Numerical Sensitivity and Efficiency in the Treatment of Epistemic and Aleatory Uncertainty

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dc.creatorChojnacki, Eric
dc.creatorBaccou, Jean
dc.creatorDestercke, Sébastien
dc.date2007-12-13
dc.date.accessioned2026-07-07T08:49:00Z
dc.date.available2026-07-07T08:49:00Z
dc.descriptionThe 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.
dc.identifierhttps://arxiv.org/abs/0712.2141
dc.identifierhttp://arxiv.org/abs/0712.2141
dc.identifierFifth International Conference on Sensitivity Analysis of Model Output, Budapest : Hongrie (2007)
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/144149
dc.subjectArtificial Intelligence
dc.subjectProbability
dc.titleNumerical Sensitivity and Efficiency in the Treatment of Epistemic and Aleatory Uncertainty
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