Application of Soft Computing in Geotechnical Earthquake Engineering

Abstract

AbstractEngineers use various soft computing techniques for solving different problems in geotechnical earthquake engineering. This paper will investigate the application of different soft computing techniques {artificial neural network (ANN), support vector machine (SVM), least square support vector machine (LSSVM), genetic programing (GP), relevance vector machine (RVM), multivariate adaptive regression spline (MARS), extreme learning machine (ELM), adaptive neurofuzzy inference system (ANFIS), minimax probability machine regression (MPMR), Gaussian process regression (GPR), adaptive neurofuzzy inference system (ANFIS)} in different fields of geotechnical earthquake engineering such as liquefaction, lateral spreading, seismic slope stability and reliability. The advantages of different soft computing techniques will be described.KeywordsArtificial neural networkSupport vector machineRelevance vector machineLeast square support vector machineGeotechnical earthquake engineering