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An Improved ACO Based Plug-in to Enhance the Interpretability of Fuzzy Rule Bases with Exceptions

  • Pablo Carmona
  • Juan Luis Castro
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5217)

Abstract

In a previous work, the authors proposed, on one hand, an extension on the syntax of fuzzy rules by including new predicates and exceptional rules and, on the other hand, the use of an ant colony optimization algorithm to obtain an optimal set of such rules that describes an initial fuzzy model. The present work proposes several extensions on that algorithm in order to improve the interpretability of the obtained fuzzy model, as well as the computational cost of the algorithm. Experimental results on several initial fuzzy models reveal the gain obtained with each extension and when applied altogether.

Keywords

Local Search Fuzzy Rule Rule Base Fuzzy Rule Base Initial 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 2008

Authors and Affiliations

  • Pablo Carmona
    • 1
  • Juan Luis Castro
    • 2
  1. 1.Department of Computer and Telematics Systems Engineering Industrial Engineering SchoolUniversity of ExtremaduraSpain
  2. 2.Department of Computer Science and Artificial Intelligence Computer and Telecommunication Engineering SchoolUniversity of GranadaSpain

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