DocumentCode
518526
Title
Research on short-term electric load forecasting based on fuzzy rules and wavelet neural network
Author
Zhang, Qian
Author_Institution
Dept. of Economic Manage., North China Electr. Power Univ., Baoding, China
Volume
3
fYear
2010
fDate
16-18 April 2010
Abstract
This paper put forward a new method of the fuzzy rules and wavelet neural network model for short-term load forecasting. The neural call function is basis of nonlinear wavelets. We overcome the shortcoming of single train set of fuzzy rules. It can be seen from the example this method can improve effectively the forecast accuracy and speed. The forecast model was tested and the result showed that it was an effective way to forecast short-term electric load.
Keywords
fuzzy set theory; load forecasting; neural nets; power engineering computing; wavelet transforms; forecast accuracy; forecast model; fuzzy rules; neural call function; nonlinear wavelets; short-term electric load forecasting; single train set; wavelet neural network; Fuzzy logic; Fuzzy neural networks; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Load forecasting; Mathematical model; Neural networks; Predictive models; Takagi-Sugeno model; electric Load Forecasting; fuzzy rules;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Engineering and Technology (ICCET), 2010 2nd International Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-6347-3
Type
conf
DOI
10.1109/ICCET.2010.5486371
Filename
5486371
Link To Document