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.
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页数：5
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