Hierarchical-interpolative fuzzy system construction by Genetic and Bacterial Programming Algorithms

Created by W.Langdon from gp-bibliography.bib Revision:1.4333

  author =       "Krisztian Balazs and Laszlo T. Koczy",
  title =        "Hierarchical-interpolative fuzzy system construction
                 by Genetic and Bacterial Programming Algorithms",
  booktitle =    "IEEE International Conference on Fuzzy Systems (FUZZ
  year =         "2011",
  month =        "27-30 " # jun,
  pages =        "2116--2122",
  address =      "Taipei, Taiwan",
  size =         "7 pages",
  abstract =     "In this paper a method is proposed for constructing
                 hierarchical-interpolative fuzzy rule bases in order to
                 model black box systems defined by input-output pairs,
                 i.e. to solve supervised machine learning problems. The
                 resulting hierarchical rule base is the knowledge base,
                 which is constructed by using evolutionary techniques,
                 namely, Genetic and Bacterial Programming Algorithms.
                 Applying hierarchical-interpolative fuzzy rule bases is
                 an advanced way of reducing the complexity of the
                 knowledge base, whereas evolutionary methods ensure a
                 relatively efficient learning process. This is the
                 reason of the investigation of this combination.",
  keywords =     "genetic algorithms, genetic programming, bacterial
                 programming, black box system, evolutionary technique,
                 hierarchical-interpolative fuzzy rule bases
                 construction, knowledge base, supervised machine
                 learning problem, fuzzy logic, knowledge based systems,
                 learning (artificial intelligence), mathematical
  DOI =          "doi:10.1109/FUZZY.2011.6007594",
  ISSN =         "1098-7584",
  notes =        "Also known as \cite{6007594}",

Genetic Programming entries for Krisztian Balazs Laszlo T Koczy