2012-08-272012-08-272011-11-04ALVES, Wesin Ribeiro. Modelos para previsão de carga a curto prazo através de redes neurais artificiais com treinamento baseado na teoria da informação. Orientadora: Adriana Rosa Garcez Castro 2011. 61 f. Dissertação (Mestrado em Engenharia Elétrica.) - Instituto de Tecnologia,, Universidade Federal do Pará, Belém, 2011. Disponível em: http://repositorio.ufpa.br/jspui/handle/2011/2894. Acesso em:.https://repositorio.ufpa.br/handle/2011/2894The previous knowledge of the load value is almighty important to the electric power system planning and operation. This paper presents results of an investigative study of application of Artificial Neural Networks as a Multilayer Perceptron with the training based on Information Theory to the problem of short term load forecasting. The learning based on Information Theory focuses on the use of the amount of information (Entropy) for the training of neural network. Two forecaster models are presented, and that they was developed using real data from an energy utility. To compare and verify the efficiency of the proposed systems, it was also developed a forecasting system using neural network trained based on the traditional criterion of mean square error (MSE). The results has showed the efficiency of proposed systems, which had better results when compared with the forecasting system based on neural network trained by criterion of MSE and with forecasting system already was presented in the literature.porAcesso AbertoPrevisão de cargasRedes neurais artificiaisTeoria da informaçãoLoad forecastingArtificial neural networksInformation theoryDissertaçãoCNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::METODOLOGIA E TECNICAS DA COMPUTACAO::LINGUAGENS DE PROGRAMACAOCNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::METODOLOGIA E TECNICAS DA COMPUTACAO::ENGENHARIA DE SOFTWARECNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::METODOLOGIA E TECNICAS DA COMPUTACAO::BANCO DE DADOS