Decision-Making with Belief Interval Distance

In this paper, we propose to use both a distance based on probabilistic transformations (mainly the pignistic transformation BetP and the Dezert-Smarandache transformation DSmP )

ER-MCDA (Evidential Reasoning – Multicriteria Decision Analysis) [15,16,17] is a methodology that combines the Analytic Hierarchy Process (AHP)[9], a multi-criteria decision

In this paper we have proposed a new method called BF- ICrA to simplify (when it is possible) Multi-Criteria Decision- Making problems based on inter-criteria analysis and

Based on all the distance values between belief intervals, we design a Euclidean-family distance using the sum of squares of all belief intervals’ distance values, and

Decision models allowing for incomplete preferences can be further divided into three subcategories: (1) strong dominance and in- terval bound dominance based on lower and

If the belief function reference lotteries we use are Bayesian belief functions, then our representation theorem coincides with Jaffray’s representation theorem for his linear

Applying this frame- work to postal address recognition implies defining the frame of discernment (or set of possible answers to the problem under study), converting PAR outputs

The notion of confidence structure can easily be extended to prediction problems, resulting in a new notion of predictive confidence structure. Using the notations introduced in