Semi-Analytical Scheme for Solving Intuitionistic Fuzzy System of Differential Equations Abstract: The aim of this article is to implement the Generalized Modified Adomian Decomposition Method to ...

Nonlinear equations systems (NESs) arise in a wide range of domains. Solving NESs requires the algorithm to locate multiple roots simultaneously. To deal with NESs efficiently, this study presents an ...

Ordinary Differential Equations. Introduction to methods for finding solutions to differential equations involving a single, independent variable. Topics include linear equations, exact solutions, ...

Introduction to analytical and numerical methods for finding solutions to differential equations involving two or more independent variables. Topics include linear partial differential equations, ...

A collection of resources about partial differential equations, deep learning, graph neural networks, dynamic system simulation. We also roughly categorize the resources into the following categories ...

A short course in differential equations by Rainville, Earl D. (Earl David), 1907-1966 Publication date 1969 Topics Differential equations, Équations différentielles, Differential equations, ...

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Rats exhibit significant recovery of locomotor function following incomplete spinal cord injuries, albeit with altered gait expression and reduced speed and stepping frequency. These changes likely ...

About DP-GST is a diffusion model leveraging Graph Neural Networks (GNNs) as its backbone, designed for solving the Group Steiner Tree (GST) problem under differential privacy constraints.

Learn about and revise how to simplify algebra using skills of expanding brackets and factorising expressions with GCSE Bitesize AQA Maths.