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August 11, 2025Frontiers in Environmental ScienceOpen Access

Morphodynamic predictions based on Machine Learning. Performance and limits for pocket beaches near the Bilbao port

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Authors

MVManuel ViñesASAgustín Sánchez‐ArcillaIEIrati Epelde

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Overview

This analysis demonstrates improved predictions of beach behavior in pocket beaches using machine learning, suggesting benefits for coastal management strategies.

Key Points

  • ML-based predictions outperformed traditional statistical methods, confirming a significant leap in predictive accuracy.
  • The gradient boosting regressor showed R² values exceeding 0.7 in several cases, indicating robust model performance.
  • Data collection involved extreme meteo-oceanographic events affecting pocket beaches, underlining environmental influences.
  • Results emphasize the necessity for sustainable coastal management, highlighting adaptive strategies for increased beach resilience.

Cite This Study

Viñes et al. (2025) studied this question.

synapsesocial.com/papers/68a360ce0a429f7973328bbchttps://doi.org/10.3389/fenvs.2025.1600473
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