Evaluation of Liquefaction Potential of Soil Based on Shear Wave Velocity Using Multi-Gene Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InCollection{Muduli:2015:hbgpa,
  author =       "Pradyut Kumar Muduli and Sarat Kumar Das",
  title =        "Evaluation of Liquefaction Potential of Soil Based on
                 Shear Wave Velocity Using Multi-Gene Genetic
                 Programming",
  booktitle =    "Handbook of Genetic Programming Applications",
  publisher =    "Springer",
  year =         "2015",
  editor =       "Amir H. Gandomi and Amir H. Alavi and Conor Ryan",
  chapter =      "12",
  pages =        "309--343",
  keywords =     "genetic algorithms, genetic programming, Shear wave
                 velocity, Liquefaction index, Multi-gene genetic
                 programming, Probability of liquefaction, Bayesian
                 mapping function",
  isbn13 =       "978-3-319-20882-4",
  DOI =          "doi:10.1007/978-3-319-20883-1_12",
  abstract =     "In this chapter, liquefaction potential of soil is
                 evaluated within deterministic as well as probabilistic
                 framework based on the post-liquefaction shear wave
                 velocity (V_s) measurement data using a soft computing
                 technique, multi-gene genetic programming (MGGP), which
                 is a variant genetic programming (GP). On the basis of
                 the developed limit state function by the MGGP, a
                 mapping function is presented to correlate probability
                 of liquefaction (P_L) with factor of safety (F_s)
                 against liquefaction using Bayesian theory of
                 conditional probability. Two examples are presented to
                 compare the developed MGGP-based deterministic as well
                 as probabilistic methods with those of available
                 artificial neural network (ANN)-based methods. The
                 findings from the above two examples confirm that
                 MGGP-based methods are more accurate than the ANN-based
                 methods in predicting the liquefied as well as
                 non-liquefied cases.",
}

Genetic Programming entries for Pradyut Kumar Muduli Sarat Kumar Das

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