LAUSR

How to efficiently handle uncertain information is still an open issue. In this paper, a new method to deal with uncertain information, named as two‐dimensional belief function (TDBF), is presented. A TDBF has two components, T = ( m A , m B ), both m A and m B are classical belief functions, while m B is a measure of reliable of m A . 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 and application of the proposed method.