Another‎ Method for Defuzzification Based On Characterization of Fuzzy ‎Numbers

Here we consider approaches to the ranking of fuzzy numbers based upon the idea of associating with a fuzzy number a scalar value, its signal/noise ratios, where the signal and the noise are defined as the middle-point and the spread of each \gamma-cut of a fuzzy number, respectively. We use the value of a as the weight of the signal/noise ratio of each \gamma-cut of a fuzzy number to calculate the ranking index of each fuzzy number. The proposed method can rank any kinds of fuzzy numbers with different kinds of membership functions.‎