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VII Brazilian Symposium on Neural Networks (SBRN'02)
Fuzzy Markov Predictor with First and Second-Order Dependences
Pernambuco, Brazil
November 11-November 14
ISBN: 0-7695-1709-9
Marcelo Andrade Teixeira, Federal University of Rio de Janeiro (UFRJ); Electric Power Research Center (CEPEL)
Gerson Zaverucha, Federal University of Rio de Janeiro (UFRJ)
We present two new versions of the Fuzzy Markov Predictor (FMP) with different dependences among the inputs: first-order and second-order dependences. The FMP is a modification of the Hidden Markov Model in order to enable it to predict numerical values. The FMP can be seen as an extension of the Fuzzy Bayes Predictor (FBP). These hybrid systems are applied to the task of monthly electric load forecasting and successfully compared with one fuzzy system, and two traditional forecasting methods, Box-Jenkins and Winters exponential smoothing.
Citation:
Marcelo Andrade Teixeira, Gerson Zaverucha, "Fuzzy Markov Predictor with First and Second-Order Dependences," sbrn, pp.80, VII Brazilian Symposium on Neural Networks (SBRN'02), 2002
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