具有饱和发生率的SIR动力学模型的NSFD方法

研究一类具有饱和发生率的SIR传染病模型,利用Mickens的非标准有限差分方法(NSFD)得到对应的离散传染病模型,在采用非标准离散化过程中,使得微分方程解的正性和模型守恒律这两个重要性质与离散模型保持一致.

基于NSFD法对离散型传染病模型的数值模拟与等量分析（英文）

通过NSFD方法研究了具有不同人口规模的离散型SI传染病模型.研究发现,模型的全局动力学行为是由基本的繁殖数量R_0决定的.借助李雅普诺夫函数和相关稳定性,当R_0≤1时,在样本空间Ω中对任意的h,无病平衡点E_0是全局渐近稳定的.当R_0>1时,在样本空间Ω中对任意的h,地方病平衡点E~*是全局渐近稳定的.最后,用数值模拟证明理论分析的有效性.

Computational Modeling of Reaction-Diffusion COVID-19 Model Having Isolated Compartment

Cases of COVID-19 and its variant omicron are raised all across the world.The most lethal form and effect of COVID-19 are the omicron version,which has been reported in tens of thousands of cases daily in numerous nations.Following WHO(World health organization)records on 30 December 2021,the cases of COVID-19 were found to be maximum for which boarding individuals were found 1,524,266,active,recovered,and discharge were found to be 82,402 and 34,258,778,respectively.While there were 160,989 active cases,33,614,434 cured cases,456,386 total deaths,and 605,885,769 total samples tested.So far,1,438,322,742 individuals have been vaccinated.The coronavirus or COVID-19 is inciting panic for several reasons.It is a new virus that has affected the whole world.Scientists have introduced certain ways to prevent the virus.One can lower the danger of infection by reducing the contact rate with other persons.Avoiding crowded places and social events withmany people reduces the chance of one being exposed to the virus.The deadly COVID-19 spreads speedily.It is thought that the upcoming waves of this pandemicwill be evenmore dreadful.Mathematicians have presented severalmathematical models to study the pandemic and predict future dangers.The need of the hour is to restrict the mobility to control the infection from spreading.Moreover,separating affected individuals from healthy people is essential to control the infection.We consider the COVID-19 model in which the population is divided into five compartments.The present model presents the population’s diffusion effects on all susceptible,exposed,infected,isolated,and recovered compartments.The reproductive number,which has a key role in the infectious models,is discussed.The equilibrium points and their stability is presented.For numerical simulations,finite difference(FD)schemes like nonstandard finite difference(NSFD),forward in time central in space(FTCS),and Crank Nicolson(CN)schemes are implemented.Some core characteristics of schemes like stability and consistency are calculated.

A Nonstandard Computational Investigation of SEIR Model with Fuzzy Transmission, Recovery and Death Rates

In this article,a Susceptible-Exposed-Infectious-Recovered(SEIR)epidemic model is considered.The equilibrium analysis and reproduction number are studied.The conventional models have made assumptions of homogeneity in disease transmission that contradict the actual reality.However,it is crucial to consider the heterogeneity of the transmission rate when modeling disease dynamics.Describing the heterogeneity of disease transmission mathematically can be achieved by incorporating fuzzy theory.A numerical scheme nonstandard,finite difference(NSFD)approach is developed for the studied model and the results of numerical simulations are presented.Simulations of the constructed scheme are presented.The positivity,convergence and consistency of the developed technique are investigated using mathematical induction,Jacobean matrix and Taylor series expansions respectively.The suggested scheme preserves all these essential characteristics of the disease dynamical models.The numerical and simulation results reveal that the proposed NSFD method provides an adequate representation of the dynamics of the disease.Moreover,the obtained method generates plausible predictions that can be used by regulators to support the decision-making process to design and develop control strategies.Effects of the natural immunity on the infected class are studied which reveals that an increase in natural immunity can decrease the infection and vice versa.

New Trends in Fuzzy Modeling Through Numerical Techniques

Amoebiasis is a parasitic intestinal infection caused by the highly pathogenic amoeba Entamoeba histolytica.It is spread through person-toperson contact or by eating or drinking food or water contaminated with feces.Its transmission rate depends on the number of cysts present in the environment.The traditional models assumed a homogeneous and contradictory transmission with reality.The heterogeneity of its transmission rate is a significant factor when modeling disease dynamics.The heterogeneity of disease transmission can be described mathematically by introducing fuzzy theory.In this context,a fuzzy SEIR Amoebiasis disease model is considered in this study.The equilibrium analysis and reproductive number are studied with fuzziness.Two numerical schemes forward Euler method and a nonstandard finite difference(NSFD)approach,are developed for the learned model,and the results of numerical simulations are presented.The numerical and simulation results reveal that the proposed NSFD method provides an adequate representation of the dynamics of the disease despite the uncertainty and heterogeneity.Moreover,the obtained method generates plausible predictions that regulators can use to support decision-making to design and develop control strategies.

Numerical Investigation of Malaria Disease Dynamics in Fuzzy Environment

The application of fuzzy theory is vital in all scientific disciplines.The construction of mathematical models with fuzziness is little studied in the literature.With this in mind and for a better understanding of the disease,an SEIR model of malaria transmission with fuzziness is examined in this study by extending a classicalmodel ofmalaria transmission.The parametersβandδ,being function of the malaria virus load,are considered fuzzy numbers.Three steady states and the reproduction number of the model are analyzed in fuzzy senses.A numerical technique is developed in a fuzzy environment to solve the studied model,which retains essential properties such as positivity and dynamic consistency.Moreover,numerical simulations are carried out to illustrate the analytical results of the developed technique.Unlike most of the classical methods in the literature,the proposed approach converges unconditionally and can be considered a reliable tool for studying malaria disease dynamics.

Modeling of Computer Virus Propagation with Fuzzy Parameters

Typically,a computer has infectivity as soon as it is infected.It is a reality that no antivirus programming can identify and eliminate all kinds of viruses,suggesting that infections would persevere on the Internet.To understand the dynamics of the virus propagation in a better way,a computer virus spread model with fuzzy parameters is presented in this work.It is assumed that all infected computers do not have the same contribution to the virus transmission process and each computer has a different degree of infectivity,which depends on the quantity of virus.Considering this,the parametersβandγbeing functions of the computer virus load,are considered fuzzy numbers.Using fuzzy theory helps us understand the spread of computer viruses more realistically as these parameters have fixed values in classical models.The essential features of the model,like reproduction number and equilibrium analysis,are discussed in fuzzy senses.Moreover,with fuzziness,two numerical methods,the forward Euler technique,and a nonstandard finite difference(NSFD)scheme,respectively,are developed and analyzed.In the evidence of the numerical simulations,the proposed NSFD method preserves the main features of the dynamic system.It can be considered a reliable tool to predict such types of solutions.

Computational Investigation of Hand Foot Mouth Disease Dynamics with Fuzziness

The first major outbreak of the severely complicated hand,foot and mouth disease(HFMD),primarily caused by enterovirus 71,was reported in Taiwan in 1998.HFMD surveillance is needed to assess the spread of HFMD.The parameters we use in mathematical models are usually classical mathematical parameters,called crisp parameters,which are taken for granted.But any biological or physical phenomenon is best explained by uncertainty.To represent a realistic situation in any mathematical model,fuzzy parameters can be very useful.Many articles have been published on how to control and prevent HFMD from the perspective of public health and statistical modeling.However,few works use fuzzy theory in building models to simulateHFMDdynamics.In this context,we examined anHFMD model with fuzzy parameters.A Non Standard Finite Difference(NSFD)scheme is developed to solve the model.The developed technique retains essential properties such as positivity and dynamic consistency.Numerical simulations are presented to support the analytical results.The convergence and consistency of the proposed method are also discussed.The proposed method converges unconditionally while the many classical methods in the literature do not possess this property.In this regard,our proposed method can be considered as a reliable tool for studying the dynamics of HFMD.

Computational Analysis for Computer Network Model with Fuzziness

A susceptible,exposed,infectious,quarantined and recovered(SEIQR)model with fuzzy parameters is studied in this work.Fuzziness in the model arises due to the different degrees of susceptibility,exposure,infectivity,quarantine and recovery among the computers under consideration due to the different sizes,models,spare parts,the surrounding environments of these PCs and many other factors like the resistance capacity of the individual PC against the virus,etc.Each individual PC has a different degree of infectivity and resis-tance against infection.In this scenario,the fuzzy model has richer dynamics than its classical counterpart in epidemiology.The reproduction number of the developed model is studied and the equilibrium analysis is performed.Two different techniques are employed to solve the model numerically.Numerical simulations are performed and the obtained results are compared.Positivity and convergence are maintained by the suggested technique which are the main features of the epidemic models.

Examination of Pine Wilt Epidemic Model through Efficient Algorithm

Pine wilt is a dramatic disease that kills infected trees within a few weeks to a few months.The cause is the pathogen Pinewood Nematode.Most plant-parasitic nematodes are attached to plant roots,but pinewood nematodes are found in the tops of trees.Nematodes kill the tree by feeding the cells around the resin ducts.The modeling of a pine wilt disease is based on six compartments,including three for plants(susceptible trees,exposed trees,and infected trees)and the other for the beetles(susceptible beetles,exposed beetles,and infected beetles).The deterministic modeling,along with subpopulations,is based on Law of mass action.The stability of the model along with equilibria is studied rigorously.The authentication of analytical results is examined through well-known computer methods like Non-standard finite difference(NSFD)and the model’s feasible properties(positivity,boundedness,and dynamical consistency).In the end,comparison analysis shows the effectiveness of the NSFD algorithm.

Numerical Treatment for Stochastic Computer Virus Model

This writing is an attempt to explain a reliable numerical treatment for stochastic computer virus model.We are comparing the solutions of stochastic and deterministic computer virus models.This paper reveals that a stochastic computer virus paradigm is pragmatic in contrast to the deterministic computer virus model.Outcomes of threshold number C^?hold in stochastic computer virus model.If C^?<1 then in such a condition virus controlled in the computer population while C^?>1 shows virus persists in the computer population.Unfortunately,stochastic numerical methods fail to cope with large step sizes of time.The suggested structure of the stochastic non-standard finite difference scheme(SNSFD)maintains all diverse characteristics such as dynamical consistency,boundedness and positivity as defined by Mickens.The numerical treatment for the stochastic computer virus model manifested that increasing the antivirus ability ultimates small virus dominance in a computer community.

A Reliable Stochastic Numerical Analysis for Typhoid Fever Incorporating With Protection Against Infection

In this paper,a reliable stochastic numerical analysis for typhoid fever incorporating with protection against infection has been considered.We have compared the solutions of stochastic and deterministic typhoid fever model.It has been shown that the stochastic typhoid fever model is more realistic as compared to the deterministic typhoid fever model.The effect of threshold number T*hold in stochastic typhoid fever model.The proposed framework of the stochastic non-standard finite difference scheme(SNSFD)preserves all dynamical properties like positivity,bounded-ness and dynamical consistency defined by Mickens,R.E.The stochastic numerical simulation of the model showed that increase in protection leads to low disease prevalence in a population.

Bio-Inspired Numerical Analysis of COVID-19 with Fuzzy Parameters

Fuzziness or uncertainties arise due to insufficient knowledge,experimental errors,operating conditions and parameters that provide inaccurate information.The concepts of susceptible,infectious and recovered are uncertain due to the different degrees in susceptibility,infectivity and recovery among the individuals of the population.The differences can arise,when the population groups under the consideration having distinct habits,customs and different age groups have different degrees of resistance,etc.More realistic models are needed which consider these different degrees of susceptibility infectivity and recovery of the individuals.In this paper,a Susceptible,Infected and Recovered(SIR)epidemic model with fuzzy parameters is discussed.The infection,recovery and death rates due to the disease are considered as fuzzy numbers.Fuzzy basic reproduction number and fuzzy equilibrium points have been derived for the studied model.Themodel is then solved numerically with three different techniques,forward Euler,Runge-Kutta fourth order method(RK-4)and the nonstandard finite difference(NSFD)methods respectively.The NSFD technique becomes more efficient and reliable among the others and preserves all the essential features of a continuous dynamical system.

环境因素影响下的宿主内部与宿主之间疾病传染耦合系统的离散情形（英文）

通过非标准差分法,研究了一个环境因素影响下的宿主内部与宿主之间疾病传染的离散耦合系统.下面将耦合系统分为快系统和慢系统来分析.在快系统中,得到了解的正性、有界性和无病平衡点和被传染平衡点的存在性,然后,用线性化方法证明了平衡点的稳定性.在慢系统中,得到地方病平衡点的存在性和它的局部稳定性.

On a diffusive bacteriophage dynamical model for bacterial infections

Bacteriophages or phages are viruses that infect bacteria and are increasingly used to control bacterial infections.We develop a reaction-diffusion model coupling the interactive dynamic of phages and bacteria with an epidemiological bacteria-borne disease model.For the submodel without phage absorption,the basic reproduction number Ro is computed.The disease-free equilibrium(DFE)is shown to be globally asymptotically stable whenever Ro is less than one,while a unique globally asymptotically endemic equilibrium is proven whenever Ro exceeds one.In the presence of phage absorption,the above stated classical condition based on Ro,as the average number of secondary human infections produced by susceptible/lysogen bacteria during their entire lifespan,is no longer suficient to guarantee the global stability of the DFE.We thus derive an additional threshold No,which is the average offspring number of lysogen bacteria produced by one infected human during the phage-bacteria interactions,and prove that the DFE is globally asymptotically stable whenever both Ro and No are under unity,and infections persist uniformly whenever Ro is greater than one.Finally,the discrete counterpart of the continuous partial differential equation model is derived by constructing a nonstandard finite difference scheme which is dynamically consistent.This consistency is shown by constructing suitable discrete Lyapunov functionals thanks to which the global stability results for the continuous model are replicated.This scheme is implemented in MatLab platform and used to assess the impact of spatial distribution of phages,on the dynamic of bacterial infections.

一类具有非线性发生率的戒烟模型动力学分析

对一类具有非线性发生率的PLSQ戒烟模型进行研究.首先,确定了模型的基本再生数,并分析了模型平衡点的存在性.然后,讨论了模型平衡点的局部稳定性和全局稳定性.最后,将发生率具体化,采用微分方程的非标准差分法(NSFD)求解戒烟模型,并将数值结果与ODE23和ODE45的计算结果比较.

双曲守恒律标量方程的高分辨率激波追踪方法

本文将四阶CWENO(中心加权基本无振荡)格式、LevelSet方法以及四阶NCE—RK(自然连续外推的Runge—Kutta)方法结合起来,追踪了一维双曲守恒律方程的激波解.利用NSFD(非标准有限差分)格式来扩展CWENO重构的范围同时提高格式的精度.上述方法也能成功追踪二维双曲守恒律方程的激波解.还将本方法与标准的激波捕捉方法相比较,由此可知基于LevelSet方法的格式的有效性和逐点收敛性.