• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.2
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• pp.1-18
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• 1989

콘태이너 선박은 출발항과 종착항의 두항구 사이를 잇는 지정된 항로를 오가면서 항로의 중도에 있는 각 항구에 기항하여 화물을 상.하역하는 형태로 각 항구 사이의 화물운송을 수행한다. 이때 이윤을 최대화 하기 위해서 선박을 어느 항구에 기항하고, 또 기항하는 항구에서는 얼마만큼의 화물을 항.하역할 것인지를 적절하게 결정해야 한다. 이러한 콘테이너 선박 운항경로 문제를 모형화 하고, 0-1 혼합정수 계획법을 이용한 수리모형을 제시한 후, 최소비용 흐름문제와 분지한계 기법을 이용한 최적해법을 제시하였다. 본 논문에서는 제시한 해법에서는 먼저, 기항하기로 한 항구의 집합에 따라 부분문제를 정의한다. 또한 분해된 부분문제에서 추가로 기항할 항구들에 대한 운항구간의 적제 한계와 운항비용을 완화시킨 문제를 정의하고, 그것을 다시 최소비용흐름문제를 이용하여 풀어서 상한값ㄹ 구한다. 이와 같은 방법으로 각 부분문제의 하한값과 하한값을 계신히여, 그것을 이용하여 분지를 절단하고, 또한 상한값이 높은 부분문제를 우선적으로 선택하여 분지합으로써 최적해를 구한다.

• Journal of Korean Society for Quality Management
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• v.27 no.2
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• pp.112-125
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• 1999

In a robust regression model, it is typically assumed that the errors are normally distributed. However, what if the error distribution is deviated from the normality and the response variables are not completely observable due to censoring? For complete data, Kim and Lai(1998) suggested a new adaptive M-estimator with an asymptotically efficient score function. The adaptive M-estimator is based on using B-splines to estimate the score function and simple cross validation to determine the knots of the B-splines, which are a modified version of Kun( 1992). We herein extend this method to right-censored data and study how well the adaptive M-estimator performs for various error distributions and censoring rates. Some impressive simulation results are shown.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.590-597
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• 2002

LNG고압펌프계통은 천연가스 고압 송출에 있어 가용도가 매우 중요한 계통이다. 본 연구에서는 현재 적용되고 있는 예방(계획)정비주기를 가용성 측면에서 재검토했다. 확률적인 운전대수와 운전 및 보전 형태에 연관된 여러제약이 고려할 때 계통 불가용도를 정량화하기 위하여 시뮬레이션 기법을 적용했다. 중도 절단된 형태의 펌프 수명 데이터를 분석해 욕조형의 고장율 함수를 도출했으며 보수시간 데이터를 분석해 확률분포모수를 구했다. 또한 주요 펌프부대설비에 대해서는 상수형의 고장율과 보전율을 도출했다. 분석된 확률모수를 작성된 시뮬레이션 모형에 입력하고 과거의 운전대수 시나리오를 설정해 실험한 결과와 실제 보수 및 운전 자료를 비교해 모형의 유효성을 보였다. 그리고 차후 예상되는 운전요구대수 시나리오를 기정하고 각 예방정비주기별로 반복 실험하여 계통의 불가용도를 보이고 적합한 예방정비주기를 도출했으며 펌프부품 교체비용의 기대 절감액을 보였다.

• Journal of the Korean Data and Information Science Society
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• v.22 no.1
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• pp.89-97
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• 2011

The aims of this study were to propose a method of estimation for mean residual life function (MRLF) from conditional survival function using the Buckley and James's (1979) pseudo random variables, and then to assess the performance of the proposed method through the simulation studies. The mean squared error (MSE) of proposed method were less than those of the Cox's proportional hazard model (PHM) and Beran's nonparametric method for non-PHM case. Futhermore in the case of PHM, the MSE's of proposed method were similar to those of Cox's PHM. Finally, to evaluate the appropriateness of practical use, we applied the proposed method to the gastric cancer data. The data set consist of the 1, 192 patients with gastric cancer underwent surgery at the Department of Surgery, K-University Hospital.

• Journal of Korean Society of Transportation
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• v.33 no.2
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• pp.125-135
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• 2015

In this study our main focus is to verify the relationship between social value of transportation system and its perceived features. To achieve this objective, we investigated the value of public bike system (PBS) through willingness to pay (WTP) analysis using contingent valuation method (CVM) and the survey was conducted for 1726 respondents who live in Suwon, Korea. Moreover the determinants related to features related to bicycle use were also gathered. The estimated binary logistic regression and censored regression reveal that the value of PBS is influenced by perceived features towards bicycle use incorporating non-congestion, transportation mode like auto and bus, and high mobility system as well as other variables such as income, bicycle ownership etc. Furthermore the results show that the perceiving of positive features to bicycle use leads to higher social value of PBS. Based on the findings, we discuss the importance of pre-review for transport policy implementation, and also explore the possibilities for application to PBS.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.777-789
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• 2020

COVID-19 has been rapidly spread world wide since late December 2019. In this paper, our interest is to estimate distribution of incubation time defined as period between infection of virus and the onset. Due to the limit of accessibility and asymptomatic feature of COVID-19 virus, the exact infection and onset time are not always observable. For estimation of incubation time, interval censoring technique is implemented. Furthermore, a competing risk model is applied to estimate the case fatality and cure fraction. Based on the result, the mean incubation time is about 5.4 days and the fatality rate is higher for older and male patient and the cure rate is higher at younger,female and asymptomatic patient.

• Journal of the Korean Data and Information Science Society
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• v.8 no.2
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• pp.183-194
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• 1997

In accelerated life tests, the failure time of an item is observed under a high stress level and based on the time, the failure rates of items we estimated at the normal stress level. In this paper, when the mean of the prior distribution of a parameter is known in Weibull lifetime model with censored failure time data, we study various estimating methods to obtain the empirical Bayes estimator of a parameter from the empirical Bayes approach under the normal stress level by considering the fact that the Bayes estimator is the function of prior parameters and of the acceleration parameter representing the effect of acceleration. And we compare the performance of several empirical Bayes estimators of a parameter in terms of the Bayes risk.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.427-436
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• 2000

In this paper, we consider a Bayesian model selection problem of lifetime distributions using fractional Bayes factor with noninformative prior when type II censored data are given. For a given type II censored data, we calculate the posterior probability of exponential, Weibull and lognormal distributions and select the model which gives the highest posterior probability. Our proposed methodology is explained and applied to real data and simulated data.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1045-1054
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• 2012

Support vector machine is known to be the very useful statistical method in classification and nonlinear function estimation. In this paper we propose a monotone support vector regression (SVR) for the estimation of monotonically decreasing function. The proposed monotone SVR is applied to smooth the Kaplan-Meier estimate of survival function. Experimental results are then presented which indicate the performance of the proposed monotone SVR using survival functions obtained by exponential distribution.

• Journal of Korea Water Resources Association
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• v.52 no.9
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• pp.627-635
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• 2019

In Korea, snow damage has been happened in the region with no snowfalls in history. Also, casual damage was caused by heavy snow. Therefore, policy about the Natural Disaster Reduction Comprehensive Plan has been changed to include the mitigation measures of snow damage. However, since heavy snow damage was not frequent, studies on snowfall have not been conducted in different points. The characteristics of snow data commonly are not same to the rainfall data. For example, some parts of the southern coastal areas are snowless during the year, so there is often no values or zero values among the annual maximum daily snow accumulation. The characteristics of this type of data is similar to the censored data. Indeed, Busan observation sites have more than 36% of no data or zero data. Despite of the different characteristics, the frequency analysis for snow data has been implemented according to the procedures for rainfall data. The frequency analysis could be implemented in both way to include the zero data or exclude the zero data. The fitness of both results would not be high enough to represent the real data shape. Therefore, in this study, a methodology for selecting a probability density function was suggested considering the characteristics of snow data in Korea. A method to select probability density function using conditional joint probability distribution was proposed. As a result, fitness from the proposed method was higher than the conventional methods. This shows that the conventional methods (includes 0 or excludes 0) overestimated snow depth. The results of this study can affect the design standards of buildings and also contribute to the establishment of measures to reduce snow damage.