谢尔宾斯基地毯中基于扩散聚集生长的复杂网络及其分析

本文提出了谢尔宾斯基地毯中一种基于次近邻扩散聚集生长的复杂网络模型生成法则.通过细致的计算机仿真模拟,初步研究了该网络的一些典型数字特征:度分布、网络直径、平均路径长度、平均聚类系数、度关联系数等.研究结果表明,按照本文提出的方法产生的复杂网络具有短的平均路径长度、较高的平均聚类系数、正的度关联系数、具备明显的齐次网络特性.同时,在变动跳动概率之差时,生成网络直径、平均路径长度、网络平均聚类系数、度关联系数等呈现规律性变化;且生成网络直径、平均路径长度、度关联系数与网络平均聚类系数呈负相关.

New complex network model based on diffusion aggregation growth mechanism in Sierpinski carpet and its analysis

In this paper,a new complex network model based on diffusion aggregation with next-nearest neighbor growth mechanism in Sierpinski carpet is proposed. Some typical characteristics of the generated networks are carefully investigated through computer simulations,including the network diameter,the average path length,the degree distribution,clustering coefficient,degree correlation etc. Our research shows that the complex network produced by our method has short average path length,high clustering coefficient,positive degree correlation and some typical characters of a homogeneous network. We also found that,the diameter,average path length,clustering coefficient and degree correlation have a regular change with different jumping probabilities chosen in our numerical experiments. Furthermore,the change of those characters with deviation between jumping probability Q and S are also investigated. The results show that the change of network diameter,average path length and degree correlation are negative correlation with that of the network clustering coefficient.