Geomechanics and Engineering

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Development of a new explicit soft computing model to predict the blast-induced ground vibration

  • Alzabeebee, Saif (Department of Roads and Transport Engineering, University of Al-Qadisiyah) ;
  • Jamei, Mehdi (Engineering Faculty, Shohadaye Hoveizeh Campus of Technology, Shahid Chamran University of Ahvaz) ;
  • Hasanipanah, Mahdi (Department of Mining Engineering, University of Kashan) ;
  • Amnieh, Hassan Bakhshandeh (School of Mining, College of Engineering, University of Tehran) ;
  • Karbasi, Masoud (Water Engineering Department, Faculty of Agriculture, University of Zanjan) ;
  • Keawsawasvong, Suraparb (Department of Civil Engineering, Thammasat School of Engineering, Thammasat University)
  • Received : 2022.04.27
  • Accepted : 2022.09.08
  • Published : 2022.09.25
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Abstract

Fragmenting the rock mass is considered as the most important work in open-pit mines. Ground vibration is the most hazardous issue of blasting which can cause critical damage to the surrounding structures. This paper focuses on developing an explicit model to predict the ground vibration through an multi objective evolutionary polynomial regression (MOGA-EPR). To this end, a database including 79 sets of data related to a quarry site in Malaysia were used. In addition, a gene expression programming (GEP) model and several empirical equations were employed to predict ground vibration, and their performances were then compared with the MOGA-EPR model using the mean absolute error (MAE), root mean square error (RMSE), mean (𝜇), standard deviation of the mean (𝜎), coefficient of determination (R2) and a20-index. Comparing the results, it was found that the MOGA-EPR model predicted the ground vibration more precisely than the GEP model and the empirical equations, where the MOGA-EPR scored lower MAE and RMSE, 𝜇 and 𝜎 closer to the optimum value, and higher R2 and a20-index. Accordingly, the proposed MOGA-EPR model can be introduced as a useful method to predict ground vibration and has the capacity to be generalized to predict other blasting effects.

Keywords

References

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