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.
[v1] 2017-12-29 06:21:14
Unique-IP document downloads: 21 times
Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.
Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.