Application of Neural Network Ensemble in NonlinearTime-Serials Forecasts

摘要：

Neural network ensemble is developed as a new neural network model in recent years.It is a paradigm where a collection of a finite number of neural networks is trained for the same task.Compared with single neural network,ensemble model has significant improvement in the learning and generalization.This paper proposes the application of neural network ensemble in prediction for Nonlinear TimeSerials. In numerical simulation,the Lorénz systems data are applied. The results show that ensemble network model has a good effect and it is suitable for the prediction of Nonlinear Time Serials.

关键词： time series BP neural networks ensemble model Bagging method cross training

作者: Sijun Peng Siru Zhu

作者单位: School of Science Wuhan University of Technology Wuhan, China Department of the Basics Air Force Radar Academy(AFRA)Wuhan, China

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: 45-47

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）