Colombian Energy Market: An approach of Anfis and Clustering Techniques to an Optimal Portfolio
dc.contributor.author | Palacios, Alejandro | spa |
dc.contributor.author | Giraldo, Marcela | spa |
dc.contributor.author | Quintero, O. L. | spa |
dc.contributor.department | Universidad EAFIT. Escuela de Ciencias. Grupo de Investigación Modelado Matemático | spa |
dc.date.accessioned | 2014-12-12T15:41:26Z | |
dc.date.available | 2014-12-12T15:41:26Z | |
dc.date.issued | 2014 | |
dc.description.abstract | This 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.uri | http://hdl.handle.net/10784/4609 | |
dc.language.iso | eng | eng |
dc.publisher | Universidad EAFIT | spa |
dc.publisher.department | Escuela de Ciencias | spa |
dc.publisher.program | Grupo de Investigación Modelado Matemático | spa |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | eng |
dc.rights.local | Acceso abierto | spa |
dc.subject.keyword | Energy Markets | eng |
dc.subject.keyword | Artificial Intelligence | eng |
dc.subject.keyword | Fuzzy Modeling | eng |
dc.subject.keyword | Neural Networks | eng |
dc.subject.keyword | ANFIS | eng |
dc.title | Colombian Energy Market: An approach of Anfis and Clustering Techniques to an Optimal Portfolio | eng |
dc.type | workingPaper | eng |
dc.type.hasVersion | draft | eng |
dc.type.local | Documento de trabajo de investigación | spa |
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