Conference Proceedings

On the neural defuzzification methods

SK Halgamuge, TA Runkler, M Glesner

Proceedings of IEEE 5th International Fuzzy Systems | I E E E | Published : 1996

Abstract

If representative real world or artificial data sets exist, neural networks can be trained to approximate different defuzzification methods - explicitly known standard methods like center of gravity, extended parametric methods like customizable basic defuzzification distribution, and also black box defuzzification methods. From the neural network point of view this kind of defuzzification is a multidimensional function approximation problem. In non black box adaptive solutions the analyzing capability of the trained network is significant to understand the specificity of the application. Using random membership functions or a carefully selected variation of membership functions as training ..

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