The Ship Motion Prediction Approach Based on BP Neural Network to Identify Volterra Series Kernels

摘要：

　　Ship motion prediction plays a prominent role in the whole ship motion process.This paper presents a new approach for ship motion prediction.In order to obtain more effective prediction result,the paper studied the BP neural network and Volterra series model,and the chaos characteristics of ship motion time series.A novel method of single-output three-layer BP neural network to identify Volterra series kernels is proposed.Multi-step prediction for the roll motion time series of ship at 135°with the method is accomplished.The simulation analysis demonstrate that the ship motion prediction approach based on BP neural network to identify Volterra series kernels has higher precision,longer prediction time,effectiveness and adaptability,and it can predict the ship motion exactly.

关键词： BP neural network Volterra series Ship motion Prediction Multi-step Prediction

作者: Xiuyan Peng Zhiguo Men Xingmei Wang Shuli Jia

作者单位: Automation College,Harbin Engineering University,Harbin 150001,China Economics and Management College,Harbin Engineering University,Harbin 150001,China Computer Science and Technology College,Harbin Engineering University,Harbin 150001,China

会议类型: 国际会议

会议名称: 第26届中国控制与决策会议(2014 CCDC)

会议地点: 长沙

会议语种:英文

页码: 2324-2328

在线出版日期: 2014-05-31（万方平台首次上网日期，不代表论文的发表时间）