Application of artificial intelligence in geotechnical engineering: A state-of-the-art review

A Baghbani, T Choudhury, S Costa, J Reiner - Earth-Science Reviews, 2022 - Elsevier
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 …

[HTML][HTML] State-of-the-art review of soft computing applications in underground excavations

W Zhang, R Zhang, C Wu, ATC Goh, S Lacasse… - Geoscience …, 2020 - Elsevier
Soft computing techniques are becoming even more popular and particularly amenable to
model the complex behaviors of most geotechnical engineering systems since they have …

A novel hybrid extreme learning machine–grey wolf optimizer (ELM-GWO) model to predict compressive strength of concrete with partial replacements for cement

M Shariati, MS Mafipour, B Ghahremani… - Engineering with …, 2022 - Springer
Compressive strength of concrete is one of the most determinant parameters in the design of
engineering structures. This parameter is generally determined by conducting several tests …

A novel approach to predict shear strength of tilted angle connectors using artificial intelligence techniques

M Shariati, MS Mafipour, P Mehrabi, A Shariati… - Engineering with …, 2021 - Springer
Shear connectors play a prominent role in the design of steel-concrete composite systems.
The behavior of shear connectors is generally determined through conducting push-out …

Flash-flood susceptibility assessment using multi-criteria decision making and machine learning supported by remote sensing and GIS techniques

R Costache, QB Pham, E Sharifi, NTT Linh, SI Abba… - Remote Sensing, 2019 - mdpi.com
Concerning the significant increase in the negative effects of flash-floods worldwide, the
main goal of this research is to evaluate the power of the Analytical Hierarchy Process …

[HTML][HTML] Application of artificial intelligence to rock mechanics: An overview

AI Lawal, S Kwon - Journal of Rock Mechanics and Geotechnical …, 2021 - Elsevier
Different artificial intelligence (AI) methods have been applied to various aspects of rock
mechanics, but the fact that none of these methods have been used as a standard implies …

Predicting blast-induced air overpressure: a robust artificial intelligence system based on artificial neural networks and random forest

H Nguyen, XN Bui - Natural Resources Research, 2019 - Springer
Blasting is the most popular method for rock fragmentation in open-pit mines. However, the
side effects caused by blasting operations include ground vibration, air overpressure (AOp) …

Prediction of blast-induced ground vibration in an open-pit mine by a novel hybrid model based on clustering and artificial neural network

H Nguyen, C Drebenstedt, XN Bui, DT Bui - Natural Resources Research, 2020 - Springer
Ground vibration (PPV) is one of the hazard effects induced by blasting operations in open-
pit mines, which can affect the surrounding structures, particularly the stability of benches …

Assessment of longstanding effects of fly ash and silica fume on the compressive strength of concrete using extreme learning machine and artificial neural network

M Shariati, DJ Armaghani, M Khandelwal, J Zhou… - Journal of Advanced …, 2021 - jaec.vn
Compressive Strength (CS) is an important mechanical feature of concrete taken as an
essential factor in construction. The current study has investigated the effect of fly ash and …

Feasibility of PSO-ANN model for predicting surface settlement caused by tunneling

M Hasanipanah, M Noorian-Bidgoli… - Engineering with …, 2016 - Springer
The potential surface settlement, especially in urban areas, is one of the most hazardous
factors in subway and other infrastructure tunnel excavations. Therefore, accurate prediction …