A fast electric load forecasting using neural networks
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Data
2000-12-01
Autores
Lopes, Mara Lúcia M. [UNESP]
Minussi, Carlos R. [UNESP]
Lotufo, Anna Diva P. [UNESP]
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Resumo
The objective of this work is the development of a methodology for electric load forecasting based on a neural network. Here, it is used Backpropagation algorithm with an adaptive process based on fuzzy logic. This methodology results in fast training, when compared to the conventional formulation of Backpropagation algorithm. Results are presented using data from a Brazilian Electric Company and the performance is very good for the proposal objective.
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Palavras-chave
Backpropagation, Fuzzy control, Fuzzy sets, Gradient methods, Kalman filtering, Neural networks, Regression analysis, Binary systems, Linear regression, Electric load forecasting
Como citar
Midwest Symposium on Circuits and Systems, v. 2, p. 646-649.