Genetic algorithm with optimized rough sets for modeling interstate conflict

Tshilidzi Marwala, Monica Lagazio

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


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.

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

Publication series

NameAdvanced Information and Knowledge Processing
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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