id	sid	tid	token	lemma	pos
gc-55	1	1	cvetkovic.indd	cvetkovic.indd	PROPN
gc-55	1	2	115	115	NUM
gc-55	1	3	�	�	PROPN
gc-55	1	4	ab	ab	PROPN
gc-55	1	5	stra	stra	PROPN
gc-55	1	6	ct	ct	PROPN
gc-55	1	7	the	the	DET
gc-55	1	8	kloštar	kloštar	NOUN
gc-55	1	9	oil	oil	PROPN
gc-55	1	10	fi	fi	NOUN
gc-55	1	11	eld	eld	NOUN
gc-55	1	12	is	be	AUX
gc-55	1	13	situated	situate	VERB
gc-55	1	14	in	in	ADP
gc-55	1	15	the	the	DET
gc-55	1	16	northern	northern	ADJ
gc-55	1	17	part	part	NOUN
gc-55	1	18	of	of	ADP
gc-55	1	19	the	the	DET
gc-55	1	20	sava	sava	PROPN
gc-55	1	21	depression	depression	NOUN
gc-55	1	22	within	within	ADP
gc-55	1	23	the	the	DET
gc-55	1	24	croatian	croatian	ADJ
gc-55	1	25	part	part	NOUN
gc-55	1	26	of	of	ADP
gc-55	1	27	the	the	DET
gc-55	1	28	pannonian	pannonian	ADJ
gc-55	1	29	basin	basin	NOUN
gc-55	1	30	.	.	PUNCT
gc-55	2	1	the	the	DET
gc-55	2	2	major	major	ADJ
gc-55	2	3	petroleum	petroleum	NOUN
gc-55	2	4	reserves	reserve	NOUN
gc-55	2	5	are	be	AUX
gc-55	2	6	confi	confi	ADJ
gc-55	2	7	ned	ned	ADJ
gc-55	2	8	to	to	ADP
gc-55	2	9	miocene	miocene	ADJ
gc-55	2	10	sandstones	sandstone	NOUN
gc-55	2	11	that	that	PRON
gc-55	2	12	comprise	comprise	VERB
gc-55	2	13	two	two	NUM
gc-55	2	14	production	production	NOUN
gc-55	2	15	units	unit	NOUN
gc-55	2	16	:	:	PUNCT
gc-55	2	17	the	the	DET
gc-55	2	18	lower	low	ADJ
gc-55	2	19	pontian	pontian	ADJ
gc-55	2	20	i	i	PRON
gc-55	2	21	sandstone	sandstone	NOUN
gc-55	2	22	series	series	NOUN
gc-55	2	23	and	and	CCONJ
gc-55	2	24	the	the	DET
gc-55	2	25	upper	upper	ADJ
gc-55	2	26	pannonian	pannonian	PROPN
gc-55	2	27	ii	ii	PROPN
gc-55	2	28	sandstone	sandstone	NOUN
gc-55	2	29	series	series	NOUN
gc-55	2	30	.	.	PUNCT
gc-55	3	1	we	we	PRON
gc-55	3	2	used	use	VERB
gc-55	3	3	well	well	NOUN
gc-55	3	4	logs	log	NOUN
gc-55	3	5	from	from	ADP
gc-55	3	6	two	two	NUM
gc-55	3	7	wells	well	NOUN
gc-55	3	8	through	through	ADP
gc-55	3	9	these	these	DET
gc-55	3	10	sandstones	sandstone	NOUN
gc-55	3	11	as	as	ADP
gc-55	3	12	input	input	NOUN
gc-55	3	13	data	datum	NOUN
gc-55	3	14	in	in	ADP
gc-55	3	15	the	the	DET
gc-55	3	16	neural	neural	ADJ
gc-55	3	17	network	network	NOUN
gc-55	3	18	analysis	analysis	NOUN
gc-55	3	19	,	,	PUNCT
gc-55	3	20	and	and	CCONJ
gc-55	3	21	used	use	VERB
gc-55	3	22	spontaneous	spontaneous	ADJ
gc-55	3	23	potential	potential	NOUN
gc-55	3	24	and	and	CCONJ
gc-55	3	25	resistivity	resistivity	NOUN
gc-55	3	26	logs	log	NOUN
gc-55	3	27	(	(	PUNCT
gc-55	3	28	r16	r16	NOUN
gc-55	3	29	and	and	CCONJ
gc-55	3	30	r64	r64	NOUN
gc-55	3	31	)	)	PUNCT
gc-55	3	32	as	as	ADP
gc-55	3	33	the	the	DET
gc-55	3	34	input	input	NOUN
gc-55	3	35	in	in	ADP
gc-55	3	36	network	network	NOUN
gc-55	3	37	training	training	NOUN
gc-55	3	38	.	.	PUNCT
gc-55	4	1	the	the	DET
gc-55	4	2	fi	fi	NOUN
gc-55	4	3	rst	rst	NOUN
gc-55	4	4	analysis	analysis	NOUN
gc-55	4	5	included	include	VERB
gc-55	4	6	prediction	prediction	NOUN
gc-55	4	7	of	of	ADP
gc-55	4	8	lithology	lithology	NOUN
gc-55	4	9	,	,	PUNCT
gc-55	4	10	which	which	PRON
gc-55	4	11	was	be	AUX
gc-55	4	12	defi	defi	NOUN
gc-55	4	13	ned	ned	NOUN
gc-55	4	14	as	as	ADP
gc-55	4	15	either	either	CCONJ
gc-55	4	16	sandstone	sandstone	NOUN
gc-55	4	17	or	or	CCONJ
gc-55	4	18	marl	marl	NOUN
gc-55	4	19	.	.	PUNCT
gc-55	5	1	these	these	DET
gc-55	5	2	two	two	NUM
gc-55	5	3	rock	rock	NOUN
gc-55	5	4	types	type	NOUN
gc-55	5	5	were	be	AUX
gc-55	5	6	assigned	assign	VERB
gc-55	5	7	categorical	categorical	ADJ
gc-55	5	8	values	value	NOUN
gc-55	5	9	of	of	ADP
gc-55	5	10	1	1	NUM
gc-55	5	11	or	or	CCONJ
gc-55	5	12	0	0	NUM
gc-55	5	13	which	which	PRON
gc-55	5	14	were	be	AUX
gc-55	5	15	then	then	ADV
gc-55	5	16	used	use	VERB
gc-55	5	17	in	in	ADP
gc-55	5	18	numerical	numerical	ADJ
gc-55	5	19	analysis	analysis	NOUN
gc-55	5	20	.	.	PUNCT
gc-55	6	1	the	the	DET
gc-55	6	2	neural	neural	ADJ
gc-55	6	3	network	network	NOUN
gc-55	6	4	was	be	AUX
gc-55	6	5	also	also	ADV
gc-55	6	6	used	use	VERB
gc-55	6	7	to	to	PART
gc-55	6	8	predict	predict	VERB
gc-55	6	9	hydrocarbon	hydrocarbon	NOUN
gc-55	6	10	saturation	saturation	NOUN
gc-55	6	11	in	in	ADP
gc-55	6	12	selected	select	VERB
gc-55	6	13	wells	well	NOUN
gc-55	6	14	.	.	PUNCT
gc-55	7	1	the	the	DET
gc-55	7	2	input	input	NOUN
gc-55	7	3	dataset	dataset	NOUN
gc-55	7	4	was	be	AUX
gc-55	7	5	extended	extend	VERB
gc-55	7	6	to	to	ADP
gc-55	7	7	depth	depth	NOUN
gc-55	7	8	and	and	CCONJ
gc-55	7	9	categorical	categorical	ADJ
gc-55	7	10	lithology	lithology	NOUN
gc-55	7	11	.	.	PUNCT
gc-55	8	1	the	the	DET
gc-55	8	2	prediction	prediction	NOUN
gc-55	8	3	results	result	NOUN
gc-55	8	4	were	be	AUX
gc-55	8	5	excellent	excellent	ADJ
gc-55	8	6	,	,	PUNCT
gc-55	8	7	because	because	SCONJ
gc-55	8	8	the	the	DET
gc-55	8	9	training	training	NOUN
gc-55	8	10	and	and	CCONJ
gc-55	8	11	prediction	prediction	NOUN
gc-55	8	12	dataset	dataset	NOUN
gc-55	8	13	showed	show	VERB
gc-55	8	14	little	little	ADJ
gc-55	8	15	disagreement	disagreement	NOUN
gc-55	8	16	between	between	ADP
gc-55	8	17	the	the	DET
gc-55	8	18	true	true	ADJ
gc-55	8	19	and	and	CCONJ
gc-55	8	20	predicted	predict	VERB
gc-55	8	21	values	value	NOUN
gc-55	8	22	.	.	PUNCT
gc-55	9	1	at	at	ADP
gc-55	9	2	present	present	ADJ
gc-55	9	3	,	,	PUNCT
gc-55	9	4	this	this	DET
gc-55	9	5	study	study	NOUN
gc-55	9	6	represents	represent	VERB
gc-55	9	7	the	the	DET
gc-55	9	8	best	good	ADJ
gc-55	9	9	and	and	CCONJ
gc-55	9	10	most	most	ADV
gc-55	9	11	useful	useful	ADJ
gc-55	9	12	application	application	NOUN
gc-55	9	13	of	of	ADP
gc-55	9	14	neural	neural	ADJ
gc-55	9	15	networks	network	NOUN
gc-55	9	16	in	in	ADP
gc-55	9	17	the	the	DET
gc-55	9	18	croatian	croatian	ADJ
gc-55	9	19	part	part	NOUN
gc-55	9	20	of	of	ADP
gc-55	9	21	the	the	DET
gc-55	9	22	pannonian	pannonian	ADJ
gc-55	9	23	basin	basin	NOUN
gc-55	9	24	.	.	PUNCT
gc-55	10	1	keywords	keyword	NOUN
gc-55	10	2	:	:	PUNCT
gc-55	10	3	kloštar	kloštar	PROPN
gc-55	10	4	fi	fi	PROPN
gc-55	10	5	eld	eld	PROPN
gc-55	10	6	,	,	PUNCT
gc-55	10	7	neural	neural	ADJ
gc-55	10	8	network	network	NOUN
gc-55	10	9	,	,	PUNCT
gc-55	10	10	prediction	prediction	NOUN
gc-55	10	11	,	,	PUNCT
gc-55	10	12	sandstone	sandstone	NOUN
gc-55	10	13	,	,	PUNCT
gc-55	10	14	hydrocarbon	hydrocarbon	NOUN
gc-55	10	15	saturation	saturation	NOUN
gc-55	10	16	,	,	PUNCT
gc-55	10	17	croatia	croatia	PROPN
gc-55	10	18	application	application	NOUN
gc-55	10	19	of	of	ADP
gc-55	10	20	neural	neural	ADJ
gc-55	10	21	networks	network	NOUN
gc-55	10	22	in	in	ADP
gc-55	10	23	petroleum	petroleum	NOUN
gc-55	10	24	reservoir	reservoir	NOUN
gc-55	10	25	lithology	lithology	NOUN
gc-55	10	26	and	and	CCONJ
gc-55	10	27	saturation	saturation	NOUN
gc-55	10	28	prediction	prediction	NOUN
gc-55	10	29	�	�	PROPN
gc-55	10	30	marko	marko	PROPN
gc-55	10	31	cvetković1	cvetković1	PROPN
gc-55	10	32	,	,	PUNCT
gc-55	10	33	josipa	josipa	ADJ
gc-55	10	34	velić1	velić1	NOUN
gc-55	10	35	and	and	CCONJ
gc-55	10	36	tomislav	tomislav	PROPN
gc-55	10	37	malvić1,2	malvić1,2	PROPN
gc-55	10	38	1	1	NUM
gc-55	10	39	department	department	NOUN
gc-55	10	40	of	of	ADP
gc-55	10	41	geology	geology	NOUN
gc-55	10	42	and	and	CCONJ
gc-55	10	43	geological	geological	ADJ
gc-55	10	44	engineering	engineering	NOUN
gc-55	10	45	,	,	PUNCT
gc-55	10	46	faculty	faculty	NOUN
gc-55	10	47	of	of	ADP
gc-55	10	48	mining	mining	NOUN
gc-55	10	49	,	,	PUNCT
gc-55	10	50	geology	geology	NOUN
gc-55	10	51	and	and	CCONJ
gc-55	10	52	petroleum	petroleum	NOUN
gc-55	10	53	engineering	engineering	NOUN
gc-55	10	54	,	,	PUNCT
gc-55	10	55	pierottijeva	pierottijeva	NOUN
gc-55	10	56	6	6	NUM
gc-55	10	57	,	,	PUNCT
gc-55	10	58	10000	10000	NUM
gc-55	10	59	zagreb	zagreb	PROPN
gc-55	10	60	,	,	PUNCT
gc-55	10	61	croatia	croatia	X
gc-55	10	62	;	;	PUNCT
gc-55	10	63	(	(	PUNCT
gc-55	10	64	marko.cvetkovic@rgn.hr	marko.cvetkovic@rgn.hr	NOUN
gc-55	10	65	)	)	PUNCT
gc-55	10	66	2	2	NUM
gc-55	10	67	development	development	NOUN
gc-55	10	68	department	department	NOUN
gc-55	10	69	,	,	PUNCT
gc-55	10	70	oil	oil	NOUN
gc-55	10	71	&	&	CCONJ
gc-55	10	72	gas	gas	NOUN
gc-55	10	73	exploration	exploration	NOUN
gc-55	10	74	and	and	CCONJ
gc-55	10	75	production	production	NOUN
gc-55	10	76	,	,	PUNCT
gc-55	10	77	ina	ina	PROPN
gc-55	10	78	-	-	PUNCT
gc-55	10	79	industrija	industrija	ADJ
gc-55	10	80	nafte	nafte	NOUN
gc-55	10	81	d.d	d.d	PROPN
gc-55	10	82	.	.	PROPN
gc-55	10	83	,	,	PUNCT
gc-55	10	84	šubićeva	šubićeva	PROPN
gc-55	10	85	29	29	NUM
gc-55	10	86	,	,	PUNCT
gc-55	10	87	10000	10000	NUM
gc-55	10	88	zagreb	zagreb	PROPN
gc-55	10	89	,	,	PUNCT
gc-55	10	90	croatia	croatia	X
gc-55	10	91	;	;	PUNCT
gc-55	10	92	(	(	PUNCT
gc-55	10	93	tomislav.malvic@ina.hr	tomislav.malvic@ina.hr	NOUN
gc-55	10	94	)	)	PUNCT
gc-55	10	95	doi	doi	NOUN
gc-55	10	96	:	:	PUNCT
gc-55	10	97	10.4154	10.4154	NUM
gc-55	10	98	/	/	SYM
gc-55	10	99	gc.2009.10	gc.2009.10	PROPN
gc-55	10	100	geologia	geologia	PROPN
gc-55	10	101	croatica	croatica	NOUN
gc-55	10	102	62/2	62/2	NUM
gc-55	11	1	115–121	115–121	NUM
gc-55	11	2	6	6	NUM
gc-55	11	3	figs	fig	NOUN
gc-55	11	4	.	.	PUNCT
gc-55	11	5	2	2	NUM
gc-55	11	6	tabs	tab	NOUN
gc-55	11	7	.	.	PUNCT
gc-55	12	1	zagreb	zagreb	PROPN
gc-55	12	2	2009	2009	NUM
gc-55	12	3	geologia	geologia	PROPN
gc-55	12	4	croaticageologia	croaticageologia	NOUN
gc-55	12	5	croatica	croatica	PROPN
gc-55	12	6	1	1	NUM
gc-55	12	7	.	.	PUNCT
gc-55	13	1	introduction	introduction	NOUN
gc-55	13	2	we	we	PRON
gc-55	13	3	used	use	VERB
gc-55	13	4	data	datum	NOUN
gc-55	13	5	from	from	ADP
gc-55	13	6	the	the	DET
gc-55	13	7	kloštar	kloštar	NOUN
gc-55	13	8	oil	oil	PROPN
gc-55	13	9	fi	fi	NOUN
gc-55	13	10	eld	eld	NOUN
gc-55	13	11	in	in	ADP
gc-55	13	12	croatia	croatia	PROPN
gc-55	13	13	to	to	PART
gc-55	13	14	test	test	VERB
gc-55	13	15	the	the	DET
gc-55	13	16	application	application	NOUN
gc-55	13	17	of	of	ADP
gc-55	13	18	neural	neural	ADJ
gc-55	13	19	networks	network	NOUN
gc-55	13	20	as	as	ADP
gc-55	13	21	a	a	DET
gc-55	13	22	part	part	NOUN
gc-55	13	23	of	of	ADP
gc-55	13	24	a	a	DET
gc-55	13	25	project	project	NOUN
gc-55	13	26	with	with	ADP
gc-55	13	27	a	a	DET
gc-55	13	28	cro	cro	NOUN
gc-55	13	29	ati	ati	NOUN
gc-55	13	30	an	an	DET
gc-55	13	31	oil	oil	NOUN
gc-55	13	32	company	company	NOUN
gc-55	13	33	(	(	PUNCT
gc-55	13	34	ina	ina	PROPN
gc-55	13	35	)	)	PUNCT
gc-55	13	36	.	.	PUNCT
gc-55	14	1	the	the	DET
gc-55	14	2	only	only	ADJ
gc-55	14	3	other	other	ADJ
gc-55	14	4	geomathematical	geomathematical	ADJ
gc-55	14	5	tools	tool	NOUN
gc-55	14	6	used	use	VERB
gc-55	14	7	on	on	ADP
gc-55	14	8	this	this	DET
gc-55	14	9	oil	oil	NOUN
gc-55	14	10	fi	fi	NOUN
gc-55	14	11	led	lead	VERB
gc-55	14	12	were	be	AUX
gc-55	14	13	several	several	ADJ
gc-55	14	14	interpolation	interpolation	NOUN
gc-55	14	15	methods	method	NOUN
gc-55	14	16	used	use	VERB
gc-55	14	17	for	for	ADP
gc-55	14	18	porosity	porosity	NOUN
gc-55	14	19	mapping	mapping	NOUN
gc-55	14	20	(	(	PUNCT
gc-55	14	21	balić	balić	PROPN
gc-55	14	22	et	et	PROPN
gc-55	14	23	al	al	PROPN
gc-55	14	24	.	.	PROPN
gc-55	14	25	,	,	PUNCT
gc-55	14	26	2008	2008	NUM
gc-55	14	27	)	)	PUNCT
gc-55	14	28	.	.	PUNCT
gc-55	15	1	the	the	DET
gc-55	15	2	fi	fi	NOUN
gc-55	15	3	eld	eld	NOUN
gc-55	15	4	is	be	AUX
gc-55	15	5	located	locate	VERB
gc-55	15	6	approximately	approximately	ADV
gc-55	15	7	35	35	NUM
gc-55	15	8	km	km	NOUN
gc-55	15	9	east	east	ADV
gc-55	15	10	of	of	ADP
gc-55	15	11	the	the	DET
gc-55	15	12	croatian	croatian	ADJ
gc-55	15	13	capital	capital	NOUN
gc-55	15	14	of	of	ADP
gc-55	15	15	zagreb	zagreb	PROPN
gc-55	15	16	(	(	PUNCT
gc-55	15	17	fig	fig	NOUN
gc-55	15	18	.	.	PUNCT
gc-55	16	1	1	1	NUM
gc-55	16	2	)	)	PUNCT
gc-55	16	3	.	.	PUNCT
gc-55	17	1	this	this	DET
gc-55	17	2	particular	particular	ADJ
gc-55	17	3	fi	fi	NOUN
gc-55	17	4	eld	eld	NOUN
gc-55	17	5	was	be	AUX
gc-55	17	6	selected	select	VERB
gc-55	17	7	because	because	SCONJ
gc-55	17	8	it	it	PRON
gc-55	17	9	is	be	AUX
gc-55	17	10	part	part	NOUN
gc-55	17	11	of	of	ADP
gc-55	17	12	a	a	DET
gc-55	17	13	joint	joint	ADJ
gc-55	17	14	research	research	NOUN
gc-55	17	15	project	project	NOUN
gc-55	17	16	between	between	ADP
gc-55	17	17	the	the	DET
gc-55	17	18	faculty	faculty	NOUN
gc-55	17	19	of	of	ADP
gc-55	17	20	mining	mining	NOUN
gc-55	17	21	,	,	PUNCT
gc-55	17	22	geology	geology	NOUN
gc-55	17	23	and	and	CCONJ
gc-55	17	24	petroleum	petroleum	NOUN
gc-55	17	25	engineering	engineering	NOUN
gc-55	17	26	,	,	PUNCT
gc-55	17	27	and	and	CCONJ
gc-55	17	28	a	a	DET
gc-55	17	29	croatian	croatian	ADJ
gc-55	17	30	oil	oil	NOUN
gc-55	17	31	company	company	NOUN
gc-55	17	32	.	.	PUNCT
gc-55	18	1	we	we	PRON
gc-55	18	2	used	use	VERB
gc-55	18	3	neural	neural	ADJ
gc-55	18	4	network	network	NOUN
gc-55	18	5	analysis	analysis	NOUN
gc-55	18	6	to	to	PART
gc-55	18	7	predict	predict	VERB
gc-55	18	8	reservoir	reservoir	NOUN
gc-55	18	9	lithology	lithology	NOUN
gc-55	18	10	of	of	ADP
gc-55	18	11	the	the	DET
gc-55	18	12	i	i	PROPN
gc-55	18	13	and	and	CCONJ
gc-55	18	14	ii	ii	PROPN
gc-55	18	15	sandstone	sandstone	NOUN
gc-55	18	16	series	series	NOUN
gc-55	18	17	as	as	ADP
gc-55	18	18	either	either	CCONJ
gc-55	18	19	shale	shale	NOUN
gc-55	18	20	or	or	CCONJ
gc-55	18	21	sandstone	sandstone	NOUN
gc-55	18	22	,	,	PUNCT
gc-55	18	23	as	as	ADV
gc-55	18	24	well	well	ADV
gc-55	18	25	as	as	ADP
gc-55	18	26	the	the	DET
gc-55	18	27	hydrocarbon	hydrocarbon	NOUN
gc-55	18	28	saturation	saturation	NOUN
gc-55	18	29	of	of	ADP
gc-55	18	30	the	the	DET
gc-55	18	31	sandstone	sandstone	NOUN
gc-55	18	32	intervals	interval	NOUN
gc-55	18	33	.	.	PUNCT
gc-55	19	1	these	these	DET
gc-55	19	2	intervals	interval	NOUN
gc-55	19	3	are	be	AUX
gc-55	19	4	generally	generally	ADV
gc-55	19	5	represented	represent	VERB
gc-55	19	6	by	by	ADP
gc-55	19	7	clastic	clastic	ADJ
gc-55	19	8	,	,	PUNCT
gc-55	19	9	brackish	brackish	ADJ
gc-55	19	10	to	to	ADP
gc-55	19	11	freshwater	freshwater	NOUN
gc-55	19	12	deposits	deposit	NOUN
gc-55	19	13	that	that	PRON
gc-55	19	14	are	be	AUX
gc-55	19	15	characteristic	characteristic	ADJ
gc-55	19	16	of	of	ADP
gc-55	19	17	the	the	DET
gc-55	19	18	upper	upper	ADJ
gc-55	19	19	pannonian	pannonian	NOUN
gc-55	19	20	and	and	CCONJ
gc-55	19	21	lower	low	ADJ
gc-55	19	22	pontian	pontian	ADJ
gc-55	19	23	succession	succession	NOUN
gc-55	19	24	throughout	throughout	ADP
gc-55	19	25	the	the	DET
gc-55	19	26	croatian	croatian	ADJ
gc-55	19	27	part	part	NOUN
gc-55	19	28	of	of	ADP
gc-55	19	29	the	the	DET
gc-55	19	30	pannonian	pannonian	ADJ
gc-55	19	31	basin	basin	NOUN
gc-55	19	32	(	(	PUNCT
gc-55	19	33	lučić	lučić	NOUN
gc-55	19	34	et	et	PROPN
gc-55	19	35	al	al	PROPN
gc-55	19	36	.	.	PROPN
gc-55	19	37	,	,	PUNCT
gc-55	19	38	2001	2001	NUM
gc-55	19	39	)	)	PUNCT
gc-55	19	40	.	.	PUNCT
gc-55	20	1	2	2	X
gc-55	20	2	.	.	X
gc-55	20	3	petroleum	petroleum	NOUN
gc-55	20	4	geology	geology	NOUN
gc-55	20	5	settings	setting	VERB
gc-55	20	6	the	the	DET
gc-55	20	7	dinaric	dinaric	ADJ
gc-55	20	8	oriented	orient	VERB
gc-55	20	9	(	(	PUNCT
gc-55	20	10	nw	nw	INTJ
gc-55	20	11	–	–	X
gc-55	20	12	se	se	ADJ
gc-55	20	13	)	)	PUNCT
gc-55	20	14	križ	križ	ADJ
gc-55	20	15	structure	structure	NOUN
gc-55	20	16	(	(	PUNCT
gc-55	20	17	including	include	VERB
gc-55	20	18	the	the	DET
gc-55	20	19	kloštar	kloštar	NOUN
gc-55	20	20	fi	fi	PROPN
gc-55	20	21	eld	eld	PROPN
gc-55	20	22	)	)	PUNCT
gc-55	20	23	is	be	AUX
gc-55	20	24	located	locate	VERB
gc-55	20	25	at	at	ADP
gc-55	20	26	the	the	DET
gc-55	20	27	most	most	ADV
gc-55	20	28	northwestern	northwestern	ADJ
gc-55	20	29	part	part	NOUN
gc-55	20	30	of	of	ADP
gc-55	20	31	moslavačka	moslavačka	PROPN
gc-55	20	32	gora	gora	PROPN
gc-55	20	33	mountain	mountain	PROPN
gc-55	20	34	.	.	PUNCT
gc-55	21	1	despite	despite	SCONJ
gc-55	21	2	many	many	ADJ
gc-55	21	3	available	available	ADJ
gc-55	21	4	well	well	PROPN
gc-55	21	5	data	datum	NOUN
gc-55	21	6	,	,	PUNCT
gc-55	21	7	the	the	DET
gc-55	21	8	borders	border	NOUN
gc-55	21	9	of	of	ADP
gc-55	21	10	the	the	DET
gc-55	21	11	stratigraphic	stratigraphic	ADJ
gc-55	21	12	units	unit	NOUN
gc-55	21	13	are	be	AUX
gc-55	21	14	commonly	commonly	ADV
gc-55	21	15	not	not	PART
gc-55	21	16	precisely	precisely	ADV
gc-55	21	17	defi	defi	NOUN
gc-55	21	18	ned	ne	VERB
gc-55	21	19	,	,	PUNCT
gc-55	21	20	mostly	mostly	ADV
gc-55	21	21	because	because	SCONJ
gc-55	21	22	of	of	ADP
gc-55	21	23	a	a	DET
gc-55	21	24	lack	lack	NOUN
gc-55	21	25	of	of	ADP
gc-55	21	26	palaeontological	palaeontological	ADJ
gc-55	21	27	samples	sample	NOUN
gc-55	21	28	and	and	CCONJ
gc-55	21	29	complex	complex	ADJ
gc-55	21	30	tectonics	tectonic	NOUN
gc-55	21	31	resulting	result	VERB
gc-55	21	32	in	in	ADP
gc-55	21	33	many	many	ADJ
gc-55	21	34	tectonic	tectonic	ADJ
gc-55	21	35	blocks	block	NOUN
gc-55	21	36	.	.	PUNCT
gc-55	22	1	at	at	ADP
gc-55	22	2	favorable	favorable	ADJ
gc-55	22	3	locations	location	NOUN
gc-55	22	4	,	,	PUNCT
gc-55	22	5	stratigraphic	stratigraphic	ADJ
gc-55	22	6	boundaries	boundary	NOUN
gc-55	22	7	are	be	AUX
gc-55	22	8	determined	determine	VERB
gc-55	22	9	based	base	VERB
gc-55	22	10	on	on	ADP
gc-55	22	11	available	available	ADJ
gc-55	22	12	well	well	PROPN
gc-55	22	13	data	datum	NOUN
gc-55	22	14	,	,	PUNCT
gc-55	22	15	including	include	VERB
gc-55	22	16	cores	core	NOUN
gc-55	22	17	,	,	PUNCT
gc-55	22	18	mud	mud	NOUN
gc-55	22	19	chips	chip	NOUN
gc-55	22	20	,	,	PUNCT
gc-55	22	21	and	and	CCONJ
gc-55	22	22	logs	log	NOUN
gc-55	22	23	.	.	PUNCT
gc-55	23	1	the	the	DET
gc-55	23	2	following	follow	VERB
gc-55	23	3	fi	fi	NOUN
gc-55	23	4	ve	ve	PROPN
gc-55	23	5	units	unit	NOUN
gc-55	23	6	are	be	AUX
gc-55	23	7	defi	defi	NOUN
gc-55	23	8	ned	ned	ADJ
gc-55	23	9	and	and	CCONJ
gc-55	23	10	degeologia	degeologia	ADJ
gc-55	23	11	croatica	croatica	PROPN
gc-55	23	12	geologia	geologia	PROPN
gc-55	23	13	croatica	croatica	PROPN
gc-55	23	14	62/2	62/2	NUM
gc-55	23	15	116	116	NUM
gc-55	23	16	the	the	DET
gc-55	23	17	pliocene	pliocene	PROPN
gc-55	23	18	deposits	deposit	NOUN
gc-55	23	19	,	,	PUNCT
gc-55	23	20	i.e.	i.e.	X
gc-55	23	21	,	,	PUNCT
gc-55	23	22	dacian	dacian	ADJ
gc-55	23	23	and	and	CCONJ
gc-55	23	24	romanian	romanian	ADJ
gc-55	23	25	,	,	PUNCT
gc-55	23	26	are	be	AUX
gc-55	23	27	also	also	ADV
gc-55	23	28	locally	locally	ADV
gc-55	23	29	known	know	VERB
gc-55	23	30	as	as	ADP
gc-55	23	31	the	the	DET
gc-55	23	32	paludina	paludina	NOUN
gc-55	23	33	beds	bed	NOUN
gc-55	23	34	.	.	PUNCT
gc-55	24	1	these	these	DET
gc-55	24	2	sediments	sediment	NOUN
gc-55	24	3	are	be	AUX
gc-55	24	4	characterized	characterize	VERB
gc-55	24	5	by	by	ADP
gc-55	24	6	the	the	DET
gc-55	24	7	alternation	alternation	NOUN
gc-55	24	8	of	of	ADP
gc-55	24	9	clays	clay	NOUN
gc-55	24	10	and	and	CCONJ
gc-55	24	11	medium	medium	NOUN
gc-55	24	12	and	and	CCONJ
gc-55	24	13	coarse	coarse	ADV
gc-55	24	14	-	-	PUNCT
gc-55	24	15	grained	grain	VERB
gc-55	24	16	sands	sand	NOUN
gc-55	24	17	.	.	PUNCT
gc-55	25	1	quaternary	quaternary	ADJ
gc-55	25	2	deposits	deposit	NOUN
gc-55	25	3	consist	consist	VERB
gc-55	25	4	predominantly	predominantly	ADV
gc-55	25	5	of	of	ADP
gc-55	25	6	yellowish	yellowish	ADJ
gc-55	25	7	sandy	sandy	ADJ
gc-55	25	8	clays	clay	NOUN
gc-55	25	9	with	with	ADP
gc-55	25	10	abundant	abundant	ADJ
gc-55	25	11	lime	lime	NOUN
gc-55	25	12	concretions	concretion	NOUN
gc-55	25	13	.	.	PUNCT
gc-55	26	1	the	the	DET
gc-55	26	2	average	average	ADJ
gc-55	26	3	thickness	thickness	NOUN
gc-55	26	4	ranges	range	VERB
gc-55	26	5	between	between	ADP
gc-55	26	6	10	10	NUM
gc-55	26	7	and	and	CCONJ
gc-55	26	8	15	15	NUM
gc-55	26	9	m.	m.	NOUN
gc-55	26	10	the	the	DET
gc-55	26	11	kloštar	kloštar	NOUN
gc-55	26	12	structure	structure	NOUN
gc-55	26	13	is	be	AUX
gc-55	26	14	a	a	DET
gc-55	26	15	faulted	fault	VERB
gc-55	26	16	anticline	anticline	NOUN
gc-55	26	17	with	with	ADP
gc-55	26	18	dinaric	dinaric	ADJ
gc-55	26	19	strike	strike	NOUN
gc-55	26	20	(	(	PUNCT
gc-55	26	21	nw	nw	INTJ
gc-55	26	22	–	–	PUNCT
gc-55	26	23	se	se	ADJ
gc-55	26	24	)	)	PUNCT
gc-55	26	25	.	.	PUNCT
gc-55	27	1	the	the	DET
gc-55	27	2	geological	geological	ADJ
gc-55	27	3	history	history	NOUN
gc-55	27	4	appears	appear	VERB
gc-55	27	5	interesting	interesting	ADJ
gc-55	27	6	,	,	PUNCT
gc-55	27	7	as	as	SCONJ
gc-55	27	8	shown	show	VERB
gc-55	27	9	by	by	ADP
gc-55	27	10	investigations	investigation	NOUN
gc-55	27	11	of	of	ADP
gc-55	27	12	structural	structural	ADJ
gc-55	27	13	settings	setting	NOUN
gc-55	27	14	and	and	CCONJ
gc-55	27	15	the	the	DET
gc-55	27	16	tectonic	tectonic	ADJ
gc-55	27	17	evolution	evolution	NOUN
gc-55	27	18	of	of	ADP
gc-55	27	19	the	the	DET
gc-55	27	20	western	western	ADJ
gc-55	27	21	part	part	NOUN
gc-55	27	22	of	of	ADP
gc-55	27	23	the	the	DET
gc-55	27	24	sava	sava	PROPN
gc-55	27	25	depression	depression	NOUN
gc-55	27	26	(	(	PUNCT
gc-55	27	27	velić	velić	NOUN
gc-55	27	28	,	,	PUNCT
gc-55	27	29	1979	1979	NUM
gc-55	27	30	,	,	PUNCT
gc-55	27	31	1980	1980	NUM
gc-55	27	32	,	,	PUNCT
gc-55	27	33	1983	1983	NUM
gc-55	27	34	)	)	PUNCT
gc-55	27	35	.	.	PUNCT
gc-55	28	1	the	the	DET
gc-55	28	2	fi	fi	NOUN
gc-55	28	3	eld	eld	NOUN
gc-55	28	4	structure	structure	NOUN
gc-55	28	5	was	be	AUX
gc-55	28	6	formed	form	VERB
gc-55	28	7	in	in	ADP
gc-55	28	8	the	the	DET
gc-55	28	9	middle	middle	ADJ
gc-55	28	10	miocene	miocene	NOUN
gc-55	28	11	,	,	PUNCT
gc-55	28	12	when	when	SCONJ
gc-55	28	13	intensive	intensive	ADJ
gc-55	28	14	badenian	badenian	ADJ
gc-55	28	15	and	and	CCONJ
gc-55	28	16	sarmatian	sarmatian	ADJ
gc-55	28	17	uplifting	uplifting	ADJ
gc-55	28	18	events	event	NOUN
gc-55	28	19	resulted	result	VERB
gc-55	28	20	in	in	ADP
gc-55	28	21	formation	formation	NOUN
gc-55	28	22	of	of	ADP
gc-55	28	23	a	a	DET
gc-55	28	24	nw	nw	NOUN
gc-55	28	25	to	to	PART
gc-55	28	26	seoriented	seoriente	VERB
gc-55	28	27	anticline	anticline	NOUN
gc-55	28	28	of	of	ADP
gc-55	28	29	7×2	7×2	NUM
gc-55	28	30	km	km	NOUN
gc-55	28	31	.	.	PUNCT
gc-55	29	1	later	later	ADV
gc-55	29	2	,	,	PUNCT
gc-55	29	3	in	in	ADP
gc-55	29	4	the	the	DET
gc-55	29	5	late	late	ADJ
gc-55	29	6	miocene	miocene	NOUN
gc-55	29	7	,	,	PUNCT
gc-55	29	8	this	this	DET
gc-55	29	9	structure	structure	NOUN
gc-55	29	10	was	be	AUX
gc-55	29	11	differentiated	differentiate	VERB
gc-55	29	12	in	in	ADP
gc-55	29	13	two	two	NUM
gc-55	29	14	smaller	small	ADJ
gc-55	29	15	parts	part	NOUN
gc-55	29	16	:	:	PUNCT
gc-55	29	17	the	the	DET
gc-55	29	18	northern	northern	ADJ
gc-55	29	19	,	,	PUNCT
gc-55	29	20	which	which	PRON
gc-55	29	21	was	be	AUX
gc-55	29	22	uplifted	uplift	VERB
gc-55	29	23	during	during	ADP
gc-55	29	24	the	the	DET
gc-55	29	25	pontian	pontian	NOUN
gc-55	29	26	,	,	PUNCT
gc-55	29	27	and	and	CCONJ
gc-55	29	28	the	the	DET
gc-55	29	29	southern	southern	NOUN
gc-55	29	30	,	,	PUNCT
gc-55	29	31	which	which	PRON
gc-55	29	32	was	be	AUX
gc-55	29	33	only	only	ADV
gc-55	29	34	activated	activate	VERB
gc-55	29	35	during	during	ADP
gc-55	29	36	the	the	DET
gc-55	29	37	upper	upper	ADJ
gc-55	29	38	pontian	pontian	NOUN
gc-55	29	39	.	.	PUNCT
gc-55	30	1	the	the	DET
gc-55	30	2	recent	recent	ADJ
gc-55	30	3	structural	structural	ADJ
gc-55	30	4	shape	shape	NOUN
gc-55	30	5	was	be	AUX
gc-55	30	6	tectonically	tectonically	ADV
gc-55	30	7	created	create	VERB
gc-55	30	8	during	during	ADP
gc-55	30	9	the	the	DET
gc-55	30	10	pliocene	pliocene	NOUN
gc-55	30	11	and	and	CCONJ
gc-55	30	12	quaternary	quaternary	ADJ
gc-55	30	13	,	,	PUNCT
gc-55	30	14	when	when	SCONJ
gc-55	30	15	the	the	DET
gc-55	30	16	main	main	ADJ
gc-55	30	17	phase	phase	NOUN
gc-55	30	18	of	of	ADP
gc-55	30	19	hydrocarbon	hydrocarbon	NOUN
gc-55	30	20	migration	migration	NOUN
gc-55	30	21	probably	probably	ADV
gc-55	30	22	occurred	occur	VERB
gc-55	30	23	.	.	PUNCT
gc-55	31	1	3	3	X
gc-55	31	2	.	.	X
gc-55	31	3	artificial	artificial	ADJ
gc-55	31	4	neural	neural	ADJ
gc-55	31	5	networks	network	NOUN
gc-55	31	6	a	a	DET
gc-55	31	7	neuron	neuron	NOUN
gc-55	31	8	is	be	AUX
gc-55	31	9	a	a	DET
gc-55	31	10	basic	basic	ADJ
gc-55	31	11	element	element	NOUN
gc-55	31	12	of	of	ADP
gc-55	31	13	a	a	DET
gc-55	31	14	network	network	NOUN
gc-55	31	15	that	that	PRON
gc-55	31	16	is	be	AUX
gc-55	31	17	mathematically	mathematically	ADV
gc-55	31	18	presented	present	VERB
gc-55	31	19	as	as	ADP
gc-55	31	20	a	a	DET
gc-55	31	21	point	point	NOUN
gc-55	31	22	in	in	ADP
gc-55	31	23	space	space	NOUN
gc-55	31	24	toward	toward	ADP
gc-55	31	25	which	which	PRON
gc-55	31	26	signals	signal	NOUN
gc-55	31	27	are	be	AUX
gc-55	31	28	transmitted	transmit	VERB
gc-55	31	29	from	from	ADP
gc-55	31	30	surrounding	surround	VERB
gc-55	31	31	neurons	neuron	NOUN
gc-55	31	32	(	(	PUNCT
gc-55	31	33	fig	fig	NOUN
gc-55	31	34	.	.	PUNCT
gc-55	32	1	2	2	NUM
gc-55	32	2	)	)	PUNCT
gc-55	32	3	.	.	PUNCT
gc-55	33	1	the	the	DET
gc-55	33	2	value	value	NOUN
gc-55	33	3	of	of	ADP
gc-55	33	4	a	a	DET
gc-55	33	5	signal	signal	NOUN
gc-55	33	6	on	on	ADP
gc-55	33	7	the	the	DET
gc-55	33	8	activity	activity	NOUN
gc-55	33	9	of	of	ADP
gc-55	33	10	a	a	DET
gc-55	33	11	neuron	neuron	NOUN
gc-55	33	12	is	be	AUX
gc-55	33	13	determined	determine	VERB
gc-55	33	14	by	by	ADP
gc-55	33	15	a	a	DET
gc-55	33	16	weight	weight	NOUN
gc-55	33	17	factor	factor	NOUN
gc-55	33	18	multiplied	multiply	VERB
gc-55	33	19	by	by	ADP
gc-55	33	20	a	a	DET
gc-55	33	21	corresponding	corresponding	ADJ
gc-55	33	22	input	input	NOUN
gc-55	33	23	signal	signal	NOUN
gc-55	33	24	.	.	PUNCT
gc-55	34	1	the	the	DET
gc-55	34	2	total	total	ADJ
gc-55	34	3	input	input	NOUN
gc-55	34	4	signal	signal	NOUN
gc-55	34	5	is	be	AUX
gc-55	34	6	determined	determine	VERB
gc-55	34	7	as	as	ADP
gc-55	34	8	a	a	DET
gc-55	34	9	summation	summation	NOUN
gc-55	34	10	of	of	ADP
gc-55	34	11	all	all	DET
gc-55	34	12	products	product	NOUN
gc-55	34	13	of	of	ADP
gc-55	34	14	weight	weight	NOUN
gc-55	34	15	factor	factor	NOUN
gc-55	34	16	multiplied	multiply	VERB
gc-55	34	17	by	by	ADP
gc-55	34	18	the	the	DET
gc-55	34	19	corresponding	corresponding	ADJ
gc-55	34	20	input	input	NOUN
gc-55	34	21	signal	signal	NOUN
gc-55	34	22	given	give	VERB
gc-55	34	23	by	by	ADP
gc-55	34	24	1	1	NUM
gc-55	34	25	(	(	PUNCT
gc-55	34	26	)	)	PUNCT
gc-55	35	1	n	n	CCONJ
gc-55	35	2	i	i	PRON
gc-55	36	1	ji	ji	INTJ
gc-55	37	1	j	j	PROPN
gc-55	37	2	j	j	PROPN
gc-55	37	3	u	u	PROPN
gc-55	37	4	w	w	NOUN
gc-55	37	5	input	input	NOUN
gc-55	37	6	=	=	NOUN
gc-55	37	7	=	=	SYM
gc-55	37	8	⋅σ	⋅σ	NOUN
gc-55	37	9	,	,	PUNCT
gc-55	37	10	scribed	scribe	VERB
gc-55	37	11	below	below	ADV
gc-55	37	12	,	,	PUNCT
gc-55	37	13	based	base	VERB
gc-55	37	14	on	on	ADP
gc-55	37	15	these	these	DET
gc-55	37	16	boundaries	boundary	NOUN
gc-55	37	17	:	:	PUNCT
gc-55	37	18	palaeozoic	palaeozoic	ADJ
gc-55	37	19	,	,	PUNCT
gc-55	37	20	middle	middle	ADJ
gc-55	37	21	miocene	miocene	NOUN
gc-55	37	22	,	,	PUNCT
gc-55	37	23	upper	upper	ADJ
gc-55	37	24	miocene	miocene	NOUN
gc-55	37	25	,	,	PUNCT
gc-55	37	26	pliocene	pliocene	PROPN
gc-55	37	27	,	,	PUNCT
gc-55	37	28	and	and	CCONJ
gc-55	37	29	quaternary	quaternary	ADJ
gc-55	37	30	sediments	sediment	NOUN
gc-55	37	31	.	.	PUNCT
gc-55	38	1	the	the	DET
gc-55	38	2	basement	basement	NOUN
gc-55	38	3	of	of	ADP
gc-55	38	4	the	the	DET
gc-55	38	5	tertiary	tertiary	ADJ
gc-55	38	6	system	system	NOUN
gc-55	38	7	represents	represent	VERB
gc-55	38	8	the	the	DET
gc-55	38	9	core	core	NOUN
gc-55	38	10	of	of	ADP
gc-55	38	11	the	the	DET
gc-55	38	12	križ	križ	ADJ
gc-55	38	13	structure	structure	NOUN
gc-55	38	14	.	.	PUNCT
gc-55	39	1	it	it	PRON
gc-55	39	2	includes	include	VERB
gc-55	39	3	extrusive	extrusive	ADJ
gc-55	39	4	igneous	igneous	ADJ
gc-55	39	5	and	and	CCONJ
gc-55	39	6	metamorphic	metamorphic	ADJ
gc-55	39	7	rocks	rock	NOUN
gc-55	39	8	,	,	PUNCT
gc-55	39	9	including	include	VERB
gc-55	39	10	granites	granite	NOUN
gc-55	39	11	of	of	ADP
gc-55	39	12	palaeozoic	palaeozoic	ADJ
gc-55	39	13	age	age	NOUN
gc-55	39	14	(	(	PUNCT
gc-55	39	15	vragović	vragović	PROPN
gc-55	39	16	&	&	CCONJ
gc-55	39	17	mayer	mayer	PROPN
gc-55	39	18	,	,	PUNCT
gc-55	39	19	1980	1980	NUM
gc-55	39	20	)	)	PUNCT
gc-55	39	21	.	.	PUNCT
gc-55	40	1	this	this	DET
gc-55	40	2	formation	formation	NOUN
gc-55	40	3	is	be	AUX
gc-55	40	4	a	a	DET
gc-55	40	5	buried	bury	VERB
gc-55	40	6	hill	hill	NOUN
gc-55	40	7	,	,	PUNCT
gc-55	40	8	formed	form	VERB
gc-55	40	9	by	by	ADP
gc-55	40	10	radial	radial	ADJ
gc-55	40	11	tectonic	tectonic	ADJ
gc-55	40	12	movements	movement	NOUN
gc-55	40	13	and	and	CCONJ
gc-55	40	14	denudation	denudation	NOUN
gc-55	40	15	processes	process	NOUN
gc-55	40	16	that	that	PRON
gc-55	40	17	occurred	occur	VERB
gc-55	40	18	before	before	ADP
gc-55	40	19	the	the	DET
gc-55	40	20	miocene	miocene	ADJ
gc-55	40	21	epoch	epoch	NOUN
gc-55	40	22	.	.	PUNCT
gc-55	41	1	the	the	DET
gc-55	41	2	rocks	rock	NOUN
gc-55	41	3	are	be	AUX
gc-55	41	4	weathered	weather	VERB
gc-55	41	5	and	and	CCONJ
gc-55	41	6	fractured	fracture	VERB
gc-55	41	7	.	.	PUNCT
gc-55	42	1	in	in	ADP
gc-55	42	2	structurally	structurally	ADV
gc-55	42	3	favourable	favourable	ADJ
gc-55	42	4	places	place	NOUN
gc-55	42	5	,	,	PUNCT
gc-55	42	6	hydrocarbon	hydrocarbon	NOUN
gc-55	42	7	accumulations	accumulation	NOUN
gc-55	42	8	are	be	AUX
gc-55	42	9	confi	confi	ADJ
gc-55	42	10	rmed	rme	VERB
gc-55	42	11	.	.	PUNCT
gc-55	43	1	the	the	DET
gc-55	43	2	middle	middle	PROPN
gc-55	43	3	miocene	miocene	NOUN
gc-55	43	4	(	(	PUNCT
gc-55	43	5	badenian	badenian	ADJ
gc-55	43	6	,	,	PUNCT
gc-55	43	7	sarmatian	sarmatian	ADJ
gc-55	43	8	)	)	PUNCT
gc-55	43	9	unit	unit	NOUN
gc-55	43	10	unconformably	unconformably	PROPN
gc-55	43	11	overlies	overlie	VERB
gc-55	43	12	the	the	DET
gc-55	43	13	palaeozoic	palaeozoic	ADJ
gc-55	43	14	igneous	igneous	ADJ
gc-55	43	15	–	–	PUNCT
gc-55	43	16	metamorphic	metamorphic	ADJ
gc-55	43	17	complex	complex	NOUN
gc-55	43	18	.	.	PUNCT
gc-55	44	1	the	the	DET
gc-55	44	2	basal	basal	ADJ
gc-55	44	3	part	part	NOUN
gc-55	44	4	is	be	AUX
gc-55	44	5	characterized	characterize	VERB
gc-55	44	6	by	by	ADP
gc-55	44	7	coarse	coarse	NOUN
gc-55	44	8	-	-	PUNCT
gc-55	44	9	grained	grain	VERB
gc-55	44	10	conglomerates	conglomerate	NOUN
gc-55	44	11	,	,	PUNCT
gc-55	44	12	conglomeratic	conglomeratic	ADJ
gc-55	44	13	sandstones	sandstone	NOUN
gc-55	44	14	,	,	PUNCT
gc-55	44	15	and	and	CCONJ
gc-55	44	16	sandstones	sandstone	NOUN
gc-55	44	17	often	often	ADV
gc-55	44	18	intercalated	intercalate	VERB
gc-55	44	19	with	with	ADP
gc-55	44	20	shale	shale	NOUN
gc-55	44	21	.	.	PUNCT
gc-55	45	1	it	it	PRON
gc-55	45	2	is	be	AUX
gc-55	45	3	overlain	overlain	NOUN
gc-55	45	4	by	by	ADP
gc-55	45	5	dark	dark	ADJ
gc-55	45	6	-	-	PUNCT
gc-55	45	7	gray	gray	ADJ
gc-55	45	8	,	,	PUNCT
gc-55	45	9	sandy	sandy	ADJ
gc-55	45	10	,	,	PUNCT
gc-55	45	11	bituminized	bituminize	VERB
gc-55	45	12	marls	marl	NOUN
gc-55	45	13	,	,	PUNCT
gc-55	45	14	partially	partially	ADV
gc-55	45	15	intercalated	intercalate	VERB
gc-55	45	16	with	with	ADP
gc-55	45	17	lightgray	lightgray	NOUN
gc-55	45	18	,	,	PUNCT
gc-55	45	19	fi	fi	NOUN
gc-55	45	20	ne	ne	ADJ
gc-55	45	21	-	-	ADJ
gc-55	45	22	grained	grain	VERB
gc-55	45	23	sandstones	sandstone	NOUN
gc-55	45	24	.	.	PUNCT
gc-55	46	1	miocene	miocene	ADJ
gc-55	46	2	beds	bed	NOUN
gc-55	46	3	form	form	VERB
gc-55	46	4	economic	economic	ADJ
gc-55	46	5	hydrocarbon	hydrocarbon	NOUN
gc-55	46	6	reservoirs	reservoir	NOUN
gc-55	46	7	at	at	ADP
gc-55	46	8	the	the	DET
gc-55	46	9	southern	southern	ADJ
gc-55	46	10	and	and	CCONJ
gc-55	46	11	eastern	eastern	ADJ
gc-55	46	12	parts	part	NOUN
gc-55	46	13	of	of	ADP
gc-55	46	14	the	the	DET
gc-55	46	15	kloštar	kloštar	NOUN
gc-55	46	16	structure	structure	NOUN
gc-55	46	17	.	.	PUNCT
gc-55	47	1	upper	upper	ADJ
gc-55	47	2	miocene	miocene	NOUN
gc-55	47	3	(	(	PUNCT
gc-55	47	4	pannonian	pannonian	ADJ
gc-55	47	5	,	,	PUNCT
gc-55	47	6	pontian	pontian	ADJ
gc-55	47	7	)	)	PUNCT
gc-55	47	8	strata	strata	NOUN
gc-55	47	9	are	be	AUX
gc-55	47	10	well	well	ADV
gc-55	47	11	documented	document	VERB
gc-55	47	12	throughout	throughout	ADP
gc-55	47	13	the	the	DET
gc-55	47	14	fi	fi	NOUN
gc-55	47	15	eld	eld	NOUN
gc-55	47	16	area	area	NOUN
gc-55	47	17	.	.	PUNCT
gc-55	48	1	lower	low	ADJ
gc-55	48	2	pannonian	pannonian	ADJ
gc-55	48	3	strata	strata	NOUN
gc-55	48	4	conformably	conformably	ADV
gc-55	48	5	overlie	overlie	PROPN
gc-55	48	6	sarmatian	sarmatian	PROPN
gc-55	48	7	bituminized	bituminize	VERB
gc-55	48	8	marls	marl	NOUN
gc-55	48	9	.	.	PUNCT
gc-55	49	1	upper	upper	ADJ
gc-55	49	2	pannonian	pannonian	ADJ
gc-55	49	3	sediments	sediment	NOUN
gc-55	49	4	are	be	AUX
gc-55	49	5	represented	represent	VERB
gc-55	49	6	by	by	ADP
gc-55	49	7	predominantly	predominantly	ADV
gc-55	49	8	brown	brown	ADJ
gc-55	49	9	or	or	CCONJ
gc-55	49	10	dark	dark	ADJ
gc-55	49	11	-	-	PUNCT
gc-55	49	12	gray	gray	ADJ
gc-55	49	13	calcareous	calcareous	ADJ
gc-55	49	14	marls	marl	NOUN
gc-55	49	15	and	and	CCONJ
gc-55	49	16	sandstones	sandstone	NOUN
gc-55	49	17	,	,	PUNCT
gc-55	49	18	located	locate	VERB
gc-55	49	19	in	in	ADP
gc-55	49	20	the	the	DET
gc-55	49	21	southwestern	southwestern	ADJ
gc-55	49	22	part	part	NOUN
gc-55	49	23	,	,	PUNCT
gc-55	49	24	and	and	CCONJ
gc-55	49	25	partially	partially	ADV
gc-55	49	26	saturated	saturate	VERB
gc-55	49	27	by	by	ADP
gc-55	49	28	hydrocarbons	hydrocarbon	NOUN
gc-55	49	29	.	.	PUNCT
gc-55	50	1	they	they	PRON
gc-55	50	2	are	be	AUX
gc-55	50	3	defi	defi	NOUN
gc-55	50	4	ned	ned	PROPN
gc-55	50	5	as	as	ADP
gc-55	50	6	the	the	DET
gc-55	50	7	ii	ii	PROPN
gc-55	50	8	sandstone	sandstone	NOUN
gc-55	50	9	series	series	NOUN
gc-55	50	10	.	.	PUNCT
gc-55	51	1	lower	low	ADJ
gc-55	51	2	pontian	pontian	ADJ
gc-55	51	3	sediments	sediment	NOUN
gc-55	51	4	are	be	AUX
gc-55	51	5	represented	represent	VERB
gc-55	51	6	by	by	ADP
gc-55	51	7	dark	dark	ADJ
gc-55	51	8	-	-	PUNCT
gc-55	51	9	gray	gray	ADJ
gc-55	51	10	,	,	PUNCT
gc-55	51	11	massive	massive	ADJ
gc-55	51	12	marls	marl	NOUN
gc-55	51	13	and	and	CCONJ
gc-55	51	14	sandy	sandy	ADJ
gc-55	51	15	marls	marl	NOUN
gc-55	51	16	to	to	ADP
gc-55	51	17	the	the	DET
gc-55	51	18	south	south	NOUN
gc-55	51	19	and	and	CCONJ
gc-55	51	20	east	east	NOUN
gc-55	51	21	of	of	ADP
gc-55	51	22	the	the	DET
gc-55	51	23	fi	fi	NOUN
gc-55	51	24	eld	eld	NOUN
gc-55	51	25	area	area	NOUN
gc-55	51	26	.	.	PUNCT
gc-55	52	1	sandstones	sandstone	NOUN
gc-55	52	2	,	,	PUNCT
gc-55	52	3	mostly	mostly	ADV
gc-55	52	4	arenites	arenite	VERB
gc-55	52	5	with	with	ADP
gc-55	52	6	minor	minor	ADJ
gc-55	52	7	proportions	proportion	NOUN
gc-55	52	8	of	of	ADP
gc-55	52	9	marl	marl	NOUN
gc-55	52	10	or	or	CCONJ
gc-55	52	11	clay	clay	NOUN
gc-55	52	12	,	,	PUNCT
gc-55	52	13	are	be	AUX
gc-55	52	14	dominant	dominant	ADJ
gc-55	52	15	in	in	ADP
gc-55	52	16	the	the	DET
gc-55	52	17	northwest	northwest	NOUN
gc-55	52	18	and	and	CCONJ
gc-55	52	19	are	be	AUX
gc-55	52	20	partially	partially	ADV
gc-55	52	21	saturated	saturate	VERB
gc-55	52	22	with	with	ADP
gc-55	52	23	hydrocarbons	hydrocarbon	NOUN
gc-55	52	24	.	.	PUNCT
gc-55	53	1	the	the	DET
gc-55	53	2	lower	low	ADJ
gc-55	53	3	pontian	pontian	ADJ
gc-55	53	4	sandstones	sandstone	NOUN
gc-55	53	5	are	be	AUX
gc-55	53	6	also	also	ADV
gc-55	53	7	called	call	VERB
gc-55	53	8	the	the	DET
gc-55	53	9	ii	ii	PROPN
gc-55	53	10	sandstone	sandstone	NOUN
gc-55	53	11	series	series	NOUN
gc-55	53	12	.	.	PUNCT
gc-55	54	1	the	the	DET
gc-55	54	2	upper	upper	ADJ
gc-55	54	3	pontian	pontian	ADJ
gc-55	54	4	succession	succession	NOUN
gc-55	54	5	is	be	AUX
gc-55	54	6	monotonous	monotonous	ADJ
gc-55	54	7	,	,	PUNCT
gc-55	54	8	consisting	consist	VERB
gc-55	54	9	of	of	ADP
gc-55	54	10	soft	soft	ADJ
gc-55	54	11	sandy	sandy	NOUN
gc-55	54	12	or	or	CCONJ
gc-55	54	13	clayey	clayey	NOUN
gc-55	54	14	sediments	sediment	NOUN
gc-55	54	15	and	and	CCONJ
gc-55	54	16	the	the	DET
gc-55	54	17	proportion	proportion	NOUN
gc-55	54	18	of	of	ADP
gc-55	54	19	sand	sand	NOUN
gc-55	54	20	increases	increase	VERB
gc-55	54	21	upward	upward	ADV
gc-55	54	22	.	.	PUNCT
gc-55	55	1	fi	fi	NOUN
gc-55	55	2	gu	gu	NOUN
gc-55	55	3	re	re	NOUN
gc-55	55	4	1	1	NUM
gc-55	55	5	:	:	PUNCT
gc-55	55	6	geographic	geographic	ADJ
gc-55	55	7	position	position	NOUN
gc-55	55	8	of	of	ADP
gc-55	55	9	the	the	DET
gc-55	55	10	kloštar	kloštar	NOUN
gc-55	55	11	fi	fi	PROPN
gc-55	55	12	eld	eld	NOUN
gc-55	55	13	in	in	ADP
gc-55	55	14	croatia	croatia	PROPN
gc-55	55	15	.	.	PUNCT
gc-55	56	1	geologia	geologia	PROPN
gc-55	56	2	croaticacvetković	croaticacvetković	PROPN
gc-55	56	3	et	et	PROPN
gc-55	56	4	al	al	PROPN
gc-55	56	5	.	.	PROPN
gc-55	56	6	:	:	PUNCT
gc-55	57	1	application	application	NOUN
gc-55	57	2	of	of	ADP
gc-55	57	3	neural	neural	ADJ
gc-55	57	4	networks	network	NOUN
gc-55	57	5	in	in	ADP
gc-55	57	6	petroleum	petroleum	NOUN
gc-55	57	7	reservoir	reservoir	NOUN
gc-55	57	8	lithology	lithology	NOUN
gc-55	57	9	and	and	CCONJ
gc-55	57	10	saturation	saturation	NOUN
gc-55	57	11	prediction	prediction	NOUN
gc-55	57	12	117	117	NUM
gc-55	57	13	where	where	SCONJ
gc-55	57	14	n	n	PRON
gc-55	57	15	represents	represent	VERB
gc-55	57	16	the	the	DET
gc-55	57	17	number	number	NOUN
gc-55	57	18	of	of	ADP
gc-55	57	19	inputs	input	NOUN
gc-55	57	20	for	for	ADP
gc-55	57	21	the	the	DET
gc-55	57	22	neuron	neuron	PROPN
gc-55	57	23	i.	i.	PROPN
gc-55	57	24	if	if	SCONJ
gc-55	57	25	the	the	DET
gc-55	57	26	total	total	ADJ
gc-55	57	27	input	input	NOUN
gc-55	57	28	signal	signal	NOUN
gc-55	57	29	has	have	VERB
gc-55	57	30	a	a	DET
gc-55	57	31	value	value	NOUN
gc-55	57	32	greater	great	ADJ
gc-55	57	33	than	than	ADP
gc-55	57	34	the	the	DET
gc-55	57	35	sensitivity	sensitivity	NOUN
gc-55	57	36	threshold	threshold	NOUN
gc-55	57	37	of	of	ADP
gc-55	57	38	a	a	DET
gc-55	57	39	neuron	neuron	NOUN
gc-55	57	40	,	,	PUNCT
gc-55	57	41	then	then	ADV
gc-55	57	42	it	it	PRON
gc-55	57	43	will	will	AUX
gc-55	57	44	have	have	VERB
gc-55	57	45	an	an	DET
gc-55	57	46	output	output	NOUN
gc-55	57	47	of	of	ADP
gc-55	57	48	maximum	maximum	ADJ
gc-55	57	49	intensity	intensity	NOUN
gc-55	57	50	.	.	PUNCT
gc-55	58	1	alternatively	alternatively	ADV
gc-55	58	2	,	,	PUNCT
gc-55	58	3	a	a	DET
gc-55	58	4	neuron	neuron	NOUN
gc-55	58	5	is	be	AUX
gc-55	58	6	inactive	inactive	ADJ
gc-55	58	7	and	and	CCONJ
gc-55	58	8	has	have	VERB
gc-55	58	9	no	no	DET
gc-55	58	10	output	output	NOUN
gc-55	58	11	.	.	PUNCT
gc-55	59	1	value	value	NOUN
gc-55	59	2	of	of	ADP
gc-55	59	3	the	the	DET
gc-55	59	4	output	output	NOUN
gc-55	59	5	is	be	AUX
gc-55	59	6	given	give	VERB
gc-55	59	7	by	by	ADP
gc-55	59	8	(	(	PUNCT
gc-55	59	9	)	)	PUNCT
gc-55	59	10	i	i	PRON
gc-55	59	11	i	i	PRON
gc-55	59	12	ioutput	ioutput	VERB
gc-55	59	13	f	f	PROPN
gc-55	59	14	u	u	PROPN
gc-55	59	15	t=	t=	PROPN
gc-55	59	16	⋅	⋅	PROPN
gc-55	59	17	,	,	PUNCT
gc-55	59	18	where	where	SCONJ
gc-55	59	19	f	f	PROPN
gc-55	59	20	represents	represent	VERB
gc-55	59	21	the	the	DET
gc-55	59	22	activation	activation	NOUN
gc-55	59	23	function	function	NOUN
gc-55	59	24	and	and	CCONJ
gc-55	59	25	ti	ti	NOUN
gc-55	59	26	,	,	PUNCT
gc-55	59	27	the	the	DET
gc-55	59	28	targeted	target	VERB
gc-55	59	29	out	out	ADP
gc-55	59	30	put	put	NOUN
gc-55	59	31	value	value	NOUN
gc-55	59	32	of	of	ADP
gc-55	59	33	neuron	neuron	PROPN
gc-55	59	34	i.	i.	PROPN
gc-55	59	35	one	one	PROPN
gc-55	59	36	can	can	AUX
gc-55	59	37	fi	fi	VERB
gc-55	59	38	nd	nd	ADV
gc-55	59	39	a	a	DET
gc-55	59	40	more	more	ADV
gc-55	59	41	detailed	detailed	ADJ
gc-55	59	42	des	des	PROPN
gc-55	59	43	crip	crip	NOUN
gc-55	59	44	tion	tion	NOUN
gc-55	59	45	of	of	ADP
gc-55	59	46	neural	neural	ADJ
gc-55	59	47	network	network	NOUN
gc-55	59	48	basics	basic	NOUN
gc-55	59	49	and	and	CCONJ
gc-55	59	50	methods	method	NOUN
gc-55	59	51	in	in	ADP
gc-55	59	52	mccul	mccul	PROPN
gc-55	59	53	lo	lo	PROPN
gc-55	59	54	ch	ch	PROPN
gc-55	59	55	&	&	CCONJ
gc-55	59	56	pitts	pitts	PROPN
gc-55	59	57	(	(	PUNCT
gc-55	59	58	1943	1943	NUM
gc-55	59	59	)	)	PUNCT
gc-55	59	60	,	,	PUNCT
gc-55	59	61	rosenblatt	rosenblatt	NOUN
gc-55	59	62	(	(	PUNCT
gc-55	59	63	1958	1958	NUM
gc-55	59	64	)	)	PUNCT
gc-55	59	65	and	and	CCONJ
gc-55	59	66	anderson	anderson	PROPN
gc-55	59	67	&	&	CCONJ
gc-55	59	68	rosenfeld	rosenfeld	PROPN
gc-55	59	69	(	(	PUNCT
gc-55	59	70	1988	1988	NUM
gc-55	59	71	)	)	PUNCT
gc-55	59	72	.	.	PUNCT
gc-55	60	1	the	the	DET
gc-55	60	2	basic	basic	ADJ
gc-55	60	3	architecture	architecture	NOUN
gc-55	60	4	of	of	ADP
gc-55	60	5	a	a	DET
gc-55	60	6	neural	neural	ADJ
gc-55	60	7	network	network	NOUN
gc-55	60	8	consists	consist	VERB
gc-55	60	9	of	of	ADP
gc-55	60	10	neurons	neuron	NOUN
gc-55	60	11	divided	divide	VERB
gc-55	60	12	into	into	ADP
gc-55	60	13	layers	layer	NOUN
gc-55	60	14	.	.	PUNCT
gc-55	61	1	three	three	NUM
gc-55	61	2	is	be	AUX
gc-55	61	3	a	a	DET
gc-55	61	4	minimum	minimum	ADJ
gc-55	61	5	number	number	NOUN
gc-55	61	6	of	of	ADP
gc-55	61	7	layers	layer	NOUN
gc-55	61	8	which	which	PRON
gc-55	61	9	a	a	DET
gc-55	61	10	neural	neural	ADJ
gc-55	61	11	network	network	NOUN
gc-55	61	12	has	have	VERB
gc-55	61	13	to	to	PART
gc-55	61	14	have	have	VERB
gc-55	61	15	.	.	PUNCT
gc-55	62	1	these	these	DET
gc-55	62	2	layers	layer	NOUN
gc-55	62	3	are	be	AUX
gc-55	62	4	the	the	DET
gc-55	62	5	input	input	NOUN
gc-55	62	6	layer	layer	NOUN
gc-55	62	7	,	,	PUNCT
gc-55	62	8	the	the	DET
gc-55	62	9	hidden	hidden	ADJ
gc-55	62	10	layer	layer	NOUN
gc-55	62	11	and	and	CCONJ
gc-55	62	12	the	the	DET
gc-55	62	13	output	output	NOUN
gc-55	62	14	layer	layer	NOUN
gc-55	62	15	.	.	PUNCT
gc-55	63	1	the	the	DET
gc-55	63	2	input	input	NOUN
gc-55	63	3	layer	layer	NOUN
gc-55	63	4	is	be	AUX
gc-55	63	5	for	for	ADP
gc-55	63	6	accepting	accept	VERB
gc-55	63	7	signals	signal	NOUN
gc-55	63	8	,	,	PUNCT
gc-55	63	9	or	or	CCONJ
gc-55	63	10	in	in	ADP
gc-55	63	11	our	our	PRON
gc-55	63	12	case	case	NOUN
gc-55	63	13	,	,	PUNCT
gc-55	63	14	input	input	NOUN
gc-55	63	15	variables	variable	NOUN
gc-55	63	16	.	.	PUNCT
gc-55	64	1	these	these	DET
gc-55	64	2	data	datum	NOUN
gc-55	64	3	are	be	AUX
gc-55	64	4	transferred	transfer	VERB
gc-55	64	5	to	to	ADP
gc-55	64	6	the	the	DET
gc-55	64	7	hidden	hide	VERB
gc-55	64	8	layer	layer	NOUN
gc-55	64	9	where	where	SCONJ
gc-55	64	10	it	it	PRON
gc-55	64	11	is	be	AUX
gc-55	64	12	processed	process	VERB
gc-55	64	13	by	by	ADP
gc-55	64	14	the	the	DET
gc-55	64	15	activation	activation	NOUN
gc-55	64	16	function	function	NOUN
gc-55	64	17	belonging	belong	VERB
gc-55	64	18	to	to	ADP
gc-55	64	19	the	the	DET
gc-55	64	20	neurons	neuron	NOUN
gc-55	64	21	within	within	ADP
gc-55	64	22	it	it	PRON
gc-55	64	23	.	.	PUNCT
gc-55	65	1	data	datum	NOUN
gc-55	65	2	which	which	PRON
gc-55	65	3	proved	prove	VERB
gc-55	65	4	to	to	PART
gc-55	65	5	be	be	AUX
gc-55	65	6	signifi	signifi	NOUN
gc-55	65	7	ca	can	AUX
gc-55	65	8	nt	not	PART
gc-55	65	9	in	in	ADP
gc-55	65	10	the	the	DET
gc-55	65	11	analysis	analysis	NOUN
gc-55	65	12	in	in	ADP
gc-55	65	13	the	the	DET
gc-55	65	14	hidden	hide	VERB
gc-55	65	15	layer	layer	NOUN
gc-55	65	16	neurons	neuron	NOUN
gc-55	65	17	is	be	AUX
gc-55	65	18	sent	send	VERB
gc-55	65	19	to	to	ADP
gc-55	65	20	the	the	DET
gc-55	65	21	output	output	NOUN
gc-55	65	22	layer	layer	NOUN
gc-55	65	23	as	as	ADP
gc-55	65	24	the	the	DET
gc-55	65	25	resulting	result	VERB
gc-55	65	26	data	datum	NOUN
gc-55	65	27	for	for	ADP
gc-55	65	28	the	the	DET
gc-55	65	29	predicted	predict	VERB
gc-55	65	30	variable	variable	NOUN
gc-55	65	31	.	.	PUNCT
gc-55	66	1	the	the	DET
gc-55	66	2	number	number	NOUN
gc-55	66	3	of	of	ADP
gc-55	66	4	hidden	hidden	ADJ
gc-55	66	5	layers	layer	NOUN
gc-55	66	6	can	can	AUX
gc-55	66	7	be	be	AUX
gc-55	66	8	more	more	ADJ
gc-55	66	9	than	than	ADP
gc-55	66	10	one	one	NUM
gc-55	66	11	or	or	CCONJ
gc-55	66	12	strictly	strictly	ADV
gc-55	66	13	one	one	NUM
gc-55	66	14	,	,	PUNCT
gc-55	66	15	depending	depend	VERB
gc-55	66	16	on	on	ADP
gc-55	66	17	the	the	DET
gc-55	66	18	type	type	NOUN
gc-55	66	19	of	of	ADP
gc-55	66	20	the	the	DET
gc-55	66	21	neural	neural	ADJ
gc-55	66	22	network	network	NOUN
gc-55	66	23	.	.	PUNCT
gc-55	67	1	for	for	ADP
gc-55	67	2	example	example	NOUN
gc-55	67	3	,	,	PUNCT
gc-55	67	4	the	the	DET
gc-55	67	5	multi	multi	ADJ
gc-55	67	6	layer	layer	NOUN
gc-55	67	7	perceptron	perceptron	PROPN
gc-55	67	8	(	(	PUNCT
gc-55	67	9	mlp	mlp	NOUN
gc-55	67	10	)	)	PUNCT
gc-55	67	11	neural	neural	ADJ
gc-55	67	12	network	network	NOUN
gc-55	67	13	is	be	AUX
gc-55	67	14	basically	basically	ADV
gc-55	67	15	designed	design	VERB
gc-55	67	16	to	to	PART
gc-55	67	17	be	be	AUX
gc-55	67	18	able	able	ADJ
gc-55	67	19	to	to	PART
gc-55	67	20	have	have	VERB
gc-55	67	21	more	more	ADJ
gc-55	67	22	than	than	ADP
gc-55	67	23	one	one	NUM
gc-55	67	24	hidden	hide	VERB
gc-55	67	25	layer	layer	NOUN
gc-55	67	26	and	and	CCONJ
gc-55	67	27	to	to	PART
gc-55	67	28	perform	perform	VERB
gc-55	67	29	better	well	ADV
gc-55	67	30	with	with	ADP
gc-55	67	31	two	two	NUM
gc-55	67	32	or	or	CCONJ
gc-55	67	33	three	three	NUM
gc-55	67	34	hidden	hidden	ADJ
gc-55	67	35	layers	layer	NOUN
gc-55	67	36	than	than	ADP
gc-55	67	37	with	with	ADP
gc-55	67	38	one	one	NUM
gc-55	67	39	.	.	PUNCT
gc-55	68	1	in	in	ADP
gc-55	68	2	opposition	opposition	NOUN
gc-55	68	3	to	to	ADP
gc-55	68	4	the	the	DET
gc-55	68	5	multi	multi	ADJ
gc-55	68	6	layer	layer	NOUN
gc-55	68	7	perceptron	perceptron	PROPN
gc-55	68	8	,	,	PUNCT
gc-55	68	9	the	the	DET
gc-55	68	10	radial	radial	ADJ
gc-55	68	11	basis	basis	NOUN
gc-55	68	12	function	function	NOUN
gc-55	68	13	(	(	PUNCT
gc-55	68	14	rbf	rbf	PROPN
gc-55	68	15	)	)	PUNCT
gc-55	68	16	neural	neural	ADJ
gc-55	68	17	network	network	NOUN
gc-55	68	18	can	can	AUX
gc-55	68	19	only	only	ADV
gc-55	68	20	have	have	VERB
gc-55	68	21	one	one	NUM
gc-55	68	22	hidden	hide	VERB
gc-55	68	23	layer	layer	NOUN
gc-55	68	24	but	but	CCONJ
gc-55	68	25	the	the	DET
gc-55	68	26	number	number	NOUN
gc-55	68	27	of	of	ADP
gc-55	68	28	neurons	neuron	NOUN
gc-55	68	29	within	within	ADP
gc-55	68	30	this	this	DET
gc-55	68	31	layer	layer	NOUN
gc-55	68	32	is	be	AUX
gc-55	68	33	much	much	ADV
gc-55	68	34	larger	large	ADJ
gc-55	68	35	than	than	ADP
gc-55	68	36	the	the	DET
gc-55	68	37	number	number	NOUN
gc-55	68	38	of	of	ADP
gc-55	68	39	neurons	neuron	NOUN
gc-55	68	40	in	in	ADP
gc-55	68	41	the	the	DET
gc-55	68	42	single	single	ADJ
gc-55	68	43	hidden	hide	VERB
gc-55	68	44	layer	layer	NOUN
gc-55	68	45	of	of	ADP
gc-55	68	46	the	the	DET
gc-55	68	47	mlp	mlp	NOUN
gc-55	68	48	.	.	PUNCT
gc-55	69	1	for	for	ADP
gc-55	69	2	this	this	DET
gc-55	69	3	analysis	analysis	NOUN
gc-55	69	4	,	,	PUNCT
gc-55	69	5	we	we	PRON
gc-55	69	6	used	use	VERB
gc-55	69	7	the	the	DET
gc-55	69	8	two	two	NUM
gc-55	69	9	aforementioned	aforementioned	ADJ
gc-55	69	10	types	type	NOUN
gc-55	69	11	of	of	ADP
gc-55	69	12	neural	neural	ADJ
gc-55	69	13	networks	network	NOUN
gc-55	69	14	,	,	PUNCT
gc-55	69	15	the	the	DET
gc-55	69	16	supervised	supervised	ADJ
gc-55	69	17	learning	learning	NOUN
gc-55	69	18	-	-	PUNCT
gc-55	69	19	multilayer	multilayer	NOUN
gc-55	69	20	perceptron	perceptron	NOUN
gc-55	69	21	and	and	CCONJ
gc-55	69	22	the	the	DET
gc-55	69	23	radial	radial	ADJ
gc-55	69	24	basis	basis	NOUN
gc-55	69	25	function	function	NOUN
gc-55	69	26	neural	neural	ADJ
gc-55	69	27	network	network	NOUN
gc-55	69	28	.	.	PUNCT
gc-55	70	1	the	the	DET
gc-55	70	2	mlp	mlp	NOUN
gc-55	70	3	network	network	NOUN
gc-55	70	4	is	be	AUX
gc-55	70	5	based	base	VERB
gc-55	70	6	on	on	ADP
gc-55	70	7	a	a	DET
gc-55	70	8	back	back	ADJ
gc-55	70	9	propagation	propagation	NOUN
gc-55	70	10	algorithm	algorithm	NOUN
gc-55	70	11	which	which	PRON
gc-55	70	12	calculates	calculate	VERB
gc-55	70	13	the	the	DET
gc-55	70	14	error	error	NOUN
gc-55	70	15	surface	surface	NOUN
gc-55	70	16	gradient	gradient	NOUN
gc-55	70	17	in	in	ADP
gc-55	70	18	each	each	DET
gc-55	70	19	step	step	NOUN
gc-55	70	20	of	of	ADP
gc-55	70	21	the	the	DET
gc-55	70	22	analysis	analysis	NOUN
gc-55	70	23	.	.	PUNCT
gc-55	71	1	in	in	ADP
gc-55	71	2	the	the	DET
gc-55	71	3	following	following	ADJ
gc-55	71	4	step	step	NOUN
gc-55	71	5	,	,	PUNCT
gc-55	71	6	the	the	DET
gc-55	71	7	weight	weight	NOUN
gc-55	71	8	factors	factor	NOUN
gc-55	71	9	are	be	AUX
gc-55	71	10	adjusted	adjust	VERB
gc-55	71	11	according	accord	VERB
gc-55	71	12	to	to	ADP
gc-55	71	13	the	the	DET
gc-55	71	14	earlier	early	ADV
gc-55	71	15	calculated	calculate	VERB
gc-55	71	16	error	error	NOUN
gc-55	71	17	surface	surface	NOUN
gc-55	71	18	gradient	gradient	NOUN
gc-55	71	19	so	so	SCONJ
gc-55	71	20	the	the	DET
gc-55	71	21	error	error	NOUN
gc-55	71	22	minimizes	minimize	VERB
gc-55	71	23	and	and	CCONJ
gc-55	71	24	a	a	DET
gc-55	71	25	new	new	ADJ
gc-55	71	26	error	error	NOUN
gc-55	71	27	surface	surface	NOUN
gc-55	71	28	is	be	AUX
gc-55	71	29	calculated	calculate	VERB
gc-55	71	30	.	.	PUNCT
gc-55	72	1	also	also	ADV
gc-55	72	2	,	,	PUNCT
gc-55	72	3	the	the	DET
gc-55	72	4	network	network	NOUN
gc-55	72	5	can	can	AUX
gc-55	72	6	utilize	utilize	VERB
gc-55	72	7	a	a	DET
gc-55	72	8	two	two	NUM
gc-55	72	9	-	-	PUNCT
gc-55	72	10	phase	phase	NOUN
gc-55	72	11	learning	learning	NOUN
gc-55	72	12	with	with	ADP
gc-55	72	13	second	second	ADJ
gc-55	72	14	learning	learning	NOUN
gc-55	72	15	algorithms	algorithm	NOUN
gc-55	72	16	such	such	ADJ
gc-55	72	17	as	as	ADP
gc-55	72	18	conjugate	conjugate	ADJ
gc-55	72	19	gradient	gradient	ADJ
gc-55	72	20	descent	descent	NOUN
gc-55	72	21	(	(	PUNCT
gc-55	72	22	gorse	gorse	NOUN
gc-55	72	23	et	et	PROPN
gc-55	72	24	al	al	PROPN
gc-55	72	25	.	.	PROPN
gc-55	72	26	,	,	PUNCT
gc-55	72	27	1997	1997	NUM
gc-55	72	28	)	)	PUNCT
gc-55	72	29	,	,	PUNCT
gc-55	72	30	quasi	quasi	NOUN
gc-55	72	31	-	-	NOUN
gc-55	72	32	newton	newton	PROPN
gc-55	72	33	(	(	PUNCT
gc-55	72	34	bishop	bishop	PROPN
gc-55	72	35	,	,	PUNCT
gc-55	72	36	1995	1995	NUM
gc-55	72	37	)	)	PUNCT
gc-55	72	38	,	,	PUNCT
gc-55	72	39	levenberg	levenberg	PROPN
gc-55	72	40	–	–	PUNCT
gc-55	72	41	marquardt	marquardt	PROPN
gc-55	72	42	(	(	PUNCT
gc-55	72	43	levenberg	levenberg	PROPN
gc-55	72	44	,	,	PUNCT
gc-55	72	45	1944	1944	NUM
gc-55	72	46	;	;	PUNCT
gc-55	72	47	marquardt	marquardt	PROPN
gc-55	72	48	,	,	PUNCT
gc-55	72	49	1963	1963	NUM
gc-55	72	50	)	)	PUNCT
gc-55	72	51	,	,	PUNCT
gc-55	72	52	quick	quick	ADJ
gc-55	72	53	propagation	propagation	NOUN
gc-55	72	54	(	(	PUNCT
gc-55	72	55	fahlman	fahlman	NOUN
gc-55	72	56	,	,	PUNCT
gc-55	72	57	1988	1988	NUM
gc-55	72	58	)	)	PUNCT
gc-55	72	59	and	and	CCONJ
gc-55	72	60	delta	delta	NOUN
gc-55	72	61	-	-	PUNCT
gc-55	72	62	bar	bar	NOUN
gc-55	72	63	-	-	PUNCT
gc-55	72	64	delta	delta	NOUN
gc-55	72	65	(	(	PUNCT
gc-55	72	66	jacobs	jacobs	PROPN
gc-55	72	67	,	,	PUNCT
gc-55	72	68	1988	1988	NUM
gc-55	72	69	)	)	PUNCT
gc-55	72	70	which	which	PRON
gc-55	72	71	basically	basically	ADV
gc-55	72	72	work	work	VERB
gc-55	72	73	on	on	ADP
gc-55	72	74	similar	similar	ADJ
gc-55	72	75	principles	principle	NOUN
gc-55	72	76	to	to	ADP
gc-55	72	77	the	the	DET
gc-55	72	78	back	back	ADJ
gc-55	72	79	propagation	propagation	NOUN
gc-55	72	80	algorithm	algorithm	NOUN
gc-55	72	81	with	with	ADP
gc-55	72	82	a	a	DET
gc-55	72	83	somewhat	somewhat	ADV
gc-55	72	84	different	different	ADJ
gc-55	72	85	approach	approach	NOUN
gc-55	72	86	.	.	PUNCT
gc-55	73	1	the	the	DET
gc-55	73	2	greatest	great	ADJ
gc-55	73	3	advantage	advantage	NOUN
gc-55	73	4	of	of	ADP
gc-55	73	5	these	these	DET
gc-55	73	6	aformentioned	aformentioned	ADJ
gc-55	73	7	algorithms	algorithm	NOUN
gc-55	73	8	over	over	ADP
gc-55	73	9	the	the	DET
gc-55	73	10	back	back	ADJ
gc-55	73	11	propagation	propagation	NOUN
gc-55	73	12	is	be	AUX
gc-55	73	13	that	that	SCONJ
gc-55	73	14	they	they	PRON
gc-55	73	15	are	be	AUX
gc-55	73	16	signifi	signifi	NOUN
gc-55	73	17	cantly	cantly	ADV
gc-55	73	18	faster	fast	ADV
gc-55	73	19	but	but	CCONJ
gc-55	73	20	sometimes	sometimes	ADV
gc-55	73	21	the	the	DET
gc-55	73	22	standard	standard	ADJ
gc-55	73	23	back	back	ADJ
gc-55	73	24	propagation	propagation	NOUN
gc-55	73	25	algorithm	algorithm	NOUN
gc-55	73	26	gives	give	VERB
gc-55	73	27	the	the	DET
gc-55	73	28	best	good	ADJ
gc-55	73	29	results	result	NOUN
gc-55	73	30	.	.	PUNCT
gc-55	74	1	for	for	ADP
gc-55	74	2	more	more	ADJ
gc-55	74	3	information	information	NOUN
gc-55	74	4	in	in	ADP
gc-55	74	5	croatian	croatian	PROPN
gc-55	74	6	on	on	ADP
gc-55	74	7	these	these	DET
gc-55	74	8	learning	learn	VERB
gc-55	74	9	algorithms	algorithm	NOUN
gc-55	74	10	please	please	INTJ
gc-55	74	11	refer	refer	VERB
gc-55	74	12	to	to	ADP
gc-55	74	13	the	the	DET
gc-55	74	14	geostatistical	geostatistical	ADJ
gc-55	74	15	dictionary	dictionary	NOUN
gc-55	74	16	of	of	ADP
gc-55	74	17	malvić	malvić	NOUN
gc-55	74	18	et	et	PROPN
gc-55	74	19	al	al	PROPN
gc-55	74	20	.	.	PUNCT
gc-55	75	1	(	(	PUNCT
gc-55	75	2	2008	2008	NUM
gc-55	75	3	)	)	PUNCT
gc-55	75	4	.	.	PUNCT
gc-55	76	1	the	the	DET
gc-55	76	2	mlp	mlp	NOUN
gc-55	76	3	is	be	AUX
gc-55	76	4	more	more	ADV
gc-55	76	5	successfully	successfully	ADV
gc-55	76	6	applied	apply	VERB
gc-55	76	7	in	in	ADP
gc-55	76	8	classifi	classifi	NOUN
gc-55	76	9	cation	cation	NOUN
gc-55	76	10	and	and	CCONJ
gc-55	76	11	prediction	prediction	NOUN
gc-55	76	12	problems	problem	NOUN
gc-55	76	13	(	(	PUNCT
gc-55	76	14	rumelhart	rumelhart	NOUN
gc-55	76	15	et	et	PROPN
gc-55	76	16	al	al	PROPN
gc-55	76	17	.	.	PROPN
gc-55	76	18	,	,	PUNCT
gc-55	76	19	1986	1986	NUM
gc-55	76	20	)	)	PUNCT
gc-55	76	21	,	,	PUNCT
gc-55	76	22	and	and	CCONJ
gc-55	76	23	is	be	AUX
gc-55	76	24	the	the	DET
gc-55	76	25	most	most	ADV
gc-55	76	26	often	often	ADV
gc-55	76	27	used	use	VERB
gc-55	76	28	neural	neural	ADJ
gc-55	76	29	network	network	NOUN
gc-55	76	30	in	in	ADP
gc-55	76	31	solving	solve	VERB
gc-55	76	32	geological	geological	ADJ
gc-55	76	33	problems	problem	NOUN
gc-55	76	34	.	.	PUNCT
gc-55	77	1	the	the	DET
gc-55	77	2	rbf	rbf	PROPN
gc-55	77	3	network	network	NOUN
gc-55	77	4	is	be	AUX
gc-55	77	5	also	also	ADV
gc-55	77	6	a	a	DET
gc-55	77	7	commonly	commonly	ADV
gc-55	77	8	used	use	VERB
gc-55	77	9	neural	neural	ADJ
gc-55	77	10	network	network	NOUN
gc-55	77	11	but	but	CCONJ
gc-55	77	12	is	be	AUX
gc-55	77	13	more	more	ADV
gc-55	77	14	successfully	successfully	ADV
gc-55	77	15	and	and	CCONJ
gc-55	77	16	frequently	frequently	ADV
gc-55	77	17	applied	apply	VERB
gc-55	77	18	in	in	ADP
gc-55	77	19	solving	solve	VERB
gc-55	77	20	classifi	classifi	ADJ
gc-55	77	21	cation	cation	NOUN
gc-55	77	22	problems	problem	NOUN
gc-55	77	23	than	than	ADP
gc-55	77	24	in	in	ADP
gc-55	77	25	solving	solve	VERB
gc-55	77	26	prediction	prediction	NOUN
gc-55	77	27	problems	problem	NOUN
gc-55	77	28	.	.	PUNCT
gc-55	78	1	neural	neural	ADJ
gc-55	78	2	networks	network	NOUN
gc-55	78	3	have	have	AUX
gc-55	78	4	been	be	AUX
gc-55	78	5	successfully	successfully	ADV
gc-55	78	6	applied	apply	VERB
gc-55	78	7	in	in	ADP
gc-55	78	8	petroleum	petroleum	NOUN
gc-55	78	9	geology	geology	NOUN
gc-55	78	10	problems	problem	NOUN
gc-55	78	11	such	such	ADJ
gc-55	78	12	as	as	ADP
gc-55	78	13	determining	determine	VERB
gc-55	78	14	reservoir	reservoir	NOUN
gc-55	78	15	properties	property	NOUN
gc-55	78	16	(	(	PUNCT
gc-55	78	17	e.g.	e.g.	ADV
gc-55	78	18	,	,	PUNCT
gc-55	78	19	lithology	lithology	NOUN
gc-55	78	20	and	and	CCONJ
gc-55	78	21	porosity	porosity	NOUN
gc-55	78	22	)	)	PUNCT
gc-55	78	23	from	from	ADP
gc-55	78	24	well	well	ADV
gc-55	78	25	logs	log	NOUN
gc-55	78	26	,	,	PUNCT
gc-55	78	27	(	(	PUNCT
gc-55	78	28	bhatt	bhatt	NOUN
gc-55	78	29	,	,	PUNCT
gc-55	78	30	2002	2002	NUM
gc-55	78	31	)	)	PUNCT
gc-55	78	32	and	and	CCONJ
gc-55	78	33	well	well	ADV
gc-55	78	34	-	-	PUNCT
gc-55	78	35	log	log	NOUN
gc-55	78	36	correlation	correlation	NOUN
gc-55	78	37	(	(	PUNCT
gc-55	78	38	luthi	luthi	NOUN
gc-55	78	39	&	&	CCONJ
gc-55	78	40	bryant	bryant	PROPN
gc-55	78	41	,	,	PUNCT
gc-55	78	42	1997	1997	NUM
gc-55	78	43	)	)	PUNCT
gc-55	78	44	.	.	PUNCT
gc-55	79	1	in	in	ADP
gc-55	79	2	the	the	DET
gc-55	79	3	croatian	croatian	ADJ
gc-55	79	4	part	part	NOUN
gc-55	79	5	of	of	ADP
gc-55	79	6	the	the	DET
gc-55	79	7	pannonian	pannonian	ADJ
gc-55	79	8	basin	basin	NOUN
gc-55	79	9	,	,	PUNCT
gc-55	79	10	only	only	ADV
gc-55	79	11	a	a	DET
gc-55	79	12	few	few	ADJ
gc-55	79	13	petroleum	petroleum	NOUN
gc-55	79	14	geology	geology	NOUN
gc-55	79	15	research	research	NOUN
gc-55	79	16	projects	project	NOUN
gc-55	79	17	have	have	AUX
gc-55	79	18	been	be	AUX
gc-55	79	19	performed	perform	VERB
gc-55	79	20	.	.	PUNCT
gc-55	80	1	in	in	ADP
gc-55	80	2	these	these	DET
gc-55	80	3	studies	study	NOUN
gc-55	80	4	,	,	PUNCT
gc-55	80	5	clastic	clastic	ADJ
gc-55	80	6	facies	facie	NOUN
gc-55	80	7	were	be	AUX
gc-55	80	8	determined	determine	VERB
gc-55	80	9	from	from	ADP
gc-55	80	10	well	well	ADV
gc-55	80	11	logs	log	NOUN
gc-55	80	12	(	(	PUNCT
gc-55	80	13	malvić	malvić	NOUN
gc-55	80	14	,	,	PUNCT
gc-55	80	15	2006	2006	NUM
gc-55	80	16	)	)	PUNCT
gc-55	80	17	and	and	CCONJ
gc-55	80	18	porosity	porosity	NOUN
gc-55	80	19	was	be	AUX
gc-55	80	20	predicted	predict	VERB
gc-55	80	21	based	base	VERB
gc-55	80	22	on	on	ADP
gc-55	80	23	well	well	ADV
gc-55	80	24	and	and	CCONJ
gc-55	80	25	seismic	seismic	ADJ
gc-55	80	26	data	datum	NOUN
gc-55	80	27	(	(	PUNCT
gc-55	80	28	malvić	malvić	NOUN
gc-55	80	29	&	&	CCONJ
gc-55	80	30	prskalo	prskalo	PROPN
gc-55	80	31	,	,	PUNCT
gc-55	80	32	2007	2007	NUM
gc-55	80	33	)	)	PUNCT
gc-55	80	34	.	.	PUNCT
gc-55	81	1	4	4	X
gc-55	81	2	.	.	X
gc-55	81	3	data	datum	NOUN
gc-55	81	4	analysis	analysis	NOUN
gc-55	81	5	we	we	PRON
gc-55	81	6	used	use	VERB
gc-55	81	7	well	well	INTJ
gc-55	81	8	log	log	NOUN
gc-55	81	9	data	datum	NOUN
gc-55	81	10	from	from	ADP
gc-55	81	11	two	two	NUM
gc-55	81	12	wells	well	NOUN
gc-55	81	13	as	as	ADP
gc-55	81	14	input	input	NOUN
gc-55	81	15	data	datum	NOUN
gc-55	81	16	for	for	ADP
gc-55	81	17	the	the	DET
gc-55	81	18	neural	neural	ADJ
gc-55	81	19	network	network	NOUN
gc-55	81	20	analysis	analysis	NOUN
gc-55	81	21	.	.	PUNCT
gc-55	82	1	the	the	DET
gc-55	82	2	data	datum	NOUN
gc-55	82	3	consist	consist	VERB
gc-55	82	4	of	of	ADP
gc-55	82	5	the	the	DET
gc-55	82	6	most	most	ADV
gc-55	82	7	basic	basic	ADJ
gc-55	82	8	well	well	NOUN
gc-55	82	9	logs	log	NOUN
gc-55	82	10	because	because	SCONJ
gc-55	82	11	measurements	measurement	NOUN
gc-55	82	12	were	be	AUX
gc-55	82	13	taken	take	VERB
gc-55	82	14	in	in	ADP
gc-55	82	15	1956	1956	NUM
gc-55	82	16	(	(	PUNCT
gc-55	82	17	well	well	ADV
gc-55	82	18	klo	klo	PROPN
gc-55	82	19	–	–	PUNCT
gc-55	82	20	a	a	NOUN
gc-55	82	21	)	)	PUNCT
gc-55	82	22	and	and	CCONJ
gc-55	82	23	1957	1957	NUM
gc-55	82	24	(	(	PUNCT
gc-55	82	25	well	well	INTJ
gc-55	82	26	klo	klo	PROPN
gc-55	82	27	–	–	PUNCT
gc-55	82	28	b	b	NOUN
gc-55	82	29	)	)	PUNCT
gc-55	82	30	.	.	PUNCT
gc-55	83	1	although	although	SCONJ
gc-55	83	2	these	these	DET
gc-55	83	3	logs	log	NOUN
gc-55	83	4	were	be	AUX
gc-55	83	5	taken	take	VERB
gc-55	83	6	some	some	DET
gc-55	83	7	50	50	NUM
gc-55	83	8	years	year	NOUN
gc-55	83	9	ago	ago	ADV
gc-55	83	10	,	,	PUNCT
gc-55	83	11	we	we	PRON
gc-55	83	12	can	can	AUX
gc-55	83	13	successfully	successfully	ADV
gc-55	83	14	use	use	VERB
gc-55	83	15	them	they	PRON
gc-55	83	16	for	for	ADP
gc-55	83	17	interpretation	interpretation	NOUN
gc-55	83	18	(	(	PUNCT
gc-55	83	19	fig	fig	NOUN
gc-55	83	20	.	.	PUNCT
gc-55	84	1	3	3	NUM
gc-55	84	2	)	)	PUNCT
gc-55	84	3	.	.	PUNCT
gc-55	85	1	available	available	ADJ
gc-55	85	2	data	datum	NOUN
gc-55	85	3	for	for	ADP
gc-55	85	4	analysis	analysis	NOUN
gc-55	85	5	included	include	VERB
gc-55	85	6	resistivity	resistivity	NOUN
gc-55	85	7	(	(	PUNCT
gc-55	85	8	r16	r16	NOUN
gc-55	85	9	and	and	CCONJ
gc-55	85	10	r64	r64	NOUN
gc-55	85	11	)	)	PUNCT
gc-55	85	12	and	and	CCONJ
gc-55	85	13	spontaneous	spontaneous	ADJ
gc-55	85	14	potential	potential	NOUN
gc-55	85	15	(	(	PUNCT
gc-55	85	16	sp	sp	NOUN
gc-55	85	17	)	)	PUNCT
gc-55	85	18	logs	log	NOUN
gc-55	85	19	.	.	PUNCT
gc-55	86	1	resolution	resolution	NOUN
gc-55	86	2	of	of	ADP
gc-55	86	3	the	the	DET
gc-55	86	4	data	datum	NOUN
gc-55	86	5	was	be	AUX
gc-55	86	6	10	10	NUM
gc-55	86	7	cases	case	NOUN
gc-55	86	8	(	(	PUNCT
gc-55	86	9	measurements	measurement	NOUN
gc-55	86	10	)	)	PUNCT
gc-55	86	11	per	per	ADP
gc-55	86	12	metre	metre	NOUN
gc-55	86	13	of	of	ADP
gc-55	86	14	well	well	ADV
gc-55	86	15	log	log	NOUN
gc-55	86	16	.	.	PUNCT
gc-55	87	1	we	we	PRON
gc-55	87	2	performed	perform	VERB
gc-55	87	3	two	two	NUM
gc-55	87	4	types	type	NOUN
gc-55	87	5	of	of	ADP
gc-55	87	6	analysis	analysis	NOUN
gc-55	87	7	.	.	PUNCT
gc-55	88	1	first	first	ADV
gc-55	88	2	we	we	PRON
gc-55	88	3	predicted	predict	VERB
gc-55	88	4	the	the	DET
gc-55	88	5	lithology	lithology	NOUN
gc-55	88	6	,	,	PUNCT
gc-55	88	7	followed	follow	VERB
gc-55	88	8	by	by	ADP
gc-55	88	9	the	the	DET
gc-55	88	10	hydrocarbon	hydrocarbon	NOUN
gc-55	88	11	saturation	saturation	NOUN
gc-55	88	12	.	.	PUNCT
gc-55	89	1	we	we	PRON
gc-55	89	2	carried	carry	VERB
gc-55	89	3	out	out	ADP
gc-55	89	4	the	the	DET
gc-55	89	5	analysis	analysis	NOUN
gc-55	89	6	such	such	ADJ
gc-55	89	7	that	that	SCONJ
gc-55	89	8	the	the	DET
gc-55	89	9	neural	neural	ADJ
gc-55	89	10	network	network	NOUN
gc-55	89	11	was	be	AUX
gc-55	89	12	fi	fi	NOUN
gc-55	89	13	rst	rst	PROPN
gc-55	89	14	trained	train	VERB
gc-55	89	15	on	on	ADP
gc-55	89	16	a	a	DET
gc-55	89	17	specifi	specifi	PROPN
gc-55	89	18	c	c	PROPN
gc-55	89	19	interval	interval	NOUN
gc-55	89	20	of	of	ADP
gc-55	89	21	well	well	INTJ
gc-55	89	22	log	log	NOUN
gc-55	89	23	data	datum	NOUN
gc-55	89	24	(	(	PUNCT
gc-55	89	25	overseen	overseen	ADJ
gc-55	89	26	learning	learning	NOUN
gc-55	89	27	)	)	PUNCT
gc-55	89	28	,	,	PUNCT
gc-55	89	29	and	and	CCONJ
gc-55	89	30	afterward	afterward	ADV
gc-55	89	31	we	we	PRON
gc-55	89	32	used	use	VERB
gc-55	89	33	the	the	DET
gc-55	89	34	trained	train	VERB
gc-55	89	35	neural	neural	ADJ
gc-55	89	36	network	network	NOUN
gc-55	89	37	to	to	PART
gc-55	89	38	predict	predict	VERB
gc-55	89	39	the	the	DET
gc-55	89	40	value	value	NOUN
gc-55	89	41	of	of	ADP
gc-55	89	42	desired	desire	VERB
gc-55	89	43	parameters	parameter	NOUN
gc-55	89	44	for	for	ADP
gc-55	89	45	the	the	DET
gc-55	89	46	intervals	interval	NOUN
gc-55	89	47	on	on	ADP
gc-55	89	48	which	which	PRON
gc-55	89	49	the	the	DET
gc-55	89	50	neural	neural	ADJ
gc-55	89	51	network	network	NOUN
gc-55	89	52	was	be	AUX
gc-55	89	53	not	not	PART
gc-55	89	54	trained	train	VERB
gc-55	89	55	.	.	PUNCT
gc-55	90	1	all	all	DET
gc-55	90	2	neural	neural	ADJ
gc-55	90	3	network	network	NOUN
gc-55	90	4	analysis	analysis	NOUN
gc-55	90	5	were	be	AUX
gc-55	90	6	made	make	VERB
gc-55	90	7	using	use	VERB
gc-55	90	8	statsoft	statsoft	ADJ
gc-55	90	9	statistica	statistica	NOUN
gc-55	90	10	7.1	7.1	NUM
gc-55	90	11	.	.	PUNCT
gc-55	91	1	fi	fi	NOUN
gc-55	91	2	gu	gu	NOUN
gc-55	91	3	re	re	ADP
gc-55	91	4	2	2	NUM
gc-55	91	5	:	:	PUNCT
gc-55	91	6	artifi	artifi	PROPN
gc-55	91	7	cial	cial	PROPN
gc-55	91	8	neuron	neuron	PROPN
gc-55	91	9	model	model	PROPN
gc-55	91	10	.	.	PUNCT
gc-55	92	1	geologia	geologia	PROPN
gc-55	92	2	croatica	croatica	PROPN
gc-55	92	3	geologia	geologia	PROPN
gc-55	92	4	croatica	croatica	PROPN
gc-55	92	5	62/2	62/2	NUM
gc-55	92	6	118	118	NUM
gc-55	92	7	4.1	4.1	NUM
gc-55	92	8	.	.	PUNCT
gc-55	93	1	lithology	lithology	NOUN
gc-55	93	2	prediction	prediction	NOUN
gc-55	93	3	to	to	PART
gc-55	93	4	predict	predict	VERB
gc-55	93	5	lithology	lithology	NOUN
gc-55	93	6	,	,	PUNCT
gc-55	93	7	we	we	PRON
gc-55	93	8	manually	manually	ADV
gc-55	93	9	determined	determine	VERB
gc-55	93	10	the	the	DET
gc-55	93	11	lithological	lithological	ADJ
gc-55	93	12	component	component	NOUN
gc-55	93	13	by	by	ADP
gc-55	93	14	distinguishing	distinguish	VERB
gc-55	93	15	layers	layer	NOUN
gc-55	93	16	of	of	ADP
gc-55	93	17	marl	marl	NOUN
gc-55	93	18	and	and	CCONJ
gc-55	93	19	sandstone	sandstone	NOUN
gc-55	93	20	from	from	ADP
gc-55	93	21	well	well	ADV
gc-55	93	22	logs	log	NOUN
gc-55	93	23	(	(	PUNCT
gc-55	93	24	bassiouni	bassiouni	PROPN
gc-55	93	25	,	,	PUNCT
gc-55	93	26	1994	1994	NUM
gc-55	93	27	)	)	PUNCT
gc-55	93	28	on	on	ADP
gc-55	93	29	wells	wells	PROPN
gc-55	93	30	klo	klo	PROPN
gc-55	93	31	–	–	PUNCT
gc-55	93	32	a	a	PROPN
gc-55	93	33	and	and	CCONJ
gc-55	93	34	klo	klo	PROPN
gc-55	93	35	–	–	PUNCT
gc-55	93	36	b.	b.	PROPN
gc-55	94	1	the	the	DET
gc-55	94	2	neural	neural	ADJ
gc-55	94	3	network	network	NOUN
gc-55	94	4	was	be	AUX
gc-55	94	5	trained	train	VERB
gc-55	94	6	on	on	ADP
gc-55	94	7	the	the	DET
gc-55	94	8	fi	fi	NOUN
gc-55	94	9	rst	rst	PROPN
gc-55	94	10	set	set	NOUN
gc-55	94	11	of	of	ADP
gc-55	94	12	data	datum	NOUN
gc-55	94	13	,	,	PUNCT
gc-55	94	14	which	which	PRON
gc-55	94	15	includes	include	VERB
gc-55	94	16	intervals	interval	NOUN
gc-55	94	17	that	that	PRON
gc-55	94	18	correspond	correspond	VERB
gc-55	94	19	to	to	ADP
gc-55	94	20	the	the	DET
gc-55	94	21	i	i	PROPN
gc-55	94	22	sandstone	sandstone	NOUN
gc-55	94	23	series	series	NOUN
gc-55	94	24	,	,	PUNCT
gc-55	94	25	and	and	CCONJ
gc-55	94	26	the	the	DET
gc-55	94	27	prediction	prediction	NOUN
gc-55	94	28	was	be	AUX
gc-55	94	29	made	make	VERB
gc-55	94	30	on	on	ADP
gc-55	94	31	the	the	DET
gc-55	94	32	intervals	interval	NOUN
gc-55	94	33	that	that	PRON
gc-55	94	34	correspond	correspond	VERB
gc-55	94	35	to	to	ADP
gc-55	94	36	the	the	DET
gc-55	94	37	ii	ii	PROPN
gc-55	94	38	sandstone	sandstone	NOUN
gc-55	94	39	series	series	NOUN
gc-55	94	40	and	and	CCONJ
gc-55	94	41	vice	vice	NOUN
gc-55	94	42	versa	versa	ADV
gc-55	94	43	.	.	PUNCT
gc-55	95	1	input	input	NOUN
gc-55	95	2	data	datum	NOUN
gc-55	95	3	for	for	ADP
gc-55	95	4	training	training	NOUN
gc-55	95	5	of	of	ADP
gc-55	95	6	the	the	DET
gc-55	95	7	neural	neural	ADJ
gc-55	95	8	network	network	NOUN
gc-55	95	9	,	,	PUNCT
gc-55	95	10	resistivity	resistivity	NOUN
gc-55	95	11	(	(	PUNCT
gc-55	95	12	r16	r16	PROPN
gc-55	95	13	,	,	PUNCT
gc-55	95	14	r64	r64	NOUN
gc-55	95	15	)	)	PUNCT
gc-55	95	16	and	and	CCONJ
gc-55	95	17	sp	sp	ADP
gc-55	95	18	logs	log	NOUN
gc-55	95	19	,	,	PUNCT
gc-55	95	20	were	be	AUX
gc-55	95	21	used	use	VERB
gc-55	95	22	.	.	PUNCT
gc-55	96	1	we	we	PRON
gc-55	96	2	defi	defi	VERB
gc-55	96	3	ned	ned	ADJ
gc-55	96	4	lithology	lithology	NOUN
gc-55	96	5	as	as	ADP
gc-55	96	6	a	a	DET
gc-55	96	7	categorical	categorical	ADJ
gc-55	96	8	variable	variable	NOUN
gc-55	96	9	(	(	PUNCT
gc-55	96	10	1	1	NUM
gc-55	96	11	for	for	ADP
gc-55	96	12	sandstone	sandstone	NOUN
gc-55	96	13	,	,	PUNCT
gc-55	96	14	0	0	NUM
gc-55	96	15	for	for	ADP
gc-55	96	16	marl	marl	NOUN
gc-55	96	17	)	)	PUNCT
gc-55	96	18	.	.	PUNCT
gc-55	97	1	for	for	ADP
gc-55	97	2	training	training	NOUN
gc-55	97	3	of	of	ADP
gc-55	97	4	the	the	DET
gc-55	97	5	neural	neural	ADJ
gc-55	97	6	network	network	NOUN
gc-55	97	7	,	,	PUNCT
gc-55	97	8	we	we	PRON
gc-55	97	9	used	use	VERB
gc-55	97	10	manually	manually	ADV
gc-55	97	11	determined	determine	VERB
gc-55	97	12	lithology	lithology	NOUN
gc-55	97	13	.	.	PUNCT
gc-55	98	1	results	result	NOUN
gc-55	98	2	described	describe	VERB
gc-55	98	3	in	in	ADP
gc-55	98	4	the	the	DET
gc-55	98	5	tables	table	NOUN
gc-55	98	6	represent	represent	VERB
gc-55	98	7	the	the	DET
gc-55	98	8	success	success	NOUN
gc-55	98	9	of	of	ADP
gc-55	98	10	the	the	DET
gc-55	98	11	neural	neural	ADJ
gc-55	98	12	network	network	NOUN
gc-55	98	13	training	training	NOUN
gc-55	98	14	.	.	PUNCT
gc-55	99	1	values	value	NOUN
gc-55	99	2	are	be	AUX
gc-55	99	3	shown	show	VERB
gc-55	99	4	as	as	ADP
gc-55	99	5	training	training	NOUN
gc-55	99	6	error	error	NOUN
gc-55	99	7	and	and	CCONJ
gc-55	99	8	prediction	prediction	NOUN
gc-55	99	9	error	error	NOUN
gc-55	99	10	.	.	PUNCT
gc-55	100	1	the	the	DET
gc-55	100	2	program	program	NOUN
gc-55	100	3	in	in	ADP
gc-55	100	4	which	which	PRON
gc-55	100	5	the	the	DET
gc-55	100	6	analyses	analysis	NOUN
gc-55	100	7	were	be	AUX
gc-55	100	8	made	make	VERB
gc-55	100	9	automatically	automatically	ADV
gc-55	100	10	divides	divide	VERB
gc-55	100	11	the	the	DET
gc-55	100	12	training	training	NOUN
gc-55	100	13	dataset	dataset	VERB
gc-55	100	14	into	into	ADP
gc-55	100	15	two	two	NUM
gc-55	100	16	parts	part	NOUN
gc-55	100	17	,	,	PUNCT
gc-55	100	18	the	the	DET
gc-55	100	19	length	length	NOUN
gc-55	100	20	of	of	ADP
gc-55	100	21	which	which	PRON
gc-55	100	22	is	be	AUX
gc-55	100	23	user	user	NOUN
gc-55	100	24	defi	defi	PROPN
gc-55	100	25	ned	ned	PROPN
gc-55	100	26	.	.	PUNCT
gc-55	101	1	the	the	DET
gc-55	101	2	fi	fi	NOUN
gc-55	101	3	rst	rst	PROPN
gc-55	101	4	set	set	NOUN
gc-55	101	5	is	be	AUX
gc-55	101	6	used	use	VERB
gc-55	101	7	for	for	ADP
gc-55	101	8	training	training	NOUN
gc-55	101	9	of	of	ADP
gc-55	101	10	the	the	DET
gc-55	101	11	neural	neural	ADJ
gc-55	101	12	network	network	NOUN
gc-55	101	13	;	;	PUNCT
gc-55	101	14	the	the	DET
gc-55	101	15	second	second	ADJ
gc-55	101	16	,	,	PUNCT
gc-55	101	17	for	for	ADP
gc-55	101	18	testing	test	VERB
gc-55	101	19	the	the	DET
gc-55	101	20	neural	neural	ADJ
gc-55	101	21	network	network	NOUN
gc-55	101	22	’s	’s	PART
gc-55	101	23	ability	ability	NOUN
gc-55	101	24	to	to	PART
gc-55	101	25	predict	predict	VERB
gc-55	101	26	cases	case	NOUN
gc-55	101	27	.	.	PUNCT
gc-55	102	1	this	this	DET
gc-55	102	2	kind	kind	NOUN
gc-55	102	3	of	of	ADP
gc-55	102	4	data	datum	NOUN
gc-55	102	5	distribution	distribution	NOUN
gc-55	102	6	minimizes	minimize	VERB
gc-55	102	7	the	the	DET
gc-55	102	8	risk	risk	NOUN
gc-55	102	9	of	of	ADP
gc-55	102	10	overtraining	overtraining	NOUN
gc-55	102	11	.	.	PUNCT
gc-55	103	1	the	the	DET
gc-55	103	2	training	training	NOUN
gc-55	103	3	procedure	procedure	NOUN
gc-55	103	4	is	be	AUX
gc-55	103	5	stopped	stop	VERB
gc-55	103	6	when	when	SCONJ
gc-55	103	7	user	user	NOUN
gc-55	103	8	-	-	PUNCT
gc-55	103	9	defi	defi	NOUN
gc-55	103	10	ned	ned	NOUN
gc-55	103	11	conditions	condition	NOUN
gc-55	103	12	have	have	AUX
gc-55	103	13	been	be	AUX
gc-55	103	14	met	meet	VERB
gc-55	103	15	(	(	PUNCT
gc-55	103	16	fi	fi	NOUN
gc-55	103	17	nal	nal	ADJ
gc-55	103	18	number	number	NOUN
gc-55	103	19	of	of	ADP
gc-55	103	20	iterations	iteration	NOUN
gc-55	103	21	or	or	CCONJ
gc-55	103	22	desired	desire	VERB
gc-55	103	23	amount	amount	NOUN
gc-55	103	24	of	of	ADP
gc-55	103	25	error	error	NOUN
gc-55	103	26	)	)	PUNCT
gc-55	103	27	or	or	CCONJ
gc-55	103	28	when	when	SCONJ
gc-55	103	29	the	the	DET
gc-55	103	30	program	program	NOUN
gc-55	103	31	decides	decide	VERB
gc-55	103	32	that	that	SCONJ
gc-55	103	33	further	further	ADJ
gc-55	103	34	training	training	NOUN
gc-55	103	35	will	will	AUX
gc-55	103	36	no	no	ADV
gc-55	103	37	longer	long	ADV
gc-55	103	38	yield	yield	VERB
gc-55	103	39	better	well	ADJ
gc-55	103	40	results	result	NOUN
gc-55	103	41	.	.	PUNCT
gc-55	104	1	results	result	NOUN
gc-55	104	2	of	of	ADP
gc-55	104	3	neural	neural	ADJ
gc-55	104	4	network	network	NOUN
gc-55	104	5	training	training	NOUN
gc-55	104	6	for	for	ADP
gc-55	104	7	the	the	DET
gc-55	104	8	prediction	prediction	NOUN
gc-55	104	9	of	of	ADP
gc-55	104	10	lithology	lithology	NOUN
gc-55	104	11	are	be	AUX
gc-55	104	12	given	give	VERB
gc-55	104	13	in	in	ADP
gc-55	104	14	table	table	NOUN
gc-55	104	15	1	1	NUM
gc-55	104	16	and	and	CCONJ
gc-55	104	17	expressed	express	VERB
gc-55	104	18	as	as	ADP
gc-55	104	19	two	two	NUM
gc-55	104	20	error	error	NOUN
gc-55	104	21	values	value	NOUN
gc-55	104	22	in	in	ADP
gc-55	104	23	percentages	percentage	NOUN
gc-55	104	24	.	.	PUNCT
gc-55	105	1	the	the	DET
gc-55	105	2	training	training	NOUN
gc-55	105	3	error	error	NOUN
gc-55	105	4	corresponds	correspond	VERB
gc-55	105	5	to	to	ADP
gc-55	105	6	the	the	DET
gc-55	105	7	previously	previously	ADV
gc-55	105	8	mentioned	mention	VERB
gc-55	105	9	dataset	dataset	NOUN
gc-55	105	10	that	that	PRON
gc-55	105	11	was	be	AUX
gc-55	105	12	used	use	VERB
gc-55	105	13	for	for	ADP
gc-55	105	14	training	train	VERB
gc-55	105	15	the	the	DET
gc-55	105	16	neural	neural	ADJ
gc-55	105	17	network	network	NOUN
gc-55	105	18	.	.	PUNCT
gc-55	106	1	the	the	DET
gc-55	106	2	selection	selection	NOUN
gc-55	106	3	error	error	NOUN
gc-55	106	4	describes	describe	VERB
gc-55	106	5	the	the	DET
gc-55	106	6	neural	neural	ADJ
gc-55	106	7	network	network	NOUN
gc-55	106	8	’s	’s	PART
gc-55	106	9	success	success	NOUN
gc-55	106	10	for	for	ADP
gc-55	106	11	predicting	predict	VERB
gc-55	106	12	the	the	DET
gc-55	106	13	values	value	NOUN
gc-55	106	14	on	on	ADP
gc-55	106	15	unknown	unknown	ADJ
gc-55	106	16	data	datum	NOUN
gc-55	106	17	.	.	PUNCT
gc-55	107	1	two	two	NUM
gc-55	107	2	neural	neural	ADJ
gc-55	107	3	networks	network	NOUN
gc-55	107	4	were	be	AUX
gc-55	107	5	trained	train	VERB
gc-55	107	6	for	for	ADP
gc-55	107	7	each	each	PRON
gc-55	107	8	well	well	NOUN
gc-55	107	9	,	,	PUNCT
gc-55	107	10	one	one	NUM
gc-55	107	11	mlp	mlp	NOUN
gc-55	107	12	and	and	CCONJ
gc-55	107	13	one	one	NUM
gc-55	107	14	rbf	rbf	PROPN
gc-55	107	15	network	network	NOUN
gc-55	107	16	.	.	PUNCT
gc-55	108	1	here	here	ADV
gc-55	108	2	the	the	DET
gc-55	108	3	prediction	prediction	NOUN
gc-55	108	4	could	could	AUX
gc-55	108	5	only	only	ADV
gc-55	108	6	be	be	AUX
gc-55	108	7	done	do	VERB
gc-55	108	8	on	on	ADP
gc-55	108	9	the	the	DET
gc-55	108	10	deeper	deep	ADJ
gc-55	108	11	or	or	CCONJ
gc-55	108	12	shallower	shallower	VERB
gc-55	108	13	parts	part	NOUN
gc-55	108	14	of	of	ADP
gc-55	108	15	the	the	DET
gc-55	108	16	well	well	INTJ
gc-55	108	17	log	log	NOUN
gc-55	108	18	in	in	ADP
gc-55	108	19	the	the	DET
gc-55	108	20	same	same	ADJ
gc-55	108	21	well	well	NOUN
gc-55	108	22	;	;	PUNCT
gc-55	108	23	cross	cross	NOUN
gc-55	108	24	-	-	NOUN
gc-55	108	25	prediction	prediction	NOUN
gc-55	108	26	or	or	CCONJ
gc-55	108	27	2d	2d	NUM
gc-55	108	28	neural	neural	ADJ
gc-55	108	29	network	network	NOUN
gc-55	108	30	analysis	analysis	NOUN
gc-55	108	31	did	do	AUX
gc-55	108	32	not	not	PART
gc-55	108	33	yield	yield	VERB
gc-55	108	34	satisfactory	satisfactory	ADJ
gc-55	108	35	results	result	NOUN
gc-55	108	36	here	here	ADV
gc-55	108	37	because	because	SCONJ
gc-55	108	38	of	of	ADP
gc-55	108	39	the	the	DET
gc-55	108	40	different	different	ADJ
gc-55	108	41	values	value	NOUN
gc-55	108	42	of	of	ADP
gc-55	108	43	sp	sp	ADP
gc-55	108	44	logs	log	NOUN
gc-55	108	45	in	in	ADP
gc-55	108	46	the	the	DET
gc-55	108	47	two	two	NUM
gc-55	108	48	wells	well	NOUN
gc-55	108	49	.	.	PUNCT
gc-55	109	1	table	table	NOUN
gc-55	109	2	1	1	NUM
gc-55	109	3	shows	show	VERB
gc-55	109	4	that	that	SCONJ
gc-55	109	5	both	both	PRON
gc-55	109	6	of	of	ADP
gc-55	109	7	the	the	DET
gc-55	109	8	neural	neural	ADJ
gc-55	109	9	networks	network	NOUN
gc-55	109	10	have	have	AUX
gc-55	109	11	been	be	AUX
gc-55	109	12	successfully	successfully	ADV
gc-55	109	13	trained	train	VERB
gc-55	109	14	on	on	ADP
gc-55	109	15	the	the	DET
gc-55	109	16	corresponding	corresponding	ADJ
gc-55	109	17	interval	interval	NOUN
gc-55	109	18	.	.	PUNCT
gc-55	110	1	the	the	DET
gc-55	110	2	anomaly	anomaly	NOUN
gc-55	110	3	is	be	AUX
gc-55	110	4	shown	show	VERB
gc-55	110	5	in	in	ADP
gc-55	110	6	table	table	NOUN
gc-55	110	7	1	1	NUM
gc-55	110	8	,	,	PUNCT
gc-55	110	9	where	where	SCONJ
gc-55	110	10	the	the	DET
gc-55	110	11	mlp	mlp	NOUN
gc-55	110	12	network	network	NOUN
gc-55	110	13	showed	show	VERB
gc-55	110	14	a	a	DET
gc-55	110	15	high	high	ADJ
gc-55	110	16	training	training	NOUN
gc-55	110	17	error	error	NOUN
gc-55	110	18	but	but	CCONJ
gc-55	110	19	low	low	ADJ
gc-55	110	20	selection	selection	NOUN
gc-55	110	21	error	error	NOUN
gc-55	110	22	.	.	PUNCT
gc-55	111	1	initially	initially	ADV
gc-55	111	2	one	one	PRON
gc-55	111	3	might	might	AUX
gc-55	111	4	presume	presume	VERB
gc-55	111	5	that	that	SCONJ
gc-55	111	6	the	the	DET
gc-55	111	7	rbf	rbf	PROPN
gc-55	111	8	network	network	NOUN
gc-55	111	9	with	with	ADP
gc-55	111	10	signifi	signifi	NOUN
gc-55	111	11	cantly	cantly	ADV
gc-55	111	12	lower	low	ADJ
gc-55	111	13	training	training	NOUN
gc-55	111	14	error	error	NOUN
gc-55	111	15	is	be	AUX
gc-55	111	16	more	more	ADV
gc-55	111	17	successful	successful	ADJ
gc-55	111	18	in	in	ADP
gc-55	111	19	predicting	predict	VERB
gc-55	111	20	the	the	DET
gc-55	111	21	unknown	unknown	ADJ
gc-55	111	22	data	data	NOUN
gc-55	111	23	interval	interval	NOUN
gc-55	111	24	,	,	PUNCT
gc-55	111	25	but	but	CCONJ
gc-55	111	26	this	this	PRON
gc-55	111	27	is	be	AUX
gc-55	111	28	not	not	PART
gc-55	111	29	the	the	DET
gc-55	111	30	case	case	NOUN
gc-55	111	31	.	.	PUNCT
gc-55	112	1	the	the	DET
gc-55	112	2	mlp	mlp	PROPN
gc-55	112	3	network	network	NOUN
gc-55	112	4	had	have	VERB
gc-55	112	5	slightly	slightly	ADV
gc-55	112	6	better	well	ADJ
gc-55	112	7	results	result	NOUN
gc-55	112	8	than	than	ADP
gc-55	112	9	the	the	DET
gc-55	112	10	rbf	rbf	PROPN
gc-55	112	11	,	,	PUNCT
gc-55	112	12	so	so	SCONJ
gc-55	112	13	we	we	PRON
gc-55	112	14	conclude	conclude	VERB
gc-55	112	15	that	that	SCONJ
gc-55	112	16	the	the	DET
gc-55	112	17	value	value	NOUN
gc-55	112	18	of	of	ADP
gc-55	112	19	the	the	DET
gc-55	112	20	selection	selection	NOUN
gc-55	112	21	error	error	NOUN
gc-55	112	22	is	be	AUX
gc-55	112	23	a	a	DET
gc-55	112	24	much	much	ADV
gc-55	112	25	more	more	ADV
gc-55	112	26	reliable	reliable	ADJ
gc-55	112	27	indicator	indicator	NOUN
gc-55	112	28	of	of	ADP
gc-55	112	29	success	success	NOUN
gc-55	112	30	of	of	ADP
gc-55	112	31	a	a	DET
gc-55	112	32	neural	neural	ADJ
gc-55	112	33	network	network	NOUN
gc-55	112	34	than	than	SCONJ
gc-55	112	35	the	the	DET
gc-55	112	36	training	training	NOUN
gc-55	112	37	error	error	NOUN
gc-55	112	38	is	be	AUX
gc-55	112	39	.	.	PUNCT
gc-55	113	1	thus	thus	ADV
gc-55	113	2	,	,	PUNCT
gc-55	113	3	when	when	SCONJ
gc-55	113	4	neural	neural	ADJ
gc-55	113	5	network	network	NOUN
gc-55	113	6	training	training	NOUN
gc-55	113	7	is	be	AUX
gc-55	113	8	fi	fi	NOUN
gc-55	113	9	nished	nishe	VERB
gc-55	113	10	,	,	PUNCT
gc-55	113	11	the	the	DET
gc-55	113	12	best	good	ADJ
gc-55	113	13	network	network	NOUN
gc-55	113	14	parameters	parameter	NOUN
gc-55	113	15	are	be	AUX
gc-55	113	16	the	the	DET
gc-55	113	17	ones	one	NOUN
gc-55	113	18	with	with	ADP
gc-55	113	19	the	the	DET
gc-55	113	20	smallest	small	ADJ
gc-55	113	21	selection	selection	NOUN
gc-55	113	22	errors	error	NOUN
gc-55	113	23	.	.	PUNCT
gc-55	114	1	the	the	DET
gc-55	114	2	relationship	relationship	NOUN
gc-55	114	3	between	between	ADP
gc-55	114	4	manually	manually	ADV
gc-55	114	5	determined	determine	VERB
gc-55	114	6	lithology	lithology	NOUN
gc-55	114	7	and	and	CCONJ
gc-55	114	8	lithology	lithology	NOUN
gc-55	114	9	gained	gain	VERB
gc-55	114	10	from	from	ADP
gc-55	114	11	neural	neural	ADJ
gc-55	114	12	network	network	NOUN
gc-55	114	13	analysis	analysis	NOUN
gc-55	114	14	is	be	AUX
gc-55	114	15	shown	show	VERB
gc-55	114	16	in	in	ADP
gc-55	114	17	figs	fig	NOUN
gc-55	114	18	.	.	PUNCT
gc-55	115	1	4	4	NUM
gc-55	115	2	and	and	CCONJ
gc-55	115	3	5	5	NUM
gc-55	115	4	.	.	NOUN
gc-55	115	5	4.2	4.2	NUM
gc-55	115	6	.	.	PUNCT
gc-55	115	7	hydrocarbon	hydrocarbon	NOUN
gc-55	115	8	saturation	saturation	NOUN
gc-55	115	9	prediction	prediction	NOUN
gc-55	115	10	as	as	SCONJ
gc-55	115	11	opposed	oppose	VERB
gc-55	115	12	to	to	ADP
gc-55	115	13	lithology	lithology	NOUN
gc-55	115	14	prediction	prediction	NOUN
gc-55	115	15	,	,	PUNCT
gc-55	115	16	hydrocarbon	hydrocarbon	NOUN
gc-55	115	17	saturation	saturation	NOUN
gc-55	115	18	prediction	prediction	NOUN
gc-55	115	19	uses	use	VERB
gc-55	115	20	cross	cross	NOUN
gc-55	115	21	-	-	NOUN
gc-55	115	22	prediction	prediction	NOUN
gc-55	115	23	.	.	PUNCT
gc-55	116	1	the	the	DET
gc-55	116	2	neural	neural	ADJ
gc-55	116	3	network	network	NOUN
gc-55	116	4	is	be	AUX
gc-55	116	5	trained	train	VERB
gc-55	116	6	on	on	ADP
gc-55	116	7	one	one	NUM
gc-55	116	8	well	well	ADV
gc-55	116	9	log	log	NOUN
gc-55	116	10	interval	interval	NOUN
gc-55	116	11	,	,	PUNCT
gc-55	116	12	much	much	ADV
gc-55	116	13	larger	large	ADJ
gc-55	116	14	than	than	ADP
gc-55	116	15	in	in	ADP
gc-55	116	16	the	the	DET
gc-55	116	17	former	former	ADJ
gc-55	116	18	prediction	prediction	NOUN
gc-55	116	19	case	case	NOUN
gc-55	116	20	.	.	PUNCT
gc-55	117	1	training	training	NOUN
gc-55	117	2	had	have	AUX
gc-55	117	3	been	be	AUX
gc-55	117	4	done	do	VERB
gc-55	117	5	on	on	ADP
gc-55	117	6	one	one	NUM
gc-55	117	7	well	well	ADV
gc-55	117	8	,	,	PUNCT
gc-55	117	9	klo	klo	PROPN
gc-55	117	10	–	–	PUNCT
gc-55	117	11	a	a	PRON
gc-55	117	12	,	,	PUNCT
gc-55	117	13	and	and	CCONJ
gc-55	117	14	prediction	prediction	NOUN
gc-55	117	15	had	have	AUX
gc-55	117	16	been	be	AUX
gc-55	117	17	performed	perform	VERB
gc-55	117	18	on	on	ADP
gc-55	117	19	another	another	DET
gc-55	117	20	well	well	NOUN
gc-55	117	21	,	,	PUNCT
gc-55	117	22	fi	fi	X
gc-55	117	23	gu	gu	NOUN
gc-55	117	24	re	re	ADP
gc-55	117	25	3	3	NUM
gc-55	117	26	:	:	PUNCT
gc-55	117	27	part	part	NOUN
gc-55	117	28	of	of	ADP
gc-55	117	29	the	the	DET
gc-55	117	30	klo	klo	PROPN
gc-55	117	31	–	–	PUNCT
gc-55	117	32	b	b	NOUN
gc-55	117	33	well	well	INTJ
gc-55	117	34	log	log	NOUN
gc-55	117	35	representing	represent	VERB
gc-55	117	36	the	the	DET
gc-55	117	37	interval	interval	NOUN
gc-55	117	38	for	for	ADP
gc-55	117	39	the	the	DET
gc-55	117	40	i	i	PROPN
gc-55	117	41	sandstone	sandstone	NOUN
gc-55	117	42	series	series	NOUN
gc-55	117	43	.	.	PUNCT
gc-55	118	1	table	table	NOUN
gc-55	118	2	1	1	NUM
gc-55	118	3	:	:	PUNCT
gc-55	118	4	neural	neural	ADJ
gc-55	118	5	network	network	NOUN
gc-55	118	6	parameters	parameter	NOUN
gc-55	118	7	for	for	ADP
gc-55	118	8	lithology	lithology	NOUN
gc-55	118	9	prediction	prediction	NOUN
gc-55	118	10	neural	neural	ADJ
gc-55	118	11	network	network	NOUN
gc-55	118	12	type	type	NOUN
gc-55	118	13	and	and	CCONJ
gc-55	118	14	propertiesa	propertiesa	ADJ
gc-55	118	15	well	well	ADJ
gc-55	118	16	training	training	NOUN
gc-55	118	17	errorb	errorb	NOUN
gc-55	118	18	selection	selection	NOUN
gc-55	118	19	errorb	errorb	NOUN
gc-55	118	20	rbf	rbf	PROPN
gc-55	118	21	3–31–1	3–31–1	PROPN
gc-55	118	22	klo	klo	PROPN
gc-55	118	23	-	-	PROPN
gc-55	118	24	a	a	DET
gc-55	118	25	0.152942	0.152942	NUM
gc-55	118	26	0.172753	0.172753	NUM
gc-55	118	27	mlp	mlp	NOUN
gc-55	118	28	3–4–6–3–1	3–4–6–3–1	NUM
gc-55	118	29	klo	klo	PROPN
gc-55	118	30	-	-	PROPN
gc-55	118	31	a	a	DET
gc-55	118	32	0.31438	0.31438	NUM
gc-55	118	33	0.133478	0.133478	NUM
gc-55	118	34	rbf	rbf	PROPN
gc-55	118	35	3–13–1	3–13–1	NUM
gc-55	118	36	klo	klo	PROPN
gc-55	118	37	-	-	PROPN
gc-55	118	38	b	b	PROPN
gc-55	118	39	0.156621	0.156621	NUM
gc-55	118	40	0.149185	0.149185	NUM
gc-55	118	41	mlp	mlp	NOUN
gc-55	118	42	3–6–4–2–1	3–6–4–2–1	NUM
gc-55	118	43	klo	klo	PROPN
gc-55	118	44	-	-	PROPN
gc-55	118	45	b	b	PROPN
gc-55	118	46	0.255012	0.255012	NUM
gc-55	118	47	0.214935	0.214935	NUM
gc-55	118	48	a	a	DET
gc-55	118	49	neural	neural	ADJ
gc-55	118	50	network	network	NOUN
gc-55	118	51	type	type	NOUN
gc-55	118	52	and	and	CCONJ
gc-55	118	53	properties	property	NOUN
gc-55	118	54	correspond	correspond	VERB
gc-55	118	55	to	to	ADP
gc-55	118	56	the	the	DET
gc-55	118	57	type	type	NOUN
gc-55	118	58	of	of	ADP
gc-55	118	59	network	network	NOUN
gc-55	118	60	and	and	CCONJ
gc-55	118	61	number	number	NOUN
gc-55	118	62	of	of	ADP
gc-55	118	63	neurons	neuron	NOUN
gc-55	118	64	per	per	ADP
gc-55	118	65	layer	layer	NOUN
gc-55	118	66	where	where	SCONJ
gc-55	118	67	fi	fi	NOUN
gc-55	118	68	rst	rst	PROPN
gc-55	118	69	and	and	CCONJ
gc-55	118	70	last	last	ADJ
gc-55	118	71	number	number	NOUN
gc-55	118	72	represent	represent	VERB
gc-55	118	73	the	the	DET
gc-55	118	74	properties	property	NOUN
gc-55	118	75	of	of	ADP
gc-55	118	76	the	the	DET
gc-55	118	77	input	input	NOUN
gc-55	118	78	and	and	CCONJ
gc-55	118	79	output	output	NOUN
gc-55	118	80	layer	layer	NOUN
gc-55	118	81	.	.	PUNCT
gc-55	119	1	values	value	NOUN
gc-55	119	2	between	between	ADP
gc-55	119	3	these	these	PRON
gc-55	119	4	represent	represent	VERB
gc-55	119	5	the	the	DET
gc-55	119	6	number	number	NOUN
gc-55	119	7	and	and	CCONJ
gc-55	119	8	properties	property	NOUN
gc-55	119	9	of	of	ADP
gc-55	119	10	the	the	DET
gc-55	119	11	hidden	hidden	ADJ
gc-55	119	12	layers	layer	NOUN
gc-55	119	13	.	.	PUNCT
gc-55	120	1	b	b	X
gc-55	120	2	error	error	NOUN
gc-55	120	3	value	value	NOUN
gc-55	120	4	ranges	range	VERB
gc-55	120	5	from	from	ADP
gc-55	120	6	0	0	NUM
gc-55	120	7	to	to	ADP
gc-55	120	8	1	1	NUM
gc-55	120	9	,	,	PUNCT
gc-55	120	10	where	where	SCONJ
gc-55	120	11	0	0	NUM
gc-55	120	12	represents	represent	VERB
gc-55	120	13	100	100	NUM
gc-55	120	14	%	%	NOUN
gc-55	120	15	success	success	NOUN
gc-55	120	16	of	of	ADP
gc-55	120	17	prediction	prediction	NOUN
gc-55	120	18	,	,	PUNCT
gc-55	120	19	i.e.	i.e.	X
gc-55	120	20	,	,	PUNCT
gc-55	120	21	no	no	DET
gc-55	120	22	error	error	NOUN
gc-55	120	23	.	.	PUNCT
gc-55	121	1	geologia	geologia	PROPN
gc-55	121	2	croaticacvetković	croaticacvetković	NOUN
gc-55	121	3	et	et	PROPN
gc-55	121	4	al	al	PROPN
gc-55	121	5	.	.	PROPN
gc-55	121	6	:	:	PUNCT
gc-55	122	1	application	application	NOUN
gc-55	122	2	of	of	ADP
gc-55	122	3	neural	neural	ADJ
gc-55	122	4	networks	network	NOUN
gc-55	122	5	in	in	ADP
gc-55	122	6	petroleum	petroleum	NOUN
gc-55	122	7	reservoir	reservoir	NOUN
gc-55	122	8	lithology	lithology	NOUN
gc-55	122	9	and	and	CCONJ
gc-55	122	10	saturation	saturation	NOUN
gc-55	122	11	prediction	prediction	NOUN
gc-55	122	12	119	119	NUM
gc-55	122	13	klo	klo	PROPN
gc-55	122	14	–	–	PUNCT
gc-55	122	15	b.	b.	PROPN
gc-55	122	16	for	for	ADP
gc-55	122	17	input	input	NOUN
gc-55	122	18	data	datum	NOUN
gc-55	122	19	we	we	PRON
gc-55	122	20	used	use	VERB
gc-55	122	21	resistivity	resistivity	NOUN
gc-55	122	22	logs	log	NOUN
gc-55	122	23	(	(	PUNCT
gc-55	122	24	r16	r16	NOUN
gc-55	122	25	,	,	PUNCT
gc-55	122	26	r64	r64	NOUN
gc-55	122	27	)	)	PUNCT
gc-55	122	28	,	,	PUNCT
gc-55	122	29	sp	sp	ADP
gc-55	122	30	logs	log	NOUN
gc-55	122	31	,	,	PUNCT
gc-55	122	32	corresponding	correspond	VERB
gc-55	122	33	data	datum	NOUN
gc-55	122	34	about	about	ADV
gc-55	122	35	well	well	ADV
gc-55	122	36	depth	depth	NOUN
gc-55	122	37	and	and	CCONJ
gc-55	122	38	lithology	lithology	NOUN
gc-55	122	39	,	,	PUNCT
gc-55	122	40	and	and	CCONJ
gc-55	122	41	the	the	DET
gc-55	122	42	hydrocarbon	hydrocarbon	NOUN
gc-55	122	43	saturation	saturation	NOUN
gc-55	122	44	value	value	NOUN
gc-55	122	45	.	.	PUNCT
gc-55	123	1	hydrocarbon	hydrocarbon	NOUN
gc-55	123	2	saturation	saturation	NOUN
gc-55	123	3	was	be	AUX
gc-55	123	4	manually	manually	ADV
gc-55	123	5	determined	determine	VERB
gc-55	123	6	from	from	ADP
gc-55	123	7	resistivity	resistivity	NOUN
gc-55	123	8	log	log	NOUN
gc-55	123	9	r64	r64	NOUN
gc-55	123	10	.	.	PUNCT
gc-55	124	1	the	the	DET
gc-55	124	2	corresponding	correspond	VERB
gc-55	124	3	data	datum	NOUN
gc-55	124	4	well	well	NOUN
gc-55	124	5	depth	depth	NOUN
gc-55	124	6	gave	give	VERB
gc-55	124	7	better	well	ADJ
gc-55	124	8	results	result	NOUN
gc-55	124	9	in	in	ADP
gc-55	124	10	this	this	DET
gc-55	124	11	neural	neural	ADJ
gc-55	124	12	network	network	NOUN
gc-55	124	13	performance	performance	NOUN
gc-55	124	14	than	than	ADP
gc-55	124	15	in	in	ADP
gc-55	124	16	lithology	lithology	NOUN
gc-55	124	17	prediction	prediction	NOUN
gc-55	124	18	,	,	PUNCT
gc-55	124	19	where	where	SCONJ
gc-55	124	20	it	it	PRON
gc-55	124	21	had	have	VERB
gc-55	124	22	little	little	ADJ
gc-55	124	23	or	or	CCONJ
gc-55	124	24	no	no	PRON
gc-55	124	25	effect	effect	NOUN
gc-55	124	26	.	.	PUNCT
gc-55	125	1	hydrocarbon	hydrocarbon	NOUN
gc-55	125	2	saturation	saturation	NOUN
gc-55	125	3	value	value	NOUN
gc-55	125	4	,	,	PUNCT
gc-55	125	5	as	as	ADV
gc-55	125	6	well	well	ADV
gc-55	125	7	as	as	ADP
gc-55	125	8	lithology	lithology	NOUN
gc-55	125	9	,	,	PUNCT
gc-55	125	10	was	be	AUX
gc-55	125	11	defi	defi	NOUN
gc-55	125	12	ned	ned	NOUN
gc-55	125	13	as	as	ADP
gc-55	125	14	a	a	DET
gc-55	125	15	categorical	categorical	ADJ
gc-55	125	16	value	value	NOUN
gc-55	125	17	.	.	PUNCT
gc-55	126	1	here	here	ADV
gc-55	126	2	“	"	PUNCT
gc-55	126	3	1	1	NUM
gc-55	126	4	”	"	PUNCT
gc-55	126	5	stands	stand	VERB
gc-55	126	6	for	for	ADP
gc-55	126	7	positive	positive	ADJ
gc-55	126	8	hydrocarbon	hydrocarbon	NOUN
gc-55	126	9	accumulation	accumulation	NOUN
gc-55	126	10	and	and	CCONJ
gc-55	126	11	“	"	PUNCT
gc-55	126	12	0	0	NUM
gc-55	126	13	”	"	PUNCT
gc-55	126	14	for	for	ADP
gc-55	126	15	fi	fi	NOUN
gc-55	126	16	gu	gu	NOUN
gc-55	126	17	re	re	ADP
gc-55	126	18	4	4	NUM
gc-55	126	19	:	:	PUNCT
gc-55	126	20	comparison	comparison	NOUN
gc-55	126	21	of	of	ADP
gc-55	126	22	mlp	mlp	PROPN
gc-55	126	23	neural	neural	PROPN
gc-55	126	24	network	network	NOUN
gc-55	126	25	predicted	predict	VERB
gc-55	126	26	(	(	PUNCT
gc-55	126	27	dotted	dotted	ADJ
gc-55	126	28	line	line	NOUN
gc-55	126	29	)	)	PUNCT
gc-55	126	30	and	and	CCONJ
gc-55	126	31	manually	manually	ADV
gc-55	126	32	determined	determine	VERB
gc-55	126	33	data	datum	NOUN
gc-55	126	34	(	(	PUNCT
gc-55	126	35	solid	solid	ADJ
gc-55	126	36	line	line	NOUN
gc-55	126	37	)	)	PUNCT
gc-55	126	38	in	in	ADP
gc-55	126	39	lithology	lithology	NOUN
gc-55	126	40	prediction	prediction	NOUN
gc-55	126	41	analysis	analysis	NOUN
gc-55	126	42	for	for	ADP
gc-55	126	43	well	well	ADV
gc-55	126	44	klo	klo	PROPN
gc-55	126	45	–	–	PUNCT
gc-55	126	46	a.	a.	NOUN
gc-55	127	1	the	the	DET
gc-55	127	2	diagram	diagram	NOUN
gc-55	127	3	’s	’s	PART
gc-55	127	4	abscissa	abscissa	NOUN
gc-55	127	5	represents	represent	VERB
gc-55	127	6	vertical	vertical	ADJ
gc-55	127	7	depth	depth	NOUN
gc-55	127	8	,	,	PUNCT
gc-55	127	9	and	and	CCONJ
gc-55	127	10	the	the	DET
gc-55	127	11	ordinate	ordinate	NOUN
gc-55	127	12	represents	represent	VERB
gc-55	127	13	the	the	DET
gc-55	127	14	value	value	NOUN
gc-55	127	15	of	of	ADP
gc-55	127	16	lithology	lithology	NOUN
gc-55	127	17	expressed	express	VERB
gc-55	127	18	as	as	ADP
gc-55	127	19	either	either	DET
gc-55	127	20	marl	marl	NOUN
gc-55	127	21	(	(	PUNCT
gc-55	127	22	0	0	NUM
gc-55	127	23	)	)	PUNCT
gc-55	127	24	or	or	CCONJ
gc-55	127	25	sandstone	sandstone	NOUN
gc-55	127	26	(	(	PUNCT
gc-55	127	27	1	1	NUM
gc-55	127	28	)	)	PUNCT
gc-55	127	29	.	.	PUNCT
gc-55	128	1	fi	fi	PROPN
gc-55	128	2	gu	gu	NOUN
gc-55	128	3	re	re	ADP
gc-55	128	4	5	5	NUM
gc-55	128	5	:	:	PUNCT
gc-55	128	6	comparison	comparison	NOUN
gc-55	128	7	of	of	ADP
gc-55	128	8	rbf	rbf	PROPN
gc-55	128	9	neural	neural	PROPN
gc-55	128	10	network	network	NOUN
gc-55	128	11	predicted	predict	VERB
gc-55	128	12	(	(	PUNCT
gc-55	128	13	dotted	dotted	ADJ
gc-55	128	14	line	line	NOUN
gc-55	128	15	)	)	PUNCT
gc-55	128	16	and	and	CCONJ
gc-55	128	17	manually	manually	ADV
gc-55	128	18	determined	determine	VERB
gc-55	128	19	data	datum	NOUN
gc-55	128	20	(	(	PUNCT
gc-55	128	21	full	full	ADJ
gc-55	128	22	line	line	NOUN
gc-55	128	23	)	)	PUNCT
gc-55	128	24	in	in	ADP
gc-55	128	25	lithology	lithology	NOUN
gc-55	128	26	prediction	prediction	NOUN
gc-55	128	27	analysis	analysis	NOUN
gc-55	128	28	for	for	ADP
gc-55	128	29	well	well	ADV
gc-55	128	30	klo	klo	PROPN
gc-55	128	31	–	–	PUNCT
gc-55	128	32	b.	b.	VERB
gc-55	128	33	the	the	DET
gc-55	128	34	diagram	diagram	NOUN
gc-55	128	35	’s	’s	PART
gc-55	128	36	abscissa	abscissa	NOUN
gc-55	128	37	represents	represent	VERB
gc-55	128	38	vertical	vertical	ADJ
gc-55	128	39	depth	depth	NOUN
gc-55	128	40	,	,	PUNCT
gc-55	128	41	and	and	CCONJ
gc-55	128	42	the	the	DET
gc-55	128	43	ordinate	ordinate	NOUN
gc-55	128	44	represents	represent	VERB
gc-55	128	45	the	the	DET
gc-55	128	46	value	value	NOUN
gc-55	128	47	of	of	ADP
gc-55	128	48	lithology	lithology	NOUN
gc-55	128	49	expressed	express	VERB
gc-55	128	50	as	as	ADP
gc-55	128	51	either	either	DET
gc-55	128	52	marl	marl	NOUN
gc-55	128	53	(	(	PUNCT
gc-55	128	54	0	0	NUM
gc-55	128	55	)	)	PUNCT
gc-55	128	56	or	or	CCONJ
gc-55	128	57	sandstone	sandstone	NOUN
gc-55	128	58	(	(	PUNCT
gc-55	128	59	1	1	NUM
gc-55	128	60	)	)	PUNCT
gc-55	128	61	.	.	PUNCT
gc-55	129	1	table	table	NOUN
gc-55	129	2	2	2	NUM
gc-55	129	3	:	:	PUNCT
gc-55	129	4	neural	neural	ADJ
gc-55	129	5	network	network	NOUN
gc-55	129	6	parameters	parameter	NOUN
gc-55	129	7	for	for	ADP
gc-55	129	8	hydrocarbon	hydrocarbon	NOUN
gc-55	129	9	saturation	saturation	NOUN
gc-55	129	10	prediction	prediction	NOUN
gc-55	129	11	neural	neural	ADJ
gc-55	129	12	network	network	NOUN
gc-55	129	13	type	type	NOUN
gc-55	129	14	and	and	CCONJ
gc-55	129	15	propertiesa	propertiesa	ADJ
gc-55	129	16	training	training	NOUN
gc-55	129	17	errorb	errorb	NOUN
gc-55	129	18	selection	selection	NOUN
gc-55	129	19	errorb	errorb	NOUN
gc-55	129	20	mlp	mlp	PROPN
gc-55	130	1	5–6–8–1	5–6–8–1	NUM
gc-55	130	2	0.056897	0.056897	NUM
gc-55	130	3	0.091173	0.091173	NUM
gc-55	130	4	a	a	DET
gc-55	130	5	neural	neural	ADJ
gc-55	130	6	network	network	NOUN
gc-55	130	7	type	type	NOUN
gc-55	130	8	and	and	CCONJ
gc-55	130	9	properties	property	NOUN
gc-55	130	10	correspond	correspond	VERB
gc-55	130	11	to	to	ADP
gc-55	130	12	the	the	DET
gc-55	130	13	type	type	NOUN
gc-55	130	14	of	of	ADP
gc-55	130	15	network	network	NOUN
gc-55	130	16	and	and	CCONJ
gc-55	130	17	number	number	NOUN
gc-55	130	18	of	of	ADP
gc-55	130	19	neurons	neuron	NOUN
gc-55	130	20	per	per	ADP
gc-55	130	21	layer	layer	NOUN
gc-55	130	22	where	where	SCONJ
gc-55	130	23	the	the	DET
gc-55	130	24	fi	fi	NOUN
gc-55	130	25	rst	rst	PROPN
gc-55	130	26	and	and	CCONJ
gc-55	130	27	last	last	ADJ
gc-55	130	28	numbers	number	NOUN
gc-55	130	29	represent	represent	VERB
gc-55	130	30	the	the	DET
gc-55	130	31	properties	property	NOUN
gc-55	130	32	of	of	ADP
gc-55	130	33	the	the	DET
gc-55	130	34	input	input	NOUN
gc-55	130	35	and	and	CCONJ
gc-55	130	36	output	output	NOUN
gc-55	130	37	layer	layer	NOUN
gc-55	130	38	.	.	PUNCT
gc-55	131	1	values	value	NOUN
gc-55	131	2	between	between	ADP
gc-55	131	3	these	these	PRON
gc-55	131	4	represent	represent	VERB
gc-55	131	5	the	the	DET
gc-55	131	6	number	number	NOUN
gc-55	131	7	and	and	CCONJ
gc-55	131	8	properties	property	NOUN
gc-55	131	9	of	of	ADP
gc-55	131	10	the	the	DET
gc-55	131	11	hidden	hidden	ADJ
gc-55	131	12	layers	layer	NOUN
gc-55	131	13	.	.	PUNCT
gc-55	132	1	b	b	X
gc-55	132	2	error	error	NOUN
gc-55	132	3	value	value	NOUN
gc-55	132	4	ranges	range	VERB
gc-55	132	5	from	from	ADP
gc-55	132	6	0	0	NUM
gc-55	132	7	to	to	ADP
gc-55	132	8	1	1	NUM
gc-55	132	9	,	,	PUNCT
gc-55	132	10	where	where	SCONJ
gc-55	132	11	0	0	NUM
gc-55	132	12	represents	represent	VERB
gc-55	132	13	100	100	NUM
gc-55	132	14	%	%	NOUN
gc-55	132	15	success	success	NOUN
gc-55	132	16	of	of	ADP
gc-55	132	17	prediction	prediction	NOUN
gc-55	132	18	,	,	PUNCT
gc-55	132	19	i.e.	i.e.	X
gc-55	132	20	,	,	PUNCT
gc-55	132	21	no	no	DET
gc-55	132	22	error	error	NOUN
gc-55	132	23	.	.	PUNCT
gc-55	133	1	geologia	geologia	PROPN
gc-55	133	2	croatica	croatica	PROPN
gc-55	133	3	geologia	geologia	PROPN
gc-55	133	4	croatica	croatica	PROPN
gc-55	133	5	62/2	62/2	NUM
gc-55	133	6	120	120	NUM
gc-55	133	7	negative	negative	ADJ
gc-55	133	8	.	.	PUNCT
gc-55	134	1	for	for	ADP
gc-55	134	2	this	this	DET
gc-55	134	3	analysis	analysis	NOUN
gc-55	134	4	,	,	PUNCT
gc-55	134	5	only	only	ADV
gc-55	134	6	the	the	DET
gc-55	134	7	mlp	mlp	PROPN
gc-55	134	8	neural	neural	ADJ
gc-55	134	9	network	network	NOUN
gc-55	134	10	was	be	AUX
gc-55	134	11	used	use	VERB
gc-55	134	12	because	because	SCONJ
gc-55	134	13	an	an	DET
gc-55	134	14	rbf	rbf	PROPN
gc-55	134	15	network	network	NOUN
gc-55	134	16	was	be	AUX
gc-55	134	17	characterized	characterize	VERB
gc-55	134	18	by	by	ADP
gc-55	134	19	a	a	DET
gc-55	134	20	high	high	ADJ
gc-55	134	21	selection	selection	NOUN
gc-55	134	22	and	and	CCONJ
gc-55	134	23	training	training	NOUN
gc-55	134	24	error	error	NOUN
gc-55	134	25	.	.	PUNCT
gc-55	135	1	neural	neural	ADJ
gc-55	135	2	network	network	NOUN
gc-55	135	3	parameters	parameter	NOUN
gc-55	135	4	are	be	AUX
gc-55	135	5	shown	show	VERB
gc-55	135	6	in	in	ADP
gc-55	135	7	table	table	NOUN
gc-55	135	8	2	2	NUM
gc-55	135	9	.	.	PUNCT
gc-55	135	10	relationships	relationship	NOUN
gc-55	135	11	between	between	ADP
gc-55	135	12	manually	manually	ADV
gc-55	135	13	determined	determine	VERB
gc-55	135	14	and	and	CCONJ
gc-55	135	15	neural	neural	ADJ
gc-55	135	16	network	network	NOUN
gc-55	135	17	predicted	predict	VERB
gc-55	135	18	hydrocarbon	hydrocarbon	NOUN
gc-55	135	19	saturation	saturation	NOUN
gc-55	135	20	are	be	AUX
gc-55	135	21	shown	show	VERB
gc-55	135	22	in	in	ADP
gc-55	135	23	fig	fig	NOUN
gc-55	135	24	.	.	PUNCT
gc-55	136	1	6	6	NUM
gc-55	136	2	.	.	NOUN
gc-55	136	3	5	5	NUM
gc-55	136	4	.	.	X
gc-55	136	5	discussion	discussion	NOUN
gc-55	136	6	generally	generally	ADV
gc-55	136	7	,	,	PUNCT
gc-55	136	8	for	for	ADP
gc-55	136	9	all	all	DET
gc-55	136	10	neural	neural	ADJ
gc-55	136	11	network	network	NOUN
gc-55	136	12	analyses	analysis	NOUN
gc-55	136	13	,	,	PUNCT
gc-55	136	14	the	the	DET
gc-55	136	15	more	more	ADJ
gc-55	136	16	input	input	NOUN
gc-55	136	17	cases	case	NOUN
gc-55	136	18	and	and	CCONJ
gc-55	136	19	more	more	ADJ
gc-55	136	20	input	input	NOUN
gc-55	136	21	variables	variable	NOUN
gc-55	136	22	used	use	VERB
gc-55	136	23	,	,	PUNCT
gc-55	136	24	the	the	PRON
gc-55	136	25	more	more	ADV
gc-55	136	26	successful	successful	ADJ
gc-55	136	27	the	the	DET
gc-55	136	28	results	result	NOUN
gc-55	136	29	and	and	CCONJ
gc-55	136	30	the	the	DET
gc-55	136	31	better	well	ADJ
gc-55	136	32	prediction	prediction	NOUN
gc-55	136	33	will	will	AUX
gc-55	136	34	be	be	AUX
gc-55	136	35	.	.	PUNCT
gc-55	137	1	prediction	prediction	NOUN
gc-55	137	2	of	of	ADP
gc-55	137	3	the	the	DET
gc-55	137	4	lithology	lithology	NOUN
gc-55	137	5	has	have	AUX
gc-55	137	6	proven	prove	VERB
gc-55	137	7	reliable	reliable	ADJ
gc-55	137	8	only	only	ADV
gc-55	137	9	when	when	SCONJ
gc-55	137	10	the	the	DET
gc-55	137	11	extrapolation	extrapolation	NOUN
gc-55	137	12	of	of	ADP
gc-55	137	13	data	datum	NOUN
gc-55	137	14	was	be	AUX
gc-55	137	15	within	within	ADP
gc-55	137	16	one	one	NUM
gc-55	137	17	well	well	ADJ
gc-55	137	18	interval	interval	NOUN
gc-55	137	19	.	.	PUNCT
gc-55	138	1	in	in	ADP
gc-55	138	2	this	this	DET
gc-55	138	3	analysis	analysis	NOUN
gc-55	138	4	the	the	DET
gc-55	138	5	most	most	ADV
gc-55	138	6	signifi	signifi	NOUN
gc-55	138	7	ca	can	AUX
gc-55	138	8	nt	not	PART
gc-55	138	9	value	value	VERB
gc-55	138	10	was	be	AUX
gc-55	138	11	the	the	DET
gc-55	138	12	sp	sp	NOUN
gc-55	138	13	log	log	NOUN
gc-55	138	14	.	.	PUNCT
gc-55	139	1	with	with	ADP
gc-55	139	2	the	the	DET
gc-55	139	3	input	input	NOUN
gc-55	139	4	of	of	ADP
gc-55	139	5	resistivity	resistivity	NOUN
gc-55	139	6	logs	log	NOUN
gc-55	139	7	alone	alone	ADV
gc-55	139	8	,	,	PUNCT
gc-55	139	9	correspondence	correspondence	NOUN
gc-55	139	10	between	between	ADP
gc-55	139	11	true	true	ADJ
gc-55	139	12	and	and	CCONJ
gc-55	139	13	predicted	predict	VERB
gc-55	139	14	values	value	NOUN
gc-55	139	15	was	be	AUX
gc-55	139	16	not	not	PART
gc-55	139	17	satisfactory	satisfactory	ADJ
gc-55	139	18	.	.	PUNCT
gc-55	140	1	also	also	ADV
gc-55	140	2	,	,	PUNCT
gc-55	140	3	the	the	DET
gc-55	140	4	input	input	NOUN
gc-55	140	5	logs	log	NOUN
gc-55	140	6	were	be	AUX
gc-55	140	7	recorded	record	VERB
gc-55	140	8	in	in	ADP
gc-55	140	9	1956	1956	NUM
gc-55	140	10	and	and	CCONJ
gc-55	140	11	1957	1957	NUM
gc-55	140	12	.	.	PUNCT
gc-55	141	1	a	a	DET
gc-55	141	2	problem	problem	NOUN
gc-55	141	3	that	that	PRON
gc-55	141	4	appeared	appear	VERB
gc-55	141	5	in	in	ADP
gc-55	141	6	this	this	DET
gc-55	141	7	study	study	NOUN
gc-55	141	8	,	,	PUNCT
gc-55	141	9	which	which	PRON
gc-55	141	10	prohibited	prohibit	VERB
gc-55	141	11	cross	cross	NOUN
gc-55	141	12	-	-	NOUN
gc-55	141	13	prediction	prediction	NOUN
gc-55	141	14	of	of	ADP
gc-55	141	15	lithology	lithology	NOUN
gc-55	141	16	,	,	PUNCT
gc-55	141	17	was	be	AUX
gc-55	141	18	different	different	ADJ
gc-55	141	19	sp	sp	ADP
gc-55	141	20	log	log	NOUN
gc-55	141	21	values	value	NOUN
gc-55	141	22	for	for	ADP
gc-55	141	23	wells	wells	PROPN
gc-55	141	24	klo	klo	PROPN
gc-55	141	25	–	–	PUNCT
gc-55	141	26	a	a	PROPN
gc-55	141	27	and	and	CCONJ
gc-55	141	28	klo	klo	PROPN
gc-55	141	29	–	–	PUNCT
gc-55	141	30	b.	b.	PROPN
gc-55	141	31	the	the	DET
gc-55	141	32	rm	rm	PROPN
gc-55	141	33	for	for	ADP
gc-55	141	34	klo	klo	PROPN
gc-55	141	35	–	–	PUNCT
gc-55	141	36	a	a	PRON
gc-55	141	37	was	be	AUX
gc-55	141	38	72	72	NUM
gc-55	141	39	ωm	ωm	VERB
gc-55	141	40	for	for	ADP
gc-55	141	41	mud	mud	NOUN
gc-55	141	42	temperature	temperature	NOUN
gc-55	141	43	of	of	ADP
gc-55	141	44	13	13	NUM
gc-55	141	45	°	°	NOUN
gc-55	141	46	c	c	NOUN
gc-55	141	47	and	and	CCONJ
gc-55	141	48	625	625	NUM
gc-55	141	49	ωm	ωm	PUNCT
gc-55	141	50	for	for	ADP
gc-55	141	51	klo	klo	PROPN
gc-55	141	52	–	–	PUNCT
gc-55	141	53	b	b	PROPN
gc-55	141	54	with	with	ADP
gc-55	141	55	a	a	DET
gc-55	141	56	mud	mud	NOUN
gc-55	141	57	temperature	temperature	NOUN
gc-55	141	58	of	of	ADP
gc-55	141	59	1	1	NUM
gc-55	141	60	°	°	NOUN
gc-55	141	61	c	c	NOUN
gc-55	141	62	.	.	PUNCT
gc-55	142	1	this	this	DET
gc-55	142	2	problem	problem	NOUN
gc-55	142	3	led	lead	VERB
gc-55	142	4	to	to	ADP
gc-55	142	5	unsuccessful	unsuccessful	ADJ
gc-55	142	6	prediction	prediction	NOUN
gc-55	142	7	in	in	ADP
gc-55	142	8	the	the	DET
gc-55	142	9	shallower	shallower	NOUN
gc-55	142	10	part	part	NOUN
gc-55	142	11	of	of	ADP
gc-55	142	12	the	the	DET
gc-55	142	13	well	well	INTJ
gc-55	142	14	log	log	NOUN
gc-55	142	15	data	datum	NOUN
gc-55	142	16	interval	interval	NOUN
gc-55	142	17	,	,	PUNCT
gc-55	142	18	where	where	SCONJ
gc-55	142	19	electric	electric	ADJ
gc-55	142	20	properties	property	NOUN
gc-55	142	21	of	of	ADP
gc-55	142	22	mud	mud	NOUN
gc-55	142	23	on	on	ADP
gc-55	142	24	wells	wells	PROPN
gc-55	142	25	klo	klo	PROPN
gc-55	142	26	–	–	PUNCT
gc-55	142	27	a	a	PROPN
gc-55	142	28	and	and	CCONJ
gc-55	142	29	klo	klo	PROPN
gc-55	142	30	–	–	PUNCT
gc-55	142	31	b	b	PROPN
gc-55	142	32	were	be	AUX
gc-55	142	33	signifi	signifi	NOUN
gc-55	142	34	cantly	cantly	ADV
gc-55	142	35	different	different	ADJ
gc-55	142	36	,	,	PUNCT
gc-55	142	37	and	and	CCONJ
gc-55	142	38	to	to	ADP
gc-55	142	39	successful	successful	ADJ
gc-55	142	40	prediction	prediction	NOUN
gc-55	142	41	in	in	ADP
gc-55	142	42	the	the	DET
gc-55	142	43	deeper	deep	ADJ
gc-55	142	44	part	part	NOUN
gc-55	142	45	of	of	ADP
gc-55	142	46	the	the	DET
gc-55	142	47	well	well	INTJ
gc-55	142	48	log	log	NOUN
gc-55	142	49	data	datum	NOUN
gc-55	142	50	interval	interval	NOUN
gc-55	142	51	(	(	PUNCT
gc-55	142	52	>	>	X
gc-55	142	53	850	850	NUM
gc-55	142	54	m	m	NOUN
gc-55	142	55	of	of	ADP
gc-55	142	56	depth	depth	NOUN
gc-55	142	57	)	)	PUNCT
gc-55	142	58	,	,	PUNCT
gc-55	142	59	where	where	SCONJ
gc-55	142	60	values	value	NOUN
gc-55	142	61	were	be	AUX
gc-55	142	62	similar	similar	ADJ
gc-55	142	63	on	on	ADP
gc-55	142	64	both	both	DET
gc-55	142	65	corresponding	correspond	VERB
gc-55	142	66	well	well	INTJ
gc-55	142	67	log	log	NOUN
gc-55	142	68	data	datum	NOUN
gc-55	142	69	intervals	interval	NOUN
gc-55	142	70	.	.	PUNCT
gc-55	143	1	this	this	DET
gc-55	143	2	problem	problem	NOUN
gc-55	143	3	probably	probably	ADV
gc-55	143	4	occurred	occur	VERB
gc-55	143	5	because	because	SCONJ
gc-55	143	6	of	of	ADP
gc-55	143	7	the	the	DET
gc-55	143	8	different	different	ADJ
gc-55	143	9	electrical	electrical	ADJ
gc-55	143	10	properties	property	NOUN
gc-55	143	11	of	of	ADP
gc-55	143	12	mud	mud	NOUN
gc-55	143	13	,	,	PUNCT
gc-55	143	14	infl	infl	PROPN
gc-55	143	15	uenced	uence	VERB
gc-55	143	16	by	by	ADP
gc-55	143	17	different	different	ADJ
gc-55	143	18	temperature	temperature	NOUN
gc-55	143	19	values	value	NOUN
gc-55	143	20	and	and	CCONJ
gc-55	143	21	the	the	DET
gc-55	143	22	composition	composition	NOUN
gc-55	143	23	of	of	ADP
gc-55	143	24	the	the	DET
gc-55	143	25	mud	mud	NOUN
gc-55	143	26	itself	itself	PRON
gc-55	143	27	.	.	PUNCT
gc-55	144	1	in	in	ADP
gc-55	144	2	deeper	deep	ADJ
gc-55	144	3	segments	segment	NOUN
gc-55	144	4	of	of	ADP
gc-55	144	5	the	the	DET
gc-55	144	6	well	well	NOUN
gc-55	144	7	,	,	PUNCT
gc-55	144	8	temperature	temperature	NOUN
gc-55	144	9	and	and	CCONJ
gc-55	144	10	electrical	electrical	ADJ
gc-55	144	11	properties	property	NOUN
gc-55	144	12	of	of	ADP
gc-55	144	13	mud	mud	NOUN
gc-55	144	14	on	on	ADP
gc-55	144	15	both	both	DET
gc-55	144	16	wells	well	NOUN
gc-55	144	17	were	be	AUX
gc-55	144	18	normalized	normalize	VERB
gc-55	144	19	,	,	PUNCT
gc-55	144	20	and	and	CCONJ
gc-55	144	21	therefore	therefore	ADV
gc-55	144	22	cross	cross	NOUN
gc-55	144	23	-	-	NOUN
gc-55	144	24	prediction	prediction	NOUN
gc-55	144	25	on	on	ADP
gc-55	144	26	deeper	deep	ADJ
gc-55	144	27	intervals	interval	NOUN
gc-55	144	28	was	be	AUX
gc-55	144	29	possible	possible	ADJ
gc-55	144	30	.	.	PUNCT
gc-55	145	1	one	one	NUM
gc-55	145	2	solution	solution	NOUN
gc-55	145	3	to	to	ADP
gc-55	145	4	this	this	DET
gc-55	145	5	problem	problem	NOUN
gc-55	145	6	for	for	ADP
gc-55	145	7	shallower	shallow	ADJ
gc-55	145	8	intervals	interval	NOUN
gc-55	145	9	could	could	AUX
gc-55	145	10	be	be	AUX
gc-55	145	11	introducing	introduce	VERB
gc-55	145	12	lithology	lithology	NOUN
gc-55	145	13	descriptive	descriptive	ADJ
gc-55	145	14	variables	variable	NOUN
gc-55	145	15	that	that	PRON
gc-55	145	16	are	be	AUX
gc-55	145	17	not	not	PART
gc-55	145	18	as	as	ADV
gc-55	145	19	dependent	dependent	ADJ
gc-55	145	20	on	on	ADP
gc-55	145	21	mud	mud	NOUN
gc-55	145	22	properties	property	NOUN
gc-55	145	23	as	as	ADP
gc-55	145	24	the	the	DET
gc-55	145	25	sp	sp	NOUN
gc-55	145	26	log	log	NOUN
gc-55	145	27	.	.	PUNCT
gc-55	146	1	for	for	ADP
gc-55	146	2	example	example	NOUN
gc-55	146	3	,	,	PUNCT
gc-55	146	4	gamma	gamma	PROPN
gc-55	146	5	ray	ray	NOUN
gc-55	146	6	logs	log	VERB
gc-55	146	7	as	as	ADV
gc-55	146	8	well	well	ADV
gc-55	146	9	as	as	ADP
gc-55	146	10	other	other	ADJ
gc-55	146	11	well	well	NOUN
gc-55	146	12	logs	log	NOUN
gc-55	146	13	that	that	PRON
gc-55	146	14	defi	defi	PROPN
gc-55	146	15	ne	ne	PROPN
gc-55	146	16	reservoir	reservoir	PROPN
gc-55	146	17	properties	property	NOUN
gc-55	146	18	,	,	PUNCT
gc-55	146	19	such	such	ADJ
gc-55	146	20	as	as	ADP
gc-55	146	21	compensated	compensate	VERB
gc-55	146	22	neutron	neutron	NOUN
gc-55	146	23	and	and	CCONJ
gc-55	146	24	density	density	NOUN
gc-55	146	25	logs	log	NOUN
gc-55	146	26	,	,	PUNCT
gc-55	146	27	could	could	AUX
gc-55	146	28	be	be	AUX
gc-55	146	29	used	use	VERB
gc-55	146	30	to	to	PART
gc-55	146	31	obtain	obtain	VERB
gc-55	146	32	better	well	ADJ
gc-55	146	33	neural	neural	ADJ
gc-55	146	34	network	network	NOUN
gc-55	146	35	performance	performance	NOUN
gc-55	146	36	.	.	PUNCT
gc-55	147	1	6	6	X
gc-55	147	2	.	.	X
gc-55	147	3	conclusions	conclusion	NOUN
gc-55	147	4	in	in	ADP
gc-55	147	5	this	this	DET
gc-55	147	6	study	study	NOUN
gc-55	147	7	,	,	PUNCT
gc-55	147	8	we	we	PRON
gc-55	147	9	trained	train	VERB
gc-55	147	10	several	several	ADJ
gc-55	147	11	artifi	artifi	ADJ
gc-55	147	12	cial	cial	ADJ
gc-55	147	13	neural	neural	ADJ
gc-55	147	14	networks	network	NOUN
gc-55	147	15	with	with	ADP
gc-55	147	16	the	the	DET
gc-55	147	17	task	task	NOUN
gc-55	147	18	of	of	ADP
gc-55	147	19	predicting	predict	VERB
gc-55	147	20	the	the	DET
gc-55	147	21	lithology	lithology	NOUN
gc-55	147	22	of	of	ADP
gc-55	147	23	upper	upper	ADJ
gc-55	147	24	pannonian	pannonian	ADJ
gc-55	147	25	sediments	sediment	NOUN
gc-55	147	26	(	(	PUNCT
gc-55	147	27	ii	ii	PROPN
gc-55	147	28	sandstone	sandstone	NOUN
gc-55	147	29	series	series	PROPN
gc-55	147	30	)	)	PUNCT
gc-55	147	31	and	and	CCONJ
gc-55	147	32	lower	low	ADJ
gc-55	147	33	pontian	pontian	ADJ
gc-55	147	34	deposits	deposit	NOUN
gc-55	147	35	(	(	PUNCT
gc-55	147	36	i	i	NOUN
gc-55	147	37	sandstone	sandstone	NOUN
gc-55	147	38	series	series	PROPN
gc-55	147	39	)	)	PUNCT
gc-55	147	40	,	,	PUNCT
gc-55	147	41	as	as	ADV
gc-55	147	42	well	well	ADV
gc-55	147	43	as	as	ADP
gc-55	147	44	hydrocarbon	hydrocarbon	NOUN
gc-55	147	45	saturation	saturation	NOUN
gc-55	147	46	within	within	ADP
gc-55	147	47	these	these	DET
gc-55	147	48	beds	bed	NOUN
gc-55	147	49	.	.	PUNCT
gc-55	148	1	sandstone	sandstone	NOUN
gc-55	148	2	facies	facie	NOUN
gc-55	148	3	are	be	AUX
gc-55	148	4	adequate	adequate	ADJ
gc-55	148	5	media	medium	NOUN
gc-55	148	6	for	for	ADP
gc-55	148	7	statistical	statistical	ADJ
gc-55	148	8	and	and	CCONJ
gc-55	148	9	neural	neural	ADJ
gc-55	148	10	network	network	NOUN
gc-55	148	11	analysis	analysis	NOUN
gc-55	148	12	.	.	PUNCT
gc-55	149	1	our	our	PRON
gc-55	149	2	analysis	analysis	NOUN
gc-55	149	3	of	of	ADP
gc-55	149	4	sandstone	sandstone	NOUN
gc-55	149	5	reservoirs	reservoir	NOUN
gc-55	149	6	of	of	ADP
gc-55	149	7	the	the	DET
gc-55	149	8	kloštar	kloštar	NOUN
gc-55	149	9	fi	fi	PROPN
gc-55	149	10	eld	eld	NOUN
gc-55	149	11	by	by	ADP
gc-55	149	12	neural	neural	ADJ
gc-55	149	13	tools	tool	NOUN
gc-55	149	14	yielded	yield	VERB
gc-55	149	15	the	the	DET
gc-55	149	16	following	follow	VERB
gc-55	149	17	results	result	NOUN
gc-55	149	18	:	:	PUNCT
gc-55	149	19	when	when	SCONJ
gc-55	149	20	determining	determine	VERB
gc-55	149	21	the	the	DET
gc-55	149	22	lithological	lithological	ADJ
gc-55	149	23	component	component	NOUN
gc-55	149	24	in	in	ADP
gc-55	149	25	wells	wells	PROPN
gc-55	149	26	klo	klo	PROPN
gc-55	149	27	–	–	PUNCT
gc-55	149	28	a	a	PROPN
gc-55	149	29	and	and	CCONJ
gc-55	149	30	klo	klo	PROPN
gc-55	149	31	–	–	PUNCT
gc-55	149	32	b	b	PROPN
gc-55	149	33	with	with	ADP
gc-55	149	34	rbf	rbf	PROPN
gc-55	149	35	and	and	CCONJ
gc-55	149	36	mlp	mlp	PROPN
gc-55	149	37	neural	neural	ADJ
gc-55	149	38	networks	network	NOUN
gc-55	149	39	,	,	PUNCT
gc-55	149	40	we	we	PRON
gc-55	149	41	achieved	achieve	VERB
gc-55	149	42	excellent	excellent	ADJ
gc-55	149	43	correspondence	correspondence	NOUN
gc-55	149	44	between	between	ADP
gc-55	149	45	true	true	ADJ
gc-55	149	46	and	and	CCONJ
gc-55	149	47	predicted	predict	VERB
gc-55	149	48	values	value	NOUN
gc-55	149	49	.	.	PUNCT
gc-55	150	1	prediction	prediction	NOUN
gc-55	150	2	of	of	ADP
gc-55	150	3	hydrocarbon	hydrocarbon	NOUN
gc-55	150	4	saturation	saturation	NOUN
gc-55	150	5	in	in	ADP
gc-55	150	6	well	well	ADV
gc-55	150	7	klo	klo	PROPN
gc-55	150	8	–	–	PUNCT
gc-55	150	9	b	b	PROPN
gc-55	150	10	with	with	ADP
gc-55	150	11	a	a	DET
gc-55	150	12	neural	neural	ADJ
gc-55	150	13	network	network	NOUN
gc-55	150	14	trained	train	VERB
gc-55	150	15	in	in	ADP
gc-55	150	16	well	well	ADV
gc-55	150	17	klo	klo	PROPN
gc-55	150	18	–	–	PUNCT
gc-55	150	19	a	a	PRON
gc-55	150	20	gave	give	VERB
gc-55	150	21	excellent	excellent	ADJ
gc-55	150	22	correspondence	correspondence	NOUN
gc-55	150	23	between	between	ADP
gc-55	150	24	true	true	ADJ
gc-55	150	25	and	and	CCONJ
gc-55	150	26	predicted	predict	VERB
gc-55	150	27	values	value	NOUN
gc-55	150	28	.	.	PUNCT
gc-55	151	1	our	our	PRON
gc-55	151	2	results	result	NOUN
gc-55	151	3	show	show	VERB
gc-55	151	4	the	the	DET
gc-55	151	5	great	great	ADJ
gc-55	151	6	potential	potential	NOUN
gc-55	151	7	of	of	ADP
gc-55	151	8	neural	neural	ADJ
gc-55	151	9	networks	network	NOUN
gc-55	151	10	’	'	PUNCT
gc-55	151	11	application	application	NOUN
gc-55	151	12	in	in	ADP
gc-55	151	13	petroleum	petroleum	NOUN
gc-55	151	14	geology	geology	NOUN
gc-55	151	15	research	research	NOUN
gc-55	151	16	,	,	PUNCT
gc-55	151	17	where	where	SCONJ
gc-55	151	18	they	they	PRON
gc-55	151	19	could	could	AUX
gc-55	151	20	be	be	AUX
gc-55	151	21	used	use	VERB
gc-55	151	22	to	to	PART
gc-55	151	23	quickly	quickly	ADV
gc-55	151	24	acquire	acquire	VERB
gc-55	151	25	results	result	NOUN
gc-55	151	26	from	from	ADP
gc-55	151	27	well	well	ADV
gc-55	151	28	logs	log	NOUN
gc-55	151	29	,	,	PUNCT
gc-55	151	30	to	to	PART
gc-55	151	31	obtain	obtain	VERB
gc-55	151	32	vertical	vertical	ADJ
gc-55	151	33	and	and	CCONJ
gc-55	151	34	lateral	lateral	ADJ
gc-55	151	35	correlation	correlation	NOUN
gc-55	151	36	of	of	ADP
gc-55	151	37	such	such	ADJ
gc-55	151	38	logs	log	NOUN
gc-55	151	39	,	,	PUNCT
gc-55	151	40	and	and	CCONJ
gc-55	151	41	to	to	PART
gc-55	151	42	solve	solve	VERB
gc-55	151	43	other	other	ADJ
gc-55	151	44	petroleum	petroleum	NOUN
gc-55	151	45	geology	geology	NOUN
gc-55	151	46	problems	problem	NOUN
gc-55	151	47	.	.	PUNCT
gc-55	152	1	fi	fi	NOUN
gc-55	152	2	gu	gu	X
gc-55	152	3	re	re	ADP
gc-55	152	4	6	6	NUM
gc-55	152	5	:	:	PUNCT
gc-55	152	6	comparison	comparison	NOUN
gc-55	152	7	of	of	ADP
gc-55	152	8	mlp	mlp	PROPN
gc-55	152	9	neural	neural	PROPN
gc-55	152	10	network	network	NOUN
gc-55	152	11	predicted	predict	VERB
gc-55	152	12	(	(	PUNCT
gc-55	152	13	dotted	dotted	ADJ
gc-55	152	14	line	line	NOUN
gc-55	152	15	)	)	PUNCT
gc-55	152	16	and	and	CCONJ
gc-55	152	17	manually	manually	ADV
gc-55	152	18	determined	determine	VERB
gc-55	152	19	data	datum	NOUN
gc-55	152	20	(	(	PUNCT
gc-55	152	21	solid	solid	ADJ
gc-55	152	22	line	line	NOUN
gc-55	152	23	)	)	PUNCT
gc-55	152	24	in	in	ADP
gc-55	152	25	hydrocarbon	hydrocarbon	NOUN
gc-55	152	26	saturation	saturation	NOUN
gc-55	152	27	analysis	analysis	NOUN
gc-55	152	28	in	in	ADP
gc-55	152	29	wells	wells	PROPN
gc-55	152	30	klo	klo	PROPN
gc-55	152	31	–	–	PUNCT
gc-55	152	32	a	a	PROPN
gc-55	152	33	and	and	CCONJ
gc-55	152	34	klo	klo	PROPN
gc-55	152	35	–	–	PUNCT
gc-55	152	36	b.	b.	PROPN
gc-55	153	1	the	the	DET
gc-55	153	2	diagram	diagram	NOUN
gc-55	153	3	ordinate	ordinate	NOUN
gc-55	153	4	represents	represent	VERB
gc-55	153	5	hydrocarbon	hydrocarbon	NOUN
gc-55	153	6	saturation	saturation	NOUN
gc-55	153	7	(	(	PUNCT
gc-55	153	8	0	0	NUM
gc-55	153	9	or	or	CCONJ
gc-55	153	10	1	1	NUM
gc-55	153	11	)	)	PUNCT
gc-55	153	12	,	,	PUNCT
gc-55	153	13	whereas	whereas	SCONJ
gc-55	153	14	the	the	DET
gc-55	153	15	abscissa	abscissa	NOUN
gc-55	153	16	represents	represent	VERB
gc-55	153	17	the	the	DET
gc-55	153	18	corresponding	correspond	VERB
gc-55	153	19	data	datum	NOUN
gc-55	153	20	depth	depth	NOUN
gc-55	153	21	.	.	PUNCT
gc-55	154	1	geologia	geologia	PROPN
gc-55	154	2	croaticacvetković	croaticacvetković	NOUN
gc-55	154	3	et	et	PROPN
gc-55	154	4	al	al	PROPN
gc-55	154	5	.	.	PROPN
gc-55	154	6	:	:	PUNCT
gc-55	155	1	application	application	NOUN
gc-55	155	2	of	of	ADP
gc-55	155	3	neural	neural	ADJ
gc-55	155	4	networks	network	NOUN
gc-55	155	5	in	in	ADP
gc-55	155	6	petroleum	petroleum	NOUN
gc-55	155	7	reservoir	reservoir	NOUN
gc-55	155	8	lithology	lithology	NOUN
gc-55	155	9	and	and	CCONJ
gc-55	155	10	saturation	saturation	NOUN
gc-55	155	11	prediction	prediction	NOUN
gc-55	155	12	121	121	NUM
gc-55	155	13	references	reference	NOUN
gc-55	155	14	anderson	anderson	PROPN
gc-55	155	15	,	,	PUNCT
gc-55	155	16	j.a	j.a	PROPN
gc-55	155	17	.	.	PROPN
gc-55	155	18	&	&	CCONJ
gc-55	155	19	rosenfled	rosenfle	VERB
gc-55	155	20	,	,	PUNCT
gc-55	155	21	e.	e.	PROPN
gc-55	155	22	(	(	PUNCT
gc-55	155	23	1988	1988	NUM
gc-55	155	24	):	):	PUNCT
gc-55	155	25	neurocomputing	neurocomputing	NOUN
gc-55	155	26	:	:	PUNCT
gc-55	155	27	foundations	foundation	NOUN
gc-55	155	28	of	of	ADP
gc-55	155	29	research	research	NOUN
gc-55	155	30	.	.	PUNCT
gc-55	155	31	–	–	PUNCT
gc-55	155	32	mit	mit	NOUN
gc-55	155	33	press	press	NOUN
gc-55	155	34	,	,	PUNCT
gc-55	155	35	cambridge	cambridge	PROPN
gc-55	155	36	,	,	PUNCT
gc-55	155	37	729	729	NUM
gc-55	155	38	p.	p.	NOUN
gc-55	155	39	balić	balić	NOUN
gc-55	155	40	,	,	PUNCT
gc-55	155	41	d.	d.	PROPN
gc-55	155	42	,	,	PUNCT
gc-55	155	43	velić	velić	PROPN
gc-55	155	44	,	,	PUNCT
gc-55	155	45	j.	j.	PROPN
gc-55	155	46	&	&	CCONJ
gc-55	155	47	malvić	malvić	PROPN
gc-55	155	48	,	,	PUNCT
gc-55	155	49	t.	t.	PROPN
gc-55	155	50	(	(	PUNCT
gc-55	155	51	2008	2008	NUM
gc-55	155	52	):	):	PUNCT
gc-55	155	53	selection	selection	NOUN
gc-55	155	54	of	of	ADP
gc-55	155	55	the	the	DET
gc-55	155	56	most	most	ADV
gc-55	155	57	appropriate	appropriate	ADJ
gc-55	155	58	method	method	NOUN
gc-55	155	59	for	for	ADP
gc-55	155	60	sandstone	sandstone	NOUN
gc-55	155	61	reservoirs	reservoir	NOUN
gc-55	155	62	in	in	ADP
gc-55	155	63	the	the	DET
gc-55	155	64	kloštar	kloštar	NOUN
gc-55	155	65	oil	oil	NOUN
gc-55	155	66	and	and	CCONJ
gc-55	155	67	gas	gas	NOUN
gc-55	155	68	fi	fi	NOUN
gc-55	155	69	eld	eld	NOUN
gc-55	155	70	.	.	PUNCT
gc-55	155	71	–	–	PUNCT
gc-55	155	72	geol	geol	NOUN
gc-55	155	73	.	.	PUNCT
gc-55	156	1	croat	croat	PROPN
gc-55	156	2	.	.	PUNCT
gc-55	156	3	,	,	PUNCT
gc-55	156	4	61/1	61/1	NUM
gc-55	156	5	,	,	PUNCT
gc-55	156	6	27–35	27–35	NUM
gc-55	156	7	.	.	PUNCT
gc-55	157	1	bassiouni	bassiouni	PROPN
gc-55	157	2	,	,	PUNCT
gc-55	157	3	z.	z.	PROPN
gc-55	157	4	(	(	PUNCT
gc-55	157	5	1994	1994	NUM
gc-55	157	6	):	):	PUNCT
gc-55	157	7	theory	theory	NOUN
gc-55	157	8	,	,	PUNCT
gc-55	157	9	measurement	measurement	NOUN
gc-55	157	10	,	,	PUNCT
gc-55	157	11	and	and	CCONJ
gc-55	157	12	interpretation	interpretation	NOUN
gc-55	157	13	of	of	ADP
gc-55	157	14	well	well	ADJ
gc-55	157	15	logs	log	NOUN
gc-55	157	16	.	.	PUNCT
gc-55	157	17	–	–	PUNCT
gc-55	157	18	society	society	NOUN
gc-55	157	19	of	of	ADP
gc-55	157	20	petroleum	petroleum	NOUN
gc-55	157	21	engineers	engineer	NOUN
gc-55	157	22	,	,	PUNCT
gc-55	157	23	richardson	richardson	PROPN
gc-55	157	24	,	,	PUNCT
gc-55	157	25	372	372	NUM
gc-55	157	26	p.	p.	PROPN
gc-55	157	27	bhatt	bhatt	PROPN
gc-55	157	28	,	,	PUNCT
gc-55	157	29	a.	a.	PROPN
gc-55	157	30	(	(	PUNCT
gc-55	157	31	2002	2002	NUM
gc-55	157	32	):	):	PUNCT
gc-55	157	33	reservoir	reservoir	NOUN
gc-55	157	34	properties	property	NOUN
gc-55	157	35	from	from	ADP
gc-55	157	36	-	-	PUNCT
gc-55	157	37	well	well	NOUN
gc-55	157	38	logs	log	NOUN
gc-55	157	39	using	use	VERB
gc-55	157	40	neural	neural	ADJ
gc-55	157	41	networks	network	NOUN
gc-55	157	42	.	.	PUNCT
gc-55	157	43	–	–	PUNCT
gc-55	157	44	unpubl	unpubl	ADJ
gc-55	157	45	.	.	PUNCT
gc-55	158	1	phd	phd	NOUN
gc-55	158	2	thesis	thesis	PROPN
gc-55	158	3	,	,	PUNCT
gc-55	158	4	ntnu	ntnu	PROPN
gc-55	158	5	,	,	PUNCT
gc-55	158	6	trondheim	trondheim	PROPN
gc-55	158	7	,	,	PUNCT
gc-55	158	8	151	151	NUM
gc-55	158	9	p.	p.	NOUN
gc-55	158	10	bishop	bishop	PROPN
gc-55	158	11	,	,	PUNCT
gc-55	158	12	c.m	c.m	PROPN
gc-55	158	13	.	.	PROPN
gc-55	158	14	(	(	PUNCT
gc-55	158	15	1995	1995	NUM
gc-55	158	16	):	):	PUNCT
gc-55	158	17	neural	neural	ADJ
gc-55	158	18	networks	network	NOUN
gc-55	158	19	for	for	ADP
gc-55	158	20	pattern	pattern	NOUN
gc-55	158	21	recognition	recognition	NOUN
gc-55	158	22	,	,	PUNCT
gc-55	158	23	1st	1st	PROPN
gc-55	158	24	edition	edition	NOUN
gc-55	158	25	.	.	PUNCT
gc-55	158	26	–	–	PUNCT
gc-55	158	27	oxford	oxford	PROPN
gc-55	158	28	university	university	NOUN
gc-55	158	29	press	press	NOUN
gc-55	158	30	,	,	PUNCT
gc-55	158	31	new	new	PROPN
gc-55	158	32	york	york	PROPN
gc-55	158	33	,	,	PUNCT
gc-55	158	34	504	504	NUM
gc-55	158	35	p.	p.	NOUN
gc-55	158	36	fahlman	fahlman	NOUN
gc-55	158	37	,	,	PUNCT
gc-55	158	38	s.e	s.e	PROPN
gc-55	158	39	.	.	PROPN
gc-55	158	40	(	(	PUNCT
gc-55	158	41	1988	1988	NUM
gc-55	158	42	):	):	PUNCT
gc-55	158	43	faster	fast	ADV
gc-55	158	44	learning	learn	VERB
gc-55	158	45	variations	variation	NOUN
gc-55	158	46	on	on	ADP
gc-55	158	47	back	back	ADJ
gc-55	158	48	-	-	PUNCT
gc-55	158	49	propagation	propagation	NOUN
gc-55	158	50	:	:	PUNCT
gc-55	158	51	an	an	DET
gc-55	158	52	empirical	empirical	ADJ
gc-55	158	53	study	study	NOUN
gc-55	158	54	.	.	PUNCT
gc-55	158	55	–	–	PUNCT
gc-55	158	56	proceedings	proceeding	NOUN
gc-55	158	57	of	of	ADP
gc-55	158	58	the	the	DET
gc-55	158	59	1988	1988	NUM
gc-55	158	60	connectionist	connectionist	NOUN
gc-55	158	61	models	model	NOUN
gc-55	158	62	summer	summer	NOUN
gc-55	158	63	school	school	NOUN
gc-55	158	64	,	,	PUNCT
gc-55	158	65	los	los	PROPN
gc-55	158	66	altos	altos	PROPN
gc-55	158	67	,	,	PUNCT
gc-55	158	68	38–51	38–51	NUM
gc-55	158	69	.	.	PUNCT
gc-55	158	70	gorse	gorse	PROPN
gc-55	158	71	,	,	PUNCT
gc-55	158	72	d.	d.	PROPN
gc-55	158	73	,	,	PUNCT
gc-55	158	74	shepherd	shepherd	NOUN
gc-55	158	75	,	,	PUNCT
gc-55	158	76	a.	a.	PROPN
gc-55	158	77	&	&	CCONJ
gc-55	158	78	taylor	taylor	PROPN
gc-55	158	79	,	,	PUNCT
gc-55	158	80	j.g	j.g	PROPN
gc-55	158	81	.	.	PROPN
gc-55	158	82	(	(	PUNCT
gc-55	158	83	1997	1997	NUM
gc-55	158	84	):	):	PUNCT
gc-55	158	85	the	the	DET
gc-55	158	86	new	new	ADJ
gc-55	158	87	era	era	NOUN
gc-55	158	88	in	in	ADP
gc-55	158	89	supervised	supervised	ADJ
gc-55	158	90	learning	learning	NOUN
gc-55	158	91	.	.	PUNCT
gc-55	158	92	–	–	PUNCT
gc-55	158	93	neural	neural	ADJ
gc-55	158	94	networks	network	NOUN
gc-55	158	95	,	,	PUNCT
gc-55	158	96	10/2	10/2	NUM
gc-55	158	97	,	,	PUNCT
gc-55	158	98	343–352	343–352	NUM
gc-55	158	99	.	.	PUNCT
gc-55	159	1	jacobs	jacobs	PROPN
gc-55	159	2	,	,	PUNCT
gc-55	159	3	r.a	r.a	PROPN
gc-55	159	4	.	.	PROPN
gc-55	159	5	(	(	PUNCT
gc-55	159	6	1988	1988	NUM
gc-55	159	7	):	):	PUNCT
gc-55	159	8	increased	increase	VERB
gc-55	159	9	rates	rate	NOUN
gc-55	159	10	of	of	ADP
gc-55	159	11	convergence	convergence	NOUN
gc-55	159	12	through	through	ADP
gc-55	159	13	learning	learn	VERB
gc-55	159	14	rate	rate	NOUN
gc-55	159	15	adaptation	adaptation	NOUN
gc-55	159	16	.	.	PUNCT
gc-55	159	17	–	–	PUNCT
gc-55	159	18	neural	neural	ADJ
gc-55	159	19	networks	network	NOUN
gc-55	159	20	,	,	PUNCT
gc-55	159	21	1	1	NUM
gc-55	159	22	,	,	PUNCT
gc-55	159	23	295–307	295–307	NUM
gc-55	159	24	.	.	PUNCT
gc-55	160	1	levenberg	levenberg	PROPN
gc-55	160	2	,	,	PUNCT
gc-55	160	3	k.	k.	PROPN
gc-55	160	4	(	(	PUNCT
gc-55	160	5	1944	1944	NUM
gc-55	160	6	):	):	PUNCT
gc-55	160	7	a	a	DET
gc-55	160	8	method	method	NOUN
gc-55	160	9	for	for	ADP
gc-55	160	10	the	the	DET
gc-55	160	11	solution	solution	NOUN
gc-55	160	12	of	of	ADP
gc-55	160	13	certain	certain	ADJ
gc-55	160	14	problems	problem	NOUN
gc-55	160	15	in	in	ADP
gc-55	160	16	least	least	ADJ
gc-55	160	17	squares	square	NOUN
gc-55	160	18	.	.	PUNCT
gc-55	160	19	–	–	PUNCT
gc-55	160	20	quardt	quardt	PROPN
gc-55	160	21	.	.	PUNCT
gc-55	161	1	appl	appl	PROPN
gc-55	161	2	.	.	PROPN
gc-55	161	3	math	math	PROPN
gc-55	161	4	.	.	PUNCT
gc-55	161	5	,	,	PUNCT
gc-55	162	1	2	2	NUM
gc-55	162	2	,	,	PUNCT
gc-55	162	3	164–168	164–168	NUM
gc-55	162	4	.	.	PUNCT
gc-55	163	1	lučić	lučić	PROPN
gc-55	163	2	,	,	PUNCT
gc-55	163	3	d.	d.	PROPN
gc-55	163	4	,	,	PUNCT
gc-55	163	5	saftić	saftić	PROPN
gc-55	163	6	,	,	PUNCT
gc-55	163	7	b.	b.	PROPN
gc-55	163	8	,	,	PUNCT
gc-55	163	9	krizmanić	krizmanić	PROPN
gc-55	163	10	,	,	PUNCT
gc-55	163	11	k.	k.	PROPN
gc-55	163	12	,	,	PUNCT
gc-55	163	13	prelogović	prelogović	PROPN
gc-55	163	14	,	,	PUNCT
gc-55	163	15	e.	e.	PROPN
gc-55	163	16	,	,	PUNCT
gc-55	163	17	britvić	britvić	PROPN
gc-55	163	18	,	,	PUNCT
gc-55	163	19	v.	v.	ADV
gc-55	163	20	,	,	PUNCT
gc-55	163	21	mesić	mesić	PROPN
gc-55	163	22	,	,	PUNCT
gc-55	163	23	i.	i.	PROPN
gc-55	163	24	&	&	CCONJ
gc-55	163	25	tadej	tadej	PROPN
gc-55	163	26	,	,	PUNCT
gc-55	163	27	j.	j.	PROPN
gc-55	163	28	(	(	PUNCT
gc-55	163	29	2001	2001	NUM
gc-55	163	30	):	):	PUNCT
gc-55	163	31	the	the	DET
gc-55	163	32	neogene	neogene	ADJ
gc-55	163	33	evolution	evolution	NOUN
gc-55	163	34	and	and	CCONJ
gc-55	163	35	hydrocarbon	hydrocarbon	NOUN
gc-55	163	36	potential	potential	NOUN
gc-55	163	37	of	of	ADP
gc-55	163	38	the	the	DET
gc-55	163	39	pannonian	pannonian	ADJ
gc-55	163	40	basin	basin	NOUN
gc-55	163	41	in	in	ADP
gc-55	163	42	croatia	croatia	PROPN
gc-55	163	43	.	.	PUNCT
gc-55	163	44	–	–	PUNCT
gc-55	163	45	mar	mar	PROPN
gc-55	163	46	.	.	PROPN
gc-55	163	47	petrol	petrol	PROPN
gc-55	163	48	.	.	PUNCT
gc-55	164	1	geol	geol	PROPN
gc-55	164	2	.	.	PUNCT
gc-55	165	1	18/1	18/1	NUM
gc-55	165	2	,	,	PUNCT
gc-55	165	3	133–147	133–147	NUM
gc-55	165	4	.	.	PUNCT
gc-55	166	1	luthi	luthi	PROPN
gc-55	166	2	,	,	PUNCT
gc-55	166	3	s.m	s.m	PROPN
gc-55	166	4	.	.	PROPN
gc-55	166	5	&	&	CCONJ
gc-55	166	6	bryant	bryant	PROPN
gc-55	166	7	,	,	PUNCT
gc-55	166	8	i.d	i.d	PROPN
gc-55	166	9	.	.	PROPN
gc-55	166	10	(	(	PUNCT
gc-55	166	11	1997	1997	NUM
gc-55	166	12	):	):	PUNCT
gc-55	166	13	well	well	ADV
gc-55	166	14	-	-	PUNCT
gc-55	166	15	log	log	NOUN
gc-55	166	16	correlation	correlation	NOUN
gc-55	166	17	using	use	VERB
gc-55	166	18	a	a	DET
gc-55	166	19	back	back	ADJ
gc-55	166	20	-	-	PUNCT
gc-55	166	21	propagation	propagation	NOUN
gc-55	166	22	neural	neural	ADJ
gc-55	166	23	network	network	NOUN
gc-55	166	24	.	.	PUNCT
gc-55	167	1	–	–	PUNCT
gc-55	167	2	math	math	NOUN
gc-55	167	3	.	.	PUNCT
gc-55	168	1	geol	geol	PROPN
gc-55	168	2	.	.	PUNCT
gc-55	169	1	29/3	29/3	NUM
gc-55	169	2	,	,	PUNCT
gc-55	169	3	413–425	413–425	NUM
gc-55	169	4	.	.	PUNCT
gc-55	169	5	malvić	malvić	NOUN
gc-55	169	6	,	,	PUNCT
gc-55	169	7	t.	t.	PROPN
gc-55	169	8	(	(	PUNCT
gc-55	169	9	2006	2006	NUM
gc-55	169	10	):	):	PUNCT
gc-55	169	11	clastic	clastic	ADJ
gc-55	169	12	facies	facie	NOUN
gc-55	169	13	prediction	prediction	NOUN
gc-55	169	14	using	use	VERB
gc-55	169	15	neural	neural	ADJ
gc-55	169	16	network	network	NOUN
gc-55	169	17	(	(	PUNCT
gc-55	169	18	case	case	NOUN
gc-55	169	19	study	study	NOUN
gc-55	169	20	from	from	ADP
gc-55	169	21	okoli	okoli	PROPN
gc-55	169	22	fi	fi	PROPN
gc-55	169	23	eld	eld	NOUN
gc-55	169	24	)	)	PUNCT
gc-55	169	25	.	.	PUNCT
gc-55	170	1	–	–	PUNCT
gc-55	170	2	nafta	nafta	PROPN
gc-55	170	3	,	,	PUNCT
gc-55	170	4	57/10	57/10	NUM
gc-55	170	5	,	,	PUNCT
gc-55	170	6	415–431	415–431	NUM
gc-55	170	7	.	.	PUNCT
gc-55	171	1	malvić	malvić	NOUN
gc-55	171	2	,	,	PUNCT
gc-55	171	3	t.	t.	PROPN
gc-55	171	4	&	&	CCONJ
gc-55	171	5	prskalo	prskalo	PROPN
gc-55	171	6	,	,	PUNCT
gc-55	171	7	s.	s.	PROPN
gc-55	171	8	(	(	PUNCT
gc-55	171	9	2007	2007	NUM
gc-55	171	10	):	):	PUNCT
gc-55	171	11	some	some	DET
gc-55	171	12	benefi	benefi	NOUN
gc-55	171	13	ts	ts	ADP
gc-55	171	14	of	of	ADP
gc-55	171	15	the	the	DET
gc-55	171	16	neural	neural	ADJ
gc-55	171	17	appro	appro	ADJ
gc-55	171	18	ach	ach	PROPN
gc-55	171	19	in	in	ADP
gc-55	171	20	porosity	porosity	NOUN
gc-55	171	21	prediction	prediction	NOUN
gc-55	171	22	(	(	PUNCT
gc-55	171	23	case	case	NOUN
gc-55	171	24	study	study	NOUN
gc-55	171	25	from	from	ADP
gc-55	171	26	beničanci	beničanci	PROPN
gc-55	171	27	fi	fi	PROPN
gc-55	171	28	eld	eld	PROPN
gc-55	171	29	)	)	PUNCT
gc-55	171	30	.	.	PUNCT
gc-55	172	1	–	–	PUNCT
gc-55	172	2	nafta	nafta	PROPN
gc-55	172	3	58/9	58/9	NUM
gc-55	172	4	,	,	PUNCT
gc-55	172	5	455–467	455–467	NUM
gc-55	172	6	.	.	PUNCT
gc-55	173	1	malvić	malvić	NOUN
gc-55	173	2	,	,	PUNCT
gc-55	173	3	t.	t.	NOUN
gc-55	173	4	,	,	PUNCT
gc-55	173	5	cvetković	cvetković	NOUN
gc-55	173	6	,	,	PUNCT
gc-55	173	7	m.	m.	NOUN
gc-55	173	8	&	&	CCONJ
gc-55	173	9	balić	balić	PROPN
gc-55	173	10	,	,	PUNCT
gc-55	173	11	d.	d.	PROPN
gc-55	173	12	(	(	PUNCT
gc-55	173	13	2008	2008	NUM
gc-55	173	14	):	):	PUNCT
gc-55	173	15	geomatematički	geomatematički	NOUN
gc-55	173	16	rječnik	rječnik	VERB
gc-55	173	17	[	[	PUNCT
gc-55	173	18	geomathematical	geomathematical	ADJ
gc-55	173	19	dictionary	dictionary	NOUN
gc-55	173	20	]	]	X
gc-55	173	21	.	.	PUNCT
gc-55	174	1	–	–	PUNCT
gc-55	174	2	hrvatsko	hrvatsko	ADV
gc-55	174	3	geološko	geološko	NOUN
gc-55	174	4	društvo	društvo	PROPN
gc-55	174	5	(	(	PUNCT
gc-55	174	6	hgd	hgd	PROPN
gc-55	174	7	)	)	PUNCT
gc-55	174	8	,	,	PUNCT
gc-55	174	9	zagreb	zagreb	PROPN
gc-55	174	10	,	,	PUNCT
gc-55	174	11	74	74	NUM
gc-55	174	12	p.	p.	PROPN
gc-55	174	13	marquardt	marquardt	PROPN
gc-55	174	14	,	,	PUNCT
gc-55	174	15	d.w	d.w	PROPN
gc-55	174	16	.	.	PUNCT
gc-55	175	1	(	(	PUNCT
gc-55	175	2	1963	1963	NUM
gc-55	175	3	):	):	PUNCT
gc-55	175	4	an	an	DET
gc-55	175	5	algorithm	algorithm	NOUN
gc-55	175	6	for	for	ADP
gc-55	175	7	least	least	ADJ
gc-55	175	8	-	-	PUNCT
gc-55	175	9	squares	square	NOUN
gc-55	175	10	estimation	estimation	NOUN
gc-55	175	11	of	of	ADP
gc-55	175	12	nonlinear	nonlinear	ADJ
gc-55	175	13	parameters	parameter	NOUN
gc-55	175	14	.	.	PUNCT
gc-55	175	15	–	–	PUNCT
gc-55	175	16	j.	j.	PROPN
gc-55	175	17	soc	soc	PROPN
gc-55	175	18	.	.	PUNCT
gc-55	176	1	indust	indust	PROPN
gc-55	176	2	.	.	PUNCT
gc-55	176	3	appl	appl	PROPN
gc-55	176	4	.	.	PROPN
gc-55	176	5	math	math	PROPN
gc-55	176	6	.	.	PUNCT
gc-55	177	1	11/2	11/2	PROPN
gc-55	177	2	,	,	PUNCT
gc-55	177	3	431–441	431–441	NUM
gc-55	177	4	.	.	PUNCT
gc-55	178	1	mcculloch	mcculloch	PROPN
gc-55	178	2	,	,	PUNCT
gc-55	178	3	w.s	w.s	PROPN
gc-55	178	4	.	.	PROPN
gc-55	178	5	&	&	CCONJ
gc-55	178	6	pitts	pitts	PROPN
gc-55	178	7	,	,	PUNCT
gc-55	178	8	w.	w.	NOUN
gc-55	178	9	(	(	PUNCT
gc-55	178	10	1943	1943	NUM
gc-55	178	11	)	)	PUNCT
gc-55	178	12	a	a	DET
gc-55	178	13	logical	logical	ADJ
gc-55	178	14	calculus	calculus	NOUN
gc-55	178	15	of	of	ADP
gc-55	178	16	ideas	idea	NOUN
gc-55	178	17	immanent	immanent	ADJ
gc-55	178	18	in	in	ADP
gc-55	178	19	nervous	nervous	ADJ
gc-55	178	20	activity	activity	NOUN
gc-55	178	21	.	.	PUNCT
gc-55	178	22	–	–	PUNCT
gc-55	178	23	b.	b.	PROPN
gc-55	178	24	math	math	NOUN
gc-55	178	25	.	.	PUNCT
gc-55	179	1	biol	biol	PROPN
gc-55	179	2	.	.	PUNCT
gc-55	180	1	5/4	5/4	NUM
gc-55	180	2	,	,	PUNCT
gc-55	180	3	115–133	115–133	NUM
gc-55	180	4	.	.	PUNCT
gc-55	181	1	rosenblatt	rosenblatt	PROPN
gc-55	181	2	,	,	PUNCT
gc-55	181	3	f.	f.	PROPN
gc-55	181	4	(	(	PUNCT
gc-55	181	5	1958	1958	NUM
gc-55	181	6	):	):	PUNCT
gc-55	181	7	the	the	DET
gc-55	181	8	perceptron	perceptron	NOUN
gc-55	181	9	:	:	PUNCT
gc-55	181	10	a	a	DET
gc-55	181	11	probabilistic	probabilistic	ADJ
gc-55	181	12	model	model	NOUN
gc-55	181	13	for	for	ADP
gc-55	181	14	information	information	NOUN
gc-55	181	15	storage	storage	NOUN
gc-55	181	16	and	and	CCONJ
gc-55	181	17	organization	organization	NOUN
gc-55	181	18	in	in	ADP
gc-55	181	19	the	the	DET
gc-55	181	20	brain	brain	NOUN
gc-55	181	21	.	.	PUNCT
gc-55	181	22	–	–	PUNCT
gc-55	181	23	psychol	psychol	NOUN
gc-55	181	24	.	.	PUNCT
gc-55	181	25	rev	rev	PROPN
gc-55	181	26	.	.	PUNCT
gc-55	182	1	65/6	65/6	NOUN
gc-55	182	2	,	,	PUNCT
gc-55	182	3	386–408	386–408	NUM
gc-55	182	4	.	.	PUNCT
gc-55	183	1	rumelhart	rumelhart	PROPN
gc-55	183	2	,	,	PUNCT
gc-55	183	3	d.e	d.e	PROPN
gc-55	183	4	.	.	PROPN
gc-55	183	5	,	,	PUNCT
gc-55	183	6	hinton	hinton	PROPN
gc-55	183	7	,	,	PUNCT
gc-55	183	8	g.e	g.e	PROPN
gc-55	183	9	.	.	PROPN
gc-55	183	10	&	&	CCONJ
gc-55	183	11	williams	williams	PROPN
gc-55	183	12	,	,	PUNCT
gc-55	183	13	r.j	r.j	PROPN
gc-55	183	14	.	.	PROPN
gc-55	183	15	(	(	PUNCT
gc-55	183	16	1986	1986	NUM
gc-55	183	17	):	):	PUNCT
gc-55	183	18	learning	learn	VERB
gc-55	183	19	internal	internal	ADJ
gc-55	183	20	representations	representation	NOUN
gc-55	183	21	by	by	ADP
gc-55	183	22	error	error	NOUN
gc-55	183	23	propagation	propagation	NOUN
gc-55	183	24	.	.	PUNCT
gc-55	183	25	–	–	PUNCT
gc-55	183	26	in	in	ADP
gc-55	183	27	:	:	PUNCT
gc-55	183	28	rumelhart	rumelhart	PROPN
gc-55	183	29	,	,	PUNCT
gc-55	183	30	d.e	d.e	PROPN
gc-55	183	31	.	.	PROPN
gc-55	183	32	&	&	CCONJ
gc-55	183	33	mcclelland	mcclelland	PROPN
gc-55	183	34	,	,	PUNCT
gc-55	183	35	j.l	j.l	PROPN
gc-55	183	36	.	.	PROPN
gc-55	183	37	(	(	PUNCT
gc-55	183	38	eds	ed	NOUN
gc-55	183	39	.	.	PROPN
gc-55	183	40	):	):	PUNCT
gc-55	183	41	parallel	parallel	ADJ
gc-55	183	42	distributed	distribute	VERB
gc-55	183	43	processing	processing	NOUN
gc-55	183	44	,	,	PUNCT
gc-55	183	45	mit	mit	NOUN
gc-55	183	46	press	press	NOUN
gc-55	183	47	,	,	PUNCT
gc-55	183	48	cambridge	cambridge	PROPN
gc-55	183	49	,	,	PUNCT
gc-55	183	50	1	1	NUM
gc-55	183	51	,	,	PUNCT
gc-55	183	52	381–362	381–362	NUM
gc-55	183	53	.	.	PUNCT
gc-55	184	1	velić	velić	PROPN
gc-55	184	2	,	,	PUNCT
gc-55	184	3	j.	j.	PROPN
gc-55	184	4	(	(	PUNCT
gc-55	184	5	1979	1979	NUM
gc-55	184	6	):	):	PUNCT
gc-55	184	7	o	o	PROPN
gc-55	184	8	razlikovanju	razlikovanju	NOUN
gc-55	184	9	neotektonskih	neotektonskih	NOUN
gc-55	184	10	,	,	PUNCT
gc-55	184	11	struktura	struktura	VERB
gc-55	184	12	u	u	NOUN
gc-55	184	13	zapadnom	zapadnom	PROPN
gc-55	184	14	dijelu	dijelu	PROPN
gc-55	184	15	savske	savske	ADJ
gc-55	184	16	depresije	depresije	NOUN
gc-55	185	1	[	[	X
gc-55	185	2	distinguishing	distinguish	VERB
gc-55	185	3	the	the	DET
gc-55	185	4	neotectonic	neotectonic	ADJ
gc-55	185	5	structures	structure	NOUN
gc-55	185	6	in	in	ADP
gc-55	185	7	western	western	ADJ
gc-55	185	8	part	part	NOUN
gc-55	185	9	of	of	ADP
gc-55	185	10	sava	sava	PROPN
gc-55	185	11	depression	depression	NOUN
gc-55	185	12	–	–	PUNCT
gc-55	185	13	in	in	ADP
gc-55	185	14	croatian	croatian	PROPN
gc-55	185	15	]	]	PUNCT
gc-55	185	16	.	.	PUNCT
gc-55	185	17	–	–	PUNCT
gc-55	185	18	geol	geol	NOUN
gc-55	185	19	.	.	PUNCT
gc-55	186	1	vjesnik	vjesnik	PROPN
gc-55	186	2	,	,	PUNCT
gc-55	186	3	31	31	NUM
gc-55	186	4	,	,	PUNCT
gc-55	186	5	175–183	175–183	NUM
gc-55	186	6	.	.	PUNCT
gc-55	187	1	velić	velić	PROPN
gc-55	187	2	,	,	PUNCT
gc-55	187	3	j.	j.	PROPN
gc-55	187	4	(	(	PUNCT
gc-55	187	5	1980	1980	NUM
gc-55	187	6	):	):	PUNCT
gc-55	187	7	geološka	geološka	PROPN
gc-55	187	8	građa	građa	PROPN
gc-55	187	9	zapadnog	zapadnog	PROPN
gc-55	187	10	dijela	dijela	PROPN
gc-55	187	11	savske	savske	ADJ
gc-55	187	12	depresije	depresije	NOUN
gc-55	188	1	[	[	X
gc-55	188	2	geological	geological	ADJ
gc-55	188	3	settings	setting	NOUN
gc-55	188	4	of	of	ADP
gc-55	188	5	the	the	DET
gc-55	188	6	western	western	ADJ
gc-55	188	7	part	part	NOUN
gc-55	188	8	of	of	ADP
gc-55	188	9	sava	sava	PROPN
gc-55	188	10	depression	depression	NOUN
gc-55	188	11	–	–	PUNCT
gc-55	188	12	in	in	ADP
gc-55	188	13	croatian	croatian	PROPN
gc-55	188	14	]	]	PUNCT
gc-55	188	15	.	.	PUNCT
gc-55	188	16	–	–	PUNCT
gc-55	188	17	unpubl	unpubl	ADJ
gc-55	188	18	.	.	PUNCT
gc-55	189	1	phd	phd	NOUN
gc-55	189	2	thesis	thesis	NOUN
gc-55	189	3	,	,	PUNCT
gc-55	189	4	faculty	faculty	NOUN
gc-55	189	5	of	of	ADP
gc-55	189	6	mining	mining	NOUN
gc-55	189	7	,	,	PUNCT
gc-55	189	8	geology	geology	NOUN
gc-55	189	9	and	and	CCONJ
gc-55	189	10	petroleum	petroleum	NOUN
gc-55	189	11	engineering	engineering	NOUN
gc-55	189	12	,	,	PUNCT
gc-55	189	13	zagreb	zagreb	PROPN
gc-55	189	14	,	,	PUNCT
gc-55	189	15	139	139	NUM
gc-55	189	16	p.	p.	NOUN
gc-55	189	17	velić	velić	NOUN
gc-55	189	18	,	,	PUNCT
gc-55	189	19	j.	j.	PROPN
gc-55	189	20	(	(	PUNCT
gc-55	189	21	1983	1983	NUM
gc-55	189	22	):	):	PUNCT
gc-55	189	23	neotektonski	neotektonski	ADJ
gc-55	189	24	odnosi	odnosi	NOUN
gc-55	189	25	i	i	PRON
gc-55	189	26	razvitak	razvitak	VERB
gc-55	189	27	zapadnog	zapadnog	PROPN
gc-55	189	28	dijela	dijela	PROPN
gc-55	189	29	savske	savske	PROPN
gc-55	189	30	potoline	potoline	PROPN
gc-55	190	1	[	[	X
gc-55	190	2	neotectonic	neotectonic	ADJ
gc-55	190	3	relations	relation	NOUN
gc-55	190	4	and	and	CCONJ
gc-55	190	5	development	development	NOUN
gc-55	190	6	of	of	ADP
gc-55	190	7	the	the	DET
gc-55	190	8	western	western	ADJ
gc-55	190	9	part	part	NOUN
gc-55	190	10	of	of	ADP
gc-55	190	11	sava	sava	PROPN
gc-55	190	12	depression	depression	NOUN
gc-55	190	13	–	–	PUNCT
gc-55	190	14	in	in	ADP
gc-55	190	15	croatian	croatian	PROPN
gc-55	190	16	]	]	PUNCT
gc-55	190	17	.	.	PUNCT
gc-55	190	18	–	–	PUNCT
gc-55	190	19	acta	acta	PROPN
gc-55	190	20	geol	geol	PROPN
gc-55	190	21	.	.	PUNCT
gc-55	191	1	13/2	13/2	NUM
gc-55	191	2	,	,	PUNCT
gc-55	191	3	26–65	26–65	NUM
gc-55	191	4	.	.	PUNCT
gc-55	192	1	vragović	vragović	PROPN
gc-55	192	2	,	,	PUNCT
gc-55	192	3	m.	m.	NOUN
gc-55	192	4	&	&	CCONJ
gc-55	192	5	majer	majer	PROPN
gc-55	192	6	,	,	PUNCT
gc-55	192	7	v.	v.	PROPN
gc-55	192	8	(	(	PUNCT
gc-55	192	9	1980	1980	NUM
gc-55	192	10	):	):	PUNCT
gc-55	192	11	prilozi	prilozi	PROPN
gc-55	192	12	za	za	PROPN
gc-55	192	13	poznavanje	poznavanje	PROPN
gc-55	192	14	metamorfnih	metamorfnih	PROPN
gc-55	192	15	stijena	stijena	PROPN
gc-55	192	16	zagrebačke	zagrebačke	PROPN
gc-55	192	17	gore	gore	PROPN
gc-55	192	18	,	,	PUNCT
gc-55	192	19	moslavačke	moslavačke	VERB
gc-55	192	20	gore	gore	PROPN
gc-55	192	21	i	i	PRON
gc-55	192	22	papuka	papuka	VERB
gc-55	192	23	(	(	PUNCT
gc-55	192	24	hrvatska	hrvatska	PROPN
gc-55	192	25	)	)	PUNCT
gc-55	193	1	[	[	X
gc-55	193	2	samples	sample	NOUN
gc-55	193	3	for	for	ADP
gc-55	193	4	recognition	recognition	NOUN
gc-55	193	5	of	of	ADP
gc-55	193	6	metamorphic	metamorphic	ADJ
gc-55	193	7	rocks	rock	NOUN
gc-55	193	8	of	of	ADP
gc-55	193	9	zagrebačka	zagrebačka	PROPN
gc-55	193	10	gora	gora	PROPN
gc-55	193	11	,	,	PUNCT
gc-55	193	12	moslavačka	moslavačka	PROPN
gc-55	193	13	gora	gora	PROPN
gc-55	193	14	and	and	CCONJ
gc-55	193	15	papuk	papuk	PROPN
gc-55	193	16	mountain	mountain	PROPN
gc-55	193	17	(	(	PUNCT
gc-55	193	18	croatia	croatia	PROPN
gc-55	193	19	)	)	PUNCT
gc-55	193	20	–	–	PUNCT
gc-55	193	21	in	in	ADP
gc-55	193	22	croatian	croatian	PROPN
gc-55	193	23	]	]	PUNCT
gc-55	193	24	.	.	PUNCT
gc-55	193	25	–	–	PUNCT
gc-55	193	26	geol	geol	NOUN
gc-55	193	27	.	.	PUNCT
gc-55	194	1	vjesnik	vjesnik	PROPN
gc-55	194	2	,	,	PUNCT
gc-55	194	3	31	31	NUM
gc-55	194	4	,	,	PUNCT
gc-55	194	5	295–308	295–308	NUM
gc-55	194	6	.	.	PUNCT
gc-55	195	1	manuscript	manuscript	NOUN
gc-55	195	2	received	receive	VERB
gc-55	195	3	december	december	PROPN
gc-55	195	4	16	16	NUM
gc-55	195	5	,	,	PUNCT
gc-55	195	6	2008	2008	NUM
gc-55	195	7	revised	revise	VERB
gc-55	195	8	manuscript	manuscript	NOUN
gc-55	195	9	accepted	accept	VERB
gc-55	195	10	may	may	PROPN
gc-55	195	11	15	15	NUM
gc-55	195	12	,	,	PUNCT
gc-55	195	13	2009	2009	NUM
gc-55	195	14	available	available	ADJ
gc-55	196	1	online	online	PROPN
gc-55	196	2	june	june	PROPN
gc-55	196	3	19	19	NUM
gc-55	196	4	,	,	PUNCT
gc-55	196	5	2009	2009	NUM