Ship Rolling Motion Prediction Based on Wavelet Neural Network

Yu Chao Wang; Fan Ming Liu; Hui Xuan Fu

doi:10.4028/www.scientific.net/AMM.190-191.724

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 190-191Ship Rolling Motion Prediction Based on Wavelet...

Ship Rolling Motion Prediction Based on Wavelet Neural Network

Abstract:

The traditional time series predictive models are not able to achieve a satisfying prediction effect in the problem of a non-linear system and nonstationary time series. To solve these problems, ship course time series prediction, which is based on back propagation wavelet neural network structure and algorithm, was proposed. It combined wavelet analysis and neural network characteristics, and employed the nonlinear Morlet wavelet radices as the activation function. This method was applied to ship rolling motion prediction, and simulation results showed the validity to improving the prediction accuracy.

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Periodical:

Applied Mechanics and Materials (Volumes 190-191)

Pages:

724-728

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.190-191.724

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Online since:

July 2012

Authors:

Yu Chao Wang, Fan Ming Liu, Hui Xuan Fu

Keywords:

BP Neural Network (BPNN), Real-Time Prediction, Ship Rolling Motion, Wavelet Neural Network (WNN)

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References

[1] X. Zhao, R. Xu and C. Kwan. "SHIP-MOTION PREDICTION: ALGORITHMS AND SIMULATION RESULTS," IEEE International Conference on Acoustics, Speech, and Signal Processing, Canada: 2004, pp.125-128.

DOI: 10.1109/icassp.2004.1327063

Google Scholar

[2] A. Khan, C. Bil, K.E. Marion. "Ship motion prediction for launch and recovery of air vehicles", Proceedings of MTS/IEEE OCEANS, United states: 2005, pp.2795-2801.

DOI: 10.1109/oceans.2005.1640198

Google Scholar

[3] Z. Qinhua, B. Albert. "Neural Network, Adaptive Wavelet Networks," IEEE Trans on Neural Networks, 3(1992) 889-898.

Google Scholar

[4] J. Zhang, G. G. Walter, Y. Miao, and W. N. W. Lee, "Wavelet neural networks for function learning," IEEE Trans. Signal Process, United States：1995, pp.1485-1497.

DOI: 10.1109/78.388860

Google Scholar

[5] S. A. Billings and H.L. Wei, "A new class of wavelet networks for nonlinear system identification," IEEE Trans Neural Networks, 2005, pp.862-874.

DOI: 10.1109/tnn.2005.849842

Google Scholar

[6] L. Fang, J. Desheng, Q. Fangpeng, "Chaotic Time Series Forecast Modeling Based on Biased Wavelet Neural Network" International Conference on Computer Science and Software Engineering, China: 2008, pp.855-858.

DOI: 10.1109/csse.2008.787

Google Scholar

[7] LIU Sheng, YU Ping. Application of H∞ Control to Ship Steering System. Journal of Marine Science and Application, 2006, pp.5-9.

Google Scholar