Quantum-behaved discrete multi-objective particle swarm optimization for complex network clustering

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• 作者：Lingling Li ; ^{linglingxidian@gmail.com}Author Vitae ; Licheng Jiao ^{lchjiao@mail.xidian.edu.cn}Author Vitae ; Jiaqi Zhao ^{jiaqizhao88@126.com}Author Vitae ; Ronghua Shang ^{rhshang@mail.xidian.edu.cn}Author Vitae ; Maoguo Gong ^{gong@ieee.org}Author Vitae
• 关键词：Multi-objective optimization ; Quantum ; Discrete particle swarm optimization ; Complex networks ; Clustering
• 刊名：Pattern Recognition
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：63
• 期：Complete
• 页码：1-14
• 全文大小：1336 K
• 卷排序：63

文摘

QDM-PSO algorithm is the first time proposed for complex network clustering. The non-dominant sorting operation is employed for individual replacement. QDM-PSO algorithm is effective for large-scale networks.