Support vector machines for modeling interstate conflict

Tshilidzi Marwala, Monica Lagazio

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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.

Original languageEnglish
Title of host publicationAdvanced Information and Knowledge Processing
PublisherSpringer London
Pages89-105
Number of pages17
Edition9780857297891
DOIs
Publication statusPublished - 2011

Publication series

NameAdvanced Information and Knowledge Processing
Number9780857297891
ISSN (Print)1610-3947
ISSN (Electronic)2197-8441

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Information Systems and Management
  • Artificial Intelligence

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