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Updated: May 9, 2025

Exploring the Effects of Atmospheric Forcings on Evaporation: Experimental Integration of the Atmospheric Boundary Layer and Shallow Subsurface
13:27

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Published on: June 8, 2015

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使用L2规范化更新增强相对湿度建模

Abdellah Ben Yahia1, Iman Kadir2, Abdelaziz Abdallaoui2

  • 1Laboratory of Analytical Chemistry and Electrochemistry, Faculty of Sciences, Processes and Environment Team, URL-CNRST N 13, Moulay Ismail University, Meknes, Morocco. abd.benyahia@edu.umi.ac.ma.

Scientific reports
|April 28, 2025
PubMed
概括

与PCA和SOM相结合的L2规范化有效地防止了用于气象建模的人工神经网络 (ANN) 的过. 这种方法通过优化模型参数来提高相对湿度的预测准确性.

关键词:
和坦吉尔.人工神经网络的人工神经网络L2 调节的规范化过度装配 过度装配 是一个问题.相对湿度 相对湿度

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