Article(id=1281685548699988900, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281685530169545672, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2025.06.1163, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1739462400000, receivedDateStr=2025-02-14, revisedDate=1744560000000, revisedDateStr=2025-04-14, acceptedDate=null, acceptedDateStr=null, onlineDate=1783507247375, onlineDateStr=2026-07-08, pubDate=1751040000000, pubDateStr=2025-06-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783507247375, onlineIssueDateStr=2026-07-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783507247375, creator=13701087609, updateTime=1783507247375, updator=13701087609, issue=Issue{id=1281685530169545672, tenantId=1146029695717560320, journalId=1146031787341344770, year='2025', volume='35', issue='6', pageStart='1', pageEnd='252', issueExtLink='null', onlineDate='null', pubDate='1751040000000', pubDateStr='2025-06-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783507242958, creator='13701087609', updateTime=1783589309504, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282029742274622413, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281685530169545672, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282029742274622414, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281685530169545672, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=165, endPage=173, ext={EN=ArticleExt(id=1281685548897121189, articleId=1281685548699988900, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Multi-agent cooperation simulation for urban flood disaster emergency rescue, columnId=1149733270084042840, journalTitle=China Safety Science Journal, columnName=Public safety, runingTitle=null, highlight=null, articleAbstract=

In order to improve the coordination performance of multi-agents in emergency rescue, the network relationship and internal correlation of four agents were sorted out for urban flood disaster events. Combined with the multi-agent theory, the multi-agent interaction and cooperation framework was built. The multi-agent cooperative simulation model for urban flood disaster emergency rescue was designed. The changes in the number of rescued victims, average rescue time and total rescue time under different disaster scenarios were studied. Results show that the extent of the disaster, the scope of search, the ability of the dominant rescuer and the number of main rescuer are important factors influencing the level of rescue collaboration. Enhancing the scope of search, improving the ability of the dominant rescuer and increasing the investment of the main rescuer contribute to the improvement of the synergistic capacity of disaster emergency response, and the proportion of those affected by disasters who are rescued rises. The robustness analysis shows that the scope of cooperation has a small effect on the number of rescued victims, and the scope of search has a significant effect on the number of rescued victims and the total rescue time. The sensitivity analysis shows that the ability of the dominant rescuer and the number of main rescuer both have a critical value. Once these the critical values are exceeded, the rescue effect will tend to be stabilized.

, authors=Qian YANG, Feiyue WANG^**, Bo MA, Jiajie LU, Zihuan WANG, authorsList=Qian YANG, Feiyue WANG, Bo MA, Jiajie LU, Zihuan WANG, authorCompany=null, correspAuthors=Feiyue WANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1281685549207499686, articleId=1281685548699988900, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=基于城市洪涝灾害应急救援的多主体协同仿真, columnId=1149733271510106222, journalTitle=中国安全科学学报, columnName=公共安全, runingTitle=null, highlight=null, articleAbstract=

为提高应急救援多主体协同绩效，针对城市洪涝灾害事件，梳理4种救援主体的网络关系和内部关联；结合多智能体理论，构建多主体交互协作框架；设计城市洪涝灾害应急救援多主体协同仿真模型，研究不同受灾情景下获救受灾者人数、平均救援时间和总救援时间的变化情况。结果表明：受灾程度、搜救范围、主导型救援主体能力值和主力型救援主体数量是影响救援协作水平的重要因素，增强主体搜救范围、提高主导型救援主体能力和加大主力型救援主体的投入有助于提升灾害应急救援的协同能力，受灾者获救比例升高。分析模型的鲁棒性和敏感性表明：合作范围对获救受灾者人数影响较小，搜救范围对获救受灾者人数和总救援时间存在显著的影响；主导型救援主体能力值和主力型救援主体数量2个参数都存在临界值，当超出临界值之后，救援效果将会趋于平稳。

, authors=杨倩, 王飞跃教授^**, 马波, 卢佳节, 王籽幻, authorsList=杨倩, 王飞跃教授, 马波, 卢佳节, 王籽幻, authorCompany=null, correspAuthors=王飞跃教授, authorNote=, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=SbWA+k+gv+Z8yia62hJkTg==, magXml=OVbWNnpvcnJ4gZFO3mHsgw==, pdfUrl=null, pdf=NDM3sKiOW2gXPDLqQIpbbg==, pdfFileSize=6991791, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=+m7TRPs1McR1X7RW7wfvUw==, mapNumber=null, fund=null)}, authors=[Author(id=1281685549534655403, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281685548699988900, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=yangqian_13@csu.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1281685549614347181, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281685548699988900, authorId=1281685549534655403, language=EN, stringName=Qian YANG, firstName=Qian, middleName=null, lastName=YANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=Institute of Disaster Prevention Science and Safety Technology, Central South University, Changsha Hunan 410075, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1281685549685650350, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281685548699988900, authorId=1281685549534655403, language=CN, stringName=杨倩, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=中南大学 防灾科学与安全技术研究所，湖南 长沙 410075, bio={"content":"

杨倩（1999—），女，贵州贵阳人，博士研究生，主要研究方向为城市公共安全、应急救援路径规划。E-mail:yangqian_13@csu.edu.cn。

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杨倩（1999—），女，贵州贵阳人，博士研究生，主要研究方向为城市公共安全、应急救援路径规划。E-mail:yangqian_13@csu.edu.cn。

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