学位(音乐)
聚类系数
迭代函数
分层网络模型
无标度网络
班级(哲学)
计算机科学
比例(比率)
数学
复杂网络
价值(数学)
层次聚类
特征(语言学)
聚类分析
统计物理学
理论计算机科学
组合数学
人工智能
统计
物理
数学分析
哲学
量子力学
语言学
声学
作者
Jia‐Bao Liu,YAN BAO,Wuting Zheng
出处
期刊:Fractals
[World Scientific]
日期:2022-06-09
卷期号:30 (07)
被引量:46
标识
DOI:10.1142/s0218348x22501365
摘要
Hierarchical networks as fundamental models to describe the complex networks, have many applications in networks science, engineering technology and so on. In this paper, we first propose a new class of hierarchical networks with fractal structure, which are the networks with triangles compared to traditional hierarchical networks. Second, we study the precise results of some structural properties to derive small-world effect and scale-free feature. Third, it is found that the constructed network is sparse through the average degree and density. Fourth, it is also demonstrated that the degree distributions of hub nodes and the bottom nodes are the power law and exponential, respectively. Finally, we prove that clustering coefficient with a definite value [Formula: see text] tends to stabilize at a lower bound as [Formula: see text] iterates to a certain number, and the average distance of [Formula: see text] has an increasing relationship along with the value of [Formula: see text].
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