首页|基于分类树的液化概率等级评估新方法

基于分类树的液化概率等级评估新方法

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目前地震液化概率评估方法普遍公式形式复杂,多公式间概率计算值一致性不高,且在场地层面中液化概率意义体现不足.基于这些问题,在衡量多个概率公式方法的一致性及判别优势后,筛选各方法对现有实测历史样本的合理概率计算值标定历史样本的液化概率等级;以分类树方法建立初步液化预测模型,将其结合我国抗震设防推荐值优化后,构建一组液化概率等级评估新方法.新方法分为单孔与场地液化可能性评估两部分,为实际工程中的液化风险评估提供量化依据.与现有方法相比,新方法省略了传统方法的公式计算过程,评估过程简便,结果直观.选用新西兰地震液化数据和某实际工程场地作为检验样本,从单孔与工程场地两方面检验了新方法的可靠性和合理性.验证结果表明,新方法对单孔回判正确率达93%,对工程场地评价合理性优于现有规范.新方法可为工程场地液化可能性评估提供方法支持,具有实际工程意义.
A new method of liquefaction probability level evaluation based on classification tree
Currently,earthquake liquefaction probability evaluation methods generally suffer from complex formula forms,inconsistent probability calculation values among multiple formulas,and insufficient significance of liquefaction probability at the site level.Based on these issues,after evaluating the consistency and discriminatory power of multiple probability formula methods,reasonable probability calculation values for existing measured historical samples were selected to calibrate the liquefaction probability levels of the samples.A preliminary liquefaction prediction model was established using the classification tree method and then optimized based on China's seismic design recommendations to develop a new method for liquefaction probability level evaluation.The new method is divided into two parts:single borehole and site liquefaction probability evaluation,which can provide a quantitative basis for liquefaction risk assessment in practical engineering.Compared with existing methods,the new method omits the traditional formula calculation process,making the evaluation process simpler and the results more intuitive.New Zealand earthquake liquefaction data and an actual engineering site were selected as test samples to validate the reliability and rationality of the new method at both the single borehole and site levels.The verification results show that the new method achieves a 93%accuracy rate for single borehole predictions and demonstrates better rationality in site evaluations compared to existing norms.The new method can provide methodological support for evaluating liquefaction probability at engineering sites and has practical engineering significance.

liquefaction probability levelssite liquefaction evaluationmachine learningstandard penetration test

杨洋、魏怡童

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东北林业大学土木与交通学院,黑龙江哈尔滨 150006

液化概率等级 场地液化评估 机器学习 标贯

国家自然科学基金资助项目黑龙江省博士后出站科研启动金

5237012841523005

2024

岩土力学
中国科学院武汉岩土力学研究所

岩土力学

CSTPCD北大核心
影响因子:1.614
ISSN:1000-7598
年,卷(期):2024.45(7)
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