• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1350-1358
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• 2008

Recently the study related to life cycle cost analysis of railway structure consisted of a complex is proceeded covering several range, which is considering the methodology of efficiency and rationalization for maintenance and analysing long-time behavior of the structure of looking at standpoint from asset management and safety. But LCCA(life cycle cost analysis) of railway structure was almost impossible as there were not anything datum for maintenance plan, such as maintenance periods related to each of components(painting and corrosion of steel, and cracking of elements, etc)and maintenance proportion, despite of its 100-year history. According, for collecting data related to railway truss bridge, bridge record cards and testing safety papers, and researching question, etc are surveyed and classified for LCC Analysis. Especially, LCC assessment on the side of assets-maintenance considering about initial cost, maintenance cost, and indirect cost is constructed. Maintenance period and complementary measure rate are very important in maintenance. To decide maintenance period, Baysian updating method is applied.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.3
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• pp.105-122
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• 1995

Based on linear models, the inference about the true measurement x$_{f}$ and the optimal designs x (nx1) for the calibration experiments are considered via Baysian statistical decision analysis. The posterior distribution of x$_{f}$ given the observation y$_{f}$ (qxl) and the calibration experiment is obtained with normal priors for x$_{f}$ and for themodel parameters (.alpha., .betha.). This posterior distribution is not in the form of any known distributions, which leads to the use of a numerical integration or an approximation for the calculation of the overall expected loss. The general structure of the expected loss function is characterized in the form of a conjecture. A near-optimal design is obtained through the approximation nof the conditional covariance matrix of the joint distribution of (x$_{f}$ , y$_{f}$ $^{T}$ )$^{T}$ . Numerical results for the univariate case are given to demonstrate the conjecture and to evaluate the approximation.n.

• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.365-376
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• 2003

In this paper we reviewed a variety of non-Gaussian time series models, and studied the model selection criteria such as AIC and BIC to select proper models. We also considered the likelihood ratio test and applied it to analysis of Polio data set.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.154-156
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• 2002

인터넷의 발전으로 우리는 많은 정보와 지식을 인터넷에서 제공받을 수 있으며 HTML, 뉴스그룹 문서, 전자메일 등의 웹 문서로 존재한다. 이러한 웹 문서들은 여러가지 목적으로 분류해야 할 필요가 있으며 이를 적용한 시스템으로는 Personal WebWatcher, InfoFinder, Webby, NewT 등이 있다. 웹 문서 분류 시스템에서는 문서분류 기법을 사용하여 웹 문서의 소속 클래스를 결정하는데 문서분류를 위한 기법 중 대표적인 알고리즘으로 나이브 베이지안(Naive Baysian), k-NN(k-Nearest Neighbor), TFIDF(Term Frequency Inverse Document Frequency)방법을 이용한다. 본 논문에서는 웹 문서를 대상으로 이러한 문서분류 알고리즘 각각의 성능을 비교 및 평가하고자 한다.

• Environmental and Resource Economics Review
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• v.11 no.4
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• pp.609-632
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• 2002

국민소득이 빠르게 증가함에 따라 1990년대 이후 가정용 난방연료의 소비구조 역시 크게 변화하고 있다. 본 연구는 에너지 및 교통수요분석에 많이 사용되는 Multinomial Probit 모형을 이용하여 가정용 난방연료의 선택 행태를 분석하였다. 모형의 추정방법으로는 베이지안(Baysian) 방법론에 의한 Gibbs Sampling기법 (McColluch et al., 2000)을 이용하여 Multinomial probit 모형에서 선택대안이 3개 이상일 경우 발생할 수 있는 추정상의 어려움을 극복하였다. 한국가구패널조사(KHPS) 자료를 이용하여 서울과 경기도 대도시 지역을 대상으로 분석한 결과, 석유와 천연가스가 연탄에 비해 더 밀접한 상호 대체관계를 가지고 있는 것으로 나타났다. 또한 소득이 높은 가구일수록 천연가스에 대한 선호도가 더 높은 것으로 나타나서 향후 공급망 확대에 따라 난방연료용 가스 소비가 더욱 늘어날 것으로 예상된다.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1786-1797
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• 2010

Automatic understanding of contents in document image is a very hard problem due to involvement with mathematically challenging problems originated mainly from the over-determined system induced by document segmentation process. In both academic and industrial areas, there have been incessant and various efforts to improve core parts of content retrieval technologies by the means of separating out segmentation related issues using semi-structured document, e.g., invoice,. In this paper we proposed classification models for text lines on invoice document in which text lines were clustered into the five categories in accordance with their contents: purchase order header, invoice header, summary header, surcharge header, purchase items. Our investigation was concentrated on the performance of machine learning based models in aspect of linear-discriminant-analysis (LDA) and non-LDA (logic based). In the group of LDA, na$\"{\i}$ve baysian, k-nearest neighbor, and SVM were used, in the group of non LDA, decision tree, random forest, and boost were used. We described the details of feature vector construction and the selection processes of the model and the parameter including training and validation. We also presented the experimental results of comparison on training/classification error levels for the models employed.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.6
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• pp.973-980
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• 2011

In this paper, we gaze upon the movement faces the problem points are difficult to identify a user based on points and that corrective action is needed to solve the identification system is proposed a new eye. Kalman filter, the current head of the location information was used to estimate the future position in order to determine the authenticity of the face facial features and structural elements, the information and the processing time is relatively fast horizontal and vertical elements of the face using the histogram analysis to detect. And an infrared illuminator obtained by constructing a bright pupil effect in real-time detection of the pupil, the pupil was tracked - geulrinteu vectors are extracted.

• Journal of Korean Society of Transportation
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• v.22 no.4 s.75
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• pp.31-42
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• 2004

This study develops Accident Modification Factors (AMF) of countermeasures with Baysian method which are newly proposed for reducing Roadway-Rail grade crossing accidents. This study proposes a new "Bayesian Analytical Framework" for countermeasure assessment which combines "Subjective" Prior Information with "Logical" based Information. The newly proposed "Bayesian Analytical Framework" consists of the following three steps: The 1st step - Countermeasure Selection, Choice of Participants, Selection of Crashes; The 2nd step-Development of Crash History Manual and Countermeasure Evaluation Manual; The 3rd step-Development of AMFs through sound statistical tests. This study used the Komogorov-Smirnov(K-S) Test to determine whether two unknown distribution functions associated with the two populations are identical. The results of the study are that individual responses did not meet the K-S test of identical distributions. while individual vs. group distributions are identical. This indicates that combining the input of several people reduces the impact of individual subjectivity and assumptions and is important for developing a repeatable distribution to develop sound AMFs of countermeasures for reducing Roadway-Rail grade crossing accidents. The procedures of the AMF development conducted in this study can be used to estimate the safety effects of countermeasures for road segments and intersections, in addition to Roadway-Rail grade crossings.

• Journal of the Korean Geotechnical Society
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• v.21 no.3
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• pp.109-118
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• 2005

It is a very difficult task to estimate engineering properties of the ground when designing underground structures, especially in tunnelling. Therefore, a feed-back system to combine the data measured in construction field with priorly estimated information at the design stage is necessary. In this paper, 3-dimensional back-analysis in tunnelling, to which only relative convergence is applied as input values, is carried out to estimate the optimum geotechnical parameters. For this purpose, the Extended Bayesian Method (EBM), which appropriately combines the objective information with the subjective one, is applied to optimize engineering parameters and 3-dimensional numerical analysis is carried out to predict a trend of relative convergence occurrence. The data measured from two tunnelling sites are used to verify the applicability of the proposed back-analysis technique. from the results of analysis, the proposed back-analysis technique is verified.

• Journal of the Korean Geotechnical Society
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• v.21 no.3
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• pp.99-108
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• 2005

One of the most important and difficult tasks in designing underground structure is the estimation of engineering properties of the ground. The main purpose of this study is to propose a new back-analysis technique in tunnelling to estimate geotechnical parameters around a tunnel. In this study, the Extended Bayesian Method, which appropriately combines objective information with subjective one, is adopted to optimize engineering parameters. By using only relative convergence data measured during tunnelling as input values in back-analysis, inevitable errors in absolute convergence estimation are excluded and 3-dimensional numerical analysis is applied to consider a trend of relative convergence occurrence. Finally, 3-dimensional back-analysis technique using relative convergence is proposed and evaluated using a hypothetical site.