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Erschienen in:
Modeling Conflicts Between States: New Developments for an Old Problem Kapitel lesen Erstes Kapitel lesen

2011 | OriginalPaper | Buchkapitel

5. Support Vector Machines for Modeling Interstate Conflict

verfasst von : Tshilidzi Marwala, Dr. Monica Lagazio

Erschienen in: Militarized Conflict Modeling Using Computational Intelligence

Verlag: Springer London

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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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Vorheriges Kapitel Bayesian Approaches to Modeling Interstate Conflict
Nächstes Kapitel Fuzzy Sets for Modeling Interstate Conflict
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Metadaten
Titel
Support Vector Machines for Modeling Interstate Conflict
verfasst von
Tshilidzi Marwala
Dr. Monica Lagazio
Copyright-Jahr
2011
Verlag
Springer London
Buch
Militarized Conflict Modeling Using Computational Intelligence

Print ISBN: 978-0-85729-789-1

Electronic ISBN: 978-0-85729-790-7

Copyright-Jahr: 2011

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