Zhang, Wenjun; Liu, Zhengjiang Real-time ship motion prediction based on time delay wavelet neural network. (English) Zbl 1449.93038 J. Appl. Math. 2014, Article ID 176297, 7 p. (2014). Summary: 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. MSC: 93B35 Sensitivity (robustness) 93C43 Delay control/observation systems 93-08 Computational methods for problems pertaining to systems and control theory PDF BibTeX XML Cite \textit{W. Zhang} and \textit{Z. Liu}, J. Appl. Math. 2014, Article ID 176297, 7 p. (2014; Zbl 1449.93038) Full Text: DOI References: [1] Fossen, T. I., Guidance and Control of Ocean Vehicles (1994), New York, NY, USA: John Wiley & Sons, New York, NY, USA [2] Yin, J. C.; Zou, Z. J.; Xu, F.; Wang, N.-N., Online ship roll motion prediction based on grey sequential extreme learning machine, Neurocomputing, 129, 168-174 (2014) [3] Yin, S.; Li, X.; Gao, H.; Kaynak, O., Data-based techniques focused on modern industry: an overview, IEEE Transactions on Industrial Electronics, 99 (2014) [4] Yin, S.; Wang, G.; Karimi, H., Data-driven design of robust fault detection system for wind turbines, Mechatronics, 24, 4, 298-306 (2014) [5] Yin, S.; Yang, X.; Karimi, H. 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