1D -FNO - Residual convolutional neural network autoregressive prediction model for deep water wave train evolution based on high-order spectral (HOS) data-Reference-Cited by-同舟云学术

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1D -FNO - Residual convolutional neural network autoregressive prediction model for deep water wave train evolution based on high-order spectral (HOS) data

Published:2024-11 Issue: Volume:311 Page:118856
ISSN:0029-8018
Container-title:Ocean Engineering
language:en
Short-container-title:Ocean Engineering

Author:

Lv Tao,Tao Aifeng^ORCID,Xie Shuya^ORCID,Zhu Yuanzhang,Fan Jun^ORCID,Wang Gang^ORCID,Zheng Jinhai

Publisher

Elsevier BV

Reference31 articles.

1. Accurate estimation of tidal level using bidirectional long short-term memory recurrent neural network;Bai;Ocean Eng.,2021

2. HOS-ocean: open-source solver for nonlinear waves in open ocean based on High-Order Spectral method;Chicrozet;Comput. Phys. Commun.,2016

3. Assessment of classical and approximated models estimating regular waves kinematics;De Serio;Ocean Eng.,2016

4. Neural networks for wave forecasting;Deo;Ocean Eng.,2001

5. An efficient surface-integral algorithm applied to unsteady gravity waves;Dold;J. Comput. Phys.,1992

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