Modeling intermolecular potential of He-F2 dimer from symmetry-adapted perturbation theory using multi-gene genetic programming

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@Article{Amiri:2013:SI,
  author =       "M. Amiri and M. Eftekhari and M. Dehestani and 
                 A. Tajaddini",
  title =        "Modeling intermolecular potential of {He-F2} dimer
                 from symmetry-adapted perturbation theory using
                 multi-gene genetic programming",
  journal =      "Scientia Iranica",
  year =         "2013",
  volume =       "20",
  number =       "3",
  pages =        "543--548",
  ISSN =         "1026-3098",
  DOI =          "doi:10.1016/j.scient.2012.12.040",
  URL =          "http://www.sciencedirect.com/science/article/pii/S1026309813000758",
  abstract =     "Abstract Any molecular dynamical calculation requires
                 a precise knowledge of interaction potential as an
                 input. In an appropriate form, such that the potential,
                 with respect to the coordinates, can be evaluated
                 easily and accurately at arbitrary geometries (in our
                 study parameters for geometry are R and theta), a good
                 potential energy expression can offer the exact
                 intermolecular behaviour of systems. There are many
                 methods to create mathematical expressions for the
                 potential energy. In this study for the first time, we
                 used the Multi-gene Genetic Programming (MGGP) method
                 to generate a potential energy model for the He-F2
                 system. The MGGP method is one of the most powerful
                 methods used for non-linear regression problems. A
                 dataset of size 714 created by the SAPT 2008 program is
                 used to generate models of MGGP. The results obtained
                 show the power of MGGP for producing an efficient
                 nonlinear regression model, in terms of accuracy and
                 complexity.",
  keywords =     "genetic algorithms, genetic programming, Potential
                 energy, SAPT, MGGP, Lennard-Jones potential",
}

Genetic Programming entries for M Amiri Mehdi Eftekhari M Dehestani Azita Tajaddini

Citations