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Militarized Conflict Modeling Using Computational Intelligence pp 89–105Cite as

Support Vector Machines for Modeling Interstate Conflict

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Part of the book series: Advanced Information and Knowledge Processing ((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.

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Authors and Affiliations

  1. University of Johannesburg, Johannesburg, South Africa

    Tshilidzi Marwala & Dr. Monica Lagazio

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  1. Tshilidzi Marwala
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  2. Dr. Monica Lagazio
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Correspondence to Tshilidzi Marwala .

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Marwala, T., Lagazio, M. (2011). Support Vector Machines for Modeling Interstate Conflict. In: Militarized Conflict Modeling Using Computational Intelligence. Advanced Information and Knowledge Processing. Springer, London. https://doi.org/10.1007/978-0-85729-790-7_5

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  • DOI: https://doi.org/10.1007/978-0-85729-790-7_5

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  • Online ISBN: 978-0-85729-790-7

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