• Journal of Advanced Marine Engineering and Technology
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• 제37권7호
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• pp.743-751
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• 2013

In this paper, an approach to deal with model uncertainty using norm-optimal iterative learning control (ILC) is mentioned. Model uncertainty generally degrades the convergence and performance of conventional learning algorithms. To deal with model uncertainty, a worst-case norm-optimal ILC is introduced. The problem is then reformulated as a convex minimization problem, which can be solved efficiently to generate the control signal. The paper also investigates the relationship between the proposed approach and conventional norm-optimal ILC; where it is found that the suggested design method is equivalent to conventional norm-optimal ILC with trial-varying parameters. Finally, simulation results of the presented technique are given.

• Communications for Statistical Applications and Methods
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• 제27권1호
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• pp.109-128
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• 2020

A climate-impact projection usually consists of several stages, and the uncertainty of the projection is known to be quite large. It is necessary to assess how much each stage contributed to the uncertainty. We call an uncertainty quantification method in which relative contribution of each stage can be evaluated as uncertainty decomposition. We propose a new Bayesian model for uncertainty decomposition in climate change impact assessments. The proposed Bayesian model can incorporate uncertainty of natural variability and utilize data in control period. We provide a simple and efficient Gibbs sampling algorithm using the auxiliary variable technique. We compare the proposed method with other existing uncertainty decomposition methods by analyzing streamflow data for Yongdam Dam basin located at Geum River in South Korea.

• International Journal of Naval Architecture and Ocean Engineering
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• 제13권1호
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• pp.292-305
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• 2021

The present study concerns uncertainty assessment of powering prediction from towing tank model tests, suggested by the International Towing Tank Conference (ITTC). The systematic uncertainty of towing tank tests was estimated by allowance of test setup and measurement accuracy of ITTC. The random uncertainty was varied from 0 to 8% of the measurement. Randomly generated inputs of test conditions and measurement data sets under systematic and random uncertainty are used to statistically analyze resistance and propulsive performance parameters at the full scale. The error propagation through an extrapolation procedure is investigated in terms of the sensitivity and coefficient of determination. By the uncertainty assessment, it is found that the uncertainty of resultant powering prediction was smaller than the test uncertainty.

• 비파괴검사학회지
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• 제29권3호
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• pp.230-234
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• 2009

As concrete ages, the surrounding environment is expected to have growing influences on the concrete. As all the impacts of the environment cannot be considered in the strength-estimating model of a nondestructive concrete test, the increase in concrete age leads to growing uncertainty in the strength-estimating model. Therefore, the variation of the model error increases. It is necessary to include those impacts in the probability model of concrete strength attained from the nondestructive tests so as to build a more accurate reliability model for structural performance evaluation. This paper reviews and categorizes the existing strength-estimating statistical models of nondestructive concrete test, and suggests a new form of the strength-estimating statistical models to properly reflect the model uncertainty due to aging of the concrete. This new form of the statistical models will lay foundation for more accurate structural performance evaluation.

• 자원ㆍ환경경제연구
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• 제29권2호
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• pp.145-170
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• 2020

본 연구는 에너지(석유, 천연가스, 석탄) 가격과 경제적(실물 및 금융) 불확실성 사이의 의존성 구조를 분석하였다. Copula 모형을 이용해 얻은 의존구조 분석 결과를 요약하면 다음과 같다. 첫째, 에너지 가격과 실물·금융 불확실성 조합의 적합한 모형을 살펴보면, 원유가격과 실물·금융 불확실성 조합은 BB7 copula 모형, 천연가스 가격과 실물·금융 불확실성 조합은 Joe copula 모형, 석탄 가격과 실물·금융 불확실성 조합은 Clayton copula 모형이 각각 가장 적합한 모형으로 선정되었다. 둘째, 전체적인 의존성 구조를 살펴보면, 원유가격, 천연가스 가격, 석탄 가격과 실물 불확실성은 양(+)의 의존성을 보였다. 그렇지만 금융 불확실성과 원유가격은 양(+)의 의존성을 갖지만, 천연가스 가격과 석탄 가격은 금융 불확성과 음(-)의 의존성을 가지는 것으로 나타났다. 전체적으로 보면, 에너지원 중 원유가격이 실물·금융 불확실성과 가장 높은 의존성을 가지는 것으로 나타났다. 셋째, 극단적인 사건을 나타내는 꼬리 의존성을 분석한 결과, 실물 불확실성과 원유, 천연가스 가격은 위 꼬리 의존성만 보이는 비대칭 관계를 가지는 것으로 나타났으며, 금융 불확실성과 원유가격은 위 꼬리 의존성만 보이는 비대칭 관계를 가지는 것으로 나타났다. 즉, 비대칭 관계를 갖는 에너지 가격은 부정적인 극단사건이 발생하는 경우 불확실성 변수와 강한 의존관계가 있는 것으로 나타났다. 반면, 경제적 불확실성과 석탄 가격은 꼬리 의존성이 없는 것으로 나타났다.

• Journal of the Korean Statistical Society
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• 제26권4호
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• pp.477-491
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• 1997

A new predictive classification rule for assigning future cases into one of two multivariate normal population (with unknown normal mixture model) is considered. The development involves calculation of posterior probability of each possible normal-mixture model via a default Bayesian test criterion, called intrinsic Bayes factor, and suggests predictive distribution for future cases to be classified that accounts for model uncertainty by weighting the effect of each model by its posterior probabiliy. In this paper, our interest is focused on constructing the classification rule that takes care of uncertainty about the types of covariance matrices (homogeneity/heterogeneity) involved in the model. For the constructed rule, a Monte Carlo simulation study demonstrates routine application and notes benefits over traditional predictive calssification rule by Geisser (1982).

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2690-2692
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• 2000

In order to design a stable robust controller, nominal model, and the upper bound about the uncertainty which is the error of the model are needed. The problem to estimate the nominal model of controlled system and the upper bound of uncertainty at the same time is called robust identifcation. When the nominal model of controlled system and the upper bound of uncertainty in relation to robust identifcation are given, the evaluation of the validity of the model and the upper bound makes it possible to distinguish whether there is a model which explains observation data including disturbance among the model set. This paper suggests a method to identify the uncertainty which removes disturbance and expounds observation data by giving a probable postulation and plural data set to disturbance. It also examines the suggested method through a numerical computation simulation and validates its effectiveness.

• 한국수자원학회논문집
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• 제48권2호
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• pp.105-114
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• 2015

급격히 발전하는 도시지역 및 산업단지의 경우 불투수지역이 대부분이며, 이로 인해 유출이 증가함에 따라 내수침수가 발생할 확률이 높아지고 있다. 도시지역의 유출해석은 대부분 SWMM 모형을 이용하여 강우-유출해석을 수행하고 있으나 이러한 모형은 실제 자연 현상을 해석하는데 한계가 있으며, 모형 자체도 불확실성을 가지고 있어 정확한 유출해석을 하는데 어려움이 있다. 따라서 본 연구에서는 모형의 매개변수를 조사하고 불확실성을 가지는 매개변수를 선정한 후 매개변수의 불확실성 정도를 불확실성 정량화 지수를 이용하여 정량화하였다. 수행 결과 관조도계수의 불확실성이 가장 크며, 유출량에 미치는 영향도 가장 컸다. 그러므로 우수관거 설계 시 관조도계수 추정을 보다 정확히 산정하여야 하며, 불확실성 정도를 예측하여 유출해석에 반영하고, 각 매개변수가 가지는 특성을 파악한다면 내수 침수를 예방하는데 큰 기여를 할 것으로 판단된다.

• Ocean Systems Engineering
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• 제6권2호
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• pp.191-201
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• 2016

Stern bearing is a key component of marine propulsion plant. Its environment is diverse, working condition changeable, and condition severe, so that stern bearing load is of strong time variability, which directly affects the safety and reliability of the system and the normal navigation of ships. In this paper, three affecting factors of the stern bearing load such as hull deformation, propeller hydrodynamic vertical force and bearing wear are calculated and characterized by random theory. The uncertainty mathematical model of stern bearing load is established to research the relationships between factors and uncertainty load of stern bearing. The validity of calculation mathematical model and results is verified by examples and experiment yet. Therefore, the research on the uncertainty load of stern bearing has important theoretical significance and engineering practical value.

• 산업경영시스템학회지
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• 제22권52호
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• pp.311-322
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• 1999

Major problems involved in an electrical utility expansion planning within a time horizon are how to efficiently deal with objectives considering multiple factors and uncertainty. But justification factors in study these days have considered only quantitative factors except qualitative factors. Therefore, the purpose of this paper is to develop a new model for economic evaluation of nuclear power plants through the scoring model with the quantitative and qualitative factors under uncertainty. The quantitative factors use a levelized generation cost method considering time value of money. Especially, the environmental, risk, and safety factors in this paper have been also explained for the rational economic justification of the qualitative factors under uncertainty. This paper not only proposes a new approach method using the scoring model in evaluating economy of the nuclear power plant in the long term, but also provides the more efficient decision making criterion for nuclear power plants under uncertainty.