Local Aggregated Differential Evolution Algorithm for Community Detection in Complex Networks

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

As one of the cornerstones in complex networks, researches on community structure upholds many advances in scientific fields like social and biological networks. A number of recent studies have concentrated on the community detection problem, which is equilibrium to the optimization of the fitness function called modularity over possible partition schemes. In this paper we propose a lightweight differential evolution algorithm with an additional local aggregation operator, which contributes to the improvement in precision, to search for the optimal division of the network. The competitive accuracy and scalability of the introduced algorithm have been demonstrated on computer generated networks and real world data sets in comparison with other famous counterparts.

源语言英语
主期刊名Proceedings of the 37th Chinese Control Conference, CCC 2018
编辑Xin Chen, Qianchuan Zhao
出版商IEEE Computer Society
2384-2389
页数6
ISBN(电子版)9789881563941
DOI
出版状态已出版 - 5 10月 2018
活动37th Chinese Control Conference, CCC 2018 - Wuhan, 中国
期限: 25 7月 201827 7月 2018

出版系列

姓名Chinese Control Conference, CCC
2018-July
ISSN(印刷版)1934-1768
ISSN(电子版)2161-2927

会议

会议37th Chinese Control Conference, CCC 2018
国家/地区中国
Wuhan
时期25/07/1827/07/18

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