On the application of neural networks trained with fem data for the identification of stiffness parameters of improved mechanical beam joints

dc.contributor.author	Badea, F.
dc.contributor.author	Pérez Fernández, Jesús Ángel
dc.contributor.author	Ozenli, F. C.
dc.contributor.author	Olazagoitia, J. L.
dc.date.accessioned	2023-11-07T09:59:23Z
dc.date.available	2023-11-07T09:59:23Z
dc.date.issued	2023
dc.identifier.citation	Mathematics, 11(15), (2023); doi:10.3390/math11153261
dc.identifier.issn	2227-7390
dc.identifier.uri	https://hdl.handle.net/10651/70238
dc.description.sponsorship	University of Design and Technology (UDIT) [INC-UDIT-2023-JCR05]
dc.language.iso	eng
dc.relation.ispartof	Mathematics
dc.rights	© 2023 by the authors
dc.rights	CC Reconocimiento 4.0 Internacional
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167580965&doi=10.3390%2fmath11153261&partnerID=40&md5=52603da044e58ef14e23f33aa7e5dc82
dc.source.uri	http://creativecommons.org/licenses/by/4.0/
dc.title	On the application of neural networks trained with fem data for the identification of stiffness parameters of improved mechanical beam joints
dc.type	journal article
dc.type	VoR
dc.identifier.doi	10.3390/math11153261
dc.relation.projectID	INC-UDIT-2023-JCR05
dc.relation.publisherversion	http://dx.doi.org/10.3390/math11153261
dc.rights.accessRights	open access