Browsing by Author "Erturk, Vedat Suat"

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Citation - WoS: 37
Citation - Scopus: 39
A delayed plant disease model with Caputo fractional derivatives
(Springer, 2022) Kumar, Pushpendra; Baleanu, Dumitru; Baleanu, Dumitru; Erturk, Vedat Suat; Inc, Mustafa; Govindaraj, V; 56389; Matematik
We analyze a time-delay Caputo-type fractional mathematical model containing the infection rate of Beddington-DeAngelis functional response to study the structure of a vector-borne plant epidemic. We prove the unique global solution existence for the given delay mathematical model by using fixed point results. We use the Adams-Bashforth-Moulton P-C algorithm for solving the given dynamical model. We give a number of graphical interpretations of the proposed solution. A number of novel results are demonstrated from the given practical and theoretical observations. By using 3-D plots we observe the variations in the flatness of our plots when the fractional order varies. The role of time delay on the proposed plant disease dynamics and the effects of infection rate in the population of susceptible and infectious classes are investigated. The main motivation of this research study is examining the dynamics of the vector-borne epidemic in the sense of fractional derivatives under memory effects. This study is an example of how the fractional derivatives are useful in plant epidemiology. The application of Caputo derivative with equal dimensionality includes the memory in the model, which is the main novelty of this study.
Citation - WoS: 0
Citation - Scopus: 0
A Study on the Nonlinear Caputo-Type Snakebite Envenoming Model with Memory
(Tech Science Press, 2023) Kumar, Pushpendra; Baleanu, Dumitru; Erturk, Vedat Suat; Govindaraj, V.; Baleanu, Dumitru; 56389; Matematik
In this article, we introduce a nonlinear Caputo-type snakebite envenoming model with memory. The well-known Caputo fractional derivative is used to generalize the previously presented integer-order model into a fractional -order sense. The numerical solution of the model is derived from a novel implementation of a finite-difference predictor-corrector (L1-PC) scheme with error estimation and stability analysis. The proof of the existence and positivity of the solution is given by using the fixed point theory. From the necessary simulations, we justify that the first-time implementation of the proposed method on an epidemic model shows that the scheme is fully suitable and time-efficient for solving epidemic models. This work aims to show the novel application of the given scheme as well as to check how the proposed snakebite envenoming model behaves in the presence of the Caputo fractional derivative, including memory effects.