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Fuzzy Clustering Method for the Identification of Joint Sets  

정용복 (서울대학교 공학연구소)
전석원 (서울대학교 지구환경시스템공학부)
Publication Information
Tunnel and Underground Space / v.13, no.4, 2003 , pp. 294-303 More about this Journal
Abstract
The structural behaviour of rock mass structure, such as tunnel or slope is critically dependent on the various characteristics of discontinuities. Therefore, it is important to survey and analyze discontinuities correctly for the design and construction of rock mass structure. One inevitable Procedure of discontinuity survey and analysis is joint set identification from a lot of raw directional joint data. The identification procedure is generally done by a graphical method. This type of analysis has some shortcomings such as subjective identification results, inability to use extra information on discontinuity, and so on. In this study, a computer program for joint set identification based on the fuzzy clustering algorithm was implemented and tested using two kinds of joint data. It was confirmed that fuzzy clustering method is effective and valid for joint set identification and estimation of mean direction and degree of clustering of huge joint data through the applications.
Keywords
fuzzy K-meat orientation matrix; distance measure; joint set identification;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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