Power Futures Price Forecasting Based on RBF Neural Network

摘要：

In order to forecast power futures price exactly, a radial basis function neural network (RBF NN) method is used in this paper. The RBK NN method has the advantages of rapid training, generality and simplicity over feed-fontard neural network. The data of Nordic electricity market is adopted for case analysis. Empirical results reveal that the RBK NN method has a more accurate result than back-propagation neural network (BP NN) method. The RBF INN method can effectively forecast power futures price.

关键词： power futures price forecasting radial basis function neural network back-propagation neural network

作者: Kewei Zhang Quansheng Shi

作者单位: Glorious Sun School of Business and Management, Donghua University, Shanghai, 200051, China Institut Institute of Electricity Finance, Shanghai University of Electric Power, Shanghai, 20090, China

会议类型: 国际会议

会议名称: The Second International Conference on Business Intelligence and Financial Engineering(BIFE 2009)(第二届商务智能与金融工程国际会议)

会议地点: 北京

会议语种:英文

页码: 50-52

在线出版日期: 2009-07-24（万方平台首次上网日期，不代表论文的发表时间）