• DocumentCode
    3019716
  • Title

    Evidence fusion methods based on the pretreatment model

  • Author

    Hu, Li-fang ; Guan, Xin ; He, You

  • Author_Institution
    Res. Inst. of Inf. Fusion, Naval Aeronaut. Astronaut. Univ., Yantai, China
  • fYear
    2009
  • fDate
    12-15 July 2009
  • Firstpage
    460
  • Lastpage
    464
  • Abstract
    Dempster´s combination rule is the most popular rule of combinations, but it is a poor solution for the management of the conflict between various information sources at the normalization step. Even when it faces high conflict information, the classical Dempster-Shafer theory can involve counter-intuitive results. To solve this problem, this paper combines fuzzy theory to put forward new improved methods of pretreatment mode based on the summary of existing conflict evidences fusion methods. Firstly, the evidence´s conflicting probability is distributed by methods of pretreatment mode which can change high conflict evidences into low conflict evidences. Then, Dempster´s combination rule is used to realize information fusion. Finally, numerical examples and simulation experiments demonstrate the proposed methods can realize the modification ideas and also will provide reasonable results with good convergence efficiency. Although evidences conflict one another highly, good combination results are also obtained.
  • Keywords
    convergence; fuzzy set theory; probability; sensor fusion; uncertainty handling; Dempster´s combination rule; classical Dempster-Shafer theory; conflict evidences fusion methods; convergence efficiency; evidence conflicting probability; evidence fusion methods; fuzzy theory; information fusion; pretreatment model; Convergence of numerical methods; Fuzzy systems; Helium; Information analysis; Numerical simulation; Pattern analysis; Pattern recognition; Stability; Time measurement; Wavelet analysis; Conflict evidence; Dempster´s combination rule; Information fusion; Reliability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wavelet Analysis and Pattern Recognition, 2009. ICWAPR 2009. International Conference on
  • Conference_Location
    Baoding
  • Print_ISBN
    978-1-4244-3728-3
  • Electronic_ISBN
    978-1-4244-3729-0
  • Type

    conf

  • DOI
    10.1109/ICWAPR.2009.5207430
  • Filename
    5207430