Evaluation of rock burst intensity based on annular grey target decision-making model with variable weight

  • Xinlong Zhou
  • Guang ZhangEmail author
  • Yinghua Song
  • Shaohua Hu
  • Mingze Liu
  • Junzhe Li
Original Paper


Rock burst is a dynamic and complex phenomenon caused by numerous factors in underground excavating. It is very difficult to make evaluations accurately, especially under incomplete information. In this paper, a methodology for rock burst intensity evaluation is proposed based on grey target decision-making theory and variable weight synthesis thought. Some main factors that influence rock burst intensity are systematically analyzed to establish the evaluation index system. A balance function is introduced to investigate the variability of attribute weight, and then the weights of contribution factors are determined by utilizing variable weight synthesis, in conjunction with grey entropy algorithm. With respect to incomplete information in reality, the annular grey target theory is first proposed to address risk level of rock burst. Different distribution sets of bull’s eye distance are constructed to quantitatively represent corresponding intensity degree. Eventually, the application and performance comparison are carried out to demonstrate the feasibility and precision of the proposed model. It is demonstrated that the outcomes of the proposed model completely coincide with actual states. Compared with rough set theory and Russenes criterion, the proposed model can efficiently reduce decision ambiguity and produce a distinct risk measurement. It provides a new resolution for the research of rock burst evaluation under limited data.


Rock burst Annular grey target decision-making method Variable weight Bull’s eye distance 



The authors are grateful to the anonymous referees for their helpful comments.

Funding information

This research is supported by the Fundamental Research Funds for the Central Universities under Grant No. 185208001, the National Natural Science Foundation of China under Grant No. 51609184, the National Key Research and Development Program of China under Grant No. 2016YFC0802509, and the National Key Research and Development Program of China under Grant No. 2017YFC0804600.


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Copyright information

© Saudi Society for Geosciences 2019

Authors and Affiliations

  • Xinlong Zhou
    • 1
  • Guang Zhang
    • 1
    Email author
  • Yinghua Song
    • 2
    • 3
  • Shaohua Hu
    • 1
  • Mingze Liu
    • 1
  • Junzhe Li
    • 1
  1. 1.School of Resources and Environmental EngineeringWuhan University of TechnologyWuhanChina
  2. 2.China Research Center for Emergency ManagementWuhan University of TechnologyWuhanChina
  3. 3.Hubei Collaborative Innovation Center for Early Warning and Emergency Response TechnologyWuhanChina

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