Function identification for the intrinsic strength and elastic properties of granitic rocks via genetic programming (GP)

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@Article{Karakus2010,
  author =       "Murat Karakus",
  title =        "Function identification for the intrinsic strength and
                 elastic properties of granitic rocks via genetic
                 programming (GP)",
  journal =      "Computer \& Geosciences",
  year =         "2011",
  volume =       "37",
  number =       "9",
  pages =        "1318--1323",
  ISSN =         "0098-3004",
  DOI =          "doi:10.1016/j.cageo.2010.09.002",
  URL =          "http://www.sciencedirect.com/science/article/B6V7D-51J36C7-1/2/c4feed49145a702b62cf7ac917871262",
  keywords =     "genetic algorithms, genetic programming, Symbolic
                 regression (SR), Elasticity modulus, Compressive
                 strength, Tensile strength, Granitic rocks",
  size =         "6 pages",
  abstract =     "Symbolic Regression (SR) analysis, employing a genetic
                 programming (GP) approach, was used to analyse
                 laboratory strength and elasticity modulus data for
                 some granitic rocks from selected regions in Turkey.
                 Total porosity (n), sonic velocity (vp), point load
                 index (Is) and Schmidt Hammer values (SH) for test
                 specimens were used to develop relations between these
                 index tests and uniaxial compressive strength
                 ([sigma]c), tensile strength ([sigma]t) and elasticity
                 modulus (E). Three GP models were developed. Each GP
                 model was run more than 50 times to optimise the GP
                 functions. Results from the GP functions were compared
                 with the measured data set and it was found that simple
                 functions may not be adequate in explaining strength
                 relations with index properties. The results also
                 indicated that GP is a potential tool for identifying
                 the key and optimal variables (terminals) for building
                 functions for predicting the elasticity modulus and the
                 strength of granitic rocks.",
}

Genetic Programming entries for Murat Karakus

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