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Virtual sensor based on a deep learning approach for estimating efficiency in chillers

dc.contributor.authorAlonso, S.
dc.contributor.authorMorán, A.
dc.contributor.authorPérez, D.
dc.contributor.authorReguera, P.
dc.contributor.authorDíaz Blanco, Ignacio 
dc.contributor.authorDomínguez, M.
dc.date.accessioned2019-11-14T10:22:33Z
dc.date.available2019-11-14T10:22:33Z
dc.date.issued2019
dc.identifier.isbn9783030202569
dc.identifier.issn1865-0929
dc.identifier.urihttp://hdl.handle.net/10651/53401
dc.descriptionInternational Conference on Engineering Applications of Neural Networks, EANN (20th. 2019. Xersonisos, Crete, Greece)
dc.description.sponsorshipThis work was supported in part by the Spanish Ministerio de Ciencia e Innovacion (MICINN) and the European FEDER funds under project CICYT DPI2015-69891-C2-1-R/2-R.
dc.format.extentp. 307-319
dc.language.isoeng
dc.relation.ispartofEngineering Applications of Neural Networks
dc.relation.ispartofseriesCommunications in Computer and Information Science
dc.rights© Springer Nature Switzerland AG 2019
dc.rightsThis is a post-peer-review, pre-copyedit version of an article published in Engineering Applications of Neural Networks. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-20257-6_26
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceScopus
dc.source.urihttps://www2.scopus.com/inward/record.uri?eid=2-s2.0-85065874349&doi=10.1007%2f978-3-030-20257-6_26&partnerID=40&md5=585f785d21917d7a07f7f903e0ba6c5a
dc.titleVirtual sensor based on a deep learning approach for estimating efficiency in chillers
dc.typeconference outputspa
dc.identifier.doi10.1007/978-3-030-20257-6_26
dc.relation.projectIDMICINN/FEDER/DPI2015-69891-C2-1-R/2-R.
dc.relation.publisherversionhttp://dx.doi.org/10.1007/978-3-030-20257-6_26
dc.rights.accessRightsopen access
dc.type.hasVersionAM


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