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Research on public security risk assessment of emergencies based on scene coupling driven

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  • Qilei Wang

    (China People’s Police University)

Abstract

The security risk in the process of emergency occurrence and development is composed of the interaction of various risk elements, which have many distinct characteristics different from the normal. This paper constructs a public security risk prediction model adapted to scene coupling drive by combining with the risk interaction coupling characteristics of HHM-RFRM theory. The qualitative, quantitative filtering, rating and risk assessment of public security risk scenarios are carried out by using Bayesian theorem and model. Combined with the actual data of multidimensional risk scenario, the coupling relationship is effectively analyzed to realize the transition from "single risk" to "coupling risk" early warning. It is found that the method has strong consistency with the actual data, the evaluation accuracy is further improved, and it has stronger adaptability to the security risk of emergencies evolution.

Suggested Citation

  • Qilei Wang, 2022. "Research on public security risk assessment of emergencies based on scene coupling driven," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 1-10, February.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:1:d:10.1007_s13198-021-01239-z
    DOI: 10.1007/s13198-021-01239-z
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    References listed on IDEAS

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    1. Lidiya N. Aleksandrovskaya & Anna E. Ardalionova & Ljubisa Papic, 2019. "Application of probability distributions mixture of safety indicator in risk assessment problems," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(1), pages 3-11, November.
    2. Hou Qing & Xie Qingsheng & Li Shaobo, 2017. "The model of information security risk assessment based on advanced evidence theory," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(3), pages 2030-2035, November.
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