• DocumentCode
    130041
  • Title

    A method of evidence of combination based on the improved similarity measure

  • Author

    Li Xinde ; Wang Fengyu ; Xu Yefan ; Chen Zongxiong

  • Author_Institution
    Key Lab. of Meas. & Control of CSE, Southeast Univ., Nanjing, China
  • fYear
    2014
  • fDate
    28-30 July 2014
  • Firstpage
    461
  • Lastpage
    466
  • Abstract
    Aiming to the phenomenon of counter intuition when dealing with some highly conflictive evidences by using the D-S combination rule, the reason for the occurrence of conflict is deeply analyzed. That is to say, it is caused by the outer conflicts among evidences and inner conflicts within the evidence itself. And then, the similarity measure is improved by considering inner and outer conflicts. The credibility is used to improve the corresponding evidential sources according to the improved similarity measure. The original evidences are clustered by using the ISODATA method. Each clustering is combined by using the unified combination rule according to its reliability computed. Finally, an example is given to compare this method in this paper with others and itself before improving. It shows that the new method solves the problem of counter intuition when combining the highly conflictive evidences and has the distinct advantage over others.
  • Keywords
    data analysis; inference mechanisms; iterative methods; pattern clustering; uncertainty handling; D-S combination rule; Dempster-Shafer theory; ISODATA method; clustering; counter intuition; highly conflictive evidences; improved similarity measure; iterative self organizing data analysis technique algorithm method; unified combination rule; Cognition; Educational institutions; Radiation detectors; Reliability; Symmetric matrices; Tumors; Clustering; Combination rule; Conflict; Evidence reasoning; Similarity measure;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation (ICIA), 2014 IEEE International Conference on
  • Conference_Location
    Hailar
  • Type

    conf

  • DOI
    10.1109/ICInfA.2014.6932700
  • Filename
    6932700