Short-Term Wind Speed Prediction Model of LS-SVM Based on Genetic Algorithm

摘要：

According to nonlinear feature of various factors related to wind speed, the method of least squares support vector machine (LS-SVM) for short-term wind speed prediction was put forward in this paper. The influence of parameters selection of LS-SVM on prediction accuracy was analyzed. The genetic algorithm was adopted to realize parameters optimization of LS-SVM and establish short-term wind speed prediction model of LS-SVM based on Genetic Algorithm. It was verified that the method proposed in this paper can quickly and effectively carry on short-term wind speed prediction by simulation example.

关键词： genetic algorithm LS-SVM wind speed prediction parameters optimal

作者: Han Xiaojuan Zhang Xilin GaoBo

作者单位: College of Control &Compu Engineering North China Electric Powe University Beijing,China Traffic control department Changchun Electric Power Bureau Changchun,China College of foreign languages North China Electric Power University Beijing,China

会议类型: 国际会议

会议名称: 2010 Third International Symposium on Intelligent Ubiquitous and Education(2010年第三届智能普适计算与教育国际研讨会 IUCE 2010)

会议地点: 北京

会议语种:英文

页码: 108-111

在线出版日期: 2010-09-18（万方平台首次上网日期，不代表论文的发表时间）