Combining partially independent belief functions - Archive ouverte HAL
Article Dans Une Revue Decision Support Systems Année : 2015

Combining partially independent belief functions

Résumé

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.
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Dates et versions

hal-01132564 , version 1 (17-03-2015)

Identifiants

Citer

Mouna Chebbah, Arnaud Martin, Boutheina Ben Yaghlane. Combining partially independent belief functions. Decision Support Systems, 2015, pp.37-46. ⟨10.1016/j.dss.2015.02.017⟩. ⟨hal-01132564⟩
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