[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 …

Advances in blast-induced impact prediction—A review of machine learning applications

NK Dumakor-Dupey, S Arya, A Jha - Minerals, 2021 - mdpi.com
Rock fragmentation in mining and construction industries is widely achieved using drilling
and blasting technique. The technique remains the most effective and efficient means of …

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 …

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 …

Prediction and optimization of back-break and rock fragmentation using an artificial neural network and a bee colony algorithm

E Ebrahimi, M Monjezi, MR Khalesi… - Bulletin of Engineering …, 2016 - Springer
In blasting works, the aim is to provide proper rock fragmentation and to avoid undesirable
environmental impacts such as back-break. Therefore, predicting fragmentation and back …

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 …

Mine-to-crusher policy: Planning of mine blasting patterns for environmentally friendly and optimum fragmentation using Monte Carlo simulation-based multi-objective …

S Hosseini, A Mousavi, M Monjezi, M Khandelwal - Resources Policy, 2022 - Elsevier
The quality of rock fragmentation intensively affects downstream operations and operational
costs. Besides, Environmental side effects are inevitable due to mine blasting despite …

[PDF][PDF] Prediction of flyrock and backbreak in open pit blasting operation: a neuro-genetic approach.

M Monjezi, H Amini Khoshalan… - Arabian Journal of …, 2012 - academia.edu
An ideally performed blasting operation enormously influences the mining overall cost. This
aim can be achieved by proper prediction and attenuation of flyrock and backbreak. Poor …

Novel approach to predicting blast-induced ground vibration using Gaussian process regression

CK Arthur, VA Temeng, YY Ziggah - Engineering with Computers, 2020 - Springer
An attempt has been made to propose a novel prediction model based on the Gaussian
process regression (GPR) approach. The proposed GPR was used to predict blast-induced …

Developing a least squares support vector machine for estimating the blast-induced flyrock

HN Rad, M Hasanipanah, M Rezaei… - Engineering with …, 2018 - Springer
In blasting operations, the main purpose is to provide appropriate rock fragmentation and to
avoid adverse effects such as flyrock and vibration. This paper presents the applicability of …