id	sid	tid	token	lemma	pos
app01-8386	1	1	acta	acta	PROPN
app01-8386	1	2	polytechnica	polytechnica	PROPN
app01-8386	1	3	ctu	ctu	PROPN
app01-8386	1	4	proceedings	proceeding	NOUN
app01-8386	1	5	https://doi.org/10.14311/app.2022.36.0099	https://doi.org/10.14311/app.2022.36.0099	VERB
app01-8386	1	6	acta	acta	PROPN
app01-8386	1	7	polytechnica	polytechnica	PROPN
app01-8386	1	8	ctu	ctu	NOUN
app01-8386	1	9	proceedings	proceeding	NOUN
app01-8386	1	10	36:99–108	36:99–108	NUM
app01-8386	1	11	,	,	PUNCT
app01-8386	1	12	2022	2022	NUM
app01-8386	1	13	©	©	ADP
app01-8386	1	14	2022	2022	NUM
app01-8386	1	15	the	the	DET
app01-8386	1	16	author(s	author(s	NOUN
app01-8386	1	17	)	)	PUNCT
app01-8386	1	18	.	.	PUNCT
app01-8386	2	1	licensed	license	VERB
app01-8386	2	2	under	under	ADP
app01-8386	2	3	a	a	DET
app01-8386	2	4	cc	cc	NOUN
app01-8386	2	5	-	-	PUNCT
app01-8386	2	6	by	by	ADP
app01-8386	2	7	4.0	4.0	NUM
app01-8386	2	8	licence	licence	NOUN
app01-8386	2	9	published	publish	VERB
app01-8386	2	10	by	by	ADP
app01-8386	2	11	the	the	DET
app01-8386	2	12	czech	czech	PROPN
app01-8386	2	13	technical	technical	PROPN
app01-8386	2	14	university	university	PROPN
app01-8386	2	15	in	in	ADP
app01-8386	2	16	prague	prague	PROPN
app01-8386	2	17	artificial	artificial	ADJ
app01-8386	2	18	intelligence	intelligence	NOUN
app01-8386	2	19	finite	finite	PROPN
app01-8386	2	20	element	element	NOUN
app01-8386	2	21	method	method	NOUN
app01-8386	2	22	hybrids	hybrid	NOUN
app01-8386	2	23	for	for	ADP
app01-8386	2	24	efficient	efficient	ADJ
app01-8386	2	25	nonlinear	nonlinear	ADJ
app01-8386	2	26	analysis	analysis	NOUN
app01-8386	2	27	of	of	ADP
app01-8386	2	28	concrete	concrete	ADJ
app01-8386	2	29	structures	structure	NOUN
app01-8386	2	30	michael	michael	PROPN
app01-8386	2	31	a.	a.	PROPN
app01-8386	2	32	krausa	krausa	PROPN
app01-8386	2	33	,	,	PUNCT
app01-8386	2	34	b,∗	b,∗	PROPN
app01-8386	2	35	,	,	PUNCT
app01-8386	2	36	rafael	rafael	PROPN
app01-8386	2	37	bischofa	bischofa	PROPN
app01-8386	2	38	,	,	PUNCT
app01-8386	2	39	walter	walter	PROPN
app01-8386	2	40	kaufmanna	kaufmanna	PROPN
app01-8386	2	41	,	,	PUNCT
app01-8386	2	42	b	b	PROPN
app01-8386	2	43	,	,	PUNCT
app01-8386	2	44	karel	karel	PROPN
app01-8386	2	45	thomaa	thomaa	VERB
app01-8386	2	46	a	a	DET
app01-8386	2	47	eth	eth	PROPN
app01-8386	2	48	zürich	zürich	PROPN
app01-8386	2	49	,	,	PUNCT
app01-8386	2	50	institute	institute	PROPN
app01-8386	2	51	of	of	ADP
app01-8386	2	52	structural	structural	ADJ
app01-8386	2	53	engineering	engineering	NOUN
app01-8386	2	54	(	(	PUNCT
app01-8386	2	55	ibk	ibk	ADJ
app01-8386	2	56	)	)	PUNCT
app01-8386	2	57	,	,	PUNCT
app01-8386	2	58	chair	chair	NOUN
app01-8386	2	59	for	for	ADP
app01-8386	2	60	concrete	concrete	ADJ
app01-8386	2	61	structures	structure	NOUN
app01-8386	2	62	and	and	CCONJ
app01-8386	2	63	bridge	bridge	NOUN
app01-8386	2	64	design	design	NOUN
app01-8386	2	65	,	,	PUNCT
app01-8386	2	66	stefano	stefano	PROPN
app01-8386	2	67	-	-	PUNCT
app01-8386	2	68	franscini	franscini	PROPN
app01-8386	2	69	-	-	PUNCT
app01-8386	2	70	platz	platz	ADJ
app01-8386	2	71	5	5	NUM
app01-8386	2	72	,	,	PUNCT
app01-8386	2	73	ch-8093	ch-8093	PROPN
app01-8386	2	74	zürich	zürich	PROPN
app01-8386	2	75	,	,	PUNCT
app01-8386	2	76	switzerland	switzerland	PROPN
app01-8386	2	77	b	b	PROPN
app01-8386	2	78	eth	eth	PROPN
app01-8386	2	79	zürich	zürich	PROPN
app01-8386	2	80	,	,	PUNCT
app01-8386	2	81	center	center	NOUN
app01-8386	2	82	for	for	ADP
app01-8386	2	83	augmented	augment	VERB
app01-8386	2	84	computational	computational	ADJ
app01-8386	2	85	design	design	NOUN
app01-8386	2	86	in	in	ADP
app01-8386	2	87	architecture	architecture	NOUN
app01-8386	2	88	,	,	PUNCT
app01-8386	2	89	engineering	engineering	NOUN
app01-8386	2	90	and	and	CCONJ
app01-8386	2	91	construction	construction	NOUN
app01-8386	2	92	,	,	PUNCT
app01-8386	2	93	design++	design++	NOUN
app01-8386	2	94	initiative	initiative	NOUN
app01-8386	2	95	and	and	CCONJ
app01-8386	2	96	immersive	immersive	ADJ
app01-8386	2	97	design	design	NOUN
app01-8386	2	98	lab	lab	NOUN
app01-8386	2	99	,	,	PUNCT
app01-8386	2	100	stefano	stefano	PROPN
app01-8386	2	101	-	-	PUNCT
app01-8386	2	102	franscini	franscini	PROPN
app01-8386	2	103	-	-	PUNCT
app01-8386	2	104	platz	platz	ADJ
app01-8386	2	105	5	5	NUM
app01-8386	2	106	,	,	PUNCT
app01-8386	2	107	ch-8093	ch-8093	PROPN
app01-8386	2	108	zürich	zürich	PROPN
app01-8386	2	109	,	,	PUNCT
app01-8386	2	110	switzerland	switzerland	PROPN
app01-8386	2	111	∗	∗	NOUN
app01-8386	2	112	corresponding	correspond	VERB
app01-8386	2	113	author	author	NOUN
app01-8386	2	114	:	:	PUNCT
app01-8386	2	115	kraus@ibk.baug.ethz.ch	kraus@ibk.baug.ethz.ch	X
app01-8386	2	116	abstract	abstract	ADJ
app01-8386	2	117	.	.	PUNCT
app01-8386	3	1	realistic	realistic	ADJ
app01-8386	3	2	structural	structural	ADJ
app01-8386	3	3	analyses	analysis	NOUN
app01-8386	3	4	and	and	CCONJ
app01-8386	3	5	optimisations	optimisation	NOUN
app01-8386	3	6	using	use	VERB
app01-8386	3	7	the	the	DET
app01-8386	3	8	non	non	ADJ
app01-8386	3	9	-	-	ADJ
app01-8386	3	10	linear	linear	ADJ
app01-8386	3	11	finite	finite	ADJ
app01-8386	3	12	element	element	NOUN
app01-8386	3	13	method	method	NOUN
app01-8386	3	14	are	be	AUX
app01-8386	3	15	possible	possible	ADJ
app01-8386	3	16	today	today	NOUN
app01-8386	3	17	yet	yet	ADV
app01-8386	3	18	suffer	suffer	VERB
app01-8386	3	19	from	from	ADP
app01-8386	3	20	being	be	AUX
app01-8386	3	21	very	very	ADV
app01-8386	3	22	time	time	NOUN
app01-8386	3	23	-	-	PUNCT
app01-8386	3	24	consuming	consume	VERB
app01-8386	3	25	,	,	PUNCT
app01-8386	3	26	particularly	particularly	ADV
app01-8386	3	27	in	in	ADP
app01-8386	3	28	case	case	NOUN
app01-8386	3	29	of	of	ADP
app01-8386	3	30	reinforced	reinforce	VERB
app01-8386	3	31	concrete	concrete	ADJ
app01-8386	3	32	plates	plate	NOUN
app01-8386	3	33	and	and	CCONJ
app01-8386	3	34	shells	shell	NOUN
app01-8386	3	35	.	.	PUNCT
app01-8386	4	1	hence	hence	ADV
app01-8386	4	2	such	such	ADJ
app01-8386	4	3	investigations	investigation	NOUN
app01-8386	4	4	are	be	AUX
app01-8386	4	5	currently	currently	ADV
app01-8386	4	6	dismissed	dismiss	VERB
app01-8386	4	7	in	in	ADP
app01-8386	4	8	the	the	DET
app01-8386	4	9	vast	vast	ADJ
app01-8386	4	10	majority	majority	NOUN
app01-8386	4	11	of	of	ADP
app01-8386	4	12	cases	case	NOUN
app01-8386	4	13	in	in	ADP
app01-8386	4	14	practice	practice	NOUN
app01-8386	4	15	.	.	PUNCT
app01-8386	5	1	the	the	DET
app01-8386	5	2	"	"	PUNCT
app01-8386	5	3	artificial	artificial	ADJ
app01-8386	5	4	intelligence	intelligence	NOUN
app01-8386	5	5	finite	finite	PROPN
app01-8386	5	6	element	element	NOUN
app01-8386	5	7	hybrids	hybrid	NOUN
app01-8386	5	8	"	"	PUNCT
app01-8386	5	9	project	project	NOUN
app01-8386	5	10	addresses	address	VERB
app01-8386	5	11	the	the	DET
app01-8386	5	12	current	current	ADJ
app01-8386	5	13	unsatisfactory	unsatisfactory	ADJ
app01-8386	5	14	situation	situation	NOUN
app01-8386	5	15	with	with	ADP
app01-8386	5	16	an	an	DET
app01-8386	5	17	approach	approach	NOUN
app01-8386	5	18	that	that	PRON
app01-8386	5	19	combines	combine	VERB
app01-8386	5	20	non	non	ADJ
app01-8386	5	21	-	-	ADJ
app01-8386	5	22	linear	linear	ADJ
app01-8386	5	23	finite	finite	ADJ
app01-8386	5	24	element	element	NOUN
app01-8386	5	25	models	model	NOUN
app01-8386	5	26	for	for	ADP
app01-8386	5	27	reinforced	reinforce	VERB
app01-8386	5	28	concrete	concrete	ADJ
app01-8386	5	29	shells	shell	NOUN
app01-8386	5	30	with	with	ADP
app01-8386	5	31	scientific	scientific	ADJ
app01-8386	5	32	machine	machine	NOUN
app01-8386	5	33	learning	learn	VERB
app01-8386	5	34	algorithms	algorithm	NOUN
app01-8386	5	35	to	to	PART
app01-8386	5	36	create	create	VERB
app01-8386	5	37	hybrid	hybrid	ADJ
app01-8386	5	38	ai	ai	ADJ
app01-8386	5	39	-	-	PUNCT
app01-8386	5	40	fem	fem	NOUN
app01-8386	5	41	models	model	NOUN
app01-8386	5	42	.	.	PUNCT
app01-8386	6	1	the	the	DET
app01-8386	6	2	ai	ai	NOUN
app01-8386	6	3	-	-	PUNCT
app01-8386	6	4	based	base	VERB
app01-8386	6	5	surrogate	surrogate	ADJ
app01-8386	6	6	material	material	NOUN
app01-8386	6	7	model	model	NOUN
app01-8386	6	8	provides	provide	VERB
app01-8386	6	9	the	the	DET
app01-8386	6	10	material	material	NOUN
app01-8386	6	11	stiffness	stiffness	NOUN
app01-8386	6	12	as	as	ADV
app01-8386	6	13	well	well	ADV
app01-8386	6	14	as	as	ADP
app01-8386	6	15	the	the	DET
app01-8386	6	16	stress	stress	NOUN
app01-8386	6	17	tensor	tensor	NOUN
app01-8386	6	18	for	for	ADP
app01-8386	6	19	given	give	VERB
app01-8386	6	20	concrete	concrete	ADJ
app01-8386	6	21	design	design	NOUN
app01-8386	6	22	parameters	parameter	NOUN
app01-8386	6	23	and	and	CCONJ
app01-8386	6	24	the	the	DET
app01-8386	6	25	strain	strain	NOUN
app01-8386	6	26	tensor	tensor	NOUN
app01-8386	6	27	.	.	PUNCT
app01-8386	7	1	this	this	DET
app01-8386	7	2	paper	paper	NOUN
app01-8386	7	3	reports	report	NOUN
app01-8386	7	4	on	on	ADP
app01-8386	7	5	the	the	DET
app01-8386	7	6	current	current	ADJ
app01-8386	7	7	status	status	NOUN
app01-8386	7	8	of	of	ADP
app01-8386	7	9	the	the	DET
app01-8386	7	10	project	project	NOUN
app01-8386	7	11	and	and	CCONJ
app01-8386	7	12	findings	finding	NOUN
app01-8386	7	13	of	of	ADP
app01-8386	7	14	the	the	DET
app01-8386	7	15	calibration	calibration	NOUN
app01-8386	7	16	of	of	ADP
app01-8386	7	17	the	the	DET
app01-8386	7	18	ai	ai	NOUN
app01-8386	7	19	-	-	PUNCT
app01-8386	7	20	based	base	VERB
app01-8386	7	21	reinforced	reinforce	VERB
app01-8386	7	22	concrete	concrete	ADJ
app01-8386	7	23	material	material	NOUN
app01-8386	7	24	model	model	NOUN
app01-8386	7	25	.	.	PUNCT
app01-8386	8	1	we	we	PRON
app01-8386	8	2	successfully	successfully	ADV
app01-8386	8	3	calibrated	calibrate	VERB
app01-8386	8	4	and	and	CCONJ
app01-8386	8	5	evaluated	evaluate	VERB
app01-8386	8	6	k	k	ADJ
app01-8386	8	7	-	-	PUNCT
app01-8386	8	8	nearest	near	ADV
app01-8386	8	9	-	-	PUNCT
app01-8386	8	10	neighbour	neighbour	NOUN
app01-8386	8	11	,	,	PUNCT
app01-8386	8	12	lgbm	lgbm	ADJ
app01-8386	8	13	and	and	CCONJ
app01-8386	8	14	resnet	resnet	ADJ
app01-8386	8	15	algorithms	algorithm	NOUN
app01-8386	8	16	and	and	CCONJ
app01-8386	8	17	report	report	VERB
app01-8386	8	18	their	their	PRON
app01-8386	8	19	predictive	predictive	ADJ
app01-8386	8	20	capabilities	capability	NOUN
app01-8386	8	21	.	.	PUNCT
app01-8386	9	1	finally	finally	ADV
app01-8386	9	2	,	,	PUNCT
app01-8386	9	3	some	some	DET
app01-8386	9	4	light	light	NOUN
app01-8386	9	5	is	be	AUX
app01-8386	9	6	shed	shed	VERB
app01-8386	9	7	on	on	ADP
app01-8386	9	8	the	the	DET
app01-8386	9	9	future	future	ADJ
app01-8386	9	10	work	work	NOUN
app01-8386	9	11	of	of	ADP
app01-8386	9	12	integrating	integrate	VERB
app01-8386	9	13	the	the	DET
app01-8386	9	14	ai	ai	ADJ
app01-8386	9	15	surrogate	surrogate	ADJ
app01-8386	9	16	material	material	NOUN
app01-8386	9	17	models	model	NOUN
app01-8386	9	18	back	back	ADV
app01-8386	9	19	into	into	ADP
app01-8386	9	20	the	the	DET
app01-8386	9	21	finite	finite	ADJ
app01-8386	9	22	element	element	NOUN
app01-8386	9	23	method	method	NOUN
app01-8386	9	24	in	in	ADP
app01-8386	9	25	the	the	DET
app01-8386	9	26	course	course	NOUN
app01-8386	9	27	of	of	ADP
app01-8386	9	28	the	the	DET
app01-8386	9	29	numerical	numerical	ADJ
app01-8386	9	30	analysis	analysis	NOUN
app01-8386	9	31	of	of	ADP
app01-8386	9	32	reinforced	reinforce	VERB
app01-8386	9	33	concrete	concrete	ADJ
app01-8386	9	34	structures	structure	NOUN
app01-8386	9	35	.	.	PUNCT
app01-8386	10	1	keywords	keyword	NOUN
app01-8386	10	2	:	:	PUNCT
app01-8386	10	3	concrete	concrete	ADJ
app01-8386	10	4	material	material	NOUN
app01-8386	10	5	model	model	NOUN
app01-8386	10	6	,	,	PUNCT
app01-8386	10	7	machine	machine	NOUN
app01-8386	10	8	and	and	CCONJ
app01-8386	10	9	deep	deep	ADJ
app01-8386	10	10	learning	learning	NOUN
app01-8386	10	11	,	,	PUNCT
app01-8386	10	12	nonlinear	nonlinear	ADJ
app01-8386	10	13	finite	finite	PROPN
app01-8386	10	14	element	element	NOUN
app01-8386	10	15	method	method	NOUN
app01-8386	10	16	,	,	PUNCT
app01-8386	10	17	surrogate	surrogate	ADJ
app01-8386	10	18	modeling	modeling	NOUN
app01-8386	10	19	,	,	PUNCT
app01-8386	10	20	uncertainty	uncertainty	NOUN
app01-8386	10	21	quantification	quantification	NOUN
app01-8386	10	22	.	.	PUNCT
app01-8386	11	1	1	1	X
app01-8386	11	2	.	.	X
app01-8386	11	3	introduction	introduction	NOUN
app01-8386	11	4	digital	digital	ADJ
app01-8386	11	5	design	design	NOUN
app01-8386	11	6	and	and	CCONJ
app01-8386	11	7	manufacturing	manufacturing	NOUN
app01-8386	11	8	methods	method	NOUN
app01-8386	11	9	,	,	PUNCT
app01-8386	11	10	such	such	ADJ
app01-8386	11	11	as	as	ADP
app01-8386	11	12	those	those	PRON
app01-8386	11	13	to	to	PART
app01-8386	11	14	be	be	AUX
app01-8386	11	15	developed	develop	VERB
app01-8386	11	16	at	at	ADP
app01-8386	11	17	the	the	DET
app01-8386	11	18	new	new	ADJ
app01-8386	11	19	immersive	immersive	NOUN
app01-8386	11	20	design	design	NOUN
app01-8386	11	21	lab	lab	NOUN
app01-8386	11	22	(	(	PUNCT
app01-8386	11	23	idl	idl	NOUN
app01-8386	11	24	)	)	PUNCT
app01-8386	11	25	at	at	ADP
app01-8386	11	26	eth	eth	PROPN
app01-8386	11	27	zurich	zurich	PROPN
app01-8386	11	28	,	,	PUNCT
app01-8386	11	29	offer	offer	VERB
app01-8386	11	30	great	great	ADJ
app01-8386	11	31	potential	potential	NOUN
app01-8386	11	32	for	for	ADP
app01-8386	11	33	significantly	significantly	ADV
app01-8386	11	34	more	more	ADV
app01-8386	11	35	efficient	efficient	ADJ
app01-8386	11	36	and	and	CCONJ
app01-8386	11	37	sustainable	sustainable	ADJ
app01-8386	11	38	construction	construction	NOUN
app01-8386	11	39	.	.	PUNCT
app01-8386	12	1	in	in	ADP
app01-8386	12	2	order	order	NOUN
app01-8386	12	3	to	to	PART
app01-8386	12	4	ensure	ensure	VERB
app01-8386	12	5	the	the	DET
app01-8386	12	6	structural	structural	ADJ
app01-8386	12	7	safety	safety	NOUN
app01-8386	12	8	,	,	PUNCT
app01-8386	12	9	economic	economic	ADJ
app01-8386	12	10	efficiency	efficiency	NOUN
app01-8386	12	11	and	and	CCONJ
app01-8386	12	12	sustainability	sustainability	NOUN
app01-8386	12	13	of	of	ADP
app01-8386	12	14	complex	complex	ADJ
app01-8386	12	15	structures	structure	NOUN
app01-8386	12	16	,	,	PUNCT
app01-8386	12	17	reliable	reliable	ADJ
app01-8386	12	18	and	and	CCONJ
app01-8386	12	19	powerful	powerful	ADJ
app01-8386	12	20	models	model	NOUN
app01-8386	12	21	for	for	ADP
app01-8386	12	22	automatic	automatic	ADJ
app01-8386	12	23	analysis	analysis	NOUN
app01-8386	12	24	,	,	PUNCT
app01-8386	12	25	optimisation	optimisation	NOUN
app01-8386	12	26	and	and	CCONJ
app01-8386	12	27	design	design	NOUN
app01-8386	12	28	are	be	AUX
app01-8386	12	29	essential	essential	ADJ
app01-8386	12	30	.	.	PUNCT
app01-8386	13	1	however	however	ADV
app01-8386	13	2	,	,	PUNCT
app01-8386	13	3	such	such	ADJ
app01-8386	13	4	models	model	NOUN
app01-8386	13	5	are	be	AUX
app01-8386	13	6	largely	largely	ADV
app01-8386	13	7	lacking	lack	VERB
app01-8386	13	8	to	to	ADP
app01-8386	13	9	date	date	NOUN
app01-8386	13	10	.	.	PUNCT
app01-8386	14	1	this	this	PRON
app01-8386	14	2	is	be	AUX
app01-8386	14	3	especially	especially	ADV
app01-8386	14	4	true	true	ADJ
app01-8386	14	5	for	for	ADP
app01-8386	14	6	concrete	concrete	ADJ
app01-8386	14	7	structures	structure	NOUN
app01-8386	14	8	,	,	PUNCT
app01-8386	14	9	as	as	SCONJ
app01-8386	14	10	their	their	PRON
app01-8386	14	11	behaviour	behaviour	NOUN
app01-8386	14	12	is	be	AUX
app01-8386	14	13	highly	highly	ADV
app01-8386	14	14	non	non	ADJ
app01-8386	14	15	-	-	ADJ
app01-8386	14	16	linear	linear	ADJ
app01-8386	14	17	.	.	PUNCT
app01-8386	15	1	realistic	realistic	ADJ
app01-8386	15	2	structural	structural	ADJ
app01-8386	15	3	analyses	analysis	NOUN
app01-8386	15	4	and	and	CCONJ
app01-8386	15	5	optimisations	optimisation	NOUN
app01-8386	15	6	using	use	VERB
app01-8386	15	7	the	the	DET
app01-8386	15	8	non	non	ADJ
app01-8386	15	9	-	-	ADJ
app01-8386	15	10	linear	linear	ADJ
app01-8386	15	11	finite	finite	ADJ
app01-8386	15	12	element	element	NOUN
app01-8386	15	13	method	method	NOUN
app01-8386	15	14	(	(	PUNCT
app01-8386	15	15	fem	fem	NOUN
app01-8386	15	16	)	)	PUNCT
app01-8386	15	17	are	be	AUX
app01-8386	15	18	possible	possible	ADJ
app01-8386	15	19	today	today	NOUN
app01-8386	15	20	,	,	PUNCT
app01-8386	15	21	yet	yet	ADV
app01-8386	15	22	being	be	AUX
app01-8386	15	23	very	very	ADV
app01-8386	15	24	time	time	NOUN
app01-8386	15	25	-	-	PUNCT
app01-8386	15	26	consuming	consume	VERB
app01-8386	15	27	even	even	ADV
app01-8386	15	28	for	for	ADP
app01-8386	15	29	the	the	DET
app01-8386	15	30	case	case	NOUN
app01-8386	15	31	of	of	ADP
app01-8386	15	32	extraordinary	extraordinary	ADJ
app01-8386	15	33	computational	computational	ADJ
app01-8386	15	34	capacities	capacity	NOUN
app01-8386	15	35	.	.	PUNCT
app01-8386	16	1	for	for	ADP
app01-8386	16	2	reasons	reason	NOUN
app01-8386	16	3	of	of	ADP
app01-8386	16	4	temporal	temporal	ADJ
app01-8386	16	5	and	and	CCONJ
app01-8386	16	6	monetary	monetary	ADJ
app01-8386	16	7	efficiency	efficiency	NOUN
app01-8386	16	8	,	,	PUNCT
app01-8386	16	9	established	establish	VERB
app01-8386	16	10	traditional	traditional	ADJ
app01-8386	16	11	and	and	CCONJ
app01-8386	16	12	in	in	ADP
app01-8386	16	13	many	many	ADJ
app01-8386	16	14	cases	case	NOUN
app01-8386	16	15	excessively	excessively	ADV
app01-8386	16	16	conservative	conservative	ADJ
app01-8386	16	17	design	design	NOUN
app01-8386	16	18	methods	method	NOUN
app01-8386	16	19	without	without	ADP
app01-8386	16	20	structural	structural	ADJ
app01-8386	16	21	optimisation	optimisation	NOUN
app01-8386	16	22	are	be	AUX
app01-8386	16	23	still	still	ADV
app01-8386	16	24	used	use	VERB
app01-8386	16	25	in	in	ADP
app01-8386	16	26	the	the	DET
app01-8386	16	27	vast	vast	ADJ
app01-8386	16	28	majority	majority	NOUN
app01-8386	16	29	of	of	ADP
app01-8386	16	30	projects	project	NOUN
app01-8386	16	31	in	in	ADP
app01-8386	16	32	practice	practice	NOUN
app01-8386	16	33	today	today	NOUN
app01-8386	16	34	.	.	PUNCT
app01-8386	17	1	the	the	DET
app01-8386	17	2	increased	increase	VERB
app01-8386	17	3	public	public	ADJ
app01-8386	17	4	awareness	awareness	NOUN
app01-8386	17	5	of	of	ADP
app01-8386	17	6	and	and	CCONJ
app01-8386	17	7	demand	demand	VERB
app01-8386	17	8	for	for	ADP
app01-8386	17	9	a	a	DET
app01-8386	17	10	sustainable	sustainable	ADJ
app01-8386	17	11	built	build	VERB
app01-8386	17	12	environment	environment	NOUN
app01-8386	17	13	however	however	ADV
app01-8386	17	14	urges	urge	VERB
app01-8386	17	15	civil	civil	ADJ
app01-8386	17	16	engineers	engineer	NOUN
app01-8386	17	17	to	to	PART
app01-8386	17	18	make	make	VERB
app01-8386	17	19	use	use	NOUN
app01-8386	17	20	of	of	ADP
app01-8386	17	21	structural	structural	ADJ
app01-8386	17	22	efficiency	efficiency	NOUN
app01-8386	17	23	to	to	ADP
app01-8386	17	24	the	the	DET
app01-8386	17	25	maximum	maximum	ADJ
app01-8386	17	26	level	level	NOUN
app01-8386	17	27	possible	possible	ADJ
app01-8386	17	28	.	.	PUNCT
app01-8386	18	1	to	to	ADP
app01-8386	18	2	that	that	DET
app01-8386	18	3	end	end	NOUN
app01-8386	18	4	,	,	PUNCT
app01-8386	18	5	a	a	DET
app01-8386	18	6	two	two	NUM
app01-8386	18	7	-	-	PUNCT
app01-8386	18	8	phased	phase	VERB
app01-8386	18	9	research	research	NOUN
app01-8386	18	10	program	program	NOUN
app01-8386	18	11	[	[	X
app01-8386	18	12	1	1	NUM
app01-8386	18	13	,	,	PUNCT
app01-8386	18	14	2	2	NUM
app01-8386	18	15	]	]	PUNCT
app01-8386	18	16	is	be	AUX
app01-8386	18	17	proposed	propose	VERB
app01-8386	18	18	to	to	PART
app01-8386	18	19	address	address	VERB
app01-8386	18	20	this	this	DET
app01-8386	18	21	unsatisfactory	unsatisfactory	ADJ
app01-8386	18	22	situation	situation	NOUN
app01-8386	18	23	.	.	PUNCT
app01-8386	19	1	in	in	ADP
app01-8386	19	2	the	the	DET
app01-8386	19	3	first	first	ADJ
app01-8386	19	4	phase	phase	NOUN
app01-8386	19	5	,	,	PUNCT
app01-8386	19	6	non	non	ADJ
app01-8386	19	7	-	-	ADJ
app01-8386	19	8	linear	linear	ADJ
app01-8386	19	9	fem	fem	NOUN
app01-8386	19	10	for	for	ADP
app01-8386	19	11	reinforced	reinforce	VERB
app01-8386	19	12	concrete	concrete	ADJ
app01-8386	19	13	plates	plate	NOUN
app01-8386	19	14	and	and	CCONJ
app01-8386	19	15	slabs	slab	NOUN
app01-8386	19	16	developed	develop	VERB
app01-8386	19	17	at	at	ADP
app01-8386	19	18	eth	eth	PROPN
app01-8386	19	19	zurich	zurich	PROPN
app01-8386	20	1	[	[	X
app01-8386	20	2	3–8	3–8	NUM
app01-8386	20	3	]	]	X
app01-8386	20	4	are	be	AUX
app01-8386	20	5	combined	combine	VERB
app01-8386	20	6	with	with	ADP
app01-8386	20	7	scientific	scientific	ADJ
app01-8386	20	8	machine	machine	NOUN
app01-8386	20	9	learning	learning	NOUN
app01-8386	20	10	(	(	PUNCT
app01-8386	20	11	sciml	sciml	NOUN
app01-8386	20	12	)	)	PUNCT
app01-8386	20	13	algorithms	algorithm	NOUN
app01-8386	20	14	to	to	PART
app01-8386	20	15	create	create	VERB
app01-8386	20	16	hybrid	hybrid	ADJ
app01-8386	20	17	ai	ai	ADJ
app01-8386	20	18	-	-	PUNCT
app01-8386	20	19	fem	fem	NOUN
app01-8386	20	20	models	model	NOUN
app01-8386	20	21	,	,	PUNCT
app01-8386	20	22	which	which	PRON
app01-8386	20	23	are	be	AUX
app01-8386	20	24	expected	expect	VERB
app01-8386	20	25	to	to	PART
app01-8386	20	26	be	be	AUX
app01-8386	20	27	much	much	ADV
app01-8386	20	28	more	more	ADV
app01-8386	20	29	efficient	efficient	ADJ
app01-8386	20	30	compared	compare	VERB
app01-8386	20	31	to	to	ADP
app01-8386	20	32	established	establish	VERB
app01-8386	20	33	analysis	analysis	NOUN
app01-8386	20	34	methods	method	NOUN
app01-8386	20	35	both	both	CCONJ
app01-8386	20	36	in	in	ADP
app01-8386	20	37	terms	term	NOUN
app01-8386	20	38	of	of	ADP
app01-8386	20	39	the	the	DET
app01-8386	20	40	computing	computing	NOUN
app01-8386	20	41	power	power	NOUN
app01-8386	20	42	required	require	VERB
app01-8386	20	43	and	and	CCONJ
app01-8386	20	44	the	the	DET
app01-8386	20	45	reliability	reliability	NOUN
app01-8386	20	46	of	of	ADP
app01-8386	20	47	predicting	predict	VERB
app01-8386	20	48	the	the	DET
app01-8386	20	49	load	load	NOUN
app01-8386	20	50	-	-	PUNCT
app01-8386	20	51	bearing	bear	VERB
app01-8386	20	52	behaviour	behaviour	NOUN
app01-8386	20	53	.	.	PUNCT
app01-8386	21	1	in	in	ADP
app01-8386	21	2	the	the	DET
app01-8386	21	3	second	second	ADJ
app01-8386	21	4	phase	phase	NOUN
app01-8386	21	5	of	of	ADP
app01-8386	21	6	this	this	DET
app01-8386	21	7	project	project	NOUN
app01-8386	21	8	,	,	PUNCT
app01-8386	21	9	the	the	DET
app01-8386	21	10	ai	ai	NOUN
app01-8386	21	11	-	-	PUNCT
app01-8386	21	12	fem	fem	NOUN
app01-8386	21	13	-	-	PUNCT
app01-8386	21	14	hybrids	hybrid	NOUN
app01-8386	21	15	will	will	AUX
app01-8386	21	16	be	be	AUX
app01-8386	21	17	used	use	VERB
app01-8386	21	18	within	within	ADP
app01-8386	21	19	a	a	DET
app01-8386	21	20	novel	novel	ADJ
app01-8386	21	21	generative	generative	ADJ
app01-8386	21	22	design	design	NOUN
app01-8386	21	23	process	process	NOUN
app01-8386	21	24	for	for	ADP
app01-8386	21	25	accelerated	accelerate	VERB
app01-8386	21	26	yet	yet	CCONJ
app01-8386	21	27	realistic	realistic	ADJ
app01-8386	21	28	conceptual	conceptual	ADJ
app01-8386	21	29	design	design	NOUN
app01-8386	21	30	of	of	ADP
app01-8386	21	31	bridges	bridge	NOUN
app01-8386	21	32	[	[	X
app01-8386	21	33	1	1	NUM
app01-8386	21	34	,	,	PUNCT
app01-8386	21	35	2	2	NUM
app01-8386	21	36	]	]	PUNCT
app01-8386	21	37	.	.	PUNCT
app01-8386	22	1	within	within	ADP
app01-8386	22	2	a	a	DET
app01-8386	22	3	fe	fe	NOUN
app01-8386	22	4	analysis	analysis	NOUN
app01-8386	22	5	,	,	PUNCT
app01-8386	22	6	a	a	DET
app01-8386	22	7	material	material	NOUN
app01-8386	22	8	model	model	NOUN
app01-8386	22	9	has	have	VERB
app01-8386	22	10	to	to	PART
app01-8386	22	11	provide	provide	VERB
app01-8386	22	12	on	on	ADP
app01-8386	22	13	the	the	DET
app01-8386	22	14	one	one	NUM
app01-8386	22	15	hand	hand	NOUN
app01-8386	22	16	the	the	DET
app01-8386	22	17	material	material	NOUN
app01-8386	22	18	stiffness	stiffness	NOUN
app01-8386	22	19	matrix	matrix	NOUN
app01-8386	22	20	and	and	CCONJ
app01-8386	22	21	on	on	ADP
app01-8386	22	22	the	the	DET
app01-8386	22	23	other	other	ADJ
app01-8386	22	24	hand	hand	NOUN
app01-8386	22	25	the	the	DET
app01-8386	22	26	current	current	ADJ
app01-8386	22	27	stress	stress	NOUN
app01-8386	22	28	state	state	NOUN
app01-8386	22	29	.	.	PUNCT
app01-8386	23	1	in	in	ADP
app01-8386	23	2	the	the	DET
app01-8386	23	3	novel	novel	ADJ
app01-8386	23	4	hybrid	hybrid	ADJ
app01-8386	23	5	artificial	artificial	ADJ
app01-8386	23	6	intelligence	intelligence	NOUN
app01-8386	23	7	finite	finite	PROPN
app01-8386	23	8	element	element	NOUN
app01-8386	23	9	(	(	PUNCT
app01-8386	23	10	aifem	aifem	NOUN
app01-8386	23	11	)	)	PUNCT
app01-8386	23	12	model	model	NOUN
app01-8386	23	13	implementation	implementation	NOUN
app01-8386	23	14	for	for	ADP
app01-8386	23	15	material	material	NOUN
app01-8386	23	16	-	-	PUNCT
app01-8386	23	17	nonlinear	nonlinear	ADJ
app01-8386	23	18	reinforced	reinforce	VERB
app01-8386	23	19	concrete	concrete	ADJ
app01-8386	23	20	slabs	slab	NOUN
app01-8386	23	21	and	and	CCONJ
app01-8386	23	22	plates	plate	NOUN
app01-8386	23	23	elements	element	NOUN
app01-8386	23	24	,	,	PUNCT
app01-8386	23	25	the	the	DET
app01-8386	23	26	mathematical	mathematical	ADJ
app01-8386	23	27	description	description	NOUN
app01-8386	23	28	of	of	ADP
app01-8386	23	29	the	the	DET
app01-8386	23	30	material	material	NOUN
app01-8386	23	31	model	model	NOUN
app01-8386	23	32	is	be	AUX
app01-8386	23	33	performed	perform	VERB
app01-8386	23	34	using	use	VERB
app01-8386	23	35	scientific	scientific	ADJ
app01-8386	23	36	machine	machine	NOUN
app01-8386	23	37	and	and	CCONJ
app01-8386	23	38	deep	deep	ADJ
app01-8386	23	39	learning	learning	NOUN
app01-8386	23	40	algorithms	algorithm	NOUN
app01-8386	23	41	,	,	PUNCT
app01-8386	23	42	which	which	PRON
app01-8386	23	43	act	act	VERB
app01-8386	23	44	as	as	ADP
app01-8386	23	45	functional	functional	ADJ
app01-8386	23	46	approximators	approximator	NOUN
app01-8386	23	47	of	of	ADP
app01-8386	23	48	the	the	DET
app01-8386	23	49	stress	stress	NOUN
app01-8386	23	50	-	-	PUNCT
app01-8386	23	51	strain	strain	NOUN
app01-8386	23	52	relationship	relationship	NOUN
app01-8386	23	53	and	and	CCONJ
app01-8386	23	54	the	the	DET
app01-8386	23	55	stiffness	stiffness	NOUN
app01-8386	23	56	-	-	PUNCT
app01-8386	23	57	strain	strain	NOUN
app01-8386	23	58	relationship	relationship	NOUN
app01-8386	23	59	based	base	VERB
app01-8386	23	60	on	on	ADP
app01-8386	23	61	numerical	numerical	ADJ
app01-8386	23	62	simulations	simulation	NOUN
app01-8386	23	63	.	.	PUNCT
app01-8386	24	1	the	the	DET
app01-8386	24	2	basic	basic	ADJ
app01-8386	24	3	data	datum	NOUN
app01-8386	24	4	set	set	VERB
app01-8386	24	5	for	for	ADP
app01-8386	24	6	training	training	NOUN
app01-8386	24	7	,	,	PUNCT
app01-8386	24	8	validation	validation	NOUN
app01-8386	24	9	and	and	CCONJ
app01-8386	24	10	testing	testing	NOUN
app01-8386	24	11	of	of	ADP
app01-8386	24	12	the	the	DET
app01-8386	24	13	ai	ai	NOUN
app01-8386	24	14	algorithms	algorithms	NOUN
app01-8386	24	15	is	be	AUX
app01-8386	24	16	generated	generate	VERB
app01-8386	24	17	by	by	ADP
app01-8386	24	18	extensive	extensive	ADJ
app01-8386	24	19	simulations	simulation	NOUN
app01-8386	24	20	of	of	ADP
app01-8386	24	21	strain	strain	ADJ
app01-8386	24	22	states	state	NOUN
app01-8386	24	23	for	for	ADP
app01-8386	24	24	different	different	ADJ
app01-8386	24	25	reinforced	reinforce	VERB
app01-8386	24	26	concrete	concrete	ADJ
app01-8386	24	27	configurations	configuration	NOUN
app01-8386	24	28	with	with	ADP
app01-8386	24	29	the	the	DET
app01-8386	24	30	material	material	NOUN
app01-8386	24	31	model	model	NOUN
app01-8386	24	32	for	for	ADP
app01-8386	24	33	reinforced	reinforce	VERB
app01-8386	24	34	99	99	NUM
app01-8386	24	35	https://doi.org/10.14311/app.2022.36.0099	https://doi.org/10.14311/app.2022.36.0099	ADJ
app01-8386	24	36	https://creativecommons.org/licenses/by/4.0/	https://creativecommons.org/licenses/by/4.0/	PROPN
app01-8386	24	37	https://www.cvut.cz/en	https://www.cvut.cz/en	PROPN
app01-8386	24	38	m.	m.	PROPN
app01-8386	24	39	a.	a.	PROPN
app01-8386	24	40	kraus	kraus	PROPN
app01-8386	24	41	,	,	PUNCT
app01-8386	24	42	r.	r.	PROPN
app01-8386	24	43	bischof	bischof	PROPN
app01-8386	24	44	,	,	PUNCT
app01-8386	24	45	w.	w.	PROPN
app01-8386	24	46	kaufmann	kaufmann	PROPN
app01-8386	24	47	,	,	PUNCT
app01-8386	24	48	k.	k.	PROPN
app01-8386	24	49	thoma	thoma	PROPN
app01-8386	24	50	acta	acta	PROPN
app01-8386	24	51	polytechnica	polytechnica	PROPN
app01-8386	24	52	ctu	ctu	NOUN
app01-8386	24	53	proceedings	proceeding	NOUN
app01-8386	24	54	concrete	concrete	ADJ
app01-8386	24	55	as	as	SCONJ
app01-8386	24	56	implemented	implement	VERB
app01-8386	24	57	in	in	ADP
app01-8386	24	58	the	the	DET
app01-8386	24	59	mentioned	mention	VERB
app01-8386	24	60	usermat	usermat	NOUN
app01-8386	24	61	in	in	ADP
app01-8386	24	62	ansys	ansys	PROPN
app01-8386	24	63	mechanical	mechanical	ADJ
app01-8386	24	64	apdl	apdl	PROPN
app01-8386	24	65	on	on	ADP
app01-8386	24	66	the	the	DET
app01-8386	24	67	basis	basis	NOUN
app01-8386	24	68	of	of	ADP
app01-8386	24	69	the	the	DET
app01-8386	24	70	cracked	crack	VERB
app01-8386	24	71	membrane	membrane	NOUN
app01-8386	24	72	model	model	NOUN
app01-8386	24	73	(	(	PUNCT
app01-8386	24	74	cmm	cmm	NOUN
app01-8386	24	75	)	)	PUNCT
app01-8386	24	76	in	in	ADP
app01-8386	24	77	combination	combination	NOUN
app01-8386	24	78	with	with	ADP
app01-8386	24	79	a	a	DET
app01-8386	24	80	reissner	reissner	NOUN
app01-8386	24	81	-	-	PUNCT
app01-8386	24	82	mindlin	mindlin	NOUN
app01-8386	24	83	layer	layer	NOUN
app01-8386	24	84	model	model	NOUN
app01-8386	24	85	.	.	PUNCT
app01-8386	25	1	this	this	DET
app01-8386	25	2	paper	paper	NOUN
app01-8386	25	3	describes	describe	VERB
app01-8386	25	4	the	the	DET
app01-8386	25	5	process	process	NOUN
app01-8386	25	6	of	of	ADP
app01-8386	25	7	data	datum	NOUN
app01-8386	25	8	generation	generation	NOUN
app01-8386	25	9	and	and	CCONJ
app01-8386	25	10	calibration	calibration	NOUN
app01-8386	25	11	of	of	ADP
app01-8386	25	12	the	the	DET
app01-8386	25	13	ai	ai	NOUN
app01-8386	25	14	-	-	PUNCT
app01-8386	25	15	based	base	VERB
app01-8386	25	16	reinforced	reinforce	VERB
app01-8386	25	17	concrete	concrete	ADJ
app01-8386	25	18	material	material	NOUN
app01-8386	25	19	model	model	NOUN
app01-8386	25	20	for	for	ADP
app01-8386	25	21	different	different	ADJ
app01-8386	25	22	machine	machine	NOUN
app01-8386	25	23	and	and	CCONJ
app01-8386	25	24	deep	deep	ADJ
app01-8386	25	25	learning	learning	NOUN
app01-8386	25	26	algorithms	algorithm	NOUN
app01-8386	25	27	for	for	ADP
app01-8386	25	28	stress	stress	NOUN
app01-8386	25	29	and	and	CCONJ
app01-8386	25	30	stiffness	stiffness	ADJ
app01-8386	25	31	tensor	tensor	NOUN
app01-8386	25	32	prediction	prediction	NOUN
app01-8386	25	33	.	.	PUNCT
app01-8386	26	1	this	this	DET
app01-8386	26	2	paper	paper	NOUN
app01-8386	26	3	is	be	AUX
app01-8386	26	4	organised	organise	VERB
app01-8386	26	5	as	as	SCONJ
app01-8386	26	6	follows	follow	VERB
app01-8386	26	7	:	:	PUNCT
app01-8386	26	8	we	we	PRON
app01-8386	26	9	first	first	ADV
app01-8386	26	10	provide	provide	VERB
app01-8386	26	11	background	background	NOUN
app01-8386	26	12	on	on	ADP
app01-8386	26	13	the	the	DET
app01-8386	26	14	materials	material	NOUN
app01-8386	26	15	and	and	CCONJ
app01-8386	26	16	methods	method	NOUN
app01-8386	26	17	from	from	ADP
app01-8386	26	18	computational	computational	ADJ
app01-8386	26	19	mechanics	mechanic	NOUN
app01-8386	26	20	and	and	CCONJ
app01-8386	26	21	scientific	scientific	ADJ
app01-8386	26	22	machine	machine	NOUN
app01-8386	26	23	learning	learning	NOUN
app01-8386	26	24	used	use	VERB
app01-8386	26	25	in	in	ADP
app01-8386	26	26	this	this	DET
app01-8386	26	27	paper	paper	NOUN
app01-8386	26	28	in	in	ADP
app01-8386	26	29	sec	sec	PROPN
app01-8386	26	30	.	.	PROPN
app01-8386	27	1	2	2	NUM
app01-8386	27	2	.	.	X
app01-8386	27	3	sec	sec	PROPN
app01-8386	27	4	.	.	PROPN
app01-8386	27	5	3	3	NUM
app01-8386	27	6	reports	report	NOUN
app01-8386	27	7	and	and	CCONJ
app01-8386	27	8	presents	present	VERB
app01-8386	27	9	selected	select	VERB
app01-8386	27	10	numerical	numerical	ADJ
app01-8386	27	11	results	result	NOUN
app01-8386	27	12	of	of	ADP
app01-8386	27	13	the	the	DET
app01-8386	27	14	sciml	sciml	NOUN
app01-8386	27	15	-	-	PUNCT
app01-8386	27	16	based	base	VERB
app01-8386	27	17	substitute	substitute	NOUN
app01-8386	27	18	concrete	concrete	ADJ
app01-8386	27	19	material	material	NOUN
app01-8386	27	20	models	model	NOUN
app01-8386	27	21	w.r.t	w.r.t	VERB
app01-8386	27	22	.	.	PUNCT
app01-8386	28	1	their	their	PRON
app01-8386	28	2	approximation	approximation	NOUN
app01-8386	28	3	accuracy	accuracy	NOUN
app01-8386	28	4	and	and	CCONJ
app01-8386	28	5	statistical	statistical	ADJ
app01-8386	28	6	qualities	quality	NOUN
app01-8386	28	7	.	.	PUNCT
app01-8386	29	1	sec	sec	PROPN
app01-8386	29	2	.	.	PROPN
app01-8386	29	3	4	4	NUM
app01-8386	29	4	presents	present	VERB
app01-8386	29	5	a	a	DET
app01-8386	29	6	discussion	discussion	NOUN
app01-8386	29	7	of	of	ADP
app01-8386	29	8	current	current	ADJ
app01-8386	29	9	findings	finding	NOUN
app01-8386	29	10	and	and	CCONJ
app01-8386	29	11	sec	sec	PROPN
app01-8386	29	12	.	.	PROPN
app01-8386	29	13	5	5	NUM
app01-8386	29	14	sheds	shed	VERB
app01-8386	29	15	light	light	NOUN
app01-8386	29	16	on	on	ADP
app01-8386	29	17	the	the	DET
app01-8386	29	18	future	future	ADJ
app01-8386	29	19	steps	step	NOUN
app01-8386	29	20	of	of	ADP
app01-8386	29	21	incorporating	incorporate	VERB
app01-8386	29	22	the	the	DET
app01-8386	29	23	sciml	sciml	NOUN
app01-8386	29	24	-	-	PUNCT
app01-8386	29	25	based	base	VERB
app01-8386	29	26	substitute	substitute	NOUN
app01-8386	29	27	concrete	concrete	ADJ
app01-8386	29	28	material	material	NOUN
app01-8386	29	29	models	model	NOUN
app01-8386	29	30	into	into	ADP
app01-8386	29	31	the	the	DET
app01-8386	29	32	fem	fem	NOUN
app01-8386	29	33	software	software	NOUN
app01-8386	29	34	ansys	ansys	PROPN
app01-8386	29	35	.	.	PUNCT
app01-8386	30	1	2	2	X
app01-8386	30	2	.	.	X
app01-8386	30	3	materials	material	NOUN
app01-8386	30	4	and	and	CCONJ
app01-8386	30	5	methods	method	NOUN
app01-8386	30	6	this	this	DET
app01-8386	30	7	section	section	NOUN
app01-8386	30	8	reports	report	VERB
app01-8386	30	9	on	on	ADP
app01-8386	30	10	materials	material	NOUN
app01-8386	30	11	and	and	CCONJ
app01-8386	30	12	methods	method	NOUN
app01-8386	30	13	for	for	ADP
app01-8386	30	14	database	database	NOUN
app01-8386	30	15	generation	generation	NOUN
app01-8386	30	16	,	,	PUNCT
app01-8386	30	17	development	development	NOUN
app01-8386	30	18	of	of	ADP
app01-8386	30	19	machine	machine	NOUN
app01-8386	30	20	and	and	CCONJ
app01-8386	30	21	deep	deep	ADJ
app01-8386	30	22	learning	learning	NOUN
app01-8386	30	23	(	(	PUNCT
app01-8386	30	24	ml	ml	PROPN
app01-8386	30	25	/	/	SYM
app01-8386	30	26	dl	dl	NOUN
app01-8386	30	27	)	)	PUNCT
app01-8386	30	28	models	model	NOUN
app01-8386	30	29	,	,	PUNCT
app01-8386	30	30	and	and	CCONJ
app01-8386	30	31	the	the	DET
app01-8386	30	32	evaluation	evaluation	NOUN
app01-8386	30	33	criteria	criterion	NOUN
app01-8386	30	34	for	for	ADP
app01-8386	30	35	the	the	DET
app01-8386	30	36	performance	performance	NOUN
app01-8386	30	37	of	of	ADP
app01-8386	30	38	the	the	DET
app01-8386	30	39	developed	develop	VERB
app01-8386	30	40	models	model	NOUN
app01-8386	30	41	as	as	ADP
app01-8386	30	42	a	a	DET
app01-8386	30	43	surrogate	surrogate	NOUN
app01-8386	30	44	for	for	ADP
app01-8386	30	45	a	a	DET
app01-8386	30	46	fem	fem	NOUN
app01-8386	30	47	.	.	PROPN
app01-8386	31	1	2.1	2.1	NUM
app01-8386	31	2	.	.	PUNCT
app01-8386	31	3	concept	concept	NOUN
app01-8386	31	4	this	this	DET
app01-8386	31	5	research	research	NOUN
app01-8386	31	6	project	project	NOUN
app01-8386	31	7	explores	explore	VERB
app01-8386	31	8	the	the	DET
app01-8386	31	9	potential	potential	NOUN
app01-8386	31	10	of	of	ADP
app01-8386	31	11	using	use	VERB
app01-8386	31	12	ml	ml	PROPN
app01-8386	31	13	/	/	SYM
app01-8386	31	14	dl	dl	X
app01-8386	31	15	surrogate	surrogate	ADJ
app01-8386	31	16	models	model	NOUN
app01-8386	31	17	of	of	ADP
app01-8386	31	18	mechanically	mechanically	ADV
app01-8386	31	19	consistent	consistent	ADJ
app01-8386	31	20	nonlinear	nonlinear	ADJ
app01-8386	31	21	finite	finite	PROPN
app01-8386	31	22	element	element	NOUN
app01-8386	31	23	material	material	NOUN
app01-8386	31	24	models	model	NOUN
app01-8386	31	25	for	for	ADP
app01-8386	31	26	reinforced	reinforce	VERB
app01-8386	31	27	concrete	concrete	ADJ
app01-8386	31	28	plates	plate	NOUN
app01-8386	31	29	and	and	CCONJ
app01-8386	31	30	shells	shell	NOUN
app01-8386	31	31	,	,	PUNCT
app01-8386	31	32	developed	develop	VERB
app01-8386	31	33	at	at	ADP
app01-8386	31	34	eth	eth	PROPN
app01-8386	31	35	zurich	zurich	PROPN
app01-8386	31	36	,	,	PUNCT
app01-8386	31	37	as	as	ADP
app01-8386	31	38	a	a	DET
app01-8386	31	39	data	data	NOUN
app01-8386	31	40	-	-	PUNCT
app01-8386	31	41	driven	drive	VERB
app01-8386	31	42	yet	yet	CCONJ
app01-8386	31	43	physics	physic	NOUN
app01-8386	31	44	-	-	PUNCT
app01-8386	31	45	informed	inform	VERB
app01-8386	31	46	ai	ai	VERB
app01-8386	31	47	method	method	NOUN
app01-8386	31	48	within	within	ADP
app01-8386	31	49	a	a	DET
app01-8386	31	50	fem	fem	NOUN
app01-8386	31	51	workflow	workflow	NOUN
app01-8386	31	52	.	.	PUNCT
app01-8386	32	1	the	the	DET
app01-8386	32	2	project	project	NOUN
app01-8386	32	3	is	be	AUX
app01-8386	32	4	divided	divide	VERB
app01-8386	32	5	into	into	ADP
app01-8386	32	6	two	two	NUM
app01-8386	32	7	parts	part	NOUN
app01-8386	32	8	.	.	PUNCT
app01-8386	33	1	the	the	DET
app01-8386	33	2	ai	ai	PROPN
app01-8386	33	3	-	-	PUNCT
app01-8386	33	4	fem	fem	NOUN
app01-8386	33	5	-	-	PUNCT
app01-8386	33	6	hybrids	hybrid	NOUN
app01-8386	33	7	of	of	ADP
app01-8386	33	8	phase	phase	NOUN
app01-8386	33	9	one	one	NUM
app01-8386	33	10	provide	provide	VERB
app01-8386	33	11	predictions	prediction	NOUN
app01-8386	33	12	of	of	ADP
app01-8386	33	13	the	the	DET
app01-8386	33	14	material	material	ADJ
app01-8386	33	15	stiffness	stiffness	NOUN
app01-8386	33	16	tensor	tensor	NOUN
app01-8386	33	17	as	as	ADV
app01-8386	33	18	well	well	ADV
app01-8386	33	19	as	as	ADP
app01-8386	33	20	the	the	DET
app01-8386	33	21	stress	stress	NOUN
app01-8386	33	22	tensor	tensor	NOUN
app01-8386	33	23	for	for	ADP
app01-8386	33	24	a	a	DET
app01-8386	33	25	current	current	ADJ
app01-8386	33	26	strain	strain	NOUN
app01-8386	33	27	state	state	NOUN
app01-8386	33	28	,	,	PUNCT
app01-8386	33	29	where	where	SCONJ
app01-8386	33	30	the	the	DET
app01-8386	33	31	sciml	sciml	NOUN
app01-8386	33	32	algorithms	algorithm	NOUN
app01-8386	33	33	act	act	VERB
app01-8386	33	34	as	as	ADP
app01-8386	33	35	functional	functional	ADJ
app01-8386	33	36	approximators	approximator	NOUN
app01-8386	33	37	of	of	ADP
app01-8386	33	38	the	the	DET
app01-8386	33	39	stress	stress	NOUN
app01-8386	33	40	-	-	PUNCT
app01-8386	33	41	strain	strain	NOUN
app01-8386	33	42	relationship	relationship	NOUN
app01-8386	33	43	and	and	CCONJ
app01-8386	33	44	the	the	DET
app01-8386	33	45	stiffness	stiffness	NOUN
app01-8386	33	46	-	-	PUNCT
app01-8386	33	47	strain	strain	NOUN
app01-8386	33	48	relationship	relationship	NOUN
app01-8386	33	49	,	,	PUNCT
app01-8386	33	50	which	which	PRON
app01-8386	33	51	was	be	AUX
app01-8386	33	52	found	find	VERB
app01-8386	33	53	to	to	PART
app01-8386	33	54	be	be	AUX
app01-8386	33	55	applicable	applicable	ADJ
app01-8386	33	56	to	to	ADP
app01-8386	33	57	a	a	DET
app01-8386	33	58	number	number	NOUN
app01-8386	33	59	of	of	ADP
app01-8386	33	60	materials	material	NOUN
app01-8386	33	61	[	[	X
app01-8386	33	62	9	9	NUM
app01-8386	33	63	]	]	PUNCT
app01-8386	33	64	.	.	PUNCT
app01-8386	34	1	the	the	DET
app01-8386	34	2	basic	basic	ADJ
app01-8386	34	3	data	datum	NOUN
app01-8386	34	4	set	set	VERB
app01-8386	34	5	for	for	ADP
app01-8386	34	6	training	training	NOUN
app01-8386	34	7	,	,	PUNCT
app01-8386	34	8	validation	validation	NOUN
app01-8386	34	9	and	and	CCONJ
app01-8386	34	10	testing	testing	NOUN
app01-8386	34	11	of	of	ADP
app01-8386	34	12	the	the	DET
app01-8386	34	13	ai	ai	NOUN
app01-8386	34	14	algorithms	algorithms	NOUN
app01-8386	34	15	is	be	AUX
app01-8386	34	16	generated	generate	VERB
app01-8386	34	17	by	by	ADP
app01-8386	34	18	an	an	DET
app01-8386	34	19	extensive	extensive	ADJ
app01-8386	34	20	simulation	simulation	NOUN
app01-8386	34	21	of	of	ADP
app01-8386	34	22	strain	strain	NOUN
app01-8386	34	23	-	-	PUNCT
app01-8386	34	24	stressstiffness	stressstiffness	NOUN
app01-8386	34	25	states	state	NOUN
app01-8386	34	26	for	for	ADP
app01-8386	34	27	different	different	ADJ
app01-8386	34	28	reinforced	reinforce	VERB
app01-8386	34	29	concrete	concrete	ADJ
app01-8386	34	30	configurations	configuration	NOUN
app01-8386	34	31	with	with	ADP
app01-8386	34	32	the	the	DET
app01-8386	34	33	material	material	NOUN
app01-8386	34	34	model	model	NOUN
app01-8386	34	35	for	for	ADP
app01-8386	34	36	reinforced	reinforce	VERB
app01-8386	34	37	concrete	concrete	NOUN
app01-8386	34	38	as	as	SCONJ
app01-8386	34	39	implemented	implement	VERB
app01-8386	34	40	in	in	ADP
app01-8386	34	41	the	the	DET
app01-8386	34	42	mentioned	mention	VERB
app01-8386	34	43	usermat	usermat	NOUN
app01-8386	34	44	in	in	ADP
app01-8386	34	45	ansys	ansys	PROPN
app01-8386	34	46	mechanical	mechanical	ADJ
app01-8386	34	47	apdl	apdl	PROPN
app01-8386	34	48	on	on	ADP
app01-8386	34	49	the	the	DET
app01-8386	34	50	basis	basis	NOUN
app01-8386	34	51	of	of	ADP
app01-8386	34	52	the	the	DET
app01-8386	34	53	cracked	crack	VERB
app01-8386	34	54	membrane	membrane	NOUN
app01-8386	34	55	model	model	NOUN
app01-8386	34	56	(	(	PUNCT
app01-8386	34	57	cmm	cmm	NOUN
app01-8386	34	58	)	)	PUNCT
app01-8386	34	59	in	in	ADP
app01-8386	34	60	combination	combination	NOUN
app01-8386	34	61	with	with	ADP
app01-8386	34	62	a	a	DET
app01-8386	34	63	layer	layer	NOUN
app01-8386	34	64	model	model	NOUN
app01-8386	34	65	based	base	VERB
app01-8386	34	66	on	on	ADP
app01-8386	34	67	reissner	reissner	ADJ
app01-8386	34	68	-	-	PUNCT
app01-8386	34	69	mindlin	mindlin	NOUN
app01-8386	34	70	plate	plate	NOUN
app01-8386	34	71	kinematics	kinematic	NOUN
app01-8386	34	72	.	.	PUNCT
app01-8386	35	1	the	the	DET
app01-8386	35	2	training	training	NOUN
app01-8386	35	3	,	,	PUNCT
app01-8386	35	4	validation	validation	NOUN
app01-8386	35	5	and	and	CCONJ
app01-8386	35	6	testing	testing	NOUN
app01-8386	35	7	of	of	ADP
app01-8386	35	8	the	the	DET
app01-8386	35	9	sciml	sciml	NOUN
app01-8386	35	10	algorithms	algorithm	NOUN
app01-8386	35	11	for	for	ADP
app01-8386	35	12	stress	stress	NOUN
app01-8386	35	13	and	and	CCONJ
app01-8386	35	14	stiffness	stiffness	ADJ
app01-8386	35	15	tensor	tensor	NOUN
app01-8386	35	16	prediction	prediction	NOUN
app01-8386	35	17	are	be	AUX
app01-8386	35	18	presented	present	VERB
app01-8386	35	19	and	and	CCONJ
app01-8386	35	20	discussed	discuss	VERB
app01-8386	35	21	in	in	ADP
app01-8386	35	22	the	the	DET
app01-8386	35	23	following	following	NOUN
app01-8386	35	24	,	,	PUNCT
app01-8386	35	25	where	where	SCONJ
app01-8386	35	26	special	special	ADJ
app01-8386	35	27	consideration	consideration	NOUN
app01-8386	35	28	is	be	AUX
app01-8386	35	29	given	give	VERB
app01-8386	35	30	to	to	PART
app01-8386	35	31	model	model	VERB
app01-8386	35	32	uncertainty	uncertainty	NOUN
app01-8386	35	33	quantification	quantification	NOUN
app01-8386	35	34	to	to	PART
app01-8386	35	35	allow	allow	VERB
app01-8386	35	36	for	for	ADP
app01-8386	35	37	a	a	DET
app01-8386	35	38	future	future	ADJ
app01-8386	35	39	eurocodecompliant	eurocodecompliant	ADJ
app01-8386	35	40	use	use	NOUN
app01-8386	35	41	within	within	ADP
app01-8386	35	42	the	the	DET
app01-8386	35	43	semi	semi	ADJ
app01-8386	35	44	-	-	ADJ
app01-8386	35	45	probabilistic	probabilistic	ADJ
app01-8386	35	46	design	design	NOUN
app01-8386	35	47	philosophy	philosophy	NOUN
app01-8386	35	48	.	.	PUNCT
app01-8386	36	1	with	with	ADP
app01-8386	36	2	the	the	DET
app01-8386	36	3	completion	completion	NOUN
app01-8386	36	4	of	of	ADP
app01-8386	36	5	the	the	DET
app01-8386	36	6	first	first	ADJ
app01-8386	36	7	phase	phase	NOUN
app01-8386	36	8	,	,	PUNCT
app01-8386	36	9	a	a	DET
app01-8386	36	10	validated	validate	VERB
app01-8386	36	11	software	software	NOUN
app01-8386	36	12	demonstrator	demonstrator	NOUN
app01-8386	36	13	of	of	ADP
app01-8386	36	14	ai	ai	PROPN
app01-8386	36	15	-	-	PUNCT
app01-8386	36	16	fem	fem	NOUN
app01-8386	36	17	-	-	PUNCT
app01-8386	36	18	hybrids	hybrid	NOUN
app01-8386	36	19	for	for	ADP
app01-8386	36	20	the	the	DET
app01-8386	36	21	efficient	efficient	ADJ
app01-8386	36	22	non	non	ADJ
app01-8386	36	23	-	-	ADJ
app01-8386	36	24	linear	linear	ADJ
app01-8386	36	25	analysis	analysis	NOUN
app01-8386	36	26	and	and	CCONJ
app01-8386	36	27	design	design	NOUN
app01-8386	36	28	of	of	ADP
app01-8386	36	29	reinforced	reinforce	VERB
app01-8386	36	30	concrete	concrete	ADJ
app01-8386	36	31	structures	structure	NOUN
app01-8386	36	32	is	be	AUX
app01-8386	36	33	available	available	ADJ
app01-8386	36	34	.	.	PUNCT
app01-8386	37	1	in	in	ADP
app01-8386	37	2	the	the	DET
app01-8386	37	3	second	second	ADJ
app01-8386	37	4	project	project	NOUN
app01-8386	37	5	phase	phase	NOUN
app01-8386	37	6	,	,	PUNCT
app01-8386	37	7	the	the	DET
app01-8386	37	8	ai	ai	NOUN
app01-8386	37	9	-	-	PUNCT
app01-8386	37	10	fem	fem	ADJ
app01-8386	37	11	-	-	PUNCT
app01-8386	37	12	hybrids	hybrid	NOUN
app01-8386	37	13	approach	approach	NOUN
app01-8386	37	14	will	will	AUX
app01-8386	37	15	be	be	AUX
app01-8386	37	16	extended	extend	VERB
app01-8386	37	17	to	to	ADP
app01-8386	37	18	structural	structural	ADJ
app01-8386	37	19	optimisation	optimisation	NOUN
app01-8386	37	20	of	of	ADP
app01-8386	37	21	concrete	concrete	ADJ
app01-8386	37	22	bridges	bridge	NOUN
app01-8386	37	23	.	.	PUNCT
app01-8386	38	1	the	the	DET
app01-8386	38	2	pilot	pilot	NOUN
app01-8386	38	3	project	project	NOUN
app01-8386	38	4	in	in	ADP
app01-8386	38	5	this	this	DET
app01-8386	38	6	phase	phase	NOUN
app01-8386	38	7	focuses	focus	VERB
app01-8386	38	8	on	on	ADP
app01-8386	38	9	concrete	concrete	ADJ
app01-8386	38	10	bridges	bridge	NOUN
app01-8386	38	11	with	with	ADP
app01-8386	38	12	a	a	DET
app01-8386	38	13	geometry	geometry	NOUN
app01-8386	38	14	defined	define	VERB
app01-8386	38	15	by	by	ADP
app01-8386	38	16	a	a	DET
app01-8386	38	17	few	few	ADJ
app01-8386	38	18	parameters	parameter	NOUN
app01-8386	38	19	.	.	PUNCT
app01-8386	39	1	while	while	SCONJ
app01-8386	39	2	the	the	DET
app01-8386	39	3	case	case	NOUN
app01-8386	39	4	study	study	NOUN
app01-8386	39	5	is	be	AUX
app01-8386	39	6	specific	specific	ADJ
app01-8386	39	7	,	,	PUNCT
app01-8386	39	8	the	the	DET
app01-8386	39	9	developed	develop	VERB
app01-8386	39	10	optimisation	optimisation	NOUN
app01-8386	39	11	methodology	methodology	NOUN
app01-8386	39	12	is	be	AUX
app01-8386	39	13	kept	keep	VERB
app01-8386	39	14	as	as	ADV
app01-8386	39	15	general	general	ADJ
app01-8386	39	16	as	as	ADP
app01-8386	39	17	possible	possible	ADJ
app01-8386	39	18	to	to	PART
app01-8386	39	19	allow	allow	VERB
app01-8386	39	20	its	its	PRON
app01-8386	39	21	application	application	NOUN
app01-8386	39	22	beyond	beyond	ADP
app01-8386	39	23	parametric	parametric	ADJ
app01-8386	39	24	concrete	concrete	ADJ
app01-8386	39	25	bridge	bridge	NOUN
app01-8386	39	26	structures	structure	NOUN
app01-8386	39	27	.	.	PUNCT
app01-8386	40	1	at	at	ADP
app01-8386	40	2	the	the	DET
app01-8386	40	3	end	end	NOUN
app01-8386	40	4	of	of	ADP
app01-8386	40	5	the	the	DET
app01-8386	40	6	research	research	NOUN
app01-8386	40	7	project	project	NOUN
app01-8386	40	8	,	,	PUNCT
app01-8386	40	9	a	a	DET
app01-8386	40	10	validated	validate	VERB
app01-8386	40	11	software	software	NOUN
app01-8386	40	12	demonstrator	demonstrator	NOUN
app01-8386	40	13	of	of	ADP
app01-8386	40	14	the	the	DET
app01-8386	40	15	aife	aife	NOUN
app01-8386	40	16	-	-	PUNCT
app01-8386	40	17	hybrids	hybrid	NOUN
app01-8386	40	18	will	will	AUX
app01-8386	40	19	be	be	AUX
app01-8386	40	20	available	available	ADJ
app01-8386	40	21	for	for	ADP
app01-8386	40	22	the	the	DET
app01-8386	40	23	efficient	efficient	ADJ
app01-8386	40	24	non	non	ADJ
app01-8386	40	25	-	-	ADJ
app01-8386	40	26	linear	linear	ADJ
app01-8386	40	27	analysis	analysis	NOUN
app01-8386	40	28	,	,	PUNCT
app01-8386	40	29	design	design	NOUN
app01-8386	40	30	and	and	CCONJ
app01-8386	40	31	optimisation	optimisation	NOUN
app01-8386	40	32	of	of	ADP
app01-8386	40	33	reinforced	reinforce	VERB
app01-8386	40	34	concrete	concrete	ADJ
app01-8386	40	35	structures	structure	NOUN
app01-8386	40	36	.	.	PUNCT
app01-8386	41	1	in	in	ADP
app01-8386	41	2	the	the	DET
app01-8386	41	3	future	future	NOUN
app01-8386	41	4	,	,	PUNCT
app01-8386	41	5	this	this	PRON
app01-8386	41	6	will	will	AUX
app01-8386	41	7	then	then	ADV
app01-8386	41	8	allow	allow	VERB
app01-8386	41	9	for	for	ADP
app01-8386	41	10	(	(	PUNCT
app01-8386	41	11	i	i	NOUN
app01-8386	41	12	)	)	PUNCT
app01-8386	41	13	realistic	realistic	ADJ
app01-8386	41	14	structural	structural	ADJ
app01-8386	41	15	analyses	analysis	NOUN
app01-8386	41	16	taking	take	VERB
app01-8386	41	17	into	into	ADP
app01-8386	41	18	account	account	NOUN
app01-8386	41	19	non	non	NOUN
app01-8386	41	20	-	-	NOUN
app01-8386	41	21	linearities	linearity	NOUN
app01-8386	41	22	and	and	CCONJ
app01-8386	41	23	(	(	PUNCT
app01-8386	41	24	ii	ii	NOUN
app01-8386	41	25	)	)	PUNCT
app01-8386	41	26	structural	structural	ADJ
app01-8386	41	27	optimisation	optimisation	NOUN
app01-8386	41	28	to	to	PART
app01-8386	41	29	be	be	AUX
app01-8386	41	30	carried	carry	VERB
app01-8386	41	31	out	out	ADP
app01-8386	41	32	much	much	ADV
app01-8386	41	33	more	more	ADV
app01-8386	41	34	efficiently	efficiently	ADV
app01-8386	41	35	.	.	PUNCT
app01-8386	42	1	the	the	DET
app01-8386	42	2	outcomes	outcome	NOUN
app01-8386	42	3	of	of	ADP
app01-8386	42	4	this	this	DET
app01-8386	42	5	research	research	NOUN
app01-8386	42	6	are	be	AUX
app01-8386	42	7	potentially	potentially	ADV
app01-8386	42	8	of	of	ADP
app01-8386	42	9	high	high	ADJ
app01-8386	42	10	interest	interest	NOUN
app01-8386	42	11	to	to	ADP
app01-8386	42	12	industry	industry	NOUN
app01-8386	42	13	and	and	CCONJ
app01-8386	42	14	engineering	engineering	NOUN
app01-8386	42	15	practice	practice	NOUN
app01-8386	42	16	,	,	PUNCT
app01-8386	42	17	as	as	SCONJ
app01-8386	42	18	structural	structural	ADJ
app01-8386	42	19	concrete	concrete	NOUN
app01-8386	42	20	is	be	AUX
app01-8386	42	21	the	the	DET
app01-8386	42	22	most	most	ADV
app01-8386	42	23	widely	widely	ADV
app01-8386	42	24	used	use	VERB
app01-8386	42	25	construction	construction	NOUN
app01-8386	42	26	material	material	NOUN
app01-8386	42	27	worldwide	worldwide	ADV
app01-8386	42	28	and	and	CCONJ
app01-8386	42	29	incorporation	incorporation	NOUN
app01-8386	42	30	of	of	ADP
app01-8386	42	31	these	these	DET
app01-8386	42	32	ideas	idea	NOUN
app01-8386	42	33	allows	allow	VERB
app01-8386	42	34	for	for	ADP
app01-8386	42	35	more	more	ADV
app01-8386	42	36	economic	economic	ADJ
app01-8386	42	37	,	,	PUNCT
app01-8386	42	38	yet	yet	CCONJ
app01-8386	42	39	sustainable	sustainable	ADJ
app01-8386	42	40	and	and	CCONJ
app01-8386	42	41	reliable	reliable	ADJ
app01-8386	42	42	design	design	NOUN
app01-8386	42	43	.	.	PUNCT
app01-8386	43	1	to	to	PART
app01-8386	43	2	achieve	achieve	VERB
app01-8386	43	3	the	the	DET
app01-8386	43	4	objectives	objective	NOUN
app01-8386	43	5	for	for	ADP
app01-8386	43	6	phase	phase	NOUN
app01-8386	43	7	one	one	NUM
app01-8386	43	8	of	of	ADP
app01-8386	43	9	the	the	DET
app01-8386	43	10	research	research	NOUN
app01-8386	43	11	project	project	NOUN
app01-8386	43	12	,	,	PUNCT
app01-8386	43	13	the	the	DET
app01-8386	43	14	following	follow	VERB
app01-8386	43	15	sequence	sequence	NOUN
app01-8386	43	16	of	of	ADP
app01-8386	43	17	steps	step	NOUN
app01-8386	43	18	was	be	AUX
app01-8386	43	19	conducted	conduct	VERB
app01-8386	43	20	:	:	PUNCT
app01-8386	43	21	(	(	PUNCT
app01-8386	43	22	1	1	NUM
app01-8386	43	23	.	.	PUNCT
app01-8386	43	24	)	)	PUNCT
app01-8386	43	25	define	define	VERB
app01-8386	43	26	relevant	relevant	ADJ
app01-8386	43	27	feature	feature	NOUN
app01-8386	43	28	x	x	NOUN
app01-8386	43	29	and	and	CCONJ
app01-8386	43	30	target	target	VERB
app01-8386	43	31	variables	variable	VERB
app01-8386	43	32	y	y	PROPN
app01-8386	43	33	for	for	ADP
app01-8386	43	34	a	a	DET
app01-8386	43	35	reinforced	reinforce	VERB
app01-8386	43	36	concrete	concrete	ADJ
app01-8386	43	37	material	material	NOUN
app01-8386	43	38	model	model	NOUN
app01-8386	43	39	(	(	PUNCT
app01-8386	43	40	cf	cf	NOUN
app01-8386	43	41	.	.	PUNCT
app01-8386	43	42	tab	tab	NOUN
app01-8386	43	43	.	.	PROPN
app01-8386	44	1	1	1	NUM
app01-8386	44	2	)	)	PUNCT
app01-8386	44	3	(	(	PUNCT
app01-8386	44	4	2	2	NUM
app01-8386	44	5	.	.	PUNCT
app01-8386	44	6	)	)	PUNCT
app01-8386	44	7	create	create	VERB
app01-8386	44	8	the	the	DET
app01-8386	44	9	database	database	NOUN
app01-8386	44	10	{	{	PUNCT
app01-8386	44	11	x	x	NOUN
app01-8386	44	12	;	;	PUNCT
app01-8386	44	13	y	y	NOUN
app01-8386	44	14	}	}	PUNCT
app01-8386	44	15	of	of	ADP
app01-8386	44	16	fem	fem	NOUN
app01-8386	44	17	simulations	simulation	NOUN
app01-8386	44	18	(	(	PUNCT
app01-8386	44	19	3	3	NUM
app01-8386	44	20	.	.	PUNCT
app01-8386	44	21	)	)	PUNCT
app01-8386	44	22	calibrate	calibrate	VERB
app01-8386	44	23	different	different	ADJ
app01-8386	44	24	ml	ml	NOUN
app01-8386	44	25	and	and	CCONJ
app01-8386	44	26	dl	dl	PROPN
app01-8386	44	27	algorithms	algorithm	NOUN
app01-8386	44	28	given	give	VERB
app01-8386	44	29	the	the	DET
app01-8386	44	30	database	database	NOUN
app01-8386	44	31	(	(	PUNCT
app01-8386	44	32	4	4	NUM
app01-8386	44	33	.	.	PUNCT
app01-8386	44	34	)	)	PUNCT
app01-8386	44	35	assess	assess	VERB
app01-8386	44	36	different	different	ADJ
app01-8386	44	37	metrics	metric	NOUN
app01-8386	44	38	for	for	ADP
app01-8386	44	39	accuracy	accuracy	NOUN
app01-8386	44	40	and	and	CCONJ
app01-8386	44	41	predictive	predictive	ADJ
app01-8386	44	42	capabilities	capability	NOUN
app01-8386	44	43	of	of	ADP
app01-8386	44	44	the	the	DET
app01-8386	44	45	ml	ml	NOUN
app01-8386	44	46	resp	resp	NOUN
app01-8386	44	47	.	.	PUNCT
app01-8386	45	1	dl	dl	PROPN
app01-8386	45	2	models	model	NOUN
app01-8386	45	3	(	(	PUNCT
app01-8386	45	4	5	5	NUM
app01-8386	45	5	.	.	PUNCT
app01-8386	45	6	)	)	PUNCT
app01-8386	45	7	implement	implement	VERB
app01-8386	45	8	a	a	DET
app01-8386	45	9	selection	selection	NOUN
app01-8386	45	10	of	of	ADP
app01-8386	45	11	ml	ml	NOUN
app01-8386	45	12	resp	resp	NOUN
app01-8386	45	13	.	.	PUNCT
app01-8386	46	1	dl	dl	PROPN
app01-8386	46	2	models	model	NOUN
app01-8386	46	3	for	for	ADP
app01-8386	46	4	implementation	implementation	NOUN
app01-8386	46	5	in	in	ADP
app01-8386	46	6	ansys	ansys	PROPN
app01-8386	46	7	(	(	PUNCT
app01-8386	46	8	6	6	NUM
app01-8386	46	9	.	.	PUNCT
app01-8386	46	10	)	)	PUNCT
app01-8386	46	11	verify	verify	VERB
app01-8386	46	12	efficiency	efficiency	NOUN
app01-8386	46	13	and	and	CCONJ
app01-8386	46	14	accuracy	accuracy	NOUN
app01-8386	46	15	at	at	ADP
app01-8386	46	16	industry	industry	NOUN
app01-8386	46	17	scale	scale	NOUN
app01-8386	46	18	via	via	ADP
app01-8386	46	19	computation	computation	NOUN
app01-8386	46	20	of	of	ADP
app01-8386	46	21	example	example	NOUN
app01-8386	46	22	problems	problem	NOUN
app01-8386	46	23	from	from	ADP
app01-8386	46	24	reinforced	reinforce	VERB
app01-8386	46	25	concrete	concrete	ADJ
app01-8386	46	26	design	design	NOUN
app01-8386	46	27	2.2	2.2	NUM
app01-8386	46	28	.	.	PUNCT
app01-8386	47	1	fem	fem	PROPN
app01-8386	47	2	material	material	PROPN
app01-8386	47	3	model	model	PROPN
app01-8386	47	4	data	data	NOUN
app01-8386	47	5	generation	generation	NOUN
app01-8386	47	6	the	the	DET
app01-8386	47	7	dataset	dataset	NOUN
app01-8386	47	8	generation	generation	NOUN
app01-8386	47	9	within	within	ADP
app01-8386	47	10	the	the	DET
app01-8386	47	11	ai	ai	ADJ
app01-8386	47	12	-	-	PUNCT
app01-8386	47	13	fem	fem	NOUN
app01-8386	47	14	-	-	PUNCT
app01-8386	47	15	hybrid	hybrid	ADJ
app01-8386	47	16	project	project	NOUN
app01-8386	47	17	was	be	AUX
app01-8386	47	18	performed	perform	VERB
app01-8386	47	19	by	by	ADP
app01-8386	47	20	nonlinear	nonlinear	ADJ
app01-8386	47	21	finite	finite	PROPN
app01-8386	47	22	element	element	NOUN
app01-8386	47	23	analysis	analysis	NOUN
app01-8386	47	24	of	of	ADP
app01-8386	47	25	a	a	DET
app01-8386	47	26	reinforced	reinforce	VERB
app01-8386	47	27	concrete	concrete	ADJ
app01-8386	47	28	structure	structure	NOUN
app01-8386	47	29	utilising	utilise	VERB
app01-8386	47	30	the	the	DET
app01-8386	47	31	cmm	cmm	NOUN
app01-8386	47	32	-	-	NOUN
app01-8386	47	33	usermat	usermat	NOUN
app01-8386	47	34	[	[	X
app01-8386	47	35	3	3	NUM
app01-8386	47	36	]	]	PUNCT
app01-8386	47	37	,	,	PUNCT
app01-8386	47	38	a	a	DET
app01-8386	47	39	mechanically	mechanically	ADV
app01-8386	47	40	consistent	consistent	ADJ
app01-8386	47	41	material	material	NOUN
app01-8386	47	42	model	model	NOUN
app01-8386	47	43	for	for	ADP
app01-8386	47	44	reinforced	reinforce	VERB
app01-8386	47	45	concrete	concrete	NOUN
app01-8386	47	46	implemented	implement	VERB
app01-8386	47	47	in	in	ADP
app01-8386	47	48	ansys	ansys	PROPN
app01-8386	47	49	mechanical	mechanical	PROPN
app01-8386	47	50	apdl	apdl	PROPN
app01-8386	47	51	,	,	PUNCT
app01-8386	47	52	cf	cf	NOUN
app01-8386	47	53	.	.	PUNCT
app01-8386	48	1	figs	fig	NOUN
app01-8386	48	2	.	.	PUNCT
app01-8386	49	1	1	1	NUM
app01-8386	49	2	and	and	CCONJ
app01-8386	49	3	2	2	NUM
app01-8386	49	4	.	.	PUNCT
app01-8386	49	5	combined	combine	VERB
app01-8386	49	6	with	with	ADP
app01-8386	49	7	a	a	DET
app01-8386	49	8	layer	layer	NOUN
app01-8386	49	9	element	element	NOUN
app01-8386	49	10	(	(	PUNCT
app01-8386	49	11	shell181	shell181	PROPN
app01-8386	49	12	)	)	PUNCT
app01-8386	49	13	,	,	PUNCT
app01-8386	49	14	the	the	DET
app01-8386	49	15	non	non	ADJ
app01-8386	49	16	-	-	ADJ
app01-8386	49	17	linear	linear	ADJ
app01-8386	49	18	fem	fem	NOUN
app01-8386	49	19	analysis	analysis	NOUN
app01-8386	49	20	of	of	ADP
app01-8386	49	21	reinforced	reinforce	VERB
app01-8386	49	22	concrete	concrete	ADJ
app01-8386	49	23	structures	structure	NOUN
app01-8386	49	24	as	as	ADP
app01-8386	49	25	girders	girder	NOUN
app01-8386	49	26	or	or	CCONJ
app01-8386	49	27	shells	shell	NOUN
app01-8386	49	28	are	be	AUX
app01-8386	49	29	possible	possible	ADJ
app01-8386	49	30	.	.	PUNCT
app01-8386	50	1	as	as	SCONJ
app01-8386	50	2	presented	present	VERB
app01-8386	50	3	in	in	ADP
app01-8386	50	4	[	[	X
app01-8386	50	5	3–5	3–5	NOUN
app01-8386	50	6	]	]	PUNCT
app01-8386	50	7	,	,	PUNCT
app01-8386	50	8	an	an	DET
app01-8386	50	9	excellent	excellent	ADJ
app01-8386	50	10	agreement	agreement	NOUN
app01-8386	50	11	between	between	ADP
app01-8386	50	12	experimental	experimental	ADJ
app01-8386	50	13	results	result	NOUN
app01-8386	50	14	and	and	CCONJ
app01-8386	50	15	fem	fem	NOUN
app01-8386	50	16	analysis	analysis	NOUN
app01-8386	50	17	utilising	utilise	VERB
app01-8386	50	18	the	the	DET
app01-8386	50	19	cmm	cmm	NOUN
app01-8386	50	20	-	-	NOUN
app01-8386	50	21	usermat	usermat	NOUN
app01-8386	50	22	is	be	AUX
app01-8386	50	23	reported	report	VERB
app01-8386	50	24	.	.	PUNCT
app01-8386	51	1	in	in	ADP
app01-8386	51	2	order	order	NOUN
app01-8386	51	3	to	to	PART
app01-8386	51	4	provide	provide	VERB
app01-8386	51	5	the	the	DET
app01-8386	51	6	necessary	necessary	ADJ
app01-8386	51	7	dataset	dataset	NOUN
app01-8386	51	8	for	for	ADP
app01-8386	51	9	the	the	DET
app01-8386	51	10	training	training	NOUN
app01-8386	51	11	of	of	ADP
app01-8386	51	12	the	the	DET
app01-8386	51	13	machine	machine	NOUN
app01-8386	51	14	learning	learn	VERB
app01-8386	51	15	algorithms	algorithm	NOUN
app01-8386	51	16	,	,	PUNCT
app01-8386	51	17	a	a	DET
app01-8386	51	18	dummy	dummy	ADJ
app01-8386	51	19	girder	girder	NOUN
app01-8386	51	20	bridge	bridge	NOUN
app01-8386	51	21	(	(	PUNCT
app01-8386	51	22	cf	cf	NOUN
app01-8386	51	23	.	.	PUNCT
app01-8386	51	24	figs	fig	NOUN
app01-8386	51	25	.	.	PUNCT
app01-8386	51	26	1	1	NUM
app01-8386	51	27	and	and	CCONJ
app01-8386	51	28	2	2	NUM
app01-8386	51	29	)	)	PUNCT
app01-8386	51	30	was	be	AUX
app01-8386	51	31	arbitrary	arbitrary	ADJ
app01-8386	51	32	loaded	load	VERB
app01-8386	51	33	incrementally	incrementally	ADV
app01-8386	51	34	until	until	ADP
app01-8386	51	35	failure	failure	NOUN
app01-8386	51	36	,	,	PUNCT
app01-8386	51	37	which	which	PRON
app01-8386	51	38	enables	enable	VERB
app01-8386	51	39	the	the	DET
app01-8386	51	40	export	export	NOUN
app01-8386	51	41	of	of	ADP
app01-8386	51	42	100	100	NUM
app01-8386	51	43	vol	vol	NOUN
app01-8386	51	44	.	.	PUNCT
app01-8386	52	1	36/2022	36/2022	NUM
app01-8386	52	2	ai	ai	ADJ
app01-8386	52	3	-	-	PUNCT
app01-8386	52	4	fem	fem	NOUN
app01-8386	52	5	-	-	PUNCT
app01-8386	52	6	hybrids	hybrid	NOUN
app01-8386	52	7	for	for	ADP
app01-8386	52	8	nonlinear	nonlinear	ADJ
app01-8386	52	9	concrete	concrete	ADJ
app01-8386	52	10	materials	material	NOUN
app01-8386	52	11	aa	aa	NOUN
app01-8386	52	12	aa	aa	PROPN
app01-8386	52	13	45.00	45.00	NUM
app01-8386	52	14	m	m	VERB
app01-8386	52	15	aa	aa	NOUN
app01-8386	52	16	5.00	5.00	NUM
app01-8386	52	17	m	m	VERB
app01-8386	52	18	aa	aa	NOUN
app01-8386	52	19	2.25	2.25	NUM
app01-8386	52	20	m	m	NOUN
app01-8386	52	21	aa	aa	NOUN
app01-8386	52	22	250	250	NUM
app01-8386	52	23	mm	mm	INTJ
app01-8386	52	24	aa	aa	NOUN
app01-8386	52	25	250	250	NUM
app01-8386	52	26	mm	mm	INTJ
app01-8386	53	1	aa	aa	NOUN
app01-8386	53	2	aa	aa	NOUN
app01-8386	53	3	400	400	NUM
app01-8386	53	4	mm	mm	INTJ
app01-8386	54	1	aa	aa	NOUN
app01-8386	54	2	1'200	1'200	NUM
app01-8386	55	1	mm	mm	INTJ
app01-8386	55	2	aa	aa	NOUN
app01-8386	55	3	495	495	NUM
app01-8386	55	4	mm	mm	NOUN
app01-8386	55	5	aa	aa	NOUN
app01-8386	55	6	480	480	NUM
app01-8386	55	7	mm	mm	NOUN
app01-8386	55	8	aa	aa	NOUN
app01-8386	55	9	437	437	NUM
app01-8386	55	10	mm	mm	INTJ
app01-8386	55	11	qn	qn	NOUN
app01-8386	55	12	qn	qn	NOUN
app01-8386	55	13	a	a	PRON
app01-8386	55	14	b	b	PROPN
app01-8386	55	15	c	c	NOUN
app01-8386	55	16	d	d	PROPN
app01-8386	55	17	b0	b0	PROPN
app01-8386	55	18	l/2	l/2	PROPN
app01-8386	55	19	l/2	l/2	PROPN
app01-8386	55	20	qn	qn	PROPN
app01-8386	55	21	y	y	PROPN
app01-8386	55	22	xz	xz	PROPN
app01-8386	55	23	x	x	PROPN
app01-8386	55	24	z	z	VERB
app01-8386	55	25	y	y	PROPN
app01-8386	55	26	8'600[kn	8'600[kn	NUM
app01-8386	55	27	]	]	X
app01-8386	55	28	[	[	X
app01-8386	55	29	knm	knm	X
app01-8386	55	30	]	]	X
app01-8386	55	31	vz	vz	NOUN
app01-8386	55	32	my	my	PRON
app01-8386	55	33	[	[	X
app01-8386	55	34	kn	kn	X
app01-8386	55	35	]	]	X
app01-8386	55	36	[	[	X
app01-8386	55	37	knm	knm	X
app01-8386	55	38	]	]	X
app01-8386	55	39	nx	nx	PROPN
app01-8386	55	40	tx	tx	PROPN
app01-8386	55	41	a	a	DET
app01-8386	55	42	z	z	NOUN
app01-8386	55	43	bz	bz	PROPN
app01-8386	55	44	l/2	l/2	PROPN
app01-8386	55	45	l/2	l/2	PROPN
app01-8386	55	46	cz	cz	NOUN
app01-8386	55	47	dz	dz	NOUN
app01-8386	55	48	(	(	PUNCT
app01-8386	55	49	a	a	NOUN
app01-8386	55	50	)	)	PUNCT
app01-8386	55	51	(	(	PUNCT
app01-8386	55	52	b	b	X
app01-8386	55	53	)	)	PUNCT
app01-8386	55	54	x	x	SYM
app01-8386	56	1	z	z	VERB
app01-8386	56	2	y	y	PROPN
app01-8386	56	3	w	w	PROPN
app01-8386	56	4	(	(	PUNCT
app01-8386	56	5	x	x	SYM
app01-8386	56	6	=	=	SYM
app01-8386	56	7	l/2	l/2	NUM
app01-8386	56	8	,	,	PUNCT
app01-8386	56	9	s1	s1	PROPN
app01-8386	56	10	)	)	PUNCT
app01-8386	56	11	w	w	NOUN
app01-8386	56	12	(	(	PUNCT
app01-8386	56	13	x	x	SYM
app01-8386	56	14	=	=	SYM
app01-8386	56	15	l/4	l/4	PROPN
app01-8386	56	16	,	,	PUNCT
app01-8386	56	17	s1	s1	NOUN
app01-8386	56	18	)	)	PUNCT
app01-8386	56	19	w	w	NOUN
app01-8386	57	1	(	(	PUNCT
app01-8386	57	2	x	x	SYM
app01-8386	57	3	=	=	SYM
app01-8386	57	4	l/2	l/2	PROPN
app01-8386	57	5	,	,	PUNCT
app01-8386	57	6	s2	s2	PROPN
app01-8386	57	7	)	)	PUNCT
app01-8386	57	8	w	w	NOUN
app01-8386	57	9	(	(	PUNCT
app01-8386	57	10	x	x	SYM
app01-8386	57	11	=	=	SYM
app01-8386	57	12	l/4	l/4	X
app01-8386	57	13	,	,	PUNCT
app01-8386	57	14	s2	s2	PROPN
app01-8386	57	15	)	)	PUNCT
app01-8386	57	16	qn	qn	PROPN
app01-8386	57	17	=	=	NOUN
app01-8386	57	18	1'911	1'911	NUM
app01-8386	57	19	kn	kn	PROPN
app01-8386	57	20	/	/	SYM
app01-8386	57	21	m	m	PROPN
app01-8386	57	22	zy	zy	NOUN
app01-8386	57	23	x	x	PROPN
app01-8386	57	24	q1	q1	PROPN
app01-8386	57	25	=	=	PUNCT
app01-8386	58	1	200	200	NUM
app01-8386	58	2	kn	kn	PROPN
app01-8386	58	3	/	/	SYM
app01-8386	58	4	m	m	PROPN
app01-8386	58	5	11'250	11'250	NUM
app01-8386	58	6	-11'250	-11'250	NUM
app01-8386	58	7	-4'500	-4'500	PROPN
app01-8386	58	8	4'500	4'500	NUM
app01-8386	58	9	-50'625	-50'625	NOUN
app01-8386	58	10	aa	aa	INTJ
app01-8386	58	11	aa	aa	NOUN
app01-8386	59	1	=	=	PUNCT
app01-8386	59	2	aa	aa	NOUN
app01-8386	59	3	=	=	PUNCT
app01-8386	59	4	aa	aa	NOUN
app01-8386	59	5	=	=	PUNCT
app01-8386	59	6	aa	aa	NOUN
app01-8386	60	1	=	=	PUNCT
app01-8386	60	2	aa	aa	NOUN
app01-8386	60	3	=	=	PUNCT
app01-8386	61	1	aa	aa	NOUN
app01-8386	61	2	aa	aa	NOUN
app01-8386	61	3	=	=	PUNCT
app01-8386	61	4	aa	aa	NOUN
app01-8386	62	1	=	=	PUNCT
app01-8386	62	2	aa	aa	NOUN
app01-8386	62	3	=	=	PUNCT
app01-8386	62	4	aa	aa	NOUN
app01-8386	62	5	=	=	PUNCT
app01-8386	62	6	aa	aa	NOUN
app01-8386	62	7	=	=	PUNCT
app01-8386	62	8	z	z	PROPN
app01-8386	62	9	x	x	SYM
app01-8386	62	10	yq1·b0/2	yq1·b0/2	PROPN
app01-8386	62	11	q1	q1	PROPN
app01-8386	62	12	parameter	parameter	PROPN
app01-8386	62	13	:	:	PUNCT
app01-8386	62	14	l	l	PROPN
app01-8386	62	15	b0	b0	PROPN
app01-8386	62	16	h0	h0	NOUN
app01-8386	62	17	tinf	tinf	VERB
app01-8386	62	18	tsup	tsup	ADJ
app01-8386	62	19	parameter	parameter	NOUN
app01-8386	62	20	:	:	PUNCT
app01-8386	62	21	tw	tw	NOUN
app01-8386	62	22	tend	tend	VERB
app01-8386	62	23	ax	ax	NOUN
app01-8386	62	24	ay	ay	PROPN
app01-8386	62	25	az	az	PROPN
app01-8386	62	26	figure	figure	NOUN
app01-8386	62	27	1	1	NUM
app01-8386	62	28	.	.	PUNCT
app01-8386	62	29	dummy	dummy	ADJ
app01-8386	62	30	girder	girder	NOUN
app01-8386	62	31	bridge	bridge	NOUN
app01-8386	62	32	used	use	VERB
app01-8386	62	33	within	within	ADP
app01-8386	62	34	ansys	ansys	PROPN
app01-8386	62	35	to	to	PART
app01-8386	62	36	generate	generate	VERB
app01-8386	62	37	the	the	DET
app01-8386	62	38	database	database	NOUN
app01-8386	62	39	.	.	PUNCT
app01-8386	63	1	features	feature	NOUN
app01-8386	63	2	xi	xi	ADP
app01-8386	63	3	targets	target	NOUN
app01-8386	63	4	yi	yi	NOUN
app01-8386	63	5	reinforcement	reinforcement	NOUN
app01-8386	63	6	layer	layer	NOUN
app01-8386	63	7	(	(	PUNCT
app01-8386	63	8	rela	rela	ADJ
app01-8386	63	9	)	)	PUNCT
app01-8386	63	10	normal	normal	ADJ
app01-8386	63	11	stress	stress	NOUN
app01-8386	63	12	in	in	ADP
app01-8386	63	13	x	x	NOUN
app01-8386	63	14	-	-	NOUN
app01-8386	63	15	direction	direction	NOUN
app01-8386	63	16	σx	σx	PROPN
app01-8386	63	17	cmm	cmm	PROPN
app01-8386	63	18	usermat	usermat	PROPN
app01-8386	63	19	model	model	PROPN
app01-8386	63	20	(	(	PUNCT
app01-8386	63	21	cmm	cmm	NOUN
app01-8386	63	22	)	)	PUNCT
app01-8386	63	23	normal	normal	ADJ
app01-8386	63	24	stress	stress	NOUN
app01-8386	63	25	in	in	ADP
app01-8386	63	26	y	y	NOUN
app01-8386	63	27	-	-	PUNCT
app01-8386	63	28	direction	direction	NOUN
app01-8386	63	29	σy	σy	NOUN
app01-8386	63	30	reinforcement	reinforcement	NOUN
app01-8386	63	31	area	area	NOUN
app01-8386	63	32	as	as	ADP
app01-8386	63	33	shear	shear	NOUN
app01-8386	63	34	stress	stress	NOUN
app01-8386	63	35	in	in	ADP
app01-8386	63	36	xy	xy	NOUN
app01-8386	63	37	-	-	PUNCT
app01-8386	63	38	direction	direction	NOUN
app01-8386	63	39	τxy	τxy	NOUN
app01-8386	63	40	reinforcement	reinforcement	NOUN
app01-8386	63	41	diameter	diameter	NOUN
app01-8386	63	42	ds	ds	ADJ
app01-8386	63	43	stiffness	stiffness	NOUN
app01-8386	63	44	component	component	NOUN
app01-8386	63	45	k11	k11	NOUN
app01-8386	63	46	effective	effective	ADJ
app01-8386	63	47	reinforcement	reinforcement	NOUN
app01-8386	63	48	ratio	ratio	NOUN
app01-8386	63	49	for	for	ADP
app01-8386	63	50	tcm	tcm	PROPN
app01-8386	63	51	model	model	PROPN
app01-8386	63	52	ρs	ρs	PROPN
app01-8386	63	53	,	,	PUNCT
app01-8386	63	54	eff	eff	PROPN
app01-8386	63	55	stiffness	stiffness	PROPN
app01-8386	63	56	component	component	NOUN
app01-8386	63	57	k12	k12	PROPN
app01-8386	63	58	reinforcement	reinforcement	NOUN
app01-8386	63	59	yield	yield	NOUN
app01-8386	63	60	stress	stress	NOUN
app01-8386	63	61	fy	fy	PROPN
app01-8386	63	62	stiffness	stiffness	NOUN
app01-8386	63	63	component	component	NOUN
app01-8386	63	64	k13	k13	NOUN
app01-8386	63	65	reinforcement	reinforcement	NOUN
app01-8386	63	66	ultimate	ultimate	ADJ
app01-8386	63	67	stress	stress	NOUN
app01-8386	63	68	fu	fu	NOUN
app01-8386	63	69	stiffness	stiffness	ADJ
app01-8386	63	70	component	component	NOUN
app01-8386	63	71	k21	k21	NOUN
app01-8386	63	72	reinforcement	reinforcement	NOUN
app01-8386	63	73	ultimate	ultimate	ADJ
app01-8386	63	74	strain	strain	NOUN
app01-8386	63	75	ϵsu	ϵsu	ADJ
app01-8386	63	76	stiffness	stiffness	NOUN
app01-8386	63	77	component	component	NOUN
app01-8386	63	78	k22	k22	NOUN
app01-8386	63	79	reinforcement	reinforcement	NOUN
app01-8386	63	80	angle	angle	NOUN
app01-8386	63	81	θs	θs	PUNCT
app01-8386	63	82	stiffness	stiffness	NOUN
app01-8386	63	83	component	component	NOUN
app01-8386	63	84	k23	k23	PROPN
app01-8386	63	85	concrete	concrete	PROPN
app01-8386	63	86	compressive	compressive	PROPN
app01-8386	63	87	strength	strength	PROPN
app01-8386	63	88	fcc	fcc	PROPN
app01-8386	63	89	stiffness	stiffness	NOUN
app01-8386	63	90	component	component	NOUN
app01-8386	63	91	k31	k31	NOUN
app01-8386	63	92	concrete	concrete	ADJ
app01-8386	63	93	ultimate	ultimate	ADJ
app01-8386	63	94	strain	strain	NOUN
app01-8386	63	95	ϵcu	ϵcu	NOUN
app01-8386	63	96	stiffness	stiffness	NOUN
app01-8386	63	97	component	component	NOUN
app01-8386	63	98	k32	k32	NOUN
app01-8386	63	99	normal	normal	ADJ
app01-8386	63	100	strain	strain	NOUN
app01-8386	63	101	in	in	ADP
app01-8386	63	102	x	x	NOUN
app01-8386	63	103	-	-	NOUN
app01-8386	63	104	direction	direction	NOUN
app01-8386	63	105	ϵx	ϵx	ADP
app01-8386	63	106	stiffness	stiffness	ADJ
app01-8386	63	107	component	component	NOUN
app01-8386	63	108	k33	k33	NOUN
app01-8386	63	109	normal	normal	ADJ
app01-8386	63	110	strain	strain	NOUN
app01-8386	63	111	in	in	ADP
app01-8386	63	112	y	y	NOUN
app01-8386	63	113	-	-	PUNCT
app01-8386	63	114	direction	direction	NOUN
app01-8386	63	115	ϵy	ϵy	NOUN
app01-8386	63	116	shear	shear	NOUN
app01-8386	63	117	strain	strain	NOUN
app01-8386	63	118	in	in	ADP
app01-8386	63	119	xy	xy	NOUN
app01-8386	63	120	-	-	PUNCT
app01-8386	63	121	direction	direction	NOUN
app01-8386	63	122	ϵxy	ϵxy	NOUN
app01-8386	63	123	table	table	NOUN
app01-8386	64	1	1	1	NUM
app01-8386	64	2	.	.	X
app01-8386	64	3	list	list	NOUN
app01-8386	64	4	of	of	ADP
app01-8386	64	5	features	feature	NOUN
app01-8386	64	6	and	and	CCONJ
app01-8386	64	7	targets	target	NOUN
app01-8386	64	8	for	for	ADP
app01-8386	64	9	data	data	NOUN
app01-8386	64	10	generation	generation	NOUN
app01-8386	64	11	and	and	CCONJ
app01-8386	64	12	calibration	calibration	NOUN
app01-8386	64	13	of	of	ADP
app01-8386	64	14	ai	ai	ADJ
app01-8386	64	15	-	-	PUNCT
app01-8386	64	16	fem	fem	NOUN
app01-8386	64	17	-	-	PUNCT
app01-8386	64	18	hybrids	hybrid	NOUN
app01-8386	64	19	.	.	PUNCT
app01-8386	65	1	note	note	VERB
app01-8386	65	2	that	that	SCONJ
app01-8386	65	3	ϵxy	ϵxy	PRON
app01-8386	65	4	is	be	AUX
app01-8386	65	5	the	the	DET
app01-8386	65	6	tensorial	tensorial	ADJ
app01-8386	65	7	component	component	NOUN
app01-8386	65	8	of	of	ADP
app01-8386	65	9	the	the	DET
app01-8386	65	10	shear	shear	NOUN
app01-8386	65	11	strain	strain	PROPN
app01-8386	65	12	γxy	γxy	PROPN
app01-8386	65	13	,	,	PUNCT
app01-8386	65	14	i.e.	i.e.	X
app01-8386	65	15	,	,	PUNCT
app01-8386	65	16	ϵxy	ϵxy	ADJ
app01-8386	65	17	=	=	NOUN
app01-8386	65	18	γxy/2	γxy/2	NOUN
app01-8386	65	19	.	.	PUNCT
app01-8386	66	1	all	all	DET
app01-8386	66	2	necessary	necessary	ADJ
app01-8386	66	3	features	feature	NOUN
app01-8386	66	4	(	(	PUNCT
app01-8386	66	5	input	input	NOUN
app01-8386	66	6	parameters	parameter	NOUN
app01-8386	66	7	x	x	NOUN
app01-8386	66	8	:	:	PUNCT
app01-8386	66	9	strain	strain	PROPN
app01-8386	66	10	tensor	tensor	NOUN
app01-8386	66	11	,	,	PUNCT
app01-8386	66	12	reinforcement	reinforcement	NOUN
app01-8386	66	13	properties	property	NOUN
app01-8386	66	14	,	,	PUNCT
app01-8386	66	15	material	material	NOUN
app01-8386	66	16	constants	constant	NOUN
app01-8386	66	17	,	,	PUNCT
app01-8386	66	18	etc	etc	X
app01-8386	66	19	.	.	X
app01-8386	66	20	acc	acc	PROPN
app01-8386	66	21	.	.	PROPN
app01-8386	66	22	to	to	PART
app01-8386	66	23	tab	tab	VERB
app01-8386	66	24	.	.	PROPN
app01-8386	66	25	1	1	NUM
app01-8386	66	26	)	)	PUNCT
app01-8386	66	27	and	and	CCONJ
app01-8386	66	28	results	result	NOUN
app01-8386	66	29	(	(	PUNCT
app01-8386	66	30	stress	stress	NOUN
app01-8386	66	31	and	and	CCONJ
app01-8386	66	32	stiffness	stiffness	ADJ
app01-8386	66	33	tensors	tensor	NOUN
app01-8386	66	34	acc	acc	PROPN
app01-8386	66	35	.	.	PROPN
app01-8386	66	36	to	to	PART
app01-8386	66	37	tab	tab	VERB
app01-8386	66	38	.	.	PROPN
app01-8386	66	39	1	1	NUM
app01-8386	66	40	)	)	PUNCT
app01-8386	66	41	in	in	ADP
app01-8386	66	42	every	every	DET
app01-8386	66	43	integration	integration	NOUN
app01-8386	66	44	point	point	NOUN
app01-8386	66	45	(	(	PUNCT
app01-8386	66	46	gausspoints	gausspoint	NOUN
app01-8386	66	47	)	)	PUNCT
app01-8386	66	48	for	for	ADP
app01-8386	66	49	all	all	DET
app01-8386	66	50	converged	converged	ADJ
app01-8386	66	51	load	load	NOUN
app01-8386	66	52	steps	step	NOUN
app01-8386	66	53	.	.	PUNCT
app01-8386	67	1	this	this	DET
app01-8386	67	2	approach	approach	NOUN
app01-8386	67	3	enables	enable	VERB
app01-8386	67	4	the	the	DET
app01-8386	67	5	collection	collection	NOUN
app01-8386	67	6	of	of	ADP
app01-8386	67	7	a	a	DET
app01-8386	67	8	considerable	considerable	ADJ
app01-8386	67	9	number	number	NOUN
app01-8386	67	10	of	of	ADP
app01-8386	67	11	data	datum	NOUN
app01-8386	67	12	points	point	NOUN
app01-8386	67	13	within	within	ADP
app01-8386	67	14	one	one	NUM
app01-8386	67	15	non	non	ADJ
app01-8386	67	16	-	-	ADJ
app01-8386	67	17	linear	linear	ADJ
app01-8386	67	18	fem	fem	NOUN
app01-8386	67	19	computations	computation	NOUN
app01-8386	67	20	,	,	PUNCT
app01-8386	67	21	as	as	SCONJ
app01-8386	67	22	in	in	ADP
app01-8386	67	23	almost	almost	ADV
app01-8386	67	24	every	every	PRON
app01-8386	67	25	integration	integration	NOUN
app01-8386	67	26	point	point	VERB
app01-8386	67	27	an	an	DET
app01-8386	67	28	individual	individual	ADJ
app01-8386	67	29	data	datum	NOUN
app01-8386	67	30	set	set	NOUN
app01-8386	67	31	exists	exist	VERB
app01-8386	67	32	.	.	PUNCT
app01-8386	68	1	for	for	ADP
app01-8386	68	2	simplicity	simplicity	NOUN
app01-8386	68	3	,	,	PUNCT
app01-8386	68	4	a	a	DET
app01-8386	68	5	dummy	dummy	ADJ
app01-8386	68	6	girder	girder	NOUN
app01-8386	68	7	bridge	bridge	NOUN
app01-8386	68	8	was	be	AUX
app01-8386	68	9	chosen	choose	VERB
app01-8386	68	10	to	to	PART
app01-8386	68	11	minimise	minimise	VERB
app01-8386	68	12	the	the	DET
app01-8386	68	13	number	number	NOUN
app01-8386	68	14	of	of	ADP
app01-8386	68	15	parameters	parameter	NOUN
app01-8386	68	16	,	,	PUNCT
app01-8386	68	17	e.g.	e.g.	ADV
app01-8386	68	18	the	the	DET
app01-8386	68	19	diameter	diameter	NOUN
app01-8386	68	20	of	of	ADP
app01-8386	68	21	the	the	DET
app01-8386	68	22	rebars	rebar	NOUN
app01-8386	68	23	or	or	CCONJ
app01-8386	68	24	the	the	DET
app01-8386	68	25	material	material	NOUN
app01-8386	68	26	constants	constant	NOUN
app01-8386	68	27	.	.	PUNCT
app01-8386	69	1	as	as	ADV
app01-8386	69	2	soon	soon	ADV
app01-8386	69	3	as	as	SCONJ
app01-8386	69	4	the	the	DET
app01-8386	69	5	general	general	ADJ
app01-8386	69	6	framework	framework	NOUN
app01-8386	69	7	of	of	ADP
app01-8386	69	8	the	the	DET
app01-8386	69	9	ai	ai	ADJ
app01-8386	69	10	-	-	PUNCT
app01-8386	69	11	fem	fem	NOUN
app01-8386	69	12	-	-	PUNCT
app01-8386	69	13	hybrids	hybrid	NOUN
app01-8386	69	14	is	be	AUX
app01-8386	69	15	established	establish	VERB
app01-8386	69	16	(	(	PUNCT
app01-8386	69	17	proof	proof	NOUN
app01-8386	69	18	of	of	ADP
app01-8386	69	19	concept	concept	NOUN
app01-8386	69	20	)	)	PUNCT
app01-8386	69	21	,	,	PUNCT
app01-8386	69	22	the	the	DET
app01-8386	69	23	results	result	NOUN
app01-8386	69	24	of	of	ADP
app01-8386	69	25	any	any	DET
app01-8386	69	26	dummy	dummy	ADJ
app01-8386	69	27	experiment	experiment	NOUN
app01-8386	69	28	and	and	CCONJ
app01-8386	69	29	the	the	DET
app01-8386	69	30	results	result	NOUN
app01-8386	69	31	of	of	ADP
app01-8386	69	32	any	any	DET
app01-8386	69	33	fem	fem	NOUN
app01-8386	69	34	analysis	analysis	NOUN
app01-8386	69	35	using	use	VERB
app01-8386	69	36	the	the	DET
app01-8386	69	37	cmm	cmm	NOUN
app01-8386	69	38	-	-	NOUN
app01-8386	69	39	usermat	usermat	NOUN
app01-8386	69	40	can	can	AUX
app01-8386	69	41	be	be	AUX
app01-8386	69	42	used	use	VERB
app01-8386	69	43	to	to	PART
app01-8386	69	44	train	train	VERB
app01-8386	69	45	the	the	DET
app01-8386	69	46	machine	machine	NOUN
app01-8386	69	47	learning	learn	VERB
app01-8386	69	48	algorithms	algorithm	NOUN
app01-8386	69	49	.	.	PUNCT
app01-8386	70	1	in	in	ADP
app01-8386	70	2	total	total	ADJ
app01-8386	70	3	the	the	DET
app01-8386	70	4	data	datum	NOUN
app01-8386	70	5	set	set	VERB
app01-8386	70	6	consists	consist	VERB
app01-8386	70	7	of	of	ADP
app01-8386	70	8	:	:	PUNCT
app01-8386	70	9	•	•	NUM
app01-8386	70	10	ns	ns	PROPN
app01-8386	70	11	,	,	PUNCT
app01-8386	70	12	wor	wor	NOUN
app01-8386	70	13	=	=	PROPN
app01-8386	70	14	10	10	NUM
app01-8386	70	15	,	,	PUNCT
app01-8386	70	16	636	636	NUM
app01-8386	70	17	,	,	PUNCT
app01-8386	70	18	800	800	NUM
app01-8386	70	19	samples	sample	NOUN
app01-8386	70	20	of	of	ADP
app01-8386	70	21	concrete	concrete	ADJ
app01-8386	70	22	elements	element	NOUN
app01-8386	70	23	without	without	ADP
app01-8386	70	24	reinforcement	reinforcement	NOUN
app01-8386	70	25	(	(	PUNCT
app01-8386	70	26	configuration	configuration	NOUN
app01-8386	70	27	"	"	PUNCT
app01-8386	70	28	cf	cf	NOUN
app01-8386	70	29	0	0	NUM
app01-8386	70	30	"	"	PUNCT
app01-8386	70	31	)	)	PUNCT
app01-8386	70	32	•	•	X
app01-8386	71	1	ns	ns	ADJ
app01-8386	71	2	,	,	PUNCT
app01-8386	71	3	wr	wr	NOUN
app01-8386	71	4	=	=	SYM
app01-8386	71	5	443	443	NUM
app01-8386	71	6	,	,	PUNCT
app01-8386	71	7	200	200	NUM
app01-8386	71	8	samples	sample	NOUN
app01-8386	71	9	of	of	ADP
app01-8386	71	10	concrete	concrete	ADJ
app01-8386	71	11	elements	element	NOUN
app01-8386	71	12	with	with	ADP
app01-8386	71	13	reinforcement	reinforcement	NOUN
app01-8386	71	14	(	(	PUNCT
app01-8386	71	15	configuration	configuration	NOUN
app01-8386	71	16	"	"	PUNCT
app01-8386	71	17	cf	cf	NOUN
app01-8386	71	18	1	1	NUM
app01-8386	71	19	"	"	PUNCT
app01-8386	71	20	)	)	PUNCT
app01-8386	71	21	2.3	2.3	NUM
app01-8386	71	22	.	.	PUNCT
app01-8386	72	1	data	datum	NOUN
app01-8386	72	2	pre	pre	VERB
app01-8386	72	3	-	-	VERB
app01-8386	72	4	processing	process	VERB
app01-8386	72	5	the	the	DET
app01-8386	72	6	data	datum	NOUN
app01-8386	72	7	generated	generate	VERB
app01-8386	72	8	in	in	ADP
app01-8386	72	9	the	the	DET
app01-8386	72	10	previous	previous	ADJ
app01-8386	72	11	section	section	NOUN
app01-8386	72	12	is	be	AUX
app01-8386	72	13	used	use	VERB
app01-8386	72	14	to	to	PART
app01-8386	72	15	develop	develop	VERB
app01-8386	72	16	the	the	DET
app01-8386	72	17	ml	ml	NOUN
app01-8386	72	18	resp	resp	NOUN
app01-8386	72	19	.	.	PUNCT
app01-8386	73	1	dl	dl	PROPN
app01-8386	73	2	models	model	NOUN
app01-8386	73	3	.	.	PUNCT
app01-8386	74	1	the	the	DET
app01-8386	74	2	dataset	dataset	NOUN
app01-8386	74	3	consists	consist	VERB
app01-8386	74	4	of	of	ADP
app01-8386	74	5	over	over	ADP
app01-8386	74	6	11	11	NUM
app01-8386	74	7	million	million	NUM
app01-8386	74	8	data	datum	NOUN
app01-8386	74	9	points	point	NOUN
app01-8386	74	10	with	with	ADP
app01-8386	74	11	14	14	NUM
app01-8386	74	12	feature	feature	NOUN
app01-8386	74	13	and	and	CCONJ
app01-8386	74	14	12	12	NUM
app01-8386	74	15	target	target	NOUN
app01-8386	74	16	variables	variable	NOUN
app01-8386	74	17	,	,	PUNCT
app01-8386	74	18	cf	cf	NOUN
app01-8386	74	19	.	.	PUNCT
app01-8386	74	20	tab	tab	NOUN
app01-8386	74	21	.	.	PUNCT
app01-8386	75	1	1	1	X
app01-8386	75	2	.	.	X
app01-8386	76	1	some	some	DET
app01-8386	76	2	dimensions	dimension	NOUN
app01-8386	76	3	of	of	ADP
app01-8386	76	4	the	the	DET
app01-8386	76	5	feature	feature	NOUN
app01-8386	76	6	dataset	dataset	NOUN
app01-8386	76	7	are	be	AUX
app01-8386	76	8	categorical	categorical	ADJ
app01-8386	76	9	(	(	PUNCT
app01-8386	76	10	reinforcement	reinforcement	NOUN
app01-8386	76	11	layer	layer	NOUN
app01-8386	76	12	,	,	PUNCT
app01-8386	76	13	cmm	cmm	NOUN
app01-8386	76	14	-	-	ADJ
app01-8386	76	15	usermat	usermat	ADJ
app01-8386	76	16	model	model	NOUN
app01-8386	76	17	)	)	PUNCT
app01-8386	76	18	,	,	PUNCT
app01-8386	76	19	while	while	SCONJ
app01-8386	76	20	the	the	DET
app01-8386	76	21	remaining	remain	VERB
app01-8386	76	22	features	feature	NOUN
app01-8386	76	23	are	be	AUX
app01-8386	76	24	all	all	PRON
app01-8386	76	25	of	of	ADP
app01-8386	76	26	numerical	numerical	ADJ
app01-8386	76	27	nature	nature	NOUN
app01-8386	76	28	.	.	PUNCT
app01-8386	77	1	for	for	ADP
app01-8386	77	2	the	the	DET
app01-8386	77	3	categorical	categorical	ADJ
app01-8386	77	4	features	feature	NOUN
app01-8386	77	5	we	we	PRON
app01-8386	77	6	use	use	VERB
app01-8386	77	7	one	one	NUM
app01-8386	77	8	-	-	PUNCT
app01-8386	77	9	hot	hot	ADJ
app01-8386	77	10	-	-	PUNCT
app01-8386	77	11	encoding	encoding	NOUN
app01-8386	77	12	.	.	PUNCT
app01-8386	78	1	all	all	DET
app01-8386	78	2	dimensions	dimension	NOUN
app01-8386	78	3	of	of	ADP
app01-8386	78	4	the	the	DET
app01-8386	78	5	target	target	NOUN
app01-8386	78	6	dataset	dataset	NOUN
app01-8386	78	7	are	be	AUX
app01-8386	78	8	of	of	ADP
app01-8386	78	9	numerical	numerical	ADJ
app01-8386	78	10	nature	nature	NOUN
app01-8386	78	11	.	.	PUNCT
app01-8386	79	1	none	none	NOUN
app01-8386	79	2	of	of	ADP
app01-8386	79	3	the	the	DET
app01-8386	79	4	attributes	attribute	NOUN
app01-8386	79	5	has	have	VERB
app01-8386	79	6	any	any	DET
app01-8386	79	7	missing	missing	ADJ
app01-8386	79	8	data	datum	NOUN
app01-8386	79	9	since	since	SCONJ
app01-8386	79	10	the	the	DET
app01-8386	79	11	data	data	NOUN
app01-8386	79	12	is	be	AUX
app01-8386	79	13	generated	generate	VERB
app01-8386	79	14	via	via	ADP
app01-8386	79	15	fem	fem	NOUN
app01-8386	79	16	analyses	analysis	NOUN
app01-8386	79	17	.	.	PUNCT
app01-8386	80	1	the	the	DET
app01-8386	80	2	range	range	NOUN
app01-8386	80	3	of	of	ADP
app01-8386	80	4	values	value	NOUN
app01-8386	80	5	101	101	NUM
app01-8386	80	6	m.	m.	PROPN
app01-8386	80	7	a.	a.	PROPN
app01-8386	80	8	kraus	kraus	PROPN
app01-8386	80	9	,	,	PUNCT
app01-8386	80	10	r.	r.	PROPN
app01-8386	80	11	bischof	bischof	PROPN
app01-8386	80	12	,	,	PUNCT
app01-8386	80	13	w.	w.	PROPN
app01-8386	80	14	kaufmann	kaufmann	PROPN
app01-8386	80	15	,	,	PUNCT
app01-8386	80	16	k.	k.	PROPN
app01-8386	80	17	thoma	thoma	PROPN
app01-8386	80	18	acta	acta	PROPN
app01-8386	80	19	polytechnica	polytechnica	PROPN
app01-8386	80	20	ctu	ctu	NOUN
app01-8386	80	21	proceedings	proceeding	NOUN
app01-8386	80	22	x	x	PUNCT
app01-8386	80	23	z	z	NOUN
app01-8386	80	24	y	y	PROPN
app01-8386	80	25	integration	integration	NOUN
app01-8386	80	26	poinst	poinst	NOUN
app01-8386	80	27	shell	shell	NOUN
app01-8386	80	28	element	element	NOUN
app01-8386	80	29	shell181	shell181	PROPN
app01-8386	80	30	l	l	NOUN
app01-8386	80	31	l	l	PROPN
app01-8386	80	32	b	b	X
app01-8386	80	33	0	0	NUM
app01-8386	80	34	h	h	NOUN
app01-8386	80	35	0	0	PUNCT
app01-8386	81	1	a	a	DET
app01-8386	81	2	y	y	PROPN
app01-8386	81	3	a	a	DET
app01-8386	81	4	z	z	NOUN
app01-8386	81	5	a	a	X
app01-8386	81	6	x	x	SYM
app01-8386	81	7	a	a	PRON
app01-8386	81	8	x	x	X
app01-8386	81	9	z	z	NOUN
app01-8386	81	10	x	x	PUNCT
app01-8386	81	11	y	y	NOUN
app01-8386	81	12	y	y	PROPN
app01-8386	81	13	x	x	SYM
app01-8386	81	14	z	z	NOUN
app01-8386	81	15	(	(	PUNCT
app01-8386	81	16	a	a	NOUN
app01-8386	81	17	)	)	PUNCT
app01-8386	81	18	(	(	PUNCT
app01-8386	81	19	b	b	X
app01-8386	81	20	)	)	PUNCT
app01-8386	81	21	(	(	PUNCT
app01-8386	81	22	c	c	X
app01-8386	81	23	)	)	PUNCT
app01-8386	81	24	figure	figure	NOUN
app01-8386	81	25	2	2	NUM
app01-8386	81	26	.	.	NOUN
app01-8386	81	27	detail	detail	NOUN
app01-8386	81	28	of	of	ADP
app01-8386	81	29	the	the	DET
app01-8386	81	30	cmm	cmm	PROPN
app01-8386	81	31	finite	finite	PROPN
app01-8386	81	32	element	element	PROPN
app01-8386	81	33	within	within	ADP
app01-8386	81	34	ansys	ansys	PROPN
app01-8386	81	35	to	to	PART
app01-8386	81	36	generate	generate	VERB
app01-8386	81	37	the	the	DET
app01-8386	81	38	database	database	NOUN
app01-8386	81	39	.	.	PUNCT
app01-8386	82	1	of	of	ADP
app01-8386	82	2	the	the	DET
app01-8386	82	3	features	feature	NOUN
app01-8386	82	4	as	as	ADV
app01-8386	82	5	well	well	ADV
app01-8386	82	6	as	as	ADP
app01-8386	82	7	the	the	DET
app01-8386	82	8	targets	target	NOUN
app01-8386	82	9	are	be	AUX
app01-8386	82	10	extremely	extremely	ADV
app01-8386	82	11	different	different	ADJ
app01-8386	82	12	,	,	PUNCT
app01-8386	82	13	hence	hence	ADV
app01-8386	82	14	we	we	PRON
app01-8386	82	15	employ	employ	VERB
app01-8386	82	16	normalization	normalization	NOUN
app01-8386	82	17	of	of	ADP
app01-8386	82	18	the	the	DET
app01-8386	82	19	data	datum	NOUN
app01-8386	82	20	.	.	PUNCT
app01-8386	83	1	for	for	ADP
app01-8386	83	2	each	each	DET
app01-8386	83	3	numerical	numerical	PROPN
app01-8386	83	4	variable	variable	PROPN
app01-8386	83	5	vi	vi	PROPN
app01-8386	83	6	we	we	PRON
app01-8386	83	7	deduce	deduce	VERB
app01-8386	83	8	its	its	PRON
app01-8386	83	9	mean	mean	NOUN
app01-8386	83	10	m	m	NOUN
app01-8386	83	11	and	and	CCONJ
app01-8386	83	12	divide	divide	VERB
app01-8386	83	13	it	it	PRON
app01-8386	83	14	by	by	ADP
app01-8386	83	15	its	its	PRON
app01-8386	83	16	standard	standard	ADJ
app01-8386	83	17	deviation	deviation	NOUN
app01-8386	83	18	s	s	PART
app01-8386	83	19	(	(	PUNCT
app01-8386	83	20	yielding	yield	VERB
app01-8386	83	21	its	its	PRON
app01-8386	83	22	z	z	NOUN
app01-8386	83	23	-	-	PUNCT
app01-8386	83	24	score	score	NOUN
app01-8386	83	25	)	)	PUNCT
app01-8386	83	26	using	use	VERB
app01-8386	83	27	:	:	PUNCT
app01-8386	83	28	zi	zi	NOUN
app01-8386	83	29	=	=	SYM
app01-8386	83	30	vi	vi	PROPN
app01-8386	84	1	−	−	NOUN
app01-8386	85	1	µi	µi	INTJ
app01-8386	85	2	σi	σi	X
app01-8386	85	3	(	(	PUNCT
app01-8386	85	4	1	1	NUM
app01-8386	85	5	)	)	PUNCT
app01-8386	85	6	for	for	ADP
app01-8386	85	7	sake	sake	NOUN
app01-8386	85	8	of	of	ADP
app01-8386	85	9	brevity	brevity	NOUN
app01-8386	85	10	of	of	ADP
app01-8386	85	11	this	this	DET
app01-8386	85	12	paper	paper	NOUN
app01-8386	85	13	,	,	PUNCT
app01-8386	85	14	we	we	PRON
app01-8386	85	15	omit	omit	VERB
app01-8386	85	16	reporting	report	VERB
app01-8386	85	17	further	further	ADJ
app01-8386	85	18	statistical	statistical	ADJ
app01-8386	85	19	properties	property	NOUN
app01-8386	85	20	or	or	CCONJ
app01-8386	85	21	histograms	histogram	NOUN
app01-8386	85	22	of	of	ADP
app01-8386	85	23	the	the	DET
app01-8386	85	24	dataset	dataset	NOUN
app01-8386	85	25	,	,	PUNCT
app01-8386	85	26	which	which	PRON
app01-8386	85	27	would	would	AUX
app01-8386	85	28	usually	usually	ADV
app01-8386	85	29	be	be	AUX
app01-8386	85	30	delivered	deliver	VERB
app01-8386	85	31	in	in	ADP
app01-8386	85	32	the	the	DET
app01-8386	85	33	exploratory	exploratory	ADJ
app01-8386	85	34	data	datum	NOUN
app01-8386	85	35	analysis	analysis	NOUN
app01-8386	85	36	step	step	NOUN
app01-8386	85	37	.	.	PUNCT
app01-8386	86	1	2.4	2.4	NUM
app01-8386	86	2	.	.	PUNCT
app01-8386	86	3	machine	machine	NOUN
app01-8386	86	4	learning	learn	VERB
app01-8386	86	5	model	model	PROPN
app01-8386	86	6	development	development	NOUN
app01-8386	86	7	in	in	ADP
app01-8386	86	8	this	this	DET
app01-8386	86	9	study	study	NOUN
app01-8386	86	10	,	,	PUNCT
app01-8386	86	11	three	three	NUM
app01-8386	86	12	ml	ml	NOUN
app01-8386	86	13	resp	resp	NOUN
app01-8386	86	14	.	.	PUNCT
app01-8386	87	1	dl	dl	PROPN
app01-8386	87	2	algorithms	algorithms	PROPN
app01-8386	87	3	for	for	ADP
app01-8386	87	4	regression	regression	NOUN
app01-8386	87	5	are	be	AUX
app01-8386	87	6	investigated	investigate	VERB
app01-8386	87	7	for	for	ADP
app01-8386	87	8	predictive	predictive	ADJ
app01-8386	87	9	capabilities	capability	NOUN
app01-8386	87	10	for	for	ADP
app01-8386	87	11	stress	stress	NOUN
app01-8386	87	12	and	and	CCONJ
app01-8386	87	13	stiffness	stiffness	ADJ
app01-8386	87	14	target	target	NOUN
app01-8386	87	15	tensors	tensor	NOUN
app01-8386	87	16	given	give	VERB
app01-8386	87	17	the	the	DET
app01-8386	87	18	strain	strain	NOUN
app01-8386	87	19	tensor	tensor	NOUN
app01-8386	87	20	together	together	ADV
app01-8386	87	21	with	with	ADP
app01-8386	87	22	concrete	concrete	ADJ
app01-8386	87	23	and	and	CCONJ
app01-8386	87	24	reinforcement	reinforcement	NOUN
app01-8386	87	25	features	feature	NOUN
app01-8386	87	26	:	:	PUNCT
app01-8386	87	27	•	•	NUM
app01-8386	87	28	k	k	X
app01-8386	87	29	-	-	PUNCT
app01-8386	87	30	nearest	near	ADJ
app01-8386	87	31	-	-	PUNCT
app01-8386	87	32	neighbours	neighbours	NOUN
app01-8386	87	33	(	(	PUNCT
app01-8386	87	34	knn	knn	PROPN
app01-8386	87	35	)	)	PUNCT
app01-8386	87	36	•	•	ADP
app01-8386	87	37	lightgbm	lightgbm	VERB
app01-8386	87	38	•	•	ADJ
app01-8386	87	39	artificial	artificial	ADJ
app01-8386	87	40	neural	neural	ADJ
app01-8386	87	41	networks	network	NOUN
app01-8386	87	42	:	:	PUNCT
app01-8386	87	43	residual	residual	ADJ
app01-8386	87	44	neural	neural	ADJ
app01-8386	87	45	networks	network	NOUN
app01-8386	87	46	(	(	PUNCT
app01-8386	87	47	resnet	resnet	NOUN
app01-8386	87	48	)	)	PUNCT
app01-8386	87	49	while	while	SCONJ
app01-8386	87	50	knn	knn	PROPN
app01-8386	87	51	is	be	AUX
app01-8386	87	52	a	a	DET
app01-8386	87	53	strictly	strictly	ADV
app01-8386	87	54	data	data	NOUN
app01-8386	87	55	-	-	PUNCT
app01-8386	87	56	driven	drive	VERB
app01-8386	87	57	approach	approach	NOUN
app01-8386	87	58	and	and	CCONJ
app01-8386	87	59	hence	hence	ADV
app01-8386	87	60	needs	need	VERB
app01-8386	87	61	to	to	PART
app01-8386	87	62	store	store	VERB
app01-8386	87	63	some	some	PRON
app01-8386	87	64	of	of	ADP
app01-8386	87	65	the	the	DET
app01-8386	87	66	simulation	simulation	NOUN
app01-8386	87	67	data	datum	NOUN
app01-8386	87	68	instances	instance	NOUN
app01-8386	87	69	,	,	PUNCT
app01-8386	87	70	lightgbm	lightgbm	VERB
app01-8386	87	71	as	as	ADV
app01-8386	87	72	well	well	ADV
app01-8386	87	73	as	as	ADP
app01-8386	87	74	resnet	resnet	NOUN
app01-8386	87	75	are	be	AUX
app01-8386	87	76	surrogate	surrogate	ADJ
app01-8386	87	77	functions	function	NOUN
app01-8386	87	78	without	without	ADP
app01-8386	87	79	the	the	DET
app01-8386	87	80	need	need	NOUN
app01-8386	87	81	to	to	PART
app01-8386	87	82	store	store	VERB
app01-8386	87	83	the	the	DET
app01-8386	87	84	training	training	NOUN
app01-8386	87	85	data	datum	NOUN
app01-8386	87	86	.	.	PUNCT
app01-8386	88	1	due	due	ADP
app01-8386	88	2	to	to	ADP
app01-8386	88	3	reasons	reason	NOUN
app01-8386	88	4	of	of	ADP
app01-8386	88	5	brevity	brevity	NOUN
app01-8386	88	6	of	of	ADP
app01-8386	88	7	this	this	DET
app01-8386	88	8	paper	paper	NOUN
app01-8386	88	9	,	,	PUNCT
app01-8386	88	10	only	only	ADV
app01-8386	88	11	selected	select	VERB
app01-8386	88	12	results	result	NOUN
app01-8386	88	13	and	and	CCONJ
app01-8386	88	14	implementation	implementation	NOUN
app01-8386	88	15	details	detail	NOUN
app01-8386	88	16	can	can	AUX
app01-8386	88	17	be	be	AUX
app01-8386	88	18	reported	report	VERB
app01-8386	88	19	.	.	PUNCT
app01-8386	89	1	the	the	DET
app01-8386	89	2	ml	ml	PROPN
app01-8386	89	3	models	model	NOUN
app01-8386	89	4	are	be	AUX
app01-8386	89	5	developed	develop	VERB
app01-8386	89	6	using	use	VERB
app01-8386	89	7	sklearn	sklearn	PROPN
app01-8386	89	8	,	,	PUNCT
app01-8386	89	9	keras	keras	PROPN
app01-8386	89	10	,	,	PUNCT
app01-8386	89	11	and	and	CCONJ
app01-8386	89	12	xgboost	xgboost	NOUN
app01-8386	89	13	(	(	PUNCT
app01-8386	89	14	extreme	extreme	ADJ
app01-8386	89	15	gradient	gradient	NOUN
app01-8386	89	16	boosting	boosting	NOUN
app01-8386	89	17	)	)	PUNCT
app01-8386	89	18	python	python	NOUN
app01-8386	89	19	libraries	library	NOUN
app01-8386	89	20	and	and	CCONJ
app01-8386	89	21	run	run	VERB
app01-8386	89	22	on	on	ADP
app01-8386	89	23	the	the	DET
app01-8386	89	24	eth	eth	PROPN
app01-8386	89	25	euler	euler	PROPN
app01-8386	89	26	cluster1	cluster1	PROPN
app01-8386	89	27	.	.	PUNCT
app01-8386	90	1	2.4.1	2.4.1	NUM
app01-8386	90	2	.	.	PUNCT
app01-8386	91	1	knn	knn	VERB
app01-8386	91	2	the	the	DET
app01-8386	91	3	k	k	PROPN
app01-8386	91	4	-	-	PUNCT
app01-8386	91	5	nearest	near	ADJ
app01-8386	91	6	-	-	PUNCT
app01-8386	91	7	neighbours	neighbours	NOUN
app01-8386	91	8	algorithm	algorithm	NOUN
app01-8386	91	9	is	be	AUX
app01-8386	91	10	a	a	DET
app01-8386	91	11	decision	decision	NOUN
app01-8386	91	12	method	method	NOUN
app01-8386	91	13	originally	originally	ADV
app01-8386	91	14	developed	develop	VERB
app01-8386	91	15	for	for	ADP
app01-8386	91	16	classification	classification	NOUN
app01-8386	91	17	tasks	task	NOUN
app01-8386	91	18	[	[	X
app01-8386	91	19	10	10	NUM
app01-8386	91	20	]	]	PUNCT
app01-8386	91	21	.	.	PUNCT
app01-8386	92	1	at	at	ADP
app01-8386	92	2	inference	inference	NOUN
app01-8386	92	3	time	time	NOUN
app01-8386	92	4	,	,	PUNCT
app01-8386	92	5	it	it	PRON
app01-8386	92	6	compares	compare	VERB
app01-8386	92	7	the	the	DET
app01-8386	92	8	previously	previously	ADV
app01-8386	92	9	unseen	unseen	ADJ
app01-8386	92	10	samples	sample	NOUN
app01-8386	92	11	to	to	ADP
app01-8386	92	12	all	all	DET
app01-8386	92	13	instances	instance	NOUN
app01-8386	92	14	in	in	ADP
app01-8386	92	15	a	a	DET
app01-8386	92	16	database	database	NOUN
app01-8386	92	17	and	and	CCONJ
app01-8386	92	18	assigns	assign	NOUN
app01-8386	92	19	classes	class	NOUN
app01-8386	92	20	by	by	ADP
app01-8386	92	21	means	mean	NOUN
app01-8386	92	22	of	of	ADP
app01-8386	92	23	majority	majority	NOUN
app01-8386	92	24	voting	voting	NOUN
app01-8386	92	25	of	of	ADP
app01-8386	92	26	the	the	DET
app01-8386	92	27	k	k	PROPN
app01-8386	92	28	nearest	near	ADJ
app01-8386	92	29	neighbours	neighbour	NOUN
app01-8386	92	30	,	,	PUNCT
app01-8386	92	31	where	where	SCONJ
app01-8386	92	32	k	k	PROPN
app01-8386	92	33	and	and	CCONJ
app01-8386	92	34	the	the	DET
app01-8386	92	35	distance	distance	NOUN
app01-8386	92	36	metric	metric	NOUN
app01-8386	92	37	are	be	AUX
app01-8386	92	38	hyperparameters	hyperparameter	NOUN
app01-8386	92	39	.	.	PUNCT
app01-8386	93	1	the	the	DET
app01-8386	93	2	algorithm	algorithm	NOUN
app01-8386	93	3	was	be	AUX
app01-8386	93	4	later	later	ADV
app01-8386	93	5	extended	extend	VERB
app01-8386	93	6	to	to	PART
app01-8386	93	7	support	support	VERB
app01-8386	93	8	regression	regression	NOUN
app01-8386	93	9	tasks	task	NOUN
app01-8386	94	1	[	[	X
app01-8386	94	2	11	11	NUM
app01-8386	94	3	]	]	PUNCT
app01-8386	94	4	by	by	ADP
app01-8386	94	5	interpolating	interpolate	VERB
app01-8386	94	6	between	between	ADP
app01-8386	94	7	the	the	DET
app01-8386	94	8	values	value	NOUN
app01-8386	94	9	of	of	ADP
app01-8386	94	10	the	the	DET
app01-8386	94	11	k	k	PROPN
app01-8386	94	12	nearest	near	ADJ
app01-8386	94	13	neighbours	neighbour	NOUN
app01-8386	94	14	(	(	PUNCT
app01-8386	94	15	e.g.	e.g.	ADV
app01-8386	94	16	through	through	ADP
app01-8386	94	17	inverse	inverse	NOUN
app01-8386	94	18	distance	distance	NOUN
app01-8386	94	19	weighted	weight	VERB
app01-8386	94	20	average	average	NOUN
app01-8386	94	21	)	)	PUNCT
app01-8386	94	22	to	to	PART
app01-8386	94	23	obtain	obtain	VERB
app01-8386	94	24	values	value	NOUN
app01-8386	94	25	for	for	ADP
app01-8386	94	26	new	new	ADJ
app01-8386	94	27	,	,	PUNCT
app01-8386	94	28	unseen	unseen	ADJ
app01-8386	94	29	samples	sample	NOUN
app01-8386	94	30	.	.	PUNCT
app01-8386	95	1	2.4.2	2.4.2	NUM
app01-8386	95	2	.	.	NOUN
app01-8386	95	3	lightgbm	lightgbm	ADJ
app01-8386	95	4	lightgbm	lightgbm	X
app01-8386	95	5	is	be	AUX
app01-8386	95	6	a	a	DET
app01-8386	95	7	gradient	gradient	ADJ
app01-8386	95	8	boosting	boost	VERB
app01-8386	95	9	decision	decision	NOUN
app01-8386	95	10	tree	tree	NOUN
app01-8386	95	11	framework	framework	NOUN
app01-8386	95	12	[	[	X
app01-8386	95	13	12	12	NUM
app01-8386	95	14	]	]	PUNCT
app01-8386	95	15	that	that	PRON
app01-8386	95	16	has	have	AUX
app01-8386	95	17	found	find	VERB
app01-8386	95	18	application	application	NOUN
app01-8386	95	19	in	in	ADP
app01-8386	95	20	many	many	ADJ
app01-8386	95	21	different	different	ADJ
app01-8386	95	22	data	datum	NOUN
app01-8386	95	23	mining	mining	NOUN
app01-8386	95	24	,	,	PUNCT
app01-8386	95	25	classification	classification	NOUN
app01-8386	95	26	and	and	CCONJ
app01-8386	95	27	regression	regression	NOUN
app01-8386	95	28	tasks	task	NOUN
app01-8386	95	29	.	.	PUNCT
app01-8386	96	1	the	the	DET
app01-8386	96	2	lightgbm	lightgbm	ADJ
app01-8386	96	3	algorithm	algorithm	NOUN
app01-8386	96	4	variant	variant	NOUN
app01-8386	96	5	used	use	VERB
app01-8386	96	6	in	in	ADP
app01-8386	96	7	this	this	DET
app01-8386	96	8	paper	paper	NOUN
app01-8386	96	9	integrates	integrate	VERB
app01-8386	96	10	a	a	DET
app01-8386	96	11	number	number	NOUN
app01-8386	96	12	of	of	ADP
app01-8386	96	13	regression	regression	NOUN
app01-8386	96	14	trees	tree	NOUN
app01-8386	96	15	to	to	PART
app01-8386	96	16	approximate	approximate	VERB
app01-8386	96	17	the	the	DET
app01-8386	96	18	dataset	dataset	NOUN
app01-8386	96	19	.	.	PUNCT
app01-8386	97	1	it	it	PRON
app01-8386	97	2	contains	contain	VERB
app01-8386	97	3	many	many	ADJ
app01-8386	97	4	of	of	ADP
app01-8386	97	5	the	the	DET
app01-8386	97	6	advantages	advantage	NOUN
app01-8386	97	7	of	of	ADP
app01-8386	97	8	other	other	ADJ
app01-8386	97	9	common	common	ADJ
app01-8386	97	10	gradient	gradient	NOUN
app01-8386	97	11	boosting	boost	VERB
app01-8386	97	12	decision	decision	NOUN
app01-8386	97	13	tree	tree	NOUN
app01-8386	97	14	algorithms	algorithm	NOUN
app01-8386	97	15	,	,	PUNCT
app01-8386	97	16	such	such	ADJ
app01-8386	97	17	as	as	ADP
app01-8386	97	18	sparse	sparse	ADJ
app01-8386	97	19	optimization	optimization	NOUN
app01-8386	97	20	,	,	PUNCT
app01-8386	97	21	parallel	parallel	ADJ
app01-8386	97	22	training	training	NOUN
app01-8386	97	23	,	,	PUNCT
app01-8386	97	24	regularization	regularization	NOUN
app01-8386	97	25	,	,	PUNCT
app01-8386	97	26	bagging	bagging	NOUN
app01-8386	97	27	,	,	PUNCT
app01-8386	97	28	and	and	CCONJ
app01-8386	97	29	early	early	ADJ
app01-8386	97	30	stopping	stopping	NOUN
app01-8386	97	31	.	.	PUNCT
app01-8386	98	1	however	however	ADV
app01-8386	98	2	,	,	PUNCT
app01-8386	98	3	it	it	PRON
app01-8386	98	4	grows	grow	VERB
app01-8386	98	5	trees	tree	NOUN
app01-8386	98	6	leaf	leaf	NOUN
app01-8386	98	7	-	-	PUNCT
app01-8386	98	8	wise	wise	ADJ
app01-8386	98	9	by	by	ADP
app01-8386	98	10	greedily	greedily	ADV
app01-8386	98	11	choosing	choose	VERB
app01-8386	98	12	the	the	DET
app01-8386	98	13	leaf	leaf	NOUN
app01-8386	98	14	that	that	PRON
app01-8386	98	15	will	will	AUX
app01-8386	98	16	lead	lead	VERB
app01-8386	98	17	to	to	ADP
app01-8386	98	18	the	the	DET
app01-8386	98	19	largest	large	ADJ
app01-8386	98	20	improvement	improvement	NOUN
app01-8386	98	21	.	.	PUNCT
app01-8386	99	1	this	this	DET
app01-8386	99	2	tree	tree	NOUN
app01-8386	99	3	-	-	PUNCT
app01-8386	99	4	growth	growth	NOUN
app01-8386	99	5	method	method	NOUN
app01-8386	99	6	,	,	PUNCT
app01-8386	99	7	in	in	ADP
app01-8386	99	8	combination	combination	NOUN
app01-8386	99	9	with	with	ADP
app01-8386	99	10	a	a	DET
app01-8386	99	11	histogram	histogram	NOUN
app01-8386	99	12	-	-	PUNCT
app01-8386	99	13	based	base	VERB
app01-8386	99	14	memory	memory	NOUN
app01-8386	99	15	and	and	CCONJ
app01-8386	99	16	computation	computation	NOUN
app01-8386	99	17	optimization	optimization	NOUN
app01-8386	99	18	,	,	PUNCT
app01-8386	99	19	make	make	VERB
app01-8386	99	20	lightgbm	lightgbm	ADJ
app01-8386	99	21	considerably	considerably	ADV
app01-8386	99	22	more	more	ADV
app01-8386	99	23	computationally	computationally	ADV
app01-8386	99	24	efficient	efficient	ADJ
app01-8386	99	25	than	than	ADP
app01-8386	99	26	other	other	ADJ
app01-8386	99	27	frameworks	framework	NOUN
app01-8386	99	28	.	.	PUNCT
app01-8386	100	1	2.4.3	2.4.3	X
app01-8386	100	2	.	.	PUNCT
app01-8386	100	3	artificial	artificial	ADJ
app01-8386	100	4	neural	neural	ADJ
app01-8386	100	5	networks	network	NOUN
app01-8386	100	6	fully	fully	ADV
app01-8386	100	7	-	-	PUNCT
app01-8386	100	8	connected	connect	VERB
app01-8386	100	9	feed	feed	NOUN
app01-8386	100	10	-	-	PUNCT
app01-8386	100	11	forward	forward	NOUN
app01-8386	100	12	neural	neural	ADJ
app01-8386	100	13	networks	network	NOUN
app01-8386	100	14	(	(	PUNCT
app01-8386	100	15	ffnn	ffnn	NOUN
app01-8386	100	16	)	)	PUNCT
app01-8386	100	17	consist	consist	NOUN
app01-8386	100	18	of	of	ADP
app01-8386	100	19	one	one	NUM
app01-8386	100	20	or	or	CCONJ
app01-8386	100	21	more	more	ADJ
app01-8386	100	22	layers	layer	NOUN
app01-8386	100	23	,	,	PUNCT
app01-8386	100	24	where	where	SCONJ
app01-8386	100	25	each	each	DET
app01-8386	100	26	node	node	NOUN
app01-8386	100	27	is	be	AUX
app01-8386	100	28	connected	connect	VERB
app01-8386	100	29	to	to	ADP
app01-8386	100	30	every	every	DET
app01-8386	100	31	node	node	NOUN
app01-8386	100	32	in	in	ADP
app01-8386	100	33	the	the	DET
app01-8386	100	34	following	follow	VERB
app01-8386	100	35	layer	layer	NOUN
app01-8386	100	36	[	[	X
app01-8386	100	37	13	13	NUM
app01-8386	100	38	]	]	PUNCT
app01-8386	100	39	.	.	PUNCT
app01-8386	101	1	despite	despite	SCONJ
app01-8386	101	2	being	be	AUX
app01-8386	101	3	very	very	ADV
app01-8386	101	4	straight	straight	ADJ
app01-8386	101	5	forward	forward	ADJ
app01-8386	101	6	architectures	architecture	NOUN
app01-8386	101	7	,	,	PUNCT
app01-8386	101	8	ffnns	ffnns	NOUN
app01-8386	101	9	are	be	AUX
app01-8386	101	10	universal	universal	ADJ
app01-8386	101	11	function	function	NOUN
app01-8386	101	12	approximators	approximator	NOUN
app01-8386	101	13	[	[	X
app01-8386	101	14	14	14	NUM
app01-8386	101	15	]	]	PUNCT
app01-8386	101	16	and	and	CCONJ
app01-8386	101	17	have	have	VERB
app01-8386	101	18	the	the	DET
app01-8386	101	19	advantage	advantage	NOUN
app01-8386	101	20	of	of	ADP
app01-8386	101	21	being	be	AUX
app01-8386	101	22	easy	easy	ADJ
app01-8386	101	23	to	to	PART
app01-8386	101	24	implement	implement	VERB
app01-8386	101	25	and	and	CCONJ
app01-8386	101	26	efficient	efficient	ADJ
app01-8386	101	27	to	to	PART
app01-8386	101	28	train	train	VERB
app01-8386	101	29	.	.	PUNCT
app01-8386	102	1	on	on	ADP
app01-8386	102	2	the	the	DET
app01-8386	102	3	other	other	ADJ
app01-8386	102	4	hand	hand	NOUN
app01-8386	102	5	,	,	PUNCT
app01-8386	102	6	the	the	DET
app01-8386	102	7	lack	lack	NOUN
app01-8386	102	8	of	of	ADP
app01-8386	102	9	implicit	implicit	ADJ
app01-8386	102	10	bias	bias	NOUN
app01-8386	102	11	limits	limit	VERB
app01-8386	102	12	their	their	PRON
app01-8386	102	13	expressiveness	expressiveness	NOUN
app01-8386	102	14	and	and	CCONJ
app01-8386	102	15	capability	capability	NOUN
app01-8386	102	16	to	to	PART
app01-8386	102	17	generalise	generalise	VERB
app01-8386	102	18	.	.	PUNCT
app01-8386	103	1	furthermore	furthermore	ADV
app01-8386	103	2	,	,	PUNCT
app01-8386	103	3	they	they	PRON
app01-8386	103	4	are	be	AUX
app01-8386	103	5	prone	prone	ADJ
app01-8386	103	6	to	to	ADP
app01-8386	103	7	pathologies	pathology	NOUN
app01-8386	103	8	like	like	ADP
app01-8386	103	9	vanishing	vanish	VERB
app01-8386	103	10	gradients	gradient	NOUN
app01-8386	103	11	[	[	X
app01-8386	103	12	15	15	NUM
app01-8386	103	13	]	]	PUNCT
app01-8386	103	14	.	.	PUNCT
app01-8386	104	1	we	we	PRON
app01-8386	104	2	therefore	therefore	ADV
app01-8386	104	3	extend	extend	VERB
app01-8386	104	4	the	the	DET
app01-8386	104	5	ffnn	ffnn	NOUN
app01-8386	104	6	by	by	ADP
app01-8386	104	7	adding	add	VERB
app01-8386	104	8	skip	skip	ADJ
app01-8386	104	9	connections	connection	NOUN
app01-8386	104	10	[	[	X
app01-8386	104	11	15	15	NUM
app01-8386	104	12	]	]	PUNCT
app01-8386	104	13	as	as	ADV
app01-8386	104	14	well	well	ADV
app01-8386	104	15	as	as	ADP
app01-8386	104	16	batch	batch	NOUN
app01-8386	104	17	normalisation	normalisation	NOUN
app01-8386	104	18	[	[	X
app01-8386	104	19	16	16	NUM
app01-8386	104	20	]	]	PUNCT
app01-8386	104	21	and	and	CCONJ
app01-8386	104	22	dropout	dropout	NOUN
app01-8386	104	23	[	[	X
app01-8386	104	24	17	17	NUM
app01-8386	104	25	]	]	PUNCT
app01-8386	104	26	,	,	PUNCT
app01-8386	104	27	cf	cf	NOUN
app01-8386	104	28	.	.	PUNCT
app01-8386	104	29	fig	fig	NOUN
app01-8386	104	30	.	.	PUNCT
app01-8386	105	1	3	3	X
app01-8386	105	2	.	.	X
app01-8386	105	3	these	these	DET
app01-8386	105	4	additions	addition	NOUN
app01-8386	105	5	allow	allow	VERB
app01-8386	105	6	us	we	PRON
app01-8386	105	7	to	to	PART
app01-8386	105	8	build	build	VERB
app01-8386	105	9	deeper	deep	ADJ
app01-8386	105	10	architectures	architecture	NOUN
app01-8386	105	11	,	,	PUNCT
app01-8386	105	12	which	which	PRON
app01-8386	105	13	were	be	AUX
app01-8386	105	14	shown	show	VERB
app01-8386	105	15	to	to	PART
app01-8386	105	16	generalise	generalise	VERB
app01-8386	105	17	better	well	ADV
app01-8386	105	18	in	in	ADP
app01-8386	105	19	practice	practice	NOUN
app01-8386	105	20	[	[	X
app01-8386	105	21	18	18	NUM
app01-8386	105	22	]	]	PUNCT
app01-8386	105	23	.	.	PUNCT
app01-8386	106	1	we	we	PRON
app01-8386	106	2	will	will	AUX
app01-8386	106	3	hereafter	hereafter	ADV
app01-8386	106	4	be	be	AUX
app01-8386	106	5	referring	refer	VERB
app01-8386	106	6	to	to	ADP
app01-8386	106	7	this	this	DET
app01-8386	106	8	model	model	NOUN
app01-8386	106	9	by	by	ADP
app01-8386	106	10	resnet	resnet	NOUN
app01-8386	106	11	.	.	PUNCT
app01-8386	107	1	2.4.4	2.4.4	X
app01-8386	107	2	.	.	PUNCT
app01-8386	108	1	hyperparameter	hyperparameter	NOUN
app01-8386	108	2	tuning	tune	VERB
app01-8386	108	3	we	we	PRON
app01-8386	108	4	employ	employ	VERB
app01-8386	108	5	bayesian	bayesian	NOUN
app01-8386	108	6	optimization	optimization	NOUN
app01-8386	108	7	in	in	ADP
app01-8386	108	8	order	order	NOUN
app01-8386	108	9	to	to	PART
app01-8386	108	10	avoid	avoid	VERB
app01-8386	108	11	running	run	VERB
app01-8386	108	12	extensive	extensive	ADJ
app01-8386	108	13	grid	grid	NOUN
app01-8386	108	14	-	-	PUNCT
app01-8386	108	15	search	search	NOUN
app01-8386	108	16	over	over	ADP
app01-8386	108	17	the	the	DET
app01-8386	108	18	entire	entire	ADJ
app01-8386	108	19	hyperparameter	hyperparameter	NOUN
app01-8386	108	20	space	space	NOUN
app01-8386	108	21	[	[	X
app01-8386	108	22	19][20	19][20	X
app01-8386	108	23	]	]	X
app01-8386	108	24	.	.	PUNCT
app01-8386	109	1	at	at	ADP
app01-8386	109	2	first	first	ADV
app01-8386	109	3	,	,	PUNCT
app01-8386	109	4	25	25	NUM
app01-8386	109	5	random	random	ADJ
app01-8386	109	6	points	point	NOUN
app01-8386	109	7	1https://scicomp.ethz.ch/wiki/euler	1https://scicomp.ethz.ch/wiki/euler	NUM
app01-8386	109	8	102	102	NUM
app01-8386	109	9	vol	vol	NOUN
app01-8386	109	10	.	.	PUNCT
app01-8386	110	1	36/2022	36/2022	NUM
app01-8386	110	2	ai	ai	ADJ
app01-8386	110	3	-	-	PUNCT
app01-8386	110	4	fem	fem	NOUN
app01-8386	110	5	-	-	PUNCT
app01-8386	110	6	hybrids	hybrid	NOUN
app01-8386	110	7	for	for	ADP
app01-8386	110	8	nonlinear	nonlinear	ADJ
app01-8386	110	9	concrete	concrete	ADJ
app01-8386	110	10	materials	material	NOUN
app01-8386	110	11	fu	fu	NOUN
app01-8386	110	12	ll	ll	AUX
app01-8386	110	13	yc	yc	VERB
app01-8386	110	14	o	o	PROPN
app01-8386	110	15	n	n	CCONJ
app01-8386	110	16	n	n	ADV
app01-8386	110	17	ec	ec	PROPN
app01-8386	110	18	te	te	PROPN
app01-8386	110	19	d	d	PROPN
app01-8386	110	20	b	b	PROPN
app01-8386	110	21	at	at	ADP
app01-8386	110	22	c	c	PROPN
app01-8386	110	23	h	h	NOUN
app01-8386	111	1	n	n	NOUN
app01-8386	111	2	o	o	NOUN
app01-8386	112	1	r	r	NOUN
app01-8386	112	2	m	m	VERB
app01-8386	112	3	a	a	DET
app01-8386	112	4	li	li	PROPN
app01-8386	112	5	sa	sa	PROPN
app01-8386	112	6	ti	ti	PROPN
app01-8386	112	7	o	o	PROPN
app01-8386	112	8	n	n	PROPN
app01-8386	112	9	d	d	NOUN
app01-8386	112	10	r	r	NOUN
app01-8386	112	11	o	o	X
app01-8386	112	12	po	po	X
app01-8386	112	13	u	u	PROPN
app01-8386	112	14	t	t	PROPN
app01-8386	112	15	fu	fu	NOUN
app01-8386	112	16	ll	ll	AUX
app01-8386	112	17	yc	yc	VERB
app01-8386	112	18	o	o	PROPN
app01-8386	112	19	n	n	CCONJ
app01-8386	112	20	n	n	ADV
app01-8386	112	21	ec	ec	PROPN
app01-8386	113	1	te	te	PROPN
app01-8386	113	2	d	d	PROPN
app01-8386	113	3	+	+	NUM
app01-8386	113	4	figure	figure	NOUN
app01-8386	113	5	3	3	NUM
app01-8386	113	6	.	.	PUNCT
app01-8386	113	7	resnet	resnet	NOUN
app01-8386	113	8	:	:	PUNCT
app01-8386	113	9	neural	neural	ADJ
app01-8386	113	10	network	network	NOUN
app01-8386	113	11	with	with	ADP
app01-8386	113	12	skip	skip	ADJ
app01-8386	113	13	connections	connection	NOUN
app01-8386	113	14	on	on	ADP
app01-8386	113	15	the	the	DET
app01-8386	113	16	hyperparameter	hyperparameter	NOUN
app01-8386	113	17	space	space	NOUN
app01-8386	113	18	are	be	AUX
app01-8386	113	19	evaluated	evaluate	VERB
app01-8386	113	20	.	.	PUNCT
app01-8386	114	1	gaussian	gaussian	ADJ
app01-8386	114	2	processes	process	NOUN
app01-8386	114	3	then	then	ADV
app01-8386	114	4	serve	serve	VERB
app01-8386	114	5	as	as	ADP
app01-8386	114	6	prior	prior	ADJ
app01-8386	114	7	distribution	distribution	NOUN
app01-8386	114	8	in	in	ADP
app01-8386	114	9	order	order	NOUN
app01-8386	114	10	to	to	PART
app01-8386	114	11	approximate	approximate	VERB
app01-8386	114	12	the	the	DET
app01-8386	114	13	unknown	unknown	ADJ
app01-8386	114	14	function	function	NOUN
app01-8386	114	15	and	and	CCONJ
app01-8386	114	16	a	a	DET
app01-8386	114	17	posterior	posterior	ADJ
app01-8386	114	18	distribution	distribution	NOUN
app01-8386	114	19	is	be	AUX
app01-8386	114	20	maintained	maintain	VERB
app01-8386	114	21	as	as	SCONJ
app01-8386	114	22	75	75	NUM
app01-8386	114	23	more	more	ADJ
app01-8386	114	24	observations	observation	NOUN
app01-8386	114	25	are	be	AUX
app01-8386	114	26	made	make	VERB
app01-8386	114	27	,	,	PUNCT
app01-8386	114	28	where	where	SCONJ
app01-8386	114	29	expected	expect	VERB
app01-8386	114	30	improvement	improvement	NOUN
app01-8386	114	31	(	(	PUNCT
app01-8386	114	32	ei	ei	NOUN
app01-8386	114	33	)	)	PUNCT
app01-8386	114	34	is	be	AUX
app01-8386	114	35	used	use	VERB
app01-8386	114	36	as	as	ADP
app01-8386	114	37	exploration	exploration	NOUN
app01-8386	114	38	strategy	strategy	NOUN
app01-8386	114	39	[	[	X
app01-8386	114	40	21	21	NUM
app01-8386	114	41	]	]	PUNCT
app01-8386	114	42	.	.	PUNCT
app01-8386	115	1	the	the	DET
app01-8386	115	2	hyperparameters	hyperparameter	NOUN
app01-8386	115	3	together	together	ADV
app01-8386	115	4	with	with	ADP
app01-8386	115	5	optimization	optimization	NOUN
app01-8386	115	6	intervals	interval	NOUN
app01-8386	115	7	are	be	AUX
app01-8386	115	8	reported	report	VERB
app01-8386	115	9	in	in	ADP
app01-8386	115	10	tabs	tab	NOUN
app01-8386	115	11	.	.	PUNCT
app01-8386	116	1	2	2	NUM
app01-8386	116	2	,	,	PUNCT
app01-8386	116	3	3	3	NUM
app01-8386	116	4	,	,	PUNCT
app01-8386	116	5	and	and	CCONJ
app01-8386	116	6	4	4	X
app01-8386	116	7	.	.	NOUN
app01-8386	116	8	hyperparameter	hyperparameter	NOUN
app01-8386	116	9	range	range	NOUN
app01-8386	116	10	number	number	NOUN
app01-8386	116	11	of	of	ADP
app01-8386	116	12	neighbours	neighbour	NOUN
app01-8386	116	13	k	k	PROPN
app01-8386	117	1	[	[	X
app01-8386	117	2	1	1	NUM
app01-8386	117	3	,	,	PUNCT
app01-8386	117	4	10	10	NUM
app01-8386	117	5	]	]	SYM
app01-8386	117	6	power	power	NOUN
app01-8386	117	7	of	of	ADP
app01-8386	117	8	minkowski	minkowski	ADJ
app01-8386	117	9	metric	metric	ADJ
app01-8386	117	10	p	p	X
app01-8386	118	1	[	[	X
app01-8386	118	2	1	1	NUM
app01-8386	118	3	,	,	PUNCT
app01-8386	118	4	3	3	NUM
app01-8386	118	5	]	]	ADJ
app01-8386	118	6	table	table	NOUN
app01-8386	118	7	2	2	NUM
app01-8386	118	8	.	.	PUNCT
app01-8386	118	9	hyperparameters	hyperparameter	NOUN
app01-8386	118	10	for	for	ADP
app01-8386	118	11	training	training	NOUN
app01-8386	118	12	settings	setting	NOUN
app01-8386	118	13	together	together	ADV
app01-8386	118	14	with	with	ADP
app01-8386	118	15	ranges	range	NOUN
app01-8386	118	16	as	as	SCONJ
app01-8386	118	17	used	use	VERB
app01-8386	118	18	for	for	ADP
app01-8386	118	19	bayesian	bayesian	NOUN
app01-8386	118	20	optimisation	optimisation	NOUN
app01-8386	118	21	of	of	ADP
app01-8386	118	22	knn	knn	PROPN
app01-8386	118	23	hyperparameter	hyperparameter	PROPN
app01-8386	118	24	range	range	PROPN
app01-8386	118	25	log	log	NOUN
app01-8386	118	26	-	-	PUNCT
app01-8386	118	27	scaling	scale	VERB
app01-8386	118	28	learning	learning	NOUN
app01-8386	118	29	rate	rate	NOUN
app01-8386	119	1	[	[	X
app01-8386	119	2	10−5	10−5	NUM
app01-8386	119	3	,	,	PUNCT
app01-8386	119	4	10−1	10−1	NUM
app01-8386	119	5	]	]	X
app01-8386	120	1	yes	yes	INTJ
app01-8386	120	2	max	max	NOUN
app01-8386	120	3	depth	depth	NOUN
app01-8386	120	4	[	[	X
app01-8386	120	5	3	3	NUM
app01-8386	120	6	,	,	PUNCT
app01-8386	120	7	50	50	NUM
app01-8386	120	8	]	]	PUNCT
app01-8386	120	9	no	no	DET
app01-8386	120	10	min	min	NOUN
app01-8386	120	11	child	child	NOUN
app01-8386	120	12	weight	weight	NOUN
app01-8386	120	13	[	[	X
app01-8386	120	14	0	0	NUM
app01-8386	120	15	,	,	PUNCT
app01-8386	120	16	10	10	NUM
app01-8386	120	17	]	]	PUNCT
app01-8386	120	18	no	no	DET
app01-8386	120	19	number	number	NOUN
app01-8386	120	20	estimators	estimator	NOUN
app01-8386	120	21	[	[	X
app01-8386	120	22	30	30	NUM
app01-8386	120	23	,	,	PUNCT
app01-8386	120	24	300	300	NUM
app01-8386	120	25	]	]	PUNCT
app01-8386	120	26	no	no	DET
app01-8386	120	27	number	number	NOUN
app01-8386	120	28	leaves	leave	VERB
app01-8386	120	29	[	[	X
app01-8386	120	30	10	10	NUM
app01-8386	120	31	,	,	PUNCT
app01-8386	120	32	100	100	NUM
app01-8386	120	33	]	]	PUNCT
app01-8386	120	34	no	no	DET
app01-8386	120	35	min	min	NOUN
app01-8386	120	36	child	child	NOUN
app01-8386	120	37	samples	sample	NOUN
app01-8386	120	38	[	[	X
app01-8386	120	39	10	10	NUM
app01-8386	120	40	,	,	PUNCT
app01-8386	120	41	30	30	NUM
app01-8386	120	42	]	]	PUNCT
app01-8386	120	43	no	no	DET
app01-8386	120	44	table	table	NOUN
app01-8386	120	45	3	3	NUM
app01-8386	120	46	.	.	PUNCT
app01-8386	120	47	hyperparameters	hyperparameter	NOUN
app01-8386	120	48	for	for	ADP
app01-8386	120	49	training	training	NOUN
app01-8386	120	50	settings	setting	NOUN
app01-8386	120	51	together	together	ADV
app01-8386	120	52	with	with	ADP
app01-8386	120	53	ranges	range	NOUN
app01-8386	120	54	as	as	SCONJ
app01-8386	120	55	used	use	VERB
app01-8386	120	56	for	for	ADP
app01-8386	120	57	bayesian	bayesian	NOUN
app01-8386	120	58	optimisation	optimisation	NOUN
app01-8386	120	59	of	of	ADP
app01-8386	120	60	lightgbm	lightgbm	ADJ
app01-8386	120	61	hyperparameter	hyperparameter	NOUN
app01-8386	120	62	range	range	NOUN
app01-8386	120	63	log	log	NOUN
app01-8386	120	64	-	-	PUNCT
app01-8386	120	65	scaling	scale	VERB
app01-8386	120	66	learning	learning	NOUN
app01-8386	120	67	rate	rate	NOUN
app01-8386	121	1	[	[	X
app01-8386	121	2	10−5	10−5	NUM
app01-8386	121	3	,	,	PUNCT
app01-8386	121	4	10−1	10−1	NUM
app01-8386	121	5	]	]	X
app01-8386	122	1	yes	yes	INTJ
app01-8386	122	2	depth	depth	NOUN
app01-8386	123	1	[	[	X
app01-8386	123	2	3	3	NUM
app01-8386	123	3	,	,	PUNCT
app01-8386	123	4	50	50	NUM
app01-8386	123	5	]	]	PUNCT
app01-8386	123	6	no	no	DET
app01-8386	123	7	width	width	ADJ
app01-8386	124	1	[	[	X
app01-8386	124	2	0	0	NUM
app01-8386	124	3	,	,	PUNCT
app01-8386	124	4	10	10	NUM
app01-8386	124	5	]	]	PUNCT
app01-8386	124	6	no	no	DET
app01-8386	124	7	activation	activation	NOUN
app01-8386	124	8	{	{	PUNCT
app01-8386	124	9	relu	relu	NOUN
app01-8386	124	10	,	,	PUNCT
app01-8386	124	11	no	no	DET
app01-8386	124	12	leakyrelu	leakyrelu	NOUN
app01-8386	124	13	}	}	PUNCT
app01-8386	124	14	table	table	NOUN
app01-8386	124	15	4	4	NUM
app01-8386	124	16	.	.	PUNCT
app01-8386	124	17	hyperparameters	hyperparameter	NOUN
app01-8386	124	18	for	for	ADP
app01-8386	124	19	training	training	NOUN
app01-8386	124	20	settings	setting	NOUN
app01-8386	124	21	together	together	ADV
app01-8386	124	22	with	with	ADP
app01-8386	124	23	ranges	range	NOUN
app01-8386	124	24	for	for	ADP
app01-8386	124	25	bayesian	bayesian	NOUN
app01-8386	124	26	optimisation	optimisation	NOUN
app01-8386	124	27	of	of	ADP
app01-8386	124	28	resnets	resnet	NOUN
app01-8386	124	29	for	for	ADP
app01-8386	124	30	the	the	DET
app01-8386	124	31	optimization	optimization	NOUN
app01-8386	124	32	procedure	procedure	NOUN
app01-8386	124	33	,	,	PUNCT
app01-8386	124	34	we	we	PRON
app01-8386	124	35	split	split	VERB
app01-8386	124	36	the	the	DET
app01-8386	124	37	dataset	dataset	NOUN
app01-8386	124	38	into	into	ADP
app01-8386	124	39	a	a	DET
app01-8386	124	40	training	training	NOUN
app01-8386	124	41	,	,	PUNCT
app01-8386	124	42	validation	validation	NOUN
app01-8386	124	43	and	and	CCONJ
app01-8386	124	44	test	test	NOUN
app01-8386	124	45	set	set	VERB
app01-8386	124	46	at	at	ADP
app01-8386	124	47	ratios	ratio	NOUN
app01-8386	124	48	of	of	ADP
app01-8386	124	49	(	(	PUNCT
app01-8386	124	50	50	50	NUM
app01-8386	124	51	;	;	PUNCT
app01-8386	124	52	25	25	NUM
app01-8386	124	53	;	;	PUNCT
app01-8386	124	54	25)%	25)%	NUM
app01-8386	124	55	of	of	ADP
app01-8386	124	56	the	the	DET
app01-8386	124	57	whole	whole	ADJ
app01-8386	124	58	dataset	dataset	NOUN
app01-8386	124	59	.	.	PUNCT
app01-8386	125	1	the	the	DET
app01-8386	125	2	regressor	regressor	NOUN
app01-8386	125	3	is	be	AUX
app01-8386	125	4	trained	train	VERB
app01-8386	125	5	on	on	ADP
app01-8386	125	6	the	the	DET
app01-8386	125	7	training	training	NOUN
app01-8386	125	8	set	set	NOUN
app01-8386	125	9	using	use	VERB
app01-8386	125	10	the	the	DET
app01-8386	125	11	hyperparameters	hyperparameter	NOUN
app01-8386	125	12	chosen	choose	VERB
app01-8386	125	13	by	by	ADP
app01-8386	125	14	the	the	DET
app01-8386	125	15	bayesian	bayesian	NOUN
app01-8386	125	16	optimization	optimization	NOUN
app01-8386	125	17	algorithm	algorithm	NOUN
app01-8386	125	18	.	.	PUNCT
app01-8386	126	1	once	once	SCONJ
app01-8386	126	2	the	the	DET
app01-8386	126	3	model	model	NOUN
app01-8386	126	4	loss	loss	NOUN
app01-8386	126	5	converged	converge	VERB
app01-8386	126	6	,	,	PUNCT
app01-8386	126	7	it	it	PRON
app01-8386	126	8	is	be	AUX
app01-8386	126	9	evaluated	evaluate	VERB
app01-8386	126	10	on	on	ADP
app01-8386	126	11	the	the	DET
app01-8386	126	12	validation	validation	NOUN
app01-8386	126	13	data	datum	NOUN
app01-8386	126	14	set	set	VERB
app01-8386	126	15	and	and	CCONJ
app01-8386	126	16	the	the	DET
app01-8386	126	17	result	result	NOUN
app01-8386	126	18	serves	serve	VERB
app01-8386	126	19	as	as	ADP
app01-8386	126	20	feedback	feedback	NOUN
app01-8386	126	21	for	for	ADP
app01-8386	126	22	the	the	DET
app01-8386	126	23	bayesian	bayesian	NOUN
app01-8386	126	24	optimization	optimization	NOUN
app01-8386	126	25	step	step	NOUN
app01-8386	126	26	to	to	PART
app01-8386	126	27	refine	refine	VERB
app01-8386	126	28	its	its	PRON
app01-8386	126	29	posterior	posterior	ADJ
app01-8386	126	30	and	and	CCONJ
app01-8386	126	31	select	select	VERB
app01-8386	126	32	new	new	ADJ
app01-8386	126	33	hyperparameters	hyperparameter	NOUN
app01-8386	126	34	.	.	PUNCT
app01-8386	127	1	finally	finally	ADV
app01-8386	127	2	,	,	PUNCT
app01-8386	127	3	the	the	DET
app01-8386	127	4	test	test	NOUN
app01-8386	127	5	set	set	NOUN
app01-8386	127	6	is	be	AUX
app01-8386	127	7	used	use	VERB
app01-8386	127	8	to	to	PART
app01-8386	127	9	estimate	estimate	VERB
app01-8386	127	10	the	the	DET
app01-8386	127	11	model	model	NOUN
app01-8386	127	12	’s	’s	PART
app01-8386	127	13	capability	capability	NOUN
app01-8386	127	14	of	of	ADP
app01-8386	127	15	generalizing	generalize	VERB
app01-8386	127	16	.	.	PUNCT
app01-8386	128	1	2.4.5	2.4.5	NUM
app01-8386	128	2	.	.	PUNCT
app01-8386	128	3	model	model	NOUN
app01-8386	128	4	quantitative	quantitative	ADJ
app01-8386	128	5	performance	performance	NOUN
app01-8386	128	6	metrics	metric	NOUN
app01-8386	128	7	and	and	CCONJ
app01-8386	128	8	ai	ai	VERB
app01-8386	128	9	surrogate	surrogate	ADJ
app01-8386	128	10	model	model	NOUN
app01-8386	128	11	selection	selection	NOUN
app01-8386	128	12	model	model	NOUN
app01-8386	128	13	selection	selection	NOUN
app01-8386	128	14	refers	refer	VERB
app01-8386	128	15	to	to	ADP
app01-8386	128	16	the	the	DET
app01-8386	128	17	process	process	NOUN
app01-8386	128	18	of	of	ADP
app01-8386	128	19	seeking	seek	VERB
app01-8386	128	20	for	for	ADP
app01-8386	128	21	a	a	DET
app01-8386	128	22	model	model	NOUN
app01-8386	128	23	in	in	ADP
app01-8386	128	24	a	a	DET
app01-8386	128	25	set	set	NOUN
app01-8386	128	26	of	of	ADP
app01-8386	128	27	candidate	candidate	NOUN
app01-8386	128	28	models	model	NOUN
app01-8386	128	29	,	,	PUNCT
app01-8386	128	30	which	which	PRON
app01-8386	128	31	delivers	deliver	VERB
app01-8386	128	32	the	the	DET
app01-8386	128	33	best	good	ADJ
app01-8386	128	34	balance	balance	NOUN
app01-8386	128	35	between	between	ADP
app01-8386	128	36	model	model	NOUN
app01-8386	128	37	fit	fit	ADJ
app01-8386	128	38	and	and	CCONJ
app01-8386	128	39	complexity	complexity	NOUN
app01-8386	129	1	[	[	X
app01-8386	129	2	22	22	NUM
app01-8386	129	3	]	]	PUNCT
app01-8386	129	4	.	.	PUNCT
app01-8386	130	1	for	for	ADP
app01-8386	130	2	regression	regression	NOUN
app01-8386	130	3	modeling	modeling	NOUN
app01-8386	130	4	,	,	PUNCT
app01-8386	130	5	the	the	DET
app01-8386	130	6	quantitative	quantitative	ADJ
app01-8386	130	7	performance	performance	NOUN
app01-8386	130	8	metrics	metric	NOUN
app01-8386	130	9	used	use	VERB
app01-8386	130	10	with	with	ADP
app01-8386	130	11	this	this	DET
app01-8386	130	12	research	research	NOUN
app01-8386	130	13	are	be	AUX
app01-8386	130	14	the	the	DET
app01-8386	130	15	mean	mean	ADJ
app01-8386	130	16	absolute	absolute	ADJ
app01-8386	130	17	error	error	NOUN
app01-8386	130	18	(	(	PUNCT
app01-8386	130	19	mae	mae	PROPN
app01-8386	130	20	)	)	PUNCT
app01-8386	130	21	,	,	PUNCT
app01-8386	130	22	root	root	NOUN
app01-8386	130	23	mean	mean	VERB
app01-8386	130	24	squared	square	VERB
app01-8386	130	25	error	error	NOUN
app01-8386	130	26	(	(	PUNCT
app01-8386	130	27	rmse	rmse	NOUN
app01-8386	130	28	)	)	PUNCT
app01-8386	130	29	,	,	PUNCT
app01-8386	130	30	rsquared	rsquare	VERB
app01-8386	130	31	(	(	PUNCT
app01-8386	130	32	r2	r2	PROPN
app01-8386	130	33	)	)	PUNCT
app01-8386	130	34	value	value	NOUN
app01-8386	130	35	as	as	ADV
app01-8386	130	36	well	well	ADV
app01-8386	130	37	as	as	ADP
app01-8386	130	38	the	the	DET
app01-8386	130	39	data	data	NOUN
app01-8386	130	40	variance	variance	NOUN
app01-8386	130	41	v	v	PROPN
app01-8386	130	42	ar	ar	PROPN
app01-8386	130	43	(	(	PUNCT
app01-8386	130	44	which	which	PRON
app01-8386	130	45	is	be	AUX
app01-8386	130	46	the	the	DET
app01-8386	130	47	square	square	NOUN
app01-8386	130	48	of	of	ADP
app01-8386	130	49	the	the	DET
app01-8386	130	50	standard	standard	ADJ
app01-8386	130	51	deviation	deviation	NOUN
app01-8386	130	52	(	(	PUNCT
app01-8386	130	53	sd	sd	NOUN
app01-8386	130	54	)	)	PUNCT
app01-8386	130	55	)	)	PUNCT
app01-8386	130	56	,	,	PUNCT
app01-8386	130	57	cf	cf	NOUN
app01-8386	130	58	.	.	PUNCT
app01-8386	130	59	tab	tab	NOUN
app01-8386	130	60	.	.	PUNCT
app01-8386	131	1	5	5	NUM
app01-8386	131	2	.	.	PUNCT
app01-8386	131	3	the	the	DET
app01-8386	131	4	mae	mae	PROPN
app01-8386	131	5	shows	show	VERB
app01-8386	131	6	the	the	DET
app01-8386	131	7	average	average	ADJ
app01-8386	131	8	difference	difference	NOUN
app01-8386	131	9	between	between	ADP
app01-8386	131	10	the	the	DET
app01-8386	131	11	actual	actual	ADJ
app01-8386	131	12	values	value	NOUN
app01-8386	131	13	of	of	ADP
app01-8386	131	14	the	the	DET
app01-8386	131	15	output	output	NOUN
app01-8386	131	16	variable	variable	NOUN
app01-8386	131	17	in	in	ADP
app01-8386	131	18	the	the	DET
app01-8386	131	19	original	original	ADJ
app01-8386	131	20	data	datum	NOUN
app01-8386	131	21	vs.	vs.	ADP
app01-8386	131	22	the	the	DET
app01-8386	131	23	predicted	predict	VERB
app01-8386	131	24	output	output	NOUN
app01-8386	131	25	values	value	NOUN
app01-8386	131	26	via	via	ADP
app01-8386	131	27	the	the	DET
app01-8386	131	28	ml	ml	PROPN
app01-8386	131	29	models	model	NOUN
app01-8386	131	30	.	.	PUNCT
app01-8386	132	1	the	the	PRON
app01-8386	132	2	lower	low	ADJ
app01-8386	132	3	the	the	DET
app01-8386	132	4	mae	mae	PROPN
app01-8386	132	5	,	,	PUNCT
app01-8386	132	6	the	the	PRON
app01-8386	132	7	more	more	ADV
app01-8386	132	8	precise	precise	ADJ
app01-8386	132	9	the	the	DET
app01-8386	132	10	performance	performance	NOUN
app01-8386	132	11	of	of	ADP
app01-8386	132	12	the	the	DET
app01-8386	132	13	model	model	NOUN
app01-8386	132	14	is	be	AUX
app01-8386	132	15	in	in	ADP
app01-8386	132	16	predicting	predict	VERB
app01-8386	132	17	future	future	ADJ
app01-8386	132	18	occurrences	occurrence	NOUN
app01-8386	132	19	of	of	ADP
app01-8386	132	20	the	the	DET
app01-8386	132	21	output	output	NOUN
app01-8386	132	22	.	.	PUNCT
app01-8386	133	1	the	the	DET
app01-8386	133	2	rmse	rmse	NOUN
app01-8386	133	3	is	be	AUX
app01-8386	133	4	defined	define	VERB
app01-8386	133	5	as	as	ADP
app01-8386	133	6	the	the	DET
app01-8386	133	7	standard	standard	ADJ
app01-8386	133	8	deviation	deviation	NOUN
app01-8386	133	9	of	of	ADP
app01-8386	133	10	the	the	DET
app01-8386	133	11	response	response	NOUN
app01-8386	133	12	variable	variable	NOUN
app01-8386	133	13	.	.	PUNCT
app01-8386	134	1	values	value	NOUN
app01-8386	134	2	of	of	ADP
app01-8386	134	3	r2	r2	PROPN
app01-8386	134	4	range	range	VERB
app01-8386	134	5	from	from	ADP
app01-8386	134	6	0	0	NUM
app01-8386	134	7	to	to	ADP
app01-8386	134	8	1	1	NUM
app01-8386	134	9	,	,	PUNCT
app01-8386	134	10	where	where	SCONJ
app01-8386	134	11	1	1	NUM
app01-8386	134	12	is	be	AUX
app01-8386	134	13	a	a	DET
app01-8386	134	14	perfect	perfect	ADJ
app01-8386	134	15	fit	fit	NOUN
app01-8386	134	16	,	,	PUNCT
app01-8386	134	17	and	and	CCONJ
app01-8386	134	18	0	0	NUM
app01-8386	134	19	means	mean	VERB
app01-8386	134	20	there	there	PRON
app01-8386	134	21	is	be	VERB
app01-8386	134	22	no	no	DET
app01-8386	134	23	gain	gain	NOUN
app01-8386	134	24	by	by	ADP
app01-8386	134	25	using	use	VERB
app01-8386	134	26	the	the	DET
app01-8386	134	27	model	model	NOUN
app01-8386	134	28	over	over	ADP
app01-8386	134	29	using	use	VERB
app01-8386	134	30	fixed	fix	VERB
app01-8386	134	31	background	background	NOUN
app01-8386	134	32	response	response	NOUN
app01-8386	134	33	rates	rate	NOUN
app01-8386	134	34	.	.	PUNCT
app01-8386	135	1	it	it	PRON
app01-8386	135	2	estimates	estimate	VERB
app01-8386	135	3	the	the	DET
app01-8386	135	4	proportion	proportion	NOUN
app01-8386	135	5	of	of	ADP
app01-8386	135	6	the	the	DET
app01-8386	135	7	variation	variation	NOUN
app01-8386	135	8	in	in	ADP
app01-8386	135	9	the	the	DET
app01-8386	135	10	response	response	NOUN
app01-8386	135	11	around	around	ADP
app01-8386	135	12	the	the	DET
app01-8386	135	13	mean	mean	NOUN
app01-8386	135	14	that	that	PRON
app01-8386	135	15	can	can	AUX
app01-8386	135	16	be	be	AUX
app01-8386	135	17	attributed	attribute	VERB
app01-8386	135	18	to	to	ADP
app01-8386	135	19	terms	term	NOUN
app01-8386	135	20	in	in	ADP
app01-8386	135	21	the	the	DET
app01-8386	135	22	model	model	NOUN
app01-8386	135	23	rather	rather	ADV
app01-8386	135	24	than	than	ADP
app01-8386	135	25	to	to	ADP
app01-8386	135	26	random	random	ADJ
app01-8386	135	27	error	error	NOUN
app01-8386	135	28	.	.	PUNCT
app01-8386	136	1	for	for	ADP
app01-8386	136	2	comparing	compare	VERB
app01-8386	136	3	different	different	ADJ
app01-8386	136	4	models	model	NOUN
app01-8386	136	5	,	,	PUNCT
app01-8386	136	6	we	we	PRON
app01-8386	136	7	provide	provide	VERB
app01-8386	136	8	taylor	taylor	PROPN
app01-8386	136	9	diagrams	diagram	NOUN
app01-8386	136	10	[	[	X
app01-8386	136	11	23	23	NUM
app01-8386	136	12	]	]	PUNCT
app01-8386	136	13	and	and	CCONJ
app01-8386	136	14	additionally	additionally	ADV
app01-8386	136	15	report	report	VERB
app01-8386	136	16	r2	r2	NOUN
app01-8386	136	17	,	,	PUNCT
app01-8386	136	18	rmse	rmse	NOUN
app01-8386	136	19	and	and	CCONJ
app01-8386	136	20	mae	mae	PROPN
app01-8386	136	21	values	value	NOUN
app01-8386	136	22	.	.	PUNCT
app01-8386	137	1	taylor	taylor	PROPN
app01-8386	137	2	diagrams	diagram	NOUN
app01-8386	137	3	are	be	AUX
app01-8386	137	4	used	use	VERB
app01-8386	137	5	to	to	PART
app01-8386	137	6	quantify	quantify	VERB
app01-8386	137	7	the	the	DET
app01-8386	137	8	degree	degree	NOUN
app01-8386	137	9	of	of	ADP
app01-8386	137	10	correspondence	correspondence	NOUN
app01-8386	137	11	between	between	ADP
app01-8386	137	12	the	the	DET
app01-8386	137	13	modeled	model	VERB
app01-8386	137	14	and	and	CCONJ
app01-8386	137	15	observed	observed	ADJ
app01-8386	137	16	data	datum	NOUN
app01-8386	137	17	using	use	VERB
app01-8386	137	18	the	the	DET
app01-8386	137	19	pearson	pearson	PROPN
app01-8386	137	20	correlation	correlation	NOUN
app01-8386	137	21	coefficient	coefficient	NOUN
app01-8386	137	22	,	,	PUNCT
app01-8386	137	23	rmse	rmse	NOUN
app01-8386	137	24	,	,	PUNCT
app01-8386	137	25	and	and	CCONJ
app01-8386	137	26	standard	standard	ADJ
app01-8386	137	27	deviation	deviation	NOUN
app01-8386	137	28	.	.	PUNCT
app01-8386	138	1	a	a	DET
app01-8386	138	2	model	model	NOUN
app01-8386	138	3	with	with	ADP
app01-8386	138	4	the	the	DET
app01-8386	138	5	highest	high	ADJ
app01-8386	138	6	r2	r2	NOUN
app01-8386	138	7	and	and	CCONJ
app01-8386	138	8	the	the	DET
app01-8386	138	9	lowest	low	ADJ
app01-8386	138	10	rmse	rmse	NOUN
app01-8386	138	11	and	and	CCONJ
app01-8386	138	12	mae	mae	PROPN
app01-8386	138	13	is	be	AUX
app01-8386	138	14	preferred	prefer	VERB
app01-8386	138	15	.	.	PUNCT
app01-8386	139	1	the	the	DET
app01-8386	139	2	details	detail	NOUN
app01-8386	139	3	of	of	ADP
app01-8386	139	4	how	how	SCONJ
app01-8386	139	5	mae	mae	PROPN
app01-8386	139	6	,	,	PUNCT
app01-8386	139	7	rmse	rmse	NOUN
app01-8386	139	8	,	,	PUNCT
app01-8386	139	9	and	and	CCONJ
app01-8386	139	10	r2	r2	PROPN
app01-8386	139	11	are	be	AUX
app01-8386	139	12	calculated	calculate	VERB
app01-8386	139	13	are	be	AUX
app01-8386	139	14	shown	show	VERB
app01-8386	139	15	in	in	ADP
app01-8386	139	16	tab	tab	NOUN
app01-8386	139	17	.	.	PUNCT
app01-8386	140	1	5	5	NUM
app01-8386	140	2	.	.	X
app01-8386	140	3	mae	mae	PROPN
app01-8386	140	4	1	1	PROPN
app01-8386	140	5	n	n	PROPN
app01-8386	140	6	∑n	∑n	PROPN
app01-8386	140	7	i=1	i=1	PROPN
app01-8386	140	8	|ŷi	|ŷi	ADJ
app01-8386	140	9	−	−	PROPN
app01-8386	140	10	yi|	yi|	PROPN
app01-8386	140	11	rmse	rmse	VERB
app01-8386	140	12	√	√	VERB
app01-8386	140	13	1	1	NUM
app01-8386	140	14	n	n	NOUN
app01-8386	141	1	∑n	∑n	PROPN
app01-8386	141	2	i=1(ŷi	i=1(ŷi	PROPN
app01-8386	141	3	−	−	PROPN
app01-8386	141	4	yi)2	yi)2	PROPN
app01-8386	141	5	r2	r2	PROPN
app01-8386	141	6	1	1	NUM
app01-8386	142	1	−	−	PROPN
app01-8386	142	2	∑n	∑n	PROPN
app01-8386	142	3	i=1	i=1	PROPN
app01-8386	142	4	(	(	PUNCT
app01-8386	142	5	ŷi−yi)2∑n	ŷi−yi)2∑n	NOUN
app01-8386	142	6	i=1	i=1	X
app01-8386	142	7	(	(	PUNCT
app01-8386	142	8	ŷi−ȳ)2	ŷi−ȳ)2	INTJ
app01-8386	142	9	,	,	PUNCT
app01-8386	142	10	ȳ	ȳ	PROPN
app01-8386	142	11	=	=	SYM
app01-8386	142	12	1	1	NUM
app01-8386	142	13	n	n	NOUN
app01-8386	142	14	∑n	∑n	PROPN
app01-8386	142	15	i=1	i=1	PROPN
app01-8386	142	16	|yi|	|yi|	PROPN
app01-8386	142	17	table	table	NOUN
app01-8386	142	18	5	5	NUM
app01-8386	142	19	.	.	PUNCT
app01-8386	143	1	regression	regression	NOUN
app01-8386	143	2	performance	performance	NOUN
app01-8386	143	3	evaluation	evaluation	NOUN
app01-8386	143	4	metrics	metric	NOUN
app01-8386	143	5	.	.	PUNCT
app01-8386	144	1	where	where	SCONJ
app01-8386	144	2	n	n	PRON
app01-8386	144	3	is	be	AUX
app01-8386	144	4	the	the	DET
app01-8386	144	5	sample	sample	NOUN
app01-8386	144	6	size	size	NOUN
app01-8386	144	7	,	,	PUNCT
app01-8386	144	8	ŷi	ŷi	PROPN
app01-8386	144	9	is	be	AUX
app01-8386	144	10	the	the	DET
app01-8386	144	11	predicted	predict	VERB
app01-8386	144	12	and	and	CCONJ
app01-8386	144	13	yi	yi	PROPN
app01-8386	144	14	is	be	AUX
app01-8386	144	15	the	the	DET
app01-8386	144	16	true	true	ADJ
app01-8386	144	17	target	target	NOUN
app01-8386	144	18	value	value	NOUN
app01-8386	144	19	,	,	PUNCT
app01-8386	144	20	sse	sse	PROPN
app01-8386	144	21	is	be	AUX
app01-8386	144	22	the	the	DET
app01-8386	144	23	sum	sum	NOUN
app01-8386	144	24	of	of	ADP
app01-8386	144	25	the	the	DET
app01-8386	144	26	square	square	NOUN
app01-8386	144	27	of	of	ADP
app01-8386	144	28	error	error	NOUN
app01-8386	144	29	and	and	CCONJ
app01-8386	144	30	sst	sst	NOUN
app01-8386	144	31	is	be	AUX
app01-8386	144	32	the	the	DET
app01-8386	144	33	total	total	ADJ
app01-8386	144	34	sum	sum	NOUN
app01-8386	144	35	of	of	ADP
app01-8386	144	36	squares	square	NOUN
app01-8386	144	37	.	.	PUNCT
app01-8386	145	1	3	3	X
app01-8386	145	2	.	.	X
app01-8386	145	3	results	result	NOUN
app01-8386	145	4	this	this	DET
app01-8386	145	5	section	section	NOUN
app01-8386	145	6	describes	describe	VERB
app01-8386	145	7	the	the	DET
app01-8386	145	8	results	result	NOUN
app01-8386	145	9	obtained	obtain	VERB
app01-8386	145	10	with	with	ADP
app01-8386	145	11	knn	knn	PROPN
app01-8386	145	12	,	,	PUNCT
app01-8386	145	13	lightgbm	lightgbm	ADJ
app01-8386	145	14	,	,	PUNCT
app01-8386	145	15	and	and	CCONJ
app01-8386	145	16	resnet	resnet	VERB
app01-8386	145	17	and	and	CCONJ
app01-8386	145	18	evaluates	evaluate	VERB
app01-8386	145	19	their	their	PRON
app01-8386	145	20	performance	performance	NOUN
app01-8386	145	21	as	as	ADP
app01-8386	145	22	a	a	DET
app01-8386	145	23	surrogate	surrogate	NOUN
app01-8386	145	24	for	for	SCONJ
app01-8386	145	25	the	the	DET
app01-8386	145	26	fem	fem	NOUN
app01-8386	145	27	data	datum	NOUN
app01-8386	145	28	generated	generate	VERB
app01-8386	145	29	and	and	CCONJ
app01-8386	145	30	used	use	VERB
app01-8386	145	31	within	within	ADP
app01-8386	145	32	this	this	DET
app01-8386	145	33	study	study	NOUN
app01-8386	145	34	,	,	PUNCT
app01-8386	145	35	cf	cf	NOUN
app01-8386	145	36	.	.	PUNCT
app01-8386	146	1	sec	sec	PROPN
app01-8386	146	2	.	.	PROPN
app01-8386	146	3	2.3	2.3	NUM
app01-8386	146	4	.	.	PUNCT
app01-8386	147	1	all	all	DET
app01-8386	147	2	three	three	NUM
app01-8386	147	3	ml	ml	NOUN
app01-8386	147	4	models	model	NOUN
app01-8386	147	5	were	be	AUX
app01-8386	147	6	trained	train	VERB
app01-8386	147	7	,	,	PUNCT
app01-8386	147	8	validated	validate	VERB
app01-8386	147	9	and	and	CCONJ
app01-8386	147	10	tested	test	VERB
app01-8386	147	11	using	use	VERB
app01-8386	147	12	the	the	DET
app01-8386	147	13	data	datum	NOUN
app01-8386	147	14	from	from	ADP
app01-8386	147	15	the	the	DET
app01-8386	147	16	total	total	NOUN
app01-8386	147	17	of	of	ADP
app01-8386	147	18	12	12	NUM
app01-8386	147	19	million	million	NUM
app01-8386	147	20	103	103	NUM
app01-8386	147	21	m.	m.	NOUN
app01-8386	147	22	a.	a.	PROPN
app01-8386	147	23	kraus	kraus	PROPN
app01-8386	147	24	,	,	PUNCT
app01-8386	147	25	r.	r.	PROPN
app01-8386	147	26	bischof	bischof	PROPN
app01-8386	147	27	,	,	PUNCT
app01-8386	147	28	w.	w.	PROPN
app01-8386	147	29	kaufmann	kaufmann	PROPN
app01-8386	147	30	,	,	PUNCT
app01-8386	147	31	k.	k.	PROPN
app01-8386	147	32	thoma	thoma	PROPN
app01-8386	147	33	acta	acta	PROPN
app01-8386	147	34	polytechnica	polytechnica	PROPN
app01-8386	147	35	ctu	ctu	PROPN
app01-8386	147	36	proceedings	proceeding	NOUN
app01-8386	147	37	data	datum	NOUN
app01-8386	147	38	points	point	NOUN
app01-8386	147	39	.	.	PUNCT
app01-8386	148	1	comparing	compare	VERB
app01-8386	148	2	the	the	DET
app01-8386	148	3	r2	r2	PROPN
app01-8386	148	4	values	value	NOUN
app01-8386	148	5	,	,	PUNCT
app01-8386	148	6	all	all	DET
app01-8386	148	7	models	model	NOUN
app01-8386	148	8	have	have	VERB
app01-8386	148	9	high	high	ADJ
app01-8386	148	10	values	value	NOUN
app01-8386	148	11	of	of	ADP
app01-8386	148	12	around	around	ADP
app01-8386	148	13	0.98	0.98	NUM
app01-8386	148	14	.	.	PUNCT
app01-8386	149	1	this	this	PRON
app01-8386	149	2	indicates	indicate	VERB
app01-8386	149	3	that	that	SCONJ
app01-8386	149	4	the	the	DET
app01-8386	149	5	ml	ml	NOUN
app01-8386	149	6	algorithms	algorithm	NOUN
app01-8386	149	7	are	be	AUX
app01-8386	149	8	able	able	ADJ
app01-8386	149	9	to	to	PART
app01-8386	149	10	describe	describe	VERB
app01-8386	149	11	over	over	ADP
app01-8386	149	12	98	98	NUM
app01-8386	149	13	%	%	NOUN
app01-8386	149	14	of	of	ADP
app01-8386	149	15	variations	variation	NOUN
app01-8386	149	16	in	in	ADP
app01-8386	149	17	the	the	DET
app01-8386	149	18	data	datum	NOUN
app01-8386	149	19	,	,	PUNCT
app01-8386	149	20	and	and	CCONJ
app01-8386	149	21	are	be	AUX
app01-8386	149	22	highly	highly	ADV
app01-8386	149	23	predictive	predictive	ADJ
app01-8386	149	24	of	of	ADP
app01-8386	149	25	the	the	DET
app01-8386	149	26	output	output	NOUN
app01-8386	149	27	based	base	VERB
app01-8386	149	28	on	on	ADP
app01-8386	149	29	the	the	DET
app01-8386	149	30	feature	feature	NOUN
app01-8386	149	31	variables	variable	NOUN
app01-8386	149	32	used	use	VERB
app01-8386	149	33	in	in	ADP
app01-8386	149	34	the	the	DET
app01-8386	149	35	study	study	NOUN
app01-8386	149	36	.	.	PUNCT
app01-8386	150	1	regarding	regard	VERB
app01-8386	150	2	the	the	DET
app01-8386	150	3	mae	mae	PROPN
app01-8386	150	4	and	and	CCONJ
app01-8386	150	5	rmse	rmse	PROPN
app01-8386	150	6	,	,	PUNCT
app01-8386	150	7	the	the	DET
app01-8386	150	8	knn	knn	PROPN
app01-8386	150	9	model	model	NOUN
app01-8386	150	10	performs	perform	VERB
app01-8386	150	11	one	one	NUM
app01-8386	150	12	order	order	NOUN
app01-8386	150	13	of	of	ADP
app01-8386	150	14	magnitude	magnitude	NOUN
app01-8386	150	15	better	well	ADJ
app01-8386	150	16	than	than	ADP
app01-8386	150	17	the	the	DET
app01-8386	150	18	other	other	ADJ
app01-8386	150	19	two	two	NUM
app01-8386	150	20	ml	ml	NOUN
app01-8386	150	21	models	model	NOUN
app01-8386	150	22	for	for	ADP
app01-8386	150	23	the	the	DET
app01-8386	150	24	cf	cf	NOUN
app01-8386	150	25	0	0	NUM
app01-8386	150	26	configuration	configuration	NOUN
app01-8386	150	27	(	(	PUNCT
app01-8386	150	28	without	without	ADP
app01-8386	150	29	reinforcement	reinforcement	NOUN
app01-8386	150	30	)	)	PUNCT
app01-8386	150	31	at	at	ADP
app01-8386	150	32	a	a	DET
app01-8386	150	33	level	level	NOUN
app01-8386	150	34	of	of	ADP
app01-8386	150	35	0.3	0.3	NUM
app01-8386	150	36	%	%	NOUN
app01-8386	150	37	resp	resp	NOUN
app01-8386	150	38	.	.	PUNCT
app01-8386	151	1	0.05	0.05	NUM
app01-8386	151	2	%	%	NOUN
app01-8386	151	3	,	,	PUNCT
app01-8386	151	4	while	while	SCONJ
app01-8386	151	5	for	for	ADP
app01-8386	151	6	the	the	DET
app01-8386	151	7	cf	cf	NOUN
app01-8386	151	8	1	1	NUM
app01-8386	151	9	configuration	configuration	NOUN
app01-8386	151	10	(	(	PUNCT
app01-8386	151	11	with	with	ADP
app01-8386	151	12	reinforcement	reinforcement	NOUN
app01-8386	151	13	)	)	PUNCT
app01-8386	151	14	the	the	DET
app01-8386	151	15	resnets	resnet	NOUN
app01-8386	151	16	has	have	VERB
app01-8386	151	17	the	the	DET
app01-8386	151	18	lowest	low	ADJ
app01-8386	151	19	rmse	rmse	ADJ
app01-8386	151	20	value	value	NOUN
app01-8386	151	21	of	of	ADP
app01-8386	151	22	2.4	2.4	NUM
app01-8386	151	23	%	%	NOUN
app01-8386	151	24	and	and	CCONJ
app01-8386	151	25	the	the	DET
app01-8386	151	26	lgbm	lgbm	NOUN
app01-8386	151	27	has	have	VERB
app01-8386	151	28	the	the	DET
app01-8386	151	29	lowest	low	ADJ
app01-8386	151	30	mae	mae	PROPN
app01-8386	151	31	value	value	NOUN
app01-8386	151	32	of	of	ADP
app01-8386	151	33	1.8	1.8	NUM
app01-8386	151	34	%	%	NOUN
app01-8386	151	35	.	.	PUNCT
app01-8386	152	1	the	the	DET
app01-8386	152	2	results	result	NOUN
app01-8386	152	3	suggest	suggest	VERB
app01-8386	152	4	that	that	SCONJ
app01-8386	152	5	all	all	DET
app01-8386	152	6	ml	ml	NOUN
app01-8386	152	7	models	model	NOUN
app01-8386	152	8	developed	develop	VERB
app01-8386	152	9	for	for	ADP
app01-8386	152	10	predicting	predict	VERB
app01-8386	152	11	the	the	DET
app01-8386	152	12	stress	stress	NOUN
app01-8386	152	13	(	(	PUNCT
app01-8386	152	14	all	all	PRON
app01-8386	152	15	in	in	ADP
app01-8386	152	16	unit	unit	NOUN
app01-8386	152	17	:	:	PUNCT
app01-8386	152	18	mpa	mpa	PROPN
app01-8386	152	19	)	)	PUNCT
app01-8386	152	20	and	and	CCONJ
app01-8386	152	21	stiffness	stiffness	NOUN
app01-8386	152	22	(	(	PUNCT
app01-8386	152	23	all	all	PRON
app01-8386	152	24	in	in	ADP
app01-8386	152	25	unit	unit	NOUN
app01-8386	152	26	:	:	PUNCT
app01-8386	152	27	mnm2	mnm2	PROPN
app01-8386	152	28	)	)	PUNCT
app01-8386	152	29	tensor	tensor	NOUN
app01-8386	152	30	components	component	NOUN
app01-8386	152	31	are	be	AUX
app01-8386	152	32	promising	promise	VERB
app01-8386	152	33	,	,	PUNCT
app01-8386	152	34	with	with	ADP
app01-8386	152	35	resnet	resnet	NOUN
app01-8386	152	36	being	be	AUX
app01-8386	152	37	the	the	DET
app01-8386	152	38	most	most	ADV
app01-8386	152	39	predictive	predictive	ADJ
app01-8386	152	40	model	model	NOUN
app01-8386	152	41	amongst	amongst	ADP
app01-8386	152	42	the	the	DET
app01-8386	152	43	three	three	NUM
app01-8386	152	44	.	.	PUNCT
app01-8386	153	1	the	the	DET
app01-8386	153	2	model	model	NOUN
app01-8386	153	3	performances	performance	NOUN
app01-8386	153	4	,	,	PUNCT
app01-8386	153	5	described	describe	VERB
app01-8386	153	6	by	by	ADP
app01-8386	153	7	the	the	DET
app01-8386	153	8	mean	mean	ADJ
app01-8386	153	9	absolute	absolute	ADJ
app01-8386	153	10	error	error	NOUN
app01-8386	153	11	mae	mae	PROPN
app01-8386	153	12	,	,	PUNCT
app01-8386	153	13	root	root	NOUN
app01-8386	153	14	mean	mean	VERB
app01-8386	153	15	squared	square	VERB
app01-8386	153	16	error	error	NOUN
app01-8386	153	17	rmse	rmse	NOUN
app01-8386	153	18	and	and	CCONJ
app01-8386	153	19	r	r	NOUN
app01-8386	153	20	-	-	PUNCT
app01-8386	153	21	squared	square	VERB
app01-8386	153	22	have	have	AUX
app01-8386	153	23	converged	converge	VERB
app01-8386	153	24	to	to	ADP
app01-8386	153	25	a	a	DET
app01-8386	153	26	stable	stable	ADJ
app01-8386	153	27	minimum	minimum	NOUN
app01-8386	153	28	during	during	ADP
app01-8386	153	29	training	training	NOUN
app01-8386	153	30	.	.	PUNCT
app01-8386	154	1	3.1	3.1	NUM
app01-8386	154	2	.	.	PUNCT
app01-8386	155	1	knn	knn	PROPN
app01-8386	155	2	model	model	PROPN
app01-8386	155	3	results	result	VERB
app01-8386	155	4	fig	fig	PROPN
app01-8386	155	5	.	.	PUNCT
app01-8386	156	1	4	4	NUM
app01-8386	156	2	provides	provide	VERB
app01-8386	156	3	selected	select	VERB
app01-8386	156	4	results	result	NOUN
app01-8386	156	5	for	for	ADP
app01-8386	156	6	the	the	DET
app01-8386	156	7	knn	knn	PROPN
app01-8386	156	8	algorithm	algorithm	PROPN
app01-8386	156	9	in	in	ADP
app01-8386	156	10	the	the	DET
app01-8386	156	11	two	two	NUM
app01-8386	156	12	configurations	configuration	NOUN
app01-8386	156	13	"	"	PUNCT
app01-8386	156	14	cf	cf	NOUN
app01-8386	156	15	0	0	NUM
app01-8386	156	16	"	"	PUNCT
app01-8386	156	17	(	(	PUNCT
app01-8386	156	18	without	without	ADP
app01-8386	156	19	reinforcement	reinforcement	NOUN
app01-8386	156	20	)	)	PUNCT
app01-8386	156	21	and	and	CCONJ
app01-8386	156	22	"	"	PUNCT
app01-8386	156	23	cf	cf	NOUN
app01-8386	156	24	1	1	NUM
app01-8386	156	25	"	"	PUNCT
app01-8386	156	26	(	(	PUNCT
app01-8386	156	27	with	with	ADP
app01-8386	156	28	reinforcement	reinforcement	NOUN
app01-8386	156	29	)	)	PUNCT
app01-8386	156	30	.	.	PUNCT
app01-8386	157	1	it	it	PRON
app01-8386	157	2	is	be	AUX
app01-8386	157	3	important	important	ADJ
app01-8386	157	4	to	to	PART
app01-8386	157	5	note	note	VERB
app01-8386	157	6	,	,	PUNCT
app01-8386	157	7	that	that	SCONJ
app01-8386	157	8	the	the	DET
app01-8386	157	9	size	size	NOUN
app01-8386	157	10	of	of	ADP
app01-8386	157	11	the	the	DET
app01-8386	157	12	trained	train	VERB
app01-8386	157	13	knn	knn	PROPN
app01-8386	157	14	model	model	NOUN
app01-8386	157	15	is	be	AUX
app01-8386	157	16	of	of	ADP
app01-8386	157	17	around	around	ADP
app01-8386	157	18	1.13	1.13	NUM
app01-8386	157	19	gb	gb	NOUN
app01-8386	157	20	,	,	PUNCT
app01-8386	157	21	as	as	SCONJ
app01-8386	157	22	it	it	PRON
app01-8386	157	23	needs	need	VERB
app01-8386	157	24	to	to	PART
app01-8386	157	25	store	store	VERB
app01-8386	157	26	all	all	DET
app01-8386	157	27	training	training	NOUN
app01-8386	157	28	samples	sample	NOUN
app01-8386	157	29	in	in	ADP
app01-8386	157	30	order	order	NOUN
app01-8386	157	31	to	to	PART
app01-8386	157	32	make	make	VERB
app01-8386	157	33	new	new	ADJ
app01-8386	157	34	predictions	prediction	NOUN
app01-8386	157	35	.	.	PUNCT
app01-8386	158	1	3.2	3.2	NUM
app01-8386	158	2	.	.	PUNCT
app01-8386	158	3	lgbm	lgbm	ADJ
app01-8386	158	4	model	model	PROPN
app01-8386	158	5	results	result	VERB
app01-8386	158	6	fig	fig	NOUN
app01-8386	158	7	.	.	PUNCT
app01-8386	159	1	5	5	NUM
app01-8386	159	2	provides	provide	VERB
app01-8386	159	3	selected	select	VERB
app01-8386	159	4	results	result	NOUN
app01-8386	159	5	for	for	ADP
app01-8386	159	6	the	the	DET
app01-8386	159	7	lgbm	lgbm	ADJ
app01-8386	159	8	algorithm	algorithm	NOUN
app01-8386	159	9	in	in	ADP
app01-8386	159	10	the	the	DET
app01-8386	159	11	two	two	NUM
app01-8386	159	12	configurations	configuration	NOUN
app01-8386	159	13	"	"	PUNCT
app01-8386	159	14	cf	cf	NOUN
app01-8386	159	15	0	0	NUM
app01-8386	159	16	"	"	PUNCT
app01-8386	159	17	(	(	PUNCT
app01-8386	159	18	without	without	ADP
app01-8386	159	19	reinforcement	reinforcement	NOUN
app01-8386	159	20	)	)	PUNCT
app01-8386	159	21	and	and	CCONJ
app01-8386	159	22	"	"	PUNCT
app01-8386	159	23	cf	cf	NOUN
app01-8386	159	24	1	1	NUM
app01-8386	159	25	"	"	PUNCT
app01-8386	159	26	(	(	PUNCT
app01-8386	159	27	with	with	ADP
app01-8386	159	28	reinforcement	reinforcement	NOUN
app01-8386	159	29	)	)	PUNCT
app01-8386	159	30	.	.	PUNCT
app01-8386	160	1	3.3	3.3	NUM
app01-8386	160	2	.	.	PUNCT
app01-8386	161	1	resnet	resnet	NOUN
app01-8386	161	2	model	model	NOUN
app01-8386	161	3	results	result	VERB
app01-8386	161	4	fig	fig	NOUN
app01-8386	161	5	.	.	PUNCT
app01-8386	162	1	6	6	NUM
app01-8386	162	2	provides	provide	VERB
app01-8386	162	3	selected	select	VERB
app01-8386	162	4	results	result	NOUN
app01-8386	162	5	for	for	ADP
app01-8386	162	6	the	the	DET
app01-8386	162	7	resnet	resnet	ADJ
app01-8386	162	8	algorithm	algorithm	NOUN
app01-8386	162	9	in	in	ADP
app01-8386	162	10	the	the	DET
app01-8386	162	11	two	two	NUM
app01-8386	162	12	configurations	configuration	NOUN
app01-8386	162	13	"	"	PUNCT
app01-8386	162	14	cf	cf	NOUN
app01-8386	162	15	0	0	NUM
app01-8386	162	16	"	"	PUNCT
app01-8386	162	17	(	(	PUNCT
app01-8386	162	18	without	without	ADP
app01-8386	162	19	reinforcement	reinforcement	NOUN
app01-8386	162	20	)	)	PUNCT
app01-8386	162	21	and	and	CCONJ
app01-8386	162	22	"	"	PUNCT
app01-8386	162	23	cf	cf	NOUN
app01-8386	162	24	1	1	NUM
app01-8386	162	25	"	"	PUNCT
app01-8386	162	26	(	(	PUNCT
app01-8386	162	27	with	with	ADP
app01-8386	162	28	reinforcement	reinforcement	NOUN
app01-8386	162	29	)	)	PUNCT
app01-8386	162	30	.	.	PUNCT
app01-8386	163	1	3.4	3.4	NUM
app01-8386	163	2	.	.	PUNCT
app01-8386	163	3	overall	overall	ADJ
app01-8386	163	4	model	model	PROPN
app01-8386	163	5	comparison	comparison	NOUN
app01-8386	163	6	results	result	VERB
app01-8386	163	7	the	the	DET
app01-8386	163	8	performances	performance	NOUN
app01-8386	163	9	of	of	ADP
app01-8386	163	10	different	different	ADJ
app01-8386	163	11	ai	ai	NOUN
app01-8386	163	12	models	model	NOUN
app01-8386	163	13	according	accord	VERB
app01-8386	163	14	to	to	ADP
app01-8386	163	15	the	the	DET
app01-8386	163	16	mentioned	mention	VERB
app01-8386	163	17	criteria	criterion	NOUN
app01-8386	163	18	are	be	AUX
app01-8386	163	19	reported	report	VERB
app01-8386	163	20	in	in	ADP
app01-8386	163	21	tab	tab	NOUN
app01-8386	163	22	.	.	PROPN
app01-8386	163	23	6	6	NUM
app01-8386	163	24	for	for	ADP
app01-8386	163	25	configuration	configuration	NOUN
app01-8386	163	26	"	"	PUNCT
app01-8386	163	27	cf	cf	NOUN
app01-8386	163	28	0	0	NUM
app01-8386	163	29	"	"	PUNCT
app01-8386	163	30	(	(	PUNCT
app01-8386	163	31	without	without	ADP
app01-8386	163	32	reinforcement	reinforcement	NOUN
app01-8386	163	33	)	)	PUNCT
app01-8386	163	34	and	and	CCONJ
app01-8386	163	35	in	in	ADP
app01-8386	163	36	tab	tab	NOUN
app01-8386	163	37	.	.	PUNCT
app01-8386	163	38	7	7	NUM
app01-8386	163	39	for	for	ADP
app01-8386	163	40	configuration	configuration	NOUN
app01-8386	163	41	"	"	PUNCT
app01-8386	163	42	cf	cf	NOUN
app01-8386	163	43	1	1	NUM
app01-8386	163	44	"	"	PUNCT
app01-8386	163	45	(	(	PUNCT
app01-8386	163	46	with	with	ADP
app01-8386	163	47	reinforcement	reinforcement	NOUN
app01-8386	163	48	)	)	PUNCT
app01-8386	163	49	.	.	PUNCT
app01-8386	164	1	model	model	PROPN
app01-8386	164	2	rmse	rmse	PROPN
app01-8386	164	3	mae	mae	PROPN
app01-8386	164	4	r2	r2	PROPN
app01-8386	164	5	v	v	PROPN
app01-8386	164	6	ar	ar	PROPN
app01-8386	164	7	knn	knn	PROPN
app01-8386	164	8	0.00045	0.00045	NUM
app01-8386	164	9	0.00310	0.00310	NUM
app01-8386	164	10	0.99955	0.99955	NUM
app01-8386	164	11	0.00044	0.00044	NUM
app01-8386	164	12	lgbm	lgbm	ADJ
app01-8386	164	13	0.00530	0.00530	NUM
app01-8386	164	14	0.01837	0.01837	NUM
app01-8386	165	1	0.99440	0.99440	NUM
app01-8386	165	2	0.00560	0.00560	NUM
app01-8386	165	3	resnet	resnet	VERB
app01-8386	165	4	0.00212	0.00212	NUM
app01-8386	165	5	0.01576	0.01576	NUM
app01-8386	165	6	0.99760	0.99760	NUM
app01-8386	165	7	0.00238	0.00238	NUM
app01-8386	165	8	table	table	NOUN
app01-8386	165	9	6	6	NUM
app01-8386	165	10	.	.	PUNCT
app01-8386	165	11	performance	performance	NOUN
app01-8386	165	12	of	of	ADP
app01-8386	165	13	different	different	ADJ
app01-8386	165	14	models	model	NOUN
app01-8386	165	15	on	on	ADP
app01-8386	165	16	test	test	NOUN
app01-8386	165	17	set	set	VERB
app01-8386	165	18	without	without	ADP
app01-8386	165	19	reinforcement	reinforcement	NOUN
app01-8386	165	20	for	for	ADP
app01-8386	165	21	model	model	NOUN
app01-8386	165	22	selection	selection	NOUN
app01-8386	165	23	purposes	purpose	NOUN
app01-8386	165	24	,	,	PUNCT
app01-8386	165	25	we	we	PRON
app01-8386	165	26	provide	provide	VERB
app01-8386	165	27	selected	select	VERB
app01-8386	165	28	results	result	NOUN
app01-8386	165	29	for	for	ADP
app01-8386	165	30	the	the	DET
app01-8386	165	31	taylor	taylor	PROPN
app01-8386	165	32	diagrams	diagram	NOUN
app01-8386	165	33	in	in	ADP
app01-8386	165	34	the	the	DET
app01-8386	165	35	two	two	NUM
app01-8386	165	36	configurations	configuration	NOUN
app01-8386	165	37	"	"	PUNCT
app01-8386	165	38	cf	cf	NOUN
app01-8386	165	39	0	0	NUM
app01-8386	165	40	"	"	PUNCT
app01-8386	165	41	(	(	PUNCT
app01-8386	165	42	without	without	ADP
app01-8386	165	43	reinforcement	reinforcement	NOUN
app01-8386	165	44	)	)	PUNCT
app01-8386	165	45	and	and	CCONJ
app01-8386	165	46	"	"	PUNCT
app01-8386	165	47	cf	cf	NOUN
app01-8386	165	48	1	1	NUM
app01-8386	165	49	"	"	PUNCT
app01-8386	165	50	(	(	PUNCT
app01-8386	165	51	with	with	ADP
app01-8386	165	52	reinforcement	reinforcement	NOUN
app01-8386	165	53	)	)	PUNCT
app01-8386	165	54	in	in	ADP
app01-8386	165	55	fig	fig	NOUN
app01-8386	165	56	.	.	PUNCT
app01-8386	166	1	7	7	X
app01-8386	166	2	.	.	X
app01-8386	166	3	model	model	PROPN
app01-8386	166	4	rmse	rmse	PROPN
app01-8386	166	5	mae	mae	PROPN
app01-8386	166	6	r2	r2	PROPN
app01-8386	166	7	v	v	PROPN
app01-8386	166	8	ar	ar	PROPN
app01-8386	166	9	knn	knn	PROPN
app01-8386	166	10	0.06678	0.06678	NUM
app01-8386	166	11	0.01579	0.01579	NUM
app01-8386	166	12	0.93789	0.93789	NUM
app01-8386	166	13	0.06678	0.06678	NUM
app01-8386	166	14	lgbm	lgbm	ADJ
app01-8386	166	15	0.02783	0.02783	NUM
app01-8386	166	16	0.02329	0.02329	NUM
app01-8386	166	17	0.97390	0.97390	NUM
app01-8386	166	18	0.02783	0.02783	NUM
app01-8386	166	19	resnet	resnet	VERB
app01-8386	166	20	0.02417	0.02417	NUM
app01-8386	166	21	0.03301	0.03301	NUM
app01-8386	166	22	0.97715	0.97715	NUM
app01-8386	166	23	0.02416	0.02416	NUM
app01-8386	166	24	table	table	NOUN
app01-8386	166	25	7	7	NUM
app01-8386	166	26	.	.	PUNCT
app01-8386	166	27	performance	performance	NOUN
app01-8386	166	28	of	of	ADP
app01-8386	166	29	different	different	ADJ
app01-8386	166	30	models	model	NOUN
app01-8386	166	31	on	on	ADP
app01-8386	166	32	test	test	NOUN
app01-8386	166	33	set	set	VERB
app01-8386	166	34	with	with	ADP
app01-8386	166	35	reinforcement	reinforcement	NOUN
app01-8386	166	36	4	4	NUM
app01-8386	166	37	.	.	PUNCT
app01-8386	166	38	discussion	discussion	VERB
app01-8386	166	39	the	the	DET
app01-8386	166	40	choice	choice	NOUN
app01-8386	166	41	for	for	ADP
app01-8386	166	42	the	the	DET
app01-8386	166	43	three	three	NUM
app01-8386	166	44	investigated	investigate	VERB
app01-8386	166	45	ai	ai	NOUN
app01-8386	166	46	algorithms	algorithm	NOUN
app01-8386	166	47	was	be	AUX
app01-8386	166	48	done	do	VERB
app01-8386	166	49	under	under	ADP
app01-8386	166	50	three	three	NUM
app01-8386	166	51	aspects	aspect	NOUN
app01-8386	166	52	:	:	PUNCT
app01-8386	166	53	modeling	model	VERB
app01-8386	166	54	bias	bias	NOUN
app01-8386	166	55	,	,	PUNCT
app01-8386	166	56	computing	compute	VERB
app01-8386	166	57	efficiency	efficiency	NOUN
app01-8386	166	58	and	and	CCONJ
app01-8386	166	59	prediction	prediction	NOUN
app01-8386	166	60	precision	precision	NOUN
app01-8386	166	61	.	.	PUNCT
app01-8386	167	1	the	the	DET
app01-8386	167	2	knn	knn	PROPN
app01-8386	167	3	and	and	CCONJ
app01-8386	167	4	lgbm	lgbm	PROPN
app01-8386	167	5	belong	belong	VERB
app01-8386	167	6	to	to	ADP
app01-8386	167	7	the	the	DET
app01-8386	167	8	family	family	NOUN
app01-8386	167	9	of	of	ADP
app01-8386	167	10	non	non	ADJ
app01-8386	167	11	-	-	ADJ
app01-8386	167	12	parametric	parametric	ADJ
app01-8386	167	13	models	model	NOUN
app01-8386	167	14	,	,	PUNCT
app01-8386	167	15	whereas	whereas	SCONJ
app01-8386	167	16	resnet	resnet	NOUN
app01-8386	167	17	is	be	AUX
app01-8386	167	18	a	a	DET
app01-8386	167	19	parametric	parametric	ADJ
app01-8386	167	20	model	model	NOUN
app01-8386	167	21	.	.	PUNCT
app01-8386	168	1	nonparametric	nonparametric	PROPN
app01-8386	168	2	ml	ml	ADP
app01-8386	168	3	algorithms	algorithm	NOUN
app01-8386	168	4	promise	promise	VERB
app01-8386	168	5	greater	great	ADJ
app01-8386	168	6	performance	performance	NOUN
app01-8386	168	7	at	at	ADP
app01-8386	168	8	the	the	DET
app01-8386	168	9	cost	cost	NOUN
app01-8386	168	10	of	of	ADP
app01-8386	168	11	higher	high	ADJ
app01-8386	168	12	data	datum	NOUN
app01-8386	168	13	requirements	requirement	NOUN
app01-8386	168	14	and	and	CCONJ
app01-8386	168	15	training	training	NOUN
app01-8386	168	16	times	time	NOUN
app01-8386	168	17	together	together	ADV
app01-8386	168	18	with	with	ADP
app01-8386	168	19	a	a	DET
app01-8386	168	20	risk	risk	NOUN
app01-8386	168	21	of	of	ADP
app01-8386	168	22	overfitting	overfitte	VERB
app01-8386	168	23	.	.	PUNCT
app01-8386	169	1	parametric	parametric	ADJ
app01-8386	169	2	ml	ml	PROPN
app01-8386	169	3	/	/	SYM
app01-8386	169	4	dl	dl	PROPN
app01-8386	169	5	models	model	NOUN
app01-8386	169	6	on	on	ADP
app01-8386	169	7	the	the	DET
app01-8386	169	8	other	other	ADJ
app01-8386	169	9	hand	hand	NOUN
app01-8386	169	10	come	come	VERB
app01-8386	169	11	with	with	ADP
app01-8386	169	12	high	high	ADJ
app01-8386	169	13	modeling	modeling	NOUN
app01-8386	169	14	bias	bias	NOUN
app01-8386	169	15	towards	towards	ADP
app01-8386	169	16	the	the	DET
app01-8386	169	17	functional	functional	ADJ
app01-8386	169	18	relation	relation	NOUN
app01-8386	169	19	,	,	PUNCT
app01-8386	169	20	yet	yet	CCONJ
app01-8386	169	21	neural	neural	ADJ
app01-8386	169	22	networks	network	NOUN
app01-8386	169	23	provide	provide	VERB
app01-8386	169	24	a	a	DET
app01-8386	169	25	great	great	ADJ
app01-8386	169	26	enough	enough	ADJ
app01-8386	169	27	expressiveness	expressiveness	NOUN
app01-8386	169	28	for	for	ADP
app01-8386	169	29	modeling	model	VERB
app01-8386	169	30	the	the	DET
app01-8386	169	31	database	database	NOUN
app01-8386	169	32	.	.	PUNCT
app01-8386	170	1	concerning	concern	VERB
app01-8386	170	2	computational	computational	ADJ
app01-8386	170	3	efficiency	efficiency	NOUN
app01-8386	170	4	in	in	ADP
app01-8386	170	5	the	the	DET
app01-8386	170	6	prediction	prediction	NOUN
app01-8386	170	7	stage	stage	NOUN
app01-8386	170	8	(	(	PUNCT
app01-8386	170	9	which	which	PRON
app01-8386	170	10	is	be	AUX
app01-8386	170	11	called	call	VERB
app01-8386	170	12	a	a	DET
app01-8386	170	13	lot	lot	NOUN
app01-8386	170	14	of	of	ADP
app01-8386	170	15	times	time	NOUN
app01-8386	170	16	during	during	ADP
app01-8386	170	17	fem	fem	NOUN
app01-8386	170	18	analysis	analysis	NOUN
app01-8386	170	19	in	in	ADP
app01-8386	170	20	each	each	DET
app01-8386	170	21	iteration	iteration	NOUN
app01-8386	170	22	step	step	NOUN
app01-8386	170	23	)	)	PUNCT
app01-8386	170	24	knn	knn	PROPN
app01-8386	170	25	requires	require	VERB
app01-8386	170	26	to	to	PART
app01-8386	170	27	store	store	VERB
app01-8386	170	28	the	the	DET
app01-8386	170	29	dataset	dataset	NOUN
app01-8386	170	30	and	and	CCONJ
app01-8386	170	31	call	call	VERB
app01-8386	170	32	it	it	PRON
app01-8386	170	33	at	at	ADP
app01-8386	170	34	prediction	prediction	NOUN
app01-8386	170	35	time	time	NOUN
app01-8386	170	36	,	,	PUNCT
app01-8386	170	37	leading	lead	VERB
app01-8386	170	38	to	to	ADP
app01-8386	170	39	impractical	impractical	ADJ
app01-8386	170	40	lengthy	lengthy	ADJ
app01-8386	170	41	procedures	procedure	NOUN
app01-8386	170	42	.	.	PUNCT
app01-8386	171	1	lgbm	lgbm	PROPN
app01-8386	171	2	and	and	CCONJ
app01-8386	171	3	resnet	resnet	NOUN
app01-8386	171	4	however	however	ADV
app01-8386	171	5	are	be	AUX
app01-8386	171	6	much	much	ADV
app01-8386	171	7	more	more	ADJ
app01-8386	171	8	time	time	NOUN
app01-8386	171	9	efficient	efficient	ADJ
app01-8386	171	10	and	and	CCONJ
app01-8386	171	11	hence	hence	ADV
app01-8386	171	12	to	to	PART
app01-8386	171	13	be	be	AUX
app01-8386	171	14	preferred	prefer	VERB
app01-8386	171	15	for	for	ADP
app01-8386	171	16	an	an	DET
app01-8386	171	17	implementation	implementation	NOUN
app01-8386	171	18	into	into	ADP
app01-8386	171	19	the	the	DET
app01-8386	171	20	fem	fem	NOUN
app01-8386	171	21	analysis	analysis	NOUN
app01-8386	171	22	.	.	PUNCT
app01-8386	172	1	the	the	DET
app01-8386	172	2	ai	ai	PROPN
app01-8386	172	3	models	model	NOUN
app01-8386	172	4	perform	perform	VERB
app01-8386	172	5	better	well	ADV
app01-8386	172	6	in	in	ADP
app01-8386	172	7	cf	cf	NOUN
app01-8386	172	8	0	0	NUM
app01-8386	172	9	(	(	PUNCT
app01-8386	172	10	without	without	ADP
app01-8386	172	11	reinforcement	reinforcement	NOUN
app01-8386	172	12	)	)	PUNCT
app01-8386	172	13	than	than	ADP
app01-8386	172	14	in	in	ADP
app01-8386	172	15	cf	cf	NOUN
app01-8386	172	16	1	1	NUM
app01-8386	172	17	accross	accross	ADV
app01-8386	172	18	the	the	DET
app01-8386	172	19	different	different	ADJ
app01-8386	172	20	quality	quality	NOUN
app01-8386	172	21	measures	measure	NOUN
app01-8386	172	22	.	.	PUNCT
app01-8386	173	1	looking	look	VERB
app01-8386	173	2	at	at	ADP
app01-8386	173	3	the	the	DET
app01-8386	173	4	r2	r2	PROPN
app01-8386	173	5	values	value	NOUN
app01-8386	173	6	,	,	PUNCT
app01-8386	173	7	all	all	DET
app01-8386	173	8	models	model	NOUN
app01-8386	173	9	have	have	VERB
app01-8386	173	10	high	high	ADJ
app01-8386	173	11	values	value	NOUN
app01-8386	173	12	of	of	ADP
app01-8386	173	13	approx	approx	PROPN
app01-8386	173	14	.	.	PUNCT
app01-8386	174	1	0.99	0.99	NUM
app01-8386	174	2	(	(	PUNCT
app01-8386	174	3	cf	cf	NOUN
app01-8386	174	4	0	0	NUM
app01-8386	174	5	)	)	PUNCT
app01-8386	174	6	resp	resp	NOUN
app01-8386	174	7	.	.	PUNCT
app01-8386	175	1	0.97	0.97	NUM
app01-8386	175	2	(	(	PUNCT
app01-8386	175	3	cf	cf	NOUN
app01-8386	175	4	1	1	NUM
app01-8386	175	5	)	)	PUNCT
app01-8386	175	6	.	.	PUNCT
app01-8386	176	1	this	this	PRON
app01-8386	176	2	means	mean	VERB
app01-8386	176	3	,	,	PUNCT
app01-8386	176	4	that	that	SCONJ
app01-8386	176	5	the	the	DET
app01-8386	176	6	ml	ml	PROPN
app01-8386	176	7	algorithms	algorithm	NOUN
app01-8386	176	8	are	be	AUX
app01-8386	176	9	able	able	ADJ
app01-8386	176	10	to	to	PART
app01-8386	176	11	describe	describe	VERB
app01-8386	176	12	over	over	ADP
app01-8386	176	13	97	97	NUM
app01-8386	176	14	%	%	NOUN
app01-8386	176	15	of	of	ADP
app01-8386	176	16	variations	variation	NOUN
app01-8386	176	17	in	in	ADP
app01-8386	176	18	the	the	DET
app01-8386	176	19	data	datum	NOUN
app01-8386	176	20	,	,	PUNCT
app01-8386	176	21	and	and	CCONJ
app01-8386	176	22	hence	hence	ADV
app01-8386	176	23	are	be	AUX
app01-8386	176	24	highly	highly	ADV
app01-8386	176	25	predictive	predictive	ADJ
app01-8386	176	26	for	for	ADP
app01-8386	176	27	the	the	DET
app01-8386	176	28	outputs	output	NOUN
app01-8386	176	29	.	.	PUNCT
app01-8386	177	1	for	for	ADP
app01-8386	177	2	cf	cf	NOUN
app01-8386	177	3	0	0	NUM
app01-8386	177	4	rmse	rmse	NOUN
app01-8386	177	5	is	be	AUX
app01-8386	177	6	around	around	ADV
app01-8386	177	7	0.35	0.35	NUM
app01-8386	177	8	%	%	NOUN
app01-8386	177	9	and	and	CCONJ
app01-8386	177	10	mae	mae	PROPN
app01-8386	177	11	is	be	AUX
app01-8386	177	12	around	around	ADP
app01-8386	177	13	1.5	1.5	NUM
app01-8386	177	14	%	%	NOUN
app01-8386	177	15	,	,	PUNCT
app01-8386	177	16	while	while	SCONJ
app01-8386	177	17	for	for	ADP
app01-8386	177	18	cf	cf	NOUN
app01-8386	177	19	1	1	NUM
app01-8386	177	20	rmse	rmse	NOUN
app01-8386	177	21	as	as	ADV
app01-8386	177	22	well	well	ADV
app01-8386	177	23	as	as	ADP
app01-8386	177	24	mae	mae	PROPN
app01-8386	177	25	lie	lie	VERB
app01-8386	177	26	about	about	ADV
app01-8386	177	27	3	3	NUM
app01-8386	177	28	%	%	NOUN
app01-8386	177	29	and	and	CCONJ
app01-8386	177	30	are	be	AUX
app01-8386	177	31	thus	thus	ADV
app01-8386	177	32	one	one	NUM
app01-8386	177	33	magnitude	magnitude	NOUN
app01-8386	177	34	bigger	big	ADJ
app01-8386	177	35	than	than	ADP
app01-8386	177	36	for	for	ADP
app01-8386	177	37	cf	cf	NOUN
app01-8386	177	38	0	0	NUM
app01-8386	177	39	.	.	PUNCT
app01-8386	178	1	it	it	PRON
app01-8386	178	2	is	be	AUX
app01-8386	178	3	noteworthy	noteworthy	ADJ
app01-8386	178	4	that	that	SCONJ
app01-8386	178	5	on	on	ADP
app01-8386	178	6	average	average	ADJ
app01-8386	178	7	,	,	PUNCT
app01-8386	178	8	every	every	DET
app01-8386	178	9	target	target	NOUN
app01-8386	178	10	is	be	AUX
app01-8386	178	11	predicted	predict	VERB
app01-8386	178	12	well	well	ADV
app01-8386	178	13	,	,	PUNCT
app01-8386	178	14	while	while	SCONJ
app01-8386	178	15	the	the	DET
app01-8386	178	16	prediction	prediction	NOUN
app01-8386	178	17	’s	’s	PART
app01-8386	178	18	standard	standard	ADJ
app01-8386	178	19	deviation	deviation	NOUN
app01-8386	178	20	is	be	AUX
app01-8386	178	21	dependent	dependent	ADJ
app01-8386	178	22	on	on	ADP
app01-8386	178	23	the	the	DET
app01-8386	178	24	respective	respective	ADJ
app01-8386	178	25	target	target	NOUN
app01-8386	178	26	quantity	quantity	NOUN
app01-8386	178	27	.	.	PUNCT
app01-8386	179	1	given	give	VERB
app01-8386	179	2	all	all	DET
app01-8386	179	3	model	model	NOUN
app01-8386	179	4	results	result	NOUN
app01-8386	179	5	,	,	PUNCT
app01-8386	179	6	especially	especially	ADV
app01-8386	179	7	the	the	DET
app01-8386	179	8	stiffness	stiffness	ADJ
app01-8386	179	9	tensor	tensor	NOUN
app01-8386	179	10	terms	term	NOUN
app01-8386	179	11	k22	k22	AUX
app01-8386	179	12	and	and	CCONJ
app01-8386	179	13	k23	k23	PROPN
app01-8386	179	14	show	show	VERB
app01-8386	179	15	severe	severe	ADJ
app01-8386	179	16	model	model	NOUN
app01-8386	179	17	predictive	predictive	ADJ
app01-8386	179	18	deviations	deviation	NOUN
app01-8386	179	19	.	.	PUNCT
app01-8386	180	1	for	for	ADP
app01-8386	180	2	model	model	NOUN
app01-8386	180	3	selection	selection	NOUN
app01-8386	180	4	,	,	PUNCT
app01-8386	180	5	inspection	inspection	NOUN
app01-8386	180	6	of	of	ADP
app01-8386	180	7	the	the	DET
app01-8386	180	8	taylor	taylor	PROPN
app01-8386	180	9	diagrams	diagram	NOUN
app01-8386	180	10	in	in	ADP
app01-8386	180	11	fig	fig	NOUN
app01-8386	180	12	.	.	PUNCT
app01-8386	181	1	7	7	NUM
app01-8386	181	2	suggests	suggest	VERB
app01-8386	181	3	that	that	SCONJ
app01-8386	181	4	all	all	PRON
app01-8386	181	5	described	describe	VERB
app01-8386	181	6	ai	ai	VERB
app01-8386	181	7	models	model	NOUN
app01-8386	181	8	possess	possess	VERB
app01-8386	181	9	great	great	ADJ
app01-8386	181	10	approximation	approximation	NOUN
app01-8386	181	11	quality	quality	NOUN
app01-8386	181	12	with	with	ADP
app01-8386	181	13	slight	slight	ADJ
app01-8386	181	14	differences	difference	NOUN
app01-8386	181	15	,	,	PUNCT
app01-8386	181	16	where	where	SCONJ
app01-8386	181	17	knn	knn	PROPN
app01-8386	181	18	outperforms	outperform	VERB
app01-8386	181	19	resnet	resnet	NOUN
app01-8386	181	20	and	and	CCONJ
app01-8386	181	21	lgbm	lgbm	ADJ
app01-8386	181	22	(	(	PUNCT
app01-8386	181	23	in	in	ADP
app01-8386	181	24	the	the	DET
app01-8386	181	25	order	order	NOUN
app01-8386	181	26	of	of	ADP
app01-8386	181	27	decreasing	decrease	VERB
app01-8386	181	28	approximation	approximation	NOUN
app01-8386	181	29	quality	quality	NOUN
app01-8386	181	30	)	)	PUNCT
app01-8386	181	31	.	.	PUNCT
app01-8386	182	1	the	the	DET
app01-8386	182	2	results	result	NOUN
app01-8386	182	3	in	in	ADP
app01-8386	182	4	summary	summary	NOUN
app01-8386	182	5	suggest	suggest	VERB
app01-8386	182	6	that	that	SCONJ
app01-8386	182	7	the	the	DET
app01-8386	182	8	ai	ai	PROPN
app01-8386	182	9	models	model	NOUN
app01-8386	182	10	developed	develop	VERB
app01-8386	182	11	for	for	ADP
app01-8386	182	12	predicting	predict	VERB
app01-8386	182	13	the	the	DET
app01-8386	182	14	stress	stress	NOUN
app01-8386	182	15	and	and	CCONJ
app01-8386	182	16	stiffness	stiffness	ADJ
app01-8386	182	17	responses	response	NOUN
app01-8386	182	18	of	of	ADP
app01-8386	182	19	the	the	DET
app01-8386	182	20	cmm	cmm	PROPN
app01-8386	182	21	user	user	PROPN
app01-8386	182	22	-	-	PUNCT
app01-8386	182	23	mat	mat	NOUN
app01-8386	182	24	are	be	AUX
app01-8386	182	25	promising	promise	VERB
app01-8386	182	26	and	and	CCONJ
app01-8386	182	27	may	may	AUX
app01-8386	182	28	be	be	AUX
app01-8386	182	29	used	use	VERB
app01-8386	182	30	within	within	ADP
app01-8386	182	31	a	a	DET
app01-8386	182	32	fem	fem	NOUN
app01-8386	182	33	.	.	PUNCT
app01-8386	183	1	given	give	VERB
app01-8386	183	2	the	the	DET
app01-8386	183	3	outlines	outline	NOUN
app01-8386	183	4	in	in	ADP
app01-8386	183	5	the	the	DET
app01-8386	183	6	beginning	beginning	NOUN
app01-8386	183	7	of	of	ADP
app01-8386	183	8	this	this	DET
app01-8386	183	9	section	section	NOUN
app01-8386	183	10	towards	towards	ADP
app01-8386	183	11	computational	computational	ADJ
app01-8386	183	12	efficiency	efficiency	NOUN
app01-8386	183	13	,	,	PUNCT
app01-8386	183	14	the	the	DET
app01-8386	183	15	resnet	resnet	NOUN
app01-8386	183	16	and	and	CCONJ
app01-8386	183	17	lgbm	lgbm	ADJ
app01-8386	183	18	are	be	AUX
app01-8386	183	19	chosen	choose	VERB
app01-8386	183	20	for	for	ADP
app01-8386	183	21	further	further	ADJ
app01-8386	183	22	implementation	implementation	NOUN
app01-8386	183	23	into	into	ADP
app01-8386	183	24	the	the	DET
app01-8386	183	25	fem	fem	NOUN
app01-8386	183	26	analysis	analysis	NOUN
app01-8386	183	27	process	process	NOUN
app01-8386	183	28	.	.	PUNCT
app01-8386	184	1	another	another	DET
app01-8386	184	2	interesting	interesting	ADJ
app01-8386	184	3	thought	thought	NOUN
app01-8386	184	4	is	be	AUX
app01-8386	184	5	to	to	PART
app01-8386	184	6	use	use	VERB
app01-8386	184	7	the	the	DET
app01-8386	184	8	calibration	calibration	NOUN
app01-8386	184	9	of	of	ADP
app01-8386	184	10	ai	ai	ADJ
app01-8386	184	11	algorithms	algorithm	NOUN
app01-8386	184	12	on	on	ADP
app01-8386	184	13	such	such	ADJ
app01-8386	184	14	numerical	numerical	ADJ
app01-8386	184	15	datasets	dataset	NOUN
app01-8386	184	16	for	for	ADP
app01-8386	184	17	non	non	ADJ
app01-8386	184	18	-	-	ADJ
app01-8386	184	19	intrusive	intrusive	ADJ
app01-8386	184	20	verification	verification	NOUN
app01-8386	184	21	purposes	purpose	NOUN
app01-8386	184	22	of	of	ADP
app01-8386	184	23	the	the	DET
app01-8386	184	24	implementa104	implementa104	PROPN
app01-8386	184	25	vol	vol	NOUN
app01-8386	184	26	.	.	PUNCT
app01-8386	185	1	36/2022	36/2022	NUM
app01-8386	185	2	ai	ai	ADJ
app01-8386	185	3	-	-	PUNCT
app01-8386	185	4	fem	fem	NOUN
app01-8386	185	5	-	-	PUNCT
app01-8386	185	6	hybrids	hybrid	NOUN
app01-8386	185	7	for	for	ADP
app01-8386	185	8	nonlinear	nonlinear	ADJ
app01-8386	185	9	concrete	concrete	ADJ
app01-8386	185	10	materials	material	NOUN
app01-8386	185	11	(	(	PUNCT
app01-8386	185	12	a	a	NOUN
app01-8386	185	13	)	)	PUNCT
app01-8386	185	14	(	(	PUNCT
app01-8386	185	15	b	b	X
app01-8386	185	16	)	)	PUNCT
app01-8386	185	17	(	(	PUNCT
app01-8386	185	18	c	c	X
app01-8386	185	19	)	)	PUNCT
app01-8386	185	20	(	(	PUNCT
app01-8386	185	21	d	d	X
app01-8386	185	22	)	)	PUNCT
app01-8386	185	23	figure	figure	NOUN
app01-8386	185	24	4	4	NUM
app01-8386	185	25	.	.	PUNCT
app01-8386	186	1	knn	knn	PROPN
app01-8386	186	2	results	result	VERB
app01-8386	186	3	for	for	ADP
app01-8386	186	4	:	:	PUNCT
app01-8386	186	5	(	(	PUNCT
app01-8386	186	6	a	a	X
app01-8386	186	7	)	)	PUNCT
app01-8386	186	8	stress	stress	NOUN
app01-8386	186	9	component	component	NOUN
app01-8386	186	10	σx	σx	NOUN
app01-8386	186	11	in	in	ADP
app01-8386	186	12	cf	cf	NOUN
app01-8386	186	13	0	0	NUM
app01-8386	186	14	,	,	PUNCT
app01-8386	186	15	(	(	PUNCT
app01-8386	186	16	b	b	NOUN
app01-8386	186	17	)	)	PUNCT
app01-8386	186	18	stiffness	stiffness	ADJ
app01-8386	186	19	component	component	NOUN
app01-8386	186	20	k11	k11	NOUN
app01-8386	186	21	in	in	ADP
app01-8386	186	22	cf	cf	PROPN
app01-8386	186	23	0	0	NUM
app01-8386	186	24	,	,	PUNCT
app01-8386	186	25	(	(	PUNCT
app01-8386	186	26	c	c	X
app01-8386	186	27	)	)	PUNCT
app01-8386	186	28	stress	stress	NOUN
app01-8386	186	29	component	component	NOUN
app01-8386	186	30	σx	σx	NOUN
app01-8386	186	31	in	in	ADP
app01-8386	186	32	cf	cf	NOUN
app01-8386	186	33	1	1	NUM
app01-8386	186	34	,	,	PUNCT
app01-8386	186	35	and	and	CCONJ
app01-8386	186	36	(	(	PUNCT
app01-8386	186	37	d	d	NOUN
app01-8386	186	38	)	)	PUNCT
app01-8386	186	39	stiffness	stiffness	ADJ
app01-8386	186	40	component	component	NOUN
app01-8386	186	41	k11	k11	NOUN
app01-8386	186	42	in	in	ADP
app01-8386	186	43	cf	cf	PROPN
app01-8386	186	44	1	1	NUM
app01-8386	186	45	.	.	PUNCT
app01-8386	187	1	(	(	PUNCT
app01-8386	187	2	a	a	X
app01-8386	187	3	)	)	PUNCT
app01-8386	187	4	(	(	PUNCT
app01-8386	187	5	b	b	X
app01-8386	187	6	)	)	PUNCT
app01-8386	187	7	(	(	PUNCT
app01-8386	187	8	c	c	X
app01-8386	187	9	)	)	PUNCT
app01-8386	187	10	(	(	PUNCT
app01-8386	187	11	d	d	X
app01-8386	187	12	)	)	PUNCT
app01-8386	187	13	figure	figure	NOUN
app01-8386	187	14	5	5	NUM
app01-8386	187	15	.	.	PUNCT
app01-8386	188	1	lgbm	lgbm	ADJ
app01-8386	188	2	results	result	NOUN
app01-8386	188	3	for	for	ADP
app01-8386	188	4	:	:	PUNCT
app01-8386	188	5	(	(	PUNCT
app01-8386	188	6	a	a	X
app01-8386	188	7	)	)	PUNCT
app01-8386	188	8	stress	stress	NOUN
app01-8386	188	9	component	component	NOUN
app01-8386	188	10	σx	σx	NOUN
app01-8386	188	11	in	in	ADP
app01-8386	188	12	cf	cf	NOUN
app01-8386	188	13	0	0	NUM
app01-8386	188	14	,	,	PUNCT
app01-8386	188	15	(	(	PUNCT
app01-8386	188	16	b	b	NOUN
app01-8386	188	17	)	)	PUNCT
app01-8386	188	18	stiffness	stiffness	ADJ
app01-8386	188	19	component	component	NOUN
app01-8386	188	20	k11	k11	NOUN
app01-8386	188	21	in	in	ADP
app01-8386	188	22	cf	cf	PROPN
app01-8386	188	23	0	0	NUM
app01-8386	188	24	,	,	PUNCT
app01-8386	188	25	(	(	PUNCT
app01-8386	188	26	c	c	X
app01-8386	188	27	)	)	PUNCT
app01-8386	188	28	stress	stress	NOUN
app01-8386	188	29	component	component	NOUN
app01-8386	188	30	σx	σx	NOUN
app01-8386	188	31	in	in	ADP
app01-8386	188	32	cf	cf	NOUN
app01-8386	188	33	1	1	NUM
app01-8386	188	34	,	,	PUNCT
app01-8386	188	35	and	and	CCONJ
app01-8386	188	36	(	(	PUNCT
app01-8386	188	37	d	d	NOUN
app01-8386	188	38	)	)	PUNCT
app01-8386	188	39	stiffness	stiffness	ADJ
app01-8386	188	40	component	component	NOUN
app01-8386	188	41	k11	k11	NOUN
app01-8386	188	42	in	in	ADP
app01-8386	188	43	cf	cf	PROPN
app01-8386	188	44	1	1	NUM
app01-8386	188	45	.	.	X
app01-8386	188	46	105	105	NUM
app01-8386	188	47	m.	m.	NOUN
app01-8386	188	48	a.	a.	PROPN
app01-8386	188	49	kraus	kraus	PROPN
app01-8386	188	50	,	,	PUNCT
app01-8386	188	51	r.	r.	PROPN
app01-8386	188	52	bischof	bischof	PROPN
app01-8386	188	53	,	,	PUNCT
app01-8386	188	54	w.	w.	PROPN
app01-8386	188	55	kaufmann	kaufmann	PROPN
app01-8386	188	56	,	,	PUNCT
app01-8386	188	57	k.	k.	PROPN
app01-8386	188	58	thoma	thoma	PROPN
app01-8386	188	59	acta	acta	PROPN
app01-8386	188	60	polytechnica	polytechnica	PROPN
app01-8386	188	61	ctu	ctu	NOUN
app01-8386	188	62	proceedings	proceeding	NOUN
app01-8386	188	63	(	(	PUNCT
app01-8386	188	64	a	a	X
app01-8386	188	65	)	)	PUNCT
app01-8386	188	66	(	(	PUNCT
app01-8386	188	67	b	b	X
app01-8386	188	68	)	)	PUNCT
app01-8386	188	69	(	(	PUNCT
app01-8386	188	70	c	c	X
app01-8386	188	71	)	)	PUNCT
app01-8386	188	72	(	(	PUNCT
app01-8386	188	73	d	d	X
app01-8386	188	74	)	)	PUNCT
app01-8386	188	75	figure	figure	NOUN
app01-8386	188	76	6	6	NUM
app01-8386	188	77	.	.	PUNCT
app01-8386	188	78	resnet	resnet	NOUN
app01-8386	188	79	results	result	NOUN
app01-8386	188	80	for	for	ADP
app01-8386	188	81	:	:	PUNCT
app01-8386	188	82	(	(	PUNCT
app01-8386	188	83	a	a	X
app01-8386	188	84	)	)	PUNCT
app01-8386	188	85	stress	stress	NOUN
app01-8386	188	86	component	component	NOUN
app01-8386	188	87	σx	σx	NOUN
app01-8386	188	88	in	in	ADP
app01-8386	188	89	cf	cf	NOUN
app01-8386	188	90	0	0	NUM
app01-8386	188	91	,	,	PUNCT
app01-8386	188	92	(	(	PUNCT
app01-8386	188	93	b	b	NOUN
app01-8386	188	94	)	)	PUNCT
app01-8386	188	95	stiffness	stiffness	ADJ
app01-8386	188	96	component	component	NOUN
app01-8386	188	97	k11	k11	NOUN
app01-8386	188	98	in	in	ADP
app01-8386	188	99	cf	cf	PROPN
app01-8386	188	100	0	0	NUM
app01-8386	188	101	,	,	PUNCT
app01-8386	188	102	(	(	PUNCT
app01-8386	188	103	c	c	X
app01-8386	188	104	)	)	PUNCT
app01-8386	188	105	stress	stress	NOUN
app01-8386	188	106	component	component	NOUN
app01-8386	188	107	σx	σx	NOUN
app01-8386	188	108	in	in	ADP
app01-8386	188	109	cf	cf	NOUN
app01-8386	188	110	1	1	NUM
app01-8386	188	111	,	,	PUNCT
app01-8386	188	112	and	and	CCONJ
app01-8386	188	113	(	(	PUNCT
app01-8386	188	114	d	d	NOUN
app01-8386	188	115	)	)	PUNCT
app01-8386	188	116	stiffness	stiffness	ADJ
app01-8386	188	117	component	component	NOUN
app01-8386	188	118	k11	k11	NOUN
app01-8386	188	119	in	in	ADP
app01-8386	188	120	cf	cf	PROPN
app01-8386	188	121	1	1	NUM
app01-8386	188	122	.	.	PUNCT
app01-8386	189	1	(	(	PUNCT
app01-8386	189	2	a	a	X
app01-8386	189	3	)	)	PUNCT
app01-8386	189	4	(	(	PUNCT
app01-8386	189	5	b	b	X
app01-8386	189	6	)	)	PUNCT
app01-8386	189	7	(	(	PUNCT
app01-8386	189	8	c	c	X
app01-8386	189	9	)	)	PUNCT
app01-8386	189	10	(	(	PUNCT
app01-8386	189	11	d	d	X
app01-8386	189	12	)	)	PUNCT
app01-8386	189	13	figure	figure	NOUN
app01-8386	189	14	7	7	NUM
app01-8386	189	15	.	.	PUNCT
app01-8386	190	1	taylor	taylor	NOUN
app01-8386	190	2	diagrams	diagram	NOUN
app01-8386	190	3	for	for	ADP
app01-8386	190	4	:	:	PUNCT
app01-8386	190	5	(	(	PUNCT
app01-8386	190	6	a	a	X
app01-8386	190	7	)	)	PUNCT
app01-8386	190	8	stress	stress	NOUN
app01-8386	190	9	component	component	NOUN
app01-8386	190	10	σx	σx	NOUN
app01-8386	190	11	in	in	ADP
app01-8386	190	12	cf	cf	NOUN
app01-8386	190	13	0	0	NUM
app01-8386	190	14	,	,	PUNCT
app01-8386	190	15	(	(	PUNCT
app01-8386	190	16	b	b	NOUN
app01-8386	190	17	)	)	PUNCT
app01-8386	190	18	stiffness	stiffness	ADJ
app01-8386	190	19	component	component	NOUN
app01-8386	190	20	k11	k11	NOUN
app01-8386	190	21	in	in	ADP
app01-8386	190	22	cf	cf	PROPN
app01-8386	190	23	0	0	NUM
app01-8386	190	24	,	,	PUNCT
app01-8386	190	25	(	(	PUNCT
app01-8386	190	26	c	c	X
app01-8386	190	27	)	)	PUNCT
app01-8386	190	28	stress	stress	NOUN
app01-8386	190	29	component	component	NOUN
app01-8386	190	30	σx	σx	NOUN
app01-8386	190	31	in	in	ADP
app01-8386	190	32	cf	cf	NOUN
app01-8386	190	33	1	1	NUM
app01-8386	190	34	,	,	PUNCT
app01-8386	190	35	and	and	CCONJ
app01-8386	190	36	(	(	PUNCT
app01-8386	190	37	d	d	NOUN
app01-8386	190	38	)	)	PUNCT
app01-8386	190	39	stiffness	stiffness	ADJ
app01-8386	190	40	component	component	NOUN
app01-8386	190	41	k11	k11	NOUN
app01-8386	190	42	in	in	ADP
app01-8386	190	43	cf	cf	PROPN
app01-8386	190	44	1	1	NUM
app01-8386	190	45	.	.	NOUN
app01-8386	190	46	106	106	NUM
app01-8386	190	47	vol	vol	NOUN
app01-8386	190	48	.	.	PUNCT
app01-8386	191	1	36/2022	36/2022	NUM
app01-8386	191	2	ai	ai	ADJ
app01-8386	191	3	-	-	PUNCT
app01-8386	191	4	fem	fem	NOUN
app01-8386	191	5	-	-	PUNCT
app01-8386	191	6	hybrids	hybrid	NOUN
app01-8386	191	7	for	for	ADP
app01-8386	191	8	nonlinear	nonlinear	ADJ
app01-8386	191	9	concrete	concrete	ADJ
app01-8386	191	10	materials	material	NOUN
app01-8386	191	11	tion	tion	NOUN
app01-8386	191	12	of	of	ADP
app01-8386	191	13	the	the	DET
app01-8386	191	14	ground	ground	NOUN
app01-8386	191	15	truth	truth	NOUN
app01-8386	191	16	data	datum	NOUN
app01-8386	191	17	generating	generating	NOUN
app01-8386	191	18	mechanism	mechanism	NOUN
app01-8386	191	19	.	.	PUNCT
app01-8386	192	1	especially	especially	ADV
app01-8386	192	2	the	the	DET
app01-8386	192	3	data	data	NOUN
app01-8386	192	4	points	point	NOUN
app01-8386	192	5	in	in	ADP
app01-8386	192	6	far	far	ADJ
app01-8386	192	7	distance	distance	NOUN
app01-8386	192	8	to	to	ADP
app01-8386	192	9	the	the	DET
app01-8386	192	10	diagonal	diagonal	ADJ
app01-8386	192	11	line	line	NOUN
app01-8386	192	12	in	in	ADP
app01-8386	192	13	figs	fig	NOUN
app01-8386	192	14	.	.	PUNCT
app01-8386	193	1	4	4	NUM
app01-8386	193	2	,	,	PUNCT
app01-8386	193	3	5,6	5,6	NUM
app01-8386	193	4	give	give	VERB
app01-8386	193	5	rise	rise	NOUN
app01-8386	193	6	to	to	ADP
app01-8386	193	7	outlier	outlier	NOUN
app01-8386	193	8	detection	detection	NOUN
app01-8386	193	9	methods	method	NOUN
app01-8386	193	10	.	.	PUNCT
app01-8386	194	1	it	it	PRON
app01-8386	194	2	is	be	AUX
app01-8386	194	3	currently	currently	ADV
app01-8386	194	4	under	under	ADP
app01-8386	194	5	investigation	investigation	NOUN
app01-8386	194	6	whether	whether	SCONJ
app01-8386	194	7	the	the	DET
app01-8386	194	8	identified	identify	VERB
app01-8386	194	9	outliers	outlier	NOUN
app01-8386	194	10	are	be	AUX
app01-8386	194	11	truly	truly	ADV
app01-8386	194	12	faulty	faulty	ADJ
app01-8386	194	13	data	datum	NOUN
app01-8386	194	14	(	(	PUNCT
app01-8386	194	15	i.e.	i.e.	X
app01-8386	194	16	the	the	DET
app01-8386	194	17	generating	generate	VERB
app01-8386	194	18	fem	fem	NOUN
app01-8386	194	19	material	material	NOUN
app01-8386	194	20	model	model	NOUN
app01-8386	194	21	is	be	AUX
app01-8386	194	22	not	not	PART
app01-8386	194	23	correct	correct	ADJ
app01-8386	194	24	)	)	PUNCT
app01-8386	194	25	or	or	CCONJ
app01-8386	194	26	the	the	DET
app01-8386	194	27	ai	ai	ADJ
app01-8386	194	28	algorithm	algorithm	NOUN
app01-8386	194	29	with	with	ADP
app01-8386	194	30	its	its	PRON
app01-8386	194	31	current	current	ADJ
app01-8386	194	32	state	state	NOUN
app01-8386	194	33	is	be	AUX
app01-8386	194	34	not	not	PART
app01-8386	194	35	able	able	ADJ
app01-8386	194	36	to	to	PART
app01-8386	194	37	approximate	approximate	VERB
app01-8386	194	38	the	the	DET
app01-8386	194	39	respective	respective	ADJ
app01-8386	194	40	quantities	quantity	NOUN
app01-8386	194	41	well	well	ADV
app01-8386	194	42	.	.	PUNCT
app01-8386	195	1	5	5	X
app01-8386	195	2	.	.	X
app01-8386	195	3	conclusions	conclusion	NOUN
app01-8386	195	4	and	and	CCONJ
app01-8386	195	5	outlook	outlook	VERB
app01-8386	195	6	this	this	DET
app01-8386	195	7	paper	paper	NOUN
app01-8386	195	8	presented	present	VERB
app01-8386	195	9	intermediate	intermediate	ADJ
app01-8386	195	10	results	result	NOUN
app01-8386	195	11	of	of	ADP
app01-8386	195	12	the	the	DET
app01-8386	195	13	first	first	ADJ
app01-8386	195	14	phase	phase	NOUN
app01-8386	195	15	of	of	ADP
app01-8386	195	16	a	a	DET
app01-8386	195	17	two	two	NUM
app01-8386	195	18	-	-	PUNCT
app01-8386	195	19	stage	stage	NOUN
app01-8386	195	20	research	research	NOUN
app01-8386	195	21	project	project	NOUN
app01-8386	195	22	conducted	conduct	VERB
app01-8386	195	23	currently	currently	ADV
app01-8386	195	24	at	at	ADP
app01-8386	195	25	eth	eth	PROPN
app01-8386	195	26	zürich	zürich	PROPN
app01-8386	195	27	.	.	PUNCT
app01-8386	196	1	it	it	PRON
app01-8386	196	2	reports	report	VERB
app01-8386	196	3	on	on	ADP
app01-8386	196	4	calibrating	calibrate	VERB
app01-8386	196	5	aibased	aibased	ADJ
app01-8386	196	6	surrogates	surrogate	NOUN
app01-8386	196	7	for	for	ADP
app01-8386	196	8	a	a	DET
app01-8386	196	9	highly	highly	ADV
app01-8386	196	10	nonlinear	nonlinear	ADJ
app01-8386	196	11	reinforced	reinforce	VERB
app01-8386	196	12	concrete	concrete	ADJ
app01-8386	196	13	plate	plate	NOUN
app01-8386	196	14	and	and	CCONJ
app01-8386	196	15	shell	shell	ADJ
app01-8386	196	16	model	model	NOUN
app01-8386	196	17	upon	upon	SCONJ
app01-8386	196	18	the	the	DET
app01-8386	196	19	cmm	cmm	NOUN
app01-8386	196	20	.	.	PUNCT
app01-8386	197	1	all	all	DET
app01-8386	197	2	three	three	NUM
app01-8386	197	3	ai	ai	NOUN
app01-8386	197	4	algorithms	algorithm	NOUN
app01-8386	197	5	have	have	AUX
app01-8386	197	6	proven	prove	VERB
app01-8386	197	7	to	to	PART
app01-8386	197	8	furnish	furnish	VERB
app01-8386	197	9	as	as	ADP
app01-8386	197	10	valid	valid	ADJ
app01-8386	197	11	candidates	candidate	NOUN
app01-8386	197	12	for	for	ADP
app01-8386	197	13	surrogate	surrogate	ADJ
app01-8386	197	14	models	model	NOUN
app01-8386	197	15	to	to	PART
app01-8386	197	16	predict	predict	VERB
app01-8386	197	17	the	the	DET
app01-8386	197	18	stress	stress	NOUN
app01-8386	197	19	and	and	CCONJ
app01-8386	197	20	stiffness	stiffness	ADJ
app01-8386	197	21	tensors	tensor	NOUN
app01-8386	197	22	used	use	VERB
app01-8386	197	23	within	within	ADP
app01-8386	197	24	a	a	DET
app01-8386	197	25	fem	fem	NOUN
app01-8386	197	26	.	.	PUNCT
app01-8386	198	1	the	the	DET
app01-8386	198	2	datadriven	datadriven	ADJ
app01-8386	198	3	knn	knn	PROPN
app01-8386	198	4	algorithm	algorithm	PROPN
app01-8386	198	5	performed	perform	VERB
app01-8386	198	6	slightly	slightly	ADV
app01-8386	198	7	better	well	ADV
app01-8386	198	8	that	that	SCONJ
app01-8386	198	9	the	the	DET
app01-8386	198	10	lgbm	lgbm	ADJ
app01-8386	198	11	and	and	CCONJ
app01-8386	198	12	resnet	resnet	ADJ
app01-8386	198	13	model	model	NOUN
app01-8386	198	14	for	for	ADP
app01-8386	198	15	prediction	prediction	NOUN
app01-8386	198	16	standard	standard	ADJ
app01-8386	198	17	deviation	deviation	NOUN
app01-8386	198	18	and	and	CCONJ
app01-8386	198	19	rmse	rmse	NOUN
app01-8386	198	20	,	,	PUNCT
app01-8386	198	21	whereas	whereas	SCONJ
app01-8386	198	22	on	on	ADP
app01-8386	198	23	average	average	ADJ
app01-8386	198	24	all	all	DET
app01-8386	198	25	models	model	NOUN
app01-8386	198	26	show	show	VERB
app01-8386	198	27	almost	almost	ADV
app01-8386	198	28	full	full	ADJ
app01-8386	198	29	correlation	correlation	NOUN
app01-8386	198	30	.	.	PUNCT
app01-8386	199	1	future	future	ADJ
app01-8386	199	2	research	research	NOUN
app01-8386	199	3	is	be	AUX
app01-8386	199	4	concerned	concern	VERB
app01-8386	199	5	with	with	ADP
app01-8386	199	6	further	far	ADV
app01-8386	199	7	improving	improve	VERB
app01-8386	199	8	predictive	predictive	ADJ
app01-8386	199	9	capabilities	capability	NOUN
app01-8386	199	10	by	by	ADP
app01-8386	199	11	training	train	VERB
app01-8386	199	12	an	an	DET
app01-8386	199	13	ensemble	ensemble	ADJ
app01-8386	199	14	model	model	NOUN
app01-8386	199	15	using	use	VERB
app01-8386	199	16	the	the	DET
app01-8386	199	17	knn	knn	PROPN
app01-8386	199	18	,	,	PUNCT
app01-8386	199	19	resnet	resnet	NOUN
app01-8386	199	20	and	and	CCONJ
app01-8386	199	21	lgbm	lgbm	ADJ
app01-8386	199	22	models	model	NOUN
app01-8386	199	23	.	.	PUNCT
app01-8386	200	1	finally	finally	ADV
app01-8386	200	2	,	,	PUNCT
app01-8386	200	3	the	the	DET
app01-8386	200	4	non	non	ADJ
app01-8386	200	5	-	-	ADJ
app01-8386	200	6	intrusive	intrusive	ADJ
app01-8386	200	7	verification	verification	NOUN
app01-8386	200	8	analysis	analysis	NOUN
app01-8386	200	9	of	of	ADP
app01-8386	200	10	the	the	DET
app01-8386	200	11	ansys	ansys	PROPN
app01-8386	200	12	user	user	PROPN
app01-8386	200	13	-	-	PUNCT
app01-8386	200	14	mat	mat	NOUN
app01-8386	200	15	by	by	ADP
app01-8386	200	16	ai	ai	VERB
app01-8386	200	17	surrogate	surrogate	ADJ
app01-8386	200	18	modelling	modelling	NOUN
app01-8386	200	19	will	will	AUX
app01-8386	200	20	shed	shed	VERB
app01-8386	200	21	light	light	NOUN
app01-8386	200	22	on	on	ADP
app01-8386	200	23	generalisation	generalisation	NOUN
app01-8386	200	24	of	of	ADP
app01-8386	200	25	this	this	DET
app01-8386	200	26	idea	idea	NOUN
app01-8386	200	27	of	of	ADP
app01-8386	200	28	physics	physics	NOUN
app01-8386	200	29	informed	inform	VERB
app01-8386	200	30	ml	ml	NOUN
app01-8386	200	31	[	[	X
app01-8386	200	32	24	24	NUM
app01-8386	200	33	]	]	PUNCT
app01-8386	200	34	.	.	PUNCT
app01-8386	201	1	acknowledgements	acknowledgement	NOUN
app01-8386	201	2	the	the	DET
app01-8386	201	3	authors	author	NOUN
app01-8386	201	4	would	would	AUX
app01-8386	201	5	like	like	VERB
app01-8386	201	6	to	to	PART
app01-8386	201	7	acknowledge	acknowledge	VERB
app01-8386	201	8	the	the	DET
app01-8386	201	9	facilities	facility	NOUN
app01-8386	201	10	at	at	ADP
app01-8386	201	11	eth	eth	PROPN
app01-8386	201	12	zürich	zürich	PROPN
app01-8386	201	13	as	as	ADV
app01-8386	201	14	well	well	ADV
app01-8386	201	15	as	as	ADP
app01-8386	201	16	the	the	DET
app01-8386	201	17	design++	design++	ADJ
app01-8386	201	18	resp	resp	NOUN
app01-8386	201	19	.	.	PUNCT
app01-8386	202	1	immersive	immersive	ADJ
app01-8386	202	2	design	design	NOUN
app01-8386	202	3	lab	lab	NOUN
app01-8386	202	4	for	for	ADP
app01-8386	202	5	providing	provide	VERB
app01-8386	202	6	computational	computational	ADJ
app01-8386	202	7	resources	resource	NOUN
app01-8386	202	8	for	for	ADP
app01-8386	202	9	the	the	DET
app01-8386	202	10	machine	machine	NOUN
app01-8386	202	11	and	and	CCONJ
app01-8386	202	12	deep	deep	ADJ
app01-8386	202	13	learning	learn	VERB
app01-8386	202	14	parts	part	NOUN
app01-8386	202	15	of	of	ADP
app01-8386	202	16	this	this	DET
app01-8386	202	17	research	research	NOUN
app01-8386	202	18	project	project	NOUN
app01-8386	202	19	.	.	PUNCT
app01-8386	203	1	this	this	DET
app01-8386	203	2	research	research	NOUN
app01-8386	203	3	was	be	AUX
app01-8386	203	4	funded	fund	VERB
app01-8386	203	5	through	through	ADP
app01-8386	203	6	the	the	DET
app01-8386	203	7	eth	eth	PROPN
app01-8386	203	8	foundation	foundation	NOUN
app01-8386	203	9	grant	grant	VERB
app01-8386	203	10	no	no	NOUN
app01-8386	203	11	.	.	PUNCT
app01-8386	204	1	2020	2020	NUM
app01-8386	204	2	-	-	PUNCT
app01-8386	204	3	hs-388	hs-388	X
app01-8386	204	4	(	(	PUNCT
app01-8386	204	5	provided	provide	VERB
app01-8386	204	6	by	by	ADP
app01-8386	204	7	kollbrunner	kollbrunner	NOUN
app01-8386	204	8	/	/	SYM
app01-8386	204	9	rodio	rodio	NOUN
app01-8386	204	10	)	)	PUNCT
app01-8386	204	11	.	.	PUNCT
app01-8386	205	1	references	reference	NOUN
app01-8386	205	2	[	[	X
app01-8386	205	3	1	1	NUM
app01-8386	205	4	]	]	PUNCT
app01-8386	205	5	m.	m.	PROPN
app01-8386	205	6	kraus	kraus	PROPN
app01-8386	205	7	,	,	PUNCT
app01-8386	205	8	w.	w.	PROPN
app01-8386	205	9	kaufmann	kaufmann	PROPN
app01-8386	205	10	,	,	PUNCT
app01-8386	205	11	k.	k.	PROPN
app01-8386	205	12	thoma	thoma	PROPN
app01-8386	205	13	.	.	PUNCT
app01-8386	206	1	(	(	PUNCT
app01-8386	206	2	research	research	NOUN
app01-8386	206	3	project	project	NOUN
app01-8386	206	4	):	):	PUNCT
app01-8386	206	5	ki	ki	PROPN
app01-8386	206	6	-	-	PUNCT
app01-8386	206	7	basierte	basierte	NOUN
app01-8386	206	8	analyse	analyse	PROPN
app01-8386	206	9	und	und	PROPN
app01-8386	206	10	optimierung	optimierung	PROPN
app01-8386	206	11	von	von	PROPN
app01-8386	206	12	betonstrukturen	betonstrukturen	PROPN
app01-8386	206	13	,	,	PUNCT
app01-8386	206	14	2020	2020	NUM
app01-8386	206	15	.	.	PUNCT
app01-8386	207	1	[	[	X
app01-8386	207	2	2	2	NUM
app01-8386	207	3	]	]	PUNCT
app01-8386	207	4	m.	m.	NOUN
app01-8386	207	5	a.	a.	PROPN
app01-8386	207	6	kraus	kraus	PROPN
app01-8386	207	7	,	,	PUNCT
app01-8386	207	8	m.	m.	PROPN
app01-8386	207	9	drass	drass	PROPN
app01-8386	207	10	,	,	PUNCT
app01-8386	207	11	b.	b.	PROPN
app01-8386	207	12	hörsch	hörsch	PROPN
app01-8386	207	13	,	,	PUNCT
app01-8386	207	14	et	et	PROPN
app01-8386	207	15	al	al	PROPN
app01-8386	207	16	.	.	PROPN
app01-8386	207	17	künstliche	künstliche	PROPN
app01-8386	207	18	intelligenz	intelligenz	PROPN
app01-8386	207	19	multiskalen	multiskalen	PROPN
app01-8386	207	20	und	und	PROPN
app01-8386	207	21	cross	cross	ADJ
app01-8386	207	22	-	-	ADJ
app01-8386	207	23	domänen	domänen	ADJ
app01-8386	207	24	synergien	synergien	PROPN
app01-8386	207	25	von	von	PROPN
app01-8386	207	26	raumfahrt	raumfahrt	PROPN
app01-8386	207	27	und	und	VERB
app01-8386	207	28	bauwesen	bauwesen	VERB
app01-8386	207	29	.	.	PUNCT
app01-8386	208	1	in	in	ADP
app01-8386	208	2	k.	k.	PROPN
app01-8386	208	3	bergmeister	bergmeister	PROPN
app01-8386	208	4	,	,	PUNCT
app01-8386	208	5	f.	f.	PROPN
app01-8386	208	6	fingerloos	fingerloos	PROPN
app01-8386	208	7	,	,	PUNCT
app01-8386	208	8	j.-d	j.-d	PROPN
app01-8386	208	9	.	.	PUNCT
app01-8386	209	1	wörner	wörner	NOUN
app01-8386	209	2	(	(	PUNCT
app01-8386	209	3	eds	ed	NOUN
app01-8386	209	4	.	.	PUNCT
app01-8386	209	5	)	)	PUNCT
app01-8386	209	6	,	,	PUNCT
app01-8386	209	7	beton	beton	PROPN
app01-8386	209	8	-	-	PUNCT
app01-8386	209	9	kalender	kalender	NOUN
app01-8386	209	10	.	.	PUNCT
app01-8386	210	1	john	john	PROPN
app01-8386	210	2	wiley	wiley	PROPN
app01-8386	210	3	&	&	CCONJ
app01-8386	210	4	sons	son	NOUN
app01-8386	210	5	,	,	PUNCT
app01-8386	210	6	schwerpunk	schwerpunk	NOUN
app01-8386	210	7	edn	edn	PROPN
app01-8386	210	8	.	.	PUNCT
app01-8386	210	9	,	,	PUNCT
app01-8386	210	10	2021	2021	NUM
app01-8386	210	11	.	.	PUNCT
app01-8386	211	1	[	[	X
app01-8386	211	2	3	3	X
app01-8386	211	3	]	]	PUNCT
app01-8386	211	4	k.	k.	PROPN
app01-8386	211	5	thoma	thoma	PROPN
app01-8386	211	6	,	,	PUNCT
app01-8386	211	7	p.	p.	NOUN
app01-8386	211	8	roos	roo	NOUN
app01-8386	211	9	,	,	PUNCT
app01-8386	211	10	m.	m.	PROPN
app01-8386	211	11	weber	weber	PROPN
app01-8386	211	12	.	.	PUNCT
app01-8386	211	13	finite	finite	PROPN
app01-8386	211	14	-	-	ADJ
app01-8386	211	15	elementeanalyse	elementeanalyse	PROPN
app01-8386	211	16	von	von	PROPN
app01-8386	211	17	stahlbetonbauteilen	stahlbetonbauteilen	VERB
app01-8386	212	1	i	i	PRON
app01-8386	212	2	m	m	PROPN
app01-8386	212	3	ebenen	ebenen	PROPN
app01-8386	212	4	spannungszustand	spannungszustand	NOUN
app01-8386	212	5	:	:	PUNCT
app01-8386	212	6	scheibenund	scheibenund	NOUN
app01-8386	212	7	plattenberechnungen	plattenberechnungen	PROPN
app01-8386	212	8	auf	auf	PROPN
app01-8386	212	9	der	der	PROPN
app01-8386	212	10	grundlage	grundlage	PROPN
app01-8386	212	11	des	des	PROPN
app01-8386	212	12	gerissenen	gerissenen	PROPN
app01-8386	212	13	scheibenmodells	scheibenmodells	PROPN
app01-8386	212	14	.	.	PUNCT
app01-8386	213	1	betonund	betonund	PROPN
app01-8386	213	2	stahlbetonbau	stahlbetonbau	VERB
app01-8386	213	3	109(4):275–283	109(4):275–283	NUM
app01-8386	213	4	,	,	PUNCT
app01-8386	213	5	2014	2014	NUM
app01-8386	213	6	.	.	PUNCT
app01-8386	214	1	https://doi.org/10.1002/best.201300087	https://doi.org/10.1002/best.201300087	X
app01-8386	214	2	.	.	PUNCT
app01-8386	215	1	[	[	X
app01-8386	215	2	4	4	X
app01-8386	215	3	]	]	PUNCT
app01-8386	215	4	k.	k.	PROPN
app01-8386	215	5	thoma	thoma	PROPN
app01-8386	215	6	,	,	PUNCT
app01-8386	215	7	p.	p.	NOUN
app01-8386	215	8	roos	roos	PROPN
app01-8386	215	9	,	,	PUNCT
app01-8386	215	10	g.	g.	PROPN
app01-8386	215	11	borkowski	borkowski	PROPN
app01-8386	215	12	.	.	PUNCT
app01-8386	216	1	finite	finite	PROPN
app01-8386	216	2	elemente	elemente	PROPN
app01-8386	216	3	analyse	analyse	PROPN
app01-8386	216	4	von	von	PROPN
app01-8386	216	5	stahlbetonplatten	stahlbetonplatten	PROPN
app01-8386	216	6	:	:	PUNCT
app01-8386	216	7	versuchsnachrechnungen	versuchsnachrechnungen	PROPN
app01-8386	216	8	von	von	PROPN
app01-8386	216	9	platten	platten	PROPN
app01-8386	216	10	mithilfe	mithilfe	PROPN
app01-8386	216	11	des	des	PROPN
app01-8386	216	12	gerissenen	gerissenen	PROPN
app01-8386	216	13	scheibenmodells	scheibenmodells	PROPN
app01-8386	216	14	.	.	PUNCT
app01-8386	217	1	betonund	betonund	PROPN
app01-8386	217	2	stahlbetonbau	stahlbetonbau	VERB
app01-8386	217	3	109(12):895–904	109(12):895–904	NUM
app01-8386	217	4	,	,	PUNCT
app01-8386	217	5	2014	2014	NUM
app01-8386	217	6	.	.	PUNCT
app01-8386	218	1	https://doi.org/10.1002/best.201400047	https://doi.org/10.1002/best.201400047	NOUN
app01-8386	218	2	.	.	PUNCT
app01-8386	219	1	[	[	X
app01-8386	219	2	5	5	NUM
app01-8386	219	3	]	]	PUNCT
app01-8386	219	4	k.	k.	PROPN
app01-8386	219	5	thoma	thoma	PROPN
app01-8386	219	6	.	.	PUNCT
app01-8386	220	1	finite	finite	PROPN
app01-8386	220	2	element	element	NOUN
app01-8386	220	3	analysis	analysis	NOUN
app01-8386	220	4	of	of	ADP
app01-8386	220	5	experimentally	experimentally	ADV
app01-8386	220	6	tested	test	VERB
app01-8386	220	7	rc	rc	PROPN
app01-8386	220	8	and	and	CCONJ
app01-8386	220	9	pc	pc	NOUN
app01-8386	220	10	beams	beam	NOUN
app01-8386	220	11	using	use	VERB
app01-8386	220	12	the	the	DET
app01-8386	220	13	cracked	crack	VERB
app01-8386	220	14	membrane	membrane	NOUN
app01-8386	220	15	model	model	NOUN
app01-8386	220	16	.	.	PUNCT
app01-8386	221	1	engineering	engineering	NOUN
app01-8386	221	2	structures	structure	NOUN
app01-8386	221	3	167:592–607	167:592–607	NUM
app01-8386	221	4	,	,	PUNCT
app01-8386	221	5	2018	2018	NUM
app01-8386	221	6	.	.	PUNCT
app01-8386	222	1	https://doi.org/10.1016/j.engstruct.2018.04.010	https://doi.org/10.1016/j.engstruct.2018.04.010	NOUN
app01-8386	222	2	.	.	PUNCT
app01-8386	223	1	[	[	X
app01-8386	223	2	6	6	NUM
app01-8386	223	3	]	]	PUNCT
app01-8386	223	4	j.	j.	PROPN
app01-8386	223	5	kollegger	kollegger	PROPN
app01-8386	223	6	.	.	PUNCT
app01-8386	224	1	algorithmus	algorithmus	PROPN
app01-8386	224	2	zur	zur	PROPN
app01-8386	224	3	bemessung	bemessung	PROPN
app01-8386	224	4	von	von	PROPN
app01-8386	224	5	flächentragwerkelementen	flächentragwerkelementen	VERB
app01-8386	224	6	unter	unter	PROPN
app01-8386	224	7	normalkraftund	normalkraftund	PROPN
app01-8386	224	8	momentenbeanspruchung	momentenbeanspruchung	PROPN
app01-8386	224	9	.	.	PUNCT
app01-8386	225	1	betonund	betonund	PROPN
app01-8386	225	2	stahlbetonbau	stahlbetonbau	VERB
app01-8386	225	3	86(5):114–119	86(5):114–119	PROPN
app01-8386	225	4	,	,	PUNCT
app01-8386	225	5	1991	1991	NUM
app01-8386	225	6	.	.	PUNCT
app01-8386	226	1	https://doi.org/10.1002/best.199100230	https://doi.org/10.1002/best.199100230	X
app01-8386	226	2	.	.	PUNCT
app01-8386	227	1	[	[	X
app01-8386	227	2	7	7	X
app01-8386	227	3	]	]	X
app01-8386	227	4	p.	p.	PROPN
app01-8386	227	5	marti	marti	PROPN
app01-8386	227	6	,	,	PUNCT
app01-8386	227	7	m.	m.	PROPN
app01-8386	227	8	alvarez	alvarez	PROPN
app01-8386	227	9	,	,	PUNCT
app01-8386	227	10	w.	w.	PROPN
app01-8386	227	11	kaufmann	kaufmann	PROPN
app01-8386	227	12	,	,	PUNCT
app01-8386	227	13	v.	v.	ADP
app01-8386	227	14	sigrist	sigrist	NOUN
app01-8386	227	15	.	.	PUNCT
app01-8386	228	1	tension	tension	NOUN
app01-8386	228	2	chord	chord	NOUN
app01-8386	228	3	model	model	NOUN
app01-8386	228	4	for	for	ADP
app01-8386	228	5	structural	structural	ADJ
app01-8386	228	6	concrete	concrete	NOUN
app01-8386	228	7	.	.	PUNCT
app01-8386	229	1	structural	structural	ADJ
app01-8386	229	2	engineering	engineering	NOUN
app01-8386	229	3	international	international	ADJ
app01-8386	229	4	:	:	PUNCT
app01-8386	229	5	journal	journal	NOUN
app01-8386	229	6	of	of	ADP
app01-8386	229	7	the	the	DET
app01-8386	229	8	international	international	ADJ
app01-8386	229	9	association	association	NOUN
app01-8386	229	10	for	for	ADP
app01-8386	229	11	bridge	bridge	NOUN
app01-8386	229	12	and	and	CCONJ
app01-8386	229	13	structural	structural	ADJ
app01-8386	229	14	engineering	engineering	NOUN
app01-8386	229	15	(	(	PUNCT
app01-8386	229	16	iabse	iabse	NOUN
app01-8386	229	17	)	)	PUNCT
app01-8386	229	18	8(4):287–298	8(4):287–298	NOUN
app01-8386	229	19	,	,	PUNCT
app01-8386	229	20	1998	1998	NUM
app01-8386	229	21	.	.	PUNCT
app01-8386	230	1	https://doi.org/10.2749/101686698780488875	https://doi.org/10.2749/101686698780488875	X
app01-8386	230	2	.	.	PUNCT
app01-8386	231	1	[	[	X
app01-8386	231	2	8	8	NUM
app01-8386	231	3	]	]	X
app01-8386	231	4	w.	w.	PROPN
app01-8386	231	5	kaufmann	kaufmann	PROPN
app01-8386	231	6	,	,	PUNCT
app01-8386	231	7	p.	p.	PROPN
app01-8386	231	8	marti	marti	PROPN
app01-8386	231	9	.	.	PUNCT
app01-8386	232	1	structural	structural	ADJ
app01-8386	232	2	concrete	concrete	NOUN
app01-8386	232	3	:	:	PUNCT
app01-8386	232	4	cracked	crack	VERB
app01-8386	232	5	membrane	membrane	NOUN
app01-8386	232	6	model	model	NOUN
app01-8386	232	7	.	.	PUNCT
app01-8386	233	1	journal	journal	PROPN
app01-8386	233	2	of	of	ADP
app01-8386	233	3	structural	structural	ADJ
app01-8386	233	4	engineering	engineering	NOUN
app01-8386	233	5	124(12):1467–1475	124(12):1467–1475	NUM
app01-8386	233	6	,	,	PUNCT
app01-8386	233	7	1998	1998	NUM
app01-8386	233	8	.	.	PUNCT
app01-8386	234	1	https://doi.org/10.1061/(asce)0733-9445	https://doi.org/10.1061/(asce)0733-9445	NOUN
app01-8386	234	2	(	(	PUNCT
app01-8386	234	3	1998)124:12(1467	1998)124:12(1467	NUM
app01-8386	234	4	)	)	PUNCT
app01-8386	234	5	.	.	PUNCT
app01-8386	235	1	[	[	X
app01-8386	235	2	9	9	NUM
app01-8386	235	3	]	]	PUNCT
app01-8386	235	4	m.	m.	NOUN
app01-8386	235	5	a.	a.	PROPN
app01-8386	235	6	kraus	kraus	PROPN
app01-8386	235	7	.	.	PUNCT
app01-8386	236	1	machine	machine	NOUN
app01-8386	236	2	learning	learn	VERB
app01-8386	236	3	techniques	technique	NOUN
app01-8386	236	4	for	for	ADP
app01-8386	236	5	the	the	DET
app01-8386	236	6	material	material	NOUN
app01-8386	236	7	parameter	parameter	NOUN
app01-8386	236	8	identification	identification	NOUN
app01-8386	236	9	of	of	ADP
app01-8386	236	10	laminated	laminated	ADJ
app01-8386	236	11	glass	glass	NOUN
app01-8386	236	12	in	in	ADP
app01-8386	236	13	the	the	DET
app01-8386	236	14	intact	intact	ADJ
app01-8386	236	15	and	and	CCONJ
app01-8386	236	16	post	post	ADJ
app01-8386	236	17	-	-	ADJ
app01-8386	236	18	fracture	fracture	ADJ
app01-8386	236	19	state	state	NOUN
app01-8386	236	20	.	.	PUNCT
app01-8386	237	1	ph.d	ph.d	PROPN
app01-8386	237	2	.	.	PUNCT
app01-8386	238	1	thesis	thesis	NOUN
app01-8386	238	2	,	,	PUNCT
app01-8386	238	3	universität	universität	ADJ
app01-8386	238	4	der	der	NOUN
app01-8386	238	5	bundeswehr	bundeswehr	NOUN
app01-8386	238	6	münchen	münchen	NOUN
app01-8386	238	7	,	,	PUNCT
app01-8386	238	8	2019	2019	NUM
app01-8386	238	9	.	.	PUNCT
app01-8386	239	1	[	[	X
app01-8386	239	2	10	10	NUM
app01-8386	239	3	]	]	X
app01-8386	239	4	e.	e.	PROPN
app01-8386	239	5	fix	fix	PROPN
app01-8386	239	6	,	,	PUNCT
app01-8386	239	7	j.	j.	PROPN
app01-8386	239	8	l.	l.	PROPN
app01-8386	239	9	hodges	hodges	PROPN
app01-8386	239	10	.	.	PUNCT
app01-8386	240	1	discriminatory	discriminatory	ADJ
app01-8386	240	2	analysis	analysis	NOUN
app01-8386	240	3	nonparametric	nonparametric	NOUN
app01-8386	240	4	discrimination	discrimination	NOUN
app01-8386	240	5	:	:	PUNCT
app01-8386	240	6	consistency	consistency	NOUN
app01-8386	240	7	properties	property	NOUN
app01-8386	240	8	.	.	PUNCT
app01-8386	241	1	international	international	ADJ
app01-8386	241	2	statistical	statistical	ADJ
app01-8386	241	3	review	review	NOUN
app01-8386	241	4	57:238	57:238	NUM
app01-8386	241	5	,	,	PUNCT
app01-8386	241	6	1989	1989	NUM
app01-8386	241	7	.	.	PUNCT
app01-8386	242	1	[	[	X
app01-8386	242	2	11	11	NUM
app01-8386	242	3	]	]	X
app01-8386	242	4	n.	n.	PROPN
app01-8386	242	5	s.	s.	PROPN
app01-8386	242	6	altman	altman	PROPN
app01-8386	242	7	.	.	PUNCT
app01-8386	243	1	an	an	DET
app01-8386	243	2	introduction	introduction	NOUN
app01-8386	243	3	to	to	ADP
app01-8386	243	4	kernel	kernel	PROPN
app01-8386	243	5	and	and	CCONJ
app01-8386	243	6	nearest	nearest	ADJ
app01-8386	243	7	-	-	PUNCT
app01-8386	243	8	neighbor	neighbor	NOUN
app01-8386	243	9	nonparametric	nonparametric	NOUN
app01-8386	243	10	regression	regression	NOUN
app01-8386	243	11	.	.	PUNCT
app01-8386	244	1	the	the	DET
app01-8386	244	2	american	american	PROPN
app01-8386	244	3	statistician	statistician	PROPN
app01-8386	244	4	46(3):175–185	46(3):175–185	PROPN
app01-8386	244	5	,	,	PUNCT
app01-8386	244	6	1992	1992	NUM
app01-8386	244	7	.	.	PUNCT
app01-8386	245	1	https://www.tandfonline.com/doi/pdf/10.1080/	https://www.tandfonline.com/doi/pdf/10.1080/	NOUN
app01-8386	245	2	00031305.1992.10475879	00031305.1992.10475879	NUM
app01-8386	245	3	https://doi.org/10.1080/00031305.1992.10475879	https://doi.org/10.1080/00031305.1992.10475879	PRON
app01-8386	245	4	.	.	PUNCT
app01-8386	246	1	[	[	X
app01-8386	246	2	12	12	NUM
app01-8386	246	3	]	]	X
app01-8386	246	4	g.	g.	PROPN
app01-8386	246	5	ke	ke	PROPN
app01-8386	246	6	,	,	PUNCT
app01-8386	246	7	q.	q.	PROPN
app01-8386	246	8	meng	meng	PROPN
app01-8386	246	9	,	,	PUNCT
app01-8386	246	10	t.	t.	PROPN
app01-8386	246	11	finley	finley	PROPN
app01-8386	246	12	,	,	PUNCT
app01-8386	246	13	et	et	PROPN
app01-8386	246	14	al	al	PROPN
app01-8386	246	15	.	.	PROPN
app01-8386	246	16	lightgbm	lightgbm	PROPN
app01-8386	246	17	:	:	PUNCT
app01-8386	246	18	a	a	DET
app01-8386	246	19	highly	highly	ADV
app01-8386	246	20	efficient	efficient	ADJ
app01-8386	246	21	gradient	gradient	NOUN
app01-8386	246	22	boosting	boost	VERB
app01-8386	246	23	decision	decision	NOUN
app01-8386	246	24	tree	tree	NOUN
app01-8386	246	25	.	.	PUNCT
app01-8386	247	1	in	in	ADP
app01-8386	247	2	i.	i.	PROPN
app01-8386	247	3	guyon	guyon	PROPN
app01-8386	247	4	,	,	PUNCT
app01-8386	247	5	u.	u.	PROPN
app01-8386	247	6	v.	v.	PROPN
app01-8386	247	7	luxburg	luxburg	PROPN
app01-8386	247	8	,	,	PUNCT
app01-8386	247	9	s.	s.	PROPN
app01-8386	247	10	bengio	bengio	PROPN
app01-8386	247	11	,	,	PUNCT
app01-8386	247	12	et	et	PROPN
app01-8386	247	13	al	al	PROPN
app01-8386	247	14	.	.	PUNCT
app01-8386	248	1	(	(	PUNCT
app01-8386	248	2	eds	ed	NOUN
app01-8386	248	3	.	.	PUNCT
app01-8386	248	4	)	)	PUNCT
app01-8386	249	1	,	,	PUNCT
app01-8386	249	2	advances	advance	NOUN
app01-8386	249	3	in	in	ADP
app01-8386	249	4	neural	neural	ADJ
app01-8386	249	5	information	information	NOUN
app01-8386	249	6	processing	processing	NOUN
app01-8386	249	7	systems	system	NOUN
app01-8386	249	8	,	,	PUNCT
app01-8386	249	9	vol	vol	NOUN
app01-8386	249	10	.	.	PROPN
app01-8386	249	11	30	30	NUM
app01-8386	249	12	.	.	PUNCT
app01-8386	250	1	curran	curran	PROPN
app01-8386	250	2	associates	associates	PROPN
app01-8386	250	3	,	,	PUNCT
app01-8386	250	4	inc	inc	PROPN
app01-8386	250	5	.	.	PROPN
app01-8386	250	6	,	,	PUNCT
app01-8386	250	7	2017	2017	NUM
app01-8386	250	8	.	.	PUNCT
app01-8386	251	1	[	[	X
app01-8386	251	2	13	13	NUM
app01-8386	251	3	]	]	X
app01-8386	251	4	y.	y.	NOUN
app01-8386	251	5	lecun	lecun	PROPN
app01-8386	251	6	,	,	PUNCT
app01-8386	251	7	y.	y.	PROPN
app01-8386	251	8	bengio	bengio	PROPN
app01-8386	251	9	,	,	PUNCT
app01-8386	251	10	g.	g.	PROPN
app01-8386	251	11	hinton	hinton	PROPN
app01-8386	251	12	.	.	PUNCT
app01-8386	252	1	deep	deep	ADJ
app01-8386	252	2	learning	learning	NOUN
app01-8386	252	3	.	.	PUNCT
app01-8386	253	1	nature	nature	NOUN
app01-8386	253	2	521(7553):436–444	521(7553):436–444	NUM
app01-8386	253	3	,	,	PUNCT
app01-8386	253	4	2015	2015	NUM
app01-8386	253	5	.	.	PUNCT
app01-8386	254	1	[	[	X
app01-8386	254	2	14	14	NUM
app01-8386	254	3	]	]	PUNCT
app01-8386	254	4	k.	k.	PROPN
app01-8386	254	5	hornik	hornik	PROPN
app01-8386	254	6	,	,	PUNCT
app01-8386	254	7	m.	m.	NOUN
app01-8386	254	8	stinchcombe	stinchcombe	PROPN
app01-8386	254	9	,	,	PUNCT
app01-8386	254	10	h.	h.	PROPN
app01-8386	254	11	white	white	PROPN
app01-8386	254	12	.	.	PUNCT
app01-8386	255	1	universal	universal	ADJ
app01-8386	255	2	approximation	approximation	NOUN
app01-8386	255	3	of	of	ADP
app01-8386	255	4	an	an	DET
app01-8386	255	5	unknown	unknown	ADJ
app01-8386	255	6	mapping	mapping	NOUN
app01-8386	255	7	and	and	CCONJ
app01-8386	255	8	its	its	PRON
app01-8386	255	9	derivatives	derivative	NOUN
app01-8386	255	10	using	use	VERB
app01-8386	255	11	multilayer	multilayer	ADJ
app01-8386	255	12	feedforward	feedforward	NOUN
app01-8386	255	13	networks	network	NOUN
app01-8386	255	14	.	.	PUNCT
app01-8386	256	1	neural	neural	ADJ
app01-8386	256	2	networks	network	NOUN
app01-8386	256	3	3(5):551–560	3(5):551–560	PROPN
app01-8386	256	4	,	,	PUNCT
app01-8386	256	5	1990	1990	NUM
app01-8386	256	6	.	.	PUNCT
app01-8386	257	1	https://doi.org/10.1016/0893-6080(90)90005-6	https://doi.org/10.1016/0893-6080(90)90005-6	ADV
app01-8386	257	2	.	.	PUNCT
app01-8386	258	1	[	[	X
app01-8386	258	2	15	15	NUM
app01-8386	258	3	]	]	X
app01-8386	258	4	a.	a.	PROPN
app01-8386	258	5	emin	emin	PROPN
app01-8386	258	6	orhan	orhan	PROPN
app01-8386	258	7	,	,	PUNCT
app01-8386	258	8	x.	x.	PROPN
app01-8386	258	9	pitkow	pitkow	PROPN
app01-8386	258	10	.	.	PUNCT
app01-8386	259	1	skip	skip	ADJ
app01-8386	259	2	connections	connection	NOUN
app01-8386	259	3	eliminate	eliminate	VERB
app01-8386	259	4	singularities	singularity	NOUN
app01-8386	259	5	.	.	PUNCT
app01-8386	260	1	arxiv	arxiv	PROPN
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app01-8386	260	8	.	.	PUNCT
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app01-8386	261	2	.	.	PUNCT
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app01-8386	264	8	.	.	PUNCT
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app01-8386	265	2	.	.	PUNCT
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app01-8386	268	3	]	]	PUNCT
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app01-8386	268	6	.	.	PUNCT
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app01-8386	269	7	.	.	PUNCT
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app01-8386	270	6	,	,	PUNCT
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app01-8386	270	8	.	.	PUNCT
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app01-8386	271	2	.	.	PUNCT
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app01-8386	272	5	https://doi.org/10.1002/best.199100230	https://doi.org/10.1002/best.199100230	NUM
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app01-8386	272	9	1998)124:12(1467	1998)124:12(1467	NUM
app01-8386	272	10	)	)	PUNCT
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app01-8386	272	12	(	(	PUNCT
app01-8386	272	13	1998)124:12(1467	1998)124:12(1467	NUM
app01-8386	272	14	)	)	PUNCT
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app01-8386	272	16	https://www.tandfonline.com/doi/pdf/10.1080/00031305.1992.10475879	https://www.tandfonline.com/doi/pdf/10.1080/00031305.1992.10475879	PUNCT
app01-8386	272	17	https://doi.org/10.1080/00031305.1992.10475879	https://doi.org/10.1080/00031305.1992.10475879	VERB
app01-8386	272	18	https://doi.org/10.1016/0893-6080(90)90005-6	https://doi.org/10.1016/0893-6080(90)90005-6	PROPN
app01-8386	272	19	1701.09175	1701.09175	NUM
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app01-8386	272	26	r.	r.	PROPN
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app01-8386	272	28	,	,	PUNCT
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app01-8386	272	34	acta	acta	PROPN
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app01-8386	272	36	ctu	ctu	NOUN
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app01-8386	272	38	[	[	X
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app01-8386	272	40	]	]	PUNCT
app01-8386	272	41	j.	j.	PROPN
app01-8386	272	42	snoek	snoek	PROPN
app01-8386	272	43	,	,	PUNCT
app01-8386	272	44	h.	h.	PROPN
app01-8386	272	45	larochelle	larochelle	PROPN
app01-8386	272	46	,	,	PUNCT
app01-8386	272	47	r.	r.	PROPN
app01-8386	272	48	p.	p.	PROPN
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app01-8386	272	50	.	.	PUNCT
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app01-8386	273	2	bayesian	bayesian	NOUN
app01-8386	273	3	optimization	optimization	NOUN
app01-8386	273	4	of	of	ADP
app01-8386	273	5	machine	machine	NOUN
app01-8386	273	6	learning	learn	VERB
app01-8386	273	7	algorithms	algorithm	NOUN
app01-8386	273	8	.	.	PUNCT
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app01-8386	274	3	of	of	ADP
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app01-8386	275	2	.	.	PUNCT
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app01-8386	276	14	.	.	PUNCT
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app01-8386	277	2	20	20	NUM
app01-8386	277	3	]	]	PUNCT
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app01-8386	277	6	.	.	PUNCT
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app01-8386	278	2	optimization	optimization	NOUN
app01-8386	278	3	:	:	PUNCT
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app01-8386	278	5	source	source	NOUN
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app01-8386	278	9	tool	tool	NOUN
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app01-8386	279	12	.	.	PUNCT
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app01-8386	280	2	application	application	NOUN
app01-8386	280	3	of	of	ADP
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app01-8386	280	5	methods	method	NOUN
app01-8386	280	6	for	for	ADP
app01-8386	280	7	seeking	seek	VERB
app01-8386	280	8	the	the	DET
app01-8386	280	9	extremum	extremum	ADJ
app01-8386	280	10	,	,	PUNCT
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app01-8386	281	2	.	.	PUNCT
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app01-8386	293	65	3.3	3.3	NUM
app01-8386	293	66	resnet	resnet	NOUN
app01-8386	293	67	model	model	NOUN
app01-8386	293	68	results	result	VERB
app01-8386	293	69	3.4	3.4	NUM
app01-8386	293	70	overall	overall	ADJ
app01-8386	293	71	model	model	NOUN
app01-8386	293	72	comparison	comparison	NOUN
app01-8386	293	73	results	result	VERB
app01-8386	293	74	4	4	NUM
app01-8386	293	75	discussion	discussion	NOUN
app01-8386	293	76	5	5	NUM
app01-8386	293	77	conclusions	conclusion	NOUN
app01-8386	293	78	and	and	CCONJ
app01-8386	293	79	outlook	outlook	NOUN
app01-8386	293	80	acknowledgements	acknowledgement	NOUN
app01-8386	293	81	references	reference	NOUN