Application of artificial intelligence in geotechnical engineering: A state-of-the-art review
Geotechnical engineering deals with soils and rocks and their use in engineering
constructions. By their nature, soils and rocks exhibit complex behaviours and a high level of …
constructions. By their nature, soils and rocks exhibit complex behaviours and a high level of …
Deep learning technologies for shield tunneling: Challenges and opportunities
C Zhou, Y Gao, EJ Chen, L Ding, W Qin - Automation in Construction, 2023 - Elsevier
Shield tunneling has been prevalent in tunnel construction since its introduction into the
field. To take advantage of the massive data generated during tunneling and to assist in …
field. To take advantage of the massive data generated during tunneling and to assist in …
[Retracted] Improved Artificial Neural Network with State Order Dataset Estimation for Brain Cancer Cell Diagnosis
Brain cancer is one of the cell synthesis diseases. Brain cancer cells are analyzed for patient
diagnosis. Due to this composite cell, the conceptual classifications differ from each and …
diagnosis. Due to this composite cell, the conceptual classifications differ from each and …
Optimization of support vector machine through the use of metaheuristic algorithms in forecasting TBM advance rate
The advance rate (AR) of a tunnel boring machine (TBM) in hard rock condition is a key
parameter for the successful accomplishment of a tunneling project, and the proper and …
parameter for the successful accomplishment of a tunneling project, and the proper and …
Automated recognition model of geomechanical information based on operational data of tunneling boring machines
When a tunnel boring machine (TBM) is applied to the tunnel constructed in the mixed-face
ground, the ground conditions ahead of tunnel face have a key impact on the operation …
ground, the ground conditions ahead of tunnel face have a key impact on the operation …
[HTML][HTML] Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques
A reliable and accurate prediction of the tunnel boring machine (TBM) performance can
assist in minimizing the relevant risks of high capital costs and in scheduling tunneling …
assist in minimizing the relevant risks of high capital costs and in scheduling tunneling …
Predictive modeling of swell-strength of expansive soils using artificial intelligence approaches: ANN, ANFIS and GEP
This study presents the development of new empirical prediction models to evaluate swell
pressure and unconfined compression strength of expansive soils (P s UCS-ES) using three …
pressure and unconfined compression strength of expansive soils (P s UCS-ES) using three …
A new hybrid grey wolf optimizer-feature weighted-multiple kernel-support vector regression technique to predict TBM performance
Full-face tunnel boring machine (TBM) is a modern and efficient tunnel construction
equipment. A reliable and accurate TBM performance (like penetration rate, PR) prediction …
equipment. A reliable and accurate TBM performance (like penetration rate, PR) prediction …
[HTML][HTML] Estimation of the TBM advance rate under hard rock conditions using XGBoost and Bayesian optimization
The advance rate (AR) of a tunnel boring machine (TBM) under hard rock conditions is a key
parameter in the successful implementation of tunneling engineering. In this study, we …
parameter in the successful implementation of tunneling engineering. In this study, we …
Forecasting tunnel boring machine penetration rate using LSTM deep neural network optimized by grey wolf optimization algorithm
Achieving an accurate and reliable estimation of tunnel boring machine (TBM) performance
can diminish the hazards related to extreme capital costs and planning tunnel construction …
can diminish the hazards related to extreme capital costs and planning tunnel construction …