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Updated: Jun 21, 2025

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基于物理的机器学习算法用于预测沉积物产量:对物理一致性,灵敏性和可解释性的分析

Ali El Bilali1,2, Youssef Brouziyne3, Oumaima Attar4

  • 1Faculty of Sciences and Techniques, Hassan II University of Casablanca, Mohammedia, Morocco. ali1gpee@gmail.com.

Environmental science and pollution research international
|July 10, 2024
PubMed
概括

基于物理的机器学习 (ML) 模型准确预测沉积物产量,优于传统方法. 额外树模型显示出与物理沉积物运输过程的最佳一致性,有助于流域管理.

关键词:
肌肉 肌肉 肌肉机器学习是机器学习.物理一致性 物理一致性沉积物的产量是沉积物的产量.灵敏度分析是一种灵敏度分析.

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