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Explicit wave height prediction model and regularity analysis for floating breakwaters based on deep symbolic regression

Jiaming Jing; Xiaofei Cheng; Haibo Chen; Wei Xie
Frontiers in Marine Science · Vol. 13 · 2026

Abstract

The accurate prediction of wave attenuation across floating breakwaters is essential for coastal structure design and nearshore aquaculture safety. This study employs Physical Symbolic Optimization (PhySO) to model the transmission of significant wave height (H s ) and maximum wave height (H max ) behind a floating breakwater in Lianjiang, Fujian Province. Using in-situ wave data including incident wave height, period, and direction, the dataset is split into 80% training and 20% testing sets, with constraints on expression complexity and physical consistency. Results show that PhySO produces explicit, interpretable formulas with strong generalization ability: the best H max expression achieves accuracy comparable to black-box machine learning models, while H s expressions show slightly lower but still reliable performance. Simple linear scaling expressions exhibit excellent robustness across all wave conditions, and incident wave height is confirmed as the dominant controlling factor. This work demonstrates the value of PhySO in balancing accuracy and physical interpretability, offering a practical and easy-to-use tool for engineering applications.

Bibliographic Information

JournalFrontiers in Marine Science
PublisherFrontiers
Publication Date2026-07-22
Publication Year2026
Volume13
Document TypeJournal Article
eISSN2296-7745
DOI10.3389/fmars.2026.1875119
SubjectMarine science; fisheries; aquaculture; pollution; ocean observation; policy

Access Information

NARA Access CoverageOA / free full text
Journal Homepagehttps://www.frontiersin.org/journals/marine-science
Publisher PageOpen Publisher Page
This article is openly available from the publisher.