河南理工大学学报（自然科学版）2013，Vol.32Issue(3)：327-331,5.
应用最小二乘支持向量机进行短期负荷预测的研究与实现
Study and implementation of theory on short-term load forecasting
摘要
Abstract
Weighted least squares fuzzy support-vector-machines method is proposed for short term load forecasting.In order to reflect the characteristic that the nearer data have a greater impact on the predicting value,the membership distribution of a time domain is introduced in a bi-direction,namely,transverse and longitudinal.To overcome the disadvantage of predicting with a fixed coefficient,a fast-leave-one-out method is used to adaptively optimize the parameters on line.The load data from a regional power grid is used for simulating and the applications of different methods are compared.The results show that the proposed method can improve the forecasting accuracy,compared with traditional methods.关键词
最小二乘支持向量机/短期负荷预测/双向加权/自适应Key words
short-term load forecasting/least squares support vector machines/two way weighted/adaptive分类
信息技术与安全科学引用本文复制引用
杨晓忠,司梦..应用最小二乘支持向量机进行短期负荷预测的研究与实现[J].河南理工大学学报（自然科学版）,2013,32(3):327-331,5.基金项目
国家自然科学基金资助项目(10771065). （10771065）
