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Numerical Control Measures of Stochastic Malaria Epidemic Model 被引量:1
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作者 Muhammad Rafiq Ali Ahmadian +3 位作者 Ali Raza Dumitru Baleanu Muhammad Sarwar Ahsan Mohammad Hasan Abdul Sathar 《Computers, Materials & Continua》 SCIE EI 2020年第10期33-51,共19页
Nonlinear stochastic modeling has significant role in the all discipline of sciences.The essential control measuring features of modeling are positivity,boundedness and dynamical consistency.Unfortunately,the existing... Nonlinear stochastic modeling has significant role in the all discipline of sciences.The essential control measuring features of modeling are positivity,boundedness and dynamical consistency.Unfortunately,the existing stochastic methods in literature do not restore aforesaid control measuring features,particularly for the stochastic models.Therefore,these gaps should be occupied up in literature,by constructing the control measuring features numerical method.We shall present a numerical control measures for stochastic malaria model in this manuscript.The results of the stochastic model are discussed in contrast of its equivalent deterministic model.If the basic reproduction number is less than one,then the disease will be in control while its value greater than one shows the perseverance of disease in the population.The standard numerical procedures are conditionally convergent.The propose method is competitive and preserve all the control measuring features unconditionally.It has also been concluded that the prevalence of malaria in the human population may be controlled by reducing the contact rate between mosquitoes and humans.The awareness programs run by world health organization in developing countries may overcome the spread of malaria disease. 展开更多
关键词 Malaria disease model stochastic modelling stochastic methods CONVERGENCE
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Numerical Treatment for Stochastic Computer Virus Model 被引量:6
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作者 Ali Raza Muhammad Shoaib Arif +6 位作者 Muhammad Rafiq Mairaj Bibi Muhammad Naveed Muhammad Usman Iqbal Zubair Butt Hafiza Anum Naseem Javeria Nawaz Abbasi 《Computer Modeling in Engineering & Sciences》 SCIE EI 2019年第8期445-465,共21页
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 s... 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. 展开更多
关键词 Computer virus euler maruyama SCHEME STOCHASTIC differential EQUATIONS STOCHASTIC EULER SCHEME STOCHASTIC RUNGE-KUTTA SCHEME STOCHASTIC NSFD SCHEME stability
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