Machine learning applied to the prediction of citrus production

dc.contributor.author	Díaz Rodríguez, Susana Irene
dc.contributor.author	Mazza, Silvia M.
dc.contributor.author	Fernández-Combarro Álvarez, Elías
dc.contributor.author	Giménez, Laura I.
dc.contributor.author	Gaiad, José E.
dc.date.accessioned	2017-12-14T11:03:40Z
dc.date.available	2017-12-14T11:03:40Z
dc.date.issued	2017
dc.identifier.citation	Spanish Journal of Agricultural Research, 15(2), e0205 (2017); doi:10.5424/sjar/2017152-9090
dc.identifier.issn	1695-971X
dc.identifier.uri	http://hdl.handle.net/10651/44716
dc.description.sponsorship	Northeastern University [SGCYT PI 1713CA03]; Spanish Ministry of Economy and Competitiveness/FEDER [TEC2015-67387-C4-3-R]
dc.format.extent	e0205
dc.language.iso	eng
dc.relation.ispartof	Spanish Journal Of Agricultural Research
dc.rights	© 2017 INIA
dc.rights	CC Reconocimiento - No comercial - Sin obras derivadas 3.0 España
dc.rights.uri	http://creativecommons.org/licenses/by-nc/3.0/es/
dc.source	WOS:000406748000020
dc.title	Machine learning applied to the prediction of citrus production	eng
dc.type	journal article
dc.identifier.doi	10.5424/sjar/2017152-9090
dc.relation.projectID	SGCYT PI 1713CA03
dc.relation.projectID	TEC2015-67387-C4-3-R
dc.relation.publisherversion	http://dx.doi.org/10.5424/sjar/2017152-9090
dc.rights.accessRights	open access

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