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 tunnel squeezing using support vector machine optimized by whale optimization algorithm

J Zhou, S Zhu, Y Qiu, DJ Armaghani, A Zhou, W Yong - Acta Geotechnica, 2022 - Springer
The squeezing behavior of surrounding rock can be described as the time-dependent large
deformation during tunnel excavation, which appears in special geological conditions, such …

[HTML][HTML] Identification of digital technologies and digitalisation trends in the mining industry

L Barnewold, BG Lottermoser - International journal of mining science and …, 2020 - Elsevier
Digitalisation in mining refers to the use of computerised or digital devices or systems and
digitised data that are to reduce costs, improve business productivity, and transform mining …

[HTML][HTML] Prediction of blasting mean fragment size using support vector regression combined with five optimization algorithms

E Li, F Yang, M Ren, X Zhang, J Zhou… - Journal of Rock …, 2021 - Elsevier
The main purpose of blasting operation is to produce desired and optimum mean size rock
fragments. Smaller or fine fragments cause the loss of ore during loading and transportation …

A hybrid metaheuristic approach using random forest and particle swarm optimization to study and evaluate backbreak in open-pit blasting

Y Dai, M Khandelwal, Y Qiu, J Zhou, M Monjezi… - Neural Computing and …, 2022 - Springer
Backbreak is a rock fracture problem that exceeds the limits of the last row of holes in an
explosion operation. Excessive backbreak increases operational costs and also poses a …

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 …

Six novel hybrid extreme learning machine–swarm intelligence optimization (ELM–SIO) models for predicting backbreak in open-pit blasting

C Li, J Zhou, M Khandelwal, X Zhang… - Natural Resources …, 2022 - Springer
Backbreak (BB) is one of the serious adverse blasting consequences in open-pit mines,
because it frequently reduces economic benefits and seriously affects the safety of mines …

A comparative study of artificial neural networks in predicting blast-induced air-blast overpressure at Deo Nai open-pit coal mine, Vietnam

H Nguyen, XN Bui, HB Bui, NL Mai - Neural Computing and Applications, 2020 - Springer
Air-blast overpressure (AOp) is one of the undesirable effects caused by blasting operations
in open-pit mines. This side effect of blasting can seriously undermine surrounding …

COSMA-RF: New intelligent model based on chaos optimized slime mould algorithm and random forest for estimating the peak cutting force of conical picks

J Zhou, Y Dai, K Du, M Khandelwal, C Li… - Transportation Geotechnics, 2022 - Elsevier
Since conical pick cutting is a complex process of multi-factor coupling effects, theoretical
model construction for cutting force prediction is a quite difficult task. In this paper, various …