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Predicting wind-driven rain amount on building facade based on machine learning models
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DOI：10.1016/j.buildenv.2025.113308.png)
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摘要
En 中文
• 野外观测测量为机器学习模型提供数据。
• 机器学习模型在恶劣天气条件下的预测精度优于ASHRAE。
• 超参数优化增强了机器学习模型的性能。
• RBF神经网络和SVM表现出高精度和稳定性。
期刊
IF:
7.6
论文数:
1.3W
被引数:
6.6W
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