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首页> 外文期刊>Fractals: An interdisciplinary journal on the complex geometry of nature >EXPLORING THE VULNERABILITY OF FRACTAL COMPLEX NETWORKS THROUGH CONNECTION PATTERN AND FRACTAL DIMENSION
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EXPLORING THE VULNERABILITY OF FRACTAL COMPLEX NETWORKS THROUGH CONNECTION PATTERN AND FRACTAL DIMENSION

机译:通过连接模式和分形维数探索分形复合网络的脆弱性

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摘要

The structure of network has a significant impact on the stability of the network. It is useful to reveal the effect of fractal structure on the vulnerability of complex network since it is a ubiquitous feature in many real-world networks. There have been many studies on the stability of the small world and scale-free models, but little has been down on the quantitative research on fractal models. In this paper, the vulnerability was studied from two perspectives: the connection pattern between hubs and the fractal dimensions of the networks. First, statistics expression of inter-connections between any two hubs was defined and used to represent the connection pattern of the whole network. Our experimental results show that statistic values of inter-connections were obvious differences for each kind of complex model, and the more interconnections, the more stable the network was. Secondly, the fractal dimension was considered to be a key factor related to vulnerability. Here we found the quantitative power function relationship between vulnerability and fractal dimension and gave the explicit mathematical formula. The results are helpful to build stable artificial network models through the analysis and comparison of the real brain network.
机译:网络结构对网络的稳定性产生了重大影响。揭示分形结构对复杂网络脆弱性的影响是有用的,因为它在许多真实网络中是一种普遍存在的特征。有很多关于小世界和无规模模型的稳定性的研究,但对分形模型的定量研究略有下降。在本文中,从两个视角研究了该漏洞:集线器与网络的分形尺寸之间的连接模式。首先,定义任何两个集线器之间的连接之间连接的统计表达式,并用于表示整个网络的连接模式。我们的实验结果表明,对于各种复杂模型,相互连接的统计值是明显的差异,并且网络的互联越稳定。其次,分形维数被认为是与脆弱性有关的关键因素。在这里,我们发现漏洞和分形维数之间的定量功率函数关系,并给出了明确的数学公式。结果有助于通过实际脑网络的分析和比较构建稳定的人工网络模型。

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