290 / 2018-04-29 10:13:08
An empirical study of early warning model on the number of coal mine accidents in China
coal mine accidents,BN model,VAR model,early warning
Final Paper
Qing Liu / University of Science and Technology Beijing
Jian Liu / University of Science and Technology Beijing
Jinxin Gao / University of Science and Technology Beijing
jingjing Wang / University of Science and Technology Beijing
Coal mining is an important energy industry and accident prone industry. The objective of this study is to establish early warning model for coal mine accidents. According to the accident data in the recent 11 years, we can conclude that the coal mine accident data has the characteristics of large fluctuations, small sample size, small value, large numerical nonlinear characteristics. Through consulting literature, analysis and comparison, policy intervention degree(PID)、Main raw material purchase price index(RMPPI)、Employment index (EI) are selected as the auxiliary variables to construct the early warning model. VAR model is applied to determine the model structure. Results show that BN model is suitable for the prediction of the number of mine accident.
Important Date
  • Conference Date

    Oct 22

    2018

    to

    Oct 24

    2018

  • May 31 2018

    Abstract Submission Deadline

  • Jul 05 2018

    Draft paper submission deadline

  • Aug 10 2018

    Draft Paper Acceptance Notification

  • Oct 24 2018

    Registration deadline

Sponsored By
University of Science and Technology Beijing
McGill University
China University of Mining and Technology (Beijing)
Henan Polytechnic University
Notheastern University
Chongqing University
China University of Mining and Technology
Laurentian University
University of Wollongong
Liaoning Technical University
Xi’an University of Science and Technology
North China University of Technology
Jiangxi University of Science and Technology
Heilongjiang University of Science and Technology
Supported By
中国职业安全健康协会
中国安全生产科学研究院
煤炭信息研究院
中安安全工程研究院
International Journal of Mining Science and Technology
Safety Science
Contact Information