首页 期刊 论文 学科刊群 资讯 加盟 关于
EN
image
Article(id=1156908031943467635, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156907871645556837, articleNumber=null, orderNo=null, doi=10.12404/j.issn.1671-1815.2309307, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1701014400000, receivedDateStr=2023-11-27, revisedDate=1720454400000, revisedDateStr=2024-07-09, acceptedDate=null, acceptedDateStr=null, onlineDate=1753757969126, onlineDateStr=2025-07-29, pubDate=1737993600000, pubDateStr=2025-01-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1753757969126, onlineIssueDateStr=2025-07-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1753757969126, creator=13701087609, updateTime=1753757969126, updator=13701087609, issue=Issue{id=1156907871645556837, tenantId=1146029695717560320, journalId=1146123166801305609, year='2025', volume='25', issue='3', pageStart='879', pageEnd='1312', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=0, createTime=1753757930909, creator=13701087609, updateTime=1765095544280, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1204461268821320541, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156907871645556837, language=EN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1204461268825514846, tenantId=1146029695717560320, journalId=1146123166801305609, issueId=1156907871645556837, language=CN, specialIssueTitle=, coverIllustrator=, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1245, endPage=1252, ext={EN=ArticleExt(id=1156908033126261368, articleId=1156908031943467635, tenantId=1146029695717560320, journalId=1146123166801305609, language=EN, title=Risk Assessment Model of Highway Tunnel Collapse Based on Rough Set-grid Search-support Vector Classification, columnId=1156262728772735295, journalTitle=Science Technology and Engineering, columnName=Papers·Traffics and Transportations, runingTitle=null, highlight=null, articleAbstract=

In order to reasonably and efficiently carry out the risk assessment of road tunnel construction collapse, the risk assessment model of road tunnel construction collapse was studied by rough set (RS), grid search method(GS) and support vector classification (SVC). Firstly, the index system of highway tunnel construction collapse risk evaluation was constructed by integrating advanced geological prediction. At the same time, the information of 100 tunnel collapse cases was collected and the index data was discretized. Secondly, attribute reduction was conducted based on the condition information entropy of rough set to obtain the reduced core index set. Then, grid search method was used to find the optimal parameters of the support vector classification training set, the risk assessment model of highway tunnel construction collapse based on rough set-grid search-support vector classification (RS-GS-SVC) was established. Finally, the model was used to predict the test samples. The results show that under the condition of the same learning sample, compared with rough set-genetic algorithm-support vector classification (RS-GA-SVC) model and Rough set-particle swarm optimization-support vector classification (RS-PSO-SVC) model, RS-GS-SVC model has higher classification accuracy; Under the same proportion of training set and test set, the prediction accuracy of RS-GS-SVC model is higher than that of GS-SVC model, with the accuracy rates of 93.33% and 90% respectively, and the operation time of RS-GS-SVC model is shorter. It can clearly be seen that the model complexity is effectively reduced and the classification accuracy is improved through the reduction of rough set conditional information entropy attributes.

, correspAuthors=Jia-jia ZENG, 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, authorCompany=null, fund=null, authors=null, authorsList=Bo WU, Jia-jia ZENG, Qi CAI, Ruo-nan ZHU, Cong LIU), CN=ArticleExt(id=1156908064122167963, articleId=1156908031943467635, tenantId=1146029695717560320, journalId=1146123166801305609, language=CN, title=基于粗糙集-网格搜索-支持向量的公路隧道施工坍塌风险评估模型, columnId=1156262730664366426, journalTitle=科学技术与工程, columnName=论文·交通运输, runingTitle=null, highlight=null, articleAbstract=

为合理高效地进行公路隧道施工坍塌风险评估,通过粗糙集(rough set,RS)理论、网格搜索法(grid search,GS)和支持向量机(support vector classification,SVC)研究了公路隧道施工坍塌风险评估模型。首先融合超前地质预报,构建公路隧道施工坍塌风险评价指标体系,同时收集100个隧道坍塌相关案例信息并对指标数据进行离散化处理,其次基于粗糙集条件信息熵进行属性约简,得到约简后的核指标集,而后采用网格搜索法寻找支持向量分类训练集的最优参数,建立基于粗糙集-网格搜索-支持向量(RS-GS-SVC)公路隧道施工坍塌风险评估模型,最后将所建模型用于对测试样本的预测。结果表明:在相同学习样本的条件下,相较于粗糙集-遗传-支持向量模型(RS-GA-SVC)和粗糙集-粒子群-支持向量模型(RS-PSO-SVC),RS-GS-SVC模型具有更高的分类精度;在训练集与测试集比例相同的条件下,RS-GS-SVC模型的预测准确率高于GS-SVC模型,准确率分别为93.33%和90%,且RS-GS-SVC模型的运算时间更短。可见,经粗糙集条件信息熵属性约简,可以有效降低模型复杂度,提高分类精度。

, correspAuthors=曾佳佳, authorNote=null, correspAuthorsNote=
* 曾佳佳(1991—),女,汉族,湖南邵阳人,博士研究生。研究方向:地下与隧道工程。E-mail:。
, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=N7j9nvGOrDElzbhXRivs8g==, magXml=IpS3ni62h2qyjQIidsGA+Q==, pdfUrl=null, pdf=uEar09kXsZV5Z/VZbh23RQ==, pdfFileSize=3804721, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=aXalQw+bnfGMV/HGHm5FtA==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=/GT/c6LpXJeCA+hI0ENAnA==, mapNumber=null, authorCompany=null, fund=null, authors=

吴波(1971—),男,汉族,四川阆中人,博士,教授。研究方向:地下与隧道工程。E-mail:。

, authorsList=吴波, 曾佳佳, 蔡琦, 朱若男, 刘聪)}, authors=[Author(id=1204780260744213099, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=wubo@ecut.edu.cn, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1204780260924568177, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, authorId=1204780260744213099, language=EN, stringName=Bo WU, firstName=Bo, middleName=null, lastName=WU, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1. School of Civil and Architecture Engineering, East China University of Technology, Nanchang 330000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1204780261025231479, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, authorId=1204780260744213099, language=CN, stringName=吴波, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1.东华理工大学土木与建筑工程学院, 南昌 330000, bio={"content":"

吴波(1971—),男,汉族,四川阆中人,博士,教授。研究方向:地下与隧道工程。E-mail:。

"}, bioImg=null, bioContent=

吴波(1971—),男,汉族,四川阆中人,博士,教授。研究方向:地下与隧道工程。E-mail:。

, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1204780260417057372, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, xref=null, ext=[AuthorCompanyExt(id=1204780260425445979, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, companyId=1204780260417057372, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. School of Civil and Architecture Engineering, East China University of Technology, Nanchang 330000, China), AuthorCompanyExt(id=1204780260429640284, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, companyId=1204780260417057372, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.东华理工大学土木与建筑工程学院, 南昌 330000)])]), Author(id=1204780261104923262, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=13051139728@163.com, emailSecond=null, emailThird=null, correspondingAuthor=1, authorType=1, ext={EN=AuthorExt(id=1204780261218169480, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, authorId=1204780261104923262, language=EN, stringName=Jia-jia ZENG, firstName=Jia-jia, middleName=null, lastName=ZENG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, *, address=2. School of Water Resources and Environment Engineering, East China University of Technology, Nanchang 330000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1204780261306249871, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, authorId=1204780261104923262, language=CN, stringName=曾佳佳, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, *, address=2.东华理工大学水资源与环境工程学院, 南昌 330000, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1204780260505137760, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, xref=null, ext=[AuthorCompanyExt(id=1204780260630966882, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, companyId=1204780260505137760, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2. School of Water Resources and Environment Engineering, East China University of Technology, Nanchang 330000, China), AuthorCompanyExt(id=1204780260635161186, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, companyId=1204780260505137760, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.东华理工大学水资源与环境工程学院, 南昌 330000)])]), Author(id=1204780261436273304, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, orderNo=2, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1204780261562102430, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, authorId=1204780261436273304, language=EN, stringName=Qi CAI, firstName=Qi, middleName=null, lastName=CAI, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1. School of Civil and Architecture Engineering, East China University of Technology, Nanchang 330000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1204780261645988519, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, authorId=1204780261436273304, language=CN, stringName=蔡琦, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1.东华理工大学土木与建筑工程学院, 南昌 330000, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1204780260417057372, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, xref=null, ext=[AuthorCompanyExt(id=1204780260425445979, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, companyId=1204780260417057372, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. School of Civil and Architecture Engineering, East China University of Technology, Nanchang 330000, China), AuthorCompanyExt(id=1204780260429640284, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, companyId=1204780260417057372, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.东华理工大学土木与建筑工程学院, 南昌 330000)])]), Author(id=1204780261771817646, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, orderNo=3, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1204780262996554425, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, authorId=1204780261771817646, language=EN, stringName=Ruo-nan ZHU, firstName=Ruo-nan, middleName=null, lastName=ZHU, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=2. School of Water Resources and Environment Engineering, East China University of Technology, Nanchang 330000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1204780263147549375, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, authorId=1204780261771817646, language=CN, stringName=朱若男, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=2, address=2.东华理工大学水资源与环境工程学院, 南昌 330000, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1204780260505137760, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, xref=null, ext=[AuthorCompanyExt(id=1204780260630966882, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, companyId=1204780260505137760, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2. School of Water Resources and Environment Engineering, East China University of Technology, Nanchang 330000, China), AuthorCompanyExt(id=1204780260635161186, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, companyId=1204780260505137760, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.东华理工大学水资源与环境工程学院, 南昌 330000)])]), Author(id=1204780263273378504, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, orderNo=4, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1204780263411790547, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, authorId=1204780263273378504, language=EN, stringName=Cong LIU, firstName=Cong, middleName=null, lastName=LIU, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1. School of Civil and Architecture Engineering, East China University of Technology, Nanchang 330000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1204780263529231068, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, authorId=1204780263273378504, language=CN, stringName=刘聪, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1.东华理工大学土木与建筑工程学院, 南昌 330000, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1204780260417057372, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, xref=null, ext=[AuthorCompanyExt(id=1204780260425445979, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, companyId=1204780260417057372, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. School of Civil and Architecture Engineering, East China University of Technology, Nanchang 330000, China), AuthorCompanyExt(id=1204780260429640284, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, companyId=1204780260417057372, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.东华理工大学土木与建筑工程学院, 南昌 330000)])])], keywords=[Keyword(id=1204780263705391848, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=EN, orderNo=1, keyword=highway tunnel collapse), Keyword(id=1204780263810249455, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=EN, orderNo=2, keyword=support vector classification), Keyword(id=1204780263923495675, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=EN, orderNo=3, keyword=rough set), Keyword(id=1204780264036741892, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=EN, orderNo=4, keyword=grid search method), Keyword(id=1204780264158376716, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=EN, orderNo=5, keyword=risk assessment), Keyword(id=1204780264263234324, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=CN, orderNo=1, keyword=风险评估), Keyword(id=1204780264363897627, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=CN, orderNo=2, keyword=公路隧道坍塌), Keyword(id=1204780264447783716, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=CN, orderNo=3, keyword=支持向量分类), Keyword(id=1204780264540058410, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=CN, orderNo=4, keyword=粗糙集), Keyword(id=1204780264640721710, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=CN, orderNo=5, keyword=网格搜索法)], refs=[Reference(id=1204780272156913667, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2018, volume=39, issue=10, pageStart=3703, pageEnd=3716, url=null, language=null, rfNumber=[1], rfOrder=0, authorNames=熊自明, 卢浩, 王明洋, journalName=岩土力学, refType=null, unstructuredReference=熊自明, 卢浩, 王明洋, 等. 我国大型岩土工程施工安全风险管理研究进展[J]. 岩土力学, 2018, 39 (10): 3703-3716., articleTitle=我国大型岩土工程施工安全风险管理研究进展, refAbstract=null), Reference(id=1204780272236605447, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2018, volume=39, issue=10, pageStart=3703, pageEnd=3716, url=null, language=null, rfNumber=[1], rfOrder=1, authorNames=Xiong Ziming, Lu Hao, Wang Mingyang, journalName=Rock and Soil Mechanics, refType=null, unstructuredReference=Xiong Ziming, Lu Hao, Wang Mingyang, et al. Research progress on safety risk management for large scale geotechnical engineering construction in China[J]. Rock and Soil Mechanics, 2018, 39 (10): 3703-3716., articleTitle=Research progress on safety risk management for large scale geotechnical engineering construction in China, refAbstract=null), Reference(id=1204780272328880140, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2022, volume=120, issue=null, pageStart=104262, pageEnd=null, url=null, language=null, rfNumber=[2], rfOrder=2, authorNames=Kim J, Kim C, Kim G, journalName=Tunnelling and Underground Space Technology, refType=null, unstructuredReference=Kim J, Kim C, Kim G, et al. Probabilistic tunnel collapse risk evaluation model using analytical hierarchy process (AHP) and Delphi survey technique[J]. Tunnelling and Underground Space Technology, 2022, 120: 104262., articleTitle=Probabilistic tunnel collapse risk evaluation model using analytical hierarchy process (AHP) and Delphi survey technique, refAbstract=null), Reference(id=1204780272408571922, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2022, volume=36, issue=4, pageStart=04022034, pageEnd=null, url=null, language=null, rfNumber=[3], rfOrder=3, authorNames=Ou X, Wu Y, Wu B, journalName=Journal of Performance of Constructed Facilities, refType=null, unstructuredReference=Ou X, Wu Y, Wu B, et al. Dynamic Bayesian network for predicting tunnel-collapse risk in the case of incomplete data[J]. Journal of Performance of Constructed Facilities, 2022, 36(4): 04022034., articleTitle=Dynamic Bayesian network for predicting tunnel-collapse risk in the case of incomplete data, refAbstract=null), Reference(id=1204780272484069398, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2018, volume=36, issue=3, pageStart=1621, pageEnd=1631, url=null, language=null, rfNumber=[4], rfOrder=4, authorNames=Gao C, Li S, Wang J, journalName=Geotechnical and Geological Engineering, refType=null, unstructuredReference=Gao C, Li S, Wang J, et al. The risk assessment of tunnels based on grey correlation and entropy weight method[J]. Geotechnical and Geological Engineering, 2018, 36(3): 1621-1631., articleTitle=The risk assessment of tunnels based on grey correlation and entropy weight method, refAbstract=null), Reference(id=1204780272593121305, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2022, volume=null, issue=9, pageStart=8785030, pageEnd=null, url=null, language=null, rfNumber=[5], rfOrder=5, authorNames=Li Z, Meng X, Liu D, journalName=Advances in Civil Engineering, refType=null, unstructuredReference=Li Z, Meng X, Liu D, et al. Disaster risk evaluation of superlong highways tunnel based on the cloud and AHP model[J]. Advances in Civil Engineering, 2022(9): 8785030., articleTitle=Disaster risk evaluation of superlong highways tunnel based on the cloud and AHP model, refAbstract=null), Reference(id=1204780272672813085, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2022, volume=12, issue=1, pageStart=1, pageEnd=19, url=null, language=null, rfNumber=[6], rfOrder=6, authorNames=Li L, Ni B, Zhang S, journalName=Scientific Reports, refType=null, unstructuredReference=Li L, Ni B, Zhang S, et al. Tunnel collapse risk assessment based on improved quantitative theory III and EW-AHP coupling weight[J]. Scientific Reports, 2022, 12(1): 1-19., articleTitle=Tunnel collapse risk assessment based on improved quantitative theory III and EW-AHP coupling weight, refAbstract=null), Reference(id=1204780272765087778, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2024, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[7], rfOrder=7, authorNames=叶华政, journalName=基于贝叶斯理论的山岭隧道施工坍塌风险评估及预警研究, refType=null, unstructuredReference=叶华政. 基于贝叶斯理论的山岭隧道施工坍塌风险评估及预警研究[D]. 南宁: 广西大学, 2024., articleTitle=null, refAbstract=null), Reference(id=1204780272861556772, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2024, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[7], rfOrder=8, authorNames=Ye Huazhen, journalName=Collapse risk assessment and early warning reserch for moutain tunnelling based on Bayesian theory, refType=null, unstructuredReference=Ye Huazhen. Collapse risk assessment and early warning reserch for moutain tunnelling based on Bayesian theory[D]. Nanning: Guangxi University, 2024., articleTitle=null, refAbstract=null), Reference(id=1204780272991580200, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2023, volume=21, issue=3, pageStart=209, pageEnd=215, url=null, language=null, rfNumber=[8], rfOrder=9, authorNames=张良, 孙永新, 王晓睿, journalName=水利与建筑工程学报, refType=null, unstructuredReference=张良, 孙永新, 王晓睿, 等. 基于粗糙集-遗传算法的山岭隧道坍塌易发性评价[J]. 水利与建筑工程学报, 2023, 21(3): 209-215., articleTitle=基于粗糙集-遗传算法的山岭隧道坍塌易发性评价, refAbstract=null), Reference(id=1204780273083854893, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2023, volume=21, issue=3, pageStart=209, pageEnd=215, url=null, language=null, rfNumber=[8], rfOrder=10, authorNames=Zhang Liang, Sun Yongxin, Wang Xiaorui, journalName=Journal of Water Resources and Architectural Engineering, refType=null, unstructuredReference=Zhang Liang, Sun Yongxin, Wang Xiaorui, et al. Collapse susceptibility evaluation of mountain tunnel based on rough set-genetic algorithm[J]. Journal of Water Resources and Architectural Engineering, 2023, 21(3): 209-215., articleTitle=Collapse susceptibility evaluation of mountain tunnel based on rough set-genetic algorithm, refAbstract=null), Reference(id=1204780273222266931, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2007, volume=177, issue=1, pageStart=3, pageEnd=27, url=null, language=null, rfNumber=[9], rfOrder=11, authorNames=Pawlak Z, Skowron A, journalName=Information Sciences, refType=null, unstructuredReference=Pawlak Z, Skowron A. Rudiments of rough sets[J]. Information Sciences, 2007, 177(1): 3-27., articleTitle=Rudiments of rough sets, refAbstract=null), Reference(id=1204780273327124533, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2013, volume=8, issue=10, pageStart=2632, pageEnd=2639, url=null, language=null, rfNumber=[10], rfOrder=12, authorNames=Yao Y, Liu Y, Yu Y, journalName=Journal of Computer Science and Technology, refType=null, unstructuredReference=Yao Y, Liu Y, Yu Y, et al. K-SVM: An effective SVM algorithm based on K-means clustering[J]. Journal of Computer Science and Technology, 2013, 8(10): 2632-2639., articleTitle=K-SVM: An effective SVM algorithm based on K-means clustering, refAbstract=null), Reference(id=1204780273444565049, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2017, volume=26, issue=4, pageStart=501, pageEnd=522, url=null, language=null, rfNumber=[11], rfOrder=13, authorNames=Su H, Wen Z, Sun X, journalName=International Journal of Damage Mechanics, refType=null, unstructuredReference=Su H, Wen Z, Sun X, et al. Rough set-support vector machine-based real-time monitoring model of safety status during dangerous dam reinforcement[J]. International Journal of Damage Mechanics, 2017, 26(4): 501-522., articleTitle=Rough set-support vector machine-based real-time monitoring model of safety status during dangerous dam reinforcement, refAbstract=null), Reference(id=1204780273553616956, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2019, volume=11, issue=5, pageStart=1687814019851893, pageEnd=null, url=null, language=null, rfNumber=[12], rfOrder=14, authorNames=Xi J, Guo H, Tian J, journalName=Advances in Mechanical Engineering, refType=null, unstructuredReference=Xi J, Guo H, Tian J, et al. A classification and recognition model for the severity of road traffic accident[J]. Advances in Mechanical Engineering, 2019, 11(5): 1687814019851893., articleTitle=A classification and recognition model for the severity of road traffic accident, refAbstract=null), Reference(id=1204780273713000513, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2020, volume=15, issue=4, pageStart=2445, pageEnd=2453, url=null, language=null, rfNumber=[13], rfOrder=15, authorNames=Liu H, Dong Y, Wang F, journalName=Evolutionary Intelligence, refType=null, unstructuredReference=Liu H, Dong Y, Wang F. Gas outburst prediction model using rough set and support vector machine[J]. Evolutionary Intelligence, 2020, 15(4): 2445-2453., articleTitle=Gas outburst prediction model using rough set and support vector machine, refAbstract=null), Reference(id=1204780276783231046, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=1982, volume=11, issue=1, pageStart=341, pageEnd=356, url=null, language=null, rfNumber=[14], rfOrder=16, authorNames=Pawlak Z, journalName=International Journal of Computer and Information Sciences, refType=null, unstructuredReference=Pawlak Z. Rough set[J]. International Journal of Computer and Information Sciences, 1982, 11(1): 341-356., articleTitle=Rough set, refAbstract=null), Reference(id=1204780276904865869, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2019, volume=40, issue=9, pageStart=3549, pageEnd=3558, url=null, language=null, rfNumber=[15], rfOrder=17, authorNames=陈舞, 张国华, 王浩, journalName=岩土力学, refType=null, unstructuredReference=陈舞, 张国华, 王浩, 等. 基于粗糙集条件信息熵的山岭隧道坍塌风险评价[J]. 岩土力学, 2019, 40(9): 3549-3558., articleTitle=基于粗糙集条件信息熵的山岭隧道坍塌风险评价, refAbstract=null), Reference(id=1204780277018112083, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2019, volume=40, issue=9, pageStart=3549, pageEnd=3558, url=null, language=null, rfNumber=[15], rfOrder=18, authorNames=Chen Wu, Zhang Guohua, Wang Hao, journalName=Rock and Soil Mechanics, refType=null, unstructuredReference=Chen Wu, Zhang Guohua, Wang Hao, et al. Risk assessment of mountain tunnel collapse based on rough set andconditional information entropy[J]. Rock and Soil Mechanics, 2019, 40(9): 3549-3558., articleTitle=Risk assessment of mountain tunnel collapse based on rough set andconditional information entropy, refAbstract=null), Reference(id=1204780277139746904, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2023, volume=23, issue=15, pageStart=6350, pageEnd=6360, url=null, language=null, rfNumber=[16], rfOrder=19, authorNames=何万才, 赵俊三, 林伊琳, journalName=科学技术与工程, refType=null, unstructuredReference=何万才, 赵俊三, 林伊琳, 等. 基于证据权和支持向量机模型的威信县滑坡易发性评价[J]. 科学技术与工程, 2023, 23(15): 6350-6360., articleTitle=基于证据权和支持向量机模型的威信县滑坡易发性评价, refAbstract=null), Reference(id=1204780277261381723, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2023, volume=23, issue=15, pageStart=6350, pageEnd=6360, url=null, language=null, rfNumber=[16], rfOrder=20, authorNames=He Wancai, Zhao Junsan, Lin Yilin, journalName=Science Technology and Engineering, refType=null, unstructuredReference=He Wancai, Zhao Junsan, Lin Yilin, et al. Landslide susceptibility assessment in Weixin County based on evidence weight and support vector machine model[J]. Science Technology and Engineering, 2023, 23(15): 6350-6360., articleTitle=Landslide susceptibility assessment in Weixin County based on evidence weight and support vector machine model, refAbstract=null), Reference(id=1204780277362045026, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2014, volume=52, issue=2, pageStart=65, pageEnd=69, url=null, language=null, rfNumber=[17], rfOrder=21, authorNames=戴思薇, 吴小俊, 高翠芳, journalName=计算机工程与应用, refType=null, unstructuredReference=戴思薇, 吴小俊, 高翠芳. 多核模糊聚类[J]. 计算机工程与应用, 2014, 52(2): 65-69., articleTitle=多核模糊聚类, refAbstract=null), Reference(id=1204780277441736805, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2014, volume=52, issue=2, pageStart=65, pageEnd=69, url=null, language=null, rfNumber=[17], rfOrder=22, authorNames=Dai Siwei, Wu Xiaojun, Gao Cuifang, journalName=Computer Engineering and Applications, refType=null, unstructuredReference=Dai Siwei, Wu Xiaojun, Gao Cuifang. Multiple kernel fuzzy clustering[J]. Computer Engineering and Applications, 2014, 52(2): 65-69., articleTitle=Multiple kernel fuzzy clustering, refAbstract=null), Reference(id=1204780277559177322, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2004, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[18], rfOrder=23, authorNames=重庆交通科研设计院, journalName=北京, refType=null, unstructuredReference=重庆交通科研设计院.公路隧道设计规范: JTG D70—2004[S]. 北京: 人民交通出版社, 2004., articleTitle=null, refAbstract=null), Reference(id=1204780277722755179, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2004, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[18], rfOrder=24, authorNames=Chongqing Communications Technology Research, Design, journalName=Beijing, refType=null, unstructuredReference=Chongqing Communications Technology Research and Design.Code for design of road tunnel: JTG D70—2004[S]. Beijing: China Communications Press, 2004., articleTitle=null, refAbstract=null), Reference(id=1204780277815029873, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2021, volume=115, issue=null, pageStart=104019, pageEnd=null, url=null, language=null, rfNumber=[19], rfOrder=25, authorNames=Ou G Z, Jiao Y Y, Zhang G H, journalName=Tunnelling and Underground Space Technology, refType=null, unstructuredReference=Ou G Z, Jiao Y Y, Zhang G H, et al. Collapse risk assessment of deep-buried tunnel during construction and its application[J]. Tunnelling and Underground Space Technology, 2021, 115: 104019., articleTitle=Collapse risk assessment of deep-buried tunnel during construction and its application, refAbstract=null), Reference(id=1204780277949247606, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2016, volume=53, issue=2, pageStart=326, pageEnd=342, url=null, language=null, rfNumber=[20], rfOrder=26, authorNames=Zhang G H, Jiao Y Y, Chen L B, journalName=Canadian Geotechnical Journal, refType=null, unstructuredReference=Zhang G H, Jiao Y Y, Chen L B, et al. Analytical model for assessing collapse risk during mountain tunnel construction[J]. Canadian Geotechnical Journal, 2016, 53(2): 326-342., articleTitle=Analytical model for assessing collapse risk during mountain tunnel construction, refAbstract=null), Reference(id=1204780278058299512, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2017, volume=63, issue=null, pageStart=69, pageEnd=94, url=null, language=null, rfNumber=[21], rfOrder=27, authorNames=Li S, Liu B, Xu X, journalName=Tunnelling and Underground Space Technology, refType=null, unstructuredReference=Li S, Liu B, Xu X, et al. An overview of ahead geological prospecting in tunneling[J]. Tunnelling and Underground Space Technology, 2017, 63: 69-94., articleTitle=An overview of ahead geological prospecting in tunneling, refAbstract=null), Reference(id=1204780278167351422, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2018, volume=66, issue=4, pageStart=784, pageEnd=797, url=null, language=null, rfNumber=[22], rfOrder=28, authorNames=Liu B, Zhang F, Li S, journalName=Geophysical Prospecting, refType=null, unstructuredReference=Liu B, Zhang F, Li S, et al. Forward modelling and imaging of ground-penetrating radar in tunnel ahead geological prospecting[J]. Geophysical Prospecting, 2018, 66(4): 784-797., articleTitle=Forward modelling and imaging of ground-penetrating radar in tunnel ahead geological prospecting, refAbstract=null), Reference(id=1204780278255431807, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2014, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[23], rfOrder=29, authorNames=陈礼彪, journalName=山岭隧道施工期安全风险评价方法研究, refType=null, unstructuredReference=陈礼彪. 山岭隧道施工期安全风险评价方法研究[D]. 武汉: 武汉大学, 2014., articleTitle=null, refAbstract=null), Reference(id=1204780278339317890, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2014, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[23], rfOrder=30, authorNames=Chen Libiao, journalName=Study on the safety risk assessment method ofmountain tunnel during construction, refType=null, unstructuredReference=Chen Libiao. Study on the safety risk assessment method ofmountain tunnel during construction[D]. Wuhan: Wuhan University, 2014., articleTitle=null, refAbstract=null), Reference(id=1204780278465147014, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2012, volume=29, issue=12, pageStart=107, pageEnd=113, url=null, language=null, rfNumber=[24], rfOrder=31, authorNames=曹更任, 蒋树屏, 谭秀梅, journalName=公路交通科技, refType=null, unstructuredReference=曹更任, 蒋树屏, 谭秀梅, 等. 地质雷达与TGP206在楚阳隧道超前地质预报中的应用[J]. 公路交通科技, 2012, 29(12): 107-113., articleTitle=地质雷达与TGP206在楚阳隧道超前地质预报中的应用, refAbstract=null), Reference(id=1204780278586781835, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2012, volume=29, issue=12, pageStart=107, pageEnd=113, url=null, language=null, rfNumber=[24], rfOrder=32, authorNames=Cao Gengren, Jiang Shuping, Tan Xiumei, journalName=Journal of Highway and Transportation Research and Development, refType=null, unstructuredReference=Cao Gengren, Jiang Shuping, Tan Xiumei, et al. Application of ground penetrating radar and TGP206 in advanced geological forecast for Chuyang Tunnel[J]. Journal of Highway and Transportation Research and Development, 2012, 29(12): 107-113., articleTitle=Application of ground penetrating radar and TGP206 in advanced geological forecast for Chuyang Tunnel, refAbstract=null), Reference(id=1204780278683250826, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2008, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[25], rfOrder=33, authorNames=周峰, journalName=山岭隧道塌方风险模糊层次评估研究, refType=null, unstructuredReference=周峰. 山岭隧道塌方风险模糊层次评估研究[D]. 长沙: 中南大学, 2008., articleTitle=null, refAbstract=null), Reference(id=1204780278796497039, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2008, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[25], rfOrder=34, authorNames=Zhou Feng, journalName=Study on fuzzy hierarchy assessment of mountain tunnel collapse risk, refType=null, unstructuredReference=Zhou Feng. Study on fuzzy hierarchy assessment of mountain tunnel collapse risk[D]. Changsha: Central South University, 2008., articleTitle=null, refAbstract=null), Reference(id=1204780278905548947, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2019, volume=34, issue=2, pageStart=11, pageEnd=17, url=null, language=null, rfNumber=[26], rfOrder=35, authorNames=张天宇, 鲁义, 施式亮, journalName=湖南科技大学学报(自然科学版), refType=null, unstructuredReference=张天宇, 鲁义, 施式亮, 等. 基于支持向量机分类算法的多煤种煤自燃危险性预测[J]. 湖南科技大学学报(自然科学版), 2019, 34 (2): 11-17., articleTitle=基于支持向量机分类算法的多煤种煤自燃危险性预测, refAbstract=null), Reference(id=1204780278989435028, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, doi=null, pmid=null, pmcid=null, year=2019, volume=34, issue=2, pageStart=11, pageEnd=17, url=null, language=null, rfNumber=[26], rfOrder=36, authorNames=Zhang Tianyu, Lu Yi, Shi Shiliang, journalName=Journal of Hunan University of Science and Technology (Natural Science Edition), refType=null, unstructuredReference=Zhang Tianyu, Lu Yi, Shi Shiliang, et al. Prediction on coal spontaneous combustion risk for multi-coal based on SVM[J]. Journal of Hunan University of Science and Technology (Natural Science Edition), 2019, 34(2): 11-17., articleTitle=Prediction on coal spontaneous combustion risk for multi-coal based on SVM, refAbstract=null)], funds=[Fund(id=1204780270407889885, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, awardId=52168055, language=CN, fundingSource=国家自然科学基金(52168055), fundOrder=null, country=null), Fund(id=1204780270491775972, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, awardId=52278397, language=CN, fundingSource=国家自然科学基金(52278397), fundOrder=null, country=null), Fund(id=1204780270567273451, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, awardId=20212ACB204001, language=CN, fundingSource=江西省自然科学基金(20212ACB204001), fundOrder=null, country=null), Fund(id=1204780270663742446, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, awardId=jxsq2020101001, language=CN, fundingSource=江西省“双千计划”创新领军人才项目(jxsq2020101001), fundOrder=null, country=null), Fund(id=1204780270810543098, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, awardId=YC2022-B179, language=CN, fundingSource=江西省研究生创新专项基金(YC2022-B179), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1204780260417057372, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, xref=null, ext=[AuthorCompanyExt(id=1204780260425445979, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, companyId=1204780260417057372, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. School of Civil and Architecture Engineering, East China University of Technology, Nanchang 330000, China), AuthorCompanyExt(id=1204780260429640284, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, companyId=1204780260417057372, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.东华理工大学土木与建筑工程学院, 南昌 330000)]), AuthorCompany(id=1204780260505137760, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, xref=null, ext=[AuthorCompanyExt(id=1204780260630966882, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, companyId=1204780260505137760, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2. School of Water Resources and Environment Engineering, East China University of Technology, Nanchang 330000, China), AuthorCompanyExt(id=1204780260635161186, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, companyId=1204780260505137760, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.东华理工大学水资源与环境工程学院, 南昌 330000)])], figs=[ArticleFig(id=1204780264909157184, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=EN, label=Fig.1, caption=Flow chart of the attribute reduction algorithm, figureFileSmall=dhtp4/0bEVMJzvCwMYZICg==, figureFileBig=+sA3rlXNuJnSZ4b07fiuGA==, tableContent=null), ArticleFig(id=1204780265014014788, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=CN, label=图1, caption=属性约简算法流程图, figureFileSmall=dhtp4/0bEVMJzvCwMYZICg==, figureFileBig=+sA3rlXNuJnSZ4b07fiuGA==, tableContent=null), ArticleFig(id=1204780265181786960, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=EN, label=Fig.2, caption=Flow chart of tunnel construction collapse risk assessment model based on RS-GS-SVC highway, figureFileSmall=O2IbOfn7+myApHfbGqiPSw==, figureFileBig=36PVPVtsngkge8ZQOF3jYQ==, tableContent=null), ArticleFig(id=1204780265274061654, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=CN, label=图2, caption=基于RS-GS-SVC公路隧道施工坍塌风险评估模型流程图, figureFileSmall=O2IbOfn7+myApHfbGqiPSw==, figureFileBig=36PVPVtsngkge8ZQOF3jYQ==, tableContent=null), ArticleFig(id=1204780265387307868, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=EN, label=Fig.3, caption=Results results of grid search method, figureFileSmall=ldYp62O2lgVpo22DN/vb2w==, figureFileBig=TFLLAisk1U4Ax4J9jcDVqw==, tableContent=null), ArticleFig(id=1204780265513136995, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=CN, label=图3, caption=网格搜索法参数寻优结果图, figureFileSmall=ldYp62O2lgVpo22DN/vb2w==, figureFileBig=TFLLAisk1U4Ax4J9jcDVqw==, tableContent=null), ArticleFig(id=1204780265638966125, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=EN, label=Fig.4, caption=Test the sample prediction results, figureFileSmall=ebi+2CtPBUS73SV7u3EFyg==, figureFileBig=gZMitHY9P58hB892QCcGNg==, tableContent=null), ArticleFig(id=1204780265836098428, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=CN, label=图4, caption=测试样本预测结果, figureFileSmall=ebi+2CtPBUS73SV7u3EFyg==, figureFileBig=gZMitHY9P58hB892QCcGNg==, tableContent=null), ArticleFig(id=1204780265932567427, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=EN, label=Table 1, caption=

Collapse grade classification table

, figureFileSmall=null, figureFileBig=null, tableContent=
坍塌等级 Ⅰ(无坍塌) Ⅱ(小坍塌) Ⅲ(中坍塌) Ⅳ(大坍塌)
坍塌高度/m — <3 [3,6] >6
坍塌体积/m3 — <30 [30,100] >100
), ArticleFig(id=1204780266062590857, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=CN, label=表1, caption=

坍塌等级划分表

, figureFileSmall=null, figureFileBig=null, tableContent=
坍塌等级 Ⅰ(无坍塌) Ⅱ(小坍塌) Ⅲ(中坍塌) Ⅳ(大坍塌)
坍塌高度/m — <3 [3,6] >6
坍塌体积/m3 — <30 [30,100] >100
), ArticleFig(id=1204780266171642766, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=EN, label=Table 2, caption=

Classification table of risk indicators

, figureFileSmall=null, figureFileBig=null, tableContent=
指标体系 指标等级
Ⅰ Ⅱ Ⅲ Ⅳ
工程地质
因素B1		 C1围岩等级([BQ]值) Ⅱ
>450		 Ⅲ
(350,450]		 Ⅳ
(250,350]		 Ⅴ、Ⅵ
≤250
C2偏压/(°) <10 [10,25) [25,40) ≥40
C3断层破碎带/m 宽度<2 2≤宽度<5 5≤宽度<10 宽度≥10
C4不良地质 不致灾
(75,100]		 轻微致灾
(50,75]		 中度致灾
(25,50]		 严重致灾[0,25]
勘察设计
因素B2		 C5开挖跨度/m <7 [7,10) [10,14) ≥14
C6深高比(H0/H) >20 (15,20] (10,15] ≤10
C7开挖方法 交叉中隔壁法 中隔壁法 台阶法 全断面法
C8地质勘察准确性/% >90 (75,90] (60,75] ≤60
C9初期支护刚度* >2 (1,2] (0.5,1] ≤0.5
施工管理
因素B3		 C10初期支护及时性/% 及时
(75,100]		 基本及时
(50,75]		 不及时
(25,50]		 非常不及时
[0,25]
C11地层加固措施 全断面帷幕注浆
加管棚超前支护		 管棚超前支护 超前小导管支护 超前锚杆支护
C12防排水措施/% 合理
(75,100]		 基本合理
(50,75]		 不合理
(25,50]		 非常不合理
[0,25]
C13爆破振动/% 合理
(75,100]		 基本合理
(50,75]		 不合理
(25,50]		 非常不合理
[0,25]
C14监控量测频率/(次·d-1) ≥4 3 2 ≤1
C15现场管理/% >90 (75,90] (60,75] ≤60
C16超前
地质预报		 地震波
反射法		 vl不变或小幅度变化;
ar<0.06;
sw<0.2		 vl小幅度变化;
ar<0.06;
0.2<sw<0.6		 vl小幅度变化;
0.06<ar<0.08;
0.2<sw<0.6		 vl大幅度降低;
ar<0.08;
sw>0.6
地质雷
达法		 掌子面围岩较好时,探测波形图深浅部同相轴分布基本一致,且无低频现象 掌子面围岩较好时,探测深度内仅局部出现富水、节理裂隙密集异常,围岩向差,有时出现低频 掌子面围岩较好时,探测深度内出现强烈富水、节理裂隙密集或溶蚀裂隙灯异常,围岩向差,一般出现低频 掌子面围岩较好时,探测深度内出现断层破碎带、溶洞等异常,一般出现低频
), ArticleFig(id=1204780266280694675, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=CN, label=表2, caption=

风险指标等级划分表

, figureFileSmall=null, figureFileBig=null, tableContent=
指标体系 指标等级
Ⅰ Ⅱ Ⅲ Ⅳ
工程地质
因素B1		 C1围岩等级([BQ]值) Ⅱ
>450		 Ⅲ
(350,450]		 Ⅳ
(250,350]		 Ⅴ、Ⅵ
≤250
C2偏压/(°) <10 [10,25) [25,40) ≥40
C3断层破碎带/m 宽度<2 2≤宽度<5 5≤宽度<10 宽度≥10
C4不良地质 不致灾
(75,100]		 轻微致灾
(50,75]		 中度致灾
(25,50]		 严重致灾[0,25]
勘察设计
因素B2		 C5开挖跨度/m <7 [7,10) [10,14) ≥14
C6深高比(H0/H) >20 (15,20] (10,15] ≤10
C7开挖方法 交叉中隔壁法 中隔壁法 台阶法 全断面法
C8地质勘察准确性/% >90 (75,90] (60,75] ≤60
C9初期支护刚度* >2 (1,2] (0.5,1] ≤0.5
施工管理
因素B3		 C10初期支护及时性/% 及时
(75,100]		 基本及时
(50,75]		 不及时
(25,50]		 非常不及时
[0,25]
C11地层加固措施 全断面帷幕注浆
加管棚超前支护		 管棚超前支护 超前小导管支护 超前锚杆支护
C12防排水措施/% 合理
(75,100]		 基本合理
(50,75]		 不合理
(25,50]		 非常不合理
[0,25]
C13爆破振动/% 合理
(75,100]		 基本合理
(50,75]		 不合理
(25,50]		 非常不合理
[0,25]
C14监控量测频率/(次·d-1) ≥4 3 2 ≤1
C15现场管理/% >90 (75,90] (60,75] ≤60
C16超前
地质预报		 地震波
反射法		 vl不变或小幅度变化;
ar<0.06;
sw<0.2		 vl小幅度变化;
ar<0.06;
0.2<sw<0.6		 vl小幅度变化;
0.06<ar<0.08;
0.2<sw<0.6		 vl大幅度降低;
ar<0.08;
sw>0.6
地质雷
达法		 掌子面围岩较好时,探测波形图深浅部同相轴分布基本一致,且无低频现象 掌子面围岩较好时,探测深度内仅局部出现富水、节理裂隙密集异常,围岩向差,有时出现低频 掌子面围岩较好时,探测深度内出现强烈富水、节理裂隙密集或溶蚀裂隙灯异常,围岩向差,一般出现低频 掌子面围岩较好时,探测深度内出现断层破碎带、溶洞等异常,一般出现低频
), ArticleFig(id=1204780267476071321, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=EN, label=Table 3, caption=

Determination of the risk factors of construction collapse in a tunnel fault zone

, figureFileSmall=null, figureFileBig=null, tableContent=
风险因素 描述 因素等级
C1围岩等级([BQ]值) [BQ]<250 Ⅳ
C2偏压/(°) 15 Ⅱ
C3断层破碎带/m 断层破碎带宽度为9.6 m Ⅲ
C4不良地质 轻微致灾 Ⅱ
C5开挖跨度/m 隧道开挖跨度为16.84 m Ⅳ
C6深高比(H0/H) 隧道深度为115 m,开挖高度为7.94 m,H0/H=14.48 Ⅲ
C7开挖方法 中隔壁法开挖 Ⅱ
C8地质勘察准确性/% 93 Ⅱ
C9初期支护刚度 初支撑由纵向距离为80 cm的20b工字钢拱架、Φ6 mm钢网、长度为3.5 m的
Φ20 mm锚杆以及厚度为28 cm的C25喷射混凝土组成		 Ⅲ
C10初期支护及时性 基本及时 Ⅱ
C11地层加固措施 采用超前小导管支护 Ⅲ
C12防排水措施/% 基本合理 Ⅱ
C13爆破振动 基本合理 Ⅱ
C14监控量测频率/(次·d-1) 监控量测频率为每天一次 Ⅳ
C15现场管理/% 85 Ⅱ
C16超前地质预报 地质雷达探测深度内仅浅部有信号,深部信号微弱,出现低频,推测存在断层破碎带 Ⅳ
), ArticleFig(id=1204780267648037791, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=CN, label=表3, caption=

隧道断裂带施工坍塌风险因素等级判定

, figureFileSmall=null, figureFileBig=null, tableContent=
风险因素 描述 因素等级
C1围岩等级([BQ]值) [BQ]<250 Ⅳ
C2偏压/(°) 15 Ⅱ
C3断层破碎带/m 断层破碎带宽度为9.6 m Ⅲ
C4不良地质 轻微致灾 Ⅱ
C5开挖跨度/m 隧道开挖跨度为16.84 m Ⅳ
C6深高比(H0/H) 隧道深度为115 m,开挖高度为7.94 m,H0/H=14.48 Ⅲ
C7开挖方法 中隔壁法开挖 Ⅱ
C8地质勘察准确性/% 93 Ⅱ
C9初期支护刚度 初支撑由纵向距离为80 cm的20b工字钢拱架、Φ6 mm钢网、长度为3.5 m的
Φ20 mm锚杆以及厚度为28 cm的C25喷射混凝土组成		 Ⅲ
C10初期支护及时性 基本及时 Ⅱ
C11地层加固措施 采用超前小导管支护 Ⅲ
C12防排水措施/% 基本合理 Ⅱ
C13爆破振动 基本合理 Ⅱ
C14监控量测频率/(次·d-1) 监控量测频率为每天一次 Ⅳ
C15现场管理/% 85 Ⅱ
C16超前地质预报 地质雷达探测深度内仅浅部有信号,深部信号微弱,出现低频,推测存在断层破碎带 Ⅳ
), ArticleFig(id=1204780267748701093, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=EN, label=Table 4, caption=

Decision information table

, figureFileSmall=null, figureFileBig=null, tableContent=
编号 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 C16 等级
1 3 2 1 2 2 3 2 1 1 1 1 1 1 1 2 1 1
2 2 1 2 1 3 1 2 2 2 3 3 2 2 2 2 1 2
3 3 1 3 2 3 2 2 1 2 3 2 1 1 2 2 2 2
4 4 2 4 3 2 3 3 2 3 2 3 3 2 3 2 4 4
5 4 1 2 2 2 3 4 3 3 3 4 3 2 4 2 2 4
6 3 1 2 2 3 4 2 4 2 3 2 3 3 2 3 2 3
7 3 3 1 1 3 3 2 2 4 4 3 2 1 2 4 3 3
8 4 1 3 2 3 2 2 2 2 3 2 2 1 2 4 2 3
9 3 1 4 2 3 3 3 2 4 4 4 3 1 2 4 3 4
10 4 1 1 1 2 3 3 2 4 3 3 4 1 2 4 4 4
11 4 1 2 1 2 3 3 2 4 4 3 4 1 2 4 3 4
12 3 1 1 2 4 4 2 2 3 3 4 3 2 2 4 4 4
13 2 1 2 1 3 4 2 1 1 2 1 2 1 2 2 2 2
14 3 1 1 3 3 2 2 1 2 1 1 2 1 2 3 3 2
15 2 2 2 1 3 4 1 1 1 2 1 2 2 2 2 2 1
16 3 2 1 1 3 3 2 1 1 1 1 2 1 1 1 1 1
17 3 2 1 2 3 3 1 1 1 1 1 1 1 1 2 3 1
18 2 1 1 2 2 3 3 1 1 1 2 2 1 1 3 2 1
19 3 2 1 1 4 4 1 2 1 1 1 2 1 1 2 2 1
20 2 1 1 2 4 4 2 2 3 2 3 3 1 3 3 2 3
21 4 1 2 1 2 4 1 4 2 3 2 2 2 2 3 3 3
22 3 1 2 1 3 1 2 4 3 4 3 2 1 2 3 3 3
23 4 1 2 2 3 4 2 2 1 2 2 2 1 2 3 1 2
24 3 2 1 1 3 2 3 1 2 3 2 3 2 1 3 2 2
25 3 1 2 2 3 4 1 1 2 2 1 2 1 2 3 2 2
26 2 1 1 2 3 1 3 2 2 1 1 1 1 1 2 2 1
27 3 1 4 1 3 4 3 3 4 4 4 3 1 2 4 4 4
28 3 1 3 4 3 3 1 3 2 4 2 2 1 2 4 4 3
29 3 1 2 1 3 4 2 4 2 4 3 2 1 2 3 2 3
30 2 4 3 2 3 4 2 2 3 4 2 2 4 3 4 2 3
), ArticleFig(id=1204780267891307440, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=CN, label=表4, caption=

决策信息表

, figureFileSmall=null, figureFileBig=null, tableContent=
编号 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15 C16 等级
1 3 2 1 2 2 3 2 1 1 1 1 1 1 1 2 1 1
2 2 1 2 1 3 1 2 2 2 3 3 2 2 2 2 1 2
3 3 1 3 2 3 2 2 1 2 3 2 1 1 2 2 2 2
4 4 2 4 3 2 3 3 2 3 2 3 3 2 3 2 4 4
5 4 1 2 2 2 3 4 3 3 3 4 3 2 4 2 2 4
6 3 1 2 2 3 4 2 4 2 3 2 3 3 2 3 2 3
7 3 3 1 1 3 3 2 2 4 4 3 2 1 2 4 3 3
8 4 1 3 2 3 2 2 2 2 3 2 2 1 2 4 2 3
9 3 1 4 2 3 3 3 2 4 4 4 3 1 2 4 3 4
10 4 1 1 1 2 3 3 2 4 3 3 4 1 2 4 4 4
11 4 1 2 1 2 3 3 2 4 4 3 4 1 2 4 3 4
12 3 1 1 2 4 4 2 2 3 3 4 3 2 2 4 4 4
13 2 1 2 1 3 4 2 1 1 2 1 2 1 2 2 2 2
14 3 1 1 3 3 2 2 1 2 1 1 2 1 2 3 3 2
15 2 2 2 1 3 4 1 1 1 2 1 2 2 2 2 2 1
16 3 2 1 1 3 3 2 1 1 1 1 2 1 1 1 1 1
17 3 2 1 2 3 3 1 1 1 1 1 1 1 1 2 3 1
18 2 1 1 2 2 3 3 1 1 1 2 2 1 1 3 2 1
19 3 2 1 1 4 4 1 2 1 1 1 2 1 1 2 2 1
20 2 1 1 2 4 4 2 2 3 2 3 3 1 3 3 2 3
21 4 1 2 1 2 4 1 4 2 3 2 2 2 2 3 3 3
22 3 1 2 1 3 1 2 4 3 4 3 2 1 2 3 3 3
23 4 1 2 2 3 4 2 2 1 2 2 2 1 2 3 1 2
24 3 2 1 1 3 2 3 1 2 3 2 3 2 1 3 2 2
25 3 1 2 2 3 4 1 1 2 2 1 2 1 2 3 2 2
26 2 1 1 2 3 1 3 2 2 1 1 1 1 1 2 2 1
27 3 1 4 1 3 4 3 3 4 4 4 3 1 2 4 4 4
28 3 1 3 4 3 3 1 3 2 4 2 2 1 2 4 4 3
29 3 1 2 1 3 4 2 4 2 4 3 2 1 2 3 2 3
30 2 4 3 2 3 4 2 2 3 4 2 2 4 3 4 2 3
), ArticleFig(id=1204780268008747958, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=EN, label=Table 5, caption=

Attribute set C conditional information entropy table

, figureFileSmall=null, figureFileBig=null, tableContent=
条件属性 条件信息熵 条件属性 条件信息熵
C 0 C8 0.198 4
C9 0.119 4 C1 0.211 8
C16 0.130 8 C6 0.216 8
C11 0.135 4 C3 0.235 4
C10 0.152 0 C4 0.254 8
C14 0.164 2 C5 0.288 2
C15 0.164 2 C2 0.348 8
C7 0.184 0 C13 0.381 0
C12 0.187 6
), ArticleFig(id=1204780268101022656, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=CN, label=表5, caption=

属性集C条件信息熵表

, figureFileSmall=null, figureFileBig=null, tableContent=
条件属性 条件信息熵 条件属性 条件信息熵
C 0 C8 0.198 4
C9 0.119 4 C1 0.211 8
C16 0.130 8 C6 0.216 8
C11 0.135 4 C3 0.235 4
C10 0.152 0 C4 0.254 8
C14 0.164 2 C5 0.288 2
C15 0.164 2 C2 0.348 8
C7 0.184 0 C13 0.381 0
C12 0.187 6
), ArticleFig(id=1204780268197491656, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=EN, label=Table 6, caption=

Comparison of the optimized model classification accuracy results

, figureFileSmall=null, figureFileBig=null, tableContent=
参数寻
优方法		 交叉验证下
分类准确率/%		 c g 时间/s
RS-GS-SVC 94.285 7 5.656 9 0.062 5 3.766 0
RS-GA-SVC 91.428 6 1.899 0 0.288 2 6.256 9
RS-PSO-SVC 92.857 1 5.918 7 0.100 0 14.967 9
), ArticleFig(id=1204780268319126475, tenantId=1146029695717560320, journalId=1146123166801305609, articleId=1156908031943467635, language=CN, label=表6, caption=

优化模型分类准确率结果对比

, figureFileSmall=null, figureFileBig=null, tableContent=
参数寻
优方法		 交叉验证下
分类准确率/%		 c g 时间/s
RS-GS-SVC 94.285 7 5.656 9 0.062 5 3.766 0
RS-GA-SVC 91.428 6 1.899 0 0.288 2 6.256 9
RS-PSO-SVC 92.857 1 5.918 7 0.100 0 14.967 9
)], attaches=null, journal=Journal(id=1146119176004939786, delFlag=0, nameCn=科学技术与工程, nameEn=Science Technology and Engineering, nameHistory1=null, nameHistory2=null, issn=1671-1815, eissn=, cn=11-4688/T, coden=null, periodic=4, language=CN, oaType=是, ccby=null, superviseOffice=null, ownerOffice=null, pubOffice=null, editorOffice=null, officeType=null, aims=null, clcCode=null, officeProv=null, officeCity=null, officeAddr=null, officeZip=null, officeEmail=null, officePhone=null, editDirector=null, officeDirector=null, officeDirectorPhone=null, officeStaffNum=null, officeEmpNum=null, coverPicUrl=UKU/O7GSka5polgCTkbIIw==, journalPrice=null, startedYear=null, abbrevIsoEn=Sci Technol Eng, journalRemark=null, publicationField=null, createdTime=null, updatedTime=1754445529766, createdBy=null, updatedBy=13701087609, firstLetterCn=S, firstLetterEn=S, subjectCode=Natural Sciences, subjectName=自然科学, subjectCodeEn=Natural Sciences, subjectNameEn=null, picCn=UKU/O7GSka5polgCTkbIIw==, picEn=5hwlULoNwcbj3xUmVi9MAQ==, jcr=null, cjcr=null, exts=[JournalExt(id=1159791870395564357, language=CN, name=科学技术与工程, nameHistory1=null, nameHistory2=null, managedBy=, sponsoredBy=, publishedBy=, editorOffice=, officeProv=null, officeCity=null, officeAddr=, officeZip=, editDirector=null, officeDirector=null, officePhone=null, coverPicUrl=null, journalRemark=, submitArticleUrl=null, websiteUrl=http://www.stae.com.cn/jsygc/home, createdTime=1754445529793, updatedTime=1754445529793, createdBy=13701087609, updatedBy=13701087609, submissionGuidelinesUrl=http://www.stae.com.cn/jsygc/site/menus/20090429150146001, submissionAuthorUrl=http://www.stae.com.cn/jsygc/author/login, submissionEditorUrl=http://www.stae.com.cn/jsygc/editor/login, submissionReviewUrl=http://www.stae.com.cn/jsygc/reviewer/login, submissionCeEditorUrl=, submissionAeEditorUrl=, option={"copyright":""}), JournalExt(id=1159791870441701702, language=EN, name=Science Technology and Engineering, nameHistory1=null, nameHistory2=null, managedBy=, sponsoredBy=, publishedBy=, editorOffice=, officeProv=null, officeCity=null, officeAddr=, officeZip=, editDirector=null, officeDirector=null, officePhone=null, coverPicUrl=null, journalRemark=, submitArticleUrl=null, websiteUrl=http://www.stae.com.cn/jsygc/home, createdTime=1754445529804, updatedTime=1754445529804, createdBy=13701087609, updatedBy=13701087609, submissionGuidelinesUrl=, submissionAuthorUrl=http://www.stae.com.cn/jsygc/author/login, submissionEditorUrl=http://www.stae.com.cn/jsygc/editor/login, submissionReviewUrl=http://www.stae.com.cn/jsygc/reviewer/login, submissionCeEditorUrl=, submissionAeEditorUrl=, option={"copyright":""})], databaseList=null, tenantJournalId=1146123166801305609, websiteList=[Website(id=1148243202391400884, webName=null, webTitle=null, webDomain=null, webCopyrigh=null, webIpcNo=null, seoTitle=null, seoKeywords=null, seoDescription=null, tenantJournalId=null, journalId=1146123166801305609, journalNameCn=null, journalNameEn=null, grayFlag=null, tenantId=1146029695717560320, platformId=null, journalGroupId=null, journalGroupNameCn=null, journalGroupNameEn=null, type=1, domain=https://castjournals.cast.org.cn/joweb/kxjsygc/CN, language=CN, createTime=1751692112777, createBy=18614031015, updateTime=1753520965431, updateBy=18614031015, name=科学技术与工程-中文站点, tplId=1146099689490845704, title=科学技术与工程, delFlag=0, indexPage=/home, props=[WebsiteProps(id=1148622798802673703, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1148243202391400884, code=articleTextType, value=kx, createTime=1751782615614, updateTime=1751782615614, creator=18614031015, updator=18614031015), WebsiteProps(id=1148622798781702180, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1148243202391400884, code=banner, value=null, createTime=1751782615609, updateTime=1751782615609, creator=18614031015, updator=18614031015), WebsiteProps(id=1148622798769119267, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1148243202391400884, code=logo, value=https://castjournals.cast.org.cn/joweb/kjdb/CN/file/pic?fileId=j86gbwi+p0Idkyl5SzIlmQ==, createTime=1751782615606, updateTime=1751782615606, creator=18614031015, updator=18614031015), WebsiteProps(id=1148622798794285094, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1148243202391400884, code=picServerUrl, value=https://castjournals.cast.org.cn/joweb/kjdb/CN/file/pic, createTime=1751782615612, updateTime=1751782615612, creator=18614031015, updator=18614031015), WebsiteProps(id=1148622798790090789, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1148243202391400884, code=staticResourcePath, value=https://castjournals.cast.org.cn/joweb/cast_kjdb_cn_619/, createTime=1751782615611, updateTime=1751782615611, creator=18614031015, updator=18614031015)]), Website(id=1155914124811976731, webName=null, webTitle=null, webDomain=null, webCopyrigh=null, webIpcNo=null, seoTitle=null, seoKeywords=null, seoDescription=null, tenantJournalId=null, journalId=1146123166801305609, journalNameCn=null, journalNameEn=null, grayFlag=null, tenantId=1146029695717560320, platformId=null, journalGroupId=null, journalGroupNameCn=null, journalGroupNameEn=null, type=1, domain=https://castjournals.cast.org.cn/joweb/kxjsygc/EN, language=EN, createTime=1753521003206, createBy=18614031015, updateTime=1753521003206, updateBy=18614031015, name=科学技术与工程-英文站点, tplId=1146101810881728533, title=Science Technology and Engineering, delFlag=0, indexPage=/home, props=[WebsiteProps(id=1155914371227308235, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1155914124811976731, code=articleTextType, value=kx, createTime=1753521061952, updateTime=1753521061952, creator=18614031015, updator=18614031015), WebsiteProps(id=1155914371210531016, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1155914124811976731, code=banner, value=null, createTime=1753521061947, updateTime=1753521061947, creator=18614031015, updator=18614031015), WebsiteProps(id=1155914371202142407, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1155914124811976731, code=logo, value=https://castjournals.cast.org.cn/joweb/kjdb/CN/file/pic?fileId=j86gbwi+p0Idkyl5SzIlmQ==, createTime=1753521061945, updateTime=1753521061945, creator=18614031015, updator=18614031015), WebsiteProps(id=1155914371223113930, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1155914124811976731, code=picServerUrl, value=https://castjournals.cast.org.cn/joweb/kjdb/CN/file/pic, createTime=1753521061950, updateTime=1753521061950, creator=18614031015, updator=18614031015), WebsiteProps(id=1155914371218919625, tenantId=1146029695717560320, journalId=null, journalGroupId=null, siteId=1155914124811976731, code=staticResourcePath, value=https://castjournals.cast.org.cn/joweb/cast_kjdb_cn_619/, createTime=1753521061949, updateTime=1753521061949, creator=18614031015, updator=18614031015)])], journalTitle=科学技术与工程, weixinUrl=null, journalUrl=null, iacademicId=null, status=0, seqNo=null, journalTitleEn=Science Technology and Engineering, journalPhotoCn=UKU/O7GSka5polgCTkbIIw==, journalPhotoEn=5hwlULoNwcbj3xUmVi9MAQ==, journalFirstLetter=S, journalRecommend=null, journalNew=null, journalCollection=null, jcrJf=null, cjcrJf=null, jcrJfStr=null, cjcrJfStr=null, submissionFirstDecision=null, sciSubjectClassification=null, casSubjectClassification=null, citeScore=null, totalCitationFrequency=null, icpCode=null, psCode=null, advertisingLicenseCode=null, copyrightInformation=null, country=null, option=null, provinceCode=null, provinceName=null, collectFlag=false), detailUrlCn=https://castjournals.cast.org.cn/joweb/kxjsygc/CN/10.12404/j.issn.1671-1815.2309307, detailUrlEn=https://castjournals.cast.org.cn/joweb/kxjsygc/EN/10.12404/j.issn.1671-1815.2309307, pdfUrlCn=https://castjournals.cast.org.cn/joweb/kxjsygc/CN/PDF/10.12404/j.issn.1671-1815.2309307, pdfUrlEn=https://castjournals.cast.org.cn/joweb/kxjsygc/EN/PDF/10.12404/j.issn.1671-1815.2309307, aliStartDate=null, aliEndDate=null, collectionFlag=false, citedCount=null, citedUrl=null, reference=null)
收藏切换
基于粗糙集-网格搜索-支持向量的公路隧道施工坍塌风险评估模型
收藏切换
PDF下载
吴波 1 , 曾佳佳 2, * , 蔡琦 1 , 朱若男 2 , 刘聪 1
科学技术与工程 | 论文·交通运输 2025,25(3): 1245-1252
收起
收藏切换
科学技术与工程 | 论文·交通运输 2025, 25(3): 1245-1252
基于粗糙集-网格搜索-支持向量的公路隧道施工坍塌风险评估模型
全屏
吴波1 , 曾佳佳2, * , 蔡琦1, 朱若男2, 刘聪1
作者信息
  • 1.东华理工大学土木与建筑工程学院, 南昌 330000
  • 2.东华理工大学水资源与环境工程学院, 南昌 330000

    • 吴波(1971—),男,汉族,四川阆中人,博士,教授。研究方向:地下与隧道工程。E-mail:。

通讯作者:

* 曾佳佳(1991—),女,汉族,湖南邵阳人,博士研究生。研究方向:地下与隧道工程。E-mail:。
Risk Assessment Model of Highway Tunnel Collapse Based on Rough Set-grid Search-support Vector Classification
Bo WU1 , Jia-jia ZENG2, * , Qi CAI1, Ruo-nan ZHU2, Cong LIU1
Affiliations
  • 1. School of Civil and Architecture Engineering, East China University of Technology, Nanchang 330000, China
  • 2. School of Water Resources and Environment Engineering, East China University of Technology, Nanchang 330000, China
出版时间: 2025-01-28 doi: 10.12404/j.issn.1671-1815.2309307
文章导航
收藏切换
摘要
收起

为合理高效地进行公路隧道施工坍塌风险评估,通过粗糙集(rough set,RS)理论、网格搜索法(grid search,GS)和支持向量机(support vector classification,SVC)研究了公路隧道施工坍塌风险评估模型。首先融合超前地质预报,构建公路隧道施工坍塌风险评价指标体系,同时收集100个隧道坍塌相关案例信息并对指标数据进行离散化处理,其次基于粗糙集条件信息熵进行属性约简,得到约简后的核指标集,而后采用网格搜索法寻找支持向量分类训练集的最优参数,建立基于粗糙集-网格搜索-支持向量(RS-GS-SVC)公路隧道施工坍塌风险评估模型,最后将所建模型用于对测试样本的预测。结果表明:在相同学习样本的条件下,相较于粗糙集-遗传-支持向量模型(RS-GA-SVC)和粗糙集-粒子群-支持向量模型(RS-PSO-SVC),RS-GS-SVC模型具有更高的分类精度;在训练集与测试集比例相同的条件下,RS-GS-SVC模型的预测准确率高于GS-SVC模型,准确率分别为93.33%和90%,且RS-GS-SVC模型的运算时间更短。可见,经粗糙集条件信息熵属性约简,可以有效降低模型复杂度,提高分类精度。

风险评估  /  公路隧道坍塌  /  支持向量分类  /  粗糙集  /  网格搜索法

In order to reasonably and efficiently carry out the risk assessment of road tunnel construction collapse, the risk assessment model of road tunnel construction collapse was studied by rough set (RS), grid search method(GS) and support vector classification (SVC). Firstly, the index system of highway tunnel construction collapse risk evaluation was constructed by integrating advanced geological prediction. At the same time, the information of 100 tunnel collapse cases was collected and the index data was discretized. Secondly, attribute reduction was conducted based on the condition information entropy of rough set to obtain the reduced core index set. Then, grid search method was used to find the optimal parameters of the support vector classification training set, the risk assessment model of highway tunnel construction collapse based on rough set-grid search-support vector classification (RS-GS-SVC) was established. Finally, the model was used to predict the test samples. The results show that under the condition of the same learning sample, compared with rough set-genetic algorithm-support vector classification (RS-GA-SVC) model and Rough set-particle swarm optimization-support vector classification (RS-PSO-SVC) model, RS-GS-SVC model has higher classification accuracy; Under the same proportion of training set and test set, the prediction accuracy of RS-GS-SVC model is higher than that of GS-SVC model, with the accuracy rates of 93.33% and 90% respectively, and the operation time of RS-GS-SVC model is shorter. It can clearly be seen that the model complexity is effectively reduced and the classification accuracy is improved through the reduction of rough set conditional information entropy attributes.

highway tunnel collapse  /  support vector classification  /  rough set  /  grid search method  /  risk assessment
吴波, 曾佳佳, 蔡琦, 朱若男, 刘聪. 基于粗糙集-网格搜索-支持向量的公路隧道施工坍塌风险评估模型. 科学技术与工程, 2025 , 25 (3) : 1245 -1252 . DOI: 10.12404/j.issn.1671-1815.2309307
Bo WU, Jia-jia ZENG, Qi CAI, Ruo-nan ZHU, Cong LIU. Risk Assessment Model of Highway Tunnel Collapse Based on Rough Set-grid Search-support Vector Classification[J]. Science Technology and Engineering, 2025 , 25 (3) : 1245 -1252 . DOI: 10.12404/j.issn.1671-1815.2309307
正文
收起
随着国民经济的快速发展,公路隧道的建设规模也在逐年递增。公路隧道建设过程中,突发性坍塌事故时有发生,常常造成人员伤亡、经济损失及工期延误,已成为一个重大安全隐患[1]。因此,合理有效地进行公路隧道施工坍塌风险评估对于隧道安全建设工作具有重要的指导意义。
近十几年来,诸多学者在隧道坍塌风险评估方面做了大量研究,Kim等[2]基于层次分析法和德尔菲调查法建立隧道坍塌风险概率评估模型;Ou等[3]提出基于参数学习的公路隧道塌方多状态动态贝叶斯网络评估方法;Gao等[4]将灰色关联度与熵权法相结合对隧道坍塌进行风险评估;Li等[5]引入云模型建立公路隧道风险综合评估模型;Li 等[6]提出改进的量化Ⅲ理论,并采用模糊综合评价法对隧道坍塌进行风险评价;叶华政[7]基于贝叶斯网络方法,考虑风险因素间的关联,通过模糊解释结构模型与因果图法对网络结构建模,实现隧道坍塌风险评估模型;张良等[8]通过粗糙集理论和条件信息熵理论确定属性核指标,利用遗传算法实现属性约简,结合模糊评价法构建风险评价模型。
以上方法均取得一定的效果,但由于隧道坍塌风险评价指标众多且指标与坍塌风险之间存在复杂的非线性关系,不论选用哪种方法都会面临处理大量数据的问题,如何高效率处理复杂数据,提高隧道坍塌风险等级预测准确率已受到众多研究者的关注。
粗糙集(rough set,RS)是一种定量分析的数学方法,它无需知晓样本数据之外的任何先验知识,在确保分类能力不变的情况下对数据进行属性约简,剔除冗余数据,降低模型维度[9]。支持向量机(support vector machines,SVM)是一种并行于人工神经网络的新型机器学习算法,在处理小样本、非线性及高维模式识别问题中具有独特优势,拥有全局最优、泛化能力强的特点[10]。粗糙集与支持向量机的结合可以很好地实现优势互补,主要表现在利用粗糙集作为支持向量机模型的前端数据处理器,通过对指标数据预处理,删除冗余信息,降低模型复杂程度,从而提高模型预测准确率,同时缩短了模型运算时间。两者的有机结合已成功应用于多个领域,如大坝加固安全监测[11]、道路交通事故分类[12]、瓦斯爆炸预测[13]等。基于此,现融合超前地质预报,构建公路隧道施工坍塌风险评价指标体系,同时收集相关隧道坍塌案例,利用粗糙集条件信息熵对指标数据进行属性约简,采用网格搜索法(grid search,GS)优化支持向量分类(support vector classification,SVC),建立基于RS-GS-SVC公路隧道施工坍塌风险评估模型,用于预测测试样本的风险等级。
1 方法
收起
1.1 基于粗糙集条件信息熵的属性约简
粗糙集(rough set,RS)是波兰数学家Pawlak[14]在1982年提出的一种处理不确定、模糊信息的工具,特点在于处理模糊信息时,不借助主观的专家经验打分,而依靠类似案例的自身数据进行推理,从不完整的信息中得到规律,提取规则,计算结果具有较强的客观性。其中基于传统依赖度属性约简的计算方法在发现关键属性及属性约简上有着巨大优势。经典粗糙集理论通常用四元组S=< U, A, V, f >表示决策信息表,其中U称为论域,A为等价关系集,依据A对U进行划分,记做U|A,A=C∪D为属性集合,C为条件属性,D为决策属性,其中C∪D=∅,V表示所有属性的值域集合,f为信息函数。
属性约简是粗糙集理论的重要研究之一。目前,属性约简算法的主要研究有基于正区域的属性约简算法、基于分辨矩阵的属性约简算法和基于信息熵的属性约简算法。本研究主要引用陈舞等[15]提出的基于粗糙集条件信息熵的属性约简算法。该方法克服了传统粗糙集依赖度计算指标权重时结果为0的问题,计算结果更加贴近实际工程。其原理如下。
设C、D在U上的划分的等价集分别为X、Y,即
U C = X = { X 1 , X 2 , … , X s } U D = Y = { Y 1 , Y 2 , … , Y t }
则C、D是论域U上的两个属性集合,两者的集合被认为是一个代数上的随机量,其概率分布为
[ X : P ] = X 1 X 2 … X s P ( X 1 ) P ( X 2 ) … P ( X s ) [ Y : P ] = Y 1 Y 2 … Y t P ( Y 1 ) P ( Y 2 ) … P ( Y t ) P ( X i ) = X i U , 　 　 i = 1,2 , … , s P ( Y j ) = Y j U , 　 　 j = 1,2 , … , t
决策属性D相对于条件属性C的信息熵定义为
$\left\{\begin{aligned} I(D \mid C)= & \sum_{i=1}^{|U| C \mid} P^{2}\left(X_{i}\right) \sum_{i=1}^{|U| D \mid} P\left(Y_{j} \mid X_{i}\right) \times \\ & {\left.\left[1-P\left(Y_{j} \mid X_{i}\right)\right)\right] } \\ P\left(Y_{j} \mid X_{i}\right)= & \frac{\left|Y_{j} \cap X_{i}\right|}{\left|X_{i}\right|} \end{aligned}\right.$
属性约简算法流程图如图1所示,具体计算步骤如下。
(1)输入决策信息表S。
(2)计算决策属性D相对于条件属性C的信息熵I(D|C)。
(3)计算决策属性D相对于条件属性C中各个属性子集的信息熵I(D|{Ci}),按照升序进行排列。
(4)令原始条件属性集合为C,约简属性集合为C*=∅。
(5)将条件信息熵中最小的属性子集Ci代入C*,计算决策属性D相对于属性约简集C*的信息熵I(D|C*),若I(D|C*)=I(D|C),则输出约简集C*,否则C=C-{Ci},继续将条件信息熵中最小的属性子集Ci代入C*,计算直到I(D|C*)=I(D|C),结束计算。
1.2 支持向量机
支持向量机(support vector machines,SVM)是统计学理论发展而来的以监督学习方式对数据进行分类和回归分析的机器学习方法。它适用于小样本、非线性及高维模式的识别,核心思想是寻找一个最优分类超平面,从而提高分类器的泛化处理能力。本研究将支持向量机应用于公路隧道施工坍塌风险等级分类,此时的支持向量机可以简称为支持向量分类(support vector classification,SVC)[16]。
以数据二分类为例,支持向量机的求解过程如下。
假设存在数据集{xi,yi},i=1,2,…,m,yi∈{-1,+1},xi∈Rn,m为样本数,Rn为n维空间,n为样本属性特征维数,当数据集为线性可分时,可用一个超平面将两类数据完全分开。即
wx+b=0
式(4)中:w为n维超平面的权重向量,决定超平面的方向;b为位移项,决定超平面与原点之间的距离。离超平面最近的特征向量与超平面的距离达到极限,即分类间隔最大,此时的超平面为最优超平面。
最优超平面可通过求解如下约束优化问题获得,即
m i n φ ( w ) = 1 2 ‖ w ‖ 2 = 1 2 ( w w ) y i ( w · x i + b ) ≥ 1 , 　 i = 1,2 , … , m
通过引入Lagrange函数,最终可以得到最优超平面的判别函数为
$f(x)=\operatorname{sgn}\left[\sum_{i=1}^{m} \alpha_{i} y_{i}\left(\boldsymbol{x}_{i} \boldsymbol{x}\right)+b\right]$
式(6)中:αi为拉格朗日乘子。
当数据集为线性不可分时,无法要求所有特征向量都满足约束条件yi(w·xi+b)≥1,为此,在约束条件中引入松弛变量ζ,同时在目标函数中引进惩罚系数c,此时的最优超平面可通过如下新的目标函数求解,即
minφ(w,ζ)= 1 2(ww)+c( ∑ i = 1 m ζi)
式(7)中:ζi≥0,惩罚系数c起到平衡算法复杂度和样本误差的作用,若c过大,可能会导致分类器过度学习,影响其泛化能力。
对于非线性数据集,可以通过引入核函数,将原始空间的样本映射到某个高维空间,使非线性问题在高维空间中转化为线性可分问题。相应的判别函数为:
$f(x)=\operatorname{sgn}\left[\sum_{i=1}^{m} \alpha_{i} y_{i} K\left(\boldsymbol{x}_{i} \boldsymbol{x}\right)+b\right]$
式(8)中:K(xi,x)为核函数,本研究采用全局分类性较优、泛化能力较强的Sigmoid核函数[17],其表达形式为:K(xi,xj)=tanh[g(xixj)+c],其中c、g为核函数参数。
在利用支持向量机对非线性样本数据集进行分类时,(c, g)是影响支持向量机分类器性能的两个关键参数,决定着分类器的准确性和泛化能力。本研究采用网格搜索法(grid search,GS)寻找最优的(c, g)参数。其基本原理是让待搜索的参数在一定的范围内划分网格并遍历网格内所有点进行取值,对于每次取定的参数组,利用交叉验证法验证每组参数组在支持向量机中对应的分类准确率,最后将分类准确率最高的参数组作为模型的最佳参数。本研究采用5折交叉验证寻找最优参数,(c, g)的搜索范围为[2-8,28]。
2 建立风险评价指标体系
收起
首先,需要对本研究的坍塌规模进行说明。参考《公路隧道设计规范》(JTG D70—2004)[18]对坍塌的分类,将公路隧道施工坍塌风险分为四个等级,如表1所示。其次,风险评价前需要对影响隧道坍塌的风险因素进行辨识。本研究基于文献[19-20],结合现场经验,分析总结了工程地质因素、勘察设计因素、施工管理因素三大隧道施工坍塌风险因素,并融合了超前地质预报,建立公路隧道施工坍塌风险评价指标体系,并进行风险指标等级的划分。本研究的超前地质预报指标采用综合超前地质预报体系,包括长距离探测的地震波反射法和短距离探测的地质雷达法。在参考文献[21-24]以及现场经验的基础上,本研究通过反射幅度比、波轴相似度等参数确定地震波反射法探测结果的分类等级,提取地质雷达法探测成果中的波形特征、频率等参数描述隧道掌子面前方的地质情况。对应的坍塌风险指标体系如表2所示。本研究依据地震波反射法和地质雷达法的探测结果分级,遵循最不利原则,确定超前地质预报等级。
3 模型建立与求解
收起
基于RS-GS-SVC公路隧道施工坍塌风险评估模型构建流程图如图2所示,具体步骤如下。
(1)选取相关案例,收集案例信息,并进行离散化处理,形成决策信息表S。
(2)采用粗糙集条件信息熵对初始决策表进行属性约简,剔除冗余指标,得到属性约简集C*。
(3)对属性约简后的指标数据进行归一化处理,公式为
X i *= X i - X m i n X m a x - X m i n
式(9)中:Xi和 X i *分别为第i个样本数据及其对应的归一化数据;Xmax和Xmin分别为各个指标的最大值和最小值。
(4)利用GS法寻找SVC的最优超参数(c,g),构建基于粗糙集公路隧道施工坍塌风险评估的优化支持向量机模型。
(5)将建立的RS-GS-SVC模型应用于测试样本,实现公路隧道施工坍塌风险等级识别。
3.1 数据采集
本研究收集的数据库为100个隧道施工段信息,来源于相关文献[25]中隧道坍塌的相关研究、公开报道以及作者所经历项目中的隧道施工段。以福建三明市莆炎高速公路隧道断裂带为例,对隧道施工段信息进行整理描述,并确定各因素对应等级,如表3所示。该隧道施工段在开挖过程中发生坍塌,坍塌体积约为65 m3,根据表1,该段的坍塌风险等级为Ⅲ。在进行数据处理分析时,将70个隧道施工段数据作为学习样本,30个隧道施工段数据作为模型的测试样本。
3.2 属性约简
将100个隧道施工段信息中条件属性和决策属性的风险划分等级Ⅰ、Ⅱ、Ⅲ、Ⅳ对应量化为数字1、2、3、4,进行离散化处理,建立离散化决策信息表S,部分数据见表4。根据公式(1)计算得到各风险指标的条件信息熵I(D|{Ci}),按照图1的步骤进行属性约简,升序排列结果见表5,经过九次循环计算,得到相应的属性约简集C* = {C9, C16, C11, C10, C14, C15, C7, C12, C8}。
3.3 模型训练与预测
3.3.1 模型参数寻优
将约简后的9个指标数据按照式(9)进行归一化处理,利用GS法寻找最优参数(c, g),搜索范围为[2-8,28],经5次交叉验证确定SVC的最优参数为c=5.656 9,g=0.062 5,其训练集分类精度结果见图3,此时交叉验证下模型训练集的分类准确率为94.285 7%。
为了进一步说明网格搜索法所得参数最优,在保证相同学习样本的前提下,将常用的遗传算法(genetic algorithm,GA)、粒子群算法(particle swarm optimization,PSO),均采用Sigmoid核函数,依据文献[26]进行调参,各算法寻优结果如表6所示。
由表6可知,当学习样本均为属性约简后的9个指标数据,经网格搜索法得到的参数组使得模型训练集在交叉验证下的分类准确率最高,且模型计算用时最短。因此,选用GS法确定的参数组作为模型的最优参数。
3.3.2 模型预测分析
将训练好的RS-GS-SVC模型对30个测试样本进行预测,此外,在保证训练集与测试集比例相同的情况下,采用GS-SVC模型对未经约简的指标数据进行预测,结果如图4所示。
图4为测试样本的混淆矩阵,每一列代表预测等级,每一列数值之和表示预测为该等级的样本数;每一行代表真实等级,每一行数值之和表示该等级的实际样本数;对角线的数值表示预测正确的样本数,从图4(a)可知,RS-GS-SVC模型预测错误的样本数为2,其分类准确率达到93.33%,图4(b)中,GS-SVC模型的分类准确率为90%。除此之外,GS-SVC模型计算时间为7.386 6 s,RS-GS-SVC模型计算时间为3.766 0 s。由此说明:基于GS-SVC模型,对指标进行粗糙集条件信息熵属性约简,能够提高模型计算精度及运行速率,降低模型复杂度。
4 结论
收起
(1)公路隧道施工坍塌风险因素复杂多变,在识别风险因素时融入超前地质预报,构建了公路隧道施工坍塌风险评价指标体系,并结合现场经验进行指标分级。
(2)将粗糙集条件信息熵属性约简与网格搜索法优化的支持向量分类有机结合,建立了基于RS-GS-SVC公路隧道施工坍塌风险评估模型,预测准确率达93.33%,符合工程要求。
(3)在保证相同学习样本以及核函数的前提下,GS法不仅具有较高的收敛速度,寻优得到的参数组也明显优化了SVC的性能。
(4)原始16个隧道坍塌指标经粗糙集条件信息熵属性约简为9个指标,降低了模型维度,缩短了模型运算时间,同时提高了模型预测准确率。
基金
收起
  • 国家自然科学基金(52168055)
  • 国家自然科学基金(52278397)
  • 江西省自然科学基金(20212ACB204001)
  • 江西省“双千计划”创新领军人才项目(jxsq2020101001)
  • 江西省研究生创新专项基金(YC2022-B179)
文献
收起
参考文献 引证文献
排序方式：
[1]
熊自明, 卢浩, 王明洋, 等. 我国大型岩土工程施工安全风险管理研究进展[J]. 岩土力学, 2018, 39 (10): 3703-3716.
Xiong Ziming, Lu Hao, Wang Mingyang, et al. Research progress on safety risk management for large scale geotechnical engineering construction in China[J]. Rock and Soil Mechanics, 2018, 39 (10): 3703-3716.
[2]
Kim J, Kim C, Kim G, et al. Probabilistic tunnel collapse risk evaluation model using analytical hierarchy process (AHP) and Delphi survey technique[J]. Tunnelling and Underground Space Technology, 2022, 120: 104262.
[3]
Ou X, Wu Y, Wu B, et al. Dynamic Bayesian network for predicting tunnel-collapse risk in the case of incomplete data[J]. Journal of Performance of Constructed Facilities, 2022, 36(4): 04022034.
[4]
Gao C, Li S, Wang J, et al. The risk assessment of tunnels based on grey correlation and entropy weight method[J]. Geotechnical and Geological Engineering, 2018, 36(3): 1621-1631.
[5]
Li Z, Meng X, Liu D, et al. Disaster risk evaluation of superlong highways tunnel based on the cloud and AHP model[J]. Advances in Civil Engineering, 2022(9): 8785030.
[6]
Li L, Ni B, Zhang S, et al. Tunnel collapse risk assessment based on improved quantitative theory III and EW-AHP coupling weight[J]. Scientific Reports, 2022, 12(1): 1-19.
[7]
叶华政. 基于贝叶斯理论的山岭隧道施工坍塌风险评估及预警研究[D]. 南宁: 广西大学, 2024.
Ye Huazhen. Collapse risk assessment and early warning reserch for moutain tunnelling based on Bayesian theory[D]. Nanning: Guangxi University, 2024.
[8]
张良, 孙永新, 王晓睿, 等. 基于粗糙集-遗传算法的山岭隧道坍塌易发性评价[J]. 水利与建筑工程学报, 2023, 21(3): 209-215.
Zhang Liang, Sun Yongxin, Wang Xiaorui, et al. Collapse susceptibility evaluation of mountain tunnel based on rough set-genetic algorithm[J]. Journal of Water Resources and Architectural Engineering, 2023, 21(3): 209-215.
[9]
Pawlak Z, Skowron A. Rudiments of rough sets[J]. Information Sciences, 2007, 177(1): 3-27.
[10]
Yao Y, Liu Y, Yu Y, et al. K-SVM: An effective SVM algorithm based on K-means clustering[J]. Journal of Computer Science and Technology, 2013, 8(10): 2632-2639.
[11]
Su H, Wen Z, Sun X, et al. Rough set-support vector machine-based real-time monitoring model of safety status during dangerous dam reinforcement[J]. International Journal of Damage Mechanics, 2017, 26(4): 501-522.
[12]
Xi J, Guo H, Tian J, et al. A classification and recognition model for the severity of road traffic accident[J]. Advances in Mechanical Engineering, 2019, 11(5): 1687814019851893.
[13]
Liu H, Dong Y, Wang F. Gas outburst prediction model using rough set and support vector machine[J]. Evolutionary Intelligence, 2020, 15(4): 2445-2453.
[14]
Pawlak Z. Rough set[J]. International Journal of Computer and Information Sciences, 1982, 11(1): 341-356.
[15]
陈舞, 张国华, 王浩, 等. 基于粗糙集条件信息熵的山岭隧道坍塌风险评价[J]. 岩土力学, 2019, 40(9): 3549-3558.
Chen Wu, Zhang Guohua, Wang Hao, et al. Risk assessment of mountain tunnel collapse based on rough set andconditional information entropy[J]. Rock and Soil Mechanics, 2019, 40(9): 3549-3558.
[16]
何万才, 赵俊三, 林伊琳, 等. 基于证据权和支持向量机模型的威信县滑坡易发性评价[J]. 科学技术与工程, 2023, 23(15): 6350-6360.
He Wancai, Zhao Junsan, Lin Yilin, et al. Landslide susceptibility assessment in Weixin County based on evidence weight and support vector machine model[J]. Science Technology and Engineering, 2023, 23(15): 6350-6360.
[17]
戴思薇, 吴小俊, 高翠芳. 多核模糊聚类[J]. 计算机工程与应用, 2014, 52(2): 65-69.
Dai Siwei, Wu Xiaojun, Gao Cuifang. Multiple kernel fuzzy clustering[J]. Computer Engineering and Applications, 2014, 52(2): 65-69.
[18]
重庆交通科研设计院.公路隧道设计规范: JTG D70—2004[S]. 北京: 人民交通出版社, 2004.
Chongqing Communications Technology Research and Design.Code for design of road tunnel: JTG D70—2004[S]. Beijing: China Communications Press, 2004.
[19]
Ou G Z, Jiao Y Y, Zhang G H, et al. Collapse risk assessment of deep-buried tunnel during construction and its application[J]. Tunnelling and Underground Space Technology, 2021, 115: 104019.
[20]
Zhang G H, Jiao Y Y, Chen L B, et al. Analytical model for assessing collapse risk during mountain tunnel construction[J]. Canadian Geotechnical Journal, 2016, 53(2): 326-342.
[21]
Li S, Liu B, Xu X, et al. An overview of ahead geological prospecting in tunneling[J]. Tunnelling and Underground Space Technology, 2017, 63: 69-94.
[22]
Liu B, Zhang F, Li S, et al. Forward modelling and imaging of ground-penetrating radar in tunnel ahead geological prospecting[J]. Geophysical Prospecting, 2018, 66(4): 784-797.
[23]
陈礼彪. 山岭隧道施工期安全风险评价方法研究[D]. 武汉: 武汉大学, 2014.
Chen Libiao. Study on the safety risk assessment method ofmountain tunnel during construction[D]. Wuhan: Wuhan University, 2014.
[24]
曹更任, 蒋树屏, 谭秀梅, 等. 地质雷达与TGP206在楚阳隧道超前地质预报中的应用[J]. 公路交通科技, 2012, 29(12): 107-113.
Cao Gengren, Jiang Shuping, Tan Xiumei, et al. Application of ground penetrating radar and TGP206 in advanced geological forecast for Chuyang Tunnel[J]. Journal of Highway and Transportation Research and Development, 2012, 29(12): 107-113.
[25]
周峰. 山岭隧道塌方风险模糊层次评估研究[D]. 长沙: 中南大学, 2008.
Zhou Feng. Study on fuzzy hierarchy assessment of mountain tunnel collapse risk[D]. Changsha: Central South University, 2008.
[26]
张天宇, 鲁义, 施式亮, 等. 基于支持向量机分类算法的多煤种煤自燃危险性预测[J]. 湖南科技大学学报(自然科学版), 2019, 34 (2): 11-17.
Zhang Tianyu, Lu Yi, Shi Shiliang, et al. Prediction on coal spontaneous combustion risk for multi-coal based on SVM[J]. Journal of Hunan University of Science and Technology (Natural Science Edition), 2019, 34(2): 11-17.
2025年第25卷第3期
PDF下载
287
111
引用本文
BibTeX
文章信息
doi: 10.12404/j.issn.1671-1815.2309307
  • 接收时间：2023-11-27
  • 首发时间：2025-07-29
  • 出版时间：2025-01-28
补充材料
相关文章
文章信息
作者
出版历史
  • 收稿日期：2023-11-27
  • 修回日期：2024-07-09
基金
国家自然科学基金(52168055)
国家自然科学基金(52278397)
江西省自然科学基金(20212ACB204001)
江西省“双千计划”创新领军人才项目(jxsq2020101001)
江西省研究生创新专项基金(YC2022-B179)
作者信息
    1.东华理工大学土木与建筑工程学院, 南昌 330000
    2.东华理工大学水资源与环境工程学院, 南昌 330000

通讯作者:

* 曾佳佳(1991—),女,汉族,湖南邵阳人,博士研究生。研究方向:地下与隧道工程。E-mail:。
参考文献
分享链接
https://castjournals.cast.org.cn/joweb/kxjsygc/CN/10.12404/j.issn.1671-1815.2309307
分享至
全文二维码

扫描看全文

引用本文
BibTeX
本文的引用情况
2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
相关链接
论文
最新文章
热读文章
热点专题
内参
蓝皮书
产业发展报告
传播力报告
期刊分级目录
资讯
学术新闻
行业新闻
学术会议
行业会议
关于
关于我们
联系我们
北京市海淀区学院南路86号
100081
010-62199257
qkjq@cast.org.cn

中国科学技术协会版权所有 京ICP 备10216604号-4 海淀分局备案 1101084647
科技导报社主办 中国科协信息中心技术支持