Forecast of the outlet turbidity and filtered volume in different microirrigation filters and filtration media by using machine learning techniques

García Nieto, Paulino José; García Gonzalo, María Esperanza; Arbat, G.; Duran Ros, M.; Pujol, T.; Puig Bargués, J.

doi:10.1016/j.cam.2023.115606

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Forecast of the outlet turbidity and filtered volume in different microirrigation filters and filtration media by using machine learning techniques

dc.contributor.author	García Nieto, Paulino José
dc.contributor.author	García Gonzalo, María Esperanza
dc.contributor.author	Arbat, G.
dc.contributor.author	Duran Ros, M.
dc.contributor.author	Pujol, T.
dc.contributor.author	Puig Bargués, J.
dc.date.accessioned	2024-02-26T07:39:02Z
dc.date.available	2024-02-26T07:39:02Z
dc.date.issued	2024
dc.identifier.citation	Journal of Computational and Applied Mathematics, 439 (2024); doi:10.1016/j.cam.2023.115606
dc.identifier.issn	0377-0427
dc.identifier.uri	https://hdl.handle.net/10651/71643
dc.description.sponsorship	The Mathematics Department at the University of Oviedo provided computational assistance, and grants AGL2015- 63750-R and RTI2018-094798-B-100 were provided by the Spanish Research Agency and the European Regional Development Fund respectively.
dc.language.iso	eng
dc.relation.ispartof	Journal of Computational and Applied Mathematics
dc.rights	© 2023 The Author(s).
dc.rights	CC Reconocimiento – No Comercial – Sin Obra Derivada 4.0 Internacional
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173585221&doi=10.1016%2fj.cam.2023.115606&partnerID=40&md5=f1152b82e508e94032e1aeb81228b8d4
dc.title	Forecast of the outlet turbidity and filtered volume in different microirrigation filters and filtration media by using machine learning techniques
dc.type	journal article
dc.identifier.doi	10.1016/j.cam.2023.115606
dc.local.notes	OA ATUO23
dc.relation.projectID	info:eu-repo/grantAgreement/MINECO//AGL2015-63750-R/ES/FILTROS GRANULARES EN SISTEMAS DE RIEGO POR GOTEO CON AGUAS RESIDUALES REGENERADAS: CONDICIONES OPERATIVAS Y CONSUMO ENERGETICO/
dc.relation.projectID	info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-094798-B-I00/ES/MEJORA DE LA RETENCION DE PARTICULAS EN FILTROS GRANULARES PARA RIEGO POR GOTEO CON AGUAS REGENERADAS/
dc.relation.publisherversion	http://dx.doi.org/10.1016/j.cam.2023.115606
dc.rights.accessRights	open access
dc.type.hasVersion	VoR

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