Modified DS evidence combination strategy based on evidence classification and uncertain entropy
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摘要: 提出了一种基于证据分类及不确定墒的修正证据合成方法,以解决证据冲突情况下的合成问题,该方法模仿人处理冲突信息时所经常采用的策略,即首先将证据分类,保证分在同一类中的证据具有较大的相似性,然后依据分类结果中各类证据的个数以及其本身具有的不确定性程度,决定对该类合成结果的信任度,并通过加权方法得到最终的合成证据.Abstract: A modified DS evidence combination method based on evidence classification and uncertain entropy was introduced. Such a method imitates human's behavior in classification to solve the problem of combing evidences with high degree of conflict. When a series of beliefs are available, first those evidences were classified into several sets to decide which ones correspond with each other and can be combined with DS rule reasonably, and then all the combination results were integrated with weight rule to form the final result.
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Key words:
- information processing /
- information fusion /
- evidence theory
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