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Mine accident prediction and analysis based on multimedia big data

  • Yuan Huang
  • Qianyu Zhou
Article
  • 17 Downloads

Abstract

Coal mine disaster early warning based on multimedia big data is an effective measure to avoid accidents such as gas, water, fire and rock burst, and to reduce casualties and property losses. Through the analysis of various data of coal mine, the analysis model is established and the correlation analysis is carried out, so as to better carry out risk early warning and prediction analysis, provide early warning and prediction information for supervision and law enforcement, and improve the scientific nature of supervision and law enforcement and the ability of early warning and prediction for accident risk. Aiming at the analysis and prediction of large mine accident data, the modeling and Simulation of large mine accident data analysis and prediction based on decision tree-BP neural network are carried out. The report of coal mine gas accident is analyzed by using the method of multimedia large data mining, and the key factors of coal mine gas accident are identified. Therefore, we can focus on strengthening the monitoring of accident factors, reduce the risk of accidents from the source, and improve the safety management level of coal mines.

Keywords

Multimedia big data Decision tree Neural network Mine accident Modeling and simulation 

Notes

Acknowledgements

This research was funded by University science and technology research youth fund project of Hebei province in 2018, grant number QN2018073.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Information and Electrical EngineeringHebei University of EngineeringHandanChina
  2. 2.School of Earth Science and EngineeringHebei University of EngineeringHandanChina

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