Çankaya GCRIS Standart veritabanının içerik oluşturulması ve kurulumu Research Ecosystems (https://www.researchecosystems.com) tarafından devam etmektedir. Bu süreçte gördüğünüz verilerde eksikler olabilir.

Browsing by Author "Arif, Muhammad Shoaib"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • Thumbnail Image
    Article
    Citation Count: Baleanu, Dumitru...et al. (2019). "Competitive Analysis for Stochastic Influenza Model With Constant Vaccination Strategy",Iet Systems Biology, Vol. 13, No. 6, pp. 316-326.
    Competitive Analysis for Stochastic Influenza Model With Constant Vaccination Strategy
    (Institution of Engineering and Technology, 2019) Baleanu, Dumitru; Raza, Ali; Rafiq, Muhammad; Arif, Muhammad Shoaib; Ali, Muhammad Asghar; 56389
    This manuscript discusses a competitive analysis of stochastic influenza model with constant vaccination strategy. The stochastic influenza model is comparatively more pragmatic versus the deterministic influenza model. The effect of influenza generation number holds in the stochastic model. If the value of this number is less than one, this situation will help us to control the disease in a population. A greater than one value of this threshold number shows the persistence of disease to become endemic. The proposed structure for the stochastic influenza model as stochastic non-standard finite difference scheme conserve all vital characteristics like positivity, boundedness and dynamical consistency defined by Mickens.
  • Thumbnail Image
    Article
    Citation Count: Raza, Ali...et al. (2020). "Numerical simulations for stochastic meme epidemic model", Advances in Difference Equations, Vol. 2020, No. 1.
    Numerical simulations for stochastic meme epidemic model
    (2020) Raza, Ali; Rafiq, Muhammad; Baleanu, Dumitru; Arif, Muhammad Shoaib; 56389
    The primary purpose of this study is to perform the comparison of deterministic and stochastic modeling. The effect of threshold number is also observed in this model. For numerical simulations, we have developed some stochastic explicit approaches, but they are dependent on time step size. The implicitly driven explicit approach has been developed for a stochastic meme model. The proposed approach is always independent of time step size. Also, we have presented theorems in support of convergence of the proposed approach for the stochastic meme model.