Jean Baccou

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The need to differentiate between epistemic and aleatory uncertainty is now well admitted by the risk analysis community. One way to do so is to model aleatory uncertainty by classical probability distributions and epistemic uncertainty by means of possibility distributions, and then propagate them by their respective calculus. The result of this(More)
This paper is devoted to some recent developments in uncertainty analysis methods of computer codes used for accident management procedures in nuclear industry. A quick overview on classical probabilistic methods for uncertainty methodology is first given. It turns out that despite its attractiveness relying on a simple implementation and convenient(More)
Since the Fukushima accident, Japanese scientists have been intensively monitoring ambient radiations in the highly contaminated territories situated within 80 km of the nuclear site. The surveys that were conducted through mainly carborne, airborne and in situ gamma-ray measurement devices, enabled to efficiently characterize the spatial distribution and(More)
This work is devoted to the construction of new kriging-based interpolating position-dependent subdivision schemes for data reconstruction. Their originality stands in the coupling of the underlying multi-scale framework associated to subdivision schemes with kriging theory. Thanks to an efficient stencil selection, they allow to cope the problem of(More)
Nowadays, the need to treat both epistemic and aleatory uncertainty in a unified framework is well recognized [1]. One method to do so is to mix probabilistic convolution (for aleatory uncertainty) and fuzzy calculus (for epistemic uncertainty). Existing propositions either concern simple models [2] or are computationally very costly [3] (a luxury not(More)