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基于免疫离散差分进化算法的复杂网络社区发现

张英杰 龚中汉 陈乾坤

张英杰, 龚中汉, 陈乾坤. 基于免疫离散差分进化算法的复杂网络社区发现. 自动化学报, 2015, 41(4): 749-757. doi: 10.16383/j.aas.2015.c140018
引用本文: 张英杰, 龚中汉, 陈乾坤. 基于免疫离散差分进化算法的复杂网络社区发现. 自动化学报, 2015, 41(4): 749-757. doi: 10.16383/j.aas.2015.c140018
ZHANG Ying-Jie, GONG Zhong-Han, CHEN Qian-Kun. Community Detection in Complex Networks Using Immune Discrete Differential Evolution Algorithm. ACTA AUTOMATICA SINICA, 2015, 41(4): 749-757. doi: 10.16383/j.aas.2015.c140018
Citation: ZHANG Ying-Jie, GONG Zhong-Han, CHEN Qian-Kun. Community Detection in Complex Networks Using Immune Discrete Differential Evolution Algorithm. ACTA AUTOMATICA SINICA, 2015, 41(4): 749-757. doi: 10.16383/j.aas.2015.c140018

基于免疫离散差分进化算法的复杂网络社区发现

doi: 10.16383/j.aas.2015.c140018
基金项目: 

国家自然科学基金(61440026),教育部博士点基金(20110161110035),湖南省自然科学基金重点项目(13JJA002)资助

详细信息
    作者简介:

    龚中汉 湖南大学信息科学与工程学院硕士研究生.2011年获得湖南大学信息科学与工程学院学士学位.主要研究方向为进化计算和数据挖掘.E-mail:hncl18@hnu.edu.cn

    通讯作者:

    张英杰 湖南大学信息科学与工程学院副教授.2005年获得湖南大学控制理论与控制工程博士学位.主要研究方向为智能控制,计算智能和节能优化控制.本文通信作者.E-mail:zhangyj@hnu.edu.cn

Community Detection in Complex Networks Using Immune Discrete Differential Evolution Algorithm

Funds: 

Supported by National Natural Science Foundation of China(61440026), Doctoral Fund of Ministry of Education of China(20110161110035), and Hunan Provincial Natural Science Foundation of China(13JJA002)

  • 摘要: 针对复杂网络社区发现问题,在标准差分进化算法的框架下,提出一种新型免疫离散差分进化算法(Immune discrete differential evolution, IDDE).该算法通过标签传播策略生成初始种群,采用离散差分进化策略来保证种群在问题空间的全局搜索能力,同时对种群中的优秀个体执行针对性的高频克隆变异操作,以提高算法的局部开发能力,改善算法的收敛性能.在计算机生成网络与真实世界网络中的仿真实验结果表明:IDDE算法具有较强的寻优性能与鲁棒性,能够有效探测复杂网络中存在的社区结构.
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出版历程
  • 收稿日期:  2014-01-10
  • 修回日期:  2014-12-02
  • 刊出日期:  2015-04-20

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