id	sid	tid	token	lemma	pos
fens-978	1	1	doi	doi	PROPN
fens-978	1	2	:	:	PUNCT
fens-978	1	3	https://doi.org/10.4316/fens.2023.017	https://doi.org/10.4316/fens.2023.017	PROPN
fens-978	1	4	188	188	NUM
fens-978	1	5	journal	journal	NOUN
fens-978	1	6	homepage	homepage	NOUN
fens-978	1	7	:	:	PUNCT
fens-978	1	8	www.fia.usv.ro/fiajournal	www.fia.usv.ro/fiajournal	ADJ
fens-978	1	9	journal	journal	NOUN
fens-978	1	10	of	of	ADP
fens-978	1	11	faculty	faculty	NOUN
fens-978	1	12	of	of	ADP
fens-978	1	13	food	food	NOUN
fens-978	1	14	engineering	engineering	NOUN
fens-978	1	15	,	,	PUNCT
fens-978	1	16	ştefan	ştefan	PROPN
fens-978	1	17	cel	cel	PROPN
fens-978	1	18	mare	mare	PROPN
fens-978	1	19	university	university	PROPN
fens-978	1	20	of	of	ADP
fens-978	1	21	suceava	suceava	PROPN
fens-978	1	22	,	,	PUNCT
fens-978	1	23	romania	romania	PROPN
fens-978	1	24	volume	volume	NOUN
fens-978	1	25	xxii	xxii	PROPN
fens-978	1	26	,	,	PUNCT
fens-978	1	27	issue	issue	NOUN
fens-978	1	28	2	2	NUM
fens-978	1	29	2023	2023	NUM
fens-978	1	30	,	,	PUNCT
fens-978	1	31	pag	pag	PROPN
fens-978	1	32	.	.	PROPN
fens-978	1	33	188	188	NUM
fens-978	1	34	198	198	NUM
fens-978	1	35	soft	soft	ADJ
fens-978	1	36	computing	computing	NOUN
fens-978	1	37	application	application	NOUN
fens-978	1	38	to	to	PART
fens-978	1	39	predict	predict	VERB
fens-978	1	40	irrigation	irrigation	NOUN
fens-978	1	41	water	water	NOUN
fens-978	1	42	quality	quality	PROPN
fens-978	1	43	index	index	NOUN
fens-978	1	44	,	,	PUNCT
fens-978	1	45	case	case	NOUN
fens-978	1	46	study	study	NOUN
fens-978	1	47	of	of	ADP
fens-978	1	48	oued	oued	PROPN
fens-978	1	49	hammam	hammam	PROPN
fens-978	1	50	north	north	PROPN
fens-978	1	51	-	-	PUNCT
fens-978	1	52	east	east	NOUN
fens-978	1	53	algeria	algeria	PROPN
fens-978	1	54	*	*	PROPN
fens-978	1	55	oswald	oswald	PROPN
fens-978	1	56	peter	peter	PROPN
fens-978	1	57	bomani1	bomani1	PROPN
fens-978	1	58	1	1	NUM
fens-978	1	59	faculty	faculty	NOUN
fens-978	1	60	of	of	ADP
fens-978	1	61	earth	earth	NOUN
fens-978	1	62	science	science	NOUN
fens-978	1	63	and	and	CCONJ
fens-978	1	64	universal	universal	ADJ
fens-978	1	65	,	,	PUNCT
fens-978	1	66	geology	geology	NOUN
fens-978	1	67	department	department	NOUN
fens-978	1	68	,	,	PUNCT
fens-978	1	69	badji	badji	PROPN
fens-978	1	70	mokhtar	mokhtar	PROPN
fens-978	1	71	university	university	PROPN
fens-978	1	72	,	,	PUNCT
fens-978	1	73	algeria	algeria	PROPN
fens-978	1	74	geobomani@gmail.com	geobomani@gmail.com	PROPN
fens-978	2	1	*	*	PUNCT
fens-978	2	2	corresponding	correspond	VERB
fens-978	2	3	author	author	NOUN
fens-978	2	4	received	receive	VERB
fens-978	2	5	9th	9th	ADJ
fens-978	2	6	april	april	PROPN
fens-978	2	7	2023	2023	NUM
fens-978	2	8	,	,	PUNCT
fens-978	2	9	accepted	accept	VERB
fens-978	2	10	29th	29th	ADJ
fens-978	2	11	september	september	PROPN
fens-978	2	12	2023	2023	NUM
fens-978	2	13	abstract	abstract	NOUN
fens-978	2	14	:	:	PUNCT
fens-978	2	15	water	water	NOUN
fens-978	2	16	quality	quality	NOUN
fens-978	2	17	for	for	ADP
fens-978	2	18	irrigation	irrigation	NOUN
fens-978	2	19	purposes	purpose	NOUN
fens-978	2	20	has	have	VERB
fens-978	2	21	yet	yet	ADV
fens-978	2	22	to	to	PART
fens-978	2	23	be	be	AUX
fens-978	2	24	considered	consider	VERB
fens-978	2	25	seriously	seriously	ADV
fens-978	2	26	in	in	ADP
fens-978	2	27	many	many	ADJ
fens-978	2	28	places	place	NOUN
fens-978	2	29	around	around	ADP
fens-978	2	30	the	the	DET
fens-978	2	31	globe	globe	NOUN
fens-978	2	32	.	.	PUNCT
fens-978	3	1	the	the	DET
fens-978	3	2	present	present	ADJ
fens-978	3	3	case	case	NOUN
fens-978	3	4	study	study	NOUN
fens-978	3	5	at	at	ADP
fens-978	3	6	the	the	DET
fens-978	3	7	oued	oued	PROPN
fens-978	3	8	-	-	PUNCT
fens-978	3	9	hammam	hammam	PROPN
fens-978	3	10	watershed	watershed	NOUN
fens-978	3	11	in	in	ADP
fens-978	3	12	northeast	northeast	PROPN
fens-978	3	13	algeria	algeria	PROPN
fens-978	3	14	aims	aim	VERB
fens-978	3	15	to	to	PART
fens-978	3	16	investigate	investigate	VERB
fens-978	3	17	using	use	VERB
fens-978	3	18	a	a	DET
fens-978	3	19	soft	soft	ADJ
fens-978	3	20	computing	computing	NOUN
fens-978	3	21	technique	technique	NOUN
fens-978	3	22	,	,	PUNCT
fens-978	3	23	namely	namely	ADV
fens-978	3	24	an	an	DET
fens-978	3	25	artificial	artificial	ADJ
fens-978	3	26	neural	neural	ADJ
fens-978	3	27	network	network	NOUN
fens-978	3	28	,	,	PUNCT
fens-978	3	29	to	to	PART
fens-978	3	30	predict	predict	VERB
fens-978	3	31	irrigation	irrigation	NOUN
fens-978	3	32	water	water	NOUN
fens-978	3	33	quality	quality	NOUN
fens-978	3	34	indicators	indicator	NOUN
fens-978	3	35	of	of	ADP
fens-978	3	36	sodium	sodium	NOUN
fens-978	3	37	absorption	absorption	NOUN
fens-978	3	38	ratio	ratio	NOUN
fens-978	3	39	(	(	PUNCT
fens-978	3	40	sar	sar	PROPN
fens-978	3	41	)	)	PUNCT
fens-978	3	42	and	and	CCONJ
fens-978	3	43	electrical	electrical	ADJ
fens-978	3	44	conductivity	conductivity	NOUN
fens-978	3	45	(	(	PUNCT
fens-978	3	46	ec	ec	PROPN
fens-978	3	47	)	)	PUNCT
fens-978	3	48	.	.	PUNCT
fens-978	4	1	fourteen	fourteen	NUM
fens-978	4	2	water	water	NOUN
fens-978	4	3	quality	quality	NOUN
fens-978	4	4	parameters	parameter	NOUN
fens-978	4	5	were	be	AUX
fens-978	4	6	collected	collect	VERB
fens-978	4	7	at	at	ADP
fens-978	4	8	zit	zit	PROPN
fens-978	4	9	emba	emba	PROPN
fens-978	4	10	reservoir	reservoir	PROPN
fens-978	4	11	from	from	ADP
fens-978	4	12	2010	2010	NUM
fens-978	4	13	to	to	ADP
fens-978	4	14	2022	2022	NUM
fens-978	4	15	.	.	PUNCT
fens-978	5	1	among	among	ADP
fens-978	5	2	them	they	PRON
fens-978	5	3	,	,	PUNCT
fens-978	5	4	four	four	NUM
fens-978	5	5	parameters	parameter	NOUN
fens-978	5	6	,	,	PUNCT
fens-978	5	7	namely	namely	ADV
fens-978	5	8	sodium	sodium	NOUN
fens-978	5	9	(	(	PUNCT
fens-978	5	10	na	na	NOUN
fens-978	5	11	)	)	PUNCT
fens-978	5	12	,	,	PUNCT
fens-978	5	13	calcium	calcium	NOUN
fens-978	5	14	(	(	PUNCT
fens-978	5	15	ca	ca	NOUN
fens-978	5	16	)	)	PUNCT
fens-978	5	17	,	,	PUNCT
fens-978	5	18	magnesium	magnesium	NOUN
fens-978	5	19	(	(	PUNCT
fens-978	5	20	mg	mg	PROPN
fens-978	5	21	)	)	PUNCT
fens-978	5	22	,	,	PUNCT
fens-978	5	23	and	and	CCONJ
fens-978	5	24	bicarbonate	bicarbonate	NOUN
fens-978	5	25	(	(	PUNCT
fens-978	5	26	hco3	hco3	NOUN
fens-978	5	27	-	-	PUNCT
fens-978	5	28	)	)	PUNCT
fens-978	5	29	,	,	PUNCT
fens-978	5	30	were	be	AUX
fens-978	5	31	used	use	VERB
fens-978	5	32	as	as	ADP
fens-978	5	33	inputs	input	NOUN
fens-978	5	34	and	and	CCONJ
fens-978	5	35	sar	sar	NOUN
fens-978	5	36	as	as	ADP
fens-978	5	37	an	an	DET
fens-978	5	38	output	output	NOUN
fens-978	5	39	.	.	PUNCT
fens-978	6	1	also	also	ADV
fens-978	6	2	,	,	PUNCT
fens-978	6	3	five	five	NUM
fens-978	6	4	parameters	parameter	NOUN
fens-978	6	5	of	of	ADP
fens-978	6	6	total	total	ADJ
fens-978	6	7	hardness	hardness	NOUN
fens-978	6	8	(	(	PUNCT
fens-978	6	9	th	th	NOUN
fens-978	6	10	)	)	PUNCT
fens-978	6	11	,	,	PUNCT
fens-978	6	12	total	total	ADJ
fens-978	6	13	dissolved	dissolve	VERB
fens-978	6	14	solids	solid	NOUN
fens-978	6	15	(	(	PUNCT
fens-978	6	16	tds	tds	PROPN
fens-978	6	17	)	)	PUNCT
fens-978	6	18	,	,	PUNCT
fens-978	6	19	calcium	calcium	NOUN
fens-978	6	20	(	(	PUNCT
fens-978	6	21	ca	ca	NOUN
fens-978	6	22	)	)	PUNCT
fens-978	6	23	,	,	PUNCT
fens-978	6	24	bicarbonate	bicarbonate	NOUN
fens-978	6	25	(	(	PUNCT
fens-978	6	26	hco3	hco3	NOUN
fens-978	6	27	-	-	PUNCT
fens-978	6	28	)	)	PUNCT
fens-978	6	29	and	and	CCONJ
fens-978	6	30	sodium	sodium	NOUN
fens-978	6	31	(	(	PUNCT
fens-978	6	32	na	na	NOUN
fens-978	6	33	)	)	PUNCT
fens-978	6	34	were	be	AUX
fens-978	6	35	used	use	VERB
fens-978	6	36	as	as	ADP
fens-978	6	37	inputs	input	NOUN
fens-978	6	38	and	and	CCONJ
fens-978	6	39	ec	ec	PROPN
fens-978	6	40	as	as	ADP
fens-978	6	41	an	an	DET
fens-978	6	42	output	output	NOUN
fens-978	6	43	;	;	PUNCT
fens-978	6	44	the	the	DET
fens-978	6	45	pearson	pearson	NOUN
fens-978	6	46	correlation	correlation	NOUN
fens-978	6	47	matrix	matrix	NOUN
fens-978	6	48	was	be	AUX
fens-978	6	49	used	use	VERB
fens-978	6	50	to	to	PART
fens-978	6	51	select	select	VERB
fens-978	6	52	the	the	DET
fens-978	6	53	input	input	NOUN
fens-978	6	54	parameters	parameter	NOUN
fens-978	6	55	with	with	ADP
fens-978	6	56	respect	respect	NOUN
fens-978	6	57	with	with	ADP
fens-978	6	58	the	the	DET
fens-978	6	59	output	output	NOUN
fens-978	6	60	parameter	parameter	NOUN
fens-978	6	61	.	.	PUNCT
fens-978	7	1	the	the	DET
fens-978	7	2	backpropagation	backpropagation	NOUN
fens-978	7	3	neural	neural	ADJ
fens-978	7	4	networks	network	NOUN
fens-978	7	5	learning	learn	VERB
fens-978	7	6	algorithm	algorithm	NOUN
fens-978	7	7	was	be	AUX
fens-978	7	8	used	use	VERB
fens-978	7	9	to	to	PART
fens-978	7	10	model	model	VERB
fens-978	7	11	the	the	DET
fens-978	7	12	sar	sar	NOUN
fens-978	7	13	and	and	CCONJ
fens-978	7	14	ec	ec	PROPN
fens-978	7	15	's	's	PART
fens-978	7	16	irrigation	irrigation	NOUN
fens-978	7	17	water	water	NOUN
fens-978	7	18	quality	quality	NOUN
fens-978	7	19	index	index	NOUN
fens-978	7	20	(	(	PUNCT
fens-978	7	21	iwqi	iwqi	PROPN
fens-978	7	22	)	)	PUNCT
fens-978	7	23	.	.	PUNCT
fens-978	8	1	the	the	DET
fens-978	8	2	models	model	NOUN
fens-978	8	3	'	'	PART
fens-978	8	4	performances	performance	NOUN
fens-978	8	5	were	be	AUX
fens-978	8	6	evaluated	evaluate	VERB
fens-978	8	7	using	use	VERB
fens-978	8	8	statistical	statistical	ADJ
fens-978	8	9	criteria	criterion	NOUN
fens-978	8	10	of	of	ADP
fens-978	8	11	correlation	correlation	NOUN
fens-978	8	12	coefficient	coefficient	NOUN
fens-978	8	13	(	(	PUNCT
fens-978	8	14	r	r	NOUN
fens-978	8	15	)	)	PUNCT
fens-978	8	16	and	and	CCONJ
fens-978	8	17	root	root	NOUN
fens-978	8	18	mean	mean	ADJ
fens-978	8	19	square	square	ADJ
fens-978	8	20	error	error	NOUN
fens-978	8	21	(	(	PUNCT
fens-978	8	22	rmse	rmse	NOUN
fens-978	8	23	)	)	PUNCT
fens-978	8	24	.	.	PUNCT
fens-978	9	1	back	back	NOUN
fens-978	9	2	propagation	propagation	NOUN
fens-978	9	3	neural	neural	ADJ
fens-978	9	4	network	network	NOUN
fens-978	9	5	learning	learn	VERB
fens-978	9	6	algorithm	algorithm	PROPN
fens-978	9	7	maximum	maximum	ADJ
fens-978	9	8	correlation	correlation	NOUN
fens-978	9	9	coefficient	coefficient	NOUN
fens-978	9	10	for	for	ADP
fens-978	9	11	sar	sar	PROPN
fens-978	9	12	and	and	CCONJ
fens-978	9	13	ec	ec	PROPN
fens-978	9	14	were	be	AUX
fens-978	9	15	0.98077	0.98077	NUM
fens-978	9	16	and	and	CCONJ
fens-978	9	17	0.97762	0.97762	NUM
fens-978	9	18	,	,	PUNCT
fens-978	9	19	respectively	respectively	ADV
fens-978	9	20	,	,	PUNCT
fens-978	9	21	also	also	ADV
fens-978	9	22	with	with	ADP
fens-978	9	23	a	a	DET
fens-978	9	24	minimum	minimum	ADJ
fens-978	9	25	rmse	rmse	NOUN
fens-978	9	26	of	of	ADP
fens-978	9	27	0.037	0.037	NUM
fens-978	9	28	for	for	ADP
fens-978	9	29	sar	sar	NOUN
fens-978	9	30	and	and	CCONJ
fens-978	9	31	101.8	101.8	NUM
fens-978	9	32	for	for	ADP
fens-978	9	33	ec	ec	PROPN
fens-978	9	34	.	.	PUNCT
fens-978	10	1	thus	thus	ADV
fens-978	10	2	,	,	PUNCT
fens-978	10	3	the	the	DET
fens-978	10	4	current	current	ADJ
fens-978	10	5	study	study	NOUN
fens-978	10	6	suggests	suggest	VERB
fens-978	10	7	that	that	SCONJ
fens-978	10	8	artificial	artificial	ADJ
fens-978	10	9	neural	neural	ADJ
fens-978	10	10	network	network	NOUN
fens-978	10	11	(	(	PUNCT
fens-978	10	12	ann	ann	PROPN
fens-978	10	13	)	)	PUNCT
fens-978	10	14	models	model	NOUN
fens-978	10	15	are	be	AUX
fens-978	10	16	the	the	DET
fens-978	10	17	most	most	ADV
fens-978	10	18	effective	effective	ADJ
fens-978	10	19	tools	tool	NOUN
fens-978	10	20	for	for	ADP
fens-978	10	21	predicting	predict	VERB
fens-978	10	22	water	water	NOUN
fens-978	10	23	quality	quality	NOUN
fens-978	10	24	parameters	parameter	NOUN
fens-978	10	25	.	.	PUNCT
fens-978	11	1	their	their	PRON
fens-978	11	2	outcome	outcome	NOUN
fens-978	11	3	can	can	AUX
fens-978	11	4	be	be	AUX
fens-978	11	5	used	use	VERB
fens-978	11	6	effectively	effectively	ADV
fens-978	11	7	in	in	ADP
fens-978	11	8	managing	manage	VERB
fens-978	11	9	and	and	CCONJ
fens-978	11	10	controlling	control	VERB
fens-978	11	11	water	water	NOUN
fens-978	11	12	pollution	pollution	NOUN
fens-978	11	13	around	around	ADP
fens-978	11	14	the	the	DET
fens-978	11	15	watershed	watershed	NOUN
fens-978	11	16	.	.	PUNCT
fens-978	12	1	keywords	keyword	NOUN
fens-978	12	2	:	:	PUNCT
fens-978	12	3	artificial	artificial	ADJ
fens-978	12	4	neural	neural	ADJ
fens-978	12	5	network	network	NOUN
fens-978	12	6	,	,	PUNCT
fens-978	12	7	algorithm	algorithm	NOUN
fens-978	12	8	,	,	PUNCT
fens-978	12	9	person	person	NOUN
fens-978	12	10	correlation	correlation	NOUN
fens-978	12	11	matrix	matrix	NOUN
fens-978	12	12	,	,	PUNCT
fens-978	12	13	sodium	sodium	NOUN
fens-978	12	14	absorption	absorption	NOUN
fens-978	12	15	ratio	ratio	NOUN
fens-978	12	16	,	,	PUNCT
fens-978	12	17	electrical	electrical	ADJ
fens-978	12	18	conductivity	conductivity	NOUN
fens-978	12	19	,	,	PUNCT
fens-978	12	20	watershed	watershe	VERB
fens-978	12	21	.	.	PUNCT
fens-978	13	1	1	1	X
fens-978	13	2	.	.	X
fens-978	13	3	introduction	introduction	NOUN
fens-978	13	4	industrialisation	industrialisation	NOUN
fens-978	13	5	and	and	CCONJ
fens-978	13	6	population	population	NOUN
fens-978	13	7	growth	growth	NOUN
fens-978	13	8	are	be	AUX
fens-978	13	9	the	the	DET
fens-978	13	10	key	key	ADJ
fens-978	13	11	factors	factor	NOUN
fens-978	13	12	for	for	ADP
fens-978	13	13	water	water	NOUN
fens-978	13	14	deficiency	deficiency	NOUN
fens-978	13	15	;	;	PUNCT
fens-978	13	16	without	without	ADP
fens-978	13	17	forgetting	forget	VERB
fens-978	13	18	,	,	PUNCT
fens-978	13	19	other	other	ADJ
fens-978	13	20	anthropogenic	anthropogenic	ADJ
fens-978	13	21	activities	activity	NOUN
fens-978	13	22	such	such	ADJ
fens-978	13	23	as	as	ADP
fens-978	13	24	agriculture	agriculture	NOUN
fens-978	13	25	,	,	PUNCT
fens-978	13	26	mining	mining	NOUN
fens-978	13	27	,	,	PUNCT
fens-978	13	28	and	and	CCONJ
fens-978	13	29	fishing	fishing	NOUN
fens-978	13	30	can	can	AUX
fens-978	13	31	lead	lead	VERB
fens-978	13	32	to	to	ADP
fens-978	13	33	water	water	NOUN
fens-978	13	34	pollution	pollution	NOUN
fens-978	13	35	.	.	PUNCT
fens-978	14	1	humans	human	NOUN
fens-978	14	2	abstract	abstract	ADJ
fens-978	14	3	water	water	NOUN
fens-978	14	4	from	from	ADP
fens-978	14	5	the	the	DET
fens-978	14	6	hydrologic	hydrologic	ADJ
fens-978	14	7	cycle	cycle	NOUN
fens-978	14	8	for	for	ADP
fens-978	14	9	its	its	PRON
fens-978	14	10	essential	essential	ADJ
fens-978	14	11	economic	economic	ADJ
fens-978	14	12	usage	usage	NOUN
fens-978	14	13	and	and	CCONJ
fens-978	14	14	return	return	VERB
fens-978	14	15	it	it	PRON
fens-978	14	16	to	to	ADP
fens-978	14	17	the	the	DET
fens-978	14	18	corresponding	corresponding	ADJ
fens-978	14	19	process	process	NOUN
fens-978	14	20	after	after	ADP
fens-978	14	21	using	use	VERB
fens-978	14	22	it	it	PRON
fens-978	14	23	[	[	X
fens-978	14	24	1	1	NUM
fens-978	14	25	]	]	PUNCT
fens-978	14	26	.	.	PUNCT
fens-978	15	1	materials	material	NOUN
fens-978	15	2	that	that	PRON
fens-978	15	3	mix	mix	VERB
fens-978	15	4	with	with	ADP
fens-978	15	5	water	water	NOUN
fens-978	15	6	throughout	throughout	ADP
fens-978	15	7	the	the	DET
fens-978	15	8	cycle	cycle	NOUN
fens-978	15	9	can	can	AUX
fens-978	15	10	generate	generate	VERB
fens-978	15	11	a	a	DET
fens-978	15	12	notion	notion	NOUN
fens-978	15	13	of	of	ADP
fens-978	15	14	water	water	NOUN
fens-978	15	15	pollution	pollution	NOUN
fens-978	15	16	since	since	SCONJ
fens-978	15	17	they	they	PRON
fens-978	15	18	can	can	AUX
fens-978	15	19	change	change	VERB
fens-978	15	20	water	water	NOUN
fens-978	15	21	's	's	PART
fens-978	15	22	chemical	chemical	NOUN
fens-978	15	23	,	,	PUNCT
fens-978	15	24	physical	physical	ADJ
fens-978	15	25	and	and	CCONJ
fens-978	15	26	biological	biological	ADJ
fens-978	15	27	properties	property	NOUN
fens-978	15	28	after	after	ADP
fens-978	15	29	natural	natural	ADJ
fens-978	15	30	purification	purification	NOUN
fens-978	15	31	[	[	X
fens-978	15	32	2	2	NUM
fens-978	15	33	]	]	PUNCT
fens-978	15	34	.	.	PUNCT
fens-978	16	1	so	so	ADV
fens-978	16	2	,	,	PUNCT
fens-978	16	3	to	to	PART
fens-978	16	4	understand	understand	VERB
fens-978	16	5	the	the	DET
fens-978	16	6	change	change	NOUN
fens-978	16	7	in	in	ADP
fens-978	16	8	these	these	DET
fens-978	16	9	properties	property	NOUN
fens-978	16	10	,	,	PUNCT
fens-978	16	11	water	water	NOUN
fens-978	16	12	quality	quality	NOUN
fens-978	16	13	assessment	assessment	NOUN
fens-978	16	14	and	and	CCONJ
fens-978	16	15	forecasting	forecasting	NOUN
fens-978	16	16	should	should	AUX
fens-978	16	17	be	be	AUX
fens-978	16	18	done	do	VERB
fens-978	16	19	to	to	PART
fens-978	16	20	comprehend	comprehend	VERB
fens-978	16	21	the	the	DET
fens-978	16	22	state	state	NOUN
fens-978	16	23	of	of	ADP
fens-978	16	24	water	water	NOUN
fens-978	16	25	and	and	CCONJ
fens-978	16	26	its	its	PRON
fens-978	16	27	suitability	suitability	NOUN
fens-978	16	28	to	to	PART
fens-978	16	29	serve	serve	VERB
fens-978	16	30	a	a	DET
fens-978	16	31	specific	specific	ADJ
fens-978	16	32	intention	intention	NOUN
fens-978	16	33	,	,	PUNCT
fens-978	16	34	for	for	ADP
fens-978	16	35	example	example	NOUN
fens-978	16	36	,	,	PUNCT
fens-978	16	37	drinking	drinking	NOUN
fens-978	16	38	or	or	CCONJ
fens-978	16	39	irrigation	irrigation	NOUN
fens-978	16	40	.	.	PUNCT
fens-978	17	1	so	so	ADV
fens-978	17	2	far	far	ADV
fens-978	17	3	,	,	PUNCT
fens-978	17	4	large	large	ADJ
fens-978	17	5	amounts	amount	NOUN
fens-978	17	6	of	of	ADP
fens-978	17	7	domestic	domestic	ADJ
fens-978	17	8	and	and	CCONJ
fens-978	17	9	industrial	industrial	ADJ
fens-978	17	10	waste	waste	NOUN
fens-978	17	11	continue	continue	VERB
fens-978	17	12	to	to	PART
fens-978	17	13	be	be	AUX
fens-978	17	14	directed	direct	VERB
fens-978	17	15	to	to	ADP
fens-978	17	16	the	the	DET
fens-978	17	17	water	water	NOUN
fens-978	17	18	sources	source	NOUN
fens-978	17	19	[	[	X
fens-978	17	20	3	3	NUM
fens-978	17	21	]	]	PUNCT
fens-978	17	22	;	;	PUNCT
fens-978	17	23	hence	hence	ADV
fens-978	17	24	,	,	PUNCT
fens-978	17	25	water	water	NOUN
fens-978	17	26	quality	quality	NOUN
fens-978	17	27	for	for	ADP
fens-978	17	28	irrigation	irrigation	NOUN
fens-978	17	29	might	might	AUX
fens-978	17	30	deteriorate	deteriorate	VERB
fens-978	17	31	,	,	PUNCT
fens-978	17	32	and	and	CCONJ
fens-978	17	33	plant	plant	NOUN
fens-978	17	34	productivity	productivity	NOUN
fens-978	17	35	of	of	ADP
fens-978	17	36	any	any	DET
fens-978	17	37	region	region	NOUN
fens-978	17	38	can	can	AUX
fens-978	17	39	be	be	AUX
fens-978	17	40	affected	affect	VERB
fens-978	17	41	.	.	PUNCT
fens-978	18	1	the	the	DET
fens-978	18	2	present	present	ADJ
fens-978	18	3	study	study	NOUN
fens-978	18	4	assesses	assess	VERB
fens-978	18	5	irrigation	irrigation	NOUN
fens-978	18	6	water	water	NOUN
fens-978	18	7	quality	quality	NOUN
fens-978	18	8	using	use	VERB
fens-978	18	9	a	a	DET
fens-978	18	10	back	back	ADJ
fens-978	18	11	-	-	PUNCT
fens-978	18	12	propagation	propagation	NOUN
fens-978	18	13	learning	learn	VERB
fens-978	18	14	neural	neural	ADJ
fens-978	18	15	network	network	NOUN
fens-978	18	16	algorithm	algorithm	NOUN
fens-978	18	17	and	and	CCONJ
fens-978	18	18	the	the	DET
fens-978	18	19	united	united	PROPN
fens-978	18	20	states	states	PROPN
fens-978	18	21	salinity	salinity	PROPN
fens-978	18	22	laboratory	laboratory	NOUN
fens-978	18	23	method	method	NOUN
fens-978	18	24	(	(	PUNCT
fens-978	18	25	ussl	ussl	ADJ
fens-978	18	26	)	)	PUNCT
fens-978	18	27	.	.	PUNCT
fens-978	19	1	ussl	ussl	ADJ
fens-978	19	2	method	method	NOUN
fens-978	19	3	typically	typically	ADV
fens-978	19	4	considers	consider	VERB
fens-978	19	5	two	two	NUM
fens-978	19	6	parameters	parameter	NOUN
fens-978	19	7	,	,	PUNCT
fens-978	19	8	namely	namely	ADV
fens-978	19	9	sodium	sodium	NOUN
fens-978	19	10	absorption	absorption	NOUN
fens-978	19	11	ratio	ratio	NOUN
fens-978	19	12	(	(	PUNCT
fens-978	19	13	sar	sar	PROPN
fens-978	19	14	)	)	PUNCT
fens-978	19	15	and	and	CCONJ
fens-978	19	16	electrical	electrical	ADJ
fens-978	19	17	conductivity	conductivity	NOUN
fens-978	19	18	(	(	PUNCT
fens-978	19	19	ec	ec	PROPN
fens-978	19	20	)	)	PUNCT
fens-978	19	21	;	;	PUNCT
fens-978	19	22	the	the	DET
fens-978	19	23	sar	sar	NOUN
fens-978	19	24	can	can	AUX
fens-978	19	25	be	be	AUX
fens-978	19	26	estimated	estimate	VERB
fens-978	19	27	using	use	VERB
fens-978	19	28	sodium	sodium	NOUN
fens-978	19	29	,	,	PUNCT
fens-978	19	30	calcium	calcium	NOUN
fens-978	19	31	,	,	PUNCT
fens-978	19	32	and	and	CCONJ
fens-978	19	33	magnesium	magnesium	NOUN
fens-978	19	34	concentrations	concentration	NOUN
fens-978	19	35	present	present	ADJ
fens-978	19	36	in	in	ADP
fens-978	19	37	water	water	NOUN
fens-978	19	38	for	for	ADP
fens-978	19	39	irrigation[4	irrigation[4	NOUN
fens-978	19	40	]	]	PUNCT
fens-978	19	41	.	.	PUNCT
fens-978	20	1	a	a	DET
fens-978	20	2	higher	high	ADJ
fens-978	20	3	amount	amount	NOUN
fens-978	20	4	of	of	ADP
fens-978	20	5	sodium	sodium	NOUN
fens-978	20	6	reduces	reduce	VERB
fens-978	20	7	the	the	DET
fens-978	20	8	soil	soil	NOUN
fens-978	20	9	infiltration	infiltration	NOUN
fens-978	20	10	rate	rate	NOUN
fens-978	20	11	,	,	PUNCT
fens-978	20	12	decreases	decrease	VERB
fens-978	20	13	soil	soil	NOUN
fens-978	20	14	stability	stability	NOUN
fens-978	20	15	,	,	PUNCT
fens-978	20	16	and	and	CCONJ
fens-978	20	17	http://www.fia.usv.ro/fiajournal	http://www.fia.usv.ro/fiajournal	ADJ
fens-978	20	18	mailto:geobomani@gmail.com	mailto:geobomani@gmail.com	PROPN
fens-978	20	19	food	food	PROPN
fens-978	20	20	and	and	CCONJ
fens-978	20	21	environment	environment	PROPN
fens-978	20	22	safety	safety	NOUN
fens-978	20	23	journal	journal	NOUN
fens-978	20	24	of	of	ADP
fens-978	20	25	faculty	faculty	NOUN
fens-978	20	26	of	of	ADP
fens-978	20	27	food	food	NOUN
fens-978	20	28	engineering	engineering	NOUN
fens-978	20	29	,	,	PUNCT
fens-978	20	30	ştefan	ştefan	PROPN
fens-978	20	31	cel	cel	PROPN
fens-978	20	32	mare	mare	PROPN
fens-978	20	33	university	university	PROPN
fens-978	20	34	suceava	suceava	PROPN
fens-978	20	35	volume	volume	PROPN
fens-978	20	36	xxii	xxii	PROPN
fens-978	20	37	,	,	PUNCT
fens-978	20	38	issue	issue	NOUN
fens-978	20	39	3	3	NUM
fens-978	20	40	–	–	PUNCT
fens-978	20	41	2023	2023	NUM
fens-978	20	42	oswald	oswald	PROPN
fens-978	20	43	peter	peter	PROPN
fens-978	20	44	bomani	bomani	PROPN
fens-978	20	45	,	,	PUNCT
fens-978	20	46	soft	soft	ADJ
fens-978	20	47	computing	computing	NOUN
fens-978	20	48	application	application	NOUN
fens-978	20	49	to	to	PART
fens-978	20	50	predict	predict	VERB
fens-978	20	51	irrigation	irrigation	NOUN
fens-978	20	52	water	water	NOUN
fens-978	20	53	quality	quality	PROPN
fens-978	20	54	index	index	NOUN
fens-978	20	55	,	,	PUNCT
fens-978	20	56	case	case	NOUN
fens-978	20	57	study	study	NOUN
fens-978	20	58	of	of	ADP
fens-978	20	59	oued	oued	PROPN
fens-978	20	60	hammam	hammam	PROPN
fens-978	20	61	north	north	PROPN
fens-978	20	62	-	-	PUNCT
fens-978	20	63	east	east	NOUN
fens-978	20	64	algeria	algeria	PROPN
fens-978	20	65	,	,	PUNCT
fens-978	20	66	food	food	NOUN
fens-978	20	67	and	and	CCONJ
fens-978	20	68	environment	environment	NOUN
fens-978	20	69	safety	safety	NOUN
fens-978	20	70	,	,	PUNCT
fens-978	20	71	volume	volume	NOUN
fens-978	20	72	xxii	xxii	PROPN
fens-978	20	73	,	,	PUNCT
fens-978	20	74	issue	issue	NOUN
fens-978	20	75	3	3	NUM
fens-978	20	76	–	–	PUNCT
fens-978	20	77	2023	2023	NUM
fens-978	20	78	,	,	PUNCT
fens-978	20	79	pag	pag	PROPN
fens-978	20	80	.	.	PROPN
fens-978	20	81	188	188	NUM
fens-978	20	82	–	–	SYM
fens-978	20	83	198	198	NUM
fens-978	20	84	189	189	NUM
fens-978	20	85	increases	increase	VERB
fens-978	20	86	the	the	DET
fens-978	20	87	sodium	sodium	NOUN
fens-978	20	88	accumulation	accumulation	NOUN
fens-978	20	89	in	in	ADP
fens-978	20	90	the	the	DET
fens-978	20	91	leaf	leaf	NOUN
fens-978	20	92	tissue	tissue	NOUN
fens-978	21	1	[	[	X
fens-978	21	2	5	5	NUM
fens-978	21	3	]	]	PUNCT
fens-978	21	4	.	.	PUNCT
fens-978	22	1	the	the	DET
fens-978	22	2	surplus	surplus	ADJ
fens-978	22	3	content	content	NOUN
fens-978	22	4	of	of	ADP
fens-978	22	5	sar	sar	PROPN
fens-978	22	6	can	can	AUX
fens-978	22	7	affect	affect	VERB
fens-978	22	8	the	the	DET
fens-978	22	9	leaves	leave	NOUN
fens-978	22	10	of	of	ADP
fens-978	22	11	plants	plant	NOUN
fens-978	22	12	like	like	ADP
fens-978	22	13	avocados	avocado	NOUN
fens-978	22	14	,	,	PUNCT
fens-978	22	15	stone	stone	NOUN
fens-978	22	16	fruits	fruit	NOUN
fens-978	22	17	,	,	PUNCT
fens-978	22	18	and	and	CCONJ
fens-978	22	19	almonds	almond	NOUN
fens-978	22	20	[	[	X
fens-978	22	21	6	6	NUM
fens-978	22	22	]	]	PUNCT
fens-978	22	23	.	.	PUNCT
fens-978	23	1	soil	soil	NOUN
fens-978	23	2	permeability	permeability	NOUN
fens-978	23	3	can	can	AUX
fens-978	23	4	also	also	ADV
fens-978	23	5	be	be	AUX
fens-978	23	6	affected	affect	VERB
fens-978	23	7	by	by	ADP
fens-978	23	8	a	a	DET
fens-978	23	9	higher	high	ADJ
fens-978	23	10	amount	amount	NOUN
fens-978	23	11	of	of	ADP
fens-978	23	12	sar	sar	PROPN
fens-978	23	13	.	.	PUNCT
fens-978	24	1	electrical	electrical	ADJ
fens-978	24	2	conductivity	conductivity	NOUN
fens-978	24	3	(	(	PUNCT
fens-978	24	4	ec	ec	PROPN
fens-978	24	5	)	)	PUNCT
fens-978	24	6	is	be	AUX
fens-978	24	7	defined	define	VERB
fens-978	24	8	as	as	ADP
fens-978	24	9	the	the	DET
fens-978	24	10	capacity	capacity	NOUN
fens-978	24	11	of	of	ADP
fens-978	24	12	water	water	NOUN
fens-978	24	13	to	to	PART
fens-978	24	14	transmit	transmit	VERB
fens-978	24	15	electrical	electrical	ADJ
fens-978	24	16	current	current	NOUN
fens-978	24	17	.	.	PUNCT
fens-978	25	1	it	it	PRON
fens-978	25	2	is	be	AUX
fens-978	25	3	directly	directly	ADV
fens-978	25	4	proportional	proportional	ADJ
fens-978	25	5	to	to	ADP
fens-978	25	6	the	the	DET
fens-978	25	7	dissolved	dissolve	VERB
fens-978	25	8	ions	ion	NOUN
fens-978	25	9	in	in	ADP
fens-978	25	10	the	the	DET
fens-978	25	11	water	water	NOUN
fens-978	25	12	and	and	CCONJ
fens-978	25	13	their	their	PRON
fens-978	25	14	charge	charge	NOUN
fens-978	25	15	;	;	PUNCT
fens-978	25	16	ec	ec	PROPN
fens-978	25	17	can	can	AUX
fens-978	25	18	affect	affect	VERB
fens-978	25	19	crop	crop	NOUN
fens-978	25	20	growth	growth	NOUN
fens-978	25	21	directly	directly	ADV
fens-978	25	22	by	by	ADP
fens-978	25	23	toxicity	toxicity	NOUN
fens-978	25	24	or	or	CCONJ
fens-978	25	25	deficiency	deficiency	NOUN
fens-978	25	26	or	or	CCONJ
fens-978	25	27	indirectly	indirectly	ADV
fens-978	25	28	by	by	ADP
fens-978	25	29	changing	change	VERB
fens-978	25	30	plant	plant	NOUN
fens-978	25	31	nutrient	nutrient	NOUN
fens-978	25	32	availability	availability	NOUN
fens-978	25	33	[	[	X
fens-978	25	34	7	7	NUM
fens-978	25	35	]	]	PUNCT
fens-978	25	36	.	.	PUNCT
fens-978	26	1	the	the	DET
fens-978	26	2	combined	combine	VERB
fens-978	26	3	techniques	technique	NOUN
fens-978	26	4	of	of	ADP
fens-978	26	5	irrigation	irrigation	NOUN
fens-978	26	6	water	water	NOUN
fens-978	26	7	quality	quality	NOUN
fens-978	26	8	index	index	NOUN
fens-978	26	9	(	(	PUNCT
fens-978	26	10	iwqi	iwqi	PROPN
fens-978	26	11	)	)	PUNCT
fens-978	26	12	and	and	CCONJ
fens-978	26	13	artificial	artificial	ADJ
fens-978	26	14	neural	neural	ADJ
fens-978	26	15	network	network	NOUN
fens-978	26	16	(	(	PUNCT
fens-978	26	17	ann	ann	PROPN
fens-978	26	18	)	)	PUNCT
fens-978	26	19	could	could	AUX
fens-978	26	20	be	be	AUX
fens-978	26	21	used	use	VERB
fens-978	26	22	in	in	ADP
fens-978	26	23	assessing	assess	VERB
fens-978	26	24	the	the	DET
fens-978	26	25	state	state	NOUN
fens-978	26	26	of	of	ADP
fens-978	26	27	water	water	NOUN
fens-978	26	28	for	for	ADP
fens-978	26	29	irrigation	irrigation	NOUN
fens-978	26	30	purposes	purpose	NOUN
fens-978	26	31	because	because	SCONJ
fens-978	26	32	these	these	DET
fens-978	26	33	techniques	technique	NOUN
fens-978	26	34	can	can	AUX
fens-978	26	35	convert	convert	VERB
fens-978	26	36	the	the	DET
fens-978	26	37	complex	complex	ADJ
fens-978	26	38	data	datum	NOUN
fens-978	26	39	that	that	PRON
fens-978	26	40	have	have	VERB
fens-978	26	41	to	to	PART
fens-978	26	42	be	be	AUX
fens-978	26	43	performed	perform	VERB
fens-978	26	44	into	into	ADP
fens-978	26	45	an	an	DET
fens-978	26	46	understandable	understandable	ADJ
fens-978	26	47	way	way	NOUN
fens-978	26	48	for	for	SCONJ
fens-978	26	49	the	the	DET
fens-978	26	50	policymakers	policymaker	NOUN
fens-978	26	51	and	and	CCONJ
fens-978	26	52	public	public	NOUN
fens-978	26	53	can	can	AUX
fens-978	26	54	be	be	AUX
fens-978	26	55	informed	inform	VERB
fens-978	26	56	on	on	ADP
fens-978	26	57	the	the	DET
fens-978	26	58	quality	quality	NOUN
fens-978	26	59	of	of	ADP
fens-978	26	60	water	water	NOUN
fens-978	26	61	.	.	PUNCT
fens-978	27	1	in	in	ADP
fens-978	27	2	present	present	ADJ
fens-978	27	3	years	year	NOUN
fens-978	27	4	,	,	PUNCT
fens-978	27	5	various	various	ADJ
fens-978	27	6	models	model	NOUN
fens-978	27	7	,	,	PUNCT
fens-978	27	8	including	include	VERB
fens-978	27	9	traditional	traditional	ADJ
fens-978	27	10	mechanistic	mechanistic	ADJ
fens-978	27	11	applications	application	NOUN
fens-978	27	12	,	,	PUNCT
fens-978	27	13	have	have	AUX
fens-978	27	14	been	be	AUX
fens-978	27	15	involved	involve	VERB
fens-978	27	16	so	so	SCONJ
fens-978	27	17	that	that	SCONJ
fens-978	27	18	managing	manage	VERB
fens-978	27	19	the	the	DET
fens-978	27	20	water	water	NOUN
fens-978	27	21	quality	quality	NOUN
fens-978	27	22	of	of	ADP
fens-978	27	23	these	these	DET
fens-978	27	24	models	model	NOUN
fens-978	27	25	requires	require	VERB
fens-978	27	26	different	different	ADJ
fens-978	27	27	input	input	NOUN
fens-978	27	28	data	datum	NOUN
fens-978	27	29	,	,	PUNCT
fens-978	27	30	which	which	PRON
fens-978	27	31	can	can	AUX
fens-978	27	32	not	not	PART
fens-978	27	33	be	be	AUX
fens-978	27	34	readily	readily	ADV
fens-978	27	35	available	available	ADJ
fens-978	27	36	and	and	CCONJ
fens-978	27	37	makes	make	VERB
fens-978	27	38	it	it	PRON
fens-978	27	39	a	a	DET
fens-978	27	40	costly	costly	ADJ
fens-978	27	41	and	and	CCONJ
fens-978	27	42	time	time	NOUN
fens-978	27	43	-	-	PUNCT
fens-978	27	44	consuming	consume	VERB
fens-978	27	45	process	process	NOUN
fens-978	27	46	.	.	PUNCT
fens-978	28	1	ann	ann	PROPN
fens-978	28	2	is	be	AUX
fens-978	28	3	the	the	DET
fens-978	28	4	appropriate	appropriate	ADJ
fens-978	28	5	approach	approach	NOUN
fens-978	28	6	for	for	ADP
fens-978	28	7	water	water	NOUN
fens-978	28	8	quality	quality	NOUN
fens-978	28	9	modelling	modelling	NOUN
fens-978	28	10	[	[	X
fens-978	28	11	8	8	NUM
fens-978	28	12	]	]	PUNCT
fens-978	28	13	.	.	PUNCT
fens-978	29	1	the	the	DET
fens-978	29	2	main	main	ADJ
fens-978	29	3	objective	objective	NOUN
fens-978	29	4	of	of	ADP
fens-978	29	5	the	the	DET
fens-978	29	6	present	present	ADJ
fens-978	29	7	work	work	NOUN
fens-978	29	8	is	be	AUX
fens-978	29	9	to	to	PART
fens-978	29	10	develop	develop	VERB
fens-978	29	11	an	an	DET
fens-978	29	12	artificial	artificial	ADJ
fens-978	29	13	neural	neural	ADJ
fens-978	29	14	network	network	NOUN
fens-978	29	15	(	(	PUNCT
fens-978	29	16	ann	ann	PROPN
fens-978	29	17	)	)	PUNCT
fens-978	29	18	model	model	NOUN
fens-978	29	19	of	of	ADP
fens-978	29	20	the	the	DET
fens-978	29	21	oued	oued	PROPN
fens-978	29	22	-	-	PUNCT
fens-978	29	23	hammam	hammam	PROPN
fens-978	29	24	watershed	watershed	NOUN
fens-978	29	25	to	to	PART
fens-978	29	26	understand	understand	VERB
fens-978	29	27	the	the	DET
fens-978	29	28	classification	classification	NOUN
fens-978	29	29	of	of	ADP
fens-978	29	30	sodium	sodium	NOUN
fens-978	29	31	absorption	absorption	NOUN
fens-978	29	32	ratio	ratio	NOUN
fens-978	29	33	(	(	PUNCT
fens-978	29	34	sar	sar	PROPN
fens-978	29	35	)	)	PUNCT
fens-978	29	36	and	and	CCONJ
fens-978	29	37	electrical	electrical	ADJ
fens-978	29	38	conductivity	conductivity	NOUN
fens-978	29	39	(	(	PUNCT
fens-978	29	40	ec	ec	PROPN
fens-978	29	41	)	)	PUNCT
fens-978	29	42	in	in	ADP
fens-978	29	43	water	water	NOUN
fens-978	29	44	for	for	ADP
fens-978	29	45	irrigation	irrigation	NOUN
fens-978	29	46	so	so	SCONJ
fens-978	29	47	that	that	SCONJ
fens-978	29	48	it	it	PRON
fens-978	29	49	can	can	AUX
fens-978	29	50	be	be	AUX
fens-978	29	51	used	use	VERB
fens-978	29	52	to	to	PART
fens-978	29	53	predict	predict	VERB
fens-978	29	54	water	water	NOUN
fens-978	29	55	quality	quality	NOUN
fens-978	29	56	and	and	CCONJ
fens-978	29	57	hence	hence	ADV
fens-978	29	58	crop	crop	NOUN
fens-978	29	59	production	production	NOUN
fens-978	29	60	improvement	improvement	NOUN
fens-978	29	61	.	.	PUNCT
fens-978	30	1	2	2	X
fens-978	30	2	.	.	X
fens-978	30	3	geographical	geographical	ADJ
fens-978	30	4	location	location	NOUN
fens-978	30	5	of	of	ADP
fens-978	30	6	the	the	DET
fens-978	30	7	study	study	NOUN
fens-978	30	8	area	area	NOUN
fens-978	30	9	the	the	DET
fens-978	30	10	oued	oued	PROPN
fens-978	30	11	-	-	PUNCT
fens-978	30	12	hammam	hammam	PROPN
fens-978	30	13	(	(	PUNCT
fens-978	30	14	figure	figure	NOUN
fens-978	30	15	1	1	NUM
fens-978	30	16	)	)	PUNCT
fens-978	30	17	watershed	watershed	NOUN
fens-978	30	18	is	be	AUX
fens-978	30	19	in	in	ADP
fens-978	30	20	the	the	DET
fens-978	30	21	skikda	skikda	NOUN
fens-978	30	22	region	region	NOUN
fens-978	30	23	northeast	northeast	ADV
fens-978	30	24	of	of	ADP
fens-978	30	25	algeria	algeria	PROPN
fens-978	30	26	,	,	PUNCT
fens-978	30	27	covering	cover	VERB
fens-978	30	28	an	an	DET
fens-978	30	29	area	area	NOUN
fens-978	30	30	of	of	ADP
fens-978	30	31	485	485	NUM
fens-978	30	32	km²	km²	NOUN
fens-978	30	33	and	and	CCONJ
fens-978	30	34	controlled	control	VERB
fens-978	30	35	by	by	ADP
fens-978	30	36	the	the	DET
fens-978	30	37	zit	zit	PROPN
fens-978	30	38	emba	emba	PROPN
fens-978	30	39	reservoir	reservoir	PROPN
fens-978	30	40	at	at	ADP
fens-978	30	41	a	a	DET
fens-978	30	42	coordinate	coordinate	NOUN
fens-978	30	43	of	of	ADP
fens-978	30	44	36.6836	36.6836	NUM
fens-978	30	45	°	°	NOUN
fens-978	30	46	n	n	CCONJ
fens-978	30	47	,	,	PUNCT
fens-978	30	48	7.3020	7.3020	NUM
fens-978	30	49	°	°	PROPN
fens-978	30	50	e.	e.	PROPN
fens-978	30	51	the	the	DET
fens-978	30	52	oued	oued	PROPN
fens-978	30	53	-	-	PUNCT
fens-978	30	54	hamman	hamman	PROPN
fens-978	30	55	is	be	AUX
fens-978	30	56	one	one	NUM
fens-978	30	57	of	of	ADP
fens-978	30	58	the	the	DET
fens-978	30	59	most	most	ADV
fens-978	30	60	potential	potential	ADJ
fens-978	30	61	tributaries	tributary	NOUN
fens-978	30	62	of	of	ADP
fens-978	30	63	the	the	DET
fens-978	30	64	west	west	PROPN
fens-978	30	65	kebir	kebir	PROPN
fens-978	30	66	wadi	wadi	NOUN
fens-978	30	67	and	and	CCONJ
fens-978	30	68	takes	take	VERB
fens-978	30	69	its	its	PRON
fens-978	30	70	source	source	NOUN
fens-978	30	71	at	at	ADP
fens-978	30	72	the	the	DET
fens-978	30	73	level	level	NOUN
fens-978	30	74	of	of	ADP
fens-978	30	75	djebel	djebel	NOUN
fens-978	30	76	bousba	bousba	NOUN
fens-978	30	77	at	at	ADP
fens-978	30	78	an	an	DET
fens-978	30	79	altitude	altitude	NOUN
fens-978	30	80	of	of	ADP
fens-978	30	81	623	623	NUM
fens-978	30	82	m.	m.	NOUN
fens-978	30	83	the	the	DET
fens-978	30	84	watershed	watershed	NOUN
fens-978	30	85	(	(	PUNCT
fens-978	30	86	figure	figure	NOUN
fens-978	30	87	2	2	NUM
fens-978	30	88	)	)	PUNCT
fens-978	30	89	which	which	PRON
fens-978	30	90	flows	flow	VERB
fens-978	30	91	into	into	ADP
fens-978	30	92	the	the	DET
fens-978	30	93	dam	dam	NOUN
fens-978	30	94	has	have	VERB
fens-978	30	95	a	a	DET
fens-978	30	96	subtropical	subtropical	ADJ
fens-978	30	97	climate	climate	NOUN
fens-978	30	98	characterized	characterize	VERB
fens-978	30	99	by	by	ADP
fens-978	30	100	hot	hot	ADJ
fens-978	30	101	summers	summer	NOUN
fens-978	30	102	and	and	CCONJ
fens-978	30	103	comparatively	comparatively	ADV
fens-978	30	104	mild	mild	ADJ
fens-978	30	105	and	and	CCONJ
fens-978	30	106	rainy	rainy	ADJ
fens-978	30	107	winters	winter	NOUN
fens-978	30	108	,	,	PUNCT
fens-978	30	109	an	an	DET
fens-978	30	110	average	average	ADJ
fens-978	30	111	annual	annual	ADJ
fens-978	30	112	temperature	temperature	NOUN
fens-978	30	113	of	of	ADP
fens-978	30	114	the	the	DET
fens-978	30	115	order	order	NOUN
fens-978	30	116	of	of	ADP
fens-978	30	117	17.3	17.3	NUM
fens-978	30	118	°	°	NOUN
fens-978	30	119	c	c	NOUN
fens-978	30	120	with	with	ADP
fens-978	30	121	a	a	DET
fens-978	30	122	minimum	minimum	NOUN
fens-978	30	123	of	of	ADP
fens-978	30	124	9.3	9.3	NUM
fens-978	30	125	°	°	NOUN
fens-978	30	126	c	c	NOUN
fens-978	30	127	in	in	ADP
fens-978	30	128	january	january	PROPN
fens-978	30	129	and	and	CCONJ
fens-978	30	130	a	a	DET
fens-978	30	131	maximum	maximum	ADJ
fens-978	30	132	reach	reach	NOUN
fens-978	30	133	of	of	ADP
fens-978	30	134	26.5	26.5	NUM
fens-978	30	135	°	°	NOUN
fens-978	30	136	c	c	NOUN
fens-978	30	137	in	in	ADP
fens-978	30	138	august	august	PROPN
fens-978	30	139	.	.	PUNCT
fens-978	31	1	potential	potential	ADJ
fens-978	31	2	evapotranspiration	evapotranspiration	NOUN
fens-978	31	3	closely	closely	ADV
fens-978	31	4	related	relate	VERB
fens-978	31	5	to	to	ADP
fens-978	31	6	temperatures	temperature	NOUN
fens-978	31	7	varies	vary	VERB
fens-978	31	8	between	between	ADP
fens-978	31	9	35	35	NUM
fens-978	31	10	mm	mm	NOUN
fens-978	31	11	in	in	ADP
fens-978	31	12	december	december	PROPN
fens-978	31	13	to	to	ADP
fens-978	31	14	200	200	NUM
fens-978	31	15	mm	mm	NOUN
fens-978	31	16	in	in	ADP
fens-978	31	17	july	july	PROPN
fens-978	31	18	and	and	CCONJ
fens-978	31	19	the	the	DET
fens-978	31	20	average	average	ADJ
fens-978	31	21	annual	annual	ADJ
fens-978	31	22	threshold	threshold	NOUN
fens-978	31	23	of	of	ADP
fens-978	31	24	1306	1306	NUM
fens-978	31	25	mm	mm	NOUN
fens-978	31	26	.	.	PUNCT
fens-978	32	1	this	this	DET
fens-978	32	2	reservoir	reservoir	NOUN
fens-978	32	3	is	be	AUX
fens-978	32	4	intended	intend	VERB
fens-978	32	5	for	for	ADP
fens-978	32	6	drinking	drinking	NOUN
fens-978	32	7	and	and	CCONJ
fens-978	32	8	irrigating	irrigate	VERB
fens-978	32	9	the	the	DET
fens-978	32	10	ben	ben	PROPN
fens-978	32	11	-	-	PUNCT
fens-978	32	12	azzouz	azzouz	PROPN
fens-978	32	13	,	,	PUNCT
fens-978	32	14	azzaba	azzaba	NOUN
fens-978	32	15	plains	plain	NOUN
fens-978	32	16	,	,	PUNCT
fens-978	32	17	and	and	CCONJ
fens-978	32	18	neighbouring	neighbouring	ADJ
fens-978	32	19	areas	area	NOUN
fens-978	32	20	.	.	PUNCT
fens-978	33	1	fig	fig	NOUN
fens-978	33	2	.	.	PUNCT
fens-978	34	1	1	1	X
fens-978	34	2	.	.	X
fens-978	34	3	geographical	geographical	ADJ
fens-978	34	4	location	location	NOUN
fens-978	34	5	of	of	ADP
fens-978	34	6	oued	oued	PROPN
fens-978	34	7	-	-	PUNCT
fens-978	34	8	hammam	hammam	PROPN
fens-978	34	9	watershed	watershed	NOUN
fens-978	34	10	(	(	PUNCT
fens-978	34	11	source	source	NOUN
fens-978	34	12	:	:	PUNCT
fens-978	34	13	own	own	ADJ
fens-978	34	14	elaboration	elaboration	NOUN
fens-978	34	15	)	)	PUNCT
fens-978	34	16	.	.	PUNCT
fens-978	35	1	fig	fig	NOUN
fens-978	35	2	.	.	PUNCT
fens-978	36	1	2	2	X
fens-978	36	2	.	.	X
fens-978	36	3	oued	oue	VERB
fens-978	36	4	-	-	PUNCT
fens-978	36	5	hammam	hammam	PROPN
fens-978	36	6	watershed	watershe	VERB
fens-978	36	7	2.1	2.1	NUM
fens-978	36	8	data	datum	NOUN
fens-978	36	9	collection	collection	NOUN
fens-978	36	10	water	water	NOUN
fens-978	36	11	samples	sample	NOUN
fens-978	36	12	were	be	AUX
fens-978	36	13	collected	collect	VERB
fens-978	36	14	each	each	DET
fens-978	36	15	month	month	NOUN
fens-978	36	16	from	from	ADP
fens-978	36	17	2010	2010	NUM
fens-978	36	18	to	to	ADP
fens-978	36	19	2022	2022	NUM
fens-978	36	20	,	,	PUNCT
fens-978	36	21	and	and	CCONJ
fens-978	36	22	the	the	DET
fens-978	36	23	sampling	sample	VERB
fens-978	36	24	station	station	NOUN
fens-978	36	25	was	be	AUX
fens-978	36	26	zit	zit	NOUN
fens-978	36	27	emba	emba	PROPN
fens-978	36	28	reservoir	reservoir	PROPN
fens-978	36	29	.	.	PUNCT
fens-978	37	1	fourteen	fourteen	NUM
fens-978	37	2	water	water	NOUN
fens-978	37	3	food	food	NOUN
fens-978	37	4	and	and	CCONJ
fens-978	37	5	environment	environment	NOUN
fens-978	37	6	safety	safety	NOUN
fens-978	37	7	journal	journal	NOUN
fens-978	37	8	of	of	ADP
fens-978	37	9	faculty	faculty	NOUN
fens-978	37	10	of	of	ADP
fens-978	37	11	food	food	NOUN
fens-978	37	12	engineering	engineering	NOUN
fens-978	37	13	,	,	PUNCT
fens-978	37	14	ştefan	ştefan	PROPN
fens-978	37	15	cel	cel	PROPN
fens-978	37	16	mare	mare	PROPN
fens-978	37	17	university	university	PROPN
fens-978	37	18	suceava	suceava	PROPN
fens-978	37	19	volume	volume	PROPN
fens-978	37	20	xxii	xxii	PROPN
fens-978	37	21	,	,	PUNCT
fens-978	37	22	issue	issue	NOUN
fens-978	37	23	3	3	NUM
fens-978	37	24	–	–	PUNCT
fens-978	37	25	2023	2023	NUM
fens-978	37	26	oswald	oswald	PROPN
fens-978	37	27	peter	peter	PROPN
fens-978	37	28	bomani	bomani	PROPN
fens-978	37	29	,	,	PUNCT
fens-978	37	30	soft	soft	ADJ
fens-978	37	31	computing	computing	NOUN
fens-978	37	32	application	application	NOUN
fens-978	37	33	to	to	PART
fens-978	37	34	predict	predict	VERB
fens-978	37	35	irrigation	irrigation	NOUN
fens-978	37	36	water	water	NOUN
fens-978	37	37	quality	quality	PROPN
fens-978	37	38	index	index	NOUN
fens-978	37	39	,	,	PUNCT
fens-978	37	40	case	case	NOUN
fens-978	37	41	study	study	NOUN
fens-978	37	42	of	of	ADP
fens-978	37	43	oued	oued	PROPN
fens-978	37	44	hammam	hammam	PROPN
fens-978	37	45	north	north	PROPN
fens-978	37	46	-	-	PUNCT
fens-978	37	47	east	east	NOUN
fens-978	37	48	algeria	algeria	PROPN
fens-978	37	49	,	,	PUNCT
fens-978	37	50	food	food	NOUN
fens-978	37	51	and	and	CCONJ
fens-978	37	52	environment	environment	NOUN
fens-978	37	53	safety	safety	NOUN
fens-978	37	54	,	,	PUNCT
fens-978	37	55	volume	volume	NOUN
fens-978	37	56	xxii	xxii	PROPN
fens-978	37	57	,	,	PUNCT
fens-978	37	58	issue	issue	NOUN
fens-978	37	59	3	3	NUM
fens-978	37	60	–	–	PUNCT
fens-978	37	61	2023	2023	NUM
fens-978	37	62	,	,	PUNCT
fens-978	37	63	pag	pag	PROPN
fens-978	37	64	.	.	PROPN
fens-978	37	65	188	188	NUM
fens-978	37	66	–	–	SYM
fens-978	37	67	198	198	NUM
fens-978	37	68	190	190	NUM
fens-978	37	69	quality	quality	NOUN
fens-978	37	70	parameters	parameter	NOUN
fens-978	37	71	were	be	AUX
fens-978	37	72	collected	collect	VERB
fens-978	37	73	and	and	CCONJ
fens-978	37	74	analyzed	analyze	VERB
fens-978	37	75	for	for	ADP
fens-978	37	76	13	13	NUM
fens-978	37	77	years	year	NOUN
fens-978	37	78	.	.	PUNCT
fens-978	38	1	the	the	DET
fens-978	38	2	parameters	parameter	NOUN
fens-978	38	3	which	which	PRON
fens-978	38	4	were	be	AUX
fens-978	38	5	investigated	investigate	VERB
fens-978	38	6	during	during	ADP
fens-978	38	7	this	this	DET
fens-978	38	8	study	study	NOUN
fens-978	38	9	are	be	AUX
fens-978	38	10	shown	show	VERB
fens-978	38	11	in	in	ADP
fens-978	38	12	table	table	NOUN
fens-978	38	13	1	1	NUM
fens-978	38	14	.	.	PUNCT
fens-978	38	15	table	table	NOUN
fens-978	38	16	1	1	NUM
fens-978	38	17	.	.	PUNCT
fens-978	39	1	parameters	parameter	NOUN
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fens-978	39	3	at	at	ADP
fens-978	39	4	the	the	DET
fens-978	39	5	zit	zit	NOUN
fens-978	39	6	-	-	PUNCT
fens-978	39	7	emba	emba	PROPN
fens-978	39	8	reservoir	reservoir	PROPN
fens-978	39	9	.	.	PUNCT
fens-978	40	1	3	3	X
fens-978	40	2	.	.	X
fens-978	40	3	material	material	NOUN
fens-978	40	4	and	and	CCONJ
fens-978	40	5	methods	method	NOUN
fens-978	40	6	3.1	3.1	NUM
fens-978	40	7	calculating	calculating	NOUN
fens-978	40	8	of	of	ADP
fens-978	40	9	sodium	sodium	NOUN
fens-978	40	10	absorption	absorption	NOUN
fens-978	40	11	ratio	ratio	NOUN
fens-978	40	12	(	(	PUNCT
fens-978	40	13	sar	sar	PROPN
fens-978	40	14	)	)	PUNCT
fens-978	40	15	estimations	estimation	NOUN
fens-978	40	16	of	of	ADP
fens-978	40	17	sar	sar	NOUN
fens-978	40	18	were	be	AUX
fens-978	40	19	done	do	VERB
fens-978	40	20	according	accord	VERB
fens-978	40	21	to	to	ADP
fens-978	40	22	the	the	DET
fens-978	40	23	[	[	X
fens-978	40	24	9	9	NUM
fens-978	40	25	]	]	PUNCT
fens-978	40	26	formula	formula	NOUN
fens-978	40	27	in	in	ADP
fens-978	40	28	which	which	PRON
fens-978	40	29	sodium	sodium	NOUN
fens-978	40	30	,	,	PUNCT
fens-978	40	31	magnesium	magnesium	NOUN
fens-978	40	32	and	and	CCONJ
fens-978	40	33	calcium	calcium	NOUN
fens-978	40	34	parameters	parameter	NOUN
fens-978	40	35	were	be	AUX
fens-978	40	36	used	use	VERB
fens-978	40	37	in	in	ADP
fens-978	40	38	the	the	DET
fens-978	40	39	calculation	calculation	NOUN
fens-978	40	40	.	.	PUNCT
fens-978	41	1	𝐒𝐀𝐑	𝐒𝐀𝐑	NOUN
fens-978	42	1	=	=	PUNCT
fens-978	43	1	[	[	X
fens-978	43	2	𝑵𝒂+	𝑵𝒂+	X
fens-978	43	3	]	]	X
fens-978	43	4	√	√	NOUN
fens-978	43	5	𝟏	𝟏	NUM
fens-978	43	6	𝟐	𝟐	NUM
fens-978	43	7	{	{	PUNCT
fens-978	43	8	[	[	X
fens-978	43	9	𝐌𝐠𝟐+	𝐌𝐠𝟐+	X
fens-978	43	10	]	]	X
fens-978	44	1	+	+	PROPN
fens-978	45	1	[	[	X
fens-978	45	2	𝑪𝒂𝟐+	𝑪𝒂𝟐+	X
fens-978	45	3	]	]	X
fens-978	45	4	}	}	PUNCT
fens-978	45	5	(	(	PUNCT
fens-978	45	6	1	1	X
fens-978	45	7	)	)	PUNCT
fens-978	46	1	where	where	SCONJ
fens-978	46	2	na+	na+	NOUN
fens-978	46	3	,	,	PUNCT
fens-978	46	4	mg2	mg2	PROPN
fens-978	46	5	+	+	PROPN
fens-978	46	6	,	,	PUNCT
fens-978	46	7	and	and	CCONJ
fens-978	46	8	ca2	ca2	PROPN
fens-978	46	9	+	+	X
fens-978	46	10	in	in	ADP
fens-978	46	11	mill	mill	NOUN
fens-978	46	12	equivalents	equivalent	NOUN
fens-978	46	13	per	per	ADP
fens-978	46	14	litre	litre	NOUN
fens-978	46	15	(	(	PUNCT
fens-978	46	16	meq	meq	NOUN
fens-978	46	17	/	/	SYM
fens-978	46	18	l	l	NOUN
fens-978	46	19	)	)	PUNCT
fens-978	46	20	.	.	PUNCT
fens-978	46	21	3.2	3.2	NUM
fens-978	46	22	the	the	DET
fens-978	46	23	general	general	ADJ
fens-978	46	24	outlook	outlook	NOUN
fens-978	46	25	of	of	ADP
fens-978	46	26	artificial	artificial	ADJ
fens-978	46	27	neural	neural	ADJ
fens-978	46	28	network	network	NOUN
fens-978	46	29	(	(	PUNCT
fens-978	46	30	ann	ann	PROPN
fens-978	46	31	)	)	PUNCT
fens-978	46	32	.	.	PUNCT
fens-978	47	1	from	from	ADP
fens-978	47	2	2008	2008	NUM
fens-978	47	3	to	to	ADP
fens-978	47	4	date	date	NOUN
fens-978	47	5	,	,	PUNCT
fens-978	47	6	the	the	DET
fens-978	47	7	application	application	NOUN
fens-978	47	8	of	of	ADP
fens-978	47	9	ann	ann	PROPN
fens-978	47	10	techniques	technique	NOUN
fens-978	47	11	in	in	ADP
fens-978	47	12	predicting	predict	VERB
fens-978	47	13	water	water	NOUN
fens-978	47	14	quality	quality	NOUN
fens-978	47	15	has	have	AUX
fens-978	47	16	become	become	VERB
fens-978	47	17	very	very	ADV
fens-978	47	18	popular	popular	ADJ
fens-978	47	19	.	.	PUNCT
fens-978	48	1	many	many	ADJ
fens-978	48	2	researchers	researcher	NOUN
fens-978	48	3	employ	employ	VERB
fens-978	48	4	this	this	DET
fens-978	48	5	method	method	NOUN
fens-978	48	6	to	to	PART
fens-978	48	7	model	model	VERB
fens-978	48	8	and	and	CCONJ
fens-978	48	9	forecast	forecast	NOUN
fens-978	48	10	water	water	NOUN
fens-978	48	11	quality	quality	NOUN
fens-978	48	12	;	;	PUNCT
fens-978	48	13	in	in	ADP
fens-978	48	14	the	the	DET
fens-978	48	15	present	present	ADJ
fens-978	48	16	study	study	NOUN
fens-978	48	17	,	,	PUNCT
fens-978	48	18	an	an	DET
fens-978	48	19	artificial	artificial	ADJ
fens-978	48	20	neural	neural	ADJ
fens-978	48	21	network	network	NOUN
fens-978	48	22	algorithm	algorithm	NOUN
fens-978	48	23	was	be	AUX
fens-978	48	24	used	use	VERB
fens-978	48	25	to	to	PART
fens-978	48	26	approximate	approximate	VERB
fens-978	48	27	irrigation	irrigation	NOUN
fens-978	48	28	water	water	NOUN
fens-978	48	29	quality	quality	NOUN
fens-978	48	30	parameters	parameter	NOUN
fens-978	48	31	(	(	PUNCT
fens-978	48	32	ec	ec	PROPN
fens-978	48	33	and	and	CCONJ
fens-978	48	34	sar	sar	PROPN
fens-978	48	35	)	)	PUNCT
fens-978	48	36	.	.	PUNCT
fens-978	49	1	ann	ann	PROPN
fens-978	49	2	models	model	NOUN
fens-978	49	3	are	be	AUX
fens-978	49	4	highly	highly	ADV
fens-978	49	5	flexible	flexible	ADJ
fens-978	49	6	function	function	NOUN
fens-978	49	7	estimators	estimator	NOUN
fens-978	49	8	that	that	PRON
fens-978	49	9	have	have	AUX
fens-978	49	10	demonstrated	demonstrate	VERB
fens-978	49	11	their	their	PRON
fens-978	49	12	usefulness	usefulness	NOUN
fens-978	49	13	in	in	ADP
fens-978	49	14	a	a	DET
fens-978	49	15	wide	wide	ADJ
fens-978	49	16	range	range	NOUN
fens-978	49	17	of	of	ADP
fens-978	49	18	water	water	NOUN
fens-978	49	19	resources	resource	NOUN
fens-978	49	20	.	.	PUNCT
fens-978	50	1	3.2.1	3.2.1	NUM
fens-978	50	2	practical	practical	ADJ
fens-978	50	3	applications	application	NOUN
fens-978	50	4	.	.	PUNCT
fens-978	51	1	in	in	ADP
fens-978	51	2	[	[	X
fens-978	51	3	10	10	NUM
fens-978	51	4	]	]	PUNCT
fens-978	51	5	,	,	PUNCT
fens-978	51	6	ann	ann	PROPN
fens-978	51	7	modelling	modelling	NOUN
fens-978	51	8	techniques	technique	NOUN
fens-978	51	9	have	have	AUX
fens-978	51	10	performed	perform	VERB
fens-978	51	11	better	well	ADV
fens-978	51	12	than	than	ADP
fens-978	51	13	classical	classical	ADJ
fens-978	51	14	models	model	NOUN
fens-978	51	15	.	.	PUNCT
fens-978	52	1	anns	anns	PROPN
fens-978	52	2	are	be	AUX
fens-978	52	3	models	model	NOUN
fens-978	52	4	influenced	influence	VERB
fens-978	52	5	by	by	ADP
fens-978	52	6	biological	biological	ADJ
fens-978	52	7	neural	neural	ADJ
fens-978	52	8	networks	network	NOUN
fens-978	52	9	[	[	X
fens-978	52	10	11	11	NUM
fens-978	52	11	]	]	PUNCT
fens-978	52	12	.	.	PUNCT
fens-978	53	1	this	this	PRON
fens-978	53	2	concerns	concern	VERB
fens-978	53	3	the	the	DET
fens-978	53	4	human	human	ADJ
fens-978	53	5	brain	brain	NOUN
fens-978	53	6	's	's	PART
fens-978	53	7	central	central	ADJ
fens-978	53	8	nervous	nervous	ADJ
fens-978	53	9	system	system	NOUN
fens-978	53	10	in	in	ADP
fens-978	53	11	animals	animal	NOUN
fens-978	53	12	[	[	X
fens-978	53	13	12	12	NUM
fens-978	53	14	]	]	PUNCT
fens-978	53	15	.	.	PUNCT
fens-978	54	1	in	in	ADP
fens-978	54	2	general	general	ADJ
fens-978	54	3	,	,	PUNCT
fens-978	54	4	ann	ann	PROPN
fens-978	54	5	can	can	AUX
fens-978	54	6	be	be	AUX
fens-978	54	7	a	a	DET
fens-978	54	8	system	system	NOUN
fens-978	54	9	of	of	ADP
fens-978	54	10	interconnected	interconnected	ADJ
fens-978	54	11	“	"	PUNCT
fens-978	54	12	neurons”[13	neurons”[13	NOUN
fens-978	54	13	]	]	PUNCT
fens-978	54	14	.	.	PUNCT
fens-978	55	1	weight	weight	NOUN
fens-978	55	2	parameters	parameter	NOUN
fens-978	55	3	and	and	CCONJ
fens-978	55	4	activation	activation	NOUN
fens-978	55	5	functions	function	NOUN
fens-978	55	6	are	be	AUX
fens-978	55	7	components	component	NOUN
fens-978	55	8	of	of	ADP
fens-978	55	9	the	the	DET
fens-978	55	10	neurons	neuron	NOUN
fens-978	55	11	[	[	X
fens-978	55	12	14	14	NUM
fens-978	55	13	]	]	PUNCT
fens-978	55	14	.	.	PUNCT
fens-978	56	1	anns	anns	PROPN
fens-978	56	2	are	be	AUX
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fens-978	56	4	divided	divide	VERB
fens-978	56	5	into	into	ADP
fens-978	56	6	three	three	NUM
fens-978	56	7	layers	layer	NOUN
fens-978	56	8	:	:	PUNCT
fens-978	56	9	input	input	NOUN
fens-978	56	10	,	,	PUNCT
fens-978	56	11	hidden	hide	VERB
fens-978	56	12	,	,	PUNCT
fens-978	56	13	and	and	CCONJ
fens-978	56	14	output	output	NOUN
fens-978	56	15	.	.	PUNCT
fens-978	57	1	when	when	SCONJ
fens-978	57	2	neurons	neuron	NOUN
fens-978	57	3	receive	receive	VERB
fens-978	57	4	information	information	NOUN
fens-978	57	5	from	from	ADP
fens-978	57	6	different	different	ADJ
fens-978	57	7	inputs	input	NOUN
fens-978	57	8	,	,	PUNCT
fens-978	57	9	they	they	PRON
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fens-978	57	11	nonlinearity	nonlinearity	NOUN
fens-978	57	12	by	by	ADP
fens-978	57	13	activation	activation	NOUN
fens-978	57	14	functions	function	NOUN
fens-978	57	15	.	.	PUNCT
fens-978	58	1	ann	ann	PROPN
fens-978	58	2	models	model	NOUN
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fens-978	58	4	strongly	strongly	ADV
fens-978	58	5	on	on	ADP
fens-978	58	6	the	the	DET
fens-978	58	7	quantity	quantity	NOUN
fens-978	58	8	of	of	ADP
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fens-978	58	10	[	[	X
fens-978	58	11	15	15	NUM
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fens-978	59	2	,	,	PUNCT
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fens-978	59	5	small	small	ADJ
fens-978	59	6	data	datum	NOUN
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fens-978	59	14	not	not	PART
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fens-978	59	16	since	since	SCONJ
fens-978	59	17	some	some	DET
fens-978	59	18	helpful	helpful	ADJ
fens-978	59	19	information	information	NOUN
fens-978	59	20	is	be	AUX
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fens-978	59	22	in	in	ADP
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fens-978	59	24	-	-	PUNCT
fens-978	59	25	term	term	NOUN
fens-978	59	26	data	datum	NOUN
fens-978	59	27	,	,	PUNCT
fens-978	59	28	which	which	PRON
fens-978	59	29	might	might	AUX
fens-978	59	30	result	result	VERB
fens-978	59	31	in	in	ADP
fens-978	59	32	poor	poor	ADJ
fens-978	59	33	prediction	prediction	NOUN
fens-978	59	34	results	result	NOUN
fens-978	59	35	[	[	X
fens-978	59	36	16	16	NUM
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fens-978	59	38	.	.	PUNCT
fens-978	60	1	in	in	ADP
fens-978	60	2	addition	addition	NOUN
fens-978	60	3	,	,	PUNCT
fens-978	60	4	data	datum	NOUN
fens-978	60	5	splitting	splitting	NOUN
fens-978	60	6	is	be	AUX
fens-978	60	7	an	an	DET
fens-978	60	8	essential	essential	ADJ
fens-978	60	9	step	step	NOUN
fens-978	60	10	in	in	ADP
fens-978	60	11	the	the	DET
fens-978	60	12	modelling	modelling	NOUN
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fens-978	61	1	in	in	ADP
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fens-978	61	5	,	,	PUNCT
fens-978	61	6	data	datum	NOUN
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fens-978	61	8	was	be	AUX
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fens-978	61	11	with	with	ADP
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fens-978	61	14	neural	neural	ADJ
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fens-978	61	16	learning	learn	VERB
fens-978	61	17	algorithm	algorithm	NOUN
fens-978	61	18	in	in	ADP
fens-978	61	19	which	which	PRON
fens-978	61	20	75	75	NUM
fens-978	61	21	%	%	NOUN
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fens-978	61	25	was	be	AUX
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fens-978	61	27	for	for	ADP
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fens-978	61	31	%	%	NOUN
fens-978	61	32	for	for	ADP
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fens-978	62	2	tests	test	NOUN
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fens-978	62	7	that	that	SCONJ
fens-978	62	8	all	all	DET
fens-978	62	9	training	training	NOUN
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fens-978	62	15	by	by	ADP
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fens-978	63	1	3.2.2	3.2.2	NUM
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fens-978	63	5	networks	network	NOUN
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fens-978	64	1	in	in	ADP
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fens-978	64	6	,	,	PUNCT
fens-978	64	7	back	back	NOUN
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fens-978	64	11	the	the	DET
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fens-978	64	13	known	know	VERB
fens-978	64	14	and	and	CCONJ
fens-978	64	15	most	most	ADV
fens-978	64	16	applied	apply	VERB
fens-978	64	17	learning	learn	VERB
fens-978	64	18	algorithm	algorithm	NOUN
fens-978	64	19	among	among	ADP
fens-978	64	20	all	all	DET
fens-978	64	21	neural	neural	ADJ
fens-978	64	22	network	network	NOUN
fens-978	64	23	prototypes	prototype	NOUN
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fens-978	64	25	17	17	NUM
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fens-978	65	2	propagation	propagation	NOUN
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fens-978	65	5	antecedently	antecedently	ADV
fens-978	65	6	been	be	AUX
fens-978	65	7	named	name	VERB
fens-978	65	8	as	as	ADP
fens-978	65	9	the	the	DET
fens-978	65	10	most	most	ADV
fens-978	65	11	common	common	ADJ
fens-978	65	12	type	type	NOUN
fens-978	65	13	of	of	ADP
fens-978	65	14	ann	ann	PROPN
fens-978	65	15	models	model	NOUN
fens-978	65	16	used	use	VERB
fens-978	65	17	in	in	ADP
fens-978	65	18	water	water	NOUN
fens-978	65	19	resources	resource	NOUN
fens-978	65	20	practical	practical	ADJ
fens-978	65	21	applications	application	NOUN
fens-978	65	22	.	.	PUNCT
fens-978	66	1	in	in	ADP
fens-978	66	2	[	[	X
fens-978	66	3	18	18	NUM
fens-978	66	4	]	]	PUNCT
fens-978	66	5	,	,	PUNCT
fens-978	66	6	it	it	PRON
fens-978	66	7	is	be	AUX
fens-978	66	8	suggested	suggest	VERB
fens-978	66	9	that	that	SCONJ
fens-978	66	10	the	the	DET
fens-978	66	11	back	back	ADJ
fens-978	66	12	-	-	PUNCT
fens-978	66	13	propagation	propagation	NOUN
fens-978	66	14	algorithm	algorithm	NOUN
fens-978	66	15	relies	rely	VERB
fens-978	66	16	on	on	ADP
fens-978	66	17	the	the	DET
fens-978	66	18	generalisation	generalisation	NOUN
fens-978	66	19	delta	delta	NOUN
fens-978	66	20	rule	rule	NOUN
fens-978	66	21	.	.	PUNCT
fens-978	67	1	the	the	DET
fens-978	67	2	back	back	ADJ
fens-978	67	3	-	-	PUNCT
fens-978	67	4	propagation	propagation	NOUN
fens-978	67	5	algorithm	algorithm	NOUN
fens-978	67	6	dataset	dataset	NOUN
fens-978	67	7	of	of	ADP
fens-978	67	8	inputs	input	NOUN
fens-978	67	9	and	and	CCONJ
fens-978	67	10	outputs	output	NOUN
fens-978	67	11	is	be	AUX
fens-978	67	12	chosen	choose	VERB
fens-978	67	13	from	from	ADP
fens-978	67	14	the	the	DET
fens-978	67	15	no	no	NOUN
fens-978	67	16	:	:	PUNCT
fens-978	67	17	parameter	parameter	NOUN
fens-978	67	18	units	unit	NOUN
fens-978	67	19	1	1	NUM
fens-978	67	20	potential	potential	ADJ
fens-978	67	21	hydrogen	hydrogen	NOUN
fens-978	67	22	(	(	PUNCT
fens-978	67	23	ph	ph	ADJ
fens-978	67	24	)	)	PUNCT
fens-978	67	25	2	2	NUM
fens-978	67	26	electrical	electrical	ADJ
fens-978	67	27	conductivity	conductivity	NOUN
fens-978	67	28	(	(	PUNCT
fens-978	67	29	ec	ec	PROPN
fens-978	67	30	)	)	PUNCT
fens-978	68	1	[	[	X
fens-978	68	2	μs	μs	NUM
fens-978	68	3	/	/	SYM
fens-978	68	4	cm	cm	NOUN
fens-978	68	5	]	]	SYM
fens-978	68	6	3	3	NUM
fens-978	68	7	calcium	calcium	NOUN
fens-978	68	8	(	(	PUNCT
fens-978	68	9	ca2	ca2	PROPN
fens-978	68	10	+	+	PROPN
fens-978	68	11	)	)	PUNCT
fens-978	69	1	[	[	X
fens-978	69	2	meq	meq	NUM
fens-978	69	3	/	/	SYM
fens-978	69	4	l	l	NOUN
fens-978	69	5	]	]	X
fens-978	69	6	4	4	NUM
fens-978	69	7	magnesium	magnesium	NOUN
fens-978	69	8	mg2	mg2	NOUN
fens-978	69	9	+	+	NOUN
fens-978	69	10	)	)	PUNCT
fens-978	70	1	[	[	X
fens-978	70	2	meq	meq	NUM
fens-978	70	3	/	/	SYM
fens-978	70	4	l	l	NOUN
fens-978	70	5	]	]	X
fens-978	70	6	5	5	NUM
fens-978	70	7	sodium	sodium	NOUN
fens-978	70	8	(	(	PUNCT
fens-978	70	9	na+	na+	NOUN
fens-978	70	10	)	)	PUNCT
fens-978	71	1	[	[	X
fens-978	71	2	meq	meq	X
fens-978	71	3	/	/	SYM
fens-978	71	4	l	l	NOUN
fens-978	71	5	]	]	X
fens-978	71	6	6	6	NUM
fens-978	71	7	bicarbonate	bicarbonate	NOUN
fens-978	71	8	(	(	PUNCT
fens-978	71	9	hco3	hco3	NOUN
fens-978	71	10	-	-	PUNCT
fens-978	71	11	)	)	PUNCT
fens-978	72	1	[	[	X
fens-978	72	2	mg	mg	NUM
fens-978	72	3	/	/	SYM
fens-978	72	4	l	l	NOUN
fens-978	72	5	]	]	X
fens-978	72	6	7	7	NUM
fens-978	72	7	potassium	potassium	NOUN
fens-978	72	8	(	(	PUNCT
fens-978	72	9	k+	k+	NOUN
fens-978	72	10	)	)	PUNCT
fens-978	73	1	[	[	X
fens-978	73	2	mg	mg	NUM
fens-978	73	3	/	/	SYM
fens-978	73	4	l	l	NOUN
fens-978	73	5	]	]	X
fens-978	73	6	8	8	NUM
fens-978	73	7	chloride	chloride	NOUN
fens-978	73	8	(	(	PUNCT
fens-978	73	9	cl	cl	NOUN
fens-978	73	10	)	)	PUNCT
fens-978	74	1	[	[	X
fens-978	74	2	mg	mg	NUM
fens-978	74	3	/	/	SYM
fens-978	74	4	l	l	NOUN
fens-978	74	5	]	]	PUNCT
fens-978	74	6	9	9	NUM
fens-978	74	7	total	total	ADJ
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fens-978	74	9	(	(	PUNCT
fens-978	74	10	th	th	NOUN
fens-978	74	11	)	)	PUNCT
fens-978	75	1	[	[	X
fens-978	75	2	mg	mg	NUM
fens-978	75	3	/	/	SYM
fens-978	75	4	l	l	NOUN
fens-978	75	5	]	]	PUNCT
fens-978	75	6	10	10	NUM
fens-978	75	7	total	total	ADJ
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fens-978	75	10	(	(	PUNCT
fens-978	75	11	tds	tds	PROPN
fens-978	75	12	)	)	PUNCT
fens-978	76	1	[	[	X
fens-978	76	2	mg	mg	NUM
fens-978	76	3	/	/	SYM
fens-978	76	4	l	l	NOUN
fens-978	76	5	]	]	SYM
fens-978	76	6	11	11	NUM
fens-978	76	7	nitrate	nitrate	NOUN
fens-978	76	8	(	(	PUNCT
fens-978	76	9	no3	no3	NOUN
fens-978	76	10	-	-	PUNCT
fens-978	76	11	)	)	PUNCT
fens-978	77	1	[	[	X
fens-978	77	2	mg	mg	NUM
fens-978	77	3	/	/	SYM
fens-978	77	4	l	l	NOUN
fens-978	77	5	]	]	X
fens-978	77	6	12	12	NUM
fens-978	77	7	nitrite	nitrite	NOUN
fens-978	77	8	(	(	PUNCT
fens-978	77	9	no2	no2	NOUN
fens-978	77	10	-	-	PUNCT
fens-978	77	11	)	)	PUNCT
fens-978	78	1	[	[	X
fens-978	78	2	mg	mg	NUM
fens-978	78	3	/	/	SYM
fens-978	78	4	l	l	NOUN
fens-978	78	5	]	]	X
fens-978	78	6	13	13	NUM
fens-978	78	7	sulphate	sulphate	NOUN
fens-978	78	8	(	(	PUNCT
fens-978	78	9	so4	so4	PROPN
fens-978	78	10	2-	2-	X
fens-978	78	11	)	)	PUNCT
fens-978	79	1	[	[	X
fens-978	79	2	mg	mg	NUM
fens-978	79	3	/	/	SYM
fens-978	79	4	l	l	NOUN
fens-978	79	5	]	]	X
fens-978	79	6	14	14	NUM
fens-978	79	7	phosphate	phosphate	NOUN
fens-978	79	8	(	(	PUNCT
fens-978	79	9	po4	po4	PROPN
fens-978	79	10	3-	3-	PROPN
fens-978	79	11	)	)	PUNCT
fens-978	79	12	[	[	X
fens-978	79	13	mg	mg	NUM
fens-978	79	14	/	/	SYM
fens-978	79	15	l	l	NOUN
fens-978	79	16	]	]	X
fens-978	79	17	food	food	NOUN
fens-978	79	18	and	and	CCONJ
fens-978	79	19	environment	environment	NOUN
fens-978	79	20	safety	safety	NOUN
fens-978	79	21	journal	journal	NOUN
fens-978	79	22	of	of	ADP
fens-978	79	23	faculty	faculty	NOUN
fens-978	79	24	of	of	ADP
fens-978	79	25	food	food	NOUN
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fens-978	79	29	cel	cel	PROPN
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fens-978	79	31	university	university	PROPN
fens-978	79	32	suceava	suceava	PROPN
fens-978	79	33	volume	volume	PROPN
fens-978	79	34	xxii	xxii	PROPN
fens-978	79	35	,	,	PUNCT
fens-978	79	36	issue	issue	NOUN
fens-978	79	37	3	3	NUM
fens-978	79	38	–	–	PUNCT
fens-978	79	39	2023	2023	NUM
fens-978	79	40	oswald	oswald	PROPN
fens-978	79	41	peter	peter	PROPN
fens-978	79	42	bomani	bomani	PROPN
fens-978	79	43	,	,	PUNCT
fens-978	79	44	soft	soft	ADJ
fens-978	79	45	computing	computing	NOUN
fens-978	79	46	application	application	NOUN
fens-978	79	47	to	to	PART
fens-978	79	48	predict	predict	VERB
fens-978	79	49	irrigation	irrigation	NOUN
fens-978	79	50	water	water	NOUN
fens-978	79	51	quality	quality	PROPN
fens-978	79	52	index	index	NOUN
fens-978	79	53	,	,	PUNCT
fens-978	79	54	case	case	NOUN
fens-978	79	55	study	study	NOUN
fens-978	79	56	of	of	ADP
fens-978	79	57	oued	oued	PROPN
fens-978	79	58	hammam	hammam	PROPN
fens-978	79	59	north	north	PROPN
fens-978	79	60	-	-	PUNCT
fens-978	79	61	east	east	NOUN
fens-978	79	62	algeria	algeria	PROPN
fens-978	79	63	,	,	PUNCT
fens-978	79	64	food	food	NOUN
fens-978	79	65	and	and	CCONJ
fens-978	79	66	environment	environment	NOUN
fens-978	79	67	safety	safety	NOUN
fens-978	79	68	,	,	PUNCT
fens-978	79	69	volume	volume	NOUN
fens-978	79	70	xxii	xxii	PROPN
fens-978	79	71	,	,	PUNCT
fens-978	79	72	issue	issue	NOUN
fens-978	79	73	3	3	NUM
fens-978	79	74	–	–	PUNCT
fens-978	79	75	2023	2023	NUM
fens-978	79	76	,	,	PUNCT
fens-978	79	77	pag	pag	PROPN
fens-978	79	78	.	.	PROPN
fens-978	79	79	188	188	NUM
fens-978	79	80	–	–	SYM
fens-978	79	81	198	198	NUM
fens-978	79	82	191	191	NUM
fens-978	79	83	training	training	NOUN
fens-978	79	84	dataset	dataset	NOUN
fens-978	79	85	,	,	PUNCT
fens-978	79	86	and	and	CCONJ
fens-978	79	87	the	the	DET
fens-978	79	88	network	network	NOUN
fens-978	79	89	computes	compute	VERB
fens-978	79	90	the	the	DET
fens-978	79	91	result	result	NOUN
fens-978	79	92	depending	depend	VERB
fens-978	79	93	on	on	ADP
fens-978	79	94	the	the	DET
fens-978	79	95	input	input	NOUN
fens-978	79	96	datasets	dataset	NOUN
fens-978	79	97	.	.	PUNCT
fens-978	80	1	this	this	DET
fens-978	80	2	output	output	NOUN
fens-978	80	3	is	be	AUX
fens-978	80	4	deducted	deduct	VERB
fens-978	80	5	from	from	ADP
fens-978	80	6	the	the	DET
fens-978	80	7	actual	actual	ADJ
fens-978	80	8	output	output	NOUN
fens-978	80	9	to	to	PART
fens-978	80	10	find	find	VERB
fens-978	80	11	the	the	DET
fens-978	80	12	output	output	NOUN
fens-978	80	13	-	-	PUNCT
fens-978	80	14	layer	layer	NOUN
fens-978	80	15	error	error	NOUN
fens-978	80	16	.	.	PUNCT
fens-978	81	1	the	the	DET
fens-978	81	2	error	error	NOUN
fens-978	81	3	is	be	AUX
fens-978	81	4	back	back	ADV
fens-978	81	5	-	-	PUNCT
fens-978	81	6	propagated	propagate	VERB
fens-978	81	7	through	through	ADP
fens-978	81	8	the	the	DET
fens-978	81	9	network	network	NOUN
fens-978	81	10	,	,	PUNCT
fens-978	81	11	and	and	CCONJ
fens-978	81	12	the	the	DET
fens-978	81	13	weights	weight	NOUN
fens-978	81	14	are	be	AUX
fens-978	81	15	suitably	suitably	ADV
fens-978	81	16	adjusted	adjust	VERB
fens-978	81	17	.	.	PUNCT
fens-978	82	1	the	the	DET
fens-978	82	2	process	process	NOUN
fens-978	82	3	proceeds	proceed	VERB
fens-978	82	4	for	for	ADP
fens-978	82	5	the	the	DET
fens-978	82	6	number	number	NOUN
fens-978	82	7	of	of	ADP
fens-978	82	8	dictated	dictate	VERB
fens-978	82	9	sweeps	sweep	NOUN
fens-978	82	10	or	or	CCONJ
fens-978	82	11	until	until	SCONJ
fens-978	82	12	the	the	DET
fens-978	82	13	desired	desire	VERB
fens-978	82	14	error	error	NOUN
fens-978	82	15	tolerance	tolerance	NOUN
fens-978	82	16	is	be	AUX
fens-978	82	17	reached	reach	VERB
fens-978	82	18	.	.	PUNCT
fens-978	83	1	the	the	DET
fens-978	83	2	root	root	NOUN
fens-978	83	3	means	mean	VERB
fens-978	83	4	square	square	ADJ
fens-978	83	5	error	error	NOUN
fens-978	83	6	(	(	PUNCT
fens-978	83	7	rmse	rmse	NOUN
fens-978	83	8	)	)	PUNCT
fens-978	83	9	above	above	ADP
fens-978	83	10	the	the	DET
fens-978	83	11	training	training	NOUN
fens-978	83	12	dataset	dataset	NOUN
fens-978	83	13	is	be	AUX
fens-978	83	14	the	the	DET
fens-978	83	15	distinctive	distinctive	ADJ
fens-978	83	16	target	target	NOUN
fens-978	83	17	function	function	NOUN
fens-978	83	18	to	to	PART
fens-978	83	19	be	be	AUX
fens-978	83	20	minimised	minimise	VERB
fens-978	83	21	.	.	PUNCT
fens-978	84	1	it	it	PRON
fens-978	84	2	employs	employ	VERB
fens-978	84	3	the	the	DET
fens-978	84	4	back	back	ADJ
fens-978	84	5	-	-	PUNCT
fens-978	84	6	propagation	propagation	NOUN
fens-978	84	7	(	(	PUNCT
fens-978	84	8	bp	bp	PROPN
fens-978	84	9	)	)	PUNCT
fens-978	84	10	of	of	ADP
fens-978	84	11	the	the	DET
fens-978	84	12	error	error	NOUN
fens-978	84	13	gradient	gradient	NOUN
fens-978	84	14	.	.	PUNCT
fens-978	85	1	this	this	DET
fens-978	85	2	training	training	NOUN
fens-978	85	3	algorithm	algorithm	NOUN
fens-978	85	4	is	be	AUX
fens-978	85	5	a	a	DET
fens-978	85	6	technique	technique	NOUN
fens-978	85	7	that	that	PRON
fens-978	85	8	assists	assist	VERB
fens-978	85	9	the	the	DET
fens-978	85	10	spread	spread	NOUN
fens-978	85	11	of	of	ADP
fens-978	85	12	error	error	NOUN
fens-978	85	13	to	to	PART
fens-978	85	14	attain	attain	VERB
fens-978	85	15	the	the	DET
fens-978	85	16	best	good	ADJ
fens-978	85	17	fit	fit	ADJ
fens-978	85	18	or	or	CCONJ
fens-978	85	19	minimum	minimum	ADJ
fens-978	85	20	error	error	NOUN
fens-978	85	21	.	.	PUNCT
fens-978	86	1	after	after	SCONJ
fens-978	86	2	the	the	DET
fens-978	86	3	dataset	dataset	NOUN
fens-978	86	4	has	have	AUX
fens-978	86	5	gone	go	VERB
fens-978	86	6	through	through	ADP
fens-978	86	7	the	the	DET
fens-978	86	8	network	network	NOUN
fens-978	86	9	in	in	ADP
fens-978	86	10	a	a	DET
fens-978	86	11	forward	forward	ADJ
fens-978	86	12	direction	direction	NOUN
fens-978	86	13	and	and	CCONJ
fens-978	86	14	the	the	DET
fens-978	86	15	network	network	NOUN
fens-978	86	16	has	have	AUX
fens-978	86	17	predicted	predict	VERB
fens-978	86	18	an	an	DET
fens-978	86	19	output	output	NOUN
fens-978	86	20	,	,	PUNCT
fens-978	86	21	the	the	DET
fens-978	86	22	back	back	ADJ
fens-978	86	23	-	-	PUNCT
fens-978	86	24	propagation	propagation	NOUN
fens-978	86	25	algorithm	algorithm	NOUN
fens-978	86	26	spreads	spread	VERB
fens-978	86	27	the	the	DET
fens-978	86	28	error	error	NOUN
fens-978	86	29	related	relate	VERB
fens-978	86	30	to	to	ADP
fens-978	86	31	the	the	DET
fens-978	86	32	output	output	NOUN
fens-978	86	33	back	back	ADV
fens-978	86	34	through	through	ADP
fens-978	86	35	the	the	DET
fens-978	86	36	model	model	NOUN
fens-978	86	37	,	,	PUNCT
fens-978	86	38	and	and	CCONJ
fens-978	86	39	weights	weight	NOUN
fens-978	86	40	are	be	AUX
fens-978	86	41	aligned	align	VERB
fens-978	86	42	accordingly	accordingly	ADV
fens-978	86	43	.	.	PUNCT
fens-978	87	1	the	the	DET
fens-978	87	2	minimization	minimization	NOUN
fens-978	87	3	of	of	ADP
fens-978	87	4	the	the	DET
fens-978	87	5	error	error	NOUN
fens-978	87	6	is	be	AUX
fens-978	87	7	achieved	achieve	VERB
fens-978	87	8	through	through	ADP
fens-978	87	9	various	various	ADJ
fens-978	87	10	iterations	iteration	NOUN
fens-978	87	11	.	.	PUNCT
fens-978	88	1	when	when	SCONJ
fens-978	88	2	the	the	DET
fens-978	88	3	training	training	NOUN
fens-978	88	4	phase	phase	NOUN
fens-978	88	5	is	be	AUX
fens-978	88	6	complete	complete	ADJ
fens-978	88	7	,	,	PUNCT
fens-978	88	8	and	and	CCONJ
fens-978	88	9	ann	ann	PROPN
fens-978	88	10	performance	performance	NOUN
fens-978	88	11	is	be	AUX
fens-978	88	12	validated	validate	VERB
fens-978	88	13	,	,	PUNCT
fens-978	88	14	the	the	DET
fens-978	88	15	validation	validation	NOUN
fens-978	88	16	phase	phase	NOUN
fens-978	88	17	can	can	AUX
fens-978	88	18	suggest	suggest	VERB
fens-978	88	19	whether	whether	SCONJ
fens-978	88	20	to	to	PART
fens-978	88	21	retrain	retrain	VERB
fens-978	88	22	the	the	DET
fens-978	88	23	model	model	NOUN
fens-978	88	24	,	,	PUNCT
fens-978	88	25	depending	depend	VERB
fens-978	88	26	on	on	ADP
fens-978	88	27	the	the	DET
fens-978	88	28	model	model	NOUN
fens-978	88	29	results	result	NOUN
fens-978	88	30	.	.	PUNCT
fens-978	89	1	before	before	ADP
fens-978	89	2	training	train	VERB
fens-978	89	3	the	the	DET
fens-978	89	4	dataset	dataset	NOUN
fens-978	89	5	,	,	PUNCT
fens-978	89	6	the	the	DET
fens-978	89	7	input	input	NOUN
fens-978	89	8	data	datum	NOUN
fens-978	89	9	were	be	AUX
fens-978	89	10	normalized	normalize	VERB
fens-978	89	11	using	use	VERB
fens-978	89	12	the	the	DET
fens-978	89	13	z	z	NOUN
fens-978	89	14	-	-	PUNCT
fens-978	89	15	score	score	NOUN
fens-978	89	16	normalization	normalization	NOUN
fens-978	89	17	technique	technique	NOUN
fens-978	89	18	.	.	PUNCT
fens-978	90	1	the	the	DET
fens-978	90	2	method	method	NOUN
fens-978	90	3	is	be	AUX
fens-978	90	4	based	base	VERB
fens-978	90	5	on	on	ADP
fens-978	90	6	the	the	DET
fens-978	90	7	calculation	calculation	NOUN
fens-978	90	8	of	of	ADP
fens-978	90	9	the	the	DET
fens-978	90	10	median	median	ADJ
fens-978	90	11	absolute	absolute	ADJ
fens-978	90	12	deviation	deviation	NOUN
fens-978	90	13	[	[	X
fens-978	90	14	19	19	NUM
fens-978	90	15	]	]	PUNCT
fens-978	90	16	,	,	PUNCT
fens-978	90	17	and	and	CCONJ
fens-978	90	18	the	the	DET
fens-978	90	19	normalization	normalization	NOUN
fens-978	90	20	score	score	NOUN
fens-978	90	21	nv	nv	PROPN
fens-978	90	22	can	can	AUX
fens-978	90	23	be	be	AUX
fens-978	90	24	calculated	calculate	VERB
fens-978	90	25	as	as	SCONJ
fens-978	90	26	follows	follow	VERB
fens-978	90	27	:	:	PUNCT
fens-978	90	28	𝒏𝒗	𝒏𝒗	VERB
fens-978	90	29	=	=	SYM
fens-978	90	30	𝒇(𝒗	𝒇(𝒗	PROPN
fens-978	90	31	)	)	PUNCT
fens-978	90	32	=	=	PUNCT
fens-978	91	1	𝒗−𝜶	𝒗−𝜶	ADJ
fens-978	91	2	𝝋	𝝋	X
fens-978	91	3	(	(	PUNCT
fens-978	91	4	2	2	NUM
fens-978	91	5	)	)	PUNCT
fens-978	91	6	where	where	SCONJ
fens-978	91	7	α	α	PRON
fens-978	91	8	represents	represent	VERB
fens-978	91	9	the	the	DET
fens-978	91	10	mean	mean	ADJ
fens-978	91	11	value	value	NOUN
fens-978	91	12	,	,	PUNCT
fens-978	91	13	while	while	SCONJ
fens-978	91	14	φ	φ	PROPN
fens-978	91	15	represents	represent	VERB
fens-978	91	16	the	the	DET
fens-978	91	17	standard	standard	ADJ
fens-978	91	18	deviation	deviation	NOUN
fens-978	91	19	of	of	ADP
fens-978	91	20	the	the	DET
fens-978	91	21	dataset	dataset	NOUN
fens-978	91	22	.	.	PUNCT
fens-978	92	1	fig	fig	NOUN
fens-978	92	2	.	.	PUNCT
fens-978	93	1	3	3	X
fens-978	93	2	.	.	X
fens-978	93	3	an	an	DET
fens-978	93	4	example	example	NOUN
fens-978	93	5	of	of	ADP
fens-978	93	6	artificial	artificial	ADJ
fens-978	93	7	neural	neural	ADJ
fens-978	93	8	network	network	NOUN
fens-978	93	9	architecture	architecture	NOUN
fens-978	93	10	with	with	ADP
fens-978	93	11	one	one	NUM
fens-978	93	12	input	input	NOUN
fens-978	93	13	layer	layer	NOUN
fens-978	93	14	(	(	PUNCT
fens-978	93	15	five	five	NUM
fens-978	93	16	input	input	NOUN
fens-978	93	17	parameters	parameter	NOUN
fens-978	93	18	)	)	PUNCT
fens-978	93	19	,	,	PUNCT
fens-978	93	20	one	one	NUM
fens-978	93	21	hidden	hide	VERB
fens-978	93	22	layer	layer	NOUN
fens-978	93	23	(	(	PUNCT
fens-978	93	24	four	four	NUM
fens-978	93	25	nodes	node	NOUN
fens-978	93	26	)	)	PUNCT
fens-978	93	27	,	,	PUNCT
fens-978	93	28	and	and	CCONJ
fens-978	93	29	one	one	NUM
fens-978	93	30	output	output	NOUN
fens-978	93	31	layer	layer	NOUN
fens-978	93	32	(	(	PUNCT
fens-978	93	33	one	one	NUM
fens-978	93	34	output	output	NOUN
fens-978	93	35	parameter	parameter	NOUN
fens-978	93	36	)	)	PUNCT
fens-978	93	37	,	,	PUNCT
fens-978	93	38	source	source	NOUN
fens-978	93	39	:	:	PUNCT
fens-978	93	40	own	own	ADJ
fens-978	93	41	elaboration	elaboration	NOUN
fens-978	93	42	.	.	PUNCT
fens-978	94	1	food	food	NOUN
fens-978	94	2	and	and	CCONJ
fens-978	94	3	environment	environment	PROPN
fens-978	94	4	safety	safety	NOUN
fens-978	94	5	journal	journal	NOUN
fens-978	94	6	of	of	ADP
fens-978	94	7	faculty	faculty	NOUN
fens-978	94	8	of	of	ADP
fens-978	94	9	food	food	NOUN
fens-978	94	10	engineering	engineering	NOUN
fens-978	94	11	,	,	PUNCT
fens-978	94	12	ştefan	ştefan	PROPN
fens-978	94	13	cel	cel	PROPN
fens-978	94	14	mare	mare	PROPN
fens-978	94	15	university	university	PROPN
fens-978	94	16	suceava	suceava	PROPN
fens-978	94	17	volume	volume	PROPN
fens-978	94	18	xxii	xxii	PROPN
fens-978	94	19	,	,	PUNCT
fens-978	94	20	issue	issue	NOUN
fens-978	94	21	3	3	NUM
fens-978	94	22	–	–	PUNCT
fens-978	94	23	2023	2023	NUM
fens-978	94	24	oswald	oswald	PROPN
fens-978	94	25	peter	peter	PROPN
fens-978	94	26	bomani	bomani	PROPN
fens-978	94	27	,	,	PUNCT
fens-978	94	28	soft	soft	ADJ
fens-978	94	29	computing	computing	NOUN
fens-978	94	30	application	application	NOUN
fens-978	94	31	to	to	PART
fens-978	94	32	predict	predict	VERB
fens-978	94	33	irrigation	irrigation	NOUN
fens-978	94	34	water	water	NOUN
fens-978	94	35	quality	quality	PROPN
fens-978	94	36	index	index	NOUN
fens-978	94	37	,	,	PUNCT
fens-978	94	38	case	case	NOUN
fens-978	94	39	study	study	NOUN
fens-978	94	40	of	of	ADP
fens-978	94	41	oued	oued	PROPN
fens-978	94	42	hammam	hammam	PROPN
fens-978	94	43	north	north	PROPN
fens-978	94	44	-	-	PUNCT
fens-978	94	45	east	east	NOUN
fens-978	94	46	algeria	algeria	PROPN
fens-978	94	47	,	,	PUNCT
fens-978	94	48	food	food	NOUN
fens-978	94	49	and	and	CCONJ
fens-978	94	50	environment	environment	NOUN
fens-978	94	51	safety	safety	NOUN
fens-978	94	52	,	,	PUNCT
fens-978	94	53	volume	volume	NOUN
fens-978	94	54	xxii	xxii	PROPN
fens-978	94	55	,	,	PUNCT
fens-978	94	56	issue	issue	NOUN
fens-978	94	57	3	3	NUM
fens-978	94	58	–	–	PUNCT
fens-978	94	59	2023	2023	NUM
fens-978	94	60	,	,	PUNCT
fens-978	94	61	pag	pag	PROPN
fens-978	94	62	.	.	PROPN
fens-978	94	63	188	188	NUM
fens-978	94	64	–	–	PUNCT
fens-978	94	65	198	198	NUM
fens-978	94	66	192	192	NUM
fens-978	94	67	4	4	NUM
fens-978	94	68	.	.	PUNCT
fens-978	94	69	results	result	NOUN
fens-978	94	70	and	and	CCONJ
fens-978	94	71	discussions	discussion	NOUN
fens-978	94	72	4.1	4.1	NUM
fens-978	94	73	selection	selection	NOUN
fens-978	94	74	of	of	ADP
fens-978	94	75	the	the	DET
fens-978	94	76	input	input	NOUN
fens-978	94	77	parameters	parameter	NOUN
fens-978	94	78	monthly	monthly	ADJ
fens-978	94	79	water	water	NOUN
fens-978	94	80	quality	quality	NOUN
fens-978	94	81	parameters	parameter	NOUN
fens-978	94	82	from	from	ADP
fens-978	94	83	2010	2010	NUM
fens-978	94	84	to	to	ADP
fens-978	94	85	2022	2022	NUM
fens-978	94	86	were	be	AUX
fens-978	94	87	measured	measure	VERB
fens-978	94	88	from	from	ADP
fens-978	94	89	the	the	DET
fens-978	94	90	station	station	NOUN
fens-978	94	91	.	.	PUNCT
fens-978	95	1	parameters	parameter	NOUN
fens-978	95	2	including	include	VERB
fens-978	95	3	ph	ph	PROPN
fens-978	95	4	,	,	PUNCT
fens-978	95	5	hco3	hco3	NOUN
fens-978	95	6	-	-	PUNCT
fens-978	95	7	,	,	PUNCT
fens-978	95	8	k+	k+	NOUN
fens-978	95	9	,	,	PUNCT
fens-978	95	10	na+	na+	NOUN
fens-978	95	11	,	,	PUNCT
fens-978	95	12	mg2	mg2	PROPN
fens-978	95	13	+	+	PROPN
fens-978	95	14	,	,	PUNCT
fens-978	95	15	th	th	X
fens-978	95	16	,	,	PUNCT
fens-978	95	17	tds	tds	PROPN
fens-978	95	18	,	,	PUNCT
fens-978	95	19	po4	po4	PROPN
fens-978	95	20	3-	3-	PROPN
fens-978	95	21	,	,	PUNCT
fens-978	95	22	so4	so4	PROPN
fens-978	95	23	2-	2-	PROPN
fens-978	95	24	,	,	PUNCT
fens-978	95	25	no2	no2	NOUN
fens-978	95	26	-	-	PUNCT
fens-978	95	27	,	,	PUNCT
fens-978	95	28	no3	no3	PROPN
fens-978	95	29	-	-	PUNCT
fens-978	95	30	,	,	PUNCT
fens-978	95	31	cl	cl	NOUN
fens-978	95	32	,	,	PUNCT
fens-978	95	33	and	and	CCONJ
fens-978	95	34	ca2	ca2	PROPN
fens-978	95	35	+	+	PROPN
fens-978	95	36	were	be	AUX
fens-978	95	37	analyzed	analyze	VERB
fens-978	95	38	using	use	VERB
fens-978	95	39	the	the	DET
fens-978	95	40	pearson	pearson	NOUN
fens-978	95	41	correlation	correlation	NOUN
fens-978	95	42	matrix	matrix	NOUN
fens-978	95	43	to	to	PART
fens-978	95	44	understand	understand	VERB
fens-978	95	45	the	the	DET
fens-978	95	46	relationship	relationship	NOUN
fens-978	95	47	between	between	ADP
fens-978	95	48	them	they	PRON
fens-978	95	49	and	and	CCONJ
fens-978	95	50	the	the	DET
fens-978	95	51	output	output	NOUN
fens-978	95	52	parameters	parameter	NOUN
fens-978	95	53	(	(	PUNCT
fens-978	95	54	ec	ec	PROPN
fens-978	95	55	and	and	CCONJ
fens-978	95	56	sa	sa	PROPN
fens-978	95	57	.	.	PUNCT
fens-978	96	1	those	those	PRON
fens-978	96	2	with	with	ADP
fens-978	96	3	a	a	DET
fens-978	96	4	high	high	ADJ
fens-978	96	5	association	association	NOUN
fens-978	96	6	with	with	ADP
fens-978	96	7	(	(	PUNCT
fens-978	96	8	sar	sar	PROPN
fens-978	96	9	and	and	CCONJ
fens-978	96	10	ec	ec	PROPN
fens-978	96	11	)	)	PUNCT
fens-978	96	12	were	be	AUX
fens-978	96	13	chosen	choose	VERB
fens-978	96	14	as	as	ADP
fens-978	96	15	input	input	NOUN
fens-978	96	16	parameters	parameter	NOUN
fens-978	96	17	.	.	PUNCT
fens-978	97	1	table	table	NOUN
fens-978	97	2	2	2	NUM
fens-978	97	3	pearson	pearson	NOUN
fens-978	97	4	correlation	correlation	NOUN
fens-978	97	5	matrix	matrix	NOUN
fens-978	97	6	between	between	ADP
fens-978	97	7	parameters	parameter	NOUN
fens-978	97	8	4.2	4.2	NUM
fens-978	97	9	training	training	NOUN
fens-978	97	10	of	of	ADP
fens-978	97	11	the	the	DET
fens-978	97	12	back	back	ADJ
fens-978	97	13	propagation	propagation	NOUN
fens-978	97	14	neural	neural	ADJ
fens-978	97	15	networks	network	NOUN
fens-978	97	16	learning	learn	VERB
fens-978	97	17	algorithm	algorithm	NOUN
fens-978	97	18	.	.	PUNCT
fens-978	98	1	a	a	DET
fens-978	98	2	trained	train	VERB
fens-978	98	3	model	model	NOUN
fens-978	98	4	can	can	AUX
fens-978	98	5	be	be	AUX
fens-978	98	6	assessed	assess	VERB
fens-978	98	7	by	by	ADP
fens-978	98	8	comparing	compare	VERB
fens-978	98	9	its	its	PRON
fens-978	98	10	predicted	predict	VERB
fens-978	98	11	parameters	parameter	NOUN
fens-978	98	12	to	to	ADP
fens-978	98	13	the	the	DET
fens-978	98	14	measured	measured	ADJ
fens-978	98	15	parameters	parameter	NOUN
fens-978	98	16	in	in	ADP
fens-978	98	17	the	the	DET
fens-978	98	18	overfitting	overfitte	VERB
fens-978	98	19	test	test	NOUN
fens-978	98	20	dataset	dataset	VERB
fens-978	98	21	.	.	PUNCT
fens-978	99	1	various	various	ADJ
fens-978	99	2	criteria	criterion	NOUN
fens-978	99	3	were	be	AUX
fens-978	99	4	adopted	adopt	VERB
fens-978	99	5	for	for	ADP
fens-978	99	6	evaluating	evaluate	VERB
fens-978	99	7	the	the	DET
fens-978	99	8	models	model	NOUN
fens-978	99	9	developed	develop	VERB
fens-978	99	10	,	,	PUNCT
fens-978	99	11	in	in	ADP
fens-978	99	12	which	which	PRON
fens-978	99	13	model	model	NOUN
fens-978	99	14	performance	performance	NOUN
fens-978	99	15	was	be	AUX
fens-978	99	16	assessed	assess	VERB
fens-978	99	17	using	use	VERB
fens-978	99	18	respected	respect	VERB
fens-978	99	19	statistical	statistical	ADJ
fens-978	99	20	error	error	NOUN
fens-978	99	21	measures	measure	NOUN
fens-978	99	22	,	,	PUNCT
fens-978	99	23	the	the	DET
fens-978	99	24	root	root	NOUN
fens-978	99	25	mean	mean	NOUN
fens-978	99	26	square	square	NOUN
fens-978	99	27	is	be	AUX
fens-978	99	28	d	d	NOUN
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fens-978	99	30	(	(	PUNCT
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fens-978	99	34	and	and	CCONJ
fens-978	99	35	the	the	DET
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fens-978	99	39	(	(	PUNCT
fens-978	99	40	r	r	NOUN
fens-978	99	41	)	)	PUNCT
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fens-978	100	11	the	the	DET
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fens-978	100	13	and	and	CCONJ
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fens-978	101	2	𝑅𝑀𝑆𝐸	𝑅𝑀𝑆𝐸	NOUN
fens-978	101	3	=	=	PUNCT
fens-978	102	1	√	√	ADP
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fens-978	103	1	[	[	X
fens-978	103	2	𝑦(𝑖	𝑦(𝑖	NOUN
fens-978	103	3	)	)	PUNCT
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fens-978	103	5	𝑧(𝑖)]2𝑛	𝑧(𝑖)]2𝑛	VERB
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fens-978	103	9	3	3	X
fens-978	103	10	)	)	PUNCT
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fens-978	103	12	−	−	NOUN
fens-978	103	13	∑	∑	PUNCT
fens-978	104	1	[	[	X
fens-978	104	2	𝑦(𝑖)−𝑧(𝑖)]2𝑛	𝑦(𝑖)−𝑧(𝑖)]2𝑛	VERB
fens-978	104	3	𝑖=1	𝑖=1	PUNCT
fens-978	104	4	∑	∑	PUNCT
fens-978	104	5	𝑧(𝑖)2𝑛	𝑧(𝑖)2𝑛	ADP
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fens-978	104	7	–	–	PUNCT
fens-978	104	8	∑	∑	PUNCT
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fens-978	104	14	4	4	NUM
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fens-978	104	40	)	)	PUNCT
fens-978	104	41	.	.	PUNCT
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fens-978	107	2	+	+	CCONJ
fens-978	107	3	k+	k+	X
fens-978	107	4	mg2	mg2	PROPN
fens-978	107	5	+	+	PROPN
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fens-978	107	17	1	1	NUM
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fens-978	107	21	1	1	NUM
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fens-978	107	23	+	+	NUM
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fens-978	107	25	0.193	0.193	NUM
fens-978	107	26	1	1	NUM
fens-978	107	27	k+	k+	X
fens-978	107	28	-0.19	-0.19	NOUN
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fens-978	107	31	1	1	NUM
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fens-978	107	38	1	1	NUM
fens-978	107	39	th	th	NOUN
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fens-978	107	45	1	1	NUM
fens-978	107	46	hco3	hco3	PROPN
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fens-978	107	53	1	1	NUM
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fens-978	107	62	1	1	NUM
fens-978	107	63	tds	td	VERB
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fens-978	107	72	1	1	NUM
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fens-978	107	83	1	1	NUM
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fens-978	107	95	1	1	NUM
fens-978	107	96	ec	ec	PROPN
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fens-978	107	108	1	1	NUM
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fens-978	107	122	1	1	NUM
fens-978	107	123	so4	so4	PROPN
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fens-978	107	125	-	-	SYM
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fens-978	107	137	0.482	0.482	NUM
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fens-978	107	139	1	1	NUM
fens-978	107	140	cl	cl	NOUN
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fens-978	108	4	1	1	NUM
fens-978	109	1	no	no	DET
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fens-978	109	10	1	1	NUM
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fens-978	109	13	th	th	X
fens-978	109	14	2	2	NUM
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fens-978	109	37	4	4	NUM
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fens-978	109	49	,	,	PUNCT
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fens-978	109	51	,	,	PUNCT
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fens-978	109	54	&	&	CCONJ
fens-978	109	55	hco3	hco3	PROPN
fens-978	109	56	5	5	NUM
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fens-978	109	58	,	,	PUNCT
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fens-978	109	63	,	,	PUNCT
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fens-978	109	67	na2	na2	PROPN
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fens-978	109	69	food	food	NOUN
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fens-978	109	76	of	of	ADP
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fens-978	109	87	,	,	PUNCT
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fens-978	111	15	cm	cm	NOUN
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fens-978	111	20	677.058	677.058	NUM
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fens-978	111	27	[	[	X
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fens-978	111	30	(	(	PUNCT
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fens-978	112	10	is	be	AUX
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fens-978	112	14	–	–	PUNCT
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fens-978	112	21	agricultural	agricultural	ADJ
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fens-978	113	1	sodium	sodium	NOUN
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fens-978	113	4	(	(	PUNCT
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fens-978	113	7	is	be	AUX
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fens-978	113	10	parameter	parameter	NOUN
fens-978	113	11	for	for	ADP
fens-978	113	12	the	the	DET
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fens-978	113	14	of	of	ADP
fens-978	113	15	the	the	DET
fens-978	113	16	suitability	suitability	NOUN
fens-978	113	17	of	of	ADP
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fens-978	113	19	water	water	NOUN
fens-978	113	20	as	as	SCONJ
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fens-978	113	32	,	,	PUNCT
fens-978	113	33	sar	sar	PROPN
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fens-978	113	35	from	from	ADP
fens-978	113	36	0.524	0.524	NUM
fens-978	113	37	to	to	ADP
fens-978	113	38	1.358	1.358	NUM
fens-978	113	39	with	with	ADP
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fens-978	113	41	average	average	NOUN
fens-978	113	42	of	of	ADP
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fens-978	113	44	,	,	PUNCT
fens-978	113	45	according	accord	VERB
fens-978	113	46	to	to	ADP
fens-978	113	47	[	[	X
fens-978	113	48	9	9	NUM
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fens-978	113	50	(	(	PUNCT
fens-978	113	51	table	table	NOUN
fens-978	113	52	5	5	NUM
fens-978	113	53	)	)	PUNCT
fens-978	113	54	,	,	PUNCT
fens-978	113	55	sodium	sodium	NOUN
fens-978	113	56	absorption	absorption	NOUN
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fens-978	113	58	of	of	ADP
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fens-978	113	61	is	be	AUX
fens-978	113	62	regarded	regard	VERB
fens-978	113	63	as	as	ADP
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fens-978	113	65	–	–	PUNCT
fens-978	113	66	excellent	excellent	ADJ
fens-978	113	67	which	which	PRON
fens-978	113	68	is	be	AUX
fens-978	113	69	suitable	suitable	ADJ
fens-978	113	70	for	for	ADP
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fens-978	114	1	table	table	NOUN
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fens-978	114	4	classes	class	NOUN
fens-978	114	5	of	of	ADP
fens-978	114	6	irrigation	irrigation	NOUN
fens-978	114	7	waters	water	NOUN
fens-978	114	8	laboratory	laboratory	NOUN
fens-978	114	9	staff	staff	NOUN
fens-978	114	10	parameters	parameter	NOUN
fens-978	114	11	mean	mean	VERB
fens-978	114	12	standard	standard	ADJ
fens-978	114	13	deviation	deviation	NOUN
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fens-978	114	15	kurtosis	kurtosis	NOUN
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fens-978	114	17	minimum	minimum	ADJ
fens-978	114	18	maximum	maximum	ADJ
fens-978	114	19	ph	ph	ADJ
fens-978	114	20	7.786	7.786	NUM
fens-978	114	21	0.218	0.218	NUM
fens-978	114	22	0.047	0.047	NUM
fens-978	114	23	0.621	0.621	NUM
fens-978	114	24	0.159	0.159	NUM
fens-978	114	25	7.3	7.3	NUM
fens-978	114	26	8.3	8.3	NUM
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fens-978	114	31	149.201	149.201	NUM
fens-978	114	32	10.006	10.006	NUM
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fens-978	114	34	10.3	10.3	NUM
fens-978	114	35	89.9	89.9	NUM
fens-978	114	36	na2	na2	NOUN
fens-978	114	37	+	+	CCONJ
fens-978	114	38	45.882	45.882	NUM
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fens-978	114	43	20	20	NUM
fens-978	114	44	58	58	NUM
fens-978	114	45	k+	k+	NOUN
fens-978	114	46	2.961	2.961	NUM
fens-978	114	47	3.032	3.032	NUM
fens-978	114	48	9.198	9.198	NUM
fens-978	114	49	39.847	39.847	NUM
fens-978	114	50	5.988	5.988	NUM
fens-978	114	51	1	1	NUM
fens-978	114	52	23	23	NUM
fens-978	114	53	mg2	mg2	NUM
fens-978	114	54	+	+	PROPN
fens-978	114	55	17.039	17.039	NUM
fens-978	114	56	5.953	5.953	NUM
fens-978	114	57	35.438	35.438	NUM
fens-978	114	58	24.46	24.46	NUM
fens-978	114	59	3.881	3.881	NUM
fens-978	114	60	3	3	NUM
fens-978	114	61	52	52	NUM
fens-978	114	62	th	th	NUM
fens-978	114	63	472.619	472.619	NUM
fens-978	114	64	33.816	33.816	NUM
fens-978	114	65	1143.55	1143.55	NUM
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fens-978	114	67	-0.122	-0.122	NUM
fens-978	114	68	372.2	372.2	NUM
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fens-978	114	70	hco3	hco3	PROPN
fens-978	114	71	146.664	146.664	NUM
fens-978	114	72	20.098	20.098	NUM
fens-978	114	73	403.938	403.938	NUM
fens-978	114	74	0.603	0.603	NUM
fens-978	114	75	-0.66	-0.66	NUM
fens-978	114	76	91.5	91.5	NUM
fens-978	114	77	184.2	184.2	NUM
fens-978	115	1	po4	po4	PROPN
fens-978	115	2	30.074	30.074	NUM
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fens-978	115	7	0	0	NUM
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fens-978	115	9	tds	td	VERB
fens-978	115	10	472.619	472.619	NUM
fens-978	115	11	33.816	33.816	NUM
fens-978	115	12	1143.55	1143.55	NUM
fens-978	115	13	1.126	1.126	NUM
fens-978	115	14	-0.122	-0.122	NUM
fens-978	115	15	372.2	372.2	NUM
fens-978	115	16	562.4	562.4	NUM
fens-978	115	17	no3	no3	NOUN
fens-978	115	18	1.759	1.759	NUM
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fens-978	115	20	3.071	3.071	NUM
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fens-978	115	23	0	0	NUM
fens-978	115	24	8	8	NUM
fens-978	115	25	no2	no2	NOUN
fens-978	115	26	0.062	0.062	NUM
fens-978	115	27	0.074	0.074	NUM
fens-978	115	28	0.005	0.005	NUM
fens-978	115	29	5.253	5.253	NUM
fens-978	115	30	2.099	2.099	NUM
fens-978	115	31	0	0	NUM
fens-978	115	32	0.37	0.37	NUM
fens-978	115	33	ec	ec	PROPN
fens-978	115	34	677.058	677.058	NUM
fens-978	115	35	41.438	41.438	NUM
fens-978	115	36	1717.18	1717.18	NUM
fens-978	115	37	0.635	0.635	NUM
fens-978	115	38	-0.989	-0.989	PUNCT
fens-978	115	39	560	560	NUM
fens-978	115	40	730	730	NUM
fens-978	115	41	sar	sar	NOUN
fens-978	115	42	0.981	0.981	NUM
fens-978	115	43	0.158	0.158	NUM
fens-978	115	44	0.025	0.025	NUM
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fens-978	115	47	0.524	0.524	NUM
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fens-978	115	49	so4	so4	PROPN
fens-978	115	50	299.96	299.96	NUM
fens-978	115	51	19.544	19.544	NUM
fens-978	115	52	381.998	381.998	NUM
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fens-978	115	55	70	70	NUM
fens-978	115	56	166	166	NUM
fens-978	115	57	cl	cl	NOUN
fens-978	115	58	85.843	85.843	NUM
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fens-978	115	60	103.454	103.454	NUM
fens-978	115	61	0.409	0.409	NUM
fens-978	115	62	0.161	0.161	NUM
fens-978	115	63	65	65	NUM
fens-978	115	64	115	115	NUM
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fens-978	115	68	µs	µs	NOUN
fens-978	115	69	/	/	SYM
fens-978	115	70	cm	cm	NOUN
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fens-978	115	73	class	class	NOUN
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fens-978	115	81	l	l	NOUN
fens-978	115	82	)	)	PUNCT
fens-978	115	83	ussl	ussl	ADJ
fens-978	115	84	class	class	NOUN
fens-978	115	85	<	<	PROPN
fens-978	115	86	250	250	NUM
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fens-978	115	88	excellent	excellent	ADJ
fens-978	115	89	<	<	X
fens-978	115	90	10	10	NUM
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fens-978	115	92	250	250	NUM
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fens-978	115	94	750	750	NUM
fens-978	115	95	c2	c2	PROPN
fens-978	115	96	good	good	ADJ
fens-978	115	97	10	10	NUM
fens-978	115	98	-	-	SYM
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fens-978	115	101	750	750	NUM
fens-978	115	102	–	–	PUNCT
fens-978	115	103	2250	2250	NUM
fens-978	115	104	c3	c3	NOUN
fens-978	115	105	satisfacto	satisfacto	PROPN
fens-978	115	106	ry	ry	PROPN
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fens-978	115	108	-	-	SYM
fens-978	115	109	26	26	NUM
fens-978	115	110	s3	s3	PROPN
fens-978	115	111	>	>	X
fens-978	115	112	2250	2250	NUM
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fens-978	115	115	>	>	SYM
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fens-978	115	117	s4	s4	PROPN
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fens-978	115	119	and	and	CCONJ
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fens-978	115	125	of	of	ADP
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fens-978	115	127	engineering	engineering	NOUN
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fens-978	115	138	3	3	NUM
fens-978	115	139	–	–	PUNCT
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fens-978	115	147	application	application	NOUN
fens-978	115	148	to	to	PART
fens-978	115	149	predict	predict	VERB
fens-978	115	150	irrigation	irrigation	NOUN
fens-978	115	151	water	water	NOUN
fens-978	115	152	quality	quality	PROPN
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fens-978	115	161	-	-	PUNCT
fens-978	115	162	east	east	NOUN
fens-978	115	163	algeria	algeria	PROPN
fens-978	115	164	,	,	PUNCT
fens-978	115	165	food	food	NOUN
fens-978	115	166	and	and	CCONJ
fens-978	115	167	environment	environment	NOUN
fens-978	115	168	safety	safety	NOUN
fens-978	115	169	,	,	PUNCT
fens-978	115	170	volume	volume	NOUN
fens-978	115	171	xxii	xxii	PROPN
fens-978	115	172	,	,	PUNCT
fens-978	115	173	issue	issue	NOUN
fens-978	115	174	3	3	NUM
fens-978	115	175	–	–	PUNCT
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fens-978	115	182	198	198	NUM
fens-978	115	183	194	194	NUM
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fens-978	115	192	sar	sar	PROPN
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fens-978	115	196	to	to	ADP
fens-978	115	197	2022	2022	NUM
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fens-978	116	1	5	5	NUM
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fens-978	116	5	electrical	electrical	ADJ
fens-978	116	6	conductivity	conductivity	NOUN
fens-978	116	7	ec	ec	PROPN
fens-978	116	8	from	from	ADP
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fens-978	116	10	to	to	ADP
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fens-978	116	12	4.3	4.3	NUM
fens-978	116	13	analysis	analysis	NOUN
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fens-978	117	13	and	and	CCONJ
fens-978	117	14	tested	test	VERB
fens-978	117	15	so	so	SCONJ
fens-978	117	16	that	that	SCONJ
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fens-978	117	22	in	in	ADP
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fens-978	117	24	hidden	hide	VERB
fens-978	117	25	layer	layer	NOUN
fens-978	117	26	and	and	CCONJ
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fens-978	117	28	functions	function	NOUN
fens-978	117	29	can	can	AUX
fens-978	117	30	be	be	AUX
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fens-978	118	1	setting	set	VERB
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fens-978	118	4	is	be	AUX
fens-978	118	5	the	the	DET
fens-978	118	6	crucial	crucial	ADJ
fens-978	118	7	phase	phase	NOUN
fens-978	118	8	in	in	ADP
fens-978	118	9	ann	ann	PROPN
fens-978	118	10	modelling	modelling	NOUN
fens-978	118	11	;	;	PUNCT
fens-978	118	12	many	many	ADJ
fens-978	118	13	nodes	node	NOUN
fens-978	118	14	may	may	AUX
fens-978	118	15	lead	lead	VERB
fens-978	118	16	to	to	ADP
fens-978	118	17	overfitting	overfitte	VERB
fens-978	118	18	,	,	PUNCT
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fens-978	118	20	a	a	DET
fens-978	118	21	small	small	ADJ
fens-978	118	22	number	number	NOUN
fens-978	118	23	might	might	AUX
fens-978	118	24	need	need	VERB
fens-978	118	25	to	to	PART
fens-978	118	26	capture	capture	VERB
fens-978	118	27	more	more	ADJ
fens-978	118	28	information	information	NOUN
fens-978	118	29	.	.	PUNCT
fens-978	119	1	two	two	NUM
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fens-978	119	4	were	be	AUX
fens-978	119	5	designed	design	VERB
fens-978	119	6	for	for	ADP
fens-978	119	7	the	the	DET
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fens-978	119	9	to	to	PART
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fens-978	119	11	the	the	DET
fens-978	119	12	oued	oued	PROPN
fens-978	119	13	-	-	PUNCT
fens-978	119	14	hammam	hammam	PROPN
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fens-978	119	16	.	.	PUNCT
fens-978	120	1	the	the	DET
fens-978	120	2	model	model	NOUN
fens-978	120	3	was	be	AUX
fens-978	120	4	trained	train	VERB
fens-978	120	5	and	and	CCONJ
fens-978	120	6	then	then	ADV
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fens-978	120	8	,	,	PUNCT
fens-978	120	9	and	and	CCONJ
fens-978	120	10	the	the	DET
fens-978	120	11	best	good	ADJ
fens-978	120	12	model	model	NOUN
fens-978	120	13	was	be	AUX
fens-978	120	14	selected	select	VERB
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fens-978	120	16	the	the	DET
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fens-978	120	18	of	of	ADP
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fens-978	120	22	(	(	PUNCT
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fens-978	120	24	)	)	PUNCT
fens-978	120	25	and	and	CCONJ
fens-978	120	26	the	the	DET
fens-978	120	27	minimum	minimum	ADJ
fens-978	120	28	root	root	NOUN
fens-978	120	29	mean	mean	VERB
fens-978	120	30	square	square	ADJ
fens-978	120	31	error	error	NOUN
fens-978	120	32	(	(	PUNCT
fens-978	120	33	rmse	rmse	NOUN
fens-978	120	34	)	)	PUNCT
fens-978	120	35	.	.	PUNCT
fens-978	121	1	the	the	DET
fens-978	121	2	selected	select	VERB
fens-978	121	3	ann	ann	PROPN
fens-978	121	4	for	for	ADP
fens-978	121	5	the	the	DET
fens-978	121	6	sar	sar	PROPN
fens-978	121	7	model	model	PROPN
fens-978	121	8	comprises	comprise	VERB
fens-978	121	9	one	one	NUM
fens-978	121	10	input	input	NOUN
fens-978	121	11	layer	layer	NOUN
fens-978	121	12	with	with	ADP
fens-978	121	13	four	four	NUM
fens-978	121	14	input	input	NOUN
fens-978	121	15	water	water	NOUN
fens-978	121	16	quality	quality	NOUN
fens-978	121	17	parameters	parameter	NOUN
fens-978	121	18	,	,	PUNCT
fens-978	121	19	two	two	NUM
fens-978	121	20	hidden	hidden	ADJ
fens-978	121	21	layers	layer	NOUN
fens-978	121	22	with	with	ADP
fens-978	121	23	ten	ten	NUM
fens-978	121	24	nodes	node	NOUN
fens-978	121	25	,	,	PUNCT
fens-978	121	26	and	and	CCONJ
fens-978	121	27	one	one	NUM
fens-978	121	28	output	output	NOUN
fens-978	121	29	layer	layer	NOUN
fens-978	121	30	with	with	ADP
fens-978	121	31	one	one	NUM
fens-978	121	32	output	output	NOUN
fens-978	121	33	parameter	parameter	NOUN
fens-978	121	34	.	.	PUNCT
fens-978	122	1	in	in	ADP
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fens-978	122	3	,	,	PUNCT
fens-978	122	4	the	the	DET
fens-978	122	5	ec	ec	PROPN
fens-978	122	6	model	model	NOUN
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fens-978	122	8	one	one	NUM
fens-978	122	9	input	input	NOUN
fens-978	122	10	layer	layer	NOUN
fens-978	122	11	with	with	ADP
fens-978	122	12	five	five	NUM
fens-978	122	13	input	input	NOUN
fens-978	122	14	water	water	NOUN
fens-978	122	15	quality	quality	NOUN
fens-978	122	16	parameters	parameter	NOUN
fens-978	122	17	,	,	PUNCT
fens-978	122	18	one	one	NUM
fens-978	122	19	hidden	hide	VERB
fens-978	122	20	layer	layer	NOUN
fens-978	122	21	with	with	ADP
fens-978	122	22	twelve	twelve	NUM
fens-978	122	23	nodes	node	NOUN
fens-978	122	24	and	and	CCONJ
fens-978	122	25	one	one	NUM
fens-978	122	26	output	output	NOUN
fens-978	122	27	layer	layer	NOUN
fens-978	122	28	with	with	ADP
fens-978	122	29	one	one	NUM
fens-978	122	30	output	output	NOUN
fens-978	122	31	parameter	parameter	NOUN
fens-978	122	32	.	.	PUNCT
fens-978	123	1	both	both	DET
fens-978	123	2	ann	ann	PROPN
fens-978	123	3	models	model	NOUN
fens-978	123	4	(	(	PUNCT
fens-978	123	5	sar	sar	NOUN
fens-978	123	6	and	and	CCONJ
fens-978	123	7	ec	ec	PROPN
fens-978	123	8	)	)	PUNCT
fens-978	123	9	were	be	AUX
fens-978	123	10	trained	train	VERB
fens-978	123	11	using	use	VERB
fens-978	123	12	the	the	DET
fens-978	123	13	back	back	ADJ
fens-978	123	14	propagation	propagation	NOUN
fens-978	123	15	artificial	artificial	ADJ
fens-978	123	16	neural	neural	ADJ
fens-978	123	17	learning	learn	VERB
fens-978	123	18	algorithm	algorithm	NOUN
fens-978	123	19	(	(	PUNCT
fens-978	123	20	bp	bp	PROPN
fens-978	123	21	)	)	PUNCT
fens-978	123	22	.	.	PUNCT
fens-978	124	1	root	root	NOUN
fens-978	124	2	mean	mean	VERB
fens-978	124	3	square	square	ADJ
fens-978	124	4	error	error	NOUN
fens-978	124	5	(	(	PUNCT
fens-978	124	6	rmse	rmse	NOUN
fens-978	124	7	)	)	PUNCT
fens-978	124	8	and	and	CCONJ
fens-978	124	9	correlation	correlation	NOUN
fens-978	124	10	coefficient	coefficient	NOUN
fens-978	124	11	(	(	PUNCT
fens-978	124	12	r	r	NOUN
fens-978	124	13	)	)	PUNCT
fens-978	124	14	as	as	SCONJ
fens-978	124	15	computed	compute	VERB
fens-978	124	16	for	for	ADP
fens-978	124	17	the	the	DET
fens-978	124	18	training	training	NOUN
fens-978	124	19	and	and	CCONJ
fens-978	124	20	validation	validation	NOUN
fens-978	124	21	dataset	dataset	NOUN
fens-978	124	22	for	for	ADP
fens-978	124	23	the	the	DET
fens-978	124	24	two	two	NUM
fens-978	124	25	models	model	NOUN
fens-978	124	26	(	(	PUNCT
fens-978	124	27	sar	sar	NOUN
fens-978	124	28	and	and	CCONJ
fens-978	124	29	ec	ec	PROPN
fens-978	124	30	)	)	PUNCT
fens-978	124	31	are	be	AUX
fens-978	124	32	shown	show	VERB
fens-978	124	33	in	in	ADP
fens-978	124	34	0	0	NUM
fens-978	124	35	0,5	0,5	NUM
fens-978	124	36	1	1	NUM
fens-978	124	37	1,5	1,5	NUM
fens-978	124	38	05.01.2010	05.01.2010	NOUN
fens-978	124	39	05.01.2014	05.01.2014	PROPN
fens-978	124	40	05.01.2018	05.01.2018	NUM
fens-978	124	41	05.01.2022	05.01.2022	X
fens-978	124	42	actual	actual	ADJ
fens-978	124	43	sar	sar	NOUN
fens-978	124	44	(	(	PUNCT
fens-978	124	45	meq	meq	PROPN
fens-978	124	46	/	/	SYM
fens-978	124	47	l	l	NOUN
fens-978	124	48	)	)	PUNCT
fens-978	124	49	actual	actual	ADJ
fens-978	124	50	sar	sar	NOUN
fens-978	124	51	(	(	PUNCT
fens-978	124	52	meq	meq	PROPN
fens-978	124	53	/	/	SYM
fens-978	124	54	l	l	NOUN
fens-978	124	55	)	)	PUNCT
fens-978	124	56	0	0	NUM
fens-978	124	57	200	200	NUM
fens-978	124	58	400	400	NUM
fens-978	124	59	600	600	NUM
fens-978	124	60	800	800	NUM
fens-978	124	61	actual	actual	ADJ
fens-978	124	62	ec	ec	NOUN
fens-978	124	63	(	(	PUNCT
fens-978	124	64	µs	µs	NOUN
fens-978	124	65	/	/	SYM
fens-978	124	66	cm	cm	NOUN
fens-978	124	67	)	)	PUNCT
fens-978	124	68	actual	actual	ADJ
fens-978	124	69	ec	ec	PROPN
fens-978	124	70	(	(	PUNCT
fens-978	124	71	µs	µs	NOUN
fens-978	124	72	/	/	SYM
fens-978	124	73	cm	cm	NOUN
fens-978	124	74	)	)	PUNCT
fens-978	124	75	food	food	NOUN
fens-978	124	76	and	and	CCONJ
fens-978	124	77	environment	environment	NOUN
fens-978	124	78	safety	safety	NOUN
fens-978	124	79	journal	journal	NOUN
fens-978	124	80	of	of	ADP
fens-978	124	81	faculty	faculty	NOUN
fens-978	124	82	of	of	ADP
fens-978	124	83	food	food	NOUN
fens-978	124	84	engineering	engineering	NOUN
fens-978	124	85	,	,	PUNCT
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fens-978	124	87	cel	cel	PROPN
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fens-978	124	90	suceava	suceava	PROPN
fens-978	124	91	volume	volume	PROPN
fens-978	124	92	xxii	xxii	PROPN
fens-978	124	93	,	,	PUNCT
fens-978	124	94	issue	issue	NOUN
fens-978	124	95	3	3	NUM
fens-978	124	96	–	–	PUNCT
fens-978	124	97	2023	2023	NUM
fens-978	124	98	oswald	oswald	PROPN
fens-978	124	99	peter	peter	PROPN
fens-978	124	100	bomani	bomani	PROPN
fens-978	124	101	,	,	PUNCT
fens-978	124	102	soft	soft	ADJ
fens-978	124	103	computing	computing	NOUN
fens-978	124	104	application	application	NOUN
fens-978	124	105	to	to	PART
fens-978	124	106	predict	predict	VERB
fens-978	124	107	irrigation	irrigation	NOUN
fens-978	124	108	water	water	NOUN
fens-978	124	109	quality	quality	PROPN
fens-978	124	110	index	index	NOUN
fens-978	124	111	,	,	PUNCT
fens-978	124	112	case	case	NOUN
fens-978	124	113	study	study	NOUN
fens-978	124	114	of	of	ADP
fens-978	124	115	oued	oued	PROPN
fens-978	124	116	hammam	hammam	PROPN
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fens-978	124	118	-	-	PUNCT
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fens-978	124	120	algeria	algeria	PROPN
fens-978	124	121	,	,	PUNCT
fens-978	124	122	food	food	NOUN
fens-978	124	123	and	and	CCONJ
fens-978	124	124	environment	environment	NOUN
fens-978	124	125	safety	safety	NOUN
fens-978	124	126	,	,	PUNCT
fens-978	124	127	volume	volume	NOUN
fens-978	124	128	xxii	xxii	PROPN
fens-978	124	129	,	,	PUNCT
fens-978	124	130	issue	issue	NOUN
fens-978	124	131	3	3	NUM
fens-978	124	132	–	–	PUNCT
fens-978	124	133	2023	2023	NUM
fens-978	124	134	,	,	PUNCT
fens-978	124	135	pag	pag	PROPN
fens-978	124	136	.	.	PROPN
fens-978	124	137	188	188	NUM
fens-978	124	138	–	–	SYM
fens-978	124	139	198	198	NUM
fens-978	124	140	195	195	NUM
fens-978	124	141	table	table	NOUN
fens-978	124	142	6	6	NUM
fens-978	124	143	,	,	PUNCT
fens-978	124	144	sar	sar	NOUN
fens-978	124	145	with	with	ADP
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fens-978	124	147	rmse	rmse	NOUN
fens-978	124	148	of	of	ADP
fens-978	124	149	0.036	0.036	NUM
fens-978	124	150	and	and	CCONJ
fens-978	124	151	0.044	0.044	NUM
fens-978	124	152	in	in	ADP
fens-978	124	153	the	the	DET
fens-978	124	154	training	training	NOUN
fens-978	124	155	and	and	CCONJ
fens-978	124	156	validation	validation	NOUN
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fens-978	124	159	,	,	PUNCT
fens-978	124	160	and	and	CCONJ
fens-978	124	161	the	the	DET
fens-978	124	162	respective	respective	ADJ
fens-978	124	163	correlation	correlation	NOUN
fens-978	124	164	coefficient	coefficient	NOUN
fens-978	124	165	of	of	ADP
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fens-978	124	167	for	for	ADP
fens-978	124	168	the	the	DET
fens-978	124	169	training	training	NOUN
fens-978	124	170	phase	phase	NOUN
fens-978	124	171	and	and	CCONJ
fens-978	124	172	0.98	0.98	NUM
fens-978	124	173	for	for	ADP
fens-978	124	174	validation	validation	NOUN
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fens-978	124	176	,	,	PUNCT
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fens-978	124	178	ec	ec	PROPN
fens-978	124	179	with	with	ADP
fens-978	124	180	the	the	DET
fens-978	124	181	rmse	rmse	NOUN
fens-978	124	182	of	of	ADP
fens-978	124	183	110.8	110.8	NUM
fens-978	124	184	and	and	CCONJ
fens-978	124	185	53.1	53.1	NUM
fens-978	124	186	in	in	ADP
fens-978	124	187	the	the	DET
fens-978	124	188	training	training	NOUN
fens-978	124	189	and	and	CCONJ
fens-978	124	190	validation	validation	NOUN
fens-978	124	191	phase	phase	NOUN
fens-978	124	192	respectively	respectively	ADV
fens-978	124	193	,	,	PUNCT
fens-978	124	194	and	and	CCONJ
fens-978	124	195	respective	respective	ADJ
fens-978	124	196	correlation	correlation	NOUN
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fens-978	124	198	of	of	ADP
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fens-978	124	200	for	for	ADP
fens-978	124	201	the	the	DET
fens-978	124	202	training	training	NOUN
fens-978	124	203	phase	phase	NOUN
fens-978	124	204	and	and	CCONJ
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fens-978	124	206	for	for	ADP
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fens-978	124	209	.	.	PUNCT
fens-978	125	1	the	the	DET
fens-978	125	2	correlation	correlation	NOUN
fens-978	125	3	coefficient	coefficient	NOUN
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fens-978	125	5	between	between	ADP
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fens-978	125	7	back	back	ADJ
fens-978	125	8	propagation	propagation	NOUN
fens-978	125	9	artificial	artificial	ADJ
fens-978	125	10	neural	neural	ADJ
fens-978	125	11	learning	learning	NOUN
fens-978	125	12	models	model	NOUN
fens-978	125	13	predicted	predict	VERB
fens-978	125	14	parameters	parameter	NOUN
fens-978	125	15	and	and	CCONJ
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fens-978	125	17	parameters	parameter	NOUN
fens-978	125	18	for	for	ADP
fens-978	125	19	the	the	DET
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fens-978	125	21	absorption	absorption	NOUN
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fens-978	125	23	(	(	PUNCT
fens-978	125	24	sar	sar	PROPN
fens-978	125	25	)	)	PUNCT
fens-978	125	26	showed	show	VERB
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fens-978	125	30	that	that	PRON
fens-978	125	31	of	of	ADP
fens-978	125	32	the	the	DET
fens-978	125	33	electrical	electrical	ADJ
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fens-978	125	35	(	(	PUNCT
fens-978	125	36	ec	ec	PROPN
fens-978	125	37	)	)	PUNCT
fens-978	125	38	model	model	NOUN
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fens-978	126	1	figure	figure	VERB
fens-978	126	2	6	6	NUM
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fens-978	126	6	between	between	ADP
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fens-978	126	8	sar	sar	NOUN
fens-978	126	9	and	and	CCONJ
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fens-978	126	11	sar	sar	NOUN
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fens-978	126	22	the	the	DET
fens-978	126	23	actual	actual	ADJ
fens-978	126	24	ec	ec	PROPN
fens-978	126	25	and	and	CCONJ
fens-978	126	26	the	the	DET
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fens-978	126	28	ec	ec	PROPN
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fens-978	127	1	the	the	DET
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fens-978	127	3	(	(	PUNCT
fens-978	127	4	8	8	NUM
fens-978	127	5	and	and	CCONJ
fens-978	127	6	9	9	NUM
fens-978	127	7	)	)	PUNCT
fens-978	127	8	reveal	reveal	VERB
fens-978	127	9	a	a	DET
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fens-978	127	11	relationship	relationship	NOUN
fens-978	127	12	between	between	ADP
fens-978	127	13	predicted	predict	VERB
fens-978	127	14	and	and	CCONJ
fens-978	127	15	actual	actual	ADJ
fens-978	127	16	parameters	parameter	NOUN
fens-978	127	17	.	.	PUNCT
fens-978	128	1	the	the	DET
fens-978	128	2	results	result	NOUN
fens-978	128	3	indicate	indicate	VERB
fens-978	128	4	the	the	DET
fens-978	128	5	performance	performance	NOUN
fens-978	128	6	of	of	ADP
fens-978	128	7	the	the	DET
fens-978	128	8	artificial	artificial	ADJ
fens-978	128	9	neural	neural	ADJ
fens-978	128	10	network	network	NOUN
fens-978	128	11	in	in	ADP
fens-978	128	12	predicting	predict	VERB
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fens-978	128	15	indicators	indicator	NOUN
fens-978	128	16	(	(	PUNCT
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fens-978	128	19	ec	ec	PROPN
fens-978	128	20	)	)	PUNCT
fens-978	128	21	.	.	PUNCT
fens-978	129	1	the	the	DET
fens-978	129	2	present	present	ADJ
fens-978	129	3	study	study	NOUN
fens-978	129	4	suggests	suggest	VERB
fens-978	129	5	that	that	SCONJ
fens-978	129	6	a	a	DET
fens-978	129	7	back	back	ADJ
fens-978	129	8	propagation	propagation	NOUN
fens-978	129	9	artificial	artificial	ADJ
fens-978	129	10	neural	neural	ADJ
fens-978	129	11	learning	learning	NOUN
fens-978	129	12	algorithm	algorithm	NOUN
fens-978	129	13	can	can	AUX
fens-978	129	14	be	be	AUX
fens-978	129	15	used	use	VERB
fens-978	129	16	to	to	PART
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fens-978	129	18	the	the	DET
fens-978	129	19	sar	sar	NOUN
fens-978	129	20	and	and	CCONJ
fens-978	129	21	ec	ec	PROPN
fens-978	129	22	of	of	ADP
fens-978	129	23	the	the	DET
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fens-978	129	25	-	-	PUNCT
fens-978	129	26	hammam	hammam	PROPN
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fens-978	129	28	for	for	ADP
fens-978	129	29	irrigation	irrigation	NOUN
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fens-978	129	31	,	,	PUNCT
fens-978	129	32	and	and	CCONJ
fens-978	129	33	it	it	PRON
fens-978	129	34	can	can	AUX
fens-978	129	35	be	be	AUX
fens-978	129	36	used	use	VERB
fens-978	129	37	to	to	PART
fens-978	129	38	monitor	monitor	VERB
fens-978	129	39	and	and	CCONJ
fens-978	129	40	control	control	NOUN
fens-978	129	41	watershed	watershe	VERB
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fens-978	130	1	so	so	ADV
fens-978	130	2	,	,	PUNCT
fens-978	130	3	ann	ann	PROPN
fens-978	130	4	has	have	AUX
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fens-978	130	7	as	as	ADP
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fens-978	130	9	in	in	ADP
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fens-978	130	11	water	water	NOUN
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fens-978	130	13	.	.	PUNCT
fens-978	131	1	table	table	NOUN
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fens-978	131	5	back	back	ADJ
fens-978	131	6	propagation	propagation	NOUN
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fens-978	131	9	learning	learn	VERB
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fens-978	131	11	for	for	ADP
fens-978	131	12	modelling	model	VERB
fens-978	131	13	the	the	DET
fens-978	131	14	sar	sar	NOUN
fens-978	131	15	and	and	CCONJ
fens-978	131	16	ec	ec	PROPN
fens-978	131	17	in	in	ADP
fens-978	131	18	the	the	DET
fens-978	131	19	oued	oued	PROPN
fens-978	131	20	-	-	PUNCT
fens-978	131	21	hammam	hammam	PROPN
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fens-978	132	1	fig	fig	NOUN
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fens-978	133	1	6	6	NUM
fens-978	133	2	actual	actual	ADJ
fens-978	133	3	and	and	CCONJ
fens-978	133	4	predicted	predict	VERB
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fens-978	133	8	according	accord	VERB
fens-978	133	9	to	to	ADP
fens-978	133	10	the	the	DET
fens-978	133	11	backpropagation	backpropagation	NOUN
fens-978	133	12	algorithm	algorithm	NOUN
fens-978	133	13	in	in	ADP
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fens-978	133	17	.	.	PUNCT
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fens-978	135	1	1,00	1,00	NUM
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fens-978	135	4	1,60	1,60	NUM
fens-978	135	5	1	1	NUM
fens-978	135	6	3	3	NUM
fens-978	135	7	5	5	NUM
fens-978	135	8	7	7	NUM
fens-978	135	9	9	9	NUM
fens-978	135	10	11	11	NUM
fens-978	135	11	13	13	NUM
fens-978	135	12	15	15	NUM
fens-978	135	13	17	17	NUM
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fens-978	135	16	23	23	NUM
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fens-978	135	21	33	33	NUM
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fens-978	135	23	37	37	NUM
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fens-978	135	25	41	41	NUM
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fens-978	135	27	45	45	NUM
fens-978	135	28	47	47	NUM
fens-978	135	29	49	49	NUM
fens-978	135	30	51	51	NUM
fens-978	135	31	s	s	NOUN
fens-978	135	32	a	a	DET
fens-978	135	33	r	r	NOUN
fens-978	135	34	(	(	PUNCT
fens-978	135	35	m	m	PROPN
fens-978	135	36	e	e	NOUN
fens-978	135	37	q	q	PROPN
fens-978	135	38	/l	/l	PUNCT
fens-978	135	39	)	)	PUNCT
fens-978	135	40	time	time	NOUN
fens-978	135	41	series	series	PROPN
fens-978	135	42	actual	actual	ADJ
fens-978	135	43	sar	sar	PROPN
fens-978	135	44	(	(	PUNCT
fens-978	135	45	meq	meq	PROPN
fens-978	135	46	/	/	SYM
fens-978	135	47	l	l	NOUN
fens-978	135	48	)	)	PUNCT
fens-978	135	49	predicted	predict	VERB
fens-978	135	50	sar	sar	X
fens-978	135	51	(	(	PUNCT
fens-978	135	52	meq	meq	PROPN
fens-978	135	53	/	/	SYM
fens-978	135	54	l	l	NOUN
fens-978	135	55	)	)	PUNCT
fens-978	135	56	model	model	NOUN
fens-978	135	57	annarchitecture	annarchitecture	NOUN
fens-978	135	58	dataset	dataset	NOUN
fens-978	135	59	root	root	NOUN
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fens-978	135	61	square	square	ADJ
fens-978	135	62	error	error	NOUN
fens-978	135	63	(	(	PUNCT
fens-978	135	64	rmse	rmse	NOUN
fens-978	135	65	)	)	PUNCT
fens-978	135	66	r	r	NOUN
fens-978	135	67	sar	sar	NOUN
fens-978	135	68	training	train	VERB
fens-978	135	69	0.036	0.036	NUM
fens-978	135	70	0.9939	0.9939	NUM
fens-978	135	71	4	4	NUM
fens-978	135	72	-	-	SYM
fens-978	135	73	10	10	NUM
fens-978	135	74	-	-	SYM
fens-978	135	75	1	1	NUM
fens-978	135	76	validation	validation	NOUN
fens-978	135	77	0.044	0.044	NUM
fens-978	135	78	0.9871	0.9871	NUM
fens-978	135	79	training	train	VERB
fens-978	135	80	110.8	110.8	NUM
fens-978	135	81	0.9693	0.9693	NUM
fens-978	135	82	ec	ec	PROPN
fens-978	135	83	5	5	NUM
fens-978	135	84	-	-	SYM
fens-978	135	85	12	12	NUM
fens-978	135	86	-	-	SYM
fens-978	135	87	1	1	NUM
fens-978	135	88	validation	validation	NOUN
fens-978	135	89	53.1	53.1	NUM
fens-978	135	90	0.9827	0.9827	NUM
fens-978	135	91	food	food	NOUN
fens-978	135	92	and	and	CCONJ
fens-978	135	93	environment	environment	NOUN
fens-978	135	94	safety	safety	NOUN
fens-978	135	95	journal	journal	NOUN
fens-978	135	96	of	of	ADP
fens-978	135	97	faculty	faculty	NOUN
fens-978	135	98	of	of	ADP
fens-978	135	99	food	food	NOUN
fens-978	135	100	engineering	engineering	NOUN
fens-978	135	101	,	,	PUNCT
fens-978	135	102	ştefan	ştefan	PROPN
fens-978	135	103	cel	cel	PROPN
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fens-978	135	105	university	university	PROPN
fens-978	135	106	suceava	suceava	PROPN
fens-978	135	107	volume	volume	PROPN
fens-978	135	108	xxii	xxii	PROPN
fens-978	135	109	,	,	PUNCT
fens-978	135	110	issue	issue	NOUN
fens-978	135	111	3	3	NUM
fens-978	135	112	–	–	PUNCT
fens-978	135	113	2023	2023	NUM
fens-978	135	114	oswald	oswald	PROPN
fens-978	135	115	peter	peter	PROPN
fens-978	135	116	bomani	bomani	PROPN
fens-978	135	117	,	,	PUNCT
fens-978	135	118	soft	soft	ADJ
fens-978	135	119	computing	computing	NOUN
fens-978	135	120	application	application	NOUN
fens-978	135	121	to	to	PART
fens-978	135	122	predict	predict	VERB
fens-978	135	123	irrigation	irrigation	NOUN
fens-978	135	124	water	water	NOUN
fens-978	135	125	quality	quality	PROPN
fens-978	135	126	index	index	NOUN
fens-978	135	127	,	,	PUNCT
fens-978	135	128	case	case	NOUN
fens-978	135	129	study	study	NOUN
fens-978	135	130	of	of	ADP
fens-978	135	131	oued	oued	PROPN
fens-978	135	132	hammam	hammam	PROPN
fens-978	135	133	north	north	PROPN
fens-978	135	134	-	-	PUNCT
fens-978	135	135	east	east	NOUN
fens-978	135	136	algeria	algeria	PROPN
fens-978	135	137	,	,	PUNCT
fens-978	135	138	food	food	NOUN
fens-978	135	139	and	and	CCONJ
fens-978	135	140	environment	environment	NOUN
fens-978	135	141	safety	safety	NOUN
fens-978	135	142	,	,	PUNCT
fens-978	135	143	volume	volume	NOUN
fens-978	135	144	xxii	xxii	PROPN
fens-978	135	145	,	,	PUNCT
fens-978	135	146	issue	issue	NOUN
fens-978	135	147	3	3	NUM
fens-978	135	148	–	–	PUNCT
fens-978	135	149	2023	2023	NUM
fens-978	135	150	,	,	PUNCT
fens-978	135	151	pag	pag	PROPN
fens-978	135	152	.	.	PROPN
fens-978	135	153	188	188	NUM
fens-978	135	154	–	–	SYM
fens-978	135	155	198	198	NUM
fens-978	135	156	196	196	NUM
fens-978	135	157	fig	fig	NOUN
fens-978	135	158	.	.	PUNCT
fens-978	136	1	7	7	NUM
fens-978	136	2	actual	actual	ADJ
fens-978	136	3	and	and	CCONJ
fens-978	136	4	predicted	predict	VERB
fens-978	136	5	electrical	electrical	ADJ
fens-978	136	6	conductivity	conductivity	NOUN
fens-978	136	7	“	"	PUNCT
fens-978	136	8	ec	ec	PROPN
fens-978	136	9	”	"	PUNCT
fens-978	137	1	according	accord	VERB
fens-978	137	2	to	to	ADP
fens-978	137	3	the	the	DET
fens-978	137	4	backpropagation	backpropagation	NOUN
fens-978	137	5	algorithm	algorithm	NOUN
fens-978	137	6	in	in	ADP
fens-978	137	7	the	the	DET
fens-978	137	8	validation	validation	NOUN
fens-978	137	9	phase	phase	NOUN
fens-978	137	10	.	.	PUNCT
fens-978	138	1	fig	fig	NOUN
fens-978	138	2	.	.	PUNCT
fens-978	139	1	8	8	NUM
fens-978	139	2	actual	actual	ADJ
fens-978	139	3	versus	versus	ADP
fens-978	139	4	predicted	predict	VERB
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fens-978	139	8	(	(	PUNCT
fens-978	139	9	sar	sar	PROPN
fens-978	139	10	)	)	PUNCT
fens-978	139	11	by	by	ADP
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fens-978	139	13	algorithm	algorithm	NOUN
fens-978	139	14	for	for	ADP
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fens-978	139	16	and	and	CCONJ
fens-978	139	17	validation	validation	NOUN
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fens-978	139	19	.	.	PUNCT
fens-978	140	1	fig	fig	NOUN
fens-978	140	2	.	.	PUNCT
fens-978	141	1	9	9	NUM
fens-978	141	2	actual	actual	ADJ
fens-978	141	3	versus	versus	ADP
fens-978	141	4	predicted	predict	VERB
fens-978	141	5	electrical	electrical	ADJ
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fens-978	141	7	(	(	PUNCT
fens-978	141	8	ec	ec	NOUN
fens-978	141	9	)	)	PUNCT
fens-978	141	10	using	use	VERB
fens-978	141	11	back	back	ADP
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fens-978	141	13	algorithm	algorithm	NOUN
fens-978	141	14	for	for	ADP
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fens-978	141	16	and	and	CCONJ
fens-978	141	17	validation	validation	NOUN
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fens-978	141	19	.	.	PUNCT
fens-978	142	1	530	530	NUM
fens-978	142	2	580	580	NUM
fens-978	142	3	630	630	NUM
fens-978	142	4	680	680	NUM
fens-978	142	5	730	730	NUM
fens-978	142	6	1	1	NUM
fens-978	142	7	3	3	NUM
fens-978	142	8	5	5	NUM
fens-978	142	9	7	7	NUM
fens-978	142	10	9	9	NUM
fens-978	142	11	11	11	NUM
fens-978	142	12	13	13	NUM
fens-978	142	13	15	15	NUM
fens-978	142	14	17	17	NUM
fens-978	142	15	19	19	NUM
fens-978	142	16	21	21	NUM
fens-978	142	17	23	23	NUM
fens-978	142	18	25	25	NUM
fens-978	142	19	27	27	NUM
fens-978	142	20	29	29	NUM
fens-978	142	21	31	31	NUM
fens-978	142	22	33	33	NUM
fens-978	142	23	35	35	NUM
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fens-978	142	25	39	39	NUM
fens-978	142	26	41	41	NUM
fens-978	142	27	43	43	NUM
fens-978	142	28	45	45	NUM
fens-978	142	29	47	47	NUM
fens-978	142	30	49	49	NUM
fens-978	142	31	51	51	NUM
fens-978	142	32	e	e	NOUN
fens-978	142	33	c	c	X
fens-978	142	34	(	(	PUNCT
fens-978	142	35	µ	µ	X
fens-978	142	36	s/	s/	NOUN
fens-978	142	37	c	c	NOUN
fens-978	142	38	m	m	NOUN
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fens-978	142	44	(	(	PUNCT
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fens-978	142	46	/	/	SYM
fens-978	142	47	cm	cm	NOUN
fens-978	142	48	)	)	PUNCT
fens-978	142	49	predicted	predict	VERB
fens-978	142	50	ec	ec	PROPN
fens-978	142	51	(	(	PUNCT
fens-978	142	52	µs	µs	NOUN
fens-978	142	53	/	/	SYM
fens-978	142	54	cm	cm	NOUN
fens-978	142	55	)	)	PUNCT
fens-978	142	56	food	food	NOUN
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fens-978	142	63	of	of	ADP
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fens-978	142	66	,	,	PUNCT
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fens-978	142	74	,	,	PUNCT
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fens-978	142	76	3	3	NUM
fens-978	142	77	–	–	PUNCT
fens-978	142	78	2023	2023	NUM
fens-978	142	79	oswald	oswald	PROPN
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fens-978	142	82	,	,	PUNCT
fens-978	142	83	soft	soft	ADJ
fens-978	142	84	computing	computing	NOUN
fens-978	142	85	application	application	NOUN
fens-978	142	86	to	to	PART
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fens-978	142	92	,	,	PUNCT
fens-978	142	93	case	case	NOUN
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fens-978	142	95	of	of	ADP
fens-978	142	96	oued	oued	PROPN
fens-978	142	97	hammam	hammam	PROPN
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fens-978	142	99	-	-	PUNCT
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fens-978	142	102	,	,	PUNCT
fens-978	142	103	food	food	NOUN
fens-978	142	104	and	and	CCONJ
fens-978	142	105	environment	environment	NOUN
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fens-978	142	107	,	,	PUNCT
fens-978	142	108	volume	volume	NOUN
fens-978	142	109	xxii	xxii	PROPN
fens-978	142	110	,	,	PUNCT
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fens-978	142	112	3	3	NUM
fens-978	142	113	–	–	PUNCT
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fens-978	142	115	,	,	PUNCT
fens-978	142	116	pag	pag	PROPN
fens-978	142	117	.	.	PROPN
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fens-978	142	119	–	–	PUNCT
fens-978	142	120	198	198	NUM
fens-978	142	121	197	197	NUM
fens-978	142	122	5	5	NUM
fens-978	142	123	.	.	PUNCT
fens-978	143	1	conclusions	conclusion	NOUN
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fens-978	143	3	conductivity	conductivity	NOUN
fens-978	143	4	and	and	CCONJ
fens-978	143	5	sodium	sodium	NOUN
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fens-978	143	8	are	be	AUX
fens-978	143	9	the	the	DET
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fens-978	143	11	used	use	VERB
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fens-978	143	13	determine	determine	VERB
fens-978	143	14	water	water	NOUN
fens-978	143	15	suitability	suitability	NOUN
fens-978	143	16	for	for	ADP
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fens-978	143	18	.	.	PUNCT
fens-978	144	1	in	in	ADP
fens-978	144	2	the	the	DET
fens-978	144	3	present	present	ADJ
fens-978	144	4	study	study	NOUN
fens-978	144	5	,	,	PUNCT
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fens-978	144	9	network	network	NOUN
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fens-978	144	11	were	be	AUX
fens-978	144	12	constructed	construct	VERB
fens-978	144	13	.	.	PUNCT
fens-978	145	1	the	the	DET
fens-978	145	2	back	back	ADJ
fens-978	145	3	propagation	propagation	NOUN
fens-978	145	4	artificial	artificial	ADJ
fens-978	145	5	neural	neural	ADJ
fens-978	145	6	learning	learning	NOUN
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fens-978	145	8	was	be	AUX
fens-978	145	9	used	use	VERB
fens-978	145	10	to	to	PART
fens-978	145	11	predict	predict	VERB
fens-978	145	12	ec	ec	PROPN
fens-978	145	13	and	and	CCONJ
fens-978	145	14	sar	sar	PROPN
fens-978	145	15	using	use	VERB
fens-978	145	16	different	different	ADJ
fens-978	145	17	input	input	NOUN
fens-978	145	18	water	water	NOUN
fens-978	145	19	quality	quality	NOUN
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fens-978	145	21	.	.	PUNCT
fens-978	146	1	qualitative	qualitative	ADJ
fens-978	146	2	and	and	CCONJ
fens-978	146	3	quantitative	quantitative	ADJ
fens-978	146	4	criteria	criterion	NOUN
fens-978	146	5	were	be	AUX
fens-978	146	6	used	use	VERB
fens-978	146	7	to	to	PART
fens-978	146	8	validate	validate	VERB
fens-978	146	9	and	and	CCONJ
fens-978	146	10	compare	compare	VERB
fens-978	146	11	the	the	DET
fens-978	146	12	models	model	NOUN
fens-978	146	13	.	.	PUNCT
fens-978	147	1	the	the	DET
fens-978	147	2	backpropagation	backpropagation	NOUN
fens-978	147	3	learning	learn	VERB
fens-978	147	4	algorithm	algorithm	NOUN
fens-978	147	5	showed	show	VERB
fens-978	147	6	a	a	DET
fens-978	147	7	high	high	ADJ
fens-978	147	8	accuracy	accuracy	NOUN
fens-978	147	9	of	of	ADP
fens-978	147	10	99	99	NUM
fens-978	147	11	%	%	NOUN
fens-978	147	12	in	in	ADP
fens-978	147	13	the	the	DET
fens-978	147	14	training	training	NOUN
fens-978	147	15	phase	phase	NOUN
fens-978	147	16	and	and	CCONJ
fens-978	147	17	98	98	NUM
fens-978	147	18	%	%	NOUN
fens-978	147	19	in	in	ADP
fens-978	147	20	the	the	DET
fens-978	147	21	validation	validation	NOUN
fens-978	147	22	phase	phase	NOUN
fens-978	147	23	in	in	ADP
fens-978	147	24	the	the	DET
fens-978	147	25	prediction	prediction	NOUN
fens-978	147	26	of	of	ADP
fens-978	147	27	sar	sar	PROPN
fens-978	147	28	.	.	PUNCT
fens-978	148	1	in	in	ADP
fens-978	148	2	comparison	comparison	NOUN
fens-978	148	3	,	,	PUNCT
fens-978	148	4	an	an	DET
fens-978	148	5	accuracy	accuracy	NOUN
fens-978	148	6	of	of	ADP
fens-978	148	7	96	96	NUM
fens-978	148	8	%	%	NOUN
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fens-978	153	2	,	,	PUNCT
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fens-978	156	8	.	.	PUNCT
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fens-978	157	2	,	,	PUNCT
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fens-978	176	3	]	]	PUNCT
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fens-978	176	6	,	,	PUNCT
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fens-978	179	2	,	,	PUNCT
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fens-978	179	4	.	.	PUNCT
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fens-978	180	4	.	.	PUNCT
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fens-978	181	42	,	,	PUNCT
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fens-978	182	2	,	,	PUNCT
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fens-978	184	2	,	,	PUNCT
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fens-978	184	4	.	.	PUNCT
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fens-978	185	2	,	,	PUNCT
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fens-978	185	4	.	.	PUNCT
fens-978	186	1	[	[	X
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fens-978	186	3	]	]	PUNCT
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fens-978	186	5	.	.	PUNCT
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fens-978	187	2	,	,	PUNCT
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fens-978	187	4	.	.	PUNCT
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fens-978	189	33	,	,	PUNCT
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fens-978	189	35	,	,	PUNCT
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fens-978	189	41	.	.	PUNCT
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fens-978	191	24	:	:	PUNCT
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fens-978	193	5	1	1	NUM
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fens-978	194	2	,	,	PUNCT
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fens-978	195	41	,	,	PUNCT
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fens-978	195	47	.	.	PUNCT
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fens-978	196	2	,	,	PUNCT
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fens-978	197	2	,	,	PUNCT
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fens-978	197	4	.	.	PUNCT
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fens-978	199	47	,	,	PUNCT
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