关键词: 位置修复, 粒子置换, 多目标粒子群, 快速排序, 均匀密度

Abstract: In order to improve the effect of signature network community discovery, and solve the evaluation indicator of the presence of data coupling and dependence, which leads some limitations of single index optimization in network community, this paper proposes signature network community discovery based on FSUD-PSO (fast sorting and uniform density of multi-objective particle swarm optimization) with location repair and particle replacement. Firstly, this paper studies the signature network model, and gives the community evaluation index of the signature network under the premise of considering the data coupling and dependence. Secondly, this paper builds a signature network model with particle coding and update rules for multi-objective optimization and network according to the characteristics of signature      design repair and particle replacement, at the same time, in order to improve multi-objective particle swarm algorithm performance, it designs the FSUD-PSO algorithm. Finally, the effectiveness of the proposed FSUD-PSO signature     network community is verified by comparing with the standard test sets.

Key words: position repair, particle replacement, multi-objective particle swarm, fast sorting, uniform density