Numerical solution of (2+1)-dimensional nonlinear sine-Gordon equation with variable coefficients by using an efficient deep learning approach
In this article, we present an efficient neural-network-based deep learning approach, physics-informed neural networks (PINNs) with regularization technique, to resolve (2+1)-dimensional nonlinear damped and undamped sine-Gordon problem with variable coefficients. We suggest a multi-objective cost f...
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| Published in: | Zeitschrift für angewandte Mathematik und Physik Vol. 76; no. 4; p. 134 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Heidelberg
Springer Nature B.V
01.08.2025
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| Subjects: | |
| ISSN: | 0044-2275, 1420-9039 |
| Online Access: | Get full text |
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