Evaluation of rockburst occurrence and intensity in underground structures using decision tree approach

  • Ebrahim GhasemiEmail author
  • Hasan Gholizadeh
  • Amoussou Coffi Adoko
Original Article


Based on reported statistics, rockburst phenomenon is the main cause of many casualties and accidents occurred during the construction of deep underground structures. Therefore, its prediction in initial stages of design has a remarkable role on enhancement of safety. In this paper, two models have been developed for rockburst evaluation using the C5.0 decision tree classifier. The first model has been applied for prediction of rockburst occurrence and the second model for prediction of rockburst intensity. These models have been developed based on a database including 174 rockburst case histories. In both models, stress coefficient, rock brittleness coefficient, and the elastic strain energy index are the predictive variables. These models are easy to use and do not require extensive knowledge. Based on decision rules derived from these models, the rockburst occurrence and intensity can be evaluated easily. The results revealed that the proposed approach is a useful and robust technique for long-term prediction of rockburst.


Underground structures Rockburst Long-term prediction Decision tree C5.0 classifier 


Compliance with ethical standards

Conflict of interest

It is declared that all the authors totally agree that there is no conflict of interest on this paper.

Supplementary material

366_2018_695_MOESM1_ESM.docx (39 kb)
Supplementary material 1 (DOCX 38 KB)


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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  • Ebrahim Ghasemi
    • 1
    Email author
  • Hasan Gholizadeh
    • 1
  • Amoussou Coffi Adoko
    • 2
  1. 1.Department of Mining EngineeringIsfahan University of TechnologyIsfahanIran
  2. 2.School of Mining and GeosciencesNazarbayev UniversityAstanaKazakhstan

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