Minimax probability machine: A new tool for modeling seismic liquefaction data

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Özet

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. © 2015, IGI Global. All rights reserved.

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AlanDeğerDil
dc.contributor.authorSamui, Pijush
dc.contributor.authorDalkiliç, Yildirim Huseyin
dc.contributor.authorRajadurai, Hariharan
dc.contributor.authorJagan, J.
dc.date.accessioned2026-10-18T20:30:05.776792170Z
dc.date.available2026-10-18T20:30:05.776792170Z
dc.date.issued2015
dc.description.abstractLiquefaction 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.
dc.identifier.doi10.4018/978-1-4666-8291-7.ch006
dc.identifier.endpage210
dc.identifier.isbn978-146668292-4; 1466682914; 978-146668291-7
dc.identifier.scopus2-s2.0-84957402026
dc.identifier.startpage182
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/ebyu/15287
dc.language.isoen
dc.publisherIGI Global
dc.relation.ispartofHandbook of Research on Swarm Intelligence in Engineering
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectEarthquake engineering
dc.subjectNeural networks
dc.subjectSeismology
dc.subjectShear flow
dc.subjectSoils
dc.subjectSupport vector machines
dc.subjectWave propagation
dc.subjectClassification technique
dc.subjectCyclic stress ratio
dc.subjectGround accelerations
dc.subjectInput variables
dc.subjectLiquefaction susceptibility
dc.subjectMinimax probability machine
dc.subjectSeismic liquefaction
dc.subjectShear wave velocity
dc.subjectSoil liquefaction
dc.titleMinimax probability machine: A new tool for modeling seismic liquefaction data
dc.typeBook Chapter
dspace.entity.typePublication
rdl.citation.scopus4
rdl.oa.statusgold
rdl.source.indexSCOPUS