Use of Intelligent Methods to Design Effective Pattern Parameters of Mine Blasting to Minimize Flyrock Distance

This publication has 63 references indexed in Scilit:

• Application of several optimization techniques for estimating TBM advance rate in granitic rocks
  Journal of Rock Mechanics and Geotechnical Engineering, 2019
• Prediction of Blast-induced Air Over-pressure in Open-Pit Mine: Assessment of Different Artificial Intelligence Techniques
  Natural Resources Research, 2019
• Development of hybrid intelligent models for predicting TBM penetration rate in hard rock condition
  Tunnelling and Underground Space Technology, 2017
• Prediction of the durability of limestone aggregates using computational techniques
  Neural Computing and Applications, 2016
• Risk Assessment and Prediction of Flyrock Distance by Combined Multiple Regression Analysis and Monte Carlo Simulation of Quarry Blasting
  Rock Mechanics and Rock Engineering, 2016
• Prediction of blast-induced air overpressure: a hybrid AI-based predictive model
  Environmental Monitoring and Assessment, 2015
• Evaluation and prediction of flyrock resulting from blasting operations using empirical and computational methods
  Engineering with Computers, 2015
• Blasting-induced flyrock and ground vibration prediction through an expert artificial neural network based on particle swarm optimization
  Arabian Journal of Geosciences, 2013
• New approach for prediction of asphaltene precipitation due to natural depletion by using evolutionary algorithm concept
  Fuel, 2012
• Blasting injuries in surface mining with emphasis on flyrock and blast area security
  Journal of Safety Research, 2004