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Updated: Sep 12, 2025

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing
08:54

Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing

Published on: February 13, 2018

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一个基于波形变换的卷积神经网络长期短期记忆 (CNN-LSTM) 注意模型,用于预测终端玻璃幕墙表面的非静止风压系数

Yuxuan Bao1, Cheng Pei1,2, Yuhao Mou1

  • 1Airport College, Civil Aviation Flight University of China, Luocheng, China.

Science progress
|August 5, 2025
PubMed
概括

一个新的波纹分解和基于注意力的神经网络准确地预测了机场玻璃幕墙上的非静止风压. 这种模型显著提高了强风条件的预测准确性.

关键词:
预测风压系数的预测注意力机制注意力机制卷积神经网络是一种卷积神经网络.长期短期记忆 神经网络 神经网络波形变换波形变换波形变换.

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