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Genetic Algorithm with Optimized Rough Sets for Modeling Interstate Conflict

  • Tshilidzi Marwala
  • Monica Lagazio
Chapter
Part of the Advanced Information and Knowledge Processing book series (AI&KP)

Abstract

This chapter presents methods to optimally granulize rough set partition sizes using a genetic algorithm. The procedure is applied to model the militarized interstate dispute data. The procedure is then compared to the rough set partition method that was based on simulated annealing. The results obtained showed that, for the data being analyzed, a genetic algorithm provides higher forecasting accuracy than does the process of simulated annealing.

Keywords

Genetic Algorithm Particle Swarm Optimization Simulated Annealing Hill Climbing Bayesian Neural Network 
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 London Limited 2011

Authors and Affiliations

  1. 1.University of JohannesburgJohannesburgSouth Africa

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