网络传播过程的单调收敛性

Gadi Fibich, Amit Golan, Steven Schochet
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引用次数: 0

摘要

我们分别在同质完整网络、环形网络和有两个同质群体的异质完整网络上分析了创新和流行病传播的巴斯模型和SI模型。我们允许网络参数与时间相关,这是分析网络最优策略的前提条件。通过对主方程进行新颖的自顶向下分析,我们给出了这些模型单调收敛到各自无限人口极限的简单证明。由此,我们分别得出了在无限同质完整网络和循环网络上,以及在具有两个同质组且参数随时间变化的异质完整网络上,Bass 和 SI 模型的预期采用或感染水平的明确表达式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Monotone convergence of spreading processes on networks
We analyze the Bass and SI models for the spreading of innovations and epidemics, respectively, on homogeneous complete networks, circular networks, and heterogeneous complete networks with two homogeneous groups. We allow the network parameters to be time dependent, which is a prerequisite for the analysis of optimal strategies on networks. Using a novel top-down analysis of the master equations, we present a simple proof for the monotone convergence of these models to their respective infinite-population limits. This leads to explicit expressions for the expected adoption or infection level in the Bass and SI models, respectively, on infinite homogeneous complete and circular networks, and on heterogeneous complete networks with two homogeneous groups with time-dependent parameters.
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