Abstract
Effectively measuring the information content of Basic Probability Assignments (BPA) is a crucial prerequisite for addressing uncertain information within the framework of Dempster-Shafer theory. In previous research, uncertainty and dissimilarity measures for BPAs were often treated separately to counteract the impact of incomplete mutual exclusion between focal elements. In this paper, we introduce a Transient Mass Function (TMF) based on the process of pignistic probability transformation to forge a link between probabilistic and evidential information. As a transient state of BPA, the TMF not only considers the structural features of the focal element but also maintains its numerical content. Carrying out probabilistic information measures on the TMF is equivalent to performing belief information measures on the original BPA. Finally, validated by numerical simulations, TMF provides a unified and effective metric framework for evidential information.
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