Wave hindcasting by coupling numerical model and artificial neural networks

By coupling numerical wave model (NWM) and artificial neural networks (ANNs), a new procedure for wave prediction is proposed. In many situations, numerical wave modeling is not justified due to economical consideration. Although incorporation of an ANN model is inexpensive, such a model needs a long time period of wave data for training, which is generally inconvenient to achieve. A proper combination of these two methods could carry the potentials of both. Based on the proposed approach, wave data are generated by a NWM by means of a short period of assumed winds at a concerned point. Then, an ANN is designed and trained using the above-mentioned generated wind-wave data. This ANN model is capable of mapping wind-velocity time series to wave height and period time series with low cost and acceptable accuracy. The method was applied for wave hindcasting to two different sites; Lake Superior and the Pacific Ocean. Simulation results show the superiority of the proposed approach.

[1]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[2]  Takashi Yasuda,et al.  Nearshore wave prediction by coupling a wave model and statistical methods , 2004 .

[3]  David J. Schwab,et al.  Has wind–wave modeling reached its limit? , 2002 .

[4]  M. C. Deo,et al.  Neural networks for wave forecasting , 2001 .

[5]  Jose-Henrique G. M. Alves,et al.  Numerical modeling of wind waves generated by tropical cyclones using moving grids , 2005 .

[6]  Hendrik L. Tolman,et al.  Distributed-memory concepts in the wave model WAVEWATCH III , 2002, Parallel Comput..

[7]  J. D. Agrawal,et al.  On-line wave prediction , 2002 .

[8]  Subba Rao,et al.  Hindcasting of storm waves using neural networks , 2005 .

[9]  O. Makarynskyy,et al.  Improving wave predictions with artificial neural networks , 2004 .

[10]  Chang Lin,et al.  Neural network for wave forecasting among multi-stations , 2002 .

[11]  Mohammad Javad Yazdanpanah,et al.  Modeling the cyclic swelling pressure of mudrock using artificial neural networks , 2006 .

[12]  Yiquan Qi,et al.  Incorporation of artificial neural networks and data assimilation techniques into a third-generation wind-wave model for wave forecasting , 2006 .

[13]  Bernard Widrow,et al.  Adaptive Signal Processing , 1985 .

[14]  Artur Dubrawski,et al.  HPC Strength Prediction Using Artificial Neural Network , 1995 .

[15]  Stanisław Ryszard Massel,et al.  Ocean Surface Waves: Their Physics and Prediction , 1996 .

[16]  Yonas B. Dibike.  Developing generic hydrodynamic models using artificial neural networks , 2002 .

[17]  Makarand Deo,et al.  Real time wave forecasting using neural networks , 1998 .

[18]  Josep R. Medina,et al.  Discussion of "Predictions of Missing Wave Data by Recurrent Neuronets" , 2004 .

[19]  Seyed Jamshid Mousavi,et al.  APPLICATION OF FUZZY INFERENCE SYSTEM IN THE PREDICTION OF WAVE PARAMETERS , 2005 .