Hybridizing Genetic Programming with Orthogonal Least Squares for Modeling of Soil Liquefaction

Created by W.Langdon from gp-bibliography.bib Revision:1.3949

@Article{Gandomi:2013:IREHM,
  author =       "Amir Hossein Gandomi and Amir Hossein Alavi",
  title =        "Hybridizing Genetic Programming with Orthogonal Least
                 Squares for Modeling of Soil Liquefaction",
  journal =      "International Journal of Earthquake Engineering and
                 Hazard Mitigation",
  year =         "2013",
  volume =       "1",
  number =       "1",
  pages =        "2--8",
  month =        sep,
  keywords =     "genetic algorithms, genetic programming, Orthogonal
                 Least Square, Modelling, Soil Liquefaction, Capacity
                 Energy, Formulation",
  ISSN =         "2282-7226",
  URL =          "http://www.praiseworthyprize.it/public/papers/paper.asp?journal=IREHM&idpaper=13484&issue=VOL_1_N_1",
  size =         "7 pages",
  abstract =     "Precise estimation of the strain energy density
                 required to trigger soil liquefaction, denoted as
                 capacity energy, has been the focus of many studies.
                 The main objective of this paper is to develop a robust
                 prediction model for the soil capacity energy using a
                 novel hybrid technique coupling genetic programming
                 with orthogonal least squares, called GP/OLS. The
                 proposed model was developed upon experimental results
                 collected through a literature review. A traditional
                 genetic programming analysis was performed to benchmark
                 the GP/OLS model. The predictions made by the derived
                 model were found to be more accurate than those
                 provided by the genetic programming and other existing
                 models. A subsequent parametric study was carried out
                 and the trends of the results were confirmed via some
                 previous laboratory studies.",
}

Genetic Programming entries for A H Gandomi A H Alavi

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