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Most Downloaded Articles
- How Many Wars Is the US Fighting Today? by Bilmes, Linda J. and Intriligator, Michael D.
- Evidence about the Link Between Education, Poverty and Terrorism among Palestinians by Berrebi, Claude
- Remittances and the Financing of Terrorism In Sub-Saharan Africa: 1974 - 2006 by Elu, Juliet U. and Price, Gregory N.
- The Impact of Employment in Israel on the Palestinian Labor Force by Etkes, Haggay
- Youth Unemployment, Terrorism and Political Violence, Evidence from the Israeli/Palestinian Conflict by Caruso, Raul and Gavrilova, Evelina
Modeling the Number of United States Military Personnel Using Artificial Neural Networks
1Global Vision, Inc.
2The Hoover Institution, Stanford University
Citation Information: Peace Economics, Peace Science and Public Policy. Volume 6, Issue 4, Pages –, ISSN (Online) 1554-8597, DOI: 10.2202/1554-8597.1039, October 2000
- Published Online:
Richardson’s concept of arms race dynamics is considered, with two objectives in mind. One is to examine the degree to which hostility, prior levels of armaments and changes in those levels by rivals facilitate the prediction of current arms, with specific attention to year-by-year changes in the quantity of United States military personnel. The second objective is to begin to evaluate the use of artificial neural networks as a way to model learning, not only in arms races, but in a broad range of social phenomena. The results show that Richardson’s class of variables alone are insufficient to predict changes in U.S. military personnel. However, these variables do predict some major, seemingly discontinuous, shifts in military personnel that arise from demobilization following the end of war. Apparently, the neural network approach can learn to discern the end of war before any clear, overt action has taken place to signal it.