Wave hindcasting by coupling numerical model and artificial neural networks
- 作者：I. Malekmohamadi ; R. Ghiassi ; M.J. Yazdanpanah
- 关键词：Wind waves prediction ; Artificial intelligence ; Numerical wave model ; Lake Superior
- 刊名：Ocean Engineering
- 出版年：2008
- 期刊代码：133_00298018
- 类别：et
- 出版时间：March 2008
- 卷：35
- 期：3-4
- 页码：417-425
- 文件大小：418 K
摘要
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.