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An Approach for Understanding and Promoting Coal Mine Safety by Exploring Coal Mine Risk Network

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  • Yongliang Deng
  • Liangliang Song
  • Zhipeng Zhou
  • Ping Liu

Abstract

Capturing the interrelations among risks is essential to thoroughly understand and promote coal mining safety. From this standpoint, 105 risks and 135 interrelations among risks had been identified from 126 typical accidents, which were also the foundation of constructing coal mine risk network (CMRN). Based on the complex network theory and Pajek , six parameters (i.e., network diameter, network density, average path length, degree, betweenness, and clustering coefficient) were employed to reveal the topological properties of CMRN. As indicated by the results, CMRN possesses scale-free network property because its cumulative degree distribution obeys power-law distribution. This means that CMRN is robust to random hazard and vulnerable to deliberate attack. CMRN is also a small-world network due to its relatively small average path length as well as high clustering coefficient, implying that accident propagation in CMRN is faster than regular network. Furthermore, the effect of risk control is explored. According to the result, it shows that roof collapse, fire, and gas concentration exceeding limit refer to three most valuable targets for risk control among all the risks. This study will help offer recommendations and proposals for making beforehand strategies that can restrain original risks and reduce accidents.

Suggested Citation

  • Yongliang Deng & Liangliang Song & Zhipeng Zhou & Ping Liu, 2017. "An Approach for Understanding and Promoting Coal Mine Safety by Exploring Coal Mine Risk Network," Complexity, Hindawi, vol. 2017, pages 1-17, October.
    • Handle: RePEc:hin:complx:7628569
    DOI: 10.1155/2017/7628569
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    References listed on IDEAS

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    Cited by:

    1. Chen, Fangyu & Wang, Hongwei & Xu, Gangyan & Ji, Hongchang & Ding, Shanlei & Wei, Yongchang, 2020. "Data-driven safety enhancing strategies for risk networks in construction engineering," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    2. Suo Qi & Wang Liyuan & Yao Tianzi & Wang Zihao, 2021. "Promoting Metro Operation Safety by Exploring Metro Operation Accident Network," Journal of Systems Science and Information, De Gruyter, vol. 9(4), pages 455-468, August.

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