Robustness and Statistical Characters of a Class of Complex Network Models
Robustness and Statistical Characters of a Class of Complex Network Models
复制标题
一类复杂网络模型的鲁棒性和统计特性
DOI：
10.1007/978-3-642-25778-0_105
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Xi-rong Ma
中科院分区：
文献类型：
--
作者：
Wei-dong Pei;Wei Xia;Xi-rong Ma
A class of dynamic complex network evolving models with multi-triangular structure is given. By utilizing the mean-field theory, it is proved that the models have the probability of power-law degree distribution with large average coefficient clusters. Then, by MATLAB tools, robustness of the models is analyzed according to two attacking strategies: random attack and max-degree attack. The results show that the robustness of the models are similar as that of the BA models at random attack, but the models are more vulnerable than that of the BA models at max-degree attack.
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