Modelling energy performance of residential dwellings by using the MARS technique, SVM-based approach, MLP neural network and M5 model tree

dc.contributor.author	García Nieto, Paulino José
dc.contributor.author	García Gonzalo, María Esperanza
dc.contributor.author	Paredes Sánchez, Beatriz María
dc.contributor.author	Paredes Sánchez, José Pablo
dc.date.accessioned	2023-08-28T09:41:57Z
dc.date.available	2023-08-28T09:41:57Z
dc.date.issued	2023
dc.identifier.citation	Applied Energy, 341 (2023); doi:10.1016/j.apenergy.2023.121074
dc.identifier.issn	0306-2619
dc.identifier.uri	https://hdl.handle.net/10651/69410
dc.language.iso	eng
dc.relation.ispartof	Applied Energy
dc.rights	© 2023 The author(s). Published by Elsevier Ltd.
dc.rights	CC Reconocimiento - No Comercial - Sin Obra Derivada 4.0 Internacional
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152732284&doi=10.1016%2fj.apenergy.2023.121074&partnerID=40&md5=183465833288ad7ba98e2ed6542467b5
dc.title	Modelling energy performance of residential dwellings by using the MARS technique, SVM-based approach, MLP neural network and M5 model tree
dc.type	journal article
dc.identifier.doi	10.1016/j.apenergy.2023.121074
dc.relation.publisherversion	http://dx.doi.org/10.1016/j.apenergy.2023.121074
dc.rights.accessRights	open access
dc.type.hasVersion	VoR

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