The small-world effect of fractal networks modeled on 'dust-like' cubes

Cheng Zeng; Yuke Huang; Yumei Xue

doi:10.1142/S0217984922501585

The small-world effect of fractal networks modeled on 'dust-like' cubes

Cheng Zeng
, Yuke Huang^*
, Yumei Xue

^*此作品的通讯作者

数学科学学院

Shandong Technology and Business University
Beijing University of Posts and Telecommunications

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

In this paper, the sequence of evolving networks is generated from some 'dust-like' cubes by applying the encoding methods in fractal and symbolic dynamical systems. Based on the self-similar structures of fractals, we study the mean clustering coefficient, the mean geodesic distance and the mean Fermat distance. The relevant results show the small-world effect of our evolving networks.

源语言	英语
文章编号	2250158
期刊	Modern Physics Letters B
卷	36
期	28-29
DOI	https://doi.org/10.1142/S0217984922501585
出版状态	已出版 - 10 10月 2022

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10.1142/S0217984922501585

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abstract = "In this paper, the sequence of evolving networks is generated from some 'dust-like' cubes by applying the encoding methods in fractal and symbolic dynamical systems. Based on the self-similar structures of fractals, we study the mean clustering coefficient, the mean geodesic distance and the mean Fermat distance. The relevant results show the small-world effect of our evolving networks.",

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AB - In this paper, the sequence of evolving networks is generated from some 'dust-like' cubes by applying the encoding methods in fractal and symbolic dynamical systems. Based on the self-similar structures of fractals, we study the mean clustering coefficient, the mean geodesic distance and the mean Fermat distance. The relevant results show the small-world effect of our evolving networks.

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KW - self-similarity

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The small-world effect of fractal networks modeled on 'dust-like' cubes

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