[HTML][HTML] Real-time prediction of rock mass classification based on TBM operation big data and stacking technique of ensemble learning

S Hou, Y Liu, Q Yang - Journal of Rock Mechanics and Geotechnical …, 2022 - Elsevier
Real-time prediction of the rock mass class in front of the tunnel face is essential for the
adaptive adjustment of tunnel boring machines (TBMs). During the TBM tunnelling process …

Success and challenges in predicting TBM penetration rate using recurrent neural networks

F Shan, X He, DJ Armaghani, P Zhang… - … and underground space …, 2022 - Elsevier
Abstract Tunnel Boring Machines (TBMs) have been increasingly used in tunnelling
projects. Forecasting future TBM performance would be desirable for project time …

Prediction model of rock mass class using classification and regression tree integrated AdaBoost algorithm based on TBM driving data

Q Liu, X Wang, X Huang, X Yin - Tunnelling and Underground Space …, 2020 - Elsevier
The real-time acquisition of surrounding rock information is important for the efficient
tunneling and hazard prevention in tunnel boring machines (TBMs). This study presents an …

An optimized system of GMDH-ANFIS predictive model by ICA for estimating pile bearing capacity

DJ Armaghani, H Harandizadeh, E Momeni… - Artificial Intelligence …, 2022 - Springer
The pile bearing capacity is considered as the most essential factor in designing deep
foundations. Direct determination of this parameter in site is costly and difficult. Hence, this …

Tensile strength prediction of rock material using non-destructive tests: A comparative intelligent study

M Parsajoo, DJ Armaghani, AS Mohammed… - Transportation …, 2021 - Elsevier
Tensile strength of rock plays a significant role in the design of tunnels and underground
engineering projects. Due to the inefficiency of direct method in determining rock tensile …

[HTML][HTML] Real-time rock mass condition prediction with TBM tunneling big data using a novel rock–machine mutual feedback perception method

Z Wu, R Wei, Z Chu, Q Liu - Journal of Rock Mechanics and Geotechnical …, 2021 - Elsevier
Real-time perception of rock mass information is of great importance to efficient tunneling
and hazard prevention in tunnel boring machines (TBMs). In this study, a TBM–rock mutual …

Proposing several hybrid PSO-extreme learning machine techniques to predict TBM performance

J Zeng, B Roy, D Kumar, AS Mohammed… - Engineering with …, 2022 - Springer
A proper planning schedule for tunnel boring machine (TBM) construction is considered as a
necessary and difficult task in tunneling projects. Therefore, prediction of TBM performance …

Investigation of disc cutter wear during shield tunnelling in weathered granite: a case study

SL Shen, N Zhang, A Zhou - Tunnelling and Underground Space …, 2023 - Elsevier
Wear characteristics of disc cutter can vary significantly during shield tunnelling in different
geological formations. This paper presents a case study on disc-cutter wear experienced …

A novel combination of PCA and machine learning techniques to select the most important factors for predicting tunnel construction performance

J Wang, AS Mohammed, E Macioszek, M Ali, DV Ulrikh… - Buildings, 2022 - mdpi.com
Numerous studies have reported the effective use of artificial intelligence approaches,
particularly artificial neural networks (ANNs)-based models, to tackle tunnelling issues …

Probabilistic analysis of the disc cutter failure during TBM tunneling in hard rock

D **, D Yuan, X Li, W Su - Tunnelling and Underground Space …, 2021 - Elsevier
TBM disc cutters used in a long-distance tunneling particularly in cutting through hard rock
would undergo substantial and intense wear. The cutting efficiency may greatly reduce and …