Introduction to the ER rule for evidence combination

Authors:
Jian-Bo Yang;Dong-Ling Xu
Affiliations:
Manchester Business School, The University of Manchester, Manchester, UK;Manchester Business School, The University of Manchester, Manchester, UK
Venue:
IUKM'11 Proceedings of the 2011 international conference on Integrated uncertainty in knowledge modelling and decision making
Year:
2011

Citing 2
Cited 0

Combining belief functions when evidence conflicts

Decision Support Systems
On the evidential reasoning algorithm for multiple attribute decision analysis under uncertainty

IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans

Quantified Score

Hi-index	0.00

Visualization

Abstract

The Evidential Reasoning (ER) approach has been developed to support multiple criteria decision making (MCDM) under uncertainty. It is built upon Dempster's rule for evidence combination and uses belief functions for dealing with probabilistic uncertainty and ignorance. In this introductory paper, following a brief introduction to Dempster's rule and the ER approach, we report the discovery of a new generic ER rule for evidence combination [16]. We first introduce the concepts and equations of a new extended belief function and then examine the detailed combination equations of the new ER rule. A numerical example is provided to illustrate the new ER rule.