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Year 2020
 
Vol 61, Issue 5, [10 - 2020]

A novel soft computing model for predicting blast - induced ground vibration in open - pit mines using gene expression programming

DOI:10.46326/JMES.KTLT2020.09

  • Affiliations:

    1 Department of Surface Mining, Mining Faculty, Hanoi University of Mining and Geology, 18 Vien st., Duc Thang ward, Bac Tu Liem dist., Hanoi, Vietnam.
    2 Center for Mining, Electro - Mechanical research, Hanoi University of Mining and Geology, 18 Vien st., Duc Thang ward, Bac Tu Liem dist., Hanoi, Vietnam3 Department of Mathematical, Basic Sciences Faculty, Hanoi University of Mining and Geology, 18 Vien st., Duc Thang ward, Bac Tu Liem dist., Hanoi, Vietnam

  • *Corresponding:
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  • Received: 25th-Aug-2020
  • Revised: 24th-Sept-2020
  • Accepted: 10th-Oct-2020
  • Online: 15th-Oct-2020
Pages: 107 - 116
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Cited by: 13

Abstract:

The efforts of this study are to develop and propose a state - of - the - art model for predicting blast - induced ground vibration in open - pit mines with high accuracy anf ability based on the gene expression programming (GEP) technique. 25 blasts were conducted in the Tan Dong Hiep quarry mines with a total of 83 blasting events that were collected for this study. The GEP method was then applied to develop a non - linear equation for predicting blast - induced ground vibration based on a variety of influential parameters. A traditional empirical equation, namely Sadovski, was also applied to compare with the proposed GEP model. The results indicated that the GEP model can predict blast - induced ground vibration in open - pit mines better than the Sadovski model with an RMSE of 0.986 and R2 of 0.867. Meanwhile, the traditional empirical model (Sadovski) only provided an accuracy with an RMSE of 1.850 và R2 of 0.767.

How to Cite
., H.Nguyen, ., N.Xuan Bui, ., H.Quang Tran and Le, G.Huong Thi 2020. A novel soft computing model for predicting blast - induced ground vibration in open - pit mines using gene expression programming (in Vietnamese). Journal of Mining and Earth Sciences. 61, 5 (Oct, 2020), 107-116. DOI:https://doi.org/10.46326/JMES.KTLT2020.09.
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