id	sid	tid	token	lemma	pos
cet-6362	1	1	untitled	untitled	ADJ
cet-6362	1	2	chemical	chemical	NOUN
cet-6362	1	3	engineering	engineering	NOUN
cet-6362	1	4	transactions	transaction	NOUN
cet-6362	1	5	vol	vol	NOUN
cet-6362	1	6	.	.	PROPN
cet-6362	2	1	33	33	NUM
cet-6362	2	2	,	,	PUNCT
cet-6362	2	3	2013	2013	NUM
cet-6362	2	4	a	a	DET
cet-6362	2	5	publication	publication	NOUN
cet-6362	2	6	of	of	ADP
cet-6362	2	7	the	the	DET
cet-6362	2	8	italian	italian	ADJ
cet-6362	2	9	association	association	NOUN
cet-6362	2	10	of	of	ADP
cet-6362	2	11	chemical	chemical	PROPN
cet-6362	2	12	engineering	engineering	NOUN
cet-6362	2	13	online	online	ADV
cet-6362	2	14	at	at	ADP
cet-6362	2	15	:	:	PUNCT
cet-6362	2	16	www.aidic.it/cet	www.aidic.it/cet	PROPN
cet-6362	2	17	guest	guest	NOUN
cet-6362	2	18	editors	editor	NOUN
cet-6362	2	19	:	:	PUNCT
cet-6362	2	20	enrico	enrico	PROPN
cet-6362	2	21	zio	zio	PROPN
cet-6362	2	22	,	,	PUNCT
cet-6362	2	23	piero	piero	PROPN
cet-6362	2	24	baraldi	baraldi	PROPN
cet-6362	2	25	copyright	copyright	NOUN
cet-6362	2	26	©	©	PROPN
cet-6362	2	27	2013	2013	NUM
cet-6362	2	28	,	,	PUNCT
cet-6362	2	29	aidic	aidic	ADJ
cet-6362	2	30	servizi	servizi	PROPN
cet-6362	2	31	s.r.l	s.r.l	NOUN
cet-6362	2	32	.	.	PUNCT
cet-6362	2	33	,	,	PUNCT
cet-6362	2	34	isbn	isbn	PROPN
cet-6362	2	35	978	978	NUM
cet-6362	2	36	-	-	SYM
cet-6362	2	37	88	88	NUM
cet-6362	2	38	-	-	PUNCT
cet-6362	2	39	95608	95608	NUM
cet-6362	2	40	-	-	PUNCT
cet-6362	2	41	24	24	NUM
cet-6362	2	42	-	-	SYM
cet-6362	2	43	2	2	NUM
cet-6362	2	44	;	;	PUNCT
cet-6362	2	45	issn	issn	PROPN
cet-6362	2	46	1974	1974	NUM
cet-6362	2	47	-	-	SYM
cet-6362	2	48	9791	9791	NUM
cet-6362	2	49	a	a	DET
cet-6362	2	50	genetic	genetic	ADJ
cet-6362	2	51	algorithm	algorithm	NOUN
cet-6362	2	52	and	and	CCONJ
cet-6362	2	53	neural	neural	ADJ
cet-6362	2	54	network	network	NOUN
cet-6362	2	55	technique	technique	NOUN
cet-6362	2	56	for	for	ADP
cet-6362	2	57	predicting	predict	VERB
cet-6362	2	58	wind	wind	NOUN
cet-6362	2	59	power	power	NOUN
cet-6362	2	60	under	under	ADP
cet-6362	2	61	uncertainty	uncertainty	NOUN
cet-6362	2	62	ronay	ronay	ADV
cet-6362	2	63	aka	aka	ADV
cet-6362	2	64	,	,	PUNCT
cet-6362	2	65	yan	yan	PROPN
cet-6362	2	66	-	-	PUNCT
cet-6362	2	67	fu	fu	PROPN
cet-6362	2	68	lia	lia	PROPN
cet-6362	2	69	,	,	PUNCT
cet-6362	2	70	valeria	valeria	PROPN
cet-6362	2	71	vitellia	vitellia	PROPN
cet-6362	2	72	,	,	PUNCT
cet-6362	2	73	enrico	enrico	PROPN
cet-6362	2	74	zio*a	zio*a	PRON
cet-6362	2	75	,	,	PUNCT
cet-6362	2	76	b	b	X
cet-6362	2	77	achair	achair	NOUN
cet-6362	2	78	on	on	ADP
cet-6362	2	79	systems	system	NOUN
cet-6362	2	80	science	science	NOUN
cet-6362	2	81	and	and	CCONJ
cet-6362	2	82	the	the	DET
cet-6362	2	83	energetic	energetic	ADJ
cet-6362	2	84	challenge	challenge	NOUN
cet-6362	2	85	,	,	PUNCT
cet-6362	2	86	european	european	PROPN
cet-6362	2	87	foundation	foundation	PROPN
cet-6362	2	88	for	for	ADP
cet-6362	2	89	new	new	ADJ
cet-6362	2	90	energy	energy	NOUN
cet-6362	2	91	électricité	électricité	PROPN
cet-6362	2	92	de	de	X
cet-6362	2	93	france	france	PROPN
cet-6362	2	94	,	,	PUNCT
cet-6362	2	95	école	école	PROPN
cet-6362	2	96	centrale	centrale	PROPN
cet-6362	2	97	paris	paris	PROPN
cet-6362	2	98	,	,	PUNCT
cet-6362	2	99	chatenay	chatenay	NOUN
cet-6362	2	100	-	-	PUNCT
cet-6362	2	101	malabry	malabry	NOUN
cet-6362	2	102	,	,	PUNCT
cet-6362	2	103	france	france	PROPN
cet-6362	2	104	,	,	PUNCT
cet-6362	2	105	and	and	CCONJ
cet-6362	2	106	supelec	supelec	NOUN
cet-6362	2	107	(	(	PUNCT
cet-6362	2	108	école	école	PROPN
cet-6362	2	109	supérieure	supérieure	PROPN
cet-6362	2	110	d'électricité	d'électricité	PROPN
cet-6362	2	111	)	)	PUNCT
cet-6362	2	112	,	,	PUNCT
cet-6362	2	113	plateau	plateau	NOUN
cet-6362	2	114	de	de	X
cet-6362	2	115	moulon	moulon	NOUN
cet-6362	2	116	,	,	PUNCT
cet-6362	2	117	gifsur	gifsur	NOUN
cet-6362	2	118	-	-	PUNCT
cet-6362	2	119	yvette	yvette	PROPN
cet-6362	2	120	,	,	PUNCT
cet-6362	2	121	france	france	PROPN
cet-6362	2	122	.	.	PUNCT
cet-6362	3	1	benergy	benergy	PROPN
cet-6362	3	2	department	department	PROPN
cet-6362	3	3	,	,	PUNCT
cet-6362	3	4	politecnico	politecnico	PROPN
cet-6362	3	5	di	di	X
cet-6362	3	6	milano	milano	PROPN
cet-6362	3	7	,	,	PUNCT
cet-6362	3	8	via	via	ADP
cet-6362	3	9	ponzio	ponzio	PROPN
cet-6362	3	10	34/3	34/3	PROPN
cet-6362	3	11	milan	milan	PROPN
cet-6362	3	12	,	,	PUNCT
cet-6362	3	13	20133	20133	NUM
cet-6362	3	14	italy	italy	PROPN
cet-6362	3	15	enrico.zio@ecp.fr	enrico.zio@ecp.fr	NOUN
cet-6362	3	16	wind	wind	NOUN
cet-6362	3	17	speed	speed	NOUN
cet-6362	3	18	uncertainty	uncertainty	NOUN
cet-6362	3	19	,	,	PUNCT
cet-6362	3	20	and	and	CCONJ
cet-6362	3	21	the	the	DET
cet-6362	3	22	variability	variability	NOUN
cet-6362	3	23	in	in	ADP
cet-6362	3	24	the	the	DET
cet-6362	3	25	physical	physical	ADJ
cet-6362	3	26	and	and	CCONJ
cet-6362	3	27	operating	operating	NOUN
cet-6362	3	28	characteristics	characteristic	NOUN
cet-6362	3	29	of	of	ADP
cet-6362	3	30	turbines	turbine	NOUN
cet-6362	3	31	have	have	VERB
cet-6362	3	32	a	a	DET
cet-6362	3	33	significant	significant	ADJ
cet-6362	3	34	impact	impact	NOUN
cet-6362	3	35	on	on	ADP
cet-6362	3	36	power	power	NOUN
cet-6362	3	37	system	system	NOUN
cet-6362	3	38	operations	operation	NOUN
cet-6362	3	39	such	such	ADJ
cet-6362	3	40	as	as	ADP
cet-6362	3	41	regulation	regulation	NOUN
cet-6362	3	42	,	,	PUNCT
cet-6362	3	43	load	load	NOUN
cet-6362	3	44	following	following	NOUN
cet-6362	3	45	,	,	PUNCT
cet-6362	3	46	balancing	balancing	NOUN
cet-6362	3	47	,	,	PUNCT
cet-6362	3	48	unit	unit	NOUN
cet-6362	3	49	commitment	commitment	NOUN
cet-6362	3	50	and	and	CCONJ
cet-6362	3	51	scheduling	scheduling	NOUN
cet-6362	3	52	.	.	PUNCT
cet-6362	4	1	in	in	ADP
cet-6362	4	2	this	this	DET
cet-6362	4	3	study	study	NOUN
cet-6362	4	4	,	,	PUNCT
cet-6362	4	5	we	we	PRON
cet-6362	4	6	consider	consider	VERB
cet-6362	4	7	historical	historical	ADJ
cet-6362	4	8	values	value	NOUN
cet-6362	4	9	of	of	ADP
cet-6362	4	10	wind	wind	NOUN
cet-6362	4	11	power	power	NOUN
cet-6362	4	12	for	for	ADP
cet-6362	4	13	predicting	predict	VERB
cet-6362	4	14	future	future	ADJ
cet-6362	4	15	values	value	NOUN
cet-6362	4	16	taking	take	VERB
cet-6362	4	17	into	into	ADP
cet-6362	4	18	account	account	NOUN
cet-6362	4	19	both	both	DET
cet-6362	4	20	the	the	DET
cet-6362	4	21	variability	variability	NOUN
cet-6362	4	22	in	in	ADP
cet-6362	4	23	the	the	DET
cet-6362	4	24	input	input	NOUN
cet-6362	4	25	and	and	CCONJ
cet-6362	4	26	the	the	DET
cet-6362	4	27	uncertainty	uncertainty	NOUN
cet-6362	4	28	in	in	ADP
cet-6362	4	29	the	the	DET
cet-6362	4	30	model	model	NOUN
cet-6362	4	31	structure	structure	NOUN
cet-6362	4	32	.	.	PUNCT
cet-6362	5	1	uncertainty	uncertainty	NOUN
cet-6362	5	2	in	in	ADP
cet-6362	5	3	the	the	DET
cet-6362	5	4	hourly	hourly	ADJ
cet-6362	5	5	wind	wind	NOUN
cet-6362	5	6	power	power	NOUN
cet-6362	5	7	input	input	NOUN
cet-6362	5	8	is	be	AUX
cet-6362	5	9	presented	present	VERB
cet-6362	5	10	as	as	ADP
cet-6362	5	11	intervals	interval	NOUN
cet-6362	5	12	of	of	ADP
cet-6362	5	13	within	within	ADP
cet-6362	5	14	-	-	PUNCT
cet-6362	5	15	hour	hour	NOUN
cet-6362	5	16	variability	variability	NOUN
cet-6362	5	17	.	.	PUNCT
cet-6362	6	1	a	a	DET
cet-6362	6	2	neural	neural	ADJ
cet-6362	6	3	network	network	NOUN
cet-6362	6	4	(	(	PUNCT
cet-6362	6	5	nn	nn	NOUN
cet-6362	6	6	)	)	PUNCT
cet-6362	6	7	is	be	AUX
cet-6362	6	8	trained	train	VERB
cet-6362	6	9	on	on	ADP
cet-6362	6	10	the	the	DET
cet-6362	6	11	interval	interval	NOUN
cet-6362	6	12	-	-	PUNCT
cet-6362	6	13	valued	value	VERB
cet-6362	6	14	inputs	input	NOUN
cet-6362	6	15	to	to	PART
cet-6362	6	16	provide	provide	VERB
cet-6362	6	17	prediction	prediction	NOUN
cet-6362	6	18	intervals	interval	NOUN
cet-6362	6	19	(	(	PUNCT
cet-6362	6	20	pis	pis	NOUN
cet-6362	6	21	)	)	PUNCT
cet-6362	6	22	in	in	ADP
cet-6362	6	23	output	output	NOUN
cet-6362	6	24	.	.	PUNCT
cet-6362	7	1	a	a	DET
cet-6362	7	2	multi	multi	ADJ
cet-6362	7	3	-	-	ADJ
cet-6362	7	4	objective	objective	ADJ
cet-6362	7	5	genetic	genetic	ADJ
cet-6362	7	6	algorithm	algorithm	NOUN
cet-6362	7	7	(	(	PUNCT
cet-6362	7	8	namely	namely	ADV
cet-6362	7	9	,	,	PUNCT
cet-6362	7	10	non	non	ADJ
cet-6362	7	11	-	-	ADJ
cet-6362	7	12	dominated	dominated	ADJ
cet-6362	7	13	sorting	sort	VERB
cet-6362	7	14	genetic	genetic	ADJ
cet-6362	7	15	algorithm	algorithm	NOUN
cet-6362	7	16	–	–	PUNCT
cet-6362	7	17	ii	ii	PROPN
cet-6362	7	18	(	(	PUNCT
cet-6362	7	19	nsga	nsga	NOUN
cet-6362	7	20	-	-	PUNCT
cet-6362	7	21	ii	ii	NOUN
cet-6362	7	22	)	)	PUNCT
cet-6362	7	23	)	)	PUNCT
cet-6362	7	24	is	be	AUX
cet-6362	7	25	used	use	VERB
cet-6362	7	26	to	to	PART
cet-6362	7	27	train	train	VERB
cet-6362	7	28	the	the	DET
cet-6362	7	29	nn	nn	PROPN
cet-6362	7	30	.	.	PROPN
cet-6362	7	31	a	a	DET
cet-6362	7	32	multi	multi	ADJ
cet-6362	7	33	-	-	ADJ
cet-6362	7	34	objective	objective	ADJ
cet-6362	7	35	framework	framework	NOUN
cet-6362	7	36	is	be	AUX
cet-6362	7	37	adopted	adopt	VERB
cet-6362	7	38	to	to	PART
cet-6362	7	39	find	find	VERB
cet-6362	7	40	pis	pis	NOUN
cet-6362	7	41	which	which	PRON
cet-6362	7	42	are	be	AUX
cet-6362	7	43	optimal	optimal	ADJ
cet-6362	7	44	for	for	ADP
cet-6362	7	45	accuracy	accuracy	NOUN
cet-6362	7	46	(	(	PUNCT
cet-6362	7	47	coverage	coverage	NOUN
cet-6362	7	48	probability	probability	NOUN
cet-6362	7	49	)	)	PUNCT
cet-6362	7	50	and	and	CCONJ
cet-6362	7	51	efficacy	efficacy	NOUN
cet-6362	7	52	(	(	PUNCT
cet-6362	7	53	width	width	PROPN
cet-6362	7	54	)	)	PUNCT
cet-6362	7	55	.	.	PUNCT
cet-6362	8	1	1	1	X
cet-6362	8	2	.	.	X
cet-6362	8	3	introduction	introduction	NOUN
cet-6362	8	4	the	the	DET
cet-6362	8	5	power	power	NOUN
cet-6362	8	6	output	output	NOUN
cet-6362	8	7	of	of	ADP
cet-6362	8	8	a	a	DET
cet-6362	8	9	wind	wind	NOUN
cet-6362	8	10	turbine	turbine	NOUN
cet-6362	8	11	mainly	mainly	ADV
cet-6362	8	12	depends	depend	VERB
cet-6362	8	13	on	on	ADP
cet-6362	8	14	the	the	DET
cet-6362	8	15	local	local	ADJ
cet-6362	8	16	wind	wind	NOUN
cet-6362	8	17	speed	speed	NOUN
cet-6362	8	18	,	,	PUNCT
cet-6362	8	19	and	and	CCONJ
cet-6362	8	20	the	the	DET
cet-6362	8	21	physical	physical	ADJ
cet-6362	8	22	and	and	CCONJ
cet-6362	8	23	operating	operating	NOUN
cet-6362	8	24	characteristics	characteristic	NOUN
cet-6362	8	25	of	of	ADP
cet-6362	8	26	the	the	DET
cet-6362	8	27	turbine	turbine	NOUN
cet-6362	8	28	.	.	PUNCT
cet-6362	9	1	wind	wind	NOUN
cet-6362	9	2	speed	speed	NOUN
cet-6362	9	3	changes	change	NOUN
cet-6362	9	4	according	accord	VERB
cet-6362	9	5	to	to	ADP
cet-6362	9	6	weather	weather	NOUN
cet-6362	9	7	conditions	condition	NOUN
cet-6362	9	8	,	,	PUNCT
cet-6362	9	9	in	in	ADP
cet-6362	9	10	time	time	NOUN
cet-6362	9	11	scales	scale	NOUN
cet-6362	9	12	ranging	range	VERB
cet-6362	9	13	from	from	ADP
cet-6362	9	14	minutes	minute	NOUN
cet-6362	9	15	to	to	ADP
cet-6362	9	16	hours	hour	NOUN
cet-6362	9	17	,	,	PUNCT
cet-6362	9	18	days	day	NOUN
cet-6362	9	19	and	and	CCONJ
cet-6362	9	20	years	year	NOUN
cet-6362	9	21	(	(	PUNCT
cet-6362	9	22	kavasseri	kavasseri	NOUN
cet-6362	9	23	and	and	CCONJ
cet-6362	9	24	seetharaman	seetharaman	NOUN
cet-6362	9	25	,	,	PUNCT
cet-6362	9	26	2009	2009	NUM
cet-6362	9	27	)	)	PUNCT
cet-6362	9	28	;	;	PUNCT
cet-6362	9	29	this	this	DET
cet-6362	9	30	aleatory	aleatory	ADJ
cet-6362	9	31	behavior	behavior	NOUN
cet-6362	9	32	induces	induce	VERB
cet-6362	9	33	a	a	DET
cet-6362	9	34	corresponding	corresponding	ADJ
cet-6362	9	35	variability	variability	NOUN
cet-6362	9	36	in	in	ADP
cet-6362	9	37	the	the	DET
cet-6362	9	38	power	power	NOUN
cet-6362	9	39	output	output	NOUN
cet-6362	9	40	.	.	PUNCT
cet-6362	10	1	uncertainty	uncertainty	NOUN
cet-6362	10	2	and	and	CCONJ
cet-6362	10	3	variability	variability	NOUN
cet-6362	10	4	of	of	ADP
cet-6362	10	5	wind	wind	NOUN
cet-6362	10	6	power	power	NOUN
cet-6362	10	7	have	have	VERB
cet-6362	10	8	significant	significant	ADJ
cet-6362	10	9	effects	effect	NOUN
cet-6362	10	10	on	on	ADP
cet-6362	10	11	wind	wind	NOUN
cet-6362	10	12	integrated	integrate	VERB
cet-6362	10	13	power	power	NOUN
cet-6362	10	14	system	system	NOUN
cet-6362	10	15	operations	operation	NOUN
cet-6362	10	16	,	,	PUNCT
cet-6362	10	17	such	such	ADJ
cet-6362	10	18	as	as	ADP
cet-6362	10	19	regulation	regulation	NOUN
cet-6362	10	20	,	,	PUNCT
cet-6362	10	21	load	load	NOUN
cet-6362	10	22	following	following	NOUN
cet-6362	10	23	,	,	PUNCT
cet-6362	10	24	balancing	balancing	NOUN
cet-6362	10	25	,	,	PUNCT
cet-6362	10	26	unit	unit	NOUN
cet-6362	10	27	commitment	commitment	NOUN
cet-6362	10	28	and	and	CCONJ
cet-6362	10	29	scheduling	scheduling	NOUN
cet-6362	10	30	(	(	PUNCT
cet-6362	10	31	lew	lew	PROPN
cet-6362	10	32	et	et	PROPN
cet-6362	10	33	al	al	PROPN
cet-6362	10	34	.	.	PROPN
cet-6362	10	35	,	,	PUNCT
cet-6362	10	36	2011	2011	NUM
cet-6362	10	37	;	;	PUNCT
cet-6362	10	38	lei	lei	PROPN
cet-6362	10	39	et	et	PROPN
cet-6362	10	40	al	al	PROPN
cet-6362	10	41	.	.	PROPN
cet-6362	10	42	,	,	PUNCT
cet-6362	10	43	2009	2009	NUM
cet-6362	10	44	)	)	PUNCT
cet-6362	10	45	.	.	PUNCT
cet-6362	11	1	several	several	ADJ
cet-6362	11	2	works	work	NOUN
cet-6362	11	3	can	can	AUX
cet-6362	11	4	be	be	AUX
cet-6362	11	5	found	find	VERB
cet-6362	11	6	in	in	ADP
cet-6362	11	7	the	the	DET
cet-6362	11	8	literature	literature	NOUN
cet-6362	11	9	which	which	PRON
cet-6362	11	10	focus	focus	VERB
cet-6362	11	11	on	on	ADP
cet-6362	11	12	providing	provide	VERB
cet-6362	11	13	a	a	DET
cet-6362	11	14	forecasting	forecasting	NOUN
cet-6362	11	15	tool	tool	NOUN
cet-6362	11	16	in	in	ADP
cet-6362	11	17	order	order	NOUN
cet-6362	11	18	to	to	PART
cet-6362	11	19	predict	predict	VERB
cet-6362	11	20	wind	wind	NOUN
cet-6362	11	21	speed	speed	NOUN
cet-6362	11	22	and	and	CCONJ
cet-6362	11	23	power	power	NOUN
cet-6362	11	24	.	.	PUNCT
cet-6362	12	1	the	the	DET
cet-6362	12	2	approaches	approach	NOUN
cet-6362	12	3	proposed	propose	VERB
cet-6362	12	4	therein	therein	ADV
cet-6362	12	5	can	can	AUX
cet-6362	12	6	be	be	AUX
cet-6362	12	7	classi	classi	ADJ
cet-6362	12	8	�	�	PROPN
cet-6362	12	9	ed	ed	PROPN
cet-6362	12	10	as	as	ADP
cet-6362	12	11	physical	physical	ADJ
cet-6362	12	12	,	,	PUNCT
cet-6362	12	13	i.e.	i.e.	X
cet-6362	12	14	making	make	VERB
cet-6362	12	15	use	use	NOUN
cet-6362	12	16	of	of	ADP
cet-6362	12	17	numerical	numerical	ADJ
cet-6362	12	18	weather	weather	NOUN
cet-6362	12	19	prediction	prediction	NOUN
cet-6362	12	20	(	(	PUNCT
cet-6362	12	21	nwp	nwp	NOUN
cet-6362	12	22	)	)	PUNCT
cet-6362	12	23	models	model	NOUN
cet-6362	12	24	(	(	PUNCT
cet-6362	12	25	giebel	giebel	VERB
cet-6362	12	26	et	et	PROPN
cet-6362	12	27	al	al	PROPN
cet-6362	12	28	.	.	PROPN
cet-6362	12	29	,	,	PUNCT
cet-6362	12	30	2006	2006	NUM
cet-6362	12	31	)	)	PUNCT
cet-6362	12	32	,	,	PUNCT
cet-6362	12	33	statistical	statistical	ADJ
cet-6362	12	34	,	,	PUNCT
cet-6362	12	35	i.e.	i.e.	X
cet-6362	12	36	data	data	NOUN
cet-6362	12	37	-	-	PUNCT
cet-6362	12	38	driven	drive	VERB
cet-6362	12	39	methods	method	NOUN
cet-6362	12	40	comprising	comprise	VERB
cet-6362	12	41	also	also	ADV
cet-6362	12	42	artificial	artificial	ADJ
cet-6362	12	43	intelligence	intelligence	NOUN
cet-6362	12	44	methods	method	NOUN
cet-6362	12	45	like	like	ADP
cet-6362	12	46	neural	neural	ADJ
cet-6362	12	47	networks	network	NOUN
cet-6362	12	48	(	(	PUNCT
cet-6362	12	49	nn	nn	NOUN
cet-6362	12	50	)	)	PUNCT
cet-6362	12	51	and	and	CCONJ
cet-6362	12	52	fuzzy	fuzzy	ADJ
cet-6362	12	53	logic	logic	NOUN
cet-6362	12	54	(	(	PUNCT
cet-6362	12	55	kusiak	kusiak	PROPN
cet-6362	12	56	et	et	PROPN
cet-6362	12	57	al	al	PROPN
cet-6362	12	58	.	.	PROPN
cet-6362	12	59	,	,	PUNCT
cet-6362	12	60	2009	2009	NUM
cet-6362	12	61	)	)	PUNCT
cet-6362	12	62	,	,	PUNCT
cet-6362	12	63	or	or	CCONJ
cet-6362	12	64	a	a	DET
cet-6362	12	65	combination	combination	NOUN
cet-6362	12	66	of	of	ADP
cet-6362	12	67	both	both	PRON
cet-6362	12	68	(	(	PUNCT
cet-6362	12	69	sideratos	siderato	NOUN
cet-6362	12	70	and	and	CCONJ
cet-6362	12	71	hatziargyriou	hatziargyriou	NOUN
cet-6362	12	72	,	,	PUNCT
cet-6362	12	73	2007	2007	NUM
cet-6362	12	74	)	)	PUNCT
cet-6362	12	75	.	.	PUNCT
cet-6362	13	1	most	most	ADJ
cet-6362	13	2	research	research	NOUN
cet-6362	13	3	has	have	AUX
cet-6362	13	4	focused	focus	VERB
cet-6362	13	5	on	on	ADP
cet-6362	13	6	point	point	NOUN
cet-6362	13	7	prediction	prediction	NOUN
cet-6362	13	8	of	of	ADP
cet-6362	13	9	wind	wind	NOUN
cet-6362	13	10	power	power	NOUN
cet-6362	13	11	with	with	ADP
cet-6362	13	12	crisp	crisp	ADJ
cet-6362	13	13	input	input	NOUN
cet-6362	13	14	data	datum	NOUN
cet-6362	13	15	.	.	PUNCT
cet-6362	14	1	however	however	ADV
cet-6362	14	2	,	,	PUNCT
cet-6362	14	3	in	in	ADP
cet-6362	14	4	order	order	NOUN
cet-6362	14	5	to	to	PART
cet-6362	14	6	reflect	reflect	VERB
cet-6362	14	7	the	the	DET
cet-6362	14	8	variability	variability	NOUN
cet-6362	14	9	of	of	ADP
cet-6362	14	10	the	the	DET
cet-6362	14	11	phenomenon	phenomenon	NOUN
cet-6362	14	12	,	,	PUNCT
cet-6362	14	13	it	it	PRON
cet-6362	14	14	is	be	AUX
cet-6362	14	15	important	important	ADJ
cet-6362	14	16	to	to	PART
cet-6362	14	17	provide	provide	VERB
cet-6362	14	18	uncertainty	uncertainty	NOUN
cet-6362	14	19	evaluation	evaluation	NOUN
cet-6362	14	20	of	of	ADP
cet-6362	14	21	its	its	PRON
cet-6362	14	22	prediction	prediction	NOUN
cet-6362	14	23	considering	consider	VERB
cet-6362	14	24	variability	variability	NOUN
cet-6362	14	25	in	in	ADP
cet-6362	14	26	the	the	DET
cet-6362	14	27	input	input	NOUN
cet-6362	14	28	,	,	PUNCT
cet-6362	14	29	which	which	PRON
cet-6362	14	30	can	can	AUX
cet-6362	14	31	be	be	AUX
cet-6362	14	32	due	due	ADJ
cet-6362	14	33	to	to	ADP
cet-6362	14	34	measurement	measurement	NOUN
cet-6362	14	35	errors	error	NOUN
cet-6362	14	36	and	and	CCONJ
cet-6362	14	37	imprecise	imprecise	ADV
cet-6362	14	38	,	,	PUNCT
cet-6362	14	39	incomplete	incomplete	ADJ
cet-6362	14	40	and	and	CCONJ
cet-6362	14	41	uncertain	uncertain	ADJ
cet-6362	14	42	information	information	NOUN
cet-6362	14	43	.	.	PUNCT
cet-6362	15	1	interval	interval	NOUN
cet-6362	15	2	-	-	PUNCT
cet-6362	15	3	valued	value	VERB
cet-6362	15	4	representation	representation	NOUN
cet-6362	15	5	(	(	PUNCT
cet-6362	15	6	moore	moore	PROPN
cet-6362	15	7	et	et	PROPN
cet-6362	15	8	al	al	PROPN
cet-6362	15	9	.	.	PROPN
cet-6362	15	10	,	,	PUNCT
cet-6362	15	11	2009	2009	NUM
cet-6362	15	12	)	)	PUNCT
cet-6362	15	13	,	,	PUNCT
cet-6362	15	14	which	which	PRON
cet-6362	15	15	means	mean	VERB
cet-6362	15	16	considering	consider	VERB
cet-6362	15	17	an	an	DET
cet-6362	15	18	interval	interval	NOUN
cet-6362	15	19	enclosing	enclose	VERB
cet-6362	15	20	real	real	ADJ
cet-6362	15	21	observations	observation	NOUN
cet-6362	15	22	instead	instead	ADV
cet-6362	15	23	of	of	ADP
cet-6362	15	24	real	real	ADJ
cet-6362	15	25	quantities	quantity	NOUN
cet-6362	15	26	themselves	themselves	PRON
cet-6362	15	27	,	,	PUNCT
cet-6362	15	28	can	can	AUX
cet-6362	15	29	be	be	AUX
cet-6362	15	30	used	use	VERB
cet-6362	15	31	to	to	PART
cet-6362	15	32	reflect	reflect	VERB
cet-6362	15	33	the	the	DET
cet-6362	15	34	variability	variability	NOUN
cet-6362	15	35	(	(	PUNCT
cet-6362	15	36	e.g.	e.g.	ADV
cet-6362	15	37	bounding	bound	VERB
cet-6362	15	38	wind	wind	NOUN
cet-6362	15	39	speeds	speed	NOUN
cet-6362	15	40	in	in	ADP
cet-6362	15	41	a	a	DET
cet-6362	15	42	given	give	VERB
cet-6362	15	43	area	area	NOUN
cet-6362	15	44	,	,	PUNCT
cet-6362	15	45	minimum	minimum	NOUN
cet-6362	15	46	and	and	CCONJ
cet-6362	15	47	maximum	maximum	ADJ
cet-6362	15	48	of	of	ADP
cet-6362	15	49	daily	daily	ADJ
cet-6362	15	50	temperature	temperature	NOUN
cet-6362	15	51	,	,	PUNCT
cet-6362	15	52	etc	etc	X
cet-6362	15	53	.	.	X
cet-6362	15	54	)	)	PUNCT
cet-6362	16	1	and	and	CCONJ
cet-6362	16	2	uncertainty	uncertainty	NOUN
cet-6362	16	3	(	(	PUNCT
cet-6362	16	4	e.g.	e.g.	ADV
cet-6362	16	5	strongly	strongly	ADV
cet-6362	16	6	skewed	skewed	ADJ
cet-6362	16	7	wind	wind	NOUN
cet-6362	16	8	speed	speed	NOUN
cet-6362	16	9	distributions	distribution	NOUN
cet-6362	16	10	,	,	PUNCT
cet-6362	16	11	imprecise	imprecise	ADJ
cet-6362	16	12	reliability	reliability	NOUN
cet-6362	16	13	of	of	ADP
cet-6362	16	14	the	the	DET
cet-6362	16	15	components	component	NOUN
cet-6362	16	16	,	,	PUNCT
cet-6362	16	17	etc	etc	X
cet-6362	16	18	.	.	X
cet-6362	16	19	)	)	PUNCT
cet-6362	17	1	in	in	ADP
cet-6362	17	2	the	the	DET
cet-6362	17	3	observed	observe	VERB
cet-6362	17	4	crisp	crisp	ADJ
cet-6362	17	5	,	,	PUNCT
cet-6362	17	6	single	single	ADJ
cet-6362	17	7	-	-	PUNCT
cet-6362	17	8	valued	value	VERB
cet-6362	17	9	measurements	measurement	NOUN
cet-6362	17	10	.	.	PUNCT
cet-6362	18	1	muñoz	muñoz	PROPN
cet-6362	18	2	san	san	PROPN
cet-6362	18	3	roque	roque	PROPN
cet-6362	18	4	et	et	PROPN
cet-6362	18	5	al	al	PROPN
cet-6362	18	6	.	.	PROPN
cet-6362	19	1	(	(	PUNCT
cet-6362	19	2	2007	2007	NUM
cet-6362	19	3	)	)	PUNCT
cet-6362	19	4	propose	propose	VERB
cet-6362	19	5	an	an	DET
cet-6362	19	6	interval	interval	NOUN
cet-6362	19	7	multi	multi	ADJ
cet-6362	19	8	-	-	ADJ
cet-6362	19	9	layer	layer	ADJ
cet-6362	19	10	perceptron	perceptron	NOUN
cet-6362	19	11	(	(	PUNCT
cet-6362	19	12	imlp	imlp	PROPN
cet-6362	19	13	)	)	PUNCT
cet-6362	19	14	model	model	NOUN
cet-6362	19	15	capable	capable	ADJ
cet-6362	19	16	of	of	ADP
cet-6362	19	17	handling	handle	VERB
cet-6362	19	18	input	input	NOUN
cet-6362	19	19	and	and	CCONJ
cet-6362	19	20	output	output	NOUN
cet-6362	19	21	interval	interval	NOUN
cet-6362	19	22	data	datum	NOUN
cet-6362	19	23	,	,	PUNCT
cet-6362	19	24	whereas	whereas	SCONJ
cet-6362	19	25	the	the	DET
cet-6362	19	26	weights	weight	NOUN
cet-6362	19	27	and	and	CCONJ
cet-6362	19	28	biases	bias	NOUN
cet-6362	19	29	defining	define	VERB
cet-6362	19	30	the	the	DET
cet-6362	19	31	network	network	NOUN
cet-6362	19	32	are	be	AUX
cet-6362	19	33	single	single	ADV
cet-6362	19	34	-	-	PUNCT
cet-6362	19	35	valued	value	VERB
cet-6362	19	36	.	.	PUNCT
cet-6362	20	1	they	they	PRON
cet-6362	20	2	test	test	VERB
cet-6362	20	3	the	the	DET
cet-6362	20	4	model	model	NOUN
cet-6362	20	5	by	by	ADP
cet-6362	20	6	application	application	NOUN
cet-6362	20	7	to	to	ADP
cet-6362	20	8	the	the	DET
cet-6362	20	9	forecasting	forecasting	NOUN
cet-6362	20	10	of	of	ADP
cet-6362	20	11	daily	daily	ADJ
cet-6362	20	12	electricity	electricity	NOUN
cet-6362	20	13	prices	price	NOUN
cet-6362	20	14	intervals	interval	NOUN
cet-6362	20	15	.	.	PUNCT
cet-6362	21	1	similarly	similarly	ADV
cet-6362	21	2	,	,	PUNCT
cet-6362	21	3	garcia	garcia	PROPN
cet-6362	21	4	-	-	PUNCT
cet-6362	21	5	ascanio	ascanio	PROPN
cet-6362	21	6	and	and	CCONJ
cet-6362	21	7	maté	maté	NOUN
cet-6362	21	8	(	(	PUNCT
cet-6362	21	9	2010	2010	NUM
cet-6362	21	10	)	)	PUNCT
cet-6362	21	11	make	make	VERB
cet-6362	21	12	a	a	DET
cet-6362	21	13	comparison	comparison	NOUN
cet-6362	21	14	between	between	ADP
cet-6362	21	15	imlp	imlp	NOUN
cet-6362	21	16	and	and	CCONJ
cet-6362	21	17	the	the	DET
cet-6362	21	18	vector	vector	NOUN
cet-6362	21	19	autoregressive	autoregressive	ADJ
cet-6362	21	20	(	(	PUNCT
cet-6362	21	21	var	var	NOUN
cet-6362	21	22	)	)	PUNCT
cet-6362	21	23	model	model	NOUN
cet-6362	21	24	for	for	ADP
cet-6362	21	25	multivariate	multivariate	NOUN
cet-6362	21	26	time	time	NOUN
cet-6362	21	27	series	series	PROPN
cet-6362	21	28	,	,	PUNCT
cet-6362	21	29	adapted	adapt	VERB
cet-6362	21	30	to	to	ADP
cet-6362	21	31	interval	interval	NOUN
cet-6362	21	32	time	time	NOUN
cet-6362	21	33	series	series	PROPN
cet-6362	21	34	(	(	PUNCT
cet-6362	21	35	its	its	PRON
cet-6362	21	36	)	)	PUNCT
cet-6362	21	37	,	,	PUNCT
cet-6362	21	38	in	in	ADP
cet-6362	21	39	order	order	NOUN
cet-6362	21	40	to	to	PART
cet-6362	21	41	forecast	forecast	VERB
cet-6362	21	42	the	the	DET
cet-6362	21	43	monthly	monthly	ADJ
cet-6362	21	44	electric	electric	ADJ
cet-6362	21	45	power	power	NOUN
cet-6362	21	46	demand	demand	NOUN
cet-6362	21	47	per	per	ADP
cet-6362	21	48	hour	hour	NOUN
cet-6362	21	49	in	in	ADP
cet-6362	21	50	spain	spain	PROPN
cet-6362	21	51	from	from	ADP
cet-6362	21	52	2006	2006	NUM
cet-6362	21	53	to	to	ADP
cet-6362	21	54	2007	2007	NUM
cet-6362	21	55	.	.	PUNCT
cet-6362	22	1	doi	doi	NOUN
cet-6362	22	2	:	:	PUNCT
cet-6362	22	3	10.3303	10.3303	NUM
cet-6362	22	4	/	/	SYM
cet-6362	22	5	cet1333155	cet1333155	NOUN
cet-6362	22	6	please	please	INTJ
cet-6362	22	7	cite	cite	VERB
cet-6362	22	8	this	this	DET
cet-6362	22	9	article	article	NOUN
cet-6362	22	10	as	as	ADP
cet-6362	22	11	:	:	PUNCT
cet-6362	22	12	ak	ak	PROPN
cet-6362	22	13	r.	r.	PROPN
cet-6362	22	14	,	,	PUNCT
cet-6362	22	15	li	li	PROPN
cet-6362	22	16	y.	y.	PROPN
cet-6362	22	17	,	,	PUNCT
cet-6362	22	18	vitelli	vitelli	PROPN
cet-6362	22	19	v.	v.	PROPN
cet-6362	22	20	,	,	PUNCT
cet-6362	22	21	zio	zio	PROPN
cet-6362	22	22	e.	e.	PROPN
cet-6362	22	23	,	,	PUNCT
cet-6362	22	24	2013	2013	NUM
cet-6362	22	25	,	,	PUNCT
cet-6362	22	26	a	a	DET
cet-6362	22	27	genetic	genetic	ADJ
cet-6362	22	28	algorithm	algorithm	NOUN
cet-6362	22	29	and	and	CCONJ
cet-6362	22	30	neural	neural	ADJ
cet-6362	22	31	network	network	NOUN
cet-6362	22	32	technique	technique	NOUN
cet-6362	22	33	for	for	ADP
cet-6362	22	34	predicting	predict	VERB
cet-6362	22	35	wind	wind	NOUN
cet-6362	22	36	power	power	NOUN
cet-6362	22	37	under	under	ADP
cet-6362	22	38	uncertainty	uncertainty	NOUN
cet-6362	22	39	,	,	PUNCT
cet-6362	22	40	chemical	chemical	NOUN
cet-6362	22	41	engineering	engineering	NOUN
cet-6362	22	42	transactions	transaction	NOUN
cet-6362	22	43	,	,	PUNCT
cet-6362	22	44	33	33	NUM
cet-6362	22	45	,	,	PUNCT
cet-6362	22	46	925	925	NUM
cet-6362	22	47	-	-	SYM
cet-6362	22	48	930	930	NUM
cet-6362	22	49	doi	doi	NOUN
cet-6362	22	50	:	:	PUNCT
cet-6362	22	51	10.3303	10.3303	NUM
cet-6362	22	52	/	/	SYM
cet-6362	22	53	cet1333155	cet1333155	NOUN
cet-6362	22	54	925	925	NUM
cet-6362	22	55	this	this	DET
cet-6362	22	56	work	work	NOUN
cet-6362	22	57	aims	aim	VERB
cet-6362	22	58	at	at	ADP
cet-6362	22	59	doing	do	VERB
cet-6362	22	60	short	short	ADJ
cet-6362	22	61	-	-	PUNCT
cet-6362	22	62	term	term	NOUN
cet-6362	22	63	(	(	PUNCT
cet-6362	22	64	1	1	NUM
cet-6362	22	65	-	-	PUNCT
cet-6362	22	66	hour	hour	NOUN
cet-6362	22	67	ahead	ahead	ADV
cet-6362	22	68	)	)	PUNCT
cet-6362	22	69	wind	wind	NOUN
cet-6362	22	70	power	power	NOUN
cet-6362	22	71	prediction	prediction	NOUN
cet-6362	22	72	taking	take	VERB
cet-6362	22	73	into	into	ADP
cet-6362	22	74	account	account	NOUN
cet-6362	22	75	both	both	DET
cet-6362	22	76	the	the	DET
cet-6362	22	77	variability	variability	NOUN
cet-6362	22	78	in	in	ADP
cet-6362	22	79	the	the	DET
cet-6362	22	80	input	input	NOUN
cet-6362	22	81	and	and	CCONJ
cet-6362	22	82	the	the	DET
cet-6362	22	83	uncertainty	uncertainty	NOUN
cet-6362	22	84	in	in	ADP
cet-6362	22	85	the	the	DET
cet-6362	22	86	model	model	NOUN
cet-6362	22	87	structure	structure	NOUN
cet-6362	22	88	(	(	PUNCT
cet-6362	22	89	pandya	pandya	PROPN
cet-6362	22	90	et	et	PROPN
cet-6362	22	91	al	al	PROPN
cet-6362	22	92	.	.	PROPN
cet-6362	22	93	,	,	PUNCT
cet-6362	22	94	2013	2013	NUM
cet-6362	22	95	)	)	PUNCT
cet-6362	22	96	.	.	PUNCT
cet-6362	23	1	with	with	ADP
cet-6362	23	2	the	the	DET
cet-6362	23	3	purpose	purpose	NOUN
cet-6362	23	4	of	of	ADP
cet-6362	23	5	exploring	explore	VERB
cet-6362	23	6	the	the	DET
cet-6362	23	7	effects	effect	NOUN
cet-6362	23	8	of	of	ADP
cet-6362	23	9	using	use	VERB
cet-6362	23	10	interval	interval	NOUN
cet-6362	23	11	-	-	PUNCT
cet-6362	23	12	input	input	NOUN
cet-6362	23	13	wind	wind	NOUN
cet-6362	23	14	power	power	NOUN
cet-6362	23	15	data	datum	NOUN
cet-6362	23	16	on	on	ADP
cet-6362	23	17	the	the	DET
cet-6362	23	18	prediction	prediction	NOUN
cet-6362	23	19	accuracy	accuracy	NOUN
cet-6362	23	20	and	and	CCONJ
cet-6362	23	21	robustness	robustness	NOUN
cet-6362	23	22	,	,	PUNCT
cet-6362	23	23	uncertainty	uncertainty	NOUN
cet-6362	23	24	in	in	ADP
cet-6362	23	25	the	the	DET
cet-6362	23	26	input	input	NOUN
cet-6362	23	27	(	(	PUNCT
cet-6362	23	28	hourly	hourly	ADJ
cet-6362	23	29	wind	wind	NOUN
cet-6362	23	30	power	power	NOUN
cet-6362	23	31	)	)	PUNCT
cet-6362	23	32	is	be	AUX
cet-6362	23	33	represented	represent	VERB
cet-6362	23	34	by	by	ADP
cet-6362	23	35	an	an	DET
cet-6362	23	36	interval	interval	NOUN
cet-6362	23	37	which	which	PRON
cet-6362	23	38	captures	capture	VERB
cet-6362	23	39	the	the	DET
cet-6362	23	40	within	within	ADJ
cet-6362	23	41	-	-	PUNCT
cet-6362	23	42	hour	hour	NOUN
cet-6362	23	43	variability	variability	NOUN
cet-6362	23	44	.	.	PUNCT
cet-6362	24	1	unlike	unlike	ADP
cet-6362	24	2	the	the	DET
cet-6362	24	3	existing	exist	VERB
cet-6362	24	4	papers	paper	NOUN
cet-6362	24	5	on	on	ADP
cet-6362	24	6	wind	wind	NOUN
cet-6362	24	7	speed	speed	NOUN
cet-6362	24	8	and	and	CCONJ
cet-6362	24	9	power	power	NOUN
cet-6362	24	10	prediction	prediction	NOUN
cet-6362	24	11	,	,	PUNCT
cet-6362	24	12	which	which	PRON
cet-6362	24	13	use	use	VERB
cet-6362	24	14	single	single	ADV
cet-6362	24	15	-	-	PUNCT
cet-6362	24	16	valued	value	VERB
cet-6362	24	17	hourly	hourly	ADJ
cet-6362	24	18	wind	wind	NOUN
cet-6362	24	19	power	power	NOUN
cet-6362	24	20	input	input	NOUN
cet-6362	24	21	(	(	PUNCT
cet-6362	24	22	kusiak	kusiak	PROPN
cet-6362	24	23	et	et	PROPN
cet-6362	24	24	al	al	PROPN
cet-6362	24	25	.	.	PROPN
cet-6362	24	26	,	,	PUNCT
cet-6362	24	27	2009	2009	NUM
cet-6362	24	28	)	)	PUNCT
cet-6362	24	29	obtained	obtain	VERB
cet-6362	24	30	as	as	ADP
cet-6362	24	31	a	a	DET
cet-6362	24	32	within	within	ADP
cet-6362	24	33	-	-	PUNCT
cet-6362	24	34	hour	hour	NOUN
cet-6362	24	35	average	average	NOUN
cet-6362	24	36	,	,	PUNCT
cet-6362	24	37	we	we	PRON
cet-6362	24	38	give	give	VERB
cet-6362	24	39	an	an	DET
cet-6362	24	40	interval	interval	NOUN
cet-6362	24	41	representation	representation	NOUN
cet-6362	24	42	to	to	ADP
cet-6362	24	43	the	the	DET
cet-6362	24	44	hourly	hourly	ADJ
cet-6362	24	45	inputs	input	NOUN
cet-6362	24	46	by	by	ADP
cet-6362	24	47	using	use	VERB
cet-6362	24	48	two	two	NUM
cet-6362	24	49	approaches	approach	NOUN
cet-6362	24	50	(	(	PUNCT
cet-6362	24	51	see	see	VERB
cet-6362	24	52	section	section	NOUN
cet-6362	24	53	4	4	NUM
cet-6362	24	54	)	)	PUNCT
cet-6362	24	55	,	,	PUNCT
cet-6362	24	56	which	which	PRON
cet-6362	24	57	quantify	quantify	VERB
cet-6362	24	58	in	in	ADP
cet-6362	24	59	two	two	NUM
cet-6362	24	60	different	different	ADJ
cet-6362	24	61	ways	way	NOUN
cet-6362	24	62	the	the	DET
cet-6362	24	63	within	within	ADP
cet-6362	24	64	-	-	PUNCT
cet-6362	24	65	hour	hour	NOUN
cet-6362	24	66	variability	variability	NOUN
cet-6362	24	67	.	.	PUNCT
cet-6362	25	1	to	to	PART
cet-6362	25	2	tackle	tackle	VERB
cet-6362	25	3	the	the	DET
cet-6362	25	4	prediction	prediction	NOUN
cet-6362	25	5	problem	problem	NOUN
cet-6362	25	6	,	,	PUNCT
cet-6362	25	7	a	a	DET
cet-6362	25	8	data	data	NOUN
cet-6362	25	9	-	-	PUNCT
cet-6362	25	10	driven	drive	VERB
cet-6362	25	11	learning	learning	NOUN
cet-6362	25	12	approach	approach	NOUN
cet-6362	25	13	is	be	AUX
cet-6362	25	14	used	use	VERB
cet-6362	25	15	,	,	PUNCT
cet-6362	25	16	i.e.	i.e.	X
cet-6362	25	17	a	a	DET
cet-6362	25	18	neural	neural	ADJ
cet-6362	25	19	network	network	NOUN
cet-6362	25	20	(	(	PUNCT
cet-6362	25	21	nn	nn	NOUN
cet-6362	25	22	)	)	PUNCT
cet-6362	25	23	trained	train	VERB
cet-6362	25	24	on	on	ADP
cet-6362	25	25	the	the	DET
cet-6362	25	26	basis	basis	NOUN
cet-6362	25	27	of	of	ADP
cet-6362	25	28	experimental	experimental	ADJ
cet-6362	25	29	data	datum	NOUN
cet-6362	25	30	(	(	PUNCT
cet-6362	25	31	historical	historical	ADJ
cet-6362	25	32	wind	wind	NOUN
cet-6362	25	33	power	power	NOUN
cet-6362	25	34	data	datum	NOUN
cet-6362	25	35	with	with	ADP
cet-6362	25	36	a	a	DET
cet-6362	25	37	time	time	NOUN
cet-6362	25	38	-	-	PUNCT
cet-6362	25	39	step	step	NOUN
cet-6362	25	40	of	of	ADP
cet-6362	25	41	5	5	NUM
cet-6362	25	42	min	min	NOUN
cet-6362	25	43	)	)	PUNCT
cet-6362	25	44	.	.	PUNCT
cet-6362	26	1	the	the	DET
cet-6362	26	2	network	network	NOUN
cet-6362	26	3	uses	use	VERB
cet-6362	26	4	interval	interval	NOUN
cet-6362	26	5	-	-	PUNCT
cet-6362	26	6	valued	value	VERB
cet-6362	26	7	data	datum	NOUN
cet-6362	26	8	but	but	CCONJ
cet-6362	26	9	its	its	PRON
cet-6362	26	10	weights	weight	NOUN
cet-6362	26	11	and	and	CCONJ
cet-6362	26	12	biases	bias	NOUN
cet-6362	26	13	are	be	AUX
cet-6362	26	14	crisp	crisp	ADJ
cet-6362	26	15	(	(	PUNCT
cet-6362	26	16	i.e.	i.e.	X
cet-6362	26	17	single	single	ADV
cet-6362	26	18	-	-	PUNCT
cet-6362	26	19	valued	value	VERB
cet-6362	26	20	)	)	PUNCT
cet-6362	26	21	.	.	PUNCT
cet-6362	27	1	for	for	ADP
cet-6362	27	2	the	the	DET
cet-6362	27	3	training	training	NOUN
cet-6362	27	4	of	of	ADP
cet-6362	27	5	the	the	DET
cet-6362	27	6	nn	nn	PROPN
cet-6362	27	7	,	,	PUNCT
cet-6362	27	8	we	we	PRON
cet-6362	27	9	implement	implement	VERB
cet-6362	27	10	a	a	DET
cet-6362	27	11	multi	multi	ADJ
cet-6362	27	12	-	-	ADJ
cet-6362	27	13	objective	objective	ADJ
cet-6362	27	14	genetic	genetic	ADJ
cet-6362	27	15	algorithm	algorithm	NOUN
cet-6362	27	16	(	(	PUNCT
cet-6362	27	17	namely	namely	ADV
cet-6362	27	18	,	,	PUNCT
cet-6362	27	19	non	non	ADJ
cet-6362	27	20	-	-	ADJ
cet-6362	27	21	dominated	dominated	ADJ
cet-6362	27	22	sorting	sort	VERB
cet-6362	27	23	genetic	genetic	ADJ
cet-6362	27	24	algorithm	algorithm	NOUN
cet-6362	27	25	–	–	PUNCT
cet-6362	27	26	ii	ii	PROPN
cet-6362	27	27	(	(	PUNCT
cet-6362	27	28	nsga	nsga	NOUN
cet-6362	27	29	-	-	PUNCT
cet-6362	27	30	ii	ii	NOUN
cet-6362	27	31	)	)	PUNCT
cet-6362	27	32	)	)	PUNCT
cet-6362	27	33	to	to	PART
cet-6362	27	34	find	find	VERB
cet-6362	27	35	the	the	DET
cet-6362	27	36	optimal	optimal	ADJ
cet-6362	27	37	parameters	parameter	NOUN
cet-6362	27	38	(	(	PUNCT
cet-6362	27	39	weights	weight	NOUN
cet-6362	27	40	and	and	CCONJ
cet-6362	27	41	biases	bias	NOUN
cet-6362	27	42	)	)	PUNCT
cet-6362	27	43	of	of	ADP
cet-6362	27	44	the	the	DET
cet-6362	27	45	nn	nn	PROPN
cet-6362	27	46	.	.	PROPN
cet-6362	27	47	the	the	DET
cet-6362	27	48	network	network	NOUN
cet-6362	27	49	maps	map	VERB
cet-6362	27	50	interval	interval	NOUN
cet-6362	27	51	-	-	PUNCT
cet-6362	27	52	valued	value	VERB
cet-6362	27	53	data	datum	NOUN
cet-6362	27	54	into	into	ADP
cet-6362	27	55	an	an	DET
cet-6362	27	56	interval	interval	NOUN
cet-6362	27	57	output	output	NOUN
cet-6362	27	58	,	,	PUNCT
cet-6362	27	59	providing	provide	VERB
cet-6362	27	60	the	the	DET
cet-6362	27	61	prediction	prediction	NOUN
cet-6362	27	62	intervals	interval	NOUN
cet-6362	27	63	(	(	PUNCT
cet-6362	27	64	pis	pis	NOUN
cet-6362	27	65	)	)	PUNCT
cet-6362	27	66	of	of	ADP
cet-6362	27	67	the	the	DET
cet-6362	27	68	wind	wind	NOUN
cet-6362	27	69	power	power	NOUN
cet-6362	27	70	.	.	PUNCT
cet-6362	28	1	the	the	DET
cet-6362	28	2	pis	pis	NOUN
cet-6362	28	3	are	be	AUX
cet-6362	28	4	optimized	optimize	VERB
cet-6362	28	5	both	both	CCONJ
cet-6362	28	6	in	in	ADP
cet-6362	28	7	terms	term	NOUN
cet-6362	28	8	of	of	ADP
cet-6362	28	9	accuracy	accuracy	NOUN
cet-6362	28	10	(	(	PUNCT
cet-6362	28	11	coverage	coverage	NOUN
cet-6362	28	12	probability	probability	NOUN
cet-6362	28	13	)	)	PUNCT
cet-6362	28	14	and	and	CCONJ
cet-6362	28	15	dimension	dimension	NOUN
cet-6362	28	16	(	(	PUNCT
cet-6362	28	17	width	width	NOUN
cet-6362	28	18	)	)	PUNCT
cet-6362	28	19	.	.	PUNCT
cet-6362	29	1	the	the	DET
cet-6362	29	2	prediction	prediction	NOUN
cet-6362	29	3	interval	interval	NOUN
cet-6362	29	4	coverage	coverage	NOUN
cet-6362	29	5	probability	probability	NOUN
cet-6362	29	6	(	(	PUNCT
cet-6362	29	7	picp	picp	NOUN
cet-6362	29	8	)	)	PUNCT
cet-6362	29	9	represents	represent	VERB
cet-6362	29	10	the	the	DET
cet-6362	29	11	probability	probability	NOUN
cet-6362	29	12	that	that	SCONJ
cet-6362	29	13	the	the	DET
cet-6362	29	14	set	set	NOUN
cet-6362	29	15	of	of	ADP
cet-6362	29	16	estimated	estimate	VERB
cet-6362	29	17	pi	pi	NOUN
cet-6362	29	18	values	value	NOUN
cet-6362	29	19	will	will	AUX
cet-6362	29	20	contain	contain	VERB
cet-6362	29	21	a	a	DET
cet-6362	29	22	certain	certain	ADJ
cet-6362	29	23	percentage	percentage	NOUN
cet-6362	29	24	of	of	ADP
cet-6362	29	25	the	the	DET
cet-6362	29	26	true	true	ADJ
cet-6362	29	27	output	output	NOUN
cet-6362	29	28	values	value	NOUN
cet-6362	29	29	.	.	PUNCT
cet-6362	30	1	prediction	prediction	NOUN
cet-6362	30	2	interval	interval	NOUN
cet-6362	30	3	width	width	NOUN
cet-6362	30	4	(	(	PUNCT
cet-6362	30	5	piw	piw	PROPN
cet-6362	30	6	)	)	PUNCT
cet-6362	30	7	simply	simply	ADV
cet-6362	30	8	measures	measure	VERB
cet-6362	30	9	the	the	DET
cet-6362	30	10	extension	extension	NOUN
cet-6362	30	11	of	of	ADP
cet-6362	30	12	the	the	DET
cet-6362	30	13	interval	interval	NOUN
cet-6362	30	14	as	as	ADP
cet-6362	30	15	the	the	DET
cet-6362	30	16	difference	difference	NOUN
cet-6362	30	17	of	of	ADP
cet-6362	30	18	the	the	DET
cet-6362	30	19	estimated	estimate	VERB
cet-6362	30	20	upper	upper	ADJ
cet-6362	30	21	bound	bind	VERB
cet-6362	30	22	and	and	CCONJ
cet-6362	30	23	lower	low	ADJ
cet-6362	30	24	bound	bound	ADJ
cet-6362	30	25	values	value	NOUN
cet-6362	30	26	.	.	PUNCT
cet-6362	31	1	the	the	DET
cet-6362	31	2	paper	paper	NOUN
cet-6362	31	3	is	be	AUX
cet-6362	31	4	organized	organize	VERB
cet-6362	31	5	as	as	SCONJ
cet-6362	31	6	follows	follow	VERB
cet-6362	31	7	.	.	PUNCT
cet-6362	32	1	section	section	NOUN
cet-6362	32	2	2	2	NUM
cet-6362	32	3	briefly	briefly	NOUN
cet-6362	32	4	introduces	introduce	VERB
cet-6362	32	5	the	the	DET
cet-6362	32	6	basic	basic	ADJ
cet-6362	32	7	concepts	concept	NOUN
cet-6362	32	8	of	of	ADP
cet-6362	32	9	interval	interval	NOUN
cet-6362	32	10	-	-	PUNCT
cet-6362	32	11	valued	value	VERB
cet-6362	32	12	nns	nn	NOUN
cet-6362	32	13	for	for	ADP
cet-6362	32	14	pis	pis	NOUN
cet-6362	32	15	estimation	estimation	NOUN
cet-6362	32	16	.	.	PUNCT
cet-6362	33	1	in	in	ADP
cet-6362	33	2	section	section	NOUN
cet-6362	33	3	3	3	NUM
cet-6362	33	4	,	,	PUNCT
cet-6362	33	5	the	the	DET
cet-6362	33	6	use	use	NOUN
cet-6362	33	7	of	of	ADP
cet-6362	33	8	nsga	nsga	NOUN
cet-6362	33	9	-	-	PUNCT
cet-6362	33	10	ii	ii	NOUN
cet-6362	33	11	for	for	ADP
cet-6362	33	12	training	train	VERB
cet-6362	33	13	an	an	DET
cet-6362	33	14	interval	interval	NOUN
cet-6362	33	15	-	-	PUNCT
cet-6362	33	16	valued	value	VERB
cet-6362	33	17	nn	nn	NOUN
cet-6362	33	18	to	to	PART
cet-6362	33	19	estimate	estimate	VERB
cet-6362	33	20	pis	pis	PROPN
cet-6362	33	21	is	be	AUX
cet-6362	33	22	described	describe	VERB
cet-6362	33	23	.	.	PUNCT
cet-6362	34	1	experimental	experimental	ADJ
cet-6362	34	2	results	result	NOUN
cet-6362	34	3	on	on	ADP
cet-6362	34	4	the	the	DET
cet-6362	34	5	real	real	ADJ
cet-6362	34	6	case	case	NOUN
cet-6362	34	7	study	study	NOUN
cet-6362	34	8	of	of	ADP
cet-6362	34	9	short	short	ADJ
cet-6362	34	10	-	-	PUNCT
cet-6362	34	11	term	term	NOUN
cet-6362	34	12	wind	wind	NOUN
cet-6362	34	13	power	power	NOUN
cet-6362	34	14	prediction	prediction	NOUN
cet-6362	34	15	are	be	AUX
cet-6362	34	16	given	give	VERB
cet-6362	34	17	in	in	ADP
cet-6362	34	18	section	section	NOUN
cet-6362	34	19	4	4	NUM
cet-6362	34	20	.	.	PUNCT
cet-6362	35	1	finally	finally	ADV
cet-6362	35	2	,	,	PUNCT
cet-6362	35	3	section	section	NOUN
cet-6362	35	4	5	5	NUM
cet-6362	35	5	concludes	conclude	VERB
cet-6362	35	6	the	the	DET
cet-6362	35	7	paper	paper	NOUN
cet-6362	35	8	with	with	ADP
cet-6362	35	9	an	an	DET
cet-6362	35	10	analysis	analysis	NOUN
cet-6362	35	11	of	of	ADP
cet-6362	35	12	the	the	DET
cet-6362	35	13	results	result	NOUN
cet-6362	35	14	obtained	obtain	VERB
cet-6362	35	15	and	and	CCONJ
cet-6362	35	16	some	some	DET
cet-6362	35	17	ideas	idea	NOUN
cet-6362	35	18	for	for	ADP
cet-6362	35	19	future	future	ADJ
cet-6362	35	20	improvements	improvement	NOUN
cet-6362	35	21	.	.	PUNCT
cet-6362	36	1	2	2	X
cet-6362	36	2	.	.	X
cet-6362	36	3	nns	nns	PROPN
cet-6362	36	4	and	and	CCONJ
cet-6362	36	5	pis	pis	PROPN
cet-6362	36	6	neural	neural	ADJ
cet-6362	36	7	networks	network	NOUN
cet-6362	36	8	(	(	PUNCT
cet-6362	36	9	nns	nn	NOUN
cet-6362	36	10	)	)	PUNCT
cet-6362	36	11	are	be	AUX
cet-6362	36	12	a	a	DET
cet-6362	36	13	promising	promising	ADJ
cet-6362	36	14	statistical	statistical	ADJ
cet-6362	36	15	data	data	NOUN
cet-6362	36	16	-	-	PUNCT
cet-6362	36	17	driven	drive	VERB
cet-6362	36	18	method	method	NOUN
cet-6362	36	19	capable	capable	ADJ
cet-6362	36	20	of	of	ADP
cet-6362	36	21	learning	learn	VERB
cet-6362	36	22	complex	complex	ADJ
cet-6362	36	23	nonlinear	nonlinear	ADJ
cet-6362	36	24	relationships	relationship	NOUN
cet-6362	36	25	among	among	ADP
cet-6362	36	26	variables	variable	NOUN
cet-6362	36	27	,	,	PUNCT
cet-6362	36	28	from	from	ADP
cet-6362	36	29	observed	observed	ADJ
cet-6362	36	30	data	datum	NOUN
cet-6362	36	31	.	.	PUNCT
cet-6362	37	1	a	a	DET
cet-6362	37	2	nn	nn	PROPN
cet-6362	37	3	is	be	AUX
cet-6362	37	4	an	an	DET
cet-6362	37	5	interconnected	interconnected	ADJ
cet-6362	37	6	assembly	assembly	NOUN
cet-6362	37	7	of	of	ADP
cet-6362	37	8	individual	individual	ADJ
cet-6362	37	9	processing	processing	NOUN
cet-6362	37	10	units	unit	NOUN
cet-6362	37	11	(	(	PUNCT
cet-6362	37	12	neurons	neuron	NOUN
cet-6362	37	13	)	)	PUNCT
cet-6362	37	14	.	.	PUNCT
cet-6362	38	1	information	information	NOUN
cet-6362	38	2	is	be	AUX
cet-6362	38	3	passed	pass	VERB
cet-6362	38	4	between	between	ADP
cet-6362	38	5	these	these	DET
cet-6362	38	6	units	unit	NOUN
cet-6362	38	7	along	along	ADP
cet-6362	38	8	interconnections	interconnection	NOUN
cet-6362	38	9	.	.	PUNCT
cet-6362	39	1	an	an	DET
cet-6362	39	2	incoming	incoming	ADJ
cet-6362	39	3	connection	connection	NOUN
cet-6362	39	4	has	have	VERB
cet-6362	39	5	two	two	NUM
cet-6362	39	6	values	value	NOUN
cet-6362	39	7	associated	associate	VERB
cet-6362	39	8	with	with	ADP
cet-6362	39	9	it	it	PRON
cet-6362	39	10	,	,	PUNCT
cet-6362	39	11	an	an	DET
cet-6362	39	12	input	input	NOUN
cet-6362	39	13	value	value	NOUN
cet-6362	39	14	and	and	CCONJ
cet-6362	39	15	a	a	DET
cet-6362	39	16	weight	weight	NOUN
cet-6362	39	17	(	(	PUNCT
cet-6362	39	18	kalogirou	kalogirou	NOUN
cet-6362	39	19	,	,	PUNCT
cet-6362	39	20	2001	2001	NUM
cet-6362	39	21	)	)	PUNCT
cet-6362	39	22	.	.	PUNCT
cet-6362	40	1	the	the	DET
cet-6362	40	2	neurons	neuron	NOUN
cet-6362	40	3	are	be	AUX
cet-6362	40	4	connected	connect	VERB
cet-6362	40	5	by	by	ADP
cet-6362	40	6	weights	weight	NOUN
cet-6362	40	7	and	and	CCONJ
cet-6362	40	8	convert	convert	VERB
cet-6362	40	9	input	input	NOUN
cet-6362	40	10	data	datum	NOUN
cet-6362	40	11	d	d	NOUN
cet-6362	40	12	=	=	PRON
cet-6362	40	13	{	{	PUNCT
cet-6362	40	14	(	(	PUNCT
cet-6362	40	15	xn	xn	PROPN
cet-6362	40	16	,	,	PUNCT
cet-6362	40	17	yn	yn	PROPN
cet-6362	40	18	n	n	NOUN
cet-6362	40	19	=	=	SYM
cet-6362	40	20	1	1	NUM
cet-6362	40	21	,	,	PUNCT
cet-6362	40	22	2	2	NUM
cet-6362	40	23	,	,	PUNCT
cet-6362	40	24	…	…	NUM
cet-6362	40	25	,	,	PUNCT
cet-6362	40	26	np	np	INTJ
cet-6362	40	27	}	}	PUNCT
cet-6362	40	28	into	into	ADP
cet-6362	40	29	output	output	NOUN
cet-6362	40	30	values	value	NOUN
cet-6362	40	31	by	by	ADP
cet-6362	40	32	using	use	VERB
cet-6362	40	33	a	a	DET
cet-6362	40	34	sigmoid	sigmoid	NOUN
cet-6362	40	35	transfer	transfer	NOUN
cet-6362	40	36	(	(	PUNCT
cet-6362	40	37	activation	activation	NOUN
cet-6362	40	38	)	)	PUNCT
cet-6362	40	39	function	function	NOUN
cet-6362	40	40	.	.	PUNCT
cet-6362	41	1	figure	figure	NOUN
cet-6362	41	2	1	1	NUM
cet-6362	41	3	shows	show	VERB
cet-6362	41	4	the	the	DET
cet-6362	41	5	scheme	scheme	NOUN
cet-6362	41	6	of	of	ADP
cet-6362	41	7	a	a	DET
cet-6362	41	8	multiple	multiple	ADJ
cet-6362	41	9	-	-	PUNCT
cet-6362	41	10	input	input	NOUN
cet-6362	41	11	neuron	neuron	NOUN
cet-6362	41	12	with	with	ADP
cet-6362	41	13	the	the	DET
cet-6362	41	14	associated	associated	ADJ
cet-6362	41	15	information	information	NOUN
cet-6362	41	16	processing	process	VERB
cet-6362	41	17	through	through	ADP
cet-6362	41	18	this	this	DET
cet-6362	41	19	neuron	neuron	NOUN
cet-6362	41	20	.	.	PUNCT
cet-6362	42	1	figure	figure	VERB
cet-6362	42	2	1	1	NUM
cet-6362	42	3	:	:	PUNCT
cet-6362	42	4	multiple	multiple	ADJ
cet-6362	42	5	input	input	NOUN
cet-6362	42	6	neuron	neuron	NOUN
cet-6362	42	7	(	(	PUNCT
cet-6362	42	8	nazzal	nazzal	PROPN
cet-6362	42	9	et	et	PROPN
cet-6362	42	10	al	al	PROPN
cet-6362	42	11	.	.	PROPN
cet-6362	42	12	,	,	PUNCT
cet-6362	42	13	2008	2008	NUM
cet-6362	42	14	)	)	PUNCT
cet-6362	42	15	a	a	DET
cet-6362	42	16	pi	pi	NOUN
cet-6362	42	17	is	be	AUX
cet-6362	42	18	defined	define	VERB
cet-6362	42	19	by	by	ADP
cet-6362	42	20	upper	upper	ADJ
cet-6362	42	21	and	and	CCONJ
cet-6362	42	22	lower	low	ADJ
cet-6362	42	23	bounds	bound	NOUN
cet-6362	42	24	that	that	PRON
cet-6362	42	25	include	include	VERB
cet-6362	42	26	a	a	DET
cet-6362	42	27	future	future	ADJ
cet-6362	42	28	unknown	unknown	ADJ
cet-6362	42	29	value	value	NOUN
cet-6362	42	30	with	with	ADP
cet-6362	42	31	a	a	DET
cet-6362	42	32	predetermined	predetermine	VERB
cet-6362	42	33	probability	probability	NOUN
cet-6362	42	34	,	,	PUNCT
cet-6362	42	35	called	call	VERB
cet-6362	42	36	confidence	confidence	NOUN
cet-6362	42	37	level	level	NOUN
cet-6362	42	38	(	(	PUNCT
cet-6362	42	39	1	1	NUM
cet-6362	42	40	)	)	PUNCT
cet-6362	42	41	.	.	PUNCT
cet-6362	43	1	the	the	DET
cet-6362	43	2	formal	formal	ADJ
cet-6362	43	3	definition	definition	NOUN
cet-6362	43	4	of	of	ADP
cet-6362	43	5	a	a	DET
cet-6362	43	6	pi	pi	NOUN
cet-6362	43	7	with	with	ADP
cet-6362	43	8	crisp	crisp	ADJ
cet-6362	43	9	data	datum	NOUN
cet-6362	43	10	can	can	AUX
cet-6362	43	11	be	be	AUX
cet-6362	43	12	presented	present	VERB
cet-6362	43	13	as	as	SCONJ
cet-6362	43	14	follows	follow	VERB
cet-6362	43	15	:	:	PUNCT
cet-6362	43	16	pr	pr	NOUN
cet-6362	43	17	y-(x	y-(x	NUM
cet-6362	43	18	)	)	PUNCT
cet-6362	43	19	<	<	X
cet-6362	44	1	y	y	PROPN
cet-6362	44	2	x	x	PROPN
cet-6362	44	3	)	)	PUNCT
cet-6362	44	4	<	<	X
cet-6362	44	5	y+(x	y+(x	PROPN
cet-6362	44	6	)	)	PUNCT
cet-6362	44	7	=	=	SYM
cet-6362	44	8	1	1	NUM
cet-6362	44	9	(	(	PUNCT
cet-6362	44	10	1	1	NUM
cet-6362	44	11	)	)	PUNCT
cet-6362	44	12	where	where	SCONJ
cet-6362	44	13	y-(x	y-(x	NUM
cet-6362	44	14	)	)	PUNCT
cet-6362	44	15	and	and	CCONJ
cet-6362	44	16	y+(x	y+(x	NUM
cet-6362	44	17	)	)	PUNCT
cet-6362	44	18	are	be	AUX
cet-6362	44	19	the	the	DET
cet-6362	44	20	estimated	estimate	VERB
cet-6362	44	21	lower	low	ADJ
cet-6362	44	22	and	and	CCONJ
cet-6362	44	23	upper	upper	ADJ
cet-6362	44	24	bounds	bound	NOUN
cet-6362	44	25	corresponding	correspond	VERB
cet-6362	44	26	to	to	ADP
cet-6362	44	27	input	input	NOUN
cet-6362	44	28	x	x	ADP
cet-6362	44	29	;	;	PUNCT
cet-6362	44	30	the	the	DET
cet-6362	44	31	confidence	confidence	NOUN
cet-6362	44	32	level	level	NOUN
cet-6362	44	33	(	(	PUNCT
cet-6362	44	34	1	1	NUM
cet-6362	44	35	)	)	PUNCT
cet-6362	44	36	refers	refer	VERB
cet-6362	44	37	to	to	ADP
cet-6362	44	38	the	the	DET
cet-6362	44	39	expected	expect	VERB
cet-6362	44	40	probability	probability	NOUN
cet-6362	44	41	that	that	SCONJ
cet-6362	44	42	the	the	DET
cet-6362	44	43	true	true	ADJ
cet-6362	44	44	value	value	NOUN
cet-6362	44	45	of	of	ADP
cet-6362	44	46	y(x	y(x	NOUN
cet-6362	44	47	)	)	PUNCT
cet-6362	44	48	lies	lie	VERB
cet-6362	44	49	within	within	ADP
cet-6362	44	50	the	the	DET
cet-6362	44	51	prediction	prediction	NOUN
cet-6362	44	52	interval	interval	NOUN
cet-6362	45	1	[	[	X
cet-6362	45	2	yx	yx	X
cet-6362	45	3	,	,	PUNCT
cet-6362	45	4	y+	y+	NUM
cet-6362	45	5	x	x	X
cet-6362	45	6	]	]	X
cet-6362	45	7	.	.	NOUN
cet-6362	45	8	1	1	NUM
cet-6362	45	9	w0j	w0j	NOUN
cet-6362	45	10	output	output	NOUN
cet-6362	45	11	(	(	PUNCT
cet-6362	45	12	y	y	NOUN
cet-6362	45	13	)	)	PUNCT
cet-6362	45	14	w1j	w1j	NOUN
cet-6362	45	15	wnj	wnj	VERB
cet-6362	45	16	x2	x2	PROPN
cet-6362	46	1	x1	x1	NUM
cet-6362	46	2	xn	xn	PROPN
cet-6362	47	1	fw2j	fw2j	PROPN
cet-6362	47	2	activation	activation	NOUN
cet-6362	47	3	function	function	VERB
cet-6362	47	4	926	926	NUM
cet-6362	47	5	when	when	SCONJ
cet-6362	47	6	interval	interval	NOUN
cet-6362	47	7	-	-	PUNCT
cet-6362	47	8	valued	value	VERB
cet-6362	47	9	data	datum	NOUN
cet-6362	47	10	are	be	AUX
cet-6362	47	11	used	use	VERB
cet-6362	47	12	as	as	ADP
cet-6362	47	13	input	input	NOUN
cet-6362	47	14	,	,	PUNCT
cet-6362	47	15	each	each	DET
cet-6362	47	16	input	input	NOUN
cet-6362	47	17	pattern	pattern	NOUN
cet-6362	47	18	xi	xi	ADP
cet-6362	47	19	is	be	AUX
cet-6362	47	20	represented	represent	VERB
cet-6362	47	21	as	as	ADP
cet-6362	47	22	an	an	DET
cet-6362	47	23	interval	interval	NOUN
cet-6362	47	24	xi	xi	PUNCT
cet-6362	48	1	=	=	PUNCT
cet-6362	49	1	[	[	X
cet-6362	49	2	xi	xi	X
cet-6362	49	3	-	-	INTJ
cet-6362	49	4	,	,	PUNCT
cet-6362	49	5	xi	xi	PUNCT
cet-6362	50	1	+	+	NOUN
cet-6362	50	2	]	]	X
cet-6362	50	3	where	where	SCONJ
cet-6362	50	4	xi	xi	PROPN
cet-6362	50	5	xi	xi	PROPN
cet-6362	51	1	+	+	CCONJ
cet-6362	51	2	are	be	AUX
cet-6362	51	3	the	the	DET
cet-6362	51	4	lower	low	ADJ
cet-6362	51	5	and	and	CCONJ
cet-6362	51	6	upper	upper	ADJ
cet-6362	51	7	bounds	bound	NOUN
cet-6362	51	8	(	(	PUNCT
cet-6362	51	9	real	real	ADJ
cet-6362	51	10	values	value	NOUN
cet-6362	51	11	)	)	PUNCT
cet-6362	51	12	of	of	ADP
cet-6362	51	13	the	the	DET
cet-6362	51	14	input	input	NOUN
cet-6362	51	15	interval	interval	NOUN
cet-6362	51	16	,	,	PUNCT
cet-6362	51	17	respectively	respectively	ADV
cet-6362	51	18	.	.	PUNCT
cet-6362	52	1	with	with	ADP
cet-6362	52	2	the	the	DET
cet-6362	52	3	same	same	ADJ
cet-6362	52	4	formulation	formulation	NOUN
cet-6362	52	5	,	,	PUNCT
cet-6362	52	6	it	it	PRON
cet-6362	52	7	is	be	AUX
cet-6362	52	8	natural	natural	ADJ
cet-6362	52	9	to	to	PART
cet-6362	52	10	describe	describe	VERB
cet-6362	52	11	each	each	DET
cet-6362	52	12	estimated	estimate	VERB
cet-6362	52	13	output	output	NOUN
cet-6362	52	14	value	value	NOUN
cet-6362	52	15	yi	yi	PROPN
cet-6362	52	16	,	,	PUNCT
cet-6362	52	17	corresponding	correspond	VERB
cet-6362	52	18	to	to	ADP
cet-6362	52	19	the	the	DET
cet-6362	52	20	i	i	PROPN
cet-6362	52	21	-	-	PUNCT
cet-6362	52	22	th	th	X
cet-6362	52	23	sample	sample	NOUN
cet-6362	52	24	xi	xi	PROPN
cet-6362	52	25	,	,	PUNCT
cet-6362	52	26	as	as	ADP
cet-6362	52	27	yi	yi	NOUN
cet-6362	52	28	=	=	PUNCT
cet-6362	53	1	[	[	X
cet-6362	53	2	yi	yi	NOUN
cet-6362	53	3	-	-	PUNCT
cet-6362	53	4	,	,	PUNCT
cet-6362	53	5	yi	yi	X
cet-6362	54	1	+	+	NOUN
cet-6362	54	2	]	]	X
cet-6362	54	3	,	,	PUNCT
cet-6362	54	4	where	where	SCONJ
cet-6362	54	5	yi	yi	PROPN
cet-6362	54	6	yi	yi	PROPN
cet-6362	54	7	+	+	CCONJ
cet-6362	54	8	are	be	AUX
cet-6362	54	9	,	,	PUNCT
cet-6362	54	10	respectively	respectively	ADV
cet-6362	54	11	,	,	PUNCT
cet-6362	54	12	the	the	DET
cet-6362	54	13	estimated	estimate	VERB
cet-6362	54	14	lower	low	ADJ
cet-6362	54	15	and	and	CCONJ
cet-6362	54	16	upper	upper	ADJ
cet-6362	54	17	bounds	bound	NOUN
cet-6362	54	18	of	of	ADP
cet-6362	54	19	the	the	DET
cet-6362	54	20	prediction	prediction	NOUN
cet-6362	54	21	interval	interval	NOUN
cet-6362	54	22	in	in	ADP
cet-6362	54	23	output	output	NOUN
cet-6362	54	24	.	.	PUNCT
cet-6362	55	1	the	the	DET
cet-6362	55	2	mathematical	mathematical	ADJ
cet-6362	55	3	formulation	formulation	NOUN
cet-6362	55	4	of	of	ADP
cet-6362	55	5	the	the	DET
cet-6362	55	6	picp	picp	PROPN
cet-6362	55	7	and	and	CCONJ
cet-6362	55	8	piw	piw	PROPN
cet-6362	55	9	measures	measure	NOUN
cet-6362	55	10	has	have	AUX
cet-6362	55	11	been	be	AUX
cet-6362	55	12	given	give	VERB
cet-6362	55	13	in	in	ADP
cet-6362	55	14	khosravi	khosravi	NOUN
cet-6362	55	15	et	et	PROPN
cet-6362	55	16	al	al	PROPN
cet-6362	55	17	.	.	PUNCT
cet-6362	56	1	(	(	PUNCT
cet-6362	56	2	2011	2011	NUM
cet-6362	56	3	)	)	PUNCT
cet-6362	56	4	.	.	PUNCT
cet-6362	57	1	in	in	ADP
cet-6362	57	2	this	this	DET
cet-6362	57	3	work	work	NOUN
cet-6362	57	4	we	we	PRON
cet-6362	57	5	have	have	AUX
cet-6362	57	6	modified	modify	VERB
cet-6362	57	7	these	these	DET
cet-6362	57	8	two	two	NUM
cet-6362	57	9	measures	measure	NOUN
cet-6362	57	10	to	to	PART
cet-6362	57	11	adapt	adapt	VERB
cet-6362	57	12	them	they	PRON
cet-6362	57	13	to	to	ADP
cet-6362	57	14	interval	interval	NOUN
cet-6362	57	15	-	-	PUNCT
cet-6362	57	16	valued	value	VERB
cet-6362	57	17	input	input	NOUN
cet-6362	57	18	and	and	CCONJ
cet-6362	57	19	output	output	NOUN
cet-6362	57	20	data	datum	NOUN
cet-6362	57	21	:	:	PUNCT
cet-6362	57	22	picp	picp	NOUN
cet-6362	57	23	=	=	NOUN
cet-6362	57	24	1	1	NUM
cet-6362	57	25	np	np	INTJ
cet-6362	57	26	ci	ci	PROPN
cet-6362	57	27	np	np	INTJ
cet-6362	57	28	i=1	i=1	PROPN
cet-6362	57	29	(	(	PUNCT
cet-6362	57	30	2	2	NUM
cet-6362	57	31	)	)	PUNCT
cet-6362	57	32	where	where	SCONJ
cet-6362	57	33	np	np	PRON
cet-6362	57	34	is	be	AUX
cet-6362	57	35	the	the	DET
cet-6362	57	36	number	number	NOUN
cet-6362	57	37	of	of	ADP
cet-6362	57	38	samples	sample	NOUN
cet-6362	57	39	in	in	ADP
cet-6362	57	40	the	the	DET
cet-6362	57	41	training	training	NOUN
cet-6362	57	42	or	or	CCONJ
cet-6362	57	43	testing	testing	NOUN
cet-6362	57	44	sets	set	NOUN
cet-6362	57	45	,	,	PUNCT
cet-6362	57	46	and	and	CCONJ
cet-6362	57	47	ci	ci	NOUN
cet-6362	57	48	=	=	SYM
cet-6362	57	49	1	1	NUM
cet-6362	57	50	yi	yi	NOUN
cet-6362	58	1	[	[	X
cet-6362	58	2	yi	yi	PROPN
cet-6362	58	3	-	-	PUNCT
cet-6362	58	4	,	,	PUNCT
cet-6362	58	5	yi	yi	X
cet-6362	59	1	+	+	NOUN
cet-6362	59	2	]	]	X
cet-6362	59	3	diam(yi	diam(yi	ADJ
cet-6362	59	4	yi	yi	PROPN
cet-6362	59	5	)	)	PUNCT
cet-6362	59	6	diam(yi	diam(yi	PROPN
cet-6362	59	7	)	)	PUNCT
cet-6362	59	8	yi	yi	NOUN
cet-6362	60	1	[	[	X
cet-6362	60	2	yi	yi	PROPN
cet-6362	60	3	-	-	PUNCT
cet-6362	60	4	,	,	PUNCT
cet-6362	60	5	yi	yi	X
cet-6362	60	6	+	+	NOUN
cet-6362	60	7	]	]	X
cet-6362	60	8	yi	yi	NOUN
cet-6362	60	9	yi	yi	PROPN
cet-6362	61	1	ø	ø	PROPN
cet-6362	61	2	0	0	NUM
cet-6362	62	1	otherwise	otherwise	ADV
cet-6362	62	2	(	(	PUNCT
cet-6362	62	3	3	3	X
cet-6362	62	4	)	)	PUNCT
cet-6362	62	5	where	where	SCONJ
cet-6362	62	6	yi	yi	NOUN
cet-6362	63	1	=	=	PUNCT
cet-6362	64	1	[	[	PUNCT
cet-6362	64	2	yi	yi	NOUN
cet-6362	64	3	-	-	PUNCT
cet-6362	64	4	,	,	PUNCT
cet-6362	64	5	yi	yi	X
cet-6362	65	1	+	+	NOUN
cet-6362	65	2	]	]	X
cet-6362	65	3	where	where	SCONJ
cet-6362	65	4	yi	yi	PROPN
cet-6362	65	5	yi	yi	PROPN
cet-6362	66	1	+	+	CCONJ
cet-6362	66	2	are	be	AUX
cet-6362	66	3	the	the	DET
cet-6362	66	4	lower	low	ADJ
cet-6362	66	5	and	and	CCONJ
cet-6362	66	6	upper	upper	ADJ
cet-6362	66	7	bounds	bound	NOUN
cet-6362	66	8	(	(	PUNCT
cet-6362	66	9	real	real	ADJ
cet-6362	66	10	values	value	NOUN
cet-6362	66	11	)	)	PUNCT
cet-6362	66	12	of	of	ADP
cet-6362	66	13	the	the	DET
cet-6362	66	14	output	output	NOUN
cet-6362	66	15	interval	interval	NOUN
cet-6362	66	16	,	,	PUNCT
cet-6362	66	17	respectively	respectively	ADV
cet-6362	66	18	,	,	PUNCT
cet-6362	66	19	and	and	CCONJ
cet-6362	66	20	diam	diam	PROPN
cet-6362	66	21	(	(	PUNCT
cet-6362	66	22	)	)	PUNCT
cet-6362	66	23	indicates	indicate	VERB
cet-6362	66	24	the	the	DET
cet-6362	66	25	width	width	NOUN
cet-6362	66	26	of	of	ADP
cet-6362	66	27	an	an	DET
cet-6362	66	28	interval	interval	NOUN
cet-6362	66	29	.	.	PUNCT
cet-6362	67	1	concerning	concern	VERB
cet-6362	67	2	piw	piw	PROPN
cet-6362	67	3	,	,	PUNCT
cet-6362	67	4	we	we	PRON
cet-6362	67	5	consider	consider	VERB
cet-6362	67	6	the	the	DET
cet-6362	67	7	following	follow	VERB
cet-6362	67	8	quantity	quantity	NOUN
cet-6362	67	9	:	:	PUNCT
cet-6362	67	10	nmpiw	nmpiw	X
cet-6362	67	11	=	=	SYM
cet-6362	67	12	1	1	NUM
cet-6362	67	13	np	np	INTJ
cet-6362	67	14	(	(	PUNCT
cet-6362	67	15	yi	yi	NOUN
cet-6362	67	16	+	+	CCONJ
cet-6362	67	17	yi	yi	PROPN
cet-6362	67	18	-	-	PUNCT
cet-6362	67	19	)	)	PUNCT
cet-6362	67	20	np	np	ADP
cet-6362	67	21	i=1	i=1	PROPN
cet-6362	67	22	tmax	tmax	PROPN
cet-6362	67	23	tmin	tmin	NOUN
cet-6362	67	24	(	(	PUNCT
cet-6362	67	25	4	4	NUM
cet-6362	67	26	)	)	PUNCT
cet-6362	67	27	where	where	SCONJ
cet-6362	67	28	nmpiw	nmpiw	NOUN
cet-6362	67	29	is	be	AUX
cet-6362	67	30	the	the	DET
cet-6362	67	31	normalized	normalize	VERB
cet-6362	67	32	mean	mean	ADJ
cet-6362	67	33	piw	piw	PROPN
cet-6362	67	34	,	,	PUNCT
cet-6362	67	35	and	and	CCONJ
cet-6362	67	36	tmin	tmin	NOUN
cet-6362	67	37	and	and	CCONJ
cet-6362	67	38	tmax	tmax	ADV
cet-6362	67	39	represent	represent	VERB
cet-6362	67	40	the	the	DET
cet-6362	67	41	true	true	ADJ
cet-6362	67	42	minimum	minimum	ADJ
cet-6362	67	43	and	and	CCONJ
cet-6362	67	44	maximum	maximum	ADJ
cet-6362	67	45	values	value	NOUN
cet-6362	67	46	of	of	ADP
cet-6362	67	47	the	the	DET
cet-6362	67	48	targets	target	NOUN
cet-6362	67	49	(	(	PUNCT
cet-6362	67	50	i.e.	i.e.	X
cet-6362	67	51	,	,	PUNCT
cet-6362	67	52	the	the	DET
cet-6362	67	53	bounds	bound	NOUN
cet-6362	67	54	of	of	ADP
cet-6362	67	55	the	the	DET
cet-6362	67	56	range	range	NOUN
cet-6362	67	57	in	in	ADP
cet-6362	67	58	which	which	PRON
cet-6362	67	59	the	the	DET
cet-6362	67	60	true	true	ADJ
cet-6362	67	61	values	value	NOUN
cet-6362	67	62	fall	fall	VERB
cet-6362	67	63	)	)	PUNCT
cet-6362	67	64	.	.	PUNCT
cet-6362	68	1	3	3	X
cet-6362	68	2	.	.	X
cet-6362	68	3	nsga	nsga	NOUN
cet-6362	68	4	-	-	PUNCT
cet-6362	68	5	ii	ii	PROPN
cet-6362	68	6	optimization	optimization	NOUN
cet-6362	68	7	of	of	ADP
cet-6362	68	8	a	a	DET
cet-6362	68	9	nn	nn	X
cet-6362	68	10	for	for	ADP
cet-6362	68	11	pis	pis	PROPN
cet-6362	68	12	estimation	estimation	PROPN
cet-6362	68	13	nsga	nsga	PROPN
cet-6362	68	14	-	-	PUNCT
cet-6362	68	15	ii	ii	PROPN
cet-6362	68	16	generates	generate	VERB
cet-6362	68	17	a	a	DET
cet-6362	68	18	pareto	pareto	ADJ
cet-6362	68	19	optimal	optimal	ADJ
cet-6362	68	20	solution	solution	NOUN
cet-6362	68	21	set	set	VERB
cet-6362	68	22	,	,	PUNCT
cet-6362	68	23	rather	rather	ADV
cet-6362	68	24	than	than	ADP
cet-6362	68	25	a	a	DET
cet-6362	68	26	single	single	ADJ
cet-6362	68	27	solution	solution	NOUN
cet-6362	68	28	,	,	PUNCT
cet-6362	68	29	by	by	ADP
cet-6362	68	30	comparing	compare	VERB
cet-6362	68	31	different	different	ADJ
cet-6362	68	32	solutions	solution	NOUN
cet-6362	68	33	via	via	ADP
cet-6362	68	34	an	an	DET
cet-6362	68	35	elitist	elitist	ADJ
cet-6362	68	36	approach	approach	NOUN
cet-6362	68	37	,	,	PUNCT
cet-6362	68	38	i.e.	i.e.	X
cet-6362	68	39	,	,	PUNCT
cet-6362	68	40	a	a	DET
cet-6362	68	41	fast	fast	ADJ
cet-6362	68	42	non	non	ADJ
cet-6362	68	43	-	-	ADJ
cet-6362	68	44	dominated	dominated	ADJ
cet-6362	68	45	sorting	sorting	NOUN
cet-6362	68	46	and	and	CCONJ
cet-6362	68	47	crowding	crowd	VERB
cet-6362	68	48	-	-	PUNCT
cet-6362	68	49	distance	distance	NOUN
cet-6362	68	50	estimation	estimation	NOUN
cet-6362	68	51	procedure	procedure	NOUN
cet-6362	68	52	(	(	PUNCT
cet-6362	68	53	konak	konak	PROPN
cet-6362	68	54	et	et	PROPN
cet-6362	68	55	al	al	PROPN
cet-6362	68	56	.	.	PROPN
cet-6362	68	57	,	,	PUNCT
cet-6362	68	58	2006	2006	NUM
cet-6362	68	59	)	)	PUNCT
cet-6362	68	60	.	.	PUNCT
cet-6362	69	1	the	the	DET
cet-6362	69	2	practical	practical	ADJ
cet-6362	69	3	implementation	implementation	NOUN
cet-6362	69	4	of	of	ADP
cet-6362	69	5	nsga	nsga	NOUN
cet-6362	69	6	-	-	PUNCT
cet-6362	69	7	ii	ii	NOUN
cet-6362	69	8	on	on	ADP
cet-6362	69	9	our	our	PRON
cet-6362	69	10	specific	specific	ADJ
cet-6362	69	11	problem	problem	NOUN
cet-6362	69	12	involves	involve	VERB
cet-6362	69	13	two	two	NUM
cet-6362	69	14	phases	phase	NOUN
cet-6362	69	15	:	:	PUNCT
cet-6362	69	16	initialization	initialization	NOUN
cet-6362	69	17	and	and	CCONJ
cet-6362	69	18	evolution	evolution	NOUN
cet-6362	69	19	.	.	PUNCT
cet-6362	70	1	these	these	PRON
cet-6362	70	2	can	can	AUX
cet-6362	70	3	be	be	AUX
cet-6362	70	4	summarized	summarize	VERB
cet-6362	70	5	as	as	SCONJ
cet-6362	70	6	follows	follow	VERB
cet-6362	70	7	(	(	PUNCT
cet-6362	70	8	ak	ak	PROPN
cet-6362	70	9	et	et	PROPN
cet-6362	70	10	al	al	PROPN
cet-6362	70	11	.	.	PROPN
cet-6362	70	12	,	,	PUNCT
cet-6362	70	13	2013	2013	NUM
cet-6362	70	14	):	):	PUNCT
cet-6362	70	15	initialization	initialization	NOUN
cet-6362	70	16	phase	phase	NOUN
cet-6362	70	17	:	:	PUNCT
cet-6362	70	18	step	step	NOUN
cet-6362	70	19	1	1	NUM
cet-6362	70	20	:	:	PUNCT
cet-6362	70	21	split	split	VERB
cet-6362	70	22	the	the	DET
cet-6362	70	23	input	input	NOUN
cet-6362	70	24	data	datum	NOUN
cet-6362	70	25	set	set	VERB
cet-6362	70	26	into	into	ADP
cet-6362	70	27	training	training	NOUN
cet-6362	70	28	(	(	PUNCT
cet-6362	70	29	dtrain	dtrain	NOUN
cet-6362	70	30	)	)	PUNCT
cet-6362	70	31	and	and	CCONJ
cet-6362	70	32	testing	testing	NOUN
cet-6362	70	33	(	(	PUNCT
cet-6362	70	34	dtest	dt	ADJ
cet-6362	70	35	)	)	PUNCT
cet-6362	70	36	subsets	subset	NOUN
cet-6362	70	37	.	.	PUNCT
cet-6362	71	1	step	step	NOUN
cet-6362	71	2	2	2	NUM
cet-6362	71	3	:	:	PUNCT
cet-6362	71	4	fix	fix	VERB
cet-6362	71	5	the	the	DET
cet-6362	71	6	maximum	maximum	ADJ
cet-6362	71	7	number	number	NOUN
cet-6362	71	8	of	of	ADP
cet-6362	71	9	generations	generation	NOUN
cet-6362	71	10	and	and	CCONJ
cet-6362	71	11	the	the	DET
cet-6362	71	12	number	number	NOUN
cet-6362	71	13	of	of	ADP
cet-6362	71	14	chromosomes	chromosome	NOUN
cet-6362	71	15	(	(	PUNCT
cet-6362	71	16	individuals	individual	NOUN
cet-6362	71	17	)	)	PUNCT
cet-6362	71	18	nc	nc	PROPN
cet-6362	71	19	in	in	ADP
cet-6362	71	20	each	each	DET
cet-6362	71	21	population	population	NOUN
cet-6362	71	22	.	.	PUNCT
cet-6362	72	1	each	each	DET
cet-6362	72	2	chromosome	chromosome	NOUN
cet-6362	72	3	codes	code	VERB
cet-6362	72	4	a	a	DET
cet-6362	72	5	solution	solution	NOUN
cet-6362	72	6	by	by	ADP
cet-6362	72	7	g	g	PROPN
cet-6362	72	8	real	real	ADV
cet-6362	72	9	-	-	PUNCT
cet-6362	72	10	valued	value	VERB
cet-6362	72	11	genes	gene	NOUN
cet-6362	72	12	,	,	PUNCT
cet-6362	72	13	where	where	SCONJ
cet-6362	72	14	g	g	PROPN
cet-6362	72	15	is	be	AUX
cet-6362	72	16	the	the	DET
cet-6362	72	17	total	total	ADJ
cet-6362	72	18	number	number	NOUN
cet-6362	72	19	of	of	ADP
cet-6362	72	20	parameters	parameter	NOUN
cet-6362	72	21	(	(	PUNCT
cet-6362	72	22	weights	weight	NOUN
cet-6362	72	23	and	and	CCONJ
cet-6362	72	24	biases	bias	NOUN
cet-6362	72	25	)	)	PUNCT
cet-6362	72	26	in	in	ADP
cet-6362	72	27	the	the	DET
cet-6362	72	28	nn	nn	NOUN
cet-6362	72	29	:	:	PUNCT
cet-6362	72	30	thus	thus	ADV
cet-6362	72	31	,	,	PUNCT
cet-6362	72	32	each	each	DET
cet-6362	72	33	chromosome	chromosome	NOUN
cet-6362	72	34	represents	represent	VERB
cet-6362	72	35	a	a	DET
cet-6362	72	36	nn	nn	PROPN
cet-6362	72	37	.	.	PROPN
cet-6362	72	38	set	set	VERB
cet-6362	72	39	the	the	DET
cet-6362	72	40	generation	generation	NOUN
cet-6362	72	41	number	number	NOUN
cet-6362	72	42	n	n	NOUN
cet-6362	72	43	=	=	NOUN
cet-6362	72	44	1	1	NUM
cet-6362	72	45	.	.	PUNCT
cet-6362	72	46	initialize	initialize	VERB
cet-6362	72	47	the	the	DET
cet-6362	72	48	first	first	ADJ
cet-6362	72	49	population	population	NOUN
cet-6362	72	50	pn	pn	PROPN
cet-6362	72	51	of	of	ADP
cet-6362	72	52	size	size	PROPN
cet-6362	72	53	nc	nc	PROPN
cet-6362	72	54	,	,	PUNCT
cet-6362	72	55	by	by	ADP
cet-6362	72	56	randomly	randomly	ADV
cet-6362	72	57	generating	generate	VERB
cet-6362	72	58	nc	nc	PROPN
cet-6362	72	59	chromosomes	chromosome	NOUN
cet-6362	72	60	(	(	PUNCT
cet-6362	72	61	corresponding	correspond	VERB
cet-6362	72	62	to	to	ADP
cet-6362	72	63	nns	nn	NOUN
cet-6362	72	64	)	)	PUNCT
cet-6362	72	65	.	.	PUNCT
cet-6362	73	1	step	step	NOUN
cet-6362	73	2	3	3	NUM
cet-6362	73	3	:	:	PUNCT
cet-6362	73	4	for	for	ADP
cet-6362	73	5	each	each	DET
cet-6362	73	6	input	input	NOUN
cet-6362	73	7	vector	vector	NOUN
cet-6362	73	8	x	x	NOUN
cet-6362	73	9	in	in	ADP
cet-6362	73	10	the	the	DET
cet-6362	73	11	training	training	NOUN
cet-6362	73	12	set	set	NOUN
cet-6362	73	13	,	,	PUNCT
cet-6362	73	14	compute	compute	VERB
cet-6362	73	15	the	the	DET
cet-6362	73	16	lower	low	ADJ
cet-6362	73	17	and	and	CCONJ
cet-6362	73	18	upper	upper	ADJ
cet-6362	73	19	bound	bind	VERB
cet-6362	73	20	outputs	output	NOUN
cet-6362	73	21	of	of	ADP
cet-6362	73	22	the	the	DET
cet-6362	73	23	nc	nc	PROPN
cet-6362	73	24	nns	nns	PROPN
cet-6362	73	25	.	.	PUNCT
cet-6362	74	1	step	step	NOUN
cet-6362	74	2	4	4	NUM
cet-6362	74	3	:	:	PUNCT
cet-6362	74	4	evaluate	evaluate	VERB
cet-6362	74	5	the	the	DET
cet-6362	74	6	two	two	NUM
cet-6362	74	7	objectives	objective	NOUN
cet-6362	74	8	picp	picp	NOUN
cet-6362	74	9	and	and	CCONJ
cet-6362	74	10	nmpiw	nmpiw	NOUN
cet-6362	74	11	for	for	ADP
cet-6362	74	12	the	the	DET
cet-6362	74	13	nc	nc	PROPN
cet-6362	74	14	nns	nns	PROPN
cet-6362	74	15	;	;	PUNCT
cet-6362	74	16	then	then	ADV
cet-6362	74	17	,	,	PUNCT
cet-6362	74	18	one	one	NUM
cet-6362	74	19	pair	pair	NOUN
cet-6362	74	20	of	of	ADP
cet-6362	74	21	values	value	NOUN
cet-6362	74	22	1	1	NUM
cet-6362	74	23	picp	picp	NOUN
cet-6362	74	24	(	(	PUNCT
cet-6362	74	25	for	for	ADP
cet-6362	74	26	minimization	minimization	NOUN
cet-6362	74	27	)	)	PUNCT
cet-6362	74	28	and	and	CCONJ
cet-6362	74	29	nmpiw	nmpiw	NOUN
cet-6362	74	30	is	be	AUX
cet-6362	74	31	associated	associate	VERB
cet-6362	74	32	to	to	ADP
cet-6362	74	33	each	each	PRON
cet-6362	74	34	of	of	ADP
cet-6362	74	35	the	the	DET
cet-6362	74	36	nc	nc	PROPN
cet-6362	74	37	chromosomes	chromosome	NOUN
cet-6362	74	38	in	in	ADP
cet-6362	74	39	the	the	DET
cet-6362	74	40	population	population	NOUN
cet-6362	74	41	pn	pn	PROPN
cet-6362	74	42	.	.	PROPN
cet-6362	74	43	step	step	NOUN
cet-6362	74	44	5	5	NUM
cet-6362	74	45	:	:	PUNCT
cet-6362	74	46	rank	rank	VERB
cet-6362	74	47	the	the	DET
cet-6362	74	48	chromosomes	chromosome	NOUN
cet-6362	74	49	(	(	PUNCT
cet-6362	74	50	vectors	vector	NOUN
cet-6362	74	51	of	of	ADP
cet-6362	74	52	g	g	PROPN
cet-6362	74	53	values	value	NOUN
cet-6362	74	54	)	)	PUNCT
cet-6362	74	55	in	in	ADP
cet-6362	74	56	the	the	DET
cet-6362	74	57	population	population	NOUN
cet-6362	74	58	pn	pn	NOUN
cet-6362	74	59	by	by	ADP
cet-6362	74	60	running	run	VERB
cet-6362	74	61	the	the	DET
cet-6362	74	62	fast	fast	ADJ
cet-6362	74	63	nondominated	nondominated	ADJ
cet-6362	74	64	sorting	sort	VERB
cet-6362	74	65	algorithm	algorithm	NOUN
cet-6362	74	66	(	(	PUNCT
cet-6362	74	67	konak	konak	PROPN
cet-6362	74	68	et	et	PROPN
cet-6362	74	69	al	al	PROPN
cet-6362	74	70	.	.	PROPN
cet-6362	74	71	,	,	PUNCT
cet-6362	74	72	2006	2006	NUM
cet-6362	74	73	)	)	PUNCT
cet-6362	74	74	with	with	ADP
cet-6362	74	75	respect	respect	NOUN
cet-6362	74	76	to	to	ADP
cet-6362	74	77	the	the	DET
cet-6362	74	78	pairs	pair	NOUN
cet-6362	74	79	of	of	ADP
cet-6362	74	80	objective	objective	ADJ
cet-6362	74	81	values	value	NOUN
cet-6362	74	82	,	,	PUNCT
cet-6362	74	83	and	and	CCONJ
cet-6362	74	84	identify	identify	VERB
cet-6362	74	85	the	the	DET
cet-6362	74	86	ranked	rank	VERB
cet-6362	74	87	non	non	ADJ
cet-6362	74	88	-	-	ADJ
cet-6362	74	89	dominated	dominated	ADJ
cet-6362	74	90	fronts	front	NOUN
cet-6362	74	91	f1	f1	NOUN
cet-6362	74	92	,	,	PUNCT
cet-6362	74	93	f2	f2	PROPN
cet-6362	74	94	,	,	PUNCT
cet-6362	74	95	…	…	PUNCT
cet-6362	74	96	,	,	PUNCT
cet-6362	74	97	fk	fk	INTJ
cet-6362	74	98	where	where	SCONJ
cet-6362	74	99	f1	f1	NOUN
cet-6362	74	100	is	be	AUX
cet-6362	74	101	the	the	DET
cet-6362	74	102	best	good	ADJ
cet-6362	74	103	front	front	NOUN
cet-6362	74	104	,	,	PUNCT
cet-6362	74	105	f2	f2	PROPN
cet-6362	74	106	is	be	AUX
cet-6362	74	107	the	the	DET
cet-6362	74	108	second	second	ADJ
cet-6362	74	109	best	good	ADJ
cet-6362	74	110	front	front	NOUN
cet-6362	74	111	and	and	CCONJ
cet-6362	74	112	fk	fk	INTJ
cet-6362	74	113	is	be	AUX
cet-6362	74	114	the	the	DET
cet-6362	74	115	least	least	ADV
cet-6362	74	116	good	good	ADJ
cet-6362	74	117	front	front	NOUN
cet-6362	74	118	.	.	PUNCT
cet-6362	75	1	step	step	NOUN
cet-6362	75	2	6	6	NUM
cet-6362	75	3	:	:	PUNCT
cet-6362	75	4	apply	apply	VERB
cet-6362	75	5	to	to	ADP
cet-6362	75	6	pn	pn	VERB
cet-6362	75	7	a	a	DET
cet-6362	75	8	binary	binary	ADJ
cet-6362	75	9	tournament	tournament	NOUN
cet-6362	75	10	selection	selection	NOUN
cet-6362	75	11	based	base	VERB
cet-6362	75	12	on	on	ADP
cet-6362	75	13	the	the	DET
cet-6362	75	14	crowding	crowd	VERB
cet-6362	75	15	distance	distance	NOUN
cet-6362	75	16	(	(	PUNCT
cet-6362	75	17	konak	konak	PROPN
cet-6362	75	18	et	et	PROPN
cet-6362	75	19	al	al	PROPN
cet-6362	75	20	.	.	PROPN
cet-6362	75	21	,	,	PUNCT
cet-6362	75	22	2006	2006	NUM
cet-6362	75	23	)	)	PUNCT
cet-6362	75	24	,	,	PUNCT
cet-6362	75	25	for	for	ADP
cet-6362	75	26	generating	generate	VERB
cet-6362	75	27	an	an	DET
cet-6362	75	28	intermediate	intermediate	ADJ
cet-6362	75	29	population	population	NOUN
cet-6362	75	30	sn	sn	PROPN
cet-6362	75	31	of	of	ADP
cet-6362	75	32	size	size	PROPN
cet-6362	75	33	nc	nc	PROPN
cet-6362	75	34	.	.	PROPN
cet-6362	75	35	step	step	PROPN
cet-6362	75	36	7	7	NUM
cet-6362	75	37	:	:	PUNCT
cet-6362	75	38	apply	apply	VERB
cet-6362	75	39	the	the	DET
cet-6362	75	40	crossover	crossover	NOUN
cet-6362	75	41	and	and	CCONJ
cet-6362	75	42	mutation	mutation	NOUN
cet-6362	75	43	operators	operator	NOUN
cet-6362	75	44	to	to	PART
cet-6362	75	45	sn	sn	VERB
cet-6362	75	46	,	,	PUNCT
cet-6362	75	47	to	to	PART
cet-6362	75	48	create	create	VERB
cet-6362	75	49	the	the	DET
cet-6362	75	50	offspring	offspring	NOUN
cet-6362	75	51	population	population	NOUN
cet-6362	75	52	qn	qn	NOUN
cet-6362	75	53	of	of	ADP
cet-6362	75	54	size	size	PROPN
cet-6362	75	55	nc	nc	PROPN
cet-6362	75	56	.	.	PROPN
cet-6362	75	57	step	step	PROPN
cet-6362	75	58	8	8	NUM
cet-6362	75	59	:	:	PUNCT
cet-6362	75	60	apply	apply	VERB
cet-6362	75	61	step	step	NOUN
cet-6362	75	62	3	3	NUM
cet-6362	75	63	onto	onto	ADP
cet-6362	75	64	qn	qn	NOUN
cet-6362	75	65	and	and	CCONJ
cet-6362	75	66	obtain	obtain	VERB
cet-6362	75	67	the	the	DET
cet-6362	75	68	lower	low	ADJ
cet-6362	75	69	and	and	CCONJ
cet-6362	75	70	upper	upper	ADJ
cet-6362	75	71	bound	bind	VERB
cet-6362	75	72	outputs	output	NOUN
cet-6362	75	73	.	.	PUNCT
cet-6362	76	1	step	step	NOUN
cet-6362	76	2	9	9	NUM
cet-6362	76	3	:	:	PUNCT
cet-6362	76	4	evaluate	evaluate	VERB
cet-6362	76	5	the	the	DET
cet-6362	76	6	two	two	NUM
cet-6362	76	7	objectives	objective	NOUN
cet-6362	76	8	in	in	ADP
cet-6362	76	9	correspondence	correspondence	NOUN
cet-6362	76	10	of	of	ADP
cet-6362	76	11	the	the	DET
cet-6362	76	12	solutions	solution	NOUN
cet-6362	76	13	in	in	ADP
cet-6362	76	14	qn	qn	NOUN
cet-6362	76	15	,	,	PUNCT
cet-6362	76	16	as	as	ADP
cet-6362	76	17	in	in	ADP
cet-6362	76	18	step	step	NOUN
cet-6362	76	19	4	4	NUM
cet-6362	76	20	.	.	PUNCT
cet-6362	76	21	927	927	NUM
cet-6362	76	22	evolution	evolution	NOUN
cet-6362	76	23	phase	phase	NOUN
cet-6362	76	24	:	:	PUNCT
cet-6362	76	25	step	step	NOUN
cet-6362	76	26	10	10	NUM
cet-6362	76	27	:	:	PUNCT
cet-6362	76	28	if	if	SCONJ
cet-6362	76	29	the	the	DET
cet-6362	76	30	maximum	maximum	ADJ
cet-6362	76	31	number	number	NOUN
cet-6362	76	32	of	of	ADP
cet-6362	76	33	generations	generation	NOUN
cet-6362	76	34	is	be	AUX
cet-6362	76	35	reached	reach	VERB
cet-6362	76	36	,	,	PUNCT
cet-6362	76	37	stop	stop	VERB
cet-6362	76	38	and	and	CCONJ
cet-6362	76	39	return	return	VERB
cet-6362	76	40	pn	pn	PROPN
cet-6362	76	41	.	.	PROPN
cet-6362	76	42	select	select	VERB
cet-6362	76	43	the	the	DET
cet-6362	76	44	first	first	ADJ
cet-6362	76	45	pareto	pareto	ADJ
cet-6362	76	46	front	front	ADJ
cet-6362	76	47	f1	f1	NOUN
cet-6362	76	48	as	as	ADP
cet-6362	76	49	the	the	DET
cet-6362	76	50	optimal	optimal	ADJ
cet-6362	76	51	solution	solution	NOUN
cet-6362	76	52	set	set	VERB
cet-6362	76	53	.	.	PUNCT
cet-6362	77	1	otherwise	otherwise	ADV
cet-6362	77	2	,	,	PUNCT
cet-6362	77	3	go	go	VERB
cet-6362	77	4	to	to	PART
cet-6362	77	5	step	step	VERB
cet-6362	77	6	11	11	NUM
cet-6362	77	7	.	.	PUNCT
cet-6362	78	1	step	step	NOUN
cet-6362	78	2	11	11	NUM
cet-6362	78	3	:	:	PUNCT
cet-6362	78	4	combine	combine	VERB
cet-6362	78	5	pn	pn	PROPN
cet-6362	78	6	and	and	CCONJ
cet-6362	78	7	qn	qn	VERB
cet-6362	78	8	to	to	PART
cet-6362	78	9	obtain	obtain	VERB
cet-6362	78	10	a	a	DET
cet-6362	78	11	union	union	NOUN
cet-6362	78	12	population	population	NOUN
cet-6362	78	13	rn	rn	PROPN
cet-6362	78	14	=	=	PROPN
cet-6362	78	15	pn	pn	PROPN
cet-6362	78	16	qn	qn	PROPN
cet-6362	78	17	.	.	PROPN
cet-6362	78	18	step	step	NOUN
cet-6362	78	19	12	12	NUM
cet-6362	78	20	:	:	PUNCT
cet-6362	78	21	apply	apply	VERB
cet-6362	78	22	steps	step	NOUN
cet-6362	78	23	3	3	NUM
cet-6362	78	24	-	-	SYM
cet-6362	78	25	5	5	NUM
cet-6362	78	26	onto	onto	ADP
cet-6362	78	27	rn	rn	PROPN
cet-6362	78	28	and	and	CCONJ
cet-6362	78	29	obtain	obtain	VERB
cet-6362	78	30	a	a	DET
cet-6362	78	31	sorted	sorted	ADJ
cet-6362	78	32	union	union	NOUN
cet-6362	78	33	population	population	NOUN
cet-6362	78	34	.	.	PUNCT
cet-6362	79	1	step	step	NOUN
cet-6362	79	2	13	13	NUM
cet-6362	79	3	:	:	PUNCT
cet-6362	79	4	select	select	VERB
cet-6362	79	5	the	the	DET
cet-6362	79	6	nc	nc	PROPN
cet-6362	79	7	best	good	ADJ
cet-6362	79	8	solutions	solution	NOUN
cet-6362	79	9	from	from	ADP
cet-6362	79	10	the	the	DET
cet-6362	79	11	sorted	sorted	ADJ
cet-6362	79	12	union	union	NOUN
cet-6362	79	13	to	to	PART
cet-6362	79	14	create	create	VERB
cet-6362	79	15	the	the	DET
cet-6362	79	16	next	next	ADJ
cet-6362	79	17	parent	parent	NOUN
cet-6362	79	18	population	population	NOUN
cet-6362	79	19	pn+1	pn+1	PROPN
cet-6362	79	20	.	.	PUNCT
cet-6362	80	1	step	step	NOUN
cet-6362	80	2	14	14	NUM
cet-6362	80	3	:	:	PUNCT
cet-6362	80	4	apply	apply	VERB
cet-6362	80	5	steps	step	NOUN
cet-6362	80	6	6	6	NUM
cet-6362	80	7	-	-	SYM
cet-6362	80	8	9	9	NUM
cet-6362	80	9	onto	onto	ADP
cet-6362	80	10	pn+1	pn+1	NOUN
cet-6362	80	11	to	to	PART
cet-6362	80	12	obtain	obtain	VERB
cet-6362	80	13	qn+1	qn+1	NUM
cet-6362	80	14	.	.	PUNCT
cet-6362	81	1	set	set	VERB
cet-6362	81	2	n	n	NOUN
cet-6362	81	3	=	=	SYM
cet-6362	81	4	n	n	PROPN
cet-6362	81	5	+	+	NOUN
cet-6362	81	6	1	1	NUM
cet-6362	81	7	;	;	PUNCT
cet-6362	81	8	and	and	CCONJ
cet-6362	81	9	go	go	VERB
cet-6362	81	10	to	to	PART
cet-6362	81	11	step	step	VERB
cet-6362	81	12	10	10	NUM
cet-6362	81	13	.	.	PUNCT
cet-6362	82	1	finally	finally	ADV
cet-6362	82	2	,	,	PUNCT
cet-6362	82	3	the	the	DET
cet-6362	82	4	best	good	ADJ
cet-6362	82	5	front	front	NOUN
cet-6362	82	6	in	in	ADP
cet-6362	82	7	terms	term	NOUN
cet-6362	82	8	of	of	ADP
cet-6362	82	9	ranking	ranking	NOUN
cet-6362	82	10	of	of	ADP
cet-6362	82	11	non	non	ADJ
cet-6362	82	12	-	-	ADJ
cet-6362	82	13	dominance	dominance	NOUN
cet-6362	82	14	and	and	CCONJ
cet-6362	82	15	diversity	diversity	NOUN
cet-6362	82	16	of	of	ADP
cet-6362	82	17	the	the	DET
cet-6362	82	18	individual	individual	ADJ
cet-6362	82	19	solutions	solution	NOUN
cet-6362	82	20	is	be	AUX
cet-6362	82	21	chosen	choose	VERB
cet-6362	82	22	,	,	PUNCT
cet-6362	82	23	and	and	CCONJ
cet-6362	82	24	testing	testing	NOUN
cet-6362	82	25	of	of	ADP
cet-6362	82	26	the	the	DET
cet-6362	82	27	trained	train	VERB
cet-6362	82	28	nn	nn	PROPN
cet-6362	82	29	with	with	ADP
cet-6362	82	30	optimal	optimal	ADJ
cet-6362	82	31	weight	weight	NOUN
cet-6362	82	32	values	value	NOUN
cet-6362	82	33	is	be	AUX
cet-6362	82	34	performed	perform	VERB
cet-6362	82	35	using	use	VERB
cet-6362	82	36	the	the	DET
cet-6362	82	37	data	datum	NOUN
cet-6362	82	38	of	of	ADP
cet-6362	82	39	the	the	DET
cet-6362	82	40	testing	testing	NOUN
cet-6362	82	41	set	set	NOUN
cet-6362	82	42	.	.	PUNCT
cet-6362	83	1	4	4	X
cet-6362	83	2	.	.	X
cet-6362	83	3	experiments	experiment	NOUN
cet-6362	83	4	and	and	CCONJ
cet-6362	83	5	results	result	NOUN
cet-6362	83	6	in	in	ADP
cet-6362	83	7	this	this	DET
cet-6362	83	8	section	section	NOUN
cet-6362	83	9	,	,	PUNCT
cet-6362	83	10	results	result	NOUN
cet-6362	83	11	of	of	ADP
cet-6362	83	12	the	the	DET
cet-6362	83	13	application	application	NOUN
cet-6362	83	14	of	of	ADP
cet-6362	83	15	the	the	DET
cet-6362	83	16	proposed	propose	VERB
cet-6362	83	17	method	method	NOUN
cet-6362	83	18	to	to	ADP
cet-6362	83	19	short	short	ADJ
cet-6362	83	20	-	-	PUNCT
cet-6362	83	21	term	term	NOUN
cet-6362	83	22	wind	wind	NOUN
cet-6362	83	23	power	power	NOUN
cet-6362	83	24	forecasting	forecasting	NOUN
cet-6362	83	25	with	with	ADP
cet-6362	83	26	interval	interval	NOUN
cet-6362	83	27	-	-	PUNCT
cet-6362	83	28	input	input	NOUN
cet-6362	83	29	data	datum	NOUN
cet-6362	83	30	are	be	AUX
cet-6362	83	31	detailed	detail	VERB
cet-6362	83	32	.	.	PUNCT
cet-6362	84	1	the	the	DET
cet-6362	84	2	considered	consider	VERB
cet-6362	84	3	5	5	NUM
cet-6362	84	4	-	-	PUNCT
cet-6362	84	5	min	min	NOUN
cet-6362	84	6	wind	wind	NOUN
cet-6362	84	7	power	power	NOUN
cet-6362	84	8	data	datum	NOUN
cet-6362	84	9	have	have	AUX
cet-6362	84	10	been	be	AUX
cet-6362	84	11	measured	measure	VERB
cet-6362	84	12	for	for	ADP
cet-6362	84	13	canunda	canunda	NOUN
cet-6362	84	14	,	,	PUNCT
cet-6362	84	15	a	a	DET
cet-6362	84	16	region	region	NOUN
cet-6362	84	17	of	of	ADP
cet-6362	84	18	south	south	PROPN
cet-6362	84	19	australia	australia	PROPN
cet-6362	84	20	.	.	PUNCT
cet-6362	85	1	the	the	DET
cet-6362	85	2	actual	actual	ADJ
cet-6362	85	3	situation	situation	NOUN
cet-6362	85	4	in	in	ADP
cet-6362	85	5	canunda	canunda	NOUN
cet-6362	85	6	wind	wind	NOUN
cet-6362	85	7	farm	farm	NOUN
cet-6362	85	8	is	be	AUX
cet-6362	85	9	characterized	characterize	VERB
cet-6362	85	10	by	by	ADP
cet-6362	85	11	the	the	DET
cet-6362	85	12	presence	presence	NOUN
cet-6362	85	13	of	of	ADP
cet-6362	85	14	23	23	NUM
cet-6362	85	15	turbines	turbine	NOUN
cet-6362	85	16	capable	capable	ADJ
cet-6362	85	17	of	of	ADP
cet-6362	85	18	generating	generate	VERB
cet-6362	85	19	approximately	approximately	ADV
cet-6362	85	20	46	46	NUM
cet-6362	85	21	megawatts	megawatt	NOUN
cet-6362	85	22	(	(	PUNCT
cet-6362	85	23	mw	mw	NOUN
cet-6362	85	24	)	)	PUNCT
cet-6362	85	25	of	of	ADP
cet-6362	85	26	electricity	electricity	NOUN
cet-6362	85	27	,	,	PUNCT
cet-6362	85	28	enough	enough	ADV
cet-6362	85	29	to	to	PART
cet-6362	85	30	provide	provide	VERB
cet-6362	85	31	the	the	DET
cet-6362	85	32	power	power	NOUN
cet-6362	85	33	needs	need	NOUN
cet-6362	85	34	of	of	ADP
cet-6362	85	35	around	around	ADP
cet-6362	85	36	30,000	30,000	NUM
cet-6362	85	37	homes	home	NOUN
cet-6362	85	38	(	(	PUNCT
cet-6362	85	39	gdf	gdf	PROPN
cet-6362	85	40	suez	suez	PROPN
cet-6362	85	41	,	,	PUNCT
cet-6362	85	42	2010	2010	NUM
cet-6362	85	43	)	)	PUNCT
cet-6362	85	44	.	.	PUNCT
cet-6362	86	1	the	the	DET
cet-6362	86	2	wind	wind	NOUN
cet-6362	86	3	power	power	NOUN
cet-6362	86	4	data	datum	NOUN
cet-6362	86	5	set	set	VERB
cet-6362	86	6	,	,	PUNCT
cet-6362	86	7	covering	cover	VERB
cet-6362	86	8	the	the	DET
cet-6362	86	9	period	period	NOUN
cet-6362	86	10	from	from	ADP
cet-6362	86	11	january	january	PROPN
cet-6362	86	12	18	18	NUM
cet-6362	86	13	,	,	PUNCT
cet-6362	86	14	2012	2012	NUM
cet-6362	86	15	till	till	SCONJ
cet-6362	86	16	march	march	PROPN
cet-6362	86	17	13	13	NUM
cet-6362	86	18	,	,	PUNCT
cet-6362	86	19	2012	2012	NUM
cet-6362	86	20	,	,	PUNCT
cet-6362	86	21	has	have	AUX
cet-6362	86	22	been	be	AUX
cet-6362	86	23	downloaded	download	VERB
cet-6362	86	24	from	from	ADP
cet-6362	86	25	the	the	DET
cet-6362	86	26	website	website	NOUN
cet-6362	86	27	aemo	aemo	NOUN
cet-6362	86	28	(	(	PUNCT
cet-6362	86	29	2012	2012	NUM
cet-6362	86	30	)	)	PUNCT
cet-6362	86	31	.	.	PUNCT
cet-6362	87	1	as	as	SCONJ
cet-6362	87	2	5	5	NUM
cet-6362	87	3	-	-	PUNCT
cet-6362	87	4	min	min	NOUN
cet-6362	87	5	data	datum	NOUN
cet-6362	87	6	have	have	AUX
cet-6362	87	7	been	be	AUX
cet-6362	87	8	collected	collect	VERB
cet-6362	87	9	,	,	PUNCT
cet-6362	87	10	there	there	PRON
cet-6362	87	11	are	be	VERB
cet-6362	87	12	12	12	NUM
cet-6362	87	13	wind	wind	NOUN
cet-6362	87	14	power	power	NOUN
cet-6362	87	15	values	value	NOUN
cet-6362	87	16	for	for	ADP
cet-6362	87	17	each	each	DET
cet-6362	87	18	hour	hour	NOUN
cet-6362	87	19	.	.	PUNCT
cet-6362	88	1	the	the	DET
cet-6362	88	2	raw	raw	ADJ
cet-6362	88	3	data	datum	NOUN
cet-6362	88	4	set	set	VERB
cet-6362	88	5	includes	include	VERB
cet-6362	88	6	6,000	6,000	NUM
cet-6362	88	7	samples	sample	NOUN
cet-6362	88	8	among	among	ADP
cet-6362	88	9	which	which	PRON
cet-6362	88	10	the	the	DET
cet-6362	88	11	first	first	ADJ
cet-6362	88	12	80	80	NUM
cet-6362	88	13	%	%	NOUN
cet-6362	88	14	(	(	PUNCT
cet-6362	88	15	the	the	DET
cet-6362	88	16	first	first	ADJ
cet-6362	88	17	4,800	4,800	NUM
cet-6362	88	18	samples	sample	NOUN
cet-6362	88	19	)	)	PUNCT
cet-6362	88	20	is	be	AUX
cet-6362	88	21	used	use	VERB
cet-6362	88	22	for	for	ADP
cet-6362	88	23	training	training	NOUN
cet-6362	88	24	and	and	CCONJ
cet-6362	88	25	the	the	DET
cet-6362	88	26	rest	rest	NOUN
cet-6362	88	27	for	for	ADP
cet-6362	88	28	testing	testing	NOUN
cet-6362	88	29	.	.	PUNCT
cet-6362	89	1	the	the	DET
cet-6362	89	2	real	real	ADJ
cet-6362	89	3	wind	wind	NOUN
cet-6362	89	4	power	power	NOUN
cet-6362	89	5	changes	change	NOUN
cet-6362	89	6	from	from	ADP
cet-6362	89	7	0	0	NUM
cet-6362	89	8	mw	mw	NOUN
cet-6362	89	9	to	to	ADP
cet-6362	89	10	43.35	43.35	NUM
cet-6362	89	11	mw	mw	VERB
cet-6362	89	12	with	with	ADP
cet-6362	89	13	an	an	DET
cet-6362	89	14	unstable	unstable	ADJ
cet-6362	89	15	behavior	behavior	NOUN
cet-6362	89	16	.	.	PUNCT
cet-6362	90	1	figure	figure	NOUN
cet-6362	90	2	2	2	NUM
cet-6362	90	3	shows	show	VERB
cet-6362	90	4	the	the	DET
cet-6362	90	5	behavior	behavior	NOUN
cet-6362	90	6	of	of	ADP
cet-6362	90	7	5	5	NUM
cet-6362	90	8	-	-	PUNCT
cet-6362	90	9	min	min	NOUN
cet-6362	90	10	wind	wind	NOUN
cet-6362	90	11	power	power	NOUN
cet-6362	90	12	values	value	NOUN
cet-6362	90	13	only	only	ADV
cet-6362	90	14	in	in	ADP
cet-6362	90	15	the	the	DET
cet-6362	90	16	first	first	ADJ
cet-6362	90	17	24	24	NUM
cet-6362	90	18	hours	hour	NOUN
cet-6362	90	19	,	,	PUNCT
cet-6362	90	20	for	for	ADP
cet-6362	90	21	the	the	DET
cet-6362	90	22	sake	sake	NOUN
cet-6362	90	23	of	of	ADP
cet-6362	90	24	clarity	clarity	NOUN
cet-6362	90	25	:	:	PUNCT
cet-6362	90	26	one	one	PRON
cet-6362	90	27	can	can	AUX
cet-6362	90	28	appreciate	appreciate	VERB
cet-6362	90	29	the	the	DET
cet-6362	90	30	within	within	ADJ
cet-6362	90	31	-	-	PUNCT
cet-6362	90	32	hour	hour	NOUN
cet-6362	90	33	variability	variability	NOUN
cet-6362	90	34	in	in	ADP
cet-6362	90	35	each	each	DET
cet-6362	90	36	individual	individual	ADJ
cet-6362	90	37	hour	hour	NOUN
cet-6362	90	38	.	.	PUNCT
cet-6362	91	1	in	in	ADP
cet-6362	91	2	order	order	NOUN
cet-6362	91	3	to	to	PART
cet-6362	91	4	represent	represent	VERB
cet-6362	91	5	hourly	hourly	ADJ
cet-6362	91	6	wind	wind	NOUN
cet-6362	91	7	power	power	NOUN
cet-6362	91	8	as	as	ADP
cet-6362	91	9	an	an	DET
cet-6362	91	10	interval	interval	NOUN
cet-6362	91	11	,	,	PUNCT
cet-6362	91	12	this	this	DET
cet-6362	91	13	5	5	NUM
cet-6362	91	14	-	-	PUNCT
cet-6362	91	15	min	min	NOUN
cet-6362	91	16	data	datum	NOUN
cet-6362	91	17	have	have	AUX
cet-6362	91	18	been	be	AUX
cet-6362	91	19	converted	convert	VERB
cet-6362	91	20	to	to	ADP
cet-6362	91	21	intervalinput	intervalinput	NOUN
cet-6362	91	22	data	datum	NOUN
cet-6362	91	23	with	with	ADP
cet-6362	91	24	two	two	NUM
cet-6362	91	25	approaches	approach	NOUN
cet-6362	91	26	,	,	PUNCT
cet-6362	91	27	named	name	VERB
cet-6362	91	28	“	"	PUNCT
cet-6362	91	29	min	min	PROPN
cet-6362	91	30	-	-	PUNCT
cet-6362	91	31	max	max	NOUN
cet-6362	91	32	”	"	PUNCT
cet-6362	91	33	and	and	CCONJ
cet-6362	91	34	“	"	PUNCT
cet-6362	91	35	mean	mean	ADJ
cet-6362	91	36	”	"	PUNCT
cet-6362	91	37	:	:	PUNCT
cet-6362	91	38	the	the	DET
cet-6362	91	39	former	former	ADJ
cet-6362	91	40	obtains	obtain	VERB
cet-6362	91	41	hourly	hourly	ADJ
cet-6362	91	42	intervals	interval	NOUN
cet-6362	91	43	by	by	ADP
cet-6362	91	44	taking	take	VERB
cet-6362	91	45	the	the	DET
cet-6362	91	46	minimum	minimum	NOUN
cet-6362	91	47	and	and	CCONJ
cet-6362	91	48	the	the	DET
cet-6362	91	49	maximum	maximum	ADJ
cet-6362	91	50	values	value	NOUN
cet-6362	91	51	of	of	ADP
cet-6362	91	52	the	the	DET
cet-6362	91	53	wind	wind	NOUN
cet-6362	91	54	power	power	NOUN
cet-6362	91	55	per	per	ADP
cet-6362	91	56	hour	hour	NOUN
cet-6362	91	57	;	;	PUNCT
cet-6362	91	58	in	in	ADP
cet-6362	91	59	the	the	DET
cet-6362	91	60	latter	latter	ADJ
cet-6362	91	61	approach	approach	NOUN
cet-6362	91	62	,	,	PUNCT
cet-6362	91	63	instead	instead	ADV
cet-6362	91	64	,	,	PUNCT
cet-6362	91	65	the	the	DET
cet-6362	91	66	within	within	ADJ
cet-6362	91	67	-	-	PUNCT
cet-6362	91	68	hour	hour	NOUN
cet-6362	91	69	mean	mean	NOUN
cet-6362	91	70	(	(	PUNCT
cet-6362	91	71	xi	xi	ADJ
cet-6362	91	72	)	)	PUNCT
cet-6362	91	73	and	and	CCONJ
cet-6362	91	74	the	the	DET
cet-6362	91	75	standard	standard	ADJ
cet-6362	91	76	deviation	deviation	NOUN
cet-6362	91	77	(	(	PUNCT
cet-6362	91	78	si	si	NOUN
cet-6362	91	79	)	)	PUNCT
cet-6362	91	80	of	of	ADP
cet-6362	91	81	12	12	NUM
cet-6362	91	82	5	5	NUM
cet-6362	91	83	-	-	PUNCT
cet-6362	91	84	min	min	NOUN
cet-6362	91	85	wind	wind	NOUN
cet-6362	91	86	power	power	NOUN
cet-6362	91	87	data	datum	NOUN
cet-6362	91	88	have	have	AUX
cet-6362	91	89	been	be	AUX
cet-6362	91	90	computed	compute	VERB
cet-6362	91	91	,	,	PUNCT
cet-6362	91	92	and	and	CCONJ
cet-6362	91	93	then	then	ADV
cet-6362	91	94	one	one	NUM
cet-6362	91	95	-	-	PUNCT
cet-6362	91	96	standard	standard	ADJ
cet-6362	91	97	deviation	deviation	NOUN
cet-6362	91	98	intervals	interval	NOUN
cet-6362	91	99	have	have	AUX
cet-6362	91	100	been	be	AUX
cet-6362	91	101	obtained	obtain	VERB
cet-6362	91	102	as	as	ADP
cet-6362	91	103	[	[	X
cet-6362	91	104	xi	xi	X
cet-6362	91	105	si	si	PROPN
cet-6362	91	106	,	,	PUNCT
cet-6362	91	107	xi	xi	X
cet-6362	91	108	si	si	X
cet-6362	91	109	]	]	PUNCT
cet-6362	91	110	.	.	PUNCT
cet-6362	92	1	figure	figure	NOUN
cet-6362	92	2	2	2	NUM
cet-6362	92	3	:	:	PUNCT
cet-6362	92	4	the	the	DET
cet-6362	92	5	5	5	NUM
cet-6362	92	6	-	-	PUNCT
cet-6362	92	7	min	min	NOUN
cet-6362	92	8	wind	wind	NOUN
cet-6362	92	9	power	power	NOUN
cet-6362	92	10	data	datum	NOUN
cet-6362	92	11	set	set	VERB
cet-6362	92	12	used	use	VERB
cet-6362	92	13	in	in	ADP
cet-6362	92	14	this	this	DET
cet-6362	92	15	study	study	NOUN
cet-6362	92	16	:	:	PUNCT
cet-6362	92	17	first	first	ADJ
cet-6362	92	18	24	24	NUM
cet-6362	92	19	h	h	NOUN
cet-6362	92	20	the	the	DET
cet-6362	92	21	architecture	architecture	NOUN
cet-6362	92	22	of	of	ADP
cet-6362	92	23	the	the	DET
cet-6362	92	24	nn	nn	PROPN
cet-6362	92	25	consists	consist	VERB
cet-6362	92	26	of	of	ADP
cet-6362	92	27	one	one	NUM
cet-6362	92	28	input	input	NOUN
cet-6362	92	29	,	,	PUNCT
cet-6362	92	30	one	one	NUM
cet-6362	92	31	hidden	hide	VERB
cet-6362	92	32	and	and	CCONJ
cet-6362	92	33	one	one	NUM
cet-6362	92	34	output	output	NOUN
cet-6362	92	35	layers	layer	NOUN
cet-6362	92	36	.	.	PUNCT
cet-6362	93	1	the	the	DET
cet-6362	93	2	number	number	NOUN
cet-6362	93	3	of	of	ADP
cet-6362	93	4	input	input	NOUN
cet-6362	93	5	neurons	neuron	NOUN
cet-6362	93	6	is	be	AUX
cet-6362	93	7	1	1	NUM
cet-6362	93	8	,	,	PUNCT
cet-6362	93	9	since	since	SCONJ
cet-6362	93	10	the	the	DET
cet-6362	93	11	historical	historical	ADJ
cet-6362	93	12	wind	wind	NOUN
cet-6362	93	13	power	power	NOUN
cet-6362	93	14	value	value	NOUN
cet-6362	93	15	wt	wt	PROPN
cet-6362	93	16	1	1	NUM
cet-6362	93	17	is	be	AUX
cet-6362	93	18	used	use	VERB
cet-6362	93	19	as	as	ADP
cet-6362	93	20	input	input	NOUN
cet-6362	93	21	variable	variable	NOUN
cet-6362	93	22	for	for	ADP
cet-6362	93	23	predicting	predict	VERB
cet-6362	93	24	wt	wt	NOUN
cet-6362	93	25	in	in	ADP
cet-6362	93	26	output	output	NOUN
cet-6362	93	27	;	;	PUNCT
cet-6362	93	28	the	the	DET
cet-6362	93	29	number	number	NOUN
cet-6362	93	30	of	of	ADP
cet-6362	93	31	hidden	hide	VERB
cet-6362	93	32	neurons	neuron	NOUN
cet-6362	93	33	is	be	AUX
cet-6362	93	34	set	set	VERB
cet-6362	93	35	to	to	ADP
cet-6362	93	36	10	10	NUM
cet-6362	93	37	after	after	ADP
cet-6362	93	38	a	a	DET
cet-6362	93	39	trial	trial	NOUN
cet-6362	93	40	-	-	PUNCT
cet-6362	93	41	and	and	CCONJ
cet-6362	93	42	-	-	PUNCT
cet-6362	93	43	error	error	NOUN
cet-6362	93	44	process	process	NOUN
cet-6362	93	45	;	;	PUNCT
cet-6362	93	46	the	the	DET
cet-6362	93	47	number	number	NOUN
cet-6362	93	48	of	of	ADP
cet-6362	93	49	output	output	NOUN
cet-6362	93	50	neurons	neuron	NOUN
cet-6362	93	51	is	be	AUX
cet-6362	93	52	1	1	NUM
cet-6362	93	53	which	which	PRON
cet-6362	93	54	results	result	VERB
cet-6362	93	55	in	in	ADP
cet-6362	93	56	interval	interval	NOUN
cet-6362	93	57	-	-	PUNCT
cet-6362	93	58	valued	value	VERB
cet-6362	93	59	estimations	estimation	NOUN
cet-6362	93	60	.	.	PUNCT
cet-6362	94	1	as	as	ADP
cet-6362	94	2	activation	activation	NOUN
cet-6362	94	3	functions	function	NOUN
cet-6362	94	4	,	,	PUNCT
cet-6362	94	5	the	the	DET
cet-6362	94	6	hyperbolic	hyperbolic	ADJ
cet-6362	94	7	tangent	tangent	NOUN
cet-6362	94	8	function	function	NOUN
cet-6362	94	9	is	be	AUX
cet-6362	94	10	used	use	VERB
cet-6362	94	11	in	in	ADP
cet-6362	94	12	the	the	DET
cet-6362	94	13	hidden	hide	VERB
cet-6362	94	14	layer	layer	NOUN
cet-6362	94	15	and	and	CCONJ
cet-6362	94	16	the	the	DET
cet-6362	94	17	logarithmic	logarithmic	ADJ
cet-6362	94	18	sigmoid	sigmoid	NOUN
cet-6362	94	19	function	function	NOUN
cet-6362	94	20	is	be	AUX
cet-6362	94	21	used	use	VERB
cet-6362	94	22	at	at	ADP
cet-6362	94	23	the	the	DET
cet-6362	94	24	output	output	NOUN
cet-6362	94	25	layer	layer	NOUN
cet-6362	94	26	.	.	PUNCT
cet-6362	95	1	all	all	DET
cet-6362	95	2	data	datum	NOUN
cet-6362	95	3	have	have	AUX
cet-6362	95	4	been	be	AUX
cet-6362	95	5	normalized	normalize	VERB
cet-6362	95	6	within	within	ADP
cet-6362	95	7	the	the	DET
cet-6362	95	8	range	range	NOUN
cet-6362	95	9	[	[	X
cet-6362	95	10	0.1	0.1	NUM
cet-6362	95	11	,	,	PUNCT
cet-6362	95	12	0.9	0.9	NUM
cet-6362	95	13	]	]	PUNCT
cet-6362	95	14	.	.	PUNCT
cet-6362	96	1	in	in	ADP
cet-6362	96	2	nsga	nsga	PROPN
cet-6362	96	3	-	-	PUNCT
cet-6362	96	4	ii	ii	NOUN
cet-6362	96	5	,	,	PUNCT
cet-6362	96	6	the	the	DET
cet-6362	96	7	population	population	NOUN
cet-6362	96	8	size	size	NOUN
cet-6362	96	9	(	(	PUNCT
cet-6362	96	10	nc	nc	PROPN
cet-6362	96	11	)	)	PUNCT
cet-6362	96	12	is	be	AUX
cet-6362	96	13	set	set	VERB
cet-6362	96	14	to	to	ADP
cet-6362	96	15	50	50	NUM
cet-6362	96	16	and	and	CCONJ
cet-6362	96	17	the	the	DET
cet-6362	96	18	number	number	NOUN
cet-6362	96	19	of	of	ADP
cet-6362	96	20	generations	generation	NOUN
cet-6362	96	21	(	(	PUNCT
cet-6362	96	22	maxgen	maxgen	PROPN
cet-6362	96	23	)	)	PUNCT
cet-6362	96	24	to	to	ADP
cet-6362	96	25	500	500	NUM
cet-6362	96	26	;	;	PUNCT
cet-6362	96	27	this	this	DET
cet-6362	96	28	latter	latter	NOUN
cet-6362	96	29	is	be	AUX
cet-6362	96	30	used	use	VERB
cet-6362	96	31	as	as	ADP
cet-6362	96	32	termination	termination	NOUN
cet-6362	96	33	condition	condition	NOUN
cet-6362	96	34	.	.	PUNCT
cet-6362	97	1	to	to	PART
cet-6362	97	2	account	account	VERB
cet-6362	97	3	for	for	ADP
cet-6362	97	4	the	the	DET
cet-6362	97	5	inherent	inherent	ADJ
cet-6362	97	6	randomness	randomness	NOUN
cet-6362	97	7	of	of	ADP
cet-6362	97	8	nsga	nsga	NOUN
cet-6362	97	9	-	-	PUNCT
cet-6362	97	10	ii	ii	NOUN
cet-6362	97	11	,	,	PUNCT
cet-6362	97	12	five	five	NUM
cet-6362	97	13	different	different	ADJ
cet-6362	97	14	runs	run	NOUN
cet-6362	97	15	have	have	AUX
cet-6362	97	16	been	be	AUX
cet-6362	97	17	performed	perform	VERB
cet-6362	97	18	and	and	CCONJ
cet-6362	97	19	an	an	DET
cet-6362	97	20	overall	overall	ADJ
cet-6362	97	21	best	good	ADJ
cet-6362	97	22	non	non	ADJ
cet-6362	97	23	-	-	ADJ
cet-6362	97	24	dominated	dominated	ADJ
cet-6362	97	25	pareto	pareto	ADJ
cet-6362	97	26	front	front	NOUN
cet-6362	97	27	has	have	AUX
cet-6362	97	28	been	be	AUX
cet-6362	97	29	obtained	obtain	VERB
cet-6362	97	30	from	from	ADP
cet-6362	97	31	the	the	DET
cet-6362	97	32	five	five	NUM
cet-6362	97	33	individual	individual	ADJ
cet-6362	97	34	fronts	front	NOUN
cet-6362	97	35	.	.	PUNCT
cet-6362	98	1	figure	figure	NOUN
cet-6362	98	2	3	3	NUM
cet-6362	98	3	illustrates	illustrate	VERB
cet-6362	98	4	the	the	DET
cet-6362	98	5	first	first	ADJ
cet-6362	98	6	(	(	PUNCT
cet-6362	98	7	best	good	ADJ
cet-6362	98	8	)	)	PUNCT
cet-6362	98	9	pareto	pareto	ADJ
cet-6362	98	10	front	front	NOUN
cet-6362	98	11	found	find	VERB
cet-6362	98	12	after	after	ADP
cet-6362	98	13	training	train	VERB
cet-6362	98	14	the	the	DET
cet-6362	98	15	nn	nn	PROPN
cet-6362	98	16	on	on	ADP
cet-6362	98	17	interval	interval	NOUN
cet-6362	98	18	data	datum	NOUN
cet-6362	98	19	constructed	construct	VERB
cet-6362	98	20	by	by	ADP
cet-6362	98	21	the	the	DET
cet-6362	98	22	min928	min928	PROPN
cet-6362	98	23	max	max	PROPN
cet-6362	98	24	approach	approach	NOUN
cet-6362	98	25	(	(	PUNCT
cet-6362	98	26	a	a	NOUN
cet-6362	98	27	)	)	PUNCT
cet-6362	98	28	and	and	CCONJ
cet-6362	98	29	mean	mean	VERB
cet-6362	98	30	approach	approach	NOUN
cet-6362	98	31	(	(	PUNCT
cet-6362	98	32	b	b	NOUN
cet-6362	98	33	)	)	PUNCT
cet-6362	98	34	.	.	PUNCT
cet-6362	99	1	given	give	VERB
cet-6362	99	2	the	the	DET
cet-6362	99	3	overall	overall	ADJ
cet-6362	99	4	best	good	ADJ
cet-6362	99	5	pareto	pareto	ADJ
cet-6362	99	6	set	set	NOUN
cet-6362	99	7	of	of	ADP
cet-6362	99	8	optimal	optimal	ADJ
cet-6362	99	9	solutions	solution	NOUN
cet-6362	99	10	(	(	PUNCT
cet-6362	99	11	i.e.	i.e.	X
cet-6362	99	12	optimal	optimal	ADJ
cet-6362	99	13	nn	nn	X
cet-6362	99	14	weights	weight	NOUN
cet-6362	99	15	)	)	PUNCT
cet-6362	99	16	,	,	PUNCT
cet-6362	99	17	one	one	PRON
cet-6362	99	18	has	have	VERB
cet-6362	99	19	to	to	PART
cet-6362	99	20	select	select	VERB
cet-6362	99	21	one	one	NUM
cet-6362	99	22	(	(	PUNCT
cet-6362	99	23	i.e.	i.e.	X
cet-6362	99	24	one	one	NUM
cet-6362	99	25	trained	train	VERB
cet-6362	99	26	nn	nn	NOUN
cet-6362	99	27	)	)	PUNCT
cet-6362	99	28	for	for	ADP
cet-6362	99	29	use	use	NOUN
cet-6362	99	30	.	.	PUNCT
cet-6362	100	1	for	for	ADP
cet-6362	100	2	both	both	DET
cet-6362	100	3	interval	interval	NOUN
cet-6362	100	4	construction	construction	NOUN
cet-6362	100	5	approaches	approach	NOUN
cet-6362	100	6	,	,	PUNCT
cet-6362	100	7	the	the	DET
cet-6362	100	8	solution	solution	NOUN
cet-6362	100	9	has	have	AUX
cet-6362	100	10	been	be	AUX
cet-6362	100	11	chosen	choose	VERB
cet-6362	100	12	as	as	ADP
cet-6362	100	13	the	the	DET
cet-6362	100	14	one	one	NOUN
cet-6362	100	15	with	with	ADP
cet-6362	100	16	smallest	small	ADJ
cet-6362	100	17	nmpiw	nmpiw	NOUN
cet-6362	100	18	among	among	ADP
cet-6362	100	19	those	those	PRON
cet-6362	100	20	with	with	ADP
cet-6362	100	21	picp	picp	PROPN
cet-6362	100	22	0.9	0.9	NUM
cet-6362	100	23	:	:	PUNCT
cet-6362	100	24	90	90	NUM
cet-6362	100	25	%	%	NOUN
cet-6362	100	26	cp	cp	INTJ
cet-6362	100	27	and	and	CCONJ
cet-6362	100	28	interval	interval	NOUN
cet-6362	100	29	width	width	NOUN
cet-6362	100	30	of	of	ADP
cet-6362	100	31	0.494	0.494	NUM
cet-6362	100	32	for	for	ADP
cet-6362	100	33	min	min	NOUN
cet-6362	100	34	-	-	PUNCT
cet-6362	100	35	max	max	NOUN
cet-6362	100	36	,	,	PUNCT
cet-6362	100	37	and	and	CCONJ
cet-6362	100	38	91	91	NUM
cet-6362	100	39	%	%	NOUN
cet-6362	100	40	cp	cp	INTJ
cet-6362	100	41	with	with	ADP
cet-6362	100	42	0.439	0.439	NUM
cet-6362	100	43	interval	interval	NOUN
cet-6362	100	44	width	width	NOUN
cet-6362	100	45	for	for	ADP
cet-6362	100	46	the	the	DET
cet-6362	100	47	mean	mean	ADJ
cet-6362	100	48	approach	approach	NOUN
cet-6362	100	49	.	.	PUNCT
cet-6362	101	1	the	the	DET
cet-6362	101	2	results	result	NOUN
cet-6362	101	3	on	on	ADP
cet-6362	101	4	the	the	DET
cet-6362	101	5	test	test	NOUN
cet-6362	101	6	dataset	dataset	NOUN
cet-6362	101	7	give	give	VERB
cet-6362	101	8	a	a	DET
cet-6362	101	9	coverage	coverage	NOUN
cet-6362	101	10	probability	probability	NOUN
cet-6362	101	11	of	of	ADP
cet-6362	101	12	82	82	NUM
cet-6362	101	13	%	%	NOUN
cet-6362	101	14	and	and	CCONJ
cet-6362	101	15	an	an	DET
cet-6362	101	16	interval	interval	NOUN
cet-6362	101	17	width	width	NOUN
cet-6362	101	18	of	of	ADP
cet-6362	101	19	0.357	0.357	NUM
cet-6362	101	20	for	for	ADP
cet-6362	101	21	the	the	DET
cet-6362	101	22	min	min	PROPN
cet-6362	101	23	-	-	ADJ
cet-6362	101	24	max	max	PROPN
cet-6362	101	25	approach	approach	NOUN
cet-6362	101	26	,	,	PUNCT
cet-6362	101	27	and	and	CCONJ
cet-6362	101	28	80	80	NUM
cet-6362	101	29	%	%	NOUN
cet-6362	101	30	cp	cp	INTJ
cet-6362	101	31	with	with	ADP
cet-6362	101	32	0.380	0.380	NUM
cet-6362	101	33	interval	interval	NOUN
cet-6362	101	34	width	width	NOUN
cet-6362	101	35	for	for	ADP
cet-6362	101	36	the	the	DET
cet-6362	101	37	mean	mean	ADJ
cet-6362	101	38	approach	approach	NOUN
cet-6362	101	39	.	.	PUNCT
cet-6362	102	1	figure	figure	NOUN
cet-6362	102	2	4	4	NUM
cet-6362	102	3	shows	show	VERB
cet-6362	102	4	the	the	DET
cet-6362	102	5	prediction	prediction	NOUN
cet-6362	102	6	intervals	interval	NOUN
cet-6362	102	7	estimated	estimate	VERB
cet-6362	102	8	on	on	ADP
cet-6362	102	9	the	the	DET
cet-6362	102	10	test	test	NOUN
cet-6362	102	11	data	datum	NOUN
cet-6362	102	12	set	set	VERB
cet-6362	102	13	by	by	ADP
cet-6362	102	14	the	the	DET
cet-6362	102	15	trained	train	VERB
cet-6362	102	16	nn	nn	PROPN
cet-6362	102	17	corresponding	correspond	VERB
cet-6362	102	18	to	to	ADP
cet-6362	102	19	the	the	DET
cet-6362	102	20	pareto	pareto	ADJ
cet-6362	102	21	solution	solution	NOUN
cet-6362	102	22	,	,	PUNCT
cet-6362	102	23	for	for	ADP
cet-6362	102	24	the	the	DET
cet-6362	102	25	min	min	PROPN
cet-6362	102	26	-	-	ADJ
cet-6362	102	27	max	max	PROPN
cet-6362	102	28	approach	approach	NOUN
cet-6362	102	29	.	.	PUNCT
cet-6362	103	1	(	(	PUNCT
cet-6362	103	2	a	a	X
cet-6362	103	3	)	)	PUNCT
cet-6362	103	4	(	(	PUNCT
cet-6362	103	5	b	b	X
cet-6362	103	6	)	)	PUNCT
cet-6362	103	7	figure	figure	NOUN
cet-6362	103	8	3	3	NUM
cet-6362	103	9	:	:	PUNCT
cet-6362	103	10	the	the	DET
cet-6362	103	11	overall	overall	ADJ
cet-6362	103	12	best	good	ADJ
cet-6362	103	13	pareto	pareto	ADJ
cet-6362	103	14	front	front	NOUN
cet-6362	103	15	obtained	obtain	VERB
cet-6362	103	16	by	by	ADP
cet-6362	103	17	training	train	VERB
cet-6362	103	18	the	the	DET
cet-6362	103	19	nn	nn	PROPN
cet-6362	103	20	for	for	ADP
cet-6362	103	21	1h	1h	NUM
cet-6362	103	22	-	-	PUNCT
cet-6362	103	23	ahead	ahead	NOUN
cet-6362	103	24	wind	wind	NOUN
cet-6362	103	25	power	power	NOUN
cet-6362	103	26	prediction	prediction	NOUN
cet-6362	103	27	:	:	PUNCT
cet-6362	103	28	(	(	PUNCT
cet-6362	103	29	a	a	X
cet-6362	103	30	)	)	PUNCT
cet-6362	103	31	min	min	ADJ
cet-6362	103	32	-	-	PUNCT
cet-6362	103	33	max	max	PROPN
cet-6362	103	34	approach	approach	NOUN
cet-6362	103	35	(	(	PUNCT
cet-6362	103	36	b	b	NOUN
cet-6362	103	37	)	)	PUNCT
cet-6362	103	38	mean	mean	VERB
cet-6362	103	39	approach	approach	NOUN
cet-6362	103	40	figure	figure	NOUN
cet-6362	103	41	4	4	NUM
cet-6362	103	42	:	:	PUNCT
cet-6362	103	43	estimated	estimate	VERB
cet-6362	103	44	pis	pis	NOUN
cet-6362	103	45	for	for	ADP
cet-6362	103	46	1h	1h	NUM
cet-6362	103	47	ahead	ahead	ADV
cet-6362	103	48	wind	wind	NOUN
cet-6362	103	49	power	power	NOUN
cet-6362	103	50	prediction	prediction	NOUN
cet-6362	103	51	on	on	ADP
cet-6362	103	52	the	the	DET
cet-6362	103	53	test	test	NOUN
cet-6362	103	54	data	datum	NOUN
cet-6362	103	55	set	set	VERB
cet-6362	103	56	(	(	PUNCT
cet-6362	103	57	solid	solid	ADJ
cet-6362	103	58	lines	line	NOUN
cet-6362	103	59	)	)	PUNCT
cet-6362	103	60	,	,	PUNCT
cet-6362	103	61	and	and	CCONJ
cet-6362	103	62	intervalvalued	intervalvalue	VERB
cet-6362	103	63	wind	wind	NOUN
cet-6362	103	64	power	power	NOUN
cet-6362	103	65	data	datum	NOUN
cet-6362	103	66	(	(	PUNCT
cet-6362	103	67	constructed	construct	VERB
cet-6362	103	68	by	by	ADP
cet-6362	103	69	the	the	DET
cet-6362	103	70	min	min	PROPN
cet-6362	103	71	-	-	ADJ
cet-6362	103	72	max	max	PROPN
cet-6362	103	73	approach	approach	NOUN
cet-6362	103	74	)	)	PUNCT
cet-6362	103	75	included	include	VERB
cet-6362	103	76	in	in	ADP
cet-6362	103	77	the	the	DET
cet-6362	103	78	test	test	NOUN
cet-6362	103	79	data	datum	NOUN
cet-6362	103	80	set	set	VERB
cet-6362	103	81	(	(	PUNCT
cet-6362	103	82	dashed	dash	VERB
cet-6362	103	83	line	line	NOUN
cet-6362	103	84	)	)	PUNCT
cet-6362	103	85	from	from	ADP
cet-6362	103	86	the	the	DET
cet-6362	103	87	results	result	NOUN
cet-6362	103	88	illustrated	illustrate	VERB
cet-6362	103	89	in	in	ADP
cet-6362	103	90	figure	figure	NOUN
cet-6362	103	91	4	4	NUM
cet-6362	103	92	,	,	PUNCT
cet-6362	103	93	one	one	PRON
cet-6362	103	94	might	might	AUX
cet-6362	103	95	say	say	VERB
cet-6362	103	96	that	that	DET
cet-6362	103	97	pis	pis	NOUN
cet-6362	103	98	obtained	obtain	VERB
cet-6362	103	99	via	via	ADP
cet-6362	103	100	the	the	DET
cet-6362	103	101	min	min	PROPN
cet-6362	103	102	-	-	ADJ
cet-6362	103	103	max	max	ADJ
cet-6362	103	104	approach	approach	NOUN
cet-6362	103	105	are	be	AUX
cet-6362	103	106	capable	capable	ADJ
cet-6362	103	107	of	of	ADP
cet-6362	103	108	capturing	capture	VERB
cet-6362	103	109	the	the	DET
cet-6362	103	110	peak	peak	NOUN
cet-6362	103	111	points	point	NOUN
cet-6362	103	112	(	(	PUNCT
cet-6362	103	113	highest	high	ADJ
cet-6362	103	114	and	and	CCONJ
cet-6362	103	115	lowest	low	ADJ
cet-6362	103	116	)	)	PUNCT
cet-6362	103	117	of	of	ADP
cet-6362	103	118	the	the	DET
cet-6362	103	119	target	target	NOUN
cet-6362	103	120	output	output	NOUN
cet-6362	103	121	.	.	PUNCT
cet-6362	104	1	the	the	DET
cet-6362	104	2	drop	drop	NOUN
cet-6362	104	3	of	of	ADP
cet-6362	104	4	coverage	coverage	NOUN
cet-6362	104	5	probability	probability	NOUN
cet-6362	104	6	from	from	ADP
cet-6362	104	7	90	90	NUM
cet-6362	104	8	%	%	NOUN
cet-6362	104	9	in	in	ADP
cet-6362	104	10	the	the	DET
cet-6362	104	11	training	training	NOUN
cet-6362	104	12	to	to	ADP
cet-6362	104	13	82	82	NUM
cet-6362	104	14	%	%	NOUN
cet-6362	104	15	in	in	ADP
cet-6362	104	16	the	the	DET
cet-6362	104	17	testing	testing	NOUN
cet-6362	104	18	dataset	dataset	NOUN
cet-6362	104	19	,	,	PUNCT
cet-6362	104	20	which	which	PRON
cet-6362	104	21	results	result	VERB
cet-6362	104	22	in	in	ADP
cet-6362	104	23	tighter	tight	ADJ
cet-6362	104	24	interval	interval	NOUN
cet-6362	104	25	widths	width	NOUN
cet-6362	104	26	,	,	PUNCT
cet-6362	104	27	can	can	AUX
cet-6362	104	28	be	be	AUX
cet-6362	104	29	due	due	ADJ
cet-6362	104	30	to	to	ADP
cet-6362	104	31	the	the	DET
cet-6362	104	32	particular	particular	ADJ
cet-6362	104	33	nature	nature	NOUN
cet-6362	104	34	of	of	ADP
cet-6362	104	35	the	the	DET
cet-6362	104	36	data	datum	NOUN
cet-6362	104	37	at	at	ADP
cet-6362	104	38	hand	hand	NOUN
cet-6362	104	39	showing	show	VERB
cet-6362	104	40	a	a	DET
cet-6362	104	41	remarkable	remarkable	ADJ
cet-6362	104	42	variability	variability	NOUN
cet-6362	104	43	in	in	ADP
cet-6362	104	44	the	the	DET
cet-6362	104	45	test	test	NOUN
cet-6362	104	46	data	datum	NOUN
cet-6362	104	47	with	with	ADP
cet-6362	104	48	respect	respect	NOUN
cet-6362	104	49	to	to	ADP
cet-6362	104	50	the	the	DET
cet-6362	104	51	training	training	NOUN
cet-6362	104	52	data	datum	NOUN
cet-6362	104	53	.	.	PUNCT
cet-6362	105	1	another	another	DET
cet-6362	105	2	reason	reason	NOUN
cet-6362	105	3	could	could	AUX
cet-6362	105	4	be	be	AUX
cet-6362	105	5	the	the	DET
cet-6362	105	6	insufficient	insufficient	ADJ
cet-6362	105	7	number	number	NOUN
cet-6362	105	8	of	of	ADP
cet-6362	105	9	observations	observation	NOUN
cet-6362	105	10	in	in	ADP
cet-6362	105	11	the	the	DET
cet-6362	105	12	training	training	NOUN
cet-6362	105	13	and	and	CCONJ
cet-6362	105	14	testing	testing	NOUN
cet-6362	105	15	samples	sample	NOUN
cet-6362	105	16	.	.	PUNCT
cet-6362	106	1	these	these	DET
cet-6362	106	2	claims	claim	NOUN
cet-6362	106	3	should	should	AUX
cet-6362	106	4	be	be	AUX
cet-6362	106	5	confirmed	confirm	VERB
cet-6362	106	6	by	by	ADP
cet-6362	106	7	using	use	VERB
cet-6362	106	8	larger	large	ADJ
cet-6362	106	9	experimental	experimental	ADJ
cet-6362	106	10	sets	set	NOUN
cet-6362	106	11	of	of	ADP
cet-6362	106	12	data	datum	NOUN
cet-6362	106	13	.	.	PUNCT
cet-6362	107	1	929	929	NUM
cet-6362	107	2	5	5	NUM
cet-6362	107	3	.	.	PUNCT
cet-6362	108	1	conclusion	conclusion	NOUN
cet-6362	108	2	variations	variation	NOUN
cet-6362	108	3	in	in	ADP
cet-6362	108	4	the	the	DET
cet-6362	108	5	generated	generate	VERB
cet-6362	108	6	power	power	NOUN
cet-6362	108	7	due	due	ADP
cet-6362	108	8	to	to	ADP
cet-6362	108	9	variability	variability	NOUN
cet-6362	108	10	in	in	ADP
cet-6362	108	11	wind	wind	NOUN
cet-6362	108	12	turbines	turbine	NOUN
cet-6362	108	13	power	power	NOUN
cet-6362	108	14	generation	generation	NOUN
cet-6362	108	15	can	can	AUX
cet-6362	108	16	lead	lead	VERB
cet-6362	108	17	to	to	ADP
cet-6362	108	18	serious	serious	ADJ
cet-6362	108	19	problems	problem	NOUN
cet-6362	108	20	,	,	PUNCT
cet-6362	108	21	especially	especially	ADV
cet-6362	108	22	in	in	ADP
cet-6362	108	23	the	the	DET
cet-6362	108	24	day	day	NOUN
cet-6362	108	25	-	-	PUNCT
cet-6362	108	26	ahead	ahead	NOUN
cet-6362	108	27	commitments	commitment	NOUN
cet-6362	108	28	of	of	ADP
cet-6362	108	29	generation	generation	NOUN
cet-6362	108	30	resources	resource	NOUN
cet-6362	108	31	to	to	PART
cet-6362	108	32	meet	meet	VERB
cet-6362	108	33	the	the	DET
cet-6362	108	34	electric	electric	ADJ
cet-6362	108	35	demand	demand	NOUN
cet-6362	108	36	.	.	PUNCT
cet-6362	109	1	in	in	ADP
cet-6362	109	2	the	the	DET
cet-6362	109	3	work	work	NOUN
cet-6362	109	4	presented	present	VERB
cet-6362	109	5	in	in	ADP
cet-6362	109	6	this	this	DET
cet-6362	109	7	paper	paper	NOUN
cet-6362	109	8	,	,	PUNCT
cet-6362	109	9	we	we	PRON
cet-6362	109	10	have	have	AUX
cet-6362	109	11	represented	represent	VERB
cet-6362	109	12	by	by	ADP
cet-6362	109	13	intervals	interval	NOUN
cet-6362	109	14	the	the	DET
cet-6362	109	15	wind	wind	NOUN
cet-6362	109	16	power	power	NOUN
cet-6362	109	17	variability	variability	NOUN
cet-6362	109	18	in	in	ADP
cet-6362	109	19	a	a	DET
cet-6362	109	20	given	give	VERB
cet-6362	109	21	time	time	NOUN
cet-6362	109	22	horizon	horizon	NOUN
cet-6362	109	23	,	,	PUNCT
cet-6362	109	24	1	1	NUM
cet-6362	109	25	h	h	NOUN
cet-6362	109	26	in	in	ADP
cet-6362	109	27	our	our	PRON
cet-6362	109	28	case	case	NOUN
cet-6362	109	29	.	.	PUNCT
cet-6362	110	1	the	the	DET
cet-6362	110	2	goal	goal	NOUN
cet-6362	110	3	is	be	AUX
cet-6362	110	4	to	to	PART
cet-6362	110	5	contribute	contribute	VERB
cet-6362	110	6	to	to	ADP
cet-6362	110	7	the	the	DET
cet-6362	110	8	understanding	understanding	NOUN
cet-6362	110	9	,	,	PUNCT
cet-6362	110	10	representation	representation	NOUN
cet-6362	110	11	and	and	CCONJ
cet-6362	110	12	analysis	analysis	NOUN
cet-6362	110	13	of	of	ADP
cet-6362	110	14	the	the	DET
cet-6362	110	15	uncertainty	uncertainty	NOUN
cet-6362	110	16	associated	associate	VERB
cet-6362	110	17	to	to	ADP
cet-6362	110	18	wind	wind	NOUN
cet-6362	110	19	power	power	NOUN
cet-6362	110	20	generation	generation	NOUN
cet-6362	110	21	prediction	prediction	NOUN
cet-6362	110	22	.	.	PUNCT
cet-6362	111	1	the	the	DET
cet-6362	111	2	original	original	ADJ
cet-6362	111	3	contributions	contribution	NOUN
cet-6362	111	4	of	of	ADP
cet-6362	111	5	the	the	DET
cet-6362	111	6	work	work	NOUN
cet-6362	111	7	are	be	AUX
cet-6362	111	8	to	to	PART
cet-6362	111	9	handle	handle	VERB
cet-6362	111	10	the	the	DET
cet-6362	111	11	prediction	prediction	NOUN
cet-6362	111	12	problem	problem	NOUN
cet-6362	111	13	with	with	ADP
cet-6362	111	14	uncertain	uncertain	ADJ
cet-6362	111	15	inputs	input	NOUN
cet-6362	111	16	in	in	ADP
cet-6362	111	17	a	a	DET
cet-6362	111	18	multi	multi	ADJ
cet-6362	111	19	-	-	ADJ
cet-6362	111	20	objective	objective	ADJ
cet-6362	111	21	framework	framework	NOUN
cet-6362	111	22	.	.	PUNCT
cet-6362	112	1	in	in	ADP
cet-6362	112	2	fact	fact	NOUN
cet-6362	112	3	,	,	PUNCT
cet-6362	112	4	rather	rather	ADV
cet-6362	112	5	than	than	ADP
cet-6362	112	6	optimizing	optimize	VERB
cet-6362	112	7	parameters	parameter	NOUN
cet-6362	112	8	and	and	CCONJ
cet-6362	112	9	subsequently	subsequently	ADV
cet-6362	112	10	obtaining	obtain	VERB
cet-6362	112	11	the	the	DET
cet-6362	112	12	outputs	output	NOUN
cet-6362	112	13	,	,	PUNCT
cet-6362	112	14	we	we	PRON
cet-6362	112	15	directly	directly	ADV
cet-6362	112	16	map	map	VERB
cet-6362	112	17	the	the	DET
cet-6362	112	18	interval	interval	NOUN
cet-6362	112	19	inputs	input	NOUN
cet-6362	112	20	into	into	ADP
cet-6362	112	21	pis	pis	PROPN
cet-6362	112	22	(	(	PUNCT
cet-6362	112	23	interval	interval	NOUN
cet-6362	112	24	outputs	output	NOUN
cet-6362	112	25	)	)	PUNCT
cet-6362	112	26	,	,	PUNCT
cet-6362	112	27	which	which	PRON
cet-6362	112	28	are	be	AUX
cet-6362	112	29	optimal	optimal	ADJ
cet-6362	112	30	both	both	PRON
cet-6362	112	31	in	in	ADP
cet-6362	112	32	terms	term	NOUN
cet-6362	112	33	of	of	ADP
cet-6362	112	34	coverage	coverage	NOUN
cet-6362	112	35	and	and	CCONJ
cet-6362	112	36	width	width	NOUN
cet-6362	112	37	.	.	PUNCT
cet-6362	113	1	moreover	moreover	ADV
cet-6362	113	2	,	,	PUNCT
cet-6362	113	3	we	we	PRON
cet-6362	113	4	explore	explore	VERB
cet-6362	113	5	two	two	NUM
cet-6362	113	6	different	different	ADJ
cet-6362	113	7	approaches	approach	NOUN
cet-6362	113	8	to	to	PART
cet-6362	113	9	represent	represent	VERB
cet-6362	113	10	input	input	NOUN
cet-6362	113	11	variability	variability	NOUN
cet-6362	113	12	,	,	PUNCT
cet-6362	113	13	and	and	CCONJ
cet-6362	113	14	to	to	PART
cet-6362	113	15	quantify	quantify	VERB
cet-6362	113	16	potential	potential	ADJ
cet-6362	113	17	uncertainties	uncertainty	NOUN
cet-6362	113	18	in	in	ADP
cet-6362	113	19	the	the	DET
cet-6362	113	20	outputs	output	NOUN
cet-6362	113	21	.	.	PUNCT
cet-6362	114	1	the	the	DET
cet-6362	114	2	results	result	NOUN
cet-6362	114	3	obtained	obtain	VERB
cet-6362	114	4	show	show	NOUN
cet-6362	114	5	that	that	SCONJ
cet-6362	114	6	nns	nn	NOUN
cet-6362	114	7	are	be	AUX
cet-6362	114	8	promising	promise	VERB
cet-6362	114	9	for	for	ADP
cet-6362	114	10	handling	handle	VERB
cet-6362	114	11	interval	interval	NOUN
cet-6362	114	12	input	input	NOUN
cet-6362	114	13	data	datum	NOUN
cet-6362	114	14	accounting	account	VERB
cet-6362	114	15	for	for	ADP
cet-6362	114	16	uncertainties	uncertainty	NOUN
cet-6362	114	17	.	.	PUNCT
cet-6362	115	1	as	as	ADP
cet-6362	115	2	for	for	ADP
cet-6362	115	3	future	future	ADJ
cet-6362	115	4	research	research	NOUN
cet-6362	115	5	,	,	PUNCT
cet-6362	115	6	the	the	DET
cet-6362	115	7	use	use	NOUN
cet-6362	115	8	of	of	ADP
cet-6362	115	9	different	different	ADJ
cet-6362	115	10	approaches	approach	NOUN
cet-6362	115	11	for	for	ADP
cet-6362	115	12	better	well	ADJ
cet-6362	115	13	interval	interval	NOUN
cet-6362	115	14	representation	representation	NOUN
cet-6362	115	15	of	of	ADP
cet-6362	115	16	wind	wind	NOUN
cet-6362	115	17	power	power	NOUN
cet-6362	115	18	data	datum	NOUN
cet-6362	115	19	will	will	AUX
cet-6362	115	20	be	be	AUX
cet-6362	115	21	explored	explore	VERB
cet-6362	115	22	to	to	PART
cet-6362	115	23	further	far	ADV
cet-6362	115	24	increase	increase	VERB
cet-6362	115	25	the	the	DET
cet-6362	115	26	accuracy	accuracy	NOUN
cet-6362	115	27	of	of	ADP
cet-6362	115	28	the	the	DET
cet-6362	115	29	predictions	prediction	NOUN
cet-6362	115	30	.	.	PUNCT
cet-6362	116	1	the	the	DET
cet-6362	116	2	extension	extension	NOUN
cet-6362	116	3	of	of	ADP
cet-6362	116	4	the	the	DET
cet-6362	116	5	approach	approach	NOUN
cet-6362	116	6	for	for	ADP
cet-6362	116	7	other	other	ADJ
cet-6362	116	8	engineering	engineering	NOUN
cet-6362	116	9	applications	application	NOUN
cet-6362	116	10	will	will	AUX
cet-6362	116	11	also	also	ADV
cet-6362	116	12	be	be	AUX
cet-6362	116	13	pursued	pursue	VERB
cet-6362	116	14	.	.	PUNCT
cet-6362	117	1	references	reference	NOUN
cet-6362	117	2	aemo	aemo	VERB
cet-6362	117	3	(	(	PUNCT
cet-6362	117	4	australian	australian	ADJ
cet-6362	117	5	energy	energy	NOUN
cet-6362	117	6	market	market	NOUN
cet-6362	117	7	operator	operator	NOUN
cet-6362	117	8	)	)	PUNCT
cet-6362	117	9	,	,	PUNCT
cet-6362	117	10	2012	2012	NUM
cet-6362	117	11	,	,	PUNCT
cet-6362	117	12	wind	wind	NOUN
cet-6362	117	13	generation	generation	NOUN
cet-6362	117	14	data	datum	NOUN
cet-6362	117	15	,	,	PUNCT
cet-6362	117	16	<	<	X
cet-6362	117	17	www.aemo.com.au/electricity/	www.aemo.com.au/electricity/	PROPN
cet-6362	117	18	data	data	NOUN
cet-6362	117	19	/	/	SYM
cet-6362	117	20	market	market	NOUN
cet-6362	117	21	-	-	PUNCT
cet-6362	117	22	management	management	NOUN
cet-6362	117	23	-	-	PUNCT
cet-6362	117	24	system	system	NOUN
cet-6362	117	25	-	-	PUNCT
cet-6362	117	26	mms	mms	ADJ
cet-6362	117	27	/	/	SYM
cet-6362	117	28	generation	generation	NOUN
cet-6362	117	29	-	-	PUNCT
cet-6362	117	30	and	and	CCONJ
cet-6362	117	31	-	-	PUNCT
cet-6362	117	32	load	load	NOUN
cet-6362	117	33	>	>	X
cet-6362	117	34	accessed	access	VERB
cet-6362	117	35	14.11.2012	14.11.2012	NUM
cet-6362	117	36	.	.	PUNCT
cet-6362	118	1	ak	ak	PROPN
cet-6362	118	2	r.	r.	PROPN
cet-6362	118	3	,	,	PUNCT
cet-6362	118	4	li	li	PROPN
cet-6362	118	5	y.	y.	PROPN
cet-6362	118	6	,	,	PUNCT
cet-6362	118	7	vitelli	vitelli	PROPN
cet-6362	118	8	v.	v.	PROPN
cet-6362	118	9	,	,	PUNCT
cet-6362	118	10	zio	zio	PROPN
cet-6362	118	11	e.	e.	PROPN
cet-6362	118	12	,	,	PUNCT
cet-6362	118	13	droguett	droguett	PROPN
cet-6362	118	14	e.	e.	PROPN
cet-6362	118	15	l.	l.	PROPN
cet-6362	118	16	,	,	PUNCT
cet-6362	118	17	jacinto	jacinto	PROPN
cet-6362	118	18	c.	c.	PROPN
cet-6362	118	19	m.	m.	PROPN
cet-6362	118	20	c.	c.	PROPN
cet-6362	118	21	,	,	PUNCT
cet-6362	118	22	2013	2013	NUM
cet-6362	118	23	,	,	PUNCT
cet-6362	118	24	nsga	nsga	NOUN
cet-6362	118	25	-	-	PUNCT
cet-6362	118	26	ii	ii	NOUN
cet-6362	118	27	-	-	PUNCT
cet-6362	118	28	trained	train	VERB
cet-6362	118	29	neural	neural	ADJ
cet-6362	118	30	network	network	NOUN
cet-6362	118	31	approach	approach	NOUN
cet-6362	118	32	to	to	ADP
cet-6362	118	33	the	the	DET
cet-6362	118	34	estimation	estimation	NOUN
cet-6362	118	35	of	of	ADP
cet-6362	118	36	prediction	prediction	NOUN
cet-6362	118	37	intervals	interval	NOUN
cet-6362	118	38	of	of	ADP
cet-6362	118	39	scale	scale	NOUN
cet-6362	118	40	deposition	deposition	NOUN
cet-6362	118	41	rate	rate	NOUN
cet-6362	118	42	in	in	ADP
cet-6362	118	43	oil	oil	NOUN
cet-6362	118	44	&	&	CCONJ
cet-6362	118	45	gas	gas	NOUN
cet-6362	118	46	equipment	equipment	NOUN
cet-6362	118	47	,	,	PUNCT
cet-6362	118	48	expert	expert	NOUN
cet-6362	118	49	systems	system	NOUN
cet-6362	118	50	with	with	ADP
cet-6362	118	51	applications	application	NOUN
cet-6362	118	52	,	,	PUNCT
cet-6362	118	53	40	40	NUM
cet-6362	118	54	(	(	PUNCT
cet-6362	118	55	4	4	NUM
cet-6362	118	56	)	)	PUNCT
cet-6362	118	57	,	,	PUNCT
cet-6362	118	58	1205	1205	NUM
cet-6362	118	59	-	-	SYM
cet-6362	118	60	1212	1212	NUM
cet-6362	118	61	.	.	PUNCT
cet-6362	119	1	gdf	gdf	PROPN
cet-6362	119	2	suez	suez	PROPN
cet-6362	119	3	australian	australian	ADJ
cet-6362	119	4	energy	energy	NOUN
cet-6362	119	5	,	,	PUNCT
cet-6362	119	6	canunda	canunda	NOUN
cet-6362	119	7	wind	wind	NOUN
cet-6362	119	8	farm	farm	NOUN
cet-6362	119	9	brochure	brochure	NOUN
cet-6362	119	10	,	,	PUNCT
cet-6362	119	11	2010	2010	NUM
cet-6362	119	12	,	,	PUNCT
cet-6362	119	13	<	<	X
cet-6362	119	14	www.gdfsuezau.com/uploads/2010/	www.gdfsuezau.com/uploads/2010/	NOUN
cet-6362	119	15	01	01	NUM
cet-6362	119	16	/	/	SYM
cet-6362	119	17	canundabrochure4ppv2.pdf	canundabrochure4ppv2.pdf	PROPN
cet-6362	119	18	>	>	VERB
cet-6362	119	19	accessed	access	VERB
cet-6362	119	20	14.11.2012	14.11.2012	NUM
cet-6362	119	21	.	.	PUNCT
cet-6362	120	1	giebel	giebel	PROPN
cet-6362	120	2	g.	g.	PROPN
cet-6362	120	3	,	,	PUNCT
cet-6362	120	4	badger	badger	PROPN
cet-6362	120	5	j.	j.	PROPN
cet-6362	120	6	,	,	PUNCT
cet-6362	120	7	marti	marti	PROPN
cet-6362	120	8	i.	i.	PROPN
cet-6362	120	9	,	,	PUNCT
cet-6362	120	10	louka	louka	PROPN
cet-6362	120	11	p.	p.	PROPN
cet-6362	120	12	,	,	PUNCT
cet-6362	120	13	kallos	kallos	PROPN
cet-6362	120	14	g.	g.	PROPN
cet-6362	120	15	,	,	PUNCT
cet-6362	120	16	palomares	palomares	PROPN
cet-6362	120	17	a.	a.	NOUN
cet-6362	120	18	m.	m.	PROPN
cet-6362	120	19	,	,	PUNCT
cet-6362	120	20	lac	lac	PROPN
cet-6362	120	21	c.	c.	PROPN
cet-6362	120	22	,	,	PUNCT
cet-6362	120	23	descombes	descombe	VERB
cet-6362	120	24	g.	g.	PROPN
cet-6362	120	25	,	,	PUNCT
cet-6362	120	26	2006	2006	NUM
cet-6362	120	27	,	,	PUNCT
cet-6362	120	28	shortterm	shortterm	PROPN
cet-6362	120	29	forecasting	forecasting	NOUN
cet-6362	120	30	using	use	VERB
cet-6362	120	31	advanced	advanced	ADJ
cet-6362	120	32	physical	physical	ADJ
cet-6362	120	33	modeling	modeling	NOUN
cet-6362	120	34	—	—	PUNCT
cet-6362	120	35	the	the	DET
cet-6362	120	36	results	result	NOUN
cet-6362	120	37	of	of	ADP
cet-6362	120	38	the	the	DET
cet-6362	120	39	anemos	anemos	NOUN
cet-6362	120	40	project	project	NOUN
cet-6362	120	41	,	,	PUNCT
cet-6362	120	42	european	european	ADJ
cet-6362	120	43	wind	wind	NOUN
cet-6362	120	44	energy	energy	NOUN
cet-6362	120	45	conference	conference	NOUN
cet-6362	120	46	(	(	PUNCT
cet-6362	120	47	ewec	ewec	NOUN
cet-6362	120	48	)	)	PUNCT
cet-6362	120	49	,	,	PUNCT
cet-6362	120	50	athens	athens	PROPN
cet-6362	120	51	,	,	PUNCT
cet-6362	120	52	greece	greece	PROPN
cet-6362	120	53	.	.	PUNCT
cet-6362	121	1	kalogirou	kalogirou	PROPN
cet-6362	121	2	s.	s.	PROPN
cet-6362	121	3	a.	a.	PROPN
cet-6362	121	4	,	,	PUNCT
cet-6362	121	5	2001	2001	NUM
cet-6362	121	6	,	,	PUNCT
cet-6362	121	7	artificial	artificial	ADJ
cet-6362	121	8	neural	neural	ADJ
cet-6362	121	9	networks	network	NOUN
cet-6362	121	10	in	in	ADP
cet-6362	121	11	renewable	renewable	ADJ
cet-6362	121	12	energy	energy	NOUN
cet-6362	121	13	systems	system	NOUN
cet-6362	121	14	applications	application	NOUN
cet-6362	121	15	:	:	PUNCT
cet-6362	121	16	a	a	DET
cet-6362	121	17	review	review	NOUN
cet-6362	121	18	,	,	PUNCT
cet-6362	121	19	renewable	renewable	ADJ
cet-6362	121	20	and	and	CCONJ
cet-6362	121	21	sustainable	sustainable	ADJ
cet-6362	121	22	energy	energy	NOUN
cet-6362	121	23	reviews	review	NOUN
cet-6362	121	24	,	,	PUNCT
cet-6362	121	25	5	5	NUM
cet-6362	121	26	,	,	PUNCT
cet-6362	121	27	373	373	NUM
cet-6362	121	28	-	-	SYM
cet-6362	121	29	401	401	NUM
cet-6362	121	30	.	.	PUNCT
cet-6362	122	1	kavasseri	kavasseri	PROPN
cet-6362	122	2	r.	r.	PROPN
cet-6362	122	3	g.	g.	PROPN
cet-6362	122	4	,	,	PUNCT
cet-6362	122	5	seetharaman	seetharaman	PROPN
cet-6362	122	6	k.	k.	PROPN
cet-6362	122	7	,	,	PUNCT
cet-6362	122	8	2009	2009	NUM
cet-6362	122	9	,	,	PUNCT
cet-6362	122	10	day	day	NOUN
cet-6362	122	11	-	-	PUNCT
cet-6362	122	12	ahead	ahead	NOUN
cet-6362	122	13	wind	wind	NOUN
cet-6362	122	14	speed	speed	NOUN
cet-6362	122	15	forecasting	forecasting	NOUN
cet-6362	122	16	using	use	VERB
cet-6362	122	17	f	f	PROPN
cet-6362	122	18	-	-	PUNCT
cet-6362	122	19	arima	arima	NOUN
cet-6362	122	20	models	model	NOUN
cet-6362	122	21	,	,	PUNCT
cet-6362	122	22	renewable	renewable	ADJ
cet-6362	122	23	energy	energy	NOUN
cet-6362	122	24	,	,	PUNCT
cet-6362	122	25	34	34	NUM
cet-6362	122	26	,	,	PUNCT
cet-6362	122	27	1388	1388	NUM
cet-6362	122	28	-	-	SYM
cet-6362	122	29	1393	1393	NUM
cet-6362	122	30	.	.	PUNCT
cet-6362	123	1	khosravi	khosravi	PROPN
cet-6362	123	2	a.	a.	NOUN
cet-6362	123	3	,	,	PUNCT
cet-6362	123	4	nahavandi	nahavandi	PROPN
cet-6362	123	5	s.	s.	PROPN
cet-6362	123	6	,	,	PUNCT
cet-6362	123	7	creighton	creighton	PROPN
cet-6362	123	8	d.	d.	PROPN
cet-6362	123	9	,	,	PUNCT
cet-6362	123	10	atiya	atiya	PROPN
cet-6362	123	11	a.	a.	PROPN
cet-6362	123	12	f.	f.	PROPN
cet-6362	123	13	,	,	PUNCT
cet-6362	123	14	2011	2011	NUM
cet-6362	123	15	,	,	PUNCT
cet-6362	123	16	lower	low	ADJ
cet-6362	123	17	upper	upper	ADJ
cet-6362	123	18	bound	bind	VERB
cet-6362	123	19	estimation	estimation	NOUN
cet-6362	123	20	method	method	NOUN
cet-6362	123	21	for	for	ADP
cet-6362	123	22	construction	construction	NOUN
cet-6362	123	23	of	of	ADP
cet-6362	123	24	neural	neural	ADJ
cet-6362	123	25	network	network	NOUN
cet-6362	123	26	-	-	PUNCT
cet-6362	123	27	based	base	VERB
cet-6362	123	28	prediction	prediction	NOUN
cet-6362	123	29	intervals	interval	NOUN
cet-6362	123	30	,	,	PUNCT
cet-6362	123	31	ieee	ieee	NOUN
cet-6362	123	32	transactions	transaction	NOUN
cet-6362	123	33	on	on	ADP
cet-6362	123	34	neural	neural	ADJ
cet-6362	123	35	networks	network	NOUN
cet-6362	123	36	,	,	PUNCT
cet-6362	123	37	22	22	NUM
cet-6362	123	38	,	,	PUNCT
cet-6362	123	39	337	337	NUM
cet-6362	123	40	-	-	SYM
cet-6362	123	41	346	346	NUM
cet-6362	123	42	.	.	PUNCT
cet-6362	124	1	konak	konak	PROPN
cet-6362	124	2	a.	a.	PROPN
cet-6362	124	3	,	,	PUNCT
cet-6362	124	4	coit	coit	PROPN
cet-6362	124	5	d.	d.	PROPN
cet-6362	124	6	w.	w.	PROPN
cet-6362	124	7	,	,	PUNCT
cet-6362	124	8	smith	smith	PROPN
cet-6362	124	9	a.	a.	PROPN
cet-6362	124	10	e.	e.	PROPN
cet-6362	124	11	,	,	PUNCT
cet-6362	124	12	2006	2006	NUM
cet-6362	124	13	,	,	PUNCT
cet-6362	124	14	multi	multi	ADJ
cet-6362	124	15	-	-	ADJ
cet-6362	124	16	objective	objective	ADJ
cet-6362	124	17	optimization	optimization	NOUN
cet-6362	124	18	using	use	VERB
cet-6362	124	19	genetic	genetic	ADJ
cet-6362	124	20	algorithms	algorithm	NOUN
cet-6362	124	21	:	:	PUNCT
cet-6362	124	22	a	a	DET
cet-6362	124	23	tutorial	tutorial	NOUN
cet-6362	124	24	,	,	PUNCT
cet-6362	124	25	reliability	reliability	NOUN
cet-6362	124	26	engineering	engineering	NOUN
cet-6362	124	27	and	and	CCONJ
cet-6362	124	28	system	system	NOUN
cet-6362	124	29	safety	safety	NOUN
cet-6362	124	30	,	,	PUNCT
cet-6362	124	31	91	91	NUM
cet-6362	124	32	,	,	PUNCT
cet-6362	124	33	992	992	NUM
cet-6362	124	34	-	-	SYM
cet-6362	124	35	1007	1007	NUM
cet-6362	124	36	.	.	PUNCT
cet-6362	125	1	kusiak	kusiak	PROPN
cet-6362	125	2	a.	a.	PROPN
cet-6362	125	3	,	,	PUNCT
cet-6362	125	4	zheng	zheng	PROPN
cet-6362	125	5	h.	h.	PROPN
cet-6362	125	6	,	,	PUNCT
cet-6362	125	7	song	song	PROPN
cet-6362	125	8	z.	z.	PROPN
cet-6362	125	9	,	,	PUNCT
cet-6362	125	10	2009	2009	NUM
cet-6362	125	11	,	,	PUNCT
cet-6362	125	12	short	short	ADJ
cet-6362	125	13	-	-	PUNCT
cet-6362	125	14	term	term	NOUN
cet-6362	125	15	prediction	prediction	NOUN
cet-6362	125	16	of	of	ADP
cet-6362	125	17	wind	wind	NOUN
cet-6362	125	18	farm	farm	NOUN
cet-6362	125	19	power	power	NOUN
cet-6362	125	20	:	:	PUNCT
cet-6362	125	21	a	a	DET
cet-6362	125	22	data	data	NOUN
cet-6362	125	23	mining	mining	NOUN
cet-6362	125	24	approach	approach	NOUN
cet-6362	125	25	,	,	PUNCT
cet-6362	125	26	ieee	ieee	NOUN
cet-6362	125	27	transactions	transaction	NOUN
cet-6362	125	28	on	on	ADP
cet-6362	125	29	energy	energy	NOUN
cet-6362	125	30	conversion	conversion	NOUN
cet-6362	125	31	.	.	PUNCT
cet-6362	126	1	24	24	NUM
cet-6362	126	2	,	,	PUNCT
cet-6362	126	3	125	125	NUM
cet-6362	126	4	-	-	SYM
cet-6362	126	5	136	136	NUM
cet-6362	126	6	.	.	PUNCT
cet-6362	127	1	lei	lei	PROPN
cet-6362	127	2	m.	m.	PROPN
cet-6362	127	3	,	,	PUNCT
cet-6362	127	4	shiyan	shiyan	PROPN
cet-6362	127	5	l.	l.	PROPN
cet-6362	127	6	,	,	PUNCT
cet-6362	127	7	chuanwen	chuanwen	PROPN
cet-6362	127	8	j.	j.	PROPN
cet-6362	127	9	,	,	PUNCT
cet-6362	127	10	hongling	hongling	PROPN
cet-6362	127	11	l.	l.	PROPN
cet-6362	127	12	,	,	PUNCT
cet-6362	127	13	yan	yan	PROPN
cet-6362	127	14	z.	z.	PROPN
cet-6362	127	15	,	,	PUNCT
cet-6362	127	16	2009	2009	NUM
cet-6362	127	17	,	,	PUNCT
cet-6362	127	18	a	a	DET
cet-6362	127	19	review	review	NOUN
cet-6362	127	20	on	on	ADP
cet-6362	127	21	the	the	DET
cet-6362	127	22	forecasting	forecasting	NOUN
cet-6362	127	23	of	of	ADP
cet-6362	127	24	wind	wind	NOUN
cet-6362	127	25	speed	speed	NOUN
cet-6362	127	26	and	and	CCONJ
cet-6362	127	27	generated	generate	VERB
cet-6362	127	28	power	power	NOUN
cet-6362	127	29	,	,	PUNCT
cet-6362	127	30	renewable	renewable	ADJ
cet-6362	127	31	and	and	CCONJ
cet-6362	127	32	sustainable	sustainable	ADJ
cet-6362	127	33	energy	energy	NOUN
cet-6362	127	34	reviews	review	NOUN
cet-6362	127	35	,	,	PUNCT
cet-6362	127	36	13	13	NUM
cet-6362	127	37	,	,	PUNCT
cet-6362	127	38	915	915	NUM
cet-6362	127	39	-	-	SYM
cet-6362	127	40	920	920	NUM
cet-6362	127	41	.	.	PUNCT
cet-6362	128	1	lew	lew	PROPN
cet-6362	128	2	d.	d.	PROPN
cet-6362	128	3	,	,	PUNCT
cet-6362	128	4	milligan	milligan	PROPN
cet-6362	128	5	m.	m.	PROPN
cet-6362	128	6	,	,	PUNCT
cet-6362	128	7	jordan	jordan	PROPN
cet-6362	128	8	g.	g.	PROPN
cet-6362	128	9	,	,	PUNCT
cet-6362	128	10	piwko	piwko	PROPN
cet-6362	128	11	r.	r.	PROPN
cet-6362	128	12	,	,	PUNCT
cet-6362	128	13	2011	2011	NUM
cet-6362	128	14	,	,	PUNCT
cet-6362	128	15	the	the	DET
cet-6362	128	16	value	value	NOUN
cet-6362	128	17	of	of	ADP
cet-6362	128	18	wind	wind	NOUN
cet-6362	128	19	power	power	NOUN
cet-6362	128	20	forecasting	forecasting	NOUN
cet-6362	128	21	,	,	PUNCT
cet-6362	128	22	91st	91st	ADJ
cet-6362	128	23	american	american	ADJ
cet-6362	128	24	meteorological	meteorological	ADJ
cet-6362	128	25	society	society	PROPN
cet-6362	128	26	annual	annual	ADJ
cet-6362	128	27	meeting	meeting	NOUN
cet-6362	128	28	,	,	PUNCT
cet-6362	128	29	the	the	DET
cet-6362	128	30	second	second	ADJ
cet-6362	128	31	conference	conference	NOUN
cet-6362	128	32	on	on	ADP
cet-6362	128	33	weather	weather	NOUN
cet-6362	128	34	,	,	PUNCT
cet-6362	128	35	climate	climate	NOUN
cet-6362	128	36	,	,	PUNCT
cet-6362	128	37	and	and	CCONJ
cet-6362	128	38	the	the	DET
cet-6362	128	39	new	new	ADJ
cet-6362	128	40	energy	energy	NOUN
cet-6362	128	41	economy	economy	NOUN
cet-6362	128	42	washington	washington	PROPN
cet-6362	128	43	,	,	PUNCT
cet-6362	128	44	usa	usa	PROPN
cet-6362	128	45	,	,	PUNCT
cet-6362	128	46	january	january	PROPN
cet-6362	128	47	26	26	NUM
cet-6362	128	48	,	,	PUNCT
cet-6362	128	49	2011	2011	NUM
cet-6362	128	50	,	,	PUNCT
cet-6362	128	51	<	<	X
cet-6362	128	52	http://www.nrel.gov/docs/fy11osti/50814.pdf	http://www.nrel.gov/docs/fy11osti/50814.pdf	X
cet-6362	128	53	>	>	PRON
cet-6362	128	54	,	,	PUNCT
cet-6362	128	55	accessed	access	VERB
cet-6362	128	56	14.11.2012	14.11.2012	NUM
cet-6362	128	57	.	.	PUNCT
cet-6362	129	1	moore	moore	PROPN
cet-6362	129	2	r.e	r.e	PROPN
cet-6362	129	3	.	.	PROPN
cet-6362	129	4	,	,	PUNCT
cet-6362	129	5	kearfott	kearfott	PROPN
cet-6362	129	6	r.b	r.b	PROPN
cet-6362	129	7	.	.	PROPN
cet-6362	129	8	,	,	PUNCT
cet-6362	129	9	cloud	cloud	PROPN
cet-6362	129	10	m.j	m.j	PROPN
cet-6362	129	11	.	.	PROPN
cet-6362	129	12	,	,	PUNCT
cet-6362	129	13	eds	eds	PROPN
cet-6362	129	14	.	.	PROPN
cet-6362	129	15	,	,	PUNCT
cet-6362	129	16	2009	2009	NUM
cet-6362	129	17	,	,	PUNCT
cet-6362	129	18	introduction	introduction	NOUN
cet-6362	129	19	to	to	ADP
cet-6362	129	20	interval	interval	NOUN
cet-6362	129	21	analysis	analysis	NOUN
cet-6362	129	22	.	.	PUNCT
cet-6362	130	1	society	society	NOUN
cet-6362	130	2	for	for	ADP
cet-6362	130	3	industrial	industrial	ADJ
cet-6362	130	4	mathematics	mathematic	NOUN
cet-6362	130	5	,	,	PUNCT
cet-6362	130	6	philadelphia	philadelphia	PROPN
cet-6362	130	7	,	,	PUNCT
cet-6362	130	8	usa	usa	PROPN
cet-6362	130	9	muñoz	muñoz	PROPN
cet-6362	130	10	san	san	PROPN
cet-6362	130	11	roque	roque	PROPN
cet-6362	130	12	a.	a.	PROPN
cet-6362	130	13	,	,	PUNCT
cet-6362	130	14	maté	maté	PROPN
cet-6362	130	15	c.	c.	PROPN
cet-6362	130	16	,	,	PUNCT
cet-6362	130	17	arroyo	arroyo	PROPN
cet-6362	130	18	j.	j.	PROPN
cet-6362	130	19	,	,	PUNCT
cet-6362	130	20	sarabia	sarabia	NOUN
cet-6362	130	21	a.	a.	NOUN
cet-6362	130	22	,	,	PUNCT
cet-6362	130	23	2007	2007	NUM
cet-6362	130	24	,	,	PUNCT
cet-6362	130	25	imlp	imlp	PROPN
cet-6362	130	26	:	:	PUNCT
cet-6362	130	27	applying	apply	VERB
cet-6362	130	28	multilayer	multilayer	ADJ
cet-6362	130	29	perceptrons	perceptron	NOUN
cet-6362	130	30	to	to	ADP
cet-6362	130	31	interval	interval	NOUN
cet-6362	130	32	-	-	PUNCT
cet-6362	130	33	valued	value	VERB
cet-6362	130	34	data	datum	NOUN
cet-6362	130	35	,	,	PUNCT
cet-6362	130	36	neural	neural	ADJ
cet-6362	130	37	processing	processing	NOUN
cet-6362	130	38	letters	letter	NOUN
cet-6362	130	39	,	,	PUNCT
cet-6362	130	40	25	25	NUM
cet-6362	130	41	,	,	PUNCT
cet-6362	130	42	157–169	157–169	NUM
cet-6362	130	43	.	.	PUNCT
cet-6362	130	44	nazzal	nazzal	PROPN
cet-6362	130	45	j.	j.	PROPN
cet-6362	130	46	m.	m.	PROPN
cet-6362	130	47	,	,	PUNCT
cet-6362	130	48	el	el	PROPN
cet-6362	130	49	-	-	PUNCT
cet-6362	130	50	emary	emary	PROPN
cet-6362	130	51	i.	i.	PROPN
cet-6362	130	52	m.	m.	PROPN
cet-6362	130	53	,	,	PUNCT
cet-6362	130	54	najim	najim	VERB
cet-6362	130	55	s.	s.	PROPN
cet-6362	130	56	a.	a.	PROPN
cet-6362	130	57	,	,	PUNCT
cet-6362	130	58	2008	2008	NUM
cet-6362	130	59	,	,	PUNCT
cet-6362	130	60	multilayer	multilayer	PROPN
cet-6362	130	61	perceptron	perceptron	PROPN
cet-6362	130	62	neural	neural	PROPN
cet-6362	130	63	network	network	NOUN
cet-6362	130	64	(	(	PUNCT
cet-6362	130	65	mlps	mlps	PROPN
cet-6362	130	66	)	)	PUNCT
cet-6362	130	67	for	for	ADP
cet-6362	130	68	analyzing	analyze	VERB
cet-6362	130	69	the	the	DET
cet-6362	130	70	properties	property	NOUN
cet-6362	130	71	of	of	ADP
cet-6362	130	72	jordan	jordan	PROPN
cet-6362	130	73	oil	oil	PROPN
cet-6362	130	74	shale	shale	NOUN
cet-6362	130	75	,	,	PUNCT
cet-6362	130	76	world	world	NOUN
cet-6362	130	77	applied	apply	VERB
cet-6362	130	78	sciences	science	NOUN
cet-6362	130	79	journal	journal	NOUN
cet-6362	130	80	,	,	PUNCT
cet-6362	130	81	5	5	NUM
cet-6362	130	82	,	,	PUNCT
cet-6362	130	83	546	546	NUM
cet-6362	130	84	-	-	SYM
cet-6362	130	85	552	552	NUM
cet-6362	130	86	.	.	PUNCT
cet-6362	131	1	pandya	pandya	PROPN
cet-6362	131	2	n.	n.	PROPN
cet-6362	131	3	,	,	PUNCT
cet-6362	131	4	gabas	gabas	PROPN
cet-6362	131	5	n.	n.	PROPN
cet-6362	131	6	,	,	PUNCT
cet-6362	131	7	marsden	marsden	PROPN
cet-6362	131	8	e.	e.	PROPN
cet-6362	131	9	,	,	PUNCT
cet-6362	131	10	2013	2013	NUM
cet-6362	131	11	,	,	PUNCT
cet-6362	131	12	uncertainty	uncertainty	NOUN
cet-6362	131	13	analysis	analysis	NOUN
cet-6362	131	14	of	of	ADP
cet-6362	131	15	phast	phast	NOUN
cet-6362	131	16	’s	’s	PART
cet-6362	131	17	atmospheric	atmospheric	ADJ
cet-6362	131	18	dispersion	dispersion	NOUN
cet-6362	131	19	model	model	NOUN
cet-6362	131	20	for	for	ADP
cet-6362	131	21	two	two	NUM
cet-6362	131	22	industrial	industrial	ADJ
cet-6362	131	23	use	use	NOUN
cet-6362	131	24	cases	case	NOUN
cet-6362	131	25	,	,	PUNCT
cet-6362	131	26	chemical	chemical	ADJ
cet-6362	131	27	engineering	engineering	NOUN
cet-6362	131	28	transactions	transaction	NOUN
cet-6362	131	29	,	,	PUNCT
cet-6362	131	30	31	31	NUM
cet-6362	131	31	,	,	PUNCT
cet-6362	131	32	97	97	NUM
cet-6362	131	33	-	-	SYM
cet-6362	131	34	102	102	NUM
cet-6362	131	35	,	,	PUNCT
cet-6362	131	36	doi	doi	NOUN
cet-6362	131	37	:	:	PUNCT
cet-6362	131	38	10.3303	10.3303	NUM
cet-6362	131	39	/	/	SYM
cet-6362	131	40	cet1331017	cet1331017	X
cet-6362	131	41	.	.	PUNCT
cet-6362	132	1	sideratos	sideratos	PROPN
cet-6362	132	2	g.	g.	PROPN
cet-6362	132	3	,	,	PUNCT
cet-6362	132	4	hatziargyriou	hatziargyriou	PROPN
cet-6362	132	5	n.	n.	PROPN
cet-6362	132	6	d.	d.	PROPN
cet-6362	132	7	,	,	PUNCT
cet-6362	132	8	2007	2007	NUM
cet-6362	132	9	,	,	PUNCT
cet-6362	132	10	an	an	DET
cet-6362	132	11	advanced	advanced	ADJ
cet-6362	132	12	statistical	statistical	ADJ
cet-6362	132	13	method	method	NOUN
cet-6362	132	14	for	for	ADP
cet-6362	132	15	wind	wind	NOUN
cet-6362	132	16	power	power	NOUN
cet-6362	132	17	forecasting	forecasting	NOUN
cet-6362	132	18	,	,	PUNCT
cet-6362	132	19	ieee	ieee	NOUN
cet-6362	132	20	transactions	transaction	NOUN
cet-6362	132	21	on	on	ADP
cet-6362	132	22	power	power	NOUN
cet-6362	132	23	systems	system	NOUN
cet-6362	132	24	,	,	PUNCT
cet-6362	132	25	22(1	22(1	NUM
cet-6362	132	26	)	)	PUNCT
cet-6362	132	27	,	,	PUNCT
cet-6362	132	28	258	258	NUM
cet-6362	132	29	-	-	SYM
cet-6362	132	30	265	265	NUM
cet-6362	132	31	.	.	PUNCT
cet-6362	132	32	930	930	NUM