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arXiv AI By Xi Wu, Yanqing Wei, Hang Yin, Pengze Li, Hongshuai Qi, Xi Chen

MorphoGP: A Nonparametric Framework for Predicting Equilibrium Beach Profiles Under Tidal Influence

Read the original on arXiv AI →

MorphoGP is a nonparametric Gaussian process framework designed to predict equilibrium beach profiles under tidal influence. It first classifies beach morphologies using a ContourCluster model based on contrastive learning, then trains a specialized Gaussian process expert for each category to learn relationships between environmental descriptors (waves, tides, sediments) and beach shape. A Gating Net probabilistically combines the experts’ outputs, achieving a 59.3% reduction in test RMSE compared to the best baseline, with a final RMSE of 0.297 m on over 180 Chinese coast beach profiles.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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