• DocumentCode
    613312
  • Title

    Analysis and prediction of insurgent influence for U.S. military strategy

  • Author

    Bernica, T.W. ; Guarino, V.E. ; Han, A.J. ; Hennet, L.F. ; Mitchell, M.A. ; Gerber, M.S. ; Brown, D.E.

  • Author_Institution
    Univ. of Virginia, Charlottesville, VA, USA
  • fYear
    2013
  • fDate
    26-26 April 2013
  • Firstpage
    161
  • Lastpage
    166
  • Abstract
    Given that many of the U.S. Military´s current conflicts involve insurgent groups, it is critical that the military understands the nature, motivations, and workings of these non-traditional forces. Many models have attempted to predict successful insurgent conflicts; however, most fail to incorporate the different types of factors collectively, namely: political, geographic, social, economic and cultural. With the creation of a model that incorporates all of these factors, predicting the success of an insurgent group before they gain influence will become a more attainable pursuit. We focused on researching past insurgencies to identify factors that lead to their successes or failures in gaining influence. Once the historical conflict data was compiled, we used the information to train and test statistical models to predict the success or failure of future insurgent conflicts. Our results indicate that certain factors have a strong correlation with the success and failure of an insurgent conflict. For historical conflicts in the testing set, the model accurately predicted the outcome of the conflict 27 out of 36 times. We discuss our data collection and modeling work in detail and offer insights into future work in this area.
  • Keywords
    electronic warfare; military equipment; statistical analysis; U.S. military strategy; cultural factor; data collection; economic factor; geographic factor; historical conflict data; insurgent groups; insurgent influence analysis; insurgent influence prediction; political factor; social factor; statistical models; Biological system modeling; Cultural differences; Data models; Economics; Force; Government; Predictive models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems and Information Engineering Design Symposium (SIEDS), 2013 IEEE
  • Conference_Location
    Charlottesville, VA
  • Print_ISBN
    978-1-4673-5662-6
  • Type

    conf

  • DOI
    10.1109/SIEDS.2013.6549512
  • Filename
    6549512