DISCRETE EVENT DYNAMIC SYSTEMS-THEORY AND APPLICATIONS离散事件动态系统：理论与应用
DISCRETE EVENT DYNAMIC SYSTEMS-THEORY AND APPLICATIONS(英文缩写 DISCRETE EVENT DYN S),ISSN 0924-6703,eISSN 1573-7594,中文译名:离散事件动态系统：理论与应用 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。
发文量统计区间：2025-10-01 至 2026-09-30，按本站收录文献的发表日期统计。
期刊介绍
历年影响因子趋势
| JCR 数据年份 | 影响因子 | JCR 分区 |
|---|---|---|
| 2021 | 1.182 | Q3 |
| 2022 | 2.000 | Q2 |
| 2023 | 1.400 | Q2 |
| 2024 | 1.600 | Q2 |
| 2025 | 1.000 | Q3 |
DISCRETE EVENT DYNAMIC SYSTEMS-THEORY AND APPLICATIONS 最新收录文献
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1. Flexible Nets: a modeling formalism for dynamic systems with uncertain parameters.
PMID:日期:2019-08-22The modeling of dynamic systems is frequently hampered by a limited knowledge of the system to be modeled and by the difficulty of acquiring accurate data. This often results in a number of uncertain system parameters that are hard to incorporate into a mathematical model. Thus, there is a need for modeling formalisms that can accommodate all available data, even if uncertain, in order to employ them and build useful models. This paper shows how the Flexible Nets (FNs) formalism can be exploited to handle uncertain parameters while offering attractive analysis possibilities. FNs are composed of two nets, an event net and an intensity net, that model the relation between the state and the processes of the system. While the event net captures how the state of the system is updated by the processes in the system, the intensity net models how the speed of such processes is determined by the state of the system. Uncertain parameters are accounted for by sets of inequalities associated with both the event net and the intensity net. FNs are not only demonstrated to be a valuable formalism to cope with system uncertainties, but also to be capable of modeling different system features, such as resource allocation and control actions, in a facile manner.
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2. A random walk model for infection on graphs: spread of epidemics & rumours with mobile agents.
PMID:日期:2010-08-17We address the question of understanding the effect of the underlying network topology on the spread of a virus and the dissemination of information when users are mobile performing independent random walks on a graph. To this end, we propose a simple model of infection that enables to study the coincidence time of two random walkers on an arbitrary graph. By studying the coincidence time of a susceptible and an infected individual both moving in the graph we obtain estimates of the infection probability. The main result of this paper is to pinpoint the impact of the network topology on the infection probability. More precisely, we prove that for homogeneous graphs including regular graphs and the classical Erdős-Rényi model, the coincidence time is inversely proportional to the number of nodes in the graph. We then study the model on power-law graphs, that exhibit heterogeneous connectivity patterns, and show the existence of a phase transition for the coincidence time depending on the parameter of the power-law of the degree distribution. We finally undertake a preliminary analysis for the case with random walkers and provide upper bounds on the convergence time for both the complete graph and regular graphs.