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Prediction of the critical temperature of a superconductor by using the WOA/MARS, Ridge, Lasso and Elastic-net machine learning techniques

dc.contributor.authorGarcía Nieto, Paulino José 
dc.contributor.authorGarcía Gonzalo, María Esperanza 
dc.contributor.authorParedes Sánchez, José Pablo 
dc.date.accessioned2022-02-01T08:05:53Z
dc.date.available2022-02-01T08:05:53Z
dc.date.issued2021
dc.identifier.citationNeural Computing and Applications, 33, p. 17131-17145 (2021); doi:10.1007/s00521-021-06304-z
dc.identifier.issn0941-0643
dc.identifier.urihttp://hdl.handle.net/10651/61719
dc.description.sponsorshipSpanish Research Projects PGC2018-098459-B-I00 and FC-GRUPIN-IDI/2018/000221, both of which are partially financed by European Funds (FEDER).
dc.format.extentp. 17131-17145
dc.language.isoeng
dc.relation.ispartofNeural Computing and Applications
dc.rights© The authors 2021, corrected publication 2021
dc.rightsCC Reconocimiento 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceScopus
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85110876159&doi=10.1007%2fs00521-021-06304-z&partnerID=40&md5=2c5eeb7d0aa4852ac7236ae96c256ac4
dc.titlePrediction of the critical temperature of a superconductor by using the WOA/MARS, Ridge, Lasso and Elastic-net machine learning techniques
dc.typejournal article
dc.identifier.doi10.1007/s00521-021-06304-z
dc.local.notesOA ATUO21
dc.relation.projectIDPGC2018-098459-B-I00
dc.relation.projectIDFC-GRUPIN-IDI/2018/000221
dc.relation.publisherversionhttp://dx.doi.org/10.1007/s00521-021-06304-z
dc.rights.accessRightsopen access
dc.type.hasVersionVoR


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