Article(id=1281627196582244692, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281627156769903305, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2026.01.0370, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1754841600000, receivedDateStr=2025-08-11, revisedDate=1762617600000, revisedDateStr=2025-11-09, acceptedDate=null, acceptedDateStr=null, onlineDate=1783493335146, onlineDateStr=2026-07-08, pubDate=1769529600000, pubDateStr=2026-01-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783493335146, onlineIssueDateStr=2026-07-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783493335146, creator=13701087609, updateTime=1783493335146, updator=13701087609, issue=Issue{id=1281627156769903305, tenantId=1146029695717560320, journalId=1146031787341344770, year='2026', volume='36', issue='1', pageStart='1', pageEnd='280', issueExtLink='null', onlineDate='null', pubDate='1769529600000', pubDateStr='2026-01-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783493325654, creator='13701087609', updateTime=1783588714348, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282027246013624992, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281627156769903305, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282027246013624993, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281627156769903305, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=227, endPage=233, ext={EN=ArticleExt(id=1281627196779376981, articleId=1281627196582244692, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Intelligent deductive for disaster evolution process under multi-disasters coupling, columnId=1278415493535076803, journalTitle=China Safety Science Journal, columnName=Disaster Prevention and Mitigation Technology and Engineering, runingTitle=null, highlight=null, articleAbstract=

In order to effectively predict disasters and evaluate the effectiveness of intervention measures, a multi-disaster coupling evolution intelligent deduction method was proposed. The disaster process, multi-disaster coupling, as well as the advantages and difficulties of evolutionary intelligent deduction, were discussed. The disaster evolution process was described, and an intelligent deduction method was established. Taking the mining process of an open-pit mine as an example, the proposed method was applied for analysis, and its effectiveness was verified. The results show that the multi-disaster coupling process is complex and changeable, with characteristics such as uncertainty, network structure effect and spatio-temporal distribution difference. The system fault evolution theory can provide support for the multi-disaster coupling evolution intelligent deduction from the perspectives of conceptual description, topological structure and mathematical analysis. The evolutionary intelligent deduction method is established, and its steps and mathematical model are provided. This method can qualitatively and quantitatively deduce the multi-disaster coupling evolution process, discover hidden disaster processes and generate emergent knowledge.

, authors=Shasha LI^{1, 2}, Tiejun CUI^{**, 1}, Jing ZHANG^{2, 3}, authorsList=Shasha LI, Tiejun CUI, Jing ZHANG, authorCompany=null, correspAuthors=Tiejun CUI, 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=1281627197093949782, articleId=1281627196582244692, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=多灾害耦合下灾害演化过程智能推演, columnId=1149735802885817075, journalTitle=中国安全科学学报, columnName=防灾减灾技术与工程, runingTitle=null, highlight=null, articleAbstract=

为有效预测灾害及评估干预措施效果，提出多灾害耦合演化智能推演方法，论述灾害过程与多灾害耦合、演化智能推演的优点和困难，描述灾害演化过程，提出智能推演方法，并以露天矿采掘过程为例，应用所提方法进行分析，验证其有效性。结果表明：多灾害耦合过程复杂多变，具有不确定、网络结构效应和时空分布差异等特征；系统故障演化理论能从概念描述、拓扑结构和数学分析角度为多灾害耦合演化智能推演提供支持；建立演化智能推演方法，给出步骤和数学模型，其能定性定量地推演多灾害耦合演化过程，发现隐藏灾害过程并涌现知识。

, authors=李莎莎副教授^{1, 2}, 崔铁军教授^{**, 1}, 张晶^{2, 3}, authorsList=李莎莎副教授, 崔铁军教授, 张晶, authorCompany=null, correspAuthors=崔铁军教授, authorNote=, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=gWmz0JoPr7Gqv5u6XOlrbw==, magXml=yKA/Rbm/LWR581+jagWOqg==, pdfUrl=null, pdf=Xkd8J1Cv4AJCv4YKqEhAtA==, pdfFileSize=2696908, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=1Vo3Q4MwSSmgmrzXNMLQZw==, mapNumber=null, fund=null)}, authors=[Author(id=1281627197567906145, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281627196582244692, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=lsslntu@163.com, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1281627199161741668, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281627196582244692, authorId=1281627197567906145, language=EN, stringName=Shasha LI, firstName=Shasha, middleName=null, lastName=LI, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=^{1, 2}, address=¹School of Environmental and Chemical Engineering, Shenyang Ligong University, Shenyang Liaoning 110159, China
²School of Safety Science, Tsinghua University, Beijing 100084, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1281627199258210661, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1281627196582244692, authorId=1281627197567906145, language=CN, stringName=李莎莎副教授, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=^{1, 2}, address=¹沈阳理工大学 环境与化学工程学院，辽宁 沈阳 110159
²清华大学 安全科学学院，北京 100084, bio={"content":"

李莎莎（1988—），女，辽宁盘锦人，博士，副教授，主要从事系统安全与安全管理等方面的研究。E-mail: lsslntu@163.com。

"}, bioImg=null, bioContent=

李莎莎（1988—），女，辽宁盘锦人，博士，副教授，主要从事系统安全与安全管理等方面的研究。E-mail: lsslntu@163.com。

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