论文摘要
Aimed at the problems of low solution precision and easy to be trapped into local optima by single objective evolutionary algorithm, a self-adaptive multi-objective optimization algorithm based on nondominated sorting genetic algorithm II（NSGA2） and Label Propagation Algorithm（LPA） is proposed. The algorithm takes Kernel K-means（KKM） and Ratio Cut（RC） as the objective functions. Two new crossover operator and the improved mutation operator is used to achieve the evolution of the population. We conducted simulation experiments in the computer-generated networks and the real-world networks environment. The results show that compared with other community detection algorithms, our algorithm has the advantages of high resolution and strong search ability, and it can effectively identify the community structure in complex networks.
论文目录
文章来源
类型: 国际会议
作者: Wen-jun LIU,Bin CHEN
来源: 2019 International Conference on Information Technology, Electrical and Electronic Engineering (ITEEE 2019) 2019-01-20
年度: 2019
分类: 基础科学,信息科技
专业: 数学,自动化技术
单位: School of Computer Science and Technology,Wuhan University of Science and Technology,Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System
分类号: TP18;O157.5
DOI: 10.26914/c.cnkihy.2019.078440
页码: 112-116
总页数: 5
文件大小: 1067k