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Minimax Probability Machine
Samui P, Dalkiliç Y.H, Rajadurai H, Jagan J.
Published in IGI Global
Pages: 182 - 210
Liquefaction in soil is one of the other major problems in geotechnical earthquake engineering. This chapter adopts Minimax Probability Machine (MPM) for prediction of seismic liquefaction potential of soil based on Shear Wave Velocity (Vs) data. MPM has been used as a classification technique. Two models (MODEL I and MODEL II) have been adopted. In MODEL I, input variables are Cyclic Stress Ratio (CSR), and Vs MODEL II uses Peck Ground Acceleration (PGA) and Vs as input variables. The developed MPM has been compared with the Artificial Neural Network (ANN) and Support Vector Machine (SVM) models. The developed MPM is a robust tool for determination of liquefaction susceptibility of soil.
About the journal
JournalAdvances in Computational Intelligence and Robotics Handbook of Research on Swarm Intelligence in Engineering
PublisherIGI Global
Open Access0