An overview of opportunities for machine learning methods in underground rock engineering design

J Morgenroth, UT Khan, MA Perras - Geosciences, 2019 - mdpi.com
Machine learning methods for data processing are gaining momentum in many geoscience
industries. This includes the mining industry, where machine learning is primarily being …

[HTML][HTML] 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) …

[HTML][HTML] Developing an XGBoost model to predict blast-induced peak particle velocity in an open-pit mine: a case study

H Nguyen, XN Bui, HB Bui, DT Cuong - Acta Geophysica, 2019 - Springer
Ground vibration is one of the most undesirable effects induced by blasting operations in
open-pit mines, and it can cause damage to surrounding structures. Therefore, predicting …

[HTML][HTML] Prediction of blast-induced air over-pressure in open-pit mine: assessment of different artificial intelligence techniques

XN Bui, H Nguyen, HA Le, HB Bui, NH Do - Natural Resources Research, 2020 - Springer
Air over-pressure (AOp) is one of the products of blasting operations for rock fragmentation
in open-pit mines. It can cause structural vibration, smash glass doors, adversely affect the …

Prediction of rockburst classification using Random Forest

L Dong, X Li, P Kang - Transactions of Nonferrous Metals Society of China, 2013 - Elsevier
Abstract The method of Random Forest (RF) was used to classify whether rockburst will
happen and the intensity of rockburst in the underground rock projects. Some main control …

XG boost algorithm to simultaneous prediction of rock fragmentation and induced ground vibration using unique blast data

NS Chandrahas, BS Choudhary, MV Teja… - Applied Sciences, 2022 - mdpi.com
The two most frequently heard terms in the mining industry are safety and production. These
two terms put a lot of pressure on blasting engineers and crew to give more while …

Automatic selection of molecular descriptors using random forest: Application to drug discovery

G Cano, J Garcia-Rodriguez, A Garcia-Garcia… - Expert Systems with …, 2017 - Elsevier
The optimal selection of chemical features (molecular descriptors) is an essential pre-
processing step for the efficient application of computational intelligence techniques in …

Effective assessment of blast-induced ground vibration using an optimized random forest model based on a Harris hawks optimization algorithm

Z Yu, X Shi, J Zhou, X Chen, X Qiu - Applied Sciences, 2020 - mdpi.com
Most mines choose the drilling and blasting method which has the characteristics of being a
cheap and efficient method to fragment rock mass, but blast-induced ground vibration …

[HTML][HTML] Prediction of blast-induced rock movement during bench blasting: use of gray wolf optimizer and support vector regression

Z Yu, X Shi, J Zhou, X Chen, X Miao, B Teng… - Natural Resources …, 2020 - Springer
A large ore loss and dilution can be expected when using a pre-blast ore boundary for
shovel guidance because of the movement and re-distribution of ore in the muck pile under …

Advanced analytics for rock blasting and explosives engineering in mining

JLV Mariz, A Soofastaei - … Leverage Advanced Analytics in Mining Industry …, 2022 - Springer
Blasting is a fundamental operation in the mining of metal and non-metal mine sites. There
is a historical story of using explosive material in both underground and surface mines sites …