<p class="Abstract" style="margin: 0cm 0cm 0pt; layout-grid-mode: char;"><span style="font-size: x-small;"><span style="font-family: Times New Roman;"><span style="mso-bidi-font-size: 9.0pt;" lang="EN-US">Social unconventional emergencies not only bring disaster to human life and living environment, but also cause losses to the country and the people. What’s more, their occurrence tends to cause series of chain reactions and inspire lots of social problems, thus likely to break the social balance, and lead to national instability and social disharmony. In this paper, “concern degree model” is introduced in the research of the evolution law of social unconventional emergencies to find the intrinsic relationship between events and phenomena, which portrays the evolution mechanism of emergencies in a more scientific way. In the assessment study of the response capability of security precaution system, based on the latest approaches of system performance assessment, combined with the concept of concern degree, the response capability of security precaution system in social unconventional emergencies is scientifically assessed. The research provides a new idea in finding the evolution law of unconventional emergencies, and makes the assessment of response capability of security system more objective and scientific. Powerful support is provided in making emergency decisions in unconventional emergencies. </span><span style="mso-fareast-language: ZH-CN; mso-bidi-font-size: 9.0pt;" lang="EN-US">A</span><span style="mso-bidi-font-size: 9.0pt;" lang="EN-US"> grey-prediction-based emergency resource allocation model is proposed according to the reality and problems of current research on emergency resource allocation and scheduling under unconventional social emergency. This model can be used to optimize the year’s total amounts of emergency resource requirements. </span></span></span></p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.