Volterra Series-based Neural Network and Its Application in Tap-water Flow Forcast

摘要：

The system of community tap-water is influenced by many factors, which is a typical nonlinear dynamic system. Both neural networks and Volterra series are widely used in nonlinear dynamic system. This paper discusses the relations between Volterra series and BP neural network, and proposes the Volterra seriesbased neural network and the solution of the hight order Volterra series kernel. In this paper, the ARMA model, BP neural network and Volterra series-based neural network are applied to short-term forecast a community tap-water flows. According to the results of the comparison, it shows that the Volterra seriesbased neural network is better than other methods.

关键词： water flow BP neural network Volterra series time series

作者: CHEN Kun LI Lixiong

作者单位: School of Mechatronics Engineering and Automation Shanghai University, Shanghai 200072, P. R. China Shanghai Key Laboratory of Power Station Automation Technology Shanghai University Shanghai 200072,

会议类型: 国际会议

会议名称: 2011 Fourth International Symposium on Computational Interlligence and Design 第四届计算智能与设计国际会议 ISCID 2011

会议地点: 杭州

会议语种:英文

页码: 97-100

在线出版日期: 2011-10-28（万方平台首次上网日期，不代表论文的发表时间）