The mean value of a fuzzy number
Fuzzy Sets and Systems - Fuzzy Numbers
Consonant approximation of belief functions
International Journal of Approximate Reasoning
When upper probabilities are possibility measures
Fuzzy Sets and Systems - Special issue dedicated to Professor Claude Ponsard
Artificial Intelligence
Supremum preserving upper probabilities
Information Sciences: an International Journal
Utilizing belief functions for the estimation of future climate change
International Journal of Approximate Reasoning
Belief functions on real numbers
International Journal of Approximate Reasoning
Representing partial ignorance
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Joint Propagation and Exploitation of Probabilistic and Possibilistic Information in Risk Assessment
IEEE Transactions on Fuzzy Systems
Fuzzy Sets and Systems
Representing parametric probabilistic models tainted with imprecision
Fuzzy Sets and Systems
International Journal of Approximate Reasoning
Unifying practical uncertainty representations -- I: Generalized p-boxes
International Journal of Approximate Reasoning
Cautious Conjunctive Merging of Belief Functions
ECSQARU '07 Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Computing expectations with continuous p-boxes: Univariate case
International Journal of Approximate Reasoning
Genetic learning of fuzzy rules based on low quality data
Fuzzy Sets and Systems
The fuzzy approach to statistical analysis
Computational Statistics & Data Analysis
On the variability of the concept of variance for fuzzy random variables
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Using cloudy kernels for imprecise linear filtering
IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty
Cumulative distribution functions, p-boxes and decisions under risk
International Journal of Knowledge Engineering and Soft Data Paradigms
Parameter estimation from small biased samples: Fuzzy sets vs statistics
Fuzzy Sets and Systems
International Journal of Approximate Reasoning
CECM: Constrained evidential C-means algorithm
Computational Statistics & Data Analysis
On the connection between probability boxes and possibility measures
Information Sciences: an International Journal
Stochastic dominance with imprecise information
Computational Statistics & Data Analysis
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The compact representation of incomplete probabilistic knowledge which can be encountered in risk evaluation problems, for instance in environmental studies is considered. Various kinds of knowledge are considered such as expert opinions about characteristics of distributions or poor statistical information. The approach is based on probability families encoded by possibility distributions and belief functions. In each case, a technique for representing the available imprecise probabilistic information faithfully is proposed, using different uncertainty frameworks, such as possibility theory, probability theory, and belief functions, etc. Moreover the use of probability-possibility transformations enables confidence intervals to be encompassed by cuts of possibility distributions, thus making the representation stronger. The respective appropriateness of pairs of cumulative distributions, continuous possibility distributions or discrete random sets for representing information about the mean value, the mode, the median and other fractiles of ill-known probability distributions is discussed in detail.