An Improved Algorithm for Dempster-Shafer Theory of Evidence

Author(s):  
Yan Chenghua ◽  
Chen Qixiang
2017 ◽  
Vol 24 (2) ◽  
pp. 653-669 ◽  
Author(s):  
Ningkui WANG ◽  
Daijun WEI

Environmental impact assessment (EIA) is usually evaluated by many factors influenced by various kinds of uncertainty or fuzziness. As a result, the key issues of EIA problem are to rep­resent and deal with the uncertain or fuzzy information. D numbers theory, as the extension of Dempster-Shafer theory of evidence, is a desirable tool that can express uncertainty and fuzziness, both complete and incomplete, quantitative or qualitative. However, some shortcomings do exist in D numbers combination process, the commutative property is not well considered when multiple D numbers are combined. Though some attempts have made to solve this problem, the previous method is not appropriate and convenience as more information about the given evaluations rep­resented by D numbers are needed. In this paper, a data-driven D numbers combination rule is proposed, commutative property is well considered in the proposed method. In the combination process, there does not require any new information except the original D numbers. An illustrative example is provided to demonstrate the effectiveness of the method.


2005 ◽  
Vol 174 (3-4) ◽  
pp. 143-164 ◽  
Author(s):  
Wei-Zhi Wu ◽  
Mei Zhang ◽  
Huai-Zu Li ◽  
Ju-Sheng Mi

2013 ◽  
Vol 8 (4) ◽  
pp. 593-607 ◽  
Author(s):  
Marco Fontani ◽  
Tiziano Bianchi ◽  
Alessia De Rosa ◽  
Alessandro Piva ◽  
Mauro Barni

2018 ◽  
Vol 613-614 ◽  
pp. 1024-1030 ◽  
Author(s):  
Cristián González ◽  
Miguel Castillo ◽  
Pablo García-Chevesich ◽  
Juan Barrios

Sign in / Sign up

Export Citation Format

Share Document