CL-PINN: A Physics-Informed Neural Networks Framework for Equatorial Tsunami Wave Propagation in Geophysical Ocean

Wave dynamics are governed by linear and nonlinear partial differential equations, where prior physical knowledge in the form of differential equations plays a crucial role in simulating dynamical models. Traditional analytical models often drift over time due to noise in real-world data, while data...

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Bibliografische Detailangaben

Hauptverfasser:	Arup Kumar Sahoo, Swarup Kumar Sahoo, S. Chakraverty
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	IEEE 2025-01-01
Schriftenreihe:	IEEE Access
Schlagworte:	Physics-informed neural networks curriculum learning tanh activation function Boussinesq-type equations symplectic artificial neural networks unsupervised
Online-Zugang:	https://ieeexplore.ieee.org/document/11136129/
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