Least Squares Support Vector Mechanics to Predict the Stability Number of Rubble-Mound Breakwaters

Water

Nuray Gedik¹ 

[1] Civil Engineering Department, Faculty of Engineering, Balikesir University, 10145 Balikesir, Turkey;

关键词: rubble-mound breakwater;    least squares support vector mechanics;    stability number;    particle swarm optimization;   

DOI  :  10.3390/w10101452

来源: DOAJ

【 摘 要 】

In coastal engineering, empirical formulas grounded on experimental works regarding the stability of breakwaters have been developed. In recent years, soft computing tools such as artificial neural networks and fuzzy models have started to be employed to diminish the time and cost spent in these mentioned experimental works. To predict the stability number of rubble-mound breakwaters, the least squares version of support vector machines (LSSVM) method is used because it can be assessed as an alternative one to diverse soft computing techniques. The LSSVM models have been operated through the selected seven parameters, which are determined by Mallows’ Cp approach, that are, namely, breakwater permeability, damage level, wave number, slope angle, water depth, significant wave heights in front of the structure, and peak wave period. The performances of the LSSVM models have shown superior accuracy (correlation coefficients (CC) of 0.997) than that of artificial neural networks (ANN), fuzzy logic (FL), and genetic programming (GP), that are all implemented in the related literature. As a result, it is thought that this study will provide a practical way for readers to estimate the stability number of rubble-mound breakwaters with more accuracy.

【 授权许可】

Unknown