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We discuss designs of type-2 fuzzy logic systems (FLSs), where the FLSs are based on rules collected from surveys of multiple experts. Two kinds of uncertainties occur in this problem: 1) the uncertainty due to different experts giving different answers to the same question; and 2) the linguistic uncertainty associated with the labels of the fuzzy sets. The latter causes different experts to assign different values to membership function parameters. We show how both kinds of uncertainties can be approached within the framework of type-2 FLSs. Uncertainty about answers to questions is treated using two different approaches: averaging the responses, or preserving all the responses. The former is computationally more efficient; however, the latter provides more information and can be used when such information is deemed useful. Uncertainty about labels of fuzzy sets is handled directly by using type-2 fuzzy sets. We demonstrate that both kinds of uncertainties can affect the crisp output of a type-2 FLS.
Fuzzy Systems Conference Proceedings, 1999. FUZZ-IEEE '99. 1999 IEEE International (Volume:3 )
Date of Conference: 22-25 Aug. 1999