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 …

Soft computing applications for optimum rock fragmentation: an advanced overview

AI Lawal, B Adebayo, TB Afeni, IA Okewale… - Geotechnical and …, 2024 - Springer
Rock fragmentation is an important phenomenon in mining engineering as its outcome
determines the productivity of the entire mining process. Its imperativeness in mining …

Prediction of blast-induced ground vibration intensity in open-pit mines using unmanned aerial vehicle and a novel intelligence system

XN Bui, Y Choi, V Atrushkevich, H Nguyen… - Natural Resources …, 2020 - Springer
Predicting and reducing blast-induced ground vibrations is a common concern among
engineers and mining enterprises. Dealing with these vibrations is a challenging issue as …

Support vector regression optimized by black widow optimization algorithm combining with feature selection by MARS for mining blast vibration prediction

G Xu, X Wang - Measurement, 2023 - Elsevier
Ground vibration induced by mine blasting is the most significant adverse effect on nearby
residents and surroundings. Accurate prediction of blasting vibration using limited monitor …

Predicting the availability of continuous mining systems using LSTM neural network

M Gomilanovic, N Stanic, D Milijanovic… - Advances in …, 2022 - journals.sagepub.com
This work deals with a model development to predict the availability of continuous systems
at the open pits using the artificial neural networks. The main idea of this work is to improve …

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 …

Multi-hazard assessment and mitigation for seismically-deficient RC building frames using artificial neural network models

J Shin, DW Scott, LK Stewart, JS Jeon - Engineering Structures, 2020 - Elsevier
Non-ductile reinforced concrete building frames have seismic and blast vulnerabilities due
to inadequate reinforcement detailing resulting in premature failure. One option to mitigate …

A novel algorithm of Nested-ELM for predicting blasting vibration

H Wei, J Chen, J Zhu, X Yang, H Chu - Engineering with Computers, 2022 - Springer
The prediction model of blasting vibration has always been a hot and difficult topic because
of the very complex nonlinear relationship between the blasting vibration and its influencing …

Design of a predictive model of rock breakage by blasting using artificial neural networks

JA Rosales-Huamani, RS Perez-Alvarado… - Symmetry, 2020 - mdpi.com
Over the years, various models have been developed in the stages of the mining process
that have allowed predicting and enhancing results, but it is the breakage, the variable that …

Indirect Determination Approach of Blast‐Induced Ground Vibration Based on a Hybrid SSA‐Optimized GP‐Based Technique

Z Jiang, H Xu, H Chen, B Gao, S Jia… - Advances in Civil …, 2021 - Wiley Online Library
The accurate determination of blast‐induced ground vibration has an important significance
in protecting human activities and the surrounding environment. For evaluating the peak …