Artificial Intelligence


TDBF: Two Dimensional Belief Function

Authors: Yangxue Li; Yong Deng

How to efficiently handle uncertain information is still an open issue. Inthis paper, a new method to deal with uncertain information, named as two dimensional belief function (TDBF), is presented. A TDBF has two components, T=(mA,mB). The first component, mA, is a classical belief function. The second component, mB, also is a classical belief function, but it is a measure of reliability of the first component. The definition of TDBF and the discounting algorithm are proposed. Compared with the classical discounting model, the proposed TDBF is more flexible and reasonable. Numerical examples are used to show the efficiency of the proposed method.

Comments: 15 Pages.

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Submission history

[v1] 2017-12-29 06:21:14

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