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无尺度网络平均路径长度的估计
引用本文:刘业政,周云龙. 无尺度网络平均路径长度的估计[J]. 系统工程理论与实践, 2014, 34(6): 1566-1571. DOI: 10.12011/1000-6788(2014)6-1566
作者姓名:刘业政  周云龙
作者单位:1. 合肥工业大学 管理学院, 合肥 230009;2. 过程优化与智能决策教育部重点实验室, 合肥 230009
基金项目:“973”计划(2013CB329603);国家自然科学基金(71071047);教育部人文社科基金(12YJC630073)
摘    要:无尺度网络的拓扑结构研究主要集中于聚类系数和平均路径长度的计算以及度分布分析. 在实际的无尺度网络中,表征网络拓扑结构的三个参数之间是互相联系的,其中一个参数均可近似用另外两个参数表示. 鉴于此,针对大规模无尺度网络的平均路径长度计算问题,基于树形结构模型给出了无尺度网络平均路径长度<l>SF 的计算公式,并分析了网络规模和节点间连接方式对平均路径长度的影响. 分析结果表明,<l>SF与无尺度网络的平均度数k、平均聚类系数C以及幂指数γ有关,从而将直接求解平均路径长度的复杂问题转化为间接求解,大大提高了分析无尺度网络拓扑结构的效率. 实验结果表明,提出的无尺度网络平均路径长度计算公式是有效的.

关 键 词:无尺度网络  聚类系数  平均路径长度  度分布  树形结构模型  
收稿时间:2012-06-18

Estimation for the average path length of scale-free networks
LIU Ye-zheng,ZHOU Yun-long. Estimation for the average path length of scale-free networks[J]. Systems Engineering —Theory & Practice, 2014, 34(6): 1566-1571. DOI: 10.12011/1000-6788(2014)6-1566
Authors:LIU Ye-zheng  ZHOU Yun-long
Affiliation:1. School of Management, Hefei University of Technology, Hefei 230009, China;2. The MOE Key Laboratory of Process Optimization and Intelligent Decision-making, Hefei 230009, China
Abstract:Studying the topology of scale-free networks mainly concentrates on computing clustering coefficient and average path length, and analyzing degree distribution. This paper argues that in real world, the three parameters are interrelated. A parameter can be replaced by the other two parameters. According to the viewpoint, this paper gives a formula to compute the average path length <l>SF of large scale-free networks based on a tree structure model, and analyzes the impact of network scale and junction between nodes on <l>SF. The results indicate that <l>SF is related to average degreek, average clustering coefficient C and power exponent γ which are three parameters characterizing the topology of scale-free networks. Therefore, the complexity can be reduced by transferring computing average path length directly to indirectly. The experiments' results show that the formula is valid and the efficiency of studying the topology of large scale-free networks is greatly raised.
Keywords:scale-free networks  clustering coefficient  average path length  degree distribution  tree structure model  
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