• 품질경영학회지
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• 제26권2호
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• pp.39-50
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• 1998

A screening procedure, where one or more correlated variables are used for screeing, is reviewed from the point of statistical hypothesis testing. Without assuming a specific probability model for the joint distribution of the performance and screening variables, some principles are provided to establish the best screeing region. A, pp.ication examples are provided for two cases; ⅰ) the case where the performance variable is dichotomous and ⅱ) the case where the performance variable is continuous. In case ⅰ), a normal model is assumed for the conditional distribution of the screening variable given the performance variable. In case ⅱ), the performance and screening variables are assumed to be jointly normally distributed.

• 한국연소학회:학술대회논문집
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• 한국연소학회 2015년도 제51회 KOSCO SYMPOSIUM 초록집
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• pp.267-268
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• 2015

The multi-environment probability density function model has been applied to simulate the turbulent $CH_4/H_2$ flames under MILD conditions. The direct quadrature method of moments (DQMOM) has been adopted to solve the transport PDF equation due to its computational efficiency and robustness. The IEM model represents the micromixing process. The numerical results obtained in this study are precisely compared with experimental data in terms of unconditional means and conditional means for scalar field including temperature and species mass fraction.

• Journal of the Korean Data and Information Science Society
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• 제22권6호
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• pp.1065-1074
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• 2011

1990년대 중반 이후 금융 분야에서 가장 많은 관심을 받는 연구 주제 중의 하나는 대표적인 위험측정 방법인 VaR (Value at risk)이다. VaR는 주어진 신뢰수준에서 정상적인 시장조건을 가정할 때 선택한 목표기간 동안 발생할 수 있는 포트폴리오의 최대손실액으로 정의된다. 본 논문에서는 국내 주가지수 자료를 이용한 포트폴리오에 다변량 정규분포를 이용하는 VaR 예측 방법인 단순이동평균법과 지수가중이동평균법을 고려하여 VaR를 예측한 결과와 t 분포 및 조건부 코퓰라 (Copula) 함수를 이용하여 VaR를 예측한 결과를 비교 평가하였다. 자료 분석 결과에 의하면 포트폴리오 구성 종목 간에 종속성구조와 비정규성이 존재하는 경우에 t 분포와 조건부 코퓰라 방식을 이용하여 VaR 추정의 정확도를 높일 수 있다는 결론을 얻을 수 있었다.

• 대한교통학회지
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• 제19권5호
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• pp.109-117
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• 2001

본 논문은 특정 도로조건에 대하여 어떤 형태의 중앙선침범 예방시설물을 설치할 것인가에 대한 비용-효율적인 기준 마련을 목표로 삼고, 그 첫 단계로 중앙선침범사고 예측모델을 개발하였다. 예측모델은 중앙선침범 예측과 침범후 대향차량과의 충돌 확률로 이루어진다. 중앙선침범 예측은 교통량에 관계되며, 이는 Hutchinson과 Kennedy(1966)의 연구에서 인용하였다. 중앙선을 침범한 후 대향차량과의 충돌 확률은 중앙선을 침범하는 차량의 침범각의 분포에 따라 주행거리와 주행시간을 계산하고, 음지수분포로 가정한 대향차량의 출현에 간격수락이론을 적용하였다. 제시된 중앙선침범사고 예측모델을 통하여 예측된 사고건수는 사고감소에 대한 편익을 계산할 수 있게 하며, 이는 중앙선침범예방시설 설치비용 계산과 함께 경제성분석을 가능하게 하여 비용-효율적인 중앙선침범예방시설 설치기준마련에 도움을 줄 것이다.

• 응용통계연구
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• 제23권6호
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• pp.1201-1208
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• 2010

확률과 통계 교육에서 학생들의 관심을 집중시켜 강의 효과를 높일 수 있는 예제들을 발굴하는 데 있어 많은 학자들의 꾸준한 노력이 뒤따라야 한다. 여러 분야의 예제를 제시할 수 있지만, 특히 다양한 예제들을 찾을 수 있는 분야가 스포츠이며, 그 중에서도 월드컵 축구는 여러 가지 흥미로운 문제들의 보고(寶庫)이다. 월드컵 축구대회는 전 국민적 관심사이기 때문에, 이 분야의 예제를 통한 학습 역시 확률과 통계에 대한 학생들의 관심도를 진작시킬 수 있는 효과적인 방법이라 본다. 본 논문에서는 월드컵 축구의 조별 리그와 16강 토너먼트 등의 경기 방식과 승점제 및 조편성과 관련된 경우의 수와 확률 문제들을 제시하였으며, 통계모형을 이용한 시뮬레이션을 통해 2010 남아공 월드컵을 앞둔 시점이라 가정하고 본선 진출 각 팀의 16강 진출 확률과 우승 확률을 계산하는 논리적 방법을 제안하였다.

• 한국항공운항학회지
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• 제19권4호
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• pp.74-82
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• 2011

In order to enhance the aviation industry in Korea, many strategies have been published by some researchers as well as the government. However, considering the constrained conditions in real, since the ranking of their importance has not determined yet, they are difficult to be implemented by decision makers. Therefore, in terms of their demand for deciding the significance of strategies, the evaluation model of this paper was developed. In this study, the Cross-impact Hierarchy Process(CHP), an linked model of both the Analytic Hierarchy Process(AHP) and Cross Impact Analysis(CIA), was selected as the best model. That is because the strategies are not independent from each other, and one strategy can affect the others depending on its realization, which can be considered in CHP. To achieve our objective, at first, the strategies were categorized and arranged according to the evaluation structure. Secondly, the parameters such as conditional probability and weights were estimated from the survey conducted by 16 experts in the aviation field. Lastly, the result of the assessment were discussed, and further studies were suggested.

• 산업경영시스템학회지
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• 제30권3호
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• pp.103-108
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• 2007

This paper presents the conceptual framework for estimating and predicting system's susceptibility to failure as function of condition parameter value which is representing the current status of performance measure using on-line performance reliability. The performance of such system depends on one parameter with a probability distribution that degrades with time gracefully. Performance reliability represents the probability that physical performance will remain satisfactory over a finite period of time or usage cycles in the future. An empirical physical performance function is constructed to incorporate explanatory variables (operating and environmental conditions) over a time or usage dimension. This function enables one to model device performance and the associated classical reliability measures simultaneously, in the performance domain and time domain. The conditional performance reliability structure developed represents a tool to predict system performance over time or usage for next usage period. By enabling such a framework, it can bring us more efficient planning and execution in system's operation control as well as maintenance to reduce costs and/or increase profits.

• 한국전산구조공학회논문집
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• 제23권6호
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• pp.641-649
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• 2010

Estimation of uncertain parameters is required in many engineering problems which involve probabilistic structural analysis as well as prognosis of existing structures. In this case, Bayesian framework is often employed, which is to represent the uncertainty of parameters in terms of probability distributions conditional on the provided data. The resulting form of distribution, however, is not amenable to the practical application due to its complex nature making the standard probability functions useless. In this study, Markov chain Monte Carlo (MCMC) method is proposed to overcome this difficulty, which is a modern computational technique for the efficient and straightforward estimation of parameters. Three case studies that implement the estimation are presented to illustrate the concept. The first one is an inverse estimation, in which the unknown input parameters are inversely estimated based on a finite number of measured response data. The next one is a metamodel uncertainty problem that arises when the original response function is approximated by a metamodel using a finite set of response values. The last one is a prognostics problem, in which the unknown parameters of the degradation model are estimated based on the monitored data.

• Nuclear Engineering and Technology
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• 제54권3호
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• pp.948-958
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• 2022

Since reliability and security of man-machine system increasingly depend on reliability of human, human reliability analysis (HRA) has attracted a lot of attention in many fields especially in nuclear engineering. Dependence assessment among human tasks is a important part in HRA which contributes to an appropriate evaluation result. Most of methods in HRA are based on experts' opinions which are subjective and uncertain. Also, the dependence influencing factors are usually considered to be constant, which is unrealistic. In this paper, a new model based on Dempster-Shafer evidence theory (DSET) and fuzzy number is proposed to handle the dependence between two tasks in HRA under uncertain and dynamic situations. First, the dependence influencing factors are identified and the judgments on the factors are represented as basic belief assignments (BBAs). Second, the BBAs of the factors that varying with time are reconstructed based on the correction BBA derived from time value. Then, BBAs of all factors are combined to gain the fused BBA. Finally, conditional human error probability (CHEP) is derived based on the fused BBA. The proposed method can deal with uncertainties in the judgments and dynamics of the dependence influencing factors. A case study is illustrated to show the effectiveness and the flexibility of the proposed method.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2003년도 공동 춘계학술대회 논문집
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• pp.65-70
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• 2003

The weight-of-evidence model one of the Bayesian probability model was applied to the task of evaluating landslide susceptibility using GIS. Using the location of the landslides and spatial database such as topography, soil, forest, geology, land use and lineament, the weight-of-evidence model was applied to calculate each factor's rating at Boun area in Korea where suffered substantial landslide damage fellowing heavy rain in 1998, The factors are slope, aspect and curvature from the topographic database, soil texture, soil material, soil drainage, soil effective thickness, and topographic type from the soil database, forest type, timber diameter, timber age and forest density from the forest map, lithology from the geological database, land use from Landsat TM satellite image and lineament from IRS satellite image. Tests of conditional independence were performed for the selection of the factors, allowing the 43 combinations of factors to be analyzed. For the analysis, the contrast value, W$\^$＋/and W$\^$-/, as each factor's rating, were overlaid to map laudslide susceptibility. The results of the analysis were validated using the observed landslide locations, and among the combinations, the combination of slope, curvature, topographic, timber diameter, geology and lineament show the best results. The results can be used for hazard prevention and planning land use and construction