A novel conflict reassignment method based on grey relational analysis (GRA)

A novel conflict reassignment method based on grey relational analysis (GRA)
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DOI:
10.1016/j.patrec.2007.06.004
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发表时间:
2007-11
期刊:
Pattern Recognit. Lett.
影响因子:
--
通讯作者:
Guoping Xu;W. Tian;Li Qian;Xiangfen Zhang
Guoping Xu;W. Tian;Li Qian;Xiangfen Zhang
中科院分区:
其他
文献类型:
--
作者:
Guoping Xu;W. Tian;Li Qian;Xiangfen Zhang

文献摘要

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在证据理论的框架下,数据融合是将不同信息源的多个信念函数组合在一起,形成一个单一的信念函数。邓普斯特组合规则是一个经典的组合规则,具有几个有趣的数学性质,被广泛应用。然而,Dempster的组合规则作为一个固有的问题,无法在规范化阶段管理来自各种信息源的现有冲突。冲突管理成为组合运行中的一个重要问题,特别是在高度冲突的情况下,冲突管理会导致组合产生不合逻辑的结果。本文引入灰色关联分析的思想,提出了一种新的信念函数冲突重分配方法,作为一种预处理方法,在组合前自动识别和重分配信念函数上的冲突。采用并实现了三个数值算例。通过对现有备选方案组合结果的分析和比较,提出的方法不仅能够灵活地解决冲突管理问题,具有更好的收敛性能,而且能够自动评估信息源的可靠性,区分不可靠信息。
In the framework of evidence theory, data fusion is to build a single belief function by combining several belief functions derived from distinct information sources. Dempster’s rule of combination, a classical combination rule with several interesting mathematical properties, is widely employed. However, as an inherent problem, Dempster’s rule of combination is incapable of managing the existing conflicts from various information sources at the step of normalization. The conflict management becomes an important problem in the operation of combination, especially in the condition of highly conflicting, which leads to produce the illogical result of combination. In this paper, we introduce the idea of grey relational analysis (GRA), and propose a new conflict reassignment approach of belief functions, as a preprocessing method, to automatically identify and reassign the conflicts on belief functions before combination. Three numerical examples are employed and implemented. Through analysis and comparison of the combined results, of the existing alternatives, the proposed approach not only can flexibly solve the problem of conflict management with better convergence performance, but also can automatically evaluate the reliability of the information sources and distinguish the unreliable information.