Solving Fractional Differential Equations by Using Triangle Neural Network

In this paper, numerical methods for solving fractional differential equations by using a triangle neural network are proposed. The fractional derivative is considered Caputo type. The fractional derivative of the triangle neural network is analyzed first. Then, based on the technique of minimizing...

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Main Authors: Feng Gao, Yumin Dong, Chunmei Chi
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Journal of Function Spaces
Online Access:http://dx.doi.org/10.1155/2021/5589905
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author Feng Gao
Yumin Dong
Chunmei Chi
author_facet Feng Gao
Yumin Dong
Chunmei Chi
author_sort Feng Gao
collection DOAJ
description In this paper, numerical methods for solving fractional differential equations by using a triangle neural network are proposed. The fractional derivative is considered Caputo type. The fractional derivative of the triangle neural network is analyzed first. Then, based on the technique of minimizing the loss function of the neural network, the proposed numerical methods reduce the fractional differential equation into a gradient descent problem or the quadratic optimization problem. By using the gradient descent process or the quadratic optimization process, the numerical solution to the FDEs can be obtained. The efficiency and accuracy of the presented methods are shown by some numerical examples. Numerical tests show that this approach is easy to implement and accurate when applied to many types of FDEs.
format Article
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institution DOAJ
issn 2314-8896
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language English
publishDate 2021-01-01
publisher Wiley
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series Journal of Function Spaces
spelling doaj-art-bad123188f8b4737a04bc7dab1b083c82025-08-20T03:23:23ZengWileyJournal of Function Spaces2314-88962314-88882021-01-01202110.1155/2021/55899055589905Solving Fractional Differential Equations by Using Triangle Neural NetworkFeng Gao0Yumin Dong1Chunmei Chi2School of Science, Qingdao University of Technology, Qingdao 266033, ChinaCollege of Computer and Information Science, Chongqing Normal University, Chongqing 401331, ChinaSchool of Information and Control Engineering, Qingdao University of Technology, Qingdao 266033, ChinaIn this paper, numerical methods for solving fractional differential equations by using a triangle neural network are proposed. The fractional derivative is considered Caputo type. The fractional derivative of the triangle neural network is analyzed first. Then, based on the technique of minimizing the loss function of the neural network, the proposed numerical methods reduce the fractional differential equation into a gradient descent problem or the quadratic optimization problem. By using the gradient descent process or the quadratic optimization process, the numerical solution to the FDEs can be obtained. The efficiency and accuracy of the presented methods are shown by some numerical examples. Numerical tests show that this approach is easy to implement and accurate when applied to many types of FDEs.http://dx.doi.org/10.1155/2021/5589905
spellingShingle Feng Gao
Yumin Dong
Chunmei Chi
Solving Fractional Differential Equations by Using Triangle Neural Network
Journal of Function Spaces
title Solving Fractional Differential Equations by Using Triangle Neural Network
title_full Solving Fractional Differential Equations by Using Triangle Neural Network
title_fullStr Solving Fractional Differential Equations by Using Triangle Neural Network
title_full_unstemmed Solving Fractional Differential Equations by Using Triangle Neural Network
title_short Solving Fractional Differential Equations by Using Triangle Neural Network
title_sort solving fractional differential equations by using triangle neural network
url http://dx.doi.org/10.1155/2021/5589905
work_keys_str_mv AT fenggao solvingfractionaldifferentialequationsbyusingtriangleneuralnetwork
AT yumindong solvingfractionaldifferentialequationsbyusingtriangleneuralnetwork
AT chunmeichi solvingfractionaldifferentialequationsbyusingtriangleneuralnetwork