Short-Term Load Forecasting Based on Gaussian Wavelet SVM

摘要：

Gaussian wavelet support vector machine (SVM) is constructed for short-term load forecasting (STLF).It is proved that the pth-derivative Gaussian wavelet is an admissible translation-invariant kernel function of SVM when p is an even number.The Gaussian wavelet SVM is constructed with wavelet kernel function, and improved stochastic focusing search (SFS) algorithm is used to optimize the parameters of SVM and its kernel function.The experiments of STLF are conducted using the proposed SVM, the conventional Gaussian SVM and Morlet wavelet SVM respectively.The comparison shows that the proposed method is efficient and superior, and has some application value in STLF.

关键词： Gaussian wavelet support vector machine short-term load forecasting Gaussian wavelet kernel stochastic focusing search.

作者: Yongkang Zheng Li Zhu Xing Zou

作者单位: Sichuan Electric Power Research Institute,Chengdu,Sichuan 610072 China Chengdu Electric Power Bureau,Sichuan 610021 China

会议类型: 国际会议

会议名称: 2011 IEEE International Conference on Smart Grid and Clean Energy Technologies(2011 IEEE智能电网与清洁能源技术国际会议 ICSGCE2011)

会议地点: 成都

会议语种:英文

页码: 238-241

在线出版日期: 2011-09-27（万方平台首次上网日期，不代表论文的发表时间）