Application of SVM and Wavelet Neural Network Method for Short-term Power Load Forecasting

被引：3
|
作者：
Zhang, Qian [1 ]
Liu, Tongna [2 ]
机构：
[1] North China Elect Power Univ, Dept Econ Management, Baoding 071000, Hebei, Peoples R China
[2] North China Elect Power Univ, Dept Elect & Commun Engn, Baoding, Hebei, Peoples R China
来源：
2010 2ND INTERNATIONAL CONFERENCE ON COMPUTER AND AUTOMATION ENGINEERING (ICCAE 2010), VOL 2 | 2010年
关键词：
SVM; fuzzy rules; electric Load Forecasting;
D O I：
10.1109/ICCAE.2010.5451579
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper put forward a new method of the SVM 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 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 short- term electric load.
引用
收藏
页码：412 / 416
页数：5
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