Research on support vector machine model based on grey relation analysis for daily load forecasting

被引：0
|
作者：
Niu, DX [1 ]
Wang, Q [1 ]
Li, JC [1 ]
机构：
[1] N China Elect Power Univ, Sch Business Adm, Baoding 071003, Peoples R China
来源：
Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Vols 1-9 | 2005年
关键词：
daily load forecasting; support vector machine; grey relation analysis;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Regarding to the daily load forecasting, the sample selection and data preprocessing are crucial to its' precision. In this paper, the grey relation analysis method is adopted to search the historical data points whose variation trends are the same as the predict point. The variation trend of each point is represented by load values of the neighboring points. As no influencing factors are used in this process, the model is both simple and practical. Finally a support vector machine model is created on the basis of the selected data points. Due to their similar trends of the selected points, the forecasting precision is raised greatly. The present method synthesizes the advantages of grey relation analysis and support vector machine. The practical examples show that the model established in this paper is feasible and effective. Compared with other models, it has a better precision performance and a higher computing speed.
引用
收藏
页码：4254 / 4259
页数：6
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