• DocumentCode
    3144278
  • Title

    An intelligent hierarchical decision architecture for operational test and evaluation

  • Author

    Beers, Major Suzanne M ; Vachtsevanos, George J.

  • Author_Institution
    Air Force Oper. Test & Evaluation Center, United States Air Force, USA
  • Volume
    1
  • fYear
    1996
  • fDate
    8-11 Sep 1996
  • Firstpage
    342
  • Abstract
    Decision-makers long for information that will make their decision processes easy and accurate. A methodology is proposed which begins with low information-content data, such as that derived from system testing, and aggregates/synthesizes the information to a higher information-content level, where it is meaningful to the decision-maker. The entire methodology, termed the intelligent hierarchical decision architecture, is composed of four stages which takes low-level test data gathered at the functional performance information level as input and the final output is a probabilistic bound on the system performance at the operational task-accomplishment information level
  • Keywords
    artificial intelligence; decision theory; equipment evaluation; decision processes; information aggregation; information synthesis; intelligent hierarchical decision architecture; low information-content data; operational evaluation; operational task-accomplishment information level; operational test; Clustering algorithms; Clustering methods; Fuzzy sets; Fuzzy systems; Performance evaluation; System performance; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on
  • Conference_Location
    New Orleans, LA
  • Print_ISBN
    0-7803-3645-3
  • Type

    conf

  • DOI
    10.1109/FUZZY.1996.551765
  • Filename
    551765