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Cluster Analysis by Variance Ratio Criterion and Quantum- ...
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由 S Wang 著作2015被引用 7 次 — (Aim) A novel and efficient method based on the quantum-behaved particle swarm was proposed to solve the cluster analysis problem.
Cluster analysis by variance ratio criterion and quantum ...
西交利物浦大学
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西交利物浦大学
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(Aim) A novel and efficient method based on the quantum-behaved particle swarm was proposed to solve the cluster analysis problem.
Cluster Analysis by Variance Ratio Criterion and Quantum- ...
Springer
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(Aim) A novel and efficient method based on the quantum-behaved particle swarm was proposed to solve the cluster analysis problem.
Cluster Analysis by Variance Ratio Criterion and Quantum- ...
ResearchGate
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(Aim) A novel and efficient method based on the quantum-behaved particle swarm was proposed to solve the cluster analysis problem.
Cluster Analysis by Variance Ratio Criterion and Quantum- ...
OUCI
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Cluster Analysis by Variance Ratio Criterion and Quantum-Behaved PSO ... Authors: Shuihua Wang; Xingxing Zhou; Guangshuai Zhang; Genlin Ji; Jiquan Yang; Zheng ...
Cluster Analysis by Variance Ratio Criterion and Quantum- ...
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Bibliographic details on Cluster Analysis by Variance Ratio Criterion and Quantum-Behaved PSO.
Cluster Analysis by Variance Ratio Criterion and Firefly Algorithm
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A new approach based on firefly algorithm (FA) using the variance ratio criterion (VRC) as fitness function to solve the cluster analysis problem more ...
Data Clustering Based on Quantum-behaved Particle Swarm ...
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This paper investigates Quantum-behaved Particle Swarm Optimization(QPSO) algorithm to cluster data based on the K-Means clustering,PSO clustering and KPSO ...
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Cluster Analysis by Variance Ratio Criterion and PSOSQP ...
ResearchGate
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We compared the PSOSQP with genetic algorithm (GA) and combinatorial particle swarm optimization (CPSO). Each algorithm was run 20 times. The results showed ...
Convergence analysis and improvements of quantum ...
ScienceDirect.com
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由 J Sun 著作2012被引用 251 次 — This paper presents a convergence analysis and performance evaluation of the QPSO algorithm and it also proposes two variants of the QPSO algorithm.
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