PhyICNet: Physics-informed interactive learning convolutional recurrent network for spatiotemporal dynamics
The numerical solution of spatiotemporal partial differential equations (PDEs) using the deep learning method has attracted considerable attention in quantum mechanics, fluid mechanics, and many other natural sciences. In this paper, we propose an interactive temporal physics-informed neural network...
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Main Authors: | Ruohan Cao, Jin Su, Jinqian Feng, Qin Guo |
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Format: | Article |
Language: | English |
Published: |
AIMS Press
2024-12-01
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Series: | Electronic Research Archive |
Subjects: | |
Online Access: | https://www.aimspress.com/article/doi/10.3934/era.2024310 |
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