• 조명전기설비학회논문지
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• 제25권5호
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• pp.45-53
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• 2011

This paper presents a novel random sampling method for generation adequacy assessment including wind-power. Although a time sequential sampling has advantages than a random sampling in its assessment results, it takes long assessment time. Therefore, an effective random sampling method for generation adequacy assessment is highly recommended to get specific reliability indices quickly. The proposed method is based on the Monte-Carlo simulation with state sampling and it can be applied to generation adequacy assessment with other intermittent power sources.

• 반도체디스플레이기술학회지
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• 제21권1호
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• pp.17-21
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• 2022

In the case of the manufacturing industry that produces high-tech components such as semiconductors and large flat panel displays, the manufacturing space is made into a cleanroom to increase product yield and reliability, and various environmental factors have been managed to maintain the environment. Among them, airborne particle is a representative management item enough to be the standard for actual cleanroom grade, and a sequential particle monitoring system is usually used as one parts of the FMS (Fab or Facility monitoring system). However, this method has a problem in that the measurement efficiency decreases as the length of the sampling tube increases. In this study, in order to solve this problem, a multiple regression model was created. This model can correct the measurement error due to the decrease in efficiency by sampling tube length.

• 한국응용곤충학회지
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• 제40권2호
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• pp.105-109
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• 2001

귤응애의 예찰방법을 개발하기 위하여 제주지역의 온주밀감원에서 귤응애 분산형태에 대해 2개년(1999~2000년)에 걸쳐 잎 표본에 대하여 각 조사일에 평균밀도를 조사하였다. Taylor's power law와 Iwao's patchiness regression을 이용하여 분산지수를 비교하였으며, 잎 표본 조사에서는 일반적으로 Taylor's power law가 Iwao's patchiness regression보다 평균-분산 관계를 더 잘 나타내었다. Taylor's power law의 기울기와 절편은 조사한 포장 간에 차이가 없었으며, 여기에서 얻어진 상수값을 이용하여 잎 표본 조사에 의한 귤응애 약 .성충에 대한 고정정확도수준에서의 표본조사법을 개발하였다. 이 조사법에 대해 resampling 기법을 이용하여 독립된 4개의 조사자료를 이용하여 분석한 결과 실질 고정정확도(D)값이 요구되는 D값보다 항상 낮았으며, 나무당 귤응애 밀도가 8마리 이상에서 필요한 조사 나무수는 18주보다 작았다.

• 반도체디스플레이기술학회지
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• 제22권1호
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• pp.1-5
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• 2023

Most of the production process is performed in a cleanroom in the case of facilities that produce semiconductor chips or display panels. Therefore, environmental management of cleanrooms is very important for product yield and quality control. Among them, airborne particles are a representative management item enough to be the standard for the actual cleanroom rating, and it is a part of the Fab or Facility monitoring system, and the sequential particle monitoring system is mainly used. However, this method has a problem in that measurement efficiency decreases as the length of the sampling tube increases. In addition, a statistically significant test of deterioration in efficiency has rarely been performed. Therefore, in this study, the statistically significant test between the number of particles measured by InSitu and the number of particles measured for each sampling tube ends(Remote). Through this, the efficiency degradation problem of the sequential particle monitoring system was confirmed by a statistical method.

• 대한기계학회논문집A
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• 제34권5호
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• pp.541-547
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• 2010

메타모델의 정확도를 엄밀하게 검증하는 것은 메타모델링에서 중요한 연구주제이다. k 점 선택교차검증기법이 많은 계산시간을 요구하면서도 메타모델의 정확도를 정략적으로 측정하지 못한다. 최근들어, 평균 $_0$ 기준이 메타모델의 정확도를 정량적으로 제공하기 위하여 제안되었다. 그러나 평균 $_0$ 검증 기준은 크리깅 메타모델이 부정확함에도 불구하고 일찍 수렴하는 경향이 있다. 따라서 본 연구에서는 최대엔트로피를 이용한 순차적 실험계획에서 크리깅모델의 평균과 분산을 이용한 정확도 평가기법을 제안한다. 이 제안한 기법은 평균 및 분산을 계산할 때 수치해석으로 구하는 것이 아니라 크리깅메타모델을 직접 적분하여 구하기 때문에 k 점 선택교차검증기법보다 효율적이며 정확하다. 제안한 기준은 실제 응답의 평균제곱오차의 경향과 매우 유사하여 순차적 실험계획의 수렴기준으로 사용할 수 있다.

• 한국CDE학회논문집
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• 제17권5호
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• pp.375-386
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• 2012

Most engineering design problems require analyses or simulations to evaluate objective functions. However, a single simulation can take many hours or even days to finish for many real world problems. As a result, design optimization becomes impossible since they require hundreds or thousands of simulation evaluations. The surrogate-based optimization (SBO) strategy became a remedy for such computationally expensive analyses and simulations. A surrogate-based optimization strategy has been developed in this study in order to improve global optimization performance. The strategy is a heuristic algorithm and it exploits not only multiple surrogates, but also multiple optimizers. Multiple optimizations of multiple surrogate models yield multiple candidate design points of optima. During the sequential sampling process, the algorithm ranks candidate design points, selects the points as many as specified, and builds the improved surrogate model. Various mathematical functions with different numbers of design variables are chosen to compare the proposed method with the other most recent algorithm, MSEGO. The proposed method shows superior performance to the other method.

• Smart Structures and Systems
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• 제21권5호
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• pp.601-609
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• 2018

The estimated probabilistic model of wind data based on the conventional approach may have high discrepancy compared with the true distribution because of the uncertainty caused by the instrument error and limited monitoring data. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method has been developed in the companion paper and is conducted to formulate the joint probability density function (PDF) of wind speed and direction using the wind monitoring data of the investigated bridge. The established bivariate model of wind speed and direction only represents the features of available wind monitoring data. To characterize the stochastic properties of the wind parameters with the subsequent wind monitoring data, in this study, Bayesian inference approach considering the uncertainty is proposed to update the wind parameters in the bivariate probabilistic model. The slice sampling algorithm of Markov chain Monte Carlo (MCMC) method is applied to establish the multi-dimensional and complex posterior distribution which is analytically intractable. The numerical simulation examples for univariate and bivariate models are carried out to verify the effectiveness of the proposed method. In addition, the proposed Bayesian inference approach is used to update and optimize the parameters in the bivariate model using the wind monitoring data from the investigated bridge. The results indicate that the proposed Bayesian inference approach is feasible and can be employed to predict the bivariate distribution of wind speed and direction with limited monitoring data.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.143-145
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• 2005

In this paper, an empirical study result on pattern estimation method is devoted to reveal underlying data patterns with a relatively reduced computational cost. Presented method performs crisp type clustering with given n number of data samples by means of the sequential agglomerative hierarchical nested model (SAHN). Conventional SAHN based clustering requires large computation time in the initial step of algorithm. To deal with this concern, we modified overall process with a partial approach. In the beginning of this method, we divide given data set to several sub groups with uniform sampling and then each divided sub data group is applied to SAHN based method. The advantage of this method reduces computation time of original process and gives similar results. Proposed is applied to several test data set and simulation result with conceptual analysis is presented.

• 전자공학회논문지CI
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• 제44권1호
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• pp.26-32
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• 2007

연속적 화자 분류에 있어서 분류 대상이 되는 화자에 대한 정보가 없거나 부족할 경우 정확한 연속적 분류가 어렵다. 이러한 문제를 해결하기 위해 표본 화자모델을 이용하는 방법이 제안되었는데, 이 방법을 이용하면 미리 준비된 화자의 데이터가 없이 화자모델 초기화와 화자분류가 가능해진다. 하지만 여전히 화자모델의 표본을 얻는 방법에 어려움이 따른다. 이 문제를 해결하기 위해 벡터 양자화에서 비롯된 화자 양자화를 제안한다. 유선전화 데이터를 이용한 실험에서 화자 양자화를 이용한 표본 화자모델 방법은 무작위 표본추출 방법을 이용할 경우 보다 25%의 성능 향상을 보였다.

• Journal of Magnetics
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• 제18권1호
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• pp.74-79
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• 2013

This paper proposes a sampling-based optimization method for electromagnetic design problems, where design sensitivities are obtained from the elaborate surrogate models based on the universal Kriging method and a local window concept. After inserting additional sequential samples to satisfy the certain convergence criterion, the elaborate surrogate model for each true performance function is generated within a relatively small area, called a hyper-cubic local window, with the center of a nominal design. From Jacobian matrices of the local models, the accurate design sensitivity values at the design point of interest are extracted, and so they make it possible to use deterministic search algorithms for fast search of an optimum in design space. The proposed method is applied to a mathematical problem and a loudspeaker design with constraint functions and is compared with the sensitivity-based optimization adopting the finite difference method.