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Enhanced data-driven shear strength predictive modeling framework for RCDBs using explainable boosting-based ensemble learning algorithms coupled with Bayesian optimization
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DOI：10.1016/j.rineng.2025.106556.png)
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摘要
En 中文
• 采用了包含950个试件的剪切破坏RCDBs数据库。
• 开发了一种增强的数据驱动框架，用于预测RCDBs的剪切强度。
• 将开发的框架与三种传统设计规范模型进行了对比评估。
• 进行了SHAP和PDPs分析，以解释开发的数据驱动框架。
Keyword:
Shear strength
RC deep beams
Data-driven approach
Artificial intelligence
Machine learning
Gradient boosting
HistGBoost
XGBoost
LightGBM
SHapley Additive exPlanations
期刊
IF:
7.9
论文数:
1.2W
被引数:
2.0W
机构
引用论文
X. The Tour of England in 1897A.P. Clark, 钢筋混凝土梁中的斜向拉力, ACI J. Proceed.. 48 (1951) (10), 145–156, https://doi.org/10.14359/11876.
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