@inbook{aa4ff2b2e2ad41769c269117697f1ad2,
title = "Particle swarm optimization and hill-climbing optimized rough sets for modeling interstate conflict",
abstract = "This chapter presents methods to optimally granulize rough set partition sizes using particle swarm optimization and hill climbing techniques. These two methods are then compared to the equal-width-bin partitioning technique. The results obtained demonstrated that hill climbing provides higher forecasting accuracy, followed by the particle swarm optimization method, which was better than the equal-width-bin technique.",
author = "Tshilidzi Marwala and Monica Lagazio",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag London Limited 2011.",
year = "2011",
doi = "10.1007/978-0-85729-790-7_8",
language = "English",
series = "Advanced Information and Knowledge Processing",
publisher = "Springer London",
number = "9780857297891",
pages = "147--164",
booktitle = "Advanced Information and Knowledge Processing",
address = "United Kingdom",
edition = "9780857297891",
}