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加权网络中的疫情传播:基于边的平均场解。

Epidemic spreading in weighted networks: an edge-based mean-field solution.

作者信息

Yang Zimo, Zhou Tao

机构信息

Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2012 May;85(5 Pt 2):056106. doi: 10.1103/PhysRevE.85.056106. Epub 2012 May 7.

Abstract

Weight distribution greatly impacts the epidemic spreading taking place on top of networks. This paper presents a study of a susceptible-infected-susceptible model on regular random networks with different kinds of weight distributions. Simulation results show that the more homogeneous weight distribution leads to higher epidemic prevalence, which, unfortunately, could not be captured by the traditional mean-field approximation. This paper gives an edge-based mean-field solution for general weight distribution, which can quantitatively reproduce the simulation results. This method could be applied to characterize the nonequilibrium steady states of dynamical processes on weighted networks.

摘要

权重分布对网络上发生的疫情传播有很大影响。本文研究了具有不同权重分布的规则随机网络上的易感-感染-易感模型。模拟结果表明,权重分布越均匀,疫情流行程度越高,遗憾的是,传统的平均场近似无法捕捉到这一点。本文给出了一种针对一般权重分布的基于边的平均场解,它可以定量地重现模拟结果。该方法可用于刻画加权网络上动态过程的非平衡稳态。

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