摘要
为解决盾构掘进过程中因盾构前倾变形、蛇形、轴线偏离及纠偏等影响施工安全性与高效性的问题,提出一种将类别型特征梯度提升(CatBoost)与第三代非支配排序遗传算法(NSGA-Ⅲ)相结合的盾构姿态多目标优化方法;以贵阳地铁为例,选取22个影响因素作为输入参数,利用CatBoost算法建立输入参数与盾构姿态之间的非线性映射函数关系,采用随机森林(RF)算法评价输入参数的重要性;以盾构姿态绝对值最小化为目标,构建CatBoost-NSGA-Ⅲ多目标优化模型,并通过案例分析验证所提方法的适用性和有效性。结果表明:采用CatBoost算法训练工程实测数据得到的预测模型具有较高的精度,5个盾构姿态目标的R^(2)范围为0.916~0.943;所研发的CatBoost-NSGA-Ⅲ盾构姿态多目标优化方法,可使盾构姿态得到显著优化,整体改进的平均值为53.34%。
To solve the problems such as forward tilt deformation,serpentine shape,axis deviation and correction during shield tunneling,which affected the safety and efficiency of shield construction,a multi-objective optimization method of shield attitude combining CatBoost and NSGA-Ⅲwas proposed.Taking Guiyang Metro as the background,22 influencing factors were selected as input parameters,and the nonlinear mapping function relationship between input parameters and shield attitude was established by using CatBoost algorithm.The importance of input parameters was evaluated by random forest(RF)algorithm.A CatBoost-NSGA-Ⅲmulti-objective optimization model was established to minimize the absolute value of the shield attitude,and the applicability and effectiveness of the proposed method were verified by a case study.The results show that the prediction model obtained by using CatBoost algorithm to train engineering measured data has high accuracy,and the R^(2)range of 5 shield attitude targets is 0.916-0.943.By using the CatBoost-NSGA-Ⅲmulti-objective optimization method,the attitude of the shield can be optimized significantly,and the average value of the overall improvement is 53.34%.
作者
吴贤国
刘俊
曹源
雷宇
李士范
覃亚伟
WU Xianguo;LIU Jun;CAO Yuan;LEI Yu;LI Shifan;QIN Yawei(School of Civil and Hydraulic Engineering,Huazhong University of Science and Technology,Wuhan Hubei 430074,China;Wuhan Huazhong University of Science and Technology Test Technology Co.,Ltd.,Wuhan Hubei 430074,China)
出处
《中国安全科学学报》
CAS
CSCD
北大核心
2024年第8期69-77,共9页
China Safety Science Journal
基金
国家自然科学基金资助(51378235,71571078,51308240)
国家重点研发计划项目(2016YFC0800208)
2021年度市教委科学技术研究计划青年项目(KJQN202103801)。
