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

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...

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Autores:
Palacios, Alejandro
Giraldo, Marcela
Quintero, O. L.
Tipo de recurso:
Fecha de publicación:
2014
Institución:
Universidad EAFIT
Repositorio:
Repositorio EAFIT
Idioma:
eng
OAI Identifier:
oai:repository.eafit.edu.co:10784/4609
Acceso en línea:
http://hdl.handle.net/10784/4609
Palabra clave:
Energy Markets
Artificial Intelligence
Fuzzy Modeling
Neural Networks
ANFIS
Rights
License
Acceso abierto
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oai_identifier_str oai:repository.eafit.edu.co:10784/4609
network_acronym_str REPOEAFIT2
network_name_str Repositorio EAFIT
repository_id_str
spelling 2014-12-12T15:41:26Z20142014-12-12T15:41:26Zhttp://hdl.handle.net/10784/4609This 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.engUniversidad EAFITGrupo de Investigación Modelado MatemáticoEscuela de CienciasColombian Energy Market: An approach of Anfis and Clustering Techniques to an Optimal PortfolioworkingPaperinfo:eu-repo/semantics/workingPaperDocumento de trabajo de investigacióndrafthttp://purl.org/coar/version/c_b1a7d7d4d402bccehttp://purl.org/coar/resource_type/c_8042Acceso abiertohttp://purl.org/coar/access_right/c_abf2Energy MarketsArtificial IntelligenceFuzzy ModelingNeural NetworksANFISUniversidad EAFIT. Escuela de Ciencias. Grupo de Investigación Modelado MatemáticoPalacios, AlejandroGiraldo, MarcelaQuintero, O. L.ORIGINAL26 ColombianEnergyMarketApproachAnfis.pdf26 ColombianEnergyMarketApproachAnfis.pdfapplication/pdf709096https://repository.eafit.edu.co/bitstreams/6fc0651b-b06d-49ce-b556-3f952db49174/downloada48823be262f3bf32b5b8bfeca1f084cMD5110784/4609oai:repository.eafit.edu.co:10784/46092014-12-12 13:47:11.853open.accesshttps://repository.eafit.edu.coRepositorio Institucional Universidad EAFITrepositorio@eafit.edu.co
dc.title.eng.fl_str_mv Colombian Energy Market: An approach of Anfis and Clustering Techniques to an Optimal Portfolio
title Colombian Energy Market: An approach of Anfis and Clustering Techniques to an Optimal Portfolio
spellingShingle Colombian Energy Market: An approach of Anfis and Clustering Techniques to an Optimal Portfolio
Energy Markets
Artificial Intelligence
Fuzzy Modeling
Neural Networks
ANFIS
title_short Colombian Energy Market: An approach of Anfis and Clustering Techniques to an Optimal Portfolio
title_full Colombian Energy Market: An approach of Anfis and Clustering Techniques to an Optimal Portfolio
title_fullStr Colombian Energy Market: An approach of Anfis and Clustering Techniques to an Optimal Portfolio
title_full_unstemmed Colombian Energy Market: An approach of Anfis and Clustering Techniques to an Optimal Portfolio
title_sort Colombian Energy Market: An approach of Anfis and Clustering Techniques to an Optimal Portfolio
dc.creator.fl_str_mv Palacios, Alejandro
Giraldo, Marcela
Quintero, O. L.
dc.contributor.department.spa.fl_str_mv Universidad EAFIT. Escuela de Ciencias. Grupo de Investigación Modelado Matemático
dc.contributor.author.spa.fl_str_mv Palacios, Alejandro
Giraldo, Marcela
Quintero, O. L.
dc.subject.keyword.eng.fl_str_mv Energy Markets
Artificial Intelligence
Fuzzy Modeling
Neural Networks
ANFIS
topic Energy Markets
Artificial Intelligence
Fuzzy Modeling
Neural Networks
ANFIS
description 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.
publishDate 2014
dc.date.available.none.fl_str_mv 2014-12-12T15:41:26Z
dc.date.issued.none.fl_str_mv 2014
dc.date.accessioned.none.fl_str_mv 2014-12-12T15:41:26Z
dc.type.eng.fl_str_mv workingPaper
dc.type.none.fl_str_mv info:eu-repo/semantics/workingPaper
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_b1a7d7d4d402bcce
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_8042
dc.type.local.spa.fl_str_mv Documento de trabajo de investigación
dc.type.hasVersion.eng.fl_str_mv draft
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10784/4609
url http://hdl.handle.net/10784/4609
dc.language.iso.eng.fl_str_mv eng
language eng
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.local.spa.fl_str_mv Acceso abierto
rights_invalid_str_mv Acceso abierto
http://purl.org/coar/access_right/c_abf2
dc.publisher.spa.fl_str_mv Universidad EAFIT
dc.publisher.program.spa.fl_str_mv Grupo de Investigación Modelado Matemático
dc.publisher.department.spa.fl_str_mv Escuela de Ciencias
institution Universidad EAFIT
bitstream.url.fl_str_mv https://repository.eafit.edu.co/bitstreams/6fc0651b-b06d-49ce-b556-3f952db49174/download
bitstream.checksum.fl_str_mv a48823be262f3bf32b5b8bfeca1f084c
bitstream.checksumAlgorithm.fl_str_mv MD5
repository.name.fl_str_mv Repositorio Institucional Universidad EAFIT
repository.mail.fl_str_mv repositorio@eafit.edu.co
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