基于随机森林-NSGA-Ⅲ的盾构姿态优化控制  

Shield Attitude Optimization and Control Based on Random Forest-NSGA-Ⅲ

作　　者：吴忠坦 吴贤国[2] 刘俊[2] 陈虹宇[3] 肖宏笛 覃亚伟[2,4] WU Zhongtan;WU Xianguo;LIU Jun;CHEN Hongyu;XIAO Hongdi;QIN Yawei(Wuhan Metro Group Co.,Ltd.,Wuhan 430030;School of Civil and Hydraulic Engineering,Huazhong University of Science and Technology,Wuhan 430074;School of Civil Engineering and Environment,Nanyang Polytechnic University,Singapore 639798;Civil Engineering Testing Center,Huazhong University of Science and Technology,Wuhan 430074)

机构地区：[1]武汉地铁集团有限公司,武汉430030 [2]华中科技大学土木与水利工程学院,武汉430074 [3]南洋理工大学土木工程与环境学院,新加坡639798 [4]武汉华中科大土木工程检测中心,武汉430074

出　　处：《现代隧道技术》2023年第5期48-57,共10页Modern Tunnelling Technology

基　　金：国家自然科学基金(51778262,71571078,51308240);国家重点研发计划(2016YFC0800208)。

摘　　要：为实现盾构机的姿态控制,保证隧道施工的安全和质量,提出一种将随机森林(RF)和非支配排序遗传算法-Ⅲ(NSGA-Ⅲ)相结合的混合智能框架。以武汉地铁为工程背景,选取17个影响因素作为输入变量,通过RF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作为NSGA-Ⅲ的适应度函数,然后通过RF算法确定关键影响因素。以盾构姿态参数绝对值最小化为目标,建立RF-NSGA-Ⅲ多目标智能优化模型,基于所提出的优化原则进行案例研究,以测试所提方法的适用性和有效性。结果表明,通过RF算法对工程实测数据进行训练模拟,得到的预测模型的精度较高;通过研发的RF-NSGA-Ⅲ智能算法,对盾构姿态的优化控制效果显著。In order to realize attitude control of the shield tunnelling machine and ensure safety and quality of tunnel construction,in this study,a hybrid intelligent framework incorporating random forest(RF)and non-dominant sorting genetic algorithm-Ⅲ(NSGA-Ⅲ)is proposed.Based on the Wuhan Metro project,17 influencing factors are selected as input variables,and the nonlinear mapping function relationship between input parameters and shield attitude is established by the RF algorithm,which is used as the fitness function of NSGA-Ⅲ,and then the key influencing factors are determined by the RF algorithm.A multi-objective intelligent optimization model of RF-NSGA-Ⅲis established to minimize the absolute value of shield attitude parameter.Based on the proposed optimization princi⁃ple,case study is conducted to test the applicability and effectiveness of the proposed method.The results show that the prediction model obtained by training and simulating measured engineering data using the RF algorithm has high accuracy.With the developed RF-NSGA-Ⅲintelligent algorithm,a remarkable optimization and control effect of shield attitude is obtained.

关 键 词：盾构 姿态控制 关键影响因素 RF-NSGA-Ⅲ 多目标优化 

分 类 号：U455.43[建筑科学—桥梁与隧道工程]