| 引用本文: | 王大任,任叶飞,张雨婷,冀昆,王宏伟,温瑞智.一种建筑工程场地参数VS30的外推模型修正方法[J].哈尔滨工业大学学报,2023,55(9):1.DOI:10.11918/202110086 |
| WANG Daren,REN Yefei,ZHANG Yuting,JI Kun,WANG Hongwei,WEN Ruizhi.Method for correcting extrapolation model of engineering site parameter VS30[J].Journal of Harbin Institute of Technology,2023,55(9):1.DOI:10.11918/202110086 |
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| 一种建筑工程场地参数VS30的外推模型修正方法 |
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王大任1,2,任叶飞1,2,张雨婷1,2,冀昆1,2,王宏伟1,2,温瑞智1,2
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(1.中国地震局工程力学研究所, 哈尔滨 150080; 2.中国地震局地震工程与工程振动重点实验室(中国地震局工程力学研究所),哈尔滨 150080)
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| 摘要: |
| 为提高覆盖土层较浅工程场地上钻孔的外推VS30值精度,选取日本KiK-net台站中符合一定条件的钻孔数据,利用相关系数矩阵排除共线性问题以确定可用于回归的3个体现钻孔剖面特性的参数,通过最优子集法建立常数外推VS30残差与这3个参数的优选函数关系,利用调整后R2、贝叶斯信息准则和k倍交叉验证3种特征选择方法确定其中的最优关系。根据修正后预测VS30与实际观测VS30间残差均值和标准差的分布给出推荐的常数外推模型修正函数。结果表明,该VS30的外推模型能够较好提高底部常速度模型的预测精度,并且在新疆地区具有一定适用性。提出的方法可以对中国不同地区的场地VS30经验估计模型建立提供参考。 |
| 关键词: 场地参数VS30 常数外推模型 修正方法 最优子集法 特征选择 |
| DOI：10.11918/202110086 |
| 分类号:P315.9 |
| 文献标识码:A |
| 基金项目:国家重点研发计划(2019YFE0115700)；国家自然科学基金(51878632)；黑龙江省自然科学基金优秀青年项目(YQ2019E036) |
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| Method for correcting extrapolation model of engineering site parameter VS30 |
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WANG Daren1,2,REN Yefei1,2,ZHANG Yuting1,2,JI Kun1,2,WANG Hongwei1,2,WEN Ruizhi1,2
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(1.Institute of Engineering Mechanics, China Earthquake Administration, Harbin 150080, China; 2.Key Lab of Earthquake Engineering and Engineering Vibration of China Earthquake Administration (Institute of Engineering Mechanics, China Earthquake Administration), Harbin 150080, China)
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| Abstract: |
| To improve the accuracy of the extrapolated VS30 values of boreholes on engineering sites with shallow overburden, this paper selects certain borehole data from KiK-net database for research. The correlation coefficient matrix was adopted to test the collinearity of parameters, and three parameters that can reflect the characteristics of borehole profiles were determined. Through the optimized subset method, the relationship functions between the residuals of VS30 estimated by bottom constant velocity (BCV) model and the three selected parameters were established. On the basis of three feature selecting methods including adjusted R2, Bayesian information criterion, and k-fold cross-validation, the optimal function was proposed. According to the distribution of mean and standard deviation of residuals between predicted and observed VS30 values, a correction function of BCV model was proposed. Results show that the extrapolation model of VS30 could improve the prediction accuracy of BCV model, and it was applicable in Xinjiang region. The method proposed in this paper can provide reference for developing empirical models for estimating VS30 in other regions of China. |
| Key words: site parameter VS30 bottom constant velocity model correcting method optimized subset method feature selection |
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