Predicting TBM penetration rate with the coupled model of partial least squares regression and deep neural network

Predicting TBM penetration rate with the coupled model of partial least squares regression and deep neural network

The scientific prediction of the TBM penetration rate is of great significance to the selection of hydraulic tunnel construction methods, construction schedule and cost estimation. In view of the high nonlinearity, fuzziness and complexity of TBM excavation process, and in order to improve the predi...

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Bibliographic Details
Main Authors: YAN Chang-bin, WANG He-jian, YANG Ji-hua, CHEN Kui, ZHOU Jian-jun, GUO Wei-xin
Format: Article
Language:English
Published: SCIENCE PRESS , 16 DONGHUANGCHENGGEN NORTH ST, BEIJING, PEOPLES R CHINA, 100717 2021-02-01
Series:Rock and Soil Mechanics
Subjects:
tunnel boring machine
penetration ratio
partial least square regression
deep neural nerwork
coupling prediction model
Online Access:http://rocksoilmech.whrsm.ac.cn/EN/10.16285/j.rsm.2020.5164

Internet

http://rocksoilmech.whrsm.ac.cn/EN/10.16285/j.rsm.2020.5164

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