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标题：Tunnels stability analysis using binary and multinomial logistic regression (LR)
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作者：R. Rafiee ; M. Ataei ; M. Kamali 等
期刊名称：Journal of Geology and Mining Research
电子版ISSN：2006-9766
出版年度：2013
卷号：5
期号：4
页码：97-107
DOI：10.5897/JGMR2013.0176
语种：English
出版社：Academic Journals
摘要：One of the most serious problems in tunneling projects are falling rock blocks. By considering this fact, the importance of stability predicting using some input parameters can be obviously understood. Among the existing rock mass classification systems for underground structures, rock mass rating (RMR) and Q are probably the most widely used ones this is rather unlikely to change, at least in the near future, frequently used and more available in tunneling projects, therefore establishing a proper and valid stability method based on such items would be useful. Since none of them (RMR and Q) can reflect the tunnel stability condition entirely and each has some lacks in rock mass properties defining, therefore both of them were used in this analysis which can provide the whole perspective of rock mass condition and stability. For this aim, data (RMR, Q, and hydraulic radius) from 104 cases of eight tunnel projects were gathered. By observing the stability condition in each tunnel, the data were classified in three categories: stable, potentially unstable and unstable. Two models next were defined and the related formulas were found using binary and multinomial logistic regression, at last the best predictor model would be selected by using the percent of correctly predicted cases in each model. The results of this paper show that the logistic regression (LR) is a robust tool to establish and develop predicting model for tunneling projects and can assist engineers to predict the stability condition of tunnels.
关键词：Logistic regression;tunneling;rock mass classification;stability