使用CatBoost预测预压混凝土连续刚性框架桥梁的机械性能
Qingfu Li1, Xiang Wang2, Xiyu Ma1
1School of Water Conservancy and Transportation, Zhengzhou University, Zhengzhou, 450001, China.
Scientific reports
|November 22, 2025
概括
本研究介绍了一种CatBoost模型,用于预测预压混凝土桥的机械性能,比传统方法提高了准确性. 该模型有效地预测压力和位移,有助于稳健的基础设施设计.
科学领域:
- 土木工程 土木工程是指土木工程.
- 计算力学 计算力学 计算力学
- 机器学习应用 机器学习应用
背景情况:
- 预压混凝土连续刚性框架桥梁是基础设施的重要组成部分.
- 传统的设计依赖于复杂的数值计算,需要高度的工程专业知识.
- 开发有效的桥梁性能预测模型至关重要.
研究的目的:
- 开发一种创新的预测模型,用于预压混凝土连续刚性框架桥梁的机械性能.
- 在关键的桥梁位置建立最大应力和位移 (垂直,横向) 的预测模型.
- 将CatBoost模型的性能与传统的机器学习算法进行比较.
主要方法:
- 利用CatBoost机器学习模型进行性能预测.
- 通过有限元模拟生成训练数据集.
- 采用贝叶斯优化用于自动化超参数调整.
- 应用了SHAP分析和部分依赖图用于模型解释性.
主要成果:
- 在测试组中,CatBoost模型展示了出色的预测性能.
- 与支持向量回归 (SVR) 和决策树 (DT) 模型相比,在预测准确度和稳定性方面取得了显著的改进.
- 确定了影响机械性能的关键参数,包括混凝土的性能和压力前损失.
结论:
- CatBoost模型提供了一种强大而准确的方法来预测预压混凝土桥的机械性能.
- 这种方法可以提高桥梁设计过程的效率和可靠性.
- 了解参数的影响有助于优化结构设计和降低风险.
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