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<item>
  <id>01358463</id>
  <dt>j</dt>
  <an>01358463</an>
  <augroup>
    <au>Pauler, Gabor</au>
  </augroup>
  <ti>Development of a neuro-fuzzy approach for treating multimodal distributions and spurious clusters.</ti>
  <so>Eur. J. Oper. Res. 112, No. 1, 207-219 (1999).</so>
  <py>1999</py>
  <pu>Elsevier Science B.V.(North-Holland), Amsterdam</pu>
  <lagroup>
    <la>EN</la>
  </lagroup>
  <ccgroup>
  </ccgroup>
  <utgroup>
    <ut>Fuzzy sets</ut>
    <ut>Neural networks</ut>
    <ut>Neuro fuzzy model free estimator</ut>
    <ut>Feature mapping</ut>
    <ut>Fuzzy wings</ut>
  </utgroup>
  <cigroup>
  </cigroup>
  <ligroup>
    <li>doi:10.1016/S0377-2217(97)00397-4</li>
  </ligroup>
  <abgroup>
    <ab>Summary: We introduce a developed approach of neuro-fuzzy model free estimators to treat decision problems, where presence of highly multimodal distributions and spurious clusters in decision spaces causes problems in estimation. After critical analysis of Kosko's DCL--AVQ + FAM neuro-fuzzy system, we developed our The Straitjacket + F-wing system. Straitjacket neural system is an improved version of Kohonen's feature mapping according to convergence and termination conditions. F-wing fuzzy system bases on the feature map produced by Straitjacket and provides faster and more exact estimator interface than Bart Kosko's FAM, using fuzzy wing functions instead of fuzzy hyperpyramids. At the end of the paper we perform a test on an artificial database comparing the efficiency of our approach with Kosko's system, discriminant analysis, hierarchic and K-mean clustering.</ab>
    <rv></rv>
  </abgroup>
</item>