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SUM NORMAL OPTIMIZATION OF FUZZY MEMBERSHIP FUNCTIONS
2002
International Journal of Uncertainty Fuzziness and Knowledge-Based Systems
Given a. fuzzy logic system, how can we determine the membership functions that will result in the best performance? H we constrain the membership functions to a certain shape (e.g., t riangles or trapezoids) then each membership function can be parameteri'l:ed by a small number of variables and the membership optimization problem can be reduced to a parameter optimization problem. This is the approach that is typically taken, hut it results in membership functions that are not (in general) sum
doi:10.1142/s0218488502001533
fatcat:zrgle47en5glta6ihifk4ep5sa