基于随机Petri网的地震紧急医疗救援过程建模。

IF 2.6 3区 数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Journal of Systems Science & Complexity Pub Date : 2021-01-01 Epub Date: 2021-01-12 DOI:10.1007/s11424-020-9139-3
Huali Sun, Jiaguo Liu, Ziqiang Han, Juan Jiang
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引用次数: 4

摘要

灾后紧急医疗救援关系到人们的生命安全。本文提出了基于救援结构过程的随机Petri网(SPN)模型和马尔可夫链(MC)模型,并将其应用于EMR过程的优化,目的是识别EMR的关键活动。以2008年汶川地震为例,建立了地震EMR过程的同构MC模型,用于测量和评价地震EMR过程的时间性能。本文提供了一种数学方法来模拟这一过程并评估EMR的效率。同时,基于MC得到了该系统在不同状态下的稳态概率表达式,并通过改变每次跃迁的发射速率来分析概率的变化。根据事件的具体数据,作者发现了EMR决策最耗时和最关键的活动。模型结果表明,关键活动可以提高医疗救援效率,为决策者提供大尺度地震时的救援策略。
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Stochastic Petri Net Based Modeling of Emergency Medical Rescue Processes during Earthquakes.

The post-disaster emergency medical rescue (EMR) is critical for people's lives. This paper presents a stochastic Petri net (SPN) model based on the process of the rescue structure and a Markov chain model (MC), which is applied to the optimization of the EMR process, with the aim of identifying the key activities of EMR. An isomorphic MC model is developed for measuring and evaluating the time performance of the EMR process during earthquakes with the data of the 2008 Wenchuan earthquake. This paper provides a mathematical approach to simulate the process and to evaluate the efficiency of EMR. Simultaneously, the expressions of the steady state probabilities of this system under various states are obtained based on the MC, and the variations of the probabilities are analyzed by changing the firing rates for every transition. Based on the concrete data of the event, the authors find the most time consuming and critical activities for EMR decisions. The model results show that the key activities can improve the efficiency of medical rescue, providing decision-makers with rescue strategies during the large scale earthquake.

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来源期刊
Journal of Systems Science & Complexity
Journal of Systems Science & Complexity 数学-数学跨学科应用
CiteScore
3.80
自引率
9.50%
发文量
90
审稿时长
6-12 weeks
期刊介绍: The Journal of Systems Science and Complexity is dedicated to publishing high quality papers on mathematical theories, methodologies, and applications of systems science and complexity science. It encourages fundamental research into complex systems and complexity and fosters cross-disciplinary approaches to elucidate the common mathematical methods that arise in natural, artificial, and social systems. Topics covered are: complex systems, systems control, operations research for complex systems, economic and financial systems analysis, statistics and data science, computer mathematics, systems security, coding theory and crypto-systems, other topics related to systems science.
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