Probabilistic foundations for measurement modelling with fuzzy random variables (Q878975)

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.