Feasibility of ICA in approximating ground vibration resulting from mine blasting View Full Text


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Article Info

DATE

2016-08-30

AUTHORS

Danial Jahed Armaghani, Mahdi Hasanipanah, Hassan Bakhshandeh Amnieh, Edy Tonnizam Mohamad

ABSTRACT

Precise prediction of blast-induced ground vibration is an essential task to reduce the environmental effects in the surface mines, civil and tunneling works. This research investigates the potential of imperialist competitive algorithm (ICA) in approximating ground vibration as a result of blasting at three quarry sites, namely Ulu Tiram, Pengerang and Masai in Malaysia. In ICA modeling, two forms of equations, namely power and quadratic, were developed. For comparison aims, several empirical models were also used. In order to develop the ICA and empirical models, maximum charge weight used per delay (W) and the distance between blasting sites and monitoring stations (D) were utilized as the independent variables, while, peak particle velocity (PPV), as a blast-induced ground vibration descriptor, was utilized as the dependent variable. Totally, 73 blasting events were monitored, and the values of W, D and PPV were carefully measured. Two statistical functions, i.e., root mean square error and coefficient of multiple determination (R2) were used to compare the performance capability of those prediction models. Simulation results show that the proposed ICA quadratic form can get more accurate predicting results than the ICA power form and empirical models. More... »

PAGES

457-465

References to SciGraph publications

  • 2016-06-17. Application of PSO to develop a powerful equation for prediction of flyrock due to blasting in NEURAL COMPUTING AND APPLICATIONS
  • 2009-11-13. Application of soft computing to predict blast-induced ground vibration in ENGINEERING WITH COMPUTERS
  • 2010-07-06. Blast-induced ground vibration prediction using support vector machine in ENGINEERING WITH COMPUTERS
  • 2015-10-31. Several non-linear models in estimating air-overpressure resulting from mine blasting in ENGINEERING WITH COMPUTERS
  • 2016-01-18. Estimation of air-overpressure produced by blasting operation through a neuro-genetic technique in ENVIRONMENTAL EARTH SCIENCES
  • 2015-06-06. Prediction of Strength Parameters of Himalayan Rocks: A Statistical and ANFIS Approach in GEOTECHNICAL AND GEOLOGICAL ENGINEERING
  • 2016-04-28. Prediction of air-overpressure caused by mine blasting using a new hybrid PSO–SVR model in ENGINEERING WITH COMPUTERS
  • 2016-06-28. Prediction of blast-produced ground vibration using particle swarm optimization 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
  • 2005-06. An intelligent approach to prediction and control ground vibration in mines in GEOTECHNICAL AND GEOLOGICAL ENGINEERING
  • 2016-06-30. Application of cuckoo search algorithm to estimate peak particle velocity in mine blasting in ENGINEERING WITH COMPUTERS
  • 2015-03-28. Prediction of Blast-Induced Flyrock in Opencast Mines Using ANN and ANFIS in GEOTECHNICAL AND GEOLOGICAL ENGINEERING
  • 2016-02-29. A new combination of artificial neural network and K-nearest neighbors models to predict blast-induced ground vibration and air-overpressure in ENGINEERING WITH COMPUTERS
  • 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
  • 2010-07-07. Intelligent systems for ground vibration measurement: a comparative study in ENGINEERING WITH COMPUTERS
  • 2012-02-12. A neuro-fuzzy approach for prediction of longitudinal wave velocity in NEURAL COMPUTING AND APPLICATIONS
  • 2012-01-22. Comparative study of cognitive systems for ground vibration measurements in NEURAL COMPUTING AND APPLICATIONS
  • 2015-03-25. Feasibility of ANFIS model for prediction of ground vibrations resulting from quarry blasting in ENVIRONMENTAL EARTH SCIENCES
  • 2013-02-07. Application of an Expert System to Predict Maximum Explosive Charge Used Per Delay in Surface Mining in ROCK MECHANICS AND ROCK ENGINEERING
  • 2010-05-01. Prediction of environmental impacts of quarry blasting operation using fuzzy logic in ENVIRONMENTAL MONITORING AND ASSESSMENT
  • 2012-04-28. A comparative study of generalized regression neural network approach and adaptive neuro-fuzzy inference systems for prediction of unconfined compressive strength of rocks in NEURAL COMPUTING AND APPLICATIONS
  • 2015-06-18. A combination of the ICA-ANN model to predict air-overpressure resulting from blasting in ENGINEERING WITH COMPUTERS
  • 2014-06-08. Environmental impact of blasting at Drenovac limestone quarry (Serbia) in ENVIRONMENTAL EARTH SCIENCES
  • 2012-02-18. Evaluation and prediction of blast-induced ground vibration at Shur River Dam, Iran, by artificial neural network in NEURAL COMPUTING AND APPLICATIONS
  • 2015-02-24. Intelligent prediction of Langmuir isotherms of Gondwana coals in India in JOURNAL OF PETROLEUM EXPLORATION AND PRODUCTION TECHNOLOGY
  • 2015-12-14. Prediction of the strength and elasticity modulus of granite through an expert artificial neural network in ARABIAN JOURNAL OF GEOSCIENCES
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    36 schema:description Precise prediction of blast-induced ground vibration is an essential task to reduce the environmental effects in the surface mines, civil and tunneling works. This research investigates the potential of imperialist competitive algorithm (ICA) in approximating ground vibration as a result of blasting at three quarry sites, namely Ulu Tiram, Pengerang and Masai in Malaysia. In ICA modeling, two forms of equations, namely power and quadratic, were developed. For comparison aims, several empirical models were also used. In order to develop the ICA and empirical models, maximum charge weight used per delay (W) and the distance between blasting sites and monitoring stations (D) were utilized as the independent variables, while, peak particle velocity (PPV), as a blast-induced ground vibration descriptor, was utilized as the dependent variable. Totally, 73 blasting events were monitored, and the values of W, D and PPV were carefully measured. Two statistical functions, i.e., root mean square error and coefficient of multiple determination (R2) were used to compare the performance capability of those prediction models. Simulation results show that the proposed ICA quadratic form can get more accurate predicting results than the ICA power form and empirical models.
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