计算机工程与应用2018，Vol.54Issue(10)：54-58,104,6.DOI:10.3778/j.issn.1002-8331.1703-0487
基于证据距离和不确定度的冲突数据融合算法
Conflict evidence combination rule based on uncertainty measurement and evidence dis-tance
摘要
Abstract
Dempster-Shafer evidence theory is widely used in many fields of information fusion.However,the counter-intuitive results may be obtained when combining with highly conflicting evidence.To deal with such a problem,this paper puts forward a new method based on the distance of evidence and the uncertainty measure.First,based on the distance of evidence,the evidence is divided into two parts,the credible evidence and the incredible evidence.Then,a novel belief entropy is applied to measure the information volume of the evidence.Finally,the weight of each evidence is obtained and used to modify the evidence before using the Dempster's combination rule.Numerical examples show that the proposed method can effectively handle conflicting evidence with better convergence.关键词
证据理论/冲突/信度熵/证据距离Key words
evidence theory/conflict/belief entropy/evidence distance分类
信息技术与安全科学引用本文复制引用
严志军,陶洋..基于证据距离和不确定度的冲突数据融合算法[J].计算机工程与应用,2018,54(10):54-58,104,6.基金项目
重庆市"121"科技支撑示范工程(No.2012jcsf-jfzhX0004). （No.2012jcsf-jfzhX0004）
