title: A unified classification model for modeling of seismic liquefaction potential of soil based on CPT.
abstract: The evaluation of liquefaction potential of soil due to an earthquake is an important step in geosciences. This article examines the capability of Minimax Probability Machine (MPM) for the prediction of seismic liquefaction potential of soil based on the Cone Penetration Test (CPT) data. The dataset has been taken from Chi-Chi earthquake. MPM is developed based on the use of hyperplanes. It has been adopted as a classification tool. This article uses two models (MODEL I and MODEL II). MODEL I employs Cone Resistance (q c) and Cyclic Stress Ratio (CSR) as input variables. q c and Peak Ground Acceleration (PGA) have been taken as inputs for MODEL II. The developed MPM gives 100% accuracy. The results show that the developed MPM can predict liquefaction potential of soil based on q c and PGA.
authors.affiliation: Centre for Disaster Mitigation and Management, VIT University, Vellore 632014, India.
authors.forename: Pijush
authors.initials: P
authors.lastname: Samui
authors.affiliation: Annai Mira College of Engineering and Technology, Department of Computer Science, Arapakam, Vellore 632517, India.
authors.forename: R
authors.initials: R
authors.lastname: Hariharan
keywords: Artificial Intelligence; Cone Penetration Test; Liquefaction; Minimax Probability Machine