In the current paper, a neural network method to solve sixth-order differential equations and their boundary conditions has been pre-sented. The idea this method incorporates is to integrate knowl-edge about the differential equation and its boundary conditions into neural networks and the training sets. Neural networks are be-ing used incessantly to solve all kinds of problems hailing a wide range of disciplines. Several examples are given to illustrate the efficiency and implementation of the Neural Network method. Keywords
In this investigation we introduced the method for solving Ordinary Differential Equations (ODEs) us...
Artificial Neural Network (ANN), particularly radial basis function (RBF) is used to solve the Parti...
Abstract—Partial differential equations (PDEs) with boundary conditions (Dirichlet or Neumann) defin...
This book introduces a variety of neural network methods for solving differential equations arising ...
We propose a solver for differential equations, which uses only a neural network. The network is bui...
Two numerical methods using neural networks for the solution of the time independent Schrödinger equ...
In this work neural networks are used to approximate the solutions of multiple differential equa- ti...
Ordinary Differential Equations (ODEs) play a key role in describing the physical, chemical, and bio...
Abstract. In this paper, a new approach is proposed in order to solve the differential equations of ...
Differential equations are ubiquitous in many fields of study, yet not all equations, whether ordina...
Differential equations are ubiquitous in many fields of study, yet not all equations, whether ordina...
Differential equations are ubiquitous in many fields of study, yet not all equations, whether ordina...
We present a method to solve initial and boundary value problems using artificial neural networks. A...
In this work we investigate neural networks and subsequently physics-informed neural networks. Physi...
Recent works have shown that neural networks can be employed to solve partial differential equations...
In this investigation we introduced the method for solving Ordinary Differential Equations (ODEs) us...
Artificial Neural Network (ANN), particularly radial basis function (RBF) is used to solve the Parti...
Abstract—Partial differential equations (PDEs) with boundary conditions (Dirichlet or Neumann) defin...
This book introduces a variety of neural network methods for solving differential equations arising ...
We propose a solver for differential equations, which uses only a neural network. The network is bui...
Two numerical methods using neural networks for the solution of the time independent Schrödinger equ...
In this work neural networks are used to approximate the solutions of multiple differential equa- ti...
Ordinary Differential Equations (ODEs) play a key role in describing the physical, chemical, and bio...
Abstract. In this paper, a new approach is proposed in order to solve the differential equations of ...
Differential equations are ubiquitous in many fields of study, yet not all equations, whether ordina...
Differential equations are ubiquitous in many fields of study, yet not all equations, whether ordina...
Differential equations are ubiquitous in many fields of study, yet not all equations, whether ordina...
We present a method to solve initial and boundary value problems using artificial neural networks. A...
In this work we investigate neural networks and subsequently physics-informed neural networks. Physi...
Recent works have shown that neural networks can be employed to solve partial differential equations...
In this investigation we introduced the method for solving Ordinary Differential Equations (ODEs) us...
Artificial Neural Network (ANN), particularly radial basis function (RBF) is used to solve the Parti...
Abstract—Partial differential equations (PDEs) with boundary conditions (Dirichlet or Neumann) defin...