id	sid	tid	token	lemma	pos
ijassa-499	1	1	adv	adv	PROPN
ijassa-499	1	2	syst	syst	PROPN
ijassa-499	1	3	sci	sci	PROPN
ijassa-499	1	4	appl	appl	PROPN
ijassa-499	1	5	2017	2017	NUM
ijassa-499	1	6	;	;	PUNCT
ijassa-499	1	7	3:58–66	3:58–66	NUM
ijassa-499	1	8	published	publish	VERB
ijassa-499	1	9	online	online	ADV
ijassa-499	1	10	at	at	ADP
ijassa-499	1	11	http://ijassa.ipu.ru/ojs/ijassa/article/view/499	http://ijassa.ipu.ru/ojs/ijassa/article/view/499	PROPN
ijassa-499	1	12	regression	regression	NOUN
ijassa-499	1	13	tree	tree	NOUN
ijassa-499	1	14	control	control	NOUN
ijassa-499	1	15	of	of	ADP
ijassa-499	1	16	multidimensional	multidimensional	ADJ
ijassa-499	1	17	static	static	ADJ
ijassa-499	1	18	object	object	NOUN
ijassa-499	1	19	ekaterina	ekaterina	PROPN
ijassa-499	1	20	mangalova1∗	mangalova1∗	PROPN
ijassa-499	1	21	1system	1system	NUM
ijassa-499	1	22	analysis	analysis	NOUN
ijassa-499	1	23	and	and	CCONJ
ijassa-499	1	24	control	control	PROPN
ijassa-499	1	25	department	department	PROPN
ijassa-499	1	26	,	,	PUNCT
ijassa-499	1	27	siberian	siberian	ADJ
ijassa-499	1	28	state	state	NOUN
ijassa-499	1	29	aerospace	aerospace	PROPN
ijassa-499	1	30	university	university	PROPN
ijassa-499	1	31	,	,	PUNCT
ijassa-499	1	32	krasnoyarsk	krasnoyarsk	PROPN
ijassa-499	1	33	,	,	PUNCT
ijassa-499	1	34	russia	russia	PROPN
ijassa-499	1	35	abstract	abstract	NOUN
ijassa-499	1	36	:	:	PUNCT
ijassa-499	1	37	in	in	ADP
ijassa-499	1	38	this	this	DET
ijassa-499	1	39	paper	paper	NOUN
ijassa-499	1	40	the	the	DET
ijassa-499	1	41	control	control	NOUN
ijassa-499	1	42	problem	problem	NOUN
ijassa-499	1	43	of	of	ADP
ijassa-499	1	44	a	a	DET
ijassa-499	1	45	static	static	ADJ
ijassa-499	1	46	system	system	NOUN
ijassa-499	1	47	under	under	ADP
ijassa-499	1	48	incomplete	incomplete	ADJ
ijassa-499	1	49	information	information	NOUN
ijassa-499	1	50	is	be	AUX
ijassa-499	1	51	discussed	discuss	VERB
ijassa-499	1	52	.	.	PUNCT
ijassa-499	2	1	a	a	DET
ijassa-499	2	2	nonparametric	nonparametric	NOUN
ijassa-499	2	3	control	control	NOUN
ijassa-499	2	4	algorithm	algorithm	NOUN
ijassa-499	2	5	based	base	VERB
ijassa-499	2	6	on	on	ADP
ijassa-499	2	7	classification	classification	NOUN
ijassa-499	2	8	and	and	CCONJ
ijassa-499	2	9	regression	regression	NOUN
ijassa-499	2	10	tree	tree	NOUN
ijassa-499	2	11	is	be	AUX
ijassa-499	2	12	proposed	propose	VERB
ijassa-499	2	13	and	and	CCONJ
ijassa-499	2	14	evaluated	evaluate	VERB
ijassa-499	2	15	for	for	ADP
ijassa-499	2	16	different	different	ADJ
ijassa-499	2	17	task	task	NOUN
ijassa-499	2	18	formulations	formulation	NOUN
ijassa-499	2	19	:	:	PUNCT
ijassa-499	2	20	controlled	control	VERB
ijassa-499	2	21	inputs	input	NOUN
ijassa-499	2	22	–	–	PUNCT
ijassa-499	2	23	one	one	NUM
ijassa-499	2	24	-	-	PUNCT
ijassa-499	2	25	dimensional	dimensional	ADJ
ijassa-499	2	26	output	output	NOUN
ijassa-499	2	27	,	,	PUNCT
ijassa-499	2	28	controlled	control	VERB
ijassa-499	2	29	and	and	CCONJ
ijassa-499	2	30	observed	observe	VERB
ijassa-499	2	31	uncontrolled	uncontrolled	ADJ
ijassa-499	2	32	inputs	input	NOUN
ijassa-499	2	33	–	–	PUNCT
ijassa-499	2	34	one	one	NUM
ijassa-499	2	35	-	-	PUNCT
ijassa-499	2	36	dimensional	dimensional	ADJ
ijassa-499	2	37	output	output	NOUN
ijassa-499	2	38	,	,	PUNCT
ijassa-499	2	39	controlled	control	VERB
ijassa-499	2	40	and	and	CCONJ
ijassa-499	2	41	observed	observe	VERB
ijassa-499	2	42	uncontrolled	uncontrolled	ADJ
ijassa-499	2	43	inputs	input	NOUN
ijassa-499	2	44	–	–	PUNCT
ijassa-499	2	45	multi	multi	ADJ
ijassa-499	2	46	-	-	ADJ
ijassa-499	2	47	dimensional	dimensional	ADJ
ijassa-499	2	48	outputs	output	NOUN
ijassa-499	2	49	.	.	PUNCT
ijassa-499	3	1	keywords	keyword	NOUN
ijassa-499	3	2	:	:	PUNCT
ijassa-499	3	3	control	control	NOUN
ijassa-499	3	4	,	,	PUNCT
ijassa-499	3	5	regression	regression	NOUN
ijassa-499	3	6	tree	tree	NOUN
ijassa-499	3	7	,	,	PUNCT
ijassa-499	3	8	machine	machine	NOUN
ijassa-499	3	9	learning	learning	NOUN
ijassa-499	3	10	,	,	PUNCT
ijassa-499	3	11	optimization	optimization	NOUN
ijassa-499	3	12	1	1	NUM
ijassa-499	3	13	.	.	PUNCT
ijassa-499	3	14	introduction	introduction	NOUN
ijassa-499	3	15	the	the	DET
ijassa-499	3	16	modeling	modeling	NOUN
ijassa-499	3	17	of	of	ADP
ijassa-499	3	18	technical	technical	ADJ
ijassa-499	3	19	systems	system	NOUN
ijassa-499	3	20	and	and	CCONJ
ijassa-499	3	21	processes	process	NOUN
ijassa-499	3	22	is	be	AUX
ijassa-499	3	23	the	the	DET
ijassa-499	3	24	essentially	essentially	ADV
ijassa-499	3	25	important	important	ADJ
ijassa-499	3	26	tool	tool	NOUN
ijassa-499	3	27	used	use	VERB
ijassa-499	3	28	in	in	ADP
ijassa-499	3	29	engineering	engineering	NOUN
ijassa-499	3	30	to	to	PART
ijassa-499	3	31	design	design	VERB
ijassa-499	3	32	,	,	PUNCT
ijassa-499	3	33	improve	improve	VERB
ijassa-499	3	34	,	,	PUNCT
ijassa-499	3	35	optimize	optimize	NOUN
ijassa-499	3	36	and	and	CCONJ
ijassa-499	3	37	control	control	NOUN
ijassa-499	3	38	systems	system	NOUN
ijassa-499	3	39	.	.	PUNCT
ijassa-499	4	1	using	use	VERB
ijassa-499	4	2	simulation	simulation	NOUN
ijassa-499	4	3	modeling	modeling	NOUN
ijassa-499	4	4	is	be	AUX
ijassa-499	4	5	generally	generally	ADV
ijassa-499	4	6	cheaper	cheap	ADJ
ijassa-499	4	7	,	,	PUNCT
ijassa-499	4	8	safer	safe	ADJ
ijassa-499	4	9	and	and	CCONJ
ijassa-499	4	10	faster	fast	ADV
ijassa-499	4	11	than	than	ADP
ijassa-499	4	12	conducting	conduct	VERB
ijassa-499	4	13	real	real	ADJ
ijassa-499	4	14	-	-	PUNCT
ijassa-499	4	15	world	world	NOUN
ijassa-499	4	16	experiments	experiment	NOUN
ijassa-499	4	17	.	.	PUNCT
ijassa-499	5	1	this	this	PRON
ijassa-499	5	2	allows	allow	VERB
ijassa-499	5	3	to	to	PART
ijassa-499	5	4	use	use	VERB
ijassa-499	5	5	modeling	modeling	NOUN
ijassa-499	5	6	for	for	ADP
ijassa-499	5	7	different	different	ADJ
ijassa-499	5	8	alternatives	alternative	NOUN
ijassa-499	5	9	analyses	analysis	NOUN
ijassa-499	5	10	.	.	PUNCT
ijassa-499	6	1	there	there	PRON
ijassa-499	6	2	are	be	VERB
ijassa-499	6	3	two	two	NUM
ijassa-499	6	4	different	different	ADJ
ijassa-499	6	5	ways	way	NOUN
ijassa-499	6	6	to	to	PART
ijassa-499	6	7	create	create	VERB
ijassa-499	6	8	simulation	simulation	NOUN
ijassa-499	6	9	models	model	NOUN
ijassa-499	6	10	:	:	PUNCT
ijassa-499	6	11	•	•	NUM
ijassa-499	6	12	manually	manually	ADV
ijassa-499	6	13	built	build	VERB
ijassa-499	6	14	models	model	NOUN
ijassa-499	6	15	.	.	PUNCT
ijassa-499	7	1	a	a	DET
ijassa-499	7	2	specialist	specialist	NOUN
ijassa-499	7	3	builds	build	VERB
ijassa-499	7	4	the	the	DET
ijassa-499	7	5	simulation	simulation	NOUN
ijassa-499	7	6	model	model	NOUN
ijassa-499	7	7	manually	manually	ADV
ijassa-499	7	8	based	base	VERB
ijassa-499	7	9	on	on	ADP
ijassa-499	7	10	his	his	PRON
ijassa-499	7	11	theoretical	theoretical	ADJ
ijassa-499	7	12	knowledge	knowledge	NOUN
ijassa-499	7	13	and	and	CCONJ
ijassa-499	7	14	technical	technical	ADJ
ijassa-499	7	15	experience	experience	NOUN
ijassa-499	7	16	.	.	PUNCT
ijassa-499	8	1	this	this	DET
ijassa-499	8	2	method	method	NOUN
ijassa-499	8	3	is	be	AUX
ijassa-499	8	4	the	the	DET
ijassa-499	8	5	most	most	ADV
ijassa-499	8	6	useful	useful	ADJ
ijassa-499	8	7	and	and	CCONJ
ijassa-499	8	8	imminent	imminent	ADJ
ijassa-499	8	9	for	for	ADP
ijassa-499	8	10	systems	system	NOUN
ijassa-499	8	11	that	that	PRON
ijassa-499	8	12	do	do	AUX
ijassa-499	8	13	not	not	PART
ijassa-499	8	14	yet	yet	ADV
ijassa-499	8	15	exist	exist	VERB
ijassa-499	8	16	.	.	PUNCT
ijassa-499	9	1	•	•	NUM
ijassa-499	9	2	statistical	statistical	ADJ
ijassa-499	9	3	modeling	modeling	NOUN
ijassa-499	9	4	.	.	PUNCT
ijassa-499	10	1	statistical	statistical	ADJ
ijassa-499	10	2	modeling	modeling	NOUN
ijassa-499	10	3	is	be	AUX
ijassa-499	10	4	based	base	VERB
ijassa-499	10	5	on	on	ADP
ijassa-499	10	6	generating	generating	NOUN
ijassa-499	10	7	models	model	NOUN
ijassa-499	10	8	by	by	ADP
ijassa-499	10	9	observations	observation	NOUN
ijassa-499	10	10	.	.	PUNCT
ijassa-499	11	1	this	this	DET
ijassa-499	11	2	method	method	NOUN
ijassa-499	11	3	can	can	AUX
ijassa-499	11	4	be	be	AUX
ijassa-499	11	5	useful	useful	ADJ
ijassa-499	11	6	for	for	ADP
ijassa-499	11	7	complicated	complicated	ADJ
ijassa-499	11	8	systems	system	NOUN
ijassa-499	11	9	when	when	SCONJ
ijassa-499	11	10	input	input	NOUN
ijassa-499	11	11	-	-	PUNCT
ijassa-499	11	12	output	output	NOUN
ijassa-499	11	13	relationships	relationship	NOUN
ijassa-499	11	14	are	be	AUX
ijassa-499	11	15	not	not	PART
ijassa-499	11	16	evident	evident	ADJ
ijassa-499	11	17	or	or	CCONJ
ijassa-499	11	18	are	be	AUX
ijassa-499	11	19	unknown	unknown	ADJ
ijassa-499	11	20	,	,	PUNCT
ijassa-499	11	21	internals	internal	NOUN
ijassa-499	11	22	are	be	AUX
ijassa-499	11	23	not	not	PART
ijassa-499	11	24	essential	essential	ADJ
ijassa-499	11	25	for	for	ADP
ijassa-499	11	26	the	the	DET
ijassa-499	11	27	technical	technical	ADJ
ijassa-499	11	28	problem	problem	NOUN
ijassa-499	11	29	.	.	PUNCT
ijassa-499	12	1	statistical	statistical	ADJ
ijassa-499	12	2	models	model	NOUN
ijassa-499	12	3	are	be	AUX
ijassa-499	12	4	used	use	VERB
ijassa-499	12	5	to	to	PART
ijassa-499	12	6	detect	detect	VERB
ijassa-499	12	7	a	a	DET
ijassa-499	12	8	deviation	deviation	NOUN
ijassa-499	12	9	of	of	ADP
ijassa-499	12	10	the	the	DET
ijassa-499	12	11	normal	normal	ADJ
ijassa-499	12	12	behavior	behavior	NOUN
ijassa-499	12	13	of	of	ADP
ijassa-499	12	14	a	a	DET
ijassa-499	12	15	system	system	NOUN
ijassa-499	12	16	and	and	CCONJ
ijassa-499	12	17	to	to	PART
ijassa-499	12	18	control	control	VERB
ijassa-499	12	19	.	.	PUNCT
ijassa-499	13	1	model	model	NOUN
ijassa-499	13	2	predictive	predictive	PROPN
ijassa-499	13	3	control	control	NOUN
ijassa-499	13	4	is	be	AUX
ijassa-499	13	5	a	a	DET
ijassa-499	13	6	family	family	NOUN
ijassa-499	13	7	of	of	ADP
ijassa-499	13	8	controllers	controller	NOUN
ijassa-499	13	9	in	in	ADP
ijassa-499	13	10	which	which	PRON
ijassa-499	13	11	there	there	PRON
ijassa-499	13	12	is	be	VERB
ijassa-499	13	13	a	a	DET
ijassa-499	13	14	direct	direct	ADJ
ijassa-499	13	15	use	use	NOUN
ijassa-499	13	16	of	of	ADP
ijassa-499	13	17	an	an	DET
ijassa-499	13	18	explicit	explicit	ADJ
ijassa-499	13	19	and	and	CCONJ
ijassa-499	13	20	separately	separately	ADV
ijassa-499	13	21	identifiable	identifiable	ADJ
ijassa-499	13	22	model	model	NOUN
ijassa-499	13	23	.	.	PUNCT
ijassa-499	14	1	control	control	NOUN
ijassa-499	14	2	algorithms	algorithm	NOUN
ijassa-499	14	3	based	base	VERB
ijassa-499	14	4	on	on	ADP
ijassa-499	14	5	model	model	NOUN
ijassa-499	14	6	predictive	predictive	PROPN
ijassa-499	14	7	control	control	NOUN
ijassa-499	14	8	concept	concept	NOUN
ijassa-499	14	9	have	have	AUX
ijassa-499	14	10	found	find	VERB
ijassa-499	14	11	wide	wide	ADJ
ijassa-499	14	12	acceptance	acceptance	NOUN
ijassa-499	14	13	in	in	ADP
ijassa-499	14	14	practical	practical	ADJ
ijassa-499	14	15	applications	application	NOUN
ijassa-499	14	16	and	and	CCONJ
ijassa-499	14	17	have	have	AUX
ijassa-499	14	18	been	be	AUX
ijassa-499	14	19	studied	study	VERB
ijassa-499	14	20	by	by	ADP
ijassa-499	14	21	researchers	researcher	NOUN
ijassa-499	14	22	.	.	PUNCT
ijassa-499	15	1	in	in	ADP
ijassa-499	15	2	[	[	X
ijassa-499	15	3	1	1	X
ijassa-499	15	4	]	]	PUNCT
ijassa-499	15	5	one	one	NUM
ijassa-499	15	6	of	of	ADP
ijassa-499	15	7	the	the	DET
ijassa-499	15	8	first	first	ADJ
ijassa-499	15	9	successful	successful	ADJ
ijassa-499	15	10	applications	application	NOUN
ijassa-499	15	11	of	of	ADP
ijassa-499	15	12	model	model	NOUN
ijassa-499	15	13	predictive	predictive	PROPN
ijassa-499	15	14	heuristic	heuristic	ADJ
ijassa-499	15	15	control	control	NOUN
ijassa-499	15	16	is	be	AUX
ijassa-499	15	17	described	describe	VERB
ijassa-499	15	18	.	.	PUNCT
ijassa-499	16	1	there	there	PRON
ijassa-499	16	2	are	be	VERB
ijassa-499	16	3	two	two	NUM
ijassa-499	16	4	commonly	commonly	ADV
ijassa-499	16	5	used	use	VERB
ijassa-499	16	6	and	and	CCONJ
ijassa-499	16	7	well	well	ADV
ijassa-499	16	8	studied	study	VERB
ijassa-499	16	9	approaches	approach	NOUN
ijassa-499	16	10	to	to	PART
ijassa-499	16	11	model	model	VERB
ijassa-499	16	12	predictive	predictive	ADJ
ijassa-499	16	13	control	control	NOUN
ijassa-499	16	14	:	:	PUNCT
ijassa-499	16	15	based	base	VERB
ijassa-499	16	16	on	on	ADP
ijassa-499	16	17	artificial	artificial	ADJ
ijassa-499	16	18	neural	neural	ADJ
ijassa-499	16	19	networks	network	NOUN
ijassa-499	16	20	and	and	CCONJ
ijassa-499	16	21	based	base	VERB
ijassa-499	16	22	on	on	ADP
ijassa-499	16	23	fuzzy	fuzzy	ADJ
ijassa-499	16	24	logic	logic	NOUN
ijassa-499	16	25	.	.	PUNCT
ijassa-499	17	1	the	the	DET
ijassa-499	17	2	use	use	NOUN
ijassa-499	17	3	of	of	ADP
ijassa-499	17	4	artificial	artificial	ADJ
ijassa-499	17	5	neural	neural	ADJ
ijassa-499	17	6	networks	network	NOUN
ijassa-499	17	7	in	in	ADP
ijassa-499	17	8	model	model	NOUN
ijassa-499	17	9	based	base	VERB
ijassa-499	17	10	control	control	NOUN
ijassa-499	17	11	,	,	PUNCT
ijassa-499	17	12	both	both	PRON
ijassa-499	17	13	as	as	ADP
ijassa-499	17	14	process	process	NOUN
ijassa-499	17	15	models	model	NOUN
ijassa-499	17	16	and	and	CCONJ
ijassa-499	17	17	as	as	ADP
ijassa-499	17	18	controllers	controller	NOUN
ijassa-499	17	19	,	,	PUNCT
ijassa-499	17	20	is	be	AUX
ijassa-499	17	21	investigated	investigate	VERB
ijassa-499	17	22	by	by	ADP
ijassa-499	17	23	d.	d.	PROPN
ijassa-499	17	24	c.	c.	PROPN
ijassa-499	17	25	psichogios	psichogios	PROPN
ijassa-499	17	26	and	and	CCONJ
ijassa-499	17	27	l.	l.	PROPN
ijassa-499	17	28	h.	h.	PROPN
ijassa-499	17	29	ungar	ungar	PROPN
ijassa-499	18	1	[	[	X
ijassa-499	18	2	2	2	NUM
ijassa-499	18	3	]	]	PUNCT
ijassa-499	18	4	.	.	PUNCT
ijassa-499	19	1	a.	a.	PROPN
ijassa-499	19	2	draeger	draeger	PROPN
ijassa-499	19	3	,	,	PUNCT
ijassa-499	19	4	s.	s.	PROPN
ijassa-499	19	5	engell	engell	PROPN
ijassa-499	19	6	,	,	PUNCT
ijassa-499	19	7	h.	h.	PROPN
ijassa-499	19	8	ranke	ranke	PROPN
ijassa-499	20	1	[	[	X
ijassa-499	20	2	3	3	NUM
ijassa-499	20	3	]	]	PUNCT
ijassa-499	20	4	implemented	implement	VERB
ijassa-499	20	5	a	a	DET
ijassa-499	20	6	feed	feed	NOUN
ijassa-499	20	7	-	-	PUNCT
ijassa-499	20	8	forward	forward	ADV
ijassa-499	20	9	neural	neural	ADJ
ijassa-499	20	10	network	network	NOUN
ijassa-499	20	11	as	as	ADP
ijassa-499	20	12	the	the	DET
ijassa-499	20	13	nonlinear	nonlinear	ADJ
ijassa-499	20	14	prediction	prediction	NOUN
ijassa-499	20	15	model	model	NOUN
ijassa-499	20	16	in	in	ADP
ijassa-499	20	17	an	an	DET
ijassa-499	20	18	extended	extend	VERB
ijassa-499	20	19	dmc	dmc	NOUN
ijassa-499	20	20	-	-	PUNCT
ijassa-499	20	21	algorithm	algorithm	NOUN
ijassa-499	20	22	to	to	ADP
ijassa-499	20	23	control	control	NOUN
ijassa-499	20	24	.	.	PUNCT
ijassa-499	21	1	h.	h.	PROPN
ijassa-499	21	2	sarimveis	sarimveis	PROPN
ijassa-499	21	3	and	and	CCONJ
ijassa-499	21	4	g.	g.	PROPN
ijassa-499	21	5	bafas	bafas	PROPN
ijassa-499	22	1	[	[	X
ijassa-499	22	2	4	4	X
ijassa-499	22	3	]	]	PUNCT
ijassa-499	22	4	introduceed	introduce	VERB
ijassa-499	22	5	the	the	DET
ijassa-499	22	6	method	method	NOUN
ijassa-499	22	7	based	base	VERB
ijassa-499	22	8	on	on	ADP
ijassa-499	22	9	a	a	DET
ijassa-499	22	10	dynamic	dynamic	ADJ
ijassa-499	22	11	fuzzy	fuzzy	ADJ
ijassa-499	22	12	model	model	NOUN
ijassa-499	22	13	of	of	ADP
ijassa-499	22	14	the	the	DET
ijassa-499	22	15	process	process	NOUN
ijassa-499	22	16	to	to	PART
ijassa-499	22	17	be	be	AUX
ijassa-499	22	18	controlled	control	VERB
ijassa-499	22	19	,	,	PUNCT
ijassa-499	22	20	which	which	PRON
ijassa-499	22	21	is	be	AUX
ijassa-499	22	22	used	use	VERB
ijassa-499	22	23	for	for	ADP
ijassa-499	22	24	predicting	predict	VERB
ijassa-499	22	25	the	the	DET
ijassa-499	22	26	future	future	ADJ
ijassa-499	22	27	behavior	behavior	NOUN
ijassa-499	22	28	of	of	ADP
ijassa-499	22	29	the	the	DET
ijassa-499	22	30	output	output	NOUN
ijassa-499	22	31	variables	variable	NOUN
ijassa-499	22	32	.	.	PUNCT
ijassa-499	23	1	in	in	ADP
ijassa-499	23	2	the	the	DET
ijassa-499	23	3	paper	paper	NOUN
ijassa-499	23	4	[	[	X
ijassa-499	23	5	5	5	X
ijassa-499	23	6	]	]	PUNCT
ijassa-499	23	7	j.	j.	PROPN
ijassa-499	23	8	m	m	PROPN
ijassa-499	23	9	da	da	PROPN
ijassa-499	23	10	costa	costa	PROPN
ijassa-499	23	11	sousa	sousa	PROPN
ijassa-499	23	12	and	and	CCONJ
ijassa-499	23	13	u.	u.	PROPN
ijassa-499	23	14	kaymak	kaymak	PROPN
ijassa-499	23	15	investigated	investigate	VERB
ijassa-499	23	16	the	the	DET
ijassa-499	23	17	use	use	NOUN
ijassa-499	23	18	of	of	ADP
ijassa-499	23	19	fuzzy	fuzzy	ADJ
ijassa-499	23	20	decision	decision	NOUN
ijassa-499	23	21	making	making	NOUN
ijassa-499	23	22	in	in	ADP
ijassa-499	23	23	model	model	NOUN
ijassa-499	23	24	predictive	predictive	ADJ
ijassa-499	23	25	control	control	NOUN
ijassa-499	23	26	.	.	PUNCT
ijassa-499	24	1	∗corresponding	∗corresponde	VERB
ijassa-499	24	2	author	author	NOUN
ijassa-499	24	3	:	:	PUNCT
ijassa-499	24	4	e.s.mangalova@hotmail.com	e.s.mangalova@hotmail.com	X
ijassa-499	25	1	http://ijassa.ipu.ru/ojs/ijassa/article/view/499	http://ijassa.ipu.ru/ojs/ijassa/article/view/499	PROPN
ijassa-499	25	2	regression	regression	NOUN
ijassa-499	25	3	tree	tree	NOUN
ijassa-499	25	4	control	control	NOUN
ijassa-499	25	5	of	of	ADP
ijassa-499	25	6	multidimensional	multidimensional	ADJ
ijassa-499	25	7	static	static	ADJ
ijassa-499	25	8	object	object	NOUN
ijassa-499	25	9	59	59	NUM
ijassa-499	25	10	in	in	ADP
ijassa-499	25	11	contrast	contrast	NOUN
ijassa-499	25	12	to	to	ADP
ijassa-499	25	13	neural	neural	ADJ
ijassa-499	25	14	network	network	NOUN
ijassa-499	25	15	and	and	CCONJ
ijassa-499	25	16	fuzzy	fuzzy	ADJ
ijassa-499	25	17	logic	logic	NOUN
ijassa-499	25	18	approaches	approach	NOUN
ijassa-499	25	19	,	,	PUNCT
ijassa-499	25	20	in	in	ADP
ijassa-499	25	21	[	[	X
ijassa-499	25	22	6	6	NUM
ijassa-499	25	23	]	]	PUNCT
ijassa-499	25	24	a	a	DET
ijassa-499	25	25	control	control	NOUN
ijassa-499	25	26	algorithm	algorithm	NOUN
ijassa-499	25	27	based	base	VERB
ijassa-499	25	28	on	on	ADP
ijassa-499	25	29	the	the	DET
ijassa-499	25	30	nadaraya	nadaraya	PROPN
ijassa-499	25	31	-	-	PUNCT
ijassa-499	25	32	watson	watson	NOUN
ijassa-499	25	33	estimator	estimator	NOUN
ijassa-499	25	34	[	[	X
ijassa-499	25	35	7	7	NUM
ijassa-499	25	36	]	]	X
ijassa-499	25	37	(	(	PUNCT
ijassa-499	25	38	as	as	ADP
ijassa-499	25	39	a	a	DET
ijassa-499	25	40	predictive	predictive	ADJ
ijassa-499	25	41	model	model	NOUN
ijassa-499	25	42	)	)	PUNCT
ijassa-499	25	43	and	and	CCONJ
ijassa-499	25	44	their	their	PRON
ijassa-499	25	45	sequence	sequence	NOUN
ijassa-499	25	46	is	be	AUX
ijassa-499	25	47	proposed	propose	VERB
ijassa-499	25	48	.	.	PUNCT
ijassa-499	26	1	however	however	ADV
ijassa-499	26	2	,	,	PUNCT
ijassa-499	26	3	there	there	PRON
ijassa-499	26	4	are	be	VERB
ijassa-499	26	5	major	major	ADJ
ijassa-499	26	6	problems	problem	NOUN
ijassa-499	26	7	with	with	ADP
ijassa-499	26	8	this	this	DET
ijassa-499	26	9	approach	approach	NOUN
ijassa-499	26	10	in	in	ADP
ijassa-499	26	11	the	the	DET
ijassa-499	26	12	case	case	NOUN
ijassa-499	26	13	of	of	ADP
ijassa-499	26	14	a	a	DET
ijassa-499	26	15	multidimensional	multidimensional	ADJ
ijassa-499	26	16	control	control	NOUN
ijassa-499	26	17	task	task	NOUN
ijassa-499	26	18	.	.	PUNCT
ijassa-499	27	1	on	on	ADP
ijassa-499	27	2	the	the	DET
ijassa-499	27	3	one	one	NUM
ijassa-499	27	4	hand	hand	NOUN
ijassa-499	27	5	,	,	PUNCT
ijassa-499	27	6	it	it	PRON
ijassa-499	27	7	is	be	AUX
ijassa-499	27	8	connected	connect	VERB
ijassa-499	27	9	with	with	ADP
ijassa-499	27	10	observations	observation	NOUN
ijassa-499	27	11	distribution	distribution	NOUN
ijassa-499	27	12	in	in	ADP
ijassa-499	27	13	a	a	DET
ijassa-499	27	14	highdimensional	highdimensional	ADJ
ijassa-499	27	15	feature	feature	NOUN
ijassa-499	27	16	space	space	NOUN
ijassa-499	27	17	(	(	PUNCT
ijassa-499	27	18	especially	especially	ADV
ijassa-499	27	19	in	in	ADP
ijassa-499	27	20	the	the	DET
ijassa-499	27	21	case	case	NOUN
ijassa-499	27	22	of	of	ADP
ijassa-499	27	23	small	small	ADJ
ijassa-499	27	24	number	number	NOUN
ijassa-499	27	25	of	of	ADP
ijassa-499	27	26	observations	observation	NOUN
ijassa-499	27	27	)	)	PUNCT
ijassa-499	27	28	.	.	PUNCT
ijassa-499	28	1	on	on	ADP
ijassa-499	28	2	the	the	DET
ijassa-499	28	3	other	other	ADJ
ijassa-499	28	4	hand	hand	NOUN
ijassa-499	28	5	,	,	PUNCT
ijassa-499	28	6	the	the	DET
ijassa-499	28	7	nadaraya	nadaraya	PROPN
ijassa-499	28	8	-	-	PUNCT
ijassa-499	28	9	watson	watson	PROPN
ijassa-499	28	10	estimator	estimator	NOUN
ijassa-499	28	11	has	have	VERB
ijassa-499	28	12	the	the	DET
ijassa-499	28	13	high	high	ADJ
ijassa-499	28	14	computational	computational	ADJ
ijassa-499	28	15	complexity	complexity	NOUN
ijassa-499	28	16	.	.	PUNCT
ijassa-499	29	1	the	the	DET
ijassa-499	29	2	bigger	big	ADJ
ijassa-499	29	3	feature	feature	NOUN
ijassa-499	29	4	space	space	NOUN
ijassa-499	29	5	dimension	dimension	NOUN
ijassa-499	29	6	,	,	PUNCT
ijassa-499	29	7	the	the	PRON
ijassa-499	29	8	harder	hard	ADJ
ijassa-499	29	9	to	to	PART
ijassa-499	29	10	optimize	optimize	VERB
ijassa-499	29	11	the	the	DET
ijassa-499	29	12	vector	vector	NOUN
ijassa-499	29	13	of	of	ADP
ijassa-499	29	14	bandwidths	bandwidth	NOUN
ijassa-499	29	15	.	.	PUNCT
ijassa-499	30	1	decision	decision	NOUN
ijassa-499	30	2	trees	tree	NOUN
ijassa-499	30	3	are	be	AUX
ijassa-499	30	4	used	use	VERB
ijassa-499	30	5	for	for	ADP
ijassa-499	30	6	solving	solve	VERB
ijassa-499	30	7	such	such	ADJ
ijassa-499	30	8	regression	regression	NOUN
ijassa-499	30	9	tasks	task	NOUN
ijassa-499	30	10	[	[	X
ijassa-499	30	11	8	8	NUM
ijassa-499	30	12	]	]	PUNCT
ijassa-499	30	13	.	.	PUNCT
ijassa-499	31	1	to	to	PART
ijassa-499	31	2	avoid	avoid	VERB
ijassa-499	31	3	these	these	DET
ijassa-499	31	4	problems	problem	NOUN
ijassa-499	31	5	it	it	PRON
ijassa-499	31	6	is	be	AUX
ijassa-499	31	7	suggested	suggest	VERB
ijassa-499	31	8	to	to	PART
ijassa-499	31	9	use	use	VERB
ijassa-499	31	10	a	a	DET
ijassa-499	31	11	decision	decision	NOUN
ijassa-499	31	12	tree	tree	NOUN
ijassa-499	31	13	instead	instead	ADV
ijassa-499	31	14	of	of	ADP
ijassa-499	31	15	the	the	DET
ijassa-499	31	16	nadaraya	nadaraya	PROPN
ijassa-499	31	17	-	-	PUNCT
ijassa-499	31	18	watson	watson	NOUN
ijassa-499	31	19	estimator	estimator	NOUN
ijassa-499	31	20	.	.	PUNCT
ijassa-499	32	1	in	in	ADP
ijassa-499	32	2	this	this	DET
ijassa-499	32	3	paper	paper	NOUN
ijassa-499	32	4	an	an	DET
ijassa-499	32	5	approach	approach	NOUN
ijassa-499	32	6	based	base	VERB
ijassa-499	32	7	on	on	ADP
ijassa-499	32	8	classification	classification	NOUN
ijassa-499	32	9	and	and	CCONJ
ijassa-499	32	10	regression	regression	NOUN
ijassa-499	32	11	tree	tree	NOUN
ijassa-499	32	12	(	(	PUNCT
ijassa-499	32	13	cart	cart	NOUN
ijassa-499	32	14	)	)	PUNCT
ijassa-499	32	15	is	be	AUX
ijassa-499	32	16	proposed	propose	VERB
ijassa-499	32	17	to	to	PART
ijassa-499	32	18	solve	solve	VERB
ijassa-499	32	19	control	control	NOUN
ijassa-499	32	20	tasks	task	NOUN
ijassa-499	32	21	.	.	PUNCT
ijassa-499	33	1	the	the	DET
ijassa-499	33	2	paper	paper	NOUN
ijassa-499	33	3	is	be	AUX
ijassa-499	33	4	organized	organize	VERB
ijassa-499	33	5	as	as	SCONJ
ijassa-499	33	6	follows	follow	VERB
ijassa-499	33	7	:	:	PUNCT
ijassa-499	33	8	in	in	ADP
ijassa-499	33	9	the	the	DET
ijassa-499	33	10	second	second	ADJ
ijassa-499	33	11	section	section	NOUN
ijassa-499	33	12	,	,	PUNCT
ijassa-499	33	13	statements	statement	NOUN
ijassa-499	33	14	of	of	ADP
ijassa-499	33	15	the	the	DET
ijassa-499	33	16	modeling	modeling	NOUN
ijassa-499	33	17	and	and	CCONJ
ijassa-499	33	18	control	control	NOUN
ijassa-499	33	19	problems	problem	NOUN
ijassa-499	33	20	are	be	AUX
ijassa-499	33	21	introduced	introduce	VERB
ijassa-499	33	22	;	;	PUNCT
ijassa-499	33	23	in	in	ADP
ijassa-499	33	24	the	the	DET
ijassa-499	33	25	third	third	ADJ
ijassa-499	33	26	section	section	NOUN
ijassa-499	33	27	,	,	PUNCT
ijassa-499	33	28	the	the	DET
ijassa-499	33	29	nonparametric	nonparametric	NOUN
ijassa-499	33	30	modeling	modeling	NOUN
ijassa-499	33	31	and	and	CCONJ
ijassa-499	33	32	control	control	NOUN
ijassa-499	33	33	algorithm	algorithm	NOUN
ijassa-499	33	34	based	base	VERB
ijassa-499	33	35	on	on	ADP
ijassa-499	33	36	the	the	DET
ijassa-499	33	37	nadaraya	nadaraya	PROPN
ijassa-499	33	38	-	-	PUNCT
ijassa-499	33	39	watson	watson	PROPN
ijassa-499	33	40	estimator	estimator	NOUN
ijassa-499	33	41	is	be	AUX
ijassa-499	33	42	presented	present	VERB
ijassa-499	33	43	;	;	PUNCT
ijassa-499	33	44	the	the	DET
ijassa-499	33	45	fourth	fourth	ADJ
ijassa-499	33	46	section	section	NOUN
ijassa-499	33	47	is	be	AUX
ijassa-499	33	48	devoted	devote	VERB
ijassa-499	33	49	to	to	ADP
ijassa-499	33	50	classification	classification	NOUN
ijassa-499	33	51	and	and	CCONJ
ijassa-499	33	52	regression	regression	NOUN
ijassa-499	33	53	tree	tree	NOUN
ijassa-499	33	54	(	(	PUNCT
ijassa-499	33	55	cart	cart	NOUN
ijassa-499	33	56	)	)	PUNCT
ijassa-499	33	57	and	and	CCONJ
ijassa-499	33	58	the	the	DET
ijassa-499	33	59	control	control	NOUN
ijassa-499	33	60	algorithm	algorithm	NOUN
ijassa-499	33	61	based	base	VERB
ijassa-499	33	62	on	on	ADP
ijassa-499	33	63	cart	cart	NOUN
ijassa-499	33	64	with	with	ADP
ijassa-499	33	65	its	its	PRON
ijassa-499	33	66	variants	variant	NOUN
ijassa-499	33	67	for	for	ADP
ijassa-499	33	68	different	different	ADJ
ijassa-499	33	69	control	control	NOUN
ijassa-499	33	70	task	task	NOUN
ijassa-499	33	71	statements	statement	NOUN
ijassa-499	33	72	.	.	PUNCT
ijassa-499	34	1	2	2	X
ijassa-499	34	2	.	.	X
ijassa-499	34	3	modeling	modeling	NOUN
ijassa-499	34	4	and	and	CCONJ
ijassa-499	34	5	control	control	NOUN
ijassa-499	34	6	tasks	task	NOUN
ijassa-499	34	7	the	the	DET
ijassa-499	34	8	block	block	NOUN
ijassa-499	34	9	scheme	scheme	NOUN
ijassa-499	34	10	of	of	ADP
ijassa-499	34	11	the	the	DET
ijassa-499	34	12	control	control	NOUN
ijassa-499	34	13	process	process	NOUN
ijassa-499	34	14	is	be	AUX
ijassa-499	34	15	shown	show	VERB
ijassa-499	34	16	in	in	ADP
ijassa-499	34	17	figure	figure	NOUN
ijassa-499	34	18	1	1	NUM
ijassa-499	34	19	.	.	PUNCT
ijassa-499	35	1	the	the	DET
ijassa-499	35	2	following	follow	VERB
ijassa-499	35	3	designations	designation	NOUN
ijassa-499	35	4	are	be	AUX
ijassa-499	35	5	taken	take	VERB
ijassa-499	35	6	:	:	PUNCT
ijassa-499	35	7	x̄	x̄	PRON
ijassa-499	35	8	is	be	AUX
ijassa-499	35	9	the	the	DET
ijassa-499	35	10	vector	vector	NOUN
ijassa-499	35	11	of	of	ADP
ijassa-499	35	12	output	output	NOUN
ijassa-499	35	13	variables	variable	NOUN
ijassa-499	35	14	,	,	PUNCT
ijassa-499	35	15	x̄∗	x̄∗	SCONJ
ijassa-499	35	16	is	be	AUX
ijassa-499	35	17	the	the	DET
ijassa-499	35	18	vector	vector	NOUN
ijassa-499	35	19	of	of	ADP
ijassa-499	35	20	the	the	DET
ijassa-499	35	21	desired	desire	VERB
ijassa-499	35	22	output	output	NOUN
ijassa-499	35	23	x̄	x̄	PROPN
ijassa-499	35	24	values	value	NOUN
ijassa-499	35	25	,	,	PUNCT
ijassa-499	35	26	ū	ū	NOUN
ijassa-499	35	27	is	be	AUX
ijassa-499	35	28	the	the	DET
ijassa-499	35	29	vector	vector	NOUN
ijassa-499	35	30	of	of	ADP
ijassa-499	35	31	controlled	control	VERB
ijassa-499	35	32	inputs	input	NOUN
ijassa-499	35	33	,	,	PUNCT
ijassa-499	35	34	v̄	v̄	PROPN
ijassa-499	35	35	is	be	AUX
ijassa-499	35	36	the	the	DET
ijassa-499	35	37	vector	vector	NOUN
ijassa-499	35	38	of	of	ADP
ijassa-499	35	39	observed	observed	ADJ
ijassa-499	35	40	uncontrolled	uncontrolled	ADJ
ijassa-499	35	41	inputs	input	NOUN
ijassa-499	35	42	,	,	PUNCT
ijassa-499	35	43	ξ	ξ	X
ijassa-499	35	44	is	be	AUX
ijassa-499	35	45	the	the	DET
ijassa-499	35	46	unobserved	unobserved	ADJ
ijassa-499	35	47	input	input	NOUN
ijassa-499	35	48	(	(	PUNCT
ijassa-499	35	49	noise	noise	NOUN
ijassa-499	35	50	)	)	PUNCT
ijassa-499	35	51	.	.	PUNCT
ijassa-499	36	1	fig.1	fig.1	ADJ
ijassa-499	36	2	the	the	DET
ijassa-499	36	3	block	block	NOUN
ijassa-499	36	4	scheme	scheme	NOUN
ijassa-499	36	5	of	of	ADP
ijassa-499	36	6	the	the	DET
ijassa-499	36	7	control	control	NOUN
ijassa-499	36	8	process	process	NOUN
ijassa-499	36	9	it	it	PRON
ijassa-499	36	10	is	be	AUX
ijassa-499	36	11	evident	evident	ADJ
ijassa-499	36	12	from	from	ADP
ijassa-499	36	13	figure	figure	NOUN
ijassa-499	36	14	1	1	NUM
ijassa-499	36	15	that	that	SCONJ
ijassa-499	36	16	the	the	DET
ijassa-499	36	17	output	output	NOUN
ijassa-499	36	18	variables	variable	NOUN
ijassa-499	36	19	x̄	x̄	PRON
ijassa-499	36	20	depend	depend	VERB
ijassa-499	36	21	on	on	ADP
ijassa-499	36	22	the	the	DET
ijassa-499	36	23	inputs	input	NOUN
ijassa-499	36	24	ū	ū	NOUN
ijassa-499	36	25	,	,	PUNCT
ijassa-499	36	26	v̄	v̄	PROPN
ijassa-499	36	27	,	,	PUNCT
ijassa-499	36	28	ξ	ξ	X
ijassa-499	36	29	.	.	PUNCT
ijassa-499	37	1	the	the	DET
ijassa-499	37	2	control	control	PROPN
ijassa-499	37	3	task	task	NOUN
ijassa-499	37	4	is	be	AUX
ijassa-499	37	5	to	to	PART
ijassa-499	37	6	build	build	VERB
ijassa-499	37	7	a	a	DET
ijassa-499	37	8	control	control	NOUN
ijassa-499	37	9	unit	unit	NOUN
ijassa-499	37	10	which	which	PRON
ijassa-499	37	11	generates	generate	VERB
ijassa-499	37	12	ū	ū	NOUN
ijassa-499	37	13	such	such	ADJ
ijassa-499	37	14	that	that	SCONJ
ijassa-499	37	15	e	e	NOUN
ijassa-499	37	16	(	(	PUNCT
ijassa-499	37	17	x̄	x̄	NOUN
ijassa-499	37	18	,	,	PUNCT
ijassa-499	37	19	x̄∗	x̄∗	ADJ
ijassa-499	37	20	)	)	PUNCT
ijassa-499	37	21	is	be	AUX
ijassa-499	37	22	minimized	minimize	VERB
ijassa-499	37	23	,	,	PUNCT
ijassa-499	37	24	where	where	SCONJ
ijassa-499	37	25	e	e	NOUN
ijassa-499	37	26	is	be	AUX
ijassa-499	37	27	some	some	DET
ijassa-499	37	28	error	error	NOUN
ijassa-499	37	29	measurement	measurement	NOUN
ijassa-499	37	30	.	.	PUNCT
ijassa-499	38	1	the	the	DET
ijassa-499	38	2	modeling	modeling	NOUN
ijassa-499	38	3	(	(	PUNCT
ijassa-499	38	4	regression	regression	NOUN
ijassa-499	38	5	)	)	PUNCT
ijassa-499	38	6	and	and	CCONJ
ijassa-499	38	7	control	control	NOUN
ijassa-499	38	8	tasks	task	NOUN
ijassa-499	38	9	are	be	AUX
ijassa-499	38	10	adjacent	adjacent	ADJ
ijassa-499	38	11	.	.	PUNCT
ijassa-499	39	1	if	if	SCONJ
ijassa-499	39	2	a	a	DET
ijassa-499	39	3	system	system	NOUN
ijassa-499	39	4	reaction	reaction	NOUN
ijassa-499	39	5	to	to	ADP
ijassa-499	39	6	an	an	DET
ijassa-499	39	7	input	input	NOUN
ijassa-499	39	8	(	(	PUNCT
ijassa-499	39	9	prediction	prediction	NOUN
ijassa-499	39	10	)	)	PUNCT
ijassa-499	39	11	is	be	AUX
ijassa-499	39	12	known	know	VERB
ijassa-499	39	13	,	,	PUNCT
ijassa-499	39	14	it	it	PRON
ijassa-499	39	15	is	be	AUX
ijassa-499	39	16	possible	possible	ADJ
ijassa-499	39	17	to	to	PART
ijassa-499	39	18	get	get	VERB
ijassa-499	39	19	the	the	DET
ijassa-499	39	20	desired	desire	VERB
ijassa-499	39	21	outputs	output	NOUN
ijassa-499	39	22	by	by	ADP
ijassa-499	39	23	identifying	identify	VERB
ijassa-499	39	24	the	the	DET
ijassa-499	39	25	controlled	control	VERB
ijassa-499	39	26	inputs	input	NOUN
ijassa-499	39	27	[	[	X
ijassa-499	39	28	9	9	NUM
ijassa-499	39	29	]	]	PUNCT
ijassa-499	39	30	.	.	PUNCT
ijassa-499	40	1	the	the	DET
ijassa-499	40	2	forward	forward	ADJ
ijassa-499	40	3	model	model	NOUN
ijassa-499	40	4	(	(	PUNCT
ijassa-499	40	5	regression	regression	NOUN
ijassa-499	40	6	model	model	NOUN
ijassa-499	40	7	)	)	PUNCT
ijassa-499	40	8	x̂	x̂	PUNCT
ijassa-499	40	9	(	(	PUNCT
ijassa-499	40	10	ū	ū	NOUN
ijassa-499	40	11	,	,	PUNCT
ijassa-499	40	12	v̄	v̄	NOUN
ijassa-499	40	13	)	)	PUNCT
ijassa-499	40	14	is	be	AUX
ijassa-499	40	15	fit	fit	ADJ
ijassa-499	40	16	using	use	VERB
ijassa-499	40	17	the	the	DET
ijassa-499	40	18	training	training	NOUN
ijassa-499	40	19	set	set	NOUN
ijassa-499	40	20	(	(	PUNCT
ijassa-499	40	21	ūi	ūi	PROPN
ijassa-499	40	22	,	,	PUNCT
ijassa-499	40	23	v̄i	v̄i	PROPN
ijassa-499	40	24	,	,	PUNCT
ijassa-499	40	25	x̄i	x̄i	PROPN
ijassa-499	40	26	,	,	PUNCT
ijassa-499	40	27	i	i	NOUN
ijassa-499	40	28	=	=	NOUN
ijassa-499	40	29	1	1	NUM
ijassa-499	40	30	,	,	PUNCT
ijassa-499	40	31	...	...	PUNCT
ijassa-499	40	32	,	,	PUNCT
ijassa-499	40	33	n	n	CCONJ
ijassa-499	40	34	)	)	PUNCT
ijassa-499	40	35	,	,	PUNCT
ijassa-499	40	36	where	where	SCONJ
ijassa-499	40	37	n	n	PRON
ijassa-499	40	38	is	be	AUX
ijassa-499	40	39	the	the	DET
ijassa-499	40	40	observations	observation	NOUN
ijassa-499	40	41	number	number	NOUN
ijassa-499	40	42	(	(	PUNCT
ijassa-499	40	43	figure	figure	NOUN
ijassa-499	40	44	2	2	NUM
ijassa-499	40	45	)	)	PUNCT
ijassa-499	40	46	.	.	PUNCT
ijassa-499	41	1	using	use	VERB
ijassa-499	41	2	the	the	DET
ijassa-499	41	3	forward	forward	ADJ
ijassa-499	41	4	model	model	NOUN
ijassa-499	41	5	x̂	x̂	PUNCT
ijassa-499	42	1	(	(	PUNCT
ijassa-499	42	2	ū	ū	NOUN
ijassa-499	42	3	,	,	PUNCT
ijassa-499	42	4	v̄	v̄	NOUN
ijassa-499	42	5	)	)	PUNCT
ijassa-499	42	6	the	the	DET
ijassa-499	42	7	reactions	reaction	NOUN
ijassa-499	42	8	to	to	ADP
ijassa-499	42	9	a	a	DET
ijassa-499	42	10	given	give	VERB
ijassa-499	42	11	input	input	NOUN
ijassa-499	42	12	can	can	AUX
ijassa-499	42	13	be	be	AUX
ijassa-499	42	14	predicted	predict	VERB
ijassa-499	42	15	.	.	PUNCT
ijassa-499	43	1	for	for	ADP
ijassa-499	43	2	control	control	NOUN
ijassa-499	43	3	task	task	NOUN
ijassa-499	43	4	solving	solving	NOUN
ijassa-499	43	5	,	,	PUNCT
ijassa-499	43	6	it	it	PRON
ijassa-499	43	7	is	be	AUX
ijassa-499	43	8	necessary	necessary	ADJ
ijassa-499	43	9	to	to	PART
ijassa-499	43	10	invert	invert	VERB
ijassa-499	43	11	the	the	DET
ijassa-499	43	12	model	model	NOUN
ijassa-499	43	13	x̂	x̂	PUNCT
ijassa-499	44	1	(	(	PUNCT
ijassa-499	44	2	ū	ū	NOUN
ijassa-499	44	3	,	,	PUNCT
ijassa-499	44	4	v̄	v̄	NOUN
ijassa-499	44	5	)	)	PUNCT
ijassa-499	44	6	.	.	PUNCT
ijassa-499	45	1	it	it	PRON
ijassa-499	45	2	means	mean	VERB
ijassa-499	45	3	that	that	SCONJ
ijassa-499	45	4	we	we	PRON
ijassa-499	45	5	should	should	AUX
ijassa-499	45	6	find	find	VERB
ijassa-499	45	7	controlled	control	VERB
ijassa-499	45	8	inputs	input	NOUN
ijassa-499	45	9	ū∗	ū∗	PROPN
ijassa-499	45	10	that	that	PRON
ijassa-499	45	11	could	could	AUX
ijassa-499	45	12	result	result	VERB
ijassa-499	45	13	in	in	ADP
ijassa-499	45	14	the	the	DET
ijassa-499	45	15	desired	desire	VERB
ijassa-499	45	16	outputs	output	NOUN
ijassa-499	45	17	x̄∗	x̄∗	ADP
ijassa-499	45	18	in	in	ADP
ijassa-499	45	19	the	the	DET
ijassa-499	45	20	case	case	NOUN
ijassa-499	45	21	of	of	ADP
ijassa-499	45	22	estimated	estimate	VERB
ijassa-499	45	23	copyright	copyright	NOUN
ijassa-499	45	24	c	c	ADP
ijassa-499	45	25	©	©	PROPN
ijassa-499	45	26	2017	2017	NUM
ijassa-499	45	27	assa	assa	NOUN
ijassa-499	45	28	.	.	PUNCT
ijassa-499	46	1	adv	adv	PROPN
ijassa-499	46	2	syst	syst	PROPN
ijassa-499	46	3	sci	sci	PROPN
ijassa-499	46	4	appl	appl	PROPN
ijassa-499	46	5	(	(	PUNCT
ijassa-499	46	6	2017	2017	NUM
ijassa-499	46	7	)	)	PUNCT
ijassa-499	46	8	60	60	NUM
ijassa-499	46	9	e.	e.	PROPN
ijassa-499	46	10	mangalova	mangalova	PROPN
ijassa-499	47	1	fig.2	fig.2	PROPN
ijassa-499	47	2	forward	forward	PROPN
ijassa-499	47	3	model	model	NOUN
ijassa-499	47	4	scheme	scheme	NOUN
ijassa-499	47	5	(	(	PUNCT
ijassa-499	47	6	regression	regression	NOUN
ijassa-499	47	7	task	task	NOUN
ijassa-499	47	8	)	)	PUNCT
ijassa-499	47	9	uncontrolled	uncontrolled	ADJ
ijassa-499	47	10	inputs	input	NOUN
ijassa-499	47	11	v̄predicted	v̄predicte	VERB
ijassa-499	47	12	(	(	PUNCT
ijassa-499	47	13	figure	figure	NOUN
ijassa-499	47	14	3	3	NUM
ijassa-499	47	15	)	)	PUNCT
ijassa-499	47	16	.	.	PUNCT
ijassa-499	48	1	in	in	ADP
ijassa-499	48	2	contrast	contrast	NOUN
ijassa-499	48	3	to	to	ADP
ijassa-499	48	4	the	the	DET
ijassa-499	48	5	forward	forward	ADJ
ijassa-499	48	6	model	model	NOUN
ijassa-499	48	7	,	,	PUNCT
ijassa-499	48	8	the	the	DET
ijassa-499	48	9	backward	backward	ADJ
ijassa-499	48	10	model	model	NOUN
ijassa-499	48	11	û	û	X
ijassa-499	48	12	(	(	PUNCT
ijassa-499	48	13	x̄∗	x̄∗	PROPN
ijassa-499	48	14	,	,	PUNCT
ijassa-499	48	15	v̄predicted	v̄predicte	VERB
ijassa-499	48	16	)	)	PUNCT
ijassa-499	48	17	is	be	AUX
ijassa-499	48	18	fit	fit	ADJ
ijassa-499	48	19	using	use	VERB
ijassa-499	48	20	the	the	DET
ijassa-499	48	21	training	training	NOUN
ijassa-499	48	22	set	set	NOUN
ijassa-499	48	23	(	(	PUNCT
ijassa-499	48	24	ūi	ūi	PROPN
ijassa-499	48	25	,	,	PUNCT
ijassa-499	48	26	v̄i	v̄i	PROPN
ijassa-499	48	27	,	,	PUNCT
ijassa-499	48	28	x̄i	x̄i	PROPN
ijassa-499	48	29	,	,	PUNCT
ijassa-499	48	30	i	i	NOUN
ijassa-499	48	31	=	=	NOUN
ijassa-499	48	32	1	1	NUM
ijassa-499	48	33	,	,	PUNCT
ijassa-499	48	34	...	...	PUNCT
ijassa-499	48	35	,	,	PUNCT
ijassa-499	48	36	n	n	CCONJ
ijassa-499	48	37	)	)	PUNCT
ijassa-499	48	38	such	such	ADJ
ijassa-499	48	39	that	that	SCONJ
ijassa-499	48	40	the	the	DET
ijassa-499	48	41	outputs	output	NOUN
ijassa-499	48	42	are	be	AUX
ijassa-499	48	43	given	give	VERB
ijassa-499	48	44	,	,	PUNCT
ijassa-499	48	45	uncontrolled	uncontrolled	ADJ
ijassa-499	48	46	inputs	input	NOUN
ijassa-499	48	47	are	be	AUX
ijassa-499	48	48	predicted	predict	VERB
ijassa-499	48	49	and	and	CCONJ
ijassa-499	48	50	we	we	PRON
ijassa-499	48	51	need	need	VERB
ijassa-499	48	52	to	to	PART
ijassa-499	48	53	determine	determine	VERB
ijassa-499	48	54	an	an	DET
ijassa-499	48	55	appropriate	appropriate	ADJ
ijassa-499	48	56	controlled	control	VERB
ijassa-499	48	57	input	input	NOUN
ijassa-499	48	58	.	.	PUNCT
ijassa-499	49	1	fig.3	fig.3	ADJ
ijassa-499	49	2	backward	backward	ADJ
ijassa-499	49	3	model	model	NOUN
ijassa-499	49	4	scheme	scheme	NOUN
ijassa-499	49	5	(	(	PUNCT
ijassa-499	49	6	control	control	NOUN
ijassa-499	49	7	task	task	NOUN
ijassa-499	49	8	)	)	PUNCT
ijassa-499	49	9	3	3	NUM
ijassa-499	49	10	.	.	X
ijassa-499	49	11	nadaraya	nadaraya	PROPN
ijassa-499	49	12	-	-	PUNCT
ijassa-499	49	13	watson	watson	PROPN
ijassa-499	49	14	estimator	estimator	NOUN
ijassa-499	49	15	approach	approach	VERB
ijassa-499	49	16	the	the	DET
ijassa-499	49	17	nadaraya	nadaraya	PROPN
ijassa-499	49	18	-	-	PUNCT
ijassa-499	49	19	watson	watson	PROPN
ijassa-499	49	20	estimator	estimator	NOUN
ijassa-499	49	21	approach	approach	NOUN
ijassa-499	49	22	was	be	AUX
ijassa-499	49	23	proposed	propose	VERB
ijassa-499	49	24	to	to	PART
ijassa-499	49	25	solve	solve	VERB
ijassa-499	49	26	control	control	NOUN
ijassa-499	49	27	tasks	task	NOUN
ijassa-499	49	28	in	in	ADP
ijassa-499	49	29	such	such	ADJ
ijassa-499	49	30	forward	forward	ADJ
ijassa-499	49	31	-	-	PUNCT
ijassa-499	49	32	backward	backward	ADJ
ijassa-499	49	33	models	model	NOUN
ijassa-499	49	34	statement	statement	VERB
ijassa-499	50	1	[	[	X
ijassa-499	50	2	6	6	NUM
ijassa-499	50	3	]	]	PUNCT
ijassa-499	50	4	.	.	PUNCT
ijassa-499	51	1	3.1	3.1	NUM
ijassa-499	51	2	.	.	PUNCT
ijassa-499	52	1	modeling	model	VERB
ijassa-499	52	2	the	the	DET
ijassa-499	52	3	nadaraya	nadaraya	PROPN
ijassa-499	52	4	-	-	PUNCT
ijassa-499	52	5	watson	watson	PROPN
ijassa-499	52	6	estimator	estimator	NOUN
ijassa-499	52	7	has	have	AUX
ijassa-499	52	8	been	be	AUX
ijassa-499	52	9	widely	widely	ADV
ijassa-499	52	10	applied	apply	VERB
ijassa-499	52	11	for	for	ADP
ijassa-499	52	12	the	the	DET
ijassa-499	52	13	nonparametric	nonparametric	NOUN
ijassa-499	52	14	regression	regression	NOUN
ijassa-499	52	15	,	,	PUNCT
ijassa-499	52	16	using	use	VERB
ijassa-499	52	17	the	the	DET
ijassa-499	52	18	weighted	weight	VERB
ijassa-499	52	19	average	average	ADJ
ijassa-499	52	20	observations	observation	NOUN
ijassa-499	52	21	output	output	NOUN
ijassa-499	52	22	in	in	ADP
ijassa-499	52	23	the	the	DET
ijassa-499	52	24	neighborhood	neighborhood	NOUN
ijassa-499	52	25	around	around	ADV
ijassa-499	52	26	(	(	PUNCT
ijassa-499	52	27	ū	ū	NOUN
ijassa-499	52	28	,	,	PUNCT
ijassa-499	52	29	v̄	v̄	NUM
ijassa-499	52	30	):	):	PUNCT
ijassa-499	52	31	x̂k	x̂k	PROPN
ijassa-499	53	1	(	(	PUNCT
ijassa-499	53	2	ū	ū	NOUN
ijassa-499	53	3	,	,	PUNCT
ijassa-499	53	4	v̄	v̄	NOUN
ijassa-499	53	5	)	)	PUNCT
ijassa-499	54	1	=	=	SYM
ijassa-499	55	1	∑n	∑n	PROPN
ijassa-499	55	2	i=1	i=1	PROPN
ijassa-499	55	3	xi	xi	PROPN
ijassa-499	55	4	∏mu	∏mu	PROPN
ijassa-499	55	5	j=1k	j=1k	PROPN
ijassa-499	55	6	(	(	PUNCT
ijassa-499	55	7	uj	uj	PROPN
ijassa-499	55	8	,	,	PUNCT
ijassa-499	55	9	uji	uji	PROPN
ijassa-499	55	10	,	,	PUNCT
ijassa-499	55	11	c	c	PROPN
ijassa-499	55	12	j	j	PROPN
ijassa-499	55	13	u	u	NOUN
ijassa-499	55	14	)	)	PUNCT
ijassa-499	55	15	∏mv	∏mv	NOUN
ijassa-499	55	16	j=1k	j=1k	NOUN
ijassa-499	55	17	(	(	PUNCT
ijassa-499	55	18	vj	vj	PROPN
ijassa-499	55	19	,	,	PUNCT
ijassa-499	55	20	vji	vji	VERB
ijassa-499	55	21	,	,	PUNCT
ijassa-499	55	22	c	c	PROPN
ijassa-499	55	23	j	j	PROPN
ijassa-499	55	24	v	v	X
ijassa-499	55	25	)	)	PUNCT
ijassa-499	55	26	∑n	∑n	PROPN
ijassa-499	55	27	i=1	i=1	PROPN
ijassa-499	55	28	∏mu	∏mu	PROPN
ijassa-499	55	29	j=1k	j=1k	PROPN
ijassa-499	55	30	(	(	PUNCT
ijassa-499	55	31	uj	uj	PROPN
ijassa-499	55	32	,	,	PUNCT
ijassa-499	55	33	uji	uji	PROPN
ijassa-499	55	34	,	,	PUNCT
ijassa-499	55	35	c	c	PROPN
ijassa-499	55	36	j	j	PROPN
ijassa-499	55	37	u	u	NOUN
ijassa-499	55	38	)	)	PUNCT
ijassa-499	55	39	∏mv	∏mv	NOUN
ijassa-499	55	40	j=1k	j=1k	NOUN
ijassa-499	55	41	(	(	PUNCT
ijassa-499	55	42	vj	vj	PROPN
ijassa-499	55	43	,	,	PUNCT
ijassa-499	55	44	vji	vji	VERB
ijassa-499	55	45	,	,	PUNCT
ijassa-499	55	46	c	c	PROPN
ijassa-499	55	47	j	j	PROPN
ijassa-499	55	48	v	v	PROPN
ijassa-499	55	49	)	)	PUNCT
ijassa-499	55	50	,	,	PUNCT
ijassa-499	55	51	k	k	X
ijassa-499	55	52	=	=	SYM
ijassa-499	55	53	1	1	NUM
ijassa-499	55	54	,	,	PUNCT
ijassa-499	55	55	...	...	PUNCT
ijassa-499	55	56	,	,	PUNCT
ijassa-499	55	57	mx	mx	PROPN
ijassa-499	55	58	,	,	PUNCT
ijassa-499	55	59	(	(	PUNCT
ijassa-499	55	60	3.1	3.1	NUM
ijassa-499	55	61	)	)	PUNCT
ijassa-499	55	62	where	where	SCONJ
ijassa-499	55	63	the	the	DET
ijassa-499	55	64	kernel	kernel	PROPN
ijassa-499	55	65	function	function	PROPN
ijassa-499	55	66	k	k	PROPN
ijassa-499	55	67	is	be	AUX
ijassa-499	55	68	a	a	DET
ijassa-499	55	69	non	non	ADJ
ijassa-499	55	70	-	-	ADJ
ijassa-499	55	71	negative	negative	ADJ
ijassa-499	55	72	function	function	NOUN
ijassa-499	55	73	that	that	PRON
ijassa-499	55	74	integrates	integrate	VERB
ijassa-499	55	75	to	to	ADP
ijassa-499	55	76	one	one	NUM
ijassa-499	55	77	and	and	CCONJ
ijassa-499	55	78	has	have	VERB
ijassa-499	55	79	zero	zero	NUM
ijassa-499	55	80	mean	mean	NOUN
ijassa-499	55	81	,	,	PUNCT
ijassa-499	55	82	c̄u	c̄u	NOUN
ijassa-499	55	83	,	,	PUNCT
ijassa-499	55	84	c̄v	c̄v	PROPN
ijassa-499	55	85	are	be	AUX
ijassa-499	55	86	the	the	DET
ijassa-499	55	87	vectors	vector	NOUN
ijassa-499	55	88	of	of	ADP
ijassa-499	55	89	bandwidths	bandwidth	NOUN
ijassa-499	55	90	,	,	PUNCT
ijassa-499	55	91	mx	mx	PROPN
ijassa-499	55	92	is	be	AUX
ijassa-499	55	93	the	the	DET
ijassa-499	55	94	number	number	NOUN
ijassa-499	55	95	of	of	ADP
ijassa-499	55	96	output	output	NOUN
ijassa-499	55	97	variables	variable	NOUN
ijassa-499	55	98	.	.	PUNCT
ijassa-499	56	1	to	to	PART
ijassa-499	56	2	identify	identify	VERB
ijassa-499	56	3	the	the	DET
ijassa-499	56	4	forward	forward	ADJ
ijassa-499	56	5	models	model	NOUN
ijassa-499	56	6	x̂k	x̂k	PUNCT
ijassa-499	57	1	(	(	PUNCT
ijassa-499	57	2	ū	ū	NOUN
ijassa-499	57	3	,	,	PUNCT
ijassa-499	57	4	v̄	v̄	NOUN
ijassa-499	57	5	)	)	PUNCT
ijassa-499	57	6	,	,	PUNCT
ijassa-499	57	7	the	the	DET
ijassa-499	57	8	bandwidths	bandwidth	NOUN
ijassa-499	57	9	c̄u	c̄u	NOUN
ijassa-499	57	10	,	,	PUNCT
ijassa-499	57	11	c̄v	c̄v	PROPN
ijassa-499	57	12	should	should	AUX
ijassa-499	57	13	be	be	AUX
ijassa-499	57	14	optimized	optimize	VERB
ijassa-499	57	15	according	accord	VERB
ijassa-499	57	16	to	to	ADP
ijassa-499	57	17	the	the	DET
ijassa-499	57	18	selected	select	VERB
ijassa-499	57	19	accuracy	accuracy	NOUN
ijassa-499	57	20	measurement	measurement	NOUN
ijassa-499	57	21	.	.	PUNCT
ijassa-499	58	1	3.2	3.2	NUM
ijassa-499	58	2	.	.	PUNCT
ijassa-499	59	1	control	control	VERB
ijassa-499	59	2	backward	backward	ADJ
ijassa-499	59	3	models	model	NOUN
ijassa-499	59	4	of	of	ADP
ijassa-499	59	5	nadaraya	nadaraya	PROPN
ijassa-499	59	6	-	-	PUNCT
ijassa-499	59	7	watson	watson	NOUN
ijassa-499	59	8	estimators	estimator	NOUN
ijassa-499	59	9	have	have	VERB
ijassa-499	59	10	the	the	DET
ijassa-499	59	11	following	follow	VERB
ijassa-499	59	12	form	form	NOUN
ijassa-499	59	13	:	:	PUNCT
ijassa-499	59	14	copyright	copyright	NOUN
ijassa-499	59	15	c	c	ADP
ijassa-499	59	16	©	©	PROPN
ijassa-499	59	17	2017	2017	NUM
ijassa-499	59	18	assa	assa	NOUN
ijassa-499	59	19	.	.	PUNCT
ijassa-499	60	1	adv	adv	PROPN
ijassa-499	60	2	syst	syst	PROPN
ijassa-499	60	3	sci	sci	PROPN
ijassa-499	60	4	appl	appl	PROPN
ijassa-499	60	5	(	(	PUNCT
ijassa-499	60	6	2017	2017	NUM
ijassa-499	60	7	)	)	PUNCT
ijassa-499	60	8	regression	regression	NOUN
ijassa-499	60	9	tree	tree	NOUN
ijassa-499	60	10	control	control	NOUN
ijassa-499	60	11	of	of	ADP
ijassa-499	60	12	multidimensional	multidimensional	ADJ
ijassa-499	60	13	static	static	ADJ
ijassa-499	60	14	object	object	NOUN
ijassa-499	60	15	61	61	NUM
ijassa-499	60	16	ûm	ûm	NOUN
ijassa-499	60	17	(	(	PUNCT
ijassa-499	60	18	u1	u1	NOUN
ijassa-499	60	19	,	,	PUNCT
ijassa-499	60	20	...	...	PUNCT
ijassa-499	60	21	,	,	PUNCT
ijassa-499	60	22	um−1	um−1	PROPN
ijassa-499	60	23	,	,	PUNCT
ijassa-499	60	24	x̄	x̄	NOUN
ijassa-499	60	25	,	,	PUNCT
ijassa-499	60	26	v̄	v̄	NOUN
ijassa-499	60	27	)	)	PUNCT
ijassa-499	61	1	=	=	NOUN
ijassa-499	62	1	∑n	∑n	PROPN
ijassa-499	62	2	i=1	i=1	PROPN
ijassa-499	63	1	u	u	NOUN
ijassa-499	63	2	m	m	VERB
ijassa-499	63	3	i	i	NOUN
ijassa-499	63	4	∏m−1	∏m−1	PROPN
ijassa-499	64	1	j=1	j=1	PROPN
ijassa-499	64	2	k	k	PROPN
ijassa-499	64	3	(	(	PUNCT
ijassa-499	64	4	uj	uj	PROPN
ijassa-499	64	5	,	,	PUNCT
ijassa-499	64	6	uji	uji	PROPN
ijassa-499	64	7	,	,	PUNCT
ijassa-499	64	8	c	c	PROPN
ijassa-499	64	9	j	j	PROPN
ijassa-499	64	10	u	u	NOUN
ijassa-499	64	11	)	)	PUNCT
ijassa-499	64	12	∏mv	∏mv	NOUN
ijassa-499	64	13	j=1k	j=1k	NOUN
ijassa-499	64	14	(	(	PUNCT
ijassa-499	64	15	vj	vj	PROPN
ijassa-499	64	16	,	,	PUNCT
ijassa-499	64	17	vji	vji	VERB
ijassa-499	64	18	,	,	PUNCT
ijassa-499	64	19	c	c	PROPN
ijassa-499	64	20	j	j	PROPN
ijassa-499	64	21	v	v	PROPN
ijassa-499	64	22	)	)	PUNCT
ijassa-499	64	23	∏mx	∏mx	NOUN
ijassa-499	64	24	j=1k	j=1k	NOUN
ijassa-499	64	25	(	(	PUNCT
ijassa-499	64	26	xj∗	xj∗	PROPN
ijassa-499	64	27	,	,	PUNCT
ijassa-499	64	28	xji	xji	PROPN
ijassa-499	64	29	,	,	PUNCT
ijassa-499	64	30	c	c	PROPN
ijassa-499	64	31	j	j	PROPN
ijassa-499	64	32	x	x	X
ijassa-499	64	33	)	)	PUNCT
ijassa-499	65	1	∑n	∑n	PROPN
ijassa-499	65	2	i=1	i=1	PROPN
ijassa-499	65	3	∏m−1	∏m−1	PROPN
ijassa-499	66	1	j=1	j=1	PROPN
ijassa-499	66	2	k	k	PROPN
ijassa-499	66	3	(	(	PUNCT
ijassa-499	66	4	uj	uj	PROPN
ijassa-499	66	5	,	,	PUNCT
ijassa-499	66	6	uji	uji	PROPN
ijassa-499	66	7	,	,	PUNCT
ijassa-499	66	8	c	c	PROPN
ijassa-499	66	9	j	j	PROPN
ijassa-499	66	10	u	u	NOUN
ijassa-499	66	11	)	)	PUNCT
ijassa-499	66	12	∏mv	∏mv	NOUN
ijassa-499	66	13	j=1k	j=1k	NOUN
ijassa-499	66	14	(	(	PUNCT
ijassa-499	66	15	vj	vj	PROPN
ijassa-499	66	16	,	,	PUNCT
ijassa-499	66	17	vji	vji	VERB
ijassa-499	66	18	,	,	PUNCT
ijassa-499	66	19	c	c	PROPN
ijassa-499	66	20	j	j	PROPN
ijassa-499	66	21	v	v	PROPN
ijassa-499	66	22	)	)	PUNCT
ijassa-499	66	23	∏mx	∏mx	NOUN
ijassa-499	66	24	j=1k	j=1k	NOUN
ijassa-499	66	25	(	(	PUNCT
ijassa-499	66	26	xj∗	xj∗	PROPN
ijassa-499	66	27	,	,	PUNCT
ijassa-499	66	28	xji	xji	PROPN
ijassa-499	66	29	,	,	PUNCT
ijassa-499	66	30	c	c	PROPN
ijassa-499	66	31	j	j	PROPN
ijassa-499	66	32	x	x	PROPN
ijassa-499	66	33	)	)	PUNCT
ijassa-499	66	34	,	,	PUNCT
ijassa-499	66	35	m	m	VERB
ijassa-499	66	36	=	=	NOUN
ijassa-499	66	37	1	1	NUM
ijassa-499	66	38	,	,	PUNCT
ijassa-499	66	39	...	...	PUNCT
ijassa-499	66	40	,	,	PUNCT
ijassa-499	66	41	mu	mu	PROPN
ijassa-499	66	42	,	,	PUNCT
ijassa-499	66	43	(	(	PUNCT
ijassa-499	66	44	3.2	3.2	NUM
ijassa-499	66	45	)	)	PUNCT
ijassa-499	66	46	the	the	DET
ijassa-499	66	47	bandwidths	bandwidth	NOUN
ijassa-499	66	48	c̄u	c̄u	NOUN
ijassa-499	66	49	,	,	PUNCT
ijassa-499	66	50	c̄v	c̄v	VERB
ijassa-499	66	51	in	in	ADP
ijassa-499	66	52	the	the	DET
ijassa-499	66	53	equations	equation	NOUN
ijassa-499	66	54	(	(	PUNCT
ijassa-499	66	55	3.1	3.1	NUM
ijassa-499	66	56	)	)	PUNCT
ijassa-499	66	57	and	and	CCONJ
ijassa-499	66	58	(	(	PUNCT
ijassa-499	66	59	3.2	3.2	NUM
ijassa-499	66	60	)	)	PUNCT
ijassa-499	66	61	are	be	AUX
ijassa-499	66	62	not	not	PART
ijassa-499	66	63	identical	identical	ADJ
ijassa-499	66	64	.	.	PUNCT
ijassa-499	67	1	there	there	PRON
ijassa-499	67	2	are	be	VERB
ijassa-499	67	3	some	some	DET
ijassa-499	67	4	important	important	ADJ
ijassa-499	67	5	limitations	limitation	NOUN
ijassa-499	67	6	on	on	ADP
ijassa-499	67	7	the	the	DET
ijassa-499	67	8	nadaraya	nadaraya	PROPN
ijassa-499	67	9	-	-	PUNCT
ijassa-499	67	10	watson	watson	NOUN
ijassa-499	67	11	algorithm	algorithm	NOUN
ijassa-499	67	12	implementation	implementation	NOUN
ijassa-499	67	13	:	:	PUNCT
ijassa-499	67	14	•	•	NUM
ijassa-499	67	15	ranking	rank	VERB
ijassa-499	67	16	input	input	NOUN
ijassa-499	67	17	features	feature	NOUN
ijassa-499	67	18	.	.	PUNCT
ijassa-499	68	1	the	the	DET
ijassa-499	68	2	controlled	control	VERB
ijassa-499	68	3	input	input	NOUN
ijassa-499	68	4	variables	variable	NOUN
ijassa-499	68	5	ū	ū	NOUN
ijassa-499	68	6	should	should	AUX
ijassa-499	68	7	be	be	AUX
ijassa-499	68	8	ranked	rank	VERB
ijassa-499	68	9	by	by	ADP
ijassa-499	68	10	their	their	PRON
ijassa-499	68	11	importance	importance	NOUN
ijassa-499	68	12	.	.	PUNCT
ijassa-499	69	1	the	the	DET
ijassa-499	69	2	process	process	NOUN
ijassa-499	69	3	(	(	PUNCT
ijassa-499	69	4	3.2	3.2	NUM
ijassa-499	69	5	)	)	PUNCT
ijassa-499	69	6	starts	start	VERB
ijassa-499	69	7	from	from	ADP
ijassa-499	69	8	the	the	DET
ijassa-499	69	9	most	most	ADV
ijassa-499	69	10	important	important	ADJ
ijassa-499	69	11	controlled	control	VERB
ijassa-499	69	12	input	input	NOUN
ijassa-499	69	13	feature	feature	NOUN
ijassa-499	69	14	and	and	CCONJ
ijassa-499	69	15	continues	continue	VERB
ijassa-499	69	16	with	with	ADP
ijassa-499	69	17	less	less	ADJ
ijassa-499	69	18	and	and	CCONJ
ijassa-499	69	19	less	less	ADV
ijassa-499	69	20	important	important	ADJ
ijassa-499	69	21	ones	one	NOUN
ijassa-499	69	22	.	.	PUNCT
ijassa-499	70	1	•	•	NUM
ijassa-499	70	2	bijective	bijective	ADJ
ijassa-499	70	3	relationship	relationship	NOUN
ijassa-499	70	4	.	.	PUNCT
ijassa-499	71	1	the	the	DET
ijassa-499	71	2	forward	forward	ADJ
ijassa-499	71	3	models	model	NOUN
ijassa-499	71	4	(	(	PUNCT
ijassa-499	71	5	the	the	DET
ijassa-499	71	6	true	true	ADJ
ijassa-499	71	7	relationships	relationship	NOUN
ijassa-499	71	8	between	between	ADP
ijassa-499	71	9	input	input	NOUN
ijassa-499	71	10	features	feature	NOUN
ijassa-499	71	11	and	and	CCONJ
ijassa-499	71	12	output	output	NOUN
ijassa-499	71	13	features	feature	NOUN
ijassa-499	71	14	)	)	PUNCT
ijassa-499	71	15	should	should	AUX
ijassa-499	71	16	be	be	AUX
ijassa-499	71	17	bijective	bijective	ADJ
ijassa-499	71	18	functions	function	NOUN
ijassa-499	71	19	.	.	PUNCT
ijassa-499	72	1	suppose	suppose	VERB
ijassa-499	72	2	there	there	PRON
ijassa-499	72	3	are	be	VERB
ijassa-499	72	4	two	two	NUM
ijassa-499	72	5	significantly	significantly	ADV
ijassa-499	72	6	different	different	ADJ
ijassa-499	72	7	controlled	control	VERB
ijassa-499	72	8	inputs	input	NOUN
ijassa-499	72	9	ū∗1	ū∗1	PUNCT
ijassa-499	72	10	and	and	CCONJ
ijassa-499	72	11	ū∗2	ū∗2	NOUN
ijassa-499	72	12	that	that	PRON
ijassa-499	72	13	produce	produce	VERB
ijassa-499	72	14	the	the	DET
ijassa-499	72	15	desired	desire	VERB
ijassa-499	72	16	output	output	NOUN
ijassa-499	72	17	.	.	PUNCT
ijassa-499	73	1	the	the	DET
ijassa-499	73	2	result	result	NOUN
ijassa-499	73	3	of	of	ADP
ijassa-499	73	4	the	the	DET
ijassa-499	73	5	algorithm	algorithm	NOUN
ijassa-499	73	6	is	be	AUX
ijassa-499	73	7	a	a	DET
ijassa-499	73	8	controlled	control	VERB
ijassa-499	73	9	input	input	NOUN
ijassa-499	73	10	values	value	NOUN
ijassa-499	73	11	between	between	ADP
ijassa-499	73	12	ū∗1	ū∗1	PUNCT
ijassa-499	73	13	and	and	CCONJ
ijassa-499	73	14	ū∗2	ū∗2	NOUN
ijassa-499	73	15	(	(	PUNCT
ijassa-499	73	16	this	this	DET
ijassa-499	73	17	control	control	NOUN
ijassa-499	73	18	does	do	AUX
ijassa-499	73	19	not	not	PART
ijassa-499	73	20	lead	lead	VERB
ijassa-499	73	21	to	to	ADP
ijassa-499	73	22	the	the	DET
ijassa-499	73	23	desired	desire	VERB
ijassa-499	73	24	output	output	NOUN
ijassa-499	73	25	)	)	PUNCT
ijassa-499	73	26	instead	instead	ADV
ijassa-499	73	27	of	of	ADP
ijassa-499	73	28	choosing	choose	VERB
ijassa-499	73	29	one	one	NUM
ijassa-499	73	30	of	of	ADP
ijassa-499	73	31	them	they	PRON
ijassa-499	73	32	.	.	PUNCT
ijassa-499	74	1	•	•	NUM
ijassa-499	74	2	curse	curse	NOUN
ijassa-499	74	3	of	of	ADP
ijassa-499	74	4	dimensionality	dimensionality	NOUN
ijassa-499	74	5	.	.	PUNCT
ijassa-499	75	1	it	it	PRON
ijassa-499	75	2	is	be	AUX
ijassa-499	75	3	connected	connect	VERB
ijassa-499	75	4	with	with	ADP
ijassa-499	75	5	observations	observation	NOUN
ijassa-499	75	6	distribution	distribution	NOUN
ijassa-499	75	7	in	in	ADP
ijassa-499	75	8	a	a	DET
ijassa-499	75	9	high	high	ADJ
ijassa-499	75	10	dimensional	dimensional	ADJ
ijassa-499	75	11	feature	feature	NOUN
ijassa-499	75	12	space	space	NOUN
ijassa-499	75	13	(	(	PUNCT
ijassa-499	75	14	especially	especially	ADV
ijassa-499	75	15	in	in	ADP
ijassa-499	75	16	the	the	DET
ijassa-499	75	17	case	case	NOUN
ijassa-499	75	18	of	of	ADP
ijassa-499	75	19	a	a	DET
ijassa-499	75	20	small	small	ADJ
ijassa-499	75	21	number	number	NOUN
ijassa-499	75	22	of	of	ADP
ijassa-499	75	23	observations	observation	NOUN
ijassa-499	75	24	)	)	PUNCT
ijassa-499	75	25	.	.	PUNCT
ijassa-499	76	1	suppose	suppose	VERB
ijassa-499	76	2	,	,	PUNCT
ijassa-499	76	3	there	there	PRON
ijassa-499	76	4	are	be	VERB
ijassa-499	76	5	n	n	PRON
ijassa-499	76	6	=	=	SYM
ijassa-499	76	7	1000	1000	NUM
ijassa-499	76	8	points	point	NOUN
ijassa-499	76	9	uniformly	uniformly	ADV
ijassa-499	76	10	distributed	distribute	VERB
ijassa-499	76	11	over	over	ADP
ijassa-499	76	12	the	the	DET
ijassa-499	76	13	ten	ten	NUM
ijassa-499	76	14	dimensional	dimensional	ADJ
ijassa-499	76	15	unit	unit	NOUN
ijassa-499	76	16	cube	cube	NOUN
ijassa-499	77	1	[	[	X
ijassa-499	77	2	0	0	NUM
ijassa-499	77	3	,	,	PUNCT
ijassa-499	77	4	1]10	1]10	NOUN
ijassa-499	77	5	.	.	PUNCT
ijassa-499	78	1	an	an	DET
ijassa-499	78	2	average	average	NOUN
ijassa-499	78	3	over	over	ADP
ijassa-499	78	4	the	the	DET
ijassa-499	78	5	neighborhood	neighborhood	NOUN
ijassa-499	78	6	of	of	ADP
ijassa-499	78	7	diameter	diameter	NOUN
ijassa-499	78	8	0.25	0.25	NUM
ijassa-499	78	9	(	(	PUNCT
ijassa-499	78	10	in	in	ADP
ijassa-499	78	11	each	each	DET
ijassa-499	78	12	coordinate	coordinate	NOUN
ijassa-499	78	13	)	)	PUNCT
ijassa-499	78	14	results	result	NOUN
ijassa-499	78	15	in	in	ADP
ijassa-499	78	16	the	the	DET
ijassa-499	78	17	volume	volume	NOUN
ijassa-499	78	18	of	of	ADP
ijassa-499	78	19	0.2510	0.2510	NUM
ijassa-499	78	20	≈	≈	PROPN
ijassa-499	78	21	0.00000095	0.00000095	NUM
ijassa-499	78	22	for	for	ADP
ijassa-499	78	23	the	the	DET
ijassa-499	78	24	corresponding	corresponding	ADJ
ijassa-499	78	25	ten	ten	NUM
ijassa-499	78	26	-	-	PUNCT
ijassa-499	78	27	dimensional	dimensional	ADJ
ijassa-499	78	28	cube	cube	NOUN
ijassa-499	78	29	.	.	PUNCT
ijassa-499	79	1	hence	hence	ADV
ijassa-499	79	2	,	,	PUNCT
ijassa-499	79	3	the	the	DET
ijassa-499	79	4	expected	expect	VERB
ijassa-499	79	5	number	number	NOUN
ijassa-499	79	6	of	of	ADP
ijassa-499	79	7	observations	observation	NOUN
ijassa-499	79	8	in	in	ADP
ijassa-499	79	9	this	this	DET
ijassa-499	79	10	cube	cube	NOUN
ijassa-499	79	11	will	will	AUX
ijassa-499	79	12	be	be	AUX
ijassa-499	79	13	0.00095	0.00095	NUM
ijassa-499	79	14	and	and	CCONJ
ijassa-499	79	15	any	any	DET
ijassa-499	79	16	averaging	averaging	NOUN
ijassa-499	79	17	can	can	AUX
ijassa-499	79	18	not	not	PART
ijassa-499	79	19	be	be	AUX
ijassa-499	79	20	expected	expect	VERB
ijassa-499	79	21	.	.	PUNCT
ijassa-499	80	1	if	if	SCONJ
ijassa-499	80	2	we	we	PRON
ijassa-499	80	3	fix	fix	VERB
ijassa-499	80	4	the	the	DET
ijassa-499	80	5	count	count	NOUN
ijassa-499	80	6	k	k	NOUN
ijassa-499	80	7	=	=	SYM
ijassa-499	80	8	1	1	NUM
ijassa-499	80	9	of	of	ADP
ijassa-499	80	10	observations	observation	NOUN
ijassa-499	80	11	over	over	ADP
ijassa-499	80	12	which	which	PRON
ijassa-499	80	13	to	to	PART
ijassa-499	80	14	average	average	VERB
ijassa-499	80	15	,	,	PUNCT
ijassa-499	80	16	the	the	DET
ijassa-499	80	17	diameter	diameter	NOUN
ijassa-499	80	18	of	of	ADP
ijassa-499	80	19	the	the	DET
ijassa-499	80	20	typical	typical	ADJ
ijassa-499	80	21	neighborhood	neighborhood	NOUN
ijassa-499	80	22	will	will	AUX
ijassa-499	80	23	be	be	AUX
ijassa-499	80	24	larger	large	ADJ
ijassa-499	80	25	than	than	ADP
ijassa-499	80	26	0.5	0.5	NUM
ijassa-499	80	27	.	.	PUNCT
ijassa-499	81	1	it	it	PRON
ijassa-499	81	2	means	mean	VERB
ijassa-499	81	3	that	that	SCONJ
ijassa-499	81	4	the	the	DET
ijassa-499	81	5	average	average	NOUN
ijassa-499	81	6	is	be	AUX
ijassa-499	81	7	calculated	calculate	VERB
ijassa-499	81	8	over	over	ADP
ijassa-499	81	9	at	at	ADV
ijassa-499	81	10	least	least	ADV
ijassa-499	81	11	one	one	NUM
ijassa-499	81	12	-	-	PUNCT
ijassa-499	81	13	half	half	NOUN
ijassa-499	81	14	of	of	ADP
ijassa-499	81	15	the	the	DET
ijassa-499	81	16	range	range	NOUN
ijassa-499	81	17	along	along	ADP
ijassa-499	81	18	each	each	DET
ijassa-499	81	19	coordinate	coordinate	NOUN
ijassa-499	81	20	[	[	X
ijassa-499	81	21	10	10	NUM
ijassa-499	81	22	]	]	PUNCT
ijassa-499	81	23	.	.	PUNCT
ijassa-499	82	1	4	4	X
ijassa-499	82	2	.	.	X
ijassa-499	82	3	decision	decision	NOUN
ijassa-499	82	4	tree	tree	NOUN
ijassa-499	82	5	approach	approach	NOUN
ijassa-499	82	6	decision	decision	NOUN
ijassa-499	82	7	trees	tree	NOUN
ijassa-499	82	8	are	be	AUX
ijassa-499	82	9	commonly	commonly	ADV
ijassa-499	82	10	used	use	VERB
ijassa-499	82	11	for	for	ADP
ijassa-499	82	12	solving	solve	VERB
ijassa-499	82	13	regression	regression	NOUN
ijassa-499	82	14	tasks	task	NOUN
ijassa-499	82	15	in	in	ADP
ijassa-499	82	16	multidimensional	multidimensional	ADJ
ijassa-499	82	17	cases	case	NOUN
ijassa-499	82	18	and	and	CCONJ
ijassa-499	82	19	allow	allow	VERB
ijassa-499	82	20	preventing	prevent	VERB
ijassa-499	82	21	the	the	DET
ijassa-499	82	22	nadaraya	nadaraya	ADJ
ijassa-499	82	23	-	-	PUNCT
ijassa-499	82	24	watson	watson	NOUN
ijassa-499	82	25	algorithm	algorithm	PROPN
ijassa-499	82	26	limitations	limitation	NOUN
ijassa-499	82	27	described	describe	VERB
ijassa-499	82	28	in	in	ADP
ijassa-499	82	29	section	section	NOUN
ijassa-499	82	30	3	3	NUM
ijassa-499	82	31	.	.	PROPN
ijassa-499	82	32	4.1	4.1	NUM
ijassa-499	82	33	.	.	PUNCT
ijassa-499	83	1	modeling	model	VERB
ijassa-499	83	2	decision	decision	NOUN
ijassa-499	83	3	tree	tree	NOUN
ijassa-499	83	4	is	be	AUX
ijassa-499	83	5	a	a	DET
ijassa-499	83	6	piecewise	piecewise	NOUN
ijassa-499	83	7	constant	constant	ADJ
ijassa-499	83	8	nonparametric	nonparametric	NOUN
ijassa-499	83	9	model	model	NOUN
ijassa-499	83	10	.	.	PUNCT
ijassa-499	84	1	the	the	DET
ijassa-499	84	2	most	most	ADV
ijassa-499	84	3	popular	popular	ADJ
ijassa-499	84	4	decision	decision	NOUN
ijassa-499	84	5	tree	tree	NOUN
ijassa-499	84	6	model	model	NOUN
ijassa-499	84	7	is	be	AUX
ijassa-499	84	8	classification	classification	NOUN
ijassa-499	84	9	and	and	CCONJ
ijassa-499	84	10	regression	regression	NOUN
ijassa-499	84	11	tree	tree	NOUN
ijassa-499	84	12	(	(	PUNCT
ijassa-499	84	13	cart	cart	NOUN
ijassa-499	84	14	)	)	PUNCT
ijassa-499	85	1	[	[	X
ijassa-499	85	2	8	8	NUM
ijassa-499	85	3	]	]	PUNCT
ijassa-499	85	4	.	.	PUNCT
ijassa-499	86	1	cart	cart	NOUN
ijassa-499	86	2	is	be	AUX
ijassa-499	86	3	a	a	DET
ijassa-499	86	4	binary	binary	ADJ
ijassa-499	86	5	tree	tree	NOUN
ijassa-499	86	6	where	where	SCONJ
ijassa-499	86	7	each	each	DET
ijassa-499	86	8	root	root	NOUN
ijassa-499	86	9	node	node	NOUN
ijassa-499	86	10	represents	represent	VERB
ijassa-499	86	11	an	an	DET
ijassa-499	86	12	input	input	NOUN
ijassa-499	86	13	variable	variable	NOUN
ijassa-499	86	14	ujr	ujr	PROPN
ijassa-499	86	15	and	and	CCONJ
ijassa-499	86	16	a	a	DET
ijassa-499	86	17	split	split	NOUN
ijassa-499	86	18	point	point	NOUN
ijassa-499	86	19	br	br	NOUN
ijassa-499	86	20	.	.	PUNCT
ijassa-499	87	1	let	let	VERB
ijassa-499	87	2	us	we	PRON
ijassa-499	87	3	aggregate	aggregate	VERB
ijassa-499	87	4	controlled	control	VERB
ijassa-499	87	5	and	and	CCONJ
ijassa-499	87	6	observed	observe	VERB
ijassa-499	87	7	uncontrolled	uncontrolled	ADJ
ijassa-499	87	8	inputs	input	NOUN
ijassa-499	87	9	to	to	PART
ijassa-499	87	10	make	make	VERB
ijassa-499	87	11	the	the	DET
ijassa-499	87	12	description	description	NOUN
ijassa-499	87	13	easier	easy	ADJ
ijassa-499	87	14	:	:	PUNCT
ijassa-499	87	15	ū	ū	NOUN
ijassa-499	87	16	=	=	SYM
ijassa-499	87	17	{	{	PUNCT
ijassa-499	87	18	u1	u1	NOUN
ijassa-499	87	19	,	,	PUNCT
ijassa-499	87	20	...	...	PUNCT
ijassa-499	87	21	,	,	PUNCT
ijassa-499	87	22	umu	umu	PROPN
ijassa-499	87	23	,	,	PUNCT
ijassa-499	87	24	v1	v1	PROPN
ijassa-499	87	25	,	,	PUNCT
ijassa-499	87	26	...	...	PUNCT
ijassa-499	87	27	,	,	PUNCT
ijassa-499	87	28	vmv	vmv	PROPN
ijassa-499	87	29	}	}	PUNCT
ijassa-499	87	30	.	.	PUNCT
ijassa-499	88	1	each	each	DET
ijassa-499	88	2	leaf	leaf	NOUN
ijassa-499	88	3	node	node	NOUN
ijassa-499	88	4	contains	contain	VERB
ijassa-499	88	5	values	value	NOUN
ijassa-499	88	6	of	of	ADP
ijassa-499	88	7	the	the	DET
ijassa-499	88	8	output	output	NOUN
ijassa-499	88	9	variable	variable	NOUN
ijassa-499	88	10	x	x	PUNCT
ijassa-499	88	11	which	which	PRON
ijassa-499	88	12	is	be	AUX
ijassa-499	88	13	used	use	VERB
ijassa-499	88	14	to	to	PART
ijassa-499	88	15	make	make	VERB
ijassa-499	88	16	a	a	DET
ijassa-499	88	17	prediction	prediction	NOUN
ijassa-499	88	18	.	.	PUNCT
ijassa-499	89	1	cart	cart	NOUN
ijassa-499	89	2	fitting	fitting	ADJ
ijassa-499	89	3	involves	involve	VERB
ijassa-499	89	4	input	input	NOUN
ijassa-499	89	5	variables	variable	NOUN
ijassa-499	89	6	and	and	CCONJ
ijassa-499	89	7	split	split	ADJ
ijassa-499	89	8	points	point	NOUN
ijassa-499	89	9	selection	selection	NOUN
ijassa-499	89	10	until	until	SCONJ
ijassa-499	89	11	a	a	DET
ijassa-499	89	12	suitable	suitable	ADJ
ijassa-499	89	13	tree	tree	NOUN
ijassa-499	89	14	is	be	AUX
ijassa-499	89	15	constructed	construct	VERB
ijassa-499	89	16	.	.	PUNCT
ijassa-499	90	1	input	input	NOUN
ijassa-499	90	2	variables	variable	NOUN
ijassa-499	90	3	and	and	CCONJ
ijassa-499	90	4	split	split	ADJ
ijassa-499	90	5	points	point	NOUN
ijassa-499	90	6	are	be	AUX
ijassa-499	90	7	chosen	choose	VERB
ijassa-499	90	8	using	use	VERB
ijassa-499	90	9	a	a	DET
ijassa-499	90	10	greedy	greedy	ADJ
ijassa-499	90	11	algorithm	algorithm	NOUN
ijassa-499	90	12	to	to	PART
ijassa-499	90	13	minimize	minimize	VERB
ijassa-499	90	14	the	the	DET
ijassa-499	90	15	:	:	PUNCT
ijassa-499	90	16	min	min	PROPN
ijassa-499	90	17	j	j	PROPN
ijassa-499	90	18	min	min	PROPN
ijassa-499	90	19	b	b	PROPN
ijassa-499	90	20	∑	∑	X
ijassa-499	90	21	i	i	PRON
ijassa-499	90	22	:	:	PUNCT
ijassa-499	90	23	uj	uj	VERB
ijassa-499	90	24	i	i	PRON
ijassa-499	90	25	<	<	X
ijassa-499	90	26	b	b	X
ijassa-499	90	27	l	l	X
ijassa-499	90	28	(	(	PUNCT
ijassa-499	90	29	xi	xi	PROPN
ijassa-499	90	30	,	,	PUNCT
ijassa-499	90	31	x̂	x̂	PUNCT
ijassa-499	91	1	−	−	PROPN
ijassa-499	91	2	(	(	PUNCT
ijassa-499	91	3	ūi	ūi	PROPN
ijassa-499	91	4	,	,	PUNCT
ijassa-499	91	5	j	j	PROPN
ijassa-499	91	6	,	,	PUNCT
ijassa-499	91	7	b	b	NOUN
ijassa-499	91	8	)	)	PUNCT
ijassa-499	91	9	)	)	PUNCT
ijassa-499	92	1	+	+	CCONJ
ijassa-499	92	2	∑	∑	PUNCT
ijassa-499	92	3	i	i	PRON
ijassa-499	92	4	:	:	PUNCT
ijassa-499	92	5	uj	uj	PROPN
ijassa-499	92	6	i	i	PRON
ijassa-499	92	7	>	>	X
ijassa-499	92	8	b	b	PROPN
ijassa-499	92	9	l	l	X
ijassa-499	92	10	(	(	PUNCT
ijassa-499	92	11	xi	xi	PROPN
ijassa-499	92	12	,	,	PUNCT
ijassa-499	92	13	x̂	x̂	PUNCT
ijassa-499	92	14	+	+	CCONJ
ijassa-499	92	15	(	(	PUNCT
ijassa-499	92	16	ūi	ūi	PROPN
ijassa-499	92	17	,	,	PUNCT
ijassa-499	92	18	j	j	PROPN
ijassa-499	92	19	,	,	PUNCT
ijassa-499	92	20	b	b	NOUN
ijassa-499	92	21	)	)	PUNCT
ijassa-499	92	22	)	)	PUNCT
ijassa-499	93	1			PROPN
ijassa-499	93	2	(	(	PUNCT
ijassa-499	93	3	4.3	4.3	NUM
ijassa-499	93	4	)	)	PUNCT
ijassa-499	93	5	where	where	SCONJ
ijassa-499	93	6	x̂−	x̂−	PROPN
ijassa-499	93	7	(	(	PUNCT
ijassa-499	93	8	ūi	ūi	PROPN
ijassa-499	93	9	,	,	PUNCT
ijassa-499	93	10	j	j	PROPN
ijassa-499	93	11	,	,	PUNCT
ijassa-499	93	12	b	b	NOUN
ijassa-499	93	13	)	)	PUNCT
ijassa-499	93	14	or	or	CCONJ
ijassa-499	93	15	x̂+	x̂+	PUNCT
ijassa-499	93	16	(	(	PUNCT
ijassa-499	93	17	ūi	ūi	PROPN
ijassa-499	93	18	,	,	PUNCT
ijassa-499	93	19	j	j	PROPN
ijassa-499	93	20	,	,	PUNCT
ijassa-499	93	21	b	b	NOUN
ijassa-499	93	22	)	)	PUNCT
ijassa-499	93	23	is	be	AUX
ijassa-499	93	24	the	the	DET
ijassa-499	93	25	prediction	prediction	NOUN
ijassa-499	93	26	in	in	ADP
ijassa-499	93	27	the	the	DET
ijassa-499	93	28	point	point	NOUN
ijassa-499	94	1	ūi	ūi	VERB
ijassa-499	94	2	based	base	VERB
ijassa-499	94	3	on	on	ADP
ijassa-499	94	4	the	the	DET
ijassa-499	94	5	subspaces	subspace	NOUN
ijassa-499	94	6	after	after	ADP
ijassa-499	94	7	splitting	splitting	NOUN
ijassa-499	94	8	:	:	PUNCT
ijassa-499	94	9	copyright	copyright	NOUN
ijassa-499	94	10	c	c	ADP
ijassa-499	94	11	©	©	PROPN
ijassa-499	94	12	2017	2017	NUM
ijassa-499	94	13	assa	assa	NOUN
ijassa-499	94	14	.	.	PUNCT
ijassa-499	95	1	adv	adv	PROPN
ijassa-499	95	2	syst	syst	PROPN
ijassa-499	95	3	sci	sci	PROPN
ijassa-499	95	4	appl	appl	PROPN
ijassa-499	95	5	(	(	PUNCT
ijassa-499	95	6	2017	2017	NUM
ijassa-499	95	7	)	)	PUNCT
ijassa-499	95	8	62	62	NUM
ijassa-499	95	9	e.	e.	PROPN
ijassa-499	95	10	mangalova	mangalova	PROPN
ijassa-499	96	1	x̂−	x̂−	PROPN
ijassa-499	96	2	(	(	PUNCT
ijassa-499	96	3	ūi	ūi	PROPN
ijassa-499	96	4	,	,	PUNCT
ijassa-499	96	5	j	j	PROPN
ijassa-499	96	6	,	,	PUNCT
ijassa-499	96	7	b	b	NOUN
ijassa-499	96	8	)	)	PUNCT
ijassa-499	96	9	=	=	PUNCT
ijassa-499	96	10	∑	∑	PUNCT
ijassa-499	96	11	i	i	PRON
ijassa-499	96	12	:	:	PUNCT
ijassa-499	96	13	uj	uj	PROPN
ijassa-499	96	14	i	i	PRON
ijassa-499	96	15	<	<	X
ijassa-499	96	16	b	b	PROPN
ijassa-499	96	17	xi∑	xi∑	PROPN
ijassa-499	97	1	i	i	PRON
ijassa-499	97	2	:	:	PUNCT
ijassa-499	97	3	uj	uj	VERB
ijassa-499	97	4	i	i	PRON
ijassa-499	97	5	<	<	X
ijassa-499	97	6	b	b	PROPN
ijassa-499	97	7	1	1	NUM
ijassa-499	97	8	,	,	PUNCT
ijassa-499	97	9	x̂+	x̂+	PUNCT
ijassa-499	98	1	(	(	PUNCT
ijassa-499	98	2	ūi	ūi	PROPN
ijassa-499	98	3	,	,	PUNCT
ijassa-499	98	4	j	j	PROPN
ijassa-499	98	5	,	,	PUNCT
ijassa-499	98	6	b	b	NOUN
ijassa-499	98	7	)	)	PUNCT
ijassa-499	98	8	=	=	PUNCT
ijassa-499	98	9	∑	∑	PUNCT
ijassa-499	98	10	i	i	PRON
ijassa-499	98	11	:	:	PUNCT
ijassa-499	98	12	uj	uj	PROPN
ijassa-499	98	13	i	i	PRON
ijassa-499	98	14	>	>	X
ijassa-499	98	15	b	b	PROPN
ijassa-499	98	16	xi∑	xi∑	PROPN
ijassa-499	99	1	i	i	PRON
ijassa-499	99	2	:	:	PUNCT
ijassa-499	99	3	uj	uj	PROPN
ijassa-499	99	4	i	i	PRON
ijassa-499	99	5	>	>	X
ijassa-499	99	6	b	b	PROPN
ijassa-499	99	7	1	1	NUM
ijassa-499	99	8	.	.	PUNCT
ijassa-499	100	1	(	(	PUNCT
ijassa-499	100	2	4.4	4.4	NUM
ijassa-499	100	3	)	)	PUNCT
ijassa-499	100	4	the	the	DET
ijassa-499	100	5	tree	tree	NOUN
ijassa-499	100	6	construction	construction	NOUN
ijassa-499	100	7	ends	end	VERB
ijassa-499	100	8	using	use	VERB
ijassa-499	100	9	a	a	DET
ijassa-499	100	10	predefined	predefine	VERB
ijassa-499	100	11	stopping	stopping	NOUN
ijassa-499	100	12	criterion	criterion	NOUN
ijassa-499	100	13	,	,	PUNCT
ijassa-499	100	14	such	such	ADJ
ijassa-499	100	15	as	as	ADP
ijassa-499	100	16	the	the	DET
ijassa-499	100	17	minimum	minimum	ADJ
ijassa-499	100	18	number	number	NOUN
ijassa-499	100	19	of	of	ADP
ijassa-499	100	20	observations	observation	NOUN
ijassa-499	100	21	assigned	assign	VERB
ijassa-499	100	22	to	to	ADP
ijassa-499	100	23	each	each	DET
ijassa-499	100	24	leaf	leaf	NOUN
ijassa-499	100	25	node	node	NOUN
ijassa-499	100	26	of	of	ADP
ijassa-499	100	27	the	the	DET
ijassa-499	100	28	tree	tree	NOUN
ijassa-499	100	29	or	or	CCONJ
ijassa-499	100	30	the	the	DET
ijassa-499	100	31	maximum	maximum	ADJ
ijassa-499	100	32	depth	depth	NOUN
ijassa-499	100	33	of	of	ADP
ijassa-499	100	34	the	the	DET
ijassa-499	100	35	tree	tree	NOUN
ijassa-499	100	36	.	.	PUNCT
ijassa-499	101	1	each	each	DET
ijassa-499	101	2	node	node	NOUN
ijassa-499	101	3	in	in	ADP
ijassa-499	101	4	the	the	DET
ijassa-499	101	5	tree	tree	NOUN
ijassa-499	101	6	corresponds	correspond	VERB
ijassa-499	101	7	to	to	ADP
ijassa-499	101	8	a	a	DET
ijassa-499	101	9	rectangular	rectangular	ADJ
ijassa-499	101	10	region	region	NOUN
ijassa-499	101	11	of	of	ADP
ijassa-499	101	12	the	the	DET
ijassa-499	101	13	predictor	predictor	NOUN
ijassa-499	101	14	space	space	NOUN
ijassa-499	101	15	sk	sk	PROPN
ijassa-499	101	16	,	,	PUNCT
ijassa-499	101	17	a	a	DET
ijassa-499	101	18	subset	subset	NOUN
ijassa-499	101	19	of	of	ADP
ijassa-499	101	20	the	the	DET
ijassa-499	101	21	observations	observation	NOUN
ijassa-499	101	22	lying	lie	VERB
ijassa-499	101	23	in	in	ADP
ijassa-499	101	24	the	the	DET
ijassa-499	101	25	region	region	NOUN
ijassa-499	101	26	sk	sk	VERB
ijassa-499	101	27	,	,	PUNCT
ijassa-499	101	28	a	a	DET
ijassa-499	101	29	constant	constant	ADJ
ijassa-499	101	30	x̂k	x̂k	NOUN
ijassa-499	102	1	which	which	PRON
ijassa-499	102	2	is	be	AUX
ijassa-499	102	3	the	the	DET
ijassa-499	102	4	average	average	ADJ
ijassa-499	102	5	response	response	NOUN
ijassa-499	102	6	of	of	ADP
ijassa-499	102	7	the	the	DET
ijassa-499	102	8	observations	observation	NOUN
ijassa-499	102	9	in	in	ADP
ijassa-499	102	10	k	k	ADV
ijassa-499	102	11	-	-	PUNCT
ijassa-499	102	12	th	th	X
ijassa-499	102	13	rectangular	rectangular	ADJ
ijassa-499	102	14	region	region	NOUN
ijassa-499	102	15	.	.	PUNCT
ijassa-499	103	1	thus	thus	ADV
ijassa-499	103	2	,	,	PUNCT
ijassa-499	103	3	the	the	DET
ijassa-499	103	4	binary	binary	ADJ
ijassa-499	103	5	tree	tree	NOUN
ijassa-499	103	6	model	model	NOUN
ijassa-499	103	7	can	can	AUX
ijassa-499	103	8	be	be	AUX
ijassa-499	103	9	formalized	formalize	VERB
ijassa-499	103	10	as	as	SCONJ
ijassa-499	103	11	follows	follow	VERB
ijassa-499	103	12	:	:	PUNCT
ijassa-499	103	13	x̂	x̂	NUM
ijassa-499	103	14	(	(	PUNCT
ijassa-499	103	15	ū	ū	NOUN
ijassa-499	103	16	)	)	PUNCT
ijassa-499	103	17	=	=	NOUN
ijassa-499	103	18	{	{	PUNCT
ijassa-499	103	19	x̂k	x̂k	NUM
ijassa-499	103	20	:	:	PUNCT
ijassa-499	103	21	ū	ū	PROPN
ijassa-499	103	22	∈	∈	PROPN
ijassa-499	103	23	sk	sk	VERB
ijassa-499	103	24	,	,	PUNCT
ijassa-499	103	25	k	k	PROPN
ijassa-499	103	26	=	=	SYM
ijassa-499	103	27	1	1	NUM
ijassa-499	103	28	,	,	PUNCT
ijassa-499	103	29	2	2	NUM
ijassa-499	103	30	,	,	PUNCT
ijassa-499	103	31	...	...	PUNCT
ijassa-499	103	32	,	,	PUNCT
ijassa-499	103	33	k	k	PROPN
ijassa-499	103	34	}	}	PUNCT
ijassa-499	103	35	.	.	PUNCT
ijassa-499	104	1	(	(	PUNCT
ijassa-499	104	2	4.5	4.5	NUM
ijassa-499	104	3	)	)	PUNCT
ijassa-499	104	4	4.2	4.2	NUM
ijassa-499	104	5	.	.	PUNCT
ijassa-499	105	1	control	control	PROPN
ijassa-499	105	2	control	control	NOUN
ijassa-499	105	3	tasks	task	NOUN
ijassa-499	105	4	can	can	AUX
ijassa-499	105	5	be	be	AUX
ijassa-499	105	6	solved	solve	VERB
ijassa-499	105	7	using	use	VERB
ijassa-499	105	8	the	the	DET
ijassa-499	105	9	regression	regression	NOUN
ijassa-499	105	10	trees	tree	NOUN
ijassa-499	105	11	in	in	ADP
ijassa-499	105	12	different	different	ADJ
ijassa-499	105	13	formulations	formulation	NOUN
ijassa-499	105	14	depending	depend	VERB
ijassa-499	105	15	on	on	ADP
ijassa-499	105	16	the	the	DET
ijassa-499	105	17	number	number	NOUN
ijassa-499	105	18	of	of	ADP
ijassa-499	105	19	input	input	NOUN
ijassa-499	105	20	and	and	CCONJ
ijassa-499	105	21	output	output	NOUN
ijassa-499	105	22	values	value	NOUN
ijassa-499	105	23	,	,	PUNCT
ijassa-499	105	24	presence	presence	NOUN
ijassa-499	105	25	of	of	ADP
ijassa-499	105	26	observed	observed	ADJ
ijassa-499	105	27	uncontrolled	uncontrolled	ADJ
ijassa-499	105	28	input	input	NOUN
ijassa-499	105	29	variables	variable	NOUN
ijassa-499	105	30	.	.	PUNCT
ijassa-499	106	1	consider	consider	VERB
ijassa-499	106	2	the	the	DET
ijassa-499	106	3	basic	basic	ADJ
ijassa-499	106	4	formulation	formulation	NOUN
ijassa-499	106	5	of	of	ADP
ijassa-499	106	6	the	the	DET
ijassa-499	106	7	problem	problem	NOUN
ijassa-499	106	8	.	.	PUNCT
ijassa-499	107	1	4.2.1	4.2.1	NUM
ijassa-499	107	2	.	.	PUNCT
ijassa-499	107	3	controlled	control	VERB
ijassa-499	107	4	inputs	input	NOUN
ijassa-499	107	5	one	one	NUM
ijassa-499	107	6	-	-	PUNCT
ijassa-499	107	7	dimensional	dimensional	ADJ
ijassa-499	107	8	output	output	NOUN
ijassa-499	107	9	.	.	PUNCT
ijassa-499	108	1	assume	assume	VERB
ijassa-499	108	2	there	there	PRON
ijassa-499	108	3	are	be	VERB
ijassa-499	108	4	only	only	ADV
ijassa-499	108	5	controlled	control	VERB
ijassa-499	108	6	variables	variable	NOUN
ijassa-499	108	7	ū	ū	NOUN
ijassa-499	108	8	and	and	CCONJ
ijassa-499	108	9	one	one	NUM
ijassa-499	108	10	output	output	NOUN
ijassa-499	108	11	variable	variable	ADJ
ijassa-499	108	12	x.	x.	NOUN
ijassa-499	108	13	decision	decision	NOUN
ijassa-499	108	14	tree	tree	NOUN
ijassa-499	108	15	is	be	AUX
ijassa-499	108	16	fit	fit	ADJ
ijassa-499	108	17	using	use	VERB
ijassa-499	108	18	the	the	DET
ijassa-499	108	19	training	training	NOUN
ijassa-499	108	20	dataset	dataset	NOUN
ijassa-499	108	21	containing	contain	VERB
ijassa-499	108	22	simultaneous	simultaneous	ADJ
ijassa-499	108	23	observations	observation	NOUN
ijassa-499	108	24	of	of	ADP
ijassa-499	108	25	ū	ū	NOUN
ijassa-499	108	26	and	and	CCONJ
ijassa-499	108	27	x.	x.	NOUN
ijassa-499	108	28	the	the	DET
ijassa-499	108	29	control	control	NOUN
ijassa-499	108	30	algorithm	algorithm	NOUN
ijassa-499	108	31	:	:	PUNCT
ijassa-499	108	32	1	1	X
ijassa-499	108	33	.	.	X
ijassa-499	108	34	set	set	VERB
ijassa-499	108	35	the	the	DET
ijassa-499	108	36	control	control	NOUN
ijassa-499	108	37	target	target	NOUN
ijassa-499	108	38	x∗.	x∗.	NOUN
ijassa-499	109	1	2	2	X
ijassa-499	109	2	.	.	X
ijassa-499	109	3	search	search	NOUN
ijassa-499	109	4	for	for	ADP
ijassa-499	109	5	such	such	ADJ
ijassa-499	109	6	leaf	leaf	NOUN
ijassa-499	109	7	node	node	NOUN
ijassa-499	109	8	that	that	SCONJ
ijassa-499	109	9	k∗	k∗	NOUN
ijassa-499	109	10	=	=	PUNCT
ijassa-499	109	11	arg	arg	NOUN
ijassa-499	109	12	min	min	PROPN
ijassa-499	109	13	k	k	PROPN
ijassa-499	109	14	d1	d1	PROPN
ijassa-499	109	15	(	(	PUNCT
ijassa-499	109	16	x̂k	x̂k	PROPN
ijassa-499	109	17	,	,	PUNCT
ijassa-499	109	18	x	x	SYM
ijassa-499	109	19	∗	∗	NOUN
ijassa-499	109	20	)	)	PUNCT
ijassa-499	109	21	,	,	PUNCT
ijassa-499	109	22	(	(	PUNCT
ijassa-499	109	23	4.6	4.6	NUM
ijassa-499	109	24	)	)	PUNCT
ijassa-499	109	25	where	where	SCONJ
ijassa-499	109	26	d1	d1	PROPN
ijassa-499	109	27	is	be	AUX
ijassa-499	109	28	a	a	DET
ijassa-499	109	29	one	one	NUM
ijassa-499	109	30	-	-	PUNCT
ijassa-499	109	31	dimensional	dimensional	ADJ
ijassa-499	109	32	distance	distance	NOUN
ijassa-499	109	33	measurement	measurement	NOUN
ijassa-499	109	34	.	.	PUNCT
ijassa-499	110	1	call	call	VERB
ijassa-499	110	2	k∗-th	k∗-th	PROPN
ijassa-499	110	3	node	node	NOUN
ijassa-499	110	4	”	"	PUNCT
ijassa-499	110	5	target	target	NOUN
ijassa-499	110	6	node	node	NOUN
ijassa-499	110	7	”	"	PUNCT
ijassa-499	110	8	.	.	PUNCT
ijassa-499	111	1	3	3	X
ijassa-499	111	2	.	.	X
ijassa-499	111	3	find	find	VERB
ijassa-499	111	4	control	control	NOUN
ijassa-499	111	5	ū∗	ū∗	PROPN
ijassa-499	111	6	contained	contain	VERB
ijassa-499	111	7	in	in	ADP
ijassa-499	111	8	the	the	DET
ijassa-499	111	9	region	region	NOUN
ijassa-499	111	10	sk∗	sk∗	NOUN
ijassa-499	111	11	.	.	PUNCT
ijassa-499	112	1	there	there	PRON
ijassa-499	112	2	are	be	VERB
ijassa-499	112	3	different	different	ADJ
ijassa-499	112	4	ways	way	NOUN
ijassa-499	112	5	to	to	PART
ijassa-499	112	6	choose	choose	VERB
ijassa-499	112	7	this	this	DET
ijassa-499	112	8	control	control	NOUN
ijassa-499	112	9	:	:	PUNCT
ijassa-499	112	10	•	•	ADP
ijassa-499	112	11	the	the	DET
ijassa-499	112	12	center	center	NOUN
ijassa-499	112	13	of	of	ADP
ijassa-499	112	14	the	the	DET
ijassa-499	112	15	rectangle	rectangle	NOUN
ijassa-499	112	16	guaranties	guarantie	VERB
ijassa-499	112	17	the	the	DET
ijassa-499	112	18	most	most	ADV
ijassa-499	112	19	accurate	accurate	ADJ
ijassa-499	112	20	forward	forward	ADJ
ijassa-499	112	21	model	model	NOUN
ijassa-499	112	22	prediction	prediction	NOUN
ijassa-499	112	23	(	(	PUNCT
ijassa-499	112	24	decision	decision	NOUN
ijassa-499	112	25	tree	tree	NOUN
ijassa-499	112	26	prediction	prediction	NOUN
ijassa-499	112	27	)	)	PUNCT
ijassa-499	112	28	.	.	PUNCT
ijassa-499	113	1	•	•	NUM
ijassa-499	113	2	points	point	NOUN
ijassa-499	113	3	on	on	ADP
ijassa-499	113	4	the	the	DET
ijassa-499	113	5	rectangle	rectangle	NOUN
ijassa-499	113	6	boundary	boundary	NOUN
ijassa-499	113	7	allow	allow	VERB
ijassa-499	113	8	to	to	PART
ijassa-499	113	9	explore	explore	VERB
ijassa-499	113	10	object	object	NOUN
ijassa-499	113	11	and	and	CCONJ
ijassa-499	113	12	collect	collect	VERB
ijassa-499	113	13	more	more	ADJ
ijassa-499	113	14	information	information	NOUN
ijassa-499	113	15	.	.	PUNCT
ijassa-499	114	1	•	•	NUM
ijassa-499	114	2	also	also	ADV
ijassa-499	114	3	the	the	DET
ijassa-499	114	4	distance	distance	NOUN
ijassa-499	114	5	between	between	ADP
ijassa-499	114	6	the	the	DET
ijassa-499	114	7	previous	previous	ADJ
ijassa-499	114	8	control	control	NOUN
ijassa-499	114	9	and	and	CCONJ
ijassa-499	114	10	the	the	DET
ijassa-499	114	11	current	current	ADJ
ijassa-499	114	12	control	control	NOUN
ijassa-499	114	13	can	can	AUX
ijassa-499	114	14	be	be	AUX
ijassa-499	114	15	minimized	minimize	VERB
ijassa-499	114	16	to	to	PART
ijassa-499	114	17	reduce	reduce	VERB
ijassa-499	114	18	interference	interference	NOUN
ijassa-499	114	19	in	in	ADP
ijassa-499	114	20	the	the	DET
ijassa-499	114	21	system	system	NOUN
ijassa-499	114	22	.	.	PUNCT
ijassa-499	115	1	the	the	DET
ijassa-499	115	2	experimental	experimental	ADJ
ijassa-499	115	3	result	result	NOUN
ijassa-499	115	4	.	.	PUNCT
ijassa-499	116	1	suppose	suppose	VERB
ijassa-499	116	2	the	the	DET
ijassa-499	116	3	object	object	NOUN
ijassa-499	116	4	is	be	AUX
ijassa-499	116	5	represented	represent	VERB
ijassa-499	116	6	by	by	ADP
ijassa-499	116	7	the	the	DET
ijassa-499	116	8	equation	equation	NOUN
ijassa-499	116	9	:	:	PUNCT
ijassa-499	116	10	x	x	SYM
ijassa-499	116	11	=	=	PUNCT
ijassa-499	116	12	sin	sin	NOUN
ijassa-499	116	13	(	(	PUNCT
ijassa-499	116	14	2πu1	2πu1	NUM
ijassa-499	116	15	)	)	PUNCT
ijassa-499	116	16	+	+	CCONJ
ijassa-499	116	17	√	√	PROPN
ijassa-499	116	18	u2	u2	NOUN
ijassa-499	116	19	−	−	PROPN
ijassa-499	116	20	u3	u3	NOUN
ijassa-499	116	21	+	+	CCONJ
ijassa-499	116	22	ξ	ξ	PROPN
ijassa-499	116	23	.	.	PUNCT
ijassa-499	117	1	this	this	DET
ijassa-499	117	2	equation	equation	NOUN
ijassa-499	117	3	is	be	AUX
ijassa-499	117	4	used	use	VERB
ijassa-499	117	5	in	in	ADP
ijassa-499	117	6	the	the	DET
ijassa-499	117	7	computational	computational	ADJ
ijassa-499	117	8	experiment	experiment	NOUN
ijassa-499	117	9	to	to	PART
ijassa-499	117	10	simulate	simulate	VERB
ijassa-499	117	11	a	a	DET
ijassa-499	117	12	real	real	ADJ
ijassa-499	117	13	process	process	NOUN
ijassa-499	117	14	.	.	PUNCT
ijassa-499	118	1	input	input	NOUN
ijassa-499	118	2	variables	variable	NOUN
ijassa-499	118	3	u1	u1	PROPN
ijassa-499	118	4	,	,	PUNCT
ijassa-499	118	5	u2	u2	NOUN
ijassa-499	118	6	,	,	PUNCT
ijassa-499	118	7	u3	u3	PROPN
ijassa-499	118	8	,	,	PUNCT
ijassa-499	118	9	u4	u4	PROPN
ijassa-499	118	10	are	be	AUX
ijassa-499	118	11	bounded	bound	VERB
ijassa-499	118	12	by	by	ADP
ijassa-499	118	13	[	[	X
ijassa-499	118	14	0	0	NUM
ijassa-499	118	15	,	,	PUNCT
ijassa-499	118	16	1	1	NUM
ijassa-499	118	17	]	]	PUNCT
ijassa-499	118	18	.	.	PUNCT
ijassa-499	119	1	the	the	DET
ijassa-499	119	2	initial	initial	ADJ
ijassa-499	119	3	dataset	dataset	NOUN
ijassa-499	119	4	contains	contain	VERB
ijassa-499	119	5	10	10	NUM
ijassa-499	119	6	points	point	NOUN
ijassa-499	119	7	distributed	distribute	VERB
ijassa-499	119	8	uniformly	uniformly	ADV
ijassa-499	119	9	.	.	PUNCT
ijassa-499	120	1	control	control	NOUN
ijassa-499	120	2	is	be	AUX
ijassa-499	120	3	selected	select	VERB
ijassa-499	120	4	as	as	ADP
ijassa-499	120	5	the	the	DET
ijassa-499	120	6	center	center	NOUN
ijassa-499	120	7	of	of	ADP
ijassa-499	120	8	the	the	DET
ijassa-499	120	9	target	target	NOUN
ijassa-499	120	10	node	node	NOUN
ijassa-499	120	11	.	.	PUNCT
ijassa-499	121	1	figure	figure	NOUN
ijassa-499	121	2	4	4	NUM
ijassa-499	121	3	illustrates	illustrate	VERB
ijassa-499	121	4	the	the	DET
ijassa-499	121	5	desired	desire	VERB
ijassa-499	121	6	outputs	output	NOUN
ijassa-499	121	7	and	and	CCONJ
ijassa-499	121	8	the	the	DET
ijassa-499	121	9	reactions	reaction	NOUN
ijassa-499	121	10	to	to	ADP
ijassa-499	121	11	a	a	DET
ijassa-499	121	12	generated	generate	VERB
ijassa-499	121	13	control	control	NOUN
ijassa-499	121	14	.	.	PUNCT
ijassa-499	122	1	figure	figure	NOUN
ijassa-499	122	2	5	5	NUM
ijassa-499	122	3	shows	show	VERB
ijassa-499	122	4	the	the	DET
ijassa-499	122	5	initial	initial	ADJ
ijassa-499	122	6	dataset	dataset	NOUN
ijassa-499	122	7	and	and	CCONJ
ijassa-499	122	8	the	the	DET
ijassa-499	122	9	observations	observation	NOUN
ijassa-499	122	10	obtained	obtain	VERB
ijassa-499	122	11	during	during	ADP
ijassa-499	122	12	the	the	DET
ijassa-499	122	13	simulation	simulation	NOUN
ijassa-499	122	14	process	process	NOUN
ijassa-499	122	15	.	.	PUNCT
ijassa-499	123	1	4.2.2	4.2.2	X
ijassa-499	123	2	.	.	NUM
ijassa-499	123	3	controlled	control	VERB
ijassa-499	123	4	and	and	CCONJ
ijassa-499	123	5	observed	observe	VERB
ijassa-499	123	6	uncontrolled	uncontrolled	ADJ
ijassa-499	123	7	inputs	input	NOUN
ijassa-499	123	8	one	one	NUM
ijassa-499	123	9	-	-	PUNCT
ijassa-499	123	10	dimensional	dimensional	ADJ
ijassa-499	123	11	output	output	NOUN
ijassa-499	123	12	.	.	PUNCT
ijassa-499	124	1	assume	assume	VERB
ijassa-499	124	2	there	there	PRON
ijassa-499	124	3	are	be	AUX
ijassa-499	124	4	controlled	control	VERB
ijassa-499	124	5	and	and	CCONJ
ijassa-499	124	6	observed	observe	VERB
ijassa-499	124	7	uncontrolled	uncontrolled	ADJ
ijassa-499	124	8	variables	variable	NOUN
ijassa-499	124	9	ū	ū	NOUN
ijassa-499	124	10	and	and	CCONJ
ijassa-499	124	11	one	one	NUM
ijassa-499	124	12	output	output	NOUN
ijassa-499	124	13	variable	variable	NOUN
ijassa-499	124	14	x.	x.	NOUN
ijassa-499	125	1	the	the	DET
ijassa-499	125	2	decision	decision	NOUN
ijassa-499	125	3	tree	tree	NOUN
ijassa-499	125	4	is	be	AUX
ijassa-499	125	5	fit	fit	ADJ
ijassa-499	125	6	using	use	VERB
ijassa-499	125	7	the	the	DET
ijassa-499	125	8	training	training	NOUN
ijassa-499	125	9	dataset	dataset	NOUN
ijassa-499	125	10	containing	contain	VERB
ijassa-499	125	11	simultaneous	simultaneous	ADJ
ijassa-499	125	12	observations	observation	NOUN
ijassa-499	125	13	of	of	ADP
ijassa-499	125	14	ū	ū	NOUN
ijassa-499	125	15	and	and	CCONJ
ijassa-499	125	16	x.	x.	NOUN
ijassa-499	125	17	the	the	DET
ijassa-499	125	18	control	control	NOUN
ijassa-499	125	19	algorithm	algorithm	NOUN
ijassa-499	125	20	:	:	PUNCT
ijassa-499	125	21	1	1	X
ijassa-499	125	22	.	.	X
ijassa-499	125	23	set	set	VERB
ijassa-499	125	24	the	the	DET
ijassa-499	125	25	control	control	NOUN
ijassa-499	125	26	target	target	NOUN
ijassa-499	125	27	x∗.	x∗.	PUNCT
ijassa-499	126	1	copyright	copyright	NOUN
ijassa-499	126	2	c	c	ADP
ijassa-499	126	3	©	©	PROPN
ijassa-499	126	4	2017	2017	NUM
ijassa-499	126	5	assa	assa	NOUN
ijassa-499	126	6	.	.	PUNCT
ijassa-499	127	1	adv	adv	PROPN
ijassa-499	127	2	syst	syst	PROPN
ijassa-499	127	3	sci	sci	PROPN
ijassa-499	127	4	appl	appl	PROPN
ijassa-499	127	5	(	(	PUNCT
ijassa-499	127	6	2017	2017	NUM
ijassa-499	127	7	)	)	PUNCT
ijassa-499	127	8	regression	regression	NOUN
ijassa-499	127	9	tree	tree	NOUN
ijassa-499	127	10	control	control	NOUN
ijassa-499	127	11	of	of	ADP
ijassa-499	127	12	multidimensional	multidimensional	ADJ
ijassa-499	127	13	static	static	ADJ
ijassa-499	127	14	object	object	NOUN
ijassa-499	127	15	63	63	NUM
ijassa-499	127	16	fig.4	fig.4	ADJ
ijassa-499	127	17	simulation	simulation	NOUN
ijassa-499	127	18	of	of	ADP
ijassa-499	127	19	a	a	DET
ijassa-499	127	20	process	process	NOUN
ijassa-499	127	21	.	.	PUNCT
ijassa-499	128	1	desired	desire	VERB
ijassa-499	128	2	outputs	output	NOUN
ijassa-499	128	3	and	and	CCONJ
ijassa-499	128	4	reactions	reaction	NOUN
ijassa-499	128	5	to	to	ADP
ijassa-499	128	6	a	a	DET
ijassa-499	128	7	generated	generate	VERB
ijassa-499	128	8	control	control	NOUN
ijassa-499	128	9	fig.5	fig.5	VERB
ijassa-499	128	10	simulation	simulation	NOUN
ijassa-499	128	11	of	of	ADP
ijassa-499	128	12	a	a	DET
ijassa-499	128	13	process	process	NOUN
ijassa-499	128	14	.	.	PUNCT
ijassa-499	129	1	initial	initial	ADJ
ijassa-499	129	2	dataset	dataset	NOUN
ijassa-499	129	3	and	and	CCONJ
ijassa-499	129	4	generated	generate	VERB
ijassa-499	129	5	dataset	dataset	NOUN
ijassa-499	129	6	2	2	NUM
ijassa-499	129	7	.	.	PUNCT
ijassa-499	129	8	predict	predict	VERB
ijassa-499	129	9	the	the	DET
ijassa-499	129	10	uncontrolled	uncontrolled	ADJ
ijassa-499	129	11	input	input	NOUN
ijassa-499	129	12	variables	variable	NOUN
ijassa-499	129	13	uj	uj	PROPN
ijassa-499	129	14	,	,	PUNCT
ijassa-499	129	15	predicted	predict	VERB
ijassa-499	129	16	,	,	PUNCT
ijassa-499	129	17	j	j	PROPN
ijassa-499	129	18	=	=	PUNCT
ijassa-499	129	19	mu	mu	PROPN
ijassa-499	129	20	+	+	CCONJ
ijassa-499	129	21	1	1	NUM
ijassa-499	129	22	,	,	PUNCT
ijassa-499	129	23	...	...	PUNCT
ijassa-499	129	24	,	,	PUNCT
ijassa-499	129	25	mu	mu	PROPN
ijassa-499	129	26	+	+	PROPN
ijassa-499	129	27	mv	mv	PROPN
ijassa-499	129	28	.	.	PROPN
ijassa-499	130	1	3	3	X
ijassa-499	130	2	.	.	X
ijassa-499	130	3	cut	cut	VERB
ijassa-499	130	4	nodes	node	NOUN
ijassa-499	130	5	which	which	PRON
ijassa-499	130	6	can	can	AUX
ijassa-499	130	7	not	not	PART
ijassa-499	130	8	be	be	AUX
ijassa-499	130	9	achieved	achieve	VERB
ijassa-499	130	10	with	with	ADP
ijassa-499	130	11	the	the	DET
ijassa-499	130	12	predicted	predict	VERB
ijassa-499	130	13	uncontrolled	uncontrolled	ADJ
ijassa-499	130	14	input	input	NOUN
ijassa-499	130	15	variables	variable	NOUN
ijassa-499	130	16	.	.	PUNCT
ijassa-499	131	1	4	4	X
ijassa-499	131	2	.	.	X
ijassa-499	131	3	search	search	NOUN
ijassa-499	131	4	for	for	ADP
ijassa-499	131	5	a	a	DET
ijassa-499	131	6	leaf	leaf	NOUN
ijassa-499	131	7	node	node	NOUN
ijassa-499	131	8	such	such	DET
ijassa-499	131	9	that	that	DET
ijassa-499	131	10	k∗	k∗	NOUN
ijassa-499	131	11	=	=	PUNCT
ijassa-499	132	1	arg	arg	NOUN
ijassa-499	132	2	min	min	PROPN
ijassa-499	132	3	k	k	NOUN
ijassa-499	132	4	,	,	PUNCT
ijassa-499	132	5	ū′∈sk	ū′∈sk	NOUN
ijassa-499	132	6	d1	d1	PROPN
ijassa-499	132	7	(	(	PUNCT
ijassa-499	132	8	x̂k	x̂k	PROPN
ijassa-499	132	9	,	,	PUNCT
ijassa-499	132	10	x	x	SYM
ijassa-499	132	11	∗	∗	NOUN
ijassa-499	132	12	)	)	PUNCT
ijassa-499	132	13	,	,	PUNCT
ijassa-499	132	14	(	(	PUNCT
ijassa-499	132	15	4.7	4.7	NUM
ijassa-499	132	16	)	)	PUNCT
ijassa-499	132	17	where	where	SCONJ
ijassa-499	132	18	ū′	ū′	PROPN
ijassa-499	132	19	is	be	AUX
ijassa-499	132	20	the	the	DET
ijassa-499	132	21	input	input	NOUN
ijassa-499	132	22	values	value	NOUN
ijassa-499	132	23	such	such	ADJ
ijassa-499	132	24	that	that	PRON
ijassa-499	132	25	u′j	u′j	NOUN
ijassa-499	132	26	,	,	PUNCT
ijassa-499	132	27	j	j	PROPN
ijassa-499	132	28	=	=	SYM
ijassa-499	132	29	1	1	NUM
ijassa-499	132	30	,	,	PUNCT
ijassa-499	132	31	...	...	PUNCT
ijassa-499	132	32	,	,	PUNCT
ijassa-499	132	33	mu	mu	PROPN
ijassa-499	132	34	can	can	AUX
ijassa-499	132	35	take	take	VERB
ijassa-499	132	36	any	any	DET
ijassa-499	132	37	value	value	NOUN
ijassa-499	132	38	and	and	CCONJ
ijassa-499	132	39	u′j	u′j	NOUN
ijassa-499	132	40	=	=	SYM
ijassa-499	132	41	uj	uj	PROPN
ijassa-499	132	42	,	,	PUNCT
ijassa-499	132	43	predicted	predict	VERB
ijassa-499	132	44	,	,	PUNCT
ijassa-499	132	45	j	j	PROPN
ijassa-499	132	46	=	=	PUNCT
ijassa-499	132	47	mu	mu	PROPN
ijassa-499	132	48	+	+	CCONJ
ijassa-499	132	49	1	1	NUM
ijassa-499	132	50	,	,	PUNCT
ijassa-499	132	51	...	...	PUNCT
ijassa-499	132	52	,	,	PUNCT
ijassa-499	132	53	mu	mu	PROPN
ijassa-499	132	54	+	+	PROPN
ijassa-499	132	55	mv	mv	PROPN
ijassa-499	132	56	.	.	PROPN
ijassa-499	132	57	5	5	NUM
ijassa-499	132	58	.	.	X
ijassa-499	132	59	find	find	VERB
ijassa-499	132	60	a	a	DET
ijassa-499	132	61	control	control	NOUN
ijassa-499	132	62	ū∗	ū∗	PROPN
ijassa-499	132	63	contained	contain	VERB
ijassa-499	132	64	in	in	ADP
ijassa-499	132	65	the	the	DET
ijassa-499	132	66	region	region	NOUN
ijassa-499	132	67	sk∗	sk∗	NOUN
ijassa-499	132	68	.	.	PUNCT
ijassa-499	133	1	the	the	DET
ijassa-499	133	2	experimental	experimental	ADJ
ijassa-499	133	3	result	result	NOUN
ijassa-499	133	4	.	.	PUNCT
ijassa-499	133	5	suppose	suppose	VERB
ijassa-499	133	6	now	now	ADV
ijassa-499	133	7	that	that	SCONJ
ijassa-499	133	8	u2	u2	NOUN
ijassa-499	133	9	is	be	AUX
ijassa-499	133	10	uncontrolled	uncontrolled	ADJ
ijassa-499	133	11	and	and	CCONJ
ijassa-499	133	12	changed	change	VERB
ijassa-499	133	13	as	as	SCONJ
ijassa-499	133	14	follows	follow	VERB
ijassa-499	133	15	u2	u2	PROPN
ijassa-499	133	16	i	i	NOUN
ijassa-499	133	17	=	=	SYM
ijassa-499	133	18	sin	sin	NOUN
ijassa-499	133	19	(	(	PUNCT
ijassa-499	133	20	πi/25	πi/25	PROPN
ijassa-499	133	21	)	)	PUNCT
ijassa-499	133	22	.	.	PUNCT
ijassa-499	134	1	the	the	DET
ijassa-499	134	2	previous	previous	ADJ
ijassa-499	134	3	value	value	NOUN
ijassa-499	134	4	of	of	ADP
ijassa-499	134	5	u2	u2	PROPN
ijassa-499	134	6	i−1	i−1	PROPN
ijassa-499	134	7	is	be	AUX
ijassa-499	134	8	used	use	VERB
ijassa-499	134	9	as	as	ADP
ijassa-499	134	10	a	a	DET
ijassa-499	134	11	prediction	prediction	NOUN
ijassa-499	134	12	for	for	ADP
ijassa-499	134	13	the	the	DET
ijassa-499	134	14	next	next	ADJ
ijassa-499	134	15	step	step	NOUN
ijassa-499	134	16	u2,prediction	u2,prediction	PROPN
ijassa-499	134	17	.	.	PUNCT
ijassa-499	135	1	figure	figure	NOUN
ijassa-499	135	2	6	6	NUM
ijassa-499	135	3	illustrates	illustrate	VERB
ijassa-499	135	4	the	the	DET
ijassa-499	135	5	desired	desire	VERB
ijassa-499	135	6	outputs	output	NOUN
ijassa-499	135	7	and	and	CCONJ
ijassa-499	135	8	the	the	DET
ijassa-499	135	9	reactions	reaction	NOUN
ijassa-499	135	10	to	to	ADP
ijassa-499	135	11	a	a	DET
ijassa-499	135	12	generated	generate	VERB
ijassa-499	135	13	control	control	NOUN
ijassa-499	135	14	.	.	PUNCT
ijassa-499	136	1	figure	figure	NOUN
ijassa-499	136	2	7	7	NUM
ijassa-499	136	3	shows	show	VERB
ijassa-499	136	4	the	the	DET
ijassa-499	136	5	initial	initial	ADJ
ijassa-499	136	6	dataset	dataset	NOUN
ijassa-499	136	7	and	and	CCONJ
ijassa-499	136	8	the	the	DET
ijassa-499	136	9	observations	observation	NOUN
ijassa-499	136	10	obtained	obtain	VERB
ijassa-499	136	11	during	during	ADP
ijassa-499	136	12	the	the	DET
ijassa-499	136	13	simulation	simulation	NOUN
ijassa-499	136	14	process	process	NOUN
ijassa-499	136	15	.	.	PUNCT
ijassa-499	137	1	4.3	4.3	NUM
ijassa-499	137	2	.	.	PUNCT
ijassa-499	137	3	multi	multi	ADJ
ijassa-499	137	4	-	-	ADJ
ijassa-499	137	5	dimensional	dimensional	ADJ
ijassa-499	137	6	output	output	NOUN
ijassa-499	137	7	,	,	PUNCT
ijassa-499	137	8	controlled	control	VERB
ijassa-499	137	9	and	and	CCONJ
ijassa-499	137	10	observed	observe	VERB
ijassa-499	137	11	uncontrolled	uncontrolled	ADJ
ijassa-499	137	12	inputs	input	NOUN
ijassa-499	137	13	assume	assume	VERB
ijassa-499	137	14	there	there	PRON
ijassa-499	137	15	are	be	AUX
ijassa-499	137	16	controlled	control	VERB
ijassa-499	137	17	and	and	CCONJ
ijassa-499	137	18	observed	observe	VERB
ijassa-499	137	19	uncontrolled	uncontrolled	ADJ
ijassa-499	137	20	variables	variable	NOUN
ijassa-499	137	21	ū	ū	NOUN
ijassa-499	137	22	and	and	CCONJ
ijassa-499	137	23	the	the	DET
ijassa-499	137	24	vector	vector	NOUN
ijassa-499	137	25	of	of	ADP
ijassa-499	137	26	output	output	NOUN
ijassa-499	137	27	variables	variable	NOUN
ijassa-499	137	28	x̄.	x̄.	PUNCT
ijassa-499	137	29	decision	decision	NOUN
ijassa-499	137	30	trees	tree	NOUN
ijassa-499	137	31	are	be	AUX
ijassa-499	137	32	fit	fit	ADJ
ijassa-499	137	33	using	use	VERB
ijassa-499	137	34	the	the	DET
ijassa-499	137	35	training	training	NOUN
ijassa-499	137	36	dataset	dataset	NOUN
ijassa-499	137	37	containing	contain	VERB
ijassa-499	137	38	simultaneous	simultaneous	ADJ
ijassa-499	137	39	observations	observation	NOUN
ijassa-499	137	40	of	of	ADP
ijassa-499	137	41	ū	ū	NOUN
ijassa-499	137	42	and	and	CCONJ
ijassa-499	137	43	x̄.	x̄.	PUNCT
ijassa-499	137	44	the	the	DET
ijassa-499	137	45	control	control	NOUN
ijassa-499	137	46	algorithm	algorithm	NOUN
ijassa-499	137	47	:	:	PUNCT
ijassa-499	137	48	1	1	X
ijassa-499	137	49	.	.	X
ijassa-499	137	50	set	set	VERB
ijassa-499	137	51	the	the	DET
ijassa-499	137	52	control	control	NOUN
ijassa-499	137	53	targets	target	NOUN
ijassa-499	137	54	x̄∗.	x̄∗.	PUNCT
ijassa-499	137	55	2	2	X
ijassa-499	137	56	.	.	X
ijassa-499	137	57	predict	predict	VERB
ijassa-499	137	58	the	the	DET
ijassa-499	137	59	uncontrolled	uncontrolled	ADJ
ijassa-499	137	60	input	input	NOUN
ijassa-499	137	61	variables	variable	NOUN
ijassa-499	137	62	uj	uj	PROPN
ijassa-499	137	63	,	,	PUNCT
ijassa-499	137	64	predicted	predict	VERB
ijassa-499	137	65	,	,	PUNCT
ijassa-499	137	66	j	j	PROPN
ijassa-499	137	67	=	=	PUNCT
ijassa-499	137	68	mu	mu	PROPN
ijassa-499	137	69	+	+	CCONJ
ijassa-499	137	70	1	1	NUM
ijassa-499	137	71	,	,	PUNCT
ijassa-499	137	72	...	...	PUNCT
ijassa-499	137	73	,	,	PUNCT
ijassa-499	137	74	mu	mu	PROPN
ijassa-499	137	75	+	+	PROPN
ijassa-499	137	76	mv	mv	PROPN
ijassa-499	137	77	.	.	PROPN
ijassa-499	138	1	3	3	X
ijassa-499	138	2	.	.	X
ijassa-499	138	3	find	find	VERB
ijassa-499	138	4	intersections	intersection	NOUN
ijassa-499	138	5	of	of	ADP
ijassa-499	138	6	nodes	node	NOUN
ijassa-499	138	7	which	which	PRON
ijassa-499	138	8	contain	contain	VERB
ijassa-499	138	9	the	the	DET
ijassa-499	138	10	predicted	predict	VERB
ijassa-499	138	11	uncontrolled	uncontrolled	ADJ
ijassa-499	138	12	variables	variable	NOUN
ijassa-499	138	13	sk	sk	VERB
ijassa-499	138	14	1,	1,	NUM
ijassa-499	138	15	...	...	PUNCT
ijassa-499	138	16	,mu	,mu	PUNCT
ijassa-499	138	17	,	,	PUNCT
ijassa-499	138	18	k	k	PROPN
ijassa-499	138	19	=	=	SYM
ijassa-499	138	20	1	1	NUM
ijassa-499	138	21	,	,	PUNCT
ijassa-499	138	22	...	...	PUNCT
ijassa-499	138	23	,	,	PUNCT
ijassa-499	138	24	k	k	PROPN
ijassa-499	138	25	′	′	NOUN
ijassa-499	138	26	and	and	CCONJ
ijassa-499	138	27	the	the	DET
ijassa-499	138	28	output	output	NOUN
ijassa-499	138	29	values	value	NOUN
ijassa-499	138	30	associated	associate	VERB
ijassa-499	138	31	with	with	ADP
ijassa-499	138	32	these	these	DET
ijassa-499	138	33	intersections	intersection	NOUN
ijassa-499	138	34	x̂1	x̂1	PUNCT
ijassa-499	139	1	k	k	NOUN
ijassa-499	139	2	,	,	PUNCT
ijassa-499	139	3	...	...	PUNCT
ijassa-499	139	4	,	,	PUNCT
ijassa-499	139	5	x̂mx	x̂mx	PROPN
ijassa-499	140	1	k	k	PROPN
ijassa-499	140	2	.	.	PUNCT
ijassa-499	141	1	copyright	copyright	NOUN
ijassa-499	142	1	c	c	ADP
ijassa-499	142	2	©	©	PROPN
ijassa-499	142	3	2017	2017	NUM
ijassa-499	142	4	assa	assa	NOUN
ijassa-499	142	5	.	.	PUNCT
ijassa-499	143	1	adv	adv	PROPN
ijassa-499	143	2	syst	syst	PROPN
ijassa-499	143	3	sci	sci	PROPN
ijassa-499	143	4	appl	appl	PROPN
ijassa-499	143	5	(	(	PUNCT
ijassa-499	143	6	2017	2017	NUM
ijassa-499	143	7	)	)	PUNCT
ijassa-499	143	8	64	64	NUM
ijassa-499	143	9	e.	e.	PROPN
ijassa-499	143	10	mangalova	mangalova	PROPN
ijassa-499	143	11	fig.6	fig.6	PROPN
ijassa-499	143	12	simulation	simulation	NOUN
ijassa-499	143	13	of	of	ADP
ijassa-499	143	14	a	a	DET
ijassa-499	143	15	process	process	NOUN
ijassa-499	143	16	with	with	ADP
ijassa-499	143	17	uncontrolled	uncontrolled	ADJ
ijassa-499	143	18	input	input	NOUN
ijassa-499	143	19	.	.	PUNCT
ijassa-499	144	1	the	the	DET
ijassa-499	144	2	desired	desire	VERB
ijassa-499	144	3	outputs	output	NOUN
ijassa-499	144	4	and	and	CCONJ
ijassa-499	144	5	the	the	DET
ijassa-499	144	6	reactions	reaction	NOUN
ijassa-499	144	7	to	to	ADP
ijassa-499	144	8	the	the	DET
ijassa-499	144	9	generated	generate	VERB
ijassa-499	144	10	control	control	PROPN
ijassa-499	144	11	fig.7	fig.7	ADJ
ijassa-499	144	12	simulation	simulation	NOUN
ijassa-499	144	13	of	of	ADP
ijassa-499	144	14	a	a	DET
ijassa-499	144	15	process	process	NOUN
ijassa-499	144	16	with	with	ADP
ijassa-499	144	17	uncontrolled	uncontrolled	ADJ
ijassa-499	144	18	input	input	NOUN
ijassa-499	144	19	.	.	PUNCT
ijassa-499	145	1	the	the	DET
ijassa-499	145	2	initial	initial	ADJ
ijassa-499	145	3	dataset	dataset	NOUN
ijassa-499	145	4	and	and	CCONJ
ijassa-499	145	5	the	the	DET
ijassa-499	145	6	generated	generate	VERB
ijassa-499	145	7	dataset	dataset	NOUN
ijassa-499	145	8	4	4	NUM
ijassa-499	145	9	.	.	PUNCT
ijassa-499	145	10	search	search	NOUN
ijassa-499	145	11	for	for	ADP
ijassa-499	145	12	a	a	DET
ijassa-499	145	13	leaf	leaf	NOUN
ijassa-499	145	14	node	node	NOUN
ijassa-499	145	15	such	such	DET
ijassa-499	145	16	that	that	DET
ijassa-499	145	17	k∗	k∗	NOUN
ijassa-499	146	1	=	=	PUNCT
ijassa-499	146	2	arg	arg	NOUN
ijassa-499	146	3	min	min	PROPN
ijassa-499	147	1	k	k	PROPN
ijassa-499	147	2	dmx	dmx	PROPN
ijassa-499	147	3	(	(	PUNCT
ijassa-499	147	4	x̂1	x̂1	PROPN
ijassa-499	147	5	k	k	PROPN
ijassa-499	147	6	,	,	PUNCT
ijassa-499	147	7	...	...	PUNCT
ijassa-499	147	8	x̂	x̂	NUM
ijassa-499	148	1	mx	mx	PROPN
ijassa-499	148	2	k	k	PROPN
ijassa-499	148	3	,	,	PUNCT
ijassa-499	148	4	x̄∗	x̄∗	ADP
ijassa-499	148	5	)	)	PUNCT
ijassa-499	148	6	,	,	PUNCT
ijassa-499	148	7	(	(	PUNCT
ijassa-499	148	8	4.8	4.8	NUM
ijassa-499	148	9	)	)	PUNCT
ijassa-499	148	10	where	where	SCONJ
ijassa-499	148	11	dmx	dmx	NOUN
ijassa-499	148	12	is	be	AUX
ijassa-499	148	13	a	a	DET
ijassa-499	148	14	multi	multi	ADJ
ijassa-499	148	15	-	-	ADJ
ijassa-499	148	16	dimensional	dimensional	ADJ
ijassa-499	148	17	distance	distance	NOUN
ijassa-499	148	18	measurement	measurement	NOUN
ijassa-499	148	19	.	.	PUNCT
ijassa-499	149	1	5	5	X
ijassa-499	149	2	.	.	X
ijassa-499	149	3	find	find	VERB
ijassa-499	149	4	a	a	DET
ijassa-499	149	5	control	control	NOUN
ijassa-499	149	6	ū∗	ū∗	PROPN
ijassa-499	149	7	contained	contain	VERB
ijassa-499	149	8	in	in	ADP
ijassa-499	149	9	the	the	DET
ijassa-499	149	10	region	region	NOUN
ijassa-499	149	11	sk∗	sk∗	VERB
ijassa-499	149	12	1,	1,	NUM
ijassa-499	149	13	...	...	PUNCT
ijassa-499	149	14	,mu	,mu	PUNCT
ijassa-499	149	15	.	.	PUNCT
ijassa-499	150	1	the	the	DET
ijassa-499	150	2	experimental	experimental	ADJ
ijassa-499	150	3	result	result	NOUN
ijassa-499	150	4	.	.	PUNCT
ijassa-499	151	1	suppose	suppose	VERB
ijassa-499	151	2	now	now	ADV
ijassa-499	151	3	there	there	PRON
ijassa-499	151	4	are	be	VERB
ijassa-499	151	5	two	two	NUM
ijassa-499	151	6	outputs	output	NOUN
ijassa-499	152	1	x1	x1	NOUN
ijassa-499	152	2	=	=	PUNCT
ijassa-499	152	3	sin	sin	NOUN
ijassa-499	152	4	(	(	PUNCT
ijassa-499	152	5	2πu1	2πu1	NUM
ijassa-499	152	6	)	)	PUNCT
ijassa-499	153	1	+	+	CCONJ
ijassa-499	153	2	√	√	PROPN
ijassa-499	153	3	u2	u2	NOUN
ijassa-499	153	4	−	−	PROPN
ijassa-499	153	5	u3	u3	NOUN
ijassa-499	153	6	+	+	CCONJ
ijassa-499	153	7	ξ	ξ	PROPN
ijassa-499	153	8	and	and	CCONJ
ijassa-499	153	9	x2	x2	NOUN
ijassa-499	153	10	=	=	PUNCT
ijassa-499	153	11	√	√	PROPN
ijassa-499	153	12	u2	u2	PROPN
ijassa-499	153	13	−	−	PROPN
ijassa-499	153	14	u3	u3	NOUN
ijassa-499	153	15	+	+	CCONJ
ijassa-499	153	16	ξ	ξ	PROPN
ijassa-499	153	17	.	.	PUNCT
ijassa-499	153	18	figure	figure	NOUN
ijassa-499	153	19	8	8	NUM
ijassa-499	153	20	illustrates	illustrate	VERB
ijassa-499	153	21	the	the	DET
ijassa-499	153	22	desired	desire	VERB
ijassa-499	153	23	outputs	output	NOUN
ijassa-499	153	24	and	and	CCONJ
ijassa-499	153	25	the	the	DET
ijassa-499	153	26	reactions	reaction	NOUN
ijassa-499	153	27	to	to	ADP
ijassa-499	153	28	a	a	DET
ijassa-499	153	29	generated	generate	VERB
ijassa-499	153	30	control	control	NOUN
ijassa-499	153	31	.	.	PUNCT
ijassa-499	154	1	the	the	DET
ijassa-499	154	2	desired	desire	VERB
ijassa-499	154	3	outputs	output	NOUN
ijassa-499	154	4	for	for	ADP
ijassa-499	154	5	x1	x1	PROPN
ijassa-499	154	6	and	and	CCONJ
ijassa-499	154	7	x2	x2	PROPN
ijassa-499	154	8	are	be	AUX
ijassa-499	154	9	the	the	DET
ijassa-499	154	10	same	same	ADJ
ijassa-499	154	11	.	.	PUNCT
ijassa-499	155	1	figure	figure	NOUN
ijassa-499	155	2	9	9	NUM
ijassa-499	155	3	shows	show	VERB
ijassa-499	155	4	the	the	DET
ijassa-499	155	5	initial	initial	ADJ
ijassa-499	155	6	dataset	dataset	NOUN
ijassa-499	155	7	and	and	CCONJ
ijassa-499	155	8	the	the	DET
ijassa-499	155	9	observations	observation	NOUN
ijassa-499	155	10	obtained	obtain	VERB
ijassa-499	155	11	during	during	ADP
ijassa-499	155	12	the	the	DET
ijassa-499	155	13	simulation	simulation	NOUN
ijassa-499	155	14	process	process	NOUN
ijassa-499	155	15	.	.	PUNCT
ijassa-499	156	1	fig.8	fig.8	PROPN
ijassa-499	156	2	simulation	simulation	NOUN
ijassa-499	156	3	of	of	ADP
ijassa-499	156	4	a	a	DET
ijassa-499	156	5	multidimensional	multidimensional	ADJ
ijassa-499	156	6	process	process	NOUN
ijassa-499	156	7	.	.	PUNCT
ijassa-499	157	1	the	the	DET
ijassa-499	157	2	desired	desire	VERB
ijassa-499	157	3	outputs	output	NOUN
ijassa-499	157	4	and	and	CCONJ
ijassa-499	157	5	the	the	DET
ijassa-499	157	6	reactions	reaction	NOUN
ijassa-499	157	7	to	to	ADP
ijassa-499	157	8	a	a	DET
ijassa-499	157	9	generated	generate	VERB
ijassa-499	157	10	control	control	NOUN
ijassa-499	157	11	copyright	copyright	NOUN
ijassa-499	157	12	c	c	ADP
ijassa-499	157	13	©	©	PROPN
ijassa-499	157	14	2017	2017	NUM
ijassa-499	157	15	assa	assa	NOUN
ijassa-499	157	16	.	.	PUNCT
ijassa-499	158	1	adv	adv	PROPN
ijassa-499	158	2	syst	syst	PROPN
ijassa-499	158	3	sci	sci	PROPN
ijassa-499	158	4	appl	appl	PROPN
ijassa-499	158	5	(	(	PUNCT
ijassa-499	158	6	2017	2017	NUM
ijassa-499	158	7	)	)	PUNCT
ijassa-499	158	8	regression	regression	NOUN
ijassa-499	158	9	tree	tree	NOUN
ijassa-499	158	10	control	control	NOUN
ijassa-499	158	11	of	of	ADP
ijassa-499	158	12	multidimensional	multidimensional	ADJ
ijassa-499	158	13	static	static	ADJ
ijassa-499	158	14	object	object	NOUN
ijassa-499	158	15	65	65	NUM
ijassa-499	158	16	fig.9	fig.9	PROPN
ijassa-499	158	17	simulation	simulation	NOUN
ijassa-499	158	18	of	of	ADP
ijassa-499	158	19	a	a	DET
ijassa-499	158	20	multidimensional	multidimensional	ADJ
ijassa-499	158	21	process	process	NOUN
ijassa-499	158	22	.	.	PUNCT
ijassa-499	159	1	the	the	DET
ijassa-499	159	2	initial	initial	ADJ
ijassa-499	159	3	dataset	dataset	NOUN
ijassa-499	159	4	and	and	CCONJ
ijassa-499	159	5	the	the	DET
ijassa-499	159	6	generated	generate	VERB
ijassa-499	159	7	dataset	dataset	NOUN
ijassa-499	159	8	)	)	PUNCT
ijassa-499	159	9	conclusion	conclusion	NOUN
ijassa-499	159	10	in	in	ADP
ijassa-499	159	11	this	this	DET
ijassa-499	159	12	paper	paper	NOUN
ijassa-499	159	13	a	a	DET
ijassa-499	159	14	control	control	NOUN
ijassa-499	159	15	task	task	NOUN
ijassa-499	159	16	of	of	ADP
ijassa-499	159	17	a	a	DET
ijassa-499	159	18	multidimensional	multidimensional	ADJ
ijassa-499	159	19	static	static	ADJ
ijassa-499	159	20	system	system	NOUN
ijassa-499	159	21	is	be	AUX
ijassa-499	159	22	discussed	discuss	VERB
ijassa-499	159	23	.	.	PUNCT
ijassa-499	160	1	the	the	DET
ijassa-499	160	2	paper	paper	NOUN
ijassa-499	160	3	presents	present	VERB
ijassa-499	160	4	the	the	DET
ijassa-499	160	5	advantages	advantage	NOUN
ijassa-499	160	6	and	and	CCONJ
ijassa-499	160	7	disadvantages	disadvantage	NOUN
ijassa-499	160	8	of	of	ADP
ijassa-499	160	9	the	the	DET
ijassa-499	160	10	nonparametric	nonparametric	ADJ
ijassa-499	160	11	algorithm	algorithm	NOUN
ijassa-499	160	12	based	base	VERB
ijassa-499	160	13	on	on	ADP
ijassa-499	160	14	the	the	DET
ijassa-499	160	15	nadaraya	nadaraya	PROPN
ijassa-499	160	16	-	-	PUNCT
ijassa-499	160	17	watson	watson	NOUN
ijassa-499	160	18	estimator	estimator	NOUN
ijassa-499	160	19	and	and	CCONJ
ijassa-499	160	20	their	their	PRON
ijassa-499	160	21	sequence	sequence	NOUN
ijassa-499	160	22	.	.	PUNCT
ijassa-499	161	1	in	in	ADP
ijassa-499	161	2	order	order	NOUN
ijassa-499	161	3	to	to	PART
ijassa-499	161	4	avoid	avoid	VERB
ijassa-499	161	5	the	the	DET
ijassa-499	161	6	disadvantages	disadvantage	NOUN
ijassa-499	161	7	of	of	ADP
ijassa-499	161	8	this	this	DET
ijassa-499	161	9	nonparametric	nonparametric	NOUN
ijassa-499	161	10	algorithm	algorithm	NOUN
ijassa-499	161	11	,	,	PUNCT
ijassa-499	161	12	the	the	DET
ijassa-499	161	13	modification	modification	NOUN
ijassa-499	161	14	with	with	ADP
ijassa-499	161	15	piecewise	piecewise	NOUN
ijassa-499	161	16	constant	constant	ADJ
ijassa-499	161	17	approximation	approximation	NOUN
ijassa-499	161	18	of	of	ADP
ijassa-499	161	19	the	the	DET
ijassa-499	161	20	nonparametric	nonparametric	NOUN
ijassa-499	161	21	estimator	estimator	NOUN
ijassa-499	161	22	is	be	AUX
ijassa-499	161	23	put	put	VERB
ijassa-499	161	24	forward	forward	ADV
ijassa-499	161	25	.	.	PUNCT
ijassa-499	162	1	in	in	ADP
ijassa-499	162	2	the	the	DET
ijassa-499	162	3	proposed	propose	VERB
ijassa-499	162	4	algorithm	algorithm	NOUN
ijassa-499	162	5	classification	classification	NOUN
ijassa-499	162	6	and	and	CCONJ
ijassa-499	162	7	regression	regression	NOUN
ijassa-499	162	8	trees	tree	NOUN
ijassa-499	162	9	are	be	AUX
ijassa-499	162	10	used	use	VERB
ijassa-499	162	11	as	as	ADP
ijassa-499	162	12	a	a	DET
ijassa-499	162	13	predictive	predictive	ADJ
ijassa-499	162	14	model	model	NOUN
ijassa-499	162	15	instead	instead	ADV
ijassa-499	162	16	of	of	ADP
ijassa-499	162	17	the	the	DET
ijassa-499	162	18	nadaraya	nadaraya	PROPN
ijassa-499	162	19	-	-	PUNCT
ijassa-499	162	20	watson	watson	NOUN
ijassa-499	162	21	estimator	estimator	NOUN
ijassa-499	162	22	.	.	PUNCT
ijassa-499	163	1	the	the	DET
ijassa-499	163	2	control	control	NOUN
ijassa-499	163	3	algorithm	algorithm	NOUN
ijassa-499	163	4	based	base	VERB
ijassa-499	163	5	on	on	ADP
ijassa-499	163	6	cart	cart	NOUN
ijassa-499	163	7	is	be	AUX
ijassa-499	163	8	tested	test	VERB
ijassa-499	163	9	for	for	ADP
ijassa-499	163	10	different	different	ADJ
ijassa-499	163	11	task	task	NOUN
ijassa-499	163	12	formulations	formulation	NOUN
ijassa-499	163	13	:	:	PUNCT
ijassa-499	163	14	controlled	control	VERB
ijassa-499	163	15	inputs	input	NOUN
ijassa-499	163	16	and	and	CCONJ
ijassa-499	163	17	one	one	NUM
ijassa-499	163	18	-	-	PUNCT
ijassa-499	163	19	dimensional	dimensional	ADJ
ijassa-499	163	20	output	output	NOUN
ijassa-499	163	21	,	,	PUNCT
ijassa-499	163	22	controlled	control	VERB
ijassa-499	163	23	and	and	CCONJ
ijassa-499	163	24	observed	observe	VERB
ijassa-499	163	25	uncontrolled	uncontrolled	ADJ
ijassa-499	163	26	inputs	input	NOUN
ijassa-499	163	27	and	and	CCONJ
ijassa-499	163	28	onedimensional	onedimensional	ADJ
ijassa-499	163	29	output	output	NOUN
ijassa-499	163	30	,	,	PUNCT
ijassa-499	163	31	controlled	control	VERB
ijassa-499	163	32	and	and	CCONJ
ijassa-499	163	33	observed	observe	VERB
ijassa-499	163	34	uncontrolled	uncontrolled	ADJ
ijassa-499	163	35	inputs	input	NOUN
ijassa-499	163	36	and	and	CCONJ
ijassa-499	163	37	multi	multi	ADJ
ijassa-499	163	38	-	-	ADJ
ijassa-499	163	39	dimensional	dimensional	ADJ
ijassa-499	163	40	outputs	output	NOUN
ijassa-499	163	41	.	.	PUNCT
ijassa-499	164	1	references	reference	NOUN
ijassa-499	164	2	1	1	NUM
ijassa-499	164	3	.	.	PUNCT
ijassa-499	165	1	richalet	richalet	PROPN
ijassa-499	165	2	j.	j.	PROPN
ijassa-499	165	3	,	,	PUNCT
ijassa-499	165	4	rault	rault	NOUN
ijassa-499	165	5	a.	a.	NOUN
ijassa-499	165	6	,	,	PUNCT
ijassa-499	165	7	testud	testud	PROPN
ijassa-499	165	8	j.l	j.l	PROPN
ijassa-499	165	9	.	.	PROPN
ijassa-499	165	10	&	&	CCONJ
ijassa-499	165	11	papon	papon	PROPN
ijassa-499	165	12	j.	j.	PROPN
ijassa-499	165	13	(	(	PUNCT
ijassa-499	165	14	1978	1978	NUM
ijassa-499	165	15	)	)	PUNCT
ijassa-499	165	16	.	.	PUNCT
ijassa-499	166	1	model	model	PROPN
ijassa-499	166	2	predictive	predictive	ADJ
ijassa-499	166	3	heuristic	heuristic	ADJ
ijassa-499	166	4	control	control	NOUN
ijassa-499	166	5	:	:	PUNCT
ijassa-499	166	6	applications	application	NOUN
ijassa-499	166	7	to	to	ADP
ijassa-499	166	8	industrial	industrial	ADJ
ijassa-499	166	9	processes	process	NOUN
ijassa-499	166	10	,	,	PUNCT
ijassa-499	166	11	automatica	automatica	PROPN
ijassa-499	166	12	,	,	PUNCT
ijassa-499	166	13	14	14	NUM
ijassa-499	166	14	(	(	PUNCT
ijassa-499	166	15	5	5	NUM
ijassa-499	166	16	)	)	PUNCT
ijassa-499	166	17	,	,	PUNCT
ijassa-499	166	18	413–428	413–428	NUM
ijassa-499	166	19	.	.	NOUN
ijassa-499	167	1	2	2	X
ijassa-499	167	2	.	.	X
ijassa-499	167	3	psichogios	psichogios	PROPN
ijassa-499	167	4	d.	d.	PROPN
ijassa-499	167	5	c.	c.	PROPN
ijassa-499	167	6	&	&	CCONJ
ijassa-499	167	7	ungar	ungar	PROPN
ijassa-499	167	8	l.	l.	PROPN
ijassa-499	167	9	h.	h.	PROPN
ijassa-499	167	10	(	(	PUNCT
ijassa-499	167	11	1991	1991	NUM
ijassa-499	167	12	)	)	PUNCT
ijassa-499	167	13	.	.	PUNCT
ijassa-499	168	1	direct	direct	ADJ
ijassa-499	168	2	and	and	CCONJ
ijassa-499	168	3	indirect	indirect	ADJ
ijassa-499	168	4	model	model	NOUN
ijassa-499	168	5	based	base	VERB
ijassa-499	168	6	control	control	NOUN
ijassa-499	168	7	using	use	VERB
ijassa-499	168	8	artificial	artificial	ADJ
ijassa-499	168	9	neural	neural	ADJ
ijassa-499	168	10	networks	network	NOUN
ijassa-499	168	11	,	,	PUNCT
ijassa-499	168	12	industrial	industrial	PROPN
ijassa-499	168	13	&	&	CCONJ
ijassa-499	168	14	engineering	engineer	VERB
ijassa-499	168	15	chemistry	chemistry	NOUN
ijassa-499	168	16	research	research	NOUN
ijassa-499	168	17	,	,	PUNCT
ijassa-499	168	18	30	30	NUM
ijassa-499	168	19	(	(	PUNCT
ijassa-499	168	20	12	12	NUM
ijassa-499	168	21	)	)	PUNCT
ijassa-499	168	22	,	,	PUNCT
ijassa-499	168	23	2564	2564	NUM
ijassa-499	168	24	–	–	PUNCT
ijassa-499	168	25	2573	2573	NUM
ijassa-499	168	26	.	.	PUNCT
ijassa-499	169	1	3	3	X
ijassa-499	169	2	.	.	X
ijassa-499	169	3	draeger	draeger	PROPN
ijassa-499	169	4	a.	a.	PROPN
ijassa-499	169	5	,	,	PUNCT
ijassa-499	169	6	engell	engell	PROPN
ijassa-499	169	7	s.	s.	PROPN
ijassa-499	169	8	&	&	CCONJ
ijassa-499	169	9	ranke	ranke	PROPN
ijassa-499	169	10	h.	h.	PROPN
ijassa-499	169	11	(	(	PUNCT
ijassa-499	169	12	1995	1995	NUM
ijassa-499	169	13	)	)	PUNCT
ijassa-499	169	14	.	.	PUNCT
ijassa-499	170	1	model	model	PROPN
ijassa-499	170	2	predictive	predictive	ADJ
ijassa-499	170	3	control	control	NOUN
ijassa-499	170	4	using	use	VERB
ijassa-499	170	5	neural	neural	ADJ
ijassa-499	170	6	networks	network	NOUN
ijassa-499	170	7	,	,	PUNCT
ijassa-499	170	8	ieee	ieee	NOUN
ijassa-499	170	9	control	control	PROPN
ijassa-499	170	10	systems	systems	PROPN
ijassa-499	170	11	magazine	magazine	NOUN
ijassa-499	170	12	,	,	PUNCT
ijassa-499	170	13	15	15	NUM
ijassa-499	170	14	(	(	PUNCT
ijassa-499	170	15	5	5	NUM
ijassa-499	170	16	)	)	PUNCT
ijassa-499	170	17	,	,	PUNCT
ijassa-499	170	18	61–66	61–66	NUM
ijassa-499	170	19	.	.	NOUN
ijassa-499	171	1	4	4	NUM
ijassa-499	171	2	.	.	X
ijassa-499	171	3	sarimveis	sarimveis	PROPN
ijassa-499	171	4	h.	h.	PROPN
ijassa-499	171	5	&	&	CCONJ
ijassa-499	171	6	bafas	bafas	PROPN
ijassa-499	171	7	g.	g.	PROPN
ijassa-499	171	8	(	(	PUNCT
ijassa-499	171	9	2003	2003	NUM
ijassa-499	171	10	)	)	PUNCT
ijassa-499	171	11	.	.	PUNCT
ijassa-499	172	1	fuzzy	fuzzy	ADJ
ijassa-499	172	2	model	model	NOUN
ijassa-499	172	3	predictive	predictive	PROPN
ijassa-499	172	4	control	control	NOUN
ijassa-499	172	5	of	of	ADP
ijassa-499	172	6	non	non	ADJ
ijassa-499	172	7	-	-	ADJ
ijassa-499	172	8	linear	linear	ADJ
ijassa-499	172	9	processes	process	NOUN
ijassa-499	172	10	using	use	VERB
ijassa-499	172	11	genetic	genetic	ADJ
ijassa-499	172	12	algorithms	algorithm	NOUN
ijassa-499	172	13	,	,	PUNCT
ijassa-499	172	14	fuzzy	fuzzy	ADJ
ijassa-499	172	15	sets	set	NOUN
ijassa-499	172	16	and	and	CCONJ
ijassa-499	172	17	systems	system	NOUN
ijassa-499	172	18	,	,	PUNCT
ijassa-499	172	19	139	139	NUM
ijassa-499	172	20	(	(	PUNCT
ijassa-499	172	21	1	1	NUM
ijassa-499	172	22	)	)	PUNCT
ijassa-499	172	23	,	,	PUNCT
ijassa-499	172	24	59–80	59–80	NUM
ijassa-499	172	25	.	.	NOUN
ijassa-499	173	1	5	5	NUM
ijassa-499	173	2	.	.	X
ijassa-499	173	3	da	da	PROPN
ijassa-499	173	4	costa	costa	PROPN
ijassa-499	173	5	sousa	sousa	PROPN
ijassa-499	173	6	j.m	j.m	PROPN
ijassa-499	173	7	.	.	PROPN
ijassa-499	173	8	&	&	CCONJ
ijassa-499	173	9	kaymak	kaymak	PROPN
ijassa-499	173	10	u.	u.	PROPN
ijassa-499	173	11	(	(	PUNCT
ijassa-499	173	12	2001	2001	NUM
ijassa-499	173	13	)	)	PUNCT
ijassa-499	173	14	.	.	PUNCT
ijassa-499	174	1	model	model	PROPN
ijassa-499	174	2	predictive	predictive	ADJ
ijassa-499	174	3	control	control	NOUN
ijassa-499	174	4	using	use	VERB
ijassa-499	174	5	fuzzy	fuzzy	ADJ
ijassa-499	174	6	decision	decision	NOUN
ijassa-499	174	7	functions	function	NOUN
ijassa-499	174	8	,	,	PUNCT
ijassa-499	174	9	ieee	ieee	NOUN
ijassa-499	174	10	transactions	transaction	NOUN
ijassa-499	174	11	on	on	ADP
ijassa-499	174	12	systems	system	NOUN
ijassa-499	174	13	,	,	PUNCT
ijassa-499	174	14	man	man	NOUN
ijassa-499	174	15	,	,	PUNCT
ijassa-499	174	16	and	and	CCONJ
ijassa-499	174	17	cybernetics	cybernetic	NOUN
ijassa-499	174	18	,	,	PUNCT
ijassa-499	174	19	part	part	NOUN
ijassa-499	174	20	b	b	PROPN
ijassa-499	174	21	(	(	PUNCT
ijassa-499	174	22	cybernetics	cybernetic	NOUN
ijassa-499	174	23	)	)	PUNCT
ijassa-499	174	24	,	,	PUNCT
ijassa-499	174	25	31	31	NUM
ijassa-499	174	26	(	(	PUNCT
ijassa-499	174	27	1	1	NUM
ijassa-499	174	28	)	)	PUNCT
ijassa-499	174	29	,	,	PUNCT
ijassa-499	174	30	54–65	54–65	NUM
ijassa-499	174	31	.	.	PUNCT
ijassa-499	175	1	6	6	NUM
ijassa-499	175	2	.	.	X
ijassa-499	176	1	medvedev	medvedev	PROPN
ijassa-499	176	2	a.v	a.v	PROPN
ijassa-499	176	3	.	.	PROPN
ijassa-499	176	4	,	,	PUNCT
ijassa-499	176	5	&	&	CCONJ
ijassa-499	176	6	raskina	raskina	PROPN
ijassa-499	176	7	a.v	a.v	PROPN
ijassa-499	176	8	.	.	PROPN
ijassa-499	176	9	(	(	PUNCT
ijassa-499	176	10	2017	2017	NUM
ijassa-499	176	11	)	)	PUNCT
ijassa-499	176	12	.	.	PUNCT
ijassa-499	177	1	on	on	ADP
ijassa-499	177	2	the	the	DET
ijassa-499	177	3	nonparametric	nonparametric	NOUN
ijassa-499	177	4	identification	identification	NOUN
ijassa-499	177	5	and	and	CCONJ
ijassa-499	177	6	dual	dual	ADJ
ijassa-499	177	7	adaptive	adaptive	ADJ
ijassa-499	177	8	control	control	NOUN
ijassa-499	177	9	of	of	ADP
ijassa-499	177	10	dynamic	dynamic	ADJ
ijassa-499	177	11	processes	process	NOUN
ijassa-499	177	12	,	,	PUNCT
ijassa-499	177	13	journal	journal	NOUN
ijassa-499	177	14	of	of	ADP
ijassa-499	177	15	siberian	siberian	PROPN
ijassa-499	177	16	federal	federal	PROPN
ijassa-499	177	17	university	university	PROPN
ijassa-499	177	18	.	.	PUNCT
ijassa-499	178	1	mathematics	mathematics	PROPN
ijassa-499	178	2	&	&	CCONJ
ijassa-499	178	3	physics	physics	PROPN
ijassa-499	178	4	,	,	PUNCT
ijassa-499	178	5	10	10	NUM
ijassa-499	178	6	(	(	PUNCT
ijassa-499	178	7	1	1	NUM
ijassa-499	178	8	)	)	PUNCT
ijassa-499	178	9	,	,	PUNCT
ijassa-499	178	10	96–107	96–107	NUM
ijassa-499	178	11	.	.	PUNCT
ijassa-499	179	1	copyright	copyright	NOUN
ijassa-499	179	2	c	c	ADP
ijassa-499	179	3	©	©	PROPN
ijassa-499	179	4	2017	2017	NUM
ijassa-499	179	5	assa	assa	NOUN
ijassa-499	179	6	.	.	PUNCT
ijassa-499	180	1	adv	adv	PROPN
ijassa-499	180	2	syst	syst	PROPN
ijassa-499	180	3	sci	sci	PROPN
ijassa-499	180	4	appl	appl	PROPN
ijassa-499	180	5	(	(	PUNCT
ijassa-499	180	6	2017	2017	NUM
ijassa-499	180	7	)	)	PUNCT
ijassa-499	180	8	66	66	NUM
ijassa-499	180	9	e.	e.	PROPN
ijassa-499	180	10	mangalova	mangalova	PROPN
ijassa-499	180	11	7	7	X
ijassa-499	180	12	.	.	X
ijassa-499	180	13	nadaraya	nadaraya	PROPN
ijassa-499	180	14	e.	e.	PROPN
ijassa-499	180	15	a.	a.	PROPN
ijassa-499	180	16	(	(	PUNCT
ijassa-499	180	17	1964	1964	NUM
ijassa-499	180	18	)	)	PUNCT
ijassa-499	180	19	.	.	PUNCT
ijassa-499	181	1	on	on	ADP
ijassa-499	181	2	estimating	estimate	VERB
ijassa-499	181	3	regression	regression	NOUN
ijassa-499	181	4	,	,	PUNCT
ijassa-499	181	5	theory	theory	NOUN
ijassa-499	181	6	of	of	ADP
ijassa-499	181	7	probability	probability	NOUN
ijassa-499	181	8	and	and	CCONJ
ijassa-499	181	9	its	its	PRON
ijassa-499	181	10	applications	application	NOUN
ijassa-499	181	11	,	,	PUNCT
ijassa-499	181	12	9	9	NUM
ijassa-499	181	13	,	,	PUNCT
ijassa-499	181	14	141–142	141–142	NUM
ijassa-499	181	15	.	.	NOUN
ijassa-499	181	16	8	8	NUM
ijassa-499	181	17	.	.	PUNCT
ijassa-499	181	18	breiman	breiman	PROPN
ijassa-499	181	19	l.	l.	PROPN
ijassa-499	181	20	,	,	PUNCT
ijassa-499	181	21	friedman	friedman	PROPN
ijassa-499	181	22	j.	j.	PROPN
ijassa-499	181	23	,	,	PUNCT
ijassa-499	181	24	stone	stone	PROPN
ijassa-499	181	25	c.	c.	PROPN
ijassa-499	181	26	j.	j.	PROPN
ijassa-499	181	27	&	&	CCONJ
ijassa-499	181	28	olshen	olshen	PROPN
ijassa-499	181	29	,	,	PUNCT
ijassa-499	181	30	r.	r.	PROPN
ijassa-499	181	31	a.	a.	PROPN
ijassa-499	181	32	(	(	PUNCT
ijassa-499	181	33	1984	1984	NUM
ijassa-499	181	34	)	)	PUNCT
ijassa-499	181	35	.	.	PUNCT
ijassa-499	182	1	classification	classification	NOUN
ijassa-499	182	2	and	and	CCONJ
ijassa-499	182	3	regression	regression	NOUN
ijassa-499	182	4	trees	tree	NOUN
ijassa-499	182	5	.	.	PUNCT
ijassa-499	183	1	crc	crc	PROPN
ijassa-499	183	2	press	press	PROPN
ijassa-499	183	3	.	.	PUNCT
ijassa-499	184	1	9	9	X
ijassa-499	184	2	.	.	X
ijassa-499	184	3	kunh	kunh	PROPN
ijassa-499	184	4	s.	s.	PROPN
ijassa-499	184	5	&	&	CCONJ
ijassa-499	184	6	guhmann	guhmann	PROPN
ijassa-499	184	7	c.	c.	PROPN
ijassa-499	184	8	(	(	PUNCT
ijassa-499	184	9	2008	2008	NUM
ijassa-499	184	10	)	)	PUNCT
ijassa-499	184	11	modeling	modeling	NOUN
ijassa-499	184	12	and	and	CCONJ
ijassa-499	184	13	control	control	NOUN
ijassa-499	184	14	with	with	ADP
ijassa-499	184	15	local	local	ADJ
ijassa-499	184	16	linearizing	linearize	VERB
ijassa-499	184	17	nadaraya	nadaraya	PROPN
ijassa-499	184	18	watson	watson	PROPN
ijassa-499	184	19	regression	regression	PROPN
ijassa-499	184	20	,	,	PUNCT
ijassa-499	184	21	arxiv:0809.3690	arxiv:0809.3690	NOUN
ijassa-499	184	22	.	.	PUNCT
ijassa-499	185	1	10	10	NUM
ijassa-499	185	2	.	.	PUNCT
ijassa-499	185	3	härdle	härdle	PROPN
ijassa-499	185	4	w.	w.	PROPN
ijassa-499	185	5	(	(	PUNCT
ijassa-499	185	6	1990	1990	NUM
ijassa-499	185	7	)	)	PUNCT
ijassa-499	185	8	applied	apply	VERB
ijassa-499	185	9	nonparametric	nonparametric	NOUN
ijassa-499	185	10	regression	regression	NOUN
ijassa-499	185	11	.	.	PUNCT
ijassa-499	186	1	cambridge	cambridge	PROPN
ijassa-499	186	2	university	university	PROPN
ijassa-499	186	3	press	press	NOUN
ijassa-499	186	4	.	.	PUNCT
ijassa-499	187	1	copyright	copyright	NOUN
ijassa-499	187	2	c	c	ADP
ijassa-499	187	3	©	©	PROPN
ijassa-499	187	4	2017	2017	NUM
ijassa-499	187	5	assa	assa	NOUN
ijassa-499	187	6	.	.	PUNCT
ijassa-499	188	1	adv	adv	PROPN
ijassa-499	188	2	syst	syst	PROPN
ijassa-499	188	3	sci	sci	PROPN
ijassa-499	188	4	appl	appl	PROPN
ijassa-499	188	5	(	(	PUNCT
ijassa-499	188	6	2017	2017	NUM
ijassa-499	188	7	)	)	PUNCT
ijassa-499	188	8	https://arxiv.org/abs/0809.3690	https://arxiv.org/abs/0809.3690	NOUN
ijassa-499	188	9	introduction	introduction	NOUN
ijassa-499	188	10	modeling	modeling	NOUN
ijassa-499	188	11	and	and	CCONJ
ijassa-499	188	12	control	control	NOUN
ijassa-499	188	13	tasks	task	NOUN
ijassa-499	188	14	nadaraya	nadaraya	PROPN
ijassa-499	188	15	-	-	PUNCT
ijassa-499	188	16	watson	watson	PROPN
ijassa-499	188	17	estimator	estimator	NOUN
ijassa-499	188	18	approach	approach	NOUN
ijassa-499	188	19	modeling	model	VERB
ijassa-499	188	20	control	control	NOUN
ijassa-499	188	21	decision	decision	NOUN
ijassa-499	188	22	tree	tree	NOUN
ijassa-499	188	23	approach	approach	NOUN
ijassa-499	188	24	modeling	model	VERB
ijassa-499	188	25	control	control	PROPN
ijassa-499	188	26	controlled	control	VERB
ijassa-499	188	27	inputs	input	NOUN
ijassa-499	188	28	one	one	NUM
ijassa-499	188	29	-	-	PUNCT
ijassa-499	188	30	dimensional	dimensional	ADJ
ijassa-499	188	31	output	output	NOUN
ijassa-499	188	32	.	.	PUNCT
ijassa-499	189	1	controlled	control	VERB
ijassa-499	189	2	and	and	CCONJ
ijassa-499	189	3	observed	observe	VERB
ijassa-499	189	4	uncontrolled	uncontrolled	ADJ
ijassa-499	189	5	inputs	input	NOUN
ijassa-499	189	6	one	one	NUM
ijassa-499	189	7	-	-	PUNCT
ijassa-499	189	8	dimensional	dimensional	ADJ
ijassa-499	189	9	output	output	NOUN
ijassa-499	189	10	.	.	PUNCT
ijassa-499	190	1	multi	multi	ADJ
ijassa-499	190	2	-	-	ADJ
ijassa-499	190	3	dimensional	dimensional	ADJ
ijassa-499	190	4	output	output	NOUN
ijassa-499	190	5	,	,	PUNCT
ijassa-499	190	6	controlled	control	VERB
ijassa-499	190	7	and	and	CCONJ
ijassa-499	190	8	observed	observe	VERB
ijassa-499	190	9	uncontrolled	uncontrolled	ADJ
ijassa-499	190	10	inputs	input	NOUN
ijassa-499	190	11	bibliography	bibliography	NOUN