Rough particle swarm optimization and its applications in data mining

DOI10.1007/s00500-008-0284-1zbMath1141.68551OpenAlexW2011375947MaRDI QIDQ939180

Bilal Alatas, Erhan Akin

Publication date: 21 August 2008

Published in: Soft Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00500-008-0284-1

zbMATH Keywords

Particle swarm optimizationNumeric association rules miningRough value

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Knowledge representation (68T30)

Related Items (3)

A survey of evolutionary computation for association rule mining ⋮ A dynamic global and local combined particle swarm optimization algorithm ⋮ Discovering gene association networks by multi-objective evolutionary quantitative association rules

Uses Software

• QuantMiner
• MODENAR

Cites Work

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• Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
• An electromagnetism-like mechanism for global optimization
• Very simple classification rules perform well on most commonly used datasets
• Genetic algorithm based framework for mining fuzzy association rules

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