首页 | 本学科首页   官方微博 | 高级检索  
     

基于判别分析法的岩爆烈度预测研究
引用本文:景杨凡,陈玉明,李岳峰,张海涛,杨荣森. 基于判别分析法的岩爆烈度预测研究[J]. 有色金属(矿山部分), 2022, 74(1): 97-102
作者姓名:景杨凡  陈玉明  李岳峰  张海涛  杨荣森
作者单位:昆明理工大学国土资源工程学院
摘    要:岩爆是岩土工程中棘手的地质灾害,工程中以预防为主。现有岩爆分级预测模型大多存在选取样本较少和准确率较低的问题。综合岩爆的参考指标,现选取围岩最大切向应力与岩石单轴抗压强度比σ_θ/σc(应力系数)、岩石单轴抗压强度与单轴抗拉强度比σct(脆性系数)和弹性能量指数Wet作为分级评判指标,广泛收集不同工程的104组岩爆实例,选取其中84组作为样本集进行训练,20组作为测试集进行检验,应用SPSS的判别分析中的Bayes判别和Fisher判别训练及测试,输出结果中,选取了训练效果较好的Bayes判别模型。对95.23%的样本集进行了正确分类,验证集检验准确率为85%,将该模型应用于工程实例中,预测结果与实际结果相符,预测结果表明该模型有较好的应用前景。

关 键 词:岩爆  判别分析模型  分级预测  SPSS  Bayes判别模型  Fisher判别训练  分级评判指标
收稿时间:2021-07-20
修稿时间:2021-07-30

Study on rockburst prediction based on discriminant analysis method
JING Yangfan,CHEN Yuming,LI Yuefeng,ZHANG Haitao and YANG Rongsen. Study on rockburst prediction based on discriminant analysis method[J]. , 2022, 74(1): 97-102
Authors:JING Yangfan  CHEN Yuming  LI Yuefeng  ZHANG Haitao  YANG Rongsen
Affiliation:(Faculty of Land Resources Engineering,Kunming University of Science and Technology,Kunming 650093,China)
Abstract:Rockburst is a difficult geological hazard in geotechnical engineering,and prevention is the main focus in engineering.Most of the existing rockburst classification prediction models have the problems of small sample selection and low accuracy.Combined with the comprehensive reference indexes of rock burst,the maximum tangential stress of surrounding rock and rock uniaxial compressive strengthσθ/σc(stress coefficient),rock uniaxial compressive strength and uniaxial tensile strengthσc/σt(brittleness coefficient)and the elastic energy index of Wet were selected as grading evaluation indexes,different engineering 104 groups of rock burst were widely collected as examples,84 groups were selected as the training sample set,the group of 20 was used for the test in the test set,Bayes discriminant of discriminant analysis of SPSS and Fisher discriminant were applied to train and test,and the better training effect the Bayes discriminant model was selected from the output.95.23%of the sample sets were correctly classified,and the accuracy of verification set was 85%.When the model was applied to an engineering example,the predicted results were consistent with the actual results.The predicted results showed that the model had a good application prospect.
Keywords:rockburst  discriminant analysis model  classification prediction  SPSS  Bayes discriminant model  Fisher discriminant  grading evaluation index
本文献已被 维普 等数据库收录!
点击此处可从《有色金属(矿山部分)》浏览原始摘要信息
点击此处可从《有色金属(矿山部分)》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号