Assessment of the ground vibration during blasting in mining projects using different computational approaches
The investigation compares the conventional, advanced machine, deep, and hybrid learning
models to introduce an optimum computational model to assess the ground vibrations …
models to introduce an optimum computational model to assess the ground vibrations …
Applications of Soft Computing Methods in Backbreak Assessment in Surface Mines: A Comprehensive Review.
M Yari, M Khandelwal, P Abbasi… - … in Engineering & …, 2024 - search.ebscohost.com
Geo-engineering problems are known for their complexity and high uncertainty levels,
requiring precise definitions, past experiences, logical reasoning, mathematical analysis …
requiring precise definitions, past experiences, logical reasoning, mathematical analysis …
A hybrid model for back-break prediction using XGBoost machine learning and metaheuristic algorithms in Chadormalu iron mine
Back-break is one of the adverse effects of blasting, which results in unstable mine walls,
high duration, falling machinery, and inappropriate fragmentation. Thus, the economic …
high duration, falling machinery, and inappropriate fragmentation. Thus, the economic …
[HTML][HTML] Indirect evaluation of the influence of rock boulders in blasting to the geohazard: Unearthing geologic insights fused with tree seed based LSTM algorithm
Effective control of blasting outcomes depends on a thorough understanding of rock geology
and the integration of geological characteristics with blast design parameters. This study …
and the integration of geological characteristics with blast design parameters. This study …
[HTML][HTML] A comprehensive survey on machine learning applications for drilling and blasting in surface mining
Drilling and blasting operations are pivotal for productivity and safety in hard rock surface
mining. These operations are restricted due to complexities such as site-specific …
mining. These operations are restricted due to complexities such as site-specific …
[HTML][HTML] Machine learning based prediction of flyrock distance in rock blasting: A safe and sustainable mining approach
Flyrock is a significant environmental and safety concern in mining and construction. It arises
from various geological and blast design factors, posing risks to workers, machinery, and …
from various geological and blast design factors, posing risks to workers, machinery, and …
Improvement of drill bit-button performance and efficiency during drilling: an application of LSTM model to Nigeria Southwest Mines
The quarry operators and managers are having a running battle in determining with
precision the rate of deterioration of the button of the drill bit as well as its consumption …
precision the rate of deterioration of the button of the drill bit as well as its consumption …
Prediction and minimization of blasting flyrock distance, using deep neural networks and gravitational search algorithm, JAYA, and multi-verse optimization algorithms
E Ghojoghi, MAE Farsangi, H Mansouri, E Rashedi - Heliyon, 2024 - cell.com
Flyrock represents a significant and fundamental challenge in surface mine blasting,
carrying inherent risks to humans and the environment. Consequently, accurate prediction …
carrying inherent risks to humans and the environment. Consequently, accurate prediction …
Foretelling the compressive strength of bamboo using machine learning techniques
Purpose The purpose of this research was to develop and evaluate a machine learning (ML)
algorithm to accurately predict bamboo compressive strength (BCS). Using a dataset of 150 …
algorithm to accurately predict bamboo compressive strength (BCS). Using a dataset of 150 …
High-Speed Motion Analysis-Based Machine Learning Models for Prediction and Simulation of Flyrock in Surface Mines
Blasting is a cost-efficient and effective technique that utilizes explosive chemical energy to
generate the necessary pressure for rock fragmentation in surface mines. However, a …
generate the necessary pressure for rock fragmentation in surface mines. However, a …