K-means particle swarm optimization with embedded chaotic search for solving multidimensional problems

DOI10.1016/j.amc.2012.09.039zbMath1309.90124OpenAlexW2005158799MaRDI QIDQ2018995

Hung-Ming Chen, Kuo-Yu Huang, Min-Yuan Cheng

Publication date: 26 March 2015

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2012.09.039

zbMATH Keywords

particle swarm optimizationchaotic searchK-means clustering

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59)

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Swarm/flock optimization algorithms as continuous dynamic systems ⋮ A novel sequence space related to \(\mathcal{L}_{p}\) defined by Orlicz function with application in pattern recognition ⋮ A fuzzy SV-\(k\)-modes algorithm for clustering categorical data with set-valued attributes ⋮ Lockage scheduling of three gorges-gezhouba dams by hybrid of chaotic particle swarm optimization and heuristic-adjusted strategies ⋮ Sequence spaces \(M(\phi)\) and \(N(\phi)\) with application in clustering ⋮ Combustion optimization of a boiler based on the chaos and Lévy flight vortex search algorithm

Cites Work

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• Chaos embedded particle swarm optimization algorithms
• Model-free adaptive control optimization using a chaotic particle swarm approach
• An improved GA and a novel PSO-GA-based hybrid algorithm
• The particle swarm optimization algorithm: Convergence analysis and parameter selection
• Improved particle swarm optimization combined with chaos
• Simple mathematical models with very complicated dynamics

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