Department of Mathematics, Urmia Branch, Urmia, Iran
Abstract
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.
Saneifard, R. (2017). Another Method for Defuzzification Based On Characterization of Fuzzy Numbers. International Journal of Industrial Mathematics, 9(4), 333-339.
MLA
Rahim Saneifard. "Another Method for Defuzzification Based On Characterization of Fuzzy Numbers". International Journal of Industrial Mathematics, 9, 4, 2017, 333-339.
HARVARD
Saneifard, R. (2017). 'Another Method for Defuzzification Based On Characterization of Fuzzy Numbers', International Journal of Industrial Mathematics, 9(4), pp. 333-339.
VANCOUVER
Saneifard, R. Another Method for Defuzzification Based On Characterization of Fuzzy Numbers. International Journal of Industrial Mathematics, 2017; 9(4): 333-339.
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