Prediction of lateral load capacity of piles using extreme learning machine

Abstract

This study presents the development of a predictive model for the lateral load capacity of pile in clay using an artificial intelligence technique, extreme learning machine (ELM). Other artificial intelligence models like artificial neural networks (ANN) (Bayesian regularization neural network (BRNN), differential evolution neural network (DENN)) are also developed to compare the ELM model with them and available empirical models in terms of different statistical criteria. A ranking system is presented to evaluate the present models for identifying the “best” model. Sensitivity analyses are made to identify important inputs contributing to the developed models.