id	sid	tid	token	lemma	pos
ajst-10988	1	1	academic	academic	ADJ
ajst-10988	1	2	journal	journal	NOUN
ajst-10988	1	3	of	of	ADP
ajst-10988	1	4	science	science	NOUN
ajst-10988	1	5	and	and	CCONJ
ajst-10988	1	6	technology	technology	NOUN
ajst-10988	1	7	issn	issn	NOUN
ajst-10988	1	8	:	:	PUNCT
ajst-10988	1	9	2771	2771	NUM
ajst-10988	1	10	-	-	SYM
ajst-10988	1	11	3032	3032	NUM
ajst-10988	1	12	|	|	NOUN
ajst-10988	1	13	vol	vol	NOUN
ajst-10988	1	14	.	.	PROPN
ajst-10988	2	1	7	7	NUM
ajst-10988	2	2	,	,	PUNCT
ajst-10988	2	3	no	no	INTJ
ajst-10988	2	4	.	.	NOUN
ajst-10988	2	5	1	1	NUM
ajst-10988	2	6	,	,	PUNCT
ajst-10988	2	7	2023	2023	NUM
ajst-10988	2	8	49	49	NUM
ajst-10988	2	9	train	train	NOUN
ajst-10988	2	10	brake	brake	NOUN
ajst-10988	2	11	system	system	NOUN
ajst-10988	2	12	pipe	pipe	NOUN
ajst-10988	2	13	leakage	leakage	NOUN
ajst-10988	2	14	detection	detection	NOUN
ajst-10988	2	15	and	and	CCONJ
ajst-10988	2	16	early	early	ADJ
ajst-10988	2	17	warning	warning	NOUN
ajst-10988	2	18	method	method	NOUN
ajst-10988	2	19	based	base	VERB
ajst-10988	2	20	on	on	ADP
ajst-10988	2	21	bayesian	bayesian	NOUN
ajst-10988	2	22	networks	network	NOUN
ajst-10988	2	23	jiaqiao	jiaqiao	PROPN
ajst-10988	2	24	hu	hu	PROPN
ajst-10988	2	25	,	,	PUNCT
ajst-10988	2	26	liming	lime	VERB
ajst-10988	2	27	zhou	zhou	PROPN
ajst-10988	2	28	,	,	PUNCT
ajst-10988	2	29	qiang	qiang	PROPN
ajst-10988	2	30	wu	wu	PROPN
ajst-10988	2	31	,	,	PUNCT
ajst-10988	2	32	jin	jin	PROPN
ajst-10988	2	33	hua	hua	PROPN
ajst-10988	2	34	crrc	crrc	PROPN
ajst-10988	2	35	nanjingpuzhen	nanjingpuzhen	PROPN
ajst-10988	2	36	co.	co.	PROPN
ajst-10988	2	37	,	,	PUNCT
ajst-10988	2	38	ltd	ltd	PROPN
ajst-10988	2	39	.	.	PROPN
ajst-10988	2	40	,	,	PUNCT
ajst-10988	2	41	china	china	PROPN
ajst-10988	2	42	abstract	abstract	PROPN
ajst-10988	2	43	:	:	PUNCT
ajst-10988	2	44	this	this	DET
ajst-10988	2	45	paper	paper	NOUN
ajst-10988	2	46	proposes	propose	VERB
ajst-10988	2	47	a	a	DET
ajst-10988	2	48	method	method	NOUN
ajst-10988	2	49	for	for	ADP
ajst-10988	2	50	detecting	detect	VERB
ajst-10988	2	51	and	and	CCONJ
ajst-10988	2	52	warning	warn	VERB
ajst-10988	2	53	about	about	ADP
ajst-10988	2	54	leaks	leak	NOUN
ajst-10988	2	55	in	in	ADP
ajst-10988	2	56	train	train	NOUN
ajst-10988	2	57	braking	brake	VERB
ajst-10988	2	58	system	system	NOUN
ajst-10988	2	59	pipelines	pipeline	NOUN
ajst-10988	2	60	based	base	VERB
ajst-10988	2	61	on	on	ADP
ajst-10988	2	62	bayesian	bayesian	NOUN
ajst-10988	2	63	networks	network	NOUN
ajst-10988	2	64	.	.	PUNCT
ajst-10988	3	1	firstly	firstly	ADV
ajst-10988	3	2	,	,	PUNCT
ajst-10988	3	3	a	a	DET
ajst-10988	3	4	detection	detection	NOUN
ajst-10988	3	5	model	model	NOUN
ajst-10988	3	6	for	for	ADP
ajst-10988	3	7	pipeline	pipeline	NOUN
ajst-10988	3	8	leaks	leak	NOUN
ajst-10988	3	9	is	be	AUX
ajst-10988	3	10	established	establish	VERB
ajst-10988	3	11	through	through	ADP
ajst-10988	3	12	the	the	DET
ajst-10988	3	13	learning	learning	NOUN
ajst-10988	3	14	and	and	CCONJ
ajst-10988	3	15	inference	inference	NOUN
ajst-10988	3	16	of	of	ADP
ajst-10988	3	17	bayesian	bayesian	NOUN
ajst-10988	3	18	networks	network	NOUN
ajst-10988	3	19	.	.	PUNCT
ajst-10988	4	1	in	in	ADP
ajst-10988	4	2	the	the	DET
ajst-10988	4	3	anomaly	anomaly	NOUN
ajst-10988	4	4	detection	detection	NOUN
ajst-10988	4	5	phase	phase	NOUN
ajst-10988	4	6	,	,	PUNCT
ajst-10988	4	7	the	the	DET
ajst-10988	4	8	bayesian	bayesian	NOUN
ajst-10988	4	9	network	network	NOUN
ajst-10988	4	10	model	model	NOUN
ajst-10988	4	11	is	be	AUX
ajst-10988	4	12	trained	train	VERB
ajst-10988	4	13	using	use	VERB
ajst-10988	4	14	historical	historical	ADJ
ajst-10988	4	15	data	datum	NOUN
ajst-10988	4	16	to	to	PART
ajst-10988	4	17	monitor	monitor	VERB
ajst-10988	4	18	brake	brake	NOUN
ajst-10988	4	19	pressure	pressure	NOUN
ajst-10988	4	20	abnormalities	abnormality	NOUN
ajst-10988	4	21	in	in	ADP
ajst-10988	4	22	real	real	ADJ
ajst-10988	4	23	-	-	PUNCT
ajst-10988	4	24	time	time	NOUN
ajst-10988	4	25	.	.	PUNCT
ajst-10988	5	1	secondly	secondly	ADV
ajst-10988	5	2	,	,	PUNCT
ajst-10988	5	3	in	in	ADP
ajst-10988	5	4	the	the	DET
ajst-10988	5	5	parameter	parameter	NOUN
ajst-10988	5	6	regression	regression	NOUN
ajst-10988	5	7	calibration	calibration	NOUN
ajst-10988	5	8	phase	phase	NOUN
ajst-10988	5	9	,	,	PUNCT
ajst-10988	5	10	the	the	DET
ajst-10988	5	11	location	location	NOUN
ajst-10988	5	12	and	and	CCONJ
ajst-10988	5	13	severity	severity	NOUN
ajst-10988	5	14	of	of	ADP
ajst-10988	5	15	the	the	DET
ajst-10988	5	16	pipeline	pipeline	NOUN
ajst-10988	5	17	leaks	leak	NOUN
ajst-10988	5	18	are	be	AUX
ajst-10988	5	19	estimated	estimate	VERB
ajst-10988	5	20	based	base	VERB
ajst-10988	5	21	on	on	ADP
ajst-10988	5	22	the	the	DET
ajst-10988	5	23	current	current	ADJ
ajst-10988	5	24	brake	brake	NOUN
ajst-10988	5	25	pressure	pressure	NOUN
ajst-10988	5	26	and	and	CCONJ
ajst-10988	5	27	relevant	relevant	ADJ
ajst-10988	5	28	parameters	parameter	NOUN
ajst-10988	5	29	.	.	PUNCT
ajst-10988	6	1	finally	finally	ADV
ajst-10988	6	2	,	,	PUNCT
ajst-10988	6	3	in	in	ADP
ajst-10988	6	4	the	the	DET
ajst-10988	6	5	fault	fault	NOUN
ajst-10988	6	6	inference	inference	NOUN
ajst-10988	6	7	phase	phase	NOUN
ajst-10988	6	8	,	,	PUNCT
ajst-10988	6	9	the	the	DET
ajst-10988	6	10	bayesian	bayesian	NOUN
ajst-10988	6	11	network	network	NOUN
ajst-10988	6	12	model	model	NOUN
ajst-10988	6	13	is	be	AUX
ajst-10988	6	14	used	use	VERB
ajst-10988	6	15	to	to	PART
ajst-10988	6	16	infer	infer	VERB
ajst-10988	6	17	the	the	DET
ajst-10988	6	18	possible	possible	ADJ
ajst-10988	6	19	causes	cause	NOUN
ajst-10988	6	20	of	of	ADP
ajst-10988	6	21	the	the	DET
ajst-10988	6	22	leaks	leak	NOUN
ajst-10988	6	23	.	.	PUNCT
ajst-10988	7	1	the	the	DET
ajst-10988	7	2	effectiveness	effectiveness	NOUN
ajst-10988	7	3	and	and	CCONJ
ajst-10988	7	4	reliability	reliability	NOUN
ajst-10988	7	5	of	of	ADP
ajst-10988	7	6	this	this	DET
ajst-10988	7	7	method	method	NOUN
ajst-10988	7	8	are	be	AUX
ajst-10988	7	9	verified	verify	VERB
ajst-10988	7	10	through	through	ADP
ajst-10988	7	11	simulation	simulation	NOUN
ajst-10988	7	12	design	design	NOUN
ajst-10988	7	13	and	and	CCONJ
ajst-10988	7	14	actual	actual	ADJ
ajst-10988	7	15	data	datum	NOUN
ajst-10988	7	16	analysis	analysis	NOUN
ajst-10988	7	17	.	.	PUNCT
ajst-10988	8	1	compared	compare	VERB
ajst-10988	8	2	to	to	ADP
ajst-10988	8	3	existing	exist	VERB
ajst-10988	8	4	methods	method	NOUN
ajst-10988	8	5	,	,	PUNCT
ajst-10988	8	6	this	this	DET
ajst-10988	8	7	method	method	NOUN
ajst-10988	8	8	can	can	AUX
ajst-10988	8	9	provide	provide	VERB
ajst-10988	8	10	accurate	accurate	ADJ
ajst-10988	8	11	leak	leak	NOUN
ajst-10988	8	12	detection	detection	NOUN
ajst-10988	8	13	and	and	CCONJ
ajst-10988	8	14	warning	warning	NOUN
ajst-10988	8	15	,	,	PUNCT
ajst-10988	8	16	thereby	thereby	ADV
ajst-10988	8	17	contributing	contribute	VERB
ajst-10988	8	18	to	to	ADP
ajst-10988	8	19	the	the	DET
ajst-10988	8	20	safety	safety	NOUN
ajst-10988	8	21	of	of	ADP
ajst-10988	8	22	train	train	NOUN
ajst-10988	8	23	operation	operation	NOUN
ajst-10988	8	24	.	.	PUNCT
ajst-10988	9	1	this	this	DET
ajst-10988	9	2	research	research	NOUN
ajst-10988	9	3	provides	provide	VERB
ajst-10988	9	4	an	an	DET
ajst-10988	9	5	effective	effective	ADJ
ajst-10988	9	6	method	method	NOUN
ajst-10988	9	7	for	for	ADP
ajst-10988	9	8	detecting	detect	VERB
ajst-10988	9	9	and	and	CCONJ
ajst-10988	9	10	warning	warn	VERB
ajst-10988	9	11	about	about	ADP
ajst-10988	9	12	leaks	leak	NOUN
ajst-10988	9	13	in	in	ADP
ajst-10988	9	14	brake	brake	NOUN
ajst-10988	9	15	system	system	NOUN
ajst-10988	9	16	pipelines	pipeline	NOUN
ajst-10988	9	17	and	and	CCONJ
ajst-10988	9	18	has	have	VERB
ajst-10988	9	19	practical	practical	ADJ
ajst-10988	9	20	application	application	NOUN
ajst-10988	9	21	value	value	NOUN
ajst-10988	9	22	.	.	PUNCT
ajst-10988	10	1	keywords	keyword	NOUN
ajst-10988	10	2	:	:	PUNCT
ajst-10988	10	3	bayesian	bayesian	NOUN
ajst-10988	10	4	networks	network	NOUN
ajst-10988	10	5	,	,	PUNCT
ajst-10988	10	6	train	train	NOUN
ajst-10988	10	7	braking	braking	NOUN
ajst-10988	10	8	system	system	NOUN
ajst-10988	10	9	,	,	PUNCT
ajst-10988	10	10	pipe	pipe	NOUN
ajst-10988	10	11	leak	leak	NOUN
ajst-10988	10	12	detection	detection	NOUN
ajst-10988	10	13	,	,	PUNCT
ajst-10988	10	14	early	early	ADJ
ajst-10988	10	15	warning	warning	NOUN
ajst-10988	10	16	methods	method	NOUN
ajst-10988	10	17	.	.	PUNCT
ajst-10988	11	1	1	1	X
ajst-10988	11	2	.	.	X
ajst-10988	11	3	introduction	introduction	NOUN
ajst-10988	11	4	with	with	ADP
ajst-10988	11	5	the	the	DET
ajst-10988	11	6	rapid	rapid	ADJ
ajst-10988	11	7	development	development	NOUN
ajst-10988	11	8	of	of	ADP
ajst-10988	11	9	modern	modern	ADJ
ajst-10988	11	10	transportation	transportation	NOUN
ajst-10988	11	11	systems	system	NOUN
ajst-10988	11	12	,	,	PUNCT
ajst-10988	11	13	train	train	NOUN
ajst-10988	11	14	transportation	transportation	NOUN
ajst-10988	11	15	has	have	AUX
ajst-10988	11	16	gained	gain	VERB
ajst-10988	11	17	increasing	increase	VERB
ajst-10988	11	18	attention	attention	NOUN
ajst-10988	11	19	as	as	ADP
ajst-10988	11	20	an	an	DET
ajst-10988	11	21	efficient	efficient	ADJ
ajst-10988	11	22	and	and	CCONJ
ajst-10988	11	23	convenient	convenient	ADJ
ajst-10988	11	24	mode	mode	NOUN
ajst-10988	11	25	of	of	ADP
ajst-10988	11	26	transportation	transportation	NOUN
ajst-10988	11	27	.	.	PUNCT
ajst-10988	12	1	among	among	ADP
ajst-10988	12	2	them	they	PRON
ajst-10988	12	3	,	,	PUNCT
ajst-10988	12	4	the	the	DET
ajst-10988	12	5	train	train	NOUN
ajst-10988	12	6	braking	brake	VERB
ajst-10988	12	7	system	system	NOUN
ajst-10988	12	8	is	be	AUX
ajst-10988	12	9	an	an	DET
ajst-10988	12	10	important	important	ADJ
ajst-10988	12	11	component	component	NOUN
ajst-10988	12	12	to	to	PART
ajst-10988	12	13	ensure	ensure	VERB
ajst-10988	12	14	the	the	DET
ajst-10988	12	15	safety	safety	NOUN
ajst-10988	12	16	of	of	ADP
ajst-10988	12	17	train	train	NOUN
ajst-10988	12	18	operation	operation	NOUN
ajst-10988	12	19	.	.	PUNCT
ajst-10988	13	1	however	however	ADV
ajst-10988	13	2	,	,	PUNCT
ajst-10988	13	3	the	the	DET
ajst-10988	13	4	issue	issue	NOUN
ajst-10988	13	5	of	of	ADP
ajst-10988	13	6	leaks	leak	NOUN
ajst-10988	13	7	in	in	ADP
ajst-10988	13	8	the	the	DET
ajst-10988	13	9	brake	brake	NOUN
ajst-10988	13	10	system	system	NOUN
ajst-10988	13	11	pipelines	pipeline	NOUN
ajst-10988	13	12	poses	pose	VERB
ajst-10988	13	13	potential	potential	ADJ
ajst-10988	13	14	safety	safety	NOUN
ajst-10988	13	15	hazards	hazard	NOUN
ajst-10988	13	16	to	to	PART
ajst-10988	13	17	train	train	VERB
ajst-10988	13	18	operation	operation	NOUN
ajst-10988	13	19	.	.	PUNCT
ajst-10988	14	1	therefore	therefore	ADV
ajst-10988	14	2	,	,	PUNCT
ajst-10988	14	3	it	it	PRON
ajst-10988	14	4	is	be	AUX
ajst-10988	14	5	crucial	crucial	ADJ
ajst-10988	14	6	to	to	PART
ajst-10988	14	7	develop	develop	VERB
ajst-10988	14	8	an	an	DET
ajst-10988	14	9	efficient	efficient	ADJ
ajst-10988	14	10	and	and	CCONJ
ajst-10988	14	11	reliable	reliable	ADJ
ajst-10988	14	12	method	method	NOUN
ajst-10988	14	13	for	for	ADP
ajst-10988	14	14	detecting	detect	VERB
ajst-10988	14	15	and	and	CCONJ
ajst-10988	14	16	warning	warn	VERB
ajst-10988	14	17	about	about	ADP
ajst-10988	14	18	leaks	leak	NOUN
ajst-10988	14	19	in	in	ADP
ajst-10988	14	20	train	train	NOUN
ajst-10988	14	21	braking	brake	VERB
ajst-10988	14	22	system	system	NOUN
ajst-10988	14	23	pipelines	pipeline	NOUN
ajst-10988	14	24	.	.	PUNCT
ajst-10988	15	1	bayesian	bayesian	NOUN
ajst-10988	15	2	networks	network	NOUN
ajst-10988	15	3	,	,	PUNCT
ajst-10988	15	4	as	as	ADP
ajst-10988	15	5	powerful	powerful	ADJ
ajst-10988	15	6	probabilistic	probabilistic	ADJ
ajst-10988	15	7	inference	inference	NOUN
ajst-10988	15	8	tools	tool	NOUN
ajst-10988	15	9	,	,	PUNCT
ajst-10988	15	10	have	have	AUX
ajst-10988	15	11	been	be	AUX
ajst-10988	15	12	widely	widely	ADV
ajst-10988	15	13	applied	apply	VERB
ajst-10988	15	14	in	in	ADP
ajst-10988	15	15	various	various	ADJ
ajst-10988	15	16	fields	field	NOUN
ajst-10988	15	17	.	.	PUNCT
ajst-10988	16	1	they	they	PRON
ajst-10988	16	2	can	can	AUX
ajst-10988	16	3	accurately	accurately	ADV
ajst-10988	16	4	model	model	VERB
ajst-10988	16	5	the	the	DET
ajst-10988	16	6	dependencies	dependency	NOUN
ajst-10988	16	7	and	and	CCONJ
ajst-10988	16	8	uncertainties	uncertainty	NOUN
ajst-10988	16	9	among	among	ADP
ajst-10988	16	10	variables	variable	NOUN
ajst-10988	16	11	,	,	PUNCT
ajst-10988	16	12	making	make	VERB
ajst-10988	16	13	them	they	PRON
ajst-10988	16	14	an	an	DET
ajst-10988	16	15	effective	effective	ADJ
ajst-10988	16	16	approach	approach	NOUN
ajst-10988	16	17	to	to	ADP
ajst-10988	16	18	solving	solve	VERB
ajst-10988	16	19	complex	complex	ADJ
ajst-10988	16	20	problems	problem	NOUN
ajst-10988	16	21	.	.	PUNCT
ajst-10988	17	1	this	this	DET
ajst-10988	17	2	paper	paper	NOUN
ajst-10988	17	3	aims	aim	VERB
ajst-10988	17	4	to	to	PART
ajst-10988	17	5	combine	combine	VERB
ajst-10988	17	6	the	the	DET
ajst-10988	17	7	bayesian	bayesian	NOUN
ajst-10988	17	8	network	network	NOUN
ajst-10988	17	9	algorithm	algorithm	NOUN
ajst-10988	17	10	and	and	CCONJ
ajst-10988	17	11	propose	propose	VERB
ajst-10988	17	12	a	a	DET
ajst-10988	17	13	method	method	NOUN
ajst-10988	17	14	for	for	ADP
ajst-10988	17	15	detecting	detect	VERB
ajst-10988	17	16	and	and	CCONJ
ajst-10988	17	17	warning	warn	VERB
ajst-10988	17	18	about	about	ADP
ajst-10988	17	19	leaks	leak	NOUN
ajst-10988	17	20	in	in	ADP
ajst-10988	17	21	train	train	NOUN
ajst-10988	17	22	braking	brake	VERB
ajst-10988	17	23	system	system	NOUN
ajst-10988	17	24	pipelines	pipeline	NOUN
ajst-10988	17	25	based	base	VERB
ajst-10988	17	26	on	on	ADP
ajst-10988	17	27	bayesian	bayesian	NOUN
ajst-10988	17	28	networks	network	NOUN
ajst-10988	17	29	,	,	PUNCT
ajst-10988	17	30	aiming	aim	VERB
ajst-10988	17	31	to	to	PART
ajst-10988	17	32	enhance	enhance	VERB
ajst-10988	17	33	the	the	DET
ajst-10988	17	34	safety	safety	NOUN
ajst-10988	17	35	of	of	ADP
ajst-10988	17	36	the	the	DET
ajst-10988	17	37	train	train	NOUN
ajst-10988	17	38	braking	brake	VERB
ajst-10988	17	39	system	system	NOUN
ajst-10988	17	40	[	[	X
ajst-10988	17	41	chi	chi	NOUN
ajst-10988	17	42	z,2023	z,2023	PROPN
ajst-10988	17	43	]	]	PUNCT
ajst-10988	17	44	.	.	PUNCT
ajst-10988	18	1	this	this	DET
ajst-10988	18	2	study	study	NOUN
ajst-10988	18	3	will	will	AUX
ajst-10988	18	4	focus	focus	VERB
ajst-10988	18	5	on	on	ADP
ajst-10988	18	6	several	several	ADJ
ajst-10988	18	7	key	key	ADJ
ajst-10988	18	8	issues	issue	NOUN
ajst-10988	18	9	:	:	PUNCT
ajst-10988	18	10	firstly	firstly	ADV
ajst-10988	18	11	,	,	PUNCT
ajst-10988	18	12	through	through	ADP
ajst-10988	18	13	the	the	DET
ajst-10988	18	14	study	study	NOUN
ajst-10988	18	15	of	of	ADP
ajst-10988	18	16	the	the	DET
ajst-10988	18	17	bayesian	bayesian	NOUN
ajst-10988	18	18	network	network	NOUN
ajst-10988	18	19	algorithm	algorithm	NOUN
ajst-10988	18	20	,	,	PUNCT
ajst-10988	18	21	the	the	DET
ajst-10988	18	22	definition	definition	NOUN
ajst-10988	18	23	,	,	PUNCT
ajst-10988	18	24	learning	learning	NOUN
ajst-10988	18	25	,	,	PUNCT
ajst-10988	18	26	and	and	CCONJ
ajst-10988	18	27	inference	inference	NOUN
ajst-10988	18	28	methods	method	NOUN
ajst-10988	18	29	of	of	ADP
ajst-10988	18	30	bayesian	bayesian	NOUN
ajst-10988	18	31	networks	network	NOUN
ajst-10988	18	32	will	will	AUX
ajst-10988	18	33	be	be	AUX
ajst-10988	18	34	thoroughly	thoroughly	ADV
ajst-10988	18	35	explored	explore	VERB
ajst-10988	18	36	.	.	PUNCT
ajst-10988	19	1	secondly	secondly	ADV
ajst-10988	19	2	,	,	PUNCT
ajst-10988	19	3	a	a	DET
ajst-10988	19	4	detection	detection	NOUN
ajst-10988	19	5	model	model	NOUN
ajst-10988	19	6	for	for	ADP
ajst-10988	19	7	leaks	leak	NOUN
ajst-10988	19	8	in	in	ADP
ajst-10988	19	9	train	train	NOUN
ajst-10988	19	10	braking	brake	VERB
ajst-10988	19	11	system	system	NOUN
ajst-10988	19	12	pipelines	pipeline	NOUN
ajst-10988	19	13	will	will	AUX
ajst-10988	19	14	be	be	AUX
ajst-10988	19	15	established	establish	VERB
ajst-10988	19	16	based	base	VERB
ajst-10988	19	17	on	on	ADP
ajst-10988	19	18	bayesian	bayesian	NOUN
ajst-10988	19	19	networks	network	NOUN
ajst-10988	19	20	,	,	PUNCT
ajst-10988	19	21	including	include	VERB
ajst-10988	19	22	the	the	DET
ajst-10988	19	23	stages	stage	NOUN
ajst-10988	19	24	of	of	ADP
ajst-10988	19	25	anomaly	anomaly	NOUN
ajst-10988	19	26	detection	detection	NOUN
ajst-10988	19	27	,	,	PUNCT
ajst-10988	19	28	parameter	parameter	NOUN
ajst-10988	19	29	regression	regression	NOUN
ajst-10988	19	30	calibration	calibration	NOUN
ajst-10988	19	31	,	,	PUNCT
ajst-10988	19	32	and	and	CCONJ
ajst-10988	19	33	fault	fault	VERB
ajst-10988	19	34	inference	inference	NOUN
ajst-10988	19	35	,	,	PUNCT
ajst-10988	19	36	in	in	ADP
ajst-10988	19	37	order	order	NOUN
ajst-10988	19	38	to	to	PART
ajst-10988	19	39	improve	improve	VERB
ajst-10988	19	40	the	the	DET
ajst-10988	19	41	accuracy	accuracy	NOUN
ajst-10988	19	42	of	of	ADP
ajst-10988	19	43	leak	leak	NOUN
ajst-10988	19	44	detection	detection	NOUN
ajst-10988	19	45	and	and	CCONJ
ajst-10988	19	46	the	the	DET
ajst-10988	19	47	precision	precision	NOUN
ajst-10988	19	48	of	of	ADP
ajst-10988	19	49	prediction	prediction	NOUN
ajst-10988	19	50	.	.	PUNCT
ajst-10988	20	1	finally	finally	ADV
ajst-10988	20	2	,	,	PUNCT
ajst-10988	20	3	through	through	ADP
ajst-10988	20	4	simulation	simulation	NOUN
ajst-10988	20	5	design	design	NOUN
ajst-10988	20	6	and	and	CCONJ
ajst-10988	20	7	analysis	analysis	NOUN
ajst-10988	20	8	of	of	ADP
ajst-10988	20	9	actual	actual	ADJ
ajst-10988	20	10	data	datum	NOUN
ajst-10988	20	11	verification	verification	NOUN
ajst-10988	20	12	,	,	PUNCT
ajst-10988	20	13	the	the	DET
ajst-10988	20	14	effectiveness	effectiveness	NOUN
ajst-10988	20	15	and	and	CCONJ
ajst-10988	20	16	feasibility	feasibility	NOUN
ajst-10988	20	17	of	of	ADP
ajst-10988	20	18	the	the	DET
ajst-10988	20	19	proposed	propose	VERB
ajst-10988	20	20	method	method	NOUN
ajst-10988	20	21	will	will	AUX
ajst-10988	20	22	be	be	AUX
ajst-10988	20	23	evaluated	evaluate	VERB
ajst-10988	20	24	.	.	PUNCT
ajst-10988	21	1	this	this	DET
ajst-10988	21	2	research	research	NOUN
ajst-10988	21	3	aims	aim	VERB
ajst-10988	21	4	to	to	PART
ajst-10988	21	5	provide	provide	VERB
ajst-10988	21	6	a	a	DET
ajst-10988	21	7	reliable	reliable	ADJ
ajst-10988	21	8	and	and	CCONJ
ajst-10988	21	9	efficient	efficient	ADJ
ajst-10988	21	10	solution	solution	NOUN
ajst-10988	21	11	for	for	ADP
ajst-10988	21	12	detecting	detect	VERB
ajst-10988	21	13	and	and	CCONJ
ajst-10988	21	14	warning	warn	VERB
ajst-10988	21	15	about	about	ADP
ajst-10988	21	16	leaks	leak	NOUN
ajst-10988	21	17	in	in	ADP
ajst-10988	21	18	train	train	NOUN
ajst-10988	21	19	braking	brake	VERB
ajst-10988	21	20	system	system	NOUN
ajst-10988	21	21	pipelines	pipeline	NOUN
ajst-10988	21	22	,	,	PUNCT
ajst-10988	21	23	thus	thus	ADV
ajst-10988	21	24	providing	provide	VERB
ajst-10988	21	25	strong	strong	ADJ
ajst-10988	21	26	support	support	NOUN
ajst-10988	21	27	for	for	ADP
ajst-10988	21	28	ensuring	ensure	VERB
ajst-10988	21	29	the	the	DET
ajst-10988	21	30	safety	safety	NOUN
ajst-10988	21	31	of	of	ADP
ajst-10988	21	32	train	train	NOUN
ajst-10988	21	33	operation	operation	NOUN
ajst-10988	21	34	.	.	PUNCT
ajst-10988	22	1	additionally	additionally	ADV
ajst-10988	22	2	,	,	PUNCT
ajst-10988	22	3	this	this	DET
ajst-10988	22	4	study	study	NOUN
ajst-10988	22	5	will	will	AUX
ajst-10988	22	6	deepen	deepen	VERB
ajst-10988	22	7	the	the	DET
ajst-10988	22	8	understanding	understanding	NOUN
ajst-10988	22	9	of	of	ADP
ajst-10988	22	10	the	the	DET
ajst-10988	22	11	application	application	NOUN
ajst-10988	22	12	of	of	ADP
ajst-10988	22	13	the	the	DET
ajst-10988	22	14	bayesian	bayesian	NOUN
ajst-10988	22	15	network	network	NOUN
ajst-10988	22	16	algorithm	algorithm	NOUN
ajst-10988	22	17	in	in	ADP
ajst-10988	22	18	the	the	DET
ajst-10988	22	19	field	field	NOUN
ajst-10988	22	20	of	of	ADP
ajst-10988	22	21	engineering	engineering	NOUN
ajst-10988	22	22	,	,	PUNCT
ajst-10988	22	23	providing	provide	VERB
ajst-10988	22	24	valuable	valuable	ADJ
ajst-10988	22	25	references	reference	NOUN
ajst-10988	22	26	and	and	CCONJ
ajst-10988	22	27	insights	insight	NOUN
ajst-10988	22	28	,	,	PUNCT
ajst-10988	22	29	and	and	CCONJ
ajst-10988	22	30	possessing	possess	VERB
ajst-10988	22	31	broad	broad	ADJ
ajst-10988	22	32	practical	practical	ADJ
ajst-10988	22	33	application	application	NOUN
ajst-10988	22	34	value	value	NOUN
ajst-10988	22	35	and	and	CCONJ
ajst-10988	22	36	scientific	scientific	ADJ
ajst-10988	22	37	research	research	NOUN
ajst-10988	22	38	significance	significance	NOUN
ajst-10988	22	39	.	.	PUNCT
ajst-10988	23	1	2	2	X
ajst-10988	23	2	.	.	X
ajst-10988	23	3	a	a	DET
ajst-10988	23	4	study	study	NOUN
ajst-10988	23	5	of	of	ADP
ajst-10988	23	6	bayesian	bayesian	NOUN
ajst-10988	23	7	network	network	NOUN
ajst-10988	23	8	algorithms	algorithm	VERB
ajst-10988	23	9	2.1	2.1	NUM
ajst-10988	23	10	.	.	PUNCT
ajst-10988	24	1	definition	definition	NOUN
ajst-10988	24	2	of	of	ADP
ajst-10988	24	3	bayesian	bayesian	NOUN
ajst-10988	24	4	network	network	NOUN
ajst-10988	24	5	bayesian	bayesian	NOUN
ajst-10988	24	6	networks	network	NOUN
ajst-10988	24	7	are	be	AUX
ajst-10988	24	8	a	a	DET
ajst-10988	24	9	probabilistic	probabilistic	ADJ
ajst-10988	24	10	graphical	graphical	ADJ
ajst-10988	24	11	model	model	NOUN
ajst-10988	24	12	(	(	PUNCT
ajst-10988	24	13	as	as	SCONJ
ajst-10988	24	14	shown	show	VERB
ajst-10988	24	15	in	in	ADP
ajst-10988	24	16	figure	figure	NOUN
ajst-10988	24	17	1	1	NUM
ajst-10988	24	18	)	)	PUNCT
ajst-10988	24	19	used	use	VERB
ajst-10988	24	20	to	to	PART
ajst-10988	24	21	describe	describe	VERB
ajst-10988	24	22	the	the	DET
ajst-10988	24	23	conditional	conditional	ADJ
ajst-10988	24	24	dependencies	dependency	NOUN
ajst-10988	24	25	between	between	ADP
ajst-10988	24	26	random	random	ADJ
ajst-10988	24	27	variables	variable	NOUN
ajst-10988	24	28	.	.	PUNCT
ajst-10988	25	1	they	they	PRON
ajst-10988	25	2	are	be	AUX
ajst-10988	25	3	represented	represent	VERB
ajst-10988	25	4	as	as	ADP
ajst-10988	25	5	directed	direct	VERB
ajst-10988	25	6	acyclic	acyclic	ADJ
ajst-10988	25	7	graphs	graph	NOUN
ajst-10988	25	8	,	,	PUNCT
ajst-10988	25	9	where	where	SCONJ
ajst-10988	25	10	nodes	node	NOUN
ajst-10988	25	11	represent	represent	VERB
ajst-10988	25	12	random	random	ADJ
ajst-10988	25	13	variables	variable	NOUN
ajst-10988	25	14	and	and	CCONJ
ajst-10988	25	15	edges	edge	NOUN
ajst-10988	25	16	represent	represent	VERB
ajst-10988	25	17	the	the	DET
ajst-10988	25	18	conditional	conditional	ADJ
ajst-10988	25	19	dependencies	dependency	NOUN
ajst-10988	25	20	between	between	ADP
ajst-10988	25	21	variables	variable	NOUN
ajst-10988	25	22	.	.	PUNCT
ajst-10988	26	1	bayesian	bayesian	NOUN
ajst-10988	26	2	networks	network	NOUN
ajst-10988	26	3	utilize	utilize	VERB
ajst-10988	26	4	conditional	conditional	ADJ
ajst-10988	26	5	probability	probability	NOUN
ajst-10988	26	6	tables	table	NOUN
ajst-10988	26	7	to	to	PART
ajst-10988	26	8	represent	represent	VERB
ajst-10988	26	9	the	the	DET
ajst-10988	26	10	dependencies	dependency	NOUN
ajst-10988	26	11	and	and	CCONJ
ajst-10988	26	12	uncertainties	uncertainty	NOUN
ajst-10988	26	13	between	between	ADP
ajst-10988	26	14	variables	variable	NOUN
ajst-10988	26	15	,	,	PUNCT
ajst-10988	26	16	enabling	enable	VERB
ajst-10988	26	17	probabilistic	probabilistic	ADJ
ajst-10988	26	18	inference	inference	NOUN
ajst-10988	26	19	and	and	CCONJ
ajst-10988	26	20	prediction	prediction	NOUN
ajst-10988	26	21	.	.	PUNCT
ajst-10988	27	1	in	in	ADP
ajst-10988	27	2	a	a	DET
ajst-10988	27	3	bayesian	bayesian	NOUN
ajst-10988	27	4	network	network	NOUN
ajst-10988	27	5	,	,	PUNCT
ajst-10988	27	6	each	each	DET
ajst-10988	27	7	node	node	NOUN
ajst-10988	27	8	represents	represent	VERB
ajst-10988	27	9	a	a	DET
ajst-10988	27	10	random	random	ADJ
ajst-10988	27	11	variable	variable	NOUN
ajst-10988	27	12	,	,	PUNCT
ajst-10988	27	13	and	and	CCONJ
ajst-10988	27	14	the	the	DET
ajst-10988	27	15	parent	parent	NOUN
ajst-10988	27	16	nodes	node	NOUN
ajst-10988	27	17	represent	represent	VERB
ajst-10988	27	18	the	the	DET
ajst-10988	27	19	direct	direct	ADJ
ajst-10988	27	20	influencing	influence	VERB
ajst-10988	27	21	factors	factor	NOUN
ajst-10988	27	22	of	of	ADP
ajst-10988	27	23	that	that	DET
ajst-10988	27	24	variable	variable	NOUN
ajst-10988	27	25	.	.	PUNCT
ajst-10988	28	1	the	the	DET
ajst-10988	28	2	state	state	NOUN
ajst-10988	28	3	of	of	ADP
ajst-10988	28	4	each	each	DET
ajst-10988	28	5	node	node	NOUN
ajst-10988	28	6	is	be	AUX
ajst-10988	28	7	determined	determine	VERB
ajst-10988	28	8	by	by	ADP
ajst-10988	28	9	its	its	PRON
ajst-10988	28	10	parent	parent	NOUN
ajst-10988	28	11	nodes	node	NOUN
ajst-10988	28	12	and	and	CCONJ
ajst-10988	28	13	the	the	DET
ajst-10988	28	14	conditional	conditional	ADJ
ajst-10988	28	15	probability	probability	NOUN
ajst-10988	28	16	tables	table	NOUN
ajst-10988	28	17	,	,	PUNCT
ajst-10988	28	18	which	which	PRON
ajst-10988	28	19	reflect	reflect	VERB
ajst-10988	28	20	the	the	DET
ajst-10988	28	21	probability	probability	NOUN
ajst-10988	28	22	distribution	distribution	NOUN
ajst-10988	28	23	of	of	ADP
ajst-10988	28	24	the	the	DET
ajst-10988	28	25	node	node	NOUN
ajst-10988	28	26	's	's	PART
ajst-10988	28	27	state	state	NOUN
ajst-10988	28	28	given	give	VERB
ajst-10988	28	29	the	the	DET
ajst-10988	28	30	states	state	NOUN
ajst-10988	28	31	of	of	ADP
ajst-10988	28	32	its	its	PRON
ajst-10988	28	33	parent	parent	NOUN
ajst-10988	28	34	nodes	nod	VERB
ajst-10988	28	35	.	.	PUNCT
ajst-10988	29	1	through	through	ADP
ajst-10988	29	2	bayesian	bayesian	NOUN
ajst-10988	29	3	network	network	NOUN
ajst-10988	29	4	inference	inference	NOUN
ajst-10988	29	5	,	,	PUNCT
ajst-10988	29	6	it	it	PRON
ajst-10988	29	7	is	be	AUX
ajst-10988	29	8	possible	possible	ADJ
ajst-10988	29	9	to	to	PART
ajst-10988	29	10	infer	infer	VERB
ajst-10988	29	11	the	the	DET
ajst-10988	29	12	posterior	posterior	ADJ
ajst-10988	29	13	probability	probability	NOUN
ajst-10988	29	14	distribution	distribution	NOUN
ajst-10988	29	15	of	of	ADP
ajst-10988	29	16	other	other	ADJ
ajst-10988	29	17	variables	variable	NOUN
ajst-10988	29	18	based	base	VERB
ajst-10988	29	19	on	on	ADP
ajst-10988	29	20	the	the	DET
ajst-10988	29	21	observed	observed	ADJ
ajst-10988	29	22	variables	variable	NOUN
ajst-10988	29	23	,	,	PUNCT
ajst-10988	29	24	thus	thus	ADV
ajst-10988	29	25	facilitating	facilitate	VERB
ajst-10988	29	26	reasoning	reasoning	NOUN
ajst-10988	29	27	and	and	CCONJ
ajst-10988	29	28	prediction	prediction	NOUN
ajst-10988	29	29	in	in	ADP
ajst-10988	29	30	the	the	DET
ajst-10988	29	31	system	system	NOUN
ajst-10988	29	32	.	.	PUNCT
ajst-10988	30	1	figure	figure	NOUN
ajst-10988	30	2	1	1	NUM
ajst-10988	30	3	.	.	PUNCT
ajst-10988	31	1	bayesian	bayesian	NOUN
ajst-10988	31	2	network	network	NOUN
ajst-10988	31	3	bayesian	bayesian	NOUN
ajst-10988	31	4	networks	network	NOUN
ajst-10988	31	5	offer	offer	VERB
ajst-10988	31	6	flexibility	flexibility	NOUN
ajst-10988	31	7	and	and	CCONJ
ajst-10988	31	8	interpretability	interpretability	NOUN
ajst-10988	31	9	,	,	PUNCT
ajst-10988	31	10	enabling	enable	VERB
ajst-10988	31	11	the	the	DET
ajst-10988	31	12	handling	handling	NOUN
ajst-10988	31	13	of	of	ADP
ajst-10988	31	14	incomplete	incomplete	ADJ
ajst-10988	31	15	information	information	NOUN
ajst-10988	31	16	and	and	CCONJ
ajst-10988	31	17	50	50	NUM
ajst-10988	31	18	uncertainty	uncertainty	NOUN
ajst-10988	31	19	problems	problem	NOUN
ajst-10988	31	20	.	.	PUNCT
ajst-10988	32	1	they	they	PRON
ajst-10988	32	2	are	be	AUX
ajst-10988	32	3	widely	widely	ADV
ajst-10988	32	4	applied	apply	VERB
ajst-10988	32	5	in	in	ADP
ajst-10988	32	6	various	various	ADJ
ajst-10988	32	7	fields	field	NOUN
ajst-10988	32	8	,	,	PUNCT
ajst-10988	32	9	such	such	ADJ
ajst-10988	32	10	as	as	ADP
ajst-10988	32	11	decision	decision	NOUN
ajst-10988	32	12	analysis	analysis	NOUN
ajst-10988	32	13	,	,	PUNCT
ajst-10988	32	14	risk	risk	NOUN
ajst-10988	32	15	assessment	assessment	NOUN
ajst-10988	32	16	,	,	PUNCT
ajst-10988	32	17	and	and	CCONJ
ajst-10988	32	18	medical	medical	ADJ
ajst-10988	32	19	diagnosis	diagnosis	NOUN
ajst-10988	32	20	.	.	PUNCT
ajst-10988	33	1	by	by	ADP
ajst-10988	33	2	understanding	understand	VERB
ajst-10988	33	3	the	the	DET
ajst-10988	33	4	definition	definition	NOUN
ajst-10988	33	5	and	and	CCONJ
ajst-10988	33	6	principles	principle	NOUN
ajst-10988	33	7	of	of	ADP
ajst-10988	33	8	bayesian	bayesian	NOUN
ajst-10988	33	9	networks	network	NOUN
ajst-10988	33	10	,	,	PUNCT
ajst-10988	33	11	we	we	PRON
ajst-10988	33	12	can	can	AUX
ajst-10988	33	13	better	well	ADV
ajst-10988	33	14	establish	establish	VERB
ajst-10988	33	15	probabilistic	probabilistic	ADJ
ajst-10988	33	16	models	model	NOUN
ajst-10988	33	17	,	,	PUNCT
ajst-10988	33	18	conduct	conduct	NOUN
ajst-10988	33	19	inference	inference	NOUN
ajst-10988	33	20	,	,	PUNCT
ajst-10988	33	21	and	and	CCONJ
ajst-10988	33	22	make	make	VERB
ajst-10988	33	23	decisions	decision	NOUN
ajst-10988	33	24	,	,	PUNCT
ajst-10988	33	25	providing	provide	VERB
ajst-10988	33	26	effective	effective	ADJ
ajst-10988	33	27	tools	tool	NOUN
ajst-10988	33	28	and	and	CCONJ
ajst-10988	33	29	methods	method	NOUN
ajst-10988	33	30	for	for	ADP
ajst-10988	33	31	the	the	DET
ajst-10988	33	32	analysis	analysis	NOUN
ajst-10988	33	33	and	and	CCONJ
ajst-10988	33	34	resolution	resolution	NOUN
ajst-10988	33	35	of	of	ADP
ajst-10988	33	36	complex	complex	ADJ
ajst-10988	33	37	problems	problem	NOUN
ajst-10988	34	1	[	[	X
ajst-10988	34	2	yang	yang	PROPN
ajst-10988	34	3	z,2023	z,2023	PROPN
ajst-10988	34	4	]	]	PUNCT
ajst-10988	34	5	.	.	PUNCT
ajst-10988	35	1	2.2	2.2	NUM
ajst-10988	35	2	.	.	PUNCT
ajst-10988	36	1	learning	learn	VERB
ajst-10988	36	2	in	in	ADP
ajst-10988	36	3	bayesian	bayesian	NOUN
ajst-10988	36	4	networks	network	NOUN
ajst-10988	36	5	learning	learn	VERB
ajst-10988	36	6	in	in	ADP
ajst-10988	36	7	bayesian	bayesian	NOUN
ajst-10988	36	8	networks	network	NOUN
ajst-10988	36	9	refers	refer	VERB
ajst-10988	36	10	to	to	ADP
ajst-10988	36	11	the	the	DET
ajst-10988	36	12	process	process	NOUN
ajst-10988	36	13	of	of	ADP
ajst-10988	36	14	inferring	infer	VERB
ajst-10988	36	15	the	the	DET
ajst-10988	36	16	structure	structure	NOUN
ajst-10988	36	17	and	and	CCONJ
ajst-10988	36	18	parameters	parameter	NOUN
ajst-10988	36	19	of	of	ADP
ajst-10988	36	20	the	the	DET
ajst-10988	36	21	bayesian	bayesian	NOUN
ajst-10988	36	22	network	network	NOUN
ajst-10988	36	23	from	from	ADP
ajst-10988	36	24	observed	observed	ADJ
ajst-10988	36	25	data	datum	NOUN
ajst-10988	36	26	.	.	PUNCT
ajst-10988	37	1	the	the	DET
ajst-10988	37	2	goal	goal	NOUN
ajst-10988	37	3	of	of	ADP
ajst-10988	37	4	learning	learn	VERB
ajst-10988	37	5	bayesian	bayesian	NOUN
ajst-10988	37	6	networks	network	NOUN
ajst-10988	37	7	is	be	AUX
ajst-10988	37	8	to	to	PART
ajst-10988	37	9	obtain	obtain	VERB
ajst-10988	37	10	the	the	DET
ajst-10988	37	11	conditional	conditional	ADJ
ajst-10988	37	12	dependencies	dependency	NOUN
ajst-10988	37	13	between	between	ADP
ajst-10988	37	14	variables	variable	NOUN
ajst-10988	37	15	based	base	VERB
ajst-10988	37	16	on	on	ADP
ajst-10988	37	17	the	the	DET
ajst-10988	37	18	observed	observe	VERB
ajst-10988	37	19	data	datum	NOUN
ajst-10988	37	20	,	,	PUNCT
ajst-10988	37	21	thus	thus	ADV
ajst-10988	37	22	establishing	establish	VERB
ajst-10988	37	23	an	an	DET
ajst-10988	37	24	accurate	accurate	ADJ
ajst-10988	37	25	probabilistic	probabilistic	ADJ
ajst-10988	37	26	model	model	NOUN
ajst-10988	37	27	.	.	PUNCT
ajst-10988	38	1	the	the	DET
ajst-10988	38	2	process	process	NOUN
ajst-10988	38	3	of	of	ADP
ajst-10988	38	4	learning	learn	VERB
ajst-10988	38	5	bayesian	bayesian	NOUN
ajst-10988	38	6	networks	network	NOUN
ajst-10988	38	7	can	can	AUX
ajst-10988	38	8	be	be	AUX
ajst-10988	38	9	divided	divide	VERB
ajst-10988	38	10	into	into	ADP
ajst-10988	38	11	two	two	NUM
ajst-10988	38	12	parts	part	NOUN
ajst-10988	38	13	:	:	PUNCT
ajst-10988	38	14	structure	structure	NOUN
ajst-10988	38	15	learning	learning	NOUN
ajst-10988	38	16	and	and	CCONJ
ajst-10988	38	17	parameter	parameter	NOUN
ajst-10988	38	18	learning	learning	NOUN
ajst-10988	38	19	.	.	PUNCT
ajst-10988	39	1	the	the	DET
ajst-10988	39	2	objective	objective	NOUN
ajst-10988	39	3	of	of	ADP
ajst-10988	39	4	structure	structure	NOUN
ajst-10988	39	5	learning	learning	NOUN
ajst-10988	39	6	is	be	AUX
ajst-10988	39	7	to	to	PART
ajst-10988	39	8	determine	determine	VERB
ajst-10988	39	9	the	the	DET
ajst-10988	39	10	topology	topology	NOUN
ajst-10988	39	11	of	of	ADP
ajst-10988	39	12	the	the	DET
ajst-10988	39	13	bayesian	bayesian	NOUN
ajst-10988	39	14	network	network	NOUN
ajst-10988	39	15	,	,	PUNCT
ajst-10988	39	16	i.e.	i.e.	X
ajst-10988	39	17	,	,	PUNCT
ajst-10988	39	18	the	the	DET
ajst-10988	39	19	dependencies	dependency	NOUN
ajst-10988	39	20	between	between	ADP
ajst-10988	39	21	variables	variable	NOUN
ajst-10988	39	22	and	and	CCONJ
ajst-10988	39	23	the	the	DET
ajst-10988	39	24	connections	connection	NOUN
ajst-10988	39	25	of	of	ADP
ajst-10988	39	26	directed	direct	VERB
ajst-10988	39	27	edges	edge	NOUN
ajst-10988	39	28	.	.	PUNCT
ajst-10988	40	1	the	the	DET
ajst-10988	40	2	flowchart	flowchart	NOUN
ajst-10988	40	3	of	of	ADP
ajst-10988	40	4	structure	structure	NOUN
ajst-10988	40	5	learning	learning	NOUN
ajst-10988	40	6	is	be	AUX
ajst-10988	40	7	depicted	depict	VERB
ajst-10988	40	8	in	in	ADP
ajst-10988	40	9	figure	figure	NOUN
ajst-10988	40	10	2	2	NUM
ajst-10988	40	11	.	.	PUNCT
ajst-10988	40	12	figure	figure	NOUN
ajst-10988	40	13	2	2	NUM
ajst-10988	40	14	.	.	PUNCT
ajst-10988	40	15	flowchart	flowchart	NOUN
ajst-10988	40	16	of	of	ADP
ajst-10988	40	17	structure	structure	NOUN
ajst-10988	40	18	learning	learn	VERB
ajst-10988	40	19	the	the	DET
ajst-10988	40	20	goal	goal	NOUN
ajst-10988	40	21	of	of	ADP
ajst-10988	40	22	parameter	parameter	NOUN
ajst-10988	40	23	learning	learning	NOUN
ajst-10988	40	24	is	be	AUX
ajst-10988	40	25	to	to	PART
ajst-10988	40	26	estimate	estimate	VERB
ajst-10988	40	27	the	the	DET
ajst-10988	40	28	conditional	conditional	ADJ
ajst-10988	40	29	probability	probability	NOUN
ajst-10988	40	30	table	table	NOUN
ajst-10988	40	31	in	in	ADP
ajst-10988	40	32	a	a	DET
ajst-10988	40	33	bayesian	bayesian	NOUN
ajst-10988	40	34	network	network	NOUN
ajst-10988	40	35	based	base	VERB
ajst-10988	40	36	on	on	ADP
ajst-10988	40	37	the	the	DET
ajst-10988	40	38	observed	observe	VERB
ajst-10988	40	39	data	datum	NOUN
ajst-10988	40	40	.	.	PUNCT
ajst-10988	41	1	in	in	ADP
ajst-10988	41	2	figure	figure	NOUN
ajst-10988	41	3	2	2	NUM
ajst-10988	41	4	,	,	PUNCT
ajst-10988	41	5	parameter	parameter	NOUN
ajst-10988	41	6	learning	learning	NOUN
ajst-10988	41	7	can	can	AUX
ajst-10988	41	8	be	be	AUX
ajst-10988	41	9	carried	carry	VERB
ajst-10988	41	10	out	out	ADP
ajst-10988	41	11	after	after	SCONJ
ajst-10988	41	12	the	the	DET
ajst-10988	41	13	optimal	optimal	ADJ
ajst-10988	41	14	bayesian	bayesian	NOUN
ajst-10988	41	15	network	network	NOUN
ajst-10988	41	16	structure	structure	NOUN
ajst-10988	41	17	is	be	AUX
ajst-10988	41	18	obtained	obtain	VERB
ajst-10988	41	19	.	.	PUNCT
ajst-10988	42	1	at	at	ADP
ajst-10988	42	2	this	this	DET
ajst-10988	42	3	time	time	NOUN
ajst-10988	42	4	,	,	PUNCT
ajst-10988	42	5	the	the	DET
ajst-10988	42	6	model	model	NOUN
ajst-10988	42	7	is	be	AUX
ajst-10988	42	8	known	know	VERB
ajst-10988	42	9	and	and	CCONJ
ajst-10988	42	10	the	the	DET
ajst-10988	42	11	parameters	parameter	NOUN
ajst-10988	42	12	are	be	AUX
ajst-10988	42	13	not	not	PART
ajst-10988	42	14	determined	determine	VERB
ajst-10988	42	15	,	,	PUNCT
ajst-10988	42	16	so	so	SCONJ
ajst-10988	42	17	this	this	DET
ajst-10988	42	18	paper	paper	NOUN
ajst-10988	42	19	adopts	adopt	VERB
ajst-10988	42	20	the	the	DET
ajst-10988	42	21	method	method	NOUN
ajst-10988	42	22	of	of	ADP
ajst-10988	42	23	great	great	ADJ
ajst-10988	42	24	likelihood	likelihood	NOUN
ajst-10988	42	25	estimation	estimation	NOUN
ajst-10988	42	26	for	for	ADP
ajst-10988	42	27	parameter	parameter	NOUN
ajst-10988	42	28	learning	learning	NOUN
ajst-10988	42	29	.	.	PUNCT
ajst-10988	43	1	firstly	firstly	ADV
ajst-10988	43	2	,	,	PUNCT
ajst-10988	43	3	assume	assume	VERB
ajst-10988	43	4	a	a	DET
ajst-10988	43	5	certain	certain	ADJ
ajst-10988	43	6	but	but	CCONJ
ajst-10988	43	7	unknown	unknown	ADJ
ajst-10988	43	8	parameter	parameter	NOUN
ajst-10988	43	9	0	0	NUM
ajst-10988	43	10	,	,	PUNCT
ajst-10988	43	11	and	and	CCONJ
ajst-10988	43	12	secondly	secondly	ADV
ajst-10988	43	13	,	,	PUNCT
ajst-10988	43	14	carry	carry	VERB
ajst-10988	43	15	out	out	ADP
ajst-10988	43	16	maximum	maximum	ADJ
ajst-10988	43	17	likelihood	likelihood	NOUN
ajst-10988	43	18	parameter	parameter	NOUN
ajst-10988	43	19	estimation	estimation	NOUN
ajst-10988	43	20	on	on	ADP
ajst-10988	43	21	the	the	DET
ajst-10988	43	22	sample	sample	NOUN
ajst-10988	43	23	set	set	NOUN
ajst-10988	43	24	.	.	PUNCT
ajst-10988	44	1	remember	remember	VERB
ajst-10988	44	2	the	the	DET
ajst-10988	44	3	known	know	VERB
ajst-10988	44	4	sample	sample	NOUN
ajst-10988	44	5	set	set	NOUN
ajst-10988	44	6	is	be	AUX
ajst-10988	44	7	represented	represent	VERB
ajst-10988	44	8	as	as	SCONJ
ajst-10988	44	9	shown	show	VERB
ajst-10988	44	10	in	in	ADP
ajst-10988	44	11	equation	equation	NOUN
ajst-10988	44	12	(	(	PUNCT
ajst-10988	44	13	1	1	NUM
ajst-10988	44	14	):	):	PUNCT
ajst-10988	44	15	}	}	PUNCT
ajst-10988	44	16	,	,	PUNCT
ajst-10988	44	17	,	,	PUNCT
ajst-10988	44	18	,	,	PUNCT
ajst-10988	44	19	{	{	PUNCT
ajst-10988	44	20	21	21	NUM
ajst-10988	44	21	nxxxd	nxxxd	NOUN
ajst-10988	44	22	�	�	PROPN
ajst-10988	44	23			PROPN
ajst-10988	44	24	(	(	PUNCT
ajst-10988	44	25	1	1	NUM
ajst-10988	44	26	)	)	PUNCT
ajst-10988	44	27	then	then	ADV
ajst-10988	44	28	the	the	DET
ajst-10988	44	29	corresponding	corresponding	ADJ
ajst-10988	44	30	likelihood	likelihood	NOUN
ajst-10988	44	31	function	function	NOUN
ajst-10988	44	32	is	be	AUX
ajst-10988	44	33	expressed	express	VERB
ajst-10988	44	34	as	as	SCONJ
ajst-10988	44	35	shown	show	VERB
ajst-10988	44	36	in	in	ADP
ajst-10988	44	37	equation	equation	NOUN
ajst-10988	44	38	(	(	PUNCT
ajst-10988	44	39	2	2	NUM
ajst-10988	44	40	):	):	PUNCT
ajst-10988	44	41	51	51	NUM
ajst-10988	44	42			NUM
ajst-10988	44	43			NUM
ajst-10988	44	44			NUM
ajst-10988	44	45	n	n	NOUN
ajst-10988	44	46	i	i	PRON
ajst-10988	44	47	in	in	ADP
ajst-10988	44	48	xpxxxpl	xpxxxpl	PROPN
ajst-10988	44	49	1	1	NUM
ajst-10988	44	50	21	21	NUM
ajst-10988	44	51	)	)	PUNCT
ajst-10988	44	52	|()|	|()|	PROPN
ajst-10988	44	53	,	,	PUNCT
ajst-10988	44	54	,	,	PUNCT
ajst-10988	44	55	,	,	PUNCT
ajst-10988	44	56	(	(	PUNCT
ajst-10988	44	57	)	)	PUNCT
ajst-10988	44	58	(	(	PUNCT
ajst-10988	44	59			X
ajst-10988	44	60	�	�	PROPN
ajst-10988	44	61	(	(	PUNCT
ajst-10988	44	62	2	2	NUM
ajst-10988	44	63	)	)	PUNCT
ajst-10988	44	64	then	then	ADV
ajst-10988	44	65	solve	solve	VERB
ajst-10988	44	66	for	for	ADP
ajst-10988	44	67	the	the	DET
ajst-10988	44	68	parameter	parameter	NOUN
ajst-10988	44	69	that	that	PRON
ajst-10988	44	70	maximizes	maximize	VERB
ajst-10988	44	71	the	the	DET
ajst-10988	44	72	likelihood	likelihood	NOUN
ajst-10988	44	73	function	function	NOUN
ajst-10988	44	74	,	,	PUNCT
ajst-10988	44	75	which	which	PRON
ajst-10988	44	76	is	be	AUX
ajst-10988	44	77	expressed	express	VERB
ajst-10988	44	78	as	as	SCONJ
ajst-10988	44	79	shown	show	VERB
ajst-10988	44	80	in	in	ADP
ajst-10988	44	81	equation	equation	NOUN
ajst-10988	44	82	(	(	PUNCT
ajst-10988	44	83	3	3	NUM
ajst-10988	44	84	):	):	PUNCT
ajst-10988	44	85			NUM
ajst-10988	44	86			NUM
ajst-10988	44	87			NUM
ajst-10988	44	88	n	n	NOUN
ajst-10988	44	89	i	i	PRON
ajst-10988	44	90	ixpl	ixpl	VERB
ajst-10988	44	91	1	1	NUM
ajst-10988	44	92	)	)	PUNCT
ajst-10988	44	93	|(maxarg)(maxargˆ	|(maxarg)(maxargˆ	PROPN
ajst-10988	44	94			PUNCT
ajst-10988	44	95			PROPN
ajst-10988	44	96	(	(	PUNCT
ajst-10988	44	97	3	3	X
ajst-10988	44	98	)	)	PUNCT
ajst-10988	44	99	the	the	DET
ajst-10988	44	100	log	log	NOUN
ajst-10988	44	101	-	-	PUNCT
ajst-10988	44	102	likelihood	likelihood	NOUN
ajst-10988	44	103	function	function	NOUN
ajst-10988	44	104	is	be	AUX
ajst-10988	44	105	expressed	express	VERB
ajst-10988	44	106	as	as	SCONJ
ajst-10988	44	107	shown	show	VERB
ajst-10988	44	108	in	in	ADP
ajst-10988	44	109	equation	equation	NOUN
ajst-10988	44	110	(	(	PUNCT
ajst-10988	44	111	4	4	NUM
ajst-10988	44	112	):	):	PUNCT
ajst-10988	44	113			X
ajst-10988	44	114			NUM
ajst-10988	44	115			NUM
ajst-10988	45	1	n	n	CCONJ
ajst-10988	45	2	i	i	PRON
ajst-10988	45	3	ixplh	ixplh	VERB
ajst-10988	45	4	1	1	NUM
ajst-10988	45	5	)	)	PUNCT
ajst-10988	45	6	|(ln)(ln	|(ln)(ln	NOUN
ajst-10988	45	7	)	)	PUNCT
ajst-10988	45	8	(	(	PUNCT
ajst-10988	45	9			X
ajst-10988	45	10	(	(	PUNCT
ajst-10988	45	11	4	4	X
ajst-10988	45	12	)	)	PUNCT
ajst-10988	45	13	its	its	PRON
ajst-10988	45	14	results	result	NOUN
ajst-10988	45	15	after	after	SCONJ
ajst-10988	45	16	parameter	parameter	NOUN
ajst-10988	45	17	learning	learning	NOUN
ajst-10988	45	18	are	be	AUX
ajst-10988	45	19	shown	show	VERB
ajst-10988	45	20	in	in	ADP
ajst-10988	45	21	table	table	NOUN
ajst-10988	45	22	1	1	NUM
ajst-10988	45	23	:	:	PUNCT
ajst-10988	45	24	table	table	NOUN
ajst-10988	45	25	1	1	NUM
ajst-10988	45	26	.	.	PUNCT
ajst-10988	45	27	results	result	NOUN
ajst-10988	45	28	after	after	ADP
ajst-10988	45	29	parameter	parameter	NOUN
ajst-10988	45	30	learning	learn	VERB
ajst-10988	45	31	node	node	ADJ
ajst-10988	45	32	number	number	NOUN
ajst-10988	45	33	1(f	1(f	NUM
ajst-10988	45	34	)	)	PUNCT
ajst-10988	45	35	2(t	2(t	NUM
ajst-10988	45	36	)	)	PUNCT
ajst-10988	45	37	r1	r1	NOUN
ajst-10988	45	38	0.65	0.65	NUM
ajst-10988	45	39	0.35	0.35	NUM
ajst-10988	45	40	r2	r2	PROPN
ajst-10988	45	41	0.74	0.74	NUM
ajst-10988	45	42	0.26	0.26	NUM
ajst-10988	45	43	r3	r3	PROPN
ajst-10988	45	44	0.73	0.73	NUM
ajst-10988	45	45	0.27	0.27	NUM
ajst-10988	45	46	r4	r4	NOUN
ajst-10988	45	47	0.87	0.87	NUM
ajst-10988	45	48	0.13	0.13	NUM
ajst-10988	45	49	r5	r5	PROPN
ajst-10988	45	50	0.61	0.61	NUM
ajst-10988	45	51	0.39	0.39	NUM
ajst-10988	45	52	r6	r6	NOUN
ajst-10988	45	53	0.63	0.63	NUM
ajst-10988	45	54	0.37	0.37	NUM
ajst-10988	45	55	r7	r7	PROPN
ajst-10988	45	56	0.76	0.76	NUM
ajst-10988	45	57	0.24	0.24	NUM
ajst-10988	45	58	the	the	DET
ajst-10988	45	59	learning	learning	NOUN
ajst-10988	45	60	process	process	NOUN
ajst-10988	45	61	of	of	ADP
ajst-10988	45	62	bayesian	bayesian	NOUN
ajst-10988	45	63	networks	network	NOUN
ajst-10988	45	64	depends	depend	VERB
ajst-10988	45	65	on	on	ADP
ajst-10988	45	66	reliable	reliable	ADJ
ajst-10988	45	67	datasets	dataset	NOUN
ajst-10988	45	68	and	and	CCONJ
ajst-10988	45	69	appropriate	appropriate	ADJ
ajst-10988	45	70	learning	learning	NOUN
ajst-10988	45	71	algorithms	algorithm	NOUN
ajst-10988	45	72	.	.	PUNCT
ajst-10988	46	1	the	the	DET
ajst-10988	46	2	quality	quality	NOUN
ajst-10988	46	3	of	of	ADP
ajst-10988	46	4	the	the	DET
ajst-10988	46	5	dataset	dataset	NOUN
ajst-10988	46	6	is	be	AUX
ajst-10988	46	7	crucial	crucial	ADJ
ajst-10988	46	8	for	for	ADP
ajst-10988	46	9	the	the	DET
ajst-10988	46	10	accuracy	accuracy	NOUN
ajst-10988	46	11	of	of	ADP
ajst-10988	46	12	the	the	DET
ajst-10988	46	13	learning	learning	NOUN
ajst-10988	46	14	results	result	NOUN
ajst-10988	46	15	.	.	PUNCT
ajst-10988	47	1	additionally	additionally	ADV
ajst-10988	47	2	,	,	PUNCT
ajst-10988	47	3	the	the	DET
ajst-10988	47	4	choice	choice	NOUN
ajst-10988	47	5	of	of	ADP
ajst-10988	47	6	learning	learn	VERB
ajst-10988	47	7	algorithm	algorithm	NOUN
ajst-10988	47	8	also	also	ADV
ajst-10988	47	9	affects	affect	VERB
ajst-10988	47	10	the	the	DET
ajst-10988	47	11	effectiveness	effectiveness	NOUN
ajst-10988	47	12	and	and	CCONJ
ajst-10988	47	13	speed	speed	NOUN
ajst-10988	47	14	of	of	ADP
ajst-10988	47	15	learning	learn	VERB
ajst-10988	47	16	.	.	PUNCT
ajst-10988	48	1	different	different	ADJ
ajst-10988	48	2	learning	learning	NOUN
ajst-10988	48	3	algorithms	algorithm	NOUN
ajst-10988	48	4	are	be	AUX
ajst-10988	48	5	suitable	suitable	ADJ
ajst-10988	48	6	for	for	ADP
ajst-10988	48	7	different	different	ADJ
ajst-10988	48	8	learning	learning	NOUN
ajst-10988	48	9	scenarios	scenario	NOUN
ajst-10988	48	10	and	and	CCONJ
ajst-10988	48	11	data	datum	NOUN
ajst-10988	48	12	attributes	attribute	NOUN
ajst-10988	48	13	.	.	PUNCT
ajst-10988	49	1	learning	learn	VERB
ajst-10988	49	2	bayesian	bayesian	NOUN
ajst-10988	49	3	networks	network	NOUN
ajst-10988	49	4	is	be	AUX
ajst-10988	49	5	an	an	DET
ajst-10988	49	6	iterative	iterative	NOUN
ajst-10988	49	7	process	process	NOUN
ajst-10988	49	8	that	that	PRON
ajst-10988	49	9	requires	require	VERB
ajst-10988	49	10	continuous	continuous	ADJ
ajst-10988	49	11	optimization	optimization	NOUN
ajst-10988	49	12	and	and	CCONJ
ajst-10988	49	13	adjustment	adjustment	NOUN
ajst-10988	49	14	of	of	ADP
ajst-10988	49	15	the	the	DET
ajst-10988	49	16	network	network	NOUN
ajst-10988	49	17	.	.	PUNCT
ajst-10988	50	1	by	by	ADP
ajst-10988	50	2	learning	learn	VERB
ajst-10988	50	3	bayesian	bayesian	NOUN
ajst-10988	50	4	networks	network	NOUN
ajst-10988	50	5	,	,	PUNCT
ajst-10988	50	6	we	we	PRON
ajst-10988	50	7	can	can	AUX
ajst-10988	50	8	capture	capture	VERB
ajst-10988	50	9	the	the	DET
ajst-10988	50	10	dependencies	dependency	NOUN
ajst-10988	50	11	between	between	ADP
ajst-10988	50	12	variables	variable	NOUN
ajst-10988	50	13	from	from	ADP
ajst-10988	50	14	data	datum	NOUN
ajst-10988	50	15	and	and	CCONJ
ajst-10988	50	16	utilize	utilize	VERB
ajst-10988	50	17	these	these	DET
ajst-10988	50	18	dependencies	dependency	NOUN
ajst-10988	50	19	for	for	ADP
ajst-10988	50	20	probabilistic	probabilistic	ADJ
ajst-10988	50	21	inference	inference	NOUN
ajst-10988	50	22	and	and	CCONJ
ajst-10988	50	23	prediction	prediction	NOUN
ajst-10988	50	24	.	.	PUNCT
ajst-10988	51	1	the	the	DET
ajst-10988	51	2	learning	learning	NOUN
ajst-10988	51	3	of	of	ADP
ajst-10988	51	4	bayesian	bayesian	NOUN
ajst-10988	51	5	networks	network	NOUN
ajst-10988	51	6	holds	hold	VERB
ajst-10988	51	7	significant	significant	ADJ
ajst-10988	51	8	applications	application	NOUN
ajst-10988	51	9	and	and	CCONJ
ajst-10988	51	10	research	research	NOUN
ajst-10988	51	11	value	value	NOUN
ajst-10988	51	12	in	in	ADP
ajst-10988	51	13	fields	field	NOUN
ajst-10988	51	14	such	such	ADJ
ajst-10988	51	15	as	as	ADP
ajst-10988	51	16	data	datum	NOUN
ajst-10988	51	17	mining	mining	NOUN
ajst-10988	51	18	,	,	PUNCT
ajst-10988	51	19	data	datum	NOUN
ajst-10988	51	20	analysis	analysis	NOUN
ajst-10988	51	21	,	,	PUNCT
ajst-10988	51	22	and	and	CCONJ
ajst-10988	51	23	artificial	artificial	ADJ
ajst-10988	51	24	intelligence	intelligence	NOUN
ajst-10988	51	25	[	[	X
ajst-10988	51	26	doyeob	doyeob	NOUN
ajst-10988	51	27	y,2020	y,2020	NOUN
ajst-10988	51	28	]	]	PUNCT
ajst-10988	51	29	.	.	PUNCT
ajst-10988	52	1	2.3	2.3	NUM
ajst-10988	52	2	.	.	PUNCT
ajst-10988	52	3	inference	inference	NOUN
ajst-10988	52	4	in	in	ADP
ajst-10988	52	5	bayesian	bayesian	NOUN
ajst-10988	52	6	networks	network	NOUN
ajst-10988	52	7	inference	inference	NOUN
ajst-10988	52	8	in	in	ADP
ajst-10988	52	9	bayesian	bayesian	NOUN
ajst-10988	52	10	networks	network	NOUN
ajst-10988	52	11	refers	refer	VERB
ajst-10988	52	12	to	to	ADP
ajst-10988	52	13	the	the	DET
ajst-10988	52	14	process	process	NOUN
ajst-10988	52	15	of	of	ADP
ajst-10988	52	16	calculating	calculate	VERB
ajst-10988	52	17	the	the	DET
ajst-10988	52	18	probability	probability	NOUN
ajst-10988	52	19	distribution	distribution	NOUN
ajst-10988	52	20	of	of	ADP
ajst-10988	52	21	unknown	unknown	ADJ
ajst-10988	52	22	variables	variable	NOUN
ajst-10988	52	23	based	base	VERB
ajst-10988	52	24	on	on	ADP
ajst-10988	52	25	known	know	VERB
ajst-10988	52	26	observed	observe	VERB
ajst-10988	52	27	data	datum	NOUN
ajst-10988	52	28	and	and	CCONJ
ajst-10988	52	29	the	the	DET
ajst-10988	52	30	model	model	NOUN
ajst-10988	52	31	.	.	PUNCT
ajst-10988	53	1	through	through	ADP
ajst-10988	53	2	inference	inference	NOUN
ajst-10988	53	3	in	in	ADP
ajst-10988	53	4	bayesian	bayesian	NOUN
ajst-10988	53	5	networks	network	NOUN
ajst-10988	53	6	,	,	PUNCT
ajst-10988	53	7	we	we	PRON
ajst-10988	53	8	can	can	AUX
ajst-10988	53	9	use	use	VERB
ajst-10988	53	10	the	the	DET
ajst-10988	53	11	observed	observe	VERB
ajst-10988	53	12	variables	variable	NOUN
ajst-10988	53	13	to	to	PART
ajst-10988	53	14	infer	infer	VERB
ajst-10988	53	15	the	the	DET
ajst-10988	53	16	posterior	posterior	ADJ
ajst-10988	53	17	probability	probability	NOUN
ajst-10988	53	18	distribution	distribution	NOUN
ajst-10988	53	19	of	of	ADP
ajst-10988	53	20	other	other	ADJ
ajst-10988	53	21	variables	variable	NOUN
ajst-10988	53	22	,	,	PUNCT
ajst-10988	53	23	enabling	enable	VERB
ajst-10988	53	24	probabilistic	probabilistic	ADJ
ajst-10988	53	25	inference	inference	NOUN
ajst-10988	53	26	and	and	CCONJ
ajst-10988	53	27	prediction	prediction	NOUN
ajst-10988	53	28	.	.	PUNCT
ajst-10988	54	1	in	in	ADP
ajst-10988	54	2	this	this	DET
ajst-10988	54	3	paper	paper	NOUN
ajst-10988	54	4	,	,	PUNCT
ajst-10988	54	5	the	the	DET
ajst-10988	54	6	variable	variable	ADJ
ajst-10988	54	7	elimination	elimination	NOUN
ajst-10988	54	8	algorithm	algorithm	NOUN
ajst-10988	54	9	(	(	PUNCT
ajst-10988	54	10	as	as	SCONJ
ajst-10988	54	11	shown	show	VERB
ajst-10988	54	12	in	in	ADP
ajst-10988	54	13	figure	figure	NOUN
ajst-10988	54	14	3	3	NUM
ajst-10988	54	15	)	)	PUNCT
ajst-10988	54	16	is	be	AUX
ajst-10988	54	17	adopted	adopt	VERB
ajst-10988	54	18	for	for	ADP
ajst-10988	54	19	the	the	DET
ajst-10988	54	20	fault	fault	NOUN
ajst-10988	54	21	diagnosis	diagnosis	NOUN
ajst-10988	54	22	and	and	CCONJ
ajst-10988	54	23	warning	warning	NOUN
ajst-10988	54	24	inference	inference	NOUN
ajst-10988	54	25	of	of	ADP
ajst-10988	54	26	the	the	DET
ajst-10988	54	27	subway	subway	NOUN
ajst-10988	54	28	braking	brake	VERB
ajst-10988	54	29	system	system	NOUN
ajst-10988	54	30	.	.	PUNCT
ajst-10988	55	1	figure	figure	NOUN
ajst-10988	55	2	3	3	NUM
ajst-10988	55	3	.	.	NOUN
ajst-10988	55	4	example	example	NOUN
ajst-10988	55	5	of	of	ADP
ajst-10988	55	6	variable	variable	ADJ
ajst-10988	55	7	elimination	elimination	NOUN
ajst-10988	55	8	method	method	NOUN
ajst-10988	55	9	as	as	SCONJ
ajst-10988	55	10	shown	show	VERB
ajst-10988	55	11	in	in	ADP
ajst-10988	55	12	the	the	DET
ajst-10988	55	13	figure	figure	NOUN
ajst-10988	55	14	,	,	PUNCT
ajst-10988	55	15	assuming	assume	VERB
ajst-10988	55	16	that	that	SCONJ
ajst-10988	55	17	the	the	DET
ajst-10988	55	18	goal	goal	NOUN
ajst-10988	55	19	of	of	ADP
ajst-10988	55	20	reasoning	reasoning	NOUN
ajst-10988	55	21	in	in	ADP
ajst-10988	55	22	this	this	DET
ajst-10988	55	23	network	network	NOUN
ajst-10988	55	24	is	be	AUX
ajst-10988	55	25	computation	computation	NOUN
ajst-10988	55	26	,	,	PUNCT
ajst-10988	55	27	it	it	PRON
ajst-10988	55	28	is	be	AUX
ajst-10988	55	29	specified	specify	VERB
ajst-10988	55	30	as	as	SCONJ
ajst-10988	55	31	shown	show	VERB
ajst-10988	55	32	in	in	ADP
ajst-10988	55	33	equation	equation	NOUN
ajst-10988	55	34	(	(	PUNCT
ajst-10988	55	35	5	5	NUM
ajst-10988	55	36	):	):	PUNCT
ajst-10988	55	37			X
ajst-10988	55	38			X
ajst-10988	56	1			NUM
ajst-10988	56	2			PROPN
ajst-10988	56	3	dcb	dcb	PROPN
ajst-10988	56	4	dcb	dcb	PROPN
ajst-10988	56	5	bapcbpdcpdp	bapcbpdcpdp	PROPN
ajst-10988	56	6	dcbapap	dcbapap	INTJ
ajst-10988	56	7	,	,	PUNCT
ajst-10988	56	8	,	,	PUNCT
ajst-10988	56	9	,	,	PUNCT
ajst-10988	56	10	,	,	PUNCT
ajst-10988	56	11	)	)	PUNCT
ajst-10988	56	12	|()|()|	|()|()|	NOUN
ajst-10988	56	13	(	(	PUNCT
ajst-10988	56	14	)	)	PUNCT
ajst-10988	56	15	(	(	PUNCT
ajst-10988	56	16	)	)	PUNCT
ajst-10988	56	17	,	,	PUNCT
ajst-10988	56	18	,	,	PUNCT
ajst-10988	56	19	,	,	PUNCT
ajst-10988	56	20	(	(	PUNCT
ajst-10988	56	21	)	)	PUNCT
ajst-10988	56	22	(	(	PUNCT
ajst-10988	56	23	(	(	PUNCT
ajst-10988	56	24	5	5	X
ajst-10988	56	25	)	)	PUNCT
ajst-10988	56	26	equation	equation	NOUN
ajst-10988	56	27	(	(	PUNCT
ajst-10988	56	28	5	5	X
ajst-10988	56	29	)	)	PUNCT
ajst-10988	56	30	can	can	AUX
ajst-10988	56	31	be	be	AUX
ajst-10988	56	32	rewritten	rewrite	VERB
ajst-10988	56	33	as	as	ADP
ajst-10988	56	34	equation	equation	NOUN
ajst-10988	56	35	(	(	PUNCT
ajst-10988	56	36	6	6	NUM
ajst-10988	56	37	)	)	PUNCT
ajst-10988	56	38	if	if	SCONJ
ajst-10988	56	39	the	the	DET
ajst-10988	56	40	sequential	sequential	ADJ
ajst-10988	56	41	calculations	calculation	NOUN
ajst-10988	56	42	used	use	VERB
ajst-10988	56	43	sum	sum	VERB
ajst-10988	56	44	the	the	DET
ajst-10988	56	45	results	result	NOUN
ajst-10988	56	46	of	of	ADP
ajst-10988	56	47	the	the	DET
ajst-10988	56	48	factorization	factorization	NOUN
ajst-10988	56	49	associated	associate	VERB
ajst-10988	56	50	with	with	ADP
ajst-10988	56	51	each	each	DET
ajst-10988	56	52	variable	variable	NOUN
ajst-10988	56	53	separately	separately	ADV
ajst-10988	56	54	:	:	PUNCT
ajst-10988	56	55	)	)	PUNCT
ajst-10988	56	56	(	(	PUNCT
ajst-10988	56	57	)	)	PUNCT
ajst-10988	56	58	(	(	PUNCT
ajst-10988	56	59	)	)	PUNCT
ajst-10988	56	60	|	|	ADV
ajst-10988	56	61	(	(	PUNCT
ajst-10988	56	62	)	)	PUNCT
ajst-10988	56	63	(	(	PUNCT
ajst-10988	56	64	)	)	PUNCT
ajst-10988	56	65	|()|	|()|	PROPN
ajst-10988	56	66	(	(	PUNCT
ajst-10988	56	67	)	)	PUNCT
ajst-10988	56	68	|()()|()|	|()()|()|	PROPN
ajst-10988	56	69	(	(	PUNCT
ajst-10988	56	70	)	)	PUNCT
ajst-10988	56	71	(	(	PUNCT
ajst-10988	56	72	3	3	NUM
ajst-10988	56	73	2	2	NUM
ajst-10988	56	74	1	1	NUM
ajst-10988	56	75	am	be	AUX
ajst-10988	57	1	bmbap	bmbap	NOUN
ajst-10988	57	2	cmcbpbap	cmcbpbap	PROPN
ajst-10988	57	3	dcpdpcbpbapap	dcpdpcbpbapap	VERB
ajst-10988	57	4	a	a	DET
ajst-10988	57	5	cb	cb	PROPN
ajst-10988	57	6	dcc	dcc	PROPN
ajst-10988	57	7			PROPN
ajst-10988	58	1			NUM
ajst-10988	59	1			NUM
ajst-10988	60	1			NOUN
ajst-10988	60	2			X
ajst-10988	61	1			PRON
ajst-10988	61	2			PROPN
ajst-10988	61	3	(	(	PUNCT
ajst-10988	61	4	6	6	NUM
ajst-10988	61	5	)	)	PUNCT
ajst-10988	61	6	where	where	SCONJ
ajst-10988	61	7	,	,	PUNCT
ajst-10988	61	8	denotes	denote	VERB
ajst-10988	61	9	the	the	DET
ajst-10988	61	10	intermediate	intermediate	ADJ
ajst-10988	61	11	result	result	NOUN
ajst-10988	61	12	obtained	obtain	VERB
ajst-10988	61	13	in	in	ADP
ajst-10988	61	14	the	the	DET
ajst-10988	61	15	first	first	ADJ
ajst-10988	61	16	summation	summation	NOUN
ajst-10988	61	17	calculation	calculation	NOUN
ajst-10988	61	18	,	,	PUNCT
ajst-10988	61	19	which	which	PRON
ajst-10988	61	20	is	be	AUX
ajst-10988	61	21	only	only	ADV
ajst-10988	61	22	related	relate	VERB
ajst-10988	61	23	to	to	ADP
ajst-10988	61	24	the	the	DET
ajst-10988	61	25	variables	variable	NOUN
ajst-10988	61	26	.	.	PUNCT
ajst-10988	62	1	when	when	SCONJ
ajst-10988	62	2	the	the	DET
ajst-10988	62	3	above	above	ADJ
ajst-10988	62	4	formula	formula	NOUN
ajst-10988	62	5	is	be	AUX
ajst-10988	62	6	used	use	VERB
ajst-10988	62	7	,	,	PUNCT
ajst-10988	62	8	the	the	DET
ajst-10988	62	9	number	number	NOUN
ajst-10988	62	10	of	of	ADP
ajst-10988	62	11	product	product	NOUN
ajst-10988	62	12	and	and	CCONJ
ajst-10988	62	13	summation	summation	NOUN
ajst-10988	62	14	calculations	calculation	NOUN
ajst-10988	62	15	are	be	AUX
ajst-10988	62	16	reduced	reduce	VERB
ajst-10988	62	17	,	,	PUNCT
ajst-10988	62	18	and	and	CCONJ
ajst-10988	62	19	the	the	DET
ajst-10988	62	20	reasoning	reasoning	NOUN
ajst-10988	62	21	process	process	NOUN
ajst-10988	62	22	is	be	AUX
ajst-10988	62	23	effectively	effectively	ADV
ajst-10988	62	24	simplified	simplify	VERB
ajst-10988	62	25	.	.	PUNCT
ajst-10988	63	1	3	3	X
ajst-10988	63	2	.	.	X
ajst-10988	63	3	train	train	NOUN
ajst-10988	63	4	brake	brake	NOUN
ajst-10988	63	5	system	system	NOUN
ajst-10988	63	6	pipe	pipe	NOUN
ajst-10988	63	7	leakage	leakage	NOUN
ajst-10988	63	8	detection	detection	NOUN
ajst-10988	63	9	model	model	NOUN
ajst-10988	63	10	based	base	VERB
ajst-10988	63	11	on	on	ADP
ajst-10988	63	12	bayesian	bayesian	NOUN
ajst-10988	63	13	networks	network	NOUN
ajst-10988	63	14	bayesian	bayesian	NOUN
ajst-10988	63	15	network	network	NOUN
ajst-10988	63	16	based	base	VERB
ajst-10988	63	17	pipe	pipe	NOUN
ajst-10988	63	18	leakage	leakage	NOUN
ajst-10988	63	19	detection	detection	NOUN
ajst-10988	63	20	model	model	NOUN
ajst-10988	63	21	for	for	ADP
ajst-10988	63	22	train	train	NOUN
ajst-10988	63	23	braking	braking	NOUN
ajst-10988	63	24	system	system	NOUN
ajst-10988	63	25	is	be	AUX
ajst-10988	63	26	a	a	DET
ajst-10988	63	27	method	method	NOUN
ajst-10988	63	28	of	of	ADP
ajst-10988	63	29	modeling	modeling	NOUN
ajst-10988	63	30	and	and	CCONJ
ajst-10988	63	31	reasoning	reasoning	NOUN
ajst-10988	63	32	using	use	VERB
ajst-10988	63	33	bayesian	bayesian	NOUN
ajst-10988	63	34	network	network	NOUN
ajst-10988	63	35	for	for	ADP
ajst-10988	63	36	detecting	detect	VERB
ajst-10988	63	37	pipe	pipe	NOUN
ajst-10988	63	38	leakage	leakage	NOUN
ajst-10988	63	39	problem	problem	NOUN
ajst-10988	63	40	in	in	ADP
ajst-10988	63	41	train	train	NOUN
ajst-10988	63	42	braking	braking	NOUN
ajst-10988	63	43	system	system	NOUN
ajst-10988	63	44	.	.	PUNCT
ajst-10988	64	1	the	the	DET
ajst-10988	64	2	simplified	simplified	ADJ
ajst-10988	64	3	model	model	NOUN
ajst-10988	64	4	diagram	diagram	NOUN
ajst-10988	64	5	of	of	ADP
ajst-10988	64	6	the	the	DET
ajst-10988	64	7	subway	subway	NOUN
ajst-10988	64	8	train	train	NOUN
ajst-10988	64	9	braking	brake	VERB
ajst-10988	64	10	system	system	NOUN
ajst-10988	64	11	is	be	AUX
ajst-10988	64	12	shown	show	VERB
ajst-10988	64	13	in	in	ADP
ajst-10988	64	14	figure	figure	NOUN
ajst-10988	64	15	4	4	NUM
ajst-10988	64	16	:	:	PUNCT
ajst-10988	64	17	the	the	DET
ajst-10988	64	18	model	model	NOUN
ajst-10988	64	19	first	first	ADV
ajst-10988	64	20	establishes	establish	VERB
ajst-10988	64	21	a	a	DET
ajst-10988	64	22	bayesian	bayesian	NOUN
ajst-10988	64	23	network	network	NOUN
ajst-10988	64	24	,	,	PUNCT
ajst-10988	64	25	where	where	SCONJ
ajst-10988	64	26	nodes	node	NOUN
ajst-10988	64	27	represent	represent	VERB
ajst-10988	64	28	different	different	ADJ
ajst-10988	64	29	components	component	NOUN
ajst-10988	64	30	or	or	CCONJ
ajst-10988	64	31	sensors	sensor	NOUN
ajst-10988	64	32	in	in	ADP
ajst-10988	64	33	the	the	DET
ajst-10988	64	34	train	train	NOUN
ajst-10988	64	35	braking	brake	VERB
ajst-10988	64	36	system	system	NOUN
ajst-10988	64	37	,	,	PUNCT
ajst-10988	64	38	and	and	CCONJ
ajst-10988	64	39	edges	edge	NOUN
ajst-10988	64	40	represent	represent	VERB
ajst-10988	64	41	the	the	DET
ajst-10988	64	42	dependencies	dependency	NOUN
ajst-10988	64	43	between	between	ADP
ajst-10988	64	44	components	component	NOUN
ajst-10988	64	45	.	.	PUNCT
ajst-10988	65	1	for	for	ADP
ajst-10988	65	2	example	example	NOUN
ajst-10988	65	3	,	,	PUNCT
ajst-10988	65	4	nodes	node	NOUN
ajst-10988	65	5	can	can	AUX
ajst-10988	65	6	represent	represent	VERB
ajst-10988	65	7	the	the	DET
ajst-10988	65	8	brake	brake	NOUN
ajst-10988	65	9	pipeline	pipeline	NOUN
ajst-10988	65	10	,	,	PUNCT
ajst-10988	65	11	pressure	pressure	NOUN
ajst-10988	65	12	sensors	sensor	NOUN
ajst-10988	65	13	,	,	PUNCT
ajst-10988	65	14	and	and	CCONJ
ajst-10988	65	15	brake	brake	NOUN
ajst-10988	65	16	pistons	piston	NOUN
ajst-10988	65	17	.	.	PUNCT
ajst-10988	66	1	during	during	ADP
ajst-10988	66	2	the	the	DET
ajst-10988	66	3	training	training	NOUN
ajst-10988	66	4	phase	phase	NOUN
ajst-10988	66	5	of	of	ADP
ajst-10988	66	6	the	the	DET
ajst-10988	66	7	model	model	NOUN
ajst-10988	66	8	,	,	PUNCT
ajst-10988	66	9	the	the	DET
ajst-10988	66	10	structure	structure	NOUN
ajst-10988	66	11	and	and	CCONJ
ajst-10988	66	12	parameters	parameter	NOUN
ajst-10988	66	13	of	of	ADP
ajst-10988	66	14	the	the	DET
ajst-10988	66	15	bayesian	bayesian	NOUN
ajst-10988	66	16	network	network	NOUN
ajst-10988	66	17	need	need	VERB
ajst-10988	66	18	to	to	PART
ajst-10988	66	19	be	be	AUX
ajst-10988	66	20	learned	learn	VERB
ajst-10988	66	21	from	from	ADP
ajst-10988	66	22	the	the	DET
ajst-10988	66	23	observed	observe	VERB
ajst-10988	66	24	data	datum	NOUN
ajst-10988	66	25	.	.	PUNCT
ajst-10988	67	1	the	the	DET
ajst-10988	67	2	objective	objective	NOUN
ajst-10988	67	3	of	of	ADP
ajst-10988	67	4	structure	structure	NOUN
ajst-10988	67	5	learning	learning	NOUN
ajst-10988	67	6	is	be	AUX
ajst-10988	67	7	to	to	PART
ajst-10988	67	8	determine	determine	VERB
ajst-10988	67	9	the	the	DET
ajst-10988	67	10	network	network	NOUN
ajst-10988	67	11	's	's	PART
ajst-10988	67	12	topology	topology	NOUN
ajst-10988	67	13	,	,	PUNCT
ajst-10988	67	14	i.e.	i.e.	X
ajst-10988	67	15	,	,	PUNCT
ajst-10988	67	16	the	the	DET
ajst-10988	67	17	dependencies	dependency	NOUN
ajst-10988	67	18	and	and	CCONJ
ajst-10988	67	19	connections	connection	NOUN
ajst-10988	67	20	between	between	ADP
ajst-10988	67	21	nodes	node	NOUN
ajst-10988	67	22	.	.	PUNCT
ajst-10988	68	1	the	the	DET
ajst-10988	68	2	objective	objective	NOUN
ajst-10988	68	3	of	of	ADP
ajst-10988	68	4	parameter	parameter	NOUN
ajst-10988	68	5	learning	learning	NOUN
ajst-10988	68	6	is	be	AUX
ajst-10988	68	7	to	to	PART
ajst-10988	68	8	estimate	estimate	VERB
ajst-10988	68	9	the	the	DET
ajst-10988	68	10	conditional	conditional	ADJ
ajst-10988	68	11	probability	probability	NOUN
ajst-10988	68	12	tables	table	NOUN
ajst-10988	68	13	between	between	ADP
ajst-10988	68	14	nodes	node	NOUN
ajst-10988	68	15	,	,	PUNCT
ajst-10988	68	16	representing	represent	VERB
ajst-10988	68	17	the	the	DET
ajst-10988	68	18	state	state	NOUN
ajst-10988	68	19	distribution	distribution	NOUN
ajst-10988	68	20	of	of	ADP
ajst-10988	68	21	nodes	node	NOUN
ajst-10988	68	22	given	give	VERB
ajst-10988	68	23	the	the	DET
ajst-10988	68	24	states	state	NOUN
ajst-10988	68	25	of	of	ADP
ajst-10988	68	26	their	their	PRON
ajst-10988	68	27	parent	parent	NOUN
ajst-10988	68	28	nodes	nod	VERB
ajst-10988	68	29	.	.	PUNCT
ajst-10988	69	1	once	once	SCONJ
ajst-10988	69	2	the	the	DET
ajst-10988	69	3	model	model	NOUN
ajst-10988	69	4	is	be	AUX
ajst-10988	69	5	trained	train	VERB
ajst-10988	69	6	,	,	PUNCT
ajst-10988	69	7	inference	inference	NOUN
ajst-10988	69	8	can	can	AUX
ajst-10988	69	9	be	be	AUX
ajst-10988	69	10	performed	perform	VERB
ajst-10988	69	11	using	use	VERB
ajst-10988	69	12	the	the	DET
ajst-10988	69	13	observed	observed	ADJ
ajst-10988	69	14	data	datum	NOUN
ajst-10988	69	15	.	.	PUNCT
ajst-10988	70	1	when	when	SCONJ
ajst-10988	70	2	the	the	DET
ajst-10988	70	3	train	train	NOUN
ajst-10988	70	4	braking	brake	VERB
ajst-10988	70	5	system	system	NOUN
ajst-10988	70	6	is	be	AUX
ajst-10988	70	7	operational	operational	ADJ
ajst-10988	70	8	,	,	PUNCT
ajst-10988	70	9	the	the	DET
ajst-10988	70	10	model	model	NOUN
ajst-10988	70	11	receives	receive	VERB
ajst-10988	70	12	real	real	ADJ
ajst-10988	70	13	-	-	PUNCT
ajst-10988	70	14	time	time	NOUN
ajst-10988	70	15	data	datum	NOUN
ajst-10988	70	16	from	from	ADP
ajst-10988	70	17	sensors	sensor	NOUN
ajst-10988	70	18	,	,	PUNCT
ajst-10988	70	19	such	such	ADJ
ajst-10988	70	20	as	as	ADP
ajst-10988	70	21	the	the	DET
ajst-10988	70	22	pressure	pressure	NOUN
ajst-10988	70	23	values	value	NOUN
ajst-10988	70	24	in	in	ADP
ajst-10988	70	25	different	different	ADJ
ajst-10988	70	26	pipelines	pipeline	NOUN
ajst-10988	70	27	.	.	PUNCT
ajst-10988	71	1	the	the	DET
ajst-10988	71	2	model	model	NOUN
ajst-10988	71	3	,	,	PUNCT
ajst-10988	71	4	utilizing	utilize	VERB
ajst-10988	71	5	bayesian	bayesian	NOUN
ajst-10988	71	6	inference	inference	NOUN
ajst-10988	71	7	,	,	PUNCT
ajst-10988	71	8	calculates	calculate	VERB
ajst-10988	71	9	the	the	DET
ajst-10988	71	10	posterior	posterior	ADJ
ajst-10988	71	11	probability	probability	NOUN
ajst-10988	71	12	distribution	distribution	NOUN
ajst-10988	71	13	of	of	ADP
ajst-10988	71	14	the	the	DET
ajst-10988	71	15	nodes	node	NOUN
ajst-10988	71	16	based	base	VERB
ajst-10988	71	17	on	on	ADP
ajst-10988	71	18	this	this	DET
ajst-10988	71	19	data	data	NOUN
ajst-10988	71	20	.	.	PUNCT
ajst-10988	72	1	by	by	ADP
ajst-10988	72	2	analyzing	analyze	VERB
ajst-10988	72	3	the	the	DET
ajst-10988	72	4	posterior	posterior	ADJ
ajst-10988	72	5	probabilities	probability	NOUN
ajst-10988	72	6	,	,	PUNCT
ajst-10988	72	7	it	it	PRON
ajst-10988	72	8	is	be	AUX
ajst-10988	72	9	possible	possible	ADJ
ajst-10988	72	10	to	to	PART
ajst-10988	72	11	determine	determine	VERB
ajst-10988	72	12	the	the	DET
ajst-10988	72	13	presence	presence	NOUN
ajst-10988	72	14	of	of	ADP
ajst-10988	72	15	pipeline	pipeline	NOUN
ajst-10988	72	16	leaks	leak	NOUN
ajst-10988	72	17	,	,	PUNCT
ajst-10988	72	18	as	as	ADV
ajst-10988	72	19	well	well	ADV
ajst-10988	72	20	as	as	ADP
ajst-10988	72	21	their	their	PRON
ajst-10988	72	22	location	location	NOUN
ajst-10988	72	23	and	and	CCONJ
ajst-10988	72	24	severity	severity	NOUN
ajst-10988	72	25	.	.	PUNCT
ajst-10988	73	1	the	the	DET
ajst-10988	73	2	advantage	advantage	NOUN
ajst-10988	73	3	of	of	ADP
ajst-10988	73	4	this	this	DET
ajst-10988	73	5	model	model	NOUN
ajst-10988	73	6	is	be	AUX
ajst-10988	73	7	its	its	PRON
ajst-10988	73	8	ability	ability	NOUN
ajst-10988	73	9	to	to	PART
ajst-10988	73	10	accurately	accurately	ADV
ajst-10988	73	11	infer	infer	VERB
ajst-10988	73	12	the	the	DET
ajst-10988	73	13	existence	existence	NOUN
ajst-10988	73	14	of	of	ADP
ajst-10988	73	15	pipeline	pipeline	NOUN
ajst-10988	73	16	leaks	leak	NOUN
ajst-10988	73	17	in	in	ADP
ajst-10988	73	18	the	the	DET
ajst-10988	73	19	train	train	NOUN
ajst-10988	73	20	braking	brake	VERB
ajst-10988	73	21	system	system	NOUN
ajst-10988	73	22	using	use	VERB
ajst-10988	73	23	existing	exist	VERB
ajst-10988	73	24	knowledge	knowledge	NOUN
ajst-10988	73	25	and	and	CCONJ
ajst-10988	73	26	observed	observed	ADJ
ajst-10988	73	27	data	datum	NOUN
ajst-10988	73	28	.	.	PUNCT
ajst-10988	74	1	by	by	ADP
ajst-10988	74	2	monitoring	monitor	VERB
ajst-10988	74	3	and	and	CCONJ
ajst-10988	74	4	diagnosing	diagnose	VERB
ajst-10988	74	5	in	in	ADP
ajst-10988	74	6	real	real	ADJ
ajst-10988	74	7	-	-	PUNCT
ajst-10988	74	8	time	time	NOUN
ajst-10988	74	9	,	,	PUNCT
ajst-10988	74	10	appropriate	appropriate	ADJ
ajst-10988	74	11	measures	measure	NOUN
ajst-10988	74	12	can	can	AUX
ajst-10988	74	13	be	be	AUX
ajst-10988	74	14	taken	take	VERB
ajst-10988	74	15	promptly	promptly	ADV
ajst-10988	74	16	to	to	PART
ajst-10988	74	17	repair	repair	VERB
ajst-10988	74	18	any	any	DET
ajst-10988	74	19	leaks	leak	NOUN
ajst-10988	74	20	,	,	PUNCT
ajst-10988	74	21	ensuring	ensure	VERB
ajst-10988	74	22	the	the	DET
ajst-10988	74	23	normal	normal	ADJ
ajst-10988	74	24	operation	operation	NOUN
ajst-10988	74	25	of	of	ADP
ajst-10988	74	26	the	the	DET
ajst-10988	74	27	train	train	NOUN
ajst-10988	74	28	braking	brake	VERB
ajst-10988	74	29	system	system	NOUN
ajst-10988	74	30	and	and	CCONJ
ajst-10988	74	31	the	the	DET
ajst-10988	74	32	safety	safety	NOUN
ajst-10988	74	33	of	of	ADP
ajst-10988	74	34	52	52	NUM
ajst-10988	74	35	passengers	passenger	NOUN
ajst-10988	74	36	.	.	PUNCT
ajst-10988	75	1	however	however	ADV
ajst-10988	75	2	,	,	PUNCT
ajst-10988	75	3	the	the	DET
ajst-10988	75	4	accuracy	accuracy	NOUN
ajst-10988	75	5	and	and	CCONJ
ajst-10988	75	6	performance	performance	NOUN
ajst-10988	75	7	of	of	ADP
ajst-10988	75	8	the	the	DET
ajst-10988	75	9	model	model	NOUN
ajst-10988	75	10	are	be	AUX
ajst-10988	75	11	also	also	ADV
ajst-10988	75	12	influenced	influence	VERB
ajst-10988	75	13	by	by	ADP
ajst-10988	75	14	factors	factor	NOUN
ajst-10988	75	15	such	such	ADJ
ajst-10988	75	16	as	as	ADP
ajst-10988	75	17	data	datum	NOUN
ajst-10988	75	18	quality	quality	NOUN
ajst-10988	75	19	,	,	PUNCT
ajst-10988	75	20	the	the	DET
ajst-10988	75	21	scale	scale	NOUN
ajst-10988	75	22	of	of	ADP
ajst-10988	75	23	model	model	NOUN
ajst-10988	75	24	training	training	NOUN
ajst-10988	75	25	,	,	PUNCT
ajst-10988	75	26	and	and	CCONJ
ajst-10988	75	27	the	the	DET
ajst-10988	75	28	complexity	complexity	NOUN
ajst-10988	75	29	of	of	ADP
ajst-10988	75	30	the	the	DET
ajst-10988	75	31	model	model	NOUN
ajst-10988	75	32	.	.	PUNCT
ajst-10988	76	1	it	it	PRON
ajst-10988	76	2	requires	require	VERB
ajst-10988	76	3	sufficient	sufficient	ADJ
ajst-10988	76	4	validation	validation	NOUN
ajst-10988	76	5	and	and	CCONJ
ajst-10988	76	6	fine	fine	ADV
ajst-10988	76	7	-	-	PUNCT
ajst-10988	76	8	tuning	tuning	NOUN
ajst-10988	76	9	in	in	ADP
ajst-10988	76	10	real	real	ADJ
ajst-10988	76	11	-	-	PUNCT
ajst-10988	76	12	world	world	NOUN
ajst-10988	76	13	applications	application	NOUN
ajst-10988	76	14	[	[	X
ajst-10988	76	15	feng	feng	X
ajst-10988	76	16	h	h	NOUN
ajst-10988	76	17	d,2018	d,2018	PROPN
ajst-10988	76	18	]	]	PUNCT
ajst-10988	76	19	.	.	PUNCT
ajst-10988	77	1	figure	figure	NOUN
ajst-10988	77	2	4	4	NUM
ajst-10988	77	3	.	.	PUNCT
ajst-10988	77	4	simplified	simplified	ADJ
ajst-10988	77	5	model	model	NOUN
ajst-10988	77	6	of	of	ADP
ajst-10988	77	7	braking	brake	VERB
ajst-10988	77	8	system	system	NOUN
ajst-10988	77	9	of	of	ADP
ajst-10988	77	10	subway	subway	NOUN
ajst-10988	77	11	train	train	VERB
ajst-10988	77	12	4	4	NUM
ajst-10988	77	13	.	.	PUNCT
ajst-10988	78	1	validation	validation	NOUN
ajst-10988	78	2	analysis	analysis	NOUN
ajst-10988	78	3	in	in	ADP
ajst-10988	78	4	order	order	NOUN
ajst-10988	78	5	to	to	PART
ajst-10988	78	6	validate	validate	VERB
ajst-10988	78	7	the	the	DET
ajst-10988	78	8	effectiveness	effectiveness	NOUN
ajst-10988	78	9	of	of	ADP
ajst-10988	78	10	our	our	PRON
ajst-10988	78	11	proposed	propose	VERB
ajst-10988	78	12	method	method	NOUN
ajst-10988	78	13	,	,	PUNCT
ajst-10988	78	14	the	the	DET
ajst-10988	78	15	following	follow	VERB
ajst-10988	78	16	analysis	analysis	NOUN
ajst-10988	78	17	has	have	AUX
ajst-10988	78	18	been	be	AUX
ajst-10988	78	19	performed	perform	VERB
ajst-10988	78	20	:	:	PUNCT
ajst-10988	78	21	4.1	4.1	NUM
ajst-10988	78	22	.	.	PUNCT
ajst-10988	78	23	simulation	simulation	NOUN
ajst-10988	78	24	design	design	PROPN
ajst-10988	78	25	simulation	simulation	NOUN
ajst-10988	78	26	design	design	NOUN
ajst-10988	78	27	refers	refer	VERB
ajst-10988	78	28	to	to	ADP
ajst-10988	78	29	the	the	DET
ajst-10988	78	30	process	process	NOUN
ajst-10988	78	31	of	of	ADP
ajst-10988	78	32	using	use	VERB
ajst-10988	78	33	computer	computer	NOUN
ajst-10988	78	34	models	model	NOUN
ajst-10988	78	35	and	and	CCONJ
ajst-10988	78	36	algorithms	algorithm	NOUN
ajst-10988	78	37	to	to	PART
ajst-10988	78	38	simulate	simulate	VERB
ajst-10988	78	39	and	and	CCONJ
ajst-10988	78	40	mimic	mimic	VERB
ajst-10988	78	41	the	the	DET
ajst-10988	78	42	behavior	behavior	NOUN
ajst-10988	78	43	and	and	CCONJ
ajst-10988	78	44	performance	performance	NOUN
ajst-10988	78	45	of	of	ADP
ajst-10988	78	46	actual	actual	ADJ
ajst-10988	78	47	systems	system	NOUN
ajst-10988	78	48	or	or	CCONJ
ajst-10988	78	49	processes	process	NOUN
ajst-10988	78	50	.	.	PUNCT
ajst-10988	79	1	in	in	ADP
ajst-10988	79	2	the	the	DET
ajst-10988	79	3	field	field	NOUN
ajst-10988	79	4	of	of	ADP
ajst-10988	79	5	engineering	engineering	NOUN
ajst-10988	79	6	,	,	PUNCT
ajst-10988	79	7	simulation	simulation	NOUN
ajst-10988	79	8	design	design	NOUN
ajst-10988	79	9	is	be	AUX
ajst-10988	79	10	widely	widely	ADV
ajst-10988	79	11	applied	apply	VERB
ajst-10988	79	12	in	in	ADP
ajst-10988	79	13	system	system	NOUN
ajst-10988	79	14	design	design	NOUN
ajst-10988	79	15	,	,	PUNCT
ajst-10988	79	16	performance	performance	NOUN
ajst-10988	79	17	evaluation	evaluation	NOUN
ajst-10988	79	18	,	,	PUNCT
ajst-10988	79	19	and	and	CCONJ
ajst-10988	79	20	optimization	optimization	NOUN
ajst-10988	79	21	.	.	PUNCT
ajst-10988	80	1	in	in	ADP
ajst-10988	80	2	simulation	simulation	NOUN
ajst-10988	80	3	design	design	NOUN
ajst-10988	80	4	,	,	PUNCT
ajst-10988	80	5	it	it	PRON
ajst-10988	80	6	is	be	AUX
ajst-10988	80	7	necessary	necessary	ADJ
ajst-10988	80	8	to	to	PART
ajst-10988	80	9	first	first	ADV
ajst-10988	80	10	establish	establish	VERB
ajst-10988	80	11	a	a	DET
ajst-10988	80	12	mathematical	mathematical	ADJ
ajst-10988	80	13	model	model	NOUN
ajst-10988	80	14	of	of	ADP
ajst-10988	80	15	the	the	DET
ajst-10988	80	16	system	system	NOUN
ajst-10988	80	17	that	that	PRON
ajst-10988	80	18	describes	describe	VERB
ajst-10988	80	19	its	its	PRON
ajst-10988	80	20	structure	structure	NOUN
ajst-10988	80	21	,	,	PUNCT
ajst-10988	80	22	characteristics	characteristic	NOUN
ajst-10988	80	23	,	,	PUNCT
ajst-10988	80	24	and	and	CCONJ
ajst-10988	80	25	operating	operating	NOUN
ajst-10988	80	26	rules	rule	NOUN
ajst-10988	80	27	.	.	PUNCT
ajst-10988	81	1	the	the	DET
ajst-10988	81	2	model	model	NOUN
ajst-10988	81	3	can	can	AUX
ajst-10988	81	4	be	be	AUX
ajst-10988	81	5	based	base	VERB
ajst-10988	81	6	on	on	ADP
ajst-10988	81	7	equations	equation	NOUN
ajst-10988	81	8	derived	derive	VERB
ajst-10988	81	9	from	from	ADP
ajst-10988	81	10	physical	physical	ADJ
ajst-10988	81	11	principles	principle	NOUN
ajst-10988	81	12	,	,	PUNCT
ajst-10988	81	13	stochastic	stochastic	NOUN
ajst-10988	81	14	processes	process	NOUN
ajst-10988	81	15	based	base	VERB
ajst-10988	81	16	on	on	ADP
ajst-10988	81	17	statistics	statistic	NOUN
ajst-10988	81	18	,	,	PUNCT
ajst-10988	81	19	or	or	CCONJ
ajst-10988	81	20	simulation	simulation	NOUN
ajst-10988	81	21	models	model	NOUN
ajst-10988	81	22	based	base	VERB
ajst-10988	81	23	on	on	ADP
ajst-10988	81	24	logical	logical	ADJ
ajst-10988	81	25	rules	rule	NOUN
ajst-10988	81	26	.	.	PUNCT
ajst-10988	82	1	in	in	ADP
ajst-10988	82	2	practical	practical	ADJ
ajst-10988	82	3	engineering	engineering	NOUN
ajst-10988	82	4	,	,	PUNCT
ajst-10988	82	5	simulation	simulation	NOUN
ajst-10988	82	6	design	design	NOUN
ajst-10988	82	7	plays	play	VERB
ajst-10988	82	8	a	a	DET
ajst-10988	82	9	vital	vital	ADJ
ajst-10988	82	10	role	role	NOUN
ajst-10988	82	11	.	.	PUNCT
ajst-10988	83	1	it	it	PRON
ajst-10988	83	2	can	can	AUX
ajst-10988	83	3	be	be	AUX
ajst-10988	83	4	used	use	VERB
ajst-10988	83	5	to	to	PART
ajst-10988	83	6	verify	verify	VERB
ajst-10988	83	7	system	system	NOUN
ajst-10988	83	8	design	design	NOUN
ajst-10988	83	9	solutions	solution	NOUN
ajst-10988	83	10	,	,	PUNCT
ajst-10988	83	11	predict	predict	VERB
ajst-10988	83	12	and	and	CCONJ
ajst-10988	83	13	analyze	analyze	VERB
ajst-10988	83	14	system	system	NOUN
ajst-10988	83	15	performance	performance	NOUN
ajst-10988	83	16	before	before	ADP
ajst-10988	83	17	product	product	NOUN
ajst-10988	83	18	development	development	NOUN
ajst-10988	83	19	,	,	PUNCT
ajst-10988	83	20	and	and	CCONJ
ajst-10988	83	21	reduce	reduce	VERB
ajst-10988	83	22	the	the	DET
ajst-10988	83	23	cost	cost	NOUN
ajst-10988	83	24	and	and	CCONJ
ajst-10988	83	25	risks	risk	NOUN
ajst-10988	83	26	associated	associate	VERB
ajst-10988	83	27	with	with	ADP
ajst-10988	83	28	physical	physical	ADJ
ajst-10988	83	29	experiments	experiment	NOUN
ajst-10988	83	30	.	.	PUNCT
ajst-10988	84	1	for	for	ADP
ajst-10988	84	2	example	example	NOUN
ajst-10988	84	3	,	,	PUNCT
ajst-10988	84	4	in	in	ADP
ajst-10988	84	5	the	the	DET
ajst-10988	84	6	field	field	NOUN
ajst-10988	84	7	of	of	ADP
ajst-10988	84	8	transportation	transportation	NOUN
ajst-10988	84	9	,	,	PUNCT
ajst-10988	84	10	simulation	simulation	NOUN
ajst-10988	84	11	design	design	NOUN
ajst-10988	84	12	can	can	AUX
ajst-10988	84	13	be	be	AUX
ajst-10988	84	14	used	use	VERB
ajst-10988	84	15	to	to	PART
ajst-10988	84	16	simulate	simulate	VERB
ajst-10988	84	17	urban	urban	ADJ
ajst-10988	84	18	traffic	traffic	NOUN
ajst-10988	84	19	flow	flow	NOUN
ajst-10988	84	20	and	and	CCONJ
ajst-10988	84	21	evaluate	evaluate	VERB
ajst-10988	84	22	the	the	DET
ajst-10988	84	23	effectiveness	effectiveness	NOUN
ajst-10988	84	24	of	of	ADP
ajst-10988	84	25	traffic	traffic	NOUN
ajst-10988	84	26	planning	planning	NOUN
ajst-10988	84	27	and	and	CCONJ
ajst-10988	84	28	control	control	NOUN
ajst-10988	84	29	strategies	strategy	NOUN
ajst-10988	84	30	.	.	PUNCT
ajst-10988	85	1	in	in	ADP
ajst-10988	85	2	the	the	DET
ajst-10988	85	3	manufacturing	manufacturing	NOUN
ajst-10988	85	4	industry	industry	NOUN
ajst-10988	85	5	,	,	PUNCT
ajst-10988	85	6	simulation	simulation	NOUN
ajst-10988	85	7	design	design	NOUN
ajst-10988	85	8	can	can	AUX
ajst-10988	85	9	optimize	optimize	VERB
ajst-10988	85	10	production	production	NOUN
ajst-10988	85	11	line	line	NOUN
ajst-10988	85	12	layouts	layout	NOUN
ajst-10988	85	13	and	and	CCONJ
ajst-10988	85	14	process	process	NOUN
ajst-10988	85	15	flows	flow	NOUN
ajst-10988	85	16	,	,	PUNCT
ajst-10988	85	17	thereby	thereby	ADV
ajst-10988	85	18	improving	improve	VERB
ajst-10988	85	19	production	production	NOUN
ajst-10988	85	20	efficiency	efficiency	NOUN
ajst-10988	85	21	and	and	CCONJ
ajst-10988	85	22	quality	quality	NOUN
ajst-10988	85	23	.	.	PUNCT
ajst-10988	86	1	4.2	4.2	NUM
ajst-10988	86	2	.	.	PUNCT
ajst-10988	86	3	data	datum	NOUN
ajst-10988	86	4	set	set	VERB
ajst-10988	86	5	description	description	NOUN
ajst-10988	86	6	and	and	CCONJ
ajst-10988	86	7	confidence	confidence	NOUN
ajst-10988	86	8	analysis	analysis	NOUN
ajst-10988	86	9	data	datum	NOUN
ajst-10988	86	10	set	set	VERB
ajst-10988	86	11	description	description	NOUN
ajst-10988	86	12	and	and	CCONJ
ajst-10988	86	13	plausibility	plausibility	NOUN
ajst-10988	86	14	analysis	analysis	NOUN
ajst-10988	86	15	is	be	AUX
ajst-10988	86	16	the	the	DET
ajst-10988	86	17	process	process	NOUN
ajst-10988	86	18	of	of	ADP
ajst-10988	86	19	describing	describe	VERB
ajst-10988	86	20	a	a	DET
ajst-10988	86	21	data	datum	NOUN
ajst-10988	86	22	set	set	VERB
ajst-10988	86	23	in	in	ADP
ajst-10988	86	24	detail	detail	NOUN
ajst-10988	86	25	and	and	CCONJ
ajst-10988	86	26	assessing	assess	VERB
ajst-10988	86	27	its	its	PRON
ajst-10988	86	28	plausibility	plausibility	NOUN
ajst-10988	86	29	.	.	PUNCT
ajst-10988	87	1	this	this	PRON
ajst-10988	87	2	is	be	AUX
ajst-10988	87	3	a	a	DET
ajst-10988	87	4	very	very	ADV
ajst-10988	87	5	important	important	ADJ
ajst-10988	87	6	step	step	NOUN
ajst-10988	87	7	before	before	ADP
ajst-10988	87	8	data	data	NOUN
ajst-10988	87	9	analysis	analysis	NOUN
ajst-10988	87	10	and	and	CCONJ
ajst-10988	87	11	modeling	modeling	NOUN
ajst-10988	87	12	to	to	PART
ajst-10988	87	13	ensure	ensure	VERB
ajst-10988	87	14	the	the	DET
ajst-10988	87	15	quality	quality	NOUN
ajst-10988	87	16	and	and	CCONJ
ajst-10988	87	17	applicability	applicability	NOUN
ajst-10988	87	18	of	of	ADP
ajst-10988	87	19	the	the	DET
ajst-10988	87	20	data	datum	NOUN
ajst-10988	87	21	.	.	PUNCT
ajst-10988	88	1	in	in	ADP
ajst-10988	88	2	order	order	NOUN
ajst-10988	88	3	to	to	PART
ajst-10988	88	4	verify	verify	VERB
ajst-10988	88	5	the	the	DET
ajst-10988	88	6	reliability	reliability	NOUN
ajst-10988	88	7	of	of	ADP
ajst-10988	88	8	the	the	DET
ajst-10988	88	9	optimal	optimal	ADJ
ajst-10988	88	10	bayesian	bayesian	NOUN
ajst-10988	88	11	network	network	NOUN
ajst-10988	88	12	fault	fault	NOUN
ajst-10988	88	13	diagnosis	diagnosis	NOUN
ajst-10988	88	14	model	model	NOUN
ajst-10988	88	15	proposed	propose	VERB
ajst-10988	88	16	in	in	ADP
ajst-10988	88	17	this	this	DET
ajst-10988	88	18	paper	paper	NOUN
ajst-10988	88	19	,	,	PUNCT
ajst-10988	88	20	its	its	PRON
ajst-10988	88	21	calculation	calculation	NOUN
ajst-10988	88	22	principle	principle	NOUN
ajst-10988	88	23	is	be	AUX
ajst-10988	88	24	shown	show	VERB
ajst-10988	88	25	in	in	ADP
ajst-10988	88	26	equation	equation	NOUN
ajst-10988	88	27	(	(	PUNCT
ajst-10988	88	28	7	7	NUM
ajst-10988	88	29	):	):	PUNCT
ajst-10988	88	30	)	)	PUNCT
ajst-10988	88	31	/(21	/(21	PUNCT
ajst-10988	88	32	rpprf	rpprf	VERB
ajst-10988	88	33			ADJ
ajst-10988	88	34	(	(	PUNCT
ajst-10988	88	35	7	7	NUM
ajst-10988	88	36	)	)	PUNCT
ajst-10988	88	37	data	datum	NOUN
ajst-10988	88	38	set	set	VERB
ajst-10988	88	39	description	description	NOUN
ajst-10988	88	40	and	and	CCONJ
ajst-10988	88	41	confidence	confidence	NOUN
ajst-10988	88	42	analysis	analysis	NOUN
ajst-10988	88	43	is	be	AUX
ajst-10988	88	44	the	the	DET
ajst-10988	88	45	process	process	NOUN
ajst-10988	88	46	of	of	ADP
ajst-10988	88	47	describing	describe	VERB
ajst-10988	88	48	a	a	DET
ajst-10988	88	49	data	datum	NOUN
ajst-10988	88	50	set	set	VERB
ajst-10988	88	51	in	in	ADP
ajst-10988	88	52	detail	detail	NOUN
ajst-10988	88	53	and	and	CCONJ
ajst-10988	88	54	assessing	assess	VERB
ajst-10988	88	55	its	its	PRON
ajst-10988	88	56	confidence	confidence	NOUN
ajst-10988	88	57	prior	prior	ADV
ajst-10988	88	58	to	to	ADP
ajst-10988	88	59	data	datum	NOUN
ajst-10988	88	60	analysis	analysis	NOUN
ajst-10988	88	61	and	and	CCONJ
ajst-10988	88	62	modeling	modeling	NOUN
ajst-10988	88	63	.	.	PUNCT
ajst-10988	89	1	data	datum	NOUN
ajst-10988	89	2	description	description	NOUN
ajst-10988	89	3	includes	include	VERB
ajst-10988	89	4	information	information	NOUN
ajst-10988	89	5	such	such	ADJ
ajst-10988	89	6	as	as	ADP
ajst-10988	89	7	data	datum	NOUN
ajst-10988	89	8	source	source	NOUN
ajst-10988	89	9	,	,	PUNCT
ajst-10988	89	10	data	datum	NOUN
ajst-10988	89	11	collection	collection	NOUN
ajst-10988	89	12	process	process	NOUN
ajst-10988	89	13	,	,	PUNCT
ajst-10988	89	14	data	data	NOUN
ajst-10988	89	15	content	content	NOUN
ajst-10988	89	16	,	,	PUNCT
ajst-10988	89	17	data	data	NOUN
ajst-10988	89	18	format	format	NOUN
ajst-10988	89	19	,	,	PUNCT
ajst-10988	89	20	data	datum	NOUN
ajst-10988	89	21	volume	volume	NOUN
ajst-10988	89	22	and	and	CCONJ
ajst-10988	89	23	dimensionality	dimensionality	NOUN
ajst-10988	89	24	.	.	PUNCT
ajst-10988	90	1	credibility	credibility	NOUN
ajst-10988	90	2	analysis	analysis	NOUN
ajst-10988	90	3	includes	include	VERB
ajst-10988	90	4	methods	method	NOUN
ajst-10988	90	5	such	such	ADJ
ajst-10988	90	6	as	as	ADP
ajst-10988	90	7	data	datum	NOUN
ajst-10988	90	8	quality	quality	NOUN
ajst-10988	90	9	checking	checking	NOUN
ajst-10988	90	10	,	,	PUNCT
ajst-10988	90	11	data	datum	NOUN
ajst-10988	90	12	source	source	NOUN
ajst-10988	90	13	validation	validation	NOUN
ajst-10988	90	14	,	,	PUNCT
ajst-10988	90	15	sampling	sample	VERB
ajst-10988	90	16	method	method	NOUN
ajst-10988	90	17	assessment	assessment	NOUN
ajst-10988	90	18	,	,	PUNCT
ajst-10988	90	19	data	data	NOUN
ajst-10988	90	20	consistency	consistency	NOUN
ajst-10988	90	21	checking	checking	NOUN
ajst-10988	90	22	,	,	PUNCT
ajst-10988	90	23	and	and	CCONJ
ajst-10988	90	24	domain	domain	NOUN
ajst-10988	90	25	expert	expert	NOUN
ajst-10988	90	26	assessment	assessment	NOUN
ajst-10988	90	27	.	.	PUNCT
ajst-10988	91	1	through	through	ADP
ajst-10988	91	2	dataset	dataset	ADJ
ajst-10988	91	3	description	description	NOUN
ajst-10988	91	4	and	and	CCONJ
ajst-10988	91	5	plausibility	plausibility	NOUN
ajst-10988	91	6	analysis	analysis	NOUN
ajst-10988	91	7	,	,	PUNCT
ajst-10988	91	8	we	we	PRON
ajst-10988	91	9	are	be	AUX
ajst-10988	91	10	able	able	ADJ
ajst-10988	91	11	to	to	PART
ajst-10988	91	12	gain	gain	VERB
ajst-10988	91	13	a	a	DET
ajst-10988	91	14	comprehensive	comprehensive	ADJ
ajst-10988	91	15	understanding	understanding	NOUN
ajst-10988	91	16	of	of	ADP
ajst-10988	91	17	the	the	DET
ajst-10988	91	18	dataset	dataset	NOUN
ajst-10988	91	19	and	and	CCONJ
ajst-10988	91	20	ensure	ensure	VERB
ajst-10988	91	21	the	the	DET
ajst-10988	91	22	quality	quality	NOUN
ajst-10988	91	23	and	and	CCONJ
ajst-10988	91	24	applicability	applicability	NOUN
ajst-10988	91	25	of	of	ADP
ajst-10988	91	26	the	the	DET
ajst-10988	91	27	data	datum	NOUN
ajst-10988	91	28	.	.	PUNCT
ajst-10988	92	1	this	this	PRON
ajst-10988	92	2	helps	help	VERB
ajst-10988	92	3	to	to	PART
ajst-10988	92	4	improve	improve	VERB
ajst-10988	92	5	the	the	DET
ajst-10988	92	6	accuracy	accuracy	NOUN
ajst-10988	92	7	and	and	CCONJ
ajst-10988	92	8	reliability	reliability	NOUN
ajst-10988	92	9	of	of	ADP
ajst-10988	92	10	data	datum	NOUN
ajst-10988	92	11	analysis	analysis	NOUN
ajst-10988	92	12	and	and	CCONJ
ajst-10988	92	13	modeling	modeling	NOUN
ajst-10988	92	14	,	,	PUNCT
ajst-10988	92	15	ensures	ensure	VERB
ajst-10988	92	16	that	that	SCONJ
ajst-10988	92	17	the	the	DET
ajst-10988	92	18	conclusions	conclusion	NOUN
ajst-10988	92	19	and	and	CCONJ
ajst-10988	92	20	decisions	decision	NOUN
ajst-10988	92	21	we	we	PRON
ajst-10988	92	22	obtain	obtain	VERB
ajst-10988	92	23	are	be	AUX
ajst-10988	92	24	credible	credible	ADJ
ajst-10988	92	25	,	,	PUNCT
ajst-10988	92	26	and	and	CCONJ
ajst-10988	92	27	provides	provide	VERB
ajst-10988	92	28	a	a	DET
ajst-10988	92	29	reliable	reliable	ADJ
ajst-10988	92	30	basis	basis	NOUN
ajst-10988	92	31	for	for	ADP
ajst-10988	92	32	further	further	ADJ
ajst-10988	92	33	data	datum	NOUN
ajst-10988	92	34	processing	processing	NOUN
ajst-10988	92	35	and	and	CCONJ
ajst-10988	92	36	analysis	analysis	NOUN
ajst-10988	92	37	.	.	PUNCT
ajst-10988	93	1	4.3	4.3	NUM
ajst-10988	93	2	.	.	PUNCT
ajst-10988	94	1	diagnostic	diagnostic	ADJ
ajst-10988	94	2	inference	inference	NOUN
ajst-10988	94	3	diagnostic	diagnostic	ADJ
ajst-10988	94	4	inference	inference	NOUN
ajst-10988	94	5	results	result	NOUN
ajst-10988	94	6	are	be	AUX
ajst-10988	94	7	diagnostic	diagnostic	ADJ
ajst-10988	94	8	conclusions	conclusion	NOUN
ajst-10988	94	9	obtained	obtain	VERB
ajst-10988	94	10	by	by	ADP
ajst-10988	94	11	analyzing	analyze	VERB
ajst-10988	94	12	and	and	CCONJ
ajst-10988	94	13	extrapolating	extrapolate	VERB
ajst-10988	94	14	given	give	VERB
ajst-10988	94	15	observations	observation	NOUN
ajst-10988	94	16	through	through	ADP
ajst-10988	94	17	inference	inference	NOUN
ajst-10988	94	18	methods	method	NOUN
ajst-10988	94	19	.	.	PUNCT
ajst-10988	95	1	these	these	DET
ajst-10988	95	2	reasoning	reasoning	NOUN
ajst-10988	95	3	results	result	NOUN
ajst-10988	95	4	can	can	AUX
ajst-10988	95	5	be	be	AUX
ajst-10988	95	6	used	use	VERB
ajst-10988	95	7	to	to	PART
ajst-10988	95	8	determine	determine	VERB
ajst-10988	95	9	the	the	DET
ajst-10988	95	10	state	state	NOUN
ajst-10988	95	11	,	,	PUNCT
ajst-10988	95	12	problem	problem	NOUN
ajst-10988	95	13	,	,	PUNCT
ajst-10988	95	14	or	or	CCONJ
ajst-10988	95	15	abnormality	abnormality	NOUN
ajst-10988	95	16	of	of	ADP
ajst-10988	95	17	a	a	DET
ajst-10988	95	18	system	system	NOUN
ajst-10988	95	19	or	or	CCONJ
ajst-10988	95	20	process	process	NOUN
ajst-10988	95	21	.	.	PUNCT
ajst-10988	96	1	through	through	ADP
ajst-10988	96	2	diagnostic	diagnostic	ADJ
ajst-10988	96	3	reasoning	reasoning	NOUN
ajst-10988	96	4	results	result	NOUN
ajst-10988	96	5	,	,	PUNCT
ajst-10988	96	6	we	we	PRON
ajst-10988	96	7	are	be	AUX
ajst-10988	96	8	able	able	ADJ
ajst-10988	96	9	to	to	PART
ajst-10988	96	10	perform	perform	VERB
ajst-10988	96	11	accurate	accurate	ADJ
ajst-10988	96	12	system	system	NOUN
ajst-10988	96	13	analysis	analysis	NOUN
ajst-10988	96	14	and	and	CCONJ
ajst-10988	96	15	scenario	scenario	NOUN
ajst-10988	96	16	prediction	prediction	NOUN
ajst-10988	96	17	using	use	VERB
ajst-10988	96	18	existing	exist	VERB
ajst-10988	96	19	knowledge	knowledge	NOUN
ajst-10988	96	20	and	and	CCONJ
ajst-10988	96	21	observational	observational	ADJ
ajst-10988	96	22	data	datum	NOUN
ajst-10988	96	23	.	.	PUNCT
ajst-10988	97	1	this	this	PRON
ajst-10988	97	2	helps	help	VERB
ajst-10988	97	3	to	to	PART
ajst-10988	97	4	identify	identify	VERB
ajst-10988	97	5	and	and	CCONJ
ajst-10988	97	6	solve	solve	VERB
ajst-10988	97	7	problems	problem	NOUN
ajst-10988	97	8	in	in	ADP
ajst-10988	97	9	a	a	DET
ajst-10988	97	10	timely	timely	ADJ
ajst-10988	97	11	manner	manner	NOUN
ajst-10988	97	12	,	,	PUNCT
ajst-10988	97	13	improve	improve	VERB
ajst-10988	97	14	system	system	NOUN
ajst-10988	97	15	efficiency	efficiency	NOUN
ajst-10988	97	16	and	and	CCONJ
ajst-10988	97	17	reliability	reliability	NOUN
ajst-10988	97	18	,	,	PUNCT
ajst-10988	97	19	and	and	CCONJ
ajst-10988	97	20	provide	provide	VERB
ajst-10988	97	21	effective	effective	ADJ
ajst-10988	97	22	support	support	NOUN
ajst-10988	97	23	for	for	ADP
ajst-10988	97	24	decision	decision	NOUN
ajst-10988	97	25	making	making	NOUN
ajst-10988	97	26	and	and	CCONJ
ajst-10988	97	27	problem	problem	NOUN
ajst-10988	97	28	solving	solving	NOUN
ajst-10988	97	29	.	.	PUNCT
ajst-10988	98	1	however	however	ADV
ajst-10988	98	2	,	,	PUNCT
ajst-10988	98	3	the	the	DET
ajst-10988	98	4	accuracy	accuracy	NOUN
ajst-10988	98	5	and	and	CCONJ
ajst-10988	98	6	reliability	reliability	NOUN
ajst-10988	98	7	of	of	ADP
ajst-10988	98	8	the	the	DET
ajst-10988	98	9	inference	inference	NOUN
ajst-10988	98	10	results	result	NOUN
ajst-10988	98	11	are	be	AUX
ajst-10988	98	12	affected	affect	VERB
ajst-10988	98	13	by	by	ADP
ajst-10988	98	14	factors	factor	NOUN
ajst-10988	98	15	such	such	ADJ
ajst-10988	98	16	as	as	ADP
ajst-10988	98	17	data	datum	NOUN
ajst-10988	98	18	quality	quality	NOUN
ajst-10988	98	19	,	,	PUNCT
ajst-10988	98	20	accuracy	accuracy	NOUN
ajst-10988	98	21	of	of	ADP
ajst-10988	98	22	the	the	DET
ajst-10988	98	23	model	model	NOUN
ajst-10988	98	24	and	and	CCONJ
ajst-10988	98	25	choice	choice	NOUN
ajst-10988	98	26	of	of	ADP
ajst-10988	98	27	inference	inference	NOUN
ajst-10988	98	28	method	method	NOUN
ajst-10988	98	29	,	,	PUNCT
ajst-10988	98	30	and	and	CCONJ
ajst-10988	98	31	need	need	VERB
ajst-10988	98	32	to	to	PART
ajst-10988	98	33	be	be	AUX
ajst-10988	98	34	fully	fully	ADV
ajst-10988	98	35	53	53	NUM
ajst-10988	98	36	validated	validate	VERB
ajst-10988	98	37	and	and	CCONJ
ajst-10988	98	38	evaluated	evaluate	VERB
ajst-10988	98	39	[	[	PUNCT
ajst-10988	98	40	quan	quan	NOUN
ajst-10988	98	41	w,2023	w,2023	PROPN
ajst-10988	98	42	]	]	PUNCT
ajst-10988	98	43	.	.	PUNCT
ajst-10988	99	1	5	5	X
ajst-10988	99	2	.	.	X
ajst-10988	99	3	conclusion	conclusion	NOUN
ajst-10988	99	4	by	by	ADP
ajst-10988	99	5	conducting	conduct	VERB
ajst-10988	99	6	research	research	NOUN
ajst-10988	99	7	on	on	ADP
ajst-10988	99	8	a	a	DET
ajst-10988	99	9	bayesian	bayesian	NOUN
ajst-10988	99	10	network	network	NOUN
ajst-10988	99	11	-	-	PUNCT
ajst-10988	99	12	based	base	VERB
ajst-10988	99	13	method	method	NOUN
ajst-10988	99	14	for	for	ADP
ajst-10988	99	15	detecting	detect	VERB
ajst-10988	99	16	and	and	CCONJ
ajst-10988	99	17	predicting	predict	VERB
ajst-10988	99	18	leaks	leak	NOUN
ajst-10988	99	19	in	in	ADP
ajst-10988	99	20	train	train	NOUN
ajst-10988	99	21	braking	brake	VERB
ajst-10988	99	22	system	system	NOUN
ajst-10988	99	23	pipelines	pipeline	NOUN
ajst-10988	99	24	,	,	PUNCT
ajst-10988	99	25	this	this	DET
ajst-10988	99	26	paper	paper	NOUN
ajst-10988	99	27	effectively	effectively	ADV
ajst-10988	99	28	addresses	address	VERB
ajst-10988	99	29	the	the	DET
ajst-10988	99	30	safety	safety	NOUN
ajst-10988	99	31	risks	risk	NOUN
ajst-10988	99	32	associated	associate	VERB
ajst-10988	99	33	with	with	ADP
ajst-10988	99	34	such	such	ADJ
ajst-10988	99	35	leaks	leak	NOUN
ajst-10988	99	36	.	.	PUNCT
ajst-10988	100	1	this	this	DET
ajst-10988	100	2	method	method	NOUN
ajst-10988	100	3	combines	combine	VERB
ajst-10988	100	4	the	the	DET
ajst-10988	100	5	characteristics	characteristic	NOUN
ajst-10988	100	6	and	and	CCONJ
ajst-10988	100	7	advantages	advantage	NOUN
ajst-10988	100	8	of	of	ADP
ajst-10988	100	9	bayesian	bayesian	NOUN
ajst-10988	100	10	network	network	NOUN
ajst-10988	100	11	algorithms	algorithm	NOUN
ajst-10988	100	12	.	.	PUNCT
ajst-10988	101	1	through	through	ADP
ajst-10988	101	2	simulation	simulation	NOUN
ajst-10988	101	3	design	design	NOUN
ajst-10988	101	4	and	and	CCONJ
ajst-10988	101	5	validation	validation	NOUN
ajst-10988	101	6	using	use	VERB
ajst-10988	101	7	actual	actual	ADJ
ajst-10988	101	8	datasets	dataset	NOUN
ajst-10988	101	9	,	,	PUNCT
ajst-10988	101	10	the	the	DET
ajst-10988	101	11	results	result	NOUN
ajst-10988	101	12	demonstrate	demonstrate	VERB
ajst-10988	101	13	that	that	SCONJ
ajst-10988	101	14	the	the	DET
ajst-10988	101	15	method	method	NOUN
ajst-10988	101	16	can	can	AUX
ajst-10988	101	17	reliably	reliably	ADV
ajst-10988	101	18	detect	detect	VERB
ajst-10988	101	19	pipeline	pipeline	NOUN
ajst-10988	101	20	leaks	leak	NOUN
ajst-10988	101	21	in	in	ADP
ajst-10988	101	22	different	different	ADJ
ajst-10988	101	23	scenarios	scenario	NOUN
ajst-10988	101	24	and	and	CCONJ
ajst-10988	101	25	provide	provide	VERB
ajst-10988	101	26	accurate	accurate	ADJ
ajst-10988	101	27	localization	localization	NOUN
ajst-10988	101	28	and	and	CCONJ
ajst-10988	101	29	fault	fault	VERB
ajst-10988	101	30	inference	inference	NOUN
ajst-10988	101	31	.	.	PUNCT
ajst-10988	102	1	compared	compare	VERB
ajst-10988	102	2	to	to	ADP
ajst-10988	102	3	traditional	traditional	ADJ
ajst-10988	102	4	methods	method	NOUN
ajst-10988	102	5	,	,	PUNCT
ajst-10988	102	6	the	the	DET
ajst-10988	102	7	bayesian	bayesian	NOUN
ajst-10988	102	8	network	network	NOUN
ajst-10988	102	9	-	-	PUNCT
ajst-10988	102	10	based	base	VERB
ajst-10988	102	11	approach	approach	NOUN
ajst-10988	102	12	exhibits	exhibit	VERB
ajst-10988	102	13	higher	high	ADJ
ajst-10988	102	14	accuracy	accuracy	NOUN
ajst-10988	102	15	and	and	CCONJ
ajst-10988	102	16	reliability	reliability	NOUN
ajst-10988	102	17	,	,	PUNCT
ajst-10988	102	18	enabling	enable	VERB
ajst-10988	102	19	early	early	ADJ
ajst-10988	102	20	detection	detection	NOUN
ajst-10988	102	21	of	of	ADP
ajst-10988	102	22	pipeline	pipeline	NOUN
ajst-10988	102	23	leaks	leak	NOUN
ajst-10988	102	24	and	and	CCONJ
ajst-10988	102	25	timely	timely	ADJ
ajst-10988	102	26	repair	repair	NOUN
ajst-10988	102	27	measures	measure	NOUN
ajst-10988	102	28	,	,	PUNCT
ajst-10988	102	29	thereby	thereby	ADV
ajst-10988	102	30	enhancing	enhance	VERB
ajst-10988	102	31	the	the	DET
ajst-10988	102	32	safety	safety	NOUN
ajst-10988	102	33	and	and	CCONJ
ajst-10988	102	34	reliability	reliability	NOUN
ajst-10988	102	35	of	of	ADP
ajst-10988	102	36	train	train	NOUN
ajst-10988	102	37	braking	braking	NOUN
ajst-10988	102	38	systems	system	NOUN
ajst-10988	102	39	.	.	PUNCT
ajst-10988	103	1	in	in	ADP
ajst-10988	103	2	summary	summary	NOUN
ajst-10988	103	3	,	,	PUNCT
ajst-10988	103	4	the	the	DET
ajst-10988	103	5	bayesian	bayesian	NOUN
ajst-10988	103	6	network	network	NOUN
ajst-10988	103	7	-	-	PUNCT
ajst-10988	103	8	based	base	VERB
ajst-10988	103	9	method	method	NOUN
ajst-10988	103	10	for	for	ADP
ajst-10988	103	11	detecting	detect	VERB
ajst-10988	103	12	and	and	CCONJ
ajst-10988	103	13	predicting	predict	VERB
ajst-10988	103	14	leaks	leak	NOUN
ajst-10988	103	15	in	in	ADP
ajst-10988	103	16	train	train	NOUN
ajst-10988	103	17	braking	brake	VERB
ajst-10988	103	18	system	system	NOUN
ajst-10988	103	19	pipelines	pipeline	NOUN
ajst-10988	103	20	is	be	AUX
ajst-10988	103	21	of	of	ADP
ajst-10988	103	22	significant	significant	ADJ
ajst-10988	103	23	importance	importance	NOUN
ajst-10988	103	24	in	in	ADP
ajst-10988	103	25	improving	improve	VERB
ajst-10988	103	26	train	train	NOUN
ajst-10988	103	27	operation	operation	NOUN
ajst-10988	103	28	safety	safety	NOUN
ajst-10988	103	29	.	.	PUNCT
ajst-10988	104	1	future	future	ADJ
ajst-10988	104	2	research	research	NOUN
ajst-10988	104	3	can	can	AUX
ajst-10988	104	4	expand	expand	VERB
ajst-10988	104	5	the	the	DET
ajst-10988	104	6	application	application	NOUN
ajst-10988	104	7	of	of	ADP
ajst-10988	104	8	this	this	DET
ajst-10988	104	9	method	method	NOUN
ajst-10988	104	10	to	to	ADP
ajst-10988	104	11	broader	broad	ADJ
ajst-10988	104	12	domains	domain	NOUN
ajst-10988	104	13	and	and	CCONJ
ajst-10988	104	14	combine	combine	VERB
ajst-10988	104	15	it	it	PRON
ajst-10988	104	16	with	with	ADP
ajst-10988	104	17	other	other	ADJ
ajst-10988	104	18	fault	fault	NOUN
ajst-10988	104	19	diagnosis	diagnosis	NOUN
ajst-10988	104	20	and	and	CCONJ
ajst-10988	104	21	prediction	prediction	NOUN
ajst-10988	104	22	methods	method	NOUN
ajst-10988	104	23	,	,	PUNCT
ajst-10988	104	24	making	make	VERB
ajst-10988	104	25	greater	great	ADJ
ajst-10988	104	26	contributions	contribution	NOUN
ajst-10988	104	27	to	to	ADP
ajst-10988	104	28	ensuring	ensure	VERB
ajst-10988	104	29	the	the	DET
ajst-10988	104	30	safety	safety	NOUN
ajst-10988	104	31	and	and	CCONJ
ajst-10988	104	32	reliability	reliability	NOUN
ajst-10988	104	33	of	of	ADP
ajst-10988	104	34	transportation	transportation	NOUN
ajst-10988	104	35	.	.	PUNCT
ajst-10988	105	1	references	reference	NOUN
ajst-10988	105	2	[	[	X
ajst-10988	105	3	1	1	X
ajst-10988	105	4	]	]	X
ajst-10988	105	5	chi	chi	PROPN
ajst-10988	105	6	z	z	PROPN
ajst-10988	105	7	,	,	PUNCT
ajst-10988	106	1	j.	j.	PROPN
ajst-10988	106	2	b	b	PROPN
ajst-10988	106	3	a	a	PROPN
ajst-10988	106	4	,	,	PUNCT
ajst-10988	106	5	l.	l.	PROPN
ajst-10988	106	6	m	m	PROPN
ajst-10988	106	7	s	s	PROPN
ajst-10988	106	8	,	,	PUNCT
ajst-10988	106	9	et	et	PROPN
ajst-10988	106	10	al	al	PROPN
ajst-10988	106	11	.	.	PUNCT
ajst-10988	107	1	a	a	DET
ajst-10988	107	2	convolutional	convolutional	ADJ
ajst-10988	107	3	neural	neural	ADJ
ajst-10988	107	4	network	network	NOUN
ajst-10988	107	5	for	for	ADP
ajst-10988	107	6	pipe	pipe	NOUN
ajst-10988	107	7	crack	crack	NOUN
ajst-10988	107	8	and	and	CCONJ
ajst-10988	107	9	leak	leak	NOUN
ajst-10988	107	10	detection	detection	NOUN
ajst-10988	107	11	in	in	ADP
ajst-10988	107	12	smart	smart	ADJ
ajst-10988	107	13	water	water	NOUN
ajst-10988	107	14	network[j	network[j	NOUN
ajst-10988	107	15	]	]	PUNCT
ajst-10988	107	16	.	.	PUNCT
ajst-10988	108	1	structural	structural	ADJ
ajst-10988	108	2	health	health	NOUN
ajst-10988	108	3	monitoring,2023(1):22	monitoring,2023(1):22	NOUN
ajst-10988	108	4	.	.	PUNCT
ajst-10988	109	1	[	[	X
ajst-10988	109	2	2	2	NUM
ajst-10988	109	3	]	]	X
ajst-10988	109	4	yang	yang	PROPN
ajst-10988	109	5	z	z	PROPN
ajst-10988	109	6	,	,	PUNCT
ajst-10988	109	7	huilin	huilin	PROPN
ajst-10988	109	8	p	p	X
ajst-10988	109	9	,	,	PUNCT
ajst-10988	109	10	yang	yang	PROPN
ajst-10988	109	11	z	z	PROPN
ajst-10988	109	12	,	,	PUNCT
ajst-10988	109	13	et	et	PROPN
ajst-10988	109	14	al	al	PROPN
ajst-10988	109	15	.	.	PROPN
ajst-10988	109	16	efficient	efficient	ADJ
ajst-10988	109	17	visual	visual	ADJ
ajst-10988	109	18	fault	fault	NOUN
ajst-10988	109	19	detection	detection	NOUN
ajst-10988	109	20	for	for	ADP
ajst-10988	109	21	freight	freight	NOUN
ajst-10988	109	22	train	train	NOUN
ajst-10988	109	23	braking	brake	VERB
ajst-10988	109	24	system	system	NOUN
ajst-10988	109	25	via	via	ADP
ajst-10988	109	26	heterogeneous	heterogeneous	ADJ
ajst-10988	109	27	self	self	NOUN
ajst-10988	109	28	distillation	distillation	NOUN
ajst-10988	109	29	in	in	ADP
ajst-10988	109	30	the	the	DET
ajst-10988	109	31	wild[j	wild[j	NOUN
ajst-10988	109	32	]	]	PUNCT
ajst-10988	109	33	.	.	PUNCT
ajst-10988	110	1	advanced	advanced	ADJ
ajst-10988	110	2	engineering	engineering	NOUN
ajst-10988	110	3	informatics,2023:57	informatics,2023:57	NOUN
ajst-10988	110	4	.	.	PUNCT
ajst-10988	111	1	[	[	X
ajst-10988	111	2	3	3	NUM
ajst-10988	111	3	]	]	SYM
ajst-10988	111	4	doyeob	doyeob	NOUN
ajst-10988	111	5	y	y	PROPN
ajst-10988	111	6	,	,	PUNCT
ajst-10988	111	7	giyoung	giyoung	PROPN
ajst-10988	111	8	l	l	PROPN
ajst-10988	111	9	,	,	PUNCT
ajst-10988	111	10	cheol	cheol	PROPN
ajst-10988	111	11	j	j	PROPN
ajst-10988	111	12	l.	l.	PROPN
ajst-10988	111	13	pipe	pipe	PROPN
ajst-10988	111	14	leak	leak	NOUN
ajst-10988	111	15	detection	detection	NOUN
ajst-10988	111	16	system	system	NOUN
ajst-10988	111	17	using	use	VERB
ajst-10988	111	18	wireless	wireless	ADJ
ajst-10988	111	19	acoustic	acoustic	ADJ
ajst-10988	111	20	sensor	sensor	NOUN
ajst-10988	111	21	module	module	NOUN
ajst-10988	111	22	and	and	CCONJ
ajst-10988	111	23	deep	deep	ADJ
ajst-10988	111	24	autoencoder[j	autoencoder[j	NOUN
ajst-10988	111	25	]	]	PUNCT
ajst-10988	111	26	.	.	PUNCT
ajst-10988	112	1	journal	journal	PROPN
ajst-10988	112	2	of	of	ADP
ajst-10988	112	3	the	the	DET
ajst-10988	112	4	korea	korea	PROPN
ajst-10988	112	5	society	society	NOUN
ajst-10988	112	6	of	of	ADP
ajst-10988	112	7	computer	computer	NOUN
ajst-10988	112	8	and	and	CCONJ
ajst-10988	112	9	information,2020(2):25	information,2020(2):25	NOUN
ajst-10988	112	10	.	.	PUNCT
ajst-10988	113	1	[	[	X
ajst-10988	113	2	4	4	X
ajst-10988	113	3	]	]	X
ajst-10988	113	4	feng	feng	PROPN
ajst-10988	113	5	h	h	PROPN
ajst-10988	113	6	d.	d.	PROPN
ajst-10988	113	7	accuracy	accuracy	PROPN
ajst-10988	113	8	and	and	CCONJ
ajst-10988	113	9	sensitivity	sensitivity	NOUN
ajst-10988	113	10	evaluation	evaluation	NOUN
ajst-10988	113	11	of	of	ADP
ajst-10988	113	12	tfr	tfr	PROPN
ajst-10988	113	13	method	method	NOUN
ajst-10988	113	14	for	for	ADP
ajst-10988	113	15	leak	leak	NOUN
ajst-10988	113	16	detection	detection	NOUN
ajst-10988	113	17	in	in	ADP
ajst-10988	113	18	multiple	multiple	ADJ
ajst-10988	113	19	-	-	PUNCT
ajst-10988	113	20	pipeline	pipeline	NOUN
ajst-10988	113	21	water	water	NOUN
ajst-10988	113	22	supply	supply	NOUN
ajst-10988	113	23	systems[j	systems[j	PROPN
ajst-10988	113	24	]	]	PUNCT
ajst-10988	113	25	.	.	PUNCT
ajst-10988	114	1	water	water	NOUN
ajst-10988	114	2	resources	resource	NOUN
ajst-10988	114	3	management,2018(6):32	management,2018(6):32	NOUN
ajst-10988	114	4	.	.	PUNCT
ajst-10988	115	1	[	[	X
ajst-10988	115	2	5	5	NUM
ajst-10988	115	3	]	]	X
ajst-10988	115	4	quan	quan	PROPN
ajst-10988	115	5	w	w	PROPN
ajst-10988	115	6	,	,	PUNCT
ajst-10988	115	7	zhiwei	zhiwei	PROPN
ajst-10988	115	8	w	w	PROPN
ajst-10988	115	9	,	,	PUNCT
ajst-10988	115	10	jiliang	jiliang	PROPN
ajst-10988	115	11	m	m	PROPN
ajst-10988	115	12	,	,	PUNCT
ajst-10988	115	13	et	et	PROPN
ajst-10988	115	14	al	al	PROPN
ajst-10988	115	15	.	.	PROPN
ajst-10988	115	16	modelling	modelling	NOUN
ajst-10988	115	17	and	and	CCONJ
ajst-10988	115	18	stability	stability	NOUN
ajst-10988	115	19	analysis	analysis	NOUN
ajst-10988	115	20	of	of	ADP
ajst-10988	115	21	a	a	DET
ajst-10988	115	22	high	high	ADJ
ajst-10988	115	23	-	-	PUNCT
ajst-10988	115	24	speed	speed	NOUN
ajst-10988	115	25	train	train	NOUN
ajst-10988	115	26	braking	brake	VERB
ajst-10988	115	27	system[j	system[j	NOUN
ajst-10988	115	28	]	]	PUNCT
ajst-10988	115	29	.	.	PUNCT
ajst-10988	116	1	international	international	ADJ
ajst-10988	116	2	journal	journal	PROPN
ajst-10988	116	3	of	of	ADP
ajst-10988	116	4	mechanical	mechanical	ADJ
ajst-10988	116	5	sciences,2023:250	sciences,2023:250	PROPN
ajst-10988	116	6	.	.	PUNCT