State-of-the-art review of geotechnical-driven artificial intelligence techniques in underground soil-structure interaction
There has been an increasing demand for underground construction due to urbanization
and limited land in metropolitan cities in the recent years. However, the behavior of …
and limited land in metropolitan cities in the recent years. However, the behavior 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 …
Introducing stacking machine learning approaches for the prediction of rock deformation
Accurate and reliable predictions of rock deformations are crucial in many rock-based
projects in civil and mining engineering. In this research, a new system for the prediction of …
projects in civil and mining engineering. In this research, a new system for the prediction of …
Development of hybrid intelligent models for predicting TBM penetration rate in hard rock condition
DJ Armaghani, ET Mohamad… - … and Underground Space …, 2017 - Elsevier
The aim of this research is to develop new intelligent prediction models for estimating the
tunnel boring machine performance (TBM) by means of the rate pf penetration (PR). To …
tunnel boring machine performance (TBM) by means of the rate pf penetration (PR). To …
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 …
Prediction of seismic slope stability through combination of particle swarm optimization and neural network
B Gordan, D Jahed Armaghani, M Hajihassani… - Engineering with …, 2016 - Springer
One of the main concerns in geotechnical engineering is slope stability prediction during the
earthquake. In this study, two intelligent systems namely artificial neural network (ANN) and …
earthquake. In this study, two intelligent systems namely artificial neural network (ANN) and …
Artificial intelligence forecasting models of uniaxial compressive strength
The uniaxial compressive strength (UCS) is a vital rock geomechanical parameter widely
used in rock engineering projects such as tunnels, dams, and rock slope stability. Since the …
used in rock engineering projects such as tunnels, dams, and rock slope stability. Since the …
Gaussian process regression technique to estimate the pile bearing capacity
A commonly-encountered problem in foundation design is the reliable prediction of the pile
bearing capacity (PBC). This study is planned to propose a feasible soft computing …
bearing capacity (PBC). This study is planned to propose a feasible soft computing …
Predicting tunnel boring machine performance through a new model based on the group method of data handling
M Koopialipoor, SS Nikouei, A Marto… - Bulletin of Engineering …, 2019 - Springer
The tunnel boring machine (TBM), developed within the past few decades, is designed to
make the process of tunnel excavation safer and more economical. The use of TBMs in civil …
make the process of tunnel excavation safer and more economical. The use of TBMs in civil …
Application of deep neural networks in predicting the penetration rate of tunnel boring machines
M Koopialipoor, H Tootoonchi… - Bulletin of Engineering …, 2019 - Springer
Performance prediction in mechanized tunnel projects utilizing a tunnel boring machine
(TBM) is a prerequisite to accurate and reliable cost estimation and project scheduling. A …
(TBM) is a prerequisite to accurate and reliable cost estimation and project scheduling. A …