Application of Artificial Neural Networks in Wave Height prediction in the Persian Gulf

F. Hosseinibalam ； Y. Dehghan

《Information Engineering》 3卷 (2014/12) Pp. 23-26

並列摘要

Accurate wave prediction and supplement is an important task in determining constructions and management of coastal structures. However, determination of wave characteristics is of particular importance. In the present study, the artificial intelligence methodology of neural networks is used to forecast the waves based on learning the characteristics of observed waves, rather than the use of the wind information. The measurements from a single station at Bushehr, North coast of the Persian Gulf, for the period July 2007 - August 2007 were used to train and to validate the employed neural networks. The results obtained show the feasibility of the neural wave characteristics forecasts for 1 and 2 h in terms of the correlation coefficient (0.78–0.9), root mean square error (.03-.07) and scatter index (0.2–0.4). Therefore, the proposed methodology could be successfully used for site-specific forecasts. It is shown that the data produced with the approach developed in this work have statistical properties very close to the properties of the measurements, thus proving that this approach can be used as a reliable tool for wind wave forecasting in coastal areas, complementary to spectral and numerical wave models.

並列關鍵字

Prediction ； Significant Waves Height ； Neural Networks ； Persian Gulf