摘要
证据理论是处理不确定问题的重要方法,其处理的证据来源于专家,而专家的知识经验是有限的,且存在一定的主观性。在证据合成中,Dempster合成规则为证据理论提供了证据合成公式,但该公式在合成高度冲突的证据时,合成结果将有悖于常理。针对上述问题,将粗糙集理论中属性依赖度的思想引入到证据理论中,以此衡量证据的重要性,更合理地解决冲突证据合成问题。研究表明,该方法避免了传统证据理论的主观因素影响,能有效提高融合结果的准确性,得到符合实际的结论。
The theory of evidence is important for solving uncertain problem,the evidence using in the evidence theory is given by experts.The expert＇s knowledge is limited,subjective and sometimes difficuh to obtain.Dempster has offered a algorithm of evidence combination,but the algorithm need independent evidence.If it is used in high conflict evidence,the result would be innormal.To solve these problems,this paper presents the algorithm of evidence theory which draws into the concept of attribute dependability of rough sets,utilizes it to weigh the evidence importance,and can combine highly conflicting evidences more satisfactory.From the results,this method avoids the subjective ingredient influence,so it improves the precision of fusion result and obtains real conclusion.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第7期44-46,50,共4页
Computer Engineering and Applications
基金
湖南省自然科学基金(the Natural Science Foundation of Hunan Province of China under Grant No.06JJ20075)
关键词
粗糙集
证据理论
信息融合
属性依赖度
rough set
evidence theory
information fusion
attribute dependence
