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Development of Ground Movements Due to a Shield Tunnelling Prediction Model Using Random Forests

机译:使用随机林的盾构隧道预测模型导致地面运动的发展

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In order to predict the exact amount of maximum surface settlement value, this paper presents a method to predict ground movement above tunnels with random forests (RF). Surface settlement above a tunnel due to a tunnel construction is predicted with the help of input variables that have direct physical significance. The RF- based model is developed by free R programs, trained and tested with parameters obtained from the detailed investigation of different tunnel projects published in literature. The maximum settlement is taken as a function of tunnel diameter, depth to the tunnel axis, cohesion, internal friction angle, compressibility modulus of soil, grouting pressure, percent tail voild grout filling, thrust force and advance rate for shield tunneling. A repeated 5-fold cross-validation procedure (10 repeats) is implemented to determine the optimal parameter values during modeling and an external testing set is employed to validate the prediction performance of models. Two performance measures namely R2 and RMSE have been employed. The RF demonstrated a promising result and predicted the desired goal fairly successfully.
机译:为了预测最大表面沉降值的确切量,本文提出了一种预测随机森林(RF)上方隧道地面运动的方法。借助具有直接物理意义的输入变量,预测了由于隧道构造而上方的隧道表面沉降。基于RF的模型由Free R程序开发,培训和测试,并使用从文献中发表的不同隧道项目的详细调查获得的参数进行了测试。最大沉降作为隧道直径的函数,深度到隧道轴,内聚力,内部摩擦角,土壤压缩模量,灌浆压力,尾部瓦氏灌浆填充,推力和盾构隧道的推进率。实现了重复的5倍交叉验证过程(10重复)以确定建模期间的最佳参数值,并且采用外部测试集来验证模型的预测性能。已经采用了两项性能措施即R2和RMSE。 RF证明了有希望的结果,并相当成功地预测了所需的目标。

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