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随机派系生长网络模型及其传输能力研究?
Random clique evolving network model and their communicability?

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丁益民 1   樊京芳 2   周斌 3   陈晓松 2 *  
文摘 本文提出一种基于随机选择的派系生长网络模型, 该网络从一个a-派系模体开始, 每个时间步 t, 在网络中随机选择m 个节点构建一个新的a-派系, 由此网络生长演化. 模拟研究表明: 该网络具有高的聚类系数和短的平均路径长度是一个小世界网络, 并且比值ρ=m/a 越小, 聚类系数越大. 而度分布则呈指数分布, 这些特征与许多交通系统的复杂网络的实证研究结果相符. 该网络的聚类系数与节点度呈幂律变化, 显示网络具有模块化层次结构的特征, 这一特征与近年来人们研究的大多数复杂网络具有模块化层次结构特征的实证研究结果相符. 我们还研究了该网络的传输能力, 研究表明该网络的传输能力随着比值ρ=m/a 的减小而增大. 这些研究结果对城市公共交通网络的构建具有一定的指导意义.
其他语种文摘 We introduce a notion of random clique evolving network, this network start from a complete subgraph of a-clique, where a is the size of the clique. In every time step T, m nodes are chosen from this network randomly, and forming a new complete subgraph of a-clique. In this way, this network grows in time steps. The numerical investigation shows that the cumulative degree distribution of this network takes an exponential function, which is the property of the homogeneous networks, and the clustering coefficient of this network is larger than that of the ER network. However, the characteristic path length of this network is the similar to that of the ER network, so this network shows the behaviors of small-world networks. Subsequent study shows that this network exhibits hierarchical modular structure for the clustering spectrum vs. k takes power-law. These results are in good agreement with the empirical results on many real-world complex networks, such as urban bus translation network or urban subway network, our model can explain the evolutionary procedure of these spatial networks. What’s more, we present a numerical investigation on the communicability of our model by the Estrada index EE(G), the Estrada index EE(G) of this network increases with decreasing the rata m/a at the same size N and the same average degree<k>. The communicability of the urban public translation networks is very important, our results have a certain guiding significance for the construction of urban bus translation network and urban subway network.
来源 中国科学. 物理学 , 力学, 天文学,2014,44(3):299-304 【核心库】
DOI 10.1360/sspma2013-00083
关键词 复杂网络 ; 派系 ; 层次结构 ; 传输能力
地址

1. 湖北大学物理学与电子技术学院, 理论物理国家重点实验室, 武汉, 430062  

2. 中国科学院理论物理研究所, 理论物理国家重点实验室, 北京, 100190  

3. 湖北大学物理学与电子技术学院, 武汉, 430062

语种 中文
文献类型 研究性论文
ISSN 1674-7275
基金 国家自然科学基金 ;  理论物理国家重点实验室开放式课题
文献收藏号 CSCD:5061218

参考文献 共 22 共2页

1.  Watts D J. Collective dynamics of"small-world" networks. Nature,1998,393:440-442 被引 2720    
2.  Barabasi A L. Emergence of scaling in random networks. Science,1999,286:509-512 被引 2314    
3.  Albert R. Statistical mechanics of complex networks. Rev Mod Phys,2002,74:47-97 被引 1174    
4.  Newman M E J. The structure and function of complex networks. SIAM Rev,2003,45:167-256 被引 969    
5.  Boccaletti S. Complex networks: Structure and dynamics. Phys Rep,2006,424:175-308 被引 502    
6.  何大韧. 复杂系统与复杂网络,2009:95-100 被引 1    
7.  Milo R. Network motifs: Simple building blocks of complex networks. Science,2002,298:824-827 被引 192    
8.  Milo R. Superfaimilies organization of modularity in metabolic networks. Science,2004,303:1538-1542 被引 53    
9.  Song C. Self-similarity of complex networks. Nature,2005,433:392-395 被引 65    
10.  Palla G. Uncovering the overlapping community structure of complex networks in nature and society. Nature,2005,435:814-818 被引 455    
11.  Xiao W K. Empirical study on clique-degree distribution of networks. Phys Rev E,2007,76:037102 被引 9    
12.  Clauset A. Hierarchical structure and the prediction of missing links in networks. Nature,2008,453:98-101 被引 128    
13.  Bathelemy M. Spatial networks. Phys Rep,2011,499:1-101 被引 1    
14.  Sen P. Small-world properties of the Indian railway network. Phys Rev E,2003,67:036106 被引 65    
15.  Seaton K A. Stations, trains and small-world networks. Phys A,2004,339:635-644 被引 32    
16.  Sienkiewicz J. Statistical analysis of 22 public transport networks in Poland. Phy Rev E,2005,72:046127 被引 64    
17.  Chen Y Z. A study on some urban bus transport networks. Phys A,2007,376:747-754 被引 1    
18.  Yang X H. Bus transport network model with ideal n-depth clique network topology. Phys A,2011,390:4660-4672 被引 1    
19.  丁益民. 基于社团结构的城市地铁网络模型研究. 物理学报,2013,62(9):098901 被引 4    
20.  Takemoto K. Evolving networks by merging cliques. Phy Rev E,2005,72:0461117 被引 9    
引证文献 1

1 丁益民 随机派系网络的渗流相变研究 中国科学. 物理学, 力学, 天文学,2016,46(6):60502-1-60502-8
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