Abstract:
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 modifi...Show MoreMetadata
Abstract:
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. 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.
Date of Conference: 11-14 November 2002
Date Added to IEEE Xplore: 25 February 2003
Print ISBN:0-7695-1709-9