Evolving Takagi-Sugeno-Kang Fuzzy Systems using Multi Population Grammar-Guided Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{conf/ijcci/TsakonasG11,
  author =       "Athanasios Tsakonas and Bogdan Gabrys",
  title =        "Evolving Takagi-Sugeno-Kang Fuzzy Systems using Multi
                 Population Grammar-Guided Genetic Programming",
  booktitle =    "Proceedings of the International Conference on
                 Evolutionary Computation Theory and Applications and
                 the Proceedings of the International Conference on
                 Fuzzy Computation Theory and Applications [parts of the
                 International Joint Conference on Computational
                 Intelligence (IJCCI (ECTA-FCTA) 2011)",
  year =         "2011",
  editor =       "Agostinho C. Rosa and Janusz Kacprzyk and 
                 Joaquim Filipe and Antonio Dourado Correia",
  pages =        "278--281",
  address =      "Paris, France",
  month =        "24-26 " # oct,
  publisher =    "SciTePress",
  keywords =     "genetic algorithms, genetic programming, fuzzy rule
                 based systems, evolutionary computation:poster",
  isbn13 =       "978-989-8425-83-6",
  URL =          "http://eprints.bournemouth.ac.uk/18460/1/Tsak%2DGabr%2DECTA%2D2011%2DCamRdy.pdf",
  URL =          "http://eprints.bournemouth.ac.uk/18460/",
  URL =          "http://dblp.l3s.de/d2r/page/publications/conf/ijcci/TsakonasG11",
  size =         "4 pages",
  abstract =     "This work proposes a novel approach for the automatic
                 generation and tuning of complete Takagi-Sugeno-Kang
                 fuzzy rule based systems. The examined system aims to
                 explore the effects of a reduced search space for a
                 genetic programming framework by means of grammar
                 guidance that describes candidate structures of fuzzy
                 rule based systems. The presented approach applies
                 context-free grammars to generate individuals and
                 evolve solutions through the search process of the
                 algorithm. A multi-population approach is adopted for
                 the genetic programming system, in order to increase
                 the depth of the search process. Two candidate grammars
                 are examined in one regression problem and one system
                 identification task. Preliminary results are included
                 and discussion proposes further research directions.",
  notes =        "ECTA http://www.ecta.ijcci.org/
                 http://www.ijcci.org/IJCCI2011/",
  bibdate =      "2012-05-03",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/conf/ijcci/ijcci2011-2.html#TsakonasG11",
}

Genetic Programming entries for Athanasios D Tsakonas Bogdan Gabrys

Citations