Time Series Prediction Using a Recursive Algorithm of a Combination of Genetic Programming and Constant Optimization

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@Article{pandyaworayan_2002_MENDELfu,
  author =       "Witthaya Panyaworayan and Georg Wuetschner",
  title =        "Time Series Prediction Using a Recursive Algorithm of
                 a Combination of Genetic Programming and Constant
                 Optimization",
  journal =      "Facta Universitatis. Series: Electronics and
                 Energetics",
  year =         "2002",
  volume =       "15",
  number =       "2",
  pages =        "265--279",
  month =        aug,
  keywords =     "genetic algorithms, genetic programming, Time series
                 prediction, sunspot numbers",
  ISSN =         "0353-3670",
  URL =          "http://factaee.elfak.ni.ac.yu/fu2k22/11wp.pdf",
  size =         "15 pages",
  abstract =     "In this paper we present a prediction process of Time
                 Series using a combination of Genetic Programming and
                 Constant Optimisation. The Genetic Programming will be
                 used to evolve the structure of the prediction
                 function, whereas the Constant Optimization will
                 determine the numerical parameters of the prediction
                 function. The prediction process is applied
                 recursively. In each recursion step, a sub-prediction
                 function is evolved. At the end of the iteration all
                 sub-prediction functions form the final prediction
                 function. The avoiding of a major problem in the
                 prediction called over-fitting is also described in
                 this article.",
  notes =        "See also \cite{pandyaworayan_2002_MENDEL}",
}

Genetic Programming entries for Witthaya Panyaworayan Georg Wuetschner

Citations