Abstract
Fuzzy systems have gained more and more attention from researchers and practitioners of various fields. In such systems, the output represented by a fuzzy set sometimes needs to be transformed into a scalar value, and this task is known as the defuzzification process. Several analytic methods have been proposed for this problem, but lately, the neural network approach has been used for this purpose. When employed as defuzzifiers, a neural network is called a defuzzification neural network. In this paper, some preliminary results on properties of such defuzzification networks will be reported.
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Saneifard, R. Some properties of neural networks in designing fuzzy systems. Neural Comput & Applic 21 (Suppl 1), 215–220 (2012). https://doi.org/10.1007/s00521-011-0777-1
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DOI: https://doi.org/10.1007/s00521-011-0777-1