id	sid	tid	token	lemma	pos
ap-1538	1	1	ap-3-12.dvi	ap-3-12.dvi	PROPN
ap-1538	1	2	acta	acta	PROPN
ap-1538	1	3	polytechnica	polytechnica	PROPN
ap-1538	1	4	vol	vol	NOUN
ap-1538	1	5	.	.	PROPN
ap-1538	2	1	52	52	NUM
ap-1538	2	2	no	no	NOUN
ap-1538	2	3	.	.	PUNCT
ap-1538	3	1	3/2012	3/2012	NUM
ap-1538	3	2	a	a	DET
ap-1538	3	3	neural	neural	ADJ
ap-1538	3	4	network	network	NOUN
ap-1538	3	5	model	model	NOUN
ap-1538	3	6	for	for	ADP
ap-1538	3	7	predicting	predict	VERB
ap-1538	3	8	nox	nox	NOUN
ap-1538	3	9	at	at	ADP
ap-1538	3	10	the	the	DET
ap-1538	3	11	mělńık	mělńık	PROPN
ap-1538	3	12	1	1	NUM
ap-1538	3	13	coal	coal	NOUN
ap-1538	3	14	-	-	PUNCT
ap-1538	3	15	powder	powder	NOUN
ap-1538	3	16	power	power	NOUN
ap-1538	3	17	plant	plant	NOUN
ap-1538	3	18	ivo	ivo	PROPN
ap-1538	3	19	bukovský1	bukovský1	PROPN
ap-1538	3	20	,	,	PUNCT
ap-1538	3	21	michal	michal	PROPN
ap-1538	3	22	kolovratńık2	kolovratńık2	PROPN
ap-1538	3	23	1czech	1czech	NUM
ap-1538	3	24	technical	technical	ADJ
ap-1538	3	25	university	university	NOUN
ap-1538	3	26	in	in	ADP
ap-1538	3	27	prague	prague	PROPN
ap-1538	3	28	,	,	PUNCT
ap-1538	3	29	faculty	faculty	NOUN
ap-1538	3	30	of	of	ADP
ap-1538	3	31	mechanical	mechanical	ADJ
ap-1538	3	32	engineering	engineering	NOUN
ap-1538	3	33	,	,	PUNCT
ap-1538	3	34	department	department	NOUN
ap-1538	3	35	of	of	ADP
ap-1538	3	36	instrumentation	instrumentation	NOUN
ap-1538	3	37	and	and	CCONJ
ap-1538	3	38	control	control	PROPN
ap-1538	3	39	engineering	engineering	NOUN
ap-1538	3	40	,	,	PUNCT
ap-1538	3	41	technická	technická	NOUN
ap-1538	3	42	4	4	NUM
ap-1538	3	43	,	,	PUNCT
ap-1538	3	44	166	166	NUM
ap-1538	3	45	07	07	NUM
ap-1538	3	46	prague	prague	NOUN
ap-1538	3	47	,	,	PUNCT
ap-1538	3	48	czech	czech	PROPN
ap-1538	3	49	republic	republic	PROPN
ap-1538	3	50	2czech	2czech	PROPN
ap-1538	3	51	technical	technical	PROPN
ap-1538	3	52	university	university	PROPN
ap-1538	3	53	in	in	ADP
ap-1538	3	54	prague	prague	PROPN
ap-1538	3	55	,	,	PUNCT
ap-1538	3	56	faculty	faculty	NOUN
ap-1538	3	57	of	of	ADP
ap-1538	3	58	mechanical	mechanical	ADJ
ap-1538	3	59	engineering	engineering	NOUN
ap-1538	3	60	,	,	PUNCT
ap-1538	3	61	department	department	NOUN
ap-1538	3	62	of	of	ADP
ap-1538	3	63	energy	energy	NOUN
ap-1538	3	64	engineering	engineering	NOUN
ap-1538	3	65	,	,	PUNCT
ap-1538	3	66	technická	technická	NOUN
ap-1538	3	67	4	4	NUM
ap-1538	3	68	,	,	PUNCT
ap-1538	3	69	166	166	NUM
ap-1538	3	70	07	07	NUM
ap-1538	3	71	prague	prague	NOUN
ap-1538	3	72	,	,	PUNCT
ap-1538	3	73	czech	czech	PROPN
ap-1538	3	74	republic	republic	NOUN
ap-1538	3	75	correspondence	correspondence	NOUN
ap-1538	3	76	to	to	ADP
ap-1538	3	77	:	:	PUNCT
ap-1538	3	78	ivo.bukovsky@fs.cvut.cz	ivo.bukovsky@fs.cvut.cz	ADJ
ap-1538	3	79	abstract	abstract	NOUN
ap-1538	3	80	this	this	DET
ap-1538	3	81	paper	paper	NOUN
ap-1538	3	82	presents	present	VERB
ap-1538	3	83	a	a	DET
ap-1538	3	84	non	non	ADJ
ap-1538	3	85	-	-	ADJ
ap-1538	3	86	conventional	conventional	ADJ
ap-1538	3	87	dynamic	dynamic	ADJ
ap-1538	3	88	neural	neural	ADJ
ap-1538	3	89	network	network	NOUN
ap-1538	3	90	that	that	PRON
ap-1538	3	91	was	be	AUX
ap-1538	3	92	designed	design	VERB
ap-1538	3	93	for	for	ADP
ap-1538	3	94	real	real	ADJ
ap-1538	3	95	time	time	NOUN
ap-1538	3	96	prediction	prediction	NOUN
ap-1538	3	97	of	of	ADP
ap-1538	3	98	nox	nox	NOUN
ap-1538	3	99	at	at	ADP
ap-1538	3	100	the	the	DET
ap-1538	3	101	coal	coal	NOUN
ap-1538	3	102	powder	powder	NOUN
ap-1538	3	103	power	power	NOUN
ap-1538	3	104	plant	plant	NOUN
ap-1538	3	105	mělńık	mělńık	PROPN
ap-1538	3	106	1	1	NUM
ap-1538	3	107	,	,	PUNCT
ap-1538	3	108	and	and	CCONJ
ap-1538	3	109	results	result	NOUN
ap-1538	3	110	on	on	ADP
ap-1538	3	111	real	real	ADJ
ap-1538	3	112	data	datum	NOUN
ap-1538	3	113	are	be	AUX
ap-1538	3	114	shown	show	VERB
ap-1538	3	115	and	and	CCONJ
ap-1538	3	116	discussed	discuss	VERB
ap-1538	3	117	.	.	PUNCT
ap-1538	4	1	the	the	DET
ap-1538	4	2	paper	paper	NOUN
ap-1538	4	3	also	also	ADV
ap-1538	4	4	presents	present	VERB
ap-1538	4	5	the	the	DET
ap-1538	4	6	signal	signal	ADJ
ap-1538	4	7	preprocessing	preprocessing	NOUN
ap-1538	4	8	techniques	technique	NOUN
ap-1538	4	9	,	,	PUNCT
ap-1538	4	10	the	the	DET
ap-1538	4	11	input	input	NOUN
ap-1538	4	12	-	-	PUNCT
ap-1538	4	13	reconfigurable	reconfigurable	NOUN
ap-1538	4	14	architecture	architecture	NOUN
ap-1538	4	15	,	,	PUNCT
ap-1538	4	16	and	and	CCONJ
ap-1538	4	17	the	the	DET
ap-1538	4	18	learning	learn	VERB
ap-1538	4	19	algorithm	algorithm	NOUN
ap-1538	4	20	of	of	ADP
ap-1538	4	21	the	the	DET
ap-1538	4	22	proposed	propose	VERB
ap-1538	4	23	neural	neural	ADJ
ap-1538	4	24	network	network	NOUN
ap-1538	4	25	,	,	PUNCT
ap-1538	4	26	which	which	PRON
ap-1538	4	27	was	be	AUX
ap-1538	4	28	designed	design	VERB
ap-1538	4	29	to	to	PART
ap-1538	4	30	handle	handle	VERB
ap-1538	4	31	the	the	DET
ap-1538	4	32	non	non	ADJ
ap-1538	4	33	-	-	NOUN
ap-1538	4	34	stationarity	stationarity	NOUN
ap-1538	4	35	of	of	ADP
ap-1538	4	36	the	the	DET
ap-1538	4	37	burning	burn	VERB
ap-1538	4	38	process	process	NOUN
ap-1538	4	39	as	as	ADV
ap-1538	4	40	well	well	ADV
ap-1538	4	41	as	as	ADP
ap-1538	4	42	individual	individual	ADJ
ap-1538	4	43	failures	failure	NOUN
ap-1538	4	44	of	of	ADP
ap-1538	4	45	the	the	DET
ap-1538	4	46	measured	measure	VERB
ap-1538	4	47	variables	variable	NOUN
ap-1538	4	48	.	.	PUNCT
ap-1538	5	1	the	the	DET
ap-1538	5	2	advantages	advantage	NOUN
ap-1538	5	3	of	of	ADP
ap-1538	5	4	our	our	PRON
ap-1538	5	5	designed	design	VERB
ap-1538	5	6	neural	neural	ADJ
ap-1538	5	7	network	network	NOUN
ap-1538	5	8	over	over	ADP
ap-1538	5	9	conventional	conventional	ADJ
ap-1538	5	10	neural	neural	ADJ
ap-1538	5	11	networks	network	NOUN
ap-1538	5	12	are	be	AUX
ap-1538	5	13	discussed	discuss	VERB
ap-1538	5	14	.	.	PUNCT
ap-1538	6	1	keywords	keyword	NOUN
ap-1538	6	2	:	:	PUNCT
ap-1538	6	3	dynamic	dynamic	ADJ
ap-1538	6	4	neural	neural	ADJ
ap-1538	6	5	networks	network	NOUN
ap-1538	6	6	,	,	PUNCT
ap-1538	6	7	prediction	prediction	NOUN
ap-1538	6	8	,	,	PUNCT
ap-1538	6	9	nox	nox	NOUN
ap-1538	6	10	emissions	emission	NOUN
ap-1538	6	11	,	,	PUNCT
ap-1538	6	12	signal	signal	ADJ
ap-1538	6	13	processing	processing	NOUN
ap-1538	6	14	.	.	PUNCT
ap-1538	7	1	1	1	NUM
ap-1538	7	2	introduction	introduction	NOUN
ap-1538	7	3	neural	neural	ADJ
ap-1538	7	4	networks	network	NOUN
ap-1538	7	5	(	(	PUNCT
ap-1538	7	6	nn	nn	NOUN
ap-1538	7	7	)	)	PUNCT
ap-1538	7	8	are	be	AUX
ap-1538	7	9	a	a	DET
ap-1538	7	10	popular	popular	ADJ
ap-1538	7	11	and	and	CCONJ
ap-1538	7	12	widely	widely	ADV
ap-1538	7	13	studied	study	VERB
ap-1538	7	14	real	real	ADJ
ap-1538	7	15	data	datum	NOUN
ap-1538	7	16	-	-	PUNCT
ap-1538	7	17	driven	drive	VERB
ap-1538	7	18	nonlinear	nonlinear	NOUN
ap-1538	7	19	modeling	modeling	NOUN
ap-1538	7	20	tool	tool	NOUN
ap-1538	7	21	for	for	ADP
ap-1538	7	22	complicated	complicated	ADJ
ap-1538	7	23	systems	system	NOUN
ap-1538	7	24	where	where	SCONJ
ap-1538	7	25	mathematical	mathematical	ADJ
ap-1538	7	26	-	-	PUNCT
ap-1538	7	27	physical	physical	ADJ
ap-1538	7	28	analysis	analysis	NOUN
ap-1538	7	29	is	be	AUX
ap-1538	7	30	unavailable	unavailable	ADJ
ap-1538	7	31	for	for	ADP
ap-1538	7	32	deriving	derive	VERB
ap-1538	7	33	a	a	DET
ap-1538	7	34	model	model	NOUN
ap-1538	7	35	.	.	PUNCT
ap-1538	8	1	unlike	unlike	ADP
ap-1538	8	2	analytical	analytical	ADJ
ap-1538	8	3	or	or	CCONJ
ap-1538	8	4	linear	linear	ADJ
ap-1538	8	5	models	model	NOUN
ap-1538	8	6	,	,	PUNCT
ap-1538	8	7	nns	nn	NOUN
ap-1538	8	8	are	be	AUX
ap-1538	8	9	black	black	ADJ
ap-1538	8	10	-	-	PUNCT
ap-1538	8	11	box	box	NOUN
ap-1538	8	12	models	model	NOUN
ap-1538	8	13	,	,	PUNCT
ap-1538	8	14	or	or	CCONJ
ap-1538	8	15	sometimes	sometimes	ADV
ap-1538	8	16	gray	gray	ADJ
ap-1538	8	17	-	-	PUNCT
ap-1538	8	18	box	box	NOUN
ap-1538	8	19	models	model	NOUN
ap-1538	8	20	,	,	PUNCT
ap-1538	8	21	that	that	PRON
ap-1538	8	22	require	require	VERB
ap-1538	8	23	proper	proper	ADJ
ap-1538	8	24	design	design	NOUN
ap-1538	8	25	of	of	ADP
ap-1538	8	26	their	their	PRON
ap-1538	8	27	mathematical	mathematical	ADJ
ap-1538	8	28	architecture	architecture	NOUN
ap-1538	8	29	and	and	CCONJ
ap-1538	8	30	an	an	DET
ap-1538	8	31	efficient	efficient	ADJ
ap-1538	8	32	learning	learning	NOUN
ap-1538	8	33	algorithm	algorithm	NOUN
ap-1538	8	34	.	.	PUNCT
ap-1538	9	1	for	for	ADP
ap-1538	9	2	the	the	DET
ap-1538	9	3	principles	principle	NOUN
ap-1538	9	4	of	of	ADP
ap-1538	9	5	fundamental	fundamental	ADJ
ap-1538	9	6	neural	neural	ADJ
ap-1538	9	7	networks	network	NOUN
ap-1538	9	8	we	we	PRON
ap-1538	9	9	may	may	AUX
ap-1538	9	10	refer	refer	VERB
ap-1538	9	11	,	,	PUNCT
ap-1538	9	12	e.g.	e.g.	ADV
ap-1538	9	13	,	,	PUNCT
ap-1538	9	14	to	to	ADP
ap-1538	9	15	[	[	X
ap-1538	9	16	1	1	NUM
ap-1538	9	17	]	]	PUNCT
ap-1538	9	18	,	,	PUNCT
ap-1538	9	19	and	and	CCONJ
ap-1538	9	20	we	we	PRON
ap-1538	9	21	may	may	AUX
ap-1538	9	22	refer	refer	VERB
ap-1538	9	23	to	to	ADP
ap-1538	9	24	less	less	ADV
ap-1538	9	25	recent	recent	ADJ
ap-1538	9	26	reviews	review	NOUN
ap-1538	9	27	[	[	X
ap-1538	9	28	2	2	NUM
ap-1538	9	29	,	,	PUNCT
ap-1538	9	30	3	3	NUM
ap-1538	9	31	]	]	PUNCT
ap-1538	9	32	for	for	ADP
ap-1538	9	33	studies	study	NOUN
ap-1538	9	34	of	of	ADP
ap-1538	9	35	nns	nn	NOUN
ap-1538	9	36	in	in	ADP
ap-1538	9	37	energetic	energetic	ADJ
ap-1538	9	38	processes	process	NOUN
ap-1538	9	39	.	.	PUNCT
ap-1538	10	1	for	for	ADP
ap-1538	10	2	more	more	ADV
ap-1538	10	3	recent	recent	ADJ
ap-1538	10	4	works	work	NOUN
ap-1538	10	5	,	,	PUNCT
ap-1538	10	6	including	include	VERB
ap-1538	10	7	studies	study	NOUN
ap-1538	10	8	of	of	ADP
ap-1538	10	9	conventional	conventional	ADJ
ap-1538	10	10	nn	nn	X
ap-1538	10	11	in	in	ADP
ap-1538	10	12	energetic	energetic	ADJ
ap-1538	10	13	processes	process	NOUN
ap-1538	10	14	,	,	PUNCT
ap-1538	10	15	we	we	PRON
ap-1538	10	16	may	may	AUX
ap-1538	10	17	refer	refer	VERB
ap-1538	10	18	to	to	ADP
ap-1538	10	19	papers	paper	NOUN
ap-1538	10	20	[	[	X
ap-1538	10	21	5–8	5–8	NOUN
ap-1538	10	22	]	]	PUNCT
ap-1538	10	23	,	,	PUNCT
ap-1538	10	24	which	which	PRON
ap-1538	10	25	deal	deal	VERB
ap-1538	10	26	with	with	ADP
ap-1538	10	27	computational	computational	ADJ
ap-1538	10	28	intelligence	intelligence	NOUN
ap-1538	10	29	tools	tool	NOUN
ap-1538	10	30	(	(	PUNCT
ap-1538	10	31	neural	neural	ADJ
ap-1538	10	32	networks	network	NOUN
ap-1538	10	33	,	,	PUNCT
ap-1538	10	34	genetic	genetic	ADJ
ap-1538	10	35	algorithms	algorithm	NOUN
ap-1538	10	36	)	)	PUNCT
ap-1538	10	37	focused	focus	VERB
ap-1538	10	38	on	on	ADP
ap-1538	10	39	biomass	biomass	NOUN
ap-1538	10	40	combustion	combustion	NOUN
ap-1538	10	41	.	.	PUNCT
ap-1538	11	1	the	the	DET
ap-1538	11	2	study	study	NOUN
ap-1538	11	3	of	of	ADP
ap-1538	11	4	non	non	ADJ
ap-1538	11	5	-	-	ADJ
ap-1538	11	6	conventional	conventional	ADJ
ap-1538	11	7	neural	neural	ADJ
ap-1538	11	8	architectures	architecture	NOUN
ap-1538	11	9	for	for	ADP
ap-1538	11	10	modeling	model	VERB
ap-1538	11	11	steady	steady	ADJ
ap-1538	11	12	state	state	NOUN
ap-1538	11	13	hot	hot	ADJ
ap-1538	11	14	steam	steam	NOUN
ap-1538	11	15	turbine	turbine	NOUN
ap-1538	11	16	data	datum	NOUN
ap-1538	11	17	and	and	CCONJ
ap-1538	11	18	for	for	ADP
ap-1538	11	19	modeling	model	VERB
ap-1538	11	20	a	a	DET
ap-1538	11	21	large	large	ADJ
ap-1538	11	22	scale	scale	NOUN
ap-1538	11	23	energetic	energetic	ADJ
ap-1538	11	24	boiler	boiler	NOUN
ap-1538	11	25	can	can	AUX
ap-1538	11	26	be	be	AUX
ap-1538	11	27	found	find	VERB
ap-1538	11	28	in	in	ADP
ap-1538	11	29	[	[	X
ap-1538	11	30	9	9	NUM
ap-1538	11	31	]	]	PUNCT
ap-1538	11	32	,	,	PUNCT
ap-1538	11	33	where	where	SCONJ
ap-1538	11	34	the	the	DET
ap-1538	11	35	advantages	advantage	NOUN
ap-1538	11	36	of	of	ADP
ap-1538	11	37	a	a	DET
ap-1538	11	38	static	static	ADJ
ap-1538	11	39	quadratic	quadratic	ADJ
ap-1538	11	40	neural	neural	ADJ
ap-1538	11	41	unit	unit	NOUN
ap-1538	11	42	(	(	PUNCT
ap-1538	11	43	qnu	qnu	PROPN
ap-1538	11	44	,	,	PUNCT
ap-1538	11	45	[	[	X
ap-1538	11	46	1	1	NUM
ap-1538	11	47	,	,	PUNCT
ap-1538	11	48	4	4	NUM
ap-1538	11	49	]	]	PUNCT
ap-1538	11	50	)	)	PUNCT
ap-1538	11	51	and	and	CCONJ
ap-1538	11	52	a	a	DET
ap-1538	11	53	special	special	ADJ
ap-1538	11	54	quadratic	quadratic	ADJ
ap-1538	11	55	neural	neural	ADJ
ap-1538	11	56	network	network	NOUN
ap-1538	11	57	[	[	X
ap-1538	11	58	9	9	NUM
ap-1538	11	59	]	]	PUNCT
ap-1538	11	60	over	over	ADP
ap-1538	11	61	conventional	conventional	ADJ
ap-1538	11	62	multilayer	multilayer	ADJ
ap-1538	11	63	perceptron	perceptron	PROPN
ap-1538	11	64	neural	neural	PROPN
ap-1538	11	65	networks	network	NOUN
ap-1538	11	66	(	(	PUNCT
ap-1538	11	67	mlp	mlp	NOUN
ap-1538	11	68	)	)	PUNCT
ap-1538	11	69	are	be	AUX
ap-1538	11	70	demonstrated	demonstrate	VERB
ap-1538	11	71	,	,	PUNCT
ap-1538	11	72	with	with	ADP
ap-1538	11	73	reference	reference	NOUN
ap-1538	11	74	to	to	ADP
ap-1538	11	75	the	the	DET
ap-1538	11	76	overfitting	overfitting	ADJ
ap-1538	11	77	and	and	CCONJ
ap-1538	11	78	local	local	ADJ
ap-1538	11	79	minima	minima	PROPN
ap-1538	11	80	problem	problem	NOUN
ap-1538	11	81	,	,	PUNCT
ap-1538	11	82	which	which	PRON
ap-1538	11	83	are	be	AUX
ap-1538	11	84	typical	typical	ADJ
ap-1538	11	85	drawbacks	drawback	NOUN
ap-1538	11	86	of	of	ADP
ap-1538	11	87	mlp	mlp	NOUN
ap-1538	11	88	(	(	PUNCT
ap-1538	11	89	even	even	ADV
ap-1538	11	90	with	with	ADP
ap-1538	11	91	a	a	DET
ap-1538	11	92	single	single	ADJ
ap-1538	11	93	hidden	hide	VERB
ap-1538	11	94	layer	layer	NOUN
ap-1538	11	95	nn	nn	PROPN
ap-1538	11	96	)	)	PUNCT
ap-1538	11	97	.	.	PUNCT
ap-1538	12	1	the	the	DET
ap-1538	12	2	advantage	advantage	NOUN
ap-1538	12	3	of	of	ADP
ap-1538	12	4	qnu	qnu	PROPN
ap-1538	12	5	is	be	AUX
ap-1538	12	6	its	its	PRON
ap-1538	12	7	nonlinear	nonlinear	ADJ
ap-1538	12	8	input	input	NOUN
ap-1538	12	9	-	-	PUNCT
ap-1538	12	10	output	output	NOUN
ap-1538	12	11	mapping	mapping	NOUN
ap-1538	12	12	,	,	PUNCT
ap-1538	12	13	while	while	SCONJ
ap-1538	12	14	this	this	DET
ap-1538	12	15	neural	neural	ADJ
ap-1538	12	16	model	model	NOUN
ap-1538	12	17	is	be	AUX
ap-1538	12	18	linear	linear	ADJ
ap-1538	12	19	in	in	ADP
ap-1538	12	20	its	its	PRON
ap-1538	12	21	parameters	parameter	NOUN
ap-1538	12	22	[	[	X
ap-1538	12	23	10	10	NUM
ap-1538	12	24	]	]	X
ap-1538	12	25	(	(	PUNCT
ap-1538	12	26	unlike	unlike	ADP
ap-1538	12	27	mlp	mlp	NOUN
ap-1538	12	28	)	)	PUNCT
ap-1538	12	29	.	.	PUNCT
ap-1538	13	1	this	this	PRON
ap-1538	13	2	allows	allow	VERB
ap-1538	13	3	us	we	PRON
ap-1538	13	4	to	to	PART
ap-1538	13	5	monitor	monitor	VERB
ap-1538	13	6	and	and	CCONJ
ap-1538	13	7	maintain	maintain	VERB
ap-1538	13	8	adaptation	adaptation	NOUN
ap-1538	13	9	stability	stability	NOUN
ap-1538	13	10	by	by	ADP
ap-1538	13	11	a	a	DET
ap-1538	13	12	comprehensible	comprehensible	ADJ
ap-1538	13	13	evaluation	evaluation	NOUN
ap-1538	13	14	of	of	ADP
ap-1538	13	15	the	the	DET
ap-1538	13	16	eigenvalues	eigenvalue	NOUN
ap-1538	13	17	of	of	ADP
ap-1538	13	18	the	the	DET
ap-1538	13	19	weight	weight	NOUN
ap-1538	13	20	update	update	NOUN
ap-1538	13	21	system	system	NOUN
ap-1538	13	22	[	[	X
ap-1538	13	23	10	10	NUM
ap-1538	13	24	]	]	PUNCT
ap-1538	13	25	that	that	PRON
ap-1538	13	26	offer	offer	VERB
ap-1538	13	27	promising	promise	VERB
ap-1538	13	28	opportunities	opportunity	NOUN
ap-1538	13	29	for	for	ADP
ap-1538	13	30	adaptive	adaptive	ADJ
ap-1538	13	31	monitoring	monitoring	NOUN
ap-1538	13	32	,	,	PUNCT
ap-1538	13	33	modeling	modeling	NOUN
ap-1538	13	34	,	,	PUNCT
ap-1538	13	35	and	and	CCONJ
ap-1538	13	36	process	process	NOUN
ap-1538	13	37	optimization	optimization	NOUN
ap-1538	13	38	by	by	ADP
ap-1538	13	39	adaptive	adaptive	ADJ
ap-1538	13	40	nonlinear	nonlinear	PROPN
ap-1538	13	41	control	control	NOUN
ap-1538	13	42	.	.	PUNCT
ap-1538	14	1	qnu	qnu	PROPN
ap-1538	14	2	can	can	AUX
ap-1538	14	3	be	be	AUX
ap-1538	14	4	seen	see	VERB
ap-1538	14	5	as	as	ADP
ap-1538	14	6	a	a	DET
ap-1538	14	7	component	component	NOUN
ap-1538	14	8	of	of	ADP
ap-1538	14	9	higher	high	ADJ
ap-1538	14	10	-	-	PUNCT
ap-1538	14	11	order	order	NOUN
ap-1538	14	12	neural	neural	ADJ
ap-1538	14	13	network	network	NOUN
ap-1538	14	14	(	(	PUNCT
ap-1538	14	15	honn	honn	PROPN
ap-1538	14	16	)	)	PUNCT
ap-1538	14	17	,	,	PUNCT
ap-1538	14	18	sometimes	sometimes	ADV
ap-1538	14	19	also	also	ADV
ap-1538	14	20	referred	refer	VERB
ap-1538	14	21	to	to	ADP
ap-1538	14	22	as	as	ADP
ap-1538	14	23	a	a	DET
ap-1538	14	24	polynomial	polynomial	ADJ
ap-1538	14	25	neural	neural	ADJ
ap-1538	14	26	network	network	NOUN
ap-1538	14	27	(	(	PUNCT
ap-1538	14	28	pnn	pnn	PROPN
ap-1538	14	29	)	)	PUNCT
ap-1538	14	30	.	.	PUNCT
ap-1538	15	1	the	the	DET
ap-1538	15	2	origins	origin	NOUN
ap-1538	15	3	of	of	ADP
ap-1538	15	4	these	these	DET
ap-1538	15	5	neural	neural	ADJ
ap-1538	15	6	networks	network	NOUN
ap-1538	15	7	can	can	AUX
ap-1538	15	8	be	be	AUX
ap-1538	15	9	traced	trace	VERB
ap-1538	15	10	back	back	ADV
ap-1538	15	11	to	to	ADP
ap-1538	15	12	works	work	NOUN
ap-1538	15	13	[	[	X
ap-1538	15	14	11–14	11–14	NUM
ap-1538	15	15	]	]	PUNCT
ap-1538	15	16	,	,	PUNCT
ap-1538	15	17	while	while	SCONJ
ap-1538	15	18	the	the	DET
ap-1538	15	19	concept	concept	NOUN
ap-1538	15	20	of	of	ADP
ap-1538	15	21	the	the	DET
ap-1538	15	22	standalone	standalone	NOUN
ap-1538	15	23	higher	high	ADJ
ap-1538	15	24	-	-	PUNCT
ap-1538	15	25	order	order	NOUN
ap-1538	15	26	neural	neural	ADJ
ap-1538	15	27	units	unit	NOUN
ap-1538	15	28	(	(	PUNCT
ap-1538	15	29	honus	honus	PROPN
ap-1538	15	30	)	)	PUNCT
ap-1538	15	31	as	as	ADP
ap-1538	15	32	a	a	DET
ap-1538	15	33	building	building	NOUN
ap-1538	15	34	component	component	NOUN
ap-1538	15	35	of	of	ADP
ap-1538	15	36	honn	honn	PROPN
ap-1538	15	37	can	can	AUX
ap-1538	15	38	be	be	AUX
ap-1538	15	39	found	find	VERB
ap-1538	15	40	in	in	ADP
ap-1538	15	41	[	[	X
ap-1538	15	42	1	1	NUM
ap-1538	15	43	]	]	PUNCT
ap-1538	15	44	and	and	CCONJ
ap-1538	15	45	in	in	ADP
ap-1538	15	46	[	[	X
ap-1538	15	47	4	4	NUM
ap-1538	15	48	]	]	PUNCT
ap-1538	15	49	.	.	PUNCT
ap-1538	16	1	the	the	DET
ap-1538	16	2	fundamental	fundamental	ADJ
ap-1538	16	3	gradient	gradient	NOUN
ap-1538	16	4	-	-	PUNCT
ap-1538	16	5	based	base	VERB
ap-1538	16	6	learning	learning	NOUN
ap-1538	16	7	rules	rule	NOUN
ap-1538	16	8	for	for	ADP
ap-1538	16	9	training	train	VERB
ap-1538	16	10	dynamic	dynamic	ADJ
ap-1538	16	11	neural	neural	ADJ
ap-1538	16	12	networks	network	NOUN
ap-1538	16	13	are	be	AUX
ap-1538	16	14	known	know	VERB
ap-1538	16	15	as	as	ADP
ap-1538	16	16	real	real	ADJ
ap-1538	16	17	-	-	PUNCT
ap-1538	16	18	time	time	NOUN
ap-1538	16	19	recurrent	recurrent	ADJ
ap-1538	16	20	learning	learning	NOUN
ap-1538	16	21	(	(	PUNCT
ap-1538	16	22	rtrl	rtrl	NOUN
ap-1538	16	23	)	)	PUNCT
ap-1538	17	1	[	[	X
ap-1538	17	2	15	15	NUM
ap-1538	17	3	]	]	PUNCT
ap-1538	17	4	and	and	CCONJ
ap-1538	17	5	back	back	NOUN
ap-1538	17	6	-	-	PUNCT
ap-1538	17	7	propagation	propagation	NOUN
ap-1538	17	8	through	through	ADP
ap-1538	17	9	time	time	NOUN
ap-1538	17	10	(	(	PUNCT
ap-1538	17	11	bptt	bptt	NOUN
ap-1538	17	12	)	)	PUNCT
ap-1538	18	1	[	[	X
ap-1538	18	2	16	16	NUM
ap-1538	18	3	,	,	PUNCT
ap-1538	18	4	17	17	NUM
ap-1538	18	5	]	]	PUNCT
ap-1538	18	6	.	.	PUNCT
ap-1538	19	1	these	these	DET
ap-1538	19	2	algorithms	algorithm	NOUN
ap-1538	19	3	can	can	AUX
ap-1538	19	4	be	be	AUX
ap-1538	19	5	made	make	VERB
ap-1538	19	6	comprehensible	comprehensible	ADJ
ap-1538	19	7	and	and	CCONJ
ap-1538	19	8	practically	practically	ADV
ap-1538	19	9	useful	useful	ADJ
ap-1538	19	10	for	for	ADP
ap-1538	19	11	real	real	ADJ
ap-1538	19	12	-	-	PUNCT
ap-1538	19	13	time	time	NOUN
ap-1538	19	14	computations	computation	NOUN
ap-1538	19	15	.	.	PUNCT
ap-1538	20	1	in	in	ADP
ap-1538	20	2	this	this	DET
ap-1538	20	3	paper	paper	NOUN
ap-1538	20	4	,	,	PUNCT
ap-1538	20	5	we	we	PRON
ap-1538	20	6	present	present	VERB
ap-1538	20	7	the	the	DET
ap-1538	20	8	resulting	result	VERB
ap-1538	20	9	neural	neural	ADJ
ap-1538	20	10	network	network	NOUN
ap-1538	20	11	architecture	architecture	NOUN
ap-1538	20	12	that	that	PRON
ap-1538	20	13	has	have	AUX
ap-1538	20	14	been	be	AUX
ap-1538	20	15	designed	design	VERB
ap-1538	20	16	and	and	CCONJ
ap-1538	20	17	tested	test	VERB
ap-1538	20	18	for	for	ADP
ap-1538	20	19	nox	nox	NOUN
ap-1538	20	20	prediction	prediction	NOUN
ap-1538	20	21	for	for	ADP
ap-1538	20	22	a	a	DET
ap-1538	20	23	pulverized	pulverize	VERB
ap-1538	20	24	coal	coal	NOUN
ap-1538	20	25	firing	firing	NOUN
ap-1538	20	26	boiler	boiler	NOUN
ap-1538	20	27	at	at	ADP
ap-1538	20	28	the	the	DET
ap-1538	20	29	power	power	NOUN
ap-1538	20	30	plant	plant	NOUN
ap-1538	20	31	“	"	PUNCT
ap-1538	20	32	elektrárna	elektrárna	PROPN
ap-1538	20	33	mělńık	mělńık	NOUN
ap-1538	20	34	1	1	NUM
ap-1538	20	35	(	(	PUNCT
ap-1538	20	36	eme	eme	NOUN
ap-1538	20	37	1	1	NUM
ap-1538	20	38	)	)	PUNCT
ap-1538	20	39	”	"	PUNCT
ap-1538	20	40	;	;	PUNCT
ap-1538	20	41	the	the	DET
ap-1538	20	42	nominal	nominal	ADJ
ap-1538	20	43	steam	steam	NOUN
ap-1538	20	44	load	load	NOUN
ap-1538	20	45	of	of	ADP
ap-1538	20	46	this	this	DET
ap-1538	20	47	boiler	boiler	NOUN
ap-1538	20	48	is	be	AUX
ap-1538	20	49	250	250	NUM
ap-1538	20	50	tons	ton	NOUN
ap-1538	20	51	per	per	ADP
ap-1538	20	52	hour	hour	NOUN
ap-1538	20	53	.	.	PUNCT
ap-1538	21	1	the	the	DET
ap-1538	21	2	goal	goal	NOUN
ap-1538	21	3	is	be	AUX
ap-1538	21	4	to	to	PART
ap-1538	21	5	design	design	VERB
ap-1538	21	6	and	and	CCONJ
ap-1538	21	7	test	test	VERB
ap-1538	21	8	a	a	DET
ap-1538	21	9	model	model	NOUN
ap-1538	21	10	that	that	PRON
ap-1538	21	11	does	do	AUX
ap-1538	21	12	not	not	PART
ap-1538	21	13	involve	involve	VERB
ap-1538	21	14	measured	measure	VERB
ap-1538	21	15	o2	o2	PROPN
ap-1538	21	16	or	or	CCONJ
ap-1538	21	17	co	co	NOUN
ap-1538	21	18	in	in	ADP
ap-1538	21	19	its	its	PRON
ap-1538	21	20	input	input	NOUN
ap-1538	21	21	and	and	CCONJ
ap-1538	21	22	that	that	PRON
ap-1538	21	23	can	can	AUX
ap-1538	21	24	potentially	potentially	ADV
ap-1538	21	25	be	be	AUX
ap-1538	21	26	used	use	VERB
ap-1538	21	27	for	for	ADP
ap-1538	21	28	optimizing	optimize	VERB
ap-1538	21	29	the	the	DET
ap-1538	21	30	energetic	energetic	ADJ
ap-1538	21	31	process	process	NOUN
ap-1538	21	32	regarding	regard	VERB
ap-1538	21	33	nox	nox	NOUN
ap-1538	21	34	and	and	CCONJ
ap-1538	21	35	co	co	NOUN
ap-1538	21	36	emissions	emission	NOUN
ap-1538	21	37	of	of	ADP
ap-1538	21	38	the	the	DET
ap-1538	21	39	pulverized	pulverize	VERB
ap-1538	21	40	firing	firing	NOUN
ap-1538	21	41	boiler	boiler	NOUN
ap-1538	21	42	at	at	ADP
ap-1538	21	43	eme	eme	NOUN
ap-1538	21	44	1	1	NUM
ap-1538	21	45	.	.	PUNCT
ap-1538	22	1	the	the	DET
ap-1538	22	2	resulting	result	VERB
ap-1538	22	3	discrete	discrete	ADJ
ap-1538	22	4	-	-	PUNCT
ap-1538	22	5	time	time	NOUN
ap-1538	22	6	dynamic	dynamic	ADJ
ap-1538	22	7	(	(	PUNCT
ap-1538	22	8	recurrent	recurrent	NOUN
ap-1538	22	9	)	)	PUNCT
ap-1538	22	10	neural	neural	ADJ
ap-1538	22	11	network	network	NOUN
ap-1538	22	12	merges	merge	VERB
ap-1538	22	13	the	the	DET
ap-1538	22	14	concept	concept	NOUN
ap-1538	22	15	of	of	ADP
ap-1538	22	16	a	a	DET
ap-1538	22	17	conventional	conventional	ADJ
ap-1538	22	18	recurrent	recurrent	NOUN
ap-1538	22	19	(	(	PUNCT
ap-1538	22	20	mlp	mlp	NOUN
ap-1538	22	21	)	)	PUNCT
ap-1538	22	22	neural	neural	ADJ
ap-1538	22	23	network	network	NOUN
ap-1538	22	24	with	with	ADP
ap-1538	22	25	qnu	qnu	PROPN
ap-1538	23	1	[	[	X
ap-1538	23	2	4	4	NUM
ap-1538	23	3	,	,	PUNCT
ap-1538	23	4	9	9	NUM
ap-1538	23	5	]	]	PUNCT
ap-1538	23	6	.	.	PUNCT
ap-1538	24	1	the	the	DET
ap-1538	24	2	17	17	NUM
ap-1538	24	3	acta	acta	PROPN
ap-1538	24	4	polytechnica	polytechnica	PROPN
ap-1538	24	5	vol	vol	NOUN
ap-1538	24	6	.	.	PROPN
ap-1538	25	1	52	52	NUM
ap-1538	25	2	no	no	NOUN
ap-1538	25	3	.	.	PUNCT
ap-1538	26	1	3/2012	3/2012	NUM
ap-1538	26	2	figure	figure	NOUN
ap-1538	26	3	1	1	NUM
ap-1538	26	4	:	:	PUNCT
ap-1538	26	5	the	the	DET
ap-1538	26	6	data	datum	NOUN
ap-1538	26	7	preprocessing	preprocesse	VERB
ap-1538	26	8	before	before	ADP
ap-1538	26	9	each	each	DET
ap-1538	26	10	reconfiguration	reconfiguration	NOUN
ap-1538	26	11	and	and	CCONJ
ap-1538	26	12	retraining	retraining	NOUN
ap-1538	26	13	of	of	ADP
ap-1538	26	14	the	the	DET
ap-1538	26	15	neural	neural	ADJ
ap-1538	26	16	network	network	NOUN
ap-1538	26	17	data	datum	NOUN
ap-1538	26	18	pre	pre	ADJ
ap-1538	26	19	-	-	ADJ
ap-1538	26	20	processing	process	VERB
ap-1538	26	21	and	and	CCONJ
ap-1538	26	22	retraining	retrain	VERB
ap-1538	26	23	strategy	strategy	NOUN
ap-1538	26	24	is	be	AUX
ap-1538	26	25	described	describe	VERB
ap-1538	26	26	in	in	ADP
ap-1538	26	27	the	the	DET
ap-1538	26	28	next	next	ADJ
ap-1538	26	29	section	section	NOUN
ap-1538	26	30	,	,	PUNCT
ap-1538	26	31	and	and	CCONJ
ap-1538	26	32	that	that	SCONJ
ap-1538	26	33	in	in	ADP
ap-1538	26	34	turn	turn	NOUN
ap-1538	26	35	is	be	AUX
ap-1538	26	36	followed	follow	VERB
ap-1538	26	37	by	by	ADP
ap-1538	26	38	the	the	DET
ap-1538	26	39	mathematical	mathematical	ADJ
ap-1538	26	40	notation	notation	NOUN
ap-1538	26	41	of	of	ADP
ap-1538	26	42	the	the	DET
ap-1538	26	43	neural	neural	ADJ
ap-1538	26	44	architecture	architecture	NOUN
ap-1538	26	45	that	that	PRON
ap-1538	26	46	led	lead	VERB
ap-1538	26	47	to	to	ADP
ap-1538	26	48	the	the	DET
ap-1538	26	49	results	result	NOUN
ap-1538	26	50	shown	show	VERB
ap-1538	26	51	in	in	ADP
ap-1538	26	52	the	the	DET
ap-1538	26	53	section	section	NOUN
ap-1538	26	54	on	on	ADP
ap-1538	26	55	discussion	discussion	NOUN
ap-1538	26	56	.	.	PUNCT
ap-1538	27	1	2	2	NUM
ap-1538	27	2	data	datum	NOUN
ap-1538	27	3	preprocessing	preprocessing	NOUN
ap-1538	27	4	and	and	CCONJ
ap-1538	27	5	network	network	NOUN
ap-1538	27	6	training	train	VERB
ap-1538	27	7	the	the	DET
ap-1538	27	8	nox	nox	NOUN
ap-1538	27	9	dynamics	dynamic	NOUN
ap-1538	27	10	of	of	ADP
ap-1538	27	11	the	the	DET
ap-1538	27	12	pulverized	pulverize	VERB
ap-1538	27	13	boiler	boiler	NOUN
ap-1538	27	14	is	be	AUX
ap-1538	27	15	highly	highly	ADV
ap-1538	27	16	nonstationary	nonstationary	ADJ
ap-1538	27	17	,	,	PUNCT
ap-1538	27	18	due	due	ADJ
ap-1538	27	19	to	to	ADP
ap-1538	27	20	varying	vary	VERB
ap-1538	27	21	technical	technical	ADJ
ap-1538	27	22	conditions	condition	NOUN
ap-1538	27	23	of	of	ADP
ap-1538	27	24	the	the	DET
ap-1538	27	25	boiler	boiler	NOUN
ap-1538	27	26	,	,	PUNCT
ap-1538	27	27	varying	vary	VERB
ap-1538	27	28	quality	quality	NOUN
ap-1538	27	29	of	of	ADP
ap-1538	27	30	the	the	DET
ap-1538	27	31	coal	coal	NOUN
ap-1538	27	32	powder	powder	NOUN
ap-1538	27	33	,	,	PUNCT
ap-1538	27	34	and	and	CCONJ
ap-1538	27	35	also	also	ADV
ap-1538	27	36	because	because	SCONJ
ap-1538	27	37	of	of	ADP
ap-1538	27	38	the	the	DET
ap-1538	27	39	measurement	measurement	NOUN
ap-1538	27	40	outages	outage	NOUN
ap-1538	27	41	that	that	PRON
ap-1538	27	42	occur	occur	VERB
ap-1538	27	43	quite	quite	ADV
ap-1538	27	44	often	often	ADV
ap-1538	27	45	on	on	ADP
ap-1538	27	46	an	an	DET
ap-1538	27	47	hourly	hourly	ADJ
ap-1538	27	48	basis	basis	NOUN
ap-1538	27	49	.	.	PUNCT
ap-1538	28	1	it	it	PRON
ap-1538	28	2	was	be	AUX
ap-1538	28	3	therefore	therefore	ADV
ap-1538	28	4	not	not	PART
ap-1538	28	5	possible	possible	ADJ
ap-1538	28	6	to	to	PART
ap-1538	28	7	obtain	obtain	VERB
ap-1538	28	8	a	a	DET
ap-1538	28	9	neural	neural	ADJ
ap-1538	28	10	network	network	NOUN
ap-1538	28	11	model	model	NOUN
ap-1538	28	12	that	that	PRON
ap-1538	28	13	would	would	AUX
ap-1538	28	14	reliably	reliably	ADV
ap-1538	28	15	predict	predict	VERB
ap-1538	28	16	the	the	DET
ap-1538	28	17	nox	nox	PROPN
ap-1538	28	18	emissions	emission	NOUN
ap-1538	28	19	from	from	ADP
ap-1538	28	20	the	the	DET
ap-1538	28	21	long	long	ADJ
ap-1538	28	22	term	term	NOUN
ap-1538	28	23	data	datum	NOUN
ap-1538	28	24	.	.	PUNCT
ap-1538	29	1	to	to	PART
ap-1538	29	2	handle	handle	VERB
ap-1538	29	3	the	the	DET
ap-1538	29	4	non	non	ADJ
ap-1538	29	5	-	-	ADJ
ap-1538	29	6	stationary	stationary	ADJ
ap-1538	29	7	nature	nature	NOUN
ap-1538	29	8	of	of	ADP
ap-1538	29	9	the	the	DET
ap-1538	29	10	boiler	boiler	NOUN
ap-1538	29	11	in	in	ADP
ap-1538	29	12	eme	eme	PROPN
ap-1538	29	13	1	1	NUM
ap-1538	29	14	,	,	PUNCT
ap-1538	29	15	we	we	PRON
ap-1538	29	16	arrived	arrive	VERB
ap-1538	29	17	at	at	ADP
ap-1538	29	18	the	the	DET
ap-1538	29	19	data	data	NOUN
ap-1538	29	20	preprocessing	preprocessing	NOUN
ap-1538	29	21	technique	technique	NOUN
ap-1538	29	22	that	that	PRON
ap-1538	29	23	is	be	AUX
ap-1538	29	24	sketched	sketch	VERB
ap-1538	29	25	in	in	ADP
ap-1538	29	26	figure	figure	NOUN
ap-1538	29	27	1	1	NUM
ap-1538	29	28	,	,	PUNCT
ap-1538	29	29	where	where	SCONJ
ap-1538	29	30	u(k	u(k	PROPN
ap-1538	29	31	)	)	PUNCT
ap-1538	29	32	is	be	AUX
ap-1538	29	33	a	a	DET
ap-1538	29	34	matrix	matrix	NOUN
ap-1538	29	35	of	of	ADP
ap-1538	29	36	recent	recent	ADJ
ap-1538	29	37	history	history	NOUN
ap-1538	29	38	(	(	PUNCT
ap-1538	29	39	a	a	DET
ap-1538	29	40	retraining	retraining	ADJ
ap-1538	29	41	window	window	NOUN
ap-1538	29	42	)	)	PUNCT
ap-1538	29	43	of	of	ADP
ap-1538	29	44	all	all	DET
ap-1538	29	45	measured	measure	VERB
ap-1538	29	46	input	input	NOUN
ap-1538	29	47	variables	variable	NOUN
ap-1538	29	48	(	(	PUNCT
ap-1538	29	49	excluding	exclude	VERB
ap-1538	29	50	measured	measure	VERB
ap-1538	29	51	o2	o2	PROPN
ap-1538	29	52	,	,	PUNCT
ap-1538	29	53	nox	nox	NOUN
ap-1538	29	54	,	,	PUNCT
ap-1538	29	55	and	and	CCONJ
ap-1538	29	56	co	co	NOUN
ap-1538	29	57	)	)	PUNCT
ap-1538	29	58	at	at	ADP
ap-1538	29	59	a	a	DET
ap-1538	29	60	reference	reference	NOUN
ap-1538	29	61	time	time	NOUN
ap-1538	29	62	k	k	PROPN
ap-1538	29	63	that	that	PRON
ap-1538	29	64	is	be	AUX
ap-1538	29	65	particularly	particularly	ADV
ap-1538	29	66	given	give	VERB
ap-1538	29	67	as	as	SCONJ
ap-1538	29	68	follows	follow	VERB
ap-1538	29	69	u(k	u(k	PROPN
ap-1538	29	70	)	)	PUNCT
ap-1538	29	71	=	=	PUNCT
ap-1538	30	1	⎡	⎡	NOUN
ap-1538	30	2	⎢⎢⎢⎢⎢⎣	⎢⎢⎢⎢⎢⎣	VERB
ap-1538	31	1	u1(k	u1(k	X
ap-1538	31	2	−ntrain+	−ntrain+	NUM
ap-1538	31	3	1	1	NUM
ap-1538	31	4	)	)	PUNCT
ap-1538	31	5	.	.	PUNCT
ap-1538	31	6	.	.	PUNCT
ap-1538	32	1	.	.	PUNCT
ap-1538	33	1	u1(k	u1(k	PRON
ap-1538	33	2	−	−	NOUN
ap-1538	33	3	1	1	NUM
ap-1538	33	4	)	)	PUNCT
ap-1538	33	5	u1(k	u1(k	PROPN
ap-1538	33	6	)	)	PUNCT
ap-1538	33	7	u2(k	u2(k	NOUN
ap-1538	33	8	−ntrain+	−ntrain+	PROPN
ap-1538	33	9	1	1	NUM
ap-1538	33	10	)	)	PUNCT
ap-1538	33	11	.	.	PUNCT
ap-1538	33	12	.	.	PUNCT
ap-1538	33	13	.	.	PUNCT
ap-1538	34	1	u2(k	u2(k	NOUN
ap-1538	34	2	−	−	NOUN
ap-1538	34	3	1	1	NUM
ap-1538	34	4	)	)	PUNCT
ap-1538	34	5	u2(k	u2(k	NOUN
ap-1538	34	6	)	)	PUNCT
ap-1538	34	7	...	...	PUNCT
ap-1538	34	8	.	.	PUNCT
ap-1538	34	9	.	.	PUNCT
ap-1538	34	10	.	.	PUNCT
ap-1538	35	1	...	...	PUNCT
ap-1538	35	2	...	...	PUNCT
ap-1538	36	1	un(k	un(k	AUX
ap-1538	36	2	−ntrain+	−ntrain+	VERB
ap-1538	36	3	1	1	NUM
ap-1538	36	4	)	)	PUNCT
ap-1538	36	5	.	.	PUNCT
ap-1538	36	6	.	.	PUNCT
ap-1538	36	7	.	.	PUNCT
ap-1538	37	1	un(k	un(k	PUNCT
ap-1538	38	1	−	−	PROPN
ap-1538	38	2	1	1	NUM
ap-1538	38	3	)	)	PUNCT
ap-1538	38	4	un(k	un(k	ADJ
ap-1538	38	5	)	)	PUNCT
ap-1538	38	6	⎤	⎤	PROPN
ap-1538	38	7	⎥⎥⎥⎥⎥⎦	⎥⎥⎥⎥⎥⎦	PROPN
ap-1538	38	8	.	.	PUNCT
ap-1538	39	1	(	(	PUNCT
ap-1538	39	2	1	1	X
ap-1538	39	3	)	)	PUNCT
ap-1538	39	4	the	the	DET
ap-1538	39	5	measured	measure	VERB
ap-1538	39	6	input	input	NOUN
ap-1538	39	7	variables	variable	NOUN
ap-1538	39	8	in	in	ADP
ap-1538	39	9	u(k	u(k	PROPN
ap-1538	39	10	)	)	PUNCT
ap-1538	39	11	are	be	AUX
ap-1538	39	12	the	the	DET
ap-1538	39	13	primary	primary	ADJ
ap-1538	39	14	,	,	PUNCT
ap-1538	39	15	secondary	secondary	ADJ
ap-1538	39	16	,	,	PUNCT
ap-1538	39	17	and	and	CCONJ
ap-1538	39	18	tertiary	tertiary	ADJ
ap-1538	39	19	air	air	NOUN
ap-1538	39	20	valves	valve	NOUN
ap-1538	39	21	,	,	PUNCT
ap-1538	39	22	and	and	CCONJ
ap-1538	39	23	also	also	ADV
ap-1538	39	24	optionally	optionally	ADV
ap-1538	39	25	the	the	DET
ap-1538	39	26	steam	steam	NOUN
ap-1538	39	27	load	load	NOUN
ap-1538	39	28	or	or	CCONJ
ap-1538	39	29	the	the	DET
ap-1538	39	30	air	air	NOUN
ap-1538	39	31	flow	flow	NOUN
ap-1538	39	32	before	before	ADP
ap-1538	39	33	the	the	DET
ap-1538	39	34	ventilator	ventilator	NOUN
ap-1538	39	35	(	(	PUNCT
ap-1538	39	36	in	in	ADP
ap-1538	39	37	total	total	NOUN
ap-1538	39	38	n	n	NOUN
ap-1538	39	39	=	=	SYM
ap-1538	39	40	18	18	NUM
ap-1538	39	41	,	,	PUNCT
ap-1538	39	42	19	19	NUM
ap-1538	39	43	,	,	PUNCT
ap-1538	39	44	20	20	NUM
ap-1538	39	45	variables	variable	NOUN
ap-1538	39	46	)	)	PUNCT
ap-1538	39	47	excluding	exclude	VERB
ap-1538	39	48	o2	o2	PROPN
ap-1538	39	49	,	,	PUNCT
ap-1538	39	50	nox	nox	NOUN
ap-1538	39	51	,	,	PUNCT
ap-1538	39	52	and	and	CCONJ
ap-1538	39	53	co.	co.	VERB
ap-1538	39	54	the	the	DET
ap-1538	39	55	principal	principal	ADJ
ap-1538	39	56	component	component	NOUN
ap-1538	39	57	analysis	analysis	NOUN
ap-1538	39	58	(	(	PUNCT
ap-1538	39	59	pca	pca	NOUN
ap-1538	39	60	)	)	PUNCT
ap-1538	39	61	block	block	NOUN
ap-1538	39	62	is	be	AUX
ap-1538	39	63	an	an	DET
ap-1538	39	64	application	application	NOUN
ap-1538	39	65	of	of	ADP
ap-1538	39	66	pca	pca	PROPN
ap-1538	39	67	to	to	ADP
ap-1538	39	68	the	the	DET
ap-1538	39	69	linearly	linearly	ADV
ap-1538	39	70	correlated	correlate	VERB
ap-1538	39	71	variables	variable	NOUN
ap-1538	39	72	,	,	PUNCT
ap-1538	39	73	so	so	CCONJ
ap-1538	39	74	the	the	DET
ap-1538	39	75	number	number	NOUN
ap-1538	39	76	of	of	ADP
ap-1538	39	77	input	input	NOUN
ap-1538	39	78	variables	variable	NOUN
ap-1538	39	79	in	in	ADP
ap-1538	39	80	upca(k	upca(k	NOUN
ap-1538	39	81	)	)	PUNCT
ap-1538	39	82	is	be	AUX
ap-1538	39	83	m	m	PRON
ap-1538	39	84	<	<	X
ap-1538	39	85	n	n	CCONJ
ap-1538	39	86	,	,	PUNCT
ap-1538	39	87	which	which	PRON
ap-1538	39	88	importantly	importantly	ADV
ap-1538	39	89	decreases	decrease	VERB
ap-1538	39	90	the	the	DET
ap-1538	39	91	computation	computation	NOUN
ap-1538	39	92	load	load	NOUN
ap-1538	39	93	while	while	SCONJ
ap-1538	39	94	it	it	PRON
ap-1538	39	95	maintains	maintain	VERB
ap-1538	39	96	information	information	NOUN
ap-1538	39	97	in	in	ADP
ap-1538	39	98	the	the	DET
ap-1538	39	99	measured	measure	VERB
ap-1538	39	100	input	input	NOUN
ap-1538	39	101	data	datum	NOUN
ap-1538	39	102	(	(	PUNCT
ap-1538	39	103	note	note	NOUN
ap-1538	39	104	,	,	PUNCT
ap-1538	39	105	figure	figure	NOUN
ap-1538	39	106	1	1	NUM
ap-1538	39	107	shows	show	VERB
ap-1538	39	108	only	only	ADV
ap-1538	39	109	a	a	DET
ap-1538	39	110	simplified	simplified	ADJ
ap-1538	39	111	sketch	sketch	NOUN
ap-1538	39	112	,	,	PUNCT
ap-1538	39	113	while	while	SCONJ
ap-1538	39	114	detailed	detailed	ADJ
ap-1538	39	115	implementation	implementation	NOUN
ap-1538	39	116	of	of	ADP
ap-1538	39	117	pca	pca	PROPN
ap-1538	39	118	that	that	PRON
ap-1538	39	119	benefits	benefit	VERB
ap-1538	39	120	from	from	ADP
ap-1538	39	121	process	process	NOUN
ap-1538	39	122	knowledge	knowledge	NOUN
ap-1538	39	123	of	of	ADP
ap-1538	39	124	the	the	DET
ap-1538	39	125	pulverized	pulverize	VERB
ap-1538	39	126	boiler	boiler	NOUN
ap-1538	39	127	at	at	ADP
ap-1538	39	128	eme	eme	NOUN
ap-1538	39	129	1	1	NUM
ap-1538	39	130	may	may	AUX
ap-1538	39	131	be	be	AUX
ap-1538	39	132	provided	provide	VERB
ap-1538	39	133	on	on	ADP
ap-1538	39	134	the	the	DET
ap-1538	39	135	basis	basis	NOUN
ap-1538	39	136	of	of	ADP
ap-1538	39	137	an	an	DET
ap-1538	39	138	official	official	ADJ
ap-1538	39	139	request	request	NOUN
ap-1538	39	140	for	for	ADP
ap-1538	39	141	[	[	X
ap-1538	39	142	19	19	NUM
ap-1538	39	143	]	]	NUM
ap-1538	39	144	)	)	PUNCT
ap-1538	39	145	.	.	PUNCT
ap-1538	40	1	the	the	DET
ap-1538	40	2	structure	structure	NOUN
ap-1538	40	3	of	of	ADP
ap-1538	40	4	the	the	DET
ap-1538	40	5	resulting	result	VERB
ap-1538	40	6	input	input	NOUN
ap-1538	40	7	data	datum	NOUN
ap-1538	40	8	matrix	matrix	NOUN
ap-1538	40	9	upca(k	upca(k	NOUN
ap-1538	40	10	)	)	PUNCT
ap-1538	40	11	that	that	PRON
ap-1538	40	12	is	be	AUX
ap-1538	40	13	used	use	VERB
ap-1538	40	14	as	as	ADP
ap-1538	40	15	the	the	DET
ap-1538	40	16	neural	neural	ADJ
ap-1538	40	17	network	network	NOUN
ap-1538	40	18	input	input	NOUN
ap-1538	40	19	(	(	PUNCT
ap-1538	40	20	after	after	ADP
ap-1538	40	21	the	the	DET
ap-1538	40	22	preprocessing	preprocessing	NOUN
ap-1538	40	23	shown	show	VERB
ap-1538	40	24	in	in	ADP
ap-1538	40	25	figure	figure	NOUN
ap-1538	40	26	1	1	NUM
ap-1538	40	27	)	)	PUNCT
ap-1538	40	28	is	be	AUX
ap-1538	40	29	as	as	SCONJ
ap-1538	40	30	follows	follow	VERB
ap-1538	40	31	upca(k	upca(k	NOUN
ap-1538	40	32	)	)	PUNCT
ap-1538	40	33	=	=	PUNCT
ap-1538	40	34	⎡	⎡	NUM
ap-1538	40	35	⎢⎢⎣	⎢⎢⎣	NOUN
ap-1538	40	36	upca1(k	upca1(k	NUM
ap-1538	40	37	−ntrain+	−ntrain+	PUNCT
ap-1538	40	38	1	1	NUM
ap-1538	40	39	)	)	PUNCT
ap-1538	40	40	.	.	PUNCT
ap-1538	40	41	.	.	PUNCT
ap-1538	40	42	.	.	PUNCT
ap-1538	41	1	upca1(k	upca1(k	NOUN
ap-1538	42	1	−	−	NOUN
ap-1538	42	2	1	1	NUM
ap-1538	42	3	)	)	PUNCT
ap-1538	42	4	upca1(k	upca1(k	NOUN
ap-1538	42	5	)	)	PUNCT
ap-1538	42	6	...	...	PUNCT
ap-1538	42	7	.	.	PUNCT
ap-1538	42	8	.	.	PUNCT
ap-1538	42	9	.	.	PUNCT
ap-1538	43	1	...	...	PUNCT
ap-1538	43	2	...	...	PUNCT
ap-1538	44	1	upcam(k	upcam(k	NOUN
ap-1538	44	2	−ntrain+	−ntrain+	NUM
ap-1538	44	3	1	1	NUM
ap-1538	44	4	)	)	PUNCT
ap-1538	44	5	.	.	PUNCT
ap-1538	44	6	.	.	PUNCT
ap-1538	44	7	.	.	PUNCT
ap-1538	45	1	upcam(k	upcam(k	NOUN
ap-1538	45	2	−	−	NOUN
ap-1538	45	3	1	1	NUM
ap-1538	45	4	)	)	PUNCT
ap-1538	45	5	upcam(k	upcam(k	PROPN
ap-1538	45	6	)	)	PUNCT
ap-1538	45	7	⎤	⎤	PROPN
ap-1538	45	8	⎥⎥⎦	⎥⎥⎦	ADV
ap-1538	45	9	.	.	PUNCT
ap-1538	46	1	(	(	PUNCT
ap-1538	46	2	2	2	X
ap-1538	46	3	)	)	PUNCT
ap-1538	46	4	the	the	DET
ap-1538	46	5	presented	present	VERB
ap-1538	46	6	data	datum	NOUN
ap-1538	46	7	pre	pre	ADJ
ap-1538	46	8	-	-	ADJ
ap-1538	46	9	processing	processing	ADJ
ap-1538	46	10	technique	technique	NOUN
ap-1538	46	11	removes	remove	VERB
ap-1538	46	12	variables	variable	NOUN
ap-1538	46	13	with	with	ADP
ap-1538	46	14	measurement	measurement	NOUN
ap-1538	46	15	outages	outage	NOUN
ap-1538	46	16	.	.	PUNCT
ap-1538	47	1	principal	principal	ADJ
ap-1538	47	2	component	component	NOUN
ap-1538	47	3	analysis	analysis	NOUN
ap-1538	47	4	results	result	NOUN
ap-1538	47	5	in	in	ADP
ap-1538	47	6	a	a	DET
ap-1538	47	7	lower	low	ADJ
ap-1538	47	8	computational	computational	ADJ
ap-1538	47	9	load	load	NOUN
ap-1538	47	10	,	,	PUNCT
ap-1538	47	11	because	because	SCONJ
ap-1538	47	12	of	of	ADP
ap-1538	47	13	the	the	DET
ap-1538	47	14	reduced	reduce	VERB
ap-1538	47	15	number	number	NOUN
ap-1538	47	16	of	of	ADP
ap-1538	47	17	external	external	ADJ
ap-1538	47	18	inputs	input	NOUN
ap-1538	47	19	into	into	ADP
ap-1538	47	20	the	the	DET
ap-1538	47	21	neural	neural	ADJ
ap-1538	47	22	network	network	NOUN
ap-1538	47	23	(	(	PUNCT
ap-1538	47	24	m	m	VERB
ap-1538	47	25	<	<	X
ap-1538	47	26	n	n	CCONJ
ap-1538	47	27	)	)	PUNCT
ap-1538	47	28	.	.	PUNCT
ap-1538	48	1	pca	pca	PROPN
ap-1538	48	2	has	have	VERB
ap-1538	48	3	a	a	DET
ap-1538	48	4	filtering	filter	VERB
ap-1538	48	5	effect	effect	NOUN
ap-1538	48	6	,	,	PUNCT
ap-1538	48	7	and	and	CCONJ
ap-1538	48	8	also	also	ADV
ap-1538	48	9	contributes	contribute	VERB
ap-1538	48	10	to	to	ADP
ap-1538	48	11	more	more	ADV
ap-1538	48	12	accurate	accurate	ADJ
ap-1538	48	13	calculations	calculation	NOUN
ap-1538	48	14	of	of	ADP
ap-1538	48	15	matrix	matrix	NOUN
ap-1538	48	16	inversion	inversion	NOUN
ap-1538	48	17	with	with	ADP
ap-1538	48	18	the	the	DET
ap-1538	48	19	bptt	bptt	NOUN
ap-1538	48	20	training	training	NOUN
ap-1538	48	21	technique	technique	NOUN
ap-1538	48	22	by	by	ADP
ap-1538	48	23	reducing	reduce	VERB
ap-1538	48	24	redundant	redundant	ADJ
ap-1538	48	25	and	and	CCONJ
ap-1538	48	26	linearly	linearly	ADV
ap-1538	48	27	correlated	correlate	VERB
ap-1538	48	28	data	datum	NOUN
ap-1538	48	29	.	.	PUNCT
ap-1538	49	1	3	3	NUM
ap-1538	49	2	neural	neural	ADJ
ap-1538	49	3	network	network	NOUN
ap-1538	49	4	for	for	ADP
ap-1538	49	5	nox	nox	NOUN
ap-1538	49	6	prediction	prediction	NOUN
ap-1538	49	7	this	this	DET
ap-1538	49	8	section	section	NOUN
ap-1538	49	9	describes	describe	VERB
ap-1538	49	10	the	the	DET
ap-1538	49	11	mathematical	mathematical	ADJ
ap-1538	49	12	notation	notation	NOUN
ap-1538	49	13	of	of	ADP
ap-1538	49	14	the	the	DET
ap-1538	49	15	designed	design	VERB
ap-1538	49	16	neural	neural	ADJ
ap-1538	49	17	network	network	NOUN
ap-1538	49	18	for	for	ADP
ap-1538	49	19	nox	nox	NOUN
ap-1538	49	20	prediction	prediction	NOUN
ap-1538	49	21	.	.	PUNCT
ap-1538	50	1	this	this	DET
ap-1538	50	2	neural	neural	ADJ
ap-1538	50	3	network	network	NOUN
ap-1538	50	4	is	be	AUX
ap-1538	50	5	a	a	DET
ap-1538	50	6	discrete	discrete	ADJ
ap-1538	50	7	-	-	PUNCT
ap-1538	50	8	time	time	NOUN
ap-1538	50	9	recurrent	recurrent	ADJ
ap-1538	50	10	architecture	architecture	NOUN
ap-1538	50	11	,	,	PUNCT
ap-1538	50	12	i.e.	i.e.	X
ap-1538	50	13	,	,	PUNCT
ap-1538	50	14	a	a	DET
ap-1538	50	15	non	non	ADJ
ap-1538	50	16	-	-	ADJ
ap-1538	50	17	linear	linear	ADJ
ap-1538	50	18	difference	difference	NOUN
ap-1538	50	19	equation	equation	NOUN
ap-1538	50	20	system	system	NOUN
ap-1538	50	21	,	,	PUNCT
ap-1538	50	22	composed	compose	VERB
ap-1538	50	23	of	of	ADP
ap-1538	50	24	a	a	DET
ap-1538	50	25	recurrent	recurrent	ADJ
ap-1538	50	26	hidden	hide	VERB
ap-1538	50	27	layer	layer	NOUN
ap-1538	50	28	of	of	ADP
ap-1538	50	29	conventional	conventional	ADJ
ap-1538	50	30	sigmoid	sigmoid	NOUN
ap-1538	50	31	neurons	neuron	NOUN
ap-1538	50	32	and	and	CCONJ
ap-1538	50	33	with	with	ADP
ap-1538	50	34	an	an	DET
ap-1538	50	35	output	output	NOUN
ap-1538	50	36	quadratic	quadratic	ADJ
ap-1538	50	37	neural	neural	ADJ
ap-1538	50	38	unit	unit	NOUN
ap-1538	50	39	with	with	ADP
ap-1538	50	40	feedbacks	feedback	NOUN
ap-1538	50	41	also	also	ADV
ap-1538	50	42	from	from	ADP
ap-1538	50	43	the	the	DET
ap-1538	50	44	output	output	NOUN
ap-1538	50	45	to	to	ADP
ap-1538	50	46	its	its	PRON
ap-1538	50	47	input	input	NOUN
ap-1538	50	48	.	.	PUNCT
ap-1538	51	1	in	in	ADP
ap-1538	51	2	particular	particular	ADJ
ap-1538	51	3	,	,	PUNCT
ap-1538	51	4	the	the	DET
ap-1538	51	5	neural	neural	ADJ
ap-1538	51	6	network	network	NOUN
ap-1538	51	7	predictive	predictive	ADJ
ap-1538	51	8	model	model	NOUN
ap-1538	51	9	is	be	AUX
ap-1538	51	10	given	give	VERB
ap-1538	51	11	as	as	ADP
ap-1538	51	12	18	18	NUM
ap-1538	51	13	acta	acta	PROPN
ap-1538	51	14	polytechnica	polytechnica	PROPN
ap-1538	51	15	vol	vol	NOUN
ap-1538	51	16	.	.	PROPN
ap-1538	52	1	52	52	NUM
ap-1538	52	2	no	no	NOUN
ap-1538	52	3	.	.	PUNCT
ap-1538	53	1	3/2012	3/2012	NOUN
ap-1538	53	2	follows	follow	VERB
ap-1538	53	3	.	.	PUNCT
ap-1538	54	1	the	the	DET
ap-1538	54	2	window	window	NOUN
ap-1538	54	3	of	of	ADP
ap-1538	54	4	external	external	ADJ
ap-1538	54	5	inputs	input	NOUN
ap-1538	54	6	for	for	ADP
ap-1538	54	7	retraining	retrain	VERB
ap-1538	54	8	the	the	DET
ap-1538	54	9	network	network	NOUN
ap-1538	54	10	at	at	ADP
ap-1538	54	11	reference	reference	NOUN
ap-1538	54	12	time	time	NOUN
ap-1538	54	13	k	k	PROPN
ap-1538	54	14	are	be	AUX
ap-1538	54	15	the	the	DET
ap-1538	54	16	pre	pre	ADJ
ap-1538	54	17	-	-	ADJ
ap-1538	54	18	processed	process	VERB
ap-1538	54	19	measured	measure	VERB
ap-1538	54	20	variables	variable	NOUN
ap-1538	54	21	upca(k	upca(k	PROPN
ap-1538	54	22	)	)	PUNCT
ap-1538	54	23	,	,	PUNCT
ap-1538	54	24	as	as	SCONJ
ap-1538	54	25	given	give	VERB
ap-1538	54	26	in	in	ADP
ap-1538	54	27	(	(	PUNCT
ap-1538	54	28	2	2	NUM
ap-1538	54	29	)	)	PUNCT
ap-1538	54	30	and	and	CCONJ
ap-1538	54	31	in	in	ADP
ap-1538	54	32	figure	figure	NOUN
ap-1538	54	33	1	1	NUM
ap-1538	54	34	.	.	PUNCT
ap-1538	55	1	the	the	DET
ap-1538	55	2	external	external	ADJ
ap-1538	55	3	inputs	input	NOUN
ap-1538	55	4	that	that	PRON
ap-1538	55	5	enter	enter	VERB
ap-1538	55	6	the	the	DET
ap-1538	55	7	neural	neural	ADJ
ap-1538	55	8	network	network	NOUN
ap-1538	55	9	for	for	ADP
ap-1538	55	10	ns	ns	NUM
ap-1538	55	11	samples	sample	NOUN
ap-1538	55	12	ahead	ahead	ADV
ap-1538	55	13	prediction	prediction	NOUN
ap-1538	55	14	at	at	ADP
ap-1538	55	15	time	time	NOUN
ap-1538	55	16	k	k	X
ap-1538	55	17	are	be	AUX
ap-1538	55	18	in	in	ADP
ap-1538	55	19	the	the	DET
ap-1538	55	20	last	last	ADJ
ap-1538	55	21	column	column	NOUN
ap-1538	55	22	of	of	ADP
ap-1538	55	23	upca(k	upca(k	PROPN
ap-1538	55	24	)	)	PUNCT
ap-1538	55	25	,	,	PUNCT
ap-1538	55	26	as	as	SCONJ
ap-1538	55	27	follows	follow	VERB
ap-1538	55	28	upca(k	upca(k	NOUN
ap-1538	55	29	)	)	PUNCT
ap-1538	56	1	=	=	PUNCT
ap-1538	56	2	[	[	PUNCT
ap-1538	56	3	upca1(k	upca1(k	NOUN
ap-1538	56	4	)	)	PUNCT
ap-1538	56	5	upca2(k	upca2(k	NOUN
ap-1538	56	6	)	)	PUNCT
ap-1538	56	7	.	.	PUNCT
ap-1538	56	8	.	.	PUNCT
ap-1538	56	9	.	.	PUNCT
ap-1538	57	1	upcar(k	upcar(k	ADJ
ap-1538	57	2	)	)	PUNCT
ap-1538	57	3	]	]	X
ap-1538	57	4	t	t	NOUN
ap-1538	57	5	,	,	PUNCT
ap-1538	57	6	(	(	PUNCT
ap-1538	57	7	3	3	X
ap-1538	57	8	)	)	PUNCT
ap-1538	57	9	where	where	SCONJ
ap-1538	57	10	k	k	PROPN
ap-1538	57	11	is	be	AUX
ap-1538	57	12	a	a	DET
ap-1538	57	13	reference	reference	NOUN
ap-1538	57	14	sample	sample	NOUN
ap-1538	57	15	time	time	NOUN
ap-1538	57	16	index	index	NOUN
ap-1538	57	17	and	and	CCONJ
ap-1538	57	18	r	r	NOUN
ap-1538	57	19	is	be	AUX
ap-1538	57	20	the	the	DET
ap-1538	57	21	dimension	dimension	NOUN
ap-1538	57	22	of	of	ADP
ap-1538	57	23	the	the	DET
ap-1538	57	24	reduced	reduce	VERB
ap-1538	57	25	vector	vector	NOUN
ap-1538	57	26	of	of	ADP
ap-1538	57	27	all	all	DET
ap-1538	57	28	measured	measure	VERB
ap-1538	57	29	external	external	ADJ
ap-1538	57	30	inputs	input	NOUN
ap-1538	57	31	by	by	ADP
ap-1538	57	32	the	the	DET
ap-1538	57	33	pca	pca	PROPN
ap-1538	57	34	method	method	NOUN
ap-1538	57	35	.	.	PUNCT
ap-1538	58	1	the	the	DET
ap-1538	58	2	input	input	NOUN
ap-1538	58	3	vector	vector	NOUN
ap-1538	58	4	to	to	ADP
ap-1538	58	5	the	the	DET
ap-1538	58	6	hidden	hide	VERB
ap-1538	58	7	layer	layer	NOUN
ap-1538	58	8	of	of	ADP
ap-1538	58	9	the	the	DET
ap-1538	58	10	neural	neural	ADJ
ap-1538	58	11	network	network	NOUN
ap-1538	58	12	is	be	AUX
ap-1538	58	13	given	give	VERB
ap-1538	58	14	in	in	ADP
ap-1538	58	15	(	(	PUNCT
ap-1538	58	16	4	4	NUM
ap-1538	58	17	)	)	PUNCT
ap-1538	58	18	as	as	ADP
ap-1538	58	19	x(k	x(k	NOUN
ap-1538	58	20	)	)	PUNCT
ap-1538	58	21	=	=	PUNCT
ap-1538	59	1	[	[	PUNCT
ap-1538	59	2	yn(k	yn(k	NOUN
ap-1538	59	3	+	+	NUM
ap-1538	59	4	nya	nya	NOUN
ap-1538	59	5	)	)	PUNCT
ap-1538	59	6	.	.	PUNCT
ap-1538	59	7	.	.	PUNCT
ap-1538	60	1	.	.	PUNCT
ap-1538	61	1	yn(k	yn(k	NUM
ap-1538	62	1	−	−	PROPN
ap-1538	62	2	nyb	nyb	PROPN
ap-1538	62	3	)	)	PUNCT
ap-1538	62	4	upca(k	upca(k	PROPN
ap-1538	62	5	+	+	CCONJ
ap-1538	62	6	nua	nua	PROPN
ap-1538	62	7	)	)	PUNCT
ap-1538	62	8	t	t	PROPN
ap-1538	62	9	.	.	PUNCT
ap-1538	62	10	.	.	PUNCT
ap-1538	62	11	.	.	PUNCT
ap-1538	63	1	upca(k	upca(k	ADV
ap-1538	63	2	−	−	PROPN
ap-1538	63	3	nub	nub	PROPN
ap-1538	63	4	)	)	PUNCT
ap-1538	63	5	t	t	PROPN
ap-1538	63	6	ξ(k	ξ(k	PROPN
ap-1538	63	7	)	)	PUNCT
ap-1538	64	1	]	]	PUNCT
ap-1538	64	2	t	t	X
ap-1538	64	3	,	,	PUNCT
ap-1538	64	4	(	(	PUNCT
ap-1538	64	5	4	4	X
ap-1538	64	6	)	)	PUNCT
ap-1538	64	7	where	where	SCONJ
ap-1538	64	8	yn	yn	PROPN
ap-1538	64	9	(	(	PUNCT
ap-1538	64	10	.	.	PUNCT
ap-1538	64	11	)	)	PUNCT
ap-1538	64	12	are	be	AUX
ap-1538	64	13	step	step	NOUN
ap-1538	64	14	-	-	PUNCT
ap-1538	64	15	delayed	delay	VERB
ap-1538	64	16	neural	neural	ADJ
ap-1538	64	17	outputs	output	NOUN
ap-1538	64	18	;	;	PUNCT
ap-1538	64	19	nya	nya	PROPN
ap-1538	64	20	,	,	PUNCT
ap-1538	64	21	nyb	nyb	PROPN
ap-1538	64	22	,	,	PUNCT
ap-1538	64	23	nua	nua	PROPN
ap-1538	64	24	,	,	PUNCT
ap-1538	64	25	and	and	CCONJ
ap-1538	64	26	nub	nub	NOUN
ap-1538	64	27	are	be	AUX
ap-1538	64	28	input	input	ADJ
ap-1538	64	29	configuration	configuration	NOUN
ap-1538	64	30	parameters	parameter	NOUN
ap-1538	64	31	;	;	PUNCT
ap-1538	64	32	and	and	CCONJ
ap-1538	64	33	ξ(k	ξ(k	NOUN
ap-1538	64	34	)	)	PUNCT
ap-1538	64	35	is	be	AUX
ap-1538	64	36	the	the	DET
ap-1538	64	37	step	step	NOUN
ap-1538	64	38	delayed	delay	VERB
ap-1538	64	39	feedback	feedback	NOUN
ap-1538	64	40	of	of	ADP
ap-1538	64	41	the	the	DET
ap-1538	64	42	hidden	hide	VERB
ap-1538	64	43	layer	layer	NOUN
ap-1538	64	44	outputs	output	NOUN
ap-1538	64	45	.	.	PUNCT
ap-1538	65	1	the	the	DET
ap-1538	65	2	output	output	NOUN
ap-1538	65	3	of	of	ADP
ap-1538	65	4	the	the	DET
ap-1538	65	5	hidden	hide	VERB
ap-1538	65	6	sigmoidal	sigmoidal	NOUN
ap-1538	65	7	layer	layer	NOUN
ap-1538	65	8	ξ(k+1	ξ(k+1	NOUN
ap-1538	65	9	)	)	PUNCT
ap-1538	65	10	(	(	PUNCT
ap-1538	65	11	6	6	NUM
ap-1538	65	12	)	)	PUNCT
ap-1538	65	13	is	be	AUX
ap-1538	65	14	calculated	calculate	VERB
ap-1538	65	15	using	use	VERB
ap-1538	65	16	the	the	DET
ap-1538	65	17	hidden	hide	VERB
ap-1538	65	18	layer	layer	NOUN
ap-1538	65	19	weight	weight	NOUN
ap-1538	65	20	matrix	matrix	NOUN
ap-1538	65	21	w	w	ADP
ap-1538	65	22	(	(	PUNCT
ap-1538	65	23	6	6	NUM
ap-1538	65	24	)	)	PUNCT
ap-1538	65	25	and	and	CCONJ
ap-1538	65	26	using	use	VERB
ap-1538	65	27	the	the	DET
ap-1538	65	28	classical	classical	ADJ
ap-1538	65	29	sigmoid	sigmoid	NOUN
ap-1538	65	30	function	function	NOUN
ap-1538	65	31	(	(	PUNCT
ap-1538	65	32	5	5	NUM
ap-1538	65	33	)	)	PUNCT
ap-1538	65	34	,	,	PUNCT
ap-1538	65	35	as	as	SCONJ
ap-1538	65	36	follows	follow	VERB
ap-1538	65	37	φ(ν	φ(ν	NOUN
ap-1538	65	38	)	)	PUNCT
ap-1538	65	39	=	=	SYM
ap-1538	65	40	2	2	NUM
ap-1538	65	41	1	1	NUM
ap-1538	65	42	+	+	CCONJ
ap-1538	65	43	e−ν	e−ν	NOUN
ap-1538	65	44	−	−	NOUN
ap-1538	65	45	1	1	NUM
ap-1538	65	46	,	,	PUNCT
ap-1538	65	47	(	(	PUNCT
ap-1538	65	48	5	5	NUM
ap-1538	65	49	)	)	PUNCT
ap-1538	65	50	where	where	SCONJ
ap-1538	65	51	ξ(k	ξ(k	NOUN
ap-1538	65	52	+	+	CCONJ
ap-1538	65	53	1	1	X
ap-1538	65	54	)	)	PUNCT
ap-1538	65	55	is	be	AUX
ap-1538	65	56	augmented	augment	VERB
ap-1538	65	57	with	with	ADP
ap-1538	65	58	a	a	DET
ap-1538	65	59	unit	unit	NOUN
ap-1538	65	60	as	as	ADP
ap-1538	65	61	ξ(k	ξ(k	PROPN
ap-1538	65	62	+	+	CCONJ
ap-1538	65	63	1	1	X
ap-1538	65	64	)	)	PUNCT
ap-1538	65	65	=	=	NOUN
ap-1538	66	1	[	[	PUNCT
ap-1538	66	2	1	1	NUM
ap-1538	66	3	φ(w	φ(w	PROPN
ap-1538	66	4	·	·	PUNCT
ap-1538	66	5	x(k	x(k	NOUN
ap-1538	66	6	)	)	PUNCT
ap-1538	66	7	)	)	PUNCT
ap-1538	66	8	]	]	PUNCT
ap-1538	66	9	,	,	PUNCT
ap-1538	66	10	(	(	PUNCT
ap-1538	66	11	6	6	NUM
ap-1538	66	12	)	)	PUNCT
ap-1538	66	13	where	where	SCONJ
ap-1538	66	14	the	the	DET
ap-1538	66	15	unit	unit	NOUN
ap-1538	66	16	allows	allow	VERB
ap-1538	66	17	the	the	DET
ap-1538	66	18	hidden	hidden	ADJ
ap-1538	66	19	layer	layer	NOUN
ap-1538	66	20	(	(	PUNCT
ap-1538	66	21	first	first	ADJ
ap-1538	66	22	column	column	NOUN
ap-1538	66	23	of	of	ADP
ap-1538	66	24	w	w	PROPN
ap-1538	66	25	)	)	PUNCT
ap-1538	66	26	and	and	CCONJ
ap-1538	66	27	also	also	ADV
ap-1538	66	28	the	the	DET
ap-1538	66	29	qnu	qnu	NOUN
ap-1538	66	30	(	(	PUNCT
ap-1538	66	31	v0,0	v0,0	NOUN
ap-1538	66	32	in	in	ADP
ap-1538	66	33	(	(	PUNCT
ap-1538	66	34	7	7	NUM
ap-1538	66	35	)	)	PUNCT
ap-1538	66	36	)	)	PUNCT
ap-1538	66	37	for	for	ADP
ap-1538	66	38	biases	bias	NOUN
ap-1538	66	39	,	,	PUNCT
ap-1538	66	40	so	so	CCONJ
ap-1538	66	41	the	the	DET
ap-1538	66	42	neural	neural	ADJ
ap-1538	66	43	output	output	NOUN
ap-1538	66	44	is	be	AUX
ap-1538	66	45	calculated	calculate	VERB
ap-1538	66	46	by	by	ADP
ap-1538	66	47	a	a	DET
ap-1538	66	48	quadratic	quadratic	ADJ
ap-1538	66	49	neural	neural	ADJ
ap-1538	66	50	unit	unit	NOUN
ap-1538	66	51	[	[	X
ap-1538	66	52	1	1	NUM
ap-1538	66	53	,	,	PUNCT
ap-1538	66	54	4	4	NUM
ap-1538	66	55	,	,	PUNCT
ap-1538	66	56	9	9	NUM
ap-1538	66	57	,	,	PUNCT
ap-1538	66	58	10	10	NUM
ap-1538	66	59	]	]	PUNCT
ap-1538	66	60	,	,	PUNCT
ap-1538	66	61	using	use	VERB
ap-1538	66	62	(	(	PUNCT
ap-1538	66	63	3)–(6	3)–(6	NUM
ap-1538	66	64	)	)	PUNCT
ap-1538	66	65	,	,	PUNCT
ap-1538	66	66	as	as	SCONJ
ap-1538	66	67	follows	follow	VERB
ap-1538	66	68	yn(k	yn(k	NOUN
ap-1538	66	69	+	+	CCONJ
ap-1538	66	70	ns	ns	NUM
ap-1538	66	71	)	)	PUNCT
ap-1538	66	72	=	=	PUNCT
ap-1538	66	73	∑	∑	PUNCT
ap-1538	66	74	i=0	i=0	PROPN
ap-1538	66	75	∑	∑	PROPN
ap-1538	66	76	j	j	PROPN
ap-1538	66	77	=	=	PROPN
ap-1538	66	78	i	i	PROPN
ap-1538	66	79	vi	vi	PROPN
ap-1538	66	80	,	,	PUNCT
ap-1538	66	81	j	j	PROPN
ap-1538	66	82	·	·	PUNCT
ap-1538	66	83	ξi(k	ξi(k	PUNCT
ap-1538	67	1	+	+	NOUN
ap-1538	67	2	1	1	X
ap-1538	67	3	)	)	PUNCT
ap-1538	67	4	·	·	PUNCT
ap-1538	67	5	ξj(k	ξj(k	PUNCT
ap-1538	68	1	+	+	CCONJ
ap-1538	68	2	1	1	NUM
ap-1538	68	3	)	)	PUNCT
ap-1538	68	4	.	.	PUNCT
ap-1538	69	1	(	(	PUNCT
ap-1538	69	2	7	7	X
ap-1538	69	3	)	)	PUNCT
ap-1538	69	4	the	the	DET
ap-1538	69	5	proposed	propose	VERB
ap-1538	69	6	dynamic	dynamic	ADJ
ap-1538	69	7	neural	neural	ADJ
ap-1538	69	8	network	network	NOUN
ap-1538	69	9	has	have	AUX
ap-1538	69	10	purposely	purposely	ADV
ap-1538	69	11	designed	design	VERB
ap-1538	69	12	properties	property	NOUN
ap-1538	69	13	that	that	PRON
ap-1538	69	14	are	be	AUX
ap-1538	69	15	worth	worth	ADJ
ap-1538	69	16	mentioning	mention	VERB
ap-1538	69	17	and	and	CCONJ
ap-1538	69	18	explaining	explain	VERB
ap-1538	69	19	.	.	PUNCT
ap-1538	70	1	the	the	DET
ap-1538	70	2	hidden	hide	VERB
ap-1538	70	3	recurrent	recurrent	ADJ
ap-1538	70	4	layer	layer	NOUN
ap-1538	70	5	of	of	ADP
ap-1538	70	6	neurons	neuron	NOUN
ap-1538	70	7	,	,	PUNCT
ap-1538	70	8	which	which	PRON
ap-1538	70	9	is	be	AUX
ap-1538	70	10	calculated	calculate	VERB
ap-1538	70	11	in	in	ADP
ap-1538	70	12	(	(	PUNCT
ap-1538	70	13	6	6	NUM
ap-1538	70	14	)	)	PUNCT
ap-1538	70	15	as	as	ADP
ap-1538	70	16	φ(w	φ(w	PROPN
ap-1538	70	17	·	·	PUNCT
ap-1538	70	18	x(k	x(k	PROPN
ap-1538	70	19	)	)	PUNCT
ap-1538	70	20	)	)	PUNCT
ap-1538	70	21	,	,	PUNCT
ap-1538	70	22	reduces	reduce	VERB
ap-1538	70	23	cognitively	cognitively	ADV
ap-1538	70	24	(	(	PUNCT
ap-1538	70	25	by	by	ADP
ap-1538	70	26	training	training	NOUN
ap-1538	70	27	)	)	PUNCT
ap-1538	70	28	the	the	DET
ap-1538	70	29	number	number	NOUN
ap-1538	70	30	of	of	ADP
ap-1538	70	31	already	already	ADV
ap-1538	70	32	pca	pca	NOUN
ap-1538	70	33	preprocessed	preprocesse	VERB
ap-1538	70	34	neural	neural	ADJ
ap-1538	70	35	inputs	input	NOUN
ap-1538	70	36	,	,	PUNCT
ap-1538	70	37	and	and	CCONJ
ap-1538	70	38	thus	thus	ADV
ap-1538	70	39	(	(	PUNCT
ap-1538	70	40	6	6	X
ap-1538	70	41	)	)	PUNCT
ap-1538	70	42	results	result	NOUN
ap-1538	70	43	in	in	ADP
ap-1538	70	44	the	the	DET
ap-1538	70	45	augmented	augment	VERB
ap-1538	70	46	vector	vector	NOUN
ap-1538	70	47	of	of	ADP
ap-1538	70	48	state	state	NOUN
ap-1538	70	49	variables	variable	NOUN
ap-1538	70	50	ξ(k+1	ξ(k+1	PRON
ap-1538	70	51	)	)	PUNCT
ap-1538	70	52	that	that	PRON
ap-1538	70	53	are	be	AUX
ap-1538	70	54	fed	feed	VERB
ap-1538	70	55	both	both	PRON
ap-1538	70	56	forward	forward	ADV
ap-1538	70	57	to	to	ADP
ap-1538	70	58	the	the	DET
ap-1538	70	59	qnu	qnu	NOUN
ap-1538	70	60	and	and	CCONJ
ap-1538	70	61	also	also	ADV
ap-1538	70	62	back	back	ADV
ap-1538	70	63	to	to	ADP
ap-1538	70	64	the	the	DET
ap-1538	70	65	network	network	NOUN
ap-1538	70	66	input	input	NOUN
ap-1538	70	67	x(k	x(k	PROPN
ap-1538	70	68	)	)	PUNCT
ap-1538	70	69	,	,	PUNCT
ap-1538	70	70	as	as	ADP
ap-1538	70	71	in	in	ADP
ap-1538	70	72	(	(	PUNCT
ap-1538	70	73	4	4	NUM
ap-1538	70	74	)	)	PUNCT
ap-1538	70	75	.	.	PUNCT
ap-1538	71	1	without	without	ADP
ap-1538	71	2	the	the	DET
ap-1538	71	3	first	first	ADJ
ap-1538	71	4	hidden	hide	VERB
ap-1538	71	5	layer	layer	NOUN
ap-1538	71	6	,	,	PUNCT
ap-1538	71	7	the	the	DET
ap-1538	71	8	number	number	NOUN
ap-1538	71	9	of	of	ADP
ap-1538	71	10	input	input	NOUN
ap-1538	71	11	variables	variable	NOUN
ap-1538	71	12	inputted	inputte	VERB
ap-1538	71	13	directly	directly	ADV
ap-1538	71	14	into	into	ADP
ap-1538	71	15	qnu	qnu	PRON
ap-1538	71	16	would	would	AUX
ap-1538	71	17	still	still	ADV
ap-1538	71	18	be	be	AUX
ap-1538	71	19	too	too	ADV
ap-1538	71	20	large	large	ADJ
ap-1538	71	21	for	for	ADP
ap-1538	71	22	the	the	DET
ap-1538	71	23	given	give	VERB
ap-1538	71	24	1	1	NUM
ap-1538	71	25	-	-	PUNCT
ap-1538	71	26	minute	minute	NOUN
ap-1538	71	27	sampling	sampling	NOUN
ap-1538	71	28	period	period	NOUN
ap-1538	71	29	,	,	PUNCT
ap-1538	71	30	as	as	SCONJ
ap-1538	71	31	we	we	PRON
ap-1538	71	32	feed	feed	VERB
ap-1538	71	33	an	an	DET
ap-1538	71	34	approximately	approximately	ADV
ap-1538	71	35	twelve	twelve	NUM
ap-1538	71	36	-	-	PUNCT
ap-1538	71	37	minute	minute	NOUN
ap-1538	71	38	history	history	NOUN
ap-1538	71	39	of	of	ADP
ap-1538	71	40	each	each	DET
ap-1538	71	41	pca	pca	NOUN
ap-1538	71	42	preprocessed	preprocesse	VERB
ap-1538	71	43	variable	variable	NOUN
ap-1538	71	44	into	into	ADP
ap-1538	71	45	the	the	DET
ap-1538	71	46	network	network	NOUN
ap-1538	71	47	input	input	NOUN
ap-1538	71	48	,	,	PUNCT
ap-1538	71	49	i.e.	i.e.	X
ap-1538	71	50	nya	nya	PROPN
ap-1538	71	51	−	−	PROPN
ap-1538	72	1	nyb	nyb	PROPN
ap-1538	72	2	=	=	PROPN
ap-1538	72	3	12	12	NUM
ap-1538	72	4	and	and	CCONJ
ap-1538	72	5	also	also	ADV
ap-1538	72	6	nua	nua	PROPN
ap-1538	72	7	−	−	PROPN
ap-1538	72	8	nub	nub	NOUN
ap-1538	72	9	=	=	PROPN
ap-1538	72	10	12	12	NUM
ap-1538	72	11	(	(	PUNCT
ap-1538	72	12	the	the	DET
ap-1538	72	13	estimated	estimate	VERB
ap-1538	72	14	time	time	NOUN
ap-1538	72	15	constant	constant	ADJ
ap-1538	72	16	of	of	ADP
ap-1538	72	17	this	this	DET
ap-1538	72	18	pulverized	pulverize	VERB
ap-1538	72	19	firing	firing	NOUN
ap-1538	72	20	boiler	boiler	NOUN
ap-1538	72	21	has	have	AUX
ap-1538	72	22	been	be	AUX
ap-1538	72	23	specified	specify	VERB
ap-1538	72	24	by	by	ADP
ap-1538	72	25	experts	expert	NOUN
ap-1538	72	26	as	as	ADP
ap-1538	72	27	approximately	approximately	ADV
ap-1538	72	28	12	12	NUM
ap-1538	72	29	minutes	minute	NOUN
ap-1538	72	30	)	)	PUNCT
ap-1538	72	31	.	.	PUNCT
ap-1538	73	1	also	also	ADV
ap-1538	73	2	,	,	PUNCT
ap-1538	73	3	the	the	DET
ap-1538	73	4	first	first	ADJ
ap-1538	73	5	layer	layer	NOUN
ap-1538	73	6	(	(	PUNCT
ap-1538	73	7	6	6	X
ap-1538	73	8	)	)	PUNCT
ap-1538	73	9	plays	play	VERB
ap-1538	73	10	a	a	DET
ap-1538	73	11	filtering	filter	VERB
ap-1538	73	12	role	role	NOUN
ap-1538	73	13	due	due	ADP
ap-1538	73	14	to	to	ADP
ap-1538	73	15	its	its	PRON
ap-1538	73	16	step	step	NOUN
ap-1538	73	17	delayed	delay	VERB
ap-1538	73	18	feedback	feedback	NOUN
ap-1538	73	19	to	to	ADP
ap-1538	73	20	the	the	DET
ap-1538	73	21	network	network	NOUN
ap-1538	73	22	input	input	NOUN
ap-1538	73	23	(	(	PUNCT
ap-1538	73	24	4	4	NUM
ap-1538	73	25	)	)	PUNCT
ap-1538	73	26	,	,	PUNCT
ap-1538	73	27	and	and	CCONJ
ap-1538	73	28	its	its	PRON
ap-1538	73	29	recurrent	recurrent	ADJ
ap-1538	73	30	feedback	feedback	NOUN
ap-1538	73	31	naturally	naturally	ADV
ap-1538	73	32	calls	call	VERB
ap-1538	73	33	for	for	ADP
ap-1538	73	34	training	training	NOUN
ap-1538	73	35	by	by	ADP
ap-1538	73	36	the	the	DET
ap-1538	73	37	backpropagation	backpropagation	NOUN
ap-1538	73	38	through	through	ADP
ap-1538	73	39	time	time	NOUN
ap-1538	73	40	method	method	NOUN
ap-1538	73	41	(	(	PUNCT
ap-1538	73	42	bptt	bptt	NOUN
ap-1538	73	43	)	)	PUNCT
ap-1538	74	1	[	[	X
ap-1538	74	2	15–17	15–17	NUM
ap-1538	74	3	]	]	PUNCT
ap-1538	74	4	,	,	PUNCT
ap-1538	74	5	which	which	PRON
ap-1538	74	6	is	be	AUX
ap-1538	74	7	a	a	DET
ap-1538	74	8	powerful	powerful	ADJ
ap-1538	74	9	and	and	CCONJ
ap-1538	74	10	efficient	efficient	ADJ
ap-1538	74	11	and	and	CCONJ
ap-1538	74	12	yet	yet	ADV
ap-1538	74	13	practical	practical	ADJ
ap-1538	74	14	optimization	optimization	NOUN
ap-1538	74	15	method	method	NOUN
ap-1538	74	16	,	,	PUNCT
ap-1538	74	17	as	as	SCONJ
ap-1538	74	18	it	it	PRON
ap-1538	74	19	can	can	AUX
ap-1538	74	20	be	be	AUX
ap-1538	74	21	achieved	achieve	VERB
ap-1538	74	22	by	by	ADP
ap-1538	74	23	a	a	DET
ap-1538	74	24	combination	combination	NOUN
ap-1538	74	25	of	of	ADP
ap-1538	74	26	a	a	DET
ap-1538	74	27	gradient	gradient	ADJ
ap-1538	74	28	descent	descent	NOUN
ap-1538	74	29	rule	rule	NOUN
ap-1538	74	30	and	and	CCONJ
ap-1538	74	31	the	the	DET
ap-1538	74	32	levenberg	levenberg	PROPN
ap-1538	74	33	-	-	PUNCT
ap-1538	74	34	marquardt	marquardt	PROPN
ap-1538	74	35	algorithm	algorithm	NOUN
ap-1538	75	1	[	[	X
ap-1538	75	2	18	18	NUM
ap-1538	75	3	]	]	PUNCT
ap-1538	75	4	.	.	PUNCT
ap-1538	76	1	the	the	DET
ap-1538	76	2	sigmoid	sigmoid	NOUN
ap-1538	76	3	function	function	NOUN
ap-1538	76	4	ϕ	ϕ	NOUN
ap-1538	76	5	(	(	PUNCT
ap-1538	76	6	.	.	PUNCT
ap-1538	76	7	)	)	PUNCT
ap-1538	76	8	,	,	PUNCT
ap-1538	76	9	which	which	PRON
ap-1538	76	10	is	be	AUX
ap-1538	76	11	usually	usually	ADV
ap-1538	76	12	considered	consider	VERB
ap-1538	76	13	as	as	ADP
ap-1538	76	14	a	a	DET
ap-1538	76	15	main	main	ADJ
ap-1538	76	16	nonlinearity	nonlinearity	NOUN
ap-1538	76	17	of	of	ADP
ap-1538	76	18	conventional	conventional	ADJ
ap-1538	76	19	neural	neural	ADJ
ap-1538	76	20	networks	network	NOUN
ap-1538	76	21	,	,	PUNCT
ap-1538	76	22	has	have	VERB
ap-1538	76	23	another	another	DET
ap-1538	76	24	importance	importance	NOUN
ap-1538	76	25	for	for	ADP
ap-1538	76	26	this	this	DET
ap-1538	76	27	dynamic	dynamic	ADJ
ap-1538	76	28	network	network	NOUN
ap-1538	76	29	,	,	PUNCT
ap-1538	76	30	because	because	SCONJ
ap-1538	76	31	the	the	DET
ap-1538	76	32	major	major	ADJ
ap-1538	76	33	nonlinearity	nonlinearity	NOUN
ap-1538	76	34	is	be	AUX
ap-1538	76	35	provided	provide	VERB
ap-1538	76	36	by	by	ADP
ap-1538	76	37	the	the	DET
ap-1538	76	38	qnu	qnu	PROPN
ap-1538	77	1	[	[	X
ap-1538	77	2	9	9	NUM
ap-1538	77	3	,	,	PUNCT
ap-1538	77	4	10	10	NUM
ap-1538	77	5	,	,	PUNCT
ap-1538	77	6	18	18	NUM
ap-1538	77	7	]	]	PUNCT
ap-1538	77	8	.	.	PUNCT
ap-1538	78	1	the	the	DET
ap-1538	78	2	sigmoid	sigmoid	NOUN
ap-1538	78	3	function	function	NOUN
ap-1538	78	4	ϕ	ϕ	PROPN
ap-1538	78	5	(	(	PUNCT
ap-1538	78	6	.	.	PUNCT
ap-1538	78	7	)	)	PUNCT
ap-1538	78	8	limits	limit	VERB
ap-1538	78	9	the	the	DET
ap-1538	78	10	output	output	NOUN
ap-1538	78	11	of	of	ADP
ap-1538	78	12	the	the	DET
ap-1538	78	13	hidden	hide	VERB
ap-1538	78	14	layer	layer	NOUN
ap-1538	78	15	into	into	ADP
ap-1538	78	16	the	the	DET
ap-1538	78	17	given	give	VERB
ap-1538	78	18	range	range	NOUN
ap-1538	78	19	of	of	ADP
ap-1538	78	20	values	value	NOUN
ap-1538	78	21	(	(	PUNCT
ap-1538	78	22	−1,+1	−1,+1	VERB
ap-1538	78	23	)	)	PUNCT
ap-1538	78	24	that	that	PRON
ap-1538	78	25	importantly	importantly	ADV
ap-1538	78	26	assures	assure	VERB
ap-1538	78	27	stability	stability	NOUN
ap-1538	78	28	of	of	ADP
ap-1538	78	29	the	the	DET
ap-1538	78	30	hidden	hide	VERB
ap-1538	78	31	layer	layer	NOUN
ap-1538	78	32	(	(	PUNCT
ap-1538	78	33	as	as	ADP
ap-1538	78	34	of	of	ADP
ap-1538	78	35	a	a	DET
ap-1538	78	36	discrete	discrete	ADJ
ap-1538	78	37	time	time	NOUN
ap-1538	78	38	dynamic	dynamic	ADJ
ap-1538	78	39	system	system	NOUN
ap-1538	78	40	,	,	PUNCT
ap-1538	78	41	and	and	CCONJ
ap-1538	78	42	this	this	PRON
ap-1538	78	43	could	could	AUX
ap-1538	78	44	not	not	PART
ap-1538	78	45	be	be	AUX
ap-1538	78	46	so	so	ADV
ap-1538	78	47	simply	simply	ADV
ap-1538	78	48	assured	assure	VERB
ap-1538	78	49	for	for	ADP
ap-1538	78	50	continuous	continuous	ADJ
ap-1538	78	51	-	-	PUNCT
ap-1538	78	52	time	time	NOUN
ap-1538	78	53	nns	nn	NOUN
ap-1538	78	54	)	)	PUNCT
ap-1538	78	55	.	.	PUNCT
ap-1538	79	1	then	then	ADV
ap-1538	79	2	,	,	PUNCT
ap-1538	79	3	there	there	PRON
ap-1538	79	4	are	be	VERB
ap-1538	79	5	always	always	ADV
ap-1538	79	6	limited	limited	ADJ
ap-1538	79	7	values	value	NOUN
ap-1538	79	8	entering	enter	VERB
ap-1538	79	9	the	the	DET
ap-1538	79	10	qnu	qnu	NOUN
ap-1538	79	11	,	,	PUNCT
ap-1538	79	12	so	so	ADV
ap-1538	79	13	its	its	PRON
ap-1538	79	14	output	output	NOUN
ap-1538	79	15	is	be	AUX
ap-1538	79	16	also	also	ADV
ap-1538	79	17	naturally	naturally	ADV
ap-1538	79	18	limited	limit	VERB
ap-1538	79	19	;	;	PUNCT
ap-1538	79	20	thus	thus	ADV
ap-1538	79	21	,	,	PUNCT
ap-1538	79	22	the	the	DET
ap-1538	79	23	stability	stability	NOUN
ap-1538	79	24	of	of	ADP
ap-1538	79	25	the	the	DET
ap-1538	79	26	state	state	NOUN
ap-1538	79	27	variables	variable	NOUN
ap-1538	79	28	and	and	CCONJ
ap-1538	79	29	of	of	ADP
ap-1538	79	30	the	the	DET
ap-1538	79	31	output	output	NOUN
ap-1538	79	32	of	of	ADP
ap-1538	79	33	the	the	DET
ap-1538	79	34	proposed	propose	VERB
ap-1538	79	35	neural	neural	ADJ
ap-1538	79	36	network	network	NOUN
ap-1538	79	37	is	be	AUX
ap-1538	79	38	naturally	naturally	ADV
ap-1538	79	39	assured	assure	VERB
ap-1538	79	40	by	by	ADP
ap-1538	79	41	preserving	preserve	VERB
ap-1538	79	42	the	the	DET
ap-1538	79	43	sigmoid	sigmoid	NOUN
ap-1538	79	44	function	function	NOUN
ap-1538	79	45	in	in	ADP
ap-1538	79	46	hidden	hidden	ADJ
ap-1538	79	47	neurons	neuron	NOUN
ap-1538	79	48	.	.	PUNCT
ap-1538	80	1	as	as	SCONJ
ap-1538	80	2	regards	regard	VERB
ap-1538	80	3	the	the	DET
ap-1538	80	4	stability	stability	NOUN
ap-1538	80	5	of	of	ADP
ap-1538	80	6	the	the	DET
ap-1538	80	7	learning	learning	NOUN
ap-1538	80	8	algorithm	algorithm	NOUN
ap-1538	80	9	,	,	PUNCT
ap-1538	80	10	and	and	CCONJ
ap-1538	80	11	thus	thus	ADV
ap-1538	80	12	its	its	PRON
ap-1538	80	13	convergence	convergence	NOUN
ap-1538	80	14	,	,	PUNCT
ap-1538	80	15	we	we	PRON
ap-1538	80	16	proposed	propose	VERB
ap-1538	80	17	a	a	DET
ap-1538	80	18	novel	novel	ADJ
ap-1538	80	19	approach	approach	NOUN
ap-1538	80	20	to	to	ADP
ap-1538	80	21	weight	weight	NOUN
ap-1538	80	22	-	-	PUNCT
ap-1538	80	23	update	update	NOUN
ap-1538	80	24	stability	stability	NOUN
ap-1538	80	25	for	for	ADP
ap-1538	80	26	gradient	gradient	ADJ
ap-1538	80	27	descent	descent	NOUN
ap-1538	80	28	training	training	NOUN
ap-1538	80	29	of	of	ADP
ap-1538	80	30	qnu	qnu	NOUN
ap-1538	80	31	in	in	ADP
ap-1538	80	32	[	[	X
ap-1538	80	33	10	10	NUM
ap-1538	80	34	]	]	PUNCT
ap-1538	80	35	,	,	PUNCT
ap-1538	80	36	and	and	CCONJ
ap-1538	80	37	this	this	DET
ap-1538	80	38	approach	approach	NOUN
ap-1538	80	39	is	be	AUX
ap-1538	80	40	applicable	applicable	ADJ
ap-1538	80	41	to	to	ADP
ap-1538	80	42	both	both	CCONJ
ap-1538	80	43	static	static	ADJ
ap-1538	80	44	and	and	CCONJ
ap-1538	80	45	dynamic	dynamic	ADJ
ap-1538	80	46	qnu	qnu	NOUN
ap-1538	80	47	,	,	PUNCT
ap-1538	80	48	and	and	CCONJ
ap-1538	80	49	also	also	ADV
ap-1538	80	50	to	to	ADP
ap-1538	80	51	the	the	DET
ap-1538	80	52	hidden	hide	VERB
ap-1538	80	53	-	-	PUNCT
ap-1538	80	54	layer	layer	NOUN
ap-1538	80	55	weight	weight	NOUN
ap-1538	80	56	system	system	NOUN
ap-1538	80	57	of	of	ADP
ap-1538	80	58	this	this	DET
ap-1538	80	59	network	network	NOUN
ap-1538	80	60	for	for	ADP
ap-1538	80	61	nox	nox	NOUN
ap-1538	80	62	prediction	prediction	NOUN
ap-1538	80	63	.	.	PUNCT
ap-1538	81	1	4	4	NUM
ap-1538	81	2	results	result	NOUN
ap-1538	81	3	and	and	CCONJ
ap-1538	81	4	discussion	discussion	NOUN
ap-1538	81	5	this	this	DET
ap-1538	81	6	section	section	NOUN
ap-1538	81	7	shows	show	VERB
ap-1538	81	8	the	the	DET
ap-1538	81	9	results	result	NOUN
ap-1538	81	10	of	of	ADP
ap-1538	81	11	3	3	NUM
ap-1538	81	12	-	-	PUNCT
ap-1538	81	13	minute	minute	NOUN
ap-1538	81	14	predictions	prediction	NOUN
ap-1538	81	15	of	of	ADP
ap-1538	81	16	nox	nox	NOUN
ap-1538	81	17	emissions	emission	NOUN
ap-1538	81	18	(	(	PUNCT
ap-1538	81	19	in	in	ADP
ap-1538	81	20	fact	fact	NOUN
ap-1538	81	21	the	the	DET
ap-1538	81	22	3	3	NUM
ap-1538	81	23	-	-	PUNCT
ap-1538	81	24	minute	minute	NOUN
ap-1538	81	25	floating	float	VERB
ap-1538	81	26	averages	average	NOUN
ap-1538	81	27	)	)	PUNCT
ap-1538	81	28	of	of	ADP
ap-1538	81	29	the	the	DET
ap-1538	81	30	pulverized	pulverize	VERB
ap-1538	81	31	firing	firing	NOUN
ap-1538	81	32	boiler	boiler	NOUN
ap-1538	81	33	at	at	ADP
ap-1538	81	34	eme	eme	NOUN
ap-1538	81	35	1	1	NUM
ap-1538	81	36	by	by	ADP
ap-1538	81	37	the	the	DET
ap-1538	81	38	proposed	propose	VERB
ap-1538	81	39	neural	neural	ADJ
ap-1538	81	40	network	network	NOUN
ap-1538	81	41	(	(	PUNCT
ap-1538	81	42	ns	ns	PROPN
ap-1538	81	43	=	=	SYM
ap-1538	81	44	3	3	NUM
ap-1538	81	45	,	,	PUNCT
ap-1538	81	46	sampling	sample	VERB
ap-1538	81	47	1	1	NUM
ap-1538	81	48	minute	minute	NOUN
ap-1538	81	49	)	)	PUNCT
ap-1538	81	50	.	.	PUNCT
ap-1538	82	1	the	the	DET
ap-1538	82	2	recurrent	recurrent	ADJ
ap-1538	82	3	network	network	NOUN
ap-1538	82	4	does	do	AUX
ap-1538	82	5	not	not	PART
ap-1538	82	6	include	include	VERB
ap-1538	82	7	measured	measure	VERB
ap-1538	82	8	o2	o2	PROPN
ap-1538	82	9	,	,	PUNCT
ap-1538	82	10	nox	nox	NOUN
ap-1538	82	11	,	,	PUNCT
ap-1538	82	12	or	or	CCONJ
ap-1538	82	13	co	co	VERB
ap-1538	82	14	on	on	ADP
ap-1538	82	15	its	its	PRON
ap-1538	82	16	input	input	NOUN
ap-1538	82	17	;	;	PUNCT
ap-1538	82	18	the	the	DET
ap-1538	82	19	introduction	introduction	NOUN
ap-1538	82	20	of	of	ADP
ap-1538	82	21	nox	nox	NOUN
ap-1538	82	22	as	as	ADP
ap-1538	82	23	a	a	DET
ap-1538	82	24	measured	measured	ADJ
ap-1538	82	25	external	external	ADJ
ap-1538	82	26	input	input	NOUN
ap-1538	82	27	resulted	result	VERB
ap-1538	82	28	in	in	ADP
ap-1538	82	29	a	a	DET
ap-1538	82	30	prediction	prediction	NOUN
ap-1538	82	31	failure	failure	NOUN
ap-1538	82	32	;	;	PUNCT
ap-1538	82	33	the	the	DET
ap-1538	82	34	model	model	NOUN
ap-1538	82	35	learned	learn	VERB
ap-1538	82	36	to	to	PART
ap-1538	82	37	follow	follow	VERB
ap-1538	82	38	blindly	blindly	ADV
ap-1538	82	39	the	the	DET
ap-1538	82	40	previous	previous	ADJ
ap-1538	82	41	measured	measured	ADJ
ap-1538	82	42	nox	nox	NOUN
ap-1538	82	43	,	,	PUNCT
ap-1538	82	44	19	19	NUM
ap-1538	82	45	acta	acta	PROPN
ap-1538	82	46	polytechnica	polytechnica	PROPN
ap-1538	82	47	vol	vol	NOUN
ap-1538	82	48	.	.	PROPN
ap-1538	83	1	52	52	NUM
ap-1538	83	2	no	no	NOUN
ap-1538	83	3	.	.	PUNCT
ap-1538	84	1	3/2012	3/2012	NUM
ap-1538	84	2	figure	figure	NOUN
ap-1538	84	3	2	2	NUM
ap-1538	84	4	:	:	PUNCT
ap-1538	84	5	nox	nox	NOUN
ap-1538	84	6	prediction	prediction	NOUN
ap-1538	84	7	by	by	ADP
ap-1538	84	8	the	the	DET
ap-1538	84	9	neural	neural	ADJ
ap-1538	84	10	network	network	NOUN
ap-1538	84	11	(	(	PUNCT
ap-1538	84	12	1)–(7	1)–(7	NUM
ap-1538	84	13	)	)	PUNCT
ap-1538	84	14	with	with	ADP
ap-1538	84	15	re	re	NOUN
ap-1538	84	16	-	-	NOUN
ap-1538	84	17	configurations	configuration	NOUN
ap-1538	84	18	and	and	CCONJ
ap-1538	84	19	re	re	NOUN
ap-1538	84	20	-	-	NOUN
ap-1538	84	21	training	training	NOUN
ap-1538	84	22	(	(	PUNCT
ap-1538	84	23	figure	figure	NOUN
ap-1538	84	24	1	1	NUM
ap-1538	84	25	)	)	PUNCT
ap-1538	84	26	figure	figure	NOUN
ap-1538	84	27	3	3	NUM
ap-1538	84	28	:	:	PUNCT
ap-1538	84	29	detail	detail	NOUN
ap-1538	84	30	from	from	ADP
ap-1538	84	31	figure	figure	NOUN
ap-1538	84	32	2	2	NUM
ap-1538	84	33	—	—	PUNCT
ap-1538	84	34	a	a	DET
ap-1538	84	35	good	good	ADJ
ap-1538	84	36	prediction	prediction	NOUN
ap-1538	84	37	figure	figure	NOUN
ap-1538	84	38	4	4	NUM
ap-1538	84	39	:	:	PUNCT
ap-1538	84	40	detail	detail	NOUN
ap-1538	84	41	from	from	ADP
ap-1538	84	42	figure	figure	NOUN
ap-1538	84	43	2	2	NUM
ap-1538	84	44	—	—	PUNCT
ap-1538	84	45	a	a	DET
ap-1538	84	46	bad	bad	ADJ
ap-1538	84	47	prediction	prediction	NOUN
ap-1538	84	48	due	due	ADP
ap-1538	84	49	to	to	ADP
ap-1538	84	50	outliers	outlier	NOUN
ap-1538	84	51	in	in	ADP
ap-1538	84	52	the	the	DET
ap-1538	84	53	training	training	NOUN
ap-1538	84	54	data	datum	NOUN
ap-1538	84	55	which	which	PRON
ap-1538	84	56	is	be	AUX
ap-1538	84	57	a	a	DET
ap-1538	84	58	typical	typical	ADJ
ap-1538	84	59	problem	problem	NOUN
ap-1538	84	60	with	with	ADP
ap-1538	84	61	the	the	DET
ap-1538	84	62	improper	improper	ADJ
ap-1538	84	63	use	use	NOUN
ap-1538	84	64	of	of	ADP
ap-1538	84	65	neural	neural	ADJ
ap-1538	84	66	networks	network	NOUN
ap-1538	84	67	for	for	ADP
ap-1538	84	68	complicated	complicated	ADJ
ap-1538	84	69	systems	system	NOUN
ap-1538	84	70	.	.	PUNCT
ap-1538	85	1	the	the	DET
ap-1538	85	2	permanent	permanent	ADJ
ap-1538	85	3	computation	computation	NOUN
ap-1538	85	4	run	run	NOUN
ap-1538	85	5	of	of	ADP
ap-1538	85	6	prediction	prediction	NOUN
ap-1538	85	7	for	for	ADP
ap-1538	85	8	24	24	NUM
ap-1538	85	9	days	day	NOUN
ap-1538	85	10	,	,	PUNCT
ap-1538	85	11	with	with	ADP
ap-1538	85	12	one	one	NUM
ap-1538	85	13	-	-	PUNCT
ap-1538	85	14	minute	minute	NOUN
ap-1538	85	15	sampling	sampling	NOUN
ap-1538	85	16	and	and	CCONJ
ap-1538	85	17	retraining	retrain	VERB
ap-1538	85	18	every	every	DET
ap-1538	85	19	30	30	NUM
ap-1538	85	20	minutes	minute	NOUN
ap-1538	85	21	,	,	PUNCT
ap-1538	85	22	is	be	AUX
ap-1538	85	23	shown	show	VERB
ap-1538	85	24	in	in	ADP
ap-1538	85	25	figure	figure	NOUN
ap-1538	85	26	2	2	NUM
ap-1538	85	27	.	.	PUNCT
ap-1538	85	28	figure	figure	NOUN
ap-1538	85	29	2	2	NUM
ap-1538	85	30	shows	show	NOUN
ap-1538	85	31	superimposed	superimpose	VERB
ap-1538	85	32	24	24	NUM
ap-1538	85	33	-	-	PUNCT
ap-1538	85	34	day	day	NOUN
ap-1538	85	35	recordings	recording	NOUN
ap-1538	85	36	of	of	ADP
ap-1538	85	37	measured	measure	VERB
ap-1538	85	38	nox	nox	NOUN
ap-1538	85	39	(	(	PUNCT
ap-1538	85	40	thick	thick	ADJ
ap-1538	85	41	line	line	NOUN
ap-1538	85	42	)	)	PUNCT
ap-1538	85	43	and	and	CCONJ
ap-1538	85	44	the	the	DET
ap-1538	85	45	three	three	NUM
ap-1538	85	46	-	-	PUNCT
ap-1538	85	47	minute	minute	NOUN
ap-1538	85	48	prediction	prediction	NOUN
ap-1538	85	49	(	(	PUNCT
ap-1538	85	50	ns	ns	NOUN
ap-1538	85	51	=	=	NOUN
ap-1538	85	52	3	3	NUM
ap-1538	85	53	)	)	PUNCT
ap-1538	85	54	of	of	ADP
ap-1538	85	55	nox	nox	NOUN
ap-1538	85	56	(	(	PUNCT
ap-1538	85	57	bold	bold	ADJ
ap-1538	85	58	line	line	NOUN
ap-1538	85	59	)	)	PUNCT
ap-1538	85	60	(	(	PUNCT
ap-1538	85	61	the	the	DET
ap-1538	85	62	three	three	NUM
ap-1538	85	63	-	-	PUNCT
ap-1538	85	64	minute	minute	NOUN
ap-1538	85	65	floating	float	VERB
ap-1538	85	66	average	average	NOUN
ap-1538	85	67	of	of	ADP
ap-1538	85	68	nox	nox	NOUN
ap-1538	85	69	is	be	AUX
ap-1538	85	70	predicted	predict	VERB
ap-1538	85	71	)	)	PUNCT
ap-1538	85	72	;	;	PUNCT
ap-1538	85	73	the	the	DET
ap-1538	85	74	neural	neural	ADJ
ap-1538	85	75	network	network	NOUN
ap-1538	85	76	is	be	AUX
ap-1538	85	77	retrained	retrain	VERB
ap-1538	85	78	every	every	DET
ap-1538	85	79	30	30	NUM
ap-1538	85	80	minutes	minute	NOUN
ap-1538	85	81	with	with	ADP
ap-1538	85	82	5	5	NUM
ap-1538	85	83	hours	hour	NOUN
ap-1538	85	84	of	of	ADP
ap-1538	85	85	the	the	DET
ap-1538	85	86	very	very	ADV
ap-1538	85	87	last	last	ADJ
ap-1538	85	88	measured	measured	ADJ
ap-1538	85	89	data	datum	NOUN
ap-1538	85	90	(	(	PUNCT
ap-1538	85	91	one	one	NUM
ap-1538	85	92	-	-	PUNCT
ap-1538	85	93	minute	minute	NOUN
ap-1538	85	94	sampling	sampling	NOUN
ap-1538	85	95	,	,	PUNCT
ap-1538	85	96	the	the	DET
ap-1538	85	97	model	model	NOUN
ap-1538	85	98	input	input	NOUN
ap-1538	85	99	excludes	exclude	VERB
ap-1538	85	100	measured	measure	VERB
ap-1538	85	101	o2	o2	PROPN
ap-1538	85	102	,	,	PUNCT
ap-1538	85	103	nox	nox	NOUN
ap-1538	85	104	,	,	PUNCT
ap-1538	85	105	co	co	NOUN
ap-1538	85	106	)	)	PUNCT
ap-1538	85	107	.	.	PUNCT
ap-1538	86	1	the	the	DET
ap-1538	86	2	network	network	NOUN
ap-1538	86	3	(	(	PUNCT
ap-1538	86	4	1)–(7	1)–(7	NUM
ap-1538	86	5	)	)	PUNCT
ap-1538	86	6	was	be	AUX
ap-1538	86	7	retrained	retrain	VERB
ap-1538	86	8	every	every	DET
ap-1538	86	9	30	30	NUM
ap-1538	86	10	minutes	minute	NOUN
ap-1538	86	11	by	by	ADP
ap-1538	86	12	the	the	DET
ap-1538	86	13	back	back	ADJ
ap-1538	86	14	propagation	propagation	NOUN
ap-1538	86	15	through	through	ADP
ap-1538	86	16	time	time	NOUN
ap-1538	86	17	algorithm	algorithm	NOUN
ap-1538	86	18	[	[	X
ap-1538	86	19	18	18	NUM
ap-1538	86	20	]	]	PUNCT
ap-1538	86	21	with	with	ADP
ap-1538	86	22	blindly	blindly	ADV
ap-1538	86	23	selected	select	VERB
ap-1538	86	24	most	most	ADV
ap-1538	86	25	recent	recent	ADJ
ap-1538	86	26	history	history	NOUN
ap-1538	86	27	of	of	ADP
ap-1538	86	28	298	298	NUM
ap-1538	86	29	samples	sample	NOUN
ap-1538	86	30	(	(	PUNCT
ap-1538	86	31	5	5	NUM
ap-1538	86	32	hours	hour	NOUN
ap-1538	86	33	)	)	PUNCT
ap-1538	86	34	of	of	ADP
ap-1538	86	35	the	the	DET
ap-1538	86	36	measured	measure	VERB
ap-1538	86	37	process	process	NOUN
ap-1538	86	38	variables	variable	NOUN
ap-1538	86	39	.	.	PUNCT
ap-1538	87	1	each	each	DET
ap-1538	87	2	retraining	retrain	VERB
ap-1538	87	3	took	take	VERB
ap-1538	87	4	less	less	ADJ
ap-1538	87	5	than	than	ADP
ap-1538	87	6	3	3	NUM
ap-1538	87	7	minutes	minute	NOUN
ap-1538	87	8	of	of	ADP
ap-1538	87	9	real	real	ADJ
ap-1538	87	10	computation	computation	NOUN
ap-1538	87	11	time	time	NOUN
ap-1538	87	12	in	in	ADP
ap-1538	87	13	matlab	matlab	PROPN
ap-1538	87	14	on	on	ADP
ap-1538	87	15	a	a	DET
ap-1538	87	16	pc	pc	NOUN
ap-1538	87	17	(	(	PUNCT
ap-1538	87	18	win7	win7	NOUN
ap-1538	87	19	,	,	PUNCT
ap-1538	87	20	i7	i7	NOUN
ap-1538	87	21	)	)	PUNCT
ap-1538	87	22	,	,	PUNCT
ap-1538	87	23	and	and	CCONJ
ap-1538	87	24	this	this	PRON
ap-1538	87	25	is	be	AUX
ap-1538	87	26	practical	practical	ADJ
ap-1538	87	27	for	for	ADP
ap-1538	87	28	real	real	ADJ
ap-1538	87	29	time	time	NOUN
ap-1538	87	30	retraining	retrain	VERB
ap-1538	87	31	implementation	implementation	NOUN
ap-1538	87	32	.	.	PUNCT
ap-1538	88	1	the	the	DET
ap-1538	88	2	good	good	ADJ
ap-1538	88	3	performance	performance	NOUN
ap-1538	88	4	of	of	ADP
ap-1538	88	5	nox	nox	NOUN
ap-1538	88	6	prediction	prediction	NOUN
ap-1538	88	7	is	be	AUX
ap-1538	88	8	apparent	apparent	ADJ
ap-1538	88	9	from	from	ADP
ap-1538	88	10	the	the	DET
ap-1538	88	11	details	detail	NOUN
ap-1538	88	12	in	in	ADP
ap-1538	88	13	figure	figure	NOUN
ap-1538	88	14	3	3	NUM
ap-1538	88	15	.	.	PUNCT
ap-1538	89	1	also	also	ADV
ap-1538	89	2	,	,	PUNCT
ap-1538	89	3	figure	figure	VERB
ap-1538	89	4	3	3	NUM
ap-1538	89	5	shows	show	VERB
ap-1538	89	6	a	a	DET
ap-1538	89	7	temporary	temporary	ADJ
ap-1538	89	8	measurement	measurement	NOUN
ap-1538	89	9	outage	outage	NOUN
ap-1538	89	10	(	(	PUNCT
ap-1538	89	11	∼	∼	NOUN
ap-1538	89	12	15	15	NUM
ap-1538	89	13	minutes	minute	NOUN
ap-1538	89	14	)	)	PUNCT
ap-1538	89	15	after	after	ADP
ap-1538	89	16	sample	sample	NOUN
ap-1538	89	17	k	k	PROPN
ap-1538	89	18	=	=	PUNCT
ap-1538	89	19	2.82e	2.82e	PROPN
ap-1538	89	20	+	+	CCONJ
ap-1538	89	21	4	4	NUM
ap-1538	89	22	;	;	PUNCT
ap-1538	89	23	the	the	DET
ap-1538	89	24	output	output	NOUN
ap-1538	89	25	of	of	ADP
ap-1538	89	26	the	the	DET
ap-1538	89	27	dynamic	dynamic	ADJ
ap-1538	89	28	neural	neural	ADJ
ap-1538	89	29	20	20	NUM
ap-1538	89	30	acta	acta	PROPN
ap-1538	89	31	polytechnica	polytechnica	PROPN
ap-1538	89	32	vol	vol	NOUN
ap-1538	89	33	.	.	PROPN
ap-1538	90	1	52	52	NUM
ap-1538	90	2	no	no	NOUN
ap-1538	90	3	.	.	PUNCT
ap-1538	91	1	3/2012	3/2012	NUM
ap-1538	91	2	network	network	NOUN
ap-1538	91	3	substitutes	substitute	VERB
ap-1538	91	4	the	the	DET
ap-1538	91	5	measurement	measurement	NOUN
ap-1538	91	6	outage	outage	NOUN
ap-1538	91	7	;	;	PUNCT
ap-1538	91	8	the	the	DET
ap-1538	91	9	good	good	ADJ
ap-1538	91	10	neural	neural	ADJ
ap-1538	91	11	network	network	NOUN
ap-1538	91	12	prediction	prediction	NOUN
ap-1538	91	13	depends	depend	VERB
ap-1538	91	14	on	on	ADP
ap-1538	91	15	availability	availability	NOUN
ap-1538	91	16	of	of	ADP
ap-1538	91	17	good	good	ADJ
ap-1538	91	18	retraining	retraining	ADJ
ap-1538	91	19	data	datum	NOUN
ap-1538	91	20	in	in	ADP
ap-1538	91	21	this	this	DET
ap-1538	91	22	observed	observe	VERB
ap-1538	91	23	period	period	NOUN
ap-1538	91	24	.	.	PUNCT
ap-1538	92	1	however	however	ADV
ap-1538	92	2	,	,	PUNCT
ap-1538	92	3	this	this	DET
ap-1538	92	4	kind	kind	NOUN
ap-1538	92	5	of	of	ADP
ap-1538	92	6	nox	nox	NOUN
ap-1538	92	7	outage	outage	NOUN
ap-1538	92	8	affects	affect	VERB
ap-1538	92	9	retraining	retrain	VERB
ap-1538	92	10	,	,	PUNCT
ap-1538	92	11	see	see	VERB
ap-1538	92	12	figure	figure	NOUN
ap-1538	92	13	4	4	NUM
ap-1538	92	14	.	.	PUNCT
ap-1538	93	1	the	the	DET
ap-1538	93	2	prediction	prediction	NOUN
ap-1538	93	3	accuracy	accuracy	NOUN
ap-1538	93	4	and	and	CCONJ
ap-1538	93	5	prediction	prediction	NOUN
ap-1538	93	6	reliability	reliability	NOUN
ap-1538	93	7	for	for	ADP
ap-1538	93	8	nox	nox	NOUN
ap-1538	93	9	prediction	prediction	NOUN
ap-1538	93	10	depends	depend	VERB
ap-1538	93	11	significantly	significantly	ADV
ap-1538	93	12	on	on	ADP
ap-1538	93	13	the	the	DET
ap-1538	93	14	retraining	retrain	VERB
ap-1538	93	15	data	datum	NOUN
ap-1538	93	16	(	(	PUNCT
ap-1538	93	17	here	here	ADV
ap-1538	93	18	,	,	PUNCT
ap-1538	93	19	the	the	DET
ap-1538	93	20	last	last	ADJ
ap-1538	93	21	298	298	NUM
ap-1538	93	22	samples	sample	NOUN
ap-1538	93	23	before	before	ADP
ap-1538	93	24	each	each	DET
ap-1538	93	25	predicted	predict	VERB
ap-1538	93	26	value	value	NOUN
ap-1538	93	27	)	)	PUNCT
ap-1538	93	28	.	.	PUNCT
ap-1538	94	1	the	the	DET
ap-1538	94	2	impact	impact	NOUN
ap-1538	94	3	of	of	ADP
ap-1538	94	4	nox	nox	NOUN
ap-1538	94	5	outliers	outlier	NOUN
ap-1538	94	6	is	be	AUX
ap-1538	94	7	apparent	apparent	ADJ
ap-1538	94	8	if	if	SCONJ
ap-1538	94	9	we	we	PRON
ap-1538	94	10	compare	compare	VERB
ap-1538	94	11	the	the	DET
ap-1538	94	12	prediction	prediction	NOUN
ap-1538	94	13	details	detail	NOUN
ap-1538	94	14	in	in	ADP
ap-1538	94	15	figure	figure	NOUN
ap-1538	94	16	3	3	NUM
ap-1538	94	17	and	and	CCONJ
ap-1538	94	18	figure	figure	VERB
ap-1538	94	19	4	4	NUM
ap-1538	94	20	,	,	PUNCT
ap-1538	94	21	and	and	CCONJ
ap-1538	94	22	it	it	PRON
ap-1538	94	23	is	be	AUX
ap-1538	94	24	clear	clear	ADJ
ap-1538	94	25	that	that	SCONJ
ap-1538	94	26	another	another	DET
ap-1538	94	27	signal	signal	ADJ
ap-1538	94	28	processing	processing	NOUN
ap-1538	94	29	technique	technique	NOUN
ap-1538	94	30	for	for	ADP
ap-1538	94	31	selecting	select	VERB
ap-1538	94	32	the	the	DET
ap-1538	94	33	retraining	retrain	VERB
ap-1538	94	34	data	datum	NOUN
ap-1538	94	35	needs	need	VERB
ap-1538	94	36	to	to	PART
ap-1538	94	37	be	be	AUX
ap-1538	94	38	involved	involve	VERB
ap-1538	94	39	in	in	ADP
ap-1538	94	40	order	order	NOUN
ap-1538	94	41	to	to	PART
ap-1538	94	42	avoid	avoid	VERB
ap-1538	94	43	nox	nox	NOUN
ap-1538	94	44	outliers	outlier	NOUN
ap-1538	94	45	in	in	ADP
ap-1538	94	46	the	the	DET
ap-1538	94	47	retraining	retrain	VERB
ap-1538	94	48	data	datum	NOUN
ap-1538	94	49	;	;	PUNCT
ap-1538	94	50	the	the	DET
ap-1538	94	51	neural	neural	ADJ
ap-1538	94	52	network	network	NOUN
ap-1538	94	53	fails	fail	VERB
ap-1538	94	54	in	in	ADP
ap-1538	94	55	prediction	prediction	NOUN
ap-1538	94	56	after	after	ADP
ap-1538	94	57	k	k	PROPN
ap-1538	94	58	=	=	PUNCT
ap-1538	94	59	3.122e+	3.122e+	NUM
ap-1538	94	60	4	4	NUM
ap-1538	94	61	because	because	SCONJ
ap-1538	94	62	of	of	ADP
ap-1538	94	63	the	the	DET
ap-1538	94	64	poor	poor	ADJ
ap-1538	94	65	retraining	retraining	ADJ
ap-1538	94	66	data	datum	NOUN
ap-1538	94	67	and	and	CCONJ
ap-1538	94	68	also	also	ADV
ap-1538	94	69	because	because	SCONJ
ap-1538	94	70	of	of	ADP
ap-1538	94	71	the	the	DET
ap-1538	94	72	outliers	outlier	NOUN
ap-1538	94	73	at	at	ADP
ap-1538	94	74	k	k	PROPN
ap-1538	94	75	=	=	SYM
ap-1538	94	76	3.12e	3.12e	NUM
ap-1538	94	77	+	+	CCONJ
ap-1538	94	78	4	4	X
ap-1538	94	79	.	.	PUNCT
ap-1538	95	1	the	the	DET
ap-1538	95	2	prediction	prediction	NOUN
ap-1538	95	3	becomes	become	VERB
ap-1538	95	4	correct	correct	ADJ
ap-1538	95	5	again	again	ADV
ap-1538	95	6	for	for	ADP
ap-1538	95	7	k	k	PROPN
ap-1538	95	8	>	>	X
ap-1538	95	9	3.133e	3.133e	NUM
ap-1538	95	10	+	+	CCONJ
ap-1538	95	11	10	10	NUM
ap-1538	95	12	,	,	PUNCT
ap-1538	95	13	because	because	SCONJ
ap-1538	95	14	the	the	DET
ap-1538	95	15	related	relate	VERB
ap-1538	95	16	retraining	retraining	ADJ
ap-1538	95	17	data	datum	NOUN
ap-1538	95	18	already	already	ADV
ap-1538	95	19	does	do	AUX
ap-1538	95	20	not	not	PART
ap-1538	95	21	include	include	VERB
ap-1538	95	22	the	the	DET
ap-1538	95	23	outliers	outlier	NOUN
ap-1538	95	24	.	.	PUNCT
ap-1538	96	1	5	5	NUM
ap-1538	96	2	conclusions	conclusion	NOUN
ap-1538	96	3	we	we	PRON
ap-1538	96	4	designed	design	VERB
ap-1538	96	5	and	and	CCONJ
ap-1538	96	6	tested	test	VERB
ap-1538	96	7	a	a	DET
ap-1538	96	8	non	non	ADJ
ap-1538	96	9	-	-	ADJ
ap-1538	96	10	conventional	conventional	ADJ
ap-1538	96	11	recurrent	recurrent	ADJ
ap-1538	96	12	neural	neural	ADJ
ap-1538	96	13	network	network	NOUN
ap-1538	96	14	for	for	ADP
ap-1538	96	15	predicting	predict	VERB
ap-1538	96	16	the	the	DET
ap-1538	96	17	nox	nox	NOUN
ap-1538	96	18	emissions	emission	NOUN
ap-1538	96	19	of	of	ADP
ap-1538	96	20	a	a	DET
ap-1538	96	21	pulverized	pulverize	VERB
ap-1538	96	22	firing	firing	NOUN
ap-1538	96	23	boiler	boiler	NOUN
ap-1538	96	24	without	without	ADP
ap-1538	96	25	using	use	VERB
ap-1538	96	26	o2	o2	PROPN
ap-1538	96	27	,	,	PUNCT
ap-1538	96	28	nox	nox	NOUN
ap-1538	96	29	,	,	PUNCT
ap-1538	96	30	or	or	CCONJ
ap-1538	96	31	co	co	VERB
ap-1538	96	32	on	on	ADP
ap-1538	96	33	the	the	DET
ap-1538	96	34	model	model	NOUN
ap-1538	96	35	input	input	NOUN
ap-1538	96	36	.	.	PUNCT
ap-1538	97	1	the	the	DET
ap-1538	97	2	proposed	propose	VERB
ap-1538	97	3	method	method	NOUN
ap-1538	97	4	handles	handles	AUX
ap-1538	97	5	process	process	VERB
ap-1538	97	6	non	non	ADJ
ap-1538	97	7	-	-	NOUN
ap-1538	97	8	stationarity	stationarity	NOUN
ap-1538	97	9	by	by	ADP
ap-1538	97	10	frequent	frequent	ADJ
ap-1538	97	11	retraining	retraining	NOUN
ap-1538	97	12	,	,	PUNCT
ap-1538	97	13	and	and	CCONJ
ap-1538	97	14	it	it	PRON
ap-1538	97	15	handles	handle	VERB
ap-1538	97	16	the	the	DET
ap-1538	97	17	outages	outage	NOUN
ap-1538	97	18	of	of	ADP
ap-1538	97	19	input	input	NOUN
ap-1538	97	20	process	process	NOUN
ap-1538	97	21	variables	variable	NOUN
ap-1538	97	22	by	by	ADP
ap-1538	97	23	input	input	NOUN
ap-1538	97	24	data	datum	NOUN
ap-1538	97	25	preprocessing	preprocessing	NOUN
ap-1538	97	26	(	(	PUNCT
ap-1538	97	27	but	but	CCONJ
ap-1538	97	28	not	not	PART
ap-1538	97	29	yet	yet	ADV
ap-1538	97	30	the	the	DET
ap-1538	97	31	outages	outage	NOUN
ap-1538	97	32	of	of	ADP
ap-1538	97	33	the	the	DET
ap-1538	97	34	predicted	predict	VERB
ap-1538	97	35	nox	nox	NOUN
ap-1538	97	36	itself	itself	PRON
ap-1538	97	37	)	)	PUNCT
ap-1538	97	38	;	;	PUNCT
ap-1538	97	39	it	it	PRON
ap-1538	97	40	is	be	AUX
ap-1538	97	41	assumed	assume	VERB
ap-1538	97	42	that	that	SCONJ
ap-1538	97	43	this	this	PRON
ap-1538	97	44	can	can	AUX
ap-1538	97	45	be	be	AUX
ap-1538	97	46	resolved	resolve	VERB
ap-1538	97	47	by	by	ADP
ap-1538	97	48	automatically	automatically	ADV
ap-1538	97	49	supervised	supervise	VERB
ap-1538	97	50	selection	selection	NOUN
ap-1538	97	51	of	of	ADP
ap-1538	97	52	the	the	DET
ap-1538	97	53	training	training	NOUN
ap-1538	97	54	data	datum	NOUN
ap-1538	97	55	where	where	SCONJ
ap-1538	97	56	nox	nox	NOUN
ap-1538	97	57	outliers	outlier	NOUN
ap-1538	97	58	do	do	AUX
ap-1538	97	59	not	not	PART
ap-1538	97	60	appear	appear	VERB
ap-1538	97	61	,	,	PUNCT
ap-1538	97	62	and	and	CCONJ
ap-1538	97	63	by	by	ADP
ap-1538	97	64	avoiding	avoid	VERB
ap-1538	97	65	unnecessary	unnecessary	ADJ
ap-1538	97	66	retraining	retraining	NOUN
ap-1538	97	67	.	.	PUNCT
ap-1538	98	1	acknowledgement	acknowledgement	NOUN
ap-1538	98	2	this	this	DET
ap-1538	98	3	work	work	NOUN
ap-1538	98	4	has	have	AUX
ap-1538	98	5	been	be	AUX
ap-1538	98	6	supported	support	VERB
ap-1538	98	7	by	by	ADP
ap-1538	98	8	grant	grant	PROPN
ap-1538	98	9	mpo	mpo	PROPN
ap-1538	98	10	fr	fr	PROPN
ap-1538	98	11	-	-	PUNCT
ap-1538	98	12	ti1/538	ti1/538	NOUN
ap-1538	98	13	,	,	PUNCT
ap-1538	98	14	and	and	CCONJ
ap-1538	98	15	in	in	ADP
ap-1538	98	16	part	part	NOUN
ap-1538	98	17	by	by	ADP
ap-1538	98	18	grant	grant	PROPN
ap-1538	98	19	sgs10/252	sgs10/252	PROPN
ap-1538	98	20	/	/	SYM
ap-1538	98	21	ohk2/3t/12	ohk2/3t/12	PROPN
ap-1538	98	22	.	.	PUNCT
ap-1538	99	1	references	reference	NOUN
ap-1538	99	2	[	[	X
ap-1538	99	3	1	1	NUM
ap-1538	99	4	]	]	X
ap-1538	99	5	gupta	gupta	PROPN
ap-1538	99	6	,	,	PUNCT
ap-1538	99	7	m.	m.	NOUN
ap-1538	99	8	m.	m.	NOUN
ap-1538	99	9	,	,	PUNCT
ap-1538	99	10	liang	liang	PROPN
ap-1538	99	11	,	,	PUNCT
ap-1538	99	12	j.	j.	PROPN
ap-1538	99	13	,	,	PUNCT
ap-1538	99	14	homma	homma	PROPN
ap-1538	99	15	,	,	PUNCT
ap-1538	99	16	n.	n.	NOUN
ap-1538	99	17	:	:	PUNCT
ap-1538	99	18	static	static	ADJ
ap-1538	99	19	and	and	CCONJ
ap-1538	99	20	dynamic	dynamic	ADJ
ap-1538	99	21	neural	neural	ADJ
ap-1538	99	22	networks	network	NOUN
ap-1538	99	23	:	:	PUNCT
ap-1538	99	24	from	from	ADP
ap-1538	99	25	fundamentals	fundamental	NOUN
ap-1538	99	26	to	to	ADP
ap-1538	99	27	advanced	advanced	ADJ
ap-1538	99	28	theory	theory	NOUN
ap-1538	99	29	.	.	PUNCT
ap-1538	100	1	ieee	ieee	PROPN
ap-1538	100	2	press	press	PROPN
ap-1538	100	3	and	and	CCONJ
ap-1538	100	4	wiley	wiley	NOUN
ap-1538	100	5	-	-	PUNCT
ap-1538	100	6	interscience	interscience	PROPN
ap-1538	100	7	,	,	PUNCT
ap-1538	100	8	john	john	PROPN
ap-1538	100	9	wiley	wiley	PROPN
ap-1538	100	10	&	&	CCONJ
ap-1538	100	11	sons	sons	PROPN
ap-1538	100	12	,	,	PUNCT
ap-1538	100	13	inc	inc	PROPN
ap-1538	100	14	.	.	PROPN
ap-1538	100	15	,	,	PUNCT
ap-1538	100	16	2003	2003	NUM
ap-1538	100	17	.	.	PUNCT
ap-1538	101	1	[	[	X
ap-1538	101	2	2	2	NUM
ap-1538	101	3	]	]	X
ap-1538	101	4	kalogirou	kalogirou	PROPN
ap-1538	101	5	,	,	PUNCT
ap-1538	101	6	s.	s.	PROPN
ap-1538	101	7	a.	a.	PROPN
ap-1538	101	8	:	:	PUNCT
ap-1538	101	9	artificial	artificial	ADJ
ap-1538	101	10	intelligence	intelligence	NOUN
ap-1538	101	11	for	for	ADP
ap-1538	101	12	the	the	DET
ap-1538	101	13	modeling	modeling	NOUN
ap-1538	101	14	and	and	CCONJ
ap-1538	101	15	control	control	NOUN
ap-1538	101	16	of	of	ADP
ap-1538	101	17	combustion	combustion	NOUN
ap-1538	101	18	processes	process	NOUN
ap-1538	101	19	:	:	PUNCT
ap-1538	101	20	a	a	DET
ap-1538	101	21	review	review	NOUN
ap-1538	101	22	,	,	PUNCT
ap-1538	101	23	progress	progress	NOUN
ap-1538	101	24	in	in	ADP
ap-1538	101	25	energy	energy	NOUN
ap-1538	101	26	and	and	CCONJ
ap-1538	101	27	combustion	combustion	NOUN
ap-1538	101	28	science	science	NOUN
ap-1538	101	29	,	,	PUNCT
ap-1538	101	30	29	29	NUM
ap-1538	101	31	,	,	PUNCT
ap-1538	101	32	2003	2003	NUM
ap-1538	101	33	,	,	PUNCT
ap-1538	101	34	p.	p.	NOUN
ap-1538	101	35	515–566	515–566	NUM
ap-1538	101	36	,	,	PUNCT
ap-1538	101	37	elsevier	elsevier	NOUN
ap-1538	101	38	.	.	PUNCT
ap-1538	102	1	issn	issn	PROPN
ap-1538	102	2	0360	0360	NUM
ap-1538	102	3	-	-	SYM
ap-1538	102	4	1285	1285	NUM
ap-1538	102	5	.	.	PUNCT
ap-1538	103	1	[	[	X
ap-1538	103	2	3	3	NUM
ap-1538	103	3	]	]	X
ap-1538	103	4	mellit	mellit	NOUN
ap-1538	103	5	,	,	PUNCT
ap-1538	103	6	a.	a.	NOUN
ap-1538	103	7	,	,	PUNCT
ap-1538	103	8	kalogirou	kalogirou	PROPN
ap-1538	103	9	,	,	PUNCT
ap-1538	103	10	s.	s.	PROPN
ap-1538	103	11	a.	a.	PROPN
ap-1538	103	12	:	:	PUNCT
ap-1538	103	13	artificial	artificial	ADJ
ap-1538	103	14	intelligence	intelligence	NOUN
ap-1538	103	15	techniques	technique	NOUN
ap-1538	103	16	for	for	ADP
ap-1538	103	17	photovoltaic	photovoltaic	NOUN
ap-1538	103	18	applications	application	NOUN
ap-1538	103	19	:	:	PUNCT
ap-1538	103	20	a	a	DET
ap-1538	103	21	review	review	NOUN
ap-1538	103	22	,	,	PUNCT
ap-1538	103	23	progress	progress	NOUN
ap-1538	103	24	in	in	ADP
ap-1538	103	25	energy	energy	NOUN
ap-1538	103	26	and	and	CCONJ
ap-1538	103	27	combustion	combustion	NOUN
ap-1538	103	28	science	science	NOUN
ap-1538	103	29	,	,	PUNCT
ap-1538	103	30	34	34	NUM
ap-1538	103	31	,	,	PUNCT
ap-1538	103	32	2008	2008	NUM
ap-1538	103	33	,	,	PUNCT
ap-1538	104	1	p.	p.	NOUN
ap-1538	104	2	574–632	574–632	NUM
ap-1538	104	3	,	,	PUNCT
ap-1538	104	4	elsevier	elsevier	NOUN
ap-1538	104	5	.	.	PUNCT
ap-1538	105	1	issn	issn	PROPN
ap-1538	105	2	0360	0360	NUM
ap-1538	105	3	-	-	SYM
ap-1538	105	4	1285	1285	NUM
ap-1538	105	5	.	.	PUNCT
ap-1538	106	1	[	[	X
ap-1538	106	2	4	4	NUM
ap-1538	106	3	]	]	X
ap-1538	106	4	bukovsky	bukovsky	NOUN
ap-1538	106	5	,	,	PUNCT
ap-1538	106	6	i.	i.	PROPN
ap-1538	106	7	,	,	PUNCT
ap-1538	106	8	bila	bila	PROPN
ap-1538	106	9	,	,	PUNCT
ap-1538	106	10	j.	j.	PROPN
ap-1538	106	11	,	,	PUNCT
ap-1538	106	12	gupta	gupta	PROPN
ap-1538	106	13	,	,	PUNCT
ap-1538	106	14	m.	m.	NOUN
ap-1538	106	15	m.	m.	NOUN
ap-1538	106	16	,	,	PUNCT
ap-1538	106	17	hou	hou	PROPN
ap-1538	106	18	,	,	PUNCT
ap-1538	106	19	z.-g	z.-g	PROPN
ap-1538	106	20	.	.	PROPN
ap-1538	106	21	,	,	PUNCT
ap-1538	106	22	homma	homma	PROPN
ap-1538	106	23	,	,	PUNCT
ap-1538	106	24	n.	n.	NOUN
ap-1538	106	25	:	:	PUNCT
ap-1538	106	26	foundation	foundation	NOUN
ap-1538	106	27	and	and	CCONJ
ap-1538	106	28	classification	classification	NOUN
ap-1538	106	29	of	of	ADP
ap-1538	106	30	nonconventional	nonconventional	ADJ
ap-1538	106	31	neural	neural	ADJ
ap-1538	106	32	units	unit	NOUN
ap-1538	106	33	and	and	CCONJ
ap-1538	106	34	paradigm	paradigm	NOUN
ap-1538	106	35	of	of	ADP
ap-1538	106	36	nonsynaptic	nonsynaptic	ADJ
ap-1538	106	37	neural	neural	ADJ
ap-1538	106	38	interaction	interaction	NOUN
ap-1538	106	39	,	,	PUNCT
ap-1538	106	40	in	in	ADP
ap-1538	106	41	discoveries	discovery	NOUN
ap-1538	106	42	and	and	CCONJ
ap-1538	106	43	breakthroughs	breakthrough	NOUN
ap-1538	106	44	in	in	ADP
ap-1538	106	45	cognitive	cognitive	ADJ
ap-1538	106	46	informatics	informatic	NOUN
ap-1538	106	47	and	and	CCONJ
ap-1538	106	48	natural	natural	ADJ
ap-1538	106	49	intelligence	intelligence	NOUN
ap-1538	106	50	.	.	PUNCT
ap-1538	107	1	in	in	ADP
ap-1538	107	2	the	the	DET
ap-1538	107	3	acini	acini	NOUN
ap-1538	107	4	book	book	NOUN
ap-1538	107	5	series	series	PROPN
ap-1538	107	6	ed	ed	PROPN
ap-1538	107	7	.	.	PUNCT
ap-1538	108	1	by	by	ADP
ap-1538	108	2	yingxu	yingxu	PROPN
ap-1538	108	3	wang	wang	PROPN
ap-1538	108	4	,	,	PUNCT
ap-1538	108	5	university	university	PROPN
ap-1538	108	6	of	of	ADP
ap-1538	108	7	calgary	calgary	PROPN
ap-1538	108	8	,	,	PUNCT
ap-1538	108	9	canada	canada	PROPN
ap-1538	108	10	:	:	PUNCT
ap-1538	108	11	igi	igi	PROPN
ap-1538	108	12	publishing	publishing	PROPN
ap-1538	108	13	,	,	PUNCT
ap-1538	108	14	hershey	hershey	PROPN
ap-1538	108	15	pa	pa	PROPN
ap-1538	108	16	,	,	PUNCT
ap-1538	108	17	usa	usa	PROPN
ap-1538	108	18	,	,	PUNCT
ap-1538	108	19	2009	2009	NUM
ap-1538	108	20	.	.	PUNCT
ap-1538	109	1	isbn	isbn	ADJ
ap-1538	109	2	978	978	NUM
ap-1538	109	3	-	-	SYM
ap-1538	109	4	1	1	NUM
ap-1538	109	5	-	-	PUNCT
ap-1538	109	6	60566	60566	NUM
ap-1538	109	7	-	-	PUNCT
ap-1538	109	8	902	902	NUM
ap-1538	109	9	-	-	PUNCT
ap-1538	109	10	1	1	NUM
ap-1538	109	11	.	.	PUNCT
ap-1538	110	1	[	[	X
ap-1538	110	2	5	5	NUM
ap-1538	110	3	]	]	X
ap-1538	110	4	pitel	pitel	ADJ
ap-1538	110	5	’	'	PUNCT
ap-1538	110	6	,	,	PUNCT
ap-1538	110	7	j.	j.	PROPN
ap-1538	110	8	,	,	PUNCT
ap-1538	110	9	mižák	mižák	PROPN
ap-1538	110	10	,	,	PUNCT
ap-1538	110	11	j.	j.	PROPN
ap-1538	110	12	:	:	PUNCT
ap-1538	110	13	approximation	approximation	NOUN
ap-1538	110	14	of	of	ADP
ap-1538	110	15	co	co	ADJ
ap-1538	110	16	/	/	SYM
ap-1538	110	17	lambda	lambda	ADJ
ap-1538	110	18	biomass	biomass	NOUN
ap-1538	110	19	combustion	combustion	NOUN
ap-1538	110	20	dependence	dependence	NOUN
ap-1538	110	21	by	by	ADP
ap-1538	110	22	artificial	artificial	ADJ
ap-1538	110	23	intelligence	intelligence	NOUN
ap-1538	110	24	techniques	technique	NOUN
ap-1538	110	25	.	.	PUNCT
ap-1538	111	1	in	in	ADP
ap-1538	111	2	annals	annal	NOUN
ap-1538	111	3	of	of	ADP
ap-1538	111	4	daaam	daaam	NOUN
ap-1538	111	5	for	for	ADP
ap-1538	111	6	2011	2011	NUM
ap-1538	111	7	&	&	CCONJ
ap-1538	111	8	proceedings	proceeding	NOUN
ap-1538	111	9	of	of	ADP
ap-1538	111	10	the	the	DET
ap-1538	111	11	22nd	22nd	ADJ
ap-1538	111	12	international	international	PROPN
ap-1538	111	13	daaam	daaam	PROPN
ap-1538	111	14	symposium	symposium	PROPN
ap-1538	111	15	,	,	PUNCT
ap-1538	111	16	vienna	vienna	PROPN
ap-1538	111	17	,	,	PUNCT
ap-1538	111	18	austria	austria	PROPN
ap-1538	111	19	,	,	PUNCT
ap-1538	111	20	23–26th	23–26th	NUM
ap-1538	111	21	november	november	PROPN
ap-1538	111	22	2011	2011	NUM
ap-1538	111	23	.	.	PUNCT
ap-1538	112	1	vienna	vienna	NOUN
ap-1538	112	2	:	:	PUNCT
ap-1538	112	3	daaam	daaam	PROPN
ap-1538	112	4	international	international	PROPN
ap-1538	112	5	,	,	PUNCT
ap-1538	112	6	2011	2011	NUM
ap-1538	112	7	,	,	PUNCT
ap-1538	113	1	p.	p.	NOUN
ap-1538	113	2	0143–0144	0143–0144	NUM
ap-1538	113	3	.	.	PUNCT
ap-1538	114	1	isbn	isbn	PROPN
ap-1538	114	2	978	978	NUM
ap-1538	114	3	-	-	SYM
ap-1538	114	4	3	3	NUM
ap-1538	114	5	-	-	PUNCT
ap-1538	114	6	901509	901509	NUM
ap-1538	114	7	-	-	PUNCT
ap-1538	114	8	83	83	NUM
ap-1538	114	9	-	-	SYM
ap-1538	114	10	4	4	NUM
ap-1538	114	11	,	,	PUNCT
ap-1538	114	12	issn	issn	NOUN
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ap-1538	114	14	-	-	SYM
ap-1538	114	15	9679	9679	NUM
ap-1538	114	16	.	.	PUNCT
ap-1538	115	1	[	[	X
ap-1538	115	2	6	6	NUM
ap-1538	115	3	]	]	SYM
ap-1538	115	4	mižák	mižák	NOUN
ap-1538	115	5	,	,	PUNCT
ap-1538	115	6	j.	j.	PROPN
ap-1538	115	7	,	,	PUNCT
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ap-1538	115	9	’	'	PUNCT
ap-1538	115	10	,	,	PUNCT
ap-1538	115	11	j.	j.	PROPN
ap-1538	115	12	:	:	PUNCT
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ap-1538	115	14	artificial	artificial	ADJ
ap-1538	115	15	neural	neural	ADJ
ap-1538	115	16	networks	network	NOUN
ap-1538	115	17	for	for	ADP
ap-1538	115	18	biomass	biomass	NOUN
ap-1538	115	19	combustion	combustion	NOUN
ap-1538	115	20	process	process	NOUN
ap-1538	115	21	control	control	NOUN
ap-1538	115	22	.	.	PUNCT
ap-1538	116	1	in	in	ADP
ap-1538	116	2	proceedings	proceeding	NOUN
ap-1538	116	3	of	of	ADP
ap-1538	116	4	2nd	2nd	ADJ
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ap-1538	116	6	seminar	seminar	NOUN
ap-1538	116	7	“	"	PUNCT
ap-1538	116	8	system	system	NOUN
ap-1538	116	9	analysis	analysis	NOUN
ap-1538	116	10	,	,	PUNCT
ap-1538	116	11	control	control	NOUN
ap-1538	116	12	and	and	CCONJ
ap-1538	116	13	information	information	NOUN
ap-1538	116	14	processing	processing	NOUN
ap-1538	116	15	”	"	PUNCT
ap-1538	116	16	,	,	PUNCT
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ap-1538	116	18	,	,	PUNCT
ap-1538	116	19	russia	russia	PROPN
ap-1538	116	20	.	.	PUNCT
ap-1538	117	1	[	[	X
ap-1538	117	2	cd	cd	PROPN
ap-1538	117	3	-	-	PUNCT
ap-1538	117	4	rom	rom	NOUN
ap-1538	117	5	]	]	PUNCT
ap-1538	117	6	.	.	PUNCT
ap-1538	118	1	rostov	rostov	PROPN
ap-1538	118	2	on	on	ADP
ap-1538	118	3	don	don	PROPN
ap-1538	118	4	:	:	PUNCT
ap-1538	118	5	don	don	PROPN
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ap-1538	118	7	technical	technical	PROPN
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ap-1538	118	9	,	,	PUNCT
ap-1538	118	10	2011	2011	NUM
ap-1538	118	11	,	,	PUNCT
ap-1538	118	12	p.	p.	NOUN
ap-1538	118	13	343–348	343–348	NUM
ap-1538	118	14	.	.	PUNCT
ap-1538	119	1	isbn	isbn	ADJ
ap-1538	119	2	978	978	NUM
ap-1538	119	3	-	-	SYM
ap-1538	119	4	5	5	NUM
ap-1538	119	5	-	-	PUNCT
ap-1538	119	6	7890	7890	NUM
ap-1538	119	7	-	-	PUNCT
ap-1538	119	8	0666	0666	NUM
ap-1538	119	9	-	-	SYM
ap-1538	119	10	5	5	NUM
ap-1538	119	11	.	.	PUNCT
ap-1538	120	1	[	[	X
ap-1538	120	2	7	7	X
ap-1538	120	3	]	]	X
ap-1538	120	4	pitel	pitel	ADJ
ap-1538	120	5	’	'	PUNCT
ap-1538	120	6	,	,	PUNCT
ap-1538	120	7	j.	j.	PROPN
ap-1538	120	8	,	,	PUNCT
ap-1538	120	9	borž́ıková	borž́ıková	PROPN
ap-1538	120	10	,	,	PUNCT
ap-1538	120	11	j.	j.	PROPN
ap-1538	120	12	,	,	PUNCT
ap-1538	120	13	mižák	mižák	PROPN
ap-1538	120	14	,	,	PUNCT
ap-1538	120	15	j.	j.	PROPN
ap-1538	120	16	:	:	PUNCT
ap-1538	120	17	biomass	biomass	NOUN
ap-1538	120	18	combustion	combustion	NOUN
ap-1538	120	19	process	process	NOUN
ap-1538	120	20	control	control	NOUN
ap-1538	120	21	using	use	VERB
ap-1538	120	22	artificial	artificial	ADJ
ap-1538	120	23	intelligence	intelligence	NOUN
ap-1538	120	24	techniques	technique	NOUN
ap-1538	120	25	.	.	PUNCT
ap-1538	121	1	in	in	ADP
ap-1538	121	2	proceedings	proceeding	NOUN
ap-1538	121	3	of	of	ADP
ap-1538	121	4	xxxvth	xxxvth	PROPN
ap-1538	121	5	seminar	seminar	NOUN
ap-1538	121	6	asr’2010	asr’2010	NOUN
ap-1538	121	7	“	"	PUNCT
ap-1538	121	8	instruments	instrument	NOUN
ap-1538	121	9	and	and	CCONJ
ap-1538	121	10	control	control	NOUN
ap-1538	121	11	”	"	PUNCT
ap-1538	121	12	.	.	PUNCT
ap-1538	122	1	ostrava	ostrava	PROPN
ap-1538	122	2	:	:	PUNCT
ap-1538	122	3	všb	všb	VERB
ap-1538	122	4	-	-	PUNCT
ap-1538	122	5	tu	tu	PROPN
ap-1538	122	6	ostrava	ostrava	PROPN
ap-1538	122	7	,	,	PUNCT
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ap-1538	122	9	,	,	PUNCT
ap-1538	122	10	p.	p.	NOUN
ap-1538	123	1	317–321	317–321	NUM
ap-1538	123	2	.	.	PUNCT
ap-1538	124	1	isbn	isbn	ADJ
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ap-1538	124	3	-	-	SYM
ap-1538	124	4	80	80	NUM
ap-1538	124	5	-	-	PUNCT
ap-1538	124	6	248	248	NUM
ap-1538	124	7	-	-	PUNCT
ap-1538	124	8	2191	2191	NUM
ap-1538	124	9	-	-	SYM
ap-1538	124	10	7	7	NUM
ap-1538	124	11	.	.	PUNCT
ap-1538	125	1	[	[	X
ap-1538	125	2	8	8	NUM
ap-1538	125	3	]	]	PUNCT
ap-1538	125	4	hošovský	hošovský	NOUN
ap-1538	125	5	,	,	PUNCT
ap-1538	125	6	a.	a.	NOUN
ap-1538	125	7	:	:	PUNCT
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ap-1538	125	10	of	of	ADP
ap-1538	125	11	neural	neural	ADJ
ap-1538	125	12	networks	network	NOUN
ap-1538	125	13	structure	structure	NOUN
ap-1538	125	14	for	for	ADP
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ap-1538	125	16	of	of	ADP
ap-1538	125	17	biomass	biomass	NOUN
ap-1538	125	18	-	-	PUNCT
ap-1538	125	19	fired	fire	VERB
ap-1538	125	20	boiler	boiler	NOUN
ap-1538	125	21	emissions	emission	NOUN
ap-1538	125	22	.	.	PUNCT
ap-1538	126	1	journal	journal	NOUN
ap-1538	126	2	of	of	ADP
ap-1538	126	3	applied	apply	VERB
ap-1538	126	4	science	science	NOUN
ap-1538	126	5	in	in	ADP
ap-1538	126	6	thermodynamics	thermodynamic	NOUN
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ap-1538	126	8	fluid	fluid	ADJ
ap-1538	126	9	mechanics	mechanic	NOUN
ap-1538	126	10	,	,	PUNCT
ap-1538	126	11	vol	vol	NOUN
ap-1538	126	12	.	.	NOUN
ap-1538	126	13	9	9	NUM
ap-1538	126	14	,	,	PUNCT
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ap-1538	126	16	.	.	NOUN
ap-1538	126	17	2	2	NUM
ap-1538	126	18	,	,	PUNCT
ap-1538	126	19	2011	2011	NUM
ap-1538	126	20	,	,	PUNCT
ap-1538	126	21	p.	p.	NOUN
ap-1538	126	22	1–6	1–6	NUM
ap-1538	126	23	.	.	PUNCT
ap-1538	127	1	issn	issn	PROPN
ap-1538	127	2	1802	1802	NUM
ap-1538	127	3	-	-	SYM
ap-1538	127	4	9388	9388	NUM
ap-1538	127	5	.	.	PUNCT
ap-1538	128	1	[	[	X
ap-1538	128	2	9	9	NUM
ap-1538	128	3	]	]	SYM
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ap-1538	128	5	,	,	PUNCT
ap-1538	128	6	i.	i.	NOUN
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ap-1538	128	8	lepold	lepold	ADJ
ap-1538	128	9	,	,	PUNCT
ap-1538	128	10	m.	m.	NOUN
ap-1538	128	11	,	,	PUNCT
ap-1538	128	12	bı́lá	bı́lá	PROPN
ap-1538	128	13	,	,	PUNCT
ap-1538	128	14	j.	j.	PROPN
ap-1538	128	15	:	:	PUNCT
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ap-1538	128	17	neural	neural	ADJ
ap-1538	128	18	unit	unit	NOUN
ap-1538	128	19	and	and	CCONJ
ap-1538	128	20	its	its	PRON
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ap-1538	128	22	in	in	ADP
ap-1538	128	23	validation	validation	NOUN
ap-1538	128	24	of	of	ADP
ap-1538	128	25	process	process	NOUN
ap-1538	128	26	data	datum	NOUN
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ap-1538	128	28	steam	steam	NOUN
ap-1538	128	29	turbine	turbine	NOUN
ap-1538	128	30	loop	loop	NOUN
ap-1538	128	31	and	and	CCONJ
ap-1538	128	32	energetic	energetic	ADJ
ap-1538	128	33	boiler	boiler	NOUN
ap-1538	128	34	,	,	PUNCT
ap-1538	128	35	wcci	wcci	NOUN
ap-1538	128	36	2010	2010	NUM
ap-1538	128	37	,	,	PUNCT
ap-1538	128	38	ieee	ieee	NOUN
ap-1538	128	39	int	int	NOUN
ap-1538	128	40	.	.	PUNCT
ap-1538	129	1	joint	joint	ADJ
ap-1538	129	2	.	.	PUNCT
ap-1538	129	3	conf	conf	PROPN
ap-1538	129	4	.	.	PUNCT
ap-1538	130	1	on	on	ADP
ap-1538	130	2	neural	neural	ADJ
ap-1538	130	3	networks	network	NOUN
ap-1538	130	4	ijcnn	ijcnn	VERB
ap-1538	130	5	,	,	PUNCT
ap-1538	130	6	barcelona	barcelona	PROPN
ap-1538	130	7	,	,	PUNCT
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ap-1538	130	9	,	,	PUNCT
ap-1538	130	10	2010	2010	NUM
ap-1538	130	11	.	.	PUNCT
ap-1538	131	1	21	21	NUM
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ap-1538	131	4	vol	vol	NOUN
ap-1538	131	5	.	.	PROPN
ap-1538	132	1	52	52	NUM
ap-1538	132	2	no	no	NOUN
ap-1538	132	3	.	.	PUNCT
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ap-1538	134	1	[	[	X
ap-1538	134	2	10	10	NUM
ap-1538	134	3	]	]	SYM
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ap-1538	134	5	,	,	PUNCT
ap-1538	134	6	i.	i.	PROPN
ap-1538	134	7	,	,	PUNCT
ap-1538	134	8	bı́lá	bı́lá	PROPN
ap-1538	134	9	,	,	PUNCT
ap-1538	134	10	j.	j.	PROPN
ap-1538	134	11	,	,	PUNCT
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ap-1538	134	13	,	,	PUNCT
ap-1538	134	14	h.	h.	PROPN
ap-1538	134	15	,	,	PUNCT
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ap-1538	134	17	,	,	PUNCT
ap-1538	134	18	r.	r.	PROPN
ap-1538	134	19	:	:	PUNCT
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ap-1538	134	24	for	for	ADP
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ap-1538	134	26	control	control	NOUN
ap-1538	134	27	,	,	PUNCT
ap-1538	134	28	automatizácia	automatizácia	PROPN
ap-1538	134	29	a	a	DET
ap-1538	134	30	riadenie	riadenie	NOUN
ap-1538	134	31	v	v	ADP
ap-1538	134	32	teórii	teórii	PROPN
ap-1538	134	33	a	a	DET
ap-1538	134	34	praxi	praxi	ADJ
ap-1538	134	35	artep	artep	NOUN
ap-1538	134	36	2012	2012	NUM
ap-1538	134	37	,	,	PUNCT
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ap-1538	134	39	2012	2012	NUM
ap-1538	134	40	.	.	PUNCT
ap-1538	135	1	isbn	isbn	ADJ
ap-1538	135	2	978	978	NUM
ap-1538	135	3	-	-	SYM
ap-1538	135	4	80	80	NUM
ap-1538	135	5	-	-	PUNCT
ap-1538	135	6	553	553	NUM
ap-1538	135	7	-	-	PUNCT
ap-1538	135	8	0835	0835	NUM
ap-1538	135	9	-	-	SYM
ap-1538	135	10	7	7	NUM
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ap-1538	136	1	[	[	X
ap-1538	136	2	11	11	NUM
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ap-1538	136	5	,	,	PUNCT
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ap-1538	136	8	:	:	PUNCT
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ap-1538	136	11	of	of	ADP
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ap-1538	136	13	systems	system	NOUN
ap-1538	136	14	,	,	PUNCT
ap-1538	136	15	ieee	ieee	NOUN
ap-1538	136	16	tran	tran	NOUN
ap-1538	136	17	.	.	PUNCT
ap-1538	137	1	on	on	ADP
ap-1538	137	2	systems	system	NOUN
ap-1538	137	3	.	.	PUNCT
ap-1538	138	1	man	man	NOUN
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ap-1538	138	4	.	.	PUNCT
ap-1538	139	1	vol	vol	NOUN
ap-1538	139	2	.	.	PUNCT
ap-1538	139	3	smc-1	smc-1	NOUN
ap-1538	139	4	,	,	PUNCT
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ap-1538	139	6	,	,	PUNCT
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ap-1538	139	8	,	,	PUNCT
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ap-1538	139	11	.	.	PUNCT
ap-1538	140	1	[	[	X
ap-1538	140	2	12	12	NUM
ap-1538	140	3	]	]	PUNCT
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ap-1538	140	5	,	,	PUNCT
ap-1538	140	6	n.	n.	PROPN
ap-1538	140	7	y.	y.	PROPN
ap-1538	140	8	,	,	PUNCT
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ap-1538	140	10	,	,	PUNCT
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ap-1538	140	16	neural	neural	ADJ
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ap-1538	140	18	by	by	ADP
ap-1538	140	19	genetic	genetic	ADJ
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ap-1538	140	23	,	,	PUNCT
ap-1538	140	24	ieee	ieee	NOUN
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ap-1538	141	1	on	on	ADP
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ap-1538	141	4	,	,	PUNCT
ap-1538	141	5	vol	vol	NOUN
ap-1538	141	6	.	.	PROPN
ap-1538	141	7	14	14	NUM
ap-1538	141	8	,	,	PUNCT
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ap-1538	141	11	2	2	NUM
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ap-1538	141	14	,	,	PUNCT
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ap-1538	141	16	,	,	PUNCT
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ap-1538	141	19	.	.	PUNCT
ap-1538	142	1	[	[	X
ap-1538	142	2	13	13	NUM
ap-1538	142	3	]	]	X
ap-1538	142	4	taylor	taylor	PROPN
ap-1538	142	5	,	,	PUNCT
ap-1538	142	6	j.	j.	PROPN
ap-1538	142	7	g.	g.	PROPN
ap-1538	142	8	,	,	PUNCT
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ap-1538	142	10	,	,	PUNCT
ap-1538	142	11	s.	s.	PROPN
ap-1538	142	12	:	:	PUNCT
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ap-1538	142	15	order	order	NOUN
ap-1538	142	16	correlations	correlation	NOUN
ap-1538	142	17	,	,	PUNCT
ap-1538	142	18	neural	neural	ADJ
ap-1538	142	19	networks	network	NOUN
ap-1538	142	20	,	,	PUNCT
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ap-1538	142	22	,	,	PUNCT
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ap-1538	142	24	,	,	PUNCT
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ap-1538	142	27	.	.	PUNCT
ap-1538	143	1	[	[	X
ap-1538	143	2	14	14	NUM
ap-1538	143	3	]	]	SYM
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ap-1538	143	5	,	,	PUNCT
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ap-1538	143	9	,	,	PUNCT
ap-1538	143	10	m.	m.	NOUN
ap-1538	143	11	,	,	PUNCT
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ap-1538	143	15	,	,	PUNCT
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ap-1538	143	17	,	,	PUNCT
ap-1538	143	18	p.	p.	NOUN
ap-1538	143	19	:	:	PUNCT
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ap-1538	143	21	-	-	PUNCT
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ap-1538	143	23	neural	neural	ADJ
ap-1538	143	24	network	network	NOUN
ap-1538	143	25	structures	structure	NOUN
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ap-1538	143	34	.	.	PUNCT
ap-1538	144	1	on	on	ADP
ap-1538	144	2	neural	neural	ADJ
ap-1538	144	3	networks	network	NOUN
ap-1538	144	4	,	,	PUNCT
ap-1538	144	5	vol	vol	NOUN
ap-1538	144	6	.	.	PROPN
ap-1538	144	7	6	6	NUM
ap-1538	144	8	,	,	PUNCT
ap-1538	144	9	no	no	INTJ
ap-1538	144	10	.	.	NOUN
ap-1538	144	11	2	2	NUM
ap-1538	144	12	,	,	PUNCT
ap-1538	144	13	march	march	NOUN
ap-1538	144	14	1995	1995	NUM
ap-1538	144	15	,	,	PUNCT
ap-1538	144	16	p.	p.	NOUN
ap-1538	144	17	422–431	422–431	NUM
ap-1538	144	18	.	.	PUNCT
ap-1538	145	1	[	[	X
ap-1538	145	2	15	15	NUM
ap-1538	145	3	]	]	X
ap-1538	145	4	williams	williams	PROPN
ap-1538	145	5	,	,	PUNCT
ap-1538	145	6	r.	r.	PROPN
ap-1538	145	7	j.	j.	PROPN
ap-1538	145	8	,	,	PUNCT
ap-1538	145	9	zipser	zipser	PROPN
ap-1538	145	10	,	,	PUNCT
ap-1538	145	11	d.	d.	PROPN
ap-1538	145	12	:	:	PUNCT
ap-1538	145	13	a	a	DET
ap-1538	145	14	learning	learn	VERB
ap-1538	145	15	algorithm	algorithm	NOUN
ap-1538	145	16	for	for	ADP
ap-1538	145	17	continually	continually	ADV
ap-1538	145	18	running	run	VERB
ap-1538	145	19	fully	fully	ADV
ap-1538	145	20	recurrent	recurrent	ADJ
ap-1538	145	21	neural	neural	ADJ
ap-1538	145	22	networks	network	NOUN
ap-1538	145	23	,	,	PUNCT
ap-1538	145	24	neural	neural	ADJ
ap-1538	145	25	comput	comput	NOUN
ap-1538	145	26	.	.	PUNCT
ap-1538	145	27	,	,	PUNCT
ap-1538	145	28	vol	vol	NOUN
ap-1538	145	29	.	.	PROPN
ap-1538	145	30	1	1	NUM
ap-1538	145	31	,	,	PUNCT
ap-1538	145	32	1989	1989	NUM
ap-1538	145	33	,	,	PUNCT
ap-1538	145	34	p.	p.	NOUN
ap-1538	145	35	270–280	270–280	NUM
ap-1538	145	36	.	.	PUNCT
ap-1538	146	1	[	[	X
ap-1538	146	2	16	16	NUM
ap-1538	146	3	]	]	X
ap-1538	146	4	werbos	werbos	PROPN
ap-1538	146	5	,	,	PUNCT
ap-1538	146	6	p.	p.	PROPN
ap-1538	146	7	j.	j.	PROPN
ap-1538	146	8	:	:	PUNCT
ap-1538	146	9	backpropagation	backpropagation	NOUN
ap-1538	146	10	through	through	ADP
ap-1538	146	11	time	time	NOUN
ap-1538	146	12	:	:	PUNCT
ap-1538	146	13	what	what	PRON
ap-1538	146	14	it	it	PRON
ap-1538	146	15	is	be	AUX
ap-1538	146	16	and	and	CCONJ
ap-1538	146	17	how	how	SCONJ
ap-1538	146	18	to	to	PART
ap-1538	146	19	do	do	VERB
ap-1538	146	20	it	it	PRON
ap-1538	146	21	,	,	PUNCT
ap-1538	146	22	proc	proc	NOUN
ap-1538	146	23	.	.	PUNCT
ap-1538	147	1	ieee	ieee	NOUN
ap-1538	147	2	,	,	PUNCT
ap-1538	147	3	vol	vol	NOUN
ap-1538	147	4	.	.	PROPN
ap-1538	147	5	78	78	NUM
ap-1538	147	6	,	,	PUNCT
ap-1538	147	7	no	no	INTJ
ap-1538	147	8	.	.	NOUN
ap-1538	147	9	10	10	NUM
ap-1538	147	10	,	,	PUNCT
ap-1538	147	11	oct	oct	PROPN
ap-1538	147	12	.	.	PROPN
ap-1538	147	13	1990	1990	NUM
ap-1538	147	14	,	,	PUNCT
ap-1538	147	15	p.	p.	NOUN
ap-1538	147	16	1	1	NUM
ap-1538	147	17	550–1	550–1	NUM
ap-1538	147	18	560	560	NUM
ap-1538	147	19	.	.	PUNCT
ap-1538	148	1	issn	issn	PROPN
ap-1538	148	2	0018	0018	NUM
ap-1538	148	3	-	-	SYM
ap-1538	148	4	9219	9219	NUM
ap-1538	148	5	.	.	PUNCT
ap-1538	149	1	[	[	X
ap-1538	149	2	17	17	NUM
ap-1538	149	3	]	]	PUNCT
ap-1538	149	4	pearlmutter	pearlmutter	NOUN
ap-1538	149	5	,	,	PUNCT
ap-1538	149	6	b.	b.	PROPN
ap-1538	149	7	a.	a.	PROPN
ap-1538	149	8	:	:	PUNCT
ap-1538	149	9	gradient	gradient	ADJ
ap-1538	149	10	calculation	calculation	NOUN
ap-1538	149	11	for	for	ADP
ap-1538	149	12	dynamic	dynamic	ADJ
ap-1538	149	13	recurrent	recurrent	ADJ
ap-1538	149	14	neural	neural	ADJ
ap-1538	149	15	networks	network	NOUN
ap-1538	149	16	:	:	PUNCT
ap-1538	149	17	a	a	DET
ap-1538	149	18	survey	survey	NOUN
ap-1538	149	19	.	.	PUNCT
ap-1538	150	1	ieee	ieee	NOUN
ap-1538	150	2	transactions	transaction	NOUN
ap-1538	150	3	on	on	ADP
ap-1538	150	4	neural	neural	ADJ
ap-1538	150	5	networks	network	NOUN
ap-1538	150	6	,	,	PUNCT
ap-1538	150	7	6	6	NUM
ap-1538	150	8	,	,	PUNCT
ap-1538	150	9	5	5	NUM
ap-1538	150	10	,	,	PUNCT
ap-1538	150	11	1995	1995	NUM
ap-1538	150	12	,	,	PUNCT
ap-1538	150	13	1	1	NUM
ap-1538	150	14	212–1228	212–1228	NUM
ap-1538	150	15	.	.	PUNCT
ap-1538	151	1	doi	doi	NOUN
ap-1538	151	2	:	:	PUNCT
ap-1538	152	1	10.1109/72.410363	10.1109/72.410363	NUM
ap-1538	152	2	.	.	PUNCT
ap-1538	153	1	[	[	X
ap-1538	153	2	18	18	NUM
ap-1538	153	3	]	]	X
ap-1538	153	4	gupta	gupta	PROPN
ap-1538	153	5	,	,	PUNCT
ap-1538	153	6	m.	m.	NOUN
ap-1538	153	7	m.	m.	NOUN
ap-1538	153	8	,	,	PUNCT
ap-1538	153	9	bukovský	bukovský	ADJ
ap-1538	153	10	,	,	PUNCT
ap-1538	153	11	i.	i.	PROPN
ap-1538	153	12	,	,	PUNCT
ap-1538	153	13	noriasu	noriasu	PROPN
ap-1538	153	14	,	,	PUNCT
ap-1538	153	15	h.	h.	PROPN
ap-1538	153	16	,	,	PUNCT
ap-1538	153	17	solo	solo	NOUN
ap-1538	153	18	,	,	PUNCT
ap-1538	153	19	m.	m.	NOUN
ap-1538	153	20	g.	g.	PROPN
ap-1538	153	21	,	,	PUNCT
ap-1538	153	22	hou	hou	PROPN
ap-1538	153	23	,	,	PUNCT
ap-1538	153	24	z.-g	z.-g	PROPN
ap-1538	153	25	.	.	PUNCT
ap-1538	153	26	:	:	PUNCT
ap-1538	153	27	fundamentals	fundamental	NOUN
ap-1538	153	28	of	of	ADP
ap-1538	153	29	higher	high	ADJ
ap-1538	153	30	order	order	NOUN
ap-1538	153	31	neural	neural	ADJ
ap-1538	153	32	networks	network	NOUN
ap-1538	153	33	for	for	ADP
ap-1538	153	34	modeling	modeling	NOUN
ap-1538	153	35	and	and	CCONJ
ap-1538	153	36	simulation	simulation	NOUN
ap-1538	153	37	,	,	PUNCT
ap-1538	153	38	in	in	ADP
ap-1538	153	39	artificial	artificial	ADJ
ap-1538	153	40	higher	high	ADJ
ap-1538	153	41	order	order	NOUN
ap-1538	153	42	neural	neural	ADJ
ap-1538	153	43	networks	network	NOUN
ap-1538	153	44	for	for	ADP
ap-1538	153	45	modeling	modeling	NOUN
ap-1538	153	46	and	and	CCONJ
ap-1538	153	47	simulation	simulation	NOUN
ap-1538	153	48	,	,	PUNCT
ap-1538	153	49	ed	ed	PROPN
ap-1538	153	50	.	.	PUNCT
ap-1538	153	51	m.	m.	PROPN
ap-1538	153	52	zhang	zhang	PROPN
ap-1538	153	53	,	,	PUNCT
ap-1538	153	54	igi	igi	PROPN
ap-1538	153	55	global	global	PROPN
ap-1538	153	56	,	,	PUNCT
ap-1538	153	57	2012	2012	NUM
ap-1538	153	58	,	,	PUNCT
ap-1538	153	59	(	(	PUNCT
ap-1538	153	60	accepted	accept	VERB
ap-1538	153	61	,	,	PUNCT
ap-1538	153	62	to	to	PART
ap-1538	153	63	appear	appear	VERB
ap-1538	153	64	in	in	ADP
ap-1538	153	65	2012	2012	NUM
ap-1538	153	66	)	)	PUNCT
ap-1538	153	67	.	.	PUNCT
ap-1538	154	1	[	[	X
ap-1538	154	2	19	19	NUM
ap-1538	154	3	]	]	PUNCT
ap-1538	154	4	bukovský	bukovský	ADJ
ap-1538	154	5	,	,	PUNCT
ap-1538	154	6	i.	i.	PROPN
ap-1538	154	7	,	,	PUNCT
ap-1538	154	8	křehĺık	křehĺık	PROPN
ap-1538	154	9	,	,	PUNCT
ap-1538	154	10	k.	k.	PROPN
ap-1538	154	11	:	:	PUNCT
ap-1538	154	12	testy	testy	PROPN
ap-1538	154	13	neuronového	neuronového	PROPN
ap-1538	154	14	modelu	modelu	PROPN
ap-1538	154	15	kotle	kotle	PROPN
ap-1538	154	16	elektrárny	elektrárny	PROPN
ap-1538	154	17	mělńık	mělńık	PROPN
ap-1538	154	18	i.	i.	PROPN
ap-1538	154	19	výzkumná	výzkumná	PROPN
ap-1538	154	20	zpráva	zpráva	PROPN
ap-1538	154	21	č.	č.	PROPN
ap-1538	154	22	6	6	NUM
ap-1538	154	23	–	–	PUNCT
ap-1538	154	24	zi00069	zi00069	PROPN
ap-1538	154	25	/	/	SYM
ap-1538	154	26	e06	e06	PROPN
ap-1538	154	27	.	.	PUNCT
ap-1538	155	1	ústav	ústav	VERB
ap-1538	156	1	př́ıstrojové	př́ıstrojové	PRON
ap-1538	156	2	a	a	DET
ap-1538	156	3	ř́ıd́ıćı	ř́ıd́ıćı	NOUN
ap-1538	156	4	techniky	techniky	VERB
ap-1538	156	5	,	,	PUNCT
ap-1538	156	6	fakulta	fakulta	NOUN
ap-1538	156	7	strojńı	strojńı	PROPN
ap-1538	156	8	,	,	PUNCT
ap-1538	156	9	čvut	čvut	PUNCT
ap-1538	156	10	v	v	ADP
ap-1538	156	11	praze	praze	NOUN
ap-1538	156	12	,	,	PUNCT
ap-1538	156	13	2011	2011	NUM
ap-1538	156	14	.	.	PUNCT
ap-1538	157	1	22	22	NUM