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谢梦龙, 叶新宇, 张升, 盛岱超. LASSO算法及其在边坡稳定性分析中的应用[J]. 岩土工程学报, 2021, 43(9): 1724-1729. DOI: 10.11779/CJGE202109018
引用本文: 谢梦龙, 叶新宇, 张升, 盛岱超. LASSO算法及其在边坡稳定性分析中的应用[J]. 岩土工程学报, 2021, 43(9): 1724-1729. DOI: 10.11779/CJGE202109018
XIE Meng-long, YE Xin-yu, ZHANG Sheng, SHENG Dai-chao. LASSO algorithm and its application in slope stability analysis[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(9): 1724-1729. DOI: 10.11779/CJGE202109018
Citation: XIE Meng-long, YE Xin-yu, ZHANG Sheng, SHENG Dai-chao. LASSO algorithm and its application in slope stability analysis[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(9): 1724-1729. DOI: 10.11779/CJGE202109018

LASSO算法及其在边坡稳定性分析中的应用

LASSO algorithm and its application in slope stability analysis

  • 摘要: 将LASSO算法引入边坡可靠度分析中,建立算法模型预测边坡安全系数,并实现搜索边坡危险区域的功能。首先,借助有限元软件实现蒙特卡洛模拟,获取边坡各处土体参数及对应安全系数数据集。其次,通过LASSO算法对获取的数据集进行分析,建立模型预测特定条件下边坡安全系数,该结果通过与普通线性回归算法预测的结果进行比较,证实了LASSO算法的优越性。同时,提出了其在边坡长期风险监控中的应用建议。最后,将LASSO算法与蒙特卡洛模拟相结合,充分考虑多次模拟结果,实现搜索边坡最危险区域功能。结果表明,与普通线性回归算法相比,LASSO算法所建立的模型能准确搜索到影响边坡稳定性的最危险区域。因此,LASSO算法能为边坡长期风险监控和边坡加固工作提供新的思路。

     

    Abstract: By introducing the LASSO algorithm into the slope reliability analysis, an algorithm model to predict the safety factor of a slope is established, and the function of searching the dangerous area of the slope is realized. First, using the finite element software is used to implement the Monte Carlo algorithm and to obtain the data of slope reliability analysis. Second, the acquired data is analyzed by the LASSO algorithm. A model is established to predict the safety factor of the slope under the specific intensity parameter distribution. The predicted results are compared with those by the ordinary linear regression algorithm to confirm the superiority of the LASSO algorithm, and its application suggestions in long-term slope risk monitoring are put forward. Third, the LASSO algorithm is combined with the Monte Carlo simulation to search for the most dangerous areas that affect the stability of the slope under multiple simulation results. The results indicate that compared with the ordinary linear regression algorithm, the model established by the LASSO algorithm can accurately find out the most dangerous area that affects the stability of the slope. Therefore, the LASSO algorithm can provide new ideas for the long-term slope risk monitoring and slope reinforcement.

     

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