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dc.contributor.authorCarpinteiro, Otávio Augusto Salgado-
dc.contributor.authorReis, Agnaldo José da Rocha-
dc.contributor.authorQuintanilha Filho, Paulo Sergio-
dc.date.accessioned2012-07-24T14:34:13Z-
dc.date.available2012-07-24T14:34:13Z-
dc.date.issued2004-
dc.identifier.citationCARPINTEIRO, 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.pt_BR
dc.identifier.urihttp://www.repositorio.ufop.br/handle/123456789/1189-
dc.description.abstractThis 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.pt_BR
dc.language.isoen_USpt_BR
dc.titleA hierarchical hybrid neural model in short-termload forecasting.pt_BR
dc.typeTrabalho apresentado em eventopt_BR
dc.rights.licenseO Periódico Applied Soft Computing concede permissão para depósito do artigo no Repositório Institucional da UFOP. Número da licença: 3291280500461.-
Appears in Collections:DECAT - Trabalhos apresentados em eventos

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