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Modelling presymptomatic infectiousness in COVID-19 模拟COVID-19的症状前传染性
4区 工程技术 Q1 Mathematics Pub Date : 2023-03-23 DOI: 10.1080/17477778.2023.2190467
Russell Cheng, Christopher Dye, John Dagpunar, Brian Williams
This paper considers SEPIR, an extension of the well-known SEIR continuous simulation compartment model. Both models can be fitted to real data as they include parameters that can be estimated from the data. SEPIR deploys an additional presymptomatic infectious compartment, not modelled in SEIR but known to exist in COVID-19. This stage can also be fitted to data. We focus on how to fit SEPIR to a first wave of COVID. Both SEIR and SEPIR and the existing SEIR models assume a homogeneous mixing population with parameters fixed. Moreover, neither includes dynamically varying control strategies deployed against the virus. If either model is to represent more than just a single wave of the epidemic, then the parameters of the model would have to be time dependent. In view of this, we also show how reproduction numbers can be calculated to investigate the long-term overall outcome of an epidemic.
本文考虑的是对著名的连续仿真室模型SEIR的扩展。两种模型都可以拟合到实际数据中,因为它们包含了可以从数据中估计出来的参数。SEPIR部署了一个额外的症状前感染室,在SEIR中没有建模,但已知在COVID-19中存在。这个阶段也可以适用于数据。我们专注于如何使SEPIR适应第一波COVID。SEIR和SEPIR以及现有的SEIR模型都假设了一个参数固定的均匀混合种群。此外,两者都不包括针对病毒部署的动态变化控制策略。如果任何一个模型要代表的不仅仅是一波流行病,那么模型的参数就必须是时间相关的。鉴于此,我们还说明如何计算繁殖数量以调查流行病的长期总体结果。
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引用次数: 2
Using a hybrid simulation model to assess the impacts of combined COVID-19 containment measures in a high-speed train station 使用混合模拟模型评估新冠肺炎联合控制措施对高速火车站的影响
IF 2.5 4区 工程技术 Q1 Mathematics Pub Date : 2023-03-20 DOI: 10.1080/17477778.2023.2189027
Hongli Zhu, Shiyong Liu, Xiaoyan Li, Weiwei Zhang, Nathaniel Osgood, P. Jia
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引用次数: 3
Hybrid Simulation Modelling of Emergency Departments for Resource Scheduling 应急部门资源调度的混合仿真建模
IF 2.5 4区 工程技术 Q1 Mathematics Pub Date : 2023-03-15 DOI: 10.1080/17477778.2023.2187321
Yinling Liu, T. Moyaux, G. Bouleux, V. Cheutet
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引用次数: 0
Modelling the leaping cycle by modified Lotka-Volterra equations with applications to technology and safety 用改进的Lotka-Volterra方程模拟跳跃周期及其在技术和安全方面的应用
IF 2.5 4区 工程技术 Q1 Mathematics Pub Date : 2023-03-08 DOI: 10.1080/17477778.2023.2176794
A. Klimenko
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引用次数: 0
Queueing inspired feature engineering to improve and simplify patient flow simulation metamodels 受排队启发的特征工程,用于改进和简化患者流模拟元模型
IF 2.5 4区 工程技术 Q1 Mathematics Pub Date : 2023-02-26 DOI: 10.1080/17477778.2023.2181716
M. Isken, Osman T. Aydas, Yazan F. Roumani
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引用次数: 1
A lane-changing behaviour algorithm for connected and autonomous vehicles to facilitate emergency vehicle movements on urban arterials in microsimulation 一种用于联网和自动驾驶车辆的变道行为算法,用于在微观模拟中促进城市主干道上的紧急车辆移动
IF 2.5 4区 工程技术 Q1 Mathematics Pub Date : 2023-02-20 DOI: 10.1080/17477778.2023.2179948
Mohamadreza Haghani, A. Hosseinzadeh, Robert Kluger
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引用次数: 0
A new teaching approach exploiting lab-scale models of manufacturing systems for simulation classes 利用实验室规模的制造系统模型进行仿真课程的新教学方法
IF 2.5 4区 工程技术 Q1 Mathematics Pub Date : 2023-02-10 DOI: 10.1080/17477778.2023.2174458
Giovanni Lugaresi, Nicla Frigerio, Ziwei Lin, Mengyi Zhang, A. Matta
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引用次数: 0
Discrete event simulation as a decision tool: a cost benefit analysis case study 离散事件模拟作为决策工具:成本效益分析案例研究
IF 2.5 4区 工程技术 Q1 Mathematics Pub Date : 2023-02-06 DOI: 10.1080/17477778.2023.2167618
G. Rotunno, Giacomo Lo Zupone, L. Carnimeo, M. P. Fanti
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引用次数: 1
Simheuristic and learnheuristic algorithms for the temporary-facility location and queuing problem during population treatment or testing events 群体处理或测试事件中临时设施位置和排队问题的模拟启发式和学习启发式算法
IF 2.5 4区 工程技术 Q1 Mathematics Pub Date : 2023-01-24 DOI: 10.1080/17477778.2023.2166879
C. Bayliss, Javier Panadero
Epidemic outbreaks, such as the one generated by the coronavirus disease, have raised the need for more efficient healthcare logistics. One of the challenges that many governments have to face in such scenarios is the deployment of temporary medical facilities across a region with the purpose of providing medical services to their citizens. This work tackles this temporary-facility location and queuing problem with the goals of minimising costs, the expected completion time, population travel time, and waiting time. The completion time for a facility depends on the numbers assigned to those facilities as well as stochastic arrival times. This work proposes a learnheuristic algorithm to solve the facility location and population assignment problem. Firstly a machine learning algorithm is trained using data from a queuing model (simulation module). The learnheuristic then constructs solutions using the machine learning algorithm to rapidly evaluate decisions in terms of facility completion and population waiting times. The efficiency and quality of the algorithm is demonstrated by comparison with exact and simulation-only (simheuristic) methodologies. A series of experiments are performed which explore the trade-offs between solution cost, completion time, population travel time, and waiting time. © 2023 The Operational Research Society.
疫情爆发,如冠状病毒疾病引发的疫情,提高了对更高效医疗物流的需求。在这种情况下,许多政府必须面临的挑战之一是在整个地区部署临时医疗设施,为其公民提供医疗服务。这项工作解决了这个临时设施的位置和排队问题,目的是最大限度地减少成本、预期完工时间、人口出行时间和等待时间。设施的完工时间取决于分配给这些设施的数字以及随机到达时间。本文提出了一种学习启发式算法来解决设施选址和人口分配问题。首先,使用来自排队模型(模拟模块)的数据来训练机器学习算法。然后,学习启发式使用机器学习算法构建解决方案,以根据设施完成情况和人口等待时间快速评估决策。通过与精确和仅模拟(simheuristic)方法的比较,证明了该算法的效率和质量。进行了一系列实验,探讨了解决方案成本、完成时间、人口旅行时间和等待时间之间的权衡。©2023运营研究学会。
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引用次数: 1
Agent-based modelling and simulation for life-cycle airport flight planning and scheduling 基于Agent的全生命周期机场飞行计划与调度建模与仿真
IF 2.5 4区 工程技术 Q1 Mathematics Pub Date : 2023-01-24 DOI: 10.1080/17477778.2023.2169643
Xiaoyu Ma, Zhou He, Pengfei Yang, Xiyang Liao, W. Liu
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引用次数: 0
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Journal of Simulation
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