Neural network approach for solving nonlocal boundary value problems

This paper proposes a radial basis function (RBF) network-based method for solving a nonlinear second-order elliptic equation with Dirichlet boundary conditions. The nonlocal term involved in the differential equation needs a completely different approach from the up-to-now-known methods for solving...

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Bibliographic Details
Published in:	Neural computing & applications Vol. 32; no. 17; pp. 14153 - 14171
Main Authors:	Palade, V., Petrov, M. S., Todorov, T. D.
Format:	Journal Article
Language:	English
Published:	London Springer London 01.09.2020 Springer Nature B.V
Subjects:	Artificial Intelligence Boundary conditions Boundary value problems Computational Biology/Bioinformatics Computational Science and Engineering Computer Science Data Mining and Knowledge Discovery Differential equations Dirichlet problem Divergence Finite element method Image Processing and Computer Vision Learning Mathematical analysis Methods Neural networks Numerical integration Original Article Probability and Statistics in Computer Science Radial basis function Variational methods RBF neural network Nonlocal nonlinear problem Two-point step size gradient method Variable learning rate
ISSN:	0941-0643, 1433-3058
Online Access:	Get full text
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