A hierarchical hybrid neural model in short-termload forecasting.

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2004
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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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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.