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Journal of Applied Mathematics
Volume 2014, Article ID 176297, 7 pages
http://dx.doi.org/10.1155/2014/176297
Research Article

Real-Time Ship Motion Prediction Based on Time Delay Wavelet Neural Network

Navigation College, Dalian Maritime University, Dalian 116026, China

Received 16 June 2014; Accepted 3 August 2014; Published 17 August 2014

Academic Editor: Zhiguang Feng

Copyright © 2014 Wenjun Zhang and Zhengjiang Liu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A wavelet neural network with time delay is proposed based on nonlinear autoregressive model with exogenous inputs (NARMAX) model, and the sensitivity method is applied in the selection of network inputs. The inclusion of delayed system information improves the network’s capability of representing the dynamic changes of time-varying systems. The implement of sensitivity analysis reduces the dimension of input as well as the dimension of networks, thus improving its generalization ability. The time delay wavelet neural network was implemented to real-time ship motion prediction, simulations are conducted based on the measured data of vessel “YUKUN,” and the results demonstrate that the feasibility of the proposed method.