Combination method of rough set and genetic programming

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  author =       "Yasser Hassan and Eiichiro Tazaki",
  title =        "Combination method of rough set and genetic
  journal =      "Kybernetes",
  year =         "2004",
  volume =       "33",
  number =       "1",
  pages =        "98--117",
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "0368-492X",
  DOI =          "doi:10.1108/03684920410514544",
  abstract =     "A methodology for using rough set for preference
                 modelling in decision problem is presented in this
                 paper; where we will introduce a new approach for
                 deriving knowledge rules from database based on rough
                 set combined with genetic programming. Genetic
                 programming belongs to the most new techniques in
                 applications of artificial intelligence. Rough set
                 theory, which emerged about 20 years back, is nowadays
                 a rapidly developing branch of artificial intelligence
                 and soft computing. At the first glance, the two
                 methodologies that we discuss are not in common. Rough
                 set construct is the representation of knowledge in
                 terms of attributes, semantic decision rules, etc. On
                 the contrary, genetic programming attempts to
                 automatically create computer programs from a
                 high-level statement of the problem requirements. But,
                 in spite of these differences, it is interesting to try
                 to incorporate both the approaches into a combined
                 system. The challenge is to obtain as much as possible
                 from this association",

Genetic Programming entries for Yasser Fouad Hassan Eiichiro Tazaki