This Python code provides a framework for solving non-linear or linear differential equations using neural networks, specifically using the PyTorch library. Additionally, it includes a class that ...

This repository contains Python code for approximating the solution of a second-order inhomogeneous ordinary differential equation (ODE) with boundary conditions using an Extreme Learning Machine (ELM ...

Abstract As we know that the power series method is a very effective method for solving the Ordinary differential equations (ODEs) which have variable coefficient, so in this paper we have studied how ...

Abstract The differential transformation method (DTM) is applied to solve the second-order random differential equations. Several examples are represented to demonstrate the effectiveness of the ...

The purpose of this paper is to solve directly the second order delay differential equations (DDEs) using The extended two and extended three point implicit one-step block methods using constant step ...

Ordinary differential equations (ODEs) are a fundamental tool for modeling dynamical systems in various scientific fields. However, solving ODEs analytically can be challenging, and numerical methods ...

This book is an introduction to the general theory of second order parabolic differential equations, which model many important, time-dependent physical systems. It studies the existence, uniqueness, ...