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

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 combi...

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Autor principal: Wang, Qilei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer India 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413360/
http://dx.doi.org/10.1007/s13198-021-01239-z
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author Wang, Qilei
author_facet Wang, Qilei
author_sort Wang, Qilei
collection PubMed
description 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.
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spelling pubmed-84133602021-09-03 Research on public security risk assessment of emergencies based on scene coupling driven Wang, Qilei Int J Syst Assur Eng Manag Review Papers 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. Springer India 2021-09-03 2022 /pmc/articles/PMC8413360/ http://dx.doi.org/10.1007/s13198-021-01239-z Text en © The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Review Papers
Wang, Qilei
Research on public security risk assessment of emergencies based on scene coupling driven
title Research on public security risk assessment of emergencies based on scene coupling driven
title_full Research on public security risk assessment of emergencies based on scene coupling driven
title_fullStr Research on public security risk assessment of emergencies based on scene coupling driven
title_full_unstemmed Research on public security risk assessment of emergencies based on scene coupling driven
title_short Research on public security risk assessment of emergencies based on scene coupling driven
title_sort research on public security risk assessment of emergencies based on scene coupling driven
topic Review Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413360/
http://dx.doi.org/10.1007/s13198-021-01239-z
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