The consideration of imprecise probability in engineering analysis to account for missing,
vague or incomplete data in the description of model uncertainties is a fast-growing field of …

Random set theory is a general framework which comprises uncertainty in the form of
probability boxes, possibility distributions, cumulative distribution functions, Dempster …

Managing the uncertainty in multidisciplinary design of safety-critical systems requires not
only the availability of a single approach or methodology to deal with uncertainty but a set of …

Sklar's theorem is an important tool that connects bidimensional distribution functions with
their marginals by means of a copula. When there is imprecision about the marginals, we …

Hybrid reliability analysis (HRA) with both aleatory and epistemic uncertainties is
investigated in this paper. The aleatory uncertainties are described by random variables …

Uncertainty analysis is widely applied in water system modeling to quantify prediction
uncertainty from models and data. Conventional methods typically handle various kinds of …

Random set theory is a generalization of Dempster-Shafer evidence theory, that employs an
infinite number of focal elements. It can be used for the estimation of the bounds of the …

Random sets are random variables whose values are sets. They are frequently interpreted
as imprecise observations of random variables. In earlier papers the author has investigated …

Evidence theory-based reliability analysis (ETRA) is investigated in this paper. To estimate
the plausibility (Pl) and belief (Bel) measures of failure probability, the active learning …

A general method for estimating the bounds of the reliability of a system in which the input
variables are described by random sets (probability distributions, probability boxes, or …