Solving variational and Cauchy problems with self-configuring genetic programming algorithm

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Sergei V. Burakov and Eugene S. Semenkin",
  title =        "Solving variational and Cauchy problems with
                 self-configuring genetic programming algorithm",
  journal =      "International Journal of Innovative Computing and
  year =         "2013",
  volume =       "5",
  number =       "3",
  pages =        "152--162",
  note =         "Special Issue on: BIOMA 2012 Advances in Bio-inspired
                 Computing. Guest Editors: Assistant Professor Jurij
                 Silc and Associate Professor Bogdan Filipic",
  keywords =     "genetic algorithms, genetic programming, Ordinary
                 differential equations; Cauchy problem; variational
                 problem; numeric methods; genetic programming
                 algorithm; self-configuration.",
  ISSN =         "1751-648X",
  DOI =          "doi:10.1504/IJICA.2013.055931",
  abstract =     "It is suggested to use genetic programming techniques
                 for solving Cauchy problem and variational problem that
                 allows getting the exact analytical solution if it does
                 exist and an approximate analytical expression
                 otherwise. Features of solving process with this
                 approach are considered. Results of numerical
                 experiments are given. The approach improvement is
                 fulfilled by adopting the self-configuring genetic
                 programming algorithm that does not require extra
                 efforts for choosing its effective settings but
                 demonstrates the competitive performance",
  notes =        "Acceptance Date: 30 Nov 2012 IJICA


Genetic Programming entries for Sergei V Burakov Eugene Semenkin