Prediction of mean wave overtopping at simple sloped breakwaters using kernel-based methods

Prediction of mean wave overtopping at simple sloped breakwaters using kernel-based methods

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...

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Bibliographic Details
Main Authors: Shabnam Hosseinzadeh, Amir Etemad-Shahidi, Ali Koosheh
Format: Article
Language:English
Published: IWA Publishing 2021-09-01
Series:Journal of Hydroinformatics
Subjects:
ard-mattern5/2-gaussian process regression (gpr)
ffbp-artificial neural network (ann)
kernel-based models
mean wave overtopping
rbf-support vector regression (svr)
simple sloped breakwaters
Online Access:http://jh.iwaponline.com/content/23/5/1030

Internet

http://jh.iwaponline.com/content/23/5/1030

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