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

Thando Tettey, Tshilidzi Marwala

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationNeural Information Processing - 13th International Conference, ICONIP 2006, Proceedings
PublisherSpringer Verlag
Pages1087-1094
Number of pages8
ISBN (Print)3540464840, 9783540464846
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event13th International Conference on Neural Information Processing, ICONIP 2006 - Hong Kong, China
Duration: 3 Oct 20066 Oct 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4234 LNCS - III
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th International Conference on Neural Information Processing, ICONIP 2006
Country/TerritoryChina
CityHong Kong
Period3/10/066/10/06

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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