Article(id=1282032687389062043, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282032292440805784, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2025.09.1527, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1744041600000, receivedDateStr=2025-04-08, revisedDate=1751212800000, revisedDateStr=2025-06-30, acceptedDate=null, acceptedDateStr=null, onlineDate=1783590011688, onlineDateStr=2026-07-09, pubDate=1758988800000, pubDateStr=2025-09-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783590011688, onlineIssueDateStr=2026-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783590011688, creator=13701087609, updateTime=1783590011688, updator=13701087609, issue=Issue{id=1282032292440805784, tenantId=1146029695717560320, journalId=1146031787341344770, year='2025', volume='35', issue='9', pageStart='1', pageEnd='268', issueExtLink='null', onlineDate='null', pubDate='1758988800000', pubDateStr='2025-09-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783589917526, creator='13701087609', updateTime=1783593837820, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282048735404344166, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282032292440805784, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282048735404344167, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282032292440805784, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=193, endPage=201, ext={EN=ArticleExt(id=1282032691520451485, articleId=1282032687389062043, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Decision-support model for safety evaluation of existing civil buildings and its application, columnId=1149733269173878863, journalTitle=China Safety Science Journal, columnName=Safety engineering technology, runingTitle=null, highlight=null, articleAbstract=

To improve the efficiency of safety inspections for existing civil buildings, this study develops a decision-support model for safety evaluation of existing civil buildings based on ML techniques. Building safety feature data were first collected from building evaluation reports. Then, a multi-dimensional indicator system integrating "design-evolution-status" features was established through correlation analysis and recursive feature elimination with cross-validation. Subsequently, five ML models were built and evaluated using performance metrics such as accuracy, precision, and recall. Furthermore, a decision-support platform for safety evaluation of existing civil buildings was developed and validated through a real engineering project to examine its practical operability. The results demonstrate that, compared to design features, evolution and status features more effectively reflect the actual safety conditions of civil buildings. In particular, building age, renovation or extension history, and concrete beam load capacity are identified as key features. Among the tested models, the Decision Tree algorithm shows the best performance in evaluating the safety of enclosure system, superstructure, foundation, and individual evaluation unit.

, authors=Mengfan DAI¹, Lingzhi LI^{**, 1}, Yuxin QIAN², Jingfeng YUAN³, Xiaojian HAN¹, Changhao ZHAO¹, authorsList=Mengfan DAI, Lingzhi LI, Yuxin QIAN, Jingfeng YUAN, Xiaojian HAN, Changhao ZHAO, authorCompany=null, correspAuthors=Lingzhi LI, 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=1282032701028938656, articleId=1282032687389062043, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=既有民用建筑安全鉴定辅助决策模型及应用, columnId=1149733269727526997, journalTitle=中国安全科学学报, columnName=安全工程技术, runingTitle=null, highlight=null, articleAbstract=

为提升建筑安全体检工作效率，基于机器学习（ML）算法，构建既有民用建筑安全鉴定辅助决策模型。首先，从房屋鉴定报告中收集建筑结构安全特征数据；其次，采用相关性分析和交叉验证递归特征消除法构建包含“设计-演变-状态”多维特征的建筑安全鉴定辅助决策指标体系；再次，构建5种ML模型，根据准确率、精确率、召回率等指标测试模型性能；最后，开发既有民用建筑安全鉴定辅助决策平台，以实际工程验证其可操作性。结果表明：相较于设计特征，演变和状态特征更能反映民用建筑的实际安全状况，其中，建筑年龄、有无改扩建和混凝土梁承载能力是关键特征；决策树在围护系统、上部承重结构、地基基础及鉴定单元安全性评估中表现最佳。

, authors=戴梦璠¹, 李灵芝副教授^{**, 1}, 钱宇昕², 袁竞峰教授³, 韩晓健教授¹, 赵昌皓¹, authorsList=戴梦璠, 李灵芝副教授, 钱宇昕, 袁竞峰教授, 韩晓健教授, 赵昌皓, authorCompany=null, correspAuthors=李灵芝副教授, authorNote=, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=cHzeqNWg6eKT/8d6DxIsrg==, magXml=Ut/oZrrLrI7dPRHm0ZZSqQ==, pdfUrl=null, pdf=IO4O299xchM+VIxEBo+zgg==, pdfFileSize=2457585, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=EZBTwOjR5o+5CsSnjEaUAg==, mapNumber=null, fund=null)}, authors=[Author(id=1282032709967000493, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282032687389062043, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=dmfw2000@163.com, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1282032710789084079, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282032687389062043, authorId=1282032709967000493, language=EN, stringName=Mengfan DAI, firstName=Mengfan, middleName=null, lastName=DAI, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=¹College of Civil Engineering, Nanjing Tech University, Nanjing Jiangsu 211816, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1282032714157110193, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282032687389062043, authorId=1282032709967000493, language=CN, stringName=戴梦璠, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=¹南京工业大学 土木工程学院，江苏 南京 211816, bio={"content":"

戴梦璠（2000—），女，江苏徐州人，硕士研究生，主要研究方向为数据挖掘、既有建筑安全评估、城市更新。E-mail:dmfw2000@163.com。

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戴梦璠（2000—），女，江苏徐州人，硕士研究生，主要研究方向为数据挖掘、既有建筑安全评估、城市更新。E-mail:dmfw2000@163.com。

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