Academic Journal

Artificial neural network for solving the nonlinear singular fractional differential equations

التفاصيل البيبلوغرافية
العنوان: Artificial neural network for solving the nonlinear singular fractional differential equations
المؤلفون: Saeed Althubiti, Manoj Kumar, Pranay Goswami, Kranti Kumar
المصدر: Applied Mathematics in Science and Engineering, Vol 31, Iss 1 (2023)
بيانات النشر: Taylor & Francis Group, 2023.
سنة النشر: 2023
المجموعة: LCC:Mathematics
LCC:Engineering (General). Civil engineering (General)
مصطلحات موضوعية: mlp neural network, nonlinear fractional differential equation, unsupervised learning, approximate solutions, Mathematics, QA1-939, Engineering (General). Civil engineering (General), TA1-2040
الوصف: 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.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2769-0911
27690911
Relation: https://doaj.org/toc/2769-0911
DOI: 10.1080/27690911.2023.2187389
URL الوصول: https://doaj.org/article/92604637c6144e92b10f8cb2d52d8bdf
رقم الانضمام: edsdoj.92604637c6144e92b10f8cb2d52d8bdf
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:27690911
DOI:10.1080/27690911.2023.2187389