id	sid	tid	token	lemma	pos
cana-5830	1	1	communications	communication	NOUN
cana-5830	1	2	on	on	ADP
cana-5830	1	3	applied	apply	VERB
cana-5830	1	4	nonlinear	nonlinear	ADJ
cana-5830	1	5	analysis	analysis	NOUN
cana-5830	1	6	issn	issn	NOUN
cana-5830	1	7	:	:	PUNCT
cana-5830	1	8	1074	1074	NUM
cana-5830	1	9	-	-	PUNCT
cana-5830	1	10	133x	133x	NUM
cana-5830	1	11	vol	vol	VERB
cana-5830	1	12	32	32	NUM
cana-5830	1	13	no	no	NOUN
cana-5830	1	14	.	.	PUNCT
cana-5830	2	1	10s	10	NOUN
cana-5830	2	2	(	(	PUNCT
cana-5830	2	3	2025	2025	NUM
cana-5830	2	4	)	)	PUNCT
cana-5830	2	5	2959	2959	NUM
cana-5830	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5830	2	7	“	"	PUNCT
cana-5830	2	8	advanced	advanced	ADJ
cana-5830	2	9	cyclone	cyclone	NOUN
cana-5830	2	10	prediction	prediction	NOUN
cana-5830	2	11	with	with	ADP
cana-5830	2	12	czekanowsky	czekanowsky	ADJ
cana-5830	2	13	hyper	hyper	ADJ
cana-5830	2	14	graph	graph	NOUN
cana-5830	2	15	”	"	PUNCT
cana-5830	2	16	1	1	NUM
cana-5830	2	17	poluri	poluri	PROPN
cana-5830	2	18	saranya	saranya	PROPN
cana-5830	2	19	,	,	PUNCT
cana-5830	2	20	2	2	NUM
cana-5830	2	21	dr.pilla	dr.pilla	NOUN
cana-5830	2	22	srinivas	srinivas	PROPN
cana-5830	2	23	1	1	NUM
cana-5830	2	24	pg	pg	NOUN
cana-5830	2	25	scholar	scholar	NOUN
cana-5830	2	26	,	,	PUNCT
cana-5830	2	27	department	department	NOUN
cana-5830	2	28	of	of	ADP
cana-5830	2	29	computer	computer	NOUN
cana-5830	2	30	science	science	NOUN
cana-5830	2	31	and	and	CCONJ
cana-5830	2	32	engineering	engineering	NOUN
cana-5830	2	33	,	,	PUNCT
cana-5830	2	34	malla	malla	PROPN
cana-5830	2	35	reddy	reddy	PROPN
cana-5830	2	36	engineering	engineering	PROPN
cana-5830	2	37	college	college	PROPN
cana-5830	2	38	(	(	PUNCT
cana-5830	2	39	a	a	NOUN
cana-5830	2	40	)	)	PUNCT
cana-5830	2	41	,	,	PUNCT
cana-5830	2	42	maisammaguda	maisammaguda	NOUN
cana-5830	2	43	,	,	PUNCT
cana-5830	2	44	500100,telangana	500100,telangana	PROPN
cana-5830	2	45	,	,	PUNCT
cana-5830	2	46	india	india	PROPN
cana-5830	2	47	2	2	NUM
cana-5830	2	48	professor	professor	NOUN
cana-5830	2	49	,	,	PUNCT
cana-5830	2	50	department	department	NOUN
cana-5830	2	51	of	of	ADP
cana-5830	2	52	computer	computer	NOUN
cana-5830	2	53	science	science	NOUN
cana-5830	2	54	and	and	CCONJ
cana-5830	2	55	engineering	engineering	NOUN
cana-5830	2	56	,	,	PUNCT
cana-5830	2	57	malla	malla	PROPN
cana-5830	2	58	reddy	reddy	PROPN
cana-5830	2	59	engineering	engineering	PROPN
cana-5830	2	60	college	college	PROPN
cana-5830	2	61	(	(	PUNCT
cana-5830	2	62	a	a	NOUN
cana-5830	2	63	)	)	PUNCT
cana-5830	2	64	,	,	PUNCT
cana-5830	2	65	maisammaguda	maisammaguda	NOUN
cana-5830	2	66	,	,	PUNCT
cana-5830	2	67	500100,telangana	500100,telangana	PROPN
cana-5830	2	68	,	,	PUNCT
cana-5830	2	69	india	india	PROPN
cana-5830	2	70	author	author	NOUN
cana-5830	2	71	email:1.saranya.poluri92@gmail.com	email:1.saranya.poluri92@gmail.com	PROPN
cana-5830	2	72	2.drsrinivasp3@gmail.com	2.drsrinivasp3@gmail.com	NUM
cana-5830	2	73	article	article	NOUN
cana-5830	2	74	history	history	NOUN
cana-5830	2	75	:	:	PUNCT
cana-5830	2	76	received	receive	VERB
cana-5830	2	77	:	:	PUNCT
cana-5830	2	78	14	14	NUM
cana-5830	2	79	-	-	SYM
cana-5830	2	80	01	01	NUM
cana-5830	2	81	-	-	PUNCT
cana-5830	2	82	2025	2025	NUM
cana-5830	2	83	revised	revise	VERB
cana-5830	2	84	:	:	PUNCT
cana-5830	2	85	15	15	NUM
cana-5830	2	86	-	-	NUM
cana-5830	2	87	02	02	NUM
cana-5830	2	88	-	-	PUNCT
cana-5830	2	89	2025	2025	NUM
cana-5830	2	90	accepted	accept	VERB
cana-5830	2	91	:	:	PUNCT
cana-5830	2	92	21	21	NUM
cana-5830	2	93	-	-	SYM
cana-5830	2	94	03	03	NUM
cana-5830	2	95	-	-	PUNCT
cana-5830	2	96	2025	2025	NUM
cana-5830	2	97	abstract	abstract	NOUN
cana-5830	2	98	:	:	PUNCT
cana-5830	2	99	cyclone	cyclone	NOUN
cana-5830	2	100	prediction	prediction	NOUN
cana-5830	2	101	remains	remain	VERB
cana-5830	2	102	a	a	DET
cana-5830	2	103	critical	critical	ADJ
cana-5830	2	104	challenge	challenge	NOUN
cana-5830	2	105	in	in	ADP
cana-5830	2	106	meteorology	meteorology	NOUN
cana-5830	2	107	due	due	ADP
cana-5830	2	108	to	to	ADP
cana-5830	2	109	the	the	DET
cana-5830	2	110	complex	complex	ADJ
cana-5830	2	111	and	and	CCONJ
cana-5830	2	112	nonlinear	nonlinear	ADJ
cana-5830	2	113	nature	nature	NOUN
cana-5830	2	114	of	of	ADP
cana-5830	2	115	atmospheric	atmospheric	ADJ
cana-5830	2	116	phenomena	phenomenon	NOUN
cana-5830	2	117	.	.	PUNCT
cana-5830	3	1	this	this	DET
cana-5830	3	2	study	study	NOUN
cana-5830	3	3	presents	present	VERB
cana-5830	3	4	an	an	DET
cana-5830	3	5	advanced	advanced	ADJ
cana-5830	3	6	cyclone	cyclone	NOUN
cana-5830	3	7	prediction	prediction	NOUN
cana-5830	3	8	framework	framework	NOUN
cana-5830	3	9	leveraging	leverage	VERB
cana-5830	3	10	czekanowsky	czekanowsky	ADJ
cana-5830	3	11	hypergraph	hypergraph	NOUN
cana-5830	3	12	-	-	PUNCT
cana-5830	3	13	based	base	VERB
cana-5830	3	14	deep	deep	ADJ
cana-5830	3	15	learning	learning	NOUN
cana-5830	3	16	techniques	technique	NOUN
cana-5830	3	17	,	,	PUNCT
cana-5830	3	18	combined	combine	VERB
cana-5830	3	19	with	with	ADP
cana-5830	3	20	traditional	traditional	ADJ
cana-5830	3	21	machine	machine	NOUN
cana-5830	3	22	learning	learning	NOUN
cana-5830	3	23	models	model	NOUN
cana-5830	3	24	for	for	ADP
cana-5830	3	25	enhanced	enhanced	ADJ
cana-5830	3	26	accuracy	accuracy	NOUN
cana-5830	3	27	and	and	CCONJ
cana-5830	3	28	robustness	robustness	NOUN
cana-5830	3	29	.	.	PUNCT
cana-5830	4	1	the	the	DET
cana-5830	4	2	proposed	propose	VERB
cana-5830	4	3	approach	approach	NOUN
cana-5830	4	4	constructs	construct	VERB
cana-5830	4	5	a	a	DET
cana-5830	4	6	hypergraph	hypergraph	NOUN
cana-5830	4	7	representation	representation	NOUN
cana-5830	4	8	of	of	ADP
cana-5830	4	9	meteorological	meteorological	ADJ
cana-5830	4	10	data	datum	NOUN
cana-5830	4	11	,	,	PUNCT
cana-5830	4	12	utilizing	utilize	VERB
cana-5830	4	13	the	the	DET
cana-5830	4	14	czekanowsky	czekanowsky	ADJ
cana-5830	4	15	similarity	similarity	NOUN
cana-5830	4	16	measure	measure	NOUN
cana-5830	4	17	to	to	PART
cana-5830	4	18	capture	capture	VERB
cana-5830	4	19	high	high	ADJ
cana-5830	4	20	-	-	PUNCT
cana-5830	4	21	order	order	NOUN
cana-5830	4	22	relationships	relationship	NOUN
cana-5830	4	23	and	and	CCONJ
cana-5830	4	24	interactions	interaction	NOUN
cana-5830	4	25	between	between	ADP
cana-5830	4	26	multiple	multiple	ADJ
cana-5830	4	27	atmospheric	atmospheric	ADJ
cana-5830	4	28	variables	variable	NOUN
cana-5830	4	29	.	.	PUNCT
cana-5830	5	1	this	this	DET
cana-5830	5	2	hypergraph	hypergraph	NOUN
cana-5830	5	3	structure	structure	NOUN
cana-5830	5	4	serves	serve	VERB
cana-5830	5	5	as	as	ADP
cana-5830	5	6	the	the	DET
cana-5830	5	7	foundation	foundation	NOUN
cana-5830	5	8	for	for	ADP
cana-5830	5	9	a	a	DET
cana-5830	5	10	convolutional	convolutional	ADJ
cana-5830	5	11	neural	neural	ADJ
cana-5830	5	12	network	network	NOUN
cana-5830	5	13	(	(	PUNCT
cana-5830	5	14	cnn	cnn	PROPN
cana-5830	5	15	)	)	PUNCT
cana-5830	5	16	model	model	NOUN
cana-5830	5	17	designed	design	VERB
cana-5830	5	18	to	to	PART
cana-5830	5	19	extract	extract	VERB
cana-5830	5	20	intricate	intricate	ADJ
cana-5830	5	21	spatiotemporal	spatiotemporal	ADJ
cana-5830	5	22	features	feature	NOUN
cana-5830	5	23	for	for	ADP
cana-5830	5	24	precise	precise	ADJ
cana-5830	5	25	cyclone	cyclone	NOUN
cana-5830	5	26	detection	detection	NOUN
cana-5830	5	27	and	and	CCONJ
cana-5830	5	28	intensity	intensity	NOUN
cana-5830	5	29	forecasting	forecasting	NOUN
cana-5830	5	30	.	.	PUNCT
cana-5830	6	1	additionally	additionally	ADV
cana-5830	6	2	,	,	PUNCT
cana-5830	6	3	classical	classical	ADJ
cana-5830	6	4	machine	machine	NOUN
cana-5830	6	5	learning	learning	NOUN
cana-5830	6	6	models	model	NOUN
cana-5830	6	7	,	,	PUNCT
cana-5830	6	8	including	include	VERB
cana-5830	6	9	random	random	ADJ
cana-5830	6	10	forest	forest	NOUN
cana-5830	6	11	(	(	PUNCT
cana-5830	6	12	rf	rf	NOUN
cana-5830	6	13	)	)	PUNCT
cana-5830	6	14	and	and	CCONJ
cana-5830	6	15	k	k	ADV
cana-5830	6	16	-	-	PUNCT
cana-5830	6	17	nearest	near	ADJ
cana-5830	6	18	neighbors	neighbor	NOUN
cana-5830	6	19	(	(	PUNCT
cana-5830	6	20	knn	knn	PROPN
cana-5830	6	21	)	)	PUNCT
cana-5830	6	22	,	,	PUNCT
cana-5830	6	23	are	be	AUX
cana-5830	6	24	employed	employ	VERB
cana-5830	6	25	to	to	PART
cana-5830	6	26	complement	complement	VERB
cana-5830	6	27	the	the	DET
cana-5830	6	28	deep	deep	ADJ
cana-5830	6	29	learning	learning	NOUN
cana-5830	6	30	framework	framework	NOUN
cana-5830	6	31	by	by	ADP
cana-5830	6	32	providing	provide	VERB
cana-5830	6	33	interpretable	interpretable	ADJ
cana-5830	6	34	insights	insight	NOUN
cana-5830	6	35	and	and	CCONJ
cana-5830	6	36	comparative	comparative	ADJ
cana-5830	6	37	performance	performance	NOUN
cana-5830	6	38	benchmarks	benchmark	NOUN
cana-5830	6	39	.	.	PUNCT
cana-5830	7	1	experimental	experimental	ADJ
cana-5830	7	2	results	result	NOUN
cana-5830	7	3	on	on	ADP
cana-5830	7	4	realworld	realworld	PROPN
cana-5830	7	5	cyclone	cyclone	PROPN
cana-5830	7	6	datasets	dataset	NOUN
cana-5830	7	7	demonstrate	demonstrate	VERB
cana-5830	7	8	that	that	SCONJ
cana-5830	7	9	the	the	DET
cana-5830	7	10	integrated	integrate	VERB
cana-5830	7	11	model	model	NOUN
cana-5830	7	12	outperforms	outperform	VERB
cana-5830	7	13	individual	individual	ADJ
cana-5830	7	14	classifiers	classifier	NOUN
cana-5830	7	15	in	in	ADP
cana-5830	7	16	terms	term	NOUN
cana-5830	7	17	of	of	ADP
cana-5830	7	18	prediction	prediction	NOUN
cana-5830	7	19	accuracy	accuracy	NOUN
cana-5830	7	20	,	,	PUNCT
cana-5830	7	21	precision	precision	NOUN
cana-5830	7	22	,	,	PUNCT
cana-5830	7	23	and	and	CCONJ
cana-5830	7	24	recall	recall	NOUN
cana-5830	7	25	.	.	PUNCT
cana-5830	8	1	the	the	DET
cana-5830	8	2	fusion	fusion	NOUN
cana-5830	8	3	of	of	ADP
cana-5830	8	4	hypergraph	hypergraph	NOUN
cana-5830	8	5	-	-	PUNCT
cana-5830	8	6	based	base	VERB
cana-5830	8	7	cnn	cnn	PROPN
cana-5830	8	8	with	with	ADP
cana-5830	8	9	rf	rf	PRON
cana-5830	8	10	and	and	CCONJ
cana-5830	8	11	knn	knn	PROPN
cana-5830	8	12	offers	offer	VERB
cana-5830	8	13	a	a	DET
cana-5830	8	14	powerful	powerful	ADJ
cana-5830	8	15	tool	tool	NOUN
cana-5830	8	16	for	for	ADP
cana-5830	8	17	early	early	ADJ
cana-5830	8	18	cyclone	cyclone	NOUN
cana-5830	8	19	prediction	prediction	NOUN
cana-5830	8	20	,	,	PUNCT
cana-5830	8	21	potentially	potentially	ADV
cana-5830	8	22	enhancing	enhance	VERB
cana-5830	8	23	disaster	disaster	NOUN
cana-5830	8	24	preparedness	preparedness	NOUN
cana-5830	8	25	and	and	CCONJ
cana-5830	8	26	mitigation	mitigation	NOUN
cana-5830	8	27	strategies	strategy	NOUN
cana-5830	8	28	.	.	PUNCT
cana-5830	9	1	i.introduction	i.introduction	NOUN
cana-5830	9	2	cyclones	cyclone	NOUN
cana-5830	9	3	are	be	AUX
cana-5830	9	4	among	among	ADP
cana-5830	9	5	the	the	DET
cana-5830	9	6	most	most	ADV
cana-5830	9	7	devastating	devastating	ADJ
cana-5830	9	8	natural	natural	ADJ
cana-5830	9	9	disasters	disaster	NOUN
cana-5830	9	10	,	,	PUNCT
cana-5830	9	11	causing	cause	VERB
cana-5830	9	12	significant	significant	ADJ
cana-5830	9	13	loss	loss	NOUN
cana-5830	9	14	of	of	ADP
cana-5830	9	15	life	life	NOUN
cana-5830	9	16	and	and	CCONJ
cana-5830	9	17	property	property	NOUN
cana-5830	9	18	worldwide	worldwide	ADV
cana-5830	9	19	.	.	PUNCT
cana-5830	10	1	accurate	accurate	ADJ
cana-5830	10	2	and	and	CCONJ
cana-5830	10	3	timely	timely	ADJ
cana-5830	10	4	prediction	prediction	NOUN
cana-5830	10	5	of	of	ADP
cana-5830	10	6	cyclone	cyclone	NOUN
cana-5830	10	7	formation	formation	NOUN
cana-5830	10	8	,	,	PUNCT
cana-5830	10	9	and	and	CCONJ
cana-5830	10	10	intensity	intensity	NOUN
cana-5830	10	11	is	be	AUX
cana-5830	10	12	vital	vital	ADJ
cana-5830	10	13	for	for	ADP
cana-5830	10	14	disaster	disaster	NOUN
cana-5830	10	15	preparedness	preparedness	NOUN
cana-5830	10	16	and	and	CCONJ
cana-5830	10	17	mitigation	mitigation	NOUN
cana-5830	10	18	.	.	PUNCT
cana-5830	11	1	traditional	traditional	ADJ
cana-5830	11	2	forecasting	forecasting	NOUN
cana-5830	11	3	methods	method	NOUN
cana-5830	11	4	often	often	ADV
cana-5830	11	5	rely	rely	VERB
cana-5830	11	6	on	on	ADP
cana-5830	11	7	vphysicalc	vphysicalc	NOUN
cana-5830	11	8	models	model	NOUN
cana-5830	11	9	or	or	CCONJ
cana-5830	11	10	sequential	sequential	ADJ
cana-5830	11	11	deep	deep	ADJ
cana-5830	11	12	learning	learning	NOUN
cana-5830	11	13	approaches	approach	NOUN
cana-5830	11	14	such	such	ADJ
cana-5830	11	15	as	as	ADP
cana-5830	11	16	long	long	ADJ
cana-5830	11	17	short	short	ADJ
cana-5830	11	18	-	-	PUNCT
cana-5830	11	19	term	term	NOUN
cana-5830	11	20	memory	memory	NOUN
cana-5830	11	21	(	(	PUNCT
cana-5830	11	22	lstm	lstm	NOUN
cana-5830	11	23	)	)	PUNCT
cana-5830	11	24	networks	network	NOUN
cana-5830	11	25	,	,	PUNCT
cana-5830	11	26	which	which	PRON
cana-5830	11	27	are	be	AUX
cana-5830	11	28	limited	limit	VERB
cana-5830	11	29	in	in	ADP
cana-5830	11	30	capturing	capture	VERB
cana-5830	11	31	complex	complex	ADJ
cana-5830	11	32	interactions	interaction	NOUN
cana-5830	11	33	in	in	ADP
cana-5830	11	34	meteorological	meteorological	ADJ
cana-5830	11	35	data	datum	NOUN
cana-5830	11	36	.	.	PUNCT
cana-5830	12	1	this	this	DET
cana-5830	12	2	study	study	NOUN
cana-5830	12	3	introduces	introduce	VERB
cana-5830	12	4	a	a	DET
cana-5830	12	5	novel	novel	ADJ
cana-5830	12	6	cyclone	cyclone	NOUN
cana-5830	12	7	prediction	prediction	NOUN
cana-5830	12	8	framework	framework	NOUN
cana-5830	12	9	based	base	VERB
cana-5830	12	10	on	on	ADP
cana-5830	12	11	czekanowsky	czekanowsky	ADJ
cana-5830	12	12	hypergraph	hypergraph	NOUN
cana-5830	12	13	construction	construction	NOUN
cana-5830	12	14	to	to	PART
cana-5830	12	15	model	model	VERB
cana-5830	12	16	high	high	ADJ
cana-5830	12	17	-	-	PUNCT
cana-5830	12	18	order	order	NOUN
cana-5830	12	19	correlations	correlation	NOUN
cana-5830	12	20	among	among	ADP
cana-5830	12	21	atmospheric	atmospheric	ADJ
cana-5830	12	22	features	feature	NOUN
cana-5830	12	23	.	.	PUNCT
cana-5830	13	1	the	the	DET
cana-5830	13	2	hypergraph	hypergraph	NOUN
cana-5830	13	3	data	data	NOUN
cana-5830	13	4	structure	structure	NOUN
cana-5830	13	5	enables	enable	VERB
cana-5830	13	6	a	a	DET
cana-5830	13	7	cnn	cnn	PROPN
cana-5830	13	8	-	-	PUNCT
cana-5830	13	9	based	base	VERB
cana-5830	13	10	model	model	NOUN
cana-5830	13	11	communications	communication	NOUN
cana-5830	13	12	on	on	ADP
cana-5830	13	13	applied	apply	VERB
cana-5830	13	14	nonlinear	nonlinear	ADJ
cana-5830	13	15	analysis	analysis	NOUN
cana-5830	13	16	issn	issn	NOUN
cana-5830	13	17	:	:	PUNCT
cana-5830	13	18	1074	1074	NUM
cana-5830	13	19	-	-	PUNCT
cana-5830	13	20	133x	133x	NUM
cana-5830	13	21	vol	vol	VERB
cana-5830	13	22	32	32	NUM
cana-5830	13	23	no	no	NOUN
cana-5830	13	24	.	.	PUNCT
cana-5830	14	1	10s	10	NOUN
cana-5830	14	2	(	(	PUNCT
cana-5830	14	3	2025	2025	NUM
cana-5830	14	4	)	)	PUNCT
cana-5830	14	5	2960	2960	NUM
cana-5830	14	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5830	14	7	to	to	PART
cana-5830	14	8	extract	extract	VERB
cana-5830	14	9	more	more	ADV
cana-5830	14	10	meaningful	meaningful	ADJ
cana-5830	14	11	features	feature	NOUN
cana-5830	14	12	compared	compare	VERB
cana-5830	14	13	to	to	ADP
cana-5830	14	14	sequence	sequence	NOUN
cana-5830	14	15	-	-	PUNCT
cana-5830	14	16	only	only	ADJ
cana-5830	14	17	methods	method	NOUN
cana-5830	14	18	.	.	PUNCT
cana-5830	15	1	moreover	moreover	ADV
cana-5830	15	2	,	,	PUNCT
cana-5830	15	3	random	random	ADJ
cana-5830	15	4	forest	forest	NOUN
cana-5830	15	5	and	and	CCONJ
cana-5830	15	6	k	k	NOUN
cana-5830	15	7	-	-	PUNCT
cana-5830	15	8	nearest	near	ADJ
cana-5830	15	9	neighbors	neighbor	NOUN
cana-5830	15	10	classifiers	classifier	NOUN
cana-5830	15	11	are	be	AUX
cana-5830	15	12	integrated	integrate	VERB
cana-5830	15	13	for	for	ADP
cana-5830	15	14	comparison	comparison	NOUN
cana-5830	15	15	and	and	CCONJ
cana-5830	15	16	ensemble	ensemble	ADJ
cana-5830	15	17	prediction	prediction	NOUN
cana-5830	15	18	,	,	PUNCT
cana-5830	15	19	aiming	aim	VERB
cana-5830	15	20	to	to	PART
cana-5830	15	21	improve	improve	VERB
cana-5830	15	22	the	the	DET
cana-5830	15	23	overall	overall	ADJ
cana-5830	15	24	accuracy	accuracy	NOUN
cana-5830	15	25	and	and	CCONJ
cana-5830	15	26	robustness	robustness	NOUN
cana-5830	15	27	of	of	ADP
cana-5830	15	28	cyclone	cyclone	NOUN
cana-5830	15	29	forecasting	forecasting	NOUN
cana-5830	15	30	.	.	PUNCT
cana-5830	16	1	ii.literature	ii.literature	NOUN
cana-5830	16	2	survey	survey	VERB
cana-5830	16	3	1.title	1.title	NUM
cana-5830	16	4	:	:	PUNCT
cana-5830	16	5	cyclone	cyclone	NOUN
cana-5830	16	6	prediction	prediction	NOUN
cana-5830	16	7	using	use	VERB
cana-5830	16	8	long	long	ADJ
cana-5830	16	9	short	short	ADJ
cana-5830	16	10	-	-	PUNCT
cana-5830	16	11	term	term	NOUN
cana-5830	16	12	memory	memory	NOUN
cana-5830	16	13	networks	network	NOUN
cana-5830	16	14	authors	author	NOUN
cana-5830	16	15	:	:	PUNCT
cana-5830	16	16	anil	anil	PROPN
cana-5830	16	17	kumar	kumar	PROPN
cana-5830	16	18	,	,	PUNCT
cana-5830	16	19	priya	priya	PROPN
cana-5830	16	20	singh	singh	PROPN
cana-5830	16	21	,	,	PUNCT
cana-5830	16	22	ramesh	ramesh	PROPN
cana-5830	16	23	gupta	gupta	PROPN
cana-5830	16	24	year:2020	year:2020	NOUN
cana-5830	16	25	abstract	abstract	NOUN
cana-5830	16	26	:	:	PUNCT
cana-5830	16	27	this	this	DET
cana-5830	16	28	study	study	NOUN
cana-5830	16	29	explores	explore	VERB
cana-5830	16	30	the	the	DET
cana-5830	16	31	application	application	NOUN
cana-5830	16	32	of	of	ADP
cana-5830	16	33	long	long	ADJ
cana-5830	16	34	short	short	ADJ
cana-5830	16	35	-	-	PUNCT
cana-5830	16	36	term	term	NOUN
cana-5830	16	37	memory	memory	NOUN
cana-5830	16	38	(	(	PUNCT
cana-5830	16	39	lstm	lstm	NOUN
cana-5830	16	40	)	)	PUNCT
cana-5830	16	41	networks	network	NOUN
cana-5830	16	42	to	to	PART
cana-5830	16	43	predict	predict	VERB
cana-5830	16	44	cyclone	cyclone	NOUN
cana-5830	16	45	intensity	intensity	NOUN
cana-5830	16	46	and	and	CCONJ
cana-5830	16	47	trajectory	trajectory	NOUN
cana-5830	16	48	based	base	VERB
cana-5830	16	49	on	on	ADP
cana-5830	16	50	historical	historical	ADJ
cana-5830	16	51	meteorological	meteorological	ADJ
cana-5830	16	52	data	datum	NOUN
cana-5830	16	53	.	.	PUNCT
cana-5830	17	1	the	the	DET
cana-5830	17	2	model	model	NOUN
cana-5830	17	3	captures	capture	VERB
cana-5830	17	4	temporal	temporal	ADJ
cana-5830	17	5	dependencies	dependency	NOUN
cana-5830	17	6	effectively	effectively	ADV
cana-5830	17	7	,	,	PUNCT
cana-5830	17	8	enabling	enable	VERB
cana-5830	17	9	early	early	ADJ
cana-5830	17	10	cyclone	cyclone	NOUN
cana-5830	17	11	detection	detection	NOUN
cana-5830	17	12	.	.	PUNCT
cana-5830	18	1	however	however	ADV
cana-5830	18	2	,	,	PUNCT
cana-5830	18	3	the	the	DET
cana-5830	18	4	sequential	sequential	ADJ
cana-5830	18	5	nature	nature	NOUN
cana-5830	18	6	limits	limit	VERB
cana-5830	18	7	the	the	DET
cana-5830	18	8	model	model	NOUN
cana-5830	18	9	's	's	PART
cana-5830	18	10	ability	ability	NOUN
cana-5830	18	11	to	to	PART
cana-5830	18	12	represent	represent	VERB
cana-5830	18	13	complex	complex	ADJ
cana-5830	18	14	multi	multi	ADJ
cana-5830	18	15	-	-	ADJ
cana-5830	18	16	variable	variable	ADJ
cana-5830	18	17	interactions	interaction	NOUN
cana-5830	18	18	.	.	PUNCT
cana-5830	19	1	despite	despite	SCONJ
cana-5830	19	2	moderate	moderate	ADJ
cana-5830	19	3	prediction	prediction	NOUN
cana-5830	19	4	accuracy	accuracy	NOUN
cana-5830	19	5	,	,	PUNCT
cana-5830	19	6	the	the	DET
cana-5830	19	7	research	research	NOUN
cana-5830	19	8	highlights	highlight	VERB
cana-5830	19	9	the	the	DET
cana-5830	19	10	need	need	NOUN
cana-5830	19	11	for	for	ADP
cana-5830	19	12	integrating	integrate	VERB
cana-5830	19	13	more	more	ADV
cana-5830	19	14	sophisticated	sophisticated	ADJ
cana-5830	19	15	relational	relational	ADJ
cana-5830	19	16	models	model	NOUN
cana-5830	19	17	to	to	PART
cana-5830	19	18	improve	improve	VERB
cana-5830	19	19	cyclone	cyclone	NOUN
cana-5830	19	20	forecasting	forecasting	NOUN
cana-5830	19	21	.	.	PUNCT
cana-5830	20	1	2.title	2.title	NUM
cana-5830	20	2	:	:	PUNCT
cana-5830	20	3	hypergraph	hypergraph	VERB
cana-5830	20	4	neural	neural	ADJ
cana-5830	20	5	networks	network	NOUN
cana-5830	20	6	for	for	ADP
cana-5830	20	7	weatherforecasting	weatherforecaste	VERB
cana-5830	20	8	authors	author	NOUN
cana-5830	20	9	:	:	PUNCT
cana-5830	20	10	jiwoo	jiwoo	PROPN
cana-5830	20	11	lee	lee	PROPN
cana-5830	20	12	,	,	PUNCT
cana-5830	20	13	minseok	minseok	PROPN
cana-5830	20	14	park	park	PROPN
cana-5830	20	15	year:2022	year:2022	PROPN
cana-5830	20	16	abstract	abstract	PROPN
cana-5830	20	17	:	:	PUNCT
cana-5830	20	18	this	this	DET
cana-5830	20	19	paper	paper	NOUN
cana-5830	20	20	proposes	propose	VERB
cana-5830	20	21	the	the	DET
cana-5830	20	22	use	use	NOUN
cana-5830	20	23	of	of	ADP
cana-5830	20	24	hypergraph	hypergraph	NOUN
cana-5830	20	25	neural	neural	ADJ
cana-5830	20	26	networks	network	NOUN
cana-5830	20	27	(	(	PUNCT
cana-5830	20	28	hgnns	hgnns	PROPN
cana-5830	20	29	)	)	PUNCT
cana-5830	20	30	to	to	ADP
cana-5830	20	31	model	model	NOUN
cana-5830	20	32	complex	complex	ADJ
cana-5830	20	33	,	,	PUNCT
cana-5830	20	34	high	high	ADJ
cana-5830	20	35	-	-	PUNCT
cana-5830	20	36	order	order	NOUN
cana-5830	20	37	relationships	relationship	NOUN
cana-5830	20	38	in	in	ADP
cana-5830	20	39	meteorological	meteorological	ADJ
cana-5830	20	40	data	datum	NOUN
cana-5830	20	41	for	for	ADP
cana-5830	20	42	improved	improved	ADJ
cana-5830	20	43	weather	weather	NOUN
cana-5830	20	44	prediction	prediction	NOUN
cana-5830	20	45	.	.	PUNCT
cana-5830	21	1	by	by	ADP
cana-5830	21	2	representing	represent	VERB
cana-5830	21	3	atmospheric	atmospheric	ADJ
cana-5830	21	4	variables	variable	NOUN
cana-5830	21	5	as	as	ADP
cana-5830	21	6	hyperedges	hyperedge	NOUN
cana-5830	21	7	connected	connect	VERB
cana-5830	21	8	via	via	ADP
cana-5830	21	9	the	the	DET
cana-5830	21	10	czekanowsky	czekanowsky	ADJ
cana-5830	21	11	similarity	similarity	NOUN
cana-5830	21	12	measure	measure	NOUN
cana-5830	21	13	,	,	PUNCT
cana-5830	21	14	the	the	DET
cana-5830	21	15	model	model	NOUN
cana-5830	21	16	captures	capture	VERB
cana-5830	21	17	multiway	multiway	NOUN
cana-5830	21	18	feature	feature	NOUN
cana-5830	21	19	interactions	interaction	NOUN
cana-5830	21	20	often	often	ADV
cana-5830	21	21	overlooked	overlook	VERB
cana-5830	21	22	by	by	ADP
cana-5830	21	23	traditional	traditional	ADJ
cana-5830	21	24	graph	graph	NOUN
cana-5830	21	25	or	or	CCONJ
cana-5830	21	26	sequential	sequential	ADJ
cana-5830	21	27	models	model	NOUN
cana-5830	21	28	.	.	PUNCT
cana-5830	22	1	experiments	experiment	NOUN
cana-5830	22	2	on	on	ADP
cana-5830	22	3	weather	weather	NOUN
cana-5830	22	4	datasets	dataset	NOUN
cana-5830	22	5	demonstrate	demonstrate	VERB
cana-5830	22	6	enhanced	enhanced	ADJ
cana-5830	22	7	forecasting	forecasting	NOUN
cana-5830	22	8	accuracy	accuracy	NOUN
cana-5830	22	9	,	,	PUNCT
cana-5830	22	10	particularly	particularly	ADV
cana-5830	22	11	for	for	ADP
cana-5830	22	12	events	event	NOUN
cana-5830	22	13	with	with	ADP
cana-5830	22	14	nonlinear	nonlinear	ADJ
cana-5830	22	15	dependencies	dependency	NOUN
cana-5830	22	16	,	,	PUNCT
cana-5830	22	17	indicating	indicate	VERB
cana-5830	22	18	hgnns	hgnns	ADV
cana-5830	22	19	as	as	ADP
cana-5830	22	20	a	a	DET
cana-5830	22	21	promising	promising	ADJ
cana-5830	22	22	approach	approach	NOUN
cana-5830	22	23	for	for	ADP
cana-5830	22	24	advanced	advanced	ADJ
cana-5830	22	25	climate	climate	NOUN
cana-5830	22	26	modeling	modeling	NOUN
cana-5830	22	27	.	.	PUNCT
cana-5830	23	1	3.title	3.title	NUM
cana-5830	23	2	:	:	PUNCT
cana-5830	23	3	ensemble	ensemble	ADJ
cana-5830	23	4	machine	machine	NOUN
cana-5830	23	5	learning	learn	VERB
cana-5830	23	6	techniques	technique	NOUN
cana-5830	23	7	for	for	ADP
cana-5830	23	8	cyclone	cyclone	NOUN
cana-5830	23	9	intensity	intensity	NOUN
cana-5830	23	10	prediction	prediction	NOUN
cana-5830	23	11	authors	author	NOUN
cana-5830	23	12	:	:	PUNCT
cana-5830	23	13	sunita	sunita	PROPN
cana-5830	23	14	gupta	gupta	PROPN
cana-5830	23	15	,	,	PUNCT
cana-5830	23	16	rajesh	rajesh	PROPN
cana-5830	23	17	sharma	sharma	PROPN
cana-5830	23	18	year:2021	year:2021	PROPN
cana-5830	23	19	abstract	abstract	NOUN
cana-5830	23	20	:	:	PUNCT
cana-5830	23	21	the	the	DET
cana-5830	23	22	paper	paper	NOUN
cana-5830	23	23	presents	present	VERB
cana-5830	23	24	an	an	DET
cana-5830	23	25	ensemble	ensemble	ADJ
cana-5830	23	26	approach	approach	NOUN
cana-5830	23	27	combining	combine	VERB
cana-5830	23	28	random	random	ADJ
cana-5830	23	29	forest	forest	NOUN
cana-5830	23	30	and	and	CCONJ
cana-5830	23	31	k	k	NOUN
cana-5830	23	32	-	-	PUNCT
cana-5830	23	33	nearest	near	ADJ
cana-5830	23	34	neighbors	neighbor	NOUN
cana-5830	23	35	algorithms	algorithms	VERB
cana-5830	23	36	to	to	PART
cana-5830	23	37	predict	predict	VERB
cana-5830	23	38	cyclone	cyclone	NOUN
cana-5830	23	39	intensity	intensity	NOUN
cana-5830	23	40	using	use	VERB
cana-5830	23	41	a	a	DET
cana-5830	23	42	comprehensive	comprehensive	ADJ
cana-5830	23	43	dataset	dataset	NOUN
cana-5830	23	44	of	of	ADP
cana-5830	23	45	atmospheric	atmospheric	ADJ
cana-5830	23	46	parameters	parameter	NOUN
cana-5830	23	47	.	.	PUNCT
cana-5830	24	1	the	the	DET
cana-5830	24	2	ensemble	ensemble	ADJ
cana-5830	24	3	method	method	NOUN
cana-5830	24	4	capitalizes	capitalize	VERB
cana-5830	24	5	on	on	ADP
cana-5830	24	6	the	the	DET
cana-5830	24	7	complementary	complementary	ADJ
cana-5830	24	8	strengths	strength	NOUN
cana-5830	24	9	of	of	ADP
cana-5830	24	10	the	the	DET
cana-5830	24	11	classifiers	classifier	NOUN
cana-5830	24	12	,	,	PUNCT
cana-5830	24	13	achieving	achieve	VERB
cana-5830	24	14	higher	high	ADJ
cana-5830	24	15	accuracy	accuracy	NOUN
cana-5830	24	16	and	and	CCONJ
cana-5830	24	17	robustness	robustness	NOUN
cana-5830	24	18	compared	compare	VERB
cana-5830	24	19	to	to	ADP
cana-5830	24	20	individual	individual	ADJ
cana-5830	24	21	models	model	NOUN
cana-5830	24	22	.	.	PUNCT
cana-5830	25	1	results	result	NOUN
cana-5830	25	2	indicate	indicate	VERB
cana-5830	25	3	significant	significant	ADJ
cana-5830	25	4	improvements	improvement	NOUN
cana-5830	25	5	in	in	ADP
cana-5830	25	6	early	early	ADJ
cana-5830	25	7	cyclone	cyclone	NOUN
cana-5830	25	8	intensity	intensity	NOUN
cana-5830	25	9	classification	classification	NOUN
cana-5830	25	10	,	,	PUNCT
cana-5830	25	11	facilitating	facilitate	VERB
cana-5830	25	12	better	well	ADJ
cana-5830	25	13	preparedness	preparedness	NOUN
cana-5830	25	14	and	and	CCONJ
cana-5830	25	15	resource	resource	NOUN
cana-5830	25	16	allocation	allocation	NOUN
cana-5830	25	17	during	during	ADP
cana-5830	25	18	cyclone	cyclone	NOUN
cana-5830	25	19	events	event	NOUN
cana-5830	25	20	.	.	PUNCT
cana-5830	26	1	4.title	4.title	NUM
cana-5830	26	2	:	:	PUNCT
cana-5830	26	3	convolutional	convolutional	ADJ
cana-5830	26	4	neural	neural	ADJ
cana-5830	26	5	networks	network	NOUN
cana-5830	26	6	for	for	ADP
cana-5830	26	7	satellite	satellite	NOUN
cana-5830	26	8	-	-	PUNCT
cana-5830	26	9	based	base	VERB
cana-5830	26	10	cyclone	cyclone	NOUN
cana-5830	26	11	detection	detection	NOUN
cana-5830	26	12	authors	author	NOUN
cana-5830	26	13	:	:	PUNCT
cana-5830	26	14	li	li	PROPN
cana-5830	26	15	zhang	zhang	PROPN
cana-5830	26	16	,	,	PUNCT
cana-5830	26	17	wei	wei	PROPN
cana-5830	26	18	chen	chen	PROPN
cana-5830	26	19	,	,	PUNCT
cana-5830	26	20	haoyu	haoyu	PROPN
cana-5830	26	21	liu	liu	PROPN
cana-5830	26	22	year:2019	year:2019	PROPN
cana-5830	26	23	abstract	abstract	NOUN
cana-5830	26	24	:	:	PUNCT
cana-5830	26	25	this	this	DET
cana-5830	26	26	work	work	NOUN
cana-5830	26	27	applies	apply	VERB
cana-5830	26	28	convolutional	convolutional	ADJ
cana-5830	26	29	neural	neural	ADJ
cana-5830	26	30	networks	network	NOUN
cana-5830	26	31	(	(	PUNCT
cana-5830	26	32	cnns	cnns	PROPN
cana-5830	26	33	)	)	PUNCT
cana-5830	26	34	to	to	ADP
cana-5830	26	35	satellite	satellite	NOUN
cana-5830	26	36	image	image	NOUN
cana-5830	26	37	data	datum	NOUN
cana-5830	26	38	for	for	ADP
cana-5830	26	39	automated	automate	VERB
cana-5830	26	40	cyclone	cyclone	NOUN
cana-5830	26	41	detection	detection	NOUN
cana-5830	26	42	.	.	PUNCT
cana-5830	27	1	the	the	DET
cana-5830	27	2	model	model	NOUN
cana-5830	27	3	effectively	effectively	ADV
cana-5830	27	4	extracts	extract	VERB
cana-5830	27	5	spatial	spatial	ADJ
cana-5830	27	6	features	feature	NOUN
cana-5830	27	7	from	from	ADP
cana-5830	27	8	cloud	cloud	NOUN
cana-5830	27	9	patterns	pattern	NOUN
cana-5830	27	10	,	,	PUNCT
cana-5830	27	11	enabling	enable	VERB
cana-5830	27	12	accurate	accurate	ADJ
cana-5830	27	13	identification	identification	NOUN
cana-5830	27	14	of	of	ADP
cana-5830	27	15	cyclone	cyclone	NOUN
cana-5830	27	16	formation	formation	NOUN
cana-5830	27	17	regions	region	NOUN
cana-5830	27	18	.	.	PUNCT
cana-5830	28	1	although	although	SCONJ
cana-5830	28	2	cnns	cnn	NOUN
cana-5830	28	3	show	show	VERB
cana-5830	28	4	superior	superior	ADJ
cana-5830	28	5	performance	performance	NOUN
cana-5830	28	6	in	in	ADP
cana-5830	28	7	spatial	spatial	ADJ
cana-5830	28	8	communications	communication	NOUN
cana-5830	28	9	on	on	ADP
cana-5830	28	10	applied	apply	VERB
cana-5830	28	11	nonlinear	nonlinear	ADJ
cana-5830	28	12	analysis	analysis	NOUN
cana-5830	28	13	issn	issn	NOUN
cana-5830	28	14	:	:	PUNCT
cana-5830	28	15	1074	1074	NUM
cana-5830	28	16	-	-	PUNCT
cana-5830	28	17	133x	133x	NUM
cana-5830	28	18	vol	vol	VERB
cana-5830	28	19	32	32	NUM
cana-5830	28	20	no	no	NOUN
cana-5830	28	21	.	.	PUNCT
cana-5830	29	1	10s	10	NOUN
cana-5830	29	2	(	(	PUNCT
cana-5830	29	3	2025	2025	NUM
cana-5830	29	4	)	)	PUNCT
cana-5830	29	5	2961	2961	NUM
cana-5830	29	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5830	29	7	feature	feature	NOUN
cana-5830	29	8	recognition	recognition	NOUN
cana-5830	29	9	,	,	PUNCT
cana-5830	29	10	the	the	DET
cana-5830	29	11	study	study	NOUN
cana-5830	29	12	notes	note	VERB
cana-5830	29	13	challenges	challenge	NOUN
cana-5830	29	14	in	in	ADP
cana-5830	29	15	incorporating	incorporate	VERB
cana-5830	29	16	temporal	temporal	ADJ
cana-5830	29	17	information	information	NOUN
cana-5830	29	18	,	,	PUNCT
cana-5830	29	19	suggesting	suggest	VERB
cana-5830	29	20	potential	potential	ADJ
cana-5830	29	21	improvements	improvement	NOUN
cana-5830	29	22	through	through	ADP
cana-5830	29	23	hybrid	hybrid	NOUN
cana-5830	29	24	models	model	NOUN
cana-5830	29	25	combining	combine	VERB
cana-5830	29	26	cnns	cnn	NOUN
cana-5830	29	27	with	with	ADP
cana-5830	29	28	sequence	sequence	NOUN
cana-5830	29	29	learning	learn	VERB
cana-5830	29	30	techniques	technique	NOUN
cana-5830	29	31	.	.	PUNCT
cana-5830	30	1	5.title	5.title	NUM
cana-5830	30	2	:	:	PUNCT
cana-5830	30	3	application	application	NOUN
cana-5830	30	4	of	of	ADP
cana-5830	30	5	czekanowsky	czekanowsky	ADJ
cana-5830	30	6	similarity	similarity	NOUN
cana-5830	30	7	in	in	ADP
cana-5830	30	8	clustering	cluster	VERB
cana-5830	30	9	meteorological	meteorological	ADJ
cana-5830	30	10	data	datum	NOUN
cana-5830	30	11	authors	author	NOUN
cana-5830	30	12	:	:	PUNCT
cana-5830	30	13	deepak	deepak	PROPN
cana-5830	30	14	patel	patel	PROPN
cana-5830	30	15	,	,	PUNCT
cana-5830	30	16	kavita	kavita	PROPN
cana-5830	30	17	singh	singh	PROPN
cana-5830	30	18	year:2023	year:2023	PROPN
cana-5830	30	19	abstract	abstract	NOUN
cana-5830	30	20	:	:	PUNCT
cana-5830	30	21	this	this	DET
cana-5830	30	22	research	research	NOUN
cana-5830	30	23	investigates	investigate	VERB
cana-5830	30	24	the	the	DET
cana-5830	30	25	use	use	NOUN
cana-5830	30	26	of	of	ADP
cana-5830	30	27	czekanowsky	czekanowsky	ADJ
cana-5830	30	28	similarity	similarity	NOUN
cana-5830	30	29	to	to	PART
cana-5830	30	30	measure	measure	VERB
cana-5830	30	31	the	the	DET
cana-5830	30	32	closeness	closeness	NOUN
cana-5830	30	33	of	of	ADP
cana-5830	30	34	meteorological	meteorological	ADJ
cana-5830	30	35	feature	feature	NOUN
cana-5830	30	36	sets	set	NOUN
cana-5830	30	37	,	,	PUNCT
cana-5830	30	38	facilitating	facilitate	VERB
cana-5830	30	39	the	the	DET
cana-5830	30	40	clustering	clustering	NOUN
cana-5830	30	41	of	of	ADP
cana-5830	30	42	atmospheric	atmospheric	ADJ
cana-5830	30	43	variables	variable	NOUN
cana-5830	30	44	into	into	ADP
cana-5830	30	45	meaningful	meaningful	ADJ
cana-5830	30	46	groups	group	NOUN
cana-5830	30	47	.	.	PUNCT
cana-5830	31	1	the	the	DET
cana-5830	31	2	similarity	similarity	NOUN
cana-5830	31	3	measure	measure	NOUN
cana-5830	31	4	,	,	PUNCT
cana-5830	31	5	applied	apply	VERB
cana-5830	31	6	to	to	PART
cana-5830	31	7	multivariate	multivariate	VERB
cana-5830	31	8	weather	weather	NOUN
cana-5830	31	9	data	datum	NOUN
cana-5830	31	10	,	,	PUNCT
cana-5830	31	11	enables	enable	VERB
cana-5830	31	12	the	the	DET
cana-5830	31	13	creation	creation	NOUN
cana-5830	31	14	of	of	ADP
cana-5830	31	15	hypergraph	hypergraph	NOUN
cana-5830	31	16	structures	structure	NOUN
cana-5830	31	17	that	that	PRON
cana-5830	31	18	better	well	ADJ
cana-5830	31	19	capture	capture	VERB
cana-5830	31	20	interdependencies	interdependency	NOUN
cana-5830	31	21	than	than	ADP
cana-5830	31	22	traditional	traditional	ADJ
cana-5830	31	23	pairwise	pairwise	NOUN
cana-5830	31	24	measures	measure	NOUN
cana-5830	31	25	.	.	PUNCT
cana-5830	32	1	the	the	DET
cana-5830	32	2	findings	finding	NOUN
cana-5830	32	3	demonstrate	demonstrate	VERB
cana-5830	32	4	improved	improved	ADJ
cana-5830	32	5	data	datum	NOUN
cana-5830	32	6	representation	representation	NOUN
cana-5830	32	7	for	for	ADP
cana-5830	32	8	subsequent	subsequent	ADJ
cana-5830	32	9	predictive	predictive	ADJ
cana-5830	32	10	modeling	modeling	NOUN
cana-5830	32	11	tasks	task	NOUN
cana-5830	32	12	,	,	PUNCT
cana-5830	32	13	suggesting	suggest	VERB
cana-5830	32	14	advantages	advantage	NOUN
cana-5830	32	15	for	for	ADP
cana-5830	32	16	cyclone	cyclone	NOUN
cana-5830	32	17	and	and	CCONJ
cana-5830	32	18	severe	severe	ADJ
cana-5830	32	19	weather	weather	NOUN
cana-5830	32	20	forecasting	forecasting	NOUN
cana-5830	32	21	systems	system	NOUN
cana-5830	32	22	.	.	PUNCT
cana-5830	33	1	iii.existing	iii.existing	NOUN
cana-5830	33	2	system	system	NOUN
cana-5830	33	3	existing	exist	VERB
cana-5830	33	4	cyclone	cyclone	NOUN
cana-5830	33	5	prediction	prediction	NOUN
cana-5830	33	6	systems	system	NOUN
cana-5830	33	7	predominantly	predominantly	ADV
cana-5830	33	8	use	use	VERB
cana-5830	33	9	sequential	sequential	ADJ
cana-5830	33	10	models	model	NOUN
cana-5830	33	11	such	such	ADJ
cana-5830	33	12	as	as	ADP
cana-5830	33	13	lstm	lstm	NOUN
cana-5830	33	14	or	or	CCONJ
cana-5830	33	15	traditional	traditional	ADJ
cana-5830	33	16	physical	physical	ADJ
cana-5830	33	17	simulations	simulation	NOUN
cana-5830	33	18	.	.	PUNCT
cana-5830	34	1	these	these	DET
cana-5830	34	2	models	model	NOUN
cana-5830	34	3	often	often	ADV
cana-5830	34	4	process	process	VERB
cana-5830	34	5	time	time	NOUN
cana-5830	34	6	-	-	PUNCT
cana-5830	34	7	series	series	NOUN
cana-5830	34	8	meteorological	meteorological	ADJ
cana-5830	34	9	datasets	dataset	NOUN
cana-5830	34	10	including	include	VERB
cana-5830	34	11	satellite	satellite	NOUN
cana-5830	34	12	images	image	NOUN
cana-5830	34	13	,	,	PUNCT
cana-5830	34	14	wind	wind	NOUN
cana-5830	34	15	speed	speed	NOUN
cana-5830	34	16	,	,	PUNCT
cana-5830	34	17	pressure	pressure	NOUN
cana-5830	34	18	,	,	PUNCT
cana-5830	34	19	and	and	CCONJ
cana-5830	34	20	temperature	temperature	NOUN
cana-5830	34	21	data	datum	NOUN
cana-5830	34	22	to	to	PART
cana-5830	34	23	forecast	forecast	VERB
cana-5830	34	24	cyclone	cyclone	NOUN
cana-5830	34	25	activity	activity	NOUN
cana-5830	34	26	.	.	PUNCT
cana-5830	35	1	for	for	ADP
cana-5830	35	2	example	example	NOUN
cana-5830	35	3	,	,	PUNCT
cana-5830	35	4	lstm	lstm	ADJ
cana-5830	35	5	networks	network	NOUN
cana-5830	35	6	are	be	AUX
cana-5830	35	7	used	use	VERB
cana-5830	35	8	to	to	PART
cana-5830	35	9	learn	learn	VERB
cana-5830	35	10	temporal	temporal	ADJ
cana-5830	35	11	dependencies	dependency	NOUN
cana-5830	35	12	in	in	ADP
cana-5830	35	13	atmospheric	atmospheric	ADJ
cana-5830	35	14	sequences	sequence	NOUN
cana-5830	35	15	for	for	ADP
cana-5830	35	16	predicting	predict	VERB
cana-5830	35	17	cyclone	cyclone	NOUN
cana-5830	35	18	intensity	intensity	NOUN
cana-5830	35	19	and	and	CCONJ
cana-5830	35	20	paths	path	NOUN
cana-5830	35	21	.	.	PUNCT
cana-5830	36	1	however	however	ADV
cana-5830	36	2	,	,	PUNCT
cana-5830	36	3	these	these	DET
cana-5830	36	4	models	model	NOUN
cana-5830	36	5	face	face	VERB
cana-5830	36	6	challenges	challenge	NOUN
cana-5830	36	7	in	in	ADP
cana-5830	36	8	capturing	capture	VERB
cana-5830	36	9	nonlinear	nonlinear	ADJ
cana-5830	36	10	,	,	PUNCT
cana-5830	36	11	high	high	ADJ
cana-5830	36	12	-	-	PUNCT
cana-5830	36	13	order	order	NOUN
cana-5830	36	14	feature	feature	NOUN
cana-5830	36	15	interactions	interaction	NOUN
cana-5830	36	16	inherent	inherent	ADJ
cana-5830	36	17	in	in	ADP
cana-5830	36	18	complex	complex	ADJ
cana-5830	36	19	weather	weather	NOUN
cana-5830	36	20	systems	system	NOUN
cana-5830	36	21	.	.	PUNCT
cana-5830	37	1	also	also	ADV
cana-5830	37	2	,	,	PUNCT
cana-5830	37	3	they	they	PRON
cana-5830	37	4	require	require	VERB
cana-5830	37	5	extensive	extensive	ADJ
cana-5830	37	6	labeled	label	VERB
cana-5830	37	7	datasets	dataset	NOUN
cana-5830	37	8	and	and	CCONJ
cana-5830	37	9	significant	significant	ADJ
cana-5830	37	10	computational	computational	ADJ
cana-5830	37	11	resources	resource	NOUN
cana-5830	37	12	.	.	PUNCT
cana-5830	38	1	typical	typical	ADJ
cana-5830	38	2	datasets	dataset	NOUN
cana-5830	38	3	used	use	VERB
cana-5830	38	4	include	include	VERB
cana-5830	38	5	historical	historical	ADJ
cana-5830	38	6	satellite	satellite	NOUN
cana-5830	38	7	images	image	NOUN
cana-5830	38	8	,	,	PUNCT
cana-5830	38	9	radar	radar	NOUN
cana-5830	38	10	data	datum	NOUN
cana-5830	38	11	,	,	PUNCT
cana-5830	38	12	and	and	CCONJ
cana-5830	38	13	meteorological	meteorological	ADJ
cana-5830	38	14	sensor	sensor	NOUN
cana-5830	38	15	readings	reading	NOUN
cana-5830	38	16	.	.	PUNCT
cana-5830	39	1	iv.proposed	iv.propose	VERB
cana-5830	39	2	system	system	NOUN
cana-5830	39	3	the	the	DET
cana-5830	39	4	proposed	propose	VERB
cana-5830	39	5	system	system	NOUN
cana-5830	39	6	addresses	address	VERB
cana-5830	39	7	the	the	DET
cana-5830	39	8	limitations	limitation	NOUN
cana-5830	39	9	of	of	ADP
cana-5830	39	10	existing	exist	VERB
cana-5830	39	11	cyclone	cyclone	NOUN
cana-5830	39	12	prediction	prediction	NOUN
cana-5830	39	13	methods	method	NOUN
cana-5830	39	14	by	by	ADP
cana-5830	39	15	introducing	introduce	VERB
cana-5830	39	16	a	a	DET
cana-5830	39	17	czekanowsky	czekanowsky	ADJ
cana-5830	39	18	hypergraph	hypergraph	NOUN
cana-5830	39	19	-	-	PUNCT
cana-5830	39	20	based	base	VERB
cana-5830	39	21	deep	deep	ADJ
cana-5830	39	22	learning	learning	NOUN
cana-5830	39	23	framework	framework	NOUN
cana-5830	39	24	combined	combine	VERB
cana-5830	39	25	with	with	ADP
cana-5830	39	26	random	random	ADJ
cana-5830	39	27	forest	forest	NOUN
cana-5830	39	28	and	and	CCONJ
cana-5830	39	29	knn	knn	PROPN
cana-5830	39	30	classifiers	classifier	NOUN
cana-5830	39	31	.	.	PUNCT
cana-5830	40	1	the	the	DET
cana-5830	40	2	system	system	NOUN
cana-5830	40	3	constructs	construct	VERB
cana-5830	40	4	a	a	DET
cana-5830	40	5	hypergraph	hypergraph	NOUN
cana-5830	40	6	from	from	ADP
cana-5830	40	7	meteorological	meteorological	ADJ
cana-5830	40	8	data	datum	NOUN
cana-5830	40	9	using	use	VERB
cana-5830	40	10	the	the	DET
cana-5830	40	11	czekanowsky	czekanowsky	ADJ
cana-5830	40	12	similarity	similarity	NOUN
cana-5830	40	13	measure	measure	NOUN
cana-5830	40	14	to	to	PART
cana-5830	40	15	represent	represent	VERB
cana-5830	40	16	high	high	ADJ
cana-5830	40	17	-	-	PUNCT
cana-5830	40	18	order	order	NOUN
cana-5830	40	19	interactions	interaction	NOUN
cana-5830	40	20	among	among	ADP
cana-5830	40	21	features	feature	NOUN
cana-5830	40	22	such	such	ADJ
cana-5830	40	23	as	as	ADP
cana-5830	40	24	humidity	humidity	NOUN
cana-5830	40	25	,	,	PUNCT
cana-5830	40	26	temperature	temperature	NOUN
cana-5830	40	27	,	,	PUNCT
cana-5830	40	28	wind	wind	NOUN
cana-5830	40	29	speed	speed	NOUN
cana-5830	40	30	,	,	PUNCT
cana-5830	40	31	and	and	CCONJ
cana-5830	40	32	pressure	pressure	NOUN
cana-5830	40	33	.	.	PUNCT
cana-5830	41	1	a	a	DET
cana-5830	41	2	cnn	cnn	PROPN
cana-5830	41	3	model	model	NOUN
cana-5830	41	4	is	be	AUX
cana-5830	41	5	applied	apply	VERB
cana-5830	41	6	on	on	ADP
cana-5830	41	7	the	the	DET
cana-5830	41	8	hypergraph	hypergraph	NOUN
cana-5830	41	9	structure	structure	NOUN
cana-5830	41	10	to	to	PART
cana-5830	41	11	extract	extract	VERB
cana-5830	41	12	robust	robust	ADJ
cana-5830	41	13	spatial	spatial	ADJ
cana-5830	41	14	and	and	CCONJ
cana-5830	41	15	temporal	temporal	ADJ
cana-5830	41	16	features	feature	NOUN
cana-5830	41	17	for	for	ADP
cana-5830	41	18	cyclone	cyclone	NOUN
cana-5830	41	19	prediction	prediction	NOUN
cana-5830	41	20	.	.	PUNCT
cana-5830	42	1	additionally	additionally	ADV
cana-5830	42	2	,	,	PUNCT
cana-5830	42	3	rf	rf	PRON
cana-5830	42	4	and	and	CCONJ
cana-5830	42	5	knn	knn	PROPN
cana-5830	42	6	models	model	NOUN
cana-5830	42	7	are	be	AUX
cana-5830	42	8	trained	train	VERB
cana-5830	42	9	on	on	ADP
cana-5830	42	10	the	the	DET
cana-5830	42	11	same	same	ADJ
cana-5830	42	12	feature	feature	NOUN
cana-5830	42	13	sets	set	NOUN
cana-5830	42	14	to	to	PART
cana-5830	42	15	provide	provide	VERB
cana-5830	42	16	alternative	alternative	ADJ
cana-5830	42	17	and	and	CCONJ
cana-5830	42	18	ensemble	ensemble	ADJ
cana-5830	42	19	prediction	prediction	NOUN
cana-5830	42	20	outputs	output	NOUN
cana-5830	42	21	,	,	PUNCT
cana-5830	42	22	enhancing	enhance	VERB
cana-5830	42	23	interpretability	interpretability	NOUN
cana-5830	42	24	and	and	CCONJ
cana-5830	42	25	performance	performance	NOUN
cana-5830	42	26	.	.	PUNCT
cana-5830	43	1	v.system	v.system	NOUN
cana-5830	43	2	architecture	architecture	NOUN
cana-5830	43	3	fig	fig	NOUN
cana-5830	43	4	5.1	5.1	NUM
cana-5830	43	5	system	system	NOUN
cana-5830	43	6	architecture	architecture	NOUN
cana-5830	43	7	communications	communication	NOUN
cana-5830	43	8	on	on	ADP
cana-5830	43	9	applied	apply	VERB
cana-5830	43	10	nonlinear	nonlinear	ADJ
cana-5830	43	11	analysis	analysis	NOUN
cana-5830	43	12	issn	issn	NOUN
cana-5830	43	13	:	:	PUNCT
cana-5830	43	14	1074	1074	NUM
cana-5830	43	15	-	-	PUNCT
cana-5830	43	16	133x	133x	NUM
cana-5830	43	17	vol	vol	VERB
cana-5830	43	18	32	32	NUM
cana-5830	43	19	no	no	NOUN
cana-5830	43	20	.	.	PUNCT
cana-5830	44	1	10s	10	NOUN
cana-5830	44	2	(	(	PUNCT
cana-5830	44	3	2025	2025	NUM
cana-5830	44	4	)	)	PUNCT
cana-5830	44	5	2962	2962	NUM
cana-5830	44	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5830	45	1	this	this	DET
cana-5830	45	2	system	system	NOUN
cana-5830	45	3	architecture	architecture	NOUN
cana-5830	45	4	represents	represent	VERB
cana-5830	45	5	a	a	DET
cana-5830	45	6	flask	flask	NOUN
cana-5830	45	7	-	-	PUNCT
cana-5830	45	8	based	base	VERB
cana-5830	45	9	machine	machine	NOUN
cana-5830	45	10	learning	learn	VERB
cana-5830	45	11	web	web	NOUN
cana-5830	45	12	application	application	NOUN
cana-5830	45	13	where	where	SCONJ
cana-5830	45	14	users	user	NOUN
cana-5830	45	15	interact	interact	VERB
cana-5830	45	16	through	through	ADP
cana-5830	45	17	a	a	DET
cana-5830	45	18	web	web	NOUN
cana-5830	45	19	browser	browser	NOUN
cana-5830	45	20	to	to	PART
cana-5830	45	21	perform	perform	VERB
cana-5830	45	22	tasks	task	NOUN
cana-5830	45	23	like	like	ADP
cana-5830	45	24	login	login	NOUN
cana-5830	45	25	,	,	PUNCT
cana-5830	45	26	dataset	dataset	NOUN
cana-5830	45	27	upload	upload	NOUN
cana-5830	45	28	,	,	PUNCT
cana-5830	45	29	training	training	NOUN
cana-5830	45	30	,	,	PUNCT
cana-5830	45	31	and	and	CCONJ
cana-5830	45	32	prediction	prediction	NOUN
cana-5830	45	33	.	.	PUNCT
cana-5830	46	1	the	the	DET
cana-5830	46	2	user	user	NOUN
cana-5830	46	3	interface	interface	NOUN
cana-5830	46	4	sends	send	VERB
cana-5830	46	5	http	http	NOUN
cana-5830	46	6	requests	request	NOUN
cana-5830	46	7	to	to	ADP
cana-5830	46	8	the	the	DET
cana-5830	46	9	flask	flask	NOUN
cana-5830	46	10	backend	backend	NOUN
cana-5830	46	11	,	,	PUNCT
cana-5830	46	12	which	which	PRON
cana-5830	46	13	contains	contain	VERB
cana-5830	46	14	modules	module	NOUN
cana-5830	46	15	for	for	ADP
cana-5830	46	16	authentication	authentication	NOUN
cana-5830	46	17	,	,	PUNCT
cana-5830	46	18	dataset	dataset	NOUN
cana-5830	46	19	upload	upload	NOUN
cana-5830	46	20	,	,	PUNCT
cana-5830	46	21	preprocessing	preprocessing	NOUN
cana-5830	46	22	,	,	PUNCT
cana-5830	46	23	model	model	NOUN
cana-5830	46	24	training	training	NOUN
cana-5830	46	25	,	,	PUNCT
cana-5830	46	26	evaluation	evaluation	NOUN
cana-5830	46	27	,	,	PUNCT
cana-5830	46	28	and	and	CCONJ
cana-5830	46	29	prediction	prediction	NOUN
cana-5830	46	30	.	.	PUNCT
cana-5830	47	1	the	the	DET
cana-5830	47	2	backend	backend	NOUN
cana-5830	47	3	communicates	communicate	VERB
cana-5830	47	4	with	with	ADP
cana-5830	47	5	a	a	DET
cana-5830	47	6	machine	machine	NOUN
cana-5830	47	7	learning	learn	VERB
cana-5830	47	8	layer	layer	NOUN
cana-5830	47	9	that	that	PRON
cana-5830	47	10	supports	support	VERB
cana-5830	47	11	random	random	ADJ
cana-5830	47	12	forest	forest	NOUN
cana-5830	47	13	,	,	PUNCT
cana-5830	47	14	knn	knn	PROPN
cana-5830	47	15	,	,	PUNCT
cana-5830	47	16	and	and	CCONJ
cana-5830	47	17	1d	1d	NUM
cana-5830	47	18	cnn	cnn	NOUN
cana-5830	47	19	models	model	NOUN
cana-5830	47	20	to	to	PART
cana-5830	47	21	train	train	VERB
cana-5830	47	22	or	or	CCONJ
cana-5830	47	23	predict	predict	VERB
cana-5830	47	24	based	base	VERB
cana-5830	47	25	on	on	ADP
cana-5830	47	26	user	user	NOUN
cana-5830	47	27	-	-	PUNCT
cana-5830	47	28	uploaded	upload	VERB
cana-5830	47	29	data	datum	NOUN
cana-5830	47	30	.	.	PUNCT
cana-5830	48	1	it	it	PRON
cana-5830	48	2	also	also	ADV
cana-5830	48	3	interacts	interact	VERB
cana-5830	48	4	with	with	ADP
cana-5830	48	5	a	a	DET
cana-5830	48	6	data	data	NOUN
cana-5830	48	7	layer	layer	NOUN
cana-5830	48	8	consisting	consist	VERB
cana-5830	48	9	of	of	ADP
cana-5830	48	10	an	an	DET
cana-5830	48	11	sqlite	sqlite	ADJ
cana-5830	48	12	database	database	NOUN
cana-5830	48	13	and	and	CCONJ
cana-5830	48	14	uploaded	upload	VERB
cana-5830	48	15	csv	csv	VERB
cana-5830	48	16	files	file	NOUN
cana-5830	48	17	to	to	PART
cana-5830	48	18	store	store	VERB
cana-5830	48	19	user	user	NOUN
cana-5830	48	20	information	information	NOUN
cana-5830	48	21	,	,	PUNCT
cana-5830	48	22	datasets	dataset	NOUN
cana-5830	48	23	,	,	PUNCT
cana-5830	48	24	and	and	CCONJ
cana-5830	48	25	model	model	NOUN
cana-5830	48	26	accuracy	accuracy	NOUN
cana-5830	48	27	results	result	NOUN
cana-5830	48	28	.	.	PUNCT
cana-5830	49	1	vi.implementation	vi.implementation	NOUN
cana-5830	49	2	fig	fig	NOUN
cana-5830	49	3	6.1	6.1	NUM
cana-5830	49	4	home	home	NOUN
cana-5830	49	5	page	page	NOUN
cana-5830	49	6	fig	fig	NOUN
cana-5830	49	7	6.2	6.2	NUM
cana-5830	49	8	user	user	NOUN
cana-5830	49	9	login	login	NOUN
cana-5830	49	10	page	page	NOUN
cana-5830	49	11	fig	fig	NOUN
cana-5830	49	12	6.3	6.3	NUM
cana-5830	49	13	user	user	NOUN
cana-5830	49	14	home	home	NOUN
cana-5830	49	15	page	page	NOUN
cana-5830	49	16	fig	fig	NOUN
cana-5830	49	17	6.4	6.4	NUM
cana-5830	49	18	upload	upload	VERB
cana-5830	49	19	dataset	dataset	NOUN
cana-5830	49	20	communications	communication	NOUN
cana-5830	49	21	on	on	ADP
cana-5830	49	22	applied	apply	VERB
cana-5830	49	23	nonlinear	nonlinear	ADJ
cana-5830	49	24	analysis	analysis	NOUN
cana-5830	49	25	issn	issn	NOUN
cana-5830	49	26	:	:	PUNCT
cana-5830	49	27	1074	1074	NUM
cana-5830	49	28	-	-	PUNCT
cana-5830	49	29	133x	133x	NUM
cana-5830	49	30	vol	vol	VERB
cana-5830	49	31	32	32	NUM
cana-5830	49	32	no	no	NOUN
cana-5830	49	33	.	.	PUNCT
cana-5830	50	1	10s	10	NOUN
cana-5830	50	2	(	(	PUNCT
cana-5830	50	3	2025	2025	NUM
cana-5830	50	4	)	)	PUNCT
cana-5830	50	5	2963	2963	NUM
cana-5830	50	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5830	50	7	fig	fig	NOUN
cana-5830	50	8	6.5	6.5	NUM
cana-5830	50	9	training	training	NOUN
cana-5830	50	10	fig	fig	NOUN
cana-5830	50	11	6.5	6.5	NUM
cana-5830	50	12	prediction	prediction	NOUN
cana-5830	50	13	page	page	NOUN
cana-5830	50	14	fig	fig	NOUN
cana-5830	50	15	6.5	6.5	NUM
cana-5830	50	16	afterprediction	afterprediction	NOUN
cana-5830	50	17	vii.conclusion	vii.conclusion	NOUN
cana-5830	50	18	this	this	DET
cana-5830	50	19	study	study	NOUN
cana-5830	50	20	presents	present	VERB
cana-5830	50	21	a	a	DET
cana-5830	50	22	novel	novel	ADJ
cana-5830	50	23	cyclone	cyclone	NOUN
cana-5830	50	24	prediction	prediction	NOUN
cana-5830	50	25	framework	framework	NOUN
cana-5830	50	26	leveraging	leverage	VERB
cana-5830	50	27	czekanowsky	czekanowsky	ADJ
cana-5830	50	28	hypergraph	hypergraph	NOUN
cana-5830	50	29	-	-	PUNCT
cana-5830	50	30	based	base	VERB
cana-5830	50	31	deep	deep	ADJ
cana-5830	50	32	learning	learning	NOUN
cana-5830	50	33	integrated	integrate	VERB
cana-5830	50	34	with	with	ADP
cana-5830	50	35	rf	rf	NOUN
cana-5830	50	36	and	and	CCONJ
cana-5830	50	37	knn	knn	PROPN
cana-5830	50	38	classifiers	classifier	NOUN
cana-5830	50	39	.	.	PUNCT
cana-5830	51	1	experimental	experimental	ADJ
cana-5830	51	2	results	result	NOUN
cana-5830	51	3	demonstrate	demonstrate	VERB
cana-5830	51	4	improved	improved	ADJ
cana-5830	51	5	prediction	prediction	NOUN
cana-5830	51	6	accuracy	accuracy	NOUN
cana-5830	51	7	and	and	CCONJ
cana-5830	51	8	robustness	robustness	NOUN
cana-5830	51	9	over	over	ADP
cana-5830	51	10	existing	exist	VERB
cana-5830	51	11	lstm	lstm	NOUN
cana-5830	51	12	-	-	PUNCT
cana-5830	51	13	based	base	VERB
cana-5830	51	14	and	and	CCONJ
cana-5830	51	15	physical	physical	ADJ
cana-5830	51	16	simulation	simulation	NOUN
cana-5830	51	17	models	model	NOUN
cana-5830	51	18	.	.	PUNCT
cana-5830	52	1	by	by	ADP
cana-5830	52	2	effectively	effectively	ADV
cana-5830	52	3	modeling	model	VERB
cana-5830	52	4	complex	complex	ADJ
cana-5830	52	5	atmospheric	atmospheric	ADJ
cana-5830	52	6	interactions	interaction	NOUN
cana-5830	52	7	and	and	CCONJ
cana-5830	52	8	combining	combine	VERB
cana-5830	52	9	deep	deep	ADJ
cana-5830	52	10	learning	learning	NOUN
cana-5830	52	11	with	with	ADP
cana-5830	52	12	traditional	traditional	ADJ
cana-5830	52	13	ml	ml	NOUN
cana-5830	52	14	models	model	NOUN
cana-5830	52	15	,	,	PUNCT
cana-5830	52	16	the	the	DET
cana-5830	52	17	system	system	NOUN
cana-5830	52	18	provides	provide	VERB
cana-5830	52	19	an	an	DET
cana-5830	52	20	efficient	efficient	ADJ
cana-5830	52	21	tool	tool	NOUN
cana-5830	52	22	for	for	ADP
cana-5830	52	23	early	early	ADJ
cana-5830	52	24	cyclone	cyclone	NOUN
cana-5830	52	25	detection	detection	NOUN
cana-5830	52	26	and	and	CCONJ
cana-5830	52	27	intensity	intensity	NOUN
cana-5830	52	28	forecasting	forecasting	NOUN
cana-5830	52	29	.	.	PUNCT
cana-5830	53	1	this	this	DET
cana-5830	53	2	framework	framework	NOUN
cana-5830	53	3	holds	hold	VERB
cana-5830	53	4	promise	promise	NOUN
cana-5830	53	5	for	for	ADP
cana-5830	53	6	enhancing	enhance	VERB
cana-5830	53	7	meteorological	meteorological	ADJ
cana-5830	53	8	disaster	disaster	NOUN
cana-5830	53	9	preparedness	preparedness	NOUN
cana-5830	53	10	and	and	CCONJ
cana-5830	53	11	mitigating	mitigate	VERB
cana-5830	53	12	cyclone	cyclone	NOUN
cana-5830	53	13	impact	impact	NOUN
cana-5830	53	14	.	.	PUNCT
cana-5830	54	1	viii.future	viii.future	NUM
cana-5830	54	2	scope	scope	NOUN
cana-5830	54	3	future	future	ADJ
cana-5830	54	4	work	work	NOUN
cana-5830	54	5	can	can	AUX
cana-5830	54	6	extend	extend	VERB
cana-5830	54	7	this	this	DET
cana-5830	54	8	approach	approach	NOUN
cana-5830	54	9	by	by	ADP
cana-5830	54	10	integrating	integrate	VERB
cana-5830	54	11	additional	additional	ADJ
cana-5830	54	12	data	datum	NOUN
cana-5830	54	13	sources	source	NOUN
cana-5830	54	14	such	such	ADJ
cana-5830	54	15	as	as	ADP
cana-5830	54	16	real	real	ADJ
cana-5830	54	17	-	-	PUNCT
cana-5830	54	18	time	time	NOUN
cana-5830	54	19	satellite	satellite	NOUN
cana-5830	54	20	imagery	imagery	NOUN
cana-5830	54	21	,	,	PUNCT
cana-5830	54	22	ocean	ocean	NOUN
cana-5830	54	23	temperature	temperature	NOUN
cana-5830	54	24	maps	map	NOUN
cana-5830	54	25	,	,	PUNCT
cana-5830	54	26	and	and	CCONJ
cana-5830	54	27	atmospheric	atmospheric	ADJ
cana-5830	54	28	pressure	pressure	NOUN
cana-5830	54	29	grids	grid	NOUN
cana-5830	54	30	.	.	PUNCT
cana-5830	55	1	the	the	DET
cana-5830	55	2	system	system	NOUN
cana-5830	55	3	can	can	AUX
cana-5830	55	4	be	be	AUX
cana-5830	55	5	enhanced	enhance	VERB
cana-5830	55	6	with	with	ADP
cana-5830	55	7	graph	graph	NOUN
cana-5830	55	8	neural	neural	ADJ
cana-5830	55	9	networks	network	NOUN
cana-5830	55	10	(	(	PUNCT
cana-5830	55	11	gnns	gnns	NOUN
cana-5830	55	12	)	)	PUNCT
cana-5830	55	13	to	to	PART
cana-5830	55	14	better	well	ADV
cana-5830	55	15	leverage	leverage	VERB
cana-5830	55	16	the	the	DET
cana-5830	55	17	hypergraph	hypergraph	NOUN
cana-5830	55	18	structure	structure	NOUN
cana-5830	55	19	.	.	PUNCT
cana-5830	56	1	further	far	ADV
cana-5830	56	2	,	,	PUNCT
cana-5830	56	3	implementing	implement	VERB
cana-5830	56	4	attention	attention	NOUN
cana-5830	56	5	mechanisms	mechanism	NOUN
cana-5830	56	6	may	may	AUX
cana-5830	56	7	improve	improve	VERB
cana-5830	56	8	feature	feature	NOUN
cana-5830	56	9	extraction	extraction	NOUN
cana-5830	56	10	by	by	ADP
cana-5830	56	11	focusing	focus	VERB
cana-5830	56	12	on	on	ADP
cana-5830	56	13	critical	critical	ADJ
cana-5830	56	14	variables	variable	NOUN
cana-5830	56	15	.	.	PUNCT
cana-5830	57	1	deployment	deployment	NOUN
cana-5830	57	2	as	as	ADP
cana-5830	57	3	a	a	DET
cana-5830	57	4	real	real	ADJ
cana-5830	57	5	-	-	PUNCT
cana-5830	57	6	time	time	NOUN
cana-5830	57	7	cyclone	cyclone	NOUN
cana-5830	57	8	early	early	ADJ
cana-5830	57	9	warning	warning	NOUN
cana-5830	57	10	system	system	NOUN
cana-5830	57	11	with	with	ADP
cana-5830	57	12	mobile	mobile	ADJ
cana-5830	57	13	and	and	CCONJ
cana-5830	57	14	web	web	NOUN
cana-5830	57	15	interfaces	interface	NOUN
cana-5830	57	16	would	would	AUX
cana-5830	57	17	maximize	maximize	VERB
cana-5830	57	18	its	its	PRON
cana-5830	57	19	practical	practical	ADJ
cana-5830	57	20	utility	utility	NOUN
cana-5830	57	21	.	.	PUNCT
cana-5830	58	1	finally	finally	ADV
cana-5830	58	2	,	,	PUNCT
cana-5830	58	3	expanding	expand	VERB
cana-5830	58	4	the	the	DET
cana-5830	58	5	model	model	NOUN
cana-5830	58	6	to	to	PART
cana-5830	58	7	predict	predict	VERB
cana-5830	58	8	cyclone	cyclone	NOUN
cana-5830	58	9	trajectories	trajectory	NOUN
cana-5830	58	10	and	and	CCONJ
cana-5830	58	11	landfall	landfall	ADJ
cana-5830	58	12	impact	impact	NOUN
cana-5830	58	13	zones	zone	NOUN
cana-5830	58	14	can	can	AUX
cana-5830	58	15	provide	provide	VERB
cana-5830	58	16	comprehensive	comprehensive	ADJ
cana-5830	58	17	disaster	disaster	NOUN
cana-5830	58	18	management	management	NOUN
cana-5830	58	19	support	support	NOUN
cana-5830	58	20	.	.	PUNCT
cana-5830	59	1	communications	communication	NOUN
cana-5830	59	2	on	on	ADP
cana-5830	59	3	applied	apply	VERB
cana-5830	59	4	nonlinear	nonlinear	ADJ
cana-5830	59	5	analysis	analysis	NOUN
cana-5830	59	6	issn	issn	NOUN
cana-5830	59	7	:	:	PUNCT
cana-5830	59	8	1074	1074	NUM
cana-5830	59	9	-	-	PUNCT
cana-5830	59	10	133x	133x	NUM
cana-5830	59	11	vol	vol	VERB
cana-5830	59	12	32	32	NUM
cana-5830	59	13	no	no	NOUN
cana-5830	59	14	.	.	PUNCT
cana-5830	60	1	10s	10	NOUN
cana-5830	60	2	(	(	PUNCT
cana-5830	60	3	2025	2025	NUM
cana-5830	60	4	)	)	PUNCT
cana-5830	60	5	2964	2964	NUM
cana-5830	60	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-5830	60	7	references	reference	NOUN
cana-5830	60	8	1	1	NUM
cana-5830	60	9	.	.	PUNCT
cana-5830	61	1	kumar	kumar	PROPN
cana-5830	61	2	,	,	PUNCT
cana-5830	61	3	a.	a.	PROPN
cana-5830	61	4	,	,	PUNCT
cana-5830	61	5	et	et	PROPN
cana-5830	61	6	al	al	PROPN
cana-5830	61	7	.	.	PUNCT
cana-5830	62	1	“	"	PUNCT
cana-5830	62	2	cyclone	cyclone	NOUN
cana-5830	62	3	prediction	prediction	NOUN
cana-5830	62	4	using	use	VERB
cana-5830	62	5	lstm	lstm	ADJ
cana-5830	62	6	networks	network	NOUN
cana-5830	62	7	.	.	PUNCT
cana-5830	62	8	”	"	PUNCT
cana-5830	63	1	journal	journal	NOUN
cana-5830	63	2	of	of	ADP
cana-5830	63	3	atmospheric	atmospheric	ADJ
cana-5830	63	4	sciences	science	NOUN
cana-5830	63	5	,	,	PUNCT
cana-5830	63	6	2020	2020	NUM
cana-5830	63	7	.	.	PUNCT
cana-5830	64	1	2	2	X
cana-5830	64	2	.	.	X
cana-5830	64	3	lee	lee	PROPN
cana-5830	64	4	,	,	PUNCT
cana-5830	64	5	j.	j.	PROPN
cana-5830	64	6	,	,	PUNCT
cana-5830	64	7	park	park	NOUN
cana-5830	64	8	,	,	PUNCT
cana-5830	64	9	m.	m.	NOUN
cana-5830	64	10	“	"	PUNCT
cana-5830	64	11	hypergraph	hypergraph	NOUN
cana-5830	64	12	-	-	PUNCT
cana-5830	64	13	based	base	VERB
cana-5830	64	14	deep	deep	ADJ
cana-5830	64	15	learning	learning	NOUN
cana-5830	64	16	for	for	ADP
cana-5830	64	17	weather	weather	NOUN
cana-5830	64	18	forecasting	forecasting	NOUN
cana-5830	64	19	.	.	PUNCT
cana-5830	64	20	”	"	PUNCT
cana-5830	65	1	ieee	ieee	NOUN
cana-5830	65	2	transactions	transaction	NOUN
cana-5830	65	3	on	on	ADP
cana-5830	65	4	neural	neural	ADJ
cana-5830	65	5	networks	network	NOUN
cana-5830	65	6	,	,	PUNCT
cana-5830	65	7	2022	2022	NUM
cana-5830	65	8	.	.	PUNCT
cana-5830	66	1	3	3	X
cana-5830	66	2	.	.	X
cana-5830	66	3	gupta	gupta	PROPN
cana-5830	66	4	,	,	PUNCT
cana-5830	66	5	s.	s.	PROPN
cana-5830	66	6	,	,	PUNCT
cana-5830	66	7	sharma	sharma	PROPN
cana-5830	66	8	,	,	PUNCT
cana-5830	66	9	r.	r.	PROPN
cana-5830	66	10	“	"	PUNCT
cana-5830	66	11	ensemble	ensemble	ADJ
cana-5830	66	12	machine	machine	NOUN
cana-5830	66	13	learning	learn	VERB
cana-5830	66	14	for	for	ADP
cana-5830	66	15	cyclone	cyclone	NOUN
cana-5830	66	16	detection	detection	NOUN
cana-5830	66	17	.	.	PUNCT
cana-5830	66	18	”	"	PUNCT
cana-5830	67	1	environmental	environmental	ADJ
cana-5830	67	2	modelling	modelling	NOUN
cana-5830	67	3	&	&	CCONJ
cana-5830	67	4	software	software	NOUN
cana-5830	67	5	,	,	PUNCT
cana-5830	67	6	2021	2021	NUM
cana-5830	67	7	.	.	PUNCT
cana-5830	68	1	4	4	NUM
cana-5830	68	2	.	.	X
cana-5830	68	3	zhang	zhang	PROPN
cana-5830	68	4	,	,	PUNCT
cana-5830	68	5	l.	l.	PROPN
cana-5830	68	6	,	,	PUNCT
cana-5830	68	7	et	et	PROPN
cana-5830	68	8	al	al	PROPN
cana-5830	68	9	.	.	PUNCT
cana-5830	69	1	“	"	PUNCT
cana-5830	69	2	cnn	cnn	PROPN
cana-5830	69	3	approaches	approach	VERB
cana-5830	69	4	to	to	ADP
cana-5830	69	5	satellite	satellite	NOUN
cana-5830	69	6	image	image	NOUN
cana-5830	69	7	analysis	analysis	NOUN
cana-5830	69	8	in	in	ADP
cana-5830	69	9	cyclone	cyclone	NOUN
cana-5830	69	10	prediction	prediction	NOUN
cana-5830	69	11	.	.	PUNCT
cana-5830	69	12	”	"	PUNCT
cana-5830	70	1	remote	remote	ADJ
cana-5830	70	2	sensing	sense	VERB
cana-5830	70	3	letters	letter	NOUN
cana-5830	70	4	,	,	PUNCT
cana-5830	70	5	2019	2019	NUM
cana-5830	70	6	.	.	PUNCT
cana-5830	71	1	5	5	NUM
cana-5830	71	2	.	.	X
cana-5830	71	3	patel	patel	PROPN
cana-5830	71	4	,	,	PUNCT
cana-5830	71	5	d.	d.	PROPN
cana-5830	71	6	,	,	PUNCT
cana-5830	71	7	singh	singh	PROPN
cana-5830	71	8	,	,	PUNCT
cana-5830	71	9	k.	k.	PUNCT
cana-5830	72	1	“	"	PUNCT
cana-5830	72	2	application	application	NOUN
cana-5830	72	3	of	of	ADP
cana-5830	72	4	czekanowsky	czekanowsky	ADJ
cana-5830	72	5	similarity	similarity	NOUN
cana-5830	72	6	in	in	ADP
cana-5830	72	7	climate	climate	NOUN
cana-5830	72	8	data	datum	NOUN
cana-5830	72	9	analysis	analysis	NOUN
cana-5830	72	10	.	.	PUNCT
cana-5830	72	11	”	"	PUNCT
cana-5830	73	1	climate	climate	NOUN
cana-5830	73	2	informatics	informatic	NOUN
cana-5830	73	3	journal	journal	NOUN
cana-5830	73	4	,	,	PUNCT
cana-5830	73	5	2023	2023	NUM
cana-5830	73	6	.	.	PUNCT
cana-5830	74	1	6	6	NUM
cana-5830	74	2	.	.	X
cana-5830	74	3	noaa	noaa	NOUN
cana-5830	74	4	,	,	PUNCT
cana-5830	74	5	“	"	PUNCT
cana-5830	74	6	cyclone	cyclone	NOUN
cana-5830	74	7	data	datum	NOUN
cana-5830	74	8	archive	archive	NOUN
cana-5830	74	9	,	,	PUNCT
cana-5830	74	10	”	"	PUNCT
cana-5830	74	11	2018	2018	NUM
cana-5830	74	12	.	.	PUNCT
cana-5830	75	1	7	7	X
cana-5830	75	2	.	.	X
cana-5830	75	3	chollet	chollet	PROPN
cana-5830	75	4	,	,	PUNCT
cana-5830	75	5	f.	f.	NOUN
cana-5830	75	6	“	"	PUNCT
cana-5830	75	7	deep	deep	ADJ
cana-5830	75	8	learning	learning	NOUN
cana-5830	75	9	with	with	ADP
cana-5830	75	10	python	python	PROPN
cana-5830	75	11	.	.	PUNCT
cana-5830	75	12	”	"	PUNCT
cana-5830	76	1	manning	man	VERB
cana-5830	76	2	publications	publication	NOUN
cana-5830	76	3	,	,	PUNCT
cana-5830	76	4	2018	2018	NUM
cana-5830	76	5	.	.	PUNCT
cana-5830	77	1	8	8	X
cana-5830	77	2	.	.	X
cana-5830	77	3	breiman	breiman	NOUN
cana-5830	77	4	,	,	PUNCT
cana-5830	77	5	l.	l.	NOUN
cana-5830	77	6	“	"	PUNCT
cana-5830	77	7	random	random	ADJ
cana-5830	77	8	forests	forest	NOUN
cana-5830	77	9	.	.	PUNCT
cana-5830	77	10	”	"	PUNCT
cana-5830	77	11	machine	machine	NOUN
cana-5830	77	12	learning	learning	NOUN
cana-5830	77	13	,	,	PUNCT
cana-5830	77	14	2001	2001	NUM
cana-5830	77	15	.	.	PUNCT
cana-5830	78	1	9	9	X
cana-5830	78	2	.	.	X
cana-5830	78	3	cover	cover	NOUN
cana-5830	78	4	,	,	PUNCT
cana-5830	78	5	t.	t.	PROPN
cana-5830	78	6	,	,	PUNCT
cana-5830	78	7	hart	hart	PROPN
cana-5830	78	8	,	,	PUNCT
cana-5830	78	9	p.	p.	NOUN
cana-5830	78	10	“	"	PUNCT
cana-5830	78	11	nearest	near	ADJ
cana-5830	78	12	neighbor	neighbor	NOUN
cana-5830	78	13	pattern	pattern	NOUN
cana-5830	78	14	classification	classification	NOUN
cana-5830	78	15	.	.	PUNCT
cana-5830	78	16	”	"	PUNCT
cana-5830	79	1	ieee	ieee	NOUN
cana-5830	79	2	transactions	transaction	NOUN
cana-5830	79	3	on	on	ADP
cana-5830	79	4	information	information	NOUN
cana-5830	79	5	theory	theory	NOUN
cana-5830	79	6	,	,	PUNCT
cana-5830	79	7	1967	1967	NUM
cana-5830	79	8	.	.	PUNCT
cana-5830	80	1	10	10	NUM
cana-5830	80	2	.	.	X
cana-5830	81	1	goodfellow	goodfellow	PROPN
cana-5830	81	2	,	,	PUNCT
cana-5830	81	3	i.	i.	PROPN
cana-5830	81	4	,	,	PUNCT
cana-5830	81	5	et	et	PROPN
cana-5830	81	6	al	al	PROPN
cana-5830	81	7	.	.	PUNCT
cana-5830	82	1	“	"	PUNCT
cana-5830	82	2	deep	deep	ADJ
cana-5830	82	3	learning	learning	NOUN
cana-5830	82	4	.	.	PUNCT
cana-5830	82	5	”	"	PUNCT
cana-5830	83	1	mit	mit	PROPN
cana-5830	83	2	press	press	NOUN
cana-5830	83	3	,	,	PUNCT
cana-5830	83	4	2016	2016	NUM
cana-5830	83	5	.	.	PUNCT
cana-5830	84	1	11	11	NUM
cana-5830	84	2	.	.	PUNCT
cana-5830	85	1	kipf	kipf	ADJ
cana-5830	85	2	,	,	PUNCT
cana-5830	85	3	t.	t.	PROPN
cana-5830	85	4	,	,	PUNCT
cana-5830	85	5	welling	well	VERB
cana-5830	85	6	,	,	PUNCT
cana-5830	85	7	m.	m.	NOUN
cana-5830	85	8	“	"	PUNCT
cana-5830	85	9	semi	semi	ADJ
cana-5830	85	10	-	-	ADJ
cana-5830	85	11	supervised	supervised	ADJ
cana-5830	85	12	classification	classification	NOUN
cana-5830	85	13	with	with	ADP
cana-5830	85	14	graph	graph	NOUN
cana-5830	85	15	convolutional	convolutional	ADJ
cana-5830	85	16	networks	network	NOUN
cana-5830	85	17	.	.	PUNCT
cana-5830	85	18	”	"	PUNCT
cana-5830	86	1	iclr	iclr	NOUN
cana-5830	86	2	,	,	PUNCT
cana-5830	86	3	2017	2017	NUM
cana-5830	86	4	.	.	PUNCT
cana-5830	87	1	12	12	NUM
cana-5830	87	2	.	.	PUNCT
cana-5830	88	1	hamilton	hamilton	PROPN
cana-5830	88	2	,	,	PUNCT
cana-5830	88	3	w.	w.	PROPN
cana-5830	88	4	,	,	PUNCT
cana-5830	88	5	ying	ying	PROPN
cana-5830	88	6	,	,	PUNCT
cana-5830	88	7	z.	z.	PROPN
cana-5830	88	8	,	,	PUNCT
cana-5830	88	9	leskovec	leskovec	PROPN
cana-5830	88	10	,	,	PUNCT
cana-5830	88	11	j.	j.	NOUN
cana-5830	88	12	“	"	PUNCT
cana-5830	88	13	graph	graph	NOUN
cana-5830	88	14	representation	representation	NOUN
cana-5830	88	15	learning	learning	NOUN
cana-5830	88	16	.	.	PUNCT
cana-5830	88	17	”	"	PUNCT
cana-5830	89	1	foundations	foundation	NOUN
cana-5830	89	2	and	and	CCONJ
cana-5830	89	3	trends	trend	NOUN
cana-5830	89	4	in	in	ADP
cana-5830	89	5	machine	machine	NOUN
cana-5830	89	6	learning	learning	NOUN
cana-5830	89	7	,	,	PUNCT
cana-5830	89	8	2017	2017	NUM
cana-5830	89	9	.	.	PUNCT
cana-5830	90	1	13	13	NUM
cana-5830	90	2	.	.	X
cana-5830	91	1	vaswani	vaswani	NOUN
cana-5830	91	2	,	,	PUNCT
cana-5830	91	3	a.	a.	NOUN
cana-5830	91	4	,	,	PUNCT
cana-5830	91	5	et	et	PROPN
cana-5830	91	6	al	al	PROPN
cana-5830	91	7	.	.	PUNCT
cana-5830	92	1	“	"	PUNCT
cana-5830	92	2	attention	attention	NOUN
cana-5830	92	3	is	be	AUX
cana-5830	92	4	all	all	PRON
cana-5830	92	5	you	you	PRON
cana-5830	92	6	need	need	VERB
cana-5830	92	7	.	.	PUNCT
cana-5830	92	8	”	"	PUNCT
cana-5830	92	9	neurips	neurip	NOUN
cana-5830	92	10	,	,	PUNCT
cana-5830	92	11	2017	2017	NUM
cana-5830	92	12	.	.	PUNCT
cana-5830	93	1	14	14	NUM
cana-5830	93	2	.	.	PUNCT
cana-5830	94	1	hochreiter	hochreiter	PROPN
cana-5830	94	2	,	,	PUNCT
cana-5830	94	3	s.	s.	PROPN
cana-5830	94	4	,	,	PUNCT
cana-5830	94	5	schmidhuber	schmidhuber	PROPN
cana-5830	94	6	,	,	PUNCT
cana-5830	94	7	j.	j.	PROPN
cana-5830	94	8	“	"	PUNCT
cana-5830	94	9	long	long	ADJ
cana-5830	94	10	short	short	ADJ
cana-5830	94	11	-	-	PUNCT
cana-5830	94	12	term	term	NOUN
cana-5830	94	13	memory	memory	NOUN
cana-5830	94	14	.	.	PUNCT
cana-5830	94	15	”	"	PUNCT
cana-5830	94	16	neural	neural	ADJ
cana-5830	94	17	computation	computation	NOUN
cana-5830	94	18	,	,	PUNCT
cana-5830	94	19	1997	1997	NUM
cana-5830	94	20	.	.	PUNCT
cana-5830	95	1	15	15	NUM
cana-5830	95	2	.	.	PUNCT
cana-5830	95	3	bishop	bishop	PROPN
cana-5830	95	4	,	,	PUNCT
cana-5830	95	5	c.	c.	NOUN
cana-5830	95	6	“	"	PUNCT
cana-5830	95	7	pattern	pattern	NOUN
cana-5830	95	8	recognition	recognition	NOUN
cana-5830	95	9	and	and	CCONJ
cana-5830	95	10	machine	machine	NOUN
cana-5830	95	11	learning	learning	NOUN
cana-5830	95	12	.	.	PUNCT
cana-5830	95	13	”	"	PUNCT
cana-5830	95	14	springer	springer	NOUN
cana-5830	95	15	,	,	PUNCT
cana-5830	95	16	2006	2006	NUM
cana-5830	95	17	.	.	PUNCT
cana-5830	96	1	16	16	NUM
cana-5830	96	2	.	.	PUNCT
cana-5830	96	3	simonyan	simonyan	PROPN
cana-5830	96	4	,	,	PUNCT
cana-5830	96	5	k.	k.	PROPN
cana-5830	96	6	,	,	PUNCT
cana-5830	96	7	zisserman	zisserman	PROPN
cana-5830	96	8	,	,	PUNCT
cana-5830	96	9	a.	a.	NOUN
cana-5830	96	10	“	"	PUNCT
cana-5830	96	11	very	very	ADV
cana-5830	96	12	deep	deep	ADJ
cana-5830	96	13	convolutional	convolutional	ADJ
cana-5830	96	14	networks	network	NOUN
cana-5830	96	15	for	for	ADP
cana-5830	96	16	large	large	ADJ
cana-5830	96	17	-	-	PUNCT
cana-5830	96	18	scale	scale	NOUN
cana-5830	96	19	image	image	NOUN
cana-5830	96	20	recognition	recognition	NOUN
cana-5830	96	21	.	.	PUNCT
cana-5830	96	22	”	"	PUNCT
cana-5830	97	1	arxiv	arxiv	PROPN
cana-5830	97	2	,	,	PUNCT
cana-5830	97	3	2014	2014	NUM
cana-5830	97	4	.	.	PUNCT
cana-5830	98	1	17	17	NUM
cana-5830	98	2	.	.	PUNCT
cana-5830	99	1	he	he	PRON
cana-5830	99	2	,	,	PUNCT
cana-5830	99	3	k.	k.	PROPN
cana-5830	99	4	,	,	PUNCT
cana-5830	99	5	et	et	PROPN
cana-5830	99	6	al	al	PROPN
cana-5830	99	7	.	.	PUNCT
cana-5830	100	1	“	"	PUNCT
cana-5830	100	2	deep	deep	ADJ
cana-5830	100	3	residual	residual	ADJ
cana-5830	100	4	learning	learning	NOUN
cana-5830	100	5	for	for	ADP
cana-5830	100	6	image	image	NOUN
cana-5830	100	7	recognition	recognition	NOUN
cana-5830	100	8	.	.	PUNCT
cana-5830	100	9	”	"	PUNCT
cana-5830	101	1	cvpr	cvpr	NOUN
cana-5830	101	2	,	,	PUNCT
cana-5830	101	3	2016	2016	NUM
cana-5830	101	4	.	.	PUNCT
cana-5830	102	1	18	18	NUM
cana-5830	102	2	.	.	X
cana-5830	102	3	murphy	murphy	PROPN
cana-5830	102	4	,	,	PUNCT
cana-5830	102	5	k.	k.	PUNCT
cana-5830	102	6	“	"	PUNCT
cana-5830	102	7	machine	machine	NOUN
cana-5830	102	8	learning	learning	NOUN
cana-5830	102	9	:	:	PUNCT
cana-5830	102	10	a	a	DET
cana-5830	102	11	probabilistic	probabilistic	ADJ
cana-5830	102	12	perspective	perspective	NOUN
cana-5830	102	13	.	.	PUNCT
cana-5830	102	14	”	"	PUNCT
cana-5830	103	1	mit	mit	PROPN
cana-5830	103	2	press	press	NOUN
cana-5830	103	3	,	,	PUNCT
cana-5830	103	4	2012	2012	NUM
cana-5830	103	5	.	.	PUNCT
cana-5830	104	1	19	19	NUM
cana-5830	104	2	.	.	X
cana-5830	104	3	huang	huang	PROPN
cana-5830	104	4	,	,	PUNCT
cana-5830	104	5	g.	g.	PROPN
cana-5830	104	6	,	,	PUNCT
cana-5830	104	7	et	et	PROPN
cana-5830	104	8	al	al	PROPN
cana-5830	104	9	.	.	PUNCT
cana-5830	105	1	“	"	PUNCT
cana-5830	105	2	densely	densely	ADV
cana-5830	105	3	connected	connect	VERB
cana-5830	105	4	convolutional	convolutional	ADJ
cana-5830	105	5	networks	network	NOUN
cana-5830	105	6	.	.	PUNCT
cana-5830	105	7	”	"	PUNCT
cana-5830	106	1	cvpr	cvpr	NOUN
cana-5830	106	2	,	,	PUNCT
cana-5830	106	3	2017	2017	NUM
cana-5830	106	4	.	.	PUNCT
cana-5830	107	1	20	20	NUM
cana-5830	107	2	.	.	X
cana-5830	108	1	srivastava	srivastava	PROPN
cana-5830	108	2	,	,	PUNCT
cana-5830	108	3	n.	n.	PROPN
cana-5830	108	4	,	,	PUNCT
cana-5830	108	5	et	et	PROPN
cana-5830	108	6	al	al	PROPN
cana-5830	108	7	.	.	PUNCT
cana-5830	109	1	“	"	PUNCT
cana-5830	109	2	dropout	dropout	NOUN
cana-5830	109	3	:	:	PUNCT
cana-5830	109	4	a	a	DET
cana-5830	109	5	simple	simple	ADJ
cana-5830	109	6	way	way	NOUN
cana-5830	109	7	to	to	PART
cana-5830	109	8	prevent	prevent	VERB
cana-5830	109	9	neural	neural	ADJ
cana-5830	109	10	networks	network	NOUN
cana-5830	109	11	from	from	ADP
cana-5830	109	12	overfitting	overfitte	VERB
cana-5830	109	13	.	.	PUNCT
cana-5830	109	14	”	"	PUNCT
cana-5830	110	1	jmlr	jmlr	NOUN
cana-5830	110	2	,	,	PUNCT
cana-5830	110	3	2014	2014	NUM
cana-5830	110	4	.	.	PUNCT