Hierarchical Proportional Redistribution for bba Approximation.

BELIEF FUNCTIONS: THEORY AND APPLICATIONS(2012)

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摘要
Dempster's rule of combination is commonly used in the field of information fusion when dealing with belief functions. However, it generally requires a high computational cost. To reduce it, a basic belief assignment (bba) approximation is needed. In this paper we present a new bba approximation approach called hierarchical proportional redistribution (HPR) allowing to approximate a bba at any given level of non-specificity. Two examples are given to show how our new HPR works.
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关键词
High Computational Cost, Information Fusion, Belief Function, Evidence Theory, Outer Approximation
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