程秋实, 杨志双, 秦胜伍, 等. 2022. 基于PSO-MLSSVR的土体参数反演方法在深基坑工程中的应用[J]. 工程地质学报, 30(2): 520-532. doi: 10.13544/j.cnki.jeg.2021-0143.
    引用本文: 程秋实, 杨志双, 秦胜伍, 等. 2022. 基于PSO-MLSSVR的土体参数反演方法在深基坑工程中的应用[J]. 工程地质学报, 30(2): 520-532. doi: 10.13544/j.cnki.jeg.2021-0143.
    Cheng Qiushi, Yang Zhishuang, Qin Shengwu, et al. 2022. Application of soil parameters inversion based on PSO-MLSSVR in deep foundation pit engineering[J]. Journal of Engineering Geology, 30(2): 520-532. doi: 10.13544/j.cnki.jeg.2021-0143.
    Citation: Cheng Qiushi, Yang Zhishuang, Qin Shengwu, et al. 2022. Application of soil parameters inversion based on PSO-MLSSVR in deep foundation pit engineering[J]. Journal of Engineering Geology, 30(2): 520-532. doi: 10.13544/j.cnki.jeg.2021-0143.

    基于PSO-MLSSVR的土体参数反演方法在深基坑工程中的应用

    APPLICATION OF SOIL PARAMETERS INVERSION BASED ON PSO-MLSSVR IN DEEP FOUNDATION PIT ENGINEERING

    • 摘要: 为了确保基坑工程安全,常常会采用数值模拟的方法预测支护结构的位移,其中岩土体力学参数的选取对于结果的影响最大。本文使用了一种粒子群(PSO)算法结合多输出最小二乘支持向量回归机(MLSSVR)的基坑土体参数位移反分析法,以深圳某深基坑的支护桩顶水平位移监测数据为依据,基于正交设计生成具有代表性的土体参数组合,通过有限元计算得到研究点的位移作为训练样本,使用粒子群PSO算法对多输出MLSSVR模型参数寻优,利用MLSSVR构建反演参数与位移之间的映射关系,反演填石层、淤泥层和砂质黏土层的土体参数,将反演参数代入有限元模型计算测点位移。结果表明:在反演参数过程中,MLSSVR模型比单输出最小二乘支持向量回归机(LSSVR)耗时更短,而且将两个模型的反演参数代入有限元模型进行计算时,MLSSVR的结果较LSSVR更贴近于实际监测值,对比结果验证了研究方法的优越性; 在施工的不同阶段,使用MLSSVR得到反演参数进行数值模拟,得到的模拟结果与监测数据吻合较好,验证该方法具有准确性和实用性。结果分析证明本文研究方法可以有助于土体参数的选取,提高基坑数值模拟结果的准确性。

       

      Abstract: In order to ensure the safety of foundation pit construction,numerical simulation is used to predict the displacement of support structure. The selection of geotechnical parameters has the greatest influence on the numerical simulation results. A back analysis method based on multioutput least-squares support vector regression machine(MLSSVR) and particle swarm(PSO) is proposed to estimate multiple geotechnical parameters. This paper uses PSO-MLSSVR method to invert geotechnical parameters based on horizontal displacement monitoring data from the top of the supporting piles in a deep foundation pit in Shenzhen. Based on the orthogonal design method,representative combinations of geotechnical parameters are generated. Using these combinations,finite element method(FEM) is used to calculate the displacement of the measured points. PSO algorithm is used to optimize the parameters of MLSSVR model. Using MLSSVR to construct mapping relationships between inversion parameters and displacements to invert soil parameters in rock-fill,silt and sandy clay layers. The inverse parameters are substituted into the finite element model to calculate the measured point displacements. The results show that the MLSSVR model takes less time than the single output least squares support vector regressor(LSSVR) in inverting the parameters. When the inversion parameters of both models are substituted into the finite element model for calculation,the results of MLSSVR are closer to the actual monitoring values than LSSVR. The comparative results validate the superiority of the study methodology. In different stages of construction,the inversion parameters obtained by MLSSVR are used for numerical simulation. The simulation results are in good agreement with the monitoring data,which verified the accuracy and practicability of this method. The results show that the method in this paper is helpful to the selection of soil parameters and improve the accuracy of numerical simulation results.

       

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