Solving initial-boundary value problems for systems of partial differential equations using neural networks and optimization techniques
DOI10.1016/j.jfranklin.2009.05.003zbMath1298.65155OpenAlexW2020561998MaRDI QIDQ468201
Publication date: 6 November 2014
Published in: Journal of the Franklin Institute (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jfranklin.2009.05.003
initial-boundary value problemsmultidimensional optimizationfeed forward artificial neural networkstime-dependent system of partial differential equations
Numerical optimization and variational techniques (65K10) Neural networks for/in biological studies, artificial life and related topics (92B20) Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems (65M99)
Related Items (19)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Modelling the dynamics of nonlinear partial differential equations using neural networks
- Numerical solution for high order differential equations using a hybrid neural network-optimization method
- Neural networks: computational models and applications.
- The solutions of vibration control problems using artificial neural networks
- Multilayer feedforward networks are universal approximators
- Novel determination of differential-equation solutions: Universal approximation method
- A hybrid neural network model for the dynamics of the Kuramoto-Sivashinsky equation
- Convergence Properties of the Nelder--Mead Simplex Method in Low Dimensions
- Feedforward Neural Network Methodology
- Neural‐network‐based approximations for solving partial differential equations
- Pseudospectral analysis for the solution of nonlinear partial differential equations
- Neural network training and simulation using a multidimensional optimization system
- Multidomain Collocation Methods for the Stream Function Formulation of the Navier–Stokes Equations
- Pseudospectral collocation methods for fourth-order differential equations
- Theoretical Numerical Analysis
- On the Structure of Continuous Functions of Several Variables
- A Simplex Method for Function Minimization
- A logical calculus of the ideas immanent in nervous activity
- Principles of Artificial Neural Networks
- Approximation by superpositions of a sigmoidal function
- Neural network method for solving partial differential equations
This page was built for publication: Solving initial-boundary value problems for systems of partial differential equations using neural networks and optimization techniques