Open Access
2014 Real-Time Ship Motion Prediction Based on Time Delay Wavelet Neural Network
Wenjun Zhang, Zhengjiang Liu
J. Appl. Math. 2014: 1-7 (2014). DOI: 10.1155/2014/176297

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.

Citation

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Wenjun Zhang. Zhengjiang Liu. "Real-Time Ship Motion Prediction Based on Time Delay Wavelet Neural Network." J. Appl. Math. 2014 1 - 7, 2014. https://doi.org/10.1155/2014/176297

Information

Published: 2014
First available in Project Euclid: 1 October 2014

zbMATH: 07131376
Digital Object Identifier: 10.1155/2014/176297

Rights: Copyright © 2014 Hindawi

Vol.2014 • 2014
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