Combining partially independent belief functions

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

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