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On types of fuzzy numbers and extension principles. (English) Zbl 0864.26010

A real function \(f\) often is fuzzified into a fuzzy function \(F\) in such a way that the arguments of \(F\) become fuzzy numbers and its values are determined from \(f\) via the extension principle \(EP\). In general, \(EP\) depends on a \(t\)-norm \(T\). Restricting furthermore the input fuzzy numbers to symmetric \(LR\)-fuzzy numbers with \(L=R\), the fuzzification of \(f\) depends of the pair \((L,T)\).
The author discusses the problem whether different such fuzzifications may yield the same fuzzy function \(F\).

MSC:

26E50 Fuzzy real analysis
94D05 Fuzzy sets and logic (in connection with information, communication, or circuits theory)
Full Text: DOI

References:

[1] Bandemer, H.; Näther, W., Fuzzy Data Analysis (1992), Kluwer Academic Publishers: Kluwer Academic Publishers Dordrecht · Zbl 0758.62003
[2] Dubois, D.; Prade, H., Fuzzy Sets and Systems: Theory and Applications (1980), Academic Press: Academic Press New York · Zbl 0444.94049
[3] Otto, K. N.; Lewis, A. D.; Antonsson, E. K., Approximating α-cuts with the vertex method, Fuzzy Sets and Systems, 55, 43-50 (1993) · Zbl 0931.26010
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