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 …
Machine learning to inform tunnelling operations: Recent advances and future trends
BB Sheil, SK Suryasentana… - Proceedings of the …, 2020 - icevirtuallibrary.com
The proliferation of data collected by modern tunnel-boring machines (TBMs) presents a
substantial opportunity for the application of machine learning (ML) to support the decision …
substantial opportunity for the application of machine learning (ML) to support the decision …
Short-term photovoltaic power forecasting based on long short term memory neural network and attention mechanism
Photovoltaic power generation forecasting is an important topic in the field of sustainable
power system design, energy conversion management, and smart grid construction …
power system design, energy conversion management, and smart grid construction …
A hybrid LSTM neural network for energy consumption forecasting of individual households
Irregular human behaviors and univariate datasets remain as two main obstacles of data-
driven energy consumption predictions for individual households. In this study, a hybrid …
driven energy consumption predictions for individual households. In this study, a hybrid …
[HTML][HTML] Comparison of machine learning methods for ground settlement prediction with different tunneling datasets
L Tang, SH Na - Journal of Rock Mechanics and Geotechnical …, 2021 - Elsevier
This study integrates different machine learning (ML) methods and 5-fold cross-validation
(CV) method to estimate the ground maximal surface settlement (MSS) induced by …
(CV) method to estimate the ground maximal surface settlement (MSS) induced by …
Multi-objective robust optimization for enhanced safety in large-diameter tunnel construction with interactive and explainable AI
Robust optimization is an ideal solution for enhancing safety in tunnel construction in the
presence of unpredictable soil conditions, especially in large-diameter tunnel construction …
presence of unpredictable soil conditions, especially in large-diameter tunnel construction …
Unsupervised learning for fault detection and diagnosis of air handling units
Supervised learning techniques have witnessed significant successes in fault detection and
diagnosis (FDD) for heating ventilation and air-conditioning (HVAC) systems. Despite the …
diagnosis (FDD) for heating ventilation and air-conditioning (HVAC) systems. Despite the …
Surface settlement prediction for urban tunneling using machine learning algorithms with Bayesian optimization
This paper describes the prediction of settlements induced by urban area tunneling using
five machine learning (ML) algorithms. The settlement database, which was collected from a …
five machine learning (ML) algorithms. The settlement database, which was collected from a …
Machine learning-based forecasting of soil settlement induced by shield tunneling construction
XW Ye, T Jin, YM Chen - Tunnelling and Underground Space Technology, 2022 - Elsevier
The subway systems have greatly released the pressure of ground traffic, but shield
construction will cause considerable disturbance to the surrounding soil. Consequently …
construction will cause considerable disturbance to the surrounding soil. Consequently …
Air quality forecasting with hybrid LSTM and extended stationary wavelet transform
Y Zeng, J Chen, N Jin, X Jin, Y Du - Building and Environment, 2022 - Elsevier
Air quality measurements and forecasting is one of the most popular research topics in the
field of sustainable intelligent environmental design, urban area development and pollution …
field of sustainable intelligent environmental design, urban area development and pollution …