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Combination of Conflict Evidence Based on Bayesian Approximation

机译:基于贝叶斯近似的冲突证据组合

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In order to solve the problems emerged in the situation trying to combine conflict evidences using Dempster-Shafer theory, a new combination rule based on Dubois and Prade rule was raised. A method of using the new rule together with Bayesian Approximation was proposed to combine evidences from different bodies. Firstly the proposition transformation of discernment frame was discussed both in the open and closed world assumption. Secondly the effect of conflict was shown based on the Dempster-Shafer theory and Bayesian theorem. And finally the modified rule depending on the cardinal of set from different evidence bodies was proposed and was showed in the numerical example. Conclusion can be drawn from the example that the new combination rule reserves more information from the combined evidences and Bayesian Approximation reduces the number of focused elements, and using both of them is an effective and accurate method in evidence combination.
机译:为了解决在试图使用Dempster-Shafer理论对冲突证据进行合并的情况下出现的问题,提出了一种基于Dubois和Prade规则的新合并规则。提出了一种将新规则与贝叶斯近似结合使用的方法,以结合来自不同物体的证据。首先,在开放世界假设和封闭世界假设中都讨论了识别框架的命题转换。其次,基于Dempster-Shafer理论和贝叶斯定理证明了冲突的影响。最后,提出了基于不同证据主体的集合基数的修改规则,并在数值例子中进行了说明。可以从以下示例得出结论:新的合并规则可从合并的证据中保留更多信息,而贝叶斯逼近可减少聚焦元素的数量,并且将它们结合使用是一种有效且准确的证据合并方法。

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