Hierarchical fuzzy system modeling by Genetic and Bacterial Programming approaches

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  author =       "Krisztian Balazs and Janos Botzheim and 
                 Laszlo T. Koczy",
  title =        "Hierarchical fuzzy system modeling by Genetic and
                 Bacterial Programming approaches",
  booktitle =    "IEEE International Conference on Fuzzy Systems
                 (FUZZ-IEEE 2010)",
  year =         "2010",
  address =      "Barcelona, Spain",
  month =        "18-23 " # jul,
  pages =        "1866--1871",
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-1-4244-6920-8",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/botzheim/Balazs_2010_ieee-fuzz.pdf",
  DOI =          "doi:10.1109/FUZZY.2010.5584220",
  size =         "6 pages",
  abstract =     "In this paper a method is proposed for constructing
                 hierarchical fuzzy rule bases in order to model black
                 box systems defined by input-output pairs, i.e. to
                 solve supervised machine learning problems. The
                 resultant hierarchical rule base is the knowledge base,
                 which is constructed by using structure constructing
                 evolutionary techniques, namely, Genetic and Bacterial
                 Programming Algorithms. Applying hierarchical fuzzy
                 rule bases is a 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.",
  notes =        "WCCI 2010. Also known as \cite{5584220}",

Genetic Programming entries for Krisztian Balazs Janos Botzheim Laszlo T Koczy