• DocumentCode
    3199937
  • Title

    Visualizing capability requirements in planning scenarios using Principal Component Analysis

  • Author

    Rempel, Mark

  • Author_Institution
    Centre for Operational Res. & Anal., Defence R&D Canada, Ottawa, ON, Canada
  • fYear
    2012
  • fDate
    11-13 July 2012
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    In recent years, a shift has occurred in defence strategic planning from being equipment focused towards being capability focused. As a result, several defence departments employ capability based planning in their force development processes rather than the traditional threat based model. However, this has led to a capability requirement visualization problem; that is, given a capability taxonomy, a set of planning scenarios, and a requirement assessment of each capability within each scenario, what are the ways to effectively and efficiently summarize and communicate the pan-scenario capability requirements to decision-makers. In this paper, we apply unsupervised learning techniques to the capability requirement visualization problem. We demonstrate how Principal Components Analysis and k-means clustering may be used to visualize and effectively communicate pan-scenario capability requirements to decision-makers.
  • Keywords
    decision making; defence industry; military computing; principal component analysis; strategic planning; unsupervised learning; capability requirements visualization; decision making; defence departments; defence strategic planning; force development process; principal component analysis; unsupervised learning; Force; Principal component analysis; Security; Strategic planning; Taxonomy; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Security and Defence Applications (CISDA), 2012 IEEE Symposium on
  • Conference_Location
    Ottawa, ON
  • Print_ISBN
    978-1-4673-1416-9
  • Type

    conf

  • DOI
    10.1109/CISDA.2012.6291513
  • Filename
    6291513