Possibilistic Information Fusion Using Maximal Coherent Subsets

被引:33
|
作者
Destercke, Sebastien [1 ,2 ]
Dubois, Didier [1 ,2 ]
Chojnacki, Eric [3 ]
机构
[1] CNRS, IRIT, F-31062 Toulouse, France
[2] Univ Toulouse, F-31062 Toulouse, France
[3] Inst Radioprotect & Surete Nucl, Cadarache, France
关键词
Fuzzy belief functions; fuzzy sets; information fusion; maximal coherent subsets (MCSs); possibility theory; BELIEF; PROBABILITIES; COMBINATION;
D O I
10.1109/TFUZZ.2008.2005731
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
When multiple sources provide information about the same unknown quantity, their fusion into a synthetic interpretable message is often a tricky problem, especially when sources are conflicting. In this paper, we propose to use possibility theory and the notion of maximal coherent subsets (MCSs), often used in logic-based representations, to build a fuzzy belief structure that will be instrumental both for extracting useful insight about various features of the information conveyed by the sources and for compressing this information into a unique possibility distribution. Extensions and properties of the basic fusion rule are also studied.
引用
收藏
页码:79 / 92
页数:14
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