Algebra of Dempster-Shafer evidence accumulation

R. H. Enders, Andrzej K. Brodzik, M. R. Pellegrini
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引用次数: 4

Abstract

In this work we focus on the relationship between the Dempster-Shafer (DS) and Bayesian evidence accumulation. While it is accepted that the DS theory is, in a certain sense, a generalization of the probability theory, the approaches vary in several important respects, including the treatment of uncertain information and the way the evidence is combined, making direct comparison of results of the two analyses difficult. In this work we ameliorate these difficulties by proposing a mathematical framework within which the relationship between the two methods can be made precise. The findings of the investigation elucidate the role uncertainty plays in the DS theory and enable evaluation of relative fitness of the two techniques for practical data fusion scenarios.
Dempster-Shafer证据积累的代数
在这项工作中,我们重点研究了Dempster-Shafer (DS)和贝叶斯证据积累之间的关系。虽然人们普遍认为DS理论在某种意义上是概率论的概括,但两种方法在几个重要方面有所不同,包括对不确定信息的处理和证据组合的方式,这使得直接比较两种分析的结果变得困难。在这项工作中,我们通过提出一个数学框架来改善这些困难,在这个框架中,两种方法之间的关系可以精确地表示出来。调查结果阐明了不确定性在DS理论中所起的作用,并能够评估两种技术在实际数据融合场景中的相对适合度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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