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Acta Geophysica

, Volume 67, Issue 2, pp 477–490 | Cite as

Developing an XGBoost model to predict blast-induced peak particle velocity in an open-pit mine: a case study

  • Hoang NguyenEmail author
  • Xuan-Nam Bui
  • Hoang-Bac Bui
  • Dao Trong Cuong
Research Article - Solid Earth Sciences

Abstract

Ground vibration is one of the most undesirable effects induced by blasting operations in open-pit mines, and it can cause damage to surrounding structures. Therefore, predicting ground vibration is important to reduce the environmental effects of mine blasting. In this study, an eXtreme gradient boosting (XGBoost) model was developed to predict peak particle velocity (PPV) induced by blasting in Deo Nai open-pit coal mine in Vietnam. Three models, namely, support vector machine (SVM), random forest (RF), and k-nearest neighbor (KNN), were also applied for comparison with XGBoost. To employ these models, 146 datasets from 146 blasting events in Deo Nai mine were used. Performance of the predictive models was evaluated using root-mean-squared error (RMSE) and coefficient of determination (R2). The results indicated that the developed XGBoost model with RMSE = 1.554, R2 = 0.955 on training datasets, and RMSE = 1.742, R2 = 0.952 on testing datasets exhibited higher performance than the SVM, RF, and KNN models. Thus, XGBoost is a robust algorithm for building a PPV predictive model. The proposed algorithm can be applied to other open-pit coal mines with conditions similar to those in Deo Nai.

Keywords

eXtreme gradient boosting XGBoost Ground vibration Peak particle velocity 

Notes

Acknowledgements

We would like to thank the Hanoi University of Mining and Geology (HUMG), Vietnam; Ministry of Education and Training of Vietnam (MOET); The Center for Mining, Electro-Mechanical research of HUMG.

Compliance with ethical standards

Conflict of interest

On behalf of all authors, I hereby attest that no conflict of interest exists in financial relationships, intellectual property, or any point related to publishing ethics.

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Copyright information

© Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2019

Authors and Affiliations

  1. 1.Department of Surface Mining, Mining FacultyHanoi University of Mining and GeologyHanoiVietnam
  2. 2.Center for Mining, Electro-Mechanical ResearchHanoi University of Mining and GeologyHanoiVietnam
  3. 3.Faculty of Geosciences and GeoengineeringHanoi University of Mining and GeologyHanoiVietnam
  4. 4.Center for Excellence in Analysis and ExperimentHanoi University of Mining and GeologyHanoiVietnam
  5. 5.Ministry of Industry and TradeHanoiVietnam

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