Article(id=1281683210169978961, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281683189131359212, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2025.05.1448, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1733846400000, receivedDateStr=2024-12-11, revisedDate=1739894400000, revisedDateStr=2025-02-19, acceptedDate=null, acceptedDateStr=null, onlineDate=1783506689826, onlineDateStr=2026-07-08, pubDate=1748361600000, pubDateStr=2025-05-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783506689826, onlineIssueDateStr=2026-07-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783506689826, creator=13701087609, updateTime=1783506689826, updator=13701087609, issue=Issue{id=1281683189131359212, tenantId=1146029695717560320, journalId=1146031787341344770, year='2025', volume='35', issue='5', pageStart='1', pageEnd='268', issueExtLink='null', onlineDate='null', pubDate='1748361600000', pubDateStr='2025-05-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783506684811, creator='13701087609', updateTime=1783589333681, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282029843684504545, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281683189131359212, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282029843684504546, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281683189131359212, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=255, endPage=262, ext={EN=ArticleExt(id=1281683210404859986, articleId=1281683210169978961, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Emergency response capacity assessment for urban flooding disasters based on improved DS theory and FBN, columnId=1149733268699918866, journalTitle=China Safety Science Journal, columnName=Emergency technology and management, runingTitle=null, highlight=null, articleAbstract=

In order to improve the emergency response capacity of urban flooding disasters, an emergency response capacity assessment model based on the combination of improved DS evidence theory and FBN was proposed. Firstly, from the whole process of disaster emergency management, the urban flood disaster emergency response capacity assessment index system was established and mapped into a Bayesian network (BN) model. Then, to address the problems of information uncertainty and strong subjectivity in the assessment process, the improved DS theory was introduced to determine the index weights. The expert knowledge combined with the fuzzy set was used to quantify the prior probability of the root node. The accident tree was applied to analyze the key indexes, and the Sorting center of mass method was used to assign basic event probabilities. The probability of flooding disaster risk was calculated through the BN model. Emergency response capacity assessment and reasoning analysis were carried out on the basis of the above results. Finally, take the main urban area of Zhengzhou city as an example, GeNIe4.0 software was used to generate the BN model of emergency response capacity assessment of flooding disaster, and the emergency response capacity level and sensitive indexes of flooding disaster in the city were obtained. The results show that the emergency response capacity of the main urban area of the city is good. The sensitive indicators affecting the emergency response capacity are timeliness of the emergency response, normality of the warning information release, professionalism of the emergency response and accuracy of flooding information feedback.

, authors=Donghua LIU, Ruiyang ZHANG, Li GUO, authorsList=Donghua LIU, Ruiyang ZHANG, Li GUO, authorCompany=null, correspAuthors=null, 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=1281683211306635349, articleId=1281683210169978961, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=基于改进DS理论-FBN的城市内涝灾害应急能力评估, columnId=1149733268855108116, journalTitle=中国安全科学学报, columnName=应急技术与管理, runingTitle=null, highlight=null, articleAbstract=

为提升城市内涝灾害应急能力，提出一种基于改进DS理论和模糊贝叶斯网络（FBN）结合的应急能力评估模型。首先，从灾害应急管理的全过程出发，建立城市内涝灾害应急能力评估指标体系，并映射为贝叶斯网络（BN）；然后，针对评估过程中的信息不确定性以及主观性较强等问题，引入改进DS理论确定指标权重，利用专家知识结合模糊集量化根节点的先验概率，采用事故树分析关键指标并利用排序质心法对基本事件概率赋值，通过FBN模型计算内涝灾害风险概率，在此基础上进行应急能力评估和推理分析；最后，以郑州市主城区为例，利用GeNIe4.0软件生成内涝灾害应急能力评估BN模型，并得到该市的内涝灾害应急能力等级和敏感指标。研究结果表明：该市主城区内涝灾害应急能力为良，影响应急能力的敏感指标为应急响应及时性、预警信息发布规范性、应急处置专业性和内涝信息反馈准确性。

, authors=刘冬华讲师, 张睿阳, 郭梨讲师, authorsList=刘冬华讲师, 张睿阳, 郭梨讲师, authorCompany=null, correspAuthors=null, authorNote=, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=r0Fae2EyXRtzBJTX5vdFqw==, magXml=W+2gtr5+o/CDEU4PjKXh+A==, pdfUrl=null, pdf=uaGhBqH87OXqDT6Znqu3sg==, pdfFileSize=6646115, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=6k35PfttKOFlcET/kRtCmw==, mapNumber=null, fund=null)}, authors=[Author(id=1281683213303124058, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281683210169978961, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=donghualiu@xauat.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1281683213395398748, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281683210169978961, authorId=1281683213303124058, language=EN, stringName=Donghua LIU, firstName=Donghua, middleName=null, lastName=LIU, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=School of Resources Engineering, Xi'an University of Architecture and Technology, Xi'an Shaanxi 710055, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1281683213475090525, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281683210169978961, authorId=1281683213303124058, language=CN, stringName=刘冬华讲师, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=null, address=西安建筑科技大学 资源工程学院，陕西 西安 710055, bio={"content":"

刘冬华（1982—），女，河南商丘人，博士，讲师，主要从事安全人机工程和安全管理等方面的研究。E-mail:donghualiu@xauat.edu.cn。

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刘冬华（1982—），女，河南商丘人，博士，讲师，主要从事安全人机工程和安全管理等方面的研究。E-mail:donghualiu@xauat.edu.cn。

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