Assessment of Using Artificial Neural Network and Support Vector Machine Techniques for Predicting Wave-Overtopping Discharges at Coastal Structures

Author:

Alshahri Abdullah H.1ORCID,Elbisy Moussa S.2ORCID

Affiliation:

1. Civil Engineering Department, College of Engineering, Taif University, Taif 21944, Saudi Arabia

2. Civil Engineering Department, College of Engineering and Islamic Architecture, Umm Al-Qura University, Makkah 24352, Saudi Arabia

Abstract

Coastal defence structures play a crucial role in protecting coastal communities against extreme weather and flooding. This study investigates artificial neural network-based approaches, such as multilayer perceptron neural network (MPNN), cascade correlation neural network (CCNN), general regression neural network (GRNN), and support vector machine (SVM) with radial-bias function for estimating the wave-overtopping discharge at coastal structures featuring a straight slope ‘without a berm’. The newly developed EurOtop database was used for this study. Discriminant analysis was performed using the principal component analysis method, and Taylor diagram visualisation and other statistical analyses were performed to evaluate the models. For predicting wave-overtopping discharge, the GRNN yielded highly accurate results. As compared to the other models, the scatter index of the GRNN (0.353) was lower than that of the SVM (0.585), CCNN (0.791), and MPNN (1.068) models. In terms of the R-index, the GRNN (0.991) was superior to the SVM (0.981), CCNN (0.958), and MPNN (0.922). The GRNN results were compared with those of the previous models. An in-depth sensitivity analysis was conducted to determine the significance of each predictive variable. Furthermore, sensitivity analysis was conducted to select the optimal validation method for the GRNN model. The results revealed that both the validation methods were highly accurate, with the leave-one-out validation method outperforming the cross-validation method by only a small margin.

Funder

Taif University Deanship of Scientific Research Project

Publisher

MDPI AG

Subject

Ocean Engineering,Water Science and Technology,Civil and Structural Engineering

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