A hierarchical hybrid neural model in short-termload forecasting.

Detalhes bibliográficos
Autor(a) principal: Carpinteiro, Otávio Augusto Salgado
Data de Publicação: 2004
Outros Autores: Reis, Agnaldo José da Rocha, Quintanilha Filho, Paulo Sergio
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UFOP
Texto Completo: http://www.repositorio.ufop.br/handle/123456789/1189
Resumo: This paper proposes a novel neural model to the problem of short-term load forecasting. The neural model is made up o f two self-organizing map nets one on top of the other |,and a single-layer perceptron. It has application into domains in which the context information given by former events plays aprimary role. The model was trained and assessed onload data extracted from a Brazilian electric utility. It was required to predict once every hour the electric load during the next six hours. The paper presents the results, and evaluates them.
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spelling Carpinteiro, Otávio Augusto SalgadoReis, Agnaldo José da RochaQuintanilha Filho, Paulo Sergio2012-07-24T14:34:13Z2012-07-24T14:34:13Z2004CARPINTEIRO, O. A. S.; REIS, A. J. da R.; QUINTANILHA FILHO, P. S. A hierarchical hybrid neural model in short-termload forecasting. In: Simpósio Brasileiro de Redes Neurais, 2004. Natal. Anais... Natal: SBRN, 2004. p.1-6. Disponível em: <http://www.gpesc.unifei.edu.br/tmp/sbrn2004-3669.pdf>. Acesso em: 23 jul. 2012.http://www.repositorio.ufop.br/handle/123456789/1189This paper proposes a novel neural model to the problem of short-term load forecasting. The neural model is made up o f two self-organizing map nets one on top of the other |,and a single-layer perceptron. It has application into domains in which the context information given by former events plays aprimary role. The model was trained and assessed onload data extracted from a Brazilian electric utility. It was required to predict once every hour the electric load during the next six hours. The paper presents the results, and evaluates them.A hierarchical hybrid neural model in short-termload forecasting.info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectO Periódico Applied Soft Computing concede permissão para depósito do artigo no Repositório Institucional da UFOP. Número da licença: 3291280500461.info:eu-repo/semantics/openAccessengreponame:Repositório Institucional da UFOPinstname:Universidade Federal de Ouro Preto (UFOP)instacron:UFOPLICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://www.repositorio.ufop.br/bitstream/123456789/1189/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52ORIGINALEVENTO_HierarchicalHybridNeural.pdfEVENTO_HierarchicalHybridNeural.pdfapplication/pdf219332http://www.repositorio.ufop.br/bitstream/123456789/1189/1/EVENTO_HierarchicalHybridNeural.pdfba8f3af8c3b38a6be970ca78d4316e00MD51123456789/11892016-10-27 09:50:36.227oai:localhost: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Repositório InstitucionalPUBhttp://www.repositorio.ufop.br/oai/requestrepositorio@ufop.edu.bropendoar:32332016-10-27T13:50:36Repositório Institucional da UFOP - Universidade Federal de Ouro Preto (UFOP)false
dc.title.pt_BR.fl_str_mv A hierarchical hybrid neural model in short-termload forecasting.
title A hierarchical hybrid neural model in short-termload forecasting.
spellingShingle A hierarchical hybrid neural model in short-termload forecasting.
Carpinteiro, Otávio Augusto Salgado
title_short A hierarchical hybrid neural model in short-termload forecasting.
title_full A hierarchical hybrid neural model in short-termload forecasting.
title_fullStr A hierarchical hybrid neural model in short-termload forecasting.
title_full_unstemmed A hierarchical hybrid neural model in short-termload forecasting.
title_sort A hierarchical hybrid neural model in short-termload forecasting.
author Carpinteiro, Otávio Augusto Salgado
author_facet Carpinteiro, Otávio Augusto Salgado
Reis, Agnaldo José da Rocha
Quintanilha Filho, Paulo Sergio
author_role author
author2 Reis, Agnaldo José da Rocha
Quintanilha Filho, Paulo Sergio
author2_role author
author
dc.contributor.author.fl_str_mv Carpinteiro, Otávio Augusto Salgado
Reis, Agnaldo José da Rocha
Quintanilha Filho, Paulo Sergio
description This paper proposes a novel neural model to the problem of short-term load forecasting. The neural model is made up o f two self-organizing map nets one on top of the other |,and a single-layer perceptron. It has application into domains in which the context information given by former events plays aprimary role. The model was trained and assessed onload data extracted from a Brazilian electric utility. It was required to predict once every hour the electric load during the next six hours. The paper presents the results, and evaluates them.
publishDate 2004
dc.date.issued.fl_str_mv 2004
dc.date.accessioned.fl_str_mv 2012-07-24T14:34:13Z
dc.date.available.fl_str_mv 2012-07-24T14:34:13Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
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dc.identifier.citation.fl_str_mv CARPINTEIRO, O. A. S.; REIS, A. J. da R.; QUINTANILHA FILHO, P. S. A hierarchical hybrid neural model in short-termload forecasting. In: Simpósio Brasileiro de Redes Neurais, 2004. Natal. Anais... Natal: SBRN, 2004. p.1-6. Disponível em: <http://www.gpesc.unifei.edu.br/tmp/sbrn2004-3669.pdf>. Acesso em: 23 jul. 2012.
dc.identifier.uri.fl_str_mv http://www.repositorio.ufop.br/handle/123456789/1189
identifier_str_mv CARPINTEIRO, O. A. S.; REIS, A. J. da R.; QUINTANILHA FILHO, P. S. A hierarchical hybrid neural model in short-termload forecasting. In: Simpósio Brasileiro de Redes Neurais, 2004. Natal. Anais... Natal: SBRN, 2004. p.1-6. Disponível em: <http://www.gpesc.unifei.edu.br/tmp/sbrn2004-3669.pdf>. Acesso em: 23 jul. 2012.
url http://www.repositorio.ufop.br/handle/123456789/1189
dc.language.iso.fl_str_mv eng
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instname_str Universidade Federal de Ouro Preto (UFOP)
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