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 …
Predicting ground vibration during rock blasting using relevance vector machine improved with dual kernels and metaheuristic algorithms
The ground vibration caused by rock blasting is an extremely hazardous outcome of the
blasting operation. Blasting activity has detrimental effects on both the ecology and the …
blasting operation. Blasting activity has detrimental effects on both the ecology and the …
[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 …
Explosive Utilization Efficiency Enhancement: An Application of Machine Learning for Powder Factor Prediction using Critical Rock characteristics
Maximizing the use of explosives is crucial for optimising blasting operations, significantly
influencing productivity and cost-effectiveness in mining activities. This work explores the …
influencing productivity and cost-effectiveness in mining activities. This work explores the …
Enhancing rock fragmentation assessment in mine blasting through machine learning algorithms: a practical approach
The optimization of blasting operations greatly benefits from the prediction of rock
fragmentation. The main factors that affect fragmentation are rock mass characteristics, blast …
fragmentation. The main factors that affect fragmentation are rock mass characteristics, blast …
[HTML][HTML] Data-driven machine learning approaches for simultaneous prediction of peak particle velocity and frequency induced by rock blasting in mining
The vibrations generated by rock blasting are a serious and hazardous outcome of these
activities, causing harmful effects on the surrounding environment as well as the nearby …
activities, causing harmful effects on the surrounding environment as well as the nearby …
A comprehensive study on the application of soft computing methods in predicting and evaluating rock fragmentation in an opencast mining
The prediction of rock fragmentation (Fr) is highly beneficial to the optimization of blasting
operations in the mining industry. The characteristics of the rock mass, the blast geometry …
operations in the mining industry. The characteristics of the rock mass, the blast geometry …
Optimization of an Artificial Neural Network Using Four Novel Metaheuristic Algorithms for the Prediction of Rock Fragmentation in Mine Blasting
Rock fragmentation is a critical process in mining operations, with blasting being one of the
most common and effective methods employed to achieve the desired results. The primary …
most common and effective methods employed to achieve the desired results. The primary …
Enhancing Rock Fragmentation in Mining: Leveraging Ensemble Classification Machine Learning Algorithms for Blast Toe Volume Assessment
The condition of the floor after an explosion is of utmost importance for safety, as it directly
impacts its stability. Moreover, it exerts an influence on fragmentation, hence affecting …
impacts its stability. Moreover, it exerts an influence on fragmentation, hence affecting …