Skip to main content

Research on the Coal Mine Production Logistics Security Status Based on Key Resources Recognition

  • Conference paper
  • First Online:
Proceedings of the 21st International Conference on Industrial Engineering and Engineering Management 2014

Abstract

To identify the safety of coal mine production logistics system and point out the focus of the safety work, this paper establishes index system of resources based on analysis of coal mine production logistics system. The evaluation system can be improved by entropy weight method through identification of key resources. Finally, according to the improved evaluation system, coal mine production logistics system is evaluated through the support vector machine (SVM) classification algorithm, to distinguish system safety level and provide a reference for coal mine production logistics safety management.

Acknowledgments: This research is sponsored by National Nature Science Fund (No. 71271194) and Science & Technology Program of Zhengzhou City (141PPTGG343).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 329.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Zhang Taifa, Mu Lihua, Zhang Hongyan. Analysis and study on coal mine accidents and prevention measures [J]. China Mining Magazine2012, (03):28-31

    Google Scholar 

  2. Yang Zhihong, Shao Bin. Research on Coal Production Logistics System [J], Coal Technology, 2012, 01:271-272

    Google Scholar 

  3. F. D. Wu, N. L. Hu. Study on the model of safety evaluation in coal mine based on Fuzzy-AHP comprehensive evaluation method [J]. Proceedings -2011 International Conference on Mechatronic Science, Electric Engineering and Computer, 2011:1671-1674

    Google Scholar 

  4. Li Xinchun, Liu Quanlong. Research on the Analysis and Evaluation of Safety Input Dynamic System in Coal Mine Enterprises [J]. Science & Technology and Economy, 2014, 02:91-95

    Google Scholar 

  5. Liu Nan. Theory of technical archives information management work of coal mine safety evaluation [J]. Shaanxi Coal, 2013, 02:135-136 + 132

    Google Scholar 

  6. Li Bin, Wang Zhijun. SVM model for comprehensive evaluation of coal mine inherent safety management and its application [J]. Mining Safety & Environmental Protection, 2013, 05:117-120

    Google Scholar 

  7. Chen Kun, Xu Longjun, Yi Jun. The evaluation of coal mine enterprise safety culture based on the principle of SMART [J]. Journal of Safety and Environment, 2010, 06: 226-230

    Google Scholar 

  8. Gao Jianning, Li Chengwu. Grey entropy model applied in the evaluation of coal mine [J]. Safety in Coal Mines, 2007, 09:87-90

    Google Scholar 

  9. Yang Wei, An Mingyan, Wang Qiuju. Quantitative analysis of artificial intelligence neural networks in risk assessment of gas accidents in coal mine [J]. Opencast Mining Technology, 2007, 05:57-59

    Google Scholar 

  10. Zhao Zhongming. Evaluation of coal mine production logistics system based on evidence theory and neural network [D]. Zhengzhou University, 2010

    Google Scholar 

  11. Jiang Huiyuan, Wang Hao. Evaluation of Supply System of Inland Water Transport Based on Entropy Proportion Means [J]. Waterway Engineering, 2008, 06:1-6

    Google Scholar 

  12. Lu Min, Zhang Zhanyu. Evaluation of sustainable utilization of water resources based on SVM [J]. Hydroelectric Energy, 2005, 05:18-21 + 4

    Google Scholar 

  13. Zhang Chaoyang. Study on evaluation of product innovation ability of private enterprises and improvement measures [D]. Tianjin University, 2009

    Google Scholar 

  14. Sun Huali, Xie Jianying, Xue Yaofeng. A Customer Satisfaction Degree Evaluation Model Based on SVM in Logistics [J]. Journal of Shanghai Jiaotong University, 2006, 04: 684-688

    Google Scholar 

  15. Liang Liming, Xia Yuchen. Liver Disease Identification Based on Hybrid Kernel SVM [J]. Industrial Control Computer, 2013, 09: 97-99

    Google Scholar 

  16. Zhu Peigen, Mei Weijiang, Shi Xiufeng, Bian Jinying. Research on the method of effective power increase of the alternative fuel forecast based on LibSVM [J]. Journal of Shihezi University (Natural Science), 2012, 05:657-660

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yun-fei An .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Atlantis Press and the authors

About this paper

Cite this paper

Wang, Jf., An, Yf., Feng, Lj., Zhai, Xq. (2015). Research on the Coal Mine Production Logistics Security Status Based on Key Resources Recognition. In: Qi, E., Shen, J., Dou, R. (eds) Proceedings of the 21st International Conference on Industrial Engineering and Engineering Management 2014. Proceedings of the International Conference on Industrial Engineering and Engineering Management. Atlantis Press, Paris. https://doi.org/10.2991/978-94-6239-102-4_66

Download citation

  • DOI: https://doi.org/10.2991/978-94-6239-102-4_66

  • Published:

  • Publisher Name: Atlantis Press, Paris

  • Print ISBN: 978-94-6239-101-7

  • Online ISBN: 978-94-6239-102-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics