Fuel Oil Price Forecasting Using Symbiotic Evolutionary Immune Clustering Neural Network

摘要：

Oil price time series is a nonlinear long-memory series,in this paper,a novel clustering method based on the symbiotic evolutionary and the immune programming algorithm is proposed,which is implemented for the prediction of oil price time series.In the design of the neural network,the number and positions of hidden layer are automatically adjust through symbiotic evolutionary and the immune programming.The weights of output layer are decided by the recursive least squares algorithm. The proposed immune clustering neural model has been implemented for New York harbor residual fuel oil prices,and compared with the traditional RBF neural network method.The test results reveal that the symbiotic evolution immune clustering neural network method possesses far superior forecast precision than the traditional method.

关键词： oil price immune programming symbiotic evolutionary neural network

作者: Xin MA

作者单位: School of Management and Economics North China University of Water Conservancy and Electric Power Zhengzhou, China, 450011

会议类型: 国际会议

会议名称: 2009 Second International Conference on Intelligent Computation Technology and Automation(2009 第二届IEEE智能计算与自动化国际会议 ICICTA 2009)

会议地点: 长沙

会议语种:英文

页码: 322-325

在线出版日期: 2009-10-10（万方平台首次上网日期，不代表论文的发表时间）