Empirical modeling of plate load test moduli of soil via gene expression programming

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@Article{Mollahasani:2011:CG,
  author =       "Ali Mollahasani and Amir Hossein Alavi and 
                 Amir Hossein Gandomi",
  title =        "Empirical modeling of plate load test moduli of soil
                 via gene expression programming",
  journal =      "Computers and Geotechnics",
  year =         "2011",
  volume =       "38",
  number =       "2",
  pages =        "281--286",
  month =        mar,
  keywords =     "genetic algorithms, genetic programming, Gene
                 expression programming, Soil deformation moduli, Soil
                 physical properties, Nonlinear modelling",
  ISSN =         "0266-352X",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0266352X1000162X",
  DOI =          "doi:10.1016/j.compgeo.2010.11.008",
  size =         "6 pages",
  abstract =     "New empirical models were developed to predict the
                 soil deformation moduli using gene expression
                 programming (GEP). The principal soil deformation
                 parameters formulated were secant (Es) and reloading
                 (Er) moduli. The proposed models relate Es and Er
                 obtained from plate load-settlement curves to the basic
                 soil physical properties. The best GEP models were
                 selected after developing and controlling several
                 models with different combinations of the influencing
                 parameters. The experimental database used for
                 developing the models was established upon a series of
                 plate load tests conducted on different soil types at
                 depths of 1-24m. To verify the applicability of the
                 derived models, they were employed to estimate the soil
                 moduli of a part of test results that were not included
                 in the analysis. The external validation of the models
                 was further verified using several statistical criteria
                 recommended by researchers. A sensitivity analysis was
                 carried out to determine the contributions of the
                 parameters affecting Es and Er. The proposed models
                 give precise estimates of the soil deformation moduli.
                 The Es prediction model provides considerably better
                 results in comparison with the model developed for Er.
                 The simplified formulation for Es significantly
                 outperforms the empirical equations found in the
                 literature. The derived models can reliably be employed
                 for pre-design purposes.",
}

Genetic Programming entries for Ali Mollahasani A H Alavi A H Gandomi

Citations