Identifying fuzzy models utilizing genetic programming

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@Article{Bastian:2000:FSS,
  author =       "Andreas Bastian",
  title =        "Identifying fuzzy models utilizing genetic
                 programming",
  journal =      "Fuzzy Sets and Systems",
  volume =       "113",
  pages =        "333--350",
  year =         "2000",
  number =       "3",
  month =        "1 " # aug,
  keywords =     "genetic algorithms, genetic programming, System
                 identification, Fuzzy modeling",
  URL =          "http://www.sciencedirect.com/science/article/B6V05-4234BFC-1/1/261a04fa056f3f0dfe0fb79a773a971a",
  abstract =     "Fuzzy models offer a convenient way to describe
                 complex nonlinear systems. Moreover, they permit the
                 user to deal with uncertainty and vagueness. Due to
                 these advantages fuzzy models are employed in various
                 fields of applications, e.g. control, forecasting, and
                 pattern recognition. Nevertheless, it has to be
                 emphasised that the identification of a fuzzy model is
                 a complex optimisation task with many local minima.
                 Genetic programming provides a way to solve such
                 complex optimization problems. In this work, the use of
                 genetic programming to identify the input variables,
                 the rule base and the involved membership functions of
                 a fuzzy model is proposed. For this purpose, several
                 new reproduction operators are introduced.",
}

Genetic Programming entries for Andreas Bastian

Citations