DocumentCode
3307748
Title
Research on Mid-long Load Forecasting Based on SVM and Wavelet Neural Network
Author
Zhang, Qian
Author_Institution
Dept. of Economic Manage., North China Electr. Power Univ., Baoding, China
fYear
2010
fDate
24-25 April 2010
Firstpage
283
Lastpage
287
Abstract
This paper put forward a new method of the SVM and wavelet neural network model for mid-long term load forecasting. The neural call function is basis of nonlinear wavelets. We overcome the shortcoming of single train set of SVM. 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 mid-long term electric load.
Keywords
Artificial neural networks; Estimation error; Load forecasting; Machine vision; Man machine systems; Neural networks; Power generation economics; Predictive models; Risk management; Support vector machines; SVM; electric Load Forecasting; fuzzy rules;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Vision and Human-Machine Interface (MVHI), 2010 International Conference on
Conference_Location
Kaifeng, China
Print_ISBN
978-1-4244-6595-8
Electronic_ISBN
978-1-4244-6596-5
Type
conf
DOI
10.1109/MVHI.2010.154
Filename
5532733
Link To Document