Title :
Fuzzy Markov predictor in electric load forecasting
Author :
Teixeira, Marcelo Andrade ; Zaverucha, Gerson
Author_Institution :
COPPE, Univ. Fed. do Rio de Janeiro, Brazil
fDate :
6/24/1905 12:00:00 AM
Abstract :
We present the fuzzy Markov predictor (FMP), a hybrid system that is applied to the task of monthly electric load forecasting. The FMP is a modification we introduce in 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) that was modified from the naive Bayes classifier. For verifying the efficiency of the FMP´s prediction, we compare it with the FBP, one fuzzy system and two traditional forecasting methods, Box-Jenkins and Winters exponential smoothing
Keywords :
Bayes methods; fuzzy set theory; hidden Markov models; load forecasting; pattern classification; FBP; FMP; HMM; fuzzy Bayes predictor; fuzzy Markov predictor; hidden Markov model; monthly electric load forecasting; naive Bayes classifier; Computer science; Electric variables measurement; Fuzzy systems; Hidden Markov models; Load forecasting; Niobium compounds; Power engineering and energy; Predictive models; Smoothing methods; Systems engineering and theory;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1007520
