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 …
Deep learning analysis for energy consumption of shield tunneling machine drive system
Inaccurate estimation of energy from the shield driving system may result in serious energy
loss and low tunneling efficiency. A deep learning network is developed in this study to …
loss and low tunneling efficiency. A deep learning network is developed in this study to …
[HTML][HTML] Machine learning-based automatic control of tunneling posture of shield machine
For a tunnel driven by a shield machine, the posture of the driving machine is essential to
the construction quality and environmental impact. However, the machine posture is …
the construction quality and environmental impact. However, the machine posture is …
A critical evaluation of machine learning and deep learning in shield-ground interaction prediction
The interaction between a shield machine and the ground is a complicated problem
involving numerous extrinsic and intrinsic factors. Machine learning (ML) algorithms have …
involving numerous extrinsic and intrinsic factors. Machine learning (ML) algorithms have …
Data-driven multi-output prediction for TBM performance during tunnel excavation: An attention-based graph convolutional network approach
A deep learning-based multi-output prediction model is developed to better understand and
more accurately estimate tunnel boring machine (TBM) performance in each segment ring …
more accurately estimate tunnel boring machine (TBM) performance in each segment ring …
An improved moth-flame optimization algorithm for support vector machine prediction of photovoltaic power generation
GQ Lin, LL Li, ML Tseng, HM Liu, DD Yuan… - Journal of Cleaner …, 2020 - Elsevier
With the expansion of grid-connected solar power generation, the variability of photovoltaic
power generation has become increasingly pronounced. Accurate photovoltaic output …
power generation has become increasingly pronounced. Accurate photovoltaic output …
Digital twin enabled real-time advanced control of TBM operation using deep learning methods
This paper establishes a digital twin (DT) enabled model that aims to achieve real-time
monitoring and control to enhance the overall performance of tunnel boring machines (TBM) …
monitoring and control to enhance the overall performance of tunnel boring machines (TBM) …
Dynamic prediction of mechanized shield tunneling performance
Slurry pressure balance shield, a kind of tunnel boring machine, is significantly affected by
the operation parameters such as advance speed and torque. In this study, a dynamic …
the operation parameters such as advance speed and torque. In this study, a dynamic …
Identification of geological characteristics from construction parameters during shield tunnelling
This paper proposes a framework to identify geological characteristics (GC) based on
borehole data and operational data during shield tunnelling using a fuzzy C-means …
borehole data and operational data during shield tunnelling using a fuzzy C-means …
Digital twin-driven framework for TBM performance prediction, visualization, and monitoring through machine learning
The rapid development in underground infrastructure is encouraging faster and more
modern ways, such as TBM tunneling, to meet the needs of the world. However, tunneling …
modern ways, such as TBM tunneling, to meet the needs of the world. However, tunneling …