These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

This is a short Python 3 script that uses the SciPy package’s integrate.odeint method to solve a set of coupled ordinary differential equations approximating the infiltration of a wetting front into ...

The book can be useful for specialists in partial differential equations, functional analysis, theory of approximation of differential equations, and for all researchers, students, and postgraduates ...

In simple words: to solve differential equations, you need to know the approximation of differential equations. Approximation of a differential equation by a difference—approximation of a differential ...

The central cell is set to 1 and then, the 1 value extends to the neighbor cells that are initially set to 0. In this paper, we are interested in exploring the capabilities of the movements of the ...

The application of radial basis function networks for approximating functions and solving partial differential equations has investigated. Fast gradient first-order methods and an algorithm of the ...

Physics Informed Neural Networks (PINNs) for the approximation of partial differential equations; Generative adversarial networks (GANs) for the learning of probability distributions from data; ...