A study on the effect of vmax in particle swarm optimisation with high dimension
International Journal of Bio-Inspired Computation
Application of particle swarm optimization to association rule mining
Applied Soft Computing
Engineering Applications of Artificial Intelligence
A survey on swarm and evolutionary algorithms for web mining applications
SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part II
Particle swarm optimisation for data warehouse logical design
International Journal of Bio-Inspired Computation
Hi-index | 0.00 |
This paper proposes the use of Particle Swarm Optimisers as a tool for data mining. To evaluate its usefulness, we empirically compare the performance of three variants of the Particle Optimiser with another evolutionary algorithm, namely a Genetic Algorithm, in rule discovery for classification tasks. Such tasks are considered core tools for Decision Support Systems in a widespread area, ranging from the industry, commerce, military and scientific fields. The data sources used here for experimental testing are commonly used and considered as a de facto standard for rule discovery algorithms reliability ranking. The results obtained in these domains seem to indicate that Particle Swarm Optimisers are competitive with other evolutionary techniques, and can be successfully applied to more demanding problem domains.