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A multi-objective evolutionary algorithm based on mixed encoding for community detection

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成果类型:
期刊论文
作者:
Yang, Simin;Li, Qingxia;Wei, Wenhong;Zhang, Yuhui
作者机构:
[Yang, Simin; Wei, Wenhong; Zhang, Yuhui] Dongguan Univ Technol, Sch Comp Sci & Technol, Dongguan 523808, Peoples R China.
[Li, Qingxia] Dongguan City Coll, Sch Comp & Informat, Dongguan 523419, Peoples R China.
语种:
英文
关键词:
Complex network;Multi-objective evolutionary;Mixed encoding;Community;Detection
期刊:
Multimedia Tools and Applications
ISSN:
1380-7501
年:
2022
基金类别:
Ministry of Science and Technology of China [2018AAA0101301]; Key Projects of Artificial Intelligence of High School in Guangdong Province [2019KZDZX1011]; Innovation Project of High School in Guangdong Province [2018KTSCX314]; Dongguan Social Development Science and Technology Project [20211800904722]; Dongguan Science and Technology Special Commissioner Project [20201800500442]
机构署名:
本校为其他机构
摘要:
Community structure is one of the most significant features in complex networks and community detection is a crucial method to analyze community structure. Existing representations in community detection have the characteristics of inflexibility and easily generate invalid solutions. To address the drawbacks, this paper proposed a multi-objective evolutionary algorithm based on mixed encoding (MOGAME). The algorithm combines the locus-based representation and labels-based representation, which can avoid generating invalid solution and improve the performance. Extensive experiments on both synt...

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