Neuro-fuzzy modeling and fuzzy rule extraction applied to conflict management

Authors:
Thando Tettey;Tshilidzi Marwala
Affiliations:
University of the Witwatersrand, School of Electrical and Information Engineering, Johannesburg, South Africa;University of the Witwatersrand, School of Electrical and Information Engineering, Johannesburg, South Africa
Venue:
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Year:
2006

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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.