Título: Técnicas de Regularização de Modelos Neurais Aplicadas à Previsão de Carga a Curto Prazo
Autores: Ferreira, Vitor Hugo; Silva, Alexandre P. Alves da
Resumo: The knowledge of loads’ future behavior is very important for decision making in power system operation. During the last years, many load models have been proposed, and the neural ones have presented the best results. One of the disadvantages of the neural models is the possibility of excessive adjustment of the training data, named overfitting, degrading the generalization performance of the estimated models. This problem can be tackled by using regularization techniques. The present shows the application of some of these techniques to short term load forecasting.
Código DOI: 10.21528/CBRN2005-179
Artigo em PDF: CBRN2005_179.pdf
Arquivo BibTex: CBRN2005_179.bib