813	239	64	value	value	NOUN
ajst-28813	239	65	is	be	AUX
ajst-28813	239	66	0.0898	0.0898	NUM
ajst-28813	239	67	.	.	PUNCT
ajst-28813	240	1	in	in	ADP
ajst-28813	240	2	order	order	NOUN
ajst-28813	240	3	to	to	PART
ajst-28813	240	4	provide	provide	VERB
ajst-28813	240	5	better	well	ADJ
ajst-28813	240	6	esn	esn	PROPN
ajst-28813	240	7	dynamic	dynamic	ADJ
ajst-28813	240	8	expression	expression	NOUN
ajst-28813	240	9	characteristics	characteristic	NOUN
ajst-28813	240	10	,	,	PUNCT
ajst-28813	240	11	it	it	PRON
ajst-28813	240	12	is	be	AUX
ajst-28813	240	13	more	more	ADV
ajst-28813	240	14	appropriate	appropriate	ADJ
ajst-28813	240	15	to	to	PART
ajst-28813	240	16	choose	choose	VERB
ajst-28813	240	17	0.22	0.22	NUM
ajst-28813	240	18	as	as	ADP
ajst-28813	240	19	the	the	DET
ajst-28813	240	20	leakage	leakage	NOUN
ajst-28813	240	21	rate	rate	NOUN
ajst-28813	240	22	of	of	ADP
ajst-28813	240	23	esn	esn	PROPN
ajst-28813	240	24	network	network	NOUN
ajst-28813	240	25	with	with	ADP
ajst-28813	240	26	a	a	DET
ajst-28813	240	27	small	small	ADJ
ajst-28813	240	28	mse	mse	NOUN
ajst-28813	240	29	gap	gap	NOUN
ajst-28813	240	30	.	.	PUNCT
ajst-28813	241	1	(	(	PUNCT
ajst-28813	241	2	2	2	X
ajst-28813	241	3	)	)	PUNCT
ajst-28813	241	4	the	the	DET
ajst-28813	241	5	number	number	NOUN
ajst-28813	241	6	of	of	ADP
ajst-28813	241	7	neurons	neuron	NOUN
ajst-28813	241	8	the	the	DET
ajst-28813	241	9	choice	choice	NOUN
ajst-28813	241	10	of	of	ADP
ajst-28813	241	11	the	the	DET
ajst-28813	241	12	number	number	NOUN
ajst-28813	241	13	of	of	ADP
ajst-28813	241	14	neurons	neuron	NOUN
ajst-28813	241	15	in	in	ADP
ajst-28813	241	16	the	the	DET
ajst-28813	241	17	hidden	hide	VERB
ajst-28813	241	18	layer	layer	NOUN
ajst-28813	241	19	of	of	ADP
ajst-28813	241	20	an	an	DET
ajst-28813	241	21	esn	esn	PROPN
ajst-28813	241	22	network	network	NOUN
ajst-28813	241	23	includes	include	VERB
ajst-28813	241	24	finding	find	VERB
ajst-28813	241	25	the	the	DET
ajst-28813	241	26	minimum	minimum	ADJ
ajst-28813	241	27	number	number	NOUN
ajst-28813	241	28	because	because	SCONJ
ajst-28813	241	29	it	it	PRON
ajst-28813	241	30	can	can	AUX
ajst-28813	241	31	directly	directly	ADV
ajst-28813	241	32	affect	affect	VERB
ajst-28813	241	33	the	the	DET
ajst-28813	241	34	computational	computational	ADJ
ajst-28813	241	35	efficiency	efficiency	NOUN
ajst-28813	241	36	of	of	ADP
ajst-28813	241	37	the	the	DET
ajst-28813	241	38	entire	entire	ADJ
ajst-28813	241	39	network	network	NOUN
ajst-28813	241	40	while	while	SCONJ
ajst-28813	241	41	minimizing	minimize	VERB
ajst-28813	241	42	the	the	DET
ajst-28813	241	43	error	error	NOUN
ajst-28813	241	44	of	of	ADP
ajst-28813	241	45	the	the	DET
ajst-28813	241	46	network	network	NOUN
ajst-28813	241	47	prediction	prediction	NOUN
ajst-28813	241	48	.	.	PUNCT
ajst-28813	242	1	as	as	SCONJ
ajst-28813	242	2	shown	show	VERB
ajst-28813	242	3	in	in	ADP
ajst-28813	242	4	figures	figure	NOUN
ajst-28813	242	5	3	3	NUM
ajst-28813	242	6	-	-	SYM
ajst-28813	242	7	10	10	NUM
ajst-28813	242	8	,	,	PUNCT
ajst-28813	242	9	a	a	DET
ajst-28813	242	10	bar	bar	NOUN
ajst-28813	242	11	plot	plot	NOUN
ajst-28813	242	12	of	of	ADP
ajst-28813	242	13	the	the	DET
ajst-28813	242	14	running	running	ADJ
ajst-28813	242	15	time	time	NOUN
ajst-28813	242	16	of	of	ADP
ajst-28813	242	17	the	the	DET
ajst-28813	242	18	esn	esn	PROPN
ajst-28813	242	19	network	network	NOUN
ajst-28813	242	20	as	as	ADP
ajst-28813	242	21	a	a	DET
ajst-28813	242	22	function	function	NOUN
ajst-28813	242	23	of	of	ADP
ajst-28813	242	24	the	the	DET
ajst-28813	242	25	number	number	NOUN
ajst-28813	242	26	of	of	ADP
ajst-28813	242	27	neurons	neuron	NOUN
ajst-28813	242	28	.	.	PUNCT
ajst-28813	243	1	as	as	ADP
ajst-28813	243	2	the	the	DET
ajst-28813	243	3	number	number	NOUN
ajst-28813	243	4	of	of	ADP
ajst-28813	243	5	neurons	neuron	NOUN
ajst-28813	243	6	increases	increase	NOUN
ajst-28813	243	7	,	,	PUNCT
ajst-28813	243	8	the	the	DET
ajst-28813	243	9	running	running	ADJ
ajst-28813	243	10	time	time	NOUN
ajst-28813	243	11	of	of	ADP
ajst-28813	243	12	the	the	DET
ajst-28813	243	13	network	network	NOUN
ajst-28813	243	14	increases	increase	VERB
ajst-28813	243	15	accordingly	accordingly	ADV
ajst-28813	243	16	.	.	PUNCT
ajst-28813	244	1	this	this	PRON
ajst-28813	244	2	is	be	AUX
ajst-28813	244	3	because	because	SCONJ
ajst-28813	244	4	more	more	ADJ
ajst-28813	244	5	neurons	neuron	NOUN
ajst-28813	244	6	mean	mean	VERB
ajst-28813	244	7	that	that	SCONJ
ajst-28813	244	8	more	more	ADV
ajst-28813	244	9	computational	computational	ADJ
ajst-28813	244	10	resources	resource	NOUN
ajst-28813	244	11	and	and	CCONJ
ajst-28813	244	12	time	time	NOUN
ajst-28813	244	13	are	be	AUX
ajst-28813	244	14	spent	spend	VERB
ajst-28813	244	15	on	on	ADP
ajst-28813	244	16	processing	processing	NOUN
ajst-28813	244	17	and	and	CCONJ
ajst-28813	244	18	transmitting	transmit	VERB
ajst-28813	244	19	information	information	NOUN
ajst-28813	244	20	.	.	PUNCT
ajst-28813	245	1	however	however	ADV
ajst-28813	245	2	,	,	PUNCT
ajst-28813	245	3	we	we	PRON
ajst-28813	245	4	can	can	AUX
ajst-28813	245	5	not	not	PART
ajst-28813	245	6	simply	simply	ADV
ajst-28813	245	7	pursue	pursue	VERB
ajst-28813	245	8	the	the	DET
ajst-28813	245	9	minimum	minimum	ADJ
ajst-28813	245	10	number	number	NOUN
ajst-28813	245	11	of	of	ADP
ajst-28813	245	12	neurons	neuron	NOUN
ajst-28813	245	13	.	.	PUNCT
ajst-28813	246	1	in	in	ADP
ajst-28813	246	2	practice	practice	NOUN
ajst-28813	246	3	,	,	PUNCT
ajst-28813	246	4	we	we	PRON
ajst-28813	246	5	need	need	VERB
ajst-28813	246	6	to	to	PART
ajst-28813	246	7	find	find	VERB
ajst-28813	246	8	a	a	DET
ajst-28813	246	9	balance	balance	NOUN
ajst-28813	246	10	between	between	ADP
ajst-28813	246	11	computational	computational	ADJ
ajst-28813	246	12	efficiency	efficiency	NOUN
ajst-28813	246	13	and	and	CCONJ
ajst-28813	246	14	predictive	predictive	ADJ
ajst-28813	246	15	accuracy	accuracy	NOUN
ajst-28813	246	16	.	.	PUNCT
ajst-28813	247	1	figure	figure	NOUN
ajst-28813	247	2	2	2	NUM
ajst-28813	247	3	-	-	SYM
ajst-28813	247	4	8	8	NUM
ajst-28813	247	5	.	.	PUNCT
ajst-28813	248	1	comparison	comparison	NOUN
ajst-28813	248	2	of	of	ADP
ajst-28813	248	3	network	network	NOUN
ajst-28813	248	4	operation	operation	NOUN
ajst-28813	248	5	data	datum	NOUN
ajst-28813	248	6	under	under	ADP
ajst-28813	248	7	different	different	ADJ
ajst-28813	248	8	number	number	NOUN
ajst-28813	248	9	of	of	ADP
ajst-28813	248	10	neurons	neuron	NOUN
ajst-28813	248	11	the	the	DET
ajst-28813	248	12	particle	particle	NOUN
ajst-28813	248	13	swarm	swarm	NOUN
ajst-28813	248	14	algorithm	algorithm	NOUN
ajst-28813	248	15	(	(	PUNCT
ajst-28813	248	16	pso	pso	NOUN
ajst-28813	248	17	)	)	PUNCT
ajst-28813	248	18	considers	consider	VERB
ajst-28813	248	19	the	the	DET
ajst-28813	248	20	balance	balance	NOUN
ajst-28813	248	21	between	between	ADP
ajst-28813	248	22	the	the	DET
ajst-28813	248	23	complexity	complexity	NOUN
ajst-28813	248	24	of	of	ADP
ajst-28813	248	25	the	the	DET
ajst-28813	248	26	network	network	NOUN
ajst-28813	248	27	and	and	CCONJ
ajst-28813	248	28	the	the	DET
ajst-28813	248	29	prediction	prediction	NOUN
ajst-28813	248	30	performance	performance	NOUN
ajst-28813	248	31	when	when	SCONJ
ajst-28813	248	32	searching	search	VERB
ajst-28813	248	33	for	for	ADP
ajst-28813	248	34	the	the	DET
ajst-28813	248	35	optimal	optimal	ADJ
ajst-28813	248	36	number	number	NOUN
ajst-28813	248	37	of	of	ADP
ajst-28813	248	38	neurons	neuron	NOUN
ajst-28813	248	39	.	.	PUNCT
ajst-28813	249	1	with	with	ADP
ajst-28813	249	2	multiple	multiple	ADJ
ajst-28813	249	3	iterations	iteration	NOUN
ajst-28813	249	4	and	and	CCONJ
ajst-28813	249	5	repeated	repeat	VERB
ajst-28813	249	6	testing	testing	NOUN
ajst-28813	249	7	,	,	PUNCT
ajst-28813	249	8	we	we	PRON
ajst-28813	249	9	253	253	NUM
ajst-28813	249	10	finally	finally	ADV
ajst-28813	249	11	determined	determine	VERB
ajst-28813	249	12	the	the	DET
ajst-28813	249	13	best	good	ADJ
ajst-28813	249	14	value	value	NOUN
ajst-28813	249	15	of	of	ADP
ajst-28813	249	16	300	300	NUM
ajst-28813	249	17	.	.	PUNCT
ajst-28813	250	1	this	this	DET
ajst-28813	250	2	value	value	NOUN
ajst-28813	250	3	ensures	ensure	VERB
ajst-28813	250	4	the	the	DET
ajst-28813	250	5	prediction	prediction	NOUN
ajst-28813	250	6	accuracy	accuracy	NOUN
ajst-28813	250	7	of	of	ADP
ajst-28813	250	8	the	the	DET
ajst-28813	250	9	model	model	NOUN
ajst-28813	250	10	while	while	SCONJ
ajst-28813	250	11	effectively	effectively	ADV
ajst-28813	250	12	avoiding	avoid	VERB
ajst-28813	250	13	overfitting	overfitte	VERB
ajst-28813	250	14	and	and	CCONJ
ajst-28813	250	15	waste	waste	NOUN
ajst-28813	250	16	of	of	ADP
ajst-28813	250	17	computational	computational	ADJ
ajst-28813	250	18	resources	resource	NOUN
ajst-28813	250	19	.	.	PUNCT
ajst-28813	251	1	as	as	SCONJ
ajst-28813	251	2	shown	show	VERB
ajst-28813	251	3	in	in	ADP
ajst-28813	251	4	table	table	NOUN
ajst-28813	251	5	2	2	NUM
ajst-28813	251	6	-	-	SYM
ajst-28813	251	7	3	3	NUM
ajst-28813	251	8	,	,	PUNCT
ajst-28813	251	9	the	the	DET
ajst-28813	251	10	standard	standard	ADJ
ajst-28813	251	11	root	root	NOUN
ajst-28813	251	12	mean	mean	VERB
ajst-28813	251	13	square	square	ADJ
ajst-28813	251	14	error	error	NOUN
ajst-28813	251	15	(	(	PUNCT
ajst-28813	251	16	nrmse	nrmse	NOUN
ajst-28813	251	17	)	)	PUNCT
ajst-28813	251	18	values	value	NOUN
ajst-28813	251	19	of	of	ADP
ajst-28813	251	20	the	the	DET
ajst-28813	251	21	network	network	NOUN
ajst-28813	251	22	after	after	ADP
ajst-28813	251	23	operation	operation	NOUN
ajst-28813	251	24	with	with	ADP
ajst-28813	251	25	different	different	ADJ
ajst-28813	251	26	numbers	number	NOUN
ajst-28813	251	27	of	of	ADP
ajst-28813	251	28	neurons	neuron	NOUN
ajst-28813	251	29	demonstrate	demonstrate	VERB
ajst-28813	251	30	this	this	DET
ajst-28813	251	31	optimization	optimization	NOUN
ajst-28813	251	32	process	process	NOUN
ajst-28813	251	33	.	.	PUNCT
ajst-28813	252	1	by	by	ADP
ajst-28813	252	2	comparing	compare	VERB
ajst-28813	252	3	the	the	DET
ajst-28813	252	4	network	network	NOUN
ajst-28813	252	5	performance	performance	NOUN
ajst-28813	252	6	with	with	ADP
ajst-28813	252	7	different	different	ADJ
ajst-28813	252	8	numbers	number	NOUN
ajst-28813	252	9	of	of	ADP
ajst-28813	252	10	neurons	neuron	NOUN
ajst-28813	252	11	,	,	PUNCT
ajst-28813	252	12	when	when	SCONJ
ajst-28813	252	13	the	the	DET
ajst-28813	252	14	number	number	NOUN
ajst-28813	252	15	of	of	ADP
ajst-28813	252	16	neurons	neuron	NOUN
ajst-28813	252	17	is	be	AUX
ajst-28813	252	18	300	300	NUM
ajst-28813	252	19	.	.	PUNCT
ajst-28813	253	1	the	the	DET
ajst-28813	253	2	network	network	NOUN
ajst-28813	253	3	achieves	achieve	VERB
ajst-28813	253	4	the	the	DET
ajst-28813	253	5	best	good	ADJ
ajst-28813	253	6	balance	balance	NOUN
ajst-28813	253	7	between	between	ADP
ajst-28813	253	8	prediction	prediction	NOUN
ajst-28813	253	9	accuracy	accuracy	NOUN
ajst-28813	253	10	and	and	CCONJ
ajst-28813	253	11	computational	computational	ADJ
ajst-28813	253	12	efficiency	efficiency	NOUN
ajst-28813	253	13	.	.	PUNCT
ajst-28813	254	1	this	this	PRON
ajst-28813	254	2	result	result	VERB
ajst-28813	254	3	not	not	PART
ajst-28813	254	4	only	only	ADV
ajst-28813	254	5	verifies	verifie	NOUN
ajst-28813	254	6	the	the	DET
ajst-28813	254	7	effectiveness	effectiveness	NOUN
ajst-28813	254	8	of	of	ADP
ajst-28813	254	9	the	the	DET
ajst-28813	254	10	pso	pso	NOUN
ajst-28813	254	11	algorithm	algorithm	NOUN
ajst-28813	254	12	in	in	ADP
ajst-28813	254	13	the	the	DET
ajst-28813	254	14	optimization	optimization	NOUN
ajst-28813	254	15	of	of	ADP
ajst-28813	254	16	neural	neural	ADJ
ajst-28813	254	17	network	network	NOUN
ajst-28813	254	18	structure	structure	NOUN
ajst-28813	254	19	,	,	PUNCT
ajst-28813	254	20	but	but	CCONJ
ajst-28813	254	21	also	also	ADV
ajst-28813	254	22	provides	provide	VERB
ajst-28813	254	23	ideas	idea	NOUN
ajst-28813	254	24	for	for	ADP
ajst-28813	254	25	subsequent	subsequent	ADJ
ajst-28813	254	26	studies	study	NOUN
ajst-28813	254	27	.	.	PUNCT
ajst-28813	255	1	table	table	NOUN
ajst-28813	255	2	2	2	NUM
ajst-28813	255	3	-	-	SYM
ajst-28813	255	4	3	3	NUM
ajst-28813	255	5	.	.	PUNCT
ajst-28813	256	1	network	network	NOUN
ajst-28813	256	2	parameters	parameter	NOUN
ajst-28813	256	3	of	of	ADP
ajst-28813	256	4	the	the	DET
ajst-28813	256	5	esn	esn	PROPN
ajst-28813	256	6	number	number	NOUN
ajst-28813	256	7	of	of	ADP
ajst-28813	256	8	neurons	neuron	NOUN
ajst-28813	256	9	nrmse	nrmse	VERB
ajst-28813	256	10	50	50	NUM
ajst-28813	256	11	0.1772	0.1772	NUM
ajst-28813	256	12	100	100	NUM
ajst-28813	256	13	0.1751	0.1751	NUM
ajst-28813	256	14	150	150	NUM
ajst-28813	256	15	0.1750	0.1750	NUM
ajst-28813	256	16	200	200	NUM
ajst-28813	256	17	0.1786	0.1786	NUM
ajst-28813	256	18	250	250	NUM
ajst-28813	256	19	0.1768	0.1768	NUM
ajst-28813	256	20	300	300	NUM
ajst-28813	256	21	0.1727	0.1727	NUM
ajst-28813	256	22	350	350	NUM
ajst-28813	256	23	0.1789	0.1789	NUM
ajst-28813	256	24	400	400	NUM
ajst-28813	256	25	0.1731	0.1731	NUM
ajst-28813	256	26	(	(	PUNCT
ajst-28813	256	27	3	3	X
ajst-28813	256	28	)	)	PUNCT
ajst-28813	256	29	sampling	sample	VERB
ajst-28813	256	30	rate	rate	NOUN
ajst-28813	256	31	it	it	PRON
ajst-28813	256	32	is	be	AUX
ajst-28813	256	33	crucial	crucial	ADJ
ajst-28813	256	34	to	to	PART
ajst-28813	256	35	ensure	ensure	VERB
ajst-28813	256	36	the	the	DET
ajst-28813	256	37	accuracy	accuracy	NOUN
ajst-28813	256	38	of	of	ADP
ajst-28813	256	39	sampling	sample	VERB
ajst-28813	256	40	rate	rate	NOUN
ajst-28813	256	41	,	,	PUNCT
ajst-28813	256	42	which	which	PRON
ajst-28813	256	43	is	be	AUX
ajst-28813	256	44	directly	directly	ADV
ajst-28813	256	45	related	relate	VERB
ajst-28813	256	46	to	to	ADP
ajst-28813	256	47	whether	whether	SCONJ
ajst-28813	256	48	the	the	DET
ajst-28813	256	49	dynamic	dynamic	ADJ
ajst-28813	256	50	behavior	behavior	NOUN
ajst-28813	256	51	of	of	ADP
ajst-28813	256	52	the	the	DET
ajst-28813	256	53	system	system	NOUN
ajst-28813	256	54	can	can	AUX
ajst-28813	256	55	be	be	AUX
ajst-28813	256	56	effectively	effectively	ADV
ajst-28813	256	57	captured	capture	VERB
ajst-28813	256	58	effectively	effectively	ADV
ajst-28813	256	59	.	.	PUNCT
ajst-28813	257	1	especially	especially	ADV
ajst-28813	257	2	for	for	ADP
ajst-28813	257	3	the	the	DET
ajst-28813	257	4	sensor	sensor	NOUN
ajst-28813	257	5	inside	inside	ADP
ajst-28813	257	6	the	the	DET
ajst-28813	257	7	electric	electric	ADJ
ajst-28813	257	8	submersible	submersible	ADJ
ajst-28813	257	9	pump	pump	NOUN
ajst-28813	257	10	,	,	PUNCT
ajst-28813	257	11	a	a	DET
ajst-28813	257	12	reasonable	reasonable	ADJ
ajst-28813	257	13	sampling	sampling	NOUN
ajst-28813	257	14	frequency	frequency	NOUN
ajst-28813	257	15	can	can	AUX
ajst-28813	257	16	make	make	VERB
ajst-28813	257	17	it	it	PRON
ajst-28813	257	18	have	have	VERB
ajst-28813	257	19	a	a	DET
ajst-28813	257	20	higher	high	ADJ
ajst-28813	257	21	work	work	NOUN
ajst-28813	257	22	efficiency	efficiency	NOUN
ajst-28813	257	23	.	.	PUNCT
ajst-28813	258	1	if	if	SCONJ
ajst-28813	258	2	the	the	DET
ajst-28813	258	3	sampling	sample	VERB
ajst-28813	258	4	rate	rate	NOUN
ajst-28813	258	5	is	be	AUX
ajst-28813	258	6	too	too	ADV
ajst-28813	258	7	low	low	ADJ
ajst-28813	258	8	,	,	PUNCT
ajst-28813	258	9	it	it	PRON
ajst-28813	258	10	may	may	AUX
ajst-28813	258	11	cause	cause	VERB
ajst-28813	258	12	some	some	DET
ajst-28813	258	13	important	important	ADJ
ajst-28813	258	14	dynamic	dynamic	ADJ
ajst-28813	258	15	changes	change	NOUN
ajst-28813	258	16	not	not	PART
ajst-28813	258	17	to	to	PART
ajst-28813	258	18	be	be	AUX
ajst-28813	258	19	captured	capture	VERB
ajst-28813	258	20	,	,	PUNCT
ajst-28813	258	21	because	because	SCONJ
ajst-28813	258	22	the	the	DET
ajst-28813	258	23	interval	interval	NOUN
ajst-28813	258	24	between	between	ADP
ajst-28813	258	25	the	the	DET
ajst-28813	258	26	data	data	NOUN
ajst-28813	258	27	points	point	NOUN
ajst-28813	258	28	is	be	AUX
ajst-28813	258	29	too	too	ADV
ajst-28813	258	30	large	large	ADJ
ajst-28813	258	31	to	to	PART
ajst-28813	258	32	capture	capture	VERB
ajst-28813	258	33	those	those	DET
ajst-28813	258	34	subtle	subtle	ADJ
ajst-28813	258	35	changes	change	NOUN
ajst-28813	258	36	.	.	PUNCT
ajst-28813	259	1	in	in	ADP
ajst-28813	259	2	figure	figure	NOUN
ajst-28813	259	3	2	2	NUM
ajst-28813	259	4	-	-	SYM
ajst-28813	259	5	9	9	NUM
ajst-28813	259	6	,	,	PUNCT
ajst-28813	259	7	we	we	PRON
ajst-28813	259	8	can	can	AUX
ajst-28813	259	9	see	see	VERB
ajst-28813	259	10	the	the	DET
ajst-28813	259	11	change	change	NOUN
ajst-28813	259	12	of	of	ADP
ajst-28813	259	13	the	the	DET
ajst-28813	259	14	well	well	ADV
ajst-28813	259	15	bottom	bottom	ADJ
ajst-28813	259	16	pressure	pressure	NOUN
ajst-28813	259	17	data	datum	NOUN
ajst-28813	259	18	of	of	ADP
ajst-28813	259	19	the	the	DET
ajst-28813	259	20	electric	electric	ADJ
ajst-28813	259	21	submersible	submersible	ADJ
ajst-28813	259	22	pump	pump	NOUN
ajst-28813	259	23	at	at	ADP
ajst-28813	259	24	different	different	ADJ
ajst-28813	259	25	sampling	sample	VERB
ajst-28813	259	26	frequencies	frequency	NOUN
ajst-28813	259	27	.	.	PUNCT
ajst-28813	260	1	by	by	ADP
ajst-28813	260	2	comparing	compare	VERB
ajst-28813	260	3	the	the	DET
ajst-28813	260	4	cases	case	NOUN
ajst-28813	260	5	of	of	ADP
ajst-28813	260	6	12	12	NUM
ajst-28813	260	7	sampling	sampling	NOUN
ajst-28813	260	8	and	and	CCONJ
ajst-28813	260	9	6	6	NUM
ajst-28813	260	10	sampling	sample	VERB
ajst-28813	260	11	per	per	ADP
ajst-28813	260	12	minute	minute	NOUN
ajst-28813	260	13	,	,	PUNCT
ajst-28813	260	14	we	we	PRON
ajst-28813	260	15	can	can	AUX
ajst-28813	260	16	clearly	clearly	ADV
ajst-28813	260	17	observe	observe	VERB
ajst-28813	260	18	that	that	SCONJ
ajst-28813	260	19	the	the	DET
ajst-28813	260	20	data	datum	NOUN
ajst-28813	260	21	image	image	NOUN
ajst-28813	260	22	slope	slope	NOUN
ajst-28813	260	23	change	change	NOUN
ajst-28813	260	24	of	of	ADP
ajst-28813	260	25	12	12	NUM
ajst-28813	260	26	sampling	sampling	NOUN
ajst-28813	260	27	per	per	ADP
ajst-28813	260	28	minute	minute	NOUN
ajst-28813	260	29	shows	show	VERB
ajst-28813	260	30	a	a	DET
ajst-28813	260	31	higher	high	ADJ
ajst-28813	260	32	degree	degree	NOUN
ajst-28813	260	33	of	of	ADP
ajst-28813	260	34	nonlinearity	nonlinearity	NOUN
ajst-28813	260	35	.	.	PUNCT
ajst-28813	261	1	this	this	DET
ajst-28813	261	2	further	far	ADV
ajst-28813	261	3	demonstrates	demonstrate	VERB
ajst-28813	261	4	the	the	DET
ajst-28813	261	5	importance	importance	NOUN
ajst-28813	261	6	of	of	ADP
ajst-28813	261	7	a	a	DET
ajst-28813	261	8	higher	high	ADJ
ajst-28813	261	9	sampling	sampling	NOUN
ajst-28813	261	10	rate	rate	NOUN
ajst-28813	261	11	in	in	ADP
ajst-28813	261	12	capturing	capture	VERB
ajst-28813	261	13	the	the	DET
ajst-28813	261	14	dynamic	dynamic	ADJ
ajst-28813	261	15	changes	change	NOUN
ajst-28813	261	16	of	of	ADP
ajst-28813	261	17	the	the	DET
ajst-28813	261	18	system	system	NOUN
ajst-28813	261	19	.	.	PUNCT
ajst-28813	262	1	instead	instead	ADV
ajst-28813	262	2	,	,	PUNCT
ajst-28813	262	3	a	a	DET
ajst-28813	262	4	lower	low	ADJ
ajst-28813	262	5	sampling	sample	VERB
ajst-28813	262	6	rate	rate	NOUN
ajst-28813	262	7	may	may	AUX
ajst-28813	262	8	cause	cause	VERB
ajst-28813	262	9	some	some	DET
ajst-28813	262	10	important	important	ADJ
ajst-28813	262	11	dynamic	dynamic	ADJ
ajst-28813	262	12	changes	change	NOUN
ajst-28813	262	13	to	to	PART
ajst-28813	262	14	be	be	AUX
ajst-28813	262	15	ignored	ignore	VERB
ajst-28813	262	16	,	,	PUNCT
ajst-28813	262	17	thus	thus	ADV
ajst-28813	262	18	affecting	affect	VERB
ajst-28813	262	19	an	an	DET
ajst-28813	262	20	accurate	accurate	ADJ
ajst-28813	262	21	assessment	assessment	NOUN
ajst-28813	262	22	of	of	ADP
ajst-28813	262	23	the	the	DET
ajst-28813	262	24	system	system	NOUN
ajst-28813	262	25	state	state	NOUN
ajst-28813	262	26	.	.	PUNCT
ajst-28813	263	1	figure	figure	NOUN
ajst-28813	263	2	2	2	NUM
ajst-28813	263	3	-	-	SYM
ajst-28813	263	4	9	9	NUM
ajst-28813	263	5	.	.	PUNCT
ajst-28813	263	6	comparison	comparison	NOUN
ajst-28813	263	7	plots	plot	NOUN
ajst-28813	263	8	of	of	ADP
ajst-28813	263	9	the	the	DET
ajst-28813	263	10	different	different	ADJ
ajst-28813	263	11	sampling	sampling	NOUN
ajst-28813	263	12	rates	rate	NOUN
ajst-28813	263	13	(	(	PUNCT
ajst-28813	263	14	4	4	X
ajst-28813	263	15	)	)	PUNCT
ajst-28813	263	16	enter	enter	VERB
ajst-28813	263	17	the	the	DET
ajst-28813	263	18	scale	scale	NOUN
ajst-28813	263	19	factor	factor	NOUN
ajst-28813	263	20	esn	esn	PROPN
ajst-28813	263	21	networks	networks	PROPN
ajst-28813	263	22	use	use	VERB
ajst-28813	263	23	the	the	DET
ajst-28813	263	24	hyperbolic	hyperbolic	ADJ
ajst-28813	263	25	tangent	tangent	NOUN
ajst-28813	263	26	function	function	NOUN
ajst-28813	263	27	as	as	ADP
ajst-28813	263	28	an	an	DET
ajst-28813	263	29	activation	activation	NOUN
ajst-28813	263	30	function	function	NOUN
ajst-28813	263	31	and	and	CCONJ
ajst-28813	263	32	handle	handle	VERB
ajst-28813	263	33	complex	complex	ADJ
ajst-28813	263	34	nonlinear	nonlinear	ADJ
ajst-28813	263	35	relationships	relationship	NOUN
ajst-28813	263	36	.	.	PUNCT
ajst-28813	264	1	when	when	SCONJ
ajst-28813	264	2	processing	process	VERB
ajst-28813	264	3	a	a	DET
ajst-28813	264	4	large	large	ADJ
ajst-28813	264	5	amount	amount	NOUN
ajst-28813	264	6	of	of	ADP
ajst-28813	264	7	fluctuating	fluctuate	VERB
ajst-28813	264	8	data	datum	NOUN
ajst-28813	264	9	,	,	PUNCT
ajst-28813	264	10	using	use	VERB
ajst-28813	264	11	small	small	ADJ
ajst-28813	264	12	input	input	NOUN
ajst-28813	264	13	scaling	scale	VERB
ajst-28813	264	14	factor	factor	NOUN
ajst-28813	264	15	can	can	AUX
ajst-28813	264	16	avoid	avoid	VERB
ajst-28813	264	17	gradient	gradient	ADJ
ajst-28813	264	18	disappearance	disappearance	NOUN
ajst-28813	264	19	and	and	CCONJ
ajst-28813	264	20	ensure	ensure	VERB
ajst-28813	264	21	stable	stable	ADJ
ajst-28813	264	22	network	network	NOUN
ajst-28813	264	23	performance	performance	NOUN
ajst-28813	264	24	.	.	PUNCT
ajst-28813	265	1	the	the	DET
ajst-28813	265	2	esn	esn	PROPN
ajst-28813	265	3	parameters	parameter	NOUN
ajst-28813	265	4	are	be	AUX
ajst-28813	265	5	shown	show	VERB
ajst-28813	265	6	in	in	ADP
ajst-28813	265	7	table	table	NOUN
ajst-28813	265	8	3	3	NUM
ajst-28813	265	9	-	-	SYM
ajst-28813	265	10	4	4	NUM
ajst-28813	265	11	,	,	PUNCT
ajst-28813	265	12	which	which	PRON
ajst-28813	265	13	are	be	AUX
ajst-28813	265	14	gradually	gradually	ADV
ajst-28813	265	15	adjusted	adjust	VERB
ajst-28813	265	16	to	to	PART
ajst-28813	265	17	accommodate	accommodate	VERB
ajst-28813	265	18	the	the	DET
ajst-28813	265	19	data	datum	NOUN
ajst-28813	265	20	complexity	complexity	NOUN
ajst-28813	265	21	,	,	PUNCT
ajst-28813	265	22	and	and	CCONJ
ajst-28813	265	23	the	the	DET
ajst-28813	265	24	slow	slow	ADJ
ajst-28813	265	25	fitting	fitting	ADJ
ajst-28813	265	26	process	process	NOUN
ajst-28813	265	27	improves	improve	VERB
ajst-28813	265	28	the	the	DET
ajst-28813	265	29	model	model	NOUN
ajst-28813	265	30	stability	stability	NOUN
ajst-28813	265	31	and	and	CCONJ
ajst-28813	265	32	accuracy	accuracy	NOUN
ajst-28813	265	33	,	,	PUNCT
ajst-28813	265	34	leading	lead	VERB
ajst-28813	265	35	to	to	ADP
ajst-28813	265	36	better	well	ADJ
ajst-28813	265	37	performance	performance	NOUN
ajst-28813	265	38	in	in	ADP
ajst-28813	265	39	practice	practice	NOUN
ajst-28813	265	40	.	.	PUNCT
ajst-28813	266	1	table	table	NOUN
ajst-28813	266	2	2	2	NUM
ajst-28813	266	3	-	-	SYM
ajst-28813	266	4	4	4	NUM
ajst-28813	266	5	.	.	PUNCT
ajst-28813	267	1	network	network	NOUN
ajst-28813	267	2	parameters	parameter	NOUN
ajst-28813	267	3	of	of	ADP
ajst-28813	267	4	the	the	DET
ajst-28813	267	5	esn	esn	PROPN
ajst-28813	267	6	parameter	parameter	PROPN
ajst-28813	267	7	name	name	NOUN
ajst-28813	267	8	sampling	sample	VERB
ajst-28813	267	9	rate	rate	NOUN
ajst-28813	267	10	12times	12time	NOUN
ajst-28813	267	11	/	/	SYM
ajst-28813	267	12	min	min	NOUN
ajst-28813	267	13	enter	enter	VERB
ajst-28813	267	14	the	the	DET
ajst-28813	267	15	scaling	scaling	ADJ
ajst-28813	267	16	factor	factor	NOUN
ajst-28813	267	17	0.1	0.1	NUM
ajst-28813	267	18	disclosure	disclosure	NOUN
ajst-28813	267	19	rate	rate	NOUN
ajst-28813	267	20	0.22	0.22	NUM
ajst-28813	267	21	number	number	NOUN
ajst-28813	267	22	of	of	ADP
ajst-28813	267	23	neurons	neuron	NOUN
ajst-28813	267	24	400	400	NUM
ajst-28813	267	25	spectral	spectral	ADJ
ajst-28813	267	26	radius	radius	NOUN
ajst-28813	267	27	0.99	0.99	NUM
ajst-28813	267	28	the	the	DET
ajst-28813	267	29	offset	offset	NOUN
ajst-28813	267	30	0.1	0.1	NUM
ajst-28813	267	31	254	254	NUM
ajst-28813	267	32	4	4	NUM
ajst-28813	267	33	.	.	PUNCT
ajst-28813	267	34	model	model	NOUN
ajst-28813	267	35	training	training	NOUN
ajst-28813	267	36	and	and	CCONJ
ajst-28813	267	37	validation	validation	NOUN
ajst-28813	267	38	4.1	4.1	NUM
ajst-28813	267	39	.	.	PUNCT
ajst-28813	268	1	network	network	NOUN
ajst-28813	268	2	parameter	parameter	NOUN
ajst-28813	268	3	determination	determination	NOUN
ajst-28813	268	4	the	the	DET
ajst-28813	268	5	parameter	parameter	NOUN
ajst-28813	268	6	configuration	configuration	NOUN
ajst-28813	268	7	of	of	ADP
ajst-28813	268	8	the	the	DET
ajst-28813	268	9	network	network	NOUN
ajst-28813	268	10	and	and	CCONJ
ajst-28813	268	11	the	the	DET
ajst-28813	268	12	implementation	implementation	NOUN
ajst-28813	268	13	of	of	ADP
ajst-28813	268	14	the	the	DET
ajst-28813	268	15	specific	specific	ADJ
ajst-28813	268	16	algorithm	algorithm	NOUN
ajst-28813	268	17	are	be	AUX
ajst-28813	268	18	constructed	construct	VERB
ajst-28813	268	19	through	through	ADP
ajst-28813	268	20	python3.9	python3.9	NOUN
ajst-28813	268	21	.	.	PUNCT
ajst-28813	269	1	based	base	VERB
ajst-28813	269	2	on	on	ADP
ajst-28813	269	3	this	this	PRON
ajst-28813	269	4	,	,	PUNCT
ajst-28813	269	5	the	the	DET
ajst-28813	269	6	corresponding	corresponding	ADJ
ajst-28813	269	7	training	training	NOUN
ajst-28813	269	8	dataset	dataset	NOUN
ajst-28813	269	9	was	be	AUX
ajst-28813	269	10	created	create	VERB
ajst-28813	269	11	according	accord	VERB
ajst-28813	269	12	to	to	ADP
ajst-28813	269	13	the	the	DET
ajst-28813	269	14	actual	actual	ADJ
ajst-28813	269	15	type	type	NOUN
ajst-28813	269	16	of	of	ADP
ajst-28813	269	17	submersible	submersible	ADJ
ajst-28813	269	18	pump	pump	NOUN
ajst-28813	269	19	wells	well	NOUN
ajst-28813	269	20	.	.	PUNCT
ajst-28813	270	1	the	the	DET
ajst-28813	270	2	data	datum	NOUN
ajst-28813	270	3	were	be	AUX
ajst-28813	270	4	generated	generate	VERB
ajst-28813	270	5	using	use	VERB
ajst-28813	270	6	the	the	DET
ajst-28813	270	7	numpy	numpy	NOUN
ajst-28813	270	8	and	and	CCONJ
ajst-28813	270	9	casadi	casadi	VERB
ajst-28813	270	10	open	open	ADJ
ajst-28813	270	11	-	-	PUNCT
ajst-28813	270	12	source	source	NOUN
ajst-28813	270	13	libraries	library	NOUN
ajst-28813	270	14	in	in	ADP
ajst-28813	270	15	the	the	DET
ajst-28813	270	16	pycharm	pycharm	PROPN
ajst-28813	270	17	development	development	NOUN
ajst-28813	270	18	environment	environment	NOUN
ajst-28813	270	19	.	.	PUNCT
ajst-28813	271	1	one	one	NUM
ajst-28813	271	2	of	of	ADP
ajst-28813	271	3	the	the	DET
ajst-28813	271	4	control	control	NOUN
ajst-28813	271	5	system	system	NOUN
ajst-28813	271	6	design	design	NOUN
ajst-28813	271	7	objectives	objective	NOUN
ajst-28813	271	8	of	of	ADP
ajst-28813	271	9	the	the	DET
ajst-28813	271	10	esn	esn	PROPN
ajst-28813	271	11	network	network	NOUN
ajst-28813	271	12	is	be	AUX
ajst-28813	271	13	to	to	PART
ajst-28813	271	14	enable	enable	VERB
ajst-28813	271	15	the	the	DET
ajst-28813	271	16	system	system	NOUN
ajst-28813	271	17	to	to	PART
ajst-28813	271	18	reach	reach	VERB
ajst-28813	271	19	a	a	DET
ajst-28813	271	20	specific	specific	ADJ
ajst-28813	271	21	reference	reference	NOUN
ajst-28813	271	22	value	value	NOUN
ajst-28813	271	23	after	after	ADP
ajst-28813	271	24	multiple	multiple	ADJ
ajst-28813	271	25	training	training	NOUN
ajst-28813	271	26	,	,	PUNCT
ajst-28813	271	27	and	and	CCONJ
ajst-28813	271	28	to	to	PART
ajst-28813	271	29	be	be	AUX
ajst-28813	271	30	stably	stably	ADV
ajst-28813	271	31	maintained	maintain	VERB
ajst-28813	271	32	at	at	ADP
ajst-28813	271	33	this	this	DET
ajst-28813	271	34	reference	reference	NOUN
ajst-28813	271	35	value	value	NOUN
ajst-28813	271	36	.	.	PUNCT
ajst-28813	272	1	however	however	ADV
ajst-28813	272	2	,	,	PUNCT
ajst-28813	272	3	in	in	ADP
ajst-28813	272	4	practice	practice	NOUN
ajst-28813	272	5	,	,	PUNCT
ajst-28813	272	6	there	there	PRON
ajst-28813	272	7	is	be	VERB
ajst-28813	272	8	an	an	DET
ajst-28813	272	9	unavoidable	unavoidable	ADJ
ajst-28813	272	10	problem	problem	NOUN
ajst-28813	272	11	:	:	PUNCT
ajst-28813	272	12	when	when	SCONJ
ajst-28813	272	13	the	the	DET
ajst-28813	272	14	system	system	NOUN
ajst-28813	272	15	reaches	reach	VERB
ajst-28813	272	16	a	a	DET
ajst-28813	272	17	steady	steady	ADJ
ajst-28813	272	18	state	state	NOUN
ajst-28813	272	19	,	,	PUNCT
ajst-28813	272	20	there	there	PRON
ajst-28813	272	21	will	will	AUX
ajst-28813	272	22	be	be	AUX
ajst-28813	272	23	a	a	DET
ajst-28813	272	24	certain	certain	ADJ
ajst-28813	272	25	deviation	deviation	NOUN
ajst-28813	272	26	between	between	ADP
ajst-28813	272	27	the	the	DET
ajst-28813	272	28	predicted	predict	VERB
ajst-28813	272	29	value	value	NOUN
ajst-28813	272	30	of	of	ADP
ajst-28813	272	31	the	the	DET
ajst-28813	272	32	esn	esn	PROPN
ajst-28813	272	33	network	network	NOUN
ajst-28813	272	34	and	and	CCONJ
ajst-28813	272	35	the	the	DET
ajst-28813	272	36	device	device	NOUN
ajst-28813	272	37	itself	itself	PRON
ajst-28813	272	38	.	.	PUNCT
ajst-28813	273	1	this	this	DET
ajst-28813	273	2	situation	situation	NOUN
ajst-28813	273	3	typically	typically	ADV
ajst-28813	273	4	occurs	occur	VERB
ajst-28813	273	5	when	when	SCONJ
ajst-28813	273	6	the	the	DET
ajst-28813	273	7	input	input	NOUN
ajst-28813	273	8	in	in	ADP
ajst-28813	273	9	the	the	DET
ajst-28813	273	10	training	training	NOUN
ajst-28813	273	11	set	set	NOUN
ajst-28813	273	12	changes	change	NOUN
ajst-28813	273	13	too	too	ADV
ajst-28813	273	14	frequently	frequently	ADV
ajst-28813	273	15	.	.	PUNCT
ajst-28813	274	1	to	to	PART
ajst-28813	274	2	make	make	VERB
ajst-28813	274	3	the	the	DET
ajst-28813	274	4	esn	esn	PROPN
ajst-28813	274	5	network	network	PROPN
ajst-28813	274	6	better	well	ADV
ajst-28813	274	7	adaptable	adaptable	ADJ
ajst-28813	274	8	,	,	PUNCT
ajst-28813	274	9	the	the	DET
ajst-28813	274	10	datasets	dataset	NOUN
ajst-28813	274	11	are	be	AUX
ajst-28813	274	12	created	create	VERB
ajst-28813	274	13	according	accord	VERB
ajst-28813	274	14	to	to	ADP
ajst-28813	274	15	the	the	DET
ajst-28813	274	16	different	different	ADJ
ajst-28813	274	17	dynamic	dynamic	ADJ
ajst-28813	274	18	properties	property	NOUN
ajst-28813	274	19	of	of	ADP
ajst-28813	274	20	the	the	DET
ajst-28813	274	21	input	input	NOUN
ajst-28813	274	22	signals	signal	NOUN
ajst-28813	274	23	,	,	PUNCT
ajst-28813	274	24	and	and	CCONJ
ajst-28813	274	25	the	the	DET
ajst-28813	274	26	stochastic	stochastic	ADJ
ajst-28813	274	27	input	input	NOUN
ajst-28813	274	28	signal	signal	NOUN
ajst-28813	274	29	equations	equation	NOUN
ajst-28813	274	30	are	be	AUX
ajst-28813	274	31	shown	show	VERB
ajst-28813	274	32	in	in	ADP
ajst-28813	274	33	equations	equation	NOUN
ajst-28813	274	34	3	3	NUM
ajst-28813	274	35	-	-	SYM
ajst-28813	274	36	1	1	NUM
ajst-28813	274	37	.	.	PUNCT
ajst-28813	275	1	in	in	ADP
ajst-28813	275	2	this	this	DET
ajst-28813	275	3	way	way	NOUN
ajst-28813	275	4	,	,	PUNCT
ajst-28813	275	5	the	the	DET
ajst-28813	275	6	esn	esn	PROPN
ajst-28813	275	7	network	network	NOUN
ajst-28813	275	8	can	can	AUX
ajst-28813	275	9	learn	learn	VERB
ajst-28813	275	10	both	both	PRON
ajst-28813	275	11	fast	fast	ADJ
ajst-28813	275	12	and	and	CCONJ
ajst-28813	275	13	slow	slow	ADJ
ajst-28813	275	14	dynamics	dynamic	NOUN
ajst-28813	275	15	,	,	PUNCT
ajst-28813	275	16	thus	thus	ADV
ajst-28813	275	17	achieving	achieve	VERB
ajst-28813	275	18	a	a	DET
ajst-28813	275	19	low	low	ADJ
ajst-28813	275	20	error	error	NOUN
ajst-28813	275	21	steady	steady	ADJ
ajst-28813	275	22	state	state	NOUN
ajst-28813	275	23	relative	relative	ADJ
ajst-28813	275	24	to	to	ADP
ajst-28813	275	25	the	the	DET
ajst-28813	275	26	target	target	NOUN
ajst-28813	275	27	object	object	NOUN
ajst-28813	275	28	and	and	CCONJ
ajst-28813	275	29	effectively	effectively	ADV
ajst-28813	275	30	tracking	track	VERB
ajst-28813	275	31	rapidly	rapidly	ADV
ajst-28813	275	32	changing	change	VERB
ajst-28813	275	33	signals	signal	NOUN
ajst-28813	275	34	.	.	PUNCT
ajst-28813	276	1	in	in	ADP
ajst-28813	276	2	further	far	ADV
ajst-28813	276	3	improving	improve	VERB
ajst-28813	276	4	the	the	DET
ajst-28813	276	5	generalization	generalization	NOUN
ajst-28813	276	6	ability	ability	NOUN
ajst-28813	276	7	and	and	CCONJ
ajst-28813	276	8	accuracy	accuracy	NOUN
ajst-28813	276	9	of	of	ADP
ajst-28813	276	10	the	the	DET
ajst-28813	276	11	esn	esn	PROPN
ajst-28813	276	12	network	network	NOUN
ajst-28813	276	13	models	model	NOUN
ajst-28813	276	14	,	,	PUNCT
ajst-28813	276	15	each	each	DET
ajst-28813	276	16	dataset	dataset	NOUN
ajst-28813	276	17	contains	contain	VERB
ajst-28813	276	18	a	a	DET
ajst-28813	276	19	larger	large	ADJ
ajst-28813	276	20	training	training	NOUN
ajst-28813	276	21	set	set	NOUN
ajst-28813	276	22	and	and	CCONJ
ajst-28813	276	23	a	a	DET
ajst-28813	276	24	smaller	small	ADJ
ajst-28813	276	25	validation	validation	NOUN
ajst-28813	276	26	set	set	NOUN
ajst-28813	276	27	.	.	PUNCT
ajst-28813	277	1	ensure	ensure	VERB
ajst-28813	277	2	that	that	SCONJ
ajst-28813	277	3	the	the	DET
ajst-28813	277	4	model	model	NOUN
ajst-28813	277	5	can	can	AUX
ajst-28813	277	6	fully	fully	ADV
ajst-28813	277	7	learn	learn	VERB
ajst-28813	277	8	the	the	DET
ajst-28813	277	9	characteristics	characteristic	NOUN
ajst-28813	277	10	of	of	ADP
ajst-28813	277	11	the	the	DET
ajst-28813	277	12	data	datum	NOUN
ajst-28813	277	13	during	during	ADP
ajst-28813	277	14	the	the	DET
ajst-28813	277	15	training	training	NOUN
ajst-28813	277	16	process	process	NOUN
ajst-28813	277	17	,	,	PUNCT
ajst-28813	277	18	and	and	CCONJ
ajst-28813	277	19	can	can	AUX
ajst-28813	277	20	verify	verify	VERB
ajst-28813	277	21	the	the	DET
ajst-28813	277	22	performance	performance	NOUN
ajst-28813	277	23	of	of	ADP
ajst-28813	277	24	the	the	DET
ajst-28813	277	25	model	model	NOUN
ajst-28813	277	26	during	during	ADP
ajst-28813	277	27	the	the	DET
ajst-28813	277	28	test	test	NOUN
ajst-28813	277	29	stage	stage	NOUN
ajst-28813	277	30	.	.	PUNCT
ajst-28813	278	1			PROPN
ajst-28813	278	2	min	min	PROPN
ajst-28813	278	3	max	max	PROPN
ajst-28813	278	4	mintx	mintx	VERB
ajst-28813	279	1	x	x	X
ajst-28813	279	2	x	x	PROPN
ajst-28813	279	3	x	x	PROPN
ajst-28813	279	4			PUNCT
ajst-28813	279	5			PROPN
ajst-28813	279	6			NOUN
ajst-28813	279	7	(	(	PUNCT
ajst-28813	279	8	3	3	NUM
ajst-28813	279	9	-	-	SYM
ajst-28813	279	10	1	1	NUM
ajst-28813	279	11	)	)	PUNCT
ajst-28813	279	12	where	where	SCONJ
ajst-28813	279	13	,	,	PUNCT
ajst-28813	279	14	minx	minx	NOUN
ajst-28813	279	15	,	,	PUNCT
ajst-28813	279	16	maxx	maxx	PROPN
ajst-28813	279	17	is	be	AUX
ajst-28813	279	18	the	the	DET
ajst-28813	279	19	minimum	minimum	ADJ
ajst-28813	279	20	and	and	CCONJ
ajst-28813	279	21	maximum	maximum	ADJ
ajst-28813	279	22	values	value	NOUN
ajst-28813	279	23	of	of	ADP
ajst-28813	279	24	the	the	DET
ajst-28813	279	25	control	control	NOUN
ajst-28813	279	26	input	input	NOUN
ajst-28813	279	27	respectively	respectively	ADV
ajst-28813	279	28	;	;	PUNCT
ajst-28813	279	29			NOUN
ajst-28813	279	30	is	be	AUX
ajst-28813	279	31	the	the	DET
ajst-28813	279	32	random	random	ADJ
ajst-28813	279	33	number	number	NOUN
ajst-28813	279	34	generated	generate	VERB
ajst-28813	279	35	through	through	ADP
ajst-28813	279	36	the	the	DET
ajst-28813	279	37	numpy	numpy	NOUN
ajst-28813	279	38	library	library	NOUN
ajst-28813	279	39	;	;	PUNCT
ajst-28813	279	40	tx	tx	PROPN
ajst-28813	279	41	is	be	AUX
ajst-28813	279	42	the	the	DET
ajst-28813	279	43	next	next	ADJ
ajst-28813	279	44	input	input	NOUN
ajst-28813	279	45	.	.	PUNCT
ajst-28813	280	1	the	the	DET
ajst-28813	280	2	initial	initial	ADJ
ajst-28813	280	3	values	value	NOUN
ajst-28813	280	4	that	that	PRON
ajst-28813	280	5	can	can	AUX
ajst-28813	280	6	be	be	AUX
ajst-28813	280	7	set	set	VERB
ajst-28813	280	8	according	accord	VERB
ajst-28813	280	9	to	to	ADP
ajst-28813	280	10	the	the	DET
ajst-28813	280	11	actual	actual	ADJ
ajst-28813	280	12	situation	situation	NOUN
ajst-28813	280	13	of	of	ADP
ajst-28813	280	14	the	the	DET
ajst-28813	280	15	electric	electric	ADJ
ajst-28813	280	16	submersible	submersible	ADJ
ajst-28813	280	17	pump	pump	NOUN
ajst-28813	280	18	well	well	ADV
ajst-28813	280	19	are	be	AUX
ajst-28813	280	20	shown	show	VERB
ajst-28813	280	21	in	in	ADP
ajst-28813	280	22	table	table	NOUN
ajst-28813	280	23	3	3	NUM
ajst-28813	280	24	-	-	SYM
ajst-28813	280	25	1	1	NUM
ajst-28813	280	26	.	.	PUNCT
ajst-28813	281	1	the	the	DET
ajst-28813	281	2	random	random	ADJ
ajst-28813	281	3	sequence	sequence	NOUN
ajst-28813	281	4	can	can	AUX
ajst-28813	281	5	adjust	adjust	VERB
ajst-28813	281	6	the	the	DET
ajst-28813	281	7	amount	amount	NOUN
ajst-28813	281	8	of	of	ADP
ajst-28813	281	9	change	change	NOUN
ajst-28813	281	10	according	accord	VERB
ajst-28813	281	11	to	to	ADP
ajst-28813	281	12	different	different	ADJ
ajst-28813	281	13	nodes	node	NOUN
ajst-28813	281	14	,	,	PUNCT
ajst-28813	281	15	that	that	ADV
ajst-28813	281	16	is	is	ADV
ajst-28813	281	17	,	,	PUNCT
ajst-28813	281	18	the	the	DET
ajst-28813	281	19	value	value	NOUN
ajst-28813	281	20	of	of	ADP
ajst-28813	281	21	each	each	DET
ajst-28813	281	22	input	input	NOUN
ajst-28813	281	23	is	be	AUX
ajst-28813	281	24	not	not	PART
ajst-28813	281	25	fixed	fix	VERB
ajst-28813	281	26	,	,	PUNCT
ajst-28813	281	27	but	but	CCONJ
ajst-28813	281	28	it	it	PRON
ajst-28813	281	29	can	can	AUX
ajst-28813	281	30	be	be	AUX
ajst-28813	281	31	changed	change	VERB
ajst-28813	281	32	according	accord	VERB
ajst-28813	281	33	to	to	ADP
ajst-28813	281	34	the	the	DET
ajst-28813	281	35	initial	initial	ADJ
ajst-28813	281	36	value	value	NOUN
ajst-28813	281	37	,	,	PUNCT
ajst-28813	281	38	so	so	SCONJ
ajst-28813	281	39	as	as	SCONJ
ajst-28813	281	40	to	to	PART
ajst-28813	281	41	be	be	AUX
ajst-28813	281	42	closer	close	ADJ
ajst-28813	281	43	to	to	ADP
ajst-28813	281	44	the	the	DET
ajst-28813	281	45	actual	actual	ADJ
ajst-28813	281	46	working	work	VERB
ajst-28813	281	47	environment	environment	NOUN
ajst-28813	281	48	in	in	ADP
ajst-28813	281	49	the	the	DET
ajst-28813	281	50	training	training	NOUN
ajst-28813	281	51	process	process	NOUN
ajst-28813	281	52	.	.	PUNCT
ajst-28813	282	1	table	table	NOUN
ajst-28813	282	2	3	3	NUM
ajst-28813	282	3	-	-	SYM
ajst-28813	282	4	1	1	NUM
ajst-28813	282	5	.	.	PUNCT
ajst-28813	282	6	initial	initial	ADJ
ajst-28813	282	7	quantities	quantity	NOUN
ajst-28813	282	8	of	of	ADP
ajst-28813	282	9	the	the	DET
ajst-28813	282	10	training	training	NOUN
ajst-28813	282	11	data	datum	NOUN
ajst-28813	282	12	input	input	NOUN
ajst-28813	282	13	data	datum	NOUN
ajst-28813	282	14	initial	initial	ADJ
ajst-28813	282	15	quantity	quantity	NOUN
ajst-28813	282	16	0whp	0whp	PROPN
ajst-28813	282	17	/mpa	/mpa	PUNCT
ajst-28813	282	18	7.4	7.4	NUM
ajst-28813	282	19	0bhp	0bhp	NOUN
ajst-28813	282	20	/mpa	/mpa	PUNCT
ajst-28813	283	1	3.0	3.0	NUM
ajst-28813	283	2	q	q	NOUN
ajst-28813	283	3	/(m³/h	/(m³/h	PROPN
ajst-28813	283	4	)	)	PUNCT
ajst-28813	283	5	30	30	NUM
ajst-28813	283	6	the	the	DET
ajst-28813	283	7	change	change	NOUN
ajst-28813	283	8	frequency	frequency	NOUN
ajst-28813	283	9	control	control	NOUN
ajst-28813	283	10	of	of	ADP
ajst-28813	283	11	the	the	DET
ajst-28813	283	12	values	value	NOUN
ajst-28813	283	13	of	of	ADP
ajst-28813	283	14	the	the	DET
ajst-28813	283	15	training	training	NOUN
ajst-28813	283	16	dataset	dataset	NOUN
ajst-28813	283	17	is	be	AUX
ajst-28813	283	18	shown	show	VERB
ajst-28813	283	19	in	in	ADP
ajst-28813	283	20	table	table	NOUN
ajst-28813	283	21	3	3	NUM
ajst-28813	283	22	-	-	SYM
ajst-28813	283	23	2	2	NUM
ajst-28813	283	24	,	,	PUNCT
ajst-28813	283	25	which	which	PRON
ajst-28813	283	26	can	can	AUX
ajst-28813	283	27	intuitively	intuitively	ADV
ajst-28813	283	28	adjust	adjust	VERB
ajst-28813	283	29	the	the	DET
ajst-28813	283	30	change	change	NOUN
ajst-28813	283	31	pattern	pattern	NOUN
ajst-28813	283	32	of	of	ADP
ajst-28813	283	33	the	the	DET
ajst-28813	283	34	training	training	NOUN
ajst-28813	283	35	data	datum	NOUN
ajst-28813	283	36	.	.	PUNCT
ajst-28813	284	1	table	table	NOUN
ajst-28813	284	2	3	3	NUM
ajst-28813	284	3	-	-	SYM
ajst-28813	284	4	2	2	NUM
ajst-28813	284	5	.	.	PUNCT
ajst-28813	284	6	initial	initial	ADJ
ajst-28813	284	7	quantities	quantity	NOUN
ajst-28813	284	8	of	of	ADP
ajst-28813	284	9	the	the	DET
ajst-28813	284	10	training	training	NOUN
ajst-28813	284	11	data	datum	NOUN
ajst-28813	284	12	the	the	DET
ajst-28813	284	13	ttle	ttle	ADJ
ajst-28813	284	14	valve	valve	NOUN
ajst-28813	284	15	control	control	NOUN
ajst-28813	285	1	z	z	PROPN
ajst-28813	285	2	/%	/%	PUNCT
ajst-28813	285	3	current	current	ADJ
ajst-28813	285	4	frequency	frequency	NOUN
ajst-28813	285	5	control	control	NOUN
ajst-28813	285	6	f	f	PROPN
ajst-28813	285	7	/hz	/hz	NOUN
ajst-28813	285	8	minx	minx	VERB
ajst-28813	285	9	0.1	0.1	NUM
ajst-28813	285	10	40	40	NUM
ajst-28813	285	11	maxx	maxx	PROPN
ajst-28813	285	12	1	1	NUM
ajst-28813	285	13	60	60	NUM
ajst-28813	285	14	the	the	DET
ajst-28813	285	15	generation	generation	NOUN
ajst-28813	285	16	effect	effect	NOUN
ajst-28813	285	17	of	of	ADP
ajst-28813	285	18	the	the	DET
ajst-28813	285	19	training	training	NOUN
ajst-28813	285	20	data	datum	NOUN
ajst-28813	285	21	set	set	VERB
ajst-28813	285	22	after	after	ADP
ajst-28813	285	23	creation	creation	NOUN
ajst-28813	285	24	is	be	AUX
ajst-28813	285	25	shown	show	VERB
ajst-28813	285	26	in	in	ADP
ajst-28813	285	27	figure	figure	NOUN
ajst-28813	285	28	3	3	NUM
ajst-28813	285	29	-	-	SYM
ajst-28813	285	30	1	1	NUM
ajst-28813	285	31	and	and	CCONJ
ajst-28813	285	32	3	3	NUM
ajst-28813	285	33	-	-	SYM
ajst-28813	285	34	2	2	NUM
ajst-28813	285	35	.	.	PUNCT
ajst-28813	286	1	the	the	DET
ajst-28813	286	2	training	training	NOUN
ajst-28813	286	3	data	datum	NOUN
ajst-28813	286	4	set	set	VERB
ajst-28813	286	5	in	in	ADP
ajst-28813	286	6	the	the	DET
ajst-28813	286	7	figure	figure	NOUN
ajst-28813	286	8	below	below	ADV
ajst-28813	286	9	contains	contain	VERB
ajst-28813	286	10	1200	1200	NUM
ajst-28813	286	11	data	datum	NOUN
ajst-28813	286	12	,	,	PUNCT
ajst-28813	286	13	and	and	CCONJ
ajst-28813	286	14	each	each	DET
ajst-28813	286	15	data	datum	NOUN
ajst-28813	286	16	can	can	AUX
ajst-28813	286	17	make	make	VERB
ajst-28813	286	18	the	the	DET
ajst-28813	286	19	system	system	NOUN
ajst-28813	286	20	reach	reach	VERB
ajst-28813	286	21	the	the	DET
ajst-28813	286	22	steady	steady	ADJ
ajst-28813	286	23	state	state	NOUN
ajst-28813	286	24	.	.	PUNCT
ajst-28813	287	1	figure	figure	VERB
ajst-28813	287	2	3	3	NUM
ajst-28813	287	3	-	-	SYM
ajst-28813	287	4	1	1	NUM
ajst-28813	287	5	shows	show	VERB
ajst-28813	287	6	that	that	SCONJ
ajst-28813	287	7	the	the	DET
ajst-28813	287	8	training	training	NOUN
ajst-28813	287	9	dataset	dataset	NOUN
ajst-28813	287	10	has	have	VERB
ajst-28813	287	11	a	a	DET
ajst-28813	287	12	faster	fast	ADJ
ajst-28813	287	13	change	change	NOUN
ajst-28813	287	14	frequency	frequency	NOUN
ajst-28813	287	15	for	for	ADP
ajst-28813	287	16	every	every	DET
ajst-28813	287	17	20	20	NUM
ajst-28813	287	18	data	data	NOUN
ajst-28813	287	19	samples	sample	NOUN
ajst-28813	287	20	;	;	PUNCT
ajst-28813	287	21	figure	figure	VERB
ajst-28813	287	22	3	3	NUM
ajst-28813	287	23	-	-	SYM
ajst-28813	287	24	2	2	NUM
ajst-28813	287	25	shows	show	VERB
ajst-28813	287	26	that	that	SCONJ
ajst-28813	287	27	the	the	DET
ajst-28813	287	28	training	training	NOUN
ajst-28813	287	29	dataset	dataset	NOUN
ajst-28813	287	30	has	have	VERB
ajst-28813	287	31	a	a	DET
ajst-28813	287	32	slower	slow	ADJ
ajst-28813	287	33	change	change	NOUN
ajst-28813	287	34	frequency	frequency	NOUN
ajst-28813	287	35	for	for	ADP
ajst-28813	287	36	every	every	DET
ajst-28813	287	37	50	50	NUM
ajst-28813	287	38	data	data	NOUN
ajst-28813	287	39	samples	sample	NOUN
ajst-28813	287	40	.	.	PUNCT
ajst-28813	288	1	figure	figure	VERB
ajst-28813	288	2	3	3	NUM
ajst-28813	288	3	-	-	SYM
ajst-28813	288	4	1	1	NUM
ajst-28813	288	5	.	.	PUNCT
ajst-28813	289	1	dataset	dataset	NOUN
ajst-28813	289	2	plots	plot	NOUN
ajst-28813	289	3	of	of	ADP
ajst-28813	289	4	the	the	DET
ajst-28813	289	5	faster	fast	ADJ
ajst-28813	289	6	change	change	NOUN
ajst-28813	289	7	frequencies	frequency	NOUN
ajst-28813	289	8	255	255	NUM
ajst-28813	289	9	figure	figure	NOUN
ajst-28813	289	10	3	3	NUM
ajst-28813	289	11	-	-	SYM
ajst-28813	289	12	2	2	NUM
ajst-28813	289	13	.	.	PUNCT
ajst-28813	289	14	dataset	dataset	NOUN
ajst-28813	289	15	plots	plot	NOUN
ajst-28813	289	16	of	of	ADP
ajst-28813	289	17	the	the	DET
ajst-28813	289	18	slower	slow	ADJ
ajst-28813	289	19	change	change	NOUN
ajst-28813	289	20	frequency	frequency	NOUN
ajst-28813	289	21	to	to	PART
ajst-28813	289	22	verify	verify	VERB
ajst-28813	289	23	the	the	DET
ajst-28813	289	24	rapid	rapid	ADJ
ajst-28813	289	25	response	response	NOUN
ajst-28813	289	26	capability	capability	NOUN
ajst-28813	289	27	of	of	ADP
ajst-28813	289	28	the	the	DET
ajst-28813	289	29	esn	esn	PROPN
ajst-28813	289	30	network	network	NOUN
ajst-28813	289	31	,	,	PUNCT
ajst-28813	289	32	data	datum	NOUN
ajst-28813	289	33	samples	sample	NOUN
ajst-28813	289	34	containing	contain	VERB
ajst-28813	289	35	different	different	ADJ
ajst-28813	289	36	change	change	NOUN
ajst-28813	289	37	frequencies	frequency	NOUN
ajst-28813	289	38	were	be	AUX
ajst-28813	289	39	designed	design	VERB
ajst-28813	289	40	when	when	SCONJ
ajst-28813	289	41	generating	generate	VERB
ajst-28813	289	42	the	the	DET
ajst-28813	289	43	training	training	NOUN
ajst-28813	289	44	dataset	dataset	NOUN
ajst-28813	289	45	.	.	PUNCT
ajst-28813	290	1	half	half	NOUN
ajst-28813	290	2	of	of	ADP
ajst-28813	290	3	the	the	DET
ajst-28813	290	4	data	data	NOUN
ajst-28813	290	5	samples	sample	NOUN
ajst-28813	290	6	in	in	ADP
ajst-28813	290	7	this	this	DET
ajst-28813	290	8	dataset	dataset	NOUN
ajst-28813	290	9	change	change	NOUN
ajst-28813	290	10	once	once	ADV
ajst-28813	290	11	for	for	ADP
ajst-28813	290	12	every	every	DET
ajst-28813	290	13	20	20	NUM
ajst-28813	290	14	data	datum	NOUN
ajst-28813	290	15	samples	sample	NOUN
ajst-28813	290	16	,	,	PUNCT
ajst-28813	290	17	and	and	CCONJ
ajst-28813	290	18	the	the	DET
ajst-28813	290	19	other	other	ADJ
ajst-28813	290	20	half	half	NOUN
ajst-28813	290	21	change	change	NOUN
ajst-28813	290	22	once	once	ADV
ajst-28813	290	23	for	for	ADP
ajst-28813	290	24	every	every	DET
ajst-28813	290	25	50	50	NUM
ajst-28813	290	26	data	data	NOUN
ajst-28813	290	27	samples	sample	NOUN
ajst-28813	290	28	.	.	PUNCT
ajst-28813	291	1	this	this	DET
ajst-28813	291	2	design	design	NOUN
ajst-28813	291	3	aims	aim	VERB
ajst-28813	291	4	to	to	PART
ajst-28813	291	5	simulate	simulate	VERB
ajst-28813	291	6	data	datum	NOUN
ajst-28813	291	7	variation	variation	NOUN
ajst-28813	291	8	at	at	ADP
ajst-28813	291	9	different	different	ADJ
ajst-28813	291	10	speeds	speed	NOUN
ajst-28813	291	11	in	in	ADP
ajst-28813	291	12	order	order	NOUN
ajst-28813	291	13	to	to	PART
ajst-28813	291	14	more	more	ADV
ajst-28813	291	15	comprehensively	comprehensively	ADV
ajst-28813	291	16	evaluate	evaluate	VERB
ajst-28813	291	17	the	the	DET
ajst-28813	291	18	performance	performance	NOUN
ajst-28813	291	19	of	of	ADP
ajst-28813	291	20	the	the	DET
ajst-28813	291	21	esn	esn	PROPN
ajst-28813	291	22	network	network	NOUN
ajst-28813	291	23	.	.	PUNCT
ajst-28813	292	1	as	as	SCONJ
ajst-28813	292	2	can	can	AUX
ajst-28813	292	3	be	be	AUX
ajst-28813	292	4	seen	see	VERB
ajst-28813	292	5	in	in	ADP
ajst-28813	292	6	figures	figure	NOUN
ajst-28813	292	7	3	3	NUM
ajst-28813	292	8	-	-	SYM
ajst-28813	292	9	3	3	NUM
ajst-28813	292	10	,	,	PUNCT
ajst-28813	292	11	the	the	DET
ajst-28813	292	12	esn	esn	PROPN
ajst-28813	292	13	network	network	NOUN
ajst-28813	292	14	still	still	ADV
ajst-28813	292	15	has	have	VERB
ajst-28813	292	16	the	the	DET
ajst-28813	292	17	ability	ability	NOUN
ajst-28813	292	18	to	to	PART
ajst-28813	292	19	respond	respond	VERB
ajst-28813	292	20	quickly	quickly	ADV
ajst-28813	292	21	when	when	SCONJ
ajst-28813	292	22	receiving	receive	VERB
ajst-28813	292	23	faster	fast	ADV
ajst-28813	292	24	or	or	CCONJ
ajst-28813	292	25	slower	slow	ADJ
ajst-28813	292	26	changes	change	NOUN
ajst-28813	292	27	in	in	ADP
ajst-28813	292	28	the	the	DET
ajst-28813	292	29	data	datum	NOUN
ajst-28813	292	30	.	.	PUNCT
ajst-28813	293	1	figure	figure	VERB
ajst-28813	293	2	3	3	NUM
ajst-28813	293	3	-	-	SYM
ajst-28813	293	4	3	3	NUM
ajst-28813	293	5	.	.	PUNCT
ajst-28813	294	1	data	datum	NOUN
ajst-28813	294	2	figures	figure	NOUN
ajst-28813	294	3	combining	combine	VERB
ajst-28813	294	4	changes	change	NOUN
ajst-28813	294	5	in	in	ADP
ajst-28813	294	6	speed	speed	NOUN
ajst-28813	294	7	and	and	CCONJ
ajst-28813	294	8	speed	speed	NOUN
ajst-28813	294	9	4.2	4.2	NUM
ajst-28813	294	10	.	.	PUNCT
ajst-28813	295	1	contrast	contrast	VERB
ajst-28813	295	2	validation	validation	NOUN
ajst-28813	295	3	with	with	ADP
ajst-28813	295	4	other	other	ADJ
ajst-28813	295	5	neural	neural	ADJ
ajst-28813	295	6	network	network	NOUN
ajst-28813	295	7	methods	method	NOUN
ajst-28813	295	8	in	in	ADP
ajst-28813	295	9	order	order	NOUN
ajst-28813	295	10	to	to	PART
ajst-28813	295	11	ensure	ensure	VERB
ajst-28813	295	12	that	that	SCONJ
ajst-28813	295	13	the	the	DET
ajst-28813	295	14	esn	esn	PROPN
ajst-28813	295	15	network	network	NOUN
ajst-28813	295	16	model	model	NOUN
ajst-28813	295	17	can	can	AUX
ajst-28813	295	18	provide	provide	VERB
ajst-28813	295	19	real	real	ADJ
ajst-28813	295	20	and	and	CCONJ
ajst-28813	295	21	reliable	reliable	ADJ
ajst-28813	295	22	prediction	prediction	NOUN
ajst-28813	295	23	results	result	NOUN
ajst-28813	295	24	in	in	ADP
ajst-28813	295	25	the	the	DET
ajst-28813	295	26	prediction	prediction	NOUN
ajst-28813	295	27	task	task	NOUN
ajst-28813	295	28	,	,	PUNCT
ajst-28813	295	29	the	the	DET
ajst-28813	295	30	long	long	ADJ
ajst-28813	295	31	and	and	CCONJ
ajst-28813	295	32	short	short	ADJ
ajst-28813	295	33	memory	memory	NOUN
ajst-28813	295	34	network	network	NOUN
ajst-28813	295	35	model	model	NOUN
ajst-28813	295	36	(	(	PUNCT
ajst-28813	295	37	lstm	lstm	NOUN
ajst-28813	295	38	)	)	PUNCT
ajst-28813	295	39	and	and	CCONJ
ajst-28813	295	40	48	48	NUM
ajst-28813	295	41	gated	gate	VERB
ajst-28813	295	42	cycle	cycle	NOUN
ajst-28813	295	43	unit	unit	NOUN
ajst-28813	295	44	(	(	PUNCT
ajst-28813	295	45	gru	gru	NOUN
ajst-28813	295	46	)	)	PUNCT
ajst-28813	295	47	network	network	NOUN
ajst-28813	295	48	model	model	NOUN
ajst-28813	295	49	are	be	AUX
ajst-28813	295	50	written	write	VERB
ajst-28813	295	51	and	and	CCONJ
ajst-28813	295	52	verified	verify	VERB
ajst-28813	295	53	.	.	PUNCT
ajst-28813	296	1	in	in	ADP
ajst-28813	296	2	this	this	DET
ajst-28813	296	3	way	way	NOUN
ajst-28813	296	4	,	,	PUNCT
ajst-28813	296	5	we	we	PRON
ajst-28813	296	6	can	can	AUX
ajst-28813	296	7	evaluate	evaluate	VERB
ajst-28813	296	8	whether	whether	SCONJ
ajst-28813	296	9	the	the	DET
ajst-28813	296	10	prediction	prediction	NOUN
ajst-28813	296	11	performance	performance	NOUN
ajst-28813	296	12	of	of	ADP
ajst-28813	296	13	esn	esn	PROPN
ajst-28813	296	14	model	model	NOUN
ajst-28813	296	15	can	can	AUX
ajst-28813	296	16	be	be	AUX
ajst-28813	296	17	better	well	ADJ
ajst-28813	296	18	than	than	ADP
ajst-28813	296	19	other	other	ADJ
ajst-28813	296	20	recurrent	recurrent	ADJ
ajst-28813	296	21	neural	neural	ADJ
ajst-28813	296	22	network	network	NOUN
ajst-28813	296	23	models	model	NOUN
ajst-28813	296	24	.	.	PUNCT
ajst-28813	297	1	these	these	DET
ajst-28813	297	2	comparison	comparison	NOUN
ajst-28813	297	3	results	result	NOUN
ajst-28813	297	4	provide	provide	VERB
ajst-28813	297	5	strong	strong	ADJ
ajst-28813	297	6	256	256	NUM
ajst-28813	297	7	support	support	NOUN
ajst-28813	297	8	for	for	ADP
ajst-28813	297	9	the	the	DET
ajst-28813	297	10	application	application	NOUN
ajst-28813	297	11	of	of	ADP
ajst-28813	297	12	esn	esn	PROPN
ajst-28813	297	13	network	network	PROPN
ajst-28813	297	14	in	in	ADP
ajst-28813	297	15	electric	electric	ADJ
ajst-28813	297	16	submersible	submersible	ADJ
ajst-28813	297	17	pump	pump	NOUN
ajst-28813	297	18	model	model	NOUN
ajst-28813	297	19	prediction	prediction	NOUN
ajst-28813	297	20	control	control	NOUN
ajst-28813	297	21	,	,	PUNCT
ajst-28813	297	22	ensure	ensure	VERB
ajst-28813	297	23	the	the	DET
ajst-28813	297	24	authenticity	authenticity	NOUN
ajst-28813	297	25	and	and	CCONJ
ajst-28813	297	26	credibility	credibility	NOUN
ajst-28813	297	27	of	of	ADP
ajst-28813	297	28	the	the	DET
ajst-28813	297	29	prediction	prediction	NOUN
ajst-28813	297	30	results	result	NOUN
ajst-28813	297	31	,	,	PUNCT
ajst-28813	297	32	and	and	CCONJ
ajst-28813	297	33	lay	lie	VERB
ajst-28813	297	34	a	a	DET
ajst-28813	297	35	foundation	foundation	NOUN
ajst-28813	297	36	for	for	ADP
ajst-28813	297	37	the	the	DET
ajst-28813	297	38	future	future	ADJ
ajst-28813	297	39	application	application	NOUN
ajst-28813	297	40	in	in	ADP
ajst-28813	297	41	other	other	ADJ
ajst-28813	297	42	industrial	industrial	ADJ
ajst-28813	297	43	process	process	NOUN
ajst-28813	297	44	control	control	NOUN
ajst-28813	297	45	.	.	PUNCT
ajst-28813	298	1	long	long	ADJ
ajst-28813	298	2	short	short	ADJ
ajst-28813	298	3	memory	memory	NOUN
ajst-28813	298	4	network	network	NOUN
ajst-28813	298	5	model	model	NOUN
ajst-28813	298	6	(	(	PUNCT
ajst-28813	298	7	lstm	lstm	NOUN
ajst-28813	298	8	)	)	PUNCT
ajst-28813	298	9	is	be	AUX
ajst-28813	298	10	a	a	DET
ajst-28813	298	11	special	special	ADJ
ajst-28813	298	12	kind	kind	NOUN
ajst-28813	298	13	of	of	ADP
ajst-28813	298	14	recurrent	recurrent	ADJ
ajst-28813	298	15	neural	neural	ADJ
ajst-28813	298	16	network	network	NOUN
ajst-28813	298	17	structure	structure	NOUN
ajst-28813	298	18	,	,	PUNCT
ajst-28813	298	19	it	it	PRON
ajst-28813	298	20	by	by	ADP
ajst-28813	298	21	introducing	introduce	VERB
ajst-28813	298	22	the	the	DET
ajst-28813	298	23	gating	gate	VERB
ajst-28813	298	24	mechanism	mechanism	NOUN
ajst-28813	298	25	to	to	PART
ajst-28813	298	26	solve	solve	VERB
ajst-28813	298	27	the	the	DET
ajst-28813	298	28	gradient	gradient	NOUN
ajst-28813	298	29	in	in	ADP
ajst-28813	298	30	traditional	traditional	ADJ
ajst-28813	298	31	loop	loop	NOUN
ajst-28813	298	32	neural	neural	ADJ
ajst-28813	298	33	network	network	NOUN
ajst-28813	298	34	,	,	PUNCT
ajst-28813	298	35	lstm	lstm	ADJ
ajst-28813	298	36	network	network	NOUN
ajst-28813	298	37	through	through	ADP
ajst-28813	298	38	three	three	NUM
ajst-28813	298	39	door	door	NOUN
ajst-28813	298	40	unit	unit	NOUN
ajst-28813	298	41	:	:	PUNCT
ajst-28813	298	42	forgotten	forget	VERB
ajst-28813	298	43	door	door	NOUN
ajst-28813	298	44	,	,	PUNCT
ajst-28813	298	45	input	input	NOUN
ajst-28813	298	46	and	and	CCONJ
ajst-28813	298	47	output	output	NOUN
ajst-28813	298	48	door	door	NOUN
ajst-28813	298	49	to	to	PART
ajst-28813	298	50	control	control	VERB
ajst-28813	298	51	the	the	DET
ajst-28813	298	52	flow	flow	NOUN
ajst-28813	298	53	of	of	ADP
ajst-28813	298	54	information	information	NOUN
ajst-28813	298	55	,	,	PUNCT
ajst-28813	298	56	makes	make	VERB
ajst-28813	298	57	the	the	DET
ajst-28813	298	58	network	network	NOUN
ajst-28813	298	59	to	to	PART
ajst-28813	298	60	learn	learn	VERB
ajst-28813	298	61	long	long	ADJ
ajst-28813	298	62	-	-	PUNCT
ajst-28813	298	63	term	term	NOUN
ajst-28813	298	64	dependence	dependence	NOUN
ajst-28813	298	65	.	.	PUNCT
ajst-28813	299	1	the	the	DET
ajst-28813	299	2	forgetting	forget	VERB
ajst-28813	299	3	gate	gate	NOUN
ajst-28813	299	4	is	be	AUX
ajst-28813	299	5	responsible	responsible	ADJ
ajst-28813	299	6	for	for	ADP
ajst-28813	299	7	determining	determine	VERB
ajst-28813	299	8	the	the	DET
ajst-28813	299	9	discard	discard	ADJ
ajst-28813	299	10	state	state	NOUN
ajst-28813	299	11	of	of	ADP
ajst-28813	299	12	the	the	DET
ajst-28813	299	13	information	information	NOUN
ajst-28813	299	14	in	in	ADP
ajst-28813	299	15	the	the	DET
ajst-28813	299	16	cell	cell	NOUN
ajst-28813	299	17	;	;	PUNCT
ajst-28813	299	18	the	the	DET
ajst-28813	299	19	input	input	NOUN
ajst-28813	299	20	gate	gate	NOUN
ajst-28813	299	21	controls	control	VERB
ajst-28813	299	22	the	the	DET
ajst-28813	299	23	addition	addition	NOUN
ajst-28813	299	24	of	of	ADP
ajst-28813	299	25	new	new	ADJ
ajst-28813	299	26	input	input	NOUN
ajst-28813	299	27	learning	learning	NOUN
ajst-28813	299	28	;	;	PUNCT
ajst-28813	299	29	and	and	CCONJ
ajst-28813	299	30	the	the	DET
ajst-28813	299	31	output	output	NOUN
ajst-28813	299	32	gate	gate	NOUN
ajst-28813	299	33	determines	determine	VERB
ajst-28813	299	34	the	the	DET
ajst-28813	299	35	output	output	NOUN
ajst-28813	299	36	of	of	ADP
ajst-28813	299	37	the	the	DET
ajst-28813	299	38	next	next	ADJ
ajst-28813	299	39	hidden	hidden	ADJ
ajst-28813	299	40	state	state	NOUN
ajst-28813	299	41	.	.	PUNCT
ajst-28813	300	1	this	this	DET
ajst-28813	300	2	structure	structure	NOUN
ajst-28813	300	3	allows	allow	VERB
ajst-28813	300	4	lstm	lstm	NOUN
ajst-28813	300	5	to	to	PART
ajst-28813	300	6	perform	perform	VERB
ajst-28813	300	7	relatively	relatively	ADV
ajst-28813	300	8	well	well	ADV
ajst-28813	300	9	when	when	SCONJ
ajst-28813	300	10	handling	handle	VERB
ajst-28813	300	11	long	long	ADJ
ajst-28813	300	12	sequence	sequence	NOUN
ajst-28813	300	13	data	datum	NOUN
ajst-28813	300	14	,	,	PUNCT
ajst-28813	300	15	especially	especially	ADV
ajst-28813	300	16	for	for	ADP
ajst-28813	300	17	tasks	task	NOUN
ajst-28813	300	18	that	that	PRON
ajst-28813	300	19	need	need	VERB
ajst-28813	300	20	to	to	PART
ajst-28813	300	21	capture	capture	VERB
ajst-28813	300	22	long	long	ADJ
ajst-28813	300	23	-	-	PUNCT
ajst-28813	300	24	term	term	NOUN
ajst-28813	300	25	dependencies	dependency	NOUN
ajst-28813	300	26	in	in	ADP
ajst-28813	300	27	time	time	NOUN
ajst-28813	300	28	series	series	PROPN
ajst-28813	300	29	data	data	PROPN
ajst-28813	300	30	.	.	PUNCT
ajst-28813	301	1	the	the	DET
ajst-28813	301	2	gating	gate	VERB
ajst-28813	301	3	cycle	cycle	NOUN
ajst-28813	301	4	unit	unit	NOUN
ajst-28813	301	5	(	(	PUNCT
ajst-28813	301	6	gru	gru	NOUN
ajst-28813	301	7	)	)	PUNCT
ajst-28813	301	8	model	model	NOUN
ajst-28813	301	9	reduces	reduce	VERB
ajst-28813	301	10	the	the	DET
ajst-28813	301	11	complexity	complexity	NOUN
ajst-28813	301	12	of	of	ADP
ajst-28813	301	13	the	the	DET
ajst-28813	301	14	model	model	NOUN
ajst-28813	301	15	by	by	ADP
ajst-28813	301	16	simplifying	simplify	VERB
ajst-28813	301	17	the	the	DET
ajst-28813	301	18	gating	gate	VERB
ajst-28813	301	19	structure	structure	NOUN
ajst-28813	301	20	of	of	ADP
ajst-28813	301	21	the	the	DET
ajst-28813	301	22	lstm	lstm	PROPN
ajst-28813	301	23	model	model	NOUN
ajst-28813	301	24	.	.	PUNCT
ajst-28813	302	1	the	the	DET
ajst-28813	302	2	gru	gru	NOUN
ajst-28813	302	3	model	model	NOUN
ajst-28813	302	4	consists	consist	VERB
ajst-28813	302	5	of	of	ADP
ajst-28813	302	6	two	two	NUM
ajst-28813	302	7	gating	gate	VERB
ajst-28813	302	8	units	unit	NOUN
ajst-28813	302	9	:	:	PUNCT
ajst-28813	302	10	reset	reset	NOUN
ajst-28813	302	11	door	door	NOUN
ajst-28813	302	12	and	and	CCONJ
ajst-28813	302	13	update	update	VERB
ajst-28813	302	14	door	door	NOUN
ajst-28813	302	15	.	.	PUNCT
ajst-28813	303	1	the	the	DET
ajst-28813	303	2	reset	reset	NOUN
ajst-28813	303	3	door	door	NOUN
ajst-28813	303	4	is	be	AUX
ajst-28813	303	5	responsible	responsible	ADJ
ajst-28813	303	6	for	for	ADP
ajst-28813	303	7	determining	determine	VERB
ajst-28813	303	8	how	how	SCONJ
ajst-28813	303	9	much	much	ADJ
ajst-28813	303	10	past	past	ADJ
ajst-28813	303	11	information	information	NOUN
ajst-28813	303	12	needs	need	VERB
ajst-28813	303	13	to	to	PART
ajst-28813	303	14	be	be	AUX
ajst-28813	303	15	forgotten	forget	VERB
ajst-28813	303	16	,	,	PUNCT
ajst-28813	303	17	while	while	SCONJ
ajst-28813	303	18	the	the	DET
ajst-28813	303	19	update	update	NOUN
ajst-28813	303	20	door	door	NOUN
ajst-28813	303	21	controls	control	VERB
ajst-28813	303	22	how	how	SCONJ
ajst-28813	303	23	much	much	ADJ
ajst-28813	303	24	new	new	ADJ
ajst-28813	303	25	information	information	NOUN
ajst-28813	303	26	is	be	AUX
ajst-28813	303	27	combined	combine	VERB
ajst-28813	303	28	with	with	ADP
ajst-28813	303	29	information	information	NOUN
ajst-28813	303	30	.	.	PUNCT
ajst-28813	304	1	this	this	DET
ajst-28813	304	2	design	design	NOUN
ajst-28813	304	3	allows	allow	VERB
ajst-28813	304	4	the	the	DET
ajst-28813	304	5	gru	gru	NOUN
ajst-28813	304	6	to	to	PART
ajst-28813	304	7	effectively	effectively	ADV
ajst-28813	304	8	balance	balance	VERB
ajst-28813	304	9	computational	computational	ADJ
ajst-28813	304	10	efficiency	efficiency	NOUN
ajst-28813	304	11	and	and	CCONJ
ajst-28813	304	12	performance	performance	NOUN
ajst-28813	304	13	when	when	SCONJ
ajst-28813	304	14	capturing	capture	VERB
ajst-28813	304	15	long	long	ADJ
ajst-28813	304	16	-	-	PUNCT
ajst-28813	304	17	term	term	NOUN
ajst-28813	304	18	dependencies	dependency	NOUN
ajst-28813	304	19	in	in	ADP
ajst-28813	304	20	time	time	NOUN
ajst-28813	304	21	-	-	PUNCT
ajst-28813	304	22	series	series	NOUN
ajst-28813	304	23	data	datum	NOUN
ajst-28813	304	24	.	.	PUNCT
ajst-28813	305	1	after	after	ADP
ajst-28813	305	2	the	the	DET
ajst-28813	305	3	construction	construction	NOUN
ajst-28813	305	4	of	of	ADP
ajst-28813	305	5	the	the	DET
ajst-28813	305	6	above	above	ADJ
ajst-28813	305	7	model	model	NOUN
ajst-28813	305	8	,	,	PUNCT
ajst-28813	305	9	the	the	DET
ajst-28813	305	10	imported	import	VERB
ajst-28813	305	11	data	datum	NOUN
ajst-28813	305	12	set	set	VERB
ajst-28813	305	13	is	be	AUX
ajst-28813	305	14	the	the	DET
ajst-28813	305	15	actual	actual	ADJ
ajst-28813	305	16	data	datum	NOUN
ajst-28813	305	17	collected	collect	VERB
ajst-28813	305	18	in	in	ADP
ajst-28813	305	19	the	the	DET
ajst-28813	305	20	first	first	ADJ
ajst-28813	305	21	120	120	NUM
ajst-28813	305	22	minutes	minute	NOUN
ajst-28813	305	23	of	of	ADP
ajst-28813	305	24	a	a	DET
ajst-28813	305	25	random	random	ADJ
ajst-28813	305	26	set	set	NOUN
ajst-28813	305	27	after	after	ADP
ajst-28813	305	28	the	the	DET
ajst-28813	305	29	submersible	submersible	ADJ
ajst-28813	305	30	pump	pump	NOUN
ajst-28813	305	31	well	well	ADV
ajst-28813	305	32	.	.	PUNCT
ajst-28813	306	1	the	the	DET
ajst-28813	306	2	comparison	comparison	NOUN
ajst-28813	306	3	results	result	NOUN
ajst-28813	306	4	of	of	ADP
ajst-28813	306	5	esn	esn	PROPN
ajst-28813	306	6	model	model	PROPN
ajst-28813	306	7	,	,	PUNCT
ajst-28813	306	8	lstm	lstm	NOUN
ajst-28813	306	9	model	model	NOUN
ajst-28813	306	10	and	and	CCONJ
ajst-28813	306	11	gru	gru	NOUN
ajst-28813	306	12	model	model	NOUN
ajst-28813	306	13	are	be	AUX
ajst-28813	306	14	shown	show	VERB
ajst-28813	306	15	in	in	ADP
ajst-28813	306	16	figure	figure	NOUN
ajst-28813	306	17	3	3	NUM
ajst-28813	306	18	-	-	SYM
ajst-28813	306	19	4	4	NUM
ajst-28813	306	20	.	.	PUNCT
ajst-28813	306	21	figure	figure	VERB
ajst-28813	306	22	3–4	3–4	NUM
ajst-28813	306	23	.	.	PUNCT
ajst-28813	306	24	schematic	schematic	ADJ
ajst-28813	306	25	of	of	ADP
ajst-28813	306	26	the	the	DET
ajst-28813	306	27	prediction	prediction	NOUN
ajst-28813	306	28	comparison	comparison	NOUN
ajst-28813	306	29	between	between	ADP
ajst-28813	306	30	three	three	NUM
ajst-28813	306	31	network	network	NOUN
ajst-28813	306	32	models	model	NOUN
ajst-28813	306	33	and	and	CCONJ
ajst-28813	306	34	true	true	ADJ
ajst-28813	306	35	values	value	NOUN
ajst-28813	306	36	the	the	DET
ajst-28813	306	37	results	result	NOUN
ajst-28813	306	38	of	of	ADP
ajst-28813	306	39	mse	mse	NOUN
ajst-28813	306	40	,	,	PUNCT
ajst-28813	306	41	nrmse	nrmse	VERB
ajst-28813	306	42	as	as	ADP
ajst-28813	306	43	standard	standard	ADJ
ajst-28813	306	44	quantities	quantity	NOUN
ajst-28813	306	45	according	accord	VERB
ajst-28813	306	46	on	on	ADP
ajst-28813	306	47	the	the	DET
ajst-28813	306	48	comparison	comparison	NOUN
ajst-28813	306	49	results	result	NOUN
ajst-28813	306	50	are	be	AUX
ajst-28813	306	51	summarized	summarize	VERB
ajst-28813	306	52	in	in	ADP
ajst-28813	306	53	table	table	NOUN
ajst-28813	306	54	3	3	NUM
ajst-28813	306	55	-	-	SYM
ajst-28813	306	56	3	3	NUM
ajst-28813	306	57	.	.	PUNCT
ajst-28813	306	58	table	table	NOUN
ajst-28813	306	59	3	3	NUM
ajst-28813	306	60	-	-	SYM
ajst-28813	306	61	3	3	NUM
ajst-28813	306	62	.	.	NOUN
ajst-28813	306	63	table	table	NOUN
ajst-28813	306	64	of	of	ADP
ajst-28813	306	65	results	result	NOUN
ajst-28813	306	66	between	between	ADP
ajst-28813	306	67	esn	esn	PROPN
ajst-28813	306	68	and	and	CCONJ
ajst-28813	306	69	lstm	lstm	PROPN
ajst-28813	306	70	and	and	CCONJ
ajst-28813	306	71	gru	gru	NOUN
ajst-28813	306	72	networks	network	NOUN
ajst-28813	306	73	network	network	NOUN
ajst-28813	306	74	type	type	NOUN
ajst-28813	306	75	mse	mse	PROPN
ajst-28813	306	76	nrmse	nrmse	NOUN
ajst-28813	306	77	training	training	NOUN
ajst-28813	306	78	times	time	NOUN
ajst-28813	306	79	training	training	NOUN
ajst-28813	306	80	duration(ｓ	duration(ｓ	NOUN
ajst-28813	306	81	)	)	PUNCT
ajst-28813	306	82	esn	esn	PROPN
ajst-28813	306	83	3.90ｅ9	3.90ｅ9	NUM
ajst-28813	306	84	0.0082	0.0082	NUM
ajst-28813	306	85	21.5	21.5	NUM
ajst-28813	306	86	lstm	lstm	NOUN
ajst-28813	306	87	9.19ｅ10	9.19ｅ10	NUM
ajst-28813	306	88	0.0203	0.0203	NUM
ajst-28813	306	89	100	100	NUM
ajst-28813	306	90	197.5	197.5	NUM
ajst-28813	306	91	gru	gru	NOUN
ajst-28813	306	92	9.06ｅ10	9.06ｅ10	NUM
ajst-28813	306	93	0.0397	0.0397	NUM
ajst-28813	306	94	160	160	NUM
ajst-28813	306	95	218.7	218.7	NUM
ajst-28813	306	96	as	as	SCONJ
ajst-28813	306	97	can	can	AUX
ajst-28813	306	98	be	be	AUX
ajst-28813	306	99	clearly	clearly	ADV
ajst-28813	306	100	seen	see	VERB
ajst-28813	306	101	from	from	ADP
ajst-28813	306	102	the	the	DET
ajst-28813	306	103	data	datum	NOUN
ajst-28813	306	104	results	result	NOUN
ajst-28813	306	105	and	and	CCONJ
ajst-28813	306	106	images	image	NOUN
ajst-28813	306	107	of	of	ADP
ajst-28813	306	108	figure	figure	NOUN
ajst-28813	306	109	3	3	NUM
ajst-28813	306	110	-	-	SYM
ajst-28813	306	111	14	14	NUM
ajst-28813	306	112	and	and	CCONJ
ajst-28813	306	113	table	table	NOUN
ajst-28813	306	114	3	3	NUM
ajst-28813	306	115	-	-	SYM
ajst-28813	306	116	3	3	NUM
ajst-28813	306	117	,	,	PUNCT
ajst-28813	306	118	it	it	PRON
ajst-28813	306	119	can	can	AUX
ajst-28813	306	120	be	be	AUX
ajst-28813	306	121	seen	see	VERB
ajst-28813	306	122	that	that	SCONJ
ajst-28813	306	123	the	the	DET
ajst-28813	306	124	esn	esn	PROPN
ajst-28813	306	125	model	model	NOUN
ajst-28813	306	126	has	have	VERB
ajst-28813	306	127	certain	certain	ADJ
ajst-28813	306	128	advantages	advantage	NOUN
ajst-28813	306	129	over	over	ADP
ajst-28813	306	130	lstm	lstm	NOUN
ajst-28813	306	131	model	model	NOUN
ajst-28813	306	132	and	and	CCONJ
ajst-28813	306	133	gru	gru	NOUN
ajst-28813	306	134	model	model	NOUN
ajst-28813	306	135	in	in	ADP
ajst-28813	306	136	terms	term	NOUN
ajst-28813	306	137	of	of	ADP
ajst-28813	306	138	prediction	prediction	NOUN
ajst-28813	306	139	accuracy	accuracy	NOUN
ajst-28813	306	140	.	.	PUNCT
ajst-28813	307	1	the	the	DET
ajst-28813	307	2	esn	esn	PROPN
ajst-28813	307	3	network	network	NOUN
ajst-28813	307	4	outperforms	outperform	VERB
ajst-28813	307	5	lstm	lstm	PROPN
ajst-28813	307	6	and	and	CCONJ
ajst-28813	307	7	gru	gru	NOUN
ajst-28813	307	8	model	model	NOUN
ajst-28813	307	9	in	in	ADP
ajst-28813	307	10	terms	term	NOUN
ajst-28813	307	11	of	of	ADP
ajst-28813	307	12	mean	mean	ADJ
ajst-28813	307	13	square	square	ADJ
ajst-28813	307	14	error	error	NOUN
ajst-28813	307	15	(	(	PUNCT
ajst-28813	307	16	mse	mse	NOUN
ajst-28813	307	17	)	)	PUNCT
ajst-28813	307	18	and	and	CCONJ
ajst-28813	307	19	standard	standard	ADJ
ajst-28813	307	20	root	root	NOUN
ajst-28813	307	21	mean	mean	VERB
ajst-28813	307	22	square	square	ADJ
ajst-28813	307	23	error	error	NOUN
ajst-28813	307	24	(	(	PUNCT
ajst-28813	307	25	nrmse	nrmse	NOUN
ajst-28813	307	26	)	)	PUNCT
ajst-28813	307	27	,	,	PUNCT
ajst-28813	307	28	especially	especially	ADV
ajst-28813	307	29	when	when	SCONJ
ajst-28813	307	30	handling	handle	VERB
ajst-28813	307	31	electric	electric	ADJ
ajst-28813	307	32	submersible	submersible	ADJ
ajst-28813	307	33	pump	pump	NOUN
ajst-28813	307	34	data	datum	NOUN
ajst-28813	307	35	with	with	ADP
ajst-28813	307	36	complex	complex	ADJ
ajst-28813	307	37	dynamic	dynamic	ADJ
ajst-28813	307	38	characteristics	characteristic	NOUN
ajst-28813	307	39	.	.	PUNCT
ajst-28813	308	1	in	in	ADP
ajst-28813	308	2	addition	addition	NOUN
ajst-28813	308	3	,	,	PUNCT
ajst-28813	308	4	esn	esn	PROPN
ajst-28813	308	5	model	model	PROPN
ajst-28813	308	6	also	also	ADV
ajst-28813	308	7	shows	show	VERB
ajst-28813	308	8	obvious	obvious	ADJ
ajst-28813	308	9	advantages	advantage	NOUN
ajst-28813	308	10	in	in	ADP
ajst-28813	308	11	computational	computational	ADJ
ajst-28813	308	12	efficiency	efficiency	NOUN
ajst-28813	308	13	,	,	PUNCT
ajst-28813	308	14	and	and	CCONJ
ajst-28813	308	15	its	its	PRON
ajst-28813	308	16	training	training	NOUN
ajst-28813	308	17	time	time	NOUN
ajst-28813	308	18	is	be	AUX
ajst-28813	308	19	much	much	ADV
ajst-28813	308	20	lower	low	ADJ
ajst-28813	308	21	than	than	ADP
ajst-28813	308	22	lstm	lstm	NOUN
ajst-28813	308	23	model	model	NOUN
ajst-28813	308	24	and	and	CCONJ
ajst-28813	308	25	gru	gru	PROPN
ajst-28813	308	26	model	model	NOUN
ajst-28813	308	27	,	,	PUNCT
ajst-28813	308	28	which	which	PRON
ajst-28813	308	29	is	be	AUX
ajst-28813	308	30	particularly	particularly	ADV
ajst-28813	308	31	important	important	ADJ
ajst-28813	308	32	in	in	ADP
ajst-28813	308	33	real	real	ADJ
ajst-28813	308	34	-	-	PUNCT
ajst-28813	308	35	time	time	NOUN
ajst-28813	308	36	control	control	NOUN
ajst-28813	308	37	and	and	CCONJ
ajst-28813	308	38	online	online	ADJ
ajst-28813	308	39	optimization	optimization	NOUN
ajst-28813	308	40	scenarios	scenario	NOUN
ajst-28813	308	41	.	.	PUNCT
ajst-28813	309	1	through	through	ADP
ajst-28813	309	2	these	these	DET
ajst-28813	309	3	comparisons	comparison	NOUN
ajst-28813	309	4	,	,	PUNCT
ajst-28813	309	5	the	the	DET
ajst-28813	309	6	esn	esn	PROPN
ajst-28813	309	7	model	model	NOUN
ajst-28813	309	8	has	have	VERB
ajst-28813	309	9	a	a	DET
ajst-28813	309	10	better	well	ADJ
ajst-28813	309	11	application	application	NOUN
ajst-28813	309	12	prospect	prospect	NOUN
ajst-28813	309	13	in	in	ADP
ajst-28813	309	14	the	the	DET
ajst-28813	309	15	predictive	predictive	ADJ
ajst-28813	309	16	control	control	NOUN
ajst-28813	309	17	of	of	ADP
ajst-28813	309	18	the	the	DET
ajst-28813	309	19	electric	electric	ADJ
ajst-28813	309	20	submersible	submersible	ADJ
ajst-28813	309	21	pump	pump	NOUN
ajst-28813	309	22	model	model	NOUN
ajst-28813	309	23	.	.	PUNCT
ajst-28813	310	1	5	5	X
ajst-28813	310	2	.	.	PUNCT
ajst-28813	310	3	model	model	NOUN
ajst-28813	310	4	performance	performance	NOUN
ajst-28813	310	5	assessment	assessment	NOUN
ajst-28813	310	6	5.1	5.1	NUM
ajst-28813	310	7	.	.	PUNCT
ajst-28813	311	1	model	model	NOUN
ajst-28813	311	2	evaluation	evaluation	NOUN
ajst-28813	311	3	in	in	ADP
ajst-28813	311	4	the	the	DET
ajst-28813	311	5	process	process	NOUN
ajst-28813	311	6	of	of	ADP
ajst-28813	311	7	model	model	NOUN
ajst-28813	311	8	adjustment	adjustment	NOUN
ajst-28813	311	9	and	and	CCONJ
ajst-28813	311	10	optimization	optimization	NOUN
ajst-28813	311	11	,	,	PUNCT
ajst-28813	311	12	this	this	DET
ajst-28813	311	13	paper	paper	NOUN
ajst-28813	311	14	focuses	focus	VERB
ajst-28813	311	15	on	on	ADP
ajst-28813	311	16	the	the	DET
ajst-28813	311	17	generalization	generalization	NOUN
ajst-28813	311	18	ability	ability	NOUN
ajst-28813	311	19	of	of	ADP
ajst-28813	311	20	the	the	DET
ajst-28813	311	21	model	model	NOUN
ajst-28813	311	22	,	,	PUNCT
ajst-28813	311	23	namely	namely	ADV
ajst-28813	311	24	the	the	DET
ajst-28813	311	25	adaptability	adaptability	NOUN
ajst-28813	311	26	under	under	ADP
ajst-28813	311	27	different	different	ADJ
ajst-28813	311	28	working	working	NOUN
ajst-28813	311	29	conditions	condition	NOUN
ajst-28813	311	30	and	and	CCONJ
ajst-28813	311	31	environments	environment	NOUN
ajst-28813	311	32	.	.	PUNCT
ajst-28813	312	1	by	by	ADP
ajst-28813	312	2	adjusting	adjust	VERB
ajst-28813	312	3	network	network	NOUN
ajst-28813	312	4	parameters	parameter	NOUN
ajst-28813	312	5	such	such	ADJ
ajst-28813	312	6	as	as	ADP
ajst-28813	312	7	leakage	leakage	NOUN
ajst-28813	312	8	rate	rate	NOUN
ajst-28813	312	9	,	,	PUNCT
ajst-28813	312	10	number	number	NOUN
ajst-28813	312	11	of	of	ADP
ajst-28813	312	12	neurons	neuron	NOUN
ajst-28813	312	13	,	,	PUNCT
ajst-28813	312	14	sampling	sample	VERB
ajst-28813	312	15	rate	rate	NOUN
ajst-28813	312	16	,	,	PUNCT
ajst-28813	312	17	and	and	CCONJ
ajst-28813	312	18	input	input	VERB
ajst-28813	312	19	scaling	scaling	NOUN
ajst-28813	312	20	factors	factor	NOUN
ajst-28813	312	21	,	,	PUNCT
ajst-28813	312	22	we	we	PRON
ajst-28813	312	23	find	find	VERB
ajst-28813	312	24	that	that	SCONJ
ajst-28813	312	25	the	the	DET
ajst-28813	312	26	resulting	result	VERB
ajst-28813	312	27	prediction	prediction	NOUN
ajst-28813	312	28	accuracy	accuracy	NOUN
ajst-28813	312	29	and	and	CCONJ
ajst-28813	312	30	stability	stability	NOUN
ajst-28813	312	31	of	of	ADP
ajst-28813	312	32	the	the	DET
ajst-28813	312	33	model	model	NOUN
ajst-28813	312	34	are	be	AUX
ajst-28813	312	35	significantly	significantly	ADV
ajst-28813	312	36	improved	improve	VERB
ajst-28813	312	37	.	.	PUNCT
ajst-28813	313	1	the	the	DET
ajst-28813	313	2	training	training	NOUN
ajst-28813	313	3	process	process	NOUN
ajst-28813	313	4	of	of	ADP
ajst-28813	313	5	the	the	DET
ajst-28813	313	6	model	model	NOUN
ajst-28813	313	7	is	be	AUX
ajst-28813	313	8	monitored	monitor	VERB
ajst-28813	313	9	in	in	ADP
ajst-28813	313	10	real	real	ADJ
ajst-28813	313	11	time	time	NOUN
ajst-28813	313	12	,	,	PUNCT
ajst-28813	313	13	which	which	PRON
ajst-28813	313	14	ensures	ensure	VERB
ajst-28813	313	15	that	that	SCONJ
ajst-28813	313	16	the	the	DET
ajst-28813	313	17	convergence	convergence	NOUN
ajst-28813	313	18	of	of	ADP
ajst-28813	313	19	the	the	DET
ajst-28813	313	20	training	training	NOUN
ajst-28813	313	21	process	process	NOUN
ajst-28813	313	22	and	and	CCONJ
ajst-28813	313	23	the	the	DET
ajst-28813	313	24	risk	risk	NOUN
ajst-28813	313	25	of	of	ADP
ajst-28813	313	26	overfitting	overfitting	NOUN
ajst-28813	313	27	of	of	ADP
ajst-28813	313	28	the	the	DET
ajst-28813	313	29	model	model	NOUN
ajst-28813	313	30	are	be	AUX
ajst-28813	313	31	minimized	minimize	VERB
ajst-28813	313	32	.	.	PUNCT
ajst-28813	314	1	next	next	ADJ
ajst-28813	314	2	is	be	AUX
ajst-28813	314	3	the	the	DET
ajst-28813	314	4	model	model	NOUN
ajst-28813	314	5	performance	performance	NOUN
ajst-28813	314	6	evaluation	evaluation	NOUN
ajst-28813	314	7	phase	phase	NOUN
ajst-28813	314	8	:	:	PUNCT
ajst-28813	314	9	257	257	NUM
ajst-28813	314	10	the	the	DET
ajst-28813	314	11	performance	performance	NOUN
ajst-28813	314	12	of	of	ADP
ajst-28813	314	13	the	the	DET
ajst-28813	314	14	model	model	NOUN
ajst-28813	314	15	on	on	ADP
ajst-28813	314	16	unknown	unknown	ADJ
ajst-28813	314	17	data	datum	NOUN
ajst-28813	314	18	is	be	AUX
ajst-28813	314	19	evaluated	evaluate	VERB
ajst-28813	314	20	by	by	ADP
ajst-28813	314	21	dividing	divide	VERB
ajst-28813	314	22	the	the	DET
ajst-28813	314	23	training	training	NOUN
ajst-28813	314	24	data	datum	NOUN
ajst-28813	314	25	into	into	ADP
ajst-28813	314	26	training	training	NOUN
ajst-28813	314	27	set	set	NOUN
ajst-28813	314	28	and	and	CCONJ
ajst-28813	314	29	test	test	NOUN
ajst-28813	314	30	set	set	VERB
ajst-28813	314	31	;	;	PUNCT
ajst-28813	314	32	as	as	SCONJ
ajst-28813	314	33	shown	show	VERB
ajst-28813	314	34	in	in	ADP
ajst-28813	314	35	figure	figure	NOUN
ajst-28813	314	36	4	4	NUM
ajst-28813	314	37	-	-	PUNCT
ajst-28813	314	38	1,4	1,4	NUM
ajst-28813	314	39	-	-	PUNCT
ajst-28813	314	40	2,4	2,4	NUM
ajst-28813	314	41	-	-	PUNCT
ajst-28813	314	42	3	3	NUM
ajst-28813	314	43	.	.	PUNCT
ajst-28813	315	1	according	accord	VERB
ajst-28813	315	2	to	to	ADP
ajst-28813	315	3	the	the	DET
ajst-28813	315	4	prediction	prediction	NOUN
ajst-28813	315	5	results	result	NOUN
ajst-28813	315	6	of	of	ADP
ajst-28813	315	7	the	the	DET
ajst-28813	315	8	test	test	NOUN
ajst-28813	315	9	set	set	NOUN
ajst-28813	315	10	,	,	PUNCT
ajst-28813	315	11	the	the	DET
ajst-28813	315	12	esn	esn	PROPN
ajst-28813	315	13	model	model	NOUN
ajst-28813	315	14	performs	perform	VERB
ajst-28813	315	15	well	well	ADV
ajst-28813	315	16	in	in	ADP
ajst-28813	315	17	the	the	DET
ajst-28813	315	18	state	state	NOUN
ajst-28813	315	19	prediction	prediction	NOUN
ajst-28813	315	20	of	of	ADP
ajst-28813	315	21	fast	fast	ADJ
ajst-28813	315	22	and	and	CCONJ
ajst-28813	315	23	slow	slow	ADJ
ajst-28813	315	24	input	input	NOUN
ajst-28813	315	25	changes	change	NOUN
ajst-28813	315	26	,	,	PUNCT
ajst-28813	315	27	and	and	CCONJ
ajst-28813	315	28	the	the	DET
ajst-28813	315	29	deviation	deviation	NOUN
ajst-28813	315	30	from	from	ADP
ajst-28813	315	31	the	the	DET
ajst-28813	315	32	predicted	predict	VERB
ajst-28813	315	33	value	value	NOUN
ajst-28813	315	34	is	be	AUX
ajst-28813	315	35	as	as	SCONJ
ajst-28813	315	36	expected	expect	VERB
ajst-28813	315	37	.	.	PUNCT
ajst-28813	316	1	figure	figure	VERB
ajst-28813	316	2	4	4	NUM
ajst-28813	316	3	-	-	SYM
ajst-28813	316	4	1	1	NUM
ajst-28813	316	5	.	.	PUNCT
ajst-28813	316	6	comparison	comparison	NOUN
ajst-28813	316	7	of	of	ADP
ajst-28813	316	8	predicted	predict	VERB
ajst-28813	316	9	value	value	NOUN
ajst-28813	316	10	and	and	CCONJ
ajst-28813	316	11	true	true	ADJ
ajst-28813	316	12	value	value	NOUN
ajst-28813	316	13	and	and	CCONJ
ajst-28813	316	14	error	error	NOUN
ajst-28813	316	15	rate	rate	NOUN
ajst-28813	316	16	of	of	ADP
ajst-28813	316	17	rapid	rapid	ADJ
ajst-28813	316	18	input	input	NOUN
ajst-28813	316	19	data	datum	NOUN
ajst-28813	316	20	figure	figure	NOUN
ajst-28813	316	21	4	4	NUM
ajst-28813	316	22	-	-	SYM
ajst-28813	316	23	2	2	NUM
ajst-28813	316	24	.	.	PUNCT
ajst-28813	316	25	comparison	comparison	NOUN
ajst-28813	316	26	of	of	ADP
ajst-28813	316	27	predicted	predict	VERB
ajst-28813	316	28	and	and	CCONJ
ajst-28813	316	29	true	true	ADJ
ajst-28813	316	30	values	value	NOUN
ajst-28813	316	31	and	and	CCONJ
ajst-28813	316	32	error	error	NOUN
ajst-28813	316	33	rate	rate	NOUN
ajst-28813	316	34	when	when	SCONJ
ajst-28813	316	35	the	the	DET
ajst-28813	316	36	slow	slow	ADJ
ajst-28813	316	37	input	input	NOUN
ajst-28813	316	38	data	datum	NOUN
ajst-28813	316	39	changes	change	NOUN
ajst-28813	316	40	figure	figure	VERB
ajst-28813	316	41	4	4	NUM
ajst-28813	316	42	-	-	SYM
ajst-28813	316	43	3	3	NUM
ajst-28813	316	44	.	.	PUNCT
ajst-28813	316	45	comparison	comparison	NOUN
ajst-28813	316	46	of	of	ADP
ajst-28813	316	47	predicted	predict	VERB
ajst-28813	316	48	and	and	CCONJ
ajst-28813	316	49	true	true	ADJ
ajst-28813	316	50	values	value	NOUN
ajst-28813	316	51	and	and	CCONJ
ajst-28813	316	52	error	error	NOUN
ajst-28813	316	53	rate	rate	NOUN
ajst-28813	316	54	between	between	ADP
ajst-28813	316	55	fast	fast	ADJ
ajst-28813	316	56	and	and	CCONJ
ajst-28813	316	57	slow	slow	ADJ
ajst-28813	316	58	input	input	NOUN
ajst-28813	316	59	data	datum	NOUN
ajst-28813	316	60	258	258	NUM
ajst-28813	316	61	when	when	SCONJ
ajst-28813	316	62	comparing	compare	VERB
ajst-28813	316	63	the	the	DET
ajst-28813	316	64	different	different	ADJ
ajst-28813	316	65	results	result	NOUN
ajst-28813	316	66	in	in	ADP
ajst-28813	316	67	this	this	DET
ajst-28813	316	68	subsection	subsection	NOUN
ajst-28813	316	69	,	,	PUNCT
ajst-28813	316	70	the	the	DET
ajst-28813	316	71	best	good	ADJ
ajst-28813	316	72	results	result	NOUN
ajst-28813	316	73	were	be	AUX
ajst-28813	316	74	obtained	obtain	VERB
ajst-28813	316	75	when	when	SCONJ
ajst-28813	316	76	using	use	VERB
ajst-28813	316	77	the	the	DET
ajst-28813	316	78	training	training	NOUN
ajst-28813	316	79	set	set	NOUN
ajst-28813	316	80	of	of	ADP
ajst-28813	316	81	fast	fast	ADJ
ajst-28813	316	82	and	and	CCONJ
ajst-28813	316	83	slow	slow	ADJ
ajst-28813	316	84	changes	change	NOUN
ajst-28813	316	85	combined	combine	VERB
ajst-28813	316	86	with	with	ADP
ajst-28813	316	87	the	the	DET
ajst-28813	316	88	input	input	NOUN
ajst-28813	316	89	.	.	PUNCT
ajst-28813	317	1	in	in	ADP
ajst-28813	317	2	table	table	NOUN
ajst-28813	317	3	4	4	NUM
ajst-28813	317	4	-	-	SYM
ajst-28813	317	5	1	1	NUM
ajst-28813	317	6	,	,	PUNCT
ajst-28813	317	7	the	the	DET
ajst-28813	317	8	mse	mse	NOUN
ajst-28813	317	9	is	be	AUX
ajst-28813	317	10	used	use	VERB
ajst-28813	317	11	to	to	PART
ajst-28813	317	12	measure	measure	VERB
ajst-28813	317	13	the	the	DET
ajst-28813	317	14	error	error	NOUN
ajst-28813	317	15	.	.	PUNCT
ajst-28813	318	1	from	from	ADP
ajst-28813	318	2	the	the	DET
ajst-28813	318	3	above	above	ADJ
ajst-28813	318	4	comparison	comparison	NOUN
ajst-28813	318	5	,	,	PUNCT
ajst-28813	318	6	the	the	DET
ajst-28813	318	7	training	training	NOUN
ajst-28813	318	8	set	set	NOUN
ajst-28813	318	9	selecting	select	VERB
ajst-28813	318	10	fast	fast	ADJ
ajst-28813	318	11	and	and	CCONJ
ajst-28813	318	12	slow	slow	ADJ
ajst-28813	318	13	change	change	NOUN
ajst-28813	318	14	combined	combine	VERB
ajst-28813	318	15	with	with	ADP
ajst-28813	318	16	the	the	DET
ajst-28813	318	17	input	input	NOUN
ajst-28813	318	18	was	be	AUX
ajst-28813	318	19	determined	determine	VERB
ajst-28813	318	20	as	as	ADP
ajst-28813	318	21	the	the	DET
ajst-28813	318	22	most	most	ADV
ajst-28813	318	23	appropriate	appropriate	ADJ
ajst-28813	318	24	training	training	NOUN
ajst-28813	318	25	set	set	NOUN
ajst-28813	318	26	for	for	ADP
ajst-28813	318	27	this	this	DET
ajst-28813	318	28	esn	esn	PROPN
ajst-28813	318	29	network	network	PROPN
ajst-28813	318	30	.	.	PUNCT
ajst-28813	319	1	table	table	NOUN
ajst-28813	319	2	4	4	NUM
ajst-28813	319	3	-	-	SYM
ajst-28813	319	4	1	1	NUM
ajst-28813	319	5	.	.	PUNCT
ajst-28813	319	6	comparison	comparison	NOUN
ajst-28813	319	7	of	of	ADP
ajst-28813	319	8	the	the	DET
ajst-28813	319	9	effect	effect	NOUN
ajst-28813	319	10	of	of	ADP
ajst-28813	319	11	input	input	NOUN
ajst-28813	319	12	data	datum	NOUN
ajst-28813	319	13	change	change	VERB
ajst-28813	319	14	speed	speed	NOUN
ajst-28813	319	15	on	on	ADP
ajst-28813	319	16	prediction	prediction	NOUN
ajst-28813	319	17	accuracy	accuracy	NOUN
ajst-28813	319	18	mse	mse	PROPN
ajst-28813	319	19	bhp	bhp	PROPN
ajst-28813	319	20	whp	whp	PROPN
ajst-28813	319	21	q	q	PROPN
ajst-28813	319	22	quick	quick	ADJ
ajst-28813	319	23	input	input	NOUN
ajst-28813	319	24	1.81ｅ11	1.81ｅ11	NUM
ajst-28813	319	25	4.14ｅ11	4.14ｅ11	NUM
ajst-28813	319	26	8.99ｅ-7	8.99ｅ-7	PROPN
ajst-28813	319	27	slow	slow	ADJ
ajst-28813	319	28	input	input	NOUN
ajst-28813	319	29	1.42ｅ10	1.42ｅ10	NUM
ajst-28813	319	30	1.88ｅ11	1.88ｅ11	NUM
ajst-28813	319	31	1.38ｅ-7	1.38ｅ-7	ADJ
ajst-28813	319	32	mixed	mixed	ADJ
ajst-28813	319	33	input	input	NOUN
ajst-28813	319	34	3.93ｅ9	3.93ｅ9	PROPN
ajst-28813	319	35	1.72ｅ10	1.72ｅ10	NUM
ajst-28813	319	36	3.15ｅ-9	3.15ｅ-9	NUM
ajst-28813	319	37	5.2	5.2	NUM
ajst-28813	319	38	.	.	PUNCT
ajst-28813	320	1	experimental	experimental	ADJ
ajst-28813	320	2	results	result	NOUN
ajst-28813	320	3	based	base	VERB
ajst-28813	320	4	on	on	ADP
ajst-28813	320	5	the	the	DET
ajst-28813	320	6	field	field	NOUN
ajst-28813	320	7	data	datum	NOUN
ajst-28813	320	8	after	after	ADP
ajst-28813	320	9	some	some	DET
ajst-28813	320	10	training	training	NOUN
ajst-28813	320	11	,	,	PUNCT
ajst-28813	320	12	the	the	DET
ajst-28813	320	13	actual	actual	ADJ
ajst-28813	320	14	data	datum	NOUN
ajst-28813	320	15	of	of	ADP
ajst-28813	320	16	the	the	DET
ajst-28813	320	17	electric	electric	ADJ
ajst-28813	320	18	submersible	submersible	ADJ
ajst-28813	320	19	pump	pump	NOUN
ajst-28813	320	20	well	well	ADV
ajst-28813	320	21	is	be	AUX
ajst-28813	320	22	introduced	introduce	VERB
ajst-28813	320	23	into	into	ADP
ajst-28813	320	24	the	the	DET
ajst-28813	320	25	esn	esn	PROPN
ajst-28813	320	26	network	network	NOUN
ajst-28813	320	27	.	.	PUNCT
ajst-28813	321	1	the	the	DET
ajst-28813	321	2	true	true	ADJ
ajst-28813	321	3	value	value	NOUN
ajst-28813	321	4	and	and	CCONJ
ajst-28813	321	5	predicted	predict	VERB
ajst-28813	321	6	value	value	NOUN
ajst-28813	321	7	and	and	CCONJ
ajst-28813	321	8	the	the	DET
ajst-28813	321	9	corresponding	corresponding	ADJ
ajst-28813	321	10	mean	mean	NOUN
ajst-28813	321	11	error	error	NOUN
ajst-28813	321	12	rate	rate	NOUN
ajst-28813	321	13	image	image	NOUN
ajst-28813	321	14	are	be	AUX
ajst-28813	321	15	obtained	obtain	VERB
ajst-28813	321	16	in	in	ADP
ajst-28813	321	17	figure	figure	NOUN
ajst-28813	321	18	4	4	NUM
ajst-28813	321	19	-	-	SYM
ajst-28813	321	20	4	4	NUM
ajst-28813	321	21	.	.	PUNCT
ajst-28813	321	22	figure	figure	VERB
ajst-28813	321	23	4	4	NUM
ajst-28813	321	24	-	-	SYM
ajst-28813	321	25	4	4	NUM
ajst-28813	321	26	.	.	PUNCT
ajst-28813	321	27	comparison	comparison	NOUN
ajst-28813	321	28	plots	plot	NOUN
ajst-28813	321	29	of	of	ADP
ajst-28813	321	30	real	real	ADJ
ajst-28813	321	31	data	datum	NOUN
ajst-28813	321	32	and	and	CCONJ
ajst-28813	321	33	predicted	predict	VERB
ajst-28813	321	34	values	value	NOUN
ajst-28813	321	35	and	and	CCONJ
ajst-28813	321	36	the	the	DET
ajst-28813	321	37	corresponding	corresponding	ADJ
ajst-28813	321	38	error	error	NOUN
ajst-28813	321	39	plots	plot	NOUN
ajst-28813	321	40	looking	look	VERB
ajst-28813	321	41	at	at	ADP
ajst-28813	321	42	figure	figure	NOUN
ajst-28813	321	43	4	4	NUM
ajst-28813	321	44	-	-	SYM
ajst-28813	321	45	4	4	NUM
ajst-28813	321	46	,	,	PUNCT
ajst-28813	321	47	we	we	PRON
ajst-28813	321	48	can	can	AUX
ajst-28813	321	49	find	find	VERB
ajst-28813	321	50	that	that	SCONJ
ajst-28813	321	51	the	the	DET
ajst-28813	321	52	esn	esn	PROPN
ajst-28813	321	53	network	network	NOUN
ajst-28813	321	54	has	have	VERB
ajst-28813	321	55	a	a	DET
ajst-28813	321	56	high	high	ADJ
ajst-28813	321	57	matching	matching	NOUN
ajst-28813	321	58	degree	degree	NOUN
ajst-28813	321	59	between	between	ADP
ajst-28813	321	60	the	the	DET
ajst-28813	321	61	actual	actual	ADJ
ajst-28813	321	62	data	datum	NOUN
ajst-28813	321	63	and	and	CCONJ
ajst-28813	321	64	the	the	DET
ajst-28813	321	65	real	real	ADJ
ajst-28813	321	66	value	value	NOUN
ajst-28813	321	67	.	.	PUNCT
ajst-28813	322	1	even	even	ADV
ajst-28813	322	2	when	when	SCONJ
ajst-28813	322	3	the	the	DET
ajst-28813	322	4	data	datum	NOUN
ajst-28813	322	5	fluctuates	fluctuate	VERB
ajst-28813	322	6	greatly	greatly	ADV
ajst-28813	322	7	,	,	PUNCT
ajst-28813	322	8	the	the	DET
ajst-28813	322	9	tracking	tracking	NOUN
ajst-28813	322	10	ability	ability	NOUN
ajst-28813	322	11	of	of	ADP
ajst-28813	322	12	the	the	DET
ajst-28813	322	13	model	model	NOUN
ajst-28813	322	14	is	be	AUX
ajst-28813	322	15	still	still	ADV
ajst-28813	322	16	excellent	excellent	ADJ
ajst-28813	322	17	.	.	PUNCT
ajst-28813	323	1	this	this	PRON
ajst-28813	323	2	indicates	indicate	VERB
ajst-28813	323	3	that	that	SCONJ
ajst-28813	323	4	the	the	DET
ajst-28813	323	5	esn	esn	PROPN
ajst-28813	323	6	network	network	NOUN
ajst-28813	323	7	performs	perform	VERB
ajst-28813	323	8	well	well	ADV
ajst-28813	323	9	in	in	ADP
ajst-28813	323	10	dealing	deal	VERB
ajst-28813	323	11	with	with	ADP
ajst-28813	323	12	the	the	DET
ajst-28813	323	13	non	non	ADJ
ajst-28813	323	14	-	-	ADJ
ajst-28813	323	15	linear	linear	ADJ
ajst-28813	323	16	and	and	CCONJ
ajst-28813	323	17	time	time	NOUN
ajst-28813	323	18	-	-	PUNCT
ajst-28813	323	19	varying	vary	VERB
ajst-28813	323	20	characteristics	characteristic	NOUN
ajst-28813	323	21	of	of	ADP
ajst-28813	323	22	the	the	DET
ajst-28813	323	23	electric	electric	ADJ
ajst-28813	323	24	submersible	submersible	ADJ
ajst-28813	323	25	pump	pump	NOUN
ajst-28813	323	26	system	system	NOUN
ajst-28813	323	27	.	.	PUNCT
ajst-28813	324	1	the	the	DET
ajst-28813	324	2	average	average	ADJ
ajst-28813	324	3	error	error	NOUN
ajst-28813	324	4	rate	rate	NOUN
ajst-28813	324	5	combined	combine	VERB
ajst-28813	324	6	with	with	ADP
ajst-28813	324	7	the	the	DET
ajst-28813	324	8	mse	mse	PROPN
ajst-28813	324	9	data	datum	NOUN
ajst-28813	324	10	collected	collect	VERB
ajst-28813	324	11	in	in	ADP
ajst-28813	324	12	table	table	NOUN
ajst-28813	324	13	4	4	NUM
ajst-28813	324	14	-	-	SYM
ajst-28813	324	15	2	2	NUM
ajst-28813	324	16	also	also	ADV
ajst-28813	324	17	confirmed	confirm	VERB
ajst-28813	324	18	the	the	DET
ajst-28813	324	19	accuracy	accuracy	NOUN
ajst-28813	324	20	of	of	ADP
ajst-28813	324	21	the	the	DET
ajst-28813	324	22	model	model	NOUN
ajst-28813	324	23	,	,	PUNCT
ajst-28813	324	24	with	with	SCONJ
ajst-28813	324	25	the	the	DET
ajst-28813	324	26	error	error	NOUN
ajst-28813	324	27	rate	rate	NOUN
ajst-28813	324	28	maintained	maintain	VERB
ajst-28813	324	29	at	at	ADP
ajst-28813	324	30	a	a	DET
ajst-28813	324	31	low	low	ADJ
ajst-28813	324	32	level	level	NOUN
ajst-28813	324	33	,	,	PUNCT
ajst-28813	324	34	which	which	PRON
ajst-28813	324	35	further	far	ADV
ajst-28813	324	36	supports	support	VERB
ajst-28813	324	37	the	the	DET
ajst-28813	324	38	effectiveness	effectiveness	NOUN
ajst-28813	324	39	and	and	CCONJ
ajst-28813	324	40	stability	stability	NOUN
ajst-28813	324	41	of	of	ADP
ajst-28813	324	42	esn	esn	PROPN
ajst-28813	324	43	network	network	NOUN
ajst-28813	324	44	in	in	ADP
ajst-28813	324	45	the	the	DET
ajst-28813	324	46	prediction	prediction	NOUN
ajst-28813	324	47	of	of	ADP
ajst-28813	324	48	electric	electric	ADJ
ajst-28813	324	49	submersible	submersible	ADJ
ajst-28813	324	50	pump	pump	NOUN
ajst-28813	324	51	well	well	NOUN
ajst-28813	324	52	data	datum	NOUN
ajst-28813	324	53	.	.	PUNCT
ajst-28813	325	1	in	in	ADP
ajst-28813	325	2	conclusion	conclusion	NOUN
ajst-28813	325	3	,	,	PUNCT
ajst-28813	325	4	the	the	DET
ajst-28813	325	5	esn	esn	PROPN
ajst-28813	325	6	network	network	PROPN
ajst-28813	325	7	model	model	NOUN
ajst-28813	325	8	shows	show	VERB
ajst-28813	325	9	its	its	PRON
ajst-28813	325	10	significant	significant	ADJ
ajst-28813	325	11	advantages	advantage	NOUN
ajst-28813	325	12	and	and	CCONJ
ajst-28813	325	13	reliability	reliability	NOUN
ajst-28813	325	14	in	in	ADP
ajst-28813	325	15	the	the	DET
ajst-28813	325	16	prediction	prediction	NOUN
ajst-28813	325	17	application	application	NOUN
ajst-28813	325	18	of	of	ADP
ajst-28813	325	19	submersible	submersible	ADJ
ajst-28813	325	20	pump	pump	NOUN
ajst-28813	325	21	well	well	NOUN
ajst-28813	325	22	data	datum	NOUN
ajst-28813	325	23	.	.	PUNCT
ajst-28813	326	1	table	table	NOUN
ajst-28813	326	2	4	4	NUM
ajst-28813	326	3	-	-	SYM
ajst-28813	326	4	2	2	NUM
ajst-28813	326	5	.	.	PUNCT
ajst-28813	326	6	comparison	comparison	NOUN
ajst-28813	326	7	table	table	NOUN
ajst-28813	326	8	of	of	ADP
ajst-28813	326	9	the	the	DET
ajst-28813	326	10	influence	influence	NOUN
ajst-28813	326	11	of	of	ADP
ajst-28813	326	12	input	input	NOUN
ajst-28813	326	13	data	datum	NOUN
ajst-28813	326	14	change	change	VERB
ajst-28813	326	15	speed	speed	NOUN
ajst-28813	326	16	on	on	ADP
ajst-28813	326	17	prediction	prediction	NOUN
ajst-28813	326	18	accuracy	accuracy	NOUN
ajst-28813	326	19	bhp	bhp	PROPN
ajst-28813	326	20	whp	whp	PROPN
ajst-28813	326	21	q	q	PROPN
ajst-28813	326	22	mse	mse	PROPN
ajst-28813	326	23	3.47ｅ9	3.47ｅ9	NUM
ajst-28813	326	24	4.91ｅ9	4.91ｅ9	NUM
ajst-28813	326	25	1.87ｅ-7	1.87ｅ-7	NUM
ajst-28813	326	26	6	6	NUM
ajst-28813	326	27	.	.	PUNCT
ajst-28813	327	1	conclusion	conclusion	NOUN
ajst-28813	327	2	by	by	ADP
ajst-28813	327	3	comparative	comparative	ADJ
ajst-28813	327	4	analysis	analysis	NOUN
ajst-28813	327	5	of	of	ADP
ajst-28813	327	6	esn	esn	PROPN
ajst-28813	327	7	network	network	PROPN
ajst-28813	327	8	model	model	NOUN
ajst-28813	327	9	with	with	ADP
ajst-28813	327	10	other	other	ADJ
ajst-28813	327	11	neural	neural	ADJ
ajst-28813	327	12	network	network	NOUN
ajst-28813	327	13	methods	method	NOUN
ajst-28813	327	14	,	,	PUNCT
ajst-28813	327	15	we	we	PRON
ajst-28813	327	16	can	can	AUX
ajst-28813	327	17	conclude	conclude	VERB
ajst-28813	327	18	that	that	SCONJ
ajst-28813	327	19	esn	esn	PROPN
ajst-28813	327	20	has	have	VERB
ajst-28813	327	21	obvious	obvious	ADJ
ajst-28813	327	22	advantages	advantage	NOUN
ajst-28813	327	23	in	in	ADP
ajst-28813	327	24	handling	handle	VERB
ajst-28813	327	25	the	the	DET
ajst-28813	327	26	electric	electric	ADJ
ajst-28813	327	27	submersible	submersible	ADJ
ajst-28813	327	28	pump	pump	NOUN
ajst-28813	327	29	well	well	ADJ
ajst-28813	327	30	data	datum	NOUN
ajst-28813	327	31	prediction	prediction	NOUN
ajst-28813	327	32	task	task	NOUN
ajst-28813	327	33	.	.	PUNCT
ajst-28813	328	1	esn	esn	PROPN
ajst-28813	328	2	network	network	PROPN
ajst-28813	328	3	is	be	AUX
ajst-28813	328	4	not	not	PART
ajst-28813	328	5	only	only	ADV
ajst-28813	328	6	more	more	ADV
ajst-28813	328	7	efficient	efficient	ADJ
ajst-28813	328	8	in	in	ADP
ajst-28813	328	9	model	model	NOUN
ajst-28813	328	10	construction	construction	NOUN
ajst-28813	328	11	and	and	CCONJ
ajst-28813	328	12	training	training	NOUN
ajst-28813	328	13	,	,	PUNCT
ajst-28813	328	14	but	but	CCONJ
ajst-28813	328	15	also	also	ADV
ajst-28813	328	16	shows	show	VERB
ajst-28813	328	17	good	good	ADJ
ajst-28813	328	18	generalization	generalization	NOUN
ajst-28813	328	19	ability	ability	NOUN
ajst-28813	328	20	and	and	CCONJ
ajst-28813	328	21	stability	stability	NOUN
ajst-28813	328	22	in	in	ADP
ajst-28813	328	23	practical	practical	ADJ
ajst-28813	328	24	application	application	NOUN
ajst-28813	328	25	.	.	PUNCT
ajst-28813	329	1	moreover	moreover	ADV
ajst-28813	329	2	,	,	PUNCT
ajst-28813	329	3	the	the	DET
ajst-28813	329	4	online	online	ADJ
ajst-28813	329	5	learning	learn	VERB
ajst-28813	329	6	ability	ability	NOUN
ajst-28813	329	7	of	of	ADP
ajst-28813	329	8	the	the	DET
ajst-28813	329	9	esn	esn	PROPN
ajst-28813	329	10	network	network	NOUN
ajst-28813	329	11	enables	enable	VERB
ajst-28813	329	12	it	it	PRON
ajst-28813	329	13	to	to	PART
ajst-28813	329	14	adapt	adapt	VERB
ajst-28813	329	15	to	to	ADP
ajst-28813	329	16	the	the	DET
ajst-28813	329	17	dynamic	dynamic	ADJ
ajst-28813	329	18	changing	change	VERB
ajst-28813	329	19	characteristics	characteristic	NOUN
ajst-28813	329	20	of	of	ADP
ajst-28813	329	21	the	the	DET
ajst-28813	329	22	electric	electric	ADJ
ajst-28813	329	23	submersible	submersible	ADJ
ajst-28813	329	24	pump	pump	NOUN
ajst-28813	329	25	system	system	NOUN
ajst-28813	329	26	,	,	PUNCT
ajst-28813	329	27	which	which	PRON
ajst-28813	329	28	has	have	VERB
ajst-28813	329	29	important	important	ADJ
ajst-28813	329	30	practical	practical	ADJ
ajst-28813	329	31	significance	significance	NOUN
ajst-28813	329	32	for	for	ADP
ajst-28813	329	33	monitoring	monitoring	NOUN
ajst-28813	329	34	and	and	CCONJ
ajst-28813	329	35	controlling	control	VERB
ajst-28813	329	36	the	the	DET
ajst-28813	329	37	production	production	NOUN
ajst-28813	329	38	process	process	NOUN
ajst-28813	329	39	of	of	ADP
ajst-28813	329	40	the	the	DET
ajst-28813	329	41	electric	electric	ADJ
ajst-28813	329	42	submersible	submersible	ADJ
ajst-28813	329	43	pump	pump	NOUN
ajst-28813	329	44	well	well	ADV
ajst-28813	329	45	in	in	ADP
ajst-28813	329	46	real	real	ADJ
ajst-28813	329	47	time	time	NOUN
ajst-28813	329	48	.	.	PUNCT
ajst-28813	330	1	therefore	therefore	ADV
ajst-28813	330	2	,	,	PUNCT
ajst-28813	330	3	esn	esn	PROPN
ajst-28813	330	4	network	network	PROPN
ajst-28813	330	5	model	model	NOUN
ajst-28813	330	6	has	have	VERB
ajst-28813	330	7	broad	broad	ADJ
ajst-28813	330	8	application	application	NOUN
ajst-28813	330	9	prospect	prospect	NOUN
ajst-28813	330	10	and	and	CCONJ
ajst-28813	330	11	popularization	popularization	NOUN
ajst-28813	330	12	value	value	NOUN
ajst-28813	330	13	in	in	ADP
ajst-28813	330	14	the	the	DET
ajst-28813	330	15	field	field	NOUN
ajst-28813	330	16	of	of	ADP
ajst-28813	330	17	submersible	submersible	ADJ
ajst-28813	330	18	pump	pump	NOUN
ajst-28813	330	19	well	well	ADJ
ajst-28813	330	20	data	datum	NOUN
ajst-28813	330	21	prediction	prediction	NOUN
ajst-28813	330	22	.	.	PUNCT
ajst-28813	331	1	259	259	NUM
ajst-28813	331	2	references	reference	NOUN
ajst-28813	331	3	[	[	X
ajst-28813	331	4	1	1	NUM
ajst-28813	331	5	]	]	X
ajst-28813	331	6	ma	ma	PROPN
ajst-28813	331	7	,	,	PUNCT
ajst-28813	331	8	q.	q.	PROPN
ajst-28813	331	9	,	,	PUNCT
ajst-28813	331	10	sun	sun	PROPN
ajst-28813	331	11	,	,	PUNCT
ajst-28813	331	12	s.	s.	PROPN
ajst-28813	331	13	,	,	PUNCT
ajst-28813	331	14	&	&	CCONJ
ajst-28813	331	15	li	li	PROPN
ajst-28813	331	16	,	,	PUNCT
ajst-28813	331	17	y.	y.	PROPN
ajst-28813	331	18	(	(	PUNCT
ajst-28813	331	19	2019	2019	NUM
ajst-28813	331	20	)	)	PUNCT
ajst-28813	331	21	.	.	PUNCT
ajst-28813	332	1	echo	echo	VERB
ajst-28813	332	2	state	state	NOUN
ajst-28813	332	3	network	network	NOUN
ajst-28813	332	4	for	for	ADP
ajst-28813	332	5	multistep	multistep	ADJ
ajst-28813	332	6	ahead	ahead	ADV
ajst-28813	332	7	wind	wind	NOUN
ajst-28813	332	8	speed	speed	NOUN
ajst-28813	332	9	forecasting[j	forecasting[j	NOUN
ajst-28813	332	10	]	]	PUNCT
ajst-28813	332	11	.	.	PUNCT
ajst-28813	333	1	energy	energy	NOUN
ajst-28813	333	2	conversion	conversion	NOUN
ajst-28813	333	3	and	and	CCONJ
ajst-28813	333	4	management	management	NOUN
ajst-28813	333	5	,	,	PUNCT
ajst-28813	333	6	180	180	NUM
ajst-28813	333	7	,	,	PUNCT
ajst-28813	333	8	783	783	NUM
ajst-28813	333	9	-	-	SYM
ajst-28813	333	10	795	795	NUM
ajst-28813	333	11	.	.	PUNCT
ajst-28813	334	1	[	[	X
ajst-28813	334	2	2	2	NUM
ajst-28813	334	3	]	]	PUNCT
ajst-28813	334	4	jean	jean	PROPN
ajst-28813	334	5	p.	p.	PROPN
ajst-28813	334	6	jordanou	jordanou	PROPN
ajst-28813	334	7	,	,	PUNCT
ajst-28813	334	8	iver	iver	PROPN
ajst-28813	334	9	osnes	osne	NOUN
ajst-28813	334	10	,	,	PUNCT
ajst-28813	334	11	sondre	sondre	PROPN
ajst-28813	334	12	b.	b.	PROPN
ajst-28813	334	13	hernes	hernes	PROPN
ajst-28813	334	14	,	,	PUNCT
ajst-28813	334	15	eduardo	eduardo	PROPN
ajst-28813	334	16	camponogara	camponogara	PROPN
ajst-28813	334	17	,	,	PUNCT
ajst-28813	334	18	eric	eric	PROPN
ajst-28813	334	19	aislan	aislan	PROPN
ajst-28813	334	20	antonelo	antonelo	PROPN
ajst-28813	334	21	,	,	PUNCT
ajst-28813	334	22	lars	lars	PROPN
ajst-28813	334	23	imsland	imsland	PROPN
ajst-28813	334	24	,	,	PUNCT
ajst-28813	334	25	nonlinear	nonlinear	ADJ
ajst-28813	334	26	model	model	NOUN
ajst-28813	334	27	predictive	predictive	PROPN
ajst-28813	334	28	control	control	NOUN
ajst-28813	334	29	of	of	ADP
ajst-28813	334	30	electrical	electrical	ADJ
ajst-28813	334	31	submersible	submersible	ADJ
ajst-28813	334	32	pumps	pump	NOUN
ajst-28813	334	33	based	base	VERB
ajst-28813	334	34	on	on	ADP
ajst-28813	334	35	echo	echo	PROPN
ajst-28813	334	36	state	state	PROPN
ajst-28813	334	37	networks[j	networks[j	PROPN
ajst-28813	334	38	]	]	PUNCT
ajst-28813	334	39	,	,	PUNCT
ajst-28813	334	40	advanced	advanced	ADJ
ajst-28813	334	41	engineering	engineering	NOUN
ajst-28813	334	42	informatics	informatic	NOUN
ajst-28813	334	43	,	,	PUNCT
ajst-28813	334	44	volume	volume	VERB
ajst-28813	334	45	52,2022,101553,issn	52,2022,101553,issn	NUM
ajst-28813	334	46	1474	1474	NUM
ajst-28813	334	47	-	-	SYM
ajst-28813	334	48	0346	0346	NUM
ajst-28813	334	49	.	.	PUNCT
ajst-28813	335	1	[	[	X
ajst-28813	335	2	3	3	NUM
ajst-28813	335	3	]	]	X
ajst-28813	335	4	binder	binder	NOUN
ajst-28813	335	5	,	,	PUNCT
ajst-28813	335	6	b.	b.	PROPN
ajst-28813	335	7	j.	j.	PROPN
ajst-28813	335	8	t.	t.	PROPN
ajst-28813	335	9	kufoalor	kufoalor	PROPN
ajst-28813	335	10	,	,	PUNCT
ajst-28813	335	11	d.	d.	PROPN
ajst-28813	335	12	k.	k.	PROPN
ajst-28813	335	13	m.	m.	PROPN
ajst-28813	335	14	pavlov	pavlov	PROPN
ajst-28813	335	15	,	,	PUNCT
ajst-28813	335	16	a.	a.	PROPN
ajst-28813	335	17	&	&	CCONJ
ajst-28813	335	18	johansen	johansen	PROPN
ajst-28813	335	19	,	,	PUNCT
ajst-28813	335	20	t.	t.	PROPN
ajst-28813	335	21	a.	a.	NOUN
ajst-28813	335	22	embedded	embed	VERB
ajst-28813	335	23	model	model	PROPN
ajst-28813	335	24	predictive	predictive	PROPN
ajst-28813	335	25	control	control	NOUN
ajst-28813	335	26	for	for	ADP
ajst-28813	335	27	an	an	DET
ajst-28813	335	28	electric	electric	ADJ
ajst-28813	335	29	submersible	submersible	ADJ
ajst-28813	335	30	pump	pump	NOUN
ajst-28813	335	31	on	on	ADP
ajst-28813	335	32	a	a	DET
ajst-28813	335	33	programmable	programmable	ADJ
ajst-28813	335	34	logic	logic	NOUN
ajst-28813	335	35	controller[j	controller[j	NOUN
ajst-28813	335	36	]	]	PUNCT
ajst-28813	335	37	,	,	PUNCT
ajst-28813	335	38	2014	2014	NUM
ajst-28813	335	39	ieee	ieee	NOUN
ajst-28813	335	40	conference	conference	NOUN
ajst-28813	335	41	on	on	ADP
ajst-28813	335	42	control	control	NOUN
ajst-28813	335	43	applications	application	NOUN
ajst-28813	335	44	(	(	PUNCT
ajst-28813	335	45	cca	cca	PROPN
ajst-28813	335	46	)	)	PUNCT
ajst-28813	335	47	,	,	PUNCT
ajst-28813	335	48	juan	juan	PROPN
ajst-28813	335	49	les	les	PROPN
ajst-28813	335	50	antibes	antibes	PROPN
ajst-28813	335	51	,	,	PUNCT
ajst-28813	335	52	france	france	PROPN
ajst-28813	335	53	,	,	PUNCT
ajst-28813	335	54	2014	2014	NUM
ajst-28813	335	55	,	,	PUNCT
ajst-28813	335	56	pp	pp	ADJ
ajst-28813	335	57	.	.	PUNCT
ajst-28813	336	1	579	579	NUM
ajst-28813	336	2	-	-	SYM
ajst-28813	336	3	585	585	NUM
ajst-28813	336	4	.	.	PUNCT
ajst-28813	337	1	[	[	X
ajst-28813	337	2	4	4	X
ajst-28813	337	3	]	]	PUNCT
ajst-28813	337	4	strand	strand	NOUN
ajst-28813	337	5	s.	s.	PROPN
ajst-28813	337	6	and	and	CCONJ
ajst-28813	337	7	sagli	sagli	PROPN
ajst-28813	337	8	,	,	PUNCT
ajst-28813	337	9	j.	j.	PROPN
ajst-28813	337	10	r.	r.	PROPN
ajst-28813	337	11	mpc	mpc	PROPN
ajst-28813	337	12	in	in	ADP
ajst-28813	337	13	statoil	statoil	PROPN
ajst-28813	337	14	–	–	PUNCT
ajst-28813	337	15	advantages	advantage	NOUN
ajst-28813	337	16	with	with	ADP
ajst-28813	337	17	inhousetechnology	inhousetechnology	NOUN
ajst-28813	337	18	,	,	PUNCT
ajst-28813	337	19	in	in	ADP
ajst-28813	337	20	int	int	NOUN
ajst-28813	337	21	.	.	PUNCT
ajst-28813	338	1	symp[j	symp[j	VERB
ajst-28813	338	2	]	]	PUNCT
ajst-28813	338	3	.	.	PUNCT
ajst-28813	339	1	advanced	advanced	ADJ
ajst-28813	339	2	control	control	PROPN
ajst-28813	339	3	chemical	chemical	PROPN
ajst-28813	339	4	processes(adchem	processes(adchem	PROPN
ajst-28813	339	5	)	)	PUNCT
ajst-28813	339	6	,	,	PUNCT
ajst-28813	339	7	hong	hong	PROPN
ajst-28813	339	8	kong	kong	PROPN
ajst-28813	339	9	,	,	PUNCT
ajst-28813	339	10	2003	2003	NUM
ajst-28813	339	11	,	,	PUNCT
ajst-28813	339	12	pp	pp	ADJ
ajst-28813	339	13	.	.	PUNCT
ajst-28813	340	1	97–103	97–103	NUM
ajst-28813	340	2	.	.	PUNCT
ajst-28813	341	1	[	[	X
ajst-28813	341	2	5	5	NUM
ajst-28813	341	3	]	]	X
ajst-28813	341	4	abb	abb	ADJ
ajst-28813	341	5	automation	automation	NOUN
ajst-28813	341	6	products	product	NOUN
ajst-28813	341	7	ac500	ac500	PROPN
ajst-28813	341	8	,	,	PUNCT
ajst-28813	341	9	cp400	cp400	NOUN
ajst-28813	341	10	,	,	PUNCT
ajst-28813	341	11	cp600	cp600	PROPN
ajst-28813	341	12	,	,	PUNCT
ajst-28813	341	13	digivis	digivi	VERB
ajst-28813	341	14	500,wireless	500,wireless	NUM
ajst-28813	341	15	.	.	PUNCT
ajst-28813	342	1	[	[	X
ajst-28813	342	2	online	online	X
ajst-28813	342	3	]	]	X
ajst-28813	342	4	.	.	PUNCT
ajst-28813	343	1	available	available	ADJ
ajst-28813	343	2	:	:	PUNCT
ajst-28813	344	1	www.abb.com	www.abb.com	X
ajst-28813	345	1	[	[	X
ajst-28813	345	2	6	6	NUM
ajst-28813	345	3	]	]	X
ajst-28813	345	4	delou	delou	NOUN
ajst-28813	345	5	,	,	PUNCT
ajst-28813	345	6	p.	p.	PROPN
ajst-28813	345	7	de	de	PROPN
ajst-28813	345	8	a.	a.	PROPN
ajst-28813	345	9	azevedo	azevedo	PROPN
ajst-28813	345	10	,	,	PUNCT
ajst-28813	345	11	julia	julia	PROPN
ajst-28813	345	12	p.	p.	PROPN
ajst-28813	345	13	a.	a.	PROPN
ajst-28813	345	14	de	de	PROPN
ajst-28813	345	15	,	,	PUNCT
ajst-28813	345	16	dinesh	dinesh	PROPN
ajst-28813	345	17	krishnamoorthy	krishnamoorthy	PROPN
ajst-28813	345	18	,	,	PUNCT
ajst-28813	345	19	maurício	maurício	NOUN
ajst-28813	345	20	b.	b.	PROPN
ajst-28813	345	21	de	de	PROPN
ajst-28813	345	22	souza	souza	PROPN
ajst-28813	345	23	,	,	PUNCT
ajst-28813	345	24	argimiro	argimiro	PROPN
ajst-28813	345	25	r.	r.	PROPN
ajst-28813	345	26	secchi	secchi	PROPN
ajst-28813	345	27	,	,	PUNCT
ajst-28813	345	28	model	model	NOUN
ajst-28813	345	29	predictive	predictive	ADJ
ajst-28813	345	30	control	control	NOUN
ajst-28813	345	31	with	with	ADP
ajst-28813	345	32	adaptive	adaptive	ADJ
ajst-28813	345	33	strategy	strategy	NOUN
ajst-28813	345	34	applied	apply	VERB
ajst-28813	345	35	to	to	ADP
ajst-28813	345	36	an	an	DET
ajst-28813	345	37	electric	electric	ADJ
ajst-28813	345	38	submersible	submersible	ADJ
ajst-28813	345	39	pump	pump	NOUN
ajst-28813	345	40	in	in	ADP
ajst-28813	345	41	a	a	DET
ajst-28813	345	42	subsea	subsea	NOUN
ajst-28813	345	43	environment[j	environment[j	NOUN
ajst-28813	345	44	]	]	X
ajst-28813	345	45	,	,	PUNCT
ajst-28813	345	46	ifacpapers	ifacpaper	NOUN
ajst-28813	345	47	online	online	ADV
ajst-28813	345	48	,	,	PUNCT
ajst-28813	345	49	volume	volume	NOUN
ajst-28813	345	50	52	52	NUM
ajst-28813	345	51	,	,	PUNCT
ajst-28813	345	52	issue	issue	NOUN
ajst-28813	345	53	1,2019:784	1,2019:784	NUM
ajst-28813	345	54	-	-	PUNCT
ajst-28813	345	55	789	789	NUM
ajst-28813	345	56	.	.	PUNCT
ajst-28813	346	1	[	[	X
ajst-28813	346	2	7	7	NUM
ajst-28813	346	3	]	]	X
ajst-28813	346	4	fontes	fonte	NOUN
ajst-28813	346	5	,	,	PUNCT
ajst-28813	346	6	r.	r.	PROPN
ajst-28813	346	7	m.	m.	PROPN
ajst-28813	346	8	santana	santana	PROPN
ajst-28813	346	9	,	,	PUNCT
ajst-28813	346	10	daniel	daniel	PROPN
ajst-28813	346	11	d.	d.	PROPN
ajst-28813	346	12	&	&	CCONJ
ajst-28813	346	13	martins	martins	PROPN
ajst-28813	346	14	,	,	PUNCT
ajst-28813	346	15	m	m	PROPN
ajst-28813	346	16	a.	a.	PROPN
ajst-28813	346	17	f.	f.	PROPN
ajst-28813	346	18	(	(	PUNCT
ajst-28813	346	19	2022	2022	NUM
ajst-28813	346	20	)	)	PUNCT
ajst-28813	346	21	.	.	PUNCT
ajst-28813	347	1	an	an	DET
ajst-28813	347	2	mpc	mpc	PROPN
ajst-28813	347	3	auto	auto	NOUN
ajst-28813	347	4	-	-	PUNCT
ajst-28813	347	5	tuning	tune	VERB
ajst-28813	347	6	framework	framework	NOUN
ajst-28813	347	7	for	for	ADP
ajst-28813	347	8	tracking	track	VERB
ajst-28813	347	9	economic	economic	ADJ
ajst-28813	347	10	goals	goal	NOUN
ajst-28813	347	11	of	of	ADP
ajst-28813	347	12	an	an	DET
ajst-28813	347	13	esp	esp	ADV
ajst-28813	347	14	-	-	PUNCT
ajst-28813	347	15	lifted	lift	VERB
ajst-28813	347	16	oil	oil	NOUN
ajst-28813	347	17	well[j	well[j	NOUN
ajst-28813	347	18	]	]	PUNCT
ajst-28813	347	19	.	.	PUNCT
ajst-28813	348	1	journal	journal	PROPN
ajst-28813	348	2	of	of	ADP
ajst-28813	348	3	petroleum	petroleum	NOUN
ajst-28813	348	4	science	science	NOUN
ajst-28813	348	5	and	and	CCONJ
ajst-28813	348	6	engineering	engineering	NOUN
ajst-28813	348	7	,	,	PUNCT
ajst-28813	348	8	volume	volume	NOUN
ajst-28813	348	9	217	217	NUM
ajst-28813	348	10	,	,	PUNCT
ajst-28813	348	11	2022	2022	NUM
ajst-28813	348	12	,	,	PUNCT
ajst-28813	348	13	110867	110867	NUM
ajst-28813	348	14	,	,	PUNCT
ajst-28813	348	15	issn	issn	PROPN
ajst-28813	348	16	0920	0920	NUM
ajst-28813	348	17	-	-	SYM
ajst-28813	348	18	4105	4105	NUM
ajst-28813	348	19	.	.	PUNCT
ajst-28813	349	1	[	[	X
ajst-28813	349	2	8	8	NUM
ajst-28813	349	3	]	]	X
ajst-28813	349	4	santana	santana	PROPN
ajst-28813	349	5	,	,	PUNCT
ajst-28813	349	6	b.	b.	PROPN
ajst-28813	349	7	a.	a.	PROPN
ajst-28813	349	8	matos	matos	PROPN
ajst-28813	349	9	vs	vs	ADP
ajst-28813	349	10	,	,	PUNCT
ajst-28813	349	11	santana	santana	PROPN
ajst-28813	349	12	dd	dd	PROPN
ajst-28813	349	13	,	,	PUNCT
ajst-28813	349	14	martins	martin	NOUN
ajst-28813	349	15	m.	m.	NOUN
ajst-28813	349	16	a.	a.	PROPN
ajst-28813	349	17	f.	f.	PROPN
ajst-28813	349	18	embedded	embed	VERB
ajst-28813	349	19	mpc	mpc	NOUN
ajst-28813	349	20	strategies	strategy	NOUN
ajst-28813	349	21	for	for	ADP
ajst-28813	349	22	esp	esp	ADV
ajst-28813	349	23	-	-	PUNCT
ajst-28813	349	24	lifted	lift	VERB
ajst-28813	349	25	oil	oil	NOUN
ajst-28813	349	26	wells	well	NOUN
ajst-28813	349	27	:	:	PUNCT
ajst-28813	349	28	hardware	hardware	NOUN
ajst-28813	349	29	-	-	PUNCT
ajst-28813	349	30	in	in	ADP
ajst-28813	349	31	-	-	PUNCT
ajst-28813	349	32	the	the	DET
ajst-28813	349	33	-	-	PUNCT
ajst-28813	349	34	loop	loop	NOUN
ajst-28813	349	35	performance	performance	NOUN
ajst-28813	349	36	analysis	analysis	NOUN
ajst-28813	349	37	of	of	ADP
ajst-28813	349	38	nonlinear	nonlinear	ADJ
ajst-28813	349	39	and	and	CCONJ
ajst-28813	349	40	robust	robust	ADJ
ajst-28813	349	41	techniques[j].processes	techniques[j].processe	NOUN
ajst-28813	349	42	.	.	PUNCT
ajst-28813	350	1	2023	2023	NUM
ajst-28813	350	2	;	;	PUNCT
ajst-28813	351	1	11(5):1354	11(5):1354	NUM
ajst-28813	351	2	.	.	PUNCT
ajst-28813	352	1	[	[	X
ajst-28813	352	2	9	9	NUM
ajst-28813	352	3	]	]	X
ajst-28813	352	4	lorenz	lorenz	PROPN
ajst-28813	352	5	t.	t.	NOUN
ajst-28813	352	6	biegler	biegler	NOUN
ajst-28813	352	7	.	.	PUNCT
ajst-28813	353	1	efficient	efficient	ADJ
ajst-28813	353	2	solution	solution	NOUN
ajst-28813	353	3	of	of	ADP
ajst-28813	353	4	dynamic	dynamic	ADJ
ajst-28813	353	5	optimization	optimization	NOUN
ajst-28813	353	6	and	and	CCONJ
ajst-28813	353	7	nmpc	nmpc	NOUN
ajst-28813	353	8	problems[m].nonlinear	problems[m].nonlinear	PROPN
ajst-28813	353	9	model	model	PROPN
ajst-28813	353	10	predictive	predictive	PROPN
ajst-28813	353	11	control	control	NOUN
ajst-28813	353	12	,	,	PUNCT
ajst-28813	353	13	2000	2000	NUM
ajst-28813	353	14	,	,	PUNCT
ajst-28813	353	15	volume	volume	NOUN
ajst-28813	353	16	26	26	NUM
ajst-28813	353	17	,	,	PUNCT
ajst-28813	353	18	isbn	isbn	ADJ
ajst-28813	353	19	:	:	PUNCT
ajst-28813	353	20	978	978	NUM
ajst-28813	353	21	-	-	SYM
ajst-28813	353	22	3	3	NUM
ajst-28813	353	23	-	-	PUNCT
ajst-28813	353	24	0348	0348	NUM
ajst-28813	353	25	-	-	PUNCT
ajst-28813	353	26	9554	9554	NUM
ajst-28813	353	27	-	-	SYM
ajst-28813	353	28	5	5	NUM
ajst-28813	353	29	.	.	PUNCT
ajst-28813	354	1	[	[	X
ajst-28813	354	2	10	10	NUM
ajst-28813	354	3	]	]	SYM
ajst-28813	354	4	victor	victor	NOUN
ajst-28813	354	5	m.	m.	NOUN
ajst-28813	354	6	zavala	zavala	PROPN
ajst-28813	354	7	,	,	PUNCT
ajst-28813	354	8	&	&	CCONJ
ajst-28813	354	9	lorenz	lorenz	PROPN
ajst-28813	354	10	t.	t.	PROPN
ajst-28813	354	11	biegler	biegler	NOUN
ajst-28813	354	12	.	.	PUNCT
ajst-28813	355	1	(	(	PUNCT
ajst-28813	355	2	2009	2009	NUM
ajst-28813	355	3	)	)	PUNCT
ajst-28813	355	4	.	.	PUNCT
ajst-28813	356	1	the	the	DET
ajst-28813	356	2	advancedstep	advancedstep	NOUN
ajst-28813	356	3	nmpc	nmpc	NOUN
ajst-28813	356	4	controller	controller	NOUN
ajst-28813	356	5	:	:	PUNCT
ajst-28813	356	6	optimality	optimality	NOUN
ajst-28813	356	7	,	,	PUNCT
ajst-28813	356	8	stability	stability	NOUN
ajst-28813	356	9	and	and	CCONJ
ajst-28813	356	10	robustness[j	robustness[j	NOUN
ajst-28813	356	11	]	]	PUNCT
ajst-28813	356	12	.	.	PUNCT
ajst-28813	357	1	automatica	automatica	PROPN
ajst-28813	357	2	,	,	PUNCT
ajst-28813	357	3	45(1	45(1	NOUN
ajst-28813	357	4	)	)	PUNCT
ajst-28813	357	5	,	,	PUNCT
ajst-28813	357	6	86	86	NUM
ajst-28813	357	7	-	-	SYM
ajst-28813	357	8	93	93	NUM
ajst-28813	357	9	.	.	PUNCT
ajst-28813	358	1	issn	issn	PROPN
ajst-28813	358	2	0005	0005	NUM
ajst-28813	358	3	-	-	SYM
ajst-28813	358	4	1098	1098	NUM
ajst-28813	358	5	.	.	PUNCT
ajst-28813	359	1	[	[	X
ajst-28813	359	2	11	11	NUM
ajst-28813	359	3	]	]	X
ajst-28813	359	4	inga	inga	PROPN
ajst-28813	359	5	j.	j.	PROPN
ajst-28813	359	6	wolf	wolf	PROPN
ajst-28813	359	7	,	,	PUNCT
ajst-28813	359	8	&	&	CCONJ
ajst-28813	359	9	wolfgang	wolfgang	PROPN
ajst-28813	359	10	marquardt	marquardt	PROPN
ajst-28813	359	11	.	.	PUNCT
ajst-28813	360	1	(	(	PUNCT
ajst-28813	360	2	2016	2016	NUM
ajst-28813	360	3	)	)	PUNCT
ajst-28813	360	4	.	.	PUNCT
ajst-28813	361	1	fast	fast	ADJ
ajst-28813	361	2	nmpc	nmpc	NOUN
ajst-28813	361	3	schemes	scheme	NOUN
ajst-28813	361	4	for	for	ADP
ajst-28813	361	5	regulatory	regulatory	ADJ
ajst-28813	361	6	and	and	CCONJ
ajst-28813	361	7	economic	economic	ADJ
ajst-28813	361	8	nmpc	nmpc	NOUN
ajst-28813	361	9	–	–	PUNCT
ajst-28813	361	10	a	a	DET
ajst-28813	361	11	review[j	review[j	NOUN
ajst-28813	361	12	]	]	PUNCT
ajst-28813	361	13	.	.	PUNCT
ajst-28813	362	1	journal	journal	PROPN
ajst-28813	362	2	of	of	ADP
ajst-28813	362	3	process	process	NOUN
ajst-28813	362	4	control	control	NOUN
ajst-28813	362	5	,	,	PUNCT
ajst-28813	362	6	44	44	NUM
ajst-28813	362	7	,	,	PUNCT
ajst-28813	362	8	162	162	NUM
ajst-28813	362	9	-	-	SYM
ajst-28813	362	10	183	183	NUM
ajst-28813	362	11	.	.	PUNCT
ajst-28813	363	1	issn	issn	PROPN
ajst-28813	363	2	0959	0959	NUM
ajst-28813	363	3	-	-	SYM
ajst-28813	363	4	1524	1524	NUM
ajst-28813	363	5	.	.	PUNCT
ajst-28813	364	1	[	[	X
ajst-28813	364	2	12	12	NUM
ajst-28813	364	3	]	]	X
ajst-28813	364	4	s.	s.	PROPN
ajst-28813	364	5	gros	gros	PROPN
ajst-28813	364	6	and	and	CCONJ
ajst-28813	364	7	m.	m.	NOUN
ajst-28813	364	8	zanon	zanon	PROPN
ajst-28813	364	9	,	,	PUNCT
ajst-28813	364	10	data	data	NOUN
ajst-28813	364	11	-	-	PUNCT
ajst-28813	364	12	driven	drive	VERB
ajst-28813	364	13	economic	economic	ADJ
ajst-28813	364	14	nmpc	nmpc	NOUN
ajst-28813	364	15	using	use	VERB
ajst-28813	364	16	reinforcement	reinforcement	NOUN
ajst-28813	364	17	learning[j	learning[j	NOUN
ajst-28813	364	18	]	]	PUNCT
ajst-28813	364	19	,	,	PUNCT
ajst-28813	364	20	ieee	ieee	NOUN
ajst-28813	364	21	transactions	transaction	NOUN
ajst-28813	364	22	on	on	ADP
ajst-28813	364	23	automatic	automatic	ADJ
ajst-28813	364	24	control	control	NOUN
ajst-28813	364	25	,	,	PUNCT
ajst-28813	364	26	vol	vol	NOUN
ajst-28813	364	27	.	.	PROPN
ajst-28813	364	28	65	65	NUM
ajst-28813	364	29	,	,	PUNCT
ajst-28813	364	30	no	no	INTJ
ajst-28813	364	31	.	.	NOUN
ajst-28813	364	32	2	2	NUM
ajst-28813	364	33	,	,	PUNCT
ajst-28813	364	34	pp	pp	ADJ
ajst-28813	364	35	.	.	PUNCT
ajst-28813	365	1	636	636	NUM
ajst-28813	365	2	-	-	SYM
ajst-28813	365	3	648	648	NUM
ajst-28813	365	4	,	,	PUNCT
ajst-28813	365	5	feb	feb	PROPN
ajst-28813	365	6	.	.	PROPN
ajst-28813	365	7	2020	2020	NUM
ajst-28813	365	8	,	,	PUNCT
ajst-28813	365	9	doi	doi	NOUN
ajst-28813	365	10	:	:	PUNCT
ajst-28813	365	11	10.1109	10.1109	NUM
ajst-28813	365	12	/	/	SYM
ajst-28813	365	13	tac.2019.2913768	tac.2019.2913768	PROPN
ajst-28813	365	14	.	.	PUNCT
ajst-28813	366	1	[	[	X
ajst-28813	366	2	13	13	NUM
ajst-28813	366	3	]	]	PUNCT
ajst-28813	366	4	rauber	rauber	PROPN
ajst-28813	366	5	t	t	PROPN
ajst-28813	366	6	w	w	PROPN
ajst-28813	366	7	,	,	PUNCT
ajst-28813	366	8	de	de	X
ajst-28813	366	9	assis	assis	PROPN
ajst-28813	366	10	boldt	boldt	PROPN
ajst-28813	366	11	f	f	PROPN
ajst-28813	366	12	,	,	PUNCT
ajst-28813	366	13	varejao	varejao	PROPN
ajst-28813	366	14	f	f	PROPN
ajst-28813	366	15	m.	m.	PROPN
ajst-28813	366	16	heterogeneous	heterogeneous	ADJ
ajst-28813	366	17	feature	feature	NOUN
ajst-28813	366	18	models	model	NOUN
ajst-28813	366	19	and	and	CCONJ
ajst-28813	366	20	feature	feature	NOUN
ajst-28813	366	21	selection	selection	NOUN
ajst-28813	366	22	applied	apply	VERB
ajst-28813	366	23	to	to	ADP
ajst-28813	366	24	bearing	bear	VERB
ajst-28813	366	25	fault	fault	NOUN
ajst-28813	366	26	diagnosis[j	diagnosis[j	NOUN
ajst-28813	366	27	]	]	PUNCT
ajst-28813	366	28	.	.	PUNCT
ajst-28813	367	1	ieee	ieee	NOUN
ajst-28813	367	2	transactions	transaction	NOUN
ajst-28813	367	3	on	on	ADP
ajst-28813	367	4	industrial	industrial	ADJ
ajst-28813	367	5	electronics	electronic	NOUN
ajst-28813	367	6	,	,	PUNCT
ajst-28813	367	7	2014	2014	NUM
ajst-28813	367	8	,	,	PUNCT
ajst-28813	367	9	62(1	62(1	NUM
ajst-28813	367	10	):	):	PUNCT
ajst-28813	367	11	637	637	NUM
ajst-28813	367	12	-	-	SYM
ajst-28813	367	13	646	646	NUM
ajst-28813	367	14	.	.	PUNCT
ajst-28813	368	1	[	[	X
ajst-28813	368	2	14	14	NUM
ajst-28813	368	3	]	]	X
ajst-28813	368	4	sofia	sofia	PROPN
ajst-28813	368	5	eriksson	eriksson	PROPN
ajst-28813	368	6	,	,	PUNCT
ajst-28813	368	7	jona	jona	PROPN
ajst-28813	368	8	nordqvist	nordqvist	PROPN
ajst-28813	368	9	.	.	PUNCT
ajst-28813	369	1	the	the	DET
ajst-28813	369	2	sherman	sherman	PROPN
ajst-28813	369	3	–	–	PUNCT
ajst-28813	369	4	morrison	morrison	PROPN
ajst-28813	369	5	–	–	PUNCT
ajst-28813	369	6	woodbury	woodbury	NOUN
ajst-28813	369	7	formula	formula	NOUN
ajst-28813	369	8	for	for	ADP
ajst-28813	369	9	the	the	DET
ajst-28813	369	10	moore	moore	PROPN
ajst-28813	369	11	–	–	PUNCT
ajst-28813	369	12	penrose	penrose	NOUN
ajst-28813	369	13	metric	metric	ADJ
ajst-28813	369	14	generalized	generalize	VERB
ajst-28813	369	15	inverse[j].(2024)inverting	inverse[j].(2024)inverte	VERB
ajst-28813	369	16	the	the	DET
ajst-28813	369	17	sum	sum	NOUN
ajst-28813	369	18	of	of	ADP
ajst-28813	369	19	two	two	NUM
ajst-28813	369	20	singular	singular	ADJ
ajst-28813	369	21	matrices	matrix	NOUN
ajst-28813	369	22	.	.	PUNCT
ajst-28813	370	1	results	result	NOUN
ajst-28813	370	2	in	in	ADP
ajst-28813	370	3	applied	applied	ADJ
ajst-28813	370	4	mathematics	mathematic	NOUN
ajst-28813	370	5	22:100463	22:100463	NUM
ajst-28813	370	6	.	.	PUNCT
ajst-28813	371	1	[	[	X
ajst-28813	371	2	15	15	NUM
ajst-28813	371	3	]	]	X
ajst-28813	371	4	richalet	richalet	PROPN
ajst-28813	371	5	j	j	PROPN
ajst-28813	371	6	,	,	PUNCT
ajst-28813	371	7	rault	rault	VERB
ajst-28813	371	8	a.testud	a.testud	ADJ
ajst-28813	371	9	et	et	NOUN
ajst-28813	371	10	al.model	al.model	NOUN
ajst-28813	371	11	predictive	predictive	ADJ
ajst-28813	371	12	heuristic	heuristic	ADJ
ajst-28813	371	13	control	control	NOUN
ajst-28813	371	14	:	:	PUNCT
ajst-28813	371	15	application	application	NOUN
ajst-28813	371	16	to	to	ADP
ajst-28813	371	17	industrial	industrial	ADJ
ajst-28813	371	18	process	process	NOUN
ajst-28813	371	19	[	[	X
ajst-28813	371	20	j	j	X
ajst-28813	371	21	]	]	X
ajst-28813	371	22	.	.	PUNCT
ajst-28813	372	1	automatica	automatica	PROPN
ajst-28813	372	2	,	,	PUNCT
ajst-28813	372	3	1978	1978	NUM
ajst-28813	372	4	,	,	PUNCT
ajst-28813	372	5	14(5	14(5	NUM
ajst-28813	372	6	):	):	PUNCT
ajst-28813	372	7	413	413	NUM
ajst-28813	372	8	-	-	SYM
ajst-28813	372	9	428	428	NUM
ajst-28813	372	10	.	.	PUNCT
ajst-28813	373	1	[	[	X
ajst-28813	373	2	16	16	NUM
ajst-28813	373	3	]	]	PUNCT
ajst-28813	373	4	m.	m.	NOUN
ajst-28813	373	5	morari	morari	PROPN
ajst-28813	373	6	,	,	PUNCT
ajst-28813	373	7	j.	j.	PROPN
ajst-28813	373	8	h.	h.	PROPN
ajst-28813	373	9	lee.applications	lee.applications	PROPN
ajst-28813	373	10	of	of	ADP
ajst-28813	373	11	nonlinear	nonlinear	ADJ
ajst-28813	373	12	model	model	NOUN
ajst-28813	373	13	predictive	predictive	PROPN
ajst-28813	373	14	control	control	NOUN
ajst-28813	373	15	in	in	ADP
ajst-28813	373	16	complex	complex	ADJ
ajst-28813	373	17	industrial	industrial	NOUN
ajst-28813	373	18	[	[	X
ajst-28813	373	19	j].computers	j].computer	NOUN
ajst-28813	373	20	&	&	CCONJ
ajst-28813	373	21	chemical	chemical	NOUN
ajst-28813	373	22	engineering,1999	engineering,1999	NOUN
ajst-28813	373	23	.	.	PUNCT
ajst-28813	374	1	[	[	X
ajst-28813	374	2	17	17	NUM
ajst-28813	374	3	]	]	X
ajst-28813	374	4	d.	d.	PROPN
ajst-28813	374	5	q.	q.	PROPN
ajst-28813	374	6	mayne	mayne	PROPN
ajst-28813	374	7	,	,	PUNCT
ajst-28813	374	8	j.	j.	PROPN
ajst-28813	374	9	b.	b.	PROPN
ajst-28813	374	10	rawlings	rawlings	PROPN
ajst-28813	374	11	,	,	PUNCT
ajst-28813	374	12	c.	c.	PROPN
ajst-28813	374	13	v.	v.	PROPN
ajst-28813	374	14	rao	rao	PROPN
ajst-28813	374	15	,	,	PUNCT
ajst-28813	374	16	p.	p.	PROPN
ajst-28813	374	17	o.	o.	PROPN
ajst-28813	374	18	m.	m.	PROPN
ajst-28813	374	19	scokaert	scokaert	PROPN
ajst-28813	374	20	.	.	PUNCT
ajst-28813	375	1	constrained	constrain	VERB
ajst-28813	375	2	control	control	NOUN
ajst-28813	375	3	and	and	CCONJ
ajst-28813	375	4	estimation	estimation	NOUN
ajst-28813	375	5	:	:	PUNCT
ajst-28813	375	6	an	an	DET
ajst-28813	375	7	optimized	optimize	VERB
ajst-28813	375	8	approach	approach	NOUN
ajst-28813	375	9	[	[	X
ajst-28813	375	10	j	j	X
ajst-28813	375	11	]	]	X
ajst-28813	375	12	.	.	PUNCT
ajst-28813	376	1	ieee	ieee	PROPN
ajst-28813	376	2	,	,	PUNCT
ajst-28813	376	3	2000	2000	NUM
ajst-28813	376	4	.	.	PUNCT