Combining partially independent belief functions
作者:
摘要
The theory of belief functions manages uncertainty and also proposes a set of combination rules to aggregate opinions of several sources. Some combination rules mix evidential information where sources are independent; other rules are suited to combine evidential information held by dependent sources. In this paper we have two main contributions: First we suggest a method to quantify sources' degree of independence that may guide the choice of the more appropriate set of combination rules. Second, we propose a new combination rule that takes consideration of sources' degree of independence. The proposed method is illustrated on generated mass functions.
论文关键词:Theory of belief functions,Combination rules,Clustering,Independence,Sources' independence,Combination rule choice
论文评审过程:Received 28 November 2013, Revised 17 January 2015, Accepted 26 February 2015, Available online 6 March 2015.
论文官网地址:https://doi.org/10.1016/j.dss.2015.02.017