Journal of Applied Mathematics
- J. Appl. Math.
- Volume 2014 (2014), Article ID 176297, 7 pages.
Real-Time Ship Motion Prediction Based on Time Delay Wavelet Neural Network
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.
J. Appl. Math., Volume 2014 (2014), Article ID 176297, 7 pages.
First available in Project Euclid: 1 October 2014
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Zhang, Wenjun; Liu, Zhengjiang. Real-Time Ship Motion Prediction Based on Time Delay Wavelet Neural Network. J. Appl. Math. 2014 (2014), Article ID 176297, 7 pages. doi:10.1155/2014/176297. https://projecteuclid.org/euclid.jam/1412177811