• DocumentCode
    3058768
  • Title

    Decomposition of belief function in hierarchical hypotheses space

  • Author

    Hau, Hai-Yen L.

  • Author_Institution
    Grumman Data Syst., Woodbury, NY, USA
  • fYear
    1990
  • fDate
    6-9 Nov 1990
  • Firstpage
    718
  • Lastpage
    724
  • Abstract
    It is shown that, in a hierarchically structured hypotheses space, any belief function whose focal elements are nodes in the hierarchy is a separable support function. An algorithm is proposed that decomposes such a separable support function into simple support functions. It is shown that the computational complexity of this decomposition algorithm is O(N2). Applications of the decomposition of separable support functions to the data fusion problem and the reasoning about control problem are discussed
  • Keywords
    computational complexity; inference mechanisms; belief function; computational complexity; data fusion; decomposition algorithm; hierarchical hypotheses space; nodes; reasoning about control; separable support function; simple support functions; Artificial intelligence; Bayesian methods; Computational complexity; Data mining; Data systems; Expert systems; Fuzzy reasoning; Fuzzy sets; Polynomials; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools for Artificial Intelligence, 1990.,Proceedings of the 2nd International IEEE Conference on
  • Conference_Location
    Herndon, VA
  • Print_ISBN
    0-8186-2084-6
  • Type

    conf

  • DOI
    10.1109/TAI.1990.130427
  • Filename
    130427
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3058768