基于XGBoost的替代技术,用于系统可靠性分析,用于基础对空洞的基础,并辅助启动
Kumar Shubham1,2, Subhadeep Metya3, Abdhesh Kumar Sinha3
1Department of Civil Engineering, Indian Institute of Technology Guwahati, Guwahati, Assam, 781039, India. shubham13202007@gmail.com.
Scientific reports
|February 3, 2026
概括
本研究提出了使用极端梯度提升 (XGBoost) 和蒙特卡洛模拟 (MCS) 在空洞上方基础可靠性分析的框架. 系统可靠性评估至关重要,与个人标准相比,故障概率显著增加.
科学领域:
- 地质技术工程 地质技术工程
- 结构可靠性分析分析
- 计算力学 计算力学 计算力学
背景情况:
- 位于空洞上方的基础构成了独特的稳定性挑战.
- 传统的可靠性方法可能无法充分捕捉时间依赖的行为和复杂的不确定性.
- 准确评估承载能力 (BC) 和结算对于基础性能至关重要.
研究的目的:
- 开发一个全面的框架,以时间依赖的系统可靠性分析的基础上空腔.
- 利用先进的机器学习和模拟技术来预测基础响应变量.
- 量化考虑系统可靠性与个人故障标准的影响.
主要方法:
- 使用极端梯度提升 (XGBoost) 回归用于承载能力 (BC) 和结算预测的替代模型的开发.
- 启动技术的应用,以纳入非正常分布数据的参数可变性和日志转换.
- 集成XGBoost代理模型与蒙特卡洛模拟 (MCS) 进行时间依赖的可靠性分析.
主要成果:
- XGBoost模型实现了高的预测准确性 (R2 = 0.97对于BC,R2 = 0.86对于结算).
- 系统可靠性分析显示,与单个BC标准相比,故障概率显著增加 (29.62%的结算标准,55.74%的系统可靠性).
- 时间依赖的灵敏度分析显示,可靠性指数随着时间的推移而逐渐下降.
结论:
- 拟议的框架有效地评估了空洞以上基础的时间依赖系统可靠性.
- 系统可靠性评估至关重要,强调仅考虑单个故障模式的局限性.
- 这些发现强调了在基础绩效分析中考虑时间变化的重要性.
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