Article(id=1242117228997444159, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242117211490419171, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1246377600000, receivedDateStr=2009-07-01, revisedDate=1250006400000, revisedDateStr=2009-08-12, acceptedDate=null, acceptedDateStr=null, onlineDate=1254067200000, onlineDateStr=2009-09-28, pubDate=1254067200000, pubDateStr=2009-09-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1254067200000, onlineIssueDateStr=2009-09-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774073424812, creator=sys-migrate, updateTime=1774073424812, updator=sys-migrate, issue=Issue{id=1242117211490419171, tenantId=1146029695717560320, journalId=1146031591421210625, year='2009', volume='27', issue='0918', pageStart='3', pageEnd='140', issueExtLink='null', onlineDate='null', pubDate='1254067200000', pubDateStr='2009-09-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=3, issueType=-1, specialIssue=null, createTime=1774073420636, creator='sys-migrate', updateTime=1774073420636, updator='sys-migrate', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=78, endPage=81, ext={EN=ArticleExt(id=1242117234642977364, articleId=1242117228997444159, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Prediction of Possibility and the Level of Rockburst Based on Uncertain Average Gradted Analysis Method, columnId=1242116080374710456, journalTitle=Science & Technology Review, columnName=Articles, runingTitle=null, highlight=null, articleAbstract=To solve the uncertain problems in rockburst prediction, uncertain average graded analysis method is applied to predict the level of rockburst. Uncertain average graded analysis model is first established for the prediction of possibility and the level of rockburst. Four indexes such as the maximum tangential stress of the cavern wall, uniaxial compressive strength, uniaxial tensile strength, and the elastic energy index are selected as the factors for synthetic evaluation of rockburst. The indexes criteria are determined by averages of each graded sample. The intensity of rockburst is divided into four grades that are considered as four normal populations in uncertain average graded analysis. Uncertain functions are obtained by indexes criteria. Uncertain average graded analysis model were obtained through training a series of underground rock projects both at home and abroad. The faith judgment criterion is used to judge which grade the evaluating sample belongs to. The processes of the proposed method are given. The proposed model is verified by the back substitution method. Results show that the back-test-correct rate is high. The proposed model is applied to two practical projects of tunnel and mine. Cases study shows that calculation results are consistent with actual conditions. The proposed model could be used widely in practical engineering., authors=null, authorsList=null, authorCompany=null, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=pqGE9pYxgn4Uljs5LPO1tQ==, pdfFileSize=355178, 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=1242117232583578588, articleId=1242117228997444159, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=基于未确知均值分类理论的岩爆发生和分级预测方法, columnId=1146540929516700224, journalTitle=科技导报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=为解决岩爆预测中的不确定性问题，将未确知均值分类理论应用于岩爆综合评判中，建立了岩爆发生和分级预测的未确知均值分类理论分析模型。模型选用最大切应力、单轴抗压强度、单轴抗拉强度和弹性能量指数4个指标作为岩爆发生和分级预测的判别因子。将岩爆烈度分为4个等级并作为未确知均值分类理论分析的4个类别。以国内外岩爆工程实测数据作为建立分类标准和模型的样本，以各等级的指标均值作为分类标准，求取未确知测度函数。采用信息熵确定权重，用置信度识别准则进行等级判定。将本研究建立的模型应用到隧道和矿山工程的岩爆预测中，结果表明，未确知均值分类分级预测方法预测结果与实际情况吻合较好，预测精度高，因而是岩爆发生和分级预测的一种有效方法，可在岩爆工程判别中应用和推广。, authors=王兴明¹,董陇军²,付玉华^1,2, authorsList=王兴明;董陇军;付玉华;, authorCompany=1. 江西理工大学应用科学学院2. 中南大学资源与安全工程学院, correspAuthors=null, authorNote=null, correspAuthorsNote=董陇军, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=zzS3dnmiNX9LWPVkFBbF8w==, pdfFileSize=355178, 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)}, authors=null, keywords=[Keyword(id=1242117232281588697, tenantId=1146029695717560320, 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