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首页> 外文会议>工业工程与系统管理2007年国际会议（International Conference on Industrial Engineering and Systems Management）（IESM 2007）论文集 >Acquisition and Combination of Evidence Based on Rough Set Theory
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Acquisition and Combination of Evidence Based on Rough Set Theory

机译：基于粗糙集理论的证据获取与组合

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In the evidence theory, the most popular rule of combination, called Dempster’s rule of combination, has several interesting mathematical properties. Evidences used in Dempster’s rule of combination are given by experts and distinct information sources have the same weight. However, experts’ knowledge related with problem domain is limited, subjective and sometimes difficult to obtain. This may result in the belief function obtained from experts unreliable. The averaging assignment of weight may also get counterintuitive result when evidences conflict. This paper proposes a new approach to acquire evidences from large decision tables using the rough set theory and clustering. And then an investigation of how to compute the weights and support degrees of evidences are undertaken. Finally, an improved rule of combination is proposed. Experimental results compared with id3 and J48 show that the proposed methods can be used effectively in decision making.
机译：在证据理论中，最流行的组合法则称为Dempster的组合法则，具有几个有趣的数学特性。邓普斯特合并规则中使用的证据由专家提供，不同的信息来源具有相同的权重。但是，专家与问题域相关的知识是有限的，主观的，有时很难获得。这可能导致从专家那里获得的置信功能不可靠。当证据冲突时，权重的平均分配也可能会得出违反直觉的结果。本文提出了一种使用粗糙集理论和聚类从大型决策表中获取证据的新方法。然后研究了如何计算证据的权重和支持度。最后，提出了一种改进的组合规则。与id3和J48进行比较的实验结果表明，所提出的方法可以有效地用于决策。

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