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.

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