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CPT-based Seismic Liquefaction Potential Evaluation Using Multi-gene Genetic Programming Approach

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Abstract

This study examines the potential of multi-gene genetic programming (MGGP) based classification approach to evaluate liquefaction potential of soil in terms liquefaction index (LI) using a large database from post liquefaction cone penetration test (CPT) measurements and field manifestations. The database consists of CPT measurements; cone tip resistance (q c ), friction ratio (R f ), vertical total stress (σ v ) and vertical effective stress of soil (σ ′ v ), seismic parameters; peak horizontal ground surface acceleration (a max ) and earthquake moment magnitude (M w), and the depth under consideration (z). The MGGP models (Model-I and Model-II) are developed for predicting occurrence and non-occurrence of liquefaction on basis of combination of above input parameters. The performance of the Model-I (95 %) is found to be more efficient compared to available artificial neural network model (91 %) and that of the Model-II (97 %) is found to be at par with the available support vector machine model (97 %) in terms of rate of successful prediction of liquefied and non-liquefied cases for testing data. Using an independent database of 96 cases, the overall classification accuracies are found to be 87 and 86 % for Model-I and Model-II respectively. Sensitivity analyses are made to identify the important parameters contributing to the prediction of LI.

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Authors and Affiliations

  1. Department of Civil Engineering, National Institute of Technology, Rourkela, 769008, Odisha, India

    Pradyut Kumar Muduli & Sarat Kumar Das

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  1. Pradyut Kumar Muduli
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  2. Sarat Kumar Das
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Correspondence to Pradyut Kumar Muduli.

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Muduli, P.K., Das, S.K. CPT-based Seismic Liquefaction Potential Evaluation Using Multi-gene Genetic Programming Approach. Indian Geotech J 44, 86–93 (2014). https://doi.org/10.1007/s40098-013-0048-4

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  • DOI: https://doi.org/10.1007/s40098-013-0048-4

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