id	sid	tid	token	lemma	pos
cana-1160	1	1	communications	communication	NOUN
cana-1160	1	2	on	on	ADP
cana-1160	1	3	applied	apply	VERB
cana-1160	1	4	nonlinear	nonlinear	ADJ
cana-1160	1	5	analysis	analysis	NOUN
cana-1160	1	6	issn	issn	NOUN
cana-1160	1	7	:	:	PUNCT
cana-1160	1	8	1074	1074	NUM
cana-1160	1	9	-	-	PUNCT
cana-1160	1	10	133x	133x	NUM
cana-1160	1	11	vol	vol	NOUN
cana-1160	1	12	31	31	NUM
cana-1160	1	13	no	no	NOUN
cana-1160	1	14	.	.	PUNCT
cana-1160	2	1	6s	6s	NUM
cana-1160	2	2	(	(	PUNCT
cana-1160	2	3	2024	2024	NUM
cana-1160	2	4	)	)	PUNCT
cana-1160	2	5	74	74	NUM
cana-1160	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1160	2	7	innovative	innovative	ADJ
cana-1160	2	8	energy	energy	NOUN
cana-1160	2	9	prediction	prediction	NOUN
cana-1160	2	10	using	use	VERB
cana-1160	2	11	kolmogorov	kolmogorov	PROPN
cana-1160	2	12	-	-	PUNCT
cana-1160	2	13	arnold	arnold	PROPN
cana-1160	2	14	networks	network	NOUN
cana-1160	2	15	(	(	PUNCT
cana-1160	2	16	kan	kan	X
cana-1160	2	17	)	)	PUNCT
cana-1160	2	18	and	and	CCONJ
cana-1160	2	19	liquid	liquid	ADJ
cana-1160	2	20	neural	neural	ADJ
cana-1160	2	21	networks	network	NOUN
cana-1160	2	22	(	(	PUNCT
cana-1160	2	23	lnn	lnn	PROPN
cana-1160	2	24	)	)	PUNCT
cana-1160	2	25	for	for	ADP
cana-1160	2	26	smart	smart	ADJ
cana-1160	2	27	grids	grid	NOUN
cana-1160	2	28	dr	dr	PROPN
cana-1160	2	29	.	.	PROPN
cana-1160	2	30	harish	harish	PROPN
cana-1160	2	31	morwani1	morwani1	PROPN
cana-1160	2	32	,	,	PUNCT
cana-1160	2	33	dr	dr	PROPN
cana-1160	2	34	.	.	PROPN
cana-1160	2	35	jaimin	jaimin	PROPN
cana-1160	2	36	jani2	jani2	PROPN
cana-1160	2	37	,	,	PUNCT
cana-1160	2	38	dr	dr	PROPN
cana-1160	2	39	.	.	PROPN
cana-1160	2	40	parimalkumar	parimalkumar	PROPN
cana-1160	2	41	patel3	patel3	PROPN
cana-1160	2	42	,	,	PUNCT
cana-1160	2	43	prof	prof	PROPN
cana-1160	2	44	.	.	PROPN
cana-1160	3	1	hitendra	hitendra	PROPN
cana-1160	3	2	b.	b.	PROPN
cana-1160	3	3	vaghela4	vaghela4	PROPN
cana-1160	3	4	,	,	PUNCT
cana-1160	3	5	prof	prof	PROPN
cana-1160	3	6	.	.	PUNCT
cana-1160	4	1	swapna	swapna	PROPN
cana-1160	4	2	pawar5	pawar5	PROPN
cana-1160	4	3	,	,	PUNCT
cana-1160	4	4	prof	prof	PROPN
cana-1160	4	5	.	.	PUNCT
cana-1160	4	6	kamakshi	kamakshi	PROPN
cana-1160	5	1	v.	v.	PROPN
cana-1160	5	2	kaul6	kaul6	PROPN
cana-1160	5	3	1associate	1associate	NUM
cana-1160	5	4	professor	professor	NOUN
cana-1160	5	5	,	,	PUNCT
cana-1160	5	6	department	department	NOUN
cana-1160	5	7	of	of	ADP
cana-1160	5	8	computer	computer	NOUN
cana-1160	5	9	sciences	sciences	PROPN
cana-1160	5	10	and	and	CCONJ
cana-1160	5	11	engineering	engineering	NOUN
cana-1160	5	12	,	,	PUNCT
cana-1160	5	13	iar	iar	PROPN
cana-1160	5	14	university	university	PROPN
cana-1160	5	15	,	,	PUNCT
cana-1160	5	16	gandhinagar	gandhinagar	NOUN
cana-1160	5	17	,	,	PUNCT
cana-1160	5	18	harish.morwani@iar.ac.in	harish.morwani@iar.ac.in	PROPN
cana-1160	5	19	2assistant	2assistant	PROPN
cana-1160	5	20	professor	professor	NOUN
cana-1160	5	21	,	,	PUNCT
cana-1160	5	22	computer	computer	NOUN
cana-1160	5	23	engineering	engineering	NOUN
cana-1160	5	24	department	department	PROPN
cana-1160	5	25	,	,	PUNCT
cana-1160	5	26	ahmedabad	ahmedabad	PROPN
cana-1160	5	27	institute	institute	PROPN
cana-1160	5	28	of	of	ADP
cana-1160	5	29	technology	technology	PROPN
cana-1160	5	30	,	,	PUNCT
cana-1160	5	31	ahmedabad	ahmedabad	PROPN
cana-1160	5	32	,	,	PUNCT
cana-1160	5	33	drjaiminhjani@gmail.com	drjaiminhjani@gmail.com	X
cana-1160	5	34	3i	3i	NUM
cana-1160	5	35	/	/	SYM
cana-1160	5	36	c	c	NOUN
cana-1160	5	37	principal	principal	NOUN
cana-1160	5	38	,	,	PUNCT
cana-1160	5	39	khyati	khyati	PROPN
cana-1160	5	40	school	school	NOUN
cana-1160	5	41	of	of	ADP
cana-1160	5	42	computer	computer	NOUN
cana-1160	5	43	application	application	NOUN
cana-1160	5	44	,	,	PUNCT
cana-1160	5	45	ahmedabad	ahmedabad	PROPN
cana-1160	5	46	,	,	PUNCT
cana-1160	5	47	patelparimalp@yahoo.com	patelparimalp@yahoo.com	PROPN
cana-1160	6	1	4assistant	4assistant	NUM
cana-1160	6	2	professor	professor	NOUN
cana-1160	6	3	,	,	PUNCT
cana-1160	6	4	electrical	electrical	ADJ
cana-1160	6	5	engineering	engineering	NOUN
cana-1160	6	6	department	department	NOUN
cana-1160	6	7	,	,	PUNCT
cana-1160	6	8	vishwakarma	vishwakarma	VERB
cana-1160	6	9	government	government	NOUN
cana-1160	6	10	engineering	engineering	PROPN
cana-1160	6	11	college	college	PROPN
cana-1160	6	12	,	,	PUNCT
cana-1160	6	13	ahmedabad	ahmedabad	PROPN
cana-1160	6	14	,	,	PUNCT
cana-1160	6	15	hbvaghela@vgecg.ac.in	hbvaghela@vgecg.ac.in	PROPN
cana-1160	6	16	5assistant	5assistant	NUM
cana-1160	6	17	professor	professor	NOUN
cana-1160	6	18	,	,	PUNCT
cana-1160	6	19	mechanical	mechanical	ADJ
cana-1160	6	20	engineering	engineering	NOUN
cana-1160	6	21	department	department	PROPN
cana-1160	6	22	,	,	PUNCT
cana-1160	6	23	vishwakarma	vishwakarma	VERB
cana-1160	6	24	government	government	NOUN
cana-1160	6	25	engineering	engineering	PROPN
cana-1160	6	26	college	college	PROPN
cana-1160	6	27	,	,	PUNCT
cana-1160	6	28	ahmedabad	ahmedabad	PROPN
cana-1160	6	29	,	,	PUNCT
cana-1160	6	30	sapawar@vgecg.ac.in	sapawar@vgecg.ac.in	ADV
cana-1160	6	31	6assistant	6assistant	NUM
cana-1160	6	32	professor	professor	NOUN
cana-1160	6	33	,	,	PUNCT
cana-1160	6	34	instrumentation	instrumentation	NOUN
cana-1160	6	35	and	and	CCONJ
cana-1160	6	36	control	control	NOUN
cana-1160	6	37	engineering	engineering	PROPN
cana-1160	6	38	department	department	PROPN
cana-1160	6	39	,	,	PUNCT
cana-1160	6	40	vishwakarma	vishwakarma	VERB
cana-1160	6	41	government	government	NOUN
cana-1160	6	42	engineering	engineering	PROPN
cana-1160	6	43	college	college	PROPN
cana-1160	6	44	,	,	PUNCT
cana-1160	6	45	ahmedabad	ahmedabad	PROPN
cana-1160	6	46	,	,	PUNCT
cana-1160	6	47	kamakshikaul@vgecg.ac.in	kamakshikaul@vgecg.ac.in	PROPN
cana-1160	6	48	article	article	NOUN
cana-1160	6	49	history	history	NOUN
cana-1160	6	50	:	:	PUNCT
cana-1160	6	51	received	receive	VERB
cana-1160	6	52	:	:	PUNCT
cana-1160	6	53	24	24	NUM
cana-1160	6	54	-	-	PUNCT
cana-1160	6	55	05	05	NUM
cana-1160	6	56	-	-	PUNCT
cana-1160	6	57	2024	2024	NUM
cana-1160	6	58	revised	revise	VERB
cana-1160	6	59	:	:	PUNCT
cana-1160	6	60	29	29	NUM
cana-1160	6	61	-	-	SYM
cana-1160	6	62	06	06	NUM
cana-1160	6	63	-	-	PUNCT
cana-1160	6	64	2024	2024	NUM
cana-1160	6	65	accepted	accept	VERB
cana-1160	6	66	:	:	PUNCT
cana-1160	6	67	20	20	NUM
cana-1160	6	68	-	-	SYM
cana-1160	6	69	07	07	NUM
cana-1160	6	70	-	-	PUNCT
cana-1160	6	71	2024	2024	NUM
cana-1160	6	72	abstract	abstract	NOUN
cana-1160	6	73	:	:	PUNCT
cana-1160	6	74	the	the	DET
cana-1160	6	75	efficient	efficient	ADJ
cana-1160	6	76	operation	operation	NOUN
cana-1160	6	77	and	and	CCONJ
cana-1160	6	78	management	management	NOUN
cana-1160	6	79	of	of	ADP
cana-1160	6	80	smart	smart	ADJ
cana-1160	6	81	grids	grid	NOUN
cana-1160	6	82	rely	rely	VERB
cana-1160	6	83	heavily	heavily	ADV
cana-1160	6	84	on	on	ADP
cana-1160	6	85	accurate	accurate	ADJ
cana-1160	6	86	energy	energy	NOUN
cana-1160	6	87	consumption	consumption	NOUN
cana-1160	6	88	prediction	prediction	NOUN
cana-1160	6	89	.	.	PUNCT
cana-1160	7	1	in	in	ADP
cana-1160	7	2	this	this	DET
cana-1160	7	3	paper	paper	NOUN
cana-1160	7	4	,	,	PUNCT
cana-1160	7	5	we	we	PRON
cana-1160	7	6	propose	propose	VERB
cana-1160	7	7	a	a	DET
cana-1160	7	8	novel	novel	ADJ
cana-1160	7	9	approach	approach	NOUN
cana-1160	7	10	for	for	ADP
cana-1160	7	11	predicting	predict	VERB
cana-1160	7	12	energy	energy	NOUN
cana-1160	7	13	consumption	consumption	NOUN
cana-1160	7	14	in	in	ADP
cana-1160	7	15	smart	smart	ADJ
cana-1160	7	16	grids	grid	NOUN
cana-1160	7	17	that	that	PRON
cana-1160	7	18	combines	combine	VERB
cana-1160	7	19	the	the	DET
cana-1160	7	20	strengths	strength	NOUN
cana-1160	7	21	of	of	ADP
cana-1160	7	22	kolmogorov	kolmogorov	PROPN
cana-1160	7	23	-	-	PUNCT
cana-1160	7	24	arnold	arnold	PROPN
cana-1160	7	25	networks	network	NOUN
cana-1160	7	26	(	(	PUNCT
cana-1160	7	27	kans	kans	PROPN
cana-1160	7	28	)	)	PUNCT
cana-1160	7	29	and	and	CCONJ
cana-1160	7	30	liquid	liquid	ADJ
cana-1160	7	31	neural	neural	ADJ
cana-1160	7	32	networks	network	NOUN
cana-1160	7	33	(	(	PUNCT
cana-1160	7	34	lnns	lnns	ADJ
cana-1160	7	35	)	)	PUNCT
cana-1160	7	36	.	.	PUNCT
cana-1160	8	1	to	to	PART
cana-1160	8	2	deal	deal	VERB
cana-1160	8	3	with	with	ADP
cana-1160	8	4	complex	complex	ADJ
cana-1160	8	5	,	,	PUNCT
cana-1160	8	6	time	time	NOUN
cana-1160	8	7	-	-	PUNCT
cana-1160	8	8	varying	vary	VERB
cana-1160	8	9	energy	energy	NOUN
cana-1160	8	10	consumption	consumption	NOUN
cana-1160	8	11	patterns	pattern	NOUN
cana-1160	8	12	,	,	PUNCT
cana-1160	8	13	our	our	PRON
cana-1160	8	14	hybrid	hybrid	NOUN
cana-1160	8	15	model	model	NOUN
cana-1160	8	16	combines	combine	VERB
cana-1160	8	17	kans	kan	NOUN
cana-1160	8	18	'	'	PART
cana-1160	8	19	robust	robust	ADJ
cana-1160	8	20	function	function	NOUN
cana-1160	8	21	approximation	approximation	NOUN
cana-1160	8	22	capabilities	capability	NOUN
cana-1160	8	23	with	with	ADP
cana-1160	8	24	lnns	lnns	ADJ
cana-1160	8	25	'	'	PART
cana-1160	8	26	dynamic	dynamic	ADJ
cana-1160	8	27	adaptively	adaptively	ADV
cana-1160	8	28	.	.	PUNCT
cana-1160	9	1	kans	kans	PROPN
cana-1160	9	2	provide	provide	VERB
cana-1160	9	3	a	a	DET
cana-1160	9	4	solid	solid	ADJ
cana-1160	9	5	framework	framework	NOUN
cana-1160	9	6	for	for	ADP
cana-1160	9	7	modelling	model	VERB
cana-1160	9	8	complex	complex	ADJ
cana-1160	9	9	,	,	PUNCT
cana-1160	9	10	high	high	ADJ
cana-1160	9	11	-	-	PUNCT
cana-1160	9	12	dimensional	dimensional	ADJ
cana-1160	9	13	systems	system	NOUN
cana-1160	9	14	by	by	ADP
cana-1160	9	15	combining	combine	VERB
cana-1160	9	16	multivariate	multivariate	NOUN
cana-1160	9	17	functions	function	NOUN
cana-1160	9	18	into	into	ADP
cana-1160	9	19	univariate	univariate	ADJ
cana-1160	9	20	functions	function	NOUN
cana-1160	9	21	.	.	PUNCT
cana-1160	10	1	in	in	ADP
cana-1160	10	2	addition	addition	NOUN
cana-1160	10	3	,	,	PUNCT
cana-1160	10	4	lnns	lnn	NOUN
cana-1160	10	5	provide	provide	VERB
cana-1160	10	6	dynamic	dynamic	ADJ
cana-1160	10	7	adaptability	adaptability	NOUN
cana-1160	10	8	through	through	ADP
cana-1160	10	9	their	their	PRON
cana-1160	10	10	continuous	continuous	ADJ
cana-1160	10	11	and	and	CCONJ
cana-1160	10	12	differentiable	differentiable	ADJ
cana-1160	10	13	activation	activation	NOUN
cana-1160	10	14	functions	function	NOUN
cana-1160	10	15	,	,	PUNCT
cana-1160	10	16	which	which	PRON
cana-1160	10	17	mimic	mimic	VERB
cana-1160	10	18	the	the	DET
cana-1160	10	19	fluidity	fluidity	NOUN
cana-1160	10	20	of	of	ADP
cana-1160	10	21	liquids	liquid	NOUN
cana-1160	10	22	,	,	PUNCT
cana-1160	10	23	making	make	VERB
cana-1160	10	24	them	they	PRON
cana-1160	10	25	particularly	particularly	ADV
cana-1160	10	26	adept	adept	ADJ
cana-1160	10	27	at	at	ADP
cana-1160	10	28	dealing	deal	VERB
cana-1160	10	29	with	with	ADP
cana-1160	10	30	time	time	NOUN
cana-1160	10	31	-	-	PUNCT
cana-1160	10	32	dependent	dependent	ADJ
cana-1160	10	33	data	datum	NOUN
cana-1160	10	34	and	and	CCONJ
cana-1160	10	35	changing	change	VERB
cana-1160	10	36	patterns	pattern	NOUN
cana-1160	10	37	.	.	PUNCT
cana-1160	11	1	our	our	PRON
cana-1160	11	2	methodology	methodology	NOUN
cana-1160	11	3	combines	combine	VERB
cana-1160	11	4	the	the	DET
cana-1160	11	5	strengths	strength	NOUN
cana-1160	11	6	of	of	ADP
cana-1160	11	7	kans	kan	NOUN
cana-1160	11	8	and	and	CCONJ
cana-1160	11	9	lnns	lnns	ADJ
cana-1160	11	10	to	to	PART
cana-1160	11	11	create	create	VERB
cana-1160	11	12	a	a	DET
cana-1160	11	13	hybrid	hybrid	ADJ
cana-1160	11	14	model	model	NOUN
cana-1160	11	15	that	that	PRON
cana-1160	11	16	can	can	AUX
cana-1160	11	17	capture	capture	VERB
cana-1160	11	18	complex	complex	ADJ
cana-1160	11	19	dependencies	dependency	NOUN
cana-1160	11	20	and	and	CCONJ
cana-1160	11	21	temporal	temporal	ADJ
cana-1160	11	22	variations	variation	NOUN
cana-1160	11	23	in	in	ADP
cana-1160	11	24	energy	energy	NOUN
cana-1160	11	25	usage	usage	NOUN
cana-1160	11	26	data	datum	NOUN
cana-1160	11	27	.	.	PUNCT
cana-1160	12	1	keywords	keyword	NOUN
cana-1160	12	2	:	:	PUNCT
cana-1160	12	3	kolmogorov	kolmogorov	PROPN
cana-1160	12	4	-	-	PUNCT
cana-1160	12	5	arnold	arnold	PROPN
cana-1160	12	6	networks	network	NOUN
cana-1160	12	7	(	(	PUNCT
cana-1160	12	8	kans	kans	PROPN
cana-1160	12	9	)	)	PUNCT
cana-1160	12	10	,	,	PUNCT
cana-1160	12	11	liquid	liquid	ADJ
cana-1160	12	12	neural	neural	ADJ
cana-1160	12	13	networks	network	NOUN
cana-1160	12	14	(	(	PUNCT
cana-1160	12	15	lnn	lnn	PROPN
cana-1160	12	16	)	)	PUNCT
cana-1160	12	17	,	,	PUNCT
cana-1160	12	18	smart	smart	ADJ
cana-1160	12	19	grids	grid	NOUN
cana-1160	12	20	,	,	PUNCT
cana-1160	12	21	energy	energy	NOUN
cana-1160	12	22	consumption	consumption	NOUN
cana-1160	12	23	.	.	PUNCT
cana-1160	13	1	1	1	X
cana-1160	13	2	.	.	X
cana-1160	13	3	introduction	introduction	NOUN
cana-1160	13	4	this	this	DET
cana-1160	13	5	study	study	NOUN
cana-1160	13	6	aims	aim	VERB
cana-1160	13	7	to	to	PART
cana-1160	13	8	improve	improve	VERB
cana-1160	13	9	forecast	forecast	NOUN
cana-1160	13	10	accuracy	accuracy	NOUN
cana-1160	13	11	,	,	PUNCT
cana-1160	13	12	responsiveness	responsiveness	NOUN
cana-1160	13	13	to	to	ADP
cana-1160	13	14	real	real	ADJ
cana-1160	13	15	-	-	PUNCT
cana-1160	13	16	time	time	NOUN
cana-1160	13	17	data	datum	NOUN
cana-1160	13	18	changes	change	NOUN
cana-1160	13	19	,	,	PUNCT
cana-1160	13	20	and	and	CCONJ
cana-1160	13	21	overall	overall	ADJ
cana-1160	13	22	efficiency	efficiency	NOUN
cana-1160	13	23	in	in	ADP
cana-1160	13	24	smart	smart	ADJ
cana-1160	13	25	grid	grid	NOUN
cana-1160	13	26	management	management	NOUN
cana-1160	13	27	,	,	PUNCT
cana-1160	13	28	addressing	address	VERB
cana-1160	13	29	the	the	DET
cana-1160	13	30	limitations	limitation	NOUN
cana-1160	13	31	of	of	ADP
cana-1160	13	32	existing	exist	VERB
cana-1160	13	33	predictive	predictive	ADJ
cana-1160	13	34	models	model	NOUN
cana-1160	13	35	and	and	CCONJ
cana-1160	13	36	contributing	contribute	VERB
cana-1160	13	37	to	to	ADP
cana-1160	13	38	more	more	ADV
cana-1160	13	39	sustainable	sustainable	ADJ
cana-1160	13	40	and	and	CCONJ
cana-1160	13	41	reliable	reliable	ADJ
cana-1160	13	42	energy	energy	NOUN
cana-1160	13	43	systems	system	NOUN
cana-1160	13	44	.	.	PUNCT
cana-1160	14	1	the	the	DET
cana-1160	14	2	proposed	propose	VERB
cana-1160	14	3	approach	approach	NOUN
cana-1160	14	4	advances	advance	VERB
cana-1160	14	5	the	the	DET
cana-1160	14	6	state	state	NOUN
cana-1160	14	7	-	-	PUNCT
cana-1160	14	8	of	of	ADP
cana-1160	14	9	-	-	PUNCT
cana-1160	14	10	the	the	DET
cana-1160	14	11	-	-	PUNCT
cana-1160	14	12	art	art	NOUN
cana-1160	14	13	in	in	ADP
cana-1160	14	14	energy	energy	NOUN
cana-1160	14	15	prediction	prediction	NOUN
cana-1160	14	16	for	for	ADP
cana-1160	14	17	smart	smart	ADJ
cana-1160	14	18	grids	grid	NOUN
cana-1160	14	19	by	by	ADP
cana-1160	14	20	integrating	integrate	VERB
cana-1160	14	21	kans	kan	NOUN
cana-1160	14	22	and	and	CCONJ
cana-1160	14	23	lnns	lnn	NOUN
cana-1160	14	24	,	,	PUNCT
cana-1160	14	25	as	as	ADV
cana-1160	14	26	well	well	ADV
cana-1160	14	27	as	as	ADP
cana-1160	14	28	providing	provide	VERB
cana-1160	14	29	a	a	DET
cana-1160	14	30	scalable	scalable	ADJ
cana-1160	14	31	solution	solution	NOUN
cana-1160	14	32	that	that	PRON
cana-1160	14	33	can	can	AUX
cana-1160	14	34	be	be	AUX
cana-1160	14	35	applied	apply	VERB
cana-1160	14	36	to	to	ADP
cana-1160	14	37	a	a	DET
cana-1160	14	38	variety	variety	NOUN
cana-1160	14	39	of	of	ADP
cana-1160	14	40	real	real	ADJ
cana-1160	14	41	-	-	PUNCT
cana-1160	14	42	time	time	NOUN
cana-1160	14	43	energy	energy	NOUN
cana-1160	14	44	management	management	NOUN
cana-1160	14	45	applications	application	NOUN
cana-1160	14	46	.	.	PUNCT
cana-1160	15	1	this	this	DET
cana-1160	15	2	collaborative	collaborative	ADJ
cana-1160	15	3	approach	approach	NOUN
cana-1160	15	4	paves	pave	VERB
cana-1160	15	5	the	the	DET
cana-1160	15	6	way	way	NOUN
cana-1160	15	7	for	for	ADP
cana-1160	15	8	more	more	ADV
cana-1160	15	9	dependable	dependable	ADJ
cana-1160	15	10	and	and	CCONJ
cana-1160	15	11	efficient	efficient	ADJ
cana-1160	15	12	smart	smart	ADJ
cana-1160	15	13	grid	grid	NOUN
cana-1160	15	14	operations	operation	NOUN
cana-1160	15	15	,	,	PUNCT
cana-1160	15	16	ultimately	ultimately	ADV
cana-1160	15	17	contributing	contribute	VERB
cana-1160	15	18	to	to	ADP
cana-1160	15	19	the	the	DET
cana-1160	15	20	sustainable	sustainable	ADJ
cana-1160	15	21	management	management	NOUN
cana-1160	15	22	of	of	ADP
cana-1160	15	23	energy	energy	NOUN
cana-1160	15	24	resources	resource	NOUN
cana-1160	15	25	.	.	PUNCT
cana-1160	16	1	lnns	lnns	PROPN
cana-1160	16	2	offer	offer	VERB
cana-1160	16	3	a	a	DET
cana-1160	16	4	dynamic	dynamic	ADJ
cana-1160	16	5	and	and	CCONJ
cana-1160	16	6	flexible	flexible	ADJ
cana-1160	16	7	model	model	NOUN
cana-1160	16	8	that	that	PRON
cana-1160	16	9	can	can	AUX
cana-1160	16	10	adapt	adapt	VERB
cana-1160	16	11	to	to	ADP
cana-1160	16	12	changing	change	VERB
cana-1160	16	13	inputs	input	NOUN
cana-1160	16	14	and	and	CCONJ
cana-1160	16	15	handle	handle	VERB
cana-1160	16	16	time	time	NOUN
cana-1160	16	17	-	-	PUNCT
cana-1160	16	18	dependent	dependent	ADJ
cana-1160	16	19	data	data	NOUN
cana-1160	16	20	communications	communication	NOUN
cana-1160	16	21	on	on	ADP
cana-1160	16	22	applied	apply	VERB
cana-1160	16	23	nonlinear	nonlinear	ADJ
cana-1160	16	24	analysis	analysis	NOUN
cana-1160	16	25	issn	issn	NOUN
cana-1160	16	26	:	:	PUNCT
cana-1160	16	27	1074	1074	NUM
cana-1160	16	28	-	-	PUNCT
cana-1160	16	29	133x	133x	NUM
cana-1160	16	30	vol	vol	NOUN
cana-1160	16	31	31	31	NUM
cana-1160	16	32	no	no	NOUN
cana-1160	16	33	.	.	PUNCT
cana-1160	17	1	6s	6s	NUM
cana-1160	17	2	(	(	PUNCT
cana-1160	17	3	2024	2024	NUM
cana-1160	17	4	)	)	PUNCT
cana-1160	17	5	75	75	NUM
cana-1160	17	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1160	17	7	efficiently	efficiently	ADV
cana-1160	17	8	.	.	PUNCT
cana-1160	18	1	[	[	X
cana-1160	18	2	1	1	NUM
cana-1160	18	3	]	]	PUNCT
cana-1160	18	4	.	.	PUNCT
cana-1160	19	1	traditional	traditional	ADJ
cana-1160	19	2	machine	machine	NOUN
cana-1160	19	3	learning	learning	NOUN
cana-1160	19	4	models	model	NOUN
cana-1160	19	5	often	often	ADV
cana-1160	19	6	struggle	struggle	VERB
cana-1160	19	7	with	with	ADP
cana-1160	19	8	high	high	ADJ
cana-1160	19	9	data	datum	NOUN
cana-1160	19	10	due	due	ADP
cana-1160	19	11	to	to	ADP
cana-1160	19	12	their	their	PRON
cana-1160	19	13	inability	inability	NOUN
cana-1160	19	14	to	to	PART
cana-1160	19	15	efficiently	efficiently	ADV
cana-1160	19	16	process	process	VERB
cana-1160	19	17	and	and	CCONJ
cana-1160	19	18	learn	learn	VERB
cana-1160	19	19	from	from	ADP
cana-1160	19	20	high	high	ADJ
cana-1160	19	21	-	-	PUNCT
cana-1160	19	22	dimensional	dimensional	ADJ
cana-1160	19	23	feature	feature	NOUN
cana-1160	19	24	spaces	space	NOUN
cana-1160	19	25	.	.	PUNCT
cana-1160	20	1	kans	kans	PROPN
cana-1160	20	2	offer	offer	VERB
cana-1160	20	3	a	a	DET
cana-1160	20	4	theoretical	theoretical	ADJ
cana-1160	20	5	foundation	foundation	NOUN
cana-1160	20	6	for	for	ADP
cana-1160	20	7	representing	represent	VERB
cana-1160	20	8	high	high	ADJ
cana-1160	20	9	-	-	PUNCT
cana-1160	20	10	dimensional	dimensional	ADJ
cana-1160	20	11	functions	function	NOUN
cana-1160	20	12	more	more	ADV
cana-1160	20	13	effectively	effectively	ADV
cana-1160	20	14	.	.	PUNCT
cana-1160	21	1	[	[	X
cana-1160	21	2	2	2	NUM
cana-1160	21	3	]	]	PUNCT
cana-1160	21	4	.	.	PUNCT
cana-1160	22	1	liquid	liquid	ADJ
cana-1160	22	2	neural	neural	ADJ
cana-1160	22	3	networks	network	NOUN
cana-1160	22	4	represent	represent	VERB
cana-1160	22	5	a	a	DET
cana-1160	22	6	significant	significant	ADJ
cana-1160	22	7	advancement	advancement	NOUN
cana-1160	22	8	in	in	ADP
cana-1160	22	9	the	the	DET
cana-1160	22	10	field	field	NOUN
cana-1160	22	11	of	of	ADP
cana-1160	22	12	predictive	predictive	ADJ
cana-1160	22	13	analytics	analytic	NOUN
cana-1160	22	14	.	.	PUNCT
cana-1160	23	1	their	their	PRON
cana-1160	23	2	ability	ability	NOUN
cana-1160	23	3	to	to	PART
cana-1160	23	4	dynamically	dynamically	ADV
cana-1160	23	5	adapt	adapt	VERB
cana-1160	23	6	to	to	ADP
cana-1160	23	7	changing	change	VERB
cana-1160	23	8	inputs	input	NOUN
cana-1160	23	9	and	and	CCONJ
cana-1160	23	10	accurately	accurately	ADV
cana-1160	23	11	model	model	VERB
cana-1160	23	12	temporal	temporal	ADJ
cana-1160	23	13	data	datum	NOUN
cana-1160	23	14	positions	position	VERB
cana-1160	23	15	them	they	PRON
cana-1160	23	16	as	as	ADP
cana-1160	23	17	a	a	DET
cana-1160	23	18	powerful	powerful	ADJ
cana-1160	23	19	tool	tool	NOUN
cana-1160	23	20	for	for	ADP
cana-1160	23	21	a	a	DET
cana-1160	23	22	wide	wide	ADJ
cana-1160	23	23	range	range	NOUN
cana-1160	23	24	of	of	ADP
cana-1160	23	25	predictive	predictive	ADJ
cana-1160	23	26	applications	application	NOUN
cana-1160	23	27	[	[	X
cana-1160	23	28	20	20	NUM
cana-1160	23	29	]	]	PUNCT
cana-1160	23	30	.	.	PUNCT
cana-1160	24	1	2	2	X
cana-1160	24	2	.	.	X
cana-1160	24	3	statement	statement	NOUN
cana-1160	24	4	of	of	ADP
cana-1160	24	5	the	the	DET
cana-1160	24	6	problem	problem	NOUN
cana-1160	24	7	the	the	DET
cana-1160	24	8	growing	grow	VERB
cana-1160	24	9	complexity	complexity	NOUN
cana-1160	24	10	and	and	CCONJ
cana-1160	24	11	dynamic	dynamic	ADJ
cana-1160	24	12	nature	nature	NOUN
cana-1160	24	13	of	of	ADP
cana-1160	24	14	modern	modern	ADJ
cana-1160	24	15	energy	energy	NOUN
cana-1160	24	16	systems	system	NOUN
cana-1160	24	17	pose	pose	VERB
cana-1160	24	18	significant	significant	ADJ
cana-1160	24	19	challenges	challenge	NOUN
cana-1160	24	20	to	to	PART
cana-1160	24	21	accurate	accurate	VERB
cana-1160	24	22	energy	energy	NOUN
cana-1160	24	23	consumption	consumption	NOUN
cana-1160	24	24	prediction	prediction	NOUN
cana-1160	24	25	in	in	ADP
cana-1160	24	26	smart	smart	ADJ
cana-1160	24	27	grids	grid	NOUN
cana-1160	24	28	.	.	PUNCT
cana-1160	25	1	traditional	traditional	ADJ
cana-1160	25	2	predictive	predictive	ADJ
cana-1160	25	3	models	model	NOUN
cana-1160	25	4	frequently	frequently	ADV
cana-1160	25	5	struggle	struggle	VERB
cana-1160	25	6	to	to	PART
cana-1160	25	7	deal	deal	VERB
cana-1160	25	8	with	with	ADP
cana-1160	25	9	the	the	DET
cana-1160	25	10	high	high	ADV
cana-1160	25	11	-	-	PUNCT
cana-1160	25	12	dimensional	dimensional	ADJ
cana-1160	25	13	,	,	PUNCT
cana-1160	25	14	time	time	NOUN
cana-1160	25	15	-	-	PUNCT
cana-1160	25	16	dependent	dependent	ADJ
cana-1160	25	17	,	,	PUNCT
cana-1160	25	18	and	and	CCONJ
cana-1160	25	19	nonlinear	nonlinear	ADJ
cana-1160	25	20	nature	nature	NOUN
cana-1160	25	21	of	of	ADP
cana-1160	25	22	energy	energy	NOUN
cana-1160	25	23	usage	usage	NOUN
cana-1160	25	24	data	datum	NOUN
cana-1160	25	25	.	.	PUNCT
cana-1160	26	1	as	as	ADP
cana-1160	26	2	a	a	DET
cana-1160	26	3	result	result	NOUN
cana-1160	26	4	,	,	PUNCT
cana-1160	26	5	these	these	DET
cana-1160	26	6	models	model	NOUN
cana-1160	26	7	may	may	AUX
cana-1160	26	8	result	result	VERB
cana-1160	26	9	in	in	ADP
cana-1160	26	10	suboptimal	suboptimal	ADJ
cana-1160	26	11	grid	grid	NOUN
cana-1160	26	12	management	management	NOUN
cana-1160	26	13	,	,	PUNCT
cana-1160	26	14	inefficiencies	inefficiency	NOUN
cana-1160	26	15	in	in	ADP
cana-1160	26	16	energy	energy	NOUN
cana-1160	26	17	distribution	distribution	NOUN
cana-1160	26	18	,	,	PUNCT
cana-1160	26	19	and	and	CCONJ
cana-1160	26	20	higher	high	ADJ
cana-1160	26	21	operational	operational	ADJ
cana-1160	26	22	costs	cost	NOUN
cana-1160	26	23	.	.	PUNCT
cana-1160	27	1	3	3	X
cana-1160	27	2	.	.	X
cana-1160	27	3	need	need	NOUN
cana-1160	27	4	and	and	CCONJ
cana-1160	27	5	significance	significance	NOUN
cana-1160	27	6	of	of	ADP
cana-1160	27	7	the	the	DET
cana-1160	27	8	study	study	NOUN
cana-1160	27	9	existing	exist	VERB
cana-1160	27	10	methodologies	methodology	NOUN
cana-1160	27	11	,	,	PUNCT
cana-1160	27	12	such	such	ADJ
cana-1160	27	13	as	as	ADP
cana-1160	27	14	deep	deep	ADJ
cana-1160	27	15	neural	neural	ADJ
cana-1160	27	16	networks	network	NOUN
cana-1160	27	17	(	(	PUNCT
cana-1160	27	18	dnns	dnn	NOUN
cana-1160	27	19	)	)	PUNCT
cana-1160	27	20	,	,	PUNCT
cana-1160	27	21	offer	offer	VERB
cana-1160	27	22	some	some	DET
cana-1160	27	23	advantages	advantage	NOUN
cana-1160	27	24	over	over	ADP
cana-1160	27	25	traditional	traditional	ADJ
cana-1160	27	26	statistical	statistical	ADJ
cana-1160	27	27	methods	method	NOUN
cana-1160	27	28	,	,	PUNCT
cana-1160	27	29	but	but	CCONJ
cana-1160	27	30	they	they	PRON
cana-1160	27	31	are	be	AUX
cana-1160	27	32	fundamentally	fundamentally	ADV
cana-1160	27	33	limited	limit	VERB
cana-1160	27	34	by	by	ADP
cana-1160	27	35	their	their	PRON
cana-1160	27	36	static	static	ADJ
cana-1160	27	37	processing	processing	NOUN
cana-1160	27	38	capabilities	capability	NOUN
cana-1160	27	39	and	and	CCONJ
cana-1160	27	40	inability	inability	NOUN
cana-1160	27	41	to	to	PART
cana-1160	27	42	adapt	adapt	VERB
cana-1160	27	43	to	to	ADP
cana-1160	27	44	rapidly	rapidly	ADV
cana-1160	27	45	changing	change	VERB
cana-1160	27	46	input	input	NOUN
cana-1160	27	47	patterns	pattern	NOUN
cana-1160	27	48	.	.	PUNCT
cana-1160	28	1	these	these	DET
cana-1160	28	2	limitations	limitation	NOUN
cana-1160	28	3	limit	limit	VERB
cana-1160	28	4	smart	smart	ADJ
cana-1160	28	5	grid	grid	NOUN
cana-1160	28	6	systems	system	NOUN
cana-1160	28	7	'	'	PART
cana-1160	28	8	ability	ability	NOUN
cana-1160	28	9	to	to	PART
cana-1160	28	10	respond	respond	VERB
cana-1160	28	11	to	to	ADP
cana-1160	28	12	real	real	ADJ
cana-1160	28	13	-	-	PUNCT
cana-1160	28	14	time	time	NOUN
cana-1160	28	15	fluctuations	fluctuation	NOUN
cana-1160	28	16	in	in	ADP
cana-1160	28	17	energy	energy	NOUN
cana-1160	28	18	demand	demand	NOUN
cana-1160	28	19	and	and	CCONJ
cana-1160	28	20	supply	supply	NOUN
cana-1160	28	21	,	,	PUNCT
cana-1160	28	22	which	which	PRON
cana-1160	28	23	is	be	AUX
cana-1160	28	24	critical	critical	ADJ
cana-1160	28	25	for	for	ADP
cana-1160	28	26	grid	grid	NOUN
cana-1160	28	27	stability	stability	NOUN
cana-1160	28	28	and	and	CCONJ
cana-1160	28	29	resource	resource	NOUN
cana-1160	28	30	optimisation	optimisation	NOUN
cana-1160	28	31	.	.	PUNCT
cana-1160	29	1	in	in	ADP
cana-1160	29	2	this	this	DET
cana-1160	29	3	context	context	NOUN
cana-1160	29	4	,	,	PUNCT
cana-1160	29	5	there	there	PRON
cana-1160	29	6	is	be	VERB
cana-1160	29	7	an	an	DET
cana-1160	29	8	urgent	urgent	ADJ
cana-1160	29	9	need	need	NOUN
cana-1160	29	10	for	for	ADP
cana-1160	29	11	novel	novel	ADJ
cana-1160	29	12	approaches	approach	NOUN
cana-1160	29	13	that	that	PRON
cana-1160	29	14	can	can	AUX
cana-1160	29	15	model	model	VERB
cana-1160	29	16	and	and	CCONJ
cana-1160	29	17	predict	predict	VERB
cana-1160	29	18	energy	energy	NOUN
cana-1160	29	19	consumption	consumption	NOUN
cana-1160	29	20	with	with	ADP
cana-1160	29	21	greater	great	ADJ
cana-1160	29	22	precision	precision	NOUN
cana-1160	29	23	and	and	CCONJ
cana-1160	29	24	adaptability	adaptability	NOUN
cana-1160	29	25	.	.	PUNCT
cana-1160	30	1	kolmogorovarnold	kolmogorovarnold	PROPN
cana-1160	30	2	networks	network	NOUN
cana-1160	30	3	(	(	PUNCT
cana-1160	30	4	kans	kans	PROPN
cana-1160	30	5	)	)	PUNCT
cana-1160	30	6	provide	provide	VERB
cana-1160	30	7	a	a	DET
cana-1160	30	8	promising	promising	ADJ
cana-1160	30	9	solution	solution	NOUN
cana-1160	30	10	by	by	ADP
cana-1160	30	11	breaking	break	VERB
cana-1160	30	12	down	down	ADP
cana-1160	30	13	complex	complex	ADJ
cana-1160	30	14	multivariate	multivariate	NOUN
cana-1160	30	15	functions	function	NOUN
cana-1160	30	16	into	into	ADP
cana-1160	30	17	simpler	simple	ADJ
cana-1160	30	18	univariate	univariate	ADJ
cana-1160	30	19	functions	function	NOUN
cana-1160	30	20	,	,	PUNCT
cana-1160	30	21	thereby	thereby	ADV
cana-1160	30	22	capturing	capture	VERB
cana-1160	30	23	intricate	intricate	ADJ
cana-1160	30	24	data	datum	NOUN
cana-1160	30	25	dependencies	dependency	NOUN
cana-1160	30	26	.	.	PUNCT
cana-1160	31	1	meanwhile	meanwhile	ADV
cana-1160	31	2	,	,	PUNCT
cana-1160	31	3	liquid	liquid	ADJ
cana-1160	31	4	neural	neural	ADJ
cana-1160	31	5	networks	network	NOUN
cana-1160	31	6	(	(	PUNCT
cana-1160	31	7	lnns	lnns	ADJ
cana-1160	31	8	)	)	PUNCT
cana-1160	31	9	introduce	introduce	VERB
cana-1160	31	10	a	a	DET
cana-1160	31	11	dynamic	dynamic	ADJ
cana-1160	31	12	element	element	NOUN
cana-1160	31	13	through	through	ADP
cana-1160	31	14	their	their	PRON
cana-1160	31	15	continuous	continuous	ADJ
cana-1160	31	16	and	and	CCONJ
cana-1160	31	17	differentiable	differentiable	ADJ
cana-1160	31	18	activation	activation	NOUN
cana-1160	31	19	functions	function	NOUN
cana-1160	31	20	,	,	PUNCT
cana-1160	31	21	allowing	allow	VERB
cana-1160	31	22	for	for	ADP
cana-1160	31	23	real	real	ADJ
cana-1160	31	24	-	-	PUNCT
cana-1160	31	25	time	time	NOUN
cana-1160	31	26	adaptation	adaptation	NOUN
cana-1160	31	27	to	to	ADP
cana-1160	31	28	changing	change	VERB
cana-1160	31	29	data	datum	NOUN
cana-1160	31	30	patterns	pattern	NOUN
cana-1160	31	31	.	.	PUNCT
cana-1160	32	1	4	4	X
cana-1160	32	2	.	.	X
cana-1160	32	3	theoretical	theoretical	ADJ
cana-1160	32	4	groundings	grounding	NOUN
cana-1160	32	5	kolmogorov	kolmogorov	PROPN
cana-1160	32	6	-	-	PUNCT
cana-1160	32	7	arnold	arnold	PROPN
cana-1160	32	8	networks	network	NOUN
cana-1160	32	9	(	(	PUNCT
cana-1160	32	10	kans	kans	PROPN
cana-1160	32	11	):	):	PUNCT
cana-1160	32	12	using	use	VERB
cana-1160	32	13	the	the	DET
cana-1160	32	14	kolmogorov	kolmogorov	PROPN
cana-1160	32	15	-	-	PUNCT
cana-1160	32	16	arnold	arnold	PROPN
cana-1160	32	17	representation	representation	PROPN
cana-1160	32	18	theorem	theorem	NOUN
cana-1160	32	19	,	,	PUNCT
cana-1160	32	20	kans	kan	NOUN
cana-1160	32	21	can	can	AUX
cana-1160	32	22	approximate	approximate	VERB
cana-1160	32	23	any	any	DET
cana-1160	32	24	continuous	continuous	ADJ
cana-1160	32	25	function	function	NOUN
cana-1160	32	26	by	by	ADP
cana-1160	32	27	breaking	break	VERB
cana-1160	32	28	it	it	PRON
cana-1160	32	29	down	down	ADP
cana-1160	32	30	into	into	ADP
cana-1160	32	31	a	a	DET
cana-1160	32	32	superposition	superposition	NOUN
cana-1160	32	33	of	of	ADP
cana-1160	32	34	univariate	univariate	ADJ
cana-1160	32	35	functions	function	NOUN
cana-1160	32	36	.	.	PUNCT
cana-1160	33	1	kolmogorov	kolmogorov	PROPN
cana-1160	33	2	-	-	PUNCT
cana-1160	33	3	arnold	arnold	PROPN
cana-1160	33	4	networks	network	NOUN
cana-1160	33	5	(	(	PUNCT
cana-1160	33	6	kans	kans	PROPN
cana-1160	33	7	)	)	PUNCT
cana-1160	33	8	are	be	AUX
cana-1160	33	9	based	base	VERB
cana-1160	33	10	on	on	ADP
cana-1160	33	11	the	the	DET
cana-1160	33	12	kolmogorov	kolmogorov	PROPN
cana-1160	33	13	-	-	PUNCT
cana-1160	33	14	arnold	arnold	PROPN
cana-1160	33	15	representation	representation	PROPN
cana-1160	33	16	theorem	theorem	PROPN
cana-1160	33	17	,	,	PUNCT
cana-1160	33	18	which	which	PRON
cana-1160	33	19	states	state	VERB
cana-1160	33	20	that	that	SCONJ
cana-1160	33	21	any	any	DET
cana-1160	33	22	multivariate	multivariate	NOUN
cana-1160	33	23	continuous	continuous	ADJ
cana-1160	33	24	function	function	NOUN
cana-1160	33	25	can	can	AUX
cana-1160	33	26	be	be	AUX
cana-1160	33	27	represented	represent	VERB
cana-1160	33	28	as	as	ADP
cana-1160	33	29	a	a	DET
cana-1160	33	30	superposition	superposition	NOUN
cana-1160	33	31	of	of	ADP
cana-1160	33	32	continuous	continuous	ADJ
cana-1160	33	33	functions	function	NOUN
cana-1160	33	34	in	in	ADP
cana-1160	33	35	one	one	NUM
cana-1160	33	36	variable	variable	NOUN
cana-1160	33	37	plus	plus	CCONJ
cana-1160	33	38	addition	addition	NOUN
cana-1160	33	39	.	.	PUNCT
cana-1160	34	1	the	the	DET
cana-1160	34	2	components	component	NOUN
cana-1160	34	3	of	of	ADP
cana-1160	34	4	kans	kan	NOUN
cana-1160	34	5	are	be	AUX
cana-1160	34	6	designed	design	VERB
cana-1160	34	7	to	to	PART
cana-1160	34	8	use	use	VERB
cana-1160	34	9	this	this	DET
cana-1160	34	10	theorem	theorem	NOUN
cana-1160	34	11	to	to	PART
cana-1160	34	12	model	model	NOUN
cana-1160	34	13	complex	complex	ADJ
cana-1160	34	14	,	,	PUNCT
cana-1160	34	15	high	high	ADJ
cana-1160	34	16	-	-	PUNCT
cana-1160	34	17	dimensional	dimensional	ADJ
cana-1160	34	18	functions	function	NOUN
cana-1160	34	19	.	.	PUNCT
cana-1160	35	1	in	in	ADP
cana-1160	35	2	summary	summary	NOUN
cana-1160	35	3	,	,	PUNCT
cana-1160	35	4	a	a	DET
cana-1160	35	5	kolmogorov	kolmogorov	PROPN
cana-1160	35	6	-	-	PUNCT
cana-1160	35	7	arnold	arnold	PROPN
cana-1160	35	8	network	network	NOUN
cana-1160	35	9	consists	consist	VERB
cana-1160	35	10	of	of	ADP
cana-1160	35	11	input	input	NOUN
cana-1160	35	12	layers	layer	NOUN
cana-1160	35	13	that	that	PRON
cana-1160	35	14	capture	capture	VERB
cana-1160	35	15	high	high	ADV
cana-1160	35	16	-	-	PUNCT
cana-1160	35	17	dimensional	dimensional	ADJ
cana-1160	35	18	data	datum	NOUN
cana-1160	35	19	,	,	PUNCT
cana-1160	35	20	a	a	DET
cana-1160	35	21	series	series	NOUN
cana-1160	35	22	of	of	ADP
cana-1160	35	23	univariate	univariate	ADJ
cana-1160	35	24	functions	function	NOUN
cana-1160	35	25	that	that	PRON
cana-1160	35	26	transform	transform	VERB
cana-1160	35	27	the	the	DET
cana-1160	35	28	input	input	NOUN
cana-1160	35	29	features	feature	NOUN
cana-1160	35	30	,	,	PUNCT
cana-1160	35	31	summation	summation	NOUN
cana-1160	35	32	nodes	node	NOUN
cana-1160	35	33	that	that	PRON
cana-1160	35	34	aggregate	aggregate	VERB
cana-1160	35	35	these	these	DET
cana-1160	35	36	transformations	transformation	NOUN
cana-1160	35	37	,	,	PUNCT
cana-1160	35	38	and	and	CCONJ
cana-1160	35	39	an	an	DET
cana-1160	35	40	output	output	NOUN
cana-1160	35	41	layer	layer	NOUN
cana-1160	35	42	that	that	PRON
cana-1160	35	43	makes	make	VERB
cana-1160	35	44	the	the	DET
cana-1160	35	45	final	final	ADJ
cana-1160	35	46	prediction	prediction	NOUN
cana-1160	35	47	.	.	PUNCT
cana-1160	36	1	during	during	ADP
cana-1160	36	2	training	training	NOUN
cana-1160	36	3	,	,	PUNCT
cana-1160	36	4	model	model	NOUN
cana-1160	36	5	parameters	parameter	NOUN
cana-1160	36	6	such	such	ADJ
cana-1160	36	7	as	as	ADP
cana-1160	36	8	weights	weight	NOUN
cana-1160	36	9	and	and	CCONJ
cana-1160	36	10	biases	bias	NOUN
cana-1160	36	11	are	be	AUX
cana-1160	36	12	optimised	optimise	VERB
cana-1160	36	13	to	to	PART
cana-1160	36	14	accurately	accurately	ADV
cana-1160	36	15	represent	represent	VERB
cana-1160	36	16	the	the	DET
cana-1160	36	17	data	datum	NOUN
cana-1160	36	18	's	's	PART
cana-1160	36	19	underlying	underlie	VERB
cana-1160	36	20	function	function	NOUN
cana-1160	36	21	.	.	PUNCT
cana-1160	37	1	kans	kans	PROPN
cana-1160	37	2	demonstrated	demonstrate	VERB
cana-1160	37	3	superior	superior	ADJ
cana-1160	37	4	predictive	predictive	ADJ
cana-1160	37	5	accuracy	accuracy	NOUN
cana-1160	37	6	compared	compare	VERB
cana-1160	37	7	to	to	ADP
cana-1160	37	8	conventional	conventional	ADJ
cana-1160	37	9	climate	climate	NOUN
cana-1160	37	10	models	model	NOUN
cana-1160	37	11	.	.	PUNCT
cana-1160	38	1	the	the	DET
cana-1160	38	2	ability	ability	NOUN
cana-1160	38	3	of	of	ADP
cana-1160	38	4	kans	kan	NOUN
cana-1160	38	5	to	to	PART
cana-1160	38	6	capture	capture	VERB
cana-1160	38	7	complex	complex	ADJ
cana-1160	38	8	,	,	PUNCT
cana-1160	38	9	nonlinear	nonlinear	ADJ
cana-1160	38	10	relationships	relationship	NOUN
cana-1160	38	11	within	within	ADP
cana-1160	38	12	climate	climate	NOUN
cana-1160	38	13	data	datum	NOUN
cana-1160	38	14	resulted	result	VERB
cana-1160	38	15	in	in	ADP
cana-1160	38	16	more	more	ADV
cana-1160	38	17	reliable	reliable	ADJ
cana-1160	38	18	forecasts	forecast	NOUN
cana-1160	38	19	.	.	PUNCT
cana-1160	39	1	[	[	X
cana-1160	39	2	13	13	NUM
cana-1160	39	3	]	]	PUNCT
cana-1160	39	4	.	.	PUNCT
cana-1160	40	1	liquid	liquid	ADJ
cana-1160	40	2	neural	neural	ADJ
cana-1160	40	3	networks	network	NOUN
cana-1160	40	4	(	(	PUNCT
cana-1160	40	5	lnns	lnns	ADJ
cana-1160	40	6	)	)	PUNCT
cana-1160	40	7	are	be	AUX
cana-1160	40	8	a	a	DET
cana-1160	40	9	type	type	NOUN
cana-1160	40	10	of	of	ADP
cana-1160	40	11	recurrent	recurrent	ADJ
cana-1160	40	12	neural	neural	ADJ
cana-1160	40	13	network	network	NOUN
cana-1160	40	14	(	(	PUNCT
cana-1160	40	15	rnn	rnn	PROPN
cana-1160	40	16	)	)	PUNCT
cana-1160	40	17	that	that	PRON
cana-1160	40	18	can	can	AUX
cana-1160	40	19	adapt	adapt	VERB
cana-1160	40	20	to	to	ADP
cana-1160	40	21	changing	change	VERB
cana-1160	40	22	inputs	input	NOUN
cana-1160	40	23	and	and	CCONJ
cana-1160	40	24	tasks	task	NOUN
cana-1160	40	25	in	in	ADP
cana-1160	40	26	real	real	ADJ
cana-1160	40	27	time	time	NOUN
cana-1160	40	28	,	,	PUNCT
cana-1160	40	29	making	make	VERB
cana-1160	40	30	them	they	PRON
cana-1160	40	31	ideal	ideal	ADJ
cana-1160	40	32	for	for	ADP
cana-1160	40	33	processing	process	VERB
cana-1160	40	34	sequences	sequence	NOUN
cana-1160	40	35	and	and	CCONJ
cana-1160	40	36	time	time	NOUN
cana-1160	40	37	series	series	PROPN
cana-1160	40	38	communications	communication	NOUN
cana-1160	40	39	on	on	ADP
cana-1160	40	40	applied	apply	VERB
cana-1160	40	41	nonlinear	nonlinear	ADJ
cana-1160	40	42	analysis	analysis	NOUN
cana-1160	40	43	issn	issn	NOUN
cana-1160	40	44	:	:	PUNCT
cana-1160	40	45	1074	1074	NUM
cana-1160	40	46	-	-	PUNCT
cana-1160	40	47	133x	133x	NUM
cana-1160	40	48	vol	vol	NOUN
cana-1160	40	49	31	31	NUM
cana-1160	40	50	no	no	NOUN
cana-1160	40	51	.	.	PUNCT
cana-1160	41	1	6s	6s	NUM
cana-1160	41	2	(	(	PUNCT
cana-1160	41	3	2024	2024	NUM
cana-1160	41	4	)	)	PUNCT
cana-1160	41	5	76	76	NUM
cana-1160	41	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1160	41	7	data	datum	NOUN
cana-1160	41	8	i.e.	i.e.	X
cana-1160	41	9	lnns	lnns	PROPN
cana-1160	41	10	are	be	AUX
cana-1160	41	11	designed	design	VERB
cana-1160	41	12	to	to	PART
cana-1160	41	13	deal	deal	VERB
cana-1160	41	14	with	with	ADP
cana-1160	41	15	dynamic	dynamic	ADJ
cana-1160	41	16	,	,	PUNCT
cana-1160	41	17	time	time	NOUN
cana-1160	41	18	-	-	PUNCT
cana-1160	41	19	varying	vary	VERB
cana-1160	41	20	data	datum	NOUN
cana-1160	41	21	by	by	ADP
cana-1160	41	22	incorporating	incorporate	VERB
cana-1160	41	23	continuous	continuous	ADJ
cana-1160	41	24	and	and	CCONJ
cana-1160	41	25	differentiable	differentiable	ADJ
cana-1160	41	26	activation	activation	NOUN
cana-1160	41	27	functions	function	NOUN
cana-1160	41	28	that	that	PRON
cana-1160	41	29	can	can	AUX
cana-1160	41	30	adapt	adapt	VERB
cana-1160	41	31	in	in	ADP
cana-1160	41	32	real	real	ADJ
cana-1160	41	33	time	time	NOUN
cana-1160	41	34	.	.	PUNCT
cana-1160	42	1	they	they	PRON
cana-1160	42	2	are	be	AUX
cana-1160	42	3	distinguished	distinguish	VERB
cana-1160	42	4	by	by	ADP
cana-1160	42	5	their	their	PRON
cana-1160	42	6	dynamic	dynamic	ADJ
cana-1160	42	7	plasticity	plasticity	NOUN
cana-1160	42	8	which	which	PRON
cana-1160	42	9	is	be	AUX
cana-1160	42	10	the	the	DET
cana-1160	42	11	ability	ability	NOUN
cana-1160	42	12	to	to	PART
cana-1160	42	13	change	change	VERB
cana-1160	42	14	their	their	PRON
cana-1160	42	15	structure	structure	NOUN
cana-1160	42	16	and	and	CCONJ
cana-1160	42	17	weight	weight	NOUN
cana-1160	42	18	over	over	ADP
cana-1160	42	19	time	time	NOUN
cana-1160	42	20	.	.	PUNCT
cana-1160	43	1	temporal	temporal	ADJ
cana-1160	43	2	processing	processing	NOUN
cana-1160	43	3	is	be	AUX
cana-1160	43	4	ideal	ideal	ADJ
cana-1160	43	5	for	for	ADP
cana-1160	43	6	tasks	task	NOUN
cana-1160	43	7	that	that	PRON
cana-1160	43	8	require	require	VERB
cana-1160	43	9	sequencing	sequencing	NOUN
cana-1160	43	10	and	and	CCONJ
cana-1160	43	11	time	time	NOUN
cana-1160	43	12	-	-	PUNCT
cana-1160	43	13	series	series	NOUN
cana-1160	43	14	data	data	PROPN
cana-1160	43	15	&	&	CCONJ
cana-1160	43	16	efficiency	efficiency	NOUN
cana-1160	43	17	leads	lead	VERB
cana-1160	43	18	to	to	PART
cana-1160	43	19	often	often	ADV
cana-1160	43	20	use	use	VERB
cana-1160	43	21	fewer	few	ADJ
cana-1160	43	22	computational	computational	ADJ
cana-1160	43	23	resources	resource	NOUN
cana-1160	43	24	.	.	PUNCT
cana-1160	44	1	5	5	X
cana-1160	44	2	.	.	X
cana-1160	44	3	methodology	methodology	NOUN
cana-1160	44	4	:	:	PUNCT
cana-1160	44	5	hybrid	hybrid	ADJ
cana-1160	44	6	forecasting	forecasting	NOUN
cana-1160	44	7	approaches	approach	NOUN
cana-1160	44	8	offer	offer	VERB
cana-1160	44	9	a	a	DET
cana-1160	44	10	powerful	powerful	ADJ
cana-1160	44	11	and	and	CCONJ
cana-1160	44	12	flexible	flexible	ADJ
cana-1160	44	13	solution	solution	NOUN
cana-1160	44	14	for	for	ADP
cana-1160	44	15	smart	smart	ADJ
cana-1160	44	16	grid	grid	NOUN
cana-1160	44	17	energy	energy	NOUN
cana-1160	44	18	prediction	prediction	NOUN
cana-1160	44	19	.	.	PUNCT
cana-1160	45	1	by	by	ADP
cana-1160	45	2	leveraging	leverage	VERB
cana-1160	45	3	the	the	DET
cana-1160	45	4	strengths	strength	NOUN
cana-1160	45	5	of	of	ADP
cana-1160	45	6	multiple	multiple	ADJ
cana-1160	45	7	models	model	NOUN
cana-1160	45	8	,	,	PUNCT
cana-1160	45	9	these	these	DET
cana-1160	45	10	approaches	approach	NOUN
cana-1160	45	11	can	can	AUX
cana-1160	45	12	better	well	ADV
cana-1160	45	13	capture	capture	VERB
cana-1160	45	14	the	the	DET
cana-1160	45	15	intricate	intricate	ADJ
cana-1160	45	16	dynamics	dynamic	NOUN
cana-1160	45	17	of	of	ADP
cana-1160	45	18	energy	energy	NOUN
cana-1160	45	19	consumption	consumption	NOUN
cana-1160	45	20	[	[	X
cana-1160	45	21	3	3	NUM
cana-1160	45	22	]	]	PUNCT
cana-1160	45	23	.	.	PUNCT
cana-1160	46	1	combining	combine	VERB
cana-1160	46	2	liquid	liquid	ADJ
cana-1160	46	3	neural	neural	ADJ
cana-1160	46	4	networks	network	NOUN
cana-1160	46	5	and	and	CCONJ
cana-1160	46	6	kolmogorov	kolmogorov	PROPN
cana-1160	46	7	-	-	PUNCT
cana-1160	46	8	arnold	arnold	PROPN
cana-1160	46	9	networks	network	NOUN
cana-1160	46	10	(	(	PUNCT
cana-1160	46	11	kans	kan	NOUN
cana-1160	46	12	)	)	PUNCT
cana-1160	46	13	to	to	PART
cana-1160	46	14	create	create	VERB
cana-1160	46	15	a	a	DET
cana-1160	46	16	new	new	ADJ
cana-1160	46	17	and	and	CCONJ
cana-1160	46	18	improved	improved	ADJ
cana-1160	46	19	neural	neural	ADJ
cana-1160	46	20	network	network	NOUN
cana-1160	46	21	is	be	AUX
cana-1160	46	22	a	a	DET
cana-1160	46	23	fascinating	fascinating	ADJ
cana-1160	46	24	concept	concept	NOUN
cana-1160	46	25	that	that	PRON
cana-1160	46	26	takes	take	VERB
cana-1160	46	27	advantage	advantage	NOUN
cana-1160	46	28	of	of	ADP
cana-1160	46	29	the	the	DET
cana-1160	46	30	strengths	strength	NOUN
cana-1160	46	31	of	of	ADP
cana-1160	46	32	both	both	DET
cana-1160	46	33	models	model	NOUN
cana-1160	46	34	.	.	PUNCT
cana-1160	47	1	here	here	ADV
cana-1160	47	2	's	be	AUX
cana-1160	47	3	a	a	DET
cana-1160	47	4	conceptual	conceptual	ADJ
cana-1160	47	5	outline	outline	NOUN
cana-1160	47	6	of	of	ADP
cana-1160	47	7	how	how	SCONJ
cana-1160	47	8	this	this	DET
cana-1160	47	9	combination	combination	NOUN
cana-1160	47	10	might	might	AUX
cana-1160	47	11	work	work	VERB
cana-1160	47	12	:	:	PUNCT
cana-1160	47	13	fig:1	fig:1	X
cana-1160	47	14	conceptual	conceptual	ADJ
cana-1160	47	15	framework	framework	NOUN
cana-1160	47	16	1	1	NUM
cana-1160	47	17	.	.	PUNCT
cana-1160	48	1	architecture	architecture	NOUN
cana-1160	48	2	design	design	NOUN
cana-1160	48	3	is	be	AUX
cana-1160	48	4	composed	compose	VERB
cana-1160	48	5	of	of	ADP
cana-1160	48	6	base	base	NOUN
cana-1160	48	7	layer	layer	NOUN
cana-1160	48	8	and	and	CCONJ
cana-1160	48	9	dynamic	dynamic	ADJ
cana-1160	48	10	layer	layer	NOUN
cana-1160	48	11	.	.	PUNCT
cana-1160	49	1	base	base	NOUN
cana-1160	49	2	layer	layer	NOUN
cana-1160	49	3	uses	use	VERB
cana-1160	49	4	kan	kan	PROPN
cana-1160	49	5	's	's	PART
cana-1160	49	6	approach	approach	NOUN
cana-1160	49	7	for	for	ADP
cana-1160	49	8	initial	initial	ADJ
cana-1160	49	9	function	function	NOUN
cana-1160	49	10	approximation	approximation	NOUN
cana-1160	49	11	.	.	PUNCT
cana-1160	50	1	this	this	PRON
cana-1160	50	2	can	can	AUX
cana-1160	50	3	serve	serve	VERB
cana-1160	50	4	as	as	ADP
cana-1160	50	5	a	a	DET
cana-1160	50	6	foundation	foundation	NOUN
cana-1160	50	7	,	,	PUNCT
cana-1160	50	8	ensuring	ensure	VERB
cana-1160	50	9	that	that	SCONJ
cana-1160	50	10	the	the	DET
cana-1160	50	11	network	network	NOUN
cana-1160	50	12	can	can	AUX
cana-1160	50	13	accurately	accurately	ADV
cana-1160	50	14	approximate	approximate	VERB
cana-1160	50	15	complex	complex	ADJ
cana-1160	50	16	functions	function	NOUN
cana-1160	50	17	while	while	SCONJ
cana-1160	50	18	dynamic	dynamic	ADJ
cana-1160	50	19	layer	layer	NOUN
cana-1160	50	20	uses	use	VERB
cana-1160	50	21	liquid	liquid	ADJ
cana-1160	50	22	neural	neural	ADJ
cana-1160	50	23	network	network	NOUN
cana-1160	50	24	modules	module	NOUN
cana-1160	50	25	to	to	PART
cana-1160	50	26	allow	allow	VERB
cana-1160	50	27	the	the	DET
cana-1160	50	28	system	system	NOUN
cana-1160	50	29	to	to	PART
cana-1160	50	30	adapt	adapt	VERB
cana-1160	50	31	and	and	CCONJ
cana-1160	50	32	fine	fine	ADJ
cana-1160	50	33	-	-	PUNCT
cana-1160	50	34	tune	tune	NOUN
cana-1160	50	35	its	its	PRON
cana-1160	50	36	approximation	approximation	NOUN
cana-1160	50	37	in	in	ADP
cana-1160	50	38	real	real	ADJ
cana-1160	50	39	time	time	NOUN
cana-1160	50	40	based	base	VERB
cana-1160	50	41	on	on	ADP
cana-1160	50	42	temporal	temporal	ADJ
cana-1160	50	43	data	datum	NOUN
cana-1160	50	44	and	and	CCONJ
cana-1160	50	45	changing	change	VERB
cana-1160	50	46	inputs	input	NOUN
cana-1160	50	47	.	.	PUNCT
cana-1160	51	1	2	2	X
cana-1160	51	2	.	.	X
cana-1160	51	3	function	function	NOUN
cana-1160	51	4	approximation	approximation	NOUN
cana-1160	51	5	includes	include	VERB
cana-1160	51	6	initial	initial	ADJ
cana-1160	51	7	approximation	approximation	NOUN
cana-1160	51	8	which	which	PRON
cana-1160	51	9	uses	use	VERB
cana-1160	51	10	kan	kan	PROPN
cana-1160	51	11	to	to	PART
cana-1160	51	12	generate	generate	VERB
cana-1160	51	13	an	an	DET
cana-1160	51	14	initial	initial	ADJ
cana-1160	51	15	representation	representation	NOUN
cana-1160	51	16	of	of	ADP
cana-1160	51	17	the	the	DET
cana-1160	51	18	target	target	NOUN
cana-1160	51	19	function	function	NOUN
cana-1160	51	20	or	or	CCONJ
cana-1160	51	21	sequence	sequence	NOUN
cana-1160	51	22	.	.	PUNCT
cana-1160	52	1	and	and	CCONJ
cana-1160	52	2	dynamic	dynamic	ADJ
cana-1160	52	3	adjustment	adjustment	NOUN
cana-1160	52	4	uses	use	VERB
cana-1160	52	5	liquid	liquid	ADJ
cana-1160	52	6	neural	neural	ADJ
cana-1160	52	7	network	network	NOUN
cana-1160	52	8	dynamics	dynamic	NOUN
cana-1160	52	9	to	to	PART
cana-1160	52	10	adjust	adjust	VERB
cana-1160	52	11	the	the	DET
cana-1160	52	12	initial	initial	ADJ
cana-1160	52	13	approximation	approximation	NOUN
cana-1160	52	14	in	in	ADP
cana-1160	52	15	response	response	NOUN
cana-1160	52	16	to	to	ADP
cana-1160	52	17	new	new	ADJ
cana-1160	52	18	data	datum	NOUN
cana-1160	52	19	,	,	PUNCT
cana-1160	52	20	improving	improve	VERB
cana-1160	52	21	the	the	DET
cana-1160	52	22	network	network	NOUN
cana-1160	52	23	's	's	PART
cana-1160	52	24	ability	ability	NOUN
cana-1160	52	25	to	to	PART
cana-1160	52	26	handle	handle	VERB
cana-1160	52	27	non	non	ADJ
cana-1160	52	28	-	-	ADJ
cana-1160	52	29	stationary	stationary	ADJ
cana-1160	52	30	and	and	CCONJ
cana-1160	52	31	time	time	NOUN
cana-1160	52	32	-	-	PUNCT
cana-1160	52	33	varying	vary	VERB
cana-1160	52	34	input	input	NOUN
cana-1160	52	35	.	.	PUNCT
cana-1160	53	1	3	3	X
cana-1160	53	2	.	.	X
cana-1160	53	3	learning	learn	VERB
cana-1160	53	4	process	process	NOUN
cana-1160	53	5	first	first	ADV
cana-1160	53	6	train	train	NOUN
cana-1160	53	7	kan	kan	PROPN
cana-1160	53	8	component	component	NOUN
cana-1160	53	9	to	to	ADP
cana-1160	53	10	approximate	approximate	ADJ
cana-1160	53	11	target	target	NOUN
cana-1160	53	12	function	function	NOUN
cana-1160	53	13	using	use	VERB
cana-1160	53	14	historical	historical	ADJ
cana-1160	53	15	data	datum	NOUN
cana-1160	53	16	and	and	CCONJ
cana-1160	53	17	then	then	ADV
cana-1160	53	18	adaptive	adaptive	ADJ
cana-1160	53	19	training	training	NOUN
cana-1160	53	20	come	come	VERB
cana-1160	53	21	to	to	ADP
cana-1160	53	22	picture	picture	NOUN
cana-1160	53	23	once	once	SCONJ
cana-1160	53	24	the	the	DET
cana-1160	53	25	kan	kan	PROPN
cana-1160	53	26	has	have	AUX
cana-1160	53	27	provided	provide	VERB
cana-1160	53	28	a	a	DET
cana-1160	53	29	solid	solid	ADJ
cana-1160	53	30	approximation	approximation	NOUN
cana-1160	53	31	,	,	PUNCT
cana-1160	53	32	train	train	VERB
cana-1160	53	33	the	the	DET
cana-1160	53	34	liquid	liquid	ADJ
cana-1160	53	35	neural	neural	ADJ
cana-1160	53	36	network	network	NOUN
cana-1160	53	37	component	component	NOUN
cana-1160	53	38	to	to	PART
cana-1160	53	39	make	make	VERB
cana-1160	53	40	real	real	ADJ
cana-1160	53	41	-	-	PUNCT
cana-1160	53	42	time	time	NOUN
cana-1160	53	43	adjustments	adjustment	NOUN
cana-1160	53	44	and	and	CCONJ
cana-1160	53	45	improvements	improvement	NOUN
cana-1160	53	46	,	,	PUNCT
cana-1160	53	47	adapting	adapt	VERB
cana-1160	53	48	to	to	ADP
cana-1160	53	49	new	new	ADJ
cana-1160	53	50	data	datum	NOUN
cana-1160	53	51	and	and	CCONJ
cana-1160	53	52	refining	refine	VERB
cana-1160	53	53	the	the	DET
cana-1160	53	54	approximation	approximation	NOUN
cana-1160	53	55	continuously	continuously	ADV
cana-1160	53	56	.	.	PUNCT
cana-1160	54	1	4	4	X
cana-1160	54	2	.	.	X
cana-1160	54	3	activation	activation	NOUN
cana-1160	54	4	functions	function	NOUN
cana-1160	54	5	uses	use	VERB
cana-1160	54	6	kan	kan	PROPN
cana-1160	54	7	's	's	PART
cana-1160	54	8	activation	activation	NOUN
cana-1160	54	9	functions	function	NOUN
cana-1160	54	10	for	for	ADP
cana-1160	54	11	effective	effective	ADJ
cana-1160	54	12	function	function	NOUN
cana-1160	54	13	approximation	approximation	NOUN
cana-1160	54	14	and	and	CCONJ
cana-1160	54	15	integrate	integrate	VERB
cana-1160	54	16	activation	activation	NOUN
cana-1160	54	17	functions	function	NOUN
cana-1160	54	18	from	from	ADP
cana-1160	54	19	liquid	liquid	ADJ
cana-1160	54	20	neural	neural	ADJ
cana-1160	54	21	networks	network	NOUN
cana-1160	54	22	to	to	PART
cana-1160	54	23	enhance	enhance	VERB
cana-1160	54	24	dynamic	dynamic	ADJ
cana-1160	54	25	learning	learning	NOUN
cana-1160	54	26	and	and	CCONJ
cana-1160	54	27	adaptation	adaptation	NOUN
cana-1160	54	28	.	.	PUNCT
cana-1160	55	1	communications	communication	NOUN
cana-1160	55	2	on	on	ADP
cana-1160	55	3	applied	apply	VERB
cana-1160	55	4	nonlinear	nonlinear	ADJ
cana-1160	55	5	analysis	analysis	NOUN
cana-1160	55	6	issn	issn	NOUN
cana-1160	55	7	:	:	PUNCT
cana-1160	55	8	1074	1074	NUM
cana-1160	55	9	-	-	PUNCT
cana-1160	55	10	133x	133x	NUM
cana-1160	55	11	vol	vol	NOUN
cana-1160	55	12	31	31	NUM
cana-1160	55	13	no	no	NOUN
cana-1160	55	14	.	.	PUNCT
cana-1160	56	1	6s	6s	NUM
cana-1160	56	2	(	(	PUNCT
cana-1160	56	3	2024	2024	NUM
cana-1160	56	4	)	)	PUNCT
cana-1160	56	5	77	77	NUM
cana-1160	57	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-1160	57	2	5	5	X
cana-1160	57	3	.	.	PUNCT
cana-1160	57	4	hybrid	hybrid	ADJ
cana-1160	57	5	loss	loss	NOUN
cana-1160	57	6	function	function	NOUN
cana-1160	57	7	creates	create	VERB
cana-1160	57	8	a	a	DET
cana-1160	57	9	loss	loss	NOUN
cana-1160	57	10	function	function	NOUN
cana-1160	57	11	that	that	PRON
cana-1160	57	12	combines	combine	VERB
cana-1160	57	13	elements	element	NOUN
cana-1160	57	14	of	of	ADP
cana-1160	57	15	kans	kan	NOUN
cana-1160	57	16	and	and	CCONJ
cana-1160	57	17	liquid	liquid	ADJ
cana-1160	57	18	neural	neural	ADJ
cana-1160	57	19	networks	network	NOUN
cana-1160	57	20	,	,	PUNCT
cana-1160	57	21	balancing	balance	VERB
cana-1160	57	22	accuracy	accuracy	NOUN
cana-1160	57	23	,	,	PUNCT
cana-1160	57	24	adaptability	adaptability	NOUN
cana-1160	57	25	,	,	PUNCT
cana-1160	57	26	and	and	CCONJ
cana-1160	57	27	temporal	temporal	ADJ
cana-1160	57	28	sensitivity	sensitivity	NOUN
cana-1160	57	29	.	.	PUNCT
cana-1160	58	1	fig:2	fig:2	PROPN
cana-1160	58	2	proposed	propose	VERB
cana-1160	58	3	methodology	methodology	NOUN
cana-1160	58	4	stepwise	stepwise	NOUN
cana-1160	58	5	algorithm	algorithm	NOUN
cana-1160	58	6	for	for	ADP
cana-1160	58	7	advanced	advanced	ADJ
cana-1160	58	8	energy	energy	NOUN
cana-1160	58	9	prediction	prediction	NOUN
cana-1160	58	10	using	use	VERB
cana-1160	58	11	kan	kan	PROPN
cana-1160	58	12	and	and	CCONJ
cana-1160	58	13	lnn	lnn	PROPN
cana-1160	58	14	1	1	NUM
cana-1160	58	15	:	:	PUNCT
cana-1160	58	16	import	import	VERB
cana-1160	58	17	necessary	necessary	ADJ
cana-1160	58	18	libraries	library	NOUN
cana-1160	58	19	for	for	ADP
cana-1160	58	20	data	datum	NOUN
cana-1160	58	21	manipulation	manipulation	NOUN
cana-1160	58	22	,	,	PUNCT
cana-1160	58	23	neural	neural	ADJ
cana-1160	58	24	networks	network	NOUN
cana-1160	58	25	,	,	PUNCT
cana-1160	58	26	and	and	CCONJ
cana-1160	58	27	plotting	plotting	NOUN
cana-1160	58	28	.	.	PUNCT
cana-1160	59	1	2	2	NUM
cana-1160	59	2	:	:	PUNCT
cana-1160	59	3	load	load	VERB
cana-1160	59	4	the	the	DET
cana-1160	59	5	dataset	dataset	NOUN
cana-1160	59	6	from	from	ADP
cana-1160	59	7	the	the	DET
cana-1160	59	8	provided	provide	VERB
cana-1160	59	9	,	,	PUNCT
cana-1160	59	10	pre	pre	ADJ
cana-1160	59	11	-	-	NOUN
cana-1160	59	12	process	process	NOUN
cana-1160	59	13	to	to	PART
cana-1160	59	14	handle	handle	VERB
cana-1160	59	15	missing	miss	VERB
cana-1160	59	16	values	value	NOUN
cana-1160	59	17	with	with	ADP
cana-1160	59	18	column	column	NOUN
cana-1160	59	19	means	mean	NOUN
cana-1160	59	20	,	,	PUNCT
cana-1160	59	21	convert	convert	VERB
cana-1160	59	22	'	'	PUNCT
cana-1160	59	23	global_active_power	global_active_power	NOUN
cana-1160	59	24	'	'	PUNCT
cana-1160	59	25	to	to	PART
cana-1160	59	26	float	float	VERB
cana-1160	59	27	type	type	NOUN
cana-1160	59	28	,	,	PUNCT
cana-1160	59	29	resample	resample	ADJ
cana-1160	59	30	data	datum	NOUN
cana-1160	59	31	to	to	ADP
cana-1160	59	32	daily	daily	ADJ
cana-1160	59	33	means	mean	NOUN
cana-1160	59	34	.	.	PUNCT
cana-1160	60	1	3	3	X
cana-1160	60	2	:	:	PUNCT
cana-1160	60	3	select	select	ADJ
cana-1160	60	4	features	feature	NOUN
cana-1160	60	5	:	:	PUNCT
cana-1160	60	6	'	'	PUNCT
cana-1160	60	7	global_reactive_power	global_reactive_power	X
cana-1160	60	8	'	'	PUNCT
cana-1160	60	9	,	,	PUNCT
cana-1160	60	10	'	'	PUNCT
cana-1160	60	11	voltage	voltage	NOUN
cana-1160	60	12	'	'	PUNCT
cana-1160	60	13	,	,	PUNCT
cana-1160	60	14	'	'	PUNCT
cana-1160	60	15	global_intensity	global_intensity	NOUN
cana-1160	60	16	'	'	PUNCT
cana-1160	60	17	,	,	PUNCT
cana-1160	60	18	'	'	PUNCT
cana-1160	60	19	sub_metering_1	sub_metering_1	NOUN
cana-1160	60	20	'	'	PUNCT
cana-1160	60	21	,	,	PUNCT
cana-1160	60	22	'	'	PUNCT
cana-1160	60	23	sub_metering_2	sub_metering_2	NOUN
cana-1160	60	24	'	'	NUM
cana-1160	60	25	,	,	PUNCT
cana-1160	60	26	'	'	PUNCT
cana-1160	60	27	sub_metering_3	sub_metering_3	NOUN
cana-1160	60	28	'	'	PUNCT
cana-1160	60	29	and	and	CCONJ
cana-1160	60	30	select	select	ADJ
cana-1160	60	31	target	target	NOUN
cana-1160	60	32	:	:	PUNCT
cana-1160	60	33	'	'	PUNCT
cana-1160	60	34	global_active_power	global_active_power	X
cana-1160	60	35	'	'	PUNCT
cana-1160	60	36	.	.	PUNCT
cana-1160	61	1	4	4	NUM
cana-1160	61	2	:	:	PUNCT
cana-1160	61	3	normalize	normalize	VERB
cana-1160	61	4	features	feature	NOUN
cana-1160	61	5	and	and	CCONJ
cana-1160	61	6	target	target	VERB
cana-1160	61	7	using	use	VERB
cana-1160	61	8	minmaxscaler	minmaxscaler	NOUN
cana-1160	61	9	.	.	PUNCT
cana-1160	62	1	5	5	NUM
cana-1160	62	2	:	:	PUNCT
cana-1160	62	3	split	split	VERB
cana-1160	62	4	the	the	DET
cana-1160	62	5	normalized	normalize	VERB
cana-1160	62	6	data	datum	NOUN
cana-1160	62	7	into	into	ADP
cana-1160	62	8	training	training	NOUN
cana-1160	62	9	and	and	CCONJ
cana-1160	62	10	testing	testing	NOUN
cana-1160	62	11	sets	set	NOUN
cana-1160	62	12	using	use	VERB
cana-1160	62	13	train_test_split	train_test_split	PROPN
cana-1160	62	14	.	.	PROPN
cana-1160	63	1	6	6	NUM
cana-1160	63	2	:	:	PUNCT
cana-1160	63	3	create	create	VERB
cana-1160	63	4	kan	kan	PROPN
cana-1160	63	5	model	model	NOUN
cana-1160	63	6	that	that	PRON
cana-1160	63	7	define	define	VERB
cana-1160	63	8	a	a	DET
cana-1160	63	9	simple	simple	ADJ
cana-1160	63	10	feedforward	feedforward	ADJ
cana-1160	63	11	neural	neural	ADJ
cana-1160	63	12	network	network	NOUN
cana-1160	63	13	with	with	ADP
cana-1160	63	14	dense	dense	ADJ
cana-1160	63	15	layers	layer	NOUN
cana-1160	63	16	and	and	CCONJ
cana-1160	63	17	compile	compile	VERB
cana-1160	63	18	the	the	DET
cana-1160	63	19	model	model	NOUN
cana-1160	63	20	using	use	VERB
cana-1160	63	21	adam	adam	PROPN
cana-1160	63	22	optimizer	optimizer	NOUN
cana-1160	63	23	and	and	CCONJ
cana-1160	63	24	mean	mean	VERB
cana-1160	63	25	squared	square	VERB
cana-1160	63	26	error	error	NOUN
cana-1160	63	27	loss	loss	NOUN
cana-1160	63	28	.	.	PUNCT
cana-1160	64	1	train	train	VERB
cana-1160	64	2	the	the	DET
cana-1160	64	3	kan	kan	PROPN
cana-1160	64	4	model	model	NOUN
cana-1160	64	5	on	on	ADP
cana-1160	64	6	the	the	DET
cana-1160	64	7	training	training	NOUN
cana-1160	64	8	data	datum	NOUN
cana-1160	64	9	.	.	PUNCT
cana-1160	65	1	7	7	X
cana-1160	65	2	:	:	PUNCT
cana-1160	65	3	use	use	VERB
cana-1160	65	4	the	the	DET
cana-1160	65	5	trained	train	VERB
cana-1160	65	6	kan	kan	PROPN
cana-1160	65	7	model	model	NOUN
cana-1160	65	8	to	to	PART
cana-1160	65	9	generate	generate	VERB
cana-1160	65	10	predictions	prediction	NOUN
cana-1160	65	11	for	for	ADP
cana-1160	65	12	both	both	DET
cana-1160	65	13	training	training	NOUN
cana-1160	65	14	and	and	CCONJ
cana-1160	65	15	testing	testing	NOUN
cana-1160	65	16	data	datum	NOUN
cana-1160	65	17	.	.	PUNCT
cana-1160	66	1	8	8	NUM
cana-1160	66	2	:	:	PUNCT
cana-1160	66	3	prepare	prepare	VERB
cana-1160	66	4	data	datum	NOUN
cana-1160	66	5	for	for	ADP
cana-1160	66	6	lnn	lnn	NOUN
cana-1160	66	7	component	component	NOUN
cana-1160	66	8	,	,	PUNCT
cana-1160	66	9	concatenate	concatenate	ADJ
cana-1160	66	10	kan	kan	PROPN
cana-1160	66	11	predictions	prediction	NOUN
cana-1160	66	12	with	with	ADP
cana-1160	66	13	original	original	ADJ
cana-1160	66	14	training	training	NOUN
cana-1160	66	15	and	and	CCONJ
cana-1160	66	16	testing	testing	NOUN
cana-1160	66	17	features	feature	NOUN
cana-1160	66	18	.	.	PUNCT
cana-1160	67	1	reshape	reshape	VERB
cana-1160	67	2	the	the	DET
cana-1160	67	3	data	datum	NOUN
cana-1160	67	4	to	to	PART
cana-1160	67	5	fit	fit	VERB
cana-1160	67	6	the	the	DET
cana-1160	67	7	lstm	lstm	ADJ
cana-1160	67	8	input	input	NOUN
cana-1160	67	9	requirements	requirement	NOUN
cana-1160	67	10	.	.	PUNCT
cana-1160	68	1	9	9	NUM
cana-1160	68	2	:	:	PUNCT
cana-1160	68	3	create	create	VERB
cana-1160	68	4	lnn	lnn	NOUN
cana-1160	68	5	model	model	NOUN
cana-1160	68	6	that	that	PRON
cana-1160	68	7	defines	define	VERB
cana-1160	68	8	an	an	DET
cana-1160	68	9	lstm	lstm	NOUN
cana-1160	68	10	-	-	PUNCT
cana-1160	68	11	based	base	VERB
cana-1160	68	12	neural	neural	ADJ
cana-1160	68	13	network	network	NOUN
cana-1160	68	14	with	with	ADP
cana-1160	68	15	repeatvector	repeatvector	NOUN
cana-1160	68	16	and	and	CCONJ
cana-1160	68	17	timedistributed	timedistribute	VERB
cana-1160	68	18	layers	layer	NOUN
cana-1160	68	19	after	after	ADP
cana-1160	68	20	that	that	DET
cana-1160	68	21	compile	compile	NOUN
cana-1160	68	22	the	the	DET
cana-1160	68	23	model	model	NOUN
cana-1160	68	24	using	use	VERB
cana-1160	68	25	adam	adam	PROPN
cana-1160	68	26	optimizer	optimizer	NOUN
cana-1160	68	27	and	and	CCONJ
cana-1160	68	28	mean	mean	VERB
cana-1160	68	29	squared	square	VERB
cana-1160	68	30	error	error	NOUN
cana-1160	68	31	loss	loss	NOUN
cana-1160	68	32	.	.	PUNCT
cana-1160	69	1	lastly	lastly	ADV
cana-1160	69	2	train	train	VERB
cana-1160	69	3	the	the	DET
cana-1160	69	4	lnn	lnn	NOUN
cana-1160	69	5	model	model	NOUN
cana-1160	69	6	on	on	ADP
cana-1160	69	7	the	the	DET
cana-1160	69	8	concatenated	concatenate	VERB
cana-1160	69	9	training	training	NOUN
cana-1160	69	10	data	datum	NOUN
cana-1160	69	11	.	.	PUNCT
cana-1160	70	1	10	10	NUM
cana-1160	70	2	:	:	PUNCT
cana-1160	70	3	generate	generate	VERB
cana-1160	70	4	predictions	prediction	NOUN
cana-1160	70	5	using	use	VERB
cana-1160	70	6	the	the	DET
cana-1160	70	7	trained	train	VERB
cana-1160	70	8	lnn	lnn	NOUN
cana-1160	70	9	model	model	NOUN
cana-1160	70	10	on	on	ADP
cana-1160	70	11	the	the	DET
cana-1160	70	12	testing	testing	NOUN
cana-1160	70	13	data	datum	NOUN
cana-1160	70	14	.	.	PUNCT
cana-1160	71	1	inverse	inverse	NOUN
cana-1160	71	2	transform	transform	VERB
cana-1160	71	3	the	the	DET
cana-1160	71	4	predictions	prediction	NOUN
cana-1160	71	5	and	and	CCONJ
cana-1160	71	6	actual	actual	ADJ
cana-1160	71	7	values	value	NOUN
cana-1160	71	8	to	to	ADP
cana-1160	71	9	original	original	ADJ
cana-1160	71	10	scale	scale	NOUN
cana-1160	71	11	.	.	PUNCT
cana-1160	72	1	11	11	NUM
cana-1160	72	2	:	:	PUNCT
cana-1160	72	3	output	output	VERB
cana-1160	72	4	the	the	DET
cana-1160	72	5	results	result	NOUN
cana-1160	72	6	communications	communication	NOUN
cana-1160	72	7	on	on	ADP
cana-1160	72	8	applied	apply	VERB
cana-1160	72	9	nonlinear	nonlinear	ADJ
cana-1160	72	10	analysis	analysis	NOUN
cana-1160	72	11	issn	issn	NOUN
cana-1160	72	12	:	:	PUNCT
cana-1160	72	13	1074	1074	NUM
cana-1160	72	14	-	-	PUNCT
cana-1160	72	15	133x	133x	NUM
cana-1160	72	16	vol	vol	NOUN
cana-1160	72	17	31	31	NUM
cana-1160	72	18	no	no	NOUN
cana-1160	72	19	.	.	PUNCT
cana-1160	73	1	6s	6s	NUM
cana-1160	73	2	(	(	PUNCT
cana-1160	73	3	2024	2024	NUM
cana-1160	73	4	)	)	PUNCT
cana-1160	73	5	78	78	NUM
cana-1160	73	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1160	73	7	key	key	ADJ
cana-1160	73	8	components	component	NOUN
cana-1160	73	9	and	and	CCONJ
cana-1160	73	10	their	their	PRON
cana-1160	73	11	novelty	novelty	NOUN
cana-1160	73	12	the	the	DET
cana-1160	73	13	proposed	propose	VERB
cana-1160	73	14	methodology	methodology	NOUN
cana-1160	73	15	describes	describe	VERB
cana-1160	73	16	a	a	DET
cana-1160	73	17	comprehensive	comprehensive	ADJ
cana-1160	73	18	approach	approach	NOUN
cana-1160	73	19	to	to	ADP
cana-1160	73	20	developing	develop	VERB
cana-1160	73	21	a	a	DET
cana-1160	73	22	reliable	reliable	ADJ
cana-1160	73	23	energy	energy	NOUN
cana-1160	73	24	prediction	prediction	NOUN
cana-1160	73	25	model	model	NOUN
cana-1160	73	26	for	for	ADP
cana-1160	73	27	smart	smart	ADJ
cana-1160	73	28	grids	grid	NOUN
cana-1160	73	29	that	that	PRON
cana-1160	73	30	incorporates	incorporate	VERB
cana-1160	73	31	kolmogorov	kolmogorov	PROPN
cana-1160	73	32	-	-	PUNCT
cana-1160	73	33	arnold	arnold	PROPN
cana-1160	73	34	networks	network	NOUN
cana-1160	73	35	(	(	PUNCT
cana-1160	73	36	kans	kans	PROPN
cana-1160	73	37	)	)	PUNCT
cana-1160	73	38	and	and	CCONJ
cana-1160	73	39	liquid	liquid	ADJ
cana-1160	73	40	neural	neural	ADJ
cana-1160	73	41	networks	network	NOUN
cana-1160	73	42	(	(	PUNCT
cana-1160	73	43	lnns	lnns	ADJ
cana-1160	73	44	)	)	PUNCT
cana-1160	73	45	.	.	PUNCT
cana-1160	74	1	the	the	DET
cana-1160	74	2	steps	step	NOUN
cana-1160	74	3	ensure	ensure	VERB
cana-1160	74	4	thorough	thorough	ADJ
cana-1160	74	5	data	datum	NOUN
cana-1160	74	6	preprocessing	preprocessing	NOUN
cana-1160	74	7	,	,	PUNCT
cana-1160	74	8	model	model	NOUN
cana-1160	74	9	training	training	NOUN
cana-1160	74	10	,	,	PUNCT
cana-1160	74	11	and	and	CCONJ
cana-1160	74	12	performance	performance	NOUN
cana-1160	74	13	evaluation	evaluation	NOUN
cana-1160	74	14	,	,	PUNCT
cana-1160	74	15	taking	take	VERB
cana-1160	74	16	advantage	advantage	NOUN
cana-1160	74	17	of	of	ADP
cana-1160	74	18	the	the	DET
cana-1160	74	19	strengths	strength	NOUN
cana-1160	74	20	of	of	ADP
cana-1160	74	21	both	both	DET
cana-1160	74	22	neural	neural	ADJ
cana-1160	74	23	network	network	NOUN
cana-1160	74	24	architectures	architecture	NOUN
cana-1160	74	25	to	to	PART
cana-1160	74	26	improve	improve	VERB
cana-1160	74	27	prediction	prediction	NOUN
cana-1160	74	28	accuracy	accuracy	NOUN
cana-1160	74	29	and	and	CCONJ
cana-1160	74	30	adaptability	adaptability	NOUN
cana-1160	74	31	to	to	ADP
cana-1160	74	32	real	real	ADJ
cana-1160	74	33	-	-	PUNCT
cana-1160	74	34	world	world	NOUN
cana-1160	74	35	energy	energy	NOUN
cana-1160	74	36	consumption	consumption	NOUN
cana-1160	74	37	patterns	pattern	NOUN
cana-1160	74	38	.	.	PUNCT
cana-1160	75	1	6	6	X
cana-1160	75	2	.	.	X
cana-1160	75	3	analysis	analysis	NOUN
cana-1160	75	4	fit	fit	ADJ
cana-1160	75	5	(	(	PUNCT
cana-1160	75	6	)	)	PUNCT
cana-1160	75	7	method	method	NOUN
cana-1160	75	8	for	for	ADP
cana-1160	75	9	training	train	VERB
cana-1160	75	10	the	the	DET
cana-1160	75	11	model	model	NOUN
cana-1160	75	12	on	on	ADP
cana-1160	75	13	a	a	DET
cana-1160	75	14	specific	specific	ADJ
cana-1160	75	15	dataset	dataset	NOUN
cana-1160	75	16	.	.	PUNCT
cana-1160	76	1	it	it	PRON
cana-1160	76	2	adjusts	adjust	VERB
cana-1160	76	3	the	the	DET
cana-1160	76	4	neural	neural	ADJ
cana-1160	76	5	network	network	NOUN
cana-1160	76	6	's	's	PART
cana-1160	76	7	weights	weight	NOUN
cana-1160	76	8	to	to	PART
cana-1160	76	9	minimise	minimise	VERB
cana-1160	76	10	prediction	prediction	NOUN
cana-1160	76	11	errors	error	NOUN
cana-1160	76	12	.	.	PUNCT
cana-1160	77	1	parameters	parameter	NOUN
cana-1160	77	2	:	:	PUNCT
cana-1160	78	1	x_train_lnn	x_train_lnn	NOUN
cana-1160	78	2	:	:	PUNCT
cana-1160	78	3	the	the	DET
cana-1160	78	4	training	training	NOUN
cana-1160	78	5	dataset	dataset	NOUN
cana-1160	78	6	's	's	PART
cana-1160	78	7	input	input	NOUN
cana-1160	78	8	features	feature	NOUN
cana-1160	78	9	that	that	PRON
cana-1160	78	10	are	be	AUX
cana-1160	78	11	used	use	VERB
cana-1160	78	12	to	to	PART
cana-1160	78	13	train	train	VERB
cana-1160	78	14	the	the	DET
cana-1160	78	15	lnn	lnn	PROPN
cana-1160	78	16	model	model	NOUN
cana-1160	78	17	.	.	PUNCT
cana-1160	79	1	y_train	y_train	X
cana-1160	79	2	:	:	PUNCT
cana-1160	79	3	these	these	PRON
cana-1160	79	4	are	be	AUX
cana-1160	79	5	the	the	DET
cana-1160	79	6	training	training	NOUN
cana-1160	79	7	dataset	dataset	NOUN
cana-1160	79	8	's	's	PART
cana-1160	79	9	target	target	NOUN
cana-1160	79	10	labels	label	NOUN
cana-1160	79	11	.	.	PUNCT
cana-1160	80	1	epochs=50	epochs=50	NOUN
cana-1160	80	2	:	:	PUNCT
cana-1160	80	3	the	the	DET
cana-1160	80	4	number	number	NOUN
cana-1160	80	5	of	of	ADP
cana-1160	80	6	epochs	epoch	NOUN
cana-1160	80	7	(	(	PUNCT
cana-1160	80	8	complete	complete	ADJ
cana-1160	80	9	runs	run	VERB
cana-1160	80	10	through	through	ADP
cana-1160	80	11	the	the	DET
cana-1160	80	12	entire	entire	ADJ
cana-1160	80	13	training	training	NOUN
cana-1160	80	14	dataset	dataset	NOUN
cana-1160	80	15	)	)	PUNCT
cana-1160	80	16	.	.	PUNCT
cana-1160	81	1	the	the	DET
cana-1160	81	2	training	training	NOUN
cana-1160	81	3	process	process	NOUN
cana-1160	81	4	will	will	AUX
cana-1160	81	5	repeat	repeat	VERB
cana-1160	81	6	50	50	NUM
cana-1160	81	7	times	time	NOUN
cana-1160	81	8	over	over	ADP
cana-1160	81	9	the	the	DET
cana-1160	81	10	training	training	NOUN
cana-1160	81	11	dataset	dataset	NOUN
cana-1160	81	12	.	.	PUNCT
cana-1160	82	1	batch_size=32	batch_size=32	PROPN
cana-1160	82	2	:	:	PUNCT
cana-1160	82	3	the	the	DET
cana-1160	82	4	number	number	NOUN
cana-1160	82	5	of	of	ADP
cana-1160	82	6	samples	sample	NOUN
cana-1160	82	7	for	for	ADP
cana-1160	82	8	each	each	DET
cana-1160	82	9	gradient	gradient	NOUN
cana-1160	82	10	update	update	NOUN
cana-1160	82	11	.	.	PUNCT
cana-1160	83	1	the	the	DET
cana-1160	83	2	dataset	dataset	NOUN
cana-1160	83	3	will	will	AUX
cana-1160	83	4	be	be	AUX
cana-1160	83	5	divided	divide	VERB
cana-1160	83	6	into	into	ADP
cana-1160	83	7	32sample	32sample	NUM
cana-1160	83	8	batches	batch	NOUN
cana-1160	83	9	,	,	PUNCT
cana-1160	83	10	with	with	ADP
cana-1160	83	11	model	model	NOUN
cana-1160	83	12	weights	weight	NOUN
cana-1160	83	13	updated	update	VERB
cana-1160	83	14	after	after	ADP
cana-1160	83	15	each	each	DET
cana-1160	83	16	batch	batch	NOUN
cana-1160	83	17	.	.	PUNCT
cana-1160	84	1	validation	validation	NOUN
cana-1160	84	2	data	datum	NOUN
cana-1160	84	3	=	=	SYM
cana-1160	84	4	(	(	PUNCT
cana-1160	84	5	x_test_lnn	x_test_lnn	PROPN
cana-1160	84	6	,	,	PUNCT
cana-1160	84	7	y_test	y_test	NUM
cana-1160	84	8	):	):	PUNCT
cana-1160	84	9	this	this	DET
cana-1160	84	10	tuple	tuple	NOUN
cana-1160	84	11	contains	contain	VERB
cana-1160	84	12	the	the	DET
cana-1160	84	13	validation	validation	NOUN
cana-1160	84	14	dataset	dataset	NOUN
cana-1160	84	15	,	,	PUNCT
cana-1160	84	16	which	which	PRON
cana-1160	84	17	is	be	AUX
cana-1160	84	18	used	use	VERB
cana-1160	84	19	to	to	PART
cana-1160	84	20	assess	assess	VERB
cana-1160	84	21	the	the	DET
cana-1160	84	22	model	model	NOUN
cana-1160	84	23	's	's	PART
cana-1160	84	24	performance	performance	NOUN
cana-1160	84	25	while	while	SCONJ
cana-1160	84	26	training	training	NOUN
cana-1160	84	27	.	.	PUNCT
cana-1160	85	1	x_test_lnn	x_test_lnn	PROPN
cana-1160	85	2	represents	represent	VERB
cana-1160	85	3	the	the	DET
cana-1160	85	4	validation	validation	NOUN
cana-1160	85	5	dataset	dataset	NOUN
cana-1160	85	6	's	's	PART
cana-1160	85	7	input	input	NOUN
cana-1160	85	8	features	feature	NOUN
cana-1160	85	9	.	.	PUNCT
cana-1160	86	1	y_test	y_test	X
cana-1160	86	2	:	:	PUNCT
cana-1160	87	1	these	these	PRON
cana-1160	87	2	are	be	AUX
cana-1160	87	3	the	the	DET
cana-1160	87	4	validation	validation	NOUN
cana-1160	87	5	dataset	dataset	NOUN
cana-1160	87	6	's	's	PART
cana-1160	87	7	target	target	NOUN
cana-1160	87	8	labels	label	NOUN
cana-1160	87	9	.	.	PUNCT
cana-1160	88	1	verbose=1	verbose=1	PROPN
cana-1160	88	2	:	:	PUNCT
cana-1160	88	3	this	this	DET
cana-1160	88	4	parameter	parameter	NOUN
cana-1160	88	5	determines	determine	VERB
cana-1160	88	6	the	the	DET
cana-1160	88	7	verbosity	verbosity	NOUN
cana-1160	88	8	of	of	ADP
cana-1160	88	9	the	the	DET
cana-1160	88	10	training	training	NOUN
cana-1160	88	11	output	output	NOUN
cana-1160	88	12	.	.	PUNCT
cana-1160	89	1	a	a	DET
cana-1160	89	2	value	value	NOUN
cana-1160	89	3	of	of	ADP
cana-1160	89	4	one	one	NUM
cana-1160	89	5	indicates	indicate	VERB
cana-1160	89	6	that	that	SCONJ
cana-1160	89	7	progress	progress	NOUN
cana-1160	89	8	and	and	CCONJ
cana-1160	89	9	loss	loss	NOUN
cana-1160	89	10	data	datum	NOUN
cana-1160	89	11	will	will	AUX
cana-1160	89	12	be	be	AUX
cana-1160	89	13	displayed	display	VERB
cana-1160	89	14	during	during	ADP
cana-1160	89	15	training	training	NOUN
cana-1160	89	16	.	.	PUNCT
cana-1160	90	1	7	7	X
cana-1160	90	2	.	.	X
cana-1160	90	3	expected	expect	VERB
cana-1160	90	4	output	output	NOUN
cana-1160	90	5	epoch	epoch	PROPN
cana-1160	90	6	1/50	1/50	NUM
cana-1160	90	7	37/37	37/37	NUM
cana-1160	90	8	━	━	NUM
cana-1160	90	9	━	━	NUM
cana-1160	90	10	━	━	NUM
cana-1160	90	11	━	━	NUM
cana-1160	90	12	━	━	NUM
cana-1160	90	13	━	━	NUM
cana-1160	90	14	━	━	NUM
cana-1160	90	15	━	━	NUM
cana-1160	90	16	━	━	NUM
cana-1160	90	17	━	━	NUM
cana-1160	90	18	━	━	NUM
cana-1160	90	19	━	━	NUM
cana-1160	90	20	━	━	NUM
cana-1160	90	21	━	━	NUM
cana-1160	90	22	━	━	NUM
cana-1160	90	23	━	━	NUM
cana-1160	90	24	━	━	NUM
cana-1160	90	25	━	━	NUM
cana-1160	90	26	━	━	NUM
cana-1160	90	27	━	━	NOUN
cana-1160	90	28	3s	3s	NUM
cana-1160	90	29	9ms	9ms	NOUN
cana-1160	90	30	/	/	SYM
cana-1160	90	31	step	step	NOUN
cana-1160	90	32	loss	loss	NOUN
cana-1160	90	33	:	:	PUNCT
cana-1160	90	34	0.0440	0.0440	NUM
cana-1160	90	35	val_loss	val_loss	NOUN
cana-1160	90	36	:	:	PUNCT
cana-1160	90	37	0.0057	0.0057	NUM
cana-1160	90	38	epoch	epoch	NOUN
cana-1160	90	39	2/50	2/50	NUM
cana-1160	90	40	37/37	37/37	NUM
cana-1160	90	41	━	━	NUM
cana-1160	90	42	━	━	NUM
cana-1160	90	43	━	━	NUM
cana-1160	90	44	━	━	NUM
cana-1160	90	45	━	━	NUM
cana-1160	90	46	━	━	NUM
cana-1160	90	47	━	━	NUM
cana-1160	90	48	━	━	NUM
cana-1160	90	49	━	━	NUM
cana-1160	90	50	━	━	NUM
cana-1160	90	51	━	━	NUM
cana-1160	90	52	━	━	NUM
cana-1160	90	53	━	━	NUM
cana-1160	90	54	━	━	NUM
cana-1160	90	55	━	━	NUM
cana-1160	90	56	━	━	NUM
cana-1160	90	57	━	━	NUM
cana-1160	90	58	━	━	NUM
cana-1160	90	59	━	━	NUM
cana-1160	90	60	━	━	NOUN
cana-1160	90	61	0s	0s	NOUN
cana-1160	90	62	3ms	3ms	ADJ
cana-1160	90	63	/	/	SYM
cana-1160	90	64	step	step	NOUN
cana-1160	90	65	loss	loss	NOUN
cana-1160	90	66	:	:	PUNCT
cana-1160	90	67	0.0045	0.0045	NUM
cana-1160	90	68	val_loss	val_loss	NOUN
cana-1160	90	69	:	:	PUNCT
cana-1160	90	70	0.0012	0.0012	NUM
cana-1160	90	71	epoch	epoch	NOUN
cana-1160	90	72	3/50	3/50	NUM
cana-1160	90	73	37/37	37/37	NUM
cana-1160	90	74	━	━	NUM
cana-1160	90	75	━	━	NUM
cana-1160	90	76	━	━	NUM
cana-1160	90	77	━	━	NUM
cana-1160	90	78	━	━	NUM
cana-1160	90	79	━	━	NUM
cana-1160	90	80	━	━	NUM
cana-1160	90	81	━	━	NUM
cana-1160	90	82	━	━	NUM
cana-1160	90	83	━	━	NUM
cana-1160	90	84	━	━	NUM
cana-1160	90	85	━	━	NUM
cana-1160	90	86	━	━	NUM
cana-1160	90	87	━	━	NUM
cana-1160	90	88	━	━	NUM
cana-1160	90	89	━	━	NUM
cana-1160	90	90	━	━	NUM
cana-1160	90	91	━	━	NUM
cana-1160	90	92	━	━	NUM
cana-1160	90	93	━	━	NOUN
cana-1160	90	94	0s	0s	NOUN
cana-1160	90	95	3ms	3ms	ADJ
cana-1160	90	96	/	/	SYM
cana-1160	90	97	step	step	NOUN
cana-1160	90	98	loss	loss	NOUN
cana-1160	90	99	:	:	PUNCT
cana-1160	90	100	0.0012	0.0012	NUM
cana-1160	90	101	val_loss	val_loss	NOUN
cana-1160	90	102	:	:	PUNCT
cana-1160	90	103	5.7784e-04	5.7784e-04	NUM
cana-1160	90	104	epoch	epoch	VERB
cana-1160	90	105	4/50	4/50	NUM
cana-1160	90	106	37/37	37/37	NUM
cana-1160	90	107	━	━	NUM
cana-1160	90	108	━	━	NUM
cana-1160	90	109	━	━	NUM
cana-1160	90	110	━	━	NUM
cana-1160	90	111	━	━	NUM
cana-1160	90	112	━	━	NUM
cana-1160	90	113	━	━	NUM
cana-1160	90	114	━	━	NUM
cana-1160	90	115	━	━	NUM
cana-1160	90	116	━	━	NUM
cana-1160	90	117	━	━	NUM
cana-1160	90	118	━	━	NUM
cana-1160	90	119	━	━	NUM
cana-1160	90	120	━	━	NUM
cana-1160	90	121	━	━	NUM
cana-1160	90	122	━	━	NUM
cana-1160	90	123	━	━	NUM
cana-1160	90	124	━	━	NUM
cana-1160	90	125	━	━	NOUN
cana-1160	90	126	0s	0s	NOUN
cana-1160	90	127	3ms	3ms	ADJ
cana-1160	90	128	/	/	SYM
cana-1160	90	129	step	step	NOUN
cana-1160	90	130	loss	loss	NOUN
cana-1160	90	131	:	:	PUNCT
cana-1160	90	132	4.6393e-04	4.6393e-04	NUM
cana-1160	90	133	val_loss	val_loss	NOUN
cana-1160	90	134	:	:	PUNCT
cana-1160	90	135	1.5180e-04	1.5180e-04	NUM
cana-1160	90	136	epoch	epoch	NOUN
cana-1160	90	137	5/50	5/50	NUM
cana-1160	90	138	37/37	37/37	NUM
cana-1160	90	139	━	━	NUM
cana-1160	90	140	━	━	NUM
cana-1160	90	141	━	━	NUM
cana-1160	90	142	━	━	NUM
cana-1160	90	143	━	━	NUM
cana-1160	90	144	━	━	NUM
cana-1160	90	145	━	━	NUM
cana-1160	90	146	━	━	NUM
cana-1160	90	147	━	━	NUM
cana-1160	90	148	━	━	NUM
cana-1160	90	149	━	━	NUM
cana-1160	90	150	━	━	NUM
cana-1160	90	151	━	━	NUM
cana-1160	90	152	━	━	NUM
cana-1160	90	153	━	━	NUM
cana-1160	90	154	━	━	NUM
cana-1160	90	155	━	━	NUM
cana-1160	90	156	━	━	NUM
cana-1160	90	157	━	━	NOUN
cana-1160	90	158	0s	0s	NOUN
cana-1160	90	159	3ms	3ms	ADJ
cana-1160	90	160	/	/	SYM
cana-1160	90	161	step	step	NOUN
cana-1160	90	162	loss	loss	NOUN
cana-1160	90	163	:	:	PUNCT
cana-1160	90	164	1.0113e-04	1.0113e-04	NUM
cana-1160	90	165	val_loss	val_loss	NOUN
cana-1160	90	166	:	:	PUNCT
cana-1160	90	167	3.0498e-04	3.0498e-04	NUM
cana-1160	90	168	epoch	epoch	NOUN
cana-1160	90	169	6/50	6/50	NUM
cana-1160	90	170	37/37	37/37	NUM
cana-1160	90	171	━	━	NUM
cana-1160	90	172	━	━	NUM
cana-1160	90	173	━	━	NUM
cana-1160	90	174	━	━	NUM
cana-1160	90	175	━	━	NUM
cana-1160	90	176	━	━	NUM
cana-1160	90	177	━	━	NUM
cana-1160	90	178	━	━	NUM
cana-1160	90	179	━	━	NUM
cana-1160	90	180	━	━	NUM
cana-1160	90	181	━	━	NUM
cana-1160	90	182	━	━	NUM
cana-1160	90	183	━	━	NUM
cana-1160	90	184	━	━	NUM
cana-1160	90	185	━	━	NUM
cana-1160	90	186	━	━	NUM
cana-1160	90	187	━	━	NUM
cana-1160	90	188	━	━	NUM
cana-1160	90	189	━	━	NOUN
cana-1160	90	190	0s	0s	NOUN
cana-1160	90	191	3ms	3ms	ADJ
cana-1160	90	192	/	/	SYM
cana-1160	90	193	step	step	NOUN
cana-1160	90	194	loss	loss	NOUN
cana-1160	90	195	:	:	PUNCT
cana-1160	90	196	2.4630e-04	2.4630e-04	NUM
cana-1160	90	197	val_loss	val_loss	NOUN
cana-1160	90	198	:	:	PUNCT
cana-1160	90	199	4.8291e-05	4.8291e-05	NUM
cana-1160	90	200	epoch	epoch	NOUN
cana-1160	90	201	7/50	7/50	NUM
cana-1160	90	202	37/37	37/37	NUM
cana-1160	90	203	━	━	NUM
cana-1160	90	204	━	━	NUM
cana-1160	90	205	━	━	NUM
cana-1160	90	206	━	━	NUM
cana-1160	90	207	━	━	NUM
cana-1160	90	208	━	━	NUM
cana-1160	90	209	━	━	NUM
cana-1160	90	210	━	━	NUM
cana-1160	90	211	━	━	NUM
cana-1160	90	212	━	━	NUM
cana-1160	90	213	━	━	NUM
cana-1160	90	214	━	━	NUM
cana-1160	90	215	━	━	NUM
cana-1160	90	216	━	━	NUM
cana-1160	90	217	━	━	NUM
cana-1160	90	218	━	━	NUM
cana-1160	90	219	━	━	NUM
cana-1160	90	220	━	━	NUM
cana-1160	90	221	━	━	NOUN
cana-1160	90	222	0s	0s	NOUN
cana-1160	90	223	3ms	3ms	ADJ
cana-1160	90	224	/	/	SYM
cana-1160	90	225	step	step	NOUN
cana-1160	90	226	loss	loss	NOUN
cana-1160	90	227	:	:	PUNCT
cana-1160	90	228	3.8744e-05	3.8744e-05	NUM
cana-1160	90	229	val_loss	val_loss	NOUN
cana-1160	90	230	:	:	PUNCT
cana-1160	90	231	.	.	PUNCT
cana-1160	90	232	.	.	PUNCT
cana-1160	90	233	.	.	PUNCT
cana-1160	91	1	communications	communication	NOUN
cana-1160	91	2	on	on	ADP
cana-1160	91	3	applied	apply	VERB
cana-1160	91	4	nonlinear	nonlinear	ADJ
cana-1160	91	5	analysis	analysis	NOUN
cana-1160	91	6	issn	issn	NOUN
cana-1160	91	7	:	:	PUNCT
cana-1160	91	8	1074	1074	NUM
cana-1160	91	9	-	-	PUNCT
cana-1160	91	10	133x	133x	NUM
cana-1160	91	11	vol	vol	NOUN
cana-1160	91	12	31	31	NUM
cana-1160	91	13	no	no	NOUN
cana-1160	91	14	.	.	PUNCT
cana-1160	92	1	6s	6s	NUM
cana-1160	92	2	(	(	PUNCT
cana-1160	92	3	2024	2024	NUM
cana-1160	92	4	)	)	PUNCT
cana-1160	92	5	79	79	NUM
cana-1160	92	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1160	93	1	the	the	DET
cana-1160	93	2	training	training	NOUN
cana-1160	93	3	process	process	NOUN
cana-1160	93	4	involves	involve	VERB
cana-1160	93	5	going	go	VERB
cana-1160	93	6	through	through	ADP
cana-1160	93	7	the	the	DET
cana-1160	93	8	entire	entire	ADJ
cana-1160	93	9	dataset	dataset	NOUN
cana-1160	93	10	50	50	NUM
cana-1160	93	11	times	time	NOUN
cana-1160	93	12	.	.	PUNCT
cana-1160	94	1	during	during	ADP
cana-1160	94	2	each	each	DET
cana-1160	94	3	epoch	epoch	NOUN
cana-1160	94	4	,	,	PUNCT
cana-1160	94	5	the	the	DET
cana-1160	94	6	model	model	NOUN
cana-1160	94	7	will	will	AUX
cana-1160	94	8	view	view	VERB
cana-1160	94	9	all	all	DET
cana-1160	94	10	training	training	NOUN
cana-1160	94	11	samples	sample	NOUN
cana-1160	94	12	once	once	ADV
cana-1160	94	13	.	.	PUNCT
cana-1160	95	1	batches	batch	NOUN
cana-1160	95	2	:	:	PUNCT
cana-1160	95	3	rather	rather	ADV
cana-1160	95	4	than	than	ADP
cana-1160	95	5	feeding	feed	VERB
cana-1160	95	6	the	the	DET
cana-1160	95	7	entire	entire	ADJ
cana-1160	95	8	dataset	dataset	NOUN
cana-1160	95	9	at	at	ADP
cana-1160	95	10	once	once	ADV
cana-1160	95	11	,	,	PUNCT
cana-1160	95	12	the	the	DET
cana-1160	95	13	data	data	NOUN
cana-1160	95	14	is	be	AUX
cana-1160	95	15	split	split	VERB
cana-1160	95	16	into	into	ADP
cana-1160	95	17	smaller	small	ADJ
cana-1160	95	18	batches	batch	NOUN
cana-1160	95	19	of	of	ADP
cana-1160	95	20	32	32	NUM
cana-1160	95	21	samples	sample	NOUN
cana-1160	95	22	.	.	PUNCT
cana-1160	96	1	this	this	PRON
cana-1160	96	2	allows	allow	VERB
cana-1160	96	3	for	for	ADP
cana-1160	96	4	more	more	ADV
cana-1160	96	5	efficient	efficient	ADJ
cana-1160	96	6	training	training	NOUN
cana-1160	96	7	and	and	CCONJ
cana-1160	96	8	better	well	ADJ
cana-1160	96	9	memory	memory	NOUN
cana-1160	96	10	utilisation	utilisation	NOUN
cana-1160	96	11	.	.	PUNCT
cana-1160	97	1	forward	forward	ADV
cana-1160	97	2	and	and	CCONJ
cana-1160	97	3	backward	backward	ADJ
cana-1160	97	4	passes	pass	NOUN
cana-1160	97	5	:	:	PUNCT
cana-1160	97	6	in	in	ADP
cana-1160	97	7	each	each	DET
cana-1160	97	8	batch	batch	NOUN
cana-1160	97	9	,	,	PUNCT
cana-1160	97	10	the	the	DET
cana-1160	97	11	model	model	NOUN
cana-1160	97	12	makes	make	VERB
cana-1160	97	13	predictions	prediction	NOUN
cana-1160	97	14	(	(	PUNCT
cana-1160	97	15	forward	forward	ADV
cana-1160	97	16	pass	pass	VERB
cana-1160	97	17	)	)	PUNCT
cana-1160	97	18	and	and	CCONJ
cana-1160	97	19	computes	compute	VERB
cana-1160	97	20	the	the	DET
cana-1160	97	21	difference	difference	NOUN
cana-1160	97	22	between	between	ADP
cana-1160	97	23	the	the	DET
cana-1160	97	24	predicted	predict	VERB
cana-1160	97	25	and	and	CCONJ
cana-1160	97	26	actual	actual	ADJ
cana-1160	97	27	target	target	NOUN
cana-1160	97	28	values	value	NOUN
cana-1160	97	29	.	.	PUNCT
cana-1160	98	1	this	this	DET
cana-1160	98	2	error	error	NOUN
cana-1160	98	3	is	be	AUX
cana-1160	98	4	then	then	ADV
cana-1160	98	5	used	use	VERB
cana-1160	98	6	to	to	PART
cana-1160	98	7	update	update	VERB
cana-1160	98	8	the	the	DET
cana-1160	98	9	model	model	NOUN
cana-1160	98	10	weights	weight	NOUN
cana-1160	98	11	(	(	PUNCT
cana-1160	98	12	backward	backward	ADJ
cana-1160	98	13	pass	pass	NOUN
cana-1160	98	14	)	)	PUNCT
cana-1160	98	15	to	to	PART
cana-1160	98	16	reduce	reduce	VERB
cana-1160	98	17	the	the	DET
cana-1160	98	18	error	error	NOUN
cana-1160	98	19	.	.	PUNCT
cana-1160	99	1	validation	validation	NOUN
cana-1160	99	2	:	:	PUNCT
cana-1160	99	3	after	after	ADP
cana-1160	99	4	each	each	DET
cana-1160	99	5	epoch	epoch	NOUN
cana-1160	99	6	,	,	PUNCT
cana-1160	99	7	the	the	DET
cana-1160	99	8	model	model	NOUN
cana-1160	99	9	's	's	PART
cana-1160	99	10	performance	performance	NOUN
cana-1160	99	11	is	be	AUX
cana-1160	99	12	assessed	assess	VERB
cana-1160	99	13	using	use	VERB
cana-1160	99	14	the	the	DET
cana-1160	99	15	validation	validation	NOUN
cana-1160	99	16	dataset	dataset	NOUN
cana-1160	99	17	.	.	PUNCT
cana-1160	100	1	this	this	DET
cana-1160	100	2	aids	aid	NOUN
cana-1160	100	3	in	in	ADP
cana-1160	100	4	monitoring	monitor	VERB
cana-1160	100	5	the	the	DET
cana-1160	100	6	model	model	NOUN
cana-1160	100	7	's	's	PART
cana-1160	100	8	performance	performance	NOUN
cana-1160	100	9	on	on	ADP
cana-1160	100	10	new	new	ADJ
cana-1160	100	11	data	datum	NOUN
cana-1160	100	12	and	and	CCONJ
cana-1160	100	13	detecting	detect	VERB
cana-1160	100	14	overfitting	overfitting	NOUN
cana-1160	100	15	.	.	PUNCT
cana-1160	101	1	no	no	INTJ
cana-1160	101	2	.	.	PUNCT
cana-1160	102	1	actual	actual	ADJ
cana-1160	102	2	predicted	predict	VERB
cana-1160	102	3	0	0	NUM
cana-1160	102	4	1.356890	1.356890	NUM
cana-1160	102	5	1.362671	1.362671	NUM
cana-1160	102	6	1	1	NUM
cana-1160	102	7	0.226467	0.226467	NUM
cana-1160	102	8	0.240507	0.240507	NUM
cana-1160	102	9	2	2	NUM
cana-1160	102	10	1.102835	1.102835	NUM
cana-1160	102	11	1.084788	1.084788	NUM
cana-1160	102	12	3	3	NUM
cana-1160	102	13	1.518482	1.518482	NUM
cana-1160	102	14	1.503372	1.503372	NUM
cana-1160	102	15	4	4	NUM
cana-1160	102	16	2.161842	2.161842	NUM
cana-1160	102	17	2.149723	2.149723	NUM
cana-1160	102	18	5	5	NUM
cana-1160	102	19	1.213460	1.213460	NUM
cana-1160	102	20	1.187006	1.187006	NUM
cana-1160	102	21	6	6	NUM
cana-1160	102	22	0.764788	0.764788	NUM
cana-1160	102	23	0.746628	0.746628	NUM
cana-1160	102	24	7	7	NUM
cana-1160	102	25	1.126901	1.126901	NUM
cana-1160	102	26	1.110468	1.110468	NUM
cana-1160	102	27	8	8	NUM
cana-1160	102	28	1.172124	1.172124	NUM
cana-1160	102	29	1.145189	1.145189	NUM
cana-1160	102	30	9	9	NUM
cana-1160	102	31	0.795132	0.795132	NUM
cana-1160	102	32	0.780315	0.780315	NUM
cana-1160	102	33	table:1	table:1	NOUN
cana-1160	102	34	actual	actual	ADJ
cana-1160	102	35	vs.	vs.	CCONJ
cana-1160	102	36	predicted	predict	VERB
cana-1160	102	37	the	the	DET
cana-1160	102	38	create_lnn	create_lnn	NOUN
cana-1160	102	39	(	(	PUNCT
cana-1160	102	40	)	)	PUNCT
cana-1160	102	41	function	function	NOUN
cana-1160	102	42	to	to	PART
cana-1160	102	43	generate	generate	VERB
cana-1160	102	44	a	a	DET
cana-1160	102	45	liquid	liquid	ADJ
cana-1160	102	46	neural	neural	ADJ
cana-1160	102	47	network	network	NOUN
cana-1160	102	48	model	model	NOUN
cana-1160	102	49	,	,	PUNCT
cana-1160	102	50	which	which	PRON
cana-1160	102	51	is	be	AUX
cana-1160	102	52	then	then	ADV
cana-1160	102	53	trained	train	VERB
cana-1160	102	54	using	use	VERB
cana-1160	102	55	the	the	DET
cana-1160	102	56	fit	fit	NOUN
cana-1160	102	57	(	(	PUNCT
cana-1160	102	58	)	)	PUNCT
cana-1160	102	59	method	method	NOUN
cana-1160	102	60	with	with	ADP
cana-1160	102	61	epoch	epoch	NOUN
cana-1160	102	62	,	,	PUNCT
cana-1160	102	63	batch	batch	NOUN
cana-1160	102	64	size	size	NOUN
cana-1160	102	65	,	,	PUNCT
cana-1160	102	66	and	and	CCONJ
cana-1160	102	67	validation	validation	NOUN
cana-1160	102	68	data	datum	NOUN
cana-1160	102	69	parameters	parameter	NOUN
cana-1160	102	70	.	.	PUNCT
cana-1160	103	1	the	the	DET
cana-1160	103	2	training	training	NOUN
cana-1160	103	3	process	process	NOUN
cana-1160	103	4	consists	consist	VERB
cana-1160	103	5	of	of	ADP
cana-1160	103	6	iterating	iterate	VERB
cana-1160	103	7	over	over	ADP
cana-1160	103	8	the	the	DET
cana-1160	103	9	dataset	dataset	NOUN
cana-1160	103	10	,	,	PUNCT
cana-1160	103	11	updating	update	VERB
cana-1160	103	12	model	model	NOUN
cana-1160	103	13	weights	weight	NOUN
cana-1160	103	14	,	,	PUNCT
cana-1160	103	15	and	and	CCONJ
cana-1160	103	16	evaluating	evaluate	VERB
cana-1160	103	17	performance	performance	NOUN
cana-1160	103	18	on	on	ADP
cana-1160	103	19	the	the	DET
cana-1160	103	20	validation	validation	NOUN
cana-1160	103	21	set	set	NOUN
cana-1160	103	22	,	,	PUNCT
cana-1160	103	23	with	with	ADP
cana-1160	103	24	progress	progress	NOUN
cana-1160	103	25	displayed	display	VERB
cana-1160	103	26	thanks	thank	NOUN
cana-1160	103	27	to	to	ADP
cana-1160	103	28	the	the	DET
cana-1160	103	29	verbose=1	verbose=1	PROPN
cana-1160	103	30	setting	setting	NOUN
cana-1160	103	31	.	.	PUNCT
cana-1160	104	1	lnns	lnns	ADJ
cana-1160	104	2	require	require	VERB
cana-1160	104	3	less	less	ADV
cana-1160	104	4	computational	computational	ADJ
cana-1160	104	5	power	power	NOUN
cana-1160	104	6	compared	compare	VERB
cana-1160	104	7	to	to	ADP
cana-1160	104	8	dnns	dnn	NOUN
cana-1160	104	9	,	,	PUNCT
cana-1160	104	10	making	make	VERB
cana-1160	104	11	them	they	PRON
cana-1160	104	12	more	more	ADV
cana-1160	104	13	suitable	suitable	ADJ
cana-1160	104	14	for	for	ADP
cana-1160	104	15	real	real	ADJ
cana-1160	104	16	-	-	PUNCT
cana-1160	104	17	time	time	NOUN
cana-1160	104	18	applications.[6	applications.[6	NOUN
cana-1160	104	19	]	]	PUNCT
cana-1160	104	20	fig:3	fig:3	PART
cana-1160	104	21	energy	energy	NOUN
cana-1160	104	22	consumption	consumption	NOUN
cana-1160	104	23	prediction	prediction	NOUN
cana-1160	104	24	8	8	NUM
cana-1160	104	25	.	.	PUNCT
cana-1160	105	1	conclusion	conclusion	VERB
cana-1160	105	2	the	the	DET
cana-1160	105	3	combination	combination	NOUN
cana-1160	105	4	of	of	ADP
cana-1160	105	5	liquid	liquid	ADJ
cana-1160	105	6	neural	neural	ADJ
cana-1160	105	7	networks	network	NOUN
cana-1160	105	8	and	and	CCONJ
cana-1160	105	9	kolmogorov	kolmogorov	PROPN
cana-1160	105	10	-	-	PUNCT
cana-1160	105	11	arnold	arnold	PROPN
cana-1160	105	12	networks	network	NOUN
cana-1160	105	13	is	be	AUX
cana-1160	105	14	a	a	DET
cana-1160	105	15	promising	promising	ADJ
cana-1160	105	16	approach	approach	NOUN
cana-1160	105	17	that	that	PRON
cana-1160	105	18	has	have	VERB
cana-1160	105	19	the	the	DET
cana-1160	105	20	potential	potential	NOUN
cana-1160	105	21	to	to	PART
cana-1160	105	22	significantly	significantly	ADV
cana-1160	105	23	improve	improve	VERB
cana-1160	105	24	neural	neural	ADJ
cana-1160	105	25	network	network	NOUN
cana-1160	105	26	performance	performance	NOUN
cana-1160	105	27	,	,	PUNCT
cana-1160	105	28	especially	especially	ADV
cana-1160	105	29	for	for	ADP
cana-1160	105	30	tasks	task	NOUN
cana-1160	105	31	involving	involve	VERB
cana-1160	105	32	complex	complex	ADJ
cana-1160	105	33	,	,	PUNCT
cana-1160	105	34	time	time	NOUN
cana-1160	105	35	-	-	PUNCT
cana-1160	105	36	varying	vary	VERB
cana-1160	105	37	data	datum	NOUN
cana-1160	105	38	.	.	PUNCT
cana-1160	106	1	this	this	DET
cana-1160	106	2	methodology	methodology	NOUN
cana-1160	106	3	describes	describe	VERB
cana-1160	106	4	a	a	DET
cana-1160	106	5	comprehensive	comprehensive	ADJ
cana-1160	106	6	approach	approach	NOUN
cana-1160	106	7	to	to	ADP
cana-1160	106	8	developing	develop	VERB
cana-1160	106	9	a	a	DET
cana-1160	106	10	reliable	reliable	ADJ
cana-1160	106	11	energy	energy	NOUN
cana-1160	106	12	prediction	prediction	NOUN
cana-1160	106	13	model	model	NOUN
cana-1160	106	14	for	for	ADP
cana-1160	106	15	smart	smart	ADJ
cana-1160	106	16	grids	grid	NOUN
cana-1160	106	17	that	that	PRON
cana-1160	106	18	incorporates	incorporate	VERB
cana-1160	106	19	kolmogorov	kolmogorov	PROPN
cana-1160	106	20	-	-	PUNCT
cana-1160	106	21	arnold	arnold	PROPN
cana-1160	106	22	networks	network	NOUN
cana-1160	106	23	(	(	PUNCT
cana-1160	106	24	kans	kans	PROPN
cana-1160	106	25	)	)	PUNCT
cana-1160	106	26	and	and	CCONJ
cana-1160	106	27	liquid	liquid	ADJ
cana-1160	106	28	neural	neural	ADJ
cana-1160	106	29	networks	network	NOUN
cana-1160	106	30	(	(	PUNCT
cana-1160	106	31	lnns	lnns	ADJ
cana-1160	106	32	)	)	PUNCT
cana-1160	106	33	.	.	PUNCT
cana-1160	107	1	the	the	DET
cana-1160	107	2	steps	step	NOUN
cana-1160	107	3	ensure	ensure	VERB
cana-1160	107	4	comprehensive	comprehensive	ADJ
cana-1160	107	5	data	datum	NOUN
cana-1160	107	6	preprocessing	preprocessing	NOUN
cana-1160	107	7	,	,	PUNCT
cana-1160	107	8	model	model	NOUN
cana-1160	107	9	training	training	NOUN
cana-1160	107	10	,	,	PUNCT
cana-1160	107	11	and	and	CCONJ
cana-1160	107	12	performance	performance	NOUN
cana-1160	107	13	evaluation	evaluation	NOUN
cana-1160	107	14	,	,	PUNCT
cana-1160	107	15	leveraging	leverage	VERB
cana-1160	107	16	the	the	DET
cana-1160	107	17	strengths	strength	NOUN
cana-1160	107	18	of	of	ADP
cana-1160	107	19	both	both	CCONJ
cana-1160	107	20	neural	neural	ADJ
cana-1160	107	21	communications	communication	NOUN
cana-1160	107	22	on	on	ADP
cana-1160	107	23	applied	apply	VERB
cana-1160	107	24	nonlinear	nonlinear	ADJ
cana-1160	107	25	analysis	analysis	NOUN
cana-1160	107	26	issn	issn	NOUN
cana-1160	107	27	:	:	PUNCT
cana-1160	107	28	1074	1074	NUM
cana-1160	107	29	-	-	PUNCT
cana-1160	107	30	133x	133x	NUM
cana-1160	107	31	vol	vol	NOUN
cana-1160	107	32	31	31	NUM
cana-1160	107	33	no	no	NOUN
cana-1160	107	34	.	.	PUNCT
cana-1160	108	1	6s	6s	NUM
cana-1160	108	2	(	(	PUNCT
cana-1160	108	3	2024	2024	NUM
cana-1160	108	4	)	)	PUNCT
cana-1160	108	5	80	80	NUM
cana-1160	108	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-1160	108	7	network	network	NOUN
cana-1160	108	8	architectures	architecture	NOUN
cana-1160	108	9	to	to	PART
cana-1160	108	10	improve	improve	VERB
cana-1160	108	11	prediction	prediction	NOUN
cana-1160	108	12	accuracy	accuracy	NOUN
cana-1160	108	13	and	and	CCONJ
cana-1160	108	14	adaptability	adaptability	NOUN
cana-1160	108	15	to	to	ADP
cana-1160	108	16	real	real	ADJ
cana-1160	108	17	-	-	PUNCT
cana-1160	108	18	world	world	NOUN
cana-1160	108	19	energy	energy	NOUN
cana-1160	108	20	consumption	consumption	NOUN
cana-1160	108	21	patterns	pattern	NOUN
cana-1160	108	22	.	.	PUNCT
cana-1160	109	1	finally	finally	ADV
cana-1160	109	2	,	,	PUNCT
cana-1160	109	3	kans	kan	NOUN
cana-1160	109	4	and	and	CCONJ
cana-1160	109	5	lnns	lnns	PROPN
cana-1160	109	6	each	each	PRON
cana-1160	109	7	bring	bring	VERB
cana-1160	109	8	distinct	distinct	ADJ
cana-1160	109	9	advantages	advantage	NOUN
cana-1160	109	10	to	to	ADP
cana-1160	109	11	the	the	DET
cana-1160	109	12	table	table	NOUN
cana-1160	109	13	.	.	PUNCT
cana-1160	110	1	researchers	researcher	NOUN
cana-1160	110	2	and	and	CCONJ
cana-1160	110	3	practitioners	practitioner	NOUN
cana-1160	110	4	can	can	AUX
cana-1160	110	5	create	create	VERB
cana-1160	110	6	powerful	powerful	ADJ
cana-1160	110	7	models	model	NOUN
cana-1160	110	8	capable	capable	ADJ
cana-1160	110	9	of	of	ADP
cana-1160	110	10	tackling	tackle	VERB
cana-1160	110	11	complex	complex	ADJ
cana-1160	110	12	,	,	PUNCT
cana-1160	110	13	real	real	ADJ
cana-1160	110	14	-	-	PUNCT
cana-1160	110	15	world	world	NOUN
cana-1160	110	16	predictive	predictive	ADJ
cana-1160	110	17	tasks	task	NOUN
cana-1160	110	18	by	by	ADP
cana-1160	110	19	combining	combine	VERB
cana-1160	110	20	kans	kan	NOUN
cana-1160	110	21	'	'	PART
cana-1160	110	22	ability	ability	NOUN
cana-1160	110	23	to	to	PART
cana-1160	110	24	handle	handle	VERB
cana-1160	110	25	high	high	ADJ
cana-1160	110	26	-	-	PUNCT
cana-1160	110	27	dimensional	dimensional	ADJ
cana-1160	110	28	data	datum	NOUN
cana-1160	110	29	with	with	ADP
cana-1160	110	30	lnns	lnns	ADJ
cana-1160	110	31	'	'	PART
cana-1160	110	32	temporal	temporal	ADJ
cana-1160	110	33	sensitivity	sensitivity	NOUN
cana-1160	110	34	and	and	CCONJ
cana-1160	110	35	dynamic	dynamic	ADJ
cana-1160	110	36	adaptation	adaptation	NOUN
cana-1160	110	37	.	.	PUNCT
cana-1160	111	1	references	reference	NOUN
cana-1160	111	2	[	[	X
cana-1160	111	3	1	1	X
cana-1160	111	4	]	]	PUNCT
cana-1160	111	5	“	"	PUNCT
cana-1160	111	6	efficient	efficient	ADJ
cana-1160	111	7	liquid	liquid	ADJ
cana-1160	111	8	neural	neural	ADJ
cana-1160	111	9	networks	network	NOUN
cana-1160	111	10	for	for	ADP
cana-1160	111	11	energy	energy	NOUN
cana-1160	111	12	prediction	prediction	NOUN
cana-1160	111	13	”	"	PUNCT
cana-1160	111	14	,	,	PUNCT
cana-1160	111	15	y.	y.	PROPN
cana-1160	111	16	zhang	zhang	PROPN
cana-1160	111	17	,	,	PUNCT
cana-1160	111	18	m.	m.	PROPN
cana-1160	111	19	tegmark	tegmark	PROPN
cana-1160	111	20	journal	journal	PROPN
cana-1160	111	21	of	of	ADP
cana-1160	111	22	neural	neural	ADJ
cana-1160	111	23	networks	network	NOUN
cana-1160	111	24	2023	2023	NUM
cana-1160	111	25	.	.	PUNCT
cana-1160	112	1	[	[	X
cana-1160	112	2	2	2	X
cana-1160	112	3	]	]	PUNCT
cana-1160	112	4	“	"	PUNCT
cana-1160	112	5	scalable	scalable	ADJ
cana-1160	112	6	kolmogorov	kolmogorov	ADJ
cana-1160	112	7	-	-	PUNCT
cana-1160	112	8	arnold	arnold	PROPN
cana-1160	112	9	networks	network	NOUN
cana-1160	112	10	for	for	ADP
cana-1160	112	11	high	high	ADJ
cana-1160	112	12	-	-	PUNCT
cana-1160	112	13	dimensional	dimensional	ADJ
cana-1160	112	14	data	datum	NOUN
cana-1160	112	15	”	"	PUNCT
cana-1160	112	16	,	,	PUNCT
cana-1160	112	17	a.	a.	PROPN
cana-1160	112	18	smith	smith	PROPN
cana-1160	112	19	,	,	PUNCT
cana-1160	112	20	b.	b.	PROPN
cana-1160	112	21	jones	jones	PROPN
cana-1160	112	22	,	,	PUNCT
cana-1160	112	23	machine	machine	NOUN
cana-1160	112	24	learning	learning	NOUN
cana-1160	112	25	review	review	NOUN
cana-1160	112	26	,	,	PUNCT
cana-1160	112	27	2021	2021	NUM
cana-1160	112	28	.	.	PUNCT
cana-1160	113	1	[	[	X
cana-1160	113	2	3	3	X
cana-1160	113	3	]	]	PUNCT
cana-1160	113	4	“	"	PUNCT
cana-1160	113	5	hybrid	hybrid	ADJ
cana-1160	113	6	approaches	approach	NOUN
cana-1160	113	7	to	to	ADP
cana-1160	113	8	smart	smart	ADJ
cana-1160	113	9	grid	grid	NOUN
cana-1160	113	10	energy	energy	NOUN
cana-1160	113	11	forecasting	forecasting	NOUN
cana-1160	113	12	,	,	PUNCT
cana-1160	113	13	r.	r.	PROPN
cana-1160	113	14	gupta	gupta	PROPN
cana-1160	113	15	,	,	PUNCT
cana-1160	113	16	l.	l.	PROPN
cana-1160	113	17	brown	brown	PROPN
cana-1160	113	18	,	,	PUNCT
cana-1160	113	19	energy	energy	NOUN
cana-1160	113	20	informatics	informatic	NOUN
cana-1160	113	21	”	"	PUNCT
cana-1160	113	22	,	,	PUNCT
cana-1160	113	23	2022	2022	NUM
cana-1160	113	24	.	.	PUNCT
cana-1160	114	1	[	[	X
cana-1160	114	2	4	4	X
cana-1160	114	3	]	]	PUNCT
cana-1160	114	4	“	"	PUNCT
cana-1160	114	5	improving	improve	VERB
cana-1160	114	6	stability	stability	NOUN
cana-1160	114	7	in	in	ADP
cana-1160	114	8	liquid	liquid	ADJ
cana-1160	114	9	neural	neural	ADJ
cana-1160	114	10	networks	network	NOUN
cana-1160	114	11	,	,	PUNCT
cana-1160	114	12	d.	d.	PROPN
cana-1160	114	13	lee	lee	PROPN
cana-1160	114	14	,	,	PUNCT
cana-1160	114	15	p.	p.	PROPN
cana-1160	114	16	wong	wong	PROPN
cana-1160	114	17	,	,	PUNCT
cana-1160	114	18	advances	advance	NOUN
cana-1160	114	19	in	in	ADP
cana-1160	114	20	neural	neural	ADJ
cana-1160	114	21	information	information	NOUN
cana-1160	114	22	processing	processing	NOUN
cana-1160	114	23	systems”,2020	systems”,2020	NOUN
cana-1160	114	24	.	.	PUNCT
cana-1160	115	1	[	[	X
cana-1160	115	2	5	5	NUM
cana-1160	115	3	]	]	PUNCT
cana-1160	115	4	“	"	PUNCT
cana-1160	115	5	applying	apply	VERB
cana-1160	115	6	kans	kan	NOUN
cana-1160	115	7	to	to	ADP
cana-1160	115	8	image	image	NOUN
cana-1160	115	9	recognition	recognition	NOUN
cana-1160	115	10	”	"	PUNCT
cana-1160	115	11	,	,	PUNCT
cana-1160	115	12	tasks	task	NOUN
cana-1160	115	13	,	,	PUNCT
cana-1160	115	14	m.	m.	NOUN
cana-1160	115	15	white	white	PROPN
cana-1160	115	16	,	,	PUNCT
cana-1160	115	17	s.	s.	PROPN
cana-1160	115	18	green	green	PROPN
cana-1160	115	19	,	,	PUNCT
cana-1160	115	20	computer	computer	NOUN
cana-1160	115	21	vision	vision	NOUN
cana-1160	115	22	journal	journal	NOUN
cana-1160	115	23	,	,	PUNCT
cana-1160	115	24	2023	2023	NUM
cana-1160	115	25	.	.	PUNCT
cana-1160	116	1	[	[	X
cana-1160	116	2	6	6	NUM
cana-1160	116	3	]	]	PUNCT
cana-1160	116	4	“	"	PUNCT
cana-1160	116	5	liquid	liquid	ADJ
cana-1160	116	6	neural	neural	ADJ
cana-1160	116	7	networks	network	NOUN
cana-1160	116	8	for	for	ADP
cana-1160	116	9	real	real	ADJ
cana-1160	116	10	-	-	PUNCT
cana-1160	116	11	time	time	NOUN
cana-1160	116	12	anomaly	anomaly	NOUN
cana-1160	116	13	detection	detection	NOUN
cana-1160	116	14	”	"	PUNCT
cana-1160	116	15	,	,	PUNCT
cana-1160	116	16	k.	k.	PROPN
cana-1160	116	17	patel	patel	PROPN
cana-1160	116	18	,	,	PUNCT
cana-1160	116	19	j.	j.	PROPN
cana-1160	116	20	singh	singh	PROPN
cana-1160	116	21	,	,	PUNCT
cana-1160	116	22	ieee	ieee	NOUN
cana-1160	116	23	transactions	transaction	NOUN
cana-1160	116	24	on	on	ADP
cana-1160	116	25	neural	neural	ADJ
cana-1160	116	26	networks	network	NOUN
cana-1160	116	27	,	,	PUNCT
cana-1160	116	28	2021	2021	NUM
cana-1160	116	29	.	.	PUNCT
cana-1160	117	1	[	[	X
cana-1160	117	2	7	7	X
cana-1160	117	3	]	]	PUNCT
cana-1160	117	4	“	"	PUNCT
cana-1160	117	5	enhancing	enhance	VERB
cana-1160	117	6	smart	smart	ADJ
cana-1160	117	7	grids	grid	NOUN
cana-1160	117	8	with	with	ADP
cana-1160	117	9	kolmogorov	kolmogorov	PROPN
cana-1160	117	10	-	-	PUNCT
cana-1160	117	11	arnold	arnold	PROPN
cana-1160	117	12	networks”,t	networks”,t	PROPN
cana-1160	117	13	.	.	PUNCT
cana-1160	117	14	miller	miller	PROPN
cana-1160	117	15	,	,	PUNCT
cana-1160	117	16	h.	h.	PROPN
cana-1160	117	17	adams	adams	PROPN
cana-1160	117	18	,	,	PUNCT
cana-1160	117	19	smart	smart	ADJ
cana-1160	117	20	grid	grid	NOUN
cana-1160	117	21	technology	technology	NOUN
cana-1160	117	22	journal	journal	NOUN
cana-1160	117	23	,	,	PUNCT
cana-1160	117	24	2022	2022	NUM
cana-1160	117	25	.	.	PUNCT
cana-1160	118	1	[	[	X
cana-1160	118	2	8	8	NUM
cana-1160	118	3	]	]	PUNCT
cana-1160	118	4	“	"	PUNCT
cana-1160	118	5	liquid	liquid	ADJ
cana-1160	118	6	neural	neural	ADJ
cana-1160	118	7	networks	network	NOUN
cana-1160	118	8	:	:	PUNCT
cana-1160	118	9	a	a	DET
cana-1160	118	10	new	new	ADJ
cana-1160	118	11	paradigm	paradigm	NOUN
cana-1160	118	12	for	for	ADP
cana-1160	118	13	ai	ai	NOUN
cana-1160	118	14	”	"	PUNCT
cana-1160	118	15	,	,	PUNCT
cana-1160	118	16	s.	s.	PROPN
cana-1160	118	17	kim	kim	PROPN
cana-1160	118	18	,	,	PUNCT
cana-1160	118	19	a.	a.	NOUN
cana-1160	118	20	park	park	NOUN
cana-1160	118	21	,	,	PUNCT
cana-1160	118	22	ai	ai	VERB
cana-1160	118	23	research	research	NOUN
cana-1160	118	24	journal	journal	NOUN
cana-1160	118	25	,	,	PUNCT
cana-1160	118	26	2024	2024	NUM
cana-1160	118	27	.	.	PUNCT
cana-1160	119	1	[	[	X
cana-1160	119	2	9	9	NUM
cana-1160	119	3	]	]	PUNCT
cana-1160	119	4	“	"	PUNCT
cana-1160	119	5	kolmogorov	kolmogorov	PROPN
cana-1160	119	6	-	-	PUNCT
cana-1160	119	7	arnold	arnold	PROPN
cana-1160	119	8	networks	network	NOUN
cana-1160	119	9	for	for	ADP
cana-1160	119	10	predictive	predictive	ADJ
cana-1160	119	11	maintenance	maintenance	NOUN
cana-1160	119	12	”	"	PUNCT
cana-1160	119	13	,	,	PUNCT
cana-1160	119	14	m.	m.	PROPN
cana-1160	119	15	johnson	johnson	PROPN
cana-1160	119	16	,	,	PUNCT
cana-1160	119	17	r.	r.	PROPN
cana-1160	119	18	kumar	kumar	PROPN
cana-1160	119	19	,	,	PUNCT
cana-1160	119	20	:	:	PUNCT
cana-1160	119	21	industrial	industrial	ADJ
cana-1160	119	22	ai	ai	PROPN
cana-1160	119	23	journal	journal	PROPN
cana-1160	119	24	,	,	PUNCT
cana-1160	119	25	2023	2023	NUM
cana-1160	119	26	.	.	PUNCT
cana-1160	120	1	[	[	X
cana-1160	120	2	10	10	NUM
cana-1160	120	3	]	]	PUNCT
cana-1160	120	4	“	"	PUNCT
cana-1160	120	5	leveraging	leverage	VERB
cana-1160	120	6	lnns	lnn	NOUN
cana-1160	120	7	for	for	ADP
cana-1160	120	8	dynamic	dynamic	ADJ
cana-1160	120	9	system	system	NOUN
cana-1160	120	10	modeling	modeling	NOUN
cana-1160	120	11	”	"	PUNCT
cana-1160	120	12	,	,	PUNCT
cana-1160	120	13	c.	c.	PROPN
cana-1160	120	14	wu	wu	PROPN
cana-1160	120	15	,	,	PUNCT
cana-1160	120	16	y.	y.	PROPN
cana-1160	120	17	zhao	zhao	PROPN
cana-1160	120	18	,	,	PUNCT
cana-1160	120	19	systems	system	NOUN
cana-1160	120	20	engineering	engineering	NOUN
cana-1160	120	21	journal	journal	NOUN
cana-1160	120	22	,	,	PUNCT
cana-1160	120	23	2021	2021	NUM
cana-1160	120	24	.	.	PUNCT
cana-1160	121	1	[	[	X
cana-1160	121	2	11	11	NUM
cana-1160	121	3	]	]	PUNCT
cana-1160	121	4	“	"	PUNCT
cana-1160	121	5	a	a	DET
cana-1160	121	6	comparative	comparative	ADJ
cana-1160	121	7	study	study	NOUN
cana-1160	121	8	of	of	ADP
cana-1160	121	9	kans	kans	PROPN
cana-1160	121	10	and	and	CCONJ
cana-1160	121	11	lnns	lnn	NOUN
cana-1160	121	12	”	"	PUNCT
cana-1160	121	13	,	,	PUNCT
cana-1160	121	14	v.	v.	PROPN
cana-1160	121	15	patel	patel	PROPN
cana-1160	121	16	,	,	PUNCT
cana-1160	121	17	l.	l.	PROPN
cana-1160	121	18	garcia	garcia	PROPN
cana-1160	121	19	,	,	PUNCT
cana-1160	121	20	neural	neural	ADJ
cana-1160	121	21	computing	computing	NOUN
cana-1160	121	22	and	and	CCONJ
cana-1160	121	23	applications	application	NOUN
cana-1160	121	24	,	,	PUNCT
cana-1160	121	25	2022	2022	NUM
cana-1160	121	26	.	.	PUNCT
cana-1160	122	1	[	[	X
cana-1160	122	2	12	12	NUM
cana-1160	122	3	]	]	PUNCT
cana-1160	122	4	“	"	PUNCT
cana-1160	122	5	advancements	advancement	NOUN
cana-1160	122	6	in	in	ADP
cana-1160	122	7	liquid	liquid	ADJ
cana-1160	122	8	neural	neural	ADJ
cana-1160	122	9	network	network	NOUN
cana-1160	122	10	architectures	architecture	NOUN
cana-1160	122	11	”	"	PUNCT
cana-1160	122	12	,	,	PUNCT
cana-1160	122	13	a.	a.	NOUN
cana-1160	122	14	brown	brown	PROPN
cana-1160	122	15	,	,	PUNCT
cana-1160	122	16	m.	m.	NOUN
cana-1160	122	17	clark	clark	PROPN
cana-1160	122	18	,	,	PUNCT
cana-1160	122	19	deep	deep	ADJ
cana-1160	122	20	learning	learning	NOUN
cana-1160	122	21	journal	journal	NOUN
cana-1160	122	22	,	,	PUNCT
cana-1160	122	23	2024	2024	NUM
cana-1160	122	24	.	.	PUNCT
cana-1160	123	1	[	[	X
cana-1160	123	2	13	13	NUM
cana-1160	123	3	]	]	PUNCT
cana-1160	123	4	“	"	PUNCT
cana-1160	123	5	kans	kan	NOUN
cana-1160	123	6	for	for	ADP
cana-1160	123	7	climate	climate	NOUN
cana-1160	123	8	modeling	modeling	NOUN
cana-1160	123	9	and	and	CCONJ
cana-1160	123	10	prediction	prediction	NOUN
cana-1160	123	11	”	"	PUNCT
cana-1160	123	12	,	,	PUNCT
cana-1160	123	13	r.	r.	PROPN
cana-1160	123	14	thompson	thompson	PROPN
cana-1160	123	15	,	,	PUNCT
cana-1160	123	16	j.	j.	PROPN
cana-1160	123	17	lopez	lopez	PROPN
cana-1160	123	18	,	,	PUNCT
cana-1160	123	19	environmental	environmental	ADJ
cana-1160	123	20	modeling	modeling	NOUN
cana-1160	123	21	journal	journal	NOUN
cana-1160	123	22	,	,	PUNCT
cana-1160	123	23	2023	2023	NUM
cana-1160	123	24	.	.	PUNCT
cana-1160	124	1	[	[	X
cana-1160	124	2	14	14	NUM
cana-1160	124	3	]	]	X
cana-1160	124	4	“	"	PUNCT
cana-1160	124	5	real	real	ADJ
cana-1160	124	6	-	-	PUNCT
cana-1160	124	7	time	time	NOUN
cana-1160	124	8	applications	application	NOUN
cana-1160	124	9	of	of	ADP
cana-1160	124	10	liquid	liquid	ADJ
cana-1160	124	11	neural	neural	NOUN
cana-1160	124	12	networks”,f	networks”,f	PROPN
cana-1160	124	13	.	.	PUNCT
cana-1160	124	14	silva	silva	PROPN
cana-1160	124	15	,	,	PUNCT
cana-1160	124	16	h.	h.	PROPN
cana-1160	124	17	lee	lee	PROPN
cana-1160	124	18	,	,	PUNCT
cana-1160	124	19	real	real	ADJ
cana-1160	124	20	-	-	PUNCT
cana-1160	124	21	time	time	NOUN
cana-1160	124	22	systems	system	NOUN
cana-1160	124	23	journal	journal	NOUN
cana-1160	124	24	,	,	PUNCT
cana-1160	124	25	2020	2020	NUM
cana-1160	124	26	.	.	PUNCT
cana-1160	125	1	[	[	X
cana-1160	125	2	15	15	NUM
cana-1160	125	3	]	]	X
cana-1160	125	4	“	"	PUNCT
cana-1160	125	5	kolmogorov	kolmogorov	PROPN
cana-1160	125	6	-	-	PUNCT
cana-1160	125	7	arnold	arnold	PROPN
cana-1160	125	8	networks	network	NOUN
cana-1160	125	9	for	for	ADP
cana-1160	125	10	financial	financial	ADJ
cana-1160	125	11	forecasting	forecasting	NOUN
cana-1160	125	12	”	"	PUNCT
cana-1160	125	13	,	,	PUNCT
cana-1160	125	14	g.	g.	PROPN
cana-1160	125	15	wang	wang	PROPN
cana-1160	125	16	,	,	PUNCT
cana-1160	125	17	t.	t.	PROPN
cana-1160	125	18	chen	chen	PROPN
cana-1160	125	19	,	,	PUNCT
cana-1160	125	20	finance	finance	NOUN
cana-1160	125	21	and	and	CCONJ
cana-1160	125	22	ai	ai	VERB
cana-1160	125	23	,	,	PUNCT
cana-1160	125	24	2022	2022	NUM
cana-1160	125	25	.	.	PUNCT
cana-1160	126	1	[	[	X
cana-1160	126	2	16	16	NUM
cana-1160	126	3	]	]	PUNCT
cana-1160	126	4	“	"	PUNCT
cana-1160	126	5	liquid	liquid	ADJ
cana-1160	126	6	neural	neural	ADJ
cana-1160	126	7	networks	network	NOUN
cana-1160	126	8	in	in	ADP
cana-1160	126	9	autonomous	autonomous	ADJ
cana-1160	126	10	vehicles	vehicle	NOUN
cana-1160	126	11	”	"	PUNCT
cana-1160	126	12	,	,	PUNCT
cana-1160	126	13	i.	i.	PROPN
cana-1160	126	14	davis	davis	PROPN
cana-1160	126	15	,	,	PUNCT
cana-1160	126	16	e.	e.	PROPN
cana-1160	126	17	martinez	martinez	PROPN
cana-1160	126	18	,	,	PUNCT
cana-1160	126	19	autonomous	autonomous	ADJ
cana-1160	126	20	systems	system	NOUN
cana-1160	126	21	,	,	PUNCT
cana-1160	126	22	2023	2023	NUM
cana-1160	126	23	.	.	PUNCT
cana-1160	127	1	[	[	X
cana-1160	127	2	17	17	NUM
cana-1160	127	3	]	]	PUNCT
cana-1160	127	4	“	"	PUNCT
cana-1160	127	5	enhancing	enhance	VERB
cana-1160	127	6	neural	neural	ADJ
cana-1160	127	7	networks	network	NOUN
cana-1160	127	8	with	with	ADP
cana-1160	127	9	kolmogorov	kolmogorov	PROPN
cana-1160	127	10	-	-	PUNCT
cana-1160	127	11	arnold	arnold	PROPN
cana-1160	127	12	techniques	technique	NOUN
cana-1160	127	13	”	"	PUNCT
cana-1160	127	14	,	,	PUNCT
cana-1160	127	15	j.	j.	PROPN
cana-1160	127	16	taylor	taylor	PROPN
cana-1160	127	17	,	,	PUNCT
cana-1160	127	18	n.	n.	PROPN
cana-1160	127	19	roberts	roberts	PROPN
cana-1160	127	20	,	,	PUNCT
cana-1160	127	21	computational	computational	ADJ
cana-1160	127	22	intelligence	intelligence	NOUN
cana-1160	127	23	journal	journal	NOUN
cana-1160	127	24	,	,	PUNCT
cana-1160	127	25	2024	2024	NUM
cana-1160	127	26	.	.	PUNCT
cana-1160	128	1	[	[	X
cana-1160	128	2	18	18	NUM
cana-1160	128	3	]	]	PUNCT
cana-1160	128	4	“	"	PUNCT
cana-1160	128	5	liquid	liquid	ADJ
cana-1160	128	6	neural	neural	ADJ
cana-1160	128	7	networks	network	NOUN
cana-1160	128	8	for	for	ADP
cana-1160	128	9	health	health	NOUN
cana-1160	128	10	monitoring	monitoring	NOUN
cana-1160	128	11	systems	system	NOUN
cana-1160	128	12	”	"	PUNCT
cana-1160	128	13	,	,	PUNCT
cana-1160	128	14	k.	k.	PROPN
cana-1160	128	15	evans	evans	PROPN
cana-1160	128	16	,	,	PUNCT
cana-1160	128	17	m.	m.	PROPN
cana-1160	128	18	wilson	wilson	PROPN
cana-1160	128	19	,	,	PUNCT
cana-1160	128	20	health	health	NOUN
cana-1160	128	21	informatics	informatic	NOUN
cana-1160	128	22	journal	journal	NOUN
cana-1160	128	23	,	,	PUNCT
cana-1160	128	24	2021	2021	NUM
cana-1160	128	25	.	.	PUNCT
cana-1160	129	1	[	[	X
cana-1160	129	2	19	19	NUM
cana-1160	129	3	]	]	PUNCT
cana-1160	129	4	“	"	PUNCT
cana-1160	129	5	kans	kan	NOUN
cana-1160	129	6	and	and	CCONJ
cana-1160	129	7	lnns	lnns	ADJ
cana-1160	129	8	:	:	PUNCT
cana-1160	129	9	synergies	synergy	NOUN
cana-1160	129	10	and	and	CCONJ
cana-1160	129	11	applications	application	NOUN
cana-1160	129	12	”	"	PUNCT
cana-1160	129	13	,	,	PUNCT
cana-1160	129	14	p.	p.	PROPN
cana-1160	129	15	young	young	PROPN
cana-1160	129	16	,	,	PUNCT
cana-1160	129	17	s.	s.	PROPN
cana-1160	129	18	white	white	PROPN
cana-1160	129	19	,	,	PUNCT
cana-1160	129	20	ai	ai	VERB
cana-1160	129	21	synergies	synergy	NOUN
cana-1160	129	22	journal	journal	NOUN
cana-1160	129	23	,	,	PUNCT
cana-1160	129	24	2022	2022	NUM
cana-1160	129	25	.	.	PUNCT
cana-1160	130	1	[	[	X
cana-1160	130	2	20	20	NUM
cana-1160	130	3	]	]	PUNCT
cana-1160	130	4	“	"	PUNCT
cana-1160	130	5	utilizing	utilize	VERB
cana-1160	130	6	liquid	liquid	ADJ
cana-1160	130	7	neural	neural	ADJ
cana-1160	130	8	networks	network	NOUN
cana-1160	130	9	for	for	ADP
cana-1160	130	10	predictive	predictive	ADJ
cana-1160	130	11	analytics	analytic	NOUN
cana-1160	130	12	”	"	PUNCT
cana-1160	130	13	,	,	PUNCT
cana-1160	130	14	l.	l.	PROPN
cana-1160	130	15	scott	scott	PROPN
cana-1160	130	16	,	,	PUNCT
cana-1160	130	17	d.	d.	PROPN
cana-1160	130	18	moore	moore	PROPN
cana-1160	130	19	,	,	PUNCT
cana-1160	130	20	predictive	predictive	ADJ
cana-1160	130	21	analytics	analytic	NOUN
cana-1160	130	22	journal	journal	NOUN
cana-1160	130	23	,	,	PUNCT
cana-1160	130	24	2023	2023	NUM
cana-1160	130	25	.	.	PUNCT