APPLIED MATHEMATICAL MODELLING应用数学建模
APPLIED MATHEMATICAL MODELLING(英文缩写 APPL MATH MODEL),ISSN 0307-904X,eISSN 1872-8480,中文译名:应用数学建模 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：2025-11-01 至 2026-10-31，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 | 5.336 | Q1 |
| 2022 | 5.000 | Q1 |
| 2023 | 4.400 | Q1 |
| 2024 | 5.100 | Q1 |
| 2025 | 5.500 | Q1 |
APPLIED MATHEMATICAL MODELLING 最新收录文献
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1. State-space formulations to understand the nonlinear viscoelastic mechanical behavior of tricuspid valve chordae tendineae.
1. 用于理解三尖瓣腱索非线性粘弹性力学行为的态空间公式化方法PMID:日期:2025-06-25[中文摘要] 状态空间表示法是系统理论中除输入-输出表示法之外对动力系统的另一种描述方式。本文采用状态空间表示法研究三尖瓣（tricuspid valve, TV）腱索的力学行为。三尖瓣腱索在载荷作用下表现出黏弹性特征，因此我们将带有附加非线性弹簧的广义Kelvin模型转化为状态空间描述，以建立不同载荷条件下的解。借助状态空间表示法，在力控制情况下可以解析获得位移响应的闭式解。考虑到生物软组织抗压缩特性，推导了在非零均值正弦循环力作用下的精确响应。相比之下，在位移输入下，状态空间表示法导致非线性动力系统，使得力响应的解析解无法获得。因此，我们借助状态空间表示法开发了一种数值方案来求解相应的力响应。基于解析解，我们进一步证明，广泛用于黏弹性材料建模的传统动态力学分析（dynamic mechanical analysis, DMA）测试不适用于识别三尖瓣腱索的非线性黏弹性力学特征。
[英文摘要] The state-space representation is an alternative description of a dynamical system to the input-output representation in the systems theory. In this paper, we used the state-space representation to study the mechanical behavior of the tricuspid valve (TV) chordae tendineae. The TV chordae behave viscoelastic features under the loading; hence, we cast the generalized Kelvin model with an additional nonlinear spring into the state-space description to develop the solution under different loading conditions. With the aid of the state-space representation, the closed-form solution of the displacement response can be analytically obtained, for the case of force control. Taking into account the in-resistance of compression of biological soft tissue, the exact response to a sinusoidal cyclic force with non-zero mean was derived. In contrast, under displacement input, the state-space representation resulted in a nonlinear dynamical system and made the analytical solution of the force response is unreachable. Thus, we developed a numerical scheme to solve the corresponding force response with the aid of the state-space representation. Based on the analytical solution, we further demonstrated that conventional dynamic mechanical analysis (DMA) testing, which has been widely used in modeling viscoelastic materials, is not suitable for the identification of the nonlinear, viscoelastic mechanical features of the TV chordae.
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2. A Stochastic Mobility-Driven Spatially Explicit SEIQRD covid-19 Model with VOCs, Seasonality, and Vaccines.
2. 一种由随机移动驱动的、具有 VOC、季节性和疫苗的时空显式 SEIQRD covid-19 模型PMID:日期:2023-06-29In this work, we extend our previously developed compartmental SEIQRD model for sars-cov-2 in Belgium. We introduce sars-cov-2 variants of concern, vaccines, and seasonality in our model, as their addition has proven necessary for modelling sars-cov-2 transmission dynamics during the 2020-2021 covid-19 pandemic in Belgium. The model is geographically stratified into eleven spatial patches (provinces), and a telecommunication dataset provided by Belgium's biggest operator is used to incorporate interprovincial mobility. We calibrate the model using the daily number of hospitalisations in each province and serological data. We find the model adequately describes these data, but the addition of interprovincial mobility was not necessary to obtain an accurate description of the 2020-2021 sars-cov-2 pandemic in Belgium. We further demonstrate how our model can be used to help policymakers decide on the optimal timing of the release of social restrictions.We find that adding spatial heterogeneity by geographically stratifying the model results in more uncertain model projections as compared to an equivalent nation-level model, which has both communicative advantages and disadvantages. We finally discuss the impact of imposing local mobility or social contact restrictions to contain an epidemic in a given province and find that lowering social contact is a more effective strategy than lowering mobility.
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3. Stationary flow driven by non-sinusoidal time-periodic pressure gradients in wavy-walled channels.
PMID:日期:2023-06-17The classical problem of secondary flow driven by a sinusoidally varying pressure gradient is extended here to address periodic pressure gradients of complex waveform, which are present in many oscillatory physiological flows. A slender two-dimensional wavy-walled channel is selected as a canonical model problem. Following standard steady-streaming analyses, valid for small values of the ratio of the stroke length of the pulsatile motion to the channel wavelength, the spatially periodic flow is described in terms of power-law expansions of , with the Womersley number assumed to be of order unity. The solution found at leading order involves a time-periodic velocity with a zero time-averaged value at any given point. As in the case of a sinusoidal pressure gradient, effects of inertia enter at the following order to induce a steady flow in the form of recirculating vortices with zero net flow rate. An improved two-term asymptotic description of this secondary flow is sought by carrying the analysis to the following order. It is found that, when the pressure gradient has a waveform with multiple harmonics, the resulting velocity corrections display a nonzero flow rate, not present in the single-frequency case, which enables stationary convective transport along the channel. Direct numerical simulations for values of of order unity are used to investigate effects of inertia and delineate the range of validity of the asymptotic limit . The comparisons of the time-averaged velocity obtained numerically with the two-term asymptotic description reveals that the latter remains remarkably accurate for values of exceeding 0.5. As an illustrative example, the results of the model problem are used to investigate the cerebrospinal-fluid flow driven along the spinal canal by the cardiac and respiratory cycles, characterized by markedly non-sinusoidal waveforms.
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4. Individual preferences, government policy, and COVID-19: A game-theoretic epidemiological analysis.
4. 个体偏好、政府政策与COVID-19：基于博弈论的流行病学分析PMID:日期:2023-06-11The ongoing COVID-19 pandemic imposes serious short-term and long-term health costs on populations. Restrictive government policy measures decrease the risks of infection, but produce similarly serious social, mental health, and economic problems. Citizens have varying preferences about the desirability of restrictive policies, and governments are thus forced to navigate this tension in making pandemic policy. This paper analyses the situation facing government using a game-theoretic epidemiological model. We classify individuals into health-centered individuals and freedom-centered individuals to capture the heterogeneous preferences of citizens. We first use the extended Susceptible-Exposed-Asymptomatic-Infectious-Recovered (SEAIR) model (adding individual preferences) and the signaling game model (adding government) to analyze the strategic situation against the backdrop of a realistic model of COVID-19 infection. We find the following: 1. There exists two pooling equilibria. When health-centered and freedom-centered individuals send anti-epidemic signals, the government will adopt strict restrictive policies under budget surplus or balance. When health-centered and freedom-centered individuals send freedom signals, the government chooses not to implement restrictive policies. 2. When governments choose not to impose restrictions, the extinction of an epidemic depends on whether it has a high infection transmission rate; when the government chooses to implement non-pharmacological interventions (NPIs), whether an epidemic will disappear depends on how strict the government's restrictions are. Based on the existing literature, we add individual preferences and put the government into the game as a player. Our research extends the current form of combining epidemiology and game theory. By using both we get a more realistic understanding of the spread of the virus and combine that with a richer understanding of the strategic social dynamics enabled by game theoretic analysis. Our findings have important implications for public management and government decision-making in the context of COVID-19 and for potential future public health emergencies.
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5. Disentangling the role of virus infectiousness and awareness-based human behavior during the early phase of the COVID-19 pandemic in the European Union.
5. 在欧盟新冠疫情早期阶段，解析病毒传染性与基于认知的人类行为的作用PMID:日期:2023-05-29In this work, we manage to disentangle the role of virus infectiousness and awareness-based human behavior in the COVID-19 pandemic. Using Bayesian inference, we quantify the uncertainty of a state-space model whose propagator is based on an unusual SEIR-type model since it incorporates the effective population fraction as a parameter. Within the Markov Chain Monte Carlo (MCMC) algorithm, Unscented Kalman Filter (UKF) may be used to evaluate the likelihood approximately. UKF is a suitable strategy in many cases, but it is not well-suited to deal with non-negativity restrictions on the state variables. To overcome this difficulty, we modify the UKF, conveniently truncating Gaussian distributions, which allows us to deal with such restrictions. We use official infection notification records to analyze the first 22 weeks of infection spread in each of the 27 countries of the European Union (EU). It is known that such records are the primary source of information to assess the early evolution of the pandemic and, at the same time, usually suffer underreporting and backlogs. Our model explicitly accounts for uncertainty in the dynamic model parameters, the dynamic model adequacy, and the infection observation process. We argue that this modeling paradigm allows us to disentangle the role of the contact rate, the effective population fraction, and the infection observation probability across time and space with an imperfect first principles model. Our findings agree with phylogenetic evidence showing little variability in the contact rate, or virus infectiousness, across EU countries during the early phase of the pandemic, highlighting the advantage of incorporating the effective population fraction into pandemic modeling for heterogeneity in both human behavior and reporting. Finally, to evaluate the consistency of our data assimilation method, we performed a forecast that adequately fits the actual data. Data-driven and model-based epidemiological studies aimed at learning the number of people infected early during a pandemic should explicitly consider the behavior-induced effective population effect. Indeed, the non-isolated, or effective, fraction of the population during the early phase of the pandemic is time-varying, and first-principles modeling with quantified uncertainty is imperative for an adequate analysis across time and space. We argue that, although good inference results may be obtained using the classical SEIR type model, the model posed in this work has allowed us to disentangle the role of virus infectiousness and awareness-based human behavior during the early phase of the COVID-19 pandemic in the European Union from official infection notification records.
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6. Optimal evaluation of re-opening policies for COVID-19 through the use of metaheuristic schemes.
6. 通过使用元启发式方案对COVID-19重新开放政策进行最优评估PMID:日期:2023-05-11A new contagious disease or unidentified COVID-19 variants could provoke a new collapse in the global economy. Under such conditions, companies, factories, and organizations must adopt reopening policies that allow their operations to reduce economic effects. Effective reopening policies should be designed using mathematical models that emulate infection chains through individual interactions. In contrast to other modeling approaches, agent-based schemes represent a computational paradigm used to characterize the person-to-person interactions of individuals inside a system, providing accurate simulation results. To evaluate the optimal conditions for a reopening policy, authorities and decision-makers need to conduct an extensive number of simulations manually, with a high possibility of losing information and important details. For this reason, the integration of optimization and simulation of reopening policies could automatically find the realistic scenario under which the lowest risk of infection was attained. In this paper, the metaheuristic technique of the Whale Optimization Algorithm is used to find the solution with the minimal transmission risk produced by an agent-based model that emulates a hypothetical re-opening context. Our scheme finds the optimal results of different generical activation scenarios. The experimental results indicate that our approach delivers practical knowledge and essential estimations for identifying optimal re-opening strategies with the lowest transmission risk.
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7. Modeling a traffic light warning system for acute respiratory infections.
7. 为急性呼吸道感染建模交通灯预警系统PMID:日期:2023-04-29The high morbidity of acute respiratory infections constitutes a crucial global health burden. In particular, for SARS-CoV-2, non-pharmaceutical intervention geared to enforce social distancing policies, vaccination, and treatments will remain an essential part of public health policies to mitigate and control disease outbreaks. However, the implementation of mitigation measures directed to increase social distancing when the risk of contagion is a complex enterprise because of the impact of NPI on beliefs, political views, economic issues, and, in general, public perception. The way of implementing these mitigation policies studied in this work is the so-called traffic-light monitoring system that attempts to regulate the application of measures that include restrictions on mobility and the size of meetings, among other non-pharmaceutical strategies. Balanced enforcement and relaxation of measures guided through a traffic-light system that considers public risk perception and economic costs may improve the public health benefit of the policies while reducing their cost. We derive a model for the epidemiological traffic-light policies based on the best response for trigger measures driven by the risk perception of people, instantaneous reproduction number, and the prevalence of a hypothetical acute respiratory infection. With numerical experiments, we evaluate and identify the role of appreciation from a hypothetical controller that could opt for protocols aligned with the cost due to the burden of the underlying disease and the economic cost of implementing measures. As the world faces new acute respiratory outbreaks, our results provide a methodology to evaluate and develop traffic light policies resulting from a delicate balance between health benefits and economic implications.
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8. Scale-free dynamics of COVID-19 in a Brazilian city.
8. 巴西某城市中COVID-19的无标度动力学PMID:日期:2023-04-21A common basis to address the dynamics of directly transmitted infectious diseases, such as COVID-19, are compartmental (or SIR) models. SIR models typically assume homogenous population mixing, a simplification that is convenient but unrealistic. Here we validate an existing model of a scale-free fractal infection process using high-resolution data on COVID-19 spread in São Caetano, Brazil. We find that transmission can be described by a network in which each infectious individual has a small number of susceptible contacts, of the order of 2-5. This model parameter correlated tightly with physical distancing measured by mobile phone data, such that in periods of greater distancing the model recovered a lower average number of contacts, and vice versa. We show that the SIR model is a special case of our scale-free fractal process model in which the parameter that reflects population structure is set at unity, indicating homogeneous mixing. Our more general framework better explained the dynamics of COVID-19 in São Caetano, used fewer parameters than a standard SIR model and accounted for geographically localized clusters of disease. Our model requires further validation in other locations and with other directly transmitted infectious agents.
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9. Modeling and multi-objective optimal control of reaction-diffusion COVID-19 system due to vaccination and patient isolation.
9. 疫苗接种和患者隔离下反应扩散COVID-19系统的建模与多目标最优控制PMID:日期:2023-02-09In this paper, a reaction-diffusion COVID-19 model is proposed to explore how vaccination-isolation strategies affect the development of the epidemic. First, the basic dynamical properties of the system are explored. Then, the system's asymptotic distributions of endemic equilibrium under different conditions are studied. Further, the global sensitivity analysis of is implemented with the aim of determining the sensitivity for these parameters. In addition, the optimal vaccination-isolation strategy based on the optimal path is proposed. Meantime, social cost , social benefit , threshold three objective optimization problem based on vaccination-isolation strategy is explored, and the maximum social cost and maximum social benefit are obtained. Finally, the instance prediction of the Lhasa epidemic in China on August 7, 2022, is made by using the piecewise infection rates , , and some key indicators are obtained as follows: (1) The basic reproduction numbers of each stage in Lhasa, China are and ; (2) The daily new cases of this epidemic will peak at 43 on the 20th day (August 26, 2022); (3) The cumulative cases in Lhasa, China will reach about 640 and be cleared about the 80th day (October 28, 2022). Our research will contribute to winning the war on epidemic prevention and control.
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10. Heterogeneity is a key factor describing the initial outbreak of COVID-19.
10. 异质性是描述COVID-19初始爆发的关键因素PMID:日期:2023-01-09Assessing the transmission potential of emerging infectious diseases, such as COVID-19, is crucial for implementing prompt and effective intervention policies. The basic reproduction number is widely used to measure the severity of the early stages of disease outbreaks. The basic reproduction number of standard ordinary differential equation models is computed for homogeneous contact patterns; however, realistic contact patterns are far from homogeneous, specifically during the early stages of disease transmission. Heterogeneity of contact patterns can lead to superspreading events that show a significantly high level of heterogeneity in generating secondary infections. This is primarily due to the large variance in the contact patterns of complex human behaviours. Hence, in this work, we investigate the impacts of heterogeneity in contact patterns on the basic reproduction number by developing two distinct model frameworks: 1) an SEIR-Erlang ordinary differential equation model and 2) an SEIR stochastic agent-based model. Furthermore, we estimated the transmission probability of both models in the context of COVID-19 in South Korea. Our results highlighted the importance of heterogeneity in contact patterns and indicated that there should be more information than one quantity (the basic reproduction number as the mean quantity), such as a degree-specific basic reproduction number in the distributional sense when the contact pattern is highly heterogeneous.