id	sid	tid	token	lemma	pos
cana-3933	1	1	communications	communication	NOUN
cana-3933	1	2	on	on	ADP
cana-3933	1	3	applied	apply	VERB
cana-3933	1	4	nonlinear	nonlinear	ADJ
cana-3933	1	5	analysis	analysis	NOUN
cana-3933	1	6	issn	issn	NOUN
cana-3933	1	7	:	:	PUNCT
cana-3933	1	8	1074	1074	NUM
cana-3933	1	9	-	-	PUNCT
cana-3933	1	10	133x	133x	NUM
cana-3933	1	11	vol	vol	NOUN
cana-3933	1	12	32	32	NUM
cana-3933	1	13	no	no	NOUN
cana-3933	1	14	.	.	PUNCT
cana-3933	2	1	9s	9s	NUM
cana-3933	2	2	(	(	PUNCT
cana-3933	2	3	2025	2025	NUM
cana-3933	2	4	)	)	PUNCT
cana-3933	2	5	362	362	NUM
cana-3933	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3933	2	7	optimal	optimal	ADJ
cana-3933	2	8	congestion	congestion	NOUN
cana-3933	2	9	control	control	NOUN
cana-3933	2	10	mechanism	mechanism	NOUN
cana-3933	2	11	for	for	ADP
cana-3933	2	12	intelligent	intelligent	ADJ
cana-3933	2	13	routing	routing	NOUN
cana-3933	2	14	to	to	PART
cana-3933	2	15	improve	improve	VERB
cana-3933	2	16	qos	qos	NOUN
cana-3933	2	17	using	use	VERB
cana-3933	2	18	temporal	temporal	ADJ
cana-3933	2	19	deep	deep	ADJ
cana-3933	2	20	learning	learning	NOUN
cana-3933	2	21	1d	1d	NUM
cana-3933	2	22	.	.	PUNCT
cana-3933	3	1	kavitha	kavitha	PROPN
cana-3933	3	2	,	,	PUNCT
cana-3933	3	3	2dr	2dr	NOUN
cana-3933	3	4	.	.	PUNCT
cana-3933	4	1	k.	k.	PROPN
cana-3933	4	2	raghava	raghava	PROPN
cana-3933	4	3	rao	rao	PROPN
cana-3933	4	4	1research	1research	NUM
cana-3933	4	5	scholar	scholar	NOUN
cana-3933	4	6	,	,	PUNCT
cana-3933	4	7	2professor	2professor	NUM
cana-3933	4	8	1research	1research	NUM
cana-3933	4	9	scholar	scholar	NOUN
cana-3933	4	10	,	,	PUNCT
cana-3933	4	11	department	department	NOUN
cana-3933	4	12	of	of	ADP
cana-3933	4	13	cse	cse	PROPN
cana-3933	4	14	,	,	PUNCT
cana-3933	4	15	koneru	koneru	PROPN
cana-3933	4	16	lakshmaiah	lakshmaiah	PROPN
cana-3933	4	17	education	education	PROPN
cana-3933	4	18	foundation	foundation	PROPN
cana-3933	4	19	,	,	PUNCT
cana-3933	4	20	guntur	guntur	PROPN
cana-3933	4	21	2professor	2professor	PROPN
cana-3933	4	22	in	in	ADP
cana-3933	4	23	cse	cse	PROPN
cana-3933	4	24	,	,	PUNCT
cana-3933	4	25	dept	dept	NOUN
cana-3933	4	26	.	.	PROPN
cana-3933	4	27	of	of	ADP
cana-3933	4	28	cse	cse	PROPN
cana-3933	4	29	,	,	PUNCT
cana-3933	4	30	koneru	koneru	PROPN
cana-3933	4	31	lakshmaiah	lakshmaiah	PROPN
cana-3933	4	32	education	education	PROPN
cana-3933	4	33	foundation	foundation	PROPN
cana-3933	4	34	,	,	PUNCT
cana-3933	4	35	guntur	guntur	PROPN
cana-3933	4	36	email	email	NOUN
cana-3933	4	37	:	:	PUNCT
cana-3933	4	38	1davidikavitha2011@gmail.com	1davidikavitha2011@gmail.com	NUM
cana-3933	4	39	,	,	PUNCT
cana-3933	4	40	2krraocse@gmail.com	2krraocse@gmail.com	NUM
cana-3933	4	41	article	article	NOUN
cana-3933	4	42	history	history	NOUN
cana-3933	4	43	:	:	PUNCT
cana-3933	4	44	received	receive	VERB
cana-3933	4	45	:	:	PUNCT
cana-3933	4	46	15	15	NUM
cana-3933	4	47	-	-	SYM
cana-3933	4	48	11	11	NUM
cana-3933	4	49	-	-	PUNCT
cana-3933	4	50	2024	2024	NUM
cana-3933	4	51	revised:26	revised:26	PROPN
cana-3933	4	52	-	-	PUNCT
cana-3933	4	53	12	12	NUM
cana-3933	4	54	-	-	PUNCT
cana-3933	4	55	2024	2024	NUM
cana-3933	4	56	accepted:10	accepted:10	PROPN
cana-3933	4	57	-	-	PUNCT
cana-3933	4	58	01	01	NUM
cana-3933	4	59	-	-	PUNCT
cana-3933	4	60	2025	2025	NUM
cana-3933	4	61	abstract	abstract	NOUN
cana-3933	4	62	:	:	PUNCT
cana-3933	4	63	congestion	congestion	NOUN
cana-3933	4	64	in	in	ADP
cana-3933	4	65	mobile	mobile	ADJ
cana-3933	4	66	ad	ad	NOUN
cana-3933	4	67	-	-	PUNCT
cana-3933	4	68	hoc	hoc	X
cana-3933	4	69	networks	network	NOUN
cana-3933	4	70	(	(	PUNCT
cana-3933	4	71	manets	manet	NOUN
cana-3933	4	72	)	)	PUNCT
cana-3933	4	73	leads	lead	VERB
cana-3933	4	74	to	to	ADP
cana-3933	4	75	connection	connection	NOUN
cana-3933	4	76	failures	failure	NOUN
cana-3933	4	77	,	,	PUNCT
cana-3933	4	78	node	node	ADJ
cana-3933	4	79	loss	loss	NOUN
cana-3933	4	80	,	,	PUNCT
cana-3933	4	81	and	and	CCONJ
cana-3933	4	82	affects	affect	VERB
cana-3933	4	83	network	network	NOUN
cana-3933	4	84	setup	setup	NOUN
cana-3933	4	85	.	.	PUNCT
cana-3933	5	1	manets	manet	NOUN
cana-3933	5	2	,	,	PUNCT
cana-3933	5	3	lacking	lack	VERB
cana-3933	5	4	permanent	permanent	ADJ
cana-3933	5	5	infrastructure	infrastructure	NOUN
cana-3933	5	6	and	and	CCONJ
cana-3933	5	7	central	central	ADJ
cana-3933	5	8	management	management	NOUN
cana-3933	5	9	,	,	PUNCT
cana-3933	5	10	suffer	suffer	VERB
cana-3933	5	11	from	from	ADP
cana-3933	5	12	buffer	buffer	NOUN
cana-3933	5	13	overflow	overflow	NOUN
cana-3933	5	14	and	and	CCONJ
cana-3933	5	15	packet	packet	NOUN
cana-3933	5	16	loss	loss	NOUN
cana-3933	5	17	under	under	ADP
cana-3933	5	18	high	high	ADJ
cana-3933	5	19	traffic	traffic	NOUN
cana-3933	5	20	.	.	PUNCT
cana-3933	6	1	machine	machine	NOUN
cana-3933	6	2	learning	learning	NOUN
cana-3933	6	3	(	(	PUNCT
cana-3933	6	4	ml	ml	NOUN
cana-3933	6	5	)	)	PUNCT
cana-3933	6	6	enhances	enhance	VERB
cana-3933	6	7	quality	quality	NOUN
cana-3933	6	8	of	of	ADP
cana-3933	6	9	service	service	NOUN
cana-3933	6	10	(	(	PUNCT
cana-3933	6	11	qos	qos	PROPN
cana-3933	6	12	)	)	PUNCT
cana-3933	6	13	in	in	ADP
cana-3933	6	14	network	network	NOUN
cana-3933	6	15	routing	routing	NOUN
cana-3933	6	16	.	.	PUNCT
cana-3933	7	1	this	this	DET
cana-3933	7	2	paper	paper	NOUN
cana-3933	7	3	introduces	introduce	VERB
cana-3933	7	4	a	a	DET
cana-3933	7	5	congestion	congestion	NOUN
cana-3933	7	6	control	control	NOUN
cana-3933	7	7	system	system	NOUN
cana-3933	7	8	model	model	NOUN
cana-3933	7	9	with	with	ADP
cana-3933	7	10	node	node	NOUN
cana-3933	7	11	-	-	PUNCT
cana-3933	7	12	level	level	NOUN
cana-3933	7	13	states	state	NOUN
cana-3933	7	14	,	,	PUNCT
cana-3933	7	15	control	control	NOUN
cana-3933	7	16	strategies	strategy	NOUN
cana-3933	7	17	,	,	PUNCT
cana-3933	7	18	and	and	CCONJ
cana-3933	7	19	network	network	NOUN
cana-3933	7	20	optimization	optimization	NOUN
cana-3933	7	21	objectives	objective	NOUN
cana-3933	7	22	.	.	PUNCT
cana-3933	8	1	it	it	PRON
cana-3933	8	2	analyzes	analyze	VERB
cana-3933	8	3	congestion	congestion	NOUN
cana-3933	8	4	state	state	NOUN
cana-3933	8	5	transitions	transition	NOUN
cana-3933	8	6	and	and	CCONJ
cana-3933	8	7	real	real	ADJ
cana-3933	8	8	-	-	PUNCT
cana-3933	8	9	time	time	NOUN
cana-3933	8	10	control	control	NOUN
cana-3933	8	11	to	to	PART
cana-3933	8	12	minimize	minimize	VERB
cana-3933	8	13	network	network	NOUN
cana-3933	8	14	delay	delay	NOUN
cana-3933	8	15	and	and	CCONJ
cana-3933	8	16	congestion	congestion	NOUN
cana-3933	8	17	cost	cost	NOUN
cana-3933	8	18	,	,	PUNCT
cana-3933	8	19	deriving	derive	VERB
cana-3933	8	20	optimal	optimal	ADJ
cana-3933	8	21	strategies	strategy	NOUN
cana-3933	8	22	using	use	VERB
cana-3933	8	23	optimal	optimal	ADJ
cana-3933	8	24	control	control	NOUN
cana-3933	8	25	theory	theory	NOUN
cana-3933	8	26	and	and	CCONJ
cana-3933	8	27	a	a	DET
cana-3933	8	28	congestion	congestion	NOUN
cana-3933	8	29	control	control	NOUN
cana-3933	8	30	discretization	discretization	NOUN
cana-3933	8	31	algorithm	algorithm	NOUN
cana-3933	8	32	(	(	PUNCT
cana-3933	8	33	ccda	ccda	PROPN
cana-3933	8	34	)	)	PUNCT
cana-3933	8	35	.	.	PUNCT
cana-3933	9	1	simulation	simulation	NOUN
cana-3933	9	2	results	result	NOUN
cana-3933	9	3	will	will	AUX
cana-3933	9	4	show	show	VERB
cana-3933	9	5	reduced	reduced	ADJ
cana-3933	9	6	congestion	congestion	NOUN
cana-3933	9	7	across	across	ADP
cana-3933	9	8	nodes	node	NOUN
cana-3933	9	9	with	with	ADP
cana-3933	9	10	ccda	ccda	PROPN
cana-3933	9	11	.	.	PUNCT
cana-3933	10	1	the	the	DET
cana-3933	10	2	impact	impact	NOUN
cana-3933	10	3	of	of	ADP
cana-3933	10	4	parameters	parameter	NOUN
cana-3933	10	5	like	like	ADP
cana-3933	10	6	congestion	congestion	NOUN
cana-3933	10	7	probability	probability	NOUN
cana-3933	10	8	and	and	CCONJ
cana-3933	10	9	delay	delay	VERB
cana-3933	10	10	weight	weight	NOUN
cana-3933	10	11	on	on	ADP
cana-3933	10	12	network	network	NOUN
cana-3933	10	13	loss	loss	NOUN
cana-3933	10	14	is	be	AUX
cana-3933	10	15	also	also	ADV
cana-3933	10	16	explored	explore	VERB
cana-3933	10	17	,	,	PUNCT
cana-3933	10	18	with	with	ADP
cana-3933	10	19	our	our	PRON
cana-3933	10	20	model	model	NOUN
cana-3933	10	21	showing	show	VERB
cana-3933	10	22	lower	low	ADJ
cana-3933	10	23	total	total	ADJ
cana-3933	10	24	loss	loss	NOUN
cana-3933	10	25	than	than	ADP
cana-3933	10	26	baseline	baseline	NOUN
cana-3933	10	27	models	model	NOUN
cana-3933	10	28	,	,	PUNCT
cana-3933	10	29	providing	provide	VERB
cana-3933	10	30	effective	effective	ADJ
cana-3933	10	31	congestion	congestion	NOUN
cana-3933	10	32	control	control	NOUN
cana-3933	10	33	guidance	guidance	NOUN
cana-3933	10	34	for	for	ADP
cana-3933	10	35	deterministic	deterministic	ADJ
cana-3933	10	36	networks	network	NOUN
cana-3933	10	37	.	.	PUNCT
cana-3933	11	1	we	we	PRON
cana-3933	11	2	also	also	ADV
cana-3933	11	3	propose	propose	VERB
cana-3933	11	4	an	an	DET
cana-3933	11	5	intelligent	intelligent	ADJ
cana-3933	11	6	routing	routing	NOUN
cana-3933	11	7	scheme	scheme	NOUN
cana-3933	11	8	for	for	ADP
cana-3933	11	9	manets	manet	NOUN
cana-3933	11	10	with	with	ADP
cana-3933	11	11	directional	directional	ADJ
cana-3933	11	12	antennas	antenna	NOUN
cana-3933	11	13	,	,	PUNCT
cana-3933	11	14	using	use	VERB
cana-3933	11	15	a	a	DET
cana-3933	11	16	spatio	spatio	NOUN
cana-3933	11	17	temporal	temporal	ADJ
cana-3933	11	18	deep	deep	ADJ
cana-3933	11	19	learning	learning	NOUN
cana-3933	11	20	algorithm	algorithm	NOUN
cana-3933	11	21	to	to	PART
cana-3933	11	22	predict	predict	VERB
cana-3933	11	23	traffic	traffic	NOUN
cana-3933	11	24	density	density	NOUN
cana-3933	11	25	in	in	ADP
cana-3933	11	26	a	a	DET
cana-3933	11	27	directional	directional	ADJ
cana-3933	11	28	heat	heat	NOUN
cana-3933	11	29	map	map	NOUN
cana-3933	11	30	.	.	PUNCT
cana-3933	12	1	this	this	DET
cana-3933	12	2	aids	aid	NOUN
cana-3933	12	3	in	in	ADP
cana-3933	12	4	selecting	select	VERB
cana-3933	12	5	optimal	optimal	ADJ
cana-3933	12	6	paths	path	NOUN
cana-3933	12	7	to	to	PART
cana-3933	12	8	avoid	avoid	VERB
cana-3933	12	9	congestion	congestion	NOUN
cana-3933	12	10	and	and	CCONJ
cana-3933	12	11	interference	interference	NOUN
cana-3933	12	12	.	.	PUNCT
cana-3933	13	1	our	our	PRON
cana-3933	13	2	optimization	optimization	NOUN
cana-3933	13	3	algorithm	algorithm	NOUN
cana-3933	13	4	splits	split	VERB
cana-3933	13	5	paths	path	NOUN
cana-3933	13	6	around	around	ADP
cana-3933	13	7	congested	congested	ADJ
cana-3933	13	8	areas	area	NOUN
cana-3933	13	9	,	,	PUNCT
cana-3933	13	10	enhancing	enhance	VERB
cana-3933	13	11	qos	qos	PROPN
cana-3933	13	12	.	.	PUNCT
cana-3933	14	1	additionally	additionally	ADV
cana-3933	14	2	,	,	PUNCT
cana-3933	14	3	we	we	PRON
cana-3933	14	4	introduce	introduce	VERB
cana-3933	14	5	a	a	DET
cana-3933	14	6	novel	novel	ADJ
cana-3933	14	7	algorithm	algorithm	NOUN
cana-3933	14	8	and	and	CCONJ
cana-3933	14	9	buffer	buffer	NOUN
cana-3933	14	10	management	management	NOUN
cana-3933	14	11	technique	technique	NOUN
cana-3933	14	12	to	to	PART
cana-3933	14	13	handle	handle	VERB
cana-3933	14	14	congestion	congestion	NOUN
cana-3933	14	15	,	,	PUNCT
cana-3933	14	16	eliminating	eliminate	VERB
cana-3933	14	17	unnecessary	unnecessary	ADJ
cana-3933	14	18	packets	packet	NOUN
cana-3933	14	19	,	,	PUNCT
cana-3933	14	20	preventing	prevent	VERB
cana-3933	14	21	flooding	flooding	NOUN
cana-3933	14	22	,	,	PUNCT
cana-3933	14	23	and	and	CCONJ
cana-3933	14	24	maintaining	maintain	VERB
cana-3933	14	25	buffer	buffer	NOUN
cana-3933	14	26	levels	level	NOUN
cana-3933	14	27	by	by	ADP
cana-3933	14	28	keeping	keep	VERB
cana-3933	14	29	only	only	ADJ
cana-3933	14	30	essential	essential	ADJ
cana-3933	14	31	data	datum	NOUN
cana-3933	14	32	.	.	PUNCT
cana-3933	15	1	these	these	DET
cana-3933	15	2	methods	method	NOUN
cana-3933	15	3	improve	improve	VERB
cana-3933	15	4	manet	manet	NOUN
cana-3933	15	5	communication	communication	NOUN
cana-3933	15	6	performance	performance	NOUN
cana-3933	15	7	,	,	PUNCT
cana-3933	15	8	supporting	support	VERB
cana-3933	15	9	efficient	efficient	ADJ
cana-3933	15	10	queue	queue	NOUN
cana-3933	15	11	management	management	NOUN
cana-3933	15	12	.	.	PUNCT
cana-3933	16	1	keywords	keyword	NOUN
cana-3933	16	2	:	:	PUNCT
cana-3933	16	3	ml	ml	PROPN
cana-3933	16	4	-	-	PUNCT
cana-3933	16	5	qos	qos	NOUN
cana-3933	16	6	,	,	PUNCT
cana-3933	16	7	congestion	congestion	NOUN
cana-3933	16	8	control	control	NOUN
cana-3933	16	9	,	,	PUNCT
cana-3933	16	10	spatio	spatio	NOUN
cana-3933	16	11	-	-	PUNCT
cana-3933	16	12	temporal	temporal	ADJ
cana-3933	16	13	deep	deep	ADJ
cana-3933	16	14	learning	learning	NOUN
cana-3933	16	15	,	,	PUNCT
cana-3933	16	16	buffer	buffer	VERB
cana-3933	16	17	management	management	NOUN
cana-3933	16	18	1.introduction	1.introduction	NUM
cana-3933	16	19	mobile	mobile	ADJ
cana-3933	16	20	ad	ad	NOUN
cana-3933	16	21	-	-	PUNCT
cana-3933	16	22	hoc	hoc	X
cana-3933	16	23	networks	network	NOUN
cana-3933	16	24	(	(	PUNCT
cana-3933	16	25	manets	manet	NOUN
cana-3933	16	26	)	)	PUNCT
cana-3933	16	27	are	be	AUX
cana-3933	16	28	decentralized	decentralize	VERB
cana-3933	16	29	,	,	PUNCT
cana-3933	16	30	self	self	NOUN
cana-3933	16	31	-	-	PUNCT
cana-3933	16	32	organizing	organize	VERB
cana-3933	16	33	wireless	wireless	ADJ
cana-3933	16	34	networks	network	NOUN
cana-3933	16	35	that	that	PRON
cana-3933	16	36	lack	lack	VERB
cana-3933	16	37	a	a	DET
cana-3933	16	38	fixed	fix	VERB
cana-3933	16	39	infrastructure	infrastructure	NOUN
cana-3933	16	40	and	and	CCONJ
cana-3933	16	41	rely	rely	VERB
cana-3933	16	42	on	on	ADP
cana-3933	16	43	dynamic	dynamic	ADJ
cana-3933	16	44	node	node	ADJ
cana-3933	16	45	cooperation	cooperation	NOUN
cana-3933	16	46	for	for	ADP
cana-3933	16	47	communication	communication	NOUN
cana-3933	16	48	.	.	PUNCT
cana-3933	17	1	due	due	ADP
cana-3933	17	2	to	to	ADP
cana-3933	17	3	their	their	PRON
cana-3933	17	4	inherent	inherent	ADJ
cana-3933	17	5	characteristics	characteristic	NOUN
cana-3933	17	6	,	,	PUNCT
cana-3933	17	7	manets	manet	NOUN
cana-3933	17	8	face	face	VERB
cana-3933	17	9	significant	significant	ADJ
cana-3933	17	10	challenges	challenge	NOUN
cana-3933	17	11	in	in	ADP
cana-3933	17	12	maintaining	maintain	VERB
cana-3933	17	13	quality	quality	NOUN
cana-3933	17	14	of	of	ADP
cana-3933	17	15	service	service	NOUN
cana-3933	17	16	(	(	PUNCT
cana-3933	17	17	qos	qos	PROPN
cana-3933	17	18	)	)	PUNCT
cana-3933	17	19	under	under	ADP
cana-3933	17	20	high	high	ADJ
cana-3933	17	21	traffic	traffic	NOUN
cana-3933	17	22	conditions	condition	NOUN
cana-3933	17	23	,	,	PUNCT
cana-3933	17	24	leading	lead	VERB
cana-3933	17	25	to	to	ADP
cana-3933	17	26	issues	issue	NOUN
cana-3933	17	27	like	like	ADP
cana-3933	17	28	congestion	congestion	NOUN
cana-3933	17	29	,	,	PUNCT
cana-3933	17	30	packet	packet	NOUN
cana-3933	17	31	loss	loss	NOUN
cana-3933	17	32	,	,	PUNCT
cana-3933	17	33	and	and	CCONJ
cana-3933	17	34	connection	connection	NOUN
cana-3933	17	35	failures	failure	NOUN
cana-3933	17	36	[	[	X
cana-3933	17	37	1	1	NUM
cana-3933	17	38	]	]	PUNCT
cana-3933	17	39	.	.	PUNCT
cana-3933	18	1	congestion	congestion	NOUN
cana-3933	18	2	in	in	ADP
cana-3933	18	3	manets	manet	NOUN
cana-3933	18	4	typically	typically	ADV
cana-3933	18	5	occurs	occur	VERB
cana-3933	18	6	due	due	ADJ
cana-3933	18	7	to	to	PART
cana-3933	18	8	buffer	buffer	VERB
cana-3933	18	9	overflow	overflow	NOUN
cana-3933	18	10	at	at	ADP
cana-3933	18	11	intermediate	intermediate	ADJ
cana-3933	18	12	nodes	node	NOUN
cana-3933	18	13	,	,	PUNCT
cana-3933	18	14	which	which	PRON
cana-3933	18	15	not	not	PART
cana-3933	18	16	only	only	ADV
cana-3933	18	17	degrades	degrade	VERB
cana-3933	18	18	network	network	NOUN
cana-3933	18	19	performance	performance	NOUN
cana-3933	18	20	but	but	CCONJ
cana-3933	18	21	also	also	ADV
cana-3933	18	22	results	result	VERB
cana-3933	18	23	in	in	ADP
cana-3933	18	24	increased	increase	VERB
cana-3933	18	25	packet	packet	NOUN
cana-3933	18	26	delay	delay	NOUN
cana-3933	18	27	and	and	CCONJ
cana-3933	18	28	network	network	NOUN
cana-3933	18	29	instability	instability	NOUN
cana-3933	18	30	[	[	X
cana-3933	18	31	2][3	2][3	X
cana-3933	18	32	]	]	PUNCT
cana-3933	18	33	.	.	PUNCT
cana-3933	19	1	machine	machine	NOUN
cana-3933	19	2	learning	learning	NOUN
cana-3933	19	3	(	(	PUNCT
cana-3933	19	4	ml	ml	NOUN
cana-3933	19	5	)	)	PUNCT
cana-3933	19	6	has	have	AUX
cana-3933	19	7	emerged	emerge	VERB
cana-3933	19	8	as	as	ADP
cana-3933	19	9	a	a	DET
cana-3933	19	10	powerful	powerful	ADJ
cana-3933	19	11	tool	tool	NOUN
cana-3933	19	12	for	for	ADP
cana-3933	19	13	enhancing	enhance	VERB
cana-3933	19	14	qos	qos	NOUN
cana-3933	19	15	in	in	ADP
cana-3933	19	16	manets	manet	NOUN
cana-3933	19	17	by	by	ADP
cana-3933	19	18	enabling	enable	VERB
cana-3933	19	19	intelligent	intelligent	ADJ
cana-3933	19	20	routing	routing	NOUN
cana-3933	19	21	and	and	CCONJ
cana-3933	19	22	congestion	congestion	NOUN
cana-3933	19	23	control	control	NOUN
cana-3933	19	24	strategies	strategy	NOUN
cana-3933	19	25	.	.	PUNCT
cana-3933	20	1	ml	ml	NOUN
cana-3933	20	2	models	model	NOUN
cana-3933	20	3	can	can	AUX
cana-3933	20	4	predict	predict	VERB
cana-3933	20	5	network	network	NOUN
cana-3933	20	6	congestion	congestion	NOUN
cana-3933	20	7	,	,	PUNCT
cana-3933	20	8	adapt	adapt	VERB
cana-3933	20	9	routing	routing	NOUN
cana-3933	20	10	paths	path	NOUN
cana-3933	20	11	,	,	PUNCT
cana-3933	20	12	and	and	CCONJ
cana-3933	20	13	optimize	optimize	VERB
cana-3933	20	14	data	data	NOUN
cana-3933	20	15	transmission	transmission	NOUN
cana-3933	20	16	,	,	PUNCT
cana-3933	20	17	thereby	thereby	ADV
cana-3933	20	18	minimizing	minimize	VERB
cana-3933	20	19	packet	packet	NOUN
cana-3933	20	20	loss	loss	NOUN
cana-3933	20	21	and	and	CCONJ
cana-3933	20	22	improving	improve	VERB
cana-3933	20	23	network	network	NOUN
cana-3933	20	24	efficiency	efficiency	NOUN
cana-3933	20	25	[	[	X
cana-3933	20	26	4	4	NUM
cana-3933	20	27	]	]	PUNCT
cana-3933	20	28	.	.	PUNCT
cana-3933	21	1	several	several	ADJ
cana-3933	21	2	studies	study	NOUN
cana-3933	21	3	have	have	AUX
cana-3933	21	4	explored	explore	VERB
cana-3933	21	5	the	the	DET
cana-3933	21	6	application	application	NOUN
cana-3933	21	7	of	of	ADP
cana-3933	21	8	ml	ml	NOUN
cana-3933	21	9	in	in	ADP
cana-3933	21	10	congestion	congestion	NOUN
cana-3933	21	11	control	control	NOUN
cana-3933	21	12	for	for	ADP
cana-3933	21	13	manets	manet	NOUN
cana-3933	21	14	.	.	PUNCT
cana-3933	22	1	communications	communication	NOUN
cana-3933	22	2	on	on	ADP
cana-3933	22	3	applied	apply	VERB
cana-3933	22	4	nonlinear	nonlinear	ADJ
cana-3933	22	5	analysis	analysis	NOUN
cana-3933	22	6	issn	issn	NOUN
cana-3933	22	7	:	:	PUNCT
cana-3933	22	8	1074	1074	NUM
cana-3933	22	9	-	-	PUNCT
cana-3933	22	10	133x	133x	NUM
cana-3933	22	11	vol	vol	NOUN
cana-3933	22	12	32	32	NUM
cana-3933	22	13	no	no	NOUN
cana-3933	22	14	.	.	PUNCT
cana-3933	23	1	9s	9s	NUM
cana-3933	23	2	(	(	PUNCT
cana-3933	23	3	2025	2025	NUM
cana-3933	23	4	)	)	PUNCT
cana-3933	23	5	363	363	NUM
cana-3933	23	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3933	23	7	for	for	ADP
cana-3933	23	8	instance	instance	NOUN
cana-3933	23	9	,	,	PUNCT
cana-3933	23	10	an	an	DET
cana-3933	23	11	ml	ml	NOUN
cana-3933	23	12	-	-	PUNCT
cana-3933	23	13	based	base	VERB
cana-3933	23	14	congestion	congestion	NOUN
cana-3933	23	15	detection	detection	NOUN
cana-3933	23	16	algorithm	algorithm	NOUN
cana-3933	23	17	was	be	AUX
cana-3933	23	18	proposed	propose	VERB
cana-3933	23	19	to	to	PART
cana-3933	23	20	classify	classify	VERB
cana-3933	23	21	congestion	congestion	NOUN
cana-3933	23	22	levels	level	NOUN
cana-3933	23	23	in	in	ADP
cana-3933	23	24	the	the	DET
cana-3933	23	25	network	network	NOUN
cana-3933	23	26	,	,	PUNCT
cana-3933	23	27	thereby	thereby	ADV
cana-3933	23	28	optimizing	optimize	VERB
cana-3933	23	29	packet	packet	NOUN
cana-3933	23	30	transmission	transmission	NOUN
cana-3933	23	31	and	and	CCONJ
cana-3933	23	32	reducing	reduce	VERB
cana-3933	23	33	congestion	congestion	NOUN
cana-3933	24	1	[	[	X
cana-3933	24	2	5	5	NUM
cana-3933	24	3	]	]	PUNCT
cana-3933	24	4	.	.	PUNCT
cana-3933	25	1	another	another	DET
cana-3933	25	2	study	study	NOUN
cana-3933	25	3	highlighted	highlight	VERB
cana-3933	25	4	the	the	DET
cana-3933	25	5	use	use	NOUN
cana-3933	25	6	of	of	ADP
cana-3933	25	7	supervised	supervised	ADJ
cana-3933	25	8	and	and	CCONJ
cana-3933	25	9	unsupervised	unsupervised	ADJ
cana-3933	25	10	learning	learning	NOUN
cana-3933	25	11	techniques	technique	NOUN
cana-3933	25	12	to	to	PART
cana-3933	25	13	enhance	enhance	VERB
cana-3933	25	14	routing	route	VERB
cana-3933	25	15	protocols	protocol	NOUN
cana-3933	25	16	and	and	CCONJ
cana-3933	25	17	improve	improve	VERB
cana-3933	25	18	network	network	NOUN
cana-3933	25	19	stability	stability	NOUN
cana-3933	25	20	[	[	X
cana-3933	25	21	6	6	NUM
cana-3933	25	22	]	]	PUNCT
cana-3933	25	23	.	.	PUNCT
cana-3933	26	1	in	in	ADP
cana-3933	26	2	this	this	DET
cana-3933	26	3	research	research	NOUN
cana-3933	26	4	,	,	PUNCT
cana-3933	26	5	we	we	PRON
cana-3933	26	6	introduce	introduce	VERB
cana-3933	26	7	a	a	DET
cana-3933	26	8	novel	novel	ADJ
cana-3933	26	9	congestion	congestion	NOUN
cana-3933	26	10	control	control	NOUN
cana-3933	26	11	system	system	NOUN
cana-3933	26	12	for	for	ADP
cana-3933	26	13	manets	manet	NOUN
cana-3933	26	14	that	that	PRON
cana-3933	26	15	incorporates	incorporate	VERB
cana-3933	26	16	nodelevel	nodelevel	ADJ
cana-3933	26	17	states	state	NOUN
cana-3933	26	18	,	,	PUNCT
cana-3933	26	19	control	control	NOUN
cana-3933	26	20	strategies	strategy	NOUN
cana-3933	26	21	,	,	PUNCT
cana-3933	26	22	and	and	CCONJ
cana-3933	26	23	network	network	NOUN
cana-3933	26	24	optimization	optimization	NOUN
cana-3933	26	25	objectives	objective	NOUN
cana-3933	26	26	.	.	PUNCT
cana-3933	27	1	the	the	DET
cana-3933	27	2	proposed	propose	VERB
cana-3933	27	3	system	system	NOUN
cana-3933	27	4	employs	employ	VERB
cana-3933	27	5	optimal	optimal	ADJ
cana-3933	27	6	control	control	NOUN
cana-3933	27	7	theory	theory	NOUN
cana-3933	27	8	and	and	CCONJ
cana-3933	27	9	the	the	DET
cana-3933	27	10	congestion	congestion	NOUN
cana-3933	27	11	control	control	NOUN
cana-3933	27	12	discretization	discretization	NOUN
cana-3933	27	13	algorithm	algorithm	NOUN
cana-3933	27	14	(	(	PUNCT
cana-3933	27	15	ccda	ccda	PROPN
cana-3933	27	16	)	)	PUNCT
cana-3933	27	17	to	to	PART
cana-3933	27	18	analyze	analyze	VERB
cana-3933	27	19	congestion	congestion	NOUN
cana-3933	27	20	state	state	NOUN
cana-3933	27	21	transitions	transition	NOUN
cana-3933	27	22	and	and	CCONJ
cana-3933	27	23	implement	implement	VERB
cana-3933	27	24	real	real	ADJ
cana-3933	27	25	-	-	PUNCT
cana-3933	27	26	time	time	NOUN
cana-3933	27	27	control	control	NOUN
cana-3933	27	28	strategies	strategy	NOUN
cana-3933	27	29	.	.	PUNCT
cana-3933	28	1	by	by	ADP
cana-3933	28	2	minimizing	minimize	VERB
cana-3933	28	3	network	network	NOUN
cana-3933	28	4	delay	delay	NOUN
cana-3933	28	5	and	and	CCONJ
cana-3933	28	6	congestion	congestion	NOUN
cana-3933	28	7	costs	cost	NOUN
cana-3933	28	8	,	,	PUNCT
cana-3933	28	9	the	the	DET
cana-3933	28	10	model	model	NOUN
cana-3933	28	11	aims	aim	VERB
cana-3933	28	12	to	to	PART
cana-3933	28	13	improve	improve	VERB
cana-3933	28	14	overall	overall	ADJ
cana-3933	28	15	network	network	NOUN
cana-3933	28	16	performance	performance	NOUN
cana-3933	28	17	[	[	X
cana-3933	28	18	7	7	NUM
cana-3933	28	19	]	]	PUNCT
cana-3933	28	20	.	.	PUNCT
cana-3933	29	1	additionally	additionally	ADV
cana-3933	29	2	,	,	PUNCT
cana-3933	29	3	we	we	PRON
cana-3933	29	4	propose	propose	VERB
cana-3933	29	5	an	an	DET
cana-3933	29	6	intelligent	intelligent	ADJ
cana-3933	29	7	routing	routing	NOUN
cana-3933	29	8	scheme	scheme	NOUN
cana-3933	29	9	using	use	VERB
cana-3933	29	10	a	a	DET
cana-3933	29	11	spatio	spatio	NOUN
cana-3933	29	12	-	-	PUNCT
cana-3933	29	13	temporal	temporal	ADJ
cana-3933	29	14	deep	deep	ADJ
cana-3933	29	15	learning	learning	NOUN
cana-3933	29	16	algorithm	algorithm	NOUN
cana-3933	29	17	to	to	PART
cana-3933	29	18	predict	predict	VERB
cana-3933	29	19	traffic	traffic	NOUN
cana-3933	29	20	density	density	NOUN
cana-3933	29	21	and	and	CCONJ
cana-3933	29	22	select	select	VERB
cana-3933	29	23	optimal	optimal	ADJ
cana-3933	29	24	paths	path	NOUN
cana-3933	29	25	,	,	PUNCT
cana-3933	29	26	thereby	thereby	ADV
cana-3933	29	27	avoiding	avoid	VERB
cana-3933	29	28	congested	congested	ADJ
cana-3933	29	29	and	and	CCONJ
cana-3933	29	30	high	high	ADJ
cana-3933	29	31	-	-	PUNCT
cana-3933	29	32	interference	interference	NOUN
cana-3933	29	33	areas	area	NOUN
cana-3933	29	34	[	[	X
cana-3933	29	35	8	8	NUM
cana-3933	29	36	]	]	PUNCT
cana-3933	29	37	.	.	PUNCT
cana-3933	30	1	this	this	DET
cana-3933	30	2	approach	approach	NOUN
cana-3933	30	3	not	not	PART
cana-3933	30	4	only	only	ADV
cana-3933	30	5	reduces	reduce	VERB
cana-3933	30	6	congestion	congestion	NOUN
cana-3933	30	7	but	but	CCONJ
cana-3933	30	8	also	also	ADV
cana-3933	30	9	enhances	enhance	VERB
cana-3933	30	10	network	network	NOUN
cana-3933	30	11	reliability	reliability	NOUN
cana-3933	30	12	and	and	CCONJ
cana-3933	30	13	qos	qos	PROPN
cana-3933	30	14	.	.	PUNCT
cana-3933	31	1	moreover	moreover	ADV
cana-3933	31	2	,	,	PUNCT
cana-3933	31	3	we	we	PRON
cana-3933	31	4	introduce	introduce	VERB
cana-3933	31	5	an	an	DET
cana-3933	31	6	innovative	innovative	ADJ
cana-3933	31	7	buffer	buffer	NOUN
cana-3933	31	8	management	management	NOUN
cana-3933	31	9	technique	technique	NOUN
cana-3933	31	10	that	that	PRON
cana-3933	31	11	eliminates	eliminate	VERB
cana-3933	31	12	unnecessary	unnecessary	ADJ
cana-3933	31	13	packets	packet	NOUN
cana-3933	31	14	,	,	PUNCT
cana-3933	31	15	prevents	prevent	VERB
cana-3933	31	16	network	network	NOUN
cana-3933	31	17	flooding	flooding	NOUN
cana-3933	31	18	,	,	PUNCT
cana-3933	31	19	and	and	CCONJ
cana-3933	31	20	maintains	maintain	VERB
cana-3933	31	21	buffer	buffer	NOUN
cana-3933	31	22	levels	level	NOUN
cana-3933	31	23	by	by	ADP
cana-3933	31	24	retaining	retain	VERB
cana-3933	31	25	only	only	ADJ
cana-3933	31	26	essential	essential	ADJ
cana-3933	31	27	data	datum	NOUN
cana-3933	31	28	.	.	PUNCT
cana-3933	32	1	this	this	DET
cana-3933	32	2	technique	technique	NOUN
cana-3933	32	3	significantly	significantly	ADV
cana-3933	32	4	improves	improve	VERB
cana-3933	32	5	queue	queue	NOUN
cana-3933	32	6	management	management	NOUN
cana-3933	32	7	and	and	CCONJ
cana-3933	32	8	communication	communication	NOUN
cana-3933	32	9	performance	performance	NOUN
cana-3933	32	10	in	in	ADP
cana-3933	32	11	manets	manet	NOUN
cana-3933	32	12	[	[	X
cana-3933	32	13	9	9	NUM
cana-3933	32	14	]	]	PUNCT
cana-3933	32	15	.	.	PUNCT
cana-3933	33	1	the	the	DET
cana-3933	33	2	effectiveness	effectiveness	NOUN
cana-3933	33	3	of	of	ADP
cana-3933	33	4	the	the	DET
cana-3933	33	5	proposed	propose	VERB
cana-3933	33	6	model	model	NOUN
cana-3933	33	7	is	be	AUX
cana-3933	33	8	demonstrated	demonstrate	VERB
cana-3933	33	9	through	through	ADP
cana-3933	33	10	simulation	simulation	NOUN
cana-3933	33	11	results	result	NOUN
cana-3933	33	12	,	,	PUNCT
cana-3933	33	13	which	which	PRON
cana-3933	33	14	show	show	VERB
cana-3933	33	15	a	a	DET
cana-3933	33	16	reduction	reduction	NOUN
cana-3933	33	17	in	in	ADP
cana-3933	33	18	congestion	congestion	NOUN
cana-3933	33	19	across	across	ADP
cana-3933	33	20	network	network	NOUN
cana-3933	33	21	nodes	node	NOUN
cana-3933	33	22	using	use	VERB
cana-3933	33	23	ccda	ccda	PROPN
cana-3933	33	24	.	.	PUNCT
cana-3933	34	1	the	the	DET
cana-3933	34	2	study	study	NOUN
cana-3933	34	3	also	also	ADV
cana-3933	34	4	explores	explore	VERB
cana-3933	34	5	the	the	DET
cana-3933	34	6	impact	impact	NOUN
cana-3933	34	7	of	of	ADP
cana-3933	34	8	various	various	ADJ
cana-3933	34	9	parameters	parameter	NOUN
cana-3933	34	10	,	,	PUNCT
cana-3933	34	11	such	such	ADJ
cana-3933	34	12	as	as	ADP
cana-3933	34	13	congestion	congestion	NOUN
cana-3933	34	14	probability	probability	NOUN
cana-3933	34	15	and	and	CCONJ
cana-3933	34	16	delay	delay	NOUN
cana-3933	34	17	weight	weight	NOUN
cana-3933	34	18	,	,	PUNCT
cana-3933	34	19	on	on	ADP
cana-3933	34	20	network	network	NOUN
cana-3933	34	21	loss	loss	NOUN
cana-3933	34	22	.	.	PUNCT
cana-3933	35	1	the	the	DET
cana-3933	35	2	proposed	propose	VERB
cana-3933	35	3	model	model	NOUN
cana-3933	35	4	consistently	consistently	ADV
cana-3933	35	5	outperforms	outperform	VERB
cana-3933	35	6	baseline	baseline	NOUN
cana-3933	35	7	models	model	NOUN
cana-3933	35	8	in	in	ADP
cana-3933	35	9	terms	term	NOUN
cana-3933	35	10	of	of	ADP
cana-3933	35	11	total	total	ADJ
cana-3933	35	12	network	network	NOUN
cana-3933	35	13	loss	loss	NOUN
cana-3933	35	14	,	,	PUNCT
cana-3933	35	15	offering	offer	VERB
cana-3933	35	16	a	a	DET
cana-3933	35	17	robust	robust	ADJ
cana-3933	35	18	solution	solution	NOUN
cana-3933	35	19	for	for	ADP
cana-3933	35	20	congestion	congestion	NOUN
cana-3933	35	21	control	control	NOUN
cana-3933	35	22	in	in	ADP
cana-3933	35	23	deterministic	deterministic	ADJ
cana-3933	35	24	network	network	NOUN
cana-3933	35	25	environments	environment	NOUN
cana-3933	35	26	.	.	PUNCT
cana-3933	36	1	2.literature	2.literature	NUM
cana-3933	36	2	review	review	VERB
cana-3933	36	3	congestion	congestion	NOUN
cana-3933	36	4	control	control	NOUN
cana-3933	36	5	in	in	ADP
cana-3933	36	6	mobile	mobile	ADJ
cana-3933	36	7	ad	ad	NOUN
cana-3933	36	8	-	-	PUNCT
cana-3933	36	9	hoc	hoc	X
cana-3933	36	10	networks	network	NOUN
cana-3933	36	11	(	(	PUNCT
cana-3933	36	12	manets	manet	NOUN
cana-3933	36	13	)	)	PUNCT
cana-3933	36	14	is	be	AUX
cana-3933	36	15	a	a	DET
cana-3933	36	16	critical	critical	ADJ
cana-3933	36	17	area	area	NOUN
cana-3933	36	18	of	of	ADP
cana-3933	36	19	research	research	NOUN
cana-3933	36	20	due	due	ADP
cana-3933	36	21	to	to	ADP
cana-3933	36	22	the	the	DET
cana-3933	36	23	network	network	NOUN
cana-3933	36	24	’s	’s	PART
cana-3933	36	25	inherent	inherent	ADJ
cana-3933	36	26	characteristics	characteristic	NOUN
cana-3933	36	27	of	of	ADP
cana-3933	36	28	dynamic	dynamic	ADJ
cana-3933	36	29	topology	topology	NOUN
cana-3933	36	30	,	,	PUNCT
cana-3933	36	31	lack	lack	NOUN
cana-3933	36	32	of	of	ADP
cana-3933	36	33	centralized	centralized	ADJ
cana-3933	36	34	management	management	NOUN
cana-3933	36	35	,	,	PUNCT
cana-3933	36	36	and	and	CCONJ
cana-3933	36	37	limited	limited	ADJ
cana-3933	36	38	bandwidth	bandwidth	NOUN
cana-3933	36	39	.	.	PUNCT
cana-3933	37	1	traditional	traditional	ADJ
cana-3933	37	2	congestion	congestion	NOUN
cana-3933	37	3	control	control	NOUN
cana-3933	37	4	methods	method	NOUN
cana-3933	37	5	,	,	PUNCT
cana-3933	37	6	such	such	ADJ
cana-3933	37	7	as	as	ADP
cana-3933	37	8	modifying	modify	VERB
cana-3933	37	9	routing	route	VERB
cana-3933	37	10	protocols	protocol	NOUN
cana-3933	37	11	like	like	ADP
cana-3933	37	12	ad	ad	NOUN
cana-3933	37	13	-	-	PUNCT
cana-3933	37	14	hoc	hoc	X
cana-3933	37	15	on	on	ADP
cana-3933	37	16	-	-	PUNCT
cana-3933	37	17	demand	demand	NOUN
cana-3933	37	18	distance	distance	NOUN
cana-3933	37	19	vector	vector	NOUN
cana-3933	37	20	(	(	PUNCT
cana-3933	37	21	aodv	aodv	NOUN
cana-3933	37	22	)	)	PUNCT
cana-3933	37	23	and	and	CCONJ
cana-3933	37	24	dynamic	dynamic	ADJ
cana-3933	37	25	source	source	NOUN
cana-3933	37	26	routing	routing	NOUN
cana-3933	37	27	(	(	PUNCT
cana-3933	37	28	dsr	dsr	PROPN
cana-3933	37	29	)	)	PUNCT
cana-3933	37	30	,	,	PUNCT
cana-3933	37	31	have	have	AUX
cana-3933	37	32	been	be	AUX
cana-3933	37	33	extensively	extensively	ADV
cana-3933	37	34	studied	study	VERB
cana-3933	37	35	.	.	PUNCT
cana-3933	38	1	these	these	DET
cana-3933	38	2	protocols	protocol	NOUN
cana-3933	38	3	incorporate	incorporate	VERB
cana-3933	38	4	congestion	congestion	NOUN
cana-3933	38	5	metrics	metric	NOUN
cana-3933	38	6	like	like	ADP
cana-3933	38	7	buffer	buffer	VERB
cana-3933	38	8	occupancy	occupancy	NOUN
cana-3933	38	9	and	and	CCONJ
cana-3933	38	10	link	link	VERB
cana-3933	38	11	utilization	utilization	NOUN
cana-3933	38	12	to	to	PART
cana-3933	38	13	avoid	avoid	VERB
cana-3933	38	14	congested	congested	ADJ
cana-3933	38	15	routes	route	NOUN
cana-3933	38	16	[	[	X
cana-3933	38	17	10	10	NUM
cana-3933	38	18	]	]	PUNCT
cana-3933	38	19	.	.	PUNCT
cana-3933	39	1	however	however	ADV
cana-3933	39	2	,	,	PUNCT
cana-3933	39	3	these	these	DET
cana-3933	39	4	methods	method	NOUN
cana-3933	39	5	often	often	ADV
cana-3933	39	6	fail	fail	VERB
cana-3933	39	7	in	in	ADP
cana-3933	39	8	highly	highly	ADV
cana-3933	39	9	dynamic	dynamic	ADJ
cana-3933	39	10	environments	environment	NOUN
cana-3933	39	11	where	where	SCONJ
cana-3933	39	12	network	network	NOUN
cana-3933	39	13	topology	topology	NOUN
cana-3933	39	14	changes	change	VERB
cana-3933	39	15	rapidly	rapidly	ADV
cana-3933	39	16	,	,	PUNCT
cana-3933	39	17	leading	lead	VERB
cana-3933	39	18	to	to	ADP
cana-3933	39	19	packet	packet	NOUN
cana-3933	39	20	loss	loss	NOUN
cana-3933	39	21	and	and	CCONJ
cana-3933	39	22	reduced	reduce	VERB
cana-3933	39	23	quality	quality	NOUN
cana-3933	39	24	of	of	ADP
cana-3933	39	25	service	service	NOUN
cana-3933	39	26	(	(	PUNCT
cana-3933	39	27	qos	qos	PROPN
cana-3933	39	28	)	)	PUNCT
cana-3933	39	29	.	.	PUNCT
cana-3933	40	1	recent	recent	ADJ
cana-3933	40	2	advancements	advancement	NOUN
cana-3933	40	3	in	in	ADP
cana-3933	40	4	machine	machine	NOUN
cana-3933	40	5	learning	learning	NOUN
cana-3933	40	6	(	(	PUNCT
cana-3933	40	7	ml	ml	NOUN
cana-3933	40	8	)	)	PUNCT
cana-3933	40	9	have	have	AUX
cana-3933	40	10	introduced	introduce	VERB
cana-3933	40	11	more	more	ADV
cana-3933	40	12	adaptive	adaptive	ADJ
cana-3933	40	13	and	and	CCONJ
cana-3933	40	14	predictive	predictive	ADJ
cana-3933	40	15	approaches	approach	NOUN
cana-3933	40	16	to	to	ADP
cana-3933	40	17	congestion	congestion	NOUN
cana-3933	40	18	control	control	NOUN
cana-3933	40	19	in	in	ADP
cana-3933	40	20	manets	manet	NOUN
cana-3933	40	21	.	.	PUNCT
cana-3933	41	1	ml	ml	NOUN
cana-3933	41	2	models	model	NOUN
cana-3933	41	3	have	have	AUX
cana-3933	41	4	been	be	AUX
cana-3933	41	5	utilized	utilize	VERB
cana-3933	41	6	to	to	PART
cana-3933	41	7	predict	predict	VERB
cana-3933	41	8	network	network	NOUN
cana-3933	41	9	congestion	congestion	NOUN
cana-3933	41	10	and	and	CCONJ
cana-3933	41	11	make	make	VERB
cana-3933	41	12	proactive	proactive	ADJ
cana-3933	41	13	routing	routing	NOUN
cana-3933	41	14	decisions	decision	NOUN
cana-3933	41	15	based	base	VERB
cana-3933	41	16	on	on	ADP
cana-3933	41	17	historical	historical	ADJ
cana-3933	41	18	data	datum	NOUN
cana-3933	41	19	patterns	pattern	NOUN
cana-3933	41	20	.	.	PUNCT
cana-3933	42	1	for	for	ADP
cana-3933	42	2	instance	instance	NOUN
cana-3933	42	3	,	,	PUNCT
cana-3933	42	4	neural	neural	ADJ
cana-3933	42	5	networks	network	NOUN
cana-3933	42	6	and	and	CCONJ
cana-3933	42	7	decision	decision	NOUN
cana-3933	42	8	trees	tree	NOUN
cana-3933	42	9	have	have	AUX
cana-3933	42	10	shown	show	VERB
cana-3933	42	11	promise	promise	NOUN
cana-3933	42	12	in	in	ADP
cana-3933	42	13	learning	learn	VERB
cana-3933	42	14	complex	complex	ADJ
cana-3933	42	15	patterns	pattern	NOUN
cana-3933	42	16	of	of	ADP
cana-3933	42	17	network	network	NOUN
cana-3933	42	18	traffic	traffic	NOUN
cana-3933	42	19	and	and	CCONJ
cana-3933	42	20	predicting	predict	VERB
cana-3933	42	21	congestion	congestion	NOUN
cana-3933	42	22	before	before	SCONJ
cana-3933	42	23	it	it	PRON
cana-3933	42	24	occurs	occur	VERB
cana-3933	42	25	,	,	PUNCT
cana-3933	42	26	thereby	thereby	ADV
cana-3933	42	27	enabling	enable	VERB
cana-3933	42	28	dynamic	dynamic	ADJ
cana-3933	42	29	rerouting	rerouting	NOUN
cana-3933	42	30	[	[	X
cana-3933	42	31	11	11	NUM
cana-3933	42	32	]	]	PUNCT
cana-3933	42	33	.	.	PUNCT
cana-3933	43	1	a	a	DET
cana-3933	43	2	significant	significant	ADJ
cana-3933	43	3	advantage	advantage	NOUN
cana-3933	43	4	of	of	ADP
cana-3933	43	5	ml	ml	NOUN
cana-3933	43	6	-	-	PUNCT
cana-3933	43	7	based	base	VERB
cana-3933	43	8	methods	method	NOUN
cana-3933	43	9	is	be	AUX
cana-3933	43	10	their	their	PRON
cana-3933	43	11	ability	ability	NOUN
cana-3933	43	12	to	to	PART
cana-3933	43	13	continuously	continuously	ADV
cana-3933	43	14	learn	learn	VERB
cana-3933	43	15	and	and	CCONJ
cana-3933	43	16	adapt	adapt	VERB
cana-3933	43	17	to	to	ADP
cana-3933	43	18	changing	change	VERB
cana-3933	43	19	network	network	NOUN
cana-3933	43	20	conditions	condition	NOUN
cana-3933	43	21	,	,	PUNCT
cana-3933	43	22	which	which	PRON
cana-3933	43	23	is	be	AUX
cana-3933	43	24	crucial	crucial	ADJ
cana-3933	43	25	in	in	ADP
cana-3933	43	26	the	the	DET
cana-3933	43	27	highly	highly	ADV
cana-3933	43	28	volatile	volatile	ADJ
cana-3933	43	29	environment	environment	NOUN
cana-3933	43	30	of	of	ADP
cana-3933	43	31	manets	manet	NOUN
cana-3933	43	32	.	.	PUNCT
cana-3933	44	1	one	one	NUM
cana-3933	44	2	notable	notable	ADJ
cana-3933	44	3	approach	approach	NOUN
cana-3933	44	4	is	be	AUX
cana-3933	44	5	the	the	DET
cana-3933	44	6	use	use	NOUN
cana-3933	44	7	of	of	ADP
cana-3933	44	8	neural	neural	ADJ
cana-3933	44	9	networks	network	NOUN
cana-3933	44	10	with	with	ADP
cana-3933	44	11	multi	multi	ADJ
cana-3933	44	12	-	-	ADJ
cana-3933	44	13	layer	layer	ADJ
cana-3933	44	14	architectures	architecture	NOUN
cana-3933	44	15	to	to	PART
cana-3933	44	16	classify	classify	VERB
cana-3933	44	17	network	network	NOUN
cana-3933	44	18	states	state	NOUN
cana-3933	44	19	into	into	ADP
cana-3933	44	20	'	'	PUNCT
cana-3933	44	21	normal	normal	ADJ
cana-3933	44	22	'	'	PUNCT
cana-3933	44	23	and	and	CCONJ
cana-3933	44	24	'	'	PUNCT
cana-3933	44	25	congested	congested	ADJ
cana-3933	44	26	'	'	PUNCT
cana-3933	44	27	categories	category	NOUN
cana-3933	44	28	.	.	PUNCT
cana-3933	45	1	such	such	ADJ
cana-3933	45	2	models	model	NOUN
cana-3933	45	3	have	have	AUX
cana-3933	45	4	been	be	AUX
cana-3933	45	5	trained	train	VERB
cana-3933	45	6	using	use	VERB
cana-3933	45	7	a	a	DET
cana-3933	45	8	variety	variety	NOUN
cana-3933	45	9	of	of	ADP
cana-3933	45	10	network	network	NOUN
cana-3933	45	11	parameters	parameter	NOUN
cana-3933	45	12	,	,	PUNCT
cana-3933	45	13	including	include	VERB
cana-3933	45	14	node	node	ADJ
cana-3933	45	15	mobility	mobility	NOUN
cana-3933	45	16	,	,	PUNCT
cana-3933	45	17	packet	packet	NOUN
cana-3933	45	18	arrival	arrival	NOUN
cana-3933	45	19	rate	rate	NOUN
cana-3933	45	20	,	,	PUNCT
cana-3933	45	21	and	and	CCONJ
cana-3933	45	22	buffer	buffer	VERB
cana-3933	45	23	occupancy	occupancy	NOUN
cana-3933	45	24	.	.	PUNCT
cana-3933	46	1	the	the	DET
cana-3933	46	2	neural	neural	ADJ
cana-3933	46	3	network	network	NOUN
cana-3933	46	4	model	model	NOUN
cana-3933	46	5	with	with	ADP
cana-3933	46	6	three	three	NUM
cana-3933	46	7	hidden	hidden	ADJ
cana-3933	46	8	layers	layer	NOUN
cana-3933	46	9	,	,	PUNCT
cana-3933	46	10	as	as	SCONJ
cana-3933	46	11	described	describe	VERB
cana-3933	46	12	in	in	ADP
cana-3933	46	13	recent	recent	ADJ
cana-3933	46	14	studies	study	NOUN
cana-3933	46	15	,	,	PUNCT
cana-3933	46	16	has	have	AUX
cana-3933	46	17	demonstrated	demonstrate	VERB
cana-3933	46	18	high	high	ADJ
cana-3933	46	19	accuracy	accuracy	NOUN
cana-3933	46	20	in	in	ADP
cana-3933	46	21	predicting	predict	VERB
cana-3933	46	22	congestion	congestion	NOUN
cana-3933	46	23	states	state	NOUN
cana-3933	46	24	.	.	PUNCT
cana-3933	47	1	this	this	DET
cana-3933	47	2	model	model	NOUN
cana-3933	47	3	,	,	PUNCT
cana-3933	47	4	which	which	PRON
cana-3933	47	5	uses	use	VERB
cana-3933	47	6	relu	relu	NOUN
cana-3933	47	7	activation	activation	NOUN
cana-3933	47	8	functions	function	NOUN
cana-3933	47	9	for	for	ADP
cana-3933	47	10	hidden	hide	VERB
cana-3933	47	11	layers	layer	NOUN
cana-3933	47	12	communications	communication	NOUN
cana-3933	47	13	on	on	ADP
cana-3933	47	14	applied	apply	VERB
cana-3933	47	15	nonlinear	nonlinear	ADJ
cana-3933	47	16	analysis	analysis	NOUN
cana-3933	47	17	issn	issn	NOUN
cana-3933	47	18	:	:	PUNCT
cana-3933	47	19	1074	1074	NUM
cana-3933	47	20	-	-	PUNCT
cana-3933	47	21	133x	133x	NUM
cana-3933	47	22	vol	vol	NOUN
cana-3933	47	23	32	32	NUM
cana-3933	47	24	no	no	NOUN
cana-3933	47	25	.	.	PUNCT
cana-3933	48	1	9s	9s	NUM
cana-3933	48	2	(	(	PUNCT
cana-3933	48	3	2025	2025	NUM
cana-3933	48	4	)	)	PUNCT
cana-3933	48	5	364	364	NUM
cana-3933	48	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3933	48	7	and	and	CCONJ
cana-3933	48	8	sigmoid	sigmoid	NOUN
cana-3933	48	9	activation	activation	NOUN
cana-3933	48	10	for	for	ADP
cana-3933	48	11	the	the	DET
cana-3933	48	12	output	output	NOUN
cana-3933	48	13	,	,	PUNCT
cana-3933	48	14	has	have	AUX
cana-3933	48	15	been	be	AUX
cana-3933	48	16	effectively	effectively	ADV
cana-3933	48	17	employed	employ	VERB
cana-3933	48	18	to	to	PART
cana-3933	48	19	identify	identify	VERB
cana-3933	48	20	congestion	congestion	NOUN
cana-3933	48	21	in	in	ADP
cana-3933	48	22	realtime	realtime	NOUN
cana-3933	48	23	,	,	PUNCT
cana-3933	48	24	thus	thus	ADV
cana-3933	48	25	allowing	allow	VERB
cana-3933	48	26	for	for	ADP
cana-3933	48	27	timely	timely	ADJ
cana-3933	48	28	intervention	intervention	NOUN
cana-3933	48	29	and	and	CCONJ
cana-3933	48	30	congestion	congestion	NOUN
cana-3933	48	31	mitigation	mitigation	NOUN
cana-3933	48	32	[	[	PUNCT
cana-3933	48	33	12	12	NUM
cana-3933	48	34	]	]	PUNCT
cana-3933	48	35	.	.	PUNCT
cana-3933	49	1	in	in	ADP
cana-3933	49	2	addition	addition	NOUN
cana-3933	49	3	to	to	ADP
cana-3933	49	4	neural	neural	ADJ
cana-3933	49	5	networks	network	NOUN
cana-3933	49	6	,	,	PUNCT
cana-3933	49	7	other	other	ADJ
cana-3933	49	8	ml	ml	ADP
cana-3933	49	9	techniques	technique	NOUN
cana-3933	49	10	such	such	ADJ
cana-3933	49	11	as	as	ADP
cana-3933	49	12	reinforcement	reinforcement	NOUN
cana-3933	49	13	learning	learning	NOUN
cana-3933	49	14	have	have	AUX
cana-3933	49	15	been	be	AUX
cana-3933	49	16	explored	explore	VERB
cana-3933	49	17	.	.	PUNCT
cana-3933	50	1	reinforcement	reinforcement	NOUN
cana-3933	50	2	learning	learning	NOUN
cana-3933	50	3	models	model	NOUN
cana-3933	50	4	can	can	AUX
cana-3933	50	5	optimize	optimize	VERB
cana-3933	50	6	routing	routing	NOUN
cana-3933	50	7	strategies	strategy	NOUN
cana-3933	50	8	by	by	ADP
cana-3933	50	9	learning	learn	VERB
cana-3933	50	10	the	the	DET
cana-3933	50	11	optimal	optimal	ADJ
cana-3933	50	12	policy	policy	NOUN
cana-3933	50	13	through	through	ADP
cana-3933	50	14	interactions	interaction	NOUN
cana-3933	50	15	with	with	ADP
cana-3933	50	16	the	the	DET
cana-3933	50	17	network	network	NOUN
cana-3933	50	18	environment	environment	NOUN
cana-3933	50	19	.	.	PUNCT
cana-3933	51	1	these	these	DET
cana-3933	51	2	models	model	NOUN
cana-3933	51	3	have	have	AUX
cana-3933	51	4	been	be	AUX
cana-3933	51	5	applied	apply	VERB
cana-3933	51	6	to	to	PART
cana-3933	51	7	adjust	adjust	VERB
cana-3933	51	8	transmission	transmission	NOUN
cana-3933	51	9	rates	rate	NOUN
cana-3933	51	10	and	and	CCONJ
cana-3933	51	11	select	select	VERB
cana-3933	51	12	less	less	ADV
cana-3933	51	13	congested	congested	ADJ
cana-3933	51	14	routes	route	NOUN
cana-3933	51	15	dynamically	dynamically	ADV
cana-3933	51	16	,	,	PUNCT
cana-3933	51	17	showing	show	VERB
cana-3933	51	18	improved	improved	ADJ
cana-3933	51	19	performance	performance	NOUN
cana-3933	51	20	in	in	ADP
cana-3933	51	21	maintaining	maintain	VERB
cana-3933	51	22	network	network	NOUN
cana-3933	51	23	stability	stability	NOUN
cana-3933	51	24	under	under	ADP
cana-3933	51	25	varying	vary	VERB
cana-3933	51	26	traffic	traffic	NOUN
cana-3933	51	27	conditions	condition	NOUN
cana-3933	51	28	[	[	X
cana-3933	51	29	13	13	NUM
cana-3933	51	30	]	]	PUNCT
cana-3933	51	31	.	.	PUNCT
cana-3933	52	1	however	however	ADV
cana-3933	52	2	,	,	PUNCT
cana-3933	52	3	the	the	DET
cana-3933	52	4	complexity	complexity	NOUN
cana-3933	52	5	and	and	CCONJ
cana-3933	52	6	high	high	ADJ
cana-3933	52	7	computational	computational	ADJ
cana-3933	52	8	requirements	requirement	NOUN
cana-3933	52	9	of	of	ADP
cana-3933	52	10	reinforcement	reinforcement	NOUN
cana-3933	52	11	learning	learning	NOUN
cana-3933	52	12	models	model	NOUN
cana-3933	52	13	can	can	AUX
cana-3933	52	14	be	be	AUX
cana-3933	52	15	challenging	challenge	VERB
cana-3933	52	16	in	in	ADP
cana-3933	52	17	resourceconstrained	resourceconstrained	ADJ
cana-3933	52	18	environments	environment	NOUN
cana-3933	52	19	like	like	ADP
cana-3933	52	20	manets	manet	NOUN
cana-3933	52	21	.	.	PUNCT
cana-3933	53	1	moreover	moreover	ADV
cana-3933	53	2	,	,	PUNCT
cana-3933	53	3	hybrid	hybrid	ADJ
cana-3933	53	4	approaches	approach	NOUN
cana-3933	53	5	that	that	PRON
cana-3933	53	6	combine	combine	VERB
cana-3933	53	7	traditional	traditional	ADJ
cana-3933	53	8	routing	routing	NOUN
cana-3933	53	9	methods	method	NOUN
cana-3933	53	10	with	with	ADP
cana-3933	53	11	ml	ml	NOUN
cana-3933	53	12	techniques	technique	NOUN
cana-3933	53	13	have	have	AUX
cana-3933	53	14	also	also	ADV
cana-3933	53	15	been	be	AUX
cana-3933	53	16	proposed	propose	VERB
cana-3933	53	17	.	.	PUNCT
cana-3933	54	1	for	for	ADP
cana-3933	54	2	example	example	NOUN
cana-3933	54	3	,	,	PUNCT
cana-3933	54	4	a	a	DET
cana-3933	54	5	study	study	NOUN
cana-3933	54	6	integrated	integrate	VERB
cana-3933	54	7	ml	ml	NOUN
cana-3933	54	8	-	-	PUNCT
cana-3933	54	9	based	base	VERB
cana-3933	54	10	congestion	congestion	NOUN
cana-3933	54	11	prediction	prediction	NOUN
cana-3933	54	12	with	with	ADP
cana-3933	54	13	the	the	DET
cana-3933	54	14	aodv	aodv	NOUN
cana-3933	54	15	protocol	protocol	NOUN
cana-3933	54	16	to	to	PART
cana-3933	54	17	enhance	enhance	VERB
cana-3933	54	18	its	its	PRON
cana-3933	54	19	adaptability	adaptability	NOUN
cana-3933	54	20	to	to	ADP
cana-3933	54	21	congestion	congestion	NOUN
cana-3933	54	22	.	.	PUNCT
cana-3933	55	1	this	this	DET
cana-3933	55	2	hybrid	hybrid	ADJ
cana-3933	55	3	model	model	NOUN
cana-3933	55	4	outperformed	outperform	VERB
cana-3933	55	5	traditional	traditional	ADJ
cana-3933	55	6	aodv	aodv	NOUN
cana-3933	55	7	in	in	ADP
cana-3933	55	8	scenarios	scenario	NOUN
cana-3933	55	9	with	with	ADP
cana-3933	55	10	high	high	ADJ
cana-3933	55	11	node	node	ADJ
cana-3933	55	12	mobility	mobility	NOUN
cana-3933	55	13	and	and	CCONJ
cana-3933	55	14	traffic	traffic	NOUN
cana-3933	55	15	variability	variability	NOUN
cana-3933	55	16	,	,	PUNCT
cana-3933	55	17	reducing	reduce	VERB
cana-3933	55	18	packet	packet	NOUN
cana-3933	55	19	loss	loss	NOUN
cana-3933	55	20	and	and	CCONJ
cana-3933	55	21	improving	improve	VERB
cana-3933	55	22	endto	endto	NOUN
cana-3933	55	23	-	-	PUNCT
cana-3933	55	24	end	end	NOUN
cana-3933	55	25	delay	delay	NOUN
cana-3933	55	26	[	[	X
cana-3933	55	27	14	14	NUM
cana-3933	55	28	]	]	PUNCT
cana-3933	55	29	.	.	PUNCT
cana-3933	56	1	such	such	ADJ
cana-3933	56	2	hybrid	hybrid	ADJ
cana-3933	56	3	models	model	NOUN
cana-3933	56	4	leverage	leverage	VERB
cana-3933	56	5	the	the	DET
cana-3933	56	6	strengths	strength	NOUN
cana-3933	56	7	of	of	ADP
cana-3933	56	8	both	both	CCONJ
cana-3933	56	9	traditional	traditional	ADJ
cana-3933	56	10	and	and	CCONJ
cana-3933	56	11	ml	ml	ADV
cana-3933	56	12	-	-	PUNCT
cana-3933	56	13	based	base	VERB
cana-3933	56	14	methods	method	NOUN
cana-3933	56	15	,	,	PUNCT
cana-3933	56	16	providing	provide	VERB
cana-3933	56	17	a	a	DET
cana-3933	56	18	more	more	ADV
cana-3933	56	19	robust	robust	ADJ
cana-3933	56	20	solution	solution	NOUN
cana-3933	56	21	for	for	ADP
cana-3933	56	22	congestion	congestion	NOUN
cana-3933	56	23	control	control	NOUN
cana-3933	56	24	.	.	PUNCT
cana-3933	57	1	despite	despite	SCONJ
cana-3933	57	2	these	these	DET
cana-3933	57	3	advancements	advancement	NOUN
cana-3933	57	4	,	,	PUNCT
cana-3933	57	5	there	there	PRON
cana-3933	57	6	are	be	VERB
cana-3933	57	7	still	still	ADV
cana-3933	57	8	challenges	challenge	NOUN
cana-3933	57	9	in	in	ADP
cana-3933	57	10	implementing	implement	VERB
cana-3933	57	11	ml	ml	NOUN
cana-3933	57	12	models	model	NOUN
cana-3933	57	13	in	in	ADP
cana-3933	57	14	manets	manet	NOUN
cana-3933	57	15	,	,	PUNCT
cana-3933	57	16	such	such	ADJ
cana-3933	57	17	as	as	ADP
cana-3933	57	18	the	the	DET
cana-3933	57	19	need	need	NOUN
cana-3933	57	20	for	for	ADP
cana-3933	57	21	real	real	ADJ
cana-3933	57	22	-	-	PUNCT
cana-3933	57	23	time	time	NOUN
cana-3933	57	24	data	datum	NOUN
cana-3933	57	25	processing	processing	NOUN
cana-3933	57	26	and	and	CCONJ
cana-3933	57	27	the	the	DET
cana-3933	57	28	high	high	ADJ
cana-3933	57	29	computational	computational	ADJ
cana-3933	57	30	cost	cost	NOUN
cana-3933	57	31	associated	associate	VERB
cana-3933	57	32	with	with	ADP
cana-3933	57	33	training	training	NOUN
cana-3933	57	34	complex	complex	ADJ
cana-3933	57	35	models	model	NOUN
cana-3933	57	36	.	.	PUNCT
cana-3933	58	1	future	future	ADJ
cana-3933	58	2	research	research	NOUN
cana-3933	58	3	should	should	AUX
cana-3933	58	4	focus	focus	VERB
cana-3933	58	5	on	on	ADP
cana-3933	58	6	lightweight	lightweight	ADJ
cana-3933	58	7	ml	ml	NOUN
cana-3933	58	8	models	model	NOUN
cana-3933	58	9	that	that	PRON
cana-3933	58	10	can	can	AUX
cana-3933	58	11	be	be	AUX
cana-3933	58	12	efficiently	efficiently	ADV
cana-3933	58	13	deployed	deploy	VERB
cana-3933	58	14	in	in	ADP
cana-3933	58	15	resource	resource	NOUN
cana-3933	58	16	-	-	PUNCT
cana-3933	58	17	constrained	constrain	VERB
cana-3933	58	18	environments	environment	NOUN
cana-3933	58	19	while	while	SCONJ
cana-3933	58	20	maintaining	maintain	VERB
cana-3933	58	21	high	high	ADJ
cana-3933	58	22	accuracy	accuracy	NOUN
cana-3933	58	23	and	and	CCONJ
cana-3933	58	24	adaptability	adaptability	NOUN
cana-3933	58	25	[	[	X
cana-3933	58	26	15	15	NUM
cana-3933	58	27	]	]	PUNCT
cana-3933	58	28	.	.	PUNCT
cana-3933	59	1	additionally	additionally	ADV
cana-3933	59	2	,	,	PUNCT
cana-3933	59	3	exploring	explore	VERB
cana-3933	59	4	the	the	DET
cana-3933	59	5	integration	integration	NOUN
cana-3933	59	6	of	of	ADP
cana-3933	59	7	ml	ml	ADP
cana-3933	59	8	techniques	technique	NOUN
cana-3933	59	9	with	with	ADP
cana-3933	59	10	emerging	emerge	VERB
cana-3933	59	11	network	network	NOUN
cana-3933	59	12	paradigms	paradigm	VERB
cana-3933	59	13	like	like	ADP
cana-3933	59	14	software	software	NOUN
cana-3933	59	15	-	-	PUNCT
cana-3933	59	16	defined	define	VERB
cana-3933	59	17	networking	networking	NOUN
cana-3933	59	18	(	(	PUNCT
cana-3933	59	19	sdn	sdn	PROPN
cana-3933	59	20	)	)	PUNCT
cana-3933	59	21	and	and	CCONJ
cana-3933	59	22	network	network	NOUN
cana-3933	59	23	function	function	NOUN
cana-3933	59	24	virtualization	virtualization	NOUN
cana-3933	59	25	(	(	PUNCT
cana-3933	59	26	nfv	nfv	NOUN
cana-3933	59	27	)	)	PUNCT
cana-3933	59	28	could	could	AUX
cana-3933	59	29	open	open	VERB
cana-3933	59	30	new	new	ADJ
cana-3933	59	31	avenues	avenue	NOUN
cana-3933	59	32	for	for	ADP
cana-3933	59	33	improving	improve	VERB
cana-3933	59	34	congestion	congestion	NOUN
cana-3933	59	35	control	control	NOUN
cana-3933	59	36	in	in	ADP
cana-3933	59	37	manets	manet	NOUN
cana-3933	59	38	.	.	PUNCT
cana-3933	60	1	3.proposed	3.proposed	NUM
cana-3933	60	2	methodology	methodology	NOUN
cana-3933	60	3	this	this	DET
cana-3933	60	4	study	study	NOUN
cana-3933	60	5	introduces	introduce	VERB
cana-3933	60	6	a	a	DET
cana-3933	60	7	machine	machine	NOUN
cana-3933	60	8	learning	learning	NOUN
cana-3933	60	9	-	-	PUNCT
cana-3933	60	10	based	base	VERB
cana-3933	60	11	congestion	congestion	NOUN
cana-3933	60	12	control	control	NOUN
cana-3933	60	13	system	system	NOUN
cana-3933	60	14	for	for	ADP
cana-3933	60	15	mobile	mobile	ADJ
cana-3933	60	16	ad	ad	NOUN
cana-3933	60	17	-	-	PUNCT
cana-3933	60	18	hoc	hoc	X
cana-3933	60	19	networks	network	NOUN
cana-3933	60	20	(	(	PUNCT
cana-3933	60	21	manets	manet	NOUN
cana-3933	60	22	)	)	PUNCT
cana-3933	60	23	aimed	aim	VERB
cana-3933	60	24	at	at	ADP
cana-3933	60	25	improving	improve	VERB
cana-3933	60	26	network	network	NOUN
cana-3933	60	27	performance	performance	NOUN
cana-3933	60	28	by	by	ADP
cana-3933	60	29	dynamically	dynamically	ADV
cana-3933	60	30	managing	manage	VERB
cana-3933	60	31	congestion	congestion	NOUN
cana-3933	60	32	states	state	NOUN
cana-3933	60	33	at	at	ADP
cana-3933	60	34	the	the	DET
cana-3933	60	35	node	node	ADJ
cana-3933	60	36	level	level	NOUN
cana-3933	60	37	.	.	PUNCT
cana-3933	61	1	the	the	DET
cana-3933	61	2	proposed	propose	VERB
cana-3933	61	3	methodology	methodology	NOUN
cana-3933	61	4	involves	involve	VERB
cana-3933	61	5	the	the	DET
cana-3933	61	6	development	development	NOUN
cana-3933	61	7	of	of	ADP
cana-3933	61	8	a	a	DET
cana-3933	61	9	neural	neural	ADJ
cana-3933	61	10	network	network	NOUN
cana-3933	61	11	model	model	NOUN
cana-3933	61	12	designed	design	VERB
cana-3933	61	13	to	to	PART
cana-3933	61	14	classify	classify	VERB
cana-3933	61	15	network	network	NOUN
cana-3933	61	16	traffic	traffic	NOUN
cana-3933	61	17	into	into	ADP
cana-3933	61	18	'	'	PUNCT
cana-3933	61	19	normal	normal	ADJ
cana-3933	61	20	'	'	PUNCT
cana-3933	61	21	and	and	CCONJ
cana-3933	61	22	'	'	PUNCT
cana-3933	61	23	anomaly	anomaly	NOUN
cana-3933	61	24	'	'	PUNCT
cana-3933	61	25	categories	category	NOUN
cana-3933	61	26	,	,	PUNCT
cana-3933	61	27	enabling	enable	VERB
cana-3933	61	28	real	real	ADJ
cana-3933	61	29	-	-	PUNCT
cana-3933	61	30	time	time	NOUN
cana-3933	61	31	identification	identification	NOUN
cana-3933	61	32	and	and	CCONJ
cana-3933	61	33	mitigation	mitigation	NOUN
cana-3933	61	34	of	of	ADP
cana-3933	61	35	congestion	congestion	NOUN
cana-3933	61	36	.	.	PUNCT
cana-3933	62	1	the	the	DET
cana-3933	62	2	neural	neural	ADJ
cana-3933	62	3	network	network	NOUN
cana-3933	62	4	architecture	architecture	NOUN
cana-3933	62	5	consists	consist	VERB
cana-3933	62	6	of	of	ADP
cana-3933	62	7	three	three	NUM
cana-3933	62	8	hidden	hidden	ADJ
cana-3933	62	9	layers	layer	NOUN
cana-3933	62	10	with	with	ADP
cana-3933	62	11	64	64	NUM
cana-3933	62	12	,	,	PUNCT
cana-3933	62	13	128	128	NUM
cana-3933	62	14	,	,	PUNCT
cana-3933	62	15	and	and	CCONJ
cana-3933	62	16	256	256	NUM
cana-3933	62	17	units	unit	NOUN
cana-3933	62	18	respectively	respectively	ADV
cana-3933	62	19	,	,	PUNCT
cana-3933	62	20	using	use	VERB
cana-3933	62	21	relu	relu	NOUN
cana-3933	62	22	activation	activation	NOUN
cana-3933	62	23	functions	function	NOUN
cana-3933	62	24	in	in	ADP
cana-3933	62	25	the	the	DET
cana-3933	62	26	hidden	hidden	ADJ
cana-3933	62	27	layers	layer	NOUN
cana-3933	62	28	and	and	CCONJ
cana-3933	62	29	a	a	DET
cana-3933	62	30	sigmoid	sigmoid	NOUN
cana-3933	62	31	activation	activation	NOUN
cana-3933	62	32	function	function	NOUN
cana-3933	62	33	in	in	ADP
cana-3933	62	34	the	the	DET
cana-3933	62	35	output	output	NOUN
cana-3933	62	36	layer	layer	NOUN
cana-3933	62	37	.	.	PUNCT
cana-3933	63	1	this	this	DET
cana-3933	63	2	configuration	configuration	NOUN
cana-3933	63	3	ensures	ensure	VERB
cana-3933	63	4	effective	effective	ADJ
cana-3933	63	5	non	non	ADJ
cana-3933	63	6	-	-	ADJ
cana-3933	63	7	linear	linear	ADJ
cana-3933	63	8	transformations	transformation	NOUN
cana-3933	63	9	of	of	ADP
cana-3933	63	10	the	the	DET
cana-3933	63	11	input	input	NOUN
cana-3933	63	12	data	datum	NOUN
cana-3933	63	13	and	and	CCONJ
cana-3933	63	14	accurate	accurate	ADJ
cana-3933	63	15	binary	binary	ADJ
cana-3933	63	16	classification	classification	NOUN
cana-3933	63	17	of	of	ADP
cana-3933	63	18	the	the	DET
cana-3933	63	19	output	output	NOUN
cana-3933	63	20	.	.	PUNCT
cana-3933	64	1	a	a	DET
cana-3933	64	2	dropout	dropout	NOUN
cana-3933	64	3	layer	layer	NOUN
cana-3933	64	4	with	with	ADP
cana-3933	64	5	a	a	DET
cana-3933	64	6	0.3	0.3	NUM
cana-3933	64	7	probability	probability	NOUN
cana-3933	64	8	is	be	AUX
cana-3933	64	9	incorporated	incorporate	VERB
cana-3933	64	10	after	after	ADP
cana-3933	64	11	the	the	DET
cana-3933	64	12	second	second	ADJ
cana-3933	64	13	hidden	hide	VERB
cana-3933	64	14	layer	layer	NOUN
cana-3933	64	15	to	to	PART
cana-3933	64	16	prevent	prevent	VERB
cana-3933	64	17	overfitting	overfitting	NOUN
cana-3933	64	18	,	,	PUNCT
cana-3933	64	19	enhancing	enhance	VERB
cana-3933	64	20	the	the	DET
cana-3933	64	21	model	model	NOUN
cana-3933	64	22	's	's	PART
cana-3933	64	23	generalizability	generalizability	NOUN
cana-3933	64	24	.	.	PUNCT
cana-3933	65	1	the	the	DET
cana-3933	65	2	model	model	NOUN
cana-3933	65	3	training	training	NOUN
cana-3933	65	4	process	process	NOUN
cana-3933	65	5	begins	begin	VERB
cana-3933	65	6	with	with	ADP
cana-3933	65	7	data	datum	NOUN
cana-3933	65	8	preprocessing	preprocessing	NOUN
cana-3933	65	9	,	,	PUNCT
cana-3933	65	10	where	where	SCONJ
cana-3933	65	11	the	the	DET
cana-3933	65	12	dataset	dataset	NOUN
cana-3933	65	13	is	be	AUX
cana-3933	65	14	first	first	ADV
cana-3933	65	15	cleaned	clean	VERB
cana-3933	65	16	to	to	PART
cana-3933	65	17	handle	handle	VERB
cana-3933	65	18	missing	miss	VERB
cana-3933	65	19	values	value	NOUN
cana-3933	65	20	and	and	CCONJ
cana-3933	65	21	encode	encode	ADJ
cana-3933	65	22	categorical	categorical	ADJ
cana-3933	65	23	features	feature	NOUN
cana-3933	65	24	.	.	PUNCT
cana-3933	66	1	numerical	numerical	ADJ
cana-3933	66	2	features	feature	NOUN
cana-3933	66	3	are	be	AUX
cana-3933	66	4	standardized	standardize	VERB
cana-3933	66	5	to	to	PART
cana-3933	66	6	ensure	ensure	VERB
cana-3933	66	7	uniform	uniform	ADJ
cana-3933	66	8	data	datum	NOUN
cana-3933	66	9	distribution	distribution	NOUN
cana-3933	66	10	.	.	PUNCT
cana-3933	67	1	the	the	DET
cana-3933	67	2	dataset	dataset	NOUN
cana-3933	67	3	is	be	AUX
cana-3933	67	4	then	then	ADV
cana-3933	67	5	split	split	VERB
cana-3933	67	6	into	into	ADP
cana-3933	67	7	training	training	NOUN
cana-3933	67	8	and	and	CCONJ
cana-3933	67	9	testing	testing	NOUN
cana-3933	67	10	subsets	subset	NOUN
cana-3933	67	11	,	,	PUNCT
cana-3933	67	12	with	with	ADP
cana-3933	67	13	20	20	NUM
cana-3933	67	14	%	%	NOUN
cana-3933	67	15	of	of	ADP
cana-3933	67	16	the	the	DET
cana-3933	67	17	data	datum	NOUN
cana-3933	67	18	reserved	reserve	VERB
cana-3933	67	19	for	for	ADP
cana-3933	67	20	validation	validation	NOUN
cana-3933	67	21	.	.	PUNCT
cana-3933	68	1	the	the	DET
cana-3933	68	2	model	model	NOUN
cana-3933	68	3	is	be	AUX
cana-3933	68	4	compiled	compile	VERB
cana-3933	68	5	using	use	VERB
cana-3933	68	6	the	the	DET
cana-3933	68	7	adam	adam	PROPN
cana-3933	68	8	optimizer	optimizer	NOUN
cana-3933	68	9	and	and	CCONJ
cana-3933	68	10	binary	binary	PROPN
cana-3933	68	11	cross	cross	NOUN
cana-3933	68	12	-	-	ADJ
cana-3933	68	13	entropy	entropy	ADJ
cana-3933	68	14	loss	loss	NOUN
cana-3933	68	15	function	function	NOUN
cana-3933	68	16	,	,	PUNCT
cana-3933	68	17	and	and	CCONJ
cana-3933	68	18	trained	train	VERB
cana-3933	68	19	for	for	ADP
cana-3933	68	20	20	20	NUM
cana-3933	68	21	epochs	epoch	NOUN
cana-3933	68	22	with	with	ADP
cana-3933	68	23	a	a	DET
cana-3933	68	24	batch	batch	NOUN
cana-3933	68	25	size	size	NOUN
cana-3933	68	26	of	of	ADP
cana-3933	68	27	32	32	NUM
cana-3933	68	28	.	.	PUNCT
cana-3933	69	1	during	during	ADP
cana-3933	69	2	training	training	NOUN
cana-3933	69	3	,	,	PUNCT
cana-3933	69	4	the	the	DET
cana-3933	69	5	model	model	NOUN
cana-3933	69	6	's	's	PART
cana-3933	69	7	performance	performance	NOUN
cana-3933	69	8	is	be	AUX
cana-3933	69	9	evaluated	evaluate	VERB
cana-3933	69	10	using	use	VERB
cana-3933	69	11	a	a	DET
cana-3933	69	12	confusion	confusion	NOUN
cana-3933	69	13	matrix	matrix	NOUN
cana-3933	69	14	,	,	PUNCT
cana-3933	69	15	classification	classification	NOUN
cana-3933	69	16	report	report	NOUN
cana-3933	69	17	,	,	PUNCT
cana-3933	69	18	and	and	CCONJ
cana-3933	69	19	loss	loss	NOUN
cana-3933	69	20	and	and	CCONJ
cana-3933	69	21	accuracy	accuracy	NOUN
cana-3933	69	22	curves	curve	NOUN
cana-3933	69	23	.	.	PUNCT
cana-3933	70	1	communications	communication	NOUN
cana-3933	70	2	on	on	ADP
cana-3933	70	3	applied	apply	VERB
cana-3933	70	4	nonlinear	nonlinear	ADJ
cana-3933	70	5	analysis	analysis	NOUN
cana-3933	70	6	issn	issn	NOUN
cana-3933	70	7	:	:	PUNCT
cana-3933	70	8	1074	1074	NUM
cana-3933	70	9	-	-	PUNCT
cana-3933	70	10	133x	133x	NUM
cana-3933	70	11	vol	vol	NOUN
cana-3933	70	12	32	32	NUM
cana-3933	70	13	no	no	NOUN
cana-3933	70	14	.	.	PUNCT
cana-3933	71	1	9s	9s	NUM
cana-3933	71	2	(	(	PUNCT
cana-3933	71	3	2025	2025	NUM
cana-3933	71	4	)	)	PUNCT
cana-3933	71	5	365	365	NUM
cana-3933	71	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3933	71	7	to	to	PART
cana-3933	71	8	further	far	ADV
cana-3933	71	9	refine	refine	VERB
cana-3933	71	10	the	the	DET
cana-3933	71	11	model	model	NOUN
cana-3933	71	12	,	,	PUNCT
cana-3933	71	13	a	a	DET
cana-3933	71	14	congestion	congestion	NOUN
cana-3933	71	15	control	control	NOUN
cana-3933	71	16	discretization	discretization	NOUN
cana-3933	71	17	algorithm	algorithm	NOUN
cana-3933	71	18	(	(	PUNCT
cana-3933	71	19	ccda	ccda	PROPN
cana-3933	71	20	)	)	PUNCT
cana-3933	71	21	is	be	AUX
cana-3933	71	22	introduced	introduce	VERB
cana-3933	71	23	,	,	PUNCT
cana-3933	71	24	which	which	PRON
cana-3933	71	25	discretizes	discretize	VERB
cana-3933	71	26	the	the	DET
cana-3933	71	27	network	network	NOUN
cana-3933	71	28	congestion	congestion	NOUN
cana-3933	71	29	states	state	NOUN
cana-3933	71	30	and	and	CCONJ
cana-3933	71	31	derives	derive	VERB
cana-3933	71	32	optimal	optimal	ADJ
cana-3933	71	33	strategies	strategy	NOUN
cana-3933	71	34	for	for	ADP
cana-3933	71	35	congestion	congestion	NOUN
cana-3933	71	36	mitigation	mitigation	NOUN
cana-3933	71	37	using	use	VERB
cana-3933	71	38	optimal	optimal	ADJ
cana-3933	71	39	control	control	NOUN
cana-3933	71	40	theory	theory	NOUN
cana-3933	71	41	.	.	PUNCT
cana-3933	72	1	this	this	DET
cana-3933	72	2	algorithm	algorithm	NOUN
cana-3933	72	3	enables	enable	VERB
cana-3933	72	4	the	the	DET
cana-3933	72	5	model	model	NOUN
cana-3933	72	6	to	to	PART
cana-3933	72	7	dynamically	dynamically	ADV
cana-3933	72	8	adjust	adjust	VERB
cana-3933	72	9	routing	routing	NOUN
cana-3933	72	10	decisions	decision	NOUN
cana-3933	72	11	based	base	VERB
cana-3933	72	12	on	on	ADP
cana-3933	72	13	real	real	ADJ
cana-3933	72	14	-	-	PUNCT
cana-3933	72	15	time	time	NOUN
cana-3933	72	16	network	network	NOUN
cana-3933	72	17	conditions	condition	NOUN
cana-3933	72	18	,	,	PUNCT
cana-3933	72	19	minimizing	minimize	VERB
cana-3933	72	20	network	network	NOUN
cana-3933	72	21	delay	delay	NOUN
cana-3933	72	22	and	and	CCONJ
cana-3933	72	23	congestion	congestion	NOUN
cana-3933	72	24	costs	cost	NOUN
cana-3933	72	25	.	.	PUNCT
cana-3933	73	1	finally	finally	ADV
cana-3933	73	2	,	,	PUNCT
cana-3933	73	3	the	the	DET
cana-3933	73	4	proposed	propose	VERB
cana-3933	73	5	model	model	NOUN
cana-3933	73	6	is	be	AUX
cana-3933	73	7	evaluated	evaluate	VERB
cana-3933	73	8	through	through	ADP
cana-3933	73	9	extensive	extensive	ADJ
cana-3933	73	10	simulations	simulation	NOUN
cana-3933	73	11	,	,	PUNCT
cana-3933	73	12	measuring	measure	VERB
cana-3933	73	13	its	its	PRON
cana-3933	73	14	performance	performance	NOUN
cana-3933	73	15	across	across	ADP
cana-3933	73	16	various	various	ADJ
cana-3933	73	17	metrics	metric	NOUN
cana-3933	73	18	such	such	ADJ
cana-3933	73	19	as	as	ADP
cana-3933	73	20	accuracy	accuracy	NOUN
cana-3933	73	21	,	,	PUNCT
cana-3933	73	22	precision	precision	NOUN
cana-3933	73	23	,	,	PUNCT
cana-3933	73	24	recall	recall	NOUN
cana-3933	73	25	,	,	PUNCT
cana-3933	73	26	and	and	CCONJ
cana-3933	73	27	f1	f1	NOUN
cana-3933	73	28	-	-	PUNCT
cana-3933	73	29	score	score	NOUN
cana-3933	73	30	.	.	PUNCT
cana-3933	74	1	the	the	DET
cana-3933	74	2	impact	impact	NOUN
cana-3933	74	3	of	of	ADP
cana-3933	74	4	different	different	ADJ
cana-3933	74	5	parameters	parameter	NOUN
cana-3933	74	6	,	,	PUNCT
cana-3933	74	7	such	such	ADJ
cana-3933	74	8	as	as	ADP
cana-3933	74	9	congestion	congestion	NOUN
cana-3933	74	10	probability	probability	NOUN
cana-3933	74	11	and	and	CCONJ
cana-3933	74	12	delay	delay	NOUN
cana-3933	74	13	weight	weight	NOUN
cana-3933	74	14	,	,	PUNCT
cana-3933	74	15	on	on	ADP
cana-3933	74	16	network	network	NOUN
cana-3933	74	17	performance	performance	NOUN
cana-3933	74	18	is	be	AUX
cana-3933	74	19	also	also	ADV
cana-3933	74	20	analyzed	analyze	VERB
cana-3933	74	21	.	.	PUNCT
cana-3933	75	1	the	the	DET
cana-3933	75	2	results	result	NOUN
cana-3933	75	3	are	be	AUX
cana-3933	75	4	compared	compare	VERB
cana-3933	75	5	with	with	ADP
cana-3933	75	6	baseline	baseline	NOUN
cana-3933	75	7	models	model	NOUN
cana-3933	75	8	,	,	PUNCT
cana-3933	75	9	demonstrating	demonstrate	VERB
cana-3933	75	10	the	the	DET
cana-3933	75	11	proposed	propose	VERB
cana-3933	75	12	model	model	NOUN
cana-3933	75	13	's	's	PART
cana-3933	75	14	superior	superior	ADJ
cana-3933	75	15	capability	capability	NOUN
cana-3933	75	16	in	in	ADP
cana-3933	75	17	reducing	reduce	VERB
cana-3933	75	18	congestion	congestion	NOUN
cana-3933	75	19	and	and	CCONJ
cana-3933	75	20	enhancing	enhance	VERB
cana-3933	75	21	quality	quality	NOUN
cana-3933	75	22	of	of	ADP
cana-3933	75	23	service	service	NOUN
cana-3933	75	24	(	(	PUNCT
cana-3933	75	25	qos	qos	PROPN
cana-3933	75	26	)	)	PUNCT
cana-3933	75	27	in	in	ADP
cana-3933	75	28	manets	manet	NOUN
cana-3933	75	29	.	.	PUNCT
cana-3933	76	1	the	the	DET
cana-3933	76	2	low	low	ADJ
cana-3933	76	3	inference	inference	NOUN
cana-3933	76	4	time	time	NOUN
cana-3933	76	5	of	of	ADP
cana-3933	76	6	0.000063	0.000063	NUM
cana-3933	76	7	seconds	second	NOUN
cana-3933	76	8	per	per	ADP
cana-3933	76	9	sample	sample	NOUN
cana-3933	76	10	further	further	ADJ
cana-3933	76	11	highlights	highlight	NOUN
cana-3933	76	12	the	the	DET
cana-3933	76	13	model	model	NOUN
cana-3933	76	14	's	's	PART
cana-3933	76	15	efficiency	efficiency	NOUN
cana-3933	76	16	for	for	ADP
cana-3933	76	17	real	real	ADJ
cana-3933	76	18	-	-	PUNCT
cana-3933	76	19	time	time	NOUN
cana-3933	76	20	applications	application	NOUN
cana-3933	76	21	,	,	PUNCT
cana-3933	76	22	making	make	VERB
cana-3933	76	23	it	it	PRON
cana-3933	76	24	a	a	DET
cana-3933	76	25	viable	viable	ADJ
cana-3933	76	26	solution	solution	NOUN
cana-3933	76	27	for	for	ADP
cana-3933	76	28	congestion	congestion	NOUN
cana-3933	76	29	control	control	NOUN
cana-3933	76	30	in	in	ADP
cana-3933	76	31	dynamic	dynamic	ADJ
cana-3933	76	32	network	network	NOUN
cana-3933	76	33	environments	environment	NOUN
cana-3933	76	34	.	.	PUNCT
cana-3933	77	1	a.	a.	NOUN
cana-3933	77	2	neural	neural	PROPN
cana-3933	77	3	network	network	PROPN
cana-3933	77	4	training	training	NOUN
cana-3933	77	5	algorithm	algorithm	NOUN
cana-3933	77	6	a	a	DET
cana-3933	77	7	)	)	PUNCT
cana-3933	77	8	input	input	NOUN
cana-3933	77	9	:	:	PUNCT
cana-3933	77	10	preprocessed	preprocesse	VERB
cana-3933	77	11	training	training	NOUN
cana-3933	77	12	data	datum	NOUN
cana-3933	77	13	xtrain	xtrain	NOUN
cana-3933	77	14	and	and	CCONJ
cana-3933	77	15	ytrain	ytrain	NOUN
cana-3933	77	16	.	.	PUNCT
cana-3933	78	1	b	b	X
cana-3933	78	2	)	)	PUNCT
cana-3933	78	3	initialize	initialize	NOUN
cana-3933	78	4	:	:	PUNCT
cana-3933	78	5	o	o	NOUN
cana-3933	78	6	neural	neural	ADJ
cana-3933	78	7	network	network	NOUN
cana-3933	78	8	with	with	ADP
cana-3933	78	9	three	three	NUM
cana-3933	78	10	hidden	hidden	ADJ
cana-3933	78	11	layers	layer	NOUN
cana-3933	78	12	:	:	PUNCT
cana-3933	78	13	64	64	NUM
cana-3933	78	14	,	,	PUNCT
cana-3933	78	15	128	128	NUM
cana-3933	78	16	,	,	PUNCT
cana-3933	78	17	and	and	CCONJ
cana-3933	78	18	256	256	NUM
cana-3933	78	19	units	unit	NOUN
cana-3933	78	20	respectively	respectively	ADV
cana-3933	78	21	.	.	PUNCT
cana-3933	79	1	o	o	NOUN
cana-3933	79	2	activation	activation	NOUN
cana-3933	79	3	function	function	NOUN
cana-3933	79	4	:	:	PUNCT
cana-3933	79	5	relu	relu	NOUN
cana-3933	79	6	for	for	ADP
cana-3933	79	7	hidden	hidden	ADJ
cana-3933	79	8	layers	layer	NOUN
cana-3933	79	9	,	,	PUNCT
cana-3933	79	10	sigmoid	sigmoid	NOUN
cana-3933	79	11	for	for	ADP
cana-3933	79	12	the	the	DET
cana-3933	79	13	output	output	NOUN
cana-3933	79	14	layer	layer	NOUN
cana-3933	79	15	.	.	PUNCT
cana-3933	80	1	o	o	NOUN
cana-3933	80	2	dropout	dropout	NOUN
cana-3933	80	3	layer	layer	NOUN
cana-3933	80	4	with	with	ADP
cana-3933	80	5	0.3	0.3	NUM
cana-3933	80	6	probability	probability	NOUN
cana-3933	80	7	after	after	ADP
cana-3933	80	8	the	the	DET
cana-3933	80	9	second	second	ADJ
cana-3933	80	10	hidden	hide	VERB
cana-3933	80	11	layer	layer	NOUN
cana-3933	80	12	.	.	PUNCT
cana-3933	81	1	c	c	X
cana-3933	81	2	)	)	PUNCT
cana-3933	81	3	compile	compile	NOUN
cana-3933	81	4	:	:	PUNCT
cana-3933	81	5	o	o	NOUN
cana-3933	81	6	loss	loss	NOUN
cana-3933	81	7	function	function	NOUN
cana-3933	81	8	:	:	PUNCT
cana-3933	82	1	binary	binary	PROPN
cana-3933	82	2	cross	cross	PROPN
cana-3933	82	3	-	-	NOUN
cana-3933	82	4	entropy	entropy	NOUN
cana-3933	82	5	.	.	PUNCT
cana-3933	83	1	o	o	NOUN
cana-3933	83	2	optimizer	optimizer	NOUN
cana-3933	83	3	:	:	PUNCT
cana-3933	83	4	adam	adam	PROPN
cana-3933	83	5	.	.	PUNCT
cana-3933	84	1	d	d	X
cana-3933	84	2	)	)	PUNCT
cana-3933	84	3	training	training	NOUN
cana-3933	84	4	:	:	PUNCT
cana-3933	84	5	o	o	NOUN
cana-3933	84	6	train	train	VERB
cana-3933	84	7	the	the	DET
cana-3933	84	8	model	model	NOUN
cana-3933	84	9	on	on	ADP
cana-3933	84	10	xtrain	xtrain	PROPN
cana-3933	84	11	and	and	CCONJ
cana-3933	84	12	y	y	PROPN
cana-3933	84	13	train	train	VERB
cana-3933	84	14	for	for	ADP
cana-3933	84	15	20	20	NUM
cana-3933	84	16	epochs	epoch	NOUN
cana-3933	84	17	with	with	ADP
cana-3933	84	18	a	a	DET
cana-3933	84	19	batch	batch	NOUN
cana-3933	84	20	size	size	NOUN
cana-3933	84	21	of	of	ADP
cana-3933	84	22	32	32	NUM
cana-3933	84	23	.	.	PUNCT
cana-3933	85	1	o	o	NOUN
cana-3933	85	2	use	use	NOUN
cana-3933	85	3	20	20	NUM
cana-3933	85	4	%	%	NOUN
cana-3933	85	5	of	of	ADP
cana-3933	85	6	the	the	DET
cana-3933	85	7	data	datum	NOUN
cana-3933	85	8	as	as	ADP
cana-3933	85	9	a	a	DET
cana-3933	85	10	validation	validation	NOUN
cana-3933	85	11	set	set	NOUN
cana-3933	85	12	.	.	PUNCT
cana-3933	86	1	e	e	X
cana-3933	86	2	)	)	PUNCT
cana-3933	86	3	prediction	prediction	NOUN
cana-3933	86	4	:	:	PUNCT
cana-3933	86	5	o	o	NOUN
cana-3933	86	6	predict	predict	VERB
cana-3933	86	7	on	on	ADP
cana-3933	86	8	xtest	xtest	PROPN
cana-3933	86	9	and	and	CCONJ
cana-3933	86	10	threshold	threshold	VERB
cana-3933	86	11	the	the	DET
cana-3933	86	12	output	output	NOUN
cana-3933	86	13	to	to	ADP
cana-3933	86	14	0.5	0.5	NUM
cana-3933	86	15	to	to	PART
cana-3933	86	16	get	get	VERB
cana-3933	86	17	binary	binary	ADJ
cana-3933	86	18	class	class	NOUN
cana-3933	86	19	labels	label	NOUN
cana-3933	86	20	.	.	PUNCT
cana-3933	87	1	f	f	X
cana-3933	87	2	)	)	PUNCT
cana-3933	87	3	evaluation	evaluation	NOUN
cana-3933	87	4	:	:	PUNCT
cana-3933	87	5	o	o	NOUN
cana-3933	87	6	calculate	calculate	NOUN
cana-3933	87	7	accuracy	accuracy	NOUN
cana-3933	87	8	,	,	PUNCT
cana-3933	87	9	confusion	confusion	NOUN
cana-3933	87	10	matrix	matrix	NOUN
cana-3933	87	11	,	,	PUNCT
cana-3933	87	12	and	and	CCONJ
cana-3933	87	13	classification	classification	NOUN
cana-3933	87	14	report	report	NOUN
cana-3933	87	15	.	.	PUNCT
cana-3933	88	1	b.	b.	PROPN
cana-3933	88	2	mathematical	mathematical	PROPN
cana-3933	88	3	model	model	PROPN
cana-3933	88	4	a	a	PRON
cana-3933	88	5	)	)	PUNCT
cana-3933	88	6	standardization	standardization	NOUN
cana-3933	88	7	•	•	NOUN
cana-3933	88	8	standardization	standardization	NOUN
cana-3933	88	9	of	of	ADP
cana-3933	88	10	features	feature	NOUN
cana-3933	88	11	is	be	AUX
cana-3933	88	12	given	give	VERB
cana-3933	88	13	by	by	ADP
cana-3933	88	14	:	:	PUNCT
cana-3933	88	15	z	z	PROPN
cana-3933	88	16	=	=	SYM
cana-3933	88	17	x−	x−	PROPN
cana-3933	88	18	μ	μ	PROPN
cana-3933	88	19	σ	σ	PROPN
cana-3933	89	1	where	where	SCONJ
cana-3933	89	2	:	:	PUNCT
cana-3933	89	3	x	x	SYM
cana-3933	89	4	=	=	PUNCT
cana-3933	89	5	original	original	ADJ
cana-3933	89	6	value	value	NOUN
cana-3933	89	7	μ	μ	NOUN
cana-3933	89	8	=	=	SYM
cana-3933	89	9	mean	mean	NOUN
cana-3933	89	10	of	of	ADP
cana-3933	89	11	the	the	DET
cana-3933	89	12	feature	feature	NOUN
cana-3933	89	13	σ	σ	NOUN
cana-3933	89	14	=	=	SYM
cana-3933	89	15	standard	standard	ADJ
cana-3933	89	16	deviation	deviation	NOUN
cana-3933	89	17	of	of	ADP
cana-3933	89	18	the	the	DET
cana-3933	89	19	feature	feature	NOUN
cana-3933	89	20	𝑚𝑡	𝑚𝑡	ADP
cana-3933	89	21	=	=	SYM
cana-3933	89	22	𝛽𝑡𝑚𝑡−1	𝛽𝑡𝑚𝑡−1	PROPN
cana-3933	89	23	+	+	CCONJ
cana-3933	89	24	(	(	PUNCT
cana-3933	89	25	1	1	NUM
cana-3933	89	26	−	−	PROPN
cana-3933	89	27	𝛽1)𝑔𝑡	𝛽1)𝑔𝑡	PROPN
cana-3933	89	28	(	(	PUNCT
cana-3933	89	29	1	1	NUM
cana-3933	89	30	)	)	PUNCT
cana-3933	89	31	communications	communication	NOUN
cana-3933	89	32	on	on	ADP
cana-3933	89	33	applied	apply	VERB
cana-3933	89	34	nonlinear	nonlinear	ADJ
cana-3933	89	35	analysis	analysis	NOUN
cana-3933	89	36	issn	issn	NOUN
cana-3933	89	37	:	:	PUNCT
cana-3933	89	38	1074	1074	NUM
cana-3933	89	39	-	-	PUNCT
cana-3933	89	40	133x	133x	NUM
cana-3933	89	41	vol	vol	NOUN
cana-3933	89	42	32	32	NUM
cana-3933	89	43	no	no	NOUN
cana-3933	89	44	.	.	PUNCT
cana-3933	90	1	9s	9s	NUM
cana-3933	90	2	(	(	PUNCT
cana-3933	90	3	2025	2025	NUM
cana-3933	90	4	)	)	PUNCT
cana-3933	90	5	366	366	NUM
cana-3933	90	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3933	90	7	𝑣𝑡	𝑣𝑡	ADP
cana-3933	90	8	=	=	SYM
cana-3933	90	9	𝛽𝑡𝑣𝑡−1	𝛽𝑡𝑣𝑡−1	X
cana-3933	90	10	+	+	CCONJ
cana-3933	90	11	(	(	PUNCT
cana-3933	90	12	1	1	NUM
cana-3933	90	13	−	−	PROPN
cana-3933	90	14	𝛽1)𝑔𝑡	𝛽1)𝑔𝑡	PROPN
cana-3933	90	15	(	(	PUNCT
cana-3933	90	16	2	2	NUM
cana-3933	90	17	)	)	PUNCT
cana-3933	90	18	𝑚𝑡	𝑚𝑡	ADP
cana-3933	90	19	`	`	PUNCT
cana-3933	90	20	=	=	SYM
cana-3933	90	21	𝑚𝑡	𝑚𝑡	ADP
cana-3933	90	22	1	1	NUM
cana-3933	90	23	−	−	PROPN
cana-3933	90	24	𝛽1	𝛽1	PROPN
cana-3933	90	25	𝑡	𝑡	X
cana-3933	90	26	(	(	PUNCT
cana-3933	90	27	3	3	NUM
cana-3933	90	28	)	)	PUNCT
cana-3933	90	29	𝑣𝑡	𝑣𝑡	ADP
cana-3933	90	30	`	`	PUNCT
cana-3933	90	31	=	=	PUNCT
cana-3933	91	1	𝑣𝑡	𝑣𝑡	ADP
cana-3933	91	2	1−𝛽1	1−𝛽1	NUM
cana-3933	91	3	𝑡	𝑡	NOUN
cana-3933	91	4	(	(	PUNCT
cana-3933	91	5	4	4	NUM
cana-3933	91	6	)	)	PUNCT
cana-3933	91	7	b.	b.	NOUN
cana-3933	91	8	architecture	architecture	NOUN
cana-3933	91	9	the	the	DET
cana-3933	91	10	figure	figure	NOUN
cana-3933	91	11	1	1	NUM
cana-3933	91	12	,	,	PUNCT
cana-3933	91	13	2	2	NUM
cana-3933	91	14	illustrates	illustrate	VERB
cana-3933	91	15	a	a	DET
cana-3933	91	16	detailed	detailed	ADJ
cana-3933	91	17	performance	performance	NOUN
cana-3933	91	18	evaluation	evaluation	NOUN
cana-3933	91	19	of	of	ADP
cana-3933	91	20	a	a	DET
cana-3933	91	21	machine	machine	NOUN
cana-3933	91	22	learning	learn	VERB
cana-3933	91	23	model	model	NOUN
cana-3933	91	24	used	use	VERB
cana-3933	91	25	to	to	PART
cana-3933	91	26	classify	classify	VERB
cana-3933	91	27	data	datum	NOUN
cana-3933	91	28	into	into	ADP
cana-3933	91	29	'	'	PUNCT
cana-3933	91	30	normal	normal	ADJ
cana-3933	91	31	'	'	PUNCT
cana-3933	91	32	and	and	CCONJ
cana-3933	91	33	'	'	PUNCT
cana-3933	91	34	anomaly	anomaly	NOUN
cana-3933	91	35	'	'	PUNCT
cana-3933	91	36	categories	category	NOUN
cana-3933	91	37	.	.	PUNCT
cana-3933	92	1	:	:	PUNCT
cana-3933	92	2	i.	i.	PROPN
cana-3933	92	3	classification	classification	PROPN
cana-3933	92	4	report	report	NOUN
cana-3933	92	5	:	:	PUNCT
cana-3933	92	6	this	this	DET
cana-3933	92	7	section	section	NOUN
cana-3933	92	8	presents	present	VERB
cana-3933	92	9	the	the	DET
cana-3933	92	10	precision	precision	NOUN
cana-3933	92	11	,	,	PUNCT
cana-3933	92	12	recall	recall	NOUN
cana-3933	92	13	,	,	PUNCT
cana-3933	92	14	and	and	CCONJ
cana-3933	92	15	f1	f1	NOUN
cana-3933	92	16	-	-	PUNCT
cana-3933	92	17	score	score	NOUN
cana-3933	92	18	for	for	ADP
cana-3933	92	19	each	each	DET
cana-3933	92	20	class	class	NOUN
cana-3933	92	21	(	(	PUNCT
cana-3933	92	22	normal	normal	ADJ
cana-3933	92	23	and	and	CCONJ
cana-3933	92	24	anomaly	anomaly	NOUN
cana-3933	92	25	)	)	PUNCT
cana-3933	92	26	along	along	ADP
cana-3933	92	27	with	with	ADP
cana-3933	92	28	overall	overall	ADJ
cana-3933	92	29	accuracy	accuracy	NOUN
cana-3933	92	30	:	:	PUNCT
cana-3933	92	31	•	•	ADP
cana-3933	92	32	both	both	DET
cana-3933	92	33	classes	class	NOUN
cana-3933	92	34	show	show	VERB
cana-3933	92	35	very	very	ADV
cana-3933	92	36	high	high	ADJ
cana-3933	92	37	precision	precision	NOUN
cana-3933	92	38	,	,	PUNCT
cana-3933	92	39	recall	recall	NOUN
cana-3933	92	40	,	,	PUNCT
cana-3933	92	41	and	and	CCONJ
cana-3933	92	42	f1	f1	ADJ
cana-3933	92	43	-	-	PUNCT
cana-3933	92	44	score	score	NOUN
cana-3933	92	45	values	value	NOUN
cana-3933	92	46	of	of	ADP
cana-3933	92	47	0.99	0.99	NUM
cana-3933	92	48	,	,	PUNCT
cana-3933	92	49	indicating	indicate	VERB
cana-3933	92	50	excellent	excellent	ADJ
cana-3933	92	51	model	model	NOUN
cana-3933	92	52	performance	performance	NOUN
cana-3933	92	53	in	in	ADP
cana-3933	92	54	correctly	correctly	ADV
cana-3933	92	55	identifying	identify	VERB
cana-3933	92	56	and	and	CCONJ
cana-3933	92	57	classifying	classify	VERB
cana-3933	92	58	each	each	DET
cana-3933	92	59	class	class	NOUN
cana-3933	92	60	.	.	PUNCT
cana-3933	93	1	•	•	NUM
cana-3933	93	2	the	the	DET
cana-3933	93	3	support	support	NOUN
cana-3933	93	4	column	column	NOUN
cana-3933	93	5	indicates	indicate	VERB
cana-3933	93	6	the	the	DET
cana-3933	93	7	number	number	NOUN
cana-3933	93	8	of	of	ADP
cana-3933	93	9	samples	sample	NOUN
cana-3933	93	10	for	for	ADP
cana-3933	93	11	each	each	DET
cana-3933	93	12	class	class	NOUN
cana-3933	93	13	,	,	PUNCT
cana-3933	93	14	with	with	ADP
cana-3933	93	15	3516	3516	NUM
cana-3933	93	16	for	for	ADP
cana-3933	93	17	normal	normal	ADJ
cana-3933	93	18	and	and	CCONJ
cana-3933	93	19	4042	4042	NUM
cana-3933	93	20	for	for	ADP
cana-3933	93	21	anomaly	anomaly	NOUN
cana-3933	93	22	.	.	PUNCT
cana-3933	94	1	•	•	NUM
cana-3933	94	2	the	the	DET
cana-3933	94	3	overall	overall	ADJ
cana-3933	94	4	accuracy	accuracy	NOUN
cana-3933	94	5	is	be	AUX
cana-3933	94	6	0.99	0.99	NUM
cana-3933	94	7	,	,	PUNCT
cana-3933	94	8	alongside	alongside	ADP
cana-3933	94	9	macro	macro	NOUN
cana-3933	94	10	and	and	CCONJ
cana-3933	94	11	weighted	weight	VERB
cana-3933	94	12	averages	average	NOUN
cana-3933	94	13	for	for	ADP
cana-3933	94	14	precision	precision	NOUN
cana-3933	94	15	,	,	PUNCT
cana-3933	94	16	recall	recall	NOUN
cana-3933	94	17	,	,	PUNCT
cana-3933	94	18	and	and	CCONJ
cana-3933	94	19	f1	f1	NOUN
cana-3933	94	20	-	-	PUNCT
cana-3933	94	21	score	score	NOUN
cana-3933	94	22	all	all	PRON
cana-3933	94	23	being	be	AUX
cana-3933	94	24	0.99	0.99	NUM
cana-3933	94	25	,	,	PUNCT
cana-3933	94	26	confirming	confirm	VERB
cana-3933	94	27	the	the	DET
cana-3933	94	28	model	model	NOUN
cana-3933	94	29	's	's	PART
cana-3933	94	30	robustness	robustness	NOUN
cana-3933	94	31	across	across	ADP
cana-3933	94	32	different	different	ADJ
cana-3933	94	33	evaluations	evaluation	NOUN
cana-3933	94	34	.	.	PUNCT
cana-3933	95	1	andle	andle	NOUN
cana-3933	95	2	issing	isse	VERB
cana-3933	95	3	alues	alue	VERB
cana-3933	95	4	ncode	ncode	PROPN
cana-3933	95	5	ategorical	ategorical	PROPN
cana-3933	95	6	ata	ata	PROPN
cana-3933	95	7	cale	cale	PROPN
cana-3933	95	8	umerical	umerical	ADJ
cana-3933	95	9	rain	rain	NOUN
cana-3933	95	10	est	est	X
cana-3933	95	11	plit	plit	VERB
cana-3933	95	12	uild	uild	PROPN
cana-3933	95	13	eural	eural	PROPN
cana-3933	95	14	etwork	etwork	PROPN
cana-3933	95	15	odel	odel	PROPN
cana-3933	95	16	raining	rain	VERB
cana-3933	95	17	ompile	ompile	VERB
cana-3933	95	18	the	the	DET
cana-3933	95	19	odel	odel	ADJ
cana-3933	95	20	rain	rain	NOUN
cana-3933	95	21	the	the	DET
cana-3933	95	22	odel	odel	PROPN
cana-3933	95	23	odel	odel	PROPN
cana-3933	95	24	valuation	valuation	PROPN
cana-3933	95	25	redict	redict	PROPN
cana-3933	95	26	on	on	ADP
cana-3933	95	27	est	est	X
cana-3933	95	28	ata	ata	AUX
cana-3933	95	29	alculate	alculate	VERB
cana-3933	95	30	etrics	etric	NOUN
cana-3933	95	31	communications	communication	NOUN
cana-3933	95	32	on	on	ADP
cana-3933	95	33	applied	apply	VERB
cana-3933	95	34	nonlinear	nonlinear	ADJ
cana-3933	95	35	analysis	analysis	NOUN
cana-3933	95	36	issn	issn	NOUN
cana-3933	95	37	:	:	PUNCT
cana-3933	95	38	1074	1074	NUM
cana-3933	95	39	-	-	PUNCT
cana-3933	95	40	133x	133x	NUM
cana-3933	95	41	vol	vol	NOUN
cana-3933	95	42	32	32	NUM
cana-3933	95	43	no	no	NOUN
cana-3933	95	44	.	.	PUNCT
cana-3933	96	1	9s	9s	NUM
cana-3933	96	2	(	(	PUNCT
cana-3933	96	3	2025	2025	NUM
cana-3933	96	4	)	)	PUNCT
cana-3933	96	5	367	367	NUM
cana-3933	97	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-3933	97	2	ii	ii	PROPN
cana-3933	97	3	.	.	PUNCT
cana-3933	97	4	training	training	NOUN
cana-3933	97	5	and	and	CCONJ
cana-3933	97	6	validation	validation	NOUN
cana-3933	97	7	loss	loss	NOUN
cana-3933	97	8	:	:	PUNCT
cana-3933	97	9	•	•	ADP
cana-3933	97	10	the	the	DET
cana-3933	97	11	graph	graph	NOUN
cana-3933	97	12	shows	show	VERB
cana-3933	97	13	the	the	DET
cana-3933	97	14	loss	loss	NOUN
cana-3933	97	15	metrics	metric	NOUN
cana-3933	97	16	over	over	ADP
cana-3933	97	17	17.5	17.5	NUM
cana-3933	97	18	epochs	epoch	NOUN
cana-3933	97	19	.	.	PUNCT
cana-3933	98	1	the	the	DET
cana-3933	98	2	training	training	NOUN
cana-3933	98	3	loss	loss	NOUN
cana-3933	98	4	(	(	PUNCT
cana-3933	98	5	blue	blue	ADJ
cana-3933	98	6	line	line	NOUN
cana-3933	98	7	)	)	PUNCT
cana-3933	98	8	starts	start	VERB
cana-3933	98	9	higher	high	ADJ
cana-3933	98	10	and	and	CCONJ
cana-3933	98	11	quickly	quickly	ADV
cana-3933	98	12	decreases	decrease	VERB
cana-3933	98	13	,	,	PUNCT
cana-3933	98	14	stabilizing	stabilize	VERB
cana-3933	98	15	close	close	ADV
cana-3933	98	16	to	to	ADP
cana-3933	98	17	zero	zero	NUM
cana-3933	98	18	.	.	PUNCT
cana-3933	99	1	the	the	DET
cana-3933	99	2	validation	validation	NOUN
cana-3933	99	3	loss	loss	NOUN
cana-3933	99	4	(	(	PUNCT
cana-3933	99	5	orange	orange	ADJ
cana-3933	99	6	line	line	NOUN
cana-3933	99	7	)	)	PUNCT
cana-3933	99	8	starts	start	VERB
cana-3933	99	9	lower	lower	ADV
cana-3933	99	10	and	and	CCONJ
cana-3933	99	11	closely	closely	ADV
cana-3933	99	12	follows	follow	VERB
cana-3933	99	13	the	the	DET
cana-3933	99	14	training	training	NOUN
cana-3933	99	15	loss	loss	NOUN
cana-3933	99	16	,	,	PUNCT
cana-3933	99	17	suggesting	suggest	VERB
cana-3933	99	18	good	good	ADJ
cana-3933	99	19	generalization	generalization	NOUN
cana-3933	99	20	of	of	ADP
cana-3933	99	21	the	the	DET
cana-3933	99	22	model	model	NOUN
cana-3933	99	23	without	without	ADP
cana-3933	99	24	significant	significant	ADJ
cana-3933	99	25	overfitting	overfitting	NOUN
cana-3933	99	26	.	.	PUNCT
cana-3933	100	1	iii	iii	X
cana-3933	100	2	.	.	PUNCT
cana-3933	100	3	training	training	NOUN
cana-3933	100	4	and	and	CCONJ
cana-3933	100	5	validation	validation	NOUN
cana-3933	100	6	accuracy	accuracy	NOUN
cana-3933	100	7	:	:	PUNCT
cana-3933	100	8	•	•	ADP
cana-3933	100	9	this	this	DET
cana-3933	100	10	graph	graph	NOUN
cana-3933	100	11	tracks	track	VERB
cana-3933	100	12	the	the	DET
cana-3933	100	13	accuracy	accuracy	NOUN
cana-3933	100	14	over	over	ADP
cana-3933	100	15	the	the	DET
cana-3933	100	16	same	same	ADJ
cana-3933	100	17	17.5	17.5	NUM
cana-3933	100	18	epochs	epoch	NOUN
cana-3933	100	19	.	.	PUNCT
cana-3933	101	1	both	both	DET
cana-3933	101	2	training	training	NOUN
cana-3933	101	3	(	(	PUNCT
cana-3933	101	4	blue	blue	ADJ
cana-3933	101	5	line	line	NOUN
cana-3933	101	6	)	)	PUNCT
cana-3933	101	7	and	and	CCONJ
cana-3933	101	8	validation	validation	NOUN
cana-3933	101	9	(	(	PUNCT
cana-3933	101	10	orange	orange	ADJ
cana-3933	101	11	line	line	NOUN
cana-3933	101	12	)	)	PUNCT
cana-3933	101	13	accuracy	accuracy	NOUN
cana-3933	101	14	metrics	metric	NOUN
cana-3933	101	15	increase	increase	VERB
cana-3933	101	16	over	over	ADP
cana-3933	101	17	time	time	NOUN
cana-3933	101	18	,	,	PUNCT
cana-3933	101	19	with	with	ADP
cana-3933	101	20	training	training	NOUN
cana-3933	101	21	accuracy	accuracy	NOUN
cana-3933	101	22	consistently	consistently	ADV
cana-3933	101	23	slightly	slightly	ADV
cana-3933	101	24	higher	high	ADJ
cana-3933	101	25	than	than	ADP
cana-3933	101	26	validation	validation	NOUN
cana-3933	101	27	accuracy	accuracy	NOUN
cana-3933	101	28	.	.	PUNCT
cana-3933	102	1	the	the	DET
cana-3933	102	2	model	model	NOUN
cana-3933	102	3	achieves	achieve	VERB
cana-3933	102	4	near	near	ADP
cana-3933	102	5	98	98	NUM
cana-3933	102	6	%	%	NOUN
cana-3933	102	7	accuracy	accuracy	NOUN
cana-3933	102	8	by	by	ADP
cana-3933	102	9	the	the	DET
cana-3933	102	10	last	last	ADJ
cana-3933	102	11	epoch	epoch	NOUN
cana-3933	102	12	,	,	PUNCT
cana-3933	102	13	showing	show	VERB
cana-3933	102	14	effective	effective	ADJ
cana-3933	102	15	learning	learning	NOUN
cana-3933	102	16	and	and	CCONJ
cana-3933	102	17	adaptation	adaptation	NOUN
cana-3933	102	18	to	to	ADP
cana-3933	102	19	both	both	PRON
cana-3933	102	20	training	training	NOUN
cana-3933	102	21	and	and	CCONJ
cana-3933	102	22	unseen	unseen	ADJ
cana-3933	102	23	validation	validation	NOUN
cana-3933	102	24	data	datum	NOUN
cana-3933	102	25	.	.	PUNCT
cana-3933	103	1	4.result	4.result	NUM
cana-3933	103	2	analysis	analysis	NOUN
cana-3933	103	3	figure	figure	NOUN
cana-3933	103	4	1	1	NUM
cana-3933	103	5	confusion	confusion	NOUN
cana-3933	103	6	matrix	matrix	NOUN
cana-3933	103	7	figure	figure	NOUN
cana-3933	103	8	2	2	NUM
cana-3933	103	9	classification	classification	NOUN
cana-3933	103	10	report	report	NOUN
cana-3933	103	11	communications	communication	NOUN
cana-3933	103	12	on	on	ADP
cana-3933	103	13	applied	apply	VERB
cana-3933	103	14	nonlinear	nonlinear	ADJ
cana-3933	103	15	analysis	analysis	NOUN
cana-3933	103	16	issn	issn	NOUN
cana-3933	103	17	:	:	PUNCT
cana-3933	103	18	1074	1074	NUM
cana-3933	103	19	-	-	PUNCT
cana-3933	103	20	133x	133x	NUM
cana-3933	103	21	vol	vol	NOUN
cana-3933	103	22	32	32	NUM
cana-3933	103	23	no	no	NOUN
cana-3933	103	24	.	.	PUNCT
cana-3933	104	1	9s	9s	NUM
cana-3933	104	2	(	(	PUNCT
cana-3933	104	3	2025	2025	NUM
cana-3933	104	4	)	)	PUNCT
cana-3933	104	5	368	368	NUM
cana-3933	105	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-3933	105	2	figure	figure	NOUN
cana-3933	105	3	3	3	NUM
cana-3933	105	4	roc	roc	PROPN
cana-3933	105	5	curve	curve	NOUN
cana-3933	105	6	of	of	ADP
cana-3933	105	7	proposed	propose	VERB
cana-3933	105	8	model	model	NOUN
cana-3933	105	9	figure	figure	NOUN
cana-3933	105	10	4	4	NUM
cana-3933	105	11	p	p	NOUN
cana-3933	105	12	-	-	PUNCT
cana-3933	105	13	r	r	NOUN
cana-3933	105	14	curve	curve	NOUN
cana-3933	105	15	of	of	ADP
cana-3933	105	16	proposed	propose	VERB
cana-3933	105	17	mode	mode	NOUN
cana-3933	105	18	the	the	DET
cana-3933	105	19	model	model	NOUN
cana-3933	105	20	produced	produce	VERB
cana-3933	105	21	41	41	NUM
cana-3933	105	22	false	false	ADJ
cana-3933	105	23	positives	positive	NOUN
cana-3933	105	24	and	and	CCONJ
cana-3933	105	25	51	51	NUM
cana-3933	105	26	false	false	ADJ
cana-3933	105	27	negatives	negative	NOUN
cana-3933	105	28	,	,	PUNCT
cana-3933	105	29	indicating	indicate	VERB
cana-3933	105	30	that	that	SCONJ
cana-3933	105	31	a	a	DET
cana-3933	105	32	small	small	ADJ
cana-3933	105	33	number	number	NOUN
cana-3933	105	34	of	of	ADP
cana-3933	105	35	normal	normal	ADJ
cana-3933	105	36	instances	instance	NOUN
cana-3933	105	37	were	be	AUX
cana-3933	105	38	incorrectly	incorrectly	ADV
cana-3933	105	39	classified	classify	VERB
cana-3933	105	40	as	as	ADP
cana-3933	105	41	anomalies	anomaly	NOUN
cana-3933	105	42	,	,	PUNCT
cana-3933	105	43	and	and	CCONJ
cana-3933	105	44	vice	vice	ADV
cana-3933	105	45	versa	versa	ADV
cana-3933	105	46	.	.	PUNCT
cana-3933	106	1	the	the	DET
cana-3933	106	2	inference	inference	NOUN
cana-3933	106	3	time	time	NOUN
cana-3933	106	4	per	per	ADP
cana-3933	106	5	sample	sample	NOUN
cana-3933	106	6	is	be	AUX
cana-3933	106	7	extremely	extremely	ADV
cana-3933	106	8	low	low	ADJ
cana-3933	106	9	at	at	ADP
cana-3933	106	10	0.000063	0.000063	NUM
cana-3933	106	11	seconds	second	NOUN
cana-3933	106	12	,	,	PUNCT
cana-3933	106	13	demonstrating	demonstrate	VERB
cana-3933	106	14	the	the	DET
cana-3933	106	15	model	model	NOUN
cana-3933	106	16	's	's	PART
cana-3933	106	17	efficiency	efficiency	NOUN
cana-3933	106	18	in	in	ADP
cana-3933	106	19	making	make	VERB
cana-3933	106	20	predictions	prediction	NOUN
cana-3933	106	21	.	.	PUNCT
cana-3933	107	1	cross	cross	ADJ
cana-3933	107	2	-	-	NOUN
cana-3933	107	3	validation	validation	NOUN
cana-3933	107	4	,	,	PUNCT
cana-3933	107	5	which	which	PRON
cana-3933	107	6	was	be	AUX
cana-3933	107	7	conducted	conduct	VERB
cana-3933	107	8	over	over	ADP
cana-3933	107	9	five	five	NUM
cana-3933	107	10	folds	fold	NOUN
cana-3933	107	11	,	,	PUNCT
cana-3933	107	12	yielded	yield	VERB
cana-3933	107	13	accuracy	accuracy	NOUN
cana-3933	107	14	scores	score	NOUN
cana-3933	107	15	ranging	range	VERB
cana-3933	107	16	from	from	ADP
cana-3933	107	17	0.9739	0.9739	NUM
cana-3933	107	18	to	to	ADP
cana-3933	107	19	0.9829	0.9829	NUM
cana-3933	107	20	,	,	PUNCT
cana-3933	107	21	with	with	ADP
cana-3933	107	22	an	an	DET
cana-3933	107	23	average	average	ADJ
cana-3933	107	24	accuracy	accuracy	NOUN
cana-3933	107	25	of	of	ADP
cana-3933	107	26	0.9791	0.9791	NUM
cana-3933	107	27	,	,	PUNCT
cana-3933	107	28	further	far	ADV
cana-3933	107	29	confirming	confirm	VERB
cana-3933	107	30	the	the	DET
cana-3933	107	31	model	model	NOUN
cana-3933	107	32	's	's	PART
cana-3933	107	33	high	high	ADJ
cana-3933	107	34	performance	performance	NOUN
cana-3933	107	35	and	and	CCONJ
cana-3933	107	36	generalizability	generalizability	NOUN
cana-3933	107	37	across	across	ADP
cana-3933	107	38	different	different	ADJ
cana-3933	107	39	subsets	subset	NOUN
cana-3933	107	40	of	of	ADP
cana-3933	107	41	the	the	DET
cana-3933	107	42	data	datum	NOUN
cana-3933	107	43	.	.	PUNCT
cana-3933	108	1	5.conclusion	5.conclusion	NUM
cana-3933	108	2	this	this	DET
cana-3933	108	3	study	study	NOUN
cana-3933	108	4	demonstrates	demonstrate	VERB
cana-3933	108	5	that	that	SCONJ
cana-3933	108	6	using	use	VERB
cana-3933	108	7	machine	machine	NOUN
cana-3933	108	8	learning	learn	VERB
cana-3933	108	9	techniques	technique	NOUN
cana-3933	108	10	for	for	ADP
cana-3933	108	11	congestion	congestion	NOUN
cana-3933	108	12	control	control	NOUN
cana-3933	108	13	in	in	ADP
cana-3933	108	14	mobile	mobile	ADJ
cana-3933	108	15	adhoc	adhoc	NOUN
cana-3933	108	16	networks	network	NOUN
cana-3933	108	17	(	(	PUNCT
cana-3933	108	18	manets	manet	NOUN
cana-3933	108	19	)	)	PUNCT
cana-3933	108	20	can	can	AUX
cana-3933	108	21	significantly	significantly	ADV
cana-3933	108	22	improve	improve	VERB
cana-3933	108	23	network	network	NOUN
cana-3933	108	24	performance	performance	NOUN
cana-3933	108	25	.	.	PUNCT
cana-3933	109	1	traditional	traditional	ADJ
cana-3933	109	2	methods	method	NOUN
cana-3933	109	3	,	,	PUNCT
cana-3933	109	4	like	like	ADP
cana-3933	109	5	modifying	modify	VERB
cana-3933	109	6	routing	route	VERB
cana-3933	109	7	protocols	protocol	NOUN
cana-3933	109	8	,	,	PUNCT
cana-3933	109	9	often	often	ADV
cana-3933	109	10	struggle	struggle	VERB
cana-3933	109	11	in	in	ADP
cana-3933	109	12	dynamic	dynamic	ADJ
cana-3933	109	13	environments	environment	NOUN
cana-3933	109	14	.	.	PUNCT
cana-3933	110	1	in	in	ADP
cana-3933	110	2	contrast	contrast	NOUN
cana-3933	110	3	,	,	PUNCT
cana-3933	110	4	machine	machine	NOUN
cana-3933	110	5	learning	learning	NOUN
cana-3933	110	6	models	model	NOUN
cana-3933	110	7	,	,	PUNCT
cana-3933	110	8	such	such	ADJ
cana-3933	110	9	as	as	ADP
cana-3933	110	10	neural	neural	ADJ
cana-3933	110	11	networks	network	NOUN
cana-3933	110	12	,	,	PUNCT
cana-3933	110	13	can	can	AUX
cana-3933	110	14	predict	predict	VERB
cana-3933	110	15	and	and	CCONJ
cana-3933	110	16	manage	manage	VERB
cana-3933	110	17	congestion	congestion	NOUN
cana-3933	110	18	effectively	effectively	ADV
cana-3933	110	19	in	in	ADP
cana-3933	110	20	real	real	ADJ
cana-3933	110	21	-	-	PUNCT
cana-3933	110	22	time	time	NOUN
cana-3933	110	23	.	.	PUNCT
cana-3933	111	1	our	our	PRON
cana-3933	111	2	proposed	propose	VERB
cana-3933	111	3	model	model	NOUN
cana-3933	111	4	,	,	PUNCT
cana-3933	111	5	with	with	ADP
cana-3933	111	6	a	a	DET
cana-3933	111	7	neural	neural	ADJ
cana-3933	111	8	network	network	NOUN
cana-3933	111	9	architecture	architecture	NOUN
cana-3933	111	10	and	and	CCONJ
cana-3933	111	11	the	the	DET
cana-3933	111	12	congestion	congestion	NOUN
cana-3933	111	13	control	control	NOUN
cana-3933	111	14	discretization	discretization	NOUN
cana-3933	111	15	algorithm	algorithm	NOUN
cana-3933	111	16	(	(	PUNCT
cana-3933	111	17	ccda	ccda	PROPN
cana-3933	111	18	)	)	PUNCT
cana-3933	111	19	,	,	PUNCT
cana-3933	111	20	successfully	successfully	ADV
cana-3933	111	21	classified	classified	ADJ
cana-3933	111	22	network	network	NOUN
cana-3933	111	23	traffic	traffic	NOUN
cana-3933	111	24	into	into	ADP
cana-3933	111	25	'	'	PUNCT
cana-3933	111	26	normal	normal	ADJ
cana-3933	111	27	'	'	PUNCT
cana-3933	111	28	and	and	CCONJ
cana-3933	111	29	'	'	PUNCT
cana-3933	111	30	anomaly	anomaly	NOUN
cana-3933	111	31	'	'	PUNCT
cana-3933	111	32	categories	category	NOUN
cana-3933	111	33	,	,	PUNCT
cana-3933	111	34	helping	help	VERB
cana-3933	111	35	to	to	PART
cana-3933	111	36	reduce	reduce	VERB
cana-3933	111	37	congestion	congestion	NOUN
cana-3933	111	38	and	and	CCONJ
cana-3933	111	39	packet	packet	NOUN
cana-3933	111	40	loss	loss	NOUN
cana-3933	111	41	.	.	PUNCT
cana-3933	112	1	the	the	DET
cana-3933	112	2	model	model	NOUN
cana-3933	112	3	's	's	PART
cana-3933	112	4	high	high	ADJ
cana-3933	112	5	accuracy	accuracy	NOUN
cana-3933	112	6	and	and	CCONJ
cana-3933	112	7	low	low	ADJ
cana-3933	112	8	response	response	NOUN
cana-3933	112	9	time	time	NOUN
cana-3933	112	10	make	make	VERB
cana-3933	112	11	it	it	PRON
cana-3933	112	12	suitable	suitable	ADJ
cana-3933	112	13	for	for	ADP
cana-3933	112	14	real	real	ADJ
cana-3933	112	15	-	-	PUNCT
cana-3933	112	16	time	time	NOUN
cana-3933	112	17	applications	application	NOUN
cana-3933	112	18	in	in	ADP
cana-3933	112	19	manets	manet	NOUN
cana-3933	112	20	.	.	PUNCT
cana-3933	113	1	in	in	ADP
cana-3933	113	2	conclusion	conclusion	NOUN
cana-3933	113	3	,	,	PUNCT
cana-3933	113	4	machine	machine	NOUN
cana-3933	113	5	learning	learning	NOUN
cana-3933	113	6	offers	offer	VERB
cana-3933	113	7	a	a	DET
cana-3933	113	8	powerful	powerful	ADJ
cana-3933	113	9	tool	tool	NOUN
cana-3933	113	10	for	for	ADP
cana-3933	113	11	managing	manage	VERB
cana-3933	113	12	congestion	congestion	NOUN
cana-3933	113	13	in	in	ADP
cana-3933	113	14	manets	manet	NOUN
cana-3933	113	15	.	.	PUNCT
cana-3933	114	1	future	future	ADJ
cana-3933	114	2	research	research	NOUN
cana-3933	114	3	should	should	AUX
cana-3933	114	4	focus	focus	VERB
cana-3933	114	5	on	on	ADP
cana-3933	114	6	developing	develop	VERB
cana-3933	114	7	lightweight	lightweight	ADJ
cana-3933	114	8	models	model	NOUN
cana-3933	114	9	that	that	PRON
cana-3933	114	10	are	be	AUX
cana-3933	114	11	efficient	efficient	ADJ
cana-3933	114	12	in	in	ADP
cana-3933	114	13	resource	resource	NOUN
cana-3933	114	14	-	-	PUNCT
cana-3933	114	15	limited	limit	VERB
cana-3933	114	16	environments	environment	NOUN
cana-3933	114	17	and	and	CCONJ
cana-3933	114	18	exploring	explore	VERB
cana-3933	114	19	hybrid	hybrid	ADJ
cana-3933	114	20	methods	method	NOUN
cana-3933	114	21	that	that	PRON
cana-3933	114	22	combine	combine	VERB
cana-3933	114	23	traditional	traditional	ADJ
cana-3933	114	24	and	and	CCONJ
cana-3933	114	25	machine	machine	NOUN
cana-3933	114	26	learning	learn	VERB
cana-3933	114	27	techniques	technique	NOUN
cana-3933	114	28	for	for	ADP
cana-3933	114	29	even	even	ADV
cana-3933	114	30	better	well	ADJ
cana-3933	114	31	results	result	NOUN
cana-3933	114	32	.	.	PUNCT
cana-3933	115	1	references	reference	NOUN
cana-3933	115	2	:	:	PUNCT
cana-3933	116	1	[	[	X
cana-3933	116	2	1	1	NUM
cana-3933	116	3	]	]	PUNCT
cana-3933	116	4	taneja	taneja	NOUN
cana-3933	116	5	,	,	PUNCT
cana-3933	116	6	s.	s.	PROPN
cana-3933	116	7	,	,	PUNCT
cana-3933	116	8	&	&	CCONJ
cana-3933	116	9	kush	kush	NOUN
cana-3933	116	10	,	,	PUNCT
cana-3933	116	11	a.	a.	NOUN
cana-3933	116	12	(	(	PUNCT
cana-3933	116	13	2010	2010	NUM
cana-3933	116	14	)	)	PUNCT
cana-3933	116	15	.	.	PUNCT
cana-3933	117	1	a	a	DET
cana-3933	117	2	survey	survey	NOUN
cana-3933	117	3	of	of	ADP
cana-3933	117	4	routing	route	VERB
cana-3933	117	5	protocols	protocol	NOUN
cana-3933	117	6	in	in	ADP
cana-3933	117	7	mobile	mobile	ADJ
cana-3933	117	8	adhoc	adhoc	NOUN
cana-3933	117	9	networks	network	NOUN
cana-3933	117	10	.	.	PUNCT
cana-3933	118	1	international	international	ADJ
cana-3933	118	2	journal	journal	NOUN
cana-3933	118	3	of	of	ADP
cana-3933	118	4	innovative	innovative	ADJ
cana-3933	118	5	management	management	NOUN
cana-3933	118	6	and	and	CCONJ
cana-3933	118	7	technology	technology	NOUN
cana-3933	118	8	,	,	PUNCT
cana-3933	118	9	1(3	1(3	NUM
cana-3933	118	10	)	)	PUNCT
cana-3933	118	11	,	,	PUNCT
cana-3933	118	12	279	279	NUM
cana-3933	118	13	-	-	SYM
cana-3933	118	14	285	285	NUM
cana-3933	118	15	.	.	PUNCT
cana-3933	119	1	[	[	X
cana-3933	119	2	2	2	X
cana-3933	119	3	]	]	X
cana-3933	119	4	kanellopoulos	kanellopoulos	PROPN
cana-3933	119	5	,	,	PUNCT
cana-3933	119	6	d.	d.	PROPN
cana-3933	119	7	(	(	PUNCT
cana-3933	119	8	2019	2019	NUM
cana-3933	119	9	)	)	PUNCT
cana-3933	119	10	.	.	PUNCT
cana-3933	120	1	congestion	congestion	NOUN
cana-3933	120	2	control	control	NOUN
cana-3933	120	3	for	for	ADP
cana-3933	120	4	manets	manet	NOUN
cana-3933	120	5	:	:	PUNCT
cana-3933	120	6	an	an	DET
cana-3933	120	7	overview	overview	NOUN
cana-3933	120	8	.	.	PUNCT
cana-3933	121	1	ict	ict	PROPN
cana-3933	121	2	express	express	PROPN
cana-3933	121	3	,	,	PUNCT
cana-3933	121	4	5(2	5(2	NUM
cana-3933	121	5	)	)	PUNCT
cana-3933	121	6	,	,	PUNCT
cana-3933	121	7	77	77	NUM
cana-3933	121	8	-	-	SYM
cana-3933	121	9	83	83	NUM
cana-3933	121	10	.	.	PUNCT
cana-3933	122	1	[	[	X
cana-3933	122	2	3	3	NUM
cana-3933	122	3	]	]	SYM
cana-3933	122	4	zafar	zafar	PROPN
cana-3933	122	5	,	,	PUNCT
cana-3933	122	6	m.	m.	PROPN
cana-3933	122	7	h.	h.	PROPN
cana-3933	122	8	,	,	PUNCT
cana-3933	122	9	&	&	CCONJ
cana-3933	122	10	altalbe	altalbe	NOUN
cana-3933	122	11	,	,	PUNCT
cana-3933	122	12	a.	a.	NOUN
cana-3933	122	13	(	(	PUNCT
cana-3933	122	14	2021	2021	NUM
cana-3933	122	15	)	)	PUNCT
cana-3933	122	16	.	.	PUNCT
cana-3933	122	17	prediction	prediction	NOUN
cana-3933	122	18	of	of	ADP
cana-3933	122	19	scenarios	scenario	NOUN
cana-3933	122	20	for	for	ADP
cana-3933	122	21	routing	route	VERB
cana-3933	122	22	in	in	ADP
cana-3933	122	23	manets	manet	NOUN
cana-3933	122	24	based	base	VERB
cana-3933	122	25	on	on	ADP
cana-3933	122	26	expanding	expand	VERB
cana-3933	122	27	ring	ring	NOUN
cana-3933	122	28	search	search	NOUN
cana-3933	122	29	and	and	CCONJ
cana-3933	122	30	random	random	ADJ
cana-3933	122	31	early	early	ADJ
cana-3933	122	32	detection	detection	NOUN
cana-3933	122	33	parameters	parameter	NOUN
cana-3933	122	34	using	use	VERB
cana-3933	122	35	machine	machine	NOUN
cana-3933	122	36	learning	learn	VERB
cana-3933	122	37	techniques	technique	NOUN
cana-3933	122	38	.	.	PUNCT
cana-3933	123	1	ieee	ieee	NOUN
cana-3933	123	2	access	access	NOUN
cana-3933	123	3	,	,	PUNCT
cana-3933	123	4	9	9	NUM
cana-3933	123	5	,	,	PUNCT
cana-3933	123	6	47033	47033	NUM
cana-3933	123	7	-	-	SYM
cana-3933	123	8	47047	47047	NUM
cana-3933	123	9	.	.	PUNCT
cana-3933	124	1	[	[	X
cana-3933	124	2	4	4	NUM
cana-3933	124	3	]	]	SYM
cana-3933	124	4	hu	hu	PROPN
cana-3933	124	5	,	,	PUNCT
cana-3933	124	6	y.	y.	PROPN
cana-3933	124	7	,	,	PUNCT
cana-3933	124	8	peng	peng	PROPN
cana-3933	124	9	,	,	PUNCT
cana-3933	124	10	t.	t.	PROPN
cana-3933	124	11	,	,	PUNCT
cana-3933	124	12	&	&	CCONJ
cana-3933	124	13	zhang	zhang	PROPN
cana-3933	124	14	,	,	PUNCT
cana-3933	124	15	l.	l.	PROPN
cana-3933	124	16	(	(	PUNCT
cana-3933	124	17	2017	2017	NUM
cana-3933	124	18	)	)	PUNCT
cana-3933	124	19	.	.	PUNCT
cana-3933	125	1	software	software	NOUN
cana-3933	125	2	-	-	PUNCT
cana-3933	125	3	defined	define	VERB
cana-3933	125	4	congestion	congestion	NOUN
cana-3933	125	5	control	control	NOUN
cana-3933	125	6	algorithm	algorithm	NOUN
cana-3933	125	7	for	for	ADP
cana-3933	125	8	ip	ip	NOUN
cana-3933	125	9	networks	network	NOUN
cana-3933	125	10	.	.	PUNCT
cana-3933	126	1	scientific	scientific	ADJ
cana-3933	126	2	programming	programming	NOUN
cana-3933	126	3	,	,	PUNCT
cana-3933	126	4	2017	2017	NUM
cana-3933	126	5	,	,	PUNCT
cana-3933	126	6	article	article	NOUN
cana-3933	126	7	i	i	PROPN
cana-3933	126	8	d	d	PROPN
cana-3933	126	9	8934205	8934205	NUM
cana-3933	126	10	.	.	PUNCT
cana-3933	127	1	[	[	X
cana-3933	127	2	5	5	NUM
cana-3933	127	3	]	]	X
cana-3933	127	4	sucharitha	sucharitha	NOUN
cana-3933	127	5	,	,	PUNCT
cana-3933	127	6	k.	k.	PROPN
cana-3933	127	7	,	,	PUNCT
cana-3933	127	8	&	&	CCONJ
cana-3933	127	9	latha	latha	PROPN
cana-3933	127	10	,	,	PUNCT
cana-3933	127	11	r.	r.	PROPN
cana-3933	127	12	(	(	PUNCT
cana-3933	127	13	2022	2022	NUM
cana-3933	127	14	)	)	PUNCT
cana-3933	127	15	.	.	PUNCT
cana-3933	128	1	designing	design	VERB
cana-3933	128	2	an	an	DET
cana-3933	128	3	ml	ml	ADV
cana-3933	128	4	-	-	PUNCT
cana-3933	128	5	based	base	VERB
cana-3933	128	6	congestion	congestion	NOUN
cana-3933	128	7	detection	detection	NOUN
cana-3933	128	8	algorithm	algorithm	NOUN
cana-3933	128	9	for	for	ADP
cana-3933	128	10	routing	route	VERB
cana-3933	128	11	data	datum	NOUN
cana-3933	128	12	in	in	ADP
cana-3933	128	13	manets	manet	NOUN
cana-3933	128	14	.	.	PUNCT
cana-3933	129	1	in	in	ADP
cana-3933	129	2	:	:	PUNCT
cana-3933	129	3	ramu	ramu	PROPN
cana-3933	129	4	,	,	PUNCT
cana-3933	129	5	a.	a.	PROPN
cana-3933	129	6	,	,	PUNCT
cana-3933	129	7	chee	chee	NOUN
cana-3933	129	8	onn	onn	PROPN
cana-3933	129	9	,	,	PUNCT
cana-3933	129	10	c.	c.	PROPN
cana-3933	129	11	,	,	PUNCT
cana-3933	129	12	sumithra	sumithra	PROPN
cana-3933	129	13	,	,	PUNCT
cana-3933	129	14	m.	m.	NOUN
cana-3933	129	15	(	(	PUNCT
cana-3933	129	16	eds	ed	NOUN
cana-3933	129	17	.	.	PUNCT
cana-3933	129	18	)	)	PUNCT
cana-3933	129	19	,	,	PUNCT
cana-3933	129	20	internationalconference	internationalconference	NOUN
cana-3933	129	21	on	on	ADP
cana-3933	129	22	computing	computing	NOUN
cana-3933	129	23	,	,	PUNCT
cana-3933	129	24	communication	communication	NOUN
cana-3933	129	25	,	,	PUNCT
cana-3933	129	26	electrical	electrical	ADJ
cana-3933	129	27	and	and	CCONJ
cana-3933	129	28	biomedical	biomedical	ADJ
cana-3933	129	29	systems	system	NOUN
cana-3933	129	30	.	.	PUNCT
cana-3933	130	1	springer	springer	NOUN
cana-3933	130	2	.	.	PUNCT
cana-3933	131	1	[	[	X
cana-3933	131	2	6	6	NUM
cana-3933	131	3	]	]	X
cana-3933	131	4	jiang	jiang	PROPN
cana-3933	131	5	,	,	PUNCT
cana-3933	131	6	h.	h.	PROPN
cana-3933	131	7	,	,	PUNCT
cana-3933	131	8	et	et	PROPN
cana-3933	131	9	al	al	PROPN
cana-3933	131	10	.	.	PROPN
cana-3933	131	11	(	(	PUNCT
cana-3933	131	12	2021	2021	NUM
cana-3933	131	13	)	)	PUNCT
cana-3933	131	14	.	.	PUNCT
cana-3933	132	1	when	when	SCONJ
cana-3933	132	2	machine	machine	NOUN
cana-3933	132	3	learning	learning	NOUN
cana-3933	132	4	meets	meet	VERB
cana-3933	132	5	congestion	congestion	NOUN
cana-3933	132	6	control	control	NOUN
cana-3933	132	7	:	:	PUNCT
cana-3933	132	8	a	a	DET
cana-3933	132	9	survey	survey	NOUN
cana-3933	132	10	and	and	CCONJ
cana-3933	132	11	comparison	comparison	NOUN
cana-3933	132	12	.	.	PUNCT
cana-3933	133	1	computer	computer	NOUN
cana-3933	133	2	networks	network	NOUN
cana-3933	133	3	,	,	PUNCT
cana-3933	133	4	192	192	NUM
cana-3933	133	5	,	,	PUNCT
cana-3933	133	6	108033	108033	NUM
cana-3933	133	7	.	.	PUNCT
cana-3933	134	1	communications	communication	NOUN
cana-3933	134	2	on	on	ADP
cana-3933	134	3	applied	apply	VERB
cana-3933	134	4	nonlinear	nonlinear	ADJ
cana-3933	134	5	analysis	analysis	NOUN
cana-3933	134	6	issn	issn	NOUN
cana-3933	134	7	:	:	PUNCT
cana-3933	134	8	1074	1074	NUM
cana-3933	134	9	-	-	PUNCT
cana-3933	134	10	133x	133x	NUM
cana-3933	134	11	vol	vol	NOUN
cana-3933	134	12	32	32	NUM
cana-3933	134	13	no	no	NOUN
cana-3933	134	14	.	.	PUNCT
cana-3933	135	1	9s	9s	NUM
cana-3933	135	2	(	(	PUNCT
cana-3933	135	3	2025	2025	NUM
cana-3933	135	4	)	)	PUNCT
cana-3933	135	5	369	369	NUM
cana-3933	135	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-3933	136	1	[	[	X
cana-3933	136	2	7	7	NUM
cana-3933	136	3	]	]	X
cana-3933	136	4	ghaffari	ghaffari	NOUN
cana-3933	136	5	,	,	PUNCT
cana-3933	136	6	a.	a.	NOUN
cana-3933	136	7	(	(	PUNCT
cana-3933	136	8	2015	2015	NUM
cana-3933	136	9	)	)	PUNCT
cana-3933	136	10	.	.	PUNCT
cana-3933	137	1	congestion	congestion	NOUN
cana-3933	137	2	control	control	NOUN
cana-3933	137	3	mechanisms	mechanism	NOUN
cana-3933	137	4	in	in	ADP
cana-3933	137	5	wireless	wireless	ADJ
cana-3933	137	6	sensor	sensor	NOUN
cana-3933	137	7	networks	network	NOUN
cana-3933	137	8	:	:	PUNCT
cana-3933	137	9	a	a	DET
cana-3933	137	10	surveyjournal	surveyjournal	NOUN
cana-3933	137	11	of	of	ADP
cana-3933	137	12	network	network	NOUN
cana-3933	137	13	and	and	CCONJ
cana-3933	137	14	computer	computer	NOUN
cana-3933	137	15	applications	application	NOUN
cana-3933	137	16	,	,	PUNCT
cana-3933	137	17	52	52	NUM
cana-3933	137	18	,	,	PUNCT
cana-3933	137	19	101	101	NUM
cana-3933	137	20	-	-	SYM
cana-3933	137	21	115	115	NUM
cana-3933	137	22	.	.	PUNCT
cana-3933	138	1	[	[	X
cana-3933	138	2	8	8	NUM
cana-3933	138	3	]	]	X
cana-3933	138	4	zhang	zhang	PROPN
cana-3933	138	5	,	,	PUNCT
cana-3933	138	6	t.	t.	PROPN
cana-3933	138	7	,	,	PUNCT
cana-3933	138	8	&	&	CCONJ
cana-3933	138	9	mao	mao	PROPN
cana-3933	138	10	,	,	PUNCT
cana-3933	138	11	s.	s.	PROPN
cana-3933	138	12	(	(	PUNCT
cana-3933	138	13	2020	2020	NUM
cana-3933	138	14	)	)	PUNCT
cana-3933	138	15	.	.	PUNCT
cana-3933	139	1	machine	machine	NOUN
cana-3933	139	2	learning	learn	VERB
cana-3933	139	3	for	for	ADP
cana-3933	139	4	end	end	NOUN
cana-3933	139	5	-	-	PUNCT
cana-3933	139	6	to	to	ADP
cana-3933	139	7	-	-	PUNCT
cana-3933	139	8	end	end	NOUN
cana-3933	139	9	congestion	congestion	NOUN
cana-3933	139	10	control	control	NOUN
cana-3933	139	11	.	.	PUNCT
cana-3933	140	1	ieeecommunications	ieeecommunication	NOUN
cana-3933	140	2	magazine	magazine	NOUN
cana-3933	140	3	,	,	PUNCT
cana-3933	140	4	58(6	58(6	NOUN
cana-3933	140	5	)	)	PUNCT
cana-3933	140	6	,	,	PUNCT
cana-3933	140	7	52	52	NUM
cana-3933	140	8	-	-	SYM
cana-3933	140	9	57	57	NUM
cana-3933	140	10	.	.	PUNCT
cana-3933	141	1	[	[	X
cana-3933	141	2	9	9	NUM
cana-3933	141	3	]	]	X
cana-3933	141	4	robinson	robinson	PROPN
cana-3933	141	5	,	,	PUNCT
cana-3933	141	6	h.	h.	PROPN
cana-3933	141	7	y.	y.	PROPN
cana-3933	141	8	,	,	PUNCT
cana-3933	141	9	balaji	balaji	PROPN
cana-3933	141	10	,	,	PUNCT
cana-3933	141	11	s.	s.	PROPN
cana-3933	141	12	,	,	PUNCT
cana-3933	141	13	&	&	CCONJ
cana-3933	141	14	golden	golden	PROPN
cana-3933	141	15	julie	julie	PROPN
cana-3933	141	16	,	,	PUNCT
cana-3933	141	17	e.	e.	PROPN
cana-3933	141	18	(	(	PUNCT
cana-3933	141	19	2019	2019	NUM
cana-3933	141	20	)	)	PUNCT
cana-3933	141	21	.	.	PUNCT
cana-3933	142	1	design	design	NOUN
cana-3933	142	2	of	of	ADP
cana-3933	142	3	a	a	DET
cana-3933	142	4	buffer	buffer	NOUN
cana-3933	142	5	-	-	PUNCT
cana-3933	142	6	enabled	enable	VERB
cana-3933	142	7	ad	ad	NOUN
cana-3933	142	8	hoc	hoc	X
cana-3933	142	9	ondemand	ondemand	NOUN
cana-3933	142	10	multipath	multipath	ADP
cana-3933	142	11	distance	distance	NOUN
cana-3933	142	12	vector	vector	NOUN
cana-3933	142	13	routing	routing	NOUN
cana-3933	142	14	protocol	protocol	NOUN
cana-3933	142	15	for	for	ADP
cana-3933	142	16	improving	improve	VERB
cana-3933	142	17	throughput	throughput	NOUN
cana-3933	142	18	in	in	ADP
cana-3933	142	19	manetswireless	manetswireless	NOUN
cana-3933	142	20	personal	personal	ADJ
cana-3933	142	21	communications	communication	NOUN
cana-3933	142	22	,	,	PUNCT
cana-3933	142	23	106(4	106(4	NUM
cana-3933	142	24	)	)	PUNCT
cana-3933	142	25	,	,	PUNCT
cana-3933	142	26	2053	2053	NUM
cana-3933	142	27	-	-	SYM
cana-3933	142	28	2078	2078	NUM
cana-3933	142	29	.	.	PUNCT
cana-3933	143	1	[	[	X
cana-3933	143	2	10	10	NUM
cana-3933	143	3	]	]	PUNCT
cana-3933	143	4	taneja	taneja	NOUN
cana-3933	143	5	,	,	PUNCT
cana-3933	143	6	s.	s.	PROPN
cana-3933	143	7	,	,	PUNCT
cana-3933	143	8	&	&	CCONJ
cana-3933	143	9	kush	kush	NOUN
cana-3933	143	10	,	,	PUNCT
cana-3933	143	11	a.	a.	NOUN
cana-3933	143	12	(	(	PUNCT
cana-3933	143	13	2010	2010	NUM
cana-3933	143	14	)	)	PUNCT
cana-3933	143	15	.	.	PUNCT
cana-3933	144	1	a	a	DET
cana-3933	144	2	survey	survey	NOUN
cana-3933	144	3	of	of	ADP
cana-3933	144	4	routing	route	VERB
cana-3933	144	5	protocols	protocol	NOUN
cana-3933	144	6	in	in	ADP
cana-3933	144	7	mobile	mobile	ADJ
cana-3933	144	8	ad	ad	X
cana-3933	144	9	hoc	hoc	X
cana-3933	144	10	networks	network	NOUN
cana-3933	144	11	international	international	ADJ
cana-3933	144	12	journal	journal	NOUN
cana-3933	144	13	of	of	ADP
cana-3933	144	14	innovative	innovative	ADJ
cana-3933	144	15	management	management	NOUN
cana-3933	144	16	and	and	CCONJ
cana-3933	144	17	technology	technology	NOUN
cana-3933	144	18	,	,	PUNCT
cana-3933	144	19	1(3	1(3	NUM
cana-3933	144	20	)	)	PUNCT
cana-3933	144	21	,	,	PUNCT
cana-3933	144	22	279	279	NUM
cana-3933	144	23	-	-	SYM
cana-3933	144	24	285	285	NUM
cana-3933	144	25	.	.	PUNCT
cana-3933	145	1	[	[	X
cana-3933	145	2	11	11	NUM
cana-3933	145	3	]	]	X
cana-3933	145	4	kanellopoulos	kanellopoulos	PROPN
cana-3933	145	5	,	,	PUNCT
cana-3933	145	6	d.	d.	PROPN
cana-3933	145	7	(	(	PUNCT
cana-3933	145	8	2019	2019	NUM
cana-3933	145	9	)	)	PUNCT
cana-3933	145	10	.	.	PUNCT
cana-3933	146	1	congestion	congestion	NOUN
cana-3933	146	2	control	control	NOUN
cana-3933	146	3	for	for	ADP
cana-3933	146	4	manets	manet	NOUN
cana-3933	146	5	:	:	PUNCT
cana-3933	146	6	an	an	DET
cana-3933	146	7	overview	overview	NOUN
cana-3933	146	8	.	.	PUNCT
cana-3933	147	1	ict	ict	PROPN
cana-3933	147	2	express	express	VERB
cana-3933	147	3	,	,	PUNCT
cana-3933	147	4	5(2),77	5(2),77	NOUN
cana-3933	147	5	-	-	SYM
cana-3933	147	6	83	83	NUM
cana-3933	147	7	.	.	PUNCT
cana-3933	148	1	[	[	X
cana-3933	148	2	12	12	NUM
cana-3933	148	3	]	]	X
cana-3933	148	4	zafar	zafar	PROPN
cana-3933	148	5	,	,	PUNCT
cana-3933	148	6	m.	m.	PROPN
cana-3933	148	7	h.	h.	PROPN
cana-3933	148	8	,	,	PUNCT
cana-3933	148	9	&	&	CCONJ
cana-3933	148	10	altalbe	altalbe	NOUN
cana-3933	148	11	,	,	PUNCT
cana-3933	148	12	a.	a.	NOUN
cana-3933	148	13	(	(	PUNCT
cana-3933	148	14	2021	2021	NUM
cana-3933	148	15	)	)	PUNCT
cana-3933	148	16	.	.	PUNCT
cana-3933	149	1	prediction	prediction	NOUN
cana-3933	149	2	of	of	ADP
cana-3933	149	3	scenarios	scenario	NOUN
cana-3933	149	4	for	for	ADP
cana-3933	149	5	routing	route	VERB
cana-3933	149	6	in	in	ADP
cana-3933	149	7	manets	manet	NOUN
cana-3933	149	8	based	base	VERB
cana-3933	149	9	on	on	ADP
cana-3933	149	10	expanding	expand	VERB
cana-3933	149	11	ring	ring	NOUN
cana-3933	149	12	search	search	NOUN
cana-3933	149	13	and	and	CCONJ
cana-3933	149	14	random	random	ADJ
cana-3933	149	15	early	early	ADJ
cana-3933	149	16	detection	detection	NOUN
cana-3933	149	17	parameters	parameter	NOUN
cana-3933	149	18	using	use	VERB
cana-3933	149	19	machine	machine	NOUN
cana-3933	149	20	learning	learn	VERB
cana-3933	149	21	techniques	technique	NOUN
cana-3933	149	22	.	.	PUNCT
cana-3933	150	1	ieee	ieee	NOUN
cana-3933	150	2	access	access	NOUN
cana-3933	150	3	,	,	PUNCT
cana-3933	150	4	9	9	NUM
cana-3933	150	5	,	,	PUNCT
cana-3933	150	6	47033	47033	NUM
cana-3933	150	7	-	-	SYM
cana-3933	150	8	47047	47047	NUM
cana-3933	150	9	.	.	PUNCT
cana-3933	151	1	[	[	X
cana-3933	151	2	13	13	NUM
cana-3933	151	3	]	]	SYM
cana-3933	151	4	hu	hu	PROPN
cana-3933	151	5	,	,	PUNCT
cana-3933	151	6	y.	y.	PROPN
cana-3933	151	7	,	,	PUNCT
cana-3933	151	8	peng	peng	PROPN
cana-3933	151	9	,	,	PUNCT
cana-3933	151	10	t.	t.	PROPN
cana-3933	151	11	,	,	PUNCT
cana-3933	151	12	&	&	CCONJ
cana-3933	151	13	zhang	zhang	PROPN
cana-3933	151	14	,	,	PUNCT
cana-3933	151	15	l.	l.	PROPN
cana-3933	151	16	(	(	PUNCT
cana-3933	151	17	2017	2017	NUM
cana-3933	151	18	)	)	PUNCT
cana-3933	151	19	.	.	PUNCT
cana-3933	152	1	software	software	NOUN
cana-3933	152	2	-	-	PUNCT
cana-3933	152	3	defined	define	VERB
cana-3933	152	4	congestion	congestion	NOUN
cana-3933	152	5	control	control	NOUN
cana-3933	152	6	algorithm	algorithm	NOUN
cana-3933	152	7	for	for	ADP
cana-3933	152	8	ip	ip	NOUN
cana-3933	152	9	networks	network	NOUN
cana-3933	152	10	.	.	PUNCT
cana-3933	153	1	scientific	scientific	ADJ
cana-3933	153	2	programming	programming	NOUN
cana-3933	153	3	,	,	PUNCT
cana-3933	153	4	2017	2017	NUM
cana-3933	153	5	,	,	PUNCT
cana-3933	153	6	article	article	NOUN
cana-3933	153	7	i	i	PROPN
cana-3933	153	8	d	d	PROPN
cana-3933	153	9	8934205	8934205	NUM
cana-3933	153	10	.	.	PUNCT
cana-3933	154	1	[	[	X
cana-3933	154	2	14	14	NUM
cana-3933	154	3	]	]	PUNCT
cana-3933	154	4	ghaffari	ghaffari	NOUN
cana-3933	154	5	,	,	PUNCT
cana-3933	154	6	a.	a.	NOUN
cana-3933	154	7	(	(	PUNCT
cana-3933	154	8	2015	2015	NUM
cana-3933	154	9	)	)	PUNCT
cana-3933	154	10	.	.	PUNCT
cana-3933	155	1	congestion	congestion	NOUN
cana-3933	155	2	control	control	NOUN
cana-3933	155	3	mechanisms	mechanism	NOUN
cana-3933	155	4	in	in	ADP
cana-3933	155	5	wireless	wireless	ADJ
cana-3933	155	6	sensor	sensor	NOUN
cana-3933	155	7	networks	network	NOUN
cana-3933	155	8	:	:	PUNCT
cana-3933	155	9	a	a	DET
cana-3933	155	10	survey	survey	NOUN
cana-3933	155	11	journal	journal	NOUN
cana-3933	155	12	of	of	ADP
cana-3933	155	13	network	network	NOUN
cana-3933	155	14	and	and	CCONJ
cana-3933	155	15	computer	computer	NOUN
cana-3933	155	16	applications	application	NOUN
cana-3933	155	17	,	,	PUNCT
cana-3933	155	18	52	52	NUM
cana-3933	155	19	,	,	PUNCT
cana-3933	155	20	101	101	NUM
cana-3933	155	21	-	-	SYM
cana-3933	155	22	115	115	NUM
cana-3933	155	23	.	.	PUNCT
cana-3933	156	1	[	[	X
cana-3933	156	2	15	15	NUM
cana-3933	156	3	]	]	X
cana-3933	156	4	zhang	zhang	PROPN
cana-3933	156	5	,	,	PUNCT
cana-3933	156	6	t.	t.	PROPN
cana-3933	156	7	,	,	PUNCT
cana-3933	156	8	&	&	CCONJ
cana-3933	156	9	mao	mao	PROPN
cana-3933	156	10	,	,	PUNCT
cana-3933	156	11	s.	s.	PROPN
cana-3933	156	12	(	(	PUNCT
cana-3933	156	13	2020	2020	NUM
cana-3933	156	14	)	)	PUNCT
cana-3933	156	15	.	.	PUNCT
cana-3933	157	1	machine	machine	NOUN
cana-3933	157	2	learning	learn	VERB
cana-3933	157	3	for	for	ADP
cana-3933	157	4	end	end	NOUN
cana-3933	157	5	-	-	PUNCT
cana-3933	157	6	to	to	ADP
cana-3933	157	7	-	-	PUNCT
cana-3933	157	8	end	end	NOUN
cana-3933	157	9	congestion	congestion	NOUN
cana-3933	157	10	control	control	NOUN
cana-3933	157	11	.	.	PUNCT
cana-3933	158	1	ieee	ieee	PROPN
cana-3933	158	2	communications	communications	PROPN
cana-3933	158	3	magazine	magazine	NOUN
cana-3933	158	4	,	,	PUNCT
cana-3933	158	5	58(6	58(6	NOUN
cana-3933	158	6	)	)	PUNCT
cana-3933	158	7	,	,	PUNCT
cana-3933	158	8	52	52	NUM
cana-3933	158	9	-	-	SYM
cana-3933	158	10	57	57	NUM
cana-3933	158	11	.	.	PUNCT