CONSTRUCTING A MULTI-PHASE NEURAL COMBINATORIAL PREDICTOR FOR TIME SERIES FORECASTING

摘要：

In this study. A four-phase neural network combinatorial procedure is proposed for time series forecasting.Some methods for formulating combinatorial predictors-including the methods of preprocessing time series data,generating a set of neural network predictors by varying training data and network type,selecting combination members from a set of individual neural predictors,and combining selected members into an aggregated predictor-are presented.For verification,some real-world experiments are conducted. The empirical results reveal that the proposed multi-phase procedrife allows one to design an effective neural network combinatorial forecasting approach for time series prediction.

作者: LEAN YU SHOUYANG WANG KIN KEUNG LAI

作者单位: Institue of Systems Science,Academy of Mathematics and Systems Science,Chinese Academy of Sciences,B Department of Management Sciences,City University of Hong Kong Tat Chee Avenue,Kowloon,Hong Kong,Chi

会议类型: 国际会议

会议名称: The 10th International Symposium on Knowledge and System Sciences,The 6th International Conference on Knowledge Management(第10届国际知识与系统科学大会、第6届知识管理国际会议)

会议地点: 香港

会议语种:英文

页码: 138-149

在线出版日期: 2009-12-03（万方平台首次上网日期，不代表论文的发表时间）