:

Jianbin Xie1, Xingru Feng2, Tianhai Gao1

  • 1Key Laboratory of Ocean Observation and Forecasting, Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China; University of Chinese Academy of Sciences, Beijing 100029, China.

PubMed
概括

本研究引入了一种使用卷积神经网络 (CNN) 的深度学习模型,从卫星数据准确估计悬浮沉积物度 (SSC). 该模型有效地预测每小时的SSC变化,优于传统方法并改善数据插值.

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