Modeling the self-similarity in complex networks based on Coulomb's law

被引：32

作者：

Zhang, Haixin ^{[1
,2
]}

Wei, Daijun ^{[1
,3
]}

Hu, Yong ^{[4
]}

Lan, Xin ^{[1
]}

Deng, Yong ^{[1
,5
]}

机构：

[1] Southwest Univ, Sch Comp & Informat Sci, Chongqing 400715, Peoples R China

[2] Chongqing Univ, Coll Comp Sci, Chongqing 400044, Peoples R China

[3] Hubei Univ Nationalities, Sch Sci, Enshi 445000, Peoples R China

[4] Guangdong Univ Foreign Studies, Inst Business Intelligence & Knowledge Discovery, Guangzhou 510006, Guangdong, Peoples R China

[5] Vanderbilt Univ, Sch Engn, Nashville, TN 37235 USA

来源：

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION | 2016年 / 35卷

基金：

中国国家自然科学基金;

关键词：

Self similarity; Complex networks; Fractal dimension; Coulomb's law; IDENTIFYING INFLUENTIAL NODES; WEIGHTED NETWORKS; FRACTALITY; TIME;

D O I：

10.1016/j.cnsns.2015.10.017

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Recently, self similarity of complex networks have attracted much attention. Fractal dimension of complex network is an open issue. Hub repulsion plays an important role in fractal topologies. This paper models the repulsion among the nodes in the complex networks in calculation of the fractal dimension of the networks. Coulomb's law is adopted to represent the repulse between two nodes of the network quantitatively. A new method to calculate the fractal dimension of complex networks is proposed. The Sierpinski triangle network and some real complex networks are investigated. The results are illustrated to show that the new model of self -similarity of complex networks is reasonable and efficient. (C) 2015 Elsevier B.V. All rights reserved.

引用

页码：97 / 104

页数：8

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