Fuzzy Markov predictor in electric load forecasting

Author

Teixeira, Marcelo Andrade ; Zaverucha, Gerson

Author_Institution

COPPE, Univ. Fed. do Rio de Janeiro, Brazil

Volume

3

fYear

2002

fDate

6/24/1905 12:00:00 AM

Firstpage

2416

Lastpage

2421

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on

Conference_Location

Honolulu, HI

ISSN

1098-7576

Print_ISBN

0-7803-7278-6

Type

conf

DOI

10.1109/IJCNN.2002.1007520

Filename

1007520