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<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">SSR</journal-id><journal-title-group><journal-title>Scientific and Social Research</journal-title></journal-title-group><issn>2661-4332</issn><eissn>2981-9946</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/ssr.v6i1.5992</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>Creating a Decision-Making Program for the Decline Period of Emergency Events</title><url>https://artdesignp.com/journal/SSR/6/1/10.26689/ssr.v6i1.5992</url><author>LiuHuajun,WangZengqiang</author><pub-date pub-type="publication-year"><year>2024</year></pub-date><volume>6</volume><issue>1</issue><history><date date-type="pub"><published-time>2024-01-20</published-time></date></history><abstract>Based on the analysis of the life cycle theory of emergencies, an emergency decision-making method basedon linguistic information and ordering organization is proposed to solve the problem of emergency plan selection duringthe decline period of emergencies. Firstly, language decision theory is introduced to determine the relative importance ofdecision members and the weight of key indicators. Secondly, the extended weighted average operator is used to aggregatethe preference information of alternative solutions and the relative importance of decision members. On this basis, theranking organization method is introduced to deal with the complex relationship between different key indicators andalternative solutions. Finally, the net flow of each alternative is ranked to determine the optimal one. The feasibility andeffectiveness of this method are verified by taking the operation recovery after a fire in a logistics park as an example.</abstract><keywords/></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>Lu Y, Gong P, Tang Y, et al., 2021, BIM-Integrated Construction Safety Risk Assessment at the Design Stage of Building Projects. Automation in Construction, 124(2): 103553.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B2" content-type="article"><label>2</label><element-citation publication-type="journal"><p>Hardison DHM, 2019, Construction Hazard Prevention Through Design: Review of Perspectives, Evidence, and Future Objective Research Agenda. Safety Science, 120: 517–526.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B3" content-type="article"><label>3</label><element-citation publication-type="journal"><p>Zhang LZN, 2019, A Quantitative Safety Regulation Compliance Level Evaluation Method. Safety Science, 112: 81–89.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B4" content-type="article"><label>4</label><element-citation publication-type="journal"><p>Golabchi A, Han SU, Abourizk S, 2018, A Simulation and Visualization-Based Framework of Labor Efficiency and Safety Analysis for Prevention Through Design and Planning. Automation in Construction, 96: 310–323.</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B5" content-type="article"><label>5</label><element-citation publication-type="journal"><p>Wang JA, Liu S, Zhang X, 2021, Application of Artificial Intelligence in University Sports Risk Recognition and Identification. Journal of Intelligent &amp; Fuzzy Systems, 40(4): 3361–3372.</p><pub-id pub-id-type="doi"/></element-citation></ref></ref-list></back></article>
