Application of deep learning algorithms in geotechnical engineering: a short critical review
W Zhang, H Li, Y Li, H Liu, Y Chen, X Ding - Artificial Intelligence Review, 2021 - Springer
With the advent of big data era, deep learning (DL) has become an essential research
subject in the field of artificial intelligence (AI). DL algorithms are characterized with powerful …
subject in the field of artificial intelligence (AI). DL algorithms are characterized with powerful …
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 …
[HTML][HTML] Deep learning in the construction industry: A review of present status and future innovations
The construction industry is known to be overwhelmed with resource planning, risk
management and logistic challenges which often result in design defects, project delivery …
management and logistic challenges which often result in design defects, project delivery …
BIM, machine learning and computer vision techniques in underground construction: Current status and future perspectives
The architecture, engineering and construction (AEC) industry is experiencing a
technological revolution driven by booming digitisation and automation. Advances in …
technological revolution driven by booming digitisation and automation. Advances in …
Adaptive VMD and multi-stage stabilized transformer-based long-distance forecasting for multiple shield machine tunneling parameters
Achieving multivariate long-distance forecasting of shield machine tunneling parameters
remains a challenge due to the huge number of tunneling parameters and the complexity of …
remains a challenge due to the huge number of tunneling parameters and the complexity of …
Shield attitude prediction based on Bayesian-LGBM machine learning
Effective shield attitude control is essential for the quality and safety of shield construction.
The traditional shield attitude control method is manual control based on a driver's …
The traditional shield attitude control method is manual control based on a driver's …
Success and challenges in predicting TBM penetration rate using recurrent neural networks
Abstract Tunnel Boring Machines (TBMs) have been increasingly used in tunnelling
projects. Forecasting future TBM performance would be desirable for project time …
projects. Forecasting future TBM performance would be desirable for project time …
Deep learning technologies for shield tunneling: Challenges and opportunities
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 …
Hard-rock tunnel lithology prediction with TBM construction big data using a global-attention-mechanism-based LSTM network
The TBM-constructed rock tunnel often suffers from low comparability of efficiency between
geological condition detection and the TBM real-time operation requirements. This article …
geological condition detection and the TBM real-time operation requirements. This article …
An adaptive hierarchical decomposition-based method for multi-step cutterhead torque forecast of shield machine
Cutterhead torque is generated by interaction between geological environment and shield
machine, which is one of the main load parameters of shield machine during the tunneling …
machine, which is one of the main load parameters of shield machine during the tunneling …