Health assessment of automotive batteries through computational intelligence-based soft sensors: An empirical study

dc.contributor.author	Almansa, E.
dc.contributor.author	Anseán González, David
dc.contributor.author	Couso Blanco, Inés
dc.contributor.author	Sánchez Ramos, Luciano
dc.date.accessioned	2018-02-06T10:10:23Z
dc.date.available	2018-02-06T10:10:23Z
dc.date.issued	2018
dc.identifier.isbn	9783319671796
dc.identifier.issn	2194-5357
dc.identifier.uri	http://hdl.handle.net/10651/45112
dc.description	International Joint Conference SOCO’17-CISIS’17-ICEUTE’17 (2017. León)
dc.description.sponsorship	DPI2013-046541-R, FEDER, Federación Española de Enfermedades Raras; TEC2016-80700-R, FEDER, Federación Española de Enfermedades Raras; TIN2014-56967-R, FEDER, Federación Española de Enfermedades Raras; MICINN, Ministerio de Ciencia e Innovación
dc.format.extent	p. 47-56
dc.language.iso	eng
dc.relation.ispartof	International Joint Conference SOCO’17-CISIS’17-ICEUTE’17
dc.relation.ispartofseries	Advances in Intelligent Systems and Computing;649
dc.rights	©,
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028651769&doi=10.1007%2f978-3-319-67180-2_5&partnerID=40&md5=acee6f7abe3fc7c2df8e046873817367
dc.title	Health assessment of automotive batteries through computational intelligence-based soft sensors: An empirical study
dc.type	conference output	spa
dc.identifier.doi	10.1007/978-3-319-67180-2_5
dc.relation.publisherversion	http://dx.doi.org/10.1007/978-3-319-67180-2_5

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