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使用基于更新的病例历史的物流模型树进行斜坡的稳定性风险评估
Feezan Ahmad1, Xiao-Wei Tang1, Mahmood Ahmad2,3
1State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China.
Mathematical biosciences and engineering : MBE
|December 21, 2023
概括
一个新的物流模型树 (LMT) 模型使用627个案例准确预测斜率稳定性. 这种先进的模型为地质工程应用提供了更高的准确性和可靠性.
科学领域:
- 地质技术工程 地质技术工程
- 计算地质学的计算地质学
- 预测建模预测建模
背景情况:
- 斜坡稳定性是土木工程项目中的一个关键因素.
- 准确的预测模型对于减轻与山体滑坡相关的风险至关重要.
- 现有的模型在预测准确性和范围上往往有局限性.
研究的目的:
- 开发和验证一种新的物流模型树 (LMT),用于预测坡度稳定性.
- 根据已建立的统计指标来评估LMT模型的性能.
- 通过案例研究和风险分析来证明LMT模型的实际适用性.
主要方法:
- 开发一个物流模型树 (LMT) 模型.
- 使用一个更新的数据库,包含627个斜坡稳定性案例.
- 输入参数包括单位重量,凝聚力,摩擦角,斜坡角,高度和孔隙压力比.
- 使用精度 (Acc),马修斯相关系数 (Mcc),AUC和F-score的性能评估.
- 通过两项涉及十个斜坡稳定事件的案例研究进行验证.
主要成果:
- 拟议的LMT模型实现了高预测性能:Acc = 85.6%,Mcc = 0.713,AUC = 0.907.
- 稳定和失败国家的F-分数分别为0.967和0.923.
- 模型预测与案例研究中的实际现场条件一致.
- 风险分析结果与观察到的条件保持一致,显示出实际效用.
结论:
- 与现有方法相比,开发的LMT模型显示了与现有方法相比,倾斜稳定的优越预测能力.
- 模型的准确性和可靠性通过严格的统计评估和案例研究验证得到证实.
- LMT模型为地质工程中的概率风险评估提供了一个有价值的工具.
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