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 …
35 Years of (AI) in geotechnical engineering: state of the art
AM Ebid - Geotechnical and Geological Engineering, 2021 - Springer
It was 35 years ago since the first usage of Artificial Intelligence (AI) technique in
geotechnical engineering, during those years many (AI) techniques were developed based …
geotechnical engineering, during those years many (AI) techniques were developed based …
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 …
[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 …
Hybridization of metaheuristic algorithms with adaptive neuro-fuzzy inference system to predict load-slip behavior of angle shear connectors at elevated temperatures
Abstract Steel-Concrete Composite floor systems are one of the essential components in the
construction industry. Recent studies have shown that fire-induced problems damage shear …
construction industry. Recent studies have shown that fire-induced problems damage shear …
[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 …
Supervised machine learning techniques to the prediction of tunnel boring machine penetration rate
Predicting the penetration rate is a complex and challenging task due to the interaction
between the tunnel boring machine (TBM) and the rock mass. Many studies highlight the …
between the tunnel boring machine (TBM) and the rock mass. Many studies highlight the …
Development of neuro-fuzzy and neuro-bee predictive models for prediction of the safety factor of eco-protection slopes
This study is aimed to investigate the surface eco-protection techniques for cohesive soil
slopes along the selected Guthrie Corridor Expressway (GCE) stretch by way of analyzing a …
slopes along the selected Guthrie Corridor Expressway (GCE) stretch by way of analyzing a …
A multi-channel decoupled deep neural network for tunnel boring machine torque and thrust prediction
Accurate prediction of thrust and torque plays a crucial role in the control parameters
optimization and intelligent tunneling of tunnel boring machines (TBMs). Currently …
optimization and intelligent tunneling of tunnel boring machines (TBMs). Currently …