Journal
JOURNAL OF ADVANCED RESEARCH
Volume 6, Issue 4, Pages 587-592Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jare.2014.02.002
Keywords
Liquefaction; Cone Penetration Test; Minimax Probability Machine; Artificial Intelligence
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The evaluation of liquefaction potential of soil due to an earthquake is an important step in geo-sciences. 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 (qc) and Cyclic Stress Ratio (CSR) as input variables. qc 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 qc and PGA. (C) 2014 Production and hosting by Elsevier B.V. on behalf of Cairo University.
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