An Improved Memetic Algorithm for Community Detection in Complex Networks

被引：0

作者：

Gong, Maoguo ^{[1
]}

Cai, Qing ^{[1
]}

Li, Yangyang ^{[1
]}

Ma, Jingjing ^{[1
]}

机构：

[1] Xidian Univ, Minist Educ, Key Lab Intelligent Percept & Image Understanding, Xian, Peoples R China

来源：

2012 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2012年

关键词：

community detection; memetic algorithm; label propagation; elitism strategy; simulated annealing; SMALL-WORLD; CONNECTIVITY; MODULARITY; GA;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

There is an increasing recognition on community detection in complex networks in recent years. In this study, we improve a recently proposed memetic algorithm for community detection in networks. By introducing a Population Generation via Label Propagation (PGLP) tactic, an Elitism Strategy (ES) and an Improved Simulated Annealing Combined Local Search (ISACLS) strategy, the improved memetic algorithm called (iMeme-Net) is put forward for solving community detection problems. Experiments on both computer-generated and real-world networks show the effectiveness and the multi-resolution ability of the proposed method.

引用

页数：8

共 56 条

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