A Further Study on Fuzzy Evidence Theory

Abstract

This paper generalizes the evidence theory and makes it can be used in fuzzy sets in order to make it can be used more effectively. With the fuzzy membership function, this paper presents a method to set up the basic probability assignment function (mass function) in evidence theory, and integrates fuzzy theory and evidence theory effectively. This method brings the evidence theory nearer to practice. This paper presents an improved combination rule to deal with consistent or inconsistent evidences obtained from multiple sources. The improved rule reflects the intersection of focus elements and adapts AND-operation to combine consistent evidences, and allocates the conflicts to vary focus elements according to relevant evidences' creditability. From the theoretic analysis and the results of the numerical examples, the given rule is very rational and effective for both high conflictive evidences and consistent evidences. Especially, the given rule can provide reasonable results with better convergence efficiency than other rules when evidence sources are high conflict.