Prediction of lateral load capacity of piles using extreme learning machine

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.