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] 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 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 …

Blasting-induced flyrock and ground vibration prediction through an expert artificial neural network based on particle swarm optimization

DJ Armaghani, M Hajihassani, ET Mohamad… - Arabian Journal of …, 2014 - Springer
Blasting is a major component of the construction and mining industries in terms of rock
fragmentation and concrete demolition. Blast designers are constantly concerned about …

Deep neural network and whale optimization algorithm to assess flyrock induced by blasting

H Guo, J Zhou, M Koopialipoor… - Engineering with …, 2021 - Springer
A wide variety of artificial intelligence methods have been utilized in the prediction of flyrock
induced by blasting. This study focuses on developing a model based on deep neural …

[HTML][HTML] Prediction of flyrock distance induced by mine blasting using a novel Harris Hawks optimization-based multi-layer perceptron neural network

BR Murlidhar, H Nguyen, J Rostami, XN Bui… - Journal of Rock …, 2021 - Elsevier
In mining or construction projects, for exploitation of hard rock with high strength properties,
blasting is frequently applied to breaking or moving them using high explosive energy …

Three hybrid intelligent models in estimating flyrock distance resulting from blasting

M Koopialipoor, A Fallah, DJ Armaghani, A Azizi… - Engineering with …, 2019 - Springer
Flyrock is an adverse effect produced by blasting in open-pit mines and tunnelling projects.
So, it seems that the precise estimation of flyrock is essential in minimizing environmental …

Artificial intelligence, machine learning and process automation: Existing knowledge frontier and way forward for mining sector

D Ali, S Frimpong - Artificial Intelligence Review, 2020 - Springer
Abstract Machine learning and artificial intelligence are the two fields of computer science
dealing with the innovative idea of inducing smartness and intelligence in machines and …

Airblast prediction through a hybrid genetic algorithm-ANN model

D Jahed Armaghani, M Hasanipanah… - Neural Computing and …, 2018 - Springer
Air overpressure is one of the most undesirable destructive effects induced by blasting
operation. Hence, a precise prediction of AOp has vital importance to minimize or reduce the …