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Measuring total uncertainty in evidence theory

Dempster–Shafer (DS) evidence theory is the most significant and effective method for uncertainty modeling and reasoning. How to measure the uncertainty in DS evidence theory precisely remains an outstanding problem. Various types of uncertainty measures for evidence have been presented. However, they all suffer some limitations. To address this issue, we propose a novel total uncertainty measure for the DS evidence theory framework that can quantify the uncertainty in the evidence. The new total uncertainty measure uses the Hellinger distance between the belief interval of every singleton and the most uncertain interval. Compared with the existing uncertainty measurement methods, the proposed approach is more sensitive to changes in evidence. The effectiveness and rationality of the brand new total uncertainty measure are illustrated by numerical examples and practical applications.