2026-10-18T23:59:40Zhttps://ebyu-rdlopen.rawdatalibrary.net/oai/requestoai:ebyu-rdlopen.rawdatalibrary.net:ebyu/152872026-10-18T20:30:05Zopenairedrivercom_ebyu_10000col_ebyu_10001Minimax probability machine: A new tool for modeling seismic liquefaction dataSamui, PijushDalkiliç, Yildirim HuseyinRajadurai, HariharanJagan, J.Earthquake engineeringNeural networksSeismologyShear flowSoilsSupport vector machinesWave propagationClassification techniqueCyclic stress ratioGround accelerationsInput variablesLiquefaction susceptibilityMinimax probability machineSeismic liquefactionShear wave velocitySoil liquefactionLiquefaction 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. © 2015, IGI Global. All rights reserved.IGI Global2015Book Chapterhttps://rdlopen.rawdatalibrary.net/r/ebyu/15287https://doi.org/10.4018/978-1-4666-8291-7.ch006978-146668292-4; 1466682914; 978-146668291-7enHandbook of Research on Swarm Intelligence in Engineeringinfo:eu-repo/semantics/openAccessinfo:eu-repo/semantics/bookParthttps://ebyu-rdlopen.rawdatalibrary.net/tr/items/ebyu/15287