• DocumentCode
    2746282
  • Title

    An Improved Algorithm for Dempster-Shafer Theory of Evidence

  • Author

    Chenghua, Yan ; Qixiang, Chen

  • Author_Institution
    Dept. of Inf. Security, Naval Univ. of Eng., Wuhan, China
  • fYear
    2009
  • fDate
    6-7 June 2009
  • Firstpage
    475
  • Lastpage
    478
  • Abstract
    The computational complexity of reasoning within the Dempster-Shafer theory of evidence is one of the major points of criticism this formalism has to face. Various approximation algorithms have been suggested that aim at overcoming this difficulty. This paper presents an improved practical algorithm through reducing the number of focal elements in the belief function involved. In this proposed algorithm, all focal elements of every piece of evidence are classified into dereliction and remainder, and the basic probability assignments of those derelictions are reassigned to the remainders when they are correlative or the dereliction is nested to the remainder. Finally, an illustrative example shows that the improved practical algorithm is effective and feasible through comparing with other approximations.
  • Keywords
    belief maintenance; computational complexity; inference mechanisms; pattern classification; probability; sensor fusion; Dempster-Shafer theory; approximation algorithm; basic probability assignment; belief function; computational complexity; evidence theory; focal element; information fusion; Approximation algorithms; Approximation methods; Computational complexity; Electronic commerce; Fault diagnosis; Information security; Monte Carlo methods; Signal processing; Signal processing algorithms; Target recognition; Dempster-Shafer theory of evidence; basic probability assignment; energy function; practical algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic Commerce and Business Intelligence, 2009. ECBI 2009. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-0-7695-3661-3
  • Type

    conf

  • DOI
    10.1109/ECBI.2009.44
  • Filename
    5189521