Probabilistic foundations for measurement modelling with fuzzy random variables
We propose fuzzy random variables as a tool for modelling measurements when both aleatory and fuzzy uncertainty have to be taken into account. Uncertainty propagation follows the ordinary scheme for the random part and uses a t-normed extension principle for the fuzzy part. We concentrate on the probabilistic theoretical underpinnings of the model, particularly limit theorems, and discuss their implications to the model. (C) 2006 Published by Elsevier B.V.
measurement fuzzy random variable archimedean t-norm central limit theorem strong law of large numbers