The deep wave height is a major parameter that affects many offshore activities such as offshore oil drilling, navigational courses, oil platform installations. This situation leads us to get accurate wave data for any targeted operational area as Alexandria at north coast of Egypt in this case of study in order to avoid its negative impacts and to handle any activity in very safe way. In this paper, we used nonlinear regression method to analyze wave heights data and this analysis resulted in deduction of an equation that help us to predict future deep wave heights for the same region. This study aimed to evaluate the results of this method as well as to make a comparison for its results with those obtained from support vector machine method that were used before in past paper for the same region data. The results explained that the use of nonlinear regression methods gave a good result compared to the results from support vector machine. However, this study revealed that support vector machine based on radial basis function is still more superior to nonlinear regression methods. Their results indicated that the error statistics of regression methods are generally within an acceptable range. Therefore, regression methods can be used successfully for prediction of wave heights.

wave heights prediction, nonlinear regression method, support vector machines, radial basis function, Alexandria deep wave heights, offshore structures.