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Health assessment of LFP automotive batteries using a fractional-order neural network

dc.contributor.authorSánchez Ramos, Luciano 
dc.contributor.authorOtero Rodríguez, José 
dc.contributor.authorAnseán González, David 
dc.contributor.authorCouso Blanco, Inés 
dc.date.accessioned2020-04-29T10:56:43Z
dc.date.available2020-04-29T10:56:43Z
dc.date.issued2019
dc.identifier.citationNeurocomputing, 391, p. 345-354 (2019); doi:10.1016/j.neucom.2019.06.107
dc.identifier.issn0925-2312
dc.identifier.urihttp://hdl.handle.net/10651/54621
dc.description.sponsorshipThis work was supported in part by the Science and Innovation Ministry and by FEDER, under the Projects TIN2014-56967-R, TEC2016-80700-R (AEI/FEDER, UE) and TIN2017-84804-R.
dc.format.extentp. 345-354
dc.language.isoeng
dc.relation.ispartofNeurocomputing
dc.rights© 2019 Elsevier
dc.sourceScopus
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85076521184&doi=10.1016%2fj.neucom.2019.06.107&partnerID=40&md5=5986892c00a2b4cdb989b41268e84c31
dc.titleHealth assessment of LFP automotive batteries using a fractional-order neural network
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1016/j.neucom.2019.06.107
dc.type.dcmitext
dc.relation.projectIDFEDER/TIN2014-56967-R
dc.relation.projectIDAEI/FEDER/TEC2016-80700-R
dc.relation.projectIDFEDER/TIN2017-84804-R
dc.relation.publisherversionhttp://dx.doi.org/10.1016/j.neucom.2019.06.107


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