基于随机森林的盾构掘进速率预测  

Prediction of Shield Tunneling Rate Based on Random Forest

作　　者：陈晓东 Chen Xiaodong(China Railway 16 Bureau Group Beijing Metro Engineering Construction Co.,Ltd.,Beijing 100018,China)

机构地区：[1]中铁十六局集团北京轨道交通工程建设有限公司,北京100018

出　　处：《市政技术》2021年第6期69-72,共4页Journal of Municipal Technology

摘　　要：盾构机掘进速率的预测是一个非线性和多变量的复杂问题,为解决这个问题,依托洛阳轨道交通2号线机场路站—洛阳火车站区间隧道工程,通过PCA算法筛选出提高计算效率的预测变量,然后输入预测模型,验证了随机森林模型的适用性和准确性。预测结果表明,该模型的预测精度较高,可以有效指导施工,提高掘进效率。Prediction of Shield tunneling rate is a nonlinearity and multi-variable complex problems.In order to solve this problem,based on section of Airport-Luoyang railway station of Luoyang Metro Line 2,the prediction variables which improved the calculation efficiency were chosen by PCA algorithm firstly.Then they were put into the prediction model.The applicability and accuracy of random forest model were verified.The prediction results show that the prediction accuracy is high and can effectively guide construction and improve tunneling efficiency.

关 键 词：掘进速率 预测模型 PCA 随机森林 

分 类 号：U455.43[建筑科学—桥梁与隧道工程]