Performance of stochastic Runge-Kutta Methods in approximating the solution of stochastic model in biological system

Performance of stochastic Runge-Kutta Methods in approximating the solution of stochastic model in biological system

Recently, modelling the biological systems by using stochastic differential equations (SDEs) are becoming an interest among researchers. In SDEs the random fluctuations are taking into account, which resulting to the complexity of finding the exact solution of SDEs and contribute to the increasing n...

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Main Authors: Noor Amalina Nisa, Ariffin, Norhayati, Rosli, Mazma Syahidatul Ayuni, Mazlan, Adam, Samsudin
Format: Conference or Workshop Item
Language:English
Published: IOP Publishing 2017
Subjects:
QA Mathematics
Online Access:http://umpir.ump.edu.my/id/eprint/20730/
http://umpir.ump.edu.my/id/eprint/20730/
http://umpir.ump.edu.my/id/eprint/20730/1/IOP.pdf
id ump-20730
recordtype eprints
spelling ump-207302018-08-06T04:33:48Z http://umpir.ump.edu.my/id/eprint/20730/ Performance of stochastic Runge-Kutta Methods in approximating the solution of stochastic model in biological system Noor Amalina Nisa, Ariffin Norhayati, Rosli Mazma Syahidatul Ayuni, Mazlan Adam, Samsudin QA Mathematics Recently, modelling the biological systems by using stochastic differential equations (SDEs) are becoming an interest among researchers. In SDEs the random fluctuations are taking into account, which resulting to the complexity of finding the exact solution of SDEs and contribute to the increasing number of research focusing in finding the best numerical approach to solve the systems of SDEs. This paper will examine the performance of 4-stage stochastic Runge-Kutta (SRK4) and specific stochastic Runge-Kutta (SRKS) methods with order 1.5 in approximating the solution of stochastic model in biological system. A comparative study of SRK4 and SRKS method will be presented in this paper. The non-linear biological model will be used to examine the performance of both methods and the result of numerical experiment will be discussed. IOP Publishing 2017 Conference or Workshop Item PeerReviewed pdf en cc_by http://umpir.ump.edu.my/id/eprint/20730/1/IOP.pdf Noor Amalina Nisa, Ariffin and Norhayati, Rosli and Mazma Syahidatul Ayuni, Mazlan and Adam, Samsudin (2017) Performance of stochastic Runge-Kutta Methods in approximating the solution of stochastic model in biological system. In: Journal of Physics: Conference Series, 1st International Conference on Applied & Industrial Mathematics and Statistics 2017 (ICoAIMS 2017), 8-10 August 2017 , Kuantan, Pahang, Malaysia. pp. 1-7., 890 (012083). ISSN 1742-6596 https://doi.org/10.1088/1742-6596/890/1/012083
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic QA Mathematics
spellingShingle QA Mathematics
Noor Amalina Nisa, Ariffin
Norhayati, Rosli
Mazma Syahidatul Ayuni, Mazlan
Adam, Samsudin
Performance of stochastic Runge-Kutta Methods in approximating the solution of stochastic model in biological system
description Recently, modelling the biological systems by using stochastic differential equations (SDEs) are becoming an interest among researchers. In SDEs the random fluctuations are taking into account, which resulting to the complexity of finding the exact solution of SDEs and contribute to the increasing number of research focusing in finding the best numerical approach to solve the systems of SDEs. This paper will examine the performance of 4-stage stochastic Runge-Kutta (SRK4) and specific stochastic Runge-Kutta (SRKS) methods with order 1.5 in approximating the solution of stochastic model in biological system. A comparative study of SRK4 and SRKS method will be presented in this paper. The non-linear biological model will be used to examine the performance of both methods and the result of numerical experiment will be discussed.
format Conference or Workshop Item
author Noor Amalina Nisa, Ariffin
Norhayati, Rosli
Mazma Syahidatul Ayuni, Mazlan
Adam, Samsudin
author_facet Noor Amalina Nisa, Ariffin
Norhayati, Rosli
Mazma Syahidatul Ayuni, Mazlan
Adam, Samsudin
author_sort Noor Amalina Nisa, Ariffin
title Performance of stochastic Runge-Kutta Methods in approximating the solution of stochastic model in biological system
title_short Performance of stochastic Runge-Kutta Methods in approximating the solution of stochastic model in biological system
title_full Performance of stochastic Runge-Kutta Methods in approximating the solution of stochastic model in biological system
title_fullStr Performance of stochastic Runge-Kutta Methods in approximating the solution of stochastic model in biological system
title_full_unstemmed Performance of stochastic Runge-Kutta Methods in approximating the solution of stochastic model in biological system
title_sort performance of stochastic runge-kutta methods in approximating the solution of stochastic model in biological system
publisher IOP Publishing
publishDate 2017
url http://umpir.ump.edu.my/id/eprint/20730/
http://umpir.ump.edu.my/id/eprint/20730/
http://umpir.ump.edu.my/id/eprint/20730/1/IOP.pdf
first_indexed 2023-09-18T22:30:04Z
last_indexed 2023-09-18T22:30:04Z
_version_ 1777416226236006400

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