Please use this identifier to cite or link to this item: http://repositorio.uisek.edu.ec/handle/123456789/4201
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dc.contributor.authorLlanes Cedeño, Edilberto Antonio-
dc.contributor.authorGuachimboza Davalos, Jorge I.-
dc.contributor.authorRubio Aguiar, Rodolfo J.-
dc.contributor.authorPeralta Zurita, Diana Belén-
dc.contributor.authorNúñez Barrionuevo, Oscar F.-
dc.date.accessioned2021-04-20T18:24:16Z-
dc.date.available2021-04-20T18:24:16Z-
dc.date.issued2020-11-11-
dc.identifier.isbn978-3-030-59193-9-
dc.identifier.isbn978-3-030-59194-6-
dc.identifier.urihttps://repositorio.uisek.edu.ec/handle/123456789/4201-
dc.description.abstractAbstract. The present work shows a multivariate regression through deep learning related to energy consumption in the province of Pichincha- Ecuador in relation to its cantons. This is done to establish consumption habits in relation to the existing population. For this, a data preprocess- ing stage was implemented and later an artificial neural network of a hidden layer and 15 neurons. As a result, a mathematical model with an absolute error of 2.2 % is obtained.es
dc.description.sponsorshipUisekes
dc.language.isoenges
dc.publisherSpringer, Chames
dc.rightsopenAccesses
dc.subjectPOWER CONSUMPTIONes
dc.subjectMULTIVARIATE REGRESSIONes
dc.subjectNEURAL NETes
dc.subjectWORKes
dc.titlePrediction of monthly electricity consumption by cantons in Ecuador through neural networks: a case studyes
dc.typeinfo:eu-repo/semantics/bookchapteres
Appears in Collections:Publicaciones UISEK

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