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Prediction Of Mean Wave Overtopping At Simple Sloped Breakwaters Using Kernel-Based Methods, Shabnam Hosseinzadeh, Amir Etemad-Shahidi, Ali Koosheh

Research outputs 2014 to 2021

The accurate prediction of the mean wave overtopping rate at breakwaters is vital for a safe design. Hence, providing a robust tool as a preliminary estimator can be useful for practitioners. Recently, soft computing tools such as artificial neural networks (ANN) have been developed as alternatives to traditional overtopping formulae. The goal of this paper is to assess the capabilities of two kernel-based methods, namely Gaussian process regression (GPR) and support vector regression for the prediction of mean wave overtopping rate at sloped breakwaters. An extensive dataset taken from the EurOtop database, including rubble mound structures with permeable core, straight …