Evolving fuzzy detectives: an investigation into the evolution of fuzzy rules

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "P. J. Bentley",
  booktitle =    "Soft Computing in Industrial Applications",
  publisher =    "Springer-Verlag London",
  title =        "Evolving fuzzy detectives: an investigation into the
                 evolution of fuzzy rules",
  year =         "1999",
  editor =       "Yukinori Suzuki and Seppo J. Ovaska and 
                 Takeshi Furuhashi and Rajkumar Roy and Yasuhiko Dote",
  pages =        "89--106",
  keywords =     "genetic algorithms, genetic programming, evolution,
                 fuzzy, industrial, industrial application, Rules",
  ISBN =         "1-85233-293-X",
  URL =          "http://www.cs.ucl.ac.uk/staff/P.Bentley/BECH4.pdf",
  URL =          "http://www.amazon.com/Computing-Industrial-Applications-Yukinori-Suzuki/dp/185233293X",
  size =         "18 pages",
  abstract =     "This paper explores the use of genetic programming to
                 evolve fuzzy rules for the purpose of fraud detection.
                 The fuzzy rule evolver designed during this research is
                 described in detail. Four key system evaluation
                 criteria are identified: intelligibility, speed,
                 handling noisy data, and accuracy. Three sets of
                 experiments are then performed in order to assess the
                 performance of different components of the system, in
                 terms of these criteria. The paper concludes: 1. that
                 many factors affect accuracy of classification, 2.
                 intelligibility and processing speed mainly seem to be
                 affected by the fuzzy membership functions and 3. noise
                 can cause loss of accuracy proportionate to the square
                 of noise.",

Genetic Programming entries for Peter J Bentley