Artificial neural network for solving the nonlinear singular fractional differential equations

被引：7
|
作者：
Althubiti, Saeed [1 ]
Kumar, Manoj [2 ]
Goswami, Pranay [2 ]
Kumar, Kranti [2 ,3 ]
机构：
[1] Taif Univ, Coll Sci, Dept Math, Taif, Saudi Arabia
[2] Dr BR Ambedkar Univeristy Delhi, Sch Liberal Studies, Delhi 110006, India
[3] Cent Univ Himachal Pradesh, Dept Math, Dharamshala, Himachal Prades, India
来源：
APPLIED MATHEMATICS IN SCIENCE AND ENGINEERING | 2023年 / 31卷 / 01期
关键词：
MLP neural network; nonlinear fractional differential equation; unsupervised learning; approximate solutions;
D O I：
10.1080/27690911.2023.2187389
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
This paper proposes an artificial neural network (ANN) architecture for solving nonlinear fractional differential equations. The proposed ANN algorithm is based on a truncated power series expansion to substitute the unknown functions in the equations in this approach. Then, a set of algebraic equations is resolved using the ANN technique in an iterative minimization process. Finally, numerical examples are provided to demonstrate the usefulness of the ANN architectures. The results verify that the suggested ANN architecture achieves high accuracy and good stability.
引用
收藏
页数：17
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