Numerical solution of coupled system of Emden-Fowler equations using artificial neural network technique
In this paper, a deep artificial neural network technique is proposed to solve the coupled system of Emden-Fowler equations. A vectorized form of algorithm is developed. Implementation and simulation of this technique is performed using Python code. This technique is implemented in various numerica...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Balikesir University
2024-01-01
|
Series: | An International Journal of Optimization and Control: Theories & Applications |
Subjects: | |
Online Access: | http://ijocta.org/index.php/files/article/view/1424 |
Summary: | In this paper, a deep artificial neural network technique is proposed to solve the coupled system of Emden-Fowler equations. A vectorized form of algorithm is developed. Implementation and simulation of this technique is performed using Python code. This technique is implemented in various numerical examples, and simulations are conducted. We have shown graphically how accurately this method works. We have shown the comparison of numerical solution and exact solution using error tables. We have also conducted a comparative analysis of our solution with alternative methods, including the Bernstein collocation method and the Homotopy analysis method. The comparative results are presented in error tables. The efficiency and accuracy of this method are demonstrated by these graphs and tables.
|
---|---|
ISSN: | 2146-0957 2146-5703 |