Title :
Short-term Load Forecasting Based on Embedded Support Vector Machine Combined with DB4 Wavelet
Author :
Gao, Rong ; Liu, Xiao-hua
Author_Institution :
Sch. of Math. & Inf., Yantai Normal Univ.
Abstract :
A method based on DB4 wavelet and support vector machine was proposed. Adapted wavelet soft-thresholding method was used to preprocessing load data according to the principle of wavelet denosing. Denoised series was decomposed using DB4 wavelet, each sub-series was embedded a matching support vector machines. The result which was modeled using support vector machine directly and the above result was compared simulation show the effectiveness of the proposed method
Keywords :
load forecasting; power engineering computing; support vector machines; wavelet transforms; DB4 wavelet; adapted wavelet soft-thresholding method; embedded support vector machine; kernel function; load data preprocessing; load forecasting; wavelet denosing; Automation; Intelligent control; Kernel; Load forecasting; Mathematics; Support vector machines; DB4 wavelet; embedded support vector machine; kernel functions; load forecasting;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1713421
