State-of-the-art review of machine learning and optimization algorithms applications in environmental effects of blasting
The technological difficulties related with blasting operations have become increasingly
significant. It is crucial to give due consideration to the evaluation of rock fragmentation and …
significant. It is crucial to give due consideration to the evaluation of rock fragmentation and …
Application of reliability-based back-propagation causality-weighted neural networks to estimate air-overpressure due to mine blasting
In the present study, the air-overpressure (AOp) due to mine blasting is predicted using an
uncertainty intelligence method based on the Z-number reliability and fuzzy cognitive map …
uncertainty intelligence method based on the Z-number reliability and fuzzy cognitive map …
Prediction of blasting induced air-overpressure using a radial basis function network with an additional hidden layer
Blasting operations are the most conventional and frequently used rock breakage approach
in the field of Civil and Mining Engineering. However, the side effects induced by blasting …
in the field of Civil and Mining Engineering. However, the side effects induced by blasting …
[HTML][HTML] Forecast of airblast vibrations induced by blasting using support vector regression optimized by the grasshopper optimization (SVR-GO) technique
Air overpressure (AOp) is an undesirable environmental effect of blasting. To date, a variety
of empirical equations have been developed to forecast this phenomenon and prevent its …
of empirical equations have been developed to forecast this phenomenon and prevent its …
Potential impacts of future climate on the spatio-temporal variability of landslide susceptibility in Iran using machine learning algorithms and CMIP6 climate-change …
The objective of this research is to examine the possible impacts of climate change on
landslide susceptibility in Iran. To accomplish this, 15 independent variables including 11 …
landslide susceptibility in Iran. To accomplish this, 15 independent variables including 11 …
Advanced tree-based techniques for predicting unconfined compressive strength of rock material employing non-destructive and petrographic tests
The accurate estimation of rock strength is an essential task in almost all rock-based
projects, such as tunnelling and excavation. Numerous efforts to create indirect techniques …
projects, such as tunnelling and excavation. Numerous efforts to create indirect techniques …
[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 …
Assessing ground vibration caused by rock blasting in surface mines using machine-learning approaches: A comparison of CART, SVR and MARS
Ground vibration induced by rock blasting is an unavoidable effect that may generate severe
damages to structures and living communities. Peak particle velocity (PPV) is the key …
damages to structures and living communities. Peak particle velocity (PPV) is the key …
Machine learning-assisted prediction of the toxicity of silver nanoparticles: a meta-analysis
Silver nanoparticles are likely to be more dangerous than other forms of silver due to the
intracellular release of silver ions upon dissolution and the formation of mixed ion-containing …
intracellular release of silver ions upon dissolution and the formation of mixed ion-containing …
Predicting the Young's modulus of rock material based on petrographic and rock index tests using boosting and bagging intelligence techniques
Rock deformation is considered one of the essential rock properties used in designing and
constructing rock-based structures, such as tunnels and slopes. This study applied two well …
constructing rock-based structures, such as tunnels and slopes. This study applied two well …