• DocumentCode
    497625
  • Title

    Dempster-Shafer Theory: Combination of information using contextual knowledge

  • Author

    Florea, Mihai Cristian ; Bossé, Éloi

  • Author_Institution
    Land & Joint Syst. Div., Thales Canada, Quebec City, QC, Canada
  • fYear
    2009
  • fDate
    6-9 July 2009
  • Firstpage
    522
  • Lastpage
    528
  • Abstract
    The aim of this paper is to investigate how to improve the process of information combination, using the Dempster-Shafer theory (DST). In presence of an overload of information and an unknown environment, the reliability of the sources of information or the sensors is usually unknown and thus cannot be used to refine the fusion process. In a previous paper, the authors have investigated different techniques to evaluate contextual knowledge from a set of mass functions (membership of a BPA to a set of BPAs, relative reliabilities of BPAs, credibility degrees, etc.). The purpose of this paper is to investigate how to use the contextual knowledge in order to improve the fusion process.
  • Keywords
    inference mechanisms; uncertainty handling; Dempster-Shafer theory; contextual knowledge; fusion process; information combination; mass functions; Decision support systems; Image sensors; Information resources; Intelligent sensors; Intelligent structures; Reliability theory; Research and development; Robustness; Sensor fusion; Sensor systems; Contextual Knowledge; Dempster-Shafer Theory; Evidence Theory; Fusion Architecture; Reliability Evaluation; Robust Combination Rule;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Fusion, 2009. FUSION '09. 12th International Conference on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    978-0-9824-4380-4
  • Type

    conf

  • Filename
    5203718