Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.dss.2015.02.017 | Decision Support Systems |
Keywords | DocType | Volume |
sources' independence,independence,combination rule choice,theory of belief functions,combination rules,clustering | Journal | 73 |
Issue | ISSN | Citations |
C | 0167-9236 | 9 |
PageRank | References | Authors |
0.56 | 17 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mouna Chebbah | 1 | 19 | 5.58 |
| Arnaud Martin | 2 | 158 | 18.26 |
| Boutheina Ben Yaghlane | 3 | 189 | 33.49 |