Investigation of Solutions of  −conformable Fractional Ordinary Differential Equation With  Artificial Neural Network

Sadullah Bulut; Muhammed Yiğider

Article Details

Investigation of Solutions of −conformable Fractional Ordinary Differential Equation With Artificial Neural Network

Authors:

Sadullah Bulut | Muhammed Yiğider

Publisher:

Igdir University

Main Topics:

Matematik

Journal:

Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.13 Issue 2, pp.1266-1274

Document Type:

Article

Publication Date:

1/2023

Document Language:

English

Document ID (Org No.):

2001289846

pISSN:

2536-4618

Keywords:

Abstract:

 İn this study, we present a method in order to get initial value fractional differential equations with artificial neural networks. On the basis of the function approach of feedforward neural networks, this method is a general method that is written in an implicit analytical form and results in the creation of a differentiable solution. The first part of the created trial solution which is stated as the sum of the two parts, with no controllable parameters, gives the initial conditions. The second part, unaffected by the initial conditions, consists of a feedforward neural network with controllable parameters weights. The applicability of this approach is demonstrated in systems of both fractional single ODEs and fractional coupled ODEs.

 İn this study, we present a method in order to get initial value fractional differential equations with artificial neural networks. On the basis of the function approach of feedforward neural networks, this method is a general method that is written in an implicit analytical form and results in the creation of a differentiable solution. The first part of the created trial solution which is stated as the sum of the two parts, with no controllable parameters, gives the initial conditions. The second part, unaffected by the initial conditions, consists of a feedforward neural network with controllable parameters weights. The applicability of this approach is demonstrated in systems of both fractional single ODEs and fractional coupled ODEs.

 İn this study, we present a method in order to get initial value fractional differential equations with artificial neural networks. On the basis of the function approach of feedforward neural networks, this method is a general method that is written in an implicit analytical form and results in the creation of a differentiable solution. The first part of the created trial solution which is stated as the sum of the two parts, with no controllable parameters, gives the initial conditions. The second part, unaffected by the initial conditions, consists of a feedforward neural network with controllable parameters weights. The applicability of this approach is demonstrated in systems of both fractional single ODEs and fractional coupled ODEs.

 İn this study, we present a method in order to get initial value fractional differential equations with artificial neural networks. On the basis of the function approach of feedforward neural networks, this method is a general method that is written in an implicit analytical form and results in the creation of a differentiable solution. The first part of the created trial solution which is stated as the sum of the two parts, with no controllable parameters, gives the initial conditions. The second part, unaffected by the initial conditions, consists of a feedforward neural network with controllable parameters weights. The applicability of this approach is demonstrated in systems of both fractional single ODEs and fractional coupled ODEs.

Article Details

Investigation of Solutions of −conformable Fractional Ordinary Differential Equation With Artificial Neural Network

Authors:

Sadullah Bulut | Muhammed Yiğider

Publisher:

Igdir University

Main Topics:

Matematik

Journal:

Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.13 Issue 2, pp.1266-1274

Document Type:

Article

Publication Date:

1/2023

Document Language:

English

Document ID (Org No.):

2001289846

pISSN:

2536-4618

• NeuralNetwork Method

• Numerical Solutions

• Fractional Diﬀerential Equations• NeuralNetwork Method

• Numerical Solutions

• Fractional Diﬀerential Equations

Issues

Article Details

Investigation of Solutions of −conformable Fractional Ordinary Differential Equation With Artificial Neural Network

Authors: Sadullah Bulut | Muhammed Yiğider

Publisher: Igdir University

Main Topics: Matematik

Journal: Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.13 Issue 2, pp.1266-1274

Document Type: Article

Publication Date: 1/2023

Document Language: English

Document ID (Org No.): 2001289846

pISSN: 2536-4618

• NeuralNetwork Method

• Numerical Solutions

• Fractional Diﬀerential Equations• NeuralNetwork Method

• Numerical Solutions

• Fractional Diﬀerential Equations

Issues

Authors:

Sadullah Bulut | Muhammed Yiğider

Publisher:

Igdir University

Main Topics:

Matematik

Journal:

Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.13 Issue 2, pp.1266-1274

Document Type:

Article

Publication Date:

1/2023

Document Language:

English

Document ID (Org No.):

2001289846

pISSN:

2536-4618