SHORT-TERM POWER LOAD FORECASTING BASE ON LS-SVM

摘要：

In order to solve the Short-term Load Forecasting problems in Power Systems, this article puts forward the Least Squares Support Vector Machines improved model by selecting the appropriate Gauss kernel function and proposing the error calculation analytical method, thus reduces the computational complicate problems when large amount of data is input in Short-term Power Load Forecasting. An example is given to prove the validity of the algorithm.

关键词： Power System Short-term Load Forecasting LS-SVM

作者: Liu Bin Xu Guang

作者单位: Electrical and Information Engineering College Shaanxi University of Science and Technology Xian, China

会议类型: 国际会议

会议名称: 2010 International Conference of Informationa Science and Management Engineering(2010年信息科学与管理工程国际学术会议 ISME 2010)

会议地点: 西安

会议语种:英文

页码: 311-314

在线出版日期: 2010-08-07（万方平台首次上网日期，不代表论文的发表时间）