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 lon...

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Bibliographic Details
Published in:Ocean engineering 2008-03, Vol.35 (3), p.417-425
Main Authors: Malekmohamadi, I., Ghiassi, R., Yazdanpanah, M.J.
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Buildings. Public works
Computation methods. Tables. Charts
Exact sciences and technology
Hydraulic constructions
Lake Superior
Marine
Numerical wave model
Port facilities and coastal structures. Lighthouses and beacons
Structural analysis. Stresses
Wind waves prediction
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Summary: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.
ISSN:0029-8018
1873-5258
DOI:10.1016/j.oceaneng.2007.09.003