Improving fuzzy c-means clustering via quantum-enhanced weighted superposition attraction algorithm

DOI10.15672/HJMS.2019.655zbMath1488.68035MaRDI QIDQ5155984

Adil Baykasoǧlu, İlker Gölcük, Fehmi Burcin Ozsoydan

Publication date: 13 October 2021

Published in: Hacettepe Journal of Mathematics and Statistics (Search for Journal in Brave)

zbMATH Keywords

pattern recognitionmetaheuristicsfuzzy c-means clusteringweighted superposition attraction

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20) Multivariate analysis and fuzziness (62H86)

Uses Software

• J-MEANS
• UCI-ml

Cites Work

• Unnamed Item
• \(K\)-harmonic means data clustering with simulated annealing heuristic
• An evolutionary technique based on K-means algorithm for optimal clustering in \({\mathbb R}^{N}\)
• Fuzzy J-means: a new heuristic for fuzzy clustering
• Cluster Validity with Fuzzy Sets

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