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 c...
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| Veröffentlicht in: | Computer modeling in engineering & sciences 2019-01, Vol.120 (2), p.445-465 |
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| container_title | Computer modeling in engineering & sciences |
| container_volume | 120 |
| creator | Raza, Ali Arif, Muhammad Shoaib Rafiq, Muhammad Bibi, Mairaj Naveed, Muhammad Iqbal, Muhammad Usman Butt, Zubair Naseem, Hafiza Anum Abbasi, Javeria Nawaz |
| description | 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. |
| doi_str_mv | 10.32604/cmes.2019.06454 |
| format | Article |
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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.</description><identifier>ISSN: 1526-1492</identifier><identifier>ISSN: 1526-1506</identifier><identifier>EISSN: 1526-1506</identifier><identifier>DOI: 10.32604/cmes.2019.06454</identifier><language>eng</language><publisher>Henderson: Tech Science Press</publisher><subject>Computer Virus ; Computer viruses ; Euler Maruyama Scheme ; Finite difference method ; Mathematical models ; Numerical methods ; Stability ; Stochastic Differential Equations ; Stochastic Euler Scheme ; Stochastic Nsfd Scheme ; Stochastic Runge-Kutta Scheme</subject><ispartof>Computer modeling in engineering & sciences, 2019-01, Vol.120 (2), p.445-465</ispartof><rights>Copyright Tech Science Press 2019</rights><rights>2019. This work is licensed under http://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-c398t-495b2c7af51f5f9325d1b63399d2e027273d99dacd73b85a0bf5c5679a473bf23</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Raza, Ali</creatorcontrib><creatorcontrib>Arif, Muhammad Shoaib</creatorcontrib><creatorcontrib>Rafiq, Muhammad</creatorcontrib><creatorcontrib>Bibi, Mairaj</creatorcontrib><creatorcontrib>Naveed, Muhammad</creatorcontrib><creatorcontrib>Iqbal, Muhammad Usman</creatorcontrib><creatorcontrib>Butt, Zubair</creatorcontrib><creatorcontrib>Naseem, Hafiza Anum</creatorcontrib><creatorcontrib>Abbasi, Javeria Nawaz</creatorcontrib><title>Numerical Treatment for Stochastic Computer Virus Model</title><title>Computer modeling in engineering & sciences</title><description>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.</description><subject>Computer Virus</subject><subject>Computer viruses</subject><subject>Euler Maruyama Scheme</subject><subject>Finite difference method</subject><subject>Mathematical models</subject><subject>Numerical methods</subject><subject>Stability</subject><subject>Stochastic Differential Equations</subject><subject>Stochastic Euler Scheme</subject><subject>Stochastic Nsfd Scheme</subject><subject>Stochastic Runge-Kutta Scheme</subject><issn>1526-1492</issn><issn>1526-1506</issn><issn>1526-1506</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNp9kDtPxDAQhC0EEsdBTxmJOsf6HXegEy-JR8FBazmODTldLsF2Cv49yQUEFdvsaDSzK30InWJYUCKAndvGxQUBrBYgGGd7aIY5ETnmIPZ_NFPkEB3FuAagghZqhuRj37hQW7PJVsGZ1LhtynwbsufU2ncTU22zZdt0fXIhe61DH7OHtnKbY3TgzSa6k-89Ry_XV6vlbX7_dHO3vLzPLVVFypniJbHSeI4994oSXuFSUKpURRwQSSStBm1sJWlZcAOl55YLqQwbDE_oHJ1Nd7vQfvQuJr1u-7AdXmpClSRCYsb_TRHJFS4YjCmYUja0MQbndRfqxoRPjUHvIOoRoh4h6h3EoXIxVert20DG_N5NsfubHgcTmAQA0Sak0aL0C4ikd7k</recordid><startdate>20190101</startdate><enddate>20190101</enddate><creator>Raza, Ali</creator><creator>Arif, Muhammad Shoaib</creator><creator>Rafiq, Muhammad</creator><creator>Bibi, Mairaj</creator><creator>Naveed, Muhammad</creator><creator>Iqbal, Muhammad Usman</creator><creator>Butt, Zubair</creator><creator>Naseem, Hafiza Anum</creator><creator>Abbasi, Javeria Nawaz</creator><general>Tech Science Press</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope></search><sort><creationdate>20190101</creationdate><title>Numerical Treatment for Stochastic Computer Virus Model</title><author>Raza, Ali ; 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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.</abstract><cop>Henderson</cop><pub>Tech Science Press</pub><doi>10.32604/cmes.2019.06454</doi><tpages>21</tpages><oa>free_for_read</oa></addata></record> |
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| source | Tech Science Press; EZB Electronic Journals Library |
| subjects | Computer Virus Computer viruses Euler Maruyama Scheme Finite difference method Mathematical models Numerical methods Stability Stochastic Differential Equations Stochastic Euler Scheme Stochastic Nsfd Scheme Stochastic Runge-Kutta Scheme |
| title | Numerical Treatment for Stochastic Computer Virus Model |
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