Evaluation and prediction of flyrock resulting from blasting operations using empirical and computational methods View Full Text


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Article Info

DATE

2015-03-20

AUTHORS

D. Jahed Armaghani, E. Tonnizam Mohamad, M. Hajihassani, S. V. Alavi Nezhad Khalil Abad, A. Marto, M. R. Moghaddam

ABSTRACT

Mines, quarries and construction sites face environmental impacts, such as flyrock, due to blasting operations. Flyrock may cause damage to structures and injury to human. Therefore, flyrock prediction is required to determine safe blasting zone. In this regard, 232 blasting operations were investigated in five granite quarries, Malaysia. Blasting parameters comprising maximum charge per delay and powder factor were prepared to predict flyrock using empirical and intelligent methods. An empirical graph was proposed to predict flyrock distance for different powder factor values. In addition, using the same datasets, two intelligent systems, namely artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) were used to predict flyrock. Considering some model performance indices including coefficient of determination (R2), value account for and root mean squared error and also using simple ranking procedure, the best flyrock prediction models were selected. It was found that the ANFIS model can predict flyrock with higher performance capacity compared to ANN predictive model. R2 values of testing datasets are 0.925 and 0.964 for ANN and ANFIS techniques, respectively, suggesting the superiority of the ANFIS technique in predicting flyrock. More... »

PAGES

109-121

References to SciGraph publications

  • 2009-11-13. Application of soft computing to predict blast-induced ground vibration in ENGINEERING WITH COMPUTERS
  • 2010-03-10. Prediction of rock fragmentation due to blasting using artificial neural network in ENGINEERING WITH COMPUTERS
  • 2013-11-27. Blasting-induced flyrock and ground vibration prediction through an expert artificial neural network based on particle swarm optimization in ARABIAN JOURNAL OF GEOSCIENCES
  • 2014-10-18. An adaptive neuro-fuzzy inference system for predicting unconfined compressive strength and Young’s modulus: a study on Main Range granite in BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
  • 2010-08-11. Prediction of flyrock and backbreak in open pit blasting operation: a neuro-genetic approach in ARABIAN JOURNAL OF GEOSCIENCES
  • 2011-03-02. Comparative analysis of intelligent algorithms to correlate strength and petrographic properties of some schistose rocks in ENGINEERING WITH COMPUTERS
  • 2014-09-04. Ground vibration prediction in quarry blasting through an artificial neural network optimized by imperialist competitive algorithm in BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
  • 2007-12-05. Prediction of ground vibrations resulting from the blasting operations in an open-pit mine by adaptive neuro-fuzzy inference system in ENVIRONMENTAL GEOLOGY
  • 2005-06. An intelligent approach to prediction and control ground vibration in mines in GEOTECHNICAL AND GEOLOGICAL ENGINEERING
  • 2014-03-14. Flyrock in bench blasting: a comprehensive review in BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
  • 2015-02-18. Prediction of seismic slope stability through combination of particle swarm optimization and neural network in ENGINEERING WITH COMPUTERS
  • 2009-10-30. Prediction and controlling of flyrock in blasting operation using artificial neural network in ARABIAN JOURNAL OF GEOSCIENCES
  • 1993. Statistical aspects of neural networks in NETWORKS AND CHAOS — STATISTICAL AND PROBABILISTIC ASPECTS
  • 2012-04-03. Evaluation of effect of blast design parameters on flyrock using artificial neural networks in NEURAL COMPUTING AND APPLICATIONS
  • 2012-10-16. Application of artificial intelligence techniques for predicting the flyrock distance caused by blasting operation in ARABIAN JOURNAL OF GEOSCIENCES
  • 2011-05-26. Evaluation of flyrock phenomenon due to blasting operation by support vector machine in NEURAL COMPUTING AND APPLICATIONS
  • 1999-10. Studies on Flyrock at Limestone Quarries in ROCK MECHANICS AND ROCK ENGINEERING
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    URI

    http://scigraph.springernature.com/pub.10.1007/s00366-015-0402-5

    DOI

    http://dx.doi.org/10.1007/s00366-015-0402-5

    DIMENSIONS

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