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Different Approaches to Induce Cooperation in Fuzzy Linguistic Models Under the COR Methodology

  • Jorge Casillas
  • Oscar Cordón
  • Francisco Herrera
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 89)

Abstract

Nowadays, Linguistic Modeling is considered to be one of the most important areas of application for Fuzzy Logic. It is accomplished by linguistic Fuzzy Rule-Based Systems, whose most interesting feature is the interpolative reasoning developed. This characteristic plays a key role in their high performance and is a consequence of the cooperation among the involved fuzzy rules.

A new approach that makes good use of this aspect inducing cooperation among rules is introduced in this chapter: the Cooperative Rules methodology. One of its interesting advantages is its flexibility allowing it to be used with different combinatorial search techniques. Thus, four specific metaheuristics are considered: simulated annealing, tabu search, genetic algorithms and ant colony optimization. Their good performance is shown when solving a real-world problem.

Keywords

Mean Square Error Tabu Search Fuzzy Rule Heuristic Information Linguistic Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Jorge Casillas
    • 1
  • Oscar Cordón
    • 1
  • Francisco Herrera
    • 1
  1. 1.Dept. Computer Science and Artificial Intelligence Computer Engineering SchoolUniversity of GranadaGranadaSpain

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