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

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

Pijush Samui, Yıldırım Huseyin Dalkiliç, Hariharan Rajadurai, J. Jagan
Copyright: © 2015 |Pages: 29
ISBN13: 9781466682917|ISBN10: 1466682914|EISBN13: 9781466682924
DOI: 10.4018/978-1-4666-8291-7.ch006
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MLA

Samui, Pijush, et al. "Minimax Probability Machine: A New Tool for Modeling Seismic Liquefaction Data." Handbook of Research on Swarm Intelligence in Engineering, edited by Siddhartha Bhattacharyya and Paramartha Dutta, IGI Global, 2015, pp. 182-210. https://doi.org/10.4018/978-1-4666-8291-7.ch006

APA

Samui, P., Dalkiliç, Y. H., Rajadurai, H., & Jagan, J. (2015). Minimax Probability Machine: A New Tool for Modeling Seismic Liquefaction Data. In S. Bhattacharyya & P. Dutta (Eds.), Handbook of Research on Swarm Intelligence in Engineering (pp. 182-210). IGI Global. https://doi.org/10.4018/978-1-4666-8291-7.ch006

Chicago

Samui, Pijush, et al. "Minimax Probability Machine: A New Tool for Modeling Seismic Liquefaction Data." In Handbook of Research on Swarm Intelligence in Engineering, edited by Siddhartha Bhattacharyya and Paramartha Dutta, 182-210. Hershey, PA: IGI Global, 2015. https://doi.org/10.4018/978-1-4666-8291-7.ch006

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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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