Adaptive step size stochastic runge-kutta method of order 1.5(1.0) for stochastic differential equations (SDEs)
The stiff stochastic differential equations (SDEs) involve the solution with sharp turning points that permit us to use a very small step size to comprehend its behavior. Since the step size must be set up to be as small as possible, the implementation of the fixed step size method will result in hi...
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Horizon Research Publishing
2023
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Online Access: | http://umpir.ump.edu.my/id/eprint/38244/1/Adaptive%20step%20size%20stochastic%20runge-kutta%20method%20of%20order%201.5%281.0%29.pdf http://umpir.ump.edu.my/id/eprint/38244/ https://doi.org/10.13189/ms.2023.110121 https://doi.org/10.13189/ms.2023.110121 |
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my.ump.umpir.382442023-09-05T07:29:09Z http://umpir.ump.edu.my/id/eprint/38244/ Adaptive step size stochastic runge-kutta method of order 1.5(1.0) for stochastic differential equations (SDEs) Noor Julailah, Abd Mutalib Norhayati, Rosli Noor Amalina Nisa, Ariffin Q Science (General) QA Mathematics The stiff stochastic differential equations (SDEs) involve the solution with sharp turning points that permit us to use a very small step size to comprehend its behavior. Since the step size must be set up to be as small as possible, the implementation of the fixed step size method will result in high computational cost. Therefore, the application of variable step size method is needed where in the implementation of variable step size methods, the step size used can be considered more flexible. This paper devotes to the development of an embedded stochastic Runge-Kutta (SRK) pair method for SDEs. The proposed method is an adaptive step size SRK method. The method is constructed by embedding a SRK method of 1.0 order into a SRK method of 1.5 order of convergence. The technique of embedding is applicable for adaptive step size implementation, henceforth an estimate error at each step can be obtained. Numerical experiments are performed to demonstrate the efficiency of the method. The results show that the solution for adaptive step size SRK method of order 1.5(1.0) gives the smallest global error compared to the global error for fix step size SRK4, Euler and Milstein methods. Hence, this method is reliable in approximating the solution of SDEs. Horizon Research Publishing 2023-01 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/38244/1/Adaptive%20step%20size%20stochastic%20runge-kutta%20method%20of%20order%201.5%281.0%29.pdf Noor Julailah, Abd Mutalib and Norhayati, Rosli and Noor Amalina Nisa, Ariffin (2023) Adaptive step size stochastic runge-kutta method of order 1.5(1.0) for stochastic differential equations (SDEs). Mathematics and Statistics, 11 (1). pp. 183-190. ISSN 2332-2071. (Published) https://doi.org/10.13189/ms.2023.110121 https://doi.org/10.13189/ms.2023.110121 |
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Q Science (General) QA Mathematics Noor Julailah, Abd Mutalib Norhayati, Rosli Noor Amalina Nisa, Ariffin Adaptive step size stochastic runge-kutta method of order 1.5(1.0) for stochastic differential equations (SDEs) |
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The stiff stochastic differential equations (SDEs) involve the solution with sharp turning points that permit us to use a very small step size to comprehend its behavior. Since the step size must be set up to be as small as possible, the implementation of the fixed step size method will result in high computational cost. Therefore, the application of variable step size method is needed where in the implementation of variable step size methods, the step size used can be considered more flexible. This paper devotes to the development of an embedded stochastic Runge-Kutta (SRK) pair method for SDEs. The proposed method is an adaptive step size SRK method. The method is constructed by embedding a SRK method of 1.0 order into a SRK method of 1.5 order of convergence. The technique of embedding is applicable for adaptive step size implementation, henceforth an estimate error at each step can be obtained. Numerical experiments are performed to demonstrate the efficiency of the method. The results show that the solution for adaptive step size SRK method of order 1.5(1.0) gives the smallest global error compared to the global error for fix step size SRK4, Euler and Milstein methods. Hence, this method is reliable in approximating the solution of SDEs. |
format |
Article |
author |
Noor Julailah, Abd Mutalib Norhayati, Rosli Noor Amalina Nisa, Ariffin |
author_facet |
Noor Julailah, Abd Mutalib Norhayati, Rosli Noor Amalina Nisa, Ariffin |
author_sort |
Noor Julailah, Abd Mutalib |
title |
Adaptive step size stochastic runge-kutta method of order 1.5(1.0) for stochastic differential equations (SDEs) |
title_short |
Adaptive step size stochastic runge-kutta method of order 1.5(1.0) for stochastic differential equations (SDEs) |
title_full |
Adaptive step size stochastic runge-kutta method of order 1.5(1.0) for stochastic differential equations (SDEs) |
title_fullStr |
Adaptive step size stochastic runge-kutta method of order 1.5(1.0) for stochastic differential equations (SDEs) |
title_full_unstemmed |
Adaptive step size stochastic runge-kutta method of order 1.5(1.0) for stochastic differential equations (SDEs) |
title_sort |
adaptive step size stochastic runge-kutta method of order 1.5(1.0) for stochastic differential equations (sdes) |
publisher |
Horizon Research Publishing |
publishDate |
2023 |
url |
http://umpir.ump.edu.my/id/eprint/38244/1/Adaptive%20step%20size%20stochastic%20runge-kutta%20method%20of%20order%201.5%281.0%29.pdf http://umpir.ump.edu.my/id/eprint/38244/ https://doi.org/10.13189/ms.2023.110121 https://doi.org/10.13189/ms.2023.110121 |
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