Research Article

Monte Carlo based stochastic approach for the first order nonlinear ODE systems

Volume: 26 Number: 1 February 20, 2020
  • Hande Uslu
  • Murat Sarı
EN TR

Monte Carlo based stochastic approach for the first order nonlinear ODE systems

Abstract

After the discovery of the effectiveness of the stochastic methods for solving real life problems, these methods have been applied to a wide range of problems in two types; deterministic problems and stochastic problems. The general opinion takes part in applying these methods to stochastic problems since it is preferable for realistic results. Moreover, those methods can also be used in dealing with deterministic models. This study aims to show how stochastic approaches can be applied to deterministic models. Thus, an algorithm based on the Monte Carlo simulation has been presented for solving some systems of nonlinear differential equations. To discuss the behavior of such models, the population equations have been taken into consideration. The considered approach has been seen to produce more accurate results than numerical techniques. A detailed discussion about the results has also been given in this work.

Keywords

References

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  7. Paul S, Mondal SP, Bhattacharya P. “Numerical solution of lotka volterra prey predator model by using runge–kutta–fehlberg method and laplace adomian decomposition method”. Alexandria Engineering Journal, 55, 613-617, 2015.
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Details

Primary Language

English

Subjects

Engineering

Journal Section

Research Article

Authors

Hande Uslu This is me
Türkiye

Murat Sarı This is me
Türkiye

Publication Date

February 20, 2020

Submission Date

October 19, 2018

Acceptance Date

-

Published in Issue

Year 2020 Volume: 26 Number: 1

APA
Uslu, H., & Sarı, M. (2020). Monte Carlo based stochastic approach for the first order nonlinear ODE systems. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 26(1), 133-139. https://izlik.org/JA94DF68JE
AMA
1.Uslu H, Sarı M. Monte Carlo based stochastic approach for the first order nonlinear ODE systems. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2020;26(1):133-139. https://izlik.org/JA94DF68JE
Chicago
Uslu, Hande, and Murat Sarı. 2020. “Monte Carlo Based Stochastic Approach for the First Order Nonlinear ODE Systems”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 26 (1): 133-39. https://izlik.org/JA94DF68JE.
EndNote
Uslu H, Sarı M (February 1, 2020) Monte Carlo based stochastic approach for the first order nonlinear ODE systems. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 26 1 133–139.
IEEE
[1]H. Uslu and M. Sarı, “Monte Carlo based stochastic approach for the first order nonlinear ODE systems”, Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol. 26, no. 1, pp. 133–139, Feb. 2020, [Online]. Available: https://izlik.org/JA94DF68JE
ISNAD
Uslu, Hande - Sarı, Murat. “Monte Carlo Based Stochastic Approach for the First Order Nonlinear ODE Systems”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 26/1 (February 1, 2020): 133-139. https://izlik.org/JA94DF68JE.
JAMA
1.Uslu H, Sarı M. Monte Carlo based stochastic approach for the first order nonlinear ODE systems. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2020;26:133–139.
MLA
Uslu, Hande, and Murat Sarı. “Monte Carlo Based Stochastic Approach for the First Order Nonlinear ODE Systems”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol. 26, no. 1, Feb. 2020, pp. 133-9, https://izlik.org/JA94DF68JE.
Vancouver
1.Hande Uslu, Murat Sarı. Monte Carlo based stochastic approach for the first order nonlinear ODE systems. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi [Internet]. 2020 Feb. 1;26(1):133-9. Available from: https://izlik.org/JA94DF68JE