Stability assessment of rubble mound breakwaters using extreme learning machine models

Abstract

The stability number of a breakwater can determine the armor unit's weight, which is an important parameter in the breakwater design process. In this paper, a novel and simple machine learning approach is proposed to evaluate the stability of rubble-mound breakwaters by using Extreme Learning Machine (ELM) models. The data-driven stability assessment models were built based on a small size of training samples with a simple establishment procedure. By comparing them with other approaches, the simulation results showed that the proposed models had good assessment performances. The least user intervention and the good generalization ability could be seen as the advantages of using the stability assessment models.