An Improved Method for Physics-Informed Neural Networks That Accelerates Convergence

An Improved Method for Physics-Informed Neural Networks That Accelerates Convergence

Physics-Informed Neural Networks (PINNs) have proven highly effective for solving high-dimensional Partial Differential Equations (PDEs), having demonstrated tremendous potential in a variety of challenging scenarios. However, traditional PINNs (vanilla PINNs), typically based on fully connected neu...

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Bibliographic Details
Main Authors: Liangliang Yan, You Zhou, Huan Liu, Lingqi Liu
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Physics-informed neural network
partial differential equations
multi-input residual network
convergence speed
unsupervised learning
Online Access:https://ieeexplore.ieee.org/document/10399482/

Internet

https://ieeexplore.ieee.org/document/10399482/

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