Comparison of different strategies of utilizing fuzzy clustering in structure identification

  title={Comparison of different strategies of utilizing fuzzy clustering in structure identification},
  author={Kemal Kilic and {\"O}zge Uncu and I. Burhan T{\"u}rksen},
  journal={Inf. Sci.},
Fuzzy systems approximate highly nonlinear systems by means of fuzzy ‘‘if–then’’ rules. In the literature, various algorithms are proposed for mining. These algorithms commonly utilize fuzzy clustering in structure identification. Basically, there are three different approaches in which one can utilize fuzzy clustering; the first one is based on input space clustering, the second one considers clustering realized in the output space, while the third one is concerned with clustering realized in… CONTINUE READING
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Localm-fsm: A new fuzzy system modeling approach using a two-step fuzzy inference mechanism based on local fuzziness level

  • O. Uncu, I. B. Turksen, K. Kilic
  • in: Proceedings of International Fuzzy Systems…
  • 2003
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