Comparison of stochastic and random models for bacterial resistance

Abstract

In this study, a mathematical model of bacterial resistance considering the immune system response and antibiotic therapy is examined under random conditions. A random model consisting of random differential equations is obtained by using the existing deterministic model. Similarly, stochastic effect terms are added to the deterministic model to form a stochastic model consisting of stochastic differential equations. The results from the random and stochastic models are also compared with the results of the deterministic model to investigate the behavior of the model components under random conditions. MSC: Primary 34F05; secondary 92D30

Diferansiyel Dönüşüm Yöntemi İle Rastgele Kalp Atış Modelinin Analizi

“…The approximate expected value of 2 is shown in Figure 2. It should be noted that more terms are needed for accurate approximate expectations [ 1 ], [ 2 ]. The first three terms have been given to present the calculation method and to underline the improvements obtained by the modification.…”

Wong-Zakai Method Applications for Explicitly Solvable Stochastic Differential Equations

“…model such events is a better modeling approach in contrast to the deterministic case. Several popular methods are used for analyzing stochastic differential equation systems, such as Euler-Maruyama and Milstein methods [1,2], which are the pioneering approximation techniques.…”

Deterministic stability and random behavior of a Hepatitis C model

“…The parameters in the deterministic System (1) are added random effects to investigate the random characteristics of the model. A random analysis of models using random differential equations with random parameters has been used before for a model of avian-influenza by Merdan and Khaniyev in 2008 and for bacterial resistance by Merdan et al, which was the motivation for the method used in this work [ 18 , 32 ]. The random model is analyzed to investigate the numerical characteristics of the event and thus comment on the random behavior of the model components.…”