Genetic-Fuzzy Modeling on High Dimensional Spaces

  • Joon-Min Gil
  • Seong-Hoon Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4251)


In this paper, in order to reduce the explosive increase of the search space as the input dimension grows, we present a new representation method for the structure of fuzzy rules, a graph structured fuzzy system. The graph structured fuzzy system can flexibly cope with the increase of the input space by selecting these fuzzy rules that significantly affects the input space among the whole set of fuzzy rules. To obtain the optimal structure and parameters of fuzzy systems, an approach to the automatic design of fuzzy systems based on L-systems is also proposed. The proposed method can efficiently construct fuzzy rules without any need for user interaction by using the rewriting mechanism of L-systems.


Membership Function Fuzzy System Fuzzy Rule Input Space Graph Structure 
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 2006

Authors and Affiliations

  • Joon-Min Gil
    • 1
  • Seong-Hoon Lee
    • 2
  1. 1.Dept. of Computer Science EducationCatholic University of DaeguGyeongbukKorea
  2. 2.Dept. of Computer ScienceCheonan UniversityCheonanKorea

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