DocumentCode
330309
Title
Load forecasting by fuzzy neural network in Box-Jenkins models
Author
Tang, W.K. ; Wong, M.H. ; Wong, Y.K. ; Chung, T.S.
Author_Institution
Dept. of Electr. Eng., Hong Kong Polytech., Hong Kong
Volume
2
fYear
1998
fDate
11-14 Oct 1998
Firstpage
1738
Abstract
In this paper, the use of fuzzy neural network (FNN) to identify appropriate Box-Jenkins models for the electricity load forecasting in Hong Kong is presented. FNN is found to be suitable for identifying the Box-Jenkins model. By using such model, one can forecast the load accurately
Keywords
autoregressive moving average processes; fuzzy neural nets; load forecasting; power engineering computing; time series; ARMA process; Box-Jenkins models; Hong Kong; fuzzy neural network; load forecasting; time series; Artificial neural networks; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Humans; Intelligent networks; Load forecasting; Power system modeling; Power system planning; Predictive models;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on
Conference_Location
San Diego, CA
ISSN
1062-922X
Print_ISBN
0-7803-4778-1
Type
conf
DOI
10.1109/ICSMC.1998.728145
Filename
728145
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