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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Hauptverfasser: | , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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. |
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ISSN: | 1526-1492 1526-1506 1526-1506 |
DOI: | 10.32604/cmes.2019.06454 |