Identification of tire model parameters with artificial neural networks

dc.contributor.author	Olazagoitia, J. L.
dc.contributor.author	Pérez Fernández, Jesús Ángel
dc.contributor.author	Badea, F.
dc.date.accessioned	2021-06-29T08:58:26Z
dc.date.available	2021-06-29T08:58:26Z
dc.date.issued	2020
dc.identifier.citation	Applied Sciences (Switzerland), 10(24), p. 1-16 (2020); doi:10.3390/app10249110
dc.identifier.issn	2076-3417
dc.identifier.uri	http://hdl.handle.net/10651/59283
dc.description.sponsorship	The authors thank the Global Nebrija-Santander Chair of Energy Recovery in Surface Transport for their financial support. This work was also supported by the Comunidad de Madrid [grant SEGVAUTO 4.0-CM-P2018EEMT-4362]; and the Agencia Estatal de Investigación [grant RETOS 2018-RTI2018-095923-B-C22].
dc.format.extent	p. 1-16
dc.language.iso	eng
dc.relation.ispartof	Applied Sciences (Switzerland)
dc.rights	© 2020 Olazagoitia et al.
dc.rights	CC Reconocimiento 4.0 Internacional
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85098290655&doi=10.3390%2fapp10249110&partnerID=40&md5=2dd5f145bf2efae816aeb0259f372cce
dc.title	Identification of tire model parameters with artificial neural networks
dc.type	journal article
dc.identifier.doi	10.3390/app10249110
dc.relation.projectID	AEI/2018-RTI2018-095923-B-C22
dc.relation.publisherversion	http://dx.doi.org/10.3390/app10249110
dc.rights.accessRights	open access
dc.type.hasVersion	VoR

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