Numerical Sensitivity and Efficiency in the Treatment of Epistemic and Aleatory Uncertainty
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The treatment of both aleatory and epistemic uncertainty by recent methods often requires an high computational effort. In this abstract, we propose a numerical sampling method allowing to lighten the computational burden of treating the information by means of so-called fuzzy random variables.