• The Journal of the Acoustical Society of Korea
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• v.17 no.8
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• pp.93-97
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• 1998

미지신호에 대한 측정에서는 오차분산의 명확한 표현이 어렵다. 본 연구에서는 이와 같은 수동측정에서의 측정정확도를 예측하기 위한 방법을 정립한다. 제안된 예측 방법은 신 뢰도를 기반으로 신호대잡음비 및 주파수대역폭과 시간적분과의 곱에 의해 정확도를 표현한 다. 본 논문에서는 배경소음 환경에서의 측정음향을 그대로 분석하는 경우와 배경소음을 예 측하여 측정음향에서 제거시키는 경우를 구분하여 광대역 음향측정시의 성능예측 기준을 시 뮬레이션하고 정확도를 예측한다.

• Journal of the KSME
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• v.43 no.6
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• pp.62-65
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• 2003

이 글에서는 가속 열노화시험을 통하여 노화수명을 예측하고 방법을 고무 재료의 수평 선도와 유한요소해석 결과로 부터 고무부품의 피로숙명을 예측하여 신뢰성을 평가하는 방법을 소개하였다.

• Journal of the KSME
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• v.55 no.10
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• pp.26-30
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• 2015

이 글에서는 제4세대 원전 고온구조재료인 Gr. 91강을 대상으로 하여 장시간 크리프 수명을 예측하고 파단수명을 확률적 신뢰도를 가지고 평가할 수 있는 방법에 대해 실 예제를 통하여 서술한다.

• Geotechnical Engineering
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• v.13 no.6
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• pp.5-12
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• 1997

Predictions of settlements under preloading for the improvement of soft soil is a very important element of construction management. Due to the non uniformity, difficulty of estimating resonable soil properties, predictions of settlements and settlement velocities at the design stage seldom agree with the actual future settlements. To overcome this problem, the prediction methods based on the settlement observation of initial preloading stage such as hyperbolic method and Asaoka method have been employed frequently. However the estimating method for the reliability of these predictions at the time of prediction has not been suggested. In this study, comparisons of predicted settlements by hyperbolic met hed and observed settlements are explored through case studies. And a stratagem of estimating reliability of settlement predictions by hyperbolic method is suggested as the result of investigation on the relationship between the initial observed time and error of settlement prediction by hyperbolic method.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.943-952
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• 2013

Wald, Agresti-Coull, Jeffreys, and Bayes-Laplace methods are commonly used for confidence interval of binomial proportion are applied for prediction intervals. We used coverage probability, mean coverage probability, root mean squared error, and mean expected width for numerical comparisons. From the comparisons, we found that Wald is not proper as for confidence interval and Agresti-Coull is too conservative to differ from confidence interval. However, Jeffrey and Bayes-Laplace are good for prediction interval and Jeffrey is especially desirable as for confidence interval.

• The Korean Journal of Applied Statistics
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• v.34 no.4
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• pp.579-588
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• 2021

Wald, Agresti-Coull, Jeffreys, and Bayes-Laplace methods are commonly used for confidence interval of binomial proportion are applied for prediction intervals. We used coverage probability, mean coverage probability, root mean squared error, and mean expected width for numerical comparisons. From the comparisons, we found that Wald is not proper as for confidence interval and Agresti-Coull is too conservative to differ from confidence interval. However, Jeffrey and Bayes-Laplace are good for prediction interval and Jeffrey is especially desirable as for confidence interval.

• ETRI Journal
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• v.14 no.1
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• pp.76-86
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• 1992

시스팀의 구조가 복잡하면 할수록 신뢰도는 중요한 문제로 부각된다. 신뢰도는 시스팀의 신뢰도 예측, 시스팀 설계시 신뢰도 배분, 장기간에 걸친 운영시 시스팀 유지와 보수 또 이에 따른 인원계획에도 영향을 미치고 있으며, 시스팀의 효율성 및 경제성 파악에 중요한 척도로 이용되고 있다. 본고에서는 신뢰도 모델로서 와이블 (Weibull) 분포의 이용과 적합도 판정문제를 고찰한다. 특히 새로운 통계방법을 이용하여 계산이 간편한 적합도 판정법을 소개한다.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.1
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• pp.9-18
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• 2015

Software Reliability Growth Models (SRGMs) are useful for determining the software release date or additional testing efforts by using software failure data. It is not appropriate for a SRGM to apply to all software. And besides a large number of SRGMs have already been proposed to estimate software reliability measures. Therefore selection of an optimal SRGM for use in a particular case has been an important issue. The existing methods for selecting a SRGM use the entire collected failure data. However, initial failure data may not affect the future failure occurrence and, in some cases, it results in the distorted result when evaluating the future failure. In this paper, we suggest a method for selecting a SRGM based on the evaluation goodness-of-fit using partial data. Our approach uses partial data except for inordinately unstable failure data in the entire failure data. We will find a portion of data used to select a SRGM through the comparison between the entire failure data and the partial failure data excluded the initial failure data with respect to the predictive ability of future failures. To justify our approach this paper shows that the predictive ability of future failures using partial data is more accurate than using the entire failure data with the real collected failure data.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.8
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• pp.751-757
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• 2016

The aim of this study is to estimate the reliability of fatigue limit of the material used for crank throw components according to the staircase method. The material used for crank throw components is forged S34MnV grade steel, which is heat treated by normalizing and tempering. In this work, to predict the reliability of the design fatigue strength, axially loaded constant amplitude fatigue testing was conducted. The test specimens were loaded with an axial push/pull load with a mean stress of 0 MPa, which corresponds to a stress ratio of R=-1. The fatigue test results were evaluated by Dixon-Mood formulas. The values of mean fatigue strength and standard deviation predicted by the staircase method were 296.3 MPa and 10.6 MPa, respectively. Finally, the reliability of the fatigue limit in some selected probability of failure is predicted. The proposed method can be applied for the determination of fatigue strength for design optimization of the forged steel.

• Journal of Korea Technology Innovation Society
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• v.1 no.2
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• pp.275-284
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• 1998

This paper investigates the responding patterns between panelists of high and low expertise, overall consistency in responses and the reliability of a technology forecasting outcomes of the study $\ulcorner$The Industrial Technology Forecasting for 2010 and New Strategies$\lrcorner$. The conclusions, based on various tests, are as follows : panelists' responses are tested to be significantly consistent : the panelist group of high expertise are more confident on their responses than the one of low expertise and the convergence ratio is higher in the latter group than in the first.