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Neuro-fuzzy Modeling and Fuzzy Rule Extraction Applied to Conflict Management

  • Thando Tettey
  • Tshilidzi Marwala
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4234)

Abstract

This paper outlines all the computational methods which have been applied to the conflict management. A survey of all the pertinent literature relating to conflict management is also presented. The paper then introduces the Takagi-Sugeno fuzzy model for the analysis of interstate conflict. It is found that using interstate variables as inputs, the Takagi-Sugeno fuzzy model is able to forecast conflict cases with an accuracy of 80.36%. Furthermore, it found that the fuzzy model offers high levels of transparency in the form of fuzzy rules. It is then shown how these rules can be translated in order to validate the fuzzy model. The Takagi-Sugeno model is found to be suitable for interstate modeling as it demonstrates good forecasting ability while offering a transparent interpretation of the modeled rules.

Keywords

Fuzzy Rule Fuzzy Model Forecast Ability Interstate Variable IEEE International Joint 
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 Berlin Heidelberg 2006

Authors and Affiliations

  • Thando Tettey
    • 1
  • Tshilidzi Marwala
    • 1
  1. 1.School of Electrical and Information EngineeringUniversity of the WitwatersrandJohannesburgSouth Africa

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