A Numerical Efficient Technique for the Solution of Susceptible Infected Recovered Epidemic Model
The essential features of the nonlinear stochastic models are positivity, dynamical consistency and boundedness. These features have a significant role in different fields of computational biology and many more. The aim of our paper, to achieve the comparison analysis of the stochastic susceptible,...
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| Veröffentlicht in: | Computer modeling in engineering & sciences 2020-01, Vol.124 (2), p.477-491 |
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| container_title | Computer modeling in engineering & sciences |
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| creator | Shoaib Arif, Muhammad Raza, Ali Abodayeh, Kamaleldin Rafiq, Muhammad Bibi, Mairaj Nazeer, Amna |
| description | The essential features of the nonlinear stochastic models are positivity, dynamical consistency and boundedness. These features have a significant role in different fields of computational biology and many more. The aim of our paper, to achieve the comparison analysis of the stochastic
susceptible, infected recovered epidemic model. The stochastic modelling is a realistic way to study the dynamics of compartmental modelling as compared to deterministic modelling. The effect of reproduction number has also observed in the stochastic susceptible, infected recovered epidemic
model. For comparison analysis, we developed some explicit stochastic techniques, but they are the time-dependent techniques. The implicitly driven explicit technique has developed for the stochastic susceptible, infected recovered epidemic model. In the support, some theorems and graphical
illustration has presented. Also, the time efficiency of this method makes it easy to find the solution of the stochastic system. The comparison with other techniques shows the efficacy and reliability of the designed technique. |
| doi_str_mv | 10.32604/cmes.2020.011121 |
| format | Article |
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susceptible, infected recovered epidemic model. The stochastic modelling is a realistic way to study the dynamics of compartmental modelling as compared to deterministic modelling. The effect of reproduction number has also observed in the stochastic susceptible, infected recovered epidemic
model. For comparison analysis, we developed some explicit stochastic techniques, but they are the time-dependent techniques. The implicitly driven explicit technique has developed for the stochastic susceptible, infected recovered epidemic model. In the support, some theorems and graphical
illustration has presented. Also, the time efficiency of this method makes it easy to find the solution of the stochastic system. The comparison with other techniques shows the efficacy and reliability of the designed technique.</description><identifier>ISSN: 1526-1492</identifier><identifier>ISSN: 1526-1506</identifier><identifier>EISSN: 1526-1506</identifier><identifier>DOI: 10.32604/cmes.2020.011121</identifier><language>eng</language><publisher>Henderson: Tech Science Press</publisher><subject>Convergence Analysis ; Epidemics ; Epidemiolocal Model ; Stochastic Differential Equations ; Stochastic models ; Stochastic systems ; Stochastic Techniques ; Time dependence</subject><ispartof>Computer modeling in engineering & sciences, 2020-01, Vol.124 (2), p.477-491</ispartof><rights>2020. This work is licensed under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3591-ebc45c6b2290273a1bc5979ea020fdd24a69e5cbf0e357979a9f175c031ab6573</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids></links><search><creatorcontrib>Shoaib Arif, Muhammad</creatorcontrib><creatorcontrib>Raza, Ali</creatorcontrib><creatorcontrib>Abodayeh, Kamaleldin</creatorcontrib><creatorcontrib>Rafiq, Muhammad</creatorcontrib><creatorcontrib>Bibi, Mairaj</creatorcontrib><creatorcontrib>Nazeer, Amna</creatorcontrib><title>A Numerical Efficient Technique for the Solution of Susceptible Infected Recovered Epidemic Model</title><title>Computer modeling in engineering & sciences</title><description>The essential features of the nonlinear stochastic models are positivity, dynamical consistency and boundedness. These features have a significant role in different fields of computational biology and many more. The aim of our paper, to achieve the comparison analysis of the stochastic
susceptible, infected recovered epidemic model. The stochastic modelling is a realistic way to study the dynamics of compartmental modelling as compared to deterministic modelling. The effect of reproduction number has also observed in the stochastic susceptible, infected recovered epidemic
model. For comparison analysis, we developed some explicit stochastic techniques, but they are the time-dependent techniques. The implicitly driven explicit technique has developed for the stochastic susceptible, infected recovered epidemic model. In the support, some theorems and graphical
illustration has presented. Also, the time efficiency of this method makes it easy to find the solution of the stochastic system. 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susceptible, infected recovered epidemic model. The stochastic modelling is a realistic way to study the dynamics of compartmental modelling as compared to deterministic modelling. The effect of reproduction number has also observed in the stochastic susceptible, infected recovered epidemic
model. For comparison analysis, we developed some explicit stochastic techniques, but they are the time-dependent techniques. The implicitly driven explicit technique has developed for the stochastic susceptible, infected recovered epidemic model. In the support, some theorems and graphical
illustration has presented. Also, the time efficiency of this method makes it easy to find the solution of the stochastic system. The comparison with other techniques shows the efficacy and reliability of the designed technique.</abstract><cop>Henderson</cop><pub>Tech Science Press</pub><doi>10.32604/cmes.2020.011121</doi><tpages>15</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Convergence Analysis Epidemics Epidemiolocal Model Stochastic Differential Equations Stochastic models Stochastic systems Stochastic Techniques Time dependence |
| title | A Numerical Efficient Technique for the Solution of Susceptible Infected Recovered Epidemic Model |
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