基于吸引和冲突元层证据的聚类置信函数
Clustering belief functions based on attracting and conflicting metalevel evidence
摘要：
在本文中，我们开发了一种基于吸引和冲突元水平证据的聚类方法。当置信函数涉及多个事件并且所有置信函数混合时，进行这种聚类。聚类过程被用作将置信函数分离成应独立处理的子集的手段。冲突元层证据是由所有信念函数的两两冲突在内部产生的，吸引元层证据则是由某种外部来源给出的。
英文摘要：
In this paper we develop a method for clustering belief functions based on attracting and conflicting metalevel evidence. Such clustering is done when the belief functions concern multiple events, and all belief functions are mixed up. The clustering process is used as the means for separating the belief functions into subsets that should be handled independently. While the conflicting metalevel evidence is generated internally from pairwise conflicts of all belief functions, the attracting metalevel evidence is assumed given by some external source.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
