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- W3201991991 abstract "Summary Detecting hiding communities is considered as a main topic in complex networks. In this article, we propose a multi‐swarm elephant herding optimization (EHO) algorithm to uncover community structures in complex environments. It adapts EHO algorithm to community detection problem. EHO algorithm relies on two procedures which are updating clan procedure and separating procedure. The main idea of our multi‐swarm approach is that the population is composed of a set of interacting clans. In each clan, a local search function is defined to determine best local individual called matriarch. Through updating clan procedure, the remaining individuals in the clan update their positions based on the matriarch position. In addition, to ensure significant individuals in the clan, a multi‐swarm cooperative algorithm is designed to implement separating procedure; clans interchange individuals to balance the exploration and exploitation abilities. A series of experiments are carried out on artificial and real networks. The results obtained by the proposed approach are better than the results obtained by some other approaches." @default.
- W3201991991 created "2021-10-11" @default.
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- W3201991991 creator A5075337649 @default.
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- W3201991991 date "2021-09-29" @default.
- W3201991991 modified "2023-09-24" @default.
- W3201991991 title "An efficient multi‐swarm elephant herding optimization for solving community detection problem in complex environment" @default.
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- W3201991991 doi "https://doi.org/10.1002/cpe.6590" @default.
- W3201991991 hasPublicationYear "2021" @default.
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