Work

Fast coastal wave climate prediction using autoencoders-based models

Year: 2026

Type: article

Abstract: • Surrogate autoencoder is proposed for spatially distributed nearshore wave prediction. • MDA and K-means organize study area into homogeneous macro-areas for enhanced analysis. • Accurate reconstruction of H s , T p , and Dir wave , with RMSE of about ∼ 10 %–15%. • The model enables near real-time predictions for efficient coastal forecasting.

Source: Ocean Engineering

DOI: 10.1016/j.oceaneng.2026.126118

Authors: Elisa Castro, Claudio Iuppa, Maria Gabriella Xibilia, Luca Patanè, Rosaria Ester Musumeci, Enrico Foti, Luca Cavallaro

Institutions: University of Catania, University of Messina

Language: English

Topic: Coastal and Marine Dynamics

Subfield: Earth-Surface Processes

Field: Earth and Planetary Sciences

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $4,150

Funders: European Commission, Ministero dell’Istruzione, dell’Università e della Ricerca, Università di Catania, Politecnico di Milano, Ministero dell'Università e della Ricerca, Ministero dell'Istruzione e del Merito

Awards: G1016654603, G4932054988, G7371128001

OpenAlex ID: W7162681295

FWCI:

Cites: 18

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