Application of artificial neural network (ANN) for prediction and optimization of blast-induced impacts

AY Al-Bakri, M Sazid - Mining, 2021 - mdpi.com
Drilling and blasting remain the preferred technique used for rock mass breaking in mining
and construction projects compared to other methods from an economic and productivity …

An uncertainty hybrid model for risk assessment and prediction of blast-induced rock mass fragmentation

S Hosseini, R Poormirzaee, M Hajihassani - International Journal of Rock …, 2022 - Elsevier
Blasting is an important mining operation that usually produce several damaging
consequences. Adverse rock fragmentation due to bench blasting is one of them. Hence …

A rock engineering systems based model to predict rock fragmentation by blasting

F Faramarzi, H Mansouri, MAE Farsangi - International Journal of Rock …, 2013 - Elsevier
A new model for prediction of rock fragmentation by blasting is presented based upon the
basic concepts of rock engineering systems (RES). The newly proposed approach involves …

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 …

Support vector machines approach to mean particle size of rock fragmentation due to bench blasting prediction

X Shi, Z Jian, B Wu, D Huang, WEI Wei - Transactions of Nonferrous Metals …, 2012 - Elsevier
Aiming at the problems of the traditional method of assessing distribution of particle size in
bench blasting, a support vector machines (SVMs) regression methodology was used to …

Rock fragmentation prediction using an artificial neural network and support vector regression hybrid approach

R Amoako, A Jha, S Zhong - Mining, 2022 - mdpi.com
While empirical rock fragmentation models are easy to parameterize for blast design, they
are usually prone to errors, resulting in less accurate fragment size prediction. Among other …

Mean particle size prediction in rock blast fragmentation using neural networks

P Kulatilake, W Qiong, T Hudaverdi, C Kuzu - Engineering Geology, 2010 - Elsevier
Multivariate analysis procedures and a neural network methodology are used to predict
mean particle size resulting from rock blast fragmentation. A blast data base developed in a …

[HTML][HTML] A new approach to represent impact of discontinuity spacing and rock mass description on the median fragment size of blasted rocks using image analysis of …

A Azizi, H Moomivand - Rock Mechanics and Rock Engineering, 2021 - Springer
Several in-situ rock mass properties and blasthole parameters can affect the rock
fragmentation. Because of the complexity of the variables affecting the fragmentation results …

Artificial neural network modeling as an approach to limestone blast production rate prediction: a comparison of PI-BANN and MVR models

BO Taiwo, G Angesom, Y Fissha, Y Kide… - Journal of Mining …, 2023 - jme.shahroodut.ac.ir
Rock blast production rate (BPR) is one of the most crucial factors in the evaluation of mine
project's performance. In order to improve the production of a limestone mine, the blast …

Application of multivariate analysis for prediction of blast-induced ground vibrations

T Hudaverdi - Soil Dynamics and Earthquake Engineering, 2012 - Elsevier
Prediction of ground vibration is of great importance in mitigation of blast-induced adverse
effects. In this research, an innovative multivariate analysis procedure for prediction of blast …