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Support Vector Machines for Modeling Interstate Conflict

  • Tshilidzi Marwala
  • Monica Lagazio
Chapter
Part of the Advanced Information and Knowledge Processing book series (AI&KP)

Abstract

Militarized conflict is one of the risks that have a significant impact on society. Militarized interstate dispute is defined as an outcome of interstate interactions, which result either in peace or conflict. The effective prediction of the possibility of conflict between states is an important decision support tool for policy makers. In previous chapters, neural networks were implemented to predict militarized interstate disputes. Support vector machines have proved to be excellent predictors and hence are introduced in this chapter for the prediction of militarized interstate disputes and then compared with the hybrid Monte Carlo trained multi-layer perceptron neural networks. The results demonstrated that support vector machines predict militarized interstate dispute better than neural networks, while neural networks give a more consistent and easy to interpret sensitivity analysis than do support vector machines.

Keywords

Support Vector Machine Radial Basis Function Hide Unit Artificial Intelligence Technique Evidence Framework 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.University of JohannesburgJohannesburgSouth Africa

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