基于基因表达式编程算法的复杂网络社区结构划分  

Community structure division in complex networks based on gene expression programming algorithm

作　　者：罗锦坤[1] 元昌安[1] 杨文[1] 胡卉颖[1] 袁晖[1] 

机构地区：[1]广西师范学院计算机与信息工程学院,南宁530023

出　　处：《计算机应用》2012年第2期317-321,共5页journal of Computer Applications

基　　金：国家自然科学基金资助项目(60763012);广西自然科学基金资助项目(2011GXNSFD018025);广西研究生教育创新计划资助项目(2011106030703M05)

摘　　要：由于复杂网络的不确定性,传统的复杂网络社区结构划分算法易造成过早收敛,使精度降低,且由于计算量大,时间复杂度较高。为克服以上不足,利用基因表达式编程(GEP)的自适应性和全局搜索能力强以及具有并行性计算等特点,优化网络社区结构的划分,提出了一种基于GEP的复杂网络社区结构划分算法,并通过实验验证了新算法的有效性。新算法在无先验信息情况下,可较准确地完成对复杂网络的社区划分。Due to the uncertainty of complex networks, traditional community structures division algorithm of the complex network could easily lead to premature convergence and decreased accuracy. And because of the large amount of computation, time complexity is high. To overcome the above shortcomings, the paper adopted GEP＇s global search ability and adaptability, and other characteristics with parallel calculations, optimized the network structure of the division of community, and proposed a community structure division algorithm of complex network based on GEP, and verified the validity of the new algorithm by experiment. The new algorithm has more accurate community division of the complex network in the case of no prior information.

关 键 词：复杂网络 社区划分 基因表达式编程 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]