An Information-based approach to handle various types of uncertainty in Fuzzy Bodies of Evidence

Fuzzy evidence theory or fuzzy Dempster-Shafer Theory captures all three types of uncertainty usually contained in a piece of information within one framework: fuzziness, non-specificity, and conflict. Therefore, it is known as one of the most promising approaches for practical applications. Quantifying the difference between two fuzzy bodies of evidence has a central role when this framework is used in applications. This work is motivated by the fact that while dissimilarity measures have been surveyed in the fields of evidence theory and fuzzy set theory, no comprehensive survey is yet available for fuzzy evidence theory. Here, we modified a set of the most discriminative dissimilarity measures (smDDM)-as the minimum set of dissimilarity with the maximal power of discrimination in evidence theory- to handle all types of uncertainty in fuzzy evidence theory. Consequently, our generalized smDDM (FsmDDM) together with one previously introduced fuzzy measure make up a set of measures that is comprehensive enough to compare all aspects of information conveyed by the fuzzy bodies of evidence. Experimental results are presented to show the efficiency of the proposed method.