Showing papers by "Mehmet Merdan published in 2018"
Journal Article•
TL;DR: In this paper, a new application of local fractional decomposition method (LFDM) was extended to derive analytical solutions in the form of a convergent series with easily computable components, requiring no linearization or small perturbation for this equation.
Abstract: In this article, local fractional decomposition method (LFDM) is applied to obtain an analytical approximate solution of nonlinear time-fractional Gas dynamics equation. A new application of local fractional decomposition method (LFDM) was extended to derive analytical solutions in the form of a convergent series with easily computable components, requiring no linearization or small perturbation for this equation. The solutions obtained by LFDM have been shown to be reliable, simple and the method is an effective technique for strong nonlinear partial equations. AMS Subject Classification: 35R11, 26A33
3 citations
22 Nov 2018
TL;DR: In this paper, a deterministic mathematical model of Ebola transmission is analyzed under random effects, where the parameters of this model are normally distributed random variables to investigate the random behavior of disease transmission, and the approximation for expected recovery is modified by using Laplace-Pade method.
Abstract: In this study, a deterministic mathematical model of Ebola transmission is analyzed under random effects. A recent compartmental model of Berge et al. incorporates both direct and indirect transmission in the model. We assume the parameters of this model are normally distributed random variables to investigate the random behavior of disease transmission. Random differential transformation method is used to obtain the approximate expectation of disease recovery. Furthermore, the approximation for expected recovery is modified by using Laplace-Pade method. Comparison of results indicate that the Laplace-Pade modification provides a better approximation. We also interpret the long term random behavior of the disease dynamics using simulation results.
2 citations
14 Nov 2018
TL;DR: In this paper, a SVEIR-type compartmental model of Poliomyelitis transmission is examined under random effects and the approximate analytical solution of the model is obtained by using Random Differential Transformation Method (RDTM).
Abstract: In this study, a SVEIR-type compartmental model of Poliomyelitis transmission is examined under random effects. We introduce Generalized Beta and normal distributed random parameters into the equation system to investigate the random dynamics of the disease. The approximate analytical solution of the model under random effects is obtained by using Random Differential Transformation Method (RDTM). Results from simulations and RDTM are analyzed to comment on the randomness of the compartments and disease transmission. It is seen that the random model successfully provides similar results that can be obtained through the deterministic model while providing additional information on the random behavior of the disease, such as the standard deviations and the variation coefficients.