Colombian Energy Market: An approach of Anfis and Clustering Techniques to an Optimal Portfolio

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dc.contributor.authorPalacios, Alejandrospa
dc.contributor.authorGiraldo, Marcelaspa
dc.contributor.authorQuintero, O. L.spa
dc.contributor.departmentUniversidad EAFIT. Escuela de Ciencias. Grupo de Investigación Modelado Matemáticospa
dc.date.accessioned2014-12-12T15:41:26Z
dc.date.available2014-12-12T15:41:26Z
dc.date.issued2014
dc.description.abstractThis paper focuses on the study of a first approach to an optimal portfolio in the Colombian Energy Market using Artificial Intelligence. Specifically, ANFIS and Clustering techniques are applied. The methodology is implemented using the Matlab Toolboxes for clustering and FIS generation. Te results are presented, as well as the analysis of them. A first approximation to an optimal portfolio obtained with this methodology is shown. Consequently, some conclusions of the different techniques available for the same purpose are discussed. Finally the future work is proposed.eng
dc.identifier.urihttp://hdl.handle.net/10784/4609
dc.language.isoengeng
dc.publisherUniversidad EAFITspa
dc.publisher.departmentEscuela de Cienciasspa
dc.publisher.programGrupo de Investigación Modelado Matemáticospa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccesseng
dc.rights.localAcceso abiertospa
dc.subject.keywordEnergy Marketseng
dc.subject.keywordArtificial Intelligenceeng
dc.subject.keywordFuzzy Modelingeng
dc.subject.keywordNeural Networkseng
dc.subject.keywordANFISeng
dc.titleColombian Energy Market: An approach of Anfis and Clustering Techniques to an Optimal Portfolioeng
dc.typeinfo:eu-repo/semantics/workingPaper
dc.type.hasVersiondrafteng
dc.type.localDocumento de trabajo de investigaciónspa

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