Probabilistic foundations for measurement modelling with fuzzy random variables
Fuzzy random variables are a well justified concept to deal with randomness and fuzziness simultaneously. Within this concept, however, modelling of fuzziness is restricted to the use of minimum t-norm which implies that fuzziness persists through propagation. In this context, the present paper is the first serious attempt to use and to discuss other, especially Archimedean t-norms. The author discusses strong laws of large numbers and central limit theorems (CLT) for special types of fuzzy random variables and presents examples where the CLT do not hold.
scientific article; zbMATH DE number 5149451