id	sid	tid	token	lemma	pos
cana-5239	1	1	communications	communication	NOUN
cana-5239	1	2	on	on	ADP
cana-5239	1	3	applied	apply	VERB
cana-5239	1	4	nonlinear	nonlinear	ADJ
cana-5239	1	5	analysis	analysis	NOUN
cana-5239	1	6	issn	issn	NOUN
cana-5239	1	7	:	:	PUNCT
cana-5239	1	8	1074	1074	NUM
cana-5239	1	9	-	-	PUNCT
cana-5239	1	10	133x	133x	NUM
cana-5239	1	11	vol	vol	VERB
cana-5239	1	12	32	32	NUM
cana-5239	1	13	no	no	NOUN
cana-5239	1	14	.	.	PUNCT
cana-5239	2	1	10s	10	NOUN
cana-5239	2	2	(	(	PUNCT
cana-5239	2	3	2025	2025	NUM
cana-5239	2	4	)	)	PUNCT
cana-5239	2	5	1372	1372	NUM
cana-5239	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5239	2	7	enhancing	enhance	VERB
cana-5239	2	8	agricultural	agricultural	ADJ
cana-5239	2	9	price	price	NOUN
cana-5239	2	10	forecasting	forecasting	NOUN
cana-5239	2	11	using	use	VERB
cana-5239	2	12	ensemble	ensemble	ADJ
cana-5239	2	13	models	model	NOUN
cana-5239	2	14	and	and	CCONJ
cana-5239	2	15	optimized	optimize	VERB
cana-5239	2	16	feature	feature	NOUN
cana-5239	2	17	selection	selection	NOUN
cana-5239	2	18	techniques	technique	NOUN
cana-5239	2	19	d.	d.	PROPN
cana-5239	2	20	lawanya1	lawanya1	PROPN
cana-5239	2	21	,	,	PUNCT
cana-5239	2	22	dr	dr	PROPN
cana-5239	2	23	.	.	PROPN
cana-5239	2	24	n.	n.	PROPN
cana-5239	2	25	muthumani2	muthumani2	PROPN
cana-5239	3	1	1research	1research	NUM
cana-5239	3	2	scholar	scholar	NOUN
cana-5239	3	3	,	,	PUNCT
cana-5239	3	4	department	department	NOUN
cana-5239	3	5	of	of	ADP
cana-5239	3	6	computer	computer	NOUN
cana-5239	3	7	science	science	NOUN
cana-5239	3	8	,	,	PUNCT
cana-5239	3	9	ppg	ppg	PROPN
cana-5239	3	10	college	college	PROPN
cana-5239	3	11	of	of	ADP
cana-5239	3	12	arts	art	NOUN
cana-5239	3	13	and	and	CCONJ
cana-5239	3	14	science	science	NOUN
cana-5239	3	15	,	,	PUNCT
cana-5239	3	16	lawanyaagriml@gmail.com	lawanyaagriml@gmail.com	X
cana-5239	3	17	2principal	2principal	NUM
cana-5239	3	18	,	,	PUNCT
cana-5239	3	19	department	department	NOUN
cana-5239	3	20	of	of	ADP
cana-5239	3	21	computer	computer	NOUN
cana-5239	3	22	science	science	PROPN
cana-5239	3	23	ppg	ppg	PROPN
cana-5239	3	24	college	college	PROPN
cana-5239	3	25	of	of	ADP
cana-5239	3	26	arts	art	NOUN
cana-5239	3	27	and	and	CCONJ
cana-5239	3	28	science	science	NOUN
cana-5239	3	29	,	,	PUNCT
cana-5239	3	30	saravanampatty	saravanampatty	NOUN
cana-5239	3	31	,	,	PUNCT
cana-5239	3	32	coimbatore	coimbatore	NOUN
cana-5239	3	33	article	article	NOUN
cana-5239	3	34	history	history	NOUN
cana-5239	3	35	:	:	PUNCT
cana-5239	3	36	received	receive	VERB
cana-5239	3	37	:	:	PUNCT
cana-5239	3	38	12	12	NUM
cana-5239	3	39	-	-	SYM
cana-5239	3	40	01	01	NUM
cana-5239	3	41	-	-	PUNCT
cana-5239	3	42	2025	2025	NUM
cana-5239	3	43	revised	revise	VERB
cana-5239	3	44	:	:	PUNCT
cana-5239	3	45	15	15	NUM
cana-5239	3	46	-	-	NUM
cana-5239	3	47	02	02	NUM
cana-5239	3	48	-	-	PUNCT
cana-5239	3	49	2025	2025	NUM
cana-5239	3	50	accepted	accept	VERB
cana-5239	3	51	:	:	PUNCT
cana-5239	3	52	01	01	NUM
cana-5239	3	53	-	-	SYM
cana-5239	3	54	03	03	NUM
cana-5239	3	55	-	-	PUNCT
cana-5239	3	56	2025	2025	NUM
cana-5239	3	57	abstract	abstract	NOUN
cana-5239	3	58	:	:	PUNCT
cana-5239	3	59	agricultural	agricultural	ADJ
cana-5239	3	60	commodity	commodity	NOUN
cana-5239	3	61	price	price	NOUN
cana-5239	3	62	fluctuations	fluctuation	NOUN
cana-5239	3	63	have	have	AUX
cana-5239	3	64	garnered	garner	VERB
cana-5239	3	65	significant	significant	ADJ
cana-5239	3	66	attention	attention	NOUN
cana-5239	3	67	due	due	ADP
cana-5239	3	68	to	to	ADP
cana-5239	3	69	their	their	PRON
cana-5239	3	70	economic	economic	ADJ
cana-5239	3	71	impact	impact	NOUN
cana-5239	3	72	.	.	PUNCT
cana-5239	4	1	this	this	DET
cana-5239	4	2	research	research	NOUN
cana-5239	4	3	addresses	address	VERB
cana-5239	4	4	the	the	DET
cana-5239	4	5	challenges	challenge	NOUN
cana-5239	4	6	of	of	ADP
cana-5239	4	7	predicting	predict	VERB
cana-5239	4	8	agricultural	agricultural	ADJ
cana-5239	4	9	commodity	commodity	NOUN
cana-5239	4	10	prices	price	NOUN
cana-5239	4	11	by	by	ADP
cana-5239	4	12	leveraging	leverage	VERB
cana-5239	4	13	advanced	advanced	ADJ
cana-5239	4	14	machine	machine	NOUN
cana-5239	4	15	learning	learn	VERB
cana-5239	4	16	techniques	technique	NOUN
cana-5239	4	17	.	.	PUNCT
cana-5239	5	1	unlike	unlike	ADP
cana-5239	5	2	traditional	traditional	ADJ
cana-5239	5	3	statistical	statistical	ADJ
cana-5239	5	4	models	model	NOUN
cana-5239	5	5	,	,	PUNCT
cana-5239	5	6	ensemble	ensemble	ADJ
cana-5239	5	7	-	-	PUNCT
cana-5239	5	8	based	base	VERB
cana-5239	5	9	machine	machine	NOUN
cana-5239	5	10	learning	learn	VERB
cana-5239	5	11	algorithms	algorithm	NOUN
cana-5239	5	12	are	be	AUX
cana-5239	5	13	employed	employ	VERB
cana-5239	5	14	to	to	PART
cana-5239	5	15	better	well	ADV
cana-5239	5	16	capture	capture	VERB
cana-5239	5	17	the	the	DET
cana-5239	5	18	nonlinear	nonlinear	ADJ
cana-5239	5	19	and	and	CCONJ
cana-5239	5	20	complex	complex	ADJ
cana-5239	5	21	dynamics	dynamic	NOUN
cana-5239	5	22	of	of	ADP
cana-5239	5	23	price	price	NOUN
cana-5239	5	24	series	series	NOUN
cana-5239	5	25	.	.	PUNCT
cana-5239	6	1	to	to	PART
cana-5239	6	2	enhance	enhance	VERB
cana-5239	6	3	predictive	predictive	ADJ
cana-5239	6	4	accuracy	accuracy	NOUN
cana-5239	6	5	,	,	PUNCT
cana-5239	6	6	this	this	DET
cana-5239	6	7	study	study	NOUN
cana-5239	6	8	incorporates	incorporate	VERB
cana-5239	6	9	feature	feature	NOUN
cana-5239	6	10	selection	selection	NOUN
cana-5239	6	11	methods	method	NOUN
cana-5239	6	12	,	,	PUNCT
cana-5239	6	13	including	include	VERB
cana-5239	6	14	principal	principal	ADJ
cana-5239	6	15	component	component	NOUN
cana-5239	6	16	analysis	analysis	NOUN
cana-5239	6	17	(	(	PUNCT
cana-5239	6	18	pca	pca	NOUN
cana-5239	6	19	)	)	PUNCT
cana-5239	6	20	,	,	PUNCT
cana-5239	6	21	recursive	recursive	ADJ
cana-5239	6	22	feature	feature	NOUN
cana-5239	6	23	elimination	elimination	NOUN
cana-5239	6	24	(	(	PUNCT
cana-5239	6	25	rfe	rfe	NOUN
cana-5239	6	26	)	)	PUNCT
cana-5239	6	27	,	,	PUNCT
cana-5239	6	28	genetic	genetic	ADJ
cana-5239	6	29	algorithm	algorithm	NOUN
cana-5239	6	30	(	(	PUNCT
cana-5239	6	31	ga	ga	NOUN
cana-5239	6	32	)	)	PUNCT
cana-5239	6	33	,	,	PUNCT
cana-5239	6	34	and	and	CCONJ
cana-5239	6	35	grey	grey	ADJ
cana-5239	6	36	wolf	wolf	PROPN
cana-5239	6	37	optimization	optimization	NOUN
cana-5239	6	38	(	(	PUNCT
cana-5239	6	39	gwo	gwo	PROPN
cana-5239	6	40	)	)	PUNCT
cana-5239	6	41	,	,	PUNCT
cana-5239	6	42	for	for	ADP
cana-5239	6	43	dimensionality	dimensionality	NOUN
cana-5239	6	44	reduction	reduction	NOUN
cana-5239	6	45	and	and	CCONJ
cana-5239	6	46	relevant	relevant	ADJ
cana-5239	6	47	feature	feature	NOUN
cana-5239	6	48	extraction	extraction	NOUN
cana-5239	6	49	.	.	PUNCT
cana-5239	7	1	the	the	DET
cana-5239	7	2	selected	select	VERB
cana-5239	7	3	features	feature	NOUN
cana-5239	7	4	are	be	AUX
cana-5239	7	5	utilized	utilize	VERB
cana-5239	7	6	by	by	ADP
cana-5239	7	7	four	four	NUM
cana-5239	7	8	ensemble	ensemble	ADJ
cana-5239	7	9	classifiers	classifier	NOUN
cana-5239	7	10	:	:	PUNCT
cana-5239	7	11	adaboost	adaboost	ADV
cana-5239	7	12	,	,	PUNCT
cana-5239	7	13	xgboost	xgboost	ADV
cana-5239	7	14	,	,	PUNCT
cana-5239	7	15	catboost	catboost	ADJ
cana-5239	7	16	,	,	PUNCT
cana-5239	7	17	and	and	CCONJ
cana-5239	7	18	gradient	gradient	ADJ
cana-5239	7	19	boosting	boosting	NOUN
cana-5239	7	20	.	.	PUNCT
cana-5239	8	1	the	the	DET
cana-5239	8	2	proposed	propose	VERB
cana-5239	8	3	model	model	NOUN
cana-5239	8	4	is	be	AUX
cana-5239	8	5	evaluated	evaluate	VERB
cana-5239	8	6	using	use	VERB
cana-5239	8	7	key	key	ADJ
cana-5239	8	8	performance	performance	NOUN
cana-5239	8	9	metrics	metric	NOUN
cana-5239	8	10	such	such	ADJ
cana-5239	8	11	as	as	ADP
cana-5239	8	12	precision	precision	NOUN
cana-5239	8	13	,	,	PUNCT
cana-5239	8	14	recall	recall	NOUN
cana-5239	8	15	,	,	PUNCT
cana-5239	8	16	kappa	kappa	ADJ
cana-5239	8	17	,	,	PUNCT
cana-5239	8	18	root	root	NOUN
cana-5239	8	19	mean	mean	VERB
cana-5239	8	20	square	square	ADJ
cana-5239	8	21	error	error	NOUN
cana-5239	8	22	(	(	PUNCT
cana-5239	8	23	rmse	rmse	NOUN
cana-5239	8	24	)	)	PUNCT
cana-5239	8	25	,	,	PUNCT
cana-5239	8	26	and	and	CCONJ
cana-5239	8	27	accuracy	accuracy	NOUN
cana-5239	8	28	.	.	PUNCT
cana-5239	9	1	experimental	experimental	ADJ
cana-5239	9	2	results	result	NOUN
cana-5239	9	3	demonstrate	demonstrate	VERB
cana-5239	9	4	that	that	SCONJ
cana-5239	9	5	the	the	DET
cana-5239	9	6	proposed	propose	VERB
cana-5239	9	7	methodology	methodology	NOUN
cana-5239	9	8	significantly	significantly	ADV
cana-5239	9	9	improves	improve	VERB
cana-5239	9	10	forecasting	forecasting	NOUN
cana-5239	9	11	performance	performance	NOUN
cana-5239	9	12	,	,	PUNCT
cana-5239	9	13	providing	provide	VERB
cana-5239	9	14	a	a	DET
cana-5239	9	15	robust	robust	ADJ
cana-5239	9	16	alternative	alternative	NOUN
cana-5239	9	17	to	to	ADP
cana-5239	9	18	traditional	traditional	ADJ
cana-5239	9	19	approaches	approach	NOUN
cana-5239	9	20	.	.	PUNCT
cana-5239	10	1	keywords	keyword	NOUN
cana-5239	10	2	:	:	PUNCT
cana-5239	10	3	machine	machine	NOUN
cana-5239	10	4	learning	learning	NOUN
cana-5239	10	5	,	,	PUNCT
cana-5239	10	6	ensemble	ensemble	ADJ
cana-5239	10	7	learning	learning	NOUN
cana-5239	10	8	,	,	PUNCT
cana-5239	10	9	agriculture	agriculture	NOUN
cana-5239	10	10	commodity	commodity	NOUN
cana-5239	10	11	,	,	PUNCT
cana-5239	10	12	classification	classification	NOUN
cana-5239	10	13	,	,	PUNCT
cana-5239	10	14	price	price	NOUN
cana-5239	10	15	forecasting	forecasting	NOUN
cana-5239	10	16	.	.	PUNCT
cana-5239	11	1	1	1	X
cana-5239	11	2	.	.	X
cana-5239	11	3	introduction	introduction	NOUN
cana-5239	11	4	agricultural	agricultural	ADJ
cana-5239	11	5	commodities	commodity	NOUN
cana-5239	11	6	play	play	VERB
cana-5239	11	7	a	a	DET
cana-5239	11	8	vital	vital	ADJ
cana-5239	11	9	role	role	NOUN
cana-5239	11	10	in	in	ADP
cana-5239	11	11	both	both	CCONJ
cana-5239	11	12	local	local	ADJ
cana-5239	11	13	and	and	CCONJ
cana-5239	11	14	global	global	ADJ
cana-5239	11	15	economies	economy	NOUN
cana-5239	11	16	,	,	PUNCT
cana-5239	11	17	influencing	influence	VERB
cana-5239	11	18	food	food	NOUN
cana-5239	11	19	security	security	NOUN
cana-5239	11	20	and	and	CCONJ
cana-5239	11	21	international	international	ADJ
cana-5239	11	22	trade	trade	NOUN
cana-5239	11	23	[	[	X
cana-5239	11	24	1	1	NUM
cana-5239	11	25	-	-	SYM
cana-5239	11	26	3	3	NUM
cana-5239	11	27	]	]	PUNCT
cana-5239	11	28	.	.	PUNCT
cana-5239	12	1	accurate	accurate	ADJ
cana-5239	12	2	price	price	NOUN
cana-5239	12	3	prediction	prediction	NOUN
cana-5239	12	4	is	be	AUX
cana-5239	12	5	essential	essential	ADJ
cana-5239	12	6	for	for	ADP
cana-5239	12	7	stabilizing	stabilize	VERB
cana-5239	12	8	farmer	farmer	NOUN
cana-5239	12	9	incomes	income	NOUN
cana-5239	12	10	,	,	PUNCT
cana-5239	12	11	mitigating	mitigate	VERB
cana-5239	12	12	market	market	NOUN
cana-5239	12	13	risks	risk	NOUN
cana-5239	12	14	,	,	PUNCT
cana-5239	12	15	and	and	CCONJ
cana-5239	12	16	supporting	support	VERB
cana-5239	12	17	informed	informed	ADJ
cana-5239	12	18	policy	policy	NOUN
cana-5239	12	19	decisions	decision	NOUN
cana-5239	12	20	to	to	PART
cana-5239	12	21	manage	manage	VERB
cana-5239	12	22	food	food	NOUN
cana-5239	12	23	supply	supply	NOUN
cana-5239	12	24	chains	chain	NOUN
cana-5239	12	25	and	and	CCONJ
cana-5239	12	26	reduce	reduce	VERB
cana-5239	12	27	market	market	NOUN
cana-5239	12	28	volatility	volatility	NOUN
cana-5239	12	29	[	[	X
cana-5239	12	30	4	4	NUM
cana-5239	12	31	,	,	PUNCT
cana-5239	12	32	5	5	NUM
cana-5239	12	33	]	]	PUNCT
cana-5239	12	34	.	.	PUNCT
cana-5239	13	1	however	however	ADV
cana-5239	13	2	,	,	PUNCT
cana-5239	13	3	agricultural	agricultural	ADJ
cana-5239	13	4	prices	price	NOUN
cana-5239	13	5	are	be	AUX
cana-5239	13	6	inherently	inherently	ADV
cana-5239	13	7	volatile	volatile	ADJ
cana-5239	13	8	,	,	PUNCT
cana-5239	13	9	driven	drive	VERB
cana-5239	13	10	by	by	ADP
cana-5239	13	11	unpredictable	unpredictable	ADJ
cana-5239	13	12	factors	factor	NOUN
cana-5239	13	13	such	such	ADJ
cana-5239	13	14	as	as	ADP
cana-5239	13	15	climate	climate	NOUN
cana-5239	13	16	conditions	condition	NOUN
cana-5239	13	17	,	,	PUNCT
cana-5239	13	18	seasonal	seasonal	ADJ
cana-5239	13	19	variations	variation	NOUN
cana-5239	13	20	,	,	PUNCT
cana-5239	13	21	and	and	CCONJ
cana-5239	13	22	macroeconomic	macroeconomic	ADJ
cana-5239	13	23	trends	trend	NOUN
cana-5239	13	24	,	,	PUNCT
cana-5239	13	25	making	make	VERB
cana-5239	13	26	forecasting	forecast	VERB
cana-5239	13	27	a	a	DET
cana-5239	13	28	significant	significant	ADJ
cana-5239	13	29	challenge	challenge	NOUN
cana-5239	13	30	[	[	X
cana-5239	13	31	6	6	NUM
cana-5239	13	32	]	]	PUNCT
cana-5239	13	33	.	.	PUNCT
cana-5239	14	1	traditional	traditional	ADJ
cana-5239	14	2	forecasting	forecasting	NOUN
cana-5239	14	3	methods	method	NOUN
cana-5239	14	4	,	,	PUNCT
cana-5239	14	5	such	such	ADJ
cana-5239	14	6	as	as	ADP
cana-5239	14	7	econometric	econometric	ADJ
cana-5239	14	8	models	model	NOUN
cana-5239	14	9	and	and	CCONJ
cana-5239	14	10	regression	regression	NOUN
cana-5239	14	11	techniques	technique	NOUN
cana-5239	14	12	,	,	PUNCT
cana-5239	14	13	have	have	AUX
cana-5239	14	14	struggled	struggle	VERB
cana-5239	14	15	to	to	PART
cana-5239	14	16	address	address	VERB
cana-5239	14	17	these	these	DET
cana-5239	14	18	complexities	complexity	NOUN
cana-5239	14	19	.	.	PUNCT
cana-5239	15	1	these	these	DET
cana-5239	15	2	approaches	approach	NOUN
cana-5239	15	3	often	often	ADV
cana-5239	15	4	fail	fail	VERB
cana-5239	15	5	to	to	PART
cana-5239	15	6	process	process	VERB
cana-5239	15	7	high	high	ADV
cana-5239	15	8	-	-	PUNCT
cana-5239	15	9	dimensional	dimensional	ADJ
cana-5239	15	10	,	,	PUNCT
cana-5239	15	11	nonlinear	nonlinear	ADJ
cana-5239	15	12	data	datum	NOUN
cana-5239	15	13	and	and	CCONJ
cana-5239	15	14	capture	capture	VERB
cana-5239	15	15	the	the	DET
cana-5239	15	16	intricate	intricate	ADJ
cana-5239	15	17	patterns	pattern	NOUN
cana-5239	15	18	within	within	ADP
cana-5239	15	19	the	the	DET
cana-5239	15	20	agricultural	agricultural	ADJ
cana-5239	15	21	sector	sector	NOUN
cana-5239	16	1	[	[	X
cana-5239	16	2	7	7	NUM
cana-5239	16	3	-	-	SYM
cana-5239	16	4	9	9	NUM
cana-5239	16	5	]	]	PUNCT
cana-5239	16	6	.	.	PUNCT
cana-5239	17	1	in	in	ADP
cana-5239	17	2	response	response	NOUN
cana-5239	17	3	,	,	PUNCT
cana-5239	17	4	machine	machine	NOUN
cana-5239	17	5	learning	learn	VERB
cana-5239	17	6	techniques	technique	NOUN
cana-5239	17	7	,	,	PUNCT
cana-5239	17	8	particularly	particularly	ADV
cana-5239	17	9	ensemble	ensemble	ADJ
cana-5239	17	10	learning	learning	NOUN
cana-5239	17	11	,	,	PUNCT
cana-5239	17	12	have	have	AUX
cana-5239	17	13	gained	gain	VERB
cana-5239	17	14	traction	traction	NOUN
cana-5239	17	15	due	due	ADP
cana-5239	17	16	to	to	ADP
cana-5239	17	17	their	their	PRON
cana-5239	17	18	ability	ability	NOUN
cana-5239	17	19	to	to	PART
cana-5239	17	20	enhance	enhance	VERB
cana-5239	17	21	prediction	prediction	NOUN
cana-5239	17	22	accuracy	accuracy	NOUN
cana-5239	17	23	and	and	CCONJ
cana-5239	17	24	generalization	generalization	NOUN
cana-5239	17	25	by	by	ADP
cana-5239	17	26	leveraging	leverage	VERB
cana-5239	17	27	multiple	multiple	ADJ
cana-5239	17	28	algorithms	algorithm	NOUN
cana-5239	17	29	[	[	X
cana-5239	17	30	10	10	NUM
cana-5239	17	31	,	,	PUNCT
cana-5239	17	32	11	11	NUM
cana-5239	17	33	]	]	PUNCT
cana-5239	17	34	.	.	PUNCT
cana-5239	18	1	this	this	DET
cana-5239	18	2	study	study	NOUN
cana-5239	18	3	proposes	propose	VERB
cana-5239	18	4	an	an	DET
cana-5239	18	5	advanced	advanced	ADJ
cana-5239	18	6	approach	approach	NOUN
cana-5239	18	7	that	that	PRON
cana-5239	18	8	integrates	integrate	VERB
cana-5239	18	9	feature	feature	NOUN
cana-5239	18	10	selection	selection	NOUN
cana-5239	18	11	techniques	technique	NOUN
cana-5239	18	12	with	with	ADP
cana-5239	18	13	ensemble	ensemble	ADJ
cana-5239	18	14	learning	learning	NOUN
cana-5239	18	15	to	to	PART
cana-5239	18	16	improve	improve	VERB
cana-5239	18	17	agricultural	agricultural	ADJ
cana-5239	18	18	commodity	commodity	NOUN
cana-5239	18	19	price	price	NOUN
cana-5239	18	20	predictions	prediction	NOUN
cana-5239	18	21	.	.	PUNCT
cana-5239	19	1	feature	feature	NOUN
cana-5239	19	2	selection	selection	NOUN
cana-5239	19	3	methods	method	NOUN
cana-5239	19	4	—	—	PUNCT
cana-5239	19	5	including	include	VERB
cana-5239	19	6	principal	principal	ADJ
cana-5239	19	7	component	component	NOUN
cana-5239	19	8	analysis	analysis	NOUN
cana-5239	19	9	(	(	PUNCT
cana-5239	19	10	pca	pca	NOUN
cana-5239	19	11	)	)	PUNCT
cana-5239	19	12	,	,	PUNCT
cana-5239	19	13	recursive	recursive	ADJ
cana-5239	19	14	feature	feature	NOUN
cana-5239	19	15	elimination	elimination	NOUN
cana-5239	19	16	(	(	PUNCT
cana-5239	19	17	rfe	rfe	NOUN
cana-5239	19	18	)	)	PUNCT
cana-5239	19	19	,	,	PUNCT
cana-5239	19	20	genetic	genetic	ADJ
cana-5239	19	21	algorithm	algorithm	NOUN
cana-5239	19	22	communications	communication	NOUN
cana-5239	19	23	on	on	ADP
cana-5239	19	24	applied	apply	VERB
cana-5239	19	25	nonlinear	nonlinear	ADJ
cana-5239	19	26	analysis	analysis	NOUN
cana-5239	19	27	issn	issn	NOUN
cana-5239	19	28	:	:	PUNCT
cana-5239	19	29	1074	1074	NUM
cana-5239	19	30	-	-	PUNCT
cana-5239	19	31	133x	133x	NUM
cana-5239	19	32	vol	vol	VERB
cana-5239	19	33	32	32	NUM
cana-5239	19	34	no	no	NOUN
cana-5239	19	35	.	.	PUNCT
cana-5239	20	1	10s	10	NOUN
cana-5239	20	2	(	(	PUNCT
cana-5239	20	3	2025	2025	NUM
cana-5239	20	4	)	)	PUNCT
cana-5239	20	5	1373	1373	NUM
cana-5239	20	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5239	20	7	(	(	PUNCT
cana-5239	20	8	ga	ga	PROPN
cana-5239	20	9	)	)	PUNCT
cana-5239	20	10	,	,	PUNCT
cana-5239	20	11	and	and	CCONJ
cana-5239	20	12	grey	grey	ADJ
cana-5239	20	13	wolf	wolf	PROPN
cana-5239	20	14	optimization	optimization	NOUN
cana-5239	20	15	(	(	PUNCT
cana-5239	20	16	gwo)—are	gwo)—are	NOUN
cana-5239	20	17	utilized	utilize	VERB
cana-5239	20	18	to	to	PART
cana-5239	20	19	extract	extract	VERB
cana-5239	20	20	the	the	DET
cana-5239	20	21	most	most	ADV
cana-5239	20	22	relevant	relevant	ADJ
cana-5239	20	23	features	feature	NOUN
cana-5239	20	24	,	,	PUNCT
cana-5239	20	25	reducing	reduce	VERB
cana-5239	20	26	noise	noise	NOUN
cana-5239	20	27	and	and	CCONJ
cana-5239	20	28	computational	computational	ADJ
cana-5239	20	29	complexity	complexity	NOUN
cana-5239	20	30	while	while	SCONJ
cana-5239	20	31	enhancing	enhance	VERB
cana-5239	20	32	model	model	NOUN
cana-5239	20	33	performance	performance	NOUN
cana-5239	20	34	[	[	X
cana-5239	20	35	12	12	NUM
cana-5239	20	36	-	-	SYM
cana-5239	20	37	17	17	NUM
cana-5239	20	38	]	]	PUNCT
cana-5239	20	39	.	.	PUNCT
cana-5239	21	1	to	to	PART
cana-5239	21	2	build	build	VERB
cana-5239	21	3	a	a	DET
cana-5239	21	4	robust	robust	ADJ
cana-5239	21	5	predictive	predictive	ADJ
cana-5239	21	6	framework	framework	NOUN
cana-5239	21	7	,	,	PUNCT
cana-5239	21	8	four	four	NUM
cana-5239	21	9	ensemble	ensemble	ADJ
cana-5239	21	10	-	-	PUNCT
cana-5239	21	11	based	base	VERB
cana-5239	21	12	classifiers	classifier	NOUN
cana-5239	21	13	—	—	PUNCT
cana-5239	21	14	adaboost	adaboost	ADV
cana-5239	21	15	,	,	PUNCT
cana-5239	21	16	xgboost	xgboost	ADV
cana-5239	21	17	,	,	PUNCT
cana-5239	21	18	catboost	catboost	ADJ
cana-5239	21	19	,	,	PUNCT
cana-5239	21	20	and	and	CCONJ
cana-5239	21	21	gradient	gradient	ADJ
cana-5239	21	22	boosting	boosting	NOUN
cana-5239	21	23	—	—	PUNCT
cana-5239	21	24	are	be	AUX
cana-5239	21	25	employed	employ	VERB
cana-5239	21	26	.	.	PUNCT
cana-5239	22	1	these	these	DET
cana-5239	22	2	classifiers	classifier	NOUN
cana-5239	22	3	,	,	PUNCT
cana-5239	22	4	known	know	VERB
cana-5239	22	5	for	for	ADP
cana-5239	22	6	their	their	PRON
cana-5239	22	7	ability	ability	NOUN
cana-5239	22	8	to	to	PART
cana-5239	22	9	transform	transform	VERB
cana-5239	22	10	weak	weak	ADJ
cana-5239	22	11	learners	learner	NOUN
cana-5239	22	12	into	into	ADP
cana-5239	22	13	strong	strong	ADJ
cana-5239	22	14	predictors	predictor	NOUN
cana-5239	22	15	,	,	PUNCT
cana-5239	22	16	are	be	AUX
cana-5239	22	17	evaluated	evaluate	VERB
cana-5239	22	18	using	use	VERB
cana-5239	22	19	key	key	ADJ
cana-5239	22	20	performance	performance	NOUN
cana-5239	22	21	metrics	metric	NOUN
cana-5239	22	22	such	such	ADJ
cana-5239	22	23	as	as	ADP
cana-5239	22	24	precision	precision	NOUN
cana-5239	22	25	,	,	PUNCT
cana-5239	22	26	recall	recall	NOUN
cana-5239	22	27	,	,	PUNCT
cana-5239	22	28	accuracy	accuracy	NOUN
cana-5239	22	29	,	,	PUNCT
cana-5239	22	30	and	and	CCONJ
cana-5239	22	31	root	root	NOUN
cana-5239	22	32	mean	mean	VERB
cana-5239	22	33	square	square	ADJ
cana-5239	22	34	error	error	NOUN
cana-5239	22	35	(	(	PUNCT
cana-5239	22	36	rmse	rmse	NOUN
cana-5239	22	37	)	)	PUNCT
cana-5239	23	1	[	[	X
cana-5239	23	2	18	18	NUM
cana-5239	23	3	-	-	SYM
cana-5239	23	4	20	20	NUM
cana-5239	23	5	]	]	PUNCT
cana-5239	23	6	.	.	PUNCT
cana-5239	24	1	by	by	ADP
cana-5239	24	2	integrating	integrate	VERB
cana-5239	24	3	advanced	advanced	ADJ
cana-5239	24	4	feature	feature	NOUN
cana-5239	24	5	selection	selection	NOUN
cana-5239	24	6	with	with	ADP
cana-5239	24	7	ensemble	ensemble	ADJ
cana-5239	24	8	learning	learning	NOUN
cana-5239	24	9	,	,	PUNCT
cana-5239	24	10	this	this	DET
cana-5239	24	11	study	study	NOUN
cana-5239	24	12	presents	present	VERB
cana-5239	24	13	a	a	DET
cana-5239	24	14	novel	novel	NOUN
cana-5239	24	15	,	,	PUNCT
cana-5239	24	16	high	high	ADJ
cana-5239	24	17	-	-	PUNCT
cana-5239	24	18	performance	performance	NOUN
cana-5239	24	19	methodology	methodology	NOUN
cana-5239	24	20	for	for	ADP
cana-5239	24	21	agricultural	agricultural	ADJ
cana-5239	24	22	price	price	NOUN
cana-5239	24	23	forecasting	forecasting	NOUN
cana-5239	24	24	.	.	PUNCT
cana-5239	25	1	extensive	extensive	ADJ
cana-5239	25	2	experimentation	experimentation	NOUN
cana-5239	25	3	and	and	CCONJ
cana-5239	25	4	comparative	comparative	ADJ
cana-5239	25	5	analysis	analysis	NOUN
cana-5239	25	6	validate	validate	VERB
cana-5239	25	7	the	the	DET
cana-5239	25	8	effectiveness	effectiveness	NOUN
cana-5239	25	9	of	of	ADP
cana-5239	25	10	this	this	DET
cana-5239	25	11	approach	approach	NOUN
cana-5239	25	12	,	,	PUNCT
cana-5239	25	13	offering	offer	VERB
cana-5239	25	14	valuable	valuable	ADJ
cana-5239	25	15	insights	insight	NOUN
cana-5239	25	16	into	into	ADP
cana-5239	25	17	enhancing	enhance	VERB
cana-5239	25	18	prediction	prediction	NOUN
cana-5239	25	19	accuracy	accuracy	NOUN
cana-5239	25	20	and	and	CCONJ
cana-5239	25	21	developing	develop	VERB
cana-5239	25	22	reliable	reliable	ADJ
cana-5239	25	23	forecasting	forecasting	NOUN
cana-5239	25	24	tools	tool	NOUN
cana-5239	25	25	for	for	ADP
cana-5239	25	26	real	real	ADJ
cana-5239	25	27	-	-	PUNCT
cana-5239	25	28	world	world	NOUN
cana-5239	25	29	agricultural	agricultural	ADJ
cana-5239	25	30	applications	application	NOUN
cana-5239	25	31	.	.	PUNCT
cana-5239	26	1	2	2	X
cana-5239	26	2	.	.	X
cana-5239	26	3	literature	literature	NOUN
cana-5239	26	4	review	review	PROPN
cana-5239	26	5	predicting	predict	VERB
cana-5239	26	6	agricultural	agricultural	ADJ
cana-5239	26	7	commodity	commodity	NOUN
cana-5239	26	8	prices	price	NOUN
cana-5239	26	9	remains	remain	VERB
cana-5239	26	10	a	a	DET
cana-5239	26	11	significant	significant	ADJ
cana-5239	26	12	challenge	challenge	NOUN
cana-5239	26	13	due	due	ADP
cana-5239	26	14	to	to	ADP
cana-5239	26	15	the	the	DET
cana-5239	26	16	complex	complex	ADJ
cana-5239	26	17	and	and	CCONJ
cana-5239	26	18	dynamic	dynamic	ADJ
cana-5239	26	19	nature	nature	NOUN
cana-5239	26	20	of	of	ADP
cana-5239	26	21	the	the	DET
cana-5239	26	22	agricultural	agricultural	ADJ
cana-5239	26	23	sector	sector	NOUN
cana-5239	26	24	.	.	PUNCT
cana-5239	27	1	traditional	traditional	ADJ
cana-5239	27	2	forecasting	forecasting	NOUN
cana-5239	27	3	techniques	technique	NOUN
cana-5239	27	4	,	,	PUNCT
cana-5239	27	5	such	such	ADJ
cana-5239	27	6	as	as	ADP
cana-5239	27	7	econometric	econometric	ADJ
cana-5239	27	8	models	model	NOUN
cana-5239	27	9	,	,	PUNCT
cana-5239	27	10	time	time	NOUN
cana-5239	27	11	-	-	PUNCT
cana-5239	27	12	series	series	NOUN
cana-5239	27	13	analysis	analysis	NOUN
cana-5239	27	14	,	,	PUNCT
cana-5239	27	15	and	and	CCONJ
cana-5239	27	16	statistical	statistical	ADJ
cana-5239	27	17	methods	method	NOUN
cana-5239	27	18	,	,	PUNCT
cana-5239	27	19	have	have	AUX
cana-5239	27	20	been	be	AUX
cana-5239	27	21	widely	widely	ADV
cana-5239	27	22	used	use	VERB
cana-5239	27	23	.	.	PUNCT
cana-5239	28	1	however	however	ADV
cana-5239	28	2	,	,	PUNCT
cana-5239	28	3	these	these	DET
cana-5239	28	4	approaches	approach	NOUN
cana-5239	28	5	often	often	ADV
cana-5239	28	6	struggle	struggle	VERB
cana-5239	28	7	to	to	PART
cana-5239	28	8	account	account	VERB
cana-5239	28	9	for	for	ADP
cana-5239	28	10	the	the	DET
cana-5239	28	11	non	non	ADJ
cana-5239	28	12	-	-	ADJ
cana-5239	28	13	linearity	linearity	ADJ
cana-5239	28	14	and	and	CCONJ
cana-5239	28	15	high	high	ADJ
cana-5239	28	16	dimensionality	dimensionality	NOUN
cana-5239	28	17	inherent	inherent	ADJ
cana-5239	28	18	in	in	ADP
cana-5239	28	19	agricultural	agricultural	ADJ
cana-5239	28	20	datasets	dataset	NOUN
cana-5239	28	21	.	.	PUNCT
cana-5239	29	1	with	with	ADP
cana-5239	29	2	advancements	advancement	NOUN
cana-5239	29	3	in	in	ADP
cana-5239	29	4	machine	machine	NOUN
cana-5239	29	5	learning	learning	NOUN
cana-5239	29	6	(	(	PUNCT
cana-5239	29	7	ml	ml	NOUN
cana-5239	29	8	)	)	PUNCT
cana-5239	29	9	,	,	PUNCT
cana-5239	29	10	researchers	researcher	NOUN
cana-5239	29	11	have	have	AUX
cana-5239	29	12	increasingly	increasingly	ADV
cana-5239	29	13	explored	explore	VERB
cana-5239	29	14	ml	ml	NOUN
cana-5239	29	15	-	-	PUNCT
cana-5239	29	16	based	base	VERB
cana-5239	29	17	methods	method	NOUN
cana-5239	29	18	to	to	PART
cana-5239	29	19	enhance	enhance	VERB
cana-5239	29	20	the	the	DET
cana-5239	29	21	accuracy	accuracy	NOUN
cana-5239	29	22	and	and	CCONJ
cana-5239	29	23	robustness	robustness	NOUN
cana-5239	29	24	of	of	ADP
cana-5239	29	25	commodity	commodity	NOUN
cana-5239	29	26	price	price	NOUN
cana-5239	29	27	predictions	prediction	NOUN
cana-5239	29	28	.	.	PUNCT
cana-5239	30	1	abdullah	abdullah	PROPN
cana-5239	30	2	[	[	X
cana-5239	30	3	21	21	NUM
cana-5239	30	4	]	]	PUNCT
cana-5239	30	5	proposed	propose	VERB
cana-5239	30	6	a	a	DET
cana-5239	30	7	hybrid	hybrid	ADJ
cana-5239	30	8	model	model	NOUN
cana-5239	30	9	for	for	ADP
cana-5239	30	10	forecasting	forecast	VERB
cana-5239	30	11	coconut	coconut	NOUN
cana-5239	30	12	prices	price	NOUN
cana-5239	30	13	,	,	PUNCT
cana-5239	30	14	addressing	address	VERB
cana-5239	30	15	the	the	DET
cana-5239	30	16	challenges	challenge	NOUN
cana-5239	30	17	posed	pose	VERB
cana-5239	30	18	by	by	ADP
cana-5239	30	19	price	price	NOUN
cana-5239	30	20	fluctuations	fluctuation	NOUN
cana-5239	30	21	.	.	PUNCT
cana-5239	31	1	the	the	DET
cana-5239	31	2	model	model	NOUN
cana-5239	31	3	integrates	integrate	VERB
cana-5239	31	4	arima	arima	PROPN
cana-5239	31	5	and	and	CCONJ
cana-5239	31	6	ann	ann	PROPN
cana-5239	31	7	techniques	technique	NOUN
cana-5239	31	8	to	to	PART
cana-5239	31	9	leverage	leverage	VERB
cana-5239	31	10	both	both	PRON
cana-5239	31	11	linear	linear	ADJ
cana-5239	31	12	and	and	CCONJ
cana-5239	31	13	nonlinear	nonlinear	ADJ
cana-5239	31	14	modeling	modeling	ADJ
cana-5239	31	15	capabilities	capability	NOUN
cana-5239	31	16	.	.	PUNCT
cana-5239	32	1	an	an	DET
cana-5239	32	2	experimental	experimental	ADJ
cana-5239	32	3	study	study	NOUN
cana-5239	32	4	demonstrated	demonstrate	VERB
cana-5239	32	5	that	that	SCONJ
cana-5239	32	6	combining	combine	VERB
cana-5239	32	7	arima	arima	PROPN
cana-5239	32	8	and	and	CCONJ
cana-5239	32	9	ann	ann	PROPN
cana-5239	32	10	improves	improve	VERB
cana-5239	32	11	forecasting	forecasting	NOUN
cana-5239	32	12	accuracy	accuracy	NOUN
cana-5239	32	13	and	and	CCONJ
cana-5239	32	14	aids	aid	NOUN
cana-5239	32	15	in	in	ADP
cana-5239	32	16	identifying	identify	VERB
cana-5239	32	17	trends	trend	NOUN
cana-5239	32	18	in	in	ADP
cana-5239	32	19	coconut	coconut	NOUN
cana-5239	32	20	price	price	NOUN
cana-5239	32	21	data	datum	NOUN
cana-5239	32	22	.	.	PUNCT
cana-5239	33	1	mohanty	mohanty	PROPN
cana-5239	33	2	et	et	PROPN
cana-5239	33	3	al	al	PROPN
cana-5239	33	4	.	.	PUNCT
cana-5239	34	1	[	[	X
cana-5239	34	2	22	22	NUM
cana-5239	34	3	]	]	PUNCT
cana-5239	34	4	introduced	introduce	VERB
cana-5239	34	5	a	a	DET
cana-5239	34	6	machine	machine	NOUN
cana-5239	34	7	learning	learning	NOUN
cana-5239	34	8	-	-	PUNCT
cana-5239	34	9	based	base	VERB
cana-5239	34	10	framework	framework	NOUN
cana-5239	34	11	for	for	ADP
cana-5239	34	12	crop	crop	NOUN
cana-5239	34	13	price	price	NOUN
cana-5239	34	14	prediction	prediction	NOUN
cana-5239	34	15	,	,	PUNCT
cana-5239	34	16	helping	help	VERB
cana-5239	34	17	farmers	farmer	NOUN
cana-5239	34	18	estimate	estimate	VERB
cana-5239	34	19	profit	profit	NOUN
cana-5239	34	20	and	and	CCONJ
cana-5239	34	21	loss	loss	NOUN
cana-5239	34	22	in	in	ADP
cana-5239	34	23	advance	advance	NOUN
cana-5239	34	24	.	.	PUNCT
cana-5239	35	1	the	the	DET
cana-5239	35	2	framework	framework	NOUN
cana-5239	35	3	consists	consist	VERB
cana-5239	35	4	of	of	ADP
cana-5239	35	5	four	four	NUM
cana-5239	35	6	key	key	ADJ
cana-5239	35	7	components	component	NOUN
cana-5239	35	8	:	:	PUNCT
cana-5239	35	9	crop	crop	NOUN
cana-5239	35	10	yield	yield	NOUN
cana-5239	35	11	prediction	prediction	NOUN
cana-5239	35	12	,	,	PUNCT
cana-5239	35	13	supply	supply	NOUN
cana-5239	35	14	-	-	PUNCT
cana-5239	35	15	demand	demand	NOUN
cana-5239	35	16	estimation	estimation	NOUN
cana-5239	35	17	,	,	PUNCT
cana-5239	35	18	and	and	CCONJ
cana-5239	35	19	price	price	NOUN
cana-5239	35	20	forecasting	forecasting	NOUN
cana-5239	35	21	.	.	PUNCT
cana-5239	36	1	various	various	ADJ
cana-5239	36	2	methods	method	NOUN
cana-5239	36	3	,	,	PUNCT
cana-5239	36	4	including	include	VERB
cana-5239	36	5	machine	machine	NOUN
cana-5239	36	6	learning	learning	NOUN
cana-5239	36	7	,	,	PUNCT
cana-5239	36	8	statistical	statistical	ADJ
cana-5239	36	9	approaches	approach	NOUN
cana-5239	36	10	,	,	PUNCT
cana-5239	36	11	and	and	CCONJ
cana-5239	36	12	time	time	NOUN
cana-5239	36	13	series	series	NOUN
cana-5239	36	14	models	model	NOUN
cana-5239	36	15	,	,	PUNCT
cana-5239	36	16	were	be	AUX
cana-5239	36	17	applied	apply	VERB
cana-5239	36	18	to	to	PART
cana-5239	36	19	predict	predict	VERB
cana-5239	36	20	prices	price	NOUN
cana-5239	36	21	based	base	VERB
cana-5239	36	22	on	on	ADP
cana-5239	36	23	supply	supply	NOUN
cana-5239	36	24	,	,	PUNCT
cana-5239	36	25	demand	demand	NOUN
cana-5239	36	26	,	,	PUNCT
cana-5239	36	27	and	and	CCONJ
cana-5239	36	28	time	time	NOUN
cana-5239	36	29	trends	trend	NOUN
cana-5239	36	30	.	.	PUNCT
cana-5239	37	1	a	a	DET
cana-5239	37	2	comparative	comparative	ADJ
cana-5239	37	3	analysis	analysis	NOUN
cana-5239	37	4	identified	identify	VERB
cana-5239	37	5	the	the	DET
cana-5239	37	6	decision	decision	NOUN
cana-5239	37	7	tree	tree	NOUN
cana-5239	37	8	regressor	regressor	NOUN
cana-5239	37	9	as	as	ADP
cana-5239	37	10	the	the	DET
cana-5239	37	11	most	most	ADV
cana-5239	37	12	effective	effective	ADJ
cana-5239	37	13	model	model	NOUN
cana-5239	37	14	,	,	PUNCT
cana-5239	37	15	achieving	achieve	VERB
cana-5239	37	16	the	the	DET
cana-5239	37	17	lowest	low	ADJ
cana-5239	37	18	root	root	NOUN
cana-5239	37	19	-	-	PUNCT
cana-5239	37	20	mean	mean	ADJ
cana-5239	37	21	-	-	PUNCT
cana-5239	37	22	square	square	NOUN
cana-5239	37	23	error	error	NOUN
cana-5239	37	24	(	(	PUNCT
cana-5239	37	25	rmse	rmse	NOUN
cana-5239	37	26	)	)	PUNCT
cana-5239	37	27	.	.	PUNCT
cana-5239	38	1	avinash	avinash	PROPN
cana-5239	38	2	et	et	PROPN
cana-5239	38	3	al	al	PROPN
cana-5239	38	4	.	.	PUNCT
cana-5239	39	1	[	[	X
cana-5239	39	2	23	23	NUM
cana-5239	39	3	]	]	PUNCT
cana-5239	39	4	developed	develop	VERB
cana-5239	39	5	a	a	DET
cana-5239	39	6	hidden	hide	VERB
cana-5239	39	7	markov	markov	NOUN
cana-5239	39	8	model	model	NOUN
cana-5239	39	9	(	(	PUNCT
cana-5239	39	10	hmm)-guided	hmm)-guided	ADJ
cana-5239	39	11	deep	deep	ADJ
cana-5239	39	12	learning	learning	NOUN
cana-5239	39	13	approach	approach	NOUN
cana-5239	39	14	for	for	ADP
cana-5239	39	15	forecasting	forecast	VERB
cana-5239	39	16	nonlinear	nonlinear	ADJ
cana-5239	39	17	and	and	CCONJ
cana-5239	39	18	nonstationary	nonstationary	ADJ
cana-5239	39	19	agricultural	agricultural	ADJ
cana-5239	39	20	commodity	commodity	NOUN
cana-5239	39	21	price	price	NOUN
cana-5239	39	22	data	datum	NOUN
cana-5239	39	23	.	.	PUNCT
cana-5239	40	1	by	by	ADP
cana-5239	40	2	incorporating	incorporate	VERB
cana-5239	40	3	technical	technical	ADJ
cana-5239	40	4	indicators	indicator	NOUN
cana-5239	40	5	,	,	PUNCT
cana-5239	40	6	this	this	DET
cana-5239	40	7	approach	approach	NOUN
cana-5239	40	8	enhances	enhance	VERB
cana-5239	40	9	forecasting	forecasting	NOUN
cana-5239	40	10	precision	precision	NOUN
cana-5239	40	11	,	,	PUNCT
cana-5239	40	12	benefiting	benefit	VERB
cana-5239	40	13	stakeholders	stakeholder	NOUN
cana-5239	40	14	such	such	ADJ
cana-5239	40	15	as	as	ADP
cana-5239	40	16	farmers	farmer	NOUN
cana-5239	40	17	and	and	CCONJ
cana-5239	40	18	policymakers	policymaker	NOUN
cana-5239	40	19	.	.	PUNCT
cana-5239	41	1	zhang	zhang	PROPN
cana-5239	41	2	and	and	CCONJ
cana-5239	41	3	tang	tang	PROPN
cana-5239	42	1	[	[	X
cana-5239	42	2	24	24	NUM
cana-5239	42	3	]	]	PUNCT
cana-5239	42	4	proposed	propose	VERB
cana-5239	42	5	a	a	DET
cana-5239	42	6	novel	novel	ADJ
cana-5239	42	7	vmd	vmd	NOUN
cana-5239	42	8	-	-	ADJ
cana-5239	42	9	sgmd	sgmd	ADJ
cana-5239	42	10	-	-	PUNCT
cana-5239	42	11	lstm	lstm	NOUN
cana-5239	42	12	model	model	NOUN
cana-5239	42	13	that	that	PRON
cana-5239	42	14	integrates	integrate	VERB
cana-5239	42	15	artificial	artificial	ADJ
cana-5239	42	16	intelligence	intelligence	NOUN
cana-5239	42	17	with	with	ADP
cana-5239	42	18	advanced	advanced	ADJ
cana-5239	42	19	quadratic	quadratic	ADJ
cana-5239	42	20	decomposition	decomposition	NOUN
cana-5239	42	21	techniques	technique	NOUN
cana-5239	42	22	.	.	PUNCT
cana-5239	43	1	initially	initially	ADV
cana-5239	43	2	,	,	PUNCT
cana-5239	43	3	the	the	DET
cana-5239	43	4	futures	future	NOUN
cana-5239	43	5	price	price	NOUN
cana-5239	43	6	data	datum	NOUN
cana-5239	43	7	undergoes	undergo	VERB
cana-5239	43	8	decomposition	decomposition	NOUN
cana-5239	43	9	using	use	VERB
cana-5239	43	10	variational	variational	ADJ
cana-5239	43	11	mode	mode	NOUN
cana-5239	43	12	decomposition	decomposition	NOUN
cana-5239	43	13	(	(	PUNCT
cana-5239	43	14	vmd	vmd	NOUN
cana-5239	43	15	)	)	PUNCT
cana-5239	43	16	and	and	CCONJ
cana-5239	43	17	further	far	ADV
cana-5239	43	18	refinement	refinement	VERB
cana-5239	43	19	through	through	ADP
cana-5239	43	20	sgmd	sgmd	NOUN
cana-5239	43	21	.	.	PUNCT
cana-5239	44	1	the	the	DET
cana-5239	44	2	final	final	ADJ
cana-5239	44	3	predictions	prediction	NOUN
cana-5239	44	4	are	be	AUX
cana-5239	44	5	generated	generate	VERB
cana-5239	44	6	by	by	ADP
cana-5239	44	7	aggregating	aggregate	VERB
cana-5239	44	8	the	the	DET
cana-5239	44	9	expected	expect	VERB
cana-5239	44	10	values	value	NOUN
cana-5239	44	11	from	from	ADP
cana-5239	44	12	different	different	ADJ
cana-5239	44	13	modal	modal	ADJ
cana-5239	44	14	components	component	NOUN
cana-5239	44	15	,	,	PUNCT
cana-5239	44	16	predicted	predict	VERB
cana-5239	44	17	using	use	VERB
cana-5239	44	18	an	an	DET
cana-5239	44	19	lstm	lstm	ADJ
cana-5239	44	20	model	model	NOUN
cana-5239	44	21	.	.	PUNCT
cana-5239	45	1	rana	rana	PROPN
cana-5239	45	2	et	et	PROPN
cana-5239	45	3	al	al	PROPN
cana-5239	45	4	.	.	PUNCT
cana-5239	46	1	[	[	X
cana-5239	46	2	25	25	NUM
cana-5239	46	3	]	]	PUNCT
cana-5239	46	4	explored	explore	VERB
cana-5239	46	5	the	the	DET
cana-5239	46	6	application	application	NOUN
cana-5239	46	7	of	of	ADP
cana-5239	46	8	a	a	DET
cana-5239	46	9	big	big	ADJ
cana-5239	46	10	data	data	NOUN
cana-5239	46	11	framework	framework	NOUN
cana-5239	46	12	for	for	ADP
cana-5239	46	13	agricultural	agricultural	ADJ
cana-5239	46	14	price	price	NOUN
cana-5239	46	15	forecasting	forecasting	NOUN
cana-5239	46	16	in	in	ADP
cana-5239	46	17	pakistan	pakistan	PROPN
cana-5239	46	18	.	.	PUNCT
cana-5239	47	1	using	use	VERB
cana-5239	47	2	a	a	DET
cana-5239	47	3	historical	historical	ADJ
cana-5239	47	4	dataset	dataset	NOUN
cana-5239	47	5	(	(	PUNCT
cana-5239	47	6	2007–2022	2007–2022	NUM
cana-5239	47	7	)	)	PUNCT
cana-5239	47	8	on	on	ADP
cana-5239	47	9	commodity	commodity	NOUN
cana-5239	47	10	prices	price	NOUN
cana-5239	47	11	across	across	ADP
cana-5239	47	12	various	various	ADJ
cana-5239	47	13	cities	city	NOUN
cana-5239	47	14	and	and	CCONJ
cana-5239	47	15	communications	communication	NOUN
cana-5239	47	16	on	on	ADP
cana-5239	47	17	applied	apply	VERB
cana-5239	47	18	nonlinear	nonlinear	ADJ
cana-5239	47	19	analysis	analysis	NOUN
cana-5239	47	20	issn	issn	NOUN
cana-5239	47	21	:	:	PUNCT
cana-5239	47	22	1074	1074	NUM
cana-5239	47	23	-	-	PUNCT
cana-5239	47	24	133x	133x	NUM
cana-5239	47	25	vol	vol	VERB
cana-5239	47	26	32	32	NUM
cana-5239	47	27	no	no	NOUN
cana-5239	47	28	.	.	PUNCT
cana-5239	48	1	10s	10	NOUN
cana-5239	48	2	(	(	PUNCT
cana-5239	48	3	2025	2025	NUM
cana-5239	48	4	)	)	PUNCT
cana-5239	48	5	1374	1374	NUM
cana-5239	48	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5239	48	7	employing	employ	VERB
cana-5239	48	8	apache	apache	NOUN
cana-5239	48	9	spark	spark	NOUN
cana-5239	48	10	for	for	ADP
cana-5239	48	11	data	datum	NOUN
cana-5239	48	12	preprocessing	preprocessing	NOUN
cana-5239	48	13	,	,	PUNCT
cana-5239	48	14	the	the	DET
cana-5239	48	15	study	study	NOUN
cana-5239	48	16	applied	apply	VERB
cana-5239	48	17	arima	arima	NOUN
cana-5239	48	18	,	,	PUNCT
cana-5239	48	19	random	random	ADJ
cana-5239	48	20	forest	forest	NOUN
cana-5239	48	21	,	,	PUNCT
cana-5239	48	22	and	and	CCONJ
cana-5239	48	23	long	long	ADJ
cana-5239	48	24	short	short	ADJ
cana-5239	48	25	-	-	PUNCT
cana-5239	48	26	term	term	NOUN
cana-5239	48	27	memory	memory	NOUN
cana-5239	48	28	(	(	PUNCT
cana-5239	48	29	lstm	lstm	NOUN
cana-5239	48	30	)	)	PUNCT
cana-5239	48	31	models	model	NOUN
cana-5239	48	32	to	to	PART
cana-5239	48	33	forecast	forecast	VERB
cana-5239	48	34	price	price	NOUN
cana-5239	48	35	trends	trend	NOUN
cana-5239	48	36	.	.	PUNCT
cana-5239	49	1	results	result	NOUN
cana-5239	49	2	indicated	indicate	VERB
cana-5239	49	3	that	that	SCONJ
cana-5239	49	4	lstm	lstm	PROPN
cana-5239	49	5	outperformed	outperform	VERB
cana-5239	49	6	arima	arima	PROPN
cana-5239	49	7	and	and	CCONJ
cana-5239	49	8	random	random	ADJ
cana-5239	49	9	forest	forest	NOUN
cana-5239	49	10	,	,	PUNCT
cana-5239	49	11	achieving	achieve	VERB
cana-5239	49	12	an	an	DET
cana-5239	49	13	r²	r²	NOUN
cana-5239	49	14	value	value	NOUN
cana-5239	49	15	of	of	ADP
cana-5239	49	16	0.8	0.8	NUM
cana-5239	49	17	and	and	CCONJ
cana-5239	49	18	the	the	DET
cana-5239	49	19	lowest	low	ADJ
cana-5239	49	20	mean	mean	ADJ
cana-5239	49	21	absolute	absolute	ADJ
cana-5239	49	22	error	error	NOUN
cana-5239	49	23	(	(	PUNCT
cana-5239	49	24	mae	mae	PROPN
cana-5239	49	25	)	)	PUNCT
cana-5239	49	26	of	of	ADP
cana-5239	49	27	125.29	125.29	NUM
cana-5239	49	28	,	,	PUNCT
cana-5239	49	29	demonstrating	demonstrate	VERB
cana-5239	49	30	its	its	PRON
cana-5239	49	31	superior	superior	ADJ
cana-5239	49	32	predictive	predictive	ADJ
cana-5239	49	33	capabilities	capability	NOUN
cana-5239	49	34	.	.	PUNCT
cana-5239	50	1	sun	sun	NOUN
cana-5239	50	2	[	[	X
cana-5239	50	3	26	26	NUM
cana-5239	50	4	]	]	PUNCT
cana-5239	50	5	investigated	investigate	VERB
cana-5239	50	6	garlic	garlic	NOUN
cana-5239	50	7	price	price	NOUN
cana-5239	50	8	forecasting	forecasting	NOUN
cana-5239	50	9	in	in	ADP
cana-5239	50	10	jinxiang	jinxiang	PROPN
cana-5239	50	11	,	,	PUNCT
cana-5239	50	12	china	china	PROPN
cana-5239	50	13	.	.	PUNCT
cana-5239	51	1	the	the	DET
cana-5239	51	2	study	study	NOUN
cana-5239	51	3	first	first	ADV
cana-5239	51	4	extracted	extract	VERB
cana-5239	51	5	features	feature	NOUN
cana-5239	51	6	using	use	VERB
cana-5239	51	7	vmd	vmd	PROPN
cana-5239	51	8	decomposition	decomposition	NOUN
cana-5239	51	9	,	,	PUNCT
cana-5239	51	10	generating	generate	VERB
cana-5239	51	11	a	a	DET
cana-5239	51	12	combined	combine	VERB
cana-5239	51	13	feature	feature	NOUN
cana-5239	51	14	set	set	NOUN
cana-5239	51	15	(	(	PUNCT
cana-5239	51	16	de_vo	de_vo	NOUN
cana-5239	51	17	)	)	PUNCT
cana-5239	51	18	by	by	ADP
cana-5239	51	19	incorporating	incorporate	VERB
cana-5239	51	20	volatility	volatility	NOUN
cana-5239	51	21	indicators	indicator	NOUN
cana-5239	51	22	.	.	PUNCT
cana-5239	52	1	classification	classification	NOUN
cana-5239	52	2	models	model	NOUN
cana-5239	52	3	,	,	PUNCT
cana-5239	52	4	including	include	VERB
cana-5239	52	5	logistic	logistic	ADJ
cana-5239	52	6	regression	regression	NOUN
cana-5239	52	7	,	,	PUNCT
cana-5239	52	8	svm	svm	NOUN
cana-5239	52	9	,	,	PUNCT
cana-5239	52	10	and	and	CCONJ
cana-5239	52	11	xgboost	xgboost	NUM
cana-5239	52	12	,	,	PUNCT
cana-5239	52	13	were	be	AUX
cana-5239	52	14	employed	employ	VERB
cana-5239	52	15	to	to	PART
cana-5239	52	16	predict	predict	VERB
cana-5239	52	17	price	price	NOUN
cana-5239	52	18	trends	trend	NOUN
cana-5239	52	19	.	.	PUNCT
cana-5239	53	1	results	result	NOUN
cana-5239	53	2	showed	show	VERB
cana-5239	53	3	that	that	SCONJ
cana-5239	53	4	feature	feature	NOUN
cana-5239	53	5	-	-	PUNCT
cana-5239	53	6	enhanced	enhance	VERB
cana-5239	53	7	models	model	NOUN
cana-5239	53	8	outperformed	outperform	VERB
cana-5239	53	9	individual	individual	ADJ
cana-5239	53	10	feature	feature	NOUN
cana-5239	53	11	-	-	PUNCT
cana-5239	53	12	based	base	VERB
cana-5239	53	13	predictions	prediction	NOUN
cana-5239	53	14	,	,	PUNCT
cana-5239	53	15	with	with	ADP
cana-5239	53	16	xgboost	xgboost	ADV
cana-5239	53	17	achieving	achieve	VERB
cana-5239	53	18	the	the	DET
cana-5239	53	19	highest	high	ADJ
cana-5239	53	20	accuracy	accuracy	NOUN
cana-5239	53	21	(	(	PUNCT
cana-5239	53	22	72.9	72.9	NUM
cana-5239	53	23	%	%	NOUN
cana-5239	53	24	)	)	PUNCT
cana-5239	53	25	,	,	PUNCT
cana-5239	53	26	followed	follow	VERB
cana-5239	53	27	by	by	ADP
cana-5239	53	28	svm	svm	PROPN
cana-5239	53	29	(	(	PUNCT
cana-5239	53	30	71.4	71.4	NUM
cana-5239	53	31	%	%	NOUN
cana-5239	53	32	)	)	PUNCT
cana-5239	53	33	and	and	CCONJ
cana-5239	53	34	logistic	logistic	ADJ
cana-5239	53	35	regression	regression	NOUN
cana-5239	53	36	(	(	PUNCT
cana-5239	53	37	62.6	62.6	NUM
cana-5239	53	38	%	%	NOUN
cana-5239	53	39	)	)	PUNCT
cana-5239	53	40	.	.	PUNCT
cana-5239	54	1	the	the	DET
cana-5239	54	2	paper	paper	NOUN
cana-5239	54	3	is	be	AUX
cana-5239	54	4	structured	structure	VERB
cana-5239	54	5	as	as	SCONJ
cana-5239	54	6	follows	follow	VERB
cana-5239	54	7	:	:	PUNCT
cana-5239	54	8	section	section	NOUN
cana-5239	54	9	2	2	NUM
cana-5239	54	10	details	detail	NOUN
cana-5239	54	11	the	the	DET
cana-5239	54	12	methodology	methodology	NOUN
cana-5239	54	13	and	and	CCONJ
cana-5239	54	14	framework	framework	NOUN
cana-5239	54	15	design	design	NOUN
cana-5239	54	16	.	.	PUNCT
cana-5239	55	1	section	section	NOUN
cana-5239	55	2	3	3	NUM
cana-5239	55	3	presents	present	VERB
cana-5239	55	4	the	the	DET
cana-5239	55	5	results	result	NOUN
cana-5239	55	6	,	,	PUNCT
cana-5239	55	7	analysis	analysis	NOUN
cana-5239	55	8	,	,	PUNCT
cana-5239	55	9	discussion	discussion	NOUN
cana-5239	55	10	,	,	PUNCT
cana-5239	55	11	and	and	CCONJ
cana-5239	55	12	evaluation	evaluation	NOUN
cana-5239	55	13	methods	method	NOUN
cana-5239	55	14	.	.	PUNCT
cana-5239	56	1	finally	finally	ADV
cana-5239	56	2	,	,	PUNCT
cana-5239	56	3	section	section	NOUN
cana-5239	56	4	4	4	NUM
cana-5239	56	5	summarizes	summarize	NOUN
cana-5239	56	6	the	the	DET
cana-5239	56	7	study	study	NOUN
cana-5239	56	8	’s	’s	PART
cana-5239	56	9	conclusions	conclusion	NOUN
cana-5239	56	10	and	and	CCONJ
cana-5239	56	11	outlines	outline	VERB
cana-5239	56	12	future	future	ADJ
cana-5239	56	13	research	research	NOUN
cana-5239	56	14	directions	direction	NOUN
cana-5239	56	15	.	.	PUNCT
cana-5239	57	1	3	3	X
cana-5239	57	2	.	.	X
cana-5239	57	3	methods	method	NOUN
cana-5239	57	4	the	the	DET
cana-5239	57	5	proposed	propose	VERB
cana-5239	57	6	approach	approach	NOUN
cana-5239	57	7	demonstrates	demonstrate	VERB
cana-5239	57	8	strong	strong	ADJ
cana-5239	57	9	potential	potential	NOUN
cana-5239	57	10	for	for	ADP
cana-5239	57	11	improving	improve	VERB
cana-5239	57	12	the	the	DET
cana-5239	57	13	accuracy	accuracy	NOUN
cana-5239	57	14	of	of	ADP
cana-5239	57	15	agricultural	agricultural	ADJ
cana-5239	57	16	commodity	commodity	NOUN
cana-5239	57	17	price	price	NOUN
cana-5239	57	18	forecasting	forecasting	NOUN
cana-5239	57	19	by	by	ADP
cana-5239	57	20	integrating	integrate	VERB
cana-5239	57	21	various	various	ADJ
cana-5239	57	22	feature	feature	NOUN
cana-5239	57	23	selection	selection	NOUN
cana-5239	57	24	techniques	technique	NOUN
cana-5239	57	25	with	with	ADP
cana-5239	57	26	machine	machine	NOUN
cana-5239	57	27	learning	learning	NOUN
cana-5239	57	28	models	model	NOUN
cana-5239	57	29	.	.	PUNCT
cana-5239	58	1	this	this	DET
cana-5239	58	2	methodology	methodology	NOUN
cana-5239	58	3	has	have	VERB
cana-5239	58	4	significant	significant	ADJ
cana-5239	58	5	implications	implication	NOUN
cana-5239	58	6	for	for	ADP
cana-5239	58	7	stakeholders	stakeholder	NOUN
cana-5239	58	8	such	such	ADJ
cana-5239	58	9	as	as	ADP
cana-5239	58	10	farmers	farmer	NOUN
cana-5239	58	11	and	and	CCONJ
cana-5239	58	12	policymakers	policymaker	NOUN
cana-5239	58	13	,	,	PUNCT
cana-5239	58	14	aiding	aid	VERB
cana-5239	58	15	in	in	ADP
cana-5239	58	16	better	well	ADJ
cana-5239	58	17	decision	decision	NOUN
cana-5239	58	18	-	-	PUNCT
cana-5239	58	19	making	make	VERB
cana-5239	58	20	and	and	CCONJ
cana-5239	58	21	market	market	NOUN
cana-5239	58	22	planning	planning	NOUN
cana-5239	58	23	.	.	PUNCT
cana-5239	59	1	initially	initially	ADV
cana-5239	59	2	,	,	PUNCT
cana-5239	59	3	the	the	DET
cana-5239	59	4	collected	collect	VERB
cana-5239	59	5	data	data	NOUN
cana-5239	59	6	undergoes	undergoe	NOUN
cana-5239	59	7	preprocessing	preprocesse	VERB
cana-5239	59	8	using	use	VERB
cana-5239	59	9	label	label	NOUN
cana-5239	59	10	encoding	encoding	NOUN
cana-5239	59	11	.	.	PUNCT
cana-5239	60	1	subsequently	subsequently	ADV
cana-5239	60	2	,	,	PUNCT
cana-5239	60	3	different	different	ADJ
cana-5239	60	4	feature	feature	NOUN
cana-5239	60	5	selection	selection	NOUN
cana-5239	60	6	algorithms	algorithm	NOUN
cana-5239	60	7	—	—	PUNCT
cana-5239	60	8	including	include	VERB
cana-5239	60	9	principal	principal	ADJ
cana-5239	60	10	component	component	NOUN
cana-5239	60	11	analysis	analysis	NOUN
cana-5239	60	12	(	(	PUNCT
cana-5239	60	13	pca	pca	NOUN
cana-5239	60	14	)	)	PUNCT
cana-5239	60	15	,	,	PUNCT
cana-5239	60	16	recursive	recursive	ADJ
cana-5239	60	17	feature	feature	NOUN
cana-5239	60	18	elimination	elimination	NOUN
cana-5239	60	19	(	(	PUNCT
cana-5239	60	20	rfe	rfe	NOUN
cana-5239	60	21	)	)	PUNCT
cana-5239	60	22	,	,	PUNCT
cana-5239	60	23	and	and	CCONJ
cana-5239	60	24	genetic	genetic	ADJ
cana-5239	60	25	algorithm	algorithm	NOUN
cana-5239	60	26	(	(	PUNCT
cana-5239	60	27	ga)—are	ga)—are	PROPN
cana-5239	60	28	applied	apply	VERB
cana-5239	60	29	to	to	PART
cana-5239	60	30	identify	identify	VERB
cana-5239	60	31	the	the	DET
cana-5239	60	32	most	most	ADV
cana-5239	60	33	relevant	relevant	ADJ
cana-5239	60	34	features	feature	NOUN
cana-5239	60	35	,	,	PUNCT
cana-5239	60	36	thereby	thereby	ADV
cana-5239	60	37	enhancing	enhance	VERB
cana-5239	60	38	classifier	classifier	NOUN
cana-5239	60	39	performance	performance	NOUN
cana-5239	60	40	.	.	PUNCT
cana-5239	61	1	finally	finally	ADV
cana-5239	61	2	,	,	PUNCT
cana-5239	61	3	the	the	DET
cana-5239	61	4	impact	impact	NOUN
cana-5239	61	5	of	of	ADP
cana-5239	61	6	these	these	DET
cana-5239	61	7	three	three	NUM
cana-5239	61	8	feature	feature	NOUN
cana-5239	61	9	selection	selection	NOUN
cana-5239	61	10	techniques	technique	NOUN
cana-5239	61	11	on	on	ADP
cana-5239	61	12	ensemble	ensemble	ADJ
cana-5239	61	13	machine	machine	NOUN
cana-5239	61	14	learning	learn	VERB
cana-5239	61	15	classifiers	classifier	NOUN
cana-5239	61	16	is	be	AUX
cana-5239	61	17	analyzed	analyze	VERB
cana-5239	61	18	and	and	CCONJ
cana-5239	61	19	evaluated	evaluate	VERB
cana-5239	61	20	.	.	PUNCT
cana-5239	62	1	the	the	DET
cana-5239	62	2	overall	overall	ADJ
cana-5239	62	3	architecture	architecture	NOUN
cana-5239	62	4	of	of	ADP
cana-5239	62	5	the	the	DET
cana-5239	62	6	proposed	propose	VERB
cana-5239	62	7	agricultural	agricultural	ADJ
cana-5239	62	8	commodity	commodity	NOUN
cana-5239	62	9	price	price	NOUN
cana-5239	62	10	prediction	prediction	NOUN
cana-5239	62	11	model	model	NOUN
cana-5239	62	12	is	be	AUX
cana-5239	62	13	illustrated	illustrate	VERB
cana-5239	62	14	in	in	ADP
cana-5239	62	15	figure	figure	NOUN
cana-5239	62	16	1	1	NUM
cana-5239	62	17	.	.	SYM
cana-5239	62	18	3.1	3.1	NUM
cana-5239	62	19	data	datum	NOUN
cana-5239	62	20	collection	collection	NOUN
cana-5239	62	21	the	the	DET
cana-5239	62	22	dataset	dataset	NOUN
cana-5239	62	23	used	use	VERB
cana-5239	62	24	in	in	ADP
cana-5239	62	25	this	this	DET
cana-5239	62	26	research	research	NOUN
cana-5239	62	27	consists	consist	VERB
cana-5239	62	28	of	of	ADP
cana-5239	62	29	historical	historical	ADJ
cana-5239	62	30	price	price	NOUN
cana-5239	62	31	data	datum	NOUN
cana-5239	62	32	for	for	ADP
cana-5239	62	33	various	various	ADJ
cana-5239	62	34	agricultural	agricultural	ADJ
cana-5239	62	35	commodities	commodity	NOUN
cana-5239	62	36	,	,	PUNCT
cana-5239	62	37	including	include	VERB
cana-5239	62	38	crop	crop	NOUN
cana-5239	62	39	prices	price	NOUN
cana-5239	62	40	such	such	ADJ
cana-5239	62	41	as	as	ADP
cana-5239	62	42	wheat	wheat	NOUN
cana-5239	62	43	,	,	PUNCT
cana-5239	62	44	rice	rice	NOUN
cana-5239	62	45	,	,	PUNCT
cana-5239	62	46	and	and	CCONJ
cana-5239	62	47	corn	corn	NOUN
cana-5239	62	48	.	.	PUNCT
cana-5239	63	1	the	the	DET
cana-5239	63	2	dataset	dataset	NOUN
cana-5239	63	3	was	be	AUX
cana-5239	63	4	sourced	source	VERB
cana-5239	63	5	from	from	ADP
cana-5239	63	6	publicly	publicly	ADV
cana-5239	63	7	available	available	ADJ
cana-5239	63	8	agricultural	agricultural	ADJ
cana-5239	63	9	databases	database	NOUN
cana-5239	63	10	,	,	PUNCT
cana-5239	63	11	including	include	VERB
cana-5239	63	12	[	[	PUNCT
cana-5239	63	13	specify	specify	VERB
cana-5239	63	14	data	datum	NOUN
cana-5239	63	15	sources	source	NOUN
cana-5239	63	16	]	]	PUNCT
cana-5239	63	17	,	,	PUNCT
cana-5239	63	18	which	which	PRON
cana-5239	63	19	provide	provide	VERB
cana-5239	63	20	daily	daily	ADV
cana-5239	63	21	,	,	PUNCT
cana-5239	63	22	weekly	weekly	ADJ
cana-5239	63	23	,	,	PUNCT
cana-5239	63	24	or	or	CCONJ
cana-5239	63	25	monthly	monthly	ADJ
cana-5239	63	26	price	price	NOUN
cana-5239	63	27	data	datum	NOUN
cana-5239	63	28	along	along	ADV
cana-5239	63	29	with	with	ADP
cana-5239	63	30	associated	associated	ADJ
cana-5239	63	31	features	feature	NOUN
cana-5239	63	32	such	such	ADJ
cana-5239	63	33	as	as	ADP
cana-5239	63	34	weather	weather	NOUN
cana-5239	63	35	conditions	condition	NOUN
cana-5239	63	36	,	,	PUNCT
cana-5239	63	37	market	market	NOUN
cana-5239	63	38	demand	demand	NOUN
cana-5239	63	39	,	,	PUNCT
cana-5239	63	40	supply	supply	NOUN
cana-5239	63	41	chain	chain	NOUN
cana-5239	63	42	data	datum	NOUN
cana-5239	63	43	,	,	PUNCT
cana-5239	63	44	and	and	CCONJ
cana-5239	63	45	macroeconomic	macroeconomic	ADJ
cana-5239	63	46	indicators	indicator	NOUN
cana-5239	63	47	.	.	PUNCT
cana-5239	64	1	3.2	3.2	NUM
cana-5239	64	2	preprocessing	preprocesse	VERB
cana-5239	64	3	the	the	DET
cana-5239	64	4	dataset	dataset	NOUN
cana-5239	64	5	underwent	underwent	NOUN
cana-5239	64	6	various	various	ADJ
cana-5239	64	7	operations	operation	NOUN
cana-5239	64	8	related	relate	VERB
cana-5239	64	9	to	to	ADP
cana-5239	64	10	data	datum	NOUN
cana-5239	64	11	cleaning	cleaning	NOUN
cana-5239	64	12	and	and	CCONJ
cana-5239	64	13	preparation	preparation	NOUN
cana-5239	64	14	,	,	PUNCT
cana-5239	64	15	including	include	VERB
cana-5239	64	16	column	column	NOUN
cana-5239	64	17	renaming	renaming	NOUN
cana-5239	64	18	,	,	PUNCT
cana-5239	64	19	duplicate	duplicate	ADJ
cana-5239	64	20	and	and	CCONJ
cana-5239	64	21	superfluous	superfluous	ADJ
cana-5239	64	22	column	column	NOUN
cana-5239	64	23	removal	removal	NOUN
cana-5239	64	24	,	,	PUNCT
cana-5239	64	25	handling	handle	VERB
cana-5239	64	26	missing	miss	VERB
cana-5239	64	27	values	value	NOUN
cana-5239	64	28	,	,	PUNCT
cana-5239	64	29	forward	forward	ADV
cana-5239	64	30	filling	fill	VERB
cana-5239	64	31	null	null	ADJ
cana-5239	64	32	values	value	NOUN
cana-5239	64	33	with	with	ADP
cana-5239	64	34	the	the	DET
cana-5239	64	35	previous	previous	ADJ
cana-5239	64	36	non	non	ADJ
cana-5239	64	37	-	-	ADJ
cana-5239	64	38	null	null	ADJ
cana-5239	64	39	value	value	NOUN
cana-5239	64	40	,	,	PUNCT
cana-5239	64	41	and	and	CCONJ
cana-5239	64	42	data	datum	NOUN
cana-5239	64	43	type	type	NOUN
cana-5239	64	44	conversion	conversion	NOUN
cana-5239	64	45	.	.	PUNCT
cana-5239	65	1	missing	miss	VERB
cana-5239	65	2	values	value	NOUN
cana-5239	65	3	were	be	AUX
cana-5239	65	4	imputed	impute	VERB
cana-5239	65	5	using	use	VERB
cana-5239	65	6	median	median	ADJ
cana-5239	65	7	imputation	imputation	NOUN
cana-5239	65	8	for	for	ADP
cana-5239	65	9	numerical	numerical	ADJ
cana-5239	65	10	variables	variable	NOUN
cana-5239	65	11	[	[	X
cana-5239	65	12	27	27	NUM
cana-5239	65	13	]	]	PUNCT
cana-5239	65	14	and	and	CCONJ
cana-5239	65	15	mode	mode	NOUN
cana-5239	65	16	imputation	imputation	NOUN
cana-5239	65	17	for	for	ADP
cana-5239	65	18	categorical	categorical	ADJ
cana-5239	65	19	variables	variable	NOUN
cana-5239	65	20	.	.	PUNCT
cana-5239	66	1	min	min	ADJ
cana-5239	66	2	-	-	PUNCT
cana-5239	66	3	max	max	ADJ
cana-5239	66	4	scaling	scaling	NOUN
cana-5239	66	5	[	[	X
cana-5239	66	6	28	28	NUM
cana-5239	66	7	]	]	PUNCT
cana-5239	66	8	was	be	AUX
cana-5239	66	9	applied	apply	VERB
cana-5239	66	10	to	to	PART
cana-5239	66	11	normalize	normalize	VERB
cana-5239	66	12	the	the	DET
cana-5239	66	13	dataset	dataset	NOUN
cana-5239	66	14	,	,	PUNCT
cana-5239	66	15	ensuring	ensure	VERB
cana-5239	66	16	that	that	SCONJ
cana-5239	66	17	all	all	DET
cana-5239	66	18	features	feature	NOUN
cana-5239	66	19	had	have	VERB
cana-5239	66	20	values	value	NOUN
cana-5239	66	21	between	between	ADP
cana-5239	66	22	0	0	NUM
cana-5239	66	23	and	and	CCONJ
cana-5239	66	24	1	1	NUM
cana-5239	66	25	.	.	PUNCT
cana-5239	67	1	this	this	PRON
cana-5239	67	2	prevents	prevent	VERB
cana-5239	67	3	bias	bias	NOUN
cana-5239	67	4	due	due	ADP
cana-5239	67	5	to	to	ADP
cana-5239	67	6	varying	vary	VERB
cana-5239	67	7	feature	feature	NOUN
cana-5239	67	8	scales	scale	NOUN
cana-5239	67	9	.	.	PUNCT
cana-5239	68	1	categorical	categorical	ADJ
cana-5239	68	2	variables	variable	NOUN
cana-5239	68	3	were	be	AUX
cana-5239	68	4	converted	convert	VERB
cana-5239	68	5	into	into	ADP
cana-5239	68	6	numerical	numerical	ADJ
cana-5239	68	7	values	value	NOUN
cana-5239	68	8	using	use	VERB
cana-5239	68	9	one	one	NUM
cana-5239	68	10	-	-	PUNCT
cana-5239	68	11	hot	hot	ADJ
cana-5239	68	12	encoding	encoding	NOUN
cana-5239	68	13	.	.	PUNCT
cana-5239	69	1	communications	communication	NOUN
cana-5239	69	2	on	on	ADP
cana-5239	69	3	applied	apply	VERB
cana-5239	69	4	nonlinear	nonlinear	ADJ
cana-5239	69	5	analysis	analysis	NOUN
cana-5239	69	6	issn	issn	NOUN
cana-5239	69	7	:	:	PUNCT
cana-5239	69	8	1074	1074	NUM
cana-5239	69	9	-	-	PUNCT
cana-5239	69	10	133x	133x	NUM
cana-5239	69	11	vol	vol	VERB
cana-5239	69	12	32	32	NUM
cana-5239	69	13	no	no	NOUN
cana-5239	69	14	.	.	PUNCT
cana-5239	70	1	10s	10	NOUN
cana-5239	70	2	(	(	PUNCT
cana-5239	70	3	2025	2025	NUM
cana-5239	70	4	)	)	PUNCT
cana-5239	70	5	1375	1375	NUM
cana-5239	70	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5239	70	7	3.3	3.3	NUM
cana-5239	70	8	feature	feature	NOUN
cana-5239	70	9	selection	selection	NOUN
cana-5239	70	10	:	:	PUNCT
cana-5239	70	11	3.3.1	3.3.1	NUM
cana-5239	70	12	principle	principle	NOUN
cana-5239	70	13	component	component	NOUN
cana-5239	70	14	analysis	analysis	NOUN
cana-5239	70	15	pca	pca	NOUN
cana-5239	70	16	is	be	AUX
cana-5239	70	17	a	a	DET
cana-5239	70	18	linear	linear	ADJ
cana-5239	70	19	dimensionality	dimensionality	NOUN
cana-5239	70	20	reduction	reduction	NOUN
cana-5239	70	21	method	method	NOUN
cana-5239	70	22	that	that	PRON
cana-5239	70	23	projects	project	VERB
cana-5239	70	24	data	datum	NOUN
cana-5239	70	25	into	into	ADP
cana-5239	70	26	a	a	DET
cana-5239	70	27	lower	lower	ADV
cana-5239	70	28	-	-	PUNCT
cana-5239	70	29	dimensional	dimensional	ADJ
cana-5239	70	30	subspace	subspace	NOUN
cana-5239	70	31	,	,	PUNCT
cana-5239	70	32	allowing	allow	VERB
cana-5239	70	33	for	for	ADP
cana-5239	70	34	the	the	DET
cana-5239	70	35	extraction	extraction	NOUN
cana-5239	70	36	of	of	ADP
cana-5239	70	37	information	information	NOUN
cana-5239	70	38	from	from	ADP
cana-5239	70	39	a	a	DET
cana-5239	70	40	high	high	ADJ
cana-5239	70	41	-	-	PUNCT
cana-5239	70	42	dimensional	dimensional	ADJ
cana-5239	70	43	environment	environment	NOUN
cana-5239	70	44	.	.	PUNCT
cana-5239	71	1	it	it	PRON
cana-5239	71	2	attempts	attempt	VERB
cana-5239	71	3	to	to	PART
cana-5239	71	4	eliminate	eliminate	VERB
cana-5239	71	5	the	the	DET
cana-5239	71	6	non	non	ADJ
cana-5239	71	7	-	-	ADJ
cana-5239	71	8	essential	essential	ADJ
cana-5239	71	9	sections	section	NOUN
cana-5239	71	10	with	with	ADP
cana-5239	71	11	less	less	ADJ
cana-5239	71	12	variation	variation	NOUN
cana-5239	71	13	and	and	CCONJ
cana-5239	71	14	keep	keep	VERB
cana-5239	71	15	the	the	DET
cana-5239	71	16	vital	vital	ADJ
cana-5239	71	17	parts	part	NOUN
cana-5239	71	18	with	with	ADP
cana-5239	71	19	more	more	ADJ
cana-5239	71	20	variation	variation	NOUN
cana-5239	71	21	in	in	ADP
cana-5239	71	22	the	the	DET
cana-5239	71	23	data	datum	NOUN
cana-5239	71	24	.	.	PUNCT
cana-5239	72	1	the	the	DET
cana-5239	72	2	algorithm	algorithm	NOUN
cana-5239	72	3	steps	step	NOUN
cana-5239	72	4	of	of	ADP
cana-5239	72	5	pca	pca	PROPN
cana-5239	72	6	is	be	AUX
cana-5239	72	7	given	give	VERB
cana-5239	72	8	in	in	ADP
cana-5239	72	9	table	table	NOUN
cana-5239	72	10	1	1	NUM
cana-5239	72	11	.	.	PUNCT
cana-5239	72	12	being	be	AUX
cana-5239	72	13	an	an	DET
cana-5239	72	14	unsupervised	unsupervised	ADJ
cana-5239	72	15	dimensionality	dimensionality	NOUN
cana-5239	72	16	reduction	reduction	NOUN
cana-5239	72	17	technique	technique	NOUN
cana-5239	72	18	,	,	PUNCT
cana-5239	72	19	pca	pca	PROPN
cana-5239	72	20	can	can	AUX
cana-5239	72	21	cluster	cluster	VERB
cana-5239	72	22	comparable	comparable	ADJ
cana-5239	72	23	data	datum	NOUN
cana-5239	72	24	points	point	NOUN
cana-5239	72	25	based	base	VERB
cana-5239	72	26	on	on	ADP
cana-5239	72	27	the	the	DET
cana-5239	72	28	feature	feature	NOUN
cana-5239	72	29	correlation	correlation	NOUN
cana-5239	72	30	between	between	ADP
cana-5239	72	31	them	they	PRON
cana-5239	72	32	without	without	ADP
cana-5239	72	33	the	the	DET
cana-5239	72	34	need	need	NOUN
cana-5239	72	35	for	for	ADP
cana-5239	72	36	supervision	supervision	NOUN
cana-5239	72	37	or	or	CCONJ
cana-5239	72	38	labeling	labeling	NOUN
cana-5239	72	39	.	.	PUNCT
cana-5239	73	1	this	this	PRON
cana-5239	73	2	is	be	AUX
cana-5239	73	3	an	an	DET
cana-5239	73	4	essential	essential	ADJ
cana-5239	73	5	observation	observation	NOUN
cana-5239	73	6	regarding	regard	VERB
cana-5239	73	7	pca	pca	PROPN
cana-5239	73	8	.	.	PROPN
cana-5239	73	9	coordinate	coordinate	NOUN
cana-5239	73	10	rotation	rotation	NOUN
cana-5239	73	11	and	and	CCONJ
cana-5239	73	12	transformation	transformation	NOUN
cana-5239	73	13	constitute	constitute	VERB
cana-5239	73	14	the	the	DET
cana-5239	73	15	mathematical	mathematical	ADJ
cana-5239	73	16	core	core	NOUN
cana-5239	73	17	of	of	ADP
cana-5239	73	18	the	the	DET
cana-5239	73	19	pca	pca	PROPN
cana-5239	73	20	approach	approach	NOUN
cana-5239	73	21	.	.	PUNCT
cana-5239	74	1	in	in	ADP
cana-5239	74	2	the	the	DET
cana-5239	74	3	new	new	ADJ
cana-5239	74	4	coordinate	coordinate	NOUN
cana-5239	74	5	system	system	NOUN
cana-5239	74	6	,	,	PUNCT
cana-5239	74	7	the	the	DET
cana-5239	74	8	original	original	ADJ
cana-5239	74	9	n	n	NOUN
cana-5239	74	10	variables	variable	NOUN
cana-5239	74	11	are	be	AUX
cana-5239	74	12	linearly	linearly	ADV
cana-5239	74	13	integrated	integrate	VERB
cana-5239	74	14	to	to	PART
cana-5239	74	15	create	create	VERB
cana-5239	74	16	n	n	DET
cana-5239	74	17	new	new	ADJ
cana-5239	74	18	variables	variable	NOUN
cana-5239	74	19	that	that	PRON
cana-5239	74	20	are	be	AUX
cana-5239	74	21	unrelated	unrelated	ADJ
cana-5239	74	22	to	to	ADP
cana-5239	74	23	one	one	NUM
cana-5239	74	24	another	another	DET
cana-5239	74	25	.	.	PUNCT
cana-5239	75	1	the	the	DET
cana-5239	75	2	essential	essential	ADJ
cana-5239	75	3	steps	step	NOUN
cana-5239	75	4	of	of	ADP
cana-5239	75	5	the	the	DET
cana-5239	75	6	pca	pca	NOUN
cana-5239	75	7	approach	approach	NOUN
cana-5239	75	8	are	be	AUX
cana-5239	75	9	stated	state	VERB
cana-5239	75	10	as	as	SCONJ
cana-5239	75	11	follows	follow	VERB
cana-5239	75	12	,	,	PUNCT
cana-5239	75	13	using	use	VERB
cana-5239	75	14	the	the	DET
cana-5239	75	15	slope	slope	NOUN
cana-5239	75	16	with	with	ADP
cana-5239	75	17	only	only	ADV
cana-5239	75	18	two	two	NUM
cana-5239	75	19	nodes	node	NOUN
cana-5239	75	20	in	in	ADP
cana-5239	75	21	the	the	DET
cana-5239	75	22	finite	finite	ADJ
cana-5239	75	23	element	element	NOUN
cana-5239	75	24	simulations	simulation	NOUN
cana-5239	75	25	as	as	ADP
cana-5239	75	26	an	an	DET
cana-5239	75	27	example	example	NOUN
cana-5239	75	28	for	for	ADP
cana-5239	75	29	simplicity	simplicity	NOUN
cana-5239	75	30	.	.	PUNCT
cana-5239	76	1	table	table	NOUN
cana-5239	76	2	1	1	NUM
cana-5239	76	3	:	:	PUNCT
cana-5239	76	4	algorithm	algorithm	NOUN
cana-5239	76	5	of	of	ADP
cana-5239	76	6	pca	pca	PROPN
cana-5239	76	7	algorithm	algorithm	NOUN
cana-5239	76	8	:	:	PUNCT
cana-5239	76	9	pca	pca	NOUN
cana-5239	76	10	step	step	NOUN
cana-5239	76	11	1	1	NUM
cana-5239	76	12	:	:	PUNCT
cana-5239	76	13	centralize	centralize	VERB
cana-5239	76	14	the	the	DET
cana-5239	76	15	cohesion	cohesion	NOUN
cana-5239	76	16	matrix	matrix	NOUN
cana-5239	76	17	step	step	NOUN
cana-5239	76	18	2	2	NUM
cana-5239	76	19	:	:	PUNCT
cana-5239	76	20	compute	compute	VERB
cana-5239	76	21	the	the	DET
cana-5239	76	22	covariance	covariance	NOUN
cana-5239	76	23	matrix	matrix	NOUN
cana-5239	76	24	step	step	NOUN
cana-5239	76	25	3	3	NUM
cana-5239	76	26	:	:	PUNCT
cana-5239	76	27	determine	determine	VERB
cana-5239	76	28	the	the	DET
cana-5239	76	29	covariance	covariance	NOUN
cana-5239	76	30	matrix	matrix	NOUN
cana-5239	76	31	's	's	PART
cana-5239	76	32	eigenvalues	eigenvalue	NOUN
cana-5239	76	33	and	and	CCONJ
cana-5239	76	34	eigenvectors	eigenvector	NOUN
cana-5239	76	35	.	.	PUNCT
cana-5239	77	1	step	step	NOUN
cana-5239	77	2	4	4	NUM
cana-5239	77	3	:	:	PUNCT
cana-5239	77	4	choose	choose	VERB
cana-5239	77	5	a	a	DET
cana-5239	77	6	benchmark	benchmark	NOUN
cana-5239	77	7	for	for	ADP
cana-5239	77	8	dimensionality	dimensionality	NOUN
cana-5239	77	9	reduction	reduction	NOUN
cana-5239	77	10	step	step	NOUN
cana-5239	77	11	5	5	NUM
cana-5239	77	12	:	:	PUNCT
cana-5239	77	13	calculate	calculate	VERB
cana-5239	77	14	the	the	DET
cana-5239	77	15	dataset	dataset	NOUN
cana-5239	77	16	after	after	ADP
cana-5239	77	17	dimensionality	dimensionality	NOUN
cana-5239	77	18	reduction	reduction	NOUN
cana-5239	77	19	figure	figure	NOUN
cana-5239	77	20	1	1	NUM
cana-5239	77	21	.	.	PUNCT
cana-5239	77	22	agriculture	agriculture	NOUN
cana-5239	77	23	commodity	commodity	NOUN
cana-5239	77	24	price	price	NOUN
cana-5239	77	25	prediction	prediction	NOUN
cana-5239	77	26	model	model	NOUN
cana-5239	77	27	communications	communication	NOUN
cana-5239	77	28	on	on	ADP
cana-5239	77	29	applied	apply	VERB
cana-5239	77	30	nonlinear	nonlinear	ADJ
cana-5239	77	31	analysis	analysis	NOUN
cana-5239	77	32	issn	issn	NOUN
cana-5239	77	33	:	:	PUNCT
cana-5239	77	34	1074	1074	NUM
cana-5239	77	35	-	-	PUNCT
cana-5239	77	36	133x	133x	NUM
cana-5239	77	37	vol	vol	VERB
cana-5239	77	38	32	32	NUM
cana-5239	77	39	no	no	NOUN
cana-5239	77	40	.	.	PUNCT
cana-5239	78	1	10s	10	NOUN
cana-5239	78	2	(	(	PUNCT
cana-5239	78	3	2025	2025	NUM
cana-5239	78	4	)	)	PUNCT
cana-5239	78	5	1376	1376	NUM
cana-5239	78	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5239	78	7	3.3.2	3.3.2	NUM
cana-5239	78	8	recursive	recursive	ADJ
cana-5239	78	9	feature	feature	NOUN
cana-5239	78	10	elimination	elimination	NOUN
cana-5239	78	11	one	one	NUM
cana-5239	78	12	feature	feature	NOUN
cana-5239	78	13	selection	selection	NOUN
cana-5239	78	14	technique	technique	NOUN
cana-5239	78	15	for	for	ADP
cana-5239	78	16	determining	determine	VERB
cana-5239	78	17	the	the	DET
cana-5239	78	18	important	important	ADJ
cana-5239	78	19	characteristics	characteristic	NOUN
cana-5239	78	20	in	in	ADP
cana-5239	78	21	a	a	DET
cana-5239	78	22	dataset	dataset	NOUN
cana-5239	78	23	is	be	AUX
cana-5239	78	24	recursive	recursive	ADJ
cana-5239	78	25	feature	feature	NOUN
cana-5239	78	26	elimination	elimination	NOUN
cana-5239	78	27	.	.	PUNCT
cana-5239	79	1	once	once	ADV
cana-5239	79	2	the	the	DET
cana-5239	79	3	least	least	ADV
cana-5239	79	4	important	important	ADJ
cana-5239	79	5	components	component	NOUN
cana-5239	79	6	have	have	AUX
cana-5239	79	7	been	be	AUX
cana-5239	79	8	eliminated	eliminate	VERB
cana-5239	79	9	several	several	ADJ
cana-5239	79	10	times	time	NOUN
cana-5239	79	11	,	,	PUNCT
cana-5239	79	12	the	the	DET
cana-5239	79	13	procedure	procedure	NOUN
cana-5239	79	14	entails	entail	VERB
cana-5239	79	15	creating	create	VERB
cana-5239	79	16	a	a	DET
cana-5239	79	17	model	model	NOUN
cana-5239	79	18	with	with	ADP
cana-5239	79	19	the	the	DET
cana-5239	79	20	remaining	remain	VERB
cana-5239	79	21	characteristics	characteristic	NOUN
cana-5239	79	22	until	until	SCONJ
cana-5239	79	23	the	the	DET
cana-5239	79	24	required	require	VERB
cana-5239	79	25	number	number	NOUN
cana-5239	79	26	of	of	ADP
cana-5239	79	27	features	feature	NOUN
cana-5239	79	28	is	be	AUX
cana-5239	79	29	reached	reach	VERB
cana-5239	79	30	.	.	PUNCT
cana-5239	80	1	rfe	rfe	NOUN
cana-5239	80	2	can	can	AUX
cana-5239	80	3	be	be	AUX
cana-5239	80	4	applied	apply	VERB
cana-5239	80	5	to	to	ADP
cana-5239	80	6	any	any	DET
cana-5239	80	7	supervised	supervised	ADJ
cana-5239	80	8	learning	learning	NOUN
cana-5239	80	9	technique	technique	NOUN
cana-5239	80	10	[	[	X
cana-5239	80	11	29	29	NUM
cana-5239	80	12	]	]	PUNCT
cana-5239	80	13	.	.	PUNCT
cana-5239	81	1	the	the	DET
cana-5239	81	2	steps	step	NOUN
cana-5239	81	3	involved	involve	VERB
cana-5239	81	4	in	in	ADP
cana-5239	81	5	the	the	DET
cana-5239	81	6	rfe	rfe	NOUN
cana-5239	81	7	is	be	AUX
cana-5239	81	8	given	give	VERB
cana-5239	81	9	in	in	ADP
cana-5239	81	10	table	table	NOUN
cana-5239	81	11	2	2	NUM
cana-5239	81	12	.	.	PUNCT
cana-5239	82	1	the	the	DET
cana-5239	82	2	rfe	rfe	NOUN
cana-5239	82	3	was	be	AUX
cana-5239	82	4	a	a	DET
cana-5239	82	5	wrapper	wrapper	NOUN
cana-5239	82	6	type	type	NOUN
cana-5239	82	7	.	.	PUNCT
cana-5239	83	1	this	this	PRON
cana-5239	83	2	indicates	indicate	VERB
cana-5239	83	3	that	that	SCONJ
cana-5239	83	4	a	a	DET
cana-5239	83	5	distinct	distinct	ADJ
cana-5239	83	6	machine	machine	NOUN
cana-5239	83	7	learning	learn	VERB
cana-5239	83	8	algorithm	algorithm	NOUN
cana-5239	83	9	is	be	AUX
cana-5239	83	10	provided	provide	VERB
cana-5239	83	11	,	,	PUNCT
cana-5239	83	12	utilized	utilize	VERB
cana-5239	83	13	as	as	ADP
cana-5239	83	14	the	the	DET
cana-5239	83	15	central	central	ADJ
cana-5239	83	16	component	component	NOUN
cana-5239	83	17	of	of	ADP
cana-5239	83	18	the	the	DET
cana-5239	83	19	method	method	NOUN
cana-5239	83	20	,	,	PUNCT
cana-5239	83	21	wrapped	wrap	VERB
cana-5239	83	22	with	with	ADP
cana-5239	83	23	rfe	rfe	NOUN
cana-5239	83	24	,	,	PUNCT
cana-5239	83	25	and	and	CCONJ
cana-5239	83	26	used	use	VERB
cana-5239	83	27	to	to	PART
cana-5239	83	28	aid	aid	VERB
cana-5239	83	29	in	in	ADP
cana-5239	83	30	feature	feature	NOUN
cana-5239	83	31	selection	selection	NOUN
cana-5239	83	32	.	.	PUNCT
cana-5239	84	1	on	on	ADP
cana-5239	84	2	the	the	DET
cana-5239	84	3	other	other	ADJ
cana-5239	84	4	hand	hand	NOUN
cana-5239	84	5	,	,	PUNCT
cana-5239	84	6	filter	filter	NOUN
cana-5239	84	7	-	-	PUNCT
cana-5239	84	8	based	base	VERB
cana-5239	84	9	feature	feature	NOUN
cana-5239	84	10	selections	selection	NOUN
cana-5239	84	11	assign	assign	VERB
cana-5239	84	12	a	a	DET
cana-5239	84	13	score	score	NOUN
cana-5239	84	14	to	to	ADP
cana-5239	84	15	every	every	DET
cana-5239	84	16	feature	feature	NOUN
cana-5239	84	17	and	and	CCONJ
cana-5239	84	18	then	then	ADV
cana-5239	84	19	choose	choose	VERB
cana-5239	84	20	the	the	DET
cana-5239	84	21	features	feature	NOUN
cana-5239	84	22	that	that	PRON
cana-5239	84	23	have	have	VERB
cana-5239	84	24	the	the	DET
cana-5239	84	25	highest	high	ADJ
cana-5239	84	26	(	(	PUNCT
cana-5239	84	27	or	or	CCONJ
cana-5239	84	28	lowest	low	ADJ
cana-5239	84	29	)	)	PUNCT
cana-5239	84	30	value	value	NOUN
cana-5239	84	31	.	.	PUNCT
cana-5239	85	1	when	when	SCONJ
cana-5239	85	2	utilizing	utilize	VERB
cana-5239	85	3	rfe	rfe	NOUN
cana-5239	85	4	,	,	PUNCT
cana-5239	85	5	two	two	NUM
cana-5239	85	6	key	key	ADJ
cana-5239	85	7	configuration	configuration	NOUN
cana-5239	85	8	options	option	NOUN
cana-5239	85	9	are	be	AUX
cana-5239	85	10	considered	consider	VERB
cana-5239	85	11	:	:	PUNCT
cana-5239	85	12	the	the	DET
cana-5239	85	13	number	number	NOUN
cana-5239	85	14	of	of	ADP
cana-5239	85	15	features	feature	NOUN
cana-5239	85	16	to	to	PART
cana-5239	85	17	choose	choose	VERB
cana-5239	85	18	,	,	PUNCT
cana-5239	85	19	and	and	CCONJ
cana-5239	85	20	the	the	DET
cana-5239	85	21	algorithm	algorithm	NOUN
cana-5239	85	22	to	to	PART
cana-5239	85	23	assist	assist	VERB
cana-5239	85	24	in	in	ADP
cana-5239	85	25	feature	feature	NOUN
cana-5239	85	26	selection	selection	NOUN
cana-5239	85	27	.	.	PUNCT
cana-5239	86	1	rfe	rfe	PROPN
cana-5239	86	2	discovers	discover	VERB
cana-5239	86	3	a	a	DET
cana-5239	86	4	subset	subset	NOUN
cana-5239	86	5	of	of	ADP
cana-5239	86	6	features	feature	NOUN
cana-5239	86	7	by	by	ADP
cana-5239	86	8	first	first	ADV
cana-5239	86	9	utilizing	utilize	VERB
cana-5239	86	10	every	every	DET
cana-5239	86	11	feature	feature	NOUN
cana-5239	86	12	in	in	ADP
cana-5239	86	13	the	the	DET
cana-5239	86	14	training	training	NOUN
cana-5239	86	15	dataset	dataset	NOUN
cana-5239	86	16	and	and	CCONJ
cana-5239	86	17	then	then	ADV
cana-5239	86	18	effectively	effectively	ADV
cana-5239	86	19	eliminating	eliminate	VERB
cana-5239	86	20	the	the	DET
cana-5239	86	21	features	feature	NOUN
cana-5239	86	22	until	until	SCONJ
cana-5239	86	23	the	the	DET
cana-5239	86	24	target	target	NOUN
cana-5239	86	25	number	number	NOUN
cana-5239	86	26	of	of	ADP
cana-5239	86	27	features	feature	NOUN
cana-5239	86	28	is	be	AUX
cana-5239	86	29	retained	retain	VERB
cana-5239	86	30	.	.	PUNCT
cana-5239	87	1	table	table	NOUN
cana-5239	87	2	2	2	NUM
cana-5239	87	3	:	:	PUNCT
cana-5239	87	4	algorithm	algorithm	NOUN
cana-5239	87	5	of	of	ADP
cana-5239	87	6	rfe	rfe	PROPN
cana-5239	87	7	algorithm	algorithm	NOUN
cana-5239	87	8	:	:	PUNCT
cana-5239	88	1	rfe	rfe	NOUN
cana-5239	88	2	step	step	NOUN
cana-5239	88	3	1	1	NUM
cana-5239	88	4	:	:	PUNCT
cana-5239	88	5	using	use	VERB
cana-5239	88	6	the	the	DET
cana-5239	88	7	selected	select	VERB
cana-5239	88	8	rfe	rfe	NOUN
cana-5239	88	9	machine	machine	NOUN
cana-5239	88	10	learning	learning	NOUN
cana-5239	88	11	algorithm	algorithm	NOUN
cana-5239	88	12	,	,	PUNCT
cana-5239	88	13	rank	rank	VERB
cana-5239	88	14	the	the	DET
cana-5239	88	15	significance	significance	NOUN
cana-5239	88	16	of	of	ADP
cana-5239	88	17	each	each	DET
cana-5239	88	18	feature	feature	NOUN
cana-5239	88	19	.	.	PUNCT
cana-5239	89	1	step	step	NOUN
cana-5239	89	2	2	2	NUM
cana-5239	89	3	:	:	PUNCT
cana-5239	89	4	remove	remove	VERB
cana-5239	89	5	the	the	DET
cana-5239	89	6	least	least	ADV
cana-5239	89	7	significant	significant	ADJ
cana-5239	89	8	element	element	NOUN
cana-5239	89	9	.	.	PUNCT
cana-5239	90	1	step	step	NOUN
cana-5239	90	2	3	3	NUM
cana-5239	90	3	:	:	PUNCT
cana-5239	90	4	build	build	VERB
cana-5239	90	5	a	a	DET
cana-5239	90	6	model	model	NOUN
cana-5239	90	7	using	use	VERB
cana-5239	90	8	the	the	DET
cana-5239	90	9	remaining	remain	VERB
cana-5239	90	10	features	feature	NOUN
cana-5239	90	11	.	.	PUNCT
cana-5239	91	1	step	step	NOUN
cana-5239	91	2	4	4	NUM
cana-5239	91	3	:	:	PUNCT
cana-5239	91	4	apply	apply	VERB
cana-5239	91	5	the	the	DET
cana-5239	91	6	dataset	dataset	NOUN
cana-5239	91	7	on	on	ADP
cana-5239	91	8	the	the	DET
cana-5239	91	9	model	model	NOUN
cana-5239	91	10	step	step	NOUN
cana-5239	91	11	5	5	NUM
cana-5239	91	12	:	:	PUNCT
cana-5239	91	13	until	until	SCONJ
cana-5239	91	14	the	the	DET
cana-5239	91	15	required	require	VERB
cana-5239	91	16	number	number	NOUN
cana-5239	91	17	of	of	ADP
cana-5239	91	18	features	feature	NOUN
cana-5239	91	19	is	be	AUX
cana-5239	91	20	attained	attain	VERB
cana-5239	91	21	,	,	PUNCT
cana-5239	91	22	repeat	repeat	VERB
cana-5239	91	23	steps	step	NOUN
cana-5239	91	24	1	1	NUM
cana-5239	91	25	-	-	SYM
cana-5239	91	26	3	3	NUM
cana-5239	91	27	.	.	X
cana-5239	91	28	3.3.3	3.3.3	NUM
cana-5239	91	29	genetic	genetic	ADJ
cana-5239	91	30	algorithm	algorithm	NOUN
cana-5239	91	31	the	the	DET
cana-5239	91	32	goal	goal	NOUN
cana-5239	91	33	of	of	ADP
cana-5239	91	34	ga	ga	PROPN
cana-5239	91	35	is	be	AUX
cana-5239	91	36	to	to	PART
cana-5239	91	37	assess	assess	VERB
cana-5239	91	38	the	the	DET
cana-5239	91	39	psychological	psychological	ADJ
cana-5239	91	40	effects	effect	NOUN
cana-5239	91	41	,	,	PUNCT
cana-5239	91	42	model	model	VERB
cana-5239	91	43	the	the	DET
cana-5239	91	44	variable	variable	ADJ
cana-5239	91	45	approaches	approach	NOUN
cana-5239	91	46	,	,	PUNCT
cana-5239	91	47	and	and	CCONJ
cana-5239	91	48	mimic	mimic	VERB
cana-5239	91	49	the	the	DET
cana-5239	91	50	natural	natural	ADJ
cana-5239	91	51	changes	change	NOUN
cana-5239	91	52	that	that	PRON
cana-5239	91	53	take	take	VERB
cana-5239	91	54	place	place	NOUN
cana-5239	91	55	in	in	ADP
cana-5239	91	56	social	social	ADJ
cana-5239	91	57	systems	system	NOUN
cana-5239	91	58	,	,	PUNCT
cana-5239	91	59	which	which	PRON
cana-5239	91	60	are	be	AUX
cana-5239	91	61	living	live	VERB
cana-5239	91	62	ecosystems	ecosystem	NOUN
cana-5239	91	63	[	[	X
cana-5239	91	64	30	30	NUM
cana-5239	91	65	]	]	PUNCT
cana-5239	91	66	.	.	PUNCT
cana-5239	92	1	ga	ga	PROPN
cana-5239	92	2	provides	provide	VERB
cana-5239	92	3	a	a	DET
cana-5239	92	4	sizable	sizable	ADJ
cana-5239	92	5	number	number	NOUN
cana-5239	92	6	of	of	ADP
cana-5239	92	7	issues	issue	NOUN
cana-5239	92	8	may	may	AUX
cana-5239	92	9	essentially	essentially	ADV
cana-5239	92	10	be	be	AUX
cana-5239	92	11	resolved	resolve	VERB
cana-5239	92	12	by	by	ADP
cana-5239	92	13	applying	apply	VERB
cana-5239	92	14	the	the	DET
cana-5239	92	15	ga	ga	PROPN
cana-5239	92	16	techniques	technique	NOUN
cana-5239	92	17	.	.	PUNCT
cana-5239	93	1	ga	ga	PROPN
cana-5239	93	2	is	be	AUX
cana-5239	93	3	a	a	DET
cana-5239	93	4	wellliked	wellliked	ADJ
cana-5239	93	5	search	search	NOUN
cana-5239	93	6	and	and	CCONJ
cana-5239	93	7	optimization	optimization	NOUN
cana-5239	93	8	technique	technique	NOUN
cana-5239	93	9	for	for	ADP
cana-5239	93	10	handling	handle	VERB
cana-5239	93	11	extremely	extremely	ADV
cana-5239	93	12	complex	complex	ADJ
cana-5239	93	13	issues	issue	NOUN
cana-5239	93	14	.	.	PUNCT
cana-5239	94	1	its	its	PRON
cana-5239	94	2	techniques	technique	NOUN
cana-5239	94	3	have	have	AUX
cana-5239	94	4	shown	show	VERB
cana-5239	94	5	to	to	PART
cana-5239	94	6	be	be	AUX
cana-5239	94	7	successful	successful	ADJ
cana-5239	94	8	in	in	ADP
cana-5239	94	9	fields	field	NOUN
cana-5239	94	10	where	where	SCONJ
cana-5239	94	11	machine	machine	NOUN
cana-5239	94	12	learning	learning	NOUN
cana-5239	94	13	is	be	AUX
cana-5239	94	14	used	use	VERB
cana-5239	94	15	.	.	PUNCT
cana-5239	95	1	this	this	DET
cana-5239	95	2	section	section	NOUN
cana-5239	95	3	contains	contain	VERB
cana-5239	95	4	a	a	DET
cana-5239	95	5	detailed	detailed	ADJ
cana-5239	95	6	description	description	NOUN
cana-5239	95	7	of	of	ADP
cana-5239	95	8	the	the	DET
cana-5239	95	9	actual	actual	ADJ
cana-5239	95	10	coded	code	VERB
cana-5239	95	11	ga	ga	PROPN
cana-5239	95	12	.	.	PUNCT
cana-5239	96	1	the	the	DET
cana-5239	96	2	flow	flow	NOUN
cana-5239	96	3	chart	chart	NOUN
cana-5239	96	4	of	of	ADP
cana-5239	96	5	the	the	DET
cana-5239	96	6	ga	ga	PROPN
cana-5239	96	7	is	be	AUX
cana-5239	96	8	illustrated	illustrate	VERB
cana-5239	96	9	in	in	ADP
cana-5239	96	10	figure	figure	NOUN
cana-5239	96	11	2	2	NUM
cana-5239	96	12	.	.	PUNCT
cana-5239	97	1	the	the	DET
cana-5239	97	2	conventional	conventional	ADJ
cana-5239	97	3	ga	ga	NOUN
cana-5239	97	4	process	process	NOUN
cana-5239	97	5	is	be	AUX
cana-5239	97	6	described	describe	VERB
cana-5239	97	7	below	below	ADP
cana-5239	97	8	.	.	PUNCT
cana-5239	98	1	initial	initial	ADJ
cana-5239	98	2	population	population	NOUN
cana-5239	98	3	this	this	PRON
cana-5239	98	4	entails	entail	VERB
cana-5239	98	5	the	the	DET
cana-5239	98	6	possible	possible	ADJ
cana-5239	98	7	solution	solution	NOUN
cana-5239	98	8	for	for	ADP
cana-5239	98	9	set	set	NOUN
cana-5239	98	10	g	g	PROPN
cana-5239	98	11	,	,	PUNCT
cana-5239	98	12	i.e.	i.e.	X
cana-5239	98	13	,	,	PUNCT
cana-5239	98	14	a	a	DET
cana-5239	98	15	series	series	NOUN
cana-5239	98	16	of	of	ADP
cana-5239	98	17	random	random	ADJ
cana-5239	98	18	generations	generation	NOUN
cana-5239	98	19	of	of	ADP
cana-5239	98	20	real	real	ADJ
cana-5239	98	21	values	value	NOUN
cana-5239	98	22	,	,	PUNCT
cana-5239	98	23	𝐺	𝐺	PROPN
cana-5239	98	24	=	=	SYM
cana-5239	98	25	{	{	PUNCT
cana-5239	98	26	𝑔1	𝑔1	PROPN
cana-5239	98	27	,	,	PUNCT
cana-5239	98	28	𝑔2	𝑔2	VERB
cana-5239	98	29	,	,	PUNCT
cana-5239	98	30	…	…	PUNCT
cana-5239	98	31	,	,	PUNCT
cana-5239	98	32	𝑔𝑠	𝑔𝑠	X
cana-5239	98	33	}	}	PUNCT
cana-5239	98	34	.	.	PUNCT
cana-5239	99	1	evaluation	evaluation	NOUN
cana-5239	99	2	to	to	PART
cana-5239	99	3	assess	assess	VERB
cana-5239	99	4	every	every	DET
cana-5239	99	5	chromosome	chromosome	NOUN
cana-5239	99	6	in	in	ADP
cana-5239	99	7	the	the	DET
cana-5239	99	8	population	population	NOUN
cana-5239	99	9	,	,	PUNCT
cana-5239	99	10	the	the	DET
cana-5239	99	11	fitness	fitness	NOUN
cana-5239	99	12	function	function	NOUN
cana-5239	99	13	,	,	PUNCT
cana-5239	99	14	which	which	PRON
cana-5239	99	15	is	be	AUX
cana-5239	99	16	defined	define	VERB
cana-5239	99	17	as	as	ADP
cana-5239	99	18	𝑓𝑖𝑡𝑛𝑒𝑠𝑠	𝑓𝑖𝑡𝑛𝑒𝑠𝑠	NOUN
cana-5239	99	19	=	=	SYM
cana-5239	99	20	𝑔(𝑃	𝑔(𝑃	PROPN
cana-5239	99	21	)	)	PUNCT
cana-5239	99	22	,	,	PUNCT
cana-5239	99	23	must	must	AUX
cana-5239	99	24	be	be	AUX
cana-5239	99	25	defined	define	VERB
cana-5239	99	26	.	.	PUNCT
cana-5239	100	1	communications	communication	NOUN
cana-5239	100	2	on	on	ADP
cana-5239	100	3	applied	apply	VERB
cana-5239	100	4	nonlinear	nonlinear	ADJ
cana-5239	100	5	analysis	analysis	NOUN
cana-5239	100	6	issn	issn	NOUN
cana-5239	100	7	:	:	PUNCT
cana-5239	100	8	1074	1074	NUM
cana-5239	100	9	-	-	PUNCT
cana-5239	100	10	133x	133x	NUM
cana-5239	100	11	vol	vol	VERB
cana-5239	100	12	32	32	NUM
cana-5239	100	13	no	no	NOUN
cana-5239	100	14	.	.	PUNCT
cana-5239	101	1	10s	10	NOUN
cana-5239	101	2	(	(	PUNCT
cana-5239	101	3	2025	2025	NUM
cana-5239	101	4	)	)	PUNCT
cana-5239	101	5	1377	1377	NUM
cana-5239	101	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5239	101	7	selection	selection	NOUN
cana-5239	101	8	the	the	DET
cana-5239	101	9	chromosomes	chromosome	NOUN
cana-5239	101	10	are	be	AUX
cana-5239	101	11	sorted	sort	VERB
cana-5239	101	12	according	accord	VERB
cana-5239	101	13	to	to	ADP
cana-5239	101	14	their	their	PRON
cana-5239	101	15	fitness	fitness	NOUN
cana-5239	101	16	values	value	NOUN
cana-5239	101	17	after	after	ADP
cana-5239	101	18	the	the	DET
cana-5239	101	19	fitness	fitness	NOUN
cana-5239	101	20	value	value	NOUN
cana-5239	101	21	computation	computation	NOUN
cana-5239	101	22	.	.	PUNCT
cana-5239	102	1	the	the	DET
cana-5239	102	2	next	next	ADJ
cana-5239	102	3	step	step	NOUN
cana-5239	102	4	is	be	AUX
cana-5239	102	5	to	to	PART
cana-5239	102	6	pick	pick	VERB
cana-5239	102	7	the	the	DET
cana-5239	102	8	parents	parent	NOUN
cana-5239	102	9	,	,	PUNCT
cana-5239	102	10	which	which	PRON
cana-5239	102	11	requires	require	VERB
cana-5239	102	12	two	two	NUM
cana-5239	102	13	parents	parent	NOUN
cana-5239	102	14	for	for	ADP
cana-5239	102	15	the	the	DET
cana-5239	102	16	crossover	crossover	NOUN
cana-5239	102	17	and	and	CCONJ
cana-5239	102	18	the	the	DET
cana-5239	102	19	mutation	mutation	NOUN
cana-5239	102	20	.	.	PUNCT
cana-5239	103	1	the	the	DET
cana-5239	103	2	genetic	genetic	ADJ
cana-5239	103	3	operators	operator	NOUN
cana-5239	103	4	are	be	AUX
cana-5239	103	5	used	use	VERB
cana-5239	103	6	to	to	PART
cana-5239	103	7	construct	construct	VERB
cana-5239	103	8	the	the	DET
cana-5239	103	9	children	child	NOUN
cana-5239	103	10	(	(	PUNCT
cana-5239	103	11	c1	c1	PROPN
cana-5239	103	12	,	,	PUNCT
cana-5239	103	13	c2	c2	PROPN
cana-5239	103	14	)	)	PUNCT
cana-5239	103	15	or	or	CCONJ
cana-5239	103	16	the	the	DET
cana-5239	103	17	parents	parent	NOUN
cana-5239	103	18	'	'	PART
cana-5239	103	19	new	new	ADJ
cana-5239	103	20	chromosomes	chromosome	NOUN
cana-5239	103	21	when	when	SCONJ
cana-5239	103	22	the	the	DET
cana-5239	103	23	selection	selection	NOUN
cana-5239	103	24	procedure	procedure	NOUN
cana-5239	103	25	is	be	AUX
cana-5239	103	26	finished	finish	VERB
cana-5239	103	27	.	.	PUNCT
cana-5239	104	1	after	after	ADP
cana-5239	104	2	then	then	ADV
cana-5239	104	3	,	,	PUNCT
cana-5239	104	4	children	child	NOUN
cana-5239	104	5	in	in	ADP
cana-5239	104	6	population	population	NOUN
cana-5239	104	7	c	c	PROPN
cana-5239	104	8	are	be	AUX
cana-5239	104	9	spared	spare	VERB
cana-5239	104	10	with	with	ADP
cana-5239	104	11	the	the	DET
cana-5239	104	12	new	new	ADJ
cana-5239	104	13	chromosomes	chromosome	NOUN
cana-5239	104	14	(	(	PUNCT
cana-5239	104	15	c1	c1	PROPN
cana-5239	104	16	,	,	PUNCT
cana-5239	104	17	c2	c2	PROPN
cana-5239	104	18	)	)	PUNCT
cana-5239	104	19	.	.	PUNCT
cana-5239	105	1	the	the	DET
cana-5239	105	2	crossover	crossover	NOUN
cana-5239	105	3	and	and	CCONJ
cana-5239	105	4	mutation	mutation	NOUN
cana-5239	105	5	operations	operation	NOUN
cana-5239	105	6	are	be	AUX
cana-5239	105	7	involved	involve	VERB
cana-5239	105	8	in	in	ADP
cana-5239	105	9	this	this	DET
cana-5239	105	10	process	process	NOUN
cana-5239	105	11	.	.	PUNCT
cana-5239	106	1	two	two	NUM
cana-5239	106	2	parents	parent	NOUN
cana-5239	106	3	that	that	PRON
cana-5239	106	4	were	be	AUX
cana-5239	106	5	chosen	choose	VERB
cana-5239	106	6	earlier	early	ADJ
cana-5239	106	7	exchange	exchange	NOUN
cana-5239	106	8	information	information	NOUN
cana-5239	106	9	using	use	VERB
cana-5239	106	10	the	the	DET
cana-5239	106	11	crossover	crossover	NOUN
cana-5239	106	12	process	process	NOUN
cana-5239	106	13	.	.	PUNCT
cana-5239	107	1	there	there	PRON
cana-5239	107	2	are	be	VERB
cana-5239	107	3	numerous	numerous	ADJ
cana-5239	107	4	crossover	crossover	NOUN
cana-5239	107	5	operator	operator	NOUN
cana-5239	107	6	techniques	technique	NOUN
cana-5239	107	7	,	,	PUNCT
cana-5239	107	8	including	include	VERB
cana-5239	107	9	arithmetical	arithmetical	ADJ
cana-5239	107	10	,	,	PUNCT
cana-5239	107	11	two-	two-	X
cana-5239	107	12	,	,	PUNCT
cana-5239	107	13	k-	k-	X
cana-5239	107	14	,	,	PUNCT
cana-5239	107	15	and	and	CCONJ
cana-5239	107	16	single	single	ADJ
cana-5239	107	17	-	-	PUNCT
cana-5239	107	18	point	point	NOUN
cana-5239	107	19	crossovers	crossover	NOUN
cana-5239	107	20	,	,	PUNCT
cana-5239	107	21	among	among	ADP
cana-5239	107	22	others	other	NOUN
cana-5239	107	23	.	.	PUNCT
cana-5239	108	1	the	the	DET
cana-5239	108	2	crossing	crossing	NOUN
cana-5239	108	3	offspring	offspring	NOUN
cana-5239	108	4	's	's	PART
cana-5239	108	5	chromosomes	chromosome	NOUN
cana-5239	108	6	'	'	PART
cana-5239	108	7	genes	gene	NOUN
cana-5239	108	8	are	be	AUX
cana-5239	108	9	altered	alter	VERB
cana-5239	108	10	during	during	ADP
cana-5239	108	11	the	the	DET
cana-5239	108	12	mutation	mutation	NOUN
cana-5239	108	13	procedure	procedure	NOUN
cana-5239	108	14	.	.	PUNCT
cana-5239	109	1	similarly	similarly	ADV
cana-5239	109	2	,	,	PUNCT
cana-5239	109	3	the	the	DET
cana-5239	109	4	mutation	mutation	NOUN
cana-5239	109	5	operator	operator	NOUN
cana-5239	109	6	has	have	VERB
cana-5239	109	7	multiple	multiple	ADJ
cana-5239	109	8	options	option	NOUN
cana-5239	109	9	.	.	PUNCT
cana-5239	110	1	children	child	NOUN
cana-5239	110	2	population	population	NOUN
cana-5239	110	3	c	c	NOUN
cana-5239	110	4	is	be	AUX
cana-5239	110	5	fully	fully	ADV
cana-5239	110	6	formed	form	VERB
cana-5239	110	7	and	and	CCONJ
cana-5239	110	8	will	will	AUX
cana-5239	110	9	be	be	AUX
cana-5239	110	10	transferred	transfer	VERB
cana-5239	110	11	to	to	ADP
cana-5239	110	12	the	the	DET
cana-5239	110	13	next	next	ADJ
cana-5239	110	14	population	population	NOUN
cana-5239	110	15	(	(	PUNCT
cana-5239	110	16	p	p	NOUN
cana-5239	110	17	)	)	PUNCT
cana-5239	110	18	after	after	ADP
cana-5239	110	19	the	the	DET
cana-5239	110	20	selection	selection	NOUN
cana-5239	110	21	,	,	PUNCT
cana-5239	110	22	crossover	crossover	NOUN
cana-5239	110	23	,	,	PUNCT
cana-5239	110	24	and	and	CCONJ
cana-5239	110	25	mutation	mutation	NOUN
cana-5239	110	26	operations	operation	NOUN
cana-5239	110	27	are	be	AUX
cana-5239	110	28	finished	finish	VERB
cana-5239	110	29	.	.	PUNCT
cana-5239	111	1	the	the	DET
cana-5239	111	2	method	method	NOUN
cana-5239	111	3	is	be	AUX
cana-5239	111	4	then	then	ADV
cana-5239	111	5	repeated	repeat	VERB
cana-5239	111	6	using	use	VERB
cana-5239	111	7	p	p	NOUN
cana-5239	111	8	in	in	ADP
cana-5239	111	9	the	the	DET
cana-5239	111	10	subsequent	subsequent	ADJ
cana-5239	111	11	iteration	iteration	NOUN
cana-5239	111	12	.	.	PUNCT
cana-5239	112	1	if	if	SCONJ
cana-5239	112	2	the	the	DET
cana-5239	112	3	number	number	NOUN
cana-5239	112	4	of	of	ADP
cana-5239	112	5	iterations	iteration	NOUN
cana-5239	112	6	exceeds	exceed	VERB
cana-5239	112	7	the	the	DET
cana-5239	112	8	maximum	maximum	ADJ
cana-5239	112	9	threshold	threshold	NOUN
cana-5239	112	10	or	or	CCONJ
cana-5239	112	11	if	if	SCONJ
cana-5239	112	12	the	the	DET
cana-5239	112	13	results	result	NOUN
cana-5239	112	14	start	start	VERB
cana-5239	112	15	to	to	PART
cana-5239	112	16	converge	converge	VERB
cana-5239	112	17	,	,	PUNCT
cana-5239	112	18	the	the	DET
cana-5239	112	19	iterations	iteration	NOUN
cana-5239	112	20	will	will	AUX
cana-5239	112	21	end	end	VERB
cana-5239	112	22	.	.	PUNCT
cana-5239	113	1	figure	figure	NOUN
cana-5239	113	2	2	2	NUM
cana-5239	113	3	.	.	PUNCT
cana-5239	113	4	flow	flow	VERB
cana-5239	113	5	chart	chart	NOUN
cana-5239	113	6	of	of	ADP
cana-5239	113	7	genetic	genetic	ADJ
cana-5239	113	8	algorithm	algorithm	NOUN
cana-5239	113	9	3.3.4	3.3.4	NUM
cana-5239	113	10	grey	grey	PROPN
cana-5239	113	11	wolf	wolf	PROPN
cana-5239	113	12	optimization	optimization	NOUN
cana-5239	113	13	grey	grey	PROPN
cana-5239	113	14	wolf	wolf	PROPN
cana-5239	113	15	optimization	optimization	NOUN
cana-5239	113	16	(	(	PUNCT
cana-5239	113	17	gwo	gwo	PROPN
cana-5239	113	18	)	)	PUNCT
cana-5239	113	19	is	be	AUX
cana-5239	113	20	a	a	DET
cana-5239	113	21	nature	nature	NOUN
cana-5239	113	22	-	-	PUNCT
cana-5239	113	23	inspired	inspire	VERB
cana-5239	113	24	metaheuristic	metaheuristic	ADJ
cana-5239	113	25	algorithm	algorithm	NOUN
cana-5239	113	26	that	that	PRON
cana-5239	113	27	mimics	mimic	VERB
cana-5239	113	28	the	the	DET
cana-5239	113	29	leadership	leadership	NOUN
cana-5239	113	30	hierarchy	hierarchy	NOUN
cana-5239	113	31	and	and	CCONJ
cana-5239	113	32	hunting	hunt	VERB
cana-5239	113	33	strategy	strategy	NOUN
cana-5239	113	34	of	of	ADP
cana-5239	113	35	grey	grey	ADJ
cana-5239	113	36	wolves	wolf	NOUN
cana-5239	113	37	in	in	ADP
cana-5239	113	38	the	the	DET
cana-5239	113	39	wild	wild	NOUN
cana-5239	113	40	.	.	PUNCT
cana-5239	114	1	it	it	PRON
cana-5239	114	2	was	be	AUX
cana-5239	114	3	introduced	introduce	VERB
cana-5239	114	4	by	by	ADP
cana-5239	114	5	seyedali	seyedali	ADJ
cana-5239	114	6	communications	communication	NOUN
cana-5239	114	7	on	on	ADP
cana-5239	114	8	applied	apply	VERB
cana-5239	114	9	nonlinear	nonlinear	ADJ
cana-5239	114	10	analysis	analysis	NOUN
cana-5239	114	11	issn	issn	NOUN
cana-5239	114	12	:	:	PUNCT
cana-5239	114	13	1074	1074	NUM
cana-5239	114	14	-	-	PUNCT
cana-5239	114	15	133x	133x	NUM
cana-5239	114	16	vol	vol	VERB
cana-5239	114	17	32	32	NUM
cana-5239	114	18	no	no	NOUN
cana-5239	114	19	.	.	PUNCT
cana-5239	115	1	10s	10	NOUN
cana-5239	115	2	(	(	PUNCT
cana-5239	115	3	2025	2025	NUM
cana-5239	115	4	)	)	PUNCT
cana-5239	115	5	1378	1378	NUM
cana-5239	116	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-5239	116	2	mirjalili	mirjalili	NOUN
cana-5239	116	3	in	in	ADP
cana-5239	116	4	2014	2014	NUM
cana-5239	116	5	[	[	X
cana-5239	116	6	31	31	NUM
cana-5239	116	7	]	]	PUNCT
cana-5239	116	8	and	and	CCONJ
cana-5239	116	9	is	be	AUX
cana-5239	116	10	widely	widely	ADV
cana-5239	116	11	used	use	VERB
cana-5239	116	12	for	for	ADP
cana-5239	116	13	solving	solve	VERB
cana-5239	116	14	optimization	optimization	NOUN
cana-5239	116	15	problems	problem	NOUN
cana-5239	116	16	.	.	PUNCT
cana-5239	117	1	the	the	DET
cana-5239	117	2	algorithm	algorithm	NOUN
cana-5239	117	3	is	be	AUX
cana-5239	117	4	inspired	inspire	VERB
cana-5239	117	5	by	by	ADP
cana-5239	117	6	the	the	DET
cana-5239	117	7	social	social	ADJ
cana-5239	117	8	structure	structure	NOUN
cana-5239	117	9	of	of	ADP
cana-5239	117	10	grey	grey	ADJ
cana-5239	117	11	wolves	wolf	NOUN
cana-5239	117	12	,	,	PUNCT
cana-5239	117	13	which	which	PRON
cana-5239	117	14	typically	typically	ADV
cana-5239	117	15	hunt	hunt	VERB
cana-5239	117	16	in	in	ADP
cana-5239	117	17	packs	pack	NOUN
cana-5239	117	18	,	,	PUNCT
cana-5239	117	19	led	lead	VERB
cana-5239	117	20	by	by	ADP
cana-5239	117	21	four	four	NUM
cana-5239	117	22	types	type	NOUN
cana-5239	117	23	of	of	ADP
cana-5239	117	24	wolves	wolf	NOUN
cana-5239	117	25	:	:	PUNCT
cana-5239	117	26	alpha	alpha	NOUN
cana-5239	117	27	(	(	PUNCT
cana-5239	117	28	leader	leader	NOUN
cana-5239	117	29	)	)	PUNCT
cana-5239	117	30	,	,	PUNCT
cana-5239	117	31	beta	beta	NOUN
cana-5239	117	32	(	(	PUNCT
cana-5239	117	33	second	second	ADJ
cana-5239	117	34	in	in	ADP
cana-5239	117	35	command	command	NOUN
cana-5239	117	36	)	)	PUNCT
cana-5239	117	37	,	,	PUNCT
cana-5239	117	38	delta	delta	NOUN
cana-5239	117	39	,	,	PUNCT
cana-5239	117	40	and	and	CCONJ
cana-5239	117	41	omega	omega	NOUN
cana-5239	117	42	(	(	PUNCT
cana-5239	117	43	followers	follower	NOUN
cana-5239	117	44	)	)	PUNCT
cana-5239	117	45	.	.	PUNCT
cana-5239	118	1	gwo	gwo	PROPN
cana-5239	118	2	models	model	NOUN
cana-5239	118	3	this	this	DET
cana-5239	118	4	hierarchy	hierarchy	NOUN
cana-5239	118	5	and	and	CCONJ
cana-5239	118	6	utilizes	utilize	VERB
cana-5239	118	7	it	it	PRON
cana-5239	118	8	to	to	PART
cana-5239	118	9	find	find	VERB
cana-5239	118	10	optimal	optimal	ADJ
cana-5239	118	11	solutions	solution	NOUN
cana-5239	118	12	by	by	ADP
cana-5239	118	13	simulating	simulate	VERB
cana-5239	118	14	the	the	DET
cana-5239	118	15	wolves	wolf	NOUN
cana-5239	118	16	'	'	PART
cana-5239	118	17	cooperative	cooperative	ADJ
cana-5239	118	18	behavior	behavior	NOUN
cana-5239	118	19	in	in	ADP
cana-5239	118	20	hunting	hunt	VERB
cana-5239	118	21	prey	prey	NOUN
cana-5239	118	22	.	.	PUNCT
cana-5239	119	1	pseudocode	pseudocode	PROPN
cana-5239	119	2	of	of	ADP
cana-5239	119	3	gwo	gwo	PROPN
cana-5239	119	4	is	be	AUX
cana-5239	119	5	given	give	VERB
cana-5239	119	6	in	in	ADP
cana-5239	119	7	table	table	NOUN
cana-5239	119	8	3	3	NUM
cana-5239	119	9	.	.	X
cana-5239	119	10	initialization	initialization	NOUN
cana-5239	119	11	:	:	PUNCT
cana-5239	119	12	initialize	initialize	VERB
cana-5239	119	13	the	the	DET
cana-5239	119	14	population	population	NOUN
cana-5239	119	15	of	of	ADP
cana-5239	119	16	grey	grey	ADJ
cana-5239	119	17	wolves	wolf	NOUN
cana-5239	119	18	(	(	PUNCT
cana-5239	119	19	candidate	candidate	NOUN
cana-5239	119	20	solutions	solution	NOUN
cana-5239	119	21	)	)	PUNCT
cana-5239	119	22	.	.	PUNCT
cana-5239	120	1	each	each	DET
cana-5239	120	2	wolf	wolf	NOUN
cana-5239	120	3	represents	represent	VERB
cana-5239	120	4	a	a	DET
cana-5239	120	5	potential	potential	ADJ
cana-5239	120	6	solution	solution	NOUN
cana-5239	120	7	to	to	ADP
cana-5239	120	8	the	the	DET
cana-5239	120	9	optimization	optimization	NOUN
cana-5239	120	10	problem	problem	NOUN
cana-5239	120	11	.	.	PUNCT
cana-5239	121	1	identify	identify	VERB
cana-5239	121	2	the	the	DET
cana-5239	121	3	alpha	alpha	NOUN
cana-5239	121	4	(	(	PUNCT
cana-5239	121	5	best	good	ADJ
cana-5239	121	6	solution	solution	NOUN
cana-5239	121	7	)	)	PUNCT
cana-5239	121	8	,	,	PUNCT
cana-5239	121	9	beta	beta	NOUN
cana-5239	121	10	(	(	PUNCT
cana-5239	121	11	second	second	ADV
cana-5239	121	12	-	-	PUNCT
cana-5239	121	13	best	good	ADJ
cana-5239	121	14	solution	solution	NOUN
cana-5239	121	15	)	)	PUNCT
cana-5239	121	16	,	,	PUNCT
cana-5239	121	17	and	and	CCONJ
cana-5239	121	18	delta	delta	NOUN
cana-5239	121	19	(	(	PUNCT
cana-5239	121	20	third	third	ADV
cana-5239	121	21	-	-	PUNCT
cana-5239	121	22	best	good	ADJ
cana-5239	121	23	solution	solution	NOUN
cana-5239	121	24	)	)	PUNCT
cana-5239	121	25	wolves	wolf	NOUN
cana-5239	121	26	based	base	VERB
cana-5239	121	27	on	on	ADP
cana-5239	121	28	their	their	PRON
cana-5239	121	29	fitness	fitness	NOUN
cana-5239	121	30	values	value	NOUN
cana-5239	121	31	(	(	PUNCT
cana-5239	121	32	objective	objective	ADJ
cana-5239	121	33	function	function	NOUN
cana-5239	121	34	)	)	PUNCT
cana-5239	121	35	.	.	PUNCT
cana-5239	122	1	update	update	NOUN
cana-5239	122	2	position	position	NOUN
cana-5239	122	3	of	of	ADP
cana-5239	122	4	grey	grey	ADJ
cana-5239	122	5	wolves	wolf	NOUN
cana-5239	122	6	:	:	PUNCT
cana-5239	122	7	for	for	ADP
cana-5239	122	8	each	each	DET
cana-5239	122	9	wolf	wolf	NOUN
cana-5239	122	10	(	(	PUNCT
cana-5239	122	11	solution	solution	NOUN
cana-5239	122	12	)	)	PUNCT
cana-5239	122	13	in	in	ADP
cana-5239	122	14	the	the	DET
cana-5239	122	15	population	population	NOUN
cana-5239	122	16	,	,	PUNCT
cana-5239	122	17	update	update	VERB
cana-5239	122	18	its	its	PRON
cana-5239	122	19	position	position	NOUN
cana-5239	122	20	based	base	VERB
cana-5239	122	21	on	on	ADP
cana-5239	122	22	the	the	DET
cana-5239	122	23	influence	influence	NOUN
cana-5239	122	24	of	of	ADP
cana-5239	122	25	alpha	alpha	NOUN
cana-5239	122	26	,	,	PUNCT
cana-5239	122	27	beta	beta	NOUN
cana-5239	122	28	,	,	PUNCT
cana-5239	122	29	and	and	CCONJ
cana-5239	122	30	delta	delta	VERB
cana-5239	122	31	wolves.the	wolves.the	DET
cana-5239	122	32	position	position	NOUN
cana-5239	122	33	update	update	NOUN
cana-5239	122	34	formula	formula	NOUN
cana-5239	122	35	is	be	AUX
cana-5239	122	36	defined	define	VERB
cana-5239	122	37	by	by	ADP
cana-5239	122	38	𝑋(𝑎	𝑋(𝑎	ADV
cana-5239	122	39	+	+	NOUN
cana-5239	122	40	1	1	NUM
cana-5239	122	41	)	)	PUNCT
cana-5239	122	42	𝑋𝛼(𝑎	𝑋𝛼(𝑎	NOUN
cana-5239	122	43	)	)	PUNCT
cana-5239	122	44	+	+	CCONJ
cana-5239	122	45	𝑋𝛽(𝑎	𝑋𝛽(𝑎	ADJ
cana-5239	122	46	)	)	PUNCT
cana-5239	122	47	+	+	NUM
cana-5239	122	48	𝑋𝛾(𝑎	𝑋𝛾(𝑎	NOUN
cana-5239	122	49	)	)	PUNCT
cana-5239	122	50	3	3	NUM
cana-5239	122	51	where	where	SCONJ
cana-5239	122	52	𝑋(𝑎	𝑋(𝑎	X
cana-5239	122	53	)	)	PUNCT
cana-5239	122	54	)	)	PUNCT
cana-5239	123	1	is	be	AUX
cana-5239	123	2	the	the	DET
cana-5239	123	3	current	current	ADJ
cana-5239	123	4	position	position	NOUN
cana-5239	123	5	of	of	ADP
cana-5239	123	6	the	the	DET
cana-5239	123	7	wolf	wolf	NOUN
cana-5239	123	8	.	.	PUNCT
cana-5239	123	9	𝑋𝛼,𝑋𝛽	𝑋𝛼,𝑋𝛽	NOUN
cana-5239	123	10	,	,	PUNCT
cana-5239	123	11	𝑋𝛾	𝑋𝛾	ADV
cana-5239	123	12	are	be	AUX
cana-5239	123	13	the	the	DET
cana-5239	123	14	positions	position	NOUN
cana-5239	123	15	of	of	ADP
cana-5239	123	16	the	the	DET
cana-5239	123	17	alpha	alpha	NOUN
cana-5239	123	18	,	,	PUNCT
cana-5239	123	19	beta	beta	NOUN
cana-5239	123	20	,	,	PUNCT
cana-5239	123	21	and	and	CCONJ
cana-5239	123	22	delta	delta	NOUN
cana-5239	123	23	wolves	wolf	NOUN
cana-5239	123	24	,	,	PUNCT
cana-5239	123	25	respectively	respectively	ADV
cana-5239	123	26	.	.	PUNCT
cana-5239	124	1	the	the	DET
cana-5239	124	2	position	position	NOUN
cana-5239	124	3	is	be	AUX
cana-5239	124	4	updated	update	VERB
cana-5239	124	5	based	base	VERB
cana-5239	124	6	on	on	ADP
cana-5239	124	7	the	the	DET
cana-5239	124	8	wolves	wolf	NOUN
cana-5239	124	9	'	'	PART
cana-5239	124	10	distances	distance	NOUN
cana-5239	124	11	from	from	ADP
cana-5239	124	12	the	the	DET
cana-5239	124	13	best	good	ADJ
cana-5239	124	14	solutions	solution	NOUN
cana-5239	124	15	.	.	PUNCT
cana-5239	125	1	encircling	encircle	VERB
cana-5239	125	2	prey	prey	NOUN
cana-5239	125	3	:	:	PUNCT
cana-5239	125	4	the	the	DET
cana-5239	125	5	grey	grey	ADJ
cana-5239	125	6	wolves	wolf	NOUN
cana-5239	125	7	attempt	attempt	VERB
cana-5239	125	8	to	to	PART
cana-5239	125	9	encircle	encircle	VERB
cana-5239	125	10	their	their	PRON
cana-5239	125	11	prey	prey	NOUN
cana-5239	125	12	(	(	PUNCT
cana-5239	125	13	optimal	optimal	ADJ
cana-5239	125	14	solution	solution	NOUN
cana-5239	125	15	)	)	PUNCT
cana-5239	125	16	by	by	ADP
cana-5239	125	17	adjusting	adjust	VERB
cana-5239	125	18	their	their	PRON
cana-5239	125	19	positions	position	NOUN
cana-5239	125	20	in	in	ADP
cana-5239	125	21	relation	relation	NOUN
cana-5239	125	22	to	to	ADP
cana-5239	125	23	alpha	alpha	NOUN
cana-5239	125	24	,	,	PUNCT
cana-5239	125	25	beta	beta	NOUN
cana-5239	125	26	,	,	PUNCT
cana-5239	125	27	and	and	CCONJ
cana-5239	125	28	delta	delta	NOUN
cana-5239	125	29	wolves	wolf	NOUN
cana-5239	125	30	.	.	PUNCT
cana-5239	126	1	the	the	DET
cana-5239	126	2	encircling	encircle	VERB
cana-5239	126	3	behavior	behavior	NOUN
cana-5239	126	4	is	be	AUX
cana-5239	126	5	mathematically	mathematically	ADV
cana-5239	126	6	modeled	model	VERB
cana-5239	126	7	as	as	ADP
cana-5239	126	8	𝑅	𝑅	PROPN
cana-5239	126	9	=	=	PUNCT
cana-5239	126	10	|𝑄.	|𝑄.	PROPN
cana-5239	126	11	𝑋𝑏(𝑎	𝑋𝑏(𝑎	PROPN
cana-5239	126	12	)	)	PUNCT
cana-5239	126	13	−	−	PROPN
cana-5239	126	14	𝑋(𝑎)|	𝑋(𝑎)|	X
cana-5239	126	15	𝑋(𝑎	𝑋(𝑎	X
cana-5239	126	16	+	+	ADJ
cana-5239	126	17	1	1	NUM
cana-5239	126	18	)	)	PUNCT
cana-5239	126	19	=	=	SYM
cana-5239	126	20	𝑋𝑏(𝑎	𝑋𝑏(𝑎	NOUN
cana-5239	126	21	)	)	PUNCT
cana-5239	126	22	−	−	PROPN
cana-5239	126	23	𝑃.	𝑃.	PROPN
cana-5239	126	24	𝑄	𝑄	PRON
cana-5239	126	25	where	where	SCONJ
cana-5239	126	26	r	r	NOUN
cana-5239	126	27	is	be	AUX
cana-5239	126	28	the	the	DET
cana-5239	126	29	distance	distance	NOUN
cana-5239	126	30	between	between	ADP
cana-5239	126	31	the	the	DET
cana-5239	126	32	wolf	wolf	NOUN
cana-5239	126	33	and	and	CCONJ
cana-5239	126	34	the	the	DET
cana-5239	126	35	prey	prey	NOUN
cana-5239	126	36	,	,	PUNCT
cana-5239	126	37	p	p	NOUN
cana-5239	126	38	and	and	CCONJ
cana-5239	126	39	q	q	NOUN
cana-5239	126	40	are	be	AUX
cana-5239	126	41	coefficient	coefficient	ADJ
cana-5239	126	42	vectors	vector	NOUN
cana-5239	126	43	that	that	PRON
cana-5239	126	44	dynamically	dynamically	ADV
cana-5239	126	45	adjust	adjust	VERB
cana-5239	126	46	the	the	DET
cana-5239	126	47	influence	influence	NOUN
cana-5239	126	48	of	of	ADP
cana-5239	126	49	alpha	alpha	NOUN
cana-5239	126	50	,	,	PUNCT
cana-5239	126	51	beta	beta	NOUN
cana-5239	126	52	,	,	PUNCT
cana-5239	126	53	and	and	CCONJ
cana-5239	126	54	delta	delta	NOUN
cana-5239	126	55	wolves	wolf	NOUN
cana-5239	126	56	on	on	ADP
cana-5239	126	57	the	the	DET
cana-5239	126	58	position	position	NOUN
cana-5239	126	59	update	update	NOUN
cana-5239	126	60	and	and	CCONJ
cana-5239	126	61	𝑋𝑏(𝑎	𝑋𝑏(𝑎	NOUN
cana-5239	126	62	)	)	PUNCT
cana-5239	126	63	denotes	denote	VERB
cana-5239	126	64	the	the	DET
cana-5239	126	65	position	position	NOUN
cana-5239	126	66	of	of	ADP
cana-5239	126	67	the	the	DET
cana-5239	126	68	best	good	ADJ
cana-5239	126	69	solution	solution	NOUN
cana-5239	126	70	found	find	VERB
cana-5239	126	71	so	so	ADV
cana-5239	126	72	far	far	ADV
cana-5239	126	73	.	.	PUNCT
cana-5239	127	1	coefficient	coefficient	NOUN
cana-5239	127	2	updates	update	VERB
cana-5239	127	3	:	:	PUNCT
cana-5239	127	4	the	the	DET
cana-5239	127	5	values	value	NOUN
cana-5239	127	6	of	of	ADP
cana-5239	127	7	p	p	NOUN
cana-5239	127	8	and	and	CCONJ
cana-5239	127	9	q	q	NOUN
cana-5239	127	10	are	be	AUX
cana-5239	127	11	updated	update	VERB
cana-5239	127	12	during	during	ADP
cana-5239	127	13	the	the	DET
cana-5239	127	14	optimization	optimization	NOUN
cana-5239	127	15	process	process	NOUN
cana-5239	127	16	to	to	PART
cana-5239	127	17	balance	balance	VERB
cana-5239	127	18	exploration	exploration	NOUN
cana-5239	127	19	and	and	CCONJ
cana-5239	127	20	exploitation	exploitation	NOUN
cana-5239	127	21	:	:	PUNCT
cana-5239	128	1	𝑃	𝑃	NOUN
cana-5239	128	2	=	=	SYM
cana-5239	128	3	2𝑡.	2𝑡.	NUM
cana-5239	128	4	𝑟1	𝑟1	NOUN
cana-5239	128	5	−	−	PROPN
cana-5239	128	6	𝑡	𝑡	PROPN
cana-5239	128	7	𝑄	𝑄	NOUN
cana-5239	128	8	=	=	SYM
cana-5239	128	9	2	2	X
cana-5239	128	10	.	.	X
cana-5239	128	11	𝑟2	𝑟2	NOUN
cana-5239	128	12	where	where	SCONJ
cana-5239	128	13	t	t	PROPN
cana-5239	128	14	denotes	denote	VERB
cana-5239	128	15	the	the	DET
cana-5239	128	16	decreases	decrease	NOUN
cana-5239	128	17	linearly	linearly	ADV
cana-5239	128	18	from	from	ADP
cana-5239	128	19	2	2	NUM
cana-5239	128	20	to	to	ADP
cana-5239	128	21	0	0	NUM
cana-5239	128	22	during	during	ADP
cana-5239	128	23	the	the	DET
cana-5239	128	24	iterations	iteration	NOUN
cana-5239	128	25	,	,	PUNCT
cana-5239	128	26	controlling	control	VERB
cana-5239	128	27	the	the	DET
cana-5239	128	28	explorationexploitation	explorationexploitation	NOUN
cana-5239	128	29	trade	trade	NOUN
cana-5239	128	30	-	-	PUNCT
cana-5239	128	31	off	off	NOUN
cana-5239	128	32	,	,	PUNCT
cana-5239	128	33	𝑟1	𝑟1	NOUN
cana-5239	128	34	and	and	CCONJ
cana-5239	128	35	𝑟2	𝑟2	NOUN
cana-5239	128	36	are	be	AUX
cana-5239	128	37	random	random	ADJ
cana-5239	128	38	vectors	vector	NOUN
cana-5239	128	39	in	in	ADP
cana-5239	128	40	[	[	X
cana-5239	128	41	0	0	NUM
cana-5239	128	42	,	,	PUNCT
cana-5239	128	43	1	1	NUM
cana-5239	128	44	]	]	PUNCT
cana-5239	128	45	to	to	PART
cana-5239	128	46	introduce	introduce	VERB
cana-5239	128	47	stochastic	stochastic	ADJ
cana-5239	128	48	behavior	behavior	NOUN
cana-5239	128	49	.	.	PUNCT
cana-5239	129	1	communications	communication	NOUN
cana-5239	129	2	on	on	ADP
cana-5239	129	3	applied	apply	VERB
cana-5239	129	4	nonlinear	nonlinear	ADJ
cana-5239	129	5	analysis	analysis	NOUN
cana-5239	129	6	issn	issn	NOUN
cana-5239	129	7	:	:	PUNCT
cana-5239	129	8	1074	1074	NUM
cana-5239	129	9	-	-	PUNCT
cana-5239	129	10	133x	133x	NUM
cana-5239	129	11	vol	vol	VERB
cana-5239	129	12	32	32	NUM
cana-5239	129	13	no	no	NOUN
cana-5239	129	14	.	.	PUNCT
cana-5239	130	1	10s	10	NOUN
cana-5239	130	2	(	(	PUNCT
cana-5239	130	3	2025	2025	NUM
cana-5239	130	4	)	)	PUNCT
cana-5239	130	5	1379	1379	NUM
cana-5239	130	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5239	130	7	exploration	exploration	NOUN
cana-5239	130	8	and	and	CCONJ
cana-5239	130	9	exploitation	exploitation	NOUN
cana-5239	130	10	:	:	PUNCT
cana-5239	130	11	exploration	exploration	NOUN
cana-5239	130	12	:	:	PUNCT
cana-5239	130	13	when	when	SCONJ
cana-5239	130	14	|𝑃|	|𝑃|	NOUN
cana-5239	130	15	>	>	SYM
cana-5239	130	16	1	1	NUM
cana-5239	130	17	,	,	PUNCT
cana-5239	130	18	the	the	DET
cana-5239	130	19	wolves	wolf	NOUN
cana-5239	130	20	search	search	VERB
cana-5239	130	21	the	the	DET
cana-5239	130	22	solution	solution	NOUN
cana-5239	130	23	space	space	NOUN
cana-5239	130	24	more	more	ADV
cana-5239	130	25	broadly	broadly	ADV
cana-5239	130	26	,	,	PUNCT
cana-5239	130	27	encouraging	encourage	VERB
cana-5239	130	28	exploration	exploration	NOUN
cana-5239	130	29	.	.	PUNCT
cana-5239	131	1	exploitation	exploitation	NOUN
cana-5239	131	2	:	:	PUNCT
cana-5239	131	3	when	when	SCONJ
cana-5239	131	4	|𝑃|	|𝑃|	VERB
cana-5239	131	5	<	<	X
cana-5239	131	6	1	1	NUM
cana-5239	131	7	,	,	PUNCT
cana-5239	131	8	the	the	DET
cana-5239	131	9	wolves	wolf	NOUN
cana-5239	131	10	focus	focus	VERB
cana-5239	131	11	on	on	ADP
cana-5239	131	12	refining	refine	VERB
cana-5239	131	13	their	their	PRON
cana-5239	131	14	positions	position	NOUN
cana-5239	131	15	around	around	ADP
cana-5239	131	16	the	the	DET
cana-5239	131	17	best	good	ADJ
cana-5239	131	18	solutions	solution	NOUN
cana-5239	131	19	found	find	VERB
cana-5239	131	20	,	,	PUNCT
cana-5239	131	21	enabling	enable	VERB
cana-5239	131	22	exploitation	exploitation	NOUN
cana-5239	131	23	.	.	PUNCT
cana-5239	132	1	fitness	fitness	NOUN
cana-5239	132	2	evaluation	evaluation	NOUN
cana-5239	132	3	:	:	PUNCT
cana-5239	132	4	evaluate	evaluate	VERB
cana-5239	132	5	the	the	DET
cana-5239	132	6	fitness	fitness	NOUN
cana-5239	132	7	(	(	PUNCT
cana-5239	132	8	objective	objective	ADJ
cana-5239	132	9	function	function	NOUN
cana-5239	132	10	value	value	NOUN
cana-5239	132	11	)	)	PUNCT
cana-5239	132	12	of	of	ADP
cana-5239	132	13	each	each	DET
cana-5239	132	14	grey	grey	ADJ
cana-5239	132	15	wolf	wolf	PROPN
cana-5239	132	16	based	base	VERB
cana-5239	132	17	on	on	ADP
cana-5239	132	18	the	the	DET
cana-5239	132	19	current	current	ADJ
cana-5239	132	20	position	position	NOUN
cana-5239	132	21	(	(	PUNCT
cana-5239	132	22	solution	solution	NOUN
cana-5239	132	23	)	)	PUNCT
cana-5239	132	24	.	.	PUNCT
cana-5239	133	1	update	update	VERB
cana-5239	133	2	the	the	DET
cana-5239	133	3	positions	position	NOUN
cana-5239	133	4	of	of	ADP
cana-5239	133	5	the	the	DET
cana-5239	133	6	alpha	alpha	NOUN
cana-5239	133	7	,	,	PUNCT
cana-5239	133	8	beta	beta	NOUN
cana-5239	133	9	,	,	PUNCT
cana-5239	133	10	and	and	CCONJ
cana-5239	133	11	delta	delta	NOUN
cana-5239	133	12	wolves	wolf	NOUN
cana-5239	133	13	if	if	SCONJ
cana-5239	133	14	new	new	ADJ
cana-5239	133	15	better	well	ADJ
cana-5239	133	16	solutions	solution	NOUN
cana-5239	133	17	are	be	AUX
cana-5239	133	18	found	find	VERB
cana-5239	133	19	.	.	PUNCT
cana-5239	134	1	termination	termination	NOUN
cana-5239	134	2	:	:	PUNCT
cana-5239	134	3	repeat	repeat	VERB
cana-5239	134	4	the	the	DET
cana-5239	134	5	position	position	NOUN
cana-5239	134	6	updating	update	VERB
cana-5239	134	7	,	,	PUNCT
cana-5239	134	8	encircling	encircle	VERB
cana-5239	134	9	,	,	PUNCT
cana-5239	134	10	and	and	CCONJ
cana-5239	134	11	fitness	fitness	NOUN
cana-5239	134	12	evaluation	evaluation	NOUN
cana-5239	134	13	steps	step	NOUN
cana-5239	134	14	until	until	SCONJ
cana-5239	134	15	the	the	DET
cana-5239	134	16	maximum	maximum	ADJ
cana-5239	134	17	number	number	NOUN
cana-5239	134	18	of	of	ADP
cana-5239	134	19	iterations	iteration	NOUN
cana-5239	134	20	is	be	AUX
cana-5239	134	21	reached	reach	VERB
cana-5239	134	22	or	or	CCONJ
cana-5239	134	23	the	the	DET
cana-5239	134	24	stopping	stopping	NOUN
cana-5239	134	25	criteria	criterion	NOUN
cana-5239	134	26	(	(	PUNCT
cana-5239	134	27	e.g.	e.g.	ADV
cana-5239	134	28	,	,	PUNCT
cana-5239	134	29	convergence	convergence	NOUN
cana-5239	134	30	)	)	PUNCT
cana-5239	134	31	are	be	AUX
cana-5239	134	32	satisfied	satisfied	ADJ
cana-5239	134	33	.	.	PUNCT
cana-5239	135	1	the	the	DET
cana-5239	135	2	alpha	alpha	ADJ
cana-5239	135	3	wolf	wolf	PROPN
cana-5239	135	4	(	(	PUNCT
cana-5239	135	5	best	good	ADJ
cana-5239	135	6	solution	solution	NOUN
cana-5239	135	7	)	)	PUNCT
cana-5239	135	8	at	at	ADP
cana-5239	135	9	the	the	DET
cana-5239	135	10	end	end	NOUN
cana-5239	135	11	of	of	ADP
cana-5239	135	12	the	the	DET
cana-5239	135	13	optimization	optimization	NOUN
cana-5239	135	14	process	process	NOUN
cana-5239	135	15	is	be	AUX
cana-5239	135	16	considered	consider	VERB
cana-5239	135	17	the	the	DET
cana-5239	135	18	optimal	optimal	ADJ
cana-5239	135	19	solution	solution	NOUN
cana-5239	135	20	.	.	PUNCT
cana-5239	136	1	table	table	NOUN
cana-5239	136	2	3	3	NUM
cana-5239	136	3	:	:	PUNCT
cana-5239	136	4	pseudocode	pseudocode	PROPN
cana-5239	136	5	of	of	ADP
cana-5239	136	6	gwo	gwo	PROPN
cana-5239	136	7	:	:	PUNCT
cana-5239	136	8	pseudocode	pseudocode	PROPN
cana-5239	136	9	of	of	ADP
cana-5239	136	10	gwo	gwo	PROPN
cana-5239	136	11	:	:	PUNCT
cana-5239	136	12	initialize	initialize	VERB
cana-5239	136	13	population	population	NOUN
cana-5239	136	14	of	of	ADP
cana-5239	136	15	grey	grey	ADJ
cana-5239	136	16	wolves	wolf	NOUN
cana-5239	136	17	(	(	PUNCT
cana-5239	136	18	solutions	solution	NOUN
cana-5239	136	19	)	)	PUNCT
cana-5239	136	20	initialize	initialize	VERB
cana-5239	136	21	maximum	maximum	ADJ
cana-5239	136	22	number	number	NOUN
cana-5239	136	23	of	of	ADP
cana-5239	136	24	iterations	iteration	NOUN
cana-5239	136	25	(	(	PUNCT
cana-5239	136	26	maxiter	maxiter	NOUN
cana-5239	136	27	)	)	PUNCT
cana-5239	136	28	initialize	initialize	VERB
cana-5239	136	29	the	the	DET
cana-5239	136	30	alpha	alpha	NOUN
cana-5239	136	31	,	,	PUNCT
cana-5239	136	32	beta	beta	NOUN
cana-5239	136	33	,	,	PUNCT
cana-5239	136	34	and	and	CCONJ
cana-5239	136	35	delta	delta	NOUN
cana-5239	136	36	wolves	wolf	NOUN
cana-5239	136	37	for	for	ADP
cana-5239	136	38	each	each	DET
cana-5239	136	39	iteration	iteration	NOUN
cana-5239	136	40	(	(	PUNCT
cana-5239	136	41	t	t	NOUN
cana-5239	136	42	=	=	SYM
cana-5239	136	43	1	1	NUM
cana-5239	136	44	to	to	PART
cana-5239	136	45	maxiter	maxiter	VERB
cana-5239	136	46	):	):	PUNCT
cana-5239	136	47	for	for	ADP
cana-5239	136	48	each	each	DET
cana-5239	136	49	grey	grey	ADJ
cana-5239	136	50	wolf	wolf	NOUN
cana-5239	136	51	:	:	PUNCT
cana-5239	136	52	update	update	VERB
cana-5239	136	53	position	position	NOUN
cana-5239	136	54	using	use	VERB
cana-5239	136	55	alpha	alpha	NOUN
cana-5239	136	56	,	,	PUNCT
cana-5239	136	57	beta	beta	NOUN
cana-5239	136	58	,	,	PUNCT
cana-5239	136	59	and	and	CCONJ
cana-5239	136	60	delta	delta	NOUN
cana-5239	136	61	positions	position	NOUN
cana-5239	136	62	encircle	encircle	VERB
cana-5239	136	63	the	the	DET
cana-5239	136	64	prey	prey	NOUN
cana-5239	136	65	by	by	ADP
cana-5239	136	66	updating	update	VERB
cana-5239	136	67	position	position	NOUN
cana-5239	136	68	vectors	vector	NOUN
cana-5239	136	69	(	(	PUNCT
cana-5239	136	70	a	a	PRON
cana-5239	136	71	,	,	PUNCT
cana-5239	136	72	c	c	NOUN
cana-5239	136	73	)	)	PUNCT
cana-5239	136	74	update	update	NOUN
cana-5239	136	75	coefficients	coefficient	NOUN
cana-5239	136	76	a	a	PRON
cana-5239	136	77	and	and	CCONJ
cana-5239	136	78	c	c	AUX
cana-5239	136	79	evaluate	evaluate	VERB
cana-5239	136	80	the	the	DET
cana-5239	136	81	fitness	fitness	NOUN
cana-5239	136	82	of	of	ADP
cana-5239	136	83	each	each	DET
cana-5239	136	84	grey	grey	ADJ
cana-5239	136	85	wolf	wolf	PROPN
cana-5239	136	86	update	update	NOUN
cana-5239	136	87	alpha	alpha	NOUN
cana-5239	136	88	,	,	PUNCT
cana-5239	136	89	beta	beta	NOUN
cana-5239	136	90	,	,	PUNCT
cana-5239	136	91	and	and	CCONJ
cana-5239	136	92	delta	delta	NOUN
cana-5239	136	93	based	base	VERB
cana-5239	136	94	on	on	ADP
cana-5239	136	95	fitness	fitness	NOUN
cana-5239	136	96	values	value	NOUN
cana-5239	136	97	if	if	SCONJ
cana-5239	136	98	stopping	stop	VERB
cana-5239	136	99	condition	condition	NOUN
cana-5239	136	100	is	be	AUX
cana-5239	136	101	met	meet	VERB
cana-5239	136	102	,	,	PUNCT
cana-5239	136	103	break	break	VERB
cana-5239	136	104	return	return	VERB
cana-5239	136	105	the	the	DET
cana-5239	136	106	alpha	alpha	ADJ
cana-5239	136	107	wolf	wolf	NOUN
cana-5239	136	108	as	as	SCONJ
cana-5239	136	109	the	the	DET
cana-5239	136	110	best	good	ADJ
cana-5239	136	111	solution	solution	NOUN
cana-5239	136	112	3.4	3.4	NUM
cana-5239	136	113	classification	classification	NOUN
cana-5239	136	114	:	:	PUNCT
cana-5239	136	115	3.4.1	3.4.1	NUM
cana-5239	136	116	adaboost	adaboost	VERB
cana-5239	136	117	an	an	DET
cana-5239	136	118	adaboost	adaboost	ADJ
cana-5239	136	119	classifier	classifier	NOUN
cana-5239	136	120	starts	start	VERB
cana-5239	136	121	by	by	ADP
cana-5239	136	122	fitting	fit	VERB
cana-5239	136	123	a	a	DET
cana-5239	136	124	copy	copy	NOUN
cana-5239	136	125	of	of	ADP
cana-5239	136	126	the	the	DET
cana-5239	136	127	original	original	ADJ
cana-5239	136	128	dataset	dataset	NOUN
cana-5239	136	129	using	use	VERB
cana-5239	136	130	a	a	DET
cana-5239	136	131	copy	copy	NOUN
cana-5239	136	132	of	of	ADP
cana-5239	136	133	the	the	DET
cana-5239	136	134	same	same	ADJ
cana-5239	136	135	classifier	classifier	NOUN
cana-5239	136	136	that	that	PRON
cana-5239	136	137	has	have	AUX
cana-5239	136	138	been	be	AUX
cana-5239	136	139	updated	update	VERB
cana-5239	136	140	to	to	PART
cana-5239	136	141	remove	remove	VERB
cana-5239	136	142	error	error	NOUN
cana-5239	136	143	-	-	PUNCT
cana-5239	136	144	prone	prone	ADJ
cana-5239	136	145	and	and	CCONJ
cana-5239	136	146	inaccurate	inaccurate	ADJ
cana-5239	136	147	data	datum	NOUN
cana-5239	136	148	points	point	NOUN
cana-5239	136	149	.	.	PUNCT
cana-5239	137	1	this	this	PRON
cana-5239	137	2	allows	allow	VERB
cana-5239	137	3	the	the	DET
cana-5239	137	4	subsequent	subsequent	ADJ
cana-5239	137	5	classifiers	classifier	NOUN
cana-5239	137	6	to	to	PART
cana-5239	137	7	concentrate	concentrate	VERB
cana-5239	137	8	on	on	ADP
cana-5239	137	9	the	the	DET
cana-5239	137	10	cases	case	NOUN
cana-5239	137	11	that	that	PRON
cana-5239	137	12	lead	lead	VERB
cana-5239	137	13	to	to	ADP
cana-5239	137	14	greater	great	ADJ
cana-5239	137	15	inaccuracy	inaccuracy	NOUN
cana-5239	137	16	[	[	X
cana-5239	137	17	32	32	NUM
cana-5239	137	18	]	]	PUNCT
cana-5239	137	19	.	.	PUNCT
cana-5239	138	1	adaboost	adaboost	PROPN
cana-5239	138	2	is	be	AUX
cana-5239	138	3	a	a	DET
cana-5239	138	4	type	type	NOUN
cana-5239	138	5	of	of	ADP
cana-5239	138	6	iterative	iterative	ADJ
cana-5239	138	7	calculation	calculation	NOUN
cana-5239	138	8	whose	whose	DET
cana-5239	138	9	basic	basic	ADJ
cana-5239	138	10	idea	idea	NOUN
cana-5239	138	11	is	be	AUX
cana-5239	138	12	to	to	PART
cana-5239	138	13	prepare	prepare	VERB
cana-5239	138	14	multiple	multiple	ADJ
cana-5239	138	15	classifiers	classifier	NOUN
cana-5239	138	16	(	(	PUNCT
cana-5239	138	17	that	that	PRON
cana-5239	138	18	is	be	AUX
cana-5239	138	19	,	,	PUNCT
cana-5239	138	20	weak	weak	ADJ
cana-5239	138	21	classifiers	classifier	NOUN
cana-5239	138	22	)	)	PUNCT
cana-5239	138	23	using	use	VERB
cana-5239	138	24	a	a	DET
cana-5239	138	25	preparation	preparation	NOUN
cana-5239	138	26	set	set	NOUN
cana-5239	138	27	,	,	PUNCT
cana-5239	138	28	and	and	CCONJ
cana-5239	138	29	then	then	ADV
cana-5239	138	30	use	use	VERB
cana-5239	138	31	several	several	ADJ
cana-5239	138	32	different	different	ADJ
cana-5239	138	33	strategies	strategy	NOUN
cana-5239	138	34	to	to	PART
cana-5239	138	35	coordinate	coordinate	VERB
cana-5239	138	36	them	they	PRON
cana-5239	138	37	to	to	PART
cana-5239	138	38	create	create	VERB
cana-5239	138	39	a	a	DET
cana-5239	138	40	more	more	ADV
cana-5239	138	41	grounded	ground	VERB
cana-5239	138	42	classifier	classifier	NOUN
cana-5239	138	43	.	.	PUNCT
cana-5239	139	1	the	the	DET
cana-5239	139	2	computation	computation	NOUN
cana-5239	139	3	itself	itself	PRON
cana-5239	139	4	is	be	AUX
cana-5239	139	5	carried	carry	VERB
cana-5239	139	6	out	out	ADP
cana-5239	139	7	by	by	ADP
cana-5239	139	8	adjusting	adjust	VERB
cana-5239	139	9	the	the	DET
cana-5239	139	10	information	information	NOUN
cana-5239	139	11	flow	flow	NOUN
cana-5239	139	12	,	,	PUNCT
cana-5239	139	13	as	as	SCONJ
cana-5239	139	14	demonstrated	demonstrate	VERB
cana-5239	139	15	by	by	ADP
cana-5239	139	16	the	the	DET
cana-5239	139	17	preparation	preparation	NOUN
cana-5239	139	18	set	set	NOUN
cana-5239	139	19	test	test	NOUN
cana-5239	139	20	's	's	PART
cana-5239	139	21	order	order	NOUN
cana-5239	139	22	amendment	amendment	NOUN
cana-5239	139	23	and	and	CCONJ
cana-5239	139	24	the	the	DET
cana-5239	139	25	final	final	ADJ
cana-5239	139	26	accuracy	accuracy	NOUN
cana-5239	139	27	of	of	ADP
cana-5239	139	28	the	the	DET
cana-5239	139	29	overall	overall	ADJ
cana-5239	139	30	arrangement	arrangement	NOUN
cana-5239	139	31	to	to	PART
cana-5239	139	32	determine	determine	VERB
cana-5239	139	33	each	each	DET
cana-5239	139	34	example	example	NOUN
cana-5239	139	35	's	's	PART
cana-5239	139	36	weight	weight	NOUN
cana-5239	139	37	.	.	PUNCT
cana-5239	140	1	subsequently	subsequently	ADV
cana-5239	140	2	,	,	PUNCT
cana-5239	140	3	forward	forward	ADV
cana-5239	140	4	the	the	DET
cana-5239	140	5	communications	communication	NOUN
cana-5239	140	6	on	on	ADP
cana-5239	140	7	applied	apply	VERB
cana-5239	140	8	nonlinear	nonlinear	ADJ
cana-5239	140	9	analysis	analysis	NOUN
cana-5239	140	10	issn	issn	NOUN
cana-5239	140	11	:	:	PUNCT
cana-5239	140	12	1074	1074	NUM
cana-5239	140	13	-	-	PUNCT
cana-5239	140	14	133x	133x	NUM
cana-5239	140	15	vol	vol	VERB
cana-5239	140	16	32	32	NUM
cana-5239	140	17	no	no	NOUN
cana-5239	140	18	.	.	PUNCT
cana-5239	141	1	10s	10	NOUN
cana-5239	141	2	(	(	PUNCT
cana-5239	141	3	2025	2025	NUM
cana-5239	141	4	)	)	PUNCT
cana-5239	141	5	1380	1380	NUM
cana-5239	142	1	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-5239	142	2	updated	update	VERB
cana-5239	142	3	data	datum	NOUN
cana-5239	142	4	to	to	ADP
cana-5239	142	5	the	the	DET
cana-5239	142	6	lower	low	ADJ
cana-5239	142	7	classifier	classifier	NOUN
cana-5239	142	8	for	for	ADP
cana-5239	142	9	preparation	preparation	NOUN
cana-5239	142	10	.	.	PUNCT
cana-5239	143	1	ultimately	ultimately	ADV
cana-5239	143	2	,	,	PUNCT
cana-5239	143	3	each	each	DET
cana-5239	143	4	preparation	preparation	NOUN
cana-5239	143	5	classifier	classifier	NOUN
cana-5239	143	6	is	be	AUX
cana-5239	143	7	combined	combine	VERB
cana-5239	143	8	to	to	PART
cana-5239	143	9	generate	generate	VERB
cana-5239	143	10	the	the	DET
cana-5239	143	11	official	official	ADJ
cana-5239	143	12	conclusion	conclusion	NOUN
cana-5239	143	13	classifier	classifier	NOUN
cana-5239	143	14	.	.	PUNCT
cana-5239	144	1	1	1	X
cana-5239	144	2	.	.	X
cana-5239	144	3	the	the	DET
cana-5239	144	4	transmission	transmission	NOUN
cana-5239	144	5	of	of	ADP
cana-5239	144	6	the	the	DET
cana-5239	144	7	example	example	NOUN
cana-5239	144	8	,	,	PUNCT
cana-5239	144	9	rather	rather	ADV
cana-5239	144	10	than	than	ADP
cana-5239	144	11	the	the	DET
cana-5239	144	12	resampling	resampling	NOUN
cana-5239	144	13	,	,	PUNCT
cana-5239	144	14	is	be	AUX
cana-5239	144	15	the	the	DET
cana-5239	144	16	focal	focal	ADJ
cana-5239	144	17	point	point	NOUN
cana-5239	144	18	of	of	ADP
cana-5239	144	19	each	each	DET
cana-5239	144	20	modification	modification	NOUN
cana-5239	144	21	;	;	PUNCT
cana-5239	144	22	2	2	X
cana-5239	144	23	.	.	X
cana-5239	145	1	the	the	DET
cana-5239	145	2	misclassified	misclassified	ADJ
cana-5239	145	3	test	test	NOUN
cana-5239	145	4	weight	weight	NOUN
cana-5239	145	5	high	high	ADV
cana-5239	145	6	and	and	CCONJ
cana-5239	145	7	the	the	DET
cana-5239	145	8	arranged	arranged	ADJ
cana-5239	145	9	effectively	effectively	ADV
cana-5239	145	10	test	test	NOUN
cana-5239	145	11	weight	weight	NOUN
cana-5239	145	12	low	low	ADJ
cana-5239	145	13	determine	determine	VERB
cana-5239	145	14	the	the	DET
cana-5239	145	15	difference	difference	NOUN
cana-5239	145	16	in	in	ADP
cana-5239	145	17	test	test	NOUN
cana-5239	145	18	dispersion	dispersion	NOUN
cana-5239	145	19	.	.	PUNCT
cana-5239	146	1	this	this	PRON
cana-5239	146	2	will	will	AUX
cana-5239	146	3	enable	enable	VERB
cana-5239	146	4	the	the	DET
cana-5239	146	5	subsequent	subsequent	ADJ
cana-5239	146	6	classifier	classifier	NOUN
cana-5239	146	7	to	to	PART
cana-5239	146	8	be	be	AUX
cana-5239	146	9	centered	center	VERB
cana-5239	146	10	around	around	ADP
cana-5239	146	11	the	the	DET
cana-5239	146	12	current	current	ADJ
cana-5239	146	13	misclassified	misclassifie	VERB
cana-5239	146	14	tests	test	NOUN
cana-5239	146	15	;	;	PUNCT
cana-5239	146	16	3	3	X
cana-5239	146	17	.	.	NOUN
cana-5239	146	18	to	to	PART
cana-5239	146	19	obtain	obtain	VERB
cana-5239	146	20	the	the	DET
cana-5239	146	21	result	result	NOUN
cana-5239	146	22	,	,	PUNCT
cana-5239	146	23	add	add	VERB
cana-5239	146	24	together	together	ADV
cana-5239	146	25	all	all	PRON
cana-5239	146	26	of	of	ADP
cana-5239	146	27	the	the	DET
cana-5239	146	28	weak	weak	ADJ
cana-5239	146	29	classifiers	classifier	NOUN
cana-5239	146	30	[	[	X
cana-5239	146	31	33	33	NUM
cana-5239	146	32	]	]	PUNCT
cana-5239	146	33	.	.	PUNCT
cana-5239	147	1	as	as	ADP
cana-5239	147	2	a	a	DET
cana-5239	147	3	result	result	NOUN
cana-5239	147	4	,	,	PUNCT
cana-5239	147	5	it	it	PRON
cana-5239	147	6	is	be	AUX
cana-5239	147	7	seen	see	VERB
cana-5239	147	8	that	that	SCONJ
cana-5239	147	9	adaboost	adaboost	ADJ
cana-5239	147	10	concentrates	concentrate	VERB
cana-5239	147	11	on	on	ADP
cana-5239	147	12	the	the	DET
cana-5239	147	13	incorrectly	incorrectly	ADV
cana-5239	147	14	identified	identify	VERB
cana-5239	147	15	points	point	NOUN
cana-5239	147	16	by	by	ADP
cana-5239	147	17	giving	give	VERB
cana-5239	147	18	the	the	DET
cana-5239	147	19	misclassified	misclassifie	VERB
cana-5239	147	20	data	datum	NOUN
cana-5239	147	21	greater	great	ADJ
cana-5239	147	22	weights	weight	NOUN
cana-5239	147	23	,	,	PUNCT
cana-5239	147	24	which	which	PRON
cana-5239	147	25	lowers	lower	VERB
cana-5239	147	26	error	error	NOUN
cana-5239	147	27	and	and	CCONJ
cana-5239	147	28	raises	raise	VERB
cana-5239	147	29	accuracy	accuracy	NOUN
cana-5239	147	30	.	.	PUNCT
cana-5239	148	1	3.4.2	3.4.2	NUM
cana-5239	148	2	xgboost	xgboost	ADP
cana-5239	148	3	extreme	extreme	ADJ
cana-5239	148	4	gradient	gradient	ADJ
cana-5239	148	5	boost	boost	NOUN
cana-5239	148	6	is	be	AUX
cana-5239	148	7	referred	refer	VERB
cana-5239	148	8	to	to	ADP
cana-5239	148	9	as	as	ADP
cana-5239	148	10	xgboost	xgboost	ADV
cana-5239	148	11	.	.	PUNCT
cana-5239	149	1	the	the	DET
cana-5239	149	2	boosting	boost	VERB
cana-5239	149	3	calculation	calculation	NOUN
cana-5239	149	4	's	's	PART
cana-5239	149	5	basic	basic	ADJ
cana-5239	149	6	idea	idea	NOUN
cana-5239	149	7	is	be	AUX
cana-5239	149	8	that	that	SCONJ
cana-5239	149	9	several	several	ADJ
cana-5239	149	10	decision	decision	NOUN
cana-5239	149	11	trees	tree	NOUN
cana-5239	149	12	outperform	outperform	VERB
cana-5239	149	13	a	a	DET
cana-5239	149	14	single	single	ADJ
cana-5239	149	15	one	one	NUM
cana-5239	149	16	.	.	PUNCT
cana-5239	150	1	not	not	PART
cana-5239	150	2	every	every	DET
cana-5239	150	3	decision	decision	NOUN
cana-5239	150	4	tree	tree	NOUN
cana-5239	150	5	will	will	AUX
cana-5239	150	6	present	present	VERB
cana-5239	150	7	well	well	ADV
cana-5239	150	8	.	.	PUNCT
cana-5239	151	1	the	the	DET
cana-5239	151	2	presentation	presentation	NOUN
cana-5239	151	3	starts	start	VERB
cana-5239	151	4	to	to	PART
cana-5239	151	5	get	get	VERB
cana-5239	151	6	better	well	ADJ
cana-5239	151	7	at	at	ADP
cana-5239	151	8	the	the	DET
cana-5239	151	9	point	point	NOUN
cana-5239	151	10	where	where	SCONJ
cana-5239	151	11	several	several	ADJ
cana-5239	151	12	trees	tree	NOUN
cana-5239	151	13	are	be	AUX
cana-5239	151	14	added	add	VERB
cana-5239	151	15	.	.	PUNCT
cana-5239	152	1	the	the	DET
cana-5239	152	2	steps	step	NOUN
cana-5239	152	3	involved	involve	VERB
cana-5239	152	4	in	in	ADP
cana-5239	152	5	xgboost	xgboost	PROPN
cana-5239	152	6	:	:	PUNCT
cana-5239	152	7	1	1	X
cana-5239	152	8	.	.	X
cana-5239	152	9	construct	construct	VERB
cana-5239	152	10	a	a	DET
cana-5239	152	11	standard	standard	NOUN
cana-5239	152	12	set	set	NOUN
cana-5239	152	13	that	that	PRON
cana-5239	152	14	is	be	AUX
cana-5239	152	15	strongly	strongly	ADV
cana-5239	152	16	connected	connect	VERB
cana-5239	152	17	,	,	PUNCT
cana-5239	152	18	and	and	CCONJ
cana-5239	152	19	if	if	SCONJ
cana-5239	152	20	any	any	PRON
cana-5239	152	21	of	of	ADP
cana-5239	152	22	the	the	DET
cana-5239	152	23	elements	element	NOUN
cana-5239	152	24	in	in	ADP
cana-5239	152	25	the	the	DET
cana-5239	152	26	prepared	prepare	VERB
cana-5239	152	27	set	set	NOUN
cana-5239	152	28	are	be	AUX
cana-5239	152	29	constant	constant	ADJ
cana-5239	152	30	,	,	PUNCT
cana-5239	152	31	discretize	discretize	VERB
cana-5239	152	32	the	the	DET
cana-5239	152	33	component	component	NOUN
cana-5239	152	34	vectors	vector	NOUN
cana-5239	152	35	.	.	PUNCT
cana-5239	153	1	2	2	X
cana-5239	153	2	.	.	X
cana-5239	153	3	after	after	ADP
cana-5239	153	4	determining	determine	VERB
cana-5239	153	5	which	which	DET
cana-5239	153	6	principles	principle	NOUN
cana-5239	153	7	produce	produce	VERB
cana-5239	153	8	the	the	DET
cana-5239	153	9	forecast	forecast	NOUN
cana-5239	153	10	mark	mark	NOUN
cana-5239	153	11	,	,	PUNCT
cana-5239	153	12	create	create	VERB
cana-5239	153	13	the	the	DET
cana-5239	153	14	new	new	ADJ
cana-5239	153	15	standard	standard	NOUN
cana-5239	153	16	set	set	NOUN
cana-5239	153	17	.	.	PUNCT
cana-5239	154	1	determine	determine	VERB
cana-5239	154	2	the	the	DET
cana-5239	154	3	lift	lift	NOUN
cana-5239	154	4	of	of	ADP
cana-5239	154	5	every	every	DET
cana-5239	154	6	standard	standard	NOUN
cana-5239	154	7	and	and	CCONJ
cana-5239	154	8	remove	remove	VERB
cana-5239	154	9	the	the	DET
cana-5239	154	10	principles	principle	NOUN
cana-5239	154	11	if	if	SCONJ
cana-5239	154	12	the	the	DET
cana-5239	154	13	lift	lift	NOUN
cana-5239	154	14	is	be	AUX
cana-5239	154	15	less	less	ADJ
cana-5239	154	16	than	than	ADP
cana-5239	154	17	1.0	1.0	NUM
cana-5239	154	18	.	.	PUNCT
cana-5239	155	1	we	we	PRON
cana-5239	155	2	can	can	AUX
cana-5239	155	3	obtain	obtain	VERB
cana-5239	155	4	the	the	DET
cana-5239	155	5	strong	strong	ADJ
cana-5239	155	6	set	set	NOUN
cana-5239	155	7	of	of	ADP
cana-5239	155	8	guidelines	guideline	NOUN
cana-5239	155	9	in	in	ADP
cana-5239	155	10	this	this	DET
cana-5239	155	11	manner	manner	NOUN
cana-5239	155	12	.	.	PUNCT
cana-5239	156	1	3	3	X
cana-5239	156	2	.	.	PUNCT
cana-5239	156	3	the	the	DET
cana-5239	156	4	concepts	concept	NOUN
cana-5239	156	5	in	in	ADP
cana-5239	156	6	the	the	DET
cana-5239	156	7	successful	successful	ADJ
cana-5239	156	8	standard	standard	NOUN
cana-5239	156	9	are	be	AUX
cana-5239	156	10	arranged	arrange	VERB
cana-5239	156	11	according	accord	VERB
cana-5239	156	12	to	to	ADP
cana-5239	156	13	their	their	PRON
cana-5239	156	14	greatest	great	ADJ
cana-5239	156	15	assistance	assistance	NOUN
cana-5239	156	16	,	,	PUNCT
cana-5239	156	17	lift	lift	NOUN
cana-5239	156	18	,	,	PUNCT
cana-5239	156	19	and	and	CCONJ
cana-5239	156	20	brief	brief	ADJ
cana-5239	156	21	length	length	NOUN
cana-5239	156	22	.	.	PUNCT
cana-5239	157	1	4	4	X
cana-5239	157	2	.	.	X
cana-5239	157	3	print	print	VERB
cana-5239	157	4	the	the	DET
cana-5239	157	5	item	item	NOUN
cana-5239	157	6	from	from	ADP
cana-5239	157	7	the	the	DET
cana-5239	157	8	capabilities	capability	NOUN
cana-5239	157	9	list	list	NOUN
cana-5239	157	10	and	and	CCONJ
cana-5239	157	11	exit	exit	NOUN
cana-5239	157	12	if	if	SCONJ
cana-5239	157	13	the	the	DET
cana-5239	157	14	cycle	cycle	NOUN
cana-5239	157	15	record	record	NOUN
cana-5239	157	16	is	be	AUX
cana-5239	157	17	larger	large	ADJ
cana-5239	157	18	than	than	ADP
cana-5239	157	19	the	the	DET
cana-5239	157	20	specified	specify	VERB
cana-5239	157	21	amount	amount	NOUN
cana-5239	157	22	.	.	PUNCT
cana-5239	158	1	if	if	SCONJ
cana-5239	158	2	not	not	PART
cana-5239	158	3	,	,	PUNCT
cana-5239	158	4	we	we	PRON
cana-5239	158	5	extract	extract	VERB
cana-5239	158	6	the	the	DET
cana-5239	158	7	principal	principal	ADJ
cana-5239	158	8	rule	rule	NOUN
cana-5239	158	9	from	from	ADP
cana-5239	158	10	the	the	DET
cana-5239	158	11	effective	effective	ADJ
cana-5239	158	12	standard	standard	ADJ
cana-5239	158	13	set	set	NOUN
cana-5239	158	14	,	,	PUNCT
cana-5239	158	15	append	append	VERB
cana-5239	158	16	its	its	PRON
cana-5239	158	17	outcome	outcome	NOUN
cana-5239	158	18	to	to	ADP
cana-5239	158	19	the	the	DET
cana-5239	158	20	capabilities	capability	NOUN
cana-5239	158	21	list	list	NOUN
cana-5239	158	22	,	,	PUNCT
cana-5239	158	23	and	and	CCONJ
cana-5239	158	24	remove	remove	VERB
cana-5239	158	25	the	the	DET
cana-5239	158	26	standard	standard	NOUN
cana-5239	158	27	from	from	ADP
cana-5239	158	28	the	the	DET
cana-5239	158	29	set	set	NOUN
cana-5239	158	30	of	of	ADP
cana-5239	158	31	workable	workable	ADJ
cana-5239	158	32	principles	principle	NOUN
cana-5239	158	33	.	.	PUNCT
cana-5239	159	1	the	the	DET
cana-5239	159	2	component	component	NOUN
cana-5239	159	3	that	that	PRON
cana-5239	159	4	is	be	AUX
cana-5239	159	5	now	now	ADV
cana-5239	159	6	listed	list	VERB
cana-5239	159	7	among	among	ADP
cana-5239	159	8	the	the	DET
cana-5239	159	9	capabilities	capability	NOUN
cana-5239	159	10	does	do	AUX
cana-5239	159	11	n't	not	PART
cana-5239	159	12	need	need	VERB
cana-5239	159	13	to	to	PART
cana-5239	159	14	be	be	AUX
cana-5239	159	15	included	include	VERB
cana-5239	159	16	.	.	PUNCT
cana-5239	160	1	5	5	X
cana-5239	160	2	.	.	X
cana-5239	160	3	remove	remove	VERB
cana-5239	160	4	instances	instance	NOUN
cana-5239	160	5	that	that	PRON
cana-5239	160	6	meet	meet	VERB
cana-5239	160	7	the	the	DET
cana-5239	160	8	requirements	requirement	NOUN
cana-5239	160	9	,	,	PUNCT
cana-5239	160	10	then	then	ADV
cana-5239	160	11	determine	determine	VERB
cana-5239	160	12	lift	lift	NOUN
cana-5239	160	13	and	and	CCONJ
cana-5239	160	14	backing	backing	NOUN
cana-5239	160	15	for	for	ADP
cana-5239	160	16	the	the	DET
cana-5239	160	17	remaining	remain	VERB
cana-5239	160	18	preparation	preparation	NOUN
cana-5239	160	19	set	set	NOUN
cana-5239	160	20	.	.	PUNCT
cana-5239	161	1	6	6	X
cana-5239	161	2	.	.	X
cana-5239	161	3	go	go	VERB
cana-5239	161	4	to	to	PART
cana-5239	161	5	step	step	VERB
cana-5239	161	6	4	4	NUM
cana-5239	161	7	after	after	ADP
cana-5239	161	8	sorting	sort	VERB
cana-5239	161	9	the	the	DET
cana-5239	161	10	requirements	requirement	NOUN
cana-5239	161	11	according	accord	VERB
cana-5239	161	12	to	to	ADP
cana-5239	161	13	the	the	DET
cana-5239	161	14	workable	workable	ADJ
cana-5239	161	15	principle	principle	NOUN
cana-5239	161	16	of	of	ADP
cana-5239	161	17	maximum	maximum	ADJ
cana-5239	161	18	assistance	assistance	NOUN
cana-5239	161	19	,	,	PUNCT
cana-5239	161	20	most	most	ADV
cana-5239	161	21	extreme	extreme	ADJ
cana-5239	161	22	lift	lift	NOUN
cana-5239	161	23	.	.	PUNCT
cana-5239	162	1	xgboost	xgboost	X
cana-5239	162	2	is	be	AUX
cana-5239	162	3	an	an	DET
cana-5239	162	4	inclination	inclination	NOUN
cana-5239	162	5	boosting	boost	VERB
cana-5239	162	6	system	system	NOUN
cana-5239	162	7	-	-	PUNCT
cana-5239	162	8	based	base	VERB
cana-5239	162	9	decision	decision	NOUN
cana-5239	162	10	tree	tree	NOUN
cana-5239	162	11	-	-	PUNCT
cana-5239	162	12	based	base	VERB
cana-5239	162	13	machine	machine	NOUN
cana-5239	162	14	learning	learn	VERB
cana-5239	162	15	calculation	calculation	NOUN
cana-5239	162	16	.	.	PUNCT
cana-5239	163	1	in	in	ADP
cana-5239	163	2	forecast	forecast	NOUN
cana-5239	163	3	problems	problem	NOUN
cana-5239	163	4	involving	involve	VERB
cana-5239	163	5	unstructured	unstructured	ADJ
cana-5239	163	6	data	datum	NOUN
cana-5239	163	7	(	(	PUNCT
cana-5239	163	8	images	image	NOUN
cana-5239	163	9	,	,	PUNCT
cana-5239	163	10	text	text	NOUN
cana-5239	163	11	,	,	PUNCT
cana-5239	163	12	etc	etc	X
cana-5239	163	13	.	.	X
cana-5239	163	14	)	)	PUNCT
cana-5239	163	15	,	,	PUNCT
cana-5239	163	16	artificial	artificial	ADJ
cana-5239	163	17	neural	neural	ADJ
cana-5239	163	18	networks	network	NOUN
cana-5239	163	19	will	will	AUX
cana-5239	163	20	typically	typically	ADV
cana-5239	163	21	outperform	outperform	VERB
cana-5239	163	22	all	all	DET
cana-5239	163	23	other	other	ADJ
cana-5239	163	24	computations	computation	NOUN
cana-5239	163	25	and	and	CCONJ
cana-5239	163	26	structures	structure	NOUN
cana-5239	163	27	.	.	PUNCT
cana-5239	164	1	nevertheless	nevertheless	ADV
cana-5239	164	2	,	,	PUNCT
cana-5239	164	3	decision	decision	NOUN
cana-5239	164	4	tree	tree	NOUN
cana-5239	164	5	based	base	VERB
cana-5239	164	6	computations	computation	NOUN
cana-5239	164	7	are	be	AUX
cana-5239	164	8	thought	think	VERB
cana-5239	164	9	to	to	PART
cana-5239	164	10	be	be	AUX
cana-5239	164	11	the	the	DET
cana-5239	164	12	most	most	ADV
cana-5239	164	13	effective	effective	ADJ
cana-5239	164	14	for	for	ADP
cana-5239	164	15	little	little	ADJ
cana-5239	164	16	to	to	PART
cana-5239	164	17	medium	medium	ADJ
cana-5239	164	18	organized	organize	VERB
cana-5239	164	19	/	/	SYM
cana-5239	164	20	forbidden	forbid	VERB
cana-5239	164	21	data	datum	NOUN
cana-5239	164	22	.	.	PUNCT
cana-5239	165	1	3.4.3	3.4.3	NUM
cana-5239	165	2	gradient	gradient	NOUN
cana-5239	165	3	boost	boost	NOUN
cana-5239	165	4	gradient	gradient	NOUN
cana-5239	165	5	boosting	boosting	NOUN
cana-5239	165	6	is	be	AUX
cana-5239	165	7	a	a	DET
cana-5239	165	8	machine	machine	NOUN
cana-5239	165	9	learning	learning	NOUN
cana-5239	165	10	technique	technique	NOUN
cana-5239	165	11	used	use	VERB
cana-5239	165	12	for	for	ADP
cana-5239	165	13	regression	regression	NOUN
cana-5239	165	14	and	and	CCONJ
cana-5239	165	15	classification	classification	NOUN
cana-5239	165	16	problems	problem	NOUN
cana-5239	165	17	,	,	PUNCT
cana-5239	165	18	which	which	PRON
cana-5239	165	19	builds	build	VERB
cana-5239	165	20	a	a	DET
cana-5239	165	21	predictive	predictive	ADJ
cana-5239	165	22	model	model	NOUN
cana-5239	165	23	in	in	ADP
cana-5239	165	24	a	a	DET
cana-5239	165	25	stage	stage	NOUN
cana-5239	165	26	-	-	PUNCT
cana-5239	165	27	wise	wise	ADJ
cana-5239	165	28	fashion	fashion	NOUN
cana-5239	165	29	.	.	PUNCT
cana-5239	166	1	it	it	PRON
cana-5239	166	2	creates	create	VERB
cana-5239	166	3	a	a	DET
cana-5239	166	4	strong	strong	ADJ
cana-5239	166	5	predictive	predictive	ADJ
cana-5239	166	6	model	model	NOUN
cana-5239	166	7	by	by	ADP
cana-5239	166	8	combining	combine	VERB
cana-5239	166	9	multiple	multiple	ADJ
cana-5239	166	10	weak	weak	ADJ
cana-5239	166	11	learners	learner	NOUN
cana-5239	166	12	,	,	PUNCT
cana-5239	166	13	typically	typically	ADV
cana-5239	166	14	decision	decision	VERB
cana-5239	166	15	trees	tree	NOUN
cana-5239	166	16	.	.	PUNCT
cana-5239	167	1	the	the	DET
cana-5239	167	2	main	main	ADJ
cana-5239	167	3	idea	idea	NOUN
cana-5239	167	4	is	be	AUX
cana-5239	167	5	to	to	PART
cana-5239	167	6	correct	correct	VERB
cana-5239	167	7	the	the	DET
cana-5239	167	8	errors	error	NOUN
cana-5239	167	9	made	make	VERB
cana-5239	167	10	by	by	ADP
cana-5239	167	11	the	the	DET
cana-5239	167	12	previous	previous	ADJ
cana-5239	167	13	models	model	NOUN
cana-5239	167	14	,	,	PUNCT
cana-5239	167	15	effectively	effectively	ADV
cana-5239	167	16	boosting	boost	VERB
cana-5239	167	17	their	their	PRON
cana-5239	167	18	performance	performance	NOUN
cana-5239	167	19	.	.	PUNCT
cana-5239	168	1	the	the	DET
cana-5239	168	2	algorithm	algorithm	NOUN
cana-5239	168	3	works	work	VERB
cana-5239	168	4	by	by	ADP
cana-5239	168	5	communications	communication	NOUN
cana-5239	168	6	on	on	ADP
cana-5239	168	7	applied	apply	VERB
cana-5239	168	8	nonlinear	nonlinear	ADJ
cana-5239	168	9	analysis	analysis	NOUN
cana-5239	168	10	issn	issn	NOUN
cana-5239	168	11	:	:	PUNCT
cana-5239	168	12	1074	1074	NUM
cana-5239	168	13	-	-	PUNCT
cana-5239	168	14	133x	133x	NUM
cana-5239	168	15	vol	vol	VERB
cana-5239	168	16	32	32	NUM
cana-5239	168	17	no	no	NOUN
cana-5239	168	18	.	.	PUNCT
cana-5239	169	1	10s	10	NOUN
cana-5239	169	2	(	(	PUNCT
cana-5239	169	3	2025	2025	NUM
cana-5239	169	4	)	)	PUNCT
cana-5239	169	5	1381	1381	NUM
cana-5239	169	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5239	169	7	sequentially	sequentially	ADV
cana-5239	169	8	adding	add	VERB
cana-5239	169	9	models	model	NOUN
cana-5239	169	10	,	,	PUNCT
cana-5239	169	11	where	where	SCONJ
cana-5239	169	12	each	each	DET
cana-5239	169	13	new	new	ADJ
cana-5239	169	14	model	model	NOUN
cana-5239	169	15	is	be	AUX
cana-5239	169	16	trained	train	VERB
cana-5239	169	17	to	to	PART
cana-5239	169	18	predict	predict	VERB
cana-5239	169	19	the	the	DET
cana-5239	169	20	residuals	residual	NOUN
cana-5239	169	21	(	(	PUNCT
cana-5239	169	22	errors	error	NOUN
cana-5239	169	23	)	)	PUNCT
cana-5239	169	24	of	of	ADP
cana-5239	169	25	the	the	DET
cana-5239	169	26	existing	exist	VERB
cana-5239	169	27	ensemble	ensemble	NOUN
cana-5239	169	28	of	of	ADP
cana-5239	169	29	models	model	NOUN
cana-5239	169	30	.	.	PUNCT
cana-5239	170	1	the	the	DET
cana-5239	170	2	final	final	ADJ
cana-5239	170	3	prediction	prediction	NOUN
cana-5239	170	4	is	be	AUX
cana-5239	170	5	obtained	obtain	VERB
cana-5239	170	6	by	by	ADP
cana-5239	170	7	aggregating	aggregate	VERB
cana-5239	170	8	the	the	DET
cana-5239	170	9	predictions	prediction	NOUN
cana-5239	170	10	of	of	ADP
cana-5239	170	11	all	all	DET
cana-5239	170	12	models	model	NOUN
cana-5239	170	13	.	.	PUNCT
cana-5239	171	1	3.4.4	3.4.4	NUM
cana-5239	171	2	catboost	catboost	NOUN
cana-5239	171	3	catboost	catboost	PROPN
cana-5239	171	4	is	be	AUX
cana-5239	171	5	a	a	DET
cana-5239	171	6	gradient	gradient	NOUN
cana-5239	171	7	-	-	PUNCT
cana-5239	171	8	boosting	boost	VERB
cana-5239	171	9	decision	decision	NOUN
cana-5239	171	10	tree	tree	NOUN
cana-5239	171	11	(	(	PUNCT
cana-5239	171	12	gbdt	gbdt	NOUN
cana-5239	171	13	)	)	PUNCT
cana-5239	171	14	architecture	architecture	NOUN
cana-5239	171	15	that	that	PRON
cana-5239	171	16	uses	use	VERB
cana-5239	171	17	fewer	few	ADJ
cana-5239	171	18	parameters	parameter	NOUN
cana-5239	171	19	and	and	CCONJ
cana-5239	171	20	an	an	DET
cana-5239	171	21	oblivious	oblivious	ADJ
cana-5239	171	22	tree	tree	NOUN
cana-5239	171	23	as	as	ADP
cana-5239	171	24	the	the	DET
cana-5239	171	25	basis	basis	NOUN
cana-5239	171	26	learner	learner	NOUN
cana-5239	171	27	.	.	PUNCT
cana-5239	172	1	it	it	PRON
cana-5239	172	2	attains	attain	VERB
cana-5239	172	3	great	great	ADJ
cana-5239	172	4	accuracy	accuracy	NOUN
cana-5239	172	5	while	while	SCONJ
cana-5239	172	6	supporting	support	VERB
cana-5239	172	7	categorical	categorical	ADJ
cana-5239	172	8	variables	variable	NOUN
cana-5239	172	9	.	.	PUNCT
cana-5239	173	1	uses	use	VERB
cana-5239	173	2	the	the	DET
cana-5239	173	3	boosting	boost	VERB
cana-5239	173	4	approaches	approach	NOUN
cana-5239	173	5	to	to	PART
cana-5239	173	6	train	train	VERB
cana-5239	173	7	a	a	DET
cana-5239	173	8	sequence	sequence	NOUN
cana-5239	173	9	of	of	ADP
cana-5239	173	10	learners	learner	NOUN
cana-5239	173	11	serially	serially	ADV
cana-5239	173	12	,	,	PUNCT
cana-5239	173	13	accumulating	accumulate	VERB
cana-5239	173	14	the	the	DET
cana-5239	173	15	outputs	output	NOUN
cana-5239	173	16	of	of	ADP
cana-5239	173	17	all	all	DET
cana-5239	173	18	learners	learner	NOUN
cana-5239	173	19	as	as	ADP
cana-5239	173	20	a	a	DET
cana-5239	173	21	result	result	NOUN
cana-5239	173	22	[	[	X
cana-5239	173	23	34	34	NUM
cana-5239	173	24	-	-	SYM
cana-5239	173	25	35	35	NUM
cana-5239	173	26	]	]	PUNCT
cana-5239	173	27	,	,	PUNCT
cana-5239	173	28	increasing	increase	VERB
cana-5239	173	29	the	the	DET
cana-5239	173	30	algorithm	algorithm	NOUN
cana-5239	173	31	's	's	PART
cana-5239	173	32	accuracy	accuracy	NOUN
cana-5239	173	33	and	and	CCONJ
cana-5239	173	34	applicability	applicability	NOUN
cana-5239	173	35	.	.	PUNCT
cana-5239	174	1	given	give	VERB
cana-5239	174	2	a	a	DET
cana-5239	174	3	training	training	NOUN
cana-5239	174	4	set	set	NOUN
cana-5239	174	5	containing	contain	VERB
cana-5239	174	6	n	n	DET
cana-5239	174	7	samples	sample	NOUN
cana-5239	174	8	,	,	PUNCT
cana-5239	174	9	d{(𝐴𝑥	d{(𝐴𝑥	NOUN
cana-5239	174	10	,	,	PUNCT
cana-5239	174	11	𝐵𝑥)𝑥=1,2,⋯,𝑛	𝐵𝑥)𝑥=1,2,⋯,𝑛	NOUN
cana-5239	174	12	}	}	PUNCT
cana-5239	174	13	where	where	SCONJ
cana-5239	174	14	𝐵𝑥	𝐵𝑥	PROPN
cana-5239	174	15	=	=	SYM
cana-5239	174	16	(	(	PUNCT
cana-5239	174	17	𝑏𝑥	𝑏𝑥	PROPN
cana-5239	174	18	1	1	NUM
cana-5239	174	19	,	,	PUNCT
cana-5239	174	20	𝑏𝑥	𝑏𝑥	PROPN
cana-5239	174	21	2	2	NUM
cana-5239	174	22	,	,	PUNCT
cana-5239	174	23	⋯	⋯	PROPN
cana-5239	174	24	,	,	PUNCT
cana-5239	174	25	𝑏𝑥	𝑏𝑥	PROPN
cana-5239	174	26	𝑛	𝑛	PROPN
cana-5239	174	27	)	)	PUNCT
cana-5239	174	28	stands	stand	VERB
cana-5239	174	29	for	for	ADP
cana-5239	174	30	labeled	label	VERB
cana-5239	174	31	values	value	NOUN
cana-5239	174	32	and	and	CCONJ
cana-5239	174	33	𝐵𝑥	𝐵𝑥	PROPN
cana-5239	174	34	∈	∈	PROPN
cana-5239	174	35	𝑅	𝑅	PROPN
cana-5239	174	36	stands	stand	VERB
cana-5239	174	37	for	for	ADP
cana-5239	174	38	the	the	DET
cana-5239	174	39	m	m	ADJ
cana-5239	174	40	-	-	ADJ
cana-5239	174	41	dimensional	dimensional	ADJ
cana-5239	174	42	input	input	NOUN
cana-5239	174	43	features	feature	NOUN
cana-5239	174	44	.	.	PUNCT
cana-5239	175	1	the	the	DET
cana-5239	175	2	next	next	ADJ
cana-5239	175	3	training	training	NOUN
cana-5239	175	4	round	round	NOUN
cana-5239	175	5	's	's	PART
cana-5239	175	6	objective	objective	NOUN
cana-5239	175	7	is	be	AUX
cana-5239	175	8	to	to	PART
cana-5239	175	9	select	select	VERB
cana-5239	175	10	a	a	DET
cana-5239	175	11	tree	tree	NOUN
cana-5239	175	12	𝑡𝑟	𝑡𝑟	VERB
cana-5239	175	13	from	from	ADP
cana-5239	175	14	the	the	DET
cana-5239	175	15	cart	cart	NOUN
cana-5239	175	16	decision	decision	NOUN
cana-5239	175	17	tree	tree	NOUN
cana-5239	175	18	set	set	VERB
cana-5239	175	19	t	t	NOUN
cana-5239	175	20	in	in	ADP
cana-5239	175	21	order	order	NOUN
cana-5239	175	22	to	to	PART
cana-5239	175	23	minimize	minimize	VERB
cana-5239	175	24	the	the	DET
cana-5239	175	25	expectation	expectation	NOUN
cana-5239	175	26	e	e	NOUN
cana-5239	175	27	(	(	PUNCT
cana-5239	175	28	·	·	PUNCT
cana-5239	175	29	)	)	PUNCT
cana-5239	175	30	of	of	ADP
cana-5239	175	31	the	the	DET
cana-5239	175	32	loss	loss	NOUN
cana-5239	175	33	function	function	NOUN
cana-5239	175	34	l	l	NOUN
cana-5239	175	35	(	(	PUNCT
cana-5239	175	36	·	·	PUNCT
cana-5239	175	37	)	)	PUNCT
cana-5239	175	38	,	,	PUNCT
cana-5239	175	39	with	with	ADP
cana-5239	175	40	the	the	DET
cana-5239	175	41	strong	strong	ADJ
cana-5239	175	42	learner	learner	NOUN
cana-5239	175	43	created	create	VERB
cana-5239	175	44	after	after	ADP
cana-5239	175	45	training	train	VERB
cana-5239	175	46	being	be	AUX
cana-5239	175	47	𝑉𝑟−1	𝑉𝑟−1	NUM
cana-5239	175	48	.	.	PUNCT
cana-5239	176	1	here	here	ADV
cana-5239	176	2	is	be	AUX
cana-5239	176	3	how	how	SCONJ
cana-5239	176	4	the	the	DET
cana-5239	176	5	parameter	parameter	NOUN
cana-5239	176	6	𝑡𝑟	𝑡𝑟	NOUN
cana-5239	176	7	is	be	AUX
cana-5239	176	8	computed	compute	VERB
cana-5239	176	9	where	where	SCONJ
cana-5239	176	10	test	test	NOUN
cana-5239	176	11	samples	sample	NOUN
cana-5239	176	12	(	(	PUNCT
cana-5239	176	13	a	a	DET
cana-5239	176	14	,	,	PUNCT
cana-5239	176	15	b	b	NOUN
cana-5239	176	16	)	)	PUNCT
cana-5239	176	17	is	be	AUX
cana-5239	176	18	not	not	PART
cana-5239	176	19	part	part	NOUN
cana-5239	176	20	of	of	ADP
cana-5239	176	21	the	the	DET
cana-5239	176	22	training	training	NOUN
cana-5239	176	23	set	set	NOUN
cana-5239	176	24	.	.	PUNCT
cana-5239	177	1	the	the	DET
cana-5239	177	2	trained	train	VERB
cana-5239	177	3	cart	cart	NOUN
cana-5239	177	4	decision	decision	NOUN
cana-5239	177	5	tree	tree	NOUN
cana-5239	177	6	𝑡𝑟	𝑡𝑟	NOUN
cana-5239	177	7	is	be	AUX
cana-5239	177	8	fitted	fit	VERB
cana-5239	177	9	by	by	ADP
cana-5239	177	10	the	the	DET
cana-5239	177	11	gbdt	gbdt	NOUN
cana-5239	177	12	using	use	VERB
cana-5239	177	13	the	the	DET
cana-5239	177	14	negative	negative	ADJ
cana-5239	177	15	gradient	gradient	NOUN
cana-5239	177	16	of	of	ADP
cana-5239	177	17	the	the	DET
cana-5239	177	18	loss	loss	NOUN
cana-5239	177	19	function	function	NOUN
cana-5239	177	20	and	and	CCONJ
cana-5239	177	21	after	after	ADP
cana-5239	177	22	n	n	PRON
cana-5239	177	23	iterations	iteration	NOUN
cana-5239	177	24	,	,	PUNCT
cana-5239	177	25	the	the	DET
cana-5239	177	26	final	final	ADJ
cana-5239	177	27	model	model	NOUN
cana-5239	177	28	m	m	PROPN
cana-5239	177	29	,	,	PUNCT
cana-5239	177	30	represented	represent	VERB
cana-5239	177	31	in	in	ADP
cana-5239	177	32	equation	equation	NOUN
cana-5239	177	33	(	(	PUNCT
cana-5239	177	34	2	2	NUM
cana-5239	177	35	)	)	PUNCT
cana-5239	177	36	,	,	PUNCT
cana-5239	177	37	is	be	AUX
cana-5239	177	38	produced	produce	VERB
cana-5239	177	39	from	from	ADP
cana-5239	177	40	the	the	DET
cana-5239	177	41	initial	initial	ADJ
cana-5239	177	42	weak	weak	ADJ
cana-5239	177	43	learner	learner	NOUN
cana-5239	177	44	𝑊0	𝑊0	PROPN
cana-5239	177	45	and	and	CCONJ
cana-5239	177	46	the	the	DET
cana-5239	177	47	n	n	CCONJ
cana-5239	177	48	-	-	PUNCT
cana-5239	177	49	th	th	VERB
cana-5239	177	50	round	round	NOUN
cana-5239	177	51	of	of	ADP
cana-5239	177	52	the	the	DET
cana-5239	177	53	training	training	NOUN
cana-5239	177	54	step	step	NOUN
cana-5239	177	55	size	size	NOUN
cana-5239	177	56	4	4	NUM
cana-5239	177	57	.	.	PUNCT
cana-5239	177	58	experimental	experimental	ADJ
cana-5239	177	59	result	result	NOUN
cana-5239	177	60	this	this	DET
cana-5239	177	61	section	section	NOUN
cana-5239	177	62	,	,	PUNCT
cana-5239	177	63	evaluate	evaluate	VERB
cana-5239	177	64	and	and	CCONJ
cana-5239	177	65	discuss	discuss	VERB
cana-5239	177	66	the	the	DET
cana-5239	177	67	performance	performance	NOUN
cana-5239	177	68	of	of	ADP
cana-5239	177	69	the	the	DET
cana-5239	177	70	ensemble	ensemble	ADJ
cana-5239	177	71	learning	learning	NOUN
cana-5239	177	72	models	model	NOUN
cana-5239	177	73	(	(	PUNCT
cana-5239	177	74	adaboost	adaboost	ADV
cana-5239	177	75	,	,	PUNCT
cana-5239	177	76	xgboost	xgboost	ADV
cana-5239	177	77	,	,	PUNCT
cana-5239	177	78	catboost	catboost	ADJ
cana-5239	177	79	,	,	PUNCT
cana-5239	177	80	and	and	CCONJ
cana-5239	177	81	gradient	gradient	ADJ
cana-5239	177	82	boosting	boosting	NOUN
cana-5239	177	83	)	)	PUNCT
cana-5239	177	84	applied	apply	VERB
cana-5239	177	85	to	to	ADP
cana-5239	177	86	agriculture	agriculture	NOUN
cana-5239	177	87	commodity	commodity	NOUN
cana-5239	177	88	price	price	NOUN
cana-5239	177	89	prediction	prediction	NOUN
cana-5239	177	90	,	,	PUNCT
cana-5239	177	91	using	use	VERB
cana-5239	177	92	multiple	multiple	ADJ
cana-5239	177	93	feature	feature	NOUN
cana-5239	177	94	selection	selection	NOUN
cana-5239	177	95	techniques	technique	NOUN
cana-5239	177	96	.	.	PUNCT
cana-5239	178	1	the	the	DET
cana-5239	178	2	dataset	dataset	NOUN
cana-5239	178	3	was	be	AUX
cana-5239	178	4	split	split	VERB
cana-5239	178	5	into	into	ADP
cana-5239	178	6	two	two	NUM
cana-5239	178	7	subsets	subset	NOUN
cana-5239	178	8	:	:	PUNCT
cana-5239	178	9	80	80	NUM
cana-5239	178	10	%	%	NOUN
cana-5239	178	11	for	for	ADP
cana-5239	178	12	training	training	NOUN
cana-5239	178	13	and	and	CCONJ
cana-5239	178	14	20	20	NUM
cana-5239	178	15	%	%	NOUN
cana-5239	178	16	for	for	ADP
cana-5239	178	17	testing	testing	NOUN
cana-5239	178	18	.	.	PUNCT
cana-5239	179	1	a	a	DET
cana-5239	179	2	5	5	NUM
cana-5239	179	3	-	-	ADJ
cana-5239	179	4	fold	fold	ADJ
cana-5239	179	5	cross	cross	ADJ
cana-5239	179	6	-	-	ADJ
cana-5239	179	7	validation	validation	ADJ
cana-5239	179	8	technique	technique	NOUN
cana-5239	179	9	was	be	AUX
cana-5239	179	10	employed	employ	VERB
cana-5239	179	11	on	on	ADP
cana-5239	179	12	the	the	DET
cana-5239	179	13	training	training	NOUN
cana-5239	179	14	data	datum	NOUN
cana-5239	179	15	to	to	PART
cana-5239	179	16	ensure	ensure	VERB
cana-5239	179	17	model	model	NOUN
cana-5239	179	18	robustness	robustness	NOUN
cana-5239	179	19	and	and	CCONJ
cana-5239	179	20	to	to	PART
cana-5239	179	21	avoid	avoid	VERB
cana-5239	179	22	overfitting	overfitte	VERB
cana-5239	179	23	.	.	PUNCT
cana-5239	180	1	the	the	DET
cana-5239	180	2	models	model	NOUN
cana-5239	180	3	were	be	AUX
cana-5239	180	4	evaluated	evaluate	VERB
cana-5239	180	5	using	use	VERB
cana-5239	180	6	several	several	ADJ
cana-5239	180	7	performance	performance	NOUN
cana-5239	180	8	metrics	metric	NOUN
cana-5239	180	9	,	,	PUNCT
cana-5239	180	10	including	include	VERB
cana-5239	180	11	accuracy	accuracy	NOUN
cana-5239	180	12	,	,	PUNCT
cana-5239	180	13	precision	precision	NOUN
cana-5239	180	14	,	,	PUNCT
cana-5239	180	15	recall	recall	NOUN
cana-5239	180	16	,	,	PUNCT
cana-5239	180	17	f1	f1	NOUN
cana-5239	180	18	score	score	NOUN
cana-5239	180	19	,	,	PUNCT
cana-5239	180	20	root	root	NOUN
cana-5239	180	21	mean	mean	VERB
cana-5239	180	22	squared	square	VERB
cana-5239	180	23	error	error	NOUN
cana-5239	180	24	(	(	PUNCT
cana-5239	180	25	rmse	rmse	NOUN
cana-5239	180	26	)	)	PUNCT
cana-5239	180	27	,	,	PUNCT
cana-5239	180	28	cohen	cohen	PROPN
cana-5239	180	29	's	's	PART
cana-5239	180	30	kappa	kappa	PROPN
cana-5239	180	31	,	,	PUNCT
cana-5239	180	32	and	and	CCONJ
cana-5239	180	33	matthews	matthews	PROPN
cana-5239	180	34	correlation	correlation	NOUN
cana-5239	180	35	coefficient	coefficient	NOUN
cana-5239	180	36	(	(	PUNCT
cana-5239	180	37	mcc	mcc	NOUN
cana-5239	180	38	)	)	PUNCT
cana-5239	180	39	.	.	PUNCT
cana-5239	181	1	table	table	NOUN
cana-5239	181	2	4	4	NUM
cana-5239	181	3	.	.	PUNCT
cana-5239	181	4	performance	performance	NOUN
cana-5239	181	5	metrics	metric	NOUN
cana-5239	181	6	of	of	ADP
cana-5239	181	7	ensemble	ensemble	ADJ
cana-5239	181	8	classifiers	classifier	NOUN
cana-5239	181	9	with	with	ADP
cana-5239	181	10	different	different	ADJ
cana-5239	181	11	feature	feature	NOUN
cana-5239	181	12	selection	selection	NOUN
cana-5239	181	13	methods	method	NOUN
cana-5239	181	14	feature	feature	VERB
cana-5239	181	15	selection	selection	NOUN
cana-5239	181	16	method	method	NOUN
cana-5239	181	17	classifier	classifier	NOUN
cana-5239	181	18	precision	precision	PROPN
cana-5239	181	19	recall	recall	NOUN
cana-5239	181	20	f1	f1	PROPN
cana-5239	181	21	score	score	NOUN
cana-5239	181	22	accuracy	accuracy	NOUN
cana-5239	181	23	rmse	rmse	PROPN
cana-5239	181	24	mcc	mcc	PROPN
cana-5239	181	25	kappa	kappa	PROPN
cana-5239	181	26	principal	principal	PROPN
cana-5239	181	27	component	component	NOUN
cana-5239	181	28	analysis	analysis	NOUN
cana-5239	181	29	(	(	PUNCT
cana-5239	181	30	pca	pca	NOUN
cana-5239	181	31	)	)	PUNCT
cana-5239	181	32	adaboost	adaboost	VERB
cana-5239	181	33	82.02	82.02	NUM
cana-5239	181	34	81.95	81.95	NUM
cana-5239	181	35	81.93	81.93	NUM
cana-5239	181	36	81.94	81.94	NUM
cana-5239	181	37	0.42	0.42	NUM
cana-5239	181	38	0.63	0.63	NUM
cana-5239	181	39	0.63	0.63	NUM
cana-5239	181	40	gradient	gradient	NOUN
cana-5239	181	41	boosting	boost	VERB
cana-5239	181	42	83.48	83.48	NUM
cana-5239	181	43	83.35	83.35	NUM
cana-5239	181	44	83.31	83.31	NUM
cana-5239	181	45	83.33	83.33	NUM
cana-5239	181	46	0.40	0.40	NUM
cana-5239	181	47	0.66	0.66	NUM
cana-5239	181	48	0.66	0.66	NUM
cana-5239	181	49	xgboost	xgboost	ADV
cana-5239	181	50	76.49	76.49	NUM
cana-5239	181	51	74.64	74.64	NUM
cana-5239	181	52	74.26	74.26	NUM
cana-5239	181	53	74.72	74.72	NUM
cana-5239	181	54	0.50	0.50	NUM
cana-5239	181	55	0.51	0.51	NUM
cana-5239	181	56	0.49	0.49	NUM
cana-5239	181	57	catboost	catboost	VERB
cana-5239	181	58	84.25	84.25	NUM
cana-5239	181	59	84.18	84.18	NUM
cana-5239	181	60	84.15	84.15	NUM
cana-5239	181	61	84.16	84.16	NUM
cana-5239	181	62	0.39	0.39	NUM
cana-5239	181	63	0.68	0.68	NUM
cana-5239	181	64	0.68	0.68	NUM
cana-5239	181	65	recursive	recursive	ADJ
cana-5239	181	66	feature	feature	NOUN
cana-5239	181	67	adaboost	adaboost	ADP
cana-5239	181	68	81.10	81.10	NUM
cana-5239	181	69	82.07	82.07	NUM
cana-5239	181	70	81.10	81.10	NUM
cana-5239	181	71	81.11	81.11	NUM
cana-5239	181	72	0.43	0.43	NUM
cana-5239	181	73	0.62	0.62	NUM
cana-5239	181	74	0.62	0.62	NUM
cana-5239	181	75	communications	communication	NOUN
cana-5239	181	76	on	on	ADP
cana-5239	181	77	applied	apply	VERB
cana-5239	181	78	nonlinear	nonlinear	ADJ
cana-5239	181	79	analysis	analysis	NOUN
cana-5239	181	80	issn	issn	NOUN
cana-5239	181	81	:	:	PUNCT
cana-5239	181	82	1074	1074	NUM
cana-5239	181	83	-	-	PUNCT
cana-5239	181	84	133x	133x	NUM
cana-5239	181	85	vol	vol	VERB
cana-5239	181	86	32	32	NUM
cana-5239	181	87	no	no	NOUN
cana-5239	181	88	.	.	PUNCT
cana-5239	182	1	10s	10	NOUN
cana-5239	182	2	(	(	PUNCT
cana-5239	182	3	2025	2025	NUM
cana-5239	182	4	)	)	PUNCT
cana-5239	182	5	1382	1382	NUM
cana-5239	182	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5239	182	7	elimination	elimination	NOUN
cana-5239	182	8	(	(	PUNCT
cana-5239	182	9	rfe	rfe	NOUN
cana-5239	182	10	)	)	PUNCT
cana-5239	182	11	gradient	gradient	NOUN
cana-5239	182	12	boosting	boost	VERB
cana-5239	182	13	75.67	75.67	NUM
cana-5239	182	14	76.66	76.66	NUM
cana-5239	182	15	76.66	76.66	NUM
cana-5239	182	16	76.66	76.66	NUM
cana-5239	182	17	0.48	0.48	NUM
cana-5239	182	18	0.53	0.53	NUM
cana-5239	182	19	0.53	0.53	NUM
cana-5239	182	20	xgboost	xgboost	ADP
cana-5239	183	1	75.13	75.13	NUM
cana-5239	183	2	74.24	74.24	NUM
cana-5239	183	3	73.80	73.80	NUM
cana-5239	183	4	74.0	74.0	NUM
cana-5239	183	5	0.50	0.50	NUM
cana-5239	183	6	0.49	0.49	NUM
cana-5239	183	7	0.48	0.48	NUM
cana-5239	183	8	catboost	catboost	VERB
cana-5239	183	9	82.01	82.01	NUM
cana-5239	183	10	82.00	82.00	NUM
cana-5239	183	11	82.00	82.00	NUM
cana-5239	183	12	82.0	82.0	NUM
cana-5239	183	13	0.42	0.42	NUM
cana-5239	183	14	0.63	0.63	NUM
cana-5239	183	15	0.63	0.63	NUM
cana-5239	183	16	genetic	genetic	ADJ
cana-5239	183	17	algorithm	algorithm	NOUN
cana-5239	183	18	(	(	PUNCT
cana-5239	183	19	ga	ga	NOUN
cana-5239	183	20	)	)	PUNCT
cana-5239	183	21	adaboost	adaboost	VERB
cana-5239	183	22	81.10	81.10	NUM
cana-5239	183	23	81.07	81.07	NUM
cana-5239	183	24	81.10	81.10	NUM
cana-5239	183	25	81.11	81.11	NUM
cana-5239	183	26	0.43	0.43	NUM
cana-5239	183	27	0.62	0.62	NUM
cana-5239	183	28	0.62	0.62	NUM
cana-5239	183	29	gradient	gradient	NOUN
cana-5239	183	30	boosting	boost	VERB
cana-5239	183	31	76.67	76.67	NUM
cana-5239	183	32	76.66	76.66	NUM
cana-5239	183	33	76.66	76.66	NUM
cana-5239	183	34	76.66	76.66	NUM
cana-5239	183	35	0.48	0.48	NUM
cana-5239	183	36	0.53	0.53	NUM
cana-5239	183	37	0.53	0.53	NUM
cana-5239	183	38	xgboost	xgboost	ADP
cana-5239	183	39	75.13	75.13	NUM
cana-5239	183	40	74.24	74.24	NUM
cana-5239	183	41	73.80	73.80	NUM
cana-5239	183	42	74.0	74.0	NUM
cana-5239	183	43	0.50	0.50	NUM
cana-5239	183	44	0.49	0.49	NUM
cana-5239	183	45	0.48	0.48	NUM
cana-5239	183	46	catboost	catboost	VERB
cana-5239	183	47	82.01	82.01	NUM
cana-5239	183	48	81.00	81.00	NUM
cana-5239	183	49	82.00	82.00	NUM
cana-5239	183	50	82.0	82.0	NUM
cana-5239	183	51	0.42	0.42	NUM
cana-5239	183	52	0.63	0.63	NUM
cana-5239	183	53	0.63	0.63	NUM
cana-5239	183	54	grey	grey	ADJ
cana-5239	183	55	wolf	wolf	PROPN
cana-5239	183	56	optimization	optimization	NOUN
cana-5239	183	57	(	(	PUNCT
cana-5239	183	58	gwo	gwo	PROPN
cana-5239	183	59	)	)	PUNCT
cana-5239	183	60	adaboost	adaboost	VERB
cana-5239	183	61	87.80	87.80	NUM
cana-5239	183	62	87.79	87.79	NUM
cana-5239	183	63	87.77	87.77	NUM
cana-5239	183	64	87.77	87.77	NUM
cana-5239	183	65	0.34	0.34	NUM
cana-5239	183	66	0.75	0.75	NUM
cana-5239	183	67	0.75	0.75	NUM
cana-5239	183	68	gradient	gradient	NOUN
cana-5239	183	69	boosting	boost	VERB
cana-5239	183	70	85.66	85.66	NUM
cana-5239	183	71	85.59	85.59	NUM
cana-5239	183	72	85.55	85.55	NUM
cana-5239	183	73	85.55	85.55	NUM
cana-5239	183	74	0.38	0.38	NUM
cana-5239	183	75	0.71	0.71	NUM
cana-5239	183	76	0.71	0.71	NUM
cana-5239	183	77	xgboost	xgboost	ADP
cana-5239	183	78	80.10	80.10	NUM
cana-5239	183	79	77.95	77.95	NUM
cana-5239	183	80	77.73	77.73	NUM
cana-5239	183	81	78.14	78.14	NUM
cana-5239	183	82	0.46	0.46	NUM
cana-5239	183	83	0.58	0.58	NUM
cana-5239	183	84	0.56	0.56	NUM
cana-5239	183	85	catboost	catboost	NOUN
cana-5239	183	86	88.15	88.15	NUM
cana-5239	183	87	88.15	88.15	NUM
cana-5239	183	88	88.14	88.14	NUM
cana-5239	183	89	88.14	88.14	NUM
cana-5239	183	90	0.34	0.34	NUM
cana-5239	183	91	0.76	0.76	NUM
cana-5239	183	92	0.76	0.76	NUM
cana-5239	183	93	table	table	NOUN
cana-5239	183	94	4	4	NUM
cana-5239	183	95	provides	provide	VERB
cana-5239	183	96	a	a	DET
cana-5239	183	97	comparison	comparison	NOUN
cana-5239	183	98	of	of	ADP
cana-5239	183	99	the	the	DET
cana-5239	183	100	performance	performance	NOUN
cana-5239	183	101	of	of	ADP
cana-5239	183	102	different	different	ADJ
cana-5239	183	103	feature	feature	NOUN
cana-5239	183	104	selection	selection	NOUN
cana-5239	183	105	methods	method	NOUN
cana-5239	183	106	combined	combine	VERB
cana-5239	183	107	with	with	ADP
cana-5239	183	108	various	various	ADJ
cana-5239	183	109	classifiers	classifier	NOUN
cana-5239	183	110	across	across	ADP
cana-5239	183	111	several	several	ADJ
cana-5239	183	112	evaluation	evaluation	NOUN
cana-5239	183	113	metrics	metric	NOUN
cana-5239	183	114	.	.	PUNCT
cana-5239	184	1	and	and	CCONJ
cana-5239	184	2	the	the	DET
cana-5239	184	3	figure	figure	NOUN
cana-5239	184	4	36	36	NUM
cana-5239	184	5	shows	show	VERB
cana-5239	184	6	the	the	DET
cana-5239	184	7	graphical	graphical	ADJ
cana-5239	184	8	visualization	visualization	NOUN
cana-5239	184	9	of	of	ADP
cana-5239	184	10	the	the	DET
cana-5239	184	11	result	result	NOUN
cana-5239	184	12	achieved	achieve	VERB
cana-5239	184	13	.	.	PUNCT
cana-5239	185	1	each	each	DET
cana-5239	185	2	combination	combination	NOUN
cana-5239	185	3	of	of	ADP
cana-5239	185	4	feature	feature	NOUN
cana-5239	185	5	selection	selection	NOUN
cana-5239	185	6	method	method	NOUN
cana-5239	185	7	and	and	CCONJ
cana-5239	185	8	classifier	classifier	NOUN
cana-5239	185	9	is	be	AUX
cana-5239	185	10	evaluated	evaluate	VERB
cana-5239	185	11	based	base	VERB
cana-5239	185	12	on	on	ADP
cana-5239	185	13	metrics	metric	NOUN
cana-5239	185	14	like	like	ADP
cana-5239	185	15	precision	precision	NOUN
cana-5239	185	16	,	,	PUNCT
cana-5239	185	17	recall	recall	NOUN
cana-5239	185	18	,	,	PUNCT
cana-5239	185	19	f1	f1	NOUN
cana-5239	185	20	score	score	NOUN
cana-5239	185	21	,	,	PUNCT
cana-5239	185	22	accuracy	accuracy	NOUN
cana-5239	185	23	,	,	PUNCT
cana-5239	185	24	rmse	rmse	NOUN
cana-5239	185	25	,	,	PUNCT
cana-5239	185	26	mcc	mcc	NOUN
cana-5239	185	27	,	,	PUNCT
cana-5239	185	28	and	and	CCONJ
cana-5239	185	29	kappa	kappa	PROPN
cana-5239	185	30	,	,	PUNCT
cana-5239	185	31	which	which	PRON
cana-5239	185	32	assess	assess	VERB
cana-5239	185	33	the	the	DET
cana-5239	185	34	quality	quality	NOUN
cana-5239	185	35	and	and	CCONJ
cana-5239	185	36	performance	performance	NOUN
cana-5239	185	37	of	of	ADP
cana-5239	185	38	the	the	DET
cana-5239	185	39	models	model	NOUN
cana-5239	185	40	.	.	PUNCT
cana-5239	186	1	figure	figure	VERB
cana-5239	186	2	3	3	NUM
cana-5239	186	3	.	.	PUNCT
cana-5239	186	4	ensemble	ensemble	ADJ
cana-5239	186	5	model	model	NOUN
cana-5239	186	6	performance	performance	NOUN
cana-5239	186	7	with	with	ADP
cana-5239	186	8	pca	pca	NOUN
cana-5239	186	9	feature	feature	NOUN
cana-5239	186	10	selection	selection	NOUN
cana-5239	186	11	figure	figure	NOUN
cana-5239	186	12	4	4	NUM
cana-5239	186	13	ensemble	ensemble	ADJ
cana-5239	186	14	model	model	NOUN
cana-5239	186	15	performance	performance	NOUN
cana-5239	186	16	with	with	ADP
cana-5239	186	17	rfe	rfe	PROPN
cana-5239	186	18	feature	feature	NOUN
cana-5239	186	19	selection	selection	NOUN
cana-5239	186	20	communications	communication	NOUN
cana-5239	186	21	on	on	ADP
cana-5239	186	22	applied	apply	VERB
cana-5239	186	23	nonlinear	nonlinear	ADJ
cana-5239	186	24	analysis	analysis	NOUN
cana-5239	186	25	issn	issn	NOUN
cana-5239	186	26	:	:	PUNCT
cana-5239	186	27	1074	1074	NUM
cana-5239	186	28	-	-	PUNCT
cana-5239	186	29	133x	133x	NUM
cana-5239	186	30	vol	vol	VERB
cana-5239	186	31	32	32	NUM
cana-5239	186	32	no	no	NOUN
cana-5239	186	33	.	.	PUNCT
cana-5239	187	1	10s	10	NOUN
cana-5239	187	2	(	(	PUNCT
cana-5239	187	3	2025	2025	NUM
cana-5239	187	4	)	)	PUNCT
cana-5239	187	5	1383	1383	NUM
cana-5239	187	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5239	187	7	4.1	4.1	NUM
cana-5239	187	8	principal	principal	ADJ
cana-5239	187	9	component	component	NOUN
cana-5239	187	10	analysis	analysis	NOUN
cana-5239	187	11	(	(	PUNCT
cana-5239	187	12	pca	pca	NOUN
cana-5239	187	13	)	)	PUNCT
cana-5239	188	1	+	+	NUM
cana-5239	188	2	classifiers	classifier	NOUN
cana-5239	188	3	the	the	DET
cana-5239	188	4	evaluation	evaluation	NOUN
cana-5239	188	5	of	of	ADP
cana-5239	188	6	pca	pca	PROPN
cana-5239	188	7	with	with	ADP
cana-5239	188	8	different	different	ADJ
cana-5239	188	9	ensemble	ensemble	ADJ
cana-5239	188	10	classifiers	classifier	NOUN
cana-5239	188	11	shown	show	VERB
cana-5239	188	12	in	in	ADP
cana-5239	188	13	figure	figure	NOUN
cana-5239	188	14	3	3	NUM
cana-5239	188	15	reveals	reveal	VERB
cana-5239	188	16	that	that	SCONJ
cana-5239	188	17	catboost	catboost	NOUN
cana-5239	188	18	outperforms	outperform	VERB
cana-5239	188	19	the	the	DET
cana-5239	188	20	others	other	NOUN
cana-5239	188	21	,	,	PUNCT
cana-5239	188	22	achieving	achieve	VERB
cana-5239	188	23	the	the	DET
cana-5239	188	24	highest	high	ADJ
cana-5239	188	25	precision	precision	NOUN
cana-5239	188	26	(	(	PUNCT
cana-5239	188	27	84.25	84.25	NUM
cana-5239	188	28	%	%	NOUN
cana-5239	188	29	)	)	PUNCT
cana-5239	188	30	,	,	PUNCT
cana-5239	188	31	recall	recall	INTJ
cana-5239	188	32	(	(	PUNCT
cana-5239	188	33	84.18	84.18	NUM
cana-5239	188	34	%	%	NOUN
cana-5239	188	35	)	)	PUNCT
cana-5239	188	36	,	,	PUNCT
cana-5239	188	37	f1	f1	NOUN
cana-5239	188	38	score	score	NOUN
cana-5239	188	39	(	(	PUNCT
cana-5239	188	40	84.15	84.15	NUM
cana-5239	188	41	%	%	NOUN
cana-5239	188	42	)	)	PUNCT
cana-5239	188	43	,	,	PUNCT
cana-5239	188	44	and	and	CCONJ
cana-5239	188	45	accuracy	accuracy	NOUN
cana-5239	188	46	(	(	PUNCT
cana-5239	188	47	84.16	84.16	NUM
cana-5239	188	48	%	%	NOUN
cana-5239	188	49	)	)	PUNCT
cana-5239	188	50	with	with	ADP
cana-5239	188	51	the	the	DET
cana-5239	188	52	lowest	low	ADJ
cana-5239	188	53	rmse	rmse	NOUN
cana-5239	188	54	(	(	PUNCT
cana-5239	188	55	0.39	0.39	NUM
cana-5239	188	56	)	)	PUNCT
cana-5239	188	57	and	and	CCONJ
cana-5239	188	58	robust	robust	ADJ
cana-5239	188	59	mcc	mcc	NOUN
cana-5239	188	60	and	and	CCONJ
cana-5239	188	61	kappa	kappa	PROPN
cana-5239	188	62	scores	score	NOUN
cana-5239	188	63	(	(	PUNCT
cana-5239	188	64	0.68	0.68	NUM
cana-5239	188	65	)	)	PUNCT
cana-5239	188	66	.	.	PUNCT
cana-5239	189	1	gradient	gradient	ADJ
cana-5239	189	2	boosting	boosting	NOUN
cana-5239	189	3	follows	follow	VERB
cana-5239	189	4	closely	closely	ADV
cana-5239	189	5	with	with	ADP
cana-5239	189	6	slightly	slightly	ADV
cana-5239	189	7	lower	low	ADJ
cana-5239	189	8	metrics	metric	NOUN
cana-5239	189	9	but	but	CCONJ
cana-5239	189	10	still	still	ADV
cana-5239	189	11	demonstrates	demonstrate	VERB
cana-5239	189	12	strong	strong	ADJ
cana-5239	189	13	reliability	reliability	NOUN
cana-5239	189	14	,	,	PUNCT
cana-5239	189	15	while	while	SCONJ
cana-5239	189	16	adaboost	adaboost	ADV
cana-5239	189	17	provides	provide	VERB
cana-5239	189	18	moderate	moderate	ADJ
cana-5239	189	19	performance	performance	NOUN
cana-5239	189	20	,	,	PUNCT
cana-5239	189	21	achieving	achieve	VERB
cana-5239	189	22	an	an	DET
cana-5239	189	23	accuracy	accuracy	NOUN
cana-5239	189	24	of	of	ADP
cana-5239	189	25	81.94	81.94	NUM
cana-5239	189	26	%	%	NOUN
cana-5239	189	27	and	and	CCONJ
cana-5239	189	28	mcc	mcc	PROPN
cana-5239	189	29	/	/	SYM
cana-5239	189	30	kappa	kappa	PROPN
cana-5239	189	31	scores	score	NOUN
cana-5239	189	32	of	of	ADP
cana-5239	189	33	0.63	0.63	NUM
cana-5239	189	34	.	.	PUNCT
cana-5239	190	1	xgboost	xgboost	PROPN
cana-5239	190	2	,	,	PUNCT
cana-5239	190	3	however	however	ADV
cana-5239	190	4	,	,	PUNCT
cana-5239	190	5	underperforms	underperform	VERB
cana-5239	190	6	with	with	ADP
cana-5239	190	7	the	the	DET
cana-5239	190	8	lowest	low	ADJ
cana-5239	190	9	accuracy	accuracy	NOUN
cana-5239	190	10	(	(	PUNCT
cana-5239	190	11	74.72	74.72	NUM
cana-5239	190	12	%	%	NOUN
cana-5239	190	13	)	)	PUNCT
cana-5239	190	14	,	,	PUNCT
cana-5239	190	15	highest	high	ADJ
cana-5239	190	16	rmse	rmse	NOUN
cana-5239	190	17	(	(	PUNCT
cana-5239	190	18	0.50	0.50	NUM
cana-5239	190	19	)	)	PUNCT
cana-5239	190	20	,	,	PUNCT
cana-5239	190	21	and	and	CCONJ
cana-5239	190	22	weaker	weak	ADJ
cana-5239	190	23	mcc	mcc	PROPN
cana-5239	190	24	/	/	SYM
cana-5239	190	25	kappa	kappa	PROPN
cana-5239	190	26	scores	score	NOUN
cana-5239	190	27	,	,	PUNCT
cana-5239	190	28	indicating	indicate	VERB
cana-5239	190	29	its	its	PRON
cana-5239	190	30	limited	limited	ADJ
cana-5239	190	31	compatibility	compatibility	NOUN
cana-5239	190	32	with	with	ADP
cana-5239	190	33	pca	pca	NOUN
cana-5239	190	34	-	-	PUNCT
cana-5239	190	35	selected	select	VERB
cana-5239	190	36	features	feature	NOUN
cana-5239	190	37	.	.	PUNCT
cana-5239	191	1	this	this	DET
cana-5239	191	2	analysis	analysis	NOUN
cana-5239	191	3	highlights	highlight	NOUN
cana-5239	191	4	catboost	catboost	VERB
cana-5239	191	5	as	as	ADP
cana-5239	191	6	the	the	DET
cana-5239	191	7	most	most	ADV
cana-5239	191	8	effective	effective	ADJ
cana-5239	191	9	classifier	classifier	NOUN
cana-5239	191	10	for	for	ADP
cana-5239	191	11	agricultural	agricultural	ADJ
cana-5239	191	12	commodity	commodity	NOUN
cana-5239	191	13	price	price	NOUN
cana-5239	191	14	prediction	prediction	NOUN
cana-5239	191	15	when	when	SCONJ
cana-5239	191	16	paired	pair	VERB
cana-5239	191	17	with	with	ADP
cana-5239	191	18	pca	pca	PROPN
cana-5239	191	19	,	,	PUNCT
cana-5239	191	20	showcasing	showcase	VERB
cana-5239	191	21	its	its	PRON
cana-5239	191	22	ability	ability	NOUN
cana-5239	191	23	to	to	PART
cana-5239	191	24	generalize	generalize	VERB
cana-5239	191	25	well	well	ADV
cana-5239	191	26	and	and	CCONJ
cana-5239	191	27	handle	handle	VERB
cana-5239	191	28	categorical	categorical	ADJ
cana-5239	191	29	features	feature	NOUN
cana-5239	191	30	efficiently	efficiently	ADV
cana-5239	191	31	.	.	PUNCT
cana-5239	192	1	4.2	4.2	NUM
cana-5239	192	2	recursive	recursive	ADJ
cana-5239	192	3	feature	feature	NOUN
cana-5239	192	4	elimination	elimination	NOUN
cana-5239	192	5	(	(	PUNCT
cana-5239	192	6	rfe	rfe	NOUN
cana-5239	192	7	)	)	PUNCT
cana-5239	192	8	+	+	NUM
cana-5239	192	9	classifiers	classifier	NOUN
cana-5239	192	10	:	:	PUNCT
cana-5239	192	11	the	the	DET
cana-5239	192	12	performance	performance	NOUN
cana-5239	192	13	evaluation	evaluation	NOUN
cana-5239	192	14	of	of	ADP
cana-5239	192	15	recursive	recursive	ADJ
cana-5239	192	16	feature	feature	NOUN
cana-5239	192	17	elimination	elimination	NOUN
cana-5239	192	18	(	(	PUNCT
cana-5239	192	19	rfe	rfe	PROPN
cana-5239	192	20	)	)	PUNCT
cana-5239	192	21	with	with	ADP
cana-5239	192	22	various	various	ADJ
cana-5239	192	23	ensemble	ensemble	ADJ
cana-5239	192	24	classifiers	classifier	NOUN
cana-5239	192	25	shown	show	VERB
cana-5239	192	26	in	in	ADP
cana-5239	192	27	figure	figure	NOUN
cana-5239	192	28	4	4	NUM
cana-5239	192	29	highlights	highlight	NOUN
cana-5239	192	30	catboost	catboost	VERB
cana-5239	192	31	as	as	ADP
cana-5239	192	32	the	the	DET
cana-5239	192	33	best	well	ADV
cana-5239	192	34	-	-	PUNCT
cana-5239	192	35	performing	perform	VERB
cana-5239	192	36	model	model	NOUN
cana-5239	192	37	,	,	PUNCT
cana-5239	192	38	achieving	achieve	VERB
cana-5239	192	39	precision	precision	NOUN
cana-5239	192	40	,	,	PUNCT
cana-5239	192	41	recall	recall	NOUN
cana-5239	192	42	,	,	PUNCT
cana-5239	192	43	and	and	CCONJ
cana-5239	192	44	f1	f1	ADJ
cana-5239	192	45	score	score	NOUN
cana-5239	192	46	of	of	ADP
cana-5239	192	47	82.0	82.0	NUM
cana-5239	192	48	%	%	NOUN
cana-5239	192	49	,	,	PUNCT
cana-5239	192	50	along	along	ADP
cana-5239	192	51	with	with	ADP
cana-5239	192	52	an	an	DET
cana-5239	192	53	accuracy	accuracy	NOUN
cana-5239	192	54	of	of	ADP
cana-5239	192	55	82.0	82.0	NUM
cana-5239	192	56	%	%	NOUN
cana-5239	192	57	,	,	PUNCT
cana-5239	192	58	the	the	DET
cana-5239	192	59	lowest	low	ADJ
cana-5239	192	60	rmse	rmse	NOUN
cana-5239	192	61	(	(	PUNCT
cana-5239	192	62	0.42	0.42	NUM
cana-5239	192	63	)	)	PUNCT
cana-5239	192	64	,	,	PUNCT
cana-5239	192	65	and	and	CCONJ
cana-5239	192	66	reliable	reliable	ADJ
cana-5239	192	67	mcc	mcc	PROPN
cana-5239	192	68	and	and	CCONJ
cana-5239	192	69	kappa	kappa	PROPN
cana-5239	192	70	scores	score	NOUN
cana-5239	192	71	(	(	PUNCT
cana-5239	192	72	0.63	0.63	NUM
cana-5239	192	73	)	)	PUNCT
cana-5239	192	74	.	.	PUNCT
cana-5239	193	1	adaboost	adaboost	PROPN
cana-5239	193	2	follows	follow	VERB
cana-5239	193	3	closely	closely	ADV
cana-5239	193	4	,	,	PUNCT
cana-5239	193	5	with	with	ADP
cana-5239	193	6	slightly	slightly	ADV
cana-5239	193	7	lower	low	ADJ
cana-5239	193	8	metrics	metric	NOUN
cana-5239	193	9	,	,	PUNCT
cana-5239	193	10	including	include	VERB
cana-5239	193	11	an	an	DET
cana-5239	193	12	accuracy	accuracy	NOUN
cana-5239	193	13	of	of	ADP
cana-5239	193	14	81.11	81.11	NUM
cana-5239	193	15	%	%	NOUN
cana-5239	193	16	and	and	CCONJ
cana-5239	193	17	mcc	mcc	PROPN
cana-5239	193	18	/	/	SYM
cana-5239	193	19	kappa	kappa	PROPN
cana-5239	193	20	scores	score	NOUN
cana-5239	193	21	of	of	ADP
cana-5239	193	22	0.62	0.62	NUM
cana-5239	193	23	,	,	PUNCT
cana-5239	193	24	showing	show	VERB
cana-5239	193	25	moderate	moderate	ADJ
cana-5239	193	26	reliability	reliability	NOUN
cana-5239	193	27	.	.	PUNCT
cana-5239	194	1	gradient	gradient	ADJ
cana-5239	194	2	boosting	boosting	NOUN
cana-5239	194	3	achieves	achieve	VERB
cana-5239	194	4	an	an	DET
cana-5239	194	5	accuracy	accuracy	NOUN
cana-5239	194	6	of	of	ADP
cana-5239	194	7	76.66	76.66	NUM
cana-5239	194	8	%	%	NOUN
cana-5239	194	9	but	but	CCONJ
cana-5239	194	10	lags	lag	VERB
cana-5239	194	11	behind	behind	ADV
cana-5239	194	12	with	with	ADP
cana-5239	194	13	a	a	DET
cana-5239	194	14	higher	high	ADJ
cana-5239	194	15	rmse	rmse	NOUN
cana-5239	194	16	(	(	PUNCT
cana-5239	194	17	0.48	0.48	NUM
cana-5239	194	18	)	)	PUNCT
cana-5239	194	19	and	and	CCONJ
cana-5239	194	20	lower	low	ADJ
cana-5239	194	21	mcc	mcc	PROPN
cana-5239	194	22	/	/	SYM
cana-5239	194	23	kappa	kappa	PROPN
cana-5239	194	24	scores	score	NOUN
cana-5239	194	25	(	(	PUNCT
cana-5239	194	26	0.53	0.53	NUM
cana-5239	194	27	)	)	PUNCT
cana-5239	194	28	.	.	PUNCT
cana-5239	195	1	xgboost	xgboost	X
cana-5239	196	1	underperforms	underperform	VERB
cana-5239	196	2	,	,	PUNCT
cana-5239	196	3	with	with	ADP
cana-5239	196	4	the	the	DET
cana-5239	196	5	lowest	low	ADJ
cana-5239	196	6	accuracy	accuracy	NOUN
cana-5239	196	7	(	(	PUNCT
cana-5239	196	8	74.0	74.0	NUM
cana-5239	196	9	%	%	NOUN
cana-5239	196	10	)	)	PUNCT
cana-5239	196	11	,	,	PUNCT
cana-5239	196	12	the	the	DET
cana-5239	196	13	highest	high	ADJ
cana-5239	196	14	rmse	rmse	NOUN
cana-5239	196	15	(	(	PUNCT
cana-5239	196	16	0.50	0.50	NUM
cana-5239	196	17	)	)	PUNCT
cana-5239	196	18	,	,	PUNCT
cana-5239	196	19	and	and	CCONJ
cana-5239	196	20	weak	weak	ADJ
cana-5239	196	21	mcc	mcc	PROPN
cana-5239	196	22	/	/	SYM
cana-5239	196	23	kappa	kappa	PROPN
cana-5239	196	24	scores	score	NOUN
cana-5239	196	25	,	,	PUNCT
cana-5239	196	26	indicating	indicate	VERB
cana-5239	196	27	limited	limited	ADJ
cana-5239	196	28	compatibility	compatibility	NOUN
cana-5239	196	29	with	with	ADP
cana-5239	196	30	rfe	rfe	PROPN
cana-5239	196	31	.	.	PUNCT
cana-5239	197	1	overall	overall	ADV
cana-5239	197	2	,	,	PUNCT
cana-5239	197	3	this	this	DET
cana-5239	197	4	analysis	analysis	NOUN
cana-5239	197	5	emphasizes	emphasize	VERB
cana-5239	197	6	catboost	catboost	NOUN
cana-5239	197	7	's	's	PART
cana-5239	197	8	robustness	robustness	NOUN
cana-5239	197	9	when	when	SCONJ
cana-5239	197	10	combined	combine	VERB
cana-5239	197	11	with	with	ADP
cana-5239	197	12	rfe	rfe	PROPN
cana-5239	197	13	for	for	ADP
cana-5239	197	14	agricultural	agricultural	ADJ
cana-5239	197	15	commodity	commodity	NOUN
cana-5239	197	16	price	price	NOUN
cana-5239	197	17	prediction	prediction	NOUN
cana-5239	197	18	,	,	PUNCT
cana-5239	197	19	while	while	SCONJ
cana-5239	197	20	adaboost	adaboost	ADV
cana-5239	197	21	also	also	ADV
cana-5239	197	22	proves	prove	VERB
cana-5239	197	23	to	to	PART
cana-5239	197	24	be	be	AUX
cana-5239	197	25	a	a	DET
cana-5239	197	26	reliable	reliable	ADJ
cana-5239	197	27	alternative	alternative	NOUN
cana-5239	197	28	.	.	PUNCT
cana-5239	198	1	figure	figure	NOUN
cana-5239	198	2	5	5	NUM
cana-5239	198	3	.	.	PUNCT
cana-5239	198	4	ensemble	ensemble	ADJ
cana-5239	198	5	model	model	NOUN
cana-5239	198	6	performance	performance	NOUN
cana-5239	198	7	with	with	ADP
cana-5239	198	8	ga	ga	PROPN
cana-5239	198	9	feature	feature	NOUN
cana-5239	198	10	selection	selection	NOUN
cana-5239	198	11	figure	figure	NOUN
cana-5239	198	12	6	6	NUM
cana-5239	198	13	ensemble	ensemble	ADJ
cana-5239	198	14	model	model	NOUN
cana-5239	198	15	performance	performance	NOUN
cana-5239	198	16	with	with	ADP
cana-5239	198	17	gwo	gwo	PROPN
cana-5239	198	18	feature	feature	NOUN
cana-5239	198	19	selection	selection	NOUN
cana-5239	198	20	4.3	4.3	NUM
cana-5239	198	21	genetic	genetic	ADJ
cana-5239	198	22	algorithm	algorithm	NOUN
cana-5239	198	23	(	(	PUNCT
cana-5239	198	24	ga	ga	NOUN
cana-5239	198	25	)	)	PUNCT
cana-5239	199	1	+	+	NUM
cana-5239	199	2	classifiers	classifier	NOUN
cana-5239	199	3	:	:	PUNCT
cana-5239	199	4	the	the	DET
cana-5239	199	5	evaluation	evaluation	NOUN
cana-5239	199	6	of	of	ADP
cana-5239	199	7	genetic	genetic	ADJ
cana-5239	199	8	algorithm	algorithm	NOUN
cana-5239	199	9	(	(	PUNCT
cana-5239	199	10	ga	ga	PROPN
cana-5239	199	11	)	)	PUNCT
cana-5239	199	12	with	with	ADP
cana-5239	199	13	ensemble	ensemble	ADJ
cana-5239	199	14	classifiers	classifier	NOUN
cana-5239	199	15	shown	show	VERB
cana-5239	199	16	in	in	ADP
cana-5239	199	17	figure	figure	NOUN
cana-5239	199	18	5	5	NUM
cana-5239	199	19	highlights	highlight	NOUN
cana-5239	199	20	catboost	catboost	VERB
cana-5239	199	21	as	as	ADP
cana-5239	199	22	the	the	DET
cana-5239	199	23	top	top	ADJ
cana-5239	199	24	performer	performer	NOUN
cana-5239	199	25	,	,	PUNCT
cana-5239	199	26	achieving	achieve	VERB
cana-5239	199	27	precision	precision	NOUN
cana-5239	199	28	,	,	PUNCT
cana-5239	199	29	recall	recall	NOUN
cana-5239	199	30	,	,	PUNCT
cana-5239	199	31	and	and	CCONJ
cana-5239	199	32	f1	f1	ADJ
cana-5239	199	33	score	score	NOUN
cana-5239	199	34	of	of	ADP
cana-5239	199	35	82.0	82.0	NUM
cana-5239	199	36	%	%	NOUN
cana-5239	199	37	,	,	PUNCT
cana-5239	199	38	accuracy	accuracy	NOUN
cana-5239	199	39	of	of	ADP
cana-5239	199	40	82.0	82.0	NUM
cana-5239	199	41	%	%	NOUN
cana-5239	199	42	,	,	PUNCT
cana-5239	199	43	the	the	DET
cana-5239	199	44	lowest	low	ADJ
cana-5239	199	45	rmse	rmse	NOUN
cana-5239	199	46	(	(	PUNCT
cana-5239	199	47	0.42	0.42	NUM
cana-5239	199	48	)	)	PUNCT
cana-5239	199	49	,	,	PUNCT
cana-5239	199	50	and	and	CCONJ
cana-5239	199	51	strong	strong	ADJ
cana-5239	199	52	mcc	mcc	PROPN
cana-5239	199	53	/	/	SYM
cana-5239	199	54	kappa	kappa	PROPN
cana-5239	199	55	scores	score	NOUN
cana-5239	199	56	(	(	PUNCT
cana-5239	199	57	0.63	0.63	NUM
cana-5239	199	58	)	)	PUNCT
cana-5239	199	59	.	.	PUNCT
cana-5239	200	1	adaboost	adaboost	ADV
cana-5239	200	2	closely	closely	ADV
cana-5239	200	3	follows	follow	VERB
cana-5239	200	4	with	with	ADP
cana-5239	200	5	an	an	DET
cana-5239	200	6	accuracy	accuracy	NOUN
cana-5239	200	7	of	of	ADP
cana-5239	200	8	81.11	81.11	NUM
cana-5239	200	9	%	%	NOUN
cana-5239	200	10	,	,	PUNCT
cana-5239	200	11	a	a	DET
cana-5239	200	12	slightly	slightly	ADV
cana-5239	200	13	higher	high	ADJ
cana-5239	200	14	rmse	rmse	NOUN
cana-5239	200	15	(	(	PUNCT
cana-5239	200	16	0.43	0.43	NUM
cana-5239	200	17	)	)	PUNCT
cana-5239	200	18	,	,	PUNCT
cana-5239	200	19	and	and	CCONJ
cana-5239	200	20	mcc	mcc	PROPN
cana-5239	200	21	/	/	SYM
cana-5239	200	22	kappa	kappa	PROPN
cana-5239	200	23	scores	score	NOUN
cana-5239	200	24	of	of	ADP
cana-5239	200	25	0.62	0.62	NUM
cana-5239	200	26	,	,	PUNCT
cana-5239	200	27	communications	communication	NOUN
cana-5239	200	28	on	on	ADP
cana-5239	200	29	applied	apply	VERB
cana-5239	200	30	nonlinear	nonlinear	ADJ
cana-5239	200	31	analysis	analysis	NOUN
cana-5239	200	32	issn	issn	NOUN
cana-5239	200	33	:	:	PUNCT
cana-5239	200	34	1074	1074	NUM
cana-5239	200	35	-	-	PUNCT
cana-5239	200	36	133x	133x	NUM
cana-5239	200	37	vol	vol	VERB
cana-5239	200	38	32	32	NUM
cana-5239	200	39	no	no	NOUN
cana-5239	200	40	.	.	PUNCT
cana-5239	201	1	10s	10	NOUN
cana-5239	201	2	(	(	PUNCT
cana-5239	201	3	2025	2025	NUM
cana-5239	201	4	)	)	PUNCT
cana-5239	201	5	1384	1384	NUM
cana-5239	201	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5239	201	7	demonstrating	demonstrate	VERB
cana-5239	201	8	moderate	moderate	ADJ
cana-5239	201	9	reliability	reliability	NOUN
cana-5239	201	10	.	.	PUNCT
cana-5239	202	1	gradient	gradient	ADJ
cana-5239	202	2	boosting	boosting	NOUN
cana-5239	202	3	performs	perform	VERB
cana-5239	202	4	reasonably	reasonably	ADV
cana-5239	202	5	with	with	ADP
cana-5239	202	6	an	an	DET
cana-5239	202	7	accuracy	accuracy	NOUN
cana-5239	202	8	of	of	ADP
cana-5239	202	9	76.66	76.66	NUM
cana-5239	202	10	%	%	NOUN
cana-5239	202	11	,	,	PUNCT
cana-5239	202	12	though	though	SCONJ
cana-5239	202	13	its	its	PRON
cana-5239	202	14	higher	high	ADJ
cana-5239	202	15	rmse	rmse	NOUN
cana-5239	202	16	(	(	PUNCT
cana-5239	202	17	0.48	0.48	NUM
cana-5239	202	18	)	)	PUNCT
cana-5239	202	19	and	and	CCONJ
cana-5239	202	20	lower	low	ADJ
cana-5239	202	21	mcc	mcc	PROPN
cana-5239	202	22	/	/	SYM
cana-5239	202	23	kappa	kappa	PROPN
cana-5239	202	24	scores	score	NOUN
cana-5239	202	25	(	(	PUNCT
cana-5239	202	26	0.53	0.53	NUM
cana-5239	202	27	)	)	PUNCT
cana-5239	202	28	suggest	suggest	VERB
cana-5239	202	29	room	room	NOUN
cana-5239	202	30	for	for	ADP
cana-5239	202	31	improvement	improvement	NOUN
cana-5239	202	32	.	.	PUNCT
cana-5239	203	1	xgboost	xgboost	ADV
cana-5239	203	2	again	again	ADV
cana-5239	203	3	underperforms	underperform	VERB
cana-5239	203	4	,	,	PUNCT
cana-5239	203	5	showing	show	VERB
cana-5239	203	6	the	the	DET
cana-5239	203	7	lowest	low	ADJ
cana-5239	203	8	accuracy	accuracy	NOUN
cana-5239	203	9	(	(	PUNCT
cana-5239	203	10	74.0	74.0	NUM
cana-5239	203	11	%	%	NOUN
cana-5239	203	12	)	)	PUNCT
cana-5239	203	13	,	,	PUNCT
cana-5239	203	14	the	the	DET
cana-5239	203	15	highest	high	ADJ
cana-5239	203	16	rmse	rmse	NOUN
cana-5239	203	17	(	(	PUNCT
cana-5239	203	18	0.50	0.50	NUM
cana-5239	203	19	)	)	PUNCT
cana-5239	203	20	,	,	PUNCT
cana-5239	203	21	and	and	CCONJ
cana-5239	203	22	weak	weak	ADJ
cana-5239	203	23	mcc	mcc	PROPN
cana-5239	203	24	/	/	SYM
cana-5239	203	25	kappa	kappa	PROPN
cana-5239	203	26	scores	score	NOUN
cana-5239	203	27	,	,	PUNCT
cana-5239	203	28	indicating	indicate	VERB
cana-5239	203	29	limited	limited	ADJ
cana-5239	203	30	effectiveness	effectiveness	NOUN
cana-5239	203	31	when	when	SCONJ
cana-5239	203	32	combined	combine	VERB
cana-5239	203	33	with	with	ADP
cana-5239	203	34	ga	ga	PROPN
cana-5239	203	35	.	.	PUNCT
cana-5239	204	1	this	this	DET
cana-5239	204	2	analysis	analysis	NOUN
cana-5239	204	3	confirms	confirm	VERB
cana-5239	204	4	catboost	catboost	PROPN
cana-5239	204	5	's	's	PART
cana-5239	204	6	robustness	robustness	NOUN
cana-5239	204	7	with	with	ADP
cana-5239	204	8	ga	ga	PROPN
cana-5239	204	9	for	for	ADP
cana-5239	204	10	agricultural	agricultural	ADJ
cana-5239	204	11	commodity	commodity	NOUN
cana-5239	204	12	price	price	NOUN
cana-5239	204	13	prediction	prediction	NOUN
cana-5239	204	14	,	,	PUNCT
cana-5239	204	15	while	while	SCONJ
cana-5239	204	16	adaboost	adaboost	ADV
cana-5239	204	17	remains	remain	VERB
cana-5239	204	18	a	a	DET
cana-5239	204	19	reliable	reliable	ADJ
cana-5239	204	20	alternative	alternative	NOUN
cana-5239	204	21	.	.	PUNCT
cana-5239	205	1	4.4	4.4	NUM
cana-5239	205	2	grey	grey	PROPN
cana-5239	205	3	wolf	wolf	PROPN
cana-5239	205	4	optimization	optimization	NOUN
cana-5239	205	5	(	(	PUNCT
cana-5239	205	6	gwo	gwo	PROPN
cana-5239	205	7	)	)	PUNCT
cana-5239	205	8	+	+	NUM
cana-5239	205	9	classifiers	classifier	NOUN
cana-5239	205	10	:	:	PUNCT
cana-5239	205	11	the	the	DET
cana-5239	205	12	performance	performance	NOUN
cana-5239	205	13	evaluation	evaluation	NOUN
cana-5239	205	14	of	of	ADP
cana-5239	205	15	grey	grey	ADJ
cana-5239	205	16	wolf	wolf	PROPN
cana-5239	205	17	optimization	optimization	NOUN
cana-5239	205	18	(	(	PUNCT
cana-5239	205	19	gwo	gwo	PROPN
cana-5239	205	20	)	)	PUNCT
cana-5239	205	21	combined	combine	VERB
cana-5239	205	22	with	with	ADP
cana-5239	205	23	ensemble	ensemble	ADJ
cana-5239	205	24	classifiers	classifier	NOUN
cana-5239	205	25	shown	show	VERB
cana-5239	205	26	in	in	ADP
cana-5239	205	27	figure	figure	NOUN
cana-5239	205	28	6	6	NUM
cana-5239	205	29	highlights	highlight	NOUN
cana-5239	205	30	catboost	catboost	VERB
cana-5239	205	31	as	as	ADP
cana-5239	205	32	the	the	DET
cana-5239	205	33	best	good	ADJ
cana-5239	205	34	performer	performer	NOUN
cana-5239	205	35	,	,	PUNCT
cana-5239	205	36	achieving	achieve	VERB
cana-5239	205	37	the	the	DET
cana-5239	205	38	highest	high	ADJ
cana-5239	205	39	precision	precision	NOUN
cana-5239	205	40	(	(	PUNCT
cana-5239	205	41	88.15	88.15	NUM
cana-5239	205	42	%	%	NOUN
cana-5239	205	43	)	)	PUNCT
cana-5239	205	44	,	,	PUNCT
cana-5239	205	45	recall	recall	INTJ
cana-5239	205	46	(	(	PUNCT
cana-5239	205	47	88.15	88.15	NUM
cana-5239	205	48	%	%	NOUN
cana-5239	205	49	)	)	PUNCT
cana-5239	205	50	,	,	PUNCT
cana-5239	205	51	f1	f1	NOUN
cana-5239	205	52	score	score	NOUN
cana-5239	205	53	(	(	PUNCT
cana-5239	205	54	88.14	88.14	NUM
cana-5239	205	55	%	%	NOUN
cana-5239	205	56	)	)	PUNCT
cana-5239	205	57	,	,	PUNCT
cana-5239	205	58	and	and	CCONJ
cana-5239	205	59	accuracy	accuracy	NOUN
cana-5239	205	60	(	(	PUNCT
cana-5239	205	61	88.14	88.14	NUM
cana-5239	205	62	%	%	NOUN
cana-5239	205	63	)	)	PUNCT
cana-5239	205	64	,	,	PUNCT
cana-5239	205	65	along	along	ADP
cana-5239	205	66	with	with	ADP
cana-5239	205	67	the	the	DET
cana-5239	205	68	lowest	low	ADJ
cana-5239	205	69	rmse	rmse	NOUN
cana-5239	205	70	(	(	PUNCT
cana-5239	205	71	0.34	0.34	NUM
cana-5239	205	72	)	)	PUNCT
cana-5239	205	73	and	and	CCONJ
cana-5239	205	74	the	the	DET
cana-5239	205	75	strongest	strong	ADJ
cana-5239	205	76	mcc	mcc	NOUN
cana-5239	205	77	and	and	CCONJ
cana-5239	205	78	kappa	kappa	PROPN
cana-5239	205	79	scores	score	NOUN
cana-5239	205	80	(	(	PUNCT
cana-5239	205	81	0.76	0.76	NUM
cana-5239	205	82	)	)	PUNCT
cana-5239	205	83	.	.	PUNCT
cana-5239	206	1	adaboost	adaboost	PROPN
cana-5239	206	2	follows	follow	VERB
cana-5239	206	3	closely	closely	ADV
cana-5239	206	4	,	,	PUNCT
cana-5239	206	5	with	with	ADP
cana-5239	206	6	slightly	slightly	ADV
cana-5239	206	7	lower	low	ADJ
cana-5239	206	8	metrics	metric	NOUN
cana-5239	206	9	,	,	PUNCT
cana-5239	206	10	including	include	VERB
cana-5239	206	11	an	an	DET
cana-5239	206	12	accuracy	accuracy	NOUN
cana-5239	206	13	of	of	ADP
cana-5239	206	14	87.77	87.77	NUM
cana-5239	206	15	%	%	NOUN
cana-5239	206	16	and	and	CCONJ
cana-5239	206	17	mcc	mcc	PROPN
cana-5239	206	18	/	/	SYM
cana-5239	206	19	kappa	kappa	PROPN
cana-5239	206	20	scores	score	NOUN
cana-5239	206	21	of	of	ADP
cana-5239	206	22	0.75	0.75	NUM
cana-5239	206	23	,	,	PUNCT
cana-5239	206	24	showcasing	showcase	VERB
cana-5239	206	25	strong	strong	ADJ
cana-5239	206	26	reliability	reliability	NOUN
cana-5239	206	27	.	.	PUNCT
cana-5239	207	1	gradient	gradient	ADJ
cana-5239	207	2	boosting	boost	VERB
cana-5239	207	3	achieves	achieve	VERB
cana-5239	207	4	moderate	moderate	ADJ
cana-5239	207	5	performance	performance	NOUN
cana-5239	207	6	,	,	PUNCT
cana-5239	207	7	with	with	ADP
cana-5239	207	8	an	an	DET
cana-5239	207	9	accuracy	accuracy	NOUN
cana-5239	207	10	of	of	ADP
cana-5239	207	11	85.55	85.55	NUM
cana-5239	207	12	%	%	NOUN
cana-5239	207	13	and	and	CCONJ
cana-5239	207	14	mcc	mcc	PROPN
cana-5239	207	15	/	/	SYM
cana-5239	207	16	kappa	kappa	PROPN
cana-5239	207	17	scores	score	NOUN
cana-5239	207	18	of	of	ADP
cana-5239	207	19	0.71	0.71	NUM
cana-5239	207	20	,	,	PUNCT
cana-5239	207	21	indicating	indicate	VERB
cana-5239	207	22	good	good	ADJ
cana-5239	207	23	but	but	CCONJ
cana-5239	207	24	less	less	ADV
cana-5239	207	25	robust	robust	ADJ
cana-5239	207	26	results	result	NOUN
cana-5239	207	27	compared	compare	VERB
cana-5239	207	28	to	to	PART
cana-5239	207	29	catboost	catboost	VERB
cana-5239	207	30	and	and	CCONJ
cana-5239	207	31	adaboost	adaboost	ADV
cana-5239	207	32	.	.	PUNCT
cana-5239	208	1	xgboost	xgboost	X
cana-5239	208	2	,	,	PUNCT
cana-5239	208	3	however	however	ADV
cana-5239	208	4	,	,	PUNCT
cana-5239	208	5	lags	lag	VERB
cana-5239	208	6	behind	behind	ADV
cana-5239	208	7	with	with	ADP
cana-5239	208	8	the	the	DET
cana-5239	208	9	lowest	low	ADJ
cana-5239	208	10	accuracy	accuracy	NOUN
cana-5239	208	11	(	(	PUNCT
cana-5239	208	12	78.14	78.14	NUM
cana-5239	208	13	%	%	NOUN
cana-5239	208	14	)	)	PUNCT
cana-5239	208	15	,	,	PUNCT
cana-5239	208	16	the	the	DET
cana-5239	208	17	highest	high	ADJ
cana-5239	208	18	rmse	rmse	NOUN
cana-5239	208	19	(	(	PUNCT
cana-5239	208	20	0.46	0.46	NUM
cana-5239	208	21	)	)	PUNCT
cana-5239	208	22	,	,	PUNCT
cana-5239	208	23	and	and	CCONJ
cana-5239	208	24	weaker	weak	ADJ
cana-5239	208	25	mcc	mcc	PROPN
cana-5239	208	26	/	/	SYM
cana-5239	208	27	kappa	kappa	PROPN
cana-5239	208	28	scores	score	NOUN
cana-5239	208	29	(	(	PUNCT
cana-5239	208	30	0.58	0.58	NUM
cana-5239	208	31	)	)	PUNCT
cana-5239	208	32	,	,	PUNCT
cana-5239	208	33	reflecting	reflect	VERB
cana-5239	208	34	limited	limited	ADJ
cana-5239	208	35	compatibility	compatibility	NOUN
cana-5239	208	36	with	with	ADP
cana-5239	208	37	gwo	gwo	PROPN
cana-5239	208	38	.	.	PUNCT
cana-5239	209	1	this	this	DET
cana-5239	209	2	analysis	analysis	NOUN
cana-5239	209	3	emphasizes	emphasize	VERB
cana-5239	209	4	catboost	catboost	PROPN
cana-5239	209	5	's	's	PART
cana-5239	209	6	superior	superior	ADJ
cana-5239	209	7	performance	performance	NOUN
cana-5239	209	8	and	and	CCONJ
cana-5239	209	9	reliability	reliability	NOUN
cana-5239	209	10	with	with	ADP
cana-5239	209	11	gwo	gwo	PROPN
cana-5239	209	12	for	for	ADP
cana-5239	209	13	agricultural	agricultural	ADJ
cana-5239	209	14	commodity	commodity	NOUN
cana-5239	209	15	price	price	NOUN
cana-5239	209	16	prediction	prediction	NOUN
cana-5239	209	17	,	,	PUNCT
cana-5239	209	18	with	with	ADP
cana-5239	209	19	adaboost	adaboost	ADV
cana-5239	209	20	as	as	ADP
cana-5239	209	21	a	a	DET
cana-5239	209	22	close	close	ADJ
cana-5239	209	23	alternative	alternative	NOUN
cana-5239	209	24	.	.	PUNCT
cana-5239	210	1	5	5	X
cana-5239	210	2	.	.	X
cana-5239	210	3	discussion	discussion	NOUN
cana-5239	210	4	this	this	DET
cana-5239	210	5	study	study	NOUN
cana-5239	210	6	evaluates	evaluate	VERB
cana-5239	210	7	the	the	DET
cana-5239	210	8	effectiveness	effectiveness	NOUN
cana-5239	210	9	of	of	ADP
cana-5239	210	10	various	various	ADJ
cana-5239	210	11	feature	feature	NOUN
cana-5239	210	12	selection	selection	NOUN
cana-5239	210	13	techniques	technique	NOUN
cana-5239	210	14	—	—	PUNCT
cana-5239	210	15	principal	principal	ADJ
cana-5239	210	16	component	component	NOUN
cana-5239	210	17	analysis	analysis	NOUN
cana-5239	210	18	(	(	PUNCT
cana-5239	210	19	pca	pca	NOUN
cana-5239	210	20	)	)	PUNCT
cana-5239	210	21	,	,	PUNCT
cana-5239	210	22	recursive	recursive	ADJ
cana-5239	210	23	feature	feature	NOUN
cana-5239	210	24	elimination	elimination	NOUN
cana-5239	210	25	(	(	PUNCT
cana-5239	210	26	rfe	rfe	NOUN
cana-5239	210	27	)	)	PUNCT
cana-5239	210	28	,	,	PUNCT
cana-5239	210	29	genetic	genetic	ADJ
cana-5239	210	30	algorithm	algorithm	NOUN
cana-5239	210	31	(	(	PUNCT
cana-5239	210	32	ga	ga	NOUN
cana-5239	210	33	)	)	PUNCT
cana-5239	210	34	,	,	PUNCT
cana-5239	210	35	and	and	CCONJ
cana-5239	210	36	grey	grey	ADJ
cana-5239	210	37	wolf	wolf	PROPN
cana-5239	210	38	optimization	optimization	NOUN
cana-5239	210	39	(	(	PUNCT
cana-5239	210	40	gwo)—in	gwo)—in	ADP
cana-5239	210	41	combination	combination	NOUN
cana-5239	210	42	with	with	ADP
cana-5239	210	43	ensemble	ensemble	ADJ
cana-5239	210	44	classifiers	classifier	NOUN
cana-5239	210	45	,	,	PUNCT
cana-5239	210	46	including	include	VERB
cana-5239	210	47	adaboost	adaboost	ADJ
cana-5239	210	48	,	,	PUNCT
cana-5239	210	49	gradient	gradient	ADJ
cana-5239	210	50	boosting	boosting	NOUN
cana-5239	210	51	,	,	PUNCT
cana-5239	210	52	xgboost	xgboost	ADV
cana-5239	210	53	,	,	PUNCT
cana-5239	210	54	and	and	CCONJ
cana-5239	210	55	catboost	catboost	NOUN
cana-5239	210	56	,	,	PUNCT
cana-5239	210	57	for	for	ADP
cana-5239	210	58	agricultural	agricultural	ADJ
cana-5239	210	59	commodity	commodity	NOUN
cana-5239	210	60	price	price	NOUN
cana-5239	210	61	prediction	prediction	NOUN
cana-5239	210	62	.	.	PUNCT
cana-5239	211	1	the	the	DET
cana-5239	211	2	objective	objective	NOUN
cana-5239	211	3	is	be	AUX
cana-5239	211	4	to	to	PART
cana-5239	211	5	determine	determine	VERB
cana-5239	211	6	the	the	DET
cana-5239	211	7	optimal	optimal	ADJ
cana-5239	211	8	combination	combination	NOUN
cana-5239	211	9	of	of	ADP
cana-5239	211	10	feature	feature	NOUN
cana-5239	211	11	selection	selection	NOUN
cana-5239	211	12	and	and	CCONJ
cana-5239	211	13	classification	classification	NOUN
cana-5239	211	14	methods	method	NOUN
cana-5239	211	15	to	to	PART
cana-5239	211	16	achieve	achieve	VERB
cana-5239	211	17	the	the	DET
cana-5239	211	18	highest	high	ADJ
cana-5239	211	19	predictive	predictive	ADJ
cana-5239	211	20	accuracy	accuracy	NOUN
cana-5239	211	21	.	.	PUNCT
cana-5239	212	1	key	key	ADJ
cana-5239	212	2	findings	finding	NOUN
cana-5239	212	3	based	base	VERB
cana-5239	212	4	on	on	ADP
cana-5239	212	5	performance	performance	NOUN
cana-5239	212	6	metrics	metric	NOUN
cana-5239	212	7	such	such	ADJ
cana-5239	212	8	as	as	ADP
cana-5239	212	9	precision	precision	NOUN
cana-5239	212	10	,	,	PUNCT
cana-5239	212	11	recall	recall	NOUN
cana-5239	212	12	,	,	PUNCT
cana-5239	212	13	f1	f1	NOUN
cana-5239	212	14	score	score	NOUN
cana-5239	212	15	,	,	PUNCT
cana-5239	212	16	accuracy	accuracy	NOUN
cana-5239	212	17	,	,	PUNCT
cana-5239	212	18	rmse	rmse	NOUN
cana-5239	212	19	,	,	PUNCT
cana-5239	212	20	mcc	mcc	NOUN
cana-5239	212	21	,	,	PUNCT
cana-5239	212	22	and	and	CCONJ
cana-5239	212	23	kappa	kappa	NOUN
cana-5239	212	24	are	be	AUX
cana-5239	212	25	as	as	SCONJ
cana-5239	212	26	follows	follow	VERB
cana-5239	212	27	:	:	PUNCT
cana-5239	212	28	best	good	ADJ
cana-5239	212	29	feature	feature	NOUN
cana-5239	212	30	selection	selection	NOUN
cana-5239	212	31	method	method	NOUN
cana-5239	212	32	:	:	PUNCT
cana-5239	212	33	grey	grey	ADJ
cana-5239	212	34	wolf	wolf	PROPN
cana-5239	212	35	optimization	optimization	NOUN
cana-5239	212	36	(	(	PUNCT
cana-5239	212	37	gwo	gwo	NOUN
cana-5239	212	38	)	)	PUNCT
cana-5239	212	39	consistently	consistently	ADV
cana-5239	212	40	outperforms	outperform	VERB
cana-5239	212	41	other	other	ADJ
cana-5239	212	42	techniques	technique	NOUN
cana-5239	212	43	,	,	PUNCT
cana-5239	212	44	achieving	achieve	VERB
cana-5239	212	45	the	the	DET
cana-5239	212	46	highest	high	ADJ
cana-5239	212	47	precision	precision	NOUN
cana-5239	212	48	,	,	PUNCT
cana-5239	212	49	recall	recall	NOUN
cana-5239	212	50	,	,	PUNCT
cana-5239	212	51	f1	f1	NOUN
cana-5239	212	52	score	score	NOUN
cana-5239	212	53	,	,	PUNCT
cana-5239	212	54	and	and	CCONJ
cana-5239	212	55	accuracy	accuracy	NOUN
cana-5239	212	56	across	across	ADP
cana-5239	212	57	all	all	DET
cana-5239	212	58	classifiers	classifier	NOUN
cana-5239	212	59	.	.	PUNCT
cana-5239	213	1	this	this	PRON
cana-5239	213	2	demonstrates	demonstrate	VERB
cana-5239	213	3	its	its	PRON
cana-5239	213	4	effectiveness	effectiveness	NOUN
cana-5239	213	5	in	in	ADP
cana-5239	213	6	selecting	select	VERB
cana-5239	213	7	relevant	relevant	ADJ
cana-5239	213	8	features	feature	NOUN
cana-5239	213	9	and	and	CCONJ
cana-5239	213	10	minimizing	minimize	VERB
cana-5239	213	11	noise	noise	NOUN
cana-5239	213	12	,	,	PUNCT
cana-5239	213	13	making	make	VERB
cana-5239	213	14	it	it	PRON
cana-5239	213	15	the	the	DET
cana-5239	213	16	most	most	ADV
cana-5239	213	17	suitable	suitable	ADJ
cana-5239	213	18	feature	feature	NOUN
cana-5239	213	19	selection	selection	NOUN
cana-5239	213	20	method	method	NOUN
cana-5239	213	21	for	for	ADP
cana-5239	213	22	agricultural	agricultural	ADJ
cana-5239	213	23	price	price	NOUN
cana-5239	213	24	prediction	prediction	NOUN
cana-5239	213	25	.	.	PUNCT
cana-5239	214	1	best	good	ADJ
cana-5239	214	2	classifier	classifier	NOUN
cana-5239	214	3	:	:	PUNCT
cana-5239	214	4	catboost	catboost	PROPN
cana-5239	214	5	emerges	emerge	VERB
cana-5239	214	6	as	as	ADP
cana-5239	214	7	the	the	DET
cana-5239	214	8	top	top	ADV
cana-5239	214	9	-	-	PUNCT
cana-5239	214	10	performing	perform	VERB
cana-5239	214	11	classifier	classifier	NOUN
cana-5239	214	12	across	across	ADP
cana-5239	214	13	all	all	DET
cana-5239	214	14	feature	feature	NOUN
cana-5239	214	15	selection	selection	NOUN
cana-5239	214	16	methods	method	NOUN
cana-5239	214	17	,	,	PUNCT
cana-5239	214	18	particularly	particularly	ADV
cana-5239	214	19	when	when	SCONJ
cana-5239	214	20	combined	combine	VERB
cana-5239	214	21	with	with	ADP
cana-5239	214	22	gwo	gwo	PROPN
cana-5239	214	23	.	.	PUNCT
cana-5239	215	1	it	it	PRON
cana-5239	215	2	achieves	achieve	VERB
cana-5239	215	3	the	the	DET
cana-5239	215	4	highest	high	ADJ
cana-5239	215	5	accuracy	accuracy	NOUN
cana-5239	215	6	(	(	PUNCT
cana-5239	215	7	88.14	88.14	NUM
cana-5239	215	8	%	%	NOUN
cana-5239	215	9	)	)	PUNCT
cana-5239	215	10	and	and	CCONJ
cana-5239	215	11	the	the	DET
cana-5239	215	12	lowest	low	ADJ
cana-5239	215	13	rmse	rmse	NOUN
cana-5239	215	14	(	(	PUNCT
cana-5239	215	15	0.34	0.34	NUM
cana-5239	215	16	)	)	PUNCT
cana-5239	215	17	,	,	PUNCT
cana-5239	215	18	highlighting	highlight	VERB
cana-5239	215	19	its	its	PRON
cana-5239	215	20	robustness	robustness	NOUN
cana-5239	215	21	in	in	ADP
cana-5239	215	22	handling	handle	VERB
cana-5239	215	23	categorical	categorical	ADJ
cana-5239	215	24	data	datum	NOUN
cana-5239	215	25	and	and	CCONJ
cana-5239	215	26	generalizing	generalize	VERB
cana-5239	215	27	to	to	ADP
cana-5239	215	28	unseen	unseen	ADJ
cana-5239	215	29	instances	instance	NOUN
cana-5239	215	30	.	.	PUNCT
cana-5239	216	1	while	while	SCONJ
cana-5239	216	2	adaboost	adaboost	ADJ
cana-5239	216	3	also	also	ADV
cana-5239	216	4	performs	perform	VERB
cana-5239	216	5	well	well	ADV
cana-5239	216	6	when	when	SCONJ
cana-5239	216	7	paired	pair	VERB
cana-5239	216	8	with	with	ADP
cana-5239	216	9	gwo	gwo	PROPN
cana-5239	216	10	,	,	PUNCT
cana-5239	216	11	its	its	PRON
cana-5239	216	12	accuracy	accuracy	NOUN
cana-5239	216	13	and	and	CCONJ
cana-5239	216	14	precision	precision	NOUN
cana-5239	216	15	are	be	AUX
cana-5239	216	16	slightly	slightly	ADV
cana-5239	216	17	lower	low	ADJ
cana-5239	216	18	than	than	ADP
cana-5239	216	19	those	those	PRON
cana-5239	216	20	of	of	ADP
cana-5239	216	21	catboost	catboost	NOUN
cana-5239	216	22	.	.	PUNCT
cana-5239	217	1	impact	impact	NOUN
cana-5239	217	2	of	of	ADP
cana-5239	217	3	feature	feature	NOUN
cana-5239	217	4	selection	selection	NOUN
cana-5239	217	5	:	:	PUNCT
cana-5239	217	6	gwo	gwo	PROPN
cana-5239	217	7	significantly	significantly	ADV
cana-5239	217	8	enhances	enhance	VERB
cana-5239	217	9	classifier	classifier	ADJ
cana-5239	217	10	performance	performance	NOUN
cana-5239	217	11	by	by	ADP
cana-5239	217	12	effectively	effectively	ADV
cana-5239	217	13	selecting	select	VERB
cana-5239	217	14	relevant	relevant	ADJ
cana-5239	217	15	features	feature	NOUN
cana-5239	217	16	.	.	PUNCT
cana-5239	218	1	while	while	SCONJ
cana-5239	218	2	pca	pca	PROPN
cana-5239	218	3	and	and	CCONJ
cana-5239	218	4	rfe	rfe	PROPN
cana-5239	218	5	yield	yield	NOUN
cana-5239	218	6	moderate	moderate	ADJ
cana-5239	218	7	results	result	NOUN
cana-5239	218	8	,	,	PUNCT
cana-5239	218	9	ga	ga	PROPN
cana-5239	218	10	performs	perform	VERB
cana-5239	218	11	similarly	similarly	ADV
cana-5239	218	12	to	to	ADP
cana-5239	218	13	communications	communication	NOUN
cana-5239	218	14	on	on	ADP
cana-5239	218	15	applied	apply	VERB
cana-5239	218	16	nonlinear	nonlinear	ADJ
cana-5239	218	17	analysis	analysis	NOUN
cana-5239	218	18	issn	issn	NOUN
cana-5239	218	19	:	:	PUNCT
cana-5239	218	20	1074	1074	NUM
cana-5239	218	21	-	-	PUNCT
cana-5239	218	22	133x	133x	NUM
cana-5239	218	23	vol	vol	VERB
cana-5239	218	24	32	32	NUM
cana-5239	218	25	no	no	NOUN
cana-5239	218	26	.	.	PUNCT
cana-5239	219	1	10s	10	NOUN
cana-5239	219	2	(	(	PUNCT
cana-5239	219	3	2025	2025	NUM
cana-5239	219	4	)	)	PUNCT
cana-5239	219	5	1385	1385	NUM
cana-5239	219	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5239	219	7	rfe	rfe	NOUN
cana-5239	219	8	.	.	PUNCT
cana-5239	220	1	these	these	DET
cana-5239	220	2	findings	finding	NOUN
cana-5239	220	3	underscore	underscore	VERB
cana-5239	220	4	the	the	DET
cana-5239	220	5	critical	critical	ADJ
cana-5239	220	6	role	role	NOUN
cana-5239	220	7	of	of	ADP
cana-5239	220	8	feature	feature	NOUN
cana-5239	220	9	selection	selection	NOUN
cana-5239	220	10	in	in	ADP
cana-5239	220	11	improving	improve	VERB
cana-5239	220	12	the	the	DET
cana-5239	220	13	predictive	predictive	ADJ
cana-5239	220	14	power	power	NOUN
cana-5239	220	15	of	of	ADP
cana-5239	220	16	ensemble	ensemble	ADJ
cana-5239	220	17	models	model	NOUN
cana-5239	220	18	.	.	PUNCT
cana-5239	221	1	6	6	X
cana-5239	221	2	.	.	X
cana-5239	221	3	conclusion	conclusion	NOUN
cana-5239	221	4	agricultural	agricultural	ADJ
cana-5239	221	5	price	price	NOUN
cana-5239	221	6	forecasting	forecasting	NOUN
cana-5239	221	7	is	be	AUX
cana-5239	221	8	a	a	DET
cana-5239	221	9	complex	complex	ADJ
cana-5239	221	10	,	,	PUNCT
cana-5239	221	11	interdisciplinary	interdisciplinary	NOUN
cana-5239	221	12	,	,	PUNCT
cana-5239	221	13	and	and	CCONJ
cana-5239	221	14	evolving	evolve	VERB
cana-5239	221	15	research	research	NOUN
cana-5239	221	16	area	area	NOUN
cana-5239	221	17	with	with	ADP
cana-5239	221	18	significant	significant	ADJ
cana-5239	221	19	implications	implication	NOUN
cana-5239	221	20	for	for	ADP
cana-5239	221	21	farmers	farmer	NOUN
cana-5239	221	22	,	,	PUNCT
cana-5239	221	23	traders	trader	NOUN
cana-5239	221	24	,	,	PUNCT
cana-5239	221	25	and	and	CCONJ
cana-5239	221	26	consumers	consumer	NOUN
cana-5239	221	27	,	,	PUNCT
cana-5239	221	28	particularly	particularly	ADV
cana-5239	221	29	for	for	ADP
cana-5239	221	30	perishable	perishable	ADJ
cana-5239	221	31	crops	crop	NOUN
cana-5239	221	32	like	like	ADP
cana-5239	221	33	vegetables	vegetable	NOUN
cana-5239	221	34	.	.	PUNCT
cana-5239	222	1	this	this	DET
cana-5239	222	2	study	study	NOUN
cana-5239	222	3	on	on	ADP
cana-5239	222	4	agricultural	agricultural	ADJ
cana-5239	222	5	commodity	commodity	NOUN
cana-5239	222	6	price	price	NOUN
cana-5239	222	7	prediction	prediction	NOUN
cana-5239	222	8	using	use	VERB
cana-5239	222	9	ensemble	ensemble	ADJ
cana-5239	222	10	learning	learning	NOUN
cana-5239	222	11	identifies	identify	VERB
cana-5239	222	12	grey	grey	PROPN
cana-5239	222	13	wolf	wolf	PROPN
cana-5239	222	14	optimization	optimization	NOUN
cana-5239	222	15	(	(	PUNCT
cana-5239	222	16	gwo	gwo	PROPN
cana-5239	222	17	)	)	PUNCT
cana-5239	222	18	and	and	CCONJ
cana-5239	222	19	catboost	catboost	VERB
cana-5239	222	20	as	as	ADP
cana-5239	222	21	the	the	DET
cana-5239	222	22	most	most	ADV
cana-5239	222	23	effective	effective	ADJ
cana-5239	222	24	combination	combination	NOUN
cana-5239	222	25	for	for	ADP
cana-5239	222	26	accurate	accurate	ADJ
cana-5239	222	27	forecasting	forecasting	NOUN
cana-5239	222	28	.	.	PUNCT
cana-5239	223	1	gwo	gwo	PROPN
cana-5239	223	2	efficiently	efficiently	ADV
cana-5239	223	3	selects	select	VERB
cana-5239	223	4	the	the	DET
cana-5239	223	5	most	most	ADV
cana-5239	223	6	relevant	relevant	ADJ
cana-5239	223	7	features	feature	NOUN
cana-5239	223	8	,	,	PUNCT
cana-5239	223	9	enhancing	enhance	VERB
cana-5239	223	10	model	model	NOUN
cana-5239	223	11	performance	performance	NOUN
cana-5239	223	12	,	,	PUNCT
cana-5239	223	13	while	while	SCONJ
cana-5239	223	14	catboost	catboost	ADJ
cana-5239	223	15	,	,	PUNCT
cana-5239	223	16	known	know	VERB
cana-5239	223	17	for	for	ADP
cana-5239	223	18	its	its	PRON
cana-5239	223	19	ability	ability	NOUN
cana-5239	223	20	to	to	PART
cana-5239	223	21	handle	handle	VERB
cana-5239	223	22	categorical	categorical	ADJ
cana-5239	223	23	data	datum	NOUN
cana-5239	223	24	and	and	CCONJ
cana-5239	223	25	strong	strong	ADJ
cana-5239	223	26	generalization	generalization	NOUN
cana-5239	223	27	capabilities	capability	NOUN
cana-5239	223	28	,	,	PUNCT
cana-5239	223	29	achieves	achieve	VERB
cana-5239	223	30	the	the	DET
cana-5239	223	31	highest	high	ADJ
cana-5239	223	32	accuracy	accuracy	NOUN
cana-5239	223	33	(	(	PUNCT
cana-5239	223	34	88.14	88.14	NUM
cana-5239	223	35	%	%	NOUN
cana-5239	223	36	)	)	PUNCT
cana-5239	223	37	and	and	CCONJ
cana-5239	223	38	lowest	low	ADJ
cana-5239	223	39	rmse	rmse	NOUN
cana-5239	223	40	(	(	PUNCT
cana-5239	223	41	0.34	0.34	NUM
cana-5239	223	42	)	)	PUNCT
cana-5239	223	43	.	.	PUNCT
cana-5239	224	1	although	although	SCONJ
cana-5239	224	2	other	other	ADJ
cana-5239	224	3	classifiers	classifier	NOUN
cana-5239	224	4	,	,	PUNCT
cana-5239	224	5	such	such	ADJ
cana-5239	224	6	as	as	ADP
cana-5239	224	7	adaboost	adaboost	ADJ
cana-5239	224	8	and	and	CCONJ
cana-5239	224	9	gradient	gradient	ADJ
cana-5239	224	10	boosting	boosting	NOUN
cana-5239	224	11	,	,	PUNCT
cana-5239	224	12	perform	perform	VERB
cana-5239	224	13	well	well	ADV
cana-5239	224	14	with	with	ADP
cana-5239	224	15	gwo	gwo	PROPN
cana-5239	224	16	,	,	PUNCT
cana-5239	224	17	xgboost	xgboost	X
cana-5239	224	18	consistently	consistently	ADV
cana-5239	224	19	underperforms	underperform	VERB
cana-5239	224	20	across	across	ADP
cana-5239	224	21	all	all	DET
cana-5239	224	22	feature	feature	NOUN
cana-5239	224	23	selection	selection	NOUN
cana-5239	224	24	methods	method	NOUN
cana-5239	224	25	.	.	PUNCT
cana-5239	225	1	the	the	DET
cana-5239	225	2	findings	finding	NOUN
cana-5239	225	3	underscore	underscore	VERB
cana-5239	225	4	that	that	SCONJ
cana-5239	225	5	the	the	DET
cana-5239	225	6	gwo	gwo	ADJ
cana-5239	225	7	-	-	ADJ
cana-5239	225	8	catboost	catboost	ADJ
cana-5239	225	9	combination	combination	NOUN
cana-5239	225	10	provides	provide	VERB
cana-5239	225	11	the	the	DET
cana-5239	225	12	most	most	ADV
cana-5239	225	13	reliable	reliable	ADJ
cana-5239	225	14	and	and	CCONJ
cana-5239	225	15	accurate	accurate	ADJ
cana-5239	225	16	approach	approach	NOUN
cana-5239	225	17	for	for	ADP
cana-5239	225	18	agricultural	agricultural	ADJ
cana-5239	225	19	price	price	NOUN
cana-5239	225	20	forecasting	forecasting	NOUN
cana-5239	225	21	,	,	PUNCT
cana-5239	225	22	making	make	VERB
cana-5239	225	23	it	it	PRON
cana-5239	225	24	a	a	DET
cana-5239	225	25	preferred	preferred	ADJ
cana-5239	225	26	choice	choice	NOUN
cana-5239	225	27	for	for	ADP
cana-5239	225	28	this	this	DET
cana-5239	225	29	predictive	predictive	ADJ
cana-5239	225	30	task	task	NOUN
cana-5239	225	31	.	.	PUNCT
cana-5239	226	1	references	reference	NOUN
cana-5239	226	2	[	[	X
cana-5239	226	3	1	1	NUM
cana-5239	226	4	]	]	X
cana-5239	226	5	weis	weis	PROPN
cana-5239	226	6	,	,	PUNCT
cana-5239	226	7	a.j	a.j	PROPN
cana-5239	226	8	.	.	PROPN
cana-5239	226	9	,	,	PUNCT
cana-5239	226	10	2007	2007	NUM
cana-5239	226	11	.	.	PUNCT
cana-5239	227	1	the	the	DET
cana-5239	227	2	global	global	ADJ
cana-5239	227	3	food	food	NOUN
cana-5239	227	4	economy	economy	NOUN
cana-5239	227	5	:	:	PUNCT
cana-5239	227	6	the	the	DET
cana-5239	227	7	battle	battle	NOUN
cana-5239	227	8	for	for	ADP
cana-5239	227	9	the	the	DET
cana-5239	227	10	future	future	NOUN
cana-5239	227	11	of	of	ADP
cana-5239	227	12	farming	farming	NOUN
cana-5239	227	13	.	.	PUNCT
cana-5239	228	1	zed	zed	NUM
cana-5239	228	2	books	book	NOUN
cana-5239	228	3	.	.	PUNCT
cana-5239	229	1	[	[	X
cana-5239	229	2	2	2	NUM
cana-5239	229	3	]	]	PUNCT
cana-5239	229	4	clay	clay	NOUN
cana-5239	229	5	,	,	PUNCT
cana-5239	229	6	j.	j.	PROPN
cana-5239	229	7	,	,	PUNCT
cana-5239	229	8	2013	2013	NUM
cana-5239	229	9	.	.	PUNCT
cana-5239	230	1	world	world	NOUN
cana-5239	230	2	agriculture	agriculture	PROPN
cana-5239	230	3	and	and	CCONJ
cana-5239	230	4	the	the	DET
cana-5239	230	5	environment	environment	NOUN
cana-5239	230	6	:	:	PUNCT
cana-5239	230	7	a	a	DET
cana-5239	230	8	commodity	commodity	NOUN
cana-5239	230	9	-	-	PUNCT
cana-5239	230	10	by	by	ADP
cana-5239	230	11	-	-	PUNCT
cana-5239	230	12	commodity	commodity	NOUN
cana-5239	230	13	guide	guide	NOUN
cana-5239	230	14	to	to	ADP
cana-5239	230	15	impacts	impact	NOUN
cana-5239	230	16	and	and	CCONJ
cana-5239	230	17	practices	practice	NOUN
cana-5239	230	18	.	.	PUNCT
cana-5239	231	1	island	island	NOUN
cana-5239	231	2	press	press	NOUN
cana-5239	231	3	.	.	PUNCT
cana-5239	232	1	[	[	X
cana-5239	232	2	3	3	X
cana-5239	232	3	]	]	PUNCT
cana-5239	232	4	yaşar	yaşar	NOUN
cana-5239	232	5	dinçer	dinçer	PROPN
cana-5239	232	6	,	,	PUNCT
cana-5239	232	7	f.c	f.c	PROPN
cana-5239	232	8	.	.	PROPN
cana-5239	232	9	,	,	PUNCT
cana-5239	232	10	yirmibeşoğlu	yirmibeşoğlu	PROPN
cana-5239	232	11	,	,	PUNCT
cana-5239	232	12	g.	g.	PROPN
cana-5239	232	13	,	,	PUNCT
cana-5239	232	14	narin	narin	NOUN
cana-5239	232	15	,	,	PUNCT
cana-5239	232	16	m.	m.	NOUN
cana-5239	232	17	and	and	CCONJ
cana-5239	232	18	saraç	saraç	PROPN
cana-5239	232	19	,	,	PUNCT
cana-5239	232	20	f.e	f.e	PROPN
cana-5239	232	21	.	.	PROPN
cana-5239	232	22	,	,	PUNCT
cana-5239	232	23	2024	2024	NUM
cana-5239	232	24	.	.	PUNCT
cana-5239	233	1	evaluating	evaluate	VERB
cana-5239	233	2	the	the	DET
cana-5239	233	3	impact	impact	NOUN
cana-5239	233	4	of	of	ADP
cana-5239	233	5	the	the	DET
cana-5239	233	6	covid-19	covid-19	PROPN
cana-5239	233	7	pandemic	pandemic	NOUN
cana-5239	233	8	on	on	ADP
cana-5239	233	9	the	the	DET
cana-5239	233	10	sustainability	sustainability	NOUN
cana-5239	233	11	of	of	ADP
cana-5239	233	12	international	international	ADJ
cana-5239	233	13	trade	trade	NOUN
cana-5239	233	14	in	in	ADP
cana-5239	233	15	agricultural	agricultural	ADJ
cana-5239	233	16	products	product	NOUN
cana-5239	233	17	in	in	ADP
cana-5239	233	18	the	the	DET
cana-5239	233	19	context	context	NOUN
cana-5239	233	20	of	of	ADP
cana-5239	233	21	crisis	crisis	NOUN
cana-5239	233	22	management	management	NOUN
cana-5239	233	23	:	:	PUNCT
cana-5239	233	24	an	an	DET
cana-5239	233	25	assessment	assessment	NOUN
cana-5239	233	26	of	of	ADP
cana-5239	233	27	the	the	DET
cana-5239	233	28	agricultural	agricultural	ADJ
cana-5239	233	29	product	product	NOUN
cana-5239	233	30	exporting	export	VERB
cana-5239	233	31	sectors	sector	NOUN
cana-5239	233	32	in	in	ADP
cana-5239	233	33	antalya	antalya	PROPN
cana-5239	233	34	,	,	PUNCT
cana-5239	233	35	türkiye	türkiye	PROPN
cana-5239	233	36	.	.	PUNCT
cana-5239	234	1	sustainability	sustainability	NOUN
cana-5239	234	2	,	,	PUNCT
cana-5239	234	3	16(13	16(13	NUM
cana-5239	234	4	)	)	PUNCT
cana-5239	234	5	,	,	PUNCT
cana-5239	234	6	p.5684	p.5684	X
cana-5239	234	7	.	.	PUNCT
cana-5239	235	1	[	[	X
cana-5239	235	2	4	4	NUM
cana-5239	235	3	]	]	X
cana-5239	235	4	tripathi	tripathi	PROPN
cana-5239	235	5	,	,	PUNCT
cana-5239	235	6	p.k	p.k	PROPN
cana-5239	235	7	.	.	PROPN
cana-5239	235	8	,	,	PUNCT
cana-5239	235	9	singh	singh	PROPN
cana-5239	235	10	,	,	PUNCT
cana-5239	235	11	c.k	c.k	PROPN
cana-5239	235	12	.	.	PROPN
cana-5239	235	13	,	,	PUNCT
cana-5239	235	14	singh	singh	PROPN
cana-5239	235	15	,	,	PUNCT
cana-5239	235	16	r.	r.	PROPN
cana-5239	235	17	and	and	CCONJ
cana-5239	235	18	deshmukh	deshmukh	PROPN
cana-5239	235	19	,	,	PUNCT
cana-5239	235	20	a.k	a.k	PROPN
cana-5239	235	21	.	.	PROPN
cana-5239	235	22	,	,	PUNCT
cana-5239	235	23	2023	2023	NUM
cana-5239	235	24	.	.	PUNCT
cana-5239	236	1	a	a	DET
cana-5239	236	2	farmer	farmer	NOUN
cana-5239	236	3	-	-	ADJ
cana-5239	236	4	centric	centric	ADJ
cana-5239	236	5	agricultural	agricultural	ADJ
cana-5239	236	6	decision	decision	NOUN
cana-5239	236	7	support	support	NOUN
cana-5239	236	8	system	system	NOUN
cana-5239	236	9	for	for	ADP
cana-5239	236	10	market	market	NOUN
cana-5239	236	11	dynamics	dynamic	NOUN
cana-5239	236	12	in	in	ADP
cana-5239	236	13	a	a	DET
cana-5239	236	14	volatile	volatile	ADJ
cana-5239	236	15	agricultural	agricultural	ADJ
cana-5239	236	16	supply	supply	NOUN
cana-5239	236	17	chain	chain	NOUN
cana-5239	236	18	.	.	PUNCT
cana-5239	237	1	benchmarking	benchmarke	VERB
cana-5239	237	2	:	:	PUNCT
cana-5239	237	3	an	an	DET
cana-5239	237	4	international	international	ADJ
cana-5239	237	5	journal	journal	NOUN
cana-5239	237	6	,	,	PUNCT
cana-5239	237	7	30(10	30(10	NUM
cana-5239	237	8	)	)	PUNCT
cana-5239	237	9	,	,	PUNCT
cana-5239	237	10	pp.3925	pp.3925	PROPN
cana-5239	237	11	-	-	PUNCT
cana-5239	237	12	3952	3952	NUM
cana-5239	237	13	.	.	PUNCT
cana-5239	238	1	[	[	X
cana-5239	238	2	5	5	NUM
cana-5239	238	3	]	]	PUNCT
cana-5239	238	4	sharma	sharma	NOUN
cana-5239	238	5	,	,	PUNCT
cana-5239	238	6	p.	p.	PROPN
cana-5239	238	7	,	,	PUNCT
cana-5239	238	8	paul	paul	PROPN
cana-5239	238	9	,	,	PUNCT
cana-5239	238	10	r.k	r.k	PROPN
cana-5239	238	11	.	.	PROPN
cana-5239	238	12	,	,	PUNCT
cana-5239	238	13	meena	meena	PROPN
cana-5239	238	14	,	,	PUNCT
cana-5239	238	15	d.c	d.c	PROPN
cana-5239	238	16	.	.	PROPN
cana-5239	238	17	and	and	CCONJ
cana-5239	238	18	anwer	anwer	PROPN
cana-5239	238	19	,	,	PUNCT
cana-5239	238	20	e.	e.	PROPN
cana-5239	238	21	,	,	PUNCT
cana-5239	238	22	2023	2023	NUM
cana-5239	238	23	.	.	PUNCT
cana-5239	239	1	understanding	understand	VERB
cana-5239	239	2	price	price	NOUN
cana-5239	239	3	volatility	volatility	NOUN
cana-5239	239	4	and	and	CCONJ
cana-5239	239	5	seasonality	seasonality	NOUN
cana-5239	239	6	in	in	ADP
cana-5239	239	7	agricultural	agricultural	ADJ
cana-5239	239	8	commodities	commodity	NOUN
cana-5239	239	9	in	in	ADP
cana-5239	239	10	india	india	PROPN
cana-5239	239	11	.	.	PUNCT
cana-5239	240	1	agricultural	agricultural	ADJ
cana-5239	240	2	economics	economics	PROPN
cana-5239	240	3	research	research	PROPN
cana-5239	240	4	review	review	PROPN
cana-5239	240	5	,	,	PUNCT
cana-5239	240	6	36(2	36(2	NUM
cana-5239	240	7	)	)	PUNCT
cana-5239	240	8	,	,	PUNCT
cana-5239	240	9	pp.177	pp.177	PROPN
cana-5239	240	10	-	-	X
cana-5239	240	11	188	188	NUM
cana-5239	240	12	.	.	PUNCT
cana-5239	241	1	[	[	X
cana-5239	241	2	6	6	NUM
cana-5239	241	3	]	]	X
cana-5239	241	4	leon	leon	PROPN
cana-5239	241	5	,	,	PUNCT
cana-5239	241	6	j.	j.	PROPN
cana-5239	241	7	,	,	PUNCT
cana-5239	241	8	2024	2024	NUM
cana-5239	241	9	.	.	PUNCT
cana-5239	242	1	forecasting	forecast	VERB
cana-5239	242	2	imported	import	VERB
cana-5239	242	3	fruit	fruit	NOUN
cana-5239	242	4	prices	price	NOUN
cana-5239	242	5	in	in	ADP
cana-5239	242	6	the	the	DET
cana-5239	242	7	united	united	PROPN
cana-5239	242	8	states	states	PROPN
cana-5239	242	9	using	use	VERB
cana-5239	242	10	neural	neural	ADJ
cana-5239	242	11	networks	network	NOUN
cana-5239	242	12	(	(	PUNCT
cana-5239	242	13	doctoral	doctoral	ADJ
cana-5239	242	14	dissertation	dissertation	NOUN
cana-5239	242	15	,	,	PUNCT
cana-5239	242	16	national	national	ADJ
cana-5239	242	17	university	university	NOUN
cana-5239	242	18	)	)	PUNCT
cana-5239	242	19	.	.	PUNCT
cana-5239	243	1	[	[	X
cana-5239	243	2	7	7	X
cana-5239	243	3	]	]	X
cana-5239	243	4	ben	ben	PROPN
cana-5239	243	5	ameur	ameur	PROPN
cana-5239	243	6	,	,	PUNCT
cana-5239	243	7	h.	h.	PROPN
cana-5239	243	8	,	,	PUNCT
cana-5239	243	9	boubaker	boubaker	PROPN
cana-5239	243	10	,	,	PUNCT
cana-5239	243	11	s.	s.	PROPN
cana-5239	243	12	,	,	PUNCT
cana-5239	243	13	ftiti	ftiti	PROPN
cana-5239	243	14	,	,	PUNCT
cana-5239	243	15	z.	z.	PROPN
cana-5239	243	16	,	,	PUNCT
cana-5239	243	17	louhichi	louhichi	PROPN
cana-5239	243	18	,	,	PUNCT
cana-5239	243	19	w.	w.	PROPN
cana-5239	243	20	and	and	CCONJ
cana-5239	243	21	tissaoui	tissaoui	PROPN
cana-5239	243	22	,	,	PUNCT
cana-5239	243	23	k.	k.	PROPN
cana-5239	243	24	,	,	PUNCT
cana-5239	243	25	2024	2024	NUM
cana-5239	243	26	.	.	PUNCT
cana-5239	244	1	forecasting	forecast	VERB
cana-5239	244	2	commodity	commodity	NOUN
cana-5239	244	3	prices	price	NOUN
cana-5239	244	4	:	:	PUNCT
cana-5239	244	5	empirical	empirical	ADJ
cana-5239	244	6	evidence	evidence	NOUN
cana-5239	244	7	using	use	VERB
cana-5239	244	8	deep	deep	ADJ
cana-5239	244	9	learning	learning	NOUN
cana-5239	244	10	tools	tool	NOUN
cana-5239	244	11	.	.	PUNCT
cana-5239	245	1	annals	annal	NOUN
cana-5239	245	2	of	of	ADP
cana-5239	245	3	operations	operation	NOUN
cana-5239	245	4	research	research	NOUN
cana-5239	245	5	,	,	PUNCT
cana-5239	245	6	339(1	339(1	NUM
cana-5239	245	7	)	)	PUNCT
cana-5239	245	8	,	,	PUNCT
cana-5239	245	9	pp.349	pp.349	NOUN
cana-5239	245	10	-	-	PUNCT
cana-5239	245	11	367	367	NUM
cana-5239	245	12	.	.	PUNCT
cana-5239	246	1	[	[	X
cana-5239	246	2	8	8	NUM
cana-5239	246	3	]	]	X
cana-5239	246	4	banerjee	banerjee	PROPN
cana-5239	246	5	,	,	PUNCT
cana-5239	246	6	s.	s.	PROPN
cana-5239	246	7	and	and	CCONJ
cana-5239	246	8	mondal	mondal	PROPN
cana-5239	246	9	,	,	PUNCT
cana-5239	246	10	a.c	a.c	PROPN
cana-5239	246	11	.	.	PROPN
cana-5239	246	12	,	,	PUNCT
cana-5239	246	13	2023	2023	NUM
cana-5239	246	14	.	.	PUNCT
cana-5239	247	1	an	an	DET
cana-5239	247	2	ingenious	ingenious	ADJ
cana-5239	247	3	method	method	NOUN
cana-5239	247	4	for	for	ADP
cana-5239	247	5	estimating	estimate	VERB
cana-5239	247	6	future	future	ADJ
cana-5239	247	7	crop	crop	NOUN
cana-5239	247	8	prices	price	NOUN
cana-5239	247	9	that	that	PRON
cana-5239	247	10	emphasises	emphasise	VERB
cana-5239	247	11	machine	machine	NOUN
cana-5239	247	12	learning	learning	NOUN
cana-5239	247	13	and	and	CCONJ
cana-5239	247	14	deep	deep	ADJ
cana-5239	247	15	learning	learning	NOUN
cana-5239	247	16	models	model	NOUN
cana-5239	247	17	.	.	PUNCT
cana-5239	248	1	international	international	ADJ
cana-5239	248	2	journal	journal	PROPN
cana-5239	248	3	of	of	ADP
cana-5239	248	4	information	information	NOUN
cana-5239	248	5	technology	technology	NOUN
cana-5239	248	6	,	,	PUNCT
cana-5239	248	7	15(8	15(8	NOUN
cana-5239	248	8	)	)	PUNCT
cana-5239	248	9	,	,	PUNCT
cana-5239	248	10	pp.4291	pp.4291	PROPN
cana-5239	248	11	-	-	PUNCT
cana-5239	248	12	4313	4313	NUM
cana-5239	248	13	.	.	PUNCT
cana-5239	249	1	[	[	X
cana-5239	249	2	9	9	NUM
cana-5239	249	3	]	]	X
cana-5239	249	4	effrosynidis	effrosynidis	PROPN
cana-5239	249	5	,	,	PUNCT
cana-5239	249	6	d.	d.	PROPN
cana-5239	249	7	,	,	PUNCT
cana-5239	249	8	spiliotis	spiliotis	PROPN
cana-5239	249	9	,	,	PUNCT
cana-5239	249	10	e.	e.	PROPN
cana-5239	249	11	,	,	PUNCT
cana-5239	249	12	sylaios	sylaios	PROPN
cana-5239	249	13	,	,	PUNCT
cana-5239	249	14	g.	g.	NOUN
cana-5239	249	15	and	and	CCONJ
cana-5239	249	16	arampatzis	arampatzi	NOUN
cana-5239	249	17	,	,	PUNCT
cana-5239	249	18	a.	a.	NOUN
cana-5239	249	19	,	,	PUNCT
cana-5239	249	20	2023	2023	NUM
cana-5239	249	21	.	.	PUNCT
cana-5239	249	22	time	time	NOUN
cana-5239	249	23	series	series	PROPN
cana-5239	249	24	and	and	CCONJ
cana-5239	249	25	regression	regression	NOUN
cana-5239	249	26	methods	method	NOUN
cana-5239	249	27	for	for	ADP
cana-5239	249	28	univariate	univariate	ADJ
cana-5239	249	29	environmental	environmental	ADJ
cana-5239	249	30	forecasting	forecasting	NOUN
cana-5239	249	31	:	:	PUNCT
cana-5239	249	32	an	an	DET
cana-5239	249	33	empirical	empirical	ADJ
cana-5239	249	34	evaluation	evaluation	NOUN
cana-5239	249	35	.	.	PUNCT
cana-5239	250	1	science	science	NOUN
cana-5239	250	2	of	of	ADP
cana-5239	250	3	the	the	DET
cana-5239	250	4	total	total	ADJ
cana-5239	250	5	environment	environment	NOUN
cana-5239	250	6	,	,	PUNCT
cana-5239	250	7	875	875	NUM
cana-5239	250	8	,	,	PUNCT
cana-5239	250	9	p.162580	p.162580	NOUN
cana-5239	250	10	.	.	PUNCT
cana-5239	251	1	communications	communication	NOUN
cana-5239	251	2	on	on	ADP
cana-5239	251	3	applied	apply	VERB
cana-5239	251	4	nonlinear	nonlinear	ADJ
cana-5239	251	5	analysis	analysis	NOUN
cana-5239	251	6	issn	issn	NOUN
cana-5239	251	7	:	:	PUNCT
cana-5239	251	8	1074	1074	NUM
cana-5239	251	9	-	-	PUNCT
cana-5239	251	10	133x	133x	NUM
cana-5239	251	11	vol	vol	VERB
cana-5239	251	12	32	32	NUM
cana-5239	251	13	no	no	NOUN
cana-5239	251	14	.	.	PUNCT
cana-5239	252	1	10s	10	NOUN
cana-5239	252	2	(	(	PUNCT
cana-5239	252	3	2025	2025	NUM
cana-5239	252	4	)	)	PUNCT
cana-5239	252	5	1386	1386	NUM
cana-5239	252	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5239	253	1	[	[	X
cana-5239	253	2	10	10	NUM
cana-5239	253	3	]	]	X
cana-5239	253	4	rane	rane	PROPN
cana-5239	253	5	,	,	PUNCT
cana-5239	253	6	n.	n.	PROPN
cana-5239	253	7	,	,	PUNCT
cana-5239	253	8	choudhary	choudhary	PROPN
cana-5239	253	9	,	,	PUNCT
cana-5239	253	10	s.p	s.p	PROPN
cana-5239	253	11	.	.	PROPN
cana-5239	253	12	and	and	CCONJ
cana-5239	253	13	rane	rane	PROPN
cana-5239	253	14	,	,	PUNCT
cana-5239	253	15	j.	j.	PROPN
cana-5239	253	16	,	,	PUNCT
cana-5239	253	17	2024	2024	NUM
cana-5239	253	18	.	.	PUNCT
cana-5239	254	1	ensemble	ensemble	ADJ
cana-5239	254	2	deep	deep	ADJ
cana-5239	254	3	learning	learning	NOUN
cana-5239	254	4	and	and	CCONJ
cana-5239	254	5	machine	machine	NOUN
cana-5239	254	6	learning	learning	NOUN
cana-5239	254	7	:	:	PUNCT
cana-5239	254	8	applications	application	NOUN
cana-5239	254	9	,	,	PUNCT
cana-5239	254	10	opportunities	opportunity	NOUN
cana-5239	254	11	,	,	PUNCT
cana-5239	254	12	challenges	challenge	NOUN
cana-5239	254	13	,	,	PUNCT
cana-5239	254	14	and	and	CCONJ
cana-5239	254	15	future	future	ADJ
cana-5239	254	16	directions	direction	NOUN
cana-5239	254	17	.	.	PUNCT
cana-5239	255	1	studies	study	NOUN
cana-5239	255	2	in	in	ADP
cana-5239	255	3	medical	medical	ADJ
cana-5239	255	4	and	and	CCONJ
cana-5239	255	5	health	health	NOUN
cana-5239	255	6	sciences	science	NOUN
cana-5239	255	7	,	,	PUNCT
cana-5239	255	8	1(2	1(2	NUM
cana-5239	255	9	)	)	PUNCT
cana-5239	255	10	,	,	PUNCT
cana-5239	255	11	pp.18	pp.18	PROPN
cana-5239	255	12	-	-	PUNCT
cana-5239	255	13	41	41	NUM
cana-5239	255	14	.	.	PUNCT
cana-5239	256	1	[	[	X
cana-5239	256	2	11	11	NUM
cana-5239	256	3	]	]	X
cana-5239	256	4	zhang	zhang	PROPN
cana-5239	256	5	,	,	PUNCT
cana-5239	256	6	y.	y.	PROPN
cana-5239	256	7	,	,	PUNCT
cana-5239	256	8	liu	liu	PROPN
cana-5239	256	9	,	,	PUNCT
cana-5239	256	10	j.	j.	PROPN
cana-5239	256	11	and	and	CCONJ
cana-5239	256	12	shen	shen	PROPN
cana-5239	256	13	,	,	PUNCT
cana-5239	256	14	w.	w.	PROPN
cana-5239	256	15	,	,	PUNCT
cana-5239	256	16	2022	2022	NUM
cana-5239	256	17	.	.	PUNCT
cana-5239	257	1	a	a	DET
cana-5239	257	2	review	review	NOUN
cana-5239	257	3	of	of	ADP
cana-5239	257	4	ensemble	ensemble	ADJ
cana-5239	257	5	learning	learning	NOUN
cana-5239	257	6	algorithms	algorithm	NOUN
cana-5239	257	7	used	use	VERB
cana-5239	257	8	in	in	ADP
cana-5239	257	9	remote	remote	ADJ
cana-5239	257	10	sensing	sense	VERB
cana-5239	257	11	applications	application	NOUN
cana-5239	257	12	.	.	PUNCT
cana-5239	258	1	applied	apply	VERB
cana-5239	258	2	sciences	science	NOUN
cana-5239	258	3	,	,	PUNCT
cana-5239	258	4	12(17	12(17	NUM
cana-5239	258	5	)	)	PUNCT
cana-5239	258	6	,	,	PUNCT
cana-5239	258	7	p.8654	p.8654	PROPN
cana-5239	258	8	.	.	PUNCT
cana-5239	259	1	[	[	X
cana-5239	259	2	12	12	NUM
cana-5239	259	3	]	]	X
cana-5239	259	4	zhang	zhang	PROPN
cana-5239	259	5	,	,	PUNCT
cana-5239	259	6	d.	d.	PROPN
cana-5239	259	7	,	,	PUNCT
cana-5239	259	8	chen	chen	PROPN
cana-5239	259	9	,	,	PUNCT
cana-5239	259	10	s.	s.	PROPN
cana-5239	259	11	,	,	PUNCT
cana-5239	259	12	liwen	liwen	PROPN
cana-5239	259	13	,	,	PUNCT
cana-5239	259	14	l.	l.	PROPN
cana-5239	259	15	and	and	CCONJ
cana-5239	259	16	xia	xia	PROPN
cana-5239	259	17	,	,	PUNCT
cana-5239	259	18	q.	q.	PROPN
cana-5239	259	19	,	,	PUNCT
cana-5239	259	20	2020	2020	NUM
cana-5239	259	21	.	.	PUNCT
cana-5239	260	1	forecasting	forecast	VERB
cana-5239	260	2	agricultural	agricultural	ADJ
cana-5239	260	3	commodity	commodity	NOUN
cana-5239	260	4	prices	price	NOUN
cana-5239	260	5	using	use	VERB
cana-5239	260	6	model	model	NOUN
cana-5239	260	7	selection	selection	NOUN
cana-5239	260	8	framework	framework	NOUN
cana-5239	260	9	with	with	ADP
cana-5239	260	10	time	time	NOUN
cana-5239	260	11	series	series	PROPN
cana-5239	260	12	features	feature	NOUN
cana-5239	260	13	and	and	CCONJ
cana-5239	260	14	forecast	forecast	NOUN
cana-5239	260	15	horizons	horizon	NOUN
cana-5239	260	16	.	.	PUNCT
cana-5239	261	1	ieee	ieee	NOUN
cana-5239	261	2	access	access	NOUN
cana-5239	261	3	,	,	PUNCT
cana-5239	261	4	8	8	NUM
cana-5239	261	5	,	,	PUNCT
cana-5239	261	6	pp.28197	pp.28197	PROPN
cana-5239	261	7	-	-	PUNCT
cana-5239	261	8	28209	28209	NUM
cana-5239	261	9	.	.	PUNCT
cana-5239	262	1	[	[	X
cana-5239	262	2	13	13	NUM
cana-5239	262	3	]	]	SYM
cana-5239	262	4	bhavani	bhavani	PROPN
cana-5239	262	5	,	,	PUNCT
cana-5239	262	6	m.	m.	NOUN
cana-5239	262	7	and	and	CCONJ
cana-5239	262	8	mounika	mounika	NOUN
cana-5239	262	9	,	,	PUNCT
cana-5239	262	10	p.	p.	NOUN
cana-5239	262	11	,	,	PUNCT
cana-5239	262	12	2022	2022	NUM
cana-5239	262	13	.	.	PUNCT
cana-5239	263	1	a	a	DET
cana-5239	263	2	novel	novel	ADJ
cana-5239	263	3	model	model	NOUN
cana-5239	263	4	selection	selection	NOUN
cana-5239	263	5	framework	framework	NOUN
cana-5239	263	6	for	for	ADP
cana-5239	263	7	forecasting	forecast	VERB
cana-5239	263	8	agricultural	agricultural	ADJ
cana-5239	263	9	commodity	commodity	NOUN
cana-5239	263	10	prices	price	NOUN
cana-5239	263	11	using	use	VERB
cana-5239	263	12	time	time	NOUN
cana-5239	263	13	series	series	PROPN
cana-5239	263	14	features	feature	NOUN
cana-5239	263	15	and	and	CCONJ
cana-5239	263	16	forecast	forecast	NOUN
cana-5239	263	17	horizons	horizon	NOUN
cana-5239	263	18	.	.	PUNCT
cana-5239	264	1	international	international	ADJ
cana-5239	264	2	journal	journal	PROPN
cana-5239	264	3	of	of	ADP
cana-5239	264	4	scientific	scientific	ADJ
cana-5239	264	5	research	research	NOUN
cana-5239	264	6	in	in	ADP
cana-5239	264	7	science	science	NOUN
cana-5239	264	8	and	and	CCONJ
cana-5239	264	9	technology	technology	NOUN
cana-5239	264	10	,	,	PUNCT
cana-5239	264	11	pp.134	pp.134	PROPN
cana-5239	264	12	-	-	SYM
cana-5239	264	13	144	144	NUM
cana-5239	264	14	.	.	PUNCT
cana-5239	265	1	[	[	X
cana-5239	265	2	14	14	NUM
cana-5239	265	3	]	]	X
cana-5239	265	4	gárate	gárate	NOUN
cana-5239	265	5	-	-	PUNCT
cana-5239	265	6	escamila	escamila	ADJ
cana-5239	265	7	,	,	PUNCT
cana-5239	265	8	a.k	a.k	PROPN
cana-5239	265	9	.	.	PROPN
cana-5239	265	10	,	,	PUNCT
cana-5239	265	11	el	el	PROPN
cana-5239	265	12	hassani	hassani	PROPN
cana-5239	265	13	,	,	PUNCT
cana-5239	265	14	a.h	a.h	PROPN
cana-5239	265	15	.	.	PROPN
cana-5239	265	16	and	and	CCONJ
cana-5239	265	17	andrès	andrès	PROPN
cana-5239	265	18	,	,	PUNCT
cana-5239	265	19	e.	e.	PROPN
cana-5239	265	20	,	,	PUNCT
cana-5239	265	21	2020	2020	NUM
cana-5239	265	22	.	.	PUNCT
cana-5239	266	1	classification	classification	NOUN
cana-5239	266	2	models	model	NOUN
cana-5239	266	3	for	for	ADP
cana-5239	266	4	heart	heart	NOUN
cana-5239	266	5	disease	disease	NOUN
cana-5239	266	6	prediction	prediction	NOUN
cana-5239	266	7	using	use	VERB
cana-5239	266	8	feature	feature	NOUN
cana-5239	266	9	selection	selection	NOUN
cana-5239	266	10	and	and	CCONJ
cana-5239	266	11	pca	pca	PROPN
cana-5239	266	12	.	.	PUNCT
cana-5239	267	1	informatics	informatic	NOUN
cana-5239	267	2	in	in	ADP
cana-5239	267	3	medicine	medicine	NOUN
cana-5239	267	4	unlocked	unlock	VERB
cana-5239	267	5	,	,	PUNCT
cana-5239	267	6	19	19	NUM
cana-5239	267	7	,	,	PUNCT
cana-5239	267	8	p.100330	p.100330	NOUN
cana-5239	267	9	.	.	PUNCT
cana-5239	268	1	[	[	X
cana-5239	268	2	15	15	NUM
cana-5239	268	3	]	]	SYM
cana-5239	268	4	sya'idah	sya'idah	PROPN
cana-5239	268	5	,	,	PUNCT
cana-5239	268	6	i.b	i.b	PROPN
cana-5239	268	7	.	.	PROPN
cana-5239	268	8	,	,	PUNCT
cana-5239	268	9	surono	surono	PROPN
cana-5239	268	10	,	,	PUNCT
cana-5239	268	11	s.	s.	PROPN
cana-5239	268	12	and	and	CCONJ
cana-5239	268	13	wen	wen	PROPN
cana-5239	268	14	,	,	PUNCT
cana-5239	268	15	g.k	g.k	PROPN
cana-5239	268	16	.	.	PROPN
cana-5239	268	17	,	,	PUNCT
cana-5239	268	18	2024	2024	NUM
cana-5239	268	19	.	.	PUNCT
cana-5239	269	1	dynamicweighted	dynamicweighte	VERB
cana-5239	269	2	particle	particle	NOUN
cana-5239	269	3	swarm	swarm	NOUN
cana-5239	269	4	optimization	optimization	NOUN
cana-5239	269	5	-	-	PUNCT
cana-5239	269	6	support	support	NOUN
cana-5239	269	7	vector	vector	NOUN
cana-5239	269	8	machine	machine	NOUN
cana-5239	269	9	optimization	optimization	NOUN
cana-5239	269	10	in	in	ADP
cana-5239	269	11	recursive	recursive	ADJ
cana-5239	269	12	feature	feature	NOUN
cana-5239	269	13	elimination	elimination	NOUN
cana-5239	269	14	feature	feature	NOUN
cana-5239	269	15	selection	selection	NOUN
cana-5239	269	16	.	.	PUNCT
cana-5239	270	1	matrik	matrik	PROPN
cana-5239	270	2	:	:	PUNCT
cana-5239	271	1	jurnal	jurnal	ADJ
cana-5239	271	2	manajemen	manajeman	NOUN
cana-5239	271	3	,	,	PUNCT
cana-5239	271	4	teknik	teknik	NOUN
cana-5239	271	5	informatika	informatika	PROPN
cana-5239	271	6	dan	dan	PROPN
cana-5239	271	7	rekayasa	rekayasa	PROPN
cana-5239	271	8	komputer	komputer	PROPN
cana-5239	271	9	,	,	PUNCT
cana-5239	271	10	23(3	23(3	NUM
cana-5239	271	11	)	)	PUNCT
cana-5239	271	12	,	,	PUNCT
cana-5239	271	13	pp.627	pp.627	PROPN
cana-5239	271	14	-	-	PUNCT
cana-5239	271	15	640	640	NUM
cana-5239	271	16	.	.	PUNCT
cana-5239	272	1	[	[	X
cana-5239	272	2	16	16	NUM
cana-5239	272	3	]	]	X
cana-5239	272	4	fang	fang	X
cana-5239	272	5	,	,	PUNCT
cana-5239	272	6	y.	y.	PROPN
cana-5239	272	7	,	,	PUNCT
cana-5239	272	8	yao	yao	PROPN
cana-5239	272	9	,	,	PUNCT
cana-5239	272	10	y.	y.	PROPN
cana-5239	272	11	,	,	PUNCT
cana-5239	272	12	lin	lin	PROPN
cana-5239	272	13	,	,	PUNCT
cana-5239	272	14	x.	x.	PROPN
cana-5239	272	15	,	,	PUNCT
cana-5239	272	16	wang	wang	PROPN
cana-5239	272	17	,	,	PUNCT
cana-5239	272	18	j.	j.	PROPN
cana-5239	272	19	and	and	CCONJ
cana-5239	272	20	zhai	zhai	PROPN
cana-5239	272	21	,	,	PUNCT
cana-5239	272	22	h.	h.	PROPN
cana-5239	272	23	,	,	PUNCT
cana-5239	272	24	2024	2024	NUM
cana-5239	272	25	.	.	PUNCT
cana-5239	273	1	a	a	DET
cana-5239	273	2	feature	feature	NOUN
cana-5239	273	3	selection	selection	NOUN
cana-5239	273	4	based	base	VERB
cana-5239	273	5	on	on	ADP
cana-5239	273	6	genetic	genetic	ADJ
cana-5239	273	7	algorithm	algorithm	NOUN
cana-5239	273	8	for	for	ADP
cana-5239	273	9	intrusion	intrusion	NOUN
cana-5239	273	10	detection	detection	NOUN
cana-5239	273	11	of	of	ADP
cana-5239	273	12	industrial	industrial	ADJ
cana-5239	273	13	control	control	NOUN
cana-5239	273	14	systems	system	NOUN
cana-5239	273	15	.	.	PUNCT
cana-5239	274	1	computers	computer	NOUN
cana-5239	274	2	&	&	CCONJ
cana-5239	274	3	security	security	NOUN
cana-5239	274	4	,	,	PUNCT
cana-5239	274	5	139	139	NUM
cana-5239	274	6	,	,	PUNCT
cana-5239	274	7	p.103675	p.103675	NOUN
cana-5239	274	8	.	.	PUNCT
cana-5239	275	1	[	[	X
cana-5239	275	2	17	17	NUM
cana-5239	275	3	]	]	X
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cana-5239	275	5	,	,	PUNCT
cana-5239	275	6	y.	y.	PROPN
cana-5239	275	7	,	,	PUNCT
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cana-5239	275	9	,	,	PUNCT
cana-5239	275	10	s.	s.	PROPN
cana-5239	275	11	and	and	CCONJ
cana-5239	275	12	wang	wang	PROPN
cana-5239	275	13	,	,	PUNCT
cana-5239	275	14	g.g	g.g	PROPN
cana-5239	275	15	.	.	PROPN
cana-5239	275	16	,	,	PUNCT
cana-5239	275	17	2024	2024	NUM
cana-5239	275	18	.	.	PUNCT
cana-5239	276	1	role	role	NOUN
cana-5239	276	2	-	-	PUNCT
cana-5239	276	3	oriented	orient	VERB
cana-5239	276	4	binary	binary	ADJ
cana-5239	276	5	grey	grey	PROPN
cana-5239	276	6	wolf	wolf	PROPN
cana-5239	276	7	optimizer	optimizer	NOUN
cana-5239	276	8	using	use	VERB
cana-5239	276	9	foraging	foraging	NOUN
cana-5239	276	10	-	-	PUNCT
cana-5239	276	11	following	follow	VERB
cana-5239	276	12	and	and	CCONJ
cana-5239	276	13	lévy	lévy	ADJ
cana-5239	276	14	flight	flight	NOUN
cana-5239	276	15	for	for	ADP
cana-5239	276	16	feature	feature	NOUN
cana-5239	276	17	selection	selection	NOUN
cana-5239	276	18	.	.	PUNCT
cana-5239	277	1	applied	apply	VERB
cana-5239	277	2	mathematical	mathematical	ADJ
cana-5239	277	3	modelling	modelling	NOUN
cana-5239	277	4	,	,	PUNCT
cana-5239	277	5	126	126	NUM
cana-5239	277	6	,	,	PUNCT
cana-5239	277	7	pp.310	pp.310	PROPN
cana-5239	277	8	-	-	PUNCT
cana-5239	277	9	326	326	NUM
cana-5239	277	10	.	.	PUNCT
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cana-5239	278	2	18	18	NUM
cana-5239	278	3	]	]	X
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cana-5239	278	6	,	,	PUNCT
cana-5239	278	7	s.	s.	PROPN
cana-5239	278	8	,	,	PUNCT
cana-5239	278	9	jennings	jennings	PROPN
cana-5239	278	10	,	,	PUNCT
cana-5239	278	11	e.	e.	PROPN
cana-5239	278	12	,	,	PUNCT
cana-5239	278	13	lenters	lenters	PROPN
cana-5239	278	14	,	,	PUNCT
cana-5239	278	15	j.d	j.d	PROPN
cana-5239	278	16	.	.	PROPN
cana-5239	278	17	,	,	PUNCT
cana-5239	278	18	verburg	verburg	PROPN
cana-5239	278	19	,	,	PUNCT
cana-5239	278	20	p.	p.	NOUN
cana-5239	278	21	,	,	PUNCT
cana-5239	278	22	tan	tan	PROPN
cana-5239	278	23	,	,	PUNCT
cana-5239	278	24	z.	z.	PROPN
cana-5239	278	25	,	,	PUNCT
cana-5239	278	26	perroud	perroud	NOUN
cana-5239	278	27	,	,	PUNCT
cana-5239	278	28	m.	m.	NOUN
cana-5239	278	29	,	,	PUNCT
cana-5239	278	30	janssen	janssen	PROPN
cana-5239	278	31	,	,	PUNCT
cana-5239	278	32	a.b	a.b	PROPN
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cana-5239	278	34	and	and	CCONJ
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cana-5239	278	36	,	,	PUNCT
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cana-5239	278	41	.	.	PUNCT
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cana-5239	279	2	modeling	modeling	NOUN
cana-5239	279	3	of	of	ADP
cana-5239	279	4	global	global	PROPN
cana-5239	279	5	lake	lake	PROPN
cana-5239	279	6	evaporation	evaporation	NOUN
cana-5239	279	7	under	under	ADP
cana-5239	279	8	climate	climate	NOUN
cana-5239	279	9	change	change	NOUN
cana-5239	279	10	.	.	PUNCT
cana-5239	280	1	journal	journal	NOUN
cana-5239	280	2	of	of	ADP
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cana-5239	280	5	631	631	NUM
cana-5239	280	6	,	,	PUNCT
cana-5239	280	7	p.130647	p.130647	NOUN
cana-5239	280	8	.	.	PUNCT
cana-5239	281	1	[	[	X
cana-5239	281	2	19	19	NUM
cana-5239	281	3	]	]	PUNCT
cana-5239	281	4	bâra	bâra	NOUN
cana-5239	281	5	,	,	PUNCT
cana-5239	281	6	a.	a.	NOUN
cana-5239	281	7	and	and	CCONJ
cana-5239	281	8	oprea	oprea	PROPN
cana-5239	281	9	,	,	PUNCT
cana-5239	281	10	s.v	s.v	PROPN
cana-5239	281	11	.	.	PROPN
cana-5239	281	12	,	,	PUNCT
cana-5239	281	13	2024	2024	NUM
cana-5239	281	14	.	.	PUNCT
cana-5239	282	1	an	an	DET
cana-5239	282	2	ensemble	ensemble	ADJ
cana-5239	282	3	learning	learning	NOUN
cana-5239	282	4	method	method	NOUN
cana-5239	282	5	for	for	ADP
cana-5239	282	6	bitcoin	bitcoin	ADJ
cana-5239	282	7	price	price	NOUN
cana-5239	282	8	prediction	prediction	NOUN
cana-5239	282	9	based	base	VERB
cana-5239	282	10	on	on	ADP
cana-5239	282	11	volatility	volatility	NOUN
cana-5239	282	12	indicators	indicator	NOUN
cana-5239	282	13	and	and	CCONJ
cana-5239	282	14	trend	trend	NOUN
cana-5239	282	15	.	.	PUNCT
cana-5239	283	1	engineering	engineering	NOUN
cana-5239	283	2	applications	application	NOUN
cana-5239	283	3	of	of	ADP
cana-5239	283	4	artificial	artificial	ADJ
cana-5239	283	5	intelligence	intelligence	NOUN
cana-5239	283	6	,	,	PUNCT
cana-5239	283	7	133	133	NUM
cana-5239	283	8	,	,	PUNCT
cana-5239	283	9	p.107991	p.107991	NUM
cana-5239	283	10	.	.	PUNCT
cana-5239	284	1	[	[	X
cana-5239	284	2	20	20	NUM
cana-5239	284	3	]	]	SYM
cana-5239	284	4	zhang	zhang	PROPN
cana-5239	284	5	,	,	PUNCT
cana-5239	284	6	j.	j.	PROPN
cana-5239	284	7	and	and	CCONJ
cana-5239	284	8	chen	chen	PROPN
cana-5239	284	9	,	,	PUNCT
cana-5239	284	10	x.	x.	NOUN
cana-5239	284	11	,	,	PUNCT
cana-5239	284	12	2024	2024	NUM
cana-5239	284	13	.	.	PUNCT
cana-5239	285	1	a	a	DET
cana-5239	285	2	two	two	NUM
cana-5239	285	3	-	-	PUNCT
cana-5239	285	4	stage	stage	NOUN
cana-5239	285	5	model	model	NOUN
cana-5239	285	6	for	for	ADP
cana-5239	285	7	stock	stock	NOUN
cana-5239	285	8	price	price	NOUN
cana-5239	285	9	prediction	prediction	NOUN
cana-5239	285	10	based	base	VERB
cana-5239	285	11	on	on	ADP
cana-5239	285	12	variational	variational	ADJ
cana-5239	285	13	mode	mode	NOUN
cana-5239	285	14	decomposition	decomposition	NOUN
cana-5239	285	15	and	and	CCONJ
cana-5239	285	16	ensemble	ensemble	ADJ
cana-5239	285	17	machine	machine	NOUN
cana-5239	285	18	learning	learning	NOUN
cana-5239	285	19	method	method	NOUN
cana-5239	285	20	.	.	PUNCT
cana-5239	286	1	soft	soft	ADJ
cana-5239	286	2	computing	computing	NOUN
cana-5239	286	3	,	,	PUNCT
cana-5239	286	4	28(3	28(3	NUM
cana-5239	286	5	)	)	PUNCT
cana-5239	286	6	,	,	PUNCT
cana-5239	286	7	pp.23852408	pp.23852408	PROPN
cana-5239	286	8	.	.	PUNCT
cana-5239	287	1	[	[	X
cana-5239	287	2	21	21	NUM
cana-5239	287	3	]	]	X
cana-5239	287	4	abdullah	abdullah	PROPN
cana-5239	287	5	et	et	PROPN
cana-5239	287	6	al	al	PROPN
cana-5239	287	7	.	.	PROPN
cana-5239	287	8	,	,	PUNCT
cana-5239	287	9	"	"	PUNCT
cana-5239	287	10	intelligent	intelligent	ADJ
cana-5239	287	11	hybrid	hybrid	ADJ
cana-5239	287	12	arima	arima	NOUN
cana-5239	287	13	-	-	PUNCT
cana-5239	287	14	narnet	narnet	NOUN
cana-5239	287	15	time	time	NOUN
cana-5239	287	16	series	series	PROPN
cana-5239	287	17	model	model	PROPN
cana-5239	287	18	to	to	PART
cana-5239	287	19	forecast	forecast	VERB
cana-5239	287	20	coconut	coconut	NOUN
cana-5239	287	21	price	price	NOUN
cana-5239	287	22	,	,	PUNCT
cana-5239	287	23	"	"	PUNCT
cana-5239	287	24	in	in	ADP
cana-5239	287	25	ieee	ieee	NOUN
cana-5239	287	26	access	access	NOUN
cana-5239	287	27	,	,	PUNCT
cana-5239	287	28	vol	vol	NOUN
cana-5239	287	29	.	.	PROPN
cana-5239	287	30	11	11	NUM
cana-5239	287	31	,	,	PUNCT
cana-5239	287	32	pp	pp	ADJ
cana-5239	287	33	.	.	PUNCT
cana-5239	288	1	48568	48568	NUM
cana-5239	288	2	-	-	SYM
cana-5239	288	3	48577	48577	NUM
cana-5239	288	4	,	,	PUNCT
cana-5239	288	5	2023	2023	NUM
cana-5239	288	6	.	.	PUNCT
cana-5239	289	1	[	[	X
cana-5239	289	2	22	22	NUM
cana-5239	289	3	]	]	PUNCT
cana-5239	289	4	mohanty	mohanty	PROPN
cana-5239	289	5	,	,	PUNCT
cana-5239	289	6	m.k	m.k	PROPN
cana-5239	289	7	.	.	PROPN
cana-5239	289	8	,	,	PUNCT
cana-5239	289	9	thakurta	thakurta	PROPN
cana-5239	289	10	,	,	PUNCT
cana-5239	289	11	p.k.g	p.k.g	NOUN
cana-5239	289	12	.	.	PUNCT
cana-5239	289	13	&	&	CCONJ
cana-5239	289	14	kar	kar	PROPN
cana-5239	289	15	,	,	PUNCT
cana-5239	289	16	s.	s.	PROPN
cana-5239	289	17	agricultural	agricultural	ADJ
cana-5239	289	18	commodity	commodity	NOUN
cana-5239	289	19	price	price	NOUN
cana-5239	289	20	prediction	prediction	NOUN
cana-5239	289	21	model	model	NOUN
cana-5239	289	22	:	:	PUNCT
cana-5239	289	23	a	a	DET
cana-5239	289	24	machine	machine	NOUN
cana-5239	289	25	learning	learn	VERB
cana-5239	289	26	framework	framework	NOUN
cana-5239	289	27	.	.	PUNCT
cana-5239	290	1	neural	neural	ADJ
cana-5239	290	2	comput	comput	PROPN
cana-5239	290	3	&	&	CCONJ
cana-5239	290	4	applic	applic	PROPN
cana-5239	290	5	35	35	NUM
cana-5239	290	6	,	,	PUNCT
cana-5239	290	7	15109–15128	15109–15128	NUM
cana-5239	290	8	(	(	PUNCT
cana-5239	290	9	2023	2023	NUM
cana-5239	290	10	)	)	PUNCT
cana-5239	290	11	.	.	PUNCT
cana-5239	291	1	[	[	X
cana-5239	291	2	23	23	NUM
cana-5239	291	3	]	]	X
cana-5239	291	4	avinash	avinash	NOUN
cana-5239	291	5	,	,	PUNCT
cana-5239	291	6	g.	g.	PROPN
cana-5239	291	7	,	,	PUNCT
cana-5239	291	8	ramasubramanian	ramasubramanian	PROPN
cana-5239	291	9	,	,	PUNCT
cana-5239	291	10	v.	v.	PROPN
cana-5239	291	11	,	,	PUNCT
cana-5239	291	12	ray	ray	NOUN
cana-5239	291	13	,	,	PUNCT
cana-5239	291	14	m.	m.	NOUN
cana-5239	291	15	,	,	PUNCT
cana-5239	291	16	paul	paul	PROPN
cana-5239	291	17	,	,	PUNCT
cana-5239	291	18	r.k	r.k	PROPN
cana-5239	291	19	.	.	PROPN
cana-5239	291	20	,	,	PUNCT
cana-5239	291	21	godara	godara	PROPN
cana-5239	291	22	,	,	PUNCT
cana-5239	291	23	s.	s.	PROPN
cana-5239	291	24	,	,	PUNCT
cana-5239	291	25	nayak	nayak	PROPN
cana-5239	291	26	,	,	PUNCT
cana-5239	291	27	g.h	g.h	PROPN
cana-5239	291	28	.	.	PROPN
cana-5239	291	29	,	,	PUNCT
cana-5239	291	30	kumar	kumar	PROPN
cana-5239	291	31	,	,	PUNCT
cana-5239	291	32	r.r	r.r	PROPN
cana-5239	291	33	.	.	PROPN
cana-5239	291	34	,	,	PUNCT
cana-5239	291	35	manjunatha	manjunatha	PROPN
cana-5239	291	36	,	,	PUNCT
cana-5239	291	37	b.	b.	PROPN
cana-5239	291	38	,	,	PUNCT
cana-5239	291	39	dahiya	dahiya	PROPN
cana-5239	291	40	,	,	PUNCT
cana-5239	291	41	s.	s.	PROPN
cana-5239	291	42	and	and	CCONJ
cana-5239	291	43	iquebal	iquebal	PROPN
cana-5239	291	44	,	,	PUNCT
cana-5239	291	45	m.a	m.a	PROPN
cana-5239	291	46	.	.	PROPN
cana-5239	291	47	,	,	PUNCT
cana-5239	291	48	2024	2024	NUM
cana-5239	291	49	.	.	PUNCT
cana-5239	292	1	hidden	hide	VERB
cana-5239	292	2	markov	markov	NOUN
cana-5239	292	3	guided	guide	VERB
cana-5239	292	4	deep	deep	ADJ
cana-5239	292	5	learning	learning	NOUN
cana-5239	292	6	models	model	NOUN
cana-5239	292	7	for	for	ADP
cana-5239	292	8	forecasting	forecast	VERB
cana-5239	292	9	highly	highly	ADV
cana-5239	292	10	volatile	volatile	ADJ
cana-5239	292	11	agricultural	agricultural	ADJ
cana-5239	292	12	commodity	commodity	NOUN
cana-5239	292	13	prices	price	NOUN
cana-5239	292	14	.	.	PUNCT
cana-5239	293	1	applied	apply	VERB
cana-5239	293	2	soft	soft	ADJ
cana-5239	293	3	computing	computing	NOUN
cana-5239	293	4	,	,	PUNCT
cana-5239	293	5	p.111557	p.111557	PROPN
cana-5239	293	6	.	.	PUNCT
cana-5239	294	1	communications	communication	NOUN
cana-5239	294	2	on	on	ADP
cana-5239	294	3	applied	apply	VERB
cana-5239	294	4	nonlinear	nonlinear	ADJ
cana-5239	294	5	analysis	analysis	NOUN
cana-5239	294	6	issn	issn	NOUN
cana-5239	294	7	:	:	PUNCT
cana-5239	294	8	1074	1074	NUM
cana-5239	294	9	-	-	PUNCT
cana-5239	294	10	133x	133x	NUM
cana-5239	294	11	vol	vol	VERB
cana-5239	294	12	32	32	NUM
cana-5239	294	13	no	no	NOUN
cana-5239	294	14	.	.	PUNCT
cana-5239	295	1	10s	10	NOUN
cana-5239	295	2	(	(	PUNCT
cana-5239	295	3	2025	2025	NUM
cana-5239	295	4	)	)	PUNCT
cana-5239	295	5	1387	1387	NUM
cana-5239	295	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5239	296	1	[	[	X
cana-5239	296	2	24	24	NUM
cana-5239	296	3	]	]	X
cana-5239	296	4	zhang	zhang	PROPN
cana-5239	296	5	,	,	PUNCT
cana-5239	296	6	t.	t.	PROPN
cana-5239	296	7	and	and	CCONJ
cana-5239	296	8	tang	tang	PROPN
cana-5239	296	9	,	,	PUNCT
cana-5239	296	10	z.	z.	PROPN
cana-5239	296	11	,	,	PUNCT
cana-5239	296	12	2024	2024	NUM
cana-5239	296	13	.	.	PUNCT
cana-5239	297	1	agricultural	agricultural	ADJ
cana-5239	297	2	commodity	commodity	NOUN
cana-5239	297	3	futures	future	NOUN
cana-5239	297	4	prices	price	NOUN
cana-5239	297	5	prediction	prediction	NOUN
cana-5239	297	6	based	base	VERB
cana-5239	297	7	on	on	ADP
cana-5239	297	8	a	a	DET
cana-5239	297	9	new	new	ADJ
cana-5239	297	10	hybrid	hybrid	ADJ
cana-5239	297	11	forecasting	forecasting	NOUN
cana-5239	297	12	model	model	NOUN
cana-5239	297	13	combining	combine	VERB
cana-5239	297	14	quadratic	quadratic	ADJ
cana-5239	297	15	decomposition	decomposition	NOUN
cana-5239	297	16	technology	technology	NOUN
cana-5239	297	17	and	and	CCONJ
cana-5239	297	18	lstm	lstm	PROPN
cana-5239	297	19	model	model	NOUN
cana-5239	297	20	.	.	PUNCT
cana-5239	298	1	frontiers	frontier	NOUN
cana-5239	298	2	in	in	ADP
cana-5239	298	3	sustainable	sustainable	ADJ
cana-5239	298	4	food	food	NOUN
cana-5239	298	5	systems	system	NOUN
cana-5239	298	6	,	,	PUNCT
cana-5239	298	7	8	8	NUM
cana-5239	298	8	,	,	PUNCT
cana-5239	298	9	p.1334098	p.1334098	NOUN
cana-5239	298	10	.	.	PUNCT
cana-5239	299	1	[	[	X
cana-5239	299	2	25	25	NUM
cana-5239	299	3	]	]	X
cana-5239	299	4	rana	rana	PROPN
cana-5239	299	5	,	,	PUNCT
cana-5239	299	6	h.	h.	PROPN
cana-5239	299	7	,	,	PUNCT
cana-5239	299	8	farooq	farooq	PROPN
cana-5239	299	9	,	,	PUNCT
cana-5239	299	10	m.u	m.u	PROPN
cana-5239	299	11	.	.	PROPN
cana-5239	299	12	,	,	PUNCT
cana-5239	299	13	kazi	kazi	PROPN
cana-5239	299	14	,	,	PUNCT
cana-5239	299	15	a.k	a.k	PROPN
cana-5239	299	16	.	.	PROPN
cana-5239	299	17	,	,	PUNCT
cana-5239	299	18	baig	baig	PROPN
cana-5239	299	19	,	,	PUNCT
cana-5239	299	20	m.a	m.a	PROPN
cana-5239	299	21	.	.	PROPN
cana-5239	299	22	and	and	CCONJ
cana-5239	299	23	akhtar	akhtar	PROPN
cana-5239	299	24	,	,	PUNCT
cana-5239	299	25	m.a	m.a	PROPN
cana-5239	299	26	.	.	PROPN
cana-5239	299	27	,	,	PUNCT
cana-5239	299	28	2024	2024	NUM
cana-5239	299	29	.	.	PUNCT
cana-5239	299	30	prediction	prediction	NOUN
cana-5239	299	31	of	of	ADP
cana-5239	299	32	agricultural	agricultural	ADJ
cana-5239	299	33	commodity	commodity	NOUN
cana-5239	299	34	prices	price	NOUN
cana-5239	299	35	using	use	VERB
cana-5239	299	36	big	big	ADJ
cana-5239	299	37	data	datum	NOUN
cana-5239	299	38	framework	framework	NOUN
cana-5239	299	39	.	.	PUNCT
cana-5239	300	1	engineering	engineering	NOUN
cana-5239	300	2	,	,	PUNCT
cana-5239	300	3	technology	technology	NOUN
cana-5239	300	4	&	&	CCONJ
cana-5239	300	5	applied	apply	VERB
cana-5239	300	6	science	science	NOUN
cana-5239	300	7	research	research	NOUN
cana-5239	300	8	,	,	PUNCT
cana-5239	300	9	14(1	14(1	NUM
cana-5239	300	10	)	)	PUNCT
cana-5239	300	11	,	,	PUNCT
cana-5239	300	12	pp.12652	pp.12652	PROPN
cana-5239	300	13	-	-	PUNCT
cana-5239	300	14	12658	12658	NUM
cana-5239	300	15	.	.	PUNCT
cana-5239	301	1	[	[	X
cana-5239	301	2	26	26	NUM
cana-5239	301	3	]	]	X
cana-5239	301	4	sun	sun	PROPN
cana-5239	301	5	,	,	PUNCT
cana-5239	301	6	f.	f.	PROPN
cana-5239	301	7	,	,	PUNCT
cana-5239	301	8	meng	meng	PROPN
cana-5239	301	9	,	,	PUNCT
cana-5239	301	10	x.	x.	PROPN
cana-5239	301	11	,	,	PUNCT
cana-5239	301	12	zhang	zhang	PROPN
cana-5239	301	13	,	,	PUNCT
cana-5239	301	14	h.	h.	PROPN
cana-5239	301	15	,	,	PUNCT
cana-5239	301	16	wang	wang	PROPN
cana-5239	301	17	,	,	PUNCT
cana-5239	301	18	y.	y.	PROPN
cana-5239	301	19	and	and	CCONJ
cana-5239	301	20	liu	liu	PROPN
cana-5239	301	21	,	,	PUNCT
cana-5239	301	22	p.	p.	PROPN
cana-5239	301	23	,	,	PUNCT
cana-5239	301	24	2024	2024	NUM
cana-5239	301	25	.	.	PUNCT
cana-5239	301	26	prediction	prediction	NOUN
cana-5239	301	27	of	of	ADP
cana-5239	301	28	weekly	weekly	ADJ
cana-5239	301	29	price	price	NOUN
cana-5239	301	30	trend	trend	NOUN
cana-5239	301	31	of	of	ADP
cana-5239	301	32	garlic	garlic	NOUN
cana-5239	301	33	based	base	VERB
cana-5239	301	34	on	on	ADP
cana-5239	301	35	classification	classification	NOUN
cana-5239	301	36	algorithm	algorithm	NOUN
cana-5239	301	37	and	and	CCONJ
cana-5239	301	38	combined	combined	ADJ
cana-5239	301	39	features	feature	NOUN
cana-5239	301	40	.	.	PUNCT
cana-5239	302	1	horticulturae	horticulturae	PROPN
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cana-5239	302	3	10(4	10(4	NUM
cana-5239	302	4	)	)	PUNCT
cana-5239	302	5	,	,	PUNCT
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cana-5239	303	1	[	[	X
cana-5239	303	2	27	27	NUM
cana-5239	303	3	]	]	X
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cana-5239	303	10	b.	b.	PROPN
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cana-5239	303	12	2024	2024	NUM
cana-5239	303	13	.	.	PUNCT
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cana-5239	304	3	missing	miss	VERB
cana-5239	304	4	data	datum	NOUN
cana-5239	304	5	and	and	CCONJ
cana-5239	304	6	comparing	compare	VERB
cana-5239	304	7	the	the	DET
cana-5239	304	8	accuracy	accuracy	NOUN
cana-5239	304	9	of	of	ADP
cana-5239	304	10	imputation	imputation	NOUN
cana-5239	304	11	methods	method	NOUN
cana-5239	304	12	using	use	VERB
cana-5239	304	13	wheat	wheat	NOUN
cana-5239	304	14	crop	crop	NOUN
cana-5239	304	15	data	datum	NOUN
cana-5239	304	16	.	.	PUNCT
cana-5239	305	1	multimedia	multimedia	NOUN
cana-5239	305	2	tools	tool	NOUN
cana-5239	305	3	and	and	CCONJ
cana-5239	305	4	applications	application	NOUN
cana-5239	305	5	,	,	PUNCT
cana-5239	305	6	83(14	83(14	NUM
cana-5239	305	7	)	)	PUNCT
cana-5239	305	8	,	,	PUNCT
cana-5239	305	9	pp.40393	pp.40393	PROPN
cana-5239	305	10	-	-	PUNCT
cana-5239	305	11	40414	40414	NUM
cana-5239	305	12	.	.	PUNCT
cana-5239	306	1	[	[	X
cana-5239	306	2	28	28	NUM
cana-5239	306	3	]	]	X
cana-5239	306	4	bukhari	bukhari	PROPN
cana-5239	306	5	,	,	PUNCT
cana-5239	306	6	s.b	s.b	PROPN
cana-5239	306	7	.	.	PROPN
cana-5239	306	8	,	,	PUNCT
cana-5239	306	9	2024	2024	NUM
cana-5239	306	10	.	.	PUNCT
cana-5239	306	11	crop	crop	NOUN
cana-5239	306	12	recommendation	recommendation	NOUN
cana-5239	306	13	system	system	NOUN
cana-5239	306	14	using	use	VERB
cana-5239	306	15	machine	machine	NOUN
cana-5239	306	16	learning	learning	NOUN
cana-5239	306	17	.	.	PUNCT
cana-5239	307	1	a	a	DET
cana-5239	307	2	data	data	NOUN
cana-5239	307	3	-	-	PUNCT
cana-5239	307	4	driven	drive	VERB
cana-5239	307	5	approach	approach	NOUN
cana-5239	307	6	to	to	ADP
cana-5239	307	7	sustainable	sustainable	ADJ
cana-5239	307	8	agriculture	agriculture	NOUN
cana-5239	307	9	.	.	PUNCT
cana-5239	308	1	journal	journal	PROPN
cana-5239	308	2	of	of	ADP
cana-5239	308	3	techno	techno	NOUN
cana-5239	308	4	trainers	trainer	NOUN
cana-5239	308	5	,	,	PUNCT
cana-5239	308	6	1(2	1(2	NUM
cana-5239	308	7	)	)	PUNCT
cana-5239	308	8	,	,	PUNCT
cana-5239	308	9	pp.26	pp.26	PROPN
cana-5239	308	10	-	-	PUNCT
cana-5239	308	11	35	35	NUM
cana-5239	308	12	.	.	PUNCT
cana-5239	309	1	[	[	X
cana-5239	309	2	29	29	NUM
cana-5239	309	3	]	]	X
cana-5239	309	4	sachdeva	sachdeva	PROPN
cana-5239	309	5	,	,	PUNCT
cana-5239	309	6	r.k	r.k	PROPN
cana-5239	309	7	.	.	PROPN
cana-5239	309	8	,	,	PUNCT
cana-5239	309	9	bathla	bathla	NOUN
cana-5239	309	10	,	,	PUNCT
cana-5239	309	11	p.	p.	NOUN
cana-5239	309	12	,	,	PUNCT
cana-5239	309	13	rani	rani	NOUN
cana-5239	309	14	,	,	PUNCT
cana-5239	309	15	p.	p.	NOUN
cana-5239	309	16	,	,	PUNCT
cana-5239	309	17	kukreja	kukreja	PROPN
cana-5239	309	18	,	,	PUNCT
cana-5239	309	19	v.	v.	PROPN
cana-5239	309	20	and	and	CCONJ
cana-5239	309	21	ahuja	ahuja	PROPN
cana-5239	309	22	,	,	PUNCT
cana-5239	309	23	r.	r.	PROPN
cana-5239	309	24	,	,	PUNCT
cana-5239	309	25	2022	2022	NUM
cana-5239	309	26	,	,	PUNCT
cana-5239	309	27	april	april	PROPN
cana-5239	309	28	.	.	PUNCT
cana-5239	310	1	a	a	DET
cana-5239	310	2	systematic	systematic	ADJ
cana-5239	310	3	method	method	NOUN
cana-5239	310	4	for	for	ADP
cana-5239	310	5	breast	breast	NOUN
cana-5239	310	6	cancer	cancer	NOUN
cana-5239	310	7	classification	classification	NOUN
cana-5239	310	8	using	use	VERB
cana-5239	310	9	rfe	rfe	PROPN
cana-5239	310	10	feature	feature	NOUN
cana-5239	310	11	selection	selection	NOUN
cana-5239	310	12	.	.	PUNCT
cana-5239	311	1	in	in	ADP
cana-5239	311	2	2022	2022	NUM
cana-5239	311	3	2nd	2nd	ADJ
cana-5239	311	4	international	international	ADJ
cana-5239	311	5	conference	conference	NOUN
cana-5239	311	6	on	on	ADP
cana-5239	311	7	advance	advance	NOUN
cana-5239	311	8	computing	computing	NOUN
cana-5239	311	9	and	and	CCONJ
cana-5239	311	10	innovative	innovative	ADJ
cana-5239	311	11	technologies	technology	NOUN
cana-5239	311	12	in	in	ADP
cana-5239	311	13	engineering	engineering	NOUN
cana-5239	311	14	(	(	PUNCT
cana-5239	311	15	icacite	icacite	PROPN
cana-5239	311	16	)	)	PUNCT
cana-5239	311	17	(	(	PUNCT
cana-5239	311	18	pp	pp	ADJ
cana-5239	311	19	.	.	PUNCT
cana-5239	312	1	1673	1673	NUM
cana-5239	312	2	-	-	SYM
cana-5239	312	3	1676	1676	NUM
cana-5239	312	4	)	)	PUNCT
cana-5239	312	5	.	.	PUNCT
cana-5239	313	1	ieee	ieee	PROPN
cana-5239	313	2	.	.	PUNCT
cana-5239	314	1	[	[	X
cana-5239	314	2	30	30	NUM
cana-5239	314	3	]	]	PUNCT
cana-5239	314	4	altarabichi	altarabichi	NOUN
cana-5239	314	5	,	,	PUNCT
cana-5239	314	6	m.g	m.g	PROPN
cana-5239	314	7	.	.	PROPN
cana-5239	314	8	,	,	PUNCT
cana-5239	314	9	nowaczyk	nowaczyk	PROPN
cana-5239	314	10	,	,	PUNCT
cana-5239	314	11	s.	s.	PROPN
cana-5239	314	12	,	,	PUNCT
cana-5239	314	13	pashami	pashami	NOUN
cana-5239	314	14	,	,	PUNCT
cana-5239	314	15	s.	s.	PROPN
cana-5239	314	16	and	and	CCONJ
cana-5239	314	17	sheikholharam	sheikholharam	NOUN
cana-5239	314	18	mashhadi	mashhadi	NOUN
cana-5239	314	19	,	,	PUNCT
cana-5239	314	20	p.	p.	NOUN
cana-5239	314	21	,	,	PUNCT
cana-5239	314	22	2023	2023	NUM
cana-5239	314	23	,	,	PUNCT
cana-5239	314	24	july	july	PROPN
cana-5239	314	25	.	.	PUNCT
cana-5239	315	1	fast	fast	ADJ
cana-5239	315	2	genetic	genetic	ADJ
cana-5239	315	3	algorithm	algorithm	NOUN
cana-5239	315	4	for	for	ADP
cana-5239	315	5	feature	feature	NOUN
cana-5239	315	6	selection	selection	NOUN
cana-5239	315	7	—	—	PUNCT
cana-5239	315	8	a	a	DET
cana-5239	315	9	qualitative	qualitative	ADJ
cana-5239	315	10	approximation	approximation	NOUN
cana-5239	315	11	approach	approach	NOUN
cana-5239	315	12	.	.	PUNCT
cana-5239	316	1	in	in	ADP
cana-5239	316	2	proceedings	proceeding	NOUN
cana-5239	316	3	of	of	ADP
cana-5239	316	4	the	the	DET
cana-5239	316	5	companion	companion	NOUN
cana-5239	316	6	conference	conference	NOUN
cana-5239	316	7	on	on	ADP
cana-5239	316	8	genetic	genetic	ADJ
cana-5239	316	9	and	and	CCONJ
cana-5239	316	10	evolutionary	evolutionary	ADJ
cana-5239	316	11	computation	computation	NOUN
cana-5239	316	12	(	(	PUNCT
cana-5239	316	13	pp	pp	ADJ
cana-5239	316	14	.	.	PUNCT
cana-5239	317	1	11	11	NUM
cana-5239	317	2	-	-	SYM
cana-5239	317	3	12	12	NUM
cana-5239	317	4	)	)	PUNCT
cana-5239	317	5	.	.	PUNCT
cana-5239	318	1	[	[	X
cana-5239	318	2	31	31	NUM
cana-5239	318	3	]	]	PUNCT
cana-5239	318	4	mirjalili	mirjalili	NOUN
cana-5239	318	5	,	,	PUNCT
cana-5239	318	6	s.	s.	PROPN
cana-5239	318	7	,	,	PUNCT
cana-5239	318	8	mirjalili	mirjalili	NOUN
cana-5239	318	9	,	,	PUNCT
cana-5239	318	10	s.m	s.m	PROPN
cana-5239	318	11	.	.	PROPN
cana-5239	318	12	and	and	CCONJ
cana-5239	318	13	lewis	lewis	PROPN
cana-5239	318	14	,	,	PUNCT
cana-5239	318	15	a.	a.	NOUN
cana-5239	318	16	,	,	PUNCT
cana-5239	318	17	2014	2014	NUM
cana-5239	318	18	.	.	PUNCT
cana-5239	319	1	grey	grey	PROPN
cana-5239	319	2	wolf	wolf	PROPN
cana-5239	319	3	optimizer	optimizer	NOUN
cana-5239	319	4	.	.	PUNCT
cana-5239	320	1	advances	advance	NOUN
cana-5239	320	2	in	in	ADP
cana-5239	320	3	engineering	engineering	NOUN
cana-5239	320	4	software	software	NOUN
cana-5239	320	5	,	,	PUNCT
cana-5239	320	6	69	69	NUM
cana-5239	320	7	,	,	PUNCT
cana-5239	320	8	pp.46	pp.46	NOUN
cana-5239	320	9	-	-	PUNCT
cana-5239	320	10	61	61	NUM
cana-5239	320	11	.	.	PUNCT
cana-5239	321	1	[	[	X
cana-5239	321	2	32	32	NUM
cana-5239	321	3	]	]	PUNCT
cana-5239	321	4	v.	v.	ADP
cana-5239	321	5	bobkov	bobkov	PROPN
cana-5239	321	6	,	,	PUNCT
cana-5239	321	7	a.	a.	PROPN
cana-5239	321	8	bobkova	bobkova	PROPN
cana-5239	321	9	,	,	PUNCT
cana-5239	321	10	s.	s.	PROPN
cana-5239	321	11	porshnev	porshnev	PROPN
cana-5239	321	12	and	and	CCONJ
cana-5239	321	13	v.	v.	ADP
cana-5239	321	14	zuzin	zuzin	NOUN
cana-5239	321	15	,	,	PUNCT
cana-5239	321	16	"	"	PUNCT
cana-5239	321	17	the	the	DET
cana-5239	321	18	application	application	NOUN
cana-5239	321	19	of	of	ADP
cana-5239	321	20	ensemble	ensemble	ADJ
cana-5239	321	21	learning	learning	NOUN
cana-5239	321	22	for	for	ADP
cana-5239	321	23	delineation	delineation	NOUN
cana-5239	321	24	of	of	ADP
cana-5239	321	25	the	the	DET
cana-5239	321	26	left	left	ADJ
cana-5239	321	27	ventricle	ventricle	NOUN
cana-5239	321	28	on	on	ADP
cana-5239	321	29	echocardiographic	echocardiographic	ADJ
cana-5239	321	30	records	record	NOUN
cana-5239	321	31	,	,	PUNCT
cana-5239	321	32	"	"	PUNCT
cana-5239	321	33	2016	2016	NUM
cana-5239	321	34	dynamics	dynamic	NOUN
cana-5239	321	35	of	of	ADP
cana-5239	321	36	systems	system	NOUN
cana-5239	321	37	,	,	PUNCT
cana-5239	321	38	mechanisms	mechanism	NOUN
cana-5239	321	39	and	and	CCONJ
cana-5239	321	40	machines	machine	NOUN
cana-5239	321	41	(	(	PUNCT
cana-5239	321	42	dynamics	dynamic	NOUN
cana-5239	321	43	)	)	PUNCT
cana-5239	321	44	,	,	PUNCT
cana-5239	321	45	omsk	omsk	PROPN
cana-5239	321	46	,	,	PUNCT
cana-5239	321	47	2016	2016	NUM
cana-5239	321	48	,	,	PUNCT
cana-5239	321	49	pp	pp	ADJ
cana-5239	321	50	.	.	PUNCT
cana-5239	322	1	1	1	NUM
cana-5239	322	2	-	-	SYM
cana-5239	322	3	5	5	NUM
cana-5239	322	4	.	.	PUNCT
cana-5239	323	1	[	[	X
cana-5239	323	2	33	33	NUM
cana-5239	323	3	]	]	PUNCT
cana-5239	323	4	x.	x.	NOUN
cana-5239	323	5	shu	shu	PROPN
cana-5239	323	6	and	and	CCONJ
cana-5239	323	7	p.	p.	PROPN
cana-5239	323	8	wang	wang	PROPN
cana-5239	323	9	,	,	PUNCT
cana-5239	323	10	"	"	PUNCT
cana-5239	323	11	an	an	DET
cana-5239	323	12	improved	improved	ADJ
cana-5239	323	13	adaboost	adaboost	ADJ
cana-5239	323	14	algorithm	algorithm	NOUN
cana-5239	323	15	based	base	VERB
cana-5239	323	16	on	on	ADP
cana-5239	323	17	uncertain	uncertain	ADJ
cana-5239	323	18	functions	function	NOUN
cana-5239	323	19	,	,	PUNCT
cana-5239	323	20	"	"	PUNCT
cana-5239	323	21	2015	2015	NUM
cana-5239	323	22	international	international	ADJ
cana-5239	323	23	conference	conference	NOUN
cana-5239	323	24	on	on	ADP
cana-5239	323	25	industrial	industrial	ADJ
cana-5239	323	26	informatics	informatic	NOUN
cana-5239	323	27	computing	computing	PROPN
cana-5239	323	28	technology	technology	NOUN
cana-5239	323	29	,	,	PUNCT
cana-5239	323	30	intelligent	intelligent	ADJ
cana-5239	323	31	technology	technology	NOUN
cana-5239	323	32	,	,	PUNCT
cana-5239	323	33	industrial	industrial	ADJ
cana-5239	323	34	information	information	NOUN
cana-5239	323	35	integration	integration	NOUN
cana-5239	323	36	,	,	PUNCT
cana-5239	323	37	wuhan	wuhan	PROPN
cana-5239	323	38	,	,	PUNCT
cana-5239	323	39	2015	2015	NUM
cana-5239	323	40	,	,	PUNCT
cana-5239	323	41	pp	pp	ADJ
cana-5239	323	42	.	.	PUNCT
cana-5239	324	1	136	136	NUM
cana-5239	324	2	-	-	SYM
cana-5239	324	3	139	139	NUM
cana-5239	324	4	[	[	X
cana-5239	324	5	34	34	NUM
cana-5239	324	6	]	]	SYM
cana-5239	324	7	prokhorenkova	prokhorenkova	PROPN
cana-5239	324	8	,	,	PUNCT
cana-5239	324	9	l.	l.	PROPN
cana-5239	324	10	;	;	PUNCT
cana-5239	324	11	gusev	gusev	NOUN
cana-5239	324	12	,	,	PUNCT
cana-5239	324	13	g.	g.	PROPN
cana-5239	324	14	;	;	PUNCT
cana-5239	324	15	vorobev	vorobev	ADJ
cana-5239	324	16	,	,	PUNCT
cana-5239	324	17	a.	a.	NOUN
cana-5239	324	18	;	;	PUNCT
cana-5239	324	19	dorogush	dorogush	ADJ
cana-5239	324	20	,	,	PUNCT
cana-5239	324	21	a.v	a.v	PROPN
cana-5239	324	22	.	.	PROPN
cana-5239	324	23	;	;	PUNCT
cana-5239	325	1	gulin	gulin	PROPN
cana-5239	325	2	,	,	PUNCT
cana-5239	325	3	a.	a.	NOUN
cana-5239	325	4	catboost	catboost	PROPN
cana-5239	325	5	:	:	PUNCT
cana-5239	325	6	unbiased	unbiased	ADJ
cana-5239	325	7	boosting	boost	VERB
cana-5239	325	8	with	with	ADP
cana-5239	325	9	categorical	categorical	ADJ
cana-5239	325	10	features	feature	NOUN
cana-5239	325	11	.	.	PUNCT
cana-5239	326	1	adv	adv	PROPN
cana-5239	326	2	.	.	PUNCT
cana-5239	326	3	neural	neural	PROPN
cana-5239	326	4	inf	inf	PROPN
cana-5239	326	5	.	.	PUNCT
cana-5239	326	6	process	process	NOUN
cana-5239	326	7	.	.	PUNCT
cana-5239	327	1	syst	syst	PROPN
cana-5239	327	2	.	.	PUNCT
cana-5239	328	1	2018	2018	NUM
cana-5239	328	2	,	,	PUNCT
cana-5239	328	3	31	31	NUM
cana-5239	328	4	,	,	PUNCT
cana-5239	328	5	6638–6648	6638–6648	NOUN
cana-5239	328	6	.	.	PUNCT
cana-5239	329	1	[	[	X
cana-5239	329	2	35	35	NUM
cana-5239	329	3	]	]	X
cana-5239	329	4	liu	liu	PROPN
cana-5239	329	5	,	,	PUNCT
cana-5239	329	6	h.	h.	PROPN
cana-5239	329	7	;	;	PUNCT
cana-5239	329	8	guo	guo	PROPN
cana-5239	329	9	,	,	PUNCT
cana-5239	329	10	l.	l.	PROPN
cana-5239	329	11	;	;	PUNCT
cana-5239	329	12	li	li	PROPN
cana-5239	329	13	,	,	PUNCT
cana-5239	329	14	h.	h.	PROPN
cana-5239	329	15	;	;	PUNCT
cana-5239	329	16	zhang	zhang	PROPN
cana-5239	329	17	,	,	PUNCT
cana-5239	329	18	w.	w.	PROPN
cana-5239	329	19	;	;	PUNCT
cana-5239	329	20	bai	bai	PROPN
cana-5239	329	21	,	,	PUNCT
cana-5239	329	22	x.	x.	NOUN
cana-5239	329	23	matching	match	VERB
cana-5239	329	24	areal	areal	NOUN
cana-5239	329	25	entities	entity	NOUN
cana-5239	329	26	with	with	ADP
cana-5239	329	27	catboost	catboost	ADJ
cana-5239	329	28	ensemble	ensemble	ADJ
cana-5239	329	29	method	method	NOUN
cana-5239	329	30	.	.	PUNCT
cana-5239	330	1	geogr	geogr	NOUN
cana-5239	330	2	.	.	PUNCT
cana-5239	331	1	inf	inf	PROPN
cana-5239	331	2	.	.	PUNCT
cana-5239	332	1	sci	sci	PROPN
cana-5239	332	2	.	.	PROPN
cana-5239	332	3	2022	2022	NUM
cana-5239	332	4	,	,	PUNCT
cana-5239	332	5	24	24	NUM
cana-5239	332	6	,	,	PUNCT
cana-5239	332	7	2198–2211	2198–2211	NUM
cana-5239	332	8	.	.	PUNCT