Article

Deep learning based bias correction model for numerical simulations of wave spectra

Ocean Engineering

Zhang, Lu; Duan, Wenyang; Huang, Limin — 2025 — Elsevier

Key information

Authors:

Zhang, Lu; Duan, Wenyang; Guedes Soares, C. (Carlos Guedes Soares); Zhang, Jie; Liu, Yuliang; Huang, Limin

Published in

December 30, 2025

Abstract

To accurately characterize the energy distribution under different frequency ranges, this paper developed a deep learning-based wave spectral bias correction model for numerical simulations of wave spectra, which addresses the shape of the numerically predicted spectra. This model preprocesses the measured wave spectra using a Gaussian filter, and the frequency of the numerical simulation results from WAVEWATCH III is matched using the interpolation method. Afterwards, the simulated wave spectra serve as the input to the proposed model, and discrepancies between the numerical simulation results and buoy measurement data are fitted using the neural network model. Moreover, the correction performance of the model is validated using measured data in terms of spectral shape, significant wave height, peak frequency, and peak energy density. With the proposed method the mean absolute percentage error of those parameters of decreases by 5 %–15 % and the spectral correlation for the Hawaiian waters is no less than 0.93. The results demonstrate that the proposed model can more accurately characterize the wave energy distribution and significantly improve the accuracy of wave simulations.

Publication details

Authors in the community:

Publication version

AO - Author's Original

Publisher

Elsevier

Link to the publisher's version

https://www.sciencedirect.com/science/article/abs/pii/S0029801825028586?via%3Dihub

Title of the publication container

Ocean Engineering

First page or article number

123175

Volume

342

Issue

Part 4

ISSN

0029-8018

DOI

10.1016/j.oceaneng.2025.123175

Fields of Science and Technology (FOS)

other-engineering-and-technologies - Other engineering and technologies

Keywords

  • Wave Spectra
  • Bias Correction
  • Buoy Measurement
  • WAVEWATCH III
  • Deep Learning

Publication language (ISO code)

eng - English

Rights type:

Open access

Financing entity

Fundação para a Ciência e a Tecnologia

Identifier for the funding entity: https://doi.org/10.13039/501100001871

Type of identifier of the funding entity: Crossref Funder

Number for the project, award or grant: UIDB-UIDP-00134-2020