SPT-Based Probabilistic Method for Evaluation of Liquefaction Potential of Soil Using Multi-Gene Genetic Programming

Abstract

The present study discusses about evaluation of liquefaction potential of soil within a probabilistic framework based on the standard penetration test (SPT) dataset using evolutionary artificial intelligence technique, multi-gene genetic programming (MGGP). Based on the developed limit state function, a relationship is given between probability of liquefaction and factor of safety against liquefaction using Bayesian theory. This Bayesian mapping function is further used to develop a probabiliy based design chart for evaluation of liquefaction potential of soil. Using an independent database the efficacy of present MGGP based probabilistic model is compared with the available artificial neural network (ANN) and statistical models in terms of rate of successful prediction of liquefaction and non-liquefaction cases. The proposed MGGP based model is found to be more accurate compared to other models.