id	sid	tid	token	lemma	pos
cana-2055	1	1	communications	communication	NOUN
cana-2055	1	2	on	on	ADP
cana-2055	1	3	applied	apply	VERB
cana-2055	1	4	nonlinear	nonlinear	ADJ
cana-2055	1	5	analysis	analysis	NOUN
cana-2055	1	6	issn	issn	NOUN
cana-2055	1	7	:	:	PUNCT
cana-2055	1	8	1074	1074	NUM
cana-2055	1	9	-	-	PUNCT
cana-2055	1	10	133x	133x	NUM
cana-2055	1	11	vol	vol	NOUN
cana-2055	1	12	32	32	NUM
cana-2055	1	13	no	no	NOUN
cana-2055	1	14	.	.	NOUN
cana-2055	1	15	3	3	NUM
cana-2055	1	16	(	(	PUNCT
cana-2055	1	17	2025	2025	NUM
cana-2055	1	18	)	)	PUNCT
cana-2055	1	19	577	577	NUM
cana-2055	1	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-2055	1	21	optimization	optimization	NOUN
cana-2055	1	22	of	of	ADP
cana-2055	1	23	crop	crop	NOUN
cana-2055	1	24	yield	yield	NOUN
cana-2055	1	25	prediction	prediction	NOUN
cana-2055	1	26	through	through	ADP
cana-2055	1	27	linear	linear	NOUN
cana-2055	1	28	modelling	modelling	NOUN
cana-2055	1	29	and	and	CCONJ
cana-2055	1	30	deep	deep	ADJ
cana-2055	1	31	learning	learning	NOUN
cana-2055	1	32	techniques	technique	NOUN
cana-2055	1	33	used	use	VERB
cana-2055	1	34	in	in	ADP
cana-2055	1	35	precision	precision	NOUN
cana-2055	1	36	agriculture	agriculture	NOUN
cana-2055	1	37	ramakrishna	ramakrishna	PROPN
cana-2055	1	38	kolikipogu1	kolikipogu1	PROPN
cana-2055	1	39	,	,	PUNCT
cana-2055	1	40	dr	dr	PROPN
cana-2055	1	41	.	.	PROPN
cana-2055	1	42	m.	m.	PROPN
cana-2055	1	43	bheemalingaiah2	bheemalingaiah2	PROPN
cana-2055	1	44	,	,	PUNCT
cana-2055	1	45	kale	kale	PROPN
cana-2055	1	46	naga	naga	PROPN
cana-2055	1	47	venkata	venkata	PROPN
cana-2055	1	48	srinivas3	srinivas3	PROPN
cana-2055	1	49	,	,	PUNCT
cana-2055	1	50	loya	loya	PROPN
cana-2055	1	51	chandrajit	chandrajit	PROPN
cana-2055	1	52	yadav4	yadav4	PROPN
cana-2055	1	53	,	,	PUNCT
cana-2055	1	54	dr.s.suma	dr.s.suma	PROPN
cana-2055	1	55	christal	christal	PROPN
cana-2055	1	56	mary	mary	PROPN
cana-2055	1	57	sundararajan5	sundararajan5	PROPN
cana-2055	1	58	,	,	PUNCT
cana-2055	1	59	dr	dr	PROPN
cana-2055	1	60	vishwa	vishwa	PROPN
cana-2055	1	61	priya	priya	PROPN
cana-2055	1	62	v	v	ADP
cana-2055	1	63	6	6	NUM
cana-2055	1	64	1	1	NUM
cana-2055	1	65	department	department	NOUN
cana-2055	1	66	of	of	ADP
cana-2055	1	67	information	information	NOUN
cana-2055	1	68	technology	technology	PROPN
cana-2055	1	69	,	,	PUNCT
cana-2055	1	70	chaitanya	chaitanya	PROPN
cana-2055	1	71	bharathi	bharathi	PROPN
cana-2055	1	72	institute	institute	PROPN
cana-2055	1	73	of	of	ADP
cana-2055	1	74	technology	technology	PROPN
cana-2055	1	75	(	(	PUNCT
cana-2055	1	76	a	a	NOUN
cana-2055	1	77	)	)	PUNCT
cana-2055	1	78	,	,	PUNCT
cana-2055	1	79	hyderabad	hyderabad	PROPN
cana-2055	1	80	,	,	PUNCT
cana-2055	1	81	india	india	PROPN
cana-2055	1	82	.	.	PUNCT
cana-2055	2	1	krkrishna.cse@gmail.com	krkrishna.cse@gmail.com	PROPN
cana-2055	2	2	2	2	NUM
cana-2055	2	3	department	department	PROPN
cana-2055	2	4	of	of	ADP
cana-2055	2	5	cse	cse	PROPN
cana-2055	2	6	,	,	PUNCT
cana-2055	2	7	j.b	j.b	PROPN
cana-2055	2	8	.	.	PROPN
cana-2055	2	9	institute	institute	PROPN
cana-2055	2	10	of	of	ADP
cana-2055	2	11	engineering	engineering	NOUN
cana-2055	2	12	and	and	CCONJ
cana-2055	2	13	technology	technology	NOUN
cana-2055	2	14	.	.	PUNCT
cana-2055	3	1	,	,	PUNCT
cana-2055	3	2	hyderabad	hyderabad	PROPN
cana-2055	3	3	,	,	PUNCT
cana-2055	3	4	india	india	PROPN
cana-2055	3	5	.	.	PUNCT
cana-2055	4	1	bheemasiva2019@gmail.com	bheemasiva2019@gmail.com	PROPN
cana-2055	5	1	https://orcid.org/0000-0002-2850-3553	https://orcid.org/0000-0002-2850-3553	PROPN
cana-2055	5	2	3	3	NUM
cana-2055	5	3	department	department	PROPN
cana-2055	5	4	of	of	ADP
cana-2055	5	5	cse	cse	PROPN
cana-2055	5	6	,	,	PUNCT
cana-2055	5	7	aditya	aditya	PROPN
cana-2055	5	8	university	university	PROPN
cana-2055	5	9	,	,	PUNCT
cana-2055	5	10	surampalem	surampalem	NOUN
cana-2055	5	11	,	,	PUNCT
cana-2055	5	12	india	india	PROPN
cana-2055	5	13	.	.	PUNCT
cana-2055	6	1	nvskale@gmail.com	nvskale@gmail.com	X
cana-2055	7	1	4department	4department	NUM
cana-2055	7	2	of	of	ADP
cana-2055	7	3	cse	cse	PROPN
cana-2055	7	4	,	,	PUNCT
cana-2055	7	5	koneru	koneru	PROPN
cana-2055	7	6	lakshmaiah	lakshmaiah	PROPN
cana-2055	7	7	education	education	PROPN
cana-2055	7	8	foundation	foundation	PROPN
cana-2055	7	9	,	,	PUNCT
cana-2055	7	10	vaddeswaram	vaddeswaram	PROPN
cana-2055	7	11	,	,	PUNCT
cana-2055	7	12	vijayawada	vijayawada	PROPN
cana-2055	7	13	,	,	PUNCT
cana-2055	7	14	india	india	PROPN
cana-2055	7	15	.	.	PUNCT
cana-2055	7	16	yadavloya@kluniversity.in	yadavloya@kluniversity.in	PROPN
cana-2055	7	17	5	5	NUM
cana-2055	7	18	department	department	NOUN
cana-2055	7	19	of	of	ADP
cana-2055	7	20	information	information	NOUN
cana-2055	7	21	technology	technology	NOUN
cana-2055	7	22	,	,	PUNCT
cana-2055	7	23	panimalar	panimalar	ADJ
cana-2055	7	24	engineering	engineering	NOUN
cana-2055	7	25	college	college	NOUN
cana-2055	7	26	,	,	PUNCT
cana-2055	7	27	chennai	chennai	PROPN
cana-2055	7	28	,	,	PUNCT
cana-2055	7	29	india	india	PROPN
cana-2055	7	30	.	.	PUNCT
cana-2055	8	1	sumasheyalin@gmail.com	sumasheyalin@gmail.com	PROPN
cana-2055	9	1	6	6	NUM
cana-2055	9	2	department	department	NOUN
cana-2055	9	3	of	of	ADP
cana-2055	9	4	computer	computer	NOUN
cana-2055	9	5	science	science	NOUN
cana-2055	9	6	,	,	PUNCT
cana-2055	9	7	vels	vels	PROPN
cana-2055	9	8	institute	institute	PROPN
cana-2055	9	9	of	of	ADP
cana-2055	9	10	science	science	NOUN
cana-2055	9	11	,	,	PUNCT
cana-2055	9	12	technology	technology	NOUN
cana-2055	9	13	and	and	CCONJ
cana-2055	9	14	advanced	advanced	ADJ
cana-2055	9	15	studies	study	NOUN
cana-2055	9	16	.	.	PUNCT
cana-2055	10	1	chennai	chennai	PROPN
cana-2055	10	2	,	,	PUNCT
cana-2055	10	3	india	india	PROPN
cana-2055	10	4	.	.	PUNCT
cana-2055	11	1	vishwapriya13@gmail.com	vishwapriya13@gmail.com	X
cana-2055	11	2	article	article	NOUN
cana-2055	11	3	history	history	NOUN
cana-2055	11	4	:	:	PUNCT
cana-2055	11	5	received	receive	VERB
cana-2055	11	6	:	:	PUNCT
cana-2055	11	7	03	03	NUM
cana-2055	11	8	-	-	SYM
cana-2055	11	9	08	08	NUM
cana-2055	11	10	-	-	PUNCT
cana-2055	11	11	2024	2024	NUM
cana-2055	11	12	revised	revise	VERB
cana-2055	11	13	:	:	PUNCT
cana-2055	11	14	25	25	NUM
cana-2055	11	15	-	-	PUNCT
cana-2055	11	16	09	09	NUM
cana-2055	11	17	-	-	PUNCT
cana-2055	11	18	2024	2024	NUM
cana-2055	11	19	accepted	accept	VERB
cana-2055	11	20	:	:	PUNCT
cana-2055	11	21	07	07	NUM
cana-2055	11	22	-	-	SYM
cana-2055	11	23	10	10	NUM
cana-2055	11	24	-	-	PUNCT
cana-2055	11	25	2024	2024	NUM
cana-2055	11	26	abstract	abstract	NOUN
cana-2055	11	27	:	:	PUNCT
cana-2055	11	28	predicting	predict	VERB
cana-2055	11	29	farm	farm	NOUN
cana-2055	11	30	-	-	PUNCT
cana-2055	11	31	level	level	NOUN
cana-2055	11	32	crop	crop	NOUN
cana-2055	11	33	yields	yield	NOUN
cana-2055	11	34	(	(	PUNCT
cana-2055	11	35	cyp	cyp	ADJ
cana-2055	11	36	)	)	PUNCT
cana-2055	11	37	is	be	AUX
cana-2055	11	38	crucial	crucial	ADJ
cana-2055	11	39	for	for	ADP
cana-2055	11	40	the	the	DET
cana-2055	11	41	import	import	NOUN
cana-2055	11	42	and	and	CCONJ
cana-2055	11	43	export	export	NOUN
cana-2055	11	44	of	of	ADP
cana-2055	11	45	farmed	farm	VERB
cana-2055	11	46	commodities	commodity	NOUN
cana-2055	11	47	and	and	CCONJ
cana-2055	11	48	raising	raise	VERB
cana-2055	11	49	farmers	farmer	NOUN
cana-2055	11	50	'	'	PART
cana-2055	11	51	incomes	income	NOUN
cana-2055	11	52	.	.	PUNCT
cana-2055	12	1	crop	crop	NOUN
cana-2055	12	2	breeding	breeding	NOUN
cana-2055	12	3	has	have	AUX
cana-2055	12	4	always	always	ADV
cana-2055	12	5	required	require	VERB
cana-2055	12	6	substantial	substantial	ADJ
cana-2055	12	7	effort	effort	NOUN
cana-2055	12	8	and	and	CCONJ
cana-2055	12	9	financial	financial	ADJ
cana-2055	12	10	investment	investment	NOUN
cana-2055	12	11	.	.	PUNCT
cana-2055	13	1	cyp	cyp	ADJ
cana-2055	13	2	is	be	AUX
cana-2055	13	3	designed	design	VERB
cana-2055	13	4	to	to	PART
cana-2055	13	5	predict	predict	VERB
cana-2055	13	6	increased	increase	VERB
cana-2055	13	7	agricultural	agricultural	ADJ
cana-2055	13	8	yield	yield	NOUN
cana-2055	13	9	.	.	PUNCT
cana-2055	14	1	this	this	DET
cana-2055	14	2	research	research	NOUN
cana-2055	14	3	presents	present	VERB
cana-2055	14	4	effective	effective	ADJ
cana-2055	14	5	deep	deep	ADJ
cana-2055	14	6	learning	learning	NOUN
cana-2055	14	7	&	&	CCONJ
cana-2055	14	8	dimensionality	dimensionality	NOUN
cana-2055	14	9	reduction	reduction	NOUN
cana-2055	14	10	(	(	PUNCT
cana-2055	14	11	dr	dr	PROPN
cana-2055	14	12	)	)	PUNCT
cana-2055	14	13	methodologies	methodology	NOUN
cana-2055	14	14	for	for	ADP
cana-2055	14	15	crop	crop	NOUN
cana-2055	14	16	yield	yield	NOUN
cana-2055	14	17	prediction	prediction	NOUN
cana-2055	14	18	(	(	PUNCT
cana-2055	14	19	cyp	cyp	ADJ
cana-2055	14	20	)	)	PUNCT
cana-2055	14	21	in	in	ADP
cana-2055	14	22	indian	indian	ADJ
cana-2055	14	23	regional	regional	ADJ
cana-2055	14	24	agriculture	agriculture	NOUN
cana-2055	14	25	.	.	PUNCT
cana-2055	15	1	this	this	DET
cana-2055	15	2	work	work	NOUN
cana-2055	15	3	consisted	consist	VERB
cana-2055	15	4	of	of	ADP
cana-2055	15	5	three	three	NUM
cana-2055	15	6	phases	phase	NOUN
cana-2055	15	7	:	:	PUNCT
cana-2055	15	8	pre	pre	ADJ
cana-2055	15	9	-	-	ADJ
cana-2055	15	10	processing	processing	ADJ
cana-2055	15	11	,	,	PUNCT
cana-2055	15	12	dimensionality	dimensionality	NOUN
cana-2055	15	13	reduction	reduction	NOUN
cana-2055	15	14	,	,	PUNCT
cana-2055	15	15	and	and	CCONJ
cana-2055	15	16	classifying	classify	VERB
cana-2055	15	17	.	.	PUNCT
cana-2055	16	1	the	the	DET
cana-2055	16	2	agricultural	agricultural	ADJ
cana-2055	16	3	information	information	NOUN
cana-2055	16	4	from	from	ADP
cana-2055	16	5	the	the	DET
cana-2055	16	6	southern	southern	PROPN
cana-2055	16	7	indian	indian	PROPN
cana-2055	16	8	area	area	NOUN
cana-2055	16	9	is	be	AUX
cana-2055	16	10	first	first	ADV
cana-2055	16	11	extracted	extract	VERB
cana-2055	16	12	from	from	ADP
cana-2055	16	13	the	the	DET
cana-2055	16	14	dataset	dataset	NOUN
cana-2055	16	15	.	.	PUNCT
cana-2055	17	1	subsequently	subsequently	ADV
cana-2055	17	2	,	,	PUNCT
cana-2055	17	3	pre	pre	ADJ
cana-2055	17	4	-	-	ADJ
cana-2055	17	5	processing	processing	NOUN
cana-2055	17	6	is	be	AUX
cana-2055	17	7	performed	perform	VERB
cana-2055	17	8	on	on	ADP
cana-2055	17	9	the	the	DET
cana-2055	17	10	gathered	gather	VERB
cana-2055	17	11	dataset	dataset	NOUN
cana-2055	17	12	via	via	ADP
cana-2055	17	13	data	datum	NOUN
cana-2055	17	14	cleaning	cleaning	NOUN
cana-2055	17	15	and	and	CCONJ
cana-2055	17	16	normalisation	normalisation	NOUN
cana-2055	17	17	.	.	PUNCT
cana-2055	18	1	subsequently	subsequently	ADV
cana-2055	18	2	,	,	PUNCT
cana-2055	18	3	dimensionality	dimensionality	NOUN
cana-2055	18	4	reduction	reduction	NOUN
cana-2055	18	5	is	be	AUX
cana-2055	18	6	executed	execute	VERB
cana-2055	18	7	utilising	utilise	VERB
cana-2055	18	8	squared	square	VERB
cana-2055	18	9	exponential	exponential	ADJ
cana-2055	18	10	kernel	kernel	NOUN
cana-2055	18	11	-	-	PUNCT
cana-2055	18	12	based	base	VERB
cana-2055	18	13	principal	principal	ADJ
cana-2055	18	14	component	component	NOUN
cana-2055	18	15	analysis	analysis	NOUN
cana-2055	18	16	(	(	PUNCT
cana-2055	18	17	sekpca	sekpca	NOUN
cana-2055	18	18	)	)	PUNCT
cana-2055	18	19	.	.	PUNCT
cana-2055	19	1	cyp	cyp	PROPN
cana-2055	19	2	uses	use	VERB
cana-2055	19	3	a	a	DET
cana-2055	19	4	weight	weight	NOUN
cana-2055	19	5	-	-	PUNCT
cana-2055	19	6	tuned	tune	VERB
cana-2055	19	7	deep	deep	ADJ
cana-2055	19	8	convolutional	convolutional	ADJ
cana-2055	19	9	neural	neural	ADJ
cana-2055	19	10	networks	network	NOUN
cana-2055	19	11	(	(	PUNCT
cana-2055	19	12	wtdcnn	wtdcnn	ADJ
cana-2055	19	13	)	)	PUNCT
cana-2055	19	14	to	to	PART
cana-2055	19	15	forecast	forecast	VERB
cana-2055	19	16	high	high	ADJ
cana-2055	19	17	agricultural	agricultural	ADJ
cana-2055	19	18	production	production	NOUN
cana-2055	19	19	profitability	profitability	NOUN
cana-2055	19	20	.	.	PUNCT
cana-2055	20	1	the	the	DET
cana-2055	20	2	results	result	NOUN
cana-2055	20	3	indicate	indicate	VERB
cana-2055	20	4	the	the	DET
cana-2055	20	5	suggested	suggest	VERB
cana-2055	20	6	technique	technique	NOUN
cana-2055	20	7	achieves	achieves	AUX
cana-2055	20	8	enhanced	enhance	VERB
cana-2055	20	9	performing	perform	VERB
cana-2055	20	10	for	for	ADP
cana-2055	20	11	cyp	cyp	ADJ
cana-2055	20	12	relative	relative	ADJ
cana-2055	20	13	to	to	ADP
cana-2055	20	14	existing	exist	VERB
cana-2055	20	15	systems	system	NOUN
cana-2055	20	16	,	,	PUNCT
cana-2055	20	17	with	with	ADP
cana-2055	20	18	an	an	DET
cana-2055	20	19	accuracy	accuracy	NOUN
cana-2055	20	20	of	of	ADP
cana-2055	20	21	98.97	98.97	NUM
cana-2055	20	22	%	%	NOUN
cana-2055	20	23	.	.	PUNCT
cana-2055	21	1	the	the	DET
cana-2055	21	2	innovation	innovation	NOUN
cana-2055	21	3	of	of	ADP
cana-2055	21	4	the	the	DET
cana-2055	21	5	suggested	suggest	VERB
cana-2055	21	6	methodology	methodology	NOUN
cana-2055	21	7	is	be	AUX
cana-2055	21	8	in	in	ADP
cana-2055	21	9	the	the	DET
cana-2055	21	10	integration	integration	NOUN
cana-2055	21	11	of	of	ADP
cana-2055	21	12	deep	deep	ADJ
cana-2055	21	13	learning	learning	NOUN
cana-2055	21	14	,	,	PUNCT
cana-2055	21	15	dimensionality	dimensionality	NOUN
cana-2055	21	16	reduction	reduction	NOUN
cana-2055	21	17	,	,	PUNCT
cana-2055	21	18	and	and	CCONJ
cana-2055	21	19	wavelet	wavelet	NOUN
cana-2055	21	20	transform	transform	VERB
cana-2055	21	21	deep	deep	ADJ
cana-2055	21	22	convolutional	convolutional	ADJ
cana-2055	21	23	neural	neural	ADJ
cana-2055	21	24	network	network	NOUN
cana-2055	21	25	methods	method	NOUN
cana-2055	21	26	for	for	ADP
cana-2055	21	27	precise	precise	ADJ
cana-2055	21	28	agricultural	agricultural	ADJ
cana-2055	21	29	production	production	NOUN
cana-2055	21	30	forecasting	forecasting	NOUN
cana-2055	21	31	,	,	PUNCT
cana-2055	21	32	particularly	particularly	ADV
cana-2055	21	33	designed	design	VERB
cana-2055	21	34	for	for	ADP
cana-2055	21	35	regional	regional	ADJ
cana-2055	21	36	crops	crop	NOUN
cana-2055	21	37	in	in	ADP
cana-2055	21	38	india	india	PROPN
cana-2055	21	39	.	.	PUNCT
cana-2055	22	1	keywords	keyword	NOUN
cana-2055	22	2	:	:	PUNCT
cana-2055	22	3	importing	import	VERB
cana-2055	22	4	and	and	CCONJ
cana-2055	22	5	exporting	exporting	NOUN
cana-2055	22	6	,	,	PUNCT
cana-2055	22	7	crop	crop	NOUN
cana-2055	22	8	breeding	breeding	NOUN
cana-2055	22	9	,	,	PUNCT
cana-2055	22	10	financial	financial	ADJ
cana-2055	22	11	investment	investment	NOUN
cana-2055	22	12	,	,	PUNCT
cana-2055	22	13	cyp	cyp	ADJ
cana-2055	22	14	,	,	PUNCT
cana-2055	22	15	sekpca	sekpca	NOUN
cana-2055	22	16	.	.	PUNCT
cana-2055	23	1	1	1	X
cana-2055	23	2	.	.	X
cana-2055	23	3	introduction	introduction	NOUN
cana-2055	23	4	the	the	DET
cana-2055	23	5	goal	goal	NOUN
cana-2055	23	6	of	of	ADP
cana-2055	23	7	agricultural	agricultural	ADJ
cana-2055	23	8	yield	yield	NOUN
cana-2055	23	9	prediction	prediction	NOUN
cana-2055	23	10	is	be	AUX
cana-2055	23	11	to	to	PART
cana-2055	23	12	estimate	estimate	VERB
cana-2055	23	13	how	how	SCONJ
cana-2055	23	14	much	much	ADJ
cana-2055	23	15	food	food	NOUN
cana-2055	23	16	will	will	AUX
cana-2055	23	17	be	be	AUX
cana-2055	23	18	harvested	harvest	VERB
cana-2055	23	19	from	from	ADP
cana-2055	23	20	a	a	DET
cana-2055	23	21	certain	certain	ADJ
cana-2055	23	22	plot	plot	NOUN
cana-2055	23	23	of	of	ADP
cana-2055	23	24	land	land	NOUN
cana-2055	23	25	.	.	PUNCT
cana-2055	24	1	in	in	ADP
cana-2055	24	2	order	order	NOUN
cana-2055	24	3	to	to	PART
cana-2055	24	4	make	make	VERB
cana-2055	24	5	educated	educate	VERB
cana-2055	24	6	judgements	judgement	NOUN
cana-2055	24	7	on	on	ADP
cana-2055	24	8	agricultural	agricultural	ADJ
cana-2055	24	9	output	output	NOUN
cana-2055	24	10	,	,	PUNCT
cana-2055	24	11	it	it	PRON
cana-2055	24	12	is	be	AUX
cana-2055	24	13	a	a	DET
cana-2055	24	14	crucial	crucial	ADJ
cana-2055	24	15	tool	tool	NOUN
cana-2055	24	16	for	for	ADP
cana-2055	24	17	farmers	farmer	NOUN
cana-2055	24	18	,	,	PUNCT
cana-2055	24	19	governments	government	NOUN
cana-2055	24	20	,	,	PUNCT
cana-2055	24	21	and	and	CCONJ
cana-2055	24	22	enterprises	enterprise	NOUN
cana-2055	24	23	.	.	PUNCT
cana-2055	25	1	predicting	predict	VERB
cana-2055	25	2	crop	crop	NOUN
cana-2055	25	3	yields	yield	NOUN
cana-2055	25	4	in	in	ADP
cana-2055	25	5	india	india	PROPN
cana-2055	25	6	is	be	AUX
cana-2055	25	7	difficult	difficult	ADJ
cana-2055	25	8	because	because	SCONJ
cana-2055	25	9	of	of	ADP
cana-2055	25	10	the	the	DET
cana-2055	25	11	country	country	NOUN
cana-2055	25	12	's	's	PART
cana-2055	25	13	varied	varied	ADJ
cana-2055	25	14	climate	climate	NOUN
cana-2055	25	15	,	,	PUNCT
cana-2055	25	16	geography	geography	NOUN
cana-2055	25	17	,	,	PUNCT
cana-2055	25	18	and	and	CCONJ
cana-2055	25	19	farming	farming	NOUN
cana-2055	25	20	techniques	technique	NOUN
cana-2055	25	21	.	.	PUNCT
cana-2055	26	1	nonetheless	nonetheless	ADV
cana-2055	26	2	,	,	PUNCT
cana-2055	26	3	one	one	PRON
cana-2055	26	4	may	may	AUX
cana-2055	26	5	anticipate	anticipate	VERB
cana-2055	26	6	crop	crop	NOUN
cana-2055	26	7	production	production	NOUN
cana-2055	26	8	based	base	VERB
cana-2055	26	9	on	on	ADP
cana-2055	26	10	a	a	DET
cana-2055	26	11	variety	variety	NOUN
cana-2055	26	12	of	of	ADP
cana-2055	26	13	criteria	criterion	NOUN
cana-2055	26	14	,	,	PUNCT
cana-2055	26	15	such	such	ADJ
cana-2055	26	16	as	as	ADP
cana-2055	26	17	:	:	PUNCT
cana-2055	26	18	mailto:krkrishna.cse@gmail.com	mailto:krkrishna.cse@gmail.com	X
cana-2055	26	19	mailto:bheemasiva2019@gmail.com	mailto:bheemasiva2019@gmail.com	PROPN
cana-2055	26	20	mailto:nvskale@gmail.com	mailto:nvskale@gmail.com	PROPN
cana-2055	26	21	mailto:yadav.loya@gmail.com	mailto:yadav.loya@gmail.com	PROPN
cana-2055	26	22	mailto:vishwapriya13@gmail.com	mailto:vishwapriya13@gmail.com	PROPN
cana-2055	26	23	communications	communication	NOUN
cana-2055	26	24	on	on	ADP
cana-2055	26	25	applied	apply	VERB
cana-2055	26	26	nonlinear	nonlinear	ADJ
cana-2055	26	27	analysis	analysis	NOUN
cana-2055	26	28	issn	issn	NOUN
cana-2055	26	29	:	:	PUNCT
cana-2055	26	30	1074	1074	NUM
cana-2055	26	31	-	-	PUNCT
cana-2055	26	32	133x	133x	NUM
cana-2055	26	33	vol	vol	NOUN
cana-2055	26	34	32	32	NUM
cana-2055	26	35	no	no	NOUN
cana-2055	26	36	.	.	NOUN
cana-2055	26	37	3	3	NUM
cana-2055	26	38	(	(	PUNCT
cana-2055	26	39	2025	2025	NUM
cana-2055	26	40	)	)	PUNCT
cana-2055	26	41	578	578	NUM
cana-2055	26	42	https://internationalpubls.com	https://internationalpubls.com	X
cana-2055	26	43	weather	weather	NOUN
cana-2055	26	44	:	:	PUNCT
cana-2055	26	45	one	one	NUM
cana-2055	26	46	of	of	ADP
cana-2055	26	47	the	the	DET
cana-2055	26	48	key	key	ADJ
cana-2055	26	49	elements	element	NOUN
cana-2055	26	50	influencing	influence	VERB
cana-2055	26	51	agricultural	agricultural	ADJ
cana-2055	26	52	productivity	productivity	NOUN
cana-2055	26	53	is	be	AUX
cana-2055	26	54	the	the	DET
cana-2055	26	55	weather	weather	NOUN
cana-2055	26	56	.	.	PUNCT
cana-2055	27	1	plant	plant	NOUN
cana-2055	27	2	growth	growth	NOUN
cana-2055	27	3	is	be	AUX
cana-2055	27	4	influenced	influence	VERB
cana-2055	27	5	by	by	ADP
cana-2055	27	6	temperature	temperature	NOUN
cana-2055	27	7	,	,	PUNCT
cana-2055	27	8	humidity	humidity	NOUN
cana-2055	27	9	,	,	PUNCT
cana-2055	27	10	and	and	CCONJ
cana-2055	27	11	rainfall	rainfall	NOUN
cana-2055	27	12	.	.	PUNCT
cana-2055	28	1	soil	soil	NOUN
cana-2055	28	2	:	:	PUNCT
cana-2055	28	3	the	the	DET
cana-2055	28	4	soil	soil	NOUN
cana-2055	28	5	type	type	NOUN
cana-2055	28	6	and	and	CCONJ
cana-2055	28	7	its	its	PRON
cana-2055	28	8	fertility	fertility	NOUN
cana-2055	28	9	influence	influence	NOUN
cana-2055	28	10	crop	crop	NOUN
cana-2055	28	11	productivity	productivity	NOUN
cana-2055	28	12	.	.	PUNCT
cana-2055	29	1	variety	variety	NOUN
cana-2055	29	2	of	of	ADP
cana-2055	29	3	crop	crop	NOUN
cana-2055	29	4	:	:	PUNCT
cana-2055	29	5	crop	crop	NOUN
cana-2055	29	6	variety	variety	NOUN
cana-2055	29	7	is	be	AUX
cana-2055	29	8	another	another	DET
cana-2055	29	9	factor	factor	NOUN
cana-2055	29	10	that	that	PRON
cana-2055	29	11	might	might	AUX
cana-2055	29	12	influence	influence	VERB
cana-2055	29	13	yield	yield	NOUN
cana-2055	29	14	.	.	PUNCT
cana-2055	30	1	when	when	SCONJ
cana-2055	30	2	it	it	PRON
cana-2055	30	3	comes	come	VERB
cana-2055	30	4	to	to	ADP
cana-2055	30	5	pests	pest	NOUN
cana-2055	30	6	and	and	CCONJ
cana-2055	30	7	illnesses	illness	NOUN
cana-2055	30	8	,	,	PUNCT
cana-2055	30	9	some	some	DET
cana-2055	30	10	kinds	kind	NOUN
cana-2055	30	11	are	be	AUX
cana-2055	30	12	resistant	resistant	ADJ
cana-2055	30	13	than	than	ADP
cana-2055	30	14	others	other	NOUN
cana-2055	30	15	.	.	PUNCT
cana-2055	31	1	practices	practice	NOUN
cana-2055	31	2	for	for	ADP
cana-2055	31	3	farm	farm	NOUN
cana-2055	31	4	management	management	NOUN
cana-2055	31	5	:	:	PUNCT
cana-2055	31	6	crop	crop	NOUN
cana-2055	31	7	output	output	NOUN
cana-2055	31	8	is	be	AUX
cana-2055	31	9	also	also	ADV
cana-2055	31	10	affected	affect	VERB
cana-2055	31	11	by	by	ADP
cana-2055	31	12	farm	farm	NOUN
cana-2055	31	13	management	management	NOUN
cana-2055	31	14	.	.	PUNCT
cana-2055	32	1	one	one	NUM
cana-2055	32	2	way	way	NOUN
cana-2055	32	3	to	to	PART
cana-2055	32	4	increase	increase	VERB
cana-2055	32	5	crop	crop	NOUN
cana-2055	32	6	output	output	NOUN
cana-2055	32	7	is	be	AUX
cana-2055	32	8	to	to	PART
cana-2055	32	9	use	use	VERB
cana-2055	32	10	good	good	ADJ
cana-2055	32	11	agricultural	agricultural	ADJ
cana-2055	32	12	management	management	NOUN
cana-2055	32	13	methods	method	NOUN
cana-2055	32	14	like	like	ADP
cana-2055	32	15	watering	watering	NOUN
cana-2055	32	16	and	and	CCONJ
cana-2055	32	17	insect	insect	NOUN
cana-2055	32	18	control	control	NOUN
cana-2055	32	19	.	.	PUNCT
cana-2055	33	1	these	these	DET
cana-2055	33	2	elements	element	NOUN
cana-2055	33	3	may	may	AUX
cana-2055	33	4	be	be	AUX
cana-2055	33	5	taken	take	VERB
cana-2055	33	6	into	into	ADP
cana-2055	33	7	consideration	consideration	NOUN
cana-2055	33	8	when	when	SCONJ
cana-2055	33	9	predicting	predict	VERB
cana-2055	33	10	crop	crop	NOUN
cana-2055	33	11	production	production	NOUN
cana-2055	33	12	using	use	VERB
cana-2055	33	13	crop	crop	NOUN
cana-2055	33	14	yield	yield	NOUN
cana-2055	33	15	prediction	prediction	NOUN
cana-2055	33	16	models	model	NOUN
cana-2055	33	17	.	.	PUNCT
cana-2055	34	1	these	these	DET
cana-2055	34	2	models	model	NOUN
cana-2055	34	3	may	may	AUX
cana-2055	34	4	use	use	VERB
cana-2055	34	5	machine	machine	NOUN
cana-2055	34	6	learning	learning	NOUN
cana-2055	34	7	,	,	PUNCT
cana-2055	34	8	statistical	statistical	ADJ
cana-2055	34	9	approaches	approach	NOUN
cana-2055	34	10	,	,	PUNCT
cana-2055	34	11	or	or	CCONJ
cana-2055	34	12	a	a	DET
cana-2055	34	13	mix	mix	NOUN
cana-2055	34	14	of	of	ADP
cana-2055	34	15	the	the	DET
cana-2055	34	16	two	two	NUM
cana-2055	34	17	.	.	PUNCT
cana-2055	35	1	soil	soil	NOUN
cana-2055	35	2	sensors	sensor	NOUN
cana-2055	35	3	,	,	PUNCT
cana-2055	35	4	weather	weather	NOUN
cana-2055	35	5	stations	station	NOUN
cana-2055	35	6	,	,	PUNCT
cana-2055	35	7	and	and	CCONJ
cana-2055	35	8	remote	remote	ADJ
cana-2055	35	9	sensing	sensing	NOUN
cana-2055	35	10	have	have	AUX
cana-2055	35	11	all	all	PRON
cana-2055	35	12	contributed	contribute	VERB
cana-2055	35	13	to	to	ADP
cana-2055	35	14	a	a	DET
cana-2055	35	15	dramatic	dramatic	ADJ
cana-2055	35	16	increase	increase	NOUN
cana-2055	35	17	in	in	ADP
cana-2055	35	18	the	the	DET
cana-2055	35	19	quantity	quantity	NOUN
cana-2055	35	20	of	of	ADP
cana-2055	35	21	data	datum	NOUN
cana-2055	35	22	used	use	VERB
cana-2055	35	23	in	in	ADP
cana-2055	35	24	agriculture	agriculture	NOUN
cana-2055	35	25	in	in	ADP
cana-2055	35	26	recent	recent	ADJ
cana-2055	35	27	years	year	NOUN
cana-2055	35	28	.	.	PUNCT
cana-2055	36	1	building	build	VERB
cana-2055	36	2	predictive	predictive	ADJ
cana-2055	36	3	models	model	NOUN
cana-2055	36	4	for	for	ADP
cana-2055	36	5	managing	manage	VERB
cana-2055	36	6	and	and	CCONJ
cana-2055	36	7	estimating	estimate	VERB
cana-2055	36	8	crop	crop	NOUN
cana-2055	36	9	yields	yield	NOUN
cana-2055	36	10	is	be	AUX
cana-2055	36	11	possible	possible	ADJ
cana-2055	36	12	with	with	ADP
cana-2055	36	13	this	this	DET
cana-2055	36	14	data	datum	NOUN
cana-2055	36	15	.	.	PUNCT
cana-2055	37	1	data	datum	NOUN
cana-2055	37	2	analysis	analysis	NOUN
cana-2055	37	3	and	and	CCONJ
cana-2055	37	4	modelling	modelling	NOUN
cana-2055	37	5	face	face	VERB
cana-2055	37	6	substantial	substantial	ADJ
cana-2055	37	7	obstacles	obstacle	NOUN
cana-2055	37	8	from	from	ADP
cana-2055	37	9	the	the	DET
cana-2055	37	10	huge	huge	ADJ
cana-2055	37	11	amount	amount	NOUN
cana-2055	37	12	and	and	CCONJ
cana-2055	37	13	complexity	complexity	NOUN
cana-2055	37	14	of	of	ADP
cana-2055	37	15	data	datum	NOUN
cana-2055	37	16	used	use	VERB
cana-2055	37	17	in	in	ADP
cana-2055	37	18	agriculture	agriculture	NOUN
cana-2055	37	19	.	.	PUNCT
cana-2055	38	1	thus	thus	ADV
cana-2055	38	2	,	,	PUNCT
cana-2055	38	3	to	to	PART
cana-2055	38	4	enhance	enhance	VERB
cana-2055	38	5	crop	crop	NOUN
cana-2055	38	6	production	production	NOUN
cana-2055	38	7	prediction	prediction	NOUN
cana-2055	38	8	and	and	CCONJ
cana-2055	38	9	management	management	NOUN
cana-2055	38	10	,	,	PUNCT
cana-2055	38	11	efficient	efficient	ADJ
cana-2055	38	12	and	and	CCONJ
cana-2055	38	13	effective	effective	ADJ
cana-2055	38	14	techniques	technique	NOUN
cana-2055	38	15	of	of	ADP
cana-2055	38	16	analysing	analyse	VERB
cana-2055	38	17	and	and	CCONJ
cana-2055	38	18	modelling	model	VERB
cana-2055	38	19	agricultural	agricultural	ADJ
cana-2055	38	20	data	datum	NOUN
cana-2055	38	21	are	be	AUX
cana-2055	38	22	required	require	VERB
cana-2055	38	23	.	.	PUNCT
cana-2055	39	1	for	for	ADP
cana-2055	39	2	india	india	PROPN
cana-2055	39	3	's	's	PART
cana-2055	39	4	massive	massive	ADJ
cana-2055	39	5	population	population	NOUN
cana-2055	39	6	,	,	PUNCT
cana-2055	39	7	agriculture	agriculture	NOUN
cana-2055	39	8	provides	provide	VERB
cana-2055	39	9	both	both	PRON
cana-2055	39	10	sustenance	sustenance	NOUN
cana-2055	39	11	and	and	CCONJ
cana-2055	39	12	economic	economic	ADJ
cana-2055	39	13	stability	stability	NOUN
cana-2055	39	14	.	.	PUNCT
cana-2055	40	1	the	the	DET
cana-2055	40	2	significant	significant	ADJ
cana-2055	40	3	climatic	climatic	ADJ
cana-2055	40	4	changes	change	NOUN
cana-2055	40	5	and	and	CCONJ
cana-2055	40	6	fast	fast	ADJ
cana-2055	40	7	population	population	NOUN
cana-2055	40	8	expansion	expansion	NOUN
cana-2055	40	9	in	in	ADP
cana-2055	40	10	india	india	PROPN
cana-2055	40	11	make	make	VERB
cana-2055	40	12	it	it	PRON
cana-2055	40	13	imperative	imperative	ADJ
cana-2055	40	14	to	to	PART
cana-2055	40	15	keep	keep	VERB
cana-2055	40	16	the	the	DET
cana-2055	40	17	supply	supply	NOUN
cana-2055	40	18	of	of	ADP
cana-2055	40	19	food	food	NOUN
cana-2055	40	20	and	and	CCONJ
cana-2055	40	21	demand	demand	NOUN
cana-2055	40	22	chain	chain	NOUN
cana-2055	40	23	in	in	ADP
cana-2055	40	24	good	good	ADJ
cana-2055	40	25	working	working	NOUN
cana-2055	40	26	order	order	NOUN
cana-2055	40	27	.	.	PUNCT
cana-2055	41	1	in	in	ADP
cana-2055	41	2	a	a	DET
cana-2055	41	3	pivotal	pivotal	ADJ
cana-2055	41	4	research	research	NOUN
cana-2055	41	5	,	,	PUNCT
cana-2055	41	6	agronomic	agronomic	ADJ
cana-2055	41	7	specialists	specialist	NOUN
cana-2055	41	8	mapped	map	VERB
cana-2055	41	9	,	,	PUNCT
cana-2055	41	10	monitored	monitor	VERB
cana-2055	41	11	,	,	PUNCT
cana-2055	41	12	analysed	analyse	VERB
cana-2055	41	13	,	,	PUNCT
cana-2055	41	14	and	and	CCONJ
cana-2055	41	15	managed	manage	VERB
cana-2055	41	16	yield	yield	NOUN
cana-2055	41	17	variability	variability	NOUN
cana-2055	41	18	to	to	PART
cana-2055	41	19	maximise	maximise	VERB
cana-2055	41	20	agricultural	agricultural	ADJ
cana-2055	41	21	output	output	NOUN
cana-2055	41	22	.	.	PUNCT
cana-2055	42	1	one	one	NUM
cana-2055	42	2	tactic	tactic	NOUN
cana-2055	42	3	that	that	PRON
cana-2055	42	4	may	may	AUX
cana-2055	42	5	aid	aid	VERB
cana-2055	42	6	in	in	ADP
cana-2055	42	7	crop	crop	NOUN
cana-2055	42	8	management	management	NOUN
cana-2055	42	9	is	be	AUX
cana-2055	42	10	the	the	DET
cana-2055	42	11	use	use	NOUN
cana-2055	42	12	of	of	ADP
cana-2055	42	13	crop	crop	NOUN
cana-2055	42	14	production	production	NOUN
cana-2055	42	15	projections	projection	NOUN
cana-2055	42	16	.	.	PUNCT
cana-2055	43	1	in	in	ADP
cana-2055	43	2	the	the	DET
cana-2055	43	3	food	food	NOUN
cana-2055	43	4	industry	industry	NOUN
cana-2055	43	5	,	,	PUNCT
cana-2055	43	6	cyp	cyp	ADJ
cana-2055	43	7	plays	play	VERB
cana-2055	43	8	a	a	DET
cana-2055	43	9	vital	vital	ADJ
cana-2055	43	10	role	role	NOUN
cana-2055	43	11	.	.	PUNCT
cana-2055	44	1	because	because	SCONJ
cana-2055	44	2	of	of	ADP
cana-2055	44	3	its	its	PRON
cana-2055	44	4	importance	importance	NOUN
cana-2055	44	5	in	in	ADP
cana-2055	44	6	national	national	ADJ
cana-2055	44	7	and	and	CCONJ
cana-2055	44	8	international	international	ADJ
cana-2055	44	9	programming	programming	NOUN
cana-2055	44	10	,	,	PUNCT
cana-2055	44	11	cyp	cyp	ADJ
cana-2055	44	12	for	for	ADP
cana-2055	44	13	important	important	ADJ
cana-2055	44	14	plants	plant	NOUN
cana-2055	44	15	including	include	VERB
cana-2055	44	16	wheat	wheat	NOUN
cana-2055	44	17	,	,	PUNCT
cana-2055	44	18	rice	rice	NOUN
cana-2055	44	19	,	,	PUNCT
cana-2055	44	20	and	and	CCONJ
cana-2055	44	21	maize	maize	NOUN
cana-2055	44	22	is	be	AUX
cana-2055	44	23	an	an	DET
cana-2055	44	24	intriguing	intriguing	ADJ
cana-2055	44	25	area	area	NOUN
cana-2055	44	26	of	of	ADP
cana-2055	44	27	study	study	NOUN
cana-2055	44	28	for	for	ADP
cana-2055	44	29	agrometeorologists	agrometeorologist	NOUN
cana-2055	44	30	.	.	PUNCT
cana-2055	45	1	consequently	consequently	ADV
cana-2055	45	2	,	,	PUNCT
cana-2055	45	3	systems	system	NOUN
cana-2055	45	4	that	that	PRON
cana-2055	45	5	evaluate	evaluate	VERB
cana-2055	45	6	accuracy	accuracy	NOUN
cana-2055	45	7	using	use	VERB
cana-2055	45	8	weather	weather	NOUN
cana-2055	45	9	data	datum	NOUN
cana-2055	45	10	do	do	AUX
cana-2055	45	11	exist	exist	VERB
cana-2055	45	12	.	.	PUNCT
cana-2055	46	1	policymakers	policymaker	NOUN
cana-2055	46	2	on	on	ADP
cana-2055	46	3	a	a	DET
cana-2055	46	4	worldwide	worldwide	NOUN
cana-2055	46	5	and	and	CCONJ
cana-2055	46	6	regional	regional	ADJ
cana-2055	46	7	scale	scale	NOUN
cana-2055	46	8	are	be	AUX
cana-2055	46	9	presently	presently	ADV
cana-2055	46	10	facing	face	VERB
cana-2055	46	11	a	a	DET
cana-2055	46	12	challenging	challenging	ADJ
cana-2055	46	13	problem	problem	NOUN
cana-2055	46	14	when	when	SCONJ
cana-2055	46	15	it	it	PRON
cana-2055	46	16	comes	come	VERB
cana-2055	46	17	to	to	ADP
cana-2055	46	18	agricultural	agricultural	ADJ
cana-2055	46	19	production	production	NOUN
cana-2055	46	20	forecasting	forecasting	NOUN
cana-2055	46	21	.	.	PUNCT
cana-2055	47	1	the	the	DET
cana-2055	47	2	best	good	ADJ
cana-2055	47	3	way	way	NOUN
cana-2055	47	4	for	for	SCONJ
cana-2055	47	5	farmers	farmer	NOUN
cana-2055	47	6	to	to	PART
cana-2055	47	7	know	know	VERB
cana-2055	47	8	when	when	SCONJ
cana-2055	47	9	and	and	CCONJ
cana-2055	47	10	what	what	PRON
cana-2055	47	11	to	to	PART
cana-2055	47	12	plant	plant	VERB
cana-2055	47	13	is	be	AUX
cana-2055	47	14	using	use	VERB
cana-2055	47	15	a	a	DET
cana-2055	47	16	trustworthy	trustworthy	ADJ
cana-2055	47	17	crop	crop	NOUN
cana-2055	47	18	production	production	NOUN
cana-2055	47	19	prediction	prediction	NOUN
cana-2055	47	20	model	model	NOUN
cana-2055	47	21	.	.	PUNCT
cana-2055	48	1	a	a	DET
cana-2055	48	2	number	number	NOUN
cana-2055	48	3	of	of	ADP
cana-2055	48	4	approaches	approach	NOUN
cana-2055	48	5	exist	exist	VERB
cana-2055	48	6	for	for	ADP
cana-2055	48	7	the	the	DET
cana-2055	48	8	purpose	purpose	NOUN
cana-2055	48	9	of	of	ADP
cana-2055	48	10	predicting	predict	VERB
cana-2055	48	11	crop	crop	NOUN
cana-2055	48	12	yields	yield	NOUN
cana-2055	48	13	.	.	PUNCT
cana-2055	49	1	machine	machine	NOUN
cana-2055	49	2	learning	learning	NOUN
cana-2055	49	3	(	(	PUNCT
cana-2055	49	4	ml	ml	NOUN
cana-2055	49	5	)	)	PUNCT
cana-2055	49	6	is	be	AUX
cana-2055	49	7	a	a	DET
cana-2055	49	8	technology	technology	NOUN
cana-2055	49	9	used	use	VERB
cana-2055	49	10	to	to	PART
cana-2055	49	11	predict	predict	VERB
cana-2055	49	12	agricultural	agricultural	ADJ
cana-2055	49	13	yields	yield	NOUN
cana-2055	49	14	,	,	PUNCT
cana-2055	49	15	alongside	alongside	ADP
cana-2055	49	16	support	support	NOUN
cana-2055	49	17	vector	vector	NOUN
cana-2055	49	18	machines	machine	NOUN
cana-2055	49	19	(	(	PUNCT
cana-2055	49	20	svm	svm	PROPN
cana-2055	49	21	)	)	PUNCT
cana-2055	49	22	,	,	PUNCT
cana-2055	49	23	random	random	ADJ
cana-2055	49	24	forests	forest	NOUN
cana-2055	49	25	(	(	PUNCT
cana-2055	49	26	rf	rf	NOUN
cana-2055	49	27	)	)	PUNCT
cana-2055	49	28	,	,	PUNCT
cana-2055	49	29	decision	decision	NOUN
cana-2055	49	30	trees	tree	NOUN
cana-2055	49	31	(	(	PUNCT
cana-2055	49	32	dt	dt	NOUN
cana-2055	49	33	)	)	PUNCT
cana-2055	49	34	,	,	PUNCT
cana-2055	49	35	and	and	CCONJ
cana-2055	49	36	others	other	NOUN
cana-2055	49	37	.	.	PUNCT
cana-2055	50	1	calibration	calibration	NOUN
cana-2055	50	2	models	model	NOUN
cana-2055	50	3	for	for	ADP
cana-2055	50	4	crops	crop	NOUN
cana-2055	50	5	are	be	AUX
cana-2055	50	6	more	more	ADV
cana-2055	50	7	readily	readily	ADV
cana-2055	50	8	adopted	adopt	VERB
cana-2055	50	9	than	than	ADP
cana-2055	50	10	simulated	simulated	ADJ
cana-2055	50	11	crop	crop	NOUN
cana-2055	50	12	models	model	NOUN
cana-2055	50	13	due	due	ADP
cana-2055	50	14	to	to	ADP
cana-2055	50	15	their	their	PRON
cana-2055	50	16	lack	lack	NOUN
cana-2055	50	17	of	of	ADP
cana-2055	50	18	need	need	NOUN
cana-2055	50	19	for	for	ADP
cana-2055	50	20	specialist	specialist	ADJ
cana-2055	50	21	expertise	expertise	NOUN
cana-2055	50	22	or	or	CCONJ
cana-2055	50	23	user	user	NOUN
cana-2055	50	24	proficiency	proficiency	NOUN
cana-2055	50	25	,	,	PUNCT
cana-2055	50	26	reduced	reduce	VERB
cana-2055	50	27	execution	execution	NOUN
cana-2055	50	28	durations	duration	NOUN
cana-2055	50	29	,	,	PUNCT
cana-2055	50	30	and	and	CCONJ
cana-2055	50	31	lower	low	ADJ
cana-2055	50	32	data	datum	NOUN
cana-2055	50	33	storage	storage	NOUN
cana-2055	50	34	constraints	constraint	NOUN
cana-2055	50	35	.	.	PUNCT
cana-2055	51	1	although	although	SCONJ
cana-2055	51	2	several	several	ADJ
cana-2055	51	3	machine	machine	NOUN
cana-2055	51	4	learning	learning	NOUN
cana-2055	51	5	models	model	NOUN
cana-2055	51	6	have	have	AUX
cana-2055	51	7	been	be	AUX
cana-2055	51	8	developed	develop	VERB
cana-2055	51	9	to	to	PART
cana-2055	51	10	enhance	enhance	VERB
cana-2055	51	11	forecast	forecast	NOUN
cana-2055	51	12	accuracy	accuracy	NOUN
cana-2055	51	13	,	,	PUNCT
cana-2055	51	14	the	the	DET
cana-2055	51	15	spatial	spatial	ADJ
cana-2055	51	16	as	as	ADV
cana-2055	51	17	well	well	ADV
cana-2055	51	18	as	as	ADP
cana-2055	51	19	temporal	temporal	ADJ
cana-2055	51	20	nonstationarity	nonstationarity	NOUN
cana-2055	51	21	inherent	inherent	ADJ
cana-2055	51	22	to	to	ADP
cana-2055	51	23	several	several	ADJ
cana-2055	51	24	geographical	geographical	ADJ
cana-2055	51	25	phenomena	phenomenon	NOUN
cana-2055	51	26	is	be	AUX
cana-2055	51	27	never	never	ADV
cana-2055	51	28	included	include	VERB
cana-2055	51	29	into	into	ADP
cana-2055	51	30	agricultural	agricultural	ADJ
cana-2055	51	31	production	production	NOUN
cana-2055	51	32	modelling	modelling	NOUN
cana-2055	51	33	.	.	PUNCT
cana-2055	52	1	recently	recently	ADV
cana-2055	52	2	,	,	PUNCT
cana-2055	52	3	deep	deep	ADJ
cana-2055	52	4	learning	learning	NOUN
cana-2055	52	5	has	have	AUX
cana-2055	52	6	been	be	AUX
cana-2055	52	7	utilised	utilise	VERB
cana-2055	52	8	to	to	PART
cana-2055	52	9	create	create	VERB
cana-2055	52	10	several	several	ADJ
cana-2055	52	11	effective	effective	ADJ
cana-2055	52	12	computations	computation	NOUN
cana-2055	52	13	,	,	PUNCT
cana-2055	52	14	as	as	SCONJ
cana-2055	52	15	it	it	PRON
cana-2055	52	16	facilitates	facilitate	VERB
cana-2055	52	17	the	the	DET
cana-2055	52	18	selection	selection	NOUN
cana-2055	52	19	of	of	ADP
cana-2055	52	20	the	the	DET
cana-2055	52	21	most	most	ADV
cana-2055	52	22	appropriate	appropriate	ADJ
cana-2055	52	23	crop	crop	NOUN
cana-2055	52	24	from	from	ADP
cana-2055	52	25	various	various	ADJ
cana-2055	52	26	alternatives	alternative	NOUN
cana-2055	52	27	.	.	PUNCT
cana-2055	53	1	it	it	PRON
cana-2055	53	2	is	be	AUX
cana-2055	53	3	a	a	DET
cana-2055	53	4	machine	machine	NOUN
cana-2055	53	5	learning	learn	VERB
cana-2055	53	6	class	class	NOUN
cana-2055	53	7	including	include	VERB
cana-2055	53	8	numerous	numerous	ADJ
cana-2055	53	9	layers	layer	NOUN
cana-2055	53	10	of	of	ADP
cana-2055	53	11	neural	neural	ADJ
cana-2055	53	12	networks	network	NOUN
cana-2055	53	13	that	that	PRON
cana-2055	53	14	can	can	AUX
cana-2055	53	15	learn	learn	VERB
cana-2055	53	16	from	from	ADP
cana-2055	53	17	data	datum	NOUN
cana-2055	53	18	.	.	PUNCT
cana-2055	54	1	by	by	ADP
cana-2055	54	2	determining	determine	VERB
cana-2055	54	3	the	the	DET
cana-2055	54	4	connections	connection	NOUN
cana-2055	54	5	between	between	ADP
cana-2055	54	6	the	the	DET
cana-2055	54	7	input	input	NOUN
cana-2055	54	8	and	and	CCONJ
cana-2055	54	9	response	response	NOUN
cana-2055	54	10	variables	variable	NOUN
cana-2055	54	11	,	,	PUNCT
cana-2055	54	12	it	it	PRON
cana-2055	54	13	hopes	hope	VERB
cana-2055	54	14	to	to	PART
cana-2055	54	15	provide	provide	VERB
cana-2055	54	16	predictions	prediction	NOUN
cana-2055	54	17	.	.	PUNCT
cana-2055	55	1	but	but	CCONJ
cana-2055	55	2	dl	dl	PROPN
cana-2055	55	3	's	's	PART
cana-2055	55	4	dependence	dependence	NOUN
cana-2055	55	5	on	on	ADP
cana-2055	55	6	hyper	hyper	NOUN
cana-2055	55	7	-	-	NOUN
cana-2055	55	8	parameters	parameter	NOUN
cana-2055	55	9	is	be	AUX
cana-2055	55	10	a	a	DET
cana-2055	55	11	major	major	ADJ
cana-2055	55	12	drawback	drawback	NOUN
cana-2055	55	13	that	that	PRON
cana-2055	55	14	may	may	AUX
cana-2055	55	15	be	be	AUX
cana-2055	55	16	circumvented	circumvent	VERB
cana-2055	55	17	to	to	PART
cana-2055	55	18	get	get	VERB
cana-2055	55	19	better	well	ADJ
cana-2055	55	20	outcomes	outcome	NOUN
cana-2055	55	21	.	.	PUNCT
cana-2055	56	1	in	in	ADP
cana-2055	56	2	the	the	DET
cana-2055	56	3	past	past	NOUN
cana-2055	56	4	,	,	PUNCT
cana-2055	56	5	experts	expert	NOUN
cana-2055	56	6	in	in	ADP
cana-2055	56	7	dl	dl	PROPN
cana-2055	56	8	approaches	approach	NOUN
cana-2055	56	9	have	have	AUX
cana-2055	56	10	often	often	ADV
cana-2055	56	11	had	have	VERB
cana-2055	56	12	to	to	PART
cana-2055	56	13	hand	hand	NOUN
cana-2055	56	14	-	-	PUNCT
cana-2055	56	15	design	design	NOUN
cana-2055	56	16	structures	structure	NOUN
cana-2055	56	17	in	in	ADP
cana-2055	56	18	order	order	NOUN
cana-2055	56	19	to	to	PART
cana-2055	56	20	forecast	forecast	VERB
cana-2055	56	21	agricultural	agricultural	ADJ
cana-2055	56	22	yields	yield	NOUN
cana-2055	56	23	.	.	PUNCT
cana-2055	57	1	their	their	PRON
cana-2055	57	2	lack	lack	NOUN
cana-2055	57	3	of	of	ADP
cana-2055	57	4	understanding	understanding	NOUN
cana-2055	57	5	of	of	ADP
cana-2055	57	6	agriculture	agriculture	NOUN
cana-2055	57	7	prevents	prevent	VERB
cana-2055	57	8	them	they	PRON
cana-2055	57	9	from	from	ADP
cana-2055	57	10	creating	create	VERB
cana-2055	57	11	excellent	excellent	ADJ
cana-2055	57	12	buildings	building	NOUN
cana-2055	57	13	.	.	PUNCT
cana-2055	58	1	consequently	consequently	ADV
cana-2055	58	2	,	,	PUNCT
cana-2055	58	3	our	our	PRON
cana-2055	58	4	study	study	NOUN
cana-2055	58	5	offered	offer	VERB
cana-2055	58	6	a	a	DET
cana-2055	58	7	realistic	realistic	ADJ
cana-2055	58	8	deep	deep	ADJ
cana-2055	58	9	-	-	PUNCT
cana-2055	58	10	learning	learn	VERB
cana-2055	58	11	strategy	strategy	NOUN
cana-2055	58	12	for	for	ADP
cana-2055	58	13	regional	regional	ADJ
cana-2055	58	14	communications	communication	NOUN
cana-2055	58	15	on	on	ADP
cana-2055	58	16	applied	apply	VERB
cana-2055	58	17	nonlinear	nonlinear	ADJ
cana-2055	58	18	analysis	analysis	NOUN
cana-2055	58	19	issn	issn	NOUN
cana-2055	58	20	:	:	PUNCT
cana-2055	58	21	1074	1074	NUM
cana-2055	58	22	-	-	PUNCT
cana-2055	58	23	133x	133x	NUM
cana-2055	58	24	vol	vol	NOUN
cana-2055	58	25	32	32	NUM
cana-2055	58	26	no	no	NOUN
cana-2055	58	27	.	.	NOUN
cana-2055	58	28	3	3	NUM
cana-2055	58	29	(	(	PUNCT
cana-2055	58	30	2025	2025	NUM
cana-2055	58	31	)	)	PUNCT
cana-2055	59	1	579	579	NUM
cana-2055	59	2	https://internationalpubls.com	https://internationalpubls.com	X
cana-2055	59	3	crops	crop	NOUN
cana-2055	59	4	in	in	ADP
cana-2055	59	5	india	india	PROPN
cana-2055	59	6	,	,	PUNCT
cana-2055	59	7	including	include	VERB
cana-2055	59	8	with	with	ADP
cana-2055	59	9	appropriate	appropriate	ADJ
cana-2055	59	10	hyperparameter	hyperparameter	NOUN
cana-2055	59	11	adjustment	adjustment	NOUN
cana-2055	59	12	for	for	ADP
cana-2055	59	13	cyp	cyp	ADJ
cana-2055	59	14	.	.	PUNCT
cana-2055	60	1	the	the	DET
cana-2055	60	2	following	follow	VERB
cana-2055	60	3	are	be	AUX
cana-2055	60	4	the	the	DET
cana-2055	60	5	primary	primary	ADJ
cana-2055	60	6	benefits	benefit	NOUN
cana-2055	60	7	of	of	ADP
cana-2055	60	8	the	the	DET
cana-2055	60	9	work	work	NOUN
cana-2055	60	10	:	:	PUNCT
cana-2055	60	11	•	•	NUM
cana-2055	60	12	data	datum	NOUN
cana-2055	60	13	cleaning	cleaning	NOUN
cana-2055	60	14	and	and	CCONJ
cana-2055	60	15	normalisation	normalisation	NOUN
cana-2055	60	16	provide	provide	VERB
cana-2055	60	17	the	the	DET
cana-2055	60	18	basis	basis	NOUN
cana-2055	60	19	of	of	ADP
cana-2055	60	20	the	the	DET
cana-2055	60	21	pre	pre	ADJ
cana-2055	60	22	-	-	ADJ
cana-2055	60	23	processing	processing	ADJ
cana-2055	60	24	steps	step	NOUN
cana-2055	60	25	used	use	VERB
cana-2055	60	26	to	to	PART
cana-2055	60	27	eliminate	eliminate	VERB
cana-2055	60	28	noise	noise	NOUN
cana-2055	60	29	and	and	CCONJ
cana-2055	60	30	standardise	standardise	VERB
cana-2055	60	31	the	the	DET
cana-2055	60	32	dataset	dataset	NOUN
cana-2055	60	33	.	.	PUNCT
cana-2055	61	1	•	•	ADP
cana-2055	61	2	to	to	PART
cana-2055	61	3	execute	execute	VERB
cana-2055	61	4	the	the	DET
cana-2055	61	5	dr	dr	PROPN
cana-2055	61	6	,	,	PUNCT
cana-2055	61	7	first	first	ADV
cana-2055	61	8	decrease	decrease	VERB
cana-2055	61	9	the	the	DET
cana-2055	61	10	dimensionality	dimensionality	NOUN
cana-2055	61	11	of	of	ADP
cana-2055	61	12	the	the	DET
cana-2055	61	13	data	datum	NOUN
cana-2055	61	14	using	use	VERB
cana-2055	61	15	the	the	DET
cana-2055	61	16	sekpca	sekpca	ADJ
cana-2055	61	17	technique	technique	NOUN
cana-2055	61	18	.	.	PUNCT
cana-2055	62	1	•	•	NUM
cana-2055	62	2	the	the	DET
cana-2055	62	3	wtdcnn	wtdcnn	ADJ
cana-2055	62	4	model	model	NOUN
cana-2055	62	5	is	be	AUX
cana-2055	62	6	used	use	VERB
cana-2055	62	7	to	to	PART
cana-2055	62	8	forecast	forecast	VERB
cana-2055	62	9	the	the	DET
cana-2055	62	10	most	most	ADV
cana-2055	62	11	lucrative	lucrative	ADJ
cana-2055	62	12	crop	crop	NOUN
cana-2055	62	13	production	production	NOUN
cana-2055	62	14	,	,	PUNCT
cana-2055	62	15	and	and	CCONJ
cana-2055	62	16	the	the	DET
cana-2055	62	17	ewoa	ewoa	ADJ
cana-2055	62	18	is	be	AUX
cana-2055	62	19	used	use	VERB
cana-2055	62	20	to	to	PART
cana-2055	62	21	determine	determine	VERB
cana-2055	62	22	the	the	DET
cana-2055	62	23	dcnn	dcnn	PROPN
cana-2055	62	24	weights	weight	NOUN
cana-2055	62	25	effectively	effectively	ADV
cana-2055	62	26	.	.	PUNCT
cana-2055	63	1	2	2	X
cana-2055	63	2	.	.	X
cana-2055	63	3	related	relate	VERB
cana-2055	63	4	works	work	VERB
cana-2055	63	5	the	the	DET
cana-2055	63	6	authors	author	NOUN
cana-2055	63	7	introduced	introduce	VERB
cana-2055	63	8	a	a	DET
cana-2055	63	9	cyp	cyp	ADJ
cana-2055	63	10	method	method	NOUN
cana-2055	63	11	using	use	VERB
cana-2055	63	12	proximate	proximate	NOUN
cana-2055	63	13	sensing	sense	VERB
cana-2055	63	14	and	and	CCONJ
cana-2055	63	15	ml	ml	ADP
cana-2055	63	16	techniques	technique	NOUN
cana-2055	63	17	.	.	PUNCT
cana-2055	64	1	training	training	NOUN
cana-2055	64	2	was	be	AUX
cana-2055	64	3	done	do	VERB
cana-2055	64	4	using	use	VERB
cana-2055	64	5	four	four	NUM
cana-2055	64	6	publicly	publicly	ADV
cana-2055	64	7	accessible	accessible	ADJ
cana-2055	64	8	datasets	dataset	NOUN
cana-2055	64	9	:	:	PUNCT
cana-2055	64	10	pe-2019	pe-2019	NOUN
cana-2055	64	11	,	,	PUNCT
cana-2055	64	12	pe-2021	pe-2021	NOUN
cana-2055	64	13	,	,	PUNCT
cana-2055	64	14	nb-2019	nb-2019	X
cana-2055	64	15	,	,	PUNCT
cana-2055	64	16	and	and	CCONJ
cana-2055	64	17	nb-2021	nb-2021	NOUN
cana-2055	64	18	.	.	PUNCT
cana-2055	65	1	for	for	ADP
cana-2055	65	2	agricultural	agricultural	ADJ
cana-2055	65	3	yield	yield	NOUN
cana-2055	65	4	prediction	prediction	NOUN
cana-2055	65	5	,	,	PUNCT
cana-2055	65	6	k	k	X
cana-2055	65	7	-	-	PUNCT
cana-2055	65	8	nearest	near	ADJ
cana-2055	65	9	neighbour	neighbour	NOUN
cana-2055	65	10	(	(	PUNCT
cana-2055	65	11	knn	knn	PROPN
cana-2055	65	12	)	)	PUNCT
cana-2055	65	13	,	,	PUNCT
cana-2055	65	14	support	support	NOUN
cana-2055	65	15	vector	vector	NOUN
cana-2055	65	16	regression	regression	NOUN
cana-2055	65	17	(	(	PUNCT
cana-2055	65	18	svr	svr	PROPN
cana-2055	65	19	)	)	PUNCT
cana-2055	65	20	,	,	PUNCT
cana-2055	65	21	linear	linear	ADJ
cana-2055	65	22	regression	regression	NOUN
cana-2055	65	23	(	(	PUNCT
cana-2055	65	24	lr	lr	NOUN
cana-2055	65	25	)	)	PUNCT
cana-2055	65	26	,	,	PUNCT
cana-2055	65	27	and	and	CCONJ
cana-2055	65	28	elastic	elastic	ADJ
cana-2055	65	29	net	net	NOUN
cana-2055	65	30	(	(	PUNCT
cana-2055	65	31	en	en	X
cana-2055	65	32	)	)	PUNCT
cana-2055	65	33	ml	ml	NOUN
cana-2055	65	34	models	model	NOUN
cana-2055	65	35	were	be	AUX
cana-2055	65	36	trained	train	VERB
cana-2055	65	37	on	on	ADP
cana-2055	65	38	the	the	DET
cana-2055	65	39	given	give	VERB
cana-2055	65	40	data	datum	NOUN
cana-2055	65	41	.	.	PUNCT
cana-2055	66	1	the	the	DET
cana-2055	66	2	svr	svr	PROPN
cana-2055	66	3	outperformed	outperform	VERB
cana-2055	66	4	other	other	ADJ
cana-2055	66	5	techniques	technique	NOUN
cana-2055	66	6	on	on	ADP
cana-2055	66	7	all	all	DET
cana-2055	66	8	four	four	NUM
cana-2055	66	9	datasets	dataset	NOUN
cana-2055	66	10	with	with	ADP
cana-2055	66	11	reduced	reduced	ADJ
cana-2055	66	12	rmse	rmse	NOUN
cana-2055	66	13	.	.	PUNCT
cana-2055	67	1	multiple	multiple	ADJ
cana-2055	67	2	cyp	cyp	ADJ
cana-2055	67	3	machine	machine	NOUN
cana-2055	67	4	-	-	PUNCT
cana-2055	67	5	learning	learn	VERB
cana-2055	67	6	models	model	NOUN
cana-2055	67	7	were	be	AUX
cana-2055	67	8	given	give	VERB
cana-2055	67	9	.	.	PUNCT
cana-2055	68	1	initial	initial	ADJ
cana-2055	68	2	irish	irish	ADJ
cana-2055	68	3	potatoes	potato	NOUN
cana-2055	68	4	and	and	CCONJ
cana-2055	68	5	maize	maize	NOUN
cana-2055	68	6	data	datum	NOUN
cana-2055	68	7	set	set	VERB
cana-2055	68	8	were	be	AUX
cana-2055	68	9	obtained	obtain	VERB
cana-2055	68	10	,	,	PUNCT
cana-2055	68	11	followed	follow	VERB
cana-2055	68	12	by	by	ADP
cana-2055	68	13	pre	pre	ADJ
cana-2055	68	14	-	-	ADJ
cana-2055	68	15	processing	processing	ADJ
cana-2055	68	16	activities	activity	NOUN
cana-2055	68	17	such	such	ADJ
cana-2055	68	18	as	as	ADP
cana-2055	68	19	null	null	ADJ
cana-2055	68	20	value	value	NOUN
cana-2055	68	21	removal	removal	NOUN
cana-2055	68	22	and	and	CCONJ
cana-2055	68	23	correlation	correlation	NOUN
cana-2055	68	24	determination	determination	NOUN
cana-2055	68	25	to	to	PART
cana-2055	68	26	improve	improve	VERB
cana-2055	68	27	system	system	NOUN
cana-2055	68	28	performance	performance	NOUN
cana-2055	68	29	.	.	PUNCT
cana-2055	69	1	cyp	cyp	ADJ
cana-2055	69	2	classification	classification	NOUN
cana-2055	69	3	was	be	AUX
cana-2055	69	4	then	then	ADV
cana-2055	69	5	done	do	VERB
cana-2055	69	6	utilising	utilise	VERB
cana-2055	69	7	three	three	NUM
cana-2055	69	8	ml	ml	NOUN
cana-2055	69	9	models	model	NOUN
cana-2055	69	10	:	:	PUNCT
cana-2055	69	11	polynomial	polynomial	ADJ
cana-2055	69	12	regression	regression	NOUN
cana-2055	69	13	(	(	PUNCT
cana-2055	69	14	pr	pr	NOUN
cana-2055	69	15	)	)	PUNCT
cana-2055	69	16	,	,	PUNCT
cana-2055	69	17	support	support	NOUN
cana-2055	69	18	vector	vector	NOUN
cana-2055	69	19	machine	machine	NOUN
cana-2055	69	20	(	(	PUNCT
cana-2055	69	21	svm	svm	PROPN
cana-2055	69	22	)	)	PUNCT
cana-2055	69	23	,	,	PUNCT
cana-2055	69	24	and	and	CCONJ
cana-2055	69	25	a	a	DET
cana-2055	69	26	random	random	ADJ
cana-2055	69	27	forest	forest	NOUN
cana-2055	69	28	(	(	PUNCT
cana-2055	69	29	rf	rf	NOUN
cana-2055	69	30	)	)	PUNCT
cana-2055	69	31	.	.	PUNCT
cana-2055	70	1	results	result	NOUN
cana-2055	70	2	indicate	indicate	VERB
cana-2055	70	3	that	that	SCONJ
cana-2055	70	4	the	the	DET
cana-2055	70	5	rf	rf	NOUN
cana-2055	70	6	model	model	NOUN
cana-2055	70	7	outperformed	outperform	VERB
cana-2055	70	8	svm	svm	PROPN
cana-2055	70	9	and	and	CCONJ
cana-2055	70	10	pr	pr	NOUN
cana-2055	70	11	in	in	ADP
cana-2055	70	12	forecasting	forecast	VERB
cana-2055	70	13	potato	potato	NOUN
cana-2055	70	14	and	and	CCONJ
cana-2055	70	15	maize	maize	NOUN
cana-2055	70	16	crop	crop	NOUN
cana-2055	70	17	yields	yield	NOUN
cana-2055	70	18	,	,	PUNCT
cana-2055	70	19	with	with	ADP
cana-2055	70	20	rmses	rmse	NOUN
cana-2055	70	21	of	of	ADP
cana-2055	70	22	510.9	510.9	NUM
cana-2055	70	23	as	as	ADV
cana-2055	70	24	well	well	ADV
cana-2055	70	25	as	as	ADP
cana-2055	70	26	129.8	129.8	NUM
cana-2055	70	27	on	on	ADP
cana-2055	70	28	tested	test	VERB
cana-2055	70	29	datasets	dataset	NOUN
cana-2055	70	30	.	.	PUNCT
cana-2055	71	1	the	the	DET
cana-2055	71	2	use	use	NOUN
cana-2055	71	3	of	of	ADP
cana-2055	71	4	cyp	cyp	ADJ
cana-2055	71	5	is	be	AUX
cana-2055	71	6	best	well	ADV
cana-2055	71	7	accomplished	accomplish	VERB
cana-2055	71	8	using	use	VERB
cana-2055	71	9	a	a	DET
cana-2055	71	10	combination	combination	NOUN
cana-2055	71	11	of	of	ADP
cana-2055	71	12	dl	dl	PROPN
cana-2055	71	13	methods	method	NOUN
cana-2055	71	14	,	,	PUNCT
cana-2055	71	15	including	include	VERB
cana-2055	71	16	temporal	temporal	ADJ
cana-2055	71	17	convolutional	convolutional	ADJ
cana-2055	71	18	networks	network	NOUN
cana-2055	71	19	&	&	CCONJ
cana-2055	71	20	recurrent	recurrent	ADJ
cana-2055	71	21	neural	neural	ADJ
cana-2055	71	22	networks	network	NOUN
cana-2055	71	23	.	.	PUNCT
cana-2055	72	1	the	the	DET
cana-2055	72	2	data	datum	NOUN
cana-2055	72	3	was	be	AUX
cana-2055	72	4	gathered	gather	VERB
cana-2055	72	5	from	from	ADP
cana-2055	72	6	many	many	ADJ
cana-2055	72	7	actual	actual	ADJ
cana-2055	72	8	tomatogrowing	tomatogrowe	VERB
cana-2055	72	9	greenhouses	greenhouse	NOUN
cana-2055	72	10	.	.	PUNCT
cana-2055	73	1	we	we	PRON
cana-2055	73	2	normalised	normalise	VERB
cana-2055	73	3	the	the	DET
cana-2055	73	4	acquired	acquire	VERB
cana-2055	73	5	data	datum	NOUN
cana-2055	73	6	first	first	ADV
cana-2055	73	7	,	,	PUNCT
cana-2055	73	8	and	and	CCONJ
cana-2055	73	9	then	then	ADV
cana-2055	73	10	we	we	PRON
cana-2055	73	11	sent	send	VERB
cana-2055	73	12	it	it	PRON
cana-2055	73	13	to	to	ADP
cana-2055	73	14	the	the	DET
cana-2055	73	15	rnn	rnn	NOUN
cana-2055	73	16	so	so	SCONJ
cana-2055	73	17	it	it	PRON
cana-2055	73	18	could	could	AUX
cana-2055	73	19	analyse	analyse	VERB
cana-2055	73	20	the	the	DET
cana-2055	73	21	normalised	normalise	VERB
cana-2055	73	22	sequence	sequence	NOUN
cana-2055	73	23	data	datum	NOUN
cana-2055	73	24	.	.	PUNCT
cana-2055	74	1	at	at	ADP
cana-2055	74	2	last	last	ADJ
cana-2055	74	3	,	,	PUNCT
cana-2055	74	4	the	the	DET
cana-2055	74	5	tcn	tcn	NOUN
cana-2055	74	6	for	for	ADP
cana-2055	74	7	tomatoes	tomato	NOUN
cana-2055	74	8	cyp	cyp	NOUN
cana-2055	74	9	received	receive	VERB
cana-2055	74	10	the	the	DET
cana-2055	74	11	rnn	rnn	NOUN
cana-2055	74	12	's	's	PART
cana-2055	74	13	output	output	NOUN
cana-2055	74	14	.	.	PUNCT
cana-2055	75	1	with	with	ADP
cana-2055	75	2	a	a	DET
cana-2055	75	3	decreased	decrease	VERB
cana-2055	75	4	rmse	rmse	NOUN
cana-2055	75	5	,	,	PUNCT
cana-2055	75	6	the	the	DET
cana-2055	75	7	strategy	strategy	NOUN
cana-2055	75	8	outperformed	outperform	VERB
cana-2055	75	9	analogous	analogous	ADJ
cana-2055	75	10	methods	method	NOUN
cana-2055	75	11	that	that	PRON
cana-2055	75	12	were	be	AUX
cana-2055	75	13	previously	previously	ADV
cana-2055	75	14	used	use	VERB
cana-2055	75	15	on	on	ADP
cana-2055	75	16	the	the	DET
cana-2055	75	17	datasets	dataset	NOUN
cana-2055	75	18	that	that	PRON
cana-2055	75	19	were	be	AUX
cana-2055	75	20	gathered	gather	VERB
cana-2055	75	21	.	.	PUNCT
cana-2055	76	1	they	they	PRON
cana-2055	76	2	introduced	introduce	VERB
cana-2055	76	3	a	a	DET
cana-2055	76	4	hybrid	hybrid	ADJ
cana-2055	76	5	method	method	NOUN
cana-2055	76	6	for	for	ADP
cana-2055	76	7	cyp	cyp	ADJ
cana-2055	76	8	with	with	ADP
cana-2055	76	9	agricultural	agricultural	ADJ
cana-2055	76	10	parameters	parameter	NOUN
cana-2055	76	11	,	,	PUNCT
cana-2055	76	12	which	which	PRON
cana-2055	76	13	they	they	PRON
cana-2055	76	14	called	call	VERB
cana-2055	76	15	reinforced	reinforced	ADJ
cana-2055	76	16	rf	rf	NOUN
cana-2055	76	17	.	.	PUNCT
cana-2055	77	1	at	at	ADP
cana-2055	77	2	first	first	ADV
cana-2055	77	3	,	,	PUNCT
cana-2055	77	4	the	the	DET
cana-2055	77	5	system	system	NOUN
cana-2055	77	6	retrieved	retrieve	VERB
cana-2055	77	7	information	information	NOUN
cana-2055	77	8	about	about	ADP
cana-2055	77	9	crops	crop	NOUN
cana-2055	77	10	from	from	ADP
cana-2055	77	11	the	the	DET
cana-2055	77	12	agricultural	agricultural	ADJ
cana-2055	77	13	dataset	dataset	NOUN
cana-2055	77	14	and	and	CCONJ
cana-2055	77	15	then	then	ADV
cana-2055	77	16	sent	send	VERB
cana-2055	77	17	it	it	PRON
cana-2055	77	18	to	to	ADP
cana-2055	77	19	the	the	DET
cana-2055	77	20	reinforced	reinforce	VERB
cana-2055	77	21	rf	rf	PRON
cana-2055	77	22	hybrid	hybrid	ADJ
cana-2055	77	23	dl	dl	PROPN
cana-2055	77	24	model	model	NOUN
cana-2055	77	25	.	.	PUNCT
cana-2055	78	1	for	for	ADP
cana-2055	78	2	each	each	DET
cana-2055	78	3	internal	internal	ADJ
cana-2055	78	4	node	node	NOUN
cana-2055	78	5	,	,	PUNCT
cana-2055	78	6	the	the	DET
cana-2055	78	7	reinforced	reinforce	VERB
cana-2055	78	8	rf	rf	NOUN
cana-2055	78	9	employed	employ	VERB
cana-2055	78	10	the	the	DET
cana-2055	78	11	reinforcement	reinforcement	NOUN
cana-2055	78	12	learning	learning	NOUN
cana-2055	78	13	technique	technique	NOUN
cana-2055	78	14	to	to	PART
cana-2055	78	15	assess	assess	VERB
cana-2055	78	16	the	the	DET
cana-2055	78	17	input	input	NOUN
cana-2055	78	18	data	datum	NOUN
cana-2055	78	19	's	's	PART
cana-2055	78	20	relevance	relevance	NOUN
cana-2055	78	21	.	.	PUNCT
cana-2055	79	1	after	after	ADP
cana-2055	79	2	that	that	PRON
cana-2055	79	3	,	,	PUNCT
cana-2055	79	4	the	the	DET
cana-2055	79	5	rf	rf	ADJ
cana-2055	79	6	classified	classified	ADJ
cana-2055	79	7	crop	crop	NOUN
cana-2055	79	8	production	production	NOUN
cana-2055	79	9	using	use	VERB
cana-2055	79	10	the	the	DET
cana-2055	79	11	most	most	ADV
cana-2055	79	12	important	important	ADJ
cana-2055	79	13	variables	variable	NOUN
cana-2055	79	14	found	find	VERB
cana-2055	79	15	by	by	ADP
cana-2055	79	16	the	the	DET
cana-2055	79	17	reinforcement	reinforcement	NOUN
cana-2055	79	18	model	model	NOUN
cana-2055	79	19	.	.	PUNCT
cana-2055	80	1	results	result	NOUN
cana-2055	80	2	were	be	AUX
cana-2055	80	3	better	well	ADJ
cana-2055	80	4	with	with	ADP
cana-2055	80	5	the	the	DET
cana-2055	80	6	hybrid	hybrid	NOUN
cana-2055	80	7	technique	technique	NOUN
cana-2055	80	8	compared	compare	VERB
cana-2055	80	9	to	to	ADP
cana-2055	80	10	the	the	DET
cana-2055	80	11	current	current	ADJ
cana-2055	80	12	machine	machine	NOUN
cana-2055	80	13	learning	learning	NOUN
cana-2055	80	14	models	model	NOUN
cana-2055	80	15	for	for	ADP
cana-2055	80	16	cyp	cyp	ADJ
cana-2055	80	17	,	,	PUNCT
cana-2055	80	18	including	include	VERB
cana-2055	80	19	svm	svm	PROPN
cana-2055	80	20	,	,	PUNCT
cana-2055	80	21	lr	lr	NOUN
cana-2055	80	22	,	,	PUNCT
cana-2055	80	23	&	&	CCONJ
cana-2055	80	24	knn	knn	PROPN
cana-2055	80	25	.	.	PUNCT
cana-2055	81	1	they	they	PRON
cana-2055	81	2	proposed	propose	VERB
cana-2055	81	3	a	a	DET
cana-2055	81	4	best	well	ADV
cana-2055	81	5	cyp	cyp	ADJ
cana-2055	81	6	deep	deep	ADJ
cana-2055	81	7	-	-	PUNCT
cana-2055	81	8	learning	learn	VERB
cana-2055	81	9	model	model	NOUN
cana-2055	81	10	.	.	PUNCT
cana-2055	82	1	the	the	DET
cana-2055	82	2	pre	pre	ADJ
cana-2055	82	3	-	-	ADJ
cana-2055	82	4	processed	processed	ADJ
cana-2055	82	5	data	datum	NOUN
cana-2055	82	6	were	be	AUX
cana-2055	82	7	used	use	VERB
cana-2055	82	8	to	to	PART
cana-2055	82	9	extract	extract	VERB
cana-2055	82	10	important	important	ADJ
cana-2055	82	11	characteristics	characteristic	NOUN
cana-2055	82	12	utilising	utilise	VERB
cana-2055	82	13	principal	principal	ADJ
cana-2055	82	14	component	component	NOUN
cana-2055	82	15	analysis	analysis	NOUN
cana-2055	82	16	.	.	PUNCT
cana-2055	83	1	the	the	DET
cana-2055	83	2	chosen	choose	VERB
cana-2055	83	3	characteristics	characteristic	NOUN
cana-2055	83	4	were	be	AUX
cana-2055	83	5	optimised	optimise	VERB
cana-2055	83	6	utilising	utilise	VERB
cana-2055	83	7	an	an	DET
cana-2055	83	8	updated	update	VERB
cana-2055	83	9	chicken	chicken	NOUN
cana-2055	83	10	swarm	swarm	NOUN
cana-2055	83	11	technique	technique	NOUN
cana-2055	83	12	to	to	PART
cana-2055	83	13	increase	increase	VERB
cana-2055	83	14	classifier	classifier	ADJ
cana-2055	83	15	performance	performance	NOUN
cana-2055	83	16	.	.	PUNCT
cana-2055	84	1	final	final	ADJ
cana-2055	84	2	classifier	classifier	NOUN
cana-2055	84	3	is	be	AUX
cana-2055	84	4	using	use	VERB
cana-2055	84	5	a	a	DET
cana-2055	84	6	discrete	discrete	ADJ
cana-2055	84	7	dbn	dbn	PROPN
cana-2055	84	8	-	-	PUNCT
cana-2055	84	9	vgg	vgg	NOUN
cana-2055	84	10	net	net	ADJ
cana-2055	84	11	classifier	classifier	NOUN
cana-2055	84	12	.	.	PUNCT
cana-2055	85	1	the	the	DET
cana-2055	85	2	method	method	NOUN
cana-2055	85	3	outperformed	outperform	VERB
cana-2055	85	4	state	state	NOUN
cana-2055	85	5	-	-	PUNCT
cana-2055	85	6	of	of	ADP
cana-2055	85	7	-	-	PUNCT
cana-2055	85	8	the	the	DET
cana-2055	85	9	-	-	PUNCT
cana-2055	85	10	art	art	NOUN
cana-2055	85	11	models	model	NOUN
cana-2055	85	12	with	with	ADP
cana-2055	85	13	98	98	NUM
cana-2055	85	14	%	%	NOUN
cana-2055	85	15	accuracy	accuracy	NOUN
cana-2055	85	16	and	and	CCONJ
cana-2055	85	17	0.02	0.02	NUM
cana-2055	85	18	%	%	NOUN
cana-2055	85	19	mse	mse	NOUN
cana-2055	85	20	.	.	PUNCT
cana-2055	86	1	their	their	PRON
cana-2055	86	2	large	large	ADJ
cana-2055	86	3	-	-	PUNCT
cana-2055	86	4	scale	scale	NOUN
cana-2055	86	5	cyp	cyp	ADJ
cana-2055	86	6	machine	machine	NOUN
cana-2055	86	7	-	-	PUNCT
cana-2055	86	8	learning	learn	VERB
cana-2055	86	9	models	model	NOUN
cana-2055	86	10	were	be	AUX
cana-2055	86	11	shown	show	VERB
cana-2055	86	12	.	.	PUNCT
cana-2055	87	1	the	the	DET
cana-2055	87	2	system	system	NOUN
cana-2055	87	3	first	first	ADV
cana-2055	87	4	gathered	gather	VERB
cana-2055	87	5	agricultural	agricultural	ADJ
cana-2055	87	6	yield	yield	NOUN
cana-2055	87	7	data	datum	NOUN
cana-2055	87	8	from	from	ADP
cana-2055	87	9	several	several	ADJ
cana-2055	87	10	sources	source	NOUN
cana-2055	87	11	,	,	PUNCT
cana-2055	87	12	including	include	VERB
cana-2055	87	13	crop	crop	NOUN
cana-2055	87	14	growth	growth	NOUN
cana-2055	87	15	simulations	simulation	NOUN
cana-2055	87	16	,	,	PUNCT
cana-2055	87	17	weather	weather	NOUN
cana-2055	87	18	measurements	measurement	NOUN
cana-2055	87	19	,	,	PUNCT
cana-2055	87	20	and	and	CCONJ
cana-2055	87	21	yield	yield	VERB
cana-2055	87	22	statistics	statistic	NOUN
cana-2055	87	23	.	.	PUNCT
cana-2055	88	1	the	the	DET
cana-2055	88	2	information	information	NOUN
cana-2055	88	3	was	be	AUX
cana-2055	88	4	cleaned	clean	VERB
cana-2055	88	5	for	for	ADP
cana-2055	88	6	categorisation	categorisation	NOUN
cana-2055	88	7	.	.	PUNCT
cana-2055	89	1	after	after	ADP
cana-2055	89	2	feature	feature	NOUN
cana-2055	89	3	design	design	NOUN
cana-2055	89	4	,	,	PUNCT
cana-2055	89	5	some	some	DET
cana-2055	89	6	input	input	NOUN
cana-2055	89	7	data	datum	NOUN
cana-2055	89	8	was	be	AUX
cana-2055	89	9	given	give	VERB
cana-2055	89	10	into	into	ADP
cana-2055	89	11	the	the	DET
cana-2055	89	12	classifier	classifier	NOUN
cana-2055	89	13	.	.	PUNCT
cana-2055	90	1	ml	ml	PROPN
cana-2055	90	2	classifiers	classifier	NOUN
cana-2055	90	3	including	include	VERB
cana-2055	90	4	knn	knn	PROPN
cana-2055	90	5	,	,	PUNCT
cana-2055	90	6	svm	svm	PROPN
cana-2055	90	7	,	,	PUNCT
cana-2055	90	8	regression	regression	NOUN
cana-2055	90	9	with	with	ADP
cana-2055	90	10	ridges	ridge	NOUN
cana-2055	90	11	,	,	PUNCT
cana-2055	90	12	as	as	ADV
cana-2055	90	13	well	well	ADV
cana-2055	90	14	as	as	ADP
cana-2055	90	15	decision	decision	NOUN
cana-2055	90	16	trees	tree	NOUN
cana-2055	90	17	with	with	ADP
cana-2055	90	18	gradient	gradient	ADJ
cana-2055	90	19	boost	boost	NOUN
cana-2055	90	20	were	be	AUX
cana-2055	90	21	used	use	VERB
cana-2055	90	22	for	for	ADP
cana-2055	90	23	cyp	cyp	ADJ
cana-2055	90	24	.	.	PUNCT
cana-2055	91	1	a	a	DET
cana-2055	91	2	weighted	weight	VERB
cana-2055	91	3	combined	combine	VERB
cana-2055	91	4	linear	linear	NOUN
cana-2055	91	5	model	model	NOUN
cana-2055	91	6	was	be	AUX
cana-2055	91	7	proposed	propose	VERB
cana-2055	91	8	to	to	PART
cana-2055	91	9	investigate	investigate	VERB
cana-2055	91	10	the	the	DET
cana-2055	91	11	potential	potential	NOUN
cana-2055	91	12	for	for	ADP
cana-2055	91	13	saffron	saffron	NOUN
cana-2055	91	14	farming	farming	NOUN
cana-2055	91	15	in	in	ADP
cana-2055	91	16	india	india	PROPN
cana-2055	91	17	using	use	VERB
cana-2055	91	18	remote	remote	ADJ
cana-2055	91	19	sensing	sensing	NOUN
cana-2055	91	20	&	&	CCONJ
cana-2055	91	21	geospatial	geospatial	ADJ
cana-2055	91	22	analytic	analytic	ADJ
cana-2055	91	23	communications	communication	NOUN
cana-2055	91	24	on	on	ADP
cana-2055	91	25	applied	apply	VERB
cana-2055	91	26	nonlinear	nonlinear	ADJ
cana-2055	91	27	analysis	analysis	NOUN
cana-2055	91	28	issn	issn	NOUN
cana-2055	91	29	:	:	PUNCT
cana-2055	91	30	1074	1074	NUM
cana-2055	91	31	-	-	PUNCT
cana-2055	91	32	133x	133x	NUM
cana-2055	91	33	vol	vol	NOUN
cana-2055	91	34	32	32	NUM
cana-2055	91	35	no	no	NOUN
cana-2055	91	36	.	.	NOUN
cana-2055	91	37	3	3	NUM
cana-2055	91	38	(	(	PUNCT
cana-2055	91	39	2025	2025	NUM
cana-2055	91	40	)	)	PUNCT
cana-2055	91	41	580	580	NUM
cana-2055	91	42	https://internationalpubls.com	https://internationalpubls.com	X
cana-2055	91	43	approaches	approach	NOUN
cana-2055	91	44	.	.	PUNCT
cana-2055	92	1	though	though	SCONJ
cana-2055	92	2	straightforward	straightforward	ADJ
cana-2055	92	3	,	,	PUNCT
cana-2055	92	4	the	the	DET
cana-2055	92	5	approach	approach	NOUN
cana-2055	92	6	misses	miss	VERB
cana-2055	92	7	intricate	intricate	ADJ
cana-2055	92	8	nonlinear	nonlinear	ADJ
cana-2055	92	9	interactions	interaction	NOUN
cana-2055	92	10	between	between	ADP
cana-2055	92	11	the	the	DET
cana-2055	92	12	factors	factor	NOUN
cana-2055	92	13	affecting	affect	VERB
cana-2055	92	14	appropriateness	appropriateness	NOUN
cana-2055	92	15	.	.	PUNCT
cana-2055	93	1	utilising	utilise	VERB
cana-2055	93	2	sar	sar	PROPN
cana-2055	93	3	information	information	PROPN
cana-2055	93	4	,	,	PUNCT
cana-2055	93	5	the	the	DET
cana-2055	93	6	height	height	NOUN
cana-2055	93	7	and	and	CCONJ
cana-2055	93	8	biomass	biomass	NOUN
cana-2055	93	9	of	of	ADP
cana-2055	93	10	india	india	PROPN
cana-2055	93	11	's	's	PART
cana-2055	93	12	rice	rice	NOUN
cana-2055	93	13	fields	field	NOUN
cana-2055	93	14	are	be	AUX
cana-2055	93	15	estimated	estimate	VERB
cana-2055	93	16	.	.	PUNCT
cana-2055	94	1	relevance	relevance	NOUN
cana-2055	94	2	vector	vector	NOUN
cana-2055	94	3	regression	regression	NOUN
cana-2055	94	4	(	(	PUNCT
cana-2055	94	5	rvr	rvr	NOUN
cana-2055	94	6	)	)	PUNCT
cana-2055	94	7	,	,	PUNCT
cana-2055	94	8	multiple	multiple	ADJ
cana-2055	94	9	linear	linear	ADJ
cana-2055	94	10	regression	regression	NOUN
cana-2055	94	11	,	,	PUNCT
cana-2055	94	12	(	(	PUNCT
cana-2055	94	13	mlr	mlr	NOUN
cana-2055	94	14	)	)	PUNCT
cana-2055	94	15	,	,	PUNCT
cana-2055	94	16	support	support	VERB
cana-2055	94	17	vector	vector	NOUN
cana-2055	94	18	regression	regression	NOUN
cana-2055	94	19	(	(	PUNCT
cana-2055	94	20	svr	svr	PROPN
cana-2055	94	21	)	)	PUNCT
cana-2055	94	22	,	,	PUNCT
cana-2055	94	23	and	and	CCONJ
cana-2055	94	24	other	other	ADJ
cana-2055	94	25	machine	machine	NOUN
cana-2055	94	26	learning	learning	NOUN
cana-2055	94	27	methods	method	NOUN
cana-2055	94	28	were	be	AUX
cana-2055	94	29	used	use	VERB
cana-2055	94	30	;	;	PUNCT
cana-2055	94	31	rvr	rvr	NOUN
cana-2055	94	32	produced	produce	VERB
cana-2055	94	33	the	the	DET
cana-2055	94	34	best	good	ADJ
cana-2055	94	35	results	result	NOUN
cana-2055	94	36	.	.	PUNCT
cana-2055	95	1	creates	create	VERB
cana-2055	95	2	and	and	CCONJ
cana-2055	95	3	assesses	assess	VERB
cana-2055	95	4	a	a	DET
cana-2055	95	5	particular	particular	ADJ
cana-2055	95	6	imageand	imageand	NOUN
cana-2055	95	7	classifier	classifier	NOUN
cana-2055	95	8	-	-	PUNCT
cana-2055	95	9	based	base	VERB
cana-2055	95	10	flood	flood	NOUN
cana-2055	95	11	detection	detection	NOUN
cana-2055	95	12	technique	technique	NOUN
cana-2055	95	13	.	.	PUNCT
cana-2055	96	1	ground	ground	NOUN
cana-2055	96	2	truth	truth	NOUN
cana-2055	96	3	data	datum	NOUN
cana-2055	96	4	,	,	PUNCT
cana-2055	96	5	such	such	ADJ
cana-2055	96	6	as	as	ADP
cana-2055	96	7	that	that	PRON
cana-2055	96	8	gathered	gather	VERB
cana-2055	96	9	from	from	ADP
cana-2055	96	10	high	high	ADJ
cana-2055	96	11	-	-	PUNCT
cana-2055	96	12	resolution	resolution	NOUN
cana-2055	96	13	optical	optical	ADJ
cana-2055	96	14	images	image	NOUN
cana-2055	96	15	or	or	CCONJ
cana-2055	96	16	ground	ground	NOUN
cana-2055	96	17	sensors	sensor	NOUN
cana-2055	96	18	,	,	PUNCT
cana-2055	96	19	is	be	AUX
cana-2055	96	20	used	use	VERB
cana-2055	96	21	to	to	PART
cana-2055	96	22	verify	verify	VERB
cana-2055	96	23	the	the	DET
cana-2055	96	24	precision	precision	NOUN
cana-2055	96	25	of	of	ADP
cana-2055	96	26	the	the	DET
cana-2055	96	27	flood	flood	NOUN
cana-2055	96	28	detection	detection	NOUN
cana-2055	96	29	system	system	NOUN
cana-2055	96	30	.	.	PUNCT
cana-2055	97	1	the	the	DET
cana-2055	97	2	suggested	suggest	VERB
cana-2055	97	3	strategy	strategy	NOUN
cana-2055	97	4	for	for	ADP
cana-2055	97	5	fast	fast	ADJ
cana-2055	97	6	adcs	adcs	ADJ
cana-2055	97	7	performance	performance	NOUN
cana-2055	97	8	sizing	sizing	NOUN
cana-2055	97	9	in	in	ADP
cana-2055	97	10	eo	eo	NOUN
cana-2055	97	11	-	-	NOUN
cana-2055	97	12	satellites	satellite	NOUN
cana-2055	97	13	uses	use	VERB
cana-2055	97	14	matching	match	VERB
cana-2055	97	15	diagrams	diagram	NOUN
cana-2055	97	16	to	to	PART
cana-2055	97	17	cut	cut	VERB
cana-2055	97	18	down	down	ADP
cana-2055	97	19	on	on	ADP
cana-2055	97	20	time	time	NOUN
cana-2055	97	21	and	and	CCONJ
cana-2055	97	22	effort	effort	NOUN
cana-2055	97	23	while	while	SCONJ
cana-2055	97	24	maintaining	maintain	VERB
cana-2055	97	25	an	an	DET
cana-2055	97	26	adequate	adequate	ADJ
cana-2055	97	27	degree	degree	NOUN
cana-2055	97	28	of	of	ADP
cana-2055	97	29	accuracy	accuracy	NOUN
cana-2055	97	30	.	.	PUNCT
cana-2055	98	1	to	to	PART
cana-2055	98	2	facilitate	facilitate	VERB
cana-2055	98	3	estimate	estimate	NOUN
cana-2055	98	4	,	,	PUNCT
cana-2055	98	5	a	a	DET
cana-2055	98	6	method	method	NOUN
cana-2055	98	7	was	be	AUX
cana-2055	98	8	suggested	suggest	VERB
cana-2055	98	9	for	for	ADP
cana-2055	98	10	optimally	optimally	ADV
cana-2055	98	11	extracting	extract	VERB
cana-2055	98	12	features	feature	NOUN
cana-2055	98	13	from	from	ADP
cana-2055	98	14	polsar	polsar	PROPN
cana-2055	98	15	pictures	picture	NOUN
cana-2055	98	16	.	.	PUNCT
cana-2055	99	1	to	to	PART
cana-2055	99	2	enhance	enhance	VERB
cana-2055	99	3	the	the	DET
cana-2055	99	4	outcomes	outcome	NOUN
cana-2055	99	5	with	with	ADP
cana-2055	99	6	the	the	DET
cana-2055	99	7	addition	addition	NOUN
cana-2055	99	8	of	of	ADP
cana-2055	99	9	polarimetric	polarimetric	ADJ
cana-2055	99	10	channels	channel	NOUN
cana-2055	99	11	,	,	PUNCT
cana-2055	99	12	a	a	DET
cana-2055	99	13	method	method	NOUN
cana-2055	99	14	based	base	VERB
cana-2055	99	15	on	on	ADP
cana-2055	99	16	the	the	DET
cana-2055	99	17	rapid	rapid	ADJ
cana-2055	99	18	independent	independent	ADJ
cana-2055	99	19	component	component	NOUN
cana-2055	99	20	analysis	analysis	NOUN
cana-2055	99	21	(	(	PUNCT
cana-2055	99	22	rapid	rapid	ADJ
cana-2055	99	23	ica	ica	PROPN
cana-2055	99	24	)	)	PUNCT
cana-2055	99	25	technique	technique	NOUN
cana-2055	99	26	is	be	AUX
cana-2055	99	27	suggested	suggest	VERB
cana-2055	99	28	.	.	PUNCT
cana-2055	100	1	they	they	PRON
cana-2055	100	2	suggested	suggest	VERB
cana-2055	100	3	a	a	DET
cana-2055	100	4	multiple	multiple	ADJ
cana-2055	100	5	scale	scale	NOUN
cana-2055	100	6	doublebranch	doublebranch	VERB
cana-2055	100	7	residual	residual	ADJ
cana-2055	100	8	spectrum	spectrum	NOUN
cana-2055	100	9	-	-	PUNCT
cana-2055	100	10	spatial	spatial	ADJ
cana-2055	100	11	net	net	NOUN
cana-2055	100	12	that	that	PRON
cana-2055	100	13	prioritises	prioritise	VERB
cana-2055	100	14	the	the	DET
cana-2055	100	15	hyper	hyper	ADJ
cana-2055	100	16	spectral	spectral	ADJ
cana-2055	100	17	photos	photo	NOUN
cana-2055	100	18	classification	classification	NOUN
cana-2055	100	19	model	model	NOUN
cana-2055	100	20	to	to	PART
cana-2055	100	21	enhance	enhance	VERB
cana-2055	100	22	accuracy	accuracy	NOUN
cana-2055	100	23	in	in	ADP
cana-2055	100	24	situations	situation	NOUN
cana-2055	100	25	when	when	SCONJ
cana-2055	100	26	the	the	DET
cana-2055	100	27	amount	amount	NOUN
cana-2055	100	28	of	of	ADP
cana-2055	100	29	training	training	NOUN
cana-2055	100	30	data	datum	NOUN
cana-2055	100	31	is	be	AUX
cana-2055	100	32	limited	limited	ADJ
cana-2055	100	33	.	.	PUNCT
cana-2055	101	1	the	the	DET
cana-2055	101	2	study	study	NOUN
cana-2055	101	3	conducted	conduct	VERB
cana-2055	101	4	in	in	ADP
cana-2055	101	5	india	india	PROPN
cana-2055	101	6	identified	identify	VERB
cana-2055	101	7	soil	soil	NOUN
cana-2055	101	8	types	type	NOUN
cana-2055	101	9	and	and	CCONJ
cana-2055	101	10	locations	location	NOUN
cana-2055	101	11	that	that	PRON
cana-2055	101	12	are	be	AUX
cana-2055	101	13	conducive	conducive	ADJ
cana-2055	101	14	to	to	PART
cana-2055	101	15	saffron	saffron	VERB
cana-2055	101	16	cultivation	cultivation	NOUN
cana-2055	101	17	by	by	ADP
cana-2055	101	18	utilising	utilise	VERB
cana-2055	101	19	the	the	DET
cana-2055	101	20	weighted	weight	VERB
cana-2055	101	21	linear	linear	PROPN
cana-2055	101	22	composition	composition	NOUN
cana-2055	101	23	technique	technique	NOUN
cana-2055	101	24	and	and	CCONJ
cana-2055	101	25	remote	remote	ADJ
cana-2055	101	26	sensing	sense	VERB
cana-2055	101	27	information	information	NOUN
cana-2055	101	28	.	.	PUNCT
cana-2055	102	1	using	use	VERB
cana-2055	102	2	classic	classic	ADJ
cana-2055	102	3	machinelearning	machinelearning	NOUN
cana-2055	102	4	methods	method	NOUN
cana-2055	102	5	for	for	ADP
cana-2055	102	6	cyp	cyp	ADJ
cana-2055	102	7	has	have	AUX
cana-2055	102	8	been	be	AUX
cana-2055	102	9	the	the	DET
cana-2055	102	10	focus	focus	NOUN
cana-2055	102	11	of	of	ADP
cana-2055	102	12	earlier	early	ADJ
cana-2055	102	13	studies	study	NOUN
cana-2055	102	14	.	.	PUNCT
cana-2055	103	1	in	in	ADP
cana-2055	103	2	order	order	NOUN
cana-2055	103	3	to	to	PART
cana-2055	103	4	predict	predict	VERB
cana-2055	103	5	agricultural	agricultural	ADJ
cana-2055	103	6	output	output	NOUN
cana-2055	103	7	according	accord	VERB
cana-2055	103	8	to	to	ADP
cana-2055	103	9	predetermined	predetermined	ADJ
cana-2055	103	10	parameters	parameter	NOUN
cana-2055	103	11	,	,	PUNCT
cana-2055	103	12	traditional	traditional	ADJ
cana-2055	103	13	ml	ml	NOUN
cana-2055	103	14	models	model	NOUN
cana-2055	103	15	are	be	AUX
cana-2055	103	16	trained	train	VERB
cana-2055	103	17	using	use	VERB
cana-2055	103	18	limited	limited	ADJ
cana-2055	103	19	amounts	amount	NOUN
cana-2055	103	20	of	of	ADP
cana-2055	103	21	data	datum	NOUN
cana-2055	103	22	.	.	PUNCT
cana-2055	104	1	but	but	CCONJ
cana-2055	104	2	it	it	PRON
cana-2055	104	3	's	be	AUX
cana-2055	104	4	not	not	PART
cana-2055	104	5	without	without	ADP
cana-2055	104	6	its	its	PRON
cana-2055	104	7	flaws	flaw	NOUN
cana-2055	104	8	.	.	PUNCT
cana-2055	105	1	for	for	ADP
cana-2055	105	2	instance	instance	NOUN
cana-2055	105	3	,	,	PUNCT
cana-2055	105	4	conventional	conventional	ADJ
cana-2055	105	5	ml	ml	NOUN
cana-2055	105	6	models	model	NOUN
cana-2055	105	7	'	'	PART
cana-2055	105	8	poorer	poor	ADJ
cana-2055	105	9	yield	yield	NOUN
cana-2055	105	10	performance	performance	NOUN
cana-2055	105	11	can	can	AUX
cana-2055	105	12	be	be	AUX
cana-2055	105	13	due	due	ADJ
cana-2055	105	14	to	to	ADP
cana-2055	105	15	characteristics	characteristic	NOUN
cana-2055	105	16	that	that	PRON
cana-2055	105	17	were	be	AUX
cana-2055	105	18	n't	not	PART
cana-2055	105	19	the	the	DET
cana-2055	105	20	most	most	ADV
cana-2055	105	21	accurate	accurate	ADJ
cana-2055	105	22	or	or	CCONJ
cana-2055	105	23	representative	representative	ADJ
cana-2055	105	24	when	when	SCONJ
cana-2055	105	25	gathered	gather	VERB
cana-2055	105	26	from	from	ADP
cana-2055	105	27	data	datum	NOUN
cana-2055	105	28	.	.	PUNCT
cana-2055	106	1	it	it	PRON
cana-2055	106	2	has	have	VERB
cana-2055	106	3	to	to	PART
cana-2055	106	4	be	be	AUX
cana-2055	106	5	able	able	ADJ
cana-2055	106	6	to	to	PART
cana-2055	106	7	process	process	VERB
cana-2055	106	8	complicated	complicated	ADJ
cana-2055	106	9	or	or	CCONJ
cana-2055	106	10	massive	massive	ADJ
cana-2055	106	11	amounts	amount	NOUN
cana-2055	106	12	of	of	ADP
cana-2055	106	13	data	datum	NOUN
cana-2055	106	14	with	with	ADP
cana-2055	106	15	ease	ease	NOUN
cana-2055	106	16	.	.	PUNCT
cana-2055	107	1	consequently	consequently	ADV
cana-2055	107	2	,	,	PUNCT
cana-2055	107	3	the	the	DET
cana-2055	107	4	authors	author	NOUN
cana-2055	107	5	advocated	advocate	VERB
cana-2055	107	6	using	use	VERB
cana-2055	107	7	dl	dl	PROPN
cana-2055	107	8	methods	method	NOUN
cana-2055	107	9	,	,	PUNCT
cana-2055	107	10	even	even	ADV
cana-2055	107	11	if	if	SCONJ
cana-2055	107	12	the	the	DET
cana-2055	107	13	model	model	NOUN
cana-2055	107	14	's	's	PART
cana-2055	107	15	prediction	prediction	NOUN
cana-2055	107	16	rate	rate	NOUN
cana-2055	107	17	and	and	CCONJ
cana-2055	107	18	computational	computational	ADJ
cana-2055	107	19	complexity	complexity	NOUN
cana-2055	107	20	may	may	AUX
cana-2055	107	21	need	need	VERB
cana-2055	107	22	some	some	DET
cana-2055	107	23	improvement	improvement	NOUN
cana-2055	107	24	.	.	PUNCT
cana-2055	108	1	in	in	ADP
cana-2055	108	2	addition	addition	NOUN
cana-2055	108	3	,	,	PUNCT
cana-2055	108	4	prior	prior	ADJ
cana-2055	108	5	efforts	effort	NOUN
cana-2055	108	6	should	should	AUX
cana-2055	108	7	have	have	AUX
cana-2055	108	8	prioritised	prioritise	VERB
cana-2055	108	9	dr	dr	PROPN
cana-2055	108	10	,	,	PUNCT
cana-2055	108	11	which	which	PRON
cana-2055	108	12	eliminates	eliminate	VERB
cana-2055	108	13	the	the	DET
cana-2055	108	14	need	need	NOUN
cana-2055	108	15	to	to	PART
cana-2055	108	16	interpret	interpret	VERB
cana-2055	108	17	dl	dl	PROPN
cana-2055	108	18	characteristics	characteristic	NOUN
cana-2055	108	19	and	and	CCONJ
cana-2055	108	20	directly	directly	ADV
cana-2055	108	21	forecasts	forecast	VERB
cana-2055	108	22	crop	crop	NOUN
cana-2055	108	23	yield	yield	NOUN
cana-2055	108	24	from	from	ADP
cana-2055	108	25	the	the	DET
cana-2055	108	26	dataset	dataset	NOUN
cana-2055	108	27	;	;	PUNCT
cana-2055	108	28	yet	yet	CCONJ
cana-2055	108	29	,	,	PUNCT
cana-2055	108	30	it	it	PRON
cana-2055	108	31	requires	require	VERB
cana-2055	108	32	more	more	ADJ
cana-2055	108	33	storage	storage	NOUN
cana-2055	108	34	capacity	capacity	NOUN
cana-2055	108	35	.	.	PUNCT
cana-2055	109	1	3	3	X
cana-2055	109	2	.	.	X
cana-2055	109	3	methodology	methodology	NOUN
cana-2055	109	4	in	in	ADP
cana-2055	109	5	this	this	DET
cana-2055	109	6	research	research	NOUN
cana-2055	109	7	,	,	PUNCT
cana-2055	109	8	an	an	DET
cana-2055	109	9	ideal	ideal	ADJ
cana-2055	109	10	dl	dl	NOUN
cana-2055	109	11	system	system	NOUN
cana-2055	109	12	with	with	ADP
cana-2055	109	13	dr	dr	PROPN
cana-2055	109	14	techniques	technique	NOUN
cana-2055	109	15	for	for	ADP
cana-2055	109	16	cyp	cyp	ADJ
cana-2055	109	17	of	of	ADP
cana-2055	109	18	regional	regional	ADJ
cana-2055	109	19	crops	crop	NOUN
cana-2055	109	20	in	in	ADP
cana-2055	109	21	india	india	PROPN
cana-2055	109	22	is	be	AUX
cana-2055	109	23	proposed	propose	VERB
cana-2055	109	24	.	.	PUNCT
cana-2055	110	1	south	south	PROPN
cana-2055	110	2	indian	indian	ADJ
cana-2055	110	3	agricultural	agricultural	ADJ
cana-2055	110	4	statistics	statistic	NOUN
cana-2055	110	5	,	,	PUNCT
cana-2055	110	6	including	include	VERB
cana-2055	110	7	rainfall	rainfall	NOUN
cana-2055	110	8	,	,	PUNCT
cana-2055	110	9	crop	crop	NOUN
cana-2055	110	10	production	production	NOUN
cana-2055	110	11	,	,	PUNCT
cana-2055	110	12	soil	soil	NOUN
cana-2055	110	13	composition	composition	NOUN
cana-2055	110	14	,	,	PUNCT
cana-2055	110	15	and	and	CCONJ
cana-2055	110	16	meteorological	meteorological	ADJ
cana-2055	110	17	information	information	NOUN
cana-2055	110	18	,	,	PUNCT
cana-2055	110	19	are	be	AUX
cana-2055	110	20	first	first	ADV
cana-2055	110	21	gathered	gather	VERB
cana-2055	110	22	from	from	ADP
cana-2055	110	23	publicly	publicly	ADV
cana-2055	110	24	accessible	accessible	ADJ
cana-2055	110	25	data	datum	NOUN
cana-2055	110	26	sources	source	NOUN
cana-2055	110	27	.	.	PUNCT
cana-2055	111	1	next	next	ADV
cana-2055	111	2	,	,	PUNCT
cana-2055	111	3	data	datum	NOUN
cana-2055	111	4	cleaning	cleaning	NOUN
cana-2055	111	5	and	and	CCONJ
cana-2055	111	6	data	datum	NOUN
cana-2055	111	7	normalisation	normalisation	NOUN
cana-2055	111	8	are	be	AUX
cana-2055	111	9	used	use	VERB
cana-2055	111	10	to	to	PART
cana-2055	111	11	complete	complete	VERB
cana-2055	111	12	the	the	DET
cana-2055	111	13	pre	pre	NOUN
cana-2055	111	14	-	-	NOUN
cana-2055	111	15	processing	processing	NOUN
cana-2055	111	16	of	of	ADP
cana-2055	111	17	the	the	DET
cana-2055	111	18	data	datum	NOUN
cana-2055	111	19	.	.	PUNCT
cana-2055	112	1	subsequently	subsequently	ADV
cana-2055	112	2	,	,	PUNCT
cana-2055	112	3	dr	dr	PROPN
cana-2055	112	4	is	be	AUX
cana-2055	112	5	generated	generate	VERB
cana-2055	112	6	by	by	ADP
cana-2055	112	7	sekpca	sekpca	NOUN
cana-2055	112	8	,	,	PUNCT
cana-2055	112	9	yielding	yield	VERB
cana-2055	112	10	reduced	reduce	VERB
cana-2055	112	11	dimensional	dimensional	ADJ
cana-2055	112	12	elements	element	NOUN
cana-2055	112	13	for	for	ADP
cana-2055	112	14	cyp	cyp	ADJ
cana-2055	112	15	.	.	PUNCT
cana-2055	113	1	lastly	lastly	ADV
cana-2055	113	2	,	,	PUNCT
cana-2055	113	3	wtdcnn	wtdcnn	VERB
cana-2055	113	4	is	be	AUX
cana-2055	113	5	used	use	VERB
cana-2055	113	6	to	to	PART
cana-2055	113	7	create	create	VERB
cana-2055	113	8	cyp	cyp	ADJ
cana-2055	113	9	.	.	PUNCT
cana-2055	113	10	fig	fig	NOUN
cana-2055	113	11	.	.	PUNCT
cana-2055	114	1	1	1	NUM
cana-2055	114	2	depicts	depict	VERB
cana-2055	114	3	the	the	DET
cana-2055	114	4	planned	plan	VERB
cana-2055	114	5	work	work	NOUN
cana-2055	114	6	's	's	PART
cana-2055	114	7	process	process	NOUN
cana-2055	114	8	.	.	PUNCT
cana-2055	115	1	communications	communication	NOUN
cana-2055	115	2	on	on	ADP
cana-2055	115	3	applied	apply	VERB
cana-2055	115	4	nonlinear	nonlinear	ADJ
cana-2055	115	5	analysis	analysis	NOUN
cana-2055	115	6	issn	issn	NOUN
cana-2055	115	7	:	:	PUNCT
cana-2055	115	8	1074	1074	NUM
cana-2055	115	9	-	-	PUNCT
cana-2055	115	10	133x	133x	NUM
cana-2055	115	11	vol	vol	NOUN
cana-2055	115	12	32	32	NUM
cana-2055	115	13	no	no	NOUN
cana-2055	115	14	.	.	NOUN
cana-2055	115	15	3	3	NUM
cana-2055	115	16	(	(	PUNCT
cana-2055	115	17	2025	2025	NUM
cana-2055	115	18	)	)	PUNCT
cana-2055	115	19	581	581	NUM
cana-2055	115	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-2055	115	21	figure	figure	NOUN
cana-2055	115	22	.	.	PUNCT
cana-2055	116	1	1	1	NUM
cana-2055	116	2	planned	plan	VERB
cana-2055	116	3	work	work	NOUN
cana-2055	116	4	's	's	PART
cana-2055	116	5	process	process	NOUN
cana-2055	116	6	3.1	3.1	NUM
cana-2055	116	7	preprocessing	preprocesse	VERB
cana-2055	116	8	the	the	DET
cana-2055	116	9	south	south	PROPN
cana-2055	116	10	indian	indian	PROPN
cana-2055	116	11	region	region	NOUN
cana-2055	116	12	's	's	PART
cana-2055	116	13	agricultural	agricultural	ADJ
cana-2055	116	14	statistics	statistic	NOUN
cana-2055	116	15	,	,	PUNCT
cana-2055	116	16	including	include	VERB
cana-2055	116	17	information	information	NOUN
cana-2055	116	18	on	on	ADP
cana-2055	116	19	rainfall	rainfall	NOUN
cana-2055	116	20	,	,	PUNCT
cana-2055	116	21	crop	crop	NOUN
cana-2055	116	22	production	production	NOUN
cana-2055	116	23	,	,	PUNCT
cana-2055	116	24	soil	soil	NOUN
cana-2055	116	25	composition	composition	NOUN
cana-2055	116	26	,	,	PUNCT
cana-2055	116	27	and	and	CCONJ
cana-2055	116	28	meteorological	meteorological	ADJ
cana-2055	116	29	conditions	condition	NOUN
cana-2055	116	30	,	,	PUNCT
cana-2055	116	31	are	be	AUX
cana-2055	116	32	first	first	ADV
cana-2055	116	33	gathered	gather	VERB
cana-2055	116	34	from	from	ADP
cana-2055	116	35	publicly	publicly	ADV
cana-2055	116	36	accessible	accessible	ADJ
cana-2055	116	37	data	datum	NOUN
cana-2055	116	38	sources	source	NOUN
cana-2055	116	39	.	.	PUNCT
cana-2055	117	1	after	after	ADP
cana-2055	117	2	that	that	PRON
cana-2055	117	3	,	,	PUNCT
cana-2055	117	4	as	as	SCONJ
cana-2055	117	5	data	datum	NOUN
cana-2055	117	6	is	be	AUX
cana-2055	117	7	gathered	gather	VERB
cana-2055	117	8	from	from	ADP
cana-2055	117	9	several	several	ADJ
cana-2055	117	10	sources	source	NOUN
cana-2055	117	11	,	,	PUNCT
cana-2055	117	12	preparation	preparation	NOUN
cana-2055	117	13	or	or	CCONJ
cana-2055	117	14	preprocessing	preprocessing	NOUN
cana-2055	117	15	is	be	AUX
cana-2055	117	16	done	do	VERB
cana-2055	117	17	.	.	PUNCT
cana-2055	118	1	since	since	SCONJ
cana-2055	118	2	it	it	PRON
cana-2055	118	3	is	be	AUX
cana-2055	118	4	gathered	gather	VERB
cana-2055	118	5	in	in	ADP
cana-2055	118	6	raw	raw	ADJ
cana-2055	118	7	form	form	NOUN
cana-2055	118	8	,	,	PUNCT
cana-2055	118	9	analysis	analysis	NOUN
cana-2055	118	10	is	be	AUX
cana-2055	118	11	not	not	PART
cana-2055	118	12	appropriate	appropriate	ADJ
cana-2055	118	13	.	.	PUNCT
cana-2055	119	1	therefore	therefore	ADV
cana-2055	119	2	,	,	PUNCT
cana-2055	119	3	in	in	ADP
cana-2055	119	4	order	order	NOUN
cana-2055	119	5	to	to	PART
cana-2055	119	6	increase	increase	VERB
cana-2055	119	7	the	the	DET
cana-2055	119	8	prediction	prediction	NOUN
cana-2055	119	9	rate	rate	NOUN
cana-2055	119	10	,	,	PUNCT
cana-2055	119	11	preprocessing	preprocessing	NOUN
cana-2055	119	12	is	be	AUX
cana-2055	119	13	crucial	crucial	ADJ
cana-2055	119	14	before	before	ADP
cana-2055	119	15	estimating	estimate	VERB
cana-2055	119	16	crop	crop	NOUN
cana-2055	119	17	production	production	NOUN
cana-2055	119	18	.	.	PUNCT
cana-2055	120	1	the	the	DET
cana-2055	120	2	following	follow	VERB
cana-2055	120	3	is	be	AUX
cana-2055	120	4	an	an	DET
cana-2055	120	5	explanation	explanation	NOUN
cana-2055	120	6	of	of	ADP
cana-2055	120	7	the	the	DET
cana-2055	120	8	preprocessing	preprocessing	NOUN
cana-2055	120	9	procedures	procedure	NOUN
cana-2055	120	10	.	.	PUNCT
cana-2055	121	1	step:1	step:1	PRON
cana-2055	121	2	cleaning	clean	VERB
cana-2055	121	3	data	datum	NOUN
cana-2055	121	4	the	the	DET
cana-2055	121	5	data	datum	NOUN
cana-2055	121	6	is	be	AUX
cana-2055	121	7	cleaned	clean	VERB
cana-2055	121	8	by	by	ADP
cana-2055	121	9	estimation	estimation	NOUN
cana-2055	121	10	for	for	ADP
cana-2055	121	11	missing	miss	VERB
cana-2055	121	12	values	value	NOUN
cana-2055	121	13	and	and	CCONJ
cana-2055	121	14	removal	removal	NOUN
cana-2055	121	15	of	of	ADP
cana-2055	121	16	errors	error	NOUN
cana-2055	121	17	after	after	SCONJ
cana-2055	121	18	it	it	PRON
cana-2055	121	19	has	have	AUX
cana-2055	121	20	been	be	AUX
cana-2055	121	21	gathered	gather	VERB
cana-2055	121	22	from	from	ADP
cana-2055	121	23	sources	source	NOUN
cana-2055	121	24	.	.	PUNCT
cana-2055	122	1	the	the	DET
cana-2055	122	2	precision	precision	NOUN
cana-2055	122	3	of	of	ADP
cana-2055	122	4	the	the	DET
cana-2055	122	5	model	model	NOUN
cana-2055	122	6	in	in	ADP
cana-2055	122	7	the	the	DET
cana-2055	122	8	data	data	NOUN
cana-2055	122	9	is	be	AUX
cana-2055	122	10	impacted	impact	VERB
cana-2055	122	11	by	by	ADP
cana-2055	122	12	missing	miss	VERB
cana-2055	122	13	variables	variable	NOUN
cana-2055	122	14	.	.	PUNCT
cana-2055	123	1	the	the	DET
cana-2055	123	2	median	median	ADJ
cana-2055	123	3	or	or	CCONJ
cana-2055	123	4	mean	mean	ADJ
cana-2055	123	5	values	value	NOUN
cana-2055	123	6	of	of	ADP
cana-2055	123	7	the	the	DET
cana-2055	123	8	whole	whole	ADJ
cana-2055	123	9	dataset	dataset	NOUN
cana-2055	123	10	or	or	CCONJ
cana-2055	123	11	another	another	DET
cana-2055	123	12	summary	summary	NOUN
cana-2055	123	13	statistic	statistic	NOUN
cana-2055	123	14	are	be	AUX
cana-2055	123	15	then	then	ADV
cana-2055	123	16	used	use	VERB
cana-2055	123	17	to	to	PART
cana-2055	123	18	replace	replace	VERB
cana-2055	123	19	the	the	DET
cana-2055	123	20	missing	miss	VERB
cana-2055	123	21	values	value	NOUN
cana-2055	123	22	.	.	PUNCT
cana-2055	124	1	in	in	ADP
cana-2055	124	2	order	order	NOUN
cana-2055	124	3	to	to	PART
cana-2055	124	4	minimise	minimise	VERB
cana-2055	124	5	noise	noise	NOUN
cana-2055	124	6	in	in	ADP
cana-2055	124	7	the	the	DET
cana-2055	124	8	dataset	dataset	NOUN
cana-2055	124	9	,	,	PUNCT
cana-2055	124	10	missing	miss	VERB
cana-2055	124	11	value	value	NOUN
cana-2055	124	12	imputation	imputation	NOUN
cana-2055	124	13	is	be	AUX
cana-2055	124	14	followed	follow	VERB
cana-2055	124	15	by	by	ADP
cana-2055	124	16	outlier	outlier	ADJ
cana-2055	124	17	reduction	reduction	NOUN
cana-2055	124	18	.	.	PUNCT
cana-2055	125	1	delete	delete	NOUN
cana-2055	125	2	:	:	PUNCT
cana-2055	125	3	removing	remove	VERB
cana-2055	125	4	outlier	outlier	NOUN
cana-2055	125	5	from	from	ADP
cana-2055	125	6	the	the	DET
cana-2055	125	7	data	data	NOUN
cana-2055	125	8	collection	collection	NOUN
cana-2055	125	9	is	be	AUX
cana-2055	125	10	the	the	DET
cana-2055	125	11	simplest	simple	ADJ
cana-2055	125	12	method	method	NOUN
cana-2055	125	13	to	to	PART
cana-2055	125	14	do	do	VERB
cana-2055	125	15	so	so	ADV
cana-2055	125	16	and	and	CCONJ
cana-2055	125	17	enhances	enhance	VERB
cana-2055	125	18	the	the	DET
cana-2055	125	19	quality	quality	NOUN
cana-2055	125	20	of	of	ADP
cana-2055	125	21	the	the	DET
cana-2055	125	22	data	datum	NOUN
cana-2055	125	23	.	.	PUNCT
cana-2055	126	1	matrix	matrix	NOUN
cana-2055	126	2	dimensions	dimension	NOUN
cana-2055	126	3	of	of	ADP
cana-2055	126	4	(	(	PUNCT
cana-2055	126	5	3355	3355	NUM
cana-2055	126	6	,	,	PUNCT
cana-2055	126	7	1	1	NUM
cana-2055	126	8	,	,	PUNCT
cana-2055	126	9	22	22	NUM
cana-2055	126	10	)	)	PUNCT
cana-2055	126	11	indicate	indicate	VERB
cana-2055	126	12	the	the	DET
cana-2055	126	13	number	number	NOUN
cana-2055	126	14	of	of	ADP
cana-2055	126	15	information	information	NOUN
cana-2055	126	16	samples	sample	NOUN
cana-2055	126	17	used	use	VERB
cana-2055	126	18	with	with	ADP
cana-2055	126	19	a	a	DET
cana-2055	126	20	1	1	NUM
cana-2055	126	21	kernel	kernel	NOUN
cana-2055	126	22	and	and	CCONJ
cana-2055	126	23	22	22	NUM
cana-2055	126	24	features	feature	NOUN
cana-2055	126	25	in	in	ADP
cana-2055	126	26	cnn	cnn	PROPN
cana-2055	126	27	.	.	PUNCT
cana-2055	127	1	the	the	DET
cana-2055	127	2	dataset	dataset	NOUN
cana-2055	127	3	consists	consist	VERB
cana-2055	127	4	of	of	ADP
cana-2055	127	5	3355	3355	NUM
cana-2055	127	6	row	row	NOUN
cana-2055	127	7	(	(	PUNCT
cana-2055	127	8	input	input	NOUN
cana-2055	127	9	sample	sample	NOUN
cana-2055	127	10	)	)	PUNCT
cana-2055	127	11	and	and	CCONJ
cana-2055	127	12	22	22	NUM
cana-2055	127	13	columns	column	NOUN
cana-2055	127	14	(	(	PUNCT
cana-2055	127	15	features	feature	NOUN
cana-2055	127	16	)	)	PUNCT
cana-2055	127	17	.	.	PUNCT
cana-2055	128	1	step:2	step:2	VERB
cana-2055	128	2	normalisation	normalisation	NOUN
cana-2055	128	3	the	the	DET
cana-2055	128	4	dataset	dataset	NOUN
cana-2055	128	5	is	be	AUX
cana-2055	128	6	normalised	normalise	VERB
cana-2055	128	7	after	after	SCONJ
cana-2055	128	8	data	data	NOUN
cana-2055	128	9	cleaning	cleaning	NOUN
cana-2055	128	10	is	be	AUX
cana-2055	128	11	completed	complete	VERB
cana-2055	128	12	.	.	PUNCT
cana-2055	129	1	the	the	DET
cana-2055	129	2	goal	goal	NOUN
cana-2055	129	3	of	of	ADP
cana-2055	129	4	normalisation	normalisation	NOUN
cana-2055	129	5	is	be	AUX
cana-2055	129	6	to	to	PART
cana-2055	129	7	make	make	VERB
cana-2055	129	8	data	datum	NOUN
cana-2055	129	9	comparable	comparable	ADJ
cana-2055	129	10	in	in	ADP
cana-2055	129	11	distribution	distribution	NOUN
cana-2055	129	12	and	and	CCONJ
cana-2055	129	13	dimensionless	dimensionless	NOUN
cana-2055	129	14	.	.	PUNCT
cana-2055	130	1	the	the	DET
cana-2055	130	2	mathematical	mathematical	ADJ
cana-2055	130	3	expression	expression	NOUN
cana-2055	130	4	for	for	ADP
cana-2055	130	5	it	it	PRON
cana-2055	130	6	is	be	AUX
cana-2055	130	7	as	as	SCONJ
cana-2055	130	8	follows	follow	VERB
cana-2055	130	9	:	:	PUNCT
cana-2055	131	1	𝐶′	𝐶′	PROPN
cana-2055	131	2	→	→	SYM
cana-2055	131	3	𝑁𝑜𝑟𝑚	𝑁𝑜𝑟𝑚	PROPN
cana-2055	131	4	=	=	SYM
cana-2055	131	5	𝐶	𝐶	PROPN
cana-2055	131	6	→	→	PUNCT
cana-2055	131	7	′	′	NUM
cana-2055	131	8	−	−	PROPN
cana-2055	131	9	𝐶	𝐶	PROPN
cana-2055	131	10	→𝑚𝑖𝑛	→𝑚𝑖𝑛	PROPN
cana-2055	131	11	′	′	NUM
cana-2055	131	12	𝐶	𝐶	PROPN
cana-2055	131	13	→𝑚𝑎𝑥	→𝑚𝑎𝑥	PROPN
cana-2055	131	14	′	′	NOUN
cana-2055	131	15	−	−	PROPN
cana-2055	131	16	𝐶	𝐶	PROPN
cana-2055	131	17	→𝑚𝑖𝑛	→𝑚𝑖𝑛	PROPN
cana-2055	131	18	′	′	NUM
cana-2055	131	19	(	(	PUNCT
cana-2055	131	20	1	1	X
cana-2055	131	21	)	)	PUNCT
cana-2055	131	22	here	here	ADV
cana-2055	131	23	,	,	PUNCT
cana-2055	131	24	𝐶′	𝐶′	PROPN
cana-2055	131	25	→𝑁𝑜𝑟𝑚	→𝑁𝑜𝑟𝑚	X
cana-2055	131	26	denotes	denote	VERB
cana-2055	131	27	the	the	DET
cana-2055	131	28	data	datum	NOUN
cana-2055	131	29	that	that	PRON
cana-2055	131	30	has	have	AUX
cana-2055	131	31	been	be	AUX
cana-2055	131	32	normalised	normalise	VERB
cana-2055	131	33	,	,	PUNCT
cana-2055	131	34	𝐶	𝐶	PROPN
cana-2055	131	35	→	→	PUNCT
cana-2055	131	36	′	′	NUM
cana-2055	131	37	represents	represent	VERB
cana-2055	131	38	the	the	DET
cana-2055	131	39	original	original	ADJ
cana-2055	131	40	information	information	NOUN
cana-2055	131	41	,	,	PUNCT
cana-2055	131	42	and	and	CCONJ
cana-2055	131	43	𝐶	𝐶	PROPN
cana-2055	131	44	→𝑚𝑖𝑛	→𝑚𝑖𝑛	PROPN
cana-2055	131	45	′	′	NUM
cana-2055	131	46	min	min	NOUN
cana-2055	131	47	and	and	CCONJ
cana-2055	131	48	𝐶	𝐶	PROPN
cana-2055	131	49	→𝑚𝑎𝑥	→𝑚𝑎𝑥	PROPN
cana-2055	131	50	′	′	NUM
cana-2055	131	51	denote	denote	VERB
cana-2055	131	52	lowest	low	ADJ
cana-2055	131	53	and	and	CCONJ
cana-2055	131	54	highest	high	ADJ
cana-2055	131	55	values	value	NOUN
cana-2055	131	56	found	find	VERB
cana-2055	131	57	in	in	ADP
cana-2055	131	58	the	the	DET
cana-2055	131	59	data	datum	NOUN
cana-2055	131	60	set	set	VERB
cana-2055	131	61	,	,	PUNCT
cana-2055	131	62	respectively	respectively	ADV
cana-2055	131	63	.	.	PUNCT
cana-2055	132	1	this	this	DET
cana-2055	132	2	minmax	minmax	PROPN
cana-2055	132	3	normalisation	normalisation	NOUN
cana-2055	132	4	places	place	VERB
cana-2055	132	5	the	the	DET
cana-2055	132	6	values	value	NOUN
cana-2055	132	7	of	of	ADP
cana-2055	132	8	the	the	DET
cana-2055	132	9	dataset	dataset	NOUN
cana-2055	132	10	between	between	ADP
cana-2055	132	11	0	0	NUM
cana-2055	132	12	and	and	CCONJ
cana-2055	132	13	1	1	NUM
cana-2055	132	14	.	.	X
cana-2055	132	15	communications	communication	NOUN
cana-2055	132	16	on	on	ADP
cana-2055	132	17	applied	apply	VERB
cana-2055	132	18	nonlinear	nonlinear	ADJ
cana-2055	132	19	analysis	analysis	NOUN
cana-2055	132	20	issn	issn	NOUN
cana-2055	132	21	:	:	PUNCT
cana-2055	132	22	1074	1074	NUM
cana-2055	132	23	-	-	PUNCT
cana-2055	132	24	133x	133x	NUM
cana-2055	132	25	vol	vol	NOUN
cana-2055	132	26	32	32	NUM
cana-2055	132	27	no	no	NOUN
cana-2055	132	28	.	.	NOUN
cana-2055	132	29	3	3	NUM
cana-2055	132	30	(	(	PUNCT
cana-2055	132	31	2025	2025	NUM
cana-2055	132	32	)	)	PUNCT
cana-2055	132	33	582	582	NUM
cana-2055	132	34	https://internationalpubls.com	https://internationalpubls.com	X
cana-2055	132	35	step:3	step:3	NOUN
cana-2055	132	36	splitting	split	VERB
cana-2055	132	37	data	datum	NOUN
cana-2055	132	38	sets	set	NOUN
cana-2055	132	39	pre	pre	ADJ
cana-2055	132	40	-	-	ADJ
cana-2055	132	41	processed	processed	ADJ
cana-2055	132	42	data	data	NOUN
cana-2055	132	43	is	be	AUX
cana-2055	132	44	divided	divide	VERB
cana-2055	132	45	into	into	ADP
cana-2055	132	46	datasets	dataset	NOUN
cana-2055	132	47	for	for	ADP
cana-2055	132	48	training	training	NOUN
cana-2055	132	49	and	and	CCONJ
cana-2055	132	50	testing	testing	NOUN
cana-2055	132	51	so	so	SCONJ
cana-2055	132	52	that	that	SCONJ
cana-2055	132	53	the	the	DET
cana-2055	132	54	suggested	suggest	VERB
cana-2055	132	55	approach	approach	NOUN
cana-2055	132	56	may	may	AUX
cana-2055	132	57	be	be	AUX
cana-2055	132	58	put	put	VERB
cana-2055	132	59	into	into	ADP
cana-2055	132	60	practice	practice	NOUN
cana-2055	132	61	.	.	PUNCT
cana-2055	133	1	for	for	ADP
cana-2055	133	2	testing	testing	NOUN
cana-2055	133	3	and	and	CCONJ
cana-2055	133	4	training	training	NOUN
cana-2055	133	5	,	,	PUNCT
cana-2055	133	6	the	the	DET
cana-2055	133	7	suggested	suggest	VERB
cana-2055	133	8	system	system	NOUN
cana-2055	133	9	selects	select	VERB
cana-2055	133	10	71	71	NUM
cana-2055	133	11	%	%	NOUN
cana-2055	133	12	and	and	CCONJ
cana-2055	133	13	31	31	NUM
cana-2055	133	14	%	%	NOUN
cana-2055	133	15	of	of	ADP
cana-2055	133	16	the	the	DET
cana-2055	133	17	data	datum	NOUN
cana-2055	133	18	,	,	PUNCT
cana-2055	133	19	respectively	respectively	ADV
cana-2055	133	20	,	,	PUNCT
cana-2055	133	21	at	at	ADP
cana-2055	133	22	random	random	ADJ
cana-2055	133	23	.	.	PUNCT
cana-2055	134	1	3.2	3.2	NUM
cana-2055	134	2	a	a	DET
cana-2055	134	3	reduction	reduction	NOUN
cana-2055	134	4	of	of	ADP
cana-2055	134	5	dimensions	dimension	NOUN
cana-2055	134	6	the	the	DET
cana-2055	134	7	dataset	dataset	NOUN
cana-2055	134	8	's	's	PART
cana-2055	134	9	dr	dr	PROPN
cana-2055	134	10	is	be	AUX
cana-2055	134	11	made	make	VERB
cana-2055	134	12	utilising	utilise	VERB
cana-2055	134	13	squared	square	VERB
cana-2055	134	14	exponentially	exponentially	ADV
cana-2055	134	15	kernel	kernel	NOUN
cana-2055	134	16	-	-	PUNCT
cana-2055	134	17	based	base	VERB
cana-2055	134	18	analysis	analysis	NOUN
cana-2055	134	19	of	of	ADP
cana-2055	134	20	principal	principal	ADJ
cana-2055	134	21	components	component	NOUN
cana-2055	134	22	after	after	SCONJ
cana-2055	134	23	it	it	PRON
cana-2055	134	24	has	have	AUX
cana-2055	134	25	been	be	AUX
cana-2055	134	26	pre	pre	VERB
cana-2055	134	27	-	-	VERB
cana-2055	134	28	processed	processed	ADJ
cana-2055	134	29	.	.	PUNCT
cana-2055	135	1	this	this	PRON
cana-2055	135	2	takes	take	VERB
cana-2055	135	3	high	high	ADV
cana-2055	135	4	-	-	PUNCT
cana-2055	135	5	dimensional	dimensional	ADJ
cana-2055	135	6	data	datum	NOUN
cana-2055	135	7	and	and	CCONJ
cana-2055	135	8	turns	turn	VERB
cana-2055	135	9	it	it	PRON
cana-2055	135	10	into	into	ADP
cana-2055	135	11	lowdimensional	lowdimensional	ADJ
cana-2055	135	12	data	datum	NOUN
cana-2055	135	13	.	.	PUNCT
cana-2055	136	1	in	in	ADP
cana-2055	136	2	principle	principle	ADJ
cana-2055	136	3	component	component	NOUN
cana-2055	136	4	analysis	analysis	NOUN
cana-2055	136	5	(	(	PUNCT
cana-2055	136	6	pca	pca	PROPN
cana-2055	136	7	)	)	PUNCT
cana-2055	136	8	,	,	PUNCT
cana-2055	136	9	the	the	DET
cana-2055	136	10	basis	basis	NOUN
cana-2055	136	11	is	be	AUX
cana-2055	136	12	changed	change	VERB
cana-2055	136	13	after	after	SCONJ
cana-2055	136	14	the	the	DET
cana-2055	136	15	principal	principal	ADJ
cana-2055	136	16	components	component	NOUN
cana-2055	136	17	are	be	AUX
cana-2055	136	18	computed	compute	VERB
cana-2055	136	19	.	.	PUNCT
cana-2055	137	1	it	it	PRON
cana-2055	137	2	resolves	resolve	VERB
cana-2055	137	3	the	the	DET
cana-2055	137	4	association	association	NOUN
cana-2055	137	5	between	between	ADP
cana-2055	137	6	the	the	DET
cana-2055	137	7	variables	variable	NOUN
cana-2055	137	8	and	and	CCONJ
cana-2055	137	9	may	may	AUX
cana-2055	137	10	greatly	greatly	ADV
cana-2055	137	11	enhance	enhance	VERB
cana-2055	137	12	the	the	DET
cana-2055	137	13	recognition	recognition	NOUN
cana-2055	137	14	and	and	CCONJ
cana-2055	137	15	diagnosis	diagnosis	NOUN
cana-2055	137	16	of	of	ADP
cana-2055	137	17	high	high	ADJ
cana-2055	137	18	-	-	PUNCT
cana-2055	137	19	dimensional	dimensional	ADJ
cana-2055	137	20	information	information	NOUN
cana-2055	137	21	in	in	ADP
cana-2055	137	22	agricultural	agricultural	ADJ
cana-2055	137	23	yields	yield	NOUN
cana-2055	137	24	during	during	ADP
cana-2055	137	25	real	real	ADJ
cana-2055	137	26	production	production	NOUN
cana-2055	137	27	.	.	PUNCT
cana-2055	138	1	still	still	ADV
cana-2055	138	2	,	,	PUNCT
cana-2055	138	3	very	very	ADV
cana-2055	138	4	uncorrelated	uncorrelated	ADJ
cana-2055	138	5	variables	variable	NOUN
cana-2055	138	6	are	be	AUX
cana-2055	138	7	a	a	DET
cana-2055	138	8	must	must	NOUN
cana-2055	138	9	for	for	SCONJ
cana-2055	138	10	pca	pca	PROPN
cana-2055	138	11	to	to	PART
cana-2055	138	12	work	work	VERB
cana-2055	138	13	.	.	PUNCT
cana-2055	139	1	also	also	ADV
cana-2055	139	2	,	,	PUNCT
cana-2055	139	3	pca	pca	PROPN
cana-2055	139	4	is	be	AUX
cana-2055	139	5	n't	not	PART
cana-2055	139	6	great	great	ADJ
cana-2055	139	7	at	at	ADP
cana-2055	139	8	spotting	spot	VERB
cana-2055	139	9	models	model	NOUN
cana-2055	139	10	in	in	ADP
cana-2055	139	11	nonlinear	nonlinear	ADJ
cana-2055	139	12	data	datum	NOUN
cana-2055	139	13	.	.	PUNCT
cana-2055	140	1	due	due	ADP
cana-2055	140	2	to	to	ADP
cana-2055	140	3	the	the	DET
cana-2055	140	4	nonlinear	nonlinear	ADJ
cana-2055	140	5	nature	nature	NOUN
cana-2055	140	6	of	of	ADP
cana-2055	140	7	the	the	DET
cana-2055	140	8	feature	feature	NOUN
cana-2055	140	9	-	-	PUNCT
cana-2055	140	10	to	to	ADP
cana-2055	140	11	-	-	PUNCT
cana-2055	140	12	feature	feature	NOUN
cana-2055	140	13	connection	connection	NOUN
cana-2055	140	14	in	in	ADP
cana-2055	140	15	the	the	DET
cana-2055	140	16	pre	pre	ADJ
cana-2055	140	17	-	-	ADJ
cana-2055	140	18	processed	processed	ADJ
cana-2055	140	19	dataset	dataset	NOUN
cana-2055	140	20	,	,	PUNCT
cana-2055	140	21	the	the	DET
cana-2055	140	22	suggested	suggest	VERB
cana-2055	140	23	method	method	NOUN
cana-2055	140	24	enhances	enhance	VERB
cana-2055	140	25	the	the	DET
cana-2055	140	26	performance	performance	NOUN
cana-2055	140	27	of	of	ADP
cana-2055	140	28	the	the	DET
cana-2055	140	29	system	system	NOUN
cana-2055	140	30	by	by	ADP
cana-2055	140	31	effectively	effectively	ADV
cana-2055	140	32	recognising	recognise	VERB
cana-2055	140	33	the	the	DET
cana-2055	140	34	nonlinear	nonlinear	ADJ
cana-2055	140	35	data	datum	NOUN
cana-2055	140	36	and	and	CCONJ
cana-2055	140	37	dr	dr	PROPN
cana-2055	140	38	in	in	ADP
cana-2055	140	39	the	the	DET
cana-2055	140	40	dataset	dataset	NOUN
cana-2055	140	41	via	via	ADP
cana-2055	140	42	the	the	DET
cana-2055	140	43	use	use	NOUN
cana-2055	140	44	of	of	ADP
cana-2055	140	45	squared	square	VERB
cana-2055	140	46	exponentially	exponentially	ADV
cana-2055	140	47	kernels	kernel	NOUN
cana-2055	140	48	in	in	ADP
cana-2055	140	49	traditional	traditional	ADJ
cana-2055	140	50	principal	principal	ADJ
cana-2055	140	51	component	component	NOUN
cana-2055	140	52	analysis	analysis	NOUN
cana-2055	140	53	(	(	PUNCT
cana-2055	140	54	pca	pca	NOUN
cana-2055	140	55	)	)	PUNCT
cana-2055	140	56	.	.	PUNCT
cana-2055	141	1	to	to	PART
cana-2055	141	2	start	start	VERB
cana-2055	141	3	,	,	PUNCT
cana-2055	141	4	take	take	VERB
cana-2055	141	5	a	a	DET
cana-2055	141	6	look	look	NOUN
cana-2055	141	7	at	at	ADP
cana-2055	141	8	the	the	DET
cana-2055	141	9	dimensional	dimensional	ADJ
cana-2055	141	10	pre	pre	ADJ
cana-2055	141	11	-	-	ADJ
cana-2055	141	12	processed	process	VERB
cana-2055	141	13	dataset	dataset	NOUN
cana-2055	141	14	and	and	CCONJ
cana-2055	141	15	apply	apply	VERB
cana-2055	141	16	eq	eq	ADP
cana-2055	141	17	.	.	PUNCT
cana-2055	142	1	(	(	PUNCT
cana-2055	142	2	2	2	NUM
cana-2055	142	3	)	)	PUNCT
cana-2055	142	4	to	to	ADP
cana-2055	142	5	the	the	DET
cana-2055	142	6	mean	mean	ADJ
cana-2055	142	7	vector	vector	NOUN
cana-2055	142	8	for	for	ADP
cana-2055	142	9	each	each	DET
cana-2055	142	10	dimension	dimension	NOUN
cana-2055	142	11	:	:	PUNCT
cana-2055	142	12	𝑉	𝑉	PROPN
cana-2055	142	13	→𝑠𝑣	→𝑠𝑣	NOUN
cana-2055	142	14	=	=	PUNCT
cana-2055	142	15	𝑃	𝑃	NOUN
cana-2055	142	16	→𝑑𝑠	→𝑑𝑠	SYM
cana-2055	142	17	−	−	PROPN
cana-2055	142	18	µ	µ	X
cana-2055	142	19	𝜎	𝜎	X
cana-2055	142	20	(	(	PUNCT
cana-2055	142	21	2	2	NUM
cana-2055	142	22	)	)	PUNCT
cana-2055	142	23	in	in	ADP
cana-2055	142	24	this	this	DET
cana-2055	142	25	context	context	NOUN
cana-2055	142	26	,	,	PUNCT
cana-2055	142	27	𝑉	𝑉	PROPN
cana-2055	142	28	→𝑠𝑣	→𝑠𝑣	PUNCT
cana-2055	142	29	is	be	AUX
cana-2055	142	30	related	relate	VERB
cana-2055	142	31	to	to	ADP
cana-2055	142	32	the	the	DET
cana-2055	142	33	scaled	scale	VERB
cana-2055	142	34	value	value	NOUN
cana-2055	142	35	,	,	PUNCT
cana-2055	142	36	𝑃	𝑃	PROPN
cana-2055	142	37	→𝑑𝑠	→𝑑𝑠	PUNCT
cana-2055	142	38	denote	denote	VERB
cana-2055	142	39	the	the	DET
cana-2055	142	40	pre	pre	ADJ
cana-2055	142	41	-	-	ADJ
cana-2055	142	42	processed	processed	ADJ
cana-2055	142	43	dataset	dataset	NOUN
cana-2055	142	44	,	,	PUNCT
cana-2055	142	45	while	while	SCONJ
cana-2055	142	46	μ	μ	PROPN
cana-2055	142	47	and	and	CCONJ
cana-2055	142	48	σ	σ	PROPN
cana-2055	142	49	signify	signify	VERB
cana-2055	142	50	the	the	DET
cana-2055	142	51	standard	standard	ADJ
cana-2055	142	52	deviation	deviation	NOUN
cana-2055	142	53	and	and	CCONJ
cana-2055	142	54	mean	mean	VERB
cana-2055	142	55	,	,	PUNCT
cana-2055	142	56	respectively	respectively	ADV
cana-2055	142	57	.	.	PUNCT
cana-2055	143	1	the	the	DET
cana-2055	143	2	sek	sek	PROPN
cana-2055	143	3	,	,	PUNCT
cana-2055	143	4	a	a	DET
cana-2055	143	5	well	well	ADV
cana-2055	143	6	-	-	PUNCT
cana-2055	143	7	known	know	VERB
cana-2055	143	8	kernel	kernel	NOUN
cana-2055	143	9	function	function	NOUN
cana-2055	143	10	for	for	ADP
cana-2055	143	11	estimating	estimate	VERB
cana-2055	143	12	covariance	covariance	NOUN
cana-2055	143	13	matrices	matrix	NOUN
cana-2055	143	14	,	,	PUNCT
cana-2055	143	15	is	be	AUX
cana-2055	143	16	then	then	ADV
cana-2055	143	17	used	use	VERB
cana-2055	143	18	to	to	PART
cana-2055	143	19	compute	compute	VERB
cana-2055	143	20	the	the	DET
cana-2055	143	21	resulting	result	VERB
cana-2055	143	22	covariance	covariance	NOUN
cana-2055	143	23	matrix	matrix	NOUN
cana-2055	143	24	.	.	PUNCT
cana-2055	144	1	utilising	utilise	VERB
cana-2055	144	2	the	the	DET
cana-2055	144	3	sek	sek	PROPN
cana-2055	144	4	produces	produce	VERB
cana-2055	144	5	a	a	DET
cana-2055	144	6	smooth	smooth	ADJ
cana-2055	144	7	prior	prior	ADV
cana-2055	144	8	for	for	ADP
cana-2055	144	9	positions	position	NOUN
cana-2055	144	10	that	that	PRON
cana-2055	144	11	are	be	AUX
cana-2055	144	12	obtained	obtain	VERB
cana-2055	144	13	from	from	ADP
cana-2055	144	14	the	the	DET
cana-2055	144	15	calculation	calculation	NOUN
cana-2055	144	16	of	of	ADP
cana-2055	144	17	covariance	covariance	NOUN
cana-2055	144	18	.	.	PUNCT
cana-2055	145	1	in	in	ADP
cana-2055	145	2	summary	summary	NOUN
cana-2055	145	3	,	,	PUNCT
cana-2055	145	4	the	the	DET
cana-2055	145	5	sek	sek	PROPN
cana-2055	145	6	function	function	NOUN
cana-2055	145	7	,	,	PUNCT
cana-2055	145	8	sek	sek	PROPN
cana-2055	145	9	(	(	PUNCT
cana-2055	145	10	𝑣𝑥	𝑣𝑥	PROPN
cana-2055	145	11	,	,	PUNCT
cana-2055	145	12	𝑣𝑦),characterises	𝑣𝑦),characterise	VERB
cana-2055	145	13	the	the	DET
cana-2055	145	14	covariance	covariance	NOUN
cana-2055	145	15	among	among	ADP
cana-2055	145	16	each	each	DET
cana-2055	145	17	pair	pair	NOUN
cana-2055	145	18	in	in	ADP
cana-2055	145	19	𝑉	𝑉	PROPN
cana-2055	145	20	→𝑠𝑣	→𝑠𝑣	PUNCT
cana-2055	145	21	,	,	PUNCT
cana-2055	145	22	and	and	CCONJ
cana-2055	145	23	is	be	AUX
cana-2055	145	24	articulated	articulate	VERB
cana-2055	145	25	as	as	SCONJ
cana-2055	145	26	follows	follow	VERB
cana-2055	145	27	:	:	PUNCT
cana-2055	145	28	∑	∑	PUNCT
cana-2055	145	29	=	=	PUNCT
cana-2055	145	30	𝑆𝐸𝐾	𝑆𝐸𝐾	PROPN
cana-2055	145	31	(	(	PUNCT
cana-2055	145	32	𝑣𝑥	𝑣𝑥	NOUN
cana-2055	145	33	,	,	PUNCT
cana-2055	145	34	𝑣𝑦	𝑣𝑦	PRON
cana-2055	145	35	)	)	PUNCT
cana-2055	145	36	(	(	PUNCT
cana-2055	145	37	3	3	X
cana-2055	145	38	)	)	PUNCT
cana-2055	145	39	𝑆𝐸𝐾(𝑣𝑥	𝑆𝐸𝐾(𝑣𝑥	PROPN
cana-2055	145	40	,	,	PUNCT
cana-2055	145	41	𝑣𝑦	𝑣𝑦	PRON
cana-2055	145	42	)	)	PUNCT
cana-2055	145	43	=	=	SYM
cana-2055	145	44	𝜎	𝜎	PROPN
cana-2055	145	45	2	2	NUM
cana-2055	145	46	exp	exp	NOUN
cana-2055	145	47	(	(	PUNCT
cana-2055	145	48	−	−	PROPN
cana-2055	145	49	||	||	NOUN
cana-2055	146	1	𝑣𝑥	𝑣𝑥	X
cana-2055	146	2	−	−	PROPN
cana-2055	146	3	𝑣𝑦)|	𝑣𝑦)|	PROPN
cana-2055	146	4	|	|	ADV
cana-2055	146	5	2	2	NUM
cana-2055	146	6	2𝑟2	2𝑟2	NUM
cana-2055	146	7	)	)	PUNCT
cana-2055	146	8	(	(	PUNCT
cana-2055	146	9	4	4	X
cana-2055	146	10	)	)	PUNCT
cana-2055	146	11	the	the	DET
cana-2055	146	12	length	length	NOUN
cana-2055	146	13	scale	scale	NOUN
cana-2055	146	14	is	be	AUX
cana-2055	146	15	denoted	denote	VERB
cana-2055	146	16	by	by	ADP
cana-2055	146	17	r	r	NOUN
cana-2055	146	18	,	,	PUNCT
cana-2055	146	19	while	while	SCONJ
cana-2055	146	20	𝜎2	𝜎2	NOUN
cana-2055	146	21	is	be	AUX
cana-2055	146	22	the	the	DET
cana-2055	146	23	total	total	ADJ
cana-2055	146	24	variance	variance	NOUN
cana-2055	146	25	.	.	PUNCT
cana-2055	147	1	then	then	ADV
cana-2055	147	2	,	,	PUNCT
cana-2055	147	3	we	we	PRON
cana-2055	147	4	can	can	AUX
cana-2055	147	5	calculate	calculate	VERB
cana-2055	147	6	the	the	DET
cana-2055	147	7	covariance	covariance	NOUN
cana-2055	147	8	matrix	matrix	NOUN
cana-2055	147	9	's	's	PART
cana-2055	147	10	eigenvalues	eigenvalue	NOUN
cana-2055	147	11	and	and	CCONJ
cana-2055	147	12	eigenvectors	eigenvector	NOUN
cana-2055	147	13	by	by	ADP
cana-2055	147	14	following	follow	VERB
cana-2055	147	15	these	these	DET
cana-2055	147	16	steps	step	NOUN
cana-2055	147	17	:	:	PUNCT
cana-2055	147	18	∑	∑	PUNCT
cana-2055	147	19	=	=	SYM
cana-2055	147	20	𝑀	𝑀	PROPN
cana-2055	147	21	→	→	SYM
cana-2055	147	22	∆	∆	PROPN
cana-2055	147	23	(	(	PUNCT
cana-2055	147	24	𝑀	𝑀	PROPN
cana-2055	147	25	→	→	SYM
cana-2055	147	26	)	)	PUNCT
cana-2055	147	27	𝑇	𝑇	PROPN
cana-2055	147	28	(	(	PUNCT
cana-2055	147	29	5	5	NUM
cana-2055	147	30	)	)	PUNCT
cana-2055	147	31	the	the	DET
cana-2055	147	32	matrix	matrix	NOUN
cana-2055	147	33	𝑀	𝑀	PROPN
cana-2055	147	34	→	→	PUNCT
cana-2055	147	35	,	,	PUNCT
cana-2055	147	36	which	which	PRON
cana-2055	147	37	is	be	AUX
cana-2055	147	38	made	make	VERB
cana-2055	147	39	up	up	ADP
cana-2055	147	40	of	of	ADP
cana-2055	147	41	eigenvectors	eigenvector	NOUN
cana-2055	147	42	,	,	PUNCT
cana-2055	147	43	and	and	CCONJ
cana-2055	147	44	the	the	DET
cana-2055	147	45	eigenvalue	eigenvalue	ADJ
cana-2055	147	46	diagonal	diagonal	ADJ
cana-2055	147	47	matrix	matrix	NOUN
cana-2055	147	48	λ	λ	NOUN
cana-2055	147	49	are	be	AUX
cana-2055	147	50	referenced	reference	VERB
cana-2055	147	51	here	here	ADV
cana-2055	147	52	.	.	PUNCT
cana-2055	148	1	the	the	DET
cana-2055	148	2	lengths	length	NOUN
cana-2055	148	3	of	of	ADP
cana-2055	148	4	these	these	DET
cana-2055	148	5	eigenvectors	eigenvector	NOUN
cana-2055	148	6	are	be	AUX
cana-2055	148	7	1	1	NUM
cana-2055	148	8	since	since	SCONJ
cana-2055	148	9	they	they	PRON
cana-2055	148	10	are	be	AUX
cana-2055	148	11	unit	unit	NOUN
cana-2055	148	12	eigen	eigen	PROPN
cana-2055	148	13	vectors	vector	NOUN
cana-2055	148	14	.	.	PUNCT
cana-2055	149	1	in	in	ADP
cana-2055	149	2	the	the	DET
cana-2055	149	3	next	next	ADJ
cana-2055	149	4	step	step	NOUN
cana-2055	149	5	,	,	PUNCT
cana-2055	149	6	the	the	DET
cana-2055	149	7	eigenvectors	eigenvector	NOUN
cana-2055	149	8	of	of	ADP
cana-2055	149	9	the	the	DET
cana-2055	149	10	covariance	covariance	NOUN
cana-2055	149	11	matrix	matrix	NOUN
cana-2055	149	12	are	be	AUX
cana-2055	149	13	arranged	arrange	VERB
cana-2055	149	14	in	in	ADP
cana-2055	149	15	descending	descend	VERB
cana-2055	149	16	order	order	NOUN
cana-2055	149	17	of	of	ADP
cana-2055	149	18	eigenvalue	eigenvalue	NOUN
cana-2055	149	19	.	.	PUNCT
cana-2055	150	1	in	in	ADP
cana-2055	150	2	this	this	DET
cana-2055	150	3	list	list	NOUN
cana-2055	150	4	,	,	PUNCT
cana-2055	150	5	the	the	DET
cana-2055	150	6	components	component	NOUN
cana-2055	150	7	are	be	AUX
cana-2055	150	8	arranged	arrange	VERB
cana-2055	150	9	in	in	ADP
cana-2055	150	10	decreasing	decrease	VERB
cana-2055	150	11	order	order	NOUN
cana-2055	150	12	of	of	ADP
cana-2055	150	13	significance	significance	NOUN
cana-2055	150	14	.	.	PUNCT
cana-2055	151	1	therefore	therefore	ADV
cana-2055	151	2	,	,	PUNCT
cana-2055	151	3	it	it	PRON
cana-2055	151	4	is	be	AUX
cana-2055	151	5	necessary	necessary	ADJ
cana-2055	151	6	to	to	PART
cana-2055	151	7	attend	attend	VERB
cana-2055	151	8	to	to	ADP
cana-2055	151	9	the	the	DET
cana-2055	151	10	less	less	ADV
cana-2055	151	11	important	important	ADJ
cana-2055	151	12	parts	part	NOUN
cana-2055	151	13	.	.	PUNCT
cana-2055	152	1	here	here	ADV
cana-2055	152	2	is	be	AUX
cana-2055	152	3	the	the	DET
cana-2055	152	4	mathematical	mathematical	ADJ
cana-2055	152	5	expression	expression	NOUN
cana-2055	152	6	:	:	PUNCT
cana-2055	152	7	communications	communication	NOUN
cana-2055	152	8	on	on	ADP
cana-2055	152	9	applied	apply	VERB
cana-2055	152	10	nonlinear	nonlinear	ADJ
cana-2055	152	11	analysis	analysis	NOUN
cana-2055	152	12	issn	issn	NOUN
cana-2055	152	13	:	:	PUNCT
cana-2055	152	14	1074	1074	NUM
cana-2055	152	15	-	-	PUNCT
cana-2055	152	16	133x	133x	NUM
cana-2055	152	17	vol	vol	NOUN
cana-2055	152	18	32	32	NUM
cana-2055	152	19	no	no	NOUN
cana-2055	152	20	.	.	NOUN
cana-2055	152	21	3	3	NUM
cana-2055	152	22	(	(	PUNCT
cana-2055	152	23	2025	2025	NUM
cana-2055	152	24	)	)	PUNCT
cana-2055	152	25	583	583	NUM
cana-2055	152	26	https://internationalpubls.com	https://internationalpubls.com	X
cana-2055	153	1	𝐷𝑅	𝐷𝑅	PROPN
cana-2055	153	2	→𝑠	→𝑠	PROPN
cana-2055	154	1	=	=	PRON
cana-2055	154	2	{	{	PUNCT
cana-2055	154	3	𝑚1	𝑚1	NOUN
cana-2055	154	4	→	→	SYM
cana-2055	154	5	,	,	PUNCT
cana-2055	154	6	𝑚2	𝑚2	PROPN
cana-2055	154	7	→	→	SYM
cana-2055	154	8	,	,	PUNCT
cana-2055	154	9	𝑚3	𝑚3	NOUN
cana-2055	154	10	→	→	SYM
cana-2055	154	11	,	,	PUNCT
cana-2055	154	12	……	……	PROPN
cana-2055	154	13	.	.	PUNCT
cana-2055	154	14	.	.	PUNCT
cana-2055	155	1	𝑚𝑛	𝑚𝑛	PRON
cana-2055	155	2	→	→	PUNCT
cana-2055	155	3	}	}	PUNCT
cana-2055	155	4	(	(	PUNCT
cana-2055	155	5	6	6	NUM
cana-2055	155	6	)	)	PUNCT
cana-2055	155	7	here	here	ADV
cana-2055	155	8	,	,	PUNCT
cana-2055	155	9	𝐷𝑅	𝐷𝑅	PROPN
cana-2055	155	10	→𝑠	→𝑠	PROPN
cana-2055	155	11	is	be	AUX
cana-2055	155	12	a	a	DET
cana-2055	155	13	collection	collection	NOUN
cana-2055	155	14	of	of	ADP
cana-2055	155	15	features	feature	NOUN
cana-2055	155	16	that	that	PRON
cana-2055	155	17	have	have	AUX
cana-2055	155	18	been	be	AUX
cana-2055	155	19	reduced	reduce	VERB
cana-2055	155	20	in	in	ADP
cana-2055	155	21	dimensionality	dimensionality	NOUN
cana-2055	155	22	and	and	CCONJ
cana-2055	155	23	include	include	VERB
cana-2055	155	24	important	important	ADJ
cana-2055	155	25	eigenvectors	eigenvector	NOUN
cana-2055	155	26	,	,	PUNCT
cana-2055	155	27	and	and	CCONJ
cana-2055	155	28	n	n	CCONJ
cana-2055	155	29	→	→	PUNCT
cana-2055	155	30	represents	represent	VERB
cana-2055	155	31	the	the	DET
cana-2055	155	32	total	total	ADJ
cana-2055	155	33	number	number	NOUN
cana-2055	155	34	of	of	ADP
cana-2055	155	35	dimensions	dimension	NOUN
cana-2055	155	36	that	that	PRON
cana-2055	155	37	have	have	AUX
cana-2055	155	38	been	be	AUX
cana-2055	155	39	chosen	choose	VERB
cana-2055	155	40	.	.	PUNCT
cana-2055	156	1	3.3	3.3	NUM
cana-2055	156	2	predicting	predict	VERB
cana-2055	156	3	yields	yield	NOUN
cana-2055	156	4	of	of	ADP
cana-2055	156	5	crops	crop	NOUN
cana-2055	156	6	the	the	DET
cana-2055	156	7	following	follow	VERB
cana-2055	156	8	procedure	procedure	NOUN
cana-2055	156	9	,	,	PUNCT
cana-2055	156	10	cyp	cyp	ADJ
cana-2055	156	11	,	,	PUNCT
cana-2055	156	12	is	be	AUX
cana-2055	156	13	performed	perform	VERB
cana-2055	156	14	using	use	VERB
cana-2055	156	15	a	a	DET
cana-2055	156	16	weight	weight	NOUN
cana-2055	156	17	-	-	PUNCT
cana-2055	156	18	tuned	tune	VERB
cana-2055	156	19	deep	deep	ADJ
cana-2055	156	20	convolutional	convolutional	ADJ
cana-2055	156	21	neural	neural	ADJ
cana-2055	156	22	network	network	NOUN
cana-2055	156	23	.	.	PUNCT
cana-2055	157	1	each	each	PRON
cana-2055	157	2	of	of	ADP
cana-2055	157	3	the	the	DET
cana-2055	157	4	many	many	ADJ
cana-2055	157	5	layers	layer	NOUN
cana-2055	157	6	that	that	PRON
cana-2055	157	7	make	make	VERB
cana-2055	157	8	up	up	ADP
cana-2055	157	9	a	a	DET
cana-2055	157	10	dcnn	dcnn	PROPN
cana-2055	157	11	performs	perform	VERB
cana-2055	157	12	a	a	DET
cana-2055	157	13	convolutional	convolutional	ADJ
cana-2055	157	14	transform	transform	NOUN
cana-2055	157	15	calculation	calculation	NOUN
cana-2055	157	16	before	before	ADP
cana-2055	157	17	going	go	VERB
cana-2055	157	18	on	on	ADP
cana-2055	157	19	to	to	ADP
cana-2055	157	20	the	the	DET
cana-2055	157	21	next	next	ADJ
cana-2055	157	22	layer	layer	NOUN
cana-2055	157	23	,	,	PUNCT
cana-2055	157	24	which	which	PRON
cana-2055	157	25	handles	handle	VERB
cana-2055	157	26	nonlinearities	nonlinearitie	NOUN
cana-2055	157	27	and	and	CCONJ
cana-2055	157	28	pooling	pool	VERB
cana-2055	157	29	operators	operator	NOUN
cana-2055	157	30	.	.	PUNCT
cana-2055	158	1	backpropagation	backpropagation	NOUN
cana-2055	158	2	training	training	NOUN
cana-2055	158	3	in	in	ADP
cana-2055	158	4	dcnn	dcnn	PROPN
cana-2055	158	5	makes	make	VERB
cana-2055	158	6	use	use	NOUN
cana-2055	158	7	of	of	ADP
cana-2055	158	8	random	random	ADJ
cana-2055	158	9	weight	weight	NOUN
cana-2055	158	10	and	and	CCONJ
cana-2055	158	11	bias	bias	NOUN
cana-2055	158	12	values	value	NOUN
cana-2055	158	13	,	,	PUNCT
cana-2055	158	14	increasing	increase	VERB
cana-2055	158	15	the	the	DET
cana-2055	158	16	likelihood	likelihood	NOUN
cana-2055	158	17	of	of	ADP
cana-2055	158	18	suboptimal	suboptimal	ADJ
cana-2055	158	19	outputs	output	NOUN
cana-2055	158	20	and	and	CCONJ
cana-2055	158	21	larger	large	ADJ
cana-2055	158	22	prediction	prediction	NOUN
cana-2055	158	23	loss	loss	NOUN
cana-2055	158	24	.	.	PUNCT
cana-2055	159	1	to	to	PART
cana-2055	159	2	improve	improve	VERB
cana-2055	159	3	detection	detection	NOUN
cana-2055	159	4	accuracy	accuracy	NOUN
cana-2055	159	5	and	and	CCONJ
cana-2055	159	6	decrease	decrease	VERB
cana-2055	159	7	network	network	NOUN
cana-2055	159	8	loss	loss	NOUN
cana-2055	159	9	,	,	PUNCT
cana-2055	159	10	it	it	PRON
cana-2055	159	11	is	be	AUX
cana-2055	159	12	vital	vital	ADJ
cana-2055	159	13	to	to	PART
cana-2055	159	14	tune	tune	VERB
cana-2055	159	15	the	the	DET
cana-2055	159	16	network	network	NOUN
cana-2055	159	17	's	's	PART
cana-2055	159	18	weights	weight	NOUN
cana-2055	159	19	and	and	CCONJ
cana-2055	159	20	biases	bias	NOUN
cana-2055	159	21	correctly	correctly	ADV
cana-2055	159	22	.	.	PUNCT
cana-2055	160	1	consequently	consequently	ADV
cana-2055	160	2	,	,	PUNCT
cana-2055	160	3	the	the	DET
cana-2055	160	4	suggested	suggest	VERB
cana-2055	160	5	method	method	NOUN
cana-2055	160	6	uses	use	VERB
cana-2055	160	7	an	an	DET
cana-2055	160	8	ewoa	ewoa	NOUN
cana-2055	160	9	to	to	PART
cana-2055	160	10	establish	establish	VERB
cana-2055	160	11	the	the	DET
cana-2055	160	12	bias	bias	NOUN
cana-2055	160	13	and	and	CCONJ
cana-2055	160	14	weights	weight	NOUN
cana-2055	160	15	of	of	ADP
cana-2055	160	16	the	the	DET
cana-2055	160	17	network	network	NOUN
cana-2055	160	18	,	,	PUNCT
cana-2055	160	19	which	which	PRON
cana-2055	160	20	minimises	minimise	VERB
cana-2055	160	21	the	the	DET
cana-2055	160	22	network	network	NOUN
cana-2055	160	23	's	's	PART
cana-2055	160	24	prediction	prediction	NOUN
cana-2055	160	25	loss	loss	NOUN
cana-2055	160	26	and	and	CCONJ
cana-2055	160	27	vanishing	vanish	VERB
cana-2055	160	28	gradient	gradient	ADJ
cana-2055	160	29	saturation	saturation	NOUN
cana-2055	160	30	for	for	ADP
cana-2055	160	31	cyp	cyp	ADJ
cana-2055	160	32	,	,	PUNCT
cana-2055	160	33	leading	lead	VERB
cana-2055	160	34	to	to	ADP
cana-2055	160	35	optimum	optimum	ADJ
cana-2055	160	36	outcomes	outcome	NOUN
cana-2055	160	37	.	.	PUNCT
cana-2055	161	1	the	the	DET
cana-2055	161	2	overall	overall	ADJ
cana-2055	161	3	architecture	architecture	NOUN
cana-2055	161	4	of	of	ADP
cana-2055	161	5	dcnn	dcnn	PROPN
cana-2055	161	6	is	be	AUX
cana-2055	161	7	shown	show	VERB
cana-2055	161	8	in	in	ADP
cana-2055	161	9	fig	fig	NOUN
cana-2055	161	10	.	.	PUNCT
cana-2055	162	1	2	2	X
cana-2055	162	2	.	.	X
cana-2055	162	3	figure	figure	NOUN
cana-2055	162	4	.	.	PUNCT
cana-2055	163	1	2	2	NUM
cana-2055	163	2	overall	overall	ADJ
cana-2055	163	3	architecture	architecture	NOUN
cana-2055	163	4	of	of	ADP
cana-2055	163	5	dcnn	dcnn	PROPN
cana-2055	163	6	the	the	DET
cana-2055	163	7	'	'	PUNCT
cana-2055	163	8	4	4	NUM
cana-2055	163	9	'	'	PART
cana-2055	163	10	layers	layer	NOUN
cana-2055	163	11	that	that	PRON
cana-2055	163	12	make	make	VERB
cana-2055	163	13	up	up	ADP
cana-2055	163	14	a	a	DET
cana-2055	163	15	dcnn	dcnn	ADJ
cana-2055	163	16	architecture	architecture	NOUN
cana-2055	163	17	are	be	AUX
cana-2055	163	18	the	the	DET
cana-2055	163	19	fully	fully	ADV
cana-2055	163	20	linked	link	VERB
cana-2055	163	21	layer	layer	NOUN
cana-2055	163	22	,	,	PUNCT
cana-2055	163	23	activation	activation	NOUN
cana-2055	163	24	,	,	PUNCT
cana-2055	163	25	pooling	pooling	NOUN
cana-2055	163	26	,	,	PUNCT
cana-2055	163	27	and	and	CCONJ
cana-2055	163	28	convolution	convolution	NOUN
cana-2055	163	29	.	.	PUNCT
cana-2055	164	1	for	for	ADP
cana-2055	164	2	backpropagation	backpropagation	NOUN
cana-2055	164	3	training	training	NOUN
cana-2055	164	4	,	,	PUNCT
cana-2055	164	5	dcnn	dcnn	PROPN
cana-2055	164	6	uses	use	VERB
cana-2055	164	7	a	a	DET
cana-2055	164	8	randomly	randomly	ADV
cana-2055	164	9	selected	select	VERB
cana-2055	164	10	network	network	NOUN
cana-2055	164	11	weight	weight	NOUN
cana-2055	164	12	and	and	CCONJ
cana-2055	164	13	biases	bias	NOUN
cana-2055	164	14	.	.	PUNCT
cana-2055	165	1	the	the	DET
cana-2055	165	2	suggested	suggest	VERB
cana-2055	165	3	method	method	NOUN
cana-2055	165	4	improves	improve	VERB
cana-2055	165	5	the	the	DET
cana-2055	165	6	network	network	NOUN
cana-2055	165	7	's	's	PART
cana-2055	165	8	yield	yield	NOUN
cana-2055	165	9	prediction	prediction	NOUN
cana-2055	165	10	performance	performance	NOUN
cana-2055	165	11	by	by	ADP
cana-2055	165	12	selecting	select	VERB
cana-2055	165	13	them	they	PRON
cana-2055	165	14	optimally	optimally	ADV
cana-2055	165	15	using	use	VERB
cana-2055	165	16	ewoa	ewoa	ADJ
cana-2055	165	17	,	,	PUNCT
cana-2055	165	18	as	as	SCONJ
cana-2055	165	19	opposed	oppose	VERB
cana-2055	165	20	to	to	PART
cana-2055	165	21	randomly	randomly	VERB
cana-2055	165	22	.	.	PUNCT
cana-2055	166	1	the	the	DET
cana-2055	166	2	woa	woa	NOUN
cana-2055	166	3	is	be	AUX
cana-2055	166	4	an	an	DET
cana-2055	166	5	innovative	innovative	ADJ
cana-2055	166	6	swarm	swarm	NOUN
cana-2055	166	7	-	-	PUNCT
cana-2055	166	8	based	base	VERB
cana-2055	166	9	optimisation	optimisation	NOUN
cana-2055	166	10	system	system	NOUN
cana-2055	166	11	that	that	PRON
cana-2055	166	12	takes	take	VERB
cana-2055	166	13	cues	cue	NOUN
cana-2055	166	14	from	from	ADP
cana-2055	166	15	the	the	DET
cana-2055	166	16	way	way	NOUN
cana-2055	166	17	humpback	humpback	NOUN
cana-2055	166	18	whales	whale	NOUN
cana-2055	166	19	hunt	hunt	NOUN
cana-2055	166	20	.	.	PUNCT
cana-2055	167	1	it	it	PRON
cana-2055	167	2	takes	take	VERB
cana-2055	167	3	three	three	NUM
cana-2055	167	4	operators	operator	NOUN
cana-2055	167	5	—	—	PUNCT
cana-2055	167	6	encircling	encircle	VERB
cana-2055	167	7	,	,	PUNCT
cana-2055	167	8	studying	study	VERB
cana-2055	167	9	,	,	PUNCT
cana-2055	167	10	and	and	CCONJ
cana-2055	167	11	attacking	attack	VERB
cana-2055	167	12	—	—	PUNCT
cana-2055	167	13	for	for	SCONJ
cana-2055	167	14	woa	woa	INTJ
cana-2055	167	15	to	to	PART
cana-2055	167	16	locate	locate	VERB
cana-2055	167	17	prey	prey	NOUN
cana-2055	167	18	.	.	PUNCT
cana-2055	168	1	a	a	DET
cana-2055	168	2	reduction	reduction	NOUN
cana-2055	168	3	in	in	ADP
cana-2055	168	4	converging	converge	VERB
cana-2055	168	5	efficiency	efficiency	NOUN
cana-2055	168	6	and	and	CCONJ
cana-2055	168	7	communications	communication	NOUN
cana-2055	168	8	on	on	ADP
cana-2055	168	9	applied	apply	VERB
cana-2055	168	10	nonlinear	nonlinear	ADJ
cana-2055	168	11	analysis	analysis	NOUN
cana-2055	168	12	issn	issn	NOUN
cana-2055	168	13	:	:	PUNCT
cana-2055	168	14	1074	1074	NUM
cana-2055	168	15	-	-	PUNCT
cana-2055	168	16	133x	133x	NUM
cana-2055	168	17	vol	vol	NOUN
cana-2055	168	18	32	32	NUM
cana-2055	168	19	no	no	NOUN
cana-2055	168	20	.	.	NOUN
cana-2055	168	21	3	3	NUM
cana-2055	168	22	(	(	PUNCT
cana-2055	168	23	2025	2025	NUM
cana-2055	168	24	)	)	PUNCT
cana-2055	168	25	584	584	NUM
cana-2055	168	26	https://internationalpubls.com	https://internationalpubls.com	X
cana-2055	168	27	algorithm	algorithm	NOUN
cana-2055	168	28	quality	quality	NOUN
cana-2055	168	29	leading	lead	VERB
cana-2055	168	30	to	to	ADP
cana-2055	168	31	optimum	optimum	ADJ
cana-2055	168	32	global	global	ADJ
cana-2055	168	33	solutions	solution	NOUN
cana-2055	168	34	is	be	AUX
cana-2055	168	35	seen	see	VERB
cana-2055	168	36	when	when	SCONJ
cana-2055	168	37	whales	whale	NOUN
cana-2055	168	38	are	be	AUX
cana-2055	168	39	initialised	initialise	VERB
cana-2055	168	40	with	with	ADP
cana-2055	168	41	a	a	DET
cana-2055	168	42	random	random	ADJ
cana-2055	168	43	population	population	NOUN
cana-2055	168	44	in	in	ADP
cana-2055	168	45	their	their	PRON
cana-2055	168	46	early	early	ADJ
cana-2055	168	47	stages	stage	NOUN
cana-2055	168	48	.	.	PUNCT
cana-2055	169	1	furthermore	furthermore	ADV
cana-2055	169	2	,	,	PUNCT
cana-2055	169	3	the	the	DET
cana-2055	169	4	algorithm	algorithm	NOUN
cana-2055	169	5	's	's	PART
cana-2055	169	6	speed	speed	NOUN
cana-2055	169	7	drops	drop	NOUN
cana-2055	169	8	as	as	SCONJ
cana-2055	169	9	it	it	PRON
cana-2055	169	10	proceeds	proceed	VERB
cana-2055	169	11	through	through	ADP
cana-2055	169	12	the	the	DET
cana-2055	169	13	search	search	NOUN
cana-2055	169	14	process	process	NOUN
cana-2055	169	15	because	because	SCONJ
cana-2055	169	16	it	it	PRON
cana-2055	169	17	becomes	become	VERB
cana-2055	169	18	trapped	trap	VERB
cana-2055	169	19	on	on	ADP
cana-2055	169	20	optimum	optimum	ADJ
cana-2055	169	21	local	local	ADJ
cana-2055	169	22	problems	problem	NOUN
cana-2055	169	23	.	.	PUNCT
cana-2055	170	1	starting	start	VERB
cana-2055	170	2	with	with	ADP
cana-2055	170	3	a	a	DET
cana-2055	170	4	tent	tent	NOUN
cana-2055	170	5	chaotic	chaotic	ADJ
cana-2055	170	6	map	map	NOUN
cana-2055	170	7	enhances	enhance	VERB
cana-2055	170	8	the	the	DET
cana-2055	170	9	algorithm	algorithm	NOUN
cana-2055	170	10	's	's	PART
cana-2055	170	11	convergence	convergence	NOUN
cana-2055	170	12	efficiency	efficiency	NOUN
cana-2055	170	13	and	and	CCONJ
cana-2055	170	14	variety	variety	NOUN
cana-2055	170	15	of	of	ADP
cana-2055	170	16	the	the	DET
cana-2055	170	17	population	population	NOUN
cana-2055	170	18	,	,	PUNCT
cana-2055	170	19	which	which	PRON
cana-2055	170	20	is	be	AUX
cana-2055	170	21	why	why	SCONJ
cana-2055	170	22	it	it	PRON
cana-2055	170	23	is	be	AUX
cana-2055	170	24	recommended	recommend	VERB
cana-2055	170	25	to	to	PART
cana-2055	170	26	utilise	utilise	VERB
cana-2055	170	27	this	this	DET
cana-2055	170	28	approach	approach	NOUN
cana-2055	170	29	.	.	PUNCT
cana-2055	171	1	also	also	ADV
cana-2055	171	2	,	,	PUNCT
cana-2055	171	3	the	the	DET
cana-2055	171	4	system	system	NOUN
cana-2055	171	5	ca	can	AUX
cana-2055	171	6	n't	not	PART
cana-2055	171	7	identify	identify	VERB
cana-2055	171	8	locally	locally	ADV
cana-2055	171	9	optimum	optimum	ADJ
cana-2055	171	10	solutions	solution	NOUN
cana-2055	171	11	since	since	SCONJ
cana-2055	171	12	the	the	DET
cana-2055	171	13	levy	levy	NOUN
cana-2055	171	14	flying	fly	VERB
cana-2055	171	15	mechanism	mechanism	NOUN
cana-2055	171	16	is	be	AUX
cana-2055	171	17	used	use	VERB
cana-2055	171	18	to	to	PART
cana-2055	171	19	update	update	VERB
cana-2055	171	20	the	the	DET
cana-2055	171	21	whales	whale	NOUN
cana-2055	171	22	'	'	PART
cana-2055	171	23	positions	position	NOUN
cana-2055	171	24	later	later	ADV
cana-2055	171	25	on	on	ADV
cana-2055	171	26	in	in	ADP
cana-2055	171	27	the	the	DET
cana-2055	171	28	algorithm	algorithm	NOUN
cana-2055	171	29	.	.	PUNCT
cana-2055	172	1	both	both	DET
cana-2055	172	2	of	of	ADP
cana-2055	172	3	these	these	DET
cana-2055	172	4	improvements	improvement	NOUN
cana-2055	172	5	to	to	ADP
cana-2055	172	6	traditional	traditional	ADJ
cana-2055	172	7	woa	woa	INTJ
cana-2055	172	8	are	be	AUX
cana-2055	172	9	known	know	VERB
cana-2055	172	10	as	as	ADP
cana-2055	172	11	ewoa	ewoa	ADJ
cana-2055	172	12	.	.	PUNCT
cana-2055	173	1	in	in	ADP
cana-2055	173	2	order	order	NOUN
cana-2055	173	3	to	to	PART
cana-2055	173	4	extract	extract	VERB
cana-2055	173	5	features	feature	NOUN
cana-2055	173	6	,	,	PUNCT
cana-2055	173	7	vwcnn	vwcnn	PROPN
cana-2055	173	8	uses	use	VERB
cana-2055	173	9	a	a	DET
cana-2055	173	10	deep	deep	ADJ
cana-2055	173	11	learning	learning	NOUN
cana-2055	173	12	-	-	PUNCT
cana-2055	173	13	based	base	VERB
cana-2055	173	14	approach	approach	NOUN
cana-2055	173	15	.	.	PUNCT
cana-2055	174	1	with	with	ADP
cana-2055	174	2	relu	relu	NOUN
cana-2055	174	3	connecting	connect	VERB
cana-2055	174	4	each	each	DET
cana-2055	174	5	convolutional	convolutional	ADJ
cana-2055	174	6	layer	layer	NOUN
cana-2055	174	7	to	to	ADP
cana-2055	174	8	an	an	DET
cana-2055	174	9	activation	activation	NOUN
cana-2055	174	10	layer	layer	NOUN
cana-2055	174	11	,	,	PUNCT
cana-2055	174	12	the	the	DET
cana-2055	174	13	network	network	NOUN
cana-2055	174	14	has	have	VERB
cana-2055	174	15	a	a	DET
cana-2055	174	16	total	total	NOUN
cana-2055	174	17	of	of	ADP
cana-2055	174	18	fifteen	fifteen	NUM
cana-2055	174	19	layers	layer	NOUN
cana-2055	174	20	:	:	PUNCT
cana-2055	174	21	five	five	NUM
cana-2055	174	22	convolutional	convolutional	ADJ
cana-2055	174	23	,	,	PUNCT
cana-2055	174	24	five	five	NUM
cana-2055	174	25	pooling	pooling	NOUN
cana-2055	174	26	,	,	PUNCT
cana-2055	174	27	and	and	CCONJ
cana-2055	174	28	three	three	NUM
cana-2055	174	29	fully	fully	ADV
cana-2055	174	30	linked	link	VERB
cana-2055	174	31	.	.	PUNCT
cana-2055	175	1	each	each	DET
cana-2055	175	2	map	map	NOUN
cana-2055	175	3	of	of	ADP
cana-2055	175	4	features	feature	NOUN
cana-2055	175	5	is	be	AUX
cana-2055	175	6	6	6	NUM
cana-2055	175	7	x	x	SYM
cana-2055	175	8	6	6	NUM
cana-2055	175	9	,	,	PUNCT
cana-2055	175	10	with	with	ADP
cana-2055	175	11	a	a	DET
cana-2055	175	12	total	total	NOUN
cana-2055	175	13	of	of	ADP
cana-2055	175	14	128	128	NUM
cana-2055	175	15	feature	feature	NOUN
cana-2055	175	16	maps	map	NOUN
cana-2055	175	17	,	,	PUNCT
cana-2055	175	18	resulting	result	VERB
cana-2055	175	19	in	in	ADP
cana-2055	175	20	an	an	DET
cana-2055	175	21	output	output	NOUN
cana-2055	175	22	size	size	NOUN
cana-2055	175	23	of	of	ADP
cana-2055	175	24	6	6	NUM
cana-2055	175	25	×	×	NOUN
cana-2055	175	26	6	6	NUM
cana-2055	175	27	×	×	NOUN
cana-2055	175	28	128	128	NUM
cana-2055	175	29	after	after	ADP
cana-2055	175	30	5th	5th	ADJ
cana-2055	175	31	pooling	pooling	NOUN
cana-2055	175	32	and	and	CCONJ
cana-2055	175	33	convolution	convolution	NOUN
cana-2055	175	34	layers	layer	NOUN
cana-2055	175	35	,	,	PUNCT
cana-2055	175	36	from	from	ADP
cana-2055	175	37	an	an	DET
cana-2055	175	38	input	input	NOUN
cana-2055	175	39	picture	picture	NOUN
cana-2055	175	40	with	with	ADP
cana-2055	175	41	dimensions	dimension	NOUN
cana-2055	175	42	of	of	ADP
cana-2055	175	43	200	200	NUM
cana-2055	175	44	×	×	NOUN
cana-2055	175	45	200	200	NUM
cana-2055	175	46	×	×	NOUN
cana-2055	175	47	3	3	NUM
cana-2055	175	48	.	.	PUNCT
cana-2055	176	1	following	follow	VERB
cana-2055	176	2	the	the	DET
cana-2055	176	3	first	first	ADJ
cana-2055	176	4	two	two	NUM
cana-2055	176	5	completely	completely	ADV
cana-2055	176	6	linked	link	VERB
cana-2055	176	7	layers	layer	NOUN
cana-2055	176	8	,	,	PUNCT
cana-2055	176	9	a	a	DET
cana-2055	176	10	vector	vector	NOUN
cana-2055	176	11	of	of	ADP
cana-2055	176	12	1024	1024	NUM
cana-2055	176	13	dimensions	dimension	NOUN
cana-2055	176	14	is	be	AUX
cana-2055	176	15	produced	produce	VERB
cana-2055	176	16	as	as	ADP
cana-2055	176	17	an	an	DET
cana-2055	176	18	output	output	NOUN
cana-2055	176	19	.	.	PUNCT
cana-2055	177	1	the	the	DET
cana-2055	177	2	soft	soft	ADJ
cana-2055	177	3	max	max	PROPN
cana-2055	177	4	classifier	classifier	NOUN
cana-2055	177	5	takes	take	VERB
cana-2055	177	6	a	a	DET
cana-2055	177	7	5	5	NUM
cana-2055	177	8	-	-	PUNCT
cana-2055	177	9	dimensional	dimensional	ADJ
cana-2055	177	10	vector	vector	NOUN
cana-2055	177	11	as	as	ADP
cana-2055	177	12	input	input	NOUN
cana-2055	177	13	and	and	CCONJ
cana-2055	177	14	output	output	NOUN
cana-2055	177	15	after	after	ADP
cana-2055	177	16	the	the	DET
cana-2055	177	17	last	last	ADJ
cana-2055	177	18	fully	fully	ADV
cana-2055	177	19	connected	connect	VERB
cana-2055	177	20	layer	layer	NOUN
cana-2055	177	21	.	.	PUNCT
cana-2055	178	1	utilising	utilise	VERB
cana-2055	178	2	a	a	DET
cana-2055	178	3	chaotic	chaotic	ADJ
cana-2055	178	4	tent	tent	NOUN
cana-2055	178	5	map	map	NOUN
cana-2055	178	6	,	,	PUNCT
cana-2055	178	7	the	the	DET
cana-2055	178	8	method	method	NOUN
cana-2055	178	9	first	first	ADV
cana-2055	178	10	initialises	initialise	VERB
cana-2055	178	11	the	the	DET
cana-2055	178	12	number	number	NOUN
cana-2055	178	13	of	of	ADP
cana-2055	178	14	people	people	NOUN
cana-2055	178	15	in	in	ADP
cana-2055	178	16	the	the	DET
cana-2055	178	17	search	search	NOUN
cana-2055	178	18	space	space	NOUN
cana-2055	178	19	.	.	PUNCT
cana-2055	179	1	tent	tent	NOUN
cana-2055	179	2	chaotic	chaotic	ADJ
cana-2055	179	3	maps	map	NOUN
cana-2055	179	4	lessen	lessen	VERB
cana-2055	179	5	the	the	DET
cana-2055	179	6	impact	impact	NOUN
cana-2055	179	7	of	of	ADP
cana-2055	179	8	the	the	DET
cana-2055	179	9	original	original	ADJ
cana-2055	179	10	population	population	NOUN
cana-2055	179	11	distribution	distribution	NOUN
cana-2055	179	12	while	while	SCONJ
cana-2055	179	13	increasing	increase	VERB
cana-2055	179	14	search	search	NOUN
cana-2055	179	15	speed	speed	NOUN
cana-2055	179	16	and	and	CCONJ
cana-2055	179	17	improving	improve	VERB
cana-2055	179	18	uniformity	uniformity	NOUN
cana-2055	179	19	of	of	ADP
cana-2055	179	20	population	population	NOUN
cana-2055	179	21	dispersion	dispersion	NOUN
cana-2055	179	22	.	.	PUNCT
cana-2055	180	1	it	it	PRON
cana-2055	180	2	is	be	AUX
cana-2055	180	3	expressed	express	VERB
cana-2055	180	4	as	as	SCONJ
cana-2055	180	5	follows	follow	VERB
cana-2055	180	6	:	:	PUNCT
cana-2055	180	7	𝑍𝜏+1	𝑍𝜏+1	X
cana-2055	180	8	→	→	SYM
cana-2055	180	9	=	=	SYM
cana-2055	180	10	{	{	PUNCT
cana-2055	180	11	2	2	NUM
cana-2055	180	12	𝑍𝜏	𝑍𝜏	PROPN
cana-2055	180	13	→	→	SYM
cana-2055	180	14	0	0	NUM
cana-2055	180	15	≤	≤	NUM
cana-2055	180	16	𝑍	𝑍	PROPN
cana-2055	180	17	→	→	SYM
cana-2055	180	18	≤	≤	NUM
cana-2055	180	19	0.5	0.5	NUM
cana-2055	180	20	2(1	2(1	NUM
cana-2055	180	21	−	−	PROPN
cana-2055	181	1	𝑍𝜏	𝑍𝜏	PROPN
cana-2055	181	2	→	→	SYM
cana-2055	181	3	)	)	PUNCT
cana-2055	181	4	,	,	PUNCT
cana-2055	181	5	0.5	0.5	NUM
cana-2055	181	6	<	<	X
cana-2055	181	7	𝑍	𝑍	PROPN
cana-2055	181	8	→	→	SYM
cana-2055	181	9	≤	≤	NUM
cana-2055	181	10	1	1	NUM
cana-2055	181	11	(	(	PUNCT
cana-2055	181	12	7	7	NUM
cana-2055	181	13	)	)	PUNCT
cana-2055	181	14	in	in	ADP
cana-2055	181	15	this	this	DET
cana-2055	181	16	context	context	NOUN
cana-2055	181	17	,	,	PUNCT
cana-2055	181	18	𝑍𝜏+1	𝑍𝜏+1	PUNCT
cana-2055	181	19	→	→	SYM
cana-2055	181	20	denotes	denote	VERB
cana-2055	181	21	the	the	DET
cana-2055	181	22	initial	initial	ADJ
cana-2055	181	23	population	population	NOUN
cana-2055	181	24	of	of	ADP
cana-2055	181	25	whales	whale	NOUN
cana-2055	181	26	as	as	SCONJ
cana-2055	181	27	determined	determine	VERB
cana-2055	181	28	by	by	ADP
cana-2055	181	29	a	a	DET
cana-2055	181	30	tent	tent	NOUN
cana-2055	181	31	map	map	NOUN
cana-2055	181	32	,	,	PUNCT
cana-2055	181	33	whereas	whereas	SCONJ
cana-2055	181	34	𝑍𝜏	𝑍𝜏	PROPN
cana-2055	181	35	→	→	PUNCT
cana-2055	181	36	represents	represent	VERB
cana-2055	181	37	the	the	DET
cana-2055	181	38	randomised	randomised	ADJ
cana-2055	181	39	populations	population	NOUN
cana-2055	181	40	.	.	PUNCT
cana-2055	182	1	next	next	ADV
cana-2055	182	2	,	,	PUNCT
cana-2055	182	3	the	the	DET
cana-2055	182	4	classifier	classifier	NOUN
cana-2055	182	5	's	's	PART
cana-2055	182	6	mean	mean	ADJ
cana-2055	182	7	square	square	ADJ
cana-2055	182	8	error	error	NOUN
cana-2055	182	9	is	be	AUX
cana-2055	182	10	used	use	VERB
cana-2055	182	11	to	to	PART
cana-2055	182	12	estimate	estimate	VERB
cana-2055	182	13	fitness	fitness	NOUN
cana-2055	182	14	(	(	PUNCT
cana-2055	182	15	𝐹𝑁	𝐹𝑁	PROPN
cana-2055	182	16	→	→	SYM
cana-2055	182	17	𝑐𝑎𝑙	𝑐𝑎𝑙	NOUN
cana-2055	182	18	)	)	PUNCT
cana-2055	182	19	of	of	ADP
cana-2055	182	20	the	the	DET
cana-2055	182	21	whale	whale	NOUN
cana-2055	182	22	in	in	ADP
cana-2055	182	23	the	the	DET
cana-2055	182	24	initialised	initialise	VERB
cana-2055	182	25	population	population	NOUN
cana-2055	182	26	.	.	PUNCT
cana-2055	183	1	to	to	PART
cana-2055	183	2	calculate	calculate	VERB
cana-2055	183	3	mse	mse	PROPN
cana-2055	183	4	,	,	PUNCT
cana-2055	183	5	one	one	PRON
cana-2055	183	6	must	must	AUX
cana-2055	183	7	subtract	subtract	VERB
cana-2055	183	8	the	the	DET
cana-2055	183	9	classifier	classifier	NOUN
cana-2055	183	10	's	's	PART
cana-2055	183	11	anticipated	anticipate	VERB
cana-2055	183	12	output	output	NOUN
cana-2055	183	13	from	from	ADP
cana-2055	183	14	the	the	DET
cana-2055	183	15	actual	actual	ADJ
cana-2055	183	16	output	output	NOUN
cana-2055	183	17	when	when	SCONJ
cana-2055	183	18	predicting	predict	VERB
cana-2055	183	19	yield	yield	NOUN
cana-2055	183	20	.	.	PUNCT
cana-2055	184	1	here	here	ADV
cana-2055	184	2	is	be	AUX
cana-2055	184	3	how	how	SCONJ
cana-2055	184	4	it	it	PRON
cana-2055	184	5	is	be	AUX
cana-2055	184	6	stated	state	VERB
cana-2055	184	7	:	:	PUNCT
cana-2055	184	8	𝐹𝑁	𝐹𝑁	PROPN
cana-2055	184	9	→	→	SYM
cana-2055	184	10	𝑐𝑎𝑙	𝑐𝑎𝑙	NOUN
cana-2055	184	11	=	=	SYM
cana-2055	184	12	𝑀𝑖𝑛	𝑀𝑖𝑛	PROPN
cana-2055	184	13	(	(	PUNCT
cana-2055	184	14	𝑀𝑆𝐸	𝑀𝑆𝐸	PROPN
cana-2055	184	15	)	)	PUNCT
cana-2055	184	16	(	(	PUNCT
cana-2055	184	17	8)	8)	NUM
cana-2055	184	18	𝑀𝑆𝐸	𝑀𝑆𝐸	NOUN
cana-2055	184	19	=	=	SYM
cana-2055	184	20	1	1	NUM
cana-2055	184	21	𝑑	𝑑	NOUN
cana-2055	184	22	∑(𝑞𝑣𝑎𝑙	∑(𝑞𝑣𝑎𝑙	PROPN
cana-2055	184	23	−	−	PROPN
cana-2055	184	24	𝑞𝑣𝑎𝑙	𝑞𝑣𝑎𝑙	PROPN
cana-2055	184	25	∗	∗	PROPN
cana-2055	184	26	)	)	PUNCT
cana-2055	184	27	(	(	PUNCT
cana-2055	184	28	9	9	X
cana-2055	184	29	)	)	PUNCT
cana-2055	184	30	𝑑	𝑑	NOUN
cana-2055	184	31	𝑝=1	𝑝=1	NOUN
cana-2055	184	32	where	where	SCONJ
cana-2055	184	33	d	d	PROPN
cana-2055	184	34	−	−	PROPN
cana-2055	184	35	is	be	AUX
cana-2055	184	36	the	the	DET
cana-2055	184	37	number	number	NOUN
cana-2055	184	38	of	of	ADP
cana-2055	184	39	samples	sample	NOUN
cana-2055	184	40	in	in	ADP
cana-2055	184	41	the	the	DET
cana-2055	184	42	training	training	NOUN
cana-2055	184	43	data	datum	NOUN
cana-2055	184	44	set	set	VERB
cana-2055	184	45	and	and	CCONJ
cana-2055	184	46	𝑞𝑣𝑎𝑙	𝑞𝑣𝑎𝑙	PROPN
cana-2055	184	47	and	and	CCONJ
cana-2055	184	48	𝑞𝑣𝑎𝑙	𝑞𝑣𝑎𝑙	PROPN
cana-2055	184	49	∗	∗	NOUN
cana-2055	184	50	are	be	AUX
cana-2055	184	51	the	the	DET
cana-2055	184	52	actual	actual	ADJ
cana-2055	184	53	and	and	CCONJ
cana-2055	184	54	predicted	predict	VERB
cana-2055	184	55	values	value	NOUN
cana-2055	184	56	of	of	ADP
cana-2055	184	57	the	the	DET
cana-2055	184	58	classifier	classifier	NOUN
cana-2055	184	59	,	,	PUNCT
cana-2055	184	60	respectively	respectively	ADV
cana-2055	184	61	.	.	PUNCT
cana-2055	185	1	after	after	ADP
cana-2055	185	2	that	that	PRON
cana-2055	185	3	,	,	PUNCT
cana-2055	185	4	you	you	PRON
cana-2055	185	5	may	may	AUX
cana-2055	185	6	find	find	VERB
cana-2055	185	7	out	out	ADP
cana-2055	185	8	where	where	SCONJ
cana-2055	185	9	the	the	DET
cana-2055	185	10	whales	whale	NOUN
cana-2055	185	11	are	be	AUX
cana-2055	185	12	and	and	CCONJ
cana-2055	185	13	encircle	encircle	VERB
cana-2055	185	14	them	they	PRON
cana-2055	185	15	.	.	PUNCT
cana-2055	186	1	in	in	ADP
cana-2055	186	2	the	the	DET
cana-2055	186	3	present	present	ADJ
cana-2055	186	4	population	population	NOUN
cana-2055	186	5	,	,	PUNCT
cana-2055	186	6	the	the	DET
cana-2055	186	7	whale	whale	NOUN
cana-2055	186	8	closest	close	ADJ
cana-2055	186	9	to	to	ADP
cana-2055	186	10	the	the	DET
cana-2055	186	11	prey	prey	NOUN
cana-2055	186	12	site	site	NOUN
cana-2055	186	13	is	be	AUX
cana-2055	186	14	deemed	deem	VERB
cana-2055	186	15	the	the	DET
cana-2055	186	16	best	good	ADJ
cana-2055	186	17	whale	whale	NOUN
cana-2055	186	18	𝑍∗	𝑍∗	NOUN
cana-2055	186	19	→	→	X
cana-2055	186	20	,	,	PUNCT
cana-2055	186	21	and	and	CCONJ
cana-2055	186	22	the	the	DET
cana-2055	186	23	positioning	positioning	NOUN
cana-2055	186	24	of	of	ADP
cana-2055	186	25	other	other	ADJ
cana-2055	186	26	whales	whale	NOUN
cana-2055	186	27	is	be	AUX
cana-2055	186	28	adjusted	adjust	VERB
cana-2055	186	29	accordingly	accordingly	ADV
cana-2055	186	30	.	.	PUNCT
cana-2055	187	1	𝐷𝑇	𝐷𝑇	PROPN
cana-2055	187	2	→	→	SYM
cana-2055	187	3	=	=	SYM
cana-2055	187	4	⃒𝛽	⃒𝛽	X
cana-2055	187	5	×	×	PROPN
cana-2055	187	6	𝑍∗	𝑍∗	PROPN
cana-2055	187	7	(	(	PUNCT
cana-2055	187	8	𝜏	𝜏	NOUN
cana-2055	187	9	)	)	PUNCT
cana-2055	187	10	−	−	NOUN
cana-2055	187	11	𝑍	𝑍	PROPN
cana-2055	187	12	→	→	SYM
cana-2055	187	13	(	(	PUNCT
cana-2055	187	14	𝜏	𝜏	NOUN
cana-2055	187	15	)	)	PUNCT
cana-2055	187	16	→	→	PUNCT
cana-2055	187	17	⃒	⃒	PROPN
cana-2055	187	18	(	(	PUNCT
cana-2055	187	19	10	10	NUM
cana-2055	187	20	)	)	PUNCT
cana-2055	187	21	𝑍	𝑍	NOUN
cana-2055	187	22	(	(	PUNCT
cana-2055	187	23	𝜏	𝜏	NOUN
cana-2055	187	24	+	+	NOUN
cana-2055	187	25	1	1	NUM
cana-2055	187	26	)	)	PUNCT
cana-2055	187	27	=	=	PUNCT
cana-2055	187	28	𝑍	𝑍	PROPN
cana-2055	187	29	∗(𝜏)−	∗(𝜏)−	PROPN
cana-2055	187	30	𝛼	𝛼	PRON
cana-2055	187	31	×	×	NOUN
cana-2055	187	32	→	→	SYM
cana-2055	187	33	𝐷𝑇	𝐷𝑇	PROPN
cana-2055	187	34	→	→	SYM
cana-2055	187	35	(	(	PUNCT
cana-2055	187	36	11	11	NUM
cana-2055	187	37	)	)	PUNCT
cana-2055	187	38	→	→	SYM
cana-2055	187	39	communications	communication	NOUN
cana-2055	187	40	on	on	ADP
cana-2055	187	41	applied	apply	VERB
cana-2055	187	42	nonlinear	nonlinear	ADJ
cana-2055	187	43	analysis	analysis	NOUN
cana-2055	187	44	issn	issn	NOUN
cana-2055	187	45	:	:	PUNCT
cana-2055	187	46	1074	1074	NUM
cana-2055	187	47	-	-	PUNCT
cana-2055	187	48	133x	133x	NUM
cana-2055	187	49	vol	vol	NOUN
cana-2055	187	50	32	32	NUM
cana-2055	187	51	no	no	NOUN
cana-2055	187	52	.	.	NOUN
cana-2055	187	53	3	3	NUM
cana-2055	187	54	(	(	PUNCT
cana-2055	187	55	2025	2025	NUM
cana-2055	187	56	)	)	PUNCT
cana-2055	187	57	585	585	NUM
cana-2055	187	58	https://internationalpubls.com	https://internationalpubls.com	X
cana-2055	187	59	the	the	DET
cana-2055	187	60	distance	distance	NOUN
cana-2055	187	61	between	between	ADP
cana-2055	187	62	the	the	DET
cana-2055	187	63	whale	whale	NOUN
cana-2055	187	64	𝑍	𝑍	NOUN
cana-2055	187	65	→	→	SYM
cana-2055	187	66	(	(	PUNCT
cana-2055	187	67	𝜏	𝜏	NOUN
cana-2055	187	68	)	)	PUNCT
cana-2055	187	69	and	and	CCONJ
cana-2055	187	70	the	the	DET
cana-2055	187	71	prey	prey	NOUN
cana-2055	187	72	𝑍∗	𝑍∗	PROPN
cana-2055	187	73	(	(	PUNCT
cana-2055	187	74	𝜏	𝜏	NOUN
cana-2055	187	75	)	)	PUNCT
cana-2055	187	76	→	→	PUNCT
cana-2055	187	77	is	be	AUX
cana-2055	187	78	represented	represent	VERB
cana-2055	187	79	by	by	ADP
cana-2055	187	80	𝐷𝑇	𝐷𝑇	PROPN
cana-2055	187	81	→	→	PUNCT
cana-2055	187	82	,	,	PUNCT
cana-2055	187	83	and	and	CCONJ
cana-2055	187	84	τ	τ	PROPN
cana-2055	187	85	represents	represent	VERB
cana-2055	187	86	the	the	DET
cana-2055	187	87	current	current	ADJ
cana-2055	187	88	iteration	iteration	NOUN
cana-2055	187	89	.	.	PUNCT
cana-2055	188	1	furthermore	furthermore	ADV
cana-2055	188	2	,	,	PUNCT
cana-2055	188	3	α	α	PROPN
cana-2055	188	4	and	and	CCONJ
cana-2055	188	5	β	β	PROPN
cana-2055	188	6	denote	denote	VERB
cana-2055	188	7	the	the	DET
cana-2055	188	8	vector	vector	NOUN
cana-2055	188	9	calculation	calculation	NOUN
cana-2055	188	10	is	be	AUX
cana-2055	188	11	using	use	VERB
cana-2055	188	12	eqs	eqs	PROPN
cana-2055	188	13	.	.	PUNCT
cana-2055	189	1	(	(	PUNCT
cana-2055	189	2	12	12	NUM
cana-2055	189	3	)	)	PUNCT
cana-2055	189	4	and	and	CCONJ
cana-2055	189	5	(	(	PUNCT
cana-2055	189	6	13	13	NUM
cana-2055	189	7	)	)	PUNCT
cana-2055	189	8	respectively	respectively	ADV
cana-2055	189	9	.	.	PUNCT
cana-2055	190	1	algorithm	algorithm	NOUN
cana-2055	190	2	:	:	PUNCT
cana-2055	190	3	1	1	NUM
cana-2055	190	4	proposed	propose	VERB
cana-2055	190	5	weight	weight	NOUN
cana-2055	190	6	-	-	PUNCT
cana-2055	190	7	tuned	tune	VERB
cana-2055	190	8	deep	deep	ADJ
cana-2055	190	9	convolutional	convolutional	ADJ
cana-2055	190	10	neural	neural	ADJ
cana-2055	190	11	network	network	NOUN
cana-2055	190	12	algorithm	algorithm	NOUN
cana-2055	190	13	.	.	PUNCT
cana-2055	191	1	communications	communication	NOUN
cana-2055	191	2	on	on	ADP
cana-2055	191	3	applied	apply	VERB
cana-2055	191	4	nonlinear	nonlinear	ADJ
cana-2055	191	5	analysis	analysis	NOUN
cana-2055	191	6	issn	issn	NOUN
cana-2055	191	7	:	:	PUNCT
cana-2055	191	8	1074	1074	NUM
cana-2055	191	9	-	-	PUNCT
cana-2055	191	10	133x	133x	NUM
cana-2055	191	11	vol	vol	NOUN
cana-2055	191	12	32	32	NUM
cana-2055	191	13	no	no	NOUN
cana-2055	191	14	.	.	NOUN
cana-2055	191	15	3	3	NUM
cana-2055	191	16	(	(	PUNCT
cana-2055	191	17	2025	2025	NUM
cana-2055	191	18	)	)	PUNCT
cana-2055	191	19	586	586	NUM
cana-2055	191	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-2055	191	21	𝛼	𝛼	NOUN
cana-2055	191	22	=	=	SYM
cana-2055	191	23	2	2	NUM
cana-2055	191	24	×	×	NOUN
cana-2055	191	25	𝑙𝑑	𝑙𝑑	NOUN
cana-2055	191	26	×	×	NOUN
cana-2055	192	1	𝑅𝑛𝑢𝑚	𝑅𝑛𝑢𝑚	ADJ
cana-2055	192	2	−	−	NOUN
cana-2055	193	1	𝑙𝑑	𝑙𝑑	INTJ
cana-2055	193	2	(	(	PUNCT
cana-2055	193	3	𝜏	𝜏	NOUN
cana-2055	193	4	)	)	PUNCT
cana-2055	193	5	(	(	PUNCT
cana-2055	193	6	12	12	NUM
cana-2055	193	7	)	)	PUNCT
cana-2055	193	8	𝛽	𝛽	NOUN
cana-2055	193	9	=	=	SYM
cana-2055	193	10	2	2	NUM
cana-2055	193	11	×	×	NOUN
cana-2055	193	12	𝑅𝑛𝑢𝑚	𝑅𝑛𝑢𝑚	ADJ
cana-2055	193	13	(	(	PUNCT
cana-2055	193	14	13	13	NUM
cana-2055	193	15	)	)	PUNCT
cana-2055	193	16	after	after	ADP
cana-2055	193	17	updating	update	VERB
cana-2055	193	18	the	the	DET
cana-2055	193	19	bubble	bubble	NOUN
cana-2055	193	20	-	-	PUNCT
cana-2055	193	21	net	net	NOUN
cana-2055	193	22	behaviour	behaviour	NOUN
cana-2055	193	23	of	of	ADP
cana-2055	193	24	the	the	DET
cana-2055	193	25	humpback	humpback	NOUN
cana-2055	193	26	whales	whale	NOUN
cana-2055	193	27	using	use	VERB
cana-2055	193	28	the	the	DET
cana-2055	193	29	following	follow	VERB
cana-2055	193	30	equation	equation	NOUN
cana-2055	193	31	,	,	PUNCT
cana-2055	193	32	where	where	SCONJ
cana-2055	193	33	𝑅𝑛𝑢𝑚	𝑅𝑛𝑢𝑚	ADJ
cana-2055	193	34	denotes	denote	VERB
cana-2055	193	35	a	a	DET
cana-2055	193	36	random	random	ADJ
cana-2055	193	37	number	number	NOUN
cana-2055	193	38	ranging	range	VERB
cana-2055	193	39	between	between	ADP
cana-2055	193	40	[	[	X
cana-2055	193	41	0	0	NUM
cana-2055	193	42	,	,	PUNCT
cana-2055	193	43	1	1	NUM
cana-2055	193	44	]	]	PUNCT
cana-2055	193	45	and	and	CCONJ
cana-2055	193	46	ld	ld	PROPN
cana-2055	193	47	decreases	decrease	VERB
cana-2055	193	48	linearly	linearly	ADV
cana-2055	193	49	from	from	ADP
cana-2055	193	50	2	2	NUM
cana-2055	193	51	to	to	ADP
cana-2055	193	52	0	0	NUM
cana-2055	193	53	throughout	throughout	ADP
cana-2055	193	54	the	the	DET
cana-2055	193	55	number	number	NOUN
cana-2055	193	56	of	of	ADP
cana-2055	193	57	iterations	iteration	NOUN
cana-2055	193	58	:	:	PUNCT
cana-2055	193	59	𝑍	𝑍	NOUN
cana-2055	193	60	→	→	SYM
cana-2055	193	61	(	(	PUNCT
cana-2055	193	62	𝜏	𝜏	NOUN
cana-2055	193	63	+	+	NOUN
cana-2055	193	64	1	1	NUM
cana-2055	193	65	)	)	PUNCT
cana-2055	193	66	=	=	PRON
cana-2055	193	67	{	{	PUNCT
cana-2055	193	68	𝑍	𝑍	PROPN
cana-2055	193	69	→	→	SYM
cana-2055	193	70	∗	∗	NOUN
cana-2055	193	71	(	(	PUNCT
cana-2055	193	72	𝜏	𝜏	NOUN
cana-2055	193	73	)	)	PUNCT
cana-2055	193	74	−	−	NOUN
cana-2055	193	75	𝛼	𝛼	NUM
cana-2055	193	76	×	×	NOUN
cana-2055	193	77	𝐷𝑇	𝐷𝑇	PROPN
cana-2055	193	78	→	→	SYM
cana-2055	193	79	𝑖𝑓	𝑖𝑓	ADP
cana-2055	193	80	𝑝	𝑝	NOUN
cana-2055	193	81	<	<	X
cana-2055	193	82	0.5	0.5	NUM
cana-2055	193	83	(	(	PUNCT
cana-2055	193	84	𝐷𝑇′	𝐷𝑇′	NOUN
cana-2055	193	85	→	→	SYM
cana-2055	193	86	)	)	PUNCT
cana-2055	193	87	×	×	NOUN
cana-2055	194	1	𝑒ℎ𝑘𝑔𝑙𝑘	𝑒ℎ𝑘𝑔𝑙𝑘	ADJ
cana-2055	194	2	×	×	PROPN
cana-2055	194	3	cos(2	cos(2	NOUN
cana-2055	194	4	×	×	NOUN
cana-2055	194	5	𝜋	𝜋	NOUN
cana-2055	194	6	×	×	PROPN
cana-2055	194	7	𝑔𝑙𝑘	𝑔𝑙𝑘	NOUN
cana-2055	194	8	)	)	PUNCT
cana-2055	195	1	+	+	CCONJ
cana-2055	195	2	𝑍	𝑍	PROPN
cana-2055	195	3	∗	∗	NOUN
cana-2055	195	4	(	(	PUNCT
cana-2055	195	5	𝜏	𝜏	NOUN
cana-2055	195	6	)	)	PUNCT
cana-2055	195	7	𝑖𝑓	𝑖𝑓	ADP
cana-2055	195	8	𝑝	𝑝	PROPN
cana-2055	195	9	≥	≥	NOUN
cana-2055	195	10	0.5	0.5	NUM
cana-2055	195	11	(	(	PUNCT
cana-2055	195	12	14	14	NUM
cana-2055	195	13	)	)	PUNCT
cana-2055	195	14	→	→	PUNCT
cana-2055	195	15	in	in	ADP
cana-2055	195	16	contrast	contrast	NOUN
cana-2055	195	17	,	,	PUNCT
cana-2055	195	18	p	p	NOUN
cana-2055	195	19	is	be	AUX
cana-2055	195	20	an	an	DET
cana-2055	195	21	arbitrarily	arbitrarily	ADV
cana-2055	195	22	integer	integer	NOUN
cana-2055	195	23	between	between	ADP
cana-2055	195	24	0	0	NUM
cana-2055	195	25	and	and	CCONJ
cana-2055	195	26	1	1	NUM
cana-2055	195	27	that	that	PRON
cana-2055	195	28	indicates	indicate	VERB
cana-2055	195	29	the	the	DET
cana-2055	195	30	probability	probability	NOUN
cana-2055	195	31	of	of	ADP
cana-2055	195	32	tracking	track	VERB
cana-2055	195	33	whale	whale	NOUN
cana-2055	195	34	positions	position	NOUN
cana-2055	195	35	using	use	VERB
cana-2055	195	36	either	either	CCONJ
cana-2055	195	37	the	the	DET
cana-2055	195	38	spiral	spiral	ADJ
cana-2055	195	39	updating	updating	NOUN
cana-2055	195	40	position	position	NOUN
cana-2055	195	41	or	or	CCONJ
cana-2055	195	42	the	the	DET
cana-2055	195	43	shrinking	shrink	VERB
cana-2055	195	44	encircling	encircle	VERB
cana-2055	195	45	technique	technique	NOUN
cana-2055	195	46	(	(	PUNCT
cana-2055	195	47	if	if	SCONJ
cana-2055	195	48	p	p	NOUN
cana-2055	195	49	is	be	AUX
cana-2055	195	50	greater	great	ADJ
cana-2055	195	51	than	than	ADP
cana-2055	195	52	or	or	CCONJ
cana-2055	195	53	equal	equal	ADJ
cana-2055	195	54	to	to	ADP
cana-2055	195	55	0.5	0.5	NUM
cana-2055	195	56	)	)	PUNCT
cana-2055	195	57	,	,	PUNCT
cana-2055	195	58	𝑔𝑙𝑘	𝑔𝑙𝑘	PROPN
cana-2055	195	59	is	be	AUX
cana-2055	195	60	an	an	DET
cana-2055	195	61	arbitrarily	arbitrarily	ADV
cana-2055	195	62	integer	integer	NOUN
cana-2055	195	63	between	between	ADP
cana-2055	195	64	-1	-1	PUNCT
cana-2055	195	65	and	and	CCONJ
cana-2055	195	66	1	1	NUM
cana-2055	195	67	,	,	PUNCT
cana-2055	195	68	and	and	CCONJ
cana-2055	195	69	ℎ𝑘	ℎ𝑘	PROPN
cana-2055	195	70	is	be	AUX
cana-2055	195	71	the	the	DET
cana-2055	195	72	shape	shape	NOUN
cana-2055	195	73	of	of	ADP
cana-2055	195	74	the	the	DET
cana-2055	195	75	spiral	spiral	ADJ
cana-2055	195	76	movement	movement	NOUN
cana-2055	195	77	.	.	PUNCT
cana-2055	196	1	next	next	ADV
cana-2055	196	2	,	,	PUNCT
cana-2055	196	3	the	the	DET
cana-2055	196	4	whales	whale	NOUN
cana-2055	196	5	begin	begin	VERB
cana-2055	196	6	their	their	PRON
cana-2055	196	7	worldwide	worldwide	ADJ
cana-2055	196	8	search	search	NOUN
cana-2055	196	9	and	and	CCONJ
cana-2055	196	10	exploration	exploration	NOUN
cana-2055	196	11	,	,	PUNCT
cana-2055	196	12	which	which	PRON
cana-2055	196	13	ends	end	VERB
cana-2055	196	14	when	when	SCONJ
cana-2055	196	15	their	their	PRON
cana-2055	196	16	absolute	absolute	ADJ
cana-2055	196	17	vectors	vector	NOUN
cana-2055	196	18	value	value	NOUN
cana-2055	196	19	is	be	AUX
cana-2055	196	20	one	one	NUM
cana-2055	196	21	or	or	CCONJ
cana-2055	196	22	larger	large	ADJ
cana-2055	196	23	.	.	PUNCT
cana-2055	197	1	if	if	SCONJ
cana-2055	197	2	not	not	PART
cana-2055	197	3	,	,	PUNCT
cana-2055	197	4	the	the	DET
cana-2055	197	5	algorithm	algorithm	NOUN
cana-2055	197	6	will	will	AUX
cana-2055	197	7	go	go	VERB
cana-2055	197	8	onto	onto	ADP
cana-2055	197	9	the	the	DET
cana-2055	197	10	exploitation	exploitation	NOUN
cana-2055	197	11	step	step	NOUN
cana-2055	197	12	.	.	PUNCT
cana-2055	198	1	the	the	DET
cana-2055	198	2	following	follow	VERB
cana-2055	198	3	expression	expression	NOUN
cana-2055	198	4	describes	describe	VERB
cana-2055	198	5	the	the	DET
cana-2055	198	6	use	use	NOUN
cana-2055	198	7	of	of	ADP
cana-2055	198	8	the	the	DET
cana-2055	198	9	random	random	ADJ
cana-2055	198	10	variable	variable	ADJ
cana-2055	198	11	𝑍	𝑍	NOUN
cana-2055	198	12	→	→	NOUN
cana-2055	198	13	𝑟𝑎𝑛𝑑	𝑟𝑎𝑛𝑑	NOUN
cana-2055	198	14	to	to	PART
cana-2055	198	15	update	update	VERB
cana-2055	198	16	the	the	DET
cana-2055	198	17	locations	location	NOUN
cana-2055	198	18	of	of	ADP
cana-2055	198	19	whales	whale	NOUN
cana-2055	198	20	during	during	ADP
cana-2055	198	21	the	the	DET
cana-2055	198	22	exploration	exploration	NOUN
cana-2055	198	23	phase	phase	NOUN
cana-2055	198	24	,	,	PUNCT
cana-2055	198	25	as	as	SCONJ
cana-2055	198	26	opposed	oppose	VERB
cana-2055	198	27	to	to	ADP
cana-2055	198	28	the	the	DET
cana-2055	198	29	best	good	ADJ
cana-2055	198	30	whale	whale	NOUN
cana-2055	198	31	𝑍	𝑍	PROPN
cana-2055	198	32	→	→	SYM
cana-2055	198	33	∗.	∗.	X
cana-2055	198	34	𝐷𝑇	𝐷𝑇	PROPN
cana-2055	198	35	→	→	SYM
cana-2055	198	36	=	=	SYM
cana-2055	198	37	⃒𝛽	⃒𝛽	X
cana-2055	198	38	×	×	PROPN
cana-2055	198	39	𝑍	𝑍	PROPN
cana-2055	198	40	→	→	SYM
cana-2055	198	41	𝑟𝑎𝑛𝑑	𝑟𝑎𝑛𝑑	NOUN
cana-2055	198	42	−	−	NOUN
cana-2055	198	43	𝑍	𝑍	PROPN
cana-2055	198	44	→	→	SYM
cana-2055	198	45	(	(	PUNCT
cana-2055	198	46	𝜏)⃒	𝜏)⃒	PROPN
cana-2055	198	47	(	(	PUNCT
cana-2055	198	48	15	15	NUM
cana-2055	198	49	)	)	PUNCT
cana-2055	198	50	𝑍	𝑍	NOUN
cana-2055	198	51	→	→	SYM
cana-2055	198	52	(	(	PUNCT
cana-2055	198	53	𝜏	𝜏	NOUN
cana-2055	198	54	+	+	NOUN
cana-2055	198	55	1	1	NUM
cana-2055	198	56	)	)	PUNCT
cana-2055	198	57	=	=	SYM
cana-2055	198	58	𝑍	𝑍	PROPN
cana-2055	198	59	→	→	SYM
cana-2055	198	60	𝑟𝑎𝑛𝑑	𝑟𝑎𝑛𝑑	NOUN
cana-2055	198	61	−	−	NOUN
cana-2055	198	62	𝛼	𝛼	NOUN
cana-2055	198	63	×	×	NOUN
cana-2055	198	64	𝐷𝑡	𝐷𝑡	PROPN
cana-2055	198	65	→	→	SYM
cana-2055	198	66	×	×	PROPN
cana-2055	198	67	𝐿𝑓(ξ	𝐿𝑓(ξ	NOUN
cana-2055	198	68	)	)	PUNCT
cana-2055	198	69	(	(	PUNCT
cana-2055	198	70	16	16	NUM
cana-2055	198	71	)	)	PUNCT
cana-2055	198	72	in	in	ADP
cana-2055	198	73	this	this	DET
cana-2055	198	74	case	case	NOUN
cana-2055	198	75	,	,	PUNCT
cana-2055	198	76	𝑍	𝑍	PROPN
cana-2055	198	77	→	→	SYM
cana-2055	198	78	𝑟𝑎𝑛𝑑	𝑟𝑎𝑛𝑑	NOUN
cana-2055	198	79	denotes	denote	NOUN
cana-2055	198	80	the	the	DET
cana-2055	198	81	randomly	randomly	ADV
cana-2055	198	82	selected	select	VERB
cana-2055	198	83	whale	whale	NOUN
cana-2055	198	84	from	from	ADP
cana-2055	198	85	the	the	DET
cana-2055	198	86	existing	exist	VERB
cana-2055	198	87	population	population	NOUN
cana-2055	198	88	,	,	PUNCT
cana-2055	198	89	and	and	CCONJ
cana-2055	198	90	𝐿𝑓(ξ	𝐿𝑓(ξ	NOUN
cana-2055	198	91	)	)	PUNCT
cana-2055	198	92	is	be	AUX
cana-2055	198	93	a	a	DET
cana-2055	198	94	levy	levy	NOUN
cana-2055	198	95	flight	flight	NOUN
cana-2055	198	96	mechanism	mechanism	NOUN
cana-2055	198	97	that	that	PRON
cana-2055	198	98	improves	improve	VERB
cana-2055	198	99	algorithm	algorithm	NOUN
cana-2055	198	100	's	's	PART
cana-2055	198	101	exploration	exploration	NOUN
cana-2055	198	102	and	and	CCONJ
cana-2055	198	103	exploitation	exploitation	NOUN
cana-2055	198	104	capabilities	capability	NOUN
cana-2055	198	105	.	.	PUNCT
cana-2055	199	1	it	it	PRON
cana-2055	199	2	is	be	AUX
cana-2055	199	3	expressed	express	VERB
cana-2055	199	4	as	as	SCONJ
cana-2055	199	5	follows	follow	VERB
cana-2055	199	6	:	:	PUNCT
cana-2055	199	7	it	it	PRON
cana-2055	199	8	is	be	AUX
cana-2055	199	9	a	a	DET
cana-2055	199	10	random	random	ADJ
cana-2055	199	11	walk	walk	NOUN
cana-2055	199	12	with	with	ADP
cana-2055	199	13	steps	step	NOUN
cana-2055	199	14	indicated	indicate	VERB
cana-2055	199	15	in	in	ADP
cana-2055	199	16	terms	term	NOUN
cana-2055	199	17	of	of	ADP
cana-2055	199	18	step	step	NOUN
cana-2055	199	19	lengths	length	NOUN
cana-2055	199	20	and	and	CCONJ
cana-2055	199	21	a	a	DET
cana-2055	199	22	specific	specific	ADJ
cana-2055	199	23	probability	probability	NOUN
cana-2055	199	24	distribution	distribution	NOUN
cana-2055	199	25	.	.	PUNCT
cana-2055	200	1	𝐿𝑓(ξ	𝐿𝑓(ξ	NOUN
cana-2055	200	2	)	)	PUNCT
cana-2055	200	3	~	~	PUNCT
cana-2055	200	4	⃒ξ⃒−1−𝜆	⃒ξ⃒−1−𝜆	X
cana-2055	200	5	(	(	PUNCT
cana-2055	200	6	17	17	NUM
cana-2055	200	7	)	)	PUNCT
cana-2055	200	8	ξ	ξ	NOUN
cana-2055	201	1	=	=	PUNCT
cana-2055	201	2	𝑁𝑢𝑑	𝑁𝑢𝑑	PROPN
cana-2055	201	3	⃒	⃒	PROPN
cana-2055	201	4	𝑁𝑣𝑑⃒	𝑁𝑣𝑑⃒	VERB
cana-2055	201	5	1/𝜆	1/𝜆	NUM
cana-2055	201	6	(	(	PUNCT
cana-2055	201	7	18	18	NUM
cana-2055	201	8	)	)	PUNCT
cana-2055	201	9	whereas	whereas	SCONJ
cana-2055	201	10	ξ	ξ	PROPN
cana-2055	201	11	denotes	denote	VERB
cana-2055	201	12	the	the	DET
cana-2055	201	13	step	step	NOUN
cana-2055	201	14	length	length	NOUN
cana-2055	201	15	,	,	PUNCT
cana-2055	201	16	λ	λ	X
cana-2055	201	17	(	(	PUNCT
cana-2055	201	18	0	0	NUM
cana-2055	201	19	<	<	X
cana-2055	201	20	λ	λ	X
cana-2055	201	21	≤	≤	NUM
cana-2055	201	22	2	2	NUM
cana-2055	201	23	)	)	PUNCT
cana-2055	201	24	denotes	denote	VERB
cana-2055	201	25	an	an	DET
cana-2055	201	26	index	index	NOUN
cana-2055	201	27	,	,	PUNCT
cana-2055	201	28	and	and	CCONJ
cana-2055	201	29	𝑁𝑢𝑑	𝑁𝑢𝑑	PROPN
cana-2055	201	30	and	and	CCONJ
cana-2055	201	31	𝑁𝑣𝑑	𝑁𝑣𝑑	PROPN
cana-2055	201	32	stand	stand	VERB
cana-2055	201	33	for	for	ADP
cana-2055	201	34	drawn	draw	VERB
cana-2055	201	35	from	from	ADP
cana-2055	201	36	normal	normal	ADJ
cana-2055	201	37	distributions	distribution	NOUN
cana-2055	201	38	,	,	PUNCT
cana-2055	201	39	respectively	respectively	ADV
cana-2055	201	40	.	.	PUNCT
cana-2055	202	1	the	the	DET
cana-2055	202	2	layer	layer	NOUN
cana-2055	202	3	of	of	ADP
cana-2055	202	4	convolution	convolution	NOUN
cana-2055	202	5	retrieves	retrieve	VERB
cana-2055	202	6	related	related	ADJ
cana-2055	202	7	features	feature	NOUN
cana-2055	202	8	from	from	ADP
cana-2055	202	9	the	the	DET
cana-2055	202	10	dimensionality	dimensionality	NOUN
cana-2055	202	11	-	-	PUNCT
cana-2055	202	12	reduced	reduce	VERB
cana-2055	202	13	data	datum	NOUN
cana-2055	202	14	set	set	VERB
cana-2055	202	15	after	after	ADP
cana-2055	202	16	selecting	select	VERB
cana-2055	202	17	weights	weight	NOUN
cana-2055	202	18	and	and	CCONJ
cana-2055	202	19	biases	bias	NOUN
cana-2055	202	20	efficiently	efficiently	ADV
cana-2055	202	21	.	.	PUNCT
cana-2055	203	1	the	the	DET
cana-2055	203	2	probability	probability	NOUN
cana-2055	203	3	of	of	ADP
cana-2055	203	4	a	a	DET
cana-2055	203	5	better	well	ADJ
cana-2055	203	6	model	model	NOUN
cana-2055	203	7	steadily	steadily	ADV
cana-2055	203	8	increases	increase	VERB
cana-2055	203	9	as	as	SCONJ
cana-2055	203	10	biases	bias	NOUN
cana-2055	203	11	and	and	CCONJ
cana-2055	203	12	weights	weight	NOUN
cana-2055	203	13	take	take	VERB
cana-2055	203	14	into	into	ADP
cana-2055	203	15	account	account	NOUN
cana-2055	203	16	the	the	DET
cana-2055	203	17	best	good	ADJ
cana-2055	203	18	value	value	NOUN
cana-2055	203	19	at	at	ADP
cana-2055	203	20	every	every	DET
cana-2055	203	21	stage	stage	NOUN
cana-2055	203	22	of	of	ADP
cana-2055	203	23	the	the	DET
cana-2055	203	24	process	process	NOUN
cana-2055	203	25	.	.	PUNCT
cana-2055	204	1	feature	feature	NOUN
cana-2055	204	2	vector	vector	NOUN
cana-2055	204	3	=	=	PUNCT
cana-2055	204	4	∑	∑	PUNCT
cana-2055	204	5	(	(	PUNCT
cana-2055	204	6	𝐷𝑅	𝐷𝑅	PROPN
cana-2055	204	7	→	→	SYM
cana-2055	204	8	𝑠	𝑠	PROPN
cana-2055	204	9	+	+	PROPN
cana-2055	204	10	�	�	PROPN
cana-2055	204	11	̆	̆	NOUN
cana-2055	204	12	�	�	PROPN
cana-2055	204	13	∗𝑑×𝑑	∗𝑑×𝑑	PROPN
cana-2055	204	14	)	)	PUNCT
cana-2055	205	1	+	+	NUM
cana-2055	205	2	�	�	PROPN
cana-2055	205	3	̆	̆	NOUN
cana-2055	205	4	�	�	PROPN
cana-2055	205	5	∗	∗	NOUN
cana-2055	205	6	(	(	PUNCT
cana-2055	205	7	19	19	NUM
cana-2055	205	8	)	)	PUNCT
cana-2055	205	9	in	in	ADP
cana-2055	205	10	this	this	DET
cana-2055	205	11	context	context	NOUN
cana-2055	205	12	,	,	PUNCT
cana-2055	205	13	𝐷𝑅	𝐷𝑅	PROPN
cana-2055	205	14	→	→	SYM
cana-2055	205	15	𝑠	𝑠	PROPN
cana-2055	205	16	symbolises	symbolise	VERB
cana-2055	205	17	the	the	DET
cana-2055	205	18	dataset	dataset	NOUN
cana-2055	205	19	subjected	subject	VERB
cana-2055	205	20	to	to	ADP
cana-2055	205	21	dimensionality	dimensionality	NOUN
cana-2055	205	22	reduction	reduction	NOUN
cana-2055	205	23	for	for	ADP
cana-2055	205	24	the	the	DET
cana-2055	205	25	convolutional	convolutional	ADJ
cana-2055	205	26	operation	operation	NOUN
cana-2055	205	27	,	,	PUNCT
cana-2055	205	28	�	�	PROPN
cana-2055	205	29	̆	̆	NOUN
cana-2055	205	30	�	�	PROPN
cana-2055	205	31	∗𝑑×𝑑	∗𝑑×𝑑	PROPN
cana-2055	205	32	represents	represent	VERB
cana-2055	205	33	the	the	DET
cana-2055	205	34	optimum	optimum	ADJ
cana-2055	205	35	filter	filter	NOUN
cana-2055	205	36	weights	weight	NOUN
cana-2055	205	37	,	,	PUNCT
cana-2055	205	38	and	and	CCONJ
cana-2055	205	39	�	�	PROPN
cana-2055	205	40	̆	̆	NOUN
cana-2055	205	41	�	�	PROPN
cana-2055	205	42	∗	∗	NOUN
cana-2055	205	43	signifies	signify	VERB
cana-2055	205	44	the	the	DET
cana-2055	205	45	bias	bias	NOUN
cana-2055	205	46	determined	determine	VERB
cana-2055	205	47	by	by	ADP
cana-2055	205	48	ewoa	ewoa	ADJ
cana-2055	205	49	,	,	PUNCT
cana-2055	205	50	while	while	SCONJ
cana-2055	205	51	d	d	PROPN
cana-2055	205	52	−	−	PROPN
cana-2055	205	53	indicates	indicate	VERB
cana-2055	205	54	the	the	DET
cana-2055	205	55	kernel	kernel	NOUN
cana-2055	205	56	size	size	NOUN
cana-2055	205	57	.	.	PUNCT
cana-2055	206	1	after	after	ADP
cana-2055	206	2	that	that	PRON
cana-2055	206	3	,	,	PUNCT
cana-2055	206	4	the	the	DET
cana-2055	206	5	activation	activation	NOUN
cana-2055	206	6	layer	layer	NOUN
cana-2055	206	7	receives	receive	VERB
cana-2055	206	8	the	the	DET
cana-2055	206	9	feature	feature	NOUN
cana-2055	206	10	vector	vector	NOUN
cana-2055	206	11	as	as	ADP
cana-2055	206	12	a	a	DET
cana-2055	206	13	result	result	NOUN
cana-2055	206	14	and	and	CCONJ
cana-2055	206	15	uses	use	VERB
cana-2055	206	16	it	it	PRON
cana-2055	206	17	to	to	PART
cana-2055	206	18	make	make	VERB
cana-2055	206	19	the	the	DET
cana-2055	206	20	output	output	NOUN
cana-2055	206	21	more	more	ADV
cana-2055	206	22	nonlinear	nonlinear	ADJ
cana-2055	206	23	.	.	PUNCT
cana-2055	207	1	the	the	DET
cana-2055	207	2	active	active	ADJ
cana-2055	207	3	layer	layer	NOUN
cana-2055	207	4	's	's	PART
cana-2055	207	5	activation	activation	NOUN
cana-2055	207	6	function	function	NOUN
cana-2055	207	7	is	be	AUX
cana-2055	207	8	relu	relu	NOUN
cana-2055	207	9	,	,	PUNCT
cana-2055	207	10	which	which	PRON
cana-2055	207	11	generates	generate	VERB
cana-2055	207	12	the	the	DET
cana-2055	207	13	input	input	NOUN
cana-2055	207	14	instantly	instantly	ADV
cana-2055	207	15	for	for	ADP
cana-2055	207	16	positive	positive	ADJ
cana-2055	207	17	input	input	NOUN
cana-2055	207	18	values	value	NOUN
cana-2055	207	19	.	.	PUNCT
cana-2055	208	1	on	on	ADP
cana-2055	208	2	the	the	DET
cana-2055	208	3	other	other	ADJ
cana-2055	208	4	hand	hand	NOUN
cana-2055	208	5	,	,	PUNCT
cana-2055	208	6	it	it	PRON
cana-2055	208	7	could	could	AUX
cana-2055	208	8	provide	provide	VERB
cana-2055	208	9	no	no	DET
cana-2055	208	10	communications	communication	NOUN
cana-2055	208	11	on	on	ADP
cana-2055	208	12	applied	apply	VERB
cana-2055	208	13	nonlinear	nonlinear	ADJ
cana-2055	208	14	analysis	analysis	NOUN
cana-2055	208	15	issn	issn	NOUN
cana-2055	208	16	:	:	PUNCT
cana-2055	208	17	1074	1074	NUM
cana-2055	208	18	-	-	PUNCT
cana-2055	208	19	133x	133x	NUM
cana-2055	208	20	vol	vol	NOUN
cana-2055	208	21	32	32	NUM
cana-2055	208	22	no	no	NOUN
cana-2055	208	23	.	.	NOUN
cana-2055	208	24	3	3	NUM
cana-2055	208	25	(	(	PUNCT
cana-2055	208	26	2025	2025	NUM
cana-2055	208	27	)	)	PUNCT
cana-2055	208	28	587	587	NUM
cana-2055	208	29	https://internationalpubls.com	https://internationalpubls.com	X
cana-2055	208	30	output	output	NOUN
cana-2055	208	31	at	at	ADV
cana-2055	208	32	all	all	ADV
cana-2055	208	33	.	.	PUNCT
cana-2055	209	1	to	to	PART
cana-2055	209	2	decrease	decrease	VERB
cana-2055	209	3	the	the	DET
cana-2055	209	4	data	datum	NOUN
cana-2055	209	5	size	size	NOUN
cana-2055	209	6	,	,	PUNCT
cana-2055	209	7	the	the	DET
cana-2055	209	8	activation	activation	NOUN
cana-2055	209	9	-	-	PUNCT
cana-2055	209	10	convolution	convolution	NOUN
cana-2055	209	11	layer	layer	NOUN
cana-2055	209	12	feeds	feed	VERB
cana-2055	209	13	its	its	PRON
cana-2055	209	14	output	output	NOUN
cana-2055	209	15	into	into	ADP
cana-2055	209	16	the	the	DET
cana-2055	209	17	pooling	pool	VERB
cana-2055	209	18	layer	layer	NOUN
cana-2055	209	19	.	.	PUNCT
cana-2055	210	1	in	in	ADP
cana-2055	210	2	order	order	NOUN
cana-2055	210	3	to	to	PART
cana-2055	210	4	provide	provide	VERB
cana-2055	210	5	output	output	NOUN
cana-2055	210	6	,	,	PUNCT
cana-2055	210	7	these	these	DET
cana-2055	210	8	polling	polling	NOUN
cana-2055	210	9	layers	layer	NOUN
cana-2055	210	10	sample	sample	VERB
cana-2055	210	11	the	the	DET
cana-2055	210	12	smaller	small	ADJ
cana-2055	210	13	rectangular	rectangular	ADJ
cana-2055	210	14	boxes	box	NOUN
cana-2055	210	15	taken	take	VERB
cana-2055	210	16	from	from	ADP
cana-2055	210	17	the	the	DET
cana-2055	210	18	convolution	convolution	NOUN
cana-2055	210	19	layer	layer	NOUN
cana-2055	210	20	.	.	PUNCT
cana-2055	211	1	the	the	DET
cana-2055	211	2	fully	fully	ADV
cana-2055	211	3	linked	link	VERB
cana-2055	211	4	layer	layer	NOUN
cana-2055	211	5	uses	use	VERB
cana-2055	211	6	the	the	DET
cana-2055	211	7	soft	soft	ADJ
cana-2055	211	8	max	max	NOUN
cana-2055	211	9	activation	activation	NOUN
cana-2055	211	10	function	function	NOUN
cana-2055	211	11	for	for	ADP
cana-2055	211	12	categorisation	categorisation	NOUN
cana-2055	211	13	and	and	CCONJ
cana-2055	211	14	receives	receive	VERB
cana-2055	211	15	the	the	DET
cana-2055	211	16	data	datum	NOUN
cana-2055	211	17	from	from	ADP
cana-2055	211	18	the	the	DET
cana-2055	211	19	polling	polling	NOUN
cana-2055	211	20	layers	layer	NOUN
cana-2055	211	21	.	.	PUNCT
cana-2055	212	1	to	to	PART
cana-2055	212	2	help	help	VERB
cana-2055	212	3	farmers	farmer	NOUN
cana-2055	212	4	choose	choose	VERB
cana-2055	212	5	crops	crop	NOUN
cana-2055	212	6	with	with	ADP
cana-2055	212	7	the	the	DET
cana-2055	212	8	best	good	ADJ
cana-2055	212	9	potential	potential	NOUN
cana-2055	212	10	for	for	ADP
cana-2055	212	11	future	future	ADJ
cana-2055	212	12	production	production	NOUN
cana-2055	212	13	,	,	PUNCT
cana-2055	212	14	the	the	DET
cana-2055	212	15	classifier	classifier	NOUN
cana-2055	212	16	predicts	predict	VERB
cana-2055	212	17	how	how	SCONJ
cana-2055	212	18	productive	productive	ADJ
cana-2055	212	19	different	different	ADJ
cana-2055	212	20	crops	crop	NOUN
cana-2055	212	21	would	would	AUX
cana-2055	212	22	be	be	AUX
cana-2055	212	23	in	in	ADP
cana-2055	212	24	different	different	ADJ
cana-2055	212	25	parts	part	NOUN
cana-2055	212	26	of	of	ADP
cana-2055	212	27	india	india	PROPN
cana-2055	212	28	throughout	throughout	ADP
cana-2055	212	29	different	different	ADJ
cana-2055	212	30	seasons	season	NOUN
cana-2055	212	31	.	.	PUNCT
cana-2055	213	1	4	4	X
cana-2055	213	2	.	.	NOUN
cana-2055	213	3	result	result	NOUN
cana-2055	213	4	and	and	CCONJ
cana-2055	213	5	discussion	discussion	VERB
cana-2055	213	6	the	the	DET
cana-2055	213	7	experimental	experimental	ADJ
cana-2055	213	8	outcomes	outcome	NOUN
cana-2055	213	9	of	of	ADP
cana-2055	213	10	the	the	DET
cana-2055	213	11	suggested	suggest	VERB
cana-2055	213	12	yield	yield	NOUN
cana-2055	213	13	prediction	prediction	NOUN
cana-2055	213	14	for	for	ADP
cana-2055	213	15	regional	regional	ADJ
cana-2055	213	16	crops	crop	NOUN
cana-2055	213	17	in	in	ADP
cana-2055	213	18	india	india	PROPN
cana-2055	213	19	utilising	utilise	VERB
cana-2055	213	20	effective	effective	ADJ
cana-2055	213	21	dl	dl	PROPN
cana-2055	213	22	and	and	CCONJ
cana-2055	213	23	dr	dr	PROPN
cana-2055	213	24	methodologies	methodology	NOUN
cana-2055	213	25	are	be	AUX
cana-2055	213	26	examined	examine	VERB
cana-2055	213	27	in	in	ADP
cana-2055	213	28	the	the	DET
cana-2055	213	29	next	next	ADJ
cana-2055	213	30	section	section	NOUN
cana-2055	213	31	.	.	PUNCT
cana-2055	214	1	regarding	regard	VERB
cana-2055	214	2	categorisation	categorisation	NOUN
cana-2055	214	3	metrics	metric	NOUN
cana-2055	214	4	,	,	PUNCT
cana-2055	214	5	the	the	DET
cana-2055	214	6	suggested	suggest	VERB
cana-2055	214	7	technique	technique	NOUN
cana-2055	214	8	is	be	AUX
cana-2055	214	9	contrasted	contrast	VERB
cana-2055	214	10	with	with	ADP
cana-2055	214	11	the	the	DET
cana-2055	214	12	cyp	cyp	ADJ
cana-2055	214	13	schemes	scheme	NOUN
cana-2055	214	14	that	that	PRON
cana-2055	214	15	are	be	AUX
cana-2055	214	16	now	now	ADV
cana-2055	214	17	in	in	ADP
cana-2055	214	18	place	place	NOUN
cana-2055	214	19	.	.	PUNCT
cana-2055	215	1	using	use	VERB
cana-2055	215	2	an	an	DET
cana-2055	215	3	intel	intel	NOUN
cana-2055	215	4	core	core	NOUN
cana-2055	215	5	i7	i7	NOUN
cana-2055	215	6	-	-	PUNCT
cana-2055	215	7	8550	8550	NUM
cana-2055	215	8	cpu	cpu	NOUN
cana-2055	215	9	,	,	PUNCT
cana-2055	215	10	an	an	DET
cana-2055	215	11	nvidia	nvidia	PROPN
cana-2055	215	12	geforce	geforce	NOUN
cana-2055	215	13	mx130	mx130	PROPN
cana-2055	215	14	graphics	graphic	NOUN
cana-2055	215	15	card	card	NOUN
cana-2055	215	16	,	,	PUNCT
cana-2055	215	17	and	and	CCONJ
cana-2055	215	18	8.0	8.0	NUM
cana-2055	215	19	gb	gb	NOUN
cana-2055	215	20	of	of	ADP
cana-2055	215	21	ram	ram	NOUN
cana-2055	215	22	,	,	PUNCT
cana-2055	215	23	the	the	DET
cana-2055	215	24	predictions	prediction	NOUN
cana-2055	215	25	were	be	AUX
cana-2055	215	26	produced	produce	VERB
cana-2055	215	27	using	use	VERB
cana-2055	215	28	python	python	NOUN
cana-2055	215	29	.	.	PUNCT
cana-2055	216	1	4.1	4.1	NUM
cana-2055	216	2	descriptions	description	NOUN
cana-2055	216	3	of	of	ADP
cana-2055	216	4	datasets	dataset	NOUN
cana-2055	216	5	the	the	DET
cana-2055	216	6	crop	crop	NOUN
cana-2055	216	7	production	production	NOUN
cana-2055	216	8	data	datum	NOUN
cana-2055	216	9	,	,	PUNCT
cana-2055	216	10	which	which	PRON
cana-2055	216	11	includes	include	VERB
cana-2055	216	12	district	district	NOUN
cana-2055	216	13	name	name	NOUN
cana-2055	216	14	,	,	PUNCT
cana-2055	216	15	production	production	NOUN
cana-2055	216	16	yield	yield	NOUN
cana-2055	216	17	,	,	PUNCT
cana-2055	216	18	year	year	NOUN
cana-2055	216	19	,	,	PUNCT
cana-2055	216	20	crop	crop	NOUN
cana-2055	216	21	class	class	NOUN
cana-2055	216	22	,	,	PUNCT
cana-2055	216	23	area	area	NOUN
cana-2055	216	24	,	,	PUNCT
cana-2055	216	25	crop	crop	NOUN
cana-2055	216	26	,	,	PUNCT
cana-2055	216	27	state	state	NOUN
cana-2055	216	28	name	name	NOUN
cana-2055	216	29	,	,	PUNCT
cana-2055	216	30	season	season	NOUN
cana-2055	216	31	,	,	PUNCT
cana-2055	216	32	and	and	CCONJ
cana-2055	216	33	crop	crop	NOUN
cana-2055	216	34	,	,	PUNCT
cana-2055	216	35	was	be	AUX
cana-2055	216	36	gathered	gather	VERB
cana-2055	216	37	using	use	VERB
cana-2055	216	38	the	the	DET
cana-2055	216	39	proposed	propose	VERB
cana-2055	216	40	system	system	NOUN
cana-2055	216	41	utilising	utilise	VERB
cana-2055	216	42	agricultureindia	agricultureindia	NOUN
cana-2055	216	43	,	,	PUNCT
cana-2055	216	44	a	a	DET
cana-2055	216	45	publicly	publicly	ADV
cana-2055	216	46	accessible	accessible	ADJ
cana-2055	216	47	data	datum	NOUN
cana-2055	216	48	source	source	NOUN
cana-2055	216	49	.	.	PUNCT
cana-2055	217	1	additionally	additionally	ADV
cana-2055	217	2	,	,	PUNCT
cana-2055	217	3	meteorological	meteorological	ADJ
cana-2055	217	4	data	datum	NOUN
cana-2055	217	5	are	be	AUX
cana-2055	217	6	gathered	gather	VERB
cana-2055	217	7	from	from	ADP
cana-2055	217	8	the	the	DET
cana-2055	217	9	indian	indian	ADJ
cana-2055	217	10	website	website	NOUN
cana-2055	217	11	and	and	CCONJ
cana-2055	217	12	include	include	VERB
cana-2055	217	13	the	the	DET
cana-2055	217	14	following	follow	VERB
cana-2055	217	15	:	:	PUNCT
cana-2055	217	16	precipitation	precipitation	NOUN
cana-2055	217	17	,	,	PUNCT
cana-2055	217	18	humidity	humidity	NOUN
cana-2055	217	19	,	,	PUNCT
cana-2055	217	20	pressure	pressure	NOUN
cana-2055	217	21	,	,	PUNCT
cana-2055	217	22	dew	dew	NOUN
cana-2055	217	23	point	point	NOUN
cana-2055	217	24	,	,	PUNCT
cana-2055	217	25	wind	wind	NOUN
cana-2055	217	26	,	,	PUNCT
cana-2055	217	27	lowest	low	ADJ
cana-2055	217	28	temperature	temperature	NOUN
cana-2055	217	29	,	,	PUNCT
cana-2055	217	30	highest	high	ADJ
cana-2055	217	31	temperature	temperature	NOUN
cana-2055	217	32	,	,	PUNCT
cana-2055	217	33	average	average	ADJ
cana-2055	217	34	temperature	temperature	NOUN
cana-2055	217	35	,	,	PUNCT
cana-2055	217	36	and	and	CCONJ
cana-2055	217	37	humidity	humidity	NOUN
cana-2055	217	38	.	.	PUNCT
cana-2055	218	1	4.2	4.2	NUM
cana-2055	218	2	analysis	analysis	NOUN
cana-2055	218	3	of	of	ADP
cana-2055	218	4	performance	performance	NOUN
cana-2055	218	5	they	they	PRON
cana-2055	218	6	compare	compare	VERB
cana-2055	218	7	the	the	DET
cana-2055	218	8	results	result	NOUN
cana-2055	218	9	of	of	ADP
cana-2055	218	10	the	the	DET
cana-2055	218	11	suggested	suggest	VERB
cana-2055	218	12	classification	classification	NOUN
cana-2055	218	13	method	method	NOUN
cana-2055	218	14	(	(	PUNCT
cana-2055	218	15	wtdcnn	wtdcnn	ADJ
cana-2055	218	16	)	)	PUNCT
cana-2055	218	17	to	to	ADP
cana-2055	218	18	those	those	PRON
cana-2055	218	19	of	of	ADP
cana-2055	218	20	present	present	ADJ
cana-2055	218	21	-	-	PUNCT
cana-2055	218	22	day	day	NOUN
cana-2055	218	23	classification	classification	NOUN
cana-2055	218	24	schemes	scheme	NOUN
cana-2055	218	25	,	,	PUNCT
cana-2055	218	26	including	include	VERB
cana-2055	218	27	dcnn	dcnn	PROPN
cana-2055	218	28	,	,	PUNCT
cana-2055	218	29	rf	rf	PROPN
cana-2055	218	30	,	,	PUNCT
cana-2055	218	31	dbn	dbn	NOUN
cana-2055	218	32	,	,	PUNCT
cana-2055	218	33	and	and	CCONJ
cana-2055	218	34	elm	elm	PROPN
cana-2055	218	35	.	.	PUNCT
cana-2055	219	1	measures	measure	NOUN
cana-2055	219	2	like	like	ADP
cana-2055	219	3	as	as	ADP
cana-2055	219	4	accuracy	accuracy	NOUN
cana-2055	219	5	(	(	PUNCT
cana-2055	219	6	ac	ac	PROPN
cana-2055	219	7	)	)	PUNCT
cana-2055	219	8	,	,	PUNCT
cana-2055	219	9	recall	recall	INTJ
cana-2055	219	10	(	(	PUNCT
cana-2055	219	11	rc	rc	PROPN
cana-2055	219	12	)	)	PUNCT
cana-2055	219	13	,	,	PUNCT
cana-2055	219	14	f	f	X
cana-2055	219	15	-	-	PUNCT
cana-2055	219	16	measure	measure	NOUN
cana-2055	219	17	(	(	PUNCT
cana-2055	219	18	fm	fm	NOUN
cana-2055	219	19	)	)	PUNCT
cana-2055	219	20	,	,	PUNCT
cana-2055	219	21	false	false	ADJ
cana-2055	219	22	positive	positive	ADJ
cana-2055	219	23	rate	rate	NOUN
cana-2055	219	24	(	(	PUNCT
cana-2055	219	25	fpr	fpr	NOUN
cana-2055	219	26	)	)	PUNCT
cana-2055	219	27	,	,	PUNCT
cana-2055	219	28	root	root	NOUN
cana-2055	219	29	mean	mean	VERB
cana-2055	219	30	square	square	ADJ
cana-2055	219	31	error	error	NOUN
cana-2055	219	32	(	(	PUNCT
cana-2055	219	33	rmse	rmse	NOUN
cana-2055	219	34	)	)	PUNCT
cana-2055	219	35	,	,	PUNCT
cana-2055	219	36	and	and	CCONJ
cana-2055	219	37	precision	precision	NOUN
cana-2055	219	38	(	(	PUNCT
cana-2055	219	39	pr	pr	NOUN
cana-2055	219	40	)	)	PUNCT
cana-2055	219	41	are	be	AUX
cana-2055	219	42	used	use	VERB
cana-2055	219	43	to	to	PART
cana-2055	219	44	assess	assess	VERB
cana-2055	219	45	the	the	DET
cana-2055	219	46	techniques	technique	NOUN
cana-2055	219	47	.	.	PUNCT
cana-2055	220	1	the	the	DET
cana-2055	220	2	following	follow	VERB
cana-2055	220	3	are	be	AUX
cana-2055	220	4	the	the	DET
cana-2055	220	5	formulae	formulae	NOUN
cana-2055	220	6	for	for	ADP
cana-2055	220	7	the	the	DET
cana-2055	220	8	dimensions	dimension	NOUN
cana-2055	220	9	given	give	VERB
cana-2055	220	10	above	above	ADV
cana-2055	220	11	.	.	PUNCT
cana-2055	221	1	pr	pr	X
cana-2055	221	2	=	=	PUNCT
cana-2055	222	1	𝑇𝑝	𝑇𝑝	PROPN
cana-2055	222	2	𝑇𝑝+𝐹𝑝	𝑇𝑝+𝐹𝑝	PROPN
cana-2055	222	3	rc	rc	X
cana-2055	222	4	=	=	SYM
cana-2055	222	5	𝑇𝑝	𝑇𝑝	PROPN
cana-2055	222	6	𝑇𝑝+𝐹𝑛	𝑇𝑝+𝐹𝑛	X
cana-2055	222	7	ac	ac	NOUN
cana-2055	222	8	=	=	SYM
cana-2055	222	9	𝑇𝑝	𝑇𝑝	PROPN
cana-2055	222	10	𝑇𝑝+𝑇𝑛+𝐹𝑝+𝐹𝑛	𝑇𝑝+𝑇𝑛+𝐹𝑝+𝐹𝑛	PROPN
cana-2055	222	11	fm	fm	NOUN
cana-2055	222	12	=	=	SYM
cana-2055	222	13	𝑇𝑝	𝑇𝑝	PROPN
cana-2055	222	14	𝑇𝑝+1/2(𝐹𝑝+𝐹𝑛	𝑇𝑝+1/2(𝐹𝑝+𝐹𝑛	NOUN
cana-2055	222	15	)	)	PUNCT
cana-2055	222	16	fpr	fpr	NOUN
cana-2055	223	1	=	=	PUNCT
cana-2055	223	2	𝐹𝑝	𝐹𝑝	PROPN
cana-2055	223	3	𝐹𝑝+𝑇𝑛	𝐹𝑝+𝑇𝑛	PROPN
cana-2055	223	4	fnr	fnr	PROPN
cana-2055	223	5	=	=	PUNCT
cana-2055	224	1	𝐹𝑛	𝐹𝑛	PROPN
cana-2055	224	2	𝐹𝑛+𝑇𝑝	𝐹𝑛+𝑇𝑝	NUM
cana-2055	224	3	mse	mse	NOUN
cana-2055	224	4	=	=	NOUN
cana-2055	224	5	1	1	NUM
cana-2055	224	6	𝑁	𝑁	PROPN
cana-2055	224	7	∑	∑	PUNCT
cana-2055	224	8	(	(	PUNCT
cana-2055	224	9	𝐴	𝐴	PROPN
cana-2055	224	10	−	−	PROPN
cana-2055	224	11	𝐵)2𝑛	𝐵)2𝑛	PROPN
cana-2055	224	12	𝑖=1	𝑖=1	ADP
cana-2055	224	13	rmse	rmse	NOUN
cana-2055	224	14	=	=	PUNCT
cana-2055	224	15	√𝑀𝑆𝐸	√𝑀𝑆𝐸	ADV
cana-2055	225	1	this	this	PRON
cana-2055	225	2	has	have	AUX
cana-2055	225	3	indicated	indicate	VERB
cana-2055	225	4	that	that	SCONJ
cana-2055	225	5	deep	deep	ADJ
cana-2055	225	6	learning	learning	NOUN
cana-2055	225	7	may	may	AUX
cana-2055	225	8	significantly	significantly	ADV
cana-2055	225	9	influence	influence	VERB
cana-2055	225	10	cyp	cyp	ADJ
cana-2055	225	11	,	,	PUNCT
cana-2055	225	12	and	and	CCONJ
cana-2055	225	13	our	our	PRON
cana-2055	225	14	findings	finding	NOUN
cana-2055	225	15	corroborate	corroborate	VERB
cana-2055	225	16	this	this	DET
cana-2055	225	17	assertion	assertion	NOUN
cana-2055	225	18	.	.	PUNCT
cana-2055	226	1	although	although	SCONJ
cana-2055	226	2	grounded	ground	VERB
cana-2055	226	3	on	on	ADP
cana-2055	226	4	fundamental	fundamental	ADJ
cana-2055	226	5	performance	performance	NOUN
cana-2055	226	6	criteria	criterion	NOUN
cana-2055	226	7	,	,	PUNCT
cana-2055	226	8	the	the	DET
cana-2055	226	9	results	result	NOUN
cana-2055	226	10	can	can	AUX
cana-2055	226	11	be	be	AUX
cana-2055	226	12	compared	compare	VERB
cana-2055	226	13	with	with	ADP
cana-2055	226	14	other	other	ADJ
cana-2055	226	15	cutting	cutting	NOUN
cana-2055	226	16	-	-	PUNCT
cana-2055	226	17	edge	edge	NOUN
cana-2055	226	18	techniques	technique	NOUN
cana-2055	226	19	.	.	PUNCT
cana-2055	227	1	the	the	DET
cana-2055	227	2	proposed	propose	VERB
cana-2055	227	3	wtdcnn	wtdcnn	VERB
cana-2055	227	4	yields	yield	VERB
cana-2055	227	5	superior	superior	ADJ
cana-2055	227	6	results	result	NOUN
cana-2055	227	7	compared	compare	VERB
cana-2055	227	8	to	to	ADP
cana-2055	227	9	the	the	DET
cana-2055	227	10	communications	communication	NOUN
cana-2055	227	11	on	on	ADP
cana-2055	227	12	applied	apply	VERB
cana-2055	227	13	nonlinear	nonlinear	ADJ
cana-2055	227	14	analysis	analysis	NOUN
cana-2055	227	15	issn	issn	NOUN
cana-2055	227	16	:	:	PUNCT
cana-2055	227	17	1074	1074	NUM
cana-2055	227	18	-	-	PUNCT
cana-2055	227	19	133x	133x	NUM
cana-2055	227	20	vol	vol	NOUN
cana-2055	227	21	32	32	NUM
cana-2055	227	22	no	no	NOUN
cana-2055	227	23	.	.	NOUN
cana-2055	227	24	3	3	NUM
cana-2055	227	25	(	(	PUNCT
cana-2055	227	26	2025	2025	NUM
cana-2055	227	27	)	)	PUNCT
cana-2055	227	28	588	588	NUM
cana-2055	227	29	https://internationalpubls.com	https://internationalpubls.com	X
cana-2055	227	30	current	current	ADJ
cana-2055	227	31	models	model	NOUN
cana-2055	227	32	.	.	PUNCT
cana-2055	228	1	the	the	DET
cana-2055	228	2	current	current	ADJ
cana-2055	228	3	dcnn	dcnn	PROPN
cana-2055	228	4	attains	attain	NOUN
cana-2055	228	5	recall	recall	VERB
cana-2055	228	6	,	,	PUNCT
cana-2055	228	7	f	f	X
cana-2055	228	8	-	-	PUNCT
cana-2055	228	9	measure	measure	NOUN
cana-2055	228	10	,	,	PUNCT
cana-2055	228	11	accuracy	accuracy	NOUN
cana-2055	228	12	,	,	PUNCT
cana-2055	228	13	and	and	CCONJ
cana-2055	228	14	precision	precision	NOUN
cana-2055	228	15	of	of	ADP
cana-2055	228	16	96.99	96.99	NUM
cana-2055	228	17	%	%	NOUN
cana-2055	228	18	,	,	PUNCT
cana-2055	228	19	96.28	96.28	NUM
cana-2055	228	20	%	%	NOUN
cana-2055	228	21	,	,	PUNCT
cana-2055	228	22	97.04	97.04	NUM
cana-2055	228	23	%	%	NOUN
cana-2055	228	24	,	,	PUNCT
cana-2055	228	25	and	and	CCONJ
cana-2055	228	26	96.79	96.79	NUM
cana-2055	228	27	%	%	NOUN
cana-2055	228	28	,	,	PUNCT
cana-2055	228	29	respectively	respectively	ADV
cana-2055	228	30	.	.	PUNCT
cana-2055	229	1	the	the	DET
cana-2055	229	2	current	current	ADJ
cana-2055	229	3	rf	rf	NOUN
cana-2055	229	4	achieves	achieve	VERB
cana-2055	229	5	an	an	DET
cana-2055	229	6	accuracy	accuracy	NOUN
cana-2055	229	7	of	of	ADP
cana-2055	229	8	89.22	89.22	NUM
cana-2055	229	9	%	%	NOUN
cana-2055	229	10	,	,	PUNCT
cana-2055	229	11	precision	precision	NOUN
cana-2055	229	12	of	of	ADP
cana-2055	229	13	89.06	89.06	NUM
cana-2055	229	14	%	%	NOUN
cana-2055	229	15	,	,	PUNCT
cana-2055	229	16	recall	recall	NOUN
cana-2055	229	17	of	of	ADP
cana-2055	229	18	89.33	89.33	NUM
cana-2055	229	19	%	%	NOUN
cana-2055	229	20	,	,	PUNCT
cana-2055	229	21	and	and	CCONJ
cana-2055	229	22	f	f	X
cana-2055	229	23	-	-	PUNCT
cana-2055	229	24	measure	measure	NOUN
cana-2055	229	25	of	of	ADP
cana-2055	229	26	89.20	89.20	NUM
cana-2055	229	27	%	%	NOUN
cana-2055	229	28	,	,	PUNCT
cana-2055	229	29	all	all	PRON
cana-2055	229	30	of	of	ADP
cana-2055	229	31	which	which	PRON
cana-2055	229	32	are	be	AUX
cana-2055	229	33	inferior	inferior	ADJ
cana-2055	229	34	to	to	ADP
cana-2055	229	35	the	the	DET
cana-2055	229	36	suggested	suggested	ADJ
cana-2055	229	37	model	model	NOUN
cana-2055	229	38	,	,	PUNCT
cana-2055	229	39	which	which	PRON
cana-2055	229	40	attains	attain	VERB
cana-2055	229	41	a	a	DET
cana-2055	229	42	maximum	maximum	ADJ
cana-2055	229	43	accuracy	accuracy	NOUN
cana-2055	229	44	of	of	ADP
cana-2055	229	45	98.97	98.97	NUM
cana-2055	229	46	%	%	NOUN
cana-2055	229	47	,	,	PUNCT
cana-2055	229	48	precision	precision	NOUN
cana-2055	229	49	of	of	ADP
cana-2055	229	50	98.67	98.67	NUM
cana-2055	229	51	%	%	NOUN
cana-2055	229	52	,	,	PUNCT
cana-2055	229	53	recall	recall	NOUN
cana-2055	229	54	of	of	ADP
cana-2055	229	55	99.04	99.04	NUM
cana-2055	229	56	%	%	NOUN
cana-2055	229	57	,	,	PUNCT
cana-2055	229	58	and	and	CCONJ
cana-2055	229	59	f	f	X
cana-2055	229	60	-	-	PUNCT
cana-2055	229	61	measure	measure	NOUN
cana-2055	229	62	of	of	ADP
cana-2055	229	63	98.88	98.88	NUM
cana-2055	229	64	%	%	NOUN
cana-2055	229	65	.	.	PUNCT
cana-2055	230	1	likewise	likewise	ADV
cana-2055	230	2	,	,	PUNCT
cana-2055	230	3	when	when	SCONJ
cana-2055	230	4	evaluating	evaluate	VERB
cana-2055	230	5	other	other	ADJ
cana-2055	230	6	approaches	approach	NOUN
cana-2055	230	7	(	(	PUNCT
cana-2055	230	8	dbn	dbn	NOUN
cana-2055	230	9	and	and	CCONJ
cana-2055	230	10	elm	elm	PROPN
cana-2055	230	11	)	)	PUNCT
cana-2055	230	12	,	,	PUNCT
cana-2055	230	13	the	the	DET
cana-2055	230	14	suggested	suggest	VERB
cana-2055	230	15	approach	approach	NOUN
cana-2055	230	16	demonstrates	demonstrate	VERB
cana-2055	230	17	superior	superior	ADJ
cana-2055	230	18	performance	performance	NOUN
cana-2055	230	19	.	.	PUNCT
cana-2055	231	1	consequently	consequently	ADV
cana-2055	231	2	,	,	PUNCT
cana-2055	231	3	the	the	DET
cana-2055	231	4	results	result	NOUN
cana-2055	231	5	demonstrated	demonstrate	VERB
cana-2055	231	6	that	that	SCONJ
cana-2055	231	7	the	the	DET
cana-2055	231	8	new	new	ADJ
cana-2055	231	9	strategy	strategy	NOUN
cana-2055	231	10	surpassed	surpass	VERB
cana-2055	231	11	the	the	DET
cana-2055	231	12	traditional	traditional	ADJ
cana-2055	231	13	approach	approach	NOUN
cana-2055	231	14	.	.	PUNCT
cana-2055	232	1	figure	figure	NOUN
cana-2055	232	2	3	3	NUM
cana-2055	232	3	illustrates	illustrate	VERB
cana-2055	232	4	the	the	DET
cana-2055	232	5	diagrammatic	diagrammatic	ADJ
cana-2055	232	6	form	form	NOUN
cana-2055	232	7	.	.	PUNCT
cana-2055	233	1	figure	figure	NOUN
cana-2055	233	2	3	3	NUM
cana-2055	233	3	displays	display	VERB
cana-2055	233	4	the	the	DET
cana-2055	233	5	results	result	NOUN
cana-2055	233	6	of	of	ADP
cana-2055	233	7	the	the	DET
cana-2055	233	8	methods	method	NOUN
cana-2055	233	9	for	for	ADP
cana-2055	233	10	ac	ac	PROPN
cana-2055	233	11	,	,	PUNCT
cana-2055	233	12	pr	pr	NOUN
cana-2055	233	13	,	,	PUNCT
cana-2055	233	14	rc	rc	PROPN
cana-2055	233	15	,	,	PUNCT
cana-2055	233	16	and	and	CCONJ
cana-2055	233	17	fm	fm	PROPN
cana-2055	233	18	.	.	PUNCT
cana-2055	234	1	the	the	DET
cana-2055	234	2	graphic	graphic	NOUN
cana-2055	234	3	clearly	clearly	ADV
cana-2055	234	4	shows	show	VERB
cana-2055	234	5	that	that	SCONJ
cana-2055	234	6	the	the	DET
cana-2055	234	7	suggested	suggest	VERB
cana-2055	234	8	approach	approach	NOUN
cana-2055	234	9	outperforms	outperform	VERB
cana-2055	234	10	the	the	DET
cana-2055	234	11	current	current	ADJ
cana-2055	234	12	systems	system	NOUN
cana-2055	234	13	.	.	PUNCT
cana-2055	235	1	compared	compare	VERB
cana-2055	235	2	to	to	ADP
cana-2055	235	3	dcnn	dcnn	PROPN
cana-2055	235	4	(	(	PUNCT
cana-2055	235	5	96.28	96.28	NUM
cana-2055	235	6	)	)	PUNCT
cana-2055	235	7	,	,	PUNCT
cana-2055	235	8	dbn	dbn	PROPN
cana-2055	235	9	(	(	PUNCT
cana-2055	235	10	94.17	94.17	NUM
cana-2055	235	11	)	)	PUNCT
cana-2055	235	12	,	,	PUNCT
cana-2055	235	13	elm	elm	PROPN
cana-2055	235	14	(	(	PUNCT
cana-2055	235	15	90.03	90.03	NUM
cana-2055	235	16	)	)	PUNCT
cana-2055	235	17	,	,	PUNCT
cana-2055	235	18	and	and	CCONJ
cana-2055	235	19	rf	rf	ADJ
cana-2055	235	20	(	(	PUNCT
cana-2055	235	21	89.22	89.22	NUM
cana-2055	235	22	)	)	PUNCT
cana-2055	235	23	,	,	PUNCT
cana-2055	235	24	the	the	DET
cana-2055	235	25	suggested	suggest	VERB
cana-2055	235	26	wtdcnn	wtdcnn	PROPN
cana-2055	235	27	achieves	achieve	VERB
cana-2055	235	28	a	a	DET
cana-2055	235	29	pr	pr	NOUN
cana-2055	235	30	of	of	ADP
cana-2055	235	31	98.68	98.68	NUM
cana-2055	235	32	.	.	PUNCT
cana-2055	236	1	similarly	similarly	ADV
cana-2055	236	2	,	,	PUNCT
cana-2055	236	3	the	the	DET
cana-2055	236	4	proposed	propose	VERB
cana-2055	236	5	technique	technique	NOUN
cana-2055	236	6	outperforms	outperform	VERB
cana-2055	236	7	other	other	ADJ
cana-2055	236	8	current	current	ADJ
cana-2055	236	9	systems	system	NOUN
cana-2055	236	10	in	in	ADP
cana-2055	236	11	terms	term	NOUN
cana-2055	236	12	of	of	ADP
cana-2055	236	13	accuracy	accuracy	NOUN
cana-2055	236	14	.	.	PUNCT
cana-2055	237	1	for	for	ADP
cana-2055	237	2	example	example	NOUN
cana-2055	237	3	,	,	PUNCT
cana-2055	237	4	wtdcnn	wtdcnn	VERB
cana-2055	237	5	achieves	achieve	VERB
cana-2055	237	6	an	an	DET
cana-2055	237	7	ac	ac	NOUN
cana-2055	237	8	of	of	ADP
cana-2055	237	9	98.97	98.97	NUM
cana-2055	237	10	,	,	PUNCT
cana-2055	237	11	whereas	whereas	SCONJ
cana-2055	237	12	rf	rf	ADJ
cana-2055	237	13	,	,	PUNCT
cana-2055	237	14	elm	elm	PROPN
cana-2055	237	15	,	,	PUNCT
cana-2055	237	16	dbn	dbn	PROPN
cana-2055	237	17	,	,	PUNCT
cana-2055	237	18	and	and	CCONJ
cana-2055	237	19	dcnn	dcnn	PROPN
cana-2055	237	20	achieve	achieve	VERB
cana-2055	237	21	lesser	less	ADJ
cana-2055	237	22	ac	ac	PROPN
cana-2055	237	23	values	value	NOUN
cana-2055	237	24	of	of	ADP
cana-2055	237	25	96.99	96.99	NUM
cana-2055	237	26	,	,	PUNCT
cana-2055	237	27	94.44	94.44	NUM
cana-2055	237	28	,	,	PUNCT
cana-2055	237	29	90.35	90.35	NUM
cana-2055	237	30	,	,	PUNCT
cana-2055	237	31	and	and	CCONJ
cana-2055	237	32	89.22	89.22	NUM
cana-2055	237	33	,	,	PUNCT
cana-2055	237	34	respectively	respectively	ADV
cana-2055	237	35	.	.	PUNCT
cana-2055	238	1	figure	figure	NOUN
cana-2055	238	2	.	.	PUNCT
cana-2055	239	1	3	3	NUM
cana-2055	239	2	evaluation	evaluation	NOUN
cana-2055	239	3	of	of	ADP
cana-2055	239	4	ac	ac	PROPN
cana-2055	239	5	and	and	CCONJ
cana-2055	239	6	pr	pr	NOUN
cana-2055	239	7	.	.	PUNCT
cana-2055	239	8	figure	figure	NOUN
cana-2055	239	9	4	4	NUM
cana-2055	239	10	displays	display	VERB
cana-2055	239	11	the	the	DET
cana-2055	239	12	results	result	NOUN
cana-2055	239	13	of	of	ADP
cana-2055	239	14	the	the	DET
cana-2055	239	15	methods	method	NOUN
cana-2055	239	16	with	with	ADP
cana-2055	239	17	respect	respect	NOUN
cana-2055	239	18	to	to	ADP
cana-2055	239	19	fm	fm	PROPN
cana-2055	239	20	and	and	CCONJ
cana-2055	239	21	rc	rc	PROPN
cana-2055	239	22	.	.	PUNCT
cana-2055	240	1	the	the	DET
cana-2055	240	2	suggested	suggest	VERB
cana-2055	240	3	model	model	NOUN
cana-2055	240	4	outperforms	outperform	VERB
cana-2055	240	5	the	the	DET
cana-2055	240	6	current	current	ADJ
cana-2055	240	7	systems	system	NOUN
cana-2055	240	8	,	,	PUNCT
cana-2055	240	9	as	as	SCONJ
cana-2055	240	10	can	can	AUX
cana-2055	240	11	be	be	AUX
cana-2055	240	12	seen	see	VERB
cana-2055	240	13	from	from	ADP
cana-2055	240	14	the	the	DET
cana-2055	240	15	picture	picture	NOUN
cana-2055	240	16	.	.	PUNCT
cana-2055	241	1	compared	compare	VERB
cana-2055	241	2	to	to	ADP
cana-2055	241	3	dcnn	dcnn	PROPN
cana-2055	241	4	(	(	PUNCT
cana-2055	241	5	96.79	96.79	NUM
cana-2055	241	6	)	)	PUNCT
cana-2055	241	7	,	,	PUNCT
cana-2055	241	8	dbn	dbn	PROPN
cana-2055	241	9	(	(	PUNCT
cana-2055	241	10	94.36	94.36	NUM
cana-2055	241	11	)	)	PUNCT
cana-2055	241	12	,	,	PUNCT
cana-2055	241	13	elm	elm	PROPN
cana-2055	241	14	(	(	PUNCT
cana-2055	241	15	90.28	90.28	NUM
cana-2055	241	16	)	)	PUNCT
cana-2055	241	17	,	,	PUNCT
cana-2055	241	18	and	and	CCONJ
cana-2055	241	19	rf	rf	ADJ
cana-2055	241	20	(	(	PUNCT
cana-2055	241	21	89.20	89.20	NUM
cana-2055	241	22	)	)	PUNCT
cana-2055	241	23	,	,	PUNCT
cana-2055	241	24	the	the	DET
cana-2055	241	25	suggested	suggest	VERB
cana-2055	241	26	wtdcnn	wtdcnn	PROPN
cana-2055	241	27	achieves	achieve	VERB
cana-2055	241	28	an	an	DET
cana-2055	241	29	fm	fm	NOUN
cana-2055	241	30	of	of	ADP
cana-2055	241	31	98.88	98.88	NUM
cana-2055	241	32	.	.	PUNCT
cana-2055	242	1	the	the	DET
cana-2055	242	2	wtdcnn	wtdcnn	NOUN
cana-2055	242	3	achieves	achieve	VERB
cana-2055	242	4	the	the	DET
cana-2055	242	5	maximum	maximum	PROPN
cana-2055	242	6	rc	rc	PROPN
cana-2055	242	7	of	of	ADP
cana-2055	242	8	99.04	99.04	NUM
cana-2055	242	9	,	,	PUNCT
cana-2055	242	10	whereas	whereas	SCONJ
cana-2055	242	11	elm	elm	PROPN
cana-2055	242	12	,	,	PUNCT
cana-2055	242	13	rf	rf	NOUN
cana-2055	242	14	,	,	PUNCT
cana-2055	242	15	dcnn	dcnn	ADJ
cana-2055	242	16	,	,	PUNCT
cana-2055	242	17	and	and	CCONJ
cana-2055	242	18	dbn	dbn	PROPN
cana-2055	242	19	achieve	achieve	VERB
cana-2055	242	20	lesser	less	ADJ
cana-2055	242	21	rcs	rcs	NOUN
cana-2055	242	22	of	of	ADP
cana-2055	242	23	97.04	97.04	NUM
cana-2055	242	24	,	,	PUNCT
cana-2055	242	25	94.67	94.67	NUM
cana-2055	242	26	,	,	PUNCT
cana-2055	242	27	90.47	90.47	NUM
cana-2055	242	28	,	,	PUNCT
cana-2055	242	29	and	and	CCONJ
cana-2055	242	30	89.33	89.33	NUM
cana-2055	242	31	,	,	PUNCT
cana-2055	242	32	respectively	respectively	ADV
cana-2055	242	33	.	.	PUNCT
cana-2055	243	1	this	this	PRON
cana-2055	243	2	means	mean	VERB
cana-2055	243	3	that	that	SCONJ
cana-2055	243	4	the	the	DET
cana-2055	243	5	suggested	suggest	VERB
cana-2055	243	6	approach	approach	NOUN
cana-2055	243	7	outperforms	outperform	VERB
cana-2055	243	8	other	other	ADJ
cana-2055	243	9	current	current	ADJ
cana-2055	243	10	systems	system	NOUN
cana-2055	243	11	.	.	PUNCT
cana-2055	244	1	figure	figure	NOUN
cana-2055	244	2	.	.	PUNCT
cana-2055	245	1	4	4	NUM
cana-2055	245	2	fm	fm	NOUN
cana-2055	245	3	and	and	CCONJ
cana-2055	245	4	rc	rc	PROPN
cana-2055	245	5	analysis	analysis	NOUN
cana-2055	245	6	.	.	PUNCT
cana-2055	246	1	communications	communication	NOUN
cana-2055	246	2	on	on	ADP
cana-2055	246	3	applied	apply	VERB
cana-2055	246	4	nonlinear	nonlinear	ADJ
cana-2055	246	5	analysis	analysis	NOUN
cana-2055	246	6	issn	issn	NOUN
cana-2055	246	7	:	:	PUNCT
cana-2055	246	8	1074	1074	NUM
cana-2055	246	9	-	-	PUNCT
cana-2055	246	10	133x	133x	NUM
cana-2055	246	11	vol	vol	NOUN
cana-2055	246	12	32	32	NUM
cana-2055	246	13	no	no	NOUN
cana-2055	246	14	.	.	NOUN
cana-2055	246	15	3	3	NUM
cana-2055	246	16	(	(	PUNCT
cana-2055	246	17	2025	2025	NUM
cana-2055	246	18	)	)	PUNCT
cana-2055	246	19	589	589	NUM
cana-2055	246	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-2055	247	1	the	the	PRON
cana-2055	247	2	suggested	suggest	VERB
cana-2055	247	3	one	one	NOUN
cana-2055	247	4	's	's	PART
cana-2055	247	5	results	result	NOUN
cana-2055	247	6	are	be	AUX
cana-2055	247	7	then	then	ADV
cana-2055	247	8	examined	examine	VERB
cana-2055	247	9	using	use	VERB
cana-2055	247	10	error	error	NOUN
cana-2055	247	11	metrics	metric	NOUN
cana-2055	247	12	,	,	PUNCT
cana-2055	247	13	such	such	ADJ
cana-2055	247	14	as	as	ADP
cana-2055	247	15	frr	frr	NOUN
cana-2055	247	16	,	,	PUNCT
cana-2055	247	17	fpr	fpr	NOUN
cana-2055	247	18	,	,	PUNCT
cana-2055	247	19	rmse	rmse	NOUN
cana-2055	247	20	,	,	PUNCT
cana-2055	247	21	fnr	fnr	PROPN
cana-2055	247	22	,	,	PUNCT
cana-2055	247	23	and	and	CCONJ
cana-2055	247	24	mse	mse	NOUN
cana-2055	247	25	metrics	metric	NOUN
cana-2055	247	26	.	.	PUNCT
cana-2055	248	1	comparing	compare	VERB
cana-2055	248	2	the	the	DET
cana-2055	248	3	results	result	NOUN
cana-2055	248	4	of	of	ADP
cana-2055	248	5	the	the	DET
cana-2055	248	6	proposed	propose	VERB
cana-2055	248	7	technique	technique	NOUN
cana-2055	248	8	to	to	ADP
cana-2055	248	9	those	those	PRON
cana-2055	248	10	of	of	ADP
cana-2055	248	11	the	the	DET
cana-2055	248	12	current	current	ADJ
cana-2055	248	13	dcnn	dcnn	PROPN
cana-2055	248	14	,	,	PUNCT
cana-2055	248	15	dbn	dbn	PROPN
cana-2055	248	16	,	,	PUNCT
cana-2055	248	17	elm	elm	PROPN
cana-2055	248	18	,	,	PUNCT
cana-2055	248	19	and	and	CCONJ
cana-2055	248	20	rf	rf	NOUN
cana-2055	248	21	approaches	approach	NOUN
cana-2055	248	22	in	in	ADP
cana-2055	248	23	terms	term	NOUN
cana-2055	248	24	of	of	ADP
cana-2055	248	25	mse	mse	NOUN
cana-2055	248	26	,	,	PUNCT
cana-2055	248	27	rmse	rmse	PROPN
cana-2055	248	28	,	,	PUNCT
cana-2055	248	29	fpr	fpr	NOUN
cana-2055	248	30	,	,	PUNCT
cana-2055	248	31	fnr	fnr	PROPN
cana-2055	248	32	,	,	PUNCT
cana-2055	248	33	and	and	CCONJ
cana-2055	248	34	frr	frr	NOUN
cana-2055	248	35	.	.	PUNCT
cana-2055	249	1	by	by	ADP
cana-2055	249	2	reducing	reduce	VERB
cana-2055	249	3	classification	classification	NOUN
cana-2055	249	4	error	error	NOUN
cana-2055	249	5	values	value	NOUN
cana-2055	249	6	,	,	PUNCT
cana-2055	249	7	the	the	DET
cana-2055	249	8	findings	finding	NOUN
cana-2055	249	9	shown	show	VERB
cana-2055	249	10	that	that	SCONJ
cana-2055	249	11	the	the	DET
cana-2055	249	12	suggested	suggest	VERB
cana-2055	249	13	strategy	strategy	NOUN
cana-2055	249	14	outperforms	outperform	VERB
cana-2055	249	15	the	the	DET
cana-2055	249	16	current	current	ADJ
cana-2055	249	17	models	model	NOUN
cana-2055	249	18	.	.	PUNCT
cana-2055	250	1	since	since	SCONJ
cana-2055	250	2	the	the	DET
cana-2055	250	3	current	current	ADJ
cana-2055	250	4	approaches	approach	NOUN
cana-2055	250	5	had	have	VERB
cana-2055	250	6	greater	great	ADJ
cana-2055	250	7	error	error	NOUN
cana-2055	250	8	values	value	NOUN
cana-2055	250	9	,	,	PUNCT
cana-2055	250	10	the	the	DET
cana-2055	250	11	suggested	suggest	VERB
cana-2055	250	12	method	method	NOUN
cana-2055	250	13	demonstrated	demonstrate	VERB
cana-2055	250	14	superior	superior	ADJ
cana-2055	250	15	performance	performance	NOUN
cana-2055	250	16	with	with	ADP
cana-2055	250	17	frr	frr	PROPN
cana-2055	250	18	,	,	PUNCT
cana-2055	250	19	mse	mse	PROPN
cana-2055	250	20	,	,	PUNCT
cana-2055	250	21	fnr	fnr	PROPN
cana-2055	250	22	,	,	PUNCT
cana-2055	250	23	fpr	fpr	NOUN
cana-2055	250	24	,	,	PUNCT
cana-2055	250	25	and	and	CCONJ
cana-2055	250	26	rmse	rmse	ADJ
cana-2055	250	27	values	value	NOUN
cana-2055	250	28	of	of	ADP
cana-2055	250	29	0.035	0.035	NUM
cana-2055	250	30	,	,	PUNCT
cana-2055	250	31	0.220	0.220	NUM
cana-2055	250	32	,	,	PUNCT
cana-2055	250	33	0.030	0.030	NUM
cana-2055	250	34	,	,	PUNCT
cana-2055	250	35	0.066	0.066	NUM
cana-2055	250	36	,	,	PUNCT
cana-2055	250	37	and	and	CCONJ
cana-2055	250	38	0.062	0.062	NUM
cana-2055	250	39	,	,	PUNCT
cana-2055	250	40	respectively	respectively	ADV
cana-2055	250	41	.	.	PUNCT
cana-2055	251	1	a	a	DET
cana-2055	251	2	sound	sound	ADJ
cana-2055	251	3	system	system	NOUN
cana-2055	251	4	,	,	PUNCT
cana-2055	251	5	on	on	ADP
cana-2055	251	6	the	the	DET
cana-2055	251	7	other	other	ADJ
cana-2055	251	8	hand	hand	NOUN
cana-2055	251	9	,	,	PUNCT
cana-2055	251	10	will	will	AUX
cana-2055	251	11	have	have	VERB
cana-2055	251	12	lower	low	ADJ
cana-2055	251	13	error	error	NOUN
cana-2055	251	14	levels	level	NOUN
cana-2055	251	15	.	.	PUNCT
cana-2055	252	1	the	the	DET
cana-2055	252	2	results	result	NOUN
cana-2055	252	3	showed	show	VERB
cana-2055	252	4	that	that	SCONJ
cana-2055	252	5	the	the	DET
cana-2055	252	6	suggested	suggest	VERB
cana-2055	252	7	approach	approach	NOUN
cana-2055	252	8	outperformed	outperform	VERB
cana-2055	252	9	the	the	DET
cana-2055	252	10	state	state	NOUN
cana-2055	252	11	-	-	PUNCT
cana-2055	252	12	of	of	ADP
cana-2055	252	13	-	-	PUNCT
cana-2055	252	14	the	the	DET
cana-2055	252	15	-	-	PUNCT
cana-2055	252	16	art	art	NOUN
cana-2055	252	17	methods	method	NOUN
cana-2055	252	18	for	for	ADP
cana-2055	252	19	precise	precise	ADJ
cana-2055	252	20	cyp	cyp	NOUN
cana-2055	252	21	.	.	PUNCT
cana-2055	253	1	in	in	ADP
cana-2055	253	2	figures	figure	NOUN
cana-2055	253	3	5	5	NUM
cana-2055	253	4	and	and	CCONJ
cana-2055	253	5	6	6	NUM
cana-2055	253	6	,	,	PUNCT
cana-2055	253	7	you	you	PRON
cana-2055	253	8	can	can	AUX
cana-2055	253	9	see	see	VERB
cana-2055	253	10	a	a	DET
cana-2055	253	11	graphical	graphical	ADJ
cana-2055	253	12	depiction	depiction	NOUN
cana-2055	253	13	.	.	PUNCT
cana-2055	254	1	figure	figure	NOUN
cana-2055	254	2	.	.	PUNCT
cana-2055	255	1	5	5	NUM
cana-2055	255	2	analysis	analysis	NOUN
cana-2055	255	3	of	of	ADP
cana-2055	255	4	mse	mse	NOUN
cana-2055	255	5	and	and	CCONJ
cana-2055	255	6	rmse	rmse	NOUN
cana-2055	255	7	.	.	PUNCT
cana-2055	256	1	figure	figure	NOUN
cana-2055	256	2	5	5	NUM
cana-2055	256	3	illustrates	illustrate	VERB
cana-2055	256	4	the	the	DET
cana-2055	256	5	mean	mean	ADJ
cana-2055	256	6	squared	square	VERB
cana-2055	256	7	error	error	NOUN
cana-2055	256	8	(	(	PUNCT
cana-2055	256	9	mse	mse	NOUN
cana-2055	256	10	)	)	PUNCT
cana-2055	256	11	and	and	CCONJ
cana-2055	256	12	root	root	NOUN
cana-2055	256	13	mean	mean	VERB
cana-2055	256	14	squared	square	VERB
cana-2055	256	15	error	error	NOUN
cana-2055	256	16	(	(	PUNCT
cana-2055	256	17	rmse	rmse	NOUN
cana-2055	256	18	)	)	PUNCT
cana-2055	256	19	of	of	ADP
cana-2055	256	20	both	both	CCONJ
cana-2055	256	21	the	the	DET
cana-2055	256	22	proposed	propose	VERB
cana-2055	256	23	and	and	CCONJ
cana-2055	256	24	current	current	ADJ
cana-2055	256	25	classifiers	classifier	NOUN
cana-2055	256	26	.	.	PUNCT
cana-2055	257	1	the	the	DET
cana-2055	257	2	new	new	ADJ
cana-2055	257	3	model	model	NOUN
cana-2055	257	4	demonstrably	demonstrably	ADV
cana-2055	257	5	outperforms	outperform	VERB
cana-2055	257	6	the	the	DET
cana-2055	257	7	previous	previous	ADJ
cana-2055	257	8	approaches	approach	NOUN
cana-2055	257	9	.	.	PUNCT
cana-2055	258	1	the	the	DET
cana-2055	258	2	suggested	suggest	VERB
cana-2055	258	3	wtdcnn	wtdcnn	PROPN
cana-2055	258	4	achieves	achieve	VERB
cana-2055	258	5	a	a	DET
cana-2055	258	6	mean	mean	ADJ
cana-2055	258	7	squared	square	VERB
cana-2055	258	8	error	error	NOUN
cana-2055	258	9	(	(	PUNCT
cana-2055	258	10	mse	mse	NOUN
cana-2055	258	11	)	)	PUNCT
cana-2055	258	12	of	of	ADP
cana-2055	258	13	0.035	0.035	NUM
cana-2055	258	14	,	,	PUNCT
cana-2055	258	15	which	which	PRON
cana-2055	258	16	is	be	AUX
cana-2055	258	17	superior	superior	ADJ
cana-2055	258	18	to	to	ADP
cana-2055	258	19	that	that	PRON
cana-2055	258	20	of	of	ADP
cana-2055	258	21	dcnn	dcnn	PROPN
cana-2055	258	22	(	(	PUNCT
cana-2055	258	23	0.096	0.096	NUM
cana-2055	258	24	)	)	PUNCT
cana-2055	258	25	,	,	PUNCT
cana-2055	258	26	dbn	dbn	PROPN
cana-2055	258	27	(	(	PUNCT
cana-2055	258	28	0.125	0.125	NUM
cana-2055	258	29	)	)	PUNCT
cana-2055	258	30	,	,	PUNCT
cana-2055	258	31	elm	elm	PROPN
cana-2055	258	32	(	(	PUNCT
cana-2055	258	33	0.346	0.346	NUM
cana-2055	258	34	)	)	PUNCT
cana-2055	258	35	,	,	PUNCT
cana-2055	258	36	and	and	CCONJ
cana-2055	258	37	rf	rf	ADJ
cana-2055	258	38	(	(	PUNCT
cana-2055	258	39	0.399	0.399	NUM
cana-2055	258	40	)	)	PUNCT
cana-2055	258	41	.	.	PUNCT
cana-2055	259	1	similarly	similarly	ADV
cana-2055	259	2	,	,	PUNCT
cana-2055	259	3	rmse	rmse	PROPN
cana-2055	259	4	achieved	achieve	VERB
cana-2055	259	5	by	by	ADP
cana-2055	259	6	the	the	DET
cana-2055	259	7	proposed	propose	VERB
cana-2055	259	8	method	method	NOUN
cana-2055	259	9	is	be	AUX
cana-2055	259	10	lower	low	ADJ
cana-2055	259	11	than	than	ADP
cana-2055	259	12	that	that	PRON
cana-2055	259	13	of	of	ADP
cana-2055	259	14	other	other	ADJ
cana-2055	259	15	existing	exist	VERB
cana-2055	259	16	schemes	scheme	NOUN
cana-2055	259	17	;	;	PUNCT
cana-2055	259	18	for	for	ADP
cana-2055	259	19	example	example	NOUN
cana-2055	259	20	,	,	PUNCT
cana-2055	259	21	the	the	DET
cana-2055	259	22	rmse	rmse	NOUN
cana-2055	259	23	achieved	achieve	VERB
cana-2055	259	24	by	by	ADP
cana-2055	259	25	the	the	DET
cana-2055	259	26	wtdcnn	wtdcnn	NOUN
cana-2055	259	27	is	be	AUX
cana-2055	259	28	0.220	0.220	NUM
cana-2055	259	29	,	,	PUNCT
cana-2055	259	30	while	while	SCONJ
cana-2055	259	31	the	the	DET
cana-2055	259	32	rmses	rmse	NOUN
cana-2055	259	33	obtained	obtain	VERB
cana-2055	259	34	by	by	ADP
cana-2055	259	35	the	the	DET
cana-2055	259	36	current	current	ADJ
cana-2055	259	37	schemes	scheme	NOUN
cana-2055	259	38	,	,	PUNCT
cana-2055	259	39	namely	namely	ADV
cana-2055	259	40	dcnn	dcnn	ADJ
cana-2055	259	41	,	,	PUNCT
cana-2055	259	42	dbn	dbn	PROPN
cana-2055	259	43	,	,	PUNCT
cana-2055	259	44	elm	elm	PROPN
cana-2055	259	45	,	,	PUNCT
cana-2055	259	46	and	and	CCONJ
cana-2055	259	47	rf	rf	NOUN
cana-2055	259	48	,	,	PUNCT
cana-2055	259	49	are	be	AUX
cana-2055	259	50	0.413	0.413	NUM
cana-2055	259	51	,	,	PUNCT
cana-2055	259	52	0.483	0.483	NUM
cana-2055	259	53	,	,	PUNCT
cana-2055	259	54	0.368	0.368	NUM
cana-2055	259	55	,	,	PUNCT
cana-2055	259	56	and	and	CCONJ
cana-2055	259	57	0.299	0.299	NUM
cana-2055	259	58	,	,	PUNCT
cana-2055	259	59	respectively	respectively	ADV
cana-2055	259	60	.	.	PUNCT
cana-2055	259	61	figure	figure	NOUN
cana-2055	259	62	.	.	PUNCT
cana-2055	260	1	6	6	NUM
cana-2055	260	2	fnr	fnr	NOUN
cana-2055	260	3	and	and	CCONJ
cana-2055	260	4	fpr	fpr	NOUN
cana-2055	260	5	evaluation	evaluation	NOUN
cana-2055	260	6	.	.	PUNCT
cana-2055	261	1	both	both	CCONJ
cana-2055	261	2	the	the	DET
cana-2055	261	3	current	current	ADJ
cana-2055	261	4	and	and	CCONJ
cana-2055	261	5	proposed	proposed	ADJ
cana-2055	261	6	classifiers	classifier	NOUN
cana-2055	261	7	'	'	PART
cana-2055	261	8	fpr	fpr	NOUN
cana-2055	261	9	and	and	CCONJ
cana-2055	261	10	fnr	fnr	PROPN
cana-2055	261	11	are	be	AUX
cana-2055	261	12	shown	show	VERB
cana-2055	261	13	in	in	ADP
cana-2055	261	14	figure	figure	NOUN
cana-2055	261	15	6	6	NUM
cana-2055	261	16	.	.	PUNCT
cana-2055	262	1	it	it	PRON
cana-2055	262	2	was	be	AUX
cana-2055	262	3	obvious	obvious	ADJ
cana-2055	262	4	that	that	SCONJ
cana-2055	262	5	the	the	DET
cana-2055	262	6	suggested	suggest	VERB
cana-2055	262	7	model	model	NOUN
cana-2055	262	8	outperformed	outperform	VERB
cana-2055	262	9	the	the	DET
cana-2055	262	10	previous	previous	ADJ
cana-2055	262	11	approaches	approach	NOUN
cana-2055	262	12	.	.	PUNCT
cana-2055	263	1	compared	compare	VERB
cana-2055	263	2	to	to	ADP
cana-2055	263	3	dcnn	dcnn	PROPN
cana-2055	263	4	(	(	PUNCT
cana-2055	263	5	0.090	0.090	NUM
cana-2055	263	6	)	)	PUNCT
cana-2055	263	7	,	,	PUNCT
cana-2055	263	8	dbn	dbn	PROPN
cana-2055	263	9	(	(	PUNCT
cana-2055	263	10	0.122	0.122	NUM
cana-2055	263	11	)	)	PUNCT
cana-2055	263	12	,	,	PUNCT
cana-2055	263	13	elm	elm	NOUN
cana-2055	263	14	(	(	PUNCT
cana-2055	263	15	0.335	0.335	NUM
cana-2055	263	16	)	)	PUNCT
cana-2055	263	17	,	,	PUNCT
cana-2055	263	18	and	and	CCONJ
cana-2055	263	19	rf	rf	ADJ
cana-2055	263	20	(	(	PUNCT
cana-2055	263	21	0.380	0.380	NUM
cana-2055	263	22	)	)	PUNCT
cana-2055	263	23	,	,	PUNCT
cana-2055	263	24	suggest	suggest	VERB
cana-2055	263	25	the	the	DET
cana-2055	263	26	wtdcnn	wtdcnn	NOUN
cana-2055	263	27	achieves	achieve	VERB
cana-2055	263	28	a	a	DET
cana-2055	263	29	lower	low	ADJ
cana-2055	263	30	fpr	fpr	NOUN
cana-2055	263	31	of	of	ADP
cana-2055	263	32	0.030	0.030	NUM
cana-2055	263	33	.	.	PUNCT
cana-2055	264	1	just	just	ADV
cana-2055	264	2	as	as	SCONJ
cana-2055	264	3	the	the	DET
cana-2055	264	4	wtdcnn	wtdcnn	NOUN
cana-2055	264	5	achieves	achieve	VERB
cana-2055	264	6	the	the	DET
cana-2055	264	7	lowest	low	ADJ
cana-2055	264	8	fnr	fnr	NOUN
cana-2055	264	9	of	of	ADP
cana-2055	264	10	0.065	0.065	NUM
cana-2055	264	11	,	,	PUNCT
cana-2055	264	12	the	the	DET
cana-2055	264	13	suggested	suggest	VERB
cana-2055	264	14	approach	approach	NOUN
cana-2055	264	15	also	also	ADV
cana-2055	264	16	achieves	achieve	VERB
cana-2055	264	17	the	the	DET
cana-2055	264	18	lowest	low	ADJ
cana-2055	264	19	rmse	rmse	NOUN
cana-2055	264	20	compared	compare	VERB
cana-2055	264	21	to	to	ADP
cana-2055	264	22	other	other	ADJ
cana-2055	264	23	current	current	ADJ
cana-2055	264	24	systems	system	NOUN
cana-2055	264	25	like	like	ADP
cana-2055	264	26	dcnn	dcnn	PROPN
cana-2055	264	27	,	,	PUNCT
cana-2055	264	28	dbn	dbn	PROPN
cana-2055	264	29	,	,	PUNCT
cana-2055	264	30	elm	elm	PROPN
cana-2055	264	31	,	,	PUNCT
cana-2055	264	32	and	and	CCONJ
cana-2055	264	33	rf	rf	NOUN
cana-2055	264	34	,	,	PUNCT
cana-2055	264	35	which	which	PRON
cana-2055	264	36	are	be	AUX
cana-2055	264	37	0.259	0.259	NUM
cana-2055	264	38	,	,	PUNCT
cana-2055	264	39	0.323	0.323	NUM
cana-2055	264	40	,	,	PUNCT
cana-2055	264	41	0.424	0.424	NUM
cana-2055	264	42	,	,	PUNCT
cana-2055	264	43	and	and	CCONJ
cana-2055	264	44	0.195	0.195	NUM
cana-2055	264	45	,	,	PUNCT
cana-2055	264	46	respectively	respectively	ADV
cana-2055	264	47	.	.	PUNCT
cana-2055	265	1	our	our	PRON
cana-2055	265	2	model	model	NOUN
cana-2055	265	3	's	's	PART
cana-2055	265	4	superior	superior	ADJ
cana-2055	265	5	performance	performance	NOUN
cana-2055	265	6	compared	compare	VERB
cana-2055	265	7	to	to	ADP
cana-2055	265	8	wtdcnn	wtdcnn	PRON
cana-2055	265	9	shows	show	VERB
cana-2055	265	10	how	how	SCONJ
cana-2055	265	11	our	our	PRON
cana-2055	265	12	suggested	suggest	VERB
cana-2055	265	13	work	work	NOUN
cana-2055	265	14	is	be	AUX
cana-2055	265	15	unique	unique	ADJ
cana-2055	265	16	thanks	thank	NOUN
cana-2055	265	17	to	to	ADP
cana-2055	265	18	the	the	DET
cana-2055	265	19	correct	correct	ADJ
cana-2055	265	20	data	datum	NOUN
cana-2055	265	21	preparation	preparation	NOUN
cana-2055	265	22	techniques	technique	NOUN
cana-2055	265	23	,	,	PUNCT
cana-2055	265	24	architecture	architecture	NOUN
cana-2055	265	25	,	,	PUNCT
cana-2055	265	26	and	and	CCONJ
cana-2055	265	27	settings	setting	VERB
cana-2055	265	28	communications	communication	NOUN
cana-2055	265	29	on	on	ADP
cana-2055	265	30	applied	apply	VERB
cana-2055	265	31	nonlinear	nonlinear	ADJ
cana-2055	265	32	analysis	analysis	NOUN
cana-2055	265	33	issn	issn	NOUN
cana-2055	265	34	:	:	PUNCT
cana-2055	265	35	1074	1074	NUM
cana-2055	265	36	-	-	PUNCT
cana-2055	265	37	133x	133x	NUM
cana-2055	265	38	vol	vol	NOUN
cana-2055	265	39	32	32	NUM
cana-2055	265	40	no	no	NOUN
cana-2055	265	41	.	.	NOUN
cana-2055	265	42	3	3	NUM
cana-2055	265	43	(	(	PUNCT
cana-2055	265	44	2025	2025	NUM
cana-2055	265	45	)	)	PUNCT
cana-2055	265	46	590	590	NUM
cana-2055	265	47	https://internationalpubls.com	https://internationalpubls.com	X
cana-2055	265	48	for	for	ADP
cana-2055	265	49	the	the	DET
cana-2055	265	50	hyperparameters	hyperparameter	NOUN
cana-2055	265	51	.	.	PUNCT
cana-2055	266	1	the	the	DET
cana-2055	266	2	suggested	suggest	VERB
cana-2055	266	3	one	one	PRON
cana-2055	266	4	makes	make	VERB
cana-2055	266	5	effective	effective	ADJ
cana-2055	266	6	use	use	NOUN
cana-2055	266	7	of	of	ADP
cana-2055	266	8	the	the	DET
cana-2055	266	9	dr	dr	PROPN
cana-2055	266	10	approach	approach	NOUN
cana-2055	266	11	and	and	CCONJ
cana-2055	266	12	preprocesses	preprocesse	NOUN
cana-2055	266	13	the	the	DET
cana-2055	266	14	data	datum	NOUN
cana-2055	266	15	set	set	VERB
cana-2055	266	16	before	before	ADP
cana-2055	266	17	making	make	VERB
cana-2055	266	18	predictions	prediction	NOUN
cana-2055	266	19	.	.	PUNCT
cana-2055	267	1	consequently	consequently	ADV
cana-2055	267	2	,	,	PUNCT
cana-2055	267	3	these	these	DET
cana-2055	267	4	methods	method	NOUN
cana-2055	267	5	provide	provide	VERB
cana-2055	267	6	better	well	ADJ
cana-2055	267	7	forecasts	forecast	NOUN
cana-2055	267	8	.	.	PUNCT
cana-2055	268	1	5	5	X
cana-2055	268	2	.	.	X
cana-2055	268	3	conclusion	conclusion	NOUN
cana-2055	268	4	and	and	CCONJ
cana-2055	268	5	future	future	ADJ
cana-2055	268	6	work	work	NOUN
cana-2055	268	7	in	in	ADP
cana-2055	268	8	order	order	NOUN
cana-2055	268	9	to	to	PART
cana-2055	268	10	improve	improve	VERB
cana-2055	268	11	cyp	cyp	ADJ
cana-2055	268	12	efficiency	efficiency	NOUN
cana-2055	268	13	for	for	ADP
cana-2055	268	14	regional	regional	ADJ
cana-2055	268	15	crops	crop	NOUN
cana-2055	268	16	in	in	ADP
cana-2055	268	17	india	india	PROPN
cana-2055	268	18	,	,	PUNCT
cana-2055	268	19	this	this	DET
cana-2055	268	20	study	study	NOUN
cana-2055	268	21	proposes	propose	VERB
cana-2055	268	22	dl	dl	PROPN
cana-2055	268	23	and	and	CCONJ
cana-2055	268	24	dr	dr	PROPN
cana-2055	268	25	methods	method	NOUN
cana-2055	268	26	.	.	PUNCT
cana-2055	269	1	there	there	PRON
cana-2055	269	2	are	be	VERB
cana-2055	269	3	'	'	PUNCT
cana-2055	269	4	three	three	NUM
cana-2055	269	5	'	'	PUNCT
cana-2055	269	6	primary	primary	ADJ
cana-2055	269	7	steps	step	NOUN
cana-2055	269	8	to	to	ADP
cana-2055	269	9	the	the	DET
cana-2055	269	10	suggested	suggest	VERB
cana-2055	269	11	system	system	NOUN
cana-2055	269	12	:	:	PUNCT
cana-2055	269	13	preprocessing	preprocessing	NOUN
cana-2055	269	14	,	,	PUNCT
cana-2055	269	15	data	datum	NOUN
cana-2055	269	16	reduction	reduction	NOUN
cana-2055	269	17	,	,	PUNCT
cana-2055	269	18	and	and	CCONJ
cana-2055	269	19	classification	classification	NOUN
cana-2055	269	20	.	.	PUNCT
cana-2055	270	1	in	in	ADP
cana-2055	270	2	terms	term	NOUN
cana-2055	270	3	of	of	ADP
cana-2055	270	4	recall	recall	NOUN
cana-2055	270	5	,	,	PUNCT
cana-2055	270	6	f	f	X
cana-2055	270	7	-	-	PUNCT
cana-2055	270	8	measure	measure	NOUN
cana-2055	270	9	,	,	PUNCT
cana-2055	270	10	accuracy	accuracy	NOUN
cana-2055	270	11	,	,	PUNCT
cana-2055	270	12	precision	precision	NOUN
cana-2055	270	13	,	,	PUNCT
cana-2055	270	14	fpr	fpr	NOUN
cana-2055	270	15	,	,	PUNCT
cana-2055	270	16	fnr	fnr	PROPN
cana-2055	270	17	,	,	PUNCT
cana-2055	270	18	mse	mse	PROPN
cana-2055	270	19	,	,	PUNCT
cana-2055	270	20	frr	frr	PROPN
cana-2055	270	21	,	,	PUNCT
cana-2055	270	22	and	and	CCONJ
cana-2055	270	23	rmse	rmse	NOUN
cana-2055	270	24	,	,	PUNCT
cana-2055	270	25	the	the	DET
cana-2055	270	26	suggested	suggest	VERB
cana-2055	270	27	work	work	NOUN
cana-2055	270	28	's	's	PART
cana-2055	270	29	findings	finding	NOUN
cana-2055	270	30	are	be	AUX
cana-2055	270	31	compared	compare	VERB
cana-2055	270	32	against	against	ADP
cana-2055	270	33	those	those	PRON
cana-2055	270	34	of	of	ADP
cana-2055	270	35	the	the	DET
cana-2055	270	36	traditional	traditional	ADJ
cana-2055	270	37	elm	elm	PROPN
cana-2055	270	38	,	,	PUNCT
cana-2055	270	39	dbn	dbn	PROPN
cana-2055	270	40	,	,	PUNCT
cana-2055	270	41	rf	rf	NOUN
cana-2055	270	42	,	,	PUNCT
cana-2055	270	43	and	and	CCONJ
cana-2055	270	44	dcnn	dcnn	ADJ
cana-2055	270	45	.	.	PUNCT
cana-2055	271	1	because	because	SCONJ
cana-2055	271	2	it	it	PRON
cana-2055	271	3	attains	attain	VERB
cana-2055	271	4	a	a	DET
cana-2055	271	5	maximum	maximum	ADJ
cana-2055	271	6	accuracy	accuracy	NOUN
cana-2055	271	7	of	of	ADP
cana-2055	271	8	98.97	98.97	NUM
cana-2055	271	9	%	%	NOUN
cana-2055	271	10	,	,	PUNCT
cana-2055	271	11	98.68	98.68	NUM
cana-2055	271	12	%	%	NOUN
cana-2055	271	13	precision	precision	NOUN
cana-2055	271	14	,	,	PUNCT
cana-2055	271	15	99.04	99.04	NUM
cana-2055	271	16	%	%	NOUN
cana-2055	271	17	recall	recall	NOUN
cana-2055	271	18	,	,	PUNCT
cana-2055	271	19	and	and	CCONJ
cana-2055	271	20	98.88	98.88	NUM
cana-2055	271	21	%	%	NOUN
cana-2055	271	22	f	f	X
cana-2055	271	23	-	-	NOUN
cana-2055	271	24	measure	measure	NOUN
cana-2055	271	25	,	,	PUNCT
cana-2055	271	26	the	the	DET
cana-2055	271	27	suggested	suggest	VERB
cana-2055	271	28	one	one	NOUN
cana-2055	271	29	produces	produce	VERB
cana-2055	271	30	much	much	ADV
cana-2055	271	31	better	well	ADJ
cana-2055	271	32	results	result	NOUN
cana-2055	271	33	.	.	PUNCT
cana-2055	272	1	with	with	ADP
cana-2055	272	2	reduced	reduce	VERB
cana-2055	272	3	error	error	NOUN
cana-2055	272	4	levels	level	NOUN
cana-2055	272	5	of	of	ADP
cana-2055	272	6	0.035	0.035	NUM
cana-2055	272	7	mse	mse	NOUN
cana-2055	272	8	,	,	PUNCT
cana-2055	272	9	0.220	0.220	NUM
cana-2055	272	10	rmse	rmse	NOUN
cana-2055	272	11	,	,	PUNCT
cana-2055	272	12	0.031	0.031	NUM
cana-2055	272	13	fpr	fpr	NOUN
cana-2055	272	14	,	,	PUNCT
cana-2055	272	15	0.066	0.066	NUM
cana-2055	272	16	and	and	CCONJ
cana-2055	272	17	fnr	fnr	PROPN
cana-2055	272	18	,	,	PUNCT
cana-2055	272	19	the	the	PRON
cana-2055	272	20	suggested	suggest	VERB
cana-2055	272	21	one	one	NUM
cana-2055	272	22	outperforms	outperform	VERB
cana-2055	272	23	the	the	DET
cana-2055	272	24	others	other	NOUN
cana-2055	272	25	.	.	PUNCT
cana-2055	273	1	the	the	DET
cana-2055	273	2	suggested	suggest	VERB
cana-2055	273	3	optimum	optimum	ADJ
cana-2055	273	4	dl	dl	NOUN
cana-2055	273	5	technique	technique	NOUN
cana-2055	273	6	with	with	ADP
cana-2055	273	7	a	a	DET
cana-2055	273	8	realistic	realistic	ADJ
cana-2055	273	9	dr	dr	PROPN
cana-2055	273	10	approach	approach	NOUN
cana-2055	273	11	outperforms	outperform	VERB
cana-2055	273	12	state	state	NOUN
cana-2055	273	13	-	-	PUNCT
cana-2055	273	14	of	of	ADP
cana-2055	273	15	-	-	PUNCT
cana-2055	273	16	the	the	DET
cana-2055	273	17	-	-	PUNCT
cana-2055	273	18	art	art	NOUN
cana-2055	273	19	cyp	cyp	ADJ
cana-2055	273	20	systems	system	NOUN
cana-2055	273	21	.	.	PUNCT
cana-2055	274	1	to	to	PART
cana-2055	274	2	make	make	VERB
cana-2055	274	3	the	the	DET
cana-2055	274	4	model	model	NOUN
cana-2055	274	5	more	more	ADV
cana-2055	274	6	generalisable	generalisable	ADJ
cana-2055	274	7	,	,	PUNCT
cana-2055	274	8	the	the	DET
cana-2055	274	9	scientists	scientist	NOUN
cana-2055	274	10	advise	advise	VERB
cana-2055	274	11	applying	apply	VERB
cana-2055	274	12	the	the	DET
cana-2055	274	13	strategy	strategy	NOUN
cana-2055	274	14	to	to	ADP
cana-2055	274	15	additional	additional	ADJ
cana-2055	274	16	areas	area	NOUN
cana-2055	274	17	and	and	CCONJ
cana-2055	274	18	crops	crop	NOUN
cana-2055	274	19	.	.	PUNCT
cana-2055	275	1	to	to	PART
cana-2055	275	2	strengthen	strengthen	VERB
cana-2055	275	3	the	the	DET
cana-2055	275	4	suggested	suggest	VERB
cana-2055	275	5	technique	technique	NOUN
cana-2055	275	6	,	,	PUNCT
cana-2055	275	7	they	they	PRON
cana-2055	275	8	advise	advise	VERB
cana-2055	275	9	adding	add	VERB
cana-2055	275	10	satellite	satellite	NOUN
cana-2055	275	11	photos	photo	NOUN
cana-2055	275	12	and	and	CCONJ
cana-2055	275	13	sensor	sensor	NOUN
cana-2055	275	14	data	datum	NOUN
cana-2055	275	15	.	.	PUNCT
cana-2055	276	1	in	in	ADP
cana-2055	276	2	conclusion	conclusion	NOUN
cana-2055	276	3	,	,	PUNCT
cana-2055	276	4	the	the	DET
cana-2055	276	5	authors	author	NOUN
cana-2055	276	6	advocate	advocate	VERB
cana-2055	276	7	using	use	VERB
cana-2055	276	8	the	the	DET
cana-2055	276	9	suggested	suggest	VERB
cana-2055	276	10	technique	technique	NOUN
cana-2055	276	11	to	to	PART
cana-2055	276	12	create	create	VERB
cana-2055	276	13	systems	system	NOUN
cana-2055	276	14	that	that	PRON
cana-2055	276	15	support	support	VERB
cana-2055	276	16	decisions	decision	NOUN
cana-2055	276	17	for	for	ADP
cana-2055	276	18	farmers	farmer	NOUN
cana-2055	276	19	to	to	PART
cana-2055	276	20	make	make	VERB
cana-2055	276	21	educated	educated	ADJ
cana-2055	276	22	crops	crop	NOUN
cana-2055	276	23	management	management	NOUN
cana-2055	276	24	and	and	CCONJ
cana-2055	276	25	production	production	NOUN
cana-2055	276	26	choices	choice	NOUN
cana-2055	276	27	.	.	PUNCT
cana-2055	277	1	integrating	integrate	VERB
cana-2055	277	2	the	the	DET
cana-2055	277	3	suggested	suggest	VERB
cana-2055	277	4	technique	technique	NOUN
cana-2055	277	5	with	with	ADP
cana-2055	277	6	precision	precision	NOUN
cana-2055	277	7	agricultural	agricultural	ADJ
cana-2055	277	8	technology	technology	NOUN
cana-2055	277	9	would	would	AUX
cana-2055	277	10	let	let	VERB
cana-2055	277	11	farmers	farmer	NOUN
cana-2055	277	12	anticipate	anticipate	VERB
cana-2055	277	13	crop	crop	NOUN
cana-2055	277	14	yields	yield	NOUN
cana-2055	277	15	and	and	CCONJ
cana-2055	277	16	make	make	VERB
cana-2055	277	17	decisions	decision	NOUN
cana-2055	277	18	in	in	ADP
cana-2055	277	19	real	real	ADJ
cana-2055	277	20	time	time	NOUN
cana-2055	277	21	.	.	PUNCT
cana-2055	278	1	they	they	PRON
cana-2055	278	2	can	can	AUX
cana-2055	278	3	create	create	VERB
cana-2055	278	4	a	a	DET
cana-2055	278	5	web	web	NOUN
cana-2055	278	6	-	-	PUNCT
cana-2055	278	7	based	base	VERB
cana-2055	278	8	tool	tool	NOUN
cana-2055	278	9	to	to	PART
cana-2055	278	10	help	help	VERB
cana-2055	278	11	farmers	farmer	NOUN
cana-2055	278	12	and	and	CCONJ
cana-2055	278	13	policymakers	policymaker	NOUN
cana-2055	278	14	make	make	VERB
cana-2055	278	15	agricultural	agricultural	ADJ
cana-2055	278	16	production	production	NOUN
cana-2055	278	17	and	and	CCONJ
cana-2055	278	18	import	import	NOUN
cana-2055	278	19	-	-	PUNCT
cana-2055	278	20	export	export	NOUN
cana-2055	278	21	choices	choice	NOUN
cana-2055	278	22	using	use	VERB
cana-2055	278	23	the	the	DET
cana-2055	278	24	suggested	suggest	VERB
cana-2055	278	25	technique	technique	NOUN
cana-2055	278	26	.	.	PUNCT
cana-2055	279	1	references	reference	NOUN
cana-2055	279	2	[	[	X
cana-2055	279	3	1	1	NUM
cana-2055	279	4	]	]	PUNCT
cana-2055	279	5	chlingaryan	chlingaryan	PROPN
cana-2055	279	6	,	,	PUNCT
cana-2055	279	7	anna	anna	PROPN
cana-2055	279	8	,	,	PUNCT
cana-2055	279	9	salah	salah	PROPN
cana-2055	279	10	sukkarieh	sukkarieh	PROPN
cana-2055	279	11	,	,	PUNCT
cana-2055	279	12	and	and	CCONJ
cana-2055	279	13	brett	brett	PROPN
cana-2055	279	14	whelan	whelan	PROPN
cana-2055	279	15	.	.	PUNCT
cana-2055	280	1	"	"	PUNCT
cana-2055	280	2	machine	machine	NOUN
cana-2055	280	3	learning	learning	NOUN
cana-2055	280	4	approaches	approach	NOUN
cana-2055	280	5	for	for	ADP
cana-2055	280	6	crop	crop	NOUN
cana-2055	280	7	yield	yield	NOUN
cana-2055	280	8	prediction	prediction	NOUN
cana-2055	280	9	and	and	CCONJ
cana-2055	280	10	nitrogen	nitrogen	NOUN
cana-2055	280	11	status	status	NOUN
cana-2055	280	12	estimation	estimation	NOUN
cana-2055	280	13	in	in	ADP
cana-2055	280	14	precision	precision	NOUN
cana-2055	280	15	agriculture	agriculture	NOUN
cana-2055	280	16	:	:	PUNCT
cana-2055	280	17	a	a	DET
cana-2055	280	18	review	review	NOUN
cana-2055	280	19	.	.	PUNCT
cana-2055	280	20	"	"	PUNCT
cana-2055	280	21	computers	computer	NOUN
cana-2055	280	22	and	and	CCONJ
cana-2055	280	23	electronics	electronic	NOUN
cana-2055	280	24	in	in	ADP
cana-2055	280	25	agriculture	agriculture	NOUN
cana-2055	280	26	151	151	NUM
cana-2055	280	27	(	(	PUNCT
cana-2055	280	28	2018	2018	NUM
cana-2055	280	29	):	):	PUNCT
cana-2055	280	30	61	61	NUM
cana-2055	280	31	-	-	SYM
cana-2055	280	32	69	69	NUM
cana-2055	280	33	.	.	PUNCT
cana-2055	281	1	[	[	X
cana-2055	281	2	2	2	NUM
cana-2055	281	3	]	]	X
cana-2055	281	4	peerlinck	peerlinck	NOUN
cana-2055	281	5	,	,	PUNCT
cana-2055	281	6	amy	amy	PROPN
cana-2055	281	7	,	,	PUNCT
cana-2055	281	8	john	john	PROPN
cana-2055	281	9	sheppard	sheppard	PROPN
cana-2055	281	10	,	,	PUNCT
cana-2055	281	11	and	and	CCONJ
cana-2055	281	12	bruce	bruce	PROPN
cana-2055	281	13	maxwell	maxwell	PROPN
cana-2055	281	14	.	.	PUNCT
cana-2055	282	1	"	"	PUNCT
cana-2055	282	2	using	use	VERB
cana-2055	282	3	deep	deep	ADJ
cana-2055	282	4	learning	learning	NOUN
cana-2055	282	5	in	in	ADP
cana-2055	282	6	yield	yield	NOUN
cana-2055	282	7	and	and	CCONJ
cana-2055	282	8	protein	protein	NOUN
cana-2055	282	9	prediction	prediction	NOUN
cana-2055	282	10	of	of	ADP
cana-2055	282	11	winter	winter	NOUN
cana-2055	282	12	wheat	wheat	NOUN
cana-2055	282	13	based	base	VERB
cana-2055	282	14	on	on	ADP
cana-2055	282	15	fertilization	fertilization	NOUN
cana-2055	282	16	prescriptions	prescription	NOUN
cana-2055	282	17	in	in	ADP
cana-2055	282	18	precision	precision	NOUN
cana-2055	282	19	agriculture	agriculture	NOUN
cana-2055	282	20	.	.	PUNCT
cana-2055	282	21	"	"	PUNCT
cana-2055	283	1	international	international	ADJ
cana-2055	283	2	conference	conference	NOUN
cana-2055	283	3	on	on	ADP
cana-2055	283	4	precision	precision	NOUN
cana-2055	283	5	agriculture	agriculture	NOUN
cana-2055	283	6	(	(	PUNCT
cana-2055	283	7	icpa	icpa	NOUN
cana-2055	283	8	)	)	PUNCT
cana-2055	283	9	.	.	PUNCT
cana-2055	284	1	2018	2018	NUM
cana-2055	284	2	.	.	PUNCT
cana-2055	285	1	[	[	X
cana-2055	285	2	3	3	NUM
cana-2055	285	3	]	]	X
cana-2055	285	4	jin	jin	NOUN
cana-2055	285	5	,	,	PUNCT
cana-2055	285	6	xue	xue	PROPN
cana-2055	285	7	-	-	PUNCT
cana-2055	285	8	bo	bo	PROPN
cana-2055	285	9	,	,	PUNCT
cana-2055	285	10	et	et	PROPN
cana-2055	285	11	al	al	PROPN
cana-2055	285	12	.	.	PUNCT
cana-2055	286	1	"	"	PUNCT
cana-2055	286	2	deep	deep	ADJ
cana-2055	286	3	learning	learning	NOUN
cana-2055	286	4	predictor	predictor	NOUN
cana-2055	286	5	for	for	ADP
cana-2055	286	6	sustainable	sustainable	ADJ
cana-2055	286	7	precision	precision	NOUN
cana-2055	286	8	agriculture	agriculture	NOUN
cana-2055	286	9	based	base	VERB
cana-2055	286	10	on	on	ADP
cana-2055	286	11	internet	internet	NOUN
cana-2055	286	12	of	of	ADP
cana-2055	286	13	things	thing	NOUN
cana-2055	286	14	system	system	NOUN
cana-2055	286	15	.	.	PUNCT
cana-2055	286	16	"	"	PUNCT
cana-2055	287	1	sustainability	sustainability	NOUN
cana-2055	287	2	12.4	12.4	NUM
cana-2055	287	3	(	(	PUNCT
cana-2055	287	4	2020	2020	NUM
cana-2055	287	5	):	):	PUNCT
cana-2055	287	6	1433	1433	NUM
cana-2055	287	7	.	.	PUNCT
cana-2055	288	1	[	[	X
cana-2055	288	2	4	4	NUM
cana-2055	288	3	]	]	X
cana-2055	288	4	sharma	sharma	NOUN
cana-2055	288	5	,	,	PUNCT
cana-2055	288	6	abhinav	abhinav	PROPN
cana-2055	288	7	,	,	PUNCT
cana-2055	288	8	et	et	PROPN
cana-2055	288	9	al	al	PROPN
cana-2055	288	10	.	.	PUNCT
cana-2055	289	1	"	"	PUNCT
cana-2055	289	2	machine	machine	NOUN
cana-2055	289	3	learning	learning	NOUN
cana-2055	289	4	applications	application	NOUN
cana-2055	289	5	for	for	ADP
cana-2055	289	6	precision	precision	NOUN
cana-2055	289	7	agriculture	agriculture	NOUN
cana-2055	289	8	:	:	PUNCT
cana-2055	289	9	a	a	DET
cana-2055	289	10	comprehensive	comprehensive	ADJ
cana-2055	289	11	review	review	NOUN
cana-2055	289	12	.	.	PUNCT
cana-2055	289	13	"	"	PUNCT
cana-2055	290	1	ieee	ieee	NOUN
cana-2055	290	2	access	access	NOUN
cana-2055	290	3	9	9	NUM
cana-2055	290	4	(	(	PUNCT
cana-2055	290	5	2020	2020	NUM
cana-2055	290	6	):	):	PUNCT
cana-2055	290	7	4843	4843	NUM
cana-2055	290	8	-	-	SYM
cana-2055	290	9	4873	4873	NUM
cana-2055	290	10	.	.	PUNCT
cana-2055	291	1	[	[	X
cana-2055	291	2	5	5	NUM
cana-2055	291	3	]	]	X
cana-2055	291	4	vaidya	vaidya	PROPN
cana-2055	291	5	,	,	PUNCT
cana-2055	291	6	renu	renu	PROPN
cana-2055	291	7	,	,	PUNCT
cana-2055	291	8	dhananjay	dhananjay	PROPN
cana-2055	291	9	nalavade	nalavade	PROPN
cana-2055	291	10	,	,	PUNCT
cana-2055	291	11	and	and	CCONJ
cana-2055	291	12	k.	k.	PROPN
cana-2055	292	1	v.	v.	PROPN
cana-2055	292	2	kale	kale	PROPN
cana-2055	292	3	.	.	PUNCT
cana-2055	293	1	"	"	PUNCT
cana-2055	293	2	hyperspectral	hyperspectral	ADJ
cana-2055	293	3	imagery	imagery	NOUN
cana-2055	293	4	for	for	ADP
cana-2055	293	5	crop	crop	NOUN
cana-2055	293	6	yield	yield	NOUN
cana-2055	293	7	estimation	estimation	NOUN
cana-2055	293	8	in	in	ADP
cana-2055	293	9	precision	precision	NOUN
cana-2055	293	10	agriculture	agriculture	NOUN
cana-2055	293	11	using	use	VERB
cana-2055	293	12	machine	machine	NOUN
cana-2055	293	13	learning	learning	NOUN
cana-2055	293	14	approaches	approach	NOUN
cana-2055	293	15	:	:	PUNCT
cana-2055	293	16	a	a	DET
cana-2055	293	17	review	review	NOUN
cana-2055	293	18	.	.	PUNCT
cana-2055	293	19	"	"	PUNCT
cana-2055	294	1	int	int	NOUN
cana-2055	294	2	.	.	PUNCT
cana-2055	295	1	j.	j.	PROPN
cana-2055	295	2	creat	creat	PROPN
cana-2055	295	3	.	.	PUNCT
cana-2055	296	1	res	re	NOUN
cana-2055	296	2	.	.	PUNCT
cana-2055	296	3	thoughts	thought	NOUN
cana-2055	296	4	9	9	NUM
cana-2055	296	5	(	(	PUNCT
cana-2055	296	6	2022	2022	NUM
cana-2055	296	7	):	):	PUNCT
cana-2055	296	8	a777	a777	PROPN
cana-2055	296	9	-	-	PUNCT
cana-2055	296	10	a789	a789	PROPN
cana-2055	296	11	.	.	PUNCT
cana-2055	297	1	[	[	X
cana-2055	297	2	6	6	NUM
cana-2055	297	3	]	]	X
cana-2055	297	4	sharma	sharma	NOUN
cana-2055	297	5	,	,	PUNCT
cana-2055	297	6	abhinav	abhinav	PROPN
cana-2055	297	7	,	,	PUNCT
cana-2055	297	8	et	et	PROPN
cana-2055	297	9	al	al	PROPN
cana-2055	297	10	.	.	PUNCT
cana-2055	298	1	"	"	PUNCT
cana-2055	298	2	machine	machine	NOUN
cana-2055	298	3	learning	learning	NOUN
cana-2055	298	4	applications	application	NOUN
cana-2055	298	5	for	for	ADP
cana-2055	298	6	precision	precision	NOUN
cana-2055	298	7	agriculture	agriculture	NOUN
cana-2055	298	8	:	:	PUNCT
cana-2055	298	9	a	a	DET
cana-2055	298	10	comprehensive	comprehensive	ADJ
cana-2055	298	11	review	review	NOUN
cana-2055	298	12	.	.	PUNCT
cana-2055	298	13	"	"	PUNCT
cana-2055	299	1	ieee	ieee	NOUN
cana-2055	299	2	access	access	NOUN
cana-2055	299	3	9	9	NUM
cana-2055	299	4	(	(	PUNCT
cana-2055	299	5	2020	2020	NUM
cana-2055	299	6	):	):	PUNCT
cana-2055	299	7	4843	4843	NUM
cana-2055	299	8	-	-	SYM
cana-2055	299	9	4873	4873	NUM
cana-2055	299	10	.	.	PUNCT
cana-2055	300	1	[	[	X
cana-2055	300	2	7	7	NUM
cana-2055	300	3	]	]	PUNCT
cana-2055	300	4	bakthavatchalam	bakthavatchalam	ADJ
cana-2055	300	5	,	,	PUNCT
cana-2055	300	6	kalaiselvi	kalaiselvi	PROPN
cana-2055	300	7	,	,	PUNCT
cana-2055	300	8	et	et	PROPN
cana-2055	300	9	al	al	PROPN
cana-2055	300	10	.	.	PUNCT
cana-2055	301	1	"	"	PUNCT
cana-2055	301	2	iot	iot	ADJ
cana-2055	301	3	framework	framework	NOUN
cana-2055	301	4	for	for	ADP
cana-2055	301	5	measurement	measurement	NOUN
cana-2055	301	6	and	and	CCONJ
cana-2055	301	7	precision	precision	NOUN
cana-2055	301	8	agriculture	agriculture	NOUN
cana-2055	301	9	:	:	PUNCT
cana-2055	301	10	predicting	predict	VERB
cana-2055	301	11	the	the	DET
cana-2055	301	12	crop	crop	NOUN
cana-2055	301	13	using	use	VERB
cana-2055	301	14	machine	machine	NOUN
cana-2055	301	15	learning	learning	NOUN
cana-2055	301	16	algorithms	algorithm	NOUN
cana-2055	301	17	.	.	PUNCT
cana-2055	301	18	"	"	PUNCT
cana-2055	302	1	technologies	technology	NOUN
cana-2055	302	2	10.1	10.1	NUM
cana-2055	302	3	(	(	PUNCT
cana-2055	302	4	2022	2022	NUM
cana-2055	302	5	):	):	PUNCT
cana-2055	302	6	13	13	NUM
cana-2055	302	7	.	.	PUNCT
cana-2055	303	1	[	[	X
cana-2055	303	2	8	8	NUM
cana-2055	303	3	]	]	X
cana-2055	303	4	mekonnen	mekonnen	NOUN
cana-2055	303	5	,	,	PUNCT
cana-2055	303	6	yemeserach	yemeserach	NOUN
cana-2055	303	7	,	,	PUNCT
cana-2055	303	8	et	et	PROPN
cana-2055	303	9	al	al	PROPN
cana-2055	303	10	.	.	PUNCT
cana-2055	303	11	"	"	PUNCT
cana-2055	303	12	machine	machine	NOUN
cana-2055	303	13	learning	learn	VERB
cana-2055	303	14	techniques	technique	NOUN
cana-2055	303	15	in	in	ADP
cana-2055	303	16	wireless	wireless	ADJ
cana-2055	303	17	sensor	sensor	NOUN
cana-2055	303	18	network	network	NOUN
cana-2055	303	19	-	-	PUNCT
cana-2055	303	20	based	base	VERB
cana-2055	303	21	precision	precision	NOUN
cana-2055	303	22	agriculture	agriculture	NOUN
cana-2055	303	23	.	.	PUNCT
cana-2055	303	24	"	"	PUNCT
cana-2055	303	25	journal	journal	NOUN
cana-2055	303	26	of	of	ADP
cana-2055	303	27	the	the	DET
cana-2055	303	28	electrochemical	electrochemical	ADJ
cana-2055	303	29	society	society	NOUN
cana-2055	303	30	167.3	167.3	NUM
cana-2055	303	31	(	(	PUNCT
cana-2055	303	32	2019	2019	NUM
cana-2055	303	33	):	):	PUNCT
cana-2055	303	34	037522	037522	NUM
cana-2055	303	35	.	.	PUNCT
cana-2055	304	1	[	[	X
cana-2055	304	2	9	9	NUM
cana-2055	304	3	]	]	PUNCT
cana-2055	304	4	p.	p.	NOUN
cana-2055	304	5	patro	patro	PROPN
cana-2055	304	6	,	,	PUNCT
cana-2055	304	7	r.	r.	PROPN
cana-2055	304	8	azhagumurugan	azhagumurugan	PROPN
cana-2055	304	9	,	,	PUNCT
cana-2055	304	10	r.	r.	PROPN
cana-2055	304	11	sathya	sathya	PROPN
cana-2055	304	12	,	,	PUNCT
cana-2055	304	13	k.	k.	PROPN
cana-2055	304	14	kumar	kumar	PROPN
cana-2055	304	15	,	,	PUNCT
cana-2055	304	16	t.	t.	PROPN
cana-2055	304	17	r.	r.	PROPN
cana-2055	304	18	kumar	kumar	PROPN
cana-2055	304	19	and	and	CCONJ
cana-2055	304	20	m.	m.	PROPN
cana-2055	304	21	v.	v.	PROPN
cana-2055	304	22	s.	s.	PROPN
cana-2055	304	23	babu	babu	PROPN
cana-2055	304	24	,	,	PUNCT
cana-2055	304	25	"	"	PUNCT
cana-2055	304	26	a	a	DET
cana-2055	304	27	hybrid	hybrid	ADJ
cana-2055	304	28	approach	approach	NOUN
cana-2055	304	29	estimates	estimate	VERB
cana-2055	304	30	the	the	DET
cana-2055	304	31	real	real	ADJ
cana-2055	304	32	-	-	PUNCT
cana-2055	304	33	time	time	NOUN
cana-2055	304	34	health	health	NOUN
cana-2055	304	35	state	state	NOUN
cana-2055	304	36	of	of	ADP
cana-2055	304	37	a	a	DET
cana-2055	304	38	bearing	bearing	NOUN
cana-2055	304	39	by	by	ADP
cana-2055	304	40	accelerated	accelerate	VERB
cana-2055	304	41	degradation	degradation	NOUN
cana-2055	304	42	tests	test	NOUN
cana-2055	304	43	,	,	PUNCT
cana-2055	304	44	machine	machine	NOUN
cana-2055	304	45	learning	learning	NOUN
cana-2055	304	46	,	,	PUNCT
cana-2055	304	47	"	"	PUNCT
cana-2055	304	48	2021	2021	NUM
cana-2055	304	49	second	second	ADJ
cana-2055	304	50	international	international	ADJ
cana-2055	304	51	conference	conference	NOUN
cana-2055	304	52	on	on	ADP
cana-2055	304	53	smart	smart	ADJ
cana-2055	304	54	technologies	technology	NOUN
cana-2055	304	55	in	in	ADP
cana-2055	304	56	computing	computing	NOUN
cana-2055	304	57	,	,	PUNCT
cana-2055	304	58	electrical	electrical	ADJ
cana-2055	304	59	and	and	CCONJ
cana-2055	304	60	electronics	electronics	NOUN
cana-2055	304	61	(	(	PUNCT
cana-2055	304	62	icstcee	icstcee	NOUN
cana-2055	304	63	)	)	PUNCT
cana-2055	304	64	,	,	PUNCT
cana-2055	304	65	bengaluru	bengaluru	PROPN
cana-2055	304	66	,	,	PUNCT
cana-2055	304	67	india	india	PROPN
cana-2055	304	68	,	,	PUNCT
cana-2055	304	69	2021	2021	NUM
cana-2055	304	70	,	,	PUNCT
cana-2055	304	71	pp	pp	ADJ
cana-2055	304	72	.	.	PUNCT
cana-2055	305	1	1	1	NUM
cana-2055	305	2	-	-	SYM
cana-2055	305	3	9	9	NUM
cana-2055	305	4	,	,	PUNCT
cana-2055	305	5	doi	doi	NOUN
cana-2055	305	6	:	:	PUNCT
cana-2055	305	7	10.1109	10.1109	NUM
cana-2055	305	8	/	/	SYM
cana-2055	305	9	icstcee54422.2021.9708591	icstcee54422.2021.9708591	PROPN
cana-2055	305	10	communications	communication	NOUN
cana-2055	305	11	on	on	ADP
cana-2055	305	12	applied	apply	VERB
cana-2055	305	13	nonlinear	nonlinear	ADJ
cana-2055	305	14	analysis	analysis	NOUN
cana-2055	305	15	issn	issn	NOUN
cana-2055	305	16	:	:	PUNCT
cana-2055	305	17	1074	1074	NUM
cana-2055	305	18	-	-	PUNCT
cana-2055	305	19	133x	133x	NUM
cana-2055	305	20	vol	vol	NOUN
cana-2055	305	21	32	32	NUM
cana-2055	306	1	no	no	NOUN
cana-2055	306	2	.	.	NOUN
cana-2055	306	3	3	3	NUM
cana-2055	306	4	(	(	PUNCT
cana-2055	306	5	2025	2025	NUM
cana-2055	306	6	)	)	PUNCT
cana-2055	307	1	591	591	NUM
cana-2055	307	2	https://internationalpubls.com	https://internationalpubls.com	X
cana-2055	308	1	[	[	X
cana-2055	308	2	10	10	NUM
cana-2055	308	3	]	]	X
cana-2055	308	4	reddy	reddy	PROPN
cana-2055	308	5	,	,	PUNCT
cana-2055	308	6	d.	d.	PROPN
cana-2055	308	7	jayanarayana	jayanarayana	PROPN
cana-2055	308	8	,	,	PUNCT
cana-2055	308	9	and	and	CCONJ
cana-2055	308	10	m.	m.	NOUN
cana-2055	308	11	rudra	rudra	PROPN
cana-2055	308	12	kumar	kumar	PROPN
cana-2055	308	13	.	.	PUNCT
cana-2055	309	1	"	"	PUNCT
cana-2055	309	2	crop	crop	NOUN
cana-2055	309	3	yield	yield	NOUN
cana-2055	309	4	prediction	prediction	NOUN
cana-2055	309	5	using	use	VERB
cana-2055	309	6	machine	machine	NOUN
cana-2055	309	7	learning	learning	NOUN
cana-2055	309	8	algorithm	algorithm	NOUN
cana-2055	309	9	.	.	PUNCT
cana-2055	309	10	"	"	PUNCT
cana-2055	310	1	2021	2021	NUM
cana-2055	310	2	5th	5th	ADJ
cana-2055	310	3	international	international	ADJ
cana-2055	310	4	conference	conference	NOUN
cana-2055	310	5	on	on	ADP
cana-2055	310	6	intelligent	intelligent	ADJ
cana-2055	310	7	computing	computing	NOUN
cana-2055	310	8	and	and	CCONJ
cana-2055	310	9	control	control	NOUN
cana-2055	310	10	systems	system	NOUN
cana-2055	310	11	(	(	PUNCT
cana-2055	310	12	iciccs	iciccs	PROPN
cana-2055	310	13	)	)	PUNCT
cana-2055	310	14	.	.	PUNCT
cana-2055	311	1	ieee	ieee	NOUN
cana-2055	311	2	,	,	PUNCT
cana-2055	311	3	2021	2021	NUM
cana-2055	311	4	.	.	PUNCT
cana-2055	312	1	[	[	X
cana-2055	312	2	11	11	NUM
cana-2055	312	3	]	]	PUNCT
cana-2055	312	4	rama	rama	PROPN
cana-2055	312	5	devi	devi	PROPN
cana-2055	312	6	,	,	PUNCT
cana-2055	312	7	o.	o.	PROPN
cana-2055	312	8	,	,	PUNCT
cana-2055	312	9	et	et	PROPN
cana-2055	312	10	al	al	PROPN
cana-2055	312	11	.	.	PUNCT
cana-2055	313	1	"	"	PUNCT
cana-2055	313	2	optimizing	optimize	VERB
cana-2055	313	3	crop	crop	NOUN
cana-2055	313	4	yield	yield	NOUN
cana-2055	313	5	prediction	prediction	NOUN
cana-2055	313	6	in	in	ADP
cana-2055	313	7	precision	precision	NOUN
cana-2055	313	8	agriculture	agriculture	NOUN
cana-2055	313	9	with	with	ADP
cana-2055	313	10	hyperspectral	hyperspectral	ADJ
cana-2055	313	11	imaging	imaging	NOUN
cana-2055	313	12	-	-	PUNCT
cana-2055	313	13	unmixing	unmixe	VERB
cana-2055	313	14	and	and	CCONJ
cana-2055	313	15	deep	deep	ADJ
cana-2055	313	16	learning	learning	NOUN
cana-2055	313	17	.	.	PUNCT
cana-2055	313	18	"	"	PUNCT
cana-2055	314	1	international	international	ADJ
cana-2055	314	2	journal	journal	NOUN
cana-2055	314	3	of	of	ADP
cana-2055	314	4	advanced	advanced	ADJ
cana-2055	314	5	computer	computer	NOUN
cana-2055	314	6	science	science	NOUN
cana-2055	314	7	&	&	CCONJ
cana-2055	314	8	applications	application	NOUN
cana-2055	314	9	14.12	14.12	NUM
cana-2055	314	10	(	(	PUNCT
cana-2055	314	11	2023	2023	NUM
cana-2055	314	12	)	)	PUNCT
cana-2055	314	13	.	.	PUNCT
cana-2055	315	1	[	[	X
cana-2055	315	2	12	12	NUM
cana-2055	315	3	]	]	SYM
cana-2055	315	4	kuradusenge	kuradusenge	NOUN
cana-2055	315	5	,	,	PUNCT
cana-2055	315	6	martin	martin	PROPN
cana-2055	315	7	,	,	PUNCT
cana-2055	315	8	et	et	PROPN
cana-2055	315	9	al	al	PROPN
cana-2055	315	10	.	.	PUNCT
cana-2055	316	1	"	"	PUNCT
cana-2055	316	2	crop	crop	NOUN
cana-2055	316	3	yield	yield	NOUN
cana-2055	316	4	prediction	prediction	NOUN
cana-2055	316	5	using	use	VERB
cana-2055	316	6	machine	machine	NOUN
cana-2055	316	7	learning	learning	NOUN
cana-2055	316	8	models	model	NOUN
cana-2055	316	9	:	:	PUNCT
cana-2055	316	10	case	case	NOUN
cana-2055	316	11	of	of	ADP
cana-2055	316	12	irish	irish	ADJ
cana-2055	316	13	potato	potato	NOUN
cana-2055	316	14	and	and	CCONJ
cana-2055	316	15	maize	maize	NOUN
cana-2055	316	16	.	.	PUNCT
cana-2055	316	17	"	"	PUNCT
cana-2055	317	1	agriculture	agriculture	NOUN
cana-2055	317	2	13.1	13.1	NUM
cana-2055	317	3	(	(	PUNCT
cana-2055	317	4	2023	2023	NUM
cana-2055	317	5	):	):	PUNCT
cana-2055	317	6	225	225	NUM
cana-2055	317	7	.	.	PUNCT
cana-2055	318	1	[	[	X
cana-2055	318	2	13	13	NUM
cana-2055	318	3	]	]	SYM
cana-2055	318	4	shaikh	shaikh	PROPN
cana-2055	318	5	,	,	PUNCT
cana-2055	318	6	tawseef	tawseef	PROPN
cana-2055	318	7	ayoub	ayoub	PROPN
cana-2055	318	8	,	,	PUNCT
cana-2055	318	9	tabasum	tabasum	NOUN
cana-2055	318	10	rasool	rasool	NOUN
cana-2055	318	11	,	,	PUNCT
cana-2055	318	12	and	and	CCONJ
cana-2055	318	13	faisal	faisal	PROPN
cana-2055	318	14	rasheed	rasheed	PROPN
cana-2055	318	15	lone	lone	PROPN
cana-2055	318	16	.	.	PUNCT
cana-2055	319	1	"	"	PUNCT
cana-2055	319	2	towards	towards	ADP
cana-2055	319	3	leveraging	leverage	VERB
cana-2055	319	4	the	the	DET
cana-2055	319	5	role	role	NOUN
cana-2055	319	6	of	of	ADP
cana-2055	319	7	machine	machine	NOUN
cana-2055	319	8	learning	learning	NOUN
cana-2055	319	9	and	and	CCONJ
cana-2055	319	10	artificial	artificial	ADJ
cana-2055	319	11	intelligence	intelligence	NOUN
cana-2055	319	12	in	in	ADP
cana-2055	319	13	precision	precision	NOUN
cana-2055	319	14	agriculture	agriculture	NOUN
cana-2055	319	15	and	and	CCONJ
cana-2055	319	16	smart	smart	ADJ
cana-2055	319	17	farming	farming	NOUN
cana-2055	319	18	.	.	PUNCT
cana-2055	319	19	"	"	PUNCT
cana-2055	319	20	computers	computer	NOUN
cana-2055	319	21	and	and	CCONJ
cana-2055	319	22	electronics	electronic	NOUN
cana-2055	319	23	in	in	ADP
cana-2055	319	24	agriculture	agriculture	NOUN
cana-2055	319	25	198	198	NUM
cana-2055	319	26	(	(	PUNCT
cana-2055	319	27	2022	2022	NUM
cana-2055	319	28	):	):	PUNCT
cana-2055	319	29	107119	107119	NUM
cana-2055	319	30	.	.	PUNCT
cana-2055	320	1	[	[	X
cana-2055	320	2	14	14	NUM
cana-2055	320	3	]	]	X
cana-2055	320	4	shamim	shamim	PROPN
cana-2055	320	5	,	,	PUNCT
cana-2055	320	6	rejuwan	rejuwan	NOUN
cana-2055	320	7	,	,	PUNCT
cana-2055	320	8	and	and	CCONJ
cana-2055	320	9	trapty	trapty	ADJ
cana-2055	320	10	agarwal	agarwal	NOUN
cana-2055	320	11	.	.	PUNCT
cana-2055	321	1	"	"	PUNCT
cana-2055	321	2	optimizing	optimize	VERB
cana-2055	321	3	crop	crop	NOUN
cana-2055	321	4	yield	yield	NOUN
cana-2055	321	5	prediction	prediction	NOUN
cana-2055	321	6	using	use	VERB
cana-2055	321	7	machine	machine	NOUN
cana-2055	321	8	learning	learning	NOUN
cana-2055	321	9	algorithms	algorithm	NOUN
cana-2055	321	10	.	.	PUNCT
cana-2055	321	11	"	"	PUNCT
cana-2055	321	12	smart	smart	ADJ
cana-2055	321	13	agritech	agritech	NOUN
cana-2055	321	14	:	:	PUNCT
cana-2055	321	15	robotics	robotic	NOUN
cana-2055	321	16	,	,	PUNCT
cana-2055	321	17	ai	ai	VERB
cana-2055	321	18	,	,	PUNCT
cana-2055	321	19	and	and	CCONJ
cana-2055	321	20	internet	internet	NOUN
cana-2055	321	21	of	of	ADP
cana-2055	321	22	things	thing	NOUN
cana-2055	321	23	(	(	PUNCT
cana-2055	321	24	iot	iot	NOUN
cana-2055	321	25	)	)	PUNCT
cana-2055	321	26	in	in	ADP
cana-2055	321	27	agriculture	agriculture	NOUN
cana-2055	321	28	(	(	PUNCT
cana-2055	321	29	2024	2024	NUM
cana-2055	321	30	):	):	PUNCT
cana-2055	321	31	443	443	NUM
cana-2055	321	32	-	-	SYM
cana-2055	321	33	487	487	NUM
cana-2055	321	34	.	.	PUNCT
cana-2055	322	1	[	[	X
cana-2055	322	2	15	15	NUM
cana-2055	322	3	]	]	X
cana-2055	322	4	rao	rao	PROPN
cana-2055	322	5	,	,	PUNCT
cana-2055	322	6	m.	m.	NOUN
cana-2055	322	7	venkateswara	venkateswara	PROPN
cana-2055	322	8	,	,	PUNCT
cana-2055	322	9	et	et	PROPN
cana-2055	322	10	al	al	PROPN
cana-2055	322	11	.	.	PUNCT
cana-2055	322	12	"	"	PUNCT
cana-2055	322	13	brinjal	brinjal	ADJ
cana-2055	322	14	crop	crop	NOUN
cana-2055	322	15	yield	yield	NOUN
cana-2055	322	16	prediction	prediction	NOUN
cana-2055	322	17	using	use	VERB
cana-2055	322	18	shuffled	shuffle	VERB
cana-2055	322	19	shepherd	shepherd	ADJ
cana-2055	322	20	optimization	optimization	NOUN
cana-2055	322	21	algorithm	algorithm	PROPN
cana-2055	322	22	based	base	VERB
cana-2055	322	23	acnn	acnn	PROPN
cana-2055	322	24	-	-	PUNCT
cana-2055	322	25	obdlstm	obdlstm	PROPN
cana-2055	322	26	model	model	NOUN
cana-2055	322	27	in	in	ADP
cana-2055	322	28	smart	smart	ADJ
cana-2055	322	29	agriculture	agriculture	NOUN
cana-2055	322	30	.	.	PUNCT
cana-2055	322	31	"	"	PUNCT
cana-2055	323	1	journal	journal	NOUN
cana-2055	323	2	of	of	ADP
cana-2055	323	3	integrated	integrate	VERB
cana-2055	323	4	science	science	NOUN
cana-2055	323	5	and	and	CCONJ
cana-2055	323	6	technology	technology	NOUN
cana-2055	323	7	12.1	12.1	NUM
cana-2055	323	8	(	(	PUNCT
cana-2055	323	9	2024	2024	NUM
cana-2055	323	10	):	):	PUNCT
cana-2055	323	11	710	710	NUM
cana-2055	323	12	-	-	SYM
cana-2055	323	13	710	710	NUM
cana-2055	323	14	.	.	PUNCT
cana-2055	324	1	[	[	X
cana-2055	324	2	16	16	NUM
cana-2055	324	3	]	]	X
cana-2055	324	4	wei	wei	PROPN
cana-2055	324	5	,	,	PUNCT
cana-2055	324	6	marcelo	marcelo	PROPN
cana-2055	324	7	chan	chan	PROPN
cana-2055	324	8	fu	fu	PROPN
cana-2055	324	9	,	,	PUNCT
cana-2055	324	10	et	et	PROPN
cana-2055	324	11	al	al	PROPN
cana-2055	324	12	.	.	PUNCT
cana-2055	325	1	"	"	PUNCT
cana-2055	325	2	carrot	carrot	NOUN
cana-2055	325	3	yield	yield	NOUN
cana-2055	325	4	mapping	mapping	NOUN
cana-2055	325	5	:	:	PUNCT
cana-2055	325	6	a	a	DET
cana-2055	325	7	precision	precision	NOUN
cana-2055	325	8	agriculture	agriculture	NOUN
cana-2055	325	9	approach	approach	NOUN
cana-2055	325	10	based	base	VERB
cana-2055	325	11	on	on	ADP
cana-2055	325	12	machine	machine	NOUN
cana-2055	325	13	learning	learning	NOUN
cana-2055	325	14	.	.	PUNCT
cana-2055	325	15	"	"	PUNCT
cana-2055	325	16	ai	ai	VERB
cana-2055	325	17	1.2	1.2	NUM
cana-2055	325	18	(	(	PUNCT
cana-2055	325	19	2020	2020	NUM
cana-2055	325	20	):	):	PUNCT
cana-2055	325	21	229	229	NUM
cana-2055	325	22	-	-	SYM
cana-2055	325	23	241	241	NUM
cana-2055	325	24	.	.	PUNCT
cana-2055	326	1	[	[	X
cana-2055	326	2	17	17	NUM
cana-2055	326	3	]	]	PUNCT
cana-2055	326	4	anusha	anusha	PROPN
cana-2055	326	5	,	,	PUNCT
cana-2055	326	6	d.	d.	PROPN
cana-2055	326	7	j.	j.	PROPN
cana-2055	326	8	,	,	PUNCT
cana-2055	326	9	r.	r.	PROPN
cana-2055	326	10	anandan	anandan	PROPN
cana-2055	326	11	,	,	PUNCT
cana-2055	326	12	and	and	CCONJ
cana-2055	326	13	p.	p.	PROPN
cana-2055	326	14	venkata	venkata	PROPN
cana-2055	326	15	krishna	krishna	PROPN
cana-2055	326	16	.	.	PUNCT
cana-2055	327	1	"	"	PUNCT
cana-2055	327	2	original	original	ADJ
cana-2055	327	3	research	research	NOUN
cana-2055	327	4	article	article	NOUN
cana-2055	327	5	a	a	DET
cana-2055	327	6	novel	novel	ADJ
cana-2055	327	7	deep	deep	ADJ
cana-2055	327	8	learning	learning	NOUN
cana-2055	327	9	and	and	CCONJ
cana-2055	327	10	internet	internet	NOUN
cana-2055	327	11	of	of	ADP
cana-2055	327	12	things	thing	NOUN
cana-2055	327	13	(	(	PUNCT
cana-2055	327	14	iot	iot	NOUN
cana-2055	327	15	)	)	PUNCT
cana-2055	327	16	enabled	enable	VERB
cana-2055	327	17	precision	precision	NOUN
cana-2055	327	18	agricultural	agricultural	ADJ
cana-2055	327	19	framework	framework	NOUN
cana-2055	327	20	for	for	ADP
cana-2055	327	21	crop	crop	NOUN
cana-2055	327	22	yield	yield	NOUN
cana-2055	327	23	production	production	NOUN
cana-2055	327	24	.	.	PUNCT
cana-2055	327	25	"	"	PUNCT
cana-2055	328	1	journal	journal	NOUN
cana-2055	328	2	of	of	ADP
cana-2055	328	3	autonomous	autonomous	ADJ
cana-2055	328	4	intelligence	intelligence	NOUN
cana-2055	328	5	7.4	7.4	NUM
cana-2055	328	6	(	(	PUNCT
cana-2055	328	7	2024	2024	NUM
cana-2055	328	8	)	)	PUNCT
cana-2055	328	9	.	.	PUNCT
cana-2055	329	1	[	[	X
cana-2055	329	2	18	18	NUM
cana-2055	329	3	]	]	X
cana-2055	329	4	elavarasan	elavarasan	ADJ
cana-2055	329	5	,	,	PUNCT
cana-2055	329	6	dhivya	dhivya	NOUN
cana-2055	329	7	,	,	PUNCT
cana-2055	329	8	and	and	CCONJ
cana-2055	329	9	pm	pm	NOUN
cana-2055	329	10	durairaj	durairaj	VERB
cana-2055	329	11	vincent	vincent	NOUN
cana-2055	329	12	.	.	PUNCT
cana-2055	330	1	"	"	PUNCT
cana-2055	330	2	crop	crop	NOUN
cana-2055	330	3	yield	yield	NOUN
cana-2055	330	4	prediction	prediction	NOUN
cana-2055	330	5	using	use	VERB
cana-2055	330	6	deep	deep	ADJ
cana-2055	330	7	reinforcement	reinforcement	NOUN
cana-2055	330	8	learning	learning	NOUN
cana-2055	330	9	model	model	NOUN
cana-2055	330	10	for	for	ADP
cana-2055	330	11	sustainable	sustainable	ADJ
cana-2055	330	12	agrarian	agrarian	ADJ
cana-2055	330	13	applications	application	NOUN
cana-2055	330	14	.	.	PUNCT
cana-2055	330	15	"	"	PUNCT
cana-2055	331	1	ieee	ieee	NOUN
cana-2055	331	2	access	access	NOUN
cana-2055	331	3	8	8	NUM
cana-2055	331	4	(	(	PUNCT
cana-2055	331	5	2020	2020	NUM
cana-2055	331	6	):	):	PUNCT
cana-2055	331	7	86886	86886	NUM
cana-2055	331	8	-	-	SYM
cana-2055	331	9	86901	86901	NUM
cana-2055	331	10	.	.	PUNCT
cana-2055	332	1	[	[	X
cana-2055	332	2	19	19	NUM
cana-2055	332	3	]	]	X
cana-2055	332	4	kumar	kumar	PROPN
cana-2055	332	5	,	,	PUNCT
cana-2055	332	6	parasuraman	parasuraman	NOUN
cana-2055	332	7	,	,	PUNCT
cana-2055	332	8	et	et	PROPN
cana-2055	332	9	al	al	PROPN
cana-2055	332	10	.	.	PUNCT
cana-2055	333	1	"	"	PUNCT
cana-2055	333	2	multiparameter	multiparameter	NOUN
cana-2055	333	3	optimization	optimization	NOUN
cana-2055	333	4	system	system	NOUN
cana-2055	333	5	with	with	ADP
cana-2055	333	6	dcnn	dcnn	PROPN
cana-2055	333	7	in	in	ADP
cana-2055	333	8	precision	precision	NOUN
cana-2055	333	9	agriculture	agriculture	NOUN
cana-2055	333	10	for	for	ADP
cana-2055	333	11	advanced	advanced	ADJ
cana-2055	333	12	irrigation	irrigation	NOUN
cana-2055	333	13	planning	planning	NOUN
cana-2055	333	14	and	and	CCONJ
cana-2055	333	15	scheduling	scheduling	NOUN
cana-2055	333	16	based	base	VERB
cana-2055	333	17	on	on	ADP
cana-2055	333	18	soil	soil	NOUN
cana-2055	333	19	moisture	moisture	NOUN
cana-2055	333	20	estimation	estimation	NOUN
cana-2055	333	21	.	.	PUNCT
cana-2055	333	22	"	"	PUNCT
cana-2055	334	1	environmental	environmental	ADJ
cana-2055	334	2	monitoring	monitoring	NOUN
cana-2055	334	3	and	and	CCONJ
cana-2055	334	4	assessment	assessment	NOUN
cana-2055	334	5	195.1	195.1	NUM
cana-2055	334	6	(	(	PUNCT
cana-2055	334	7	2023	2023	NUM
cana-2055	334	8	):	):	PUNCT
cana-2055	334	9	13	13	NUM
cana-2055	334	10	[	[	SYM
cana-2055	334	11	20	20	NUM
cana-2055	334	12	]	]	PUNCT
cana-2055	334	13	sishodia	sishodia	NOUN
cana-2055	334	14	,	,	PUNCT
cana-2055	334	15	rajendra	rajendra	PROPN
cana-2055	334	16	p.	p.	PROPN
cana-2055	334	17	,	,	PUNCT
cana-2055	334	18	ram	ram	PROPN
cana-2055	334	19	l.	l.	PROPN
cana-2055	334	20	ray	ray	PROPN
cana-2055	334	21	,	,	PUNCT
cana-2055	334	22	and	and	CCONJ
cana-2055	334	23	sudhir	sudhir	PROPN
cana-2055	334	24	k.	k.	PROPN
cana-2055	334	25	singh	singh	PROPN
cana-2055	334	26	.	.	PUNCT
cana-2055	335	1	"	"	PUNCT
cana-2055	335	2	applications	application	NOUN
cana-2055	335	3	of	of	ADP
cana-2055	335	4	remote	remote	ADJ
cana-2055	335	5	sensing	sensing	NOUN
cana-2055	335	6	in	in	ADP
cana-2055	335	7	precision	precision	NOUN
cana-2055	335	8	agriculture	agriculture	NOUN
cana-2055	335	9	:	:	PUNCT
cana-2055	335	10	a	a	DET
cana-2055	335	11	review	review	NOUN
cana-2055	335	12	.	.	PUNCT
cana-2055	335	13	"	"	PUNCT
cana-2055	336	1	remote	remote	ADJ
cana-2055	336	2	sensing	sense	VERB
cana-2055	336	3	12.19	12.19	NUM
cana-2055	336	4	(	(	PUNCT
cana-2055	336	5	2020	2020	NUM
cana-2055	336	6	):	):	PUNCT
cana-2055	336	7	3136	3136	NUM
cana-2055	336	8	.	.	PUNCT
cana-2055	337	1	[	[	X
cana-2055	337	2	21	21	NUM
cana-2055	337	3	]	]	X
cana-2055	337	4	nevavuori	nevavuori	PROPN
cana-2055	337	5	,	,	PUNCT
cana-2055	337	6	petteri	petteri	PROPN
cana-2055	337	7	,	,	PUNCT
cana-2055	337	8	et	et	PROPN
cana-2055	337	9	al	al	PROPN
cana-2055	337	10	.	.	PUNCT
cana-2055	337	11	"	"	PUNCT
cana-2055	337	12	crop	crop	NOUN
cana-2055	337	13	yield	yield	NOUN
cana-2055	337	14	prediction	prediction	NOUN
cana-2055	337	15	using	use	VERB
cana-2055	337	16	multitemporal	multitemporal	PROPN
cana-2055	337	17	uav	uav	PROPN
cana-2055	337	18	data	data	PROPN
cana-2055	337	19	and	and	CCONJ
cana-2055	337	20	spatio	spatio	PROPN
cana-2055	337	21	-	-	PUNCT
cana-2055	337	22	temporal	temporal	ADJ
cana-2055	337	23	deep	deep	ADJ
cana-2055	337	24	learning	learning	NOUN
cana-2055	337	25	models	model	NOUN
cana-2055	337	26	.	.	PUNCT
cana-2055	337	27	"	"	PUNCT
cana-2055	338	1	remote	remote	ADJ
cana-2055	338	2	sensing	sense	VERB
cana-2055	338	3	12.23	12.23	NUM
cana-2055	338	4	(	(	PUNCT
cana-2055	338	5	2020	2020	NUM
cana-2055	338	6	):	):	PUNCT
cana-2055	338	7	4000	4000	NUM
cana-2055	338	8	.	.	PUNCT
cana-2055	339	1	[	[	X
cana-2055	339	2	22	22	NUM
cana-2055	339	3	]	]	X
cana-2055	339	4	akhter	akhter	NOUN
cana-2055	339	5	,	,	PUNCT
cana-2055	339	6	ravesa	ravesa	NOUN
cana-2055	339	7	,	,	PUNCT
cana-2055	339	8	and	and	CCONJ
cana-2055	339	9	shabir	shabir	PROPN
cana-2055	339	10	ahmad	ahmad	PROPN
cana-2055	339	11	sofi	sofi	PROPN
cana-2055	339	12	.	.	PUNCT
cana-2055	340	1	"	"	PUNCT
cana-2055	340	2	precision	precision	NOUN
cana-2055	340	3	agriculture	agriculture	NOUN
cana-2055	340	4	using	use	VERB
cana-2055	340	5	iot	iot	PROPN
cana-2055	340	6	data	datum	NOUN
cana-2055	340	7	analytics	analytic	NOUN
cana-2055	340	8	and	and	CCONJ
cana-2055	340	9	machine	machine	NOUN
cana-2055	340	10	learning	learning	NOUN
cana-2055	340	11	.	.	PUNCT
cana-2055	340	12	"	"	PUNCT
cana-2055	341	1	journal	journal	NOUN
cana-2055	341	2	of	of	ADP
cana-2055	341	3	king	king	PROPN
cana-2055	341	4	saud	saud	PROPN
cana-2055	341	5	university	university	PROPN
cana-2055	341	6	-	-	PUNCT
cana-2055	341	7	computer	computer	NOUN
cana-2055	341	8	and	and	CCONJ
cana-2055	341	9	information	information	NOUN
cana-2055	341	10	sciences	science	NOUN
cana-2055	341	11	34.8	34.8	NUM
cana-2055	341	12	(	(	PUNCT
cana-2055	341	13	2022	2022	NUM
cana-2055	341	14	):	):	PUNCT
cana-2055	341	15	5602	5602	NUM
cana-2055	341	16	-	-	SYM
cana-2055	341	17	5618	5618	NUM
cana-2055	341	18	.	.	PUNCT
cana-2055	342	1	[	[	X
cana-2055	342	2	23	23	NUM
cana-2055	342	3	]	]	X
cana-2055	342	4	darwin	darwin	PROPN
cana-2055	342	5	,	,	PUNCT
cana-2055	342	6	bini	bini	PROPN
cana-2055	342	7	,	,	PUNCT
cana-2055	342	8	et	et	PROPN
cana-2055	342	9	al	al	PROPN
cana-2055	342	10	.	.	PUNCT
cana-2055	343	1	"	"	PUNCT
cana-2055	343	2	recognition	recognition	NOUN
cana-2055	343	3	of	of	ADP
cana-2055	343	4	bloom	bloom	NOUN
cana-2055	343	5	/	/	SYM
cana-2055	343	6	yield	yield	NOUN
cana-2055	343	7	in	in	ADP
cana-2055	343	8	crop	crop	NOUN
cana-2055	343	9	images	image	NOUN
cana-2055	343	10	using	use	VERB
cana-2055	343	11	deep	deep	ADJ
cana-2055	343	12	learning	learning	NOUN
cana-2055	343	13	models	model	NOUN
cana-2055	343	14	for	for	ADP
cana-2055	343	15	smart	smart	ADJ
cana-2055	343	16	agriculture	agriculture	NOUN
cana-2055	343	17	:	:	PUNCT
cana-2055	343	18	a	a	DET
cana-2055	343	19	review	review	NOUN
cana-2055	343	20	.	.	PUNCT
cana-2055	343	21	"	"	PUNCT
cana-2055	344	1	agronomy	agronomy	NOUN
cana-2055	344	2	11.4	11.4	NUM
cana-2055	344	3	(	(	PUNCT
cana-2055	344	4	2021	2021	NUM
cana-2055	344	5	):	):	PUNCT
cana-2055	344	6	646	646	NUM
cana-2055	344	7	.	.	PUNCT
cana-2055	345	1	[	[	X
cana-2055	345	2	24	24	NUM
cana-2055	345	3	]	]	PUNCT
cana-2055	345	4	gómez	gómez	NOUN
cana-2055	345	5	,	,	PUNCT
cana-2055	345	6	diego	diego	PROPN
cana-2055	345	7	,	,	PUNCT
cana-2055	345	8	et	et	PROPN
cana-2055	345	9	al	al	PROPN
cana-2055	345	10	.	.	PUNCT
cana-2055	345	11	"	"	PUNCT
cana-2055	345	12	potato	potato	NOUN
cana-2055	345	13	yield	yield	NOUN
cana-2055	345	14	prediction	prediction	NOUN
cana-2055	345	15	using	use	VERB
cana-2055	345	16	machine	machine	NOUN
cana-2055	345	17	learning	learn	VERB
cana-2055	345	18	techniques	technique	NOUN
cana-2055	345	19	and	and	CCONJ
cana-2055	345	20	sentinel	sentinel	ADJ
cana-2055	345	21	2	2	NUM
cana-2055	345	22	data	datum	NOUN
cana-2055	345	23	.	.	PUNCT
cana-2055	345	24	"	"	PUNCT
cana-2055	346	1	remote	remote	ADJ
cana-2055	346	2	sensing	sense	VERB
cana-2055	346	3	11.15	11.15	NUM
cana-2055	346	4	(	(	PUNCT
cana-2055	346	5	2019	2019	NUM
cana-2055	346	6	):	):	PUNCT
cana-2055	346	7	1745	1745	NUM
cana-2055	346	8	.	.	PUNCT
cana-2055	347	1	[	[	X
cana-2055	347	2	25	25	NUM
cana-2055	347	3	]	]	X
cana-2055	347	4	singh	singh	PROPN
cana-2055	347	5	,	,	PUNCT
cana-2055	347	6	chaitanya	chaitanya	PROPN
cana-2055	347	7	,	,	PUNCT
cana-2055	347	8	et	et	PROPN
cana-2055	347	9	al	al	PROPN
cana-2055	347	10	.	.	PUNCT
cana-2055	348	1	"	"	PUNCT
cana-2055	348	2	applied	apply	VERB
cana-2055	348	3	machine	machine	NOUN
cana-2055	348	4	tool	tool	NOUN
cana-2055	348	5	data	datum	NOUN
cana-2055	348	6	condition	condition	NOUN
cana-2055	348	7	to	to	ADP
cana-2055	348	8	predictive	predictive	VERB
cana-2055	348	9	smart	smart	ADJ
cana-2055	348	10	maintenance	maintenance	NOUN
cana-2055	348	11	by	by	ADP
cana-2055	348	12	using	use	VERB
cana-2055	348	13	artificial	artificial	ADJ
cana-2055	348	14	intelligence	intelligence	NOUN
cana-2055	348	15	.	.	PUNCT
cana-2055	348	16	"	"	PUNCT
cana-2055	349	1	international	international	ADJ
cana-2055	349	2	conference	conference	NOUN
cana-2055	349	3	on	on	ADP
cana-2055	349	4	emerging	emerge	VERB
cana-2055	349	5	technologies	technology	NOUN
cana-2055	349	6	in	in	ADP
cana-2055	349	7	computer	computer	NOUN
cana-2055	349	8	engineering	engineering	NOUN
cana-2055	349	9	.	.	PUNCT
cana-2055	350	1	cham	cham	PROPN
cana-2055	350	2	:	:	PUNCT
cana-2055	350	3	springer	springer	NOUN
cana-2055	350	4	international	international	ADJ
cana-2055	350	5	publishing	publishing	NOUN
cana-2055	350	6	,	,	PUNCT
cana-2055	350	7	2022	2022	NUM