Rank-dependent deactivation in network evolution

被引：6

作者：

Xu, Xin-Jian ^{[1
,2
]}

Zhou, Ming-Chen ^{[1
]}

机构：

[1] Shanghai Univ, Coll Sci, Dept Math, Shanghai 200444, Peoples R China

[2] Shanghai Univ, Inst Syst Sci, Shanghai 200444, Peoples R China

来源：

PHYSICAL REVIEW E | 2009年 / 80卷 / 06期

关键词：

complex networks; graph theory; probability; random processes; COMPLEX NETWORKS; WORLD;

D O I：

10.1103/PhysRevE.80.066105

中图分类号：

O35 [流体力学]; O53 [等离子体物理学];

学科分类号：

070204 ; 080103 ; 080704 ;

摘要：

A rank-dependent deactivation mechanism is introduced to network evolution. The growth dynamics of the network is based on a finite memory of individuals, which is implemented by deactivating one site at each time step. The model shows striking features of a wide range of real-world networks: power-law degree distribution, high clustering coefficient, and disassortative degree correlation.

引用

页数：5

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