id	sid	tid	token	lemma	pos
ajst-29293	1	1	academic	academic	ADJ
ajst-29293	1	2	journal	journal	NOUN
ajst-29293	1	3	of	of	ADP
ajst-29293	1	4	science	science	NOUN
ajst-29293	1	5	and	and	CCONJ
ajst-29293	1	6	technology	technology	NOUN
ajst-29293	1	7	issn	issn	NOUN
ajst-29293	1	8	:	:	PUNCT
ajst-29293	1	9	2771	2771	NUM
ajst-29293	1	10	-	-	SYM
ajst-29293	1	11	3032	3032	NUM
ajst-29293	1	12	|	|	NOUN
ajst-29293	1	13	vol	vol	NOUN
ajst-29293	1	14	.	.	PUNCT
ajst-29293	2	1	14	14	NUM
ajst-29293	2	2	,	,	PUNCT
ajst-29293	2	3	no	no	INTJ
ajst-29293	2	4	.	.	NOUN
ajst-29293	2	5	1	1	NUM
ajst-29293	2	6	,	,	PUNCT
ajst-29293	2	7	2025	2025	NUM
ajst-29293	2	8	90	90	NUM
ajst-29293	2	9	optimizing	optimize	VERB
ajst-29293	2	10	electric	electric	ADJ
ajst-29293	2	11	vehicle	vehicle	NOUN
ajst-29293	2	12	clustering	cluster	VERB
ajst-29293	2	13	through	through	ADP
ajst-29293	2	14	improved	improve	VERB
ajst-29293	2	15	mvabc‐gmm	mvabc‐gmm	NOUN
ajst-29293	2	16	algorithm	algorithm	NOUN
ajst-29293	2	17	based	base	VERB
ajst-29293	2	18	on	on	ADP
ajst-29293	2	19	gaussian	gaussian	ADJ
ajst-29293	2	20	mixture	mixture	NOUN
ajst-29293	2	21	model	model	NOUN
ajst-29293	2	22	and	and	CCONJ
ajst-29293	2	23	monte	monte	PROPN
ajst-29293	2	24	carlo	carlo	PROPN
ajst-29293	2	25	prediction	prediction	PROPN
ajst-29293	2	26	bingcheng	bingcheng	PROPN
ajst-29293	2	27	li	li	PROPN
ajst-29293	2	28	,	,	PUNCT
ajst-29293	2	29	guifang	guifang	PROPN
ajst-29293	2	30	guo	guo	PROPN
ajst-29293	2	31	*	*	PROPN
ajst-29293	2	32	school	school	NOUN
ajst-29293	2	33	of	of	ADP
ajst-29293	2	34	information	information	NOUN
ajst-29293	2	35	engineering	engineering	NOUN
ajst-29293	2	36	,	,	PUNCT
ajst-29293	2	37	xizang	xizang	PROPN
ajst-29293	2	38	minzu	minzu	PROPN
ajst-29293	2	39	university	university	PROPN
ajst-29293	2	40	,	,	PUNCT
ajst-29293	2	41	shaanxi	shaanxi	PROPN
ajst-29293	2	42	,	,	PUNCT
ajst-29293	2	43	china	china	PROPN
ajst-29293	2	44	*	*	PUNCT
ajst-29293	2	45	corresponding	correspond	VERB
ajst-29293	2	46	author	author	NOUN
ajst-29293	2	47	abstract	abstract	NOUN
ajst-29293	2	48	:	:	PUNCT
ajst-29293	2	49	in	in	ADP
ajst-29293	2	50	the	the	DET
ajst-29293	2	51	practical	practical	ADJ
ajst-29293	2	52	application	application	NOUN
ajst-29293	2	53	of	of	ADP
ajst-29293	2	54	electric	electric	ADJ
ajst-29293	2	55	vehicle	vehicle	NOUN
ajst-29293	2	56	(	(	PUNCT
ajst-29293	2	57	ev	ev	INTJ
ajst-29293	2	58	)	)	PUNCT
ajst-29293	2	59	charging	charging	NOUN
ajst-29293	2	60	,	,	PUNCT
ajst-29293	2	61	significant	significant	ADJ
ajst-29293	2	62	differences	difference	NOUN
ajst-29293	2	63	in	in	ADP
ajst-29293	2	64	charging	charge	VERB
ajst-29293	2	65	behaviors	behavior	NOUN
ajst-29293	2	66	across	across	ADP
ajst-29293	2	67	different	different	ADJ
ajst-29293	2	68	time	time	NOUN
ajst-29293	2	69	periods	period	NOUN
ajst-29293	2	70	lead	lead	VERB
ajst-29293	2	71	to	to	ADP
ajst-29293	2	72	scheduling	scheduling	NOUN
ajst-29293	2	73	challenges	challenge	NOUN
ajst-29293	2	74	,	,	PUNCT
ajst-29293	2	75	especially	especially	ADV
ajst-29293	2	76	when	when	SCONJ
ajst-29293	2	77	dealing	deal	VERB
ajst-29293	2	78	with	with	ADP
ajst-29293	2	79	a	a	DET
ajst-29293	2	80	large	large	ADJ
ajst-29293	2	81	number	number	NOUN
ajst-29293	2	82	of	of	ADP
ajst-29293	2	83	vehicles	vehicle	NOUN
ajst-29293	2	84	,	,	PUNCT
ajst-29293	2	85	potentially	potentially	ADV
ajst-29293	2	86	causing	cause	VERB
ajst-29293	2	87	the	the	DET
ajst-29293	2	88	"	"	PUNCT
ajst-29293	2	89	curse	curse	NOUN
ajst-29293	2	90	of	of	ADP
ajst-29293	2	91	dimensionality	dimensionality	NOUN
ajst-29293	2	92	"	"	PUNCT
ajst-29293	2	93	in	in	ADP
ajst-29293	2	94	scheduling	scheduling	NOUN
ajst-29293	2	95	.	.	PUNCT
ajst-29293	3	1	to	to	PART
ajst-29293	3	2	address	address	VERB
ajst-29293	3	3	this	this	DET
ajst-29293	3	4	issue	issue	NOUN
ajst-29293	3	5	,	,	PUNCT
ajst-29293	3	6	an	an	DET
ajst-29293	3	7	improved	improved	ADJ
ajst-29293	3	8	mvabc	mvabc	PROPN
ajst-29293	3	9	-	-	PUNCT
ajst-29293	3	10	gmm	gmm	NOUN
ajst-29293	3	11	algorithm	algorithm	NOUN
ajst-29293	3	12	based	base	VERB
ajst-29293	3	13	on	on	ADP
ajst-29293	3	14	the	the	DET
ajst-29293	3	15	gaussian	gaussian	ADJ
ajst-29293	3	16	mixture	mixture	NOUN
ajst-29293	3	17	model	model	NOUN
ajst-29293	3	18	(	(	PUNCT
ajst-29293	3	19	gmm	gmm	NOUN
ajst-29293	3	20	)	)	PUNCT
ajst-29293	3	21	is	be	AUX
ajst-29293	3	22	proposed	propose	VERB
ajst-29293	3	23	for	for	ADP
ajst-29293	3	24	clustering	cluster	VERB
ajst-29293	3	25	large	large	ADJ
ajst-29293	3	26	-	-	PUNCT
ajst-29293	3	27	scale	scale	NOUN
ajst-29293	3	28	evs	evs	NOUN
ajst-29293	3	29	,	,	PUNCT
ajst-29293	3	30	aiming	aim	VERB
ajst-29293	3	31	to	to	PART
ajst-29293	3	32	optimize	optimize	VERB
ajst-29293	3	33	ev	ev	PRON
ajst-29293	3	34	scheduling	scheduling	NOUN
ajst-29293	3	35	strategies	strategy	NOUN
ajst-29293	3	36	and	and	CCONJ
ajst-29293	3	37	enhance	enhance	VERB
ajst-29293	3	38	the	the	DET
ajst-29293	3	39	utilization	utilization	NOUN
ajst-29293	3	40	efficiency	efficiency	NOUN
ajst-29293	3	41	of	of	ADP
ajst-29293	3	42	grid	grid	NOUN
ajst-29293	3	43	resources	resource	NOUN
ajst-29293	3	44	.	.	PUNCT
ajst-29293	4	1	the	the	DET
ajst-29293	4	2	charging	charge	VERB
ajst-29293	4	3	data	datum	NOUN
ajst-29293	4	4	is	be	AUX
ajst-29293	4	5	fitted	fit	VERB
ajst-29293	4	6	using	use	VERB
ajst-29293	4	7	a	a	DET
ajst-29293	4	8	gaussian	gaussian	ADJ
ajst-29293	4	9	distribution	distribution	NOUN
ajst-29293	4	10	,	,	PUNCT
ajst-29293	4	11	and	and	CCONJ
ajst-29293	4	12	a	a	DET
ajst-29293	4	13	monte	monte	PROPN
ajst-29293	4	14	carlo	carlo	PROPN
ajst-29293	4	15	prediction	prediction	NOUN
ajst-29293	4	16	model	model	NOUN
ajst-29293	4	17	is	be	AUX
ajst-29293	4	18	built	build	VERB
ajst-29293	4	19	to	to	PART
ajst-29293	4	20	simulate	simulate	VERB
ajst-29293	4	21	the	the	DET
ajst-29293	4	22	charging	charge	VERB
ajst-29293	4	23	behavior	behavior	NOUN
ajst-29293	4	24	patterns	pattern	NOUN
ajst-29293	4	25	of	of	ADP
ajst-29293	4	26	evs	evs	PROPN
ajst-29293	4	27	.	.	PUNCT
ajst-29293	5	1	clustering	cluster	VERB
ajst-29293	5	2	evaluation	evaluation	NOUN
ajst-29293	5	3	metrics	metric	NOUN
ajst-29293	5	4	are	be	AUX
ajst-29293	5	5	introduced	introduce	VERB
ajst-29293	5	6	to	to	PART
ajst-29293	5	7	determine	determine	VERB
ajst-29293	5	8	the	the	DET
ajst-29293	5	9	optimal	optimal	ADJ
ajst-29293	5	10	number	number	NOUN
ajst-29293	5	11	of	of	ADP
ajst-29293	5	12	clusters	cluster	NOUN
ajst-29293	5	13	.	.	PUNCT
ajst-29293	6	1	comparisons	comparison	NOUN
ajst-29293	6	2	show	show	VERB
ajst-29293	6	3	that	that	SCONJ
ajst-29293	6	4	the	the	DET
ajst-29293	6	5	improved	improved	ADJ
ajst-29293	6	6	algorithm	algorithm	NOUN
ajst-29293	6	7	significantly	significantly	ADV
ajst-29293	6	8	enhances	enhance	VERB
ajst-29293	6	9	convergence	convergence	NOUN
ajst-29293	6	10	speed	speed	NOUN
ajst-29293	6	11	and	and	CCONJ
ajst-29293	6	12	clustering	clustering	ADJ
ajst-29293	6	13	performance	performance	NOUN
ajst-29293	6	14	.	.	PUNCT
ajst-29293	7	1	the	the	DET
ajst-29293	7	2	clustering	clustering	ADJ
ajst-29293	7	3	center	center	NOUN
ajst-29293	7	4	at	at	ADP
ajst-29293	7	5	the	the	DET
ajst-29293	7	6	position	position	NOUN
ajst-29293	7	7	(	(	PUNCT
ajst-29293	7	8	17.79	17.79	NUM
ajst-29293	7	9	,	,	PUNCT
ajst-29293	7	10	7.62	7.62	NUM
ajst-29293	7	11	)	)	PUNCT
ajst-29293	7	12	in	in	ADP
ajst-29293	7	13	the	the	DET
ajst-29293	7	14	cross	cross	ADJ
ajst-29293	7	15	-	-	ADJ
ajst-29293	7	16	shaped	shaped	ADJ
ajst-29293	7	17	region	region	NOUN
ajst-29293	7	18	visually	visually	ADV
ajst-29293	7	19	reflects	reflect	VERB
ajst-29293	7	20	the	the	DET
ajst-29293	7	21	charging	charge	VERB
ajst-29293	7	22	patterns	pattern	NOUN
ajst-29293	7	23	of	of	ADP
ajst-29293	7	24	ev	ev	ADP
ajst-29293	7	25	users	user	NOUN
ajst-29293	7	26	.	.	PUNCT
ajst-29293	8	1	keywords	keyword	NOUN
ajst-29293	8	2	:	:	PUNCT
ajst-29293	8	3	electric	electric	ADJ
ajst-29293	8	4	vehicles	vehicle	NOUN
ajst-29293	8	5	;	;	PUNCT
ajst-29293	8	6	clustering	cluster	VERB
ajst-29293	8	7	algorithm	algorithm	NOUN
ajst-29293	8	8	;	;	PUNCT
ajst-29293	8	9	mvabc	mvabc	PROPN
ajst-29293	8	10	-	-	PUNCT
ajst-29293	8	11	gmm	gmm	PROPN
ajst-29293	8	12	;	;	PUNCT
ajst-29293	8	13	monte	monte	PROPN
ajst-29293	8	14	carlo	carlo	PROPN
ajst-29293	8	15	;	;	PUNCT
ajst-29293	8	16	clustering	cluster	VERB
ajst-29293	8	17	evaluation	evaluation	NOUN
ajst-29293	8	18	metrics	metric	NOUN
ajst-29293	8	19	.	.	PUNCT
ajst-29293	9	1	1	1	X
ajst-29293	9	2	.	.	X
ajst-29293	9	3	introduction	introduction	NOUN
ajst-29293	9	4	the	the	DET
ajst-29293	9	5	rapid	rapid	ADJ
ajst-29293	9	6	development	development	NOUN
ajst-29293	9	7	of	of	ADP
ajst-29293	9	8	electric	electric	ADJ
ajst-29293	9	9	vehicles	vehicle	NOUN
ajst-29293	9	10	(	(	PUNCT
ajst-29293	9	11	evs	evs	NOUN
ajst-29293	9	12	)	)	PUNCT
ajst-29293	9	13	in	in	ADP
ajst-29293	9	14	recent	recent	ADJ
ajst-29293	9	15	years	year	NOUN
ajst-29293	9	16	has	have	AUX
ajst-29293	9	17	provided	provide	VERB
ajst-29293	9	18	a	a	DET
ajst-29293	9	19	promising	promising	ADJ
ajst-29293	9	20	pathway	pathway	NOUN
ajst-29293	9	21	for	for	ADP
ajst-29293	9	22	addressing	address	VERB
ajst-29293	9	23	the	the	DET
ajst-29293	9	24	challenges	challenge	NOUN
ajst-29293	9	25	of	of	ADP
ajst-29293	9	26	renewable	renewable	ADJ
ajst-29293	9	27	energy	energy	NOUN
ajst-29293	9	28	integration	integration	NOUN
ajst-29293	9	29	.	.	PUNCT
ajst-29293	10	1	however	however	ADV
ajst-29293	10	2	,	,	PUNCT
ajst-29293	10	3	it	it	PRON
ajst-29293	10	4	has	have	AUX
ajst-29293	10	5	also	also	ADV
ajst-29293	10	6	revealed	reveal	VERB
ajst-29293	10	7	several	several	ADJ
ajst-29293	10	8	issues	issue	NOUN
ajst-29293	10	9	.	.	PUNCT
ajst-29293	11	1	when	when	SCONJ
ajst-29293	11	2	the	the	DET
ajst-29293	11	3	number	number	NOUN
ajst-29293	11	4	of	of	ADP
ajst-29293	11	5	evs	evs	PROPN
ajst-29293	11	6	reaches	reach	VERB
ajst-29293	11	7	a	a	DET
ajst-29293	11	8	certain	certain	ADJ
ajst-29293	11	9	threshold	threshold	NOUN
ajst-29293	11	10	,	,	PUNCT
ajst-29293	11	11	a	a	DET
ajst-29293	11	12	large	large	ADJ
ajst-29293	11	13	number	number	NOUN
ajst-29293	11	14	of	of	ADP
ajst-29293	11	15	vehicles	vehicle	NOUN
ajst-29293	11	16	may	may	AUX
ajst-29293	11	17	connect	connect	VERB
ajst-29293	11	18	to	to	ADP
ajst-29293	11	19	the	the	DET
ajst-29293	11	20	grid	grid	NOUN
ajst-29293	11	21	during	during	ADP
ajst-29293	11	22	specific	specific	ADJ
ajst-29293	11	23	periods	period	NOUN
ajst-29293	11	24	,	,	PUNCT
ajst-29293	11	25	leading	lead	VERB
ajst-29293	11	26	to	to	ADP
ajst-29293	11	27	increased	increase	VERB
ajst-29293	11	28	grid	grid	NOUN
ajst-29293	11	29	load	load	NOUN
ajst-29293	11	30	,	,	PUNCT
ajst-29293	11	31	reduced	reduce	VERB
ajst-29293	11	32	stability	stability	NOUN
ajst-29293	11	33	,	,	PUNCT
ajst-29293	11	34	line	line	NOUN
ajst-29293	11	35	congestion	congestion	NOUN
ajst-29293	11	36	,	,	PUNCT
ajst-29293	11	37	and	and	CCONJ
ajst-29293	11	38	load	load	NOUN
ajst-29293	11	39	imbalances	imbalance	NOUN
ajst-29293	11	40	[	[	X
ajst-29293	11	41	1	1	NUM
ajst-29293	11	42	]	]	PUNCT
ajst-29293	11	43	.	.	PUNCT
ajst-29293	12	1	the	the	DET
ajst-29293	12	2	clustered	clustered	ADJ
ajst-29293	12	3	charging	charge	VERB
ajst-29293	12	4	behavior	behavior	NOUN
ajst-29293	12	5	of	of	ADP
ajst-29293	12	6	evs	evs	NOUN
ajst-29293	12	7	inevitably	inevitably	ADV
ajst-29293	12	8	imposes	impose	VERB
ajst-29293	12	9	significant	significant	ADJ
ajst-29293	12	10	negative	negative	ADJ
ajst-29293	12	11	impacts	impact	NOUN
ajst-29293	12	12	on	on	ADP
ajst-29293	12	13	the	the	DET
ajst-29293	12	14	power	power	NOUN
ajst-29293	12	15	grid	grid	NOUN
ajst-29293	12	16	,	,	PUNCT
ajst-29293	12	17	including	include	VERB
ajst-29293	12	18	heightened	heighten	VERB
ajst-29293	12	19	instability	instability	NOUN
ajst-29293	12	20	,	,	PUNCT
ajst-29293	12	21	line	line	NOUN
ajst-29293	12	22	congestion	congestion	NOUN
ajst-29293	12	23	,	,	PUNCT
ajst-29293	12	24	and	and	CCONJ
ajst-29293	12	25	severe	severe	ADJ
ajst-29293	12	26	peak	peak	NOUN
ajst-29293	12	27	-	-	PUNCT
ajst-29293	12	28	valley	valley	NOUN
ajst-29293	12	29	differences	difference	NOUN
ajst-29293	12	30	[	[	X
ajst-29293	12	31	2	2	NUM
ajst-29293	12	32	]	]	PUNCT
ajst-29293	12	33	.	.	PUNCT
ajst-29293	13	1	against	against	ADP
ajst-29293	13	2	this	this	DET
ajst-29293	13	3	backdrop	backdrop	NOUN
ajst-29293	13	4	,	,	PUNCT
ajst-29293	13	5	adopting	adopt	VERB
ajst-29293	13	6	a	a	DET
ajst-29293	13	7	more	more	ADV
ajst-29293	13	8	precise	precise	ADJ
ajst-29293	13	9	and	and	CCONJ
ajst-29293	13	10	efficient	efficient	ADJ
ajst-29293	13	11	clustering	clustering	NOUN
ajst-29293	13	12	method	method	NOUN
ajst-29293	13	13	to	to	ADP
ajst-29293	13	14	group	group	NOUN
ajst-29293	13	15	evs	evs	PROPN
ajst-29293	13	16	based	base	VERB
ajst-29293	13	17	on	on	ADP
ajst-29293	13	18	similar	similar	ADJ
ajst-29293	13	19	charging	charging	NOUN
ajst-29293	13	20	periods	period	NOUN
ajst-29293	13	21	can	can	AUX
ajst-29293	13	22	help	help	VERB
ajst-29293	13	23	optimize	optimize	VERB
ajst-29293	13	24	loadshifting	loadshifting	NOUN
ajst-29293	13	25	strategies	strategy	NOUN
ajst-29293	13	26	and	and	CCONJ
ajst-29293	13	27	improve	improve	VERB
ajst-29293	13	28	the	the	DET
ajst-29293	13	29	utilization	utilization	NOUN
ajst-29293	13	30	efficiency	efficiency	NOUN
ajst-29293	13	31	of	of	ADP
ajst-29293	13	32	grid	grid	NOUN
ajst-29293	13	33	resources	resource	NOUN
ajst-29293	13	34	.	.	PUNCT
ajst-29293	14	1	therefore	therefore	ADV
ajst-29293	14	2	,	,	PUNCT
ajst-29293	14	3	this	this	DET
ajst-29293	14	4	paper	paper	NOUN
ajst-29293	14	5	combines	combine	VERB
ajst-29293	14	6	probabilistic	probabilistic	ADJ
ajst-29293	14	7	statistics	statistic	NOUN
ajst-29293	14	8	with	with	ADP
ajst-29293	14	9	clustering	clustering	ADJ
ajst-29293	14	10	algorithms	algorithm	NOUN
ajst-29293	14	11	to	to	PART
ajst-29293	14	12	propose	propose	VERB
ajst-29293	14	13	a	a	DET
ajst-29293	14	14	more	more	ADV
ajst-29293	14	15	accurate	accurate	ADJ
ajst-29293	14	16	and	and	CCONJ
ajst-29293	14	17	efficient	efficient	ADJ
ajst-29293	14	18	method	method	NOUN
ajst-29293	14	19	for	for	ADP
ajst-29293	14	20	simulating	simulate	VERB
ajst-29293	14	21	and	and	CCONJ
ajst-29293	14	22	clustering	cluster	VERB
ajst-29293	14	23	ev	ev	ADP
ajst-29293	14	24	charging	charge	VERB
ajst-29293	14	25	behaviors	behavior	NOUN
ajst-29293	14	26	.	.	PUNCT
ajst-29293	15	1	2	2	X
ajst-29293	15	2	.	.	X
ajst-29293	15	3	literature	literature	NOUN
ajst-29293	15	4	review	review	PROPN
ajst-29293	15	5	in	in	ADP
ajst-29293	15	6	data	data	NOUN
ajst-29293	15	7	analysis	analysis	NOUN
ajst-29293	15	8	and	and	CCONJ
ajst-29293	15	9	pattern	pattern	NOUN
ajst-29293	15	10	recognition	recognition	NOUN
ajst-29293	15	11	,	,	PUNCT
ajst-29293	15	12	the	the	DET
ajst-29293	15	13	proper	proper	ADJ
ajst-29293	15	14	selection	selection	NOUN
ajst-29293	15	15	of	of	ADP
ajst-29293	15	16	clustering	clustering	ADJ
ajst-29293	15	17	algorithms	algorithms	NOUN
ajst-29293	15	18	is	be	AUX
ajst-29293	15	19	critical	critical	ADJ
ajst-29293	15	20	,	,	PUNCT
ajst-29293	15	21	as	as	SCONJ
ajst-29293	15	22	it	it	PRON
ajst-29293	15	23	directly	directly	ADV
ajst-29293	15	24	impacts	impact	VERB
ajst-29293	15	25	the	the	DET
ajst-29293	15	26	accuracy	accuracy	NOUN
ajst-29293	15	27	and	and	CCONJ
ajst-29293	15	28	effectiveness	effectiveness	NOUN
ajst-29293	15	29	of	of	ADP
ajst-29293	15	30	the	the	DET
ajst-29293	15	31	analysis	analysis	NOUN
ajst-29293	15	32	results	result	NOUN
ajst-29293	15	33	.	.	PUNCT
ajst-29293	16	1	different	different	ADJ
ajst-29293	16	2	clustering	cluster	VERB
ajst-29293	16	3	algorithms	algorithm	NOUN
ajst-29293	16	4	exhibit	exhibit	VERB
ajst-29293	16	5	significant	significant	ADJ
ajst-29293	16	6	differences	difference	NOUN
ajst-29293	16	7	in	in	ADP
ajst-29293	16	8	theoretical	theoretical	ADJ
ajst-29293	16	9	foundations	foundation	NOUN
ajst-29293	16	10	,	,	PUNCT
ajst-29293	16	11	suitability	suitability	NOUN
ajst-29293	16	12	for	for	ADP
ajst-29293	16	13	data	datum	NOUN
ajst-29293	16	14	characteristics	characteristic	NOUN
ajst-29293	16	15	,	,	PUNCT
ajst-29293	16	16	and	and	CCONJ
ajst-29293	16	17	processing	processing	NOUN
ajst-29293	16	18	capabilities	capability	NOUN
ajst-29293	16	19	.	.	PUNCT
ajst-29293	17	1	an	an	DET
ajst-29293	17	2	inappropriate	inappropriate	ADJ
ajst-29293	17	3	choice	choice	NOUN
ajst-29293	17	4	may	may	AUX
ajst-29293	17	5	lead	lead	VERB
ajst-29293	17	6	to	to	ADP
ajst-29293	17	7	distorted	distorted	ADJ
ajst-29293	17	8	clustering	clustering	NOUN
ajst-29293	17	9	results	result	NOUN
ajst-29293	17	10	,	,	PUNCT
ajst-29293	17	11	loss	loss	NOUN
ajst-29293	17	12	of	of	ADP
ajst-29293	17	13	patterns	pattern	NOUN
ajst-29293	17	14	,	,	PUNCT
ajst-29293	17	15	or	or	CCONJ
ajst-29293	17	16	an	an	DET
ajst-29293	17	17	inability	inability	NOUN
ajst-29293	17	18	to	to	PART
ajst-29293	17	19	effectively	effectively	ADV
ajst-29293	17	20	interpret	interpret	VERB
ajst-29293	17	21	data	datum	NOUN
ajst-29293	17	22	trends	trend	NOUN
ajst-29293	17	23	.	.	PUNCT
ajst-29293	18	1	therefore	therefore	ADV
ajst-29293	18	2	,	,	PUNCT
ajst-29293	18	3	the	the	DET
ajst-29293	18	4	correct	correct	ADJ
ajst-29293	18	5	selection	selection	NOUN
ajst-29293	18	6	of	of	ADP
ajst-29293	18	7	clustering	clustering	ADJ
ajst-29293	18	8	algorithms	algorithms	NOUN
ajst-29293	18	9	is	be	AUX
ajst-29293	18	10	of	of	ADP
ajst-29293	18	11	paramount	paramount	ADJ
ajst-29293	18	12	importance	importance	NOUN
ajst-29293	18	13	.	.	PUNCT
ajst-29293	19	1	different	different	ADJ
ajst-29293	19	2	clustering	cluster	VERB
ajst-29293	19	3	algorithms	algorithm	NOUN
ajst-29293	19	4	have	have	AUX
ajst-29293	19	5	been	be	AUX
ajst-29293	19	6	designed	design	VERB
ajst-29293	19	7	and	and	CCONJ
ajst-29293	19	8	studied	study	VERB
ajst-29293	19	9	by	by	ADP
ajst-29293	19	10	many	many	ADJ
ajst-29293	19	11	scholars	scholar	NOUN
ajst-29293	19	12	.	.	PUNCT
ajst-29293	20	1	the	the	DET
ajst-29293	20	2	gaussian	gaussian	ADJ
ajst-29293	20	3	mixture	mixture	NOUN
ajst-29293	20	4	model	model	NOUN
ajst-29293	20	5	(	(	PUNCT
ajst-29293	20	6	gmm	gmm	NOUN
ajst-29293	20	7	)	)	PUNCT
ajst-29293	20	8	is	be	AUX
ajst-29293	20	9	a	a	DET
ajst-29293	20	10	probability	probability	NOUN
ajst-29293	20	11	distribution	distribution	NOUN
ajst-29293	20	12	-	-	PUNCT
ajst-29293	20	13	based	base	VERB
ajst-29293	20	14	clustering	clustering	ADJ
ajst-29293	20	15	algorithm	algorithm	NOUN
ajst-29293	20	16	that	that	PRON
ajst-29293	20	17	achieves	achieve	VERB
ajst-29293	20	18	"	"	PUNCT
ajst-29293	20	19	soft	soft	ADJ
ajst-29293	20	20	classification	classification	NOUN
ajst-29293	20	21	"	"	PUNCT
ajst-29293	20	22	by	by	ADP
ajst-29293	20	23	calculating	calculate	VERB
ajst-29293	20	24	the	the	DET
ajst-29293	20	25	probability	probability	NOUN
ajst-29293	20	26	distribution	distribution	NOUN
ajst-29293	20	27	of	of	ADP
ajst-29293	20	28	samples	sample	NOUN
ajst-29293	20	29	belonging	belong	VERB
ajst-29293	20	30	to	to	ADP
ajst-29293	20	31	each	each	DET
ajst-29293	20	32	cluster	cluster	NOUN
ajst-29293	20	33	[	[	X
ajst-29293	20	34	3	3	NUM
ajst-29293	20	35	]	]	PUNCT
ajst-29293	20	36	.	.	PUNCT
ajst-29293	21	1	compared	compare	VERB
ajst-29293	21	2	to	to	ADP
ajst-29293	21	3	partitionbased	partitionbase	VERB
ajst-29293	21	4	clustering	clustering	NOUN
ajst-29293	21	5	and	and	CCONJ
ajst-29293	21	6	hierarchical	hierarchical	ADJ
ajst-29293	21	7	clustering	clustering	NOUN
ajst-29293	21	8	,	,	PUNCT
ajst-29293	21	9	gmm	gmm	PROPN
ajst-29293	21	10	demonstrates	demonstrate	VERB
ajst-29293	21	11	advantages	advantage	NOUN
ajst-29293	21	12	in	in	ADP
ajst-29293	21	13	terms	term	NOUN
ajst-29293	21	14	of	of	ADP
ajst-29293	21	15	time	time	NOUN
ajst-29293	21	16	complexity	complexity	NOUN
ajst-29293	21	17	and	and	CCONJ
ajst-29293	21	18	the	the	DET
ajst-29293	21	19	local	local	ADJ
ajst-29293	21	20	optima	optima	PROPN
ajst-29293	21	21	problem	problem	NOUN
ajst-29293	21	22	,	,	PUNCT
ajst-29293	21	23	enabling	enable	VERB
ajst-29293	21	24	more	more	ADV
ajst-29293	21	25	efficient	efficient	ADJ
ajst-29293	21	26	handling	handling	NOUN
ajst-29293	21	27	of	of	ADP
ajst-29293	21	28	large	large	ADJ
ajst-29293	21	29	-	-	PUNCT
ajst-29293	21	30	scale	scale	NOUN
ajst-29293	21	31	datasets	dataset	NOUN
ajst-29293	21	32	.	.	PUNCT
ajst-29293	22	1	gmm	gmm	PROPN
ajst-29293	22	2	provides	provide	VERB
ajst-29293	22	3	soft	soft	ADJ
ajst-29293	22	4	assignments	assignment	NOUN
ajst-29293	22	5	,	,	PUNCT
ajst-29293	22	6	where	where	SCONJ
ajst-29293	22	7	each	each	DET
ajst-29293	22	8	data	data	NOUN
ajst-29293	22	9	point	point	NOUN
ajst-29293	22	10	can	can	AUX
ajst-29293	22	11	belong	belong	VERB
ajst-29293	22	12	to	to	ADP
ajst-29293	22	13	multiple	multiple	ADJ
ajst-29293	22	14	clusters	cluster	NOUN
ajst-29293	22	15	with	with	ADP
ajst-29293	22	16	certain	certain	ADJ
ajst-29293	22	17	probabilities	probability	NOUN
ajst-29293	22	18	.	.	PUNCT
ajst-29293	23	1	this	this	DET
ajst-29293	23	2	feature	feature	NOUN
ajst-29293	23	3	makes	make	VERB
ajst-29293	23	4	gmm	gmm	PRON
ajst-29293	23	5	perform	perform	VERB
ajst-29293	23	6	better	well	ADV
ajst-29293	23	7	in	in	ADP
ajst-29293	23	8	cases	case	NOUN
ajst-29293	23	9	where	where	SCONJ
ajst-29293	23	10	data	datum	NOUN
ajst-29293	23	11	distributions	distribution	NOUN
ajst-29293	23	12	overlap	overlap	VERB
ajst-29293	23	13	or	or	CCONJ
ajst-29293	23	14	exhibit	exhibit	VERB
ajst-29293	23	15	uncertainty	uncertainty	NOUN
ajst-29293	23	16	.	.	PUNCT
ajst-29293	24	1	comparative	comparative	ADJ
ajst-29293	24	2	analyses	analysis	NOUN
ajst-29293	24	3	in	in	ADP
ajst-29293	24	4	the	the	DET
ajst-29293	24	5	literature	literature	NOUN
ajst-29293	24	6	[	[	X
ajst-29293	24	7	4	4	X
ajst-29293	24	8	]	]	PUNCT
ajst-29293	24	9	suggest	suggest	VERB
ajst-29293	24	10	that	that	SCONJ
ajst-29293	24	11	gmm	gmm	PROPN
ajst-29293	24	12	outperforms	outperform	VERB
ajst-29293	24	13	hierarchical	hierarchical	ADJ
ajst-29293	24	14	clustering	clustering	NOUN
ajst-29293	24	15	,	,	PUNCT
ajst-29293	24	16	k	k	NOUN
ajst-29293	24	17	-	-	PUNCT
ajst-29293	24	18	means	means	NOUN
ajst-29293	24	19	,	,	PUNCT
ajst-29293	24	20	k	k	NOUN
ajst-29293	24	21	-	-	NOUN
ajst-29293	24	22	medoids	medoid	NOUN
ajst-29293	24	23	,	,	PUNCT
ajst-29293	24	24	and	and	CCONJ
ajst-29293	24	25	self	self	NOUN
ajst-29293	24	26	-	-	PUNCT
ajst-29293	24	27	organizing	organize	VERB
ajst-29293	24	28	maps	map	NOUN
ajst-29293	24	29	(	(	PUNCT
ajst-29293	24	30	som	som	NOUN
ajst-29293	24	31	)	)	PUNCT
ajst-29293	24	32	in	in	ADP
ajst-29293	24	33	clustering	clustering	ADJ
ajst-29293	24	34	performance	performance	NOUN
ajst-29293	24	35	and	and	CCONJ
ajst-29293	24	36	demonstrates	demonstrate	VERB
ajst-29293	24	37	significant	significant	ADJ
ajst-29293	24	38	flexibility	flexibility	NOUN
ajst-29293	24	39	in	in	ADP
ajst-29293	24	40	accommodating	accommodate	VERB
ajst-29293	24	41	cluster	cluster	NOUN
ajst-29293	24	42	shapes	shape	NOUN
ajst-29293	24	43	.	.	PUNCT
ajst-29293	25	1	although	although	SCONJ
ajst-29293	25	2	gmm	gmm	PROPN
ajst-29293	25	3	is	be	AUX
ajst-29293	25	4	well	well	ADV
ajst-29293	25	5	-	-	PUNCT
ajst-29293	25	6	suited	suit	VERB
ajst-29293	25	7	for	for	ADP
ajst-29293	25	8	clustering	cluster	VERB
ajst-29293	25	9	ev	ev	PRON
ajst-29293	25	10	connection	connection	NOUN
ajst-29293	25	11	and	and	CCONJ
ajst-29293	25	12	disconnection	disconnection	NOUN
ajst-29293	25	13	time	time	NOUN
ajst-29293	25	14	data	data	PROPN
ajst-29293	25	15	,	,	PUNCT
ajst-29293	25	16	its	its	PRON
ajst-29293	25	17	computational	computational	ADJ
ajst-29293	25	18	time	time	NOUN
ajst-29293	25	19	complexity	complexity	NOUN
ajst-29293	25	20	increases	increase	VERB
ajst-29293	25	21	significantly	significantly	ADV
ajst-29293	25	22	as	as	ADP
ajst-29293	25	23	the	the	DET
ajst-29293	25	24	number	number	NOUN
ajst-29293	25	25	of	of	ADP
ajst-29293	25	26	evs	evs	NOUN
ajst-29293	25	27	or	or	CCONJ
ajst-29293	25	28	the	the	DET
ajst-29293	25	29	volume	volume	NOUN
ajst-29293	25	30	of	of	ADP
ajst-29293	25	31	charging	charge	VERB
ajst-29293	25	32	behavior	behavior	NOUN
ajst-29293	25	33	data	datum	NOUN
ajst-29293	25	34	grows	grow	VERB
ajst-29293	25	35	within	within	ADP
ajst-29293	25	36	a	a	DET
ajst-29293	25	37	region	region	NOUN
ajst-29293	25	38	.	.	PUNCT
ajst-29293	26	1	moreover	moreover	ADV
ajst-29293	26	2	,	,	PUNCT
ajst-29293	26	3	the	the	DET
ajst-29293	26	4	em	em	PROPN
ajst-29293	26	5	algorithm	algorithm	NOUN
ajst-29293	26	6	in	in	ADP
ajst-29293	26	7	gmm	gmm	PROPN
ajst-29293	26	8	is	be	AUX
ajst-29293	26	9	highly	highly	ADV
ajst-29293	26	10	sensitive	sensitive	ADJ
ajst-29293	26	11	to	to	ADP
ajst-29293	26	12	initial	initial	ADJ
ajst-29293	26	13	parameters	parameter	NOUN
ajst-29293	26	14	(	(	PUNCT
ajst-29293	26	15	means	mean	NOUN
ajst-29293	26	16	,	,	PUNCT
ajst-29293	26	17	covariances	covariance	NOUN
ajst-29293	26	18	,	,	PUNCT
ajst-29293	26	19	weights	weight	NOUN
ajst-29293	26	20	)	)	PUNCT
ajst-29293	26	21	,	,	PUNCT
ajst-29293	26	22	and	and	CCONJ
ajst-29293	26	23	inappropriate	inappropriate	ADJ
ajst-29293	26	24	initial	initial	ADJ
ajst-29293	26	25	values	value	NOUN
ajst-29293	26	26	may	may	AUX
ajst-29293	26	27	result	result	VERB
ajst-29293	26	28	in	in	ADP
ajst-29293	26	29	convergence	convergence	NOUN
ajst-29293	26	30	to	to	ADP
ajst-29293	26	31	local	local	ADJ
ajst-29293	26	32	optima	optima	NOUN
ajst-29293	26	33	.	.	PUNCT
ajst-29293	27	1	to	to	PART
ajst-29293	27	2	address	address	VERB
ajst-29293	27	3	these	these	DET
ajst-29293	27	4	shortcomings	shortcoming	NOUN
ajst-29293	27	5	and	and	CCONJ
ajst-29293	27	6	achieve	achieve	VERB
ajst-29293	27	7	better	well	ADJ
ajst-29293	27	8	clustering	clustering	ADJ
ajst-29293	27	9	results	result	NOUN
ajst-29293	27	10	for	for	ADP
ajst-29293	27	11	ev	ev	INTJ
ajst-29293	27	12	connection	connection	NOUN
ajst-29293	27	13	and	and	CCONJ
ajst-29293	27	14	disconnection	disconnection	NOUN
ajst-29293	27	15	time	time	NOUN
ajst-29293	27	16	data	data	PROPN
ajst-29293	27	17	,	,	PUNCT
ajst-29293	27	18	this	this	DET
ajst-29293	27	19	paper	paper	NOUN
ajst-29293	27	20	incorporates	incorporate	VERB
ajst-29293	27	21	the	the	DET
ajst-29293	27	22	minimum	minimum	ADJ
ajst-29293	27	23	variance	variance	NOUN
ajst-29293	27	24	(	(	PUNCT
ajst-29293	27	25	mv	mv	NOUN
ajst-29293	27	26	)	)	PUNCT
ajst-29293	27	27	theory	theory	NOUN
ajst-29293	27	28	and	and	CCONJ
ajst-29293	27	29	combines	combine	VERB
ajst-29293	27	30	it	it	PRON
ajst-29293	27	31	with	with	ADP
ajst-29293	27	32	the	the	DET
ajst-29293	27	33	artificial	artificial	ADJ
ajst-29293	27	34	bee	bee	NOUN
ajst-29293	27	35	colony	colony	NOUN
ajst-29293	27	36	(	(	PUNCT
ajst-29293	27	37	abc	abc	PROPN
ajst-29293	27	38	)	)	PUNCT
ajst-29293	27	39	algorithm	algorithm	NOUN
ajst-29293	27	40	to	to	PART
ajst-29293	27	41	improve	improve	VERB
ajst-29293	27	42	the	the	DET
ajst-29293	27	43	gmm	gmm	PROPN
ajst-29293	27	44	algorithm	algorithm	NOUN
ajst-29293	27	45	.	.	PUNCT
ajst-29293	28	1	this	this	DET
ajst-29293	28	2	enhancement	enhancement	NOUN
ajst-29293	28	3	aims	aim	VERB
ajst-29293	28	4	to	to	PART
ajst-29293	28	5	improve	improve	VERB
ajst-29293	28	6	clustering	clustering	ADJ
ajst-29293	28	7	performance	performance	NOUN
ajst-29293	28	8	and	and	CCONJ
ajst-29293	28	9	convergence	convergence	NOUN
ajst-29293	28	10	efficiency	efficiency	NOUN
ajst-29293	28	11	,	,	PUNCT
ajst-29293	28	12	enabling	enable	VERB
ajst-29293	28	13	more	more	ADV
ajst-29293	28	14	accurate	accurate	ADJ
ajst-29293	28	15	clustering	clustering	NOUN
ajst-29293	28	16	of	of	ADP
ajst-29293	28	17	ev	ev	ADP
ajst-29293	28	18	connection	connection	NOUN
ajst-29293	28	19	and	and	CCONJ
ajst-29293	28	20	disconnection	disconnection	NOUN
ajst-29293	28	21	time	time	NOUN
ajst-29293	28	22	data	data	PROPN
ajst-29293	28	23	.	.	PUNCT
ajst-29293	29	1	3	3	X
ajst-29293	29	2	.	.	X
ajst-29293	29	3	experimental	experimental	ADJ
ajst-29293	29	4	analysis	analysis	NOUN
ajst-29293	29	5	3.1	3.1	NUM
ajst-29293	29	6	.	.	PUNCT
ajst-29293	29	7	probability	probability	NOUN
ajst-29293	29	8	density	density	NOUN
ajst-29293	29	9	function	function	VERB
ajst-29293	29	10	fitting	fitting	ADJ
ajst-29293	29	11	fig	fig	NOUN
ajst-29293	29	12	.	.	PUNCT
ajst-29293	29	13	1	1	NUM
ajst-29293	29	14	show	show	VERB
ajst-29293	29	15	the	the	DET
ajst-29293	29	16	statistics	statistic	NOUN
ajst-29293	29	17	of	of	ADP
ajst-29293	29	18	the	the	DET
ajst-29293	29	19	times	time	NOUN
ajst-29293	29	20	when	when	SCONJ
ajst-29293	29	21	electric	electric	ADJ
ajst-29293	29	22	vehicles	vehicle	NOUN
ajst-29293	29	23	(	(	PUNCT
ajst-29293	29	24	evs	evs	NOUN
ajst-29293	29	25	)	)	PUNCT
ajst-29293	29	26	return	return	VERB
ajst-29293	29	27	home	home	ADV
ajst-29293	29	28	and	and	CCONJ
ajst-29293	29	29	leave	leave	VERB
ajst-29293	29	30	home	home	NOUN
ajst-29293	29	31	,	,	PUNCT
ajst-29293	29	32	respectively	respectively	ADV
ajst-29293	29	33	,	,	PUNCT
ajst-29293	29	34	based	base	VERB
ajst-29293	29	35	on	on	ADP
ajst-29293	29	36	the	the	DET
ajst-29293	29	37	"	"	PUNCT
ajst-29293	29	38	big	big	ADJ
ajst-29293	29	39	data	datum	NOUN
ajst-29293	29	40	report	report	NOUN
ajst-29293	29	41	on	on	ADP
ajst-29293	29	42	the	the	DET
ajst-29293	29	43	travel	travel	NOUN
ajst-29293	29	44	of	of	ADP
ajst-29293	29	45	small	small	ADJ
ajst-29293	29	46	pure	pure	ADJ
ajst-29293	29	47	electric	electric	ADJ
ajst-29293	29	48	passenger	passenger	NOUN
ajst-29293	29	49	cars	car	NOUN
ajst-29293	29	50	in	in	ADP
ajst-29293	29	51	china	china	PROPN
ajst-29293	29	52	"	"	PUNCT
ajst-29293	30	1	[	[	X
ajst-29293	30	2	5	5	NUM
ajst-29293	30	3	]	]	PUNCT
ajst-29293	30	4	.	.	PUNCT
ajst-29293	31	1	91	91	NUM
ajst-29293	31	2	figure	figure	NOUN
ajst-29293	31	3	1	1	NUM
ajst-29293	31	4	.	.	PUNCT
ajst-29293	32	1	the	the	DET
ajst-29293	32	2	time	time	NOUN
ajst-29293	32	3	of	of	ADP
ajst-29293	32	4	electric	electric	ADJ
ajst-29293	32	5	vehicle	vehicle	NOUN
ajst-29293	32	6	grid	grid	NOUN
ajst-29293	32	7	connection	connection	NOUN
ajst-29293	32	8	and	and	CCONJ
ajst-29293	32	9	disconnection	disconnection	NOUN
ajst-29293	32	10	.	.	PUNCT
ajst-29293	33	1	typically	typically	ADV
ajst-29293	33	2	,	,	PUNCT
ajst-29293	33	3	ev	ev	ADP
ajst-29293	33	4	users	user	NOUN
ajst-29293	33	5	connect	connect	VERB
ajst-29293	33	6	their	their	PRON
ajst-29293	33	7	vehicles	vehicle	NOUN
ajst-29293	33	8	to	to	ADP
ajst-29293	33	9	the	the	DET
ajst-29293	33	10	grid	grid	NOUN
ajst-29293	33	11	for	for	ADP
ajst-29293	33	12	charging	charge	VERB
ajst-29293	33	13	after	after	ADP
ajst-29293	33	14	returning	return	VERB
ajst-29293	33	15	home	home	NOUN
ajst-29293	33	16	.	.	PUNCT
ajst-29293	34	1	therefore	therefore	ADV
ajst-29293	34	2	,	,	PUNCT
ajst-29293	34	3	in	in	ADP
ajst-29293	34	4	this	this	DET
ajst-29293	34	5	study	study	NOUN
ajst-29293	34	6	,	,	PUNCT
ajst-29293	34	7	the	the	DET
ajst-29293	34	8	return	return	NOUN
ajst-29293	34	9	home	home	NOUN
ajst-29293	34	10	time	time	NOUN
ajst-29293	34	11	of	of	ADP
ajst-29293	34	12	ev	ev	PRON
ajst-29293	34	13	users	user	NOUN
ajst-29293	34	14	is	be	AUX
ajst-29293	34	15	regarded	regard	VERB
ajst-29293	34	16	as	as	ADP
ajst-29293	34	17	the	the	DET
ajst-29293	34	18	connection	connection	NOUN
ajst-29293	34	19	time	time	NOUN
ajst-29293	34	20	to	to	ADP
ajst-29293	34	21	the	the	DET
ajst-29293	34	22	grid	grid	NOUN
ajst-29293	34	23	(	(	PUNCT
ajst-29293	34	24	entry	entry	NOUN
ajst-29293	34	25	time	time	NOUN
ajst-29293	34	26	)	)	PUNCT
ajst-29293	34	27	.	.	PUNCT
ajst-29293	35	1	similarly	similarly	ADV
ajst-29293	35	2	,	,	PUNCT
ajst-29293	35	3	the	the	DET
ajst-29293	35	4	departure	departure	NOUN
ajst-29293	35	5	time	time	NOUN
ajst-29293	35	6	the	the	DET
ajst-29293	35	7	following	following	ADJ
ajst-29293	35	8	day	day	NOUN
ajst-29293	35	9	is	be	AUX
ajst-29293	35	10	considered	consider	VERB
ajst-29293	35	11	the	the	DET
ajst-29293	35	12	disconnection	disconnection	NOUN
ajst-29293	35	13	time	time	NOUN
ajst-29293	35	14	from	from	ADP
ajst-29293	35	15	the	the	DET
ajst-29293	35	16	grid	grid	NOUN
ajst-29293	35	17	(	(	PUNCT
ajst-29293	35	18	exit	exit	NOUN
ajst-29293	35	19	time	time	NOUN
ajst-29293	35	20	)	)	PUNCT
ajst-29293	35	21	.	.	PUNCT
ajst-29293	36	1	by	by	ADP
ajst-29293	36	2	inputting	inputte	VERB
ajst-29293	36	3	the	the	DET
ajst-29293	36	4	statistical	statistical	ADJ
ajst-29293	36	5	data	datum	NOUN
ajst-29293	36	6	fig	fig	NOUN
ajst-29293	36	7	.	.	PUNCT
ajst-29293	36	8	1	1	NUM
ajst-29293	36	9	into	into	ADP
ajst-29293	36	10	matlab	matlab	NOUN
ajst-29293	36	11	and	and	CCONJ
ajst-29293	36	12	processing	process	VERB
ajst-29293	36	13	it	it	PRON
ajst-29293	36	14	through	through	ADP
ajst-29293	36	15	programming	programming	NOUN
ajst-29293	36	16	with	with	ADP
ajst-29293	36	17	the	the	DET
ajst-29293	36	18	fit	fit	ADJ
ajst-29293	36	19	function	function	NOUN
ajst-29293	36	20	,	,	PUNCT
ajst-29293	36	21	the	the	DET
ajst-29293	36	22	probability	probability	NOUN
ajst-29293	36	23	distribution	distribution	NOUN
ajst-29293	36	24	functions	function	NOUN
ajst-29293	36	25	for	for	ADP
ajst-29293	36	26	ev	ev	INTJ
ajst-29293	36	27	connection	connection	NOUN
ajst-29293	36	28	and	and	CCONJ
ajst-29293	36	29	disconnection	disconnection	NOUN
ajst-29293	36	30	times	time	NOUN
ajst-29293	36	31	were	be	AUX
ajst-29293	36	32	derived	derive	VERB
ajst-29293	36	33	,	,	PUNCT
ajst-29293	36	34	as	as	SCONJ
ajst-29293	36	35	shown	show	VERB
ajst-29293	36	36	below	below	ADP
ajst-29293	36	37	:	:	PUNCT
ajst-29293	36	38	2	2	NUM
ajst-29293	36	39	2	2	NUM
ajst-29293	36	40	1	1	NUM
ajst-29293	36	41	1	1	NUM
ajst-29293	36	42	1	1	NUM
ajst-29293	36	43	2	2	NUM
ajst-29293	36	44	2	2	NUM
ajst-29293	36	45	2	2	NUM
ajst-29293	36	46	(	(	PUNCT
ajst-29293	36	47	)	)	PUNCT
ajst-29293	36	48	exp	exp	NOUN
ajst-29293	36	49	(	(	PUNCT
ajst-29293	36	50	(	(	PUNCT
ajst-29293	36	51	(	(	PUNCT
ajst-29293	36	52	)	)	PUNCT
ajst-29293	36	53	/	/	SYM
ajst-29293	36	54	)	)	PUNCT
ajst-29293	36	55	)	)	PUNCT
ajst-29293	36	56	exp	exp	NOUN
ajst-29293	36	57	(	(	PUNCT
ajst-29293	36	58	(	(	PUNCT
ajst-29293	36	59	(	(	PUNCT
ajst-29293	36	60	)	)	PUNCT
ajst-29293	36	61	/	/	SYM
ajst-29293	36	62	)	)	PUNCT
ajst-29293	36	63	)	)	PUNCT
ajst-29293	37	1	stf	stf	PROPN
ajst-29293	37	2	x	x	PUNCT
ajst-29293	37	3	a	a	DET
ajst-29293	37	4	x	x	X
ajst-29293	37	5	b	b	PROPN
ajst-29293	37	6	c	c	NOUN
ajst-29293	37	7	a	a	DET
ajst-29293	37	8	x	x	X
ajst-29293	37	9	b	b	PROPN
ajst-29293	37	10	c	c	PROPN
ajst-29293	37	11			PROPN
ajst-29293	37	12			PROPN
ajst-29293	37	13			PROPN
ajst-29293	37	14			ADV
ajst-29293	37	15			VERB
ajst-29293	37	16			PROPN
ajst-29293	37	17			PROPN
ajst-29293	37	18	(	(	PUNCT
ajst-29293	37	19	1	1	NUM
ajst-29293	37	20	)	)	SYM
ajst-29293	37	21	2	2	NUM
ajst-29293	37	22	2	2	NUM
ajst-29293	37	23	3	3	NUM
ajst-29293	37	24	3	3	NUM
ajst-29293	37	25	3	3	NUM
ajst-29293	37	26	4	4	NUM
ajst-29293	37	27	4	4	NUM
ajst-29293	37	28	4	4	NUM
ajst-29293	37	29	(	(	PUNCT
ajst-29293	37	30	)	)	PUNCT
ajst-29293	37	31	exp	exp	NOUN
ajst-29293	37	32	(	(	PUNCT
ajst-29293	37	33	(	(	PUNCT
ajst-29293	37	34	(	(	PUNCT
ajst-29293	37	35	)	)	PUNCT
ajst-29293	37	36	/	/	SYM
ajst-29293	37	37	)	)	PUNCT
ajst-29293	37	38	)	)	PUNCT
ajst-29293	37	39	exp	exp	NOUN
ajst-29293	37	40	(	(	PUNCT
ajst-29293	37	41	(	(	PUNCT
ajst-29293	37	42	(	(	PUNCT
ajst-29293	37	43	)	)	PUNCT
ajst-29293	37	44	/	/	SYM
ajst-29293	37	45	)	)	PUNCT
ajst-29293	37	46	)	)	PUNCT
ajst-29293	38	1	stf	stf	PROPN
ajst-29293	38	2	x	x	PUNCT
ajst-29293	38	3	a	a	DET
ajst-29293	38	4	x	x	X
ajst-29293	38	5	b	b	PROPN
ajst-29293	38	6	c	c	NOUN
ajst-29293	38	7	a	a	DET
ajst-29293	38	8	x	x	X
ajst-29293	38	9	b	b	PROPN
ajst-29293	38	10	c	c	PROPN
ajst-29293	38	11			PROPN
ajst-29293	38	12			PROPN
ajst-29293	38	13			PROPN
ajst-29293	38	14			ADV
ajst-29293	38	15			VERB
ajst-29293	38	16			PROPN
ajst-29293	38	17			PROPN
ajst-29293	38	18	(	(	PUNCT
ajst-29293	38	19	2	2	NUM
ajst-29293	38	20	)	)	PUNCT
ajst-29293	38	21	eq.(1	eq.(1	NUM
ajst-29293	38	22	)	)	PUNCT
ajst-29293	38	23	represents	represent	VERB
ajst-29293	38	24	the	the	DET
ajst-29293	38	25	probability	probability	NOUN
ajst-29293	38	26	density	density	NOUN
ajst-29293	38	27	function	function	NOUN
ajst-29293	38	28	(	(	PUNCT
ajst-29293	38	29	pdf	pdf	NOUN
ajst-29293	38	30	)	)	PUNCT
ajst-29293	38	31	for	for	ADP
ajst-29293	38	32	the	the	DET
ajst-29293	38	33	start	start	NOUN
ajst-29293	38	34	time	time	NOUN
ajst-29293	38	35	of	of	ADP
ajst-29293	38	36	ev	ev	NOUN
ajst-29293	38	37	charging	charging	NOUN
ajst-29293	38	38	,	,	PUNCT
ajst-29293	38	39	and	and	CCONJ
ajst-29293	38	40	eq.(2	eq.(2	ADJ
ajst-29293	38	41	)	)	PUNCT
ajst-29293	38	42	represents	represent	VERB
ajst-29293	38	43	the	the	DET
ajst-29293	38	44	pdf	pdf	NOUN
ajst-29293	38	45	for	for	ADP
ajst-29293	38	46	the	the	DET
ajst-29293	38	47	end	end	NOUN
ajst-29293	38	48	time	time	NOUN
ajst-29293	38	49	of	of	ADP
ajst-29293	38	50	ev	ev	NOUN
ajst-29293	38	51	charging	charging	NOUN
ajst-29293	38	52	.	.	PUNCT
ajst-29293	39	1	the	the	DET
ajst-29293	39	2	probability	probability	NOUN
ajst-29293	39	3	density	density	NOUN
ajst-29293	39	4	function	function	NOUN
ajst-29293	39	5	curves	curve	NOUN
ajst-29293	39	6	derived	derive	VERB
ajst-29293	39	7	from	from	ADP
ajst-29293	39	8	eq.(1	eq.(1	ADJ
ajst-29293	39	9	)	)	PUNCT
ajst-29293	39	10	and	and	CCONJ
ajst-29293	39	11	(	(	PUNCT
ajst-29293	39	12	2	2	X
ajst-29293	39	13	)	)	PUNCT
ajst-29293	39	14	are	be	AUX
ajst-29293	39	15	shown	show	VERB
ajst-29293	39	16	as	as	ADP
ajst-29293	39	17	fig	fig	NOUN
ajst-29293	39	18	.	.	PUNCT
ajst-29293	40	1	2	2	NUM
ajst-29293	40	2	:	:	PUNCT
ajst-29293	40	3	figure	figure	NOUN
ajst-29293	40	4	2	2	NUM
ajst-29293	40	5	.	.	NOUN
ajst-29293	40	6	probability	probability	NOUN
ajst-29293	40	7	density	density	NOUN
ajst-29293	40	8	curve	curve	NOUN
ajst-29293	40	9	of	of	ADP
ajst-29293	40	10	electric	electric	ADJ
ajst-29293	40	11	vehicles	vehicle	NOUN
ajst-29293	40	12	based	base	VERB
ajst-29293	40	13	on	on	ADP
ajst-29293	40	14	the	the	DET
ajst-29293	40	15	fitted	fit	VERB
ajst-29293	40	16	curves	curve	NOUN
ajst-29293	40	17	,	,	PUNCT
ajst-29293	40	18	we	we	PRON
ajst-29293	40	19	obtained	obtain	VERB
ajst-29293	40	20	the	the	DET
ajst-29293	40	21	parameters	parameter	NOUN
ajst-29293	40	22	of	of	ADP
ajst-29293	40	23	the	the	DET
ajst-29293	40	24	probability	probability	NOUN
ajst-29293	40	25	density	density	NOUN
ajst-29293	40	26	functions	function	NOUN
ajst-29293	40	27	.	.	PUNCT
ajst-29293	41	1	the	the	DET
ajst-29293	41	2	parameter	parameter	NOUN
ajst-29293	41	3	details	detail	NOUN
ajst-29293	41	4	are	be	AUX
ajst-29293	41	5	listed	list	VERB
ajst-29293	41	6	in	in	ADP
ajst-29293	41	7	table	table	NOUN
ajst-29293	41	8	1	1	NUM
ajst-29293	41	9	below	below	ADV
ajst-29293	41	10	.	.	PUNCT
ajst-29293	42	1	table	table	NOUN
ajst-29293	42	2	1	1	NUM
ajst-29293	42	3	.	.	PUNCT
ajst-29293	42	4	table	table	NOUN
ajst-29293	42	5	of	of	ADP
ajst-29293	42	6	probability	probability	NOUN
ajst-29293	42	7	density	density	NOUN
ajst-29293	42	8	function	function	NOUN
ajst-29293	42	9	parameters	parameter	NOUN
ajst-29293	42	10	parameter	parameter	NOUN
ajst-29293	42	11	value	value	NOUN
ajst-29293	42	12	parameter	parameter	NOUN
ajst-29293	42	13	value	value	NOUN
ajst-29293	42	14	parameter	parameter	NOUN
ajst-29293	42	15	value	value	NOUN
ajst-29293	42	16	1a	1a	PROPN
ajst-29293	42	17	0.1732	0.1732	NUM
ajst-29293	42	18	1b	1b	NUM
ajst-29293	42	19	17.79	17.79	NUM
ajst-29293	42	20	1c	1c	NUM
ajst-29293	42	21	1.358	1.358	NUM
ajst-29293	42	22	2a	2a	NUM
ajst-29293	42	23	0.0221	0.0221	NUM
ajst-29293	42	24	2b	2b	NUM
ajst-29293	42	25	0.346	0.346	NUM
ajst-29293	42	26	2c	2c	NUM
ajst-29293	42	27	14.25	14.25	NUM
ajst-29293	42	28	3a	3a	NUM
ajst-29293	42	29	0.2908	0.2908	NUM
ajst-29293	42	30	3b	3b	NUM
ajst-29293	42	31	7.62	7.62	NUM
ajst-29293	42	32	3c	3c	NUM
ajst-29293	42	33	0.97	0.97	NUM
ajst-29293	42	34	4a	4a	NOUN
ajst-29293	42	35	0.0276	0.0276	NUM
ajst-29293	42	36	4b	4b	PROPN
ajst-29293	42	37	22.76	22.76	NUM
ajst-29293	42	38	4c	4c	NOUN
ajst-29293	42	39	9.352	9.352	NUM
ajst-29293	42	40	from	from	ADP
ajst-29293	42	41	table	table	NOUN
ajst-29293	42	42	1	1	NUM
ajst-29293	42	43	,	,	PUNCT
ajst-29293	42	44	we	we	PRON
ajst-29293	42	45	can	can	AUX
ajst-29293	42	46	conclude	conclude	VERB
ajst-29293	42	47	that	that	SCONJ
ajst-29293	42	48	the	the	DET
ajst-29293	42	49	primary	primary	ADJ
ajst-29293	42	50	peak	peak	NOUN
ajst-29293	42	51	of	of	ADP
ajst-29293	42	52	the	the	DET
ajst-29293	42	53	connection	connection	NOUN
ajst-29293	42	54	probability	probability	NOUN
ajst-29293	42	55	is	be	AUX
ajst-29293	42	56	around	around	ADP
ajst-29293	42	57	17:50	17:50	NUM
ajst-29293	42	58	,	,	PUNCT
ajst-29293	42	59	where	where	SCONJ
ajst-29293	42	60	the	the	DET
ajst-29293	42	61	proportion	proportion	NOUN
ajst-29293	42	62	of	of	ADP
ajst-29293	42	63	evs	evs	NOUN
ajst-29293	42	64	charging	charging	NOUN
ajst-29293	42	65	is	be	AUX
ajst-29293	42	66	approximately	approximately	ADV
ajst-29293	42	67	17.32	17.32	NUM
ajst-29293	42	68	%	%	NOUN
ajst-29293	42	69	.	.	PUNCT
ajst-29293	43	1	the	the	DET
ajst-29293	43	2	secondary	secondary	ADJ
ajst-29293	43	3	peak	peak	NOUN
ajst-29293	43	4	occurs	occur	VERB
ajst-29293	43	5	around	around	ADP
ajst-29293	43	6	0:20	0:20	NUM
ajst-29293	43	7	,	,	PUNCT
ajst-29293	43	8	with	with	ADP
ajst-29293	43	9	a	a	DET
ajst-29293	43	10	charging	charge	VERB
ajst-29293	43	11	proportion	proportion	NOUN
ajst-29293	43	12	of	of	ADP
ajst-29293	43	13	approximately	approximately	ADV
ajst-29293	43	14	2.21	2.21	NUM
ajst-29293	43	15	%	%	NOUN
ajst-29293	43	16	.	.	PUNCT
ajst-29293	44	1	for	for	ADP
ajst-29293	44	2	the	the	DET
ajst-29293	44	3	disconnection	disconnection	NOUN
ajst-29293	44	4	probability	probability	NOUN
ajst-29293	44	5	,	,	PUNCT
ajst-29293	44	6	the	the	DET
ajst-29293	44	7	primary	primary	ADJ
ajst-29293	44	8	peak	peak	NOUN
ajst-29293	44	9	is	be	AUX
ajst-29293	44	10	around	around	ADP
ajst-29293	44	11	7:30	7:30	NUM
ajst-29293	44	12	,	,	PUNCT
ajst-29293	44	13	with	with	ADP
ajst-29293	44	14	a	a	DET
ajst-29293	44	15	charging	charge	VERB
ajst-29293	44	16	proportion	proportion	NOUN
ajst-29293	44	17	of	of	ADP
ajst-29293	44	18	approximately	approximately	ADV
ajst-29293	44	19	29.08	29.08	NUM
ajst-29293	44	20	%	%	NOUN
ajst-29293	44	21	,	,	PUNCT
ajst-29293	44	22	while	while	SCONJ
ajst-29293	44	23	the	the	DET
ajst-29293	44	24	secondary	secondary	ADJ
ajst-29293	44	25	peak	peak	NOUN
ajst-29293	44	26	is	be	AUX
ajst-29293	44	27	around	around	ADP
ajst-29293	44	28	22:50	22:50	NUM
ajst-29293	44	29	,	,	PUNCT
ajst-29293	44	30	with	with	ADP
ajst-29293	44	31	a	a	DET
ajst-29293	44	32	charging	charge	VERB
ajst-29293	44	33	proportion	proportion	NOUN
ajst-29293	44	34	of	of	ADP
ajst-29293	44	35	approximately	approximately	ADV
ajst-29293	44	36	2.76	2.76	NUM
ajst-29293	44	37	%	%	NOUN
ajst-29293	44	38	.	.	PUNCT
ajst-29293	45	1	the	the	DET
ajst-29293	45	2	probability	probability	NOUN
ajst-29293	45	3	density	density	NOUN
ajst-29293	45	4	function	function	NOUN
ajst-29293	45	5	curves	curve	NOUN
ajst-29293	45	6	for	for	ADP
ajst-29293	45	7	the	the	DET
ajst-29293	45	8	connection	connection	NOUN
ajst-29293	45	9	and	and	CCONJ
ajst-29293	45	10	disconnection	disconnection	NOUN
ajst-29293	45	11	times	time	NOUN
ajst-29293	45	12	of	of	ADP
ajst-29293	45	13	evs	evs	PROPN
ajst-29293	45	14	align	align	VERB
ajst-29293	45	15	perfectly	perfectly	ADV
ajst-29293	45	16	with	with	ADP
ajst-29293	45	17	the	the	DET
ajst-29293	45	18	statistical	statistical	ADJ
ajst-29293	45	19	patterns	pattern	NOUN
ajst-29293	45	20	reported	report	VERB
ajst-29293	45	21	in	in	ADP
ajst-29293	45	22	the	the	DET
ajst-29293	45	23	"	"	PUNCT
ajst-29293	45	24	big	big	ADJ
ajst-29293	45	25	data	datum	NOUN
ajst-29293	45	26	report	report	NOUN
ajst-29293	45	27	on	on	ADP
ajst-29293	45	28	the	the	DET
ajst-29293	45	29	travel	travel	NOUN
ajst-29293	45	30	of	of	ADP
ajst-29293	45	31	small	small	ADJ
ajst-29293	45	32	pure	pure	ADJ
ajst-29293	45	33	electric	electric	ADJ
ajst-29293	45	34	passenger	passenger	NOUN
ajst-29293	45	35	cars	car	NOUN
ajst-29293	45	36	in	in	ADP
ajst-29293	45	37	china	china	PROPN
ajst-29293	45	38	.	.	PUNCT
ajst-29293	45	39	"	"	PUNCT
ajst-29293	46	1	3.2	3.2	NUM
ajst-29293	46	2	.	.	PUNCT
ajst-29293	46	3	simulation	simulation	NOUN
ajst-29293	46	4	of	of	ADP
ajst-29293	46	5	electric	electric	ADJ
ajst-29293	46	6	vehicle	vehicle	NOUN
ajst-29293	46	7	charging	charge	VERB
ajst-29293	46	8	behavior	behavior	NOUN
ajst-29293	46	9	the	the	DET
ajst-29293	46	10	monte	monte	PROPN
ajst-29293	46	11	carlo	carlo	PROPN
ajst-29293	46	12	algorithm	algorithm	PROPN
ajst-29293	46	13	is	be	AUX
ajst-29293	46	14	widely	widely	ADV
ajst-29293	46	15	used	use	VERB
ajst-29293	46	16	in	in	ADP
ajst-29293	46	17	research	research	NOUN
ajst-29293	46	18	fields	field	NOUN
ajst-29293	46	19	such	such	ADJ
ajst-29293	46	20	as	as	ADP
ajst-29293	46	21	power	power	NOUN
ajst-29293	46	22	prediction	prediction	NOUN
ajst-29293	46	23	for	for	ADP
ajst-29293	46	24	electric	electric	ADJ
ajst-29293	46	25	vehicles	vehicle	NOUN
ajst-29293	46	26	[	[	X
ajst-29293	46	27	6].in	6].in	ADP
ajst-29293	46	28	the	the	DET
ajst-29293	46	29	previous	previous	ADJ
ajst-29293	46	30	section	section	NOUN
ajst-29293	46	31	,	,	PUNCT
ajst-29293	46	32	the	the	DET
ajst-29293	46	33	probability	probability	NOUN
ajst-29293	46	34	density	density	NOUN
ajst-29293	46	35	functions	function	NOUN
ajst-29293	46	36	for	for	ADP
ajst-29293	46	37	ev	ev	INTJ
ajst-29293	46	38	charging	charge	VERB
ajst-29293	46	39	connection	connection	NOUN
ajst-29293	46	40	and	and	CCONJ
ajst-29293	46	41	disconnection	disconnection	NOUN
ajst-29293	46	42	times	time	NOUN
ajst-29293	46	43	,	,	PUNCT
ajst-29293	46	44	which	which	PRON
ajst-29293	46	45	exhibit	exhibit	VERB
ajst-29293	46	46	general	general	ADJ
ajst-29293	46	47	regularities	regularity	NOUN
ajst-29293	46	48	,	,	PUNCT
ajst-29293	46	49	were	be	AUX
ajst-29293	46	50	fitted	fit	VERB
ajst-29293	46	51	.	.	PUNCT
ajst-29293	47	1	using	use	VERB
ajst-29293	47	2	these	these	DET
ajst-29293	47	3	pdfs	pdfs	NOUN
ajst-29293	47	4	,	,	PUNCT
ajst-29293	47	5	the	the	DET
ajst-29293	47	6	monte	monte	PROPN
ajst-29293	47	7	carlo	carlo	PROPN
ajst-29293	47	8	simulation	simulation	PROPN
ajst-29293	47	9	method	method	NOUN
ajst-29293	47	10	can	can	AUX
ajst-29293	47	11	generate	generate	VERB
ajst-29293	47	12	time	time	NOUN
ajst-29293	47	13	data	datum	NOUN
ajst-29293	47	14	for	for	ADP
ajst-29293	47	15	ev	ev	NOUN
ajst-29293	47	16	connection	connection	NOUN
ajst-29293	47	17	and	and	CCONJ
ajst-29293	47	18	disconnection	disconnection	NOUN
ajst-29293	47	19	that	that	PRON
ajst-29293	47	20	satisfy	satisfy	VERB
ajst-29293	47	21	the	the	DET
ajst-29293	47	22	given	give	VERB
ajst-29293	47	23	probability	probability	NOUN
ajst-29293	47	24	distributions	distribution	NOUN
ajst-29293	47	25	.	.	PUNCT
ajst-29293	48	1	using	use	VERB
ajst-29293	48	2	this	this	DET
ajst-29293	48	3	method	method	NOUN
ajst-29293	48	4	,	,	PUNCT
ajst-29293	48	5	10,000	10,000	NUM
ajst-29293	48	6	sets	set	NOUN
ajst-29293	48	7	of	of	ADP
ajst-29293	48	8	ev	ev	PRON
ajst-29293	48	9	connection	connection	NOUN
ajst-29293	48	10	and	and	CCONJ
ajst-29293	48	11	disconnection	disconnection	NOUN
ajst-29293	48	12	time	time	NOUN
ajst-29293	48	13	data	datum	NOUN
ajst-29293	48	14	were	be	AUX
ajst-29293	48	15	simulated	simulate	VERB
ajst-29293	48	16	,	,	PUNCT
ajst-29293	48	17	and	and	CCONJ
ajst-29293	48	18	the	the	DET
ajst-29293	48	19	distribution	distribution	NOUN
ajst-29293	48	20	results	result	NOUN
ajst-29293	48	21	are	be	AUX
ajst-29293	48	22	shown	show	VERB
ajst-29293	48	23	in	in	ADP
ajst-29293	48	24	fig	fig	NOUN
ajst-29293	48	25	.	.	PUNCT
ajst-29293	49	1	3	3	NUM
ajst-29293	49	2	.	.	X
ajst-29293	49	3	92	92	NUM
ajst-29293	49	4	fig	fig	NOUN
ajst-29293	49	5	.	.	PUNCT
ajst-29293	50	1	3	3	NUM
ajst-29293	50	2	includes	include	VERB
ajst-29293	50	3	the	the	DET
ajst-29293	50	4	connection	connection	NOUN
ajst-29293	50	5	and	and	CCONJ
ajst-29293	50	6	disconnection	disconnection	NOUN
ajst-29293	50	7	time	time	NOUN
ajst-29293	50	8	data	datum	NOUN
ajst-29293	50	9	of	of	ADP
ajst-29293	50	10	10,000	10,000	NUM
ajst-29293	50	11	evs	evs	NOUN
ajst-29293	50	12	.	.	PUNCT
ajst-29293	51	1	the	the	DET
ajst-29293	51	2	data	data	NOUN
ajst-29293	51	3	points	point	NOUN
ajst-29293	51	4	are	be	AUX
ajst-29293	51	5	most	most	ADV
ajst-29293	51	6	densely	densely	ADV
ajst-29293	51	7	distributed	distribute	VERB
ajst-29293	51	8	in	in	ADP
ajst-29293	51	9	the	the	DET
ajst-29293	51	10	time	time	NOUN
ajst-29293	51	11	intervals	interval	NOUN
ajst-29293	51	12	of	of	ADP
ajst-29293	51	13	16:00	16:00	NUM
ajst-29293	51	14	to	to	ADP
ajst-29293	51	15	21:00	21:00	NUM
ajst-29293	51	16	for	for	ADP
ajst-29293	51	17	connection	connection	NOUN
ajst-29293	51	18	and	and	CCONJ
ajst-29293	51	19	6:00	6:00	NUM
ajst-29293	51	20	to	to	ADP
ajst-29293	51	21	9:00	9:00	NUM
ajst-29293	51	22	for	for	ADP
ajst-29293	51	23	disconnection	disconnection	NOUN
ajst-29293	51	24	,	,	PUNCT
ajst-29293	51	25	indicating	indicate	VERB
ajst-29293	51	26	that	that	SCONJ
ajst-29293	51	27	most	most	ADJ
ajst-29293	51	28	vehicles	vehicle	NOUN
ajst-29293	51	29	are	be	AUX
ajst-29293	51	30	online	online	ADJ
ajst-29293	51	31	during	during	ADP
ajst-29293	51	32	these	these	DET
ajst-29293	51	33	periods	period	NOUN
ajst-29293	51	34	.	.	PUNCT
ajst-29293	52	1	the	the	DET
ajst-29293	52	2	sparse	sparse	ADJ
ajst-29293	52	3	data	datum	NOUN
ajst-29293	52	4	points	point	NOUN
ajst-29293	52	5	in	in	ADP
ajst-29293	52	6	the	the	DET
ajst-29293	52	7	upper	upper	ADV
ajst-29293	52	8	-	-	PUNCT
ajst-29293	52	9	left	left	ADJ
ajst-29293	52	10	corner	corner	NOUN
ajst-29293	52	11	of	of	ADP
ajst-29293	52	12	the	the	DET
ajst-29293	52	13	figure	figure	NOUN
ajst-29293	52	14	suggest	suggest	VERB
ajst-29293	52	15	that	that	SCONJ
ajst-29293	52	16	few	few	ADJ
ajst-29293	52	17	vehicles	vehicle	NOUN
ajst-29293	52	18	connect	connect	VERB
ajst-29293	52	19	to	to	ADP
ajst-29293	52	20	the	the	DET
ajst-29293	52	21	grid	grid	NOUN
ajst-29293	52	22	between	between	ADP
ajst-29293	52	23	0:00	0:00	PROPN
ajst-29293	52	24	and	and	CCONJ
ajst-29293	52	25	12:00	12:00	NUM
ajst-29293	52	26	and	and	CCONJ
ajst-29293	52	27	disconnect	disconnect	NOUN
ajst-29293	52	28	between	between	ADP
ajst-29293	52	29	16:00	16:00	NUM
ajst-29293	52	30	and	and	CCONJ
ajst-29293	52	31	24:00	24:00	NUM
ajst-29293	52	32	,	,	PUNCT
ajst-29293	52	33	which	which	PRON
ajst-29293	52	34	aligns	align	VERB
ajst-29293	52	35	with	with	ADP
ajst-29293	52	36	the	the	DET
ajst-29293	52	37	statistical	statistical	ADJ
ajst-29293	52	38	patterns	pattern	NOUN
ajst-29293	52	39	reported	report	VERB
ajst-29293	52	40	in	in	ADP
ajst-29293	52	41	the	the	DET
ajst-29293	52	42	"	"	PUNCT
ajst-29293	52	43	big	big	ADJ
ajst-29293	52	44	data	datum	NOUN
ajst-29293	52	45	report	report	NOUN
ajst-29293	52	46	on	on	ADP
ajst-29293	52	47	the	the	DET
ajst-29293	52	48	travel	travel	NOUN
ajst-29293	52	49	of	of	ADP
ajst-29293	52	50	small	small	ADJ
ajst-29293	52	51	pure	pure	ADJ
ajst-29293	52	52	electric	electric	ADJ
ajst-29293	52	53	passenger	passenger	NOUN
ajst-29293	52	54	cars	car	NOUN
ajst-29293	52	55	in	in	ADP
ajst-29293	52	56	china	china	PROPN
ajst-29293	52	57	"	"	PUNCT
ajst-29293	52	58	.	.	PUNCT
ajst-29293	53	1	the	the	DET
ajst-29293	53	2	data	datum	NOUN
ajst-29293	53	3	generated	generate	VERB
ajst-29293	53	4	by	by	ADP
ajst-29293	53	5	this	this	DET
ajst-29293	53	6	model	model	NOUN
ajst-29293	53	7	adheres	adhere	VERB
ajst-29293	53	8	to	to	ADP
ajst-29293	53	9	the	the	DET
ajst-29293	53	10	general	general	ADJ
ajst-29293	53	11	rules	rule	NOUN
ajst-29293	53	12	of	of	ADP
ajst-29293	53	13	vehicle	vehicle	NOUN
ajst-29293	53	14	charging	charge	VERB
ajst-29293	53	15	behavior	behavior	NOUN
ajst-29293	53	16	.	.	PUNCT
ajst-29293	54	1	figure	figure	VERB
ajst-29293	54	2	3	3	NUM
ajst-29293	54	3	.	.	PUNCT
ajst-29293	55	1	monte	monte	PROPN
ajst-29293	55	2	carlo	carlo	PROPN
ajst-29293	55	3	simulation	simulation	PROPN
ajst-29293	55	4	for	for	ADP
ajst-29293	55	5	10,000	10,000	NUM
ajst-29293	55	6	evs	evs	NOUN
ajst-29293	55	7	3.3	3.3	NUM
ajst-29293	55	8	.	.	PUNCT
ajst-29293	56	1	clustering	cluster	VERB
ajst-29293	56	2	process	process	NOUN
ajst-29293	56	3	of	of	ADP
ajst-29293	56	4	electric	electric	ADJ
ajst-29293	56	5	vehicle	vehicle	NOUN
ajst-29293	56	6	groups	group	NOUN
ajst-29293	56	7	based	base	VERB
ajst-29293	56	8	on	on	ADP
ajst-29293	56	9	the	the	DET
ajst-29293	56	10	mvabc	mvabc	PROPN
ajst-29293	56	11	-	-	PUNCT
ajst-29293	56	12	gmm	gmm	NOUN
ajst-29293	56	13	algorithm	algorithm	NOUN
ajst-29293	56	14	based	base	VERB
ajst-29293	56	15	on	on	ADP
ajst-29293	56	16	the	the	DET
ajst-29293	56	17	simulation	simulation	NOUN
ajst-29293	56	18	using	use	VERB
ajst-29293	56	19	the	the	DET
ajst-29293	56	20	monte	monte	PROPN
ajst-29293	56	21	carlo	carlo	PROPN
ajst-29293	56	22	method	method	NOUN
ajst-29293	56	23	,	,	PUNCT
ajst-29293	56	24	data	datum	NOUN
ajst-29293	56	25	reflecting	reflect	VERB
ajst-29293	56	26	the	the	DET
ajst-29293	56	27	general	general	ADJ
ajst-29293	56	28	patterns	pattern	NOUN
ajst-29293	56	29	of	of	ADP
ajst-29293	56	30	electric	electric	ADJ
ajst-29293	56	31	vehicle	vehicle	NOUN
ajst-29293	56	32	(	(	PUNCT
ajst-29293	56	33	ev	ev	INTJ
ajst-29293	56	34	)	)	PUNCT
ajst-29293	56	35	charging	charge	VERB
ajst-29293	56	36	behavior	behavior	NOUN
ajst-29293	56	37	were	be	AUX
ajst-29293	56	38	obtained	obtain	VERB
ajst-29293	56	39	.	.	PUNCT
ajst-29293	57	1	this	this	DET
ajst-29293	57	2	data	data	NOUN
ajst-29293	57	3	consists	consist	VERB
ajst-29293	57	4	of	of	ADP
ajst-29293	57	5	a	a	DET
ajst-29293	57	6	twodimensional	twodimensional	ADJ
ajst-29293	57	7	dataset	dataset	NOUN
ajst-29293	57	8	of	of	ADP
ajst-29293	57	9	ev	ev	INTJ
ajst-29293	57	10	connection	connection	NOUN
ajst-29293	57	11	and	and	CCONJ
ajst-29293	57	12	disconnection	disconnection	NOUN
ajst-29293	57	13	times	time	NOUN
ajst-29293	57	14	.	.	PUNCT
ajst-29293	58	1	to	to	PART
ajst-29293	58	2	perform	perform	VERB
ajst-29293	58	3	a	a	DET
ajst-29293	58	4	more	more	ADV
ajst-29293	58	5	precise	precise	ADJ
ajst-29293	58	6	clustering	clustering	NOUN
ajst-29293	58	7	of	of	ADP
ajst-29293	58	8	evs	evs	NOUN
ajst-29293	58	9	with	with	ADP
ajst-29293	58	10	similar	similar	ADJ
ajst-29293	58	11	grid	grid	NOUN
ajst-29293	58	12	connection	connection	NOUN
ajst-29293	58	13	periods	period	NOUN
ajst-29293	58	14	,	,	PUNCT
ajst-29293	58	15	the	the	DET
ajst-29293	58	16	mvabc	mvabc	PROPN
ajst-29293	58	17	-	-	PUNCT
ajst-29293	58	18	gmm	gmm	NOUN
ajst-29293	58	19	algorithm	algorithm	NOUN
ajst-29293	58	20	is	be	AUX
ajst-29293	58	21	used	use	VERB
ajst-29293	58	22	for	for	ADP
ajst-29293	58	23	clustering	cluster	VERB
ajst-29293	58	24	the	the	DET
ajst-29293	58	25	ev	ev	NOUN
ajst-29293	58	26	charging	charge	VERB
ajst-29293	58	27	behavior	behavior	NOUN
ajst-29293	58	28	.	.	PUNCT
ajst-29293	59	1	this	this	DET
ajst-29293	59	2	algorithm	algorithm	NOUN
ajst-29293	59	3	combines	combine	VERB
ajst-29293	59	4	the	the	DET
ajst-29293	59	5	minimum	minimum	ADJ
ajst-29293	59	6	variance	variance	NOUN
ajst-29293	59	7	theory	theory	NOUN
ajst-29293	59	8	with	with	ADP
ajst-29293	59	9	the	the	DET
ajst-29293	59	10	global	global	ADJ
ajst-29293	59	11	search	search	NOUN
ajst-29293	59	12	capability	capability	NOUN
ajst-29293	59	13	of	of	ADP
ajst-29293	59	14	the	the	DET
ajst-29293	59	15	artificial	artificial	ADJ
ajst-29293	59	16	bee	bee	NOUN
ajst-29293	59	17	colony	colony	NOUN
ajst-29293	59	18	(	(	PUNCT
ajst-29293	59	19	abc	abc	PROPN
ajst-29293	59	20	)	)	PUNCT
ajst-29293	59	21	algorithm	algorithm	NOUN
ajst-29293	59	22	,	,	PUNCT
ajst-29293	59	23	addressing	address	VERB
ajst-29293	59	24	the	the	DET
ajst-29293	59	25	issues	issue	NOUN
ajst-29293	59	26	in	in	ADP
ajst-29293	59	27	the	the	DET
ajst-29293	59	28	expectationmaximization	expectationmaximization	NOUN
ajst-29293	59	29	(	(	PUNCT
ajst-29293	59	30	em	em	NOUN
ajst-29293	59	31	)	)	PUNCT
ajst-29293	59	32	algorithm	algorithm	NOUN
ajst-29293	59	33	of	of	ADP
ajst-29293	59	34	gaussian	gaussian	ADJ
ajst-29293	59	35	mixture	mixture	NOUN
ajst-29293	59	36	models	model	NOUN
ajst-29293	59	37	(	(	PUNCT
ajst-29293	59	38	gmm	gmm	NOUN
ajst-29293	59	39	)	)	PUNCT
ajst-29293	59	40	,	,	PUNCT
ajst-29293	59	41	such	such	ADJ
ajst-29293	59	42	as	as	ADP
ajst-29293	59	43	sensitivity	sensitivity	NOUN
ajst-29293	59	44	to	to	ADP
ajst-29293	59	45	initial	initial	ADJ
ajst-29293	59	46	parameters	parameter	NOUN
ajst-29293	59	47	and	and	CCONJ
ajst-29293	59	48	susceptibility	susceptibility	NOUN
ajst-29293	59	49	to	to	ADP
ajst-29293	59	50	local	local	ADJ
ajst-29293	59	51	optima	optima	NOUN
ajst-29293	59	52	.	.	PUNCT
ajst-29293	60	1	this	this	PRON
ajst-29293	60	2	ultimately	ultimately	ADV
ajst-29293	60	3	enables	enable	VERB
ajst-29293	60	4	accurate	accurate	ADJ
ajst-29293	60	5	clustering	clustering	NOUN
ajst-29293	60	6	of	of	ADP
ajst-29293	60	7	ev	ev	ADP
ajst-29293	60	8	charging	charge	VERB
ajst-29293	60	9	behavior	behavior	NOUN
ajst-29293	60	10	.	.	PUNCT
ajst-29293	61	1	the	the	DET
ajst-29293	61	2	algorithm	algorithm	NOUN
ajst-29293	61	3	flow	flow	NOUN
ajst-29293	61	4	is	be	AUX
ajst-29293	61	5	shown	show	VERB
ajst-29293	61	6	in	in	ADP
ajst-29293	61	7	fig	fig	NOUN
ajst-29293	61	8	.	.	PUNCT
ajst-29293	62	1	4	4	X
ajst-29293	62	2	.	.	X
ajst-29293	62	3	figure	figure	VERB
ajst-29293	62	4	4	4	NUM
ajst-29293	62	5	.	.	PUNCT
ajst-29293	63	1	flowchart	flowchart	NOUN
ajst-29293	63	2	of	of	ADP
ajst-29293	63	3	clustering	clustering	NOUN
ajst-29293	63	4	based	base	VERB
ajst-29293	63	5	on	on	ADP
ajst-29293	63	6	the	the	DET
ajst-29293	63	7	improved	improved	ADJ
ajst-29293	63	8	gaussian	gaussian	ADJ
ajst-29293	63	9	mixture	mixture	NOUN
ajst-29293	63	10	model	model	NOUN
ajst-29293	63	11	93	93	NUM
ajst-29293	63	12	3.4	3.4	NUM
ajst-29293	63	13	.	.	PUNCT
ajst-29293	64	1	experimental	experimental	ADJ
ajst-29293	64	2	analysis	analysis	NOUN
ajst-29293	64	3	the	the	DET
ajst-29293	64	4	mvabc	mvabc	PROPN
ajst-29293	64	5	-	-	PUNCT
ajst-29293	64	6	gmm	gmm	NOUN
ajst-29293	64	7	algorithm	algorithm	NOUN
ajst-29293	64	8	is	be	AUX
ajst-29293	64	9	used	use	VERB
ajst-29293	64	10	to	to	PART
ajst-29293	64	11	perform	perform	VERB
ajst-29293	64	12	clustering	cluster	VERB
ajst-29293	64	13	analysis	analysis	NOUN
ajst-29293	64	14	on	on	ADP
ajst-29293	64	15	the	the	DET
ajst-29293	64	16	10,000	10,000	NUM
ajst-29293	64	17	sets	set	NOUN
ajst-29293	64	18	of	of	ADP
ajst-29293	64	19	electric	electric	ADJ
ajst-29293	64	20	vehicle	vehicle	NOUN
ajst-29293	64	21	(	(	PUNCT
ajst-29293	64	22	ev	ev	NOUN
ajst-29293	64	23	)	)	PUNCT
ajst-29293	64	24	charging	charge	VERB
ajst-29293	64	25	connections	connection	NOUN
ajst-29293	64	26	and	and	CCONJ
ajst-29293	64	27	disconnection	disconnection	NOUN
ajst-29293	64	28	time	time	NOUN
ajst-29293	64	29	data	datum	NOUN
ajst-29293	64	30	generated	generate	VERB
ajst-29293	64	31	through	through	ADP
ajst-29293	64	32	the	the	DET
ajst-29293	64	33	monte	monte	PROPN
ajst-29293	64	34	carlo	carlo	PROPN
ajst-29293	64	35	method	method	NOUN
ajst-29293	64	36	.	.	PUNCT
ajst-29293	65	1	the	the	DET
ajst-29293	65	2	control	control	NOUN
ajst-29293	65	3	parameters	parameter	NOUN
ajst-29293	65	4	,	,	PUNCT
ajst-29293	65	5	including	include	VERB
ajst-29293	65	6	the	the	DET
ajst-29293	65	7	number	number	NOUN
ajst-29293	65	8	of	of	ADP
ajst-29293	65	9	scout	scout	NOUN
ajst-29293	65	10	bees	bee	NOUN
ajst-29293	65	11	,	,	PUNCT
ajst-29293	65	12	follower	follower	NOUN
ajst-29293	65	13	bees	bee	NOUN
ajst-29293	65	14	,	,	PUNCT
ajst-29293	65	15	and	and	CCONJ
ajst-29293	65	16	worker	worker	NOUN
ajst-29293	65	17	bees	bee	NOUN
ajst-29293	65	18	,	,	PUNCT
ajst-29293	65	19	are	be	AUX
ajst-29293	65	20	all	all	ADV
ajst-29293	65	21	set	set	VERB
ajst-29293	65	22	to	to	ADP
ajst-29293	65	23	14	14	NUM
ajst-29293	65	24	.	.	PUNCT
ajst-29293	66	1	the	the	DET
ajst-29293	66	2	bee	bee	PROPN
ajst-29293	66	3	colony	colony	NOUN
ajst-29293	66	4	algorithm	algorithm	NOUN
ajst-29293	66	5	performs	perform	VERB
ajst-29293	66	6	5	5	NUM
ajst-29293	66	7	iterations	iteration	NOUN
ajst-29293	66	8	,	,	PUNCT
ajst-29293	66	9	with	with	SCONJ
ajst-29293	66	10	the	the	DET
ajst-29293	66	11	convergence	convergence	NOUN
ajst-29293	66	12	condition	condition	NOUN
ajst-29293	66	13	set	set	VERB
ajst-29293	66	14	to	to	ADP
ajst-29293	66	15	a	a	DET
ajst-29293	66	16	maximum	maximum	NOUN
ajst-29293	66	17	of	of	ADP
ajst-29293	66	18	100	100	NUM
ajst-29293	66	19	iterations	iteration	NOUN
ajst-29293	66	20	.	.	PUNCT
ajst-29293	67	1	the	the	DET
ajst-29293	67	2	number	number	NOUN
ajst-29293	67	3	of	of	ADP
ajst-29293	67	4	clusters	cluster	NOUN
ajst-29293	67	5	is	be	AUX
ajst-29293	67	6	also	also	ADV
ajst-29293	67	7	defined	define	VERB
ajst-29293	67	8	.	.	PUNCT
ajst-29293	68	1	the	the	DET
ajst-29293	68	2	clustering	clustering	NOUN
ajst-29293	68	3	and	and	CCONJ
ajst-29293	68	4	iteration	iteration	NOUN
ajst-29293	68	5	processes	process	NOUN
ajst-29293	68	6	are	be	AUX
ajst-29293	68	7	shown	show	VERB
ajst-29293	68	8	in	in	ADP
ajst-29293	68	9	fig	fig	NOUN
ajst-29293	68	10	.	.	PUNCT
ajst-29293	69	1	5(a	5(a	NUM
ajst-29293	69	2	)	)	PUNCT
ajst-29293	69	3	and	and	CCONJ
ajst-29293	69	4	fig	fig	NOUN
ajst-29293	69	5	.	.	PUNCT
ajst-29293	70	1	6(a	6(a	NUM
ajst-29293	70	2	)	)	PUNCT
ajst-29293	70	3	.	.	PUNCT
ajst-29293	71	1	in	in	ADP
ajst-29293	71	2	article	article	NOUN
ajst-29293	71	3	[	[	X
ajst-29293	71	4	7	7	NUM
ajst-29293	71	5	]	]	PUNCT
ajst-29293	71	6	,	,	PUNCT
ajst-29293	71	7	a	a	DET
ajst-29293	71	8	simple	simple	ADJ
ajst-29293	71	9	and	and	CCONJ
ajst-29293	71	10	efficient	efficient	ADJ
ajst-29293	71	11	k	k	ADJ
ajst-29293	71	12	-	-	PUNCT
ajst-29293	71	13	means	means	NOUN
ajst-29293	71	14	algorithm	algorithm	NOUN
ajst-29293	71	15	is	be	AUX
ajst-29293	71	16	used	use	VERB
ajst-29293	71	17	to	to	PART
ajst-29293	71	18	optimize	optimize	VERB
ajst-29293	71	19	the	the	DET
ajst-29293	71	20	initial	initial	ADJ
ajst-29293	71	21	clustering	clustering	ADJ
ajst-29293	71	22	centers	center	NOUN
ajst-29293	71	23	for	for	ADP
ajst-29293	71	24	gmm	gmm	NOUN
ajst-29293	71	25	clustering	clustering	NOUN
ajst-29293	71	26	,	,	PUNCT
ajst-29293	71	27	which	which	PRON
ajst-29293	71	28	provides	provide	VERB
ajst-29293	71	29	a	a	DET
ajst-29293	71	30	good	good	ADJ
ajst-29293	71	31	comparative	comparative	ADJ
ajst-29293	71	32	basis	basis	NOUN
ajst-29293	71	33	.	.	PUNCT
ajst-29293	72	1	based	base	VERB
ajst-29293	72	2	on	on	ADP
ajst-29293	72	3	the	the	DET
ajst-29293	72	4	kmeans	kmeans	PROPN
ajst-29293	72	5	-	-	PUNCT
ajst-29293	72	6	gmm	gmm	NOUN
ajst-29293	72	7	algorithm	algorithm	NOUN
ajst-29293	72	8	,	,	PUNCT
ajst-29293	72	9	clustering	cluster	VERB
ajst-29293	72	10	analysis	analysis	NOUN
ajst-29293	72	11	is	be	AUX
ajst-29293	72	12	also	also	ADV
ajst-29293	72	13	performed	perform	VERB
ajst-29293	72	14	on	on	ADP
ajst-29293	72	15	the	the	DET
ajst-29293	72	16	10,000	10,000	NUM
ajst-29293	72	17	sets	set	NOUN
ajst-29293	72	18	of	of	ADP
ajst-29293	72	19	ev	ev	ADP
ajst-29293	72	20	charging	charge	VERB
ajst-29293	72	21	connection	connection	NOUN
ajst-29293	72	22	and	and	CCONJ
ajst-29293	72	23	disconnection	disconnection	NOUN
ajst-29293	72	24	time	time	NOUN
ajst-29293	72	25	behavior	behavior	NOUN
ajst-29293	72	26	data	datum	NOUN
ajst-29293	72	27	generated	generate	VERB
ajst-29293	72	28	through	through	ADP
ajst-29293	72	29	the	the	DET
ajst-29293	72	30	monte	monte	PROPN
ajst-29293	72	31	carlo	carlo	PROPN
ajst-29293	72	32	method	method	NOUN
ajst-29293	72	33	.	.	PUNCT
ajst-29293	73	1	the	the	DET
ajst-29293	73	2	number	number	NOUN
ajst-29293	73	3	of	of	ADP
ajst-29293	73	4	clusters	cluster	NOUN
ajst-29293	73	5	is	be	AUX
ajst-29293	73	6	set	set	VERB
ajst-29293	73	7	,	,	PUNCT
ajst-29293	73	8	with	with	ADP
ajst-29293	73	9	a	a	DET
ajst-29293	73	10	maximum	maximum	NOUN
ajst-29293	73	11	of	of	ADP
ajst-29293	73	12	100	100	NUM
ajst-29293	73	13	iterations	iteration	NOUN
ajst-29293	73	14	.	.	PUNCT
ajst-29293	74	1	the	the	DET
ajst-29293	74	2	initial	initial	ADJ
ajst-29293	74	3	clustering	clustering	ADJ
ajst-29293	74	4	centers	center	NOUN
ajst-29293	74	5	are	be	AUX
ajst-29293	74	6	randomly	randomly	ADV
ajst-29293	74	7	selected	select	VERB
ajst-29293	74	8	from	from	ADP
ajst-29293	74	9	6	6	NUM
ajst-29293	74	10	data	datum	NOUN
ajst-29293	74	11	points	point	NOUN
ajst-29293	74	12	in	in	ADP
ajst-29293	74	13	the	the	DET
ajst-29293	74	14	dataset	dataset	NOUN
ajst-29293	74	15	.	.	PUNCT
ajst-29293	75	1	the	the	DET
ajst-29293	75	2	final	final	ADJ
ajst-29293	75	3	clustering	clustering	NOUN
ajst-29293	75	4	results	result	NOUN
ajst-29293	75	5	and	and	CCONJ
ajst-29293	75	6	iteration	iteration	NOUN
ajst-29293	75	7	processes	process	NOUN
ajst-29293	75	8	are	be	AUX
ajst-29293	75	9	shown	show	VERB
ajst-29293	75	10	in	in	ADP
ajst-29293	75	11	fig	fig	NOUN
ajst-29293	75	12	.	.	PUNCT
ajst-29293	76	1	5(b	5(b	NUM
ajst-29293	76	2	)	)	PUNCT
ajst-29293	76	3	and	and	CCONJ
ajst-29293	76	4	fig	fig	NOUN
ajst-29293	76	5	.	.	PUNCT
ajst-29293	77	1	6(b	6(b	NUM
ajst-29293	77	2	)	)	PUNCT
ajst-29293	77	3	.	.	PUNCT
ajst-29293	78	1	(	(	PUNCT
ajst-29293	78	2	a	a	X
ajst-29293	78	3	)	)	PUNCT
ajst-29293	78	4	(	(	PUNCT
ajst-29293	78	5	b	b	X
ajst-29293	78	6	)	)	PUNCT
ajst-29293	78	7	figure	figure	NOUN
ajst-29293	78	8	5	5	NUM
ajst-29293	78	9	.	.	PUNCT
ajst-29293	78	10	clustering	cluster	VERB
ajst-29293	78	11	effect	effect	NOUN
ajst-29293	78	12	comparison	comparison	NOUN
ajst-29293	78	13	(	(	PUNCT
ajst-29293	78	14	a	a	NOUN
ajst-29293	78	15	)	)	PUNCT
ajst-29293	78	16	(	(	PUNCT
ajst-29293	78	17	b	b	X
ajst-29293	78	18	)	)	PUNCT
ajst-29293	78	19	figure	figure	NOUN
ajst-29293	78	20	6	6	NUM
ajst-29293	78	21	.	.	PUNCT
ajst-29293	78	22	iteration	iteration	NOUN
ajst-29293	78	23	process	process	NOUN
ajst-29293	78	24	comparison	comparison	NOUN
ajst-29293	78	25	comparison	comparison	NOUN
ajst-29293	78	26	of	of	ADP
ajst-29293	78	27	the	the	DET
ajst-29293	78	28	two	two	NUM
ajst-29293	78	29	algorithms	algorithm	NOUN
ajst-29293	78	30	:	:	PUNCT
ajst-29293	78	31	1	1	X
ajst-29293	78	32	.	.	X
ajst-29293	78	33	convergence	convergence	NOUN
ajst-29293	78	34	of	of	ADP
ajst-29293	78	35	fitness	fitness	PROPN
ajst-29293	78	36	comparison	comparison	NOUN
ajst-29293	78	37	:	:	PUNCT
ajst-29293	78	38	the	the	DET
ajst-29293	78	39	clustering	clustering	ADJ
ajst-29293	78	40	process	process	NOUN
ajst-29293	78	41	of	of	ADP
ajst-29293	78	42	the	the	DET
ajst-29293	78	43	kmeans	kmeans	PROPN
ajst-29293	78	44	-	-	PUNCT
ajst-29293	78	45	gmm	gmm	PROPN
ajst-29293	78	46	algorithm	algorithm	NOUN
ajst-29293	78	47	relies	rely	VERB
ajst-29293	78	48	heavily	heavily	ADV
ajst-29293	78	49	on	on	ADP
ajst-29293	78	50	the	the	DET
ajst-29293	78	51	randomly	randomly	ADV
ajst-29293	78	52	selected	select	VERB
ajst-29293	78	53	initial	initial	ADJ
ajst-29293	78	54	clustering	clustering	ADJ
ajst-29293	78	55	centers	center	NOUN
ajst-29293	78	56	,	,	PUNCT
ajst-29293	78	57	which	which	PRON
ajst-29293	78	58	causes	cause	VERB
ajst-29293	78	59	significant	significant	ADJ
ajst-29293	78	60	oscillation	oscillation	NOUN
ajst-29293	78	61	in	in	ADP
ajst-29293	78	62	the	the	DET
ajst-29293	78	63	fitness	fitness	NOUN
ajst-29293	78	64	value	value	NOUN
ajst-29293	78	65	during	during	ADP
ajst-29293	78	66	the	the	DET
ajst-29293	78	67	initial	initial	ADJ
ajst-29293	78	68	phase	phase	NOUN
ajst-29293	78	69	,	,	PUNCT
ajst-29293	78	70	slower	slow	ADJ
ajst-29293	78	71	convergence	convergence	NOUN
ajst-29293	78	72	,	,	PUNCT
ajst-29293	78	73	and	and	CCONJ
ajst-29293	78	74	a	a	DET
ajst-29293	78	75	higher	high	ADJ
ajst-29293	78	76	likelihood	likelihood	NOUN
ajst-29293	78	77	of	of	ADP
ajst-29293	78	78	getting	getting	AUX
ajst-29293	78	79	stuck	stick	VERB
ajst-29293	78	80	in	in	ADP
ajst-29293	78	81	local	local	ADJ
ajst-29293	78	82	optima	optima	NOUN
ajst-29293	78	83	.	.	PUNCT
ajst-29293	79	1	as	as	SCONJ
ajst-29293	79	2	shown	show	VERB
ajst-29293	79	3	in	in	ADP
ajst-29293	79	4	fig	fig	NOUN
ajst-29293	79	5	.	.	PUNCT
ajst-29293	80	1	6(b	6(b	NUM
ajst-29293	80	2	)	)	PUNCT
ajst-29293	80	3	,	,	PUNCT
ajst-29293	80	4	the	the	DET
ajst-29293	80	5	kmeansgmm	kmeansgmm	PROPN
ajst-29293	80	6	algorithm	algorithm	NOUN
ajst-29293	80	7	only	only	ADV
ajst-29293	80	8	stabilizes	stabilize	VERB
ajst-29293	80	9	after	after	ADP
ajst-29293	80	10	93	93	NUM
ajst-29293	80	11	iterations	iteration	NOUN
ajst-29293	80	12	,	,	PUNCT
ajst-29293	80	13	with	with	ADP
ajst-29293	80	14	the	the	DET
ajst-29293	80	15	fitness	fitness	NOUN
ajst-29293	80	16	value	value	NOUN
ajst-29293	80	17	gradually	gradually	ADV
ajst-29293	80	18	increasing	increase	VERB
ajst-29293	80	19	through	through	ADP
ajst-29293	80	20	fluctuations	fluctuation	NOUN
ajst-29293	80	21	and	and	CCONJ
ajst-29293	80	22	ultimately	ultimately	ADV
ajst-29293	80	23	reaching	reach	VERB
ajst-29293	80	24	a	a	DET
ajst-29293	80	25	suboptimal	suboptimal	ADJ
ajst-29293	80	26	solution	solution	NOUN
ajst-29293	80	27	.	.	PUNCT
ajst-29293	81	1	in	in	ADP
ajst-29293	81	2	contrast	contrast	NOUN
ajst-29293	81	3	,	,	PUNCT
ajst-29293	81	4	the	the	DET
ajst-29293	81	5	mvabc	mvabc	PROPN
ajst-29293	81	6	-	-	PUNCT
ajst-29293	81	7	gmm	gmm	NOUN
ajst-29293	81	8	algorithm	algorithm	NOUN
ajst-29293	81	9	selects	select	NOUN
ajst-29293	81	10	initial	initial	ADJ
ajst-29293	81	11	clustering	clustering	ADJ
ajst-29293	81	12	centers	center	NOUN
ajst-29293	81	13	based	base	VERB
ajst-29293	81	14	on	on	ADP
ajst-29293	81	15	the	the	DET
ajst-29293	81	16	minimum	minimum	ADJ
ajst-29293	81	17	variance	variance	NOUN
ajst-29293	81	18	theory	theory	NOUN
ajst-29293	81	19	and	and	CCONJ
ajst-29293	81	20	incorporates	incorporate	VERB
ajst-29293	81	21	the	the	DET
ajst-29293	81	22	artificial	artificial	ADJ
ajst-29293	81	23	bee	bee	NOUN
ajst-29293	81	24	colony	colony	NOUN
ajst-29293	81	25	(	(	PUNCT
ajst-29293	81	26	abc	abc	PROPN
ajst-29293	81	27	)	)	PUNCT
ajst-29293	81	28	algorithm	algorithm	NOUN
ajst-29293	81	29	for	for	ADP
ajst-29293	81	30	global	global	ADJ
ajst-29293	81	31	search	search	NOUN
ajst-29293	81	32	and	and	CCONJ
ajst-29293	81	33	local	local	ADJ
ajst-29293	81	34	optimization	optimization	NOUN
ajst-29293	81	35	,	,	PUNCT
ajst-29293	81	36	significantly	significantly	ADV
ajst-29293	81	37	improving	improve	VERB
ajst-29293	81	38	both	both	DET
ajst-29293	81	39	convergence	convergence	NOUN
ajst-29293	81	40	speed	speed	NOUN
ajst-29293	81	41	and	and	CCONJ
ajst-29293	81	42	stability	stability	NOUN
ajst-29293	81	43	.	.	PUNCT
ajst-29293	82	1	as	as	SCONJ
ajst-29293	82	2	shown	show	VERB
ajst-29293	82	3	in	in	ADP
ajst-29293	82	4	fig	fig	NOUN
ajst-29293	82	5	.	.	PUNCT
ajst-29293	83	1	6(a	6(a	NUM
ajst-29293	83	2	)	)	PUNCT
ajst-29293	84	1	,	,	PUNCT
ajst-29293	84	2	the	the	DET
ajst-29293	84	3	mvabc	mvabc	PROPN
ajst-29293	84	4	-	-	PUNCT
ajst-29293	84	5	gmm	gmm	NOUN
ajst-29293	84	6	algorithm	algorithm	NOUN
ajst-29293	84	7	escapes	escape	VERB
ajst-29293	84	8	local	local	ADJ
ajst-29293	84	9	optima	optima	NOUN
ajst-29293	84	10	after	after	ADP
ajst-29293	84	11	just	just	ADV
ajst-29293	84	12	32	32	NUM
ajst-29293	84	13	iterations	iteration	NOUN
ajst-29293	84	14	and	and	CCONJ
ajst-29293	84	15	quickly	quickly	ADV
ajst-29293	84	16	converges	converge	VERB
ajst-29293	84	17	to	to	ADP
ajst-29293	84	18	a	a	DET
ajst-29293	84	19	stable	stable	ADJ
ajst-29293	84	20	state	state	NOUN
ajst-29293	84	21	,	,	PUNCT
ajst-29293	84	22	demonstrating	demonstrate	VERB
ajst-29293	84	23	better	well	ADJ
ajst-29293	84	24	global	global	ADJ
ajst-29293	84	25	search	search	NOUN
ajst-29293	84	26	capability	capability	NOUN
ajst-29293	84	27	and	and	CCONJ
ajst-29293	84	28	optimization	optimization	NOUN
ajst-29293	84	29	efficiency	efficiency	NOUN
ajst-29293	84	30	.	.	PUNCT
ajst-29293	85	1	2	2	X
ajst-29293	85	2	.	.	X
ajst-29293	85	3	clustering	cluster	VERB
ajst-29293	85	4	results	result	NOUN
ajst-29293	85	5	comparison	comparison	NOUN
ajst-29293	85	6	:	:	PUNCT
ajst-29293	85	7	from	from	ADP
ajst-29293	85	8	the	the	DET
ajst-29293	85	9	clustering	clustering	ADJ
ajst-29293	85	10	results	result	NOUN
ajst-29293	85	11	,	,	PUNCT
ajst-29293	85	12	the	the	DET
ajst-29293	85	13	kmeans	kmeans	PROPN
ajst-29293	85	14	-	-	PUNCT
ajst-29293	85	15	gmm	gmm	PROPN
ajst-29293	85	16	algorithm	algorithm	NOUN
ajst-29293	85	17	's	's	PART
ajst-29293	85	18	cluster	cluster	NOUN
ajst-29293	85	19	center	center	NOUN
ajst-29293	85	20	distribution	distribution	NOUN
ajst-29293	85	21	is	be	AUX
ajst-29293	85	22	significantly	significantly	ADV
ajst-29293	85	23	influenced	influence	VERB
ajst-29293	85	24	by	by	ADP
ajst-29293	85	25	the	the	DET
ajst-29293	85	26	initial	initial	ADJ
ajst-29293	85	27	values	value	NOUN
ajst-29293	85	28	,	,	PUNCT
ajst-29293	85	29	leading	lead	VERB
ajst-29293	85	30	to	to	ADP
ajst-29293	85	31	uneven	uneven	ADJ
ajst-29293	85	32	distribution	distribution	NOUN
ajst-29293	85	33	of	of	ADP
ajst-29293	85	34	certain	certain	ADJ
ajst-29293	85	35	categories	category	NOUN
ajst-29293	85	36	of	of	ADP
ajst-29293	85	37	electric	electric	ADJ
ajst-29293	85	38	vehicles	vehicle	NOUN
ajst-29293	85	39	.	.	PUNCT
ajst-29293	86	1	as	as	SCONJ
ajst-29293	86	2	shown	show	VERB
ajst-29293	86	3	in	in	ADP
ajst-29293	86	4	fig	fig	NOUN
ajst-29293	86	5	.	.	PUNCT
ajst-29293	87	1	5(b	5(b	NUM
ajst-29293	87	2	)	)	PUNCT
ajst-29293	87	3	.	.	PUNCT
ajst-29293	88	1	this	this	PRON
ajst-29293	88	2	causes	cause	VERB
ajst-29293	88	3	some	some	DET
ajst-29293	88	4	dense	dense	ADJ
ajst-29293	88	5	points	point	NOUN
ajst-29293	88	6	and	and	CCONJ
ajst-29293	88	7	sparse	sparse	ADJ
ajst-29293	88	8	points	point	NOUN
ajst-29293	88	9	that	that	PRON
ajst-29293	88	10	are	be	AUX
ajst-29293	88	11	far	far	ADV
ajst-29293	88	12	apart	apart	ADV
ajst-29293	88	13	to	to	PART
ajst-29293	88	14	be	be	AUX
ajst-29293	88	15	grouped	group	VERB
ajst-29293	88	16	into	into	ADP
ajst-29293	88	17	the	the	DET
ajst-29293	88	18	same	same	ADJ
ajst-29293	88	19	cluster	cluster	NOUN
ajst-29293	88	20	,	,	PUNCT
ajst-29293	88	21	failing	fail	VERB
ajst-29293	88	22	to	to	PART
ajst-29293	88	23	fully	fully	ADV
ajst-29293	88	24	reflect	reflect	VERB
ajst-29293	88	25	the	the	DET
ajst-29293	88	26	charging	charge	VERB
ajst-29293	88	27	patterns	pattern	NOUN
ajst-29293	88	28	and	and	CCONJ
ajst-29293	88	29	user	user	NOUN
ajst-29293	88	30	habits	habit	NOUN
ajst-29293	88	31	of	of	ADP
ajst-29293	88	32	electric	electric	ADJ
ajst-29293	88	33	vehicles	vehicle	NOUN
ajst-29293	88	34	.	.	PUNCT
ajst-29293	89	1	in	in	ADP
ajst-29293	89	2	contrast	contrast	NOUN
ajst-29293	89	3	,	,	PUNCT
ajst-29293	89	4	the	the	DET
ajst-29293	89	5	mvabcgmm	mvabcgmm	NOUN
ajst-29293	89	6	algorithm	algorithm	NOUN
ajst-29293	89	7	,	,	PUNCT
ajst-29293	89	8	through	through	ADP
ajst-29293	89	9	optimization	optimization	NOUN
ajst-29293	89	10	of	of	ADP
ajst-29293	89	11	the	the	DET
ajst-29293	89	12	initial	initial	ADJ
ajst-29293	89	13	parameters	parameter	NOUN
ajst-29293	89	14	and	and	CCONJ
ajst-29293	89	15	global	global	ADJ
ajst-29293	89	16	search	search	NOUN
ajst-29293	89	17	,	,	PUNCT
ajst-29293	89	18	not	not	PART
ajst-29293	89	19	only	only	ADV
ajst-29293	89	20	ensures	ensure	VERB
ajst-29293	89	21	a	a	DET
ajst-29293	89	22	more	more	ADV
ajst-29293	89	23	even	even	ADJ
ajst-29293	89	24	distribution	distribution	NOUN
ajst-29293	89	25	of	of	ADP
ajst-29293	89	26	the	the	DET
ajst-29293	89	27	cluster	cluster	NOUN
ajst-29293	89	28	centers	center	NOUN
ajst-29293	89	29	in	in	ADP
ajst-29293	89	30	the	the	DET
ajst-29293	89	31	data	data	NOUN
ajst-29293	89	32	space	space	NOUN
ajst-29293	89	33	but	but	CCONJ
ajst-29293	89	34	also	also	ADV
ajst-29293	89	35	effectively	effectively	ADV
ajst-29293	89	36	groups	group	VERB
ajst-29293	89	37	the	the	DET
ajst-29293	89	38	points	point	NOUN
ajst-29293	89	39	that	that	PRON
ajst-29293	89	40	are	be	AUX
ajst-29293	89	41	sparsely	sparsely	ADV
ajst-29293	89	42	distributed	distribute	VERB
ajst-29293	89	43	due	due	ADP
ajst-29293	89	44	to	to	ADP
ajst-29293	89	45	the	the	DET
ajst-29293	89	46	crossing	crossing	NOUN
ajst-29293	89	47	region	region	NOUN
ajst-29293	89	48	into	into	ADP
ajst-29293	89	49	the	the	DET
ajst-29293	89	50	same	same	ADJ
ajst-29293	89	51	category	category	NOUN
ajst-29293	89	52	.	.	PUNCT
ajst-29293	90	1	the	the	DET
ajst-29293	90	2	data	data	NOUN
ajst-29293	90	3	points	point	NOUN
ajst-29293	90	4	within	within	ADP
ajst-29293	90	5	different	different	ADJ
ajst-29293	90	6	categories	category	NOUN
ajst-29293	90	7	are	be	AUX
ajst-29293	90	8	more	more	ADV
ajst-29293	90	9	regularly	regularly	ADV
ajst-29293	90	10	distributed	distribute	VERB
ajst-29293	90	11	,	,	PUNCT
ajst-29293	90	12	allowing	allow	VERB
ajst-29293	90	13	for	for	ADP
ajst-29293	90	14	a	a	DET
ajst-29293	90	15	more	more	ADV
ajst-29293	90	16	accurate	accurate	ADJ
ajst-29293	90	17	reflection	reflection	NOUN
ajst-29293	90	18	of	of	ADP
ajst-29293	90	19	the	the	DET
ajst-29293	90	20	charging	charge	VERB
ajst-29293	90	21	behavior	behavior	NOUN
ajst-29293	90	22	characteristics	characteristic	NOUN
ajst-29293	90	23	of	of	ADP
ajst-29293	90	24	electric	electric	ADJ
ajst-29293	90	25	vehicles	vehicle	NOUN
ajst-29293	90	26	.	.	PUNCT
ajst-29293	91	1	as	as	SCONJ
ajst-29293	91	2	shown	show	VERB
ajst-29293	91	3	in	in	ADP
ajst-29293	91	4	fig	fig	NOUN
ajst-29293	91	5	.	.	PUNCT
ajst-29293	92	1	5(a	5(a	NUM
ajst-29293	92	2	)	)	PUNCT
ajst-29293	92	3	.	.	PUNCT
ajst-29293	93	1	4	4	X
ajst-29293	93	2	.	.	X
ajst-29293	93	3	conclusion	conclusion	NOUN
ajst-29293	93	4	this	this	DET
ajst-29293	93	5	paper	paper	NOUN
ajst-29293	93	6	focuses	focus	VERB
ajst-29293	93	7	on	on	ADP
ajst-29293	93	8	the	the	DET
ajst-29293	93	9	analysis	analysis	NOUN
ajst-29293	93	10	of	of	ADP
ajst-29293	93	11	electric	electric	ADJ
ajst-29293	93	12	vehicle	vehicle	NOUN
ajst-29293	93	13	(	(	PUNCT
ajst-29293	93	14	ev	ev	PROPN
ajst-29293	93	15	)	)	PUNCT
ajst-29293	93	16	94	94	NUM
ajst-29293	93	17	charging	charge	VERB
ajst-29293	93	18	behavior	behavior	NOUN
ajst-29293	93	19	patterns	pattern	NOUN
ajst-29293	93	20	and	and	CCONJ
ajst-29293	93	21	regional	regional	ADJ
ajst-29293	93	22	clustering	clustering	ADJ
ajst-29293	93	23	methods	method	NOUN
ajst-29293	93	24	.	.	PUNCT
ajst-29293	94	1	by	by	ADP
ajst-29293	94	2	combining	combine	VERB
ajst-29293	94	3	probability	probability	NOUN
ajst-29293	94	4	statistics	statistic	NOUN
ajst-29293	94	5	and	and	CCONJ
ajst-29293	94	6	clustering	clustering	ADJ
ajst-29293	94	7	algorithms	algorithm	NOUN
ajst-29293	94	8	,	,	PUNCT
ajst-29293	94	9	a	a	PRON
ajst-29293	94	10	more	more	ADV
ajst-29293	94	11	precise	precise	ADJ
ajst-29293	94	12	and	and	CCONJ
ajst-29293	94	13	efficient	efficient	ADJ
ajst-29293	94	14	ev	ev	ADP
ajst-29293	94	15	charging	charge	VERB
ajst-29293	94	16	behavior	behavior	NOUN
ajst-29293	94	17	simulation	simulation	NOUN
ajst-29293	94	18	and	and	CCONJ
ajst-29293	94	19	clustering	clustering	NOUN
ajst-29293	94	20	method	method	NOUN
ajst-29293	94	21	is	be	AUX
ajst-29293	94	22	proposed	propose	VERB
ajst-29293	94	23	.	.	PUNCT
ajst-29293	95	1	for	for	ADP
ajst-29293	95	2	clustering	cluster	VERB
ajst-29293	95	3	analysis	analysis	NOUN
ajst-29293	95	4	of	of	ADP
ajst-29293	95	5	charging	charge	VERB
ajst-29293	95	6	behavior	behavior	NOUN
ajst-29293	95	7	data	datum	NOUN
ajst-29293	95	8	,	,	PUNCT
ajst-29293	95	9	the	the	DET
ajst-29293	95	10	gmm	gmm	X
ajst-29293	95	11	(	(	PUNCT
ajst-29293	95	12	gaussian	gaussian	ADJ
ajst-29293	95	13	mixture	mixture	NOUN
ajst-29293	95	14	model	model	NOUN
ajst-29293	95	15	)	)	PUNCT
ajst-29293	95	16	algorithm	algorithm	NOUN
ajst-29293	95	17	was	be	AUX
ajst-29293	95	18	selected	select	VERB
ajst-29293	95	19	after	after	ADP
ajst-29293	95	20	comparison	comparison	NOUN
ajst-29293	95	21	,	,	PUNCT
ajst-29293	95	22	as	as	SCONJ
ajst-29293	95	23	it	it	PRON
ajst-29293	95	24	performed	perform	VERB
ajst-29293	95	25	soft	soft	ADJ
ajst-29293	95	26	clustering	clustering	NOUN
ajst-29293	95	27	on	on	ADP
ajst-29293	95	28	ev	ev	INTJ
ajst-29293	95	29	connection	connection	NOUN
ajst-29293	95	30	and	and	CCONJ
ajst-29293	95	31	disconnection	disconnection	NOUN
ajst-29293	95	32	time	time	NOUN
ajst-29293	95	33	data	data	PROPN
ajst-29293	95	34	.	.	PUNCT
ajst-29293	96	1	the	the	DET
ajst-29293	96	2	results	result	NOUN
ajst-29293	96	3	demonstrated	demonstrate	VERB
ajst-29293	96	4	gmm	gmm	PROPN
ajst-29293	96	5	's	's	PART
ajst-29293	96	6	advantages	advantage	NOUN
ajst-29293	96	7	in	in	ADP
ajst-29293	96	8	handling	handle	VERB
ajst-29293	96	9	overlapping	overlap	VERB
ajst-29293	96	10	data	datum	NOUN
ajst-29293	96	11	distributions	distribution	NOUN
ajst-29293	96	12	and	and	CCONJ
ajst-29293	96	13	uncertainties	uncertainty	NOUN
ajst-29293	96	14	.	.	PUNCT
ajst-29293	97	1	however	however	ADV
ajst-29293	97	2	,	,	PUNCT
ajst-29293	97	3	it	it	PRON
ajst-29293	97	4	was	be	AUX
ajst-29293	97	5	also	also	ADV
ajst-29293	97	6	found	find	VERB
ajst-29293	97	7	that	that	SCONJ
ajst-29293	97	8	gmm	gmm	PROPN
ajst-29293	97	9	is	be	AUX
ajst-29293	97	10	sensitive	sensitive	ADJ
ajst-29293	97	11	to	to	ADP
ajst-29293	97	12	initial	initial	ADJ
ajst-29293	97	13	parameters	parameter	NOUN
ajst-29293	97	14	,	,	PUNCT
ajst-29293	97	15	can	can	AUX
ajst-29293	97	16	get	get	AUX
ajst-29293	97	17	trapped	trap	VERB
ajst-29293	97	18	in	in	ADP
ajst-29293	97	19	local	local	ADJ
ajst-29293	97	20	optima	optima	NOUN
ajst-29293	97	21	,	,	PUNCT
ajst-29293	97	22	and	and	CCONJ
ajst-29293	97	23	has	have	VERB
ajst-29293	97	24	a	a	DET
ajst-29293	97	25	relatively	relatively	ADV
ajst-29293	97	26	slow	slow	ADJ
ajst-29293	97	27	convergence	convergence	NOUN
ajst-29293	97	28	rate	rate	NOUN
ajst-29293	97	29	.	.	PUNCT
ajst-29293	98	1	to	to	PART
ajst-29293	98	2	address	address	VERB
ajst-29293	98	3	these	these	DET
ajst-29293	98	4	issues	issue	NOUN
ajst-29293	98	5	,	,	PUNCT
ajst-29293	98	6	this	this	DET
ajst-29293	98	7	chapter	chapter	NOUN
ajst-29293	98	8	introduces	introduce	VERB
ajst-29293	98	9	the	the	DET
ajst-29293	98	10	mvabc	mvabc	PROPN
ajst-29293	98	11	-	-	PUNCT
ajst-29293	98	12	gmm	gmm	NOUN
ajst-29293	98	13	(	(	PUNCT
ajst-29293	98	14	minimum	minimum	NOUN
ajst-29293	98	15	variance	variance	NOUN
ajst-29293	98	16	and	and	CCONJ
ajst-29293	98	17	artificial	artificial	ADJ
ajst-29293	98	18	bee	bee	NOUN
ajst-29293	98	19	colony	colony	NOUN
ajst-29293	98	20	optimized	optimize	VERB
ajst-29293	98	21	gmm	gmm	PROPN
ajst-29293	98	22	)	)	PUNCT
ajst-29293	98	23	algorithm	algorithm	NOUN
ajst-29293	98	24	,	,	PUNCT
ajst-29293	98	25	combining	combine	VERB
ajst-29293	98	26	the	the	DET
ajst-29293	98	27	minimum	minimum	ADJ
ajst-29293	98	28	variance	variance	NOUN
ajst-29293	98	29	theory	theory	NOUN
ajst-29293	98	30	and	and	CCONJ
ajst-29293	98	31	the	the	DET
ajst-29293	98	32	artificial	artificial	ADJ
ajst-29293	98	33	bee	bee	NOUN
ajst-29293	98	34	colony	colony	NOUN
ajst-29293	98	35	(	(	PUNCT
ajst-29293	98	36	abc	abc	PROPN
ajst-29293	98	37	)	)	PUNCT
ajst-29293	98	38	algorithm	algorithm	NOUN
ajst-29293	98	39	.	.	PUNCT
ajst-29293	99	1	the	the	DET
ajst-29293	99	2	comparison	comparison	NOUN
ajst-29293	99	3	with	with	ADP
ajst-29293	99	4	gmm	gmm	NOUN
ajst-29293	99	5	optimized	optimize	VERB
ajst-29293	99	6	by	by	ADP
ajst-29293	99	7	the	the	DET
ajst-29293	99	8	k	k	PROPN
ajst-29293	99	9	-	-	PUNCT
ajst-29293	99	10	means	means	NOUN
ajst-29293	99	11	algorithm	algorithm	NOUN
ajst-29293	99	12	significantly	significantly	ADV
ajst-29293	99	13	improved	improve	VERB
ajst-29293	99	14	convergence	convergence	NOUN
ajst-29293	99	15	speed	speed	NOUN
ajst-29293	99	16	and	and	CCONJ
ajst-29293	99	17	clustering	clustering	ADJ
ajst-29293	99	18	performance	performance	NOUN
ajst-29293	99	19	.	.	PUNCT
ajst-29293	100	1	references	reference	NOUN
ajst-29293	100	2	[	[	X
ajst-29293	100	3	1	1	X
ajst-29293	100	4	]	]	PUNCT
ajst-29293	100	5	gonzález	gonzález	PROPN
ajst-29293	100	6	l	l	PROPN
ajst-29293	100	7	g	g	PROPN
ajst-29293	100	8	,	,	PUNCT
ajst-29293	100	9	siavichay	siavichay	PROPN
ajst-29293	100	10	e	e	PROPN
ajst-29293	100	11	,	,	PUNCT
ajst-29293	100	12	espinoza	espinoza	PROPN
ajst-29293	100	13	j	j	PROPN
ajst-29293	100	14	l.	l.	PROPN
ajst-29293	100	15	impact	impact	PROPN
ajst-29293	100	16	of	of	ADP
ajst-29293	100	17	ev	ev	ADP
ajst-29293	100	18	fast	fast	ADJ
ajst-29293	100	19	charging	charge	VERB
ajst-29293	100	20	stations	station	NOUN
ajst-29293	100	21	on	on	ADP
ajst-29293	100	22	the	the	DET
ajst-29293	100	23	power	power	NOUN
ajst-29293	100	24	distribution	distribution	NOUN
ajst-29293	100	25	network	network	NOUN
ajst-29293	100	26	of	of	ADP
ajst-29293	100	27	alatin	alatin	PROPN
ajst-29293	100	28	american	american	PROPN
ajst-29293	100	29	intermediate	intermediate	ADJ
ajst-29293	100	30	city[j	city[j	PROPN
ajst-29293	100	31	]	]	PUNCT
ajst-29293	100	32	.	.	PUNCT
ajst-29293	101	1	renewable	renewable	ADJ
ajst-29293	101	2	and	and	CCONJ
ajst-29293	101	3	sustainable	sustainable	ADJ
ajst-29293	101	4	energy	energy	NOUN
ajst-29293	101	5	reviews	review	NOUN
ajst-29293	101	6	,	,	PUNCT
ajst-29293	101	7	2019	2019	NUM
ajst-29293	101	8	,	,	PUNCT
ajst-29293	101	9	144	144	NUM
ajst-29293	101	10	(	(	PUNCT
ajst-29293	101	11	107	107	NUM
ajst-29293	101	12	):	):	PUNCT
ajst-29293	101	13	309	309	NUM
ajst-29293	101	14	-	-	SYM
ajst-29293	101	15	318	318	NUM
ajst-29293	101	16	.	.	PUNCT
ajst-29293	102	1	[	[	X
ajst-29293	102	2	2	2	NUM
ajst-29293	102	3	]	]	PUNCT
ajst-29293	102	4	kempton	kempton	PROPN
ajst-29293	102	5	w	w	PROPN
ajst-29293	102	6	,	,	PUNCT
ajst-29293	102	7	tomi	tomi	PROPN
ajst-29293	102	8	j.	j.	PROPN
ajst-29293	102	9	vehicle	vehicle	PROPN
ajst-29293	102	10	-	-	PUNCT
ajst-29293	102	11	to	to	ADP
ajst-29293	102	12	-	-	PUNCT
ajst-29293	102	13	grid	grid	NOUN
ajst-29293	102	14	power	power	NOUN
ajst-29293	102	15	implementation	implementation	NOUN
ajst-29293	102	16	:	:	PUNCT
ajst-29293	102	17	from	from	ADP
ajst-29293	102	18	stabilizing	stabilize	VERB
ajst-29293	102	19	the	the	DET
ajst-29293	102	20	grid	grid	NOUN
ajst-29293	102	21	to	to	ADP
ajst-29293	102	22	supporting	support	VERB
ajst-29293	102	23	large	large	ADJ
ajst-29293	102	24	-	-	PUNCT
ajst-29293	102	25	scale	scale	NOUN
ajst-29293	102	26	renewable	renewable	ADJ
ajst-29293	102	27	energy[j	energy[j	NOUN
ajst-29293	102	28	]	]	PUNCT
ajst-29293	102	29	.	.	PUNCT
ajst-29293	103	1	journal	journal	PROPN
ajst-29293	103	2	of	of	ADP
ajst-29293	103	3	power	power	NOUN
ajst-29293	103	4	sources	source	NOUN
ajst-29293	103	5	,	,	PUNCT
ajst-29293	103	6	2021	2021	NUM
ajst-29293	103	7	,	,	PUNCT
ajst-29293	103	8	144(1	144(1	NUM
ajst-29293	103	9	):	):	PUNCT
ajst-29293	103	10	280	280	NUM
ajst-29293	103	11	-	-	SYM
ajst-29293	103	12	294	294	NUM
ajst-29293	103	13	.	.	PUNCT
ajst-29293	104	1	[	[	X
ajst-29293	104	2	3	3	X
ajst-29293	104	3	]	]	X
ajst-29293	104	4	liu	liu	PROPN
ajst-29293	104	5	jinpeng	jinpeng	PROPN
ajst-29293	104	6	,	,	PUNCT
ajst-29293	104	7	yang	yang	PROPN
ajst-29293	104	8	hao	hao	PROPN
ajst-29293	104	9	,	,	PUNCT
ajst-29293	104	10	wu	wu	PROPN
ajst-29293	104	11	lan	lan	PROPN
ajst-29293	104	12	,	,	PUNCT
ajst-29293	104	13	et	et	PROPN
ajst-29293	104	14	al	al	PROPN
ajst-29293	104	15	.	.	PUNCT
ajst-29293	104	16	evaluation	evaluation	NOUN
ajst-29293	104	17	of	of	ADP
ajst-29293	104	18	residential	residential	ADJ
ajst-29293	104	19	demand	demand	NOUN
ajst-29293	104	20	response	response	NOUN
ajst-29293	104	21	potential	potential	ADJ
ajst-29293	104	22	under	under	ADP
ajst-29293	104	23	multiple	multiple	ADJ
ajst-29293	104	24	confidence	confidence	NOUN
ajst-29293	104	25	scenarios	scenario	NOUN
ajst-29293	104	26	based	base	VERB
ajst-29293	104	27	on	on	ADP
ajst-29293	104	28	gaussian	gaussian	ADJ
ajst-29293	104	29	mixture	mixture	NOUN
ajst-29293	104	30	model[j	model[j	PROPN
ajst-29293	104	31	]	]	PUNCT
ajst-29293	104	32	.	.	PUNCT
ajst-29293	105	1	electric	electric	ADJ
ajst-29293	105	2	power	power	PROPN
ajst-29293	105	3	engineering	engineering	NOUN
ajst-29293	105	4	technology	technology	NOUN
ajst-29293	105	5	,	,	PUNCT
ajst-29293	105	6	2023	2023	NUM
ajst-29293	105	7	,	,	PUNCT
ajst-29293	105	8	42（2	42（2	PROPN
ajst-29293	105	9	）	）	NOUN
ajst-29293	105	10	:	:	PUNCT
ajst-29293	106	1	20	20	NUM
ajst-29293	106	2	-	-	SYM
ajst-29293	106	3	28	28	NUM
ajst-29293	106	4	[	[	X
ajst-29293	106	5	4	4	NUM
ajst-29293	106	6	]	]	X
ajst-29293	106	7	zhang	zhang	PROPN
ajst-29293	106	8	meixia	meixia	PROPN
ajst-29293	106	9	,	,	PUNCT
ajst-29293	106	10	li	li	PROPN
ajst-29293	106	11	li	li	PROPN
ajst-29293	106	12	,	,	PUNCT
ajst-29293	106	13	yang	yang	PROPN
ajst-29293	106	14	xiu	xiu	PROPN
ajst-29293	106	15	,	,	PUNCT
ajst-29293	106	16	et	et	PROPN
ajst-29293	106	17	al	al	PROPN
ajst-29293	106	18	.	.	PROPN
ajst-29293	106	19	load	load	NOUN
ajst-29293	106	20	classification	classification	NOUN
ajst-29293	106	21	method	method	NOUN
ajst-29293	106	22	based	base	VERB
ajst-29293	106	23	on	on	ADP
ajst-29293	106	24	gaussian	gaussian	ADJ
ajst-29293	106	25	mixture	mixture	NOUN
ajst-29293	106	26	model	model	NOUN
ajst-29293	106	27	clustering	cluster	VERB
ajst-29293	106	28	and	and	CCONJ
ajst-29293	106	29	multidimensional	multidimensional	ADJ
ajst-29293	106	30	scaling	scaling	NOUN
ajst-29293	106	31	analysis[j	analysis[j	PROPN
ajst-29293	106	32	]	]	PUNCT
ajst-29293	106	33	.	.	PUNCT
ajst-29293	107	1	power	power	NOUN
ajst-29293	107	2	system	system	NOUN
ajst-29293	107	3	technology	technology	NOUN
ajst-29293	107	4	,	,	PUNCT
ajst-29293	107	5	2020	2020	NUM
ajst-29293	107	6	,	,	PUNCT
ajst-29293	107	7	44(11	44(11	NUM
ajst-29293	107	8	):	):	PUNCT
ajst-29293	107	9	4283	4283	NUM
ajst-29293	107	10	-	-	SYM
ajst-29293	107	11	4296	4296	NUM
ajst-29293	107	12	.	.	PUNCT
ajst-29293	108	1	[	[	X
ajst-29293	108	2	5	5	X
ajst-29293	108	3	]	]	X
ajst-29293	108	4	wang	wang	PROPN
ajst-29293	108	5	tonghui	tonghui	PROPN
ajst-29293	108	6	,	,	PUNCT
ajst-29293	108	7	hou	hou	PROPN
ajst-29293	108	8	yi	yi	PROPN
ajst-29293	108	9	,	,	PUNCT
ajst-29293	108	10	yan	yan	PROPN
ajst-29293	108	11	ying	ying	PROPN
ajst-29293	108	12	.	.	PUNCT
ajst-29293	109	1	china	china	PROPN
ajst-29293	109	2	new	new	ADJ
ajst-29293	109	3	energy	energy	NOUN
ajst-29293	109	4	passenger	passenger	NOUN
ajst-29293	109	5	car	car	NOUN
ajst-29293	109	6	big	big	ADJ
ajst-29293	109	7	data	data	PROPN
ajst-29293	109	8	research	research	NOUN
ajst-29293	109	9	report	report	NOUN
ajst-29293	109	10	[	[	X
ajst-29293	109	11	m	m	X
ajst-29293	109	12	]	]	X
ajst-29293	109	13	.	.	PUNCT
ajst-29293	110	1	beijing	beijing	PROPN
ajst-29293	110	2	:	:	PUNCT
ajst-29293	111	1	china	china	PROPN
ajst-29293	111	2	machine	machine	PROPN
ajst-29293	111	3	press	press	PROPN
ajst-29293	111	4	,	,	PUNCT
ajst-29293	111	5	2021	2021	NUM
ajst-29293	111	6	.	.	PUNCT
ajst-29293	112	1	[	[	X
ajst-29293	112	2	6	6	NUM
ajst-29293	112	3	]	]	PUNCT
ajst-29293	112	4	wang	wang	PROPN
ajst-29293	112	5	xin	xin	PROPN
ajst-29293	112	6	,	,	PUNCT
ajst-29293	112	7	ding	ding	PROPN
ajst-29293	112	8	yunfei	yunfei	PROPN
ajst-29293	112	9	,	,	PUNCT
ajst-29293	112	10	lu	lu	PROPN
ajst-29293	112	11	hongzhuang	hongzhuang	PROPN
ajst-29293	112	12	.	.	PUNCT
ajst-29293	113	1	improved	improved	ADJ
ajst-29293	113	2	kernel	kernel	PROPN
ajst-29293	113	3	extreme	extreme	ADJ
ajst-29293	113	4	learning	learn	VERB
ajst-29293	113	5	machine	machine	NOUN
ajst-29293	113	6	for	for	ADP
ajst-29293	113	7	electric	electric	ADJ
ajst-29293	113	8	vehicle	vehicle	NOUN
ajst-29293	113	9	charging	charge	VERB
ajst-29293	113	10	load	load	NOUN
ajst-29293	113	11	prediction	prediction	NOUN
ajst-29293	113	12	.	.	PUNCT
ajst-29293	114	1	journal	journal	PROPN
ajst-29293	114	2	of	of	ADP
ajst-29293	114	3	shanghai	shanghai	PROPN
ajst-29293	114	4	university	university	PROPN
ajst-29293	114	5	of	of	ADP
ajst-29293	114	6	electric	electric	PROPN
ajst-29293	114	7	power	power	NOUN
ajst-29293	114	8	,	,	PUNCT
ajst-29293	114	9	2022	2022	NUM
ajst-29293	114	10	,	,	PUNCT
ajst-29293	114	11	25(1	25(1	NUM
ajst-29293	114	12	):	):	PUNCT
ajst-29293	114	13	1	1	NUM
ajst-29293	114	14	-	-	SYM
ajst-29293	114	15	6	6	NUM
ajst-29293	114	16	.	.	PUNCT
ajst-29293	115	1	[	[	X
ajst-29293	115	2	7	7	X
ajst-29293	115	3	]	]	X
ajst-29293	115	4	bu	bu	PROPN
ajst-29293	115	5	hui	hui	PROPN
ajst-29293	115	6	.	.	PUNCT
ajst-29293	115	7	research	research	NOUN
ajst-29293	115	8	on	on	ADP
ajst-29293	115	9	user	user	NOUN
ajst-29293	115	10	information	information	NOUN
ajst-29293	115	11	demand	demand	NOUN
ajst-29293	115	12	aggregation	aggregation	NOUN
ajst-29293	115	13	and	and	CCONJ
ajst-29293	115	14	application	application	NOUN
ajst-29293	115	15	in	in	ADP
ajst-29293	115	16	online	online	ADJ
ajst-29293	115	17	q&a	q&a	PROPN
ajst-29293	115	18	communities	community	NOUN
ajst-29293	115	19	based	base	VERB
ajst-29293	115	20	on	on	ADP
ajst-29293	115	21	the	the	DET
ajst-29293	115	22	integration	integration	NOUN
ajst-29293	115	23	of	of	ADP
ajst-29293	115	24	gmm	gmm	PROPN
ajst-29293	115	25	and	and	CCONJ
ajst-29293	115	26	k	k	NOUN
ajst-29293	115	27	-	-	PUNCT
ajst-29293	115	28	means	mean	VERB
ajst-29293	115	29	[	[	X
ajst-29293	115	30	d	d	X
ajst-29293	115	31	]	]	X
ajst-29293	115	32	.	.	PUNCT
ajst-29293	116	1	qufu	qufu	PROPN
ajst-29293	116	2	normal	normal	ADJ
ajst-29293	116	3	university	university	NOUN
ajst-29293	116	4	,	,	PUNCT
ajst-29293	116	5	2022	2022	NUM
ajst-29293	116	6	.	.	PUNCT