恶心
发表于 2025-3-25 03:33:46
Interdisciplinary Applied Mathematicshttp://image.papertrans.cn/m/image/626935.jpg
灰心丧气
发表于 2025-3-25 11:24:40
https://doi.org/10.1007/978-3-319-50806-1Dynamic Processes; Mathematical Modeling; Propagation Models; Epidemics; Stochastic processes; Mean-field
积云
发表于 2025-3-25 15:22:16
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Rustproof
发表于 2025-3-25 16:23:24
Disease spread in networks with large-scale structure,This book has developed analytic models of disease spread on networks. All of our tractable models require closure assumptions. The closure process assumes that we can explain the dynamics at the network scale by understanding the dynamics locally at the level of small units with random connections between these units.
作呕
发表于 2025-3-25 21:38:39
978-3-319-84494-7Springer International Publishing AG 2017
Occipital-Lobe
发表于 2025-3-26 02:30:13
Mathematics of Epidemics on Networks978-3-319-50806-1Series ISSN 0939-6047 Series E-ISSN 2196-9973
Osmosis
发表于 2025-3-26 04:37:12
Propagation models on networks: bottom-up,ger structures are represented in terms of smaller structures, in order to create a closed system of equations. In most cases, this representation involves an approximation, but in the case of SIR dynamics on trees or networks with ., it is possible to reduce the number of equations considerably while keeping the model exact.
Eeg332
发表于 2025-3-26 11:49:07
Mean-field approximations for homogeneous networks,re widespread in the physics and mathematical biology literature. These are used to approximate stochastic processes, with the potential to be exact in the large system or “thermodynamic” limit, see (for example, [., ., ., .] and the literature overview in Section .).
懒惰民族
发表于 2025-3-26 14:38:28
Non-Markovian epidemics, many studies . More recently, it has been shown that one can readily apply results from queueing or branching process theory, or use martingales to cast the same questions within a different framework and obtain results more readily.
的阐明
发表于 2025-3-26 19:10:54
Textbook 2017atical origin and explains how these relate to each other with special focus on epidemic spread on networks. The content of the book is at the interface of graph theory, stochastic processes and dynamical systems. The authors set out to make a significant contribution to closing the gap between mode