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arxiv: 1801.00702 · v1 · pith:VFLPNXWRnew · submitted 2017-12-25 · 💻 cs.AI

A total uncertainty measure for D numbers based on belief intervals

classification 💻 cs.AI
keywords uncertaintymeasurenumberstheorytotalbeliefdempster-shaferintervals
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As a generalization of Dempster-Shafer theory, the theory of D numbers is a new theoretical framework for uncertainty reasoning. Measuring the uncertainty of knowledge or information represented by D numbers is an unsolved issue in that theory. In this paper, inspired by distance based uncertainty measures for Dempster-Shafer theory, a total uncertainty measure for a D number is proposed based on its belief intervals. The proposed total uncertainty measure can simultaneously capture the discord, and non-specificity, and non-exclusiveness involved in D numbers. And some basic properties of this total uncertainty measure, including range, monotonicity, generalized set consistency, are also presented.

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