Minimax Probability Machine: A New Tool for Modeling Seismic Liquefaction Data

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Author(s): Pijush Samui (National Institute of Technology Patna, India), Yıldırım Huseyin Dalkiliç (Erzincan University, Turkey), Hariharan Rajadurai (VIT University, India)and J. Jagan (VIT University, India)
Copyright: 2015
Pages: 29
Source title: Handbook of Research on Swarm Intelligence in Engineering
Source Author(s)/Editor(s): Siddhartha Bhattacharyya (RCC Institute of Information Technology, India)and Paramartha Dutta (Visva-Bharati University, India)
DOI: 10.4018/978-1-4666-8291-7.ch006

Keywords: Artificial Intelligence / Computer Science & IT / Engineering Science / Engineering Science Reference

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Abstract

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.

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Minimax Probability Machine: A New Tool for Modeling Seismic Liquefaction Data

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