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Fuzzy C-means 클러스터링 기법을 이용한 콘 관입 데이터의 해석
우철웅,장병욱,원저윤 한국농공학회 2003 한국농공학회논문집 Vol.45 No.3
Methods of fuzzy C-means have been used to characterize geotechnical information from static cone penetration data. As contrary with traditional classification methods such as Robertson classification chart, the FCM expresses classes not conclusiveness but fuzzy. The results show that the FCM is useful to characterize ground information that can not be easily found by using normal classification chart. But optimal number of classes may not be easily defined. So, the optimal number of classes should be determined considering not only technical measures but engineering aspects.
우철웅,장병욱 한국농공학회 2003 한국농공학회논문집 Vol.45 No.6
Most construction works on the soft ground adopt instrumentation to manage settlement and stability of the embankment. The rapid progress of the information technologies and the digital data acquisition on the soft ground instrumentation has led to the fast-growing amount of data. Although valuable information about the behaviour of the soft ground may be hiding behind the data, most of the data are used restrictedly only for the management of settlement and stability. One of the critical issues on soft ground instrumentation is the long-term settlement prediction. Some observational settlement analysis methods are used for this purpose. But the reliability of the analysis results is remained in vague. The knowledge could be discovered from a large volume of experiences on the observational settlement analysis. In this article, we present a database to store settlement records and data mining procedure. A large volume of knowledge about observational settlement prediction were collected from the database by applying the filtering algorithm and knowledge discovery algorithm. Statistical analysis revealed that the reliability of observational settlement analysis depends on stay duration and estimated degree of consolidation.
우철웅,장병욱 한국농공학회 2003 한국농공학회논문집 Vol.45 No.5
Observational methods such as the Asaoka's method and the hyperbolic method are widely applied on the settlement analysis using observed settlement. The most unreliable aspects in those methods is arose from the subjective discretion of initial non-linearity on linear regression. The initial non-linearity is inevitable due to the settlement behaviour itself. Therefore an objective method is essential to achieve more reliable results on settlement analysis. It was found that the initial non-linear data are statistical outliers. New automation algorithms of the hyperbolic and the Asaoka's method were developed based on outlier detection method. The methods are a successive detection of outliers and a searching method of suitable hyperbolic range for the Asaoka's and the hyperbolic method respectively. Applicability of the algorithms was verified through case studies.
연약지반 계측관리를 위한 지능형 데이터베이스 시스템 개발
우철웅 ( Woo Chull Woong ),장병욱 ( Chang Pyoung Wuck ) 한국농공학회 1999 한국농공학회 학술대회초록집 Vol.1999 No.-
For many soft ground embankment projects, instrumentation programs for stability and setttlement management is being essential. This usually leads to generate large volume of data, which can be used for further research. Database technique is most effective method for data management. Data produced by soft ground embankment instrumentation can not be used by itself but must be reproduced using geotechnical analysis technique. In this study, a intelligent database system for softground called IDSIM was developed to examine applicability intellgent database. The IDSIM analysis instrumenation data automatically and present results by Web/DB interface successfully.
우철웅 ( Woo Chull-woong ),장병욱 ( Chang Pyoung-wuck ) 한국농공학회 2003 한국농공학회 학술대회초록집 Vol.2003 No.-
In this study, a grouping of particle-size distributions(PSDs) by means of the fuzzy c-means clustering method(FCM) was presented. The classification was performed with the whole and the major soil series representing pedological origin. In case of the major soil series, PSDs were clustered as 2-4 groups and the characteristics of clustering results were quite different between the soil series. It was found that the characteristics of PSDs at center of each class can be explained by formation process of each soil series. In case of whole soil data, PSDs were classified to 8 classes in which 4 classes were single mode and 4 classes were bimode distributions. Through this study, it is concluded that pedogenetic process is a plausible explanation for grain size distribution of soils.
우철웅 ( Woo Chull Woong ),장병욱 ( Chang Pyoung Wuck ),송창섭 ( Song Chang Sub ) 한국농공학회 1996 韓國農工學會誌 : 전원과 자원 Vol.38 No.6
The theory of consolidation has been achieved remarkable development in terms of theory such as finite consolidation theory, two dimensional Rendulic consolidation theory. Though those theories are well defined, the analysis is by no means straightforward, because associated properties are very difficult to determine in the laboratory, Therefore Terzaghi's one dimensional consolidation theory and Barron's cylindrical consolidation theory are still widely used in engineering practice. The theoretical shortcomings of those consolidation theories and uncertainties of associated properties make inevitably some discrepancy between theoretical and field settlements. Field settlement measurement by settlement plate is, therefore, widely used to overcome the discrepancy. Ultimate settlement is one of the most important factor of embankment construction on soft soils. Nowadays the ultimate settlement prediction methods using field settlement data are widely accepted as a helpful tool for field settlement analysis of embankment construction on soft soils. Among the various methods of ultimate settlement prediction, hyperbolic method and Asaoka's method are most commonly used because of their simplicity and ability to give a reasonable estimate of consolidation settlement. In this paper, the reliability of hyperbolic method and Asaoka's method has been examined using analytical methods. It is shown that both hyperbolic method and Asaoka's method are significantly affected by the direction of drainage.
우철웅 ( Woo Chull Woong ),장병욱 ( Chang Pyoung Wuck ) 한국농공학회 2003 韓國農工學會誌 : 전원과 자원 Vol.45 No.6
Most construction works on the soft ground adopt instrumentation to manage settlement and stability of the embankment. The rapid progress of the information technologies and the digital data acquisition on the soft ground instrumentation has led to the fast-growing amount of data. Although valuable information about the behaviour of the soft ground may be hiding behind the data, most of the data are used restrictedly only for the management of settlement and stability. One of the critical issues on soft ground instrumentation is the long-term settlement prediction. Some observational settlement analysis methods are used for this purpose. But the reliability of the analysis results is remained in vague. The knowledge could be discovered from a large volume of experiences on the observational settlement analysis. In this article, we present a database to store settlement records and data mining procedure. A large volume of knowledge about observational settlement prediction were collected from the database by applying the filtering algorithm and knowledge discovery algorithm. Statistical analysis revealed that the reliability of observational settlement analysis depends on stay duration and estimated degree of consolidation.