Model uncertainty of SPT-based method for evaluation of seismic soil liquefaction potential using multi-gene genetic programming

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@Article{Muduli:2015:SF,
  author =       "Pradyut Kumar Muduli and Sarat Kumar Das",
  title =        "Model uncertainty of SPT-based method for evaluation
                 of seismic soil liquefaction potential using multi-gene
                 genetic programming",
  journal =      "Soils and Foundations",
  year =         "2015",
  ISSN =         "0038-0806",
  DOI =          "doi:10.1016/j.sandf.2015.02.003",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0038080615000232",
  abstract =     "In this paper, the model uncertainty of the developed
                 standard penetration test (SPT)-based model for
                 evaluation of liquefaction potential of soil is
                 estimated within the framework of the first-order
                 reliability method (FORM). First, an empirical model to
                 determine the cyclic resistance ratio (CRR) of the soil
                 is developed, based on the post-liquefaction SPT data
                 using an evolutionary artificial intelligence
                 technique, multi-gene genetic programming (MGGP). This
                 developed resistance model along with an existing
                 cyclic stress ratio (CSR) model forms a limit state
                 function for reliability-based approach for
                 liquefaction triggering analysis. The uncertainty of
                 the developed limit state model is represented by a
                 log-normal random variable, in terms of its mean and
                 the coefficient of variation, estimated through an
                 extensive reliability analysis following a trial and
                 error approach using Bayesian mapping functions
                 calibrated with a high quality post-liquefaction case
                 history database. A deterministic model with a mapping
                 function relating the probability of liquefaction (PL)
                 and the factor of safety against liquefaction (Fs) is
                 also developed for use in absence of parameter
                 uncertainties. Two examples are presented to compare
                 the present MGGP-based reliability method with the
                 available regression-based reliability method.",
  keywords =     "genetic algorithms, genetic programming, Standard
                 penetration test, Liquefaction index, Probability of
                 liquefaction, Bayesian mapping function, Reliability
                 index, Notional probability",
}

Genetic Programming entries for Pradyut Kumar Muduli Sarat Kumar Das

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