• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.109-110
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• 2006

Various parametric methods, Larson-Miller (L-M), Orr-Sherby-Dorn (O-S-D), Manson-Haferd (M-H) parameters, and minimum commitment method (MCM), were used to predict longer rupture time from short-term creep data. A number of the creep data were collected through literature surveys and experimental data produced in KAERI for predicting the creep type of type 316LN SS. Polynomial equations for predicting the creep life were obtained by the time-temperature parameters (TTP) and the MCM. standard error (SE) and standard error or mean (SEM) values were compared for the each method with temperatures. The TTP methods were good in the creep-life prediction, but the MCM was much superior to the TTP ones at $700^{\circ}C\;and\;750^{\circ}C$. The MCM was found to be lower in the SE values compared to the TTP methods

• Journal of the Korean Statistical Society
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• 제14권2호
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• pp.63-75
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• 1985

This paper considers a statistical calibration problem in which the standard as wel as the nonstandard measurement is subject to error. Since the classicla approach cannot handle this situation properly, a functional relationship model with additional feature of prediction is proposed. For the analysis of the problem four different approaches-two estimation techniques (ordinary and grouping least squares) combined with two prediction methods (classical and inverse prediction)-are considered. By Monte Carlo simulation the perromance of each approach is assessed in term of the probability of concentration. The simulation results indicate that the ordinary least squares with inverse prediction is generally preferred in interpolation while the grouping least squares with classical prediction turns out to be better in extrapolation.

• 한국태양에너지학회 논문집
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• 제32권2호
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• pp.74-86
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• 2012

For the improvement of environmental comfort in the buildings with the blind control, the objective of this study is to prevent the direct glare caused by the daylight inlet. During the process of solar profile prediction, time are significant factors that may cause error and glare during the blind control. This research proposes and evaluates the correction and control method to minimize prediction error. For the local areas with different longitude and local standard meridian, error occurred in the process of the time conversion from local standard time to apparent solar time. In order to correct error in time conversion, apparent solar time should be recalculated after adjusting the day of year and the equation of time. To solve the problems by the potential time errors, control method is suggested to divide the control sections using the calibrated fitting-curve and this method is verified through simulations. The proposed correction and control method, which considered potential time errors by loop lop leap years, could solve the problems about direct glare caused by daylight inlet on the work-plane according to the prediction errors of solar profile. And also these methods could maximize daylight inlet and solar heat gain, because the blocked area on windows could be minimized.

• Journal of the Korean Statistical Society
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• 제17권1호
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• pp.9-23
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• 1988

The classicla theory of statistical calibration assumes that the standard measurement is exact. From a realistic point of view, however, this assumption needs to be relaxed so that more meaningful calibration procedures may be developed. This paper presents a model which explicitly considers errors in both standard and nonstandard measurements. Under the assumption that replicated observations are available in the calibration experiment, three estimation techniques (ordinary least squares, grouping least squares, and maximum likelihood estimation) combined with two prediction methods (direct and inverse prediction) are compared in terms of the asymptotic mean square error of prediction.

• 한국통신학회논문지
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• 제25권6A호
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• pp.782-793
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• 2000

본 논문은 10GHz이상의 주파수 대역을 사용하는 위성 통신 링크에서 강우에 의해 감쇠된 신호 레벨을 동적으로 예측하기 위한 비교적 간단한 예측 기법을 제시한다. 예측 기법은 이산시간 저역 통과 필터링, 기울기에 근거한 예측, 평균 오차 보정, 고정 및 가변 혼합 예측 여유 할당의 4가지 기능 블록을 갖는다. Ku 대역의 측정 데이터로부터 주파수 스케일링에 의해 얻어진 Ka 대역 강우 감쇠 데이터를 이용하여 시뮬레이션을 수행하였다. 평균 오차 보정을 갖는 기울기 예측 기법은 1dB 이하의 표준 편차를 가지며, 평균 오차 보정에 의해 약 1.5~2.5 배의 예측 오차 감소를 보인다. 요구되는 평균 여유 면에서, 혼합 예측 여유 할당은 고정 여유 방법과 가변 여유 방법에 비해 더 적은 평균 여유를 요구한다.

• 대기
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• 제32권4호
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• pp.263-276
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• 2022

The observation error of satellite radiation data that assimilated into the Korean Integrated Model (KIM) was diagnosed by applying the Hollingsworth and Lönnberg and Desrozier techniques commonly used. The magnitude and correlation of the observation error, and the degree of contribution for the satellite radiance data were calculated. The observation errors of the similar device, such as Advanced Technology Microwave Sounder (ATMS) and Advanced Microwave Sounding Unit-A shows different characteristics. The model resolution accounts for only 1% of the observation error, and seasonal variation is not significant factor, either. The observation error used in the KIM is amplified by 3-8 times compared to the diagnosed value or standard deviation of first-guess departures. The new inflation value was calculated based on the correlation between channels and the ratio of background error and observation error. As a result of performing the model sensitivity evaluation by applying the newly inflated observation error of ATMS, the error of temperature and water vapor analysis field were decreased. And temperature and water vapor forecast field have been significantly improved, so the accuracy of precipitation prediction has also been increased by 1.7% on average in Asia especially.

• 대한산업공학회지
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• 제19권1호
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• pp.39-46
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• 1993

In developing a multiple regression relationship, independent variables are frequently measured with error. For these situations the problem of estimating unknown parameters has been extensively discussed in the literature while little attention has been given to the prediction problem. In this paper a criterion is developed for assessing the severeness of measurement errors in each independent variable on the predicted values. Using the developed criterion we can present a guideline as to which measurement error should be controlled for a more accurate prediction. Proposed methods are illustrated with a standard data system in work measurement.

• Journal of Advanced Marine Engineering and Technology
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• 제21권1호
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• pp.66-70
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• 1997

In this paper a new learning algorithm for curvature smoothing and improved generalization for multi-layer neural networks is proposed. To enhance the generalization ability a constraint term of hidden neuron activations is added to the conventional output error, which gives the curvature smoothing characteristics to multi-layer neural networks. When the total cost consisted of the output error and hidden error is minimized by gradient-descent methods, the additional descent term gives not only the Hebbian learning but also the synaptic weight decay. Therefore it incorporates error back-propagation, Hebbian, and weight decay, and additional computational requirements to the standard error back-propagation is negligible. From the computer simulation of the time series prediction with Santafe competition data it is shown that the proposed learning algorithm gives much better generalization performance.

• 한국식품과학회지
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• 제24권5호
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• pp.408-413
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• 1992

신속간편법으로서 식품의 성분함량 측정에 이용되는 근적외 반사분광분석에서 문제가 되고 있는 시료의 균질도의 차이가 흡광도에 미치는 영향을 조사하고 흡광도로 나타난 수치를 수학적으로 처리함으로써 예측의 오차는 다음과 같이 감소하였다. 1. 세절도가 일정한 시료의 흡광도를 무변형, 1차 미분 및 2차 미분하여 calibration한 후 세절도가 다양한 시료의 성분을 예측한 결과 예측오차(standard error of prediction)는 수분함량에 있어서 1.478%, 0.658% 및 0.580%, 지방함량의 예측오차 0.949%, 0.637%, 및 0.527%이었으며 단백질 측정시 각각 0.514%, 0.493% 및 0.394%로 2차 미분의 예측오차가 모든 성분측정에서 가장 낮음을 알 수 있었다. 2. 세절도가 다양한 시료의 무변형, 1차 미분 및 2차 미분처리한 calibration을 이용하여 세절도가 다양한 시료의 성분을 예측한 결과 수분함량 예측오차는 각각 1.026%, 0.589% 및 0.568%, 지방함량 예측오차는 각각 0.828%, 0.639% 및 0.602% 이었으며 단백질함량 예측오차는 0.860%, 0.557% 및 0.399%로서 역시 2차 미분, 1차 미분, 무변형의 순으로 정확성이 높았다. 결과를 종합할 때 흡광도를 수학적으로 처리하여 calibration에 이용하므로서 calibration시료의 세절도에 관계없이 측정결과의 정확성은 높아졌다.

• 한국태양에너지학회 논문집
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• 제36권3호
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• pp.33-43
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• 2016

Daylight is an important factor which influences building energy efficiency and visual comfort for occupants. It is important to predict precise sky luminance at the early stages of design to reduce light energy in the building. This study predicted sky luminance distributions of standard sky model(CIE overcast sky, CIE clear sky) that was provided from the CIE(Commission internationale de $l^{\prime}{\acute{e}}clairage$). Afterward, result of sky luminance was compared and verified with simulation value of Radiance program. From the CIE overcast sky, zenith and horizon ratio is about 3:1. From the CIE clear sky, luminance value gets most high value around the sun. On the other hand, luminance value is the lowest in the opposite direction of the sun when angle is $90^{\circ}$ between the sun and sky element. As a result of comparing the calculation results with Radiance program, sky luminance prediction error rate is 0.4~1.3% when it is CIE overcast sky. Also, sky luminance prediction error rate is 0.3~1.5% when it is CIE clear sky. When compared with the results of radiance simulation, it was evaluated as fairly accurate.